diff --git a/apple-touch-icon-120x120.png b/apple-touch-icon-120x120.png index 366fea21..a12f18b7 100644 Binary files a/apple-touch-icon-120x120.png and b/apple-touch-icon-120x120.png differ diff --git a/apple-touch-icon-152x152.png b/apple-touch-icon-152x152.png index f47d334c..f2950913 100644 Binary files a/apple-touch-icon-152x152.png and b/apple-touch-icon-152x152.png differ diff --git a/apple-touch-icon-180x180.png b/apple-touch-icon-180x180.png index a8509d12..3a986027 100644 Binary files a/apple-touch-icon-180x180.png and b/apple-touch-icon-180x180.png differ diff --git a/apple-touch-icon-60x60.png b/apple-touch-icon-60x60.png index 4e108df3..6fdf8907 100644 Binary files a/apple-touch-icon-60x60.png and b/apple-touch-icon-60x60.png differ diff --git a/apple-touch-icon-76x76.png b/apple-touch-icon-76x76.png index f7cc5743..f7439886 100644 Binary files a/apple-touch-icon-76x76.png and b/apple-touch-icon-76x76.png differ diff --git a/apple-touch-icon.png b/apple-touch-icon.png index 739bf08a..4f5bc688 100644 Binary files a/apple-touch-icon.png and b/apple-touch-icon.png differ diff --git a/articles/fib.html b/articles/fib.html index 7791104a..9bc8a676 100644 --- a/articles/fib.html +++ b/articles/fib.html @@ -446,7 +446,7 @@

Show 
 show_fibmatrix(fibdata, plotly = TRUE)
-

From these plots, we can view locations and general trends in FIB +

From these plots, we can view locations and general trends in FIB data for the Hillsborough and Alafia river basins. Additional functions may be added in the future to evaluate FIB data at other locations.

diff --git a/articles/habitatmasterplan.html b/articles/habitatmasterplan.html index 62944d22..903aefcd 100644 --- a/articles/habitatmasterplan.html +++ b/articles/habitatmasterplan.html @@ -359,9 +359,9 @@

Report card plottwocol = T, where red shows the target or goal is not -met, green shows the target or goal is met, a plus symbol shows the -target or goal is likely to be met, and a negative symbols shows the -target or goal is not likely to be met.

+met, green shows the target or goal is met, an up arrow shows the target +or goal is likely to be met, and a down arrow shows the target or goal +is not likely to be met.

 show_hmpreport(acres = acres, subtacres = subtacres, hmptrgs = hmptrgs, typ = 'targets', twocol = T)

diff --git a/articles/intro.html b/articles/intro.html index 5d7babbe..ee93a7ca 100644 --- a/articles/intro.html +++ b/articles/intro.html @@ -581,7 +581,7 @@

Show 
 show_matrix(epcdata, plotly = TRUE)
-

Results can also be obtained for a selected year. Outcomes can be +

Results can also be obtained for a selected year. Outcomes can be returned in tabular format with anlz_yrattain(). This table also shows segment averages for chlorophyll and light attenuation, including the associated targets.

@@ -648,7 +648,7 @@

Show 
 show_segplotly(epcdata, width = 1000, height = 600)
-

From these plots, we can quickly view a summary of the environmental +

From these plots, we can quickly view a summary of the environmental history of water quality in Tampa Bay. Degraded conditions were common early in the period of record, particularly for Old Tampa Bay and Hillsborough Bay. Conditions began to improve by the late 1980s and @@ -679,50 +679,50 @@

Reasonable Assurance reporting
 show_annualassess(epcdata, yrsel = 2023)
- - + +
- - - + + + - - - - - + + + + + - - - - - + + + + + - - - - - + + + + + - - - - - + + + + + - - - - - + + + + +

Segment

Chl-a (ug/L)

Light Penetration (m-1)

Segment

Chl-a (ug/L)

Light Penetration (m-1)

2023

target

2023

target

2023

target

2023

target

OTB

6.2

8.5

0.73

0.83

OTB

6.2

8.5

0.73

0.83

HB

6.9

13.2

0.79

1.58

HB

6.9

13.2

0.79

1.58

MTB

3.7

7.4

0.47

0.83

MTB

3.7

7.4

0.47

0.83

LTB

2.6

4.6

0.54

0.63

LTB

2.6

4.6

0.54

0.63
@@ -732,51 +732,51 @@

Reasonable Assurance reporting
 show_annualassess(epcdata, yrsel = 2023, caption = TRUE)

- - - + +
Water quality outcomes for 2023.
+ - - - + + + - - - - - + + + + + - - - - - + + + + + - - - - - + + + + + - - - - - + + + + + - - - - - + + + + +
Water quality outcomes for 2023.

Segment

Chl-a (ug/L)

Light Penetration (m-1)

Segment

Chl-a (ug/L)

Light Penetration (m-1)

2023

target

2023

target

2023

target

2023

target

OTB

6.2

8.5

0.73

0.83

OTB

6.2

8.5

0.73

0.83

HB

6.9

13.2

0.79

1.58

HB

6.9

13.2

0.79

1.58

MTB

3.7

7.4

0.47

0.83

MTB

3.7

7.4

0.47

0.83

LTB

2.6

4.6

0.54

0.63

LTB

2.6

4.6

0.54

0.63
@@ -791,50 +791,50 @@

Reasonable Assurance reporting
 show_ratab(epcdata, yrsel = 2023, bay_segment = 'OTB')

- - + +
- - - + + + - - - - - + + + + + - - - - - - - + + + + + + + - - - - - - - + + + + + + + - - - - - - - + + + + + + + - - + +

Bay Segment Reasonable Assurance Assessment Steps

DATA USED TO ASSESS ANNUAL REASONABLE ASSURANCE

OUTCOME

Bay Segment Reasonable Assurance Assessment Steps

DATA USED TO ASSESS ANNUAL REASONABLE ASSURANCE

OUTCOME

Year 1 (2022)

Year 2 (2023)

Year 3 (2024)

Year 4 (2025)

Year 5 (2026)

Year 1 (2022)

Year 2 (2023)

Year 3 (2024)

Year 4 (2025)

Year 5 (2026)

NMC Action 1: Determine if observed chlorophyll-a exceeds FDEP threshold of 9.3 ug/L

No (7.1)

No (6.2)

All years below threshold so far, not necessary for NMC Actions 2-5

NMC Action 1: Determine if observed chlorophyll-a exceeds FDEP threshold of 9.3 ug/L

No (7.1)

No (6.2)

All years below threshold so far, not necessary for NMC Actions 2-5

NMC Action 2: Determine if any observed chlorophyll-a exceedences occurred for 2 consecutive years

No

No

All years met threshold, not necessary for NMC Actions 3-5

NMC Action 2: Determine if any observed chlorophyll-a exceedences occurred for 2 consecutive years

No

No

All years met threshold, not necessary for NMC Actions 3-5

NMC Action 3: Determine if observed hydrologically-normalized total load exceeds federally-recognized TMDL of 486 tons/year

N/A

N/A

Not necessary due to observed water quality and seagrass conditions in the bay segment

NMC Action 3: Determine if observed hydrologically-normalized total load exceeds federally-recognized TMDL of 486 tons/year

N/A

N/A

Not necessary due to observed water quality and seagrass conditions in the bay segment

NMC Actions 4-5: Determine if any entity/source/facility specific exceedences of 5-yr average allocation occurred during implementation period

Not necessary when chlorophyll-a threshold met

NMC Actions 4-5: Determine if any entity/source/facility specific exceedences of 5-yr average allocation occurred during implementation period

Not necessary when chlorophyll-a threshold met
diff --git a/articles/seagrasstransect.html b/articles/seagrasstransect.html index 7cb6b5dd..bfdb47f5 100644 --- a/articles/seagrasstransect.html +++ b/articles/seagrasstransect.html @@ -431,7 +431,7 @@

Plotting results
 show_transect(transect, site = 'S3T10', species = 'Halodule', varplo = 'Abundance', plotly = T)
-

The show_transect() function can also be used to plot +

The show_transect() function can also be used to plot multiple species. One to many species can be provided to the species argument.

@@ -453,7 +453,7 @@ 
Plotting results
 show_transectsum(transectocc, site = 'S3T10')
-

A summary matrix of frequency occurrence estimates across all species +

A summary matrix of frequency occurrence estimates across all species can be plotted with show_transectmatrix(). This uses results from the anlz_transectocc() and anlz_transectave() functions to estimate annual averages by @@ -474,7 +474,7 @@

Plotting results
 show_transectmatrix(transectocc, plotly = T)
-

Time series plots of annual averages of frequency occurrence +

Time series plots of annual averages of frequency occurrence estimates by each species can be shown with the show_transectavespp() function. By default, all estimates are averaged across all bay segments for each species. The plot is a @@ -494,7 +494,7 @@

Plotting results
 show_transectavespp(transectocc, bay_segment = 'LTB', species = c('Syringodium', 'Thalassia'), plotly = T)
-

As an alternative to plotting the species averages over time with +

As an alternative to plotting the species averages over time with show_transectavespp(), a table can be created by setting asreact = TRUE. Filtering options that apply to the plot also apply to the table, e.g., filtering by the four major bay segments diff --git a/articles/tbbi.html b/articles/tbbi.html index 2943b721..1dc27c59 100644 --- a/articles/tbbi.html +++ b/articles/tbbi.html @@ -313,7 +313,7 @@

Plotting results
 show_tbbimatrix(tbbiscr, plotly = T)
- +

Additional sediment data @@ -431,7 +431,7 @@

Additional sediment data
 show_sedimentave(sedimentdata, param = 'Arsenic', yrrng = c(1993, 2022), plotly = T)

-

The values used in the plot can be returned with +

The values used in the plot can be returned with anlz_sedimentave().

 anlz_sedimentave(sedimentdata, param = 'Arsenic', yrrng = c(1993, 2022))
@@ -473,7 +473,7 @@ 
Additional sediment data
 show_sedimentpelave(sedimentdata, yrrng = c(1993, 2022), plotly = T)
-

The values used in the plot can be returned with +

The values used in the plot can be returned with anlz_sedimentpelave().

 anlz_sedimentpelave(sedimentdata, yrrng = c(1993, 2022))
@@ -503,7 +503,7 @@ 
Additional sediment data
 show_sedimentalratio(sedimentdata, param = 'Zinc', bay_segment = c('HB', 'LTB'), plotly = T)
- +

References diff --git a/articles/tbni.html b/articles/tbni.html index a63967ca..47b5fe14 100644 --- a/articles/tbni.html +++ b/articles/tbni.html @@ -329,13 +329,13 @@

Plotting results
 show_tbniscr(tbniscr, plotly = T)

-
+
 show_tbniscrall(tbniscr, plotly = T)

 

-
+
 show_tbnimatrix(tbniscr, plotly = T)

 

-
The breakpoints for the categorical outcomes of the TBNI scores shown
+
The breakpoints for the categorical outcomes of the TBNI scores shown
 by the colors in each graph are based on the 33rd and 50th percentiles
 of the distribution of all TBNI scores calculated for Tampa Bay. This
 plotting option is provided for consistency with existing TBEP reporting
diff --git a/articles/tidalcreeks.html b/articles/tidalcreeks.html
index ff3cfef1..8d1a2fd2 100644
--- a/articles/tidalcreeks.html
+++ b/articles/tidalcreeks.html
@@ -370,7 +370,7 @@ 
Indicator functionscntdat <- anlz_tdlcrkindic(tidalcreeks, iwrraw, yr = 2023)
 show_tdlcrkindic(id = id, cntdat = cntdat, thrsel = TRUE)

 

-
The show_tdlcrkindiccdf() function is similar except
+
The show_tdlcrkindiccdf() function is similar except
 that empirical cumulative distribution functions (CDF) are plotted to
 evaluate outcomes for a specific creek relative to the entire
 distribution of creeks in southwest Florida. Each indicator and each
@@ -383,7 +383,7 @@ 
Indicator functions
 show_tdlcrkindiccdf(id = id, cntdat = cntdat, thrsel = TRUE)
- +
diff --git a/favicon-16x16.png b/favicon-16x16.png index 9f775e18..c817e621 100644 Binary files a/favicon-16x16.png and b/favicon-16x16.png differ diff --git a/favicon-32x32.png b/favicon-32x32.png index 5dbd603c..83066ee7 100644 Binary files a/favicon-32x32.png and b/favicon-32x32.png differ diff --git a/pkgdown.yml b/pkgdown.yml index 55982d5b..732f4617 100644 --- a/pkgdown.yml +++ b/pkgdown.yml @@ -9,7 +9,7 @@ articles: tbbi: tbbi.html tbni: tbni.html tidalcreeks: tidalcreeks.html -last_built: 2024-06-10T14:32Z +last_built: 2024-06-10T14:39Z urls: reference: https://tbep-tech.github.io/tbeptools/reference article: https://tbep-tech.github.io/tbeptools/articles diff --git a/reference/show_annualassess.html b/reference/show_annualassess.html index 7430b606..6a39159c 100644 --- a/reference/show_annualassess.html +++ b/reference/show_annualassess.html @@ -111,8 +111,8 @@

Value

Examples

show_annualassess(epcdata, yrsel = 2023)
-
Segment
Chl-a (ug/L)
Light Penetration (m-1)
2023
target
2023
target
OTB
6.2
8.5
0.73
0.83
HB
6.9
13.2
0.79
1.58
MTB
3.7
7.4
0.47
0.83
LTB
2.6
4.6
0.54
0.63
show_annualassess(epcdata, yrsel = 2023, caption = TRUE)
-
Water quality outcomes for 2023.
Segment
Chl-a (ug/L)
Light Penetration (m-1)
2023
target
2023
target
OTB
6.2
8.5
0.73
0.83
HB
6.9
13.2
0.79
1.58
MTB
3.7
7.4
0.47
0.83
LTB
2.6
4.6
0.54
0.63
+

Segment

Chl-a (ug/L)

Light Penetration (m-1)

2023

target

2023

target

OTB

6.2

8.5

0.73

0.83

HB

6.9

13.2

0.79

1.58

MTB

3.7

7.4

0.47

0.83

LTB

2.6

4.6

0.54

0.63

show_annualassess(epcdata, yrsel = 2023, caption = TRUE) +
Water quality outcomes for 2023.

Segment

Chl-a (ug/L)

Light Penetration (m-1)

2023

target

2023

target

OTB

6.2

8.5

0.73

0.83

HB

6.9

13.2

0.79

1.58

MTB

3.7

7.4

0.47

0.83

LTB

2.6

4.6

0.54

0.63

diff --git a/reference/show_hmpreport.html b/reference/show_hmpreport.html index 2fc2d34a..dc248cbe 100644 --- a/reference/show_hmpreport.html +++ b/reference/show_hmpreport.html @@ -134,7 +134,7 @@

Value

Details

-

If twocol = F, colors indicate both if the target/goal is met and the likelihood of attaining the target/goal by 2030/2050. Red indicates the target/goal is not met and will likely not be met by 2030/2050 (trending below target/goal), yellow indicates the target/goal is met although it likely will not be met by 2030/2050 (trending below target/goal), light green indicates the target/goal is not met although it will likely be met by 2030/2050 (trending above target/goal), and green indicates the target/goal is met and will likely be met by 2030/2050 (trending above target/goal). Numbers in each cell show the proportion of the target or goal met at each year where data are available. If twocol = T, the colors indicate if the goal is met (green) or not met (red) and the symbols in each cell indicate if the goal is likely to be met (+) or not (-) by 2030/2050. In both cases, the colors and trends are relative to the 2030 targets or 2050 goals using the typ argument.

+

If twocol = F, colors indicate both if the target/goal is met and the likelihood of attaining the target/goal by 2030/2050. Red indicates the target/goal is not met and will likely not be met by 2030/2050 (trending below target/goal), yellow indicates the target/goal is met although it likely will not be met by 2030/2050 (trending below target/goal), light green indicates the target/goal is not met although it will likely be met by 2030/2050 (trending above target/goal), and green indicates the target/goal is met and will likely be met by 2030/2050 (trending above target/goal). Numbers in each cell show the proportion of the target or goal met at each year where data are available. If twocol = T, the colors indicate if the goal is met (green) or not met (red) and the symbols in each cell indicate if the goal is likely to be met (up arrow) or not (down arrow) by 2030/2050. In both cases, the colors and trends are relative to the 2030 targets or 2050 goals using the typ argument.

The report card provides no information on artificial reefs, living shorelines, and hard bottom habitats. These habitats are not assessed in routine data products from the Southwest Florida Water Management District, although targets and goals are provided in the Habitat Master Plan.

The subtidal data in subtacres and the inter/supratidal data in acres are provided as different datasets by the Southwest Florida Water Management District. The years in each dataset typically do not match and each dataset is collected at approximate 2 to 3 year intervals. By default, year on the y-axis is shown as a continuous variable, where gaps are shown in years when each dataset was unavailable. Use ycollapse = TRUE to remove years without data.

diff --git a/reference/show_matrixplotly.html b/reference/show_matrixplotly.html index 1aa4cf2a..36936865 100644 --- a/reference/show_matrixplotly.html +++ b/reference/show_matrixplotly.html @@ -103,7 +103,7 @@

Examples
mat <- show_wqmatrix(epcdata)
 show_matrixplotly(mat)
 

-
+ diff --git a/reference/show_ratab.html b/reference/show_ratab.html index 2faeee42..050fd7e6 100644 --- a/reference/show_ratab.html +++ b/reference/show_ratab.html @@ -133,7 +133,7 @@

Examples#> Registered S3 method overwritten by 'ftExtra': #> method from #> as_flextable.data.frame flextable -

Bay Segment Reasonable Assurance Assessment Steps

DATA USED TO ASSESS ANNUAL REASONABLE ASSURANCE

OUTCOME

Year 1 (2022)

Year 2 (2023)

Year 3 (2024)

Year 4 (2025)

Year 5 (2026)

NMC Action 1: Determine if observed chlorophyll-a exceeds FDEP threshold of 9.3 ug/L

No (7.1)

No (6.2)

All years below threshold so far, not necessary for NMC Actions 2-5

NMC Action 2: Determine if any observed chlorophyll-a exceedences occurred for 2 consecutive years

No

No

All years met threshold, not necessary for NMC Actions 3-5

NMC Action 3: Determine if observed hydrologically-normalized total load exceeds federally-recognized TMDL of 486 tons/year

N/A

N/A

Not necessary due to observed water quality and seagrass conditions in the bay segment

NMC Actions 4-5: Determine if any entity/source/facility specific exceedences of 5-yr average allocation occurred during implementation period

Not necessary when chlorophyll-a threshold met

+

Bay Segment Reasonable Assurance Assessment Steps

DATA USED TO ASSESS ANNUAL REASONABLE ASSURANCE

OUTCOME

Year 1 (2022)

Year 2 (2023)

Year 3 (2024)

Year 4 (2025)

Year 5 (2026)

NMC Action 1: Determine if observed chlorophyll-a exceeds FDEP threshold of 9.3 ug/L

No (7.1)

No (6.2)

All years below threshold so far, not necessary for NMC Actions 2-5

NMC Action 2: Determine if any observed chlorophyll-a exceedences occurred for 2 consecutive years

No

No

All years met threshold, not necessary for NMC Actions 3-5

NMC Action 3: Determine if observed hydrologically-normalized total load exceeds federally-recognized TMDL of 486 tons/year

N/A

N/A

Not necessary due to observed water quality and seagrass conditions in the bay segment

NMC Actions 4-5: Determine if any entity/source/facility specific exceedences of 5-yr average allocation occurred during implementation period

Not necessary when chlorophyll-a threshold met

diff --git a/reference/show_sedimentpelaveplotly.html b/reference/show_sedimentpelaveplotly.html index a0ef1741..5da55082 100644 --- a/reference/show_sedimentpelaveplotly.html +++ b/reference/show_sedimentpelaveplotly.html @@ -89,7 +89,7 @@

Examples
p <- show_sedimentpelave(sedimentdata)
 show_sedimentpelaveplotly(p)
 

-
+ diff --git a/reference/show_segplotly.html b/reference/show_segplotly.html index ffd03a04..95fc1c3b 100644 --- a/reference/show_segplotly.html +++ b/reference/show_segplotly.html @@ -116,7 +116,7 @@

DetailsExamples

show_segplotly(epcdata)
 

-
+ diff --git a/reference/show_tbniscrplotly.html b/reference/show_tbniscrplotly.html index 699ec505..0de47ba9 100644 --- a/reference/show_tbniscrplotly.html +++ b/reference/show_tbniscrplotly.html @@ -90,7 +90,7 @@

Examplesp <- show_tbniscrall(tbniscr) show_tbniscrplotly(p)
- + diff --git a/reference/show_tdlcrkindic.html b/reference/show_tdlcrkindic.html index d411c3a5..00f304cb 100644 --- a/reference/show_tdlcrkindic.html +++ b/reference/show_tdlcrkindic.html @@ -106,7 +106,7 @@

Examplesid <- sample(unique(cntdat$id), 1) show_tdlcrkindic(id, cntdat, thrsel = TRUE)
- + diff --git a/reference/show_tdlcrkindiccdf.html b/reference/show_tdlcrkindiccdf.html index 9c840566..889cbabe 100644 --- a/reference/show_tdlcrkindiccdf.html +++ b/reference/show_tdlcrkindiccdf.html @@ -110,7 +110,7 @@

Examplesid <- sample(unique(cntdat$id), 1) show_tdlcrkindiccdf(id, cntdat, thrsel = TRUE)
- + diff --git a/reference/show_transectsum.html b/reference/show_transectsum.html index d2700ff1..920983eb 100644 --- a/reference/show_transectsum.html +++ b/reference/show_transectsum.html @@ -116,7 +116,7 @@

Examplestransectocc <- anlz_transectocc(transect) show_transectsum(transectocc, site = 'S3T10')
- + diff --git a/search.json b/search.json index 37054540..e7e88103 100644 --- a/search.json +++ b/search.json @@ -1 +1 @@ -[{"path":"https://tbep-tech.github.io/tbeptools/CONTRIBUTING.html","id":null,"dir":"","previous_headings":"","what":"Contributing to tbeptools","title":"Contributing to tbeptools","text":"outlines propose change tbeptools. detailed info contributing , please see development contributing guide.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/CONTRIBUTING.html","id":"fixing-typos","dir":"","previous_headings":"","what":"Fixing typos","title":"Contributing to tbeptools","text":"Small typos grammatical errors documentation may edited directly using GitHub web interface, long changes made source file. YES: edit roxygen comment .R file R/. : edit .Rd file man/.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/CONTRIBUTING.html","id":"prerequisites","dir":"","previous_headings":"","what":"Prerequisites","title":"Contributing to tbeptools","text":"make substantial pull request, always file issue make sure someone team agrees ’s problem. ’ve found bug, create associated issue illustrate bug minimal reprex.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/CONTRIBUTING.html","id":"pull-request-process","dir":"","previous_headings":"","what":"Pull request process","title":"Contributing to tbeptools","text":"recommend create Git branch pull request (PR). Look Travis AppVeyor build status making changes. README contain badges continuous integration services used package. New code follow tidyverse style guide. can use styler package apply styles, please don’t restyle code nothing PR. use roxygen2, Markdown syntax, documentation. use testthat. Contributions test cases included easier accept. user-facing changes, add bullet top NEWS.md current development version header describing changes made followed GitHub username, links relevant issue(s)/PR(s).","code":""},{"path":"https://tbep-tech.github.io/tbeptools/CONTRIBUTING.html","id":"code-of-conduct","dir":"","previous_headings":"","what":"Code of Conduct","title":"Contributing to tbeptools","text":"Please note tbeptools project released Contributor Code Conduct. contributing project agree abide terms.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/CONTRIBUTING.html","id":"see-tidyverse-development-contributing-guide","dir":"","previous_headings":"","what":"See tidyverse development contributing guide","title":"Contributing to tbeptools","text":"details.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/ISSUE_TEMPLATE.html","id":null,"dir":"","previous_headings":"","what":"Issues reporting guide","title":"Issues reporting guide","text":"Please briefly describe problem output expect. question, please don’t use form. Instead, ask https://stackoverflow.com/ https://community.rstudio.com/. Please include minimal reproducible example (AKA reprex). ’ve never heard reprex , start reading https://www.tidyverse.org/help/#reprex. Brief description problem","code":"# insert reprex here"},{"path":"https://tbep-tech.github.io/tbeptools/LICENSE.html","id":null,"dir":"","previous_headings":"","what":"MIT License","title":"MIT License","text":"Copyright (c) 2024 tbeptools authors Permission hereby granted, free charge, person obtaining copy software associated documentation files (“Software”), deal Software without restriction, including without limitation rights use, copy, modify, merge, publish, distribute, sublicense, /sell copies Software, permit persons Software furnished , subject following conditions: copyright notice permission notice shall included copies substantial portions Software. SOFTWARE PROVIDED “”, WITHOUT WARRANTY KIND, EXPRESS IMPLIED, INCLUDING LIMITED WARRANTIES MERCHANTABILITY, FITNESS PARTICULAR PURPOSE NONINFRINGEMENT. EVENT SHALL AUTHORS COPYRIGHT HOLDERS LIABLE CLAIM, DAMAGES LIABILITY, WHETHER ACTION CONTRACT, TORT OTHERWISE, ARISING , CONNECTION SOFTWARE USE DEALINGS SOFTWARE.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/articles/fib.html","id":"background","dir":"Articles","previous_headings":"","what":"Background","title":"Fecal Indicator Bacteria","text":"Fecal Indicator Bacteria (FIB) used track concentrations pathogens surface waters may detrimental human health environment. commonly measured select indicators present human gut can enter environment wastewater discharges illicit sources. Common indicators include concentrations E. coli, Enterococcus, Fecal Coliform number colony forming units (CFU) per 100 mL water. Many monitoring programs routinely measure FIB concentrations select locations. Environmental Protection Commission (EPC) Hillsborough County tracking FIB indicators several decades part long-term monitoring. Functions tbeptools can used download EPC FIB data, analyze results, create summary maps plots. vignette describes use functions. functions focused reporting Hillsborough River fecal coliform impairment associated Basin Management Action Plan (BMAP). tools can used track long-term changes FIBs basin assess progress reducing fecal coliform levels. Data collected monitoring program processed maintained spreadsheet titled RWMDataSpreadsheet_ThroughCurrentReportMonth.xlsx https://epcbocc.sharepoint.com/:x:/s/Share/EWKgPirIkoxMp9Hm_wVEICsBk6avI9iSRjFiOxX58wXzIQ?e=kAWZXl&download=1 (viewable ). data include observations stations parameters throughout period record. FIB data collected stations additional water quality data collected. dataset used reporting water quality indicators Tampa Bay (see water quality data vignette).","code":""},{"path":"https://tbep-tech.github.io/tbeptools/articles/fib.html","id":"read","dir":"Articles","previous_headings":"","what":"Read","title":"Fecal Indicator Bacteria","text":"main function importing FIB data read_importfib(). function downloads latest file one already available location specified xlsx input argument. function operates similarly read_importwq() importing water quality data. Please refer see water quality data vignette additional details import function. FIB data can downloaded follows: data object called fibdata also provided package, although may contain current data available EPC. View help file download date. fibdata object includes monthly samples FIB data select stations Hillsborough River basin. stations include samples beginning 1972. default output read_importwq() returns stations FIB data EPC. = F read_importfib(), stations AreaName source data Hillsborough River, Hillsborough River Tributary, Alafia River, Alafia River Tributary, Lake Thonotosassa, Lake Thonotosassa Tributary, Lake Roberta. Values returned E. coli (ecoli), Enterococcus (ecocci), Fecal Coliform (fcolif), Total Coliform (totcol). Values shown # colonies per 100 mL water (#/100mL). Qualifier columns also returned _q suffix. Qualifier codes can interpreted source spreadsheet. Concentrations noted < > raw data reported , numeric value shown. Samples notation can determined qualifier columns. fibdata object can used remaining FIB functions.","code":"fibdata <- read_importfib('vignettes/current_data.xlsx', download_latest = T) fibdata #> # A tibble: 76,502 × 18 #> area epchc_station class SampleTime yr mo Latitude Longitude #> #> 1 Hills… 2 3M 2024-01-08 14:46:00 2024 1 27.9 -82.5 #> 2 Hills… 6 3M 2024-01-16 09:50:00 2024 1 27.9 -82.5 #> 3 Hills… 7 3M 2024-01-16 10:07:00 2024 1 27.9 -82.5 #> 4 Hills… 8 3M 2024-01-16 12:50:00 2024 1 27.9 -82.4 #> 5 Middl… 9 2 2024-01-16 11:58:00 2024 1 27.8 -82.4 #> 6 Middl… 11 2 2024-01-16 10:20:00 2024 1 27.8 -82.5 #> 7 Middl… 13 2 2024-01-16 10:36:00 2024 1 27.8 -82.5 #> 8 Middl… 14 2 2024-01-16 11:26:00 2024 1 27.8 -82.5 #> 9 Middl… 16 2 2024-01-30 09:10:00 2024 1 27.7 -82.5 #> 10 Middl… 19 2 2024-01-30 09:25:00 2024 1 27.7 -82.6 #> # ℹ 76,492 more rows #> # ℹ 10 more variables: Total_Depth_m , Sample_Depth_m , ecoli , #> # ecoli_q , ecocci , ecocci_q , fcolif , fcolif_q , #> # totcol , totcol_q "},{"path":"https://tbep-tech.github.io/tbeptools/articles/fib.html","id":"retrieving-additional-fib-data","dir":"Articles","previous_headings":"Read","what":"Retrieving additional FIB data","title":"Fecal Indicator Bacteria","text":"FIB functions tbeptools developed work long-term monitoring data Environmental Protection Commission Hillsborough County. Additional monitoring programs Tampa Bay can also used develop complete description FIB data. read_importwqp() function can used retrieve data USEPA Water Quality Portal data monitoring organizations around Tampa Bay watershed. function retrieves additional FIB data using type = 'fib' specified organization identified. data can retrieved follows typically take less one minute download.","code":"# get Manatee County data mancodata <- read_importwqp(org = '21FLMANA_WQX', type = 'fib', trace = T) # get Pinellas County data pincodata <- read_importwqp(org = '21FLPDEM_WQX', type = 'fib', trace = T)"},{"path":"https://tbep-tech.github.io/tbeptools/articles/fib.html","id":"analyze","dir":"Articles","previous_headings":"","what":"Analyze","title":"Fecal Indicator Bacteria","text":"anlz_fibmap() function assigns categories observation fibdata selected month year. results mapped using anlz_fibmap() (see ). categories specific E. coli Enterococcus assigned based station class freshwater (class 1 3F) marine (class 2 3M), respectively. station categorized one four ranges defined thresholds noted cat column output, corresponding colors appropriate range noted col column output. thresholds EPC follows E. coli Enterococcus. yrsel mosel arguments can used filter results year month. specifying arguments return results entire period record. areasel argument can indicate either \"Alafia\" \"Hillsborough\" select data corresponding river basins, rows fibdata filtered based selection. stations returned argument set NULL (default). Alafia River basin includes values area column fibdata \"Alafia River\" \"Alafia River Tributary\". Hillsborough River basin includes values area column fibdat \"Hillsborough River\", \"Hillsborough River Tributary\", \"Lake Thonotosassa\", \"Lake Thonotosassa Tributary\", \"Lake Roberta\". areas may present based selection yrsel mosel. valid options areasel include \"Alafia River\", \"Hillsborough River\", \"Big Bend\", \"Cockroach Bay\", \"East Lake Outfall\", \"Hillsborough Bay\", \"Little Manatee\", \"Lower Tampa Bay\", \"McKay Bay\", \"Middle Tampa Bay\", \"Old Tampa Bay\", \"Palm River\", \"Tampa Bypass Canal\", \"Valrico Lake\". anlz_fibmatrix() function creates summary FIB categories station year output show_fibmatrix() function described . function assigns Microbial Water Quality Assessment (MWQA) letter categories station year based likelihood fecal coliform concentrations exceed 400 CFU / 100 mL given year. default, results year based right-centered window uses previous two years current year calculate probabilities monthly samples (lagyr = 3). columns station year include estimated geometric mean fecal coliform concentrations (gmean) category indicating letter outcome based likelihood exceedences (cat).","code":"anlz_fibmap(fibdata) #> # A tibble: 76,502 × 12 #> area epchc_station class yr mo Latitude Longitude ecoli ecocci ind #> #> 1 Hillsb… 2 3M 2024 1 27.9 -82.5 NA 24 Ente… #> 2 Hillsb… 6 3M 2024 1 27.9 -82.5 NA 2 Ente… #> 3 Hillsb… 7 3M 2024 1 27.9 -82.5 NA 2 Ente… #> 4 Hillsb… 8 3M 2024 1 27.9 -82.4 NA 10 Ente… #> 5 Middle… 9 2 2024 1 27.8 -82.4 NA 2 Ente… #> 6 Middle… 11 2 2024 1 27.8 -82.5 NA 2 Ente… #> 7 Middle… 13 2 2024 1 27.8 -82.5 NA 2 Ente… #> 8 Middle… 14 2 2024 1 27.8 -82.5 NA 2 Ente… #> 9 Middle… 16 2 2024 1 27.7 -82.5 NA 2 Ente… #> 10 Middle… 19 2 2024 1 27.7 -82.6 NA 2 Ente… #> # ℹ 76,492 more rows #> # ℹ 2 more variables: cat , col anlz_fibmap(fibdata, yrsel = 2023, mosel = 7) #> # A tibble: 207 × 12 #> area epchc_station class yr mo Latitude Longitude ecoli ecocci ind #> #> 1 Hillsb… 2 3M 2023 7 27.9 -82.5 NA 800 Ente… #> 2 Hillsb… 6 3M 2023 7 27.9 -82.5 NA 2 Ente… #> 3 Hillsb… 7 3M 2023 7 27.9 -82.5 NA 2 Ente… #> 4 Hillsb… 8 3M 2023 7 27.9 -82.4 NA 2 Ente… #> 5 Middle… 9 2 2023 7 27.8 -82.4 NA 2 Ente… #> 6 Middle… 11 2 2023 7 27.8 -82.5 NA 2 Ente… #> 7 Middle… 13 2 2023 7 27.8 -82.5 NA 2 Ente… #> 8 Middle… 14 2 2023 7 27.8 -82.5 NA 2 Ente… #> 9 Middle… 16 2 2023 7 27.7 -82.5 NA 2 Ente… #> 10 Middle… 19 2 2023 7 27.7 -82.6 NA 2 Ente… #> # ℹ 197 more rows #> # ℹ 2 more variables: cat , col anlz_fibmap(fibdata, yrsel = 2023, mosel = 7, areasel = 'Hillsborough River') #> # A tibble: 47 × 12 #> area epchc_station class yr mo Latitude Longitude ecoli ecocci ind #> #> 1 Hillsb… 2 3M 2023 7 27.9 -82.5 NA 800 Ente… #> 2 Hillsb… 105 3M 2023 7 28.0 -82.4 NA 128 Ente… #> 3 Hillsb… 106 1 2023 7 28.1 -82.4 144 232 E. c… #> 4 Lake T… 107 3F 2023 7 28.0 -82.3 570 1550 E. c… #> 5 Hillsb… 108 3F 2023 7 28.1 -82.2 187 276 E. c… #> 6 Lake T… 118 3F 2023 7 28.1 -82.3 4 7 E. c… #> 7 Hillsb… 120 3F 2023 7 28.1 -82.4 100 410 E. c… #> 8 Lake T… 135 3F 2023 7 28.1 -82.3 4 4 E. c… #> 9 Hillsb… 137 3M 2023 7 28.0 -82.5 NA 680 Ente… #> 10 Hillsb… 143 3F 2023 7 28.1 -82.1 800 1333 E. c… #> # ℹ 37 more rows #> # ℹ 2 more variables: cat , col anlz_fibmatrix(fibdata) #> # A tibble: 8,800 × 4 #> yr epchc_station gmean cat #> #> 1 1985 2 52.4 B #> 2 1985 6 7.21 A #> 3 1985 7 4.64 A #> 4 1985 8 9.49 A #> 5 1985 9 6.32 A #> 6 1985 11 5.18 A #> 7 1985 13 4 A #> 8 1985 14 6.35 A #> 9 1985 16 4 A #> 10 1985 19 4 A #> # ℹ 8,790 more rows"},{"path":"https://tbep-tech.github.io/tbeptools/articles/fib.html","id":"show","dir":"Articles","previous_headings":"","what":"Show","title":"Fecal Indicator Bacteria","text":"show_fibmap() function creates map FIB sites thresholds based output anlz_fibmap(). arguments apply anlz_fibmap() also apply show_fibmap() freshwater marine stations categorized relevant thresholds plotted selected year, month, area. Unlike anlz_fibmap(), yrsel mosel arguments required. Sites Hillsborough Alafia river basins can shown using areasel argument. Additional information site can seen placing cursor location. map inset can also seen clicking arrow button left. show_fibmatrix() function creates stoplight graphic summarized FIB data selected stations year available data [1]. matrix colors based likelihood fecal indicator bacteria concentrations exceed 400 CFU / 100 mL given year (using Fecal Coliform, fcolif fibdata). likelihoods categorized , B, C, D, E (Microbial Water Quality Assessment MWQA categories) corresponding colors, breakpoints category <10%, 10-30%, 30-50%, 50-75%, >75% (right-closed). Methods rationale categorization scheme provided Florida Department Environmental Protection, Figure 8 [2] [1]. default, results year based right-centered window uses previous two years current year calculate probabilities monthly samples (lagyr = 3). example shows results using monthly observations year. default stations used TBEP report #05-13 [3] Hillsborough River Basin Management Action Plan (BMAP) subbasins. include Blackwater Creek (WBID 1482, EPC stations 143, 108), Baker Creek (WBID 1522C, EPC station 107), Lake Thonotosassa (WBID 1522B, EPC stations 135, 118), Flint Creek (WBID 1522A, EPC station 148), Lower Hillsborough River (WBID 1443E, EPC stations 105, 152, 137). stations fibdata can plotted using stas argument. yrrng argument can also used select year range, default 1985 current year data fibdata. preferred, matrix can also returned HTML table can sorted scrolled. first ten rows shown default. default number rows (10) can changed nrows argument. Use sufficiently large number show rows. plotly (interactive, dynamic plot) can returned setting plotly argument TRUE. plots, can view locations general trends FIB data Hillsborough Alafia river basins. Additional functions may added future evaluate FIB data locations.","code":"show_fibmap(fibdata, yrsel = 2023, mosel = 7, areasel = NULL) show_fibmap(fibdata, yrsel = 2023, mosel = 7, areasel = 'Hillsborough River') show_fibmap(fibdata, yrsel = 2023, mosel = 7, areasel = 'Alafia River') show_fibmatrix(fibdata) show_fibmatrix(fibdata, lagyr = 1) show_fibmatrix(fibdata, stas = c(115, 116)) show_fibmatrix(fibdata, yrrng = c(1990, 2020)) show_fibmatrix(fibdata, asreact = TRUE) show_fibmatrix(fibdata, plotly = TRUE)"},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/articles/habitatmasterplan.html","id":"background","dir":"Articles","previous_headings":"","what":"Background","title":"Habitat Master Plan","text":"Dashboard: https://shiny.tbep.org/landuse-change/ habitats Tampa Bay provide food, shelter, important services support birds, fish, mammals, invertebrates. Significant habitat alteration loss occurred development activities. address challenges, Habitat Master Plan (2020 Update) [1] provides set targets goals , achieved, provide healthy balanced coverage native habitats Tampa Bay watershed. update builds previous Habitat Master Plan [2] several ways. target goal setting approach informed past changes forty years habitat restoration experience region. approach also identifies possible today rather replicating past ecological conditions accounts potential future effects sea-level rise, climate change, development. Habitat Master Plan defines 10-year (2030) habitat protection restoration targets 30-year (2050) goals. Maps habitat protection restoration opportunity areas targets goals can attained additional products available new plan. Please visit https://tbep.org/habitat-master-plan-update/ additional information.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/articles/habitatmasterplan.html","id":"datasets","dir":"Articles","previous_headings":"","what":"Datasets","title":"Habitat Master Plan","text":"Three internal datasets tbeptools provide necessary information create Habitat Master Plan report card. Summary annual acreage estimates major habitat type intertidal supratidal strata. Summary annual acreage estimates major habitat type subtidal stratam. table targets goals major habitat type, developed Habitat Master Plan 2020 update [1] (select columns shown). datasets created repository https://github.com/tbep-tech/hmpu-workflow require updates land use cover datasets produced every two three years Southwest Florida Water Management District.","code":"acres #> # A tibble: 90 × 3 #> # Groups: name [9] #> name HMPU_TARGETS Acres #> #> 1 1990 Coastal Uplands 5078. #> 2 1990 Developed 372438. #> 3 1990 Forested Freshwater Wetlands 159561. #> 4 1990 Mangrove Forests 13522. #> 5 1990 Native Uplands 229990. #> 6 1990 Non-Forested Freshwater Wetlands 54454. #> 7 1990 Open Water 38357. #> 8 1990 Restorable 571513. #> 9 1990 Salt Barrens 468 #> 10 1990 Salt Marshes 4482. #> # ℹ 80 more rows subtacres #> # A tibble: 65 × 3 #> name HMPU_TARGETS Acres #> #> 1 1988 Open Water 197802. #> 2 1988 Restorable 72.9 #> 3 1988 Seagrasses 23279. #> 4 1988 Tidal Flats 21686. #> 5 1990 Open Water 197058. #> 6 1990 Restorable 67.0 #> 7 1990 Seagrasses 25218. #> 8 1990 Tidal Flats 20433. #> 9 1992 Open Water 195908. #> 10 1992 Restorable 86.0 #> # ℹ 55 more rows hmptrgs[, c(\"Category\", \"HMPU_TARGETS\", \"Target2030\", \"Goal2050\")] #> Category HMPU_TARGETS Target2030 Goal2050 #> 1 Subtidal Hard Bottom 423.0 423.0 #> 2 Subtidal Artificial Reefs 166.0 166.0 #> 3 Subtidal Tidal Flats 16220.0 16220.0 #> 4 Subtidal Seagrasses 40000.0 40000.0 #> 5 Subtidal Oyster Bars 221.0 471.0 #> 6 Intertidal Living Shorelines 21.3 56.3 #> 7 Intertidal Total Intertidal 21353.0 23803.0 #> 8 Intertidal Mangrove Forests 15300.0 15300.0 #> 9 Intertidal Salt Barrens 546.0 796.0 #> 10 Intertidal Salt Marshes 4807.0 5457.0 #> 11 Intertidal Tidal Tributaries 4.0 18.0 #> 12 Supratidal Coastal Uplands 3769.0 4219.0 #> 13 Supratidal Non-Forested Freshwater Wetlands 68937.0 71787.0 #> 14 Supratidal Forested Freshwater Wetlands 152282.0 152732.0 #> 15 Supratidal Native Uplands 141050.0 142100.0"},{"path":"https://tbep-tech.github.io/tbeptools/articles/habitatmasterplan.html","id":"report-card-summary","dir":"Articles","previous_headings":"","what":"Report card summary","title":"Habitat Master Plan","text":"important reporting product Habitat Master Plan report card summarizes attainment targets goals evaluates prior trends identify coverages trending targets goals. Two functions provided tbeptools create report card. anlz_hmpreport() summarizes datasets provide necessary information creating report card. show_hmpreport() generates plot report card. latter can used former provided need view data behind report card. Using anlz_hmpreport() function summarizes acreage coverage estimates habitat type, compares targets goals year data, assesses coverage trend year pairs determine changes trending targets goals. columns follows: year: Year assessment metric: Habitat type assessed Acres: Coverage estimate year lacres: Coverage estimate previous set available data lyr: Year previous set available data category: Strata habitat type Target: 2030 target habitat type Habitat Master Plan Goal: 2050 goal habitat type Habitat Master Plan acresdiff: Difference acres current year previous set available data yeardiff: Difference years current year previous set available data changerate: Acreage change per year current year relative previous set available data targetrate: Annual rate required achieve 2030 target goalrate: Annual rate required achieve 2050 goal targetprop: Proportion target met current year goalprop: Proportion goal met current year targeteval: number indicating target status current year report card goaleval: number indicating goal status current year report card important columns output targetprop, goalprop, targeteval, goaleval. targetprop goalprop columns indicate proportion target goal met habitat type current assessment year. targeteval goaleval columns one four values, -1, 0, 0.5, 1, habitat type year. numbers define habitat status assessment year: -1: target goal met, trending 0: target goal met, trending 0.5: target goal met, trending 1: target goal met, trending ","code":"anlz_hmpreport(acres = acres, subtacres = subtacres, hmptrgs = hmptrgs) #> # A tibble: 150 × 17 #> year metric Acres lacres lyr category Target Goal acresdiff yeardiff #> #> 1 1990 Seagrasses 25218. 23279. 1988 Subtidal 40000 40000 1939. 2 #> 2 1990 Tidal Fla… 20433. 21686. 1988 Subtidal 16220 16220 -1253. 2 #> 3 1992 Seagrasses 25746. 25218. 1990 Subtidal 40000 40000 528. 2 #> 4 1992 Tidal Fla… 20594. 20433. 1990 Subtidal 16220 16220 161. 2 #> 5 1994 Seagrasses 26524. 25746. 1992 Subtidal 40000 40000 778. 2 #> 6 1994 Tidal Fla… 20244. 20594. 1992 Subtidal 16220 16220 -349. 2 #> 7 1996 Seagrasses 26924. 26524. 1994 Subtidal 40000 40000 400. 2 #> 8 1996 Tidal Fla… 20443. 20244. 1994 Subtidal 16220 16220 199. 2 #> 9 1999 Seagrasses 24840. 26924. 1996 Subtidal 40000 40000 -2083. 3 #> 10 1999 Tidal Fla… 27085. 20443. 1996 Subtidal 16220 16220 6642. 3 #> # ℹ 140 more rows #> # ℹ 7 more variables: changerate , targetrate , goalrate , #> # targetprop , goalprop , targeteval , goaleval "},{"path":"https://tbep-tech.github.io/tbeptools/articles/habitatmasterplan.html","id":"report-card-plot","dir":"Articles","previous_headings":"","what":"Report card plot","title":"Habitat Master Plan","text":"show_hmpreport() can used create Habitat Master Plan report card. anlz_hmpreport() function used internally need used separately. input files . plot shows report card 2030 targets, using typ = \"targets\". colors cell correspond numbers targeteval column (goaleval typ = \"goals\") returned anlz_hmpreport(). numbers cell indicate proportion target targetprop (goal goalprop typ = \"goals\") met habitat type assessment year. Note creation datasets generate summaries continuous year varies subtidal inter/supratidal habitat. 2050 goals report card can shown using typ = \"goals\". subtidal data subtacres inter/supratidal data acres provided different datasets Southwest Florida Water Management District. years dataset typically match dataset collected approximate 2 3 year intervals. default, year y-axis shown continuous variable, gaps shown years dataset unavailable. Use ycollapse = TRUE remove years without data. Different strata can also selected using strata argument. Note use ycollapse = T remove years without data. strata can combined single plot collapsed years using patchwork library. text showing proportion target goal met year can suppressed using text = NULL. size text can changed entering numeric value (default text = 2.5). alternative form report card can returned attainment targets goals likelihood attainment shown differently using colors shapes, respectively. plotted using twocol = T, red shows target goal met, green shows target goal met, plus symbol shows target goal likely met, negative symbols shows target goal likely met. report card provides information artificial reefs, living shorelines, hard bottom habitats. habitats assessed routine data products Southwest Florida Water Management District, although targets goals provided Habitat Master Plan.","code":"show_hmpreport(acres = acres, subtacres = subtacres, hmptrgs = hmptrgs, typ = 'targets') show_hmpreport(acres = acres, subtacres = subtacres, hmptrgs = hmptrgs, typ = 'goals') show_hmpreport(acres = acres, subtacres = subtacres, hmptrgs = hmptrgs, typ = 'targets', ycollapse = T) show_hmpreport(acres = acres, subtacres = subtacres, hmptrgs = hmptrgs, typ = 'targets', strata = c('Intertidal', 'Supratidal'), ycollapse = T) library(patchwork) library(ggplot2) p1 <- show_hmpreport(acres = acres, subtacres = subtacres, hmptrgs = hmptrgs, typ = 'targets', strata = 'Subtidal', ycollapse = T) p2 <- show_hmpreport(acres = acres, subtacres = subtacres, hmptrgs = hmptrgs, typ = 'targets', strata = c('Intertidal', 'Supratidal'), ycollapse = T) + labs(title = NULL) p1 + p2 + plot_layout(ncol = 2, guides = 'collect') show_hmpreport(acres = acres, subtacres = subtacres, hmptrgs = hmptrgs, typ = 'targets', text = NULL) show_hmpreport(acres = acres, subtacres = subtacres, hmptrgs = hmptrgs, typ = 'targets', twocol = T)"},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/articles/intro.html","id":"background","dir":"Articles","previous_headings":"","what":"Background","title":"Water Quality Data","text":"Dashboard: https://shiny.tbep.org/wq-dash vignette provides overview functions tbeptools can used work water quality data Tampa Bay. View vignettes topical introductions reporting products (e.g., seagrasess, tidal creeks, etc.). environmental recovery Tampa Bay exceptional success story coastal water quality management. Nitrogen loads mid 1970s estimated 8.2 million kg/yr, approximately 5.5 million kg/yr entering upper Bay alone [2]. Reduced water clarity associated phytoplankton biomass contributed dramatic reduction areal coverage seagrass [3] development hypoxic events, causing decline benthic faunal production [4]. Extensive efforts reduce nutrient loads Bay occurred late 1970s, notable improvements infrastructure wastewater treatment 1979. Improvements water clarity decreases chlorophyll concentrations observed Bay-wide 1980s, conditions generally remaining constant present day [5]. Tracking changes environmental condition past present day possible without long-term monitoring dataset. Data collected monthly Environmental Protection Commission Hillsborough County since 1974 [6,7]. Samples taken forty-five stations water collection monitoring sonde bottom, mid- surface depths, depending parameter. locations monitoring stations fixed cover entire Bay uppermost mesohaline sections lowermost euhaline portions direct interaction Gulf Mexico. 515 observations available different parameters station, e.g., nitrogen, chlorophyll-, secchi depth. Data collected monitoring program processed maintained spreadsheet titled RWMDataSpreadsheet_ThroughCurrentReportMonth.xlsx https://epcbocc.sharepoint.com/:x:/s/Share/EWKgPirIkoxMp9Hm_wVEICsBk6avI9iSRjFiOxX58wXzIQ?e=kAWZXl&download=1 (viewable ). data include observations stations parameters throughout period record. date, systematic tools importing, analyzing, reporting information data. tbeptools package provides developed address need. Locations long-term monitoring stations Tampa Bay. Bay separated four segments defined chemical, physical, geopolitical boundaries.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/articles/intro.html","id":"read","dir":"Articles","previous_headings":"","what":"Read","title":"Water Quality Data","text":"main function importing water quality data read_importwq(). function downloads latest file one already available location specified xlsx input argument. First, create character path location file. one exist, specify desired location name downloaded file. , want put file vignettes folder name current_results.xls. Note file path relative root working directly current R session. can view working directory getwd(). Now pass xlsx object read_importwq() function. get error message function indicating file found. makes sense file doesn’t exist yet, need tell function download latest file. done changing download_latest argument TRUE (default FALSE). Now get message, indication file server downloaded. ’ll data downloaded saved epcdata object finishes downloading. try run function downloading data server, get following message. check done make sure data unnecessarily downloaded current file matches file server. Every time tbeptools used work monitoring data, read_importwq() used import data. always receive message File current... local file matches one server. However, new data regularly collected posted server. download_latest = TRUE local file date, receive following message: argument na indicates fields downloaded spreadsheet treated blank values assigned NA. number strings can added function replace fields NA values. data successfully imported, can view assigned object: data include bay segment name, station number, sample time, year, month, latitude, longitude, station depth, sample depth, total nitrogen, secchi depth, chlorophyll, salinity, water temperature, turbidity, water color. parameters can included setting = TRUE read_importwq(). import function also available download format phytoplankton cell count data. read_importphyto() function works similarly import function water quality data. Start specifying path data downloaded set download_latest TRUE. function download summarize data file PlanktonDataList_ThroughCurrentReportMonth.xlsx EPC website. phytoplankton data successfully imported, can view assigned object: data highly summarized raw data file available online. Cell counts (number cells per 0.1mL) selected taxa summed station quarters (.e., Jan/Feb/Mar, Apr/May/Jun, etc.). quarter indicated yrqrt column specified starting date quarter (e.g., 1975-07-01 quarter Jul/Aug/Sep 1975). data primarily used support analyses water quality dashboard: https://shiny.tbep.org/wq-dash/","code":"xlsx <- 'vignettes/current_results.xlsx' epcdata <- read_importwq(xlsx) epcdata <- read_importwq(xlsx, download_latest = TRUE) #> File vignettes/current_results.xlsx does not exist, replacing with downloaded file... #> trying URL 'https://epcbocc.sharepoint.com/:x:/s/Share/EYXZ5t16UlFGk1rzIU91VogBa8U37lh8z_Hftf2KJISSHg?e=8r1SUL&download=1' length 24562051 bytes (23.4 MB) epcdata <- read_importwq(xlsx, download_latest = TRUE) #> File is current... #> Replacing local file with current... epcdata #> # A tibble: 27,961 × 26 #> bay_segment epchc_station SampleTime yr mo Latitude Longitude #> #> 1 HB 6 2023-12-19 10:01:00 2023 12 27.9 -82.5 #> 2 HB 7 2023-12-19 10:12:00 2023 12 27.9 -82.5 #> 3 HB 8 2023-12-19 12:39:00 2023 12 27.9 -82.4 #> 4 MTB 9 2023-12-19 11:54:00 2023 12 27.8 -82.4 #> 5 MTB 11 2023-12-19 10:25:00 2023 12 27.8 -82.5 #> 6 MTB 13 2023-12-19 10:38:00 2023 12 27.8 -82.5 #> 7 MTB 14 2023-12-19 11:24:00 2023 12 27.8 -82.5 #> 8 MTB 16 2023-12-20 09:35:00 2023 12 27.7 -82.5 #> 9 MTB 19 2023-12-20 09:49:00 2023 12 27.7 -82.6 #> 10 LTB 23 2023-12-20 13:16:00 2023 12 27.7 -82.6 #> # ℹ 27,951 more rows #> # ℹ 19 more variables: Total_Depth_m , Sample_Depth_m , tn , #> # tn_q , sd_m , sd_raw_m , sd_q , chla , #> # chla_q , Sal_Top_ppth , Sal_Mid_ppth , #> # Sal_Bottom_ppth , Temp_Water_Top_degC , #> # Temp_Water_Mid_degC , Temp_Water_Bottom_degC , #> # `Turbidity_JTU-NTU` , Turbidity_Q , Color_345_F45_PCU , … xlsx <- 'phyto_data.xlsx' phytodata <- read_importphyto(xlsx, download_latest = T) #> File vignettes/phyto_data.xlsx does not exist, replacing with downloaded file... #> trying URL 'https://epcbocc.sharepoint.com/:x:/s/Share/ETAfRQ5drmRHntDd1O8s3FQB180Fumed4nQ99w-OIVDxrA?e=eSmtxD&download=1' length 12319508 bytes (11.7 MB) phytodata #> # A tibble: 21,143 × 8 #> epchc_station Date name units count yrqrt yr mo #> #> 1 11 1975-07-23 other /0.1mL 0 1975-07-01 1975 Jul #> 2 11 1976-01-07 other /0.1mL 1 1976-01-01 1976 Jan #> 3 11 1977-01-05 other /0.1mL 1 1977-01-01 1977 Jan #> 4 11 1977-04-20 Tripos hircus /0.1mL 1 1977-04-01 1977 Apr #> 5 11 1977-04-20 other /0.1mL 1 1977-04-01 1977 Apr #> 6 11 1977-07-13 other /0.1mL 12 1977-07-01 1977 Jul #> 7 11 1978-01-11 other /0.1mL 16 1978-01-01 1978 Jan #> 8 11 1979-02-08 other /0.1mL 1 1979-01-01 1979 Feb #> 9 11 1979-05-02 Karenia brevis /0.1mL 1 1979-04-01 1979 May #> 10 11 1979-05-30 other /0.1mL 1 1979-04-01 1979 May #> # ℹ 21,133 more rows"},{"path":"https://tbep-tech.github.io/tbeptools/articles/intro.html","id":"retrieving-additional-water-quality-data","dir":"Articles","previous_headings":"Read","what":"Retrieving additional water quality data","title":"Water Quality Data","text":"water quality functions tbeptools developed work long-term monitoring data Environmental Protection Commission Hillsborough County. Additional monitoring programs Tampa Bay can also used develop complete description water quality. read_importwqp() function can used retrieve data USEPA Water Quality Portal data monitoring organizations around Tampa Bay watershed. function retrieves nutrient, chlorophyll, secchi, temperature, salinity, turbidity data available estuarine stations monitored organization type = 'wq'. data can retrieved follows typically take less one minute download.","code":"# get Manatee County data mancodata <- read_importwqp(org = '21FLMANA_WQX', type = 'wq', trace = T) # get Pinellas County data pincodata <- read_importwqp(org = '21FLPDEM_WQX', type = 'wq', trace = T)"},{"path":"https://tbep-tech.github.io/tbeptools/articles/intro.html","id":"analyze","dir":"Articles","previous_headings":"","what":"Analyze","title":"Water Quality Data","text":"functions anlz_avedat() anlz_avedatsite() summarize station data bay segments sites, respectively. functions return annual means chlorophyll light attenuation (based Secchi depth measurements) monthly means year chlorophyll light attenuation. summaries used determine bay segment targets water quality met using anlz_attain() anlz_attainsite() function. use anlz_avedat() summarize data bay segment estimate annual monthly means chlorophyll light attenuation. output two-element list annual (ann) monthly (mos) means segment. output can analyzed anlz_attain() determine bay segment outcomes met year. results used plotting functions described . short, chl_la column indicates categorical outcome chlorophyll light attenuation segment. outcomes integer values zero three. relative exceedances water quality thresholds segment, duration magnitude, indicated higher integer values. Similar information can obtained individual sites using anlz_avedatsite() anlz_attainsite(). main difference yes/column metis added indicates target segment threshold site.","code":"avedat <- anlz_avedat(epcdata) avedat #> $ann #> # A tibble: 608 × 4 #> yr bay_segment var val #> #> 1 1974 HB mean_chla 22.4 #> 2 1974 LTB mean_chla 4.24 #> 3 1974 MTB mean_chla 9.66 #> 4 1974 OTB mean_chla 10.2 #> 5 1975 HB mean_chla 27.9 #> 6 1975 LTB mean_chla 4.93 #> 7 1975 MTB mean_chla 11.4 #> 8 1975 OTB mean_chla 13.2 #> 9 1976 HB mean_chla 29.5 #> 10 1976 LTB mean_chla 5.08 #> # ℹ 598 more rows #> #> $mos #> # A tibble: 4,724 × 5 #> bay_segment yr mo var val #> #> 1 HB 1974 1 mean_chla 36.2 #> 2 LTB 1974 1 mean_chla 1.75 #> 3 MTB 1974 1 mean_chla 11.5 #> 4 OTB 1974 1 mean_chla 4.4 #> 5 HB 1974 2 mean_chla 42.4 #> 6 LTB 1974 2 mean_chla 5.5 #> 7 MTB 1974 2 mean_chla 9.35 #> 8 OTB 1974 2 mean_chla 4.07 #> 9 HB 1974 3 mean_chla 14.9 #> 10 LTB 1974 3 mean_chla 5.88 #> # ℹ 4,714 more rows anlz_attain(avedat) #> # A tibble: 200 × 4 #> bay_segment yr chl_la outcome #> #> 1 HB 1974 3_0 yellow #> 2 HB 1975 3_2 red #> 3 HB 1976 3_2 red #> 4 HB 1977 3_2 red #> 5 HB 1978 3_3 red #> 6 HB 1979 3_3 red #> 7 HB 1980 3_3 red #> 8 HB 1981 3_3 red #> 9 HB 1982 3_3 red #> 10 HB 1983 3_0 yellow #> # ℹ 190 more rows anlz_avedatsite(epcdata) %>% anlz_attainsite #> # A tibble: 2,250 × 9 #> yr bay_segment epchc_station var val target smallex thresh met #> #> 1 1974 HB 6 chla 25.6 13.2 14.1 15 no #> 2 1974 HB 7 chla 21.6 13.2 14.1 15 no #> 3 1974 HB 8 chla 22.6 13.2 14.1 15 no #> 4 1974 HB 44 chla 23.4 13.2 14.1 15 no #> 5 1974 HB 52 chla 23.5 13.2 14.1 15 no #> 6 1974 HB 55 chla 20.2 13.2 14.1 15 no #> 7 1974 HB 70 chla 33.1 13.2 14.1 15 no #> 8 1974 HB 71 chla 25.8 13.2 14.1 15 no #> 9 1974 HB 73 chla 17.6 13.2 14.1 15 no #> 10 1974 HB 80 chla 10.5 13.2 14.1 15 yes #> # ℹ 2,240 more rows"},{"path":"https://tbep-tech.github.io/tbeptools/articles/intro.html","id":"show","dir":"Articles","previous_headings":"","what":"Show","title":"Water Quality Data","text":"External package libraries R can used plot time series data. ’s example using popular ggplot2 package. data wrangling dplyr done first filter data want plot. show_thrplot() function provides descriptive assessment annual trends chosen bay segment relative defined targets thresholds. plot show annual averages across stations Old Tampa bay (bay_segment = \"OTB\") chlorophyll (thr = \"chla\"). red line shows annual trends horizontal blue lines indicate thresholds targets chlorophyll-specific Old Tampa Bay. dashed dotted blue lines indicate +1 +2 standard errors management target shown filled line. target standard errors considered identifying annual segment outcome chlorophyll. can show plot light attenuation changing thr = \"chla\" thr = \"la\". Note change horizontal reference lines light attenuation target. year range plot can also specified using yrrng argument, default year range epcdata. show_thrplot() function uses results anlz_avedat() function. example, can retrieve values plot follows: Similarly, show_boxplot() function provides assessment seasonal changes chlorophyll light attenuation values bay segment. recent year highlighted red default. allows simple evaluation recent year compared historical averages. large exceedance value shown blue text dotted line. corresponds “large” magnitude change +2 standard errors bay segment threshold dotted line shown show_thrplot(). different subset years selected year interest can also viewed changing yrrng yrsel arguments. show 1980 compared monthly averages 2008 2018. show_thrplot() function useful understand annual variation chlorophyll light attenuation relative management targets bay segment. information plots can provide understanding annual reporting outcomes determined. noted , outcome integer zero three assigned bay segment annual estimate chlorophyll light attenuation. outcomes based exceedance annual estimate threshold target (blue lines show_thrplot()) duration exceedance years prior. following graphic describes logic [8]. Outcomes annual estimates water quality assigned integer value zero three depending magnitude duration exceedence. outcomes assigned chlorophyll light attenuation. duration criteria determined based whether exceedance observed years prior current year. exceedance criteria chlorophyll light-attenuation specific segment. tbeptools package contains targets data file reference determining annual outcomes. file loaded automatically package can viewed command line. final plotting function show_matrix(), creates annual reporting matrix reflects combined outcomes chlorophyll light attenuation. Tracking attainment bay segment specific targets indicators provides framework bay management actions developed initiated. year segment, color-coded management action assigned: Stay Course: Continue planned projects. Report data via annual progress reports Baywide Environmental Monitoring Report. Caution: Review monitoring data nitrogen loading estimates. Begin/continue TAC Management Board development specific management recommendations. Alert: Finalize development implement appropriate management actions get back track. management category action based combination outcomes chlorophyll light attenuation [8]. Management action categories assigned bay segment year based chlorophyll light attenuation outcomes. results can viewed show_matrix(). matrix also ggplot object layout can changed using ggplot elements. Note use txtsz = NULL remove color labels. preferred, matrix can also returned HTML table can sorted scrolled. first ten rows shown default. default number rows (10) can changed nrows argument. Use sufficiently large number show rows. plotly (interactive, dynamic plot) can returned setting plotly argument TRUE. Results can also obtained selected year. Outcomes can returned tabular format anlz_yrattain(). table also shows segment averages chlorophyll light attenuation, including associated targets. map showing individual sites achieved chlorophyll targets can obtained show_sitemap(). station averages chlorophyll selected year shown next point. Stations red failed meet segment target. show_sitemap() function also includes argument specify particular monthly range selected year. option chosen, averages shown continuous values station. Another map can created show_sitesegmap() similar show_sitemap(), except bay segments shown colored annual outcome. map useful understand site data correspond bay segment. Bay segment exceedances can also viewed matrix using show_wqmatrix(). thresholds values correspond Florida DEP criteria (large exceedance defined +2 standard errors segment target). default, show_wqmatrix() function returns chlorophyll exceedances segment. Light attenuation exceedances can viewed changing param argument. results show_matrix() show_wqmatrix() can combined individual segment using show_segmatrix() function. useful understand water quality parameter driving management outcome given year. plot shows light attenuation chlorophyll outcomes show_wqmatrix() next segment management outcomes show_matrix(). one segment can plotted function call. Finally, segment plots can shown together using show_segplotly() function combines chlorophyll secchi data given segment. function combines outputs show_thrplot() show_segmatrix(). final plot interactive can zoomed dragging mouse pointer section plot. Information cell value can seen hovering location plot. plots, can quickly view summary environmental history water quality Tampa Bay. Degraded conditions common early period record, particularly Old Tampa Bay Hillsborough Bay. Conditions began improve late 1980s early 1990s, good conditions persisting present day. However, recent trends Old Tampa Bay shown conditions changing “stay course” “caution”.","code":"toplo <- epcdata %>% filter(epchc_station == '52') ggplot(toplo, aes(x = SampleTime, y = chla)) + geom_line() + geom_point() + scale_y_log10() + labs( y = 'Chlorophyll-a concentration (ug/L)', x = NULL, title = 'Chlorophyll trends', subtitle = 'Hillsborough Bay station 52, all dates' ) + theme_bw() show_thrplot(epcdata, bay_segment = \"OTB\", thr = \"chla\") show_thrplot(epcdata, bay_segment = \"OTB\", thr = \"la\") show_thrplot(epcdata, bay_segment = \"OTB\", thr = \"la\", yrrng = c(2000, 2018)) epcdata %>% anlz_avedat %>% .[['ann']] %>% filter(bay_segment == 'OTB') %>% filter(var == 'mean_la') %>% filter(yr >= 2000 & yr <= 2018) #> # A tibble: 19 × 4 #> yr bay_segment var val #> #> 1 2000 OTB mean_la 0.733 #> 2 2001 OTB mean_la 0.951 #> 3 2002 OTB mean_la 0.927 #> 4 2003 OTB mean_la 1.04 #> 5 2004 OTB mean_la 0.878 #> 6 2005 OTB mean_la 0.769 #> 7 2006 OTB mean_la 0.620 #> 8 2007 OTB mean_la 0.677 #> 9 2008 OTB mean_la 0.696 #> 10 2009 OTB mean_la 0.808 #> 11 2010 OTB mean_la 0.842 #> 12 2011 OTB mean_la 0.912 #> 13 2012 OTB mean_la 0.687 #> 14 2013 OTB mean_la 0.567 #> 15 2014 OTB mean_la 0.606 #> 16 2015 OTB mean_la 0.560 #> 17 2016 OTB mean_la 0.575 #> 18 2017 OTB mean_la 0.682 #> 19 2018 OTB mean_la 0.678 show_boxplot(epcdata, param = 'chla', bay_segment = \"OTB\") show_boxplot(epcdata, param = 'la', bay_segment = \"HB\") show_boxplot(epcdata, param = 'chla', bay_segment = \"OTB\", yrrng = c(2008, 2018), yrsel = 1980) targets #> bay_segment name chla_target chla_smallex chla_thresh #> 1 OTB Old Tampa Bay 8.5 8.9 9.3 #> 2 HB Hillsborough Bay 13.2 14.1 15.0 #> 3 MTB Middle Tampa Bay 7.4 7.9 8.5 #> 4 LTB Lower Tampa Bay 4.6 4.8 5.1 #> 5 BCBN Boca Ciega Bay North 7.7 NaN 8.3 #> 6 BCBS Boca Ciega Bay South 6.1 NaN 6.3 #> 7 TCB Terra Ceia Bay 7.5 NaN 8.7 #> 8 MR Manatee River 7.3 NaN 8.8 #> 9 RALTB Remainder Lower Tampa Bay NaN NaN 5.1 #> la_target la_smallex la_thresh #> 1 0.83 0.86 0.88 #> 2 1.58 1.63 1.67 #> 3 0.83 0.87 0.91 #> 4 0.63 0.66 0.68 #> 5 NaN NaN NaN #> 6 NaN NaN NaN #> 7 NaN NaN NaN #> 8 NaN NaN NaN #> 9 NaN NaN NaN show_matrix(epcdata) show_matrix(epcdata, txtsz = NULL) + scale_y_continuous(expand = c(0,0), breaks = sort(unique(epcdata$yr))) + coord_flip() + theme(axis.text.x = element_text(angle = 45, hjust = 1, size = 7)) show_matrix(epcdata, asreact = TRUE) show_matrix(epcdata, plotly = TRUE) anlz_yrattain(epcdata, yrsel = 2018) #> # A tibble: 4 × 6 #> bay_segment chla_val chla_target la_val la_target outcome #> #> 1 OTB 9.22 8.5 0.678 0.83 yellow #> 2 HB 13.9 13.2 1.09 1.58 green #> 3 MTB 7.05 7.4 0.570 0.83 green #> 4 LTB 4.65 4.6 0.593 0.63 green show_sitemap(epcdata, yrsel = 2018) show_sitemap(epcdata, yrsel = 2018, mosel = c(7, 9)) show_sitesegmap(epcdata, yrsel = 2018) show_wqmatrix(epcdata) show_wqmatrix(epcdata, param = 'la') show_segmatrix(epcdata, bay_segment = 'OTB') show_segplotly(epcdata, width = 1000, height = 600)"},{"path":"https://tbep-tech.github.io/tbeptools/articles/intro.html","id":"reasonable-assurance-reporting","dir":"Articles","previous_headings":"Show","what":"Reasonable Assurance reporting","title":"Water Quality Data","text":"TBEP collaboration Tampa Bay Nitrogen Management Consortium (NMC) reports annually water quality conditions Tampa Bay Reasonable Assurance (RA) plan Florida Department Environmental Protection (FDEP). plan comprehensive approach managing nitrogen pollution Tampa Bay provides “reasonable assurance” designated uses waterbody segments bay maintained restored response potential nutrient impairments. Annual reports FDEP critical part plan tbeptools package includes functions facilitate reporting. functions previously described (e.g., show_wqmatrix()). First, show_annualassess() function can create simple table annual management outcome assessments chlorophyll-light attenuation bay segment. provides summary results given year, including segment-averaged chlorophyll-light attenuation bay segment names colored management outcome. required inputs EPC dataset selected year. Segment Chl-(ug/L) Light Penetration (m-1) 2023 target 2023 target OTB 6.2 8.5 0.73 0.83 HB 6.9 13.2 0.79 1.58 MTB 3.7 7.4 0.47 0.83 LTB 2.6 4.6 0.54 0.63 default caption can also included setting caption = TRUE. Water quality outcomes 2023. Segment Chl-(ug/L) Light Penetration (m-1) 2023 target 2023 target OTB 6.2 8.5 0.73 0.83 HB 6.9 13.2 0.79 1.58 MTB 3.7 7.4 0.47 0.83 LTB 2.6 4.6 0.54 0.63 Second, show_ratab() function provides table annual water quality outcomes relative five-year RA reporting period. table includes associated NMC actions followed based water quality outcomes, actions provide reasonable assurance water quality maintained restored following outcomes. results specific four bay segments. Bay Segment Reasonable Assurance Assessment Steps DATA USED ASSESS ANNUAL REASONABLE ASSURANCE OUTCOME Year 1 (2022) Year 2 (2023) Year 3 (2024) Year 4 (2025) Year 5 (2026) NMC Action 1: Determine observed chlorophyll-exceeds FDEP threshold 9.3 ug/L (7.1) (6.2) years threshold far, necessary NMC Actions 2-5 NMC Action 2: Determine observed chlorophyll-exceedences occurred 2 consecutive years years met threshold, necessary NMC Actions 3-5 NMC Action 3: Determine observed hydrologically-normalized total load exceeds federally-recognized TMDL 486 tons/year N/N/ necessary due observed water quality seagrass conditions bay segment NMC Actions 4-5: Determine entity/source/facility specific exceedences 5-yr average allocation occurred implementation period necessary chlorophyll-threshold met show_ratab() function developed 2022-2026 RA period currently work previous RA periods. function may updated future accommodate different periods.","code":"show_annualassess(epcdata, yrsel = 2023) show_annualassess(epcdata, yrsel = 2023, caption = TRUE) show_ratab(epcdata, yrsel = 2023, bay_segment = 'OTB')"},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/articles/seagrasstransect.html","id":"data-import-and-included-datasets","dir":"Articles","previous_headings":"","what":"Data import and included datasets","title":"Seagrass Transect Data","text":"two datasets included tbeptools show actively monitored transect locations Tampa Bay. trnpts dataset point object starting location transect trnlns dataset line object showing approximate direction length transect beginning point trnpts. dataset also includes MonAgency column indicates monitoring agency collects data transect. two datasets sf() (simple features) objects easily mapped mapview() view locations. transect data can downloaded Water Atlas using read_transect() function. required argument function training, indicates want download training data complete dataset, .e., training = TRUE training = FALSE (default). former case, small dataset downloaded includes data collected annual training event. primarily used internally TBEP staff assess precision among different training crews. data downloaded JSON object formatted internally using read_formtransect() function. Shoot density reported number shoots per square meter corrected quadrat size entered raw data. Abundance reported numeric value 0 -5 Braun-Blanquet coverage estimates blade length cm. Change training argument FALSE download entire transect database. may take seconds. columns complete transect database describe crew (Crew), monitoring agency (MonitoringAgency), sample date (Date), transect name (Transect), meter location quadrat along transect (Site, m), depth site (Depth, cm), Seagrass species (Savspecies), distance seagrass edge transect (SeagrassEdge, m), seagrass variable (var), average value variable (aveval), standard deviation variable appropriate (sdval). raw, unformatted transect data preferred, use raw = TRUE argument read_transect().","code":"trnpts #> Simple feature collection with 66 features and 11 fields #> Geometry type: POINT #> Dimension: XY #> Bounding box: xmin: -82.8089 ymin: 27.49925 xmax: -82.39305 ymax: 28.0001 #> Geodetic CRS: WGS 84 #> First 10 features: #> SEGMENT TRANSECT TRAN_ID Metermark ID LAT_DD LONG_DD MonAgency STATUS #> 1 1 1 S1T1 0 START 27.99498 -82.68325 EPCHC ACTIVE #> 2 1 3 S1T3 0 START 28.00010 -82.66417 EPCHC ACTIVE #> 3 1 5 S1T5 0 START 27.95788 -82.54663 FDEP ACTIVE #> 4 1 6 S1T6 0 START 27.91348 -82.53282 EPCHC ACTIVE #> 5 1 8 S1T8 0 START 27.86233 -82.56867 EPCHC ACTIVE #> 6 1 13 S1T13 0 START 27.92428 -82.70232 EPCHC ACTIVE #> 7 1 14 S1T14 0 START 27.85533 -82.59738 EPCHC ACTIVE #> 8 1 15 S1T15 0 START 27.87408 -82.53098 EPCHC ACTIVE #> 9 1 16 S1T16 0 START 27.88228 -82.62015 PCDEM ACTIVE #> 10 1 17 S1T17 0 START 27.90498 -82.64793 PCDEM ACTIVE #> Comments bay_segment geometry #> 1 OTB POINT (-82.68325 27.99498) #> 2 OTB POINT (-82.66417 28.0001) #> 3 OTB POINT (-82.54663 27.95788) #> 4 OTB POINT (-82.53282 27.91348) #> 5 OTB POINT (-82.56867 27.86233) #> 6 OTB POINT (-82.70232 27.92428) #> 7 OTB POINT (-82.59738 27.85533) #> 8 OTB POINT (-82.53098 27.87408) #> 9 OTB POINT (-82.62015 27.88228) #> 10 OTB POINT (-82.64793 27.90498) trnlns #> Simple feature collection with 61 features and 7 fields #> Geometry type: LINESTRING #> Dimension: XYM #> Bounding box: xmin: -82.8118 ymin: 27.49807 xmax: -82.39306 ymax: 28.0001 #> m_range: mmin: 0 mmax: 2700 #> Geodetic CRS: WGS 84 #> First 10 features: #> OBJECTID Site Shape_Leng MonAgency ActiveYN Comments #> 1 1 S1T1 300.1400 EPCHC YES #> 2 5 S1T13 1102.6182 EPCHC YES #> 3 6 S1T14 800.4500 EPCHC YES #> 4 7 S1T15 701.0075 EPCHC YES #> 5 8 S1T16 998.9961 PCDEM YES #> 6 9 S1T17 2698.5773 PCDEM YES #> 7 10 S1T18 997.5451 EPCHC YES #> 8 12 S1T3 401.5991 EPCHC YES #> 9 14 S1T5 457.5927 FDEP YES #> 10 15 S1T6 398.6606 EPCHC YES #> geometry bearing #> 1 LINESTRING M (-82.68325 27.... 116.533756 #> 2 LINESTRING M (-82.70232 27.... -4.689701 #> 3 LINESTRING M (-82.59738 27.... 109.402541 #> 4 LINESTRING M (-82.53098 27.... -85.765142 #> 5 LINESTRING M (-82.62015 27.... 13.913960 #> 6 LINESTRING M (-82.64791 27.... -21.165576 #> 7 LINESTRING M (-82.61143 27.... -123.050914 #> 8 LINESTRING M (-82.66417 28.... -128.034327 #> 9 LINESTRING M (-82.54663 27.... -121.861907 #> 10 LINESTRING M (-82.53282 27.... -89.362036 cols <- c(\"#E16A86\", \"#CB7F2F\", \"#9F9400\", \"#50A315\", \"#00AC79\", \"#00AAB7\", \"#009ADE\", \"#A87BE4\", \"#DA65C3\") mapview(trnpts, zcol = 'MonAgency', lwd = 0, legend = F, homebutton = F, col.regions = cols) + mapview(trnlns, zcol = 'MonAgency', homebutton = F, layer.name = 'Monitoring Agency', lwd = 4, color = cols) # import training data traindat <- read_transect(training = TRUE) # view the data traindat #> # A tibble: 957 × 11 #> yr grp grpact Crew MonitoringAgency Site Depth Savspecies var aveval #> #> 1 2020 A 2020:… K. H… MCNRD 1 -50 Halodule Abun… 3 #> 2 2020 A 2020:… K. H… MCNRD 1 -50 Halodule Blad… 0 #> 3 2020 A 2020:… K. H… MCNRD 1 -50 Halodule Shor… 0 #> 4 2020 A 2020:… K. H… MCNRD 3 -60 Halodule Abun… 5 #> 5 2020 A 2020:… K. H… MCNRD 3 -60 Halodule Blad… 22 #> 6 2020 A 2020:… K. H… MCNRD 3 -60 Halodule Shor… 27.3 #> 7 2020 A 2020:… K. H… MCNRD 3 -60 Thalassia Abun… 1 #> 8 2020 A 2020:… K. H… MCNRD 3 -60 Thalassia Blad… 45.2 #> 9 2020 A 2020:… K. H… MCNRD 3 -60 Thalassia Shor… 0.667 #> 10 2020 A 2020:… K. H… MCNRD 4 -90 Halodule Abun… 1 #> # ℹ 947 more rows #> # ℹ 1 more variable: sdval # import entire transct dataset as JSON transect <- read_transect(training = FALSE) # view the data transect #> # A tibble: 152,580 × 11 #> Crew MonitoringAgency Date Transect Site Depth Savspecies #> #> 1 Ali Mauer, Melis… PCDEM 2020-11-04 S5T8 0 -5 No Cover #> 2 Ali Mauer, Melis… PCDEM 2020-11-04 S5T8 0 -5 No Cover #> 3 Ali Mauer, Melis… PCDEM 2020-11-04 S5T8 0 -5 No Cover #> 4 Ali Mauer, Melis… PCDEM 2020-11-04 S5T8 10 -12 Halodule #> 5 Ali Mauer, Melis… PCDEM 2020-11-04 S5T8 10 -12 Halodule #> 6 Ali Mauer, Melis… PCDEM 2020-11-04 S5T8 10 -12 Halodule #> 7 Ali Mauer, Melis… PCDEM 2020-11-04 S5T8 100 -180 Syringodi… #> 8 Ali Mauer, Melis… PCDEM 2020-11-04 S5T8 100 -180 Syringodi… #> 9 Ali Mauer, Melis… PCDEM 2020-11-04 S5T8 100 -180 Syringodi… #> 10 Ali Mauer, Melis… PCDEM 2020-11-04 S5T8 11 -20 Halodule #> # ℹ 152,570 more rows #> # ℹ 4 more variables: SeagrassEdge , var , aveval , sdval # raw transect data transectraw <- read_transect(training = FALSE, raw = TRUE) # view the data transectraw #> # A tibble: 51,174 × 46 #> IDall AssessmentYear CreatedAt Crew CountingTech SeagrassEdge Secchi Sonde #> #> 1 2 1998 1998-10-15… NA NA NA NA FALSE #> 2 2 1998 1998-10-15… NA NA NA NA FALSE #> 3 2 1998 1998-10-15… NA NA NA NA FALSE #> 4 2 1998 1998-10-15… NA NA NA NA FALSE #> 5 2 1998 1998-10-15… NA NA NA NA FALSE #> 6 2 1998 1998-10-15… NA NA NA NA FALSE #> 7 2 1998 1998-10-15… NA NA NA NA FALSE #> 8 2 1998 1998-10-15… NA NA NA NA FALSE #> 9 2 1998 1998-10-15… NA NA NA NA FALSE #> 10 2 1998 1998-10-15… NA NA NA NA FALSE #> # ℹ 51,164 more rows #> # ℹ 38 more variables: Weather , Hidden , HiddenReason , #> # IsComplete , QASubmittedAt , ReadyForQA , #> # QACompletedAt , MonitoringAgency , Transect , #> # BaySegment , ID , ObservationDate , Site , #> # Species , SpeciesAbundance , Appearance , #> # BladeLength_1 , BladeLength_2 , BladeLength_3 , …"},{"path":"https://tbep-tech.github.io/tbeptools/articles/seagrasstransect.html","id":"calculating-seagrass-frequency-occurrence","dir":"Articles","previous_headings":"","what":"Calculating seagrass frequency occurrence","title":"Seagrass Transect Data","text":"rest seagrass functions tbeptools developed work complete database. show_complot() function (see ) developed training data. rest functions can used estimate plot frequency occurrence data. anlz_transectocc() function summarizes frequency occurrence transects dates collapsing species results across quadrats within transect. Abundance frequency occurrence estimated Sherwood et al. 2017, equations 1 2 [1]. short, frequency occurrence estimated number instances species observed along transect divided number placements along transect average abundance estimated sum species-specific Braun-Blanquet scores divided number placements along transect. estimates obtained seagrass species, including Caulerpa spp. (attached macroalgae) Dapis (cyanobacteria), whereas attached drift algae species aggregated. Drift attached macroalgae cyanobacteria (Dapis) estimates may accurate prior 2021. second function, anlz_transectave(), takes results anlz_transectocc() estimates annual results across major bay segments seagrass species averaging frequency occurrence across transects. function used internally within show_transectmatrix() function create summary plots. frequency occurrence estimates also binned categories simple trend assessments, e.g., red < 25%, orange 25-50%, yellow 50-75%, green > 75%. Results specific bay segments annual ranges can filtered bay_segment yrrng arguments. third function, anlz_transectavespp(), takes results anlz_transectocc() estimates annual averages across major bay segments last function, results retained individual species. function used internally within show_transectavespp() function create summary plots. summaries aggregated across selected bay segments, .e., default average species/year across segments. Results individual bay segment can returned appropriate argument, e.g., using bay_segment = 'OTB' select Old Tampa Bay. Results can also filtered specific species using species argument, default return . Caulerpa spp. Dapis spp. also included. Results individual bay segments anlz_transectavespp() can retained setting by_seg argument TRUE. Note totals returned case.","code":"transectocc <- anlz_transectocc(transect) transectocc #> # A tibble: 37,625 × 6 #> # Groups: Date, Transect [1,505] #> Date Transect Savspecies nsites foest bbest #> #> 1 1997-10-11 S2T3 \"AA\" 41 0 0 #> 2 1997-10-11 S2T3 \"Caulerpa\" 41 0 0 #> 3 1997-10-11 S2T3 \"DA\" 41 0 0 #> 4 1997-10-11 S2T3 \"DB: Dictyota\\r\\n\" 41 0 0 #> 5 1997-10-11 S2T3 \"DB: Drift Brown\\r\\n\" 41 0 0 #> 6 1997-10-11 S2T3 \"DG: Chaetomorpha\\r\\n\" 41 0 0 #> 7 1997-10-11 S2T3 \"DG: Drift Green\" 41 0 0 #> 8 1997-10-11 S2T3 \"DG: Ulva\" 41 0 0 #> 9 1997-10-11 S2T3 \"DG: Ulva fasciata\\r\\n\" 41 0 0 #> 10 1997-10-11 S2T3 \"DR: Acanthophora\" 41 0 0 #> # ℹ 37,615 more rows transectave <- anlz_transectave(transectocc) transectave #> # A tibble: 156 × 4 #> # Groups: bay_segment [6] #> bay_segment yr foest focat #> #> 1 Tampa Bay 1998 58.0 #E9C318 #> 2 OTB 1998 65.5 #E9C318 #> 3 HB 1998 15.0 #CC3231 #> 4 MTB 1998 53.7 #E9C318 #> 5 LTB 1998 80.8 #2DC938 #> 6 BCB 1998 81.0 #2DC938 #> 7 Tampa Bay 1999 51.5 #E9C318 #> 8 OTB 1999 64.7 #E9C318 #> 9 HB 1999 10.1 #CC3231 #> 10 MTB 1999 51.8 #E9C318 #> # ℹ 146 more rows transectavespp <- anlz_transectavespp(transectocc) transectavespp #> # A tibble: 208 × 3 #> yr Savspecies foest #> #> 1 1998 Caulerpa 0.0166 #> 2 1998 Dapis 0 #> 3 1998 Halodule 0.361 #> 4 1998 Halophila 0 #> 5 1998 Ruppia 0.0112 #> 6 1998 Syringodium 0.0451 #> 7 1998 Thalassia 0.254 #> 8 1998 total 0.580 #> 9 1999 Caulerpa 0.0277 #> 10 1999 Dapis 0 #> # ℹ 198 more rows transectavespp <- anlz_transectavespp(transectocc, by_seg = TRUE) transectavespp #> # A tibble: 1,170 × 5 #> yr bay_segment Savspecies foest nsites #> #> 1 1998 BCB Caulerpa 0 96 #> 2 1998 BCB Dapis 0 96 #> 3 1998 BCB Halodule 0.613 96 #> 4 1998 BCB Halophila 0 96 #> 5 1998 BCB No Cover 0.190 96 #> 6 1998 BCB Ruppia 0 96 #> 7 1998 BCB Syringodium 0 96 #> 8 1998 BCB Thalassia 0.304 96 #> 9 1998 BCB total 0.810 96 #> 10 1998 HB Caulerpa 0 285 #> # ℹ 1,160 more rows"},{"path":"https://tbep-tech.github.io/tbeptools/articles/seagrasstransect.html","id":"plotting-results","dir":"Articles","previous_headings":"","what":"Plotting results","title":"Seagrass Transect Data","text":"one plotting function training data. show_compplot() function used compare training data crews selected species (species argument) variable (varplo argument). rest plotting functions work complete transect data. Data individual transect can viewed show_transect() function entering transect (site) number, species (one many), variable plot. plot shows relative values selected species variable distance along transect (x-axis) year sampling (y-axis). plots provide overall summary temporal spatial changes selected seagrass metric individual location. plot can also produced plotly interactive plot setting plotly = TRUE inside function. Note size legend merged species legend, point size average abundance species. sizes can viewed mouseover point. show_transect() function can also used plot multiple species. One many species can provided species argument. plots can also separated facets species using facet = TRUE. useful reduce overplotting multiple species found location. show_transectsum() function provides alternative summary data individual transect. plot provides quick visual assessment frequency occurrence abundance multiple species changed time selected transect. Unlike show_transect(), plot shows aggregated results across quadrats along transect uses summarized data anlz_transectocc() function input. summary matrix frequency occurrence estimates across species can plotted show_transectmatrix(). uses results anlz_transectocc() anlz_transectave() functions estimate annual averages bay segment. continuous frequency occurrence estimates binned color categories described , Table 1 [2]. default color scheme based arbitrary breaks 25, 50, 75 percent frequency occurrence. don’t necessarily translate ecological breakpoints. Use neutral = TRUE use neutral continuous color palette. matrix can also produced plotly interactive plot setting plotly = TRUE inside function. Time series plots annual averages frequency occurrence estimates species can shown show_transectavespp() function. default, estimates averaged across bay segments species. plot representation Figure 2 [2]. Results individual segments species can returned bay_segment species arguments. Use argument total = FALSE omit total frequency occurrence plot. plot can also produced plotly interactive plot setting plotly = TRUE inside function. alternative plotting species averages time show_transectavespp(), table can created setting asreact = TRUE. Filtering options apply plot also apply table, e.g., filtering four major bay segments specific year ranges. Also note totals returned table. describes methods tbeptools working transect monitoring data. Seagrass coverage maps also created approximately biennially Southwest Florida Water Management District, available https://data-swfwmd.opendata.arcgis.com/. seagrass data object included package shows Tampa Bay coverage total year available data, including 1950s reference estimate. show_seagrasscoverage() function creates flagship seagrass coverage graphic report changes time data.","code":"show_compplot(traindat, yr = 2023, site = '2', species = 'Halodule', varplo = 'Abundance', base_size = 14) show_transect(transect, site = 'S3T10', species = 'Halodule', varplo = 'Abundance') show_transect(transect, site = 'S3T10', species = 'Halodule', varplo = 'Abundance', plotly = T) show_transect(transect, site = 'S3T10', species = c('Halodule', 'Syringodium', 'Thalassia'), varplo = 'Abundance') show_transect(transect, site = 'S3T10', species = c('Halodule', 'Syringodium', 'Thalassia'), varplo = 'Abundance', facet = TRUE) show_transectsum(transectocc, site = 'S3T10') show_transectmatrix(transectocc) show_transectmatrix(transectocc, neutral = T) show_transectmatrix(transectocc, plotly = T) show_transectavespp(transectocc) show_transectavespp(transectocc, bay_segment = 'LTB', species = c('Syringodium', 'Thalassia'), total = FALSE) show_transectavespp(transectocc, bay_segment = 'LTB', species = c('Syringodium', 'Thalassia'), plotly = T) show_transectavespp(transectocc, asreact = T, bay_segment = c('HB', 'OTB', 'MTB', 'LTB'), yrrng = c(2006, 2012)) show_seagrasscoverage(seagrass)"},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/articles/tbbi.html","id":"background","dir":"Articles","previous_headings":"","what":"Background","title":"Tampa Bay Benthic Index","text":"Tampa Bay Benthic Index (TBBI) [1,2]) assessment method quantifies ecological health benthic community Tampa Bay. index provides complementary approach evaluating environmental condition supported assessment methods currently available region (e.g., water quality report card, nekton index, etc.). tbeptools package includes several functions described import data required index plot results view trends time. functions described detail . TBBI uses data Tampa Bay Benthic Monitoring Program part Environmental Protection Commission (EPC) Hillsborough Country. data updated annually public site maintained EPC, typically December Summer/Fall sampling. website hosts water quality data used water quality report card. required data TBBI extensive water quality report card data made available zipped folder csv files, available . process downloading working data similar functions tbeptools.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/articles/tbbi.html","id":"data-import-and-included-datasets","dir":"Articles","previous_headings":"","what":"Data import and included datasets","title":"Tampa Bay Benthic Index","text":"Data calculating TBBI scores can imported current R session using read_importbenthic() function. function downloads zipped folder base tables used TBBI EPC site data already downloaded location specified input arguments. download data tbeptools, first create character path location want download zipped files. one exist, specify location name downloaded file. , name folder benthic.zip download desktop. Running code return following error: get error message function indicating file found. makes sense file exist yet, need tell function download latest file. done changing download_latest argument TRUE (default FALSE). Now get indication file server downloaded. download complete, ’ll data downloaded saved benthicdata object current R session. try run function downloading data, get following message. check done make sure data unnecessarily downloaded current file matches file server. Every time tbeptools used work benthic data, read_importbenthic() used import data. always receive message File current... local file matches one server. However, data periodically updated posted server. download_latest = TRUE local file date, receive following message:","code":"path <- '~/Desktop/benthic.zip' benthicdata <- read_importbenthic(path) #> Error in read_importbenthic() : File at path does not exist, use download_latest = TRUE benthicdata <- read_importbenthic(path, download_latest = T) #> File ~/Desktop/benthic.zip does not exist, replacing with downloaded file... #> trying URL 'https://epcbocc.sharepoint.com/:u:/s/Share/EQUCWBuwCNdGuMREYAyAD1gBKC98mYtCHMWX0FYLrbT4KA?e=nDfnnQ&download=1' length 37122877 bytes (35.4 MB) benthicdata <- read_importbenthic(path, download_latest = T) #> File is current.. #> Replacing local file with current..."},{"path":"https://tbep-tech.github.io/tbeptools/articles/tbbi.html","id":"calculating-tbbi-scores","dir":"Articles","previous_headings":"","what":"Calculating TBBI scores","title":"Tampa Bay Benthic Index","text":"data imported, can view assigned object. data provided nested tibble includes three different datasets: station information, field sample data (salinity), detailed taxa information. individual datasets can viewed extracting parent object using deframe() function tibble package. anlz_tbbiscr() function uses nested benthicdata estimate TBBI scores site. TBBI scores typically range 0 100 grouped categories describe general condition benthic community. Scores less 73 considered “degraded”, scores 73 87 “intermediate”, scores greater 87 “healthy”. Locations sampled organisms found assigned score zero category “empty sample”. total abundance (TotalAbundance, organisms/m2), species richness (SpeciesRichness) bottom salinity (Salinity, psu) also provided. metrics TBBI corrected salinity bottom measurements taken time sampling required accurate calculation TBBI.","code":"benthicdata #> # A tibble: 3 × 2 #> name value #> #> 1 stations #> 2 fieldsamples #> 3 taxacounts # see all deframe(benthicdata) #> $stations #> # A tibble: 4,787 × 10 #> StationID StationNumber AreaAbbr FundingProject ProgramID ProgramName #> #> 1 448 02BBs301 MTB Apollo Beach 4 Benthic Monitoring #> 2 449 02BBs305 MTB Apollo Beach 4 Benthic Monitoring #> 3 450 02BBs307 MTB Apollo Beach 4 Benthic Monitoring #> 4 451 02BBs364 MTB Apollo Beach 4 Benthic Monitoring #> 5 452 02BBs369 MTB Apollo Beach 4 Benthic Monitoring #> 6 453 02BBs395 MTB Apollo Beach 4 Benthic Monitoring #> 7 454 02BBs397 MTB Apollo Beach 4 Benthic Monitoring #> 8 455 02BBs398 MTB Apollo Beach 4 Benthic Monitoring #> 9 456 02BBs401 MTB Apollo Beach 4 Benthic Monitoring #> 10 457 02BBs402 MTB Apollo Beach 4 Benthic Monitoring #> # ℹ 4,777 more rows #> # ℹ 4 more variables: Latitude , Longitude , date , yr #> #> $fieldsamples #> # A tibble: 5,197 × 3 #> StationID date Salinity #> #> 1 448 2002-05-21 30.5 #> 2 449 2002-05-20 30.8 #> 3 450 2002-05-21 30.5 #> 4 451 2002-05-21 30.6 #> 5 452 2002-05-20 30 #> 6 453 2002-05-21 30.6 #> 7 454 2002-05-21 30.5 #> 8 455 2002-05-21 30.3 #> 9 456 2002-05-20 30.0 #> 10 457 2002-05-20 29.9 #> # ℹ 5,187 more rows #> #> $taxacounts #> # A tibble: 149,657 × 7 #> StationID TaxaCountID TaxaListID FAMILY NAME TaxaCount AdjCount #> #> 1 11321 152055 1198 Anomiidae Anomia … 1 25 #> 2 11321 152056 1224 Carditidae Cardite… 1 25 #> 3 584 233277 624 Cirratulidae Chaetoz… 1 25 #> 4 11321 152057 1306 Veneridae Chione … 3 75 #> 5 3132 239443 352 Pilargidae Sigambr… 14 350 #> 6 11321 152058 1088 Pyramidellidae Turboni… 6 150 #> 7 2541 140530 258 NULL NEMERTEA 8 200 #> 8 2542 140531 258 NULL NEMERTEA 2 50 #> 9 2992 140631 262 NULL Palaeon… 4 100 #> 10 3003 140635 285 Tetrastemmatidae Tetrast… 2 50 #> # ℹ 149,647 more rows # get only station dat deframe(benthicdata)[['stations']] #> # A tibble: 4,787 × 10 #> StationID StationNumber AreaAbbr FundingProject ProgramID ProgramName #> #> 1 448 02BBs301 MTB Apollo Beach 4 Benthic Monitoring #> 2 449 02BBs305 MTB Apollo Beach 4 Benthic Monitoring #> 3 450 02BBs307 MTB Apollo Beach 4 Benthic Monitoring #> 4 451 02BBs364 MTB Apollo Beach 4 Benthic Monitoring #> 5 452 02BBs369 MTB Apollo Beach 4 Benthic Monitoring #> 6 453 02BBs395 MTB Apollo Beach 4 Benthic Monitoring #> 7 454 02BBs397 MTB Apollo Beach 4 Benthic Monitoring #> 8 455 02BBs398 MTB Apollo Beach 4 Benthic Monitoring #> 9 456 02BBs401 MTB Apollo Beach 4 Benthic Monitoring #> 10 457 02BBs402 MTB Apollo Beach 4 Benthic Monitoring #> # ℹ 4,777 more rows #> # ℹ 4 more variables: Latitude , Longitude , date , yr tbbiscr <- anlz_tbbiscr(benthicdata) tbbiscr #> # A tibble: 4,787 × 15 #> StationID StationNumber AreaAbbr FundingProject ProgramID ProgramName #> #> 1 448 02BBs301 MTB Apollo Beach 4 Benthic Monitoring #> 2 449 02BBs305 MTB Apollo Beach 4 Benthic Monitoring #> 3 450 02BBs307 MTB Apollo Beach 4 Benthic Monitoring #> 4 451 02BBs364 MTB Apollo Beach 4 Benthic Monitoring #> 5 452 02BBs369 MTB Apollo Beach 4 Benthic Monitoring #> 6 453 02BBs395 MTB Apollo Beach 4 Benthic Monitoring #> 7 454 02BBs397 MTB Apollo Beach 4 Benthic Monitoring #> 8 455 02BBs398 MTB Apollo Beach 4 Benthic Monitoring #> 9 456 02BBs401 MTB Apollo Beach 4 Benthic Monitoring #> 10 457 02BBs402 MTB Apollo Beach 4 Benthic Monitoring #> # ℹ 4,777 more rows #> # ℹ 9 more variables: Latitude , Longitude , date , yr , #> # TotalAbundance , SpeciesRichness , TBBI , TBBICat , #> # Salinity "},{"path":"https://tbep-tech.github.io/tbeptools/articles/tbbi.html","id":"plotting-results","dir":"Articles","previous_headings":"","what":"Plotting results","title":"Tampa Bay Benthic Index","text":"TBBI scores can viewed annual averages bay segment using show_tbbimatrix() function. show_tbbimatrix() plots annual bay segment averages categorical values conventional “stoplight” graphic. baywide estimate also returned, one based samples across locations (“”) another weighted relative surface areas bay segment (“(wt)”). input show_tbbimatrix() function output anlz_tbbiscr() function. matrix can also produced plotly interactive plot setting plotly = TRUE inside function.","code":"show_tbbimatrix(tbbiscr) show_tbbimatrix(tbbiscr, plotly = T)"},{"path":"https://tbep-tech.github.io/tbeptools/articles/tbbi.html","id":"additional-sediment-data","dir":"Articles","previous_headings":"","what":"Additional sediment data","title":"Tampa Bay Benthic Index","text":"addition biological data, sediment contaminant concentrations measured sites within Tampa Bay. include 100 different constituents grouped broadly metals, organics, physical, . concentrations constituents can compared relative Threshold Effects Levels (TEL) Potential Effects Levels (PEL), available, relative indications likelihood concentrations toxic effects invertebrates inhabit sediments. functions tbeptools can used retrieve sediment data provide indication concentrations relative TEL PEL thresholds. read_importsediment() function retrieve sediment data Tampa Bay collected annually Environmental Protection Commission Hillsborough County. data retrieved location biological data used calculate TBBI. data imported, can view assigned object. show_sedimentmap() function can used create maps selected parameters relative TEL PEL values. Green points show concentrations TEL, yellow points show concentrations TEL PEL, red points show concentrations PEL. applicable TEL PEL values parameter indicated legend. selected stations sampled years within yrrng argument. single year data can shown well. map showing concentrations returned TEL PEL values available parameter. Maps total contaminant values (e.g., Total DDT, Total PAH, Total PCB, Total LMW PAH, Total HMW PAH) can also returned. Although totals included sedimentdata object, calculated tbeptools using anlz_sedimentaddtot() function. Simply entering name total parameter show_sedimentmap() function produce summary map. PEL ratio can also used assess relative sediment quality given measured contaminants. show_sedimentpelmap() function creates map average PEL ratios graded F benthic stations monitored Tampa Bay. PEL ratio contaminant concentration divided Potential Effects Levels (PEL) applies contaminant, available. Higher ratios lower grades indicate sediment conditions likely unfavorable invertebrates. station average combines PEL ratios across contaminants measured station. average PEL ratios grades used create map can also returned data frame using anlz_sedimentpel(). Plots bay segment averages sediment concentrations selected parameters can created show_sedimentave(). plot includes appropriate lines TEL PEL values, well grand mean across segments. former omitted plot unavailable selected parameter. plot can returned interactive plotly object using plotly = T. values used plot can returned anlz_sedimentave(). , total contaminant values (e.g., Total DDT, Total PAH, Total PCB, Total LMW PAH, Total HMW PAH) can also returned even though included sedimentdata object. anlz_sedimentaddtot() function used calculate totals within anlz_sedimentave(). similar plot bay segment averages average PEL ratios can created show_sedimentpelave(). colors indicate grades (green) F (red). plot can returned interactive plotly object using plotly = T. values used plot can returned anlz_sedimentpelave(). show_sedimentalratio() function creates plot selected metal parameter Aluminum. plot provides information concentration parameter relative background levels, Aluminum present common metal Earth’s crust. elevated ratio metal parameter relative aluminum suggests higher background concentrations [3]. linear fit log-log model shown solid black line, 95% prediction intervals. TEL/PEL values, available, also shown horizontal red lines. plot can returned interactive plotly object using plotly = T.","code":"path <- '~/Desktop/sediment.zip' sedimentdata <- read_importsediment(path, download_latest = T) sedimentdata #> # A tibble: 221,597 × 24 #> ProgramId ProgramName FundingProject yr AreaAbbr StationID StationNumber #> #> 1 4 Benthic Moni… TBEP 1993 HB 2463 93HB15 #> 2 4 Benthic Moni… TBEP 1993 HB 2463 93HB15 #> 3 4 Benthic Moni… TBEP 1993 HB 2463 93HB15 #> 4 4 Benthic Moni… TBEP 1993 HB 2463 93HB15 #> 5 4 Benthic Moni… TBEP 1993 HB 2463 93HB15 #> 6 4 Benthic Moni… TBEP 1993 HB 2463 93HB15 #> 7 4 Benthic Moni… TBEP 1993 HB 2463 93HB15 #> 8 4 Benthic Moni… TBEP 1993 HB 2463 93HB15 #> 9 4 Benthic Moni… TBEP 1993 HB 2463 93HB15 #> 10 4 Benthic Moni… TBEP 1993 HB 2463 93HB15 #> # ℹ 221,587 more rows #> # ℹ 17 more variables: Latitude , Longitude , Replicate , #> # SedResultsType , Parameter , ValueAdjusted , Units , #> # Qualifier , MDLnum , PQLnum , TEL , PEL , #> # BetweenTELPEL , ExceedsPEL , PELRatio , #> # PreparationDate , AnalysisTimeMerge show_sedimentmap(sedimentdata, param = 'Arsenic', yrrng = c(1993, 2022)) show_sedimentmap(sedimentdata, param = 'Arsenic', yrrng = 2022) show_sedimentmap(sedimentdata, param = 'Selenium', yrrng = c(1993, 2022)) show_sedimentmap(sedimentdata, param = 'Total DDT', yrrng = c(1993, 2022)) show_sedimentpelmap(sedimentdata, yrrng = c(1993, 2022)) anlz_sedimentpel(sedimentdata, yrrng = c(1993, 2022)) #> # A tibble: 2,233 × 7 #> yr AreaAbbr StationNumber Latitude Longitude PELRatio Grade #> #> 1 1993 HB 93HB15 27.8 -82.4 0.0157 B #> 2 1993 HB 93HB16 27.8 -82.5 0.0261 C #> 3 1993 HB 93HB23 27.9 -82.4 0.0174 B #> 4 1993 LTB 93LTB24 27.7 -82.6 0.0124 B #> 5 1993 LTB 93LTB25 27.6 -82.6 0.0189 B #> 6 1993 LTB 93LTB26 27.6 -82.7 0.00997 B #> 7 1993 LTB 93LTB27 27.6 -82.7 0.0125 B #> 8 1993 LTB 93LTB28 27.6 -82.7 0.0887 D #> 9 1993 LTB 93LTB29 27.6 -82.6 0.0350 C #> 10 1993 LTB 93LTB30 27.6 -82.6 0.0496 C #> # ℹ 2,223 more rows show_sedimentave(sedimentdata, param = 'Arsenic', yrrng = c(1993, 2022)) show_sedimentave(sedimentdata, param = 'Arsenic', yrrng = c(1993, 2022), plotly = T) anlz_sedimentave(sedimentdata, param = 'Arsenic', yrrng = c(1993, 2022)) #> # A tibble: 7 × 8 #> AreaAbbr TEL PEL Units ave lov hiv grandave #> #> 1 BCB 7.24 41.6 mg/kg 2.64 2.34 2.94 2.57 #> 2 HB 7.24 41.6 mg/kg 2.93 0.665 5.20 2.57 #> 3 LTB 7.24 41.6 mg/kg 2.93 2.47 3.40 2.57 #> 4 MR 7.24 41.6 mg/kg 1.66 1.37 1.95 2.57 #> 5 MTB 7.24 41.6 mg/kg 2.17 1.86 2.48 2.57 #> 6 OTB 7.24 41.6 mg/kg 3.24 0.707 5.78 2.57 #> 7 TCB 7.24 41.6 mg/kg 2.40 1.92 2.88 2.57 anlz_sedimentave(sedimentdata, param = 'Total DDT', yrrng = c(1993, 2022)) #> # A tibble: 7 × 8 #> AreaAbbr TEL PEL Units ave lov hiv grandave #> #> 1 BCB 3.89 51.7 ug/kg 0.570 0.382 0.757 0.700 #> 2 HB 3.89 51.7 ug/kg 1.77 0.870 2.67 0.700 #> 3 LTB 3.89 51.7 ug/kg 0.218 0.105 0.332 0.700 #> 4 MR 3.89 51.7 ug/kg 0.838 0.517 1.16 0.700 #> 5 MTB 3.89 51.7 ug/kg 0.434 0.285 0.582 0.700 #> 6 OTB 3.89 51.7 ug/kg 0.490 0.274 0.706 0.700 #> 7 TCB 3.89 51.7 ug/kg 0.582 0.202 0.962 0.700 show_sedimentpelave(sedimentdata, yrrng = c(1993, 2022)) show_sedimentpelave(sedimentdata, yrrng = c(1993, 2022), plotly = T) anlz_sedimentpelave(sedimentdata, yrrng = c(1993, 2022)) #> # A tibble: 7 × 5 #> AreaAbbr ave lov hiv grandave #> #> 1 BCB 0.0535 0.0445 0.0625 0.0522 #> 2 HB 0.118 0.0663 0.169 0.0522 #> 3 LTB 0.0281 0.0247 0.0315 0.0522 #> 4 MR 0.0446 0.0375 0.0516 0.0522 #> 5 MTB 0.0374 0.0327 0.0421 0.0522 #> 6 OTB 0.0506 0.0371 0.0642 0.0522 #> 7 TCB 0.0337 0.0265 0.0409 0.0522 show_sedimentalratio(sedimentdata, param = 'Zinc', bay_segment = c('HB', 'LTB')) show_sedimentalratio(sedimentdata, param = 'Zinc', bay_segment = c('HB', 'LTB'), plotly = T)"},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/articles/tbni.html","id":"background","dir":"Articles","previous_headings":"","what":"Background","title":"Tampa Bay Nekton Index","text":"Tampa Bay Nekton Index (TBNI) [1,2]) multimetric assessment method quantifies ecological health nekton community Tampa Bay. index provides complementary approach evaluating environmental condition supported assessment methods currently available Tampa Bay (e.g., water quality report card, Benthic index, etc.). tbeptools package includes several functions described import data required index, analyze data calculate metrics index scores, plot results view trends time. functions described detail . TBNI uses catch data Florida Fish Wildlife Conservation Commission (FWC) Fish Wildlife Research Institute’s (FWRI) Fisheries-Independent Monitoring (FIM) program. Catch results center-bag seine longest consistent record FIM database used develop TBNI. include counts taxa identification individuals caught near shore areas, generally early recruits, juveniles, smaller-bodied nekton. fish selected invertebrates identified lowest possible taxon (usually species), counted, subset measured. Current protocols established 1998 TBNI estimates unavailable prior date.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/articles/tbni.html","id":"data-import-and-included-datasets","dir":"Articles","previous_headings":"","what":"Data import and included datasets","title":"Tampa Bay Nekton Index","text":"Data required calculating TBNI scores can imported current R session using read_importfim() function. function downloads latest FIM file FTP site data already downloaded location specified input arguments. download data, first create character path location file. one exist, specify desired location name downloaded file. , want put file desktop home directory name fimdata.csv. Running code return following error: get error message function indicating file found. makes sense file doesn’t exist yet, need tell function download latest file. done changing download_latest argument TRUE (default FALSE). Now get indication file server downloaded. download complete, ’ll data downloaded saved fimdata object current R session. try run function downloading data server, get following message. check done make sure data unnecessarily downloaded current matches file server. Every time tbeptools used work FIM data, read_importfim() used import data. always receive message File current... local file matches one server. However, new data regularly collected posted server. download_latest = TRUE local file date, receive following message: data successfully imported, can view assigned object: imported data formatted calculating TBNI. columns include Reference FIM sampling site, sampling date, sampling Zone, sampling Grid, NODCCODE unique identifier species, sample year, sample month, total catch Total_N, scientific name, column indicating species included index, several columns indicating species-specific information required metrics. final columns, separate lookup table provided package merged imported FIM data. file, tbnispp, can viewed anytime package loaded: read_importfim() function can also return simple features object sampled stations raw FIM data setting . data matched appropriate bay segments tabulating TBNI scores. resulting dataset indicates sampling occurred can mapped mapview() function. ease use, dataset named fimstations included tbeptools. read_importfim() function processes observed data needed TBNI, including merging rows tbnispp fimstations data. imported, metrics scores can calculated.","code":"csv <- '~/Desktop/fimdata.csv' fimdata <- read_importfim(csv) #> Error in read_importfim(csv) : file.exists(csv) is not TRUE fimdata <- read_importfim(csv, download_latest = T) #> File ~/Desktop/fimdata.csv does not exist, replacing with downloaded file... #> trying URL 'ftp://ftp.floridamarine.org/users/fim/tmac/NektonIndex/TampaBay_NektonIndexData.csv' length 11083878 bytes (10.6 MB) fimdata <- read_importfim(csv, download_latest = T) #> File is current.. #> Replacing local file with current... head(fimdata) #> # A tibble: 6 × 19 #> Reference Sampling_Date Latitude Longitude Zone Grid NODCCODE Year Month #> #> 1 TBM19980109… 1998-01-09 28.0 -82.7 A 31 8747020… 1998 1 #> 2 TBM19980109… 1998-01-09 28.0 -82.7 A 31 8805020… 1998 1 #> 3 TBM19980109… 1998-01-09 27.9 -82.7 A 62 6177010… 1998 1 #> 4 TBM19980109… 1998-01-09 27.9 -82.7 A 63 9998000… 1998 1 #> 5 TBM19980109… 1998-01-09 27.9 -82.6 A 65 8820020… 1998 1 #> 6 TBM19980109… 1998-01-09 27.9 -82.6 A 65 8826020… 1998 1 #> # ℹ 10 more variables: Total_N , ScientificName , #> # Include_TB_Index , Hab_Cat , Est_Cat , Est_Use , #> # Feeding_Cat , Feeding_Guild , Selected_Taxa , #> # bay_segment head(tbnispp) #> NODCCODE ScientificName Include_TB_Index Hab_Cat Est_Cat #> 1 8860030201 Acanthostracion quadricornis Y B MS #> 2 8858010000 Achiridae spp. N B ES #> 3 8858030202 Achirus lineatus Y B ES #> 4 8804040401 Adinia xenica Y B ES #> 5 8713070101 Aetobatus narinari Y B MS #> 6 8739010101 Albula vulpes Y P MS #> Est_Use Feeding_Cat Feeding_Guild Selected_Taxa #> 1 O TS ZB N #> 2 O TS ZB N #> 3 O TS ZB N #> 4 O TS ZP N #> 5 F TS ZB N #> 6 S TS ZB Y fimstations <- read_importfim(csv, download_latest = TRUE, locs = TRUE) mapview(fimstations, zcol = 'bay_segment')"},{"path":"https://tbep-tech.github.io/tbeptools/articles/tbni.html","id":"calculating-metrics-and-tbni-scores","dir":"Articles","previous_headings":"","what":"Calculating metrics and TBNI scores","title":"Tampa Bay Nekton Index","text":"Metrics scores Tampa Bay Nekton Index can calculated using two functions. anlz_tbnimet() function calculates raw metrics anlz_tbniscr() function calculates scored metrics final TBNI score. functions use imported formatted FIM data input. TBNI includes five metrics sensitive stressor gradients provide unique information Nekton community response environmental conditions. metrics include: NumTaxa: Species richness BenthicTaxa: Species richness benthic taxa TaxaSelect: Number “selected” species (.e., commercially /recreationally important) NumGuilds: Number trophic guilds Shannon: Shannon Diversity (H) Raw metrics first calculated observed data scaled standard score 0 - 10 accounting expected relationships environmental gradients 5th/95th percentiles distributions. final TBNI score summed average scores ranging 0 - 100. raw metrics, scored metrics, final TBNI score returned anlz_tbniscr() function. five metrics chosen TBNI appropriate Tampa Bay dataset selected larger pool candidate metrics. potential metrics can calculated using anlz_tbnimet() function. metrics can used standalone assessments developing Nekton index outside Tampa Bay. argument = TRUE must used return metrics, otherwise selected five TBNI returned.","code":"tbniscr <- anlz_tbniscr(fimdata) head(tbniscr) #> # A tibble: 6 × 16 #> Reference Year Month Season bay_segment TBNI_Score NumTaxa ScoreNumTaxa #> #> 1 TBM1998010906 1998 1 Winter OTB 18 2 2 #> 2 TBM1998010910 1998 1 Winter OTB 14 1 1 #> 3 TBM1998010912 1998 1 Winter OTB 0 0 0 #> 4 TBM1998010914 1998 1 Winter OTB 20 2 2 #> 5 TBM1998010915 1998 1 Winter MTB 46 4 4 #> 6 TBM1998010917 1998 1 Winter MTB 24 2 2 #> # ℹ 8 more variables: BenthicTaxa , ScoreBenthicTaxa , #> # TaxaSelect , ScoreTaxaSelect , NumGuilds , #> # ScoreNumGuilds , Shannon , ScoreShannon tbnimet <- anlz_tbnimet(fimdata, all = T) head(tbnimet) #> # A tibble: 6 × 37 #> Reference Year Month Season bay_segment NumTaxa NumIndiv Shannon Simpson #> #> 1 TBM1998010906 1998 1 Winter OTB 2 17 0.362 1.26 #> 2 TBM1998010910 1998 1 Winter OTB 1 1 0 1 #> 3 TBM1998010912 1998 1 Winter OTB 0 0 0 0 #> 4 TBM1998010914 1998 1 Winter OTB 2 2 0.693 2 #> 5 TBM1998010915 1998 1 Winter MTB 4 11 1.16 2.81 #> 6 TBM1998010917 1998 1 Winter MTB 2 5 0.500 1.47 #> # ℹ 28 more variables: Pielou , TaxaSelect , NumGuilds , #> # TSTaxa , TGTaxa , BenthicTaxa , PelagicTaxa , #> # OblTaxa , MSTaxa , ESTaxa , SelectIndiv , Taxa90 , #> # TSAbund , TGAbund , BenthicAbund , PelagicAbund , #> # OblAbund , ESAbund , MSAbund , Num_LR , PropTG , #> # PropTS , PropBenthic , PropPelagic , PropObl , #> # PropMS , PropES , PropSelect "},{"path":"https://tbep-tech.github.io/tbeptools/articles/tbni.html","id":"plotting-results","dir":"Articles","previous_headings":"","what":"Plotting results","title":"Tampa Bay Nekton Index","text":"TBNI scores can viewed annual averages using show_tbniscr(), show_tbniscrall() show_tbnimatrix() functions. show_tbniscr() creates line graph values time bay segment, whereas show_tbniscrall() function plots overall average across bay segments time. show_tbnimatrix() plots annual bay segment averages categorical values conventional “stoplight” graphic. input function output anlz_tbniscr() function. plots can also produced plotly interactive plots setting plotly = TRUE inside function. breakpoints categorical outcomes TBNI scores shown colors graph based 33rd 50th percentiles distribution TBNI scores calculated Tampa Bay. plotting option provided consistency existing TBEP reporting tools, e.g., water quality report card returned show_matrix(). categorical outcomes serve management guidelines year activities support environmental resources Bay: Stay Course, Caution, Alert [3]. graphs returned plotting functions ggplot objects can modified. can combined using patchwork single graphic showing trends time categorical outcomes matrix continuous scores bottom plot.","code":"show_tbniscr(tbniscr) show_tbniscrall(tbniscr) show_tbnimatrix(tbniscr) show_tbniscr(tbniscr, plotly = T) show_tbniscrall(tbniscr, plotly = T) show_tbnimatrix(tbniscr, plotly = T) p1 <- show_tbnimatrix(tbniscr, txtsz = NULL, rev = TRUE, position = 'bottom') + scale_y_continuous(expand = c(0,0), breaks = c(1998:2020)) + coord_flip() + theme(axis.text.x = element_blank()) p2 <- show_tbniscr(tbniscr) p1 + p2 + plot_layout(ncol = 1, heights = c(0.3, 1))"},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/articles/tidalcreeks.html","id":"background","dir":"Articles","previous_headings":"","what":"Background","title":"Tidal Creek Assessment","text":"Dashboard: https://shiny.tbep.org/tidalcreek-dash/ Tidal creeks (aka tributaries) essential habitats Tampa Bay Estuary serve important focal points understanding watershed inputs affect water quality. fundamental goal Tampa Bay Estuary Program develop effective nutrient management strategies support ecological function tidal creeks. partnership Sarasota Bay NEP, Coastal & Heartland NEP, local government agency stakeholders, open science framework developed assessing tidal creek condition based host commonly collected water quality data [1–3]. assessments can support tracking water quality management goals can help refine restoration management plans priority tributaries, including need hydrologic restoration can support critical nursery habitats sportfishes. tbeptools package includes simple features spatial data object population tidal creeks southwest Florida, called tidalcreeks(). includes 615 polyline features designated water body ID (WBID), creek id (JEI), FDEP class (class, 1 potable water, 2 shellfish harvesting propagation, 3F/3M freshwater/marine fish consumption, recreation, propagation maintenance healthy, well-balanced population fish wildlife). tidal creek assessment framework established based data FDEP Impaired Waters Rule database run 56 available includes data collected January 10th 2019. However, framework intends link future IWR databases refresh site new data becomes available. Raw updated data IWR database required assessment provided tbeptools package iwrraw() data object.","code":"mapview(tidalcreeks, homebutton = F, legend = F)"},{"path":"https://tbep-tech.github.io/tbeptools/articles/tidalcreeks.html","id":"assessment","dir":"Articles","previous_headings":"","what":"Assessment","title":"Tidal Creek Assessment","text":"tidal creek assessment framework includes “report card” “indicators” assessment provided separate tabs dashboard. report card provides assessment total nitrogen concentrations (limiting nutrient creeks) based annual geometric average concentrations relative standards developed contributing freshwater streams. indicators based several water quality metrics derived outcomes study describe tidal creek condition provide insights site specific attributes creeks may govern overall creek health.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/articles/tidalcreeks.html","id":"report-card","dir":"Articles","previous_headings":"","what":"Report card","title":"Tidal Creek Assessment","text":"report card similar TBEP water quality report card tidal creeks assigned categories within assessment framework intended serve mechanism evaluating data relative need management action, identify stewardship goals , properly pursued, may preclude need regulatory actions. categories established based principally fish biological response indicator. Tidal creeks assigned one five categories: Data: Data unavailable evaluation. Monitor: Creek nitrogen concentrations protect individual creek types within larger population creeks. Caution: Creek nutrients showing signs elevated nutrient concentrations may increase risk eutrophic condition. Investigate: Creek nutrient concentrations margin safety protect creek potential impairment. Prioritize: Creek nutrient concentrations exceeded regulatory standard associated freshwater portion tributary indicating actions needed identify remediative measures reduce nutrients creek. Conceptually, thresholds appear figure . Scoring rubrik tidal creeks based nitrogen thresholds. Prioritize category defined based Florida’s freshwater stream numeric nutrient criteria (NNC).Two different freshwater stream NNC applicable region; West Central NNC 1.65 mg/l Peninsular region NNC 1.54 mg/l. histograms figure represent range annual geometric mean (AGM) nitrogen concentrations associated Prioritize Investigate categories based NNC. example , maximum expected distribution AGMs exceed 1.65 mg/l 1:3 exceedence probability (defined F..C. 62-303) generated using monte carlo simulation highest observed standard deviation data collected first creeks study. Investigate category defined explicit margin safety adjusting distribution find grand geometric average result 1:20 chance exceeding 1.65 mg/l. Assignment creek Caution category depended creek length adjustment described protect smaller creeks elevated nutrient concentrations. tidaltargets() data object included tbeptools includes thresholds. Note “Caution” category function creek length. scoring algorithm derived define final report card outcome creek using entire ten year record available data based following criteria. single exceedance Prioritize Investigate categories year ten year record result classification creek respective category unless least three years data threshold level category. Creeks assigned next lower category one AGM TN given level multiple years (.e., two) given levels defining cutoff points category. example, creek least 4 years data single exceedance Prioritize threshold assigned Investigate category. Outcomes exemplified .","code":"tidaltargets #> region prioritize investigate #> 1 West Central 1.65 1.38 #> 2 Peninsula 1.54 1.30 #> caution #> 1 1.38 - 0.0174 * (23.78 - (Creek_Length_m / 1000)) #> 2 1.30 - 0.0174 * (23.78 - (Creek_Length_m / 1000))"},{"path":"https://tbep-tech.github.io/tbeptools/articles/tidalcreeks.html","id":"report-card-functions","dir":"Articles","previous_headings":"Report card","what":"Report card functions","title":"Tidal Creek Assessment","text":"two primary functions tidal creek assessments anlz_tdlcrk() obtain scores show_tdlcrk() view interactive map results. anlz_tdlcrk() function uses included tidalcreeks() iwrraw() datasets estimate scores: results include unique creek identifier (id, based wbid JEI fields), waterbody id (wbid), creek ID (JEI), FDEP class (class), results assessment remaining columns. columns monitor, caution, investigate, prioritize indicate number years 2012 2021 nitrogen values within ranges appropriate creek type specified within tidaltargets(). score column indicates overall category assigned creek period record. Note many creeks assigned Data value sufficient data unavailable. summation four component columns (monitor, caution, investigate, prioritize) provides number years data available creek. show_tdlcrk() function can used output anlz_tdlcrk() view interactive map results. Creeks color-coded exceedance categories, “Data” creeks shown light blue. report card style matrix can plotted using show_tdlcrkmatrix() function shows overall creek score number years data used estimate overall score. plot shows matrix rows individual creeks columns overall creek score. columns show overall creek score number years prior ten years nitrogen values creek assigned four score categories. Number years mapped cell transparency. default, plot shows creeks marine WBID (water body identifier) designation 3M 2. can changed class argument (.e., class c('3M', '2', '3F', '1') marine freshwater WBIDs).","code":"results <- anlz_tdlcrk(tidalcreeks, iwrraw) results #> # A tibble: 615 × 10 #> id wbid JEI name class monitor caution investigate prioritize score #> #> 1 1 1983B CC01 Rock Cr… 2 NA NA NA NA No D… #> 2 2 2052 CC01 Rock Cr… 3M 10 NA NA NA Moni… #> 3 3 1983B CC02 Oyster … 2 NA NA NA NA No D… #> 4 4 2067 CC02 Oyster … 3M 10 NA NA NA Moni… #> 5 5 1983B CC03 Buck Cr… 2 NA NA NA NA No D… #> 6 6 2068 CC03 Buck Cr… 3M 9 1 NA NA Moni… #> 7 7 2078A CC04 Buck Cr… 2 NA NA 1 NA Inve… #> 8 8 2078A CC05 Coral C… 2 NA NA NA NA No D… #> 9 9 2078B CC05 Coral C… 2 4 1 NA NA Moni… #> 10 10 2065C CC06 Catfish… 2 NA NA NA NA No D… #> # ℹ 605 more rows show_tdlcrk(results) show_tdlcrkmatrix(results)"},{"path":"https://tbep-tech.github.io/tbeptools/articles/tidalcreeks.html","id":"indicator-functions","dir":"Articles","previous_headings":"Report card","what":"Indicator functions","title":"Tidal Creek Assessment","text":"Water quality Indicators developed provide context interpreting report card outcomes described detail Wessel et al. 2021 include thresholds total nitrogen (>1.1 mg/l), chlorophyll (>11 ug/l), dissolved oxygen (< 42 % saturation), trophic state index score (>55), chlorophyll/nitrogen ratio (>15) ratio nitrates tidal freshwater portion creek (>1) (data available). results indicator relative established thresholds calculated annual basis synthesized 10 year period calculating percentage annual outcomes exceeding identified threshold indicator values total number years available data. integrative summary indicators presented using standardized polar coordinate system Radar Charts provide single multi-metric summary plot results across indicators. anlz_tdlcrkindic() function generates annual outcomes wbid/JEI combination. Individual creek indicators summarized using multivariate response plot called “radar plot” indicates percentage years indicator exceeded respective threshold value. plots created using radar = TRUE argument anlz_tdlcrkindic() function using results show_tdlcrkradar() function. radar plots apply marine WBIDs tidal creeks (Florida DEP class 2, 3M). Indicators without data creek point plot. General descriptive plots annual outcomes provided interactive plotly graphics using show_tdlcrkindic() show_tdlcrkindiccdf() functions. show_tdlcrindic() function produces bar plots annual outcomes selected creek. creek plot selected id argument integer used filter results anlz_tdlcrkindic() function, latter passed cntdat argument. thrsel argument plots dotted red lines based threshold values. year unique color. show_tdlcrkindiccdf() function similar except empirical cumulative distribution functions (CDF) plotted evaluate outcomes specific creek relative entire distribution creeks southwest Florida. indicator year selected creek plotted CDF curves. Location points indicate comparison population trajectory indicators time (.e., brown older observations blue recent). Holding mouse cursor point shows year holding cursor line shows percentile value CDF.","code":"results <- anlz_tdlcrkindic(tidalcreeks, iwrraw) head(results) #> id name JEI wbid class year CHLAC COLOR COND DO DOSAT #> 1 2 Rock Creek CC01 2052 3M 2014 2.380249 14.69473 NA 3.308289 60.31523 #> 2 2 Rock Creek CC01 2052 3M 2015 2.647817 21.91113 NA 4.034172 55.41609 #> 3 2 Rock Creek CC01 2052 3M 2016 2.265462 19.13080 NA 3.980251 55.96637 #> 4 2 Rock Creek CC01 2052 3M 2017 2.851726 15.39576 NA 4.157777 60.18017 #> 5 2 Rock Creek CC01 2052 3M 2018 1.934899 11.65500 NA 4.219790 63.32630 #> 6 2 Rock Creek CC01 2052 3M 2019 2.071003 7.21425 NA 3.015847 44.90322 #> NO23 ORGN SALIN TKN TN TP TSS TURB #> 1 0.007575792 NA 26.63714 0.6161702 0.6228782 0.06938150 NA 2.044623 #> 2 0.009361504 NA 19.10494 0.6465161 0.5678241 0.07602770 NA 1.814818 #> 3 0.008532522 NA 25.84531 0.5813818 0.5408161 0.08330509 NA 2.082253 #> 4 0.007447260 NA 24.86909 0.6255197 0.6326848 0.07566682 NA 1.802161 #> 5 0.006994714 NA 31.32419 0.5668727 0.5734574 0.07432007 NA 2.454007 #> 6 0.007047106 NA 31.63214 0.5053022 0.4577485 0.06300538 NA 1.831953 #> chla_tn_ratio tn_tp_ratio chla_tsi tn_tsi tn2_tsi tp_tsi tp2_tsi #> 1 3.821371 8.977584 29.28775 46.62660 49.42526 60.45694 76.25504 #> 2 4.663093 7.468648 30.82179 44.79432 47.43600 62.15842 78.41391 #> 3 4.188970 6.491994 28.57601 43.82942 46.38844 63.85868 80.57123 #> 4 4.507341 8.361456 31.89011 46.93590 49.76107 62.06992 78.30162 #> 5 3.374095 7.716050 26.30480 44.98978 47.64821 61.73589 77.87779 #> 6 4.524324 7.265229 27.28367 40.52758 42.80384 58.66389 73.97999 #> nut_tsi tsi no23_source no23_tidal no23_ratio do_bnml do_prop #> 1 49.42526 39.35651 NA NA NA 0 1 #> 2 47.43600 39.12890 NA NA NA 0 1 #> 3 46.38844 37.48223 NA NA NA 0 1 #> 4 49.76107 40.82559 NA NA NA 0 0 #> 5 47.64821 36.97650 NA NA NA 0 1 #> 6 42.80384 35.04375 NA NA NA 1 1 cntdat <- anlz_tdlcrkindic(tidalcreeks, iwrraw, yr = 2023, radar = T) # get random creek id set.seed(123) id <- sample(unique(cntdat$id), 1) show_tdlcrkradar(id = id, cntdat = cntdat) cntdat <- anlz_tdlcrkindic(tidalcreeks, iwrraw, yr = 2023) show_tdlcrkindic(id = id, cntdat = cntdat, thrsel = TRUE) show_tdlcrkindiccdf(id = id, cntdat = cntdat, thrsel = TRUE)"},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/authors.html","id":null,"dir":"","previous_headings":"","what":"Authors","title":"Authors and Citation","text":"Marcus Beck. Author, maintainer. Meagan Schrandt. Author. Mike Wessel. Author. Ed Sherwood. Author. Gary Raulerson. Author. Adhokshaja Achar Budihal Prasad. Author. Benjamin Best. Author.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/authors.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Authors and Citation","text":"Beck, M.W., Schrandt, M.N., Wessel, M.R., Sherwood, E.T., Raulerson, G.E., Budihal Prasad, .., Best, B.D., (2021). tbeptools: R package synthesizing estuarine data environmental research. Journal Open Source Software, 6(65), 3485, https://doi.org/10.21105/joss.03485","code":"@Article{, title = {{t}beptools: An {R} package for synthesizing estuarine data for environmental research}, author = {Marcus Beck and Meagan Schrandt and Mike Wessel and Ed Sherwood and Gary Raulerson and Adhokshaja Achar {Budihal Prasad} and Benjamin Best}, journal = {Journal of Open Source Software}, year = {2021}, volume = {6}, number = {65}, pages = {3485}, doi = {10.21105/joss.03485}, }"},{"path":"https://tbep-tech.github.io/tbeptools/index.html","id":"tbeptools","dir":"","previous_headings":"","what":"Data and Indicators for the Tampa Bay Estuary Program","title":"Data and Indicators for the Tampa Bay Estuary Program","text":"R package Tampa Bay Estuary Program functions. Please see vignettes full description.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/index.html","id":"installation","dir":"","previous_headings":"","what":"Installation","title":"Data and Indicators for the Tampa Bay Estuary Program","text":"package can installed r-universe. source code available tbep-tech GitHub group web page: https://github.com/tbep-tech/tbeptools. Note tbeptools needs installed , needs loaded every new R session (.e., library(tbeptools)). package loaded, can view help files function typing question mark followed function name, e.g., ?read_importwq, console. help files provide brief description function required arguments needed run function.","code":"# enable repos options(repos = c( tbeptech = 'https://tbep-tech.r-universe.dev', CRAN = 'https://cloud.r-project.org')) # install tbeptools install.packages('tbeptools') # load tbeptools library(tbeptools)"},{"path":"https://tbep-tech.github.io/tbeptools/index.html","id":"package-vignettes","dir":"","previous_headings":"","what":"Package vignettes","title":"Data and Indicators for the Tampa Bay Estuary Program","text":"vignettes organized topic excellent place start understanding use package. Currently, six vignettes available tbeptools: Water Quality Data: Overview functions working water quality data water quality report card Tampa Bay Nekton Index: Overview functions import, analyze, plot results Tampa Bay Nekton Index Tampa Bay Benthic Index: Overview functions import data Tampa Bay Benthic Index, development Tidal Creeks Assessment: Overview functions import, analyze, plot results assessment tidal creeks southwest Florida Seagrass Transect Data: Overview functions import, analyze, plot results seagrass transect data collected Tampa Bay Habitat Master Plan: Overview functions analyze create report card Tampa Bay Habitat Master Plan 2020 update Fecal Indicator Bacteria: Overview functions import, analyze, plot results Fecal Indicator Bacteria (FIB)","code":""},{"path":"https://tbep-tech.github.io/tbeptools/index.html","id":"usage","dir":"","previous_headings":"","what":"Usage","title":"Data and Indicators for the Tampa Bay Estuary Program","text":"core functions tbeptools three categories based mode use. function named using prefix mode use, followed function . prefixes : read: Import current data main site. anlz: Analyze summarize imported data. show: Create plot analyzed data. functions can easily found RStudio loading package typing prefix command line. autofill dialog box pop showing functions apply prefix. eliminates need searching individual functions know category function need (e.g., read, anlz, show). function also includes semi-descriptive suffix generally describes category applies (e.g, water quality, seagrass) (e.g., imports, formats). follow loose convention attempts strike balance description brevity. optimal balance often hard achieve. aid understanding, provide brief description suffixes used . Suffix descriptions: attain: Analyze functions summarize data relative attainment categories specific bay segments ave, med: Analyze functions summarize data averages medians benthic: Applies benthic monitoring data used Tampa Bay Benthic Index fim: Applies data Fisheries Independent Monitoring program used Tampa Bay Nekton Index form: intermediate function formatting imported data downstream analysis hmp: Functions work Habitat Master Plan data import: function used import data source external package indic: function analyzes plots individual tidal creek indicator values, opposed integrated creek scores iwr: Functions data apply Impaired Waters Rule (IWR) data maintained Florida Department Environmental Protection used source data tidal creek functions matrix: plotting function creates report card style matrix met: function analyses plots individual metrics integrated indices, e.g., TBBI, TBNI phyto: Applies phytoplankton data Hillsborough County Environmental Protection Commission plotly: plotting function returns interactive plotly object scr: function analyses plots summary scores integrated indices, e.g., TBBI, TBNI seg, site: Functions analyze plot results relative bay segments individual monitoring sites tbbi: Applies Tampa Bay Benthic Index (TBBI) tbni: Applies Tampa Bay Nekton Index (TBNI) tdlcrk: Applies tidal creeks transect: Applies seagrass transect data wq: Applies water quality function reference page can also viewed complete list functions organized category, description , links help files. following example demonstrates use subset functions water quality data read file Hillsborough County Environmental Protection Commission long-term monitoring dataset (available https://www.tampabay.wateratlas.usf.edu/), analyze monthly annual averages major bay segments Tampa Bay, plot annual time series one bay segments. Functions tbeptools also support creation content interactive, online dashboards can facilitate informed decisions without requiring intimate understanding R programming language methods analysis. dashboards include assessments water quality, seagrasses, nekton communities, tidal creeks.","code":"# load the package library(tbeptools) # read current data wqdat <- read_importwq(xlsx = \"wqdata.xlsx\", download_latest = TRUE) wqdat ## # A tibble: 26,611 x 22 ## bay_segment epchc_station SampleTime yr mo ## ## 1 HB 6 2021-06-08 10:59:00 2021 6 ## 2 HB 7 2021-06-08 11:13:00 2021 6 ## 3 HB 8 2021-06-08 14:15:00 2021 6 ## 4 MTB 9 2021-06-08 13:14:00 2021 6 ## 5 MTB 11 2021-06-08 11:30:00 2021 6 ## # ... with 26,606 more rows, and 17 more variables: ## # Latitude , Longitude , Total_Depth_m , ## # Sample_Depth_m , tn , tn_q , sd_m , ## # sd_raw_m , sd_q , chla , chla_q , ## # Sal_Top_ppth , Sal_Mid_ppth , ## # Sal_Bottom_ppth , Temp_Water_Top_degC , ## # Temp_Water_Mid_degC , ... # analyze monthly and annual means by bay segment avedat <- anlz_avedat(wqdat) avedat ## $ann ## # A tibble: 584 x 4 ## yr bay_segment var val ## ## 1 1974 HB mean_chla 22.4 ## 2 1974 LTB mean_chla 4.24 ## 3 1974 MTB mean_chla 9.66 ## 4 1974 OTB mean_chla 10.2 ## 5 1975 HB mean_chla 27.9 ## # ... with 579 more rows ## ## $mos ## # A tibble: 4,484 x 5 ## bay_segment yr mo var val ## ## 1 HB 1974 1 mean_chla 36.2 ## 2 LTB 1974 1 mean_chla 1.75 ## 3 MTB 1974 1 mean_chla 11.5 ## 4 OTB 1974 1 mean_chla 4.4 ## 5 HB 1974 2 mean_chla 42.4 ## # ... with 4,479 more rows # show annual time series of chlorophyll for Hillsborough bay segment show_thrplot(wqdat, bay_segment = \"HB\", yrrng = c(1975, 2020))"},{"path":"https://tbep-tech.github.io/tbeptools/index.html","id":"issues-and-suggestions","dir":"","previous_headings":"","what":"Issues and suggestions","title":"Data and Indicators for the Tampa Bay Estuary Program","text":"Please report issues suggestions issues link repository. guide posting issues can found .","code":""},{"path":"https://tbep-tech.github.io/tbeptools/index.html","id":"contributing","dir":"","previous_headings":"","what":"Contributing","title":"Data and Indicators for the Tampa Bay Estuary Program","text":"Please view contributing guidelines changes pull requests.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/acres.html","id":null,"dir":"Reference","previous_headings":"","what":"Tampa Bay intertidal and supratidal land use and cover — acres","title":"Tampa Bay intertidal and supratidal land use and cover — acres","text":"Tampa Bay intertidal supratidal land use cover Habitat Master Plan reporting","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/acres.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tampa Bay intertidal and supratidal land use and cover — acres","text":"","code":"acres"},{"path":"https://tbep-tech.github.io/tbeptools/reference/acres.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Tampa Bay intertidal and supratidal land use and cover — acres","text":"data frame","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/acres.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tampa Bay intertidal and supratidal land use and cover — acres","text":"","code":"if (FALSE) { load(url(\"https://github.com/tbep-tech/hmpu-workflow/raw/master/data/acres.RData\")) save(acres, file = 'data/acres.RData', compress = 'xz') }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_attain.html","id":null,"dir":"Reference","previous_headings":"","what":"Get attainment categories — anlz_attain","title":"Get attainment categories — anlz_attain","text":"Get attainment categories year bay segment using chlorophyll light attenuation","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_attain.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get attainment categories — anlz_attain","text":"","code":"anlz_attain(avedat, magdurout = FALSE, trgs = NULL)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_attain.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get attainment categories — anlz_attain","text":"avedat result returned anlz_avedat magdurout logical indicating separate magnitude duration estimates returned trgs optional data.frame annual bay segment water quality targets, defaults targets","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_attain.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get attainment categories — anlz_attain","text":"data.frame year bay segment showing attainment category","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_attain.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get attainment categories — anlz_attain","text":"","code":"avedat <- anlz_avedat(epcdata) anlz_attain(avedat) #> # A tibble: 200 × 4 #> bay_segment yr chl_la outcome #> #> 1 HB 1974 3_0 yellow #> 2 HB 1975 3_2 red #> 3 HB 1976 3_2 red #> 4 HB 1977 3_2 red #> 5 HB 1978 3_3 red #> 6 HB 1979 3_3 red #> 7 HB 1980 3_3 red #> 8 HB 1981 3_3 red #> 9 HB 1982 3_3 red #> 10 HB 1983 3_0 yellow #> # ℹ 190 more rows"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_attainsite.html","id":null,"dir":"Reference","previous_headings":"","what":"Get site attainments — anlz_attainsite","title":"Get site attainments — anlz_attainsite","text":"Get site attainment categories chlorophyll light attenuation","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_attainsite.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get site attainments — anlz_attainsite","text":"","code":"anlz_attainsite( avedatsite, thr = c(\"chla\", \"la\"), trgs = NULL, yrrng = NULL, thrs = FALSE )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_attainsite.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get site attainments — anlz_attainsite","text":"avedatsite result returned anlz_avedatsite thr chr string indicating water quality value appropriate threshold plot, one \"chl\" chlorophyll \"la\" light availability trgs optional data.frame annual bay segment water quality targets, defaults targets yrrng optional numeric value year return, defaults thrs logical indicating attainment category relative targets (default) thresholds","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_attainsite.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get site attainments — anlz_attainsite","text":"data.frame year site showing attainment category","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_attainsite.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Get site attainments — anlz_attainsite","text":"function simplication attainment categories returned anlz_attain. Sites compared targets/thresholds apply separately chlorophyll light attenuation.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_attainsite.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get site attainments — anlz_attainsite","text":"","code":"avedatsite <- anlz_avedatsite(epcdata) anlz_attainsite(avedatsite) #> # A tibble: 2,250 × 9 #> yr bay_segment epchc_station var val target smallex thresh met #> #> 1 1974 HB 6 chla 25.6 13.2 14.1 15 no #> 2 1974 HB 7 chla 21.6 13.2 14.1 15 no #> 3 1974 HB 8 chla 22.6 13.2 14.1 15 no #> 4 1974 HB 44 chla 23.4 13.2 14.1 15 no #> 5 1974 HB 52 chla 23.5 13.2 14.1 15 no #> 6 1974 HB 55 chla 20.2 13.2 14.1 15 no #> 7 1974 HB 70 chla 33.1 13.2 14.1 15 no #> 8 1974 HB 71 chla 25.8 13.2 14.1 15 no #> 9 1974 HB 73 chla 17.6 13.2 14.1 15 no #> 10 1974 HB 80 chla 10.5 13.2 14.1 15 yes #> # ℹ 2,240 more rows"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_avedat.html","id":null,"dir":"Reference","previous_headings":"","what":"Estimate annual means — anlz_avedat","title":"Estimate annual means — anlz_avedat","text":"Estimate annual means chlorophyll secchi data","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_avedat.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Estimate annual means — anlz_avedat","text":"","code":"anlz_avedat(epcdata, partialyr = FALSE)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_avedat.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Estimate annual means — anlz_avedat","text":"epcdata data.frame formatted read_importwq partialyr logical indicating incomplete annual data recent year approximated five year monthly averages parameter","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_avedat.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Estimate annual means — anlz_avedat","text":"Mean estimates chlorophyll secchi","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_avedat.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Estimate annual means — anlz_avedat","text":"","code":"# view average estimates anlz_avedat(epcdata) #> $ann #> # A tibble: 608 × 4 #> yr bay_segment var val #> #> 1 1974 HB mean_chla 22.4 #> 2 1974 LTB mean_chla 4.24 #> 3 1974 MTB mean_chla 9.66 #> 4 1974 OTB mean_chla 10.2 #> 5 1975 HB mean_chla 27.9 #> 6 1975 LTB mean_chla 4.93 #> 7 1975 MTB mean_chla 11.4 #> 8 1975 OTB mean_chla 13.2 #> 9 1976 HB mean_chla 29.5 #> 10 1976 LTB mean_chla 5.08 #> # ℹ 598 more rows #> #> $mos #> # A tibble: 4,724 × 5 #> bay_segment yr mo var val #> #> 1 HB 1974 1 mean_chla 36.2 #> 2 LTB 1974 1 mean_chla 1.75 #> 3 MTB 1974 1 mean_chla 11.5 #> 4 OTB 1974 1 mean_chla 4.4 #> 5 HB 1974 2 mean_chla 42.4 #> 6 LTB 1974 2 mean_chla 5.5 #> 7 MTB 1974 2 mean_chla 9.35 #> 8 OTB 1974 2 mean_chla 4.07 #> 9 HB 1974 3 mean_chla 14.9 #> 10 LTB 1974 3 mean_chla 5.88 #> # ℹ 4,714 more rows #>"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_avedatsite.html","id":null,"dir":"Reference","previous_headings":"","what":"Estimate annual means by site — anlz_avedatsite","title":"Estimate annual means by site — anlz_avedatsite","text":"Estimate annual means site chlorophyll secchi data","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_avedatsite.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Estimate annual means by site — anlz_avedatsite","text":"","code":"anlz_avedatsite(epcdata, partialyr = FALSE)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_avedatsite.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Estimate annual means by site — anlz_avedatsite","text":"epcdata data.frame formatted read_importwq partialyr logical indicating incomplete annual data recent year approximated five year monthly averages parameter","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_avedatsite.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Estimate annual means by site — anlz_avedatsite","text":"Mean estimates chlorophyll secchi","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_avedatsite.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Estimate annual means by site — anlz_avedatsite","text":"","code":"# view average estimates anlz_avedatsite(epcdata) #> $ann #> # A tibble: 6,838 × 5 #> yr bay_segment epchc_station var val #> #> 1 1974 HB 6 mean_chla 25.6 #> 2 1974 HB 7 mean_chla 21.6 #> 3 1974 HB 8 mean_chla 22.6 #> 4 1974 HB 44 mean_chla 23.4 #> 5 1974 HB 52 mean_chla 23.5 #> 6 1974 HB 55 mean_chla 20.2 #> 7 1974 HB 70 mean_chla 33.1 #> 8 1974 HB 71 mean_chla 25.8 #> 9 1974 HB 73 mean_chla 17.6 #> 10 1974 HB 80 mean_chla 10.5 #> # ℹ 6,828 more rows #> #> $mos #> # A tibble: 48,727 × 6 #> bay_segment epchc_station yr mo var val #> #> 1 HB 6 1974 1 mean_chla 53 #> 2 HB 7 1974 1 mean_chla 19 #> 3 HB 8 1974 1 mean_chla 46 #> 4 HB 44 1974 1 mean_chla 24 #> 5 HB 52 1974 1 mean_chla 28 #> 6 HB 55 1974 1 mean_chla 33 #> 7 HB 70 1974 1 mean_chla 58 #> 8 HB 71 1974 1 mean_chla 73 #> 9 HB 73 1974 1 mean_chla 17 #> 10 HB 80 1974 1 mean_chla 11 #> # ℹ 48,717 more rows #>"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_fibmap.html","id":null,"dir":"Reference","previous_headings":"","what":"Assign threshold categories to Fecal Indicator Bacteria (FIB) data — anlz_fibmap","title":"Assign threshold categories to Fecal Indicator Bacteria (FIB) data — anlz_fibmap","text":"Assign threshold categories Fecal Indicator Bacteria (FIB) data","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_fibmap.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Assign threshold categories to Fecal Indicator Bacteria (FIB) data — anlz_fibmap","text":"","code":"anlz_fibmap(fibdata, yrsel = NULL, mosel = NULL, areasel = NULL)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_fibmap.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Assign threshold categories to Fecal Indicator Bacteria (FIB) data — anlz_fibmap","text":"fibdata input FIB data.frame returned read_importfib yrsel optional numeric value filter output years fibdata mosel optional numeric value filter output month fibdata areasel optional character string filter output stations area column fibdata, see details","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_fibmap.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Assign threshold categories to Fecal Indicator Bacteria (FIB) data — anlz_fibmap","text":"data.frame similar fibdata additional columns describing station categories optionally filtered arguments passed function","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_fibmap.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Assign threshold categories to Fecal Indicator Bacteria (FIB) data — anlz_fibmap","text":"function used create FIB categories mapping using show_fibmap. Categories based relevant thresholds assigned observation. categories specific E. coli Enterococcus assigned based station class freshwater (class 1 3F) marine (class 2 3M), respectively. station categorized one four ranges defined thresholds noted cat column output, corresponding colors appropriate range noted col column output. areasel argument can indicate valid entries area column fibdata. example, use either \"Alafia River\" \"Hillsborough River\" corresponding river basins, rows fibdata filtered based selection. stations returned argument set NULL (default). Alafia River basin includes values area column fibdata \"Alafia River\" \"Alafia River Tributary\". Hillsborough River basin includes values area column fibdat \"Hillsborough River\", \"Hillsborough River Tributary\", \"Lake Thonotosassa\", \"Lake Thonotosassa Tributary\", \"Lake Roberta\". areas may present based selection. valid options areasel include \"Alafia River\", \"Hillsborough River\", \"Big Bend\", \"Cockroach Bay\", \"East Lake Outfall\", \"Hillsborough Bay\", \"Little Manatee\", \"Lower Tampa Bay\", \"McKay Bay\", \"Middle Tampa Bay\", \"Old Tampa Bay\", \"Palm River\", \"Tampa Bypass Canal\", \"Valrico Lake\".","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_fibmap.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Assign threshold categories to Fecal Indicator Bacteria (FIB) data — anlz_fibmap","text":"","code":"# assign categories to all anlz_fibmap(fibdata) #> # A tibble: 76,502 × 12 #> area epchc_station class yr mo Latitude Longitude ecoli ecocci ind #> #> 1 Hillsb… 2 3M 2024 1 27.9 -82.5 NA 24 Ente… #> 2 Hillsb… 6 3M 2024 1 27.9 -82.5 NA 2 Ente… #> 3 Hillsb… 7 3M 2024 1 27.9 -82.5 NA 2 Ente… #> 4 Hillsb… 8 3M 2024 1 27.9 -82.4 NA 10 Ente… #> 5 Middle… 9 2 2024 1 27.8 -82.4 NA 2 Ente… #> 6 Middle… 11 2 2024 1 27.8 -82.5 NA 2 Ente… #> 7 Middle… 13 2 2024 1 27.8 -82.5 NA 2 Ente… #> 8 Middle… 14 2 2024 1 27.8 -82.5 NA 2 Ente… #> 9 Middle… 16 2 2024 1 27.7 -82.5 NA 2 Ente… #> 10 Middle… 19 2 2024 1 27.7 -82.6 NA 2 Ente… #> # ℹ 76,492 more rows #> # ℹ 2 more variables: cat , col # filter by year, month, and area anlz_fibmap(fibdata, yrsel = 2020, mosel = 7, areasel = 'Alafia River') #> # A tibble: 24 × 12 #> area epchc_station class yr mo Latitude Longitude ecoli ecocci ind #> #> 1 Alafia… 74 3M 2020 7 27.9 -82.4 NA 168 Ente… #> 2 Alafia… 111 3F 2020 7 27.9 -82.2 50 7000 E. c… #> 3 Alafia… 114 3F 2020 7 27.9 -82.3 447 1560 E. c… #> 4 Alafia… 115 3F 2020 7 27.9 -82.1 80 260 E. c… #> 5 Alafia… 116 3F 2020 7 27.9 -82.1 30 367 E. c… #> 6 Alafia… 139 3F 2020 7 27.7 -82.1 47 100 E. c… #> 7 Alafia… 151 3F 2020 7 27.9 -82.2 90 25 E. c… #> 8 Alafia… 153 3M 2020 7 27.9 -82.3 NA 4000 Ente… #> 9 Alafia… 154 3F 2020 7 27.9 -82.1 433 1367 E. c… #> 10 Alafia… 155 3F 2020 7 27.9 -82.2 170 233 E. c… #> # ℹ 14 more rows #> # ℹ 2 more variables: cat , col "},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_fibmatrix.html","id":null,"dir":"Reference","previous_headings":"","what":"Analyze Fecal Indicator Bacteria categories over time by station — anlz_fibmatrix","title":"Analyze Fecal Indicator Bacteria categories over time by station — anlz_fibmatrix","text":"Analyze Fecal Indicator Bacteria categories time station","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_fibmatrix.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Analyze Fecal Indicator Bacteria categories over time by station — anlz_fibmatrix","text":"","code":"anlz_fibmatrix(fibdata, yrrng = NULL, stas = NULL, lagyr = 3)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_fibmatrix.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Analyze Fecal Indicator Bacteria categories over time by station — anlz_fibmatrix","text":"fibdata input data frame returned read_importfib yrrng numeric vector indicating min, max years include, defaults range years epcdata stas optional numeric vector stations include, see details lagyr numeric year lag calculate categories, see details","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_fibmatrix.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Analyze Fecal Indicator Bacteria categories over time by station — anlz_fibmatrix","text":"tibble object FIB summaries year station, including columns estimated geometric mean fecal coliform concentrations (gmean), proportions samples exceeding 400 CFU / 100 mL (exced), count samples (cnt), category indicating letter outcome based proportion exceedences (cat).","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_fibmatrix.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Analyze Fecal Indicator Bacteria categories over time by station — anlz_fibmatrix","text":"function used create output plotting matrix stoplight graphic FIB categories station year. station year combination categorized based likelihood fecal indicator bacteria concentrations exceeding 400 CFU / 100 mL given year (using Fecal Coliform, fcolif fibdata). proportions categorized , B, C, D, E (Microbial Water Quality Assessment MWQA categories) corresponding colors, breakpoints category <10%, 10-30%, 30-50%, 50-75%, >75% (right-closed). default, results year based right-centered window uses previous two years current year calculate probabilities using monthly samples (lagyr = 3). See show_fibmatrix additional details.","code":""},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_fibmatrix.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Analyze Fecal Indicator Bacteria categories over time by station — anlz_fibmatrix","text":"","code":"anlz_fibmatrix(fibdata) #> # A tibble: 8,800 × 4 #> yr epchc_station gmean cat #> #> 1 1985 2 52.4 B #> 2 1985 6 7.21 A #> 3 1985 7 4.64 A #> 4 1985 8 9.49 A #> 5 1985 9 6.32 A #> 6 1985 11 5.18 A #> 7 1985 13 4 A #> 8 1985 14 6.35 A #> 9 1985 16 4 A #> 10 1985 19 4 A #> # ℹ 8,790 more rows"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_hmpreport.html","id":null,"dir":"Reference","previous_headings":"","what":"Evaluate Habitat Master Plan progress for report card — anlz_hmpreport","title":"Evaluate Habitat Master Plan progress for report card — anlz_hmpreport","text":"Evaluate Habitat Master Plan progress report card","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_hmpreport.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Evaluate Habitat Master Plan progress for report card — anlz_hmpreport","text":"","code":"anlz_hmpreport(acres, subtacres, hmptrgs)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_hmpreport.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Evaluate Habitat Master Plan progress for report card — anlz_hmpreport","text":"acres data.frame intertidal supratidal land use cover habitat types year data subtacres data.frame subtidal cover habitat types year data hmptrgs data.frame Habitat Master Plan targets goals","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_hmpreport.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Evaluate Habitat Master Plan progress for report card — anlz_hmpreport","text":"summarized data.frame appropriate creating report card","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_hmpreport.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Evaluate Habitat Master Plan progress for report card — anlz_hmpreport","text":"relevant output columns targeteval goaleval indicate numeric values -1 (target met, trending ), 0 (target met, trending ), 0.5 (target met, trending ), 1 (target met, trending ). Columns output follows: year Year assessment metric Habitat type assessed Acres Coverage estimate year lacres Coverage estimate previous set available data lyr Year previous set available data category Strata habitat type Target 2030 target habitat type Habitat Master Plan Goal 2050 goal habitat type Habitat Master Plan acresdiff Difference acres current year previous set available data yeardiff Difference years current year previous set available data changerate Acreage change per year current year relative previous set available data targetrate Annual rate required achieve 2030 target goalrate Annual rate required achieve 2050 goal targetprop Proportion target met current year goalprop Proportion goal met current year targeteval number indicating target status current year report card goaleval number indicating goal status current year report card numbers targeteval goaleval one four values -1, 0, 0.5, 1. numbers define status assessment year: -1 target goal met, trending 0 target goal met, trending 0.5 target goal met, trending 1 target goal met, trending ","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_hmpreport.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Evaluate Habitat Master Plan progress for report card — anlz_hmpreport","text":"","code":"# view summarized data for report card anlz_hmpreport(acres, subtacres, hmptrgs) #> # A tibble: 150 × 17 #> year metric Acres lacres lyr category Target Goal acresdiff yeardiff #> #> 1 1990 Seagrasses 25218. 23279. 1988 Subtidal 40000 40000 1939. 2 #> 2 1990 Tidal Fla… 20433. 21686. 1988 Subtidal 16220 16220 -1253. 2 #> 3 1992 Seagrasses 25746. 25218. 1990 Subtidal 40000 40000 528. 2 #> 4 1992 Tidal Fla… 20594. 20433. 1990 Subtidal 16220 16220 161. 2 #> 5 1994 Seagrasses 26524. 25746. 1992 Subtidal 40000 40000 778. 2 #> 6 1994 Tidal Fla… 20244. 20594. 1992 Subtidal 16220 16220 -349. 2 #> 7 1996 Seagrasses 26924. 26524. 1994 Subtidal 40000 40000 400. 2 #> 8 1996 Tidal Fla… 20443. 20244. 1994 Subtidal 16220 16220 199. 2 #> 9 1999 Seagrasses 24840. 26924. 1996 Subtidal 40000 40000 -2083. 3 #> 10 1999 Tidal Fla… 27085. 20443. 1996 Subtidal 16220 16220 6642. 3 #> # ℹ 140 more rows #> # ℹ 7 more variables: changerate , targetrate , goalrate , #> # targetprop , goalprop , targeteval , goaleval "},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_hydroload.html","id":null,"dir":"Reference","previous_headings":"","what":"Estimate hydrological estimates and adjustment factors for bay segments — anlz_hydroload","title":"Estimate hydrological estimates and adjustment factors for bay segments — anlz_hydroload","text":"Estimate hydrological estimates adjustment factors bay segments","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_hydroload.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Estimate hydrological estimates and adjustment factors for bay segments — anlz_hydroload","text":"","code":"anlz_hydroload(yrs, noaa_key = NULL, trace = FALSE)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_hydroload.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Estimate hydrological estimates and adjustment factors for bay segments — anlz_hydroload","text":"yrs numeric vector indicating years return noaa_key user-supplied NOAA key, see details trace logical indicating function progress printed consol","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_hydroload.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Estimate hydrological estimates and adjustment factors for bay segments — anlz_hydroload","text":"data frame hydrological load estimates bay segments requested years","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_hydroload.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Estimate hydrological estimates and adjustment factors for bay segments — anlz_hydroload","text":"function uses rainfall streamflow data NOAA USGS requires API key. See \"Authentication\" section help file ncdc defunct rnoaa package. key can added R environment file called later use, see examples. estimates used annual compliance assessment reports produced Tampa Bay Nitrogen Management Consortium. Load estimates adjustment factors based regression models https://drive.google.com/file/d/11NT0NQ2WbPO6pVZaD7P7Z6qjcwO1jxHw/view?usp=drivesdk","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_hydroload.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Estimate hydrological estimates and adjustment factors for bay segments — anlz_hydroload","text":"","code":"if (FALSE) { # this function requires an API key # save it to the R environment file (only once) # save the key, do only once cat(\"NOAA_KEY=XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX\\n\", file=file.path(normalizePath(\"~/\"), \".Renviron\"), append=TRUE) # retrieve the key after saving, may need to restart R noaa_key <- Sys.getenv('NOAA_key') # get estimates for 2021 anlz_hydroload(2021, noaa_key) }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_iwrraw.html","id":null,"dir":"Reference","previous_headings":"","what":"Format raw IWR data — anlz_iwrraw","title":"Format raw IWR data — anlz_iwrraw","text":"Format raw IWR data","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_iwrraw.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Format raw IWR data — anlz_iwrraw","text":"","code":"anlz_iwrraw(iwrraw, tidalcreeks, yr = 2023)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_iwrraw.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Format raw IWR data — anlz_iwrraw","text":"iwrraw FDEP impaired waters rule data base data.frame tidalcreeks sf object population tidal creeks yr numeric reference year evaluate, scores based ten years data using yr last year","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_iwrraw.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Format raw IWR data — anlz_iwrraw","text":"data.frame formatted data","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_iwrraw.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Format raw IWR data — anlz_iwrraw","text":"function subsets raw IWR data ten years starting value yr subsets creek population tidalcreeks. Select water quality parameters masterCode filtered names combined continuity.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_iwrraw.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Format raw IWR data — anlz_iwrraw","text":"","code":"anlz_iwrraw(iwrraw, tidalcreeks, yr = 2023) #> wbid class JEI year date masterCode result rCode #> 1 2052 3M CC01 2014 2014-03-03 CHLAC 0.5877866649 #> 2 2052 3M CC01 2014 2014-03-03 COLOR 0.9162907319 U #> 3 2052 3M CC01 2014 2014-03-03 DOSAT 4.1835756960 + #> 4 2052 3M CC01 2014 2014-03-03 NO23 -5.5214609179 U #> 5 2052 3M CC01 2014 2014-03-03 SALIN 3.5292973843 #> 6 2052 3M CC01 2014 2014-03-03 TKN -0.6733445533 #> 7 2052 3M CC01 2014 2014-03-03 TN -0.6694306539 + #> 8 2052 3M CC01 2014 2014-03-03 TP -2.7968814148 #> 9 2052 3M CC01 2014 2014-03-03 TURB 1.2527629685 #> 10 2052 3M CC01 2014 2014-04-07 CHLAC 0.2623642645 I #> 11 2052 3M CC01 2014 2014-04-07 COLOR 0.9162907319 U #> 12 2052 3M CC01 2014 2014-04-07 DO 1.3862943611 #> 13 2052 3M CC01 2014 2014-04-07 DOSAT 4.0656020934 + #> 14 2052 3M CC01 2014 2014-04-07 NO23 -5.2983173665 I #> 15 2052 3M CC01 2014 2014-04-07 SALIN 3.5582011305 #> 16 2052 3M CC01 2014 2014-04-07 TKN -0.6733445533 #> 17 2052 3M CC01 2014 2014-04-07 TN -0.6655320135 + #> 18 2052 3M CC01 2014 2014-04-07 TP -2.6882475738 #> 19 2052 3M CC01 2014 2014-04-07 TURB 0.7884573604 #> 20 2052 3M CC01 2014 2014-05-05 CHLAC 0.8754687374 #> 21 2052 3M CC01 2014 2014-05-05 COLOR 3.4011973817 #> 22 2052 3M CC01 2014 2014-05-05 DO 1.5040773968 #> 23 2052 3M CC01 2014 2014-05-05 DOSAT 4.1399550735 + #> 24 2052 3M CC01 2014 2014-05-05 NO23 -4.7105307016 I #> 25 2052 3M CC01 2014 2014-05-05 SALIN 3.3032169733 #> 26 2052 3M CC01 2014 2014-05-05 TKN -0.3856624808 #> 27 2052 3M CC01 2014 2014-05-05 TN -0.3797973614 + #> 28 2052 3M CC01 2014 2014-05-05 TP -2.2072749132 #> 29 2052 3M CC01 2014 2014-05-05 TURB 1.2237754316 A #> 30 2052 3M CC01 2014 2014-06-02 CHLAC 0.8754687374 #> 31 2052 3M CC01 2014 2014-06-02 COLOR 2.7080502011 #> 32 2052 3M CC01 2014 2014-06-02 DO 0.9555114450 #> 33 2052 3M CC01 2014 2014-06-02 DOSAT 3.6635616461 + #> 34 2052 3M CC01 2014 2014-06-02 NO23 -4.9618451299 I #> 35 2052 3M CC01 2014 2014-06-02 SALIN 3.4719664526 #> 36 2052 3M CC01 2014 2014-06-02 TKN -0.6348782724 #> 37 2052 3M CC01 2014 2014-06-02 TN -0.6273594400 + #> 38 2052 3M CC01 2014 2014-06-02 TP -2.6592600369 #> 39 2052 3M CC01 2014 2014-06-02 TURB 0.7419373447 #> 40 2052 3M CC01 2014 2014-07-07 CHLAC 1.0986122887 #> 41 2052 3M CC01 2014 2014-07-07 COLOR 2.2512917986 #> 42 2052 3M CC01 2014 2014-07-07 DO 1.4350845253 #> 43 2052 3M CC01 2014 2014-07-07 NO23 -5.5214609179 U #> 44 2052 3M CC01 2014 2014-07-07 TKN -0.5621189182 #> 45 2052 3M CC01 2014 2014-07-07 TN -0.5586162876 + #> 46 2052 3M CC01 2014 2014-07-07 TP -2.9565115604 #> 47 2052 3M CC01 2014 2014-07-07 TURB 1.0986122887 #> 48 2052 3M CC01 2014 2014-08-04 CHLAC 1.0296194172 #> 49 2052 3M CC01 2014 2014-08-04 COLOR 2.3025850930 #> 50 2052 3M CC01 2014 2014-08-04 DO 1.0647107370 #> 51 2052 3M CC01 2014 2014-08-04 DOSAT 3.8543938926 + #> 52 2052 3M CC01 2014 2014-08-04 NO23 -5.5214609179 U #> 53 2052 3M CC01 2014 2014-08-04 SALIN 3.5292973843 #> 54 2052 3M CC01 2014 2014-08-04 TN -0.4748151862 + #> 55 2052 3M CC01 2014 2014-08-04 TURB 0.5877866649 #> 56 2052 3M CC01 2014 2014-09-08 CHLAC 1.4350845253 #> 57 2052 3M CC01 2014 2014-09-08 COLOR 2.8332133441 #> 58 2052 3M CC01 2014 2014-09-08 DO 0.8329091229 #> 59 2052 3M CC01 2014 2014-09-08 DOSAT 3.5779478934 + #> 60 2052 3M CC01 2014 2014-09-08 NO23 -4.7105307016 I #> 61 2052 3M CC01 2014 2014-09-08 SALIN 3.4965075615 #> 62 2052 3M CC01 2014 2014-09-08 TKN -0.3424903089 #> 63 2052 3M CC01 2014 2014-09-08 TN -0.3368723166 + #> 64 2052 3M CC01 2014 2014-09-08 TP -2.7030626596 #> 65 2052 3M CC01 2014 2014-09-08 TURB 0.4700036292 #> 66 2052 3M CC01 2014 2014-10-06 CHLAC 1.1314021115 #> 67 2052 3M CC01 2014 2014-10-06 COLOR 5.2470240722 #> 68 2052 3M CC01 2014 2014-10-06 DOSAT 4.1141471895 + #> 69 2052 3M CC01 2014 2014-10-06 NO23 -3.8167128256 #> 70 2052 3M CC01 2014 2014-10-06 SALIN 2.0918640617 #> 71 2052 3M CC01 2014 2014-10-06 TKN 0.0953101798 #> 72 2052 3M CC01 2014 2014-10-06 TN 0.1151128071 + #> 73 2052 3M CC01 2014 2014-10-06 TP -2.3025850930 #> 74 2052 3M CC01 2014 2014-10-06 TURB 0.3364722366 #> 75 2052 3M CC01 2014 2014-11-03 CHLAC 0.7884573604 A #> 76 2052 3M CC01 2014 2014-11-03 COLOR 3.5263605246 A #> 77 2052 3M CC01 2014 2014-11-03 DOSAT 4.8698394841 + #> 78 2052 3M CC01 2014 2014-11-03 NO23 -4.4228486292 #> 79 2052 3M CC01 2014 2014-11-03 SALIN 3.2425923515 #> 80 2052 3M CC01 2014 2014-11-03 TKN -0.5276327421 #> 81 2052 3M CC01 2014 2014-11-03 TN -0.5074978337 + #> 82 2052 3M CC01 2014 2014-11-03 TP -2.7806208939 #> 83 2052 3M CC01 2014 2014-11-03 TURB 0.1823215568 #> 84 2052 3M CC01 2014 2014-12-01 CHLAC 0.5877866649 #> 85 2052 3M CC01 2014 2014-12-01 COLOR 2.7725887222 A #> 86 2052 3M CC01 2014 2014-12-01 DOSAT 4.4272389775 + #> 87 2052 3M CC01 2014 2014-12-01 NO23 -4.3428059215 #> 88 2052 3M CC01 2014 2014-12-01 SALIN 3.3178157727 #> 89 2052 3M CC01 2014 2014-12-01 TKN -0.6539264674 #> 90 2052 3M CC01 2014 2014-12-01 TN -0.6292338548 + #> 91 2052 3M CC01 2014 2014-12-01 TP -2.9187712324 #> 92 2052 3M CC01 2014 2014-12-01 TURB 0.4700036292 #> 93 2052 3M CC01 2015 2015-01-05 CHLAC 0.9932517730 #> 94 2052 3M CC01 2015 2015-01-05 COLOR 1.8405496334 #> 95 2052 3M CC01 2015 2015-01-05 DO 1.5260563035 #> 96 2052 3M CC01 2015 2015-01-05 DOSAT 4.1835756960 + #> 97 2052 3M CC01 2015 2015-01-05 NO23 -4.9618451299 I #> 98 2052 3M CC01 2015 2015-01-05 SALIN 3.5438536821 #> 99 2052 3M CC01 2015 2015-01-05 TKN -0.8675005677 #> 100 2052 3M CC01 2015 2015-01-05 TN -0.8580218238 + #> 101 2052 3M CC01 2015 2015-01-05 TP -2.6310891600 #> 102 2052 3M CC01 2015 2015-01-05 TURB 0.7419373447 #> 103 2052 3M CC01 2015 2015-02-02 CHLAC 0.4700036292 I #> 104 2052 3M CC01 2015 2015-02-02 COLOR 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#> 433 2052 3M CC01 2019 2019-03-04 TP -2.6172958378 #> 434 2052 3M CC01 2019 2019-03-04 TURB 0.4700036292 #> 435 2052 3M CC01 2019 2019-04-01 CHLAC 0.9162907319 #> 436 2052 3M CC01 2019 2019-04-01 COLOR 2.0014800002 #> 437 2052 3M CC01 2019 2019-04-01 DO 1.4883995841 #> 438 2052 3M CC01 2019 2019-04-01 DOSAT 4.1620032107 #> 439 2052 3M CC01 2019 2019-04-01 NO23 -5.5214609179 I #> 440 2052 3M CC01 2019 2019-04-01 SALIN 3.4094961845 #> 441 2052 3M CC01 2019 2019-04-01 TKN -0.9162907319 I #> 442 2052 3M CC01 2019 2019-04-01 TN -1.8078888512 + #> 443 2052 3M CC01 2019 2019-04-01 TP -2.5510464523 #> 444 2052 3M CC01 2019 2019-04-01 TURB 0.2623642645 #> 445 2052 3M CC01 2019 2019-06-03 CHLAC 0.4700036292 I #> 446 2052 3M CC01 2019 2019-06-03 COLOR 1.4586150227 I #> 447 2052 3M CC01 2019 2019-06-03 DO 0.3001045925 #> 448 2052 3M CC01 2019 2019-06-03 DOSAT 3.1267605360 #> 449 2052 3M CC01 2019 2019-06-03 NO23 -5.5214609179 I #> 450 2052 3M CC01 2019 2019-06-03 SALIN 3.5871235452 #> 451 2052 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3.5234150144 #> 961 2067 3M CC02 2017 2017-02-06 TKN -0.5108256238 #> 962 2067 3M CC02 2017 2017-02-06 TN -0.4861330112 + #> 963 2067 3M CC02 2017 2017-02-06 TP -2.5383074265 #> 964 2067 3M CC02 2017 2017-02-06 TURB 0.9162907319 #> 965 2067 3M CC02 2017 2017-03-06 CHLAC 0.2623642645 I #> 966 2067 3M CC02 2017 2017-03-06 COLOR 2.7080502011 #> 967 2067 3M CC02 2017 2017-03-06 DO 1.3862943611 #> 968 2067 3M CC02 2017 2017-03-06 DOSAT 3.9778107460 + #> 969 2067 3M CC02 2017 2017-03-06 NO23 -4.9618451299 I #> 970 2067 3M CC02 2017 2017-03-06 SALIN 3.5174978374 #> 971 2067 3M CC02 2017 2017-03-06 TKN -0.5798184953 #> 972 2067 3M CC02 2017 2017-03-06 TN -0.5727010275 + #> 973 2067 3M CC02 2017 2017-03-06 TP -2.6882475738 #> 974 2067 3M CC02 2017 2017-03-06 TURB 1.3083328197 #> 975 2067 3M CC02 2017 2017-04-03 CHLAC 0.6931471806 #> 976 2067 3M CC02 2017 2017-04-03 COLOR 2.3978952728 #> 977 2067 3M CC02 2017 2017-04-03 DO 1.2809338455 #> 978 2067 3M CC02 2017 2017-04-03 DOSAT 4.0000338828 + #> 979 2067 3M CC02 2017 2017-04-03 NO23 -4.9618451299 I #> 980 2067 3M CC02 2017 2017-04-03 SALIN 3.5835189385 #> 981 2067 3M CC02 2017 2017-04-03 TKN -0.4155154440 #> 982 2067 3M CC02 2017 2017-04-03 TN -0.4094731295 + #> 983 2067 3M CC02 2017 2017-04-03 TP -2.6592600369 #> 984 2067 3M CC02 2017 2017-04-03 TURB 1.3862943611 #> 985 2067 3M CC02 2017 2017-05-01 CHLAC 0.7884573604 #> 986 2067 3M CC02 2017 2017-05-01 COLOR 1.5040773968 I #> 987 2067 3M CC02 2017 2017-05-01 DO 1.2527629685 #> 988 2067 3M CC02 2017 2017-05-01 DOSAT 3.9852734672 + #> 989 2067 3M CC02 2017 2017-05-01 NO23 -5.5214609179 U #> 990 2067 3M CC02 2017 2017-05-01 SALIN 3.5918177413 #> 991 2067 3M CC02 2017 2017-05-01 TKN -0.4462871026 #> 992 2067 3M CC02 2017 2017-05-01 TN -0.4431669753 + #> 993 2067 3M CC02 2017 2017-05-01 TP -3.1010927892 #> 994 2067 3M CC02 2017 2017-05-01 TURB 0.8754687374 #> 995 2067 3M CC02 2017 2017-07-10 CHLAC 1.0296194172 #> 996 2067 3M CC02 2017 2017-07-10 COLOR 3.1354942159 #> 997 2067 3M CC02 2017 2017-07-10 DO 1.1314021115 #> 998 2067 3M CC02 2017 2017-07-10 DOSAT 3.8938590348 + #> 999 2067 3M CC02 2017 2017-07-10 NO23 -4.4228486292 #> 1000 2067 3M CC02 2017 2017-07-10 SALIN 3.3978584804 #> 1001 2067 3M CC02 2017 2017-07-10 TKN -0.4620354596 #> 1002 2067 3M CC02 2017 2017-07-10 TN -0.4431669753 + #> 1003 2067 3M CC02 2017 2017-07-10 TP -2.7181005370 #> 1004 2067 3M CC02 2017 2017-07-10 TURB 1.4586150227 #> 1005 2067 3M CC02 2017 2017-08-07 CHLAC 1.1631508098 #> 1006 2067 3M CC02 2017 2017-08-07 COLOR 3.8712010109 #> 1007 2067 3M CC02 2017 2017-08-07 DO 0.8754687374 #> 1008 2067 3M CC02 2017 2017-08-07 DOSAT 3.6216707044 + #> 1009 2067 3M CC02 2017 2017-08-07 NO23 -4.5098600062 #> 1010 2067 3M CC02 2017 2017-08-07 SALIN 3.2542429687 #> 1011 2067 3M CC02 2017 2017-08-07 TKN -0.4307829161 #> 1012 2067 3M CC02 2017 2017-08-07 TN -0.4140014391 + #> 1013 2067 3M CC02 2017 2017-08-07 TP -2.5639498571 #> 1014 2067 3M CC02 2017 2017-08-07 TURB 0.5306282511 #> 1015 2067 3M CC02 2017 2017-10-02 CHLAC 1.0986122887 #> 1016 2067 3M CC02 2017 2017-10-02 COLOR 3.6888794541 #> 1017 2067 3M CC02 2017 2017-10-02 NO23 -5.2983173665 I #> 1018 2067 3M CC02 2017 2017-10-02 TKN -0.5276327421 #> 1019 2067 3M CC02 2017 2017-10-02 TN -0.5208759596 + #> 1020 2067 3M CC02 2017 2017-10-02 TP -2.3025850930 #> 1021 2067 3M CC02 2017 2017-10-02 TURB 1.0296194172 #> 1022 2067 3M CC02 2017 2017-11-06 CHLAC 0.9162907319 #> 1023 2067 3M CC02 2017 2017-11-06 COLOR 3.2188758249 #> 1024 2067 3M CC02 2017 2017-11-06 DO 1.2527629685 #> 1025 2067 3M CC02 2017 2017-11-06 DOSAT 3.8938590348 + #> 1026 2067 3M CC02 2017 2017-11-06 NO23 -4.6051701860 #> 1027 2067 3M CC02 2017 2017-11-06 SALIN 3.3499040873 #> 1028 2067 3M CC02 2017 2017-11-06 TKN -0.4620354596 #> 1029 2067 3M CC02 2017 2017-11-06 TN -0.4462871026 + #> 1030 2067 3M CC02 2017 2017-11-06 TP -2.6036901858 #> 1031 2067 3M CC02 2017 2017-11-06 TURB 0.8754687374 A #> 1032 2067 3M CC02 2017 2017-12-04 CHLAC 0.7884573604 #> 1033 2067 3M CC02 2017 2017-12-04 COLOR 2.5649493575 #> 1034 2067 3M CC02 2017 2017-12-04 DO 1.3862943611 #> 1035 2067 3M CC02 2017 2017-12-04 DOSAT 4.0181832013 + #> 1036 2067 3M CC02 2017 2017-12-04 NO23 -4.9618451299 I #> 1037 2067 3M CC02 2017 2017-12-04 SALIN 3.5025498759 #> 1038 2067 3M CC02 2017 2017-12-04 TKN -0.4780358009 #> 1039 2067 3M CC02 2017 2017-12-04 TN -0.4716049106 + #> 1040 2067 3M CC02 2017 2017-12-04 TP -2.6882475738 #> 1041 2067 3M CC02 2017 2017-12-04 TURB 1.3862943611 A #> 1042 2067 3M CC02 2018 2018-01-02 CHLAC 0.9932517730 #> 1043 2067 3M CC02 2018 2018-01-02 COLOR 2.5649493575 #> 1044 2067 3M CC02 2018 2018-01-02 DO 0.7884573604 #> 1045 2067 3M CC02 2018 2018-01-02 DOSAT 3.2580965380 + #> 1046 2067 3M CC02 2018 2018-01-02 NO23 -4.2686979494 #> 1047 2067 3M CC02 2018 2018-01-02 SALIN 3.4688560301 #> 1048 2067 3M CC02 2018 2018-01-02 TKN -0.6348782724 #> 1049 2067 3M CC02 2018 2018-01-02 TN -0.6088060321 + #> 1050 2067 3M CC02 2018 2018-01-02 TP -2.3434070875 #> 1051 2067 3M CC02 2018 2018-01-02 TURB 1.5260563035 #> 1052 2067 3M CC02 2018 2018-02-05 CHLAC 0.0953101798 I #> 1053 2067 3M CC02 2018 2018-02-05 COLOR 2.6390573296 #> 1054 2067 3M CC02 2018 2018-02-05 DO 1.5040773968 #> 1055 2067 3M CC02 2018 2018-02-05 DOSAT 4.0724397268 + #> 1056 2067 3M CC02 2018 2018-02-05 NO23 -4.1351665567 #> 1057 2067 3M CC02 2018 2018-02-05 SALIN 3.3877743613 #> 1058 2067 3M CC02 2018 2018-02-05 TKN -0.7339691751 #> 1059 2067 3M CC02 2018 2018-02-05 TN -0.7011793523 + #> 1060 2067 3M CC02 2018 2018-02-05 TP -2.7030626596 #> 1061 2067 3M CC02 2018 2018-02-05 TURB 1.2809338455 #> 1062 2067 3M CC02 2018 2018-03-05 CHLAC 0.6931471806 #> 1063 2067 3M CC02 2018 2018-03-05 COLOR 2.0014800002 #> 1064 2067 3M CC02 2018 2018-03-05 DO 1.5475625087 #> 1065 2067 3M CC02 2018 2018-03-05 DOSAT 4.1351665567 + #> 1066 2067 3M CC02 2018 2018-03-05 NO23 -5.1159958098 I #> 1067 2067 3M CC02 2018 2018-03-05 SALIN 3.5835189385 #> 1068 2067 3M CC02 2018 2018-03-05 TKN -0.7339691751 #> 1069 2067 3M CC02 2018 2018-03-05 TN -0.7256703723 + #> 1070 2067 3M CC02 2018 2018-03-05 TP -2.7333680091 #> 1071 2067 3M CC02 2018 2018-03-05 TURB 1.5892352051 A #> 1072 2067 3M CC02 2018 2018-04-02 CHLAC 0.6931471806 #> 1073 2067 3M CC02 2018 2018-04-02 COLOR 1.2527629685 I #> 1074 2067 3M CC02 2018 2018-04-02 DO 1.4109869737 #> 1075 2067 3M CC02 2018 2018-04-02 DOSAT 4.0926765051 + #> 1076 2067 3M CC02 2018 2018-04-02 NO23 -4.7105307016 I #> 1077 2067 3M CC02 2018 2018-04-02 SALIN 3.5945687746 #> 1078 2067 3M CC02 2018 2018-04-02 TKN -0.6539264674 #> 1079 2067 3M CC02 2018 2018-04-02 TN -0.6462635947 + #> 1080 2067 3M CC02 2018 2018-04-02 TP -2.5510464523 #> 1081 2067 3M CC02 2018 2018-04-02 TURB 1.7227665977 #> 1082 2067 3M CC02 2018 2018-05-07 CHLAC 0.5306282511 #> 1083 2067 3M CC02 2018 2018-05-07 COLOR 1.8245492921 #> 1084 2067 3M CC02 2018 2018-05-07 DO 1.3609765531 #> 1085 2067 3M CC02 2018 2018-05-07 DOSAT 3.9608131696 #> 1086 2067 3M CC02 2018 2018-05-07 NO23 -5.2983173665 I #> 1087 2067 3M CC02 2018 2018-05-07 SALIN 3.6027767551 #> 1088 2067 3M CC02 2018 2018-05-07 TKN -0.3147107448 #> 1089 2067 3M CC02 2018 2018-05-07 TN -0.3092462504 + #> 1090 2067 3M CC02 2018 2018-05-07 TP -2.7488721956 #> 1091 2067 3M CC02 2018 2018-05-07 TURB 1.3083328197 #> 1092 2067 3M CC02 2018 2018-07-09 CHLAC 1.6094379124 #> 1093 2067 3M CC02 2018 2018-07-09 COLOR 2.7725887222 #> 1094 2067 3M CC02 2018 2018-07-09 DO 1.0818051704 #> 1095 2067 3M CC02 2018 2018-07-09 DOSAT 3.8308129500 #> 1096 2067 3M CC02 2018 2018-07-09 NO23 -5.2983173665 I #> 1097 2067 3M CC02 2018 2018-07-09 SALIN 3.4741380061 #> 1098 2067 3M CC02 2018 2018-07-09 TKN -0.5276327421 #> 1099 2067 3M CC02 2018 2018-07-09 TN -0.5208759596 + #> 1100 2067 3M CC02 2018 2018-07-09 TURB 0.9932517730 #> 1101 2067 3M CC02 2018 2018-08-06 CHLAC 1.8562979904 #> 1102 2067 3M CC02 2018 2018-08-06 COLOR 3.5263605246 A #> 1103 2067 3M CC02 2018 2018-08-06 DO 0.8586616190 #> 1104 2067 3M CC02 2018 2018-08-06 DOSAT 3.6270040504 #> 1105 2067 3M CC02 2018 2018-08-06 NO23 -5.1159958098 I #> 1106 2067 3M CC02 2018 2018-08-06 SALIN 3.4968105459 #> 1107 2067 3M CC02 2018 2018-08-06 TKN -0.2107210313 #> 1108 2067 3M CC02 2018 2018-08-06 TN -0.2057949130 + #> 1109 2067 3M CC02 2018 2018-08-06 TP -2.3968957725 #> 1110 2067 3M CC02 2018 2018-08-06 TURB 1.0296194172 A #> 1111 2067 3M CC02 2019 2019-02-04 CHLAC -0.1984509387 I #> 1112 2067 3M CC02 2019 2019-02-04 COLOR 3.1354942159 #> 1113 2067 3M CC02 2019 2019-02-04 DO 1.3323660191 #> 1114 2067 3M CC02 2019 2019-02-04 DOSAT 3.8999504242 #> 1115 2067 3M CC02 2019 2019-02-04 NO23 -4.1997050779 #> 1116 2067 3M CC02 2019 2019-02-04 SALIN 3.2669037939 #> 1117 2067 3M CC02 2019 2019-02-04 TKN -0.6931471806 #> 1118 2067 3M CC02 2019 2019-02-04 TN -0.6635883783 + #> 1119 2067 3M CC02 2019 2019-02-04 TP -2.7181005370 #> 1120 2067 3M CC02 2019 2019-02-04 TURB 0.9932517730 #> 1121 2067 3M CC02 2019 2019-03-04 CHLAC 0.2623642645 I #> 1122 2067 3M CC02 2019 2019-03-04 COLOR 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NO23 -4.8283137373 I #> 1141 2067 3M CC02 2019 2019-05-06 SALIN 3.5522002552 #> 1142 2067 3M CC02 2019 2019-05-06 TKN -0.5108256238 #> 1143 2067 3M CC02 2019 2019-05-06 TN -0.5041810810 + #> 1144 2067 3M CC02 2019 2019-05-06 TP -2.7030626596 #> 1145 2067 3M CC02 2019 2019-05-06 TURB 1.0647107370 #> 1146 2067 3M CC02 2019 2019-06-03 CHLAC 0.6418538862 I #> 1147 2067 3M CC02 2019 2019-06-03 COLOR 1.3350010667 I #> 1148 2067 3M CC02 2019 2019-06-03 DO 0.4700036292 #> 1149 2067 3M CC02 2019 2019-06-03 DOSAT 3.2771447330 #> 1150 2067 3M CC02 2019 2019-06-03 NO23 -4.3428059215 #> 1151 2067 3M CC02 2019 2019-06-03 SALIN 3.5882300460 #> 1152 2067 3M CC02 2019 2019-06-03 TKN -0.5447271754 #> 1153 2067 3M CC02 2019 2019-06-03 TN -0.5225608800 + #> 1154 2067 3M CC02 2019 2019-06-03 TP -2.6172958378 #> 1155 2067 3M CC02 2019 2019-06-03 TURB 0.6931471806 #> 1156 2067 3M CC02 2019 2019-07-01 CHLAC 0.7419373447 I #> 1157 2067 3M CC02 2019 2019-07-01 COLOR 1.9315214116 #> 1158 2067 3M CC02 2019 2019-07-01 NO23 -4.8283137373 I #> 1159 2067 3M CC02 2019 2019-07-01 SALIN 3.5424075502 #> 1160 2067 3M CC02 2019 2019-07-01 TKN -0.5621189182 #> 1161 2067 3M CC02 2019 2019-07-01 TN -0.5551258827 + #> 1162 2067 3M CC02 2019 2019-07-01 TP -3.1941832123 #> 1163 2067 3M CC02 2019 2019-07-01 TURB 0.8329091229 #> 1164 2067 3M CC02 2019 2019-08-05 CHLAC 0.6418538862 I #> 1165 2067 3M CC02 2019 2019-08-05 COLOR 3.7841896339 A #> 1166 2067 3M CC02 2019 2019-08-05 DO 0.6312717768 #> 1167 2067 3M CC02 2019 2019-08-05 DOSAT 3.3775875160 #> 1168 2067 3M CC02 2019 2019-08-05 NO23 -4.7105307016 I #> 1169 2067 3M CC02 2019 2019-08-05 SALIN 3.3617633124 #> 1170 2067 3M CC02 2019 2019-08-05 TKN -0.4780358009 #> 1171 2067 3M CC02 2019 2019-08-05 TN -0.4716049106 + #> 1172 2067 3M CC02 2019 2019-08-05 TP -3.1010927892 #> 1173 2067 3M CC02 2019 2019-08-05 TURB 0.4054651081 #> 1174 2067 3M CC02 2019 2019-10-07 CHLAC 1.3350010667 #> 1175 2067 3M CC02 2019 2019-10-07 COLOR 1.2809338455 I #> 1176 2067 3M CC02 2019 2019-10-07 DO 1.0508216248 #> 1177 2067 3M CC02 2019 2019-10-07 DOSAT 3.7750571504 #> 1178 2067 3M CC02 2019 2019-10-07 NO23 -5.2983173665 I #> 1179 2067 3M CC02 2019 2019-10-07 SALIN 3.5389282774 #> 1180 2067 3M CC02 2019 2019-10-07 TKN -0.6733445533 #> 1181 2067 3M CC02 2019 2019-10-07 TN -0.6655320135 + #> 1182 2067 3M CC02 2019 2019-10-07 TP -2.9759296463 #> 1183 2067 3M CC02 2019 2019-10-07 TURB 1.1314021115 #> 1184 2067 3M CC02 2019 2019-11-04 CHLAC 1.6292405397 #> 1185 2067 3M CC02 2019 2019-11-04 COLOR 1.4816045409 I #> 1186 2067 3M CC02 2019 2019-11-04 DO 0.4762341790 #> 1187 2067 3M CC02 2019 2019-11-04 DOSAT 3.2464909919 #> 1188 2067 3M CC02 2019 2019-11-04 NO23 -4.4228486292 #> 1189 2067 3M CC02 2019 2019-11-04 SALIN 3.5177945292 #> 1190 2067 3M CC02 2019 2019-11-04 TKN -0.4307829161 #> 1191 2067 3M CC02 2019 2019-11-04 TN -0.4124897230 + #> 1192 2067 3M CC02 2019 2019-11-04 TP -2.5257286443 #> 1193 2067 3M CC02 2019 2019-11-04 TURB 1.2809338455 #> 1194 2067 3M CC02 2019 2019-12-02 CHLAC 0.0953101798 I #> 1195 2067 3M CC02 2019 2019-12-02 COLOR 0.9162907319 U #> 1196 2067 3M CC02 2019 2019-12-02 DO 0.9932517730 #> 1197 2067 3M CC02 2019 2019-12-02 DOSAT 3.6454498962 #> 1198 2067 3M CC02 2019 2019-12-02 NO23 -4.4228486292 #> 1199 2067 3M CC02 2019 2019-12-02 SALIN 3.5133348816 #> 1200 2067 3M CC02 2019 2019-12-02 TKN -0.7765287895 #> 1201 2067 3M CC02 2019 2019-12-02 TN -0.7507762934 + #> 1202 2067 3M CC02 2019 2019-12-02 TP -2.9374633654 #> 1203 2067 3M CC02 2019 2019-12-02 TURB 0.7419373447 #> 1204 2067 3M CC02 2020 2020-01-06 CHLAC 0.6931471806 I #> 1205 2067 3M CC02 2020 2020-01-06 COLOR 2.5649493575 #> 1206 2067 3M CC02 2020 2020-01-06 NO23 -4.2686979494 #> 1207 2067 3M CC02 2020 2020-01-06 SALIN 3.4775409482 #> 1208 2067 3M CC02 2020 2020-01-06 TKN -0.4620354596 #> 1209 2067 3M CC02 2020 2020-01-06 TN -0.4400565529 + #> 1210 2067 3M CC02 2020 2020-01-06 TP -2.3859667019 #> 1211 2067 3M CC02 2020 2020-01-06 TURB 1.2809338455 #> 1212 2067 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2067 3M CC02 2020 2020-03-02 TURB 1.7749523509 A #> 1231 2067 3M CC02 2020 2020-09-08 CHLAC 1.4350845253 #> 1232 2067 3M CC02 2020 2020-09-08 COLOR 3.9318256327 A #> 1233 2067 3M CC02 2020 2020-09-08 DO 0.6259384309 #> 1234 2067 3M CC02 2020 2020-09-08 DOSAT 3.3214324132 #> 1235 2067 3M CC02 2020 2020-09-08 NO23 -4.2686979494 #> 1236 2067 3M CC02 2020 2020-09-08 SALIN 3.2268439945 #> 1237 2067 3M CC02 2020 2020-09-08 TKN -0.3856624808 #> 1238 2067 3M CC02 2020 2020-09-08 TN -0.3652833185 + #> 1239 2067 3M CC02 2020 2020-09-08 TP -2.5639498571 #> 1240 2067 3M CC02 2020 2020-09-08 TURB 0.7419373447 #> 1241 2067 3M CC02 2020 2020-10-05 CHLAC 0.8754687374 I #> 1242 2067 3M CC02 2020 2020-10-05 COLOR 3.4339872045 A #> 1243 2067 3M CC02 2020 2020-10-05 DO 0.7793248768 #> 1244 2067 3M CC02 2020 2020-10-05 DOSAT 3.4038604991 #> 1245 2067 3M CC02 2020 2020-10-05 NO23 -3.6496587410 #> 1246 2067 3M CC02 2020 2020-10-05 SALIN 3.3769046891 #> 1247 2067 3M CC02 2020 2020-10-05 TKN -0.5447271754 #> 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NO23 -5.5214609179 U #> 1481 2067 3M CC02 2023 2023-01-03 SALIN 3.4249139083 #> 1482 2067 3M CC02 2023 2023-01-03 TKN -0.5798184953 #> 1483 2067 3M CC02 2023 2023-01-03 TN -0.5762534291 + #> 1484 2067 3M CC02 2023 2023-01-03 TP -2.5383074265 #> 1485 2067 3M CC02 2023 2023-01-03 TURB 1.0296194172 #> 1486 2067 3M CC02 2023 2023-02-06 CHLAC 0.8754687374 I #> 1487 2067 3M CC02 2023 2023-02-06 COLOR 2.1747517215 #> 1488 2067 3M CC02 2023 2023-02-06 DO 1.8017098001 #> 1489 2067 3M CC02 2023 2023-02-06 DOSAT 4.4260435201 #> 1490 2067 3M CC02 2023 2023-02-06 NO23 -5.1159958098 I #> 1491 2067 3M CC02 2023 2023-02-06 SALIN 3.4895134627 #> 1492 2067 3M CC02 2023 2023-02-06 TKN -0.7765287895 #> 1493 2067 3M CC02 2023 2023-02-06 TN -0.7678707268 + #> 1494 2067 3M CC02 2023 2023-02-06 TP -2.6882475738 #> 1495 2067 3M CC02 2023 2023-02-06 TURB 0.9932517730 #> 1496 2067 3M CC02 2023 2023-03-06 DO 1.7369512327 #> 1497 2067 3M CC02 2023 2023-03-06 DOSAT 4.4555094114 #> 1498 2067 3M CC02 2023 2023-03-06 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2018-05-08 TKN -0.4462871026 #> 1517 2067 3M CC02 2018 2018-05-08 TN -0.4431669753 + #> 1518 2067 3M CC02 2018 2018-05-08 TP -2.7181005370 #> 1519 2067 3M CC02 2018 2018-05-08 TSS 1.6094379124 I #> 1520 2067 3M CC02 2018 2018-05-08 TURB 1.2237754316 #> 1521 2067 3M CC02 2018 2018-06-26 CHLAC 2.5649493575 #> 1522 2067 3M CC02 2018 2018-06-26 COND 10.6878456131 #> 1523 2067 3M CC02 2018 2018-06-26 DO 1.2947271676 #> 1524 2067 3M CC02 2018 2018-06-26 DOSAT 4.0395363257 #> 1525 2067 3M CC02 2018 2018-06-26 NO23 -4.9618451299 I #> 1526 2067 3M CC02 2018 2018-06-26 TKN -0.3566749439 #> 1527 2067 3M CC02 2018 2018-06-26 TN -0.3509769228 + #> 1528 2067 3M CC02 2018 2018-06-26 TP -2.3025850930 #> 1529 2067 3M CC02 2018 2018-06-26 TSS 2.0794415417 I #> 1530 2067 3M CC02 2018 2018-06-26 TURB 1.0647107370 A #> 1531 2067 3M CC02 2018 2018-09-18 CHLAC 2.3978952728 #> 1532 2067 3M CC02 2018 2018-09-18 COND 10.2632925926 #> 1533 2067 3M CC02 2018 2018-09-18 DO 0.9745596400 #> 1534 2067 3M CC02 2018 2018-09-18 DOSAT 3.6963514690 #> 1535 2067 3M CC02 2018 2018-09-18 NO23 -3.2188758249 #> 1536 2067 3M CC02 2018 2018-09-18 TKN -0.2231435513 #> 1537 2067 3M CC02 2018 2018-09-18 TN -0.1743533871 + #> 1538 2067 3M CC02 2018 2018-09-18 TP -2.0402208285 #> 1539 2067 3M CC02 2018 2018-09-18 TSS 1.3862943611 I #> 1540 2067 3M CC02 2018 2018-09-18 TURB 0.7884573604 #> 1541 2067 3M CC02 2018 2018-12-04 CHLAC 1.2809338455 #> 1542 2067 3M CC02 2018 2018-12-04 COND 10.8257007122 #> 1543 2067 3M CC02 2018 2018-12-04 DO 1.6272778306 #> 1544 2067 3M CC02 2018 2018-12-04 DOSAT 4.3107991254 #> 1545 2067 3M CC02 2018 2018-12-04 NO23 -1.9661128564 G #> 1546 2067 3M CC02 2018 2018-12-04 SALIN 3.4949912609 #> 1547 2067 3M CC02 2018 2018-12-04 TKN -0.4155154440 #> 1548 2067 3M CC02 2018 2018-12-04 TN -0.2231435513 + #> 1549 2067 3M CC02 2018 2018-12-04 TP -2.5010360317 #> 1550 2067 3M CC02 2018 2018-12-04 TSS 2.3025850930 I #> 1551 2067 3M CC02 2018 2018-12-04 TURB 0.4054651081 #> 1552 2068 3M CC03 2014 2014-01-06 CHLAC 0.3364722366 I #> 1553 2068 3M CC03 2014 2014-01-06 COLOR 2.5649493575 #> 1554 2068 3M CC03 2014 2014-01-06 DO 1.3862943611 #> 1555 2068 3M CC03 2014 2014-01-06 DOSAT 3.9963641539 + #> 1556 2068 3M CC03 2014 2014-01-06 NO23 -4.7105307016 I #> 1557 2068 3M CC03 2014 2014-01-06 SALIN 3.4904285154 #> 1558 2068 3M CC03 2014 2014-01-06 TKN -0.6161861394 #> 1559 2068 3M CC03 2014 2014-01-06 TN -0.6088060321 + #> 1560 2068 3M CC03 2014 2014-01-06 TP -3.1010927892 #> 1561 2068 3M CC03 2014 2014-01-06 TURB 0.4054651081 #> 1562 2068 3M CC03 2014 2014-02-03 CHLAC 1.8870696490 #> 1563 2068 3M CC03 2014 2014-02-03 COLOR 3.5263605246 #> 1564 2068 3M CC03 2014 2014-02-03 DO 0.7884573604 #> 1565 2068 3M CC03 2014 2014-02-03 DOSAT 3.2921262866 + #> 1566 2068 3M CC03 2014 2014-02-03 NO23 -3.6888794541 #> 1567 2068 3M CC03 2014 2014-02-03 SALIN 2.6602595373 #> 1568 2068 3M CC03 2014 2014-02-03 TKN 0.0000000000 #> 1569 2068 3M CC03 2014 2014-02-03 TN 0.0246926126 + #> 1570 2068 3M CC03 2014 2014-02-03 TP -2.3025850930 #> 1571 2068 3M CC03 2014 2014-02-03 TURB 0.8329091229 #> 1572 2068 3M CC03 2014 2014-03-03 CHLAC 1.0986122887 #> 1573 2068 3M CC03 2014 2014-03-03 COLOR 2.8332133441 #> 1574 2068 3M CC03 2014 2014-03-03 DO 0.7884573604 #> 1575 2068 3M CC03 2014 2014-03-03 DOSAT 3.3638415951 + #> 1576 2068 3M CC03 2014 2014-03-03 NO23 -5.5214609179 I #> 1577 2068 3M CC03 2014 2014-03-03 SALIN 3.2657594108 #> 1578 2068 3M CC03 2014 2014-03-03 TKN -0.4462871026 #> 1579 2068 3M CC03 2014 2014-03-03 TN -0.4400565529 + #> 1580 2068 3M CC03 2014 2014-03-03 TP -2.6592600369 #> 1581 2068 3M CC03 2014 2014-03-03 TURB 0.7884573604 #> 1582 2068 3M CC03 2014 2014-04-07 CHLAC 1.2237754316 #> 1583 2068 3M CC03 2014 2014-04-07 COLOR 3.4011973817 A #> 1584 2068 3M CC03 2014 2014-04-07 DO 0.6418538862 #> 1585 2068 3M CC03 2014 2014-04-07 DOSAT 3.2580965380 + #> 1586 2068 3M CC03 2014 2014-04-07 NO23 -4.3428059215 #> 1587 2068 3M CC03 2014 2014-04-07 SALIN 3.1000922889 #> 1588 2068 3M 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3M CC03 2014 2014-06-02 NO23 -5.2983173665 I #> 1607 2068 3M CC03 2014 2014-06-02 SALIN 3.0633909220 #> 1608 2068 3M CC03 2014 2014-06-02 TKN -0.2744368457 #> 1609 2068 3M CC03 2014 2014-06-02 TN -0.2691874898 + #> 1610 2068 3M CC03 2014 2014-06-02 TP -2.9957322736 #> 1611 2068 3M CC03 2014 2014-06-02 TURB 0.5877866649 #> 1612 2068 3M CC03 2014 2014-07-07 CHLAC 1.4350845253 #> 1613 2068 3M CC03 2014 2014-07-07 COLOR 3.6375861597 A #> 1614 2068 3M CC03 2014 2014-07-07 DO -0.9162907319 #> 1615 2068 3M CC03 2014 2014-07-07 DOSAT 1.8562979904 + #> 1616 2068 3M CC03 2014 2014-07-07 NO23 -5.5214609179 I #> 1617 2068 3M CC03 2014 2014-07-07 SALIN 3.5438536821 #> 1618 2068 3M CC03 2014 2014-07-07 TKN -0.2357223335 #> 1619 2068 3M CC03 2014 2014-07-07 TN -0.2306718177 + #> 1620 2068 3M CC03 2014 2014-07-07 TP -3.1235656451 #> 1621 2068 3M CC03 2014 2014-07-07 TURB 1.8082887712 #> 1622 2068 3M CC03 2014 2014-08-04 CHLAC 1.6292405397 #> 1623 2068 3M CC03 2014 2014-08-04 COLOR 3.6375861597 #> 1624 2068 3M CC03 2014 2014-08-04 DO -0.3566749439 #> 1625 2068 3M CC03 2014 2014-08-04 DOSAT 2.3887627892 + #> 1626 2068 3M CC03 2014 2014-08-04 NO23 -5.5214609179 I #> 1627 2068 3M CC03 2014 2014-08-04 SALIN 3.4242626546 #> 1628 2068 3M CC03 2014 2014-08-04 TKN -0.1508228897 #> 1629 2068 3M CC03 2014 2014-08-04 TN -0.1461825102 + #> 1630 2068 3M CC03 2014 2014-08-04 TP -2.9565115604 #> 1631 2068 3M CC03 2014 2014-08-04 TURB 1.2809338455 #> 1632 2068 3M CC03 2014 2014-09-08 CHLAC 2.3025850930 #> 1633 2068 3M CC03 2014 2014-09-08 COLOR 3.2958368660 #> 1634 2068 3M CC03 2014 2014-09-08 DO -1.2039728043 #> 1635 2068 3M CC03 2014 2014-09-08 DOSAT 1.5040773968 + #> 1636 2068 3M CC03 2014 2014-09-08 NO23 -5.5214609179 U #> 1637 2068 3M CC03 2014 2014-09-08 SALIN 3.4011973817 #> 1638 2068 3M CC03 2014 2014-09-08 TKN -0.1508228897 #> 1639 2068 3M CC03 2014 2014-09-08 TN -0.1485000083 + #> 1640 2068 3M CC03 2014 2014-09-08 TP -2.8824035882 #> 1641 2068 3M CC03 2014 2014-09-08 TURB 1.1631508098 #> 1642 2068 3M CC03 2014 2014-10-06 CHLAC 2.3025850930 #> 1643 2068 3M CC03 2014 2014-10-06 COLOR 4.1588830834 #> 1644 2068 3M CC03 2014 2014-10-06 DO 0.6931471806 #> 1645 2068 3M CC03 2014 2014-10-06 DOSAT 3.2464909919 + #> 1646 2068 3M CC03 2014 2014-10-06 NO23 -4.7105307016 I #> 1647 2068 3M CC03 2014 2014-10-06 SALIN 2.7080502011 #> 1648 2068 3M CC03 2014 2014-10-06 TKN -0.1165338163 #> 1649 2068 3M CC03 2014 2014-10-06 TN -0.1120495038 + #> 1650 2068 3M CC03 2014 2014-10-06 TP -1.9661128564 #> 1651 2068 3M CC03 2014 2014-10-06 TURB 1.1631508098 #> 1652 2068 3M CC03 2014 2014-11-03 CHLAC 2.3978952728 #> 1653 2068 3M CC03 2014 2014-11-03 COLOR 3.5835189385 #> 1654 2068 3M CC03 2014 2014-11-03 DO 1.3862943611 #> 1655 2068 3M CC03 2014 2014-11-03 DOSAT 3.8543938926 + #> 1656 2068 3M CC03 2014 2014-11-03 NO23 -4.5098600062 #> 1657 2068 3M CC03 2014 2014-11-03 SALIN 3.1612467120 #> 1658 2068 3M CC03 2014 2014-11-03 TKN -0.1743533871 #> 1659 2068 3M CC03 2014 2014-11-03 TN -0.1613431504 + #> 1660 2068 3M CC03 2014 2014-11-03 TP -2.6036901858 #> 1661 2068 3M CC03 2014 2014-11-03 TURB 1.0647107370 #> 1662 2068 3M CC03 2015 2015-01-05 CHLAC 2.0281482473 #> 1663 2068 3M CC03 2015 2015-01-05 COLOR 3.2188758249 #> 1664 2068 3M CC03 2015 2015-01-05 DO 0.9162907319 #> 1665 2068 3M CC03 2015 2015-01-05 DOSAT 3.5438536821 + #> 1666 2068 3M CC03 2015 2015-01-05 NO23 -4.4228486292 #> 1667 2068 3M CC03 2015 2015-01-05 SALIN 3.2995337279 #> 1668 2068 3M CC03 2015 2015-01-05 TKN -0.0512932944 #> 1669 2068 3M CC03 2015 2015-01-05 TN -0.0387408283 + #> 1670 2068 3M CC03 2015 2015-01-05 TP -2.5383074265 #> 1671 2068 3M CC03 2015 2015-01-05 TURB 0.6418538862 #> 1672 2068 3M CC03 2015 2015-02-02 CHLAC 0.6418538862 #> 1673 2068 3M CC03 2015 2015-02-02 COLOR 2.3025850930 #> 1674 2068 3M CC03 2015 2015-02-02 DO 1.4109869737 #> 1675 2068 3M CC03 2015 2015-02-02 DOSAT 3.9778107460 + #> 1676 2068 3M CC03 2015 2015-02-02 NO23 -5.1159958098 I #> 1677 2068 3M CC03 2015 2015-02-02 SALIN 3.3911470458 #> 1678 2068 3M CC03 2015 2015-02-02 TKN -0.7765287895 #> 1679 2068 3M CC03 2015 2015-02-02 TN -0.7678707268 + #> 1680 2068 3M CC03 2015 2015-02-02 TP -2.9957322736 #> 1681 2068 3M CC03 2015 2015-02-02 TURB 0.3364722366 #> 1682 2068 3M CC03 2015 2015-03-02 CHLAC 1.6677068206 A #> 1683 2068 3M CC03 2015 2015-03-02 COLOR 3.1354942159 #> 1684 2068 3M CC03 2015 2015-03-02 DO 0.9932517730 #> 1685 2068 3M CC03 2015 2015-03-02 DOSAT 3.5862928653 + #> 1686 2068 3M CC03 2015 2015-03-02 NO23 -4.5098600062 #> 1687 2068 3M CC03 2015 2015-03-02 SALIN 3.1311369106 #> 1688 2068 3M CC03 2015 2015-03-02 TKN -0.4780358009 #> 1689 2068 3M CC03 2015 2015-03-02 TN -0.4604494164 + #> 1690 2068 3M CC03 2015 2015-03-02 TP -2.8824035882 #> 1691 2068 3M CC03 2015 2015-03-02 TURB 0.3364722366 #> 1692 2068 3M CC03 2015 2015-04-06 CHLAC 0.8754687374 #> 1693 2068 3M CC03 2015 2015-04-06 COLOR 3.0910424534 #> 1694 2068 3M CC03 2015 2015-04-06 DO -0.1053605157 #> 1695 2068 3M CC03 2015 2015-04-06 DOSAT 2.5494451709 + #> 1696 2068 3M CC03 2015 2015-04-06 NO23 -5.5214609179 U #> 1697 2068 3M CC03 2015 2015-04-06 SALIN 3.4011973817 #> 1698 2068 3M CC03 2015 2015-04-06 TKN -0.3566749439 #> 1699 2068 3M CC03 2015 2015-04-06 TN -0.3538218750 + #> 1700 2068 3M CC03 2015 2015-04-06 TP -3.2188758249 #> 1701 2068 3M CC03 2015 2015-04-06 TURB 0.4700036292 #> 1702 2068 3M CC03 2015 2015-05-04 CHLAC 0.9932517730 #> 1703 2068 3M CC03 2015 2015-05-04 COLOR 3.2188758249 #> 1704 2068 3M CC03 2015 2015-05-04 DO 0.1823215568 #> 1705 2068 3M CC03 2015 2015-05-04 DOSAT 2.8622008809 + #> 1706 2068 3M CC03 2015 2015-05-04 NO23 -4.8283137373 I #> 1707 2068 3M CC03 2015 2015-05-04 SALIN 3.4904285154 #> 1708 2068 3M CC03 2015 2015-05-04 TKN -0.3856624808 #> 1709 2068 3M CC03 2015 2015-05-04 TN -0.3797973614 + #> 1710 2068 3M CC03 2015 2015-05-04 TP -3.2968373663 #> 1711 2068 3M CC03 2015 2015-05-04 TURB 0.6931471806 #> 1712 2068 3M CC03 2015 2015-06-01 CHLAC 1.7749523509 #> 1713 2068 3M CC03 2015 2015-06-01 COLOR 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TURB 1.5892352051 #> 1732 2068 3M CC03 2015 2015-09-08 CHLAC 1.7227665977 #> 1733 2068 3M CC03 2015 2015-09-08 COLOR 3.8286413965 #> 1734 2068 3M CC03 2015 2015-09-08 DO 0.0000000000 #> 1735 2068 3M CC03 2015 2015-09-08 DOSAT 2.6602595373 + #> 1736 2068 3M CC03 2015 2015-09-08 NO23 -4.8283137373 I #> 1737 2068 3M CC03 2015 2015-09-08 SALIN 2.9014215941 #> 1738 2068 3M CC03 2015 2015-09-08 TKN -0.2357223335 #> 1739 2068 3M CC03 2015 2015-09-08 TN -0.2306718177 + #> 1740 2068 3M CC03 2015 2015-09-08 TP -3.0159349809 #> 1741 2068 3M CC03 2015 2015-09-08 TURB 0.6931471806 #> 1742 2068 3M CC03 2015 2015-10-05 CHLAC 1.4586150227 #> 1743 2068 3M CC03 2015 2015-10-05 COLOR 3.2958368660 A #> 1744 2068 3M CC03 2015 2015-10-05 DO 0.6418538862 #> 1745 2068 3M CC03 2015 2015-10-05 DOSAT 3.3214324132 + #> 1746 2068 3M CC03 2015 2015-10-05 NO23 -5.5214609179 U #> 1747 2068 3M CC03 2015 2015-10-05 SALIN 3.3741687093 #> 1748 2068 3M CC03 2015 2015-10-05 TKN -0.4307829161 #> 1749 2068 3M CC03 2015 2015-10-05 TN -0.4277107171 + #> 1750 2068 3M CC03 2015 2015-10-05 TP -3.0576076773 #> 1751 2068 3M CC03 2015 2015-10-05 TURB 0.8754687374 #> 1752 2068 3M CC03 2015 2015-12-07 CHLAC 1.3609765531 #> 1753 2068 3M CC03 2015 2015-12-07 COLOR 3.2188758249 #> 1754 2068 3M CC03 2015 2015-12-07 DO 1.1314021115 #> 1755 2068 3M CC03 2015 2015-12-07 DOSAT 3.7447870861 + #> 1756 2068 3M CC03 2015 2015-12-07 NO23 -4.5098600062 #> 1757 2068 3M CC03 2015 2015-12-07 SALIN 3.4144426084 #> 1758 2068 3M CC03 2015 2015-12-07 TKN -0.4462871026 #> 1759 2068 3M CC03 2015 2015-12-07 TN -0.4292456368 + #> 1760 2068 3M CC03 2015 2015-12-07 TP -2.8473122684 #> 1761 2068 3M CC03 2015 2015-12-07 TURB 1.1939224685 #> 1762 2068 3M CC03 2016 2016-01-04 CHLAC 1.3083328197 #> 1763 2068 3M CC03 2016 2016-01-04 COLOR 3.3672958300 #> 1764 2068 3M CC03 2016 2016-01-04 DO 0.0000000000 #> 1765 2068 3M CC03 2016 2016-01-04 DOSAT 2.5176964726 + #> 1766 2068 3M CC03 2016 2016-01-04 NO23 -4.0173835211 #> 1767 2068 3M CC03 2016 2016-01-04 SALIN 3.1904763503 #> 1768 2068 3M CC03 2016 2016-01-04 TKN -0.3566749439 #> 1769 2068 3M CC03 2016 2016-01-04 TN -0.3312857099 + #> 1770 2068 3M CC03 2016 2016-01-04 TP -2.6172958378 #> 1771 2068 3M CC03 2016 2016-01-04 TURB 0.8754687374 #> 1772 2068 3M CC03 2016 2016-02-01 CHLAC 1.0647107370 #> 1773 2068 3M CC03 2016 2016-02-01 COLOR 3.6635616461 #> 1774 2068 3M CC03 2016 2016-02-01 DOSAT 3.7256934272 + #> 1775 2068 3M CC03 2016 2016-02-01 NO23 -2.7030626596 #> 1776 2068 3M CC03 2016 2016-02-01 SALIN 2.7850112422 #> 1777 2068 3M CC03 2016 2016-02-01 TKN -0.2357223335 #> 1778 2068 3M CC03 2016 2016-02-01 TN -0.1543173604 + #> 1779 2068 3M CC03 2016 2016-02-01 TP -2.0402208285 #> 1780 2068 3M CC03 2016 2016-02-01 TURB 0.6418538862 #> 1781 2068 3M CC03 2016 2016-03-07 CHLAC 1.7227665977 #> 1782 2068 3M CC03 2016 2016-03-07 COLOR 3.5835189385 #> 1783 2068 3M CC03 2016 2016-03-07 DO 0.8329091229 #> 1784 2068 3M CC03 2016 2016-03-07 DOSAT 3.2995337279 + #> 1785 2068 3M CC03 2016 2016-03-07 NO23 -4.7105307016 I #> 1786 2068 3M CC03 2016 2016-03-07 SALIN 2.7080502011 #> 1787 2068 3M CC03 2016 2016-03-07 TKN -0.3011050928 #> 1788 2068 3M CC03 2016 2016-03-07 TN -0.2957142441 + #> 1789 2068 3M CC03 2016 2016-03-07 TP -2.3025850930 #> 1790 2068 3M CC03 2016 2016-03-07 TURB 1.1631508098 A #> 1791 2068 3M CC03 2016 2016-04-04 CHLAC 0.9932517730 #> 1792 2068 3M CC03 2016 2016-04-04 COLOR 3.5263605246 #> 1793 2068 3M CC03 2016 2016-04-04 DO 0.9555114450 #> 1794 2068 3M CC03 2016 2016-04-04 DOSAT 3.5263605246 + #> 1795 2068 3M CC03 2016 2016-04-04 NO23 -4.5098600062 #> 1796 2068 3M CC03 2016 2016-04-04 SALIN 3.0007198151 #> 1797 2068 3M CC03 2016 2016-04-04 TKN -0.3566749439 #> 1798 2068 3M CC03 2016 2016-04-04 TN -0.3410828492 + #> 1799 2068 3M CC03 2016 2016-04-04 TP -2.3859667019 #> 1800 2068 3M CC03 2016 2016-04-04 TURB 1.0296194172 #> 1801 2068 3M CC03 2016 2016-05-02 CHLAC 0.3364722366 I #> 1802 2068 3M CC03 2016 2016-05-02 COLOR 3.2580965380 #> 1803 2068 3M CC03 2016 2016-05-02 DO 0.7884573604 #> 1804 2068 3M CC03 2016 2016-05-02 DOSAT 3.5234150144 + #> 1805 2068 3M CC03 2016 2016-05-02 NO23 -5.5214609179 U #> 1806 2068 3M CC03 2016 2016-05-02 SALIN 3.6270040504 #> 1807 2068 3M CC03 2016 2016-05-02 TKN -0.3566749439 #> 1808 2068 3M CC03 2016 2016-05-02 TN -0.3538218750 + #> 1809 2068 3M CC03 2016 2016-05-02 TP -2.5639498571 #> 1810 2068 3M CC03 2016 2016-05-02 TURB 0.0953101798 #> 1811 2068 3M CC03 2017 2017-08-07 CHLAC 2.3978952728 #> 1812 2068 3M CC03 2017 2017-08-07 COLOR 4.2195077052 #> 1813 2068 3M CC03 2017 2017-08-07 DOSAT 2.3513752572 + #> 1814 2068 3M CC03 2017 2017-08-07 NO23 -5.5214609179 U #> 1815 2068 3M CC03 2017 2017-08-07 SALIN 1.4350845253 #> 1816 2068 3M CC03 2017 2017-08-07 TKN 0.5306282511 #> 1817 2068 3M CC03 2017 2017-08-07 TN 0.5318040302 + #> 1818 2068 3M CC03 2017 2017-08-07 TP -2.7030626596 #> 1819 2068 3M CC03 2017 2017-08-07 TURB 0.9162907319 #> 1820 2068 3M CC03 2017 2017-09-05 CHLAC 2.7080502011 #> 1821 2068 3M CC03 2017 2017-09-05 COLOR 5.0106352941 #> 1822 2068 3M CC03 2017 2017-09-05 DO 0.6931471806 #> 1823 2068 3M CC03 2017 2017-09-05 DOSAT 3.2884018875 + #> 1824 2068 3M CC03 2017 2017-09-05 NO23 -4.4228486292 #> 1825 2068 3M CC03 2017 2017-09-05 SALIN 2.2721258855 #> 1826 2068 3M CC03 2017 2017-09-05 TKN 0.1823215568 #> 1827 2068 3M CC03 2017 2017-09-05 TN 0.1922718876 + #> 1828 2068 3M CC03 2017 2017-09-05 TP -1.7719568419 #> 1829 2068 3M CC03 2017 2017-09-05 TURB 1.3350010667 #> 1830 2068 3M CC03 2017 2017-10-02 CHLAC 2.5649493575 #> 1831 2068 3M CC03 2017 2017-10-02 COLOR 4.0943445622 A #> 1832 2068 3M CC03 2017 2017-10-02 NO23 -5.5214609179 U #> 1833 2068 3M CC03 2017 2017-10-02 TKN -0.0725706928 #> 1834 2068 3M CC03 2017 2017-10-02 TN -0.0704224643 + #> 1835 2068 3M CC03 2017 2017-10-02 TP -2.3025850930 #> 1836 2068 3M CC03 2017 2017-10-02 TURB 1.8870696490 #> 1837 2068 3M CC03 2017 2017-11-06 CHLAC 1.1631508098 #> 1838 2068 3M CC03 2017 2017-11-06 COLOR 3.5835189385 #> 1839 2068 3M CC03 2017 2017-11-06 DO 1.3083328197 #> 1840 2068 3M CC03 2017 2017-11-06 DOSAT 3.9080149840 + #> 1841 2068 3M CC03 2017 2017-11-06 NO23 -5.2983173665 I #> 1842 2068 3M CC03 2017 2017-11-06 SALIN 3.1354942159 #> 1843 2068 3M CC03 2017 2017-11-06 TKN -0.2744368457 #> 1844 2068 3M CC03 2017 2017-11-06 TN -0.2691874898 + #> 1845 2068 3M CC03 2017 2017-11-06 TP -2.4418471603 #> 1846 2068 3M CC03 2017 2017-11-06 TURB 1.2237754316 #> 1847 2068 3M CC03 2018 2018-01-02 CHLAC 1.0647107370 #> 1848 2068 3M CC03 2018 2018-01-02 COLOR 3.0445224377 #> 1849 2068 3M CC03 2018 2018-01-02 NO23 -4.9618451299 I #> 1850 2068 3M CC03 2018 2018-01-02 SALIN 3.4563166809 #> 1851 2068 3M CC03 2018 2018-01-02 TKN -0.4780358009 #> 1852 2068 3M CC03 2018 2018-01-02 TN -0.4716049106 + #> 1853 2068 3M CC03 2018 2018-01-02 TP -2.4079456087 #> 1854 2068 3M CC03 2018 2018-01-02 TURB 1.1314021115 #> 1855 2068 3M CC03 2018 2018-02-05 CHLAC 0.9932517730 A #> 1856 2068 3M CC03 2018 2018-02-05 COLOR 3.2188758249 #> 1857 2068 3M CC03 2018 2018-02-05 DO 1.3609765531 #> 1858 2068 3M CC03 2018 2018-02-05 DOSAT 3.8979240810 + #> 1859 2068 3M CC03 2018 2018-02-05 NO23 -4.3428059215 #> 1860 2068 3M CC03 2018 2018-02-05 SALIN 3.0587070727 #> 1861 2068 3M CC03 2018 2018-02-05 TKN -0.4780358009 #> 1862 2068 3M CC03 2018 2018-02-05 TN -0.4572848568 + #> 1863 2068 3M CC03 2018 2018-02-05 TP -2.6310891600 #> 1864 2068 3M CC03 2018 2018-02-05 TURB 0.8754687374 #> 1865 2068 3M CC03 2018 2018-03-05 CHLAC 0.6418538862 #> 1866 2068 3M CC03 2018 2018-03-05 COLOR 2.5649493575 #> 1867 2068 3M CC03 2018 2018-03-05 DO 1.5686159179 #> 1868 2068 3M CC03 2018 2018-03-05 DOSAT 4.0517849478 + #> 1869 2068 3M CC03 2018 2018-03-05 NO23 -5.2983173665 I #> 1870 2068 3M CC03 2018 2018-03-05 SALIN 3.4781584228 #> 1871 2068 3M CC03 2018 2018-03-05 TKN -0.5798184953 #> 1872 2068 3M CC03 2018 2018-03-05 TN -0.5727010275 + #> 1873 2068 3M CC03 2018 2018-03-05 TP -2.7488721956 #> 1874 2068 3M CC03 2018 2018-03-05 TURB 2.2407096893 #> 1875 2068 3M CC03 2018 2018-04-02 CHLAC -0.5978370008 U #> 1876 2068 3M CC03 2018 2018-04-02 COLOR 0.9162907319 U #> 1877 2068 3M CC03 2018 2018-04-02 DO 1.2237754316 #> 1878 2068 3M CC03 2018 2018-04-02 DOSAT 3.8877303129 + #> 1879 2068 3M CC03 2018 2018-04-02 NO23 -3.7297014486 #> 1880 2068 3M CC03 2018 2018-04-02 SALIN 3.5553480615 #> 1881 2068 3M CC03 2018 2018-04-02 TKN 1.0296194172 #> 1882 2068 3M CC03 2018 2018-04-02 TN 1.0381543196 + #> 1883 2068 3M CC03 2018 2018-04-02 TP -1.7719568419 #> 1884 2068 3M CC03 2018 2018-04-02 TURB 1.3862943611 #> 1885 2068 3M CC03 2018 2018-05-07 CHLAC 0.4054651081 I #> 1886 2068 3M CC03 2018 2018-05-07 COLOR 2.6390573296 #> 1887 2068 3M CC03 2018 2018-05-07 DO -0.1984509387 #> 1888 2068 3M CC03 2018 2018-05-07 DOSAT 2.5416019935 #> 1889 2068 3M CC03 2018 2018-05-07 NO23 -5.5214609179 U #> 1890 2068 3M CC03 2018 2018-05-07 SALIN 3.6109179126 #> 1891 2068 3M CC03 2018 2018-05-07 TKN -0.6161861394 #> 1892 2068 3M CC03 2018 2018-05-07 TN -0.6124892775 + #> 1893 2068 3M CC03 2018 2018-05-07 TP -2.8824035882 #> 1894 2068 3M CC03 2018 2018-05-07 TURB 0.8754687374 #> 1895 2068 3M CC03 2018 2018-08-06 CHLAC 1.5475625087 #> 1896 2068 3M CC03 2018 2018-08-06 COLOR 3.8918202981 #> 1897 2068 3M CC03 2018 2018-08-06 DO -0.9162907319 #> 1898 2068 3M CC03 2018 2018-08-06 DOSAT 1.8245492921 #> 1899 2068 3M CC03 2018 2018-08-06 NO23 -5.5214609179 I #> 1900 2068 3M CC03 2018 2018-08-06 SALIN 3.3332753652 #> 1901 2068 3M CC03 2018 2018-08-06 TKN 0.2623642645 #> 1902 2068 3M CC03 2018 2018-08-06 TN 0.2654364635 + #> 1903 2068 3M CC03 2018 2018-08-06 TP -2.4191189092 #> 1904 2068 3M CC03 2018 2018-08-06 TURB 1.6486586256 #> 1905 2068 3M CC03 2019 2019-03-04 CHLAC 0.2623642645 I #> 1906 2068 3M CC03 2019 2019-03-04 COLOR 3.6635616461 #> 1907 2068 3M CC03 2019 2019-03-04 DO 1.0919233005 #> 1908 2068 3M CC03 2019 2019-03-04 DOSAT 3.6506582413 #> 1909 2068 3M CC03 2019 2019-03-04 NO23 -5.5214609179 U #> 1910 2068 3M CC03 2019 2019-03-04 SALIN 2.3105532626 #> 1911 2068 3M CC03 2019 2019-03-04 TKN -0.3147107448 #> 1912 2068 3M CC03 2019 2019-03-04 TN -0.3119747650 + #> 1913 2068 3M CC03 2019 2019-03-04 TP -2.3025850930 #> 1914 2068 3M CC03 2019 2019-03-04 TURB 0.8754687374 #> 1915 2068 3M CC03 2019 2019-05-06 CHLAC 1.3862943611 #> 1916 2068 3M CC03 2019 2019-05-06 COLOR 3.4965075615 #> 1917 2068 3M CC03 2019 2019-05-06 DO -1.8325814637 #> 1918 2068 3M CC03 2019 2019-05-06 DOSAT 0.9932517730 #> 1919 2068 3M CC03 2019 2019-05-06 NO23 -5.5214609179 U #> 1920 2068 3M CC03 2019 2019-05-06 SALIN 3.3809946743 #> 1921 2068 3M CC03 2019 2019-05-06 TKN -0.3566749439 #> 1922 2068 3M CC03 2019 2019-05-06 TN -0.3538218750 + #> 1923 2068 3M CC03 2019 2019-05-06 TP -3.0159349809 #> 1924 2068 3M CC03 2019 2019-05-06 TURB 0.6418538862 #> 1925 2068 3M CC03 2019 2019-06-03 CHLAC 1.0986122887 #> 1926 2068 3M CC03 2019 2019-06-03 COLOR 2.9957322736 #> 1927 2068 3M CC03 2019 2019-06-03 DO -0.8675005677 #> 1928 2068 3M CC03 2019 2019-06-03 DOSAT 1.8870696490 #> 1929 2068 3M CC03 2019 2019-06-03 NO23 -5.5214609179 U #> 1930 2068 3M CC03 2019 2019-06-03 SALIN 3.6068556186 #> 1931 2068 3M CC03 2019 2019-06-03 TKN -0.3424903089 #> 1932 2068 3M CC03 2019 2019-06-03 TN -0.3396773676 + #> 1933 2068 3M CC03 2019 2019-06-03 TP -3.0791138825 #> 1934 2068 3M CC03 2019 2019-06-03 TURB 0.9555114450 #> 1935 2068 3M CC03 2019 2019-07-01 CHLAC 1.9740810260 #> 1936 2068 3M CC03 2019 2019-07-01 COLOR 3.2958368660 A #> 1937 2068 3M CC03 2019 2019-07-01 DO -0.5978370008 #> 1938 2068 3M CC03 2019 2019-07-01 DOSAT 2.1517622033 #> 1939 2068 3M CC03 2019 2019-07-01 NO23 -5.5214609179 U #> 1940 2068 3M CC03 2019 2019-07-01 SALIN 3.5160130561 #> 1941 2068 3M CC03 2019 2019-07-01 TKN -0.2613647641 #> 1942 2068 3M CC03 2019 2019-07-01 TN -0.2587707290 + #> 1943 2068 3M CC03 2019 2019-07-01 TP -3.0159349809 #> 1944 2068 3M CC03 2019 2019-07-01 TURB 1.6486586256 A #> 1945 2068 3M CC03 2019 2019-10-07 TN -0.6462635947 + #> 1946 2068 3M CC03 2019 2019-10-07 CHLAC 1.0647107370 I #> 1947 2068 3M CC03 2019 2019-10-07 COLOR 1.9169226122 #> 1948 2068 3M CC03 2019 2019-10-07 DO 0.6931471806 #> 1949 2068 3M CC03 2019 2019-10-07 DOSAT 3.4436180975 #> 1950 2068 3M CC03 2019 2019-10-07 NO23 -5.1159958098 I #> 1951 2068 3M CC03 2019 2019-10-07 SALIN 3.5392186796 #> 1952 2068 3M CC03 2019 2019-10-07 TKN -0.6539264674 #> 1953 2068 3M CC03 2019 2019-10-07 TP -2.5902671654 #> 1954 2068 3M CC03 2019 2019-10-07 TURB 0.7884573604 #> 1955 2068 3M CC03 2019 2019-11-04 CHLAC 1.7227665977 #> 1956 2068 3M CC03 2019 2019-11-04 COLOR 2.8903717579 #> 1957 2068 3M CC03 2019 2019-11-04 DO 0.3646431136 #> 1958 2068 3M CC03 2019 2019-11-04 DOSAT 3.0349529867 #> 1959 2068 3M CC03 2019 2019-11-04 NO23 -4.3428059215 #> 1960 2068 3M CC03 2019 2019-11-04 SALIN 3.6030491975 #> 1961 2068 3M CC03 2019 2019-11-04 TKN -0.3566749439 #> 1962 2068 3M CC03 2019 2019-11-04 TN -0.3382738586 + #> 1963 2068 3M CC03 2019 2019-11-04 TP -2.7488721956 #> 1964 2068 3M CC03 2019 2019-11-04 TURB 1.1631508098 #> 1965 2068 3M CC03 2019 2019-12-02 CHLAC 0.8754687374 I #> 1966 2068 3M CC03 2019 2019-12-02 COLOR 2.1860512767 #> 1967 2068 3M CC03 2019 2019-12-02 DO 1.0367368850 #> 1968 2068 3M CC03 2019 2019-12-02 DOSAT 3.6988297850 #> 1969 2068 3M CC03 2019 2019-12-02 NO23 -4.1997050779 #> 1970 2068 3M CC03 2019 2019-12-02 SALIN 3.4977189487 #> 1971 2068 3M CC03 2019 2019-12-02 TKN -0.4620354596 #> 1972 2068 3M CC03 2019 2019-12-02 TN -0.4385049622 + #> 1973 2068 3M CC03 2019 2019-12-02 TP -2.9187712324 #> 1974 2068 3M CC03 2019 2019-12-02 TURB 0.6418538862 #> 1975 2068 3M CC03 2020 2020-01-06 CHLAC 1.2237754316 #> 1976 2068 3M CC03 2020 2020-01-06 COLOR 3.5263605246 A #> 1977 2068 3M CC03 2020 2020-01-06 DO 1.1184149160 #> 1978 2068 3M CC03 2020 2020-01-06 DOSAT 3.5862928653 #> 1979 2068 3M CC03 2020 2020-01-06 NO23 -4.1997050779 #> 1980 2068 3M CC03 2020 2020-01-06 SALIN 2.7491921444 #> 1981 2068 3M CC03 2020 2020-01-06 TKN 0.0953101798 #> 1982 2068 3M CC03 2020 2020-01-06 TN 0.1088544049 + #> 1983 2068 3M CC03 2020 2020-01-06 TP -2.5510464523 #> 1984 2068 3M CC03 2020 2020-01-06 TURB 1.4350845253 #> 1985 2068 3M CC03 2020 2020-02-03 CHLAC 0.5877866649 I #> 1986 2068 3M CC03 2020 2020-02-03 COLOR 3.3672958300 #> 1987 2068 3M CC03 2020 2020-02-03 DO 1.4011829736 #> 1988 2068 3M CC03 2020 2020-02-03 DOSAT 3.7909846771 #> 1989 2068 3M CC03 2020 2020-02-03 NO23 -4.9618451299 I #> 1990 2068 3M CC03 2020 2020-02-03 SALIN 3.0819099698 #> 1991 2068 3M CC03 2020 2020-02-03 TKN -0.2107210313 #> 1992 2068 3M CC03 2020 2020-02-03 TN -0.2057949130 + #> 1993 2068 3M CC03 2020 2020-02-03 TP -2.7968814148 #> 1994 2068 3M CC03 2020 2020-02-03 TURB 0.5877866649 #> 1995 2068 3M CC03 2020 2020-03-02 CHLAC 0.6931471806 I #> 1996 2068 3M CC03 2020 2020-03-02 COLOR 2.6390573296 #> 1997 2068 3M CC03 2020 2020-03-02 DO 1.4951487660 #> 1998 2068 3M CC03 2020 2020-03-02 DOSAT 4.0360089852 #> 1999 2068 3M CC03 2020 2020-03-02 NO23 -5.2983173665 I #> 2000 2068 3M CC03 2020 2020-03-02 SALIN 3.4600950229 #> 2001 2068 3M CC03 2020 2020-03-02 TKN -0.5108256238 #> 2002 2068 3M CC03 2020 2020-03-02 TN -0.5041810810 + #> 2003 2068 3M CC03 2020 2020-03-02 TP -2.6450754019 #> 2004 2068 3M CC03 2020 2020-03-02 TURB 1.5040773968 #> 2005 2068 3M CC03 2020 2020-09-08 CHLAC 2.7725887222 #> 2006 2068 3M CC03 2020 2020-09-08 COLOR 4.8675344505 #> 2007 2068 3M CC03 2020 2020-09-08 DO 0.4510756194 #> 2008 2068 3M CC03 2020 2020-09-08 DOSAT 3.0155349009 #> 2009 2068 3M CC03 2020 2020-09-08 NO23 -5.5214609179 U #> 2010 2068 3M CC03 2020 2020-09-08 SALIN 1.5151272330 #> 2011 2068 3M CC03 2020 2020-09-08 TKN 0.0953101798 #> 2012 2068 3M CC03 2020 2020-09-08 TN 0.0971267107 + #> 2013 2068 3M CC03 2020 2020-09-08 TP -2.2072749132 #> 2014 2068 3M CC03 2020 2020-09-08 TURB 1.3862943611 #> 2015 2068 3M CC03 2020 2020-10-05 CHLAC 2.0918640617 #> 2016 2068 3M CC03 2020 2020-10-05 COLOR 4.2046926194 #> 2017 2068 3M CC03 2020 2020-10-05 DO 0.4121096508 #> 2018 2068 3M CC03 2020 2020-10-05 DOSAT 3.0587070727 #> 2019 2068 3M CC03 2020 2020-10-05 NO23 -4.7105307016 I #> 2020 2068 3M CC03 2020 2020-10-05 SALIN 3.2027464429 #> 2021 2068 3M CC03 2020 2020-10-05 TKN -0.3147107448 #> 2022 2068 3M CC03 2020 2020-10-05 TN -0.3092462504 + #> 2023 2068 3M CC03 2020 2020-10-05 TP -2.5133061243 #> 2024 2068 3M CC03 2020 2020-10-05 TURB 1.3350010667 #> 2025 2068 3M CC03 2020 2020-11-02 CHLAC 1.4816045409 #> 2026 2068 3M CC03 2020 2020-11-02 COLOR 3.6888794541 #> 2027 2068 3M CC03 2020 2020-11-02 DO 0.6523251860 #> 2028 2068 3M CC03 2020 2020-11-02 DOSAT 3.3428618046 #> 2029 2068 3M CC03 2020 2020-11-02 NO23 -4.7105307016 I #> 2030 2068 3M CC03 2020 2020-11-02 SALIN 3.3721118008 #> 2031 2068 3M CC03 2020 2020-11-02 TKN -0.1984509387 #> 2032 2068 3M CC03 2020 2020-11-02 TN -0.1935847491 + #> 2033 2068 3M CC03 2020 2020-11-02 TP -2.6882475738 #> 2034 2068 3M CC03 2020 2020-11-02 TURB 1.1939224685 #> 2035 2068 3M CC03 2020 2020-12-07 CHLAC 0.4054651081 I #> 2036 2068 3M CC03 2020 2020-12-07 COLOR 3.2958368660 A #> 2037 2068 3M CC03 2020 2020-12-07 DO 1.3480731483 #> 2038 2068 3M CC03 2020 2020-12-07 DOSAT 3.9278963546 #> 2039 2068 3M CC03 2020 2020-12-07 NO23 -3.6119184130 #> 2040 2068 3M CC03 2020 2020-12-07 SALIN 3.3641875560 #> 2041 2068 3M CC03 2020 2020-12-07 TKN -0.5276327421 #> 2042 2068 3M CC03 2020 2020-12-07 TN -0.4828862551 + #> 2043 2068 3M CC03 2020 2020-12-07 TP -2.6036901858 #> 2044 2068 3M CC03 2020 2020-12-07 TURB 0.7419373447 #> 2045 2068 3M CC03 2021 2021-01-04 CHLAC 1.3609765531 #> 2046 2068 3M CC03 2021 2021-01-04 COLOR 3.1780538303 A #> 2047 2068 3M CC03 2021 2021-01-04 DO 0.7701082217 #> 2048 2068 3M CC03 2021 2021-01-04 DOSAT 3.3393219779 #> 2049 2068 3M CC03 2021 2021-01-04 NO23 -4.3428059215 #> 2050 2068 3M CC03 2021 2021-01-04 SALIN 3.2638491905 #> 2051 2068 3M CC03 2021 2021-01-04 TKN -0.4780358009 #> 2052 2068 3M CC03 2021 2021-01-04 TN -0.4572848568 + #> 2053 2068 3M CC03 2021 2021-01-04 TP -2.3025850930 #> 2054 2068 3M CC03 2021 2021-01-04 TURB 0.8329091229 #> 2055 2068 3M CC03 2021 2021-02-01 CHLAC 0.3364722366 I #> 2056 2068 3M CC03 2021 2021-02-01 COLOR 1.9878743482 #> 2057 2068 3M CC03 2021 2021-02-01 DO 1.3454723666 #> 2058 2068 3M CC03 2021 2021-02-01 DOSAT 3.9156165409 #> 2059 2068 3M CC03 2021 2021-02-01 NO23 -4.4228486292 #> 2060 2068 3M CC03 2021 2021-02-01 SALIN 3.4937765630 #> 2061 2068 3M CC03 2021 2021-02-01 TKN -0.7133498879 #> 2062 2068 3M CC03 2021 2021-02-01 TN -0.6891551593 + #> 2063 2068 3M CC03 2021 2021-02-01 TP -2.7646205526 #> 2064 2068 3M CC03 2021 2021-02-01 TURB 1.0647107370 #> 2065 2068 3M CC03 2021 2021-04-05 CHLAC 0.5877866649 I #> 2066 2068 3M CC03 2021 2021-04-05 COLOR 2.5649493575 #> 2067 2068 3M CC03 2021 2021-04-05 DO 0.9932517730 #> 2068 2068 3M CC03 2021 2021-04-05 DOSAT 3.6323091026 #> 2069 2068 3M CC03 2021 2021-04-05 NO23 -5.5214609179 U #> 2070 2068 3M CC03 2021 2021-04-05 SALIN 3.5984075509 #> 2071 2068 3M CC03 2021 2021-04-05 TKN -0.6348782724 #> 2072 2068 3M CC03 2021 2021-04-05 TN -0.6311117896 + #> 2073 2068 3M CC03 2021 2021-04-05 TP -2.9374633654 #> 2074 2068 3M CC03 2021 2021-04-05 TURB 0.9162907319 #> 2075 2068 3M CC03 2021 2021-05-03 CHLAC 0.4054651081 I #> 2076 2068 3M CC03 2021 2021-05-03 COLOR 3.0910424534 A #> 2077 2068 3M CC03 2021 2021-05-03 DO -0.4307829161 #> 2078 2068 3M CC03 2021 2021-05-03 DOSAT 2.3125354238 #> 2079 2068 3M CC03 2021 2021-05-03 NO23 -5.5214609179 U #> 2080 2068 3M CC03 2021 2021-05-03 SALIN 3.5931942040 #> 2081 2068 3M CC03 2021 2021-05-03 TKN -0.6348782724 #> 2082 2068 3M CC03 2021 2021-05-03 TN -0.6311117896 + #> 2083 2068 3M CC03 2021 2021-05-03 TP -3.1010927892 #> 2084 2068 3M CC03 2021 2021-05-03 TURB 1.6094379124 A #> 2085 2068 3M CC03 2021 2021-06-07 CHLAC 0.8754687374 I #> 2086 2068 3M CC03 2021 2021-06-07 COLOR 2.9444389792 #> 2087 2068 3M CC03 2021 2021-06-07 DO -0.4462871026 #> 2088 2068 3M CC03 2021 2021-06-07 DOSAT 2.3418058061 #> 2089 2068 3M CC03 2021 2021-06-07 NO23 -5.5214609179 U #> 2090 2068 3M 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2068 3M CC03 2022 2022-02-07 TN -0.8818893052 + #> 2163 2068 3M CC03 2022 2022-02-07 TP -2.6736487744 #> 2164 2068 3M CC03 2022 2022-02-07 TURB 0.4054651081 #> 2165 2068 3M CC03 2022 2022-03-07 CHLAC 0.7419373447 I #> 2166 2068 3M CC03 2022 2022-03-07 COLOR 2.3025850930 A #> 2167 2068 3M CC03 2022 2022-03-07 DO 0.5306282511 #> 2168 2068 3M CC03 2022 2022-03-07 DOSAT 3.1863526332 #> 2169 2068 3M CC03 2022 2022-03-07 NO23 -5.1159958098 I #> 2170 2068 3M CC03 2022 2022-03-07 SALIN 3.5331024525 #> 2171 2068 3M CC03 2022 2022-03-07 TKN -0.4307829161 #> 2172 2068 3M CC03 2022 2022-03-07 TN -0.4246479275 + #> 2173 2068 3M CC03 2022 2022-03-07 TP -2.8647040111 #> 2174 2068 3M CC03 2022 2022-03-07 TURB 0.9555114450 #> 2175 2068 3M CC03 2022 2022-04-04 CHLAC 0.0000000000 I #> 2176 2068 3M CC03 2022 2022-04-04 COLOR 2.5649493575 #> 2177 2068 3M CC03 2022 2022-04-04 DO -0.2107210313 #> 2178 2068 3M CC03 2022 2022-04-04 DOSAT 2.5416019935 #> 2179 2068 3M CC03 2022 2022-04-04 NO23 -5.1159958098 I #> 2180 2068 3M CC03 2022 2022-04-04 TKN -0.6161861394 #> 2181 2068 3M CC03 2022 2022-04-04 TN -0.6088060321 + #> 2182 2068 3M CC03 2022 2022-04-04 TP -2.9957322736 #> 2183 2068 3M CC03 2022 2022-04-04 TURB 1.0986122887 #> 2184 2068 3M CC03 2022 2022-05-02 CHLAC 0.3364722366 U #> 2185 2068 3M CC03 2022 2022-05-02 DO -0.5108256238 #> 2186 2068 3M CC03 2022 2022-05-02 DOSAT 2.2082744135 #> 2187 2068 3M CC03 2022 2022-05-02 NO23 -5.5214609179 U #> 2188 2068 3M CC03 2022 2022-05-02 SALIN 3.5366020187 #> 2189 2068 3M CC03 2022 2022-05-02 TN -0.5762534291 + #> 2190 2068 3M CC03 2022 2022-06-06 CHLAC 1.7047480922 #> 2191 2068 3M CC03 2022 2022-06-06 COLOR 4.0430512678 #> 2192 2068 3M CC03 2022 2022-06-06 DO -0.4462871026 #> 2193 2068 3M CC03 2022 2022-06-06 DOSAT 2.1972245773 #> 2194 2068 3M CC03 2022 2022-06-06 NO23 -4.6051701860 I #> 2195 2068 3M CC03 2022 2022-06-06 SALIN 2.9210087274 #> 2196 2068 3M CC03 2022 2022-06-06 TKN 0.1823215568 #> 2197 2068 3M CC03 2022 2022-06-06 TN 0.1856493469 + #> 2198 2068 3M CC03 2022 2022-06-06 TP -2.9374633654 #> 2199 2068 3M CC03 2022 2022-06-06 TURB 1.3609765531 #> 2200 2068 3M CC03 2022 2022-07-05 CHLAC 2.0541237337 #> 2201 2068 3M CC03 2022 2022-07-05 COLOR 3.8501476017 A #> 2202 2068 3M CC03 2022 2022-07-05 DO -0.5447271754 #> 2203 2068 3M CC03 2022 2022-07-05 DOSAT 2.1860512767 #> 2204 2068 3M CC03 2022 2022-07-05 NO23 -3.9120230054 #> 2205 2068 3M CC03 2022 2022-07-05 SALIN 3.2327787300 #> 2206 2068 3M CC03 2022 2022-07-05 TKN 0.0953101798 #> 2207 2068 3M CC03 2022 2022-07-05 TN 0.1133286853 + #> 2208 2068 3M CC03 2022 2022-07-05 TP -2.6036901858 #> 2209 2068 3M CC03 2022 2022-07-05 TURB 2.0149030205 #> 2210 2068 3M CC03 2022 2022-08-01 CHLAC 1.8082887712 #> 2211 2068 3M CC03 2022 2022-08-01 COLOR 3.5553480615 A #> 2212 2068 3M CC03 2022 2022-08-01 DO -0.8209805521 #> 2213 2068 3M CC03 2022 2022-08-01 DOSAT 1.9315214116 #> 2214 2068 3M CC03 2022 2022-08-01 NO23 -5.2983173665 I #> 2215 2068 3M CC03 2022 2022-08-01 SALIN 3.3904734183 #> 2216 2068 3M CC03 2022 2022-08-01 TKN -0.3011050928 #> 2217 2068 3M CC03 2022 2022-08-01 TN -0.2957142441 + #> 2218 2068 3M CC03 2022 2022-08-01 TP -2.9004220937 #> 2219 2068 3M CC03 2022 2022-08-01 TURB 1.0296194172 #> 2220 2068 3M CC03 2022 2022-11-07 CHLAC 2.7725887222 #> 2221 2068 3M CC03 2022 2022-11-07 COLOR 3.9889840466 A #> 2222 2068 3M CC03 2022 2022-11-07 DO -0.4462871026 #> 2223 2068 3M CC03 2022 2022-11-07 DOSAT 2.2192034841 #> 2224 2068 3M CC03 2022 2022-11-07 NO23 -5.5214609179 I #> 2225 2068 3M CC03 2022 2022-11-07 SALIN 3.1945831323 #> 2226 2068 3M CC03 2022 2022-11-07 TKN 0.0000000000 #> 2227 2068 3M CC03 2022 2022-11-07 TN 0.0039920213 + #> 2228 2068 3M CC03 2022 2022-11-07 TP -1.5606477483 #> 2229 2068 3M CC03 2022 2022-11-07 TURB 2.7725887222 #> 2230 2068 3M CC03 2022 2022-12-05 CHLAC 2.7725887222 #> 2231 2068 3M CC03 2022 2022-12-05 COLOR 4.0430512678 #> 2232 2068 3M CC03 2022 2022-12-05 DO 0.5766133643 #> 2233 2068 3M CC03 2022 2022-12-05 DOSAT 3.1863526332 #> 2234 2068 3M CC03 2022 2022-12-05 NO23 -5.5214609179 U #> 2235 2068 3M CC03 2022 2022-12-05 SALIN 3.0223742045 #> 2236 2068 3M CC03 2022 2022-12-05 TKN -0.1625189295 #> 2237 2068 3M CC03 2022 2022-12-05 TN -0.1601687522 + #> 2238 2068 3M CC03 2022 2022-12-05 TP -1.1394342832 #> 2239 2068 3M CC03 2022 2022-12-05 TURB 1.5040773968 #> 2240 2068 3M CC03 2023 2023-01-03 CHLAC 1.6486586256 #> 2241 2068 3M CC03 2023 2023-01-03 COLOR 4.0604430105 #> 2242 2068 3M CC03 2023 2023-01-03 DO 0.7080357931 #> 2243 2068 3M CC03 2023 2023-01-03 DOSAT 3.2884018875 #> 2244 2068 3M CC03 2023 2023-01-03 NO23 -4.2686979494 #> 2245 2068 3M CC03 2023 2023-01-03 TKN -0.0512932944 #> 2246 2068 3M CC03 2023 2023-01-03 TN -0.0366639844 + #> 2247 2068 3M CC03 2023 2023-01-03 TP -0.7133498879 #> 2248 2068 3M CC03 2023 2023-01-03 TURB 0.3364722366 #> 2249 2068 3M CC03 2023 2023-02-06 CHLAC 1.6292405397 #> 2250 2068 3M CC03 2023 2023-02-06 COLOR 2.7080502011 A #> 2251 2068 3M CC03 2023 2023-02-06 DO 1.2781522025 #> 2252 2068 3M CC03 2023 2023-02-06 DOSAT 3.8958936235 #> 2253 2068 3M CC03 2023 2023-02-06 NO23 -4.6051701860 I #> 2254 2068 3M CC03 2023 2023-02-06 SALIN 3.4404180948 #> 2255 2068 3M CC03 2023 2023-02-06 TKN -0.3566749439 #> 2256 2068 3M CC03 2023 2023-02-06 TN -0.3509769228 + #> 2257 2068 3M CC03 2023 2023-02-06 TP -2.2072749132 #> 2258 2068 3M CC03 2023 2023-02-06 TURB 1.1314021115 #> 2259 2068 3M CC03 2023 2023-03-06 DO 0.1570037488 #> 2260 2068 3M CC03 2023 2023-03-06 DOSAT 2.8791984573 #> 2261 2068 3M CC03 2023 2023-03-06 SALIN 3.5962157693 #> 2262 2068 3M CC03 2018 2018-03-13 CHLAC 0.9555114450 #> 2263 2068 3M CC03 2018 2018-03-13 COND 10.8817948782 #> 2264 2068 3M CC03 2018 2018-03-13 DO 2.0794415417 #> 2265 2068 3M CC03 2018 2018-03-13 DOSAT 4.6812048723 #> 2266 2068 3M CC03 2018 2018-03-13 NO23 -4.7105307016 I #> 2267 2068 3M CC03 2018 2018-03-13 SALIN 3.6778185068 + #> 2268 2068 3M CC03 2018 2018-03-13 TKN -0.4942963218 #> 2269 2068 3M CC03 2018 2018-03-13 TN -0.4877603508 + #> 2270 2068 3M CC03 2018 2018-03-13 TP -2.4191189092 #> 2271 2068 3M CC03 2018 2018-03-13 TSS 1.3862943611 I #> 2272 2068 3M CC03 2018 2018-03-13 TURB 1.0647107370 #> 2273 2068 3M CC03 2018 2018-05-08 CHLAC 1.1631508098 #> 2274 2068 3M CC03 2018 2018-05-08 COND 10.9254527508 #> 2275 2068 3M CC03 2018 2018-05-08 DO 1.4973884086 #> 2276 2068 3M CC03 2018 2018-05-08 DOSAT 4.2091602367 #> 2277 2068 3M CC03 2018 2018-05-08 NO23 -5.5214609179 U #> 2278 2068 3M CC03 2018 2018-05-08 SALIN 3.5973122606 + #> 2279 2068 3M CC03 2018 2018-05-08 TKN -0.5108256238 #> 2280 2068 3M CC03 2018 2018-05-08 TN -0.5074978337 + #> 2281 2068 3M CC03 2018 2018-05-08 TP -3.2441936329 #> 2282 2068 3M CC03 2018 2018-05-08 TSS 2.0794415417 I #> 2283 2068 3M CC03 2018 2018-05-08 TURB 1.3083328197 #> 2284 2068 3M CC03 2018 2018-06-26 CHLAC 2.4849066498 #> 2285 2068 3M CC03 2018 2018-06-26 COND 10.7823463704 #> 2286 2068 3M CC03 2018 2018-06-26 DO 1.1118575154 #> 2287 2068 3M CC03 2018 2018-06-26 DOSAT 3.8628327612 #> 2288 2068 3M CC03 2018 2018-06-26 NO23 -5.5214609179 U #> 2289 2068 3M CC03 2018 2018-06-26 SALIN 3.3414473773 + #> 2290 2068 3M CC03 2018 2018-06-26 TKN -0.4155154440 #> 2291 2068 3M CC03 2018 2018-06-26 TN -0.4124897230 + #> 2292 2068 3M CC03 2018 2018-06-26 TSS 2.0794415417 I #> 2293 2068 3M CC03 2018 2018-06-26 TURB 1.4816045409 #> 2294 2068 3M CC03 2018 2018-09-18 CHLAC 2.2617630985 #> 2295 2068 3M CC03 2018 2018-09-18 COND 9.9966590834 #> 2296 2068 3M CC03 2018 2018-09-18 DO 0.8020015855 #> 2297 2068 3M CC03 2018 2018-09-18 DOSAT 3.4812400893 #> 2298 2068 3M CC03 2018 2018-09-18 NO23 -4.7105307016 I #> 2299 2068 3M CC03 2018 2018-09-18 TKN -0.0833816089 #> 2300 2068 3M CC03 2018 2018-09-18 TN -0.0790432073 + #> 2301 2068 3M CC03 2018 2018-09-18 TP -2.3227878003 #> 2302 2068 3M CC03 2018 2018-09-18 TSS 1.0986122887 U #> 2303 2068 3M CC03 2018 2018-09-18 TURB 1.2809338455 A #> 2304 2068 3M CC03 2018 2018-12-04 CHLAC 1.6486586256 #> 2305 2068 3M CC03 2018 2018-12-04 COND 10.7489265434 #> 2306 2068 3M CC03 2018 2018-12-04 DO 1.5644405465 #> 2307 2068 3M CC03 2018 2018-12-04 DOSAT 4.2239097666 #> 2308 2068 3M CC03 2018 2018-12-04 NO23 -1.8971199849 G #> 2309 2068 3M CC03 2018 2018-12-04 SALIN 3.4094961845 #> 2310 2068 3M CC03 2018 2018-12-04 TKN -0.3285040670 #> 2311 2068 3M CC03 2018 2018-12-04 TN -0.1392620673 + #> 2312 2068 3M CC03 2018 2018-12-04 TP -2.6450754019 #> 2313 2068 3M CC03 2018 2018-12-04 TSS 2.1972245773 I #> 2314 2068 3M CC03 2018 2018-12-04 TURB 0.5306282511 #> 2315 2078A 2 CC04 2019 2019-08-13 CHLAC 3.1780538303 #> 2316 2078A 2 CC04 2019 2019-08-13 COND 9.8642788393 #> 2317 2078A 2 CC04 2019 2019-08-13 DO 1.7647307968 #> 2318 2078A 2 CC04 2019 2019-08-13 DOSAT 4.4176350621 #> 2319 2078A 2 CC04 2019 2019-08-13 NO23 -5.2983173665 I #> 2320 2078A 2 CC04 2019 2019-08-13 SALIN 2.4274540750 #> 2321 2078A 2 CC04 2019 2019-08-13 TKN 0.3364722366 #> 2322 2078A 2 CC04 2019 2019-08-13 TN 0.3393253056 + #> 2323 2078A 2 CC04 2019 2019-08-13 TP -2.9759296463 #> 2324 2078A 2 CC04 2019 2019-08-13 TSS 1.6094379124 I #> 2325 2078A 2 CC04 2019 2019-08-13 TURB 0.7419373447 #> 2326 2078B 2 CC05 2019 2019-01-17 COND 10.7433722892 #> 2327 2078B 2 CC05 2019 2019-01-17 DO 1.9065751437 #> 2328 2078B 2 CC05 2019 2019-01-17 DOSAT 4.4030540019 #> 2329 2078B 2 CC05 2019 2019-01-17 SALIN 3.4045251718 #> 2330 2078B 2 CC05 2019 2019-01-17 TN -0.3827256211 + #> 2331 2078B 2 CC05 2019 2019-01-24 CHLAC 0.2623642645 I #> 2332 2078B 2 CC05 2019 2019-01-24 COND 10.7763069502 #> 2333 2078B 2 CC05 2019 2019-01-24 DO 1.8702625307 #> 2334 2078B 2 CC05 2019 2019-01-24 DOSAT 4.4531838290 #> 2335 2078B 2 CC05 2019 2019-01-24 NO23 -5.1159958098 I #> 2336 2078B 2 CC05 2019 2019-01-24 SALIN 3.4413791713 #> 2337 2078B 2 CC05 2019 2019-01-24 TKN -0.7985076962 #> 2338 2078B 2 CC05 2019 2019-01-24 TN -0.7896580809 + #> 2339 2078B 2 CC05 2019 2019-01-24 TP -3.5065578973 #> 2340 2078B 2 CC05 2019 2019-01-24 TSS 1.0986122887 I #> 2341 2078B 2 CC05 2019 2019-01-24 TURB 0.2623642645 #> 2342 2078B 2 CC05 2019 2019-03-12 CHLAC 1.2809338455 #> 2343 2078B 2 CC05 2019 2019-03-12 COND 10.4768935315 #> 2344 2078B 2 CC05 2019 2019-03-12 DO 1.6992786164 #> 2345 2078B 2 CC05 2019 2019-03-12 DOSAT 4.3412046402 #> 2346 2078B 2 CC05 2019 2019-03-12 NO23 -5.5214609179 U #> 2347 2078B 2 CC05 2019 2019-03-12 SALIN 3.1059310659 #> 2348 2078B 2 CC05 2019 2019-03-12 TKN -0.3424903089 #> 2349 2078B 2 CC05 2019 2019-03-12 TN -0.3396773676 + #> 2350 2078B 2 CC05 2019 2019-03-12 TP -3.2441936329 #> 2351 2078B 2 CC05 2019 2019-03-12 TSS 2.1972245773 I #> 2352 2078B 2 CC05 2019 2019-03-12 TURB 0.6931471806 #> 2353 2078B 2 CC05 2019 2019-04-16 CHLAC 1.4816045409 #> 2354 2078B 2 CC05 2019 2019-04-16 COND 10.7360705353 #> 2355 2078B 2 CC05 2019 2019-04-16 DO 1.6505798558 #> 2356 2078B 2 CC05 2019 2019-04-16 DOSAT 4.3094559418 #> 2357 2078B 2 CC05 2019 2019-04-16 NO23 -5.5214609179 U #> 2358 2078B 2 CC05 2019 2019-04-16 SALIN 3.3951793093 #> 2359 2078B 2 CC05 2019 2019-04-16 TKN -0.2484613593 #> 2360 2078B 2 CC05 2019 2019-04-16 TN -0.2459005384 + #> 2361 2078B 2 CC05 2019 2019-04-16 TP -3.7722610631 #> 2362 2078B 2 CC05 2019 2019-04-16 TSS 1.6094379124 I #> 2363 2078B 2 CC05 2019 2019-04-16 TURB 0.6418538862 #> 2364 2078B 2 CC05 2019 2019-06-11 CHLAC 1.1314021115 #> 2365 2078B 2 CC05 2019 2019-06-11 COND 10.8909447918 #> 2366 2078B 2 CC05 2019 2019-06-11 DO 1.2059708070 #> 2367 2078B 2 CC05 2019 2019-06-11 DOSAT 4.0127729085 #> 2368 2078B 2 CC05 2019 2019-06-11 NO23 -5.5214609179 I #> 2369 2078B 2 CC05 2019 2019-06-11 SALIN 3.5635996377 #> 2370 2078B 2 CC05 2019 2019-06-11 TKN -0.3285040670 #> 2371 2078B 2 CC05 2019 2019-06-11 TN -0.3229638866 + #> 2372 2078B 2 CC05 2019 2019-06-11 TP -3.3242363405 #> 2373 2078B 2 CC05 2019 2019-06-11 TSS 1.0986122887 U #> 2374 2078B 2 CC05 2019 2019-06-11 TURB 0.3364722366 #> 2375 2078B 2 CC05 2019 2019-08-13 CHLAC 2.8332133441 #> 2376 2078B 2 CC05 2019 2019-08-13 COND 10.2219412837 #> 2377 2078B 2 CC05 2019 2019-08-13 DO 1.4036429995 #> 2378 2078B 2 CC05 2019 2019-08-13 DOSAT 4.0926765051 #> 2379 2078B 2 CC05 2019 2019-08-13 NO23 -4.6051701860 I #> 2380 2078B 2 CC05 2019 2019-08-13 SALIN 2.8195915758 #> 2381 2078B 2 CC05 2019 2019-08-13 TKN 0.6418538862 #> 2382 2078B 2 CC05 2019 2019-08-13 TN 0.6439569364 + #> 2383 2078B 2 CC05 2019 2019-08-13 TP -2.9759296463 #> 2384 2078B 2 CC05 2019 2019-08-13 TSS 1.7917594692 I #> 2385 2078B 2 CC05 2019 2019-08-13 TURB 0.7884573604 #> 2386 2078B 2 CC05 2019 2019-08-13 COND 10.3244650523 #> 2387 2078B 2 CC05 2019 2019-08-13 DO 1.0543120298 #> 2388 2078B 2 CC05 2019 2019-08-13 DOSAT 3.7541989202 #> 2389 2078B 2 CC05 2019 2019-08-13 SALIN 2.9322598506 #> 2390 2078B 2 CC05 2019 2019-10-01 COND 10.7304660807 #> 2391 2078B 2 CC05 2019 2019-10-01 DO 1.5644405465 #> 2392 2078B 2 CC05 2019 2019-10-01 DOSAT 4.2724907476 #> 2393 2078B 2 CC05 2019 2019-10-01 SALIN 3.3864220961 #> 2394 2078B 2 CC05 2019 2019-11-04 COND 10.7792062586 #> 2395 2078B 2 CC05 2019 2019-11-04 DO 1.5151272330 #> 2396 2078B 2 CC05 2019 2019-11-04 DOSAT 4.2061840440 #> 2397 2078B 2 CC05 2019 2019-11-04 SALIN 3.4423393250 #> 2398 2078B 2 CC05 2019 2019-11-19 CHLAC 2.6390573296 #> 2399 2078B 2 CC05 2019 2019-11-19 COND 10.8493565039 #> 2400 2078B 2 CC05 2019 2019-11-19 DO 2.0135687975 #> 2401 2078B 2 CC05 2019 2019-11-19 DOSAT 4.6298627986 #> 2402 2078B 2 CC05 2019 2019-11-19 NO23 -5.5214609179 U #> 2403 2078B 2 CC05 2019 2019-11-19 SALIN 3.5234150144 #> 2404 2078B 2 CC05 2019 2019-11-19 TKN -0.3011050928 #> 2405 2078B 2 CC05 2019 2019-11-19 TN -0.2984060358 + #> 2406 2078B 2 CC05 2019 2019-11-19 TP -2.8302178351 #> 2407 2078B 2 CC05 2019 2019-11-19 TSS 2.0794415417 I #> 2408 2078B 2 CC05 2019 2019-11-19 TURB 1.0296194172 A #> 2409 2078B 2 CC05 2020 2020-02-13 CHLAC 2.1400661635 A #> 2410 2078B 2 CC05 2020 2020-02-13 COND 10.7287588860 #> 2411 2078B 2 CC05 2020 2020-02-13 DO 1.8961194846 #> 2412 2078B 2 CC05 2020 2020-02-13 DOSAT 4.5747109785 #> 2413 2078B 2 CC05 2020 2020-02-13 NO23 -5.5214609179 U #> 2414 2078B 2 CC05 2020 2020-02-13 SALIN 3.3857452771 #> 2415 2078B 2 CC05 2020 2020-02-13 TKN -0.3424903089 #> 2416 2078B 2 CC05 2020 2020-02-13 TN -0.3396773676 + #> 2417 2078B 2 CC05 2020 2020-02-13 TP -3.3242363405 #> 2418 2078B 2 CC05 2020 2020-02-13 TSS 2.2617630985 I #> 2419 2078B 2 CC05 2020 2020-02-13 TURB 1.0296194172 #> 2420 2078B 2 CC05 2020 2020-03-24 CHLAC 2.2617630985 #> 2421 2078B 2 CC05 2020 2020-03-24 COND 10.9026109427 #> 2422 2078B 2 CC05 2020 2020-03-24 DO 1.8357763546 #> 2423 2078B 2 CC05 2020 2020-03-24 DOSAT 4.5900565482 #> 2424 2078B 2 CC05 2020 2020-03-24 NO23 -5.5214609179 U #> 2425 2078B 2 CC05 2020 2020-03-24 SALIN 3.5787855313 #> 2426 2078B 2 CC05 2020 2020-03-24 TKN -0.6161861394 #> 2427 2078B 2 CC05 2020 2020-03-24 TN -0.6124892775 + #> 2428 2078B 2 CC05 2020 2020-03-24 TP -2.5902671654 #> 2429 2078B 2 CC05 2020 2020-03-24 TSS 2.4849066498 A #> 2430 2078B 2 CC05 2020 2020-03-24 TURB 1.0647107370 #> 2431 2078B 2 CC05 2020 2020-06-15 CHLAC 2.8332133441 #> 2432 2078B 2 CC05 2020 2020-06-15 COND 10.3780433051 #> 2433 2078B 2 CC05 2020 2020-06-15 DO 1.2325602612 #> 2434 2078B 2 CC05 2020 2020-06-15 DOSAT 3.9199911751 #> 2435 2078B 2 CC05 2020 2020-06-15 NO23 -5.5214609179 I #> 2436 2078B 2 CC05 2020 2020-06-15 SALIN 2.9907197317 #> 2437 2078B 2 CC05 2020 2020-06-15 TKN 0.1823215568 #> 2438 2078B 2 CC05 2020 2020-06-15 TN 0.1856493469 + #> 2439 2078B 2 CC05 2020 2020-06-15 TP -3.0159349809 #> 2440 2078B 2 CC05 2020 2020-06-15 TSS 1.6094379124 I #> 2441 2078B 2 CC05 2020 2020-06-15 TURB 0.9932517730 #> 2442 2078B 2 CC05 2020 2020-07-27 CHLAC 2.5649493575 A #> 2443 2078B 2 CC05 2020 2020-07-27 COND 10.7499993898 #> 2444 2078B 2 CC05 2020 2020-07-27 DO 1.4422019931 #> 2445 2078B 2 CC05 2020 2020-07-27 DOSAT 4.2150861799 #> 2446 2078B 2 CC05 2020 2020-07-27 NO23 -5.5214609179 U #> 2447 2078B 2 CC05 2020 2020-07-27 SALIN 3.4041928906 #> 2448 2078B 2 CC05 2020 2020-07-27 TKN -0.3424903089 #> 2449 2078B 2 CC05 2020 2020-07-27 TN -0.3396773676 + #> 2450 2078B 2 CC05 2020 2020-07-27 TP -3.1010927892 #> 2451 2078B 2 CC05 2020 2020-07-27 TSS 1.6094379124 I #> 2452 2078B 2 CC05 2020 2020-07-27 TURB 1.1631508098 #> 2453 2078B 2 CC05 2020 2020-08-26 CHLAC 2.8903717579 #> 2454 2078B 2 CC05 2020 2020-08-26 COND 10.1730947543 #> 2455 2078B 2 CC05 2020 2020-08-26 DO 1.5062971535 #> 2456 2078B 2 CC05 2020 2020-08-26 DOSAT 4.1972019477 #> 2457 2078B 2 CC05 2020 2020-08-26 NO23 -5.5214609179 U #> 2458 2078B 2 CC05 2020 2020-08-26 SALIN 2.7625383864 #> 2459 2078B 2 CC05 2020 2020-08-26 TKN -0.0618754037 #> 2460 2078B 2 CC05 2020 2020-08-26 TN -0.0597500044 + #> 2461 2078B 2 CC05 2020 2020-08-26 TP -2.9565115604 #> 2462 2078B 2 CC05 2020 2020-08-26 TSS 1.7917594692 I #> 2463 2078B 2 CC05 2020 2020-08-26 TURB 1.0647107370 #> 2464 2078B 2 CC05 2021 2021-01-14 CHLAC 0.9162907319 #> 2465 2078B 2 CC05 2021 2021-01-14 COND 10.6789517756 #> 2466 2078B 2 CC05 2021 2021-01-14 DO 1.7422190237 #> 2467 2078B 2 CC05 2021 2021-01-14 DOSAT 4.2427645673 #> 2468 2078B 2 CC05 2021 2021-01-14 NO23 -4.6051701860 #> 2469 2078B 2 CC05 2021 2021-01-14 SALIN 3.3339886320 #> 2470 2078B 2 CC05 2021 2021-01-14 TKN -0.6348782724 #> 2471 2078B 2 CC05 2021 2021-01-14 TN -0.6161861394 + #> 2472 2078B 2 CC05 2021 2021-01-14 TP -3.4420193762 #> 2473 2078B 2 CC05 2021 2021-01-14 TSS 1.0986122887 I #> 2474 2078B 2 CC05 2021 2021-01-14 TURB 0.5306282511 #> 2475 2078B 2 CC05 2021 2021-02-24 COND 10.7448823096 #> 2476 2078B 2 CC05 2021 2021-02-24 DO 1.5518087996 #> 2477 2078B 2 CC05 2021 2021-02-24 DOSAT 4.1987045775 #> 2478 2078B 2 CC05 2021 2021-02-24 NO23 -4.6051701860 I #> 2479 2078B 2 CC05 2021 2021-02-24 SALIN 3.4061849232 #> 2480 2078B 2 CC05 2021 2021-02-24 TKN -0.8915981193 #> 2481 2078B 2 CC05 2021 2021-02-24 TN -0.8818893052 + #> 2482 2078B 2 CC05 2021 2021-02-24 TP -3.2441936329 #> 2483 2078B 2 CC05 2021 2021-02-24 TSS 1.0986122887 I #> 2484 2078B 2 CC05 2021 2021-03-23 CHLAC 1.1939224685 #> 2485 2078B 2 CC05 2021 2021-03-23 COND 10.8800451952 #> 2486 2078B 2 CC05 2021 2021-03-23 DO 1.7783364489 #> 2487 2078B 2 CC05 2021 2021-03-23 DOSAT 4.4042772436 #> 2488 2078B 2 CC05 2021 2021-03-23 NO23 -4.9618451299 I #> 2489 2078B 2 CC05 2021 2021-03-23 SALIN 3.5579161896 #> 2490 2078B 2 CC05 2021 2021-03-23 TKN -0.5447271754 #> 2491 2078B 2 CC05 2021 2021-03-23 TN -0.5378542962 + #> 2492 2078B 2 CC05 2021 2021-03-23 TP -2.8134107168 #> 2493 2078B 2 CC05 2021 2021-03-23 TSS 2.4849066498 #> 2494 2078B 2 CC05 2021 2021-03-23 TURB 1.6863989536 #> 2495 2078B 2 CC05 2021 2021-07-28 CHLAC 2.5649493575 #> 2496 2078B 2 CC05 2021 2021-07-28 COND 10.0731881321 #> 2497 2078B 2 CC05 2021 2021-07-28 DO 0.9001613499 #> 2498 2078B 2 CC05 2021 2021-07-28 DOSAT 3.6027767551 #> 2499 2078B 2 CC05 2021 2021-07-28 NO23 -5.5214609179 U #> 2500 2078B 2 CC05 2021 2021-07-28 SALIN 2.6665335209 #> 2501 2078B 2 CC05 2021 2021-07-28 TKN 0.0000000000 #> 2502 2078B 2 CC05 2021 2021-07-28 TN 0.0019980027 + #> 2503 2078B 2 CC05 2021 2021-07-28 TP -3.1010927892 #> 2504 2078B 2 CC05 2021 2021-07-28 TSS 1.3862943611 I #> 2505 2078B 2 CC05 2021 2021-07-28 TURB 1.0296194172 #> 2506 2078B 2 CC05 2021 2021-08-26 CHLAC 2.4849066498 #> 2507 2078B 2 CC05 2021 2021-08-26 COND 10.2519942268 #> 2508 2078B 2 CC05 2021 2021-08-26 DO 1.3737155789 #> 2509 2078B 2 CC05 2021 2021-08-26 DOSAT 4.0324691585 #> 2510 2078B 2 CC05 2021 2021-08-26 NO23 -5.5214609179 U #> 2511 2078B 2 CC05 2021 2021-08-26 SALIN 2.8553201198 #> 2512 2078B 2 CC05 2021 2021-08-26 TKN -0.2231435513 #> 2513 2078B 2 CC05 2021 2021-08-26 TN -0.2206466711 + #> 2514 2078B 2 CC05 2021 2021-08-26 TP -2.8134107168 #> 2515 2078B 2 CC05 2021 2021-08-26 TSS 1.9459101491 I #> 2516 2078B 2 CC05 2021 2021-08-26 TURB 0.8754687374 #> 2517 2078B 2 CC05 2021 2021-09-13 CHLAC 2.5649493575 #> 2518 2078B 2 CC05 2021 2021-09-13 COND 10.4619312252 #> 2519 2078B 2 CC05 2021 2021-09-13 DO 1.4929040962 #> 2520 2078B 2 CC05 2021 2021-09-13 DOSAT 4.2091602367 #> 2521 2078B 2 CC05 2021 2021-09-13 NO23 -5.5214609179 U #> 2522 2078B 2 CC05 2021 2021-09-13 SALIN 3.0842009215 #> 2523 2078B 2 CC05 2021 2021-09-13 TKN -0.0943106795 #> 2524 2078B 2 CC05 2021 2021-09-13 TN -0.0921152889 + #> 2525 2078B 2 CC05 2021 2021-09-13 TP -2.9565115604 #> 2526 2078B 2 CC05 2021 2021-09-13 TSS 2.0794415417 I #> 2527 2078B 2 CC05 2021 2021-09-13 TURB 1.0986122887 A #> 2528 2078B 2 CC05 2022 2022-04-19 CHLAC 2.3978952728 #> 2529 2078B 2 CC05 2022 2022-04-19 COND 10.9594532665 #> 2530 2078B 2 CC05 2022 2022-04-19 DO 1.6486586256 #> 2531 2078B 2 CC05 2022 2022-04-19 DOSAT 4.3845235149 #> 2532 2078B 2 CC05 2022 2022-04-19 NO23 -5.5214609179 U #> 2533 2078B 2 CC05 2022 2022-04-19 SALIN 3.6449275666 #> 2534 2078B 2 CC05 2022 2022-04-19 TKN -0.4462871026 #> 2535 2078B 2 CC05 2022 2022-04-19 TN -0.4431669753 + #> 2536 2078B 2 CC05 2022 2022-04-19 TP -2.6592600369 #> 2537 2078B 2 CC05 2022 2022-04-19 TSS 3.0910424534 #> 2538 2078B 2 CC05 2022 2022-04-19 TURB 1.5892352051 A #> 2539 2078B 2 CC05 2022 2022-05-10 CHLAC 1.9021075264 #> 2540 2078B 2 CC05 2022 2022-05-10 COND 10.8257603561 #> 2541 2078B 2 CC05 2022 2022-05-10 DO 1.6114359151 #> 2542 2078B 2 CC05 2022 2022-05-10 DOSAT 4.3148178850 #> 2543 2078B 2 CC05 2022 2022-05-10 NO23 -5.5214609179 U #> 2544 2078B 2 CC05 2022 2022-05-10 SALIN 3.4943840964 #> 2545 2078B 2 CC05 2022 2022-05-10 TKN -0.1984509387 #> 2546 2078B 2 CC05 2022 2022-05-10 TN -0.1960148839 + #> 2547 2078B 2 CC05 2022 2022-05-10 TP -2.6450754019 #> 2548 2078B 2 CC05 2022 2022-05-10 TSS 2.1972245773 I #> 2549 2078B 2 CC05 2022 2022-05-10 TURB 1.6486586256 #> 2550 2078B 2 CC05 2022 2022-09-20 CHLAC 2.2082744135 #> 2551 2078B 2 CC05 2022 2022-09-20 COND 10.0045990539 #> 2552 2078B 2 CC05 2022 2022-09-20 DO 0.9001613499 #> 2553 2078B 2 CC05 2022 2022-09-20 DOSAT 3.5695326965 #> 2554 2078B 2 CC05 2022 2022-09-20 NO23 -5.5214609179 U #> 2555 2078B 2 CC05 2022 2022-09-20 SALIN 2.5832425505 #> 2556 2078B 2 CC05 2022 2022-09-20 TKN 0.0953101798 #> 2557 2078B 2 CC05 2022 2022-09-20 TN 0.0971267107 + #> 2558 2078B 2 CC05 2022 2022-09-20 TP -2.7333680091 #> 2559 2078B 2 CC05 2022 2022-09-20 TSS 1.3862943611 I #> 2560 2078B 2 CC05 2022 2022-09-20 TURB 0.4054651081 A #> 2561 2078B 2 CC05 2022 2022-10-31 CHLAC 2.7725887222 #> 2562 2078B 2 CC05 2022 2022-10-31 COND 10.6157508503 #> 2563 2078B 2 CC05 2022 2022-10-31 DO 1.1505720276 #> 2564 2078B 2 CC05 2022 2022-10-31 DOSAT 3.8329797981 #> 2565 2078B 2 CC05 2022 2022-10-31 NO23 -5.5214609179 U #> 2566 2078B 2 CC05 2022 2022-10-31 SALIN 3.2584810795 #> 2567 2078B 2 CC05 2022 2022-10-31 TKN -1.8325814637 U #> 2568 2078B 2 CC05 2022 2022-10-31 TN -2.5010360317 + #> 2569 2078B 2 CC05 2022 2022-10-31 TP -2.9374633654 #> 2570 2078B 2 CC05 2022 2022-10-31 TSS 1.7917594692 I #> 2571 2078B 2 CC05 2022 2022-10-31 TURB 1.2237754316 #> 2572 2078B 2 CC05 2021 2021-03-23 CHLAC 1.5892352051 #> 2573 2078B 2 CC05 2021 2021-03-23 COND 10.8660128047 #> 2574 2078B 2 CC05 2021 2021-03-23 DO 2.0162354658 #> 2575 2078B 2 CC05 2021 2021-03-23 DOSAT 4.6802776585 #> 2576 2078B 2 CC05 2021 2021-03-23 NO23 -5.5214609179 U #> 2577 2078B 2 CC05 2021 2021-03-23 SALIN 3.5415388662 #> 2578 2078B 2 CC05 2021 2021-03-23 TKN 0.0953101798 #> 2579 2078B 2 CC05 2021 2021-03-23 TN 0.0971267107 + #> 2580 2078B 2 CC05 2021 2021-03-23 TP -3.2968373663 #> 2581 2078B 2 CC05 2021 2021-03-23 TSS 1.0986122887 I #> 2582 2078B 2 CC05 2021 2021-03-23 TURB 0.7884573604 #> 2583 2078B 2 CC05 2021 2021-07-28 CHLAC 1.5686159179 I #> 2584 2078B 2 CC05 2021 2021-07-28 COND 9.6616070559 #> 2585 2078B 2 CC05 2021 2021-07-28 DO -0.3566749439 #> 2586 2078B 2 CC05 2021 2021-07-28 DOSAT 2.3418058061 #> 2587 2078B 2 CC05 2021 2021-07-28 NO23 -5.5214609179 U #> 2588 2078B 2 CC05 2021 2021-07-28 SALIN 2.2049722641 #> 2589 2078B 2 CC05 2021 2021-07-28 TKN 0.0953101798 #> 2590 2078B 2 CC05 2021 2021-07-28 TN 0.0971267107 + #> 2591 2078B 2 CC05 2021 2021-07-28 TP -3.3242363405 #> 2592 2078B 2 CC05 2021 2021-07-28 TSS 1.0986122887 U #> 2593 2078B 2 CC05 2021 2021-07-28 TURB 0.5306282511 #> 2594 2078B 2 CC05 2021 2021-08-26 CHLAC 2.5649493575 #> 2595 2078B 2 CC05 2021 2021-08-26 COND 9.7645702533 #> 2596 2078B 2 CC05 2021 2021-08-26 DO 0.7030975114 #> 2597 2078B 2 CC05 2021 2021-08-26 DOSAT 3.3141860047 #> 2598 2078B 2 CC05 2021 2021-08-26 NO23 -5.5214609179 U #> 2599 2078B 2 CC05 2021 2021-08-26 SALIN 2.3223877203 #> 2600 2078B 2 CC05 2021 2021-08-26 TKN 0.2623642645 #> 2601 2078B 2 CC05 2021 2021-08-26 TN 0.2639015438 + #> 2602 2078B 2 CC05 2021 2021-08-26 TP -2.9565115604 #> 2603 2078B 2 CC05 2021 2021-08-26 TSS 2.3025850930 I #> 2604 2078B 2 CC05 2021 2021-08-26 TURB 2.3978952728 #> 2605 2078B 2 CC05 2021 2021-09-13 CHLAC 2.8332133441 A #> 2606 2078B 2 CC05 2021 2021-09-13 COND 10.1916695000 #> 2607 2078B 2 CC05 2021 2021-09-13 DO 1.2296405511 #> 2608 2078B 2 CC05 2021 2021-09-13 DOSAT 3.9239515763 #> 2609 2078B 2 CC05 2021 2021-09-13 NO23 -5.5214609179 U #> 2610 2078B 2 CC05 2021 2021-09-13 SALIN 2.7868613815 #> 2611 2078B 2 CC05 2021 2021-09-13 TKN 0.0953101798 #> 2612 2078B 2 CC05 2021 2021-09-13 TN 0.0971267107 + #> 2613 2078B 2 CC05 2021 2021-09-13 TP -2.9957322736 #> 2614 2078B 2 CC05 2021 2021-09-13 TSS 1.6094379124 I #> 2615 2078B 2 CC05 2021 2021-09-13 TURB 1.7578579176 #> 2616 2078B 2 CC05 2021 2021-10-20 CHLAC 2.7725887222 #> 2617 2078B 2 CC05 2021 2021-10-20 COND 10.4756810512 #> 2618 2078B 2 CC05 2021 2021-10-20 DO 0.2700271372 #> 2619 2078B 2 CC05 2021 2021-10-20 DOSAT 2.9391619221 #> 2620 2078B 2 CC05 2021 2021-10-20 NO23 -5.5214609179 U #> 2621 2078B 2 CC05 2021 2021-10-20 SALIN 3.1099534176 #> 2622 2078B 2 CC05 2021 2021-10-20 TKN 0.0953101798 #> 2623 2078B 2 CC05 2021 2021-10-20 TN 0.0971267107 + #> 2624 2078B 2 CC05 2021 2021-10-20 TP -3.1235656451 #> 2625 2078B 2 CC05 2021 2021-10-20 TSS 1.9459101491 I #> 2626 2078B 2 CC05 2021 2021-10-20 TURB 1.4109869737 #> 2627 2078B 2 CC05 2022 2022-04-06 CHLAC 1.8718021769 #> 2628 2078B 2 CC05 2022 2022-04-06 COND 11.0061250625 #> 2629 2078B 2 CC05 2022 2022-04-06 DO 0.6365768291 #> 2630 2078B 2 CC05 2022 2022-04-06 DOSAT 3.3911470458 #> 2631 2078B 2 CC05 2022 2022-04-06 NO23 -5.5214609179 U #> 2632 2078B 2 CC05 2022 2022-04-06 SALIN 3.6980869349 #> 2633 2078B 2 CC05 2022 2022-04-06 TKN -0.0512932944 #> 2634 2078B 2 CC05 2022 2022-04-06 TN -0.0491902442 + #> 2635 2078B 2 CC05 2022 2022-04-06 TP -3.1700856607 #> 2636 2078B 2 CC05 2022 2022-04-06 TSS 1.3862943611 I #> 2637 2078B 2 CC05 2022 2022-04-06 TURB 0.0953101798 #> 2638 2078B 2 CC05 2022 2022-05-10 CHLAC 2.5649493575 #> 2639 2078B 2 CC05 2022 2022-05-10 COND 10.7027274806 #> 2640 2078B 2 CC05 2022 2022-05-10 DO 1.1281710909 #> 2641 2078B 2 CC05 2022 2022-05-10 DOSAT 3.7841896339 #> 2642 2078B 2 CC05 2022 2022-05-10 NO23 -5.5214609179 U #> 2643 2078B 2 CC05 2022 2022-05-10 SALIN 3.3579418730 #> 2644 2078B 2 CC05 2022 2022-05-10 TKN -0.0512932944 #> 2645 2078B 2 CC05 2022 2022-05-10 TN -0.0491902442 + #> 2646 2078B 2 CC05 2022 2022-05-10 TP -3.1010927892 #> 2647 2078B 2 CC05 2022 2022-05-10 TSS 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CC104 2023 2023-05-10 COND 9.6875057942 #> 2914 2035 3F CC104 2023 2023-05-10 DO 1.1216775616 #> 2915 2035 3F CC104 2023 2023-05-10 DOSAT 3.6913763343 #> 2916 2035 3F CC104 2023 2023-05-10 SALIN 2.2417729536 #> 2917 2035 3F CC104 2022 2022-01-24 COND 8.4487001950 #> 2918 2035 3F CC104 2022 2022-01-24 DO 2.1447610078 #> 2919 2035 3F CC104 2022 2022-01-24 DOSAT 4.4624538838 #> 2920 2035 3F CC104 2022 2022-01-24 SALIN 0.9202827531 #> 2921 2035 3F CC104 2022 2022-03-03 COND 9.6867608690 #> 2922 2035 3F CC104 2022 2022-03-03 DO 1.4516138272 #> 2923 2035 3F CC104 2022 2022-03-03 DOSAT 3.9608131696 #> 2924 2035 3F CC104 2022 2022-03-03 SALIN 2.2449559802 #> 2925 2035 3F CC104 2022 2022-05-23 COND 10.0031066176 #> 2926 2035 3F CC104 2022 2022-05-23 DO 1.0986122887 #> 2927 2035 3F CC104 2022 2022-05-23 DOSAT 3.7518542533 #> 2928 2035 3F CC104 2022 2022-05-23 SALIN 2.9019708937 #> 2929 2035 3F CC104 2022 2022-06-27 COND 7.9745328441 #> 2930 2035 3F CC104 2022 2022-06-27 DO 1.6544112781 #> 2931 2035 3F CC104 2022 2022-06-27 DOSAT 4.2150861799 #> 2932 2035 3F CC104 2022 2022-06-27 SALIN 0.4054651081 #> 2933 2035 3F CC104 2023 2023-01-09 COND 7.0958932211 #> 2934 2035 3F CC104 2023 2023-01-09 DO 2.1575593209 #> 2935 2035 3F CC104 2023 2023-01-09 DOSAT 4.5464811896 #> 2936 2035 3F CC104 2023 2023-01-09 SALIN -0.5108256238 #> 2937 2035 3F CC104 2023 2023-03-14 COND 9.4841009891 #> 2938 2035 3F CC104 2023 2023-03-14 DO 0.9820784724 #> 2939 2035 3F CC104 2023 2023-03-14 DOSAT 3.5292973843 #> 2940 2035 3F CC104 2023 2023-03-14 SALIN 2.0215475633 #> 2941 2035 3F CC104 2023 2023-05-10 COND 9.8215722593 #> 2942 2035 3F CC104 2023 2023-05-10 DO 1.3660916538 #> 2943 2035 3F CC104 2023 2023-05-10 DOSAT 3.9627161197 #> 2944 2035 3F CC104 2023 2023-05-10 SALIN 2.3860067011 #> 2945 2035 3F CC104 2014 2014-05-28 COND 7.0817085861 #> 2946 2035 3F CC104 2014 2014-05-28 DO 1.5560371357 #> 2947 2035 3F CC104 2014 2014-05-28 DOSAT 4.0145795938 + #> 2948 2035 3F CC104 2014 2014-05-28 SALIN -0.5276327421 #> 2949 2035 3F CC104 2014 2014-10-02 COND 5.9506425526 #> 2950 2035 3F CC104 2014 2014-10-02 DO 1.6770965609 #> 2951 2035 3F CC104 2014 2014-10-02 DOSAT 4.2061840440 + #> 2952 2035 3F CC104 2014 2014-10-02 SALIN -1.7147984281 #> 2953 2035 3F CC104 2016 2016-06-02 COND 6.8068293604 #> 2954 2035 3F CC104 2016 2016-06-02 DO 1.3837912309 #> 2955 2035 3F CC104 2016 2016-06-02 DOSAT 3.8501476017 + #> 2956 2035 3F CC104 2016 2016-06-02 SALIN -0.8209805521 #> 2957 2035 3F CC104 2016 2016-09-21 COND 6.3664704477 #> 2958 2035 3F CC104 2016 2016-09-21 DO 1.6389967147 #> 2959 2035 3F CC104 2016 2016-09-21 DOSAT 4.1697612015 + #> 2960 2035 3F CC104 2016 2016-09-21 SALIN -1.2729656758 #> 2961 2035 3F CC104 2017 2017-05-09 COND 6.9791452751 #> 2962 2035 3F CC104 2017 2017-05-09 DO 1.4134230285 #> 2963 2035 3F CC104 2017 2017-05-09 DOSAT 3.8220982979 + #> 2964 2035 3F CC104 2017 2017-05-09 SALIN -0.6348782724 #> 2965 2035 3F CC104 2017 2017-09-27 COND 6.1654178542 #> 2966 2035 3F CC104 2017 2017-09-27 DO 1.6937790609 #> 2967 2035 3F CC104 2017 2017-09-27 DOSAT 4.2195077052 + #> 2968 2035 3F CC104 2017 2017-09-27 SALIN -1.4696759701 #> 2969 2035 3F CC104 2018 2018-06-04 COND 6.2672005485 #> 2970 2035 3F CC104 2018 2018-06-04 DO 1.6808279085 #> 2971 2035 3F CC104 2018 2018-06-04 DOSAT 4.2209772132 + #> 2972 2035 3F CC104 2018 2018-06-04 SALIN -1.3862943611 #> 2973 2035 3F CC104 2018 2018-09-12 COND 6.2265366693 #> 2974 2035 3F CC104 2018 2018-09-12 DO 1.7749523509 #> 2975 2035 3F CC104 2018 2018-09-12 DOSAT 4.3040650932 + #> 2976 2035 3F CC104 2018 2018-09-12 SALIN -1.4271163556 #> 2977 2045 3M CC15 2018 2018-03-07 CHLAC 2.2617630985 #> 2978 2045 3M CC15 2018 2018-03-07 COND 10.0150289273 #> 2979 2045 3M CC15 2018 2018-03-07 DO 2.0281482473 #> 2980 2045 3M CC15 2018 2018-03-07 DOSAT 4.5475410732 #> 2981 2045 3M CC15 2018 2018-03-07 NO23 -5.5214609179 U #> 2982 2045 3M CC15 2018 2018-03-07 SALIN 2.6595599919 + #> 2983 2045 3M CC15 2018 2018-03-07 TKN -0.1743533871 #> 2984 2045 3M CC15 2018 2018-03-07 TN -0.1719752647 + #> 2985 2045 3M CC15 2018 2018-03-07 TP -1.8325814637 #> 2986 2045 3M CC15 2018 2018-03-07 TSS 1.0986122887 U #> 2987 2045 3M CC15 2018 2018-03-07 TURB 1.2809338455 #> 2988 2045 3M CC15 2018 2018-04-09 CHLAC 1.8870696490 #> 2989 2045 3M CC15 2018 2018-04-09 COND 10.4012279368 #> 2990 2045 3M CC15 2018 2018-04-09 DO 1.7227665977 #> 2991 2045 3M CC15 2018 2018-04-09 DOSAT 4.3438054219 #> 2992 2045 3M CC15 2018 2018-04-09 NO23 -5.5214609179 I #> 2993 2045 3M CC15 2018 2018-04-09 SALIN 3.0017143452 + #> 2994 2045 3M CC15 2018 2018-04-09 TKN -0.2357223335 #> 2995 2045 3M CC15 2018 2018-04-09 TN -0.2306718177 + #> 2996 2045 3M CC15 2018 2018-04-09 TP -1.5606477483 #> 2997 2045 3M CC15 2018 2018-04-09 TSS 2.7080502011 #> 2998 2045 3M CC15 2018 2018-04-09 TURB 1.8718021769 A #> 2999 2045 3M CC15 2018 2018-05-24 CHLAC 2.3978952728 #> 3000 2045 3M CC15 2018 2018-05-24 COND 9.3056505518 #> 3001 2045 3M CC15 2018 2018-05-24 DO 1.9198594719 #> 3002 2045 3M CC15 2018 2018-05-24 DOSAT 4.4589876758 #> 3003 2045 3M CC15 2018 2018-05-24 NO23 -3.3524072175 #> 3004 2045 3M CC15 2018 2018-05-24 SALIN 1.7833912196 + #> 3005 2045 3M CC15 2018 2018-05-24 TKN -0.1392620673 #> 3006 2045 3M CC15 2018 2018-05-24 TN -0.0998203353 + #> 3007 2045 3M CC15 2018 2018-05-24 TP -1.6094379124 #> 3008 2045 3M CC15 2018 2018-05-24 TSS 1.7917594692 I #> 3009 2045 3M CC15 2018 2018-05-24 TURB 1.3350010667 #> 3010 2045 3M CC15 2018 2018-05-24 SALIN 1.8991179875 + #> 3011 2045 3M CC15 2018 2018-05-24 COND 9.4091912307 #> 3012 2045 3M CC15 2018 2018-05-24 DO 1.7833912196 #> 3013 2045 3M CC15 2018 2018-05-24 DOSAT 4.3630986248 #> 3014 2045 3M CC15 2018 2018-05-24 COND 9.3056505518 #> 3015 2045 3M CC15 2018 2018-05-24 DO 1.9198594719 #> 3016 2045 3M CC15 2018 2018-05-24 DOSAT 4.4589876758 #> 3017 2045 3M CC15 2018 2018-05-24 SALIN 1.7833912196 + #> 3018 2045 3M CC15 2018 2018-07-23 CHLAC 2.0149030205 #> 3019 2045 3M CC15 2018 2018-07-23 COND 6.5087691370 #> 3020 2045 3M CC15 2018 2018-07-23 DO 1.7800242130 #> 3021 2045 3M CC15 2018 2018-07-23 DOSAT 4.3567088267 #> 3022 2045 3M CC15 2018 2018-07-23 NO23 -1.9661128564 #> 3023 2045 3M CC15 2018 2018-07-23 SALIN -1.1394342832 #> 3024 2045 3M CC15 2018 2018-07-23 TKN 0.1823215568 #> 3025 2045 3M CC15 2018 2018-07-23 TN 0.2926696140 + #> 3026 2045 3M CC15 2018 2018-07-23 TP -1.1394342832 #> 3027 2045 3M CC15 2018 2018-07-23 TSS 1.3862943611 I #> 3028 2045 3M CC15 2018 2018-07-23 TURB 1.3083328197 #> 3029 2045 3M CC15 2018 2018-08-21 CHLAC 2.0794415417 #> 3030 2045 3M CC15 2018 2018-08-21 COND 6.4393503711 #> 3031 2045 3M CC15 2018 2018-08-21 DO 1.6601310267 #> 3032 2045 3M CC15 2018 2018-08-21 DOSAT 4.2341065046 #> 3033 2045 3M CC15 2018 2018-08-21 NO23 -2.6736487744 #> 3034 2045 3M CC15 2018 2018-08-21 SALIN -1.2039728043 #> 3035 2045 3M CC15 2018 2018-08-21 TKN 0.0953101798 #> 3036 2045 3M CC15 2018 2018-08-21 TN 0.1561486825 + #> 3037 2045 3M CC15 2018 2018-08-21 TP -1.2378743560 #> 3038 2045 3M CC15 2018 2018-08-21 TSS 1.0986122887 I #> 3039 2045 3M CC15 2018 2018-08-21 TURB 1.0986122887 #> 3040 2045 3M CC15 2018 2018-08-21 COND 6.4264884575 #> 3041 2045 3M CC15 2018 2018-08-21 DO 1.6114359151 #> 3042 2045 3M CC15 2018 2018-08-21 DOSAT 4.1774594689 #> 3043 2045 3M CC15 2018 2018-08-21 SALIN -1.2039728043 #> 3044 2045 3M CC15 2019 2019-02-07 CHLAC 3.2188758249 A #> 3045 2045 3M CC15 2019 2019-02-07 COND 8.6916505732 #> 3046 2045 3M CC15 2019 2019-02-07 NO23 -5.1159958098 I #> 3047 2045 3M CC15 2019 2019-02-07 SALIN 1.1755733298 #> 3048 2045 3M CC15 2019 2019-02-07 TKN 0.0953101798 #> 3049 2045 3M CC15 2019 2019-02-07 TN 0.0989399479 + #> 3050 2045 3M CC15 2019 2019-02-07 TP -1.6607312068 #> 3051 2045 3M CC15 2019 2019-02-07 TSS 2.3025850930 I #> 3052 2045 3M CC15 2019 2019-02-07 TURB 2.0281482473 #> 3053 2045 3M CC15 2019 2019-03-13 CHLAC 1.8870696490 #> 3054 2045 3M CC15 2019 2019-03-13 COND 9.4304392931 #> 3055 2045 3M CC15 2019 2019-03-13 DO 1.8961194846 #> 3056 2045 3M CC15 2019 2019-03-13 DOSAT 4.4188406078 #> 3057 2045 3M CC15 2019 2019-03-13 NO23 -5.2983173665 I #> 3058 2045 3M CC15 2019 2019-03-13 SALIN 1.9657127764 #> 3059 2045 3M CC15 2019 2019-03-13 TKN -0.1625189295 #> 3060 2045 3M CC15 2019 2019-03-13 TN -0.1578240852 + #> 3061 2045 3M CC15 2019 2019-03-13 TP -1.8325814637 #> 3062 2045 3M CC15 2019 2019-03-13 TSS 2.0794415417 I #> 3063 2045 3M CC15 2019 2019-03-13 TURB 1.5892352051 #> 3064 2045 3M CC15 2019 2019-04-23 CHLAC 1.7749523509 #> 3065 2045 3M CC15 2019 2019-04-23 COND 9.9110588180 #> 3066 2045 3M CC15 2019 2019-04-23 DO 1.8562979904 #> 3067 2045 3M CC15 2019 2019-04-23 DOSAT 4.3845235149 #> 3068 2045 3M CC15 2019 2019-04-23 NO23 -5.5214609179 U #> 3069 2045 3M CC15 2019 2019-04-23 SALIN 2.4882344399 #> 3070 2045 3M CC15 2019 2019-04-23 TKN -0.2744368457 #> 3071 2045 3M CC15 2019 2019-04-23 TN -0.2718087233 + #> 3072 2045 3M CC15 2019 2019-04-23 TP -1.6607312068 #> 3073 2045 3M CC15 2019 2019-04-23 TSS 2.0794415417 I #> 3074 2045 3M CC15 2019 2019-04-23 TURB 1.4586150227 #> 3075 2045 3M CC15 2019 2019-07-22 CHLAC 2.4849066498 #> 3076 2045 3M CC15 2019 2019-07-22 COND 8.5083542427 #> 3077 2045 3M CC15 2019 2019-07-22 DO 1.7227665977 #> 3078 2045 3M CC15 2019 2019-07-22 DOSAT 4.3174881135 #> 3079 2045 3M CC15 2019 2019-07-22 NO23 -3.5065578973 #> 3080 2045 3M CC15 2019 2019-07-22 SALIN 0.9707789172 #> 3081 2045 3M CC15 2019 2019-07-22 TKN -0.0512932944 #> 3082 2045 3M CC15 2019 2019-07-22 TN -0.0202027073 + #> 3083 2045 3M CC15 2019 2019-07-22 TP -1.1086626245 #> 3084 2045 3M CC15 2019 2019-07-22 TSS 1.6094379124 I #> 3085 2045 3M CC15 2019 2019-07-22 TURB 1.3862943611 #> 3086 2045 3M CC15 2019 2019-09-04 COND 7.2896105215 #> 3087 2045 3M CC15 2019 2019-09-04 DO 1.6213664833 #> 3088 2045 3M CC15 2019 2019-09-04 DOSAT 4.2061840440 #> 3089 2045 3M CC15 2019 2019-09-04 NO23 -2.4191189092 #> 3090 2045 3M CC15 2019 2019-09-04 SALIN -0.3147107448 #> 3091 2045 3M CC15 2019 2019-09-04 TKN 0.1823215568 #> 3092 2045 3M CC15 2019 2019-09-04 TN 0.2538667240 + #> 3093 2045 3M CC15 2019 2019-09-04 TP -0.9675840263 #> 3094 2045 3M CC15 2019 2019-09-04 TSS 1.0986122887 I #> 3095 2045 3M CC15 2019 2019-09-04 TURB 1.0986122887 #> 3096 2045 3M CC15 2020 2020-02-18 CHLAC 2.7080502011 #> 3097 2045 3M CC15 2020 2020-02-18 COND 10.0136863448 #> 3098 2045 3M CC15 2020 2020-02-18 DO 1.9358598132 #> 3099 2045 3M CC15 2020 2020-02-18 DOSAT 4.5272086445 #> 3100 2045 3M CC15 2020 2020-02-18 NO23 -4.8283137373 I #> 3101 2045 3M CC15 2020 2020-02-18 SALIN 2.5967461315 #> 3102 2045 3M CC15 2020 2020-02-18 TKN -0.1165338163 #> 3103 2045 3M CC15 2020 2020-02-18 TN -0.1120495038 + #> 3104 2045 3M CC15 2020 2020-02-18 TP -1.6094379124 #> 3105 2045 3M CC15 2020 2020-02-18 TSS 2.7080502011 #> 3106 2045 3M CC15 2020 2020-02-18 TURB 1.7227665977 #> 3107 2045 3M CC15 2020 2020-02-18 COND 10.0120728629 #> 3108 2045 3M CC15 2020 2020-02-18 DO 1.9227877316 #> 3109 2045 3M CC15 2020 2020-02-18 DOSAT 4.5086592856 #> 3110 2045 3M CC15 2020 2020-02-18 SALIN 2.5952547070 #> 3111 2045 3M CC15 2020 2020-06-09 CHLAC 2.4849066498 #> 3112 2045 3M CC15 2020 2020-06-09 COND 9.2513863414 #> 3113 2045 3M CC15 2020 2020-06-09 DO 1.9315214116 #> 3114 2045 3M CC15 2020 2020-06-09 DOSAT 4.5239601306 #> 3115 2045 3M CC15 2020 2020-06-09 NO23 -3.3813947544 #> 3116 2045 3M CC15 2020 2020-06-09 SALIN 1.7664416612 #> 3117 2045 3M CC15 2020 2020-06-09 TKN -0.0304592075 #> 3118 2045 3M CC15 2020 2020-06-09 TN 0.0039920213 + #> 3119 2045 3M CC15 2020 2020-06-09 TP -1.4696759701 #> 3120 2045 3M CC15 2020 2020-06-09 TSS 1.0986122887 I #> 3121 2045 3M CC15 2020 2020-06-09 TURB 0.9162907319 #> 3122 2045 3M CC15 2020 2020-06-09 COND 9.5815590414 #> 3123 2045 3M CC15 2020 2020-06-09 DO 1.6544112781 #> 3124 2045 3M CC15 2020 2020-06-09 DOSAT 4.2076732475 #> 3125 2045 3M CC15 2020 2020-06-09 SALIN 2.1552445051 #> 3126 2045 3M CC15 2020 2020-08-10 COND 9.2688922589 #> 3127 2045 3M CC15 2020 2020-08-10 DO 1.6370530795 #> 3128 2045 3M CC15 2020 2020-08-10 DOSAT 4.2710950740 #> 3129 2045 3M CC15 2020 2020-08-10 SALIN -1.4567168254 #> 3130 2045 3M CC15 2020 2020-08-10 COND 9.4812068515 #> 3131 2045 3M CC15 2020 2020-08-10 DO 1.4398351280 #> 3132 2045 3M CC15 2020 2020-08-10 DOSAT 4.0758410907 #> 3133 2045 3M CC15 2020 2020-08-10 SALIN 0.2207406667 #> 3134 2045 3M CC15 2020 2020-09-22 CHLAC 2.2192034841 #> 3135 2045 3M CC15 2020 2020-09-22 COND 6.5750758406 #> 3136 2045 3M CC15 2020 2020-09-22 DO 1.7934247485 #> 3137 2045 3M CC15 2020 2020-09-22 DOSAT 4.3359826962 #> 3138 2045 3M CC15 2020 2020-09-22 NO23 -2.7968814148 #> 3139 2045 3M CC15 2020 2020-09-22 SALIN -1.0498221245 #> 3140 2045 3M CC15 2020 2020-09-22 TKN 0.2623642645 #> 3141 2045 3M CC15 2020 2020-09-22 TN 0.3082197237 + #> 3142 2045 3M CC15 2020 2020-09-22 TP -0.9942522733 #> 3143 2045 3M CC15 2020 2020-09-22 TSS 1.3862943611 I #> 3144 2045 3M CC15 2020 2020-09-22 TURB 1.2809338455 #> 3145 2045 3M CC15 2020 2020-10-20 CHLAC 3.0445224377 #> 3146 2045 3M CC15 2020 2020-10-20 COND 8.3209349689 #> 3147 2045 3M CC15 2020 2020-10-20 DO 1.7119945008 #> 3148 2045 3M CC15 2020 2020-10-20 DOSAT 4.2640873368 #> 3149 2045 3M CC15 2020 2020-10-20 NO23 -2.5010360317 #> 3150 2045 3M CC15 2020 2020-10-20 SALIN 0.7747271676 #> 3151 2045 3M CC15 2020 2020-10-20 TKN 0.2623642645 #> 3152 2045 3M CC15 2020 2020-10-20 TN 0.3235317253 + #> 3153 2045 3M CC15 2020 2020-10-20 TP -0.9942522733 #> 3154 2045 3M CC15 2020 2020-10-20 TSS 1.6094379124 I #> 3155 2045 3M CC15 2020 2020-10-20 TURB 1.2809338455 #> 3156 2045 3M CC15 2020 2020-12-14 CHLAC 2.6390573296 #> 3157 2045 3M CC15 2020 2020-12-14 COND 9.2314166976 #> 3158 2045 3M CC15 2020 2020-12-14 DO 2.0930978681 #> 3159 2045 3M CC15 2020 2020-12-14 DOSAT 4.5695430083 #> 3160 2045 3M CC15 2020 2020-12-14 NO23 -4.9618451299 I #> 3161 2045 3M CC15 2020 2020-12-14 SALIN 1.7526720805 #> 3162 2045 3M CC15 2020 2020-12-14 TKN 0.0000000000 #> 3163 2045 3M CC15 2020 2020-12-14 TN 0.0039920213 + #> 3164 2045 3M CC15 2020 2020-12-14 TP -1.4696759701 #> 3165 2045 3M CC15 2020 2020-12-14 TSS 1.6094379124 I #> 3166 2045 3M CC15 2020 2020-12-14 TURB 1.3609765531 A #> 3167 2045 3M CC15 2021 2021-02-03 CHLAC 1.7404661748 #> 3168 2045 3M CC15 2021 2021-02-03 COND 9.8506140629 #> 3169 2045 3M CC15 2021 2021-02-03 DO 2.1424163408 #> 3170 2045 3M CC15 2021 2021-02-03 DOSAT 4.5528237056 #> 3171 2045 3M CC15 2021 2021-02-03 NO23 -5.5214609179 U #> 3172 2045 3M CC15 2021 2021-02-03 SALIN 2.4248027257 #> 3173 2045 3M CC15 2021 2021-02-03 TKN -0.3424903089 #> 3174 2045 3M CC15 2021 2021-02-03 TN -0.3396773676 + #> 3175 2045 3M CC15 2021 2021-02-03 TP -1.9661128564 #> 3176 2045 3M CC15 2021 2021-02-03 TSS 1.3862943611 I #> 3177 2045 3M CC15 2021 2021-02-03 TURB 1.0296194172 #> 3178 2045 3M CC15 2021 2021-03-09 CHLAC 2.4849066498 #> 3179 2045 3M CC15 2021 2021-03-09 COND 9.8787336881 #> 3180 2045 3M CC15 2021 2021-03-09 DO 2.1690537004 #> 3181 2045 3M CC15 2021 2021-03-09 DOSAT 4.6510991179 #> 3182 2045 3M CC15 2021 2021-03-09 NO23 -5.5214609179 I #> 3183 2045 3M CC15 2021 2021-03-09 SALIN 2.4544474423 #> 3184 2045 3M CC15 2021 2021-03-09 TKN 0.0000000000 #> 3185 2045 3M CC15 2021 2021-03-09 TN 0.0039920213 + #> 3186 2045 3M CC15 2021 2021-03-09 TP -1.4696759701 #> 3187 2045 3M CC15 2021 2021-03-09 TSS 3.2958368660 #> 3188 2045 3M CC15 2021 2021-03-09 TURB 2.3978952728 A #> 3189 2045 3M CC15 2021 2021-05-05 CHLAC 1.8082887712 #> 3190 2045 3M CC15 2021 2021-05-05 COND 10.2487071336 #> 3191 2045 3M CC15 2021 2021-05-05 DO 1.8082887712 #> 3192 2045 3M CC15 2021 2021-05-05 DOSAT 4.4986979415 #> 3193 2045 3M CC15 2021 2021-05-05 NO23 -5.5214609179 U #> 3194 2045 3M CC15 2021 2021-05-05 SALIN 2.8489708922 #> 3195 2045 3M CC15 2021 2021-05-05 TKN -0.2231435513 #> 3196 2045 3M CC15 2021 2021-05-05 TN -0.2206466711 + #> 3197 2045 3M CC15 2021 2021-05-05 TP -1.6094379124 #> 3198 2045 3M CC15 2021 2021-05-05 TSS 1.9459101491 I #> 3199 2045 3M CC15 2021 2021-05-05 TURB 1.3350010667 #> 3200 2045 3M CC15 2021 2021-06-03 CHLAC 1.8245492921 #> 3201 2045 3M CC15 2021 2021-06-03 COND 10.3770473511 #> 3202 2045 3M CC15 2021 2021-06-03 DO 1.7715567619 #> 3203 2045 3M CC15 2021 2021-06-03 DOSAT 4.4331949212 #> 3204 2045 3M CC15 2021 2021-06-03 NO23 -5.5214609179 U #> 3205 2045 3M CC15 2021 2021-06-03 SALIN 2.9937302709 #> 3206 2045 3M CC15 2021 2021-06-03 TKN -0.1743533871 #> 3207 2045 3M CC15 2021 2021-06-03 TN -0.1719752647 + #> 3208 2045 3M CC15 2021 2021-06-03 TP -1.5606477483 #> 3209 2045 3M CC15 2021 2021-06-03 TSS 1.7917594692 I #> 3210 2045 3M CC15 2021 2021-06-03 TURB 1.2237754316 #> 3211 2045 3M CC15 2021 2021-07-01 CHLAC 2.1860512767 #> 3212 2045 3M CC15 2021 2021-07-01 COND 10.1292277297 #> 3213 2045 3M CC15 2021 2021-07-01 DO 1.7351891177 #> 3214 2045 3M CC15 2021 2021-07-01 DOSAT 4.3541414312 #> 3215 2045 3M CC15 2021 2021-07-01 NO23 -5.5214609179 U #> 3216 2045 3M CC15 2021 2021-07-01 SALIN 2.7232671669 #> 3217 2045 3M CC15 2021 2021-07-01 TKN -0.4155154440 #> 3218 2045 3M CC15 2021 2021-07-01 TN -0.4124897230 + #> 3219 2045 3M CC15 2021 2021-07-01 TP -1.5606477483 #> 3220 2045 3M CC15 2021 2021-07-01 TSS 1.0986122887 U #> 3221 2045 3M CC15 2021 2021-07-01 TURB 1.3083328197 #> 3222 2045 3M CC15 2021 2021-07-29 CHLAC 1.5892352051 #> 3223 2045 3M CC15 2021 2021-07-29 COND 7.4764723812 #> 3224 2045 3M CC15 2021 2021-07-29 DO 1.4303112465 #> 3225 2045 3M CC15 2021 2021-07-29 DOSAT 4.0145795938 #> 3226 2045 3M CC15 2021 2021-07-29 NO23 -2.4769384801 #> 3227 2045 3M CC15 2021 2021-07-29 SALIN -0.1165338163 #> 3228 2045 3M CC15 2021 2021-07-29 TKN 0.3364722366 #> 3229 2045 3M CC15 2021 2021-07-29 TN 0.3947411447 + #> 3230 2045 3M CC15 2021 2021-07-29 TP -0.4780358009 #> 3231 2045 3M CC15 2021 2021-07-29 TSS 1.7917594692 I #> 3232 2045 3M CC15 2021 2021-07-29 TURB 1.6292405397 #> 3233 2045 3M CC15 2021 2021-08-25 CHLAC 2.7725887222 #> 3234 2045 3M CC15 2021 2021-08-25 COND 6.9107507880 #> 3235 2045 3M CC15 2021 2021-08-25 DO 1.3376291891 #> 3236 2045 3M CC15 2021 2021-08-25 DOSAT 3.9120230054 #> 3237 2045 3M CC15 2021 2021-08-25 NO23 -2.9565115604 #> 3238 2045 3M CC15 2021 2021-08-25 SALIN -0.7133498879 #> 3239 2045 3M CC15 2021 2021-08-25 TKN 0.0953101798 #> 3240 2045 3M CC15 2021 2021-08-25 TN 0.1414995623 + #> 3241 2045 3M CC15 2021 2021-08-25 TP -0.8915981193 #> 3242 2045 3M CC15 2021 2021-08-25 TSS 1.0986122887 I #> 3243 2045 3M CC15 2021 2021-08-25 TURB 1.0647107370 #> 3244 2045 3M CC15 2021 2021-09-23 CHLAC 2.2300144002 #> 3245 2045 3M CC15 2021 2021-09-23 COND 6.2653012127 #> 3246 2045 3M CC15 2021 2021-09-23 DO 1.4060969884 #> 3247 2045 3M CC15 2021 2021-09-23 DOSAT 3.9550824949 #> 3248 2045 3M CC15 2021 2021-09-23 NO23 -3.0365542681 #> 3249 2045 3M CC15 2021 2021-09-23 SALIN -1.3862943611 #> 3250 2045 3M CC15 2021 2021-09-23 TKN 0.0953101798 #> 3251 2045 3M CC15 2021 2021-09-23 TN 0.1380212979 + #> 3252 2045 3M CC15 2021 2021-09-23 TP -1.3093333200 #> 3253 2045 3M CC15 2021 2021-09-23 TSS 1.3862943611 I #> 3254 2045 3M CC15 2021 2021-09-23 TURB 1.2527629685 #> 3255 2045 3M CC15 2021 2021-10-21 CHLAC 3.5263605246 #> 3256 2045 3M CC15 2021 2021-10-21 COND 8.7135820054 #> 3257 2045 3M CC15 2021 2021-10-21 DO 1.7732559977 #> 3258 2045 3M CC15 2021 2021-10-21 DOSAT 4.2918283668 #> 3259 2045 3M CC15 2021 2021-10-21 NO23 -2.9957322736 #> 3260 2045 3M CC15 2021 2021-10-21 SALIN 1.1939224685 #> 3261 2045 3M CC15 2021 2021-10-21 TKN 0.2623642645 #> 3262 2045 3M CC15 2021 2021-10-21 TN 0.3001045925 + #> 3263 2045 3M CC15 2021 2021-10-21 TP -1.1711829815 #> 3264 2045 3M CC15 2021 2021-10-21 TSS 1.6094379124 I #> 3265 2045 3M CC15 2021 2021-10-21 TURB 1.2809338455 #> 3266 2045 3M CC15 2021 2021-11-22 COND 9.2692694395 #> 3267 2045 3M CC15 2021 2021-11-22 DO 1.9516081702 #> 3268 2045 3M CC15 2021 2021-11-22 DOSAT 4.4647580323 #> 3269 2045 3M CC15 2021 2021-11-22 NO23 -4.7105307016 I #> 3270 2045 3M CC15 2021 2021-11-22 SALIN 1.7917594692 #> 3271 2045 3M CC15 2021 2021-11-22 TKN -0.1863295782 #> 3272 2045 3M CC15 2021 2021-11-22 TN -0.1815218766 + #> 3273 2045 3M CC15 2021 2021-11-22 TP -1.7147984281 #> 3274 2045 3M CC15 2021 2021-11-22 TSS 1.0986122887 I #> 3275 2045 3M CC15 2021 2021-11-22 TURB 0.9932517730 #> 3276 2045 3M CC15 2022 2022-02-22 CHLAC 1.5040773968 #> 3277 2045 3M CC15 2022 2022-02-22 COND 10.3013572215 #> 3278 2045 3M CC15 2022 2022-02-22 DO 1.9169226122 #> 3279 2045 3M CC15 2022 2022-02-22 DOSAT 4.4986979415 #> 3280 2045 3M CC15 2022 2022-02-22 NO23 -5.5214609179 U #> 3281 2045 3M CC15 2022 2022-02-22 SALIN 2.9139797717 #> 3282 2045 3M CC15 2022 2022-02-22 TKN -0.3285040670 #> 3283 2045 3M CC15 2022 2022-02-22 TN -0.3257301401 + #> 3284 2045 3M CC15 2022 2022-02-22 TP -2.0402208285 #> 3285 2045 3M CC15 2022 2022-02-22 TSS 2.3978952728 #> 3286 2045 3M CC15 2022 2022-02-22 TURB 1.3083328197 #> 3287 2045 3M CC15 2022 2022-04-20 CHLAC 0.4700036292 U #> 3288 2045 3M CC15 2022 2022-04-20 COND 10.5349454823 #> 3289 2045 3M CC15 2022 2022-04-20 DO 1.6919391339 #> 3290 2045 3M CC15 2022 2022-04-20 DOSAT 4.2972854062 #> 3291 2045 3M CC15 2022 2022-04-20 NO23 -5.5214609179 U #> 3292 2045 3M CC15 2022 2022-04-20 SALIN 3.1722034167 #> 3293 2045 3M CC15 2022 2022-04-20 TKN -0.1508228897 #> 3294 2045 3M CC15 2022 2022-04-20 TN -0.1485000083 + #> 3295 2045 3M CC15 2022 2022-04-20 TP -1.9661128564 #> 3296 2045 3M CC15 2022 2022-04-20 TSS 2.5649493575 #> 3297 2045 3M CC15 2022 2022-04-20 TURB 1.8082887712 #> 3298 2045 3M CC15 2022 2022-06-07 CHLAC 1.5260563035 #> 3299 2045 3M CC15 2022 2022-06-07 COND 10.2575891884 #> 3300 2045 3M CC15 2022 2022-06-07 DO 1.7137979278 #> 3301 2045 3M CC15 2022 2022-06-07 DOSAT 4.3870141762 #> 3302 2045 3M CC15 2022 2022-06-07 NO23 -4.8283137373 I #> 3303 2045 3M CC15 2022 2022-06-07 SALIN 2.8604851241 #> 3304 2045 3M CC15 2022 2022-06-07 TKN -0.3710636814 #> 3305 2045 3M CC15 2022 2022-06-07 TN -0.3652833185 + #> 3306 2045 3M CC15 2022 2022-06-07 TP -1.5606477483 #> 3307 2045 3M CC15 2022 2022-06-07 TSS 2.3025850930 #> 3308 2045 3M CC15 2022 2022-06-07 TURB 0.9932517730 #> 3309 2045 3M CC15 2022 2022-08-15 CHLAC 3.2188758249 #> 3310 2045 3M CC15 2022 2022-08-15 COND 8.2671921859 #> 3311 2045 3M CC15 2022 2022-08-15 DO 1.6094379124 #> 3312 2045 3M CC15 2022 2022-08-15 DOSAT 4.2136079830 #> 3313 2045 3M CC15 2022 2022-08-15 NO23 -4.7105307016 I #> 3314 2045 3M CC15 2022 2022-08-15 SALIN 0.7129498079 #> 3315 2045 3M CC15 2022 2022-08-15 TKN 0.0000000000 #> 3316 2045 3M CC15 2022 2022-08-15 TN 0.0039920213 + #> 3317 2045 3M CC15 2022 2022-08-15 TP -1.2378743560 #> 3318 2045 3M CC15 2022 2022-08-15 TSS 1.3862943611 I #> 3319 2045 3M CC15 2022 2022-08-15 TURB 1.0296194172 #> 3320 2045 3M CC15 2022 2022-12-15 CHLAC 4.9416424226 #> 3321 2045 3M CC15 2022 2022-12-15 COND 9.5450252980 #> 3322 2045 3M CC15 2022 2022-12-15 DO 1.8531680974 #> 3323 2045 3M CC15 2022 2022-12-15 DOSAT 4.3681812279 #> 3324 2045 3M CC15 2022 2022-12-15 NO23 -5.5214609179 U #> 3325 2045 3M CC15 2022 2022-12-15 SALIN 2.0881534823 #> 3326 2045 3M CC15 2022 2022-12-15 TKN 0.5306282511 #> 3327 2045 3M CC15 2022 2022-12-15 TN 0.5318040302 + #> 3328 2045 3M CC15 2022 2022-12-15 TP -1.0788096614 #> 3329 2045 3M CC15 2022 2022-12-15 TSS 2.8332133441 #> 3330 2045 3M CC15 2022 2022-12-15 TURB 2.1400661635 #> 3331 2045 3M CC15 2023 2023-01-11 CHLAC 2.1400661635 #> 3332 2045 3M CC15 2023 2023-01-11 COND 9.5500929367 #> 3333 2045 3M CC15 2023 2023-01-11 DO 1.9125010869 #> 3334 2045 3M CC15 2023 2023-01-11 DOSAT 4.3630986248 #> 3335 2045 3M CC15 2023 2023-01-11 NO23 -4.2686979494 #> 3336 2045 3M CC15 2023 2023-01-11 SALIN 2.0992441690 #> 3337 2045 3M CC15 2023 2023-01-11 TKN -0.2876820725 #> 3338 2045 3M CC15 2023 2023-01-11 TN -0.2691874898 + #> 3339 2045 3M CC15 2023 2023-01-11 TP -1.6607312068 #> 3340 2045 3M CC15 2023 2023-01-11 TSS 1.7917594692 I #> 3341 2045 3M CC15 2023 2023-01-11 TURB 0.8754687374 #> 3342 2045 3M CC15 2023 2023-03-23 CHLAC 1.4109869737 I #> 3343 2045 3M CC15 2023 2023-03-23 COND 10.2374208545 #> 3344 2045 3M CC15 2023 2023-03-23 DO 1.8609745382 #> 3345 2045 3M CC15 2023 2023-03-23 DOSAT 4.4030540019 #> 3346 2045 3M CC15 2023 2023-03-23 NO23 -5.5214609179 U #> 3347 2045 3M CC15 2023 2023-03-23 SALIN 2.8449093838 #> 3348 2045 3M CC15 2023 2023-03-23 TKN -0.3424903089 #> 3349 2045 3M CC15 2023 2023-03-23 TN -0.3396773676 + #> 3350 2045 3M CC15 2023 2023-03-23 TP -1.5606477483 #> 3351 2045 3M CC15 2023 2023-03-23 TSS 1.7917594692 I #> 3352 2045 3M CC15 2023 2023-03-23 TURB 1.2809338455 #> 3353 2045 3M CC15 2023 2023-05-08 CHLAC 1.1314021115 #> 3354 2045 3M CC15 2023 2023-05-08 COND 10.4129822911 #> 3355 2045 3M CC15 2023 2023-05-08 DO 1.6992786164 #> 3356 2045 3M CC15 2023 2023-05-08 DOSAT 4.3148178850 #> 3357 2045 3M CC15 2023 2023-05-08 NO23 -5.5214609179 U #> 3358 2045 3M CC15 2023 2023-05-08 SALIN 3.0359140632 #> 3359 2045 3M CC15 2023 2023-05-08 TKN -0.3147107448 #> 3360 2045 3M CC15 2023 2023-05-08 TN -0.3119747650 + #> 3361 2045 3M CC15 2023 2023-05-08 TP -1.6607312068 #> 3362 2045 3M CC15 2023 2023-05-08 TSS 2.6390573296 #> 3363 2045 3M CC15 2023 2023-05-08 TURB 1.3350010667 #> 3364 2043 3M CC16 2014 2014-06-26 COND 9.8119751520 #> 3365 2043 3M CC16 2014 2014-06-26 DO 2.4230312461 #> 3366 2043 3M CC16 2014 2014-06-26 DOSAT 5.0801613567 #> 3367 2043 3M CC16 2014 2014-06-26 COND 9.5792797987 #> 3368 2043 3M CC16 2014 2014-06-26 DO 1.2441545940 #> 3369 2043 3M CC16 2014 2014-06-26 DOSAT 3.9852734672 #> 3370 2043 3M CC16 2018 2018-03-07 CHLAC 1.8870696490 #> 3371 2043 3M CC16 2018 2018-03-07 COND 10.1527665775 #> 3372 2043 3M CC16 2018 2018-03-07 DO 1.9878743482 #> 3373 2043 3M CC16 2018 2018-03-07 DOSAT 4.5347477217 #> 3374 2043 3M CC16 2018 2018-03-07 NO23 -5.5214609179 U #> 3375 2043 3M CC16 2018 2018-03-07 SALIN 2.8081971497 + #> 3376 2043 3M CC16 2018 2018-03-07 TKN -0.3424903089 #> 3377 2043 3M CC16 2018 2018-03-07 TN -0.3396773676 + #> 3378 2043 3M CC16 2018 2018-03-07 TP -1.7719568419 #> 3379 2043 3M CC16 2018 2018-03-07 TSS 1.6094379124 I #> 3380 2043 3M CC16 2018 2018-03-07 TURB 1.0986122887 #> 3381 2043 3M CC16 2018 2018-03-07 COND 10.2049615773 #> 3382 2043 3M CC16 2018 2018-03-07 DO 2.0281482473 #> 3383 2043 3M CC16 2018 2018-03-07 DOSAT 4.5653893160 #> 3384 2043 3M CC16 2018 2018-03-07 SALIN 2.8701690506 + #> 3385 2043 3M CC16 2018 2018-04-09 CHLAC 1.9315214116 #> 3386 2043 3M CC16 2018 2018-04-09 COND 10.4399809231 #> 3387 2043 3M CC16 2018 2018-04-09 DO 1.8082887712 #> 3388 2043 3M CC16 2018 2018-04-09 DOSAT 4.4426512565 #> 3389 2043 3M CC16 2018 2018-04-09 NO23 -5.2983173665 I #> 3390 2043 3M CC16 2018 2018-04-09 SALIN 3.0445224377 + #> 3391 2043 3M CC16 2018 2018-04-09 TKN -0.3011050928 #> 3392 2043 3M CC16 2018 2018-04-09 TN -0.2957142441 + #> 3393 2043 3M CC16 2018 2018-04-09 TP -1.6607312068 #> 3394 2043 3M CC16 2018 2018-04-09 TSS 2.0794415417 I #> 3395 2043 3M CC16 2018 2018-04-09 TURB 1.4816045409 #> 3396 2043 3M CC16 2018 2018-05-24 CHLAC 2.2925347571 #> 3397 2043 3M CC16 2018 2018-05-24 COND 9.8201059436 #> 3398 2043 3M CC16 2018 2018-05-24 DO 1.7749523509 #> 3399 2043 3M CC16 2018 2018-05-24 DOSAT 4.3719762988 #> 3400 2043 3M CC16 2018 2018-05-24 NO23 -4.4228486292 #> 3401 2043 3M CC16 2018 2018-05-24 SALIN 2.3360198691 + #> 3402 2043 3M CC16 2018 2018-05-24 TKN -0.1984509387 #> 3403 2043 3M CC16 2018 2018-05-24 TN -0.1839228382 + #> 3404 2043 3M CC16 2018 2018-05-24 TP -1.6094379124 #> 3405 2043 3M CC16 2018 2018-05-24 TSS 2.3025850930 I #> 3406 2043 3M CC16 2018 2018-05-24 TURB 1.6863989536 #> 3407 2043 3M CC16 2018 2018-05-24 COND 9.8362788028 #> 3408 2043 3M CC16 2018 2018-05-24 DO 1.7698546338 #> 3409 2043 3M CC16 2018 2018-05-24 DOSAT 4.3681812279 #> 3410 2043 3M CC16 2018 2018-05-24 SALIN 2.3532782073 + #> 3411 2043 3M CC16 2018 2018-07-23 CHLAC 2.4849066498 #> 3412 2043 3M CC16 2018 2018-07-23 COND 7.2034055211 #> 3413 2043 3M CC16 2018 2018-07-23 DO 1.7833912196 #> 3414 2043 3M CC16 2018 2018-07-23 DOSAT 4.3694478525 #> 3415 2043 3M CC16 2018 2018-07-23 NO23 -2.1202635362 #> 3416 2043 3M CC16 2018 2018-07-23 SALIN -0.4004775666 #> 3417 2043 3M CC16 2018 2018-07-23 TKN 0.1823215568 #> 3418 2043 3M CC16 2018 2018-07-23 TN 0.2776317366 + #> 3419 2043 3M CC16 2018 2018-07-23 TP -1.1394342832 #> 3420 2043 3M CC16 2018 2018-07-23 TSS 1.0986122887 I #> 3421 2043 3M CC16 2018 2018-07-23 TURB 1.0986122887 #> 3422 2043 3M CC16 2018 2018-07-23 COND 7.2034055211 #> 3423 2043 3M CC16 2018 2018-07-23 DO 1.7578579176 #> 3424 2043 3M CC16 2018 2018-07-23 DOSAT 4.3438054219 #> 3425 2043 3M CC16 2018 2018-07-23 SALIN -0.4155154440 #> 3426 2043 3M CC16 2018 2018-08-21 CHLAC 2.8332133441 A #> 3427 2043 3M CC16 2018 2018-08-21 COND 6.5308776277 #> 3428 2043 3M CC16 2018 2018-08-21 DO 1.7083778603 #> 3429 2043 3M CC16 2018 2018-08-21 DOSAT 4.2931954210 #> 3430 2043 3M CC16 2018 2018-08-21 NO23 -2.8824035882 #> 3431 2043 3M CC16 2018 2018-08-21 SALIN -1.1086626245 #> 3432 2043 3M CC16 2018 2018-08-21 TKN 0.0953101798 #> 3433 2043 3M CC16 2018 2018-08-21 TN 0.1449657703 + #> 3434 2043 3M CC16 2018 2018-08-21 TP -1.2378743560 #> 3435 2043 3M CC16 2018 2018-08-21 TSS 1.0986122887 I #> 3436 2043 3M CC16 2018 2018-08-21 TURB 1.2809338455 #> 3437 2043 3M CC16 2018 2018-08-21 COND 6.5337888379 #> 3438 2043 3M CC16 2018 2018-08-21 DO 1.6882490929 #> 3439 2043 3M CC16 2018 2018-08-21 DOSAT 4.2724907476 #> 3440 2043 3M CC16 2018 2018-08-21 SALIN -1.1086626245 #> 3441 2043 3M CC16 2019 2019-02-07 CHLAC 3.1354942159 #> 3442 2043 3M CC16 2019 2019-02-07 COND 9.1573614472 #> 3443 2043 3M CC16 2019 2019-02-07 NO23 -5.5214609179 U #> 3444 2043 3M CC16 2019 2019-02-07 SALIN 1.6733512382 #> 3445 2043 3M CC16 2019 2019-02-07 TKN -0.0725706928 #> 3446 2043 3M CC16 2019 2019-02-07 TN -0.0704224643 + #> 3447 2043 3M CC16 2019 2019-02-07 TP -1.8325814637 #> 3448 2043 3M CC16 2019 2019-02-07 TSS 1.9459101491 I #> 3449 2043 3M CC16 2019 2019-02-07 TURB 1.6863989536 #> 3450 2043 3M CC16 2019 2019-03-13 CHLAC 2.1517622033 #> 3451 2043 3M CC16 2019 2019-03-13 COND 9.7229244488 #> 3452 2043 3M CC16 2019 2019-03-13 DO 1.7369512327 #> 3453 2043 3M CC16 2019 2019-03-13 DOSAT 4.2780540443 + #> 3454 2043 3M CC16 2019 2019-03-13 NO23 -5.5214609179 U #> 3455 2043 3M CC16 2019 2019-03-13 SALIN 2.2823823857 #> 3456 2043 3M CC16 2019 2019-03-13 TKN -0.2613647641 #> 3457 2043 3M CC16 2019 2019-03-13 TN -0.2587707290 + #> 3458 2043 3M CC16 2019 2019-03-13 TP -1.8971199849 #> 3459 2043 3M CC16 2019 2019-03-13 TSS 1.6094379124 I #> 3460 2043 3M CC16 2019 2019-03-13 TURB 1.2527629685 #> 3461 2043 3M CC16 2019 2019-03-13 COND 9.7228046524 #> 3462 2043 3M CC16 2019 2019-03-13 DO 1.6992786164 #> 3463 2043 3M CC16 2019 2019-03-13 DOSAT 4.2398868675 #> 3464 2043 3M CC16 2019 2019-03-13 SALIN 2.2823823857 #> 3465 2043 3M CC16 2019 2019-04-23 CHLAC 2.3978952728 #> 3466 2043 3M CC16 2019 2019-04-23 COND 9.9710060043 #> 3467 2043 3M CC16 2019 2019-04-23 DO 1.8341801851 #> 3468 2043 3M CC16 2019 2019-04-23 DOSAT 4.3707128748 #> 3469 2043 3M CC16 2019 2019-04-23 NO23 -5.5214609179 U #> 3470 2043 3M CC16 2019 2019-04-23 SALIN 2.5533438113 #> 3471 2043 3M CC16 2019 2019-04-23 TKN -0.1863295782 #> 3472 2043 3M CC16 2019 2019-04-23 TN -0.1839228382 + #> 3473 2043 3M CC16 2019 2019-04-23 TP -1.7147984281 #> 3474 2043 3M CC16 2019 2019-04-23 TSS 1.6094379124 I #> 3475 2043 3M CC16 2019 2019-04-23 TURB 1.0296194172 #> 3476 2043 3M CC16 2019 2019-07-22 CHLAC 2.4849066498 #> 3477 2043 3M CC16 2019 2019-07-22 COND 8.7887458819 #> 3478 2043 3M CC16 2019 2019-07-22 DO 1.7850704811 #> 3479 2043 3M CC16 2019 2019-07-22 DOSAT 4.3969152472 #> 3480 2043 3M CC16 2019 2019-07-22 NO23 -5.5214609179 U #> 3481 2043 3M CC16 2019 2019-07-22 SALIN 1.2669476035 #> 3482 2043 3M CC16 2019 2019-07-22 TKN -0.0833816089 #> 3483 2043 3M CC16 2019 2019-07-22 TN -0.0812100554 + #> 3484 2043 3M CC16 2019 2019-07-22 TP -1.2378743560 #> 3485 2043 3M CC16 2019 2019-07-22 TSS 1.0986122887 I #> 3486 2043 3M CC16 2019 2019-07-22 TURB 1.0986122887 #> 3487 2043 3M CC16 2019 2019-09-04 CHLAC 2.3025850930 #> 3488 2043 3M CC16 2019 2019-09-04 COND 7.9875244798 #> 3489 2043 3M CC16 2019 2019-09-04 DO 1.7101878155 #> 3490 2043 3M CC16 2019 2019-09-04 DOSAT 4.2972854062 #> 3491 2043 3M CC16 2019 2019-09-04 NO23 -2.3025850930 #> 3492 2043 3M CC16 2019 2019-09-04 SALIN 0.4187103349 #> 3493 2043 3M CC16 2019 2019-09-04 TKN 0.1823215568 #> 3494 2043 3M CC16 2019 2019-09-04 TN 0.2623642645 + #> 3495 2043 3M CC16 2019 2019-09-04 TP -0.9162907319 #> 3496 2043 3M CC16 2019 2019-09-04 TSS 1.7917594692 I #> 3497 2043 3M CC16 2019 2019-09-04 TURB 1.3350010667 #> 3498 2043 3M CC16 2020 2020-02-18 CHLAC 2.3978952728 #> 3499 2043 3M CC16 2020 2020-02-18 COND 10.0826374182 #> 3500 2043 3M CC16 2020 2020-02-18 DO 2.0202221820 #> 3501 2043 3M CC16 2020 2020-02-18 DOSAT 4.6170987569 #> 3502 2043 3M CC16 2020 2020-02-18 NO23 -5.5214609179 U #> 3503 2043 3M CC16 2020 2020-02-18 SALIN 2.6720775406 #> 3504 2043 3M CC16 2020 2020-02-18 TKN -0.1984509387 #> 3505 2043 3M CC16 2020 2020-02-18 TN -0.1960148839 + #> 3506 2043 3M CC16 2020 2020-02-18 TP -1.7147984281 #> 3507 2043 3M CC16 2020 2020-02-18 TSS 2.4849066498 #> 3508 2043 3M CC16 2020 2020-02-18 TURB 1.5260563035 #> 3509 2043 3M CC16 2020 2020-02-18 COND 10.0856841015 #> 3510 2043 3M CC16 2020 2020-02-18 DO 2.0055258587 #> 3511 2043 3M CC16 2020 2020-02-18 DOSAT 4.6001576442 #> 3512 2043 3M CC16 2020 2020-02-18 SALIN 2.6755270094 #> 3513 2043 3M CC16 2020 2020-06-09 CHLAC 1.9459101491 #> 3514 2043 3M CC16 2020 2020-06-09 COND 9.1632487644 #> 3515 2043 3M CC16 2020 2020-06-09 DO 1.8779371655 #> 3516 2043 3M CC16 2020 2020-06-09 DOSAT 4.4716387934 #> 3517 2043 3M CC16 2020 2020-06-09 NO23 -3.5404594490 #> 3518 2043 3M CC16 2020 2020-06-09 SALIN 1.6695918353 #> 3519 2043 3M CC16 2020 2020-06-09 TKN -0.1743533871 #> 3520 2043 3M CC16 2020 2020-06-09 TN -0.1404121537 + #> 3521 2043 3M CC16 2020 2020-06-09 TP -1.5606477483 #> 3522 2043 3M CC16 2020 2020-06-09 TSS 1.0986122887 I #> 3523 2043 3M CC16 2020 2020-06-09 TURB 0.8329091229 #> 3524 2043 3M CC16 2020 2020-06-09 COND 9.4707797080 #> 3525 2043 3M CC16 2020 2020-06-09 DO 1.8855533485 #> 3526 2043 3M CC16 2020 2020-06-09 DOSAT 4.4986979415 #> 3527 2043 3M CC16 2020 2020-06-09 SALIN 2.0041790572 #> 3528 2043 3M CC16 2020 2020-08-10 COND 9.6776528834 #> 3529 2043 3M CC16 2020 2020-08-10 DO 1.5973653312 #> 3530 2043 3M CC16 2020 2020-08-10 DOSAT 4.2541932632 #> 3531 2043 3M CC16 2020 2020-08-10 SALIN 2.2093727113 #> 3532 2043 3M CC16 2020 2020-09-22 CHLAC 2.1041341543 #> 3533 2043 3M CC16 2020 2020-09-22 COND 6.8012830345 #> 3534 2043 3M CC16 2020 2020-09-22 DO 1.8500283774 #> 3535 2043 3M CC16 2020 2020-09-22 DOSAT 4.3932138241 #> 3536 2043 3M CC16 2020 2020-09-22 NO23 -2.6882475738 #> 3537 2043 3M CC16 2020 2020-09-22 SALIN -0.8209805521 #> 3538 2043 3M CC16 2020 2020-09-22 TKN 0.1823215568 #> 3539 2043 3M CC16 2020 2020-09-22 TN 0.2374408560 + #> 3540 2043 3M CC16 2020 2020-09-22 TP -1.0498221245 #> 3541 2043 3M CC16 2020 2020-09-22 TSS 1.3862943611 I #> 3542 2043 3M CC16 2020 2020-09-22 TURB 1.1314021115 A #> 3543 2043 3M CC16 2020 2020-10-20 CHLAC 2.3978952728 #> 3544 2043 3M CC16 2020 2020-10-20 COND 8.8590793179 #> 3545 2043 3M CC16 2020 2020-10-20 DO 1.7281094422 #> 3546 2043 3M CC16 2020 2020-10-20 DOSAT 4.2835865619 #> 3547 2043 3M CC16 2020 2020-10-20 NO23 -2.2072749132 #> 3548 2043 3M CC16 2020 2020-10-20 SALIN 1.3480731483 #> 3549 2043 3M CC16 2020 2020-10-20 TKN 0.1823215568 #> 3550 2043 3M CC16 2020 2020-10-20 TN 0.2700271372 + #> 3551 2043 3M CC16 2020 2020-10-20 TP -1.1086626245 #> 3552 2043 3M CC16 2020 2020-10-20 TSS 1.7917594692 I #> 3553 2043 3M CC16 2020 2020-10-20 TURB 1.3350010667 #> 3554 2043 3M CC16 2020 2020-12-14 CHLAC 2.6390573296 #> 3555 2043 3M CC16 2020 2020-12-14 COND 9.3722891390 #> 3556 2043 3M CC16 2020 2020-12-14 DO 2.0554049639 #> 3557 2043 3M CC16 2020 2020-12-14 DOSAT 4.5261269786 #> 3558 2043 3M CC16 2020 2020-12-14 NO23 -5.5214609179 U #> 3559 2043 3M CC16 2020 2020-12-14 SALIN 1.9035989510 #> 3560 2043 3M CC16 2020 2020-12-14 TKN -0.0408219945 #> 3561 2043 3M CC16 2020 2020-12-14 TN -0.0387408283 + #> 3562 2043 3M CC16 2020 2020-12-14 TP -1.6094379124 #> 3563 2043 3M CC16 2020 2020-12-14 TSS 1.6094379124 I #> 3564 2043 3M CC16 2020 2020-12-14 TURB 1.2237754316 #> 3565 2043 3M CC16 2021 2021-02-03 CHLAC 2.3978952728 #> 3566 2043 3M CC16 2021 2021-02-03 COND 9.8437906253 #> 3567 2043 3M CC16 2021 2021-02-03 DO 2.0360119838 #> 3568 2043 3M CC16 2021 2021-02-03 DOSAT 4.4379342666 #> 3569 2043 3M CC16 2021 2021-02-03 NO23 -5.5214609179 U #> 3570 2043 3M CC16 2021 2021-02-03 SALIN 2.4185887688 #> 3571 2043 3M CC16 2021 2021-02-03 TKN -0.2484613593 #> 3572 2043 3M CC16 2021 2021-02-03 TN -0.2459005384 + #> 3573 2043 3M CC16 2021 2021-02-03 TP -2.2072749132 #> 3574 2043 3M CC16 2021 2021-02-03 TSS 1.3862943611 I #> 3575 2043 3M CC16 2021 2021-02-03 TURB 1.0986122887 #> 3576 2043 3M CC16 2021 2021-03-23 CHLAC 2.5649493575 #> 3577 2043 3M CC16 2021 2021-03-23 COND 10.0172179429 #> 3578 2043 3M CC16 2021 2021-03-23 DO 1.8484548129 #> 3579 2043 3M CC16 2021 2021-03-23 DOSAT 4.3320482649 #> 3580 2043 3M CC16 2021 2021-03-23 NO23 -5.5214609179 U #> 3581 2043 3M CC16 2021 2021-03-23 SALIN 2.6056482675 #> 3582 2043 3M CC16 2021 2021-03-23 TKN -0.1165338163 #> 3583 2043 3M CC16 2021 2021-03-23 TN -0.1142891464 + #> 3584 2043 3M CC16 2021 2021-03-23 TP -1.8971199849 #> 3585 2043 3M CC16 2021 2021-03-23 TSS 1.7917594692 I #> 3586 2043 3M CC16 2021 2021-03-23 TURB 1.3862943611 #> 3587 2043 3M CC16 2021 2021-05-05 CHLAC 2.2823823857 #> 3588 2043 3M CC16 2021 2021-05-05 COND 10.2634321453 #> 3589 2043 3M CC16 2021 2021-05-05 DO 1.7263316639 #> 3590 2043 3M CC16 2021 2021-05-05 DOSAT 4.4200447019 #> 3591 2043 3M CC16 2021 2021-05-05 NO23 -5.5214609179 I #> 3592 2043 3M CC16 2021 2021-05-05 SALIN 2.8650539499 #> 3593 2043 3M CC16 2021 2021-05-05 TKN -0.0833816089 #> 3594 2043 3M CC16 2021 2021-05-05 TN -0.0790432073 + #> 3595 2043 3M CC16 2021 2021-05-05 TP -1.5606477483 #> 3596 2043 3M CC16 2021 2021-05-05 TSS 2.0794415417 I #> 3597 2043 3M CC16 2021 2021-05-05 TURB 1.4816045409 #> 3598 2043 3M CC16 2021 2021-06-03 CHLAC 2.4849066498 #> 3599 2043 3M CC16 2021 2021-06-03 COND 10.3258753278 #> 3600 2043 3M CC16 2021 2021-06-03 DO 1.6524974019 #> 3601 2043 3M CC16 2021 2021-06-03 DOSAT 4.3094559418 #> 3602 2043 3M CC16 2021 2021-06-03 NO23 -5.5214609179 U #> 3603 2043 3M CC16 2021 2021-06-03 SALIN 2.9375733594 #> 3604 2043 3M CC16 2021 2021-06-03 TKN 0.0000000000 #> 3605 2043 3M CC16 2021 2021-06-03 TN 0.0019980027 + #> 3606 2043 3M CC16 2021 2021-06-03 TP -1.6607312068 #> 3607 2043 3M CC16 2021 2021-06-03 TSS 2.0794415417 I #> 3608 2043 3M CC16 2021 2021-06-03 TURB 1.4109869737 #> 3609 2043 3M CC16 2021 2021-07-01 CHLAC 3.0910424534 #> 3610 2043 3M CC16 2021 2021-07-01 COND 10.1819522754 #> 3611 2043 3M CC16 2021 2021-07-01 DO 1.6956156087 #> 3612 2043 3M CC16 2021 2021-07-01 DOSAT 4.3567088267 #> 3613 2043 3M CC16 2021 2021-07-01 NO23 -3.0791138825 #> 3614 2043 3M CC16 2021 2021-07-01 SALIN 2.7775762638 #> 3615 2043 3M CC16 2021 2021-07-01 TKN -0.2357223335 #> 3616 2043 3M CC16 2021 2021-07-01 TN -0.1791266659 + #> 3617 2043 3M CC16 2021 2021-07-01 TP -1.5606477483 #> 3618 2043 3M CC16 2021 2021-07-01 TSS 2.3025850930 #> 3619 2043 3M CC16 2021 2021-07-01 TURB 1.7404661748 #> 3620 2043 3M CC16 2022 2022-02-22 CHLAC 1.0986122887 #> 3621 2043 3M CC16 2022 2022-02-22 COND 10.3057809695 #> 3622 2043 3M CC16 2022 2022-02-22 DO 1.8794650496 #> 3623 2043 3M CC16 2022 2022-02-22 DOSAT 4.4543472963 #> 3624 2043 3M CC16 2022 2022-02-22 NO23 -4.9618451299 I #> 3625 2043 3M CC16 2022 2022-02-22 SALIN 2.9199305601 #> 3626 2043 3M CC16 2022 2022-02-22 TKN -0.4307829161 #> 3627 2043 3M CC16 2022 2022-02-22 TN -0.4246479275 + #> 3628 2043 3M CC16 2022 2022-02-22 TP -2.3859667019 #> 3629 2043 3M CC16 2022 2022-02-22 TSS 2.3025850930 I #> 3630 2043 3M CC16 2022 2022-02-22 TURB 0.6931471806 #> 3631 2043 3M CC16 2022 2022-06-07 CHLAC 2.7080502011 #> 3632 2043 3M CC16 2022 2022-06-07 COND 10.2345882454 #> 3633 2043 3M CC16 2022 2022-06-07 DO 1.4182774070 #> 3634 2043 3M CC16 2022 2022-06-07 DOSAT 4.1026433650 #> 3635 2043 3M CC16 2022 2022-06-07 NO23 -5.5214609179 U #> 3636 2043 3M CC16 2022 2022-06-07 SALIN 2.8361502037 #> 3637 2043 3M CC16 2022 2022-06-07 TKN -0.1165338163 #> 3638 2043 3M CC16 2022 2022-06-07 TN -0.1142891464 + #> 3639 2043 3M CC16 2022 2022-06-07 TP -1.6607312068 #> 3640 2043 3M CC16 2022 2022-06-07 TSS 2.5649493575 #> 3641 2043 3M CC16 2022 2022-06-07 TURB 1.6863989536 #> 3642 2043 3M CC16 2022 2022-08-15 CHLAC 2.9957322736 A #> 3643 2043 3M CC16 2022 2022-08-15 COND 8.1639409548 #> 3644 2043 3M CC16 2022 2022-08-15 DO 1.4350845253 #> 3645 2043 3M CC16 2022 2022-08-15 DOSAT 4.0145795938 #> 3646 2043 3M CC16 2022 2022-08-15 NO23 -4.7105307016 I #> 3647 2043 3M CC16 2022 2022-08-15 SALIN 0.6043159669 #> 3648 2043 3M CC16 2022 2022-08-15 TKN -0.1278333715 #> 3649 2043 3M CC16 2022 2022-08-15 TN -0.1232982163 + #> 3650 2043 3M CC16 2022 2022-08-15 TP -1.3093333200 #> 3651 2043 3M CC16 2022 2022-08-15 TSS 1.3862943611 I #> 3652 2043 3M CC16 2022 2022-08-15 TURB 1.2527629685 #> 3653 2043 3M CC16 2022 2022-12-15 CHLAC 4.8675344505 #> 3654 2043 3M CC16 2022 2022-12-15 COND 9.6068992706 #> 3655 2043 3M CC16 2022 2022-12-15 DO 2.1781550146 #> 3656 2043 3M CC16 2022 2022-12-15 DOSAT 4.6950108900 #> 3657 2043 3M CC16 2022 2022-12-15 NO23 -5.5214609179 U #> 3658 2043 3M CC16 2022 2022-12-15 SALIN 2.1575593209 #> 3659 2043 3M CC16 2022 2022-12-15 TKN 0.5306282511 #> 3660 2043 3M CC16 2022 2022-12-15 TN 0.5318040302 + #> 3661 2043 3M CC16 2022 2022-12-15 TP -1.1711829815 #> 3662 2043 3M CC16 2022 2022-12-15 TSS 2.8903717579 #> 3663 2043 3M CC16 2022 2022-12-15 TURB 1.8562979904 #> 3664 2043 3M CC16 2021 2021-02-03 CHLAC 3.1354942159 #> 3665 2043 3M CC16 2021 2021-02-03 COND 9.5834200199 #> 3666 2043 3M CC16 2021 2021-02-03 DO 2.0041790572 #> 3667 2043 3M CC16 2021 2021-02-03 DOSAT 4.4042772436 #> 3668 2043 3M CC16 2021 2021-02-03 NO23 -5.5214609179 U #> 3669 2043 3M CC16 2021 2021-02-03 SALIN 2.1365305087 #> 3670 2043 3M CC16 2021 2021-02-03 TKN -0.1278333715 #> 3671 2043 3M CC16 2021 2021-02-03 TN -0.1255632230 + #> 3672 2043 3M CC16 2021 2021-02-03 TP -2.1202635362 #> 3673 2043 3M CC16 2021 2021-02-03 TSS 1.9459101491 I #> 3674 2043 3M CC16 2021 2021-02-03 TURB 1.7578579176 #> 3675 2043 3M CC16 2021 2021-03-23 CHLAC 3.2188758249 #> 3676 2043 3M CC16 2021 2021-03-23 COND 9.8242819944 #> 3677 2043 3M CC16 2021 2021-03-23 DO 1.7867469274 #> 3678 2043 3M CC16 2021 2021-03-23 DOSAT 4.2640873368 #> 3679 2043 3M CC16 2021 2021-03-23 NO23 -5.5214609179 U #> 3680 2043 3M CC16 2021 2021-03-23 SALIN 2.3951642743 #> 3681 2043 3M CC16 2021 2021-03-23 TKN 0.0953101798 #> 3682 2043 3M CC16 2021 2021-03-23 TN 0.0971267107 + #> 3683 2043 3M CC16 2021 2021-03-23 TP -1.6094379124 #> 3684 2043 3M CC16 2021 2021-03-23 TSS 2.3978952728 #> 3685 2043 3M CC16 2021 2021-03-23 TURB 2.0412203289 #> 3686 2043 3M CC16 2021 2021-05-05 CHLAC 2.7725887222 #> 3687 2043 3M CC16 2021 2021-05-05 COND 10.1696522784 #> 3688 2043 3M CC16 2021 2021-05-05 DO 1.3711807233 #> 3689 2043 3M CC16 2021 2021-05-05 DOSAT 4.0342406382 #> 3690 2043 3M CC16 2021 2021-05-05 NO23 -5.5214609179 U #> 3691 2043 3M CC16 2021 2021-05-05 SALIN 2.7638002162 #> 3692 2043 3M CC16 2021 2021-05-05 TKN -0.0304592075 #> 3693 2043 3M CC16 2021 2021-05-05 TN -0.0283994745 + #> 3694 2043 3M CC16 2021 2021-05-05 TP -1.5606477483 #> 3695 2043 3M CC16 2021 2021-05-05 TSS 1.7917594692 I #> 3696 2043 3M CC16 2021 2021-05-05 TURB 1.5260563035 #> 3697 2043 3M CC16 2021 2021-06-03 CHLAC 2.8903717579 #> 3698 2043 3M CC16 2021 2021-06-03 COND 10.2473963549 #> 3699 2043 3M CC16 2021 2021-06-03 DO 1.5475625087 #> 3700 2043 3M CC16 2021 2021-06-03 DOSAT 4.2002049529 #> 3701 2043 3M CC16 2021 2021-06-03 NO23 -4.9618451299 I #> 3702 2043 3M CC16 2021 2021-06-03 SALIN 2.8518619031 #> 3703 2043 3M CC16 2021 2021-06-03 TKN 0.1823215568 #> 3704 2043 3M CC16 2021 2021-06-03 TN 0.1856493469 + #> 3705 2043 3M CC16 2021 2021-06-03 TP -1.5606477483 #> 3706 2043 3M CC16 2021 2021-06-03 TSS 2.3978952728 #> 3707 2043 3M CC16 2021 2021-06-03 TURB 1.6486586256 #> 3708 2043 3M CC16 2021 2021-07-01 CHLAC 3.4339872045 #> 3709 2043 3M CC16 2021 2021-07-01 COND 10.0458547938 #> 3710 2043 3M CC16 2021 2021-07-01 DO 1.9837562915 #> 3711 2043 3M CC16 2021 2021-07-01 DOSAT 4.6091622073 #> 3712 2043 3M CC16 2021 2021-07-01 NO23 -3.4420193762 #> 3713 2043 3M CC16 2021 2021-07-01 SALIN 2.6304489551 #> 3714 2043 3M CC16 2021 2021-07-01 TKN -0.0304592075 #> 3715 2043 3M CC16 2021 2021-07-01 TN 0.0019980027 + #> 3716 2043 3M CC16 2021 2021-07-01 TP -1.3862943611 #> 3717 2043 3M CC16 2021 2021-07-01 TSS 1.7917594692 I #> 3718 2043 3M CC16 2021 2021-07-01 TURB 1.6677068206 #> 3719 2043 3M CC16 2022 2022-02-22 CHLAC 1.6094379124 #> 3720 2043 3M CC16 2022 2022-02-22 COND 10.1823685085 #> 3721 2043 3M CC16 2022 2022-02-22 DO 1.7422190237 #> 3722 2043 3M CC16 2022 2022-02-22 DOSAT 4.3148178850 #> 3723 2043 3M CC16 2022 2022-02-22 NO23 -4.6051701860 I #> 3724 2043 3M CC16 2022 2022-02-22 SALIN 2.7788192720 #> 3725 2043 3M CC16 2022 2022-02-22 TKN -0.2484613593 #> 3726 2043 3M CC16 2022 2022-02-22 TN -0.2433462586 + #> 3727 2043 3M CC16 2022 2022-02-22 TP -2.3025850930 #> 3728 2043 3M CC16 2022 2022-02-22 TSS 2.4849066498 #> 3729 2043 3M CC16 2022 2022-02-22 TURB 1.6486586256 #> 3730 2043 3M CC16 2022 2022-06-07 CHLAC 2.1400661635 #> 3731 2043 3M CC16 2022 2022-06-07 COND 10.2020724724 #> 3732 2043 3M CC16 2022 2022-06-07 DO 1.5151272330 #> 3733 2043 3M CC16 2022 2022-06-07 DOSAT 4.1713056034 #> 3734 2043 3M CC16 2022 2022-06-07 NO23 -3.9633162998 #> 3735 2043 3M CC16 2022 2022-06-07 SALIN 2.7997173896 #> 3736 2043 3M CC16 2022 2022-06-07 TKN -0.1625189295 #> 3737 2043 3M CC16 2022 2022-06-07 TN -0.1404121537 + #> 3738 2043 3M CC16 2022 2022-06-07 TP -1.4271163556 #> 3739 2043 3M CC16 2022 2022-06-07 TSS 2.3025850930 #> 3740 2043 3M CC16 2022 2022-06-07 TURB 1.3350010667 #> 3741 2043 3M CC16 2022 2022-08-15 CHLAC 3.0445224377 #> 3742 2043 3M CC16 2022 2022-08-15 COND 7.8363697605 #> 3743 2043 3M CC16 2022 2022-08-15 DO 1.5539252025 #> 3744 2043 3M CC16 2022 2022-08-15 DOSAT 4.1319614258 #> 3745 2043 3M CC16 2022 2022-08-15 NO23 -4.0173835211 #> 3746 2043 3M CC16 2022 2022-08-15 SALIN 0.2623642645 #> 3747 2043 3M CC16 2022 2022-08-15 TKN -0.1863295782 #> 3748 2043 3M CC16 2022 2022-08-15 TN -0.1648746432 + #> 3749 2043 3M CC16 2022 2022-08-15 TP -1.6094379124 #> 3750 2043 3M CC16 2022 2022-08-15 TSS 2.0794415417 I #> 3751 2043 3M CC16 2022 2022-08-15 TURB 1.4109869737 #> 3752 2043 3M CC16 2022 2022-12-15 CHLAC 3.6109179126 #> 3753 2043 3M CC16 2022 2022-12-15 COND 9.5544264071 #> 3754 2043 3M CC16 2022 2022-12-15 DO 1.8405496334 #> 3755 2043 3M CC16 2022 2022-12-15 DOSAT 4.3554259529 #> 3756 2043 3M CC16 2022 2022-12-15 NO23 -5.5214609179 U #> 3757 2043 3M CC16 2022 2022-12-15 SALIN 2.0992441690 #> 3758 2043 3M CC16 2022 2022-12-15 TKN -0.1743533871 #> 3759 2043 3M CC16 2022 2022-12-15 TN -0.1719752647 + #> 3760 2043 3M CC16 2022 2022-12-15 TP -1.7719568419 #> 3761 2043 3M CC16 2022 2022-12-15 TSS 1.7917594692 I #> 3762 2043 3M CC16 2022 2022-12-15 TURB 1.2809338455 #> 3763 2048A 3M CC18 2014 2014-01-06 DO 1.7917594692 #> 3764 2048A 3M CC18 2014 2014-01-06 DOSAT 4.3107991254 + #> 3765 2048A 3M CC18 2014 2014-01-06 NO23 -4.7105307016 I #> 3766 2048A 3M CC18 2014 2014-01-06 SALIN 3.0819099698 #> 3767 2048A 3M CC18 2014 2014-01-06 TKN -0.3011050928 #> 3768 2048A 3M CC18 2014 2014-01-06 TN -0.2957142441 + #> 3769 2048A 3M CC18 2014 2014-01-06 TP -2.7333680091 #> 3770 2048A 3M CC18 2014 2014-02-03 CHLAC 1.3350010667 #> 3771 2048A 3M CC18 2014 2014-02-03 COLOR 3.2188758249 #> 3772 2048A 3M CC18 2014 2014-02-03 DO 1.6677068206 #> 3773 2048A 3M CC18 2014 2014-02-03 DOSAT 4.1820501426 + #> 3774 2048A 3M CC18 2014 2014-02-03 NO23 -4.5098600062 #> 3775 2048A 3M CC18 2014 2014-02-03 SALIN 2.9496883351 #> 3776 2048A 3M CC18 2014 2014-02-03 TKN -0.6348782724 #> 3777 2048A 3M CC18 2014 2014-02-03 TN -0.6143360001 + #> 3778 2048A 3M CC18 2014 2014-02-03 TP -2.5133061243 #> 3779 2048A 3M CC18 2014 2014-02-03 TURB 0.4700036292 #> 3780 2048A 3M CC18 2014 2014-03-03 CHLAC 1.0296194172 #> 3781 2048A 3M CC18 2014 2014-03-03 COLOR 3.2580965380 #> 3782 2048A 3M CC18 2014 2014-03-03 DOSAT 4.3201512310 + #> 3783 2048A 3M CC18 2014 2014-03-03 NO23 -5.5214609179 I #> 3784 2048A 3M CC18 2014 2014-03-03 SALIN 3.0349529867 #> 3785 2048A 3M CC18 2014 2014-03-03 TKN -0.4155154440 #> 3786 2048A 3M CC18 2014 2014-03-03 TN -0.4094731295 + #> 3787 2048A 3M CC18 2014 2014-03-03 TP -2.3859667019 #> 3788 2048A 3M CC18 2014 2014-03-03 TURB 0.6418538862 #> 3789 2048A 3M CC18 2014 2014-04-07 CHLAC 1.5892352051 #> 3790 2048A 3M CC18 2014 2014-04-07 COLOR 3.3322045102 #> 3791 2048A 3M CC18 2014 2014-04-07 DO 2.2082744135 #> 3792 2048A 3M CC18 2014 2014-04-07 DOSAT 4.7492705300 + #> 3793 2048A 3M CC18 2014 2014-04-07 NO23 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CC18 2014 2014-06-02 NO23 -4.6051701860 #> 3812 2048A 3M CC18 2014 2014-06-02 SALIN 3.1441522787 #> 3813 2048A 3M CC18 2014 2014-06-02 TKN -0.4004775666 #> 3814 2048A 3M CC18 2014 2014-06-02 TN -0.3856624808 + #> 3815 2048A 3M CC18 2014 2014-06-02 TP -1.5606477483 #> 3816 2048A 3M CC18 2014 2014-06-02 TURB 0.9555114450 #> 3817 2048A 3M CC18 2014 2014-08-04 CHLAC 1.9740810260 #> 3818 2048A 3M CC18 2014 2014-08-04 COLOR 4.7874917428 #> 3819 2048A 3M CC18 2014 2014-08-04 DO 0.7371640660 #> 3820 2048A 3M CC18 2014 2014-08-04 DOSAT 3.3568971228 + #> 3821 2048A 3M CC18 2014 2014-08-04 NO23 -4.8283137373 I #> 3822 2048A 3M CC18 2014 2014-08-04 TKN 0.0953101798 #> 3823 2048A 3M CC18 2014 2014-08-04 TN 0.0989399479 + #> 3824 2048A 3M CC18 2014 2014-08-04 TP -1.3862943611 #> 3825 2048A 3M CC18 2014 2014-08-04 TURB 1.2527629685 #> 3826 2048A 3M CC18 2014 2014-09-08 CHLAC 1.8082887712 #> 3827 2048A 3M CC18 2014 2014-09-08 COLOR 4.1108738642 #> 3828 2048A 3M CC18 2014 2014-09-08 DO 1.3083328197 #> 3829 2048A 3M CC18 2014 2014-09-08 DOSAT 3.8958936235 + #> 3830 2048A 3M CC18 2014 2014-09-08 NO23 -4.5098600062 #> 3831 2048A 3M CC18 2014 2014-09-08 SALIN 2.1162555148 #> 3832 2048A 3M CC18 2014 2014-09-08 TKN -0.0833816089 #> 3833 2048A 3M CC18 2014 2014-09-08 TN -0.0714960017 + #> 3834 2048A 3M CC18 2014 2014-09-08 TP -1.4696759701 #> 3835 2048A 3M CC18 2014 2014-09-08 TURB 0.5877866649 #> 3836 2048A 3M CC18 2014 2014-10-06 CHLAC 2.3978952728 #> 3837 2048A 3M CC18 2014 2014-10-06 COLOR 5.1929568509 #> 3838 2048A 3M CC18 2014 2014-10-06 DO 2.1400661635 #> 3839 2048A 3M CC18 2014 2014-10-06 DOSAT 4.6376373761 + #> 3840 2048A 3M CC18 2014 2014-10-06 NO23 -3.9633162998 #> 3841 2048A 3M CC18 2014 2014-10-06 SALIN 0.5877866649 #> 3842 2048A 3M CC18 2014 2014-10-06 TKN -0.0943106795 #> 3843 2048A 3M CC18 2014 2014-10-06 TN -0.0736465402 + #> 3844 2048A 3M CC18 2014 2014-10-06 TP -1.8971199849 #> 3845 2048A 3M CC18 2014 2014-10-06 TURB 0.4700036292 A #> 3846 2048A 3M CC18 2014 2014-11-03 CHLAC 1.8405496334 #> 3847 2048A 3M CC18 2014 2014-11-03 COLOR 4.5325994932 #> 3848 2048A 3M CC18 2014 2014-11-03 NO23 -4.2686979494 #> 3849 2048A 3M CC18 2014 2014-11-03 SALIN 2.5726122302 #> 3850 2048A 3M CC18 2014 2014-11-03 TKN -0.1743533871 #> 3851 2048A 3M CC18 2014 2014-11-03 TN -0.1578240852 + #> 3852 2048A 3M CC18 2014 2014-11-03 TP -1.6607312068 #> 3853 2048A 3M CC18 2014 2014-11-03 TURB 0.5306282511 A #> 3854 2048A 3M CC18 2014 2014-12-01 CHLAC 0.6418538862 #> 3855 2048A 3M CC18 2014 2014-12-01 COLOR 3.8712010109 A #> 3856 2048A 3M CC18 2014 2014-12-01 DO 1.7047480922 #> 3857 2048A 3M CC18 2014 2014-12-01 SALIN 2.6100697927 #> 3858 2048A 3M CC18 2014 2014-12-01 TN -0.0899247075 + #> 3859 2048A 3M CC18 2014 2014-12-01 TURB 0.0000000000 #> 3860 2048A 3M CC18 2015 2015-01-05 CHLAC 2.0149030205 #> 3861 2048A 3M CC18 2015 2015-01-05 COLOR 3.5835189385 #> 3862 2048A 3M CC18 2015 2015-01-05 DO 1.7578579176 #> 3863 2048A 3M CC18 2015 2015-01-05 DOSAT 4.3333614627 + #> 3864 2048A 3M 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2.9285235239 #> 3882 2048A 3M CC18 2015 2015-03-02 TN -0.3147107448 + #> 3883 2048A 3M CC18 2015 2015-03-02 TURB 0.7884573604 #> 3884 2048A 3M CC18 2015 2015-04-06 CHLAC 3.2580965380 A #> 3885 2048A 3M CC18 2015 2015-04-06 COLOR 3.6109179126 #> 3886 2048A 3M CC18 2015 2015-04-06 DO 2.3025850930 #> 3887 2048A 3M CC18 2015 2015-04-06 DOSAT 4.8706066495 + #> 3888 2048A 3M CC18 2015 2015-04-06 NO23 -4.5098600062 #> 3889 2048A 3M CC18 2015 2015-04-06 SALIN 2.7278528284 #> 3890 2048A 3M CC18 2015 2015-04-06 TKN 0.4700036292 #> 3891 2048A 3M CC18 2015 2015-04-06 TN 0.4768551042 + #> 3892 2048A 3M CC18 2015 2015-04-06 TP -1.2378743560 #> 3893 2048A 3M CC18 2015 2015-04-06 TURB 1.5892352051 #> 3894 2048A 3M CC18 2015 2015-06-01 CHLAC 1.3083328197 #> 3895 2048A 3M CC18 2015 2015-06-01 COLOR 3.6109179126 #> 3896 2048A 3M CC18 2015 2015-06-01 DO 1.3609765531 #> 3897 2048A 3M CC18 2015 2015-06-01 DOSAT 3.9834130015 + #> 3898 2048A 3M CC18 2015 2015-06-01 NO23 -4.7105307016 I #> 3899 2048A 3M CC18 2015 2015-06-01 SALIN 2.9285235239 #> 3900 2048A 3M CC18 2015 2015-06-01 TKN -0.3710636814 #> 3901 2048A 3M CC18 2015 2015-06-01 TN -0.3652833185 + #> 3902 2048A 3M CC18 2015 2015-06-01 TP -1.5141277326 #> 3903 2048A 3M CC18 2015 2015-06-01 TURB 0.9555114450 #> 3904 2048A 3M CC18 2015 2015-08-03 CHLAC 1.6677068206 #> 3905 2048A 3M CC18 2015 2015-08-03 COLOR 5.1929568509 #> 3906 2048A 3M CC18 2015 2015-08-03 NO23 -4.5098600062 #> 3907 2048A 3M CC18 2015 2015-08-03 SALIN 2.1282317058 #> 3908 2048A 3M CC18 2015 2015-08-03 TKN -0.0618754037 #> 3909 2048A 3M CC18 2015 2015-08-03 TN -0.0502412164 + #> 3910 2048A 3M CC18 2015 2015-08-03 TP -1.4271163556 #> 3911 2048A 3M CC18 2015 2015-08-03 TURB 0.7884573604 #> 3912 2048A 3M CC18 2015 2015-09-08 CHLAC 1.7749523509 #> 3913 2048A 3M CC18 2015 2015-09-08 COLOR 5.0751738152 #> 3914 2048A 3M CC18 2015 2015-09-08 DO 1.2527629685 #> 3915 2048A 3M CC18 2015 2015-09-08 DOSAT 3.6163087613 + #> 3916 2048A 3M CC18 2015 2015-09-08 NO23 -2.9374633654 #> 3917 2048A 3M CC18 2015 2015-09-08 SALIN 1.0647107370 #> 3918 2048A 3M CC18 2015 2015-09-08 TKN 0.0000000000 #> 3919 2048A 3M CC18 2015 2015-09-08 TN 0.0516432332 + #> 3920 2048A 3M CC18 2015 2015-09-08 TP -1.5606477483 #> 3921 2048A 3M CC18 2015 2015-09-08 TURB 0.0953101798 #> 3922 2048A 3M CC18 2015 2015-10-05 CHLAC 0.6418538862 #> 3923 2048A 3M CC18 2015 2015-10-05 COLOR 5.0751738152 #> 3924 2048A 3M CC18 2015 2015-10-05 DOSAT 4.6091622073 + #> 3925 2048A 3M CC18 2015 2015-10-05 NO23 -3.0576076773 #> 3926 2048A 3M CC18 2015 2015-10-05 SALIN 1.9459101491 #> 3927 2048A 3M CC18 2015 2015-10-05 TKN -0.0304592075 #> 3928 2048A 3M CC18 2015 2015-10-05 TN 0.0168571171 + #> 3929 2048A 3M CC18 2015 2015-10-05 TP -1.2039728043 #> 3930 2048A 3M CC18 2015 2015-10-05 TURB 0.6418538862 #> 3931 2048A 3M CC18 2015 2015-12-07 CHLAC 0.8754687374 #> 3932 2048A 3M CC18 2015 2015-12-07 COLOR 3.9120230054 #> 3933 2048A 3M CC18 2015 2015-12-07 DO 2.5416019935 #> 3934 2048A 3M CC18 2015 2015-12-07 NO23 -3.4420193762 #> 3935 2048A 3M CC18 2015 2015-12-07 TKN -0.2876820725 #> 3936 2048A 3M CC18 2015 2015-12-07 TN -0.2459005384 + #> 3937 2048A 3M CC18 2015 2015-12-07 TP -2.2072749132 #> 3938 2048A 3M CC18 2015 2015-12-07 TURB 0.1823215568 #> 3939 2048A 3M CC18 2016 2016-01-04 CHLAC 4.4188406078 #> 3940 2048A 3M CC18 2016 2016-01-04 COLOR 3.6888794541 A #> 3941 2048A 3M CC18 2016 2016-01-04 DOSAT 3.6888794541 + #> 3942 2048A 3M CC18 2016 2016-01-04 NO23 -3.2968373663 #> 3943 2048A 3M CC18 2016 2016-01-04 SALIN 2.8094026954 #> 3944 2048A 3M CC18 2016 2016-01-04 TKN -0.1863295782 #> 3945 2048A 3M CC18 2016 2016-01-04 TN -0.1427163022 + #> 3946 2048A 3M CC18 2016 2016-01-04 TP -2.3025850930 #> 3947 2048A 3M CC18 2016 2016-01-04 TURB 0.6931471806 #> 3948 2048A 3M CC18 2016 2016-02-01 CHLAC 0.8329091229 #> 3949 2048A 3M CC18 2016 2016-02-01 COLOR 4.4659081187 #> 3950 2048A 3M CC18 2016 2016-02-01 DO 1.5686159179 #> 3951 2048A 3M CC18 2016 2016-02-01 DOSAT 4.0018637094 + #> 3952 2048A 3M CC18 2016 2016-02-01 NO23 -4.8283137373 I #> 3953 2048A 3M CC18 2016 2016-02-01 SALIN 2.0281482473 #> 3954 2048A 3M CC18 2016 2016-02-01 TKN -0.4155154440 #> 3955 2048A 3M CC18 2016 2016-02-01 TN -0.4094731295 + #> 3956 2048A 3M CC18 2016 2016-02-01 TP -2.4304184645 #> 3957 2048A 3M CC18 2016 2016-02-01 TURB 0.2623642645 A #> 3958 2048A 3M CC18 2016 2016-03-07 CHLAC 0.0953101798 I #> 3959 2048A 3M CC18 2016 2016-03-07 COLOR 4.1108738642 #> 3960 2048A 3M CC18 2016 2016-03-07 DOSAT 4.2076732475 + #> 3961 2048A 3M CC18 2016 2016-03-07 NO23 -4.8283137373 U #> 3962 2048A 3M CC18 2016 2016-03-07 SALIN 1.9740810260 #> 3963 2048A 3M CC18 2016 2016-03-07 TN -0.0790432073 + #> 3964 2048A 3M CC18 2016 2016-03-07 TURB 0.6931471806 #> 3965 2048A 3M CC18 2016 2016-04-04 CHLAC 1.6677068206 #> 3966 2048A 3M CC18 2016 2016-04-04 COLOR 3.8918202981 #> 3967 2048A 3M CC18 2016 2016-04-04 DO 1.6677068206 #> 3968 2048A 3M CC18 2016 2016-04-04 DOSAT 4.1941898972 + #> 3969 2048A 3M CC18 2016 2016-04-04 NO23 -5.2983173665 I #> 3970 2048A 3M CC18 2016 2016-04-04 SALIN 2.3978952728 #> 3971 2048A 3M CC18 2016 2016-04-04 TKN -0.3011050928 #> 3972 2048A 3M CC18 2016 2016-04-04 TN -0.2957142441 + #> 3973 2048A 3M CC18 2016 2016-04-04 TP -1.9661128564 #> 3974 2048A 3M CC18 2016 2016-04-04 TURB 1.0647107370 #> 3975 2048A 3M CC18 2016 2016-05-02 CHLAC 1.1314021115 #> 3976 2048A 3M CC18 2016 2016-05-02 COLOR 3.8918202981 A #> 3977 2048A 3M CC18 2016 2016-05-02 DO 1.3862943611 #> 3978 2048A 3M CC18 2016 2016-05-02 DOSAT 4.0109629533 + #> 3979 2048A 3M CC18 2016 2016-05-02 NO23 -5.5214609179 I #> 3980 2048A 3M CC18 2016 2016-05-02 SALIN 2.7850112422 #> 3981 2048A 3M CC18 2016 2016-05-02 TKN -0.1984509387 #> 3982 2048A 3M CC18 2016 2016-05-02 TN -0.1935847491 + #> 3983 2048A 3M CC18 2016 2016-05-02 TP -1.8325814637 #> 3984 2048A 3M CC18 2016 2016-05-02 TURB 0.3364722366 #> 3985 2048A 3M CC18 2016 2016-07-05 CHLAC 1.4586150227 #> 3986 2048A 3M CC18 2016 2016-07-05 COLOR 4.5747109785 #> 3987 2048A 3M CC18 2016 2016-07-05 DOSAT 4.0758410907 + #> 3988 2048A 3M CC18 2016 2016-07-05 NO23 -5.5214609179 I #> 3989 2048A 3M CC18 2016 2016-07-05 SALIN 2.1400661635 #> 3990 2048A 3M CC18 2016 2016-07-05 TKN 0.0000000000 #> 3991 2048A 3M CC18 2016 2016-07-05 TN 0.0039920213 + #> 3992 2048A 3M CC18 2016 2016-07-05 TP -0.9162907319 #> 3993 2048A 3M CC18 2016 2016-07-05 TURB 0.6931471806 #> 3994 2048A 3M CC18 2016 2016-08-01 CHLAC 1.9878743482 #> 3995 2048A 3M CC18 2016 2016-08-01 COLOR 4.4659081187 #> 3996 2048A 3M CC18 2016 2016-08-01 NO23 -5.2983173665 I #> 3997 2048A 3M CC18 2016 2016-08-01 SALIN 1.9878743482 #> 3998 2048A 3M CC18 2016 2016-08-01 TN 0.0989399479 + #> 3999 2048A 3M CC18 2016 2016-08-01 TURB 0.6931471806 #> 4000 2048A 3M CC18 2016 2016-10-03 CHLAC 1.9740810260 #> 4001 2048A 3M CC18 2016 2016-10-03 COLOR 4.7004803658 #> 4002 2048A 3M CC18 2016 2016-10-03 DO 1.8870696490 #> 4003 2048A 3M CC18 2016 2016-10-03 DOSAT 4.4438270356 + #> 4004 2048A 3M CC18 2016 2016-10-03 NO23 -4.8283137373 I #> 4005 2048A 3M CC18 2016 2016-10-03 SALIN 1.4158531634 #> 4006 2048A 3M CC18 2016 2016-10-03 TKN -0.1625189295 #> 4007 2048A 3M CC18 2016 2016-10-03 TN -0.1578240852 + #> 4008 2048A 3M CC18 2016 2016-10-03 TP -1.6607312068 #> 4009 2048A 3M CC18 2016 2016-10-03 TURB 0.5306282511 #> 4010 2048A 3M CC18 2016 2016-11-07 CHLAC 0.9932517730 #> 4011 2048A 3M CC18 2016 2016-11-07 COLOR 3.8918202981 #> 4012 2048A 3M CC18 2016 2016-11-07 DOSAT 3.8501476017 + #> 4013 2048A 3M CC18 2016 2016-11-07 NO23 -4.1997050779 #> 4014 2048A 3M CC18 2016 2016-11-07 SALIN 3.0773122605 #> 4015 2048A 3M CC18 2016 2016-11-07 TKN -0.3011050928 #> 4016 2048A 3M CC18 2016 2016-11-07 TN -0.2810375297 + #> 4017 2048A 3M CC18 2016 2016-11-07 TP -1.8971199849 #> 4018 2048A 3M CC18 2016 2016-11-07 TURB 1.1939224685 #> 4019 2048A 3M CC18 2016 2016-12-05 CHLAC 0.9555114450 I #> 4020 2048A 3M CC18 2016 2016-12-05 COLOR 3.4657359028 #> 4021 2048A 3M CC18 2016 2016-12-05 DO 0.9555114450 #> 4022 2048A 3M CC18 2016 2016-12-05 DOSAT 3.5263605246 + #> 4023 2048A 3M CC18 2016 2016-12-05 NO23 -4.2686979494 #> 4024 2048A 3M CC18 2016 2016-12-05 SALIN 3.0726933147 #> 4025 2048A 3M CC18 2016 2016-12-05 TKN -0.4780358009 #> 4026 2048A 3M CC18 2016 2016-12-05 TN -0.4557063245 + #> 4027 2048A 3M CC18 2016 2016-12-05 TP -2.4191189092 #> 4028 2048A 3M CC18 2016 2016-12-05 TURB 0.6418538862 #> 4029 2048A 3M CC18 2017 2017-01-03 CHLAC 0.7884573604 #> 4030 2048A 3M CC18 2017 2017-01-03 COLOR 3.2580965380 A #> 4031 2048A 3M CC18 2017 2017-01-03 DOSAT 3.7999735016 + #> 4032 2048A 3M CC18 2017 2017-01-03 NO23 -4.3428059215 #> 4033 2048A 3M CC18 2017 2017-01-03 SALIN 3.1135153092 #> 4034 2048A 3M CC18 2017 2017-01-03 TKN -0.4004775666 #> 4035 2048A 3M CC18 2017 2017-01-03 TN -0.3812604194 + #> 4036 2048A 3M CC18 2017 2017-01-03 TP -2.1202635362 #> 4037 2048A 3M CC18 2017 2017-01-03 TURB 1.2809338455 #> 4038 2048A 3M CC18 2017 2017-02-06 CHLAC 1.4816045409 #> 4039 2048A 3M CC18 2017 2017-02-06 COLOR 3.2188758249 #> 4040 2048A 3M CC18 2017 2017-02-06 DOSAT 3.7999735016 + #> 4041 2048A 3M CC18 2017 2017-02-06 NO23 -4.7105307016 I #> 4042 2048A 3M CC18 2017 2017-02-06 SALIN 3.1135153092 #> 4043 2048A 3M CC18 2017 2017-02-06 TKN -0.3011050928 #> 4044 2048A 3M CC18 2017 2017-02-06 TN -0.2957142441 + #> 4045 2048A 3M CC18 2017 2017-02-06 TP -2.3126354288 #> 4046 2048A 3M CC18 2017 2017-02-06 TURB 1.0647107370 #> 4047 2048A 3M CC18 2017 2017-03-06 CHLAC 1.6677068206 #> 4048 2048A 3M CC18 2017 2017-03-06 COLOR 3.0445224377 #> 4049 2048A 3M CC18 2017 2017-03-06 DO 2.0541237337 #> 4050 2048A 3M CC18 2017 2017-03-06 DOSAT 4.6071681887 + #> 4051 2048A 3M CC18 2017 2017-03-06 NO23 -5.5214609179 U #> 4052 2048A 3M CC18 2017 2017-03-06 SALIN 3.2921262866 #> 4053 2048A 3M CC18 2017 2017-03-06 TKN -0.3011050928 #> 4054 2048A 3M CC18 2017 2017-03-06 TN -0.2984060358 + #> 4055 2048A 3M CC18 2017 2017-03-06 TP -2.6592600369 #> 4056 2048A 3M CC18 2017 2017-03-06 TURB 1.0986122887 #> 4057 2048A 3M CC18 2017 2017-04-03 CHLAC 1.5892352051 #> 4058 2048A 3M CC18 2017 2017-04-03 COLOR 3.1354942159 #> 4059 2048A 3M CC18 2017 2017-04-03 DO 1.7749523509 #> 4060 2048A 3M CC18 2017 2017-04-03 DOSAT 4.3040650932 + #> 4061 2048A 3M CC18 2017 2017-04-03 NO23 -4.7105307016 I #> 4062 2048A 3M CC18 2017 2017-04-03 SALIN 1.5260563035 #> 4063 2048A 3M CC18 2017 2017-04-03 TN -0.2691874898 + #> 4064 2048A 3M CC18 2017 2017-04-03 TURB 0.9555114450 #> 4065 2048A 3M CC18 2017 2017-05-01 CHLAC 2.2407096893 A #> 4066 2048A 3M CC18 2017 2017-05-01 COLOR 3.4011973817 A #> 4067 2048A 3M CC18 2017 2017-05-01 DO 1.9169226122 #> 4068 2048A 3M CC18 2017 2017-05-01 DOSAT 4.6061696863 + #> 4069 2048A 3M CC18 2017 2017-05-01 NO23 -5.5214609179 U #> 4070 2048A 3M CC18 2017 2017-05-01 SALIN 3.4210000090 #> 4071 2048A 3M CC18 2017 2017-05-01 TKN 0.0953101798 #> 4072 2048A 3M CC18 2017 2017-05-01 TN 0.0971267107 + #> 4073 2048A 3M CC18 2017 2017-05-01 TP -2.1202635362 #> 4074 2048A 3M CC18 2017 2017-05-01 TURB 1.3609765531 #> 4075 2048A 3M CC18 2017 2017-06-05 CHLAC 1.4350845253 #> 4076 2048A 3M CC18 2017 2017-06-05 COLOR 3.6635616461 #> 4077 2048A 3M CC18 2017 2017-06-05 DO 1.8870696490 #> 4078 2048A 3M CC18 2017 2017-06-05 DOSAT 4.6141299274 + #> 4079 2048A 3M CC18 2017 2017-06-05 NO23 -5.2983173665 I #> 4080 2048A 3M CC18 2017 2017-06-05 SALIN 3.4843122884 #> 4081 2048A 3M CC18 2017 2017-06-05 TN -0.1461825102 + #> 4082 2048A 3M CC18 2017 2017-06-05 TURB 0.8754687374 #> 4083 2048A 3M CC18 2017 2017-07-10 CHLAC 2.0281482473 #> 4084 2048A 3M CC18 2017 2017-07-10 COLOR 5.1357984371 #> 4085 2048A 3M CC18 2017 2017-07-10 DO 0.8754687374 #> 4086 2048A 3M CC18 2017 2017-07-10 DOSAT 3.4904285154 + #> 4087 2048A 3M CC18 2017 2017-07-10 SALIN 2.3513752572 #> 4088 2048A 3M CC18 2017 2017-07-10 TN 0.2768738737 + #> 4089 2048A 3M CC18 2017 2017-07-10 TURB 0.6931471806 #> 4090 2048A 3M CC18 2017 2017-08-07 CHLAC 0.7419373447 #> 4091 2048A 3M CC18 2017 2017-08-07 COLOR 5.3471075307 #> 4092 2048A 3M CC18 2017 2017-08-07 DOSAT 2.9123506646 + #> 4093 2048A 3M CC18 2017 2017-08-07 NO23 -2.6592600369 #> 4094 2048A 3M CC18 2017 2017-08-07 SALIN 0.9162907319 #> 4095 2048A 3M CC18 2017 2017-08-07 TKN 0.1823215568 #> 4096 2048A 3M CC18 2017 2017-08-07 TN 0.2390169005 + #> 4097 2048A 3M CC18 2017 2017-08-07 TP -1.3470736480 #> 4098 2048A 3M CC18 2017 2017-08-07 TURB 1.0296194172 #> 4099 2048A 3M CC18 2017 2017-09-05 CHLAC 2.2512917986 #> 4100 2048A 3M CC18 2017 2017-09-05 COLOR 5.2470240722 #> 4101 2048A 3M CC18 2017 2017-09-05 DO 2.2721258855 #> 4102 2048A 3M CC18 2017 2017-09-05 DOSAT 4.8354879411 + #> 4103 2048A 3M CC18 2017 2017-09-05 NO23 -3.2968373663 #> 4104 2048A 3M CC18 2017 2017-09-05 SALIN 1.1631508098 #> 4105 2048A 3M CC18 2017 2017-09-05 TKN 0.0000000000 #> 4106 2048A 3M CC18 2017 2017-09-05 TN 0.0363319292 + #> 4107 2048A 3M CC18 2017 2017-09-05 TP -1.8971199849 #> 4108 2048A 3M CC18 2017 2017-09-05 TURB 0.7419373447 #> 4109 2048A 3M CC18 2017 2017-11-06 CHLAC 1.2809338455 #> 4110 2048A 3M CC18 2017 2017-11-06 COLOR 4.3307333403 #> 4111 2048A 3M CC18 2017 2017-11-06 DO 2.0412203289 #> 4112 2048A 3M CC18 2017 2017-11-06 NO23 -4.3428059215 #> 4113 2048A 3M CC18 2017 2017-11-06 SALIN 2.2721258855 #> 4114 2048A 3M CC18 2017 2017-11-06 TKN -0.3285040670 #> 4115 2048A 3M CC18 2017 2017-11-06 TN -0.3106095771 + #> 4116 2048A 3M CC18 2017 2017-11-06 TP -1.8325814637 #> 4117 2048A 3M CC18 2017 2017-11-06 TURB 0.3364722366 #> 4118 2048A 3M CC18 2017 2017-12-04 CHLAC 0.8329091229 #> 4119 2048A 3M CC18 2017 2017-12-04 COLOR 3.8066624898 #> 4120 2048A 3M CC18 2017 2017-12-04 DO 2.0794415417 #> 4121 2048A 3M CC18 2017 2017-12-04 DOSAT 4.6700211583 + #> 4122 2048A 3M CC18 2017 2017-12-04 NO23 -5.5214609179 U #> 4123 2048A 3M CC18 2017 2017-12-04 SALIN 3.3214324132 #> 4124 2048A 3M CC18 2017 2017-12-04 TKN -0.2876820725 #> 4125 2048A 3M CC18 2017 2017-12-04 TN -0.2850189550 + #> 4126 2048A 3M CC18 2017 2017-12-04 TP -2.2072749132 #> 4127 2048A 3M CC18 2017 2017-12-04 TURB -0.1625189295 #> 4128 2048A 3M CC18 2018 2018-01-02 CHLAC 1.5475625087 #> 4129 2048A 3M CC18 2018 2018-01-02 COLOR 3.4965075615 #> 4130 2048A 3M CC18 2018 2018-01-02 DOSAT 4.3161538905 + #> 4131 2048A 3M CC18 2018 2018-01-02 NO23 -5.5214609179 U #> 4132 2048A 3M CC18 2018 2018-01-02 SALIN 2.4248027257 #> 4133 2048A 3M CC18 2018 2018-01-02 TN -0.4910229965 + #> 4134 2048A 3M CC18 2018 2018-01-02 TURB 0.5877866649 #> 4135 2048A 3M CC18 2018 2018-03-05 CHLAC 0.8329091229 #> 4136 2048A 3M CC18 2018 2018-03-05 COLOR 3.5835189385 #> 4137 2048A 3M CC18 2018 2018-03-05 NO23 -5.5214609179 U #> 4138 2048A 3M CC18 2018 2018-03-05 TKN -0.3011050928 #> 4139 2048A 3M CC18 2018 2018-03-05 TN -0.2984060358 + #> 4140 2048A 3M CC18 2018 2018-03-05 TP -1.8971199849 #> 4141 2048A 3M CC18 2018 2018-03-05 TURB 1.0296194172 #> 4142 2048A 3M CC18 2018 2018-04-02 CHLAC 1.6677068206 #> 4143 2048A 3M CC18 2018 2018-04-02 COLOR 3.3322045102 #> 4144 2048A 3M CC18 2018 2018-04-02 DOSAT 4.2513483110 + #> 4145 2048A 3M CC18 2018 2018-04-02 NO23 -5.2983173665 I #> 4146 2048A 3M CC18 2018 2018-04-02 SALIN 3.2027464429 #> 4147 2048A 3M CC18 2018 2018-04-02 TKN -0.2613647641 #> 4148 2048A 3M CC18 2018 2018-04-02 TN -0.2561834054 + #> 4149 2048A 3M CC18 2018 2018-04-02 TP -1.9661128564 #> 4150 2048A 3M CC18 2018 2018-04-02 TURB 1.3083328197 #> 4151 2048A 3M CC18 2018 2018-05-07 CHLAC 1.8562979904 #> 4152 2048A 3M CC18 2018 2018-05-07 COLOR 3.3322045102 A #> 4153 2048A 3M CC18 2018 2018-05-07 DO 2.1016921506 #> 4154 2048A 3M CC18 2018 2018-05-07 DOSAT 4.6051701860 #> 4155 2048A 3M CC18 2018 2018-05-07 NO23 -5.5214609179 I #> 4156 2048A 3M CC18 2018 2018-05-07 SALIN 3.2812870850 #> 4157 2048A 3M CC18 2018 2018-05-07 TKN -0.0943106795 #> 4158 2048A 3M CC18 2018 2018-05-07 TN -0.0899247075 + #> 4159 2048A 3M CC18 2018 2018-05-07 TP -2.2072749132 #> 4160 2048A 3M CC18 2018 2018-05-07 TURB 1.2527629685 #> 4161 2048A 3M CC18 2018 2018-06-04 CHLAC 1.8405496334 #> 4162 2048A 3M CC18 2018 2018-06-04 COLOR 4.6051701860 #> 4163 2048A 3M CC18 2018 2018-06-04 DO 2.0906287311 #> 4164 2048A 3M CC18 2018 2018-06-04 DOSAT 4.6011621646 #> 4165 2048A 3M CC18 2018 2018-06-04 NO23 -4.6051701860 I #> 4166 2048A 3M CC18 2018 2018-06-04 SALIN 1.8115620965 #> 4167 2048A 3M CC18 2018 2018-06-04 TKN -0.0725706928 #> 4168 2048A 3M CC18 2018 2018-06-04 TN -0.0682788408 + #> 4169 2048A 3M CC18 2018 2018-06-04 TP -1.6094379124 #> 4170 2048A 3M CC18 2018 2018-06-04 TURB 0.5306282511 #> 4171 2048A 3M CC18 2018 2018-07-09 CHLAC 2.4849066498 #> 4172 2048A 3M CC18 2018 2018-07-09 COLOR 4.9416424226 #> 4173 2048A 3M CC18 2018 2018-07-09 DO 1.4929040962 #> 4174 2048A 3M CC18 2018 2018-07-09 DOSAT 4.1415461637 #> 4175 2048A 3M CC18 2018 2018-07-09 NO23 -4.9618451299 I #> 4176 2048A 3M CC18 2018 2018-07-09 SALIN 1.3402504226 #> 4177 2048A 3M CC18 2018 2018-07-09 TKN -0.2231435513 #> 4178 2048A 3M CC18 2018 2018-07-09 TN -0.2181560098 + #> 4179 2048A 3M CC18 2018 2018-07-09 TP -1.7719568419 #> 4180 2048A 3M CC18 2018 2018-07-09 TURB 0.8754687374 #> 4181 2048A 3M CC18 2019 2019-05-06 CHLAC 0.9555114450 #> 4182 2048A 3M CC18 2019 2019-05-06 COLOR 3.6109179126 #> 4183 2048A 3M CC18 2019 2019-05-06 DO 0.8837675402 #> 4184 2048A 3M CC18 2019 2019-05-06 DOSAT 3.5351453542 #> 4185 2048A 3M CC18 2019 2019-05-06 NO23 -5.2983173665 I #> 4186 2048A 3M CC18 2019 2019-05-06 SALIN 2.9719517449 #> 4187 2048A 3M CC18 2019 2019-05-06 TKN -0.2744368457 #> 4188 2048A 3M CC18 2019 2019-05-06 TN -0.2691874898 + #> 4189 2048A 3M CC18 2019 2019-05-06 TP -1.7719568419 #> 4190 2048A 3M CC18 2019 2019-05-06 TURB 0.7419373447 #> 4191 2048A 3M CC18 2019 2019-06-03 CHLAC 1.5686159179 #> 4192 2048A 3M CC18 2019 2019-06-03 COLOR 3.7376696183 #> 4193 2048A 3M CC18 2019 2019-06-03 DO 0.6418538862 #> 4194 2048A 3M CC18 2019 2019-06-03 DOSAT 3.3322045102 #> 4195 2048A 3M CC18 2019 2019-06-03 NO23 -5.5214609179 U #> 4196 2048A 3M CC18 2019 2019-06-03 SALIN 3.0363942553 #> 4197 2048A 3M CC18 2019 2019-06-03 TKN -0.0725706928 #> 4198 2048A 3M CC18 2019 2019-06-03 TN -0.0704224643 + #> 4199 2048A 3M CC18 2019 2019-06-03 TP -1.3470736480 #> 4200 2048A 3M CC18 2019 2019-06-03 TURB 1.4586150227 A #> 4201 2048A 3M CC18 2019 2019-07-01 CHLAC 1.6863989536 #> 4202 2048A 3M CC18 2019 2019-07-01 COLOR 3.6635616461 #> 4203 2048A 3M CC18 2019 2019-07-01 DO 0.9162907319 #> 4204 2048A 3M CC18 2019 2019-07-01 DOSAT 3.4483989831 #> 4205 2048A 3M CC18 2019 2019-07-01 NO23 -5.5214609179 U #> 4206 2048A 3M CC18 2019 2019-07-01 SALIN 2.9678470701 #> 4207 2048A 3M CC18 2019 2019-07-01 TKN -0.2484613593 #> 4208 2048A 3M CC18 2019 2019-07-01 TN -0.2459005384 + #> 4209 2048A 3M CC18 2019 2019-07-01 TP -1.2729656758 #> 4210 2048A 3M CC18 2019 2019-07-01 TURB 0.4054651081 #> 4211 2048A 3M CC18 2019 2019-08-05 CHLAC 1.4109869737 #> 4212 2048A 3M CC18 2019 2019-08-05 COLOR 5.0751738152 #> 4213 2048A 3M CC18 2019 2019-08-05 DO 1.1378330018 #> 4214 2048A 3M CC18 2019 2019-08-05 DOSAT 3.7305011288 #> 4215 2048A 3M CC18 2019 2019-08-05 NO23 -5.5214609179 I #> 4216 2048A 3M CC18 2019 2019-08-05 SALIN 1.6134299337 #> 4217 2048A 3M CC18 2019 2019-08-05 TKN -0.0618754037 #> 4218 2048A 3M CC18 2019 2019-08-05 TN -0.0576291128 + #> 4219 2048A 3M CC18 2019 2019-08-05 TP -1.5606477483 #> 4220 2048A 3M CC18 2019 2019-08-05 TURB 0.8754687374 #> 4221 2048A 3M CC18 2019 2019-10-07 CHLAC 1.0986122887 I #> 4222 2048A 3M CC18 2019 2019-10-07 COLOR 4.3820266347 #> 4223 2048A 3M CC18 2019 2019-10-07 DO 1.0152306797 #> 4224 2048A 3M CC18 2019 2019-10-07 DOSAT 3.6375861597 #> 4225 2048A 3M CC18 2019 2019-10-07 NO23 -4.9618451299 I #> 4226 2048A 3M CC18 2019 2019-10-07 SALIN 2.7389026646 #> 4227 2048A 3M CC18 2019 2019-10-07 TKN -0.1278333715 #> 4228 2048A 3M CC18 2019 2019-10-07 TN -0.1232982163 + #> 4229 2048A 3M CC18 2019 2019-10-07 TP -1.3862943611 #> 4230 2048A 3M CC18 2019 2019-10-07 TURB 0.4054651081 #> 4231 2048A 3M CC18 2019 2019-11-04 CHLAC 1.0296194172 #> 4232 2048A 3M CC18 2019 2019-11-04 COLOR 4.1431347264 #> 4233 2048A 3M CC18 2019 2019-11-04 DO 1.2267122913 #> 4234 2048A 3M CC18 2019 2019-11-04 DOSAT 3.8177123260 #> 4235 2048A 3M CC18 2019 2019-11-04 NO23 -5.5214609179 I #> 4236 2048A 3M CC18 2019 2019-11-04 SALIN 2.8075938314 #> 4237 2048A 3M CC18 2019 2019-11-04 TKN -0.1508228897 #> 4238 2048A 3M CC18 2019 2019-11-04 TN -0.1461825102 + #> 4239 2048A 3M CC18 2019 2019-11-04 TP -1.6094379124 #> 4240 2048A 3M CC18 2019 2019-11-04 TURB 0.2623642645 A #> 4241 2048A 3M CC18 2019 2019-11-04 DO 1.2267122913 #> 4242 2048A 3M CC18 2019 2019-11-04 DOSAT 3.8177123260 #> 4243 2048A 3M CC18 2019 2019-11-04 SALIN 2.8075938314 #> 4244 2048A 3M CC18 2019 2019-12-02 CHLAC 1.2809338455 #> 4245 2048A 3M CC18 2019 2019-12-02 COLOR 3.6888794541 A #> 4246 2048A 3M CC18 2019 2019-12-02 DO 1.5518087996 #> 4247 2048A 3M CC18 2019 2019-12-02 DOSAT 4.1059436981 #> 4248 2048A 3M CC18 2019 2019-12-02 NO23 -5.5214609179 U #> 4249 2048A 3M CC18 2019 2019-12-02 SALIN 2.9412760878 #> 4250 2048A 3M CC18 2019 2019-12-02 TKN -0.2613647641 #> 4251 2048A 3M CC18 2019 2019-12-02 TN -0.2587707290 + #> 4252 2048A 3M CC18 2019 2019-12-02 TP -2.2072749132 #> 4253 2048A 3M CC18 2019 2019-12-02 TURB 0.0953101798 #> 4254 2048A 3M CC18 2020 2020-01-06 CHLAC 1.7578579176 #> 4255 2048A 3M CC18 2020 2020-01-06 COLOR 3.5263605246 #> 4256 2048A 3M CC18 2020 2020-01-06 DO 1.6770965609 #> 4257 2048A 3M CC18 2020 2020-01-06 DOSAT 4.1541845626 #> 4258 2048A 3M CC18 2020 2020-01-06 NO23 -5.5214609179 U #> 4259 2048A 3M CC18 2020 2020-01-06 SALIN 2.8713021952 #> 4260 2048A 3M CC18 2020 2020-01-06 TKN -0.5276327421 #> 4261 2048A 3M CC18 2020 2020-01-06 TN -0.5242486441 + #> 4262 2048A 3M CC18 2020 2020-01-06 TP -1.8971199849 #> 4263 2048A 3M CC18 2020 2020-01-06 TURB 0.3364722366 #> 4264 2048A 3M CC18 2020 2020-02-03 CHLAC 2.6390573296 #> 4265 2048A 3M CC18 2020 2020-02-03 COLOR 3.3672958300 #> 4266 2048A 3M CC18 2020 2020-02-03 DO 1.7137979278 #> 4267 2048A 3M CC18 2020 2020-02-03 DOSAT 4.1941898972 #> 4268 2048A 3M CC18 2020 2020-02-03 NO23 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#> 4357 2048A 3M CC18 2021 2021-05-03 NO23 -5.5214609179 I #> 4358 2048A 3M CC18 2021 2021-05-03 SALIN 3.1726224404 #> 4359 2048A 3M CC18 2021 2021-05-03 TKN -0.3566749439 #> 4360 2048A 3M CC18 2021 2021-05-03 TN -0.3509769228 + #> 4361 2048A 3M CC18 2021 2021-05-03 TP -1.8325814637 #> 4362 2048A 3M CC18 2021 2021-05-03 TURB 0.5877866649 #> 4363 2048A 3M CC18 2021 2021-06-07 CHLAC 1.5686159179 I #> 4364 2048A 3M CC18 2021 2021-06-07 COLOR 3.5835189385 #> 4365 2048A 3M CC18 2021 2021-06-07 DO 1.0508216248 #> 4366 2048A 3M CC18 2021 2021-06-07 DOSAT 4.2918283668 #> 4367 2048A 3M CC18 2021 2021-06-07 NO23 -5.2983173665 I #> 4368 2048A 3M CC18 2021 2021-06-07 SALIN 3.2476576263 #> 4369 2048A 3M CC18 2021 2021-06-07 TKN -0.2484613593 #> 4370 2048A 3M CC18 2021 2021-06-07 TN -0.2433462586 + #> 4371 2048A 3M CC18 2021 2021-06-07 TP -1.5141277326 #> 4372 2048A 3M CC18 2021 2021-06-07 TURB 0.5306282511 #> 4373 2048A 3M CC18 2021 2021-08-02 CHLAC 1.8082887712 #> 4374 2048A 3M CC18 2021 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TURB 0.5306282511 #> 4498 2048A 3M CC18 2022 2022-12-05 CHLAC 1.1314021115 #> 4499 2048A 3M CC18 2022 2022-12-05 COLOR 4.2341065046 #> 4500 2048A 3M CC18 2022 2022-12-05 DO 1.7119945008 #> 4501 2048A 3M CC18 2022 2022-12-05 DOSAT 4.2046926194 #> 4502 2048A 3M CC18 2022 2022-12-05 NO23 -4.6051701860 #> 4503 2048A 3M CC18 2022 2022-12-05 SALIN 2.4475508632 #> 4504 2048A 3M CC18 2022 2022-12-05 TKN -0.1984509387 #> 4505 2048A 3M CC18 2022 2022-12-05 TN -0.1863295782 + #> 4506 2048A 3M CC18 2022 2022-12-05 TP -1.7719568419 #> 4507 2048A 3M CC18 2022 2022-12-05 TURB -0.0512932944 I #> 4508 2048A 3M CC18 2023 2023-02-06 CHLAC 1.5260563035 #> 4509 2048A 3M CC18 2023 2023-02-06 COLOR 3.4657359028 #> 4510 2048A 3M CC18 2023 2023-02-06 DO 1.6863989536 #> 4511 2048A 3M CC18 2023 2023-02-06 DOSAT 4.2341065046 #> 4512 2048A 3M CC18 2023 2023-02-06 NO23 -5.2983173665 I #> 4513 2048A 3M CC18 2023 2023-02-06 SALIN 2.9269179576 #> 4514 2048A 3M CC18 2023 2023-02-06 TKN -0.4155154440 #> 4515 2048A 3M CC18 2023 2023-02-06 TN -0.4094731295 + #> 4516 2048A 3M CC18 2023 2023-02-06 TP -2.1202635362 #> 4517 2048A 3M CC18 2023 2023-02-06 TURB 0.6931471806 #> 4518 2048A 3M CC18 2023 2023-03-06 CHLAC 1.8718021769 #> 4519 2048A 3M CC18 2023 2023-03-06 COLOR 3.3672958300 #> 4520 2048A 3M CC18 2023 2023-03-06 DO 1.1442227999 #> 4521 2048A 3M CC18 2023 2023-03-06 DOSAT 3.7977338590 #> 4522 2048A 3M CC18 2023 2023-03-06 NO23 -4.4228486292 #> 4523 2048A 3M CC18 2023 2023-03-06 SALIN 3.0199369623 #> 4524 2048A 3M CC18 2023 2023-03-06 TKN 0.1823215568 #> 4525 2048A 3M CC18 2023 2023-03-06 TN 0.1922718876 + #> 4526 2048A 3M CC18 2023 2023-03-06 TP -1.9661128564 #> 4527 2048A 3M CC18 2023 2023-03-06 TURB 0.7884573604 #> 4528 2060A1 2 CC25 2014 2014-02-12 CHLAC 1.4109869737 #> 4529 2060A1 2 CC25 2014 2014-02-12 COLOR 3.2188758249 #> 4530 2060A1 2 CC25 2014 2014-02-12 COND 10.5921245776 #> 4531 2060A1 2 CC25 2014 2014-02-12 DO 1.9933388426 #> 4532 2060A1 2 CC25 2014 2014-02-12 DOSAT 4.5570298107 + #> 4533 2060A1 2 CC25 2014 2014-02-12 NO23 -5.5214609179 U #> 4534 2060A1 2 CC25 2014 2014-02-12 SALIN 3.2367157430 #> 4535 2060A1 2 CC25 2014 2014-02-12 TKN -0.7657178734 #> 4536 2060A1 2 CC25 2014 2014-02-12 TN -0.7657178734 #> 4537 2060A1 2 CC25 2014 2014-02-12 TP -2.0099154790 #> 4538 2060A1 2 CC25 2014 2014-02-12 TSS 1.7917594692 #> 4539 2060A1 2 CC25 2014 2014-02-12 TURB 0.1823215568 #> 4540 2060A1 2 CC25 2014 2014-02-12 COND 10.5938809449 #> 4541 2060A1 2 CC25 2014 2014-02-12 DO 1.9919755159 #> 4542 2060A1 2 CC25 2014 2014-02-12 DOSAT 4.5559799418 + #> 4543 2060A1 2 CC25 2014 2014-02-12 SALIN 3.2386784522 #> 4544 2060A1 2 CC25 2014 2014-07-09 CHLAC 2.1838015570 #> 4545 2060A1 2 CC25 2014 2014-07-09 COLOR 3.8066624898 #> 4546 2060A1 2 CC25 2014 2014-07-09 COND 10.5001238327 #> 4547 2060A1 2 CC25 2014 2014-07-09 DO 1.7047480922 #> 4548 2060A1 2 CC25 2014 2014-07-09 DOSAT 4.4164280614 + #> 4549 2060A1 2 CC25 2014 2014-07-09 NO23 -5.5214609179 U #> 4550 2060A1 2 CC25 2014 2014-07-09 SALIN 3.1271990363 #> 4551 2060A1 2 CC25 2014 2014-07-09 TKN -0.2319320573 #> 4552 2060A1 2 CC25 2014 2014-07-09 TN -0.2319320573 #> 4553 2060A1 2 CC25 2014 2014-07-09 TP -1.3167682985 #> 4554 2060A1 2 CC25 2014 2014-07-09 TSS 1.9286186519 #> 4555 2060A1 2 CC25 2014 2014-07-09 TURB 0.8329091229 #> 4556 2060A1 2 CC25 2014 2014-07-09 COND 10.5012245483 #> 4557 2060A1 2 CC25 2014 2014-07-09 DO 1.7029282555 #> 4558 2060A1 2 CC25 2014 2014-07-09 DOSAT 4.4115854369 + #> 4559 2060A1 2 CC25 2014 2014-07-09 SALIN 3.1285133848 #> 4560 2060A1 2 CC25 2014 2014-08-12 CHLAC 3.6558396000 #> 4561 2060A1 2 CC25 2014 2014-08-12 COLOR 4.3820266347 #> 4562 2060A1 2 CC25 2014 2014-08-12 COND 9.9744118909 #> 4563 2060A1 2 CC25 2014 2014-08-12 DO 1.9643112344 #> 4564 2060A1 2 CC25 2014 2014-08-12 DOSAT 4.6424659707 + #> 4565 2060A1 2 CC25 2014 2014-08-12 NO23 -5.5214609179 U #> 4566 2060A1 2 CC25 2014 2014-08-12 SALIN 2.5478814489 #> 4567 2060A1 2 CC25 2014 2014-08-12 TKN 0.1484200051 #> 4568 2060A1 2 CC25 2014 2014-08-12 TN 0.1484200051 #> 4569 2060A1 2 CC25 2014 2014-08-12 TP -0.9808292530 #> 4570 2060A1 2 CC25 2014 2014-08-12 TSS 2.3887627892 #> 4571 2060A1 2 CC25 2014 2014-08-12 TURB 1.6292405397 #> 4572 2060A1 2 CC25 2014 2014-08-12 COND 9.9753429896 #> 4573 2060A1 2 CC25 2014 2014-08-12 DO 1.9586853405 #> 4574 2060A1 2 CC25 2014 2014-08-12 DOSAT 4.6366688530 + #> 4575 2060A1 2 CC25 2014 2014-08-12 SALIN 2.5486636156 #> 4576 2060A1 2 CC25 2014 2014-08-12 COND 9.9753429896 #> 4577 2060A1 2 CC25 2014 2014-08-12 DO 1.9530276168 #> 4578 2060A1 2 CC25 2014 2014-08-12 DOSAT 4.6308379327 + #> 4579 2060A1 2 CC25 2014 2014-08-12 SALIN 2.5486636156 #> 4580 2060A1 2 CC25 2014 2014-10-21 CHLAC 0.9555114450 #> 4581 2060A1 2 CC25 2014 2014-10-21 COLOR 4.7874917428 #> 4582 2060A1 2 CC25 2014 2014-10-21 COND 10.1330107108 #> 4583 2060A1 2 CC25 2014 2014-10-21 DO 1.4701758451 #> 4584 2060A1 2 CC25 2014 2014-10-21 DOSAT 4.0809215419 + #> 4585 2060A1 2 CC25 2014 2014-10-21 NO23 -3.1941832123 #> 4586 2060A1 2 CC25 2014 2014-10-21 SALIN 2.7258901192 #> 4587 2060A1 2 CC25 2014 2014-10-21 TKN -0.1053605157 #> 4588 2060A1 2 CC25 2014 2014-10-21 TN -0.0608121394 #> 4589 2060A1 2 CC25 2014 2014-10-21 TP -1.4354846053 #> 4590 2060A1 2 CC25 2014 2014-10-21 TSS 1.5973653312 #> 4591 2060A1 2 CC25 2014 2014-10-21 TURB 0.8329091229 #> 4592 2060A1 2 CC25 2014 2014-10-21 COND 10.1472177375 #> 4593 2060A1 2 CC25 2014 2014-10-21 DO 1.4182774070 #> 4594 2060A1 2 CC25 2014 2014-10-21 DOSAT 4.0271358125 + #> 4595 2060A1 2 CC25 2014 2014-10-21 SALIN 2.7414849772 #> 4596 2060A1 2 CC25 2014 2014-10-21 COND 10.1612257486 #> 4597 2060A1 2 CC25 2014 2014-10-21 DO 1.3862943611 #> 4598 2060A1 2 CC25 2014 2014-10-21 DOSAT 3.9963641539 + #> 4599 2060A1 2 CC25 2014 2014-10-21 SALIN 2.7581094010 #> 4600 2060A1 2 CC25 2015 2015-02-03 CHLAC 1.7209792872 #> 4601 2060A1 2 CC25 2015 2015-02-03 COLOR 3.8066624898 #> 4602 2060A1 2 CC25 2015 2015-02-03 COND 10.4795389612 #> 4603 2060A1 2 CC25 2015 2015-02-03 DO 2.1758874399 #> 4604 2060A1 2 CC25 2015 2015-02-03 DOSAT 4.6596583713 + #> 4605 2060A1 2 CC25 2015 2015-02-03 NO23 -5.5214609179 U #> 4606 2060A1 2 CC25 2015 2015-02-03 SALIN 3.1130707660 #> 4607 2060A1 2 CC25 2015 2015-02-03 TKN -0.4975803970 #> 4608 2060A1 2 CC25 2015 2015-02-03 TN -0.4975803970 #> 4609 2060A1 2 CC25 2015 2015-02-03 TP -2.1037342342 #> 4610 2060A1 2 CC25 2015 2015-02-03 TSS 2.6100697927 #> 4611 2060A1 2 CC25 2015 2015-02-03 TURB 0.7884573604 #> 4612 2060A1 2 CC25 2015 2015-02-03 COND 10.4887710872 #> 4613 2060A1 2 CC25 2015 2015-02-03 DO 2.1644717909 #> 4614 2060A1 2 CC25 2015 2015-02-03 DOSAT 4.6482296754 + #> 4615 2060A1 2 CC25 2015 2015-02-03 SALIN 3.1232455939 #> 4616 2060A1 2 CC25 2015 2015-02-03 COND 10.4921072037 #> 4617 2060A1 2 CC25 2015 2015-02-03 DO 2.1621729393 #> 4618 2060A1 2 CC25 2015 2015-02-03 DOSAT 4.6463121293 + #> 4619 2060A1 2 CC25 2015 2015-02-03 SALIN 3.1267605360 #> 4620 2060A1 2 CC25 2016 2016-09-13 CHLAC 1.4206957878 #> 4621 2060A1 2 CC25 2016 2016-09-13 COND 8.8724871823 #> 4622 2060A1 2 CC25 2016 2016-09-13 DO 1.7191887764 #> 4623 2060A1 2 CC25 2016 2016-09-13 DOSAT 4.3346729383 + #> 4624 2060A1 2 CC25 2016 2016-09-13 NO23 -2.7333680091 #> 4625 2060A1 2 CC25 2016 2016-09-13 SALIN 1.3584091576 #> 4626 2060A1 2 CC25 2016 2016-09-13 TKN 0.2851789422 #> 4627 2060A1 2 CC25 2016 2016-09-13 TN 0.3364722366 #> 4628 2060A1 2 CC25 2016 2016-09-13 TP -1.2207799226 #> 4629 2060A1 2 CC25 2016 2016-09-13 TSS 0.4700036292 I #> 4630 2060A1 2 CC25 2016 2016-09-13 TURB 0.6418538862 #> 4631 2060A1 2 CC25 2016 2016-09-13 COND 9.4834162920 #> 4632 2060A1 2 CC25 2016 2016-09-13 DO 1.6882490929 #> 4633 2060A1 2 CC25 2016 2016-09-13 DOSAT 4.3134800921 + #> 4634 2060A1 2 CC25 2016 2016-09-13 SALIN 2.0162354658 #> 4635 2060A1 2 CC25 2016 2016-09-13 COND 9.6395220067 #> 4636 2060A1 2 CC25 2016 2016-09-13 DO 1.6544112781 #> 4637 2060A1 2 CC25 2016 2016-09-13 DOSAT 4.2835865619 + #> 4638 2060A1 2 CC25 2016 2016-09-13 SALIN 2.1849270495 #> 4639 2046 3M CC31 2018 2018-03-07 CHLAC 1.6094379124 #> 4640 2046 3M CC31 2018 2018-03-07 COND 10.3531928066 #> 4641 2046 3M CC31 2018 2018-03-07 DO 1.9021075264 #> 4642 2046 3M CC31 2018 2018-03-07 DOSAT 4.4670568839 #> 4643 2046 3M CC31 2018 2018-03-07 NO23 -4.7105307016 I #> 4644 2046 3M CC31 2018 2018-03-07 SALIN 3.0170044088 + #> 4645 2046 3M CC31 2018 2018-03-07 TKN -0.3710636814 #> 4646 2046 3M CC31 2018 2018-03-07 TN -0.3652833185 + #> 4647 2046 3M CC31 2018 2018-03-07 TP -1.8971199849 #> 4648 2046 3M CC31 2018 2018-03-07 TSS 1.3862943611 I #> 4649 2046 3M CC31 2018 2018-03-07 TURB 0.8754687374 #> 4650 2046 3M CC31 2018 2018-04-09 CHLAC 1.2809338455 A #> 4651 2046 3M CC31 2018 2018-04-09 COND 10.6261935353 #> 4652 2046 3M CC31 2018 2018-04-09 DO 1.3083328197 #> 4653 2046 3M CC31 2018 2018-04-09 DOSAT 3.9702919136 #> 4654 2046 3M CC31 2018 2018-04-09 NO23 -3.7297014486 #> 4655 2046 3M CC31 2018 2018-04-09 SALIN 3.2484346271 + #> 4656 2046 3M CC31 2018 2018-04-09 TKN -0.3147107448 #> 4657 2046 3M CC31 2018 2018-04-09 TN -0.2823629110 + #> 4658 2046 3M CC31 2018 2018-04-09 TP -1.7147984281 #> 4659 2046 3M CC31 2018 2018-04-09 TSS 1.6094379124 I #> 4660 2046 3M CC31 2018 2018-04-09 TURB 0.6931471806 #> 4661 2046 3M CC31 2018 2018-05-24 CHLAC 2.7080502011 #> 4662 2046 3M CC31 2018 2018-05-24 COND 9.7756541810 #> 4663 2046 3M CC31 2018 2018-05-24 DO 1.5303947051 #> 4664 2046 3M CC31 2018 2018-05-24 DOSAT 4.1009891049 #> 4665 2046 3M CC31 2018 2018-05-24 NO23 -3.1010927892 #> 4666 2046 3M CC31 2018 2018-05-24 SALIN 2.3065771143 + #> 4667 2046 3M CC31 2018 2018-05-24 TKN -0.2613647641 #> 4668 2046 3M CC31 2018 2018-05-24 TN -0.2045671657 + #> 4669 2046 3M CC31 2018 2018-05-24 TP -1.4271163556 #> 4670 2046 3M CC31 2018 2018-05-24 TSS 1.6094379124 I #> 4671 2046 3M CC31 2018 2018-05-24 TURB 0.9932517730 #> 4672 2046 3M CC31 2018 2018-07-23 CHLAC 1.4350845253 #> 4673 2046 3M CC31 2018 2018-07-23 COND 8.9291703831 #> 4674 2046 3M CC31 2018 2018-07-23 DO 1.6937790609 #> 4675 2046 3M CC31 2018 2018-07-23 DOSAT 4.3040650932 #> 4676 2046 3M CC31 2018 2018-07-23 NO23 -2.0402208285 #> 4677 2046 3M CC31 2018 2018-07-23 SALIN 1.4182774070 #> 4678 2046 3M CC31 2018 2018-07-23 TKN 0.0000000000 #> 4679 2046 3M CC31 2018 2018-07-23 TN 0.1222176327 + #> 4680 2046 3M CC31 2018 2018-07-23 TP -0.9162907319 #> 4681 2046 3M CC31 2018 2018-07-23 TSS 1.3862943611 I #> 4682 2046 3M CC31 2018 2018-07-23 TURB 0.9162907319 A #> 4683 2046 3M CC31 2018 2018-08-21 CHLAC 2.7080502011 #> 4684 2046 3M CC31 2018 2018-08-21 COND 8.6210125201 #> 4685 2046 3M CC31 2018 2018-08-21 DO 1.4586150227 #> 4686 2046 3M CC31 2018 2018-08-21 DOSAT 4.0724397268 #> 4687 2046 3M CC31 2018 2018-08-21 NO23 -3.4737680745 #> 4688 2046 3M CC31 2018 2018-08-21 SALIN 1.0885619528 #> 4689 2046 3M CC31 2018 2018-08-21 TKN 1.7047480922 #> 4690 2046 3M CC31 2018 2018-08-21 TN 1.7103686310 + #> 4691 2046 3M CC31 2018 2018-08-21 TSS 1.6094379124 I #> 4692 2046 3M CC31 2018 2018-08-21 TURB 1.3350010667 #> 4693 2046 3M CC31 2018 2018-11-12 CHLAC 1.5686159179 #> 4694 2046 3M CC31 2018 2018-11-12 COND 10.1213773269 #> 4695 2046 3M CC31 2018 2018-11-12 DO 1.6695918353 #> 4696 2046 3M CC31 2018 2018-11-12 DOSAT 4.3121405072 #> 4697 2046 3M CC31 2018 2018-11-12 NO23 -3.4112477175 #> 4698 2046 3M CC31 2018 2018-11-12 SALIN 2.7127060126 #> 4699 2046 3M CC31 2018 2018-11-12 TKN -0.3011050928 #> 4700 2046 3M CC31 2018 2018-11-12 TN -0.2574762304 + #> 4701 2046 3M CC31 2018 2018-11-12 TP -1.8325814637 #> 4702 2046 3M CC31 2018 2018-11-12 TSS 1.3862943611 I #> 4703 2046 3M CC31 2018 2018-11-12 TURB 0.4700036292 #> 4704 2046 3M CC31 2018 2018-11-12 COND 10.3160937688 #> 4705 2046 3M CC31 2018 2018-11-12 DO 1.5581446180 #> 4706 2046 3M CC31 2018 2018-11-12 DOSAT 4.2076732475 #> 4707 2046 3M CC31 2018 2018-11-12 SALIN 2.9269179576 #> 4708 2046 3M CC31 2019 2019-02-07 CHLAC 3.3672958300 #> 4709 2046 3M CC31 2019 2019-02-07 COND 9.8807305654 #> 4710 2046 3M CC31 2019 2019-02-07 NO23 -5.5214609179 U #> 4711 2046 3M CC31 2019 2019-02-07 SALIN 2.4544474423 #> 4712 2046 3M CC31 2019 2019-02-07 TKN -0.3710636814 #> 4713 2046 3M CC31 2019 2019-02-07 TN -0.3681693234 + #> 4714 2046 3M CC31 2019 2019-02-07 TP -1.6607312068 #> 4715 2046 3M CC31 2019 2019-02-07 TSS 3.3322045102 A #> 4716 2046 3M CC31 2019 2019-02-07 TURB 2.4849066498 A #> 4717 2046 3M CC31 2019 2019-03-13 CHLAC 2.3978952728 #> 4718 2046 3M CC31 2019 2019-03-13 COND 10.1587109973 #> 4719 2046 3M CC31 2019 2019-03-13 DO 1.5830939371 #> 4720 2046 3M CC31 2019 2019-03-13 DOSAT 4.1588830834 #> 4721 2046 3M CC31 2019 2019-03-13 NO23 -5.5214609179 U #> 4722 2046 3M CC31 2019 2019-03-13 SALIN 2.7568403653 #> 4723 2046 3M CC31 2019 2019-03-13 TKN -0.2876820725 #> 4724 2046 3M CC31 2019 2019-03-13 TN -0.2850189550 + #> 4725 2046 3M CC31 2019 2019-03-13 TP -1.7719568419 #> 4726 2046 3M CC31 2019 2019-03-13 TSS 1.3862943611 I #> 4727 2046 3M CC31 2019 2019-03-13 TURB 0.8754687374 #> 4728 2046 3M CC31 2019 2019-04-23 CHLAC 1.8562979904 #> 4729 2046 3M CC31 2019 2019-04-23 COND 10.2120745857 #> 4730 2046 3M CC31 2019 2019-04-23 DO 1.8389610707 #> 4731 2046 3M CC31 2019 2019-04-23 DOSAT 4.4188406078 #> 4732 2046 3M CC31 2019 2019-04-23 NO23 -5.5214609179 U #> 4733 2046 3M CC31 2019 2019-04-23 SALIN 2.8154087194 #> 4734 2046 3M CC31 2019 2019-04-23 TKN -0.4307829161 #> 4735 2046 3M CC31 2019 2019-04-23 TN -0.4277107171 + #> 4736 2046 3M CC31 2019 2019-04-23 TP -1.6094379124 #> 4737 2046 3M CC31 2019 2019-04-23 TSS 2.5649493575 #> 4738 2046 3M CC31 2019 2019-04-23 TURB 1.4350845253 #> 4739 2046 3M CC31 2019 2019-07-22 CHLAC 2.0281482473 #> 4740 2046 3M CC31 2019 2019-07-22 COND 9.5882287123 #> 4741 2046 3M CC31 2019 2019-07-22 DO 1.6808279085 #> 4742 2046 3M CC31 2019 2019-07-22 DOSAT 4.3174881135 #> 4743 2046 3M CC31 2019 2019-07-22 NO23 -5.1159958098 I #> 4744 2046 3M CC31 2019 2019-07-22 SALIN 2.1282317058 #> 4745 2046 3M CC31 2019 2019-07-22 TKN -0.2484613593 #> 4746 2046 3M CC31 2019 2019-07-22 TN -0.2433462586 + #> 4747 2046 3M CC31 2019 2019-07-22 TP -1.3862943611 #> 4748 2046 3M CC31 2019 2019-07-22 TSS 0.6931471806 I #> 4749 2046 3M CC31 2019 2019-07-22 TURB 0.7419373447 #> 4750 2046 3M CC31 2019 2019-09-04 CHLAC 2.6390573296 #> 4751 2046 3M CC31 2019 2019-09-04 COND 9.5618419571 #> 4752 2046 3M CC31 2019 2019-09-04 DO 1.6486586256 #> 4753 2046 3M CC31 2019 2019-09-04 DOSAT 4.2752762647 #> 4754 2046 3M CC31 2019 2019-09-04 NO23 -3.1465551633 #> 4755 2046 3M CC31 2019 2019-09-04 SALIN 2.1004689089 #> 4756 2046 3M CC31 2019 2019-09-04 TKN -0.1863295782 #> 4757 2046 3M CC31 2019 2019-09-04 TN -0.1358197231 + #> 4758 2046 3M CC31 2019 2019-09-04 TP -1.5141277326 #> 4759 2046 3M CC31 2019 2019-09-04 TSS 1.3862943611 I #> 4760 2046 3M CC31 2019 2019-09-04 TURB 0.6418538862 #> 4761 2046 3M CC31 2020 2020-01-14 COND 10.2603574775 #> 4762 2046 3M CC31 2020 2020-01-14 DO 1.8341801851 #> 4763 2046 3M CC31 2020 2020-01-14 DOSAT 4.4140096805 #> 4764 2046 3M CC31 2020 2020-01-14 SALIN 2.8690346205 #> 4765 2046 3M CC31 2020 2020-02-18 CHLAC 0.8329091229 I #> 4766 2046 3M CC31 2020 2020-02-18 COND 10.3879178649 #> 4767 2046 3M CC31 2020 2020-02-18 DO 1.8976198599 #> 4768 2046 3M CC31 2020 2020-02-18 DOSAT 4.5075573571 #> 4769 2046 3M CC31 2020 2020-02-18 NO23 -4.8283137373 I #> 4770 2046 3M CC31 2020 2020-02-18 SALIN 3.0106208860 #> 4771 2046 3M CC31 2020 2020-02-18 TKN -0.5447271754 #> 4772 2046 3M CC31 2020 2020-02-18 TN -0.5378542962 + #> 4773 2046 3M CC31 2020 2020-02-18 TP -2.0402208285 #> 4774 2046 3M CC31 2020 2020-02-18 TSS 1.0986122887 I #> 4775 2046 3M CC31 2020 2020-02-18 TURB 0.4700036292 #> 4776 2046 3M CC31 2020 2020-06-09 CHLAC 2.9444389792 #> 4777 2046 3M CC31 2020 2020-06-09 COND 10.1025842827 #> 4778 2046 3M CC31 2020 2020-06-09 DO 1.5973653312 #> 4779 2046 3M CC31 2020 2020-06-09 DOSAT 4.2297491992 #> 4780 2046 3M CC31 2020 2020-06-09 NO23 -4.9618451299 I #> 4781 2046 3M CC31 2020 2020-06-09 SALIN 2.6919208192 #> 4782 2046 3M CC31 2020 2020-06-09 TKN 0.0000000000 #> 4783 2046 3M CC31 2020 2020-06-09 TN 0.0039920213 + #> 4784 2046 3M CC31 2020 2020-06-09 TP -1.2729656758 #> 4785 2046 3M CC31 2020 2020-06-09 TSS 1.3862943611 I #> 4786 2046 3M CC31 2020 2020-06-09 TURB 0.5306282511 #> 4787 2046 3M CC31 2020 2020-08-10 COND 10.0585663729 #> 4788 2046 3M CC31 2020 2020-08-10 DO 0.7419373447 #> 4789 2046 3M CC31 2020 2020-08-10 DOSAT 3.4177266836 #> 4790 2046 3M CC31 2020 2020-08-10 SALIN 2.6426223958 #> 4791 2046 3M CC31 2020 2020-09-22 CHLAC 2.4849066498 #> 4792 2046 3M CC31 2020 2020-09-22 COND 9.3350328159 #> 4793 2046 3M CC31 2020 2020-09-22 DO 1.5789787049 #> 4794 2046 3M CC31 2020 2020-09-22 DOSAT 4.1573193614 #> 4795 2046 3M CC31 2020 2020-09-22 NO23 -3.0791138825 #> 4796 2046 3M CC31 2020 2020-09-22 SALIN 1.8578592709 #> 4797 2046 3M CC31 2020 2020-09-22 TKN -0.0408219945 #> 4798 2046 3M CC31 2020 2020-09-22 TN 0.0059820717 + #> 4799 2046 3M CC31 2020 2020-09-22 TP -1.4271163556 #> 4800 2046 3M CC31 2020 2020-09-22 TSS 1.0986122887 I #> 4801 2046 3M CC31 2020 2020-09-22 TURB 0.9932517730 #> 4802 2046 3M CC31 2020 2020-10-20 CHLAC 1.4586150227 #> 4803 2046 3M CC31 2020 2020-10-20 COND 9.7670949276 #> 4804 2046 3M CC31 2020 2020-10-20 DO 1.4085449701 #> 4805 2046 3M CC31 2020 2020-10-20 DOSAT 4.0000338828 #> 4806 2046 3M CC31 2020 2020-10-20 NO23 -2.5510464523 #> 4807 2046 3M CC31 2020 2020-10-20 SALIN 2.3282528397 #> 4808 2046 3M CC31 2020 2020-10-20 TKN -0.0833816089 #> 4809 2046 3M CC31 2020 2020-10-20 TN -0.0020020027 + #> 4810 2046 3M CC31 2020 2020-10-20 TP -1.5141277326 #> 4811 2046 3M CC31 2020 2020-10-20 TSS 1.0986122887 I #> 4812 2046 3M CC31 2020 2020-10-20 TURB 0.5877866649 #> 4813 2046 3M CC31 2020 2020-12-14 CHLAC 1.0647107370 #> 4814 2046 3M CC31 2020 2020-12-14 COND 9.9551782679 #> 4815 2046 3M CC31 2020 2020-12-14 DO 1.8293763328 #> 4816 2046 3M CC31 2020 2020-12-14 DOSAT 4.3528552574 #> 4817 2046 3M CC31 2020 2020-12-14 NO23 -2.7181005370 #> 4818 2046 3M CC31 2020 2020-12-14 SALIN 2.5360749364 #> 4819 2046 3M CC31 2020 2020-12-14 TKN -0.2107210313 #> 4820 2046 3M CC31 2020 2020-12-14 TN -0.1323891880 + #> 4821 2046 3M CC31 2020 2020-12-14 TP -2.1202635362 #> 4822 2046 3M CC31 2020 2020-12-14 TSS 1.6094379124 I #> 4823 2046 3M CC31 2020 2020-12-14 TURB 0.5306282511 #> 4824 2046 3M CC31 2021 2021-02-03 CHLAC 0.9932517730 #> 4825 2046 3M CC31 2021 2021-02-03 COND 10.2269830978 #> 4826 2046 3M CC31 2021 2021-02-03 DO 2.0655961349 #> 4827 2046 3M CC31 2021 2021-02-03 DOSAT 4.5130548971 #> 4828 2046 3M CC31 2021 2021-02-03 NO23 -4.0745419349 #> 4829 2046 3M CC31 2021 2021-02-03 SALIN 2.8355635214 #> 4830 2046 3M CC31 2021 2021-02-03 TKN -0.4780358009 #> 4831 2046 3M CC31 2021 2021-02-03 TN -0.4509856234 + #> 4832 2046 3M CC31 2021 2021-02-03 TP -2.3025850930 #> 4833 2046 3M CC31 2021 2021-02-03 TSS 1.7917594692 I #> 4834 2046 3M CC31 2021 2021-02-03 TURB 0.5306282511 #> 4835 2046 3M CC31 2021 2021-03-09 CHLAC 2.0918640617 #> 4836 2046 3M CC31 2021 2021-03-09 COND 10.3281668796 #> 4837 2046 3M CC31 2021 2021-03-09 DO 2.2523438766 #> 4838 2046 3M CC31 2021 2021-03-09 DOSAT 4.7757564866 #> 4839 2046 3M CC31 2021 2021-03-09 NO23 -5.5214609179 U #> 4840 2046 3M CC31 2021 2021-03-09 SALIN 2.9460166813 #> 4841 2046 3M CC31 2021 2021-03-09 TKN -0.1863295782 #> 4842 2046 3M CC31 2021 2021-03-09 TN -0.1839228382 + #> 4843 2046 3M CC31 2021 2021-03-09 TP -1.5606477483 #> 4844 2046 3M CC31 2021 2021-03-09 TSS 2.8332133441 #> 4845 2046 3M CC31 2021 2021-03-09 TURB 2.0412203289 #> 4846 2046 3M CC31 2021 2021-05-05 CHLAC 0.9555114450 #> 4847 2046 3M CC31 2021 2021-05-05 COND 10.5683895677 #> 4848 2046 3M CC31 2021 2021-05-05 DO 1.3402504226 #> 4849 2046 3M CC31 2021 2021-05-05 DOSAT 4.0465538984 #> 4850 2046 3M CC31 2021 2021-05-05 NO23 -5.5214609179 U #> 4851 2046 3M CC31 2021 2021-05-05 SALIN 3.2043711387 #> 4852 2046 3M CC31 2021 2021-05-05 TKN -0.4620354596 #> 4853 2046 3M CC31 2021 2021-05-05 TN -0.4588658848 + #> 4854 2046 3M CC31 2021 2021-05-05 TP -1.5141277326 #> 4855 2046 3M CC31 2021 2021-05-05 TSS 1.7917594692 I #> 4856 2046 3M CC31 2021 2021-05-05 TURB 0.4700036292 #> 4857 2046 3M CC31 2021 2021-06-03 CHLAC 0.9932517730 I #> 4858 2046 3M CC31 2021 2021-06-03 COND 10.6275033568 #> 4859 2046 3M CC31 2021 2021-06-03 DO 0.8329091229 #> 4860 2046 3M CC31 2021 2021-06-03 DOSAT 3.5322256441 #> 4861 2046 3M CC31 2021 2021-06-03 NO23 -5.5214609179 U #> 4862 2046 3M CC31 2021 2021-06-03 SALIN 3.2718477096 #> 4863 2046 3M CC31 2021 2021-06-03 TKN -0.3285040670 #> 4864 2046 3M CC31 2021 2021-06-03 TN -0.3257301401 + #> 4865 2046 3M CC31 2021 2021-06-03 TP -1.4271163556 #> 4866 2046 3M CC31 2021 2021-06-03 TSS 1.0986122887 I #> 4867 2046 3M CC31 2021 2021-06-03 TURB 0.5306282511 #> 4868 2046 3M CC31 2021 2021-07-01 CHLAC 2.7080502011 #> 4869 2046 3M CC31 2021 2021-07-01 COND 10.4739019677 #> 4870 2046 3M CC31 2021 2021-07-01 DO 1.6770965609 #> 4871 2046 3M CC31 2021 2021-07-01 DOSAT 4.3107991254 #> 4872 2046 3M CC31 2021 2021-07-01 NO23 -5.2983173665 I #> 4873 2046 3M CC31 2021 2021-07-01 SALIN 3.1014427280 #> 4874 2046 3M CC31 2021 2021-07-01 TKN -0.4462871026 #> 4875 2046 3M CC31 2021 2021-07-01 TN -0.4400565529 + #> 4876 2046 3M CC31 2021 2021-07-01 TP -1.2729656758 #> 4877 2046 3M CC31 2021 2021-07-01 TSS 1.7917594692 I #> 4878 2046 3M CC31 2021 2021-07-01 TURB 0.4054651081 #> 4879 2046 3M CC31 2021 2021-07-29 CHLAC 2.9444389792 #> 4880 2046 3M CC31 2021 2021-07-29 COND 9.3783094225 #> 4881 2046 3M CC31 2021 2021-07-29 DO 1.3558351536 #> 4882 2046 3M CC31 2021 2021-07-29 DOSAT 3.9646154555 #> 4883 2046 3M CC31 2021 2021-07-29 NO23 -3.3242363405 #> 4884 2046 3M CC31 2021 2021-07-29 SALIN 1.9021075264 #> 4885 2046 3M CC31 2021 2021-07-29 TKN 0.0953101798 #> 4886 2046 3M CC31 2021 2021-07-29 TN 0.1275133203 + #> 4887 2046 3M CC31 2021 2021-07-29 TP -0.9942522733 #> 4888 2046 3M CC31 2021 2021-07-29 TSS 1.6094379124 I #> 4889 2046 3M CC31 2021 2021-07-29 TURB 1.6094379124 #> 4890 2046 3M CC31 2021 2021-08-25 CHLAC 2.4849066498 #> 4891 2046 3M CC31 2021 2021-08-25 COND 9.4766200382 #> 4892 2046 3M CC31 2021 2021-08-25 DO 0.8153648133 #> 4893 2046 3M CC31 2021 2021-08-25 DOSAT 3.4404180948 #> 4894 2046 3M CC31 2021 2021-08-25 NO23 -4.0745419349 #> 4895 2046 3M CC31 2021 2021-08-25 SALIN 2.0095554142 #> 4896 2046 3M CC31 2021 2021-08-25 TKN 0.0000000000 #> 4897 2046 3M CC31 2021 2021-08-25 TN 0.0168571171 + #> 4898 2046 3M CC31 2021 2021-08-25 TP -1.1086626245 #> 4899 2046 3M CC31 2021 2021-08-25 TSS 1.7917594692 I #> 4900 2046 3M CC31 2021 2021-08-25 TURB 1.1939224685 #> 4901 2046 3M CC31 2021 2021-09-23 CHLAC 3.0445224377 #> 4902 2046 3M CC31 2021 2021-09-23 COND 8.7826296549 #> 4903 2046 3M CC31 2021 2021-09-23 DO 1.4747630091 #> 4904 2046 3M CC31 2021 2021-09-23 DOSAT 4.0483006237 #> 4905 2046 3M CC31 2021 2021-09-23 NO23 -3.0576076773 #> 4906 2046 3M CC31 2021 2021-09-23 SALIN 1.2641267271 #> 4907 2046 3M CC31 2021 2021-09-23 TKN -0.0943106795 #> 4908 2046 3M CC31 2021 2021-09-23 TN -0.0439518875 + #> 4909 2046 3M CC31 2021 2021-09-23 TP -1.4271163556 #> 4910 2046 3M CC31 2021 2021-09-23 TSS 1.3862943611 I #> 4911 2046 3M CC31 2021 2021-09-23 TURB 1.1631508098 #> 4912 2046 3M CC31 2021 2021-10-21 CHLAC 2.3025850930 #> 4913 2046 3M CC31 2021 2021-10-21 COND 9.9156631285 #> 4914 2046 3M CC31 2021 2021-10-21 DO 1.5040773968 #> 4915 2046 3M CC31 2021 2021-10-21 DOSAT 4.0690267542 #> 4916 2046 3M CC31 2021 2021-10-21 NO23 -3.1465551633 #> 4917 2046 3M CC31 2021 2021-10-21 SALIN 2.4907230351 #> 4918 2046 3M CC31 2021 2021-10-21 TKN -0.1278333715 #> 4919 2046 3M CC31 2021 2021-10-21 TN -0.0801260445 + #> 4920 2046 3M CC31 2021 2021-10-21 TP -1.5141277326 #> 4921 2046 3M CC31 2021 2021-10-21 TSS 1.0986122887 U #> 4922 2046 3M CC31 2021 2021-10-21 TURB 0.4700036292 A #> 4923 2046 3M CC31 2021 2021-11-22 COND 10.1079374614 #> 4924 2046 3M CC31 2021 2021-11-22 DO 1.7316555452 #> 4925 2046 3M CC31 2021 2021-11-22 DOSAT 4.2877159552 #> 4926 2046 3M CC31 2021 2021-11-22 NO23 -2.8134107168 #> 4927 2046 3M CC31 2021 2021-11-22 SALIN 2.7020321288 #> 4928 2046 3M CC31 2021 2021-11-22 TKN -0.6733445533 #> 4929 2046 3M CC31 2021 2021-11-22 TN -0.5621189182 + #> 4930 2046 3M CC31 2021 2021-11-22 TP -2.3025850930 #> 4931 2046 3M CC31 2021 2021-11-22 TSS 1.6094379124 I #> 4932 2046 3M CC31 2021 2021-11-22 TURB 0.1823215568 A #> 4933 2046 3M CC31 2022 2022-02-22 CHLAC 1.3083328197 #> 4934 2046 3M CC31 2022 2022-02-22 COND 10.5165899421 #> 4935 2046 3M CC31 2022 2022-02-22 DO 1.8547342684 #> 4936 2046 3M CC31 2022 2022-02-22 DOSAT 4.4320065670 #> 4937 2046 3M CC31 2022 2022-02-22 NO23 -5.5214609179 U #> 4938 2046 3M CC31 2022 2022-02-22 SALIN 3.1527360224 #> 4939 2046 3M CC31 2022 2022-02-22 TKN -0.6931471806 #> 4940 2046 3M CC31 2022 2022-02-22 TN -0.6891551593 + #> 4941 2046 3M CC31 2022 2022-02-22 TP -2.4304184645 #> 4942 2046 3M CC31 2022 2022-02-22 TSS 2.0794415417 I #> 4943 2046 3M CC31 2022 2022-02-22 TURB 0.4054651081 A #> 4944 2046 3M CC31 2022 2022-04-20 CHLAC 1.5260563035 #> 4945 2046 3M CC31 2022 2022-04-20 COND 10.6492271832 #> 4946 2046 3M CC31 2022 2022-04-20 DO 1.5581446180 #> 4947 2046 3M CC31 2022 2022-04-20 DOSAT 4.1805222585 #> 4948 2046 3M CC31 2022 2022-04-20 NO23 -5.5214609179 U #> 4949 2046 3M CC31 2022 2022-04-20 SALIN 3.2987954480 #> 4950 2046 3M CC31 2022 2022-04-20 TKN -0.5447271754 #> 4951 2046 3M CC31 2022 2022-04-20 TN -0.5412848313 + #> 4952 2046 3M CC31 2022 2022-04-20 TP -1.8325814637 #> 4953 2046 3M CC31 2022 2022-04-20 TSS 2.0794415417 I #> 4954 2046 3M CC31 2022 2022-04-20 TURB 1.0296194172 #> 4955 2046 3M CC31 2022 2022-06-07 CHLAC 1.9021075264 #> 4956 2046 3M CC31 2022 2022-06-07 COND 10.4903571304 #> 4957 2046 3M CC31 2022 2022-06-07 DO 1.2412685891 #> 4958 2046 3M CC31 2022 2022-06-07 DOSAT 3.9318256327 #> 4959 2046 3M CC31 2022 2022-06-07 NO23 -5.2983173665 I #> 4960 2046 3M CC31 2022 2022-06-07 SALIN 3.1188344707 #> 4961 2046 3M CC31 2022 2022-06-07 TKN -0.4942963218 #> 4962 2046 3M CC31 2022 2022-06-07 TN -0.4877603508 + #> 4963 2046 3M CC31 2022 2022-06-07 TP -1.4696759701 #> 4964 2046 3M CC31 2022 2022-06-07 TSS 2.0794415417 I #> 4965 2046 3M CC31 2022 2022-06-07 TURB 0.1823215568 #> 4966 2046 3M CC31 2022 2022-08-15 CHLAC 2.1282317058 #> 4967 2046 3M CC31 2022 2022-08-15 COND 9.6188009891 #> 4968 2046 3M CC31 2022 2022-08-15 DO 0.9895411936 #> 4969 2046 3M CC31 2022 2022-08-15 DOSAT 3.6054978452 #> 4970 2046 3M CC31 2022 2022-08-15 NO23 -3.4737680745 #> 4971 2046 3M CC31 2022 2022-08-15 SALIN 2.1667653699 #> 4972 2046 3M CC31 2022 2022-08-15 TKN -0.0833816089 #> 4973 2046 3M CC31 2022 2022-08-15 TN -0.0502412164 + #> 4974 2046 3M CC31 2022 2022-08-15 TP -1.4696759701 #> 4975 2046 3M CC31 2022 2022-08-15 TSS 1.0986122887 I #> 4976 2046 3M CC31 2022 2022-08-15 TURB 0.6931471806 #> 4977 2046 3M CC31 2022 2022-12-15 CHLAC 0.9555114450 #> 4978 2046 3M CC31 2022 2022-12-15 COND 10.2729108893 #> 4979 2046 3M CC31 2022 2022-12-15 DO 1.7630170004 #> 4980 2046 3M CC31 2022 2022-12-15 DOSAT 4.3267781604 #> 4981 2046 3M CC31 2022 2022-12-15 NO23 -2.9759296463 #> 4982 2046 3M CC31 2022 2022-12-15 SALIN 2.8836827697 #> 4983 2046 3M CC31 2022 2022-12-15 TKN -0.4942963218 #> 4984 2046 3M CC31 2022 2022-12-15 TN -0.4140014391 + #> 4985 2046 3M CC31 2022 2022-12-15 TP -1.6094379124 #> 4986 2046 3M CC31 2022 2022-12-15 TSS 2.0794415417 I #> 4987 2046 3M CC31 2022 2022-12-15 TURB 0.0000000000 #> 4988 2046 3M CC31 2023 2023-01-11 CHLAC 2.0668627595 #> 4989 2046 3M CC31 2023 2023-01-11 COND 10.2352702390 #> 4990 2046 3M CC31 2023 2023-01-11 DO 1.7984040119 #> 4991 2046 3M CC31 2023 2023-01-11 DOSAT 4.2849649218 #> 4992 2046 3M CC31 2023 2023-01-11 NO23 -3.9633162998 #> 4993 2046 3M CC31 2023 2023-01-11 SALIN 2.8443278194 #> 4994 2046 3M CC31 2023 2023-01-11 TKN -0.5798184953 #> 4995 2046 3M CC31 2023 2023-01-11 TN -0.5464528014 + #> 4996 2046 3M CC31 2023 2023-01-11 TP -1.8325814637 #> 4997 2046 3M CC31 2023 2023-01-11 TSS 1.7917594692 I #> 4998 2046 3M CC31 2023 2023-01-11 TURB 0.7419373447 #> 4999 2046 3M CC31 2023 2023-03-23 CHLAC 1.7578579176 #> 5000 2046 3M CC31 2023 2023-03-23 COND 10.4503364755 #> 5001 2046 3M CC31 2023 2023-03-23 DO 1.8840347453 #> 5002 2046 3M CC31 2023 2023-03-23 DOSAT 4.4461744545 #> 5003 2046 3M CC31 2023 2023-03-23 NO23 -5.5214609179 U #> 5004 2046 3M CC31 2023 2023-03-23 SALIN 3.0796137575 #> 5005 2046 3M CC31 2023 2023-03-23 TKN -0.1984509387 #> 5006 2046 3M CC31 2023 2023-03-23 TN -0.1960148839 + #> 5007 2046 3M CC31 2023 2023-03-23 TP -1.1711829815 #> 5008 2046 3M CC31 2023 2023-03-23 TSS 2.7725887222 #> 5009 2046 3M CC31 2023 2023-03-23 TURB 1.7047480922 #> 5010 2046 3M CC31 2023 2023-05-08 CHLAC 1.2809338455 #> 5011 2046 3M CC31 2023 2023-05-08 COND 10.5443145959 #> 5012 2046 3M CC31 2023 2023-05-08 DO 1.6014057407 #> 5013 2046 3M CC31 2023 2023-05-08 DOSAT 4.2370008626 #> 5014 2046 3M CC31 2023 2023-05-08 NO23 -4.7105307016 I #> 5015 2046 3M CC31 2023 2023-05-08 SALIN 3.1813816204 #> 5016 2046 3M CC31 2023 2023-05-08 TKN -0.3710636814 #> 5017 2046 3M CC31 2023 2023-05-08 TN -0.3652833185 + #> 5018 2046 3M CC31 2023 2023-05-08 TP -1.6094379124 #> 5019 2046 3M CC31 2023 2023-05-08 TSS 1.7917594692 I #> 5020 2046 3M CC31 2023 2023-05-08 TURB 0.0953101798 #> 5021 2056E 3M CC34 2015 2015-04-06 CHLAC 1.5040773968 #> 5022 2056E 3M CC34 2015 2015-04-06 COLOR 3.8066624898 #> 5023 2056E 3M CC34 2015 2015-04-06 COND 10.4003156667 #> 5024 2056E 3M CC34 2015 2015-04-06 DO 2.1317967720 #> 5025 2056E 3M CC34 2015 2015-04-06 DOSAT 4.7899886230 + #> 5026 2056E 3M CC34 2015 2015-04-06 NO23 -5.5214609179 U #> 5027 2056E 3M CC34 2015 2015-04-06 SALIN 3.0194488002 #> 5028 2056E 3M CC34 2015 2015-04-06 TKN -0.3509769228 #> 5029 2056E 3M CC34 2015 2015-04-06 TN -0.3509769228 #> 5030 2056E 3M CC34 2015 2015-04-06 TP -1.6928195214 #> 5031 2056E 3M CC34 2015 2015-04-06 TSS 1.6253112616 #> 5032 2056E 3M CC34 2015 2015-04-06 TURB 1.0647107370 #> 5033 2056E 3M CC34 2015 2015-04-06 COND 10.4033533361 #> 5034 2056E 3M CC34 2015 2015-04-06 DO 2.1341664414 #> 5035 2056E 3M CC34 2015 2015-04-06 DOSAT 4.7899886230 + #> 5036 2056E 3M CC34 2015 2015-04-06 SALIN 3.0233474406 #> 5037 2056E 3M CC34 2015 2015-04-06 COND 10.4069864009 #> 5038 2056E 3M CC34 2015 2015-04-06 DO 2.1435893615 #> 5039 2056E 3M CC34 2015 2015-04-06 DOSAT 4.7949637576 + #> 5040 2056E 3M CC34 2015 2015-04-06 SALIN 3.0272309406 #> 5041 2056E 3M CC36 2015 2015-04-06 CHLAC 1.5040773968 #> 5042 2056E 3M CC36 2015 2015-04-06 COLOR 3.8066624898 #> 5043 2056E 3M CC36 2015 2015-04-06 COND 10.4003156667 #> 5044 2056E 3M CC36 2015 2015-04-06 DO 2.1317967720 #> 5045 2056E 3M CC36 2015 2015-04-06 DOSAT 4.7899886230 + #> 5046 2056E 3M CC36 2015 2015-04-06 NO23 -5.5214609179 U #> 5047 2056E 3M CC36 2015 2015-04-06 SALIN 3.0194488002 #> 5048 2056E 3M CC36 2015 2015-04-06 TKN -0.3509769228 #> 5049 2056E 3M CC36 2015 2015-04-06 TN -0.3509769228 #> 5050 2056E 3M CC36 2015 2015-04-06 TP -1.6928195214 #> 5051 2056E 3M CC36 2015 2015-04-06 TSS 1.6253112616 #> 5052 2056E 3M CC36 2015 2015-04-06 TURB 1.0647107370 #> 5053 2056E 3M CC36 2015 2015-04-06 COND 10.4033533361 #> 5054 2056E 3M CC36 2015 2015-04-06 DO 2.1341664414 #> 5055 2056E 3M CC36 2015 2015-04-06 DOSAT 4.7899886230 + #> 5056 2056E 3M CC36 2015 2015-04-06 SALIN 3.0233474406 #> 5057 2056E 3M CC36 2015 2015-04-06 COND 10.4069864009 #> 5058 2056E 3M CC36 2015 2015-04-06 DO 2.1435893615 #> 5059 2056E 3M CC36 2015 2015-04-06 DOSAT 4.7949637576 + #> 5060 2056E 3M CC36 2015 2015-04-06 SALIN 3.0272309406 #> 5061 2056E 3M CC37 2014 2014-01-06 CHLAC 1.5686159179 #> 5062 2056E 3M CC37 2014 2014-01-06 COLOR 2.9957322736 A #> 5063 2056E 3M CC37 2014 2014-01-06 DOSAT 4.3832758541 + #> 5064 2056E 3M CC37 2014 2014-01-06 NO23 -4.3428059215 #> 5065 2056E 3M CC37 2014 2014-01-06 SALIN 3.3032169733 #> 5066 2056E 3M CC37 2014 2014-01-06 TKN -0.5978370008 #> 5067 2056E 3M CC37 2014 2014-01-06 TN -0.5744756508 + #> 5068 2056E 3M CC37 2014 2014-01-06 TP -2.3025850930 #> 5069 2056E 3M CC37 2014 2014-01-06 TURB 0.2623642645 #> 5070 2056E 3M CC37 2014 2014-02-03 CHLAC 1.4816045409 #> 5071 2056E 3M CC37 2014 2014-02-03 COLOR 2.7725887222 #> 5072 2056E 3M CC37 2014 2014-02-03 DO 1.8562979904 #> 5073 2056E 3M CC37 2014 2014-02-03 DOSAT 4.3502779364 + #> 5074 2056E 3M CC37 2014 2014-02-03 NO23 -3.2968373663 #> 5075 2056E 3M CC37 2014 2014-02-03 SALIN 2.6461747974 #> 5076 2056E 3M CC37 2014 2014-02-03 TKN -0.1743533871 #> 5077 2056E 3M CC37 2014 2014-02-03 TN -0.1312482866 + #> 5078 2056E 3M CC37 2014 2014-02-03 TP -2.3025850930 #> 5079 2056E 3M CC37 2014 2014-02-03 TURB 0.7419373447 #> 5080 2056E 3M CC37 2014 2014-03-03 CHLAC 1.7578579176 #> 5081 2056E 3M CC37 2014 2014-03-03 COLOR 2.8903717579 A #> 5082 2056E 3M CC37 2014 2014-03-03 DO 1.8082887712 #> 5083 2056E 3M CC37 2014 2014-03-03 DOSAT 4.3579900568 + #> 5084 2056E 3M CC37 2014 2014-03-03 NO23 -4.5098600062 #> 5085 2056E 3M CC37 2014 2014-03-03 SALIN 3.1000922889 #> 5086 2056E 3M CC37 2014 2014-03-03 TKN -0.2744368457 #> 5087 2056E 3M CC37 2014 2014-03-03 TN -0.2600669054 + #> 5088 2056E 3M CC37 2014 2014-03-03 TP -1.8971199849 #> 5089 2056E 3M CC37 2014 2014-03-03 TURB 1.0296194172 #> 5090 2056E 3M CC37 2014 2014-04-07 CHLAC 2.2721258855 #> 5091 2056E 3M CC37 2014 2014-04-07 COLOR 2.9444389792 #> 5092 2056E 3M CC37 2014 2014-04-07 DO 1.8718021769 #> 5093 2056E 3M CC37 2014 2014-04-07 DOSAT 4.4953553200 + #> 5094 2056E 3M CC37 2014 2014-04-07 NO23 -4.9618451299 I #> 5095 2056E 3M CC37 2014 2014-04-07 SALIN 3.1000922889 #> 5096 2056E 3M CC37 2014 2014-04-07 TKN -0.4942963218 #> 5097 2056E 3M CC37 2014 2014-04-07 TN -0.4877603508 + #> 5098 2056E 3M CC37 2014 2014-04-07 TP -1.7147984281 #> 5099 2056E 3M CC37 2014 2014-04-07 TURB 1.2237754316 #> 5100 2056E 3M CC37 2014 2014-05-05 CHLAC 3.0445224377 #> 5101 2056E 3M CC37 2014 2014-05-05 COLOR 3.0910424534 #> 5102 2056E 3M CC37 2014 2014-05-05 DO 1.7917594692 #> 5103 2056E 3M CC37 2014 2014-05-05 DOSAT 4.4152196020 + #> 5104 2056E 3M CC37 2014 2014-05-05 NO23 -5.1159958098 I #> 5105 2056E 3M CC37 2014 2014-05-05 SALIN 3.2068032436 #> 5106 2056E 3M CC37 2014 2014-05-05 TKN -0.0100503359 #> 5107 2056E 3M CC37 2014 2014-05-05 TN -0.0060180723 + #> 5108 2056E 3M CC37 2014 2014-05-05 TP -1.2729656758 #> 5109 2056E 3M CC37 2014 2014-05-05 TURB 1.9315214116 #> 5110 2056E 3M CC37 2014 2014-06-02 CHLAC 2.2617630985 #> 5111 2056E 3M CC37 2014 2014-06-02 COLOR 3.2188758249 #> 5112 2056E 3M CC37 2014 2014-06-02 DO 1.6292405397 #> 5113 2056E 3M CC37 2014 2014-06-02 DOSAT 4.3040650932 + #> 5114 2056E 3M CC37 2014 2014-06-02 NO23 -5.1159958098 I #> 5115 2056E 3M CC37 2014 2014-06-02 SALIN 3.2425923515 #> 5116 2056E 3M CC37 2014 2014-06-02 TKN -0.1625189295 #> 5117 2056E 3M CC37 2014 2014-06-02 TN -0.1578240852 + #> 5118 2056E 3M CC37 2014 2014-06-02 TP -1.0216512475 #> 5119 2056E 3M CC37 2014 2014-06-02 TURB 1.4816045409 #> 5120 2056E 3M CC37 2014 2014-07-07 CHLAC 2.5649493575 #> 5121 2056E 3M CC37 2014 2014-07-07 COLOR 3.3672958300 A #> 5122 2056E 3M CC37 2014 2014-07-07 NO23 -5.5214609179 I #> 5123 2056E 3M CC37 2014 2014-07-07 SALIN 3.1398326175 #> 5124 2056E 3M CC37 2014 2014-07-07 TKN -0.0304592075 #> 5125 2056E 3M CC37 2014 2014-07-07 TN -0.0263439753 + #> 5126 2056E 3M CC37 2014 2014-07-07 TP -0.9675840263 #> 5127 2056E 3M CC37 2014 2014-07-07 TURB 1.5260563035 #> 5128 2056E 3M CC37 2014 2014-08-04 CHLAC 2.7080502011 #> 5129 2056E 3M CC37 2014 2014-08-04 COLOR 4.0073331852 A #> 5130 2056E 3M CC37 2014 2014-08-04 DO 1.7047480922 #> 5131 2056E 3M CC37 2014 2014-08-04 DOSAT 4.3214801348 + #> 5132 2056E 3M CC37 2014 2014-08-04 NO23 -4.5098600062 #> 5133 2056E 3M CC37 2014 2014-08-04 SALIN 2.4336133554 #> 5134 2056E 3M CC37 2014 2014-08-04 TKN 0.0953101798 #> 5135 2056E 3M CC37 2014 2014-08-04 TN 0.1052605107 + #> 5136 2056E 3M CC37 2014 2014-08-04 TP -0.7550225843 #> 5137 2056E 3M CC37 2014 2014-08-04 TURB 1.0296194172 #> 5138 2056E 3M CC37 2014 2014-09-08 CHLAC 0.5877866649 #> 5139 2056E 3M CC37 2014 2014-09-08 COLOR 3.6375861597 A #> 5140 2056E 3M CC37 2014 2014-09-08 DOSAT 3.7588718259 + #> 5141 2056E 3M CC37 2014 2014-09-08 NO23 -4.1997050779 #> 5142 2056E 3M CC37 2014 2014-09-08 SALIN 2.6318888401 #> 5143 2056E 3M CC37 2014 2014-09-08 TKN -0.1743533871 #> 5144 2056E 3M CC37 2014 2014-09-08 TN -0.1566538100 + #> 5145 2056E 3M CC37 2014 2014-09-08 TP -1.0498221245 #> 5146 2056E 3M CC37 2014 2014-09-08 TURB 0.6931471806 A #> 5147 2056E 3M CC37 2014 2014-10-06 CHLAC 1.7917594692 #> 5148 2056E 3M CC37 2014 2014-10-06 COLOR 4.1588830834 A #> 5149 2056E 3M CC37 2014 2014-10-06 DO 1.3350010667 #> 5150 2056E 3M CC37 2014 2014-10-06 DOSAT 3.8458832029 + #> 5151 2056E 3M CC37 2014 2014-10-06 NO23 -2.9957322736 #> 5152 2056E 3M CC37 2014 2014-10-06 SALIN 1.9600947840 #> 5153 2056E 3M CC37 2014 2014-10-06 TKN -0.1508228897 #> 5154 2056E 3M CC37 2014 2014-10-06 TN -0.0943106795 + #> 5155 2056E 3M CC37 2014 2014-10-06 TP -1.1086626245 #> 5156 2056E 3M CC37 2014 2014-10-06 TURB 0.8754687374 #> 5157 2056E 3M CC37 2014 2014-11-03 CHLAC 2.1517622033 #> 5158 2056E 3M CC37 2014 2014-11-03 COLOR 3.9318256327 A #> 5159 2056E 3M CC37 2014 2014-11-03 DO 1.8245492921 #> 5160 2056E 3M CC37 2014 2014-11-03 DOSAT 4.2499227940 + #> 5161 2056E 3M CC37 2014 2014-11-03 NO23 -4.2686979494 #> 5162 2056E 3M CC37 2014 2014-11-03 SALIN 2.7600099400 #> 5163 2056E 3M CC37 2014 2014-11-03 TKN -0.1508228897 #> 5164 2056E 3M CC37 2014 2014-11-03 TN -0.1346749033 + #> 5165 2056E 3M CC37 2014 2014-11-03 TP -1.5606477483 #> 5166 2056E 3M CC37 2014 2014-11-03 TURB 0.7884573604 #> 5167 2056E 3M CC37 2014 2014-12-01 CHLAC 2.1633230257 #> 5168 2056E 3M CC37 2014 2014-12-01 COLOR 3.4657359028 #> 5169 2056E 3M CC37 2014 2014-12-01 DO 1.9600947840 #> 5170 2056E 3M CC37 2014 2014-12-01 DOSAT 4.4343818650 + #> 5171 2056E 3M CC37 2014 2014-12-01 NO23 -3.4737680745 #> 5172 2056E 3M CC37 2014 2014-12-01 SALIN 2.8622008809 #> 5173 2056E 3M CC37 2014 2014-12-01 TKN -0.3147107448 #> 5174 2056E 3M CC37 2014 2014-12-01 TN -0.2731219211 + #> 5175 2056E 3M CC37 2014 2014-12-01 TP -1.9661128564 #> 5176 2056E 3M CC37 2014 2014-12-01 TURB 0.7884573604 #> 5177 2056E 3M CC37 2015 2015-01-05 CHLAC 1.8870696490 #> 5178 2056E 3M CC37 2015 2015-01-05 COLOR 3.2958368660 A #> 5179 2056E 3M CC37 2015 2015-01-05 DO 1.7917594692 #> 5180 2056E 3M CC37 2015 2015-01-05 DOSAT 4.3732381286 + #> 5181 2056E 3M CC37 2015 2015-01-05 NO23 -3.9633162998 #> 5182 2056E 3M CC37 2015 2015-01-05 SALIN 2.9549102790 #> 5183 2056E 3M CC37 2015 2015-01-05 TKN -0.4780358009 #> 5184 2056E 3M CC37 2015 2015-01-05 TN -0.4478508246 + #> 5185 2056E 3M CC37 2015 2015-01-05 TP -2.1202635362 #> 5186 2056E 3M CC37 2015 2015-01-05 TURB 0.8754687374 #> 5187 2056E 3M CC37 2015 2015-02-02 CHLAC 1.6094379124 #> 5188 2056E 3M CC37 2015 2015-02-02 COLOR 2.8332133441 A #> 5189 2056E 3M CC37 2015 2015-02-02 DO 1.8245492921 #> 5190 2056E 3M CC37 2015 2015-02-02 DOSAT 4.3333614627 + #> 5191 2056E 3M CC37 2015 2015-02-02 NO23 -4.6051701860 #> 5192 2056E 3M CC37 2015 2015-02-02 SALIN 3.0773122605 #> 5193 2056E 3M CC37 2015 2015-02-02 TKN -0.6733445533 #> 5194 2056E 3M CC37 2015 2015-02-02 TN -0.6539264674 + #> 5195 2056E 3M CC37 2015 2015-02-02 TP -2.1202635362 #> 5196 2056E 3M CC37 2015 2015-02-02 TURB 0.9162907319 #> 5197 2056E 3M CC37 2015 2015-03-02 CHLAC 2.0014800002 #> 5198 2056E 3M CC37 2015 2015-03-02 COLOR 3.2958368660 #> 5199 2056E 3M CC37 2015 2015-03-02 DO 1.6486586256 #> 5200 2056E 3M CC37 2015 2015-03-02 DOSAT 4.2002049529 + #> 5201 2056E 3M CC37 2015 2015-03-02 NO23 -2.9759296463 #> 5202 2056E 3M CC37 2015 2015-03-02 SALIN 2.9285235239 #> 5203 2056E 3M CC37 2015 2015-03-02 TKN -0.3566749439 #> 5204 2056E 3M CC37 2015 2015-03-02 TN -0.2863496272 + #> 5205 2056E 3M CC37 2015 2015-03-02 TP -2.0402208285 #> 5206 2056E 3M CC37 2015 2015-03-02 TURB 0.7419373447 #> 5207 2056E 3M CC37 2015 2015-04-06 CHLAC 1.8245492921 #> 5208 2056E 3M CC37 2015 2015-04-06 COLOR 3.2188758249 A #> 5209 2056E 3M CC37 2015 2015-04-06 DO 1.6292405397 #> 5210 2056E 3M CC37 2015 2015-04-06 DOSAT 4.2297491992 + #> 5211 2056E 3M CC37 2015 2015-04-06 NO23 -4.5098600062 #> 5212 2056E 3M CC37 2015 2015-04-06 SALIN 3.0252910758 #> 5213 2056E 3M CC37 2015 2015-04-06 TKN -0.1165338163 #> 5214 2056E 3M CC37 2015 2015-04-06 TN -0.1042500214 + #> 5215 2056E 3M CC37 2015 2015-04-06 TP -1.6094379124 #> 5216 2056E 3M CC37 2015 2015-04-06 TURB 1.3083328197 #> 5217 2056E 3M CC37 2015 2015-05-04 CHLAC 1.7917594692 #> 5218 2056E 3M CC37 2015 2015-05-04 COLOR 3.2958368660 A #> 5219 2056E 3M CC37 2015 2015-05-04 DO 1.4816045409 #> 5220 2056E 3M CC37 2015 2015-05-04 DOSAT 4.0724397268 + #> 5221 2056E 3M CC37 2015 2015-05-04 NO23 -5.2983173665 I #> 5222 2056E 3M CC37 2015 2015-05-04 SALIN 3.0773122605 #> 5223 2056E 3M CC37 2015 2015-05-04 TKN -0.3856624808 #> 5224 2056E 3M CC37 2015 2015-05-04 TN -0.3797973614 + #> 5225 2056E 3M CC37 2015 2015-05-04 TP -2.0402208285 #> 5226 2056E 3M CC37 2015 2015-05-04 TURB 1.3350010667 #> 5227 2056E 3M CC37 2015 2015-06-01 CHLAC 2.7080502011 #> 5228 2056E 3M CC37 2015 2015-06-01 COLOR 3.2188758249 A #> 5229 2056E 3M CC37 2015 2015-06-01 DOSAT 4.0587173846 + #> 5230 2056E 3M CC37 2015 2015-06-01 NO23 -5.1159958098 I #> 5231 2056E 3M CC37 2015 2015-06-01 SALIN 2.8332133441 #> 5232 2056E 3M CC37 2015 2015-06-01 TKN 0.0000000000 #> 5233 2056E 3M CC37 2015 2015-06-01 TN 0.0039920213 + #> 5234 2056E 3M CC37 2015 2015-06-01 TP -1.1711829815 #> 5235 2056E 3M CC37 2015 2015-06-01 TURB 1.5475625087 A #> 5236 2056E 3M CC37 2015 2015-08-03 CHLAC 3.2580965380 #> 5237 2056E 3M CC37 2015 2015-08-03 COLOR 3.8286413965 #> 5238 2056E 3M CC37 2015 2015-08-03 DO 1.9169226122 #> 5239 2056E 3M CC37 2015 2015-08-03 DOSAT 4.4784725329 + #> 5240 2056E 3M CC37 2015 2015-08-03 NO23 -4.0173835211 #> 5241 2056E 3M CC37 2015 2015-08-03 SALIN 1.9021075264 #> 5242 2056E 3M CC37 2015 2015-08-03 TKN 0.0000000000 #> 5243 2056E 3M CC37 2015 2015-08-03 TN 0.0178399181 + #> 5244 2056E 3M CC37 2015 2015-08-03 TP -0.8439700703 #> 5245 2056E 3M CC37 2015 2015-08-03 TURB 1.0986122887 A #> 5246 2056E 3M CC37 2015 2015-09-08 CHLAC 2.7080502011 #> 5247 2056E 3M CC37 2015 2015-09-08 COLOR 4.7004803658 A #> 5248 2056E 3M CC37 2015 2015-09-08 DO 1.7227665977 #> 5249 2056E 3M CC37 2015 2015-09-08 DOSAT 4.3067641502 + #> 5250 2056E 3M CC37 2015 2015-09-08 NO23 -3.3242363405 #> 5251 2056E 3M CC37 2015 2015-09-08 SALIN 1.7749523509 #> 5252 2056E 3M CC37 2015 2015-09-08 TKN 0.1823215568 #> 5253 2056E 3M CC37 2015 2015-09-08 TN 0.2118803590 + #> 5254 2056E 3M CC37 2015 2015-09-08 TP -0.2613647641 #> 5255 2056E 3M CC37 2015 2015-09-08 TURB 1.3083328197 #> 5256 2056E 3M CC37 2015 2015-10-05 CHLAC 2.3978952728 #> 5257 2056E 3M CC37 2015 2015-10-05 COLOR 4.5643481915 A #> 5258 2056E 3M CC37 2015 2015-10-05 DO 1.8562979904 #> 5259 2056E 3M CC37 2015 2015-10-05 DOSAT 4.3732381286 + #> 5260 2056E 3M CC37 2015 2015-10-05 NO23 -3.7722610631 #> 5261 2056E 3M CC37 2015 2015-10-05 SALIN 2.2721258855 #> 5262 2056E 3M CC37 2015 2015-10-05 TKN -0.2876820725 #> 5263 2056E 3M CC37 2015 2015-10-05 TN -0.2574762304 + #> 5264 2056E 3M CC37 2015 2015-10-05 TP -0.9416085399 #> 5265 2056E 3M CC37 2015 2015-10-05 TURB 0.4054651081 #> 5266 2056E 3M CC37 2016 2016-02-01 CHLAC 2.6390573296 #> 5267 2056E 3M CC37 2016 2016-02-01 COLOR 4.5217885770 A #> 5268 2056E 3M CC37 2016 2016-02-01 NO23 -1.9661128564 #> 5269 2056E 3M CC37 2016 2016-02-01 TKN -0.3285040670 #> 5270 2056E 3M CC37 2016 2016-02-01 TN -0.1508228897 + #> 5271 2056E 3M CC37 2016 2016-02-01 TP -1.0216512475 #> 5272 2056E 3M CC37 2016 2016-02-01 TURB 0.9162907319 #> 5273 2056E 3M CC37 2016 2016-03-07 CHLAC 2.4849066498 #> 5274 2056E 3M CC37 2016 2016-03-07 COLOR 3.8918202981 A #> 5275 2056E 3M CC37 2016 2016-03-07 DO 1.6331544391 #> 5276 2056E 3M CC37 2016 2016-03-07 DOSAT 4.0859763126 + #> 5277 2056E 3M CC37 2016 2016-03-07 NO23 -4.1997050779 #> 5278 2056E 3M CC37 2016 2016-03-07 SALIN 2.7040421797 #> 5279 2056E 3M CC37 2016 2016-03-07 TKN -0.3011050928 #> 5280 2056E 3M CC37 2016 2016-03-07 TN -0.2810375297 + #> 5281 2056E 3M CC37 2016 2016-03-07 TP -1.5141277326 #> 5282 2056E 3M CC37 2016 2016-03-07 TURB 1.2527629685 #> 5283 2056E 3M CC37 2016 2016-04-04 CHLAC 2.3978952728 #> 5284 2056E 3M CC37 2016 2016-04-04 COLOR 3.6635616461 #> 5285 2056E 3M CC37 2016 2016-04-04 DO 1.3711807233 #> 5286 2056E 3M CC37 2016 2016-04-04 DOSAT 3.9512437186 + #> 5287 2056E 3M CC37 2016 2016-04-04 NO23 -3.5065578973 #> 5288 2056E 3M CC37 2016 2016-04-04 SALIN 2.6905648868 #> 5289 2056E 3M CC37 2016 2016-04-04 TKN -0.0202027073 #> 5290 2056E 3M CC37 2016 2016-04-04 TN 0.0099503309 + #> 5291 2056E 3M CC37 2016 2016-04-04 TP -1.3470736480 #> 5292 2056E 3M CC37 2016 2016-04-04 TURB 1.5260563035 #> 5293 2056E 3M CC37 2017 2017-02-06 CHLAC 2.8903717579 #> 5294 2056E 3M CC37 2017 2017-02-06 COLOR 2.9444389792 A #> 5295 2056E 3M CC37 2017 2017-02-06 DO 1.6311994042 #> 5296 2056E 3M CC37 2017 2017-02-06 DOSAT 4.2239097666 + #> 5297 2056E 3M CC37 2017 2017-02-06 NO23 -5.5214609179 U #> 5298 2056E 3M CC37 2017 2017-02-06 SALIN 3.3138223022 #> 5299 2056E 3M CC37 2017 2017-02-06 TKN -0.0943106795 #> 5300 2056E 3M CC37 2017 2017-02-06 TN -0.0921152889 + #> 5301 2056E 3M CC37 2017 2017-02-06 TP -1.7147984281 #> 5302 2056E 3M CC37 2017 2017-02-06 TURB 1.8562979904 #> 5303 2056E 3M CC37 2017 2017-03-06 CHLAC 2.1517622033 #> 5304 2056E 3M CC37 2017 2017-03-06 COLOR 2.7080502011 #> 5305 2056E 3M CC37 2017 2017-03-06 DO 1.7191887764 #> 5306 2056E 3M CC37 2017 2017-03-06 DOSAT 4.2931954210 + #> 5307 2056E 3M CC37 2017 2017-03-06 NO23 -5.5214609179 U #> 5308 2056E 3M CC37 2017 2017-03-06 SALIN 3.3279095859 #> 5309 2056E 3M CC37 2017 2017-03-06 TKN -0.1743533871 #> 5310 2056E 3M CC37 2017 2017-03-06 TN -0.1719752647 + #> 5311 2056E 3M CC37 2017 2017-03-06 TP -1.9661128564 #> 5312 2056E 3M CC37 2017 2017-03-06 TURB 1.3862943611 #> 5313 2056E 3M CC37 2017 2017-04-03 CHLAC 2.3978952728 #> 5314 2056E 3M CC37 2017 2017-04-03 COLOR 2.7080502011 A #> 5315 2056E 3M CC37 2017 2017-04-03 DO 1.5727739281 #> 5316 2056E 3M CC37 2017 2017-04-03 DOSAT 4.2640873368 + #> 5317 2056E 3M CC37 2017 2017-04-03 NO23 -5.5214609179 U #> 5318 2056E 3M CC37 2017 2017-04-03 SALIN 3.3914836895 #> 5319 2056E 3M CC37 2017 2017-04-03 TKN -0.1508228897 #> 5320 2056E 3M CC37 2017 2017-04-03 TN -0.1485000083 + #> 5321 2056E 3M CC37 2017 2017-04-03 TP -1.6607312068 #> 5322 2056E 3M CC37 2017 2017-04-03 TURB 1.3862943611 A #> 5323 2056E 3M CC37 2017 2017-07-10 CHLAC 2.7080502011 #> 5324 2056E 3M CC37 2017 2017-07-10 COLOR 4.7874917428 A #> 5325 2056E 3M CC37 2017 2017-07-10 DO 0.8415671857 #> 5326 2056E 3M CC37 2017 2017-07-10 DOSAT 3.4965075615 + #> 5327 2056E 3M CC37 2017 2017-07-10 NO23 -5.1159958098 I #> 5328 2056E 3M CC37 2017 2017-07-10 TKN 0.1823215568 #> 5329 2056E 3M CC37 2017 2017-07-10 TN 0.1856493469 + #> 5330 2056E 3M CC37 2017 2017-07-10 TP -0.4780358009 #> 5331 2056E 3M CC37 2017 2017-07-10 TURB 1.1939224685 #> 5332 2056E 3M CC37 2017 2017-08-07 CHLAC 1.6863989536 #> 5333 2056E 3M CC37 2017 2017-08-07 COLOR 4.7004803658 #> 5334 2056E 3M CC37 2017 2017-08-07 DO 0.7793248768 #> 5335 2056E 3M CC37 2017 2017-08-07 DOSAT 3.4144426084 + #> 5336 2056E 3M CC37 2017 2017-08-07 NO23 -2.2072749132 #> 5337 2056E 3M CC37 2017 2017-08-07 SALIN 1.7647307968 #> 5338 2056E 3M CC37 2017 2017-08-07 TKN 0.1823215568 #> 5339 2056E 3M CC37 2017 2017-08-07 TN 0.2700271372 + #> 5340 2056E 3M CC37 2017 2017-08-07 TP -0.8209805521 #> 5341 2056E 3M CC37 2017 2017-08-07 TURB 0.7884573604 #> 5342 2056E 3M CC37 2017 2017-09-05 CHLAC 2.8332133441 #> 5343 2056E 3M CC37 2017 2017-09-05 COLOR 4.4998096703 #> 5344 2056E 3M CC37 2017 2017-09-05 DO 1.4516138272 #> 5345 2056E 3M CC37 2017 2017-09-05 DOSAT 4.0377742107 + #> 5346 2056E 3M CC37 2017 2017-09-05 NO23 -2.4889146712 #> 5347 2056E 3M CC37 2017 2017-09-05 SALIN 0.1906203596 #> 5348 2056E 3M CC37 2017 2017-09-05 TKN -0.0725706928 #> 5349 2056E 3M CC37 2017 2017-09-05 TN 0.0129162253 + #> 5350 2056E 3M CC37 2017 2017-09-05 TP -0.9675840263 #> 5351 2056E 3M CC37 2017 2017-09-05 TURB 1.0986122887 #> 5352 2056E 3M CC37 2017 2017-10-02 CHLAC 1.9169226122 #> 5353 2056E 3M CC37 2017 2017-10-02 COLOR 4.4886363697 A #> 5354 2056E 3M CC37 2017 2017-10-02 NO23 -2.9565115604 #> 5355 2056E 3M CC37 2017 2017-10-02 TKN -0.8675005677 #> 5356 2056E 3M CC37 2017 2017-10-02 TN -0.7507762934 + #> 5357 2056E 3M CC37 2017 2017-10-02 TP -0.6348782724 #> 5358 2056E 3M CC37 2017 2017-10-02 TURB 0.7419373447 #> 5359 2056E 3M CC37 2017 2017-11-06 CHLAC 1.6292405397 #> 5360 2056E 3M CC37 2017 2017-11-06 COLOR 3.8918202981 A #> 5361 2056E 3M CC37 2017 2017-11-06 DO 1.7595805709 #> 5362 2056E 3M CC37 2017 2017-11-06 DOSAT 4.3605476030 #> 5363 2056E 3M CC37 2017 2017-11-06 NO23 -3.7722610631 #> 5364 2056E 3M CC37 2017 2017-11-06 SALIN 2.9549102790 #> 5365 2056E 3M CC37 2017 2017-11-06 TKN -0.4620354596 #> 5366 2056E 3M CC37 2017 2017-11-06 TN -0.4261781497 + #> 5367 2056E 3M CC37 2017 2017-11-06 TP -1.4696759701 #> 5368 2056E 3M CC37 2017 2017-11-06 TURB 0.2623642645 #> 5369 2056E 3M CC37 2017 2017-12-04 CHLAC 1.6677068206 #> 5370 2056E 3M CC37 2017 2017-12-04 COLOR 3.4657359028 #> 5371 2056E 3M CC37 2017 2017-12-04 DO 1.5686159179 #> 5372 2056E 3M CC37 2017 2017-12-04 DOSAT 4.1541845626 #> 5373 2056E 3M CC37 2017 2017-12-04 NO23 -5.5214609179 U #> 5374 2056E 3M CC37 2017 2017-12-04 SALIN 3.0914968955 #> 5375 2056E 3M CC37 2017 2017-12-04 TKN -0.1743533871 #> 5376 2056E 3M CC37 2017 2017-12-04 TN -0.1719752647 + #> 5377 2056E 3M CC37 2017 2017-12-04 TP -1.2039728043 #> 5378 2056E 3M CC37 2017 2017-12-04 TURB 1.0647107370 #> 5379 2056E 3M CC37 2018 2018-01-02 CHLAC 2.8332133441 #> 5380 2056E 3M CC37 2018 2018-01-02 COLOR 3.2188758249 #> 5381 2056E 3M CC37 2018 2018-01-02 DO 1.7101878155 #> 5382 2056E 3M CC37 2018 2018-01-02 DOSAT 4.1789920363 + #> 5383 2056E 3M CC37 2018 2018-01-02 NO23 -5.2983173665 I #> 5384 2056E 3M CC37 2018 2018-01-02 SALIN 3.1045866785 #> 5385 2056E 3M CC37 2018 2018-01-02 TKN -0.1278333715 #> 5386 2056E 3M CC37 2018 2018-01-02 TN -0.1232982163 + #> 5387 2056E 3M CC37 2018 2018-01-02 TP -0.6348782724 #> 5388 2056E 3M CC37 2018 2018-01-02 TURB 1.5040773968 #> 5389 2056E 3M CC37 2018 2018-02-05 CHLAC 3.0445224377 #> 5390 2056E 3M CC37 2018 2018-02-05 COLOR 3.0910424534 #> 5391 2056E 3M CC37 2018 2018-02-05 DO 1.7227665977 #> 5392 2056E 3M CC37 2018 2018-02-05 DOSAT 4.3067641502 #> 5393 2056E 3M CC37 2018 2018-02-05 NO23 -4.1351665567 #> 5394 2056E 3M CC37 2018 2018-02-05 SALIN 3.1311369106 #> 5395 2056E 3M CC37 2018 2018-02-05 TKN -0.5108256238 #> 5396 2056E 3M CC37 2018 2018-02-05 TN -0.4845083154 + #> 5397 2056E 3M CC37 2018 2018-02-05 TP -2.0402208285 #> 5398 2056E 3M CC37 2018 2018-02-05 TURB 1.3609765531 #> 5399 2056E 3M CC37 2018 2018-03-05 CHLAC 1.9315214116 #> 5400 2056E 3M CC37 2018 2018-03-05 COLOR 3.1780538303 A #> 5401 2056E 3M CC37 2018 2018-03-05 DO 1.4973884086 #> 5402 2056E 3M CC37 2018 2018-03-05 DOSAT 4.0656020934 #> 5403 2056E 3M CC37 2018 2018-03-05 NO23 -5.2983173665 I #> 5404 2056E 3M CC37 2018 2018-03-05 SALIN 3.1540172525 #> 5405 2056E 3M CC37 2018 2018-03-05 TKN -0.2613647641 #> 5406 2056E 3M CC37 2018 2018-03-05 TN -0.2561834054 + #> 5407 2056E 3M CC37 2018 2018-03-05 TP -1.6607312068 #> 5408 2056E 3M CC37 2018 2018-03-05 TURB 1.3083328197 #> 5409 2056E 3M CC37 2018 2018-04-02 CHLAC 2.3978952728 #> 5410 2056E 3M CC37 2018 2018-04-02 COLOR 2.9444389792 A #> 5411 2056E 3M CC37 2018 2018-04-02 DO 1.3660916538 #> 5412 2056E 3M CC37 2018 2018-04-02 DOSAT 3.9963641539 #> 5413 2056E 3M CC37 2018 2018-04-02 NO23 -4.8283137373 I #> 5414 2056E 3M CC37 2018 2018-04-02 SALIN 3.2461018111 #> 5415 2056E 3M CC37 2018 2018-04-02 TKN -0.2613647641 #> 5416 2056E 3M CC37 2018 2018-04-02 TN -0.2561834054 + #> 5417 2056E 3M CC37 2018 2018-04-02 TP -1.6607312068 #> 5418 2056E 3M CC37 2018 2018-04-02 TURB 1.4109869737 A #> 5419 2056E 3M CC37 2018 2018-05-07 CHLAC 2.6390573296 #> 5420 2056E 3M CC37 2018 2018-05-07 COLOR 3.0445224377 #> 5421 2056E 3M CC37 2018 2018-05-07 DO 1.4011829736 #> 5422 2056E 3M CC37 2018 2018-05-07 DOSAT 4.0656020934 #> 5423 2056E 3M CC37 2018 2018-05-07 NO23 -5.2983173665 I #> 5424 2056E 3M CC37 2018 2018-05-07 SALIN 3.3225148596 #> 5425 2056E 3M CC37 2018 2018-05-07 TKN -0.0833816089 #> 5426 2056E 3M CC37 2018 2018-05-07 TN -0.0790432073 + #> 5427 2056E 3M CC37 2018 2018-05-07 TP -1.5606477483 #> 5428 2056E 3M CC37 2018 2018-05-07 TURB 1.5260563035 #> 5429 2056E 3M CC37 2018 2018-06-04 CHLAC 3.2958368660 #> 5430 2056E 3M CC37 2018 2018-06-04 COLOR 4.4773368145 #> 5431 2056E 3M CC37 2018 2018-06-04 DO 1.9286186519 #> 5432 2056E 3M CC37 2018 2018-06-04 DOSAT 4.5390303835 #> 5433 2056E 3M CC37 2018 2018-06-04 NO23 -4.0745419349 #> 5434 2056E 3M CC37 2018 2018-06-04 SALIN 1.9095425049 #> 5435 2056E 3M CC37 2018 2018-06-04 TKN 0.1823215568 #> 5436 2056E 3M CC37 2018 2018-06-04 TN 0.1963888140 + #> 5437 2056E 3M CC37 2018 2018-06-04 TP -0.9942522733 #> 5438 2056E 3M CC37 2018 2018-06-04 TURB 1.3862943611 #> 5439 2056E 3M CC37 2018 2018-07-09 CHLAC 2.6390573296 #> 5440 2056E 3M CC37 2018 2018-07-09 COLOR 4.8675344505 #> 5441 2056E 3M CC37 2018 2018-07-09 DO 1.2919836816 #> 5442 2056E 3M CC37 2018 2018-07-09 DOSAT 3.7977338590 #> 5443 2056E 3M CC37 2018 2018-07-09 NO23 -2.6310891600 #> 5444 2056E 3M CC37 2018 2018-07-09 SALIN 1.8148247422 #> 5445 2056E 3M CC37 2018 2018-07-09 TKN 0.1823215568 #> 5446 2056E 3M CC37 2018 2018-07-09 TN 0.2405904649 + #> 5447 2056E 3M CC37 2018 2018-07-09 TP -0.8675005677 #> 5448 2056E 3M CC37 2018 2018-07-09 TURB 0.6931471806 A #> 5449 2056E 3M CC37 2018 2018-08-06 CHLAC 1.8562979904 #> 5450 2056E 3M CC37 2018 2018-08-06 COLOR 4.8675344505 #> 5451 2056E 3M CC37 2018 2018-08-06 DO 1.3428648032 #> 5452 2056E 3M CC37 2018 2018-08-06 DOSAT 3.9435216725 #> 5453 2056E 3M CC37 2018 2018-08-06 NO23 -1.8325814637 #> 5454 2056E 3M CC37 2018 2018-08-06 SALIN 1.1281710909 #> 5455 2056E 3M CC37 2018 2018-08-06 TKN 0.0953101798 #> 5456 2056E 3M CC37 2018 2018-08-06 TN 0.2311117210 + #> 5457 2056E 3M CC37 2018 2018-08-06 TP -0.8209805521 #> 5458 2056E 3M CC37 2018 2018-08-06 TURB 0.5877866649 #> 5459 2056E 3M CC37 2019 2019-02-04 CHLAC 1.9878743482 A #> 5460 2056E 3M CC37 2019 2019-02-04 COLOR 3.3322045102 #> 5461 2056E 3M CC37 2019 2019-02-04 DO 2.0438143640 #> 5462 2056E 3M CC37 2019 2019-02-04 DOSAT 4.5622626850 #> 5463 2056E 3M CC37 2019 2019-02-04 NO23 -5.2983173665 I #> 5464 2056E 3M CC37 2019 2019-02-04 SALIN 2.7447035188 #> 5465 2056E 3M CC37 2019 2019-02-04 TKN -0.4780358009 #> 5466 2056E 3M CC37 2019 2019-02-04 TN -0.4716049106 + #> 5467 2056E 3M CC37 2019 2019-02-04 TP -1.7147984281 #> 5468 2056E 3M CC37 2019 2019-02-04 TURB 0.7884573604 #> 5469 2056E 3M CC37 2019 2019-05-06 CHLAC 2.3978952728 #> 5470 2056E 3M CC37 2019 2019-05-06 COLOR 3.1780538303 A #> 5471 2056E 3M CC37 2019 2019-05-06 DO 1.3110318766 #> 5472 2056E 3M CC37 2019 2019-05-06 DOSAT 3.9759363312 #> 5473 2056E 3M CC37 2019 2019-05-06 NO23 -5.5214609179 U #> 5474 2056E 3M CC37 2019 2019-05-06 SALIN 3.0320642028 #> 5475 2056E 3M CC37 2019 2019-05-06 TN -0.2331938872 + #> 5476 2056E 3M CC37 2019 2019-05-06 TP -1.4696759701 #> 5477 2056E 3M CC37 2019 2019-05-06 TURB 1.3350010667 #> 5478 2056E 3M CC37 2019 2019-06-03 CHLAC 2.0281482473 #> 5479 2056E 3M CC37 2019 2019-06-03 COLOR 3.2188758249 A #> 5480 2056E 3M CC37 2019 2019-06-03 DO 1.2864740258 #> 5481 2056E 3M CC37 2019 2019-06-03 DOSAT 3.9815490681 #> 5482 2056E 3M CC37 2019 2019-06-03 NO23 -5.5214609179 U #> 5483 2056E 3M CC37 2019 2019-06-03 SALIN 2.9982291538 #> 5484 2056E 3M CC37 2019 2019-06-03 TKN -0.0512932944 #> 5485 2056E 3M CC37 2019 2019-06-03 TN -0.0491902442 + #> 5486 2056E 3M CC37 2019 2019-06-03 TP -0.9416085399 #> 5487 2056E 3M CC37 2019 2019-06-03 TURB 0.8754687374 #> 5488 2056E 3M CC37 2019 2019-07-01 CHLAC 3.1354942159 #> 5489 2056E 3M CC37 2019 2019-07-01 COLOR 3.5553480615 A #> 5490 2056E 3M CC37 2019 2019-07-01 DO 0.6259384309 #> 5491 2056E 3M CC37 2019 2019-07-01 DOSAT 3.1441522787 #> 5492 2056E 3M CC37 2019 2019-07-01 NO23 -5.5214609179 I #> 5493 2056E 3M CC37 2019 2019-07-01 SALIN 2.7825390531 #> 5494 2056E 3M CC37 2019 2019-07-01 TKN -0.1278333715 #> 5495 2056E 3M CC37 2019 2019-07-01 TN -0.1232982163 + #> 5496 2056E 3M CC37 2019 2019-07-01 TP -0.5798184953 #> 5497 2056E 3M CC37 2019 2019-07-01 TURB 1.0296194172 #> 5498 2056E 3M CC37 2019 2019-08-05 CHLAC 3.1354942159 #> 5499 2056E 3M CC37 2019 2019-08-05 COLOR 4.2341065046 A #> 5500 2056E 3M CC37 2019 2019-08-05 DO 1.9685099810 #> 5501 2056E 3M CC37 2019 2019-08-05 DOSAT 4.5880240272 #> 5502 2056E 3M CC37 2019 2019-08-05 NO23 -4.9618451299 I #> 5503 2056E 3M CC37 2019 2019-08-05 SALIN 2.0744289999 #> 5504 2056E 3M CC37 2019 2019-08-05 TKN -0.1053605157 #> 5505 2056E 3M CC37 2019 2019-08-05 TN -0.1009259186 + #> 5506 2056E 3M CC37 2019 2019-08-05 TP -1.1086626245 #> 5507 2056E 3M CC37 2019 2019-08-05 TURB 1.1314021115 #> 5508 2056E 3M CC37 2019 2019-10-07 CHLAC 2.0794415417 #> 5509 2056E 3M CC37 2019 2019-10-07 COLOR 3.7376696183 A #> 5510 2056E 3M CC37 2019 2019-10-07 DO 1.4036429995 #> 5511 2056E 3M CC37 2019 2019-10-07 DOSAT 4.0910056610 #> 5512 2056E 3M CC37 2019 2019-10-07 NO23 -5.5214609179 U #> 5513 2056E 3M CC37 2019 2019-10-07 SALIN 3.0842009215 #> 5514 2056E 3M CC37 2019 2019-10-07 TKN -0.3566749439 #> 5515 2056E 3M CC37 2019 2019-10-07 TN -0.3538218750 + #> 5516 2056E 3M CC37 2019 2019-10-07 TP -1.6607312068 #> 5517 2056E 3M CC37 2019 2019-10-07 TURB 0.4054651081 #> 5518 2056E 3M CC37 2019 2019-11-04 CHLAC 1.1939224685 #> 5519 2056E 3M CC37 2019 2019-11-04 COLOR 3.5835189385 #> 5520 2056E 3M CC37 2019 2019-11-04 DO 1.6034198401 #> 5521 2056E 3M CC37 2019 2019-11-04 DOSAT 4.2470656492 #> 5522 2056E 3M CC37 2019 2019-11-04 NO23 -4.4228486292 #> 5523 2056E 3M CC37 2019 2019-11-04 SALIN 2.9922261342 #> 5524 2056E 3M CC37 2019 2019-11-04 TKN -0.3285040670 #> 5525 2056E 3M CC37 2019 2019-11-04 TN -0.3119747650 + #> 5526 2056E 3M CC37 2019 2019-11-04 TP -1.4271163556 #> 5527 2056E 3M CC37 2019 2019-11-04 TURB 0.0000000000 #> 5528 2056E 3M CC37 2019 2019-12-02 CHLAC 1.8245492921 A #> 5529 2056E 3M CC37 2019 2019-12-02 COLOR 3.3322045102 #> 5530 2056E 3M CC37 2019 2019-12-02 DO 1.3532545070 #> 5531 2056E 3M CC37 2019 2019-12-02 DOSAT 3.9740583963 #> 5532 2056E 3M CC37 2019 2019-12-02 NO23 -5.2983173665 I #> 5533 2056E 3M CC37 2019 2019-12-02 SALIN 3.1363634033 #> 5534 2056E 3M CC37 2019 2019-12-02 TKN -0.4942963218 #> 5535 2056E 3M CC37 2019 2019-12-02 TN -0.4877603508 + #> 5536 2056E 3M CC37 2019 2019-12-02 TP -1.8325814637 #> 5537 2056E 3M CC37 2019 2019-12-02 TURB 0.7884573604 #> 5538 2056E 3M CC37 2020 2020-01-06 CHLAC 2.7080502011 #> 5539 2056E 3M CC37 2020 2020-01-06 COLOR 3.1354942159 A #> 5540 2056E 3M CC37 2020 2020-01-06 DO 2.0055258587 #> 5541 2056E 3M CC37 2020 2020-01-06 DOSAT 4.5347477217 #> 5542 2056E 3M CC37 2020 2020-01-06 NO23 -4.7105307016 I #> 5543 2056E 3M CC37 2020 2020-01-06 SALIN 3.0387917630 #> 5544 2056E 3M CC37 2020 2020-01-06 TKN -0.3710636814 #> 5545 2056E 3M CC37 2020 2020-01-06 TN -0.3652833185 + #> 5546 2056E 3M CC37 2020 2020-01-06 TP -1.6607312068 #> 5547 2056E 3M CC37 2020 2020-01-06 TURB 1.0647107370 #> 5548 2056E 3M CC37 2020 2020-02-03 CHLAC 2.5649493575 #> 5549 2056E 3M CC37 2020 2020-02-03 COLOR 2.9957322736 #> 5550 2056E 3M CC37 2020 2020-02-03 DO 1.8148247422 #> 5551 2056E 3M CC37 2020 2020-02-03 DOSAT 4.2808241292 #> 5552 2056E 3M CC37 2020 2020-02-03 NO23 -4.3428059215 #> 5553 2056E 3M CC37 2020 2020-02-03 SALIN 3.1175073305 #> 5554 2056E 3M CC37 2020 2020-02-03 TKN -0.3856624808 #> 5555 2056E 3M CC37 2020 2020-02-03 TN -0.3667252798 + #> 5556 2056E 3M CC37 2020 2020-02-03 TP -1.9661128564 #> 5557 2056E 3M CC37 2020 2020-02-03 TURB 1.4109869737 A #> 5558 2056E 3M CC37 2020 2020-03-02 CHLAC 1.9740810260 #> 5559 2056E 3M CC37 2020 2020-03-02 COLOR 2.8903717579 #> 5560 2056E 3M CC37 2020 2020-03-02 DO 1.8484548129 #> 5561 2056E 3M CC37 2020 2020-03-02 DOSAT 4.3832758541 #> 5562 2056E 3M CC37 2020 2020-03-02 NO23 -5.2983173665 I #> 5563 2056E 3M CC37 2020 2020-03-02 SALIN 3.1320098918 #> 5564 2056E 3M CC37 2020 2020-03-02 TKN -0.4004775666 #> 5565 2056E 3M CC37 2020 2020-03-02 TN -0.3945251681 + #> 5566 2056E 3M CC37 2020 2020-03-02 TP -1.9661128564 #> 5567 2056E 3M CC37 2020 2020-03-02 TURB 1.2809338455 A #> 5568 2056E 3M CC37 2020 2020-09-08 CHLAC 1.6486586256 #> 5569 2056E 3M CC37 2020 2020-09-08 COLOR 4.4998096703 #> 5570 2056E 3M CC37 2020 2020-09-08 DO 0.8837675402 #> 5571 2056E 3M CC37 2020 2020-09-08 DOSAT 3.5085559000 #> 5572 2056E 3M CC37 2020 2020-09-08 NO23 -3.1465551633 #> 5573 2056E 3M CC37 2020 2020-09-08 SALIN 2.2428350886 #> 5574 2056E 3M CC37 2020 2020-09-08 TKN -0.1743533871 #> 5575 2056E 3M CC37 2020 2020-09-08 TN -0.1244300784 + #> 5576 2056E 3M CC37 2020 2020-09-08 TP -0.9162907319 #> 5577 2056E 3M CC37 2020 2020-09-08 TURB 0.4700036292 #> 5578 2056E 3M CC37 2020 2020-10-05 CHLAC 1.7047480922 #> 5579 2056E 3M CC37 2020 2020-10-05 COLOR 4.5951198501 A #> 5580 2056E 3M CC37 2020 2020-10-05 DO 0.8837675402 #> 5581 2056E 3M CC37 2020 2020-10-05 DOSAT 3.4657359028 #> 5582 2056E 3M CC37 2020 2020-10-05 NO23 -3.2701691193 #> 5583 2056E 3M CC37 2020 2020-10-05 SALIN 2.6181254936 #> 5584 2056E 3M CC37 2020 2020-10-05 TKN 0.1823215568 #> 5585 2056E 3M CC37 2020 2020-10-05 TN 0.2134971743 + #> 5586 2056E 3M CC37 2020 2020-10-05 TP -0.7765287895 #> 5587 2056E 3M CC37 2020 2020-10-05 TURB 0.3364722366 #> 5588 2056E 3M CC37 2020 2020-11-02 CHLAC 2.1400661635 #> 5589 2056E 3M CC37 2020 2020-11-02 COLOR 4.2046926194 #> 5590 2056E 3M CC37 2020 2020-11-02 DO 1.8468787684 #> 5591 2056E 3M CC37 2020 2020-11-02 DOSAT 4.4670568839 #> 5592 2056E 3M CC37 2020 2020-11-02 NO23 -3.2968373663 #> 5593 2056E 3M CC37 2020 2020-11-02 SALIN 2.6525374912 #> 5594 2056E 3M CC37 2020 2020-11-02 TKN -0.3147107448 #> 5595 2056E 3M CC37 2020 2020-11-02 TN -0.2652684776 + #> 5596 2056E 3M CC37 2020 2020-11-02 TP -1.3093333200 #> 5597 2056E 3M CC37 2020 2020-11-02 TURB 0.6931471806 A #> 5598 2056E 3M CC37 2020 2020-12-07 CHLAC 1.6677068206 #> 5599 2056E 3M CC37 2020 2020-12-07 COLOR 3.8712010109 #> 5600 2056E 3M CC37 2020 2020-12-07 DO 1.9050881545 #> 5601 2056E 3M CC37 2020 2020-12-07 DOSAT 4.4164280614 #> 5602 2056E 3M CC37 2020 2020-12-07 NO23 -3.9633162998 #> 5603 2056E 3M CC37 2020 2020-12-07 SALIN 2.8735646396 #> 5604 2056E 3M CC37 2020 2020-12-07 TKN -0.4942963218 #> 5605 2056E 3M CC37 2020 2020-12-07 TN -0.4636240223 + #> 5606 2056E 3M CC37 2020 2020-12-07 TP -1.8325814637 #> 5607 2056E 3M CC37 2020 2020-12-07 TURB 0.1823215568 #> 5608 2056E 3M CC37 2021 2021-01-04 CHLAC 0.8754687374 I #> 5609 2056E 3M CC37 2021 2021-01-04 COLOR 3.5835189385 #> 5610 2056E 3M CC37 2021 2021-01-04 DO 1.4279160358 #> 5611 2056E 3M CC37 2021 2021-01-04 DOSAT 3.9569963711 #> 5612 2056E 3M CC37 2021 2021-01-04 NO23 -4.1351665567 #> 5613 2056E 3M CC37 2021 2021-01-04 SALIN 2.8249439526 #> 5614 2056E 3M CC37 2021 2021-01-04 TKN -0.3285040670 #> 5615 2056E 3M CC37 2021 2021-01-04 TN -0.3065251603 + #> 5616 2056E 3M CC37 2021 2021-01-04 TP -1.8971199849 #> 5617 2056E 3M CC37 2021 2021-01-04 TURB 0.6418538862 #> 5618 2056E 3M CC37 2021 2021-02-01 CHLAC 1.0986122887 #> 5619 2056E 3M CC37 2021 2021-02-01 COLOR 3.2958368660 A #> 5620 2056E 3M CC37 2021 2021-02-01 DO 2.0464016876 #> 5621 2056E 3M CC37 2021 2021-02-01 DOSAT 4.5767707115 #> 5622 2056E 3M CC37 2021 2021-02-01 NO23 -5.1159958098 I #> 5623 2056E 3M CC37 2021 2021-02-01 SALIN 2.9957322736 #> 5624 2056E 3M CC37 2021 2021-02-01 TKN -0.5108256238 #> 5625 2056E 3M CC37 2021 2021-02-01 TN -0.5041810810 + #> 5626 2056E 3M CC37 2021 2021-02-01 TP -2.1202635362 #> 5627 2056E 3M CC37 2021 2021-02-01 TURB 0.6418538862 #> 5628 2056E 3M CC37 2021 2021-03-01 CHLAC 1.5260563035 #> 5629 2056E 3M CC37 2021 2021-03-01 COLOR 3.2580965380 A #> 5630 2056E 3M CC37 2021 2021-03-01 DO 1.4134230285 #> 5631 2056E 3M CC37 2021 2021-03-01 DOSAT 4.0412953411 #> 5632 2056E 3M CC37 2021 2021-03-01 NO23 -5.1159958098 I #> 5633 2056E 3M CC37 2021 2021-03-01 SALIN 3.0445224377 #> 5634 2056E 3M CC37 2021 2021-03-01 TKN -0.6161861394 #> 5635 2056E 3M CC37 2021 2021-03-01 TN -0.6088060321 + #> 5636 2056E 3M CC37 2021 2021-03-01 TP -1.9661128564 #> 5637 2056E 3M CC37 2021 2021-03-01 TURB 1.1314021115 A #> 5638 2056E 3M CC37 2021 2021-04-05 CHLAC 1.7917594692 #> 5639 2056E 3M CC37 2021 2021-04-05 COLOR 3.1354942159 #> 5640 2056E 3M CC37 2021 2021-04-05 DO 1.5040773968 #> 5641 2056E 3M CC37 2021 2021-04-05 DOSAT 4.0604430105 #> 5642 2056E 3M CC37 2021 2021-04-05 NO23 -4.5098600062 #> 5643 2056E 3M CC37 2021 2021-04-05 SALIN 3.1599747169 #> 5644 2056E 3M CC37 2021 2021-04-05 TKN -0.1984509387 #> 5645 2056E 3M CC37 2021 2021-04-05 TN -0.1851254841 + #> 5646 2056E 3M CC37 2021 2021-04-05 TP -1.7719568419 #> 5647 2056E 3M CC37 2021 2021-04-05 TURB 1.7047480922 #> 5648 2056E 3M CC37 2021 2021-05-03 CHLAC 2.0149030205 #> 5649 2056E 3M CC37 2021 2021-05-03 COLOR 3.1354942159 #> 5650 2056E 3M CC37 2021 2021-05-03 DO 1.1314021115 #> 5651 2056E 3M CC37 2021 2021-05-03 DOSAT 3.8286413965 #> 5652 2056E 3M CC37 2021 2021-05-03 NO23 -4.8283137373 I #> 5653 2056E 3M CC37 2021 2021-05-03 SALIN 3.2196755050 #> 5654 2056E 3M CC37 2021 2021-05-03 TKN -0.3011050928 #> 5655 2056E 3M CC37 2021 2021-05-03 TN -0.2957142441 + #> 5656 2056E 3M CC37 2021 2021-05-03 TP -1.4696759701 #> 5657 2056E 3M CC37 2021 2021-05-03 TURB 1.5260563035 #> 5658 2056E 3M CC37 2021 2021-06-07 CHLAC 2.2617630985 #> 5659 2056E 3M CC37 2021 2021-06-07 COLOR 2.8903717579 #> 5660 2056E 3M CC37 2021 2021-06-07 DO 1.1314021115 #> 5661 2056E 3M CC37 2021 2021-06-07 DOSAT 3.8286413965 #> 5662 2056E 3M CC37 2021 2021-06-07 NO23 -5.5214609179 U #> 5663 2056E 3M CC37 2021 2021-06-07 SALIN 3.2196755050 #> 5664 2056E 3M CC37 2021 2021-06-07 TKN 0.0953101798 #> 5665 2056E 3M CC37 2021 2021-06-07 TN 0.0971267107 + #> 5666 2056E 3M CC37 2021 2021-06-07 TP -1.3093333200 #> 5667 2056E 3M CC37 2021 2021-06-07 TURB 1.2809338455 #> 5668 2056E 3M CC37 2021 2021-08-02 CHLAC 2.7080502011 #> 5669 2056E 3M CC37 2021 2021-08-02 COLOR 4.5217885770 #> 5670 2056E 3M CC37 2021 2021-08-02 DO 1.6034198401 #> 5671 2056E 3M CC37 2021 2021-08-02 DOSAT 4.2766661190 #> 5672 2056E 3M CC37 2021 2021-08-02 NO23 -5.5214609179 U #> 5673 2056E 3M CC37 2021 2021-08-02 SALIN 2.1871742415 #> 5674 2056E 3M CC37 2021 2021-08-02 TKN -0.1053605157 #> 5675 2056E 3M CC37 2021 2021-08-02 TN -0.1031407589 + #> 5676 2056E 3M CC37 2021 2021-08-02 TP -0.6733445533 #> 5677 2056E 3M CC37 2021 2021-08-02 TURB 0.8754687374 #> 5678 2056E 3M CC37 2021 2021-09-07 CHLAC 1.8405496334 #> 5679 2056E 3M CC37 2021 2021-09-07 COLOR 4.2341065046 #> 5680 2056E 3M CC37 2021 2021-09-07 DO 1.5260563035 #> 5681 2056E 3M CC37 2021 2021-09-07 DOSAT 4.1447207695 #> 5682 2056E 3M CC37 2021 2021-09-07 NO23 -3.6119184130 #> 5683 2056E 3M CC37 2021 2021-09-07 SALIN 2.0041790572 #> 5684 2056E 3M CC37 2021 2021-09-07 TKN -0.0943106795 #> 5685 2056E 3M CC37 2021 2021-09-07 TN -0.0650719967 + #> 5686 2056E 3M CC37 2021 2021-09-07 TP -1.0788096614 #> 5687 2056E 3M CC37 2021 2021-09-07 TURB 0.5306282511 A #> 5688 2056E 3M CC37 2021 2021-10-04 CHLAC 2.4849066498 #> 5689 2056E 3M CC37 2021 2021-10-04 COLOR 4.5643481915 A #> 5690 2056E 3M CC37 2021 2021-10-04 DO 0.4446858213 #> 5691 2056E 3M CC37 2021 2021-10-04 DOSAT 3.0587070727 #> 5692 2056E 3M CC37 2021 2021-10-04 NO23 -3.0576076773 #> 5693 2056E 3M CC37 2021 2021-10-04 SALIN 2.4932054526 #> 5694 2056E 3M CC37 2021 2021-10-04 TKN 0.0953101798 #> 5695 2056E 3M CC37 2021 2021-10-04 TN 0.1371498381 + #> 5696 2056E 3M CC37 2021 2021-10-04 TP -0.7985076962 #> 5697 2056E 3M CC37 2021 2021-10-04 TURB 0.4054651081 #> 5698 2056E 3M CC37 2021 2021-11-01 CHLAC 1.7749523509 #> 5699 2056E 3M CC37 2021 2021-11-01 COLOR 3.7612001157 A #> 5700 2056E 3M CC37 2021 2021-11-01 DO 1.2325602612 #> 5701 2056E 3M CC37 2021 2021-11-01 DOSAT 3.8177123260 #> 5702 2056E 3M CC37 2021 2021-11-01 NO23 -3.5065578973 #> 5703 2056E 3M CC37 2021 2021-11-01 SALIN 2.9444389792 #> 5704 2056E 3M CC37 2021 2021-11-01 TKN -0.2231435513 #> 5705 2056E 3M CC37 2021 2021-11-01 TN -0.1863295782 + #> 5706 2056E 3M CC37 2021 2021-11-01 TP -1.6094379124 #> 5707 2056E 3M CC37 2021 2021-11-01 TURB 0.2623642645 #> 5708 2056E 3M CC37 2021 2021-12-06 CHLAC 1.7578579176 #> 5709 2056E 3M CC37 2021 2021-12-06 COLOR 3.0445224377 #> 5710 2056E 3M CC37 2021 2021-12-06 DO 1.5260563035 #> 5711 2056E 3M CC37 2021 2021-12-06 DOSAT 4.1157798429 #> 5712 2056E 3M CC37 2021 2021-12-06 NO23 -4.7105307016 I #> 5713 2056E 3M CC37 2021 2021-12-06 SALIN 3.1471649773 #> 5714 2056E 3M CC37 2021 2021-12-06 TKN -0.5978370008 #> 5715 2056E 3M CC37 2021 2021-12-06 TN -0.5905905922 + #> 5716 2056E 3M CC37 2021 2021-12-06 TP -2.1202635362 #> 5717 2056E 3M CC37 2021 2021-12-06 TURB 0.4700036292 #> 5718 2056E 3M CC37 2022 2022-01-03 CHLAC 2.1162555148 #> 5719 2056E 3M CC37 2022 2022-01-03 COLOR 2.8903717579 #> 5720 2056E 3M CC37 2022 2022-01-03 DO 1.2974631474 #> 5721 2056E 3M CC37 2022 2022-01-03 DOSAT 3.9160150267 #> 5722 2056E 3M CC37 2022 2022-01-03 NO23 -4.9618451299 I #> 5723 2056E 3M CC37 2022 2022-01-03 SALIN 3.1289511173 #> 5724 2056E 3M CC37 2022 2022-01-03 TKN -0.4780358009 #> 5725 2056E 3M CC37 2022 2022-01-03 TN -0.4716049106 + #> 5726 2056E 3M CC37 2022 2022-01-03 TP -1.9661128564 #> 5727 2056E 3M CC37 2022 2022-01-03 TURB 1.2809338455 A #> 5728 2056E 3M CC37 2022 2022-02-07 CHLAC 2.0918640617 #> 5729 2056E 3M CC37 2022 2022-02-07 COLOR 2.6390573296 #> 5730 2056E 3M CC37 2022 2022-02-07 DO 1.5518087996 #> 5731 2056E 3M CC37 2022 2022-02-07 DOSAT 4.1075897890 #> 5732 2056E 3M CC37 2022 2022-02-07 NO23 -4.1351665567 #> 5733 2056E 3M CC37 2022 2022-02-07 SALIN 3.2323841749 #> 5734 2056E 3M CC37 2022 2022-02-07 TKN -0.2484613593 #> 5735 2056E 3M CC37 2022 2022-02-07 TN -0.2281560931 + #> 5736 2056E 3M CC37 2022 2022-02-07 TP -2.1202635362 #> 5737 2056E 3M CC37 2022 2022-02-07 TURB 0.5877866649 #> 5738 2056E 3M CC37 2022 2022-03-07 CHLAC 1.3350010667 #> 5739 2056E 3M CC37 2022 2022-03-07 COLOR 2.3978952728 #> 5740 2056E 3M CC37 2022 2022-03-07 DO 1.5769147207 #> 5741 2056E 3M CC37 2022 2022-03-07 DOSAT 4.2150861799 #> 5742 2056E 3M CC37 2022 2022-03-07 NO23 -5.5214609179 I #> 5743 2056E 3M CC37 2022 2022-03-07 SALIN 3.2820383998 #> 5744 2056E 3M CC37 2022 2022-03-07 TKN -0.4004775666 #> 5745 2056E 3M CC37 2022 2022-03-07 TN -0.3945251681 + #> 5746 2056E 3M CC37 2022 2022-03-07 TP -2.0402208285 #> 5747 2056E 3M CC37 2022 2022-03-07 TURB 1.0647107370 #> 5748 2056E 3M CC37 2022 2022-04-04 CHLAC 1.6863989536 #> 5749 2056E 3M CC37 2022 2022-04-04 COLOR 2.5649493575 #> 5750 2056E 3M CC37 2022 2022-04-04 DO 1.4816045409 #> 5751 2056E 3M CC37 2022 2022-04-04 DOSAT 4.1319614258 #> 5752 2056E 3M CC37 2022 2022-04-04 NO23 -4.5098600062 #> 5753 2056E 3M CC37 2022 2022-04-04 SALIN 3.3311325072 #> 5754 2056E 3M CC37 2022 2022-04-04 TN -0.6520052372 + #> 5755 2056E 3M CC37 2022 2022-04-04 TP -1.7719568419 #> 5756 2056E 3M CC37 2022 2022-04-04 TURB 1.1631508098 #> 5757 2056E 3M CC37 2022 2022-05-02 CHLAC 1.5892352051 #> 5758 2056E 3M CC37 2022 2022-05-02 COLOR 2.7080502011 #> 5759 2056E 3M CC37 2022 2022-05-02 DO 1.3660916538 #> 5760 2056E 3M CC37 2022 2022-05-02 DOSAT 4.0500443033 #> 5761 2056E 3M CC37 2022 2022-05-02 NO23 -5.2983173665 I #> 5762 2056E 3M CC37 2022 2022-05-02 SALIN 3.3755376349 #> 5763 2056E 3M CC37 2022 2022-05-02 TKN -0.2744368457 #> 5764 2056E 3M CC37 2022 2022-05-02 TN -0.2691874898 + #> 5765 2056E 3M CC37 2022 2022-05-02 TP -1.6094379124 #> 5766 2056E 3M CC37 2022 2022-05-02 TURB 1.2527629685 A #> 5767 2056E 3M CC37 2022 2022-06-06 CHLAC 2.9444389792 #> 5768 2056E 3M CC37 2022 2022-06-06 COLOR 3.0910424534 #> 5769 2056E 3M CC37 2022 2022-06-06 DO 1.1019400788 #> 5770 2056E 3M CC37 2022 2022-06-06 DOSAT 3.7909846771 #> 5771 2056E 3M CC37 2022 2022-06-06 NO23 -5.1159958098 I #> 5772 2056E 3M CC37 2022 2022-06-06 SALIN 3.1851121947 #> 5773 2056E 3M CC37 2022 2022-06-06 TKN -0.0725706928 #> 5774 2056E 3M CC37 2022 2022-06-06 TN -0.0682788408 + #> 5775 2056E 3M CC37 2022 2022-06-06 TP -1.1711829815 #> 5776 2056E 3M CC37 2022 2022-06-06 TURB 1.3609765531 A #> 5777 2056E 3M CC37 2022 2022-07-05 CHLAC 1.7047480922 #> 5778 2056E 3M CC37 2022 2022-07-05 COLOR 3.6635616461 #> 5779 2056E 3M CC37 2022 2022-07-05 DO 1.3056264581 #> 5780 2056E 3M CC37 2022 2022-07-05 DOSAT 3.9684033389 #> 5781 2056E 3M CC37 2022 2022-07-05 NO23 -5.5214609179 U #> 5782 2056E 3M CC37 2022 2022-07-05 SALIN 2.7047112998 #> 5783 2056E 3M CC37 2022 2022-07-05 TKN -0.2613647641 #> 5784 2056E 3M CC37 2022 2022-07-05 TN -0.2587707290 + #> 5785 2056E 3M CC37 2022 2022-07-05 TP -1.3093333200 #> 5786 2056E 3M CC37 2022 2022-07-05 TURB 0.5877866649 A #> 5787 2056E 3M CC37 2022 2022-08-01 CHLAC 1.9459101491 #> 5788 2056E 3M CC37 2022 2022-08-01 COLOR 4.1588830834 #> 5789 2056E 3M CC37 2022 2022-08-01 DO 1.2029723040 #> 5790 2056E 3M CC37 2022 2022-08-01 DOSAT 3.8501476017 #> 5791 2056E 3M CC37 2022 2022-08-01 NO23 -5.5214609179 I #> 5792 2056E 3M CC37 2022 2022-08-01 SALIN 2.5201129055 #> 5793 2056E 3M CC37 2022 2022-08-01 TKN 0.0000000000 #> 5794 2056E 3M CC37 2022 2022-08-01 TN 0.0039920213 + #> 5795 2056E 3M CC37 2022 2022-08-01 TP -1.1394342832 #> 5796 2056E 3M CC37 2022 2022-08-01 TURB 0.7419373447 #> 5797 2056E 3M CC37 2022 2022-09-06 CHLAC 2.5649493575 #> 5798 2056E 3M CC37 2022 2022-09-06 COLOR 4.3694478525 A #> 5799 2056E 3M CC37 2022 2022-09-06 NO23 -5.1159958098 I #> 5800 2056E 3M CC37 2022 2022-09-06 SALIN 2.2955604781 #> 5801 2056E 3M CC37 2022 2022-09-06 TKN -0.1508228897 #> 5802 2056E 3M CC37 2022 2022-09-06 TN -0.1461825102 + #> 5803 2056E 3M CC37 2022 2022-09-06 TP -1.1086626245 #> 5804 2056E 3M CC37 2022 2022-09-06 TURB 0.6418538862 #> 5805 2056E 3M CC37 2022 2022-11-07 COLOR 4.2046926194 A #> 5806 2056E 3M CC37 2022 2022-11-07 DO 1.5238800241 #> 5807 2056E 3M CC37 2022 2022-11-07 DOSAT 4.1383614476 #> 5808 2056E 3M CC37 2022 2022-11-07 NO23 -3.0159349809 #> 5809 2056E 3M CC37 2022 2022-11-07 SALIN 2.7744619666 #> 5810 2056E 3M CC37 2022 2022-11-07 TKN -0.0725706928 #> 5811 2056E 3M CC37 2022 2022-11-07 TN -0.0212236365 + #> 5812 2056E 3M CC37 2022 2022-11-07 TP -0.9416085399 #> 5813 2056E 3M CC37 2022 2022-11-07 TURB 0.5306282511 #> 5814 2056E 3M CC37 2022 2022-11-07 CHLAC 2.1517622033 #> 5815 2056E 3M CC37 2022 2022-11-07 COLOR 4.1431347264 #> 5816 2056E 3M CC37 2022 2022-11-07 DO 1.5238800241 #> 5817 2056E 3M CC37 2022 2022-11-07 DOSAT 4.1383614476 #> 5818 2056E 3M CC37 2022 2022-11-07 NO23 -2.9957322736 #> 5819 2056E 3M CC37 2022 2022-11-07 SALIN 2.7744619666 #> 5820 2056E 3M CC37 2022 2022-11-07 TKN 0.0000000000 #> 5821 2056E 3M CC37 2022 2022-11-07 TN 0.0487901642 + #> 5822 2056E 3M CC37 2022 2022-11-07 TP -0.9162907319 #> 5823 2056E 3M CC37 2022 2022-11-07 TURB 0.6418538862 #> 5824 2056E 3M CC37 2022 2022-12-05 CHLAC 2.3025850930 #> 5825 2056E 3M CC37 2022 2022-12-05 COLOR 3.8918202981 A #> 5826 2056E 3M CC37 2022 2022-12-05 DO 1.3812818193 #> 5827 2056E 3M CC37 2022 2022-12-05 DOSAT 3.9337844972 #> 5828 2056E 3M CC37 2022 2022-12-05 NO23 -2.8824035882 #> 5829 2056E 3M CC37 2022 2022-12-05 SALIN 2.8219739474 #> 5830 2056E 3M CC37 2022 2022-12-05 TKN -0.3147107448 #> 5831 2056E 3M CC37 2022 2022-12-05 TN -0.2407984866 + #> 5832 2056E 3M CC37 2022 2022-12-05 TP -1.4696759701 #> 5833 2056E 3M CC37 2022 2022-12-05 TURB 0.5306282511 #> 5834 2056E 3M CC37 2023 2023-01-03 CHLAC 2.8903717579 #> 5835 2056E 3M CC37 2023 2023-01-03 COLOR 3.4011973817 A #> 5836 2056E 3M CC37 2023 2023-01-03 DO 1.5953389881 #> 5837 2056E 3M CC37 2023 2023-01-03 DOSAT 4.1510399059 #> 5838 2056E 3M CC37 2023 2023-01-03 NO23 -3.8167128256 #> 5839 2056E 3M CC37 2023 2023-01-03 SALIN 2.9699015135 #> 5840 2056E 3M CC37 2023 2023-01-03 TKN -0.1984509387 #> 5841 2056E 3M CC37 2023 2023-01-03 TN -0.1719752647 + #> 5842 2056E 3M CC37 2023 2023-01-03 TP -1.6094379124 #> 5843 2056E 3M CC37 2023 2023-01-03 TURB 1.4109869737 #> 5844 2056E 3M CC37 2023 2023-02-06 CHLAC 1.8082887712 #> 5845 2056E 3M CC37 2023 2023-02-06 COLOR 3.1780538303 #> 5846 2056E 3M CC37 2023 2023-02-06 DO 1.5953389881 #> 5847 2056E 3M CC37 2023 2023-02-06 DOSAT 4.1510399059 #> 5848 2056E 3M CC37 2023 2023-02-06 NO23 -5.5214609179 U #> 5849 2056E 3M CC37 2023 2023-02-06 SALIN 2.9699015135 #> 5850 2056E 3M CC37 2023 2023-02-06 TKN -0.3011050928 #> 5851 2056E 3M CC37 2023 2023-02-06 TN -0.2984060358 + #> 5852 2056E 3M CC37 2023 2023-02-06 TP -1.7147984281 #> 5853 2056E 3M CC37 2023 2023-02-06 TURB 0.6418538862 #> 5854 2056E 3M CC37 2023 2023-03-06 DO 1.1085626195 #> 5855 2056E 3M CC37 2023 2023-03-06 DOSAT 3.7727609381 #> 5856 2056E 3M CC37 2023 2023-03-06 SALIN 3.0905878046 #> 5857 2056E 3M CC42 2019 2019-10-10 CHLAC 1.5892352051 #> 5858 2056E 3M CC42 2019 2019-10-10 COND 9.8078573215 #> 5859 2056E 3M CC42 2019 2019-10-10 NO23 -3.7722610631 #> 5860 2056E 3M CC42 2019 2019-10-10 SALIN 2.3721111556 #> 5861 2056E 3M CC42 2019 2019-10-10 TKN -0.3566749439 #> 5862 2056E 3M CC42 2019 2019-10-10 TN -0.3243460568 + #> 5863 2056E 3M CC42 2019 2019-10-10 TP -1.0498221245 #> 5864 2056E 3M CC42 2019 2019-10-10 TSS 1.7917594692 I #> 5865 2056E 3M CC42 2019 2019-10-10 TURB 1.0647107370 #> 5866 2056C2 3M CC45 2014 2014-06-10 COND 9.8892364868 #> 5867 2056C2 3M CC45 2014 2014-06-10 DO 1.9344157696 #> 5868 2056C2 3M CC45 2014 2014-06-10 DOSAT 4.5920849464 + #> 5869 2056C2 3M CC45 2014 2014-06-10 SALIN 2.4595888418 #> 5870 2056C2 3M CC45 2014 2014-06-10 NO23 -5.5214609179 U #> 5871 2056C2 3M CC45 2014 2014-06-10 TKN 1.2809338455 #> 5872 2056C2 3M CC45 2014 2014-06-10 TN 1.2809338455 #> 5873 2056C2 3M CC45 2014 2014-06-10 TSS 2.3513752572 #> 5874 2056C2 3M CC45 2014 2014-06-10 COND 9.8874597915 #> 5875 2056C2 3M CC45 2014 2014-06-10 DO 2.0014800002 #> 5876 2056C2 3M CC45 2014 2014-06-10 DOSAT 4.6587109529 + #> 5877 2056C2 3M CC45 2014 2014-06-10 SALIN 2.4587337755 #> 5878 2056C2 3M CC45 2014 2014-06-10 COND 9.9269599087 #> 5879 2056C2 3M CC45 2014 2014-06-10 DO 1.9933388426 #> 5880 2056C2 3M CC45 2014 2014-06-10 DOSAT 4.6510991179 + #> 5881 2056C2 3M CC45 2014 2014-06-10 SALIN 2.5014359517 #> 5882 2056C2 3M CC45 2014 2014-06-10 COND 9.9782238987 #> 5883 2056C2 3M CC45 2014 2014-06-10 DO 1.8916048042 #> 5884 2056C2 3M CC45 2014 2014-06-10 DOSAT 4.5475410732 + #> 5885 2056C2 3M CC45 2014 2014-06-10 SALIN 2.5572273114 #> 5886 2056C2 3M CC45 2014 2014-06-10 COND 10.0037852739 #> 5887 2056C2 3M CC45 2014 2014-06-10 DO 1.8017098001 #> 5888 2056C2 3M CC45 2014 2014-06-10 DOSAT 4.4578295981 + #> 5889 2056C2 3M CC45 2014 2014-06-10 SALIN 2.5862591440 #> 5890 2056C2 3M CC45 2014 2014-06-10 COND 10.0950165901 #> 5891 2056C2 3M CC45 2014 2014-06-10 DO 1.5475625087 #> 5892 2056C2 3M CC45 2014 2014-06-10 DOSAT 4.2061840440 + #> 5893 2056C2 3M CC45 2014 2014-06-10 SALIN 2.6932749155 #> 5894 2056C2 3M CC45 2014 2014-06-10 COND 10.1085078656 #> 5895 2056C2 3M CC45 2014 2014-06-10 DO 1.4562867329 #> 5896 2056C2 3M CC45 2014 2014-06-10 DOSAT 4.1141471895 + #> 5897 2056C2 3M CC45 2014 2014-06-10 SALIN 2.6932749155 #> 5898 2056C2 3M CC45 2014 2014-06-10 COND 10.1103391071 #> 5899 2056C2 3M CC45 2014 2014-06-10 DO 1.4182774070 #> 5900 2056C2 3M CC45 2014 2014-06-10 DOSAT 4.0775374439 + #> 5901 2056C2 3M CC45 2014 2014-06-10 SALIN 2.7020321288 #> 5902 2056C2 3M CC45 2014 2014-06-10 COND 10.1112331617 #> 5903 2056C2 3M CC45 2014 2014-06-10 DO 1.4109869737 #> 5904 2056C2 3M CC45 2014 2014-06-10 DOSAT 4.0690267542 + #> 5905 2056C2 3M CC45 2014 2014-06-10 SALIN 2.7027025948 #> 5906 2056C2 3M CC45 2014 2014-06-10 COND 10.1134242764 #> 5907 2056C2 3M CC45 2014 2014-06-10 DO 1.3787660947 #> 5908 2056C2 3M CC45 2014 2014-06-10 DOSAT 4.0377742107 + #> 5909 2056C2 3M CC45 2014 2014-06-10 SALIN 2.7053799725 #> 5910 2056C2 3M CC45 2014 2014-07-10 COND 9.9863570304 #> 5911 2056C2 3M CC45 2014 2014-07-10 DO 2.9204697891 #> 5912 2056C2 3M CC45 2014 2014-07-10 DOSAT 5.6028565561 + #> 5913 2056C2 3M CC45 2014 2014-07-10 SALIN 2.5664866368 #> 5914 2056C2 3M CC45 2014 2014-07-10 NO23 -4.1351665567 I #> 5915 2056C2 3M CC45 2014 2014-07-10 TKN 0.5933268453 #> 5916 2056C2 3M CC45 2014 2014-07-10 TN 0.5988365011 #> 5917 2056C2 3M CC45 2014 2014-07-10 TSS 2.6602595373 #> 5918 2056C2 3M CC45 2014 2014-07-10 COND 10.2631181243 #> 5919 2056C2 3M CC45 2014 2014-07-10 DO 2.5136560631 #> 5920 2056C2 3M CC45 2014 2014-07-10 DOSAT 5.1935122522 + #> 5921 2056C2 3M CC45 2014 2014-07-10 SALIN 2.7219531063 #> 5922 2056C2 3M CC45 2014 2014-07-10 COND 10.5858012624 #> 5923 2056C2 3M CC45 2014 2014-07-10 DO 1.3584091576 #> 5924 2056C2 3M CC45 2014 2014-07-10 DOSAT 4.0893320204 + #> 5925 2056C2 3M CC45 2014 2014-07-10 SALIN 3.2284300377 #> 5926 2056C2 3M CC45 2014 2014-07-10 COND 10.5893079577 #> 5927 2056C2 3M CC45 2014 2014-07-10 DO 1.2383742310 #> 5928 2056C2 3M CC45 2014 2014-07-10 DOSAT 3.9702919136 + #> 5929 2056C2 3M CC45 2014 2014-07-10 SALIN 3.2327787300 #> 5930 2056C2 3M CC45 2014 2014-07-10 COND 10.5894086880 #> 5931 2056C2 3M CC45 2014 2014-07-10 DO 1.2178757095 #> 5932 2056C2 3M CC45 2014 2014-07-10 DOSAT 3.9493187902 + #> 5933 2056C2 3M CC45 2014 2014-07-10 SALIN 3.2335673736 #> 5934 2056C2 3M CC45 2014 2014-07-10 COND 10.5868621364 #> 5935 2056C2 3M CC45 2014 2014-07-10 DO 0.7654678421 #> 5936 2056C2 3M CC45 2014 2014-07-10 DOSAT 3.4965075615 + #> 5937 2056C2 3M CC45 2014 2014-07-10 SALIN 3.2331731296 #> 5938 2053 2 CC50 2018 2018-03-15 CHLAC 0.9932517730 #> 5939 2053 2 CC50 2018 2018-03-15 COND 10.6964800681 #> 5940 2053 2 CC50 2018 2018-03-15 DO 2.0918640617 #> 5941 2053 2 CC50 2018 2018-03-15 DOSAT 4.6249728133 #> 5942 2053 2 CC50 2018 2018-03-15 NO23 -5.5214609179 U #> 5943 2053 2 CC50 2018 2018-03-15 SALIN 3.5010427166 + #> 5944 2053 2 CC50 2018 2018-03-15 TKN -0.5108256238 #> 5945 2053 2 CC50 2018 2018-03-15 TN -0.5074978337 + #> 5946 2053 2 CC50 2018 2018-03-15 TP -1.8325814637 #> 5947 2053 2 CC50 2018 2018-03-15 TSS 1.7917594692 I #> 5948 2053 2 CC50 2018 2018-03-15 TURB 1.1631508098 A #> 5949 2053 2 CC50 2018 2018-03-29 CHLAC 1.9459101491 #> 5950 2053 2 CC50 2018 2018-03-29 COND 10.6310361598 #> 5951 2053 2 CC50 2018 2018-03-29 DO 1.8405496334 #> 5952 2053 2 CC50 2018 2018-03-29 DOSAT 4.4426512565 #> 5953 2053 2 CC50 2018 2018-03-29 NO23 -5.5214609179 U #> 5954 2053 2 CC50 2018 2018-03-29 SALIN 3.3382575819 + #> 5955 2053 2 CC50 2018 2018-03-29 TKN 0.4054651081 #> 5956 2053 2 CC50 2018 2018-03-29 TN 0.4067975533 + #> 5957 2053 2 CC50 2018 2018-03-29 TP -1.8325814637 #> 5958 2053 2 CC50 2018 2018-03-29 TSS 2.6390573296 #> 5959 2053 2 CC50 2018 2018-03-29 TURB 1.7047480922 #> 5960 2053 2 CC50 2018 2018-04-23 CHLAC 2.0794415417 #> 5961 2053 2 CC50 2018 2018-04-23 COND 10.6468524493 #> 5962 2053 2 CC50 2018 2018-04-23 DO 1.9459101491 #> 5963 2053 2 CC50 2018 2018-04-23 DOSAT 4.6249728133 #> 5964 2053 2 CC50 2018 2018-04-23 NO23 -5.5214609179 U #> 5965 2053 2 CC50 2018 2018-04-23 SALIN 3.2649957605 + #> 5966 2053 2 CC50 2018 2018-04-23 TKN -0.3710636814 #> 5967 2053 2 CC50 2018 2018-04-23 TN -0.3681693234 + #> 5968 2053 2 CC50 2018 2018-04-23 TP -1.5141277326 #> 5969 2053 2 CC50 2018 2018-04-23 TSS 3.3322045102 A #> 5970 2053 2 CC50 2018 2018-04-23 TURB 1.8718021769 #> 5971 2053 2 CC50 2018 2018-05-10 CHLAC 1.7917594692 #> 5972 2053 2 CC50 2018 2018-05-10 COND 10.6712318713 #> 5973 2053 2 CC50 2018 2018-05-10 DO 1.5040773968 #> 5974 2053 2 CC50 2018 2018-05-10 DOSAT 4.1588830834 #> 5975 2053 2 CC50 2018 2018-05-10 NO23 -5.2983173665 I #> 5976 2053 2 CC50 2018 2018-05-10 SALIN 3.3214324132 #> 5977 2053 2 CC50 2018 2018-05-10 TKN -0.1165338163 #> 5978 2053 2 CC50 2018 2018-05-10 TN -0.1120495038 + #> 5979 2053 2 CC50 2018 2018-05-10 TP -1.3862943611 #> 5980 2053 2 CC50 2018 2018-05-10 TSS 2.7080502011 #> 5981 2053 2 CC50 2018 2018-05-10 TURB 1.9021075264 #> 5982 2053 2 CC50 2018 2018-06-11 CHLAC 2.6390573296 #> 5983 2053 2 CC50 2018 2018-06-11 COND 9.5468126086 #> 5984 2053 2 CC50 2018 2018-06-11 DO 1.6094379124 #> 5985 2053 2 CC50 2018 2018-06-11 DOSAT 4.2341065046 #> 5986 2053 2 CC50 2018 2018-06-11 NO23 -2.7806208939 #> 5987 2053 2 CC50 2018 2018-06-11 SALIN 2.0918640617 #> 5988 2053 2 CC50 2018 2018-06-11 TKN 0.1823215568 #> 5989 2053 2 CC50 2018 2018-06-11 TN 0.2326977641 + #> 5990 2053 2 CC50 2018 2018-06-11 TP -0.7133498879 #> 5991 2053 2 CC50 2018 2018-06-11 TSS 1.3862943611 I #> 5992 2053 2 CC50 2018 2018-06-11 TURB 0.7419373447 #> 5993 2053 2 CC50 2018 2018-06-25 CHLAC 3.4011973817 #> 5994 2053 2 CC50 2018 2018-06-25 COND 10.0243768698 #> 5995 2053 2 CC50 2018 2018-06-25 DO 1.7209792872 #> 5996 2053 2 CC50 2018 2018-06-25 DOSAT 4.3719762988 #> 5997 2053 2 CC50 2018 2018-06-25 NO23 -2.9374633654 #> 5998 2053 2 CC50 2018 2018-06-25 SALIN 2.5055259370 + #> 5999 2053 2 CC50 2018 2018-06-25 TKN 0.0953101798 #> 6000 2053 2 CC50 2018 2018-06-25 TN 0.1423672413 + #> 6001 2053 2 CC50 2018 2018-06-25 TP -0.9162907319 #> 6002 2053 2 CC50 2018 2018-06-25 TSS 1.3862943611 I #> 6003 2053 2 CC50 2018 2018-06-25 TURB 0.9932517730 #> 6004 2053 2 CC50 2018 2018-08-07 CHLAC 2.8332133441 #> 6005 2053 2 CC50 2018 2018-08-07 COND 7.3382381501 #> 6006 2053 2 CC50 2018 2018-08-07 DO 1.7698546338 #> 6007 2053 2 CC50 2018 2018-08-07 DOSAT 4.3438054219 #> 6008 2053 2 CC50 2018 2018-08-07 NO23 -3.1235656451 #> 6009 2053 2 CC50 2018 2018-08-07 SALIN -0.2613647641 #> 6010 2053 2 CC50 2018 2018-08-07 TKN 0.0953101798 #> 6011 2053 2 CC50 2018 2018-08-07 TN 0.1345308930 + #> 6012 2053 2 CC50 2018 2018-08-07 TP -1.2378743560 #> 6013 2053 2 CC50 2018 2018-08-07 TSS 1.3862943611 I #> 6014 2053 2 CC50 2018 2018-08-07 TURB 0.9162907319 A #> 6015 2053 2 CC50 2018 2018-09-06 CHLAC 2.0014800002 #> 6016 2053 2 CC50 2018 2018-09-06 COND 8.6513743729 #> 6017 2053 2 CC50 2018 2018-09-06 DO 1.8341801851 #> 6018 2053 2 CC50 2018 2018-09-06 DOSAT 4.4236483094 #> 6019 2053 2 CC50 2018 2018-09-06 NO23 -2.5383074265 #> 6020 2053 2 CC50 2018 2018-09-06 SALIN 1.1281710909 #> 6021 2053 2 CC50 2018 2018-09-06 TKN 0.1823215568 #> 6022 2053 2 CC50 2018 2018-09-06 TN 0.2460785226 + #> 6023 2053 2 CC50 2018 2018-09-06 TP -1.2378743560 #> 6024 2053 2 CC50 2018 2018-09-06 TSS 1.3862943611 I #> 6025 2053 2 CC50 2018 2018-09-06 TURB 0.6931471806 #> 6026 2053 2 CC50 2018 2018-09-20 CHLAC 2.5649493575 #> 6027 2053 2 CC50 2018 2018-09-20 COND 9.3369730229 #> 6028 2053 2 CC50 2018 2018-09-20 DO 1.6582280766 #> 6029 2053 2 CC50 2018 2018-09-20 DOSAT 4.1682144108 #> 6030 2053 2 CC50 2018 2018-09-20 NO23 -4.1351665567 #> 6031 2053 2 CC50 2018 2018-09-20 SALIN 1.8562979904 #> 6032 2053 2 CC50 2018 2018-09-20 TKN -0.0725706928 #> 6033 2053 2 CC50 2018 2018-09-20 TN -0.0555127099 + #> 6034 2053 2 CC50 2018 2018-09-20 TP -1.1394342832 #> 6035 2053 2 CC50 2018 2018-09-20 TSS 1.3862943611 I #> 6036 2053 2 CC50 2018 2018-09-20 TURB 0.4700036292 #> 6037 2053 2 CC50 2018 2018-10-24 CHLAC 1.9600947840 #> 6038 2053 2 CC50 2018 2018-10-24 COND 10.0400269167 #> 6039 2053 2 CC50 2018 2018-10-24 DO 1.9430489168 #> 6040 2053 2 CC50 2018 2018-10-24 DOSAT 4.5496574761 #> 6041 2053 2 CC50 2018 2018-10-24 NO23 -2.7488721956 #> 6042 2053 2 CC50 2018 2018-10-24 SALIN 2.6246685922 #> 6043 2053 2 CC50 2018 2018-10-24 TKN -0.3011050928 #> 6044 2053 2 CC50 2018 2018-10-24 TN -0.2181560098 + #> 6045 2053 2 CC50 2018 2018-10-24 TP -1.4271163556 #> 6046 2053 2 CC50 2018 2018-10-24 TSS 1.6094379124 I #> 6047 2053 2 CC50 2018 2018-10-24 TURB 0.9162907319 #> 6048 2053 2 CC50 2019 2019-04-17 CHLAC 1.5892352051 I #> 6049 2053 2 CC50 2019 2019-04-17 COND 10.3074515345 #> 6050 2053 2 CC50 2019 2019-04-17 DO 1.9878743482 #> 6051 2053 2 CC50 2019 2019-04-17 DOSAT 4.5981455711 #> 6052 2053 2 CC50 2019 2019-04-17 NO23 -5.5214609179 U #> 6053 2053 2 CC50 2019 2019-04-17 SALIN 2.9193910403 #> 6054 2053 2 CC50 2019 2019-04-17 TKN -0.4462871026 #> 6055 2053 2 CC50 2019 2019-04-17 TN -0.4431669753 + #> 6056 2053 2 CC50 2019 2019-04-17 TP -1.6607312068 #> 6057 2053 2 CC50 2019 2019-04-17 TSS 2.9444389792 A #> 6058 2053 2 CC50 2019 2019-04-17 TURB 1.0296194172 #> 6059 2053 2 CC50 2019 2019-07-15 CHLAC 3.0910424534 #> 6060 2053 2 CC50 2019 2019-07-15 COND 10.0506999322 #> 6061 2053 2 CC50 2019 2019-07-15 DO 1.9430489168 #> 6062 2053 2 CC50 2019 2019-07-15 DOSAT 4.5971380143 #> 6063 2053 2 CC50 2019 2019-07-15 NO23 -5.5214609179 U #> 6064 2053 2 CC50 2019 2019-07-15 SALIN 2.6333266549 #> 6065 2053 2 CC50 2019 2019-07-15 TKN -0.2107210313 #> 6066 2053 2 CC50 2019 2019-07-15 TN -0.2082549388 + #> 6067 2053 2 CC50 2019 2019-07-15 TP -1.4696759701 #> 6068 2053 2 CC50 2019 2019-07-15 TSS 2.0794415417 I #> 6069 2053 2 CC50 2019 2019-07-15 TURB 0.9932517730 #> 6070 2053 2 CC50 2019 2019-08-19 CHLAC 1.4816045409 #> 6071 2053 2 CC50 2019 2019-08-19 COND 7.3530819205 #> 6072 2053 2 CC50 2019 2019-08-19 DO 1.5665304114 #> 6073 2053 2 CC50 2019 2019-08-19 DOSAT 4.1367652781 #> 6074 2053 2 CC50 2019 2019-08-19 NO23 -2.6036901858 #> 6075 2053 2 CC50 2019 2019-08-19 SALIN -0.2484613593 #> 6076 2053 2 CC50 2019 2019-08-19 TKN 0.3364722366 #> 6077 2053 2 CC50 2019 2019-08-19 TN 0.3879797938 + #> 6078 2053 2 CC50 2019 2019-08-19 TP -0.8209805521 #> 6079 2053 2 CC50 2019 2019-08-19 TSS 1.0986122887 I #> 6080 2053 2 CC50 2019 2019-08-19 TURB 0.7884573604 #> 6081 2053 2 CC50 2019 2019-09-11 CHLAC 3.0910424534 #> 6082 2053 2 CC50 2019 2019-09-11 COND 9.8378817954 #> 6083 2053 2 CC50 2019 2019-09-11 DO 1.9139771020 #> 6084 2053 2 CC50 2019 2019-09-11 DOSAT 4.5475410732 #> 6085 2053 2 CC50 2019 2019-09-11 NO23 -4.0173835211 #> 6086 2053 2 CC50 2019 2019-09-11 SALIN 2.4015250408 #> 6087 2053 2 CC50 2019 2019-09-11 TKN -0.0725706928 #> 6088 2053 2 CC50 2019 2019-09-11 TN -0.0534007767 + #> 6089 2053 2 CC50 2019 2019-09-11 TP -1.2039728043 #> 6090 2053 2 CC50 2019 2019-09-11 TSS 1.6094379124 I #> 6091 2053 2 CC50 2019 2019-09-11 TURB 0.7884573604 #> 6092 2053 2 CC50 2019 2019-10-09 CHLAC 1.1939224685 #> 6093 2053 2 CC50 2019 2019-10-09 COND 10.2652793829 #> 6094 2053 2 CC50 2019 2019-10-09 DO 1.7065646232 #> 6095 2053 2 CC50 2019 2019-10-09 DOSAT 4.3554259529 #> 6096 2053 2 CC50 2019 2019-10-09 NO23 -5.5214609179 I #> 6097 2053 2 CC50 2019 2019-10-09 SALIN 2.8713021952 #> 6098 2053 2 CC50 2019 2019-10-09 TKN -0.4155154440 #> 6099 2053 2 CC50 2019 2019-10-09 TN -0.4094731295 + #> 6100 2053 2 CC50 2019 2019-10-09 TP -1.5141277326 #> 6101 2053 2 CC50 2019 2019-10-09 TSS 1.0986122887 U #> 6102 2053 2 CC50 2019 2019-10-09 TURB -0.1625189295 #> 6103 2053 2 CC50 2020 2020-02-13 CHLAC 1.5475625087 #> 6104 2053 2 CC50 2020 2020-02-13 COND 10.4652439050 #> 6105 2053 2 CC50 2020 2020-02-13 DO 1.8017098001 #> 6106 2053 2 CC50 2020 2020-02-13 DOSAT 4.4067192473 #> 6107 2053 2 CC50 2020 2020-02-13 NO23 -5.5214609179 U #> 6108 2053 2 CC50 2020 2020-02-13 SALIN 3.0946722214 #> 6109 2053 2 CC50 2020 2020-02-13 TKN -0.4620354596 #> 6110 2053 2 CC50 2020 2020-02-13 TN -0.4588658848 + #> 6111 2053 2 CC50 2020 2020-02-13 TP -1.8325814637 #> 6112 2053 2 CC50 2020 2020-02-13 TSS 2.7080502011 #> 6113 2053 2 CC50 2020 2020-02-13 TURB 2.0014800002 A #> 6114 2053 2 CC50 2020 2020-03-24 CHLAC 1.3350010667 #> 6115 2053 2 CC50 2020 2020-03-24 COND 10.5688523521 #> 6116 2053 2 CC50 2020 2020-03-24 DO 1.9401794743 #> 6117 2053 2 CC50 2020 2020-03-24 DOSAT 4.6434288981 #> 6118 2053 2 CC50 2020 2020-03-24 NO23 -5.5214609179 U #> 6119 2053 2 CC50 2020 2020-03-24 SALIN 3.2047769005 #> 6120 2053 2 CC50 2020 2020-03-24 TKN -0.4462871026 #> 6121 2053 2 CC50 2020 2020-03-24 TN -0.4431669753 + #> 6122 2053 2 CC50 2020 2020-03-24 TP -1.8325814637 #> 6123 2053 2 CC50 2020 2020-03-24 TSS 2.7725887222 #> 6124 2053 2 CC50 2020 2020-03-24 TURB 1.5260563035 #> 6125 2053 2 CC50 2020 2020-06-22 CHLAC 3.1780538303 #> 6126 2053 2 CC50 2020 2020-06-22 COND 9.9972510823 #> 6127 2053 2 CC50 2020 2020-06-22 DO 1.7173950539 #> 6128 2053 2 CC50 2020 2020-06-22 DOSAT 4.3795235045 #> 6129 2053 2 CC50 2020 2020-06-22 NO23 -4.5098600062 #> 6130 2053 2 CC50 2020 2020-06-22 SALIN 2.5718485799 #> 6131 2053 2 CC50 2020 2020-06-22 TKN -0.0100503359 #> 6132 2053 2 CC50 2020 2020-06-22 TN 0.0009995003 + #> 6133 2053 2 CC50 2020 2020-06-22 TP -1.2039728043 #> 6134 2053 2 CC50 2020 2020-06-22 TSS 1.7917594692 I #> 6135 2053 2 CC50 2020 2020-06-22 TURB 0.7884573604 A #> 6136 2053 2 CC50 2020 2020-07-27 CHLAC 1.7578579176 #> 6137 2053 2 CC50 2020 2020-07-27 COND 10.1123293191 #> 6138 2053 2 CC50 2020 2020-07-27 DO 1.5644405465 #> 6139 2053 2 CC50 2020 2020-07-27 DOSAT 4.2239097666 #> 6140 2053 2 CC50 2020 2020-07-27 NO23 -4.1351665567 #> 6141 2053 2 CC50 2020 2020-07-27 SALIN 2.7006898467 #> 6142 2053 2 CC50 2020 2020-07-27 TN -0.3481400415 + #> 6143 2053 2 CC50 2020 2020-07-27 TP -1.3093333200 #> 6144 2053 2 CC50 2020 2020-07-27 TSS 1.0986122887 U #> 6145 2053 2 CC50 2020 2020-07-27 TURB 0.5306282511 #> 6146 2053 2 CC50 2020 2020-08-26 CHLAC 2.2300144002 #> 6147 2053 2 CC50 2020 2020-08-26 COND 9.8854254097 #> 6148 2053 2 CC50 2020 2020-08-26 DO 1.7850704811 #> 6149 2053 2 CC50 2020 2020-08-26 DOSAT 4.4188406078 #> 6150 2053 2 CC50 2020 2020-08-26 NO23 -5.5214609179 U #> 6151 2053 2 CC50 2020 2020-08-26 SALIN 2.4535879665 #> 6152 2053 2 CC50 2020 2020-08-26 TKN -0.1984509387 #> 6153 2053 2 CC50 2020 2020-08-26 TN -0.1960148839 + #> 6154 2053 2 CC50 2020 2020-08-26 TP -1.3862943611 #> 6155 2053 2 CC50 2020 2020-08-26 TSS 1.0986122887 U #> 6156 2053 2 CC50 2020 2020-08-26 TURB 0.0953101798 #> 6157 2053 2 CC50 2021 2021-01-14 CHLAC 1.6094379124 A #> 6158 2053 2 CC50 2021 2021-01-14 COND 10.2228136303 #> 6159 2053 2 CC50 2021 2021-01-14 DO 2.0967901800 #> 6160 2053 2 CC50 2021 2021-01-14 DOSAT 4.5580785785 #> 6161 2053 2 CC50 2021 2021-01-14 NO23 -5.5214609179 I #> 6162 2053 2 CC50 2021 2021-01-14 SALIN 2.8314470792 #> 6163 2053 2 CC50 2021 2021-01-14 TKN -0.2876820725 #> 6164 2053 2 CC50 2021 2021-01-14 TN -0.2823629110 + #> 6165 2053 2 CC50 2021 2021-01-14 TP -1.7147984281 #> 6166 2053 2 CC50 2021 2021-01-14 TSS 2.5649493575 A #> 6167 2053 2 CC50 2021 2021-01-14 TURB 1.4586150227 #> 6168 2053 2 CC50 2021 2021-02-24 COND 10.2486009183 #> 6169 2053 2 CC50 2021 2021-02-24 DO 2.0955609236 #> 6170 2053 2 CC50 2021 2021-02-24 DOSAT 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6189 2053 2 CC50 2021 2021-07-28 COND 9.4095190458 #> 6190 2053 2 CC50 2021 2021-07-28 DO 0.9516578757 #> 6191 2053 2 CC50 2021 2021-07-28 DOSAT 3.5638829639 #> 6192 2053 2 CC50 2021 2021-07-28 NO23 -3.1700856607 #> 6193 2053 2 CC50 2021 2021-07-28 SALIN 1.9373017745 #> 6194 2053 2 CC50 2021 2021-07-28 TKN 0.1823215568 #> 6195 2053 2 CC50 2021 2021-07-28 TN 0.2167229835 + #> 6196 2053 2 CC50 2021 2021-07-28 TP -0.7550225843 #> 6197 2053 2 CC50 2021 2021-07-28 TSS 1.3862943611 I #> 6198 2053 2 CC50 2021 2021-07-28 TURB 1.7404661748 #> 6199 2053 2 CC50 2021 2021-08-26 CHLAC 1.5260563035 #> 6200 2053 2 CC50 2021 2021-08-26 COND 9.2069345788 #> 6201 2053 2 CC50 2021 2021-08-26 DO 1.0296194172 #> 6202 2053 2 CC50 2021 2021-08-26 DOSAT 3.6270040504 #> 6203 2053 2 CC50 2021 2021-08-26 NO23 -2.7488721956 #> 6204 2053 2 CC50 2021 2021-08-26 SALIN 1.7191887764 #> 6205 2053 2 CC50 2021 2021-08-26 TKN -0.3285040670 #> 6206 2053 2 CC50 2021 2021-08-26 TN -0.2433462586 + #> 6207 2053 2 CC50 2021 2021-08-26 TP -1.0216512475 #> 6208 2053 2 CC50 2021 2021-08-26 TSS 1.0986122887 I #> 6209 2053 2 CC50 2021 2021-08-26 TURB 0.9555114450 #> 6210 2053 2 CC50 2021 2021-09-13 CHLAC 1.7578579176 #> 6211 2053 2 CC50 2021 2021-09-13 COND 9.5941731800 #> 6212 2053 2 CC50 2021 2021-09-13 DO 1.4422019931 #> 6213 2053 2 CC50 2021 2021-09-13 DOSAT 4.0707346966 #> 6214 2053 2 CC50 2021 2021-09-13 NO23 -2.7806208939 #> 6215 2053 2 CC50 2021 2021-09-13 SALIN 2.1365305087 #> 6216 2053 2 CC50 2021 2021-09-13 TKN -0.0618754037 #> 6217 2053 2 CC50 2021 2021-09-13 TN 0.0019980027 + #> 6218 2053 2 CC50 2021 2021-09-13 TP -1.2039728043 #> 6219 2053 2 CC50 2021 2021-09-13 TSS 1.0986122887 I #> 6220 2053 2 CC50 2021 2021-09-13 TURB 0.5877866649 #> 6221 2053 2 CC50 2022 2022-03-16 COND 10.6209126256 #> 6222 2053 2 CC50 2022 2022-03-16 DO 1.9080599249 #> 6223 2053 2 CC50 2022 2022-03-16 DOSAT 4.5152454785 #> 6224 2053 2 CC50 2022 2022-03-16 SALIN 3.2676659890 #> 6225 2053 2 CC50 2022 2022-05-04 COND 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#> 6244 2054 3F CC53 2014 2014-01-06 TN -0.0714960017 + #> 6245 2054 3F CC53 2014 2014-01-06 TP -2.9565115604 #> 6246 2054 3F CC53 2014 2014-01-06 TURB 1.1939224685 A #> 6247 2054 3F CC53 2014 2014-02-03 CHLAC 2.5649493575 #> 6248 2054 3F CC53 2014 2014-02-03 COLOR 4.0073331852 #> 6249 2054 3F CC53 2014 2014-02-03 DO 2.0014800002 #> 6250 2054 3F CC53 2014 2014-02-03 DOSAT 4.3956829611 + #> 6251 2054 3F CC53 2014 2014-02-03 NO23 -2.1202635362 #> 6252 2054 3F CC53 2014 2014-02-03 SALIN -0.3566749439 #> 6253 2054 3F CC53 2014 2014-02-03 TKN 0.0953101798 #> 6254 2054 3F CC53 2014 2014-02-03 TN 0.1988508587 + #> 6255 2054 3F CC53 2014 2014-02-03 TP -1.9661128564 #> 6256 2054 3F CC53 2014 2014-02-03 TURB 1.3350010667 #> 6257 2054 3F CC53 2014 2014-03-03 CHLAC 2.4849066498 #> 6258 2054 3F CC53 2014 2014-03-03 COLOR 4.1271343850 #> 6259 2054 3F CC53 2014 2014-03-03 DO 1.8082887712 #> 6260 2054 3F CC53 2014 2014-03-03 DOSAT 4.2398868675 + #> 6261 2054 3F CC53 2014 2014-03-03 NO23 -5.5214609179 U #> 6262 2054 3F CC53 2014 2014-03-03 SALIN 0.8754687374 #> 6263 2054 3F CC53 2014 2014-03-03 TKN 0.0953101798 #> 6264 2054 3F CC53 2014 2014-03-03 TN 0.0971267107 + #> 6265 2054 3F CC53 2014 2014-03-03 TP -2.0402208285 #> 6266 2054 3F CC53 2014 2014-03-03 TURB 1.7227665977 #> 6267 2054 3F CC53 2014 2014-04-07 CHLAC 2.3978952728 #> 6268 2054 3F CC53 2014 2014-04-07 COLOR 4.0253516907 #> 6269 2054 3F CC53 2014 2014-04-07 DO 1.6292405397 #> 6270 2054 3F CC53 2014 2014-04-07 DOSAT 4.0960098415 + #> 6271 2054 3F CC53 2014 2014-04-07 NO23 -4.3428059215 #> 6272 2054 3F CC53 2014 2014-04-07 TKN -0.0943106795 #> 6273 2054 3F CC53 2014 2014-04-07 TN -0.0801260445 + #> 6274 2054 3F CC53 2014 2014-04-07 TP -2.1202635362 #> 6275 2054 3F CC53 2014 2014-04-07 TURB 1.1939224685 #> 6276 2054 3F CC53 2014 2014-05-05 CHLAC 2.4849066498 #> 6277 2054 3F CC53 2014 2014-05-05 COLOR 4.0073331852 #> 6278 2054 3F CC53 2014 2014-05-05 DO 1.9459101491 #> 6279 2054 3F CC53 2014 2014-05-05 DOSAT 4.4006030202 + #> 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-2.9187712324 #> 6388 2054 3F CC53 2015 2015-05-04 TKN 0.1823215568 #> 6389 2054 3F CC53 2015 2015-05-04 TN 0.2263384422 + #> 6390 2054 3F CC53 2015 2015-05-04 TP -2.3968957725 #> 6391 2054 3F CC53 2015 2015-05-04 TURB 1.2809338455 #> 6392 2054 3F CC53 2015 2015-06-01 CHLAC 2.3025850930 #> 6393 2054 3F CC53 2015 2015-06-01 COLOR 4.2766661190 #> 6394 2054 3F CC53 2015 2015-06-01 DO 1.3711807233 #> 6395 2054 3F CC53 2015 2015-06-01 DOSAT 3.9259259106 + #> 6396 2054 3F CC53 2015 2015-06-01 NO23 -4.6051701860 #> 6397 2054 3F CC53 2015 2015-06-01 SALIN 1.2059708070 #> 6398 2054 3F CC53 2015 2015-06-01 TKN -0.0100503359 #> 6399 2054 3F CC53 2015 2015-06-01 TN 0.0000000000 + #> 6400 2054 3F CC53 2015 2015-06-01 TP -1.5141277326 #> 6401 2054 3F CC53 2015 2015-06-01 TURB 0.7419373447 #> 6402 2054 3F CC53 2015 2015-08-03 CHLAC 0.5877866649 #> 6403 2054 3F CC53 2015 2015-08-03 COLOR 4.9416424226 #> 6404 2054 3F CC53 2015 2015-08-03 DO 1.3428648032 #> 6405 2054 3F CC53 2015 2015-08-03 DOSAT 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2016-02-01 TP -2.6592600369 #> 6460 2054 3F CC53 2016 2016-02-01 TURB 0.5877866649 A #> 6461 2054 3F CC53 2016 2016-03-07 CHLAC 0.4054651081 I #> 6462 2054 3F CC53 2016 2016-03-07 COLOR 4.3174881135 #> 6463 2054 3F CC53 2016 2016-03-07 DO 1.6074359098 #> 6464 2054 3F CC53 2016 2016-03-07 DOSAT 4.0127729085 + #> 6465 2054 3F CC53 2016 2016-03-07 NO23 -3.6119184130 #> 6466 2054 3F CC53 2016 2016-03-07 SALIN -2.3025850930 #> 6467 2054 3F CC53 2016 2016-03-07 TKN -0.3147107448 #> 6468 2054 3F CC53 2016 2016-03-07 TN -0.2783920255 + #> 6469 2054 3F CC53 2016 2016-03-07 TP -2.9004220937 #> 6470 2054 3F CC53 2016 2016-03-07 TURB 0.5306282511 A #> 6471 2054 3F CC53 2016 2016-04-04 CHLAC 2.0149030205 #> 6472 2054 3F CC53 2016 2016-04-04 COLOR 4.0604430105 #> 6473 2054 3F CC53 2016 2016-04-04 DO 1.5454325825 #> 6474 2054 3F CC53 2016 2016-04-04 DOSAT 4.0253516907 + #> 6475 2054 3F CC53 2016 2016-04-04 NO23 -3.7722610631 #> 6476 2054 3F CC53 2016 2016-04-04 SALIN -1.3093333200 #> 6477 2054 3F 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CC53 2017 2017-01-03 CHLAC 2.1633230257 #> 6550 2054 3F CC53 2017 2017-01-03 COLOR 3.7841896339 A #> 6551 2054 3F CC53 2017 2017-01-03 DO 1.5892352051 #> 6552 2054 3F CC53 2017 2017-01-03 DOSAT 4.0638853547 + #> 6553 2054 3F CC53 2017 2017-01-03 NO23 -5.1159958098 I #> 6554 2054 3F CC53 2017 2017-01-03 SALIN 1.8405496334 #> 6555 2054 3F CC53 2017 2017-01-03 TKN -0.3710636814 #> 6556 2054 3F CC53 2017 2017-01-03 TN -0.3652833185 + #> 6557 2054 3F CC53 2017 2017-01-03 TP -1.9661128564 #> 6558 2054 3F CC53 2017 2017-01-03 TURB 0.9555114450 #> 6559 2054 3F CC53 2017 2017-02-06 CHLAC 1.7047480922 #> 6560 2054 3F CC53 2017 2017-02-06 COLOR 3.6635616461 #> 6561 2054 3F CC53 2017 2017-02-06 DO 1.3609765531 #> 6562 2054 3F CC53 2017 2017-02-06 DOSAT 3.7819143201 + #> 6563 2054 3F CC53 2017 2017-02-06 NO23 -2.6310891600 #> 6564 2054 3F CC53 2017 2017-02-06 SALIN 1.2527629685 #> 6565 2054 3F CC53 2017 2017-02-06 TKN -0.2876820725 #> 6566 2054 3F CC53 2017 2017-02-06 TN -0.1960148839 + #> 6567 2054 3F CC53 2017 2017-02-06 TP -2.1202635362 #> 6568 2054 3F CC53 2017 2017-02-06 TURB 1.1939224685 A #> 6569 2054 3F CC53 2017 2017-03-06 CHLAC 1.0986122887 #> 6570 2054 3F CC53 2017 2017-03-06 COLOR 3.7135720667 #> 6571 2054 3F CC53 2017 2017-03-06 DO 1.5789787049 #> 6572 2054 3F CC53 2017 2017-03-06 DOSAT 4.0145795938 + #> 6573 2054 3F CC53 2017 2017-03-06 NO23 -2.5770219387 #> 6574 2054 3F CC53 2017 2017-03-06 SALIN 1.4445632692 #> 6575 2054 3F CC53 2017 2017-03-06 TKN -0.3856624808 #> 6576 2054 3F CC53 2017 2017-03-06 TN -0.2797139028 + #> 6577 2054 3F CC53 2017 2017-03-06 TP -1.6094379124 #> 6578 2054 3F CC53 2017 2017-03-06 TURB 0.9932517730 #> 6579 2054 3F CC53 2017 2017-04-03 CHLAC 2.0149030205 #> 6580 2054 3F CC53 2017 2017-04-03 COLOR 3.8286413965 #> 6581 2054 3F CC53 2017 2017-04-03 DO 1.0612565021 #> 6582 2054 3F CC53 2017 2017-04-03 DOSAT 3.6163087613 + #> 6583 2054 3F CC53 2017 2017-04-03 NO23 -3.4112477175 #> 6584 2054 3F CC53 2017 2017-04-03 SALIN 2.1610215287 #> 6585 2054 3F CC53 2017 2017-04-03 TKN -0.0725706928 #> 6586 2054 3F CC53 2017 2017-04-03 TN -0.0377018672 + #> 6587 2054 3F CC53 2017 2017-04-03 TP -1.4271163556 #> 6588 2054 3F CC53 2017 2017-04-03 TURB 1.0296194172 A #> 6589 2054 3F CC53 2017 2017-05-01 CHLAC 2.2512917986 #> 6590 2054 3F CC53 2017 2017-05-01 COLOR 4.0253516907 A #> 6591 2054 3F CC53 2017 2017-05-01 DO 1.1817271954 #> 6592 2054 3F CC53 2017 2017-05-01 DOSAT 3.7796338174 + #> 6593 2054 3F CC53 2017 2017-05-01 NO23 -4.7105307016 I #> 6594 2054 3F CC53 2017 2017-05-01 SALIN 2.6049094422 #> 6595 2054 3F CC53 2017 2017-05-01 TKN 0.5306282511 #> 6596 2054 3F CC53 2017 2017-05-01 TN 0.5329784284 + #> 6597 2054 3F CC53 2017 2017-05-01 TP -1.5141277326 #> 6598 2054 3F CC53 2017 2017-05-01 TURB 0.7884573604 #> 6599 2054 3F CC53 2017 2017-06-05 COLOR 4.0430512678 A #> 6600 2054 3F CC53 2017 2017-06-05 NO23 -4.0173835211 #> 6601 2054 3F CC53 2017 2017-06-05 TKN 0.0000000000 #> 6602 2054 3F CC53 2017 2017-06-05 TN 0.0178399181 + #> 6603 2054 3F CC53 2017 2017-06-05 TP -1.2378743560 #> 6604 2054 3F CC53 2017 2017-07-10 CHLAC 1.0986122887 #> 6605 2054 3F CC53 2017 2017-07-10 COLOR 5.2983173665 #> 6606 2054 3F CC53 2017 2017-07-10 DO 0.8020015855 #> 6607 2054 3F CC53 2017 2017-07-10 DOSAT 3.3707381742 + #> 6608 2054 3F CC53 2017 2017-07-10 NO23 -1.9661128564 #> 6609 2054 3F CC53 2017 2017-07-10 SALIN -1.2378743560 #> 6610 2054 3F CC53 2017 2017-07-10 TKN 0.3364722366 #> 6611 2054 3F CC53 2017 2017-07-10 TN 0.4317824164 + #> 6612 2054 3F CC53 2017 2017-07-10 TP -1.4696759701 #> 6613 2054 3F CC53 2017 2017-07-10 TURB 1.1939224685 #> 6614 2054 3F CC53 2017 2017-11-06 CHLAC 1.8870696490 #> 6615 2054 3F CC53 2017 2017-11-06 COLOR 4.9416424226 #> 6616 2054 3F CC53 2017 2017-11-06 DO 1.5973653312 #> 6617 2054 3F CC53 2017 2017-11-06 DOSAT 4.0621656639 #> 6618 2054 3F CC53 2017 2017-11-06 NO23 -1.3470736480 #> 6619 2054 3F CC53 2017 2017-11-06 SALIN -1.4696759701 #> 6620 2054 3F CC53 2017 2017-11-06 TKN 0.0953101798 #> 6621 2054 3F CC53 2017 2017-11-06 TN 0.3074846997 + #> 6622 2054 3F CC53 2017 2017-11-06 TP -2.0402208285 #> 6623 2054 3F CC53 2017 2017-11-06 TURB 1.3609765531 #> 6624 2054 3F CC53 2017 2017-12-04 CHLAC 2.7080502011 #> 6625 2054 3F CC53 2017 2017-12-04 COLOR 4.2341065046 #> 6626 2054 3F CC53 2017 2017-12-04 DO 1.7422190237 #> 6627 2054 3F CC53 2017 2017-12-04 DOSAT 4.1759245492 #> 6628 2054 3F CC53 2017 2017-12-04 NO23 -1.6094379124 #> 6629 2054 3F CC53 2017 2017-12-04 SALIN -0.7133498879 #> 6630 2054 3F CC53 2017 2017-12-04 TKN -0.0202027073 #> 6631 2054 3F CC53 2017 2017-12-04 TN 0.1655144385 + #> 6632 2054 3F CC53 2017 2017-12-04 TP -2.0402208285 #> 6633 2054 3F CC53 2017 2017-12-04 TURB 1.2809338455 A #> 6634 2054 3F CC53 2018 2018-01-02 CHLAC 3.2188758249 #> 6635 2054 3F CC53 2018 2018-01-02 COLOR 4.0253516907 #> 6636 2054 3F CC53 2018 2018-01-02 DO 1.7298840655 #> 6637 2054 3F CC53 2018 2018-01-02 DOSAT 4.0758410907 + #> 6638 2054 3F CC53 2018 2018-01-02 NO23 -2.0402208285 #> 6639 2054 3F CC53 2018 2018-01-02 SALIN -0.8915981193 #> 6640 2054 3F CC53 2018 2018-01-02 TKN 0.0000000000 #> 6641 2054 3F CC53 2018 2018-01-02 TN 0.1222176327 + #> 6642 2054 3F CC53 2018 2018-01-02 TP -1.9661128564 #> 6643 2054 3F CC53 2018 2018-01-02 TURB 1.8245492921 #> 6644 2054 3F CC53 2018 2018-02-05 CHLAC 3.5263605246 #> 6645 2054 3F CC53 2018 2018-02-05 COLOR 4.2484952420 #> 6646 2054 3F CC53 2018 2018-02-05 DO 1.9712993831 #> 6647 2054 3F CC53 2018 2018-02-05 DOSAT 4.3681812279 #> 6648 2054 3F CC53 2018 2018-02-05 NO23 -0.9416085399 #> 6649 2054 3F CC53 2018 2018-02-05 SALIN -0.9416085399 #> 6650 2054 3F CC53 2018 2018-02-05 TKN 0.1823215568 #> 6651 2054 3F CC53 2018 2018-02-05 TN 0.4637340162 + #> 6652 2054 3F CC53 2018 2018-02-05 TP -1.7719568419 #> 6653 2054 3F CC53 2018 2018-02-05 TURB 1.8870696490 #> 6654 2054 3F CC53 2018 2018-05-07 CHLAC 2.6390573296 #> 6655 2054 3F CC53 2018 2018-05-07 COLOR 3.9318256327 #> 6656 2054 3F CC53 2018 2018-05-07 DO 1.3217558400 #> 6657 2054 3F CC53 2018 2018-05-07 DOSAT 3.8877303129 #> 6658 2054 3F CC53 2018 2018-05-07 NO23 -5.1159958098 I #> 6659 2054 3F CC53 2018 2018-05-07 SALIN 1.9974177062 #> 6660 2054 3F CC53 2018 2018-05-07 TKN -0.0100503359 #> 6661 2054 3F CC53 2018 2018-05-07 TN -0.0060180723 + #> 6662 2054 3F CC53 2018 2018-05-07 TP -1.3862943611 #> 6663 2054 3F CC53 2018 2018-05-07 TURB 1.1939224685 #> 6664 2054 3F CC53 2018 2018-07-09 CHLAC 0.9162907319 #> 6665 2054 3F CC53 2018 2018-07-09 COLOR 5.0106352941 #> 6666 2054 3F CC53 2018 2018-07-09 DO 1.3532545070 #> 6667 2054 3F CC53 2018 2018-07-09 DOSAT 3.9435216725 #> 6668 2054 3F CC53 2018 2018-07-09 NO23 -4.3428059215 #> 6669 2054 3F CC53 2018 2018-07-09 SALIN -3.2188758249 #> 6670 2054 3F CC53 2018 2018-07-09 TKN 0.0953101798 #> 6671 2054 3F CC53 2018 2018-07-09 TN 0.1070590723 + #> 6672 2054 3F CC53 2018 2018-07-09 TP -2.5510464523 #> 6673 2054 3F CC53 2018 2018-07-09 TURB 0.9555114450 #> 6674 2054 3F CC53 2019 2019-02-04 CHLAC 1.2527629685 #> 6675 2054 3F 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2019 2019-03-04 TURB 2.0918640617 #> 6694 2054 3F CC53 2019 2019-04-01 CHLAC 2.0794415417 #> 6695 2054 3F CC53 2019 2019-04-01 COLOR 4.1896547420 #> 6696 2054 3F CC53 2019 2019-04-01 DO 1.6074359098 #> 6697 2054 3F CC53 2019 2019-04-01 DOSAT 4.0775374439 #> 6698 2054 3F CC53 2019 2019-04-01 NO23 -4.8283137373 I #> 6699 2054 3F CC53 2019 2019-04-01 SALIN -0.9675840263 #> 6700 2054 3F CC53 2019 2019-04-01 TKN 0.0000000000 #> 6701 2054 3F CC53 2019 2019-04-01 TN 0.0039920213 + #> 6702 2054 3F CC53 2019 2019-04-01 TP -2.3434070875 #> 6703 2054 3F CC53 2019 2019-04-01 TURB 1.0986122887 #> 6704 2054 3F CC53 2019 2019-05-06 CHLAC 2.1400661635 #> 6705 2054 3F CC53 2019 2019-05-06 COLOR 4.2046926194 A #> 6706 2054 3F CC53 2019 2019-05-06 DO 1.4182774070 #> 6707 2054 3F CC53 2019 2019-05-06 DOSAT 3.9608131696 #> 6708 2054 3F CC53 2019 2019-05-06 NO23 -4.8283137373 I #> 6709 2054 3F CC53 2019 2019-05-06 SALIN 0.7371640660 #> 6710 2054 3F CC53 2019 2019-05-06 TKN 0.0953101798 #> 6711 2054 3F CC53 2019 2019-05-06 TN 0.0989399479 + #> 6712 2054 3F CC53 2019 2019-05-06 TP -1.8325814637 #> 6713 2054 3F CC53 2019 2019-05-06 TURB 1.0647107370 #> 6714 2054 3F CC53 2019 2019-08-05 CHLAC 0.4700036292 I #> 6715 2054 3F CC53 2019 2019-08-05 COLOR 5.3936275464 #> 6716 2054 3F CC53 2019 2019-08-05 DO 1.2383742310 #> 6717 2054 3F CC53 2019 2019-08-05 DOSAT 3.7750571504 #> 6718 2054 3F CC53 2019 2019-08-05 NO23 -2.3859667019 #> 6719 2054 3F CC53 2019 2019-08-05 SALIN -1.7719568419 #> 6720 2054 3F CC53 2019 2019-08-05 TKN 0.4700036292 #> 6721 2054 3F CC53 2019 2019-08-05 TN 0.5259112612 + #> 6722 2054 3F CC53 2019 2019-08-05 TP -1.3862943611 #> 6723 2054 3F CC53 2019 2019-08-05 TURB 0.9162907319 #> 6724 2054 3F CC53 2020 2020-01-06 CHLAC 1.8405496334 #> 6725 2054 3F CC53 2020 2020-01-06 COLOR 3.8712010109 A #> 6726 2054 3F CC53 2020 2020-01-06 DO 1.7439688054 #> 6727 2054 3F CC53 2020 2020-01-06 DOSAT 4.1255201797 #> 6728 2054 3F CC53 2020 2020-01-06 NO23 -2.8824035882 #> 6729 2054 3F CC53 2020 2020-01-06 SALIN -0.5276327421 #> 6730 2054 3F CC53 2020 2020-01-06 TKN -0.4155154440 #> 6731 2054 3F CC53 2020 2020-01-06 TN -0.3340751120 + #> 6732 2054 3F CC53 2020 2020-01-06 TP -2.3644604967 #> 6733 2054 3F CC53 2020 2020-01-06 TURB 0.7884573604 #> 6734 2054 3F CC53 2020 2020-02-03 CHLAC 1.6292405397 #> 6735 2054 3F CC53 2020 2020-02-03 COLOR 3.7612001157 #> 6736 2054 3F CC53 2020 2020-02-03 DO 1.6808279085 #> 6737 2054 3F CC53 2020 2020-02-03 DOSAT 4.0395363257 #> 6738 2054 3F CC53 2020 2020-02-03 NO23 -2.6450754019 #> 6739 2054 3F CC53 2020 2020-02-03 SALIN -0.1053605157 #> 6740 2054 3F CC53 2020 2020-02-03 TKN -0.2613647641 #> 6741 2054 3F CC53 2020 2020-02-03 TN -0.1731636190 + #> 6742 2054 3F CC53 2020 2020-02-03 TP -2.2072749132 #> 6743 2054 3F CC53 2020 2020-02-03 TURB 0.7419373447 #> 6744 2054 3F CC53 2020 2020-03-02 CHLAC 2.7080502011 #> 6745 2054 3F CC53 2020 2020-03-02 COLOR 3.8501476017 #> 6746 2054 3F CC53 2020 2020-03-02 DO 1.9657127764 #> 6747 2054 3F CC53 2020 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2020-12-07 COLOR 4.7874917428 #> 6766 2054 3F CC53 2020 2020-12-07 DO 1.9344157696 #> 6767 2054 3F CC53 2020 2020-12-07 DOSAT 4.3280982926 #> 6768 2054 3F CC53 2020 2020-12-07 NO23 -1.8971199849 #> 6769 2054 3F CC53 2020 2020-12-07 SALIN -1.3470736480 #> 6770 2054 3F CC53 2020 2020-12-07 TKN 0.1823215568 #> 6771 2054 3F CC53 2020 2020-12-07 TN 0.3001045925 + #> 6772 2054 3F CC53 2020 2020-12-07 TP -2.0402208285 #> 6773 2054 3F CC53 2020 2020-12-07 TURB 0.8754687374 #> 6774 2054 3F CC53 2021 2021-01-04 CHLAC 1.6863989536 #> 6775 2054 3F CC53 2021 2021-01-04 COLOR 4.4773368145 A #> 6776 2054 3F CC53 2021 2021-01-04 DO 1.7766458314 #> 6777 2054 3F CC53 2021 2021-01-04 DOSAT 4.1866198383 #> 6778 2054 3F CC53 2021 2021-01-04 NO23 -2.2072749132 #> 6779 2054 3F CC53 2021 2021-01-04 SALIN -1.3470736480 #> 6780 2054 3F CC53 2021 2021-01-04 TN 0.1906203596 + #> 6781 2054 3F CC53 2021 2021-01-04 TP -2.3025850930 #> 6782 2054 3F CC53 2021 2021-01-04 TURB 0.9932517730 #> 6783 2054 3F CC53 2021 2021-02-01 CHLAC 2.6390573296 #> 6784 2054 3F CC53 2021 2021-02-01 COLOR 4.2046926194 A #> 6785 2054 3F CC53 2021 2021-02-01 DO 1.8779371655 #> 6786 2054 3F CC53 2021 2021-02-01 DOSAT 4.2822062994 #> 6787 2054 3F CC53 2021 2021-02-01 NO23 -5.5214609179 U #> 6788 2054 3F CC53 2021 2021-02-01 SALIN 0.1739533071 #> 6789 2054 3F CC53 2021 2021-02-01 TKN -0.0408219945 #> 6790 2054 3F CC53 2021 2021-02-01 TN -0.0387408283 + #> 6791 2054 3F CC53 2021 2021-02-01 TP -2.0402208285 #> 6792 2054 3F CC53 2021 2021-02-01 TURB 1.4350845253 A #> 6793 2054 3F CC53 2021 2021-03-01 CHLAC 2.6390573296 #> 6794 2054 3F CC53 2021 2021-03-01 COLOR 4.0604430105 #> 6795 2054 3F CC53 2021 2021-03-01 DO 1.7369512327 #> 6796 2054 3F CC53 2021 2021-03-01 DOSAT 4.2239097666 #> 6797 2054 3F CC53 2021 2021-03-01 NO23 -5.5214609179 U #> 6798 2054 3F CC53 2021 2021-03-01 SALIN -0.5108256238 #> 6799 2054 3F CC53 2021 2021-03-01 TKN 0.0953101798 #> 6800 2054 3F CC53 2021 2021-03-01 TN 0.0971267107 + #> 6801 2054 3F CC53 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2021-10-04 NO23 -2.9004220937 #> 6856 2054 3F CC53 2021 2021-10-04 SALIN -2.0402208285 #> 6857 2054 3F CC53 2021 2021-10-04 TKN -0.0725706928 #> 6858 2054 3F CC53 2021 2021-10-04 TN -0.0151136378 + #> 6859 2054 3F CC53 2021 2021-10-04 TP -1.7719568419 #> 6860 2054 3F CC53 2021 2021-10-04 TURB 0.7419373447 A #> 6861 2054 3F CC53 2021 2021-11-01 CHLAC 2.1282317058 #> 6862 2054 3F CC53 2021 2021-11-01 COLOR 4.2766661190 #> 6863 2054 3F CC53 2021 2021-11-01 DO 1.0681530812 #> 6864 2054 3F CC53 2021 2021-11-01 DOSAT 3.5322256441 #> 6865 2054 3F CC53 2021 2021-11-01 NO23 -2.6450754019 #> 6866 2054 3F CC53 2021 2021-11-01 SALIN -1.4696759701 #> 6867 2054 3F CC53 2021 2021-11-01 TKN -0.0304592075 #> 6868 2054 3F CC53 2021 2021-11-01 TN 0.0401817896 + #> 6869 2054 3F CC53 2021 2021-11-01 TP -1.8971199849 #> 6870 2054 3F CC53 2021 2021-11-01 TURB 0.5306282511 #> 6871 2054 3F CC53 2021 2021-12-06 CHLAC 2.1282317058 #> 6872 2054 3F CC53 2021 2021-12-06 COLOR 4.3174881135 #> 6873 2054 3F CC53 2021 2021-12-06 NO23 -2.9957322736 #> 6874 2054 3F CC53 2021 2021-12-06 TKN 0.0953101798 #> 6875 2054 3F CC53 2021 2021-12-06 TN 0.1397619424 + #> 6876 2054 3F CC53 2021 2021-12-06 TP -2.3025850930 #> 6877 2054 3F CC53 2021 2021-12-06 TURB 0.7419373447 #> 6878 2054 3F CC53 2022 2022-01-03 CHLAC 1.2527629685 #> 6879 2054 3F CC53 2022 2022-01-03 COLOR 4.0943445622 A #> 6880 2054 3F CC53 2022 2022-01-03 DO 1.3402504226 #> 6881 2054 3F CC53 2022 2022-01-03 DOSAT 3.8286413965 #> 6882 2054 3F CC53 2022 2022-01-03 NO23 -4.1997050779 #> 6883 2054 3F CC53 2022 2022-01-03 SALIN 1.3376291891 #> 6884 2054 3F CC53 2022 2022-01-03 TKN -0.1053605157 #> 6885 2054 3F CC53 2022 2022-01-03 TN -0.0888312137 + #> 6886 2054 3F CC53 2022 2022-01-03 TP -1.7719568419 #> 6887 2054 3F CC53 2022 2022-01-03 TURB 0.6418538862 #> 6888 2054 3F CC53 2022 2022-02-07 CHLAC 2.2082744135 #> 6889 2054 3F CC53 2022 2022-02-07 COLOR 3.8286413965 #> 6890 2054 3F CC53 2022 2022-02-07 DO 1.7047480922 #> 6891 2054 3F CC53 2022 2022-02-07 DOSAT 4.1541845626 #> 6892 2054 3F CC53 2022 2022-02-07 NO23 -4.9618451299 I #> 6893 2054 3F CC53 2022 2022-02-07 SALIN 1.3270750015 #> 6894 2054 3F CC53 2022 2022-02-07 TKN -0.1863295782 #> 6895 2054 3F CC53 2022 2022-02-07 TN -0.1815218766 + #> 6896 2054 3F CC53 2022 2022-02-07 TP -1.8325814637 #> 6897 2054 3F CC53 2022 2022-02-07 TURB 1.2237754316 #> 6898 2054 3F CC53 2022 2022-03-07 CHLAC 2.3025850930 #> 6899 2054 3F CC53 2022 2022-03-07 COLOR 3.8066624898 A #> 6900 2054 3F CC53 2022 2022-03-07 NO23 -5.2983173665 I #> 6901 2054 3F CC53 2022 2022-03-07 TKN -0.1278333715 #> 6902 2054 3F CC53 2022 2022-03-07 TN -0.1232982163 + #> 6903 2054 3F CC53 2022 2022-03-07 TP -1.6094379124 #> 6904 2054 3F CC53 2022 2022-03-07 TURB 1.0296194172 #> 6905 2054 3F CC53 2022 2022-04-04 CHLAC 2.7725887222 #> 6906 2054 3F CC53 2022 2022-04-04 COLOR 3.9702919136 A #> 6907 2054 3F CC53 2022 2022-04-04 DO 1.1908875648 #> 6908 2054 3F CC53 2022 2022-04-04 DOSAT 3.7208625000 #> 6909 2054 3F CC53 2022 2022-04-04 NO23 -4.1997050779 #> 6910 2054 3F CC53 2022 2022-04-04 SALIN 2.1860512767 #> 6911 2054 3F CC53 2022 2022-04-04 TKN -0.3147107448 #> 6912 2054 3F CC53 2022 2022-04-04 TN -0.2943710606 + #> 6913 2054 3F CC53 2022 2022-04-04 TP -1.2378743560 #> 6914 2054 3F CC53 2022 2022-04-04 TURB 1.0296194172 #> 6915 2054 3F CC53 2022 2022-05-02 CHLAC 2.4849066498 #> 6916 2054 3F CC53 2022 2022-05-02 COLOR 4.0073331852 #> 6917 2054 3F CC53 2022 2022-05-02 NO23 -3.9120230054 #> 6918 2054 3F CC53 2022 2022-05-02 SALIN 2.5152741864 #> 6919 2054 3F CC53 2022 2022-05-02 TKN 0.0953101798 #> 6920 2054 3F CC53 2022 2022-05-02 TN 0.1133286853 + #> 6921 2054 3F CC53 2022 2022-05-02 TP -1.1394342832 #> 6922 2054 3F CC53 2022 2022-05-02 TURB 1.0986122887 #> 6923 2054 3F CC53 2022 2022-12-05 CHLAC 1.6094379124 #> 6924 2054 3F CC53 2022 2022-12-05 COLOR 4.7004803658 #> 6925 2054 3F CC53 2022 2022-12-05 NO23 -1.4696759701 #> 6926 2054 3F CC53 2022 2022-12-05 SALIN -1.3862943611 #> 6927 2054 3F CC53 2022 2022-12-05 TKN -0.0833816089 #> 6928 2054 3F CC53 2022 2022-12-05 TN 0.1397619424 + #> 6929 2054 3F CC53 2022 2022-12-05 TP -1.8971199849 #> 6930 2054 3F CC53 2022 2022-12-05 TURB 1.3350010667 #> 6931 2054 3F CC53 2023 2023-01-03 CHLAC 2.3978952728 #> 6932 2054 3F CC53 2023 2023-01-03 COLOR 4.2484952420 A #> 6933 2054 3F CC53 2023 2023-01-03 DO 2.1090003439 #> 6934 2054 3F CC53 2023 2023-01-03 DOSAT 4.5261269786 #> 6935 2054 3F CC53 2023 2023-01-03 NO23 -1.4271163556 #> 6936 2054 3F CC53 2023 2023-01-03 SALIN -1.1086626245 #> 6937 2054 3F CC53 2023 2023-01-03 TKN -0.1625189295 #> 6938 2054 3F CC53 2023 2023-01-03 TN 0.0861776962 + #> 6939 2054 3F CC53 2023 2023-01-03 TP -2.3025850930 #> 6940 2054 3F CC53 2023 2023-01-03 TURB 0.7884573604 #> 6941 2054 3F CC53 2023 2023-02-06 CHLAC 3.4965075615 #> 6942 2054 3F CC53 2023 2023-02-06 COLOR 4.0253516907 #> 6943 2054 3F CC53 2023 2023-02-06 DO 1.9740810260 #> 6944 2054 3F CC53 2023 2023-02-06 DOSAT 4.3919769655 #> 6945 2054 3F CC53 2023 2023-02-06 NO23 -5.2983173665 I #> 6946 2054 3F CC53 2023 2023-02-06 SALIN -0.4780358009 #> 6947 2054 3F CC53 2023 2023-02-06 TKN 0.0953101798 #> 6948 2054 3F CC53 2023 2023-02-06 TN 0.0989399479 + #> 6949 2054 3F CC53 2023 2023-02-06 TP -1.8325814637 #> 6950 2054 3F CC53 2023 2023-02-06 TURB 1.6863989536 #> 6951 2054 3F CC53 2023 2023-03-06 DO 1.5623463049 #> 6952 2054 3F CC53 2023 2023-03-06 DOSAT 4.0253516907 #> 6953 2054 3F CC53 2023 2023-03-06 SALIN 0.8501509294 #> 6954 2054 3F CC53 2014 2014-04-07 CHLAC 1.0986122887 #> 6955 2054 3F CC53 2014 2014-04-07 COLOR 5.0751738152 #> 6956 2054 3F CC53 2014 2014-04-07 COND 7.1701195434 #> 6957 2054 3F CC53 2014 2014-04-07 DO 1.7029282555 #> 6958 2054 3F CC53 2014 2014-04-07 DOSAT 4.0976723523 #> 6959 2054 3F CC53 2014 2014-04-07 NO23 -3.1700856607 #> 6960 2054 3F CC53 2014 2014-04-07 SALIN -0.3566749439 + #> 6961 2054 3F CC53 2014 2014-04-07 TKN 0.6418538862 #> 6962 2054 3F CC53 2014 2014-04-07 TN 0.6637183699 + #> 6963 2054 3F CC53 2014 2014-04-07 TP 0.0953101798 #> 6964 2054 3F CC53 2014 2014-04-07 TSS 2.9444389792 #> 6965 2054 3F CC53 2014 2014-04-07 TURB 2.7725887222 #> 6966 2054 3F CC53 2015 2015-05-21 COND 7.9291264873 #> 6967 2054 3F CC53 2015 2015-05-21 DO 1.4109869737 #> 6968 2054 3F CC53 2015 2015-05-21 DOSAT 3.9702919136 #> 6969 2054 3F CC53 2015 2015-05-21 SALIN 0.2851789422 + #> 6970 2054 3F CC53 2015 2015-07-15 COND 6.5439118456 #> 6971 2054 3F CC53 2015 2015-07-15 COND 6.5453496603 #> 6972 2054 3F CC53 2015 2015-07-15 SALIN -1.1711829815 + #> 6973 2054 3F CC53 2015 2015-08-06 COND 4.9052747784 #> 6974 2054 3F CC53 2015 2015-08-06 DO 1.4109869737 #> 6975 2054 3F CC53 2015 2015-08-06 DOSAT 3.9702919136 #> 6976 2054 3F CC53 2015 2015-08-19 COND 4.8751973232 #> 6977 2054 3F CC53 2015 2015-08-19 DO 1.2527629685 #> 6978 2054 3F CC53 2015 2015-08-19 DOSAT 3.8501476017 #> 6979 2054 3F CC53 2015 2015-09-15 COND 5.4764635519 #> 6980 2054 3F CC53 2015 2015-09-15 DO 1.1314021115 #> 6981 2054 3F CC53 2015 2015-09-15 DOSAT 3.6888794541 #> 6982 2054 3F CC53 2015 2015-09-15 SALIN -2.2072749132 + #> 6983 2054 3F CC53 2015 2015-09-15 COND 5.4764635519 #> 6984 2054 3F CC53 2015 2015-09-15 DO 1.0986122887 #> 6985 2054 3F CC53 2015 2015-09-15 DOSAT 3.6635616461 #> 6986 2054 3F CC53 2015 2015-09-15 SALIN -2.2072749132 + #> 6987 2054 3F CC53 2015 2015-11-25 COND 6.2225762681 #> 6988 2054 3F CC53 2015 2015-11-25 DO 1.7047480922 #> 6989 2054 3F CC53 2015 2015-11-25 DOSAT 4.1431347264 #> 6990 2054 3F CC53 2015 2015-11-25 SALIN -1.3470736480 + #> 6991 2054 3F CC53 2015 2015-11-25 COND 6.2285110036 #> 6992 2054 3F CC53 2015 2015-11-25 DO 1.6863989536 #> 6993 2054 3F CC53 2015 2015-11-25 DOSAT 4.1431347264 #> 6994 2054 3F CC53 2015 2015-11-25 SALIN -1.3470736480 + #> 6995 2054 3F CC53 2021 2021-02-02 COND 7.0184017991 #> 6996 2054 3F CC53 2021 2021-02-02 DO 1.9183921202 #> 6997 2054 3F CC53 2021 2021-02-02 DOSAT 4.2822062994 #> 6998 2054 3F CC53 2021 2021-02-02 SALIN -0.5798184953 #> 6999 2054 3F CC53 2021 2021-03-16 COND 7.8504931809 #> 7000 2054 3F CC53 2021 2021-03-16 DO 1.7783364489 #> 7001 2054 3F CC53 2021 2021-03-16 DOSAT 4.2527717988 #> 7002 2054 3F CC53 2021 2021-03-16 SALIN 0.2776317366 #> 7003 2054 3F CC53 2021 2021-09-30 COND 4.8880909413 #> 7004 2054 3F CC53 2021 2021-09-30 DO 1.3532545070 #> 7005 2054 3F CC53 2021 2021-09-30 DOSAT 3.8774315607 #> 7006 2054 3F CC53 2021 2021-09-30 SALIN -2.8134107168 #> 7007 2054 3F CC53 2021 2021-09-30 COND 4.8797670189 #> 7008 2054 3F CC53 2021 2021-09-30 DO 1.2412685891 #> 7009 2054 3F CC53 2021 2021-09-30 DOSAT 3.7750571504 #> 7010 2054 3F CC53 2021 2021-09-30 SALIN -2.8134107168 #> 7011 2054 3F CC53 2021 2021-10-27 COND 6.5250296578 #> 7012 2054 3F CC53 2021 2021-10-27 DO 1.5195132049 #> 7013 2054 3F CC53 2021 2021-10-27 DOSAT 4.0412953411 #> 7014 2054 3F CC53 2021 2021-10-27 SALIN -1.1086626245 #> 7015 2054 3F CC53 2021 2021-10-27 COND 6.5264948596 #> 7016 2054 3F CC53 2021 2021-10-27 DO 1.5129270121 #> 7017 2054 3F CC53 2021 2021-10-27 DOSAT 4.0342406382 #> 7018 2054 3F CC53 2021 2021-10-27 SALIN -1.1086626245 #> 7019 2054 3F CC53 2021 2021-11-18 COND 4.7104306966 #> 7020 2054 3F CC53 2021 2021-11-18 DO 1.8578592709 #> 7021 2054 3F CC53 2021 2021-11-18 DOSAT 4.2682978693 #> 7022 2054 3F CC53 2021 2021-11-18 SALIN -2.9957322736 #> 7023 2059 3M CC55 2015 2015-05-21 COND 9.9007337643 #> 7024 2059 3M CC55 2015 2015-05-21 DO 1.2237754316 #> 7025 2059 3M CC55 2015 2015-05-21 DOSAT 3.8286413965 #> 7026 2059 3M CC55 2015 2015-05-21 SALIN 2.4105422345 + #> 7027 2059 3M CC55 2015 2015-07-15 COND 6.7190131544 #> 7028 2059 3M CC55 2015 2015-07-15 SALIN -0.9416085399 + #> 7029 2059 3M CC55 2015 2015-08-06 COND 6.4019171967 #> 7030 2059 3M CC55 2015 2015-08-06 DO 1.6292405397 #> 7031 2059 3M CC55 2015 2015-08-06 DOSAT 4.1896547420 #> 7032 2059 3M CC55 2015 2015-08-06 SALIN -1.3093333200 + #> 7033 2059 3M CC55 2015 2015-08-19 COND 6.2785214242 #> 7034 2059 3M CC55 2015 2015-08-19 DO 1.6094379124 #> 7035 2059 3M CC55 2015 2015-08-19 DOSAT 4.1431347264 #> 7036 2059 3M CC55 2015 2015-08-19 SALIN -1.3862943611 + #> 7037 2059 3M CC55 2015 2015-09-15 COND 6.2205901701 #> 7038 2059 3M CC55 2015 2015-09-15 DO 1.4816045409 #> 7039 2059 3M CC55 2015 2015-09-15 DOSAT 4.0073331852 #> 7040 2059 3M CC55 2015 2015-09-15 SALIN -1.4271163556 + #> 7041 2059 3M CC55 2015 2015-10-08 CHLAC 0.2623642645 I #> 7042 2059 3M CC55 2015 2015-10-08 COND 6.3969296552 #> 7043 2059 3M CC55 2015 2015-10-08 DO 1.6486586256 #> 7044 2059 3M CC55 2015 2015-10-08 DOSAT 4.2046926194 #> 7045 2059 3M CC55 2015 2015-10-08 NO23 -2.7646205526 #> 7046 2059 3M CC55 2015 2015-10-08 SALIN -1.2378743560 + #> 7047 2059 3M CC55 2015 2015-10-08 TKN -0.1625189295 #> 7048 2059 3M CC55 2015 2015-10-08 TN -0.0910193984 + #> 7049 2059 3M CC55 2015 2015-10-08 TP -2.6310891600 #> 7050 2059 3M CC55 2015 2015-10-08 TSS 1.9459101491 I #> 7051 2059 3M CC55 2015 2015-10-08 TURB 2.0794415417 #> 7052 2059 3M CC55 2015 2015-11-05 CHLAC 0.5877866649 #> 7053 2059 3M CC55 2015 2015-11-05 COND 6.6982680541 #> 7054 2059 3M CC55 2015 2015-11-05 DO 1.9600947840 #> 7055 2059 3M CC55 2015 2015-11-05 DOSAT 4.4773368145 #> 7056 2059 3M CC55 2015 2015-11-05 SALIN -0.9416085399 + #> 7057 2059 3M CC55 2015 2015-11-05 TN -0.0693500781 + #> 7058 2059 3M CC55 2015 2015-11-05 TSS 1.7917594692 I #> 7059 2059 3M CC55 2015 2015-11-05 TURB 2.2721258855 #> 7060 2059 3M CC55 2015 2015-11-25 COND 6.7007311095 #> 7061 2059 3M CC55 2015 2015-11-25 DO 2.0014800002 #> 7062 2059 3M CC55 2015 2015-11-25 DOSAT 4.4188406078 #> 7063 2059 3M CC55 2015 2015-11-25 SALIN -0.8209805521 + #> 7064 2059 3M CC55 2015 2015-12-03 CHLAC 0.5306282511 #> 7065 2059 3M CC55 2015 2015-12-03 COLOR 4.7004803658 #> 7066 2059 3M CC55 2015 2015-12-03 COND 6.8448154792 #> 7067 2059 3M CC55 2015 2015-12-03 DO 1.8900953699 #> 7068 2059 3M CC55 2015 2015-12-03 DOSAT 4.3694478525 #> 7069 2059 3M CC55 2015 2015-12-03 NO23 -2.7488721956 #> 7070 2059 3M CC55 2015 2015-12-03 SALIN -0.7550225843 + #> 7071 2059 3M CC55 2015 2015-12-03 TKN -0.2357223335 #> 7072 2059 3M CC55 2015 2015-12-03 TN -0.1578240852 + #> 7073 2059 3M CC55 2015 2015-12-03 TP -2.8647040111 #> 7074 2059 3M CC55 2015 2015-12-03 TSS 1.3862943611 I #> 7075 2059 3M CC55 2015 2015-12-03 TURB 2.1282317058 #> 7076 2059 3M CC55 2015 2015-05-21 COND 7.3472997007 #> 7077 2059 3M CC55 2015 2015-05-21 DO 0.9932517730 #> 7078 2059 3M CC55 2015 2015-05-21 DOSAT 3.4657359028 #> 7079 2059 3M CC55 2015 2015-05-21 SALIN -0.3285040670 + #> 7080 2059 3M CC55 2015 2015-07-15 COND 9.6044074351 #> 7081 2059 3M CC55 2015 2015-08-06 COND 6.4068799861 #> 7082 2059 3M CC55 2015 2015-08-06 DO 1.6486586256 #> 7083 2059 3M CC55 2015 2015-08-06 DOSAT 4.2195077052 #> 7084 2059 3M CC55 2015 2015-08-06 SALIN -1.3093333200 + #> 7085 2059 3M CC55 2015 2015-08-19 COND 6.2653012127 #> 7086 2059 3M CC55 2015 2015-08-19 DO 1.3862943611 #> 7087 2059 3M CC55 2015 2015-08-19 DOSAT 4.0604430105 #> 7088 2059 3M CC55 2015 2015-08-19 SALIN -1.4271163556 + #> 7089 2059 3M CC55 2015 2015-09-15 COND 6.2519038832 #> 7090 2059 3M CC55 2015 2015-09-15 DO 1.6863989536 #> 7091 2059 3M CC55 2015 2015-09-15 DOSAT 4.1271343850 #> 7092 2059 3M CC55 2015 2015-09-15 SALIN -1.4271163556 + #> 7093 2059 3M CC55 2015 2015-11-25 COND 8.4348979487 #> 7094 2059 3M CC55 2015 2015-11-25 DO -0.1053605157 #> 7095 2059 3M CC55 2015 2015-11-25 DOSAT 2.3025850930 #> 7096 2059 3M CC55 2015 2015-11-25 SALIN 1.0152306797 + #> 7097 2059 3M CC56 2015 2015-05-21 COND 9.6019769721 #> 7098 2059 3M CC56 2015 2015-05-21 DO 0.6931471806 #> 7099 2059 3M CC56 2015 2015-05-21 DOSAT 3.1780538303 #> 7100 2059 3M CC56 2015 2015-05-21 SALIN 2.1459312829 + #> 7101 2059 3M CC56 2015 2015-07-15 COND 8.4859089014 #> 7102 2059 3M CC56 2015 2015-07-15 SALIN 0.9001613499 + #> 7103 2059 3M CC56 2015 2015-08-06 COND 6.3952615981 #> 7104 2059 3M CC56 2015 2015-08-06 DO 0.9932517730 #> 7105 2059 3M CC56 2015 2015-08-06 DOSAT 3.4657359028 #> 7106 2059 3M CC56 2015 2015-08-06 SALIN -1.3093333200 + #> 7107 2059 3M CC56 2015 2015-08-19 COND 6.1820849067 #> 7108 2059 3M CC56 2015 2015-08-19 DO 0.9932517730 #> 7109 2059 3M CC56 2015 2015-08-19 DOSAT 3.4965075615 #> 7110 2059 3M CC56 2015 2015-08-19 SALIN -1.5141277326 + #> 7111 2059 3M CC56 2015 2015-09-15 COND 6.2576675879 #> 7112 2059 3M CC56 2015 2015-09-15 DO 0.0953101798 #> 7113 2059 3M CC56 2015 2015-09-15 DOSAT 2.5649493575 #> 7114 2059 3M CC56 2015 2015-09-15 SALIN -1.4271163556 + #> 7115 2059 3M CC56 2015 2015-11-25 COND 7.6343372356 #> 7116 2059 3M CC56 2015 2015-11-25 DO 0.9555114450 #> 7117 2059 3M CC56 2015 2015-11-25 DOSAT 3.4011973817 #> 7118 2059 3M CC56 2015 2015-11-25 SALIN 0.1570037488 + #> 7119 2059 3M CC56 2015 2015-05-21 COND 9.9350831141 #> 7120 2059 3M CC56 2015 2015-05-21 DO 0.7884573604 #> 7121 2059 3M CC56 2015 2015-05-21 DOSAT 3.3672958300 #> 7122 2059 3M CC56 2015 2015-05-21 SALIN 2.4865719291 + #> 7123 2059 3M CC56 2015 2015-07-15 CHLAC 1.0986122887 #> 7124 2059 3M CC56 2015 2015-07-15 COND 9.6128678361 #> 7125 2059 3M CC56 2015 2015-07-15 NO23 -5.5214609179 U #> 7126 2059 3M CC56 2015 2015-07-15 SALIN 2.0881534823 + #> 7127 2059 3M CC56 2015 2015-07-15 TKN 0.2623642645 #> 7128 2059 3M CC56 2015 2015-07-15 TN 0.2639015438 + #> 7129 2059 3M CC56 2015 2015-07-15 TP -0.9416085399 #> 7130 2059 3M CC56 2015 2015-07-15 TSS 1.0986122887 U #> 7131 2059 3M CC56 2015 2015-07-15 TURB 1.3862943611 #> 7132 2059 3M CC56 2015 2015-08-06 COND 6.5366915976 #> 7133 2059 3M CC56 2015 2015-08-06 DO 0.2623642645 #> 7134 2059 3M CC56 2015 2015-08-06 DOSAT 2.7725887222 #> 7135 2059 3M CC56 2015 2015-08-06 SALIN -1.1394342832 + #> 7136 2059 3M CC56 2015 2015-08-19 CHLAC 1.0296194172 #> 7137 2059 3M CC56 2015 2015-08-19 COLOR 5.4380793089 #> 7138 2059 3M CC56 2015 2015-08-19 COND 6.4488893941 #> 7139 2059 3M CC56 2015 2015-08-19 DO 0.1823215568 #> 7140 2059 3M CC56 2015 2015-08-19 DOSAT 2.7725887222 #> 7141 2059 3M CC56 2015 2015-08-19 NO23 -5.5214609179 U #> 7142 2059 3M CC56 2015 2015-08-19 SALIN -1.2378743560 + #> 7143 2059 3M CC56 2015 2015-08-19 TKN 0.4054651081 #> 7144 2059 3M CC56 2015 2015-08-19 TN 0.4067975533 + #> 7145 2059 3M CC56 2015 2015-08-19 TP -0.0304592075 #> 7146 2059 3M CC56 2015 2015-08-19 TSS 1.7917594692 I #> 7147 2059 3M CC56 2015 2015-08-19 TURB 1.5686159179 #> 7148 2059 3M CC56 2015 2015-09-15 COND 6.8134445995 #> 7149 2059 3M CC56 2015 2015-09-15 DO 0.0000000000 #> 7150 2059 3M CC56 2015 2015-09-15 DOSAT 2.3025850930 #> 7151 2059 3M CC56 2015 2015-09-15 SALIN -0.8439700703 + #> 7152 2059 3M CC56 2015 2015-11-25 COND 7.8038433035 #> 7153 2059 3M CC56 2015 2015-11-25 DO 1.8718021769 #> 7154 2059 3M CC56 2015 2015-11-25 DOSAT 4.2626798770 #> 7155 2059 3M CC56 2015 2015-11-25 SALIN 0.3576744443 + #> 7156 2059 3M CC56 2018 2018-03-06 CHLAC 1.7917594692 #> 7157 2059 3M CC56 2018 2018-03-06 COND 9.8471817163 #> 7158 2059 3M CC56 2018 2018-03-06 DO 0.6205764877 #> 7159 2059 3M CC56 2018 2018-03-06 DOSAT 3.0445224377 #> 7160 2059 3M CC56 2018 2018-03-06 NO23 -2.6592600369 #> 7161 2059 3M CC56 2018 2018-03-06 SALIN 2.5748996883 + #> 7162 2059 3M CC56 2018 2018-03-06 TKN -0.0833816089 #> 7163 2059 3M CC56 2018 2018-03-06 TN -0.0100503359 + #> 7164 2059 3M CC56 2018 2018-03-06 TP -1.2378743560 #> 7165 2059 3M CC56 2018 2018-03-06 TSS 1.0986122887 U #> 7166 2059 3M CC56 2018 2018-03-06 TURB 0.1823215568 #> 7167 2059 3M CC56 2018 2018-03-29 CHLAC 2.1747517215 #> 7168 2059 3M CC56 2018 2018-03-29 COND 10.2506170836 #> 7169 2059 3M CC56 2018 2018-03-29 DO 1.3083328197 #> 7170 2059 3M CC56 2018 2018-03-29 DOSAT 3.8501476017 #> 7171 2059 3M CC56 2018 2018-03-29 NO23 -4.7105307016 I #> 7172 2059 3M CC56 2018 2018-03-29 SALIN 2.9156062291 + #> 7173 2059 3M CC56 2018 2018-03-29 TKN -0.2484613593 #> 7174 2059 3M CC56 2018 2018-03-29 TN -0.2433462586 + #> 7175 2059 3M CC56 2018 2018-03-29 TP -1.2039728043 #> 7176 2059 3M CC56 2018 2018-03-29 TSS 1.3862943611 I #> 7177 2059 3M CC56 2018 2018-03-29 TURB 0.8754687374 #> 7178 2059 3M CC56 2018 2018-04-12 COND 10.0096027833 #> 7179 2059 3M CC56 2018 2018-04-12 DO -0.3566749439 #> 7180 2059 3M CC56 2018 2018-04-12 DOSAT 2.0794415417 #> 7181 2059 3M CC56 2018 2018-04-12 SALIN 2.6932749155 + #> 7182 2059 3M CC56 2018 2018-04-19 CHLAC 0.0953101798 I #> 7183 2059 3M CC56 2018 2018-04-19 COND 10.2545668701 #> 7184 2059 3M CC56 2018 2018-04-19 DO 1.0260415958 #> 7185 2059 3M CC56 2018 2018-04-19 DOSAT 3.5025498759 #> 7186 2059 3M CC56 2018 2018-04-19 NO23 -4.6051701860 I #> 7187 2059 3M CC56 2018 2018-04-19 SALIN 2.9150643705 + #> 7188 2059 3M CC56 2018 2018-04-19 TKN -0.1863295782 #> 7189 2059 3M CC56 2018 2018-04-19 TN -0.1815218766 + #> 7190 2059 3M CC56 2018 2018-04-19 TP -1.0788096614 #> 7191 2059 3M CC56 2018 2018-04-19 TSS 1.3862943611 I #> 7192 2059 3M CC56 2018 2018-04-19 TURB 0.1823215568 #> 7193 2059 3M CC56 2018 2018-05-10 CHLAC 1.0296194172 #> 7194 2059 3M CC56 2018 2018-05-10 COND 10.2722540975 #> 7195 2059 3M CC56 2018 2018-05-10 DO -0.1053605157 #> 7196 2059 3M CC56 2018 2018-05-10 DOSAT 2.4849066498 #> 7197 2059 3M CC56 2018 2018-05-10 NO23 -5.5214609179 U #> 7198 2059 3M CC56 2018 2018-05-10 SALIN 2.8848007128 #> 7199 2059 3M CC56 2018 2018-05-10 TKN -0.0725706928 #> 7200 2059 3M CC56 2018 2018-05-10 TN -0.0704224643 + #> 7201 2059 3M CC56 2018 2018-05-10 TP -0.8209805521 #> 7202 2059 3M CC56 2018 2018-05-10 TSS 1.0986122887 I #> 7203 2059 3M CC56 2018 2018-05-10 TURB 0.5306282511 #> 7204 2059 3M CC56 2018 2018-06-25 CHLAC 0.6931471806 #> 7205 2059 3M CC56 2018 2018-06-25 COND 7.7536235466 #> 7206 2059 3M CC56 2018 2018-06-25 DO 1.0296194172 #> 7207 2059 3M CC56 2018 2018-06-25 DOSAT 3.2695689392 #> 7208 2059 3M CC56 2018 2018-06-25 NO23 -5.5214609179 U #> 7209 2059 3M CC56 2018 2018-06-25 SALIN 0.1397619424 + #> 7210 2059 3M CC56 2018 2018-06-25 TKN 0.2623642645 #> 7211 2059 3M CC56 2018 2018-06-25 TN 0.2639015438 + #> 7212 2059 3M CC56 2018 2018-06-25 TP -1.4696759701 #> 7213 2059 3M CC56 2018 2018-06-25 TSS 1.0986122887 I #> 7214 2059 3M CC56 2018 2018-06-25 TURB 1.3862943611 #> 7215 2059 3M CC56 2018 2018-07-17 CHLAC 0.9932517730 #> 7216 2059 3M CC56 2018 2018-07-17 COND 6.8437499490 #> 7217 2059 3M CC56 2018 2018-07-17 DO -0.1863295782 #> 7218 2059 3M CC56 2018 2018-07-17 DOSAT 2.3418058061 #> 7219 2059 3M CC56 2018 2018-07-17 NO23 -3.3524072175 #> 7220 2059 3M CC56 2018 2018-07-17 SALIN -0.8439700703 + #> 7221 2059 3M CC56 2018 2018-07-17 TKN 0.2623642645 #> 7222 2059 3M CC56 2018 2018-07-17 TN 0.2889312919 + #> 7223 2059 3M CC56 2018 2018-07-17 TP -1.3093333200 #> 7224 2059 3M CC56 2018 2018-07-17 TSS 1.0986122887 I #> 7225 2059 3M CC56 2018 2018-07-17 TURB 0.0953101798 #> 7226 2059 3M CC56 2018 2018-08-01 CHLAC 0.8754687374 #> 7227 2059 3M CC56 2018 2018-08-01 COND 6.0038870671 #> 7228 2059 3M CC56 2018 2018-08-01 DO 0.7129498079 #> 7229 2059 3M CC56 2018 2018-08-01 DOSAT 3.2580965380 #> 7230 2059 3M CC56 2018 2018-08-01 NO23 -3.6119184130 #> 7231 2059 3M CC56 2018 2018-08-01 SALIN -1.6607312068 #> 7232 2059 3M CC56 2018 2018-08-01 TKN 0.0953101798 #> 7233 2059 3M CC56 2018 2018-08-01 TN 0.1195592351 + #> 7234 2059 3M CC56 2018 2018-08-01 TP -1.7719568419 #> 7235 2059 3M CC56 2018 2018-08-01 TSS 0.6931471806 U #> 7236 2059 3M CC56 2018 2018-08-01 TURB 0.0953101798 #> 7237 2059 3M CC56 2018 2018-08-20 CHLAC 0.4054651081 I #> 7238 2059 3M CC56 2018 2018-08-20 NO23 -1.4696759701 #> 7239 2059 3M CC56 2018 2018-08-20 TKN -0.3147107448 #> 7240 2059 3M CC56 2018 2018-08-20 TN -0.0408219945 + #> 7241 2059 3M CC56 2018 2018-08-20 TP -0.9416085399 #> 7242 2059 3M CC56 2018 2018-08-20 TSS 1.0986122887 U #> 7243 2059 3M CC56 2018 2018-08-20 TURB 0.7419373447 #> 7244 2059 3M CC56 2018 2018-08-21 CHLAC 0.7419373447 #> 7245 2059 3M CC56 2018 2018-08-21 COND 5.9401712527 #> 7246 2059 3M CC56 2018 2018-08-21 DO 0.9516578757 #> 7247 2059 3M CC56 2018 2018-08-21 DOSAT 3.4436180975 #> 7248 2059 3M CC56 2018 2018-08-21 NO23 -3.7297014486 #> 7249 2059 3M CC56 2018 2018-08-21 SALIN -1.7147984281 #> 7250 2059 3M CC56 2018 2018-08-21 TKN 0.0000000000 #> 7251 2059 3M CC56 2018 2018-08-21 TN 0.0237165266 + #> 7252 2059 3M CC56 2018 2018-08-21 TP -1.8325814637 #> 7253 2059 3M CC56 2018 2018-08-21 TSS 1.0986122887 I #> 7254 2059 3M CC56 2018 2018-08-21 TURB 0.3364722366 A #> 7255 2059 3M CC56 2018 2018-09-20 CHLAC 1.5040773968 #> 7256 2059 3M CC56 2018 2018-09-20 COND 7.2661287796 #> 7257 2059 3M CC56 2018 2018-09-20 DO 0.9555114450 #> 7258 2059 3M CC56 2018 2018-09-20 DOSAT 3.5862928653 #> 7259 2059 3M CC56 2018 2018-09-20 NO23 -3.1010927892 #> 7260 2059 3M CC56 2018 2018-09-20 SALIN -0.3424903089 #> 7261 2059 3M CC56 2018 2018-09-20 TKN 0.1823215568 #> 7262 2059 3M CC56 2018 2018-09-20 TN 0.2191355299 + #> 7263 2059 3M CC56 2018 2018-09-20 TP -1.0788096614 #> 7264 2059 3M CC56 2018 2018-09-20 TSS 1.0986122887 I #> 7265 2059 3M CC56 2018 2018-09-20 TURB 0.9162907319 #> 7266 2059 3M CC56 2018 2018-10-24 CHLAC 1.1314021115 #> 7267 2059 3M CC56 2018 2018-10-24 COND 9.4323632956 #> 7268 2059 3M CC56 2018 2018-10-24 DO 0.5068176024 #> 7269 2059 3M CC56 2018 2018-10-24 DOSAT 3.0726933147 #> 7270 2059 3M CC56 2018 2018-10-24 NO23 -3.4737680745 #> 7271 2059 3M CC56 2018 2018-10-24 SALIN 1.9671123567 #> 7272 2059 3M CC56 2018 2018-10-24 TKN -0.0408219945 #> 7273 2059 3M CC56 2018 2018-10-24 TN -0.0090407447 + #> 7274 2059 3M CC56 2018 2018-10-24 TP -1.2039728043 #> 7275 2059 3M CC56 2018 2018-10-24 TSS 0.6931471806 I #> 7276 2059 3M CC56 2018 2018-10-24 TURB 1.7227665977 #> 7277 2059 3M CC56 2019 2019-01-16 CHLAC -0.1053605157 I #> 7278 2059 3M CC56 2019 2019-01-16 COND 9.0122552200 #> 7279 2059 3M CC56 2019 2019-01-16 DO 0.3852624008 #> 7280 2059 3M CC56 2019 2019-01-16 DOSAT 2.7080502011 #> 7281 2059 3M CC56 2019 2019-01-16 NO23 -2.5010360317 #> 7282 2059 3M CC56 2019 2019-01-16 SALIN 1.5216989981 #> 7283 2059 3M CC56 2019 2019-01-16 TKN -0.0618754037 #> 7284 2059 3M CC56 2019 2019-01-16 TN 0.0217614918 + #> 7285 2059 3M CC56 2019 2019-01-16 TP -1.3862943611 #> 7286 2059 3M CC56 2019 2019-01-16 TSS 0.6931471806 U #> 7287 2059 3M CC56 2019 2019-01-16 TURB 0.0000000000 #> 7288 2059 3M CC56 2019 2019-01-24 COND 9.8578100390 #> 7289 2059 3M CC56 2019 2019-01-24 DO 1.6770965609 #> 7290 2059 3M CC56 2019 2019-01-24 DOSAT 4.1588830834 #> 7291 2059 3M CC56 2019 2019-01-24 NO23 -3.2968373663 #> 7292 2059 3M CC56 2019 2019-01-24 SALIN 2.4327357775 #> 7293 2059 3M CC56 2019 2019-01-24 TKN -0.3147107448 #> 7294 2059 3M CC56 2019 2019-01-24 TN -0.2652684776 + #> 7295 2059 3M CC56 2019 2019-01-24 TP -1.3470736480 #> 7296 2059 3M CC56 2019 2019-01-24 TSS 1.0986122887 U #> 7297 2059 3M CC56 2019 2019-01-24 TURB 0.6418538862 #> 7298 2059 3M CC56 2019 2019-03-12 CHLAC 0.1823215568 I #> 7299 2059 3M CC56 2019 2019-03-12 COND 9.1291303166 #> 7300 2059 3M CC56 2019 2019-03-12 DO 0.4824261492 #> 7301 2059 3M CC56 2019 2019-03-12 DOSAT 2.9496883351 #> 7302 2059 3M CC56 2019 2019-03-12 NO23 -3.2968373663 #> 7303 2059 3M CC56 2019 2019-03-12 SALIN 1.6114359151 #> 7304 2059 3M CC56 2019 2019-03-12 TKN -0.0408219945 #> 7305 2059 3M CC56 2019 2019-03-12 TN -0.0030045090 + #> 7306 2059 3M CC56 2019 2019-03-12 TP -1.0498221245 #> 7307 2059 3M CC56 2019 2019-03-12 TSS 0.6931471806 I #> 7308 2059 3M CC56 2019 2019-03-12 TURB 0.0000000000 #> 7309 2059 3M CC56 2019 2019-04-23 CHLAC 1.1939224685 #> 7310 2059 3M CC56 2019 2019-04-23 COND 9.4766200382 #> 7311 2059 3M CC56 2019 2019-04-23 DO 0.7929925155 #> 7312 2059 3M CC56 2019 2019-04-23 DOSAT 3.3286266888 #> 7313 2059 3M CC56 2019 2019-04-23 NO23 -3.5755507688 #> 7314 2059 3M CC56 2019 2019-04-23 SALIN 2.0175661380 #> 7315 2059 3M CC56 2019 2019-04-23 TKN -0.1984509387 #> 7316 2059 3M CC56 2019 2019-04-23 TN -0.1648746432 + #> 7317 2059 3M CC56 2019 2019-04-23 TP -1.1086626245 #> 7318 2059 3M CC56 2019 2019-04-23 TSS 0.6931471806 I #> 7319 2059 3M CC56 2019 2019-04-23 TURB 0.2623642645 #> 7320 2059 3M CC56 2019 2019-06-11 CHLAC 1.8245492921 I #> 7321 2059 3M CC56 2019 2019-06-11 COND 9.8113722636 #> 7322 2059 3M CC56 2019 2019-06-11 DO 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2014 2014-06-02 COLOR 2.3978952728 #> 7521 2063 3M CC64 2014 2014-06-02 DO 1.0116009117 #> 7522 2063 3M CC64 2014 2014-06-02 DOSAT 3.7111300630 + #> 7523 2063 3M CC64 2014 2014-06-02 NO23 -5.1159958098 I #> 7524 2063 3M CC64 2014 2014-06-02 SALIN 3.3347013904 #> 7525 2063 3M CC64 2014 2014-06-02 TKN -0.4462871026 #> 7526 2063 3M CC64 2014 2014-06-02 TN -0.4400565529 + #> 7527 2063 3M CC64 2014 2014-06-02 TP -2.0402208285 #> 7528 2063 3M CC64 2014 2014-06-02 TURB 0.6931471806 #> 7529 2063 3M CC64 2014 2014-07-07 CHLAC 1.7047480922 #> 7530 2063 3M CC64 2014 2014-07-07 COLOR 3.1354942159 #> 7531 2063 3M CC64 2014 2014-07-07 DOSAT 3.7495040759 + #> 7532 2063 3M CC64 2014 2014-07-07 NO23 -4.5098600062 #> 7533 2063 3M CC64 2014 2014-07-07 SALIN 3.2611687371 #> 7534 2063 3M CC64 2014 2014-07-07 TKN -0.1863295782 #> 7535 2063 3M CC64 2014 2014-07-07 TN -0.1731636190 + #> 7536 2063 3M CC64 2014 2014-07-07 TP -2.0402208285 #> 7537 2063 3M CC64 2014 2014-07-07 TURB 0.6931471806 #> 7538 2063 3M 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2063 3M CC64 2015 2015-01-05 TKN -0.5621189182 #> 7593 2063 3M CC64 2015 2015-01-05 TN -0.4684049079 + #> 7594 2063 3M CC64 2015 2015-01-05 TP -2.3025850930 #> 7595 2063 3M CC64 2015 2015-01-05 TURB 0.6931471806 #> 7596 2063 3M CC64 2015 2015-02-02 CHLAC 0.2623642645 I #> 7597 2063 3M CC64 2015 2015-02-02 COLOR 2.3025850930 #> 7598 2063 3M CC64 2015 2015-02-02 DOSAT 4.3932138241 + #> 7599 2063 3M CC64 2015 2015-02-02 NO23 -4.3428059215 #> 7600 2063 3M CC64 2015 2015-02-02 SALIN 3.3214324132 #> 7601 2063 3M CC64 2015 2015-02-02 TKN -0.9942522733 I #> 7602 2063 3M CC64 2015 2015-02-02 TN -1.7544636845 + #> 7603 2063 3M CC64 2015 2015-02-02 TP -2.4534079827 #> 7604 2063 3M CC64 2015 2015-02-02 TURB 0.7884573604 A #> 7605 2063 3M CC64 2015 2015-03-02 CHLAC 1.1631508098 A #> 7606 2063 3M CC64 2015 2015-03-02 COLOR 2.8903717579 #> 7607 2063 3M CC64 2015 2015-03-02 DO 1.9430489168 #> 7608 2063 3M CC64 2015 2015-03-02 DOSAT 4.5152454785 + #> 7609 2063 3M CC64 2015 2015-03-02 NO23 -3.1941832123 #> 7610 2063 3M CC64 2015 2015-03-02 SALIN 3.2136622578 #> 7611 2063 3M CC64 2015 2015-03-02 TKN -0.4942963218 #> 7612 2063 3M CC64 2015 2015-03-02 TN -0.4292456368 + #> 7613 2063 3M CC64 2015 2015-03-02 TP -2.2072749132 #> 7614 2063 3M CC64 2015 2015-03-02 TURB 0.8754687374 #> 7615 2063 3M CC64 2015 2015-04-06 CHLAC 0.9162907319 #> 7616 2063 3M CC64 2015 2015-04-06 COLOR 2.9957322736 #> 7617 2063 3M CC64 2015 2015-04-06 DO 1.3558351536 #> 7618 2063 3M CC64 2015 2015-04-06 DOSAT 4.0036901940 + #> 7619 2063 3M CC64 2015 2015-04-06 NO23 -4.6051701860 #> 7620 2063 3M CC64 2015 2015-04-06 SALIN 3.2268439945 #> 7621 2063 3M CC64 2015 2015-04-06 TKN -0.4462871026 #> 7622 2063 3M CC64 2015 2015-04-06 TN -0.4307829161 + #> 7623 2063 3M CC64 2015 2015-04-06 TP -2.3025850930 #> 7624 2063 3M CC64 2015 2015-04-06 TURB 0.6931471806 #> 7625 2063 3M CC64 2015 2015-05-04 CHLAC 1.2809338455 #> 7626 2063 3M CC64 2015 2015-05-04 COLOR 2.9444389792 #> 7627 2063 3M CC64 2015 2015-05-04 DOSAT 4.0673158898 + #> 7628 2063 3M CC64 2015 2015-05-04 NO23 -4.8283137373 I #> 7629 2063 3M CC64 2015 2015-05-04 SALIN 3.2820383998 #> 7630 2063 3M CC64 2015 2015-05-04 TKN -0.7133498879 #> 7631 2063 3M CC64 2015 2015-05-04 TN -0.7052197618 + #> 7632 2063 3M CC64 2015 2015-05-04 TP -2.7806208939 #> 7633 2063 3M CC64 2015 2015-05-04 TURB 0.7884573604 #> 7634 2063 3M CC64 2015 2015-06-01 CHLAC 1.1631508098 #> 7635 2063 3M CC64 2015 2015-06-01 COLOR 2.8332133441 #> 7636 2063 3M CC64 2015 2015-06-01 DO 1.0647107370 #> 7637 2063 3M CC64 2015 2015-06-01 DOSAT 3.7773481021 + #> 7638 2063 3M CC64 2015 2015-06-01 NO23 -4.6051701860 I #> 7639 2063 3M CC64 2015 2015-06-01 SALIN 3.3214324132 #> 7640 2063 3M CC64 2015 2015-06-01 TKN -0.5621189182 #> 7641 2063 3M CC64 2015 2015-06-01 TN -0.5551258827 + #> 7642 2063 3M CC64 2015 2015-06-01 TP -2.3025850930 #> 7643 2063 3M CC64 2015 2015-06-01 TURB 0.4700036292 #> 7644 2063 3M CC64 2015 2015-08-03 CHLAC 2.2407096893 #> 7645 2063 3M CC64 2015 2015-08-03 COLOR 4.1588830834 #> 7646 2063 3M CC64 2015 2015-08-03 DO 0.7654678421 #> 7647 2063 3M CC64 2015 2015-08-03 DOSAT 3.4045251718 + #> 7648 2063 3M CC64 2015 2015-08-03 NO23 -4.6051701860 I #> 7649 2063 3M CC64 2015 2015-08-03 SALIN 2.8039662579 #> 7650 2063 3M CC64 2015 2015-08-03 TKN -0.0512932944 #> 7651 2063 3M CC64 2015 2015-08-03 TN -0.0470916075 + #> 7652 2063 3M CC64 2015 2015-08-03 TP -2.0402208285 #> 7653 2063 3M CC64 2015 2015-08-03 TURB 0.5877866649 #> 7654 2063 3M CC64 2015 2015-09-08 CHLAC 1.3609765531 #> 7655 2063 3M CC64 2015 2015-09-08 COLOR 4.5432947823 #> 7656 2063 3M CC64 2015 2015-09-08 NO23 -3.6888794541 #> 7657 2063 3M CC64 2015 2015-09-08 SALIN 1.3584091576 #> 7658 2063 3M CC64 2015 2015-09-08 TKN -0.1743533871 #> 7659 2063 3M CC64 2015 2015-09-08 TN -0.1450257721 + #> 7660 2063 3M CC64 2015 2015-09-08 TP -2.2072749132 #> 7661 2063 3M CC64 2015 2015-09-08 TURB 0.5306282511 #> 7662 2063 3M CC64 2015 2015-10-05 CHLAC 1.5892352051 #> 7663 2063 3M CC64 2015 2015-10-05 COLOR 4.5643481915 #> 7664 2063 3M CC64 2015 2015-10-05 DO 1.1085626195 #> 7665 2063 3M CC64 2015 2015-10-05 DOSAT 3.6888794541 + #> 7666 2063 3M CC64 2015 2015-10-05 NO23 -3.3524072175 #> 7667 2063 3M CC64 2015 2015-10-05 SALIN 2.4069451083 #> 7668 2063 3M CC64 2015 2015-10-05 TKN -0.1984509387 #> 7669 2063 3M CC64 2015 2015-10-05 TN -0.1566538100 + #> 7670 2063 3M CC64 2015 2015-10-05 TP -1.5606477483 #> 7671 2063 3M CC64 2015 2015-10-05 TURB 0.3364722366 A #> 7672 2063 3M CC64 2015 2015-12-07 CHLAC 0.9555114450 #> 7673 2063 3M CC64 2015 2015-12-07 COLOR 3.4965075615 #> 7674 2063 3M CC64 2015 2015-12-07 DO 1.1314021115 #> 7675 2063 3M CC64 2015 2015-12-07 DOSAT 3.6988297850 + #> 7676 2063 3M CC64 2015 2015-12-07 NO23 -2.8824035882 #> 7677 2063 3M CC64 2015 2015-12-07 SALIN 3.0540011817 #> 7678 2063 3M CC64 2015 2015-12-07 TKN -0.4780358009 #> 7679 2063 3M CC64 2015 2015-12-07 TN -0.3915622029 + #> 7680 2063 3M CC64 2015 2015-12-07 TP -2.2072749132 #> 7681 2063 3M CC64 2015 2015-12-07 TURB 0.7884573604 #> 7682 2063 3M CC64 2016 2016-01-04 CHLAC 0.4700036292 I #> 7683 2063 3M CC64 2016 2016-01-04 COLOR 3.1780538303 #> 7684 2063 3M CC64 2016 2016-01-04 DO 1.1631508098 #> 7685 2063 3M CC64 2016 2016-01-04 DOSAT 3.7281001673 + #> 7686 2063 3M CC64 2016 2016-01-04 NO23 -2.7030626596 #> 7687 2063 3M CC64 2016 2016-01-04 SALIN 3.1112906142 #> 7688 2063 3M CC64 2016 2016-01-04 TKN -0.3011050928 #> 7689 2063 3M CC64 2016 2016-01-04 TN -0.2144316107 + #> 7690 2063 3M CC64 2016 2016-01-04 TP -2.0402208285 #> 7691 2063 3M CC64 2016 2016-01-04 TURB 0.9162907319 #> 7692 2063 3M CC64 2016 2016-02-01 COLOR 4.1896547420 A #> 7693 2063 3M CC64 2016 2016-02-01 DOSAT 4.5053498507 + #> 7694 2063 3M CC64 2016 2016-02-01 NO23 -4.1997050779 #> 7695 2063 3M CC64 2016 2016-02-01 SALIN 1.9810014689 #> 7696 2063 3M CC64 2016 2016-02-01 TKN -0.5447271754 #> 7697 2063 3M CC64 2016 2016-02-01 TN -0.5191938734 + #> 7698 2063 3M CC64 2016 2016-02-01 TP -2.8473122684 #> 7699 2063 3M CC64 2016 2016-02-01 TURB 0.5877866649 #> 7700 2063 3M CC64 2016 2016-03-07 CHLAC 0.6418538862 I #> 7701 2063 3M CC64 2016 2016-03-07 COLOR 3.7841896339 #> 7702 2063 3M CC64 2016 2016-03-07 NO23 -4.1997050779 #> 7703 2063 3M CC64 2016 2016-03-07 SALIN 2.6159349122 #> 7704 2063 3M CC64 2016 2016-03-07 TKN -0.2231435513 #> 7705 2063 3M CC64 2016 2016-03-07 TN -0.2045671657 + #> 7706 2063 3M CC64 2016 2016-03-07 TP -2.3538783874 #> 7707 2063 3M CC64 2016 2016-03-07 TURB 0.4700036292 #> 7708 2063 3M CC64 2016 2016-04-04 CHLAC 1.2237754316 #> 7709 2063 3M CC64 2016 2016-04-04 COLOR 3.3322045102 A #> 7710 2063 3M CC64 2016 2016-04-04 DO 1.6094379124 #> 7711 2063 3M CC64 2016 2016-04-04 DOSAT 4.2061840440 + #> 7712 2063 3M CC64 2016 2016-04-04 NO23 -3.7297014486 #> 7713 2063 3M CC64 2016 2016-04-04 SALIN 2.9236990707 #> 7714 2063 3M CC64 2016 2016-04-04 TN -0.3092462504 + #> 7715 2063 3M CC64 2016 2016-04-04 TP -2.2072749132 #> 7716 2063 3M CC64 2016 2016-04-04 TURB 0.7419373447 #> 7717 2063 3M CC64 2016 2016-05-02 CHLAC 0.8754687374 #> 7718 2063 3M CC64 2016 2016-05-02 COLOR 3.1780538303 #> 7719 2063 3M CC64 2016 2016-05-02 DO 1.1631508098 #> 7720 2063 3M CC64 2016 2016-05-02 DOSAT 3.8394523126 + #> 7721 2063 3M CC64 2016 2016-05-02 NO23 -4.5098600062 #> 7722 2063 3M CC64 2016 2016-05-02 SALIN 3.1428583384 #> 7723 2063 3M CC64 2016 2016-05-02 TKN -0.5276327421 #> 7724 2063 3M CC64 2016 2016-05-02 TN -0.5091603444 + #> 7725 2063 3M CC64 2016 2016-05-02 TP -2.3025850930 #> 7726 2063 3M CC64 2016 2016-05-02 TURB 0.6931471806 #> 7727 2063 3M CC64 2016 2016-06-06 NO23 -4.6051701860 I #> 7728 2063 3M CC64 2016 2016-06-06 SALIN 3.2120525995 #> 7729 2063 3M CC64 2016 2016-06-06 TKN -0.4462871026 #> 7730 2063 3M CC64 2016 2016-06-06 TN -0.4400565529 + #> 7731 2063 3M CC64 2016 2016-06-06 TP -2.1202635362 #> 7732 2063 3M CC64 2016 2016-07-05 CHLAC 1.0296194172 #> 7733 2063 3M CC64 2016 2016-07-05 COLOR 3.9702919136 #> 7734 2063 3M CC64 2016 2016-07-05 DO 0.5596157879 #> 7735 2063 3M CC64 2016 2016-07-05 DOSAT 3.2503744919 + #> 7736 2063 3M CC64 2016 2016-07-05 NO23 -5.5214609179 U #> 7737 2063 3M CC64 2016 2016-07-05 SALIN 2.8864752876 #> 7738 2063 3M CC64 2016 2016-07-05 TKN -0.2484613593 #> 7739 2063 3M CC64 2016 2016-07-05 TN -0.2459005384 + #> 7740 2063 3M CC64 2016 2016-07-05 TP -1.6607312068 #> 7741 2063 3M CC64 2016 2016-07-05 TURB 0.6418538862 #> 7742 2063 3M CC64 2016 2016-08-01 CHLAC 0.7884573604 #> 7743 2063 3M CC64 2016 2016-08-01 COLOR 4.0073331852 A #> 7744 2063 3M CC64 2016 2016-08-01 DO 0.9669838462 #> 7745 2063 3M CC64 2016 2016-08-01 DOSAT 3.6428355156 + #> 7746 2063 3M CC64 2016 2016-08-01 NO23 -4.3428059215 #> 7747 2063 3M CC64 2016 2016-08-01 SALIN 2.6232182656 #> 7748 2063 3M CC64 2016 2016-08-01 TKN -0.1625189295 #> 7749 2063 3M CC64 2016 2016-08-01 TN -0.1473405879 + #> 7750 2063 3M CC64 2016 2016-08-01 TP -1.9661128564 #> 7751 2063 3M CC64 2016 2016-08-01 TURB 0.3364722366 #> 7752 2063 3M CC64 2016 2016-10-03 CHLAC 1.3350010667 #> 7753 2063 3M CC64 2016 2016-10-03 COLOR 3.9702919136 #> 7754 2063 3M CC64 2016 2016-10-03 DO 0.7178397932 #> 7755 2063 3M CC64 2016 2016-10-03 DOSAT 3.3568971228 + #> 7756 2063 3M CC64 2016 2016-10-03 NO23 -4.1351665567 #> 7757 2063 3M CC64 2016 2016-10-03 SALIN 2.5892666651 #> 7758 2063 3M CC64 2016 2016-10-03 TKN -0.4620354596 #> 7759 2063 3M CC64 2016 2016-10-03 TN -0.4369557752 + #> 7760 2063 3M CC64 2016 2016-10-03 TP -1.8325814637 #> 7761 2063 3M CC64 2016 2016-10-03 TURB 0.1823215568 #> 7762 2063 3M CC64 2016 2016-11-07 CHLAC 0.8754687374 #> 7763 2063 3M CC64 2016 2016-11-07 COLOR 2.8332133441 A #> 7764 2063 3M CC64 2016 2016-11-07 DO 1.3402504226 #> 7765 2063 3M CC64 2016 2016-11-07 DOSAT 3.9473901493 + #> 7766 2063 3M CC64 2016 2016-11-07 NO23 -4.7105307016 I #> 7767 2063 3M CC64 2016 2016-11-07 SALIN 3.3178157727 #> 7768 2063 3M CC64 2016 2016-11-07 TKN -0.4155154440 #> 7769 2063 3M CC64 2016 2016-11-07 TN -0.4094731295 + #> 7770 2063 3M CC64 2016 2016-11-07 TP -2.3330443005 #> 7771 2063 3M CC64 2016 2016-11-07 TURB 0.6418538862 #> 7772 2063 3M CC64 2016 2016-12-05 CHLAC 2.6390573296 #> 7773 2063 3M CC64 2016 2016-12-05 COLOR 2.7080502011 #> 7774 2063 3M CC64 2016 2016-12-05 DO 1.6094379124 #> 7775 2063 3M CC64 2016 2016-12-05 DOSAT 4.2165621949 + #> 7776 2063 3M CC64 2016 2016-12-05 NO23 -5.5214609179 U #> 7777 2063 3M CC64 2016 2016-12-05 SALIN 3.3792925463 #> 7778 2063 3M CC64 2016 2016-12-05 TKN -0.3285040670 #> 7779 2063 3M CC64 2016 2016-12-05 TN -0.3257301401 + #> 7780 2063 3M CC64 2016 2016-12-05 TP -1.7147984281 #> 7781 2063 3M CC64 2016 2016-12-05 TURB 0.8329091229 #> 7782 2063 3M CC64 2017 2017-01-03 CHLAC 0.7419373447 #> 7783 2063 3M CC64 2017 2017-01-03 COLOR 2.1860512767 #> 7784 2063 3M CC64 2017 2017-01-03 DO 1.6292405397 #> 7785 2063 3M CC64 2017 2017-01-03 DOSAT 4.2370008626 + #> 7786 2063 3M CC64 2017 2017-01-03 NO23 -5.5214609179 U #> 7787 2063 3M CC64 2017 2017-01-03 SALIN 3.3911470458 #> 7788 2063 3M CC64 2017 2017-01-03 TKN -0.6733445533 #> 7789 2063 3M CC64 2017 2017-01-03 TN -0.6694306539 + #> 7790 2063 3M CC64 2017 2017-01-03 TP -2.3751557858 #> 7791 2063 3M CC64 2017 2017-01-03 TURB 0.4700036292 #> 7792 2063 3M CC64 2017 2017-02-06 CHLAC 1.3083328197 #> 7793 2063 3M CC64 2017 2017-02-06 COLOR 2.2300144002 #> 7794 2063 3M CC64 2017 2017-02-06 DO 1.6770965609 #> 7795 2063 3M CC64 2017 2017-02-06 DOSAT 4.2654928184 + #> 7796 2063 3M CC64 2017 2017-02-06 NO23 -3.3242363405 #> 7797 2063 3M CC64 2017 2017-02-06 SALIN 3.3965197921 #> 7798 2063 3M CC64 2017 2017-02-06 TKN -0.3566749439 #> 7799 2063 3M CC64 2017 2017-02-06 TN -0.3065251603 + #> 7800 2063 3M CC64 2017 2017-02-06 TP -2.4418471603 #> 7801 2063 3M CC64 2017 2017-02-06 TURB 0.9555114450 #> 7802 2063 3M CC64 2017 2017-03-06 CHLAC 1.2237754316 #> 7803 2063 3M CC64 2017 2017-03-06 COLOR 1.7917594692 #> 7804 2063 3M CC64 2017 2017-03-06 DO 1.6770965609 #> 7805 2063 3M CC64 2017 2017-03-06 DOSAT 4.2598590007 + #> 7806 2063 3M CC64 2017 2017-03-06 NO23 -5.1159958098 I #> 7807 2063 3M CC64 2017 2017-03-06 SALIN 3.4124669739 #> 7808 2063 3M CC64 2017 2017-03-06 TKN -0.5798184953 #> 7809 2063 3M CC64 2017 2017-03-06 TN -0.5727010275 + #> 7810 2063 3M CC64 2017 2017-03-06 TP -2.5257286443 #> 7811 2063 3M CC64 2017 2017-03-06 TURB 0.9932517730 #> 7812 2063 3M CC64 2017 2017-04-03 CHLAC 1.4586150227 #> 7813 2063 3M CC64 2017 2017-04-03 COLOR 2.3978952728 #> 7814 2063 3M CC64 2017 2017-04-03 DO 1.3635373740 #> 7815 2063 3M CC64 2017 2017-04-03 DOSAT 4.0638853547 + #> 7816 2063 3M CC64 2017 2017-04-03 NO23 -4.9618451299 I #> 7817 2063 3M CC64 2017 2017-04-03 SALIN 3.5115454388 #> 7818 2063 3M CC64 2017 2017-04-03 TKN -0.3424903089 #> 7819 2063 3M CC64 2017 2017-04-03 TN -0.3368723166 + #> 7820 2063 3M CC64 2017 2017-04-03 TP -2.4769384801 #> 7821 2063 3M CC64 2017 2017-04-03 TURB 0.8754687374 #> 7822 2063 3M CC64 2017 2017-05-01 CHLAC 1.0296194172 #> 7823 2063 3M CC64 2017 2017-05-01 COLOR 2.6390573296 #> 7824 2063 3M CC64 2017 2017-05-01 DO 1.3480731483 #> 7825 2063 3M CC64 2017 2017-05-01 DOSAT 4.0604430105 + #> 7826 2063 3M CC64 2017 2017-05-01 NO23 -5.5214609179 U #> 7827 2063 3M CC64 2017 2017-05-01 SALIN 3.5377658244 #> 7828 2063 3M CC64 2017 2017-05-01 TKN -0.2876820725 #> 7829 2063 3M CC64 2017 2017-05-01 TN -0.2850189550 + #> 7830 2063 3M CC64 2017 2017-05-01 TP -2.6736487744 #> 7831 2063 3M CC64 2017 2017-05-01 TURB 0.7419373447 #> 7832 2063 3M CC64 2017 2017-06-05 CHLAC 1.3862943611 A #> 7833 2063 3M CC64 2017 2017-06-05 COLOR 2.7080502011 #> 7834 2063 3M CC64 2017 2017-06-05 DO 2.1294214740 #> 7835 2063 3M CC64 2017 2017-06-05 DOSAT 4.8835592115 + #> 7836 2063 3M CC64 2017 2017-06-05 NO23 -4.5098600062 #> 7837 2063 3M CC64 2017 2017-06-05 SALIN 3.5322256441 #> 7838 2063 3M CC64 2017 2017-06-05 TKN -0.3147107448 #> 7839 2063 3M CC64 2017 2017-06-05 TN -0.2997546537 + #> 7840 2063 3M CC64 2017 2017-06-05 TP -2.5639498571 #> 7841 2063 3M CC64 2017 2017-06-05 TURB 0.8754687374 #> 7842 2063 3M CC64 2017 2017-07-10 CHLAC 2.2512917986 #> 7843 2063 3M CC64 2017 2017-07-10 COLOR 4.4426512565 #> 7844 2063 3M CC64 2017 2017-07-10 DO 0.8458682676 #> 7845 2063 3M CC64 2017 2017-07-10 DOSAT 3.5292973843 + #> 7846 2063 3M CC64 2017 2017-07-10 NO23 -4.6051701860 I #> 7847 2063 3M CC64 2017 2017-07-10 SALIN 2.7408400239 #> 7848 2063 3M CC64 2017 2017-07-10 TKN 0.0000000000 #> 7849 2063 3M CC64 2017 2017-07-10 TN 0.0039920213 + #> 7850 2063 3M CC64 2017 2017-07-10 TP -1.5141277326 #> 7851 2063 3M CC64 2017 2017-07-10 TURB 0.4054651081 #> 7852 2063 3M CC64 2017 2017-08-07 CHLAC 1.5892352051 #> 7853 2063 3M CC64 2017 2017-08-07 COLOR 4.5747109785 A #> 7854 2063 3M CC64 2017 2017-08-07 DO 0.4121096508 #> 7855 2063 3M CC64 2017 2017-08-07 DOSAT 3.0349529867 + #> 7856 2063 3M CC64 2017 2017-08-07 NO23 -3.7297014486 #> 7857 2063 3M CC64 2017 2017-08-07 SALIN 2.0693912058 #> 7858 2063 3M CC64 2017 2017-08-07 TKN -0.0202027073 #> 7859 2063 3M CC64 2017 2017-08-07 TN 0.0039920213 + #> 7860 2063 3M CC64 2017 2017-08-07 TP -1.6607312068 #> 7861 2063 3M CC64 2017 2017-08-07 TURB 0.6931471806 #> 7862 2063 3M CC64 2017 2017-09-05 CHLAC 1.6094379124 #> 7863 2063 3M CC64 2017 2017-09-05 COLOR 4.7874917428 #> 7864 2063 3M CC64 2017 2017-09-05 DO 0.8586616190 #> 7865 2063 3M CC64 2017 2017-09-05 DOSAT 3.4404180948 + #> 7866 2063 3M CC64 2017 2017-09-05 NO23 -3.0159349809 #> 7867 2063 3M CC64 2017 2017-09-05 SALIN 0.9001613499 #> 7868 2063 3M CC64 2017 2017-09-05 TKN -0.1508228897 #> 7869 2063 3M CC64 2017 2017-09-05 TN -0.0954101848 + #> 7870 2063 3M CC64 2017 2017-09-05 TP -2.0402208285 #> 7871 2063 3M CC64 2017 2017-09-05 TURB 0.5877866649 #> 7872 2063 3M CC64 2017 2017-10-02 CHLAC 1.3083328197 #> 7873 2063 3M CC64 2017 2017-10-02 COLOR 4.4998096703 #> 7874 2063 3M CC64 2017 2017-10-02 NO23 -3.1465551633 #> 7875 2063 3M CC64 2017 2017-10-02 TKN -0.9675840263 #> 7876 2063 3M CC64 2017 2017-10-02 TN -0.8603830999 + #> 7877 2063 3M CC64 2017 2017-10-02 TP -1.6094379124 #> 7878 2063 3M CC64 2017 2017-10-02 TURB 0.3364722366 #> 7879 2063 3M CC64 2017 2017-11-06 CHLAC 0.7419373447 #> 7880 2063 3M CC64 2017 2017-11-06 COLOR 3.5835189385 #> 7881 2063 3M CC64 2017 2017-11-06 DO 2.0014800002 #> 7882 2063 3M CC64 2017 2017-11-06 DOSAT 4.5890408041 + #> 7883 2063 3M CC64 2017 2017-11-06 NO23 -3.4420193762 #> 7884 2063 3M CC64 2017 2017-11-06 SALIN 3.0864866368 #> 7885 2063 3M CC64 2017 2017-11-06 TKN -0.5798184953 #> 7886 2063 3M CC64 2017 2017-11-06 TN -0.5242486441 + #> 7887 2063 3M CC64 2017 2017-11-06 TP -1.8971199849 #> 7888 2063 3M CC64 2017 2017-11-06 TURB 0.3364722366 #> 7889 2063 3M CC64 2017 2017-12-04 CHLAC 0.9162907319 #> 7890 2063 3M CC64 2017 2017-12-04 COLOR 3.1780538303 #> 7891 2063 3M CC64 2017 2017-12-04 DO 1.5644405465 #> 7892 2063 3M CC64 2017 2017-12-04 DOSAT 4.1287459889 #> 7893 2063 3M CC64 2017 2017-12-04 NO23 -4.5098600062 #> 7894 2063 3M CC64 2017 2017-12-04 SALIN 3.3403852423 #> 7895 2063 3M CC64 2017 2017-12-04 TKN -0.5276327421 #> 7896 2063 3M CC64 2017 2017-12-04 TN -0.5091603444 + #> 7897 2063 3M CC64 2017 2017-12-04 TP -2.2072749132 #> 7898 2063 3M CC64 2017 2017-12-04 TURB 0.3364722366 #> 7899 2063 3M CC64 2018 2018-01-02 CHLAC 2.7725887222 #> 7900 2063 3M CC64 2018 2018-01-02 COLOR 3.0910424534 #> 7901 2063 3M CC64 2018 2018-01-02 DOSAT 4.0360089852 + #> 7902 2063 3M CC64 2018 2018-01-02 NO23 -5.5214609179 U #> 7903 2063 3M CC64 2018 2018-01-02 SALIN 3.2657594108 #> 7904 2063 3M CC64 2018 2018-01-02 TKN -0.3147107448 #> 7905 2063 3M CC64 2018 2018-01-02 TN -0.3119747650 + #> 7906 2063 3M CC64 2018 2018-01-02 TP -1.6607312068 #> 7907 2063 3M CC64 2018 2018-01-02 TURB 2.3978952728 #> 7908 2063 3M CC64 2018 2018-03-05 CHLAC 0.5306282511 I #> 7909 2063 3M CC64 2018 2018-03-05 COLOR 2.6390573296 #> 7910 2063 3M CC64 2018 2018-03-05 DOSAT 4.2416144810 #> 7911 2063 3M CC64 2018 2018-03-05 NO23 -5.5214609179 I #> 7912 2063 3M CC64 2018 2018-03-05 SALIN 3.3467411959 #> 7913 2063 3M CC64 2018 2018-03-05 TKN -0.5621189182 #> 7914 2063 3M CC64 2018 2018-03-05 TN -0.5551258827 + #> 7915 2063 3M CC64 2018 2018-03-05 TP -2.1202635362 #> 7916 2063 3M CC64 2018 2018-03-05 TURB 0.4700036292 #> 7917 2063 3M CC64 2018 2018-04-02 CHLAC 0.7419373447 #> 7918 2063 3M CC64 2018 2018-04-02 COLOR 2.3978952728 #> 7919 2063 3M CC64 2018 2018-04-02 DO 1.5040773968 #> 7920 2063 3M CC64 2018 2018-04-02 DOSAT 3.4307561839 #> 7921 2063 3M CC64 2018 2018-04-02 NO23 -4.9618451299 I #> 7922 2063 3M CC64 2018 2018-04-02 SALIN 3.4330189940 #> 7923 2063 3M CC64 2018 2018-04-02 TKN -0.6539264674 #> 7924 2063 3M CC64 2018 2018-04-02 TN -0.6462635947 + #> 7925 2063 3M CC64 2018 2018-04-02 TP -2.2072749132 #> 7926 2063 3M CC64 2018 2018-04-02 TURB 0.7884573604 #> 7927 2063 3M CC64 2018 2018-05-07 CHLAC 1.4350845253 #> 7928 2063 3M CC64 2018 2018-05-07 COLOR 2.5649493575 #> 7929 2063 3M CC64 2018 2018-05-07 DO 1.3962446920 #> 7930 2063 3M CC64 2018 2018-05-07 DOSAT 4.0842942264 #> 7931 2063 3M CC64 2018 2018-05-07 NO23 -5.1159958098 I #> 7932 2063 3M CC64 2018 2018-05-07 SALIN 3.4388142452 #> 7933 2063 3M CC64 2018 2018-05-07 TKN -0.3424903089 #> 7934 2063 3M CC64 2018 2018-05-07 TN -0.3368723166 + #> 7935 2063 3M CC64 2018 2018-05-07 TP -2.0402208285 #> 7936 2063 3M CC64 2018 2018-05-07 TURB 1.0986122887 #> 7937 2063 3M CC64 2018 2018-07-09 CHLAC 0.9555114450 #> 7938 2063 3M CC64 2018 2018-07-09 COLOR 4.5747109785 #> 7939 2063 3M CC64 2018 2018-07-09 DO 0.6312717768 #> 7940 2063 3M CC64 2018 2018-07-09 DOSAT 3.2308043957 #> 7941 2063 3M CC64 2018 2018-07-09 NO23 -3.6119184130 #> 7942 2063 3M CC64 2018 2018-07-09 SALIN 1.8640801308 #> 7943 2063 3M CC64 2018 2018-07-09 TKN 0.0000000000 #> 7944 2063 3M CC64 2018 2018-07-09 TN 0.0266419309 + #> 7945 2063 3M CC64 2018 2018-07-09 TP -2.3025850930 #> 7946 2063 3M CC64 2018 2018-07-09 TURB 0.1823215568 #> 7947 2063 3M CC64 2018 2018-08-06 CHLAC 1.0986122887 #> 7948 2063 3M CC64 2018 2018-08-06 COLOR 4.5951198501 #> 7949 2063 3M CC64 2018 2018-08-06 DO 0.8796267475 #> 7950 2063 3M CC64 2018 2018-08-06 DOSAT 3.4339872045 #> 7951 2063 3M CC64 2018 2018-08-06 NO23 -3.4737680745 #> 7952 2063 3M CC64 2018 2018-08-06 SALIN 1.6448050563 #> 7953 2063 3M CC64 2018 2018-08-06 TKN -0.1508228897 #> 7954 2063 3M CC64 2018 2018-08-06 TN -0.1154108515 + #> 7955 2063 3M CC64 2018 2018-08-06 TP -2.3227878003 #> 7956 2063 3M CC64 2018 2018-08-06 TURB 0.5877866649 #> 7957 2063 3M CC64 2019 2019-02-04 CHLAC 1.1314021115 #> 7958 2063 3M CC64 2019 2019-02-04 COLOR 3.0910424534 #> 7959 2063 3M CC64 2019 2019-02-04 DO 1.8764069433 #> 7960 2063 3M CC64 2019 2019-02-04 DOSAT 4.4200447019 #> 7961 2063 3M CC64 2019 2019-02-04 NO23 -4.8283137373 I #> 7962 2063 3M CC64 2019 2019-02-04 SALIN 3.0928589843 #> 7963 2063 3M CC64 2019 2019-02-04 TKN -0.7765287895 #> 7964 2063 3M CC64 2019 2019-02-04 TN -0.7678707268 + #> 7965 2063 3M CC64 2019 2019-02-04 TP -2.3025850930 #> 7966 2063 3M CC64 2019 2019-02-04 TURB 0.6418538862 #> 7967 2063 3M CC64 2019 2019-03-04 CHLAC 0.8329091229 #> 7968 2063 3M CC64 2019 2019-03-04 COLOR 3.1354942159 #> 7969 2063 3M CC64 2019 2019-03-04 DO 1.6014057407 #> 7970 2063 3M CC64 2019 2019-03-04 DOSAT 4.2297491992 #> 7971 2063 3M CC64 2019 2019-03-04 NO23 -4.8283137373 I #> 7972 2063 3M CC64 2019 2019-03-04 SALIN 2.9992261628 #> 7973 2063 3M CC64 2019 2019-03-04 TKN -0.5798184953 #> 7974 2063 3M CC64 2019 2019-03-04 TN -0.5727010275 + #> 7975 2063 3M CC64 2019 2019-03-04 TP -2.3025850930 #> 7976 2063 3M CC64 2019 2019-03-04 TURB 0.5306282511 #> 7977 2063 3M CC64 2019 2019-04-01 CHLAC 0.4700036292 I #> 7978 2063 3M CC64 2019 2019-04-01 COLOR 2.7725887222 #> 7979 2063 3M CC64 2019 2019-04-01 DO 1.3962446920 #> 7980 2063 3M CC64 2019 2019-04-01 DOSAT 3.9889840466 #> 7981 2063 3M CC64 2019 2019-04-01 NO23 -4.5098600062 #> 7982 2063 3M CC64 2019 2019-04-01 SALIN 3.1210424645 #> 7983 2063 3M CC64 2019 2019-04-01 TKN -0.5276327421 #> 7984 2063 3M CC64 2019 2019-04-01 TN -0.5091603444 + #> 7985 2063 3M CC64 2019 2019-04-01 TP -2.3126354288 #> 7986 2063 3M CC64 2019 2019-04-01 TURB 0.4700036292 #> 7987 2063 3M CC64 2019 2019-05-06 CHLAC 0.6931471806 I #> 7988 2063 3M CC64 2019 2019-05-06 COLOR 2.9444389792 #> 7989 2063 3M CC64 2019 2019-05-06 DO 0.8372475245 #> 7990 2063 3M CC64 2019 2019-05-06 DOSAT 3.5292973843 #> 7991 2063 3M CC64 2019 2019-05-06 NO23 -4.6051701860 I #> 7992 2063 3M CC64 2019 2019-05-06 SALIN 3.2331731296 #> 7993 2063 3M CC64 2019 2019-05-06 TKN -0.5621189182 #> 7994 2063 3M CC64 2019 2019-05-06 TN -0.5551258827 + #> 7995 2063 3M CC64 2019 2019-05-06 TP -2.2072749132 #> 7996 2063 3M CC64 2019 2019-05-06 TURB 0.2623642645 #> 7997 2063 3M CC64 2019 2019-06-03 CHLAC 0.7419373447 I #> 7998 2063 3M CC64 2019 2019-06-03 COLOR 2.8903717579 #> 7999 2063 3M CC64 2019 2019-06-03 DO 1.2974631474 #> 8000 2063 3M CC64 2019 2019-06-03 DOSAT 3.7220724215 #> 8001 2063 3M CC64 2019 2019-06-03 NO23 -5.2983173665 I #> 8002 2063 3M CC64 2019 2019-06-03 SALIN 3.2703291065 #> 8003 2063 3M CC64 2019 2019-06-03 TKN -0.3856624808 #> 8004 2063 3M CC64 2019 2019-06-03 TN -0.3797973614 + #> 8005 2063 3M CC64 2019 2019-06-03 TP -2.3025850930 #> 8006 2063 3M CC64 2019 2019-06-03 TURB 0.2623642645 #> 8007 2063 3M CC64 2019 2019-07-01 CHLAC 1.0986122887 #> 8008 2063 3M CC64 2019 2019-07-01 COLOR 2.8903717579 #> 8009 2063 3M CC64 2019 2019-07-01 DO 1.4036429995 #> 8010 2063 3M CC64 2019 2019-07-01 DOSAT 4.1108738642 #> 8011 2063 3M CC64 2019 2019-07-01 NO23 -5.1159958098 I #> 8012 2063 3M CC64 2019 2019-07-01 SALIN 3.1675825305 #> 8013 2063 3M CC64 2019 2019-07-01 TKN -0.4780358009 #> 8014 2063 3M CC64 2019 2019-07-01 TN -0.4716049106 + #> 8015 2063 3M CC64 2019 2019-07-01 TP -2.2072749132 #> 8016 2063 3M CC64 2019 2019-07-01 TURB 0.5877866649 #> 8017 2063 3M CC64 2019 2019-08-05 CHLAC 1.7578579176 #> 8018 2063 3M CC64 2019 2019-08-05 COLOR 3.9120230054 #> 8019 2063 3M CC64 2019 2019-08-05 DO 1.3001916621 #> 8020 2063 3M CC64 2019 2019-08-05 DOSAT 3.9702919136 #> 8021 2063 3M CC64 2019 2019-08-05 NO23 -5.5214609179 U #> 8022 2063 3M CC64 2019 2019-08-05 SALIN 2.8273136219 #> 8023 2063 3M CC64 2019 2019-08-05 TKN -0.1863295782 #> 8024 2063 3M CC64 2019 2019-08-05 TN -0.1839228382 + #> 8025 2063 3M CC64 2019 2019-08-05 TP -1.8325814637 #> 8026 2063 3M CC64 2019 2019-08-05 TURB 0.4700036292 #> 8027 2063 3M CC64 2019 2019-10-07 CHLAC 1.1939224685 #> 8028 2063 3M CC64 2019 2019-10-07 COLOR 3.2958368660 #> 8029 2063 3M CC64 2019 2019-10-07 DO 1.6863989536 #> 8030 2063 3M CC64 2019 2019-10-07 DOSAT 4.3412046402 #> 8031 2063 3M CC64 2019 2019-10-07 NO23 -5.1159958098 I #> 8032 2063 3M CC64 2019 2019-10-07 SALIN 3.2672849641 #> 8033 2063 3M CC64 2019 2019-10-07 TKN -0.4780358009 #> 8034 2063 3M CC64 2019 2019-10-07 TN -0.4716049106 + #> 8035 2063 3M CC64 2019 2019-10-07 TP -2.1202635362 #> 8036 2063 3M CC64 2019 2019-10-07 TURB 0.2623642645 #> 8037 2063 3M CC64 2019 2019-11-04 CHLAC 1.1939224685 #> 8038 2063 3M CC64 2019 2019-11-04 COLOR 3.1354942159 #> 8039 2063 3M CC64 2019 2019-11-04 DO 1.3110318766 #> 8040 2063 3M CC64 2019 2019-11-04 DOSAT 3.9646154555 #> 8041 2063 3M CC64 2019 2019-11-04 NO23 -4.6051701860 #> 8042 2063 3M CC64 2019 2019-11-04 SALIN 3.2503744919 #> 8043 2063 3M CC64 2019 2019-11-04 TKN -0.4307829161 #> 8044 2063 3M CC64 2019 2019-11-04 TN -0.4155154440 + #> 8045 2063 3M CC64 2019 2019-11-04 TP -2.1202635362 #> 8046 2063 3M CC64 2019 2019-11-04 TURB 0.0953101798 #> 8047 2063 3M CC64 2020 2020-01-06 CHLAC 1.0296194172 #> 8048 2063 3M CC64 2020 2020-01-06 COLOR 2.8332133441 #> 8049 2063 3M CC64 2020 2020-01-06 DO 1.6937790609 #> 8050 2063 3M CC64 2020 2020-01-06 DOSAT 4.2312037449 #> 8051 2063 3M CC64 2020 2020-01-06 NO23 -4.0745419349 #> 8052 2063 3M CC64 2020 2020-01-06 SALIN 3.2188758249 #> 8053 2063 3M CC64 2020 2020-01-06 TKN -0.4155154440 #> 8054 2063 3M CC64 2020 2020-01-06 TN -0.3900840061 + #> 8055 2063 3M CC64 2020 2020-01-06 TP -2.2072749132 #> 8056 2063 3M CC64 2020 2020-01-06 TURB 0.6931471806 #> 8057 2063 3M CC64 2020 2020-02-03 CHLAC 0.2623642645 I #> 8058 2063 3M CC64 2020 2020-02-03 COLOR 2.8332133441 #> 8059 2063 3M CC64 2020 2020-02-03 DO 1.5789787049 #> 8060 2063 3M CC64 2020 2020-02-03 DOSAT 4.0842942264 #> 8061 2063 3M CC64 2020 2020-02-03 NO23 -3.5755507688 #> 8062 2063 3M CC64 2020 2020-02-03 SALIN 3.2104403460 #> 8063 2063 3M CC64 2020 2020-02-03 TKN -0.6539264674 #> 8064 2063 3M CC64 2020 2020-02-03 TN -0.6014799920 + #> 8065 2063 3M CC64 2020 2020-02-03 TP -2.3434070875 #> 8066 2063 3M CC64 2020 2020-02-03 TURB 0.9162907319 #> 8067 2063 3M CC64 2020 2020-03-02 CHLAC 0.6931471806 I #> 8068 2063 3M CC64 2020 2020-03-02 COLOR 2.5649493575 A #> 8069 2063 3M CC64 2020 2020-03-02 DO 1.7749523509 #> 8070 2063 3M CC64 2020 2020-03-02 DOSAT 4.3067641502 #> 8071 2063 3M CC64 2020 2020-03-02 NO23 -5.5214609179 I #> 8072 2063 3M CC64 2020 2020-03-02 SALIN 3.2924979647 #> 8073 2063 3M CC64 2020 2020-03-02 TKN -0.8915981193 #> 8074 2063 3M CC64 2020 2020-03-02 TN -0.8818893052 + #> 8075 2063 3M CC64 2020 2020-03-02 TP -2.3968957725 #> 8076 2063 3M CC64 2020 2020-03-02 TURB 0.2623642645 #> 8077 2063 3M CC64 2020 2020-09-08 CHLAC 2.3025850930 A #> 8078 2063 3M CC64 2020 2020-09-08 COLOR 4.0253516907 #> 8079 2063 3M CC64 2020 2020-09-08 DO 0.1484200051 #> 8080 2063 3M CC64 2020 2020-09-08 DOSAT 2.8332133441 #> 8081 2063 3M CC64 2020 2020-09-08 NO23 -5.1159958098 I #> 8082 2063 3M CC64 2020 2020-09-08 SALIN 2.9693882982 #> 8083 2063 3M CC64 2020 2020-09-08 TKN -0.2231435513 #> 8084 2063 3M CC64 2020 2020-09-08 TN -0.2181560098 + #> 8085 2063 3M CC64 2020 2020-09-08 TP -1.5141277326 #> 8086 2063 3M CC64 2020 2020-09-08 TURB 0.5306282511 #> 8087 2063 3M CC64 2020 2020-10-05 CHLAC 1.5040773968 #> 8088 2063 3M CC64 2020 2020-10-05 COLOR 4.2626798770 #> 8089 2063 3M CC64 2020 2020-10-05 DO 1.1600209168 #> 8090 2063 3M CC64 2020 2020-10-05 DOSAT 3.7495040759 #> 8091 2063 3M CC64 2020 2020-10-05 NO23 -3.0365542681 #> 8092 2063 3M CC64 2020 2020-10-05 SALIN 2.5649493575 #> 8093 2063 3M CC64 2020 2020-10-05 TKN -0.0408219945 #> 8094 2063 3M CC64 2020 2020-10-05 TN 0.0079681696 + #> 8095 2063 3M CC64 2020 2020-10-05 TP -1.8971199849 #> 8096 2063 3M CC64 2020 2020-10-05 TURB 0.0953101798 #> 8097 2063 3M CC64 2020 2020-11-02 CHLAC 1.1631508098 I #> 8098 2063 3M CC64 2020 2020-11-02 COLOR 4.0073331852 A #> 8099 2063 3M CC64 2020 2020-11-02 NO23 -3.9633162998 #> 8100 2063 3M CC64 2020 2020-11-02 SALIN 2.7562052430 #> 8101 2063 3M CC64 2020 2020-11-02 TKN -0.3710636814 #> 8102 2063 3M CC64 2020 2020-11-02 TN -0.3438997525 + #> 8103 2063 3M CC64 2020 2020-11-02 TP -2.0402208285 #> 8104 2063 3M CC64 2020 2020-11-02 TURB 0.2623642645 #> 8105 2063 3M CC64 2020 2020-12-07 CHLAC 0.3364722366 I #> 8106 2063 3M CC64 2020 2020-12-07 COLOR 3.6635616461 #> 8107 2063 3M CC64 2020 2020-12-07 DO 1.6677068206 #> 8108 2063 3M CC64 2020 2020-12-07 DOSAT 4.1743872699 #> 8109 2063 3M CC64 2020 2020-12-07 NO23 -3.8167128256 #> 8110 2063 3M CC64 2020 2020-12-07 SALIN 2.9982291538 #> 8111 2063 3M CC64 2020 2020-12-07 TKN -0.3856624808 #> 8112 2063 3M CC64 2020 2020-12-07 TN -0.3538218750 + #> 8113 2063 3M CC64 2020 2020-12-07 TP -2.4769384801 #> 8114 2063 3M CC64 2020 2020-12-07 TURB 0.1823215568 #> 8115 2063 3M CC64 2021 2021-01-04 CHLAC 0.3364722366 I #> 8116 2063 3M CC64 2021 2021-01-04 COLOR 3.1780538303 #> 8117 2063 3M CC64 2021 2021-01-04 DO 1.4816045409 #> 8118 2063 3M CC64 2021 2021-01-04 DOSAT 4.0271358125 #> 8119 2063 3M CC64 2021 2021-01-04 NO23 -4.1351665567 #> 8120 2063 3M CC64 2021 2021-01-04 SALIN 3.1376657694 #> 8121 2063 3M CC64 2021 2021-01-04 TKN -0.5276327421 #> 8122 2063 3M CC64 2021 2021-01-04 TN -0.5008752929 + #> 8123 2063 3M CC64 2021 2021-01-04 TP -2.3025850930 #> 8124 2063 3M CC64 2021 2021-01-04 TURB 0.2623642645 #> 8125 2063 3M CC64 2021 2021-02-01 CHLAC 0.9932517730 #> 8126 2063 3M CC64 2021 2021-02-01 COLOR 2.8332133441 #> 8127 2063 3M CC64 2021 2021-02-01 DO 1.8082887712 #> 8128 2063 3M CC64 2021 2021-02-01 DOSAT 4.3489867806 #> 8129 2063 3M CC64 2021 2021-02-01 NO23 -4.9618451299 I #> 8130 2063 3M CC64 2021 2021-02-01 SALIN 3.2120525995 #> 8131 2063 3M CC64 2021 2021-02-01 TKN -0.5276327421 #> 8132 2063 3M CC64 2021 2021-02-01 TN -0.5208759596 + #> 8133 2063 3M CC64 2021 2021-02-01 TP -2.3751557858 #> 8134 2063 3M CC64 2021 2021-02-01 TURB 1.1631508098 #> 8135 2063 3M CC64 2021 2021-03-01 CHLAC 0.6418538862 I #> 8136 2063 3M CC64 2021 2021-03-01 COLOR 2.6390573296 #> 8137 2063 3M CC64 2021 2021-03-01 DO 1.5454325825 #> 8138 2063 3M CC64 2021 2021-03-01 DOSAT 4.1956970565 #> 8139 2063 3M CC64 2021 2021-03-01 NO23 -4.8283137373 I #> 8140 2063 3M CC64 2021 2021-03-01 SALIN 3.2861605717 #> 8141 2063 3M CC64 2021 2021-03-01 TKN -0.9675840263 I #> 8142 2063 3M CC64 2021 2021-03-01 TN -1.8078888512 + #> 8143 2063 3M CC64 2021 2021-03-01 TP -2.3859667019 #> 8144 2063 3M CC64 2021 2021-03-01 TURB 0.6931471806 A #> 8145 2063 3M CC64 2021 2021-04-05 CHLAC 1.5475625087 #> 8146 2063 3M CC64 2021 2021-04-05 COLOR 2.7080502011 #> 8147 2063 3M CC64 2021 2021-04-05 DO 1.6505798558 #> 8148 2063 3M CC64 2021 2021-04-05 DOSAT 4.2370008626 #> 8149 2063 3M CC64 2021 2021-04-05 NO23 -5.5214609179 U #> 8150 2063 3M CC64 2021 2021-04-05 SALIN 3.3010086544 #> 8151 2063 3M CC64 2021 2021-04-05 TN -0.4277107171 + #> 8152 2063 3M CC64 2021 2021-04-05 TP -2.2072749132 #> 8153 2063 3M CC64 2021 2021-04-05 TURB 1.2527629685 #> 8154 2063 3M CC64 2021 2021-05-03 CHLAC 0.9932517730 #> 8155 2063 3M CC64 2021 2021-05-03 COLOR 2.9957322736 #> 8156 2063 3M CC64 2021 2021-05-03 DO 1.2584609896 #> 8157 2063 3M CC64 2021 2021-05-03 DOSAT 3.9740583963 #> 8158 2063 3M CC64 2021 2021-05-03 NO23 -5.5214609179 U #> 8159 2063 3M CC64 2021 2021-05-03 SALIN 3.3641875560 #> 8160 2063 3M CC64 2021 2021-05-03 TKN -0.7133498879 #> 8161 2063 3M CC64 2021 2021-05-03 TN -0.7092765625 + #> 8162 2063 3M CC64 2021 2021-05-03 TP -2.3227878003 #> 8163 2063 3M CC64 2021 2021-05-03 TURB 0.7419373447 #> 8164 2063 3M CC64 2021 2021-06-07 CHLAC 1.7578579176 #> 8165 2063 3M CC64 2021 2021-06-07 COLOR 2.8332133441 #> 8166 2063 3M CC64 2021 2021-06-07 DO 0.9707789172 #> 8167 2063 3M CC64 2021 2021-06-07 DOSAT 3.6788291183 #> 8168 2063 3M CC64 2021 2021-06-07 NO23 -4.3428059215 #> 8169 2063 3M CC64 2021 2021-06-07 SALIN 3.2839142210 #> 8170 2063 3M CC64 2021 2021-06-07 TKN -0.4620354596 #> 8171 2063 3M CC64 2021 2021-06-07 TN -0.4416105547 + #> 8172 2063 3M CC64 2021 2021-06-07 TP -2.4304184645 #> 8173 2063 3M CC64 2021 2021-06-07 TURB 0.4054651081 #> 8174 2063 3M CC64 2021 2021-08-02 CHLAC 1.6094379124 #> 8175 2063 3M CC64 2021 2021-08-02 COLOR 4.3438054219 #> 8176 2063 3M CC64 2021 2021-08-02 DO 1.4255150743 #> 8177 2063 3M CC64 2021 2021-08-02 DOSAT 4.1092331747 #> 8178 2063 3M CC64 2021 2021-08-02 NO23 -4.8283137373 I #> 8179 2063 3M CC64 2021 2021-08-02 SALIN 2.4292177439 #> 8180 2063 3M CC64 2021 2021-08-02 TKN -0.1278333715 #> 8181 2063 3M CC64 2021 2021-08-02 TN -0.1232982163 + #> 8182 2063 3M CC64 2021 2021-08-02 TP -1.7719568419 #> 8183 2063 3M CC64 2021 2021-08-02 TURB 0.6418538862 #> 8184 2063 3M CC64 2021 2021-09-07 CHLAC 0.9555114450 #> 8185 2063 3M CC64 2021 2021-09-07 COLOR 4.1271343850 #> 8186 2063 3M CC64 2021 2021-09-07 DO 0.9820784724 #> 8187 2063 3M CC64 2021 2021-09-07 DOSAT 3.6375861597 #> 8188 2063 3M CC64 2021 2021-09-07 NO23 -3.8167128256 #> 8189 2063 3M CC64 2021 2021-09-07 SALIN 2.5687881338 #> 8190 2063 3M CC64 2021 2021-09-07 TKN -0.1053605157 #> 8191 2063 3M CC64 2021 2021-09-07 TN -0.0812100554 + #> 8192 2063 3M CC64 2021 2021-09-07 TP -1.8325814637 #> 8193 2063 3M CC64 2021 2021-09-07 TURB 0.0953101798 #> 8194 2063 3M CC64 2021 2021-10-04 CHLAC 1.1939224685 #> 8195 2063 3M CC64 2021 2021-10-04 COLOR 3.7841896339 #> 8196 2063 3M CC64 2021 2021-10-04 DO 1.0577902941 #> 8197 2063 3M CC64 2021 2021-10-04 DOSAT 3.7135720667 #> 8198 2063 3M CC64 2021 2021-10-04 NO23 -4.7105307016 I #> 8199 2063 3M CC64 2021 2021-10-04 SALIN 2.9069010598 #> 8200 2063 3M CC64 2021 2021-10-04 TKN -0.3566749439 #> 8201 2063 3M CC64 2021 2021-10-04 TN -0.3509769228 + #> 8202 2063 3M CC64 2021 2021-10-04 TP -1.8325814637 #> 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2022 2022-06-06 CHLAC 1.9459101491 #> 8275 2063 3M CC64 2022 2022-06-06 COLOR 3.7612001157 A #> 8276 2063 3M CC64 2022 2022-06-06 DO 1.3987168811 #> 8277 2063 3M CC64 2022 2022-06-06 DOSAT 4.0775374439 #> 8278 2063 3M CC64 2022 2022-06-06 NO23 -4.7105307016 I #> 8279 2063 3M CC64 2022 2022-06-06 SALIN 3.2588654731 #> 8280 2063 3M CC64 2022 2022-06-06 TKN -0.1165338163 #> 8281 2063 3M CC64 2022 2022-06-06 TN -0.1120495038 + #> 8282 2063 3M CC64 2022 2022-06-06 TP -2.4304184645 #> 8283 2063 3M CC64 2022 2022-06-06 TURB 1.0647107370 #> 8284 2063 3M CC64 2022 2022-07-05 CHLAC 1.6292405397 #> 8285 2063 3M CC64 2022 2022-07-05 COLOR 2.8903717579 #> 8286 2063 3M CC64 2022 2022-07-05 NO23 -5.2983173665 I #> 8287 2063 3M CC64 2022 2022-07-05 SALIN 3.2534704696 #> 8288 2063 3M CC64 2022 2022-07-05 TKN -0.5447271754 #> 8289 2063 3M CC64 2022 2022-07-05 TN -0.5378542962 + #> 8290 2063 3M CC64 2022 2022-07-05 TP -2.1202635362 #> 8291 2063 3M CC64 2022 2022-07-05 TURB 0.0953101798 #> 8292 2063 3M 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3M CC64 2022 2022-09-06 TP -1.8325814637 #> 8311 2063 3M CC64 2022 2022-09-06 TURB 0.7419373447 #> 8312 2063 3M CC64 2022 2022-11-07 CHLAC 0.8754687374 I #> 8313 2063 3M CC64 2022 2022-11-07 COLOR 4.2341065046 #> 8314 2063 3M CC64 2022 2022-11-07 DO 0.9360933592 #> 8315 2063 3M CC64 2022 2022-11-07 DOSAT 3.5263605246 #> 8316 2063 3M CC64 2022 2022-11-07 NO23 -3.2968373663 #> 8317 2063 3M CC64 2022 2022-11-07 SALIN 2.6049094422 #> 8318 2063 3M CC64 2022 2022-11-07 TKN -0.2744368457 #> 8319 2063 3M CC64 2022 2022-11-07 TN -0.2269006002 + #> 8320 2063 3M CC64 2022 2022-11-07 TP -1.7147984281 #> 8321 2063 3M CC64 2022 2022-11-07 TURB 0.1823215568 #> 8322 2063 3M CC64 2022 2022-12-05 CHLAC 1.0296194172 #> 8323 2063 3M CC64 2022 2022-12-05 COLOR 3.6109179126 #> 8324 2063 3M CC64 2022 2022-12-05 DO 1.3190856114 #> 8325 2063 3M CC64 2022 2022-12-05 DOSAT 3.8918202981 #> 8326 2063 3M CC64 2022 2022-12-05 NO23 -2.8647040111 #> 8327 2063 3M CC64 2022 2022-12-05 SALIN 2.9992261628 #> 8328 2063 3M CC64 2022 2022-12-05 TKN -0.4004775666 #> 8329 2063 3M CC64 2022 2022-12-05 TN -0.3188288014 + #> 8330 2063 3M CC64 2022 2022-12-05 TP -1.7719568419 #> 8331 2063 3M CC64 2022 2022-12-05 TURB 1.0296194172 #> 8332 2063 3M CC64 2023 2023-01-03 CHLAC 1.3083328197 #> 8333 2063 3M CC64 2023 2023-01-03 COLOR 2.7080502011 #> 8334 2063 3M CC64 2023 2023-01-03 DO 1.6524974019 #> 8335 2063 3M CC64 2023 2023-01-03 DOSAT 3.6133473915 #> 8336 2063 3M CC64 2023 2023-01-03 NO23 -3.2188758249 #> 8337 2063 3M CC64 2023 2023-01-03 SALIN 3.1582762027 #> 8338 2063 3M CC64 2023 2023-01-03 TKN -0.7133498879 #> 8339 2063 3M CC64 2023 2023-01-03 TN -0.6348782724 + #> 8340 2063 3M CC64 2023 2023-01-03 TP -1.9661128564 #> 8341 2063 3M CC64 2023 2023-01-03 TURB 0.2623642645 #> 8342 2063 3M CC64 2023 2023-02-06 CHLAC 1.0986122887 #> 8343 2063 3M CC64 2023 2023-02-06 COLOR 2.7725887222 #> 8344 2063 3M CC64 2023 2023-02-06 DO 1.4586150227 #> 8345 2063 3M CC64 2023 2023-02-06 DOSAT 4.0430512678 #> 8346 2063 3M CC64 2023 2023-02-06 NO23 -4.2686979494 #> 8347 2063 3M CC64 2023 2023-02-06 SALIN 3.2284300377 #> 8348 2063 3M CC64 2023 2023-02-06 TKN -0.4942963218 #> 8349 2063 3M CC64 2023 2023-02-06 TN -0.4716049106 + #> 8350 2063 3M CC64 2023 2023-02-06 TP -2.0402208285 #> 8351 2063 3M CC64 2023 2023-02-06 TURB 0.6418538862 #> 8352 2063 3M CC64 2023 2023-03-06 CHLAC 0.9932517730 #> 8353 2063 3M CC64 2023 2023-03-06 COLOR 2.7725887222 #> 8354 2063 3M CC64 2023 2023-03-06 DO 1.3962446920 #> 8355 2063 3M CC64 2023 2023-03-06 DOSAT 4.0758410907 #> 8356 2063 3M CC64 2023 2023-03-06 NO23 -4.9618451299 I #> 8357 2063 3M CC64 2023 2023-03-06 SALIN 3.3170908724 #> 8358 2063 3M CC64 2023 2023-03-06 TKN -0.6161861394 #> 8359 2063 3M CC64 2023 2023-03-06 TN -0.6088060321 + #> 8360 2063 3M CC64 2023 2023-03-06 TP -2.0402208285 #> 8361 2063 3M CC64 2023 2023-03-06 TURB 0.8754687374 #> 8362 2063 3M CC64 2014 2014-01-07 CHLAC 1.0986122887 #> 8363 2063 3M CC64 2014 2014-01-07 TN -0.9942522733 #> 8364 2063 3M CC64 2014 2014-01-07 TP -2.5510464523 #> 8365 2063 3M CC64 2014 2014-02-04 CHLAC 0.0000000000 #> 8366 2063 3M CC64 2014 2014-02-04 TN -1.0498221245 #> 8367 2063 3M CC64 2014 2014-02-04 TP -2.6310891600 #> 8368 2063 3M CC64 2014 2014-03-04 CHLAC 1.3862943611 #> 8369 2063 3M CC64 2014 2014-03-04 TN -0.5978370008 #> 8370 2063 3M CC64 2014 2014-03-04 TP -2.7333680091 #> 8371 2063 3M CC64 2014 2014-04-01 CHLAC 1.0986122887 #> 8372 2063 3M CC64 2014 2014-04-01 TN -1.0788096614 #> 8373 2063 3M CC64 2014 2014-04-01 TP -2.7181005370 #> 8374 2063 3M CC64 2014 2014-06-03 CHLAC 1.3862943611 #> 8375 2063 3M CC64 2014 2014-06-03 TN -0.5798184953 #> 8376 2063 3M CC64 2014 2014-06-03 TP -2.2072749132 #> 8377 2063 3M CC64 2014 2014-09-02 CHLAC 3.1354942159 #> 8378 2063 3M CC64 2014 2014-09-02 TP -2.3126354288 #> 8379 2063 3M CC64 2014 2014-11-04 CHLAC 0.6931471806 #> 8380 2063 3M CC64 2014 2014-11-04 TN -0.5798184953 #> 8381 2063 3M CC64 2014 2014-11-04 TP -2.6310891600 #> 8382 2063 3M CC64 2014 2014-12-02 CHLAC 0.0000000000 #> 8383 2063 3M CC64 2014 2014-12-02 TN -0.4942963218 #> 8384 2063 3M CC64 2014 2014-12-02 TP -2.3751557858 #> 8385 2063 3M CC64 2015 2015-01-03 CHLAC 0.0000000000 #> 8386 2063 3M CC64 2015 2015-01-03 TN -0.3011050928 #> 8387 2063 3M CC64 2015 2015-01-03 TP -1.8018098051 #> 8388 2063 3M CC64 2015 2015-02-02 CHLAC 0.6931471806 #> 8389 2063 3M CC64 2015 2015-03-03 CHLAC 0.0000000000 #> 8390 2063 3M CC64 2015 2015-03-03 TN -0.5798184953 #> 8391 2063 3M CC64 2015 2015-03-03 TP -2.2730262908 #> 8392 2063 3M CC64 2015 2015-04-02 CHLAC 0.6931471806 #> 8393 2063 3M CC64 2015 2015-04-02 TN -0.4462871026 #> 8394 2063 3M CC64 2015 2015-04-02 TP -2.2926347621 #> 8395 2063 3M CC64 2015 2015-05-05 CHLAC 1.0986122887 #> 8396 2063 3M CC64 2015 2015-05-05 TN -0.8209805521 #> 8397 2063 3M CC64 2015 2015-05-05 TP -2.5257286443 #> 8398 2063 3M CC64 2015 2015-09-09 CHLAC 1.0986122887 #> 8399 2063 3M CC64 2015 2015-09-09 TN -0.5978370008 #> 8400 2063 3M CC64 2015 2015-09-09 TP -2.9759296463 #> 8401 2063 3M CC64 2015 2015-10-07 CHLAC 1.6094379124 #> 8402 2063 3M CC64 2015 2015-11-04 CHLAC 1.0986122887 #> 8403 2063 3M CC64 2015 2015-11-04 TN -0.6539264674 #> 8404 2063 3M CC64 2015 2015-11-04 TP -2.6172958378 #> 8405 2063 3M CC64 2015 2015-11-15 CHLAC 1.6094379124 #> 8406 2063 3M CC64 2015 2015-11-15 TN -0.8439700703 #> 8407 2063 3M CC64 2015 2015-11-15 TP -2.7968814148 #> 8408 2063 3M CC64 2016 2016-01-06 TN -0.1053605157 #> 8409 2063 3M CC64 2016 2016-01-06 TP -2.3126354288 #> 8410 2063 3M CC64 2016 2016-02-02 CHLAC 1.6094379124 #> 8411 2063 3M CC64 2016 2016-02-02 TN -0.2231435513 #> 8412 2063 3M CC64 2016 2016-02-02 TP -2.9957322736 #> 8413 2063 3M CC64 2016 2016-06-11 CHLAC 2.5649493575 #> 8414 2063 3M CC64 2016 2016-06-11 TN -0.8439700703 #> 8415 2063 3M CC64 2016 2016-06-11 TP -2.7488721956 #> 8416 2063 3M CC64 2016 2016-07-08 CHLAC 1.0986122887 #> 8417 2063 3M CC64 2016 2016-07-08 TN -0.7765287895 #> 8418 2063 3M CC64 2016 2016-07-08 TP -3.7722610631 #> 8419 2063 3M CC64 2016 2016-10-03 CHLAC 1.0986122887 #> 8420 2063 3M CC64 2016 2016-10-03 TN -0.2231435513 #> 8421 2063 3M CC64 2016 2016-10-03 TP -2.0874737134 #> 8422 2063 3M CC64 2018 2018-12-04 CHLAC 1.0986122887 #> 8423 2063 3M CC64 2018 2018-12-04 TN -0.7985076962 #> 8424 2063 3M CC64 2018 2018-12-04 TP -2.3644604967 #> 8425 2063 3M CC64 2019 2019-01-09 CHLAC 0.6931471806 I #> 8426 2063 3M CC64 2019 2019-01-09 TN -1.2039728043 #> 8427 2063 3M CC64 2019 2019-01-09 TP -2.7333680091 #> 8428 2065B 2 CC67 2015 2015-04-07 CHLAC 0.6931471806 #> 8429 2065B 2 CC67 2015 2015-04-07 COLOR 3.4011973817 #> 8430 2065B 2 CC67 2015 2015-04-07 COND 10.6960274770 #> 8431 2065B 2 CC67 2015 2015-04-07 DO 1.8164520818 #> 8432 2065B 2 CC67 2015 2015-04-07 DOSAT 4.4931206822 + #> 8433 2065B 2 CC67 2015 2015-04-07 NO23 -5.1159958098 I #> 8434 2065B 2 CC67 2015 2015-04-07 SALIN 3.3492020865 #> 8435 2065B 2 CC67 2015 2015-04-07 TKN -0.2587707290 #> 8436 2065B 2 CC67 2015 2015-04-07 TN -0.2510287548 #> 8437 2065B 2 CC67 2015 2015-04-07 TP -2.4079456087 #> 8438 2065B 2 CC67 2015 2015-04-07 TSS 2.2257040487 #> 8439 2065B 2 CC67 2015 2015-04-07 TURB 0.2623642645 #> 8440 2065B 2 CC67 2015 2015-04-07 COND 10.6958011046 #> 8441 2065B 2 CC67 2015 2015-04-07 DO 1.8033586051 #> 8442 2065B 2 CC67 2015 2015-04-07 DOSAT 4.4796069630 + #> 8443 2065B 2 CC67 2015 2015-04-07 SALIN 3.3488509013 #> 8444 2065B 2 CC67 2015 2015-11-03 CHLAC 2.0476928434 #> 8445 2065B 2 CC67 2015 2015-11-03 COLOR 4.0073331852 #> 8446 2065B 2 CC67 2015 2015-11-03 COND 10.5339611386 #> 8447 2065B 2 CC67 2015 2015-11-03 DO 2.0731719287 #> 8448 2065B 2 CC67 2015 2015-11-03 DOSAT 4.7723781050 + #> 8449 2065B 2 CC67 2015 2015-11-03 NO23 -5.5214609179 U #> 8450 2065B 2 CC67 2015 2015-11-03 SALIN 3.1658969001 #> 8451 2065B 2 CC67 2015 2015-11-03 TKN -0.4557063245 #> 8452 2065B 2 CC67 2015 2015-11-03 TN -0.4557063245 #> 8453 2065B 2 CC67 2015 2015-11-03 TP -2.0557250151 #> 8454 2065B 2 CC67 2015 2015-11-03 TSS 1.7369512327 #> 8455 2065B 2 CC67 2015 2015-11-03 TURB -0.3566749439 #> 8456 2065B 2 CC67 2015 2015-11-03 COND 10.5312958918 #> 8457 2065B 2 CC67 2015 2015-11-03 DO 2.0955609236 #> 8458 2065B 2 CC67 2015 2015-11-03 DOSAT 4.7966166506 + #> 8459 2065B 2 CC67 2015 2015-11-03 SALIN 3.1629401925 #> 8460 2065B 2 CC67 2017 2017-04-05 CHLAC -0.0502412164 I #> 8461 2065B 2 CC67 2017 2017-04-05 COND 10.7904503955 #> 8462 2065B 2 CC67 2017 2017-04-05 DO 1.9586853405 #> 8463 2065B 2 CC67 2017 2017-04-05 DOSAT 4.6653241088 + #> 8464 2065B 2 CC67 2017 2017-04-05 NO23 -4.8283137373 I #> 8465 2065B 2 CC67 2017 2017-04-05 SALIN 3.4541060373 #> 8466 2065B 2 CC67 2017 2017-04-05 TKN -0.4261781497 #> 8467 2065B 2 CC67 2017 2017-04-05 TN -0.4140014391 #> 8468 2065B 2 CC67 2017 2017-04-05 TP -2.7030626596 #> 8469 2065B 2 CC67 2017 2017-04-05 TSS 2.1972245773 #> 8470 2065B 2 CC67 2017 2017-04-05 TURB 0.0000000000 #> 8471 2065B 2 CC67 2017 2017-04-05 COND 10.7904771690 #> 8472 2065B 2 CC67 2017 2017-04-05 DO 1.9699056546 #> 8473 2065B 2 CC67 2017 2017-04-05 DOSAT 4.6784206477 + #> 8474 2065B 2 CC67 2017 2017-04-05 SALIN 3.4541060373 #> 8475 2065B 2 CC67 2017 2017-04-05 COND 10.7905760186 #> 8476 2065B 2 CC67 2017 2017-04-05 DO 1.9712993831 #> 8477 2065B 2 CC67 2017 2017-04-05 DOSAT 4.6802776585 + #> 8478 2065B 2 CC67 2017 2017-04-05 SALIN 3.4541060373 #> 8479 2065B 2 CC67 2017 2017-04-05 COND 10.7905821964 #> 8480 2065B 2 CC67 2017 2017-04-05 DO 1.9726911717 #> 8481 2065B 2 CC67 2017 2017-04-05 DOSAT 4.6812048723 + #> 8482 2065B 2 CC67 2017 2017-04-05 SALIN 3.4541060373 #> 8483 2065B 2 CC67 2017 2017-06-05 CHLAC 1.3686394259 #> 8484 2065B 2 CC67 2017 2017-06-05 NO23 -4.1351665567 #> 8485 2065B 2 CC67 2017 2017-06-05 TKN -0.2600669054 #> 8486 2065B 2 CC67 2017 2017-06-05 TN -0.2395270306 #> 8487 2065B 2 CC67 2017 2017-06-05 TP -2.5770219387 #> 8488 2065B 2 CC67 2017 2017-06-05 TSS 2.4595888418 #> 8489 2065B 2 CC67 2017 2017-06-05 TURB 0.0000000000 #> 8490 2065B 2 CC67 2017 2017-06-05 COND 10.8045448425 #> 8491 2065B 2 CC67 2017 2017-06-05 DO 1.6134299337 #> 8492 2065B 2 CC67 2017 2017-06-05 DOSAT 4.3592696476 + #> 8493 2065B 2 CC67 2017 2017-06-05 SALIN 3.4679210137 #> 8494 2065B 2 CC67 2017 2017-06-05 COND 10.8049143616 #> 8495 2065B 2 CC67 2017 2017-06-05 DO 1.6524974019 #> 8496 2065B 2 CC67 2017 2017-06-05 DOSAT 4.3981460166 + #> 8497 2065B 2 CC67 2017 2017-06-05 SALIN 3.4682327830 #> 8498 2065B 2 CC67 2017 2017-06-05 COND 10.8052533058 #> 8499 2065B 2 CC67 2017 2017-06-05 DO 1.6677068206 #> 8500 2065B 2 CC67 2017 2017-06-05 DOSAT 4.4140096805 + #> 8501 2065B 2 CC67 2017 2017-06-05 SALIN 3.4685444551 #> 8502 2065B 2 CC67 2017 2017-08-15 CHLAC 2.7850112422 #> 8503 2065B 2 CC67 2017 2017-08-15 COND 10.0070409363 #> 8504 2065B 2 CC67 2017 2017-08-15 DO 1.7474592103 #> 8505 2065B 2 CC67 2017 2017-08-15 DOSAT 4.4693504628 + #> 8506 2065B 2 CC67 2017 2017-08-15 NO23 -3.2968373663 #> 8507 2065B 2 CC67 2017 2017-08-15 SALIN 2.5794589667 #> 8508 2065B 2 CC67 2017 2017-08-15 TKN 0.0953101798 #> 8509 2065B 2 CC67 2017 2017-08-15 TN 0.1310282624 #> 8510 2065B 2 CC67 2017 2017-08-15 TP -1.0555527992 #> 8511 2065B 2 CC67 2017 2017-08-15 TSS 0.8458682676 #> 8512 2065B 2 CC67 2017 2017-08-15 TURB 0.6931471806 #> 8513 2065B 2 CC67 2017 2017-08-15 COND 10.1682757999 #> 8514 2065B 2 CC67 2017 2017-08-15 DO 0.5822156199 #> 8515 2065B 2 CC67 2017 2017-08-15 DOSAT 3.2771447330 + #> 8516 2065B 2 CC67 2017 2017-08-15 SALIN 2.7593768283 #> 8517 2065B 2 CC67 2017 2017-08-15 COND 10.1784604545 #> 8518 2065B 2 CC67 2017 2017-08-15 DO 0.5306282511 #> 8519 2065B 2 CC67 2017 2017-08-15 DOSAT 3.2268439945 + #> 8520 2065B 2 CC67 2017 2017-08-15 SALIN 2.7707119622 #> 8521 2065B 2 CC67 2018 2018-04-09 CHLAC 0.8109302162 #> 8522 2065B 2 CC67 2018 2018-04-09 COND 10.7756173069 #> 8523 2065B 2 CC67 2018 2018-04-09 DO 1.9387416596 #> 8524 2065B 2 CC67 2018 2018-04-09 DOSAT 4.6395716127 + #> 8525 2065B 2 CC67 2018 2018-04-09 NO23 -4.8283137373 I #> 8526 2065B 2 CC67 2018 2018-04-09 SALIN 3.4375293109 #> 8527 2065B 2 CC67 2018 2018-04-09 TKN -0.3945251681 #> 8528 2065B 2 CC67 2018 2018-04-09 TN -0.3827256211 #> 8529 2065B 2 CC67 2018 2018-04-09 TP -2.5902671654 #> 8530 2065B 2 CC67 2018 2018-04-09 TSS 1.4816045409 #> 8531 2065B 2 CC67 2018 2018-04-09 TURB 0.0953101798 #> 8532 2065B 2 CC67 2018 2018-04-09 COND 10.7754082549 #> 8533 2065B 2 CC67 2018 2018-04-09 DO 1.9473377010 #> 8534 2065B 2 CC67 2018 2018-04-09 DOSAT 4.6482296754 + #> 8535 2065B 2 CC67 2018 2018-04-09 SALIN 3.4375293109 #> 8536 2065B 2 CC67 2018 2018-04-09 COND 10.7754082549 #> 8537 2065B 2 CC67 2018 2018-04-09 DO 1.9487632180 #> 8538 2065B 2 CC67 2018 2018-04-09 DOSAT 4.6501435516 + #> 8539 2065B 2 CC67 2018 2018-04-09 SALIN 3.4375293109 #> 8540 2065B 2 CC67 2018 2018-05-23 CHLAC 1.1216775616 #> 8541 2065B 2 CC67 2018 2018-05-23 COND 10.7435212354 #> 8542 2065B 2 CC67 2018 2018-05-23 DO 1.8885836539 #> 8543 2065B 2 CC67 2018 2018-05-23 DOSAT 4.5910712616 + #> 8544 2065B 2 CC67 2018 2018-05-23 NO23 -4.6051701860 I #> 8545 2065B 2 CC67 2018 2018-05-23 SALIN 3.4011973817 #> 8546 2065B 2 CC67 2018 2018-05-23 TKN -0.1696027844 #> 8547 2065B 2 CC67 2018 2018-05-23 TN -0.1578240852 #> 8548 2065B 2 CC67 2018 2018-05-23 TP -2.0794415417 #> 8549 2065B 2 CC67 2018 2018-05-23 TSS 1.5686159179 #> 8550 2065B 2 CC67 2018 2018-05-23 TURB 1.0647107370 #> 8551 2065B 2 CC67 2018 2018-05-23 DOSAT 4.6793495842 + #> 8552 2065B 2 CC67 2018 2018-05-23 COND 10.7527727226 #> 8553 2065B 2 CC67 2018 2018-05-23 DO 1.9782390362 #> 8554 2065B 2 CC67 2018 2018-05-23 SALIN 3.4118075608 #> 8555 2065B 2 CC67 2018 2018-10-11 CHLAC 1.4109869737 #> 8556 2065B 2 CC67 2018 2018-10-11 COND 10.5316641186 #> 8557 2065B 2 CC67 2018 2018-10-11 DO 1.6467336972 #> 8558 2065B 2 CC67 2018 2018-10-11 DOSAT 4.3148178850 + #> 8559 2065B 2 CC67 2018 2018-10-11 NO23 -4.9618451299 I #> 8560 2065B 2 CC67 2018 2018-10-11 SALIN 3.1654750481 #> 8561 2065B 2 CC67 2018 2018-10-11 TKN -0.1960148839 #> 8562 2065B 2 CC67 2018 2018-10-11 TN -0.1875351238 #> 8563 2065B 2 CC67 2018 2018-10-11 TP -2.1202635362 #> 8564 2065B 2 CC67 2018 2018-10-11 TSS 1.8453002362 #> 8565 2065B 2 CC67 2018 2018-10-11 TURB 0.6931471806 #> 8566 2065B 2 CC67 2018 2018-10-11 COND 10.5317548204 #> 8567 2065B 2 CC67 2018 2018-10-11 DO 1.6448050563 #> 8568 2065B 2 CC67 2018 2018-10-11 DOSAT 4.3121405072 + #> 8569 2065B 2 CC67 2018 2018-10-11 SALIN 3.1654750481 #> 8570 2065B 2 CC67 2018 2018-10-11 COND 10.5326214074 #> 8571 2065B 2 CC67 2018 2018-10-11 DO 1.6370530795 #> 8572 2065B 2 CC67 2018 2018-10-11 DOSAT 4.3054155323 + #> 8573 2065B 2 CC67 2018 2018-10-11 SALIN 3.1663185741 #> 8574 2065B 2 CC67 2019 2019-03-05 CHLAC 1.6094379124 #> 8575 2065B 2 CC67 2019 2019-03-05 COND 10.4627604245 #> 8576 2065B 2 CC67 2019 2019-03-05 DO 1.8325814637 #> 8577 2065B 2 CC67 2019 2019-03-05 DOSAT 4.5163389723 + #> 8578 2065B 2 CC67 2019 2019-03-05 NO23 -5.1159958098 U #> 8579 2065B 2 CC67 2019 2019-03-05 SALIN 3.5550051456 #> 8580 2065B 2 CC67 2019 2019-03-05 TKN -0.2691874898 #> 8581 2065B 2 CC67 2019 2019-03-05 TN -0.2691874898 #> 8582 2065B 2 CC67 2019 2019-03-05 TP -2.3644604967 #> 8583 2065B 2 CC67 2019 2019-03-05 TSS 1.9919755159 #> 8584 2065B 2 CC67 2019 2019-03-05 TURB 0.8754687374 #> 8585 2065B 2 CC67 2019 2019-03-05 COND 10.4628461645 #> 8586 2065B 2 CC67 2019 2019-03-05 DO 1.8309801824 #> 8587 2065B 2 CC67 2019 2019-03-05 DOSAT 4.5152454785 + #> 8588 2065B 2 CC67 2019 2019-03-05 SALIN 3.5550908856 #> 8589 2065B 2 CC67 2019 2019-03-05 COND 10.4631604817 #> 8590 2065B 2 CC67 2019 2019-03-05 DO 1.8277699068 #> 8591 2065B 2 CC67 2019 2019-03-05 DOSAT 4.5119578043 + #> 8592 2065B 2 CC67 2019 2019-03-05 SALIN 3.5554052027 #> 8593 2065B 2 CC67 2020 2020-01-15 COND 10.6506753751 #> 8594 2065B 2 CC67 2020 2020-01-15 DO 2.0592388344 #> 8595 2065B 2 CC67 2020 2020-01-15 DOSAT 4.6737629775 + #> 8596 2065B 2 CC67 2020 2020-01-15 NO23 -5.1159958098 U #> 8597 2065B 2 CC67 2020 2020-01-15 SALIN 3.3010086544 #> 8598 2065B 2 CC67 2020 2020-01-15 TKN -0.4109802888 #> 8599 2065B 2 CC67 2020 2020-01-15 TN -0.4109802888 #> 8600 2065B 2 CC67 2020 2020-01-15 TP -2.4304184645 #> 8601 2065B 2 CC67 2020 2020-01-15 TSS 1.4816045409 #> 8602 2065B 2 CC67 2020 2020-01-15 TURB 0.0000000000 #> 8603 2065B 2 CC67 2020 2020-01-15 COND 10.6625933392 #> 8604 2065B 2 CC67 2020 2020-01-15 DO 2.0630580624 #> 8605 2065B 2 CC67 2020 2020-01-15 DOSAT 4.6756286496 + #> 8606 2065B 2 CC67 2020 2020-01-15 SALIN 3.3141860047 #> 8607 2065B 2 CC67 2020 2020-02-11 COND 10.6620033783 #> 8608 2065B 2 CC67 2020 2020-02-11 NO23 -5.1159958098 U #> 8609 2065B 2 CC67 2020 2020-02-11 SALIN 3.3141860047 #> 8610 2065B 2 CC67 2020 2020-02-11 TKN -0.3538218750 #> 8611 2065B 2 CC67 2020 2020-02-11 TN -0.3495574762 + #> 8612 2065B 2 CC67 2020 2020-02-11 TP -2.6036901858 #> 8613 2065B 2 CC67 2020 2020-02-11 TSS 1.2029723040 #> 8614 2065B 2 CC67 2020 2020-02-11 TURB -0.2613647641 #> 8615 2065B 2 CC67 2020 2020-02-11 COND 10.6633887669 #> 8616 2065B 2 CC67 2020 2020-02-11 SALIN 3.3156394933 #> 8617 2065B 2 CC67 2020 2020-11-04 COND 10.4405071004 #> 8618 2065B 2 CC67 2020 2020-11-04 DO 1.8033586051 #> 8619 2065B 2 CC67 2020 2020-11-04 DOSAT 4.3782695858 + #> 8620 2065B 2 CC67 2020 2020-11-04 NO23 -5.1159958098 U #> 8621 2065B 2 CC67 2020 2020-11-04 SALIN 3.0685179433 #> 8622 2065B 2 CC67 2020 2020-11-04 TKN -0.9808292530 #> 8623 2065B 2 CC67 2020 2020-11-04 TN -0.9808292530 #> 8624 2065B 2 CC67 2020 2020-11-04 TP -1.9173226922 #> 8625 2065B 2 CC67 2020 2020-11-04 TSS 3.3322045102 #> 8626 2065B 2 CC67 2020 2020-11-04 TURB 0.5306282511 #> 8627 2065B 2 CC67 2020 2020-11-04 COND 10.4404486499 #> 8628 2065B 2 CC67 2020 2020-11-04 DO 1.8000582720 #> 8629 2065B 2 CC67 2020 2020-11-04 DOSAT 4.3744983683 + #> 8630 2065B 2 CC67 2020 2020-11-04 SALIN 3.0685179433 #> 8631 2065B 2 CC67 2020 2020-11-04 COND 10.4404778756 #> 8632 2065B 2 CC67 2020 2020-11-04 DO 1.7984040119 #> 8633 2065B 2 CC67 2020 2020-11-04 DOSAT 4.3732381286 + #> 8634 2065B 2 CC67 2020 2020-11-04 SALIN 3.0685179433 #> 8635 2065B 2 CC67 2021 2021-05-17 COND 10.7266756661 #> 8636 2065B 2 CC67 2021 2021-05-17 DO 1.8976198599 #> 8637 2065B 2 CC67 2021 2021-05-17 DOSAT 4.5859873666 + #> 8638 2065B 2 CC67 2021 2021-05-17 NO23 -5.1159958098 U #> 8639 2065B 2 CC67 2021 2021-05-17 SALIN 3.3830334110 #> 8640 2065B 2 CC67 2021 2021-05-17 TKN -0.6520052372 #> 8641 2065B 2 CC67 2021 2021-05-17 TN -0.6520052372 #> 8642 2065B 2 CC67 2021 2021-05-17 TP -2.2926347621 #> 8643 2065B 2 CC67 2021 2021-05-17 TSS 2.7343675094 #> 8644 2065B 2 CC67 2021 2021-05-17 TURB -0.4416105547 #> 8645 2065B 2 CC67 2021 2021-05-17 COND 10.7266317622 #> 8646 2065B 2 CC67 2021 2021-05-17 DO 1.9110228901 #> 8647 2065B 2 CC67 2021 2021-05-17 DOSAT 4.5991521137 + #> 8648 2065B 2 CC67 2021 2021-05-17 SALIN 3.3830334110 #> 8649 2065B 2 CC67 2021 2021-05-17 COND 10.7261267283 #> 8650 2065B 2 CC67 2021 2021-05-17 DO 1.9110228901 #> 8651 2065B 2 CC67 2021 2021-05-17 DOSAT 4.5991521137 + #> 8652 2065B 2 CC67 2021 2021-05-17 SALIN 3.3823542939 #> 8653 2081 3F CC67 2016 2016-04-27 CHLAC 1.7404661748 #> 8654 2081 3F CC67 2016 2016-04-27 COLOR 4.2046926194 #> 8655 2081 3F CC67 2016 2016-04-27 COND 6.3135480463 #> 8656 2081 3F CC67 2016 2016-04-27 DO 2.0918640617 #> 8657 2081 3F CC67 2016 2016-04-27 DOSAT 4.5849674787 #> 8658 2081 3F CC67 2016 2016-04-27 NO23 -4.3428059215 #> 8659 2081 3F CC67 2016 2016-04-27 SALIN -1.3093333200 + #> 8660 2081 3F CC67 2016 2016-04-27 TKN -0.1625189295 #> 8661 2081 3F CC67 2016 2016-04-27 TN -0.1473405879 + #> 8662 2081 3F CC67 2016 2016-04-27 TP -2.9187712324 #> 8663 2081 3F CC67 2016 2016-04-27 TSS 1.0986122887 I #> 8664 2081 3F CC67 2016 2016-04-27 TURB 1.8870696490 #> 8665 2081 3F CC67 2016 2016-09-21 CHLAC 2.2082744135 A #> 8666 2081 3F CC67 2016 2016-09-21 COLOR 4.9416424226 #> 8667 2081 3F CC67 2016 2016-09-21 COND 5.8636311756 #> 8668 2081 3F CC67 2016 2016-09-21 DO 1.7227665977 #> 8669 2081 3F CC67 2016 2016-09-21 DOSAT 4.3040650932 #> 8670 2081 3F CC67 2016 2016-09-21 NO23 -2.9565115604 #> 8671 2081 3F CC67 2016 2016-09-21 SALIN -1.6094379124 #> 8672 2081 3F CC67 2016 2016-09-21 TKN -0.1863295782 #> 8673 2081 3F CC67 2016 2016-09-21 TN -0.1255632230 + #> 8674 2081 3F CC67 2016 2016-09-21 TP -2.3025850930 #> 8675 2081 3F CC67 2016 2016-09-21 TSS 2.8332133441 #> 8676 2081 3F CC67 2016 2016-09-21 TURB 2.3025850930 #> 8677 2081 3F CC67 2016 2016-12-13 CHLAC 0.5306282511 I #> 8678 2081 3F CC67 2016 2016-12-13 COLOR 4.0253516907 #> 8679 2081 3F CC67 2016 2016-12-13 COND 6.2709884319 #> 8680 2081 3F CC67 2016 2016-12-13 DO 2.1860512767 #> 8681 2081 3F CC67 2016 2016-12-13 DOSAT 4.5951198501 #> 8682 2081 3F CC67 2016 2016-12-13 NO23 -1.8971199849 #> 8683 2081 3F CC67 2016 2016-12-13 SALIN -1.6094379124 #> 8684 2081 3F CC67 2016 2016-12-13 TKN -0.4942963218 #> 8685 2081 3F CC67 2016 2016-12-13 TN -0.2744368457 + #> 8686 2081 3F CC67 2016 2016-12-13 TP -2.9759296463 #> 8687 2081 3F CC67 2016 2016-12-13 TSS 1.3862943611 I #> 8688 2081 3F CC67 2016 2016-12-13 TURB 1.6486586256 #> 8689 2081 3F CC67 2016 2016-12-28 CHLAC 1.0296194172 #> 8690 2081 3F CC67 2016 2016-12-28 COLOR 4.1896547420 A #> 8691 2081 3F CC67 2016 2016-12-28 COND 6.2747620212 #> 8692 2081 3F CC67 2016 2016-12-28 NO23 -2.2072749132 #> 8693 2081 3F CC67 2016 2016-12-28 SALIN -1.3093333200 + #> 8694 2081 3F CC67 2016 2016-12-28 TKN -0.4004775666 #> 8695 2081 3F CC67 2016 2016-12-28 TN -0.2484613593 + #> 8696 2081 3F CC67 2016 2016-12-28 TP -2.6882475738 #> 8697 2081 3F CC67 2016 2016-12-28 TSS 1.7917594692 I #> 8698 2081 3F CC67 2016 2016-12-28 TURB 1.9878743482 A #> 8699 2081 3F CC67 2017 2017-07-26 CHLAC 2.3025850930 #> 8700 2081 3F CC67 2017 2017-07-26 COLOR 5.3471075307 #> 8701 2081 3F CC67 2017 2017-07-26 COND 5.8435444170 #> 8702 2081 3F CC67 2017 2017-07-26 DO 1.6486586256 #> 8703 2081 3F CC67 2017 2017-07-26 DOSAT 4.2626798770 #> 8704 2081 3F CC67 2017 2017-07-26 NO23 -3.3813947544 #> 8705 2081 3F CC67 2017 2017-07-26 TKN 0.0953101798 #> 8706 2081 3F CC67 2017 2017-07-26 TN 0.1257512053 + #> 8707 2081 3F CC67 2017 2017-07-26 TP -2.4191189092 #> 8708 2081 3F CC67 2017 2017-07-26 TSS 2.4849066498 #> 8709 2081 3F CC67 2017 2017-07-26 TURB 1.9315214116 #> 8710 2081 3F CC67 2017 2017-08-21 CHLAC 1.4350845253 #> 8711 2081 3F CC67 2017 2017-08-21 COLOR 4.7874917428 #> 8712 2081 3F CC67 2017 2017-08-21 COND 6.0497334552 #> 8713 2081 3F CC67 2017 2017-08-21 DO 1.9169226122 #> 8714 2081 3F CC67 2017 2017-08-21 DOSAT 4.5108595065 #> 8715 2081 3F CC67 2017 2017-08-21 NO23 -2.9957322736 #> 8716 2081 3F CC67 2017 2017-08-21 TKN -0.1984509387 #> 8717 2081 3F CC67 2017 2017-08-21 TN -0.1392620673 + #> 8718 2081 3F CC67 2017 2017-08-21 TP -2.7488721956 #> 8719 2081 3F CC67 2017 2017-08-21 TSS 2.3025850930 I #> 8720 2081 3F CC67 2017 2017-08-21 TURB 1.9740810260 A #> 8721 2081 3F CC67 2017 2017-10-04 CHLAC 2.0014800002 #> 8722 2081 3F CC67 2017 2017-10-04 COLOR 4.7874917428 #> 8723 2081 3F CC67 2017 2017-10-04 COND 5.9188938543 #> 8724 2081 3F CC67 2017 2017-10-04 DO 1.8718021769 #> 8725 2081 3F CC67 2017 2017-10-04 DOSAT 4.3944491547 #> 8726 2081 3F CC67 2017 2017-10-04 NO23 -3.1235656451 #> 8727 2081 3F CC67 2017 2017-10-04 SALIN -1.7719568419 + #> 8728 2081 3F CC67 2017 2017-10-04 TKN -0.2231435513 #> 8729 2081 3F CC67 2017 2017-10-04 TN -0.1696027844 + #> 8730 2081 3F CC67 2017 2017-10-04 TP -2.7488721956 #> 8731 2081 3F CC67 2017 2017-10-04 TSS 2.0794415417 I #> 8732 2081 3F CC67 2017 2017-10-04 TURB 1.6486586256 A #> 8733 2081 3F CC67 2017 2017-11-08 CHLAC 1.7404661748 #> 8734 2081 3F CC67 2017 2017-11-08 COLOR 4.2341065046 #> 8735 2081 3F CC67 2017 2017-11-08 COND 6.1377270541 #> 8736 2081 3F CC67 2017 2017-11-08 DO 2.1747517215 #> 8737 2081 3F CC67 2017 2017-11-08 DOSAT 4.6634390941 #> 8738 2081 3F CC67 2017 2017-11-08 NO23 -2.7030626596 #> 8739 2081 3F CC67 2017 2017-11-08 SALIN -1.4696759701 + #> 8740 2081 3F CC67 2017 2017-11-08 TKN -0.4942963218 #> 8741 2081 3F CC67 2017 2017-11-08 TN -0.3900840061 + #> 8742 2081 3F CC67 2017 2017-11-08 TP -3.1235656451 #> 8743 2081 3F CC67 2017 2017-11-08 TSS 1.0986122887 I #> 8744 2081 3F CC67 2017 2017-11-08 TURB 1.5686159179 #> 8745 2081 3F CC67 2017 2017-11-30 CHLAC 1.6677068206 #> 8746 2081 3F CC67 2017 2017-11-30 COLOR 4.1271343850 A #> 8747 2081 3F CC67 2017 2017-11-30 COND 6.2519038832 #> 8748 2081 3F CC67 2017 2017-11-30 DO 2.3025850930 #> 8749 2081 3F CC67 2017 2017-11-30 DOSAT 4.7535901911 #> 8750 2081 3F CC67 2017 2017-11-30 NO23 -3.2188758249 #> 8751 2081 3F CC67 2017 2017-11-30 SALIN -1.3470736480 + #> 8752 2081 3F CC67 2017 2017-11-30 TKN -0.5798184953 #> 8753 2081 3F CC67 2017 2017-11-30 TN -0.5108256238 + #> 8754 2081 3F CC67 2017 2017-11-30 TP -3.1700856607 #> 8755 2081 3F CC67 2017 2017-11-30 TSS 1.3862943611 I #> 8756 2081 3F CC67 2017 2017-11-30 TURB 1.5475625087 #> 8757 2081 3F CC67 2018 2018-04-12 COND 6.1717005974 #> 8758 2081 3F CC67 2018 2018-04-12 DO 2.6461747974 #> 8759 2081 3F CC67 2018 2018-04-12 DOSAT 5.1239639794 #> 8760 2081 3F CC67 2018 2018-04-12 SALIN -1.4696759701 + #> 8761 2081 3F CC67 2018 2018-04-19 CHLAC 2.2512917986 #> 8762 2081 3F CC67 2018 2018-04-19 COLOR 4.0943445622 #> 8763 2081 3F CC67 2018 2018-04-19 COND 6.0980742822 #> 8764 2081 3F CC67 2018 2018-04-19 DO 2.7317667277 #> 8765 2081 3F CC67 2018 2018-04-19 DOSAT 5.3107398865 #> 8766 2081 3F CC67 2018 2018-04-19 NO23 -5.5214609179 U #> 8767 2081 3F CC67 2018 2018-04-19 SALIN -1.6094379124 + #> 8768 2081 3F CC67 2018 2018-04-19 TKN -0.3424903089 #> 8769 2081 3F CC67 2018 2018-04-19 TN -0.3396773676 + #> 8770 2081 3F CC67 2018 2018-04-19 TP -4.2686979494 #> 8771 2081 3F CC67 2018 2018-04-19 TSS 1.0986122887 I #> 8772 2081 3F CC67 2018 2018-04-19 TURB 0.4054651081 #> 8773 2081 3F CC67 2018 2018-07-17 CHLAC 2.3978952728 #> 8774 2081 3F CC67 2018 2018-07-17 COLOR 5.2470240722 #> 8775 2081 3F CC67 2018 2018-07-17 COND 5.6559918108 #> 8776 2081 3F CC67 2018 2018-07-17 DO 1.6677068206 #> 8777 2081 3F CC67 2018 2018-07-17 DOSAT 4.2541932632 #> 8778 2081 3F CC67 2018 2018-07-17 NO23 -3.8167128256 #> 8779 2081 3F CC67 2018 2018-07-17 TKN -0.0304592075 #> 8780 2081 3F CC67 2018 2018-07-17 TN -0.0080321717 + #> 8781 2081 3F CC67 2018 2018-07-17 TP -2.7968814148 #> 8782 2081 3F CC67 2018 2018-07-17 TSS 1.7917594692 I #> 8783 2081 3F CC67 2018 2018-07-17 TURB 1.7047480922 #> 8784 2081 3F CC67 2018 2018-08-01 CHLAC 2.0014800002 #> 8785 2081 3F CC67 2018 2018-08-01 COLOR 4.9416424226 #> 8786 2081 3F CC67 2018 2018-08-01 COND 5.9269260260 #> 8787 2081 3F CC67 2018 2018-08-01 DO 1.8900953699 #> 8788 2081 3F CC67 2018 2018-08-01 DOSAT 4.4624538838 #> 8789 2081 3F CC67 2018 2018-08-01 NO23 -3.2188758249 #> 8790 2081 3F CC67 2018 2018-08-01 SALIN -1.7147984281 #> 8791 2081 3F CC67 2018 2018-08-01 TKN -0.2613647641 #> 8792 2081 3F CC67 2018 2018-08-01 TN -0.2107210313 + #> 8793 2081 3F CC67 2018 2018-08-01 TP -2.8824035882 #> 8794 2081 3F CC67 2018 2018-08-01 TSS 1.7917594692 I #> 8795 2081 3F CC67 2018 2018-08-01 TURB 1.7404661748 #> 8796 2081 3F CC67 2018 2018-08-01 COND 5.9269260260 #> 8797 2081 3F CC67 2018 2018-08-01 DO 1.8900953699 #> 8798 2081 3F CC67 2018 2018-08-01 DOSAT 4.4624538838 #> 8799 2081 3F CC67 2018 2018-08-01 SALIN -1.7147984281 #> 8800 2081 3F CC67 2018 2018-08-20 CHLAC 2.2407096893 #> 8801 2081 3F CC67 2018 2018-08-20 COLOR 5.0751738152 #> 8802 2081 3F CC67 2018 2018-08-20 COND 5.3706380281 #> 8803 2081 3F CC67 2018 2018-08-20 DO 1.5216989981 #> 8804 2081 3F CC67 2018 2018-08-20 DOSAT 4.0758410907 #> 8805 2081 3F CC67 2018 2018-08-20 NO23 -3.4420193762 #> 8806 2081 3F CC67 2018 2018-08-20 SALIN -2.3025850930 #> 8807 2081 3F CC67 2018 2018-08-20 TKN -0.0618754037 #> 8808 2081 3F CC67 2018 2018-08-20 TN -0.0283994745 + #> 8809 2081 3F CC67 2018 2018-08-20 TP -2.4534079827 #> 8810 2081 3F CC67 2018 2018-08-20 TSS 2.1972245773 I #> 8811 2081 3F CC67 2018 2018-08-20 TURB 1.9315214116 #> 8812 2081 3F CC67 2018 2018-09-10 CHLAC 1.5260563035 #> 8813 2081 3F CC67 2018 2018-09-10 COLOR 4.4998096703 A #> 8814 2081 3F CC67 2018 2018-09-10 COND 6.0520891689 #> 8815 2081 3F CC67 2018 2018-09-10 DO 1.9865035460 #> 8816 2081 3F CC67 2018 2018-09-10 DOSAT 4.5941092386 #> 8817 2081 3F CC67 2018 2018-09-10 SALIN -1.6094379124 #> 8818 2081 3F CC67 2018 2018-09-10 TN -0.2057949130 + #> 8819 2081 3F CC67 2018 2018-09-10 TSS 2.3025850930 A #> 8820 2081 3F CC67 2018 2018-09-10 TURB 2.0281482473 #> 8821 2081 3F CC67 2018 2018-11-12 CHLAC 2.2300144002 #> 8822 2081 3F CC67 2018 2018-11-12 COLOR 3.9120230054 #> 8823 2081 3F CC67 2018 2018-11-12 COND 6.2595814641 #> 8824 2081 3F CC67 2018 2018-11-12 DO 2.1174596089 #> 8825 2081 3F CC67 2018 2018-11-12 DOSAT 4.6180864113 #> 8826 2081 3F CC67 2018 2018-11-12 NO23 -2.3751557858 #> 8827 2081 3F CC67 2018 2018-11-12 SALIN -1.3862943611 #> 8828 2081 3F CC67 2018 2018-11-12 TKN -0.2484613593 #> 8829 2081 3F CC67 2018 2018-11-12 TN -0.1358197231 + #> 8830 2081 3F CC67 2018 2018-11-12 TP -2.8473122684 #> 8831 2081 3F CC67 2018 2018-11-12 TSS 2.1972245773 I #> 8832 2081 3F CC67 2018 2018-11-12 TURB 2.0014800002 A #> 8833 2082A 3F CC70 2018 2018-10-18 CHLAC 0.9932517730 #> 8834 2082A 3F CC70 2018 2018-10-18 COLOR 4.2484952420 #> 8835 2082A 3F CC70 2018 2018-10-18 COND 5.5721540322 #> 8836 2082A 3F CC70 2018 2018-10-18 DO 1.7681496036 #> 8837 2082A 3F CC70 2018 2018-10-18 DOSAT 4.3148178850 #> 8838 2082A 3F CC70 2018 2018-10-18 NO23 -2.1202635362 #> 8839 2082A 3F CC70 2018 2018-10-18 SALIN -2.1202635362 #> 8840 2082A 3F CC70 2018 2018-10-18 TKN 0.1823215568 #> 8841 2082A 3F CC70 2018 2018-10-18 TN 0.2776317366 + #> 8842 2082A 3F CC70 2018 2018-10-18 TP -3.0365542681 #> 8843 2082A 3F CC70 2018 2018-10-18 TSS 2.3978952728 A #> 8844 2082A 3F CC70 2018 2018-10-18 TURB 1.9600947840 #> 8845 2082A 3F CC70 2019 2019-05-08 CHLAC 0.4054651081 I #> 8846 2082A 3F CC70 2019 2019-05-08 COLOR 3.5263605246 A #> 8847 2082A 3F CC70 2019 2019-05-08 COND 6.4167322825 #> 8848 2082A 3F CC70 2019 2019-05-08 DO 1.6900958155 #> 8849 2082A 3F CC70 2019 2019-05-08 DOSAT 4.2384449062 #> 8850 2082A 3F CC70 2019 2019-05-08 NO23 -5.5214609179 U #> 8851 2082A 3F CC70 2019 2019-05-08 SALIN -1.2039728043 #> 8852 2082A 3F CC70 2019 2019-05-08 TKN -0.3011050928 #> 8853 2082A 3F CC70 2019 2019-05-08 TN -0.2984060358 + #> 8854 2082A 3F CC70 2019 2019-05-08 TP -3.1941832123 #> 8855 2082A 3F CC70 2019 2019-05-08 TSS 0.6931471806 I #> 8856 2082A 3F CC70 2019 2019-05-08 TURB 1.2527629685 #> 8857 2079 2 CC74 2017 2017-03-13 COND 11.1102514581 #> 8858 2079 2 CC74 2017 2017-03-13 DO 2.0668627595 #> 8859 2079 2 CC74 2017 2017-03-13 DOSAT 4.8362819070 #> 8860 2079 2 CC74 2017 2017-03-13 SALIN 3.8066624898 #> 8861 2079 2 CC74 2017 2017-05-15 CHLAC 0.9162907319 #> 8862 2079 2 CC74 2017 2017-05-15 COND 10.9460055668 #> 8863 2079 2 CC74 2017 2017-05-15 DO 1.7917594692 #> 8864 2079 2 CC74 2017 2017-05-15 DOSAT 4.2341065046 #> 8865 2079 2 CC74 2017 2017-05-15 NO23 -4.8283137373 U #> 8866 2079 2 CC74 2017 2017-05-15 SALIN 3.5759906720 + #> 8867 2079 2 CC74 2017 2017-05-15 TKN -0.3011050928 #> 8868 2079 2 CC74 2017 2017-05-15 TN -0.2957142441 + #> 8869 2079 2 CC74 2017 2017-05-15 TP -3.6888794541 #> 8870 2079 2 CC74 2017 2017-05-15 TSS 1.3862943611 I #> 8871 2079 2 CC74 2017 2017-05-15 TURB 0.0000000000 #> 8872 2079 2 CC74 2017 2017-07-20 CHLAC 1.5475625087 #> 8873 2079 2 CC74 2017 2017-07-20 COND 10.6434228946 #> 8874 2079 2 CC74 2017 2017-07-20 DO 1.5040773968 #> 8875 2079 2 CC74 2017 2017-07-20 DOSAT 4.2484952420 #> 8876 2079 2 CC74 2017 2017-07-20 NO23 -5.5214609179 U #> 8877 2079 2 CC74 2017 2017-07-20 TKN -0.0943106795 #> 8878 2079 2 CC74 2017 2017-07-20 TN -0.0921152889 + #> 8879 2079 2 CC74 2017 2017-07-20 TP -3.4112477175 #> 8880 2079 2 CC74 2017 2017-07-20 TSS 1.0986122887 U #> 8881 2079 2 CC74 2017 2017-07-20 TURB 0.4054651081 #> 8882 2079 2 CC74 2017 2017-10-24 COND 10.5655567775 #> 8883 2079 2 CC74 2017 2017-10-24 DO 1.4586150227 #> 8884 2079 2 CC74 2017 2017-10-24 DOSAT 4.1431347264 #> 8885 2079 2 CC74 2017 2017-10-24 SALIN 3.1531632815 + #> 8886 2079 2 CC74 2018 2018-03-15 CHLAC 2.0918640617 #> 8887 2079 2 CC74 2018 2018-03-15 COND 11.0381102787 #> 8888 2079 2 CC74 2018 2018-03-15 DO 2.2407096893 #> 8889 2079 2 CC74 2018 2018-03-15 DOSAT 4.9972122738 #> 8890 2079 2 CC74 2018 2018-03-15 NO23 -4.1997050779 #> 8891 2079 2 CC74 2018 2018-03-15 TKN -0.1508228897 #> 8892 2079 2 CC74 2018 2018-03-15 TN -0.1335313926 + #> 8893 2079 2 CC74 2018 2018-03-15 TP -3.1941832123 #> 8894 2079 2 CC74 2018 2018-03-15 TSS 1.9459101491 I #> 8895 2079 2 CC74 2018 2018-03-15 TURB 1.0986122887 #> 8896 2079 2 CC74 2018 2018-04-23 CHLAC 2.7725887222 #> 8897 2079 2 CC74 2018 2018-04-23 COND 10.9748485413 #> 8898 2079 2 CC74 2018 2018-04-23 DO 2.2823823857 #> 8899 2079 2 CC74 2018 2018-04-23 DOSAT 5.0498560072 #> 8900 2079 2 CC74 2018 2018-04-23 NO23 -5.5214609179 U #> 8901 2079 2 CC74 2018 2018-04-23 SALIN 3.5937442590 + #> 8902 2079 2 CC74 2018 2018-04-23 TKN -0.1984509387 #> 8903 2079 2 CC74 2018 2018-04-23 TN -0.1960148839 + #> 8904 2079 2 CC74 2018 2018-04-23 TP -3.2441936329 #> 8905 2079 2 CC74 2018 2018-04-23 TSS 2.4849066498 #> 8906 2079 2 CC74 2018 2018-04-23 TURB 0.6931471806 #> 8907 2079 2 CC74 2018 2018-06-11 CHLAC 3.1780538303 #> 8908 2079 2 CC74 2018 2018-06-11 COND 10.6286177789 #> 8909 2079 2 CC74 2018 2018-06-11 DO 1.8245492921 #> 8910 2079 2 CC74 2018 2018-06-11 DOSAT 4.5643481915 #> 8911 2079 2 CC74 2018 2018-06-11 NO23 -5.5214609179 U #> 8912 2079 2 CC74 2018 2018-06-11 SALIN 3.2695689392 #> 8913 2079 2 CC74 2018 2018-06-11 TKN -0.0943106795 #> 8914 2079 2 CC74 2018 2018-06-11 TN -0.0921152889 + #> 8915 2079 2 CC74 2018 2018-06-11 TP -2.9957322736 #> 8916 2079 2 CC74 2018 2018-06-11 TSS 1.7917594692 I #> 8917 2079 2 CC74 2018 2018-06-11 TURB 1.1314021115 #> 8918 2079 2 CC74 2018 2018-08-07 CHLAC 1.9600947840 #> 8919 2079 2 CC74 2018 2018-08-07 COND 10.5844609322 #> 8920 2079 2 CC74 2018 2018-08-07 DO 1.9387416596 #> 8921 2079 2 CC74 2018 2018-08-07 DOSAT 4.6709579265 #> 8922 2079 2 CC74 2018 2018-08-07 NO23 -5.5214609179 U #> 8923 2079 2 CC74 2018 2018-08-07 SALIN 3.2200751054 #> 8924 2079 2 CC74 2018 2018-08-07 TKN -0.0202027073 #> 8925 2079 2 CC74 2018 2018-08-07 TN -0.0181639706 + #> 8926 2079 2 CC74 2018 2018-08-07 TP -2.6882475738 #> 8927 2079 2 CC74 2018 2018-08-07 TSS 1.0986122887 U #> 8928 2079 2 CC74 2018 2018-08-07 TURB 0.4054651081 #> 8929 2079 2 CC74 2018 2018-09-06 CHLAC 1.6486586256 #> 8930 2079 2 CC74 2018 2018-09-06 COND 10.3441267357 #> 8931 2079 2 CC74 2018 2018-09-06 DO 1.4231083342 #> 8932 2079 2 CC74 2018 2018-09-06 DOSAT 4.1026433650 #> 8933 2079 2 CC74 2018 2018-09-06 NO23 -5.5214609179 U #> 8934 2079 2 CC74 2018 2018-09-06 SALIN 2.9559514035 #> 8935 2079 2 CC74 2018 2018-09-06 TKN 0.7419373447 #> 8936 2079 2 CC74 2018 2018-09-06 TN 0.7428892725 + #> 8937 2079 2 CC74 2018 2018-09-06 TP -2.5770219387 #> 8938 2079 2 CC74 2018 2018-09-06 TSS 1.0986122887 I #> 8939 2079 2 CC74 2018 2018-09-06 TURB 0.0953101798 #> 8940 2079 2 CC74 2019 2019-04-17 CHLAC 2.1162555148 #> 8941 2079 2 CC74 2019 2019-04-17 COND 10.8549137412 #> 8942 2079 2 CC74 2019 2019-04-17 DO 2.2159372863 #> 8943 2079 2 CC74 2019 2019-04-17 DOSAT 4.9236239171 #> 8944 2079 2 CC74 2019 2019-04-17 NO23 -5.5214609179 U #> 8945 2079 2 CC74 2019 2019-04-17 SALIN 3.5269485870 #> 8946 2079 2 CC74 2019 2019-04-17 TKN -0.1278333715 #> 8947 2079 2 CC74 2019 2019-04-17 TN -0.1255632230 + #> 8948 2079 2 CC74 2019 2019-04-17 TP -3.4737680745 #> 8949 2079 2 CC74 2019 2019-04-17 TSS 3.4011973817 #> 8950 2079 2 CC74 2019 2019-04-17 TURB -0.2231435513 #> 8951 2079 2 CC74 2019 2019-07-15 CHLAC 3.7612001157 #> 8952 2079 2 CC74 2019 2019-07-15 COND 10.6353745614 #> 8953 2079 2 CC74 2019 2019-07-15 DO 1.9796212064 #> 8954 2079 2 CC74 2019 2019-07-15 DOSAT 4.7104306966 #> 8955 2079 2 CC74 2019 2019-07-15 NO23 -5.5214609179 U #> 8956 2079 2 CC74 2019 2019-07-15 SALIN 3.2782761681 #> 8957 2079 2 CC74 2019 2019-07-15 TKN 0.0953101798 #> 8958 2079 2 CC74 2019 2019-07-15 TN 0.0971267107 + #> 8959 2079 2 CC74 2019 2019-07-15 TP -2.7806208939 #> 8960 2079 2 CC74 2019 2019-07-15 TSS 2.8332133441 #> 8961 2079 2 CC74 2019 2019-07-15 TURB 1.6094379124 #> 8962 2079 2 CC74 2019 2019-08-19 CHLAC 2.4849066498 #> 8963 2079 2 CC74 2019 2019-08-19 COND 10.4673514473 #> 8964 2079 2 CC74 2019 2019-08-19 DO 1.3635373740 #> 8965 2079 2 CC74 2019 2019-08-19 DOSAT 4.0826093060 #> 8966 2079 2 CC74 2019 2019-08-19 NO23 -5.5214609179 U #> 8967 2079 2 CC74 2019 2019-08-19 SALIN 3.0901329490 #> 8968 2079 2 CC74 2019 2019-08-19 TKN 0.4054651081 #> 8969 2079 2 CC74 2019 2019-08-19 TN 0.4067975533 + #> 8970 2079 2 CC74 2019 2019-08-19 TP -3.2968373663 #> 8971 2079 2 CC74 2019 2019-08-19 TSS 2.4849066498 #> 8972 2079 2 CC74 2019 2019-08-19 TURB 0.7419373447 #> 8973 2079 2 CC74 2019 2019-09-11 CHLAC 2.9444389792 #> 8974 2079 2 CC74 2019 2019-09-11 COND 10.7330214205 #> 8975 2079 2 CC74 2019 2019-09-11 DO 1.7783364489 #> 8976 2079 2 CC74 2019 2019-09-11 DOSAT 4.5152454785 #> 8977 2079 2 CC74 2019 2019-09-11 NO23 -5.5214609179 U #> 8978 2079 2 CC74 2019 2019-09-11 SALIN 3.3874364664 #> 8979 2079 2 CC74 2019 2019-09-11 TKN -0.0100503359 #> 8980 2079 2 CC74 2019 2019-09-11 TN -0.0080321717 + #> 8981 2079 2 CC74 2019 2019-09-11 TP -2.8647040111 #> 8982 2079 2 CC74 2019 2019-09-11 TSS 1.3862943611 I #> 8983 2079 2 CC74 2019 2019-09-11 TURB 0.7884573604 #> 8984 2079 2 CC74 2019 2019-10-09 CHLAC 3.4339872045 #> 8985 2079 2 CC74 2019 2019-10-09 COND 10.7419897010 #> 8986 2079 2 CC74 2019 2019-10-09 DO 1.5432981099 #> 8987 2079 2 CC74 2019 2019-10-09 DOSAT 4.2640873368 #> 8988 2079 2 CC74 2019 2019-10-09 NO23 -5.5214609179 U #> 8989 2079 2 CC74 2019 2019-10-09 SALIN 3.3981928726 #> 8990 2079 2 CC74 2019 2019-10-09 TKN -0.1278333715 #> 8991 2079 2 CC74 2019 2019-10-09 TN -0.1255632230 + #> 8992 2079 2 CC74 2019 2019-10-09 TP -2.8302178351 #> 8993 2079 2 CC74 2019 2019-10-09 TSS 1.9459101491 I #> 8994 2079 2 CC74 2019 2019-10-09 TURB 0.6931471806 #> 8995 2079 2 CC74 2020 2020-02-13 CHLAC 2.3978952728 #> 8996 2079 2 CC74 2020 2020-02-13 COND 10.7930235471 #> 8997 2079 2 CC74 2020 2020-02-13 DO 2.0464016876 #> 8998 2079 2 CC74 2020 2020-02-13 DOSAT 4.7388265708 #> 8999 2079 2 CC74 2020 2020-02-13 NO23 -5.5214609179 U #> 9000 2079 2 CC74 2020 2020-02-13 SALIN 3.4575777151 #> 9001 2079 2 CC74 2020 2020-02-13 TKN -0.0512932944 #> 9002 2079 2 CC74 2020 2020-02-13 TN -0.0491902442 + #> 9003 2079 2 CC74 2020 2020-02-13 TP -3.0365542681 #> 9004 2079 2 CC74 2020 2020-02-13 TSS 2.3025850930 I #> 9005 2079 2 CC74 2020 2020-02-13 TURB 0.6931471806 #> 9006 2079 2 CC74 2020 2020-03-24 CHLAC 2.0014800002 #> 9007 2079 2 CC74 2020 2020-03-24 COND 10.9585136130 #> 9008 2079 2 CC74 2020 2020-03-24 DO 1.8115620965 #> 9009 2079 2 CC74 2020 2020-03-24 DOSAT 4.5664293577 #> 9010 2079 2 CC74 2020 2020-03-24 NO23 -5.5214609179 U #> 9011 2079 2 CC74 2020 2020-03-24 SALIN 3.6425737012 #> 9012 2079 2 CC74 2020 2020-03-24 TKN -0.0512932944 #> 9013 2079 2 CC74 2020 2020-03-24 TN -0.0491902442 + #> 9014 2079 2 CC74 2020 2020-03-24 TP -3.3242363405 #> 9015 2079 2 CC74 2020 2020-03-24 TSS 1.6094379124 I #> 9016 2079 2 CC74 2020 2020-03-24 TURB 0.7419373447 #> 9017 2079 2 CC74 2020 2020-06-15 CHLAC 3.1354942159 #> 9018 2079 2 CC74 2020 2020-06-15 COND 10.7369834598 #> 9019 2079 2 CC74 2020 2020-06-15 DO 0.5822156199 #> 9020 2079 2 CC74 2020 2020-06-15 DOSAT 3.3141860047 #> 9021 2079 2 CC74 2020 2020-06-15 NO23 -5.5214609179 U #> 9022 2079 2 CC74 2020 2020-06-15 SALIN 3.3924929410 #> 9023 2079 2 CC74 2020 2020-06-15 TKN 0.3364722366 #> 9024 2079 2 CC74 2020 2020-06-15 TN 0.3378997886 + #> 9025 2079 2 CC74 2020 2020-06-15 TP -2.7488721956 #> 9026 2079 2 CC74 2020 2020-06-15 TSS 1.3862943611 I #> 9027 2079 2 CC74 2020 2020-06-15 TURB 2.0668627595 #> 9028 2079 2 CC74 2020 2020-07-27 CHLAC 3.4339872045 #> 9029 2079 2 CC74 2020 2020-07-27 COND 10.7988201898 #> 9030 2079 2 CC74 2020 2020-07-27 DO 1.9572739077 #> 9031 2079 2 CC74 2020 2020-07-27 DOSAT 4.7326835063 #> 9032 2079 2 CC74 2020 2020-07-27 NO23 -5.5214609179 U #> 9033 2079 2 CC74 2020 2020-07-27 SALIN 3.4594662898 #> 9034 2079 2 CC74 2020 2020-07-27 TKN 0.0000000000 #> 9035 2079 2 CC74 2020 2020-07-27 TN 0.0019980027 + #> 9036 2079 2 CC74 2020 2020-07-27 TP -3.1700856607 #> 9037 2079 2 CC74 2020 2020-07-27 TSS 1.7917594692 I #> 9038 2079 2 CC74 2020 2020-07-27 TURB 1.2809338455 #> 9039 2079 2 CC74 2023 2023-02-13 CHLAC 3.3672958300 #> 9040 2079 2 CC74 2023 2023-02-13 COND 10.8175959048 #> 9041 2079 2 CC74 2023 2023-02-13 DO 1.8277699068 #> 9042 2079 2 CC74 2023 2023-02-13 DOSAT 4.4091553021 #> 9043 2079 2 CC74 2023 2023-02-13 NO23 -5.5214609179 U #> 9044 2079 2 CC74 2023 2023-02-13 SALIN 3.4879865117 #> 9045 2079 2 CC74 2023 2023-02-13 TKN 0.2623642645 #> 9046 2079 2 CC74 2023 2023-02-13 TN 0.2639015438 + #> 9047 2079 2 CC74 2023 2023-02-13 TP -2.2072749132 #> 9048 2079 2 CC74 2023 2023-02-13 TSS 2.8903717579 A #> 9049 2079 2 CC74 2023 2023-02-13 TURB 1.4350845253 #> 9050 2079 2 CC74 2023 2023-04-10 COND 10.9901959367 #> 9051 2079 2 CC74 2023 2023-04-10 DO 1.6714733034 #> 9052 2079 2 CC74 2023 2023-04-10 DOSAT 4.3770140929 #> 9053 2079 2 CC74 2023 2023-04-10 NO23 -5.5214609179 U #> 9054 2079 2 CC74 2023 2023-04-10 SALIN 3.6810992668 #> 9055 2079 2 CC74 2023 2023-04-10 TKN -0.0618754037 #> 9056 2079 2 CC74 2023 2023-04-10 TN -0.0597500044 + #> 9057 2079 2 CC74 2023 2023-04-10 TP -3.4737680745 #> 9058 2079 2 CC74 2023 2023-04-10 TSS 1.3862943611 I #> 9059 2079 2 CC74 2014 2014-03-26 SALIN 3.5351453542 #> 9060 2079 2 CC74 2014 2014-03-26 SALIN 3.5351453542 #> 9061 2079 2 CC74 2014 2014-07-22 SALIN 3.4719664526 #> 9062 2079 2 CC74 2014 2014-07-22 SALIN 3.4719664526 #> 9063 2079 2 CC74 2014 2014-09-11 DO 1.5475625087 #> 9064 2079 2 CC74 2014 2014-09-11 DOSAT 4.3280982926 + #> 9065 2079 2 CC74 2014 2014-09-11 SALIN 3.4011973817 #> 9066 2079 2 CC74 2015 2015-09-14 SALIN 3.1986731176 #> 9067 2079 2 CC74 2015 2015-09-14 SALIN 3.1986731176 #> 9068 2079 2 CC74 2016 2016-05-18 DO 2.1282317058 #> 9069 2079 2 CC74 2016 2016-05-18 DOSAT 4.8933521335 + #> 9070 2079 2 CC74 2016 2016-05-18 SALIN 3.5145260670 #> 9071 2079 2 CC74 2016 2016-05-18 DO 2.2721258855 #> 9072 2079 2 CC74 2016 2016-05-18 DOSAT 5.0395466376 + #> 9073 2079 2 CC74 2016 2016-05-18 SALIN 3.5174978374 #> 9074 2079 2 CC74 2016 2016-08-01 DO 2.1282317058 #> 9075 2079 2 CC74 2016 2016-08-01 DOSAT 4.9243509255 + #> 9076 2079 2 CC74 2016 2016-08-01 SALIN 3.4531571206 #> 9077 2079 2 CC74 2016 2016-08-01 DO 2.1162555148 #> 9078 2079 2 CC74 2016 2016-08-01 DOSAT 4.9170569471 + #> 9079 2079 2 CC74 2016 2016-08-01 SALIN 3.4995332824 #> 9080 2079 2 CC74 2016 2016-08-17 DO 2.0014800002 #> 9081 2079 2 CC74 2016 2016-08-17 DOSAT 4.7578912730 + #> 9082 2079 2 CC74 2016 2016-08-17 SALIN 3.3357695763 #> 9083 2079 2 CC74 2016 2016-08-17 DO 1.9021075264 #> 9084 2079 2 CC74 2016 2016-08-17 DOSAT 4.6672055769 + #> 9085 2079 2 CC74 2016 2016-08-17 SALIN 3.4111477125 #> 9086 2079 2 CC74 2016 2016-09-08 DO 1.9459101491 #> 9087 2079 2 CC74 2016 2016-09-08 DOSAT 4.6463121293 + #> 9088 2079 2 CC74 2016 2016-09-08 SALIN 3.0492730405 #> 9089 2079 2 CC74 2016 2016-09-08 DO 1.7749523509 #> 9090 2079 2 CC74 2016 2016-09-08 DOSAT 4.5009201646 + #> newComment disqual disqual2 #> 1 NA NA #> 2 U NA NA #> 3 + NA NA #> 4 U NA NA #> 5 NA NA #> 6 NA NA #> 7 + NA NA #> 8 NA NA #> 9 NA NA #> 10 I NA NA #> 11 U NA NA #> 12 NA NA #> 13 + NA NA #> 14 I NA NA #> 15 NA NA #> 16 NA NA #> 17 + NA NA #> 18 NA NA #> 19 NA NA #> 20 NA NA #> 21 NA NA #> 22 NA NA #> 23 + NA NA #> 24 I NA NA #> 25 NA NA #> 26 NA NA #> 27 + NA NA #> 28 NA NA #> 29 A NA NA #> 30 NA NA #> 31 NA NA #> 32 NA NA #> 33 + NA NA #> 34 I NA NA #> 35 NA NA #> 36 NA NA #> 37 + NA NA #> 38 NA NA #> 39 NA NA #> 40 NA NA #> 41 NA NA #> 42 NA NA #> 43 U NA NA #> 44 NA NA #> 45 + NA NA #> 46 NA NA #> 47 NA NA #> 48 NA NA #> 49 NA NA #> 50 NA NA #> 51 + NA NA #> 52 U NA NA #> 53 NA NA #> 54 + NA NA #> 55 NA NA #> 56 NA NA #> 57 NA NA #> 58 NA NA #> 59 + NA NA #> 60 I NA NA #> 61 NA NA #> 62 NA NA #> 63 + NA NA #> 64 NA NA #> 65 NA NA #> 66 NA NA #> 67 NA NA #> 68 + NA NA #> 69 NA NA #> 70 NA NA #> 71 NA NA #> 72 + NA NA #> 73 NA NA #> 74 NA NA #> 75 A NA NA #> 76 A NA NA #> 77 + NA NA #> 78 NA NA #> 79 NA NA #> 80 NA NA #> 81 + NA NA #> 82 NA NA #> 83 NA NA #> 84 NA NA #> 85 A NA NA #> 86 + NA NA #> 87 NA NA #> 88 NA NA #> 89 NA NA #> 90 + NA NA #> 91 NA NA #> 92 NA NA #> 93 NA NA #> 94 NA NA #> 95 NA NA #> 96 + NA NA #> 97 I NA NA #> 98 NA NA #> 99 NA NA #> 100 + NA NA #> 101 NA NA #> 102 NA NA #> 103 I NA NA #> 104 U NA NA #> 105 NA NA #> 106 + NA NA #> 107 I NA NA #> 108 NA NA #> 109 I NA NA #> 110 + NA NA #> 111 NA NA #> 112 NA NA #> 113 NA NA #> 114 NA NA #> 115 NA NA #> 116 + NA NA #> 117 U NA NA #> 118 NA NA #> 119 NA NA #> 120 + NA NA #> 121 NA NA #> 122 NA NA #> 123 NA NA #> 124 NA NA #> 125 NA NA #> 126 + NA NA #> 127 U NA NA #> 128 NA NA #> 129 I NA NA #> 130 + NA NA #> 131 NA NA #> 132 NA NA #> 133 NA NA #> 134 NA NA #> 135 NA NA #> 136 + NA NA #> 137 NA NA #> 138 NA NA #> 139 NA NA #> 140 + NA NA #> 141 NA NA #> 142 NA NA #> 143 NA NA #> 144 NA NA #> 145 NA NA #> 146 + NA NA #> 147 NA NA #> 148 NA NA #> 149 NA NA #> 150 + NA NA #> 151 NA NA #> 152 NA NA #> 153 NA NA #> 154 NA NA #> 155 NA NA #> 156 + NA NA #> 157 NA NA #> 158 NA NA #> 159 NA NA #> 160 + NA NA #> 161 NA NA #> 162 NA NA #> 163 NA NA #> 164 NA NA #> 165 NA NA #> 166 + NA NA #> 167 NA NA #> 168 NA NA #> 169 NA NA #> 170 + NA NA #> 171 NA NA #> 172 NA NA #> 173 NA NA #> 174 NA NA #> 175 NA NA #> 176 + NA NA #> 177 NA NA #> 178 NA NA #> 179 NA NA #> 180 + NA NA #> 181 NA NA #> 182 NA NA #> 183 NA NA #> 184 NA NA #> 185 NA NA #> 186 + NA NA #> 187 I NA NA #> 188 NA NA #> 189 NA NA #> 190 + NA NA #> 191 NA NA #> 192 NA NA #> 193 NA NA #> 194 NA NA #> 195 NA NA #> 196 + NA NA #> 197 NA NA #> 198 NA NA #> 199 NA NA #> 200 + NA NA #> 201 NA NA #> 202 NA NA #> 203 I NA NA #> 204 NA NA #> 205 NA NA #> 206 + NA NA #> 207 U NA NA #> 208 NA NA #> 209 I NA NA #> 210 + NA NA #> 211 NA NA #> 212 NA NA #> 213 NA NA #> 214 NA NA #> 215 NA NA #> 216 + NA NA #> 217 I NA NA #> 218 NA NA #> 219 NA NA #> 220 + NA NA #> 221 NA NA #> 222 NA NA #> 223 NA NA #> 224 NA NA #> 225 NA NA #> 226 + NA NA #> 227 NA NA #> 228 NA NA #> 229 NA NA #> 230 + NA NA #> 231 NA NA #> 232 NA NA #> 233 NA NA #> 234 NA NA #> 235 NA NA #> 236 + NA NA #> 237 I NA NA #> 238 NA NA #> 239 NA NA #> 240 + NA NA #> 241 NA NA #> 242 NA NA #> 243 NA NA #> 244 NA NA #> 245 NA NA #> 246 + NA NA #> 247 NA NA #> 248 NA NA #> 249 NA NA #> 250 + NA NA #> 251 NA NA #> 252 NA NA #> 253 I NA NA #> 254 U NA NA #> 255 NA NA #> 256 + NA NA #> 257 I NA NA #> 258 NA NA #> 259 NA NA #> 260 + NA NA #> 261 NA NA #> 262 NA NA #> 263 NA NA #> 264 I NA NA #> 265 NA NA #> 266 + NA NA #> 267 NA NA #> 268 NA NA #> 269 NA NA #> 270 + NA NA #> 271 NA NA #> 272 NA NA #> 273 I NA NA #> 274 U NA NA #> 275 NA NA #> 276 + NA NA #> 277 U NA NA #> 278 NA NA #> 279 NA NA #> 280 + NA NA #> 281 NA NA #> 282 NA NA #> 283 NA NA #> 284 NA NA #> 285 + NA NA #> 286 NA NA #> 287 I NA NA #> 288 NA NA #> 289 NA NA #> 290 + NA NA #> 291 I NA NA #> 292 NA NA #> 293 NA NA #> 294 + NA NA #> 295 NA NA #> 296 NA NA #> 297 NA NA #> 298 + NA NA #> 299 NA NA #> 300 NA NA #> 301 A NA NA #> 302 NA NA #> 303 + NA NA #> 304 I NA NA #> 305 NA NA #> 306 NA NA #> 307 + NA NA #> 308 NA NA #> 309 NA NA #> 310 NA NA #> 311 NA NA #> 312 NA NA #> 313 + NA NA #> 314 NA NA #> 315 NA NA #> 316 NA NA #> 317 + NA NA #> 318 NA NA #> 319 A NA NA #> 320 NA NA #> 321 NA NA #> 322 I NA NA #> 323 NA NA #> 324 + NA NA #> 325 NA NA #> 326 NA NA #> 327 NA NA #> 328 NA NA #> 329 NA NA #> 330 + NA NA #> 331 NA NA #> 332 NA NA #> 333 NA NA #> 334 + NA NA #> 335 NA NA #> 336 NA NA #> 337 I NA NA #> 338 NA NA #> 339 NA NA #> 340 + NA NA #> 341 I NA NA #> 342 NA NA #> 343 NA NA #> 344 + NA NA #> 345 NA NA #> 346 NA NA #> 347 I NA NA #> 348 NA NA #> 349 NA NA #> 350 + NA NA #> 351 NA NA #> 352 NA NA #> 353 NA NA #> 354 + NA NA #> 355 NA NA #> 356 NA NA #> 357 NA NA #> 358 NA NA #> 359 NA NA #> 360 + NA NA #> 361 NA NA #> 362 NA NA #> 363 NA NA #> 364 + NA NA #> 365 NA NA #> 366 A NA NA #> 367 I NA NA #> 368 NA NA #> 369 NA NA #> 370 + NA NA #> 371 U NA NA #> 372 NA NA #> 373 NA NA #> 374 + NA NA #> 375 NA NA #> 376 NA NA #> 377 I NA NA #> 378 I NA NA #> 379 + NA NA #> 380 U NA NA #> 381 NA NA #> 382 NA NA #> 383 + NA NA #> 384 NA NA #> 385 NA NA #> 386 NA NA #> 387 NA NA #> 388 NA NA #> 389 NA NA #> 390 U NA NA #> 391 NA NA #> 392 NA NA #> 393 + NA NA #> 394 NA NA #> 395 NA NA #> 396 NA NA #> 397 NA NA #> 398 NA NA #> 399 NA NA #> 400 NA NA #> 401 NA NA #> 402 NA NA #> 403 + NA NA #> 404 NA NA #> 405 NA NA #> 406 NA NA #> 407 NA NA #> 408 NA NA #> 409 NA NA #> 410 I NA NA #> 411 NA NA #> 412 NA NA #> 413 + NA NA #> 414 NA NA #> 415 NA NA #> 416 I NA NA #> 417 NA NA #> 418 NA NA #> 419 NA NA #> 420 NA NA #> 421 NA NA #> 422 NA NA #> 423 + NA NA #> 424 NA NA #> 425 NA NA #> 426 I NA NA #> 427 NA NA #> 428 NA NA #> 429 NA NA #> 430 I NA NA #> 431 NA NA #> 432 + NA NA #> 433 NA NA #> 434 NA NA #> 435 NA NA #> 436 NA NA #> 437 NA NA #> 438 NA NA #> 439 I NA NA #> 440 NA NA #> 441 I NA NA #> 442 + NA NA #> 443 NA NA #> 444 NA NA #> 445 I NA NA #> 446 I NA NA #> 447 NA NA #> 448 NA NA #> 449 I NA NA #> 450 NA NA #> 451 NA NA #> 452 + NA NA #> 453 NA NA #> 454 NA NA #> 455 I NA NA #> 456 NA NA #> 457 NA NA #> 458 NA NA #> 459 I NA NA #> 460 NA NA #> 461 NA NA #> 462 + NA NA #> 463 NA NA #> 464 NA NA #> 465 NA NA #> 466 I NA NA #> 467 NA NA #> 468 NA NA #> 469 I NA NA #> 470 NA NA #> 471 NA NA #> 472 + NA NA #> 473 NA NA #> 474 NA NA #> 475 NA NA #> 476 I NA NA #> 477 NA NA #> 478 NA NA #> 479 NA NA #> 480 NA NA #> 481 NA NA #> 482 + NA NA #> 483 NA NA #> 484 NA NA #> 485 I NA NA #> 486 U NA NA #> 487 I NA NA #> 488 NA NA #> 489 + NA NA #> 490 NA NA #> 491 NA NA #> 492 I NA NA #> 493 NA NA #> 494 NA NA #> 495 NA NA #> 496 NA NA #> 497 NA NA #> 498 NA NA #> 499 + NA NA #> 500 NA NA #> 501 NA NA #> 502 U NA NA #> 503 I NA NA #> 504 NA NA #> 505 NA NA #> 506 NA NA #> 507 NA NA #> 508 NA NA #> 509 + NA NA #> 510 NA NA #> 511 NA NA #> 512 I NA NA #> 513 I NA NA #> 514 NA NA #> 515 NA NA #> 516 U NA NA #> 517 NA NA #> 518 I NA NA #> 519 + NA NA #> 520 NA NA #> 521 NA NA #> 522 I NA NA #> 523 I NA NA #> 524 NA NA #> 525 NA NA #> 526 NA NA #> 527 + NA NA #> 528 NA NA #> 529 A NA NA #> 530 I NA NA #> 531 I NA NA #> 532 NA NA #> 533 NA NA #> 534 U NA NA #> 535 NA NA #> 536 I NA NA #> 537 + NA NA #> 538 NA NA #> 539 NA NA #> 540 NA NA #> 541 I NA NA #> 542 NA NA #> 543 NA NA #> 544 U NA NA #> 545 NA NA #> 546 NA NA #> 547 + NA NA #> 548 NA NA #> 549 NA NA #> 550 NA NA #> 551 NA NA #> 552 NA NA #> 553 NA NA #> 554 I NA NA #> 555 NA NA #> 556 NA NA #> 557 + NA NA #> 558 NA NA #> 559 NA NA #> 560 NA NA #> 561 NA NA #> 562 NA NA #> 563 NA NA #> 564 NA NA #> 565 NA NA #> 566 NA NA #> 567 + NA NA #> 568 NA NA #> 569 NA NA #> 570 NA NA #> 571 NA NA #> 572 NA NA #> 573 NA NA #> 574 U NA NA #> 575 NA NA #> 576 NA NA #> 577 + NA NA #> 578 NA NA #> 579 NA NA #> 580 NA NA #> 581 NA NA #> 582 NA NA #> 583 NA NA #> 584 NA NA #> 585 NA NA #> 586 NA NA #> 587 + NA NA #> 588 NA NA #> 589 NA NA #> 590 I NA NA #> 591 U NA NA #> 592 NA NA #> 593 NA NA #> 594 I NA NA #> 595 NA NA #> 596 NA NA #> 597 + NA NA #> 598 NA NA #> 599 NA NA #> 600 I NA NA #> 601 U NA NA #> 602 NA NA #> 603 NA NA #> 604 I NA NA #> 605 NA NA #> 606 I NA NA #> 607 + NA NA #> 608 NA NA #> 609 A NA NA #> 610 I NA NA #> 611 U NA NA #> 612 NA NA #> 613 NA NA #> 614 I NA NA #> 615 NA NA #> 616 NA NA #> 617 + NA NA #> 618 NA NA #> 619 NA NA #> 620 I NA NA #> 621 U NA NA #> 622 NA NA #> 623 NA NA #> 624 U NA NA #> 625 NA NA #> 626 + NA NA #> 627 NA NA #> 628 NA NA #> 629 I NA NA #> 630 U NA NA #> 631 NA NA #> 632 NA NA #> 633 U NA NA #> 634 NA NA #> 635 NA NA #> 636 + NA NA #> 637 NA NA #> 638 NA NA #> 639 I NA NA #> 640 U NA NA #> 641 NA NA #> 642 NA NA #> 643 U NA NA #> 644 NA NA #> 645 NA NA #> 646 + NA NA #> 647 NA NA #> 648 NA NA #> 649 NA NA #> 650 NA NA #> 651 NA NA #> 652 NA NA #> 653 U NA NA #> 654 NA NA #> 655 NA NA #> 656 + NA NA #> 657 NA NA #> 658 NA NA #> 659 NA NA #> 660 NA NA #> 661 NA NA #> 662 NA NA #> 663 I NA NA #> 664 NA NA #> 665 NA NA #> 666 + NA NA #> 667 NA NA #> 668 NA NA #> 669 NA NA #> 670 NA NA #> 671 NA NA #> 672 NA NA #> 673 I NA NA #> 674 NA NA #> 675 NA NA #> 676 + NA NA #> 677 NA NA #> 678 NA NA #> 679 NA NA #> 680 I NA NA #> 681 NA NA #> 682 NA NA #> 683 I NA NA #> 684 NA NA #> 685 NA NA #> 686 + NA NA #> 687 NA NA #> 688 NA NA #> 689 NA NA #> 690 NA NA #> 691 NA NA #> 692 NA NA #> 693 NA NA #> 694 NA NA #> 695 NA NA #> 696 + NA NA #> 697 NA NA #> 698 NA NA #> 699 NA NA #> 700 NA NA #> 701 NA NA #> 702 NA NA #> 703 I NA NA #> 704 NA NA #> 705 NA NA #> 706 + NA NA #> 707 NA NA #> 708 NA NA #> 709 I NA NA #> 710 U NA NA #> 711 NA NA #> 712 NA NA #> 713 I NA NA #> 714 NA NA #> 715 I NA NA #> 716 + NA NA #> 717 NA NA #> 718 NA NA #> 719 NA NA #> 720 I NA NA #> 721 U NA NA #> 722 NA NA #> 723 NA NA #> 724 + NA NA #> 725 NA NA #> 726 NA NA #> 727 NA NA #> 728 A NA NA #> 729 NA NA #> 730 + NA NA #> 731 NA NA #> 732 NA NA #> 733 NA NA #> 734 + NA NA #> 735 NA NA #> 736 NA NA #> 737 NA NA #> 738 I NA NA #> 739 NA NA #> 740 I NA NA #> 741 NA NA #> 742 NA NA #> 743 + NA NA #> 744 NA NA #> 745 NA NA #> 746 NA NA #> 747 I NA NA #> 748 NA NA #> 749 + NA NA #> 750 I NA NA #> 751 NA NA #> 752 NA NA #> 753 + NA NA #> 754 NA NA #> 755 NA NA #> 756 NA NA #> 757 NA NA #> 758 + NA NA #> 759 I NA NA #> 760 NA NA #> 761 NA NA #> 762 + NA NA #> 763 NA NA #> 764 NA NA #> 765 NA NA #> 766 NA NA #> 767 NA NA #> 768 + NA NA #> 769 I NA NA #> 770 NA NA #> 771 NA NA #> 772 + NA NA #> 773 NA NA #> 774 NA NA #> 775 NA NA #> 776 NA NA #> 777 + NA NA #> 778 NA NA #> 779 NA NA #> 780 NA NA #> 781 + NA NA #> 782 NA NA #> 783 NA NA #> 784 I NA NA #> 785 NA NA #> 786 + NA NA #> 787 NA NA #> 788 NA NA #> 789 NA NA #> 790 + NA NA #> 791 NA NA #> 792 NA NA #> 793 I NA NA #> 794 I NA NA #> 795 NA NA #> 796 I NA NA #> 797 NA NA #> 798 I NA NA #> 799 + NA NA #> 800 NA NA #> 801 NA NA #> 802 NA NA #> 803 NA NA #> 804 NA NA #> 805 + NA NA #> 806 NA NA #> 807 NA NA #> 808 NA NA #> 809 + NA NA #> 810 NA NA #> 811 NA NA #> 812 NA NA #> 813 NA NA #> 814 NA NA #> 815 NA NA #> 816 NA NA #> 817 NA NA #> 818 + NA NA #> 819 NA NA #> 820 NA NA #> 821 NA NA #> 822 NA NA #> 823 + NA NA #> 824 NA NA #> 825 NA NA #> 826 NA NA #> 827 + NA NA #> 828 NA NA #> 829 NA NA #> 830 NA NA #> 831 NA NA #> 832 I NA NA #> 833 NA NA #> 834 NA NA #> 835 + NA NA #> 836 NA NA #> 837 A NA NA #> 838 I NA NA #> 839 NA NA #> 840 NA NA #> 841 NA NA #> 842 NA NA #> 843 NA NA #> 844 + NA NA #> 845 NA NA #> 846 NA NA #> 847 NA NA #> 848 A NA NA #> 849 NA NA #> 850 + NA NA #> 851 I NA NA #> 852 NA NA #> 853 NA NA #> 854 + NA NA #> 855 NA NA #> 856 NA NA #> 857 NA NA #> 858 NA NA #> 859 NA NA #> 860 + NA NA #> 861 NA NA #> 862 NA NA #> 863 NA NA #> 864 + NA NA #> 865 NA NA #> 866 NA NA #> 867 NA NA #> 868 NA NA #> 869 NA NA #> 870 NA NA #> 871 NA NA #> 872 + NA NA #> 873 NA NA #> 874 NA NA #> 875 I NA NA #> 876 NA NA #> 877 NA NA #> 878 + NA NA #> 879 NA NA #> 880 NA NA #> 881 NA NA #> 882 + NA NA #> 883 NA NA #> 884 A NA NA #> 885 I NA NA #> 886 NA NA #> 887 NA NA #> 888 + NA NA #> 889 I NA NA #> 890 NA NA #> 891 NA NA #> 892 + NA NA #> 893 NA NA #> 894 NA NA #> 895 I NA NA #> 896 NA NA #> 897 NA NA #> 898 + NA NA #> 899 I NA NA #> 900 NA NA #> 901 NA NA #> 902 + NA NA #> 903 NA NA #> 904 NA NA #> 905 NA NA #> 906 NA NA #> 907 NA NA #> 908 + NA NA #> 909 I NA NA #> 910 NA NA #> 911 NA NA #> 912 + NA NA #> 913 NA NA #> 914 NA NA #> 915 NA NA #> 916 NA NA #> 917 NA NA #> 918 + NA NA #> 919 NA NA #> 920 NA NA #> 921 NA NA #> 922 + NA NA #> 923 NA NA #> 924 NA NA #> 925 NA NA #> 926 NA NA #> 927 NA NA #> 928 + NA NA #> 929 NA NA #> 930 NA NA #> 931 NA NA #> 932 + NA NA #> 933 NA NA #> 934 NA NA #> 935 I NA NA #> 936 U NA NA #> 937 NA NA #> 938 + NA NA #> 939 NA NA #> 940 NA NA #> 941 NA NA #> 942 + NA NA #> 943 NA NA #> 944 A NA NA #> 945 NA NA #> 946 I NA NA #> 947 NA NA #> 948 + NA NA #> 949 NA NA #> 950 NA NA #> 951 NA NA #> 952 + NA NA #> 953 NA NA #> 954 NA NA #> 955 NA NA #> 956 A NA NA #> 957 NA NA #> 958 + NA NA #> 959 NA NA #> 960 NA NA #> 961 NA NA #> 962 + NA NA #> 963 NA NA #> 964 NA NA #> 965 I NA NA #> 966 NA NA #> 967 NA NA #> 968 + NA NA #> 969 I NA NA #> 970 NA NA #> 971 NA NA #> 972 + NA NA #> 973 NA NA #> 974 NA NA #> 975 NA NA #> 976 NA NA #> 977 NA NA #> 978 + NA NA #> 979 I NA NA #> 980 NA NA #> 981 NA NA #> 982 + NA NA #> 983 NA NA #> 984 NA NA #> 985 NA NA #> 986 I NA NA #> 987 NA NA #> 988 + NA NA #> 989 U NA NA #> 990 NA NA #> 991 NA NA #> 992 + NA NA #> 993 NA NA #> 994 NA NA #> 995 NA NA #> 996 NA NA #> 997 NA NA #> 998 + NA NA #> 999 NA NA #> 1000 NA NA #> 1001 NA NA #> 1002 + NA NA #> 1003 NA NA #> 1004 NA NA #> 1005 NA NA #> 1006 NA NA #> 1007 NA NA #> 1008 + NA NA #> 1009 NA NA #> 1010 NA NA #> 1011 NA NA #> 1012 + NA NA #> 1013 NA NA #> 1014 NA NA #> 1015 NA NA #> 1016 NA NA #> 1017 I NA NA #> 1018 NA NA #> 1019 + NA NA #> 1020 NA NA #> 1021 NA NA #> 1022 NA NA #> 1023 NA NA #> 1024 NA NA #> 1025 + NA NA #> 1026 NA NA #> 1027 NA NA #> 1028 NA NA #> 1029 + NA NA #> 1030 NA NA #> 1031 A NA NA #> 1032 NA NA #> 1033 NA NA #> 1034 NA NA #> 1035 + NA NA #> 1036 I NA NA #> 1037 NA NA #> 1038 NA NA #> 1039 + NA NA #> 1040 NA NA #> 1041 A NA NA #> 1042 NA NA #> 1043 NA NA #> 1044 NA NA #> 1045 + NA NA #> 1046 NA NA #> 1047 NA NA #> 1048 NA NA #> 1049 + NA NA #> 1050 NA NA #> 1051 NA NA #> 1052 I NA NA #> 1053 NA NA #> 1054 NA NA #> 1055 + NA NA #> 1056 NA NA #> 1057 NA NA #> 1058 NA NA #> 1059 + NA NA #> 1060 NA NA #> 1061 NA NA #> 1062 NA NA #> 1063 NA NA #> 1064 NA NA #> 1065 + NA NA #> 1066 I NA NA #> 1067 NA NA #> 1068 NA NA #> 1069 + NA NA #> 1070 NA NA #> 1071 A NA NA #> 1072 NA NA #> 1073 I NA NA #> 1074 NA NA #> 1075 + NA NA #> 1076 I NA NA #> 1077 NA NA #> 1078 NA NA #> 1079 + NA NA #> 1080 NA NA #> 1081 NA NA #> 1082 NA NA #> 1083 NA NA #> 1084 NA NA #> 1085 NA NA #> 1086 I NA NA #> 1087 NA NA #> 1088 NA NA #> 1089 + NA NA #> 1090 NA NA #> 1091 NA NA #> 1092 NA NA #> 1093 NA NA #> 1094 NA NA #> 1095 NA NA #> 1096 I NA NA #> 1097 NA NA #> 1098 NA NA #> 1099 + NA NA #> 1100 NA NA #> 1101 NA NA #> 1102 A NA NA #> 1103 NA NA #> 1104 NA NA #> 1105 I NA NA #> 1106 NA NA #> 1107 NA NA #> 1108 + NA NA #> 1109 NA NA #> 1110 A NA NA #> 1111 I NA NA #> 1112 NA NA #> 1113 NA NA #> 1114 NA NA #> 1115 NA NA #> 1116 NA NA #> 1117 NA NA #> 1118 + NA NA #> 1119 NA NA #> 1120 NA NA #> 1121 I NA NA #> 1122 NA NA #> 1123 I NA NA #> 1124 NA NA #> 1125 NA NA #> 1126 + NA NA #> 1127 NA NA #> 1128 NA NA #> 1129 I NA NA #> 1130 NA NA #> 1131 U NA NA #> 1132 NA NA #> 1133 + NA NA #> 1134 NA NA #> 1135 NA NA #> 1136 I NA NA #> 1137 NA NA #> 1138 NA NA #> 1139 NA NA #> 1140 I NA NA #> 1141 NA NA #> 1142 NA NA #> 1143 + NA NA #> 1144 NA NA #> 1145 NA NA #> 1146 I NA NA #> 1147 I NA NA #> 1148 NA NA #> 1149 NA NA #> 1150 NA NA #> 1151 NA NA #> 1152 NA NA #> 1153 + NA NA #> 1154 NA NA #> 1155 NA NA #> 1156 I NA NA #> 1157 NA NA #> 1158 I NA NA #> 1159 NA NA #> 1160 NA NA #> 1161 + NA NA #> 1162 NA NA #> 1163 NA NA #> 1164 I NA NA #> 1165 A NA NA #> 1166 NA NA #> 1167 NA NA #> 1168 I NA NA #> 1169 NA NA #> 1170 NA NA #> 1171 + NA NA #> 1172 NA NA #> 1173 NA NA #> 1174 NA NA #> 1175 I NA NA #> 1176 NA NA #> 1177 NA NA #> 1178 I NA NA #> 1179 NA NA #> 1180 NA NA #> 1181 + NA NA #> 1182 NA NA #> 1183 NA NA #> 1184 NA NA #> 1185 I NA NA #> 1186 NA NA #> 1187 NA NA #> 1188 NA NA #> 1189 NA NA #> 1190 NA NA #> 1191 + NA NA #> 1192 NA NA #> 1193 NA NA #> 1194 I NA NA #> 1195 U NA NA #> 1196 NA NA #> 1197 NA NA #> 1198 NA NA #> 1199 NA NA #> 1200 NA NA #> 1201 + NA NA #> 1202 NA NA #> 1203 NA NA #> 1204 I NA NA #> 1205 NA NA #> 1206 NA NA #> 1207 NA NA #> 1208 NA NA #> 1209 + NA NA #> 1210 NA NA #> 1211 NA NA #> 1212 I NA NA #> 1213 NA NA #> 1214 NA NA #> 1215 NA NA #> 1216 NA NA #> 1217 NA NA #> 1218 NA NA #> 1219 + NA NA #> 1220 NA NA #> 1221 NA NA #> 1222 I NA NA #> 1223 U NA NA #> 1224 NA NA #> 1225 NA NA #> 1226 I NA NA #> 1227 NA NA #> 1228 + NA NA #> 1229 NA NA #> 1230 A NA NA #> 1231 NA NA #> 1232 A NA NA #> 1233 NA NA #> 1234 NA NA #> 1235 NA NA #> 1236 NA NA #> 1237 NA NA #> 1238 + NA NA #> 1239 NA NA #> 1240 NA NA #> 1241 I NA NA #> 1242 A NA NA #> 1243 NA NA #> 1244 NA NA #> 1245 NA NA #> 1246 NA NA #> 1247 NA NA #> 1248 + NA NA #> 1249 NA NA #> 1250 A NA NA #> 1251 + NA NA #> 1252 NA NA #> 1253 NA NA #> 1254 NA NA #> 1255 NA NA #> 1256 NA NA #> 1257 NA NA #> 1258 NA NA #> 1259 NA NA #> 1260 NA NA #> 1261 U NA NA #> 1262 NA NA #> 1263 NA NA #> 1264 NA NA #> 1265 NA NA #> 1266 NA NA #> 1267 + NA NA #> 1268 NA NA #> 1269 NA NA #> 1270 I NA NA #> 1271 U NA NA #> 1272 NA NA #> 1273 NA NA #> 1274 I NA NA #> 1275 NA NA #> 1276 NA NA #> 1277 + NA NA #> 1278 NA NA #> 1279 NA NA #> 1280 I NA NA #> 1281 I NA NA #> 1282 NA NA #> 1283 NA NA #> 1284 I NA NA #> 1285 NA NA #> 1286 NA NA #> 1287 + NA NA #> 1288 NA NA #> 1289 NA NA #> 1290 + NA NA #> 1291 I NA NA #> 1292 NA NA #> 1293 NA NA #> 1294 NA NA #> 1295 I NA NA #> 1296 NA NA #> 1297 I NA NA #> 1298 NA NA #> 1299 NA NA #> 1300 I NA NA #> 1301 NA NA #> 1302 NA NA #> 1303 NA NA #> 1304 I NA NA #> 1305 NA NA #> 1306 NA NA #> 1307 + NA NA #> 1308 NA NA #> 1309 NA NA #> 1310 I NA NA #> 1311 I NA NA #> 1312 NA NA #> 1313 NA NA #> 1314 I NA NA #> 1315 NA NA #> 1316 NA NA #> 1317 + NA NA #> 1318 NA NA #> 1319 NA NA #> 1320 NA NA #> 1321 NA NA #> 1322 NA NA #> 1323 NA NA #> 1324 U NA NA #> 1325 NA NA #> 1326 NA NA #> 1327 + NA NA #> 1328 NA NA #> 1329 NA NA #> 1330 NA NA #> 1331 NA NA #> 1332 NA NA #> 1333 NA NA #> 1334 I NA NA #> 1335 NA NA #> 1336 NA NA #> 1337 + NA NA #> 1338 NA NA #> 1339 NA NA #> 1340 NA NA #> 1341 NA NA #> 1342 NA NA #> 1343 NA NA #> 1344 I NA NA #> 1345 NA NA #> 1346 NA NA #> 1347 + NA NA #> 1348 NA NA #> 1349 A NA NA #> 1350 NA NA #> 1351 NA NA #> 1352 NA NA #> 1353 NA NA #> 1354 NA NA #> 1355 NA NA #> 1356 NA NA #> 1357 + NA NA #> 1358 NA NA #> 1359 NA NA #> 1360 I NA NA #> 1361 U NA NA #> 1362 NA NA #> 1363 NA NA #> 1364 I NA NA #> 1365 NA NA #> 1366 NA NA #> 1367 + NA NA #> 1368 NA NA #> 1369 NA NA #> 1370 I NA NA #> 1371 I NA NA #> 1372 NA NA #> 1373 NA NA #> 1374 NA NA #> 1375 NA NA #> 1376 NA NA #> 1377 + NA NA #> 1378 NA NA #> 1379 NA NA #> 1380 I NA NA #> 1381 U NA NA #> 1382 NA NA #> 1383 NA NA #> 1384 NA NA #> 1385 NA NA #> 1386 NA NA #> 1387 + NA NA #> 1388 NA NA #> 1389 NA NA #> 1390 I NA NA #> 1391 U NA NA #> 1392 NA NA #> 1393 NA NA #> 1394 U NA NA #> 1395 NA NA #> 1396 I NA NA #> 1397 + NA NA #> 1398 NA NA #> 1399 NA NA #> 1400 I NA NA #> 1401 U NA NA #> 1402 NA NA #> 1403 NA NA #> 1404 I NA NA #> 1405 NA NA #> 1406 I NA NA #> 1407 + NA NA #> 1408 NA NA #> 1409 A NA NA #> 1410 I NA NA #> 1411 U NA NA #> 1412 NA NA #> 1413 NA NA #> 1414 I NA NA #> 1415 NA NA #> 1416 NA NA #> 1417 + NA NA #> 1418 NA NA #> 1419 NA NA #> 1420 I NA NA #> 1421 NA NA #> 1422 NA NA #> 1423 NA NA #> 1424 I NA NA #> 1425 NA NA #> 1426 NA NA #> 1427 + NA NA #> 1428 NA NA #> 1429 NA NA #> 1430 NA NA #> 1431 I NA NA #> 1432 NA NA #> 1433 NA NA #> 1434 I NA NA #> 1435 NA NA #> 1436 NA NA #> 1437 + NA NA #> 1438 NA NA #> 1439 A NA NA #> 1440 I NA NA #> 1441 I NA NA #> 1442 NA NA #> 1443 NA NA #> 1444 NA NA #> 1445 NA NA #> 1446 NA NA #> 1447 + NA NA #> 1448 NA NA #> 1449 NA NA #> 1450 NA NA #> 1451 NA NA #> 1452 I NA NA #> 1453 NA NA #> 1454 NA NA #> 1455 + NA NA #> 1456 NA NA #> 1457 NA NA #> 1458 NA NA #> 1459 A NA NA #> 1460 NA NA #> 1461 NA NA #> 1462 U NA NA #> 1463 NA NA #> 1464 NA NA #> 1465 + NA NA #> 1466 NA NA #> 1467 A NA NA #> 1468 NA NA #> 1469 A NA NA #> 1470 I NA NA #> 1471 NA NA #> 1472 NA NA #> 1473 + NA NA #> 1474 NA NA #> 1475 NA NA #> 1476 NA NA #> 1477 NA NA #> 1478 NA NA #> 1479 NA NA #> 1480 U NA NA #> 1481 NA NA #> 1482 NA NA #> 1483 + NA NA #> 1484 NA NA #> 1485 NA NA #> 1486 I NA NA #> 1487 NA NA #> 1488 NA NA #> 1489 NA NA #> 1490 I NA NA #> 1491 NA NA #> 1492 NA NA #> 1493 + NA NA #> 1494 NA NA #> 1495 NA NA #> 1496 NA NA #> 1497 NA NA #> 1498 NA NA #> 1499 NA NA #> 1500 NA NA #> 1501 NA NA #> 1502 NA NA #> 1503 U NA NA #> 1504 + NA NA #> 1505 I NA NA #> 1506 + NA NA #> 1507 NA NA #> 1508 NA NA #> 1509 NA NA #> 1510 NA NA #> 1511 NA NA #> 1512 NA NA #> 1513 NA NA #> 1514 U NA NA #> 1515 + NA NA #> 1516 NA NA #> 1517 + NA NA #> 1518 NA NA #> 1519 I NA NA #> 1520 NA NA #> 1521 NA NA #> 1522 NA NA #> 1523 NA NA #> 1524 NA NA #> 1525 I NA NA #> 1526 NA NA #> 1527 + NA NA #> 1528 NA NA #> 1529 I NA NA #> 1530 A NA NA #> 1531 NA NA #> 1532 NA NA #> 1533 NA NA #> 1534 NA NA #> 1535 NA NA #> 1536 NA NA #> 1537 + NA NA #> 1538 NA NA #> 1539 I NA NA #> 1540 NA NA #> 1541 NA NA #> 1542 NA NA #> 1543 NA NA #> 1544 NA NA #> 1545 G NA NA #> 1546 NA NA #> 1547 NA NA #> 1548 + NA NA #> 1549 NA NA #> 1550 I NA NA #> 1551 NA NA #> 1552 I NA NA #> 1553 NA NA #> 1554 NA NA #> 1555 + NA NA #> 1556 I NA NA #> 1557 NA NA #> 1558 NA NA #> 1559 + NA NA #> 1560 NA NA #> 1561 NA NA #> 1562 NA NA #> 1563 NA NA #> 1564 NA NA #> 1565 + NA NA #> 1566 NA NA #> 1567 NA NA #> 1568 NA NA #> 1569 + NA NA #> 1570 NA NA #> 1571 NA NA #> 1572 NA NA #> 1573 NA NA #> 1574 NA NA #> 1575 + NA NA #> 1576 I NA NA #> 1577 NA NA #> 1578 NA NA #> 1579 + NA NA #> 1580 NA NA #> 1581 NA NA #> 1582 NA NA #> 1583 A NA NA #> 1584 NA NA #> 1585 + NA NA #> 1586 NA NA #> 1587 NA NA #> 1588 NA NA #> 1589 + NA NA #> 1590 NA NA #> 1591 A NA NA #> 1592 NA NA #> 1593 NA NA #> 1594 NA NA #> 1595 + NA NA #> 1596 NA NA #> 1597 NA NA #> 1598 NA NA #> 1599 + NA NA #> 1600 NA NA #> 1601 NA NA #> 1602 NA NA #> 1603 A NA NA #> 1604 NA NA #> 1605 + NA NA #> 1606 I NA NA #> 1607 NA NA #> 1608 NA NA #> 1609 + NA NA #> 1610 NA NA #> 1611 NA NA #> 1612 NA NA #> 1613 A NA NA #> 1614 NA NA #> 1615 + NA NA #> 1616 I NA NA #> 1617 NA NA #> 1618 NA NA #> 1619 + NA NA #> 1620 NA NA #> 1621 NA NA #> 1622 NA NA #> 1623 NA NA #> 1624 NA NA #> 1625 + NA NA #> 1626 I NA NA #> 1627 NA NA #> 1628 NA NA #> 1629 + NA NA #> 1630 NA NA #> 1631 NA NA #> 1632 NA NA #> 1633 NA NA #> 1634 NA NA #> 1635 + NA NA #> 1636 U NA NA #> 1637 NA NA #> 1638 NA NA #> 1639 + NA NA #> 1640 NA NA #> 1641 NA NA #> 1642 NA NA #> 1643 NA NA #> 1644 NA NA #> 1645 + NA NA #> 1646 I NA NA #> 1647 NA NA #> 1648 NA NA #> 1649 + NA NA #> 1650 NA NA #> 1651 NA NA #> 1652 NA NA #> 1653 NA NA #> 1654 NA NA #> 1655 + NA NA #> 1656 NA NA #> 1657 NA NA #> 1658 NA NA #> 1659 + NA NA #> 1660 NA NA #> 1661 NA NA #> 1662 NA NA #> 1663 NA NA #> 1664 NA NA #> 1665 + NA NA #> 1666 NA NA #> 1667 NA NA #> 1668 NA NA #> 1669 + NA NA #> 1670 NA NA #> 1671 NA NA #> 1672 NA NA #> 1673 NA NA #> 1674 NA NA #> 1675 + NA NA #> 1676 I NA NA #> 1677 NA NA #> 1678 NA NA #> 1679 + NA NA #> 1680 NA NA #> 1681 NA NA #> 1682 A NA NA #> 1683 NA NA #> 1684 NA NA #> 1685 + NA NA #> 1686 NA NA #> 1687 NA NA #> 1688 NA NA #> 1689 + NA NA #> 1690 NA NA #> 1691 NA NA #> 1692 NA NA #> 1693 NA NA #> 1694 NA NA #> 1695 + NA NA #> 1696 U NA NA #> 1697 NA NA #> 1698 NA NA #> 1699 + NA NA #> 1700 NA NA #> 1701 NA NA #> 1702 NA NA #> 1703 NA NA #> 1704 NA NA #> 1705 + NA NA #> 1706 I NA NA #> 1707 NA NA #> 1708 NA NA #> 1709 + NA NA #> 1710 NA NA #> 1711 NA NA #> 1712 NA NA #> 1713 NA NA #> 1714 NA NA #> 1715 + NA NA #> 1716 I NA NA #> 1717 NA NA #> 1718 NA NA #> 1719 + NA NA #> 1720 NA NA #> 1721 NA NA #> 1722 NA NA #> 1723 NA NA #> 1724 NA NA #> 1725 + NA NA #> 1726 I NA NA #> 1727 NA NA #> 1728 NA NA #> 1729 + NA NA #> 1730 NA NA #> 1731 NA NA #> 1732 NA NA #> 1733 NA NA #> 1734 NA NA #> 1735 + NA NA #> 1736 I NA NA #> 1737 NA NA #> 1738 NA NA #> 1739 + NA NA #> 1740 NA NA #> 1741 NA NA #> 1742 NA NA #> 1743 A NA NA #> 1744 NA NA #> 1745 + NA NA #> 1746 U NA NA #> 1747 NA NA #> 1748 NA NA #> 1749 + NA NA #> 1750 NA NA #> 1751 NA NA #> 1752 NA NA #> 1753 NA NA #> 1754 NA NA #> 1755 + NA NA #> 1756 NA NA #> 1757 NA NA #> 1758 NA NA #> 1759 + NA NA #> 1760 NA NA #> 1761 NA NA #> 1762 NA NA #> 1763 NA NA #> 1764 NA NA #> 1765 + NA NA #> 1766 NA NA #> 1767 NA NA #> 1768 NA NA #> 1769 + NA NA #> 1770 NA NA #> 1771 NA NA #> 1772 NA NA #> 1773 NA NA #> 1774 + NA NA #> 1775 NA NA #> 1776 NA NA #> 1777 NA NA #> 1778 + NA NA #> 1779 NA NA #> 1780 NA NA #> 1781 NA NA #> 1782 NA NA #> 1783 NA NA #> 1784 + NA NA #> 1785 I NA NA #> 1786 NA NA #> 1787 NA NA #> 1788 + NA NA #> 1789 NA NA #> 1790 A NA NA #> 1791 NA NA #> 1792 NA NA #> 1793 NA NA #> 1794 + NA NA #> 1795 NA NA #> 1796 NA NA #> 1797 NA NA #> 1798 + NA NA #> 1799 NA NA #> 1800 NA NA #> 1801 I NA NA #> 1802 NA NA #> 1803 NA NA #> 1804 + NA NA #> 1805 U NA NA #> 1806 NA NA #> 1807 NA NA #> 1808 + NA NA #> 1809 NA NA #> 1810 NA NA #> 1811 NA NA #> 1812 NA NA #> 1813 + NA NA #> 1814 U NA NA #> 1815 NA NA #> 1816 NA NA #> 1817 + NA NA #> 1818 NA NA #> 1819 NA NA #> 1820 NA NA #> 1821 NA NA #> 1822 NA NA #> 1823 + NA NA #> 1824 NA NA #> 1825 NA NA #> 1826 NA NA #> 1827 + NA NA #> 1828 NA NA #> 1829 NA NA #> 1830 NA NA #> 1831 A NA NA #> 1832 U NA NA #> 1833 NA NA #> 1834 + NA NA #> 1835 NA NA #> 1836 NA NA #> 1837 NA NA #> 1838 NA NA #> 1839 NA NA #> 1840 + NA NA #> 1841 I NA NA #> 1842 NA NA #> 1843 NA NA #> 1844 + NA NA #> 1845 NA NA #> 1846 NA NA #> 1847 NA NA #> 1848 NA NA #> 1849 I NA NA #> 1850 NA NA #> 1851 NA NA #> 1852 + NA NA #> 1853 NA NA #> 1854 NA NA #> 1855 A NA NA #> 1856 NA NA #> 1857 NA NA #> 1858 + NA NA #> 1859 NA NA #> 1860 NA NA #> 1861 NA NA #> 1862 + NA NA #> 1863 NA NA #> 1864 NA NA #> 1865 NA NA #> 1866 NA NA #> 1867 NA NA #> 1868 + NA NA #> 1869 I NA NA #> 1870 NA NA #> 1871 NA NA #> 1872 + NA NA #> 1873 NA NA #> 1874 NA NA #> 1875 U NA NA #> 1876 U NA NA #> 1877 NA NA #> 1878 + NA NA #> 1879 NA NA #> 1880 NA NA #> 1881 NA NA #> 1882 + NA NA #> 1883 NA NA #> 1884 NA NA #> 1885 I NA NA #> 1886 NA NA #> 1887 NA NA #> 1888 NA NA #> 1889 U NA NA #> 1890 NA NA #> 1891 NA NA #> 1892 + NA NA #> 1893 NA NA #> 1894 NA NA #> 1895 NA NA #> 1896 NA NA #> 1897 NA NA #> 1898 NA NA #> 1899 I NA NA #> 1900 NA NA #> 1901 NA NA #> 1902 + NA NA #> 1903 NA NA #> 1904 NA NA #> 1905 I NA NA #> 1906 NA NA #> 1907 NA NA #> 1908 NA NA #> 1909 U NA NA #> 1910 NA NA #> 1911 NA NA #> 1912 + NA NA #> 1913 NA NA #> 1914 NA NA #> 1915 NA NA #> 1916 NA NA #> 1917 NA NA #> 1918 NA NA #> 1919 U NA NA #> 1920 NA NA #> 1921 NA NA #> 1922 + NA NA #> 1923 NA NA #> 1924 NA NA #> 1925 NA NA #> 1926 NA NA #> 1927 NA NA #> 1928 NA NA #> 1929 U NA NA #> 1930 NA NA #> 1931 NA NA #> 1932 + NA NA #> 1933 NA NA #> 1934 NA NA #> 1935 NA NA #> 1936 A NA NA #> 1937 NA NA #> 1938 NA NA #> 1939 U NA NA #> 1940 NA NA #> 1941 NA NA #> 1942 + NA NA #> 1943 NA NA #> 1944 A NA NA #> 1945 + NA NA #> 1946 I NA NA #> 1947 NA NA #> 1948 NA NA #> 1949 NA NA #> 1950 I NA NA #> 1951 NA NA #> 1952 NA NA #> 1953 NA NA #> 1954 NA NA #> 1955 NA NA #> 1956 NA NA #> 1957 NA NA #> 1958 NA NA #> 1959 NA NA #> 1960 NA NA #> 1961 NA NA #> 1962 + NA NA #> 1963 NA NA #> 1964 NA NA #> 1965 I NA NA #> 1966 NA NA #> 1967 NA NA #> 1968 NA NA #> 1969 NA NA #> 1970 NA NA #> 1971 NA NA #> 1972 + NA NA #> 1973 NA NA #> 1974 NA NA #> 1975 NA NA #> 1976 A NA NA #> 1977 NA NA #> 1978 NA NA #> 1979 NA NA #> 1980 NA NA #> 1981 NA NA #> 1982 + NA NA #> 1983 NA NA #> 1984 NA NA #> 1985 I NA NA #> 1986 NA NA #> 1987 NA NA #> 1988 NA NA #> 1989 I NA NA #> 1990 NA NA #> 1991 NA NA #> 1992 + NA NA #> 1993 NA NA #> 1994 NA NA #> 1995 I NA NA #> 1996 NA NA #> 1997 NA NA #> 1998 NA NA #> 1999 I NA NA #> 2000 NA NA #> 2001 NA NA #> 2002 + NA NA #> 2003 NA NA #> 2004 NA NA #> 2005 NA NA #> 2006 NA NA #> 2007 NA NA #> 2008 NA NA #> 2009 U NA NA #> 2010 NA NA #> 2011 NA NA #> 2012 + NA NA #> 2013 NA NA #> 2014 NA NA #> 2015 NA NA #> 2016 NA NA #> 2017 NA NA #> 2018 NA NA #> 2019 I NA NA #> 2020 NA NA #> 2021 NA NA #> 2022 + NA NA #> 2023 NA NA #> 2024 NA NA #> 2025 NA NA #> 2026 NA NA #> 2027 NA NA #> 2028 NA NA #> 2029 I NA NA #> 2030 NA NA #> 2031 NA NA #> 2032 + NA NA #> 2033 NA NA #> 2034 NA NA #> 2035 I NA NA #> 2036 A NA NA #> 2037 NA NA #> 2038 NA NA #> 2039 NA NA #> 2040 NA NA #> 2041 NA NA #> 2042 + NA NA #> 2043 NA NA #> 2044 NA NA #> 2045 NA NA #> 2046 A NA NA #> 2047 NA NA #> 2048 NA NA #> 2049 NA NA #> 2050 NA NA #> 2051 NA NA #> 2052 + NA NA #> 2053 NA NA #> 2054 NA NA #> 2055 I NA NA #> 2056 NA NA #> 2057 NA NA #> 2058 NA NA #> 2059 NA NA #> 2060 NA NA #> 2061 NA NA #> 2062 + NA NA #> 2063 NA NA #> 2064 NA NA #> 2065 I NA NA #> 2066 NA NA #> 2067 NA NA #> 2068 NA NA #> 2069 U NA NA #> 2070 NA NA #> 2071 NA NA #> 2072 + NA NA #> 2073 NA NA #> 2074 NA NA #> 2075 I NA NA #> 2076 A NA NA #> 2077 NA NA #> 2078 NA NA #> 2079 U NA NA #> 2080 NA NA #> 2081 NA NA #> 2082 + NA NA #> 2083 NA NA #> 2084 A NA NA #> 2085 I NA NA #> 2086 NA NA #> 2087 NA NA #> 2088 NA NA #> 2089 U NA NA #> 2090 NA NA #> 2091 NA NA #> 2092 + NA NA #> 2093 NA NA #> 2094 NA NA #> 2095 NA NA #> 2096 NA NA #> 2097 NA NA #> 2098 NA NA #> 2099 U NA NA #> 2100 NA NA #> 2101 NA NA #> 2102 + NA NA #> 2103 NA NA #> 2104 NA NA #> 2105 NA NA #> 2106 NA NA #> 2107 NA NA #> 2108 NA NA #> 2109 U NA NA #> 2110 NA NA #> 2111 NA NA #> 2112 + NA NA #> 2113 NA NA #> 2114 NA NA #> 2115 NA NA #> 2116 A NA NA #> 2117 NA NA #> 2118 NA NA #> 2119 I NA NA #> 2120 NA NA #> 2121 NA NA #> 2122 + NA NA #> 2123 NA NA #> 2124 NA NA #> 2125 I NA NA #> 2126 NA NA #> 2127 NA NA #> 2128 NA NA #> 2129 I NA NA #> 2130 NA NA #> 2131 NA NA #> 2132 + NA NA #> 2133 NA NA #> 2134 A NA NA #> 2135 I NA NA #> 2136 NA NA #> 2137 NA NA #> 2138 NA NA #> 2139 NA NA #> 2140 NA NA #> 2141 NA NA #> 2142 + NA NA #> 2143 NA NA #> 2144 NA NA #> 2145 NA NA #> 2146 NA NA #> 2147 NA NA #> 2148 NA NA #> 2149 I NA NA #> 2150 NA NA #> 2151 NA NA #> 2152 + NA NA #> 2153 NA NA #> 2154 NA NA #> 2155 U NA NA #> 2156 A NA NA #> 2157 NA NA #> 2158 NA NA #> 2159 I NA NA #> 2160 NA NA #> 2161 NA NA #> 2162 + NA NA #> 2163 NA NA #> 2164 NA NA #> 2165 I NA NA #> 2166 A NA NA #> 2167 NA NA #> 2168 NA NA #> 2169 I NA NA #> 2170 NA NA #> 2171 NA NA #> 2172 + NA NA #> 2173 NA NA #> 2174 NA NA #> 2175 I NA NA #> 2176 NA NA #> 2177 NA NA #> 2178 NA NA #> 2179 I NA NA #> 2180 NA NA #> 2181 + NA NA #> 2182 NA NA #> 2183 NA NA #> 2184 U NA NA #> 2185 NA NA #> 2186 NA NA #> 2187 U NA NA #> 2188 NA NA #> 2189 + NA NA #> 2190 NA NA #> 2191 NA NA #> 2192 NA NA #> 2193 NA NA #> 2194 I NA NA #> 2195 NA NA #> 2196 NA NA #> 2197 + NA NA #> 2198 NA NA #> 2199 NA NA #> 2200 NA NA #> 2201 A NA NA #> 2202 NA NA #> 2203 NA NA #> 2204 NA NA #> 2205 NA NA #> 2206 NA NA #> 2207 + NA NA #> 2208 NA NA #> 2209 NA NA #> 2210 NA NA #> 2211 A NA NA #> 2212 NA NA #> 2213 NA NA #> 2214 I NA NA #> 2215 NA NA #> 2216 NA NA #> 2217 + NA NA #> 2218 NA NA #> 2219 NA NA #> 2220 NA NA #> 2221 A NA NA #> 2222 NA NA #> 2223 NA NA #> 2224 I NA NA #> 2225 NA NA #> 2226 NA NA #> 2227 + NA NA #> 2228 NA NA #> 2229 NA NA #> 2230 NA NA #> 2231 NA NA #> 2232 NA NA #> 2233 NA NA #> 2234 U NA NA #> 2235 NA NA #> 2236 NA NA #> 2237 + NA NA #> 2238 NA NA #> 2239 NA NA #> 2240 NA NA #> 2241 NA NA #> 2242 NA NA #> 2243 NA NA #> 2244 NA NA #> 2245 NA NA #> 2246 + NA NA #> 2247 NA NA #> 2248 NA NA #> 2249 NA NA #> 2250 A NA NA #> 2251 NA NA #> 2252 NA NA #> 2253 I NA NA #> 2254 NA NA #> 2255 NA NA #> 2256 + NA NA #> 2257 NA NA #> 2258 NA NA #> 2259 NA NA #> 2260 NA NA #> 2261 NA NA #> 2262 NA NA #> 2263 NA NA #> 2264 NA NA #> 2265 NA NA #> 2266 I NA NA #> 2267 + NA NA #> 2268 NA NA #> 2269 + NA NA #> 2270 NA NA #> 2271 I NA NA #> 2272 NA NA #> 2273 NA NA #> 2274 NA NA #> 2275 NA NA #> 2276 NA NA #> 2277 U NA NA #> 2278 + NA NA #> 2279 NA NA #> 2280 + NA NA #> 2281 NA NA #> 2282 I NA NA #> 2283 NA NA #> 2284 NA NA #> 2285 NA NA #> 2286 NA NA #> 2287 NA NA #> 2288 U NA NA #> 2289 + NA NA #> 2290 NA NA #> 2291 + NA NA #> 2292 I NA NA #> 2293 NA NA #> 2294 NA NA #> 2295 NA NA #> 2296 NA NA #> 2297 NA NA #> 2298 I NA NA #> 2299 NA NA #> 2300 + NA NA #> 2301 NA NA #> 2302 U NA NA #> 2303 A NA NA #> 2304 NA NA #> 2305 NA NA #> 2306 NA NA #> 2307 NA NA #> 2308 G NA NA #> 2309 NA NA #> 2310 NA NA #> 2311 + NA NA #> 2312 NA NA #> 2313 I NA NA #> 2314 NA NA #> 2315 NA NA #> 2316 NA NA #> 2317 NA NA #> 2318 NA NA #> 2319 I NA NA #> 2320 NA NA #> 2321 NA NA #> 2322 + NA NA #> 2323 NA NA #> 2324 I NA NA #> 2325 NA NA #> 2326 NA NA #> 2327 NA NA #> 2328 NA NA #> 2329 NA NA #> 2330 + NA NA #> 2331 I NA NA #> 2332 NA NA #> 2333 NA NA #> 2334 NA NA #> 2335 I NA NA #> 2336 NA NA #> 2337 NA NA #> 2338 + NA NA #> 2339 NA NA #> 2340 I NA NA #> 2341 NA NA #> 2342 NA NA #> 2343 NA NA #> 2344 NA NA #> 2345 NA NA #> 2346 U NA NA #> 2347 NA NA #> 2348 NA NA #> 2349 + NA NA #> 2350 NA NA #> 2351 I NA NA #> 2352 NA NA #> 2353 NA NA #> 2354 NA NA #> 2355 NA NA #> 2356 NA NA #> 2357 U NA NA #> 2358 NA NA #> 2359 NA NA #> 2360 + NA NA #> 2361 NA NA #> 2362 I NA NA #> 2363 NA NA #> 2364 NA NA #> 2365 NA NA #> 2366 NA NA #> 2367 NA NA #> 2368 I NA NA #> 2369 NA NA #> 2370 NA NA #> 2371 + NA NA #> 2372 NA NA #> 2373 U NA NA #> 2374 NA NA #> 2375 NA NA #> 2376 NA NA #> 2377 NA NA #> 2378 NA NA #> 2379 I NA NA #> 2380 NA NA #> 2381 NA NA #> 2382 + NA NA #> 2383 NA NA #> 2384 I NA NA #> 2385 NA NA #> 2386 NA NA #> 2387 NA NA #> 2388 NA NA #> 2389 NA NA #> 2390 NA NA #> 2391 NA NA #> 2392 NA NA #> 2393 NA NA #> 2394 NA NA #> 2395 NA NA #> 2396 NA NA #> 2397 NA NA #> 2398 NA NA #> 2399 NA NA #> 2400 NA NA #> 2401 NA NA #> 2402 U NA NA #> 2403 NA NA #> 2404 NA NA #> 2405 + NA NA #> 2406 NA NA #> 2407 I NA NA #> 2408 A NA NA #> 2409 A NA NA #> 2410 NA NA #> 2411 NA NA #> 2412 NA NA #> 2413 U NA NA #> 2414 NA NA #> 2415 NA NA #> 2416 + NA NA #> 2417 NA NA #> 2418 I NA NA #> 2419 NA NA #> 2420 NA NA #> 2421 NA NA #> 2422 NA NA #> 2423 NA NA #> 2424 U NA NA #> 2425 NA NA #> 2426 NA NA #> 2427 + NA NA #> 2428 NA NA #> 2429 A NA NA #> 2430 NA NA #> 2431 NA NA #> 2432 NA NA #> 2433 NA NA #> 2434 NA NA #> 2435 I NA NA #> 2436 NA NA #> 2437 NA NA #> 2438 + NA NA #> 2439 NA NA #> 2440 I NA NA #> 2441 NA NA #> 2442 A NA NA #> 2443 NA NA #> 2444 NA NA #> 2445 NA NA #> 2446 U NA NA #> 2447 NA NA #> 2448 NA NA #> 2449 + NA NA #> 2450 NA NA #> 2451 I NA NA #> 2452 NA NA #> 2453 NA NA #> 2454 NA NA #> 2455 NA NA #> 2456 NA NA #> 2457 U NA NA #> 2458 NA NA #> 2459 NA NA #> 2460 + NA NA #> 2461 NA NA #> 2462 I NA NA #> 2463 NA NA #> 2464 NA NA #> 2465 NA NA #> 2466 NA NA #> 2467 NA NA #> 2468 NA NA #> 2469 NA NA #> 2470 NA NA #> 2471 + NA NA #> 2472 NA NA #> 2473 I NA NA #> 2474 NA NA #> 2475 NA NA #> 2476 NA NA #> 2477 NA NA #> 2478 I NA NA #> 2479 NA NA #> 2480 NA NA #> 2481 + NA NA #> 2482 NA NA #> 2483 I NA NA #> 2484 NA NA #> 2485 NA NA #> 2486 NA NA #> 2487 NA NA #> 2488 I NA NA #> 2489 NA NA #> 2490 NA NA #> 2491 + NA NA #> 2492 NA NA #> 2493 NA NA #> 2494 NA NA #> 2495 NA NA #> 2496 NA NA #> 2497 NA NA #> 2498 NA NA #> 2499 U NA NA #> 2500 NA NA #> 2501 NA NA #> 2502 + NA NA #> 2503 NA NA #> 2504 I NA NA #> 2505 NA NA #> 2506 NA NA #> 2507 NA NA #> 2508 NA NA #> 2509 NA NA #> 2510 U NA NA #> 2511 NA NA #> 2512 NA NA #> 2513 + NA NA #> 2514 NA NA #> 2515 I NA NA #> 2516 NA NA #> 2517 NA NA #> 2518 NA NA #> 2519 NA NA #> 2520 NA NA #> 2521 U NA NA #> 2522 NA NA #> 2523 NA NA #> 2524 + NA NA #> 2525 NA NA #> 2526 I NA NA #> 2527 A NA NA #> 2528 NA NA #> 2529 NA NA #> 2530 NA NA #> 2531 NA NA #> 2532 U NA NA #> 2533 NA NA #> 2534 NA NA #> 2535 + NA NA #> 2536 NA NA #> 2537 NA NA #> 2538 A NA NA #> 2539 NA NA #> 2540 NA NA #> 2541 NA NA #> 2542 NA NA #> 2543 U NA NA #> 2544 NA NA #> 2545 NA NA #> 2546 + NA NA #> 2547 NA NA #> 2548 I NA NA #> 2549 NA NA #> 2550 NA NA #> 2551 NA NA #> 2552 NA NA #> 2553 NA NA #> 2554 U NA NA #> 2555 NA NA #> 2556 NA NA #> 2557 + NA NA #> 2558 NA NA #> 2559 I NA NA #> 2560 A NA NA #> 2561 NA NA #> 2562 NA NA #> 2563 NA NA #> 2564 NA NA #> 2565 U NA NA #> 2566 NA NA #> 2567 U NA NA #> 2568 + NA NA #> 2569 NA NA #> 2570 I NA NA #> 2571 NA NA #> 2572 NA NA #> 2573 NA NA #> 2574 NA NA #> 2575 NA NA #> 2576 U NA NA #> 2577 NA NA #> 2578 NA NA #> 2579 + NA NA #> 2580 NA NA #> 2581 I NA NA #> 2582 NA NA #> 2583 I NA NA #> 2584 NA NA #> 2585 NA NA #> 2586 NA NA #> 2587 U NA NA #> 2588 NA NA #> 2589 NA NA #> 2590 + NA NA #> 2591 NA NA #> 2592 U NA NA #> 2593 NA NA #> 2594 NA NA #> 2595 NA NA #> 2596 NA NA #> 2597 NA NA #> 2598 U NA NA #> 2599 NA NA #> 2600 NA NA #> 2601 + NA NA #> 2602 NA NA #> 2603 I NA NA #> 2604 NA NA #> 2605 A NA NA #> 2606 NA NA #> 2607 NA NA #> 2608 NA NA #> 2609 U NA NA #> 2610 NA NA #> 2611 NA NA #> 2612 + NA NA #> 2613 NA NA #> 2614 I NA NA #> 2615 NA NA #> 2616 NA NA #> 2617 NA NA #> 2618 NA NA #> 2619 NA NA #> 2620 U NA NA #> 2621 NA NA #> 2622 NA NA #> 2623 + NA NA #> 2624 NA NA #> 2625 I NA NA #> 2626 NA NA #> 2627 NA NA #> 2628 NA NA #> 2629 NA NA #> 2630 NA NA #> 2631 U NA NA #> 2632 NA NA #> 2633 NA NA #> 2634 + NA NA #> 2635 NA NA #> 2636 I NA NA #> 2637 NA NA #> 2638 NA NA #> 2639 NA NA #> 2640 NA NA #> 2641 NA NA #> 2642 U NA NA #> 2643 NA NA #> 2644 NA NA #> 2645 + NA NA #> 2646 NA NA #> 2647 I NA NA #> 2648 NA NA #> 2649 I NA NA #> 2650 NA NA #> 2651 NA NA #> 2652 NA NA #> 2653 U NA NA #> 2654 NA NA #> 2655 NA NA #> 2656 + NA NA #> 2657 NA NA #> 2658 I NA NA #> 2659 I NA NA #> 2660 A NA NA #> 2661 NA NA #> 2662 NA NA #> 2663 NA NA #> 2664 U NA NA #> 2665 NA NA #> 2666 NA NA #> 2667 + NA NA #> 2668 NA NA #> 2669 I NA NA #> 2670 NA NA #> 2671 NA NA #> 2672 NA NA #> 2673 NA NA #> 2674 NA NA #> 2675 U NA NA #> 2676 NA NA #> 2677 NA NA #> 2678 + NA NA #> 2679 NA NA #> 2680 NA NA #> 2681 NA NA #> 2682 NA NA #> 2683 NA NA #> 2684 NA NA #> 2685 U NA NA #> 2686 NA NA #> 2687 NA NA #> 2688 + NA NA #> 2689 NA NA #> 2690 I NA NA #> 2691 I NA NA #> 2692 I NA NA #> 2693 NA NA #> 2694 + NA NA #> 2695 NA NA #> 2696 NA NA #> 2697 NA NA #> 2698 NA NA #> 2699 + NA NA #> 2700 NA NA #> 2701 NA NA #> 2702 NA NA #> 2703 + NA NA #> 2704 NA NA #> 2705 NA NA #> 2706 NA NA #> 2707 + NA NA #> 2708 NA NA #> 2709 NA NA #> 2710 NA NA #> 2711 + NA NA #> 2712 NA NA #> 2713 NA NA #> 2714 NA NA #> 2715 + NA NA #> 2716 NA NA #> 2717 NA NA #> 2718 NA NA #> 2719 + NA NA #> 2720 NA NA #> 2721 NA NA #> 2722 NA NA #> 2723 + NA NA #> 2724 NA NA #> 2725 NA NA #> 2726 NA NA #> 2727 + NA NA #> 2728 NA NA #> 2729 + NA NA #> 2730 NA NA #> 2731 NA NA #> 2732 NA NA #> 2733 + NA NA #> 2734 NA NA #> 2735 NA NA #> 2736 NA NA #> 2737 + NA NA #> 2738 NA NA #> 2739 NA NA #> 2740 NA NA #> 2741 + NA NA #> 2742 NA NA #> 2743 NA NA #> 2744 NA NA #> 2745 + NA NA #> 2746 NA NA #> 2747 NA NA #> 2748 NA NA #> 2749 + NA NA #> 2750 NA NA #> 2751 NA NA #> 2752 NA NA #> 2753 + NA NA #> 2754 NA NA #> 2755 NA NA #> 2756 NA NA #> 2757 + NA NA #> 2758 NA NA #> 2759 + NA NA #> 2760 NA NA #> 2761 NA NA #> 2762 NA NA #> 2763 + NA NA #> 2764 NA NA #> 2765 NA NA #> 2766 NA NA #> 2767 + NA NA #> 2768 NA NA #> 2769 NA NA #> 2770 NA NA #> 2771 + NA NA #> 2772 NA NA #> 2773 NA NA #> 2774 NA NA #> 2775 + NA NA #> 2776 NA NA #> 2777 NA NA #> 2778 NA NA #> 2779 + NA NA #> 2780 NA NA #> 2781 NA NA #> 2782 NA NA #> 2783 NA NA #> 2784 NA NA #> 2785 NA NA #> 2786 NA NA #> 2787 NA NA #> 2788 NA NA #> 2789 NA NA #> 2790 NA NA #> 2791 NA NA #> 2792 NA NA #> 2793 NA NA #> 2794 NA NA #> 2795 NA NA #> 2796 NA NA #> 2797 NA NA #> 2798 NA NA #> 2799 NA NA #> 2800 NA NA #> 2801 NA NA #> 2802 NA NA #> 2803 NA NA #> 2804 NA NA #> 2805 NA NA #> 2806 NA NA #> 2807 NA NA #> 2808 I NA NA #> 2809 NA NA #> 2810 NA NA #> 2811 NA NA #> 2812 NA NA #> 2813 NA NA #> 2814 NA NA #> 2815 NA NA #> 2816 + NA NA #> 2817 NA NA #> 2818 I NA NA #> 2819 NA NA #> 2820 I NA NA #> 2821 A NA NA #> 2822 NA NA #> 2823 NA NA #> 2824 NA NA #> 2825 NA NA #> 2826 NA NA #> 2827 NA NA #> 2828 + NA NA #> 2829 NA NA #> 2830 I NA NA #> 2831 A NA NA #> 2832 NA NA #> 2833 A NA NA #> 2834 NA NA #> 2835 NA NA #> 2836 NA NA #> 2837 NA NA #> 2838 NA NA #> 2839 NA NA #> 2840 + NA NA #> 2841 NA NA #> 2842 I NA NA #> 2843 A NA NA #> 2844 I NA NA #> 2845 A NA NA #> 2846 NA NA #> 2847 NA NA #> 2848 NA NA #> 2849 NA NA #> 2850 NA NA #> 2851 NA NA #> 2852 + NA NA #> 2853 NA NA #> 2854 NA NA #> 2855 NA NA #> 2856 NA NA #> 2857 NA NA #> 2858 NA NA #> 2859 NA NA #> 2860 NA NA #> 2861 NA NA #> 2862 NA NA #> 2863 + NA NA #> 2864 NA NA #> 2865 I NA NA #> 2866 NA NA #> 2867 NA NA #> 2868 NA NA #> 2869 NA NA #> 2870 NA NA #> 2871 NA NA #> 2872 NA NA #> 2873 NA NA #> 2874 + NA NA #> 2875 NA NA #> 2876 I NA NA #> 2877 NA NA #> 2878 NA NA #> 2879 NA NA #> 2880 NA NA #> 2881 NA NA #> 2882 NA NA #> 2883 NA NA #> 2884 NA NA #> 2885 + NA NA #> 2886 NA NA #> 2887 I NA NA #> 2888 NA NA #> 2889 NA NA #> 2890 NA NA #> 2891 NA NA #> 2892 NA NA #> 2893 NA NA #> 2894 NA NA #> 2895 NA NA #> 2896 NA NA #> 2897 NA NA #> 2898 NA NA #> 2899 NA NA #> 2900 NA NA #> 2901 NA NA #> 2902 NA NA #> 2903 NA NA #> 2904 NA NA #> 2905 NA NA #> 2906 NA NA #> 2907 NA NA #> 2908 NA NA #> 2909 NA NA #> 2910 NA NA #> 2911 NA NA #> 2912 NA NA #> 2913 NA NA #> 2914 NA NA #> 2915 NA NA #> 2916 NA NA #> 2917 NA NA #> 2918 NA NA #> 2919 NA NA #> 2920 NA NA #> 2921 NA NA #> 2922 NA NA #> 2923 NA NA #> 2924 NA NA #> 2925 NA NA #> 2926 NA NA #> 2927 NA NA #> 2928 NA NA #> 2929 NA NA #> 2930 NA NA #> 2931 NA NA #> 2932 NA NA #> 2933 NA NA #> 2934 NA NA #> 2935 NA NA #> 2936 NA NA #> 2937 NA NA #> 2938 NA NA #> 2939 NA NA #> 2940 NA NA #> 2941 NA NA #> 2942 NA NA #> 2943 NA NA #> 2944 NA NA #> 2945 NA NA #> 2946 NA NA #> 2947 + NA NA #> 2948 NA NA #> 2949 NA NA #> 2950 NA NA #> 2951 + NA NA #> 2952 NA NA #> 2953 NA NA #> 2954 NA NA #> 2955 + NA NA #> 2956 NA NA #> 2957 NA NA #> 2958 NA NA #> 2959 + NA NA #> 2960 NA NA #> 2961 NA NA #> 2962 NA NA #> 2963 + NA NA #> 2964 NA NA #> 2965 NA NA #> 2966 NA NA #> 2967 + NA NA #> 2968 NA NA #> 2969 NA NA #> 2970 NA NA #> 2971 + NA NA #> 2972 NA NA #> 2973 NA NA #> 2974 NA NA #> 2975 + NA NA #> 2976 NA NA #> 2977 NA NA #> 2978 NA NA #> 2979 NA NA #> 2980 NA NA #> 2981 U NA NA #> 2982 + NA NA #> 2983 NA NA #> 2984 + NA NA #> 2985 NA NA #> 2986 U NA NA #> 2987 NA NA #> 2988 NA NA #> 2989 NA NA #> 2990 NA NA #> 2991 NA NA #> 2992 I NA NA #> 2993 + NA NA #> 2994 NA NA #> 2995 + NA NA #> 2996 NA NA #> 2997 NA NA #> 2998 A NA NA #> 2999 NA NA #> 3000 NA NA #> 3001 NA NA #> 3002 NA NA #> 3003 NA NA #> 3004 + NA NA #> 3005 NA NA #> 3006 + NA NA #> 3007 NA NA #> 3008 I NA NA #> 3009 NA NA #> 3010 + NA NA #> 3011 NA NA #> 3012 NA NA #> 3013 NA NA #> 3014 NA NA #> 3015 NA NA #> 3016 NA NA #> 3017 + NA NA #> 3018 NA NA #> 3019 NA NA #> 3020 NA NA #> 3021 NA NA #> 3022 NA NA #> 3023 NA NA #> 3024 NA NA #> 3025 + NA NA #> 3026 NA NA #> 3027 I NA NA #> 3028 NA NA #> 3029 NA NA #> 3030 NA NA #> 3031 NA NA #> 3032 NA NA #> 3033 NA NA #> 3034 NA NA #> 3035 NA NA #> 3036 + NA NA #> 3037 NA NA #> 3038 I NA NA #> 3039 NA NA #> 3040 NA NA #> 3041 NA NA #> 3042 NA NA #> 3043 NA NA #> 3044 A NA NA #> 3045 NA NA #> 3046 I NA NA #> 3047 NA NA #> 3048 NA NA #> 3049 + NA NA #> 3050 NA NA #> 3051 I NA NA #> 3052 NA NA #> 3053 NA NA #> 3054 NA NA #> 3055 NA NA #> 3056 NA NA #> 3057 I NA NA #> 3058 NA NA #> 3059 NA NA #> 3060 + NA NA #> 3061 NA NA #> 3062 I NA NA #> 3063 NA NA #> 3064 NA NA #> 3065 NA NA #> 3066 NA NA #> 3067 NA NA #> 3068 U NA NA #> 3069 NA NA #> 3070 NA NA #> 3071 + NA NA #> 3072 NA NA #> 3073 I NA NA #> 3074 NA NA #> 3075 NA NA #> 3076 NA NA #> 3077 NA NA #> 3078 NA NA #> 3079 NA NA #> 3080 NA NA #> 3081 NA NA #> 3082 + NA NA #> 3083 NA NA #> 3084 I NA NA #> 3085 NA NA #> 3086 NA NA #> 3087 NA NA #> 3088 NA NA #> 3089 NA NA #> 3090 NA NA #> 3091 NA NA #> 3092 + NA NA #> 3093 NA NA #> 3094 I NA NA #> 3095 NA NA #> 3096 NA NA #> 3097 NA NA #> 3098 NA NA #> 3099 NA NA #> 3100 I NA NA #> 3101 NA NA #> 3102 NA NA #> 3103 + NA NA #> 3104 NA NA #> 3105 NA NA #> 3106 NA NA #> 3107 NA NA #> 3108 NA NA #> 3109 NA NA #> 3110 NA NA #> 3111 NA NA #> 3112 NA NA #> 3113 NA NA #> 3114 NA NA #> 3115 NA NA #> 3116 NA NA #> 3117 NA NA #> 3118 + NA NA #> 3119 NA NA #> 3120 I NA NA #> 3121 NA NA #> 3122 NA NA #> 3123 NA NA #> 3124 NA NA #> 3125 NA NA #> 3126 NA NA #> 3127 NA NA #> 3128 NA NA #> 3129 NA NA #> 3130 NA NA #> 3131 NA NA #> 3132 NA NA #> 3133 NA NA #> 3134 NA NA #> 3135 NA NA #> 3136 NA NA #> 3137 NA NA #> 3138 NA NA #> 3139 NA NA #> 3140 NA NA #> 3141 + NA NA #> 3142 NA NA #> 3143 I NA NA #> 3144 NA NA #> 3145 NA NA #> 3146 NA NA #> 3147 NA NA #> 3148 NA NA #> 3149 NA NA #> 3150 NA NA #> 3151 NA NA #> 3152 + NA NA #> 3153 NA NA #> 3154 I NA NA #> 3155 NA NA #> 3156 NA NA #> 3157 NA NA #> 3158 NA NA #> 3159 NA NA #> 3160 I NA NA #> 3161 NA NA #> 3162 NA NA #> 3163 + NA NA #> 3164 NA NA #> 3165 I NA NA #> 3166 A NA NA #> 3167 NA NA #> 3168 NA NA #> 3169 NA NA #> 3170 NA NA #> 3171 U NA NA #> 3172 NA NA #> 3173 NA NA #> 3174 + NA NA #> 3175 NA NA #> 3176 I NA NA #> 3177 NA NA #> 3178 NA NA #> 3179 NA NA #> 3180 NA NA #> 3181 NA NA #> 3182 I NA NA #> 3183 NA NA #> 3184 NA NA #> 3185 + NA NA #> 3186 NA NA #> 3187 NA NA #> 3188 A NA NA #> 3189 NA NA #> 3190 NA NA #> 3191 NA NA #> 3192 NA NA #> 3193 U NA NA #> 3194 NA NA #> 3195 NA NA #> 3196 + NA NA #> 3197 NA NA #> 3198 I NA NA #> 3199 NA NA #> 3200 NA NA #> 3201 NA NA #> 3202 NA NA #> 3203 NA NA #> 3204 U NA NA #> 3205 NA NA #> 3206 NA NA #> 3207 + NA NA #> 3208 NA NA #> 3209 I NA NA #> 3210 NA NA #> 3211 NA NA #> 3212 NA NA #> 3213 NA NA #> 3214 NA NA #> 3215 U NA NA #> 3216 NA NA #> 3217 NA NA #> 3218 + NA NA #> 3219 NA NA #> 3220 U NA NA #> 3221 NA NA #> 3222 NA NA #> 3223 NA NA #> 3224 NA NA #> 3225 NA NA #> 3226 NA NA #> 3227 NA NA #> 3228 NA NA #> 3229 + NA NA #> 3230 NA NA #> 3231 I NA NA #> 3232 NA NA #> 3233 NA NA #> 3234 NA NA #> 3235 NA NA #> 3236 NA NA #> 3237 NA NA #> 3238 NA NA #> 3239 NA NA #> 3240 + NA NA #> 3241 NA NA #> 3242 I NA NA #> 3243 NA NA #> 3244 NA NA #> 3245 NA NA #> 3246 NA NA #> 3247 NA NA #> 3248 NA NA #> 3249 NA NA #> 3250 NA NA #> 3251 + NA NA #> 3252 NA NA #> 3253 I NA NA #> 3254 NA NA #> 3255 NA NA #> 3256 NA NA #> 3257 NA NA #> 3258 NA NA #> 3259 NA NA #> 3260 NA NA #> 3261 NA NA #> 3262 + NA NA #> 3263 NA NA #> 3264 I NA NA #> 3265 NA NA #> 3266 NA NA #> 3267 NA NA #> 3268 NA NA #> 3269 I NA NA #> 3270 NA NA #> 3271 NA NA #> 3272 + NA NA #> 3273 NA NA #> 3274 I NA NA #> 3275 NA NA #> 3276 NA NA #> 3277 NA NA #> 3278 NA NA #> 3279 NA NA #> 3280 U NA NA #> 3281 NA NA #> 3282 NA NA #> 3283 + NA NA #> 3284 NA NA #> 3285 NA NA #> 3286 NA NA #> 3287 U NA NA #> 3288 NA NA #> 3289 NA NA #> 3290 NA NA #> 3291 U NA NA #> 3292 NA NA #> 3293 NA NA #> 3294 + NA NA #> 3295 NA NA #> 3296 NA NA #> 3297 NA NA #> 3298 NA NA #> 3299 NA NA #> 3300 NA NA #> 3301 NA NA #> 3302 I NA NA #> 3303 NA NA #> 3304 NA NA #> 3305 + NA NA #> 3306 NA NA #> 3307 NA NA #> 3308 NA NA #> 3309 NA NA #> 3310 NA NA #> 3311 NA NA #> 3312 NA NA #> 3313 I NA NA #> 3314 NA NA #> 3315 NA NA #> 3316 + NA NA #> 3317 NA NA #> 3318 I NA NA #> 3319 NA NA #> 3320 NA NA #> 3321 NA NA #> 3322 NA NA #> 3323 NA NA #> 3324 U NA NA #> 3325 NA NA #> 3326 NA NA #> 3327 + NA NA #> 3328 NA NA #> 3329 NA NA #> 3330 NA NA #> 3331 NA NA #> 3332 NA NA #> 3333 NA NA #> 3334 NA NA #> 3335 NA NA #> 3336 NA NA #> 3337 NA NA #> 3338 + NA NA #> 3339 NA NA #> 3340 I NA NA #> 3341 NA NA #> 3342 I NA NA #> 3343 NA NA #> 3344 NA NA #> 3345 NA NA #> 3346 U NA NA #> 3347 NA NA #> 3348 NA NA #> 3349 + NA NA #> 3350 NA NA #> 3351 I NA NA #> 3352 NA NA #> 3353 NA NA #> 3354 NA NA #> 3355 NA NA #> 3356 NA NA #> 3357 U NA NA #> 3358 NA NA #> 3359 NA NA #> 3360 + NA NA #> 3361 NA NA #> 3362 NA NA #> 3363 NA NA #> 3364 NA NA #> 3365 NA NA #> 3366 NA NA #> 3367 NA NA #> 3368 NA NA #> 3369 NA NA #> 3370 NA NA #> 3371 NA NA #> 3372 NA NA #> 3373 NA NA #> 3374 U NA NA #> 3375 + NA NA #> 3376 NA NA #> 3377 + NA NA #> 3378 NA NA #> 3379 I NA NA #> 3380 NA NA #> 3381 NA NA #> 3382 NA NA #> 3383 NA NA #> 3384 + NA NA #> 3385 NA NA #> 3386 NA NA #> 3387 NA NA #> 3388 NA NA #> 3389 I NA NA #> 3390 + NA NA #> 3391 NA NA #> 3392 + NA NA #> 3393 NA NA #> 3394 I NA NA #> 3395 NA NA #> 3396 NA NA #> 3397 NA NA #> 3398 NA NA #> 3399 NA NA #> 3400 NA NA #> 3401 + NA NA #> 3402 NA NA #> 3403 + NA NA #> 3404 NA NA #> 3405 I NA NA #> 3406 NA NA #> 3407 NA NA #> 3408 NA NA #> 3409 NA NA #> 3410 + NA NA #> 3411 NA NA #> 3412 NA NA #> 3413 NA NA #> 3414 NA NA #> 3415 NA NA #> 3416 NA NA #> 3417 NA NA #> 3418 + NA NA #> 3419 NA NA #> 3420 I NA NA #> 3421 NA NA #> 3422 NA NA #> 3423 NA NA #> 3424 NA NA #> 3425 NA NA #> 3426 A NA NA #> 3427 NA NA #> 3428 NA NA #> 3429 NA NA #> 3430 NA NA #> 3431 NA NA #> 3432 NA NA #> 3433 + NA NA #> 3434 NA NA #> 3435 I NA NA #> 3436 NA NA #> 3437 NA NA #> 3438 NA NA #> 3439 NA NA #> 3440 NA NA #> 3441 NA NA #> 3442 NA NA #> 3443 U NA NA #> 3444 NA NA #> 3445 NA NA #> 3446 + NA NA #> 3447 NA NA #> 3448 I NA NA #> 3449 NA NA #> 3450 NA NA #> 3451 NA NA #> 3452 NA NA #> 3453 + NA NA #> 3454 U NA NA #> 3455 NA NA #> 3456 NA NA #> 3457 + NA NA #> 3458 NA NA #> 3459 I NA NA #> 3460 NA NA #> 3461 NA NA #> 3462 NA NA #> 3463 NA NA #> 3464 NA NA #> 3465 NA NA #> 3466 NA NA #> 3467 NA NA #> 3468 NA NA #> 3469 U NA NA #> 3470 NA NA #> 3471 NA NA #> 3472 + NA NA #> 3473 NA NA #> 3474 I NA NA #> 3475 NA NA #> 3476 NA NA #> 3477 NA NA #> 3478 NA NA #> 3479 NA NA #> 3480 U NA NA #> 3481 NA NA #> 3482 NA NA #> 3483 + NA NA #> 3484 NA NA #> 3485 I NA NA #> 3486 NA NA #> 3487 NA NA #> 3488 NA NA #> 3489 NA NA #> 3490 NA NA #> 3491 NA NA #> 3492 NA NA #> 3493 NA NA #> 3494 + NA NA #> 3495 NA NA #> 3496 I NA NA #> 3497 NA NA #> 3498 NA NA #> 3499 NA NA #> 3500 NA NA #> 3501 NA NA #> 3502 U NA NA #> 3503 NA NA #> 3504 NA NA #> 3505 + NA NA #> 3506 NA NA #> 3507 NA NA #> 3508 NA NA #> 3509 NA NA #> 3510 NA NA #> 3511 NA NA #> 3512 NA NA #> 3513 NA NA #> 3514 NA NA #> 3515 NA NA #> 3516 NA NA #> 3517 NA NA #> 3518 NA NA #> 3519 NA NA #> 3520 + NA NA #> 3521 NA NA #> 3522 I NA NA #> 3523 NA NA #> 3524 NA NA #> 3525 NA NA #> 3526 NA NA #> 3527 NA NA #> 3528 NA NA #> 3529 NA NA #> 3530 NA NA #> 3531 NA NA #> 3532 NA NA #> 3533 NA NA #> 3534 NA NA #> 3535 NA NA #> 3536 NA NA #> 3537 NA NA #> 3538 NA NA #> 3539 + NA NA #> 3540 NA NA #> 3541 I NA NA #> 3542 A NA NA #> 3543 NA NA #> 3544 NA NA #> 3545 NA NA #> 3546 NA NA #> 3547 NA NA #> 3548 NA NA #> 3549 NA NA #> 3550 + NA NA #> 3551 NA NA #> 3552 I NA NA #> 3553 NA NA #> 3554 NA NA #> 3555 NA NA #> 3556 NA NA #> 3557 NA NA #> 3558 U NA NA #> 3559 NA NA #> 3560 NA NA #> 3561 + NA NA #> 3562 NA NA #> 3563 I NA NA #> 3564 NA NA #> 3565 NA NA #> 3566 NA NA #> 3567 NA NA #> 3568 NA NA #> 3569 U NA NA #> 3570 NA NA #> 3571 NA NA #> 3572 + NA NA #> 3573 NA NA #> 3574 I NA NA #> 3575 NA NA #> 3576 NA NA #> 3577 NA NA #> 3578 NA NA #> 3579 NA NA #> 3580 U NA NA #> 3581 NA NA #> 3582 NA NA #> 3583 + NA NA #> 3584 NA NA #> 3585 I NA NA #> 3586 NA NA #> 3587 NA NA #> 3588 NA NA #> 3589 NA NA #> 3590 NA NA #> 3591 I NA NA #> 3592 NA NA #> 3593 NA NA #> 3594 + NA NA #> 3595 NA NA #> 3596 I NA NA #> 3597 NA NA #> 3598 NA NA #> 3599 NA NA #> 3600 NA NA #> 3601 NA NA #> 3602 U NA NA #> 3603 NA NA #> 3604 NA NA #> 3605 + NA NA #> 3606 NA NA #> 3607 I NA NA #> 3608 NA NA #> 3609 NA NA #> 3610 NA NA #> 3611 NA NA #> 3612 NA NA #> 3613 NA NA #> 3614 NA NA #> 3615 NA NA #> 3616 + NA NA #> 3617 NA NA #> 3618 NA NA #> 3619 NA NA #> 3620 NA NA #> 3621 NA NA #> 3622 NA NA #> 3623 NA NA #> 3624 I NA NA #> 3625 NA NA #> 3626 NA NA #> 3627 + NA NA #> 3628 NA NA #> 3629 I NA NA #> 3630 NA NA #> 3631 NA NA #> 3632 NA NA #> 3633 NA NA #> 3634 NA NA #> 3635 U NA NA #> 3636 NA NA #> 3637 NA NA #> 3638 + NA NA #> 3639 NA NA #> 3640 NA NA #> 3641 NA NA #> 3642 A NA NA #> 3643 NA NA #> 3644 NA NA #> 3645 NA NA #> 3646 I NA NA #> 3647 NA NA #> 3648 NA NA #> 3649 + NA NA #> 3650 NA NA #> 3651 I NA NA #> 3652 NA NA #> 3653 NA NA #> 3654 NA NA #> 3655 NA NA #> 3656 NA NA #> 3657 U NA NA #> 3658 NA NA #> 3659 NA NA #> 3660 + NA NA #> 3661 NA NA #> 3662 NA NA #> 3663 NA NA #> 3664 NA NA #> 3665 NA NA #> 3666 NA NA #> 3667 NA NA #> 3668 U NA NA #> 3669 NA NA #> 3670 NA NA #> 3671 + NA NA #> 3672 NA NA #> 3673 I NA NA #> 3674 NA NA #> 3675 NA NA #> 3676 NA NA #> 3677 NA NA #> 3678 NA NA #> 3679 U NA NA #> 3680 NA NA #> 3681 NA NA #> 3682 + NA NA #> 3683 NA NA #> 3684 NA NA #> 3685 NA NA #> 3686 NA NA #> 3687 NA NA #> 3688 NA NA #> 3689 NA NA #> 3690 U NA NA #> 3691 NA NA #> 3692 NA NA #> 3693 + NA NA #> 3694 NA NA #> 3695 I NA NA #> 3696 NA NA #> 3697 NA NA #> 3698 NA NA #> 3699 NA NA #> 3700 NA NA #> 3701 I NA NA #> 3702 NA NA #> 3703 NA NA #> 3704 + NA NA #> 3705 NA NA #> 3706 NA NA #> 3707 NA NA #> 3708 NA NA #> 3709 NA NA #> 3710 NA NA #> 3711 NA NA #> 3712 NA NA #> 3713 NA NA #> 3714 NA NA #> 3715 + NA NA #> 3716 NA NA #> 3717 I NA NA #> 3718 NA NA #> 3719 NA NA #> 3720 NA NA #> 3721 NA NA #> 3722 NA NA #> 3723 I NA NA #> 3724 NA NA #> 3725 NA NA #> 3726 + NA NA #> 3727 NA NA #> 3728 NA NA #> 3729 NA NA #> 3730 NA NA #> 3731 NA NA #> 3732 NA NA #> 3733 NA NA #> 3734 NA NA #> 3735 NA NA #> 3736 NA NA #> 3737 + NA NA #> 3738 NA NA #> 3739 NA NA #> 3740 NA NA #> 3741 NA NA #> 3742 NA NA #> 3743 NA NA #> 3744 NA NA #> 3745 NA NA #> 3746 NA NA #> 3747 NA NA #> 3748 + NA NA #> 3749 NA NA #> 3750 I NA NA #> 3751 NA NA #> 3752 NA NA #> 3753 NA NA #> 3754 NA NA #> 3755 NA NA #> 3756 U NA NA #> 3757 NA NA #> 3758 NA NA #> 3759 + NA NA #> 3760 NA NA #> 3761 I NA NA #> 3762 NA NA #> 3763 NA NA #> 3764 + NA NA #> 3765 I NA NA #> 3766 NA NA #> 3767 NA NA #> 3768 + NA NA #> 3769 NA NA #> 3770 NA NA #> 3771 NA NA #> 3772 NA NA #> 3773 + NA NA #> 3774 NA NA #> 3775 NA NA #> 3776 NA NA #> 3777 + NA NA #> 3778 NA NA #> 3779 NA NA #> 3780 NA NA #> 3781 NA NA #> 3782 + NA NA #> 3783 I NA NA #> 3784 NA NA #> 3785 NA NA #> 3786 + NA NA #> 3787 NA NA #> 3788 NA NA #> 3789 NA NA #> 3790 NA NA #> 3791 NA NA #> 3792 + NA NA #> 3793 I NA NA #> 3794 NA NA #> 3795 NA NA #> 3796 + NA NA #> 3797 NA NA #> 3798 NA NA #> 3799 NA NA #> 3800 A NA NA #> 3801 NA NA #> 3802 + NA NA #> 3803 NA NA #> 3804 NA NA #> 3805 NA NA #> 3806 + NA NA #> 3807 NA NA #> 3808 A NA NA #> 3809 NA NA #> 3810 A NA NA #> 3811 NA NA #> 3812 NA NA #> 3813 NA NA #> 3814 + NA NA #> 3815 NA NA #> 3816 NA NA #> 3817 NA NA #> 3818 NA NA #> 3819 NA NA #> 3820 + NA NA #> 3821 I NA NA #> 3822 NA NA #> 3823 + NA NA #> 3824 NA NA #> 3825 NA NA #> 3826 NA NA #> 3827 NA NA #> 3828 NA NA #> 3829 + NA NA #> 3830 NA NA #> 3831 NA NA #> 3832 NA NA #> 3833 + NA NA #> 3834 NA NA #> 3835 NA NA #> 3836 NA NA #> 3837 NA NA #> 3838 NA NA #> 3839 + NA NA #> 3840 NA NA #> 3841 NA NA #> 3842 NA NA #> 3843 + NA NA #> 3844 NA NA #> 3845 A NA NA #> 3846 NA NA #> 3847 NA NA #> 3848 NA NA #> 3849 NA NA #> 3850 NA NA #> 3851 + NA NA #> 3852 NA NA #> 3853 A NA NA #> 3854 NA NA #> 3855 A NA NA #> 3856 NA NA #> 3857 NA NA #> 3858 + NA NA #> 3859 NA NA #> 3860 NA NA #> 3861 NA NA #> 3862 NA NA #> 3863 + NA NA #> 3864 NA NA #> 3865 NA NA #> 3866 NA NA #> 3867 + NA NA #> 3868 NA NA #> 3869 NA NA #> 3870 NA NA #> 3871 NA NA #> 3872 + NA NA #> 3873 I NA NA #> 3874 NA NA #> 3875 + NA NA #> 3876 NA NA #> 3877 NA NA #> 3878 NA NA #> 3879 NA NA #> 3880 + NA NA #> 3881 NA NA #> 3882 + NA NA #> 3883 NA NA #> 3884 A NA NA #> 3885 NA NA #> 3886 NA NA #> 3887 + NA NA #> 3888 NA NA #> 3889 NA NA #> 3890 NA NA #> 3891 + NA NA #> 3892 NA NA #> 3893 NA NA #> 3894 NA NA #> 3895 NA NA #> 3896 NA NA #> 3897 + NA NA #> 3898 I NA NA #> 3899 NA NA #> 3900 NA NA #> 3901 + NA NA #> 3902 NA NA #> 3903 NA NA #> 3904 NA NA #> 3905 NA NA #> 3906 NA NA #> 3907 NA NA #> 3908 NA NA #> 3909 + NA NA #> 3910 NA NA #> 3911 NA NA #> 3912 NA NA #> 3913 NA NA #> 3914 NA NA #> 3915 + NA NA #> 3916 NA NA #> 3917 NA NA #> 3918 NA NA #> 3919 + NA NA #> 3920 NA NA #> 3921 NA NA #> 3922 NA NA #> 3923 NA NA #> 3924 + NA NA #> 3925 NA NA #> 3926 NA NA #> 3927 NA NA #> 3928 + NA NA #> 3929 NA NA #> 3930 NA NA #> 3931 NA NA #> 3932 NA NA #> 3933 NA NA #> 3934 NA NA #> 3935 NA NA #> 3936 + NA NA #> 3937 NA NA #> 3938 NA NA #> 3939 NA NA #> 3940 A NA NA #> 3941 + NA NA #> 3942 NA NA #> 3943 NA NA #> 3944 NA NA #> 3945 + NA NA #> 3946 NA NA #> 3947 NA NA #> 3948 NA NA #> 3949 NA NA #> 3950 NA NA #> 3951 + NA NA #> 3952 I NA NA #> 3953 NA NA #> 3954 NA NA #> 3955 + NA NA #> 3956 NA NA #> 3957 A NA NA #> 3958 I NA NA #> 3959 NA NA #> 3960 + NA NA #> 3961 U NA NA #> 3962 NA NA #> 3963 + NA NA #> 3964 NA NA #> 3965 NA NA #> 3966 NA NA #> 3967 NA NA #> 3968 + NA NA #> 3969 I NA NA #> 3970 NA NA #> 3971 NA NA #> 3972 + NA NA #> 3973 NA NA #> 3974 NA NA #> 3975 NA NA #> 3976 A NA NA #> 3977 NA NA #> 3978 + NA NA #> 3979 I NA NA #> 3980 NA NA #> 3981 NA NA #> 3982 + NA NA #> 3983 NA NA #> 3984 NA NA #> 3985 NA NA #> 3986 NA NA #> 3987 + NA NA #> 3988 I NA NA #> 3989 NA NA #> 3990 NA NA #> 3991 + NA NA #> 3992 NA NA #> 3993 NA NA #> 3994 NA NA #> 3995 NA NA #> 3996 I NA NA #> 3997 NA NA #> 3998 + NA NA #> 3999 NA NA #> 4000 NA NA #> 4001 NA NA #> 4002 NA NA #> 4003 + NA NA #> 4004 I NA NA #> 4005 NA NA #> 4006 NA NA #> 4007 + NA NA #> 4008 NA NA #> 4009 NA NA #> 4010 NA NA #> 4011 NA NA #> 4012 + NA NA #> 4013 NA NA #> 4014 NA NA #> 4015 NA NA #> 4016 + NA NA #> 4017 NA NA #> 4018 NA NA #> 4019 I NA NA #> 4020 NA NA #> 4021 NA NA #> 4022 + NA NA #> 4023 NA NA #> 4024 NA NA #> 4025 NA NA #> 4026 + NA NA #> 4027 NA NA #> 4028 NA NA #> 4029 NA NA #> 4030 A NA NA #> 4031 + NA NA #> 4032 NA NA #> 4033 NA NA #> 4034 NA NA #> 4035 + NA NA #> 4036 NA NA #> 4037 NA NA #> 4038 NA NA #> 4039 NA NA #> 4040 + NA NA #> 4041 I NA NA #> 4042 NA NA #> 4043 NA NA #> 4044 + NA NA #> 4045 NA NA #> 4046 NA NA #> 4047 NA NA #> 4048 NA NA #> 4049 NA NA #> 4050 + NA NA #> 4051 U NA NA #> 4052 NA NA #> 4053 NA NA #> 4054 + NA NA #> 4055 NA NA #> 4056 NA NA #> 4057 NA NA #> 4058 NA NA #> 4059 NA NA #> 4060 + NA NA #> 4061 I NA NA #> 4062 NA NA #> 4063 + NA NA #> 4064 NA NA #> 4065 A NA NA #> 4066 A NA NA #> 4067 NA NA #> 4068 + NA NA #> 4069 U NA NA #> 4070 NA NA #> 4071 NA NA #> 4072 + NA NA #> 4073 NA NA #> 4074 NA NA #> 4075 NA NA #> 4076 NA NA #> 4077 NA NA #> 4078 + NA NA #> 4079 I NA NA #> 4080 NA NA #> 4081 + NA NA #> 4082 NA NA #> 4083 NA NA #> 4084 NA NA #> 4085 NA NA #> 4086 + NA NA #> 4087 NA NA #> 4088 + NA NA #> 4089 NA NA #> 4090 NA NA #> 4091 NA NA #> 4092 + NA NA #> 4093 NA NA #> 4094 NA NA #> 4095 NA NA #> 4096 + NA NA #> 4097 NA NA #> 4098 NA NA #> 4099 NA NA #> 4100 NA NA #> 4101 NA NA #> 4102 + NA NA #> 4103 NA NA #> 4104 NA NA #> 4105 NA NA #> 4106 + NA NA #> 4107 NA NA #> 4108 NA NA #> 4109 NA NA #> 4110 NA NA #> 4111 NA NA #> 4112 NA NA #> 4113 NA NA #> 4114 NA NA #> 4115 + NA NA #> 4116 NA NA #> 4117 NA NA #> 4118 NA NA #> 4119 NA NA #> 4120 NA NA #> 4121 + NA NA #> 4122 U NA NA #> 4123 NA NA #> 4124 NA NA #> 4125 + NA NA #> 4126 NA NA #> 4127 NA NA #> 4128 NA NA #> 4129 NA NA #> 4130 + NA NA #> 4131 U NA NA #> 4132 NA NA #> 4133 + NA NA #> 4134 NA NA #> 4135 NA NA #> 4136 NA NA #> 4137 U NA NA #> 4138 NA NA #> 4139 + NA NA #> 4140 NA NA #> 4141 NA NA #> 4142 NA NA #> 4143 NA NA #> 4144 + NA NA #> 4145 I NA NA #> 4146 NA NA #> 4147 NA NA #> 4148 + NA NA #> 4149 NA NA #> 4150 NA NA #> 4151 NA NA #> 4152 A NA NA #> 4153 NA NA #> 4154 NA NA #> 4155 I NA NA #> 4156 NA NA #> 4157 NA NA #> 4158 + NA NA #> 4159 NA NA #> 4160 NA NA #> 4161 NA NA #> 4162 NA NA #> 4163 NA NA #> 4164 NA NA #> 4165 I NA NA #> 4166 NA NA #> 4167 NA NA #> 4168 + NA NA #> 4169 NA NA #> 4170 NA NA #> 4171 NA NA #> 4172 NA NA #> 4173 NA NA #> 4174 NA NA #> 4175 I NA NA #> 4176 NA NA #> 4177 NA NA #> 4178 + NA NA #> 4179 NA NA #> 4180 NA NA #> 4181 NA NA #> 4182 NA NA #> 4183 NA NA #> 4184 NA NA #> 4185 I NA NA #> 4186 NA NA #> 4187 NA NA #> 4188 + NA NA #> 4189 NA NA #> 4190 NA NA #> 4191 NA NA #> 4192 NA NA #> 4193 NA NA #> 4194 NA NA #> 4195 U NA NA #> 4196 NA NA #> 4197 NA NA #> 4198 + NA NA #> 4199 NA NA #> 4200 A NA NA #> 4201 NA NA #> 4202 NA NA #> 4203 NA NA #> 4204 NA NA #> 4205 U NA NA #> 4206 NA NA #> 4207 NA NA #> 4208 + NA NA #> 4209 NA NA #> 4210 NA NA #> 4211 NA NA #> 4212 NA NA #> 4213 NA NA #> 4214 NA NA #> 4215 I NA NA #> 4216 NA NA #> 4217 NA NA #> 4218 + NA NA #> 4219 NA NA #> 4220 NA NA #> 4221 I NA NA #> 4222 NA NA #> 4223 NA NA #> 4224 NA NA #> 4225 I NA NA #> 4226 NA NA #> 4227 NA NA #> 4228 + NA NA #> 4229 NA NA #> 4230 NA NA #> 4231 NA NA #> 4232 NA NA #> 4233 NA NA #> 4234 NA NA #> 4235 I NA NA #> 4236 NA NA #> 4237 NA NA #> 4238 + NA NA #> 4239 NA NA #> 4240 A NA NA #> 4241 NA NA #> 4242 NA NA #> 4243 NA NA #> 4244 NA NA #> 4245 A NA NA #> 4246 NA NA #> 4247 NA NA #> 4248 U NA NA #> 4249 NA NA #> 4250 NA NA #> 4251 + NA NA #> 4252 NA NA #> 4253 NA NA #> 4254 NA NA #> 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NA #> 6187 NA NA #> 6188 NA NA #> 6189 NA NA #> 6190 NA NA #> 6191 NA NA #> 6192 NA NA #> 6193 NA NA #> 6194 NA NA #> 6195 + NA NA #> 6196 NA NA #> 6197 I NA NA #> 6198 NA NA #> 6199 NA NA #> 6200 NA NA #> 6201 NA NA #> 6202 NA NA #> 6203 NA NA #> 6204 NA NA #> 6205 NA NA #> 6206 + NA NA #> 6207 NA NA #> 6208 I NA NA #> 6209 NA NA #> 6210 NA NA #> 6211 NA NA #> 6212 NA NA #> 6213 NA NA #> 6214 NA NA #> 6215 NA NA #> 6216 NA NA #> 6217 + NA NA #> 6218 NA NA #> 6219 I NA NA #> 6220 NA NA #> 6221 NA NA #> 6222 NA NA #> 6223 NA NA #> 6224 NA NA #> 6225 NA NA #> 6226 NA NA #> 6227 NA NA #> 6228 NA NA #> 6229 NA NA #> 6230 NA NA #> 6231 NA NA #> 6232 NA NA #> 6233 NA NA #> 6234 NA NA #> 6235 NA NA #> 6236 NA NA #> 6237 NA NA #> 6238 A NA NA #> 6239 NA NA #> 6240 + NA NA #> 6241 NA NA #> 6242 NA NA #> 6243 NA NA #> 6244 + NA NA #> 6245 NA NA #> 6246 A NA NA #> 6247 NA NA #> 6248 NA NA #> 6249 NA NA #> 6250 + NA NA #> 6251 NA NA #> 6252 NA NA #> 6253 NA NA #> 6254 + NA NA #> 6255 NA NA #> 6256 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7911 I NA NA #> 7912 NA NA #> 7913 NA NA #> 7914 + NA NA #> 7915 NA NA #> 7916 NA NA #> 7917 NA NA #> 7918 NA NA #> 7919 NA NA #> 7920 NA NA #> 7921 I NA NA #> 7922 NA NA #> 7923 NA NA #> 7924 + NA NA #> 7925 NA NA #> 7926 NA NA #> 7927 NA NA #> 7928 NA NA #> 7929 NA NA #> 7930 NA NA #> 7931 I NA NA #> 7932 NA NA #> 7933 NA NA #> 7934 + NA NA #> 7935 NA NA #> 7936 NA NA #> 7937 NA NA #> 7938 NA NA #> 7939 NA NA #> 7940 NA NA #> 7941 NA NA #> 7942 NA NA #> 7943 NA NA #> 7944 + NA NA #> 7945 NA NA #> 7946 NA NA #> 7947 NA NA #> 7948 NA NA #> 7949 NA NA #> 7950 NA NA #> 7951 NA NA #> 7952 NA NA #> 7953 NA NA #> 7954 + NA NA #> 7955 NA NA #> 7956 NA NA #> 7957 NA NA #> 7958 NA NA #> 7959 NA NA #> 7960 NA NA #> 7961 I NA NA #> 7962 NA NA #> 7963 NA NA #> 7964 + NA NA #> 7965 NA NA #> 7966 NA NA #> 7967 NA NA #> 7968 NA NA #> 7969 NA NA #> 7970 NA NA #> 7971 I NA NA #> 7972 NA NA #> 7973 NA NA #> 7974 + NA NA #> 7975 NA NA #> 7976 NA NA #> 7977 I NA NA #> 7978 NA NA #> 7979 NA NA #> 7980 NA NA #> 7981 NA NA #> 7982 NA NA #> 7983 NA NA #> 7984 + NA NA #> 7985 NA NA #> 7986 NA NA #> 7987 I NA NA #> 7988 NA NA #> 7989 NA NA #> 7990 NA NA #> 7991 I NA NA #> 7992 NA NA #> 7993 NA NA #> 7994 + NA NA #> 7995 NA NA #> 7996 NA NA #> 7997 I NA NA #> 7998 NA NA #> 7999 NA NA #> 8000 NA NA #> 8001 I NA NA #> 8002 NA NA #> 8003 NA NA #> 8004 + NA NA #> 8005 NA NA #> 8006 NA NA #> 8007 NA NA #> 8008 NA NA #> 8009 NA NA #> 8010 NA NA #> 8011 I NA NA #> 8012 NA NA #> 8013 NA NA #> 8014 + NA NA #> 8015 NA NA #> 8016 NA NA #> 8017 NA NA #> 8018 NA NA #> 8019 NA NA #> 8020 NA NA #> 8021 U NA NA #> 8022 NA NA #> 8023 NA NA #> 8024 + NA NA #> 8025 NA NA #> 8026 NA NA #> 8027 NA NA #> 8028 NA NA #> 8029 NA NA #> 8030 NA NA #> 8031 I NA NA #> 8032 NA NA #> 8033 NA NA #> 8034 + NA NA #> 8035 NA NA #> 8036 NA NA #> 8037 NA NA #> 8038 NA NA #> 8039 NA NA #> 8040 NA NA #> 8041 NA NA #> 8042 NA NA #> 8043 NA NA #> 8044 + NA NA #> 8045 NA NA #> 8046 NA NA #> 8047 NA NA #> 8048 NA NA #> 8049 NA NA #> 8050 NA NA #> 8051 NA NA #> 8052 NA NA #> 8053 NA NA #> 8054 + NA NA #> 8055 NA NA #> 8056 NA NA #> 8057 I NA NA #> 8058 NA NA #> 8059 NA NA #> 8060 NA NA #> 8061 NA NA #> 8062 NA NA #> 8063 NA NA #> 8064 + NA NA #> 8065 NA NA #> 8066 NA NA #> 8067 I NA NA #> 8068 A NA NA #> 8069 NA NA #> 8070 NA NA #> 8071 I NA NA #> 8072 NA NA #> 8073 NA NA #> 8074 + NA NA #> 8075 NA NA #> 8076 NA NA #> 8077 A NA NA #> 8078 NA NA #> 8079 NA NA #> 8080 NA NA #> 8081 I NA NA #> 8082 NA NA #> 8083 NA NA #> 8084 + NA NA #> 8085 NA NA #> 8086 NA NA #> 8087 NA NA #> 8088 NA NA #> 8089 NA NA #> 8090 NA NA #> 8091 NA NA #> 8092 NA NA #> 8093 NA NA #> 8094 + NA NA #> 8095 NA NA #> 8096 NA NA #> 8097 I NA NA #> 8098 A NA NA #> 8099 NA NA #> 8100 NA NA #> 8101 NA NA #> 8102 + NA NA #> 8103 NA NA #> 8104 NA NA #> 8105 I NA NA #> 8106 NA NA #> 8107 NA NA #> 8108 NA NA #> 8109 NA NA #> 8110 NA NA #> 8111 NA NA #> 8112 + NA NA #> 8113 NA NA #> 8114 NA NA #> 8115 I NA NA #> 8116 NA NA #> 8117 NA NA #> 8118 NA NA #> 8119 NA NA #> 8120 NA NA #> 8121 NA NA #> 8122 + NA NA #> 8123 NA NA #> 8124 NA NA #> 8125 NA NA #> 8126 NA NA #> 8127 NA NA #> 8128 NA NA #> 8129 I NA NA #> 8130 NA NA #> 8131 NA NA #> 8132 + NA NA #> 8133 NA NA #> 8134 NA NA #> 8135 I NA NA #> 8136 NA NA #> 8137 NA NA #> 8138 NA NA #> 8139 I NA NA #> 8140 NA NA #> 8141 I NA NA #> 8142 + NA NA #> 8143 NA NA #> 8144 A NA NA #> 8145 NA NA #> 8146 NA NA #> 8147 NA NA #> 8148 NA NA #> 8149 U NA NA #> 8150 NA NA #> 8151 + NA NA #> 8152 NA NA #> 8153 NA NA #> 8154 NA NA #> 8155 NA NA #> 8156 NA NA #> 8157 NA NA #> 8158 U NA NA #> 8159 NA NA #> 8160 NA NA #> 8161 + NA NA #> 8162 NA NA #> 8163 NA NA #> 8164 NA NA #> 8165 NA NA #> 8166 NA NA #> 8167 NA NA #> 8168 NA NA #> 8169 NA NA #> 8170 NA NA #> 8171 + NA NA #> 8172 NA NA #> 8173 NA NA #> 8174 NA NA #> 8175 NA NA #> 8176 NA NA #> 8177 NA NA #> 8178 I NA NA #> 8179 NA NA #> 8180 NA NA #> 8181 + NA NA #> 8182 NA NA #> 8183 NA NA #> 8184 NA NA #> 8185 NA NA #> 8186 NA NA #> 8187 NA NA #> 8188 NA NA #> 8189 NA NA #> 8190 NA NA #> 8191 + NA NA #> 8192 NA NA #> 8193 NA NA #> 8194 NA NA #> 8195 NA NA #> 8196 NA NA #> 8197 NA NA #> 8198 I NA NA #> 8199 NA NA #> 8200 NA NA #> 8201 + NA NA #> 8202 NA NA #> 8203 NA NA #> 8204 I NA NA #> 8205 A NA NA #> 8206 NA NA #> 8207 NA NA #> 8208 NA NA #> 8209 NA NA #> 8210 NA NA #> 8211 + NA NA #> 8212 NA NA #> 8213 NA NA #> 8214 I NA NA #> 8215 A NA NA #> 8216 NA NA #> 8217 + NA NA #> 8218 NA NA #> 8219 NA NA #> 8220 NA NA #> 8221 + NA NA #> 8222 NA NA #> 8223 NA NA #> 8224 NA NA #> 8225 NA NA #> 8226 NA NA #> 8227 NA NA #> 8228 NA NA #> 8229 NA NA #> 8230 NA NA #> 8231 + NA NA #> 8232 NA NA #> 8233 NA NA #> 8234 I NA NA #> 8235 I NA NA #> 8236 NA NA #> 8237 NA NA #> 8238 I NA NA #> 8239 NA NA #> 8240 NA NA #> 8241 + NA NA #> 8242 NA NA #> 8243 I NA NA #> 8244 I NA NA #> 8245 I NA NA #> 8246 NA NA #> 8247 NA NA #> 8248 U NA NA #> 8249 NA NA #> 8250 NA NA #> 8251 + NA NA #> 8252 NA NA #> 8253 NA NA #> 8254 NA NA #> 8255 NA NA #> 8256 NA NA #> 8257 NA NA #> 8258 I NA NA #> 8259 NA NA #> 8260 I NA NA #> 8261 + NA NA #> 8262 NA NA #> 8263 NA NA #> 8264 NA NA #> 8265 I NA NA #> 8266 NA NA #> 8267 NA NA #> 8268 I NA NA #> 8269 NA NA #> 8270 NA NA #> 8271 + NA NA #> 8272 NA NA #> 8273 I NA NA #> 8274 NA NA #> 8275 A NA NA #> 8276 NA NA #> 8277 NA NA #> 8278 I NA NA #> 8279 NA NA #> 8280 NA NA #> 8281 + NA NA #> 8282 NA NA #> 8283 NA NA #> 8284 NA NA #> 8285 NA NA #> 8286 I NA NA #> 8287 NA NA #> 8288 NA NA #> 8289 + NA NA #> 8290 NA NA #> 8291 NA NA #> 8292 NA NA #> 8293 A NA NA #> 8294 NA NA #> 8295 NA NA #> 8296 I NA NA #> 8297 NA NA #> 8298 NA NA #> 8299 + NA NA #> 8300 NA NA #> 8301 NA NA #> 8302 NA NA #> 8303 NA NA #> 8304 NA NA #> 8305 NA NA #> 8306 I NA NA #> 8307 NA NA #> 8308 NA NA #> 8309 + NA NA #> 8310 NA NA #> 8311 NA NA #> 8312 I NA NA #> 8313 NA NA #> 8314 NA NA #> 8315 NA NA #> 8316 NA NA #> 8317 NA NA #> 8318 NA NA #> 8319 + NA NA #> 8320 NA NA #> 8321 NA NA #> 8322 NA NA #> 8323 NA NA #> 8324 NA NA #> 8325 NA NA #> 8326 NA NA #> 8327 NA NA #> 8328 NA NA #> 8329 + NA NA #> 8330 NA NA #> 8331 NA NA #> 8332 NA NA #> 8333 NA NA #> 8334 NA NA #> 8335 NA NA #> 8336 NA NA #> 8337 NA NA #> 8338 NA NA #> 8339 + NA NA #> 8340 NA NA #> 8341 NA NA #> 8342 NA NA #> 8343 NA NA #> 8344 NA NA #> 8345 NA NA #> 8346 NA NA #> 8347 NA NA #> 8348 NA NA #> 8349 + NA NA #> 8350 NA NA #> 8351 NA NA #> 8352 NA NA #> 8353 NA NA #> 8354 NA NA #> 8355 NA NA #> 8356 I NA NA #> 8357 NA NA #> 8358 NA NA #> 8359 + NA NA #> 8360 NA NA #> 8361 NA NA #> 8362 NA NA #> 8363 NA NA #> 8364 NA NA #> 8365 NA NA #> 8366 NA NA #> 8367 NA NA #> 8368 NA NA #> 8369 NA NA #> 8370 NA NA #> 8371 NA NA #> 8372 NA NA #> 8373 NA NA #> 8374 NA NA #> 8375 NA NA #> 8376 NA NA #> 8377 NA NA #> 8378 NA NA #> 8379 NA NA #> 8380 NA NA #> 8381 NA NA #> 8382 NA NA #> 8383 NA NA #> 8384 NA NA #> 8385 NA NA #> 8386 NA NA #> 8387 NA NA #> 8388 NA NA #> 8389 NA NA #> 8390 NA NA #> 8391 NA NA #> 8392 NA NA #> 8393 NA NA #> 8394 NA NA #> 8395 NA NA #> 8396 NA NA #> 8397 NA NA #> 8398 NA NA #> 8399 NA NA #> 8400 NA NA #> 8401 NA NA #> 8402 NA NA #> 8403 NA NA #> 8404 NA NA #> 8405 NA NA #> 8406 NA NA #> 8407 NA NA #> 8408 NA NA #> 8409 NA NA #> 8410 NA NA #> 8411 NA NA #> 8412 NA NA #> 8413 NA NA #> 8414 NA NA #> 8415 NA NA #> 8416 NA NA #> 8417 NA NA #> 8418 NA NA #> 8419 NA NA #> 8420 NA NA #> 8421 NA NA #> 8422 NA NA #> 8423 NA NA #> 8424 NA NA #> 8425 I NA NA #> 8426 NA NA #> 8427 NA NA #> 8428 NA NA #> 8429 NA NA #> 8430 NA NA #> 8431 NA NA #> 8432 + NA NA #> 8433 I NA NA #> 8434 NA NA #> 8435 NA NA #> 8436 NA NA #> 8437 NA NA #> 8438 NA NA #> 8439 NA NA #> 8440 NA NA #> 8441 NA NA #> 8442 + NA NA #> 8443 NA NA #> 8444 NA NA #> 8445 NA NA #> 8446 NA NA #> 8447 NA NA #> 8448 + NA NA #> 8449 U NA NA #> 8450 NA NA #> 8451 NA NA #> 8452 NA NA #> 8453 NA NA #> 8454 NA NA #> 8455 NA NA #> 8456 NA NA #> 8457 NA NA #> 8458 + NA NA #> 8459 NA NA #> 8460 I NA NA #> 8461 NA NA #> 8462 NA NA #> 8463 + NA NA #> 8464 I NA NA #> 8465 NA NA #> 8466 NA NA #> 8467 NA NA #> 8468 NA NA #> 8469 NA NA #> 8470 NA NA #> 8471 NA NA #> 8472 NA NA #> 8473 + NA NA #> 8474 NA NA #> 8475 NA NA #> 8476 NA NA #> 8477 + NA NA #> 8478 NA NA #> 8479 NA NA #> 8480 NA NA #> 8481 + NA NA #> 8482 NA NA #> 8483 NA NA #> 8484 NA NA #> 8485 NA NA #> 8486 NA NA #> 8487 NA NA #> 8488 NA NA #> 8489 NA NA #> 8490 NA NA #> 8491 NA NA #> 8492 + NA NA #> 8493 NA NA #> 8494 NA NA #> 8495 NA NA #> 8496 + NA NA #> 8497 NA NA #> 8498 NA NA #> 8499 NA NA #> 8500 + NA NA #> 8501 NA NA #> 8502 NA NA #> 8503 NA NA #> 8504 NA NA #> 8505 + NA NA #> 8506 NA NA #> 8507 NA NA #> 8508 NA NA #> 8509 NA NA #> 8510 NA NA #> 8511 NA NA #> 8512 NA NA #> 8513 NA NA #> 8514 NA NA #> 8515 + NA NA #> 8516 NA NA #> 8517 NA NA #> 8518 NA NA #> 8519 + NA NA #> 8520 NA NA #> 8521 NA NA #> 8522 NA NA #> 8523 NA NA #> 8524 + NA NA #> 8525 I NA NA #> 8526 NA NA #> 8527 NA NA #> 8528 NA NA #> 8529 NA NA #> 8530 NA NA #> 8531 NA NA #> 8532 NA NA #> 8533 NA NA #> 8534 + NA NA #> 8535 NA NA #> 8536 NA NA #> 8537 NA NA #> 8538 + NA NA #> 8539 NA NA #> 8540 NA NA #> 8541 NA NA #> 8542 NA NA #> 8543 + NA NA #> 8544 I NA NA #> 8545 NA NA #> 8546 NA NA #> 8547 NA NA #> 8548 NA NA #> 8549 NA NA #> 8550 NA NA #> 8551 + NA NA #> 8552 NA NA #> 8553 NA NA #> 8554 NA NA #> 8555 NA NA #> 8556 NA NA #> 8557 NA NA #> 8558 + NA NA #> 8559 I NA NA #> 8560 NA NA #> 8561 NA NA #> 8562 NA NA #> 8563 NA NA #> 8564 NA NA #> 8565 NA NA #> 8566 NA NA #> 8567 NA NA #> 8568 + NA NA #> 8569 NA NA #> 8570 NA NA #> 8571 NA NA #> 8572 + NA NA #> 8573 NA NA #> 8574 NA NA #> 8575 NA NA #> 8576 NA NA #> 8577 + NA NA #> 8578 U NA NA #> 8579 NA NA #> 8580 NA NA #> 8581 NA NA #> 8582 NA NA #> 8583 NA NA #> 8584 NA NA #> 8585 NA NA #> 8586 NA NA #> 8587 + NA NA #> 8588 NA NA #> 8589 NA NA #> 8590 NA NA #> 8591 + NA NA #> 8592 NA NA #> 8593 NA NA #> 8594 NA NA #> 8595 + NA NA #> 8596 U NA NA #> 8597 NA NA #> 8598 NA NA #> 8599 NA NA #> 8600 NA NA #> 8601 NA NA #> 8602 NA NA #> 8603 NA NA #> 8604 NA NA #> 8605 + NA NA #> 8606 NA NA #> 8607 NA NA #> 8608 U NA NA #> 8609 NA NA #> 8610 NA NA #> 8611 + NA NA #> 8612 NA NA #> 8613 NA NA #> 8614 NA NA #> 8615 NA NA #> 8616 NA NA #> 8617 NA NA #> 8618 NA NA #> 8619 + NA NA #> 8620 U NA NA #> 8621 NA NA #> 8622 NA NA #> 8623 NA NA #> 8624 NA NA #> 8625 NA NA #> 8626 NA NA #> 8627 NA NA #> 8628 NA NA #> 8629 + NA NA #> 8630 NA NA #> 8631 NA NA #> 8632 NA NA #> 8633 + NA NA #> 8634 NA NA #> 8635 NA NA #> 8636 NA NA #> 8637 + NA NA #> 8638 U NA NA #> 8639 NA NA #> 8640 NA NA #> 8641 NA NA #> 8642 NA NA #> 8643 NA NA #> 8644 NA NA #> 8645 NA NA #> 8646 NA NA #> 8647 + NA NA #> 8648 NA NA #> 8649 NA NA #> 8650 NA NA #> 8651 + NA NA #> 8652 NA NA #> 8653 NA NA #> 8654 NA NA #> 8655 NA NA #> 8656 NA NA #> 8657 NA NA #> 8658 NA NA #> 8659 + NA NA #> 8660 NA NA #> 8661 + NA NA #> 8662 NA NA #> 8663 I NA NA #> 8664 NA NA #> 8665 A NA NA #> 8666 NA NA #> 8667 NA NA #> 8668 NA NA #> 8669 NA NA #> 8670 NA NA #> 8671 NA NA #> 8672 NA NA #> 8673 + NA NA #> 8674 NA NA #> 8675 NA NA #> 8676 NA NA #> 8677 I NA NA #> 8678 NA NA #> 8679 NA NA #> 8680 NA NA #> 8681 NA NA #> 8682 NA NA #> 8683 NA NA #> 8684 NA NA #> 8685 + NA NA #> 8686 NA NA #> 8687 I NA NA #> 8688 NA NA #> 8689 NA NA #> 8690 A NA NA #> 8691 NA NA #> 8692 NA NA #> 8693 + NA NA #> 8694 NA NA #> 8695 + NA NA #> 8696 NA NA #> 8697 I NA NA #> 8698 A NA NA #> 8699 NA NA #> 8700 NA NA #> 8701 NA NA #> 8702 NA NA #> 8703 NA NA #> 8704 NA NA #> 8705 NA NA #> 8706 + NA NA #> 8707 NA NA #> 8708 NA NA #> 8709 NA NA #> 8710 NA NA #> 8711 NA NA #> 8712 NA NA #> 8713 NA NA #> 8714 NA NA #> 8715 NA NA #> 8716 NA NA #> 8717 + NA NA #> 8718 NA NA #> 8719 I NA NA #> 8720 A NA NA #> 8721 NA NA #> 8722 NA NA #> 8723 NA NA #> 8724 NA NA #> 8725 NA NA #> 8726 NA NA #> 8727 + NA NA #> 8728 NA NA #> 8729 + NA NA #> 8730 NA NA #> 8731 I NA NA #> 8732 A NA NA #> 8733 NA NA #> 8734 NA NA #> 8735 NA NA #> 8736 NA NA #> 8737 NA NA #> 8738 NA NA #> 8739 + NA NA #> 8740 NA NA #> 8741 + NA NA #> 8742 NA NA #> 8743 I NA NA #> 8744 NA NA #> 8745 NA NA #> 8746 A NA NA #> 8747 NA NA #> 8748 NA NA #> 8749 NA NA #> 8750 NA NA #> 8751 + NA NA #> 8752 NA NA #> 8753 + NA NA #> 8754 NA NA #> 8755 I NA NA #> 8756 NA NA #> 8757 NA NA #> 8758 NA NA #> 8759 NA NA #> 8760 + NA NA #> 8761 NA NA #> 8762 NA NA #> 8763 NA NA #> 8764 NA NA #> 8765 NA NA #> 8766 U NA NA #> 8767 + NA NA #> 8768 NA NA #> 8769 + NA NA #> 8770 NA NA #> 8771 I NA NA #> 8772 NA NA #> 8773 NA NA #> 8774 NA NA #> 8775 NA NA #> 8776 NA NA #> 8777 NA NA #> 8778 NA NA #> 8779 NA NA #> 8780 + NA NA #> 8781 NA NA #> 8782 I NA NA #> 8783 NA NA #> 8784 NA NA #> 8785 NA NA #> 8786 NA NA #> 8787 NA NA #> 8788 NA NA #> 8789 NA NA #> 8790 NA NA #> 8791 NA NA #> 8792 + NA NA #> 8793 NA NA #> 8794 I NA NA #> 8795 NA NA #> 8796 NA NA #> 8797 NA NA #> 8798 NA NA #> 8799 NA NA #> 8800 NA NA #> 8801 NA NA #> 8802 NA NA #> 8803 NA NA #> 8804 NA NA #> 8805 NA NA #> 8806 NA NA #> 8807 NA NA #> 8808 + NA NA #> 8809 NA NA #> 8810 I NA NA #> 8811 NA NA #> 8812 NA NA 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9088 NA NA #> 9089 NA NA #> 9090 + NA NA #> [ reached 'max' / getOption(\"max.print\") -- omitted 165157 rows ]"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_refs.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert references csv to bib — anlz_refs","title":"Convert references csv to bib — anlz_refs","text":"Convert references csv bib","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_refs.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert references csv to bib — anlz_refs","text":"","code":"anlz_refs(path)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_refs.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert references csv to bib — anlz_refs","text":"path chr string path reference csv file data frame object","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_refs.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert references csv to bib — anlz_refs","text":"data frame references formatted bib entries","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_refs.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Convert references csv to bib — anlz_refs","text":"","code":"# input and format path <- 'https://raw.githubusercontent.com/tbep-tech/tbep-refs/master/tbep-refs.csv' bibs <- anlz_refs(path) if (FALSE) { # save output writeLines(bibs, 'formatted.bib') }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_sedimentaddtot.html","id":null,"dir":"Reference","previous_headings":"","what":"Add contaminant totals to sediment data — anlz_sedimentaddtot","title":"Add contaminant totals to sediment data — anlz_sedimentaddtot","text":"Add contaminant totals sediment data","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_sedimentaddtot.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Add contaminant totals to sediment data — anlz_sedimentaddtot","text":"","code":"anlz_sedimentaddtot( sedimentdata, yrrng = c(1993, 2022), bay_segment = c(\"HB\", \"OTB\", \"MTB\", \"LTB\", \"TCB\", \"MR\", \"BCB\"), funding_proj = \"TBEP\", param = NULL, pelave = TRUE )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_sedimentaddtot.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Add contaminant totals to sediment data — anlz_sedimentaddtot","text":"sedimentdata input sediment data.frame returned read_importsediment yrrng numeric vector indicating min, max years include, use single year one year data bay_segment chr string bay segment, one many \"HB\", \"OTB\", \"MTB\", \"LTB\", \"TCB\", \"MR\", \"BCB\" funding_proj chr string funding project, one many \"TBEP\" (default), \"TBEP-Special\", \"Apollo Beach\", \"Janicki Contract\", \"Rivers\", \"Tidal Streams\" param optional character string parameter filter results pelave logical indicating output used anlz_sedimentpel","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_sedimentaddtot.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Add contaminant totals to sediment data — anlz_sedimentaddtot","text":"data.frame object similar input, filtered arguments contaminant totals added. Replicate samples also removed.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_sedimentaddtot.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Add contaminant totals to sediment data — anlz_sedimentaddtot","text":"function adds totals sedimentdata input total PCBs, total DDT, total LMW PAH, total HMW PAH, total PAH. Appropriate TEL/PEL values totals also added.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_sedimentaddtot.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Add contaminant totals to sediment data — anlz_sedimentaddtot","text":"","code":"anlz_sedimentaddtot(sedimentdata) #> # A tibble: 62,667 × 24 #> ProgramId ProgramName FundingProject yr AreaAbbr StationID StationNumber #> #> 1 4 Benthic Moni… TBEP 1993 HB 2463 93HB15 #> 2 4 Benthic Moni… TBEP 1993 HB 2463 93HB15 #> 3 4 Benthic Moni… TBEP 1993 HB 2463 93HB15 #> 4 4 Benthic Moni… TBEP 1993 HB 2463 93HB15 #> 5 4 Benthic Moni… TBEP 1993 HB 2463 93HB15 #> 6 4 Benthic Moni… TBEP 1993 HB 2463 93HB15 #> 7 4 Benthic Moni… TBEP 1993 HB 2463 93HB15 #> 8 4 Benthic Moni… TBEP 1993 HB 2463 93HB15 #> 9 4 Benthic Moni… TBEP 1993 HB 2463 93HB15 #> 10 4 Benthic Moni… TBEP 1993 HB 2464 93HB16 #> # ℹ 62,657 more rows #> # ℹ 17 more variables: Latitude , Longitude , Replicate , #> # SedResultsType , Parameter , ValueAdjusted , Units , #> # Qualifier , MDLnum , PQLnum , TEL , PEL , #> # BetweenTELPEL , ExceedsPEL , PELRatio , #> # PreparationDate , AnalysisTimeMerge "},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_sedimentave.html","id":null,"dir":"Reference","previous_headings":"","what":"Get average concentrations for a sediment parameter by bay segment — anlz_sedimentave","title":"Get average concentrations for a sediment parameter by bay segment — anlz_sedimentave","text":"Get average concentrations sediment parameter bay segment","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_sedimentave.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get average concentrations for a sediment parameter by bay segment — anlz_sedimentave","text":"","code":"anlz_sedimentave( sedimentdata, param, yrrng = c(1993, 2022), bay_segment = c(\"HB\", \"OTB\", \"MTB\", \"LTB\", \"TCB\", \"MR\", \"BCB\"), funding_proj = \"TBEP\" )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_sedimentave.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get average concentrations for a sediment parameter by bay segment — anlz_sedimentave","text":"sedimentdata input sediment data.frame returned read_importsediment param chr string parameter plot yrrng numeric vector indicating min, max years include, use single year one year data bay_segment chr string bay segment, one many \"HB\", \"OTB\", \"MTB\", \"LTB\", \"TCB\", \"MR\", \"BCB\" funding_proj chr string funding project, one many \"TBEP\" (default), \"TBEP-Special\", \"Apollo Beach\", \"Janicki Contract\", \"Rivers\", \"Tidal Streams\"","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_sedimentave.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get average concentrations for a sediment parameter by bay segment — anlz_sedimentave","text":"data.frame object average sediment concentrations selected parameter bay segment","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_sedimentave.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Get average concentrations for a sediment parameter by bay segment — anlz_sedimentave","text":"Summaries bay segments returned default. averages confidence intervals specific year ranges yrrng.","code":""},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_sedimentave.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get average concentrations for a sediment parameter by bay segment — anlz_sedimentave","text":"","code":"anlz_sedimentave(sedimentdata, param = 'Arsenic') #> # A tibble: 7 × 8 #> AreaAbbr TEL PEL Units ave lov hiv grandave #> #> 1 BCB 7.24 41.6 mg/kg 2.64 2.34 2.94 2.57 #> 2 HB 7.24 41.6 mg/kg 2.93 0.665 5.20 2.57 #> 3 LTB 7.24 41.6 mg/kg 2.93 2.47 3.40 2.57 #> 4 MR 7.24 41.6 mg/kg 1.66 1.37 1.95 2.57 #> 5 MTB 7.24 41.6 mg/kg 2.17 1.86 2.48 2.57 #> 6 OTB 7.24 41.6 mg/kg 3.24 0.707 5.78 2.57 #> 7 TCB 7.24 41.6 mg/kg 2.40 1.92 2.88 2.57"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_sedimentpel.html","id":null,"dir":"Reference","previous_headings":"","what":"Get sediment PEL ratios at stations in Tampa Bay — anlz_sedimentpel","title":"Get sediment PEL ratios at stations in Tampa Bay — anlz_sedimentpel","text":"Get sediment PEL ratios stations Tampa Bay","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_sedimentpel.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get sediment PEL ratios at stations in Tampa Bay — anlz_sedimentpel","text":"","code":"anlz_sedimentpel( sedimentdata, yrrng = c(1993, 2022), bay_segment = c(\"HB\", \"OTB\", \"MTB\", \"LTB\", \"TCB\", \"MR\", \"BCB\"), funding_proj = \"TBEP\" )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_sedimentpel.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get sediment PEL ratios at stations in Tampa Bay — anlz_sedimentpel","text":"sedimentdata input sediment data.frame returned read_importsediment yrrng numeric vector indicating min, max years include, use single year one year data bay_segment chr string bay segment, one many \"HB\", \"OTB\", \"MTB\", \"LTB\", \"TCB\", \"MR\", \"BCB\" funding_proj chr string funding project, one many \"TBEP\" (default), \"TBEP-Special\", \"Apollo Beach\", \"Janicki Contract\", \"Rivers\", \"Tidal Streams\"","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_sedimentpel.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get sediment PEL ratios at stations in Tampa Bay — anlz_sedimentpel","text":"data.frame object average PEL ratios grades station","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_sedimentpel.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Get sediment PEL ratios at stations in Tampa Bay — anlz_sedimentpel","text":"Average PEL ratios contaminants graded F benthic stations monitored Tampa Bay estimated. PEL measure likely contaminant toxic effect invertebrates inhabit sediment. PEL ratio contaminant concentration divided Potential Effects Levels (PEL) applies contaminant, available. Higher ratios lower grades indicate sediment conditions likely unfavorable invertebrates. station average combines PEL ratios across contaminants measured station grade applies average. grade breaks PEL ratio 0.00756, 0.02052, 0.08567, 0.28026, lower grades assigned higher breaks.","code":""},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_sedimentpel.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get sediment PEL ratios at stations in Tampa Bay — anlz_sedimentpel","text":"","code":"anlz_sedimentpel(sedimentdata) #> # A tibble: 2,233 × 7 #> yr AreaAbbr StationNumber Latitude Longitude PELRatio Grade #> #> 1 1993 HB 93HB15 27.8 -82.4 0.0157 B #> 2 1993 HB 93HB16 27.8 -82.5 0.0261 C #> 3 1993 HB 93HB23 27.9 -82.4 0.0174 B #> 4 1993 LTB 93LTB24 27.7 -82.6 0.0124 B #> 5 1993 LTB 93LTB25 27.6 -82.6 0.0189 B #> 6 1993 LTB 93LTB26 27.6 -82.7 0.00997 B #> 7 1993 LTB 93LTB27 27.6 -82.7 0.0125 B #> 8 1993 LTB 93LTB28 27.6 -82.7 0.0887 D #> 9 1993 LTB 93LTB29 27.6 -82.6 0.0350 C #> 10 1993 LTB 93LTB30 27.6 -82.6 0.0496 C #> # ℹ 2,223 more rows"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_sedimentpelave.html","id":null,"dir":"Reference","previous_headings":"","what":"Get average concentrations for a sediment parameter by bay segment — anlz_sedimentpelave","title":"Get average concentrations for a sediment parameter by bay segment — anlz_sedimentpelave","text":"Get average concentrations sediment parameter bay segment","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_sedimentpelave.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get average concentrations for a sediment parameter by bay segment — anlz_sedimentpelave","text":"","code":"anlz_sedimentpelave( sedimentdata, yrrng = c(1993, 2022), bay_segment = c(\"HB\", \"OTB\", \"MTB\", \"LTB\", \"TCB\", \"MR\", \"BCB\"), funding_proj = \"TBEP\" )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_sedimentpelave.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get average concentrations for a sediment parameter by bay segment — anlz_sedimentpelave","text":"sedimentdata input sediment data.frame returned read_importsediment yrrng numeric vector indicating min, max years include, use single year one year data bay_segment chr string bay segment, one many \"HB\", \"OTB\", \"MTB\", \"LTB\", \"TCB\", \"MR\", \"BCB\" funding_proj chr string funding project, one many \"TBEP\" (default), \"TBEP-Special\", \"Apollo Beach\", \"Janicki Contract\", \"Rivers\", \"Tidal Streams\"","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_sedimentpelave.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get average concentrations for a sediment parameter by bay segment — anlz_sedimentpelave","text":"data.frame average average PEL ratios bay segment","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_sedimentpelave.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Get average concentrations for a sediment parameter by bay segment — anlz_sedimentpelave","text":"Summaries bay segments returned default. averages confidence intervals specific year ranges yrrng.","code":""},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_sedimentpelave.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get average concentrations for a sediment parameter by bay segment — anlz_sedimentpelave","text":"","code":"anlz_sedimentpelave(sedimentdata) #> # A tibble: 7 × 5 #> AreaAbbr ave lov hiv grandave #> #> 1 BCB 0.0535 0.0445 0.0625 0.0522 #> 2 HB 0.118 0.0663 0.169 0.0522 #> 3 LTB 0.0281 0.0247 0.0315 0.0522 #> 4 MR 0.0446 0.0375 0.0516 0.0522 #> 5 MTB 0.0374 0.0327 0.0421 0.0522 #> 6 OTB 0.0506 0.0371 0.0642 0.0522 #> 7 TCB 0.0337 0.0265 0.0409 0.0522"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbbimed.html","id":null,"dir":"Reference","previous_headings":"","what":"Get annual medians of Tampa Bay Benthic Index scores by bay segment — anlz_tbbimed","title":"Get annual medians of Tampa Bay Benthic Index scores by bay segment — anlz_tbbimed","text":"Get annual medians Tampa Bay Benthic Index scores bay segment","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbbimed.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get annual medians of Tampa Bay Benthic Index scores by bay segment — anlz_tbbimed","text":"","code":"anlz_tbbimed( tbbiscr, bay_segment = c(\"HB\", \"OTB\", \"MTB\", \"LTB\", \"TCB\", \"MR\", \"BCB\", \"All\", \"All (wt)\"), rev = FALSE, yrrng = c(1993, 2022) )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbbimed.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get annual medians of Tampa Bay Benthic Index scores by bay segment — anlz_tbbimed","text":"tbbiscr input data frame returned anlz_tbbiscr bay_segment chr string bay segment, one many \"HB\", \"OTB\", \"MTB\", \"LTB\", \"TCB\", \"MR\", \"BCB\", \"\", \"(wt)\" rev logical factor levels bay segments reversed yrrng numeric indicating year ranges evaluate","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbbimed.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get annual medians of Tampa Bay Benthic Index scores by bay segment — anlz_tbbimed","text":"data frame annual medians bay segment","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbbimed.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Get annual medians of Tampa Bay Benthic Index scores by bay segment — anlz_tbbimed","text":"Additional summaries provided entire bay, summary across categories (\"\") summary weighted across relative sizes bay segment (\"(wt)\"). sampling funded TBEP part routine EPC benthic monitoring program included final categories.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbbimed.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get annual medians of Tampa Bay Benthic Index scores by bay segment — anlz_tbbimed","text":"","code":"tbbiscr <- anlz_tbbiscr(benthicdata) anlz_tbbimed(tbbiscr) #> # A tibble: 268 × 6 #> # Rowwise: #> bay_segment yr Degraded Healthy Intermediate TBBICat #> #> 1 All 1993 0.3 0.244 0.456 Poor #> 2 All 1994 0.449 0.180 0.371 Poor #> 3 All 1995 0.133 0.508 0.359 Fair #> 4 All 1996 0.138 0.569 0.292 Fair #> 5 All 1997 0.157 0.421 0.421 Fair #> 6 All 1998 0.231 0.316 0.453 Poor #> 7 All 1999 0.107 0.377 0.516 Fair #> 8 All 2000 0.163 0.407 0.430 Fair #> 9 All 2001 0.231 0.321 0.449 Poor #> 10 All 2002 0.2 0.425 0.375 Poor #> # ℹ 258 more rows"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbbiscr.html","id":null,"dir":"Reference","previous_headings":"","what":"Get Tampa Bay Benthic Index scores — anlz_tbbiscr","title":"Get Tampa Bay Benthic Index scores — anlz_tbbiscr","text":"Get Tampa Bay Benthic Index scores","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbbiscr.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get Tampa Bay Benthic Index scores — anlz_tbbiscr","text":"","code":"anlz_tbbiscr(benthicdata)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbbiscr.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get Tampa Bay Benthic Index scores — anlz_tbbiscr","text":"benthicdata nested tibble formatted read_importbenthic","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbbiscr.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get Tampa Bay Benthic Index scores — anlz_tbbiscr","text":"single data frame TBBI scores site.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbbiscr.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Get Tampa Bay Benthic Index scores — anlz_tbbiscr","text":"function calculates scores TBBI based station, taxa, field sample data. total TBBI scores returned TBBI TBBICat, latter categorical description scores.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbbiscr.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get Tampa Bay Benthic Index scores — anlz_tbbiscr","text":"","code":"anlz_tbbiscr(benthicdata) #> # A tibble: 4,787 × 15 #> StationID StationNumber AreaAbbr FundingProject ProgramID ProgramName #> #> 1 448 02BBs301 MTB Apollo Beach 4 Benthic Monitoring #> 2 449 02BBs305 MTB Apollo Beach 4 Benthic Monitoring #> 3 450 02BBs307 MTB Apollo Beach 4 Benthic Monitoring #> 4 451 02BBs364 MTB Apollo Beach 4 Benthic Monitoring #> 5 452 02BBs369 MTB Apollo Beach 4 Benthic Monitoring #> 6 453 02BBs395 MTB Apollo Beach 4 Benthic Monitoring #> 7 454 02BBs397 MTB Apollo Beach 4 Benthic Monitoring #> 8 455 02BBs398 MTB Apollo Beach 4 Benthic Monitoring #> 9 456 02BBs401 MTB Apollo Beach 4 Benthic Monitoring #> 10 457 02BBs402 MTB Apollo Beach 4 Benthic Monitoring #> # ℹ 4,777 more rows #> # ℹ 9 more variables: Latitude , Longitude , date , yr , #> # TotalAbundance , SpeciesRichness , TBBI , TBBICat , #> # Salinity "},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbniave.html","id":null,"dir":"Reference","previous_headings":"","what":"Get annual averages of Tampa Bay Nekton Index scores by bay segment — anlz_tbniave","title":"Get annual averages of Tampa Bay Nekton Index scores by bay segment — anlz_tbniave","text":"Get annual averages Tampa Bay Nekton Index scores bay segment","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbniave.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get annual averages of Tampa Bay Nekton Index scores by bay segment — anlz_tbniave","text":"","code":"anlz_tbniave( tbniscr, bay_segment = c(\"OTB\", \"HB\", \"MTB\", \"LTB\"), rev = FALSE, perc = c(32, 46) )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbniave.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get annual averages of Tampa Bay Nekton Index scores by bay segment — anlz_tbniave","text":"tbniscr input data frame returned anlz_tbniscr bay_segment chr string bay segment, one many \"OTB\", \"HB\", \"MTB\", \"LTB\" rev logical factor levels bay segments reversed perc numeric values indicating break points score categories","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbniave.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get annual averages of Tampa Bay Nekton Index scores by bay segment — anlz_tbniave","text":"data frame annual averages bay segment","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbniave.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get annual averages of Tampa Bay Nekton Index scores by bay segment — anlz_tbniave","text":"","code":"tbniscr <- anlz_tbniscr(fimdata) anlz_tbniave(tbniscr) #> # A tibble: 100 × 5 #> bay_segment Year Segment_TBNI Action outcome #> #> 1 HB 1998 47 Stay the Course green #> 2 HB 1999 47 Stay the Course green #> 3 HB 2000 44 Caution yellow #> 4 HB 2001 44 Caution yellow #> 5 HB 2002 39 Caution yellow #> 6 HB 2003 41 Caution yellow #> 7 HB 2004 41 Caution yellow #> 8 HB 2005 32 Caution yellow #> 9 HB 2006 41 Caution yellow #> 10 HB 2007 42 Caution yellow #> # ℹ 90 more rows"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbnimet.html","id":null,"dir":"Reference","previous_headings":"","what":"Get all raw metrics for Tampa Bay Nekton Index — anlz_tbnimet","title":"Get all raw metrics for Tampa Bay Nekton Index — anlz_tbnimet","text":"Get raw metrics Tampa Bay Nekton Index","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbnimet.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get all raw metrics for Tampa Bay Nekton Index — anlz_tbnimet","text":"","code":"anlz_tbnimet(fimdata, all = FALSE)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbnimet.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get all raw metrics for Tampa Bay Nekton Index — anlz_tbnimet","text":"fimdata data.frame formatted read_importfim logical indicating TBNI metrics returned (default), otherwise calcualted","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbnimet.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get all raw metrics for Tampa Bay Nekton Index — anlz_tbnimet","text":"data frame raw metrics wide fomat. = TRUE, metrics returned, otherwise NumTaxa, BenthicTaxa, TaxaSelect, NumGuilds, Shannon returned.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbnimet.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Get all raw metrics for Tampa Bay Nekton Index — anlz_tbnimet","text":"raw metrics returned addition required TBNI. row shows metric values station, year, month fish catch data available.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbnimet.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get all raw metrics for Tampa Bay Nekton Index — anlz_tbnimet","text":"","code":"anlz_tbnimet(fimdata) #> # A tibble: 7,445 × 10 #> Reference Year Month Season bay_segment NumTaxa Shannon TaxaSelect NumGuilds #> #> 1 TBM19980… 1998 1 Winter OTB 2 0.362 0 2 #> 2 TBM19980… 1998 1 Winter OTB 1 0 1 1 #> 3 TBM19980… 1998 1 Winter OTB 0 0 0 0 #> 4 TBM19980… 1998 1 Winter OTB 2 0.693 0 1 #> 5 TBM19980… 1998 1 Winter MTB 4 1.16 1 2 #> 6 TBM19980… 1998 1 Winter MTB 2 0.500 1 1 #> 7 TBM19980… 1998 1 Winter MTB 5 0.426 2 3 #> 8 TBM19980… 1998 1 Winter OTB 0 0 0 0 #> 9 TBM19980… 1998 1 Winter HB 4 0.794 1 4 #> 10 TBM19980… 1998 1 Winter HB 1 0 0 1 #> # ℹ 7,435 more rows #> # ℹ 1 more variable: BenthicTaxa "},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbniscr.html","id":null,"dir":"Reference","previous_headings":"","what":"Get Tampa Bay Nekton Index scores — anlz_tbniscr","title":"Get Tampa Bay Nekton Index scores — anlz_tbniscr","text":"Get Tampa Bay Nekton Index scores","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbniscr.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get Tampa Bay Nekton Index scores — anlz_tbniscr","text":"","code":"anlz_tbniscr(fimdata, raw = TRUE)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbniscr.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get Tampa Bay Nekton Index scores — anlz_tbniscr","text":"fimdata data.frame formatted read_importfim raw logical indicating raw metric values also returned","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbniscr.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get Tampa Bay Nekton Index scores — anlz_tbniscr","text":"data frame metrics TBNI scores wide format.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbniscr.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Get Tampa Bay Nekton Index scores — anlz_tbniscr","text":"function calculates raw scored metrics TBNI, including NumTaxa, BenthicTaxa, TaxaSelect, NumGuilds, Shannon. total TBNI score returned TBNI_Score.","code":""},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbniscr.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get Tampa Bay Nekton Index scores — anlz_tbniscr","text":"","code":"anlz_tbniscr(fimdata) #> # A tibble: 7,445 × 16 #> Reference Year Month Season bay_segment TBNI_Score NumTaxa ScoreNumTaxa #> #> 1 TBM1998010906 1998 1 Winter OTB 18 2 2 #> 2 TBM1998010910 1998 1 Winter OTB 14 1 1 #> 3 TBM1998010912 1998 1 Winter OTB 0 0 0 #> 4 TBM1998010914 1998 1 Winter OTB 20 2 2 #> 5 TBM1998010915 1998 1 Winter MTB 46 4 4 #> 6 TBM1998010917 1998 1 Winter MTB 24 2 2 #> 7 TBM1998010920 1998 1 Winter MTB 50 5 5 #> 8 TBM1998010922 1998 1 Winter OTB 0 0 0 #> 9 TBM1998010926 1998 1 Winter HB 48 4 4 #> 10 TBM1998010928 1998 1 Winter HB 8 1 1 #> # ℹ 7,435 more rows #> # ℹ 8 more variables: BenthicTaxa , ScoreBenthicTaxa , #> # TaxaSelect , ScoreTaxaSelect , NumGuilds , #> # ScoreNumGuilds , Shannon , ScoreShannon "},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tdlcrk.html","id":null,"dir":"Reference","previous_headings":"","what":"Estimate tidal creek report card scores — anlz_tdlcrk","title":"Estimate tidal creek report card scores — anlz_tdlcrk","text":"Estimate tidal creek report card scores","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tdlcrk.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Estimate tidal creek report card scores — anlz_tdlcrk","text":"","code":"anlz_tdlcrk(tidalcreeks, iwrraw, tidtrgs = NULL, yr = 2023)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tdlcrk.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Estimate tidal creek report card scores — anlz_tdlcrk","text":"tidalcreeks sf object population tidal creeks iwrraw FDEP impaired waters data base data.frame tidtrgs optional data.frame tidal creek nitrogen targets, defaults tidaltargets yr numeric reference year evaluate, scores based planning period beginning ten years prior date","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tdlcrk.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Estimate tidal creek report card scores — anlz_tdlcrk","text":"data.frame report card scores creek, prioritize, investigate, caution, monitor, data","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tdlcrk.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Estimate tidal creek report card scores — anlz_tdlcrk","text":"","code":"anlz_tdlcrk(tidalcreeks, iwrraw, yr = 2023) #> # A tibble: 615 × 10 #> id wbid JEI name class monitor caution investigate prioritize score #> #> 1 1 1983B CC01 Rock Cr… 2 NA NA NA NA No D… #> 2 2 2052 CC01 Rock Cr… 3M 10 NA NA NA Moni… #> 3 3 1983B CC02 Oyster … 2 NA NA NA NA No D… #> 4 4 2067 CC02 Oyster … 3M 10 NA NA NA Moni… #> 5 5 1983B CC03 Buck Cr… 2 NA NA NA NA No D… #> 6 6 2068 CC03 Buck Cr… 3M 9 1 NA NA Moni… #> 7 7 2078A CC04 Buck Cr… 2 NA NA 1 NA Inve… #> 8 8 2078A CC05 Coral C… 2 NA NA NA NA No D… #> 9 9 2078B CC05 Coral C… 2 4 1 NA NA Moni… #> 10 10 2065C CC06 Catfish… 2 NA NA NA NA No D… #> # ℹ 605 more rows"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tdlcrkindic.html","id":null,"dir":"Reference","previous_headings":"","what":"Analyze tidal creek water quality indicators — anlz_tdlcrkindic","title":"Analyze tidal creek water quality indicators — anlz_tdlcrkindic","text":"Estimate tidal creek water quality indicators support report card scores","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tdlcrkindic.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Analyze tidal creek water quality indicators — anlz_tdlcrkindic","text":"","code":"anlz_tdlcrkindic(tidalcreeks, iwrraw, yr = 2023, radar = FALSE)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tdlcrkindic.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Analyze tidal creek water quality indicators — anlz_tdlcrkindic","text":"tidalcreeks sf object population tidal creeks iwrraw FDEP impaired waters rule data base data.frame yr numeric reference year evaluate, scores based planning period beginning ten years prior date radar logical indicating output show_tdlcrkradar, see details","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tdlcrkindic.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Analyze tidal creek water quality indicators — anlz_tdlcrkindic","text":"data.frame indicator values tidal creek","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tdlcrkindic.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Analyze tidal creek water quality indicators — anlz_tdlcrkindic","text":"Annual geometric means additional water quality data available wbid, JEI combination. Florida trophic state index values also estimated data available. Nitrogen ratios estimated JEIs cover source (upstream, freshwater) tidal (downstream) WBIDs, defined ratio concentrations two (.e., ratios > 1 mean source higher concentrations). Nitrogen ratios given year reflect ratio median nitrogen concentrations measured source tidal segment day. Note ratio one can obtained source tidal segments minimum detection. Indicators years 10% observations exceed saturation criteria also estimated. do_bnml do_prop columns show 1 0 given year indicate ten percent observations percent saturation 42. first column based binomial probability exceedance takes account number observations year second column based simple proportional estimate raw data. radar = TRUE, output returned format use show_tdlcrkradar Specifically, results calculated percentage years indicator exceeds relevant threshold. applies marine WBIDs tidal creeks (Florida DEP class 2, 3M). Six indicators returned percentage exceedances based total nitrogen (tn_ind) greater 1.1 mg/L, chlorophyll (chla_ind) greater 11 ug/L, trophic state index (tsi_ind) greater 55 (100), nitrate/nitrite ratio marine upstream segments (nox_ind) greater one, chlorophyll total nitrogen ratios > 15, percentage years ten percent observations percent saturation 42.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tdlcrkindic.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Analyze tidal creek water quality indicators — anlz_tdlcrkindic","text":"","code":"dat <- anlz_tdlcrkindic(tidalcreeks, iwrraw, yr = 2023) head(dat) #> id name JEI wbid class year CHLAC COLOR COND DO DOSAT #> 1 2 Rock Creek CC01 2052 3M 2014 2.380249 14.69473 NA 3.308289 60.31523 #> 2 2 Rock Creek CC01 2052 3M 2015 2.647817 21.91113 NA 4.034172 55.41609 #> 3 2 Rock Creek CC01 2052 3M 2016 2.265462 19.13080 NA 3.980251 55.96637 #> 4 2 Rock Creek CC01 2052 3M 2017 2.851726 15.39576 NA 4.157777 60.18017 #> 5 2 Rock Creek CC01 2052 3M 2018 1.934899 11.65500 NA 4.219790 63.32630 #> 6 2 Rock Creek CC01 2052 3M 2019 2.071003 7.21425 NA 3.015847 44.90322 #> NO23 ORGN SALIN TKN TN TP TSS TURB #> 1 0.007575792 NA 26.63714 0.6161702 0.6228782 0.06938150 NA 2.044623 #> 2 0.009361504 NA 19.10494 0.6465161 0.5678241 0.07602770 NA 1.814818 #> 3 0.008532522 NA 25.84531 0.5813818 0.5408161 0.08330509 NA 2.082253 #> 4 0.007447260 NA 24.86909 0.6255197 0.6326848 0.07566682 NA 1.802161 #> 5 0.006994714 NA 31.32419 0.5668727 0.5734574 0.07432007 NA 2.454007 #> 6 0.007047106 NA 31.63214 0.5053022 0.4577485 0.06300538 NA 1.831953 #> chla_tn_ratio tn_tp_ratio chla_tsi tn_tsi tn2_tsi tp_tsi tp2_tsi #> 1 3.821371 8.977584 29.28775 46.62660 49.42526 60.45694 76.25504 #> 2 4.663093 7.468648 30.82179 44.79432 47.43600 62.15842 78.41391 #> 3 4.188970 6.491994 28.57601 43.82942 46.38844 63.85868 80.57123 #> 4 4.507341 8.361456 31.89011 46.93590 49.76107 62.06992 78.30162 #> 5 3.374095 7.716050 26.30480 44.98978 47.64821 61.73589 77.87779 #> 6 4.524324 7.265229 27.28367 40.52758 42.80384 58.66389 73.97999 #> nut_tsi tsi no23_source no23_tidal no23_ratio do_bnml do_prop #> 1 49.42526 39.35651 NA NA NA 0 1 #> 2 47.43600 39.12890 NA NA NA 0 1 #> 3 46.38844 37.48223 NA NA NA 0 1 #> 4 49.76107 40.82559 NA NA NA 0 0 #> 5 47.64821 36.97650 NA NA NA 0 1 #> 6 42.80384 35.04375 NA NA NA 1 1"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_transectave.html","id":null,"dir":"Reference","previous_headings":"","what":"Get annual averages of seagrass frequency occurrence by bay segments and year — anlz_transectave","title":"Get annual averages of seagrass frequency occurrence by bay segments and year — anlz_transectave","text":"Get annual averages seagrass frequency occurrence bay segments year","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_transectave.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get annual averages of seagrass frequency occurrence by bay segments and year — anlz_transectave","text":"","code":"anlz_transectave( transectocc, bay_segment = c(\"OTB\", \"HB\", \"MTB\", \"LTB\", \"BCB\"), total = TRUE, yrrng = c(1998, 2023), rev = FALSE )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_transectave.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get annual averages of seagrass frequency occurrence by bay segments and year — anlz_transectave","text":"transectocc data frame returned anlz_transectocc bay_segment chr string bay segment, one many \"OTB\", \"HB\", \"MTB\", \"LTB\", \"BCB\" total logical indicating average frequency occurrence calculated entire bay across segments yrrng numeric indicating year ranges evaluate rev logical factor levels bay segments reversed","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_transectave.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get annual averages of seagrass frequency occurrence by bay segments and year — anlz_transectave","text":"data frame annual averages bay segment","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_transectave.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Get annual averages of seagrass frequency occurrence by bay segments and year — anlz_transectave","text":"focat column returned results shows color category based arbitrary breaks frequency occurrence estimates (foest) 25, 50, 75 percent. necessarily translate ecological breakpoints.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_transectave.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get annual averages of seagrass frequency occurrence by bay segments and year — anlz_transectave","text":"","code":"if (FALSE) { transect <- read_transect() } transectocc <- anlz_transectocc(transect) anlz_transectave(transectocc) #> # A tibble: 156 × 4 #> # Groups: bay_segment [6] #> bay_segment yr foest focat #> #> 1 Tampa Bay 1998 58.0 #E9C318 #> 2 OTB 1998 65.5 #E9C318 #> 3 HB 1998 15.0 #CC3231 #> 4 MTB 1998 53.7 #E9C318 #> 5 LTB 1998 80.8 #2DC938 #> 6 BCB 1998 81.0 #2DC938 #> 7 Tampa Bay 1999 51.5 #E9C318 #> 8 OTB 1999 64.7 #E9C318 #> 9 HB 1999 10.1 #CC3231 #> 10 MTB 1999 51.8 #E9C318 #> # ℹ 146 more rows"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_transectavespp.html","id":null,"dir":"Reference","previous_headings":"","what":"Get annual averages of seagrass frequency occurrence by bay segments, year, and species — anlz_transectavespp","title":"Get annual averages of seagrass frequency occurrence by bay segments, year, and species — anlz_transectavespp","text":"Get annual averages seagrass frequency occurrence bay segments, year, species","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_transectavespp.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get annual averages of seagrass frequency occurrence by bay segments, year, and species — anlz_transectavespp","text":"","code":"anlz_transectavespp( transectocc, bay_segment = c(\"OTB\", \"HB\", \"MTB\", \"LTB\", \"BCB\"), yrrng = c(1998, 2023), species = c(\"Halodule\", \"Syringodium\", \"Thalassia\", \"Ruppia\", \"Halophila\", \"Caulerpa\", \"Dapis\"), total = TRUE, by_seg = FALSE )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_transectavespp.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get annual averages of seagrass frequency occurrence by bay segments, year, and species — anlz_transectavespp","text":"transectocc data frame returned anlz_transectocc bay_segment chr string bay segment, one many \"OTB\", \"HB\", \"MTB\", \"LTB\", \"BCB\" yrrng numeric indicating year ranges evaluate species chr string species summarize, one many \"Halodule\", \"Syringodium\", \"Thalassia\", \"Ruppia\", \"Halophila\", \"Caulerpa\", \"Dapis\" total logical indicating total frequency occurrence species also returned by_seg logical indicating separate results bay segments retained","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_transectavespp.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get annual averages of seagrass frequency occurrence by bay segments, year, and species — anlz_transectavespp","text":"data frame annual averages bay segment","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_transectavespp.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Get annual averages of seagrass frequency occurrence by bay segments, year, and species — anlz_transectavespp","text":"Frequency occurrence estimates averaged across segments bay_segment by_seg = F, .e., separate results location returned. Results retained bay segment by_seg = T. Also note totals across species (total = T) returned by_seg = T.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_transectavespp.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get annual averages of seagrass frequency occurrence by bay segments, year, and species — anlz_transectavespp","text":"","code":"if (FALSE) { transect <- read_transect() } transectocc <- anlz_transectocc(transect) anlz_transectavespp(transectocc) #> # A tibble: 208 × 3 #> yr Savspecies foest #> #> 1 1998 Caulerpa 0.0166 #> 2 1998 Dapis 0 #> 3 1998 Halodule 0.361 #> 4 1998 Halophila 0 #> 5 1998 Ruppia 0.0112 #> 6 1998 Syringodium 0.0451 #> 7 1998 Thalassia 0.254 #> 8 1998 total 0.580 #> 9 1999 Caulerpa 0.0277 #> 10 1999 Dapis 0 #> # ℹ 198 more rows"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_transectocc.html","id":null,"dir":"Reference","previous_headings":"","what":"Get seagrass average abundance and occurrence across transects — anlz_transectocc","title":"Get seagrass average abundance and occurrence across transects — anlz_transectocc","text":"Get seagrass average abundance occurrence across transects","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_transectocc.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get seagrass average abundance and occurrence across transects — anlz_transectocc","text":"","code":"anlz_transectocc(transect)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_transectocc.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get seagrass average abundance and occurrence across transects — anlz_transectocc","text":"transect data frame returned read_transect","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_transectocc.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get seagrass average abundance and occurrence across transects — anlz_transectocc","text":"data frame abundance frequency occurrence estimates aggregated species, transect, date. nsites column total number placements sampled along transect particular date.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_transectocc.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Get seagrass average abundance and occurrence across transects — anlz_transectocc","text":"Abundance frequency occurrence estimated Sherwood et al. 2017, equations 1 2. short, frequency occurrence estimated number instances species observed along transect divided number placements along transect average abundance estimated sum species-specific Braun-Blanquet scores divided number placements along transect. estimates obtained seagrass species including Caulerpa (attached macroalgae) Dapis (cyanobacteria), whereas attached drift algae species aggregated. Drift attached macroalgae cyanobacteria (Dapis) estimates may accurate prior 2021.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_transectocc.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Get seagrass average abundance and occurrence across transects — anlz_transectocc","text":"Sherwood, E.T., Greening, H.S., Johansson, J.O.R., Kaufman, K., Raulerson, G.E. 2017. Tampa Bay (Florida, USA): Documenting seagrass recovery since 1980's reviewing benefits. Southeastern Geographer. 57(3):294-319.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_transectocc.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get seagrass average abundance and occurrence across transects — anlz_transectocc","text":"","code":"if (FALSE) { transect <- read_transect() } anlz_transectocc(transect) #> # A tibble: 37,625 × 6 #> # Groups: Date, Transect [1,505] #> Date Transect Savspecies nsites foest bbest #> #> 1 1997-10-11 S2T3 \"AA\" 41 0 0 #> 2 1997-10-11 S2T3 \"Caulerpa\" 41 0 0 #> 3 1997-10-11 S2T3 \"DA\" 41 0 0 #> 4 1997-10-11 S2T3 \"DB: Dictyota\\r\\n\" 41 0 0 #> 5 1997-10-11 S2T3 \"DB: Drift Brown\\r\\n\" 41 0 0 #> 6 1997-10-11 S2T3 \"DG: Chaetomorpha\\r\\n\" 41 0 0 #> 7 1997-10-11 S2T3 \"DG: Drift Green\" 41 0 0 #> 8 1997-10-11 S2T3 \"DG: Ulva\" 41 0 0 #> 9 1997-10-11 S2T3 \"DG: Ulva fasciata\\r\\n\" 41 0 0 #> 10 1997-10-11 S2T3 \"DR: Acanthophora\" 41 0 0 #> # ℹ 37,615 more rows"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_yrattain.html","id":null,"dir":"Reference","previous_headings":"","what":"Get attainment categories for a chosen year — anlz_yrattain","title":"Get attainment categories for a chosen year — anlz_yrattain","text":"Get attainment categories chosen year","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_yrattain.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get attainment categories for a chosen year — anlz_yrattain","text":"","code":"anlz_yrattain(epcdata, yrsel, partialyr = FALSE)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_yrattain.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get attainment categories for a chosen year — anlz_yrattain","text":"epcdata data frame epc data returned read_importwq yrsel numeric indicating chosen year partialyr logical indicating incomplete annual data recent year approximated five year monthly averages parameter","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_yrattain.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get attainment categories for a chosen year — anlz_yrattain","text":"data.frame chosen year bay segments showing bay segment averages chloropyll concentration, light attenuations, segment targets, attainment categories.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_yrattain.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get attainment categories for a chosen year — anlz_yrattain","text":"","code":"# defaults to current year anlz_yrattain(epcdata, yrsel = 2023) #> # A tibble: 4 × 6 #> bay_segment chla_val chla_target la_val la_target outcome #> #> 1 OTB 6.21 8.5 0.734 0.83 green #> 2 HB 6.93 13.2 0.791 1.58 green #> 3 MTB 3.68 7.4 0.472 0.83 green #> 4 LTB 2.60 4.6 0.536 0.63 green"},{"path":"https://tbep-tech.github.io/tbeptools/reference/benthicdata.html","id":null,"dir":"Reference","previous_headings":"","what":"Benthic data for the Tampa Bay Benthic Index current as of 03132024 — benthicdata","title":"Benthic data for the Tampa Bay Benthic Index current as of 03132024 — benthicdata","text":"Benthic data Tampa Bay Benthic Index current 03132024","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/benthicdata.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Benthic data for the Tampa Bay Benthic Index current as of 03132024 — benthicdata","text":"","code":"benthicdata"},{"path":"https://tbep-tech.github.io/tbeptools/reference/benthicdata.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Benthic data for the Tampa Bay Benthic Index current as of 03132024 — benthicdata","text":"nested tibble 3 rows 2 variables: name chr identifying dataset stations, fieldsamples, taxacounts value list dataframes dataset","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/benthicdata.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Benthic data for the Tampa Bay Benthic Index current as of 03132024 — benthicdata","text":"Index corresponding list element value column view dataset. example, stations data first row can viewed benthicdata$value[[1]].","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/benthicdata.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Benthic data for the Tampa Bay Benthic Index current as of 03132024 — benthicdata","text":"","code":"if (FALSE) { # location to download data path <- '~/Desktop/benthic.zip' # load and assign to object benthicdata <- read_importbenthic(path, download_latest = TRUE, remove = TRUE) save(benthicdata, file = 'data/benthicdata.RData', compress = 'xz') }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/bsmap.html","id":null,"dir":"Reference","previous_headings":"","what":"Terrain basemap — bsmap","title":"Terrain basemap — bsmap","text":"Terrain basemap","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/bsmap.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Terrain basemap — bsmap","text":"","code":"bsmap"},{"path":"https://tbep-tech.github.io/tbeptools/reference/bsmap.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Terrain basemap — bsmap","text":"ggmap object","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/epcdata.html","id":null,"dir":"Reference","previous_headings":"","what":"All bay data as of 20240201 — epcdata","title":"All bay data as of 20240201 — epcdata","text":"bay data 20240201","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/epcdata.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"All bay data as of 20240201 — epcdata","text":"","code":"epcdata"},{"path":"https://tbep-tech.github.io/tbeptools/reference/epcdata.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"All bay data as of 20240201 — epcdata","text":"data frame 27961 rows 26 variables: bay_segment chr epchc_station num SampleTime POSIXct yr num mo num Latitude num Longitude num Total_Depth_m num Sample_Depth_m num tn num tn_q chr sd_m num sd_raw_m num sd_q chr chla num chla_q chr Sal_Top_ppth num Sal_Mid_ppth num Sal_Bottom_ppth num Temp_Water_Top_degC num Temp_Water_Mid_degC num Temp_Water_Bottom_degC num Turbidity_JTU-NTU num Turbidity_Q num Color_345_F45_PCU num Color_345_F45_Q num","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/epcdata.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"All bay data as of 20240201 — epcdata","text":"","code":"if (FALSE) { xlsx <- '~/Desktop/epcdata.xlsx' epcdata <- read_importwq(xlsx, download_latest = TRUE) nrow(epcdata) ncol(epcdata) save(epcdata, file = 'data/epcdata.RData', compress = 'xz') }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/fibdata.html","id":null,"dir":"Reference","previous_headings":"","what":"All Fecal Indicator Bacteria (FIB) data as of 20240320 — fibdata","title":"All Fecal Indicator Bacteria (FIB) data as of 20240320 — fibdata","text":"Fecal Indicator Bacteria (FIB) data 20240320","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/fibdata.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"All Fecal Indicator Bacteria (FIB) data as of 20240320 — fibdata","text":"","code":"fibdata"},{"path":"https://tbep-tech.github.io/tbeptools/reference/fibdata.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"All Fecal Indicator Bacteria (FIB) data as of 20240320 — fibdata","text":"data frame 76502 rows 18 variables: area chr epchc_station num class chr SampleTime POSIXct yr num mo num Latitude num Longitude num Total_Depth_m num Sample_Depth_m num ecoli num ecoli_q chr ecocci num ecocci_q chr fcolif num fcolif_q chr totcol num totcol_q chr","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/fibdata.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"All Fecal Indicator Bacteria (FIB) data as of 20240320 — fibdata","text":"","code":"if (FALSE) { xlsx <- tempfile(fileext = '.xlsx') fibdata <- read_importfib(xlsx, download_latest = TRUE) nrow(fibdata) ncol(fibdata) save(fibdata, file = 'data/fibdata.RData', compress = 'xz') file.remove(xlsx) }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/fimdata.html","id":null,"dir":"Reference","previous_headings":"","what":"FIM data for Tampa Bay Nekton Index current as of 08232023 — fimdata","title":"FIM data for Tampa Bay Nekton Index current as of 08232023 — fimdata","text":"FIM data Tampa Bay Nekton Index current 08232023","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/fimdata.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"FIM data for Tampa Bay Nekton Index current as of 08232023 — fimdata","text":"","code":"fimdata"},{"path":"https://tbep-tech.github.io/tbeptools/reference/fimdata.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"FIM data for Tampa Bay Nekton Index current as of 08232023 — fimdata","text":"data frame 49874 rows 19 variables: Reference chr Sampling_Date Date Latitude num Longitude num Zone chr Grid int NODCCODE chr Year num Month num Total_N num ScientificName chr Include_TB_Index chr Hab_Cat chr Est_Cat chr Est_Use chr Feeding_Cat chr Feeding_Guild chr Selected_Taxa chr bay_segment chr","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/fimdata.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"FIM data for Tampa Bay Nekton Index current as of 08232023 — fimdata","text":"","code":"if (FALSE) { csv <- '~/Desktop/fimdata.csv' fimdata <- read_importfim(csv, download_latest = TRUE) save(fimdata, file = 'data/fimdata.RData', compress = 'xz') }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/fimstations.html","id":null,"dir":"Reference","previous_headings":"","what":"Spatial data object of FIM stations including Tampa Bay segments — fimstations","title":"Spatial data object of FIM stations including Tampa Bay segments — fimstations","text":"Spatial data object FIM stations including Tampa Bay segments","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/fimstations.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Spatial data object of FIM stations including Tampa Bay segments — fimstations","text":"","code":"fimstations"},{"path":"https://tbep-tech.github.io/tbeptools/reference/fimstations.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Spatial data object of FIM stations including Tampa Bay segments — fimstations","text":"simple features sf object (POINT) 7450 features 2 fields, +proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs Reference num bay_segment chr","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/fimstations.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Spatial data object of FIM stations including Tampa Bay segments — fimstations","text":"","code":"if (FALSE) { # file path csv <- '~/Desktop/fimraw.csv' # load and assign to object fimstations <- read_importfim(csv, download_latest = TRUE, locs = TRUE) save(fimstations, file = 'data/fimstations.RData', compress = 'xz') }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/hmptrgs.html","id":null,"dir":"Reference","previous_headings":"","what":"Habitat Master Plan targets and goals — hmptrgs","title":"Habitat Master Plan targets and goals — hmptrgs","text":"Habitat Master Plan targets goals","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/hmptrgs.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Habitat Master Plan targets and goals — hmptrgs","text":"","code":"hmptrgs"},{"path":"https://tbep-tech.github.io/tbeptools/reference/hmptrgs.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Habitat Master Plan targets and goals — hmptrgs","text":"data frame showing 2030 targets 2050 goals","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/hmptrgs.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Habitat Master Plan targets and goals — hmptrgs","text":"","code":"if (FALSE) { library(dplyr) load(url(\"https://github.com/tbep-tech/hmpu-workflow/raw/master/data/trgs.RData\")) hmptrgs <- trgs %>% rename(Goal2050 = Target2050) save(hmptrgs, file = 'data/hmptrgs.RData', compress = 'xz') }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/iwrraw.html","id":null,"dir":"Reference","previous_headings":"","what":"FDEP IWR run 65 — iwrraw","title":"FDEP IWR run 65 — iwrraw","text":"Florida Department Environmental Protection, Impaired Waters Rule, Run 65","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/iwrraw.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"FDEP IWR run 65 — iwrraw","text":"","code":"iwrraw"},{"path":"https://tbep-tech.github.io/tbeptools/reference/iwrraw.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"FDEP IWR run 65 — iwrraw","text":"data frame 537946 rows 11 variables","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/iwrraw.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"FDEP IWR run 65 — iwrraw","text":"File created using workflow , example old Run 61.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/iwrraw.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"FDEP IWR run 65 — iwrraw","text":"","code":"if (FALSE) { library(dplyr) load(file = '../../02_DOCUMENTS/tidal_creeks/iwrraw_run61.RData') iwrraw <- sf::st_set_geometry(iwrraw, NULL) %>% rename(JEI = jei) save(iwrraw, file = 'data/iwrraw.RData', compress = 'xz') }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/phytodata.html","id":null,"dir":"Reference","previous_headings":"","what":"Phytoplankton data current as of 03202024 — phytodata","title":"Phytoplankton data current as of 03202024 — phytodata","text":"Phytoplankton data current 03202024","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/phytodata.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Phytoplankton data current as of 03202024 — phytodata","text":"","code":"phytodata"},{"path":"https://tbep-tech.github.io/tbeptools/reference/phytodata.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Phytoplankton data current as of 03202024 — phytodata","text":"nested tibble 21143 rows 8 variables: epchc_station chr Date Date name chr units chr count num yrqrt Date yr num mo Ord.factor","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/phytodata.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Phytoplankton data current as of 03202024 — phytodata","text":"","code":"if (FALSE) { # location to download data path <- tempfile(fileext = '.xlsx') # load and assign to object phytodata <- read_importphyto(path, download_latest = TRUE) nrow(phytodata) ncol(phytodata) save(phytodata, file = 'data/phytodata.RData', compress = 'xz') file.remove(path) }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_dlcurrent.html","id":null,"dir":"Reference","previous_headings":"","what":"Download latest file from epchc.org — read_dlcurrent","title":"Download latest file from epchc.org — read_dlcurrent","text":"Download latest file epchc.org","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_dlcurrent.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Download latest file from epchc.org — read_dlcurrent","text":"","code":"read_dlcurrent(locin, download_latest = TRUE, urlin)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_dlcurrent.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Download latest file from epchc.org — read_dlcurrent","text":"locin chr string path local file, overwrite current download_latest logical download latest file regardless local copy urlin url file location","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_dlcurrent.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Download latest file from epchc.org — read_dlcurrent","text":"local copy specified path locin overwritten new file current download_latest = TRUE. function nothing download_latest = FALSE.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_dlcurrent.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Download latest file from epchc.org — read_dlcurrent","text":"local copy checked temporary file downloaded location specified urlin. local file replaced downloaded file MD5 hashes different.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_dlcurrent.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Download latest file from epchc.org — read_dlcurrent","text":"","code":"if (FALSE) { locin <- '~/Desktop/RWMDataSpreadsheet_ThroughCurrentReportMonth.xlsx' urlin1 <- 'https://epcbocc.sharepoint.com/:x:/s/Share/' urlin2 <- 'EYXZ5t16UlFGk1rzIU91VogBa8U37lh8z_Hftf2KJISSHg?e=8r1SUL' urlin <- paste0(urlin1, urlin2, '&download=1') read_dlcurrent(locin = locin, urlin = urlin) }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formbenthic.html","id":null,"dir":"Reference","previous_headings":"","what":"Format benthic data for the Tampa Bay Benthic Index — read_formbenthic","title":"Format benthic data for the Tampa Bay Benthic Index — read_formbenthic","text":"Format benthic data Tampa Bay Benthic Index","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formbenthic.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Format benthic data for the Tampa Bay Benthic Index — read_formbenthic","text":"","code":"read_formbenthic(pathin)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formbenthic.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Format benthic data for the Tampa Bay Benthic Index — read_formbenthic","text":"pathin path unzipped csv files base tables used calculate benthic index","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formbenthic.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Format benthic data for the Tampa Bay Benthic Index — read_formbenthic","text":"nested tibble station, field sample, taxa data","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formbenthic.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Format benthic data for the Tampa Bay Benthic Index — read_formbenthic","text":"Function used internally within read_importbenthic","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formbenthic.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Format benthic data for the Tampa Bay Benthic Index — read_formbenthic","text":"","code":"if (FALSE) { # location to download data path <- '~/Desktop/benthic.zip' # download urlin1 <- 'https://epcbocc.sharepoint.com/:x:/s/Share/' urlin2 <- 'EQUCWBuwCNdGuMREYAyAD1gBKC98mYtCHMWX0FYLrbT4KA?e=nDfnnQ' urlin <- paste0(urlin1, urlin2, '&download=1') read_dlcurrent(path, download_latest = TRUE, urlin = urlin) # unzip tmppth <- tempfile() utils::unzip(path, exdir = tmppth, overwrite = TRUE) # format benthic data read_formbenthic(pathin = tmppth) # remove temporary path unlink(tmppth, recursive = TRUE) }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formfib.html","id":null,"dir":"Reference","previous_headings":"","what":"Format Fecal Indicator Bacteria (FIB) data — read_formfib","title":"Format Fecal Indicator Bacteria (FIB) data — read_formfib","text":"Format Fecal Indicator Bacteria (FIB) data","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formfib.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Format Fecal Indicator Bacteria (FIB) data — read_formfib","text":"","code":"read_formfib(datin, all = FALSE)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formfib.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Format Fecal Indicator Bacteria (FIB) data — read_formfib","text":"datin input data.frame loaded read_importepc logical indicating stations FIB data returned, default FALSE","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formfib.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Format Fecal Indicator Bacteria (FIB) data — read_formfib","text":"lightly formatted data.frame FIB data","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formfib.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Format Fecal Indicator Bacteria (FIB) data — read_formfib","text":"Formats input data read_importepc appropriate FIB results, see details read_importfib information.","code":""},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formfib.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Format Fecal Indicator Bacteria (FIB) data — read_formfib","text":"","code":"if (FALSE) { # file path xlsx <- '~/Desktop/RWMDataSpreadsheet_ThroughCurrentReportMonth.xlsx' # load raw data and assign to object epcall <- read_importepc(xlsx, download_latest = T) # final formatting fibdata <- read_formfib(epcall) }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formfim.html","id":null,"dir":"Reference","previous_headings":"","what":"Format FIM data for the Tampa Bay Nekton Index — read_formfim","title":"Format FIM data for the Tampa Bay Nekton Index — read_formfim","text":"Format FIM data Tampa Bay Nekton Index","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formfim.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Format FIM data for the Tampa Bay Nekton Index — read_formfim","text":"","code":"read_formfim(datin, locs = FALSE)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formfim.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Format FIM data for the Tampa Bay Nekton Index — read_formfim","text":"datin input data.frame loaded read_importfim locs logical indicating spatial features object returned locations FIM sampling station","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formfim.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Format FIM data for the Tampa Bay Nekton Index — read_formfim","text":"formatted data.frame FIM data locs = FALSE, otherwise simple features object locs = TRUE","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formfim.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Format FIM data for the Tampa Bay Nekton Index — read_formfim","text":"Function used internally within read_importfim","code":""},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formfim.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Format FIM data for the Tampa Bay Nekton Index — read_formfim","text":"","code":"if (FALSE) { # file path csv <- '~/Desktop/fimraw.csv' # load and assign to object fimdata <- read_importfim(csv) }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formphyto.html","id":null,"dir":"Reference","previous_headings":"","what":"Format phytoplankton data — read_formphyto","title":"Format phytoplankton data — read_formphyto","text":"Format phytoplankton data","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formphyto.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Format phytoplankton data — read_formphyto","text":"","code":"read_formphyto(datin)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formphyto.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Format phytoplankton data — read_formphyto","text":"datin input data.frame loaded read_importphyto","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formphyto.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Format phytoplankton data — read_formphyto","text":"formatted data.frame phytoplankton count data","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formphyto.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Format phytoplankton data — read_formphyto","text":"seven taxonomic groups summarized. Pyrodinium bahamense, Karenia brevis, Tripos hircus, Pseudo-nitzschia sp., Pseudo-nitzschia pungens retained species level. Bacillariophyta Cyanobacteria retained phylum level. taxa grouped \"\" category.","code":""},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formphyto.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Format phytoplankton data — read_formphyto","text":"","code":"if (FALSE) { # file path xlsx <- '~/Desktop/phyto_data.xlsx' # load and assign to object phytodata <- read_importphyto(xlsx) }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formsediment.html","id":null,"dir":"Reference","previous_headings":"","what":"Format sediment data — read_formsediment","title":"Format sediment data — read_formsediment","text":"Format sediment data","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formsediment.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Format sediment data — read_formsediment","text":"","code":"read_formsediment(pathin)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formsediment.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Format sediment data — read_formsediment","text":"pathin path unzipped csv files sediment result tables","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formsediment.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Format sediment data — read_formsediment","text":"data.frame sediment data Tampa Bay","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formsediment.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Format sediment data — read_formsediment","text":"Function used internally within read_importsediment","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formsediment.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Format sediment data — read_formsediment","text":"","code":"if (FALSE) { # location to download data path <- '~/Desktop/sediment.zip' # download urlin1 <- 'https://epcbocc.sharepoint.com/:x:/s/Share/' urlin2 <- 'Ef9utuKCHD9LliarsOPKCJwB5kxgCObf0tY5x5wX20JQUA?e=DuTseb' urlin <- paste0(urlin1, urlin2, '&download=1') read_dlcurrent(path, download_latest = TRUE, urlin = urlin) # unzip tmppth <- tempfile() utils::unzip(path, exdir = tmppth, overwrite = TRUE) # format sediment data read_formsediment(pathin = tmppth) # remove temporary path unlink(tmppth, recursive = TRUE) }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formtransect.html","id":null,"dir":"Reference","previous_headings":"","what":"Format seagrass transect data from Water Atlas — read_formtransect","title":"Format seagrass transect data from Water Atlas — read_formtransect","text":"Format seagrass transect data Water Atlas","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formtransect.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Format seagrass transect data from Water Atlas — read_formtransect","text":"","code":"read_formtransect(jsn, training = FALSE, raw = FALSE)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formtransect.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Format seagrass transect data from Water Atlas — read_formtransect","text":"jsn data frame returned fromJSON training logical input transect training data complete database raw logical indicating raw, unformatted data returned, see details","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formtransect.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Format seagrass transect data from Water Atlas — read_formtransect","text":"data frame long format","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formtransect.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Format seagrass transect data from Water Atlas — read_formtransect","text":"Shoot density reported number shoots per square meter corrected quadrat size entered raw data. Shoot density blade height (cm) based averages across random observations transect point entered separately data form. Abundance reported numeric value 0 - 5 Braun-Blanquet coverage estimates. raw = TRUE, unformatted data returned. default use formatting allows raw data used downstream functions. raw data may extra information may use outside plotting functions package.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formtransect.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Format seagrass transect data from Water Atlas — read_formtransect","text":"","code":"library(jsonlite) if (FALSE) { # all transect data url <- 'http://dev.seagrass.wateratlas.usf.edu/api/assessments/all__use-with-care' jsn <- fromJSON(url) trndat <- read_formtransect(jsn) } # training transect data url <- 'http://dev.seagrass.wateratlas.usf.edu/api/assessments/training' jsn <- fromJSON(url) trndat <- read_formtransect(jsn, training = TRUE)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formwq.html","id":null,"dir":"Reference","previous_headings":"","what":"Format water quality data — read_formwq","title":"Format water quality data — read_formwq","text":"Format water quality data","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formwq.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Format water quality data — read_formwq","text":"","code":"read_formwq(datin, all = FALSE)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formwq.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Format water quality data — read_formwq","text":"datin input data.frame loaded read_importepc logical indicating water quality parameters returned, see details","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formwq.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Format water quality data — read_formwq","text":"lightly formatted data.frame chloropyll secchi observations","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formwq.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Format water quality data — read_formwq","text":"Secchi data VOB depths secchis < 0.5 ft bottom assigned NA, function used internally within read_importwq","code":""},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formwq.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Format water quality data — read_formwq","text":"","code":"if (FALSE) { # file path xlsx <- '~/Desktop/RWMDataSpreadsheet_ThroughCurrentReportMonth.xlsx' # load raw data and assign to object epcall <- read_importepc(xlsx, download_latest = T) # final formatting epcdata <- read_formwq(epcall) }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formwqp.html","id":null,"dir":"Reference","previous_headings":"","what":"Format data and station metadata from the Water Quality Portal — read_formwqp","title":"Format data and station metadata from the Water Quality Portal — read_formwqp","text":"Format data station metadata Water Quality Portal","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formwqp.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Format data and station metadata from the Water Quality Portal — read_formwqp","text":"","code":"read_formwqp(res, sta, org, type, trace = F)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formwqp.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Format data and station metadata from the Water Quality Portal — read_formwqp","text":"res data frame containing results obtained API sta data frame containing station metadata obtained API org chr string indicating organization identifier type chr string indicating data type download, one \"wq\" \"fib\" trace Logical indicating whether display progress messages, default FALSE","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formwqp.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Format data and station metadata from the Water Quality Portal — read_formwqp","text":"data frame containing formatted water quality station metadata","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formwqp.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Format data and station metadata from the Water Quality Portal — read_formwqp","text":"function used read_importwqp combine, format, process data (res) station metadata (sta) obtained Water Quality Portal selected county data type. resulting data frame includes date, time, station identifier, latitude, longitude, variable name, value, unit, quality flag.","code":""},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formwqp.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Format data and station metadata from the Water Quality Portal — read_formwqp","text":"","code":"if (FALSE) { url <- list( Result = \"https://www.waterqualitydata.us/data/Result/search?mimeType=csv&zip=no\", Station = \"https://www.waterqualitydata.us/data/Station/search?mimeType=csv&zip=no\" ) headers <- c( \"Content-Type\" = \"application/json\", \"Accept\" = \"application/zip\" ) body <- list( organization = c(\"21FLMANA_WQX\"), sampleMedia = c(\"Water\"), characteristicType = c(\"Information\", \"Nutrient\", \"Biological, Algae, Phytoplankton, Photosynthetic Pigments\"), providers = c(\"STORET\"), siteType = c(\"Estuary\") ) res <- url[['Result']] %>% httr::POST(httr::add_headers(headers), body = jsonlite::toJSON(body)) %>% httr::content('text') %>% read.csv(text = .) sta <- url[['Station']] %>% httr::POST(httr::add_headers(headers), body = jsonlite::toJSON(body)) %>% httr::content('text') %>% read.csv(text = .) # combine and format read_formwqp(res, sta, '21FLMANA_WQX', type = 'wq') }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importbenthic.html","id":null,"dir":"Reference","previous_headings":"","what":"Download and import benthic data for Tampa Bay — read_importbenthic","title":"Download and import benthic data for Tampa Bay — read_importbenthic","text":"Download import benthic data Tampa Bay","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importbenthic.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Download and import benthic data for Tampa Bay — read_importbenthic","text":"","code":"read_importbenthic(path, download_latest = FALSE, remove = FALSE)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importbenthic.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Download and import benthic data for Tampa Bay — read_importbenthic","text":"path chr string local path zipped folder downloaded, must include .zip extension download_latest logical download latest recent dataset available remove logical downloaded folder removed unzipping","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importbenthic.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Download and import benthic data for Tampa Bay — read_importbenthic","text":"nested tibble station, taxa, field sample data.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importbenthic.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Download and import benthic data for Tampa Bay — read_importbenthic","text":"function downloads unzips folder base tables used calculate benthic index https://epcbocc.sharepoint.com/:u:/s/Share/EQUCWBuwCNdGuMREYAyAD1gBKC98mYtCHMWX0FYLrbT4KA?e=nDfnnQ&download=1 (viewable https://epcbocc.sharepoint.com/:f:/s/Share/EtOJfziTTa9FliL1oROb9OsBRZU-nO60fu_0NRC162hHjQ?e=4gUXgJ). Index corresponding list element value column view dataset. example, stations data first row can viewed benthicdata$value[[1]].","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importbenthic.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Download and import benthic data for Tampa Bay — read_importbenthic","text":"","code":"if (FALSE) { # location to download data path <- '~/Desktop/benthic.zip' # load and assign to object benthicdata <- read_importbenthic(path, download_latest = TRUE) }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importepc.html","id":null,"dir":"Reference","previous_headings":"","what":"Download and/or import local water quality file for internal use — read_importepc","title":"Download and/or import local water quality file for internal use — read_importepc","text":"Download /import local water quality file internal use","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importepc.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Download and/or import local water quality file for internal use — read_importepc","text":"","code":"read_importepc(xlsx, download_latest = FALSE, na = c(\"\", \"NULL\"))"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importepc.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Download and/or import local water quality file for internal use — read_importepc","text":"xlsx chr string path local excel file, overwrite current download_latest logical passed read_dlcurrent download raw data compare existing xlsx available na chr vector strings interpret NA, passed read_xlsx","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importepc.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Download and/or import local water quality file for internal use — read_importepc","text":"unformatted data.frame EPC","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importepc.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Download and/or import local water quality file for internal use — read_importepc","text":"Loads \"RWMDataSpreadsheet\" worksheet file located xlsx. file downloaded https://epcbocc.sharepoint.com/:x:/s/Share/EYXZ5t16UlFGk1rzIU91VogBa8U37lh8z_Hftf2KJISSHg?e=8r1SUL&download=1. files can viewed https://epcbocc.sharepoint.com/:f:/s/Share/EiypSSYdsEFCi84Sv_6-t7kBUYaXiIqN0B1n2w57Z_V3kQ?e=NdZQcU. function used internally read_importwq read_importfib use source data Environmental Protection Commission Hillsborough County.","code":""},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importepc.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Download and/or import local water quality file for internal use — read_importepc","text":"","code":"if (FALSE) { # file path xlsx <- '~/Desktop/RWMDataSpreadsheet_ThroughCurrentReportMonth.xlsx' # load and assign to object epcall <- read_importepc(xlsx, download_latest = T) }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importfib.html","id":null,"dir":"Reference","previous_headings":"","what":"Load local water quality file for Fecal Indicator Bacteria (FIB) — read_importfib","title":"Load local water quality file for Fecal Indicator Bacteria (FIB) — read_importfib","text":"Load local water quality file Fecal Indicator Bacteria (FIB)","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importfib.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Load local water quality file for Fecal Indicator Bacteria (FIB) — read_importfib","text":"","code":"read_importfib(xlsx, download_latest = FALSE, na = c(\"\", \"NULL\"), all = TRUE)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importfib.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Load local water quality file for Fecal Indicator Bacteria (FIB) — read_importfib","text":"xlsx chr string path local excel file, overwrite current download_latest logical passed read_dlcurrent download raw data compare existing xlsx available na chr vector strings interpret NA, passed read_xlsx logical indicating stations FIB data returned, default TRUE, see details","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importfib.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Load local water quality file for Fecal Indicator Bacteria (FIB) — read_importfib","text":"data.frame formatted FIB data.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importfib.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Load local water quality file for Fecal Indicator Bacteria (FIB) — read_importfib","text":"Loads \"RWMDataSpreadsheet\" worksheet file located xlsx. file downloaded https://epcbocc.sharepoint.com/:x:/s/Share/EYXZ5t16UlFGk1rzIU91VogBa8U37lh8z_Hftf2KJISSHg?e=8r1SUL&download=1. files can viewed https://epcbocc.sharepoint.com/:f:/s/Share/EiypSSYdsEFCi84Sv_6-t7kBUYaXiIqN0B1n2w57Z_V3kQ?e=NdZQcU. Returns FIB data including E. coli, Enterococcus, Fecal Coliform, Total Coliform concentrations waterbody class (freshwater 1 3F, marine 2 3M) stations sample dates, function used internally within read_importfib Values returned E. coli (ecoli), Enterococcus (ecocci), Fecal Coliform (fcolif), Total Coliform (totcol). Values shown # colonies per 100 mL water (#/100mL). Qualifier columns also returned _q suffix. Qualifier codes can interpreted source spreadsheet. Concentrations noted < > raw data reported , numeric value shown. Samples notation can determined qualifier columns. = FALSE, stations AreaName source data Hillsborough River, Hillsborough River Tributary, Alafia River, Alafia River Tributary, Lake Thonotosassa, Lake Thonotosassa Tributary, Lake Roberta.","code":""},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importfib.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Load local water quality file for Fecal Indicator Bacteria (FIB) — read_importfib","text":"","code":"if (FALSE) { # file path xlsx <- '~/Desktop/RWMDataSpreadsheet_ThroughCurrentReportMonth.xlsx' # load and assign to object fibdata <- read_importfib(xlsx, download_latest = T) }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importfim.html","id":null,"dir":"Reference","previous_headings":"","what":"Load local FIM data for the Tampa Bay Nekton Index — read_importfim","title":"Load local FIM data for the Tampa Bay Nekton Index — read_importfim","text":"Load local FIM data Tampa Bay Nekton Index","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importfim.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Load local FIM data for the Tampa Bay Nekton Index — read_importfim","text":"","code":"read_importfim(csv, download_latest = FALSE, locs = FALSE)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importfim.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Load local FIM data for the Tampa Bay Nekton Index — read_importfim","text":"csv chr string path local csv file, overwrite current download_latest logical passed read_dlcurrent download raw data compare existing csv available locs logical indicating spatial features object returned locations FIM sampling station","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importfim.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Load local FIM data for the Tampa Bay Nekton Index — read_importfim","text":"formatted data.frame FIM data locs = FALSE, otherwise simple features object locs = TRUE","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importfim.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Load local FIM data for the Tampa Bay Nekton Index — read_importfim","text":"Data downloaded ftp://ftp.floridamarine.org/users/fim/tmac/NektonIndex/TampaBay_NektonIndexData.csv.","code":""},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importfim.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Load local FIM data for the Tampa Bay Nekton Index — read_importfim","text":"","code":"if (FALSE) { # file path csv <- '~/Desktop/fimraw.csv' # load and assign to object fimdata <- read_importfim(csv, download_latest = TRUE) }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importphyto.html","id":null,"dir":"Reference","previous_headings":"","what":"Load local phytoplankton cell count file — read_importphyto","title":"Load local phytoplankton cell count file — read_importphyto","text":"Load local phytoplankton cell count file","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importphyto.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Load local phytoplankton cell count file — read_importphyto","text":"","code":"read_importphyto(xlsx, download_latest = FALSE, na = c(\"\", \"NULL\"))"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importphyto.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Load local phytoplankton cell count file — read_importphyto","text":"xlsx chr string path local excel file, overwrite current download_latest logical passed read_dlcurrent download raw data compare existing xlsx available na chr vector strings interpret NA, passed read_xlsx","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importphyto.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Load local phytoplankton cell count file — read_importphyto","text":"data.frame formatted water quality data.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importphyto.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Load local phytoplankton cell count file — read_importphyto","text":"Phytoplankton cell count data downloaded https://epcbocc.sharepoint.com/:x:/s/Share/ETAfRQ5drmRHntDd1O8s3FQB180Fumed4nQ99w-OIVDxrA?e=eSmtxD&download=1","code":""},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importphyto.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Load local phytoplankton cell count file — read_importphyto","text":"","code":"if (FALSE) { # file path xlsx <- '~/Desktop/phyto_data.xlsx' # load and assign to object phytodata <- read_importphyto(xlsx, download_latest = T) }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importsediment.html","id":null,"dir":"Reference","previous_headings":"","what":"Download and import sediment data for Tampa Bay — read_importsediment","title":"Download and import sediment data for Tampa Bay — read_importsediment","text":"Download import sediment data Tampa Bay","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importsediment.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Download and import sediment data for Tampa Bay — read_importsediment","text":"","code":"read_importsediment(path, download_latest = FALSE, remove = FALSE)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importsediment.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Download and import sediment data for Tampa Bay — read_importsediment","text":"path chr string local path zipped folder downloaded, must include .zip extension download_latest logical download latest recent dataset available remove logical downloaded folder removed unzipping","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importsediment.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Download and import sediment data for Tampa Bay — read_importsediment","text":"data.frame sediment data Tampa Bay","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importsediment.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Download and import sediment data for Tampa Bay — read_importsediment","text":"function downloads unzips folder results tables https://epcbocc.sharepoint.com/:u:/s/Share/Ef9utuKCHD9LliarsOPKCJwB5kxgCObf0tY5x5wX20JQUA?e=DuTseb&download=1 (viewable https://epcbocc.sharepoint.com/:f:/s/Share/EtOJfziTTa9FliL1oROb9OsBRZU-nO60fu_0NRC162hHjQ?e=4gUXgJ). row entries columns \"BetweenTELPEL\" \"ExceedsPEL\" rows \"Qualifier\" column \"U\" \"T\" (detection, detected) assigned NA, regardless entry source data.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importsediment.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Download and import sediment data for Tampa Bay — read_importsediment","text":"","code":"if (FALSE) { # location to download data path <- '~/Desktop/sediment.zip' # load and assign to object sedimentdata <- read_importsediment(path, download_latest = TRUE) }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importwq.html","id":null,"dir":"Reference","previous_headings":"","what":"Load local water quality file — read_importwq","title":"Load local water quality file — read_importwq","text":"Load local water quality file","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importwq.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Load local water quality file — read_importwq","text":"","code":"read_importwq(xlsx, download_latest = FALSE, na = c(\"\", \"NULL\"), all = FALSE)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importwq.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Load local water quality file — read_importwq","text":"xlsx chr string path local excel file, overwrite current download_latest logical passed read_dlcurrent download raw data compare existing xlsx available na chr vector strings interpret NA, passed read_xlsx logical indicating water quality parameters returned, see details","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importwq.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Load local water quality file — read_importwq","text":"data.frame formatted water quality data.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importwq.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Load local water quality file — read_importwq","text":"Loads \"RWMDataSpreadsheet\" worksheet file located xlsx. file downloaded https://epcbocc.sharepoint.com/:x:/s/Share/EYXZ5t16UlFGk1rzIU91VogBa8U37lh8z_Hftf2KJISSHg?e=8r1SUL&download=1. files can viewed https://epcbocc.sharepoint.com/:f:/s/Share/EiypSSYdsEFCi84Sv_6-t7kBUYaXiIqN0B1n2w57Z_V3kQ?e=NdZQcU. Water quality parameters returned default total nitrogen (tn), Secchi depth (sd), chlorophyll-(chla), salinity (top, mid, bottom depths, Sal_ prefix), water temperature (top, mid, bottom depths, Temp_Water_ prefix), turbidity (Turbidity_JTU-NTU), water color (Color_345_F45). Additional qualifier columns include _Q suffix also returned, excluding salinity water temperature. water quality parameters qualifiers can returned setting = T.","code":""},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importwq.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Load local water quality file — read_importwq","text":"","code":"if (FALSE) { # file path xlsx <- '~/Desktop/RWMDataSpreadsheet_ThroughCurrentReportMonth.xlsx' # load and assign to object epcdata <- read_importwq(xlsx, download_latest = T) # get all water quality parameters epcdataall <- read_importwq(xlsx, download_latest = T, all = T) }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importwqp.html","id":null,"dir":"Reference","previous_headings":"","what":"Import data from the Water Quality Portal — read_importwqp","title":"Import data from the Water Quality Portal — read_importwqp","text":"Import data Water Quality Portal","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importwqp.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Import data from the Water Quality Portal — read_importwqp","text":"","code":"read_importwqp(org, type, trace = F)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importwqp.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Import data from the Water Quality Portal — read_importwqp","text":"org chr string indicating organization identifier, see details type chr string indicating data type download, one \"wq\" \"fib\" trace logical indicating whether display progress messages, default FALSE","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importwqp.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Import data from the Water Quality Portal — read_importwqp","text":"data frame containing imported data selected county","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importwqp.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Import data from the Water Quality Portal — read_importwqp","text":"function retrieves data Water Quality Portal API (https://www.waterqualitydata.us/) selected counties around Tampa Bay watershed. type data returned defined type argument either \"wq\" \"fib\" water quality Fecal Indicator Bacteria data, respectively. org argument retrieves data specific organization. Valid entries org include \"21FLCOSP_WQX\" (City St. Petersburg), \"21FLDOH_WQX\" (Florida Department Health), \"21FLHILL_WQX\" (Hillsborough County), \"21FLMANA_WQX\" (Manatee County), \"21FLPASC_WQX\" (Pasco County), \"21FLPDEM_WQX\" (Pinellas County), \"21FLPOLK_WQX\" (Polk County), \"21FLTPA_WQX\" (Florida Department Environmental Protection, Southwest District). naming convention follows Organization ID Water Quality Portal. function fetches results station metadata, combines formats using read_formwqp function, returns processed data data frame. Parameters specific type argument.","code":""},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importwqp.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Import data from the Water Quality Portal — read_importwqp","text":"","code":"if (FALSE) { # get Manatee County water quality data mancodata <- read_importwqp(org = '21FLMANA_WQX', type = 'wq', trace = T) # get Pinellas County FIB data pincodata <- read_importwqp(org = '21FLPDEM_WQX', type = 'fib', trace = T) }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_transect.html","id":null,"dir":"Reference","previous_headings":"","what":"Import JSON seagrass transect data from Water Atlas — read_transect","title":"Import JSON seagrass transect data from Water Atlas — read_transect","text":"Import JSON seagrass transect data Water Atlas","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_transect.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Import JSON seagrass transect data from Water Atlas — read_transect","text":"","code":"read_transect(training = FALSE, raw = FALSE)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_transect.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Import JSON seagrass transect data from Water Atlas — read_transect","text":"training logical training data imported complete database raw logical indicating raw, unformatted data returned, see details","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_transect.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Import JSON seagrass transect data from Water Atlas — read_transect","text":"data frame","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_transect.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Import JSON seagrass transect data from Water Atlas — read_transect","text":"function imports JSON file USF Water Atlas. training = TRUE, dataset TBEP training survey imported http://dev.seagrass.wateratlas.usf.edu/api/assessments/training. training = FALSE, entire transect survey database imported http://dev.seagrass.wateratlas.usf.edu/api/assessments/all__use--care. Abundance reported numeric value 0 -5 Braun-Blanquet coverage estimates, blade length cm, short shoot density number shoots per square meter. short density corrected quadrat size included raw data. raw = TRUE, unformatted data returned. default use formatting allows raw data used downstream functions. raw data may extra information may use outside plotting functions package.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_transect.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Import JSON seagrass transect data from Water Atlas — read_transect","text":"","code":"if (FALSE) { # get training data transect <- read_transect(training = TRUE) # import all transect data transect <- read_transect() }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/seagrass.html","id":null,"dir":"Reference","previous_headings":"","what":"Seagrass coverage by year — seagrass","title":"Seagrass coverage by year — seagrass","text":"Seagrass coverage year","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/seagrass.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Seagrass coverage by year — seagrass","text":"","code":"seagrass"},{"path":"https://tbep-tech.github.io/tbeptools/reference/seagrass.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Seagrass coverage by year — seagrass","text":"data frame used create flagship seagrass coverage graphic: Year int Acres num Hectares num","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/seagrass.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Seagrass coverage by year — seagrass","text":"Original data Southwest Florida Water Management District available online . Totals Tampa Bay.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/seagrass.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Seagrass coverage by year — seagrass","text":"","code":"if (FALSE) { seagrass <- structure(list( Year = c(1950L, 1982L, 1988L, 1990L, 1992L, 1994L, 1996L, 1999L, 2001L, 2004L, 2006L, 2008L, 2010L, 2012L, 2014L, 2016L, 2018L, 2020L, 2022L), Acres = c(40420, 21650, 23285, 25226, 25753, 26518, 26916, 24841, 26078, 27021, 28299, 29647, 32897, 34642, 40294.71, 41655.16, 40651.55, 34298, 30137), Hectares = c(16357.39, 8761.44, 9423.11, 10208.6, 10421.87, 10731.45, 10892.52, 10052.8, 10553.39, 10935.01, 11452.2, 11997.72, 13312.94, 14019.27, 16306.69, 16857.25, 16451.1, 13880, 12196) ), class = \"data.frame\", row.names = c(NA, -19L)) save(seagrass, file = 'data/seagrass.RData', compress = 'xz') }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/sedimentdata.html","id":null,"dir":"Reference","previous_headings":"","what":"Sediment data for the Tampa Bay current as of 12142023 — sedimentdata","title":"Sediment data for the Tampa Bay current as of 12142023 — sedimentdata","text":"Sediment data Tampa Bay current 12142023","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/sedimentdata.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Sediment data for the Tampa Bay current as of 12142023 — sedimentdata","text":"","code":"sedimentdata"},{"path":"https://tbep-tech.github.io/tbeptools/reference/sedimentdata.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Sediment data for the Tampa Bay current as of 12142023 — sedimentdata","text":"data.frame 216627 rows 24 variables: ProgramId int ProgramName chr FundingProject chr yr int AreaAbbr chr StationID int StationNumber chr Latitude num Longitude num Replicate chr SedResultsType chr Parameter chr ValueAdjusted num Units chr Qualifier chr MDLnum num PQLnum num TEL num PEL num BetweenTELPEL chr ExceedsPEL chr PreparationDate chr AnalysisTimeMerge chr PELGrade Factor","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/sedimentdata.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Sediment data for the Tampa Bay current as of 12142023 — sedimentdata","text":"","code":"if (FALSE) { # location to download data path <- '~/Desktop/sediment.zip' # load and assign to object sedimentdata <- read_importsediment(path, download_latest = TRUE, remove = TRUE) save(sedimentdata, file = 'data/sedimentdata.RData', compress = 'xz') }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/sgmanagement.html","id":null,"dir":"Reference","previous_headings":"","what":"Seagrass management areas for Tampa Bay — sgmanagement","title":"Seagrass management areas for Tampa Bay — sgmanagement","text":"Seagrass management areas Tampa Bay","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/sgmanagement.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Seagrass management areas for Tampa Bay — sgmanagement","text":"","code":"sgmanagement"},{"path":"https://tbep-tech.github.io/tbeptools/reference/sgmanagement.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Seagrass management areas for Tampa Bay — sgmanagement","text":"simple features sf object (MULTIPOLYGON) 30 features 1 field, +proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs areas int","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/sgmanagement.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Seagrass management areas for Tampa Bay — sgmanagement","text":"polygons seagrass management areas Tampa Bay provide finer division areas within major segments (tbseg) relevance locations seagrass beds.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/sgmanagement.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Seagrass management areas for Tampa Bay — sgmanagement","text":"","code":"if (FALSE) { library(sf) library(dplyr) library(tools) # NAD83(HARN) / Florida West (ftUS) # same as sgseg prj <- 2882 # create sf object of boundaries sgmanagement <- st_read( dsn = '~/Desktop/TBEP/GISboundaries/Seagrass_Management_Areas/TBEP_SG_MA_FINAL_Projectfix.shp', drivers = 'ESRI Shapefile' ) %>% select(areas = TBEP_SG_MA) %>% st_zm() %>% st_transform(prj) # save save(sgmanagement, file = 'data/sgmanagement.RData', compress = 'xz') }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/sgseg.html","id":null,"dir":"Reference","previous_headings":"","what":"Seagrass segment reporting boundaries for southwest Florida — sgseg","title":"Seagrass segment reporting boundaries for southwest Florida — sgseg","text":"Seagrass segment reporting boundaries southwest Florida","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/sgseg.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Seagrass segment reporting boundaries for southwest Florida — sgseg","text":"","code":"sgseg"},{"path":"https://tbep-tech.github.io/tbeptools/reference/sgseg.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Seagrass segment reporting boundaries for southwest Florida — sgseg","text":"simple features sf object (POLYGON) 22 features 1 field, +proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs segment chr","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/sgseg.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Seagrass segment reporting boundaries for southwest Florida — sgseg","text":"polygons used Southwest Florida Water Management District summarizing seagrass coverage estimates major coastal estuarine boundaries.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/sgseg.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Seagrass segment reporting boundaries for southwest Florida — sgseg","text":"","code":"if (FALSE) { library(sf) library(dplyr) library(tools) # create sf object of boundaries # make sure projection does not change sgseg <- st_read( dsn = '~/Desktop/TBEP/GISboundaries/Seagrass_Segment_Boundaries/Seagrass_Segment_Boundaries.shp', drivers = 'ESRI Shapefile' ) %>% select(segment = SEAGRASSSE) %>% mutate( segment = tolower(segment), segment = case_when( segment == 'terra ciea bay' ~ 'Terra Ceia Bay', T ~ segment ), segment = toTitleCase(segment) ) # save save(sgseg, file = 'data/sgseg.RData', compress = 'xz') }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_annualassess.html","id":null,"dir":"Reference","previous_headings":"","what":"Create a table for the annual management outcome assessments — show_annualassess","title":"Create a table for the annual management outcome assessments — show_annualassess","text":"Create table annual management outcome assessments chlorophyll-light attenuation bay segment","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_annualassess.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Create a table for the annual management outcome assessments — show_annualassess","text":"","code":"show_annualassess( epcdata, yrsel, partialyr = F, caption = F, family = \"Arial\", txtsz = 12, width = NULL )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_annualassess.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Create a table for the annual management outcome assessments — show_annualassess","text":"epcdata data frame epc data returned read_importwq yrsel numeric indicating chosen year partialyr logical indicating incomplete annual data recent year approximated five year monthly averages parameter caption logical indicating caption added using set_caption family chr string indicating font family text labels txtsz numeric indicating font size width optional numeric value indicating width inches","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_annualassess.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Create a table for the annual management outcome assessments — show_annualassess","text":"flextable object showing segment-averaged chlorophyll-light attenuation selected year, bay segment names colored management outcome used show_matrix.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_annualassess.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Create a table for the annual management outcome assessments — show_annualassess","text":"Segment Chl-(ug/L) Light Penetration (m-1) 2023 target 2023 target OTB 6.2 8.5 0.73 0.83 HB 6.9 13.2 0.79 1.58 MTB 3.7 7.4 0.47 0.83 LTB 2.6 4.6 0.54 0.63 Water quality outcomes 2023. Segment Chl-(ug/L) Light Penetration (m-1) 2023 target 2023 target OTB 6.2 8.5 0.73 0.83 HB 6.9 13.2 0.79 1.58 MTB 3.7 7.4 0.47 0.83 LTB 2.6 4.6 0.54 0.63","code":"show_annualassess(epcdata, yrsel = 2023) .cl-5fd07b38{}.cl-5fca7238{font-family:'Arial';font-size:12pt;font-weight:normal;font-style:normal;text-decoration:none;color:rgba(0, 0, 0, 1.00);background-color:transparent;}.cl-5fca7242{font-family:'Arial';font-size:7.2pt;font-weight:normal;font-style:normal;text-decoration:none;color:rgba(0, 0, 0, 1.00);background-color:transparent;position: relative;bottom:3.6pt;}.cl-5fccf382{margin:0;text-align:left;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);padding-bottom:5pt;padding-top:5pt;padding-left:5pt;padding-right:5pt;line-height: 1;background-color:transparent;}.cl-5fccf38c{margin:0;text-align:center;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);padding-bottom:5pt;padding-top:5pt;padding-left:5pt;padding-right:5pt;line-height: 1;background-color:transparent;}.cl-5fcd0714{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 1.5pt solid rgba(102, 102, 102, 1.00);border-top: 1.5pt solid rgba(102, 102, 102, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-5fcd0715{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 1.5pt solid rgba(102, 102, 102, 1.00);border-top: 1.5pt solid rgba(102, 102, 102, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-5fcd071e{width:0.75in;background-color:rgba(45, 201, 56, 1.00);vertical-align: middle;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-5fcd071f{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-5fcd0720{width:0.75in;background-color:rgba(45, 201, 56, 1.00);vertical-align: middle;border-bottom: 1.5pt solid rgba(102, 102, 102, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-5fcd0728{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 1.5pt solid rgba(102, 102, 102, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}SegmentChl-a (ug/L)Light Penetration (m-1)2023target2023targetOTB6.28.50.730.83HB6.913.20.791.58MTB3.77.40.470.83LTB2.64.60.540.63show_annualassess(epcdata, yrsel = 2023, caption = TRUE) .cl-6004323e{}.cl-5ffdd6d2{font-family:'Arial';font-size:12pt;font-weight:normal;font-style:normal;text-decoration:none;color:rgba(0, 0, 0, 1.00);background-color:transparent;}.cl-5ffdd6dc{font-family:'Arial';font-size:7.2pt;font-weight:normal;font-style:normal;text-decoration:none;color:rgba(0, 0, 0, 1.00);background-color:transparent;position: relative;bottom:3.6pt;}.cl-600122f6{margin:0;text-align:left;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);padding-bottom:5pt;padding-top:5pt;padding-left:5pt;padding-right:5pt;line-height: 1;background-color:transparent;}.cl-6001230a{margin:0;text-align:center;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);padding-bottom:5pt;padding-top:5pt;padding-left:5pt;padding-right:5pt;line-height: 1;background-color:transparent;}.cl-60013426{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 1.5pt solid rgba(102, 102, 102, 1.00);border-top: 1.5pt solid rgba(102, 102, 102, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-60013430{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 1.5pt solid rgba(102, 102, 102, 1.00);border-top: 1.5pt solid rgba(102, 102, 102, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-60013431{width:0.75in;background-color:rgba(45, 201, 56, 1.00);vertical-align: middle;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-60013432{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-60013433{width:0.75in;background-color:rgba(45, 201, 56, 1.00);vertical-align: middle;border-bottom: 1.5pt solid rgba(102, 102, 102, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-6001343a{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 1.5pt solid rgba(102, 102, 102, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-5ffa3fae{font-family:'Arial';font-size:12pt;font-weight:normal;font-style:normal;text-decoration:none;color:rgba(0, 0, 0, 1.00);background-color:transparent;}Water quality outcomes for 2023.SegmentChl-a (ug/L)Light Penetration (m-1)2023target2023targetOTB6.28.50.730.83HB6.913.20.791.58MTB3.77.40.470.83LTB2.64.60.540.63"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_boxplot.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot monthly chlorophyll or light attenuation values for a segment — show_boxplot","title":"Plot monthly chlorophyll or light attenuation values for a segment — show_boxplot","text":"Plot monthly chlorophyll light attenuation values bay segment","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_boxplot.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot monthly chlorophyll or light attenuation values for a segment — show_boxplot","text":"","code":"show_boxplot( epcdata, param = c(\"chla\", \"la\"), yrsel = NULL, yrrng = c(1975, 2023), ptsz = 0.5, bay_segment = c(\"OTB\", \"HB\", \"MTB\", \"LTB\"), trgs = NULL, family = NA, labelexp = TRUE, txtlab = TRUE, partialyr = FALSE )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_boxplot.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot monthly chlorophyll or light attenuation values for a segment — show_boxplot","text":"epcdata data frame epc data returned read_importwq param chr string parameter plot, one \"chla\" chlorophyll \"la\" light attenuation yrsel numeric year emphasize, shown separate red points plot yrrng numeric vector indicating min, max years include ptsz numeric indicating point size observations yrsel bay_segment chr string bay segment, one \"OTB\", \"HB\", \"MTB\", \"LTB\" trgs optional data.frame annual bay segment water quality targets, defaults targets family optional chr string indicating font family text labels labelexp logical indicating y axis target labels plotted expressions, default TRUE txtlab logical indicating text label target value shown plot partialyr logical indicating incomplete annual data recent year approximated five year monthly averages parameter","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_boxplot.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot monthly chlorophyll or light attenuation values for a segment — show_boxplot","text":"ggplot object","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_boxplot.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Plot monthly chlorophyll or light attenuation values for a segment — show_boxplot","text":"Points included yrsel plotted box plots using position_jitter. Use ptsz = -1 suppress. dotted line plot shows large exceedance value.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_boxplot.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot monthly chlorophyll or light attenuation values for a segment — show_boxplot","text":"","code":"show_boxplot(epcdata, bay_segment = 'OTB')"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_compplot.html","id":null,"dir":"Reference","previous_headings":"","what":"Make a bar plot for transect training group comparisons — show_compplot","title":"Make a bar plot for transect training group comparisons — show_compplot","text":"Make bar plot transect training group comparisons","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_compplot.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Make a bar plot for transect training group comparisons — show_compplot","text":"","code":"show_compplot( transect, yr, site, species = c(\"Halodule\", \"Syringodium\", \"Thalassia\", \"Halophila\", \"Ruppia\"), varplo = c(\"Abundance\", \"Blade Length\", \"Short Shoot Density\"), base_size = 18, xtxt = 10, size = 1 )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_compplot.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Make a bar plot for transect training group comparisons — show_compplot","text":"transect data frame returned read_transect yr numeric year training data plot site chr string indicating site results plot species chr string indicating species plot varplo chr string indicating variable plot base_size numeric indicating text scaling size plot xtxt numeric indicating text size x-axis labels size numeric indicating line size","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_compplot.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Make a bar plot for transect training group comparisons — show_compplot","text":"ggplot object","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_compplot.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Make a bar plot for transect training group comparisons — show_compplot","text":"","code":"transect <- read_transect(training = TRUE) show_compplot(transect, yr = 2023, site = '2', species = 'Halodule', varplo = 'Abundance')"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_fibmap.html","id":null,"dir":"Reference","previous_headings":"","what":"Map Fecal Indicator Bacteria (FIB) results by month, year, and location — show_fibmap","title":"Map Fecal Indicator Bacteria (FIB) results by month, year, and location — show_fibmap","text":"Map Fecal Indicator Bacteria (FIB) results month, year, location","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_fibmap.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Map Fecal Indicator Bacteria (FIB) results by month, year, and location — show_fibmap","text":"","code":"show_fibmap(fibdata, yrsel, mosel, areasel = NULL)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_fibmap.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Map Fecal Indicator Bacteria (FIB) results by month, year, and location — show_fibmap","text":"fibdata input FIB data.frame returned read_importfib yrsel optional numeric value filter output years fibdata mosel optional numeric value filter output month fibdata areasel optional character string filter output stations area column fibdata, see details","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_fibmap.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Map Fecal Indicator Bacteria (FIB) results by month, year, and location — show_fibmap","text":"leaflet map selected year, month, area showing stations FIB concentration category","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_fibmap.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Map Fecal Indicator Bacteria (FIB) results by month, year, and location — show_fibmap","text":"Placing mouse cursor item map reveal additional information station.","code":""},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_fibmap.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Map Fecal Indicator Bacteria (FIB) results by month, year, and location — show_fibmap","text":"","code":"# show selected year, month show_fibmap(fibdata, yrsel = 2023, mosel = 8) {\"x\":{\"options\":{\"crs\":{\"crsClass\":\"L.CRS.EPSG3857\",\"code\":null,\"proj4def\":null,\"projectedBounds\":null,\"options\":{}}},\"fitBounds\":[27.53248,-82.783203,28.149932,-82.061156,[]],\"calls\":[{\"method\":\"addProviderTiles\",\"args\":[\"Esri.WorldGrayCanvas\",null,\"Esri.WorldGrayCanvas\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.NatGeoWorldMap\",null,\"Esri.NatGeoWorldMap\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.OceanBasemap\",null,\"Esri.OceanBasemap\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.WorldPhysical\",null,\"Esri.WorldPhysical\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.WorldShadedRelief\",null,\"Esri.WorldShadedRelief\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.WorldTerrain\",null,\"Esri.WorldTerrain\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.WorldImagery\",null,\"Esri.WorldImagery\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.WorldTopoMap\",null,\"Esri.WorldTopoMap\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.DeLorme\",null,\"Esri.DeLorme\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.WorldStreetMap\",null,\"Esri.WorldStreetMap\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri\",null,\"Esri\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addLayersControl\",\"args\":[[\"Esri.WorldGrayCanvas\",\"Esri.NatGeoWorldMap\",\"Esri.OceanBasemap\",\"Esri.WorldPhysical\",\"Esri.WorldShadedRelief\",\"Esri.WorldTerrain\",\"Esri.WorldImagery\",\"Esri.WorldTopoMap\",\"Esri.DeLorme\",\"Esri.WorldStreetMap\",\"Esri\"],[],{\"collapsed\":true,\"autoZIndex\":true,\"position\":\"topleft\"}]},{\"method\":\"addMiniMap\",\"args\":[null,\"Esri.WorldGrayCanvas\",\"bottomleft\",150,150,19,19,-5,false,false,false,true,false,true,{\"color\":\"#ff7800\",\"weight\":1,\"clickable\":false},{\"color\":\"#000000\",\"weight\":1,\"clickable\":false,\"opacity\":0,\"fillOpacity\":0},{\"hideText\":\"Hide MiniMap\",\"showText\":\"Show 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\",\"data:image/png;base64,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\",\"data:image/png;base64,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\",\"data:image/png;base64,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\",\"data:image/png;base64,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\",\"data:image/png;base64,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\",\"data:image/png;base64,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\",\"data:image/png;base64,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Number: 2
Class: Marine (Enterococcus<\\/i>)
Category: 35 - 129 (42/100mL)<\\/html>\",\"Station Number: 6
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 7
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 8
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (6/100mL)<\\/html>\",\"Station Number: 9
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 11
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 13
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 14
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 16
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 19
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 21
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 22
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 23
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 24
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 25
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 28
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 32
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 33
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 36
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 38
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 40
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 41
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 42
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 44
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 46
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 47
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 50
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 51
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 52
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 54
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (8/100mL)<\\/html>\",\"Station Number: 55
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 58
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 60
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 61
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (4/100mL)<\\/html>\",\"Station Number: 62
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 63
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 64
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 65
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (8/100mL)<\\/html>\",\"Station Number: 66
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 67
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 68
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 70
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 71
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 73
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 74
Class: Marine (Enterococcus<\\/i>)
Category: 130 - 999 (472/100mL)<\\/html>\",\"Station Number: 80
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 81
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 82
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 84
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 90
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 91
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 92
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 93
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 94
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 95
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 96
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 97
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 101
Class: Marine (Enterococcus<\\/i>)
Category: 130 - 999 (412/100mL)<\\/html>\",\"Station Number: 102
Class: Marine (Enterococcus<\\/i>)
Category: 130 - 999 (327/100mL)<\\/html>\",\"Station Number: 103
Class: Marine (Enterococcus<\\/i>)
Category: 130 - 999 (173/100mL)<\\/html>\",\"Station Number: 104
Class: Marine (Enterococcus<\\/i>)
Category: > 999 (1020/100mL)<\\/html>\",\"Station Number: 105
Class: Marine (Enterococcus<\\/i>)
Category: 35 - 129 (50/100mL)<\\/html>\",\"Station Number: 106
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (48/100mL)<\\/html>\",\"Station Number: 107
Class: Freshwater (E. coli<\\/i>)
Category: 126 - 409 (150/100mL)<\\/html>\",\"Station Number: 108
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (123/100mL)<\\/html>\",\"Station Number: 109
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 110
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (4/100mL)<\\/html>\",\"Station Number: 111
Class: Freshwater (E. coli<\\/i>)
Category: > 999 (1033/100mL)<\\/html>\",\"Station Number: 112
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 113
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (20/100mL)<\\/html>\",\"Station Number: 114
Class: Freshwater (E. coli<\\/i>)
Category: 126 - 409 (140/100mL)<\\/html>\",\"Station Number: 115
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (100/100mL)<\\/html>\",\"Station Number: 116
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (53/100mL)<\\/html>\",\"Station Number: 118
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (33/100mL)<\\/html>\",\"Station Number: 120
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (73/100mL)<\\/html>\",\"Station Number: 129
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (92/100mL)<\\/html>\",\"Station Number: 132
Class: Freshwater (E. coli<\\/i>)
Category: 410 - 999 (467/100mL)<\\/html>\",\"Station Number: 133
Class: Marine (Enterococcus<\\/i>)
Category: > 999 (1500/100mL)<\\/html>\",\"Station Number: 135
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (7/100mL)<\\/html>\",\"Station Number: 137
Class: Marine (Enterococcus<\\/i>)
Category: 35 - 129 (80/100mL)<\\/html>\",\"Station Number: 138
Class: Freshwater (E. coli<\\/i>)
Category: 126 - 409 (333/100mL)<\\/html>\",\"Station Number: 139
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (96/100mL)<\\/html>\",\"Station Number: 140
Class: Freshwater (E. coli<\\/i>)
Category: 126 - 409 (273/100mL)<\\/html>\",\"Station Number: 141
Class: Freshwater (E. coli<\\/i>)
Category: 126 - 409 (287/100mL)<\\/html>\",\"Station Number: 142
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (96/100mL)<\\/html>\",\"Station Number: 143
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (90/100mL)<\\/html>\",\"Station Number: 144
Class: Marine (Enterococcus<\\/i>)
Category: 35 - 129 (120/100mL)<\\/html>\",\"Station Number: 145
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (20/100mL)<\\/html>\",\"Station Number: 146
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (10/100mL)<\\/html>\",\"Station Number: 147
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (100/100mL)<\\/html>\",\"Station Number: 148
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (30/100mL)<\\/html>\",\"Station Number: 149
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (56/100mL)<\\/html>\",\"Station Number: 151
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (70/100mL)<\\/html>\",\"Station Number: 152
Class: Marine (Enterococcus<\\/i>)
Category: 130 - 999 (144/100mL)<\\/html>\",\"Station Number: 153
Class: Marine (Enterococcus<\\/i>)
Category: 130 - 999 (700/100mL)<\\/html>\",\"Station Number: 154
Class: Freshwater (E. coli<\\/i>)
Category: 126 - 409 (260/100mL)<\\/html>\",\"Station Number: 155
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (110/100mL)<\\/html>\",\"Station Number: 158
Class: Freshwater (E. coli<\\/i>)
Category: 126 - 409 (220/100mL)<\\/html>\",\"Station Number: 160
Class: Freshwater (E. coli<\\/i>)
Category: 126 - 409 (270/100mL)<\\/html>\",\"Station Number: 161
Class: Freshwater (E. coli<\\/i>)
Category: 126 - 409 (187/100mL)<\\/html>\",\"Station Number: 163
Class: Freshwater (E. coli<\\/i>)
Category: 126 - 409 (180/100mL)<\\/html>\",\"Station Number: 164
Class: Freshwater (E. coli<\\/i>)
Category: 126 - 409 (140/100mL)<\\/html>\",\"Station Number: 165
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (60/100mL)<\\/html>\",\"Station Number: 166
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (107/100mL)<\\/html>\",\"Station Number: 167
Class: Freshwater (E. coli<\\/i>)
Category: 410 - 999 (460/100mL)<\\/html>\",\"Station Number: 168
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (40/100mL)<\\/html>\",\"Station Number: 169
Class: Freshwater (E. coli<\\/i>)
Category: 410 - 999 (575/100mL)<\\/html>\",\"Station Number: 170
Class: Freshwater (E. coli<\\/i>)
Category: 126 - 409 (310/100mL)<\\/html>\",\"Station Number: 171
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (42/100mL)<\\/html>\",\"Station Number: 172
Class: Freshwater (E. coli<\\/i>)
Category: 126 - 409 (280/100mL)<\\/html>\",\"Station Number: 173
Class: Freshwater (E. coli<\\/i>)
Category: 126 - 409 (210/100mL)<\\/html>\",\"Station Number: 174
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (34/100mL)<\\/html>\",\"Station Number: 175
Class: Freshwater (E. coli<\\/i>)
Category: 410 - 999 (980/100mL)<\\/html>\",\"Station Number: 176
Class: Marine (Enterococcus<\\/i>)
Category: 35 - 129 (128/100mL)<\\/html>\",\"Station Number: 177
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 178
Class: Marine (Enterococcus<\\/i>)
Category: 130 - 999 (630/100mL)<\\/html>\",\"Station Number: 179
Class: Marine (Enterococcus<\\/i>)
Category: 130 - 999 (240/100mL)<\\/html>\",\"Station Number: 180
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 181
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (4/100mL)<\\/html>\",\"Station Number: 182
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (32/100mL)<\\/html>\",\"Station Number: 264
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (28/100mL)<\\/html>\",\"Station Number: 265
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (90/100mL)<\\/html>\",\"Station Number: 266
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (60/100mL)<\\/html>\",\"Station Number: 267
Class: Freshwater (E. coli<\\/i>)
Category: 126 - 409 (340/100mL)<\\/html>\",\"Station Number: 268
Class: Freshwater (E. coli<\\/i>)
Category: 410 - 999 (560/100mL)<\\/html>\",\"Station Number: 269
Class: Freshwater (E. coli<\\/i>)
Category: 126 - 409 (147/100mL)<\\/html>\",\"Station Number: 270
Class: Marine (Enterococcus<\\/i>)
Category: 35 - 129 (117/100mL)<\\/html>\",\"Station Number: 271
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (90/100mL)<\\/html>\",\"Station Number: 1510
Class: Marine (Enterococcus<\\/i>)
Category: 35 - 129 (110/100mL)<\\/html>\"],{\"interactive\":false,\"permanent\":false,\"direction\":\"auto\",\"opacity\":1,\"offset\":[0,0],\"textsize\":\"10px\",\"textOnly\":false,\"className\":\"\",\"sticky\":true},null]},{\"method\":\"addControl\",\"args\":[\"Marine (Enterococcus<\\/em>)<\\/b>
#/100mL
< 35
35 - 129
130 - 999
> 999\",\"topright\",null,\"info legend\"]},{\"method\":\"addControl\",\"args\":[\"Freshwater (E. Coli<\\/em>)<\\/b>
#/100mL
< 126
126 - 409
410 - 999
> 999\",\"topright\",null,\"info legend\"]}],\"limits\":{\"lat\":[27.53248,28.149932],\"lng\":[-82.783203,-82.061156]}},\"evals\":[],\"jsHooks\":{\"render\":[{\"code\":\"function(el, x, data) {\\n return (\\n function(el, x) {\\n var myMap = this;\\n myMap.on('baselayerchange',\\n function (e) {\\n myMap.minimap.changeLayer(L.tileLayer.provider(e.name));\\n })\\n }).call(this.getMap(), el, x, data);\\n}\",\"data\":null}]}} # show selected year, month, and area show_fibmap(fibdata, yrsel = 2020, mosel = 7, areasel = 'Alafia River') {\"x\":{\"options\":{\"crs\":{\"crsClass\":\"L.CRS.EPSG3857\",\"code\":null,\"proj4def\":null,\"projectedBounds\":null,\"options\":{}}},\"fitBounds\":[27.722349,-82.383348,27.937863,-82.061156,[]],\"calls\":[{\"method\":\"addProviderTiles\",\"args\":[\"Esri.WorldGrayCanvas\",null,\"Esri.WorldGrayCanvas\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.NatGeoWorldMap\",null,\"Esri.NatGeoWorldMap\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.OceanBasemap\",null,\"Esri.OceanBasemap\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.WorldPhysical\",null,\"Esri.WorldPhysical\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.WorldShadedRelief\",null,\"Esri.WorldShadedRelief\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.WorldTerrain\",null,\"Esri.WorldTerrain\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.WorldImagery\",null,\"Esri.WorldImagery\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.WorldTopoMap\",null,\"Esri.WorldTopoMap\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.DeLorme\",null,\"Esri.DeLorme\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.WorldStreetMap\",null,\"Esri.WorldStreetMap\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri\",null,\"Esri\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addLayersControl\",\"args\":[[\"Esri.WorldGrayCanvas\",\"Esri.NatGeoWorldMap\",\"Esri.OceanBasemap\",\"Esri.WorldPhysical\",\"Esri.WorldShadedRelief\",\"Esri.WorldTerrain\",\"Esri.WorldImagery\",\"Esri.WorldTopoMap\",\"Esri.DeLorme\",\"Esri.WorldStreetMap\",\"Esri\"],[],{\"collapsed\":true,\"autoZIndex\":true,\"position\":\"topleft\"}]},{\"method\":\"addMiniMap\",\"args\":[null,\"Esri.WorldGrayCanvas\",\"bottomleft\",150,150,19,19,-5,false,false,false,true,false,true,{\"color\":\"#ff7800\",\"weight\":1,\"clickable\":false},{\"color\":\"#000000\",\"weight\":1,\"clickable\":false,\"opacity\":0,\"fillOpacity\":0},{\"hideText\":\"Hide 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MiniMap\"},[]]},{\"method\":\"addMarkers\",\"args\":[[27.859145,27.937863,27.857283,27.862966,27.862607,27.722349,27.908457,27.869101,27.926909,27.854094,27.872697,27.857382,27.884933],[-82.383348,-82.193917,-82.269149,-82.13696899999999,-82.136984,-82.061156,-82.189373,-82.326401,-82.065258,-82.24644600000001,-82.211276,-82.35382199999999,-82.30665],{\"iconUrl\":{\"data\":[\"data:image/png;base64,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\",\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAroAAAJkCAYAAAD+yYJGAAAAAXNSR0IArs4c6QAAAARnQU1BAACxjwv8YQUAAAAJcEhZcwAAMsAAADLAAShkWtsAAEb3SURBVHhe7d0LuOVXfdf/qNVqqdVq1WpVtE2BzFm/E8qQs9YOaVNFba1Si5ZWi/aixabFWq2lWou2tYpSWkWptn8ghABhIAm5EBISchlIMnPWb8/kThKSkAuEW4AkJIFyCYH/93tmAZPf+WRyzplz+f72fr+f5/WkT5OZs8/e67e+38OTyzFERLT5dVc/++mpL6ekPr/cnJVqvsb++MCKlf+7nHXoz5VT/K9tv4yIiIiIKGbdcv5BW17P6/ry5fVY+TX2a9tvQ0REREQUo66Wl3R9vlUtsetjv4f9Xu23JSIiIiLamXbtPfkbU1/26KV14/z39N+7fRkiIiIiou1rYX95ji2ltwyX1E10i3+N9uWIiIiIiLa+hT7/rFhMt4R/rfZliYiIiIi2roV9kxPVQrqV/Gu2L09EREREtPntPrj7G2zxvHm4iG6Dm/1rt5dBRERERLS5pZrPEEvotvCv3V4GEREREdHmdehfIaaX0G3Dv3qMiIiIiDazXf0J35r68mm5fG4jfw3+WtrLIiIiIiI6urqaf08tnjvCXkt7WUREREREGy/1J0zkwrmD/DW1l0dEREREtLFSzRerZXMn+WtqL4+IiIiIaP3ZUvljwyUzkB9rL5OIiIiIaH2lWm4TC2YI/trayyQiIiIiWntdn39VLZix5F9tL5eIiIiI6MlbmD77r6RavqCXyzj8NfprbS+biIiIiOjIdX1+rVosY8qvbS+biIiIiOiJ6/rJ9+iFMrLJ97SXT0RERESkS32+XC+Tcflrbi+fiIiIiGh1tjT+xHCJHJGfaN8GEREREdFhffmYP5T6cpdYIEfBX7t/D+27ISIiIiI6VNfnX1cL5LjkX2/fDhERERGRLbnTk75dL44jZN9L+7aIiIiIaN5LfT5dLo0j5N9L+7aIiIiIaJ7r+slz1cI4bpPntm+PiIiIiOa11Jcr9bI4Xv49tW+PiIiIiOaxbjm/SC2KM8G+t/ZtEhEREdE8dexFx3596su9ckmcAf69+ffYvl0iIiIimpe65fwytSDOFPse27dLRERERPNQ2jd5hlwMZ5B/r+3bJiIiIqJZL9WyRy2Fs8i/1/ZtExEREdEs1y3nv6sWwnWZiv9fZPY9t2+fiIiIiGa11Jcql8H1mk70/z8g/57bt09EREREs1i3nH9OLYIbMr7/Vffn2ttARERERLPUrr0nf2Pq831yCdyoES27/r37e9DeDiIiIiKalWzZe8Vw+ZtDr2hvBxERERHNQt2B0omlb3OM7W9hsPeivS1ERERENPZSX86WS98c8veivS1ERERENOa6af5BtfDNNXtP2ttDRERERGMt9fkauexttnH9g2nXtLeHiIiIiMZYN82/oBY9GHtv2ttERERERGOqu/Gkb059fkAuefD/VfcBf4/a20VEREREYyn15ZVqwcPX+HvU3i4iIiIiGkPdgfIstdhBsPeqvW1EREREFL3Ul/PlUodV/L1qbxsRERERRa6rSz+sFjocgb1n7e0jIiIioqilmm+Sy9x2q+L/F5S/Z+3tIyIiIqKI2XL5ErXIYQ3svWtvIxERERFFKi3nv5Bq/rRc4nZIEv+/qPy98/ewvZ1EREREFKVUy/9TCxzWzt/D9nYSERERUYS6ulTU4oYNsPeyva1EREREtNOlmt8plzasm7+X7W0lIiIiop2sq5N/ohY2HAV7T9vbS0REREQ7Var5fXJZw4b5e9reXiIiIiLaibpa/qNa1LAJ7L1tbzMRERERbWddXfrLtox9Xi5pMX24UX8uHn9v7T1ubzcRERERbVep5tfIBS2o1E/e7tSfi8rf4/Z2ExEREdF21NWl71aLWVSpz+9Lffn/DhnZ31Ns73V724mIiIhoq0s1XyaXsoBsuX0s1ckZX110D/3fj6m/NiJ/r9vbTkRERERb2WItP64WsrBqPvDVJbfx/5/8a4Py97y9/URERES0VaVa7lTLWES21H5quOQe5lPq10Tk73l7+4mIiIhoK7KF69fUIhaVLbOXD5bbw12ufk1U/t63j4GIiIiINrPuqmd/uy1cXxouYFHZInvvYLFV7lW/Nqgv+WfQPg4iIiIi2qxSn08Xy1dYabmcJxbbx7O/Rv3aqPwzaB8HEREREW1GXT95rlq8ArtFLraC/7WDXxvc5LntYyEiIiKio80Wwiv10hVP6vOjC31543ChfSKH/tr8qPq9IrLXfGX7WIiIiIjoaLLl6qeHy1ZwdbjMPhn/NYPfI7qfbh8PEREREW2kXe/d9cdsERzNP7C10JcHhkvsWvmvVb9nRPZ67/XPpn1MRERERLTeUp//m1q0okr95NLhArt2k0vV7xmVfzbtYyIiIiKi9dRNT3y6WrDCqvkDeoFdO/895O8dlX1G7eMiIiIiorWW+vxmuVwFtVDzOWp5XQ//PdTvHZV/Ru3jIiIiIqK1tNiX71eLVWA3qcV1I/z3Gvzeofln1T42IiIiInqybOFbVktVSLV8PvX59OHCunH5dP895dcKyF7zcvvYiIiIiOhILfb5Z9VCFVYt+1cvq0fHf0/5tYLyz6x9fERERESkWrx+8Sm2OH1suEiFVfMn1aK6Gfz3ll8zpo/5Z9c+RiIiIiIalvr8W2KJiuwStaRuBv+9B18rNP/s2sdIRERERIe3OJ0ktUCFVcvdakHdTP415NcOyj/D9nESERER0Veyxe4stTxFZa/37MOX0i1ytvraUdnrPat9nERERETkLU7L89TiFNgNg4V0y/jXGnzt0PyzbB8rEREREdmCdHC4MEWVavmsOU0tpVvCv5Z9TfVagjrYPlYiIiKi+W5hOf+CWJYCm1wtF9It5F9Tv5aY/DNtHy8RERHRfNZdddI3p5ofUMtSSDV/XC2i28G/tnxNAa18pvbZto+ZiIiIaP5KtbxSLUpR2QL3TrWEbgv72uo1ReWfbfuYiYiIiOarbn95llqQorJF8065gG4new3qtYVln3H7uImIiIjmp1TL+XI5iurA5K1y+dxG/hrkawvKP+P2cRMRERHNR4vL+R+pxSisablOLZ47wV+LfI1B+WfdPnYiIiKi2S/VfKNaiiKy1/qZ1E9eq5bOnWGvxV6Teq0R+WfdPnYiIiKi2W6hLv2SWoiiStN8pV44d5C9JvVao/LPvH38RERERLPZ4r7Jn+9qfkQtQyFNy0flohmAvzb5miOyz9w/+3YMiIiIiGavVMv/lYtQVLVcqJbMCPy1ydcclH/27RgQERERzVaLyzmrBSisabldLZiR+GuUrz0oPwPtOBARERHNTraYXaSWn6js9e45fKkMao967VHZ672oHQciIiKi2Whxmv+xWnyiSnVyzWChjMteq/oeovKz0I4FERER0fjr+nyrWnpiyo+k6eTVcqmMyF6rv2b9vUSUb23HgoiIiGjcpWn5Fb3wBFXzu+VCGZi/Zvm9BOVnoh0PIiIionF2/HXl27o+f04tOyHV8mG1SI6Bv3b5PYWUP+dnox0TIiIiovGVpuXVetGJKdV8gVoiR8Feu/qeovKz0Y4JERER0bjq6tJ3qwUnqlTL++QCOSb2PajvLSw7I+24EBEREY2nVPNlcrkJyF7rl1KdnCGXxzHx78G+F/U9RuRnpB0XIiIionG0UMuPq8UmrJoPyMVxhPx7kd9jUH5W2rEhIiIiil+q+U611IS0XB5SC+OY+fckv9eA/Ky0Y0NEREQUu1TLr6mFJqo0LZerZXHU7HtS32tUfmba8SEiIiKK2WJd+utdLeP5e0T7cu+qJXF23Ku+55DszPjZaceIiIiIKF6p5tfLRSYoWwbPGyyHs+Q89T1H5WenHSMiIiKiWC3Wpb+pFpjAbhHL4Uzx73HwPYfmZ6gdJyIiIqI4pZrfo5aXiFKfH13oyxvVcjhLDn2P+VH1HkTkZ6gdJyIiIqIYLdTyL9TiEpUtf71aDGdT7tV7EJWfpXasiIiIiHa23Qd3/9Gulg+qpSUiW/4eWL0MzrwH1HsRkp0lP1PteBERERHtXKmW/yoXlqBSP7lULIIzbnKpei+i8jPVjhcRERHRzrTYn/A0tagE9gG9CM4+/94H70VofrbaMSMiIiLa/lLNZ6glJaqF6eQctQTOA//e1XsSlZ+tdsyIiIiItrfFfvJ9akGJyhan96oFcK7Ye6Dem6j8jLXjRkRERLR9dbXsV8tJUJ9P03y6XP7mib0H/l4M3pu47Iy140ZERES0PdnSdIpcTIKy17v8uIVvvi2r9ygqe72ntGNHREREtLUtXrL4lK6Wj6qlJKRaPjlY9OaevyfyvYrIzpqfuXb8iIiIiLau1OeXy4UkqDQtl6hlb67Ze6Leq6j8zLXjR0RERLQ1Le6bJLWIRGVL3d2rljx8xd3qPYvKz147hkRERESbX1rOZ6klJKpUy9liwYOz90a9Z1H52WvHkIiIiGhzW9xfnqcWkKhSn2+UCx4Ok29U711UfgbbcSQiIiLavLpaDqrlI6jPplpO08sdvsreI3+vBu9dXHYG23EkIiIi2pxSn/+1XDzCmlwtFzus4u+Vfg9j8rPYjiURERHR0XX8dcf/6a7P96ulI6b8cbXQ4Yn5e6bfy4jy/X4m2/EkIiIi2nipz/9LLxwxpZrfqZY5HIG9Z+q9jMrPZDueRERERBtrcTr5LrVoRGUL251ykcOTs/dOvadR+dlsx5SIiIho/dkCdJ5aMuLKZ65a4LAm/t7p9zQme83ntWNKREREtL4WpvkfqgUjrFquGy5vWB9/D+V7G5Sf0XZciYiIiNaeLRI3DBeLsGr5jP3xVLW8Ye38PWzvpX6f47mhHVciIiKitZX6/O/EUhGWLWlXDpc2bNiV6j2Oys9qO7ZERERER+6Z157057o+P6yWiqA+JpY1HAV/TwfvcWD5YT+z7fgSERERPXG26PyuXijCunC4qOHo+Hs6eI9Ds9f8u+34EhEREemOP1CW1CIRVs13DJc0bA5/b+V7HpSf3XaMiYiIiFZnC8O4/pe8Wt6iljRsAntv1Xse2IXtGBMRERE9voVp/lGxPISV+sk1ckHDJppco977qPwMt+NMRERE9LVsUbhluDiEVfMjizW/Ri9n2Cz+Hvt7LT+DmG5px5mIiIjoUKku/YpYGuKq+d1qMcPm8/dafgZB+Vlux5qIiIjmveP3l2+zZeZzamkIqeaPqIUMW8ffc/lZRGRn2c90O95EREQ0z6VaXi0XhqDSNF+gljFsIXvP1WcRlZ/pdryJiIhoXltcziepRSEqW2Buk4sYtp699+ozicrPdjvmRERENI+lmi9VS0JINX8pTSdnyCUMW8/ee/8M5GcTkJ/tdsyJiIho3lqoS/9MLQhhTcsBuYBh2/hnID+boPyMt+NORERE81RX8/vVchDUQ2rxwvbzz2Lw2cRlZ7wddyIiIpqXUi3/WS4GQdmCdcVw4cKOuUJ9RlH5WW/HnoiIiGa945fzX+tqeUwtBRGlablXLFvYSfaZqM8qJDvrfubb8SciIqJZLtVymlwIgrLF6vxVixZ22vnqs4rKz3w7/kRERDSrLdSlv6EWgbgmt4glCwH4Z6M/s5j87LfHgIiIiGaxblT/Odf8RVum3qiWLOw8/2wOfUbqswvIzn57DIiIiGjWSnXyz+UCEFTqc68WLESSe/XZReXPQHsciIiIaFY6ee/JX9fV/AE1/CNKNT+oFyuEY5+V+gxDsmfAn4X2WBAREdEslGr5TTn4g7Ll6TK5VCEe+6zUZxiVPwvtsSAiIqKx98xr83eqgR/YB+RChbD8Mxt8hqH5M9EeDyIiIhpz3TS/SQ37qBaWy7lqmUJc/pmpzzIseyba40FERERjbaE/4fvkoA8q1fxetUhhBOyzU59pVP5stMeEiIiIxljX531qyEeUavmCvd7T5RKF8FY+u5XPUH++8eR97TEhIiKisWXLxyl6wMeUlsvycHnCyNhnqD7bqOw1n9IeFyIiIhpLuw/u/oaulo+q4R5SzfevWpowSv5Zys84IntG/Flpjw0RERGNodTnl8vBHlSalkvU0oQRss9SfcZR+bPSHhsiIiKK3vH9CQtqoEeV+sndcmHCiE3uVp91VP7MtMeHiIiIItf1+Uw1zOOanK2XJYzX5Gz9WUeVz2yPDxEREUVtoZ/8fT3IY0p9vlEvShi/fKP6zKPyZ6c9RkRERBSxrpYDaogH9dk0LafpJQmjZ5+tf8aDzzwue3baY0RERETRsuXi5+UADyrVvG/VcoTZYp+x+uyjstf88+1xIiIioijtPrj7T3W1fFIN76A+vmopwkzyz3rw2cdlz5A/S+2xIiIiogilPv9PObiDStPJO9VShBlkn7U6A1H5s9QeKyIiItrpdvUnPlMN7KhSzXfKhQizyz5zdRai8meqPV5ERES0k3V9PlcN67Cm+Uy5DGFm+Wcuz0JY+dz2eBEREdFOZUvE8/Wgjsle7/WHL0CYK9erMxGVvd7nt8eMiIiIdiIbyONZHmr5jP3x1MHygznhn307A/p8xHN9e8yIiIhou0t9/kUxnMOyZeeq4fKDuXOVOhtR+TPWHjciIiLarnYf3P0tNogfGg7mwD4mlh7MIT8Lg7MR2UP+rLXHjoiIiLajrs+vEkM5rIV+cqFaejB//CyoMxJXflV77IiIiGir27W/LOmBHFW+Qy08mF9+JvRZicmfufb4ERER0VbW1TKy/0WsvEUtO5hffiYGZyQ2e+ba40dERERb1cJy/lE5iINKNV+rFh3Az4Y6M1H5s9ceQyIiItqKulpuUUM4qEcWa36NXHIw9/xs+BkZnJm47NlrjyERERFtdmk5/wc5gMOavFstOMBX+BnRZycmfwbb40hERESb1XddfeJf6mr+rBq+MeWPqMUGGPKzos9QQPYM+rPYHksiIiLajNLyyj/Ao4dvRDVfoJYaYMjPijxDQfmz2B5LIiIiOtoWDpTnqIEbVZqW29RCAzwhOzPqLEXlz2R7PImIiOhossH6ruGgDexLi315s1xmgCfgZ8bPzuAsRfau9ngSERHRRkvT/E/FkI2rlgNqkQGejJ8deaaC8mezPaZERES0kUb1X5CalofUAgOslZ8hebZCyne0x5SIiIjWW+rzf9IDNiZbVK4YLi7AOl2hzlZU/oy2x5WIiIjW2nHXTJ5qQ/SLarhGlGr+kFhagPWzs6TOWET+jPqz2h5bIiIiWks2RF83HKqRLfblfLm0AOvkZ0mdscBe1x5bIiIierIWDuTvFcM0rppvVQsLsFF+puRZC8qf2fb4EhER0ZGywbl3OEjDqvmL5k1qWQE2ys/UytlSZy6mve3xJSIioicqTfNPiSEaVuonvVpUgKM36dWZi8qf3fYYExER0bCT9578dV2f71FDNKJU84N6QQE2iZ0xdfZiyvf4M9weZyIiIjq8VMtv6gEaky0hl8nlBNgsdsbU2YvKn+H2OBMREdFXOm45f6canGHV8kG5mACbzM+aPINB+bPcHmsiIiLyVv7hGzE0AztXLSXAZvOzNjh7sdmz3B5rIiIiWqhLf0cOzKDScrlZLSTAlrEzp85iVP5Mt8ebiIhovutq3qeGZUSpli9008npchkBtsjKmfOzJ85kSPZMt8ebiIhofrPh/TNyUAZlS8fycAkBtsmyOpNR+bPdHnMiIqL5q+wvf6Kr+SNqSMaU7xfLB7Bt/AzqsxmQPdv+jLfHnYiIaL7qavkfckDG9S61fADbxc/g4EzGZs94e9yJiIjmp111aZccjEGlfnK3WjyA7Te5W53RqPxZb489ERHRfNTV/FY1FAN7m146gO3lZ3FwNmOzZ7099kRERLNfqkt/Tw7EoFKfb1QLB7Bz8o3qrEblz3x7/ImIiGa7ruapGoYx5c+laTlNLxvADrEz6WdTn9mA7Jlvjz8REdHslmr5V3IQBpX6vE8uGsCOG8+/f9r5s9+uASIiotnr2Lr0TTbsPqGGYET+WvWCAQQxsufJ74B2HRAREc1WXS2/owZgWLVcLJcLIAg/o/LsRmV3QLsOiIiIZqeFunS8HHxBpT7fqRYLIJ58pzrDUfld0K4FIiKi2air+Rw19KJKy+UsvVQAwdhZVWc4LLsL2rVAREQ0/tL+8nw58IJK03K9XCiAqOzMqrMcVaqTH2rXAxER0bjrpuU6NewiSn3+A/vjqXKZAII6dGZXzq481+HYndCuByIiovFmw/cX5aALKtVylVokgPDs7KozHZXfDe2aICIiGl9PO7j7W2wAP6SGXEQ2eO9btTwAo5LvU2c7Inu9D/kd0a4LIiKicdX1+VVqwMU1uXD14gCMh59hfbajyq9q1wUREdF4WphOTtCDLap8h1ocgLHxs6zPeEx+V7Rrg4iIaBzZsH2HGmqBvUUtDcDY+FkenO3g8jvatUFERBQ/G7Y/ogdaTKnma4fLAjBqdqbVWY/KXvOPtOuDiIgodja4bh4OssAeSdP8mlWLAjBmdqb9bA/OemQ3t+uDiIgobqnP/14MsbBSLe+RiwIwdna21ZmPyu+Odo0QERHF6xkHnvUXbViN519aX/NH5IIAzAg/4/LsB+R3h98h7TohIiKKVdfn31cDLKxpuUAtB8Cs8DMuz35Y+ffbdUJERBSnhenkRD24Ykq13KYWA2Dm2FlXz0BUfpe0a4WIiChGNqAuGQ6ssGr58mJf3iyXAmDG+Fn3My+fhZguadcKERHRzmfD9IViWEV2cLgMALPMz/zgGQjNXvML2/VCRES0s9lQul0Nq6AeOnwBAOaFn/3BsxCWvd7b2/VCRES0c3V9fqkaVFGlWvYOFwBgLtjZV89EXPml7ZohIiLa/o7bN3lq6vOjekjFY6/1Q3IBAOZG/pB6NiLyu8XvmHbdEBERbW9dLa9TAyqqxb6cr4c/MB/8GVDPRlh2x7TrhoiIaPtaWM7fKwdTVDXfqgY/MG/8WZDPSFB+17Rrh4iIaHvqxvT3+9XyWDfNb1JDH5g3/iysPBPqWYnI7pp27RAREW19aTn/lBxIQaVapmrgA3PLngn1rETld067foiIiLawM1/wR1LN96hhFFHq84Ny0ANzLz+onpmI/M7xu6fdQkRERFtTV5f+ixpEUS1O82V6yAPzzZ8N9cyEZXdPu4aIiIg2v137y7FyAMX1QTXgARziz8jgmQnN76B2HREREW1uXS1vVMMnrGk5Vw13AIf4MyKfnajsDmrXERER0eaVlvPfloMnKBviNw+HOgDpZvUMReV3UbuWiIiINqeu5qvV0InIBvcX7I9vGAxzAEJ7VvyZkc9TOHYXtWuJiIjo6LPB8i/lwAkqTcvycJgDOAJ7ZtSzFJbdSe16IiIi2nhP3XvyH099/rAcNiHl++UgB3BE/uzoZyoev5P8bmrXFBER0cbqpuW/q0ET2LvUEAdwZP7sDJ6l2OxuatcUERHR+lu4Jh8nB0xQqc/3qAEOYK3G8x+DcX5HteuKiIhofdkgectwsIRWy9v08AawFv4MyWcrrre064qIiGjtpQP5B8RQCSvVcpMa3ADWyZ4l9YxF5XdVu7aIiIjWVupzr4ZKTPlzqU5eL4c2gPWxZ8mfKf2sxeN3Vbu2iIiInrxuOnmxGihh1bxPDmwAG+LPlHzWorI7q11fRERET9yxdembUp8/LodJQKmWT6hBDeAo2bOlnrmI/M7yu6tdY0RERLqult9RgySsWi6WQxrAUfFnSz5zUdnd1a4xIiKi1S3UpePlAAkqLZe71IAGsEnsGVPPXlR+h7XrjIiI6PF1NZ+jhkdUNojPWjWYAWyms9SzF5bdYe06IyIi+lqpLv2QHBxBLdSlG8RQBrDJ/FlTz2BUfpe1a42IiOhQqebr1NCIyF7rH3QHyqlqKAPYXCvPmj9z4lmMyO+ydq0RERGt/ANo/1YNjMCuUgMZwNbwZ27wDMZmd1q73oiIaJ57Rn/Cn021fEoOi4BSn+9TgxjAVsv3qWcyIr/T/G5r1xwREc1rXc3/Rw2KqGzgXrR6AAPYBhepZzIsu9vaNUdERPNY6k94thwQQaU+3yGGL4Btk+9Qz2ZUfse1646IiOatruYL1HAIq07eqocvgO3gz6B8NqOyO65dd0RENE91/eQFcjAElfp8rRq8ALZbvlY9o3FNXtCuPSIimpdSLe/VQyEee62fTtP8Gj10AWwrfxbtmVTPakR+17Vrj4iI5qGull9WAyGqNC3vkQMXwM6wZ1I9q2HZndeuPyIimuV29Sd8a6rlM3IYBGSv9aNy0ALYWfZsqmc2Ir/z/O5r1yAREc1qXc2/pwZBYO+QQxbAjvJnc/CsxmZ3X7sGiYhoFkv9iRM5AIJK03KbGrAAgrBnVD27Ufkd2K5DIiKatVLNF6vLP6rUL+2RwxVAEEt71LMbld+B7TokIqJZKu0vL1QXf2AH9WAFEIk/q4NnNzS/C9u1SEREs1Kq5XZ16UeU+vywGqgAosoPq2c5Ir8L27VIRESzULecX6ou/MD26mEKICJ/ZgfPcGx2J7brkYiIxtyuq57zV1OfH5WXfUCp5g+rQQogOHt21TMdkd+Jfje2a5KIiMZa1+dT1UUf1WJfzpdDFEBo/uyqZzqufGq7JomIaIyl/eVkfcFHlW9VAxTAOPgzrJ/tmPyObNclERGNLRs8V6jLPaRaHuum+U3DwQlgPPwZXnmW1TMekL3mK9p1SUREY6rr80+qiz2sWqbDoQlgfPxZls94WPkn27VJRESj6MvH/GEbOHfrSz2eNC0PDoclgBGzZ1o96xHZ673b78x2exIRUfS6Pv+GutADu3zVoAQwWv5MD57x4PJvtOuTiIgit3DgxO/QF3lQtXxQDUoA4+bPtnzmg/K7s12jREQUNbuw3zC8wIM7Vw1JAOPmz/bgWY/uDe0aJSKiiHXT8rfE5R2WDcObh8MRwEy5WT37Ydkd2q5TIiKKlg2Vq+TlHVCqK/+1tjcMhiKAGbLyjB961uU9EI295qvadUpERJHq+vwidXGHVUsdDkUAs8efdXkHhJVf1K5VIiKK0LG3f//Xpz5/SF/aEeX71UAEMJv8mdd3QTx+l/qd2q5XIiLa6bp+8jJ1YUeVar5UDUMAM8qeeXUXxDV5WbteiYhoJ1tYzsfpizqm1Od75CAEMOPyPepOiMrv1nbNEhHRTmUX8p7hBR3c2/QQBDDL/Nkf3AXR7WnXLBER7URpOf+AuJzjquUmNQABzAe/A+TdEJTfse26JSKi7S7V3KvLOaSaP5+mk9er4QdgTtgd4HeBvCMC8ju2XbdERLSddXXpxepiDqvm/XLwAZgrfhfIOyIqu2vbtUtERNvR068+8U+mmj8uL+WAUi2fUAMPwJyyO0HdFRH5Xet3brt+iYhoq+tq+W11IYc1LRfLYQdgLvmdIO+KqOzObdcvERFtZWk5L8qLOCgbancNhxwAmLvUnRGV373tGiYioq2qq+P6V/SkaTlLDDgA887uBnVnhGV3b7uGiYhoK+rq0j+QF3BcN8gBBwDG74jBnRGb3cHtOiYios0u1XytvHwDSn3+A/vj69RwAwB36I5YuSvkPRKN38HtOiYios2sq+XfqIs3rGm5Sg02ADic3xXyDonK7uJ2LRMR0Wa0a3/5M6nmB+WlG1Dq831qoAGAlu9Td0lEfhf7ndyuZyIiOtq6Wv63unCjssF10epBBgBP6CJ1l4Rld3K7nomI6Gjqat4tL9qgbGC9fzDAAGAt3q/ulLDsbm7XNBERbbTU57fLSzaqOnmrGGAAcER+d8g7JSi/m9s1TUREG6mrSz+sLtiwar5ODTAAWAu/Q+TdEpXd0e26JiKi9Zb6fJO8XAOyIfVpe72vHQ4uAFi7lTvk0+qOicjv6HZdExHReuqm5SXqYo0q1fKe1UMLANbJ7hJ1x4Rld3W7tomIaC3t6k/4Vrvwx/O/atTy0VXDCgA2yu4UdddEZK/3035nt+ubiIierK7m31MXamDvWDWoAGCD/E4Z3DGx2Z3drm8iIjpSqT9hIi/SqOrS7WpQAcDR8LtF3jlB+d3drnEiInqiUs0Xq0s0KhtIe4YDCgA2wR5150Tld3e7xomISGWX5Y8NL8/gDorhBACbwu+YwZ0T3Y+165yIiIalWm4TF2dIqeaH0wE9nABgU/gdY3eNuoMi8ju8XedERHR4XZ9/VV2cge2VgwkANpHfNYO7J7j8q+1aJyIib2H67L+SavmCvjTjsdf6YTWQAGBL2J2j7qKI/C73O71d70RE1PX5terCjCr1k7fLYQQAW2LydnUXxZVf2653IqL5rusn36MvyqjyrXoQAcDW8btH30lRTb6nXfNERPNb6vPl+pIMqJbHUs1nqCEEAFvK7h6/g+TdFJDf7e2aJyKaz+wy/Inh5RjcVA4gANgGfgcN7qTofqJd90REc9aXj/lDdnHfJS7GkFItnxoOHQDYdnYXqTsqInu9d/ld3259IqL5qevzr6uLMSq7sC9/3LABgJ0xnr/da0X+9XbtExHNR930pG/XF2JMqc/3imEDADsk36vuqrDszm/XPxHR7GeX9OnyMgzKXu95etgAwE7I56m7Kiq/89v1T0Q023X95LnqIgzsZj1oAGDn+N00uKuCmzy3jQEiotnNLugr9SUYT+rzowt9eeNwwADATjt0N+VH1d0Vkb3mK9sYICKazbrl/CJ1AQZWh8MFAKLwO2pwZ8VmM6CNAyKi2erYi479eruYR/MPUKRaHhgOFQAIx+4qdYdFZK/3Xp8FbSwQEc1O9pP8y9TFF1XqJ5euGigAEM7kUnWHhWWzoI0FIqLZKO2bPENeeFHV/AE9UAAgHr+z5F0WlM+ENh6IiMZfqmWPuuwCe5saJgAQkd9ZgzssNJ8JbTwQEY27bjn/XXXRBXaTGiQAEJnfXYO7LDabDW1MEBGNN7uAx/RPBX8+1cnrhwMEAMKzu8vvsMGdFpa95trGBBHROLOf2H9OXXBhTcv+VcMDAEbC7zB5t0VlM6KNCyKicbVr78nfmPp8n7zcArIh8Ynh0ACAEfqEuuMi8hnhs6KNDSKi8WSX2CuGl1ps+RIxMABgVPwu03dcWK9oY4OIaBx1B0onLrO4puUuNTAAYIz8TpN3XVQ2M9r4ICKKn120Z8vLLCh7vWcdPiQAYOTOUnddVPZ6z27jg4godt00/6C6yAK7YTAgAGD0/G4b3HWx2exoY4SIKG6pz9fISywge62ftT++Tg0JABizQ3fbyh0n779ofHa0MUJEFDP7ifwX1AUWVs1XqwEBALPA7zh590VlM6SNEyKiWHU3nvTN9hP5A/LyCshe631qMADAbBnTv+bRZojNkjZWiIjiZBfqK9XFFVWq+Z2rBwIAzBi769QdGJW95le2sUJEFKPuQHmWurDCquX9q4YBAMwov/PkXRiVzZQ2XoiIdj67SM+Xl1VU08lbh4MAAGaV33nyLgzKXvP5bbwQEe1sXV36YXVRhVXLdcMhAACzzu8+eSdGZbOljRkiop0r1XyTvKQCSsv5M2k6ea0aAgAw0/zusztQ3Y0R+WxpY4aIaGfqanmJuqCiStPyHjkAAGAe2B2o7sawbMa0cUNEtL2l5fwX7CfuT8vLKaBUy0flxQ8A88TuQnVHRuQzxmdNGztERNuXXZb/T11MYU3LO+SlDwBzxO9CeUcG5bOmjR0iou2pq0tFXUiB3a4ufACYR34nDu7I2GzmtPFDRLT1jfBfQL5neNEDwBzbo+7KqHzmtPFDRLS1dXXyT9RFFFXq8zXikgeAOZevUXdmWDZ72hgiItq67Cfr98lLKCC7yB9O0/JqfckDwBxbuRvzw+rujMhnTxtDRERbU1fLf1QXUGB75QUPAPC/V3fv4M6MzWZQG0dERJtbV5f+sl0yn5eXT0wfVhc7AOBr/K4c3J1x+QyyWdTGEhHR5pVqfo28eIJK/eTt6lIHABxu8nZ1h0bls6iNJSKizcl+gv5udeFElfr8Pn2hAwBWG88/e7HCZlIbT0RER5/9BH2ZvGwCskv7sVQnZ6y+yAEA0qE78zF1p0bkM6mNJyKio2uxlh9XF01YNR9YdYkDAI7I7055pwbls6mNKSKijZdquVNdMhHZZf2p4eUNAFizT6m7NSKfTW1MERFtLLtIfk1dMFHZJX354NIGAKzd5epujcpnVBtXRETrq7vq2d9uF8mXhhdLVHZB3zu4sAEA63evumOD+pLPqja2iIjWXurz6eJSCSstl/PEhQ0AWA+7S9UdG5XPqja2iIjWVtdPnqsulMBukRc2AGDd/E4d3LHBTZ7bxhcR0ZNnF92V+jKJx36af3ShL28cXtQAgI05dKfmR9WdG5G95ivb+CIiOnJ2afz08BIJrg4vaQDA0fG7dXDXRvfTbYwREel2vXfXH7MLbjT/IMJCXx4YXs4AgM3hd6y6eyOy13uvz7A2zoiIVpf6/N/UBRJV6ieXDi9mAMBmmVyq7t6ofIa1cUZE9Pi66YlPVxdHWDV/QF/MAIDN4netvIOjslnWxhoR0deyn4TfLC+NoBZqPkddygCAzeN3rbqDo/JZ1sYaEdGhFvvy/erCCOwmdSEDADaf37mDOzg0n2ltvBERrfzrxJbVZRFSLZ+3n9hPH17EAICtkk/3u1feyQHZa15u442I5r3FPv+suijCqmX/6ksYALCV/O6Vd3JQPtvamCOieW3x+sWn2IXwseEFEVbNn1QXMABg6/kdLO/mmD7mM66NOyKax1Kff0tcDpFdoi5fAMDW8zt4cCeH5jOujTsimrcWp5OkLoawarlbXbwAgO3jd7G8o4PyWdfGHhHNU3ZhnaUuhajs9Z59+GULANgRZ6s7Oip7vWe1sUdE89LitDxPXQiB3TC4aAEAO8Tv5MEdHZrPvDb+iGgesgf/4PAiiCrV8llzmrpsAQA7wO9ku5vVnR3UwTb+iGjWW1jOvyAugcAmV8uLFgCwY/xu1nd2TD772hgkolmtu+qkb041P6AugZBq/ri6YAEAO8/vaHl3B7Qy+2wGtnFIRLNYquWV6gKIyi6md6rLFQAQgN3R6u6OymdgG4dENGt1+8uz1IMflV2gd8qLFQAQh93V6g4Py2ZhG4tENEvZT7Lny4c+qgOTt8pLFQAQht/V8g4PymdhG4tENCstLud/pB74sKblOnWhAgDi8Ttb3uVB+Uxs45GIZqFU843qYY/IXutnUj95rbpMAQAR2Z1td7e60yPymdjGIxGNvYW69EvqQY8qTfOV+iIFAIRld7e606Py2djGJBGNtcV9kz/f1fyIeshDmpaPygsUABCe3+Hybo/IZqPPyDYuiWiMpVr+r3zAo6rlQnV5AgDi8ztc3u1B+Yxs45KIxtbics7qwQ5rWm5XFycAYDz8Lpd3fFA+K9vYJKIxZRfOReqhjspe757DL0sAwCjtUXd8VPZ6L2pjk4jG0uI0/2P1QEeV6uSawUUJABgru9PVXR+Vz8w2PoloDHV9vlU9zDHlR9J08mp5WQIAxsfudL/b9Z0fUb61jU8iil6all/RD3JQNb9bXpQAgNHyu13e+UH57GxjlIiidvx15dvsJ9PPqYc4pFo+rC5IAMD4+R0v7/6Q8ud8hrZxSkQRs59IX60f4JhSzReoyxEAMAPsjld3f1Q+Q9s4JaJodXXpu9WDG1Wq5X3yYgQAzA6769UMCMtmaRurRBQp+8n5MvnQBmSv9UupTs6QlyIAYHb4XW93vpoFEfksbWOViKK0UMuPqwc2rJoPyAsRADBz/M6XsyAon6ltvBJRhOwn0DvVwxrScnlIXYQAgNnld7+cCQH5TG3jlYh2ulTLr6kHNao0LZerSxAAMMPs7lczISqfrW3MEtFOtViX/npXy3j+3qe+3Lvq8gMAzIt71WwIyWarz9g2boloJ0o1v14+oEHZJXfe4NIDAMyP89RsiMpnbBu3RLTd2U+af1M9mIHdIi49AMAc8VkwmA2h+axtY5eItjP7SfM96qGMKPX50YW+vFFdegCA+XFoFuRH1ayIyGdtG7tEtF0t1PIv1AMZlV1qvbrwAADzKPdqVkTlM7eNXyLa6nYf3P1Hu1o+qB7GiOxSe2D1JQcAmHMPqJkRks1cn71tDBPRVpZq+a/yQQwq9ZNLxQUHAJhrk0vVzIjKZ28bw0S0VS32JzxNPYCBfUBfcACAeeczYjAzQvMZ3MYxEW1FqeYz1MMX1cJ0co663AAA8BmhZkdUPoPbOCaizW6xn3yfevCisgvhvepiAwDgq2xWqBkSlc/iNpaJaDPratmvHrqgPp+m+XR5qQEA8BU2K3xmDGZIXDaL21gmos3KLoNT5AMXlL3e5cddZAAAPLFlNUuistd7ShvPRHS0LV6y+BT7CfKj6mELqZZPDi4wAACOyGeHnCkR2Uz22dzGNBEdTanPL5cPWlBpWi5RlxgAAE/IZoeaKVH5bG5jmog22uK+SVIPWFR2Wd296vICAGBt7lazJSqf0W1cE9FGSsv5LPVwRZVqOVtcXAAAPDmbIWq2ROUzuo1rIlpvi/vL89SDFVXq843y4gIAYM3yjWrGROWzuo1tIlpPXS0H1UMV1GftJ/HT9KUFAMAa2SzxmTKYMXHZrG5jm4jWmv1E+6/lAxXW5Gp5YQEAsE4+U/SsiclndhvfRPRkHX/d8X+66/P96mGKKX9cXVQAAGyUzxY9cyLK9/vsbmOciI6U/WT4v/SDFFOq+Z3qkgIAYMNstqiZE5XP7jbGieiJWpxOvks9QFHZRXSnvKAAADhaNmPU7InKZ3gb50Sksgf7PPXwxJXPXHUxAQCwCXzG6NkTk73m89o4J6JhC9P8D9WDE1Yt1w0vJQAANpPPGjmDgvJZ3sY6ER2ePSA3DB+YsGr5jP3xVHUpAQCwWXzWtJmj51E8N7SxTkRfKfX534mHJSy7fK4cXkYAAGyRK9UsispnehvvRPTMa0/6c12fH1YPS1AfE5cQAABbxmfPYBYFlh/22d7GPNF8Zw/w7+oHJawLhxcQAABbyWfPYBaFZq/5d9uYJ5rfjj9QltQDElbNdwwvHwAAtoPPIDmbgvIZ38Y90XxmD8K4fkKt5S3q8gEAYMvZDFKzKbAL27gnmr8WpvlHxUMRVuon18iLBwCAbTO5Rs2oqHzWt7FPNF/ZA3DL8IEIq+ZHFmt+jb50AADYHj6LfCbJWRXTLW3sE81PqS79ingY4qr53erCAQBgu/lMkrMqKJ/5bfwTzX7H7y/fZg/p59TDEFLNH1EXDQAAO8Vnk5xZEdnM99nf1gCi2S7V8mr5IASVpvkCdckAALBjbDapmRWVz/62BhDNbovL+ST1AERlD+Zt8oIBAGCn2YxSsysq3wHaOkA0m6WaL1WHP6Sav5SmkzPk5QIAwE6zGeWzSs6wgHwHaOsA0ey1UJf+mTr4YU3LAXmxAAAQhM8qOcOC8l2grQVEs5X91Pl+deiDekhdKAAAROMzazDD4rJdoK0FRLNTquU/ywMflF0cVwwvEgAAgrpCzbKofCdo6wHR+Dt+Of+1rpbH1GGPKE3LveISAQAgLptdaqaFZDuB7wZtTSAad/aT22nyoAdlF8b5qy4QAABiO1/NtKh8N2hrAtF4W6hLf0Md8Lgmt4jLAwCA8HyG6dkWk+8IbV0gGmfdqP4zhfmLdkm8UV0eAABE5zPs0CxTMy4g2xHaukA0vlKd/HN5sINKfe7VxQEAwHjkXs24qHxXaGsD0Xg6ee/JX2c/qX1AHeqIUs0P6gsDAICRsZmmZl1Itiv4ztDWB6JxlGr5TXmgg7JL4TJ5WQAAMDY209Ssi8p3hrY+EMXvmdfm71QHObAPyIsCAICR8tk2mHWh+e7Q1gii2HXT/CZ1iKNaWC7nqksCAICx8tmmZl5Ytju0NYIobgv9Cd8nD3BQqeb3qgsCAIDRsxmnZl9UvkO0dYIoZl2f96nDG1Gq5Qv2ek+XlwMAACO3MuNWZp2eg/HkfW2dIIqXPVSn6IMbU1ouy8NLAQCAmWKzTs3AqOw1n9LWCqI47T64+xu6Wj6qDm1INd+/6jIAAGAG+cyTszAi2yV8p2jrBVGMUp9fLg9sUGlaLlGXAQAAM8dmnpqFUflO0dYLop3v+P6EBXVQo0r95G55EQAAMLMmd6uZGJXvFm3NINrZuj6fqQ5pXJOz9SUAAMCsmpytZ2JU+cy2ZhDtXAv95O/rAxpT6vON+gIAAGDW5RvVbIzKd4y2bhDtTF0tB9ThDOqzaVpO0w8/AAAzzmagz8LBbIzLdoy2bhBtf/bQ/Lw8mEGlmveteugBAJgnNgvVjIzKXvPPt7WDaPvafXD3n7KftD6pDmVQH1/1sAMAMId8Jg5mZFy2a/jO0dYPou0p9fl/ygMZVJpO3qkedgAA5o7NRDUro/Kdo60fRFvfrv7EZ6qDGFWq+U75oAMAMK9sNqqZGZXvHm0NIdrauj6fqw5hWNN8pnzIAQCYUz4b5cwMK5/b1hCircsejufrAxiTvd7rD3+wAQDAV12vZmdU9nqf39YRoq3JDtp4HopaPmN/PHXwUAMAAOMzss1KPUfjub6tI0SbX+rzL4pDF5Y9xFcNH2oAAPA4V6kZGpXvIm0tIdq8dh/c/S12wB4aHrjAPiYeZgAAMOAzczBDI3vId5K2nhBtTl2fXyUOW1gL/eRC9TADAIDH85mpZmlc+VVtPSE6+nbtL0v6oEWV71APMgAA0Hx26pkak+8mbU0hOrq6Wkb2k155i3qIAQCA5rNzMEtjs92krSlEG29hOf+oPGBBpZqvVQ8wAAB4EjZD1WyNyneUtq4QbSz7iekWdbiCemSx5tfIhxcAAByRz1CfpYPZGpftKG1dIVp/aTn/B3mwwpq8Wz24AABgbXyW6hkbk+8qbW0hWnvfdfWJf6mr+bPqUMWUP6IeWAAAsD4+U/WsDch2Fd9Z2vpCtLbS8srfmK4PVUQ1X6AeVgAAsD4+U+WsDcp3lra+ED15CwfKc9RBiipNy23qQQUAABtks1XN3Kh8d2lrDNGRswPzruEBCuxLi315s3xIAQDAhvhs9Rk7mLmRvautMURPXJrmfyoOT1y1HFAPKAAAODo+Y+XsDcp3mLbOEOlG9V9GmZaH1IMJAAA2h89aOYNDyne0dYZodanP/0kfnJjsAbxi+EACAIBNdYWawVH5LtPWGqKvddw1k6fa4fiiOjQRpZo/JB5GAACw2Wzmqlkcke8yvtO09YboUHY4Xjc8LJEt9uV8+TACAIBN5TNXzeLAXtfWGyL/14nl7xWHJK6ab1UPIgAA2Bo+e+VMDsp3m7bm0LxnB2Lv8ICEVfMXzZvUQwgAALaGz96VGaxmc0x725pD81ya5p8ShyOs1E969QACAICtNunVbI7Kd5y27tA8dvLek7+u6/M96nBElGp+UD94AABgW9gsVjM6pnyP7zpt7aF5K9Xym/pgxGQP12XyoQMAANvDZrGa0VH5rtPWHpqnjlvO36kORFi1fFA+cAAAYFv5TJazOijfedr6Q/PSyt9ULg5DYOeqhw0AAGwvn8mDGR2b7Txt/aF5aKEu/R15EIJKy+Vm9aABAIAdYrNZzeyofPdpaxDNevaTzT51CCJKtXyhm05Olw8ZAADYESuz2We0mN0h2e7T1iCa5exQ/ow8AEHZw7Q8fLgAAEAIy2p2R+U7UFuHaBYr+8ufsJ9oPqI+/Jjy/eKhAgAAQfis1jM8INuBfBdqaxHNWl0t/0N+8HG9Sz1UAAAgBp/Vg9kdm+1CbS2iWWpXXdolP/CgUj+5Wz1QAAAgmsndapZH5TtRW49oVupqfqv6sAN7m36YAABAJD6zBzM8NtuJ2npEs1CqS39PftBBpT7fqB4kAAAQVb5RzfSofDdqaxKNPfvJZao+5Jjy59K0nKYfIgAAEJLNbp/herYHZLtRW5NozKVa/pX8gIOynwj3yQcIAAAEN55/T7/zHamtSzTGjq1L32Qf4ifUhxuRv1b94AAAgFEY2d7hu1Jbm2hsdbX8jvpgw6rlYvnQAACAUfBZLmd8VLYrtbWJxtRCXTpefqBBpT7fqR4YAAAwNvlONeuj8p2prU80lrqaz1EfZlRpuZylHxYAADAqNtPVrA/Ldqa2PtEYSvvL8+UHGVSaluvlgwIAAMbJZrua+VH57tTWKIpeNy3XqQ8xotTnP7A/niofEgAAMEqHZvvKjJfzPxzbndoaRZGzQ/WL8gMMKtVylXpAAADAyNmMV7M/Kt+h2jpFEXvawd3fYgfrIfXhRWQH6r5VDwUAAJgh+T61A0Rkr/ch36XaWkXR6vr8KvXBxTW5cPUDAQAAZoXPer0DRJVf1dYqitTCdHKC/sCiyneoBwIAAMwWn/l6F4jJd6q2XlGU7BC9Q31Ygb1FPQwAAGC2+Mwf7ADB5Xe09YoiZIfoR/QHFVOq+drhQwAAAGaYzX61E0Rlr/lH2ppFO519IDcPP6DAHknT/JpVDwAAAJhdNvt9BxjsBJHd3NYs2slSn/+9+HDCSrW8Rz4AAABgttkOoHaDqHzHausW7UTPOPCsv2gfwnj+Zcw1f0QefAAAMBd8F5A7QkC+Y/mu1dYu2u66Pv+++mDCmpYL1KEHAADzwXcBuSOElX+/rV20nS1MJyfqDySmVMtt6sADAIA5YzuB2hWi8p2rrV+0Xdkbf8nwgwirli8v9uXN8rADAIC54juB7wZyZ4jpkrZ+0XZkh+SF4kOI7ODwkAMAgPnlu8FgVwjNXvML2xpGW5292berDyGohw4/2AAAAM53hMHOEJa93tvbGkZbWdfnl6oPIKpUy97hwQYAAPAdQe0OceWXtnWMtqLj9k2emvr8qH7z47HX+iF5sAEAAFbkD6kdIiLfwXwXa2sZbXZdLa9Tb3xUi305Xx9qAACAlX8w7Xy1Q4Rlu1hby2gzW1jO3yvf8KhqvlUdaAAAgMP5ziB3iaB8J2vrGW1W9hPEeP4+lloe66b5TeowAwAAHM53hpXdQe0UEdlO1tYz2ozScv4p+UYHlWqZqoMMAAAg2e6gdoqofDdraxodVWe+4I+kmu9Rb3JEqc8PygMMAABwRPlBtVtE5LuZ72htW6ON1tWl/6Le4KgWp/kyfXgBAACemO8QarcIy3a0tq7RRtq1vxwr39i4PqgOLgAAwFr4LjHYLULzXa2tbbTeulreqN7UsKblXHVoAQAA1sJ3CbljRGW7WlvbaD2l5fy35RsalB3Om4eHFQAAYANuVrtGVL6ztfWN1lpX89XqzYzIDuQX7I9vGBxSAACAdWs7he8Wcu8Ix3a2tr7RWrI37F/KNzKoNC3Lw0MKAACwYbZbqJ0jLNvd2hpHR+qpe0/+46nPH5ZvYkj5fnlAAQAAjoLvGHr3iMd3N9/h2jpHT1Q3Lf9dvYGBvUsdTgAAgKPhO8Zg54jNdri2zpFq4Zp8nHzjgrKfXu5RBxMAAGBzjOc/muV8l2trHQ2zN+gtwzcstFrepg8lAADA0fNdQ+4gcb2lrXV0eOlA/gHxZoWVarlJHUgAAIBNZTuH2kWi8p2urXf0lVKfe/VmxZQ/l+rk9fIwAgAAbCbbOXz30DtJPL7TtfWOvG46ebF6o8KqeZ88iAAAAFvAdw+5k0Rlu11b8+a7Y+vSN9nm/3H5JgWUavmEOoAAAABbynYQtZtE5Lud73ht3Zvfulp+R71BYdVysTx8AAAAW8h3ELmbRGU7Xlv35rOFunS8fGOCSsvlLnXwAAAAtoXtImpHicp3vbb2zV9dzeeoNyUqO2BnrTpwAAAA2+cstaOEZbteW/vmq1SXfki+IUHZTyQ3iMMGAACwrXwnUbtKVL7ztfVvfko1X6fejIjstf5Bd6Ccqg4bAADAdlrZSXw3ETtLRL7ztfVvPupq+bfqjQjsKnXQAAAAdoLvJoNdJTbb/doaONs9oz/hz6ZaPiXfhIBSn+9TBwwAAGBn5fvU7hKR736+A7Z1cHbrav4/6g2Iyg7SRasPFgAAwI67SO0uYdkO2NbB2Sz1JzxbfuNB2U9Kd4hDBQAAEES+Q+0wUfku2NbC2cs2+QvUNx1WnbxVHyoAAICd57uK3GGisl2wrYWzVddPXiC/4aDsJ6Rr1YECAACIJV+rdpm4Ji9o6+HslGp5r/5m47HX+uk0za/RhwkAACAQ31lsd1E7TUS+E7b1cDbqavll9Y1GlablPfIgAQAARGS7i9ppwrLdsK2J425Xf8K32ub+GflNBmSv9aPyAAEAAERmO4zabSLy3dB3xLYujreu5t9T32Bg75CHBwAAIDDfYQY7TWy2I7Z1cZyl/sSJ/MaCStNymzo4AAAAo2C7jNpxovJdsa2N4yvVfLH6pqJK/dIeeWgAAABGYWmP2nGi8l2xrY3jKu0vL1TfUGAH9YEBAAAYD99pBjtOaL4ztvVxPKVablffTESpzw+rgwIAADBO+WG180TkO2NbH8dRt5xfqr6RwPbqQwIAADA+vtsMdp3YbHdsa2Tsdl31nL9qP0U8Kr+JgFLNH1YHBAAAYNRsx1G7T0S+O/oO2dbJuHV9PlV9A1Et9uV8eTgAAABGzHcctfvElU9t62TM0v5ysn7hUeVb1cEAAACYBb7r6B0oJt8l21oZL3tDr1AvOqRaHuum+U3DAwEAADArfNdZ2XnULhSQveYr2loZK/uJ4SfVCw6rlunwMAAAAMwa33nkLhRW/sm2Xgbpy8f8YXsj79YvNp40LQ8ODwEAAMDMst1H7UQR2eu923fLtmXufLZ5/4Z6oYFdvuoAAAAAzCjffQa7UHD5N9qaubMtHDjxO/QLDKqWD6oDAAAAMMt8B5K7UVC+Y7Z1c+eyF/KG4QsL7lz14QMAAMwy34EGO1F0b2jr5s7UTcvfEi8qLPuQbx5+6AAAAHPkZrUjhWW7Zls7tz97s66SLyqgVFf+a21vGHzYAAAAc2NlFzq0E8l9KRp7zVe1tXN76/r8IvWCwqqlDj9sAACAeeM7kdyVwsovauvn9nTs7d//9anPH9IvJqJ8v/qgAQAA5pHvRnpnisd3Tt892xq69XX95GXqhUSVar5UfcgAAABzyXYjtTPFNXlZW0O3toXlfJx+ATHZTwH3yA8YAABgruV71O4Ule+gbR3duuwL7Rl+4eDepj9cAACA+eU70mBnim5PW0e3prScf0B80bhquUl9sAAAAFj5B9NukjtUUL6LtrV080s19+qLhlTz59N08nr1oQIAAMDYruQ7k9ylAvJdtK2lm1tXl16svmBYNe+XHygAAAC+yncmuUtFZTtpW083p6dffeKftA364/KLBZRq+YT6IAEAACDY7qR2qoh8J/XdtK2pR19Xy2+rLxTWtFwsP0QAAACs4ruT3Kmist20ralHV1rOi/ILBGUf1l3DDw8AAABP6i61W0XlO2pbVzeebcyj+ldPpGk5S3xwAAAAOBLbodRuFZbtqG1d3VhdXfoH8jcGAAAAdprtqm1tXX+p5mvlbwoAAADsMN9V29q6vrpa/o36DQEAAIAwbGdt6+va2rW//BnbkB+UvxkAAAAQhO+svru2NfbJs834f6vfCAAAAAjHdte2xh65rubd8jcAAAAAorIdtq2zT1zq89vlLwYAAACC8h22rbO6ri79sPqFAAAAQHi2y7a1dnW2Cd8kfxEAAAAQnO+yba19fN20vET9AgAAAGA0bKdt6+3XSjW/T/7FAAAAwEj4TtvW20MtTsvz1F8IAAAAjI3vtm3NXflXip2j/iIAAABgdGy3XVlyFw6c+B3yLwAAAABGynfcY7rp5MXqTwIAAACjZTuu/+d+f1v+SQAAAGCsbMc9JtXyNvknAQAAgJFKfTnb/yMR16g/CQAAAIyV77j+7899QP1JAAAAYKx8x/X/RfdB9ScBAACAsfId1/8X3WvVnwQAAADGyndc/mE0AAAAzJyVfxjN/o9XDP8EAAAAMHKvOKZbzj8n/gQAAAAwXrbjHrPrmnKs/JMAAADASPmOe4zX1XyO+gsAAACA8cnnriy53uL+8jz9FwEAAADjsjgtz2tr7qG6mm9VfyEAAAAwGrbTtvX2ay1MJ78k/2IAAABgJHynbevt40t9frP6BQAAAEB0vsu2tXZ1i5csPiXV8l71CwEAAICoUl9u9l22rbW61J84Ub8YAAAAiMp32LbOHrl0oPyM+g0AAACAaHx3bWvs2tq1nE+yX3jL8DcCAAAAgrhl4UB5Tltf19euvSd/Y+rLHvGbAgAAADsm1bLHd9W2tm68rpZfTjW/T30RAAAAYLus7KS2m7Y1dfPqpvkHU1/OU18UAAAA2CorO6jtom0t3boW+xOeZl/slNTn37I/nmWb9TX2fz+gXhQAAACwVr5THtotbcc8tGue0l397Ke3NXQdHXPM/w+LdBQvQyJLdgAAAABJRU5ErkJggg==\",\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAroAAAJkCAYAAAD+yYJGAAAAAXNSR0IArs4c6QAAAARnQU1BAACxjwv8YQUAAAAJcEhZcwAAMsAAADLAAShkWtsAAEjjSURBVHhe7Z0L3KTnWZdvFUUpoigqiopyFAVRVLRABUFF0SIoiIiCqJTSUmuz3/POpoCrIkjLQRS1tmmahjaHkjSHpmmSNm16TtMkDW2aY0nTps1x553ZzaHNgSbe9zd3aTP73+x+3858c78z1/X7Xb9nmt39vnfe93n+93/Sza4BAMDiOdjsq/tmz56M7EW+ntN3dq2vk2399cT/Wf7Ys+Pn5i8DAAAAAKiJF9jv9vJ6waSzJ3bi9q/xX5tfBgAAAACgBl5UmxfWm+YL7C68Kb5WflkAAAAAgNVw73Ps8yfNzhKF9cT0rxlfO78NAAAAAMDe0W/ZN3shvVEW1UXoXzu+R347AAAAAIDl03f2E7KcLsH4XvltAQAAAACWhxfPb1KFdJnG98xvDwAAAACweJ44YJ83aXaDKqNL1b9nfO+8DAAAAACAxdJ3doYsontgfO+8DAAAAACAxZF/hJgsoXslf/QYAAAAACyUe7fsi71oPjhfPFfgg3EteVkAAAAAACeGF8yXzBXOVfqSvCwAAAAAgN3Tb9nTRdlcqXFNeXkAAAAAALtj3OxSVTZXaVxTXh4AAAAAwM7pO/uXqmhWMK4tLxMAAAAAYGf0zW5RJbOCcW15mQAAAAAAx4+XyZ+aL5cF/am8XAAAAACAY9OfZH+m7+xRUSxLGdcY15qXDQAAAADw1EyavVwVy5L6teZlAwAAAAAcncnI/rYslJX1a87LBwAAAADQ9M3eLMtkYeOa8/IBAAAAAI7ES+OPzJfIAfkj+TYAAAAAAD7DE0/Y7+o7+7AokIMwrj3eQ74dAAAAAIAZ02b/WRXIIRnvId8OAAAAAIDZof32Zao4DtF4L/m2AAAAAGDTmXZ2uiqNQzTeS74tAAAAANhkps2+QxXGIRvvKd8eAAAAAGwqfWdvV2VxyMZ7yrcHAAAAAJuIF8IfU0VR2sQ/K2y8t3ybAAAAALBJ3Po8+1wvrx9TJXEt9PcW7zHfLgAAAABsCn2zn5cFcY2M95hvFwAAAAA2gYMn2V9QxXAdjfeabxsAAAAA1p1Js7NUKVxL/b3m2wYAAACAdabv7B/KQrgDp+KfVTbec759AAAAAFhX+mbvUWVwpw6p7MZ7zrcPAAAAAOvIpNlzVBHcCP29520AAAAAgHXi3gP2+X1n98oSuEunI/3PKxrvPe5B3g4AAAAAWBcmzX5RFcCN0u9B3g4AAAAAWAf6zr5OFr8FOMD/MO3r8rYAAAAAwNDxgnfufOHbYM/N2wIAAAAAQ2bS7LtF2dts/Z7k7QEAAACAodJ3dq0sewt2UH/cmN+TvD0AAAAAMEQmzZ6vit5SbOKfVdbvTd4mAAAAABgSh/bbF/bNJrLkYfwlEpO4R3m7AAAAAGAoTDv7VVXw8DPGPcrbBQAAAABDYNrsG1SxwyONe5W3DQAAAACqM+3sQlXq8EjjXuVtAwAAAIDKjDv7PlXo8OjGPcvbBwAAAABVmTS7XpW5vbYX/6ysfs/y9gEAAABARfpmTRa5FTikP1c3jHuXtxEAAAAAKnHPyfYn+s4eVCVuZQ7oz9aNexf3MG8nAAAAAFShb/Z/VYFbpdOR/udVjXuYtxMAAAAAKjDu7G+p4lbBof0WhriXeVsBAAAAYNV4QbtkvrDhrr0kbysAAAAArJK+2Q+KslbKAf6HaT+YtxcAAAAAVoUXs5vnixqesDfn7QUAAACAVTBp9kJR0nAR+r3N2wwAAAAAe8m4sz/dN3tElrSC9p3dGaofq2jc27jHebsBAAAAYK/wMnbKfDmr7LTZ60L1Y4U9JW83AAAAAOwFk2bPEKWssvH7iF+aDuv3FPu9ztsOAAAAAMvGC9jlRxSyovbNPtV3doa/3i668Tr+2Wf/nOJenrcdAAAAAJbJZGQ/LMpYWfstu9rXT//b3FnZnf0z+fNL6vc8bz8AAAAALItJs9tkGatos0O+Pqnk/o6zH9O/rpp+z/P2AwAAAMAy8NJ14IgSVts3u7rozn5M/ZqqHsjHAAAAAACL5J799mV9Z4+LAlbSfss+5qsquL9j/hz566sZ9z6eQT4OAAAAAFgUfbPTVQGrqhfDC3yVBffT5s+Rv76i8QzycQAAAADAIjjY7DtU8Sprsxt9leX2CGc/V3+dgsazyMcCAAAAACdK39nbVemqqF/rY9Nmr/LXutjOGT83fo2/ll+vmvEs8rEAAAAAwInQN/v3qnBVddrZe3yVpfZo5q+RX6+i8Uzy8QAAAADAbvjgAft9kzag/2Cr2cRXWWaPZf5a+XXL6c8knk0+JgAAAADYKf2W/ZwsWlVt9iZfZZE9prNfq79uQePZ5GMCAAAAgJ1wsNlXq4JV1b7ZR33VJfY4za8hv35F4xnl4wIAAACA48WL1Jnzxaq457mywO7A+Brqa1f1zHxcAAAAAHA89Fv2D0Spquz1riquuzG+lvoeJY1nlY8NAAAAAI7FpNmVqlRVtG/2SN9t/2UWqrTu2Pha8TX9tfx+5fRnlY8NAAAAAJ4KL3o/IQtVUaedvdtXWVp3a35N+f0qGs8sHx8AAAAAKB7fZ0+bNLtHlamK9s3GvsqyeqLm15bft5z+zOLZ5WMEAAAAgHm8NL34iBJV28tcWVQXYHxt9T2r+uJ8jAAAAADw2fT77GtFeSrruNntvqqCujDze8jvX9F4hvk4AQAAAODTTJqdo8pTYc91ZUFdoPE91PeuqT/DfJwAAAAAEExG9kxZnIrad/Z+X1UxXbj5veR1lNSfZT5WAAAAAPCCdM0RhamoXjw/2Tc7zV/LYrpo43vF9/TX8noKek0+VgAAAIDNZtzs+aIslXXc2Tt9laV0Web3lNdT0Xim+XgBAAAANpND++0L+2YTVZYq6td6n6+yjC7b/N7yuqoZzzSebT5mAAAAgM2j37JfVUWprM0u8VUW0aU7+976ugoazzYfMwAAAMBmcV+zb1AFqarjZrf5qkvoHpnXIK+vovGM83EDAAAAbA59ZxeqclTV6che46ssoHtlXoO8vorGM87HDQAAALAZjLfsn6liVFUvbNf5KsvnXpvXIq+zovGs87EDAAAArD99sw+oUlTSZg8dGtnL/bUsnnvt9rX4Nflrfb3FjGedjx0AAABgvek721KFqKp+vW/3VZbOVZnXJK+3ovHM8/EDAAAArCcP7LM/Pmn2gCpDRb3blWWzgHFt6prr6c88nn1uAwAAAID1o+/s/8giVNRxZxf7qkrmys1rk9dd0Xj2uQ0AAAAA1ovxfvubqgCVdWS3+ipLZhln16ivv6CxB3I7AAAAAKwPk2ZvUOWnqtORneWrLphFzGuU119S3wO5HQAAAADWg76zfyGLT1H9eq/1VZbLaua1yvdR0dgLuS0AAAAAho8XnJvmC09VvYg9MGn2Mn8ti2U5/Vq3r1m8l6LelNsCAAAAYNh4sTl5ruiU1kvjW33VpbKoec3y/RT15NweAAAAAMPkoRfal3ipeXiu5FT2TleWyQEY167eU0Ufjr2R2wQAAABgeORvAVBFp6TjLbvIV1Uiy5vXLt9XSX1v5DYBAAAAGBb3NXuGLDhF7Tu72VdZIodivgf5/ioaeyS3CwAAAMBw8NJ1uSo3FfVrfXza7Ax/LQvkUIz3EO/FX8v3Wc3YI7ldAAAAAIbBeMt+WBWbqnrhutpXWR6HZr4X+T4rGnsltw0AAABAffpmt6lSU1G/1sO+ytI4VPM9yfdbzdgruW0AAAAAajPu7IAqNIV9sysL44CN96Tea0ljz+T2AQAAAKjJdJ/9+b4N5/eITpp9zFdVFIfv7L3p913M2DOxd3IbAQAAANTDC8srVZGpat/ZBb7qojhw873J913R2Du5jQAAAABqMR3Zt6sCU9ZmN/oqS+LaOHuP+v0XNPZQbicAAACAOvTN3qbKS1Ef6zt7la+6IK6J+R4fc9U9KGfsodxOAAAAADUYd/bvVHGpqheqq3yV5XDdzPcq70NFYy/ltgIAAABYLU88y36vF5Q75gtLYSeuLIVrbLxndS8qekfsqdxeAAAAAKujb/bfRFmp7JtcVQbX2XjP6l6UNPZUbi8AAACA1XB4v32VKipV9QL1UV9VEVx7873L+1LR2Fu5zQAAAAD2Hi9PZ6iSUlW/3vN8lUVw3c33Lu9LRWNv5TYDAAAA2FsOdfadqqCUtdkHfZUlcGOc3QN9fwoaeyy3GwAAAMDe4UXk3fPFpLCP9M1O91UXwA0x78EjrrpHFX13bjcAAACAvcEL07NFKSmrX++Vvsryt2nmvZD3qaKx13LbAQAAACyXu/fZ07yA3D1fSKrqRWnsqyx9m2reE3m/Cnp37LncfgAAAADLYzKyF4kyUtdml/kqC9/GOrsn+n5V1Pdcbj8AAACA5dDvs6+VRaSofbPbfdVlb8PNeyPvW0Vj7+U2BAAAAFg8Xo7OUSWkqn1n5/oqi96mm/dG3reKxt7LbQgAAACwWCb77JmqgFR1vGUf8FWWPJyZ90jev5L6HsztCAAAALA4+mbXyPJR0Waf7Ds7zV/Lgoczt++R3yt/re9jMWMP5nYEAAAAWAzjzv6DKh6Ffacryx0eYdwrdQ9LGnsxtyUAAADAiTF9vv3hvrNelY6K9s3u81UVOjyKec/k/axm7MXYk7k9AQAAAHaPl6D/oQpHYS9xZaHDoxr3TN3LksaezO0JAAAAsDumI/urqmhU1QvQbb6qIofHMO+dvK8Vjb2Z2xQAAABg53j5uWC+YFTWr/c3fJVFDp/avHfyvlY09mZuUwAAAICdMe3sn6qCUdjrXFni8LiNe6jubUljj+Z2BQAAADh++s7er8pFUR/qt+xUX1V5w+M07+FDrrrH5Yw9mtsVAAAA4Pjom+1TxaKqXnje7qssb7gz817K+1zR2Ku5bQEAAACemvtPtj/mBeL++UJR1mb3+CpLG+7S2T3V97ue98eeze0LAAAAcHT6zv63KBOVvdjVhQ13a9xTda9LGns2ty8AAACA5lBn36iKRFX7Zh/yVRU1PEHz3sr7XtHYu7mNAQAAAI7EC8Og/k3euLOzfZVFDU/MvLfyvhf14tzGAAAAAE/mULMfEOWhriO71ldZ0nBBzu6xvv8FjT2c2xkAAADgM0ya3ajKQ0mbPTDu7BR/rQsaLsTte+z32l/r51BN38O5nQEAAABmeKE5WRaHovadvdVXWc5wsea9ls+horGXc1sDAADApjN+gX1J3+xhVRoq6sXrLl9lKcPlmPdcPo9qxl6OPZ3bGwAAADaZcbOXqcJQVS9dF/kqCxkux7zn8nlUNPZ0bm8AAADYVCYj+xZVFKraN7vFV1nGcLnmvZfPpaS+t3ObAwAAwCbi5eVNsiQUtO/s8WlnZ/hrWcRwuca9j2fgr+XzqWbs7dzmAAAAsGlMmv1rVRAKe7UrSxjumfEM1LOpqe/x3O4AAACwSfSd/ZYsBzU97KrihXtvPAv1jMoZezy3OwAAAGwKk2b/SRWDqnpheYuvqnThHpvPQj6nkvpez20PAAAA6850ZH+ub/YpWQoKOm32MV9l6cLVmM9EPq9qxl6PPZ/bHwAAANaZvrPTVCGoql/vhb7KwoWrMZ+JfF4VjT2f2x8AAADWlWmzv6OKQFlnfy2xLFu4Yof0V0a7sffzGAAAAMA60g/or3Ptm/22X++r/LUuWrhS49nEM/LX8vlVM/Z+HgMAAABYN6bN/q0qAGUd2VW+ypKFRZw9I/38ChpnII8DAAAArAtPHLDP6Zt9VA3/ivq1Tn3V5QpLmc9KPsdqxhmIs5DHAgAAANaBaWc/qwZ/VfvOLvdVFiusZT4r+RwrGmchjwUAAAAMncPNvlIN/Kp6cYp/8yxLFdY0n5l8nhWNM5HHAwAAAIaMl5BXq2FfVb/e832VhQprms9MPs+KxpnI4wEAAABDxQf6d6pBX9ZmH/RVliks7uzZ6eda0DgbeUwAAABgiHj5eJca8hX14vFo3+x0f62LFJY2nl08Q38tn285/WzkMQEAAICh4cXj2XLAV7XZlb7KEoUDcfYM9fMtaJyRPC4AAAAwFO58ln1e39ndarhX1K+191WXJxyU+Szlc65mnJE4K3lsAAAAYAhMmr1IDfaqTju7zFdZnHBY5rOUz7mkflby2AAAAEB1+s7+khzoVW12u6+yNOFAnT1T/bwLGmcmjw8AAABUxof2b6hhXthzXV2YcKjGM1XPuqRxZvL4AAAAQFUmzf6xGuRV7Zt9wFdVlHDg5rOVz72kfnbyGAEAAEBF+s6ulkO8oNNmn/T1NFcWJRy8p+Uzls+/mnF28hgBAABANSZb9jw1wMs6+zN+VUHCdXFAf47ztn6G8jgBAABAFSYj+0N9s7Ec3hVtdp+vuhzhejl71nofFHP7DPlZymMFAAAAFfAh/SvzQ7u4l7i6GOG6Gc9a7YGq/koeKwAAAFg10y37K2JYV/Y2VxUiXF/jmau9UNI4U3m8AAAAYJX0nZ2vhnVh448/U2UI19dB/ZF3cabyeAEAAMCqmI7se9Wgrmrf7Dd9VUUI19x89nJfVDTOVh4zAAAAWAUDKw8P9Vt2qq+yCOF6m8/+IVftjXLG2cpjBgAAAHvNtLOT1ICuqheHd/gqSxBuhrkH5P6oaJyxPG4AAACwV9x/kn2RD+LD84O5sPe4svzgxhl7Qe2Rih6Os5bHDgAAAPaCabNfE0O5she7qvTg5hl7Qe2RksZZy2MHAAAAy2bc2TeqgVzVvtmHfFWFBzfU3BNyv1Q0zlwePwAAAFgmPngH9W/E3LNdWXhwY409ofZKVS/O4wcAAADLom/2A2IIl9Wv932+qqKDG27uDblvKhpnL48hAAAALAMftjeqIVzSZg/4eooriw5uvKfkHtH7p5hx9vIYAgAAwKKZbNl+NYCrOh3ZW31VBQdx29wjcv+U1M9gHkcAAABYFAeb/am+2Sfl8K3pXa4sN4hzxl5Re6iccQbjLOaxBAAAgEXgQzYKgRy+FZ12dpGv84UG8Qhzr8h9VNSX5rEEAACAE6Xfsm8Ww7ayt7iy1CAexdgzai+VNM5kHk8AAAA4ESbN3qiGbVEfd890VZlBPJqxZ2LvqD1VTz+TeTwBAABgt0xG9q/koK3r1a4qMojHMvaO2lM19bOZxxQAAAB2Qz+gv0Fq2tlhX1WBQTwucw/J/VXNOJt5TAEAAGCn+DD9mfnhWty3uLLAIB6nsYfU3qrqz+RxBQAAgONlss++tO/st8VgrerHXVVcEHdq7CW1x8q5fUb9rOaxBQAAgONh0uwVarBW1Qf+hb6q0oK4I3MvyX1WUj+reWwBAADgWExH9m1yoFa12U2+ytKCuCtne0rvt4LGmc3jCwAAAE+FD84r5gdpVeP/uu237NX+WhcWxF0Ye2pgv3Xnijy+AAAAcDSmnf2oGKJ1bXaVr7KsIJ6Qs72l911B4+zmMQYAAIB5rjhgn9N39hE1RCvaN5v6qksK4gLMPSb3XzXj7MYZzuMMAAAAn02/ZT+rBmhhL3dlQUFckLHH1N4raZzhPM4AAADwae5r9pVqcJa12R2+qmKCuFhne03vw4LGWc5jDQAAAEHfbf8HXXJwFvV8VxcTxMUae03twZLGWc5jDQAAAOMt+/tqYFbVB/kNvqpCgrgUc8/J/VjRONN5vAEAADabSbN3qWFZ0b7Zo9POTvfXspAgLsPYc7H3/LXcl+X0M53HGwAAYHPpO/txOSiLOm12pa+yjCAu09x7cl9WNM52HnMAAIDN444X2B/om92lhmRFfXD3vsoSgrgX5h6U+7OacbbjjOdxBwAA2Cx8GP7C/HAsbbM3+ioLCOKeONuDen/W9BfyuAMAAGwO4332F8VQrOztri4fiHtr7EW1R0saZz2PPQAAwGYwafYaNRTL2uy1vqrSgbi3zvai3qcV9bOexx4AAGD96Tv7R3IgFnXa7AO+6tKBuAJzT8r9WtE483n8AQAA1hsffO+dH4RV9QH9sK+nubJwIK7I03Jvyn1b0Pfm8QcAAFhffOD95NwArO3sz/hVRQNxtQ7oz59OfzJjAAAAYP0YH7Av8GF3cG74lbVv29eqSwZiAXOPyv1b0IORARkHAAAA68Wk2S+L4VfXkV3qqywYiCWc7VG9fyvqGZBxAAAAsD74QP56OfiK2je7zVddLhALmXtV7uOSehZkLAAAAKwHPuDOO2LgFdbLwzm+ymKBWMncq3IfF/W8jAUAAIDhM96y7xXDrqzTzn7TV1kqECuae1bu54pOm31PxgMAAMCw8cF23fygq2rf7BO+nurKQoFY1FNz78p9XdDrMh4AAACGS9/ZSWLIldXLwjt8VUUCsbS5d+W+rmhkQ8YEAADA8LjzJPuiSbPDashVdNzZvb7KEoE4BHMPy/1dTs+GyIiMCwAAgGHRN/s1OeCKOu3sYl9lgUAcgrmH5f6uaGRExgUAAMBwOLjP/oYabFXtO/uQr7I8IA7J3Mtyn1c0siJjAwAAYBj0zV6vhlpVp52d7assDohDMvey3OcVjazI2AAAAKhP39k/VwOtrM3e56ssDYiDdLan9X4vaGRGxgcAAEBtfMjeoIZZUR9wT3F1YUAcprGnY2+rPV9Pz4yMDwAAgLr0zUZykBXVr/dtvqqigDhoc2/LfV/RyI6MEQAAgHrc90L7kz6whvOH1je7y1dZEhDXwtke1/u/np+IDMk4AQAAqIUP1f8nhldZpyO7yFddEBDXwNzjcv+X1DMk4wQAAKAOfWffJAdXUftmt/gqywHiOpl7XZ6DikaWZKwAAADUwAfUZfMDq7hnurIYIK6ZsdfVGajqZRkrAAAAq2fS7IfEsCpr39k1vqpCgLiW5p6X56GknikZLwAAAKvFB9OtRwyqqjY77KssA4hr7Wzv63NRz1szXgAAAFbHZGQ/LYZUWftmV/iqiwDiGpt7X56Lknq2ZMwAAADsPXftsy+dNHtMDqmaftyVJQBxQ4wzoM5GPT1bImMybgAAAPaWvtkr5IAq6rSzC31Vwx9xI8wzIM9HRSNjMm4AAAD2joP77NvUYKpq39lNvsrhj7hJ5lmQ56SikTUZOwAAAHvDkH6/37jZp6advdpfy8GPuEnGWYgz4a/lealmZE3GDgAAwPIZd/ajaiBV1Qfle32VQx9xE80zIc9LRSNzMn4AAACWxxPfb7/Hh+RH1DCqaN/Z1Fc57BE32Twb8txUMzInsidjCAAAYDn4wPmvahAV9nJXDnrEDTfOhjozJY3syRgCAABYPPfut69QA6isze7wVQ14RAxnZ0Sfn4JGBmUcAQAALJa+2avU8CnryM73VQ94RHxpnhF9fgoaGZRxBAAAsDjGnf09NXiq2nd2g696uCPi75hnRZ6jikYWZSwBAAAsBh8w75wfOIV9dNrZr/sqBzsifsY8K4+66ixV9J0ZSwAAACdO3+xZYtjUdWRX+iqHOiIKZ2dGn6eCRiZlPAEAAOyeJw7Y7/fBcuf8oKlq31nvqx7miHhU8+zIc1XQOyObMqYAAAB2hw+//y6GTFn7Zm/0VQ5yRDy6eXbkuapoZFPGFAAAwM65v7OvUQOmqj744i+ykEMcEY9tniF5vioaGZVxBQAAsDN8kJw9P1hK2+y1vsoBjojH4ewM6fNV07MzrgAAAI6fvtl3iaFS1nFn1/uqhzciHrd5luQ5q2hkVcYWAADA8TFpdpUaKkV92IfdK32VgxsRj988Sw+76qzV07MqYwsAAODYTEb2XDlQqtrsXb7KoY2Iu3B2pvR5q6hnVsYXAADA0Rk/z77Ah9x9cpgUtO/soK96WCPirs2zJc9dOT2zIrsyxgAAADTjZr8sB0lR/Xov9VUOakTcvXm25LmraGRXxhgAAMCRTEb29WqAVLVv9mFf5ZBGxBM3z5g8fyX1DMs4AwAAeDI+1M6Tw6Oo/cjO8VUOaEQ8cfOMyfNX0ciwjDMAAIDPcLDZ96jBUdVxs/f7KoczIi7OPGvyHFY0sixjDQAAYEbf2XVqaFTUr/UThzo71V/LwYyIizPOWpw5fy3PYzUjyzLWAAAAtv8DtBeogVFVH2Tv8FUOZURcvHnm5HmsaGRaxhsAAGwyh/fbH500O6SGRUV94N7rqxzGiLg88+zJc1lOz7TItow5AADYVPpm/0sOiqo2e4OvchAj4hKdnT19Lgsa2ZYxBwAAm8ihZn9dDYjCfsjVQxgR98I4g+psljQyLuMOAAA2jb6zi9RwqOq42Wt8VcMXEffAPIPyfFY0Mi7jDgAANom+2ferwVBVH1jv81UOX0TcO/MsynNa0ci6jD0AANgUJs0+qIZCUR90T3Hl4EXEPTXOYpxJdVbr6VmXsQcAAJtA31knB0JR+2Zv81UNXERcgXkm5XmtaGRexh8AAKwzD27ZF0+aPaSGQUV9QN3tqxy2iLg682zKc1tOz7zIvoxBAABYVzz0X3LEECjsuNnrfZWDFhFXZ55NeW6L+pKMQQAAWEcO77eni/Cva7NbfJVDFhELODuj+vwWNDIw4xAAANYNH0qXqvCv6nhkZ/mqBywirtw8o/L8ltQzMOMQAADWiYPNfkgGf1H7Ztf4KocrItYxz6o8xxWNLMxYBACAdaHv7FYV+kW935VDFRFLGmdWneVyRhZmLAIAwDowbvbTKvCr6oPoCl/VMEXEguaZlee5opGJGY8AADBkJiP7s32zx1TYV7Tfsjt9lcMUEeuaZ1ee62puZ6JnY8YkAAAMlb6zU1XQV3Xa2YW+ykGKiHXNsyvPdUUjGzMmAQBgiEyafasK+MLe5MohioiDMM6wOts19YzMuAQAgKHRd/YWGe4F7bfsU369r/bXangi4gCMMxxn2V/Lc17NyMiMSwAAGBLTLfs3KtgL+15XDk9EHJRxltUZL2lkZcYmAAAMgScO2O/um92uQr2oU1cNTEQcpnGm1VkvZ2RlZGbGJwAAVKfv7L+oQK+qD5o3+6qGJSIO0DzT8rxXNDIz4xMAACpzaMu+XAV5Ye9w5bBExEEbZ1ud+ZJGdmaMAgBAVfrOfl2FeGHPd9WQRMRhG2dbnfmSRnZmjAIAQEUO7be/qwK8rM1u8FUNSERcB2dnXJ//gkaGZpwCAEA1+mbvUOFdUb/Wx/rR9r991gMSEQdvnPE46/5a5kA1I0MzTgEAoBLTzn5MBXdVfaC8x1c5HBFxfcyzLnOgopGlGasAAFCBx59nn+sB/fH5wC5s78qhiIhraZx5lQUV/XhkasYrAACsmr7Zz4uwLmvf2Zt8VcMQEdfQPPMyDyoamZrxCgAAq2Tc2deooK6qD5CP+CqHISKur3n2ZS5UNLI1YxYAAFbFZGRnqZCuqg+71/oqByEirq959mUulNSzNWMWAABWgQ+O75IBXdfrXTkEEXEjjAxQ2VDSyNiMWwAA2Gs8hK9S4VzRfsse8et9pb9Www8RN8DIgMgCfy1zopqRsRm3AACwl0y27LkqmKs67uzdvsrhh4ibY2aBzImSetZm7AIAwF5wsNkf7JvdJ0O5oH1nB32VQw8RN8/MBJkX1YysjczN+AUAgGUz7uyXVCCXtdmlvsqBh4gb6CwTdF4UNDI34xcAAJbJZMv+sgriwn7Y1cMOETfZyAaVGTX17M0YBgCAZdEP7Y/oaXaOr2rIIeImO8sGnRsFjezNGAYAgGUwGdk/UQFcVR8M7/dVDzlE3HgzI2R+lNQzOOMYAAAWjQ+F98nwrekn+pG9wlc54BARMyM+4aoMKWdkcMYxAAAskmln/1EFb1Wnzd7hqxxuiIifNrNC5khFI4szlgEAYBEceoH9kb6zqQrdot7ryqGGiCiMzFBZUs7I4sjkjGcAADhR+mb/UwVuWUf2Bl/VMENEPNJZZug8KWhkcsYzAACcCIf2219TQVvVvrPf8lUPM0TEo5jZIXOlopHNGdMAALBb+mavUyFb1mav8VUOMkTEozrLDp0rBY1szpgGAIDdMO3s+1TAVrXv7Dpf9RBDRDyGmSEyXyoaGZ1xDQAAO8WD9Pr5YC3sg32zl/sqBxgi4rHMDHnQVRlT0eszrgEAYCdMmzURqmXtO3ubr3J4ISIer5klMmcqGlmdsQ0AAMfDvVv2xR6gQ/q3Gne7cmghIu7CyBSVNRV9MDI74xsAAI6FB+dL5oK0tH2z1/uqhhUi4o7NTJF5U9SXZHwDAMBT0W/Z00WIlrXv7FZf5bBCRNytmS0ydyoa2Z0xDgAAR2Pc7FIVomUd2Vm+ykGFiLhrZ9mic6egkd0Z4wAAoOg7+5cqQMva7Bpf9ZBCRDxRZxmj86egkeEZ5wAAME/f7BYVnkW9fzISgwkRcVHOMuZ+V2VQOSPDM84BAOCz8ZD8qfnQLO4V7pGDCRFxsUbWqAyq6k9lrAMAQNCfZH+m7+xREZhVvdNVAwkRcRlG5qgsKmdkeWR6xjsAAExmfxuQDM2KepC/zlc1jBARF25mjsyjknqmZ7wDAGw2k5H9bRmURZ12dpOvchghIi7LzB6ZSyX1bM+YBwDYXPpmb5YhWdFmn/LrPcNfy0GEiLgst7PHM8hf63wqZmR7xjwAwGbiYfgj8+FY3Pe6cgghIu6BkUEqm6r6Ixn3AACbxRNP2O/qO/uwCMaaNjvkqxo8iIh75yyLdE4VMzI+sj5jHwBgc5g2+88qGAsbv8VCDx5ExL1zOL/dy42sz9gHANgMDu23L1OBWNZmH/NVDRxExL13lkk6rwoamZ/xDwCw/kw7O12FYVX7Zhf4qgcOIuIem5kk86qikfkZ/wAA68202XeoICzsDa4cNoiIKzSySWVWSSP7cwwAAKwvfWdvVyFY0maP9c1e5a/VkEFEXJnb2eQZ5a91fhUzsj/HAADAeuJB92MqAMva7D2+yiGDiLhyZxml86ugMQNyHAAArBe3Ps8+d0j/AUXfbOKrHi6IiEXMrJI5Vk6fATELciwAAKwPHsY/L4OvqH69b/JVDhZExCpmVskcq2jMghwLAADrwcGT7C+owKuqB/FHfZVDBRGxmplZMs8qGjMhxwMAwPCZNDtLhV1ZR/ZaX+VAQUQs5yyzdJ5V1GdCjgcAgGHTd/YPZdAVddrZ9b7qYYKIWNTMLplrFY3ZkGMCAGC49EP6r4KbPTJt9kp/LQcJImJVt7PLM8xf63wrZsyGHBMAAMPEQ/c5KuAK+25XDhFExAEYGaayraY+I3JcAAAMi3sP2Of3nd0rw62iIzvoqxociIjDcZZlOueKGTMiZkWODQCA4eCf1H9RBVthL3P14EBEHI6RZSrjauqzIscGAMAw8E/pXycDra4fdtXAQEQcopFpKutKGjMjxwcAQH08uM6dD7LSNjvHVzUsEBGH5yzTdN7V9NwcHwAAtfGA/W4RYmXtO3u/r3pYICIO1Mw2mXsl9dmRYwQAoC4ertfKEKtos0+6r/DXclAgIg7WyLbIOJV9BY3ZkWMEAKAmHqrPVwFW1mbv9FUPCUTEoTvLOJ1/FfUZkuMEAKAWh/bbF/bNJjK8ahp/9JkeDoiI6+Ng/pjHmCExS3KsAADUYdrZr6rgKmuzS3xVQwERcX2cZZ3OwYLGLMmxAgBQg2mzb1CBVdjfcvVQQERcPyPzVBaWNGZKjhcAgNXjn8AvVGFV1pG9xlc1DBAR189Z5uk8LGjMlBwvAACrZdzZ96mgqmrf7Dpf9TBARFxTM/tkLlY0ZkuOGQCA1TFpdr0KqYp60D/k1/tyfy0HASLi2urZt52BIhtL6rMlxwwAwGrw0GwyoIo67extvuohgIi45mYGynysaMyYHDcAAHvLPSfbn+g7e1CFU0mb3e2rDH9ExI1xloU6J4sZMyZmTY4dAIC9wz9p/18VTFWddvZ6X3XwIyJuiJmFMicrGrMmxw4AwN4w7uxvqUAq7K2uDH1ExA00MlFlZUlj5uT4AQBYPh48g/oDyCfNzvJVhT0i4uY5y0SdlzW9JMcPAMBy6Zv9oAihyl7r6rBHRNxcIxtVZpY0Zk+OIQCA5eGBc/N8ABX2/kmzl/mqQh4RcXOdZeP9rsrOit6cYwgAYDl4ML5QhE9dm13hqw55RMRNd5aROj8r6jMoxxEAwGIZd/an+2aPyPApaN/Znb7qcEdExG0zK2WOVjNmUMyiHEsAAIvDQ+aU+dCp7LTZ63yVwY6IiDMzK2WOFvWUHEsAAIth0uwZImwqG7+PWIY6IiIe4ZD+24v4LQzPyPEEAHDieLBcfkTQFLVv9qm+szP8tQpzREScMzIzstNfy1wt6OU5ngAATozJyH5YhExZ+y272lcZ5oiIqM3slLlaUp9NOaYAAHbPpNltMmQq2uyQrzLEERHxGM4yVOdrNX025ZgCANgdHiYHjgiX2r7Z1QGOiIjHMjJUZWtVD+S4AgDYGffsty/rO3tcBEtJ+y37mK8quBER8TjNLJU5W82YUTGrcmwBABw/fbPTVbBU1QPvAl9lcCMi4vGZWSpztqIxq3JsAQAcHwebfYcKlLI2u9FXGdqIiLhDZ5mq87agMbNyfAEAHBv/RP92FSYV9Wt9bNrsVf5aBzYiIu7IyNTIVn8tc7eaMbNyfAEAPDV9s3+vgqSq087e46sMa0RE3J2ZrTJ3KxqzK8cYAIDmgwfs903agP5DhGYTX2VIIyLiiZkZK/O3nD67YoblOAMAOJJ+y35OBkhVm73JVxnQiIh4gs4yVudvQWOG5TgDAHgyB5t9tQqOqvbNPuqrDmdERFyImbUyhysasyzHGgDAZ/CAOHM+MIp7niuDGRERF2Zkrcrgqp6ZYw0AYEa/Zf9AhEVlr3dVICMi4uKNzFVZXNKYaTneAADMJs2uVGFR0b7ZI323/ZdZqDBGRMQFG5kb2euvZS6X02dajjcA2HQ8wH5CBkVRp52921cZxoiIuBwze2UuVzRmW445ANhUHt9nT/NPvveokKho32zsqwxhRERcrpnBMp/L6bMtZlyOOwDYRDwMXnxEONT2MlcGMCIiLt3IYJXNVX1xjjsA2DT6ffa1IhTKOm52u68qeBERcY/MLJY5XdGYdTn2AGCTmDQ7R4VCYc91ZfAiIuKeGVmsMrqmPuty7AHApjAZ2TNlIBS17+z9vqrARUTEPTYzWeZ1SX3m5fgDgE3AD/41RwRBUT1QP9k3O81fy8BFRMS9NTI5stlfy9wu6DU5/gBg3Rk3e74IgbKOO3unrzJsERFxNWY2y9yuaMy+HIMAsK4c2m9f6J/EJyoEKurXep+vMmQREXG1ZkbL/K5mzL6YgTkOAWAd6bfsV1UAlLXZJb7KgEVExBU7y2id3wWNGZjjEADWjfuafYM6+FUdN7vNVx2uiIhYwsxqmeMVjVmYYxEA1om+swvVoa/qdGSv8VUGKyIi1jCzWuZ4RWMW5lgEgHVhvGX/TB34qnoQXeerDFVERKxlZrbM84rGTMzxCADrQN/sA+qwl7TZQ4dG9nJ/LQMVERFruZ3Znt3+Wud6MWMm5ngEgKHjn7S31EGvql/v232VYYqIiDXN7Ja5XtGYjTkmAWCoPLDP/rh/yn5AHfKi3u3KEEVExPJGhqtsr6fPxpiROS4BYIj4J9b/Iw94UcedXeyrCk9ERCxuZrjM94rGjMxxCQBDY7zf/qY62GUd2a2+yvBERMSBOMtynfMFjVmZYxMAhsSk2RvUoa7qdGRn+aqDExERB2Fmucz5kvqszLEJAEOh7+xfyANdVL/ea32VoYmIiMMyM13mfUVjZub4BIAh4Af3pvmDXFUPmAf8E/XL/LUMTEREHJie6dvZLjK/qDfl+ASA6viBPXnuAJfWw/CtvuqwRETEQZrZLnO/qCfnGAWAqjz0QvsSP6wPzx3eyt7pypBERMTBGxmvsr+iD8cMzXEKABXJ3wKgDnBJx1t2ka8qHBERceBmxsv8L6nP0BynAFCN+5o9Qx7covad3eyrDEdERFwPM+vlHKhozNIcqwBQCQ+Ty9Whrahf6+PTZmf4axmMiIi4HkbWR+b7azkPqhmzNMcqAFRhvGU/rA5sVT1IrvZVhiIiIq6XmflyHlQ0ZmqOVwCoQN/sNnVYK+rXethXGYaIiLieZvbLuVDNmKk5XgFg1Yw7O6AOamHf7MogRETEtTWyX82EksZszTELAKtius/+vH/yHMzvfZo0+5ivKgAREXHdnc0APR+KGbM1ZmyOWwBYBX4QX6kOaFX7zi7wVQcgIiKutTkD5HyoaMzYHLcAsNdMR/bt6mCWtdmNvsrwQ0TEDXE2C/ScKGjM2hy7ALCX+CfNt6lDWdTH/JP8q3zVwYeIiBthzoLHXDUryhmzNscuAOwV487+nTqQVfWguMpXGXqIiLhZ5kyQ86KiMXNz/ALAsnniWfZ7/eDdMX8QCztxZdghIuLGGrNBzYyK3hGzN8cwACwT/yT838QhrOybXBVyiIi4ucZsUDOjpDF7cwwDwLI4vN++Sh3AqnowfNRXFXCIiLjh5oyQ86OiMYNzHAPAMvBQOEMdvqr69Z7nqww4RETcbHNGyPlR0ZjBOY4BYNEc6uw71cEra7MP+irDDRERcdvZrNBzpKAxi3MsA8Ai8QP27vkDV9hH/JPv6b7qYENERHRzVjziqllS0XfnWAaAReFB8Gxx2Mrq13ulrzLUEBERP9ucGXKeVDRmco5nADhR7t5nT/ODdff8QauqB8DYVxlmiIiIypwdcq4U9O6YzTmmAeBEmIzsReKQ1bXZZb7KIENERJTOZoeeKxX12ZxjGgB2S7/PvlYesKL6J/LbfdUhhoiI+BTmDJHzpaIxo3NcA8Bu8EN/jjpcVe07O9dXGWCIiIhPZc4QOV8qGjM6xzUA7JTJPnumOlhVHW/ZB3yV4YWIiHg85iyRc6akPqtzbAPATvBPitfIQ1XRZp/0T+Kn+WsZXIiIiMfj9izxmeKv9bwpZszqHNsAcLyMO/sP6kAV9p2uDC1ERMQdGjNFzZqSxszO8Q0Ax2L6fPvD/om2V4epov5p9j5fVVAhIiLuypwtcu5UM2Z2zO4c4wDwVPjh/h/qIBX2ElcGFSIi4i6N2aJmTkljducYB4CjMR3ZX1UHqKp+sG/zVQUUIiLiCZkzRs6fisYMz3EOAAo/1BfMH5zK+vX+hq8yoBAREU/EnDFy/lQ0ZniOcwCYZ9rZP1UHp7DXuTKcEBERF2TMGjWDShqzPMc6AHw2fWfvV4emqA/1W3aqryqUEBERF2LOmodcNYvKGbM8xzoAfJq+2T51YKrqB/ntvspQQkREXKQ5c+Q8qmjM9BzvAHD/yfbH/GDcP39QytrsHl9lGCEiIi7F2ezRc6me98dszzEPsNn4J9X/LQ5JZS92dRAhIiIux5g9aiaVNGZ7jnmAzeVQZ9+oDkhV+2Yf8lUFECIi4lLNGSTnU0Vjxue4B9hM/CAM6hPquLOzfZUBhIiIuExzBsn5VNSLc9wDbB6Hmv2AOBR1Hdm1vsrwQURE3BNns0jPqYLGrM+xD7BZTJrdqA5FSZs94J+kT/HXOngQERH3wO1Z5DPJX+t5VU2f9Tn2ATYHP6gnywNR1L6zt/oqQwcREXEvzZkk51VFY+bn+AdYf8YvsC/pmz2sDkNFPVDu8lWGDSIi4irM2STnVjVj5sfszxoAsN6Mm71MHYSqephc5KsMGkRExFWYs0nOrYrG7M8aALC+TEb2LeoAVNU/hd7iqwwZRETEVZozSs6vknoHyDoAsJ74oXyT3PwF9U/Lj087O8Nfy4BBRERcpTGjYlb5aznHqhkdIOsAwPoxafav1cYv7NWuDBdERMQixqxSM6ym3gWyFgCsF/6p87fkpq/pYVcFCiIiYjVjZqlZVs7oAlkLANYH/wT3n9SGr6ofxLf4qsIEERGxlDmz5DwrqXeCrAcAw2c6sj/XN/uU3OwFnTb7mK8yTBARESuas0vOtWpGJ4hukDUBYNj4J83T1Eavql/vhb7KIEFERKxozi451yoa3SBrAsBw8U+Yf0dt8LLO/lpiGSKIiIilHdJfre9GR8i6ADBM/BPbYP6awr7Zb/v1vspf6wBBREQsbMywmGX+Ws65akZHyLoAMDz8k9q/VRu7rCO7ylcZHoiIiINwNsv0nCtodIWsDQDD4YkD9jn+qfKjalNX1K916qsODURExAGZM03Ou2pGV4jOkPUBYBhMO/tZtaGr2nd2ua8yMBAREYdkzjQ57yoanSHrA0B9Djf7SrWRq+qBEP/mWYYFIiLiEM3ZJudeRaM7ZI0AqI0frlerTVxVv97zfZVBgYiIOERztsm5V9HoDlkjAOriG/U71QYua7MP+ipDAhERcdDOZpyefwWNDpF1AqAmfqjepTZvRf1APdo3O91f64BAREQcsDHjYtb5azkHy+kdIusEQD38QD1bbtyqNrvSVxkOiIiIa+Fs1uk5WNDoElkrAOpw57Ps8/xT491q01bUr7X3VYcCIiLiGpkzT87DakaXiE6R9QKgBv6J8UVqw1Z12tllvspAQEREXCdz5sl5WFLvFFkvAFaPf/r6S3KjVrXZ7b7KMEBERFxLZ7NPz8WCRrfImgGwWnwz/obapIU919VBgIiIuJ7G7FMzsaTRLbJmAKwO/4T4j9UGrWrf7AO+qgBARERca3MGyvlYUu8YWTcAVoN/4rpabs6CTpt90tfTXBkAiIiIa+5pOQvlnKxmdIysGwB7z2TLnqc2Zllnf8avOviIiIib4YD+vPttvWtk7QDYOyYj+0N9s7HclBVtdp+v+tAjIiJukrOZqOdlMbe7hneOrB8Ae4Nvvl+Z34zFvcTVBx4REXGzjJmoZmVVfyXrB8DymW7ZXxGbsLK3ueqgIyIibqoxG9XMLGl0j6whAMul7+x8tQkLG3/8mTrkiIiIm+qg/mjQ6B5ZQwCWx3Rk36s2YFX7Zr/pqzrgiIiIG23OSDk/KxodJOsIwHIY2KF4qN+yU32VBxwREXGTzRn5kKtmaDmjg2QdAVg8085OUhuvqn4g3uGrPNyIiIi4/W91Y1bKOVrR6CJZSwAWx/0n2Rf5Bjs8v+EKe48rDzUiIiI+yZiZapZW9HB0kqwnAIth2uzXxGar7MWuOsyIiIj4ZGNmqlla0ugkWU8ATpxxZ9+oNlpV+2Yf8lUdZERERBTm7JRztaLRTbKmAJwYvqEG9UnPPduVBxkRERGlMTvVTK3qxVlTAHaPf8L7AbG5yurX+z5f1QFGRETEpzBnqJyvFY2OknUFYHf4JrpRba6SNnvA11NceYARERHxKT0lZ6mes8WMjpJ1BWDnTLZsv9pYVZ2O7K2+qoOLiIiIx2HOUjlnS+pdJWsLwPFzsNmf8k9Kn5SbqqZ3ufLQIiIi4o6MmapmbTmjq0RnyfoCcHz45omNLjdVRaedXeTr/EFFRETEHZozVc7bor406wvAsem37JvFJqrsLa48rIiIiLgrY7aqmVvS6C5ZYwCemkmzN6pNVNTH3TNddUgRERFxd8ZsjRmrZm89vbtkjQE4OpOR/Su5gep6tasOKCIiIp6YMWPV7K2pd5isMwCafkB/M8q0s8O+qoOJiIiICzBnrZzD1YwOk3UG4Eh8k/zM/KYp7ltceTARERFxIcasVTO4qj+TtQbgM0z22Zf2nf222DBV/birDiQiIiIu1pi5ahaXc7vLeKfJegMwY9LsFWrDVNU38oW+qsOIiIiICzRnrpzHJfVOk/UGwGw6sm+TG6WqzW7yVR5GREREXIKz2avnckGj22TNgU3HN8QV8xukqvF/SfRb9mp/rQ8iIiIiLtyYvQP7LY5XZM2BTWba2Y+KzVHXZlf5Kg8hIiIiLtHZDNbzuaDRcbLuwCZyxQH7HP909hG1OSraN5v6qg8fIiIiLt2cxXJOVzM6TnSdrD2wafRb9rNqYxT2clcePERERNwTYxarGV3S6DpZe2CTuK/ZV6oNUdZmd/iqDhwiIiLupbOZrOd1QaPzZP2BTaHvtv+DLrkhinq+qw8cIiIi7qUxk9WsLml0nqw/sAmMt+zvq41QVd+gN/iqDhoiIiKuwJzNcm5XNLpP1iBYdybN3qU2QUX7Zo9OOzvdX8uDhoiIiHtvzOaY0f5azu9yevfJGgTrjH8C+3G5AYo6bXalr/KQISIi4urMGS3nd0WjA2UdgnXkjhfYH/BPX3eph19R35C9r/JwISIi4urNWS3neDWjA0UXyloE64Y/5F+Yf+ilbfZGX+XBQkRExALOZrWe4zX9haxFsE6M99lfFA+7sre7+lAhIiJiJWNmq1le0uhEWY9gXfBPXK9RD7uszV7rqzpMiIiIWMnZzNbzvKLeibIewTrQd/aP5IMu6rTZB3zVhwkRERHLmbNbzvWKRjfKmgRDxx/oe+cfcFV94z3s62muPEiIiIhY0tNyhsv5XtD3Zk2CIeMP8ifnHmxtZ3/GrzpAiIiIWNkB/Tn96U9mXYIhMj5gX+AP8eDcQy1r37avVR8eRERELG/OcjnnC3owulLWJhga/snql8VDrevILvVVHhxEREQcgLNZrud8Rb0rZW2CIeEb7evlAy2qfwK8zVd9aBAREXEw5kyX876k3pmyPsFQ8Ad33hEPsrB+KM7xVR4YREREHI450+W8L+p5WZ9gCIy37HvFQyzrtLPf9FUeFkRERByeOdvl3K9odKesUVAdf2DXzT/Aqvqnvk/4eqorDwoiIiIO0lNzxsv5X9DrskZBZfrOThIPr6x+CN7hqzogiIiIOGBzxsv5X9HoUFmnoCJ3nmRfNGl2WD28io47u9dXeTgQERFx+Oaslz2gnN6hoktlrYJq+CenX5MPrqjTzi72VR4MREREHL4562UPqGh0qaxVUImD++xvqAdW1b6zD/kqDwUiIiKujznzZR+oaHSqrFdQBf8E8nr1sKrqn/DO9lUeCERERFwfc+bLPlDR6FRZr6AC/knpn6sHVdZm7/NVHgZERERcQ2ezX/eCgka3ypoFq8Y3zw3qIRX1AfcUVx8EREREXEdj9kcHUN2gnt6tsmbBKumbjeQDKqpf79t8VQcAERER19jsALIfVDQ6VtYtWAX3vdD+pD+I4fxhzM3u8lVufkRERNwAZ11A94R6fiK6VtYu2Gt8s/w/8VDKOh3ZRb7qjY+IiIhrb3YB2RNK6l0raxfsJX1n3yQfSFH7Zrf4Kjc9IiIibo7ZCWRfqGh0rqxfsFf4jb9s/kEU90xXbnhERETcKKMTqK5Q1cuyfsFeMGn2Q+IhlNU/CV3jq9roiIiIuIFmN5C9oaTevbKGwbLxG37rEQ+gqs0O+yo3OSIiIm6ws46g+0M9b80aBstkMrKfFje/rH2zK3zVGxwRERE31uwIsj+U1DtY1jFYBnftsy/1Tz+PyZtf04+7cnMjIiIiutEVVIeop3ew6GJZy2DR+CefV8gbX9RpZxf6qjY1IiIi4kuzK8geUdHoYlnLYJEc3Gffpm54VfvObvJVbmpERETET5udQfaJikYny3oGi2JIv49l3OxT/gnt1f5abmhERETETxudIbqDv5a9oprRybKewSIYd/aj6kZX1TfAe32VmxkRERFx3uwOsldUNLpZ1jQ4EZ74fvs9/vA/om5yRfvOpr7KTYyIiIh4NLNDyH5Rzehm0dGyrsFu8Rv5X9UNLuzlrtzAiIiIiE9hdAjVLUoaHS3rGuyGe/fbV6gbW9Zmd/iqNi4iIiLisZ11Cd0zChpdLWsb7BT/pPAqdVPLOrLzfdUbFxEREfFYzrqE7hkFja6WtQ12wrizv6duaFX7zm7wVW9aRERExOM0O4XsGxWNzpb1DY4Xv3HvnL+RhX102tmv+yo3LCIiIuLxmp3iUVd1joq+M+sbHA99s2eJm1jXkV3pq9ysiIiIiDt21i107yhodLescfBUPHHAfr/fsDvnb2BV+856X/UmRURERNyl2TFk/yjondHhss7B0fCH+t/FzSurf4J5o69ygyIiIiLu1uwYsn9UNDpc1jlQ3N/Z16gbV1V/oPEXWcjNiYiIiHiiZteQPaSi0eWy1sE8foPOnr9hpW32Wl/lxkREREQ8YWddQ/eQmp6dtQ4+m77Zd4mbVdZxZ9f7qjclIiIi4oLMziH7SEWj02W9g0/jn1iuUjerqA/7Q3ylr3JDIiIiIi7K7BwPu6qT1NM7XdY7CCYje668UVVt9i5f5WZEREREXLiz7qF7SUW922XN22zGz7Mv8Id3n7xJBe07O+ir3oSIiIiISzI7iOwn5fRuFx0v697mMm72y/IGFdWv91Jf5QZEREREXJbZQWQ/qWh0vKx7m8lkZF+vbkxV+2Yf9lVuPkRERMRlm11E9pSSetfL2rd5+MM6T96UovYjO8dXufEQERERl212EdlTKhpdL2vfZnGw2feoG1LVcbP3+yo3HSIiIuJemZ1E9pWKRufL+rc59J1dp25GRf1aP3Gos1P9tdxwiIiIiHtldJLoJv5a9pZqRufL+rcZ+CeRF6gbUVV/QO/wVW42RERExL02u4nsLRWN7pc1cL05vN/+6KTZIXUTKuob6V5f5SZDREREXJXZUWR/Kad3v+iAWQfXl77Z/5I3oKrN3uCr3GCIiIiIK3PWUXR/KWh0wKyD68mhZn9dvfHCfsjVmwsRERFx9UZXUR2mpNEFsxauH31nF6k3XdVxs9f4qjYVIiIi4srNriJ7TEWjC2YtXC/6Zt+v3nBV/UG8z1e5qRARERGrmJ1F9pmKRifMerg+TJp9UL3Zoj7onuLKDYWIiIhYyOgs0V1Up6mnd8Ksh+uBf9Lo5Bstqn/SeJuvaiMhIiIiljO7i+w1FY1umDVx2Dy4ZV/szf0h9SYr6jf+bl/lJkJERESsanYY2W/K6d0wOmLWxeHib+YlR7y5wo6bvd5XuYEQERERq5odRvabor4k6+IwObzfni7eVF2b3eKr3DyIiIiI5Z11Gd1zChpdMWvj8PCbfal6U1Udj+wsX/XGQURERCxudhnZc0rqXTFr47A42OyH5Bsqat/sGl/lpkFEREQcitlpZN+paHTGrI/Doe/sVvVminq/KzcLIiIi4gCNbqM6TzmjM2Z9HAbjZj+t3khV/QZf4avaJIiIiIiDM7uN7D0Vje6YNbI2k5H92b7ZY+pNVLTfsjt9lZsEERERcahmx5H9p5rb3dE7ZNbJuvgniFPVG6jqtLMLfZUbBBEREXGoZseR/aei0SGzTtZk0uxb1YUX9iZXbg5ERETENTC6jupANfUumbWyHt7E3yIvuqD9ln3Kr/fV/lptCkRERMTBG10nOo+/ln2omtEls1bWYrpl/0ZdcGHf68pNgYiIiLhGRudRXaik0SmzXtbgiQP2u/tmt6uLLerUVRsBERERcR2N7qM6UTmjU0a3zJq5evrO/ou60Kr6DXyzr2oTICIiIq6d2X1kL6podMusmavl0JZ9ubrAwt7hyk2AiIiIuMZGB1LdqKTRMbNurg5v3L+uLq6w57vq4SMiIiKus9GBVDcqaXTMrJur4dB++7vqwsra7AZf1YNHREREXH9nXUj3pIJG18zauff0zd6hLqqifq2P9aPtf/usHzwiIiLimhtdKDqRv5Z9qZrRNbN27i3Tzn5MXVBV/Ua9x1f50BERERE3xexEsi9VNDpn1s+94fHn2ef6N/74/IUUtnflw0ZERETcQKMbqc5U0Y9H98waunz8k8DPi4soa9/Zm3xVDxkRERFx48xuJHtTRaN7Zg1dLuPOvkZdQFX9xnzEV/mQERERETfV7EiyP1U0OmjW0eUxGdlZ6ptX1R/ia32VDxgRERFxU82OJPtTSb2DZh1dDn5Dvkt+47pe78qHi4iIiIjbXUl1qJJGF81aunj8i1+lvmlF+y17xK/3lf5aPVRERETEjTe6UnQmfy37VDWji2YtXSyTLXuu+oZVHXf2bl/lQ0VERETEmdmZZJ8qqXfSrKeL4WCzP+gN+j75zQrad3bQV/kwEREREfHJZneSvaqa0Umjm2ZNPXG86f+S+kZlbXapr/JBIiIiIuKcs+6ke1VBo5tmTT0xJlv2l9U3KOyHXf0QEREREfFoRodS3aqm3lGzru6efmh/9ESzc3xVDw8RERERj+asQ+l+VdDoqFlXd8dkZP9EfWFERERExJXrXTVr687xpvw++UUREREREVdsdNWsrTtj2tl/VF8QEREREbGK0Vmzvh4fh15gf6TvbKq+GCIiIiJiFaOzRnfNGnts+mb/U30hRERERMRqRnfNGvvUHNpvf019AURERETEqkaHzTp7dLwRv079YkRERETEqkaHzTqrmXb2feoXIiIiIiJWN7ps1toj8Z9w/fwvQEREREQciNdnrX0y02ZN/GRERERExMEYnTbr7WfwH7h5/iciIiIiIg7Mm7PezpiM7JniJyEiIiIiDk/vtllzt/+khfPkT0JEREREHJjRbbdL7qEt+3L1ExARERERh2p03PhtC89VP4iIiIiIOFi948Z/hPZLR/wAIiIiIuKAHXvHjd+f+1r1g4iIiIiIA/Zc6zu7VvwAIiIiIuJgjY4b/0Z3on4QEREREXGoRseNf6M7VT+IiIiIiDhUo+PGv9F9n/pBRERERMShGh2X/xgNEREREdfRc23S7BfFDyAiIiIiDlfvuFF0nyN/EBERERFxqHrHtUP77SvkDyIiIiIiDtTouBb4/zhv/gcREREREYdo39n52yU3mOyzZ6qfhIiIiIg4OEf2zKy5M/pmN8mfiIiIiIg4EKPTZr39DNPOttRPRkREREQcitFps94+Gf/BM+d/MiIiIiLiQDwza+2R3L3PnjZp9kHxixARERERy9o3uyG6bNZaTb9lT1e/GBERERGxqtFhs84+NYc6+3H1BRARERERqxndNWvs8TEZ2bdMmt2ovhgiIiIi4sr1rtpv2Tdnfd0Z9z7HPt+/wFnyCyMiIiIirsixd9Toqllbd0/fWedf8Ob5b4CIiIiIuMfeHN00a+rimDT77r7ZBXPfDBERERFxqW53UO+iWUuXx+H99lX+zZ7t3/TF/g3P8VZ9rf/vyfwFISIiIiLuxOiU0S2jY469a0bnPNjsq7OG7gCz/w/rFSSiaAwoOQAAAABJRU5ErkJggg==\",\"data:image/png;base64,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\",\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAroAAAJkCAYAAAD+yYJGAAAAAXNSR0IArs4c6QAAAARnQU1BAACxjwv8YQUAAAAJcEhZcwAAMsAAADLAAShkWtsAAEc4SURBVHhe7d0LvKVXedfxUavVUluBzF7vCQja0tZqFa1apVCtVq1WqW2tVq1Sq9bSUkUrVNFqW1tR2lJbq2IJIYRcIZALIZArM3u9eyYJuZGEJCQ0CbnM7LX35AoEEkIS1/POE5Ps85/JOWfOPvt59/79Pp/vh36YZOac/b7rWc+kJNlFRETb372j47+pDJvXl7Z5W2nTWSWnayY5PWDs/7b/bmo/Vv8Y+2P9TyMiIiIiilkZDb63LrPnTtrmqU2pf479uf7TEBERERHFaDJKb67L6i1yid0M+znqz+U/LRERERHRYprs2f3VdUE9Y93CeuzOsJ/bfxkiIiIiop1rktdePWnTzWJJ3Sb15867X+2/HBERERHR/Jvk5if0cjoH9dfyX5aIiIiIaH5Nhru/XS6k81R/Tf/liYiIiIi2vwNXr31VadNNchmdI/s17df2L4OIiIiIaHub5OY0tYjuiPpr+5dBRERERLR9df8IMbWA7iT+0WNEREREtJ1N9uxu6qL5+XWL5877vH0t/mURERERER1bk5zeIZbOxahfi39ZRERERERbr+wdvEounAtkX5N/eUREREREW6vkdKFaNhfJvib/8oiIiIiINl9pB/9QLZoR2NfmXyYRERER0eYqbbpVLZkR2NfmXyYRERER0cYrufmPasGMxL5G/3KJiIiIiJ6/e4fH/8GS05fUchmJfY32tfqXTURERER09Ca5eZdaLEOqX6t/2URERERER246bP6CXCgDs6/Zv3wiIiIiIl1dHC+bXSR74DL/8omIiIiI1lcXxh+ZWSD75Ef82yAiIiIieqanntr1O+qyeMfM8tgnd9j34N8OEREREdHhJm36ebE89kz6ef92iIiIiIi6fwPa1+nFsX/se/Fvi4iIiIhWvZLTyWpp7CP7XvzbIiIiIqJV7tC+wXephbHP7Hvyb4+IiIiIVrVJm7JaFvstZf/2iIiIiGgVK3nwY3pR7D/73vzbJCIiIqJV6raPvOIrJ226Ry2JR1LEfxdXuse+R/92iYiIiGhVKrl5q14Qj6xfi679Vd3mrf7tEhEREdEqdGDP2h9Ri+FG9G3Zte/Vv20iIiIiWvbKsDlDLYXLyL5X/7aJiIiIaJmbts3fUAvhZtSfQ/73Udn37N8+ERERES1rdfG7YnYR3CxbdKftmvyxoK7wb5+IiIiIlrFJbn5SLIFb0re/qmvfu38MRERERLRMTfbs/uq67E3kErhFvVp27Xuvn4F/HERERES0LJWcfkUugMdiJP67wOwz8I+DiIiIiJahsnfwx9Xit4rss/CPhYiIiIj6XmnTB9TSt4rss/CPhYiIiIj6XBkNvlctfKvMPhP/eIiIiIior5U2XaOWvVVmn4l/PERERETUx6bt4I1q0YP9EyMGb/SPiYiIiIj61EPty144yekBteShqp+NfUb+cRERERFRX5rk5tflgjdHJev/Pqz6GfnHRURERER9aLp/7VvlYrcDivjvIrPPyj82IiIiIopeXeDOm13ocETn+cdGRERERJE7mJsfFMscjsI+M//4iIiIiChqJTc3qmVuJ027fzVwWvffR2WfmX98RERERBSxyTC9WS1yi3B42e2R+tn5x0hEREREkSqXDtIkN5+XSxyeX/3s7DP0j5OIiIiIolTa9H/kAocNs8/QP04iIiIiilBpB39eLW7YPPss/WMlIiIiokVX2vRRtbRh8+yz9I+ViIiIiBZZyYN/oBY2bJ19pv7xEhEREdGiKjl9Si1r2Dr7TP3jJSIiIqJFNM2D/6AWNRw7+2z9YyYiIiKiney+K17y0klOj6klLaTcHOioH4uofrb2GfvHTUREREQ7VV3GTli3nEWWmw911I/FdYJ/3ERERES0E01Ha98hlrKwuv8dcU6/Zfr2vym2z9o/diIiIiKad3UBu3R2IYuqtM0TdcE97elF1/7v7r8Tf2xQl/rHTkRERETzrC5er5tZxEIrOV31rCX36b+qe5X6YwN7nX/8RERERDSvJrm5XSxiIZU2PTS75D6t+zHx54RUP3P/+ImIiIhoHpXc/JxcxKLKzWVqyT2s/pj6c4Kyz94fAxERERFtZ6UdfF1pmyfVEhZRyekeveA+o/tjxJ8bkX329gz8cRARERHRdlWXwpPVAhZWTufOLrbCufLPDcqegT8OIiIiItqOSh58l1q8wsrp5pmF9mhulj9HUPYs/LEQERER0bFWcspq6YqotOnxSZtOEQutVv/Yw3+O/vmisWfhj4WIiIiIjqUyHPxztXCFNWqukAvt0difo36uoOyZ+OMhIiIioq30yffv+j29+hu2hukBuchuQPfnip8zInsm9mz8MRERERHRZhu36b+qRSusnC6ZXWA34RL5cwZlz8YfExERERFtpkOj479JLVhh5XTXzOK6FXfJnzsoe0b+uIiIiIhoo9VF6vTZxSq0nM6eWVq34mz5c8d1uj8uIiIiItpIk9z8dbFUhTVtmxvF0rol3c8lfo2w6rPyx0ZEREREz1ddni6XS1VMj9m/SEEtrVvR/Vz155z5NeKqz8ofGxEREREdrbo4/YRcqKLKzX61sB6b+nOqXyuq+sz88RERERGRavyJ9IK6NBW5TAVUcrpPL6rHrvu5xa8ZUn1m9uz8MRIRERHRbKVtflkuUkHVZfQitaRuh+7nFr9mVPbs/DESERER0bO7f1/6FrVARVXy4E61oG6n7tcQv3ZU9gz9cRIRERHR003bdJZanqKqS+gH1HK6nbpfQ/zaUdkz9MdJRERERNahNr1WLU5R1YXuerWYzkP3a4mvISp7lv5YiYiIiGjSpqvV0hRT+uLBPDhJLaXz0P1a9dfUX0tE6Wp/rERERESrXWkHb9QLU0xlmEZqIZ2n7tcUX0tU9kz98RIRERGtZne1L3thyekBtSxFVBfOqVpEd0L3a4uvKSJ7pvZs/TETERERrV7j3Py6WpSiKm36qFpCd0L3a4uvKSp7tv6YiYiIiFarA8O1b1ULUlTjYXO7WkB3Uvc1iK8tKnvG/riJiIiIVqdxbs5Ty1FYo+Z9avncUfY1qK8tKHvG/riJiIiIVqPJsPk7ajGKato218nFcwG6r0V8jWHVZ+2PnYiIiGj5m+TmBrkURZTTI/Xrfdfswrk43dfyiPxaI6rP2h87ERER0XJXl583rVuGAis55fXL5mJ1X5P4WgN7kz9+IiIiouVsvC8NStt8TixCIZU2jdWiGUH3tYmvOSJ75vbs/TUgIiIiWr7qcva/1SIUVcmDC9SSGUH3tYmvOSp79v4aEBERES1X45z+nFqA4kq3qQUzFPsa5dcek70D/joQERERLU8lp4+o5SeuwRlyuYzEvkb5tcdk74C/DkRERETL0TSnv68Wn7ByumbdUhnXNfJ7CMreBX8tiIiIiPrfpE23qKUnopLtb5ZL7xQLZUz1az38NevvJ550i78WRERERP2uLjZv0QtPUMO0Vy6UkdnXrL6XsNJb/PUgIiIi6mf37X/pS+pS86heduIpuTkgF8ke6L528T3FlB61d8NfEyIiIqL+VZead65fcuIq7eB8tUT2Qfe1i+8psHf6a0JERETUrw7sXfsOsdyEVdr0KbVA9kn3PYjvLSp7R/x1ISIiIupP42FzqVpuIiq5ebIuiqfNLo49dFr3vYjvMSJ7R/x1ISIiIupHdYl53exSE1nJ6SqxNPZS972I7zGw1/lrQ0RERBS/SW5uFwtNSCU3D6uFsc+670l8ryHVd8VfGyIiIqLY1SXr5+RCE9S0bS5Ty2Kfdd+T+F6jsnfGXx8iIiKimI2H6Q/36X8jOmnTPWpRXAr2vcnvOR57Z+zd8deIiIiIKF4lp/eoRSaudK5cEpeBfW/ye47J3h1/jYiIiIhiNR6mv6wWmLjSzXJBXCb2PcrvPSZ7h/x1IiIiIopTyWmolpeY0uPVKXI5XCb2PXbfq/oM4rF3yF8nIiIiohiN2/TP1OISVh5cKRfDpVS/V/UZBGXvkr9WRERERIvtqat3/e7SprvV0hJSTg+sXwaX3gPyswjI3iV7p/z1IiIiIlpckzb9klpYopqO0iViEVxq3fcsPou40i/560VERES0mKb5+G/Ui0pQOd01uwSukLvkZxKUvVv+mhERERHtfJPcnKaWlLByOntm+VslZ8vPJKr6bvlrRkRERLSzTfatfbdcUIIqufmkWP5WSvcZiM8mrPqO+etGREREtHPVRWT/usUkqtw8VnI6WS1/q+TwZ9A8Jj+jmPb760ZERES0M5VR83qxlIQ1zs3lavFbRd1nIT6jqOxd89eOiIiIaL6NL0ovKG0zVktJUPephW+l2WeiP6tw7F2zd85fPyIiIqL5NW2bt6mFJKr69V4kl70V1n0m4rOKyt45f/2IiIiI5tN4T/oWtYjENbhTLXqo7LORn1lM9u75a0hERES0/ZVhOkstIVGVPPiAXPLwW91nIz6zqOzd89eQiIiIaHsbt+m1agGJapzTDWrBwzO6z0h8dlHZO+ivIxEREdH2Vdp0tVo+Iqpf6xdLOzhJLXd4hn1G9lmpzzAiewf9dSQiIiLansY5/Su1eEQ1bdNILXZYr/usxGcYlb2L/loSERERHVsP7vnaP1Byul8tHTGlqVrocBT2mcnPMh57F+2d9NeTiIiIaOvVReh/qIUjqukofXTdIoej6j4z8VmGVd9Jfz2JiIiIttZ07/F/Si4aUQ2b22eXOGyQfXbqMw3K3k1/TYmIiIg2X10ozp1dMCIrbfN+ucTheXWfnfhMAzvXX1MiIiKizVUXiR+YWSxCq4vadWqBw8Z1n6H4bAP7AX9diYiIiDZeXSKun1kq4srpkZKbE2cXN2yOf4aPyM84puv9dSUiIiLaWKVt/q1YKsIqbcqzSxu2pvssxWcclb2r/toSERERHb2DudldcvNZtVQEVdTChmNgn6n+rMOxd9XeWX99iYiIiI5cXRz+l1oowsrpgnWLGo7VBfKzDsreWX99iYiIiHT37U/fphaJqEpOnxZLGrZB99mKzzwqe3f9NSYiIiJa36Tt11/Jm+TBmWpJw3aon636zMNKF/hrTERERPTcpqP0Q3qBiCpdoxc0bBv7jOVnH5O9w/46ExERET1TXWpuVstDROO2+dw4pxPkcoZtY5+xfdbqGcSUbvbXmYiIiOhw42F6i14cYipt2qsWM2y/7rMWzyAqe5f9tSYiIqJV7+5LX/SSktOjammIqC5eB9VChvnpPnPxLCKyd9neaX+9iYiIaJUbD9M71cIQ1+B8tYxhjuwzl88iJnun/fUmIiKiVW3Srr1GLQpRlWG6VS5imLvusxfPJK611/hrTkRERKvYJDeX6CUhnpKbJ6ejdJpawjB/9tnbM1DPJqT6bvtrTkRERKtWXQT+sVwQwkpXqQUMO8iegXw2QdV33F93IiIiWqVKbn5bLgcxPSwXL+w8exb6GYVj77i/7kRERLQq1QXgP6vFIKrSNh+TSxd2XPcsxDOKyt51f+2JiIho2Rtfnv5QvfyfUEtBTOketXBhgeyZyGcVj73r9s77609ERETLXGmbk9RCEFZuzpPLFhaoPhP1rIKyd95ffyIiIlrWDo3SX1KLQFzpZr1oYeF69K+MNvbu+zEgIiKiZaxP/zrX+rV+edqmU+SShYWzZ2PPSD27iOzd92NAREREy1ZdTP6pWgDiGlypFiwEYs9IPruY7Az4cSAiIqJl6ak9u76iLiZ3qcs/pvTguqUKMdmzks8woHoG7Cz4sSAiIqJlqF7wvygv/qDGw3Tpc5YphNU9K/EMw6pnwY8FERER9b3p5cd9g7zwo7K/8iwWKoTWo/9vQfOUnQk/HkRERNTnJm06VV32UY2H6RyxSCGw7pmJZxlXOtWPBxEREfW1A8O179YXfVC5+aRapNAH9dmpZxqUnQ0/JkRERNTHStvsU5d8RCU3Xyo5nayXKERnz86eoXq2EdnZ8GNCREREfasMm9erCz6s3FyuFij0SX2G6tkGZWfEjwsRERH1pQMfWvuqkpuxutwjql/r/XpxQt90z1I844jsjNhZ8WNDREREfai0zdvUxR7VtG0uUksT+qd7luIZR2VnxY8NERERRW/cpj+mLvS4BneqhQk9Zs9UPuuY7Mz48SEiIqLIlbZ5v7rMo5q26QNyWUJvdc9UPOuo7Mz48SEiIqKojXP6W+oijyvdoBYlLAF7tvKZx2Rnx48RERERRazkdJW6xEMapS9O28FJcklC73XPtj5j+ewDsrPjx4iIiIiiVZeLf6ku8KjqYrFvdjnCcumesXj2YdUz5MeJiIiIovTA1S/82npJ3ycv74CmbZo+eyHC8uqetXgHQqpnyM6SHysiIiKK0KRNvyYv7qBKmz46uxBhOXXPWrwDcaVf82NFREREi24y2v0n9YUdVG5uVwsRlll95updiKqeKT9eREREtMgmbTpHXtZBdf/4M7kMYVn17R95Z2fKjxcREREtqtKufb++qGMqOX1CLUJYft2zF+9EVHa2/JgRERHRIiq56dHykB6ZDAcnqiUIK8Cevb0D8t2Ix86WHzMiIiLa6aa5+Wl1QUdVhqmVCxBWRvcOiHcjKjtjftyIiIhop/rs1WvH1Yv44dmLOazcFLX4YBXVd0G9IzE9bGfNjx0RERHtRNNR85viUo4rpwvWLzxYURfIdyQoO2t+7IiIiGjejYfp29SFHFXJzafFsoMV1r0T4l2Jys6cHz8iIiKaZ6Vnf0Vs0g7OVMsOVpi9E/JdicnOnB8/IiIimlfjYfohdRFHVReEa+Wig5XXvRvinYnKzp4fQyIiIppHdTm4WV3CEZW2+VxdaE6YXXAAd0L3joh3JyI7e34MiYiIaLsbt+nfqws4rrRXLDfAM+wdke9OTHYG/TgSERHRdnVo9OLjS5u+qC7fmNJBudgAs+xdke9QPHYG7Sz6sSQiIqLt6PBCoC/fmAbnr1toAMXeFfkOBVW/Zj+WREREdKxN8tqr5YUbVrp13TIDHI29M/JdCqqeST+eREREdCzVReBiednG9OS4TaevW2SAo+jemfruzLxLcdUz6ceTiIiItlrJzT+SF21UOV317AUG2ISr5DsVlJ1NP6ZERES0lfr0b5CqX+vDYnkBNqx7h8S7FZGdTT+mREREtNlK2/wndcGGlZuPqeUF2Lj6Dql3Kyg7o35ciYiIaKM9sK95eb1Ev6wu14hKbu7ViwuwOd27JN6xiOyM2ln1Y0tEREQbado271YXa1i5OU8tLcDm1XdJvWNB2Vn1Y0tERETP16E2fae6UKMqOd2iFxZga7p3SrxrUdmZ9eNLRERER2uSmz3qMo0pfXmc06lqWQG2qnun6rul37mA6pn140tERERHarIv/ai8SKPKgyvVogIcu/puqXcuqnp2/RgTERHRbHv27PqKSZs+Iy/RgEpOD+oFBdge3Tsm3r2Y0mfsDPtxJiIiomc3zukX9QUaVbpULSfAtrF3TL57MdkZ9uNMRERET3fP3uO+QV2cUZWc7paLCbDNundNvINR2Vn2Y01ERERWvdBPVZdmXOmc2YUEmAt71+Q7GFQ9y36siYiIaDJc+2vywgyqtOmmdcsIMEfdOyfexbDqmfbjTUREtNqVnPbJyzKmL9Wv92S1jADz0r1z9d2beRfDsjPtx5uIiGh1K23z4+qiDCs3l6tFBJi/+u6pdzIoO9t+zImIiFavu/e/9PfVy/CguiQjKrm5Xy8gwM7o3kHxbkZkZ9vOuB93IiKi1apehP9dXZBh5XTx7OIB7LCL5bsZlJ1xP+5ERESr08Hc/FF1MQZ2p1g6gJ1n76J+R0Oys+7HnoiIaDUquXmfuhSjKqP0Qbl0ADusexfFOxqVnXU/9kRERMvfdJj+proQw8rphtllA1iwG+S7GpSdeT/+REREy92kTR9Xl2FIOT06bQcnzSwZwEL5O/mofGdDSh/3409ERLS81Qvvp/RFGFNp077ZJQOIoHs3xTsbV/opHwNERETL131XvOhr6mV3SF+C8ZRcv1axYABRdO+oeHdjSodsBvg4ICIiWq7qRfd2fQHGVNp0oVougCi6d1S8u3Glt/s4ICIiWp4m7e5X6osvqFFzu1osgHDsXVXvcFi7X+ljgYiIaDmqF/LZ+tKLqQzTWesWCiCg7l0V73BYdRb4WCAiIup/pV37fnnhBVVy+sTsMgFE1r2z4l2O6tC+te/z8UBERNTvpm26Tl12IeX0hUkenDi7SACxde/sF+Q7HZDNBB8PRERE/a3k5qfVRRdVyaldv0QA8XXvrnino7LZ4GOCiIiofx3Ys3ZcvcweVpdcRPVrnagFAuiL7h0W73ZENhtsRvi4ICIi6lf1IvtNdcHFlS5QywPQG/YOy3c7JpsRPi6IiIj608G9zZ9VF1tUpW0+LRcHoGe6d1m841HZrPCxQURE1I9Kbj6sLrXAzlRLA9A79i7rdzwkmxU+NoiIiOI3bdPfUxdaWDldu25ZAPrtWvmuB2Uzw8cHERFR7EqbblKXWUTTtvncpE0niEUB6K/6Th9+t/V7H43NDB8fREREcauX7L9TF1lcabhuSQCWgb3b8p0Pqs4OHyNERETxmg6PW6uXVW/+ofV1ETj4nMUAWDb2jst3P6A6O2yG+DghIiKKVb2o/q+8wMIanP+cpQBYNvaOy3c/qDpDfJwQERHFabJv97fLiyuo0qZb1y0FwBLq3nVxBsKqs8THChERUYzqZXqRvLQiyvaf6XS1FABLp3vXZ85AYDZLfKwQEREtvjJa+2F1YUVVL9Kr5UIALKnunRdnISqbKT5eiIiIFltpm9vUZRXUw2oRAJaevfv6TIRjM8XHCxER0eKats3PqosqqpKbPXIJAJZc9+6LMxGVzRYfM0RERDvfwcual9cL6fHZCyqwe9UCAKwMOwP6bET0uM0YHzdEREQ7Wxk27xaXU1y5OU9e/sDKqGdAnY2gbMb4uCEiItq5xm36TnUxRVVyukVf/MBq6c6COCNR2azxsUNERLQz9el/7zfO6Yn6n6eqSx9YOfUs+JmQ5yUamzU+doiIiOZfvSR/VF1IUZU8+Li88IEV1Z0JcVaispnj44eIiGh+PfX+Xb+r5PQZdRlFVNr0oLrogVXXnQ1xZiKymWOzx8cQERHRfKoX5H9RF1FU01G6dPaCB5B+qzsb4syEVWePjyEiIqLtb7Jn9yvkBRRWunv2cgfwLHZG5NkJqs4gH0dERETbW70UT5GXT1jpHHm5AzjMzog8O1GlU3wcERERbV+lHfxVffHEVNp0k7zYATxHd1bEGYrKZpGPJSIiou2pXoYjdekE9aX69b5XXeoAnqs7K/XMzJyhsGwW+VgiIiI69kq79i/UhRPWqLlcXegAjsDOjDpLQdlM8vFERES09e7c8/LfW3JzQF02MaX75UUO4Ojs7MgzFY/NJJtNPqaIiIi21jQ3/01dNGHldPG6CxzARlwsz1RQNpt8TBEREW2++y5vvlldMGHZv8hCX+AANqY3/zIYYzPKxxUREdHmqhfJmbMXS2TTnD4oLm4AG9SdIXG2AjvTxxUREdHGm46a7xGXSlglNzeqixvA5nRnSZyxqGxW+dgiIiLaWPUCuXL2QomqtOnRktN71KUNYHPsLNmZUmctqCt9bBERET1/kza9QVwmYdVLeZ+6sAFsTXemxFmLK73BxxcREdGRu+0jL/qaemlM9WUST72QD6mLGsCx6c6WOHMxpanNLh9jREREuvEwvV1fJDGVnC5UlzSAY9OdLXHmorLZ5WOMiIhofZN29yvVBRJWbu5QFzSA7VLPmDp7Ye1+pY8zIiKi51YvtrP15RHTtE1nrb+YAWyX7oyJsxdWnWE+zoiIiJ6p5MH3yYsjqmG6fvZSBjAHdtbUGQzKZpmPNSIiosOVnK5Tl0ZE9Wv9wmQ0OFFeygC2Vz1r3ZkTZzEim2U+1oiIiGzJbf6NujCiKqPUygsZwFx0Z06cxahspvl4IyKiVe7eK49/cb0UHlKXRUi5maiLGMC81bOnzmRANtNstvmYIyKiVa20zf9UF0VUJaeP6EsYwDx1Z0+cyahstvmYIyKiVezQqPkz6oKIato2n1YXMICd0Z1BcTajshnn446IiFatehGcP3sxhJab96nLF8BOqWdQnc24zvdxR0REq9S0bf6uuBQiu1ZfvAB2lJ1FfUZDslnnY4+IiFalSW4+qS6FoD5fL9gT1l24ABbhhO5M6rMaT511PvaIiGgVqhfVz8gLIaiS03DmogWwQN2ZFGc1rDrzfPwREdEyN7lydzNp0yPyMghonNN49pIFsHjd2RRnNqY68+rs8zFIRETLWh3479AXQUwlDz6sLlkAi9WdTXFm40rv8DFIRETLWBkNXqUvgKjSreqCBRCEnVF5dmOyGejjkIiIlq1pmy5Uwz+qMhycIS9XACF0Z1Sc3ahsBvo4JCKiZapeSD+sBn9c6Wp1sQIIxs6qPMMx2Sz0sUhERMtSyek2NfQjKrn5rLxQAYTUnVlxliOyWehjkYiIlqHSNj+rBn5UZdjsUZcpgJi6MyvOclQ2E308EhFRnzvQrr2sDvXH1bCPaDxsDqiLFEBs3dkVZzoim4k2G31MEhFRXyu5OVEN+qimbXOeukQBxNadXXGmo7LZ6GOSiIj62MHc/EU14ONKt6gLFEBP2BmWZzsmm5E+LomIqG+V3HxMDfeISk5PTNt0qrw8AfSCnWE7y+qMR2Qz0sclERH1qckw/RM12OMafFxdnAB6xs6yPONB1VnpY5OIiPrQU0/t+p2T3Nwph3pI6UF5YQLoJzvT8qwHVGelzUwfn0REFL16yfyCHOhBlTy4TF6WAHqpO9PirMeVfsHHJxERRW4y2v31epBHle5WFyWAnrOzLc98UHV2+hglIqKolTa9Vw7xsNI58pIE0G92tuWZj8lmp49RIiKKWGkHf0UN8LjSTfKCBLAc7IzLsx+TzVAfp0REFK2SU6uGd0T2byYqw/ReeTkCWAp2xvv0b2a0GerjlIiIIjXNaz+mBndYw+YKdTECWDJ21tUMCMpmqY9VIiKK0JO3veIrJ226Vw3tkHK6f91lCGCZ3S9nQUjpXpupPl6JiGjRTUfNW/XADmqYLhEXIYBlZWdezYKgbKb6eCUiokV2cG/zzWpQR1Vy+oy8CAEste7si5kQlc1WH7NERLSo6kA+Y3ZAR1ZG6YPqEgSw3LqzL2ZCYGf4mCUiokV0cG/zPWI4h1Vyc6O6AAGshm4GiNkQlc1YH7dERLTT1UvjSjWcIyo5PTbN6T3q8gOwGmwG2CxQMyIim7E+bomIaCcbt+kNajCHldP+2UsPwEraL2dEUDZrfewSEdFOdGj04t9f2jRVQzmknA7NXHQAVtshOSsCsllrM9fHLxERzbt6SfyqGshRTdt04cwlB2CFdTNBzIqw6sz18UtERPOs5MGfkIM4qGnb3DF7yQFANxvEzIjKZq+PYSIimlcl9+sf0VPadJa65ACstm42iJkRlc1eH8NERDSPynDwt9UAjitdry44AOjYjJCzIyabwT6OiYhouyttulYN35By+kK9FN697mIDAOcz4gtyhgRkM9jHMRERbWelXfvXavBGNc2pnb3UAGBWNyvEDInKZrGPZSIi2o4e2v/SF5U2PaiGbki5magLDQC0OjPULAnIZrHNZB/PRER0rNXh+huzwza0UfqIvswAQLCZoWZJXL/h45mIiI6lQ+3anxZDNqySm9+WFxkAHEU3O8RMicpms49pIiLaapPcfEgN2ajqZfU+dYkBwNF0s0PMlLDqbPYxTUREW6kO0h+UAzaocW6uUxcYAGxEN0PEbAmrzmgf10REtNnqIL1x3WCNKg8+X3LzLnV5AcBGHJ4hg8/LGRPTjT6uiYhoM01G6c1iqAY2GKqLCwA2xWaJnDFB1VntY5uIiDbSZM/upg7Q3vxVjdKmsbywAGALupkiZk1Qn7eZ7eObiIierzro3yGGaWCDD89eVACwZTZT5KwJqs5sH99ERHS0yt7Bq+QgDaq06bZ1lxQAHKNutoiZE5XNbh/jRER0pEpOF6ohGlUZDs5QlxQAHItutoiZE5XNbh/jRESkKu3gH6oBGle6Wl1QALAtbMbI2ROTzXAf50RENFtp061qeEZUcvPZyUhcTACwXeqM6WaNmEER2Qz3cU5ERM+uDvP/qAZnWLnZIy8mANhWddaoGRSUzXIf60REZN07PP4Plpy+pIZmRHWQH9AXEgBsv27miFkUkc1ym+k+3omIaGL/NiAxMMMaNR9SlxEAzIXNHDWLoqoz3cc7EdFqNx02f0EOyqhyumXdJQQA83eLnElB2Wz3MU9EtLrVgXjZ7IAMKzdP1MvmtJnLBwB2Qp09dQap2RTTZT7miYhWszoIf2RmMIZW2vRxcfkAwI7oZpCYTYH9iI97IqLV6qmndv2OOgTvmBmKYZWcHlIXDwDspG4WiRkV1B02633sExGtTpM2/bwYioENLlOXDgDsKJtFckZFlX7exz4R0WpU2sHX6YEYU2nTPfLCAYAF6GaSmFVR2cz38U9EtPyVnE5WwzCsnM6dvWgAYIHOlbMqKJv5Pv6JiJa7Q/sG36UGYVzpJnHJAMBi2WySMysmm/1+DRARLW91OGc1BCMqbfP4ZJhOkZcMACxSnU3djBKzK6aU/RogIlrOSh78mB6AYV0hLxgAiMBmlJ5dIdkd4NcBEdFyddtHXvGV9Xf0vfkbKEpOD8iLBQAC6WaVmGExpXvsLvBrgYhoeSq5easefDGNc7pEXSoAEEk3q8QMi8ruAr8WiIiWowN71v6IGnhRlZzuUhcKAETUzSwxy6KyO8GvByKi/leGzRlq2EU1HaUPqssEACLqZpaYZVHZneDXAxFRv5u2zd9Qgy6s3NyoLhIAiK3OLjXTgrK7wa8JIqL+Vgdaf/6u4Nw8Nh2l9+hLBADiOjy7msfkbIvpCr8miIj6WR26PymGW1jTttmvLhAA6INuhonZFla9I/y6ICLqV5M9u7+6DrGJHG4BTdt0SF0cANAn3SwTMy4kuyPqXeHXBhFRfyo5/YocbEGVNl2kLg0A6JNulokZF5XdFX5tEBH1o7J38MfVQAvsDnVhAEAv2UzTsy4kuzP8+iAiil9p0wfUMItq2g7OkpcFAPRQN9PErIvK7gy/PoiIYldGg+9VgyyudL26KACg12y2yZkXk90dfo0QEcWt/s78GjXEYkpfnLaDd8tLAgB6rJttdcbp2ReP3R1+jRARxawO1jeqARZVHawjdUEAwDLoZpyYfVHZHeLXCRFRrB5qX/bCOlgfUMMromnbTGYvBQBYNt2sEzMwpHqH2F3i1woRUZwmufl1ObiCGg/TR2cvBABYNt2sEzMwrHqX+LVCRBSj6f61b5UDK6iSm99WFwIALKNu5olZGJXdKX69EBEtvjqYzpsdVJHVof8+dRkAwDLqZp6YhYGd59cLEdFiO5ibHxRDKqw68K9TFwEALLNu9omZGJXdLX7NEBEtrjo8b1RDKqKSB49MRs271CUAAEutzr5uBorZGJHdLX7NEBEtpskwvVkNqKgOjdJQXgAAsAK6GShmY1j1jvHrhohoZyuXDtIkN5+Xwymg0qaxGvwAsEq6WShmZEj1jrG7xq8dIqKdqw7L/yMHU1iDD6uhDwArxWahnJEx2V3j1w4R0c5U2sGfVwMpqjoob5MDHwBWUDcTxayMyu4cv36IiOZfHZL9+geQt4Mz1LAHgJVkM1HOypjszvHrh4hovpU8+AdqEEVVB+Q1ctADwArrZqOYmVHZ3ePXEBHR/Co5fUoNoaA+O2nTO9WQB4CVZrOxm5FydoZjd49fQ0RE82maB/9BDaCwcrNHDngAQFVnpJqdQdkd5NcREdH2dt8VL3lpHYyPqeETUm4OrB/qAIDnqrNSzdCI6h1kd5FfS0RE21cdMiesGzqR5eZD6wc6AOC56qxUMzSuE/xaIiLanqajte8Qwyas7n9HLAc6AGBWz/7ei6fsTvLriYjo2KuD5dLZQRNVaZsn6uA+bXaQAwCO6LRudoqZGtSlfj0RER1bdaC8bmbAhFZyukoMcQDAUXSzU8zUwF7n1xQR0dab5OZ2MWBCKm16SA1wAMDz62aomK0h1bvJrykioq1VcvNzcsBElZvL1PAGAGxEnaFqtgZld5RfV0REm6u0g68rbfOkGi4RlZzu0YMbALBR3SwVMzYiu6PsrvJri4ho49Vhd7IaLGHldO7swAYAbNq5csYGZXeVX1tERBur5MF3qYESVk43zwxqAMDW3SxnbVB2Z/n1RUT0/NXfIWc1TCIqbXp80qZTxKAGAGxFnamHZ6ueu9HYneXXFxHR0SvDwT9XgySsUXOFHNQAgK2z2apmblB2d/k1RkSk++T7d/2eXv2NCMP0gBzQAIBj1s1YMXsjsrvL7jC/zoiI1jdu039VAySsnC6ZHcwAgG1ziZy9Qdkd5tcZEdFzOzQ6/pvU4Agrp7tmBjIAYPvdJWdwUHaX+bVGRPRMdUCcPjswQsvp7JlhDADYfmfLGRzX6X6tEREdbpKbvy6GRVjTtrlRDGMAwBx0M1fM4rDqnebXGxFRt+heLodFTI/ZPyBcDWMAwPbrZm6dvTOzOK56p/n1RkSrXh0IPyEHRVS52a8GMQBgnursVTM5qnq3+TVHRKva+BPpBXUYFDkkAio53acHMABg3roZLGZzSPVuszvOrzsiWsVK2/yyHBBB1SF7kRq+AID562awmM1R2R3n1x0RrVr370vfogZDVCUP7lSDFwCwc7pZLGZ0VHbX+bVHRKvUtE1nqaEQVR2uH1BDFwCwc7pZLGZ0VHbX+bVHRKvSoTa9Vg2EqOqgul4NXADAzutmspjVUdmd59cfEa1CkzZdrYZBTOmLB/PgJDVsAQA7r5vJdTbrmR1RutqvPyJa9ko7eKMeBDGVYRqpQQsAWJxuNouZHZXdfX4NEtGydlf7sheWnB5QQyCiOkinasACABavm9Fidkdkd5/dgX4dEtEyNs7Nr6sBEFVp00fVcAUALF43o8XsjsruQL8OiWjZOjBc+1Z18KMaD5vb1WAFAMTRzWoxw6Oyu9CvRSJapurvZM9Thz6sUfM+NVQBAIHYrFYzPCi7C/1aJKJlaTJs/o468FFN2+Y6OVABAOF0M1vM8rDqnejXIxEtQ5Pc3CAPe0Q5PVK/3nfNDlIAQFTdzH5EzvSI6p3o1yMR9b16qN+07pAHVnLK64coACCybnaLmR7Ym/yaJKK+Nt6XBqVtPicOeEilTWM1QAEA8XUzXMz2iOxutDvSr0si6mN16PxvdcCjKnlwgRqeAID4uhkuZntUdkf6dUlEfWuc059TBzuudJsanACAHrFZLmd8THZX+rVJRH2q5PQRdajjGpwhhyYAoD9slssZH5PdlX5tElFfmub099WBDiuna9YNSwBAX10jZ31Qdmf69UlEfWjSplvUYY6oZPub5dI7xaAEAPRRnemHZ7ue+/GkW/z6JKLo1QP7Fn2QgxqmvXJQAgD6y2a7mvlhpbf4NUpEUbtv/0tfUg/ro/oQx1N/x39ADkgAQO91M17M/pjSo3aH+nVKRBGrh/Wd6w9vXKUdnK+GIwCg/7oZL2Z/YO/065SIonVg79p3iEMbVmnTp9RgBAAsj27WizsgKrtL/VolokiNh82l6tBGVHLzZB2Ap80ORADA0jmtm/niLojI7lK/VokoSvVwvm72sEZWcrpKDEMAwBLqZr64CwJ7nV+vRBShSW5uFwc1pPo7+4fVIAQALK9u9os7IaR6p/r1SkSLrg6Pn5MHNahp21ymhiAAYHl1s1/cCVHZ3erXLBEtqvEw/eE+/W+fJm26Rw1AAMAKsDtA3g3x2N1qd6xft0S0iEpO71EHNK50rhx+AIDlZ3eAvBtisjvWr1si2unq7zT/sjqYcaWb5eADAKwOuwvkHRGT3bV+7RLRTlZ/pzlUhzKm9Hh1ihx6AIDVYXdBdyeouyIeu2v92iWinWrcpn+mDmRYeXClHHgAgBVU7wR1VwRld65fv0Q07566etfvLm26Wx3GkHJ6YP2QAwCsuAfknRGQ3bl29/o1TETzbNKmX1IHMarpKF0iBhwAYIV1d4O4M+JKv+TXMBHNq2k+/hv1AQwqp7tmhxsAAO4ueXcEZXewX8dENI8muTlNHb6wcjp7ZqgBAPC0s+XdEVW9g/06JqLtbrJv7bvlwQuq5OaTYqgBAPD/dXeFuEPCqnexX8tEtJ3VA7Z/3YGLKjePlZxOVkMNAICnHb4rmsfkXRLTfr+WiWi7KqPm9eKwhTXOzeVqoAEAMKu7M8RdEpXdyX49E9GxNr4ovaC0zVgdtqDuU4MMAIAjsrtD3ynh2J1sd7Nf00R0LE3b5m3qoEVVv96L5BADAOAIurtD3ClR2d3s1zQRbbXxnvQt6oDFNbhTDTAAAJ6X3SHybonJ7mi/roloK5VhOksdrqhKHnxADi8AAJ5Hd4eIuyUqu6P9uiaizTZu02vVwYpqnNMNanABALBR3V0i7pio7K72a5uINlNp09XqUEVUv9YvlnZwkhpaAABslN0ldqeouyYiu6v92iaijVZ/R/uv1IGKatqmkRpYAABsVneniLsmKruz/fomoufrwT1f+wdKTverwxRTmqpBBQDAltndIu+ceOzOtrvbr3EiOlr1gP8PdZCimo7SR9cNKAAAjkF3t4g7J6x6d/s1TkRHarr3+D8lD1BUw+b22eEEAMC2sDtG3T1B2R3u1zkRqepBOXf24ERW2ub9cjgBAHCMujtG3D2BnevXORHNVg/ID8wcmNDqALpODSYAALZLd9eIOyiwH/BrnYieXT0c188clrhyeqTk5sTZgQQAwHbyu+YReRfFdL1f60T0dPV3rP9WHJawSpvy7DACAGAeujtH3EVR2Z3u1zsRHczN7vo71s+qwxJUUYMIAIC5sbtH30nh2J1ud7tf80SrXT0Q/0sdlLByumDdAAIAYL4ukHdSUHa3+zVPtLrdtz99mzogUZWcPi2GDwAAc9fdQeJuisrueL/uiVazSduv36FO8uBMNXwAAJi/egepuymsdIFf90Sr13SUfkgfjKjSNXrwAACwQ+wukndUTHbX+7VPtFrVw3qzOhQRjdvmc+OcTpBDBwCAHWJ3kd1J6q6KKd3s1z7R6jQeprfoAxFTadNeNXAAANhp3Z0k7qqo7M73659o+bv70he9pOT0qDoMEdWBclANGgAAFqW7m8SdFZHd+Xb3+xpAtNzV39m9Ux2EuAbnqyEDAMDC2N0k76yY7O73NYBoeZu0a69RByCqMky3ygEDAMCCdXeUuLviWnuNrwNEy9kkN5folz+ekpsnp6N0mhouAAAsmt1RdlepOyykugP4OkC0fNUX/B/LFz+sdJUaLAAAhGF3lbzDgqq7gK8FRMtV/V3nb8uXPqaH5UABACAau7P0XRaO7QK+FhAtT/XF/s/qhY+qtM3H5DABACCY7s4Sd1lUthP4ekDU/8aXpz9UX+on1MseU7pHDRIAAMKyu0veafHYTmC7ga8JRP2u/k7zJPWih5Wb8+QQAQAgrHp3qTstKNsNfE0g6m+HRukvqRc8rnSzHiAAAATXo3+1vrEdwdcFon5WD11v/jWFpU1fnrbpFDk8AAAIzu4wu8vUHRdT2uvrAlH/qgfun+oXO6rBlWpwAADQG3aXyTsuJtsVfG0g6k9P7dn1FfXA3aVe6pjSg+uGBQAAfWR3mrzrAqq7gu0Mvj4Q9aP64v6ifKGDGg/Tpc8ZEgAA9FR3p4m7Lqy6M/j6QBS/6eXHfYN8kaOyv/IsBgUAAD3Wo/+vavOU7Q6+RhDFbtKmU9VLHFX9ne85YkAAANBb3d0m7ry40qm+RhDF7cBw7bv1CxxUbj6pBgQAAP1X7zh19wVlO4SvE0QxK22zT728EZXcfKnkdLIeDgAA9JvdcXbXqTswItshfJ0gilcZNq9XL25YublcDQYAAJZHvevUHRiU7RK+VhDF6cCH1r6q/q5xrF7aiOrXer8eCAAALJfuzhN3YUS2S9hO4esFUYxK27xNvbBRTdvmIjUMAABYNt2dJ+7CqGyn8PWCaPGN2/TH1Isa1+BONQgAAFhadvfJOzEm2y18zSBabPV3Xu9XL2lU0zZ9QA4BAACWVHf3iTsxKtstfM0gWlzjnP6WekHjSjeoAQAAwNKzO1DejTHZjuHrBtFiKjldpV7OkEbpi9N2cJI8/AAALLnuDqx3obwjA7Idw9cNop2vHpp/qV7MqOqB2Td76AEAWCXdXSjuyLDqruFrB9HO9cDVL/za+vLdJ1/KgKZtmj77oAMAsKq6O1HclSHVXcN2Dl8/iHamSZt+Tb6QQZU2fXT2oAMAsIq6O1HclXGlX/P1g2j+TUa7/6R+EYPKze3qoAMAsLrq3ajuzKjq7uFrCNF8q7+zOke+hEF1//gzecgBAFhNfftHg9ru4WsI0fwq7dr36xcwppLTJ9QBBwBg1XV3pLg7o7IdxNcRovlUctOjQ5EemQwHJ6rDDQDAyrM70u5KeYfGYzuIryNE2980Nz+tXryoyjC18mADAIBOd1eKOzQq20V8LSHavj579dpx9QV7ePaFCys3RR1oAAAwq96Z6i6N6WHbSXw9IdqepqPmN8XLFldOF6w/yAAAQLhA3qVB2U7i6wnRsTcepm9TL1pUJTefFocYAAAcQXd3ijs1KttNfE0hOrZKz36nN2kHZ6pDDAAAjsDuTnmnxmS7ia8pRFuv/o7ph9QLFlV98a+VBxgAABxVd4eKuzUq21F8XSHaWvWlv1m9XBGVtvlcPagnzB5cAACwISd0d6m4YyOyHcXXFaLNN27Tv1cvVlxprzi0AABgo+wulXdsTLar+NpCtPEOjV58fGnTF9VLFVM6KA8sAADYHLtT5V0bj+0qtrP4+kK0sQ6/6Pqlimlw/rqDCgAANs/uVHnXBlW/Zl9fiJ6/SV57tXyRwkq3rjukAABg6+xulXduUHV38TWG6OjVF/xi+RLF9OS4TaevO6AAAGDLuru13rEzd25cdXfxNYboyJXc/CP5AkWV01XPPpgAAGDbXCXv3qBsh/F1hkjXp38zSv1aHxaHEgAAbJPurhV3cES2w/g6Q7S+0jb/Sb04YeXmY+pQAgCA7VLvWnUHB2W7jK81RM/0wL7m5fXl+LJ6aSKqv2u7Vx9IAACwnbo7V9zFEdkuYzuNrzdEh5u2zbvVCxNWbs5ThxEAAGy3euequzgo22l8vSHatetQm75TvShRlZxu0QcRAADMQ3f3ijs5KtttfM2hVa/+Tm2PekliSl8e53SqOoQAAGA+uru33sH6bg6o7ja+5tAqN9mXflS+IFHlwZXqAAIAgHmrd7C6m6OqO46vO7SK7dmz6yvq784+I1+OgEpOD+qDBwAAdkJ3F4s7Oqb0Gdt1fO2hVWuc0y/qFyOqdKk6dAAAYIfYXSzv6Jhs1/G1h1ape/Ye9w3qhYiq/g7ybnngAADAjuruZHFXR2U7j68/tCrVF/VU9TLElc6ZPWgAAGAB7E6Wd3VQdefx9YdWoclw7a/JFyGo0qab1h0yAACwMN3dLO7ssOru42sQLXslp33yJYjpS/XrPVkdMgAAsBjd3Vzv6Jk7OyzbfXwNomWutM2PqxcgrNxcrg4YAABYtHpHq7s7KNuBfB2iZezu/S/9ffUhH1QPP6KSm/v1wQIAABF0d7W4wyOyHch2IV+LaNmqD/i/qwcfVk4Xzx4oAAAQysXyDg/KdiFfi2iZOpibP6oeeGB3isMEAACisTtb3+Uh2U7k6xEtSyU371MPO6oySh+UhwkAAITS3dniLo/KdiJfj2gZmg7T31QPOqycbpg9RAAAILQb5J0elO1GviZR35u06ePqIYeU06PTdnDSzOEBAACB+d39qLzbQ0of9zWJ+lx9kD+lH3BMpU37Zg8PAACIr7vDxd0eV/opX5eoj913xYu+pj7EQ/rhxlNy/VrFwQEAAP3Q3eXijo8pHbJdydcm6lv1Ab5dP9iY6u8EL1SHBgAA9EN3l4s7Pq70dl+bqE9N2t2v1A80qFFzuzowAACgZ+xOV3d9WLtf6esT9aX6op2tH2ZMZZjOWndQAABA73R3urjrw6o7k69P1IdKu/b98kEGVXL6xOwhAQAA/dXd7eLOj8p2J1+jKHrTNl2nHmJIOX1hkgcnzh4QAADQZ93d/gV59wdku5OvURS5kpufVg8wqvo7vnb94QAAAH3X3fHi7o/KdihfpyhiB/asHVcf0sPq4YWUm4k6GAAAYDnUvWQid4CAbIeyXcrXKopWfUC/qR5cXOkCdSgAAMCSsLte7gAx2S7laxVF6uDe5s+qBxZVaZtPywMBAACWSnfni10gKtupfL2iKNXfgXxYPazAzlSHAQAALBm78/UuEJLtVL5eUYSmbfp76kGFldO16w4BAABYZtfKnSAo2618zaJFV9p0k3pIEU3b5nOTNp0gDgAAAFhW9e4/vAPo/SAa2618zaJFVl+ef6ceUFxpuO7lBwAAy892ALkbBFV3LF+3aBFNh8et1YfQm38Yc33BDz7nhQcAAKvFdgG5IwRUdyzbtXztop2uPoD/Kx9MWIPzn/OyAwCA1WK7gNwRgqq7lq9dtJNN9u3+dvlAgiptunXdyw4AAFZOtxOIXSGsunP5+kU7VX1JLpIPI6Js/5lOVy87AABYMd1OMLMrBGY7l69ftBOV0doPqwcRVX1BrpYvOgAAWEndbiB2hqhs9/I1jOZdaZvb1EMI6mH1ggMAgBVnO4LeHcKx3cvXMJpn07b5WfUAoiq52SNfbgAAsNK6HUHsDlHZDubrGM2jg5c1L68f9OOzH3xg96oXGwAAoGO7gt4hInrcdjFfy2i7K8Pm3eJDjys358mXGgAAoFN3BbVDBGW7mK9ltJ2N2/Sd6gOPquR0i36hAQAAntHtDGKXiMp2Ml/PaLvq0/+OZZzTE/U/T1UvMwAAwHPUncF3B7lXRGM7ma9ntB3Vh/+j6oOOquTBx+WLDAAAIHS7g9gporLdzNc0Opaeev+u31Vy+oz6kCMqbXpQvcAAAABH0+0QYreIyHYz29F8XaOtVh/8f1EfcFTTUbp09sUFAAB4Pt0OIXaLsOqO5usabaXJnt2vkB9sWOnu2ZcWAABgw2yXkDtGUHVX87WNNlt92KfIDzWsdI58aQEAADbCdgm5Y0SVTvG1jTZTaQd/VX+gMZU23SRfWAAAgE3odgqxa0RlO5uvb7TR6kMeqQ8zqC/Vr/e96mUFAADYjG6nqLvFzK4Rlu1svr7RRirt2r9QH2RYo+Zy9aICAABsie0WaucIynY3X+PoaN255+W/t+TmgPoQY0r3yxcUAADgWNiOIXePeGx3sx3O1zk6UtPc/Df1AYaV08XrXkwAAIBjd7HcPYKyHc7XOVLdd3nzzeqDC8v+RRb6xQQAANgOvfmXZhnb5Xyto9nqB3Tm7AcW2TSnD4oXEgAAYFt0u4bYQQI709c6enbTUfM94sMKq+TmRvVCAgAAbKdu5xC7SFS20/l6R09XP5grZz+oqEqbHi05vUe9jAAAANvJdg7bPdROEtSVvt6RNWnTG8SHFFZ92fapFxEAAGAeut1D7CRxpTf4mrfa3faRF31N/TCm+kOKp75oh9QLCAAAME/dDiJ2k5jS1HY8X/dWt/EwvV1/QDGVnC5ULx8AAMA8dTuI2E2ish3P173VbNLufqX6YMLKzR3qxQMAANgZdRdRO0pYu1/pa9/qVR/Y2fpDiWnaprPWv3AAAAA7o9tFxI4SVt31fO1brUoefJ/8QKIaputnXzYAAIAdZzuJ2lWCsp3P17/VqeR0nfowIqpf6xcmo8GJ8mUDAADYSXUn6XYTsbNEZDufr3+rUcnNv1EfRFRllFr5ogEAACxAt5uInSUq2/18DVzu7r3y+BfXb/Yh9SGElJuJesEAAAAWq+4oancJyHY/2wF9HVzeStv8T/UBRFVy+oh+uQAAABan21HE7hKV7YC+Di5nh0bNn1HfeFTTtvm0erEAAAAi6HYVscNEZbugr4XLV/0Gz5/9hkPLzfvUSwUAABBD3VXUDhPX+b4WLlf1dxx/V3yzkV2rXygAAIBAbGfRu0xIthP6erg81d9xfFJ9s0F9vr44J6x7kQAAAOI5odtd9E4TT90JfT1cjuoD+Bn5jQZVchrOvEAAAABhdbuL2GnCqruhr4n9bnLl7mbSpkfkNxnQOKfx7MsDAAAQXbfDiN0mprob1h3R18X+Vr+Rd+hvMKaSBx9WLw8AAEBk3Q4jdpu40jt8XexnZTR4lf7Gokq3qhcHAACgF2yXkTtOTLYr+trYv6ZtulB9U1GV4eAM+dIAAAD0QLfLiB0nKtsVfW3sV/WD/mH1DcWVrlYvDAAAQK/YTiN3nZhsZ/T1sT+VnG5T30xEJTeflS8KAABAD3W7jdh5IrKd0dfHflTa5mfVNxJVGTZ71EsCAADQR91uI3aeqGx39DUydgfatZfVL/Zx9U1ENB42B9QLAgAA0GfdjiN2n4hsd7Qd0tfJuJXcnKi+gaimbXOeejkAAAD6rNtxxO4Tle2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Number: 74
Class: Marine (Enterococcus<\\/i>)
Category: 130 - 999 (168/100mL)<\\/html>\",\"Station Number: 111
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (50/100mL)<\\/html>\",\"Station Number: 114
Class: Freshwater (E. coli<\\/i>)
Category: 410 - 999 (447/100mL)<\\/html>\",\"Station Number: 115
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (80/100mL)<\\/html>\",\"Station Number: 116
Class: Freshwater (E. coli<\\/i>)
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Class: Freshwater (E. coli<\\/i>)
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Class: Freshwater (E. coli<\\/i>)
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Class: Marine (Enterococcus<\\/i>)
Category: > 999 (4000/100mL)<\\/html>\",\"Station Number: 154
Class: Freshwater (E. coli<\\/i>)
Category: 410 - 999 (433/100mL)<\\/html>\",\"Station Number: 155
Class: Freshwater (E. coli<\\/i>)
Category: 126 - 409 (170/100mL)<\\/html>\",\"Station Number: 166
Class: Freshwater (E. coli<\\/i>)
Category: 126 - 409 (310/100mL)<\\/html>\",\"Station Number: 178
Class: Marine (Enterococcus<\\/i>)
Category: 130 - 999 (650/100mL)<\\/html>\",\"Station Number: 179
Class: Marine (Enterococcus<\\/i>)
Category: > 999 (1010/100mL)<\\/html>\"],{\"interactive\":false,\"permanent\":false,\"direction\":\"auto\",\"opacity\":1,\"offset\":[0,0],\"textsize\":\"10px\",\"textOnly\":false,\"className\":\"\",\"sticky\":true},null]},{\"method\":\"addControl\",\"args\":[\"Marine (Enterococcus<\\/em>)<\\/b>
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> 999\",\"topright\",null,\"info legend\"]},{\"method\":\"addControl\",\"args\":[\"Freshwater (E. Coli<\\/em>)<\\/b>
#/100mL
< 126
126 - 409
410 - 999
> 999\",\"topright\",null,\"info legend\"]}],\"limits\":{\"lat\":[27.722349,27.937863],\"lng\":[-82.383348,-82.061156]}},\"evals\":[],\"jsHooks\":{\"render\":[{\"code\":\"function(el, x, data) {\\n return (\\n function(el, x) {\\n var myMap = this;\\n myMap.on('baselayerchange',\\n function (e) {\\n myMap.minimap.changeLayer(L.tileLayer.provider(e.name));\\n })\\n }).call(this.getMap(), el, x, data);\\n}\",\"data\":null}]}}"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_fibmatrix.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot a matrix of Fecal Indicator Bacteria categories over time by station — show_fibmatrix","title":"Plot a matrix of Fecal Indicator Bacteria categories over time by station — show_fibmatrix","text":"Plot matrix Fecal Indicator Bacteria categories time station","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_fibmatrix.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot a matrix of Fecal Indicator Bacteria categories over time by station — show_fibmatrix","text":"","code":"show_fibmatrix( fibdata, yrrng = NULL, stas = c(143, 108, 107, 135, 118, 148, 105, 152, 137), lagyr = 3, txtsz = 3, asreact = FALSE, nrows = 10, family = NA, plotly = FALSE, width = NULL, height = NULL )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_fibmatrix.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot a matrix of Fecal Indicator Bacteria categories over time by station — show_fibmatrix","text":"fibdata input data frame returned read_importfib yrrng numeric vector indicating min, max years include, defaults range years epcdata stas optional numeric vector stations include, see details lagyr numeric year lag calculate categories, see details txtsz numeric size text plot, applies tab = FALSE. Use txtsz = NULL suppress. asreact logical indicating reactable object returned nrows asreact = TRUE, numeric specifying number rows table family optional chr string indicating font family text labels plotly logical matrix created using plotly width numeric width plot pixels, applies plotly = TRUE height numeric height plot pixels, applies plotly = TRUE","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_fibmatrix.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot a matrix of Fecal Indicator Bacteria categories over time by station — show_fibmatrix","text":"static ggplot object returned default. reactable table returned asreact = TRUE. interactive plotly object returned plotly = TRUE.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_fibmatrix.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Plot a matrix of Fecal Indicator Bacteria categories over time by station — show_fibmatrix","text":"matrix color codes years stations based likelihood fecal indicator bacteria concentrations exceeding 400 CFU / 100 mL (using Fecal Coliform, fcolif fibdata). likelihoods categorized , B, C, D, E (Microbial Water Quality Assessment MWQA categories) corresponding colors, breakpoints category <10%, 10-30%, 30-50%, 50-75%, >75% (right-closed). default, results year based right-centered window uses previous two years current year calculate probabilities monthly samples (lagyr = 3). Methods rationale categorization scheme provided Florida Department Environmental Protection, Figure 8 document http://publicfiles.dep.state.fl.us/DEAR/BMAP/Tampa/MST%20Report/Fecal%20BMAP%20DST%20Final%20Report%20--%20June%202008.pdf Morrison et al. 2009 BASIS 5 proceedings. default stations used TBEP report #05-13 (https://drive.google.com/file/d/1MZnK3cMzV7LRg6dTbCKX8AOZU0GNurJJ/view) Hillsborough River Basin Management Action Plan (BMAP) subbasins. include Blackwater Creek (WBID 1482, EPC stations 143, 108), Baker Creek (WBID 1522C, EPC station 107), Lake Thonotosassa (WBID 1522B, EPC stations 135, 118), Flint Creek (WBID 1522A, EPC station 148), Lower Hillsborough River (WBID 1443E, EPC stations 105, 152, 137). stations fibdata can plotted using stas argument.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_fibmatrix.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot a matrix of Fecal Indicator Bacteria categories over time by station — show_fibmatrix","text":"","code":"show_fibmatrix(fibdata)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_hmpreport.html","id":null,"dir":"Reference","previous_headings":"","what":"Show Habitat Master Plan progress report card — show_hmpreport","title":"Show Habitat Master Plan progress report card — show_hmpreport","text":"Show Habitat Master Plan progress report card","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_hmpreport.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Show Habitat Master Plan progress report card — show_hmpreport","text":"","code":"show_hmpreport( acres, subtacres, hmptrgs, typ, twocol = FALSE, strata = c(\"Subtidal\", \"Intertidal\", \"Supratidal\"), ycollapse = FALSE, text = 2.5, xang = 25, family = NA, width = NULL, height = NULL )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_hmpreport.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Show Habitat Master Plan progress report card — show_hmpreport","text":"acres data.frame intertidal supratidal land use cover habitat types year data subtacres data.frame subtidal cover habitat types year data hmptrgs data.frame Habitat Master Plan targets goals typ character string indicating \"targets\" \"goals\" twocol logical indicating two colors show target goals met symbols indicate likelihood attaining targets goals, see details strata character string indicating strata plot, one many \"Subtidal\", \"Intertidal\", \"Supratidal\" ycollapse logical indicating y-axis collapsed year data, see details text numeric indicating text size proportion target goal met habitat types shown cell types symbols twocol = T, use NULL suppress xang numeric angle habitat labels x-axis (top) family optional chr string indicating font family text labels width numeric width plot pixels, applies plotly = TRUE height numeric height plot pixels, applies plotly = TRUE","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_hmpreport.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Show Habitat Master Plan progress report card — show_hmpreport","text":"ggplot2 object showing overall progress attaining Habitat Master Plan targets goals.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_hmpreport.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Show Habitat Master Plan progress report card — show_hmpreport","text":"twocol = F, colors indicate target/goal met likelihood attaining target/goal 2030/2050. Red indicates target/goal met likely met 2030/2050 (trending target/goal), yellow indicates target/goal met although likely met 2030/2050 (trending target/goal), light green indicates target/goal met although likely met 2030/2050 (trending target/goal), green indicates target/goal met likely met 2030/2050 (trending target/goal). Numbers cell show proportion target goal met year data available. twocol = T, colors indicate goal met (green) met (red) symbols cell indicate goal likely met (+) (-) 2030/2050. cases, colors trends relative 2030 targets 2050 goals using typ argument. report card provides information artificial reefs, living shorelines, hard bottom habitats. habitats assessed routine data products Southwest Florida Water Management District, although targets goals provided Habitat Master Plan. subtidal data subtacres inter/supratidal data acres provided different datasets Southwest Florida Water Management District. years dataset typically match dataset collected approximate 2 3 year intervals. default, year y-axis shown continuous variable, gaps shown years dataset unavailable. Use ycollapse = TRUE remove years without data.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_hmpreport.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Show Habitat Master Plan progress report card — show_hmpreport","text":"","code":"# view summarized data for report card, targets show_hmpreport(acres, subtacres, hmptrgs, typ = \"targets\") # view summarized data for report card, goals show_hmpreport(acres, subtacres, hmptrgs, typ = \"goals\") # remove empty years show_hmpreport(acres, subtacres, hmptrgs, typ = \"targets\", ycollapse = TRUE) # select only subtidal show_hmpreport(acres, subtacres, hmptrgs, typ = \"targets\", ycollapse = TRUE, strata = 'Subtidal')"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_matrix.html","id":null,"dir":"Reference","previous_headings":"","what":"Create a colorized table for indicator reporting — show_matrix","title":"Create a colorized table for indicator reporting — show_matrix","text":"Create colorized table indicator reporting","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_matrix.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Create a colorized table for indicator reporting — show_matrix","text":"","code":"show_matrix( epcdata, txtsz = 3, trgs = NULL, yrrng = NULL, bay_segment = c(\"OTB\", \"HB\", \"MTB\", \"LTB\"), asreact = FALSE, nrows = 10, abbrev = FALSE, family = NA, historic = TRUE, plotly = FALSE, partialyr = FALSE, width = NULL, height = NULL )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_matrix.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Create a colorized table for indicator reporting — show_matrix","text":"epcdata data frame epc data returned read_importwq txtsz numeric size text plot, applies tab = FALSE trgs optional data.frame annual bay segment water quality targets, defaults targets yrrng numeric vector indicating min, max years include, defaults range years epcdata bay_segment chr string bay segments include, one \"OTB\", \"HB\", \"MTB\", \"LTB\" asreact logical indicating reactable object returned nrows asreact = TRUE, numeric specifying number rows table abbrev logical indicating text labels plot abbreviated first letter family optional chr string indicating font family text labels historic logical historic data used 2005 earlier plotly logical matrix created using plotly partialyr logical indicating incomplete annual data recent year approximated five year monthly averages parameter width numeric width plot pixels, applies plotly = TRUE height numeric height plot pixels, applies plotly = TRUE","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_matrix.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Create a colorized table for indicator reporting — show_matrix","text":"static ggplot object returned asreact = FALSE, otherwise reactable table returned","code":""},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_matrix.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Create a colorized table for indicator reporting — show_matrix","text":"","code":"show_matrix(epcdata)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_matrixplotly.html","id":null,"dir":"Reference","previous_headings":"","what":"Creates a plotly matrix from any matrix function input — show_matrixplotly","title":"Creates a plotly matrix from any matrix function input — show_matrixplotly","text":"Creates plotly matrix matrix function input","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_matrixplotly.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Creates a plotly matrix from any matrix function input — show_matrixplotly","text":"","code":"show_matrixplotly( mat, family = NA, tooltip = \"Result\", width = NULL, height = NULL )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_matrixplotly.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Creates a plotly matrix from any matrix function input — show_matrixplotly","text":"mat input matrix output show_matrix, show_segmatrix, show_wqmatrix, show_tbnimatrix family optional chr string indicating font family text labels tooltip chr string indicating column name tooltip width numeric width plot pixels height numeric height plot pixels","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_matrixplotly.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Creates a plotly matrix from any matrix function input — show_matrixplotly","text":"plotly data object","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_matrixplotly.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Creates a plotly matrix from any matrix function input — show_matrixplotly","text":"","code":"mat <- show_wqmatrix(epcdata) show_matrixplotly(mat) {\"x\":{\"data\":[{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-2001.5,-2000.5,-2000.5,-2001.5,-2001.5],\"text\":\"Result: Below (Average: 10.1, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":true,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-1999.5,-1998.5,-1998.5,-1999.5,-1999.5],\"text\":\"Result: Below (Average: 10.3, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-2020.5,-2019.5,-2019.5,-2020.5,-2020.5],\"text\":\"Result: Below (Average: 10.5, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-2006.5,-2005.5,-2005.5,-2006.5,-2006.5],\"text\":\"Result: Below (Average: 10.9, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-2019.5,-2018.5,-2018.5,-2019.5,-2019.5],\"text\":\"Result: Below (Average: 11, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-1992.5,-1991.5,-1991.5,-1992.5,-1992.5],\"text\":\"Result: Below (Average: 11.1, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-2011.5,-2010.5,-2010.5,-2011.5,-2011.5],\"text\":\"Result: Below (Average: 11.2, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-2016.5,-2015.5,-2015.5,-2016.5,-2016.5],\"text\":\"Result: Below (Average: 11.4, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-2008.5,-2007.5,-2007.5,-2008.5,-2008.5],\"text\":\"Result: Below (Average: 11.6, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-2004.5,-2003.5,-2003.5,-2004.5,-2004.5],\"text\":\"Result: Below (Average: 11.9, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-1997.5,-1996.5,-1996.5,-1997.5,-1997.5],\"text\":\"Result: Below (Average: 12, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-2003.5,-2002.5,-2002.5,-2003.5,-2003.5],\"text\":\"Result: Below (Average: 12.4, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-2012.5,-2011.5,-2011.5,-2012.5,-2012.5],\"text\":\"Result: Below (Average: 12.6, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-1990.5,-1989.5,-1989.5,-1990.5,-1990.5],\"text\":\"Result: Below (Average: 12.8, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-2013.5,-2012.5,-2012.5,-2013.5,-2013.5],\"text\":\"Result: Below (Average: 12.9, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-1988.5,-1987.5,-1987.5,-1988.5,-1988.5],\"text\":\"Result: Below (Average: 13, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5],\"y\":[-1984.5,-1983.5,-1983.5,-1984.5,-1984.5,null,-2005.5,-2004.5,-2004.5,-2005.5,-2005.5,null,-2014.5,-2013.5,-2013.5,-2014.5,-2014.5],\"text\":\"Result: Below (Average: 13.1, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-2002.5,-2001.5,-2001.5,-2002.5,-2002.5],\"text\":\"Result: Below (Average: 13.7, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-2018.5,-2017.5,-2017.5,-2018.5,-2018.5],\"text\":\"Result: Below (Average: 13.9, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-1991.5,-1990.5,-1990.5,-1991.5,-1991.5],\"text\":\"Result: Below (Average: 14.1, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5],\"y\":[-1987.5,-1986.5,-1986.5,-1987.5,-1987.5,null,-1989.5,-1988.5,-1988.5,-1989.5,-1989.5],\"text\":\"Result: Below (Average: 14.2, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-2009.5,-2008.5,-2008.5,-2009.5,-2009.5],\"text\":\"Result: Below (Average: 14.6, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5],\"y\":[-1996.5,-1995.5,-1995.5,-1996.5,-1996.5],\"text\":\"Result: Below (Average: 2.2, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5],\"y\":[-2023.5,-2022.5,-2022.5,-2023.5,-2023.5],\"text\":\"Result: Below (Average: 2.6, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5,null,3.5,3.5,4.5,4.5,3.5],\"y\":[-2008.5,-2007.5,-2007.5,-2008.5,-2008.5,null,-2020.5,-2019.5,-2019.5,-2020.5,-2020.5],\"text\":\"Result: Below (Average: 2.8, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5],\"y\":[-2016.5,-2015.5,-2015.5,-2016.5,-2016.5],\"text\":\"Result: Below (Average: 3, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5],\"y\":[-2007.5,-2006.5,-2006.5,-2007.5,-2007.5],\"text\":\"Result: Below (Average: 3.1, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5],\"y\":[-2021.5,-2020.5,-2020.5,-2021.5,-2021.5],\"text\":\"Result: Below (Average: 3.2, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5],\"y\":[-2017.5,-2016.5,-2016.5,-2017.5,-2017.5],\"text\":\"Result: Below (Average: 3.3, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5,null,3.5,3.5,4.5,4.5,3.5],\"y\":[-2003.5,-2002.5,-2002.5,-2003.5,-2003.5,null,-2014.5,-2013.5,-2013.5,-2014.5,-2014.5],\"text\":\"Result: Below (Average: 3.4, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5],\"y\":[-1988.5,-1987.5,-1987.5,-1988.5,-1988.5],\"text\":\"Result: Below (Average: 3.5, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5,null,3.5,3.5,4.5,4.5,3.5,null,3.5,3.5,4.5,4.5,3.5,null,3.5,3.5,4.5,4.5,3.5],\"y\":[-1987.5,-1986.5,-1986.5,-1987.5,-1987.5,null,-1991.5,-1990.5,-1990.5,-1991.5,-1991.5,null,-1993.5,-1992.5,-1992.5,-1993.5,-1993.5,null,-2022.5,-2021.5,-2021.5,-2022.5,-2022.5],\"text\":\"Result: Below (Average: 3.6, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5],\"y\":[-2006.5,-2005.5,-2005.5,-2006.5,-2006.5],\"text\":\"Result: Below (Average: 3.7, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-2023.5,-2022.5,-2022.5,-2023.5,-2023.5],\"text\":\"Result: Below (Average: 3.7, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5],\"y\":[-2002.5,-2001.5,-2001.5,-2002.5,-2002.5],\"text\":\"Result: Below (Average: 3.8, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5,null,3.5,3.5,4.5,4.5,3.5,null,3.5,3.5,4.5,4.5,3.5,null,3.5,3.5,4.5,4.5,3.5,null,3.5,3.5,4.5,4.5,3.5,null,3.5,3.5,4.5,4.5,3.5],\"y\":[-1984.5,-1983.5,-1983.5,-1984.5,-1984.5,null,-1986.5,-1985.5,-1985.5,-1986.5,-1986.5,null,-2010.5,-2009.5,-2009.5,-2010.5,-2010.5,null,-2013.5,-2012.5,-2012.5,-2013.5,-2013.5,null,-2015.5,-2014.5,-2014.5,-2015.5,-2015.5,null,-2019.5,-2018.5,-2018.5,-2019.5,-2019.5],\"text\":\"Result: Below (Average: 3.9, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5],\"y\":[-1992.5,-1991.5,-1991.5,-1992.5,-1992.5],\"text\":\"Result: Below (Average: 4, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5],\"y\":[-1990.5,-1989.5,-1989.5,-1990.5,-1990.5],\"text\":\"Result: Below (Average: 4.1, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5],\"y\":[-1999.5,-1998.5,-1998.5,-1999.5,-1999.5],\"text\":\"Result: Below (Average: 4.2, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5],\"y\":[-2011.5,-2010.5,-2010.5,-2011.5,-2011.5],\"text\":\"Result: Below (Average: 4.3, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5,null,3.5,3.5,4.5,4.5,3.5,null,3.5,3.5,4.5,4.5,3.5],\"y\":[-1995.5,-1994.5,-1994.5,-1995.5,-1995.5,null,-2009.5,-2008.5,-2008.5,-2009.5,-2009.5,null,-2012.5,-2011.5,-2011.5,-2012.5,-2012.5],\"text\":\"Result: Below (Average: 4.4, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5],\"y\":[-2000.5,-1999.5,-1999.5,-2000.5,-2000.5],\"text\":\"Result: Below (Average: 4.5, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5],\"y\":[-1997.5,-1996.5,-1996.5,-1997.5,-1997.5],\"text\":\"Result: Below (Average: 4.6, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5],\"y\":[-2018.5,-2017.5,-2017.5,-2018.5,-2018.5],\"text\":\"Result: Below (Average: 4.7, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5,null,3.5,3.5,4.5,4.5,3.5,null,3.5,3.5,4.5,4.5,3.5],\"y\":[-1978.5,-1977.5,-1977.5,-1978.5,-1978.5,null,-1985.5,-1984.5,-1984.5,-1985.5,-1985.5,null,-2001.5,-2000.5,-2000.5,-2001.5,-2001.5],\"text\":\"Result: Below (Average: 4.8, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5],\"y\":[-1975.5,-1974.5,-1974.5,-1975.5,-1975.5],\"text\":\"Result: Below (Average: 4.9, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5],\"y\":[-2021.5,-2020.5,-2020.5,-2021.5,-2021.5,null,-2022.5,-2021.5,-2021.5,-2022.5,-2022.5],\"text\":\"Result: Below (Average: 5, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5,null,3.5,3.5,4.5,4.5,3.5,null,3.5,3.5,4.5,4.5,3.5],\"y\":[-1976.5,-1975.5,-1975.5,-1976.5,-1976.5,null,-1989.5,-1988.5,-1988.5,-1989.5,-1989.5,null,-2004.5,-2003.5,-2003.5,-2004.5,-2004.5],\"text\":\"Result: Below (Average: 5.1, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-2006.5,-2005.5,-2005.5,-2006.5,-2006.5],\"text\":\"Result: Below (Average: 5.1, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-1996.5,-1995.5,-1995.5,-1996.5,-1996.5],\"text\":\"Result: Below (Average: 5.3, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5],\"y\":[-2007.5,-2006.5,-2006.5,-2007.5,-2007.5,null,-2020.5,-2019.5,-2019.5,-2020.5,-2020.5],\"text\":\"Result: Below (Average: 5.5, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5],\"y\":[-2008.5,-2007.5,-2007.5,-2008.5,-2008.5,null,-2016.5,-2015.5,-2015.5,-2016.5,-2016.5,null,-2019.5,-2018.5,-2018.5,-2019.5,-2019.5],\"text\":\"Result: Below (Average: 5.7, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-2017.5,-2016.5,-2016.5,-2017.5,-2017.5],\"text\":\"Result: Below (Average: 5.8, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5],\"y\":[-2000.5,-1999.5,-1999.5,-2000.5,-2000.5,null,-2002.5,-2001.5,-2001.5,-2002.5,-2002.5,null,-2010.5,-2009.5,-2009.5,-2010.5,-2010.5],\"text\":\"Result: Below (Average: 6.1, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-2023.5,-2022.5,-2022.5,-2023.5,-2023.5],\"text\":\"Result: Below (Average: 6.2, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-2006.5,-2005.5,-2005.5,-2006.5,-2006.5],\"text\":\"Result: Below (Average: 6.3, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5],\"y\":[-1992.5,-1991.5,-1991.5,-1992.5,-1992.5,null,-2009.5,-2008.5,-2008.5,-2009.5,-2009.5],\"text\":\"Result: Below (Average: 6.5, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5],\"y\":[-1993.5,-1992.5,-1992.5,-1993.5,-1993.5,null,-2004.5,-2003.5,-2003.5,-2004.5,-2004.5],\"text\":\"Result: Below (Average: 6.6, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5],\"y\":[-2013.5,-2012.5,-2012.5,-2013.5,-2013.5,null,-2014.5,-2013.5,-2013.5,-2014.5,-2014.5],\"text\":\"Result: Below (Average: 6.8, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-1996.5,-1995.5,-1995.5,-1996.5,-1996.5],\"text\":\"Result: Below (Average: 6.8, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-2023.5,-2022.5,-2022.5,-2023.5,-2023.5],\"text\":\"Result: Below (Average: 6.9, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-2018.5,-2017.5,-2017.5,-2018.5,-2018.5],\"text\":\"Result: Below (Average: 7, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-2022.5,-2021.5,-2021.5,-2022.5,-2022.5],\"text\":\"Result: Below (Average: 7.1, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-1999.5,-1998.5,-1998.5,-1999.5,-1999.5],\"text\":\"Result: Below (Average: 7.2, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-2000.5,-1999.5,-1999.5,-2000.5,-2000.5],\"text\":\"Result: Below (Average: 7.2, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-2010.5,-2009.5,-2009.5,-2010.5,-2010.5],\"text\":\"Result: Below (Average: 7.4, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-2005.5,-2004.5,-2004.5,-2005.5,-2005.5],\"text\":\"Result: Below (Average: 7.6, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-1993.5,-1992.5,-1992.5,-1993.5,-1993.5],\"text\":\"Result: Below (Average: 7.6, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5],\"y\":[-1988.5,-1987.5,-1987.5,-1988.5,-1988.5,null,-2001.5,-2000.5,-2000.5,-2001.5,-2001.5],\"text\":\"Result: Below (Average: 7.7, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5],\"y\":[-2003.5,-2002.5,-2002.5,-2003.5,-2003.5,null,-2012.5,-2011.5,-2011.5,-2012.5,-2012.5],\"text\":\"Result: Below (Average: 7.8, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5],\"y\":[-2002.5,-2001.5,-2001.5,-2002.5,-2002.5,null,-2012.5,-2011.5,-2011.5,-2012.5,-2012.5],\"text\":\"Result: Below (Average: 7.8, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-1991.5,-1990.5,-1990.5,-1991.5,-1991.5],\"text\":\"Result: Below (Average: 7.9, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5],\"y\":[-1992.5,-1991.5,-1991.5,-1992.5,-1992.5,null,-2014.5,-2013.5,-2013.5,-2014.5,-2014.5],\"text\":\"Result: Below (Average: 7.9, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5],\"y\":[-1997.5,-1996.5,-1996.5,-1997.5,-1997.5,null,-2011.5,-2010.5,-2010.5,-2011.5,-2011.5],\"text\":\"Result: Below (Average: 8, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-2015.5,-2014.5,-2014.5,-2015.5,-2015.5],\"text\":\"Result: Below (Average: 8.1, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-1999.5,-1998.5,-1998.5,-1999.5,-1999.5],\"text\":\"Result: Below (Average: 8.1, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-1986.5,-1985.5,-1985.5,-1986.5,-1986.5],\"text\":\"Result: Below (Average: 8.2, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-1988.5,-1987.5,-1987.5,-1988.5,-1988.5],\"text\":\"Result: Below (Average: 8.2, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-2007.5,-2006.5,-2006.5,-2007.5,-2007.5],\"text\":\"Result: Below (Average: 8.3, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-1991.5,-1990.5,-1990.5,-1991.5,-1991.5],\"text\":\"Result: Below (Average: 8.3, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5],\"y\":[-1989.5,-1988.5,-1988.5,-1989.5,-1989.5,null,-1990.5,-1989.5,-1989.5,-1990.5,-1990.5],\"text\":\"Result: Below (Average: 8.4, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5],\"y\":[-1997.5,-1996.5,-1996.5,-1997.5,-1997.5,null,-2005.5,-2004.5,-2004.5,-2005.5,-2005.5],\"text\":\"Result: Below (Average: 8.4, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5],\"y\":[-2001.5,-2000.5,-2000.5,-2001.5,-2001.5,null,-2007.5,-2006.5,-2006.5,-2007.5,-2007.5],\"text\":\"Result: Below (Average: 8.6, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-2013.5,-2012.5,-2012.5,-2013.5,-2013.5],\"text\":\"Result: Below (Average: 8.7, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-2000.5,-1999.5,-1999.5,-2000.5,-2000.5],\"text\":\"Result: Below (Average: 8.8, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-2022.5,-2021.5,-2021.5,-2022.5,-2022.5],\"text\":\"Result: Below (Average: 8.9, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-2015.5,-2014.5,-2014.5,-2015.5,-2015.5],\"text\":\"Result: Below (Average: 9, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-2016.5,-2015.5,-2015.5,-2016.5,-2016.5],\"text\":\"Result: Below (Average: 9, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5],\"y\":[-1984.5,-1983.5,-1983.5,-1984.5,-1984.5,null,-2018.5,-2017.5,-2017.5,-2018.5,-2018.5],\"text\":\"Result: Below (Average: 9.2, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-2008.5,-2007.5,-2007.5,-2008.5,-2008.5],\"text\":\"Result: Below (Average: 9.3, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-1996.5,-1995.5,-1995.5,-1996.5,-1996.5],\"text\":\"Result: Below (Average: 9.6, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-2017.5,-2016.5,-2016.5,-2017.5,-2017.5],\"text\":\"Result: Below (Average: 9.7, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5],\"y\":[-1993.5,-1992.5,-1992.5,-1993.5,-1993.5,null,-2010.5,-2009.5,-2009.5,-2010.5,-2010.5],\"text\":\"Result: Below (Average: 9.8, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-2021.5,-2020.5,-2020.5,-2021.5,-2021.5],\"text\":\"Result: Below (Average: 9.9, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-1976.5,-1975.5,-1975.5,-1976.5,-1976.5],\"text\":\"Result: Above (Average: 10, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":true,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-1995.5,-1994.5,-1994.5,-1995.5,-1995.5],\"text\":\"Result: Above (Average: 10.3, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-1986.5,-1985.5,-1985.5,-1986.5,-1986.5],\"text\":\"Result: Above (Average: 10.6, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-2015.5,-2014.5,-2014.5,-2015.5,-2015.5],\"text\":\"Result: Above (Average: 10.7, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-1976.5,-1975.5,-1975.5,-1976.5,-1976.5],\"text\":\"Result: Above (Average: 10.9, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-1994.5,-1993.5,-1993.5,-1994.5,-1994.5],\"text\":\"Result: Above (Average: 11, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5],\"y\":[-1985.5,-1984.5,-1984.5,-1985.5,-1985.5,null,-1998.5,-1997.5,-1997.5,-1998.5,-1998.5],\"text\":\"Result: Above (Average: 11.2, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-1978.5,-1977.5,-1977.5,-1978.5,-1978.5],\"text\":\"Result: Above (Average: 11.3, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-1975.5,-1974.5,-1974.5,-1975.5,-1975.5],\"text\":\"Result: Above (Average: 11.4, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5],\"y\":[-1977.5,-1976.5,-1976.5,-1977.5,-1977.5,null,-2011.5,-2010.5,-2010.5,-2011.5,-2011.5],\"text\":\"Result: Above (Average: 11.4, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-1995.5,-1994.5,-1994.5,-1995.5,-1995.5],\"text\":\"Result: Above (Average: 11.5, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-2003.5,-2002.5,-2002.5,-2003.5,-2003.5],\"text\":\"Result: Above (Average: 11.7, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-2004.5,-2003.5,-2003.5,-2004.5,-2004.5],\"text\":\"Result: Above (Average: 11.8, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-1981.5,-1980.5,-1980.5,-1981.5,-1981.5],\"text\":\"Result: Above (Average: 12, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-2009.5,-2008.5,-2008.5,-2009.5,-2009.5],\"text\":\"Result: Above (Average: 12.1, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-1998.5,-1997.5,-1997.5,-1998.5,-1998.5],\"text\":\"Result: Above (Average: 12.2, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-1985.5,-1984.5,-1984.5,-1985.5,-1985.5],\"text\":\"Result: Above (Average: 13, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-1982.5,-1981.5,-1981.5,-1982.5,-1982.5],\"text\":\"Result: Above (Average: 13, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-1977.5,-1976.5,-1976.5,-1977.5,-1977.5],\"text\":\"Result: Above (Average: 13.1, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-1975.5,-1974.5,-1974.5,-1975.5,-1975.5],\"text\":\"Result: Above (Average: 13.2, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-1981.5,-1980.5,-1980.5,-1981.5,-1981.5],\"text\":\"Result: Above (Average: 13.6, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-1980.5,-1979.5,-1979.5,-1980.5,-1980.5],\"text\":\"Result: Above (Average: 13.9, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-1980.5,-1979.5,-1979.5,-1980.5,-1980.5],\"text\":\"Result: Above (Average: 14.7, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-1986.5,-1985.5,-1985.5,-1986.5,-1986.5],\"text\":\"Result: Above (Average: 16.8, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-1983.5,-1982.5,-1982.5,-1983.5,-1983.5],\"text\":\"Result: Above (Average: 17.5, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-1979.5,-1978.5,-1978.5,-1979.5,-1979.5],\"text\":\"Result: Above (Average: 17.7, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-1979.5,-1978.5,-1978.5,-1979.5,-1979.5],\"text\":\"Result: Above (Average: 18, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5],\"y\":[-1994.5,-1993.5,-1993.5,-1994.5,-1994.5,null,-1995.5,-1994.5,-1994.5,-1995.5,-1995.5],\"text\":\"Result: Above (Average: 18.7, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-1982.5,-1981.5,-1981.5,-1982.5,-1982.5],\"text\":\"Result: Above (Average: 18.8, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-1985.5,-1984.5,-1984.5,-1985.5,-1985.5],\"text\":\"Result: Above (Average: 19.3, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-1983.5,-1982.5,-1982.5,-1983.5,-1983.5],\"text\":\"Result: Above (Average: 19.3, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-1998.5,-1997.5,-1997.5,-1998.5,-1998.5],\"text\":\"Result: Above (Average: 20.7, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-1978.5,-1977.5,-1977.5,-1978.5,-1978.5],\"text\":\"Result: Above (Average: 22, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-1980.5,-1979.5,-1979.5,-1980.5,-1980.5],\"text\":\"Result: Above (Average: 22.6, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-1983.5,-1982.5,-1982.5,-1983.5,-1983.5],\"text\":\"Result: Above (Average: 25.9, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-1975.5,-1974.5,-1974.5,-1975.5,-1975.5],\"text\":\"Result: Above (Average: 27.9, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-1976.5,-1975.5,-1975.5,-1976.5,-1976.5],\"text\":\"Result: Above (Average: 29.5, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-1979.5,-1978.5,-1978.5,-1979.5,-1979.5],\"text\":\"Result: Above (Average: 29.7, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-1981.5,-1980.5,-1980.5,-1981.5,-1981.5],\"text\":\"Result: Above (Average: 31.1, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-1977.5,-1976.5,-1976.5,-1977.5,-1977.5],\"text\":\"Result: Above (Average: 32.5, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-1982.5,-1981.5,-1981.5,-1982.5,-1982.5],\"text\":\"Result: Above (Average: 36.1, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5],\"y\":[-1977.5,-1976.5,-1976.5,-1977.5,-1977.5],\"text\":\"Result: Above (Average: 5.3, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5],\"y\":[-1994.5,-1993.5,-1993.5,-1994.5,-1994.5],\"text\":\"Result: Above (Average: 5.5, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5],\"y\":[-1998.5,-1997.5,-1997.5,-1998.5,-1998.5],\"text\":\"Result: Above (Average: 5.9, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5,null,3.5,3.5,4.5,4.5,3.5],\"y\":[-1980.5,-1979.5,-1979.5,-1980.5,-1980.5,null,-1982.5,-1981.5,-1981.5,-1982.5,-1982.5],\"text\":\"Result: Above (Average: 6.1, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5,null,3.5,3.5,4.5,4.5,3.5],\"y\":[-1981.5,-1980.5,-1980.5,-1981.5,-1981.5,null,-2005.5,-2004.5,-2004.5,-2005.5,-2005.5],\"text\":\"Result: Above (Average: 6.2, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5,null,3.5,3.5,4.5,4.5,3.5],\"y\":[-1979.5,-1978.5,-1978.5,-1979.5,-1979.5,null,-1983.5,-1982.5,-1982.5,-1983.5,-1983.5],\"text\":\"Result: Above (Average: 7.3, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-1987.5,-1986.5,-1986.5,-1987.5,-1987.5],\"text\":\"Result: Above (Average: 8.6, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-1984.5,-1983.5,-1983.5,-1984.5,-1984.5],\"text\":\"Result: Above (Average: 8.8, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5],\"y\":[-1987.5,-1986.5,-1986.5,-1987.5,-1987.5,null,-1989.5,-1988.5,-1988.5,-1989.5,-1989.5,null,-1990.5,-1989.5,-1989.5,-1990.5,-1990.5],\"text\":\"Result: Above (Average: 9.3, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5],\"y\":[-1994.5,-1993.5,-1993.5,-1994.5,-1994.5,null,-2021.5,-2020.5,-2020.5,-2021.5,-2021.5],\"text\":\"Result: Above (Average: 9.4, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5],\"y\":[-1978.5,-1977.5,-1977.5,-1978.5,-1978.5,null,-2017.5,-2016.5,-2016.5,-2017.5,-2017.5,null,-2020.5,-2019.5,-2019.5,-2020.5,-2020.5],\"text\":\"Result: Above (Average: 9.5, Threshold: 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approximated five year monthly averages parameter outtxt1 optional text NMC action 1, added outcome column outtxt2 optional text NMC action 2, added outcome column outtxt3 optional text NMC action 3, added outcome column outtxt45 optional text NMC actions 4 5, added outcome column txtsz numeric indicating font size width optional numeric value indicating width inches","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_ratab.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Create a bay segment assessment table for the 2022-2026 reasonable assurance period — show_ratab","text":"flextable object showing reasonable assurance compliance bay segment selected year within five-year period.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_ratab.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Create a bay segment assessment table for the 2022-2026 reasonable assurance period — show_ratab","text":"Choosing bay_segment = 'RALTB' work epcdata additional data needed use option.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_ratab.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Create a bay segment assessment table for the 2022-2026 reasonable assurance period — show_ratab","text":"Bay Segment Reasonable Assurance Assessment Steps DATA USED ASSESS ANNUAL REASONABLE ASSURANCE OUTCOME Year 1 (2022) Year 2 (2023) Year 3 (2024) Year 4 (2025) Year 5 (2026) NMC Action 1: Determine observed chlorophyll-exceeds FDEP threshold 9.3 ug/L (7.1) (6.2) years threshold far, necessary NMC Actions 2-5 NMC Action 2: Determine observed chlorophyll-exceedences occurred 2 consecutive years years met threshold, necessary NMC Actions 3-5 NMC Action 3: Determine observed hydrologically-normalized total load exceeds federally-recognized TMDL 486 tons/year N/N/ necessary due observed water quality seagrass 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1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-65359dda{width:0.6in;background-color:rgba(173, 216, 230, 1.00);vertical-align: middle;border-bottom: 1pt solid rgba(102, 102, 102, 1.00);border-top: 1pt solid rgba(102, 102, 102, 1.00);border-left: 1pt solid rgba(102, 102, 102, 1.00);border-right: 1pt solid rgba(102, 102, 102, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}Bay Segment Reasonable Assurance Assessment StepsDATA USED TO ASSESS ANNUAL REASONABLE ASSURANCEOUTCOMEYear 1 (2022)Year 2 (2023)Year 3 (2024)Year 4 (2025)Year 5 (2026)NMC Action 1: Determine if observed chlorophyll-a exceeds FDEP threshold of 9.3 ug/LNo (7.1)No (6.2)All years below threshold so far, not necessary for NMC Actions 2-5NMC Action 2: Determine if any observed chlorophyll-a exceedences occurred for 2 consecutive yearsNoNoAll years met threshold, not necessary for NMC Actions 3-5NMC Action 3: Determine if observed hydrologically-normalized total load exceeds federally-recognized TMDL of 486 tons/yearN/AN/ANot necessary due to observed water quality and seagrass conditions in the bay segmentNMC Actions 4-5: Determine if any entity/source/facility specific exceedences of 5-yr average allocation occurred during implementation periodNot necessary when chlorophyll-a threshold met"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_reactable.html","id":null,"dir":"Reference","previous_headings":"","what":"Create reactable table from matrix data — show_reactable","title":"Create reactable table from matrix data — show_reactable","text":"Create reactable table matrix data","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_reactable.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Create reactable table from matrix data — show_reactable","text":"","code":"show_reactable(totab, colfun, nrows = 10, txtsz = 3)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_reactable.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Create reactable table from matrix data — show_reactable","text":"totab data frame wide format summarized results colfun Function specifying colors treated cell background nrows numeric specifying number rows table txtsz numeric indicating text size cells, use txtsz = NULL suppress","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_reactable.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Create reactable table from matrix data — show_reactable","text":"reactable table","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_reactable.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Create reactable table from matrix data — show_reactable","text":"function used internally within show_matrix show_wqmatrix","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_reactable.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Create reactable table from matrix data — show_reactable","text":"","code":"data(targets) data(epcdata) library(tidyr) library(dplyr) #> #> Attaching package: ‘dplyr’ #> The following objects are masked from ‘package:stats’: #> #> filter, lag #> The following objects are masked from ‘package:base’: #> #> intersect, setdiff, setequal, union # data totab <- anlz_avedat(epcdata) %>% .$ann %>% filter(var %in% 'mean_chla') %>% left_join(targets, by = 'bay_segment') %>% select(bay_segment, yr, val, chla_thresh) %>% mutate( bay_segment = factor(bay_segment, levels = c('OTB', 'HB', 'MTB', 'LTB')), outcome = case_when( val < chla_thresh ~ 'green', val >= chla_thresh ~ 'red' ) ) %>% select(bay_segment, yr, outcome) %>% spread(bay_segment, outcome) # color function colfun <- function(x){ out <- case_when( x == 'red' ~ '#FF3333', x == 'green' ~ '#33FF3B' ) return(out) } show_reactable(totab, colfun) {\"x\":{\"tag\":{\"name\":\"Reactable\",\"attribs\":{\"data\":{\"yr\":[1974,1975,1976,1977,1978,1979,1980,1981,1982,1983,1984,1985,1986,1987,1988,1989,1990,1991,1992,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013,2014,2015,2016,2017,2018,2019,2020,2021,2022,2023],\"OTB\":[\"red\",\"red\",\"red\",\"red\",\"red\",\"red\",\"red\",\"red\",\"red\",\"red\",\"green\",\"red\",\"red\",\"red\",\"green\",\"red\",\"red\",\"green\",\"green\",\"green\",\"red\",\"red\",\"green\",\"green\",\"red\",\"green\",\"green\",\"green\",\"green\",\"red\",\"red\",\"green\",\"green\",\"green\",\"green\",\"red\",\"green\",\"red\",\"green\",\"green\",\"green\",\"red\",\"green\",\"red\",\"green\",\"red\",\"red\",\"red\",\"green\",\"green\"],\"HB\":[\"red\",\"red\",\"red\",\"red\",\"red\",\"red\",\"red\",\"red\",\"red\",\"red\",\"green\",\"red\",\"red\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"red\",\"red\",\"green\",\"green\",\"red\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\"],\"MTB\":[\"red\",\"red\",\"red\",\"red\",\"red\",\"red\",\"red\",\"red\",\"red\",\"red\",\"red\",\"red\",\"green\",\"red\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"red\",\"red\",\"green\",\"green\",\"red\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\"],\"LTB\":[\"green\",\"green\",\"green\",\"red\",\"green\",\"red\",\"red\",\"red\",\"red\",\"red\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"red\",\"green\",\"green\",\"green\",\"red\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"red\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\"]},\"columns\":[{\"id\":\"yr\",\"name\":\"Year\",\"type\":\"numeric\",\"style\":{\"fontSize\":\"16px\"}},{\"id\":\"OTB\",\"name\":\"OTB\",\"type\":\"character\",\"style\":[{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"backgrou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a barplot of seagrass coverage over time in Tampa Bay — show_seagrasscoverage","title":"Create a barplot of seagrass coverage over time in Tampa Bay — show_seagrasscoverage","text":"Create barplot seagrass coverage time Tampa Bay","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_seagrasscoverage.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Create a barplot of seagrass coverage over time in Tampa Bay — show_seagrasscoverage","text":"","code":"show_seagrasscoverage( seagrass, maxyr = 2022, family = NA, lastlab = \"acres\", axsbrk = c(0.08, 0.1) )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_seagrasscoverage.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Create a barplot of seagrass coverage over time in Tampa Bay — show_seagrasscoverage","text":"seagrass input data.frame included package seagrass maxyr numeric maximum year plot family optional chr string indicating font family text labels lastlab chr string text append label last bar barplot axsbrk numeric vector length two indicating x-axis break occurs","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_seagrasscoverage.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Create a barplot of seagrass coverage over time in Tampa Bay — show_seagrasscoverage","text":"grid object showing acres total seagrass coverage Tampa Bay time.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_seagrasscoverage.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Create a barplot of seagrass coverage over time in Tampa Bay — show_seagrasscoverage","text":"function creates flagship seagrass coverage graphic report coverage changes time. data pre-processed included package seagrass dataset. Original data Southwest Florida Water Management District available online https://data-swfwmd.opendata.arcgis.com/. function data used create plot distinct used transect monitoring program.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_seagrasscoverage.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Create a barplot of seagrass coverage over time in Tampa Bay — show_seagrasscoverage","text":"","code":"show_seagrasscoverage(seagrass)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentalratio.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot metal concentrations against aluminum — show_sedimentalratio","title":"Plot metal concentrations against aluminum — show_sedimentalratio","text":"Plot metal concentrations aluminum","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentalratio.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot metal concentrations against aluminum — show_sedimentalratio","text":"","code":"show_sedimentalratio( sedimentdata, param, yrrng = c(1993, 2022), bay_segment = c(\"HB\", \"OTB\", \"MTB\", \"LTB\", \"TCB\", \"MR\", \"BCB\"), funding_proj = \"TBEP\", lnsz = 1, base_size = 12, plotly = FALSE, family = NA, width = NULL, height = NULL )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentalratio.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot metal concentrations against aluminum — show_sedimentalratio","text":"sedimentdata input sediment data.frame returned read_importsediment param chr string parameter plot, must metal yrrng numeric vector indicating min, max years include, use single year one year data bay_segment chr string bay segment, one many \"HB\", \"OTB\", \"MTB\", \"LTB\", \"TCB\", \"MR\", \"BCB\" funding_proj chr string funding project, one many \"TBEP\" (default), \"TBEP-Special\", \"Apollo Beach\", \"Janicki Contract\", \"Rivers\", \"Tidal Streams\" lnsz numeric line size base_size numeric indicating text scaling size plot plotly logical matrix created using plotly family optional chr string indicating font family text labels width numeric width plot pixels, applies plotly = TRUE height numeric height plot pixels, applies plotly = TRUE","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentalratio.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot metal concentrations against aluminum — show_sedimentalratio","text":"ggplot object plotly object plotly = TRUE showing ratio selected parameter plotted aluminum concentrations collected site. Black lines show linear fit log-log model 95","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentalratio.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Plot metal concentrations against aluminum — show_sedimentalratio","text":"plot shows selected contaminant concentration relative aluminum, latter present common metal Earth's crust. elevated ratio metal parameter relative aluminum suggests higher background concentrations. Lines Threshold Effect Level (TEL) Potential Effect Level (PEL) shown parameter, available.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentalratio.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Plot metal concentrations against aluminum — show_sedimentalratio","text":"Schropp, S. J., Graham Lewis, F., Windom, H. L., Ryan, J. D., Calder, F. D., & Burney, L. C. 1990. Interpretation metal concentrations estuarine sediments Florida using aluminum reference element. Estuaries. 13:227-235.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentalratio.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot metal concentrations against aluminum — show_sedimentalratio","text":"","code":"show_sedimentalratio(sedimentdata, param = 'Arsenic') #> Warning: log-10 transformation introduced infinite values. #> Warning: log-10 transformation introduced infinite values."},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentave.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot sediment concentration averages by bay segment — show_sedimentave","title":"Plot sediment concentration averages by bay segment — show_sedimentave","text":"Plot sediment concentration averages bay segment","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentave.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot sediment concentration averages by bay segment — show_sedimentave","text":"","code":"show_sedimentave( sedimentdata, param, yrrng = c(1993, 2022), bay_segment = c(\"HB\", \"OTB\", \"MTB\", \"LTB\", \"TCB\", \"MR\", \"BCB\"), funding_proj = \"TBEP\", lnsz = 1, base_size = 12, plotly = FALSE, family = NA, width = NULL, height = NULL )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentave.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot sediment concentration averages by bay segment — show_sedimentave","text":"sedimentdata input sediment data.frame returned read_importsediment param chr string parameter plot yrrng numeric vector indicating min, max years include, use single year one year data bay_segment chr string bay segment, one many \"HB\", \"OTB\", \"MTB\", \"LTB\", \"TCB\", \"MR\", \"BCB\" funding_proj chr string funding project, one many \"TBEP\" (default), \"TBEP-Special\", \"Apollo Beach\", \"Janicki Contract\", \"Rivers\", \"Tidal Streams\" lnsz numeric line size base_size numeric indicating text scaling size plot plotly logical matrix created using plotly family optional chr string indicating font family text labels width numeric width plot pixels, applies plotly = TRUE height numeric height plot pixels, applies plotly = TRUE","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentave.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot sediment concentration averages by bay segment — show_sedimentave","text":"ggplot object plotly object plotly = TRUE showing sediment averages 95","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentave.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Plot sediment concentration averages by bay segment — show_sedimentave","text":"Lines Threshold Effect Level (TEL) Potential Effect Level (PEL) shown parameter, available. Confidence intervals may shown segments insufficient data.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentave.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot sediment concentration averages by bay segment — show_sedimentave","text":"","code":"show_sedimentave(sedimentdata, param = 'Arsenic')"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentmap.html","id":null,"dir":"Reference","previous_headings":"","what":"Make a map for sediment contaminants at stations in Tampa Bay — show_sedimentmap","title":"Make a map for sediment contaminants at stations in Tampa Bay — show_sedimentmap","text":"Make map sediment contaminants stations Tampa Bay","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentmap.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Make a map for sediment contaminants at stations in Tampa Bay — show_sedimentmap","text":"","code":"show_sedimentmap( sedimentdata, param, yrrng = c(1993, 2022), funding_proj = \"TBEP\", weight = 1.5 )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentmap.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Make a map for sediment contaminants at stations in Tampa Bay — show_sedimentmap","text":"sedimentdata input sediment data.frame returned read_importsediment param chr string parameter plot yrrng numeric vector indicating min, max years include, use single year one year data funding_proj chr string funding project, one many \"TBEP\" (default), \"TBEP-Special\", \"Apollo Beach\", \"Janicki Contract\", \"Rivers\", \"Tidal Streams\" weight numeric outline width station points map","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentmap.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Make a map for sediment contaminants at stations in Tampa Bay — show_sedimentmap","text":"leaflet object","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentmap.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Make a map for sediment contaminants at stations in Tampa Bay — show_sedimentmap","text":"map shows sediment contaminant concentrations selected parameter relative Threshold Effects Levels (TEL) Potential Effects Levels (PEL), available. Green points show concentrations TEL, yellow points show concentrations TEL PEL, red points show concentrations PEL. applicable TEL PEL values parameter indicated legend. TEL PEL thresholds available, map sediment concentrations shown warning returned console.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentmap.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Make a map for sediment contaminants at stations in Tampa Bay — show_sedimentmap","text":"","code":"show_sedimentmap(sedimentdata, param = 'Arsenic') 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mg/kg\",\"StationNumber: 93LTB39, Year: 1993, Value: 0.1 mg/kg\",\"StationNumber: 93LTB40, Year: 1993, Value: 10.3 mg/kg\",\"StationNumber: 93MTB41, Year: 1993, Value: 1.1 mg/kg\",\"StationNumber: 93MTB42, Year: 1993, Value: 1.4 mg/kg\",\"StationNumber: 93MTB43, Year: 1993, Value: 2.2 mg/kg\",\"StationNumber: 93MTB44, Year: 1993, Value: 0.2 mg/kg\",\"StationNumber: 93MTB45, Year: 1993, Value: 1 mg/kg\",\"StationNumber: 93MTB47, Year: 1993, Value: 0.8 mg/kg\",\"StationNumber: 93MTB48, Year: 1993, Value: 1.2 mg/kg\",\"StationNumber: 93MTB49, Year: 1993, Value: 0.1 mg/kg\",\"StationNumber: 93MTB50, Year: 1993, Value: 0.4 mg/kg\",\"StationNumber: 93MTB51, Year: 1993, Value: 0.2 mg/kg\",\"StationNumber: 93MTB52, Year: 1993, Value: 0.01 mg/kg\",\"StationNumber: 93MTB53, Year: 1993, Value: 0.2 mg/kg\",\"StationNumber: 93MTB54, Year: 1993, Value: 0.8 mg/kg\",\"StationNumber: 93MTB55, Year: 1993, Value: 5.4 mg/kg\",\"StationNumber: 93MTB56, Year: 1993, Value: 1.1 mg/kg\",\"StationNumber: 93MTB57, Year: 1993, Value: 1.4 mg/kg\",\"StationNumber: 93MTB58, Year: 1993, Value: 0.01 mg/kg\",\"StationNumber: 93MTB59, Year: 1993, Value: 1.7 mg/kg\",\"StationNumber: 93MTB60, Year: 1993, Value: 2.4 mg/kg\",\"StationNumber: 93MTB61, Year: 1993, Value: 3.6 mg/kg\",\"StationNumber: 93OTB63, Year: 1993, Value: 5.5 mg/kg\",\"StationNumber: 93OTB64, Year: 1993, Value: 0.1 mg/kg\",\"StationNumber: 93OTB65, Year: 1993, Value: 1 mg/kg\",\"StationNumber: 93OTB66, Year: 1993, Value: 0.9 mg/kg\",\"StationNumber: 93OTB67, Year: 1993, Value: 0.9 mg/kg\",\"StationNumber: 93OTB68, Year: 1993, Value: 1.1 mg/kg\",\"StationNumber: 93OTB69, Year: 1993, Value: 1 mg/kg\",\"StationNumber: 93OTB70, Year: 1993, Value: 1.2 mg/kg\",\"StationNumber: 93OTB71, Year: 1993, Value: 1.1 mg/kg\",\"StationNumber: 93OTB72, Year: 1993, Value: 1.3 mg/kg\",\"StationNumber: 93OTB73, Year: 1993, Value: 0.7 mg/kg\",\"StationNumber: 93OTB76, Year: 1993, Value: 1.8 mg/kg\",\"StationNumber: 93OTB77, Year: 1993, Value: 0.3 mg/kg\",\"StationNumber: 93OTB78, Year: 1993, Value: 0.01 mg/kg\",\"StationNumber: 93OTB79, Year: 1993, Value: 3.7 mg/kg\",\"StationNumber: 93OTB80, Year: 1993, Value: 1.1 mg/kg\",\"StationNumber: 93OTB83, Year: 1993, Value: 0.6 mg/kg\",\"StationNumber: 94HB03, Year: 1994, Value: 11.53 mg/kg\",\"StationNumber: 94HB04, Year: 1994, Value: 8.831 mg/kg\",\"StationNumber: 94HB05, Year: 1994, Value: 0.01 mg/kg\",\"StationNumber: 94HB06, Year: 1994, Value: 0.469 mg/kg\",\"StationNumber: 94HB07, Year: 1994, Value: 18.34 mg/kg\",\"StationNumber: 94HB08, Year: 1994, Value: 6.249 mg/kg\",\"StationNumber: 94HB09, Year: 1994, Value: 3.867 mg/kg\",\"StationNumber: 94HB10, Year: 1994, Value: 0.01 mg/kg\",\"StationNumber: 94HB12, Year: 1994, Value: 2.244 mg/kg\",\"StationNumber: 94HB13, Year: 1994, Value: 0.523 mg/kg\",\"StationNumber: 94HB14, Year: 1994, Value: 1.158 mg/kg\",\"StationNumber: 94HB15, Year: 1994, Value: 1.3 mg/kg\",\"StationNumber: 94HB16, Year: 1994, Value: 0.01 mg/kg\",\"StationNumber: 94HB18, Year: 1994, Value: 0.785 mg/kg\",\"StationNumber: 94HB19, Year: 1994, Value: 2.992 mg/kg\",\"StationNumber: 94HB20, Year: 1994, Value: 6.697 mg/kg\",\"StationNumber: 94HB21, Year: 1994, Value: 4.794 mg/kg\",\"StationNumber: 94HB22, Year: 1994, Value: 0.559 mg/kg\",\"StationNumber: 94HB23, Year: 1994, Value: 5.137 mg/kg\",\"StationNumber: 94LTB24, Year: 1994, Value: 2.557 mg/kg\",\"StationNumber: 94LTB25, Year: 1994, Value: 10.23 mg/kg\",\"StationNumber: 94LTB26, Year: 1994, Value: 0.982 mg/kg\",\"StationNumber: 94LTB27, Year: 1994, Value: 2.211 mg/kg\",\"StationNumber: 94LTB28, Year: 1994, Value: 3.464 mg/kg\",\"StationNumber: 94LTB29, Year: 1994, Value: 2.906 mg/kg\",\"StationNumber: 94LTB30, Year: 1994, Value: 3.515 mg/kg\",\"StationNumber: 94LTB31, Year: 1994, Value: 1.09 mg/kg\",\"StationNumber: 94LTB32, Year: 1994, Value: 0.538 mg/kg\",\"StationNumber: 94LTB33, Year: 1994, Value: 4.454 mg/kg\",\"StationNumber: 94LTB34, Year: 1994, Value: 1.975 mg/kg\",\"StationNumber: 94LTB35, Year: 1994, Value: 0.164 mg/kg\",\"StationNumber: 94LTB36, Year: 1994, Value: 4.695 mg/kg\",\"StationNumber: 94LTB37, Year: 1994, Value: 5.033 mg/kg\",\"StationNumber: 94LTB38, Year: 1994, Value: 2.197 mg/kg\",\"StationNumber: 94LTB39, Year: 1994, Value: 12.93 mg/kg\",\"StationNumber: 94LTB40, Year: 1994, Value: 8.954 mg/kg\",\"StationNumber: 94MR23, Year: 1994, Value: 0 mg/kg\",\"StationNumber: 94MR24, Year: 1994, Value: 0 mg/kg\",\"StationNumber: 94MR26, Year: 1994, Value: 0 mg/kg\",\"StationNumber: 94MR27, Year: 1994, Value: 0 mg/kg\",\"StationNumber: 94MR28, Year: 1994, Value: 0 mg/kg\",\"StationNumber: 94MR29, Year: 1994, Value: 0 mg/kg\",\"StationNumber: 94MR31, Year: 1994, Value: 0 mg/kg\",\"StationNumber: 94MR32, Year: 1994, Value: 0 mg/kg\",\"StationNumber: 94MR34, Year: 1994, Value: 0 mg/kg\",\"StationNumber: 94MR43, Year: 1994, Value: 0 mg/kg\",\"StationNumber: 94MTB41, Year: 1994, Value: 0.465 mg/kg\",\"StationNumber: 94MTB42, Year: 1994, Value: 0.074 mg/kg\",\"StationNumber: 94MTB43, Year: 1994, Value: 6.242 mg/kg\",\"StationNumber: 94MTB44, Year: 1994, Value: 3.975 mg/kg\",\"StationNumber: 94MTB45, Year: 1994, Value: 0.417 mg/kg\",\"StationNumber: 94MTB47, Year: 1994, Value: 6.591 mg/kg\",\"StationNumber: 94MTB48, Year: 1994, Value: 0.209 mg/kg\",\"StationNumber: 94MTB49, Year: 1994, Value: 9.619 mg/kg\",\"StationNumber: 94MTB50, Year: 1994, Value: 1.634 mg/kg\",\"StationNumber: 94MTB51, Year: 1994, Value: 1.203 mg/kg\",\"StationNumber: 94MTB52, Year: 1994, Value: 0.01 mg/kg\",\"StationNumber: 94MTB53, Year: 1994, Value: 0.173 mg/kg\",\"StationNumber: 94MTB54, Year: 1994, Value: 2.975 mg/kg\",\"StationNumber: 94MTB55, Year: 1994, Value: 0.01 mg/kg\",\"StationNumber: 94MTB56, Year: 1994, Value: 0.028 mg/kg\",\"StationNumber: 94MTB57, Year: 1994, Value: 0.01 mg/kg\",\"StationNumber: 94MTB58, Year: 1994, Value: 11.58 mg/kg\",\"StationNumber: 94MTB59, Year: 1994, Value: 1.603 mg/kg\",\"StationNumber: 94MTB60, Year: 1994, Value: 0.01 mg/kg\",\"StationNumber: 94MTB61, Year: 1994, Value: 2.096 mg/kg\",\"StationNumber: 94OTB63, Year: 1994, Value: 8.811 mg/kg\",\"StationNumber: 94OTB64, Year: 1994, Value: 0.01 mg/kg\",\"StationNumber: 94OTB65, Year: 1994, Value: 0.01 mg/kg\",\"StationNumber: 94OTB66, Year: 1994, Value: 0.01 mg/kg\",\"StationNumber: 94OTB67, Year: 1994, Value: 1.513 mg/kg\",\"StationNumber: 94OTB68, Year: 1994, Value: 0.01 mg/kg\",\"StationNumber: 94OTB69, Year: 1994, Value: 0.01 mg/kg\",\"StationNumber: 94OTB70, Year: 1994, Value: 0.01 mg/kg\",\"StationNumber: 94OTB71, Year: 1994, Value: 1.415 mg/kg\",\"StationNumber: 94OTB72, Year: 1994, Value: 0.159 mg/kg\",\"StationNumber: 94OTB73, Year: 1994, Value: 1.64 mg/kg\",\"StationNumber: 94OTB76, Year: 1994, Value: 0.683 mg/kg\",\"StationNumber: 94OTB77, Year: 1994, Value: 0.111 mg/kg\",\"StationNumber: 94OTB78, Year: 1994, Value: 4.152 mg/kg\",\"StationNumber: 94OTB79, Year: 1994, Value: 0.086 mg/kg\",\"StationNumber: 94OTB80, Year: 1994, Value: 0.01 mg/kg\",\"StationNumber: 94OTB83, Year: 1994, Value: 0.01 mg/kg\",\"StationNumber: 94TCB22, Year: 1994, Value: 0 mg/kg\",\"StationNumber: 94TCB37, Year: 1994, Value: 0 mg/kg\",\"StationNumber: 94TCB38, Year: 1994, Value: 0 mg/kg\",\"StationNumber: 94TCB39, Year: 1994, Value: 0 mg/kg\",\"StationNumber: 94TCB40, Year: 1994, Value: 0 mg/kg\",\"StationNumber: 94TCB41, Year: 1994, Value: 0 mg/kg\",\"StationNumber: 94TCB42, Year: 1994, Value: 0 mg/kg\",\"StationNumber: 95BCB01, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95BCB02, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95BCB03, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95BCB04, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95BCB05, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95BCB06, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95BCB07, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95BCB08, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95BCB09, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95BCB10, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95BCB11, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95BCB12, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95BCB13, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95BCB14, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95BCB15, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95BCB16, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95BCB17, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95BCB18, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95BCB19, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95BCB20, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95BCB21, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95HB14, Year: 1995, Value: 0.565 mg/kg\",\"StationNumber: 95HB16, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95HB17, Year: 1995, Value: 0.844 mg/kg\",\"StationNumber: 95HB18, Year: 1995, Value: 2.685 mg/kg\",\"StationNumber: 95HB19, Year: 1995, Value: 0.011 mg/kg\",\"StationNumber: 95HB22, Year: 1995, Value: 0.134 mg/kg\",\"StationNumber: 95HB23, Year: 1995, Value: 2.499 mg/kg\",\"StationNumber: 95HB24, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95HB25, Year: 1995, Value: 0.258 mg/kg\",\"StationNumber: 95HB26, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95HB27, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95HB28, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95HB29, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95HB37, Year: 1995, Value: 1.482 mg/kg\",\"StationNumber: 95HB38, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95HB40, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95HB41, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95HB42, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95HB43, Year: 1995, Value: 0.432 mg/kg\",\"StationNumber: 95HB44, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95HB45, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95HB46, Year: 1995, Value: 3.023 mg/kg\",\"StationNumber: 95HB48, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95HB49, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95HB51, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95HB52, Year: 1995, Value: 1.696 mg/kg\",\"StationNumber: 95HB54, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95HB55, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95HB56, Year: 1995, Value: 4.81 mg/kg\",\"StationNumber: 95LTB01, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95LTB02, Year: 1995, Value: 0.076 mg/kg\",\"StationNumber: 95LTB04, Year: 1995, Value: 1.513 mg/kg\",\"StationNumber: 95LTB05, Year: 1995, Value: 1.347 mg/kg\",\"StationNumber: 95LTB06, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95LTB07, Year: 1995, Value: 0.876 mg/kg\",\"StationNumber: 95LTB08, Year: 1995, Value: 2.389 mg/kg\",\"StationNumber: 95LTB09, Year: 1995, Value: 1.187 mg/kg\",\"StationNumber: 95LTB10, Year: 1995, Value: 1.839 mg/kg\",\"StationNumber: 95LTB11, Year: 1995, Value: 2.845 mg/kg\",\"StationNumber: 95LTB12, Year: 1995, Value: 0.953 mg/kg\",\"StationNumber: 95LTB13, Year: 1995, Value: 1.192 mg/kg\",\"StationNumber: 95LTB15, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95LTB17, Year: 1995, Value: 1.678 mg/kg\",\"StationNumber: 95LTB18, Year: 1995, Value: 1.29 mg/kg\",\"StationNumber: 95LTB19, Year: 1995, Value: 0.872 mg/kg\",\"StationNumber: 95LTB20, Year: 1995, Value: 0.139 mg/kg\",\"StationNumber: 95LTB21, Year: 1995, Value: 0.009 mg/kg\",\"StationNumber: 95LTB23, Year: 1995, Value: 1.475 mg/kg\",\"StationNumber: 95LTB25, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95LTB26, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95LTB29, Year: 1995, Value: 0.225 mg/kg\",\"StationNumber: 95MR23, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95MR24, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95MR25, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95MR26, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95MR27, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95MR28, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95MR29, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95MR31, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95MR32, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95MR34, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95MR43, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95MTB03, Year: 1995, Value: 0.098 mg/kg\",\"StationNumber: 95MTB04, Year: 1995, Value: 0.296 mg/kg\",\"StationNumber: 95MTB06, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95MTB07, Year: 1995, Value: 2.145 mg/kg\",\"StationNumber: 95MTB08, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95MTB10, Year: 1995, Value: 0.254 mg/kg\",\"StationNumber: 95MTB15, Year: 1995, Value: 0.107 mg/kg\",\"StationNumber: 95MTB16, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95MTB17, Year: 1995, Value: 9.688 mg/kg\",\"StationNumber: 95MTB18, Year: 1995, Value: 5.681 mg/kg\",\"StationNumber: 95MTB19, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95MTB21, Year: 1995, Value: 0.19 mg/kg\",\"StationNumber: 95MTB24, Year: 1995, Value: 0.144 mg/kg\",\"StationNumber: 95MTB25, Year: 1995, Value: 0.264 mg/kg\",\"StationNumber: 95MTB26, Year: 1995, Value: 0.067 mg/kg\",\"StationNumber: 95MTB29, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95MTB30, Year: 1995, Value: 0.738 mg/kg\",\"StationNumber: 95MTB31, Year: 1995, Value: 0.483 mg/kg\",\"StationNumber: 95MTB32, Year: 1995, Value: 0.445 mg/kg\",\"StationNumber: 95MTB34, Year: 1995, Value: 1.065 mg/kg\",\"StationNumber: 95MTB35, Year: 1995, Value: 0.129 mg/kg\",\"StationNumber: 95OTB02, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95OTB03, Year: 1995, Value: 0.259 mg/kg\",\"StationNumber: 95OTB05, Year: 1995, Value: 0.772 mg/kg\",\"StationNumber: 95OTB06, Year: 1995, Value: 0.84 mg/kg\",\"StationNumber: 95OTB07, Year: 1995, Value: 0.274 mg/kg\",\"StationNumber: 95OTB08, Year: 1995, Value: 0.087 mg/kg\",\"StationNumber: 95OTB11, Year: 1995, Value: 0.214 mg/kg\",\"StationNumber: 95OTB12, Year: 1995, Value: 0.344 mg/kg\",\"StationNumber: 95OTB13, Year: 1995, Value: 0.269 mg/kg\",\"StationNumber: 95OTB14, Year: 1995, Value: 0.451 mg/kg\",\"StationNumber: 95OTB15, Year: 1995, Value: 7.62 mg/kg\",\"StationNumber: 95OTB17, Year: 1995, Value: 0.59 mg/kg\",\"StationNumber: 95OTB18, Year: 1995, Value: 0.356 mg/kg\",\"StationNumber: 95OTB19, Year: 1995, Value: 3.07 mg/kg\",\"StationNumber: 95OTB20, Year: 1995, Value: 0.314 mg/kg\",\"StationNumber: 95OTB22, Year: 1995, Value: 0.522 mg/kg\",\"StationNumber: 95OTB23, Year: 1995, Value: 0.135 mg/kg\",\"StationNumber: 95OTB24, Year: 1995, Value: 0.476 mg/kg\",\"StationNumber: 95OTB25, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95OTB26, Year: 1995, Value: 0.226 mg/kg\",\"StationNumber: 95OTB27, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95OTB29, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95OTB30, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95TCB22, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95TCB37, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95TCB38, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95TCB39, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95TCB40, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95TCB41, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95TCB42, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 96BCB02, Year: 1996, Value: 1.681 mg/kg\",\"StationNumber: 96BCB04, Year: 1996, Value: 4.387 mg/kg\",\"StationNumber: 96BCB07, Year: 1996, Value: 1.51 mg/kg\",\"StationNumber: 96BCB08, Year: 1996, Value: 2.112 mg/kg\",\"StationNumber: 96BCB12, Year: 1996, Value: 1.308 mg/kg\",\"StationNumber: 96BCB13, Year: 1996, Value: 5.299 mg/kg\",\"StationNumber: 96BCB15, Year: 1996, Value: 3.323 mg/kg\",\"StationNumber: 96BCB19, Year: 1996, Value: 0.7 mg/kg\",\"StationNumber: 96BCB24, Year: 1996, Value: 0.754 mg/kg\",\"StationNumber: 96BCB26, Year: 1996, Value: 0.16 mg/kg\",\"StationNumber: 96BCB27, Year: 1996, Value: 0.783 mg/kg\",\"StationNumber: 96BCB30, Year: 1996, Value: 0.546 mg/kg\",\"StationNumber: 96BCB31, Year: 1996, Value: 0.256 mg/kg\",\"StationNumber: 96BCB34, Year: 1996, Value: 0.29 mg/kg\",\"StationNumber: 96BCB36, Year: 1996, Value: 0.591 mg/kg\",\"StationNumber: 96BCB39, Year: 1996, Value: 0.25 mg/kg\",\"StationNumber: 96BCB40, Year: 1996, Value: 1.148 mg/kg\",\"StationNumber: 96BCB41, Year: 1996, Value: 0.01 mg/kg\",\"StationNumber: 96BCB44, Year: 1996, Value: 0.98 mg/kg\",\"StationNumber: 96BCB46, Year: 1996, Value: 0.339 mg/kg\",\"StationNumber: 96BCB49, Year: 1996, Value: 0.01 mg/kg\",\"StationNumber: 96HB13, Year: 1996, Value: 2.778 mg/kg\",\"StationNumber: 96HB16, Year: 1996, Value: 0.534 mg/kg\",\"StationNumber: 96HB18, Year: 1996, Value: 1.303 mg/kg\",\"StationNumber: 96HB20, Year: 1996, Value: 4.202 mg/kg\",\"StationNumber: 96HB22, Year: 1996, Value: 3.994 mg/kg\",\"StationNumber: 96HB23, Year: 1996, Value: 2.264 mg/kg\",\"StationNumber: 96HB24, Year: 1996, Value: 0.182 mg/kg\",\"StationNumber: 96HB26, Year: 1996, Value: 0.077 mg/kg\",\"StationNumber: 96HB27, Year: 1996, Value: 2.885 mg/kg\",\"StationNumber: 96HB29, Year: 1996, Value: 1.112 mg/kg\",\"StationNumber: 96HB36, Year: 1996, Value: 1.771 mg/kg\",\"StationNumber: 96HB37, Year: 1996, Value: 1.839 mg/kg\",\"StationNumber: 96HB38, Year: 1996, Value: 2.504 mg/kg\",\"StationNumber: 96HB39, Year: 1996, Value: 1.465 mg/kg\",\"StationNumber: 96HB42, Year: 1996, Value: 2.318 mg/kg\",\"StationNumber: 96HB43, Year: 1996, Value: 2.562 mg/kg\",\"StationNumber: 96HB44, Year: 1996, Value: 1.521 mg/kg\",\"StationNumber: 96HB45, Year: 1996, Value: 0.167 mg/kg\",\"StationNumber: 96HB46, Year: 1996, Value: 7.157 mg/kg\",\"StationNumber: 96HB47, Year: 1996, Value: 0.464 mg/kg\",\"StationNumber: 96HB48, Year: 1996, Value: 4.527 mg/kg\",\"StationNumber: 96HB50, Year: 1996, Value: 0.914 mg/kg\",\"StationNumber: 96HB51, Year: 1996, Value: 0.333 mg/kg\",\"StationNumber: 96HB52, Year: 1996, Value: 0.158 mg/kg\",\"StationNumber: 96HB53, Year: 1996, Value: 0.597 mg/kg\",\"StationNumber: 96HB54, Year: 1996, Value: 0.378 mg/kg\",\"StationNumber: 96HB56, Year: 1996, Value: 5.858 mg/kg\",\"StationNumber: 96LTB01, Year: 1996, Value: 0.01 mg/kg\",\"StationNumber: 96LTB02, Year: 1996, Value: 1.027 mg/kg\",\"StationNumber: 96LTB03, Year: 1996, Value: 1.366 mg/kg\",\"StationNumber: 96LTB04, Year: 1996, Value: 2.045 mg/kg\",\"StationNumber: 96LTB05, Year: 1996, Value: 1.675 mg/kg\",\"StationNumber: 96LTB06, Year: 1996, Value: 0.221 mg/kg\",\"StationNumber: 96LTB07, Year: 1996, Value: 0.01 mg/kg\",\"StationNumber: 96LTB08, Year: 1996, Value: 0.48 mg/kg\",\"StationNumber: 96LTB09, Year: 1996, Value: 0.01 mg/kg\",\"StationNumber: 96LTB10, Year: 1996, Value: 11.04 mg/kg\",\"StationNumber: 96LTB11, Year: 1996, Value: 1.949 mg/kg\",\"StationNumber: 96LTB12, Year: 1996, Value: 0.571 mg/kg\",\"StationNumber: 96LTB13, Year: 1996, Value: 2.568 mg/kg\",\"StationNumber: 96LTB15, Year: 1996, Value: 0.01 mg/kg\",\"StationNumber: 96LTB17, Year: 1996, Value: 6.999 mg/kg\",\"StationNumber: 96LTB18, Year: 1996, Value: 2.186 mg/kg\",\"StationNumber: 96LTB19, Year: 1996, Value: 2.416 mg/kg\",\"StationNumber: 96LTB20, Year: 1996, Value: 0.01 mg/kg\",\"StationNumber: 96LTB21, Year: 1996, Value: 0.131 mg/kg\",\"StationNumber: 96LTB23, Year: 1996, Value: 2.988 mg/kg\",\"StationNumber: 96LTB24, Year: 1996, Value: 1.609 mg/kg\",\"StationNumber: 96LTB25, Year: 1996, Value: 0.876 mg/kg\",\"StationNumber: 96LTB26, Year: 1996, Value: 0.241 mg/kg\",\"StationNumber: 96LTB27, Year: 1996, Value: 2.428 mg/kg\",\"StationNumber: 96MR20, Year: 1996, Value: 0.485 mg/kg\",\"StationNumber: 96MR21, Year: 1996, Value: 0.319 mg/kg\",\"StationNumber: 96MR23, Year: 1996, Value: 0.042 mg/kg\",\"StationNumber: 96MR24, Year: 1996, Value: 0.449 mg/kg\",\"StationNumber: 96MR25, Year: 1996, Value: 0.192 mg/kg\",\"StationNumber: 96MR26, Year: 1996, Value: 0.486 mg/kg\",\"StationNumber: 96MR27, Year: 1996, Value: 0.302 mg/kg\",\"StationNumber: 96MR28, Year: 1996, Value: 0.01 mg/kg\",\"StationNumber: 96MR29, Year: 1996, Value: 0.596 mg/kg\",\"StationNumber: 96MR30, Year: 1996, Value: 0.01 mg/kg\",\"StationNumber: 96MR31, Year: 1996, Value: 0.01 mg/kg\",\"StationNumber: 96MR32, Year: 1996, Value: 0.716 mg/kg\",\"StationNumber: 96MR43, Year: 1996, Value: 0.01 mg/kg\",\"StationNumber: 96MTB04, Year: 1996, Value: 0.503 mg/kg\",\"StationNumber: 96MTB05, Year: 1996, Value: 0.329 mg/kg\",\"StationNumber: 96MTB07, Year: 1996, Value: 0.458 mg/kg\",\"StationNumber: 96MTB09, Year: 1996, Value: 2.141 mg/kg\",\"StationNumber: 96MTB10, Year: 1996, Value: 0.591 mg/kg\",\"StationNumber: 96MTB11, Year: 1996, Value: 1.049 mg/kg\",\"StationNumber: 96MTB12, Year: 1996, Value: 0.633 mg/kg\",\"StationNumber: 96MTB13, Year: 1996, Value: 0 mg/kg\",\"StationNumber: 96MTB14, Year: 1996, Value: 6.52 mg/kg\",\"StationNumber: 96MTB15, Year: 1996, Value: 0.01 mg/kg\",\"StationNumber: 96MTB16, Year: 1996, Value: 0.063 mg/kg\",\"StationNumber: 96MTB17, Year: 1996, Value: 1.839 mg/kg\",\"StationNumber: 96MTB18, Year: 1996, Value: 0.01 mg/kg\",\"StationNumber: 96MTB19, Year: 1996, Value: 0.119 mg/kg\",\"StationNumber: 96MTB20, Year: 1996, Value: 4.526 mg/kg\",\"StationNumber: 96MTB23, Year: 1996, Value: 0.01 mg/kg\",\"StationNumber: 96MTB24, Year: 1996, Value: 0.485 mg/kg\",\"StationNumber: 96MTB25, Year: 1996, Value: 0.756 mg/kg\",\"StationNumber: 96MTB26, Year: 1996, Value: 0.01 mg/kg\",\"StationNumber: 96MTB30, Year: 1996, Value: 0.024 mg/kg\",\"StationNumber: 96MTB31, Year: 1996, Value: 0.827 mg/kg\",\"StationNumber: 96MTB32, Year: 1996, Value: 5.666 mg/kg\",\"StationNumber: 96MTB34, Year: 1996, Value: 0.664 mg/kg\",\"StationNumber: 96MTB35, Year: 1996, Value: 0.206 mg/kg\",\"StationNumber: 96OTB07, Year: 1996, Value: 0.477 mg/kg\",\"StationNumber: 96OTB11, Year: 1996, Value: 0.239 mg/kg\",\"StationNumber: 96OTB12, Year: 1996, Value: 1.951 mg/kg\",\"StationNumber: 96OTB13, Year: 1996, Value: 0.721 mg/kg\",\"StationNumber: 96OTB14, Year: 1996, Value: 1.631 mg/kg\",\"StationNumber: 96OTB17, Year: 1996, Value: 1.716 mg/kg\",\"StationNumber: 96OTB18, Year: 1996, Value: 1.202 mg/kg\",\"StationNumber: 96OTB19, Year: 1996, Value: 1.134 mg/kg\",\"StationNumber: 96OTB20, Year: 1996, Value: 1.832 mg/kg\",\"StationNumber: 96OTB23, Year: 1996, Value: 0.698 mg/kg\",\"StationNumber: 96OTB24, Year: 1996, Value: 0.749 mg/kg\",\"StationNumber: 96OTB26, Year: 1996, Value: 0.526 mg/kg\",\"StationNumber: 96OTB27, Year: 1996, Value: 0.629 mg/kg\",\"StationNumber: 96OTB29, Year: 1996, Value: 0.574 mg/kg\",\"StationNumber: 96OTB30, Year: 1996, Value: 0.106 mg/kg\",\"StationNumber: 96TCB22, Year: 1996, Value: 3.557 mg/kg\",\"StationNumber: 96TCB36, Year: 1996, Value: 1.001 mg/kg\",\"StationNumber: 96TCB37, Year: 1996, Value: 5.738 mg/kg\",\"StationNumber: 96TCB38, Year: 1996, Value: 2.784 mg/kg\",\"StationNumber: 96TCB39, Year: 1996, Value: 1.919 mg/kg\",\"StationNumber: 96TCB40, Year: 1996, Value: 1.242 mg/kg\",\"StationNumber: 96TCB41, Year: 1996, Value: 1.244 mg/kg\",\"StationNumber: 96TCB42, Year: 1996, Value: 0.01 mg/kg\",\"StationNumber: 97BCB02, Year: 1997, Value: 0.9 mg/kg\",\"StationNumber: 97BCB08, Year: 1997, Value: 3.79 mg/kg\",\"StationNumber: 97BCB10, Year: 1997, Value: 1.504 mg/kg\",\"StationNumber: 97BCB13, Year: 1997, Value: 1.11 mg/kg\",\"StationNumber: 97BCB17, Year: 1997, Value: 3.833 mg/kg\",\"StationNumber: 97BCB18, Year: 1997, Value: 0.053 mg/kg\",\"StationNumber: 97BCB27, Year: 1997, Value: 7.606 mg/kg\",\"StationNumber: 97BCB30, Year: 1997, Value: 1.439 mg/kg\",\"StationNumber: 97BCB31, Year: 1997, Value: 0.01 mg/kg\",\"StationNumber: 97BCB36, Year: 1997, Value: 0.548 mg/kg\",\"StationNumber: 97BCB37, Year: 1997, Value: 0.041 mg/kg\",\"StationNumber: 97BCB40, Year: 1997, Value: 2.312 mg/kg\",\"StationNumber: 97BCB46, Year: 1997, Value: 1.153 mg/kg\",\"StationNumber: 97BCB50, Year: 1997, Value: 3.046 mg/kg\",\"StationNumber: 97BCB57-1, Year: 1997, Value: 4.964 mg/kg\",\"StationNumber: 97BCB58-1, Year: 1997, Value: 8.192 mg/kg\",\"StationNumber: 97BCB58-2, Year: 1997, Value: 1.739 mg/kg\",\"StationNumber: 97BCB59-1, Year: 1997, Value: 1.017 mg/kg\",\"StationNumber: 97BCB59-2, Year: 1997, Value: 1.042 mg/kg\",\"StationNumber: 97BCB60-2, Year: 1997, Value: 0.932 mg/kg\",\"StationNumber: 97BCB60-4, Year: 1997, Value: 1.016 mg/kg\",\"StationNumber: 97HB10, Year: 1997, Value: 2.262 mg/kg\",\"StationNumber: 97HB13, Year: 1997, Value: 3.367 mg/kg\",\"StationNumber: 97HB18, Year: 1997, Value: 0.393 mg/kg\",\"StationNumber: 97HB22, Year: 1997, Value: 1.588 mg/kg\",\"StationNumber: 97HB23, Year: 1997, Value: 0.17 mg/kg\",\"StationNumber: 97HB24, Year: 1997, Value: 0.01 mg/kg\",\"StationNumber: 97HB27, Year: 1997, Value: 0.01 mg/kg\",\"StationNumber: 97HB29, Year: 1997, Value: 1.632 mg/kg\",\"StationNumber: 97HB36, Year: 1997, Value: 0.01 mg/kg\",\"StationNumber: 97HB37, Year: 1997, Value: 1.131 mg/kg\",\"StationNumber: 97HB38, Year: 1997, Value: 0.753 mg/kg\",\"StationNumber: 97HB39, Year: 1997, Value: 1.737 mg/kg\",\"StationNumber: 97HB43, Year: 1997, Value: 0.107 mg/kg\",\"StationNumber: 97HB44, Year: 1997, Value: 0.576 mg/kg\",\"StationNumber: 97HB45, Year: 1997, Value: 0.888 mg/kg\",\"StationNumber: 97HB46, Year: 1997, Value: 0.424 mg/kg\",\"StationNumber: 97HB48, Year: 1997, Value: 0.494 mg/kg\",\"StationNumber: 97HB50, Year: 1997, Value: 2.002 mg/kg\",\"StationNumber: 97HB53, Year: 1997, Value: 0.349 mg/kg\",\"StationNumber: 97HB54, Year: 1997, Value: 0.918 mg/kg\",\"StationNumber: 97HB55, Year: 1997, Value: 0.597 mg/kg\",\"StationNumber: 97HB56, Year: 1997, Value: 0.564 mg/kg\",\"StationNumber: 97LTB01, Year: 1997, Value: 0.364 mg/kg\",\"StationNumber: 97LTB02, Year: 1997, Value: 0.667 mg/kg\",\"StationNumber: 97LTB03, Year: 1997, Value: 1.481 mg/kg\",\"StationNumber: 97LTB06, Year: 1997, Value: 1.145 mg/kg\",\"StationNumber: 97LTB07, Year: 1997, Value: 1.822 mg/kg\",\"StationNumber: 97LTB09, Year: 1997, Value: 5.154 mg/kg\",\"StationNumber: 97LTB10, Year: 1997, Value: 9.854 mg/kg\",\"StationNumber: 97LTB11, Year: 1997, Value: 10.221 mg/kg\",\"StationNumber: 97LTB12, Year: 1997, Value: 2.644 mg/kg\",\"StationNumber: 97LTB13, Year: 1997, Value: 1.991 mg/kg\",\"StationNumber: 97LTB15, Year: 1997, Value: 0.607 mg/kg\",\"StationNumber: 97LTB17, Year: 1997, Value: 3.416 mg/kg\",\"StationNumber: 97LTB18, Year: 1997, Value: 2.814 mg/kg\",\"StationNumber: 97LTB19, Year: 1997, Value: 2.16 mg/kg\",\"StationNumber: 97LTB20, Year: 1997, Value: 0.558 mg/kg\",\"StationNumber: 97LTB21, Year: 1997, Value: 1.584 mg/kg\",\"StationNumber: 97LTB23, Year: 1997, Value: 2.302 mg/kg\",\"StationNumber: 97LTB24, Year: 1997, Value: 0.57 mg/kg\",\"StationNumber: 97LTB25, Year: 1997, Value: 0.538 mg/kg\",\"StationNumber: 97LTB26, Year: 1997, Value: 0.1 mg/kg\",\"StationNumber: 97LTB28, Year: 1997, Value: 0.01 mg/kg\",\"StationNumber: 97MR09, Year: 1997, Value: 0.458 mg/kg\",\"StationNumber: 97MR10, Year: 1997, Value: 0.672 mg/kg\",\"StationNumber: 97MR11, Year: 1997, Value: 2.184 mg/kg\",\"StationNumber: 97MR12, Year: 1997, Value: 1.339 mg/kg\",\"StationNumber: 97MR13, Year: 1997, Value: 1.416 mg/kg\",\"StationNumber: 97MR14, Year: 1997, Value: 1.886 mg/kg\",\"StationNumber: 97MR15, Year: 1997, Value: 1.079 mg/kg\",\"StationNumber: 97MR16, Year: 1997, Value: 1.293 mg/kg\",\"StationNumber: 97MR17, Year: 1997, Value: 0.902 mg/kg\",\"StationNumber: 97MR18, Year: 1997, Value: 1.223 mg/kg\",\"StationNumber: 97MR19, Year: 1997, Value: 1.164 mg/kg\",\"StationNumber: 97MR20, Year: 1997, Value: 1.285 mg/kg\",\"StationNumber: 97MR21, Year: 1997, Value: 1.766 mg/kg\",\"StationNumber: 97MTB02, Year: 1997, Value: 0.086 mg/kg\",\"StationNumber: 97MTB03, Year: 1997, Value: 0.01 mg/kg\",\"StationNumber: 97MTB04, Year: 1997, Value: 0.531 mg/kg\",\"StationNumber: 97MTB05, Year: 1997, Value: 0.01 mg/kg\",\"StationNumber: 97MTB07, Year: 1997, Value: 1.425 mg/kg\",\"StationNumber: 97MTB09, Year: 1997, Value: 0.514 mg/kg\",\"StationNumber: 97MTB10, Year: 1997, Value: 1.592 mg/kg\",\"StationNumber: 97MTB12, Year: 1997, Value: 0.718 mg/kg\",\"StationNumber: 97MTB14, Year: 1997, Value: 1.277 mg/kg\",\"StationNumber: 97MTB15, Year: 1997, Value: 0.612 mg/kg\",\"StationNumber: 97MTB16, Year: 1997, Value: 1.06 mg/kg\",\"StationNumber: 97MTB17, Year: 1997, Value: 1.021 mg/kg\",\"StationNumber: 97MTB18, Year: 1997, Value: 0.336 mg/kg\",\"StationNumber: 97MTB19, Year: 1997, Value: 0.112 mg/kg\",\"StationNumber: 97MTB23, Year: 1997, Value: 0.992 mg/kg\",\"StationNumber: 97MTB24, Year: 1997, Value: 6.807 mg/kg\",\"StationNumber: 97MTB25, Year: 1997, Value: 1.392 mg/kg\",\"StationNumber: 97MTB26, Year: 1997, Value: 0.193 mg/kg\",\"StationNumber: 97MTB30, Year: 1997, Value: 0.442 mg/kg\",\"StationNumber: 97MTB31, Year: 1997, Value: 0.756 mg/kg\",\"StationNumber: 97MTB32, Year: 1997, Value: 8.261 mg/kg\",\"StationNumber: 97MTB35, Year: 1997, Value: 0.47 mg/kg\",\"StationNumber: 97OTB03, Year: 1997, Value: 3.828 mg/kg\",\"StationNumber: 97OTB06, Year: 1997, Value: 0.01 mg/kg\",\"StationNumber: 97OTB07, Year: 1997, Value: 0.01 mg/kg\",\"StationNumber: 97OTB11, Year: 1997, Value: 0.142 mg/kg\",\"StationNumber: 97OTB12, Year: 1997, Value: 0.01 mg/kg\",\"StationNumber: 97OTB13, Year: 1997, Value: 0.724 mg/kg\",\"StationNumber: 97OTB17, Year: 1997, Value: 0.01 mg/kg\",\"StationNumber: 97OTB18, Year: 1997, Value: 0.029 mg/kg\",\"StationNumber: 97OTB19, Year: 1997, Value: 0.012 mg/kg\",\"StationNumber: 97OTB20, Year: 1997, Value: 0.01 mg/kg\",\"StationNumber: 97OTB22, Year: 1997, Value: 0.13 mg/kg\",\"StationNumber: 97OTB23, Year: 1997, Value: 0.01 mg/kg\",\"StationNumber: 97OTB24, Year: 1997, Value: 0.01 mg/kg\",\"StationNumber: 97OTB26, Year: 1997, Value: 0.01 mg/kg\",\"StationNumber: 97OTB27, Year: 1997, Value: 0.01 mg/kg\",\"StationNumber: 97OTB29, Year: 1997, Value: 0.01 mg/kg\",\"StationNumber: 97TCB01, Year: 1997, Value: 2.943 mg/kg\",\"StationNumber: 97TCB02, Year: 1997, Value: 2.221 mg/kg\",\"StationNumber: 97TCB03, Year: 1997, Value: 4.341 mg/kg\",\"StationNumber: 97TCB04, Year: 1997, Value: 3.585 mg/kg\",\"StationNumber: 97TCB05, Year: 1997, Value: 2.998 mg/kg\",\"StationNumber: 97TCB06, Year: 1997, Value: 1.551 mg/kg\",\"StationNumber: 97TCB07, Year: 1997, Value: 3.303 mg/kg\",\"StationNumber: 97TCB08, Year: 1997, Value: 0.787 mg/kg\",\"StationNumber: 98BCB06, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98BCB09, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98BCB11, Year: 1998, Value: 0.445 mg/kg\",\"StationNumber: 98BCB12, Year: 1998, Value: 2.509 mg/kg\",\"StationNumber: 98BCB15, Year: 1998, Value: 0.358 mg/kg\",\"StationNumber: 98BCB17, Year: 1998, Value: 1.517 mg/kg\",\"StationNumber: 98BCB21, Year: 1998, Value: 0.54 mg/kg\",\"StationNumber: 98BCB27, Year: 1998, Value: 0.102 mg/kg\",\"StationNumber: 98BCB28, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98BCB32, Year: 1998, Value: 0.09 mg/kg\",\"StationNumber: 98BCB38, Year: 1998, Value: 0.595 mg/kg\",\"StationNumber: 98BCB40, Year: 1998, Value: 0.392 mg/kg\",\"StationNumber: 98BCB43, Year: 1998, Value: 0.065 mg/kg\",\"StationNumber: 98BCB46, Year: 1998, Value: 1.568 mg/kg\",\"StationNumber: 98BCB57/1, Year: 1998, Value: 4.454 mg/kg\",\"StationNumber: 98BCB58/1, Year: 1998, Value: 4.341 mg/kg\",\"StationNumber: 98BCB58/2, Year: 1998, Value: 3.761 mg/kg\",\"StationNumber: 98BCB59/1, Year: 1998, Value: 0.088 mg/kg\",\"StationNumber: 98BCB59/2, Year: 1998, Value: 1.103 mg/kg\",\"StationNumber: 98BCB60/2, Year: 1998, Value: 0.999 mg/kg\",\"StationNumber: 98BCB60/4, Year: 1998, Value: 1.03 mg/kg\",\"StationNumber: 98HB003, Year: 1998, Value: 0.036 mg/kg\",\"StationNumber: 98HB006, Year: 1998, Value: 3.089 mg/kg\",\"StationNumber: 98HB014, Year: 1998, Value: 2.09 mg/kg\",\"StationNumber: 98HB016, Year: 1998, Value: 1.995 mg/kg\",\"StationNumber: 98HB017, Year: 1998, Value: 0.072 mg/kg\",\"StationNumber: 98HB024, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98HB030, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98HB049, Year: 1998, Value: 2.146 mg/kg\",\"StationNumber: 98HB052, Year: 1998, Value: 0.64 mg/kg\",\"StationNumber: 98HB056, Year: 1998, Value: 1.656 mg/kg\",\"StationNumber: 98HB059, Year: 1998, Value: 0.534 mg/kg\",\"StationNumber: 98HB069, Year: 1998, Value: 0.785 mg/kg\",\"StationNumber: 98HB080, Year: 1998, Value: 3.475 mg/kg\",\"StationNumber: 98HB089, Year: 1998, Value: 0.435 mg/kg\",\"StationNumber: 98HB130, Year: 1998, Value: 0.358 mg/kg\",\"StationNumber: 98HB153, Year: 1998, Value: 0.777 mg/kg\",\"StationNumber: 98HB171, Year: 1998, Value: 0.842 mg/kg\",\"StationNumber: 98HB180, Year: 1998, Value: 1.348 mg/kg\",\"StationNumber: 98HB224, Year: 1998, Value: 1.942 mg/kg\",\"StationNumber: 98HB237, Year: 1998, Value: 0.471 mg/kg\",\"StationNumber: 98HB245, Year: 1998, Value: 0.642 mg/kg\",\"StationNumber: 98HB252, Year: 1998, Value: 1.898 mg/kg\",\"StationNumber: 98HB280, Year: 1998, Value: 0.134 mg/kg\",\"StationNumber: 98HB789, Year: 1998, Value: 2.42 mg/kg\",\"StationNumber: 98HBDIcanal, Year: 1998, Value: 0.931 mg/kg\",\"StationNumber: 98HBspark, Year: 1998, Value: 0.258 mg/kg\",\"StationNumber: 98LTB0014, Year: 1998, Value: 2.93 mg/kg\",\"StationNumber: 98LTB0025, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98LTB0049, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98LTB0095, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98LTB0123, Year: 1998, Value: 0.56 mg/kg\",\"StationNumber: 98LTB0144, Year: 1998, Value: 0.476 mg/kg\",\"StationNumber: 98LTB0151, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98LTB0168, Year: 1998, Value: 0.441 mg/kg\",\"StationNumber: 98LTB0183, Year: 1998, Value: 0.828 mg/kg\",\"StationNumber: 98LTB0223, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98LTB0244, Year: 1998, Value: 0.078 mg/kg\",\"StationNumber: 98LTB0273, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98LTB0307, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98LTB0364, Year: 1998, Value: 0.105 mg/kg\",\"StationNumber: 98LTB0393, Year: 1998, Value: 0.397 mg/kg\",\"StationNumber: 98LTB0762, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98LTB1057, Year: 1998, Value: 0.673 mg/kg\",\"StationNumber: 98MR09, Year: 1998, Value: 0.125 mg/kg\",\"StationNumber: 98MR10, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98MR11, Year: 1998, Value: 0.99 mg/kg\",\"StationNumber: 98MR12, Year: 1998, Value: 0.198 mg/kg\",\"StationNumber: 98MR13, Year: 1998, Value: 1.029 mg/kg\",\"StationNumber: 98MR14, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98MR15, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98MR16, Year: 1998, Value: 0.352 mg/kg\",\"StationNumber: 98MR17, Year: 1998, Value: 0.36 mg/kg\",\"StationNumber: 98MR18, Year: 1998, Value: 0.322 mg/kg\",\"StationNumber: 98MR19, Year: 1998, Value: 0.176 mg/kg\",\"StationNumber: 98MR20, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98MR21, Year: 1998, Value: 2.438 mg/kg\",\"StationNumber: 98MTB0032, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98MTB0035, Year: 1998, Value: 0.482 mg/kg\",\"StationNumber: 98MTB0052, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98MTB0067, Year: 1998, Value: 1.03 mg/kg\",\"StationNumber: 98MTB0090, Year: 1998, Value: 0.747 mg/kg\",\"StationNumber: 98MTB0103, Year: 1998, Value: 0.073 mg/kg\",\"StationNumber: 98MTB0133, Year: 1998, Value: 0.164 mg/kg\",\"StationNumber: 98MTB0187, Year: 1998, Value: 1.46 mg/kg\",\"StationNumber: 98MTB0191, Year: 1998, Value: 0.192 mg/kg\",\"StationNumber: 98MTB0208, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98MTB0270, Year: 1998, Value: 0.016 mg/kg\",\"StationNumber: 98MTB0275, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98MTB0283, Year: 1998, Value: 0.376 mg/kg\",\"StationNumber: 98MTB0322, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98MTB0331, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98MTB0416, Year: 1998, Value: 3.312 mg/kg\",\"StationNumber: 98MTB0460, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98MTB0688, Year: 1998, Value: 0.769 mg/kg\",\"StationNumber: 98MTB0694, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98MTB1036, Year: 1998, Value: 0.018 mg/kg\",\"StationNumber: 98OTB0036, Year: 1998, Value: 0.256 mg/kg\",\"StationNumber: 98OTB0039, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98OTB0048, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98OTB0056, Year: 1998, Value: 0.499 mg/kg\",\"StationNumber: 98OTB0125, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98OTB0177, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98OTB0185, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98OTB0199, Year: 1998, Value: 2.325 mg/kg\",\"StationNumber: 98OTB0232, Year: 1998, Value: 0.301 mg/kg\",\"StationNumber: 98OTB0239, Year: 1998, Value: 1.557 mg/kg\",\"StationNumber: 98OTB0274, Year: 1998, Value: 2.028 mg/kg\",\"StationNumber: 98OTB0425, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98OTB0596, Year: 1998, Value: 8.041 mg/kg\",\"StationNumber: 98OTB0721, Year: 1998, Value: 0.397 mg/kg\",\"StationNumber: 98OTB1140, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98OTB1227, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98TCB01, Year: 1998, Value: 1.816 mg/kg\",\"StationNumber: 98TCB02, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98TCB04, Year: 1998, Value: 1.3 mg/kg\",\"StationNumber: 98TCB05, Year: 1998, Value: 0.903 mg/kg\",\"StationNumber: 98TCB06, Year: 1998, Value: 1.118 mg/kg\",\"StationNumber: 98TCB07, Year: 1998, Value: 0.966 mg/kg\",\"StationNumber: 98TCB08, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 99BCB2025, Year: 1999, Value: 0.194 mg/kg\",\"StationNumber: 99BCB2041, Year: 1999, Value: 0.553 mg/kg\",\"StationNumber: 99BCB2063, Year: 1999, Value: 1.16 mg/kg\",\"StationNumber: 99BCB2069, Year: 1999, Value: 0.715 mg/kg\",\"StationNumber: 99BCB2070, Year: 1999, Value: 0.693 mg/kg\",\"StationNumber: 99BCB2086, Year: 1999, Value: 0.348 mg/kg\",\"StationNumber: 99BCB2094, Year: 1999, Value: 1.893 mg/kg\",\"StationNumber: 99BCB2115, Year: 1999, Value: 1.48 mg/kg\",\"StationNumber: 99BCB2132, Year: 1999, Value: 0.09 mg/kg\",\"StationNumber: 99BCB2295, Year: 1999, Value: 0.01 mg/kg\",\"StationNumber: 99BCB2358, Year: 1999, Value: 0.627 mg/kg\",\"StationNumber: 99BCB2423, Year: 1999, Value: 0.758 mg/kg\",\"StationNumber: 99BCB2514, Year: 1999, Value: 0.18 mg/kg\",\"StationNumber: 99BCB2585, Year: 1999, Value: 0.374 mg/kg\",\"StationNumber: 99BCB57/1, Year: 1999, Value: 3.215 mg/kg\",\"StationNumber: 99BCB58/1, Year: 1999, Value: 2.112 mg/kg\",\"StationNumber: 99BCB58/2, Year: 1999, Value: 1.224 mg/kg\",\"StationNumber: 99BCB59/1, Year: 1999, Value: 0.044 mg/kg\",\"StationNumber: 99BCB59/2, Year: 1999, Value: 0.787 mg/kg\",\"StationNumber: 99BCB60/2, Year: 1999, Value: 0.589 mg/kg\",\"StationNumber: 99BCB60/4, Year: 1999, Value: 1.162 mg/kg\",\"StationNumber: 99HB2001, Year: 1999, Value: 0.01 mg/kg\",\"StationNumber: 99HB2012, Year: 1999, Value: 1.721 mg/kg\",\"StationNumber: 99HB2013, Year: 1999, Value: 0.197 mg/kg\",\"StationNumber: 99HB2019, Year: 1999, Value: 0.01 mg/kg\",\"StationNumber: 99HB2040, Year: 1999, Value: 0.331 mg/kg\",\"StationNumber: 99HB2041, Year: 1999, Value: 0.988 mg/kg\",\"StationNumber: 99HB2043, Year: 1999, Value: 0.235 mg/kg\",\"StationNumber: 99HB2044, Year: 1999, Value: 0.82 mg/kg\",\"StationNumber: 99HB2051, Year: 1999, Value: 0.847 mg/kg\",\"StationNumber: 99HB2055, Year: 1999, Value: 1.08 mg/kg\",\"StationNumber: 99HB2058, Year: 1999, Value: 3.832 mg/kg\",\"StationNumber: 99HB2061, Year: 1999, Value: 5.185 mg/kg\",\"StationNumber: 99HB2085, Year: 1999, Value: 3.395 mg/kg\",\"StationNumber: 99HB2094, Year: 1999, Value: 0.205 mg/kg\",\"StationNumber: 99HB2124, Year: 1999, Value: 2.804 mg/kg\",\"StationNumber: 99HB2157, Year: 1999, Value: 0.252 mg/kg\",\"StationNumber: 99HB2176, Year: 1999, Value: 0.468 mg/kg\",\"StationNumber: 99HB2207, Year: 1999, Value: 2.127 mg/kg\",\"StationNumber: 99HB2214, Year: 1999, Value: 0.649 mg/kg\",\"StationNumber: 99HB2233, Year: 1999, Value: 2.896 mg/kg\",\"StationNumber: 99HB2393, Year: 1999, Value: 1.265 mg/kg\",\"StationNumber: 99HB2445, Year: 1999, Value: 1.072 mg/kg\",\"StationNumber: 99HB2757, Year: 1999, Value: 1.051 mg/kg\",\"StationNumber: 99LTB2014, Year: 1999, Value: 0.01 mg/kg\",\"StationNumber: 99LTB2021, Year: 1999, Value: 11.552 mg/kg\",\"StationNumber: 99LTB2041, Year: 1999, Value: 4.997 mg/kg\",\"StationNumber: 99LTB2071, Year: 1999, Value: 5.805 mg/kg\",\"StationNumber: 99LTB2112, Year: 1999, Value: 3.993 mg/kg\",\"StationNumber: 99LTB2124, Year: 1999, Value: 0.035 mg/kg\",\"StationNumber: 99LTB2203, Year: 1999, Value: 0.664 mg/kg\",\"StationNumber: 99LTB2214, Year: 1999, Value: 0.098 mg/kg\",\"StationNumber: 99LTB2247, Year: 1999, Value: 0.297 mg/kg\",\"StationNumber: 99LTB2267, Year: 1999, Value: 1.444 mg/kg\",\"StationNumber: 99LTB2277, Year: 1999, Value: 0.692 mg/kg\",\"StationNumber: 99LTB2290, Year: 1999, Value: 1.374 mg/kg\",\"StationNumber: 99LTB2327, Year: 1999, Value: 0.362 mg/kg\",\"StationNumber: 99LTB2546, Year: 1999, Value: 0.994 mg/kg\",\"StationNumber: 99LTB2617, Year: 1999, Value: 3.167 mg/kg\",\"StationNumber: 99LTB3020, Year: 1999, Value: 0.368 mg/kg\",\"StationNumber: 99MR09, Year: 1999, Value: 0.375 mg/kg\",\"StationNumber: 99MR10, Year: 1999, Value: 0.445 mg/kg\",\"StationNumber: 99MR11, Year: 1999, Value: 1.258 mg/kg\",\"StationNumber: 99MR12, Year: 1999, Value: 0.538 mg/kg\",\"StationNumber: 99MR13, Year: 1999, Value: 0.57 mg/kg\",\"StationNumber: 99MR14, Year: 1999, Value: 0.402 mg/kg\",\"StationNumber: 99MR15, Year: 1999, Value: 0.668 mg/kg\",\"StationNumber: 99MR16, Year: 1999, Value: 0.087 mg/kg\",\"StationNumber: 99MR17, Year: 1999, Value: 0.01 mg/kg\",\"StationNumber: 99MR18, Year: 1999, Value: 0.01 mg/kg\",\"StationNumber: 99MR19, Year: 1999, Value: 0.01 mg/kg\",\"StationNumber: 99MR20, Year: 1999, Value: 0.01 mg/kg\",\"StationNumber: 99MR21, Year: 1999, Value: 0.01 mg/kg\",\"StationNumber: 99MTB2029, Year: 1999, Value: 1.088 mg/kg\",\"StationNumber: 99MTB2059, Year: 1999, Value: 0.528 mg/kg\",\"StationNumber: 99MTB2060, Year: 1999, Value: 0.709 mg/kg\",\"StationNumber: 99MTB2108, Year: 1999, Value: 0.57 mg/kg\",\"StationNumber: 99MTB2109, Year: 1999, Value: 0.25 mg/kg\",\"StationNumber: 99MTB2116, Year: 1999, Value: 0.479 mg/kg\",\"StationNumber: 99MTB2129, Year: 1999, Value: 1.833 mg/kg\",\"StationNumber: 99MTB2149, Year: 1999, Value: 0.968 mg/kg\",\"StationNumber: 99MTB2165, Year: 1999, Value: 0.712 mg/kg\",\"StationNumber: 99MTB2240, Year: 1999, Value: 0.188 mg/kg\",\"StationNumber: 99MTB2243, Year: 1999, Value: 1.994 mg/kg\",\"StationNumber: 99MTB2244, Year: 1999, Value: 2.396 mg/kg\",\"StationNumber: 99MTB2253, Year: 1999, Value: 1.24 mg/kg\",\"StationNumber: 99MTB2268, Year: 1999, Value: 1.218 mg/kg\",\"StationNumber: 99MTB2274, Year: 1999, Value: 2.485 mg/kg\",\"StationNumber: 99MTB2291, Year: 1999, Value: 0.01 mg/kg\",\"StationNumber: 99MTB2358, Year: 1999, Value: 0.699 mg/kg\",\"StationNumber: 99MTB2385, Year: 1999, Value: 0.269 mg/kg\",\"StationNumber: 99MTB2554, Year: 1999, Value: 0.524 mg/kg\",\"StationNumber: 99MTB2598, Year: 1999, Value: 1.573 mg/kg\",\"StationNumber: 99MTB2642, Year: 1999, Value: 0.016 mg/kg\",\"StationNumber: 99OTB2002, Year: 1999, Value: 0.452 mg/kg\",\"StationNumber: 99OTB2005, Year: 1999, Value: 0.022 mg/kg\",\"StationNumber: 99OTB2009, Year: 1999, Value: 0.41 mg/kg\",\"StationNumber: 99OTB2010, Year: 1999, Value: 0.29 mg/kg\",\"StationNumber: 99OTB2022, Year: 1999, Value: 0.836 mg/kg\",\"StationNumber: 99OTB2045, Year: 1999, Value: 0.166 mg/kg\",\"StationNumber: 99OTB2067, Year: 1999, Value: 0.055 mg/kg\",\"StationNumber: 99OTB2111, Year: 1999, Value: 0.071 mg/kg\",\"StationNumber: 99OTB2121, Year: 1999, Value: 0.29 mg/kg\",\"StationNumber: 99OTB2225, Year: 1999, Value: 0.203 mg/kg\",\"StationNumber: 99OTB2296, Year: 1999, Value: 0.839 mg/kg\",\"StationNumber: 99OTB2313, Year: 1999, Value: 0.875 mg/kg\",\"StationNumber: 99OTB2316, Year: 1999, Value: 1.126 mg/kg\",\"StationNumber: 99OTB2331, Year: 1999, Value: 0.353 mg/kg\",\"StationNumber: 99OTB2395, Year: 1999, Value: 0.233 mg/kg\",\"StationNumber: 99OTB2482, Year: 1999, Value: 1.236 mg/kg\",\"StationNumber: 99OTB2908, Year: 1999, Value: 0.307 mg/kg\",\"StationNumber: 99OTB2994, Year: 1999, Value: 0.038 mg/kg\",\"StationNumber: 99OTB3046, Year: 1999, Value: 0.397 mg/kg\",\"StationNumber: 99TCB01, Year: 1999, Value: 1.95 mg/kg\",\"StationNumber: 99TCB02, Year: 1999, Value: 0.225 mg/kg\",\"StationNumber: 99TCB03, Year: 1999, Value: 4.578 mg/kg\",\"StationNumber: 99TCB04, Year: 1999, Value: 2.024 mg/kg\",\"StationNumber: 99TCB05, Year: 1999, Value: 1.134 mg/kg\",\"StationNumber: 99TCB06, Year: 1999, Value: 1.082 mg/kg\",\"StationNumber: 99TCB07, Year: 1999, Value: 1.652 mg/kg\",\"StationNumber: 99TCB08, Year: 1999, Value: 0.01 mg/kg\",\"StationNumber: 00BCB4000, Year: 2000, Value: 7.05 mg/kg\",\"StationNumber: 00BCB4001, Year: 2000, Value: 8.917 mg/kg\",\"StationNumber: 00BCB4004, Year: 2000, Value: 5.717 mg/kg\",\"StationNumber: 00BCB4033, Year: 2000, Value: 6.44 mg/kg\",\"StationNumber: 00BCB4034, Year: 2000, Value: 6.595 mg/kg\",\"StationNumber: 00BCB4037, Year: 2000, Value: 5.573 mg/kg\",\"StationNumber: 00BCB4038, Year: 2000, Value: 7.398 mg/kg\",\"StationNumber: 00BCB4041, Year: 2000, Value: 8.081 mg/kg\",\"StationNumber: 00BCB4042, Year: 2000, Value: 8.315 mg/kg\",\"StationNumber: 00BCB4046, Year: 2000, Value: 7.3 mg/kg\",\"StationNumber: 00BCB4079, Year: 2000, Value: 5.898 mg/kg\",\"StationNumber: 00BCB4084, Year: 2000, Value: 6.968 mg/kg\",\"StationNumber: 00BCB4090, Year: 2000, Value: 8.108 mg/kg\",\"StationNumber: 00BCB4100, Year: 2000, Value: 7.966 mg/kg\",\"StationNumber: 00BCB4124, Year: 2000, Value: 5.814 mg/kg\",\"StationNumber: 00BCB4165, Year: 2000, Value: 5.405 mg/kg\",\"StationNumber: 00BCB4174, Year: 2000, Value: 8.747 mg/kg\",\"StationNumber: 00BCB4207, Year: 2000, Value: 7.704 mg/kg\",\"StationNumber: 00BCB4268, Year: 2000, Value: 7.855 mg/kg\",\"StationNumber: 00BCB4299, Year: 2000, Value: 8.06 mg/kg\",\"StationNumber: 00BCB4312, Year: 2000, Value: 8.316 mg/kg\",\"StationNumber: 00BCB58/1, Year: 2000, Value: 5.498 mg/kg\",\"StationNumber: 00BCB58/2, Year: 2000, Value: 4.644 mg/kg\",\"StationNumber: 00BCB59/1, Year: 2000, Value: 6.148 mg/kg\",\"StationNumber: 00BCB59/2, Year: 2000, Value: 5.036 mg/kg\",\"StationNumber: 00BCB60/2, Year: 2000, Value: 5.003 mg/kg\",\"StationNumber: 00BCB60/4, Year: 2000, Value: 4.842 mg/kg\",\"StationNumber: 00HB4002, Year: 2000, Value: 5.886 mg/kg\",\"StationNumber: 00HB4006, Year: 2000, Value: 6.219 mg/kg\",\"StationNumber: 00HB4019, Year: 2000, Value: 3.684 mg/kg\",\"StationNumber: 00HB4023, Year: 2000, Value: 5.729 mg/kg\",\"StationNumber: 00HB4032, Year: 2000, Value: 5.767 mg/kg\",\"StationNumber: 00HB4033, Year: 2000, Value: 4.768 mg/kg\",\"StationNumber: 00HB4038, Year: 2000, Value: 6.182 mg/kg\",\"StationNumber: 00HB4047, Year: 2000, Value: 5.84 mg/kg\",\"StationNumber: 00HB4058, Year: 2000, Value: 3.097 mg/kg\",\"StationNumber: 00HB4077, Year: 2000, Value: 6.608 mg/kg\",\"StationNumber: 00HB4082, Year: 2000, Value: 6.717 mg/kg\",\"StationNumber: 00HB4083, Year: 2000, Value: 7.399 mg/kg\",\"StationNumber: 00HB4093, Year: 2000, Value: 1.936 mg/kg\",\"StationNumber: 00HB4094, Year: 2000, Value: 2.189 mg/kg\",\"StationNumber: 00HB4100, Year: 2000, Value: 4.324 mg/kg\",\"StationNumber: 00HB4106, Year: 2000, Value: 2.128 mg/kg\",\"StationNumber: 00HB4144, Year: 2000, Value: 1.909 mg/kg\",\"StationNumber: 00HB4152, Year: 2000, Value: 7.008 mg/kg\",\"StationNumber: 00HB4267, Year: 2000, Value: 4.486 mg/kg\",\"StationNumber: 00HB4291, Year: 2000, Value: 4.846 mg/kg\",\"StationNumber: 00HB4316, Year: 2000, Value: 6.769 mg/kg\",\"StationNumber: 00HB4505, Year: 2000, Value: 4.805 mg/kg\",\"StationNumber: 00LTB4039, Year: 2000, Value: 2.434 mg/kg\",\"StationNumber: 00LTB4051, Year: 2000, Value: 4.039 mg/kg\",\"StationNumber: 00LTB4066, Year: 2000, Value: 1.702 mg/kg\",\"StationNumber: 00LTB4117, Year: 2000, Value: 3.904 mg/kg\",\"StationNumber: 00LTB4151, Year: 2000, Value: 5.587 mg/kg\",\"StationNumber: 00LTB4185, Year: 2000, Value: 3.635 mg/kg\",\"StationNumber: 00LTB4286, Year: 2000, Value: 5.878 mg/kg\",\"StationNumber: 00LTB4340, Year: 2000, Value: 2.792 mg/kg\",\"StationNumber: 00LTB4484, Year: 2000, Value: 2.7 mg/kg\",\"StationNumber: 00LTB4487, Year: 2000, Value: 1.721 mg/kg\",\"StationNumber: 00LTB4513, Year: 2000, Value: 1.915 mg/kg\",\"StationNumber: 00LTB4529, Year: 2000, Value: 5.51 mg/kg\",\"StationNumber: 00LTB4536, Year: 2000, Value: 6.17 mg/kg\",\"StationNumber: 00LTB4637, Year: 2000, Value: 9.27 mg/kg\",\"StationNumber: 00LTB4677, Year: 2000, Value: 1.76 mg/kg\",\"StationNumber: 00LTB4730, Year: 2000, Value: 9.63 mg/kg\",\"StationNumber: 00LTB4749, Year: 2000, Value: 1.727 mg/kg\",\"StationNumber: 00MR09, Year: 2000, Value: 7.262 mg/kg\",\"StationNumber: 00MR10, Year: 2000, Value: 7.28 mg/kg\",\"StationNumber: 00MR11, Year: 2000, Value: 7.022 mg/kg\",\"StationNumber: 00MR12, Year: 2000, Value: 6.682 mg/kg\",\"StationNumber: 00MR13, Year: 2000, Value: 6.746 mg/kg\",\"StationNumber: 00MR14, Year: 2000, Value: 5.791 mg/kg\",\"StationNumber: 00MR15, Year: 2000, Value: 5.559 mg/kg\",\"StationNumber: 00MR16, Year: 2000, Value: 4.961 mg/kg\",\"StationNumber: 00MR17, Year: 2000, Value: 5.02 mg/kg\",\"StationNumber: 00MR18, Year: 2000, Value: 5.104 mg/kg\",\"StationNumber: 00MR19, Year: 2000, Value: 7.434 mg/kg\",\"StationNumber: 00MR20, Year: 2000, Value: 2.837 mg/kg\",\"StationNumber: 00MR21, Year: 2000, Value: 4.022 mg/kg\",\"StationNumber: 00MTB4030, Year: 2000, Value: 4.501 mg/kg\",\"StationNumber: 00MTB4032, Year: 2000, Value: 8.919 mg/kg\",\"StationNumber: 00MTB4041, Year: 2000, Value: 2.068 mg/kg\",\"StationNumber: 00MTB4061, Year: 2000, Value: 2.284 mg/kg\",\"StationNumber: 00MTB4072, Year: 2000, Value: 1.826 mg/kg\",\"StationNumber: 00MTB4086, Year: 2000, Value: 1.935 mg/kg\",\"StationNumber: 00MTB4090, Year: 2000, Value: 9.376 mg/kg\",\"StationNumber: 00MTB4098, Year: 2000, Value: 19.11 mg/kg\",\"StationNumber: 00MTB4100, Year: 2000, Value: 5.523 mg/kg\",\"StationNumber: 00MTB4106, Year: 2000, Value: 2.373 mg/kg\",\"StationNumber: 00MTB4159, Year: 2000, Value: 2.926 mg/kg\",\"StationNumber: 00MTB4181, Year: 2000, Value: 5.332 mg/kg\",\"StationNumber: 00MTB4193, Year: 2000, Value: 2.564 mg/kg\",\"StationNumber: 00MTB4201, Year: 2000, Value: 5.145 mg/kg\",\"StationNumber: 00MTB4249, Year: 2000, Value: 5.123 mg/kg\",\"StationNumber: 00MTB4265, Year: 2000, Value: 18.11 mg/kg\",\"StationNumber: 00MTB4310, Year: 2000, Value: 4.749 mg/kg\",\"StationNumber: 00MTB4363, Year: 2000, Value: 5.988 mg/kg\",\"StationNumber: 00MTB4504, Year: 2000, Value: 1.819 mg/kg\",\"StationNumber: 00MTB4584, Year: 2000, Value: 4.649 mg/kg\",\"StationNumber: 00MTB4653, Year: 2000, Value: 6.862 mg/kg\",\"StationNumber: 00MTB4845, Year: 2000, Value: 6.98 mg/kg\",\"StationNumber: 00MTB5125, Year: 2000, Value: 6.297 mg/kg\",\"StationNumber: 00OTB4011, Year: 2000, Value: 6.398 mg/kg\",\"StationNumber: 00OTB4019, Year: 2000, Value: 5.242 mg/kg\",\"StationNumber: 00OTB4037, Year: 2000, Value: 5.554 mg/kg\",\"StationNumber: 00OTB4040, Year: 2000, Value: 6.998 mg/kg\",\"StationNumber: 00OTB4044, Year: 2000, Value: 6.455 mg/kg\",\"StationNumber: 00OTB4096, Year: 2000, Value: 6.509 mg/kg\",\"StationNumber: 00OTB4105, Year: 2000, Value: 4.904 mg/kg\",\"StationNumber: 00OTB4123, Year: 2000, Value: 6.756 mg/kg\",\"StationNumber: 00OTB4132, Year: 2000, Value: 4.869 mg/kg\",\"StationNumber: 00OTB4138, Year: 2000, Value: 5.793 mg/kg\",\"StationNumber: 00OTB4149, Year: 2000, Value: 6.974 mg/kg\",\"StationNumber: 00OTB4192, Year: 2000, Value: 4.798 mg/kg\",\"StationNumber: 00OTB4217, Year: 2000, Value: 6.639 mg/kg\",\"StationNumber: 00OTB4254, Year: 2000, Value: 8.763 mg/kg\",\"StationNumber: 00OTB4278, Year: 2000, Value: 2.048 mg/kg\",\"StationNumber: 00OTB4402, Year: 2000, Value: 7.662 mg/kg\",\"StationNumber: 00OTB4407, Year: 2000, Value: 8.601 mg/kg\",\"StationNumber: 00OTB4650, Year: 2000, Value: 8.558 mg/kg\",\"StationNumber: 00OTB4946, Year: 2000, Value: 7.083 mg/kg\",\"StationNumber: 00TCB01, Year: 2000, Value: 5.933 mg/kg\",\"StationNumber: 00TCB02, Year: 2000, Value: 3.519 mg/kg\",\"StationNumber: 00TCB03, Year: 2000, Value: 9.862 mg/kg\",\"StationNumber: 00TCB04, Year: 2000, Value: 4.401 mg/kg\",\"StationNumber: 00TCB05, Year: 2000, Value: 6.928 mg/kg\",\"StationNumber: 00TCB06, Year: 2000, Value: 6.186 mg/kg\",\"StationNumber: 00TCB07, Year: 2000, Value: 6.023 mg/kg\",\"StationNumber: 00TCB08, Year: 2000, Value: 5.912 mg/kg\",\"StationNumber: 01BCB57/1, Year: 2001, Value: 2.985 mg/kg\",\"StationNumber: 01BCB58/1, Year: 2001, Value: 4.108 mg/kg\",\"StationNumber: 01BCB58/2, Year: 2001, Value: 4.081 mg/kg\",\"StationNumber: 01BCB59/1, Year: 2001, Value: 2.709 mg/kg\",\"StationNumber: 01BCB59/2, Year: 2001, Value: 2.059 mg/kg\",\"StationNumber: 01BCB60/2, Year: 2001, Value: 3.449 mg/kg\",\"StationNumber: 01BCB60/4, Year: 2001, Value: 0.432 mg/kg\",\"StationNumber: 01BCB6001, Year: 2001, Value: 4.072 mg/kg\",\"StationNumber: 01BCB6009, Year: 2001, Value: 3.178 mg/kg\",\"StationNumber: 01BCB6018, Year: 2001, Value: 2.845 mg/kg\",\"StationNumber: 01BCB6019, Year: 2001, Value: 3.296 mg/kg\",\"StationNumber: 01BCB6031, Year: 2001, Value: 3.409 mg/kg\",\"StationNumber: 01BCB6063, Year: 2001, Value: 0.01 mg/kg\",\"StationNumber: 01BCB6072, Year: 2001, Value: 3.246 mg/kg\",\"StationNumber: 01BCB6089, Year: 2001, Value: 2.207 mg/kg\",\"StationNumber: 01BCB6109, Year: 2001, Value: 2.415 mg/kg\",\"StationNumber: 01BCB6114, Year: 2001, Value: 2.628 mg/kg\",\"StationNumber: 01BCB6152, Year: 2001, Value: 2.854 mg/kg\",\"StationNumber: 01BCB6178, Year: 2001, Value: 2.596 mg/kg\",\"StationNumber: 01BCB6190, Year: 2001, Value: 2.145 mg/kg\",\"StationNumber: 01BCB6230, Year: 2001, Value: 3.755 mg/kg\",\"StationNumber: 01BCB6263, Year: 2001, Value: 1.707 mg/kg\",\"StationNumber: 01BCB6359, Year: 2001, Value: 1.433 mg/kg\",\"StationNumber: 01HB6019, Year: 2001, Value: 0.01 mg/kg\",\"StationNumber: 01HB6022, Year: 2001, Value: 1.909 mg/kg\",\"StationNumber: 01HB6032, Year: 2001, Value: 2.588 mg/kg\",\"StationNumber: 01HB6035, Year: 2001, Value: 0.01 mg/kg\",\"StationNumber: 01HB6045, Year: 2001, Value: 0.325 mg/kg\",\"StationNumber: 01HB6064, Year: 2001, Value: 0.01 mg/kg\",\"StationNumber: 01HB6066, Year: 2001, Value: 1.155 mg/kg\",\"StationNumber: 01HB6087, Year: 2001, Value: 0.01 mg/kg\",\"StationNumber: 01HB6093, Year: 2001, Value: 2.265 mg/kg\",\"StationNumber: 01HB6102, Year: 2001, Value: 2.313 mg/kg\",\"StationNumber: 01HB6108, Year: 2001, Value: 0.01 mg/kg\",\"StationNumber: 01HB6131, Year: 2001, Value: 0.71 mg/kg\",\"StationNumber: 01HB6140, Year: 2001, Value: 2.982 mg/kg\",\"StationNumber: 01HB6145, Year: 2001, Value: 2.677 mg/kg\",\"StationNumber: 01HB6159, Year: 2001, Value: 2.869 mg/kg\",\"StationNumber: 01HB6186, Year: 2001, Value: 0.01 mg/kg\",\"StationNumber: 01HB6187, Year: 2001, Value: 3.434 mg/kg\",\"StationNumber: 01HB6249, Year: 2001, Value: 0.01 mg/kg\",\"StationNumber: 01HB6261, Year: 2001, Value: 3.626 mg/kg\",\"StationNumber: 01HB6264, Year: 2001, Value: 1.742 mg/kg\",\"StationNumber: 01HB6283, Year: 2001, Value: 1.357 mg/kg\",\"StationNumber: 01HB6305, Year: 2001, Value: 2.006 mg/kg\",\"StationNumber: 01HB6374, Year: 2001, Value: 0.01 mg/kg\",\"StationNumber: 01HB6453, Year: 2001, Value: 2.977 mg/kg\",\"StationNumber: 01HB6537, Year: 2001, Value: 3.517 mg/kg\",\"StationNumber: 01LTB6026, Year: 2001, Value: 14.165 mg/kg\",\"StationNumber: 01LTB6027, Year: 2001, Value: 1.328 mg/kg\",\"StationNumber: 01LTB6050, Year: 2001, Value: 0.606 mg/kg\",\"StationNumber: 01LTB6104, Year: 2001, Value: 0.01 mg/kg\",\"StationNumber: 01LTB6120, Year: 2001, Value: 0.01 mg/kg\",\"StationNumber: 01LTB6122, Year: 2001, Value: 0.66 mg/kg\",\"StationNumber: 01LTB6158, Year: 2001, Value: 5.092 mg/kg\",\"StationNumber: 01LTB6302, Year: 2001, Value: 0.01 mg/kg\",\"StationNumber: 01LTB6346, Year: 2001, Value: 0 mg/kg\",\"StationNumber: 01LTB6380, Year: 2001, Value: 0.874 mg/kg\",\"StationNumber: 01LTB6595, Year: 2001, Value: 3.852 mg/kg\",\"StationNumber: 01LTB6869, Year: 2001, Value: 0.01 mg/kg\",\"StationNumber: 01MR09, Year: 2001, Value: 0 mg/kg\",\"StationNumber: 01MR12, Year: 2001, Value: 0 mg/kg\",\"StationNumber: 01MR13, Year: 2001, Value: 0 mg/kg\",\"StationNumber: 01MR14, Year: 2001, Value: 0 mg/kg\",\"StationNumber: 01MR17, Year: 2001, Value: 0 mg/kg\",\"StationNumber: 01MR18, Year: 2001, Value: 0 mg/kg\",\"StationNumber: 01MR19, Year: 2001, Value: 0 mg/kg\",\"StationNumber: 01MR20, Year: 2001, Value: 0 mg/kg\",\"StationNumber: 01MR21, Year: 2001, Value: 0 mg/kg\",\"StationNumber: 01MTB6002, Year: 2001, Value: 0.981 mg/kg\",\"StationNumber: 01MTB6011, Year: 2001, Value: 0.416 mg/kg\",\"StationNumber: 01MTB6014, Year: 2001, Value: 0.01 mg/kg\",\"StationNumber: 01MTB6049, Year: 2001, Value: 0.168 mg/kg\",\"StationNumber: 01MTB6059, Year: 2001, Value: 5.14 mg/kg\",\"StationNumber: 01MTB6064, Year: 2001, Value: 3.241 mg/kg\",\"StationNumber: 01MTB6068, Year: 2001, Value: 5.837 mg/kg\",\"StationNumber: 01MTB6080, Year: 2001, Value: 3.556 mg/kg\",\"StationNumber: 01MTB6133, Year: 2001, Value: 2.453 mg/kg\",\"StationNumber: 01MTB6154, Year: 2001, Value: 0.963 mg/kg\",\"StationNumber: 01MTB6188, Year: 2001, Value: 0.797 mg/kg\",\"StationNumber: 01MTB6189, Year: 2001, Value: 2.868 mg/kg\",\"StationNumber: 01MTB6196, Year: 2001, Value: 2.703 mg/kg\",\"StationNumber: 01MTB6229, Year: 2001, Value: 2.698 mg/kg\",\"StationNumber: 01MTB6257, Year: 2001, Value: 0.988 mg/kg\",\"StationNumber: 01MTB6265, Year: 2001, Value: 4.324 mg/kg\",\"StationNumber: 01MTB6290, Year: 2001, Value: 3.339 mg/kg\",\"StationNumber: 01MTB6325, Year: 2001, Value: 2.765 mg/kg\",\"StationNumber: 01MTB6327, Year: 2001, Value: 4.862 mg/kg\",\"StationNumber: 01MTB6328, Year: 2001, Value: 3.179 mg/kg\",\"StationNumber: 01MTB6464, Year: 2001, Value: 3.707 mg/kg\",\"StationNumber: 01MTB6495, Year: 2001, Value: 3.297 mg/kg\",\"StationNumber: 01MTB6527, Year: 2001, Value: 3.538 mg/kg\",\"StationNumber: 01MTB6638, Year: 2001, Value: 4.338 mg/kg\",\"StationNumber: 01MTB6699, Year: 2001, Value: 4.171 mg/kg\",\"StationNumber: 01MTB7153, Year: 2001, Value: 3.938 mg/kg\",\"StationNumber: 01OTB6010, Year: 2001, Value: 3.892 mg/kg\",\"StationNumber: 01OTB6017, Year: 2001, Value: 3.183 mg/kg\",\"StationNumber: 01OTB6021, Year: 2001, Value: 2.793 mg/kg\",\"StationNumber: 01OTB6022, Year: 2001, Value: 1.206 mg/kg\",\"StationNumber: 01OTB6025, Year: 2001, Value: 0.01 mg/kg\",\"StationNumber: 01OTB6028, Year: 2001, Value: 5.384 mg/kg\",\"StationNumber: 01OTB6078, Year: 2001, Value: 3.845 mg/kg\",\"StationNumber: 01OTB6103, Year: 2001, Value: 5.634 mg/kg\",\"StationNumber: 01OTB6135, Year: 2001, Value: 2.772 mg/kg\",\"StationNumber: 01OTB6152, Year: 2001, Value: 28.868 mg/kg\",\"StationNumber: 01OTB6178, Year: 2001, Value: 9.713 mg/kg\",\"StationNumber: 01OTB6186, Year: 2001, Value: 5.55 mg/kg\",\"StationNumber: 01OTB6234, Year: 2001, Value: 5.199 mg/kg\",\"StationNumber: 01OTB6239, Year: 2001, Value: 0.01 mg/kg\",\"StationNumber: 01OTB6441, Year: 2001, Value: 5.652 mg/kg\",\"StationNumber: 01OTB6784, Year: 2001, Value: 10.207 mg/kg\",\"StationNumber: 01OTB6830, Year: 2001, Value: 5.184 mg/kg\",\"StationNumber: 01SAFHAB, Year: 2001, Value: 0.01 mg/kg\",\"StationNumber: 01TCB02, Year: 2001, Value: 0 mg/kg\",\"StationNumber: 01TCB03, Year: 2001, Value: 0 mg/kg\",\"StationNumber: 01TCB04, Year: 2001, Value: 0 mg/kg\",\"StationNumber: 01TCB06, Year: 2001, Value: 0 mg/kg\",\"StationNumber: 01TCB07, Year: 2001, Value: 0 mg/kg\",\"StationNumber: 02BCB05, Year: 2002, Value: 5.202 mg/kg\",\"StationNumber: 02BCB20, Year: 2002, Value: 1.257 mg/kg\",\"StationNumber: 02BCB32, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02BCB52, Year: 2002, Value: 0.407 mg/kg\",\"StationNumber: 02BCB62, Year: 2002, Value: 3.401 mg/kg\",\"StationNumber: 02BCB69, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02BCB74, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02BCB83, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02BCB90, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH03-2, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH03-4, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH03-5, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH05-3, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH05-4, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH05-5, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH07-1, Year: 2002, Value: 0.426 mg/kg\",\"StationNumber: 02DH07-2, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH07-3, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH08-1, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH08-2, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH08-3, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH09-1, Year: 2002, Value: 2.957 mg/kg\",\"StationNumber: 02DH09-2, Year: 2002, Value: 1.154 mg/kg\",\"StationNumber: 02DH09-3, Year: 2002, Value: 3.812 mg/kg\",\"StationNumber: 02DH11A-1, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH11A-2, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH11A-3, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH11B-1, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH11B-4, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH11B-5, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH14-1, Year: 2002, Value: 1.74 mg/kg\",\"StationNumber: 02DH14-3, Year: 2002, Value: 1.197 mg/kg\",\"StationNumber: 02DH14-4, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH15-1, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH15-2, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH15-5, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH18-1, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH18-2, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH18-3, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH20-3, Year: 2002, Value: 0.146 mg/kg\",\"StationNumber: 02DH20-4, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH20-5, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH21A-1, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH21A-3, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH21A-5, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH21B-1, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH21B-3, Year: 2002, Value: 0.323 mg/kg\",\"StationNumber: 02DH21B-4, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02HB09, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02HB20, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02HB21, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02HB27, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02HB39, Year: 2002, Value: 0.328 mg/kg\",\"StationNumber: 02HB42, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02HB49, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02HB50, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02HB51, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02HB55, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02LTB01, Year: 2002, Value: 3.105 mg/kg\",\"StationNumber: 02LTB02, Year: 2002, Value: 4.432 mg/kg\",\"StationNumber: 02LTB03, Year: 2002, Value: 0.925 mg/kg\",\"StationNumber: 02LTB04, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02LTB05, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02LTB06, Year: 2002, Value: 0.657 mg/kg\",\"StationNumber: 02LTB07, Year: 2002, Value: 0.376 mg/kg\",\"StationNumber: 02LTB08, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02LTB09, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02MR02, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02MR04, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02MR06, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02MR08, Year: 2002, Value: 0.022 mg/kg\",\"StationNumber: 02MR10, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02MR11, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02MR12, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02MTB11, Year: 2002, Value: 0.563 mg/kg\",\"StationNumber: 02MTB12, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02MTB18, Year: 2002, Value: 1.634 mg/kg\",\"StationNumber: 02MTB19, Year: 2002, Value: 6.859 mg/kg\",\"StationNumber: 02MTB21, Year: 2002, Value: 0.379 mg/kg\",\"StationNumber: 02MTB23, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02MTB27, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02MTB29, Year: 2002, Value: 4.363 mg/kg\",\"StationNumber: 02MTB32, Year: 2002, Value: 0.595 mg/kg\",\"StationNumber: 02MTB34, Year: 2002, Value: 0.126 mg/kg\",\"StationNumber: 02OTB02, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02OTB04, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02OTB27, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02OTB49, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02OTB50, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02OTB52, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02OTB60, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02OTB66, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02TCB03, Year: 2002, Value: 1.409 mg/kg\",\"StationNumber: 02TCB05, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02TCB07, Year: 2002, Value: 3.347 mg/kg\",\"StationNumber: 02TCB09, Year: 2002, Value: 0.612 mg/kg\",\"StationNumber: 03BCB107, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03BCB120, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03BCB126, Year: 2003, Value: 0.086 mg/kg\",\"StationNumber: 03BCB190, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03BCB230, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03BCB242, Year: 2003, Value: 2.439 mg/kg\",\"StationNumber: 03BCB278, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03BCB287, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03BCB338, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03BCB439, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03HB01, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03HB02, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03HB04, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03HB06, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03HB09, Year: 2003, Value: 5.878 mg/kg\",\"StationNumber: 03HB10, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03HB11, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03HB12, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03HB14, Year: 2003, Value: 0.176 mg/kg\",\"StationNumber: 03HB16, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03HB18, Year: 2003, Value: 1.028 mg/kg\",\"StationNumber: 03HB21, Year: 2003, Value: 3.834 mg/kg\",\"StationNumber: 03HB27, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03HB28, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03HB30, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03HB32, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03HB33, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03HB34, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03HB37, Year: 2003, Value: 0.988 mg/kg\",\"StationNumber: 03HB38, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03HB41, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03HB42, Year: 2003, Value: 1.908 mg/kg\",\"StationNumber: 03HB44, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03HB47, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03HB50, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03HB51, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03HB52, Year: 2003, Value: 3.438 mg/kg\",\"StationNumber: 03HB53, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03LTB01, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03LTB02, Year: 2003, Value: 7.824 mg/kg\",\"StationNumber: 03LTB03, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03LTB04, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03LTB05, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03LTB06, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03LTB07, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03LTB08, Year: 2003, Value: 1.746 mg/kg\",\"StationNumber: 03LTB09, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03LTB10, Year: 2003, Value: 3.726 mg/kg\",\"StationNumber: 03LTB11, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03LTB12, Year: 2003, Value: 5.634 mg/kg\",\"StationNumber: 03MR02, Year: 2003, Value: 0.283 mg/kg\",\"StationNumber: 03MR04, Year: 2003, Value: 0.17 mg/kg\",\"StationNumber: 03MR06, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03MR07, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03MR08, Year: 2003, Value: 0.608 mg/kg\",\"StationNumber: 03MR09, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03MR10, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03MTB03, Year: 2003, Value: 1.161 mg/kg\",\"StationNumber: 03MTB08, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03MTB10, Year: 2003, Value: 1.265 mg/kg\",\"StationNumber: 03MTB11, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03MTB13, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03MTB14, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03MTB15, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03MTB16, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03MTB17, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03MTB18, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03MTB19, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03MTB21, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03MTB24, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03MTB25, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03MTB27, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03MTB28, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03MTB30, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03MTB31, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03MTB32, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03MTB33, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03MTB34, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03MTB35, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03OTB157, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03OTB200, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03OTB413, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03OTB414, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03OTB507, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03OTB623, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03OTB706, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03OTB794, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03OTB929, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03TCB01, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03TCB03, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03TCB05, Year: 2003, Value: 3.05 mg/kg\",\"StationNumber: 04BCB01, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04BCB02, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04BCB03, Year: 2004, Value: 2.501 mg/kg\",\"StationNumber: 04BCB04, Year: 2004, Value: 0.51 mg/kg\",\"StationNumber: 04BCB05, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04BCB06, Year: 2004, Value: 0.839 mg/kg\",\"StationNumber: 04BCB07, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04BCB08, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04BCB09, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04BCB10, Year: 2004, Value: 2.332 mg/kg\",\"StationNumber: 04HB01, Year: 2004, Value: 0.523 mg/kg\",\"StationNumber: 04HB02, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04HB03, Year: 2004, Value: 0.552 mg/kg\",\"StationNumber: 04HB04, Year: 2004, Value: 1.214 mg/kg\",\"StationNumber: 04HB05, Year: 2004, Value: 0.346 mg/kg\",\"StationNumber: 04HB06, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04HB07, Year: 2004, Value: 1.338 mg/kg\",\"StationNumber: 04HB08, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04HB09, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04HB10, Year: 2004, Value: 2.967 mg/kg\",\"StationNumber: 04HB11, Year: 2004, Value: 0.026 mg/kg\",\"StationNumber: 04HB12, Year: 2004, Value: 0.348 mg/kg\",\"StationNumber: 04HB13, Year: 2004, Value: 0.431 mg/kg\",\"StationNumber: 04HB14, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04HB15, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04HB16, Year: 2004, Value: 0.477 mg/kg\",\"StationNumber: 04HB17, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04HB18, Year: 2004, Value: 2.08 mg/kg\",\"StationNumber: 04HB19, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04HB20, Year: 2004, Value: 0.117 mg/kg\",\"StationNumber: 04HB21, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04HB23, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04HB24, Year: 2004, Value: 0.37 mg/kg\",\"StationNumber: 04HB25, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04HB26, Year: 2004, Value: 0.004 mg/kg\",\"StationNumber: 04LTB01, Year: 2004, Value: 3.535 mg/kg\",\"StationNumber: 04LTB02, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04LTB03, Year: 2004, Value: 0.715 mg/kg\",\"StationNumber: 04LTB04, Year: 2004, Value: 2.723 mg/kg\",\"StationNumber: 04LTB05, Year: 2004, Value: 0.562 mg/kg\",\"StationNumber: 04LTB06, Year: 2004, Value: 3.492 mg/kg\",\"StationNumber: 04LTB07, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04LTB08, Year: 2004, Value: 4.848 mg/kg\",\"StationNumber: 04LTB09, Year: 2004, Value: 0.25 mg/kg\",\"StationNumber: 04LTB10, Year: 2004, Value: 1.579 mg/kg\",\"StationNumber: 04LTB11, Year: 2004, Value: 1.156 mg/kg\",\"StationNumber: 04MR01, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04MR02, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04MR03, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04MR04, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04MR05, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04MR06, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04MR08, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04MR09, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04MR10, Year: 2004, Value: 0.32 mg/kg\",\"StationNumber: 04MR11, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04MTB01, Year: 2004, Value: 2.748 mg/kg\",\"StationNumber: 04MTB02, Year: 2004, Value: 2.306 mg/kg\",\"StationNumber: 04MTB04, Year: 2004, Value: 0.557 mg/kg\",\"StationNumber: 04MTB05, Year: 2004, Value: 1.049 mg/kg\",\"StationNumber: 04MTB06, Year: 2004, Value: 1.363 mg/kg\",\"StationNumber: 04MTB07, Year: 2004, Value: 0.169 mg/kg\",\"StationNumber: 04MTB08, Year: 2004, Value: 0.219 mg/kg\",\"StationNumber: 04MTB09, Year: 2004, Value: 1.226 mg/kg\",\"StationNumber: 04MTB10, Year: 2004, Value: 1.518 mg/kg\",\"StationNumber: 04MTB11, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04MTB12, Year: 2004, Value: 1.075 mg/kg\",\"StationNumber: 04MTB13, Year: 2004, Value: 0.444 mg/kg\",\"StationNumber: 04MTB14, Year: 2004, Value: 0.936 mg/kg\",\"StationNumber: 04MTB15, Year: 2004, Value: 0.83 mg/kg\",\"StationNumber: 04MTB16, Year: 2004, Value: 1.378 mg/kg\",\"StationNumber: 04MTB17, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04MTB18, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04MTB19, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04MTB20, Year: 2004, Value: 0.469 mg/kg\",\"StationNumber: 04MTB21, Year: 2004, Value: 16.571 mg/kg\",\"StationNumber: 04MTB22, Year: 2004, Value: 0.19 mg/kg\",\"StationNumber: 04MTB24, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04OTB01, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04OTB02, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04OTB03, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04OTB04, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04OTB05, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04OTB06, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04OTB07, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04OTB08, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04OTB09, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04TCB07, Year: 2004, Value: 1.789 mg/kg\",\"StationNumber: 05BCB01, Year: 2005, Value: 0.505 mg/kg\",\"StationNumber: 05BCB02, Year: 2005, Value: 0.245 mg/kg\",\"StationNumber: 05BCB03, Year: 2005, Value: 0.638 mg/kg\",\"StationNumber: 05BCB04, Year: 2005, Value: 0.791 mg/kg\",\"StationNumber: 05BCB05, Year: 2005, Value: 6.022 mg/kg\",\"StationNumber: 05BCB06, Year: 2005, Value: 2.432 mg/kg\",\"StationNumber: 05BCB07, Year: 2005, Value: 0.357 mg/kg\",\"StationNumber: 05BCB08, Year: 2005, Value: 1.489 mg/kg\",\"StationNumber: 05BCB09, Year: 2005, Value: 0.987 mg/kg\",\"StationNumber: 05BCB10, Year: 2005, Value: 0.021 mg/kg\",\"StationNumber: 05HB01, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05HB02, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05HB03, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05HB04, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05HB05, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05HB06, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05HB07, Year: 2005, Value: 0.733 mg/kg\",\"StationNumber: 05HB08, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05HB09, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05HB10, Year: 2005, Value: 0.598 mg/kg\",\"StationNumber: 05HB11, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05HB12, Year: 2005, Value: 3.811 mg/kg\",\"StationNumber: 05HB13, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05HB14, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05HB15, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05HB16, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05HB17, Year: 2005, Value: 0.036 mg/kg\",\"StationNumber: 05HB18, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05HB19, Year: 2005, Value: 0.322 mg/kg\",\"StationNumber: 05HB20, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05HB21, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05HB22, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05HB23, Year: 2005, Value: 0.616 mg/kg\",\"StationNumber: 05HB24, Year: 2005, Value: 2.172 mg/kg\",\"StationNumber: 05LTB01, Year: 2005, Value: 5.537 mg/kg\",\"StationNumber: 05LTB02, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05LTB03, Year: 2005, Value: 2.554 mg/kg\",\"StationNumber: 05LTB04, Year: 2005, Value: 2.548 mg/kg\",\"StationNumber: 05LTB05, Year: 2005, Value: 1.008 mg/kg\",\"StationNumber: 05LTB06, Year: 2005, Value: 2.134 mg/kg\",\"StationNumber: 05LTB07, Year: 2005, Value: 3.24 mg/kg\",\"StationNumber: 05LTB08, Year: 2005, Value: 2.144 mg/kg\",\"StationNumber: 05LTB09, Year: 2005, Value: 4.455 mg/kg\",\"StationNumber: 05LTB10, Year: 2005, Value: 0.116 mg/kg\",\"StationNumber: 05LTB11, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05MR02, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05MR04, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05MR06, Year: 2005, Value: 1.085 mg/kg\",\"StationNumber: 05MR08, Year: 2005, Value: 0.372 mg/kg\",\"StationNumber: 05MR09, Year: 2005, Value: 0.97 mg/kg\",\"StationNumber: 05MR11, Year: 2005, Value: 0.271 mg/kg\",\"StationNumber: 05MTB01, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05MTB02, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05MTB03, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05MTB04, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05MTB05, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05MTB06, Year: 2005, Value: 0.691 mg/kg\",\"StationNumber: 05MTB07, Year: 2005, Value: 0.685 mg/kg\",\"StationNumber: 05MTB08, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05MTB09, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05MTB10, Year: 2005, Value: 0.871 mg/kg\",\"StationNumber: 05MTB11, Year: 2005, Value: 0.609 mg/kg\",\"StationNumber: 05MTB12, Year: 2005, Value: 0.585 mg/kg\",\"StationNumber: 05MTB13, Year: 2005, Value: 1.943 mg/kg\",\"StationNumber: 05MTB14, Year: 2005, Value: 8.527 mg/kg\",\"StationNumber: 05MTB15, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05MTB16, Year: 2005, Value: 0.45 mg/kg\",\"StationNumber: 05MTB17, Year: 2005, Value: 0.043 mg/kg\",\"StationNumber: 05MTB18, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05MTB19, Year: 2005, Value: 0.177 mg/kg\",\"StationNumber: 05MTB20, Year: 2005, Value: 2.689 mg/kg\",\"StationNumber: 05MTB21, Year: 2005, Value: 0.156 mg/kg\",\"StationNumber: 05MTB22, Year: 2005, Value: 0.31 mg/kg\",\"StationNumber: 05OTB01, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05OTB02, Year: 2005, Value: 0.308 mg/kg\",\"StationNumber: 05OTB03, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05OTB04, Year: 2005, Value: 0.154 mg/kg\",\"StationNumber: 05OTB05, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05OTB06, Year: 2005, Value: 0.727 mg/kg\",\"StationNumber: 05OTB07, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05OTB08, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05OTB09, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05OTB10, Year: 2005, Value: 0.348 mg/kg\",\"StationNumber: 05TCB01, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05TCB03, Year: 2005, Value: 1.689 mg/kg\",\"StationNumber: 05TCB05, Year: 2005, Value: 1.313 mg/kg\",\"StationNumber: 05TCB07, Year: 2005, Value: 0.98 mg/kg\",\"StationNumber: 05TCB10, Year: 2005, Value: 2.404 mg/kg\",\"StationNumber: 06BCB01, Year: 2006, Value: 10.76 mg/kg\",\"StationNumber: 06BCB02, Year: 2006, Value: 7.6 mg/kg\",\"StationNumber: 06BCB03, Year: 2006, Value: 6.966 mg/kg\",\"StationNumber: 06BCB04, Year: 2006, Value: 6.49 mg/kg\",\"StationNumber: 06BCB05, Year: 2006, Value: 1.041 mg/kg\",\"StationNumber: 06BCB06, Year: 2006, Value: 5.932 mg/kg\",\"StationNumber: 06BCB07, Year: 2006, Value: 0.01 mg/kg\",\"StationNumber: 06BCB08, Year: 2006, Value: 2.144 mg/kg\",\"StationNumber: 06BCB09, Year: 2006, Value: 6.173 mg/kg\",\"StationNumber: 06HB01, Year: 2006, Value: 0.768 mg/kg\",\"StationNumber: 06HB02, Year: 2006, Value: 6.388 mg/kg\",\"StationNumber: 06HB03, Year: 2006, Value: 0.01 mg/kg\",\"StationNumber: 06HB04, Year: 2006, Value: 5.29 mg/kg\",\"StationNumber: 06HB05, Year: 2006, Value: 0.01 mg/kg\",\"StationNumber: 06HB06, Year: 2006, Value: 8.423 mg/kg\",\"StationNumber: 06HB08, Year: 2006, Value: 4.515 mg/kg\",\"StationNumber: 06HB09, Year: 2006, Value: 0.01 mg/kg\",\"StationNumber: 06HB10, Year: 2006, Value: 9.296 mg/kg\",\"StationNumber: 06HB11, Year: 2006, Value: 9.144 mg/kg\",\"StationNumber: 06HB12, Year: 2006, Value: 1.668 mg/kg\",\"StationNumber: 06HB13, Year: 2006, Value: 0.01 mg/kg\",\"StationNumber: 06HB14, Year: 2006, Value: 0.01 mg/kg\",\"StationNumber: 06HB15, Year: 2006, Value: 3.641 mg/kg\",\"StationNumber: 06HB16, Year: 2006, Value: 3.091 mg/kg\",\"StationNumber: 06HB17, Year: 2006, Value: 0.01 mg/kg\",\"StationNumber: 06HB18, Year: 2006, Value: 0.01 mg/kg\",\"StationNumber: 06HB19, Year: 2006, Value: 0.01 mg/kg\",\"StationNumber: 06HB20, Year: 2006, Value: 0.01 mg/kg\",\"StationNumber: 06HB21, Year: 2006, Value: 0.01 mg/kg\",\"StationNumber: 06HB22, Year: 2006, Value: 0.958 mg/kg\",\"StationNumber: 06HB23, Year: 2006, Value: 0.01 mg/kg\",\"StationNumber: 06HB24, Year: 2006, Value: 0.867 mg/kg\",\"StationNumber: 06HB25, Year: 2006, Value: 3.199 mg/kg\",\"StationNumber: 06LTB01, Year: 2006, Value: 5.442 mg/kg\",\"StationNumber: 06LTB02, Year: 2006, Value: 6.614 mg/kg\",\"StationNumber: 06LTB03, Year: 2006, Value: 13.302 mg/kg\",\"StationNumber: 06LTB04, Year: 2006, Value: 9.592 mg/kg\",\"StationNumber: 06LTB05, Year: 2006, Value: 6.313 mg/kg\",\"StationNumber: 06LTB06, Year: 2006, Value: 8.886 mg/kg\",\"StationNumber: 06LTB07, Year: 2006, Value: 7.536 mg/kg\",\"StationNumber: 06LTB08, Year: 2006, Value: 6.973 mg/kg\",\"StationNumber: 06MR05, Year: 2006, Value: 0.01 mg/kg\",\"StationNumber: 06MR06, Year: 2006, Value: 6.076 mg/kg\",\"StationNumber: 06MR07, Year: 2006, Value: 1.121 mg/kg\",\"StationNumber: 06MR08, Year: 2006, Value: 6.41 mg/kg\",\"StationNumber: 06MR10, Year: 2006, Value: 0.01 mg/kg\",\"StationNumber: 06MTB01, Year: 2006, Value: 21.691 mg/kg\",\"StationNumber: 06MTB02, Year: 2006, Value: 7.887 mg/kg\",\"StationNumber: 06MTB03, Year: 2006, Value: 0.01 mg/kg\",\"StationNumber: 06MTB04, Year: 2006, Value: 5.141 mg/kg\",\"StationNumber: 06MTB05, Year: 2006, Value: 6.599 mg/kg\",\"StationNumber: 06MTB06, Year: 2006, Value: 0.01 mg/kg\",\"StationNumber: 06MTB07, Year: 2006, Value: 8.465 mg/kg\",\"StationNumber: 06MTB08, Year: 2006, Value: 7.305 mg/kg\",\"StationNumber: 06MTB09, Year: 2006, Value: 9.749 mg/kg\",\"StationNumber: 06MTB10, Year: 2006, Value: 7.082 mg/kg\",\"StationNumber: 06MTB11, Year: 2006, Value: 4.9 mg/kg\",\"StationNumber: 06MTB12, Year: 2006, Value: 5.42 mg/kg\",\"StationNumber: 06MTB13, Year: 2006, Value: 2.843 mg/kg\",\"StationNumber: 06MTB14, Year: 2006, Value: 6.476 mg/kg\",\"StationNumber: 06MTB15, Year: 2006, Value: 6.64 mg/kg\",\"StationNumber: 06MTB16, Year: 2006, Value: 5.146 mg/kg\",\"StationNumber: 06MTB17, Year: 2006, Value: 8.46 mg/kg\",\"StationNumber: 06MTB18, Year: 2006, Value: 1.724 mg/kg\",\"StationNumber: 06MTB19, Year: 2006, Value: 5.701 mg/kg\",\"StationNumber: 06OTB01, Year: 2006, Value: 5.045 mg/kg\",\"StationNumber: 06OTB02, Year: 2006, Value: 6.294 mg/kg\",\"StationNumber: 06OTB03, Year: 2006, Value: 5.32 mg/kg\",\"StationNumber: 06OTB04, Year: 2006, Value: 5.697 mg/kg\",\"StationNumber: 06OTB05, Year: 2006, Value: 2.581 mg/kg\",\"StationNumber: 06OTB06, Year: 2006, Value: 0.01 mg/kg\",\"StationNumber: 06OTB07, Year: 2006, Value: 2.085 mg/kg\",\"StationNumber: 06OTB08, Year: 2006, Value: 5.097 mg/kg\",\"StationNumber: 06TCB01, Year: 2006, Value: 0.01 mg/kg\",\"StationNumber: 06TCB02, Year: 2006, Value: 0.01 mg/kg\",\"StationNumber: 06TCB03, Year: 2006, Value: 0.01 mg/kg\",\"StationNumber: 06TCB04, Year: 2006, Value: 0.01 mg/kg\",\"StationNumber: 06TCB09, Year: 2006, Value: 0.189 mg/kg\",\"StationNumber: 07BCB06, Year: 2007, Value: 0.01 mg/kg\",\"StationNumber: 07BCB09, Year: 2007, Value: 0.01 mg/kg\",\"StationNumber: 07BCB15, Year: 2007, Value: 7.27 mg/kg\",\"StationNumber: 07BCB28, Year: 2007, Value: 6.46 mg/kg\",\"StationNumber: 07BCB29, Year: 2007, Value: 0.61 mg/kg\",\"StationNumber: 07BCB30, Year: 2007, Value: 9.62 mg/kg\",\"StationNumber: 07BCB41, Year: 2007, Value: 6.85 mg/kg\",\"StationNumber: 07BCB42, Year: 2007, Value: 11.82 mg/kg\",\"StationNumber: 07BCB44, Year: 2007, Value: 7.13 mg/kg\",\"StationNumber: 07BCB45, Year: 2007, Value: 8.32 mg/kg\",\"StationNumber: 07HB13, Year: 2007, Value: 0.01 mg/kg\",\"StationNumber: 07HB21, Year: 2007, Value: 0.01 mg/kg\",\"StationNumber: 07HB34, Year: 2007, Value: 0.01 mg/kg\",\"StationNumber: 07HB37, Year: 2007, Value: 0.01 mg/kg\",\"StationNumber: 07HB38, Year: 2007, Value: 0.01 mg/kg\",\"StationNumber: 07HB41, Year: 2007, Value: 0.01 mg/kg\",\"StationNumber: 07HB42, Year: 2007, Value: 0.01 mg/kg\",\"StationNumber: 07HB44, Year: 2007, Value: 0.01 mg/kg\",\"StationNumber: 07HB53, Year: 2007, Value: 0.01 mg/kg\",\"StationNumber: 07LTB91, Year: 2007, Value: 0.01 mg/kg\",\"StationNumber: 07MR09, Year: 2007, Value: 0.11 mg/kg\",\"StationNumber: 07MR28, Year: 2007, Value: 0.01 mg/kg\",\"StationNumber: 07MR42, Year: 2007, Value: 0.01 mg/kg\",\"StationNumber: 07MR46, Year: 2007, Value: 0.01 mg/kg\",\"StationNumber: 07MR50, Year: 2007, Value: 0.01 mg/kg\",\"StationNumber: 07MTB34, Year: 2007, Value: 9.44 mg/kg\",\"StationNumber: 07MTB39, Year: 2007, Value: 4.6 mg/kg\",\"StationNumber: 07MTB40, Year: 2007, Value: 0.01 mg/kg\",\"StationNumber: 07MTB43, Year: 2007, Value: 0.51 mg/kg\",\"StationNumber: 07MTB44, Year: 2007, Value: 0.01 mg/kg\",\"StationNumber: 07MTB47, Year: 2007, Value: 10.84 mg/kg\",\"StationNumber: 07MTB54, Year: 2007, Value: 13.61 mg/kg\",\"StationNumber: 07OTB04, Year: 2007, Value: 0.01 mg/kg\",\"StationNumber: 07OTB08, Year: 2007, Value: 7.25 mg/kg\",\"StationNumber: 07OTB18, Year: 2007, Value: 0.01 mg/kg\",\"StationNumber: 07OTB21, Year: 2007, Value: 2.99 mg/kg\",\"StationNumber: 07OTB24, Year: 2007, Value: 3.72 mg/kg\",\"StationNumber: 07OTB25, Year: 2007, Value: 7.21 mg/kg\",\"StationNumber: 07OTB31, Year: 2007, Value: 10.48 mg/kg\",\"StationNumber: 07TCB14, Year: 2007, Value: 0.01 mg/kg\",\"StationNumber: 07TCB15, Year: 2007, Value: 0.01 mg/kg\",\"StationNumber: 07TCB20, Year: 2007, Value: 8.27 mg/kg\",\"StationNumber: 07TCB22, Year: 2007, Value: 1.55 mg/kg\",\"StationNumber: 08BCB02, Year: 2008, Value: 2.25 mg/kg\",\"StationNumber: 08BCB05, Year: 2008, Value: 0.01 mg/kg\",\"StationNumber: 08BCB12, Year: 2008, Value: 0.01 mg/kg\",\"StationNumber: 08BCB15, Year: 2008, Value: 0.01 mg/kg\",\"StationNumber: 08BCB16, Year: 2008, Value: 4.4 mg/kg\",\"StationNumber: 08BCB17, Year: 2008, Value: 3.34 mg/kg\",\"StationNumber: 08BCB23, Year: 2008, Value: 0.01 mg/kg\",\"StationNumber: 08BCB26, Year: 2008, Value: 9.9 mg/kg\",\"StationNumber: 08BCB29, Year: 2008, Value: 7.8 mg/kg\",\"StationNumber: 08BCB35, Year: 2008, Value: 7.83 mg/kg\",\"StationNumber: 08BCB38, Year: 2008, Value: 6.95 mg/kg\",\"StationNumber: 08HB13, Year: 2008, Value: 0.01 mg/kg\",\"StationNumber: 08HB14, Year: 2008, Value: 0.01 mg/kg\",\"StationNumber: 08HB17, Year: 2008, Value: 0.01 mg/kg\",\"StationNumber: 08HB21, Year: 2008, Value: 0.01 mg/kg\",\"StationNumber: 08HB27, Year: 2008, Value: 0.01 mg/kg\",\"StationNumber: 08HB34, Year: 2008, Value: 4.62 mg/kg\",\"StationNumber: 08HB43, Year: 2008, Value: 4.15 mg/kg\",\"StationNumber: 08HB44, Year: 2008, Value: 6.35 mg/kg\",\"StationNumber: 08HB48, Year: 2008, Value: 7.51 mg/kg\",\"StationNumber: 08LTB69, Year: 2008, Value: 9.07 mg/kg\",\"StationNumber: 08LTB79, Year: 2008, Value: 22.19 mg/kg\",\"StationNumber: 08LTB82, Year: 2008, Value: 9.06 mg/kg\",\"StationNumber: 08MR08, Year: 2008, Value: 11.03 mg/kg\",\"StationNumber: 08MR35, Year: 2008, Value: 6.78 mg/kg\",\"StationNumber: 08MR40, Year: 2008, Value: 2.73 mg/kg\",\"StationNumber: 08MR43, Year: 2008, Value: 0.01 mg/kg\",\"StationNumber: 08MR53, Year: 2008, Value: 4.18 mg/kg\",\"StationNumber: 08MR54, Year: 2008, Value: 5.54 mg/kg\",\"StationNumber: 08MTB37, Year: 2008, Value: 6.6 mg/kg\",\"StationNumber: 08MTB47, Year: 2008, Value: 8.06 mg/kg\",\"StationNumber: 08MTB53, Year: 2008, Value: 0 mg/kg\",\"StationNumber: 08MTB62, Year: 2008, Value: 11.22 mg/kg\",\"StationNumber: 08MTB73, Year: 2008, Value: 4.04 mg/kg\",\"StationNumber: 08OTB05, Year: 2008, Value: 0.01 mg/kg\",\"StationNumber: 08OTB07, Year: 2008, Value: 0.46 mg/kg\",\"StationNumber: 08OTB13, Year: 2008, Value: 6.98 mg/kg\",\"StationNumber: 08OTB15, Year: 2008, Value: 3.77 mg/kg\",\"StationNumber: 08OTB17, Year: 2008, Value: 8.33 mg/kg\",\"StationNumber: 08OTB23, Year: 2008, Value: 11.18 mg/kg\",\"StationNumber: 08OTB27, Year: 2008, Value: 9.44 mg/kg\",\"StationNumber: 08TCB01, Year: 2008, Value: 1.91 mg/kg\",\"StationNumber: 08TCB07, Year: 2008, Value: 0.01 mg/kg\",\"StationNumber: 08TCB26, Year: 2008, Value: 0.07 mg/kg\",\"StationNumber: 10BCB06, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10BCB11, Year: 2010, Value: 5.82 mg/kg\",\"StationNumber: 10BCB17, Year: 2010, Value: 5.65 mg/kg\",\"StationNumber: 10BCB25, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10BCB28, Year: 2010, Value: 7.31 mg/kg\",\"StationNumber: 10BCB30, Year: 2010, Value: 8.9 mg/kg\",\"StationNumber: 10BCB37, Year: 2010, Value: 5.2 mg/kg\",\"StationNumber: 10BCB41, Year: 2010, Value: 4.55 mg/kg\",\"StationNumber: 10BCB46, Year: 2010, Value: 5.05 mg/kg\",\"StationNumber: 10BCB47, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10BCB49, Year: 2010, Value: 6.65 mg/kg\",\"StationNumber: 10HB21, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10HB22, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10HB25, Year: 2010, Value: 10.85 mg/kg\",\"StationNumber: 10HB26, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10HB34, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10HB44, Year: 2010, Value: 6.34 mg/kg\",\"StationNumber: 10HB46, Year: 2010, Value: 5.15 mg/kg\",\"StationNumber: 10HB48, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10HB54, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10LTB71, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10LTB76, Year: 2010, Value: 4.59 mg/kg\",\"StationNumber: 10LTB89, Year: 2010, Value: 9.22 mg/kg\",\"StationNumber: 10MR25, Year: 2010, Value: 7.48 mg/kg\",\"StationNumber: 10MR29, Year: 2010, Value: 9.82 mg/kg\",\"StationNumber: 10MR33, Year: 2010, Value: 4.36 mg/kg\",\"StationNumber: 10MR40, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10MR44, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10MTB30, Year: 2010, Value: 9.2 mg/kg\",\"StationNumber: 10MTB35, Year: 2010, Value: 5.93 mg/kg\",\"StationNumber: 10MTB43, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10MTB53, Year: 2010, Value: 9.06 mg/kg\",\"StationNumber: 10MTB56, Year: 2010, Value: 9.26 mg/kg\",\"StationNumber: 10OTB04, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10OTB05, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10OTB07, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10OTB08, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10OTB09, Year: 2010, Value: 4.65 mg/kg\",\"StationNumber: 10OTB12, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10OTB13, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10OTB14, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10OTB15, Year: 2010, Value: 9.77 mg/kg\",\"StationNumber: 10OTB16, Year: 2010, Value: 9.77 mg/kg\",\"StationNumber: 10OTB18, Year: 2010, Value: 8.82 mg/kg\",\"StationNumber: 10OTB19, Year: 2010, Value: 4.94 mg/kg\",\"StationNumber: 10OTB20, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10OTB21, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10OTB24, Year: 2010, Value: 6.72 mg/kg\",\"StationNumber: 10OTB25, Year: 2010, Value: 7.91 mg/kg\",\"StationNumber: 10OTB26, Year: 2010, Value: 8.22 mg/kg\",\"StationNumber: 10OTB28, Year: 2010, Value: 10.09 mg/kg\",\"StationNumber: 10OTB29, Year: 2010, Value: 9.46 mg/kg\",\"StationNumber: 10OTB96, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10OTB97, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10OTB98, Year: 2010, Value: 9.71 mg/kg\",\"StationNumber: 10TCB01, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10TCB11, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10TCB13, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10TCB20, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 11BCB05, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11BCB09, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11BCB12, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11BCB20, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11BCB22, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11BCB26, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11BCB35, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11BCB42, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11BCB43, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11BCB44, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11BCB48, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11HB09, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11HB13, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11HB29, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11HB31, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11HB35, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11HB36, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11HB38, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11HB40, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11HB47, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11LTB69, Year: 2011, Value: 4.07 mg/kg\",\"StationNumber: 11LTB75, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11LTB80, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11MR18, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11MR32, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11MR35, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11MR37, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11MR43, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11MR45, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11MR52, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11MTB39, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11MTB44, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11MTB46, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11MTB54, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11MTB72, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11OTB08, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11OTB09, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11OTB18, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11OTB24, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11OTB26, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11OTB31, Year: 2011, Value: 4.24 mg/kg\",\"StationNumber: 11OTB32, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11TCB10, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11TCB12, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 12BCB06, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12BCB14, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12BCB19, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12BCB23, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12BCB25, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12BCB27, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12BCB35, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12BCB40, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12BCB44, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12BCB46, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12BCB49, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12HB27, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12HB28, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12HB31, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12HB32, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12HB38, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12HB40, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12HB45, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12HB53, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12HB54, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12LTB78, Year: 2012, Value: 10.58 mg/kg\",\"StationNumber: 12LTB84, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12LTB93, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12MR08, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12MR17, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12MR33, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12MR36, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12MR43, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12MR46, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12MR54, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12MTB47, Year: 2012, Value: 4.25 mg/kg\",\"StationNumber: 12MTB53, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12MTB58, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12MTB63, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12MTB64, Year: 2012, Value: 4.45 mg/kg\",\"StationNumber: 12OTB04, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12OTB08, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12OTB13, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12OTB14, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12OTB18, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12OTB19, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12OTB20, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12TCB05, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12TCB13, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 13BCB05, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13BCB07, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13BCB09, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13BCB10, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13BCB11, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13BCB17, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13BCB22, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13BCB30, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13BCB41, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13BCB43, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13BCB48, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13HB09, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13HB13, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13HB25, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13HB26, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13HB35, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13HB36, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13HB41, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13HB44, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13HB48, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13LTB79, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13LTB82, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13LTB86, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13MR09, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13MR24, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13MR31, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13MR44, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13MR45, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13MR48, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13MTB34, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13MTB35, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13MTB41, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13MTB45, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13MTB55, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13OTB12, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13OTB15, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13OTB16, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13OTB21, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13OTB27, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13OTB28, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13OTB29, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13TCB01, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13TCB11, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13TCB14, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 14BCB03, Year: 2014, Value: 2.785 mg/kg\",\"StationNumber: 14BCB12, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14BCB15, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14BCB17, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14BCB20, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14BCB25, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14BCB29, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14BCB33, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14BCB35, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14BCB41, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14BCB47, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14HB20, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14HB21, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14HB26, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14HB33, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14HB43, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14HB44, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14HB46, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14HB47, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14HB54, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14LTB71, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14LTB81, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14LTB90, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14MR29, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14MR35, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14MR37, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14MR38, Year: 2014, Value: 2.785 mg/kg\",\"StationNumber: 14MR47, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14MTB39, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14MTB41, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14MTB46, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14MTB54, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14MTB63, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14OTB04, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14OTB08, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14OTB14, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14OTB18, Year: 2014, Value: 463.9 mg/kg\",\"StationNumber: 14OTB19, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14OTB21, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14OTB25, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14TCB15, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14TCB20, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14TCB21, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14TCB22, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 15BCB09, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15BCB12, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15BCB15, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15BCB26, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15BCB30, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15BCB31, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15BCB34, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15BCB39, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15BCB43, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15BCB47, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15BCB48, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15HB09, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15HB14, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15HB27, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15HB36, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15HB37, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15HB39, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15HB40, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15HB41, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15HB48, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15LTB70, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15LTB76, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15LTB94, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15MR08, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15MR28, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15MR30, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15MR33, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15MR42, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15MR52, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15MTB40, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15MTB49, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15MTB52, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15MTB55, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15MTB62, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15OTB12, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15OTB15, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15OTB20, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15OTB24, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15OTB26, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15OTB28, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15OTB29, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15TCB01, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15TCB11, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15TCB12, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 16BCB20, Year: 2016, Value: 3.32 mg/kg\",\"StationNumber: 16BCB22, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16BCB25, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16BCB29, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16BCB34, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16BCB35, Year: 2016, Value: 3.05 mg/kg\",\"StationNumber: 16BCB36, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16BCB37, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16BCB41, Year: 2016, Value: 2.42 mg/kg\",\"StationNumber: 16BCB42, Year: 2016, Value: 1.18 mg/kg\",\"StationNumber: 16BCB43, Year: 2016, Value: 3.21 mg/kg\",\"StationNumber: 16DH01-1, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH01-2, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH01-3, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH01-4, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH02-1, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH02-2, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH02-3, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH02-4, Year: 2016, Value: 3.25 mg/kg\",\"StationNumber: 16DH03-1, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH03-2, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH03-3, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH03-4, Year: 2016, Value: 0.76 mg/kg\",\"StationNumber: 16DH04-1, Year: 2016, Value: 2.53 mg/kg\",\"StationNumber: 16DH04-2, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH04-3, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH04-4, Year: 2016, Value: 3.5 mg/kg\",\"StationNumber: 16DH05-1, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH05-2, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH05-3, Year: 2016, Value: 1.87 mg/kg\",\"StationNumber: 16DH05-4, Year: 2016, Value: 2.91 mg/kg\",\"StationNumber: 16DH06-1, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH06-2, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH06-3, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH06-4, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH07-1, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH07-2, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH07-3, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH07-4, Year: 2016, Value: 1.85 mg/kg\",\"StationNumber: 16DH08-1, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH08-2, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH08-3, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH08-4, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH09-1, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH09-2, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH09-3, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH09-4, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH10-1, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH10-2, Year: 2016, Value: 2.25 mg/kg\",\"StationNumber: 16DH10-3, Year: 2016, Value: 1.16 mg/kg\",\"StationNumber: 16DH10-4, Year: 2016, Value: 3.43 mg/kg\",\"StationNumber: 16HB19, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16HB20, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16HB21, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16HB27, Year: 2016, Value: 2.44 mg/kg\",\"StationNumber: 16HB28, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16HB32, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16HB33, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16HB37, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16HB48, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16LTB71, Year: 2016, Value: 3.21 mg/kg\",\"StationNumber: 16LTB79, Year: 2016, Value: 8.12 mg/kg\",\"StationNumber: 16LTB85, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16MR17, Year: 2016, Value: 2.41 mg/kg\",\"StationNumber: 16MR25, Year: 2016, Value: 1.84 mg/kg\",\"StationNumber: 16MR29, Year: 2016, Value: 0.62 mg/kg\",\"StationNumber: 16MR33, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16MR43, Year: 2016, Value: 2.1 mg/kg\",\"StationNumber: 16MR44, Year: 2016, Value: 0.09 mg/kg\",\"StationNumber: 16MR45, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16MTB41, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16MTB47, Year: 2016, Value: 3.95 mg/kg\",\"StationNumber: 16MTB48, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16MTB53, Year: 2016, Value: 4.34 mg/kg\",\"StationNumber: 16MTB72, Year: 2016, Value: 1.69 mg/kg\",\"StationNumber: 16OTB08, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16OTB09, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16OTB13, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16OTB14, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16OTB18, Year: 2016, Value: 1.78 mg/kg\",\"StationNumber: 16OTB22, Year: 2016, Value: 3.79 mg/kg\",\"StationNumber: 16OTB25, Year: 2016, Value: 1.02 mg/kg\",\"StationNumber: 16TCB14, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16TCB20, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 17BCB15, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17BCB26, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17BCB27, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17BCB30, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17BCB35, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17BCB36, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17BCB40, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17BCB42, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17BCB43, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17BCB44, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17BCB48, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17BCB48, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17HB10, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17HB13, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17HB15, Year: 2017, Value: 8.39 mg/kg\",\"StationNumber: 17HB26, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17HB34, Year: 2017, Value: 524.32 mg/kg\",\"StationNumber: 17HB36, Year: 2017, Value: 8.91 mg/kg\",\"StationNumber: 17HB41, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17HB42, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17HB43, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17LTB70, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17LTB83, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17LTB89, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17MR09, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17MR18, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17MR24, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17MR32, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17MR35, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17MR37, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17MTB34, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17MTB35, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17MTB46, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17MTB55, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17MTB63, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17OTB04, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17OTB07, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17OTB12, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17OTB19, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17OTB21, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17OTB28, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17OTB32, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17TCB12, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17TCB13, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17TCB21, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17TCP01, Year: 2017, Value: 20.64 mg/kg\",\"StationNumber: 17TCP02, Year: 2017, Value: 17.43 mg/kg\",\"StationNumber: 17TCP03, Year: 2017, Value: 15.42 mg/kg\",\"StationNumber: 17TCP04, Year: 2017, Value: 14.89 mg/kg\",\"StationNumber: 17TCP05, Year: 2017, Value: 9.77 mg/kg\",\"StationNumber: 17TCP06, Year: 2017, Value: 27.33 mg/kg\",\"StationNumber: 17TCP07, Year: 2017, Value: 11.7 mg/kg\",\"StationNumber: 17TCP08, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17TCP09, Year: 2017, Value: 8.06 mg/kg\",\"StationNumber: 17TCP10, Year: 2017, Value: 8.39 mg/kg\",\"StationNumber: 18BCB11, Year: 2018, Value: 24.7 mg/kg\",\"StationNumber: 18BCB15, Year: 2018, Value: 1.51 mg/kg\",\"StationNumber: 18BCB19, Year: 2018, Value: 0.01 mg/kg\",\"StationNumber: 18BCB20, Year: 2018, Value: 1.19 mg/kg\",\"StationNumber: 18BCB22, Year: 2018, Value: 1.43 mg/kg\",\"StationNumber: 18BCB24, Year: 2018, Value: 0.01 mg/kg\",\"StationNumber: 18BCB26, Year: 2018, Value: 1.76 mg/kg\",\"StationNumber: 18BCB37, Year: 2018, Value: 0.01 mg/kg\",\"StationNumber: 18BCB42, Year: 2018, Value: 0.01 mg/kg\",\"StationNumber: 18BCB44, Year: 2018, Value: 0.01 mg/kg\",\"StationNumber: 18BCB46, Year: 2018, Value: 0.01 mg/kg\",\"StationNumber: 18HB14, Year: 2018, Value: 2.7 mg/kg\",\"StationNumber: 18HB20, Year: 2018, Value: 4.74 mg/kg\",\"StationNumber: 18HB21, Year: 2018, Value: 1.96 mg/kg\",\"StationNumber: 18HB26, Year: 2018, Value: 2.48 mg/kg\",\"StationNumber: 18HB29, Year: 2018, Value: 1.98 mg/kg\",\"StationNumber: 18HB33, Year: 2018, Value: 3.56 mg/kg\",\"StationNumber: 18HB38, Year: 2018, Value: 3.23 mg/kg\",\"StationNumber: 18HB41, Year: 2018, Value: 1.26 mg/kg\",\"StationNumber: 18HB46, Year: 2018, Value: 1.05 mg/kg\",\"StationNumber: 18LTB75, Year: 2018, Value: 0.01 mg/kg\",\"StationNumber: 18LTB79, Year: 2018, Value: 14.24 mg/kg\",\"StationNumber: 18LTB81, Year: 2018, Value: 0.01 mg/kg\",\"StationNumber: 18LTB82, Year: 2018, Value: 0.1 mg/kg\",\"StationNumber: 18MR25, Year: 2018, Value: 7.31 mg/kg\",\"StationNumber: 18MR37, Year: 2018, Value: 0.78 mg/kg\",\"StationNumber: 18MR46, Year: 2018, Value: 0.07 mg/kg\",\"StationNumber: 18MTB41, Year: 2018, Value: 1.08 mg/kg\",\"StationNumber: 18MTB42, Year: 2018, Value: 2.2 mg/kg\",\"StationNumber: 18MTB48, Year: 2018, Value: 1.01 mg/kg\",\"StationNumber: 18MTB56, Year: 2018, Value: 1.63 mg/kg\",\"StationNumber: 18OTB04, Year: 2018, Value: 0.01 mg/kg\",\"StationNumber: 18OTB08, Year: 2018, Value: 0.01 mg/kg\",\"StationNumber: 18OTB13, Year: 2018, Value: 0.01 mg/kg\",\"StationNumber: 18OTB14, Year: 2018, Value: 0.01 mg/kg\",\"StationNumber: 18OTB15, Year: 2018, Value: 0.01 mg/kg\",\"StationNumber: 18OTB21, Year: 2018, Value: 0.01 mg/kg\",\"StationNumber: 18OTB24, Year: 2018, Value: 0.01 mg/kg\",\"StationNumber: 18TCB05, Year: 2018, Value: 9.11 mg/kg\",\"StationNumber: 18TCB11, Year: 2018, Value: 6.79 mg/kg\",\"StationNumber: 18TCB14, Year: 2018, Value: 5.34 mg/kg\",\"StationNumber: 18TCB15, Year: 2018, Value: 6.28 mg/kg\",\"StationNumber: 18TCB21, Year: 2018, Value: 15.39 mg/kg\",\"StationNumber: 18TCB22, Year: 2018, Value: 5.61 mg/kg\",\"StationNumber: 19BCB27, Year: 2019, Value: 5.22 mg/kg\",\"StationNumber: 19BCB29, Year: 2019, Value: 5.87 mg/kg\",\"StationNumber: 19BCB30, Year: 2019, Value: 12.82 mg/kg\",\"StationNumber: 19BCB34, Year: 2019, Value: 0.26 mg/kg\",\"StationNumber: 19BCB35, Year: 2019, Value: 5.29 mg/kg\",\"StationNumber: 19BCB36, Year: 2019, Value: 0.01 mg/kg\",\"StationNumber: 19BCB40, Year: 2019, Value: 0.86 mg/kg\",\"StationNumber: 19BCB41, Year: 2019, Value: 0.61 mg/kg\",\"StationNumber: 19BCB43, Year: 2019, Value: 0.3 mg/kg\",\"StationNumber: 19BCB49, Year: 2019, Value: 1.28 mg/kg\",\"StationNumber: 19BCB50, Year: 2019, Value: 0.01 mg/kg\",\"StationNumber: 19HB09, Year: 2019, Value: 0.5 mg/kg\",\"StationNumber: 19HB16, Year: 2019, Value: 15.28 mg/kg\",\"StationNumber: 19HB25, Year: 2019, Value: 0.59 mg/kg\",\"StationNumber: 19HB27, Year: 2019, Value: 3.02 mg/kg\",\"StationNumber: 19HB32, Year: 2019, Value: 3.82 mg/kg\",\"StationNumber: 19HB37, Year: 2019, Value: 3.57 mg/kg\",\"StationNumber: 19HB39, Year: 2019, Value: 0.66 mg/kg\",\"StationNumber: 19HB40, Year: 2019, Value: 1.14 mg/kg\",\"StationNumber: 19HB47, Year: 2019, Value: 0.06 mg/kg\",\"StationNumber: 19LTB76, Year: 2019, Value: 1.06 mg/kg\",\"StationNumber: 19LTB78, Year: 2019, Value: 0.74 mg/kg\",\"StationNumber: 19LTB88, Year: 2019, Value: 6.12 mg/kg\",\"StationNumber: 19LTB90, Year: 2019, Value: 0.55 mg/kg\",\"StationNumber: 19MR17, Year: 2019, Value: 1.46 mg/kg\",\"StationNumber: 19MR18, Year: 2019, Value: 1.44 mg/kg\",\"StationNumber: 19MR29, Year: 2019, Value: 2.28 mg/kg\",\"StationNumber: 19MR33, Year: 2019, Value: 0.66 mg/kg\",\"StationNumber: 19MR43, Year: 2019, Value: 5.07 mg/kg\",\"StationNumber: 19MR44, Year: 2019, Value: 6.22 mg/kg\",\"StationNumber: 19MR52, Year: 2019, Value: 1.98 mg/kg\",\"StationNumber: 19MTB36, Year: 2019, Value: 2.26 mg/kg\",\"StationNumber: 19MTB47, Year: 2019, Value: 0.31 mg/kg\",\"StationNumber: 19MTB54, Year: 2019, Value: 1.61 mg/kg\",\"StationNumber: 19MTB54, Year: 2019, Value: 2.2 mg/kg\",\"StationNumber: 19MTB62, Year: 2019, Value: 0.55 mg/kg\",\"StationNumber: 19OTB07, Year: 2019, Value: 1.5 mg/kg\",\"StationNumber: 19OTB18, Year: 2019, Value: 1.2 mg/kg\",\"StationNumber: 19OTB20, Year: 2019, Value: 0.38 mg/kg\",\"StationNumber: 19OTB23, Year: 2019, Value: 0.9 mg/kg\",\"StationNumber: 19OTB25, Year: 2019, Value: 0.94 mg/kg\",\"StationNumber: 19OTB29, Year: 2019, Value: 1.32 mg/kg\",\"StationNumber: 19OTB31, Year: 2019, Value: 2.03 mg/kg\",\"StationNumber: 19TCB01, Year: 2019, Value: 4.92 mg/kg\",\"StationNumber: 19TCB20, Year: 2019, Value: 3.89 mg/kg\",\"StationNumber: 20BCB10, Year: 2020, Value: 0.63 mg/kg\",\"StationNumber: 20BCB17, Year: 2020, Value: 0.92 mg/kg\",\"StationNumber: 20BCB22, Year: 2020, Value: 15.76 mg/kg\",\"StationNumber: 20BCB23, Year: 2020, Value: 0.99 mg/kg\",\"StationNumber: 20BCB35, Year: 2020, Value: 3.19 mg/kg\",\"StationNumber: 20BCB37, Year: 2020, Value: 1.91 mg/kg\",\"StationNumber: 20BCB40, Year: 2020, Value: 0.63 mg/kg\",\"StationNumber: 20BCB43, Year: 2020, Value: 1.81 mg/kg\",\"StationNumber: 20BCB47, Year: 2020, Value: 1.65 mg/kg\",\"StationNumber: 20BCB48, Year: 2020, Value: 0.78 mg/kg\",\"StationNumber: 20BCB49, Year: 2020, Value: 1.3 mg/kg\",\"StationNumber: 20HB09, Year: 2020, Value: 0.01 mg/kg\",\"StationNumber: 20HB10, Year: 2020, Value: 0.01 mg/kg\",\"StationNumber: 20HB21, Year: 2020, Value: 0.01 mg/kg\",\"StationNumber: 20HB26, Year: 2020, Value: 8.35 mg/kg\",\"StationNumber: 20HB38, Year: 2020, Value: 3.49 mg/kg\",\"StationNumber: 20HB41, Year: 2020, Value: 3.54 mg/kg\",\"StationNumber: 20HB46, Year: 2020, Value: 1.16 mg/kg\",\"StationNumber: 20HB47, Year: 2020, Value: 0.34 mg/kg\",\"StationNumber: 20HB52, Year: 2020, Value: 2.28 mg/kg\",\"StationNumber: 20LTB70, Year: 2020, Value: 0.79 mg/kg\",\"StationNumber: 20LTB71, Year: 2020, Value: 0.96 mg/kg\",\"StationNumber: 20LTB77, Year: 2020, Value: 2.21 mg/kg\",\"StationNumber: 20LTB85, Year: 2020, Value: 10.94 mg/kg\",\"StationNumber: 20MR08, Year: 2020, Value: 1.25 mg/kg\",\"StationNumber: 20MR09, Year: 2020, Value: 1.22 mg/kg\",\"StationNumber: 20MR33, Year: 2020, Value: 1.25 mg/kg\",\"StationNumber: 20MR36, Year: 2020, Value: 1.24 mg/kg\",\"StationNumber: 20MR44, Year: 2020, Value: 6.25 mg/kg\",\"StationNumber: 20MR49, Year: 2020, Value: 0.94 mg/kg\",\"StationNumber: 20MTB35, Year: 2020, Value: 3.65 mg/kg\",\"StationNumber: 20MTB46, Year: 2020, Value: 0.23 mg/kg\",\"StationNumber: 20MTB52, Year: 2020, Value: 1.12 mg/kg\",\"StationNumber: 20MTB63, Year: 2020, Value: 0.48 mg/kg\",\"StationNumber: 20OTB13, Year: 2020, Value: 0.01 mg/kg\",\"StationNumber: 20OTB14, Year: 2020, Value: 0.01 mg/kg\",\"StationNumber: 20OTB15, Year: 2020, Value: 0.01 mg/kg\",\"StationNumber: 20OTB19, Year: 2020, Value: 0.01 mg/kg\",\"StationNumber: 20OTB21, Year: 2020, Value: 0.01 mg/kg\",\"StationNumber: 20OTB24, Year: 2020, Value: 0.01 mg/kg\",\"StationNumber: 20OTB32, Year: 2020, Value: 0.01 mg/kg\",\"StationNumber: 20TCB10, Year: 2020, Value: 4.53 mg/kg\",\"StationNumber: 20TCB12, Year: 2020, Value: 3.28 mg/kg\",\"StationNumber: 20TCB20, Year: 2020, Value: 3.03 mg/kg\",\"StationNumber: 21BCB09, Year: 2021, Value: 11.03 mg/kg\",\"StationNumber: 21BCB12, Year: 2021, Value: 4.15 mg/kg\",\"StationNumber: 21BCB15, Year: 2021, Value: 8.58 mg/kg\",\"StationNumber: 21BCB22, Year: 2021, Value: 1.46 mg/kg\",\"StationNumber: 21BCB25, Year: 2021, Value: 3.25 mg/kg\",\"StationNumber: 21BCB26, Year: 2021, Value: 5.19 mg/kg\",\"StationNumber: 21BCB29, Year: 2021, Value: 2.06 mg/kg\",\"StationNumber: 21BCB36, Year: 2021, Value: 0.98 mg/kg\",\"StationNumber: 21BCB41, Year: 2021, Value: 1.48 mg/kg\",\"StationNumber: 21BCB44, Year: 2021, Value: 4.08 mg/kg\",\"StationNumber: 21BCB50, Year: 2021, Value: 0.79 mg/kg\",\"StationNumber: 21HB13, Year: 2021, Value: 3.05 mg/kg\",\"StationNumber: 21HB19, Year: 2021, Value: 3.23 mg/kg\",\"StationNumber: 21HB20, Year: 2021, Value: 0.39 mg/kg\",\"StationNumber: 21HB27, Year: 2021, Value: 2.12 mg/kg\",\"StationNumber: 21HB34, Year: 2021, Value: 0.2 mg/kg\",\"StationNumber: 21HB36, Year: 2021, Value: 1.6 mg/kg\",\"StationNumber: 21HB37, Year: 2021, Value: 2.04 mg/kg\",\"StationNumber: 21HB40, Year: 2021, Value: 1.21 mg/kg\",\"StationNumber: 21HB43, Year: 2021, Value: 1.09 mg/kg\",\"StationNumber: 21LTB78, Year: 2021, Value: 3.26 mg/kg\",\"StationNumber: 21LTB83, Year: 2021, Value: 1.43 mg/kg\",\"StationNumber: 21LTB84, Year: 2021, Value: 5.27 mg/kg\",\"StationNumber: 21LTB89, Year: 2021, Value: 0.38 mg/kg\",\"StationNumber: 21MR24, Year: 2021, Value: 1.29 mg/kg\",\"StationNumber: 21MR29, Year: 2021, Value: 1.72 mg/kg\",\"StationNumber: 21MR45, Year: 2021, Value: 4.29 mg/kg\",\"StationNumber: 21MR47, Year: 2021, Value: 1.64 mg/kg\",\"StationNumber: 21MR52, Year: 2021, Value: 1.92 mg/kg\",\"StationNumber: 21MTB40, Year: 2021, Value: 0.15 mg/kg\",\"StationNumber: 21MTB43, Year: 2021, Value: 3.11 mg/kg\",\"StationNumber: 21MTB48, Year: 2021, Value: 1.12 mg/kg\",\"StationNumber: 21MTB62, Year: 2021, Value: 3.19 mg/kg\",\"StationNumber: 21OTB08, Year: 2021, Value: 0.22 mg/kg\",\"StationNumber: 21OTB12, Year: 2021, Value: 4.8 mg/kg\",\"StationNumber: 21OTB13, Year: 2021, Value: 0.45 mg/kg\",\"StationNumber: 21OTB18, Year: 2021, Value: 2.44 mg/kg\",\"StationNumber: 21OTB21, Year: 2021, Value: 0.24 mg/kg\",\"StationNumber: 21OTB25, Year: 2021, Value: 0.32 mg/kg\",\"StationNumber: 21OTB28, Year: 2021, Value: 0.16 mg/kg\",\"StationNumber: 21TCB02, Year: 2021, Value: 11.5 mg/kg\",\"StationNumber: 21TCB13, Year: 2021, Value: 7.11 mg/kg\",\"StationNumber: 21TCB22, Year: 2021, Value: 4.36 mg/kg\",\"StationNumber: 21TCB26, Year: 2021, Value: 2.49 mg/kg\",\"StationNumber: 22BCB02, Year: 2022, Value: 5.83 mg/kg\",\"StationNumber: 22BCB05, Year: 2022, Value: 1.17 mg/kg\",\"StationNumber: 22BCB11, Year: 2022, Value: 1.49 mg/kg\",\"StationNumber: 22BCB12, Year: 2022, Value: 1.1 mg/kg\",\"StationNumber: 22BCB17, Year: 2022, Value: 2.31 mg/kg\",\"StationNumber: 22BCB27, Year: 2022, Value: 1.33 mg/kg\",\"StationNumber: 22BCB30, Year: 2022, Value: 0.91 mg/kg\",\"StationNumber: 22BCB34, Year: 2022, Value: 0.62 mg/kg\",\"StationNumber: 22BCB35, Year: 2022, Value: 0.48 mg/kg\",\"StationNumber: 22BCB45, Year: 2022, Value: 1.24 mg/kg\",\"StationNumber: 22BCB47, Year: 2022, Value: 3.19 mg/kg\",\"StationNumber: 22HB10, Year: 2022, Value: 0.54 mg/kg\",\"StationNumber: 22HB19, Year: 2022, Value: 0.13 mg/kg\",\"StationNumber: 22HB21, Year: 2022, Value: 0.22 mg/kg\",\"StationNumber: 22HB25, Year: 2022, Value: 1.8 mg/kg\",\"StationNumber: 22HB26, Year: 2022, Value: 4.73 mg/kg\",\"StationNumber: 22HB28, Year: 2022, Value: 0.27 mg/kg\",\"StationNumber: 22HB32, Year: 2022, Value: 3.93 mg/kg\",\"StationNumber: 22HB40, Year: 2022, Value: 0.56 mg/kg\",\"StationNumber: 22HB46, Year: 2022, Value: 0.97 mg/kg\",\"StationNumber: 22LTB70, Year: 2022, Value: 2.91 mg/kg\",\"StationNumber: 22LTB79, Year: 2022, Value: 10.38 mg/kg\",\"StationNumber: 22LTB81, Year: 2022, Value: 0.9 mg/kg\",\"StationNumber: 22LTB90, Year: 2022, Value: 0.01 mg/kg\",\"StationNumber: 22MR17, Year: 2022, Value: 1.62 mg/kg\",\"StationNumber: 22MR25, Year: 2022, Value: 1.11 mg/kg\",\"StationNumber: 22MR32, Year: 2022, Value: 2.35 mg/kg\",\"StationNumber: 22MR37, Year: 2022, Value: 1.94 mg/kg\",\"StationNumber: 22MR42, Year: 2022, Value: 0.87 mg/kg\",\"StationNumber: 22MR44, Year: 2022, Value: 1.16 mg/kg\",\"StationNumber: 22MR46, Year: 2022, Value: 0.24 mg/kg\",\"StationNumber: 22MR52, Year: 2022, Value: 4.05 mg/kg\",\"StationNumber: 22MTB35, Year: 2022, Value: 1.69 mg/kg\",\"StationNumber: 22MTB37, Year: 2022, Value: 0.46 mg/kg\",\"StationNumber: 22MTB41, Year: 2022, Value: 2.4 mg/kg\",\"StationNumber: 22MTB55, Year: 2022, Value: 0.8 mg/kg\",\"StationNumber: 22OTB02, Year: 2022, Value: 1.05 mg/kg\",\"StationNumber: 22OTB07, Year: 2022, Value: 2.48 mg/kg\",\"StationNumber: 22OTB19, Year: 2022, Value: 1.75 mg/kg\",\"StationNumber: 22OTB22, Year: 2022, Value: 0.22 mg/kg\",\"StationNumber: 22OTB28, Year: 2022, Value: 0.25 mg/kg\",\"StationNumber: 22OTB29, Year: 2022, Value: 0.19 mg/kg\",\"StationNumber: 22OTB32, Year: 2022, Value: 0.15 mg/kg\",\"StationNumber: 22TCB20, Year: 2022, Value: 2.86 mg/kg\"],{\"interactive\":false,\"permanent\":false,\"direction\":\"auto\",\"opacity\":1,\"offset\":[0,0],\"textsize\":\"10px\",\"textOnly\":false,\"className\":\"\",\"sticky\":true},null]}],\"limits\":{\"lat\":[27.4934,28.03793],\"lng\":[-82.84670300000001,-82.343422]}},\"evals\":[],\"jsHooks\":{\"render\":[{\"code\":\"function(el, x, data) {\\n return (\\n function(el, x) {\\n var myMap = this;\\n myMap.on('baselayerchange',\\n function (e) {\\n myMap.minimap.changeLayer(L.tileLayer.provider(e.name));\\n })\\n }).call(this.getMap(), el, x, data);\\n}\",\"data\":null}]}}"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentpelave.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot summary of PEL averages by bay segment — show_sedimentpelave","title":"Plot summary of PEL averages by bay segment — show_sedimentpelave","text":"Plot summary PEL averages bay segment","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentpelave.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot summary of PEL averages by bay segment — show_sedimentpelave","text":"","code":"show_sedimentpelave( sedimentdata, yrrng = c(1993, 2022), bay_segment = c(\"HB\", \"OTB\", \"MTB\", \"LTB\", \"TCB\", \"MR\", \"BCB\"), funding_proj = \"TBEP\", alph = 1, ylim = c(0, 0.4), lnsz = 1, base_size = 12, plotly = FALSE, family = NA, width = NULL, height = NULL )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentpelave.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot summary of PEL averages by bay segment — show_sedimentpelave","text":"sedimentdata input sediment data.frame returned read_importsediment yrrng numeric vector indicating min, max years include, use single year one year data bay_segment chr string bay segment, one many \"HB\", \"OTB\", \"MTB\", \"LTB\", \"TCB\", \"MR\", \"BCB\" funding_proj chr string funding project, one many \"TBEP\" (default), \"TBEP-Special\", \"Apollo Beach\", \"Janicki Contract\", \"Rivers\", \"Tidal Streams\" alph numeric indicating alpha value score category colors ylim numeric y axis limits lnsz numeric line size base_size numeric indicating text scaling size plot plotly logical matrix created using plotly family optional chr string indicating font family text labels width numeric width plot pixels, applies plotly = TRUE height numeric height plot pixels, applies plotly = TRUE","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentpelave.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot summary of PEL averages by bay segment — show_sedimentpelave","text":"ggplot object plotly object plotly = TRUE showing PEL averages (average averages) 95","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentpelave.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Plot summary of PEL averages by bay segment — show_sedimentpelave","text":"Lines grades shown plot. Confidence intervals may shown segments insufficient data.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentpelave.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot summary of PEL averages by bay segment — show_sedimentpelave","text":"","code":"show_sedimentpelave(sedimentdata)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentpelaveplotly.html","id":null,"dir":"Reference","previous_headings":"","what":"Creates a plotly object for average PEL plots — show_sedimentpelaveplotly","title":"Creates a plotly object for average PEL plots — show_sedimentpelaveplotly","text":"Creates plotly object average PEL plots","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentpelaveplotly.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Creates a plotly object for average PEL plots — show_sedimentpelaveplotly","text":"","code":"show_sedimentpelaveplotly(p, width = NULL, height = NULL)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentpelaveplotly.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Creates a plotly object for average PEL plots — show_sedimentpelaveplotly","text":"p ggplot object output show_sedimentpelave width numeric width plot pixels height numeric height plot pixels","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentpelaveplotly.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Creates a plotly object for average PEL plots — show_sedimentpelaveplotly","text":"plotly data object","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentpelaveplotly.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Creates a plotly object for average PEL plots — show_sedimentpelaveplotly","text":"","code":"p <- show_sedimentpelave(sedimentdata) show_sedimentpelaveplotly(p) {\"x\":{\"data\":[{\"x\":[null,null,null,null,null],\"y\":[null,0.0075599999999999999,0.0075599999999999999,null,null],\"text\":\"\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":1.8897637795275593,\"color\":\"transparent\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[null,null,null,null,null],\"y\":[0.0075599999999999999,0.02052,0.02052,0.0075599999999999999,0.0075599999999999999],\"text\":\"\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":1.8897637795275593,\"color\":\"transparent\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(162,253,122,1)\",\"hoveron\":\"fills\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[null,null,null,null,null],\"y\":[0.02052,0.085669999999999996,0.085669999999999996,0.02052,0.02052],\"text\":\"\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":1.8897637795275593,\"color\":\"transparent\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(233,195,24,1)\",\"hoveron\":\"fills\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[null,null,null,null,null],\"y\":[0.085669999999999996,0.28026000000000001,0.28026000000000001,0.085669999999999996,0.085669999999999996],\"text\":\"\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":1.8897637795275593,\"color\":\"transparent\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(238,118,0,1)\",\"hoveron\":\"fills\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[null,null,null,null,null],\"y\":[0.28026000000000001,null,null,0.28026000000000001,0.28026000000000001],\"text\":\"\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":1.8897637795275593,\"color\":\"transparent\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[7,1,4,6,3,2,5],\"y\":[0.053520437964741263,0.11766095904182264,0.028110742831749039,0.044553811438690069,0.037404087404364364,0.050639528194187294,0.03365804003727018],\"text\":[\"AreaAbbr: BCB
ave: 0.05352044\",\"AreaAbbr: HB
ave: 0.11766096\",\"AreaAbbr: LTB
ave: 0.02811074\",\"AreaAbbr: MR
ave: 0.04455381\",\"AreaAbbr: MTB
ave: 0.03740409\",\"AreaAbbr: OTB
ave: 0.05063953\",\"AreaAbbr: TCB
ave: 0.03365804\"],\"type\":\"scatter\",\"mode\":\"markers\",\"marker\":{\"autocolorscale\":false,\"color\":\"rgba(0,0,0,1)\",\"opacity\":1,\"size\":11.338582677165356,\"symbol\":\"circle\",\"line\":{\"width\":1.8897637795275593,\"color\":\"rgba(0,0,0,1)\"}},\"hoveron\":\"points\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[7,1,4,6,3,2,5],\"y\":[0.053520437964741263,0.11766095904182264,0.028110742831749039,0.044553811438690069,0.037404087404364364,0.050639528194187294,0.03365804003727018],\"text\":[\"AreaAbbr: BCB
ave: 0.05352044
lov: 0.04450421
hiv: 0.06253667\",\"AreaAbbr: HB
ave: 0.11766096
lov: 0.06630981
hiv: 0.16901211\",\"AreaAbbr: LTB
ave: 0.02811074
lov: 0.02473974
hiv: 0.03148174\",\"AreaAbbr: MR
ave: 0.04455381
lov: 0.03754802
hiv: 0.05155960\",\"AreaAbbr: MTB
ave: 0.03740409
lov: 0.03268379
hiv: 0.04212438\",\"AreaAbbr: OTB
ave: 0.05063953
lov: 0.03706261
hiv: 0.06421645\",\"AreaAbbr: TCB
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C\",\"StationNumber: 94LTB35, Year: 1994, PEL ratio: 0.01209, Grade: B\",\"StationNumber: 94LTB36, Year: 1994, PEL ratio: 0.04666, Grade: C\",\"StationNumber: 94LTB37, Year: 1994, PEL ratio: 0.10165, Grade: D\",\"StationNumber: 94LTB38, Year: 1994, PEL ratio: 0.02221, Grade: C\",\"StationNumber: 94LTB39, Year: 1994, PEL ratio: 0.08637, Grade: D\",\"StationNumber: 94LTB40, Year: 1994, PEL ratio: 0.06117, Grade: C\",\"StationNumber: 94MR23, Year: 1994, PEL ratio: 0, Grade: A\",\"StationNumber: 94MR24, Year: 1994, PEL ratio: 0, Grade: A\",\"StationNumber: 94MR26, Year: 1994, PEL ratio: 0, Grade: A\",\"StationNumber: 94MR27, Year: 1994, PEL ratio: 0, Grade: A\",\"StationNumber: 94MR28, Year: 1994, PEL ratio: 0, Grade: A\",\"StationNumber: 94MR29, Year: 1994, PEL ratio: 0, Grade: A\",\"StationNumber: 94MR31, Year: 1994, PEL ratio: 0, Grade: A\",\"StationNumber: 94MR32, Year: 1994, PEL ratio: 0, Grade: A\",\"StationNumber: 94MR34, Year: 1994, PEL ratio: 0, Grade: A\",\"StationNumber: 94MR43, Year: 1994, PEL ratio: 0, Grade: A\",\"StationNumber: 94MTB41, Year: 1994, PEL ratio: 0.00869, Grade: B\",\"StationNumber: 94MTB42, Year: 1994, PEL ratio: 0.00546, Grade: A\",\"StationNumber: 94MTB43, Year: 1994, PEL ratio: 0.07634, Grade: C\",\"StationNumber: 94MTB44, Year: 1994, PEL ratio: 0.09942, Grade: D\",\"StationNumber: 94MTB45, Year: 1994, PEL ratio: 0.03607, Grade: C\",\"StationNumber: 94MTB47, Year: 1994, PEL ratio: 0.03786, Grade: C\",\"StationNumber: 94MTB48, Year: 1994, PEL ratio: 0.00958, Grade: B\",\"StationNumber: 94MTB49, Year: 1994, PEL ratio: 0.08992, Grade: D\",\"StationNumber: 94MTB50, Year: 1994, PEL ratio: 0.04484, Grade: C\",\"StationNumber: 94MTB51, Year: 1994, PEL ratio: 0.01764, Grade: B\",\"StationNumber: 94MTB52, Year: 1994, PEL ratio: 0.01808, Grade: B\",\"StationNumber: 94MTB53, Year: 1994, PEL ratio: 0.01368, Grade: B\",\"StationNumber: 94MTB54, Year: 1994, PEL ratio: 0.05744, Grade: C\",\"StationNumber: 94MTB55, Year: 1994, PEL ratio: 0.00805, Grade: B\",\"StationNumber: 94MTB56, Year: 1994, PEL ratio: 0.03262, Grade: C\",\"StationNumber: 94MTB57, Year: 1994, PEL ratio: 0.03071, Grade: C\",\"StationNumber: 94MTB58, Year: 1994, PEL ratio: 0.10823, Grade: D\",\"StationNumber: 94MTB59, Year: 1994, PEL ratio: 0.0237, Grade: C\",\"StationNumber: 94MTB60, Year: 1994, PEL ratio: 0.00788, Grade: B\",\"StationNumber: 94MTB61, Year: 1994, PEL ratio: 0.14417, Grade: D\",\"StationNumber: 94OTB63, Year: 1994, PEL ratio: 0.16877, Grade: D\",\"StationNumber: 94OTB64, Year: 1994, PEL ratio: 0.01051, Grade: B\",\"StationNumber: 94OTB65, Year: 1994, PEL ratio: 0.02364, Grade: C\",\"StationNumber: 94OTB66, Year: 1994, PEL ratio: 0.0106, Grade: B\",\"StationNumber: 94OTB67, Year: 1994, PEL ratio: 0.03548, Grade: C\",\"StationNumber: 94OTB68, Year: 1994, PEL ratio: 0.01448, Grade: B\",\"StationNumber: 94OTB69, Year: 1994, PEL ratio: 0.01953, Grade: B\",\"StationNumber: 94OTB70, Year: 1994, PEL ratio: 0.00537, Grade: A\",\"StationNumber: 94OTB71, Year: 1994, PEL ratio: 0.0663, Grade: C\",\"StationNumber: 94OTB72, Year: 1994, PEL ratio: 0.01765, Grade: B\",\"StationNumber: 94OTB73, Year: 1994, PEL ratio: 0.09561, Grade: D\",\"StationNumber: 94OTB76, Year: 1994, PEL ratio: 0.01769, Grade: B\",\"StationNumber: 94OTB77, Year: 1994, PEL ratio: 0.00515, Grade: A\",\"StationNumber: 94OTB78, Year: 1994, PEL ratio: 0.15079, Grade: D\",\"StationNumber: 94OTB79, Year: 1994, PEL ratio: 0.02344, Grade: C\",\"StationNumber: 94OTB80, Year: 1994, PEL ratio: 0.02606, Grade: C\",\"StationNumber: 94OTB83, Year: 1994, PEL ratio: 0.01552, Grade: B\",\"StationNumber: 94TCB22, Year: 1994, PEL ratio: 0, Grade: A\",\"StationNumber: 94TCB37, Year: 1994, PEL ratio: 0, Grade: A\",\"StationNumber: 94TCB38, Year: 1994, PEL ratio: 0, Grade: A\",\"StationNumber: 94TCB39, Year: 1994, PEL ratio: 0, Grade: A\",\"StationNumber: 94TCB40, Year: 1994, PEL ratio: 0, Grade: A\",\"StationNumber: 94TCB41, Year: 1994, PEL ratio: 0, Grade: A\",\"StationNumber: 94TCB42, Year: 1994, PEL ratio: 0, Grade: A\",\"StationNumber: 95BCB01, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95BCB02, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95BCB03, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95BCB04, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95BCB05, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95BCB06, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95BCB07, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95BCB08, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95BCB09, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95BCB10, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95BCB11, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95BCB12, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95BCB13, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95BCB14, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95BCB15, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95BCB16, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95BCB17, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95BCB18, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95BCB19, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95BCB20, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95BCB21, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95HB14, Year: 1995, PEL ratio: 0.27004, Grade: D\",\"StationNumber: 95HB16, Year: 1995, PEL ratio: 0.46027, Grade: F\",\"StationNumber: 95HB17, Year: 1995, PEL ratio: 0.04182, Grade: C\",\"StationNumber: 95HB18, Year: 1995, PEL ratio: 0.25744, Grade: D\",\"StationNumber: 95HB19, Year: 1995, PEL ratio: 0.02669, Grade: C\",\"StationNumber: 95HB22, Year: 1995, PEL ratio: 0.08766, Grade: D\",\"StationNumber: 95HB23, Year: 1995, PEL ratio: 0.17389, Grade: D\",\"StationNumber: 95HB24, Year: 1995, PEL ratio: 0.00709, Grade: A\",\"StationNumber: 95HB25, Year: 1995, PEL ratio: 0.10295, Grade: D\",\"StationNumber: 95HB26, Year: 1995, PEL ratio: 0.00947, Grade: B\",\"StationNumber: 95HB27, Year: 1995, PEL ratio: 0.00545, Grade: A\",\"StationNumber: 95HB28, Year: 1995, PEL ratio: 0.00784, Grade: B\",\"StationNumber: 95HB29, Year: 1995, PEL ratio: 0.06887, Grade: C\",\"StationNumber: 95HB37, Year: 1995, PEL ratio: 0.07591, Grade: C\",\"StationNumber: 95HB38, Year: 1995, PEL ratio: 0.00626, Grade: A\",\"StationNumber: 95HB40, Year: 1995, PEL ratio: 0.00642, Grade: A\",\"StationNumber: 95HB41, Year: 1995, PEL ratio: 0.00725, Grade: A\",\"StationNumber: 95HB42, Year: 1995, PEL ratio: 0.00695, Grade: A\",\"StationNumber: 95HB43, Year: 1995, PEL ratio: 0.07978, Grade: C\",\"StationNumber: 95HB44, Year: 1995, PEL ratio: 0.00487, Grade: A\",\"StationNumber: 95HB45, Year: 1995, PEL ratio: 0.0044, Grade: A\",\"StationNumber: 95HB46, Year: 1995, PEL ratio: 0.11769, Grade: D\",\"StationNumber: 95HB48, Year: 1995, PEL ratio: 0.01232, Grade: B\",\"StationNumber: 95HB49, Year: 1995, PEL ratio: 0.00484, Grade: A\",\"StationNumber: 95HB51, Year: 1995, PEL ratio: 0.00683, Grade: A\",\"StationNumber: 95HB52, Year: 1995, PEL ratio: 0.12448, Grade: D\",\"StationNumber: 95HB54, Year: 1995, PEL ratio: 0.00769, Grade: B\",\"StationNumber: 95HB55, Year: 1995, PEL ratio: 0.00545, Grade: A\",\"StationNumber: 95HB56, Year: 1995, PEL ratio: 0.19484, Grade: D\",\"StationNumber: 95LTB01, Year: 1995, PEL ratio: 0.00385, Grade: A\",\"StationNumber: 95LTB02, Year: 1995, PEL ratio: 0.00483, Grade: A\",\"StationNumber: 95LTB04, Year: 1995, PEL ratio: 0.01579, Grade: B\",\"StationNumber: 95LTB05, Year: 1995, PEL ratio: 0.02646, Grade: C\",\"StationNumber: 95LTB06, Year: 1995, PEL ratio: 0.00405, Grade: A\",\"StationNumber: 95LTB07, Year: 1995, PEL ratio: 0.00392, Grade: A\",\"StationNumber: 95LTB08, Year: 1995, PEL ratio: 0.00633, Grade: A\",\"StationNumber: 95LTB09, Year: 1995, PEL ratio: 0.00764, Grade: B\",\"StationNumber: 95LTB10, Year: 1995, PEL ratio: 0.00838, Grade: B\",\"StationNumber: 95LTB11, Year: 1995, PEL ratio: 0.01854, Grade: B\",\"StationNumber: 95LTB12, Year: 1995, PEL ratio: 0.05258, Grade: C\",\"StationNumber: 95LTB13, Year: 1995, PEL ratio: 0.03364, Grade: C\",\"StationNumber: 95LTB15, Year: 1995, PEL ratio: 0.00223, Grade: A\",\"StationNumber: 95LTB17, Year: 1995, PEL ratio: 0.00912, Grade: B\",\"StationNumber: 95LTB18, Year: 1995, PEL ratio: 0.00937, Grade: B\",\"StationNumber: 95LTB19, Year: 1995, PEL ratio: 0.00514, Grade: A\",\"StationNumber: 95LTB20, Year: 1995, PEL ratio: 0.00586, Grade: A\",\"StationNumber: 95LTB21, Year: 1995, PEL ratio: 0.00346, Grade: A\",\"StationNumber: 95LTB23, Year: 1995, PEL ratio: 0.01403, Grade: B\",\"StationNumber: 95LTB25, Year: 1995, PEL ratio: 0.002, Grade: A\",\"StationNumber: 95LTB26, Year: 1995, PEL ratio: 0.00213, Grade: A\",\"StationNumber: 95LTB29, Year: 1995, PEL ratio: 0.00364, Grade: A\",\"StationNumber: 95MR23, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95MR24, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95MR25, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95MR26, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95MR27, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95MR28, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95MR29, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95MR31, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95MR32, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95MR34, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95MR43, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95MTB03, Year: 1995, PEL ratio: 0.00465, Grade: A\",\"StationNumber: 95MTB04, Year: 1995, PEL ratio: 0.008, Grade: B\",\"StationNumber: 95MTB06, Year: 1995, PEL ratio: 0.00235, Grade: A\",\"StationNumber: 95MTB07, Year: 1995, PEL ratio: 0.12807, Grade: D\",\"StationNumber: 95MTB08, Year: 1995, PEL ratio: 0.00916, Grade: B\",\"StationNumber: 95MTB10, Year: 1995, PEL ratio: 0.00729, Grade: A\",\"StationNumber: 95MTB15, Year: 1995, PEL ratio: 0.00246, Grade: A\",\"StationNumber: 95MTB16, Year: 1995, PEL ratio: 0.00155, Grade: A\",\"StationNumber: 95MTB17, Year: 1995, PEL ratio: 0.01668, Grade: B\",\"StationNumber: 95MTB18, Year: 1995, PEL ratio: 0.03443, Grade: C\",\"StationNumber: 95MTB19, Year: 1995, PEL ratio: 0.00365, Grade: A\",\"StationNumber: 95MTB21, Year: 1995, PEL ratio: 0.02294, Grade: C\",\"StationNumber: 95MTB24, Year: 1995, PEL ratio: 0.00408, Grade: A\",\"StationNumber: 95MTB25, Year: 1995, PEL ratio: 0.0049, Grade: A\",\"StationNumber: 95MTB26, Year: 1995, PEL ratio: 0.00385, Grade: A\",\"StationNumber: 95MTB29, Year: 1995, PEL ratio: 0.0045, Grade: A\",\"StationNumber: 95MTB30, Year: 1995, PEL ratio: 0.00748, Grade: A\",\"StationNumber: 95MTB31, Year: 1995, PEL ratio: 0.0045, Grade: A\",\"StationNumber: 95MTB32, Year: 1995, PEL ratio: 0.00689, Grade: A\",\"StationNumber: 95MTB34, Year: 1995, PEL ratio: 0.01326, Grade: B\",\"StationNumber: 95MTB35, Year: 1995, PEL ratio: 0.00817, Grade: B\",\"StationNumber: 95OTB02, Year: 1995, PEL ratio: 0.01655, Grade: B\",\"StationNumber: 95OTB03, Year: 1995, PEL ratio: 0.00572, Grade: A\",\"StationNumber: 95OTB05, Year: 1995, PEL ratio: 0.02432, Grade: C\",\"StationNumber: 95OTB06, Year: 1995, PEL ratio: 0.00961, Grade: B\",\"StationNumber: 95OTB07, Year: 1995, PEL ratio: 0.00772, Grade: B\",\"StationNumber: 95OTB08, Year: 1995, PEL ratio: 0.00541, Grade: A\",\"StationNumber: 95OTB11, Year: 1995, PEL ratio: 0.01187, Grade: B\",\"StationNumber: 95OTB12, Year: 1995, PEL ratio: 0.01178, Grade: B\",\"StationNumber: 95OTB13, Year: 1995, PEL ratio: 0.00594, Grade: A\",\"StationNumber: 95OTB14, Year: 1995, PEL ratio: 0.00796, Grade: B\",\"StationNumber: 95OTB15, Year: 1995, PEL ratio: 0.28594, Grade: F\",\"StationNumber: 95OTB17, Year: 1995, PEL ratio: 0.00668, Grade: A\",\"StationNumber: 95OTB18, Year: 1995, PEL ratio: 0.00656, Grade: A\",\"StationNumber: 95OTB19, Year: 1995, PEL ratio: 0.04972, Grade: C\",\"StationNumber: 95OTB20, Year: 1995, PEL ratio: 0.00788, Grade: B\",\"StationNumber: 95OTB22, Year: 1995, PEL ratio: 0.01855, Grade: B\",\"StationNumber: 95OTB23, Year: 1995, PEL ratio: 0.00383, Grade: A\",\"StationNumber: 95OTB24, Year: 1995, PEL ratio: 0.00477, Grade: A\",\"StationNumber: 95OTB25, Year: 1995, PEL ratio: 0.00588, Grade: A\",\"StationNumber: 95OTB26, Year: 1995, PEL ratio: 0.00476, Grade: A\",\"StationNumber: 95OTB27, Year: 1995, PEL ratio: 0.0039, Grade: A\",\"StationNumber: 95OTB29, Year: 1995, PEL ratio: 0.00722, Grade: A\",\"StationNumber: 95OTB30, Year: 1995, PEL ratio: 0.00191, Grade: A\",\"StationNumber: 95TCB22, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95TCB37, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95TCB38, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95TCB39, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95TCB40, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95TCB41, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95TCB42, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 96BCB02, Year: 1996, PEL ratio: 0.02981, Grade: C\",\"StationNumber: 96BCB04, Year: 1996, PEL ratio: 0.21792, Grade: D\",\"StationNumber: 96BCB07, Year: 1996, PEL ratio: 0.04432, Grade: C\",\"StationNumber: 96BCB08, Year: 1996, PEL ratio: 0.02026, Grade: B\",\"StationNumber: 96BCB12, Year: 1996, PEL ratio: 0.03692, Grade: C\",\"StationNumber: 96BCB13, Year: 1996, PEL ratio: 0.31368, Grade: F\",\"StationNumber: 96BCB15, Year: 1996, PEL ratio: 0.18237, Grade: D\",\"StationNumber: 96BCB19, Year: 1996, PEL ratio: 0.01925, Grade: B\",\"StationNumber: 96BCB24, Year: 1996, PEL ratio: 0.03429, Grade: C\",\"StationNumber: 96BCB26, Year: 1996, PEL ratio: 0.01638, Grade: B\",\"StationNumber: 96BCB27, Year: 1996, PEL ratio: 0.02494, Grade: C\",\"StationNumber: 96BCB30, Year: 1996, PEL ratio: 0.01775, Grade: B\",\"StationNumber: 96BCB31, Year: 1996, PEL ratio: 0.26305, Grade: D\",\"StationNumber: 96BCB34, Year: 1996, PEL ratio: 0.01272, Grade: B\",\"StationNumber: 96BCB36, Year: 1996, PEL ratio: 0.00987, Grade: B\",\"StationNumber: 96BCB39, Year: 1996, PEL ratio: 0.01263, Grade: B\",\"StationNumber: 96BCB40, Year: 1996, PEL ratio: 0.01665, Grade: B\",\"StationNumber: 96BCB41, Year: 1996, PEL ratio: 0.00563, Grade: A\",\"StationNumber: 96BCB44, Year: 1996, PEL ratio: 0.02696, Grade: C\",\"StationNumber: 96BCB46, Year: 1996, PEL ratio: 0.00262, Grade: A\",\"StationNumber: 96BCB49, Year: 1996, PEL ratio: 0.00173, Grade: A\",\"StationNumber: 96HB13, Year: 1996, PEL ratio: 0.28424, Grade: F\",\"StationNumber: 96HB16, Year: 1996, PEL ratio: 0.01524, Grade: B\",\"StationNumber: 96HB18, Year: 1996, PEL ratio: 0.52049, Grade: F\",\"StationNumber: 96HB20, Year: 1996, PEL ratio: 0.14092, Grade: D\",\"StationNumber: 96HB22, Year: 1996, PEL ratio: 0.16443, Grade: D\",\"StationNumber: 96HB23, Year: 1996, PEL ratio: 0.07935, Grade: C\",\"StationNumber: 96HB24, Year: 1996, PEL ratio: 0.00728, Grade: A\",\"StationNumber: 96HB26, Year: 1996, PEL ratio: 0.00701, Grade: A\",\"StationNumber: 96HB27, Year: 1996, PEL ratio: 0.05771, Grade: C\",\"StationNumber: 96HB29, Year: 1996, PEL ratio: 0.01207, Grade: B\",\"StationNumber: 96HB36, Year: 1996, PEL ratio: 0.03241, Grade: C\",\"StationNumber: 96HB37, Year: 1996, PEL ratio: 0.03752, Grade: C\",\"StationNumber: 96HB38, Year: 1996, PEL ratio: 0.10492, Grade: D\",\"StationNumber: 96HB39, Year: 1996, PEL ratio: 0.01913, Grade: B\",\"StationNumber: 96HB42, Year: 1996, PEL ratio: 0.05108, Grade: C\",\"StationNumber: 96HB43, Year: 1996, PEL ratio: 0.08509, Grade: C\",\"StationNumber: 96HB44, Year: 1996, PEL ratio: 0.02579, Grade: C\",\"StationNumber: 96HB45, Year: 1996, PEL ratio: 0.00593, Grade: A\",\"StationNumber: 96HB46, Year: 1996, PEL ratio: 11.28998, Grade: F\",\"StationNumber: 96HB47, Year: 1996, PEL ratio: 0.01428, Grade: B\",\"StationNumber: 96HB48, Year: 1996, PEL ratio: 0.1139, Grade: D\",\"StationNumber: 96HB50, Year: 1996, PEL ratio: 0.02802, Grade: C\",\"StationNumber: 96HB51, Year: 1996, PEL ratio: 0.00781, Grade: B\",\"StationNumber: 96HB52, Year: 1996, PEL ratio: 0.00565, Grade: A\",\"StationNumber: 96HB53, Year: 1996, PEL ratio: 0.00529, Grade: A\",\"StationNumber: 96HB54, Year: 1996, PEL ratio: 0.00646, Grade: A\",\"StationNumber: 96HB56, Year: 1996, PEL ratio: 0.15168, Grade: D\",\"StationNumber: 96LTB01, Year: 1996, PEL ratio: 0.07215, Grade: C\",\"StationNumber: 96LTB02, Year: 1996, PEL ratio: 0.01176, Grade: B\",\"StationNumber: 96LTB03, Year: 1996, PEL ratio: 0.01258, Grade: B\",\"StationNumber: 96LTB04, Year: 1996, PEL ratio: 0.00388, Grade: A\",\"StationNumber: 96LTB05, Year: 1996, PEL ratio: 0.00328, Grade: A\",\"StationNumber: 96LTB06, Year: 1996, PEL ratio: 0.01863, Grade: B\",\"StationNumber: 96LTB07, Year: 1996, PEL ratio: 0.01085, Grade: B\",\"StationNumber: 96LTB08, Year: 1996, PEL ratio: 0.00503, Grade: A\",\"StationNumber: 96LTB09, Year: 1996, PEL ratio: 0.00497, Grade: A\",\"StationNumber: 96LTB10, Year: 1996, PEL ratio: 0.01922, Grade: B\",\"StationNumber: 96LTB11, Year: 1996, PEL ratio: 0.02443, Grade: C\",\"StationNumber: 96LTB12, Year: 1996, PEL ratio: 0.01365, Grade: B\",\"StationNumber: 96LTB13, Year: 1996, PEL ratio: 0.05548, Grade: C\",\"StationNumber: 96LTB15, Year: 1996, PEL ratio: 0.00203, Grade: A\",\"StationNumber: 96LTB17, Year: 1996, PEL ratio: 0.01376, Grade: B\",\"StationNumber: 96LTB18, Year: 1996, PEL ratio: 0.01093, Grade: B\",\"StationNumber: 96LTB19, Year: 1996, PEL ratio: 0.00533, Grade: A\",\"StationNumber: 96LTB20, Year: 1996, PEL ratio: 0.00274, Grade: A\",\"StationNumber: 96LTB21, Year: 1996, PEL ratio: 0.00191, Grade: A\",\"StationNumber: 96LTB23, Year: 1996, PEL ratio: 0.00883, Grade: B\",\"StationNumber: 96LTB24, Year: 1996, PEL ratio: 0.00966, Grade: B\",\"StationNumber: 96LTB25, Year: 1996, PEL ratio: 0.0028, Grade: A\",\"StationNumber: 96LTB26, Year: 1996, PEL ratio: 0.00167, Grade: A\",\"StationNumber: 96LTB27, Year: 1996, PEL ratio: 0.00845, Grade: B\",\"StationNumber: 96MR20, Year: 1996, PEL ratio: 0.0375, Grade: C\",\"StationNumber: 96MR21, Year: 1996, PEL ratio: 0.01873, Grade: B\",\"StationNumber: 96MR23, Year: 1996, PEL ratio: 0.03078, Grade: C\",\"StationNumber: 96MR24, Year: 1996, PEL ratio: 0.04434, Grade: C\",\"StationNumber: 96MR25, Year: 1996, PEL ratio: 0.0361, Grade: C\",\"StationNumber: 96MR26, Year: 1996, PEL ratio: 0.02689, Grade: C\",\"StationNumber: 96MR27, Year: 1996, PEL ratio: 0.02357, Grade: C\",\"StationNumber: 96MR28, Year: 1996, PEL ratio: 0.00874, Grade: B\",\"StationNumber: 96MR29, Year: 1996, PEL ratio: 0.04221, Grade: C\",\"StationNumber: 96MR30, Year: 1996, PEL ratio: 0.03112, Grade: C\",\"StationNumber: 96MR31, Year: 1996, PEL ratio: 0.01702, Grade: B\",\"StationNumber: 96MR32, Year: 1996, PEL ratio: 0.0686, Grade: C\",\"StationNumber: 96MR43, Year: 1996, PEL ratio: 0.00642, Grade: A\",\"StationNumber: 96MTB04, Year: 1996, PEL ratio: 0.00399, Grade: A\",\"StationNumber: 96MTB05, Year: 1996, PEL ratio: 0.00738, Grade: A\",\"StationNumber: 96MTB07, Year: 1996, PEL ratio: 0.01865, Grade: B\",\"StationNumber: 96MTB09, Year: 1996, PEL ratio: 0.04135, Grade: C\",\"StationNumber: 96MTB10, Year: 1996, PEL ratio: 0.00598, Grade: A\",\"StationNumber: 96MTB11, Year: 1996, PEL ratio: 0.0094, Grade: B\",\"StationNumber: 96MTB12, Year: 1996, PEL ratio: 0.01296, Grade: B\",\"StationNumber: 96MTB13, Year: 1996, PEL ratio: 0.00054, Grade: A\",\"StationNumber: 96MTB14, Year: 1996, PEL ratio: 0.21228, Grade: D\",\"StationNumber: 96MTB15, Year: 1996, PEL ratio: 0.00246, Grade: A\",\"StationNumber: 96MTB16, Year: 1996, PEL ratio: 0.00187, Grade: A\",\"StationNumber: 96MTB17, Year: 1996, PEL ratio: 0.02882, Grade: C\",\"StationNumber: 96MTB18, Year: 1996, PEL ratio: 0.00511, Grade: A\",\"StationNumber: 96MTB19, Year: 1996, PEL ratio: 0.00327, Grade: A\",\"StationNumber: 96MTB20, Year: 1996, PEL ratio: 0.07168, Grade: C\",\"StationNumber: 96MTB23, Year: 1996, PEL ratio: 0.00289, Grade: A\",\"StationNumber: 96MTB24, Year: 1996, PEL ratio: 0.0044, Grade: A\",\"StationNumber: 96MTB25, Year: 1996, PEL ratio: 0.00302, Grade: A\",\"StationNumber: 96MTB26, Year: 1996, PEL ratio: 0.00717, Grade: A\",\"StationNumber: 96MTB30, Year: 1996, PEL ratio: 0.00823, Grade: B\",\"StationNumber: 96MTB31, Year: 1996, PEL ratio: 0.01583, Grade: B\",\"StationNumber: 96MTB32, Year: 1996, PEL ratio: 0.02658, Grade: C\",\"StationNumber: 96MTB34, Year: 1996, PEL ratio: 0.01453, Grade: B\",\"StationNumber: 96MTB35, Year: 1996, PEL ratio: 0.00178, Grade: A\",\"StationNumber: 96OTB07, Year: 1996, PEL ratio: 0.00525, Grade: A\",\"StationNumber: 96OTB11, Year: 1996, PEL ratio: 0.0031, Grade: A\",\"StationNumber: 96OTB12, Year: 1996, PEL ratio: 0.01689, Grade: B\",\"StationNumber: 96OTB13, Year: 1996, PEL ratio: 0.00455, Grade: A\",\"StationNumber: 96OTB14, Year: 1996, PEL ratio: 0.01495, Grade: B\",\"StationNumber: 96OTB17, Year: 1996, PEL ratio: 0.00886, Grade: B\",\"StationNumber: 96OTB18, Year: 1996, PEL ratio: 0.01434, Grade: B\",\"StationNumber: 96OTB19, Year: 1996, PEL ratio: 0.01141, Grade: B\",\"StationNumber: 96OTB20, Year: 1996, PEL ratio: 0.09948, Grade: D\",\"StationNumber: 96OTB23, Year: 1996, PEL ratio: 0.00414, Grade: A\",\"StationNumber: 96OTB24, Year: 1996, PEL ratio: 0.00798, Grade: B\",\"StationNumber: 96OTB26, Year: 1996, PEL ratio: 0.00414, Grade: A\",\"StationNumber: 96OTB27, Year: 1996, PEL ratio: 0.00358, Grade: A\",\"StationNumber: 96OTB29, Year: 1996, PEL ratio: 0.00299, Grade: A\",\"StationNumber: 96OTB30, Year: 1996, PEL ratio: 0.01598, Grade: B\",\"StationNumber: 96TCB22, Year: 1996, PEL ratio: 0.03815, Grade: C\",\"StationNumber: 96TCB36, Year: 1996, PEL ratio: 0.0182, Grade: B\",\"StationNumber: 96TCB37, Year: 1996, PEL ratio: 0.06747, Grade: C\",\"StationNumber: 96TCB38, Year: 1996, PEL ratio: 0.04811, Grade: C\",\"StationNumber: 96TCB39, Year: 1996, PEL ratio: 0.03235, Grade: C\",\"StationNumber: 96TCB40, Year: 1996, PEL ratio: 0.02086, Grade: C\",\"StationNumber: 96TCB41, Year: 1996, PEL ratio: 0.02591, Grade: C\",\"StationNumber: 96TCB42, Year: 1996, PEL ratio: 0.01431, Grade: B\",\"StationNumber: 97BCB02, Year: 1997, PEL ratio: 0.02654, Grade: C\",\"StationNumber: 97BCB08, Year: 1997, PEL ratio: 0.06243, Grade: C\",\"StationNumber: 97BCB10, Year: 1997, PEL ratio: 0.07472, Grade: C\",\"StationNumber: 97BCB13, Year: 1997, PEL ratio: 0.02112, Grade: C\",\"StationNumber: 97BCB17, Year: 1997, PEL ratio: 0.06466, Grade: C\",\"StationNumber: 97BCB18, Year: 1997, PEL ratio: 0.03013, Grade: C\",\"StationNumber: 97BCB27, Year: 1997, PEL ratio: 0.25161, Grade: D\",\"StationNumber: 97BCB30, Year: 1997, PEL ratio: 0.02293, Grade: C\",\"StationNumber: 97BCB31, Year: 1997, PEL ratio: 0.00973, Grade: B\",\"StationNumber: 97BCB36, Year: 1997, PEL ratio: 0.01281, Grade: B\",\"StationNumber: 97BCB37, Year: 1997, PEL ratio: 0.01861, Grade: B\",\"StationNumber: 97BCB40, Year: 1997, PEL ratio: 0.03448, Grade: C\",\"StationNumber: 97BCB46, Year: 1997, PEL ratio: 0.01276, Grade: B\",\"StationNumber: 97BCB50, Year: 1997, PEL ratio: 0.0087, Grade: B\",\"StationNumber: 97BCB57-1, Year: 1997, PEL ratio: 0.12797, Grade: D\",\"StationNumber: 97BCB58-1, Year: 1997, PEL ratio: 0.29199, Grade: F\",\"StationNumber: 97BCB58-2, Year: 1997, PEL ratio: 0.04357, Grade: C\",\"StationNumber: 97BCB59-1, Year: 1997, PEL ratio: 0.0167, Grade: B\",\"StationNumber: 97BCB59-2, Year: 1997, PEL ratio: 0.02798, Grade: C\",\"StationNumber: 97BCB60-2, Year: 1997, PEL ratio: 0.00469, Grade: A\",\"StationNumber: 97BCB60-4, Year: 1997, PEL ratio: 0.00523, Grade: A\",\"StationNumber: 97HB10, Year: 1997, PEL ratio: 1.45751, Grade: F\",\"StationNumber: 97HB13, Year: 1997, PEL ratio: 0.20993, Grade: D\",\"StationNumber: 97HB18, Year: 1997, PEL ratio: 0.0395, Grade: C\",\"StationNumber: 97HB22, Year: 1997, PEL ratio: 0.23185, Grade: D\",\"StationNumber: 97HB23, Year: 1997, PEL ratio: 0.01374, Grade: B\",\"StationNumber: 97HB24, Year: 1997, PEL ratio: 0.00515, Grade: A\",\"StationNumber: 97HB27, Year: 1997, PEL ratio: 0.00494, Grade: A\",\"StationNumber: 97HB29, Year: 1997, PEL ratio: 0.18186, Grade: D\",\"StationNumber: 97HB36, Year: 1997, PEL ratio: 0.00827, Grade: B\",\"StationNumber: 97HB37, Year: 1997, PEL ratio: 0.06009, Grade: C\",\"StationNumber: 97HB38, Year: 1997, PEL ratio: 0.04075, Grade: C\",\"StationNumber: 97HB39, Year: 1997, PEL ratio: 0.08084, Grade: C\",\"StationNumber: 97HB43, Year: 1997, PEL ratio: 0.0066, Grade: A\",\"StationNumber: 97HB44, Year: 1997, PEL ratio: 0.01905, Grade: B\",\"StationNumber: 97HB45, Year: 1997, PEL ratio: 0.03887, Grade: C\",\"StationNumber: 97HB46, Year: 1997, PEL ratio: 0.00974, Grade: B\",\"StationNumber: 97HB48, Year: 1997, PEL ratio: 0.00871, Grade: B\",\"StationNumber: 97HB50, Year: 1997, PEL ratio: 0.08114, Grade: C\",\"StationNumber: 97HB53, Year: 1997, PEL ratio: 0.00914, Grade: B\",\"StationNumber: 97HB54, Year: 1997, PEL ratio: 0.01088, Grade: B\",\"StationNumber: 97HB55, Year: 1997, PEL ratio: 0.02004, Grade: B\",\"StationNumber: 97HB56, Year: 1997, PEL ratio: 0.01339, Grade: B\",\"StationNumber: 97LTB01, Year: 1997, PEL ratio: 0.0117, Grade: B\",\"StationNumber: 97LTB02, Year: 1997, PEL ratio: 0.01631, Grade: B\",\"StationNumber: 97LTB03, Year: 1997, PEL ratio: 0.01214, Grade: B\",\"StationNumber: 97LTB06, Year: 1997, PEL ratio: 0.01536, Grade: B\",\"StationNumber: 97LTB07, Year: 1997, PEL ratio: 0.00826, Grade: B\",\"StationNumber: 97LTB09, Year: 1997, PEL ratio: 0.01935, Grade: B\",\"StationNumber: 97LTB10, Year: 1997, PEL ratio: 0.02574, Grade: C\",\"StationNumber: 97LTB11, Year: 1997, PEL ratio: 0.0151, Grade: B\",\"StationNumber: 97LTB12, Year: 1997, PEL ratio: 0.01318, Grade: B\",\"StationNumber: 97LTB13, Year: 1997, PEL ratio: 0.00402, Grade: A\",\"StationNumber: 97LTB15, Year: 1997, PEL ratio: 0.00573, Grade: A\",\"StationNumber: 97LTB17, Year: 1997, PEL ratio: 0.00975, Grade: B\",\"StationNumber: 97LTB18, Year: 1997, PEL ratio: 0.00942, Grade: B\",\"StationNumber: 97LTB19, Year: 1997, PEL ratio: 0.00972, Grade: B\",\"StationNumber: 97LTB20, Year: 1997, PEL ratio: 0.00464, Grade: A\",\"StationNumber: 97LTB21, Year: 1997, PEL ratio: 0.00565, Grade: A\",\"StationNumber: 97LTB23, Year: 1997, PEL ratio: 0.01146, Grade: B\",\"StationNumber: 97LTB24, Year: 1997, PEL ratio: 0.00376, Grade: A\",\"StationNumber: 97LTB25, Year: 1997, PEL ratio: 0.00699, Grade: A\",\"StationNumber: 97LTB26, Year: 1997, PEL ratio: 0.00218, Grade: A\",\"StationNumber: 97LTB28, Year: 1997, PEL ratio: 0.00444, Grade: A\",\"StationNumber: 97MR09, Year: 1997, PEL ratio: 0.01198, Grade: B\",\"StationNumber: 97MR10, Year: 1997, PEL ratio: 0.02239, Grade: C\",\"StationNumber: 97MR11, Year: 1997, PEL ratio: 0.04743, Grade: C\",\"StationNumber: 97MR12, Year: 1997, PEL ratio: 0.04395, Grade: C\",\"StationNumber: 97MR13, Year: 1997, PEL ratio: 0.0476, Grade: C\",\"StationNumber: 97MR14, Year: 1997, PEL ratio: 0.08134, Grade: C\",\"StationNumber: 97MR15, Year: 1997, PEL ratio: 0.02453, Grade: C\",\"StationNumber: 97MR16, Year: 1997, PEL ratio: 0.05074, Grade: C\",\"StationNumber: 97MR17, Year: 1997, PEL ratio: 0.02537, Grade: C\",\"StationNumber: 97MR18, Year: 1997, PEL ratio: 0.00736, Grade: A\",\"StationNumber: 97MR19, Year: 1997, PEL ratio: 0.04387, Grade: C\",\"StationNumber: 97MR20, Year: 1997, PEL ratio: 0.05581, Grade: C\",\"StationNumber: 97MR21, Year: 1997, PEL ratio: 0.04083, Grade: C\",\"StationNumber: 97MTB02, Year: 1997, PEL ratio: 0.02552, Grade: C\",\"StationNumber: 97MTB03, Year: 1997, PEL ratio: 0.00549, Grade: A\",\"StationNumber: 97MTB04, Year: 1997, PEL ratio: 0.0071, Grade: A\",\"StationNumber: 97MTB05, Year: 1997, PEL ratio: 0.00589, Grade: A\",\"StationNumber: 97MTB07, Year: 1997, PEL ratio: 0.01701, Grade: B\",\"StationNumber: 97MTB09, Year: 1997, PEL ratio: 0.01016, Grade: B\",\"StationNumber: 97MTB10, Year: 1997, PEL ratio: 0.01151, Grade: B\",\"StationNumber: 97MTB12, Year: 1997, PEL ratio: 0.01224, Grade: B\",\"StationNumber: 97MTB14, Year: 1997, PEL ratio: 0.04718, Grade: C\",\"StationNumber: 97MTB15, Year: 1997, PEL ratio: 0.00923, Grade: B\",\"StationNumber: 97MTB16, Year: 1997, PEL ratio: 0.02076, Grade: C\",\"StationNumber: 97MTB17, Year: 1997, PEL ratio: 0.01049, Grade: B\",\"StationNumber: 97MTB18, Year: 1997, PEL ratio: 0.00491, Grade: A\",\"StationNumber: 97MTB19, Year: 1997, PEL ratio: 0.00548, Grade: A\",\"StationNumber: 97MTB23, Year: 1997, PEL ratio: 0.01245, Grade: B\",\"StationNumber: 97MTB24, Year: 1997, PEL ratio: 0.01036, Grade: B\",\"StationNumber: 97MTB25, Year: 1997, PEL ratio: 0.0052, Grade: A\",\"StationNumber: 97MTB26, Year: 1997, PEL ratio: 0.00284, Grade: A\",\"StationNumber: 97MTB30, Year: 1997, PEL ratio: 0.00464, Grade: A\",\"StationNumber: 97MTB31, Year: 1997, PEL ratio: 0.00402, Grade: A\",\"StationNumber: 97MTB32, Year: 1997, PEL ratio: 0.02691, Grade: C\",\"StationNumber: 97MTB35, Year: 1997, PEL ratio: 0.00417, Grade: A\",\"StationNumber: 97OTB03, Year: 1997, PEL ratio: 0.08428, Grade: C\",\"StationNumber: 97OTB06, Year: 1997, PEL ratio: 0.00508, Grade: A\",\"StationNumber: 97OTB07, Year: 1997, PEL ratio: 0.04147, Grade: C\",\"StationNumber: 97OTB11, Year: 1997, PEL ratio: 0.01536, Grade: B\",\"StationNumber: 97OTB12, Year: 1997, PEL ratio: 0.00901, Grade: B\",\"StationNumber: 97OTB13, Year: 1997, PEL ratio: 0.02195, Grade: C\",\"StationNumber: 97OTB17, Year: 1997, PEL ratio: 0.02135, Grade: C\",\"StationNumber: 97OTB18, Year: 1997, PEL ratio: 0.01639, Grade: B\",\"StationNumber: 97OTB19, Year: 1997, PEL ratio: 0.00365, Grade: A\",\"StationNumber: 97OTB20, Year: 1997, PEL ratio: 0.0108, Grade: B\",\"StationNumber: 97OTB22, Year: 1997, PEL ratio: 0.00594, Grade: A\",\"StationNumber: 97OTB23, Year: 1997, PEL ratio: 0.00358, Grade: A\",\"StationNumber: 97OTB24, Year: 1997, PEL ratio: 0.01809, Grade: B\",\"StationNumber: 97OTB26, Year: 1997, PEL ratio: 0.00369, Grade: A\",\"StationNumber: 97OTB27, Year: 1997, PEL ratio: 0.0027, Grade: A\",\"StationNumber: 97OTB29, Year: 1997, PEL ratio: 0.00729, Grade: A\",\"StationNumber: 97TCB01, Year: 1997, PEL ratio: 0.03736, Grade: C\",\"StationNumber: 97TCB02, Year: 1997, PEL ratio: 0.05752, Grade: C\",\"StationNumber: 97TCB03, Year: 1997, PEL ratio: 0.07413, Grade: C\",\"StationNumber: 97TCB04, Year: 1997, PEL ratio: 0.0463, Grade: C\",\"StationNumber: 97TCB05, Year: 1997, PEL ratio: 0.03402, Grade: C\",\"StationNumber: 97TCB06, Year: 1997, PEL ratio: 0.03071, Grade: C\",\"StationNumber: 97TCB07, Year: 1997, PEL ratio: 0.06132, Grade: C\",\"StationNumber: 97TCB08, Year: 1997, PEL ratio: 0.0461, Grade: C\",\"StationNumber: 98BCB06, Year: 1998, PEL ratio: 0.00538, Grade: A\",\"StationNumber: 98BCB09, Year: 1998, PEL ratio: 0.00305, Grade: A\",\"StationNumber: 98BCB11, Year: 1998, PEL ratio: 0.00393, Grade: A\",\"StationNumber: 98BCB12, Year: 1998, PEL ratio: 0.02037, Grade: B\",\"StationNumber: 98BCB15, Year: 1998, PEL ratio: 0.0045, Grade: A\",\"StationNumber: 98BCB17, Year: 1998, PEL ratio: 0.01586, Grade: B\",\"StationNumber: 98BCB21, Year: 1998, PEL ratio: 0.0041, Grade: A\",\"StationNumber: 98BCB27, Year: 1998, PEL ratio: 0.01015, Grade: B\",\"StationNumber: 98BCB28, Year: 1998, PEL ratio: 0.0098, Grade: B\",\"StationNumber: 98BCB32, Year: 1998, PEL ratio: 0.00254, Grade: A\",\"StationNumber: 98BCB38, Year: 1998, PEL ratio: 0.00578, Grade: A\",\"StationNumber: 98BCB40, Year: 1998, PEL ratio: 0.00383, Grade: A\",\"StationNumber: 98BCB43, Year: 1998, PEL ratio: 0.00199, Grade: A\",\"StationNumber: 98BCB46, Year: 1998, PEL ratio: 0.01378, Grade: B\",\"StationNumber: 98BCB57/1, Year: 1998, PEL ratio: 0.06999, Grade: C\",\"StationNumber: 98BCB58/1, Year: 1998, PEL ratio: 0.1367, Grade: D\",\"StationNumber: 98BCB58/2, Year: 1998, PEL ratio: 0.02526, Grade: C\",\"StationNumber: 98BCB59/1, Year: 1998, PEL ratio: 0.00363, Grade: A\",\"StationNumber: 98BCB59/2, Year: 1998, PEL ratio: 0.02915, Grade: C\",\"StationNumber: 98BCB60/2, Year: 1998, PEL ratio: 0.00939, Grade: B\",\"StationNumber: 98BCB60/4, Year: 1998, PEL ratio: 0.02529, Grade: C\",\"StationNumber: 98HB003, Year: 1998, PEL ratio: 0.0024, Grade: A\",\"StationNumber: 98HB006, Year: 1998, PEL ratio: 0.97324, Grade: F\",\"StationNumber: 98HB014, Year: 1998, PEL ratio: 0.0317, Grade: C\",\"StationNumber: 98HB016, Year: 1998, PEL ratio: 0.11511, Grade: D\",\"StationNumber: 98HB017, Year: 1998, PEL ratio: 0.00283, Grade: A\",\"StationNumber: 98HB024, Year: 1998, PEL ratio: 0.03375, Grade: C\",\"StationNumber: 98HB030, Year: 1998, PEL ratio: 0.00478, Grade: A\",\"StationNumber: 98HB049, Year: 1998, PEL ratio: 0.00685, Grade: A\",\"StationNumber: 98HB052, Year: 1998, PEL ratio: 0.04381, Grade: C\",\"StationNumber: 98HB056, Year: 1998, PEL ratio: 0.00367, Grade: A\",\"StationNumber: 98HB059, Year: 1998, PEL ratio: 0.00786, Grade: B\",\"StationNumber: 98HB069, Year: 1998, PEL ratio: 0.01266, Grade: B\",\"StationNumber: 98HB080, Year: 1998, PEL ratio: 0.10159, Grade: D\",\"StationNumber: 98HB089, Year: 1998, PEL ratio: 0.01263, Grade: B\",\"StationNumber: 98HB130, Year: 1998, PEL ratio: 0.00708, Grade: A\",\"StationNumber: 98HB153, Year: 1998, PEL ratio: 0.00364, Grade: A\",\"StationNumber: 98HB171, Year: 1998, PEL ratio: 0.07363, Grade: C\",\"StationNumber: 98HB180, Year: 1998, PEL ratio: 0.02965, Grade: C\",\"StationNumber: 98HB224, Year: 1998, PEL ratio: 0.0387, Grade: C\",\"StationNumber: 98HB237, Year: 1998, PEL ratio: 0.00906, Grade: B\",\"StationNumber: 98HB245, Year: 1998, PEL ratio: 0.02123, Grade: C\",\"StationNumber: 98HB252, Year: 1998, PEL ratio: 0.04475, Grade: C\",\"StationNumber: 98HB280, Year: 1998, PEL ratio: 0.01676, Grade: B\",\"StationNumber: 98HB789, Year: 1998, PEL ratio: 0.07519, Grade: C\",\"StationNumber: 98HBDIcanal, Year: 1998, PEL ratio: 0.0396, Grade: C\",\"StationNumber: 98HBspark, Year: 1998, PEL ratio: 0.12448, Grade: D\",\"StationNumber: 98LTB0014, Year: 1998, PEL ratio: 0.01019, Grade: B\",\"StationNumber: 98LTB0025, Year: 1998, PEL ratio: 0.00349, Grade: A\",\"StationNumber: 98LTB0049, Year: 1998, PEL ratio: 0.0015, Grade: A\",\"StationNumber: 98LTB0095, Year: 1998, PEL ratio: 0.00272, Grade: A\",\"StationNumber: 98LTB0123, Year: 1998, PEL ratio: 0.0128, Grade: B\",\"StationNumber: 98LTB0144, Year: 1998, PEL ratio: 0.00354, Grade: A\",\"StationNumber: 98LTB0151, Year: 1998, PEL ratio: 0.01302, Grade: B\",\"StationNumber: 98LTB0168, Year: 1998, PEL ratio: 0.00254, Grade: A\",\"StationNumber: 98LTB0183, Year: 1998, PEL ratio: 0.00534, Grade: A\",\"StationNumber: 98LTB0223, Year: 1998, PEL ratio: 0.00257, Grade: A\",\"StationNumber: 98LTB0244, Year: 1998, PEL ratio: 0.00145, Grade: A\",\"StationNumber: 98LTB0273, Year: 1998, PEL ratio: 0.00217, Grade: A\",\"StationNumber: 98LTB0307, Year: 1998, PEL ratio: 0.00156, Grade: A\",\"StationNumber: 98LTB0364, Year: 1998, PEL ratio: 0.00282, Grade: A\",\"StationNumber: 98LTB0393, Year: 1998, PEL ratio: 0.00144, Grade: A\",\"StationNumber: 98LTB0762, Year: 1998, PEL ratio: 0.00278, Grade: A\",\"StationNumber: 98LTB1057, Year: 1998, PEL ratio: 0.00277, Grade: A\",\"StationNumber: 98MR09, Year: 1998, PEL ratio: 0.00264, Grade: A\",\"StationNumber: 98MR10, Year: 1998, PEL ratio: 0.00747, Grade: A\",\"StationNumber: 98MR11, Year: 1998, PEL ratio: 0.02354, Grade: C\",\"StationNumber: 98MR12, Year: 1998, PEL ratio: 0.01409, Grade: B\",\"StationNumber: 98MR13, Year: 1998, PEL ratio: 0.04647, Grade: C\",\"StationNumber: 98MR14, Year: 1998, PEL ratio: 0.01126, Grade: B\",\"StationNumber: 98MR15, Year: 1998, PEL ratio: 0.01005, Grade: B\",\"StationNumber: 98MR16, Year: 1998, PEL ratio: 0.0221, Grade: C\",\"StationNumber: 98MR17, Year: 1998, PEL ratio: 0.01136, Grade: B\",\"StationNumber: 98MR18, Year: 1998, PEL ratio: 0.00778, Grade: B\",\"StationNumber: 98MR19, Year: 1998, PEL ratio: 0.00838, Grade: B\",\"StationNumber: 98MR20, Year: 1998, PEL ratio: 0.00821, Grade: B\",\"StationNumber: 98MR21, Year: 1998, PEL ratio: 0.18896, Grade: D\",\"StationNumber: 98MTB0032, Year: 1998, PEL ratio: 0.0044, Grade: A\",\"StationNumber: 98MTB0035, Year: 1998, PEL ratio: 0.02315, Grade: C\",\"StationNumber: 98MTB0052, Year: 1998, PEL ratio: 0.01441, Grade: B\",\"StationNumber: 98MTB0067, Year: 1998, PEL ratio: 0.00681, Grade: A\",\"StationNumber: 98MTB0090, Year: 1998, PEL ratio: 0.00845, Grade: B\",\"StationNumber: 98MTB0103, Year: 1998, PEL ratio: 0.00342, Grade: A\",\"StationNumber: 98MTB0133, Year: 1998, PEL ratio: 0.00293, Grade: A\",\"StationNumber: 98MTB0187, Year: 1998, PEL ratio: 0.0175, Grade: B\",\"StationNumber: 98MTB0191, Year: 1998, PEL ratio: 0.29254, Grade: F\",\"StationNumber: 98MTB0208, Year: 1998, PEL ratio: 0.00527, Grade: A\",\"StationNumber: 98MTB0270, Year: 1998, PEL ratio: 0.00339, Grade: A\",\"StationNumber: 98MTB0275, Year: 1998, PEL ratio: 0.00228, Grade: A\",\"StationNumber: 98MTB0283, Year: 1998, PEL ratio: 0.00476, Grade: A\",\"StationNumber: 98MTB0322, Year: 1998, PEL ratio: 0.00756, Grade: B\",\"StationNumber: 98MTB0331, Year: 1998, PEL ratio: 0.00226, Grade: A\",\"StationNumber: 98MTB0416, Year: 1998, PEL ratio: 0.01759, Grade: B\",\"StationNumber: 98MTB0460, Year: 1998, PEL ratio: 0.00109, Grade: A\",\"StationNumber: 98MTB0688, Year: 1998, PEL ratio: 0.00187, Grade: A\",\"StationNumber: 98MTB0694, Year: 1998, PEL ratio: 0.00183, Grade: A\",\"StationNumber: 98MTB1036, Year: 1998, PEL ratio: 0.00193, Grade: A\",\"StationNumber: 98OTB0036, Year: 1998, PEL ratio: 0.0377, Grade: C\",\"StationNumber: 98OTB0039, Year: 1998, PEL ratio: 0.01561, Grade: B\",\"StationNumber: 98OTB0048, Year: 1998, PEL ratio: 0.00858, Grade: B\",\"StationNumber: 98OTB0056, Year: 1998, PEL ratio: 0.01204, Grade: B\",\"StationNumber: 98OTB0125, Year: 1998, PEL ratio: 0.00279, Grade: A\",\"StationNumber: 98OTB0177, Year: 1998, PEL ratio: 0.00429, Grade: A\",\"StationNumber: 98OTB0185, Year: 1998, PEL ratio: 0.00276, Grade: A\",\"StationNumber: 98OTB0199, Year: 1998, PEL ratio: 0.0051, Grade: A\",\"StationNumber: 98OTB0232, Year: 1998, PEL ratio: 0.00966, Grade: B\",\"StationNumber: 98OTB0239, Year: 1998, PEL ratio: 0.00934, Grade: B\",\"StationNumber: 98OTB0274, Year: 1998, PEL ratio: 0.00653, Grade: A\",\"StationNumber: 98OTB0425, Year: 1998, PEL ratio: 0.00388, Grade: A\",\"StationNumber: 98OTB0596, Year: 1998, PEL ratio: 0.13969, Grade: D\",\"StationNumber: 98OTB0721, Year: 1998, PEL ratio: 0.01378, Grade: B\",\"StationNumber: 98OTB1140, Year: 1998, PEL ratio: 0.01913, Grade: B\",\"StationNumber: 98OTB1227, Year: 1998, PEL ratio: 0.00236, Grade: A\",\"StationNumber: 98TCB01, Year: 1998, PEL ratio: 0.00905, Grade: B\",\"StationNumber: 98TCB02, Year: 1998, PEL ratio: 0.00594, Grade: A\",\"StationNumber: 98TCB04, Year: 1998, PEL ratio: 0.0067, Grade: A\",\"StationNumber: 98TCB05, Year: 1998, PEL ratio: 0.00686, Grade: A\",\"StationNumber: 98TCB06, Year: 1998, PEL ratio: 0.00741, Grade: A\",\"StationNumber: 98TCB07, Year: 1998, PEL ratio: 0.0084, Grade: B\",\"StationNumber: 98TCB08, Year: 1998, PEL ratio: 0.02781, Grade: C\",\"StationNumber: 99BCB2025, Year: 1999, PEL ratio: 0.005, Grade: A\",\"StationNumber: 99BCB2041, Year: 1999, PEL ratio: 0.00537, Grade: A\",\"StationNumber: 99BCB2063, Year: 1999, PEL ratio: 0.01586, Grade: B\",\"StationNumber: 99BCB2069, Year: 1999, PEL ratio: 0.00888, Grade: B\",\"StationNumber: 99BCB2070, Year: 1999, PEL ratio: 0.00858, Grade: B\",\"StationNumber: 99BCB2086, Year: 1999, PEL ratio: 0.00471, Grade: A\",\"StationNumber: 99BCB2094, Year: 1999, PEL ratio: 0.02788, Grade: C\",\"StationNumber: 99BCB2115, Year: 1999, PEL ratio: 0.01214, Grade: B\",\"StationNumber: 99BCB2132, Year: 1999, PEL ratio: 0.00326, Grade: A\",\"StationNumber: 99BCB2295, Year: 1999, PEL ratio: 0.00282, Grade: A\",\"StationNumber: 99BCB2358, Year: 1999, PEL ratio: 0.00626, Grade: A\",\"StationNumber: 99BCB2423, Year: 1999, PEL ratio: 0.00676, Grade: A\",\"StationNumber: 99BCB2514, Year: 1999, PEL ratio: 0.00801, Grade: B\",\"StationNumber: 99BCB2585, Year: 1999, PEL ratio: 0.00657, Grade: A\",\"StationNumber: 99BCB57/1, Year: 1999, PEL ratio: 0.05417, Grade: C\",\"StationNumber: 99BCB58/1, Year: 1999, PEL ratio: 0.09826, Grade: D\",\"StationNumber: 99BCB58/2, Year: 1999, PEL ratio: 0.01409, Grade: B\",\"StationNumber: 99BCB59/1, Year: 1999, PEL ratio: 0.0028, Grade: A\",\"StationNumber: 99BCB59/2, Year: 1999, PEL ratio: 0.02713, Grade: C\",\"StationNumber: 99BCB60/2, Year: 1999, PEL ratio: 0.0045, Grade: A\",\"StationNumber: 99BCB60/4, Year: 1999, PEL ratio: 0.0094, Grade: B\",\"StationNumber: 99HB2001, Year: 1999, PEL ratio: 0.00875, Grade: B\",\"StationNumber: 99HB2012, Year: 1999, PEL ratio: 0.05472, Grade: C\",\"StationNumber: 99HB2013, Year: 1999, PEL ratio: 0.01091, Grade: B\",\"StationNumber: 99HB2019, Year: 1999, PEL ratio: 0.01342, Grade: B\",\"StationNumber: 99HB2040, Year: 1999, PEL ratio: 0.00861, Grade: B\",\"StationNumber: 99HB2041, Year: 1999, PEL ratio: 0.00984, Grade: B\",\"StationNumber: 99HB2043, Year: 1999, PEL ratio: 0.00514, Grade: A\",\"StationNumber: 99HB2044, Year: 1999, PEL ratio: 0.01258, Grade: B\",\"StationNumber: 99HB2051, Year: 1999, PEL ratio: 0.04843, Grade: C\",\"StationNumber: 99HB2055, Year: 1999, PEL ratio: 0.01863, Grade: B\",\"StationNumber: 99HB2058, Year: 1999, PEL ratio: 0.1295, Grade: D\",\"StationNumber: 99HB2061, Year: 1999, PEL ratio: 0.66795, Grade: F\",\"StationNumber: 99HB2085, Year: 1999, PEL ratio: 0.11485, Grade: D\",\"StationNumber: 99HB2094, Year: 1999, PEL ratio: 0.00687, Grade: A\",\"StationNumber: 99HB2124, Year: 1999, PEL ratio: 0.08012, Grade: C\",\"StationNumber: 99HB2157, Year: 1999, PEL ratio: 0.01348, Grade: B\",\"StationNumber: 99HB2176, Year: 1999, PEL ratio: 0.07747, Grade: C\",\"StationNumber: 99HB2207, Year: 1999, PEL ratio: 0.09551, Grade: D\",\"StationNumber: 99HB2214, Year: 1999, PEL ratio: 0.00568, Grade: A\",\"StationNumber: 99HB2233, Year: 1999, PEL ratio: 0.04361, Grade: C\",\"StationNumber: 99HB2393, Year: 1999, PEL ratio: 0.01757, Grade: B\",\"StationNumber: 99HB2445, Year: 1999, PEL ratio: 0.0179, Grade: B\",\"StationNumber: 99HB2757, Year: 1999, PEL ratio: 0.01124, Grade: B\",\"StationNumber: 99LTB2014, Year: 1999, PEL ratio: 0.00357, Grade: A\",\"StationNumber: 99LTB2021, Year: 1999, PEL ratio: 0.02082, Grade: C\",\"StationNumber: 99LTB2041, Year: 1999, PEL ratio: 0.01184, Grade: B\",\"StationNumber: 99LTB2071, Year: 1999, PEL ratio: 0.04983, Grade: C\",\"StationNumber: 99LTB2112, Year: 1999, PEL ratio: 0.01, Grade: B\",\"StationNumber: 99LTB2124, Year: 1999, PEL ratio: 0.00203, Grade: A\",\"StationNumber: 99LTB2203, Year: 1999, PEL ratio: 0.03476, Grade: C\",\"StationNumber: 99LTB2214, Year: 1999, PEL ratio: 0.00338, Grade: A\",\"StationNumber: 99LTB2247, Year: 1999, PEL ratio: 0.00398, Grade: A\",\"StationNumber: 99LTB2267, Year: 1999, PEL ratio: 0.00762, Grade: B\",\"StationNumber: 99LTB2277, Year: 1999, PEL ratio: 0.00489, Grade: A\",\"StationNumber: 99LTB2290, Year: 1999, PEL ratio: 0.00641, Grade: A\",\"StationNumber: 99LTB2327, Year: 1999, PEL ratio: 0.00354, Grade: A\",\"StationNumber: 99LTB2546, Year: 1999, PEL ratio: 0.00355, Grade: A\",\"StationNumber: 99LTB2617, Year: 1999, PEL ratio: 0.0074, Grade: A\",\"StationNumber: 99LTB3020, Year: 1999, PEL ratio: 0.00328, Grade: A\",\"StationNumber: 99MR09, Year: 1999, PEL ratio: 0.00455, Grade: A\",\"StationNumber: 99MR10, Year: 1999, PEL ratio: 0.00816, Grade: B\",\"StationNumber: 99MR11, Year: 1999, PEL ratio: 0.01449, Grade: B\",\"StationNumber: 99MR12, Year: 1999, PEL ratio: 0.00376, Grade: A\",\"StationNumber: 99MR13, Year: 1999, PEL ratio: 0.00522, Grade: A\",\"StationNumber: 99MR14, Year: 1999, PEL ratio: 0.00891, Grade: B\",\"StationNumber: 99MR15, Year: 1999, PEL ratio: 0.00463, Grade: A\",\"StationNumber: 99MR16, Year: 1999, PEL ratio: 0.00967, Grade: B\",\"StationNumber: 99MR17, Year: 1999, PEL ratio: 0.00407, Grade: A\",\"StationNumber: 99MR18, Year: 1999, PEL ratio: 0.00432, Grade: A\",\"StationNumber: 99MR19, Year: 1999, PEL ratio: 0.007, Grade: A\",\"StationNumber: 99MR20, Year: 1999, PEL ratio: 0.00696, Grade: A\",\"StationNumber: 99MR21, Year: 1999, PEL ratio: 0.00917, Grade: B\",\"StationNumber: 99MTB2029, Year: 1999, PEL ratio: 0.00978, Grade: B\",\"StationNumber: 99MTB2059, Year: 1999, PEL ratio: 0.00849, Grade: B\",\"StationNumber: 99MTB2060, Year: 1999, PEL ratio: 0.00498, Grade: A\",\"StationNumber: 99MTB2108, Year: 1999, PEL ratio: 0.01361, Grade: B\",\"StationNumber: 99MTB2109, Year: 1999, PEL ratio: 0.00725, Grade: A\",\"StationNumber: 99MTB2116, Year: 1999, PEL ratio: 0.01071, Grade: B\",\"StationNumber: 99MTB2129, Year: 1999, PEL ratio: 0.00543, Grade: A\",\"StationNumber: 99MTB2149, Year: 1999, PEL ratio: 0.00588, Grade: A\",\"StationNumber: 99MTB2165, Year: 1999, PEL ratio: 0.00463, Grade: A\",\"StationNumber: 99MTB2240, Year: 1999, PEL ratio: 0.00258, Grade: A\",\"StationNumber: 99MTB2243, Year: 1999, PEL ratio: 0.00684, Grade: A\",\"StationNumber: 99MTB2244, Year: 1999, PEL ratio: 0.00704, Grade: A\",\"StationNumber: 99MTB2253, Year: 1999, PEL ratio: 0.00506, Grade: A\",\"StationNumber: 99MTB2268, Year: 1999, PEL ratio: 0.00697, Grade: A\",\"StationNumber: 99MTB2274, Year: 1999, PEL ratio: 0.00654, Grade: A\",\"StationNumber: 99MTB2291, Year: 1999, PEL ratio: 0.00339, Grade: A\",\"StationNumber: 99MTB2358, Year: 1999, PEL ratio: 0.02137, Grade: C\",\"StationNumber: 99MTB2385, Year: 1999, PEL ratio: 0.00448, Grade: A\",\"StationNumber: 99MTB2554, Year: 1999, PEL ratio: 0.00369, Grade: A\",\"StationNumber: 99MTB2598, Year: 1999, PEL ratio: 0.00643, Grade: A\",\"StationNumber: 99MTB2642, Year: 1999, PEL ratio: 0.00161, Grade: A\",\"StationNumber: 99OTB2002, Year: 1999, PEL ratio: 0.00876, Grade: B\",\"StationNumber: 99OTB2005, Year: 1999, PEL ratio: 0.00294, Grade: A\",\"StationNumber: 99OTB2009, Year: 1999, PEL ratio: 0.00343, Grade: A\",\"StationNumber: 99OTB2010, Year: 1999, PEL ratio: 0.00216, Grade: A\",\"StationNumber: 99OTB2022, Year: 1999, PEL ratio: 0.00491, Grade: A\",\"StationNumber: 99OTB2045, Year: 1999, PEL ratio: 0.00455, Grade: A\",\"StationNumber: 99OTB2067, Year: 1999, PEL ratio: 0.00573, Grade: A\",\"StationNumber: 99OTB2111, Year: 1999, PEL ratio: 0.00613, Grade: A\",\"StationNumber: 99OTB2121, Year: 1999, PEL ratio: 0.00637, Grade: A\",\"StationNumber: 99OTB2225, Year: 1999, PEL ratio: 0.00677, Grade: A\",\"StationNumber: 99OTB2296, Year: 1999, PEL ratio: 0.0151, Grade: B\",\"StationNumber: 99OTB2313, Year: 1999, PEL ratio: 0.01389, Grade: B\",\"StationNumber: 99OTB2316, Year: 1999, PEL ratio: 0.02452, Grade: C\",\"StationNumber: 99OTB2331, Year: 1999, PEL ratio: 0.00962, Grade: B\",\"StationNumber: 99OTB2395, Year: 1999, PEL ratio: 0.00307, Grade: A\",\"StationNumber: 99OTB2482, Year: 1999, PEL ratio: 0.02893, Grade: C\",\"StationNumber: 99OTB2908, Year: 1999, PEL ratio: 0.00461, Grade: A\",\"StationNumber: 99OTB2994, Year: 1999, PEL ratio: 0.00236, Grade: A\",\"StationNumber: 99OTB3046, Year: 1999, PEL ratio: 0.01179, Grade: B\",\"StationNumber: 99TCB01, Year: 1999, PEL ratio: 0.00891, Grade: B\",\"StationNumber: 99TCB02, Year: 1999, PEL ratio: 0.00618, Grade: A\",\"StationNumber: 99TCB03, Year: 1999, PEL ratio: 0.01419, Grade: B\",\"StationNumber: 99TCB04, Year: 1999, PEL ratio: 0.00915, Grade: B\",\"StationNumber: 99TCB05, Year: 1999, PEL ratio: 0.00868, Grade: B\",\"StationNumber: 99TCB06, Year: 1999, PEL ratio: 0.01238, Grade: B\",\"StationNumber: 99TCB07, Year: 1999, PEL ratio: 0.01057, Grade: B\",\"StationNumber: 99TCB08, Year: 1999, PEL ratio: 0.00285, Grade: A\",\"StationNumber: 00BCB4000, Year: 2000, PEL ratio: 0.03235, Grade: C\",\"StationNumber: 00BCB4001, Year: 2000, PEL ratio: 0.03269, Grade: C\",\"StationNumber: 00BCB4004, Year: 2000, PEL ratio: 0.02038, Grade: B\",\"StationNumber: 00BCB4033, Year: 2000, PEL ratio: 0.08678, Grade: D\",\"StationNumber: 00BCB4034, Year: 2000, PEL ratio: 0.03197, Grade: C\",\"StationNumber: 00BCB4037, Year: 2000, PEL ratio: 0.02797, Grade: C\",\"StationNumber: 00BCB4038, Year: 2000, PEL ratio: 0.81297, Grade: F\",\"StationNumber: 00BCB4041, Year: 2000, PEL ratio: 0.03473, Grade: C\",\"StationNumber: 00BCB4042, Year: 2000, PEL ratio: 0.03588, Grade: C\",\"StationNumber: 00BCB4046, Year: 2000, PEL ratio: 0.03579, Grade: C\",\"StationNumber: 00BCB4079, Year: 2000, PEL ratio: 0.02888, Grade: C\",\"StationNumber: 00BCB4084, Year: 2000, PEL ratio: 0.03169, Grade: C\",\"StationNumber: 00BCB4090, Year: 2000, PEL ratio: 0.0329, Grade: C\",\"StationNumber: 00BCB4100, Year: 2000, PEL ratio: 0.03654, Grade: C\",\"StationNumber: 00BCB4124, Year: 2000, PEL ratio: 0.0309, Grade: C\",\"StationNumber: 00BCB4165, Year: 2000, PEL ratio: 0.03378, Grade: C\",\"StationNumber: 00BCB4174, Year: 2000, PEL ratio: 0.03618, Grade: C\",\"StationNumber: 00BCB4207, Year: 2000, PEL ratio: 0.03283, Grade: C\",\"StationNumber: 00BCB4268, Year: 2000, PEL ratio: 0.03803, Grade: C\",\"StationNumber: 00BCB4299, Year: 2000, PEL ratio: 0.04446, Grade: C\",\"StationNumber: 00BCB4312, Year: 2000, PEL ratio: 0.03143, Grade: C\",\"StationNumber: 00BCB58/1, Year: 2000, PEL ratio: 0.18329, Grade: D\",\"StationNumber: 00BCB58/2, Year: 2000, PEL ratio: 0.04382, Grade: C\",\"StationNumber: 00BCB59/1, Year: 2000, PEL ratio: 0.04353, Grade: C\",\"StationNumber: 00BCB59/2, Year: 2000, PEL ratio: 0.06279, Grade: C\",\"StationNumber: 00BCB60/2, Year: 2000, PEL ratio: 0.04105, Grade: C\",\"StationNumber: 00BCB60/4, Year: 2000, PEL ratio: 0.04149, Grade: C\",\"StationNumber: 00HB4002, Year: 2000, PEL ratio: 0.04724, Grade: C\",\"StationNumber: 00HB4006, Year: 2000, PEL ratio: 0.04834, Grade: C\",\"StationNumber: 00HB4019, Year: 2000, PEL ratio: 0.10805, Grade: D\",\"StationNumber: 00HB4023, Year: 2000, PEL ratio: 0.0462, Grade: C\",\"StationNumber: 00HB4032, Year: 2000, PEL ratio: 0.04776, Grade: C\",\"StationNumber: 00HB4033, Year: 2000, PEL ratio: 0.05791, Grade: C\",\"StationNumber: 00HB4038, Year: 2000, PEL ratio: 0.04416, Grade: C\",\"StationNumber: 00HB4047, Year: 2000, PEL ratio: 0.04742, Grade: C\",\"StationNumber: 00HB4058, Year: 2000, PEL ratio: 0.01604, Grade: B\",\"StationNumber: 00HB4077, Year: 2000, PEL ratio: 0.05066, Grade: C\",\"StationNumber: 00HB4082, Year: 2000, PEL ratio: 0.04468, Grade: C\",\"StationNumber: 00HB4083, Year: 2000, PEL ratio: 0.04996, Grade: C\",\"StationNumber: 00HB4093, Year: 2000, PEL ratio: 0.06406, Grade: C\",\"StationNumber: 00HB4094, Year: 2000, PEL ratio: 0.06062, Grade: C\",\"StationNumber: 00HB4100, Year: 2000, PEL ratio: 0.04297, Grade: C\",\"StationNumber: 00HB4106, Year: 2000, PEL ratio: 0.09251, Grade: D\",\"StationNumber: 00HB4144, Year: 2000, PEL ratio: 0.53451, Grade: F\",\"StationNumber: 00HB4152, Year: 2000, PEL ratio: 0.04469, Grade: C\",\"StationNumber: 00HB4267, Year: 2000, PEL ratio: 0.06204, Grade: C\",\"StationNumber: 00HB4291, Year: 2000, PEL ratio: 0.05424, Grade: C\",\"StationNumber: 00HB4316, Year: 2000, PEL ratio: 0.05501, Grade: C\",\"StationNumber: 00HB4505, Year: 2000, PEL ratio: 0.06045, Grade: C\",\"StationNumber: 00LTB4039, Year: 2000, PEL ratio: 0.04606, Grade: C\",\"StationNumber: 00LTB4051, Year: 2000, PEL ratio: 0.19124, Grade: D\",\"StationNumber: 00LTB4066, Year: 2000, PEL ratio: 0.05414, Grade: C\",\"StationNumber: 00LTB4117, Year: 2000, PEL ratio: 0.05562, Grade: C\",\"StationNumber: 00LTB4151, Year: 2000, PEL ratio: 0.03939, Grade: C\",\"StationNumber: 00LTB4185, Year: 2000, PEL ratio: 0.04507, Grade: C\",\"StationNumber: 00LTB4286, Year: 2000, PEL ratio: 0.05463, Grade: C\",\"StationNumber: 00LTB4340, Year: 2000, PEL ratio: 0.05064, Grade: C\",\"StationNumber: 00LTB4484, Year: 2000, PEL ratio: 0.0517, Grade: C\",\"StationNumber: 00LTB4487, Year: 2000, PEL ratio: 0.04958, Grade: C\",\"StationNumber: 00LTB4513, Year: 2000, PEL ratio: 0.05351, Grade: C\",\"StationNumber: 00LTB4529, Year: 2000, PEL ratio: 0.049, Grade: C\",\"StationNumber: 00LTB4536, Year: 2000, PEL ratio: 0.05145, Grade: C\",\"StationNumber: 00LTB4637, Year: 2000, PEL ratio: 0.04148, Grade: C\",\"StationNumber: 00LTB4677, Year: 2000, PEL ratio: 0.04906, Grade: C\",\"StationNumber: 00LTB4730, Year: 2000, PEL ratio: 0.04835, Grade: C\",\"StationNumber: 00LTB4749, Year: 2000, PEL ratio: 0.04495, Grade: C\",\"StationNumber: 00MR09, Year: 2000, PEL ratio: 0.04919, Grade: C\",\"StationNumber: 00MR10, Year: 2000, PEL ratio: 0.06403, Grade: C\",\"StationNumber: 00MR11, Year: 2000, PEL ratio: 0.05939, Grade: C\",\"StationNumber: 00MR12, Year: 2000, PEL ratio: 0.05823, Grade: C\",\"StationNumber: 00MR13, Year: 2000, PEL ratio: 0.06481, Grade: C\",\"StationNumber: 00MR14, Year: 2000, PEL ratio: 0.0737, Grade: C\",\"StationNumber: 00MR15, Year: 2000, PEL ratio: 0.0527, Grade: C\",\"StationNumber: 00MR16, Year: 2000, PEL ratio: 0.08249, Grade: C\",\"StationNumber: 00MR17, Year: 2000, PEL ratio: 0.08444, Grade: C\",\"StationNumber: 00MR18, Year: 2000, PEL ratio: 0.08809, Grade: D\",\"StationNumber: 00MR19, Year: 2000, PEL ratio: 0.08127, Grade: C\",\"StationNumber: 00MR20, Year: 2000, PEL ratio: 0.11393, Grade: D\",\"StationNumber: 00MR21, Year: 2000, PEL ratio: 0.07841, Grade: C\",\"StationNumber: 00MTB4030, Year: 2000, PEL ratio: 0.07289, Grade: C\",\"StationNumber: 00MTB4032, Year: 2000, PEL ratio: 0.04097, Grade: C\",\"StationNumber: 00MTB4041, Year: 2000, PEL ratio: 0.04387, Grade: C\",\"StationNumber: 00MTB4061, Year: 2000, PEL ratio: 0.05053, Grade: C\",\"StationNumber: 00MTB4072, Year: 2000, PEL ratio: 0.04819, Grade: C\",\"StationNumber: 00MTB4086, Year: 2000, PEL ratio: 0.03955, Grade: C\",\"StationNumber: 00MTB4090, Year: 2000, PEL ratio: 0.33753, Grade: F\",\"StationNumber: 00MTB4098, Year: 2000, PEL ratio: 0.0477, Grade: C\",\"StationNumber: 00MTB4100, Year: 2000, PEL ratio: 0.05472, Grade: C\",\"StationNumber: 00MTB4106, Year: 2000, PEL ratio: 0.04444, Grade: C\",\"StationNumber: 00MTB4159, Year: 2000, PEL ratio: 0.0458, Grade: C\",\"StationNumber: 00MTB4181, Year: 2000, PEL ratio: 0.05132, Grade: C\",\"StationNumber: 00MTB4193, Year: 2000, PEL ratio: 0.03968, Grade: C\",\"StationNumber: 00MTB4201, Year: 2000, PEL ratio: 0.05155, Grade: C\",\"StationNumber: 00MTB4249, Year: 2000, PEL ratio: 0.033, Grade: C\",\"StationNumber: 00MTB4265, Year: 2000, PEL ratio: 0.04253, Grade: C\",\"StationNumber: 00MTB4310, Year: 2000, PEL ratio: 0.04594, Grade: C\",\"StationNumber: 00MTB4363, Year: 2000, PEL ratio: 0.07539, Grade: C\",\"StationNumber: 00MTB4504, Year: 2000, PEL ratio: 0.04349, Grade: C\",\"StationNumber: 00MTB4584, Year: 2000, PEL ratio: 0.04498, Grade: C\",\"StationNumber: 00MTB4653, Year: 2000, PEL ratio: 0.04232, Grade: C\",\"StationNumber: 00MTB4845, Year: 2000, PEL ratio: 0.04253, Grade: C\",\"StationNumber: 00MTB5125, Year: 2000, PEL ratio: 0.03946, Grade: C\",\"StationNumber: 00OTB4011, Year: 2000, PEL ratio: 0.03964, Grade: C\",\"StationNumber: 00OTB4019, Year: 2000, PEL ratio: 0.04292, Grade: C\",\"StationNumber: 00OTB4037, Year: 2000, PEL ratio: 0.05343, Grade: C\",\"StationNumber: 00OTB4040, Year: 2000, PEL ratio: 0.04909, Grade: C\",\"StationNumber: 00OTB4044, Year: 2000, PEL ratio: 0.04244, Grade: C\",\"StationNumber: 00OTB4096, Year: 2000, PEL ratio: 0.03974, Grade: C\",\"StationNumber: 00OTB4105, Year: 2000, PEL ratio: 0.04131, Grade: C\",\"StationNumber: 00OTB4123, Year: 2000, PEL ratio: 0.06385, Grade: C\",\"StationNumber: 00OTB4132, Year: 2000, PEL ratio: 0.06645, Grade: C\",\"StationNumber: 00OTB4138, Year: 2000, PEL ratio: 0.05762, Grade: C\",\"StationNumber: 00OTB4149, Year: 2000, PEL ratio: 0.0568, Grade: C\",\"StationNumber: 00OTB4192, Year: 2000, PEL ratio: 0.03756, Grade: C\",\"StationNumber: 00OTB4217, Year: 2000, PEL ratio: 0.05579, Grade: C\",\"StationNumber: 00OTB4254, Year: 2000, PEL ratio: 0.0437, Grade: C\",\"StationNumber: 00OTB4278, Year: 2000, PEL ratio: 0.25534, Grade: D\",\"StationNumber: 00OTB4402, Year: 2000, PEL ratio: 0.0459, Grade: C\",\"StationNumber: 00OTB4407, Year: 2000, PEL ratio: 0.04964, Grade: C\",\"StationNumber: 00OTB4650, Year: 2000, PEL ratio: 0.04792, Grade: C\",\"StationNumber: 00OTB4946, Year: 2000, PEL ratio: 0.05067, Grade: C\",\"StationNumber: 00TCB01, Year: 2000, PEL ratio: 0.04699, Grade: C\",\"StationNumber: 00TCB02, Year: 2000, PEL ratio: 0.04205, Grade: C\",\"StationNumber: 00TCB03, Year: 2000, PEL ratio: 0.03651, Grade: C\",\"StationNumber: 00TCB04, Year: 2000, PEL ratio: 0.04109, Grade: C\",\"StationNumber: 00TCB05, Year: 2000, PEL ratio: 0.04353, Grade: C\",\"StationNumber: 00TCB06, Year: 2000, PEL ratio: 0.04342, Grade: C\",\"StationNumber: 00TCB07, Year: 2000, PEL ratio: 0.04274, Grade: C\",\"StationNumber: 00TCB08, Year: 2000, PEL ratio: 0.04303, Grade: C\",\"StationNumber: 01BCB57/1, Year: 2001, PEL ratio: 0.05374, Grade: C\",\"StationNumber: 01BCB58/1, Year: 2001, PEL ratio: 0.12193, Grade: D\",\"StationNumber: 01BCB58/2, Year: 2001, PEL ratio: 0.027, Grade: C\",\"StationNumber: 01BCB59/1, Year: 2001, PEL ratio: 0.02094, Grade: C\",\"StationNumber: 01BCB59/2, Year: 2001, PEL ratio: 0.04048, Grade: C\",\"StationNumber: 01BCB60/2, Year: 2001, PEL ratio: 0.01653, Grade: B\",\"StationNumber: 01BCB60/4, Year: 2001, PEL ratio: 0.01424, Grade: B\",\"StationNumber: 01BCB6001, Year: 2001, PEL ratio: 0.0563, Grade: C\",\"StationNumber: 01BCB6009, Year: 2001, PEL ratio: 0.04348, Grade: C\",\"StationNumber: 01BCB6018, Year: 2001, PEL ratio: 0.01682, Grade: B\",\"StationNumber: 01BCB6019, Year: 2001, PEL ratio: 0.01532, Grade: B\",\"StationNumber: 01BCB6031, Year: 2001, PEL ratio: 0.02161, Grade: C\",\"StationNumber: 01BCB6063, Year: 2001, PEL ratio: 0.0077, Grade: B\",\"StationNumber: 01BCB6072, Year: 2001, PEL ratio: 0.03264, Grade: C\",\"StationNumber: 01BCB6089, Year: 2001, PEL ratio: 0.02463, Grade: C\",\"StationNumber: 01BCB6109, Year: 2001, PEL ratio: 0.02845, Grade: C\",\"StationNumber: 01BCB6114, Year: 2001, PEL ratio: 0.02671, Grade: C\",\"StationNumber: 01BCB6152, Year: 2001, PEL ratio: 0.0269, Grade: C\",\"StationNumber: 01BCB6178, Year: 2001, PEL ratio: 0.02377, Grade: C\",\"StationNumber: 01BCB6190, Year: 2001, PEL ratio: 0.02239, Grade: C\",\"StationNumber: 01BCB6230, Year: 2001, PEL ratio: 0.05637, Grade: C\",\"StationNumber: 01BCB6263, Year: 2001, PEL ratio: 0.04428, Grade: C\",\"StationNumber: 01BCB6359, Year: 2001, PEL ratio: 0.04232, Grade: C\",\"StationNumber: 01HB6019, Year: 2001, PEL ratio: 0.13163, Grade: D\",\"StationNumber: 01HB6022, Year: 2001, PEL ratio: 0.07712, Grade: C\",\"StationNumber: 01HB6032, Year: 2001, PEL ratio: 0.03892, Grade: C\",\"StationNumber: 01HB6035, Year: 2001, PEL ratio: 0.06366, Grade: C\",\"StationNumber: 01HB6045, Year: 2001, PEL ratio: 0.04136, Grade: C\",\"StationNumber: 01HB6064, Year: 2001, PEL ratio: 0.08868, Grade: D\",\"StationNumber: 01HB6066, Year: 2001, PEL ratio: 0.04113, Grade: C\",\"StationNumber: 01HB6087, Year: 2001, PEL ratio: 0.07944, Grade: C\",\"StationNumber: 01HB6093, Year: 2001, PEL ratio: 0.0345, Grade: C\",\"StationNumber: 01HB6102, Year: 2001, PEL ratio: 0.04233, Grade: C\",\"StationNumber: 01HB6108, Year: 2001, PEL ratio: 0.07274, Grade: C\",\"StationNumber: 01HB6131, Year: 2001, PEL ratio: 0.03937, Grade: C\",\"StationNumber: 01HB6140, Year: 2001, PEL ratio: 0.03728, Grade: C\",\"StationNumber: 01HB6145, Year: 2001, PEL ratio: 0.03711, Grade: C\",\"StationNumber: 01HB6159, Year: 2001, PEL ratio: 0.05123, Grade: C\",\"StationNumber: 01HB6186, Year: 2001, PEL ratio: 0.11466, Grade: D\",\"StationNumber: 01HB6187, Year: 2001, PEL ratio: 0.03548, Grade: C\",\"StationNumber: 01HB6249, Year: 2001, PEL ratio: 0.02319, Grade: C\",\"StationNumber: 01HB6261, Year: 2001, PEL ratio: 0.04047, Grade: C\",\"StationNumber: 01HB6264, Year: 2001, PEL ratio: 0.03946, Grade: C\",\"StationNumber: 01HB6283, Year: 2001, PEL ratio: 0.03557, Grade: C\",\"StationNumber: 01HB6305, Year: 2001, PEL ratio: 0.0378, Grade: C\",\"StationNumber: 01HB6374, Year: 2001, PEL ratio: 0.09193, Grade: D\",\"StationNumber: 01HB6453, Year: 2001, PEL ratio: 0.05442, Grade: C\",\"StationNumber: 01HB6537, Year: 2001, PEL ratio: 0.03766, Grade: C\",\"StationNumber: 01LTB6026, Year: 2001, PEL ratio: 0.05204, Grade: C\",\"StationNumber: 01LTB6027, Year: 2001, PEL ratio: 0.03496, Grade: C\",\"StationNumber: 01LTB6050, Year: 2001, PEL ratio: 0.04404, Grade: C\",\"StationNumber: 01LTB6104, Year: 2001, PEL ratio: 0.0209, Grade: C\",\"StationNumber: 01LTB6120, Year: 2001, PEL ratio: 0.04069, Grade: C\",\"StationNumber: 01LTB6122, Year: 2001, PEL ratio: 0.05444, Grade: C\",\"StationNumber: 01LTB6158, Year: 2001, PEL ratio: 0.09951, Grade: D\",\"StationNumber: 01LTB6302, Year: 2001, PEL ratio: 0.04098, Grade: C\",\"StationNumber: 01LTB6346, Year: 2001, PEL ratio: 0.00189, Grade: A\",\"StationNumber: 01LTB6380, Year: 2001, PEL ratio: 0.04602, Grade: C\",\"StationNumber: 01LTB6595, Year: 2001, PEL ratio: 0.04587, Grade: C\",\"StationNumber: 01LTB6869, Year: 2001, PEL ratio: 0.03876, Grade: C\",\"StationNumber: 01MR09, Year: 2001, PEL ratio: 0.00085, Grade: A\",\"StationNumber: 01MR12, Year: 2001, PEL ratio: 0.00214, Grade: A\",\"StationNumber: 01MR13, Year: 2001, PEL ratio: 0.0031, Grade: A\",\"StationNumber: 01MR14, Year: 2001, PEL ratio: 0, Grade: A\",\"StationNumber: 01MR17, Year: 2001, PEL ratio: 0, Grade: A\",\"StationNumber: 01MR18, Year: 2001, PEL ratio: 0, Grade: A\",\"StationNumber: 01MR19, Year: 2001, PEL ratio: 0, Grade: A\",\"StationNumber: 01MR20, Year: 2001, PEL ratio: 0, Grade: A\",\"StationNumber: 01MR21, Year: 2001, PEL ratio: 0, Grade: A\",\"StationNumber: 01MTB6002, Year: 2001, PEL ratio: 0.04429, Grade: C\",\"StationNumber: 01MTB6011, Year: 2001, PEL ratio: 0.03017, Grade: C\",\"StationNumber: 01MTB6014, Year: 2001, PEL ratio: 0.03931, Grade: C\",\"StationNumber: 01MTB6049, Year: 2001, PEL ratio: 0.04162, Grade: C\",\"StationNumber: 01MTB6059, Year: 2001, PEL ratio: 0.03202, Grade: C\",\"StationNumber: 01MTB6064, Year: 2001, PEL ratio: 0.02866, Grade: C\",\"StationNumber: 01MTB6068, Year: 2001, PEL ratio: 0.03092, Grade: C\",\"StationNumber: 01MTB6080, Year: 2001, PEL ratio: 0.03134, Grade: C\",\"StationNumber: 01MTB6133, Year: 2001, PEL ratio: 0.03877, Grade: C\",\"StationNumber: 01MTB6154, Year: 2001, PEL ratio: 0.03081, Grade: C\",\"StationNumber: 01MTB6188, Year: 2001, PEL ratio: 0.04865, Grade: C\",\"StationNumber: 01MTB6189, Year: 2001, PEL ratio: 0.04606, Grade: C\",\"StationNumber: 01MTB6196, Year: 2001, PEL ratio: 0.03661, Grade: C\",\"StationNumber: 01MTB6229, Year: 2001, PEL ratio: 0.03253, Grade: C\",\"StationNumber: 01MTB6257, Year: 2001, PEL ratio: 0.04035, Grade: C\",\"StationNumber: 01MTB6265, Year: 2001, PEL ratio: 0.03247, Grade: C\",\"StationNumber: 01MTB6290, Year: 2001, PEL ratio: 0.03227, Grade: C\",\"StationNumber: 01MTB6325, Year: 2001, PEL ratio: 0.03135, Grade: C\",\"StationNumber: 01MTB6327, Year: 2001, PEL ratio: 0.0343, Grade: C\",\"StationNumber: 01MTB6328, Year: 2001, PEL ratio: 0.0383, Grade: C\",\"StationNumber: 01MTB6464, Year: 2001, PEL ratio: 0.03323, Grade: C\",\"StationNumber: 01MTB6495, Year: 2001, PEL ratio: 0.03374, Grade: C\",\"StationNumber: 01MTB6527, Year: 2001, PEL ratio: 0.0365, Grade: C\",\"StationNumber: 01MTB6638, Year: 2001, PEL ratio: 0.03712, Grade: C\",\"StationNumber: 01MTB6699, Year: 2001, PEL ratio: 0.03196, Grade: C\",\"StationNumber: 01MTB7153, Year: 2001, PEL ratio: 0.02961, Grade: C\",\"StationNumber: 01OTB6010, Year: 2001, PEL ratio: 0.0366, Grade: C\",\"StationNumber: 01OTB6017, Year: 2001, PEL ratio: 0.0392, Grade: C\",\"StationNumber: 01OTB6021, Year: 2001, PEL ratio: 0.035, Grade: C\",\"StationNumber: 01OTB6022, Year: 2001, PEL ratio: 0.03556, Grade: C\",\"StationNumber: 01OTB6025, Year: 2001, PEL ratio: 0.0835, Grade: C\",\"StationNumber: 01OTB6028, Year: 2001, PEL ratio: 0.04087, Grade: C\",\"StationNumber: 01OTB6078, Year: 2001, PEL ratio: 0.03835, Grade: C\",\"StationNumber: 01OTB6103, Year: 2001, PEL ratio: 0.04375, Grade: C\",\"StationNumber: 01OTB6135, Year: 2001, PEL ratio: 0.1479, Grade: D\",\"StationNumber: 01OTB6152, Year: 2001, PEL ratio: 0.17372, Grade: D\",\"StationNumber: 01OTB6178, Year: 2001, PEL ratio: 0.04426, Grade: C\",\"StationNumber: 01OTB6186, Year: 2001, PEL ratio: 0.03888, Grade: C\",\"StationNumber: 01OTB6234, Year: 2001, PEL ratio: 0.03095, Grade: C\",\"StationNumber: 01OTB6239, Year: 2001, PEL ratio: 0.07735, Grade: C\",\"StationNumber: 01OTB6441, Year: 2001, PEL ratio: 0.03373, Grade: C\",\"StationNumber: 01OTB6784, Year: 2001, PEL ratio: 0.03879, Grade: C\",\"StationNumber: 01OTB6830, Year: 2001, PEL ratio: 0.03885, Grade: C\",\"StationNumber: 01SAFHAB, Year: 2001, PEL ratio: 0.05562, Grade: C\",\"StationNumber: 01TCB02, Year: 2001, PEL ratio: 0, Grade: A\",\"StationNumber: 01TCB03, Year: 2001, PEL ratio: 0, Grade: A\",\"StationNumber: 01TCB04, Year: 2001, PEL ratio: 0.00149, Grade: A\",\"StationNumber: 01TCB06, Year: 2001, PEL ratio: 0, Grade: A\",\"StationNumber: 01TCB07, Year: 2001, PEL ratio: 0, Grade: A\",\"StationNumber: 02BCB05, Year: 2002, PEL ratio: 0.09921, Grade: D\",\"StationNumber: 02BCB20, Year: 2002, PEL ratio: 0.03895, Grade: C\",\"StationNumber: 02BCB32, Year: 2002, PEL ratio: 0.02428, Grade: C\",\"StationNumber: 02BCB52, Year: 2002, PEL ratio: 0.03041, Grade: C\",\"StationNumber: 02BCB62, Year: 2002, PEL ratio: 0.07542, Grade: C\",\"StationNumber: 02BCB69, Year: 2002, PEL ratio: 0.02783, Grade: C\",\"StationNumber: 02BCB74, Year: 2002, PEL ratio: 0.02301, Grade: C\",\"StationNumber: 02BCB83, Year: 2002, PEL ratio: 0.02746, Grade: C\",\"StationNumber: 02BCB90, Year: 2002, PEL ratio: 0.02852, Grade: C\",\"StationNumber: 02DH09-1, Year: 2002, PEL ratio: 0.19807, Grade: D\",\"StationNumber: 02DH09-2, Year: 2002, PEL ratio: 0.12272, Grade: D\",\"StationNumber: 02DH09-3, Year: 2002, PEL ratio: 0.30626, Grade: F\",\"StationNumber: 02DH11A-1, Year: 2002, PEL ratio: 0.10175, Grade: D\",\"StationNumber: 02DH11A-2, Year: 2002, PEL ratio: 0.11172, Grade: D\",\"StationNumber: 02DH11A-3, Year: 2002, PEL ratio: 0.14465, Grade: D\",\"StationNumber: 02DH11B-1, Year: 2002, PEL ratio: 0.10113, Grade: D\",\"StationNumber: 02DH11B-4, Year: 2002, PEL ratio: 0.12537, Grade: D\",\"StationNumber: 02DH11B-5, Year: 2002, PEL ratio: 0.13789, Grade: D\",\"StationNumber: 02HB09, Year: 2002, PEL ratio: 0.16733, Grade: D\",\"StationNumber: 02HB20, Year: 2002, PEL ratio: 0.02678, Grade: C\",\"StationNumber: 02HB21, Year: 2002, PEL ratio: 0.02244, Grade: C\",\"StationNumber: 02HB27, Year: 2002, PEL ratio: 0.03078, Grade: C\",\"StationNumber: 02HB39, Year: 2002, PEL ratio: 0.21706, Grade: D\",\"StationNumber: 02HB42, Year: 2002, PEL ratio: 0.02683, Grade: C\",\"StationNumber: 02HB49, Year: 2002, PEL ratio: 0.03845, Grade: C\",\"StationNumber: 02HB50, Year: 2002, PEL ratio: 0.32514, Grade: F\",\"StationNumber: 02HB51, Year: 2002, PEL ratio: 0.06603, Grade: C\",\"StationNumber: 02HB55, Year: 2002, PEL ratio: 0.05778, Grade: C\",\"StationNumber: 02LTB01, Year: 2002, PEL ratio: 0.02663, Grade: C\",\"StationNumber: 02LTB02, Year: 2002, PEL ratio: 0.02978, Grade: C\",\"StationNumber: 02LTB03, Year: 2002, PEL ratio: 0.02042, Grade: B\",\"StationNumber: 02LTB04, Year: 2002, PEL ratio: 0.02782, Grade: C\",\"StationNumber: 02LTB05, Year: 2002, PEL ratio: 0.02348, Grade: C\",\"StationNumber: 02LTB06, Year: 2002, PEL ratio: 0.04038, Grade: C\",\"StationNumber: 02LTB07, Year: 2002, PEL ratio: 0.03048, Grade: C\",\"StationNumber: 02LTB08, Year: 2002, PEL ratio: 0.02061, Grade: C\",\"StationNumber: 02LTB09, Year: 2002, PEL ratio: 0.02023, Grade: B\",\"StationNumber: 02MR02, Year: 2002, PEL ratio: 0.03322, Grade: C\",\"StationNumber: 02MR04, Year: 2002, PEL ratio: 0.03337, Grade: C\",\"StationNumber: 02MR06, Year: 2002, PEL ratio: 0.14519, Grade: D\",\"StationNumber: 02MR08, Year: 2002, PEL ratio: 0.02507, Grade: C\",\"StationNumber: 02MR10, Year: 2002, PEL ratio: 0.04251, Grade: C\",\"StationNumber: 02MR11, Year: 2002, PEL ratio: 0.03906, Grade: C\",\"StationNumber: 02MR12, Year: 2002, PEL ratio: 0.03873, Grade: C\",\"StationNumber: 02DH08-1, Year: 2002, PEL ratio: 0.09017, Grade: D\",\"StationNumber: 02DH08-2, Year: 2002, PEL ratio: 0.10363, Grade: D\",\"StationNumber: 02DH08-3, Year: 2002, PEL ratio: 0.08051, Grade: C\",\"StationNumber: 02DH14-1, Year: 2002, PEL ratio: 0.18895, Grade: D\",\"StationNumber: 02DH14-3, Year: 2002, PEL ratio: 0.12398, Grade: D\",\"StationNumber: 02DH14-4, Year: 2002, PEL ratio: 0.13475, Grade: D\",\"StationNumber: 02DH15-1, Year: 2002, PEL ratio: 0.03722, Grade: C\",\"StationNumber: 02DH15-2, Year: 2002, PEL ratio: 0.03193, Grade: C\",\"StationNumber: 02DH15-5, Year: 2002, PEL ratio: 0.10865, Grade: D\",\"StationNumber: 02MTB11, Year: 2002, PEL ratio: 0.03207, Grade: C\",\"StationNumber: 02MTB12, Year: 2002, PEL ratio: 0.03458, Grade: C\",\"StationNumber: 02MTB18, Year: 2002, PEL ratio: 0.06402, Grade: C\",\"StationNumber: 02MTB19, Year: 2002, PEL ratio: 0.02845, Grade: C\",\"StationNumber: 02MTB21, Year: 2002, PEL ratio: 0.07645, Grade: C\",\"StationNumber: 02MTB23, Year: 2002, PEL ratio: 0.04157, Grade: C\",\"StationNumber: 02MTB27, Year: 2002, PEL ratio: 0.03517, Grade: C\",\"StationNumber: 02MTB29, Year: 2002, PEL ratio: 0.03409, Grade: C\",\"StationNumber: 02MTB32, Year: 2002, PEL ratio: 0.03217, Grade: C\",\"StationNumber: 02MTB34, Year: 2002, PEL ratio: 0.0336, Grade: C\",\"StationNumber: 02DH03-2, Year: 2002, PEL ratio: 0.15, Grade: D\",\"StationNumber: 02DH03-4, Year: 2002, PEL ratio: 0.15355, Grade: D\",\"StationNumber: 02DH03-5, Year: 2002, PEL ratio: 0.18194, Grade: D\",\"StationNumber: 02DH05-3, Year: 2002, PEL ratio: 0.02701, Grade: C\",\"StationNumber: 02DH05-4, Year: 2002, PEL ratio: 0.08347, Grade: C\",\"StationNumber: 02DH05-5, Year: 2002, PEL ratio: 0.03648, Grade: C\",\"StationNumber: 02DH07-1, Year: 2002, PEL ratio: 0.08738, Grade: D\",\"StationNumber: 02DH07-2, Year: 2002, PEL ratio: 0.09842, Grade: D\",\"StationNumber: 02DH07-3, Year: 2002, PEL ratio: 0.09265, Grade: D\",\"StationNumber: 02DH18-1, Year: 2002, PEL ratio: 0.03811, Grade: C\",\"StationNumber: 02DH18-2, Year: 2002, PEL ratio: 0.04678, Grade: C\",\"StationNumber: 02DH18-3, Year: 2002, PEL ratio: 0.0332, Grade: C\",\"StationNumber: 02DH20-3, Year: 2002, PEL ratio: 0.09118, Grade: D\",\"StationNumber: 02DH20-4, Year: 2002, PEL ratio: 0.0982, Grade: D\",\"StationNumber: 02DH20-5, Year: 2002, PEL ratio: 0.08451, Grade: C\",\"StationNumber: 02DH21A-1, Year: 2002, PEL ratio: 0.08952, Grade: D\",\"StationNumber: 02DH21A-3, Year: 2002, PEL ratio: 0.10866, Grade: D\",\"StationNumber: 02DH21A-5, Year: 2002, PEL ratio: 0.11684, Grade: D\",\"StationNumber: 02DH21B-1, Year: 2002, PEL ratio: 0.13203, Grade: D\",\"StationNumber: 02DH21B-3, Year: 2002, PEL ratio: 0.12143, Grade: D\",\"StationNumber: 02DH21B-4, Year: 2002, PEL ratio: 0.1119, Grade: D\",\"StationNumber: 02OTB02, Year: 2002, PEL ratio: 0.02894, Grade: C\",\"StationNumber: 02OTB04, Year: 2002, PEL ratio: 0.03118, Grade: C\",\"StationNumber: 02OTB27, Year: 2002, PEL ratio: 0.02515, Grade: C\",\"StationNumber: 02OTB49, Year: 2002, PEL ratio: 0.0374, Grade: C\",\"StationNumber: 02OTB50, Year: 2002, PEL ratio: 0.04422, Grade: C\",\"StationNumber: 02OTB52, Year: 2002, PEL ratio: 0.03468, Grade: C\",\"StationNumber: 02OTB60, Year: 2002, PEL ratio: 0.0399, Grade: C\",\"StationNumber: 02OTB66, Year: 2002, PEL ratio: 0.04346, Grade: C\",\"StationNumber: 02TCB03, Year: 2002, PEL ratio: 0.02956, Grade: C\",\"StationNumber: 02TCB05, Year: 2002, PEL ratio: 0.05723, Grade: C\",\"StationNumber: 02TCB07, Year: 2002, PEL ratio: 0.04305, Grade: C\",\"StationNumber: 02TCB09, Year: 2002, PEL ratio: 0.041, Grade: C\",\"StationNumber: 03BCB107, Year: 2003, PEL ratio: 0.04845, Grade: C\",\"StationNumber: 03BCB120, Year: 2003, PEL ratio: 0.07755, Grade: C\",\"StationNumber: 03BCB126, Year: 2003, PEL ratio: 0.05955, Grade: C\",\"StationNumber: 03BCB190, Year: 2003, PEL ratio: 0.07526, Grade: C\",\"StationNumber: 03BCB230, Year: 2003, PEL ratio: 0.04192, Grade: C\",\"StationNumber: 03BCB242, Year: 2003, PEL ratio: 0.1701, Grade: D\",\"StationNumber: 03BCB278, Year: 2003, PEL ratio: 0.04954, Grade: C\",\"StationNumber: 03BCB287, Year: 2003, PEL ratio: 0.0426, Grade: C\",\"StationNumber: 03BCB338, Year: 2003, PEL ratio: 0.05523, Grade: C\",\"StationNumber: 03BCB439, Year: 2003, PEL ratio: 0.05588, Grade: C\",\"StationNumber: 03HB01, Year: 2003, PEL ratio: 0.05953, Grade: C\",\"StationNumber: 03HB02, Year: 2003, PEL ratio: 0.09513, Grade: D\",\"StationNumber: 03HB04, Year: 2003, PEL ratio: 0.05264, Grade: C\",\"StationNumber: 03HB06, Year: 2003, PEL ratio: 0.2787, Grade: D\",\"StationNumber: 03HB09, Year: 2003, PEL ratio: 2.62709, Grade: F\",\"StationNumber: 03HB10, Year: 2003, PEL ratio: 0.07527, Grade: C\",\"StationNumber: 03HB11, Year: 2003, PEL ratio: 0.05917, Grade: C\",\"StationNumber: 03HB12, Year: 2003, PEL ratio: 0.08962, Grade: D\",\"StationNumber: 03HB14, Year: 2003, PEL ratio: 0.05233, Grade: C\",\"StationNumber: 03HB16, Year: 2003, PEL ratio: 0.08913, Grade: D\",\"StationNumber: 03HB18, Year: 2003, PEL ratio: 0.07056, Grade: C\",\"StationNumber: 03HB21, Year: 2003, PEL ratio: 0.02956, Grade: C\",\"StationNumber: 03HB27, Year: 2003, PEL ratio: 0.11208, Grade: D\",\"StationNumber: 03HB28, Year: 2003, PEL ratio: 0.13538, Grade: D\",\"StationNumber: 03HB30, Year: 2003, PEL ratio: 0.05101, Grade: C\",\"StationNumber: 03HB32, Year: 2003, PEL ratio: 0.08584, Grade: D\",\"StationNumber: 03HB33, Year: 2003, PEL ratio: 0.04992, Grade: C\",\"StationNumber: 03HB34, Year: 2003, PEL ratio: 0.05096, Grade: C\",\"StationNumber: 03HB37, Year: 2003, PEL ratio: 0.17023, Grade: D\",\"StationNumber: 03HB38, Year: 2003, PEL ratio: 0.04877, Grade: C\",\"StationNumber: 03HB41, Year: 2003, PEL ratio: 0.07016, Grade: C\",\"StationNumber: 03HB42, Year: 2003, PEL ratio: 0.11971, Grade: D\",\"StationNumber: 03HB44, Year: 2003, PEL ratio: 0.04723, Grade: C\",\"StationNumber: 03HB47, Year: 2003, PEL ratio: 0.0484, Grade: C\",\"StationNumber: 03HB50, Year: 2003, PEL ratio: 0.04892, Grade: C\",\"StationNumber: 03HB51, Year: 2003, PEL ratio: 0.07784, Grade: C\",\"StationNumber: 03HB52, Year: 2003, PEL ratio: 0.10156, Grade: D\",\"StationNumber: 03HB53, Year: 2003, PEL ratio: 0.04264, Grade: C\",\"StationNumber: 03LTB01, Year: 2003, PEL ratio: 0.0462, Grade: C\",\"StationNumber: 03LTB02, Year: 2003, PEL ratio: 0.0405, Grade: C\",\"StationNumber: 03LTB03, Year: 2003, PEL ratio: 0.04888, Grade: C\",\"StationNumber: 03LTB04, Year: 2003, PEL ratio: 0.05672, Grade: C\",\"StationNumber: 03LTB05, Year: 2003, PEL ratio: 0.03249, Grade: C\",\"StationNumber: 03LTB06, Year: 2003, PEL ratio: 0.04582, Grade: C\",\"StationNumber: 03LTB07, Year: 2003, PEL ratio: 0.05602, Grade: C\",\"StationNumber: 03LTB08, Year: 2003, PEL ratio: 0.02753, Grade: C\",\"StationNumber: 03LTB09, Year: 2003, PEL ratio: 0.04842, Grade: C\",\"StationNumber: 03LTB10, Year: 2003, PEL ratio: 0.03141, Grade: C\",\"StationNumber: 03LTB11, Year: 2003, PEL ratio: 0.05041, Grade: C\",\"StationNumber: 03LTB12, Year: 2003, PEL ratio: 0.04109, Grade: C\",\"StationNumber: 03MR02, Year: 2003, PEL ratio: 0.07551, Grade: C\",\"StationNumber: 03MR04, Year: 2003, PEL ratio: 0.06186, Grade: C\",\"StationNumber: 03MR06, Year: 2003, PEL ratio: 0.11177, Grade: D\",\"StationNumber: 03MR07, Year: 2003, PEL ratio: 0.04271, Grade: C\",\"StationNumber: 03MR08, Year: 2003, PEL ratio: 0.04877, Grade: C\",\"StationNumber: 03MR09, Year: 2003, PEL ratio: 0.04126, Grade: C\",\"StationNumber: 03MR10, Year: 2003, PEL ratio: 0.05761, Grade: C\",\"StationNumber: 03MTB03, Year: 2003, PEL ratio: 0.05627, Grade: C\",\"StationNumber: 03MTB08, Year: 2003, PEL ratio: 0.06744, Grade: C\",\"StationNumber: 03MTB10, Year: 2003, PEL ratio: 0.04607, Grade: C\",\"StationNumber: 03MTB11, Year: 2003, PEL ratio: 0.0679, Grade: C\",\"StationNumber: 03MTB13, Year: 2003, PEL ratio: 0.08571, Grade: D\",\"StationNumber: 03MTB14, Year: 2003, PEL ratio: 0.07424, Grade: C\",\"StationNumber: 03MTB15, Year: 2003, PEL ratio: 0.07661, Grade: C\",\"StationNumber: 03MTB16, Year: 2003, PEL ratio: 0.07141, Grade: C\",\"StationNumber: 03MTB17, Year: 2003, PEL ratio: 0.04297, Grade: C\",\"StationNumber: 03MTB18, Year: 2003, PEL ratio: 0.06047, Grade: C\",\"StationNumber: 03MTB19, Year: 2003, PEL ratio: 0.0635, Grade: C\",\"StationNumber: 03MTB21, Year: 2003, PEL ratio: 0.06752, Grade: C\",\"StationNumber: 03MTB24, Year: 2003, PEL ratio: 0.05516, Grade: C\",\"StationNumber: 03MTB25, Year: 2003, PEL ratio: 0.06373, Grade: C\",\"StationNumber: 03MTB27, Year: 2003, PEL ratio: 0.05651, Grade: C\",\"StationNumber: 03MTB28, Year: 2003, PEL ratio: 0.06933, Grade: C\",\"StationNumber: 03MTB30, Year: 2003, PEL ratio: 0.43636, Grade: F\",\"StationNumber: 03MTB31, Year: 2003, PEL ratio: 0.07005, Grade: C\",\"StationNumber: 03MTB32, Year: 2003, PEL ratio: 0.05667, Grade: C\",\"StationNumber: 03MTB33, Year: 2003, PEL ratio: 0.07011, Grade: C\",\"StationNumber: 03MTB34, Year: 2003, PEL ratio: 0.06682, Grade: C\",\"StationNumber: 03MTB35, Year: 2003, PEL ratio: 0.07621, Grade: C\",\"StationNumber: 03OTB157, Year: 2003, PEL ratio: 0.05915, Grade: C\",\"StationNumber: 03OTB200, Year: 2003, PEL ratio: 0.16694, Grade: D\",\"StationNumber: 03OTB413, Year: 2003, PEL ratio: 0.05894, Grade: C\",\"StationNumber: 03OTB414, Year: 2003, PEL ratio: 0.04976, Grade: C\",\"StationNumber: 03OTB507, Year: 2003, PEL ratio: 0.07151, Grade: C\",\"StationNumber: 03OTB623, Year: 2003, PEL ratio: 0.19749, Grade: D\",\"StationNumber: 03OTB706, Year: 2003, PEL ratio: 0.11944, Grade: D\",\"StationNumber: 03OTB794, Year: 2003, PEL ratio: 0.05991, Grade: C\",\"StationNumber: 03OTB929, Year: 2003, PEL ratio: 0.09521, Grade: D\",\"StationNumber: 03TCB01, Year: 2003, PEL ratio: 0.03963, Grade: C\",\"StationNumber: 03TCB03, Year: 2003, PEL ratio: 0.04315, Grade: C\",\"StationNumber: 03TCB05, Year: 2003, PEL ratio: 0.04569, Grade: C\",\"StationNumber: 04BCB01, Year: 2004, PEL ratio: 0.03545, Grade: C\",\"StationNumber: 04BCB02, Year: 2004, PEL ratio: 0.03051, Grade: C\",\"StationNumber: 04BCB03, Year: 2004, PEL ratio: 0.1299, Grade: D\",\"StationNumber: 04BCB04, Year: 2004, PEL ratio: 0.04849, Grade: C\",\"StationNumber: 04BCB05, Year: 2004, PEL ratio: 0.02806, Grade: C\",\"StationNumber: 04BCB06, Year: 2004, PEL ratio: 0.05131, Grade: C\",\"StationNumber: 04BCB07, Year: 2004, PEL ratio: 0.02049, Grade: B\",\"StationNumber: 04BCB08, Year: 2004, PEL ratio: 0.03435, Grade: C\",\"StationNumber: 04BCB09, Year: 2004, PEL ratio: 0.0386, Grade: C\",\"StationNumber: 04BCB10, Year: 2004, PEL ratio: 0.03223, Grade: C\",\"StationNumber: 04HB01, Year: 2004, PEL ratio: 0.01651, Grade: B\",\"StationNumber: 04HB02, Year: 2004, PEL ratio: 0.0358, Grade: C\",\"StationNumber: 04HB03, Year: 2004, PEL ratio: 0.12867, Grade: D\",\"StationNumber: 04HB04, Year: 2004, PEL ratio: 0.08639, Grade: D\",\"StationNumber: 04HB05, Year: 2004, PEL ratio: 0.02012, Grade: B\",\"StationNumber: 04HB06, Year: 2004, PEL ratio: 0.02029, Grade: B\",\"StationNumber: 04HB07, Year: 2004, PEL ratio: 0.02572, Grade: C\",\"StationNumber: 04HB08, Year: 2004, PEL ratio: 0.02404, Grade: C\",\"StationNumber: 04HB09, Year: 2004, PEL ratio: 0.04005, Grade: C\",\"StationNumber: 04HB10, Year: 2004, PEL ratio: 0.18388, Grade: D\",\"StationNumber: 04HB11, Year: 2004, PEL ratio: 0.02011, Grade: B\",\"StationNumber: 04HB12, Year: 2004, PEL ratio: 0.11403, Grade: D\",\"StationNumber: 04HB13, Year: 2004, PEL ratio: 0.14349, Grade: D\",\"StationNumber: 04HB14, Year: 2004, PEL ratio: 0.02109, Grade: C\",\"StationNumber: 04HB15, Year: 2004, PEL ratio: 0.02016, Grade: B\",\"StationNumber: 04HB16, Year: 2004, PEL ratio: 0.01749, Grade: B\",\"StationNumber: 04HB17, Year: 2004, PEL ratio: 0.18354, Grade: D\",\"StationNumber: 04HB18, Year: 2004, PEL ratio: 0.4013, Grade: F\",\"StationNumber: 04HB19, Year: 2004, PEL ratio: 0.12724, Grade: D\",\"StationNumber: 04HB20, Year: 2004, PEL ratio: 0.02398, Grade: C\",\"StationNumber: 04HB21, Year: 2004, PEL ratio: 0.02873, Grade: C\",\"StationNumber: 04HB23, Year: 2004, PEL ratio: 0.02633, Grade: C\",\"StationNumber: 04HB24, Year: 2004, PEL ratio: 0.02717, Grade: C\",\"StationNumber: 04HB25, Year: 2004, PEL ratio: 0.05102, Grade: C\",\"StationNumber: 04HB26, Year: 2004, PEL ratio: 0.14601, Grade: D\",\"StationNumber: 04LTB01, Year: 2004, PEL ratio: 0.01329, Grade: B\",\"StationNumber: 04LTB02, Year: 2004, PEL ratio: 0.02081, Grade: C\",\"StationNumber: 04LTB03, Year: 2004, PEL ratio: 0.02025, Grade: B\",\"StationNumber: 04LTB04, Year: 2004, PEL ratio: 0.01177, Grade: B\",\"StationNumber: 04LTB05, Year: 2004, PEL ratio: 0.0211, Grade: C\",\"StationNumber: 04LTB06, Year: 2004, PEL ratio: 0.01694, Grade: B\",\"StationNumber: 04LTB07, Year: 2004, PEL ratio: 0.01745, Grade: B\",\"StationNumber: 04LTB08, Year: 2004, PEL ratio: 0.03084, Grade: C\",\"StationNumber: 04LTB09, Year: 2004, PEL ratio: 0.02538, Grade: C\",\"StationNumber: 04LTB10, Year: 2004, PEL ratio: 0.02293, Grade: C\",\"StationNumber: 04LTB11, Year: 2004, PEL ratio: 0.03789, Grade: C\",\"StationNumber: 04MR01, Year: 2004, PEL ratio: 0.08777, Grade: D\",\"StationNumber: 04MR02, Year: 2004, PEL ratio: 0.02688, Grade: C\",\"StationNumber: 04MR03, Year: 2004, PEL ratio: 0.01966, Grade: B\",\"StationNumber: 04MR04, Year: 2004, PEL ratio: 0.04362, Grade: C\",\"StationNumber: 04MR05, Year: 2004, PEL ratio: 0.03869, Grade: C\",\"StationNumber: 04MR06, Year: 2004, PEL ratio: 0.01585, Grade: B\",\"StationNumber: 04MR08, Year: 2004, PEL ratio: 0.06183, Grade: C\",\"StationNumber: 04MR09, Year: 2004, PEL ratio: 0.03834, Grade: C\",\"StationNumber: 04MR10, Year: 2004, PEL ratio: 0.02989, Grade: C\",\"StationNumber: 04MR11, Year: 2004, PEL ratio: 0.04141, Grade: C\",\"StationNumber: 04MTB01, Year: 2004, PEL ratio: 0.0143, Grade: B\",\"StationNumber: 04MTB02, Year: 2004, PEL ratio: 0.0336, Grade: C\",\"StationNumber: 04MTB04, Year: 2004, PEL ratio: 0.02691, Grade: C\",\"StationNumber: 04MTB05, Year: 2004, PEL ratio: 0.02789, Grade: C\",\"StationNumber: 04MTB06, Year: 2004, PEL ratio: 0.01916, Grade: B\",\"StationNumber: 04MTB07, Year: 2004, PEL ratio: 0.01837, Grade: B\",\"StationNumber: 04MTB08, Year: 2004, PEL ratio: 0.02226, Grade: C\",\"StationNumber: 04MTB09, Year: 2004, PEL ratio: 0.0162, Grade: B\",\"StationNumber: 04MTB10, Year: 2004, PEL ratio: 0.02033, Grade: B\",\"StationNumber: 04MTB11, Year: 2004, PEL ratio: 0.02662, Grade: C\",\"StationNumber: 04MTB12, Year: 2004, PEL ratio: 0.0287, Grade: C\",\"StationNumber: 04MTB13, Year: 2004, PEL ratio: 0.03236, Grade: C\",\"StationNumber: 04MTB14, Year: 2004, PEL ratio: 0.03029, Grade: C\",\"StationNumber: 04MTB15, Year: 2004, PEL ratio: 0.01749, Grade: B\",\"StationNumber: 04MTB16, Year: 2004, PEL ratio: 0.01835, Grade: B\",\"StationNumber: 04MTB17, Year: 2004, PEL ratio: 0.02028, Grade: B\",\"StationNumber: 04MTB18, Year: 2004, PEL ratio: 0.01928, Grade: B\",\"StationNumber: 04MTB19, Year: 2004, PEL ratio: 0.03315, Grade: C\",\"StationNumber: 04MTB20, Year: 2004, PEL ratio: 0.02831, Grade: C\",\"StationNumber: 04MTB21, Year: 2004, PEL ratio: 0.03321, Grade: C\",\"StationNumber: 04MTB22, Year: 2004, PEL ratio: 0.02665, Grade: C\",\"StationNumber: 04MTB24, Year: 2004, PEL ratio: 0.0288, Grade: C\",\"StationNumber: 04OTB01, Year: 2004, PEL ratio: 0.02555, Grade: C\",\"StationNumber: 04OTB02, Year: 2004, PEL ratio: 0.02935, Grade: C\",\"StationNumber: 04OTB03, Year: 2004, PEL ratio: 0.03106, Grade: C\",\"StationNumber: 04OTB04, Year: 2004, PEL ratio: 0.02777, Grade: C\",\"StationNumber: 04OTB05, Year: 2004, PEL ratio: 0.12197, Grade: D\",\"StationNumber: 04OTB06, Year: 2004, PEL ratio: 0.02194, Grade: C\",\"StationNumber: 04OTB07, Year: 2004, PEL ratio: 0.10091, Grade: D\",\"StationNumber: 04OTB08, Year: 2004, PEL ratio: 0.0248, Grade: C\",\"StationNumber: 04OTB09, Year: 2004, PEL ratio: 0.0243, Grade: C\",\"StationNumber: 04TCB07, Year: 2004, PEL ratio: 0.03924, Grade: C\",\"StationNumber: 05BCB01, Year: 2005, PEL ratio: 0.02056, Grade: C\",\"StationNumber: 05BCB02, Year: 2005, PEL ratio: 0.01422, Grade: B\",\"StationNumber: 05BCB03, Year: 2005, PEL ratio: 0.0279, Grade: C\",\"StationNumber: 05BCB04, Year: 2005, PEL ratio: 0.01565, Grade: B\",\"StationNumber: 05BCB05, Year: 2005, PEL ratio: 0.94385, Grade: F\",\"StationNumber: 05BCB06, Year: 2005, PEL ratio: 0.03608, Grade: C\",\"StationNumber: 05BCB07, Year: 2005, PEL ratio: 0.01302, Grade: B\",\"StationNumber: 05BCB08, Year: 2005, PEL ratio: 0.0183, Grade: B\",\"StationNumber: 05BCB09, Year: 2005, PEL ratio: 0.02383, Grade: C\",\"StationNumber: 05BCB10, Year: 2005, PEL ratio: 0.01397, Grade: B\",\"StationNumber: 05HB01, Year: 2005, PEL ratio: 0.02071, Grade: C\",\"StationNumber: 05HB02, Year: 2005, PEL ratio: 0.01836, Grade: B\",\"StationNumber: 05HB03, Year: 2005, PEL ratio: 0.01997, Grade: B\",\"StationNumber: 05HB04, Year: 2005, PEL ratio: 0.0672, Grade: C\",\"StationNumber: 05HB05, Year: 2005, PEL ratio: 0.10587, Grade: D\",\"StationNumber: 05HB06, Year: 2005, PEL ratio: 0.07366, Grade: C\",\"StationNumber: 05HB07, Year: 2005, PEL ratio: 0.01737, Grade: B\",\"StationNumber: 05HB08, Year: 2005, PEL ratio: 0.01899, Grade: B\",\"StationNumber: 05HB09, Year: 2005, PEL ratio: 0.03392, Grade: C\",\"StationNumber: 05HB10, Year: 2005, PEL ratio: 0.03834, Grade: C\",\"StationNumber: 05HB11, Year: 2005, PEL ratio: 0.01724, Grade: B\",\"StationNumber: 05HB12, Year: 2005, PEL ratio: 1.00876, Grade: F\",\"StationNumber: 05HB13, Year: 2005, PEL ratio: 0.03924, Grade: C\",\"StationNumber: 05HB14, Year: 2005, PEL ratio: 0.15213, Grade: D\",\"StationNumber: 05HB15, Year: 2005, PEL ratio: 0.07682, Grade: C\",\"StationNumber: 05HB16, Year: 2005, PEL ratio: 0.11966, Grade: D\",\"StationNumber: 05HB17, Year: 2005, PEL ratio: 0.28594, Grade: F\",\"StationNumber: 05HB18, Year: 2005, PEL ratio: 0.02303, Grade: C\",\"StationNumber: 05HB19, Year: 2005, PEL ratio: 0.01643, Grade: B\",\"StationNumber: 05HB20, Year: 2005, PEL ratio: 0.01686, Grade: B\",\"StationNumber: 05HB21, Year: 2005, PEL ratio: 0.0478, Grade: C\",\"StationNumber: 05HB22, Year: 2005, PEL ratio: 0.04996, Grade: C\",\"StationNumber: 05HB23, Year: 2005, PEL ratio: 0.02946, Grade: C\",\"StationNumber: 05HB24, Year: 2005, PEL ratio: 0.01751, Grade: B\",\"StationNumber: 05LTB01, Year: 2005, PEL ratio: 0.02599, Grade: C\",\"StationNumber: 05LTB02, Year: 2005, PEL ratio: 0.01545, Grade: B\",\"StationNumber: 05LTB03, Year: 2005, PEL ratio: 0.01154, Grade: B\",\"StationNumber: 05LTB04, Year: 2005, PEL ratio: 0.03654, Grade: C\",\"StationNumber: 05LTB05, Year: 2005, PEL ratio: 0.01619, Grade: B\",\"StationNumber: 05LTB06, Year: 2005, PEL ratio: 0.0193, Grade: B\",\"StationNumber: 05LTB07, Year: 2005, PEL ratio: 0.01402, Grade: B\",\"StationNumber: 05LTB08, Year: 2005, PEL ratio: 0.0167, Grade: B\",\"StationNumber: 05LTB09, Year: 2005, PEL ratio: 0.02347, Grade: C\",\"StationNumber: 05LTB10, Year: 2005, PEL ratio: 0.01211, Grade: B\",\"StationNumber: 05LTB11, Year: 2005, PEL ratio: 0.01356, Grade: B\",\"StationNumber: 05MR02, Year: 2005, PEL ratio: 0.01442, Grade: B\",\"StationNumber: 05MR04, Year: 2005, PEL ratio: 0.02173, Grade: C\",\"StationNumber: 05MR06, Year: 2005, PEL ratio: 0.01537, Grade: B\",\"StationNumber: 05MR08, Year: 2005, PEL ratio: 0.01574, Grade: B\",\"StationNumber: 05MR09, Year: 2005, PEL ratio: 0.01971, Grade: B\",\"StationNumber: 05MR11, Year: 2005, PEL ratio: 0.08271, Grade: C\",\"StationNumber: 05MTB01, Year: 2005, PEL ratio: 0.02214, Grade: C\",\"StationNumber: 05MTB02, Year: 2005, PEL ratio: 0.0218, Grade: C\",\"StationNumber: 05MTB03, Year: 2005, PEL ratio: 0.01836, Grade: B\",\"StationNumber: 05MTB04, Year: 2005, PEL ratio: 0.01475, Grade: B\",\"StationNumber: 05MTB05, Year: 2005, PEL ratio: 0.01741, Grade: B\",\"StationNumber: 05MTB06, Year: 2005, PEL ratio: 0.01714, Grade: B\",\"StationNumber: 05MTB07, Year: 2005, PEL ratio: 0.03643, Grade: C\",\"StationNumber: 05MTB08, Year: 2005, PEL ratio: 0.02875, Grade: C\",\"StationNumber: 05MTB09, Year: 2005, PEL ratio: 0.01427, Grade: B\",\"StationNumber: 05MTB10, Year: 2005, PEL ratio: 0.01804, Grade: B\",\"StationNumber: 05MTB11, Year: 2005, PEL ratio: 0.01786, Grade: B\",\"StationNumber: 05MTB12, Year: 2005, PEL ratio: 0.01943, Grade: B\",\"StationNumber: 05MTB13, Year: 2005, PEL ratio: 0.01404, Grade: B\",\"StationNumber: 05MTB14, Year: 2005, PEL ratio: 0.02263, Grade: C\",\"StationNumber: 05MTB15, Year: 2005, PEL ratio: 0.10298, Grade: D\",\"StationNumber: 05MTB16, Year: 2005, PEL ratio: 0.01322, Grade: B\",\"StationNumber: 05MTB17, Year: 2005, PEL ratio: 0.01324, Grade: B\",\"StationNumber: 05MTB18, Year: 2005, PEL ratio: 0.01423, Grade: B\",\"StationNumber: 05MTB19, Year: 2005, PEL ratio: 0.01217, Grade: B\",\"StationNumber: 05MTB20, Year: 2005, PEL ratio: 0.01481, Grade: B\",\"StationNumber: 05MTB21, Year: 2005, PEL ratio: 0.03798, Grade: C\",\"StationNumber: 05MTB22, Year: 2005, PEL ratio: 0.0196, Grade: B\",\"StationNumber: 05OTB01, Year: 2005, PEL ratio: 0.01507, Grade: B\",\"StationNumber: 05OTB02, Year: 2005, PEL ratio: 0.02508, Grade: C\",\"StationNumber: 05OTB03, Year: 2005, PEL ratio: 0.01587, Grade: B\",\"StationNumber: 05OTB04, Year: 2005, PEL ratio: 0.02237, Grade: C\",\"StationNumber: 05OTB05, Year: 2005, PEL ratio: 0.0268, Grade: C\",\"StationNumber: 05OTB06, Year: 2005, PEL ratio: 0.05287, Grade: C\",\"StationNumber: 05OTB07, Year: 2005, PEL ratio: 0.02997, Grade: C\",\"StationNumber: 05OTB08, Year: 2005, PEL ratio: 0.01315, Grade: B\",\"StationNumber: 05OTB09, Year: 2005, PEL ratio: 0.04264, Grade: C\",\"StationNumber: 05OTB10, Year: 2005, PEL ratio: 0.01673, Grade: B\",\"StationNumber: 05TCB01, Year: 2005, PEL ratio: 0.02249, Grade: C\",\"StationNumber: 05TCB03, Year: 2005, PEL ratio: 0.01896, Grade: B\",\"StationNumber: 05TCB05, Year: 2005, PEL ratio: 0.01899, Grade: B\",\"StationNumber: 05TCB07, Year: 2005, PEL ratio: 0.11125, Grade: D\",\"StationNumber: 05TCB10, Year: 2005, PEL ratio: 0.01684, Grade: B\",\"StationNumber: 06BCB01, Year: 2006, PEL ratio: 0.04257, Grade: C\",\"StationNumber: 06BCB02, Year: 2006, PEL ratio: 0.03339, Grade: C\",\"StationNumber: 06BCB03, Year: 2006, PEL ratio: 0.03085, Grade: C\",\"StationNumber: 06BCB04, Year: 2006, PEL ratio: 0.04285, Grade: C\",\"StationNumber: 06BCB05, Year: 2006, PEL ratio: 0.02977, Grade: C\",\"StationNumber: 06BCB06, Year: 2006, PEL ratio: 0.03224, Grade: C\",\"StationNumber: 06BCB07, Year: 2006, PEL ratio: 0.05354, Grade: C\",\"StationNumber: 06BCB08, Year: 2006, PEL ratio: 0.03691, Grade: C\",\"StationNumber: 06BCB09, Year: 2006, PEL ratio: 0.02935, Grade: C\",\"StationNumber: 06HB01, Year: 2006, PEL ratio: 0.05456, Grade: C\",\"StationNumber: 06HB02, Year: 2006, PEL ratio: 0.07105, Grade: C\",\"StationNumber: 06HB03, Year: 2006, PEL ratio: 0.09993, Grade: D\",\"StationNumber: 06HB04, Year: 2006, PEL ratio: 0.04056, Grade: C\",\"StationNumber: 06HB05, Year: 2006, PEL ratio: 0.05604, Grade: C\",\"StationNumber: 06HB06, Year: 2006, PEL ratio: 0.05301, Grade: C\",\"StationNumber: 06HB08, Year: 2006, PEL ratio: 0.04385, Grade: C\",\"StationNumber: 06HB09, Year: 2006, PEL ratio: 0.326, Grade: F\",\"StationNumber: 06HB10, Year: 2006, PEL ratio: 0.03664, Grade: C\",\"StationNumber: 06HB11, Year: 2006, PEL ratio: 0.04268, Grade: C\",\"StationNumber: 06HB12, Year: 2006, PEL ratio: 0.04913, Grade: C\",\"StationNumber: 06HB13, Year: 2006, PEL ratio: 0.03765, Grade: C\",\"StationNumber: 06HB14, Year: 2006, PEL ratio: 0.04626, Grade: C\",\"StationNumber: 06HB15, Year: 2006, PEL ratio: 0.02753, Grade: C\",\"StationNumber: 06HB16, Year: 2006, PEL ratio: 0.02342, Grade: C\",\"StationNumber: 06HB17, Year: 2006, PEL ratio: 0.04712, Grade: C\",\"StationNumber: 06HB18, Year: 2006, PEL ratio: 0.14179, Grade: D\",\"StationNumber: 06HB19, Year: 2006, PEL ratio: 0.05858, Grade: C\",\"StationNumber: 06HB20, Year: 2006, PEL ratio: 0.10134, Grade: D\",\"StationNumber: 06HB21, Year: 2006, PEL ratio: 0.08326, Grade: C\",\"StationNumber: 06HB22, Year: 2006, PEL ratio: 0.033, Grade: C\",\"StationNumber: 06HB23, Year: 2006, PEL ratio: 0.02427, Grade: C\",\"StationNumber: 06HB24, Year: 2006, PEL ratio: 0.04327, Grade: C\",\"StationNumber: 06HB25, Year: 2006, PEL ratio: 0.01783, Grade: B\",\"StationNumber: 06LTB01, Year: 2006, PEL ratio: 0.03721, Grade: C\",\"StationNumber: 06LTB02, Year: 2006, PEL ratio: 0.0323, Grade: C\",\"StationNumber: 06LTB03, Year: 2006, PEL ratio: 0.03756, Grade: C\",\"StationNumber: 06LTB04, Year: 2006, PEL ratio: 0.03755, Grade: C\",\"StationNumber: 06LTB05, Year: 2006, PEL ratio: 0.02195, Grade: C\",\"StationNumber: 06LTB06, Year: 2006, PEL ratio: 0.0252, Grade: C\",\"StationNumber: 06LTB07, Year: 2006, PEL ratio: 0.02677, Grade: C\",\"StationNumber: 06LTB08, Year: 2006, PEL ratio: 0.034, Grade: C\",\"StationNumber: 06MR05, Year: 2006, PEL ratio: 0.06293, Grade: C\",\"StationNumber: 06MR06, Year: 2006, PEL ratio: 0.0353, Grade: C\",\"StationNumber: 06MR07, Year: 2006, PEL ratio: 0.03329, Grade: C\",\"StationNumber: 06MR08, Year: 2006, PEL ratio: 0.02817, Grade: C\",\"StationNumber: 06MR10, Year: 2006, PEL ratio: 0.0606, Grade: C\",\"StationNumber: 06MTB01, Year: 2006, PEL ratio: 0.0429, Grade: C\",\"StationNumber: 06MTB02, Year: 2006, PEL ratio: 0.03147, Grade: C\",\"StationNumber: 06MTB03, Year: 2006, PEL ratio: 0.07411, Grade: C\",\"StationNumber: 06MTB04, Year: 2006, PEL ratio: 0.03457, Grade: C\",\"StationNumber: 06MTB05, Year: 2006, PEL ratio: 0.04597, Grade: C\",\"StationNumber: 06MTB06, Year: 2006, PEL ratio: 0.04758, Grade: C\",\"StationNumber: 06MTB07, Year: 2006, PEL ratio: 0.03733, Grade: C\",\"StationNumber: 06MTB08, Year: 2006, PEL ratio: 0.02422, Grade: C\",\"StationNumber: 06MTB09, Year: 2006, PEL ratio: 0.03151, Grade: C\",\"StationNumber: 06MTB10, Year: 2006, PEL ratio: 0.03838, Grade: C\",\"StationNumber: 06MTB11, Year: 2006, PEL ratio: 0.05121, Grade: C\",\"StationNumber: 06MTB12, Year: 2006, PEL ratio: 0.03322, Grade: C\",\"StationNumber: 06MTB13, Year: 2006, PEL ratio: 0.04635, Grade: C\",\"StationNumber: 06MTB14, Year: 2006, PEL ratio: 0.02936, Grade: C\",\"StationNumber: 06MTB15, Year: 2006, PEL ratio: 0.04074, Grade: C\",\"StationNumber: 06MTB16, Year: 2006, PEL ratio: 0.02985, Grade: C\",\"StationNumber: 06MTB17, Year: 2006, PEL ratio: 0.04129, Grade: C\",\"StationNumber: 06MTB18, Year: 2006, PEL ratio: 0.02464, Grade: C\",\"StationNumber: 06MTB19, Year: 2006, PEL ratio: 0.03277, Grade: C\",\"StationNumber: 06OTB01, Year: 2006, PEL ratio: 0.03793, Grade: C\",\"StationNumber: 06OTB02, Year: 2006, PEL ratio: 0.03026, Grade: C\",\"StationNumber: 06OTB03, Year: 2006, PEL ratio: 0.02375, Grade: C\",\"StationNumber: 06OTB04, Year: 2006, PEL ratio: 0.03499, Grade: C\",\"StationNumber: 06OTB05, Year: 2006, PEL ratio: 0.03108, Grade: C\",\"StationNumber: 06OTB06, Year: 2006, PEL ratio: 0.03693, Grade: C\",\"StationNumber: 06OTB07, Year: 2006, PEL ratio: 0.03414, Grade: C\",\"StationNumber: 06OTB08, Year: 2006, PEL ratio: 0.03241, Grade: C\",\"StationNumber: 06TCB01, Year: 2006, PEL ratio: 0.01865, Grade: B\",\"StationNumber: 06TCB02, Year: 2006, PEL ratio: 0.02033, Grade: B\",\"StationNumber: 06TCB03, Year: 2006, PEL ratio: 0.02258, Grade: C\",\"StationNumber: 06TCB04, Year: 2006, PEL ratio: 0.02342, Grade: C\",\"StationNumber: 06TCB09, Year: 2006, PEL ratio: 0.02164, Grade: C\",\"StationNumber: 07BCB06, Year: 2007, PEL ratio: 0.03022, Grade: C\",\"StationNumber: 07BCB09, Year: 2007, PEL ratio: 0.04305, Grade: C\",\"StationNumber: 07BCB15, Year: 2007, PEL ratio: 0.03284, Grade: C\",\"StationNumber: 07BCB28, Year: 2007, PEL ratio: 0.0147, Grade: B\",\"StationNumber: 07BCB29, Year: 2007, PEL ratio: 0.03304, Grade: C\",\"StationNumber: 07BCB30, Year: 2007, PEL ratio: 0.02747, Grade: C\",\"StationNumber: 07BCB41, Year: 2007, PEL ratio: 0.02363, Grade: C\",\"StationNumber: 07BCB42, Year: 2007, PEL ratio: 0.03369, Grade: C\",\"StationNumber: 07BCB44, Year: 2007, PEL ratio: 0.02609, Grade: C\",\"StationNumber: 07BCB45, Year: 2007, PEL ratio: 0.04507, Grade: C\",\"StationNumber: 07HB13, Year: 2007, PEL ratio: 0.02193, Grade: C\",\"StationNumber: 07HB21, Year: 2007, PEL ratio: 0.64118, Grade: F\",\"StationNumber: 07HB34, Year: 2007, PEL ratio: 0.02191, Grade: C\",\"StationNumber: 07HB37, Year: 2007, PEL ratio: 0.03607, Grade: C\",\"StationNumber: 07HB38, Year: 2007, PEL ratio: 0.01243, Grade: B\",\"StationNumber: 07HB41, Year: 2007, PEL ratio: 0.00402, Grade: A\",\"StationNumber: 07HB42, Year: 2007, PEL ratio: 0.04791, Grade: C\",\"StationNumber: 07HB44, Year: 2007, PEL ratio: 0.05993, Grade: C\",\"StationNumber: 07HB53, Year: 2007, PEL ratio: 0.04356, Grade: C\",\"StationNumber: 07LTB91, Year: 2007, PEL ratio: 0.01736, Grade: B\",\"StationNumber: 07MR09, Year: 2007, PEL ratio: 0.00426, Grade: A\",\"StationNumber: 07MR28, Year: 2007, PEL ratio: 0.01592, Grade: B\",\"StationNumber: 07MR42, Year: 2007, PEL ratio: 0.01369, Grade: B\",\"StationNumber: 07MR46, Year: 2007, PEL ratio: 0.01441, Grade: B\",\"StationNumber: 07MR50, Year: 2007, PEL ratio: 0.00928, Grade: B\",\"StationNumber: 07MTB34, Year: 2007, PEL ratio: 0.03749, Grade: C\",\"StationNumber: 07MTB39, Year: 2007, PEL ratio: 0.02821, Grade: C\",\"StationNumber: 07MTB40, Year: 2007, PEL ratio: 0.03116, Grade: C\",\"StationNumber: 07MTB43, Year: 2007, PEL ratio: 0.03052, Grade: C\",\"StationNumber: 07MTB44, Year: 2007, PEL ratio: 0.0747, Grade: C\",\"StationNumber: 07MTB47, Year: 2007, PEL ratio: 0.04289, Grade: C\",\"StationNumber: 07MTB54, Year: 2007, PEL ratio: 0.03469, Grade: C\",\"StationNumber: 07OTB04, Year: 2007, PEL ratio: 0.0814, Grade: C\",\"StationNumber: 07OTB08, Year: 2007, PEL ratio: 0.03439, Grade: C\",\"StationNumber: 07OTB18, Year: 2007, PEL ratio: 0.03309, Grade: C\",\"StationNumber: 07OTB21, Year: 2007, PEL ratio: 0.05054, Grade: C\",\"StationNumber: 07OTB24, Year: 2007, PEL ratio: 0.03054, Grade: C\",\"StationNumber: 07OTB25, Year: 2007, PEL ratio: 0.02688, Grade: C\",\"StationNumber: 07OTB31, Year: 2007, PEL ratio: 0.03368, Grade: C\",\"StationNumber: 07TCB14, Year: 2007, PEL ratio: 0.02992, Grade: C\",\"StationNumber: 07TCB15, Year: 2007, PEL ratio: 0.0222, Grade: C\",\"StationNumber: 07TCB20, Year: 2007, PEL ratio: 0.01955, Grade: B\",\"StationNumber: 07TCB22, Year: 2007, PEL ratio: 0.01339, Grade: B\",\"StationNumber: 08BCB02, Year: 2008, PEL ratio: 0.02083, Grade: C\",\"StationNumber: 08BCB05, Year: 2008, PEL ratio: 0.02657, Grade: C\",\"StationNumber: 08BCB12, Year: 2008, PEL ratio: 0.02728, Grade: C\",\"StationNumber: 08BCB15, Year: 2008, PEL ratio: 0.06515, Grade: C\",\"StationNumber: 08BCB16, Year: 2008, PEL ratio: 0.03082, Grade: C\",\"StationNumber: 08BCB17, Year: 2008, PEL ratio: 0.09679, Grade: D\",\"StationNumber: 08BCB23, Year: 2008, PEL ratio: 0.1008, Grade: D\",\"StationNumber: 08BCB26, Year: 2008, PEL ratio: 0.0274, Grade: C\",\"StationNumber: 08BCB29, Year: 2008, PEL ratio: 0.0277, Grade: C\",\"StationNumber: 08BCB35, Year: 2008, PEL ratio: 0.03788, Grade: C\",\"StationNumber: 08BCB38, Year: 2008, PEL ratio: 0.02984, Grade: C\",\"StationNumber: 08HB13, Year: 2008, PEL ratio: 0.07748, Grade: C\",\"StationNumber: 08HB14, Year: 2008, PEL ratio: 0.03813, Grade: C\",\"StationNumber: 08HB17, Year: 2008, PEL ratio: 0.24554, Grade: D\",\"StationNumber: 08HB21, Year: 2008, PEL ratio: 0.15288, Grade: D\",\"StationNumber: 08HB27, Year: 2008, PEL ratio: 0.05295, Grade: C\",\"StationNumber: 08HB34, Year: 2008, PEL ratio: 0.02555, Grade: C\",\"StationNumber: 08HB43, Year: 2008, PEL ratio: 0.02778, Grade: C\",\"StationNumber: 08HB44, Year: 2008, PEL ratio: 0.02327, Grade: C\",\"StationNumber: 08HB48, Year: 2008, PEL ratio: 0.02752, Grade: C\",\"StationNumber: 08LTB69, Year: 2008, PEL ratio: 0.02295, Grade: C\",\"StationNumber: 08LTB79, Year: 2008, PEL ratio: 0.04396, Grade: C\",\"StationNumber: 08LTB82, Year: 2008, PEL ratio: 0.02777, Grade: C\",\"StationNumber: 08MR08, Year: 2008, PEL ratio: 0.03334, Grade: C\",\"StationNumber: 08MR35, Year: 2008, PEL ratio: 0.02726, Grade: C\",\"StationNumber: 08MR40, Year: 2008, PEL ratio: 0.03952, Grade: C\",\"StationNumber: 08MR43, Year: 2008, PEL ratio: 0.08724, Grade: D\",\"StationNumber: 08MR53, Year: 2008, PEL ratio: 0.02561, Grade: C\",\"StationNumber: 08MR54, Year: 2008, PEL ratio: 0.02649, Grade: C\",\"StationNumber: 08MTB37, Year: 2008, PEL ratio: 0.02715, Grade: C\",\"StationNumber: 08MTB47, Year: 2008, PEL ratio: 0.02945, Grade: C\",\"StationNumber: 08MTB53, Year: 2008, PEL ratio: 0, Grade: A\",\"StationNumber: 08MTB62, Year: 2008, PEL ratio: 0.03147, Grade: C\",\"StationNumber: 08MTB73, Year: 2008, PEL ratio: 0.085, Grade: C\",\"StationNumber: 08OTB05, Year: 2008, PEL ratio: 0.02469, Grade: C\",\"StationNumber: 08OTB07, Year: 2008, PEL ratio: 0.03217, Grade: C\",\"StationNumber: 08OTB13, Year: 2008, PEL ratio: 0.02418, Grade: C\",\"StationNumber: 08OTB15, Year: 2008, PEL ratio: 0.03404, Grade: C\",\"StationNumber: 08OTB17, Year: 2008, PEL ratio: 0.02613, Grade: C\",\"StationNumber: 08OTB23, Year: 2008, PEL ratio: 0.03692, Grade: C\",\"StationNumber: 08OTB27, Year: 2008, PEL ratio: 0.03973, Grade: C\",\"StationNumber: 08TCB01, Year: 2008, PEL ratio: 0.02193, Grade: C\",\"StationNumber: 08TCB07, Year: 2008, PEL ratio: 0.02717, Grade: C\",\"StationNumber: 08TCB26, Year: 2008, PEL ratio: 0.03977, Grade: C\",\"StationNumber: 09BCB06, Year: 2009, PEL ratio: 0.2271, Grade: D\",\"StationNumber: 09BCB07, Year: 2009, PEL ratio: 0.22765, Grade: D\",\"StationNumber: 09BCB10, Year: 2009, PEL ratio: 0.22887, Grade: D\",\"StationNumber: 09BCB18, Year: 2009, PEL ratio: 0.22738, Grade: D\",\"StationNumber: 09BCB20, Year: 2009, PEL ratio: 0.2271, Grade: D\",\"StationNumber: 09BCB22, Year: 2009, PEL ratio: 0.22745, Grade: D\",\"StationNumber: 09BCB25, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 09BCB31, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 09BCB34, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 09BCB36, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 09BCB43, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 09HB05, Year: 2009, PEL ratio: 0.2648, Grade: D\",\"StationNumber: 09HB11, Year: 2009, PEL ratio: 0.23926, Grade: D\",\"StationNumber: 09HB15, Year: 2009, PEL ratio: 0.2285, Grade: D\",\"StationNumber: 09HB23, Year: 2009, PEL ratio: 0.22717, Grade: D\",\"StationNumber: 09HB24, Year: 2009, PEL ratio: 0.22751, Grade: D\",\"StationNumber: 09HB32, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 09HB35, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 09HB53, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 09HB56, Year: 2009, PEL ratio: 0.24223, Grade: D\",\"StationNumber: 09LTB77, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 09LTB90, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 09MR17, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 09MR30, Year: 2009, PEL ratio: 0.22715, Grade: D\",\"StationNumber: 09MR36, Year: 2009, PEL ratio: 0.23016, Grade: D\",\"StationNumber: 09MR46, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 09MR49, Year: 2009, PEL ratio: 0.22727, Grade: D\",\"StationNumber: 09MTB42, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 09MTB44, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 09MTB48, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 09MTB50, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 09MTB63, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 09MTB72, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 09OTB09, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 09OTB10, Year: 2009, PEL ratio: 0.23279, Grade: D\",\"StationNumber: 09OTB14, Year: 2009, PEL ratio: 0.22724, Grade: D\",\"StationNumber: 09OTB16, Year: 2009, PEL ratio: 0.2271, Grade: D\",\"StationNumber: 09OTB20, Year: 2009, PEL ratio: 0.22738, Grade: D\",\"StationNumber: 09OTB28, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 09OTB29, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 09TCB10, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 09TCB13, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 09TCB14, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 09TCB22, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 10BCB06, Year: 2010, PEL ratio: 0.05418, Grade: C\",\"StationNumber: 10BCB11, Year: 2010, PEL ratio: 0.06776, Grade: C\",\"StationNumber: 10BCB17, Year: 2010, PEL ratio: 0.05636, Grade: C\",\"StationNumber: 10BCB25, Year: 2010, PEL ratio: 0.04525, Grade: C\",\"StationNumber: 10BCB28, Year: 2010, PEL ratio: 0.058, Grade: C\",\"StationNumber: 10BCB30, Year: 2010, PEL ratio: 0.05066, Grade: C\",\"StationNumber: 10BCB37, Year: 2010, PEL ratio: 0.05759, Grade: C\",\"StationNumber: 10BCB41, Year: 2010, PEL ratio: 0.16956, Grade: D\",\"StationNumber: 10BCB46, Year: 2010, PEL ratio: 0.04398, Grade: C\",\"StationNumber: 10BCB47, Year: 2010, PEL ratio: 0.05076, Grade: C\",\"StationNumber: 10BCB49, Year: 2010, PEL ratio: 0.04946, Grade: C\",\"StationNumber: 10HB21, Year: 2010, PEL ratio: 0.11698, Grade: D\",\"StationNumber: 10HB22, Year: 2010, PEL ratio: 0.1448, Grade: D\",\"StationNumber: 10HB25, Year: 2010, PEL ratio: 0.06694, Grade: C\",\"StationNumber: 10HB26, Year: 2010, PEL ratio: 0.09827, Grade: D\",\"StationNumber: 10HB34, Year: 2010, PEL ratio: 0.05702, Grade: C\",\"StationNumber: 10HB44, Year: 2010, PEL ratio: 0.05266, Grade: C\",\"StationNumber: 10HB46, Year: 2010, PEL ratio: 0.05934, Grade: C\",\"StationNumber: 10HB48, Year: 2010, PEL ratio: 0.05189, Grade: C\",\"StationNumber: 10HB54, Year: 2010, PEL ratio: 0.06254, Grade: C\",\"StationNumber: 10LTB71, Year: 2010, PEL ratio: 0.03978, Grade: C\",\"StationNumber: 10LTB76, Year: 2010, PEL ratio: 0.04208, Grade: C\",\"StationNumber: 10LTB89, Year: 2010, PEL ratio: 0.04389, Grade: C\",\"StationNumber: 10MR25, Year: 2010, PEL ratio: 0.04098, Grade: C\",\"StationNumber: 10MR29, Year: 2010, PEL ratio: 0.04883, Grade: C\",\"StationNumber: 10MR33, Year: 2010, PEL ratio: 0.04098, Grade: C\",\"StationNumber: 10MR40, Year: 2010, PEL ratio: 0.05975, Grade: C\",\"StationNumber: 10MR44, Year: 2010, PEL ratio: 0.05334, Grade: C\",\"StationNumber: 10MTB30, Year: 2010, PEL ratio: 0.11699, Grade: D\",\"StationNumber: 10MTB35, Year: 2010, PEL ratio: 0.0404, Grade: C\",\"StationNumber: 10MTB43, Year: 2010, PEL ratio: 0.05591, Grade: C\",\"StationNumber: 10MTB53, Year: 2010, PEL ratio: 0.05385, Grade: C\",\"StationNumber: 10MTB56, Year: 2010, PEL ratio: 0.04796, Grade: C\",\"StationNumber: 10OTB04, Year: 2010, PEL ratio: 0.06327, Grade: C\",\"StationNumber: 10OTB05, Year: 2010, PEL ratio: 0.04514, Grade: C\",\"StationNumber: 10OTB07, Year: 2010, PEL ratio: 0.0966, Grade: D\",\"StationNumber: 10OTB08, Year: 2010, PEL ratio: 0.05185, Grade: C\",\"StationNumber: 10OTB09, Year: 2010, PEL ratio: 0.0499, Grade: C\",\"StationNumber: 10OTB12, Year: 2010, PEL ratio: 0.04749, Grade: C\",\"StationNumber: 10OTB13, Year: 2010, PEL ratio: 0.09096, Grade: D\",\"StationNumber: 10OTB14, Year: 2010, PEL ratio: 0.05743, Grade: C\",\"StationNumber: 10OTB15, Year: 2010, PEL ratio: 0.0503, Grade: C\",\"StationNumber: 10OTB16, Year: 2010, PEL ratio: 0.04904, Grade: C\",\"StationNumber: 10OTB18, Year: 2010, PEL ratio: 0.04797, Grade: C\",\"StationNumber: 10OTB19, Year: 2010, PEL ratio: 0.04649, Grade: C\",\"StationNumber: 10OTB20, Year: 2010, PEL ratio: 0.05188, Grade: C\",\"StationNumber: 10OTB21, Year: 2010, PEL ratio: 0.09696, Grade: D\",\"StationNumber: 10OTB24, Year: 2010, PEL ratio: 0.04571, Grade: C\",\"StationNumber: 10OTB25, Year: 2010, PEL ratio: 0.04516, Grade: C\",\"StationNumber: 10OTB26, Year: 2010, PEL ratio: 0.06229, Grade: C\",\"StationNumber: 10OTB28, Year: 2010, PEL ratio: 0.05494, Grade: C\",\"StationNumber: 10OTB29, Year: 2010, PEL ratio: 0.0463, Grade: C\",\"StationNumber: 10OTB96, Year: 2010, PEL ratio: 0.09566, Grade: D\",\"StationNumber: 10OTB97, Year: 2010, PEL ratio: 0.0741, Grade: C\",\"StationNumber: 10OTB98, Year: 2010, PEL ratio: 0.057, Grade: C\",\"StationNumber: 10TCB01, Year: 2010, PEL ratio: 0.03856, Grade: C\",\"StationNumber: 10TCB11, Year: 2010, PEL ratio: 0.04704, Grade: C\",\"StationNumber: 10TCB13, Year: 2010, PEL ratio: 0.04199, Grade: C\",\"StationNumber: 10TCB20, Year: 2010, PEL ratio: 0.03693, Grade: C\",\"StationNumber: 11BCB05, Year: 2011, PEL ratio: 0.03406, Grade: C\",\"StationNumber: 11BCB09, Year: 2011, PEL ratio: 0.07696, Grade: C\",\"StationNumber: 11BCB12, Year: 2011, PEL ratio: 0.03876, Grade: C\",\"StationNumber: 11BCB20, Year: 2011, PEL ratio: 0.0708, Grade: C\",\"StationNumber: 11BCB22, Year: 2011, PEL ratio: 0.03401, Grade: C\",\"StationNumber: 11BCB26, Year: 2011, PEL ratio: 0.05588, Grade: C\",\"StationNumber: 11BCB35, Year: 2011, PEL ratio: 0.0405, Grade: C\",\"StationNumber: 11BCB42, Year: 2011, PEL ratio: 0.05499, Grade: C\",\"StationNumber: 11BCB43, Year: 2011, PEL ratio: 0.03362, Grade: C\",\"StationNumber: 11BCB44, Year: 2011, PEL ratio: 0.03382, Grade: C\",\"StationNumber: 11BCB48, Year: 2011, PEL ratio: 0.03412, Grade: C\",\"StationNumber: 11HB09, Year: 2011, PEL ratio: 0.04257, Grade: C\",\"StationNumber: 11HB13, Year: 2011, PEL ratio: 0.05996, Grade: C\",\"StationNumber: 11HB29, Year: 2011, PEL ratio: 0.0821, Grade: C\",\"StationNumber: 11HB31, Year: 2011, PEL ratio: 0.0332, Grade: C\",\"StationNumber: 11HB35, Year: 2011, PEL ratio: 0.03838, Grade: C\",\"StationNumber: 11HB36, Year: 2011, PEL ratio: 0.04301, Grade: C\",\"StationNumber: 11HB38, Year: 2011, PEL ratio: 0.03229, Grade: C\",\"StationNumber: 11HB40, Year: 2011, PEL ratio: 0.04344, Grade: C\",\"StationNumber: 11HB47, Year: 2011, PEL ratio: 0.07343, Grade: C\",\"StationNumber: 11LTB69, Year: 2011, PEL ratio: 0.03431, Grade: C\",\"StationNumber: 11LTB75, Year: 2011, PEL ratio: 0.03175, Grade: C\",\"StationNumber: 11LTB80, Year: 2011, PEL ratio: 0.02849, Grade: C\",\"StationNumber: 11MR18, Year: 2011, PEL ratio: 0.03158, Grade: C\",\"StationNumber: 11MR32, Year: 2011, PEL ratio: 0.08626, Grade: D\",\"StationNumber: 11MR35, Year: 2011, PEL ratio: 0.2895, Grade: F\",\"StationNumber: 11MR37, Year: 2011, PEL ratio: 0.04922, Grade: C\",\"StationNumber: 11MR43, Year: 2011, PEL ratio: 0.22016, Grade: D\",\"StationNumber: 11MR45, Year: 2011, PEL ratio: 0.05964, Grade: C\",\"StationNumber: 11MR52, Year: 2011, PEL ratio: 0.05915, Grade: C\",\"StationNumber: 11MTB39, Year: 2011, PEL ratio: 0.03658, Grade: C\",\"StationNumber: 11MTB44, Year: 2011, PEL ratio: 0.03276, Grade: C\",\"StationNumber: 11MTB46, Year: 2011, PEL ratio: 0.03321, Grade: C\",\"StationNumber: 11MTB54, Year: 2011, PEL ratio: 0.03421, Grade: C\",\"StationNumber: 11MTB72, Year: 2011, PEL ratio: 0.03547, Grade: C\",\"StationNumber: 11OTB08, Year: 2011, PEL ratio: 0.05594, Grade: C\",\"StationNumber: 11OTB09, Year: 2011, PEL ratio: 0.03373, Grade: C\",\"StationNumber: 11OTB18, Year: 2011, PEL ratio: 0.03456, Grade: C\",\"StationNumber: 11OTB24, Year: 2011, PEL ratio: 0.03411, Grade: C\",\"StationNumber: 11OTB26, Year: 2011, PEL ratio: 0.03346, Grade: C\",\"StationNumber: 11OTB31, Year: 2011, PEL ratio: 0.03496, Grade: C\",\"StationNumber: 11OTB32, Year: 2011, PEL ratio: 0.03287, Grade: C\",\"StationNumber: 11TCB10, Year: 2011, PEL ratio: 0.02871, Grade: C\",\"StationNumber: 11TCB12, Year: 2011, PEL ratio: 0.03385, Grade: C\",\"StationNumber: 12BCB06, Year: 2012, PEL ratio: 0.04452, Grade: C\",\"StationNumber: 12BCB14, Year: 2012, PEL ratio: 0.38368, Grade: F\",\"StationNumber: 12BCB19, Year: 2012, PEL ratio: 0.03721, Grade: C\",\"StationNumber: 12BCB23, Year: 2012, PEL ratio: 0.04469, Grade: C\",\"StationNumber: 12BCB25, Year: 2012, PEL ratio: 0.03922, Grade: C\",\"StationNumber: 12BCB27, Year: 2012, PEL ratio: 0.07968, Grade: C\",\"StationNumber: 12BCB35, Year: 2012, PEL ratio: 0.04033, Grade: C\",\"StationNumber: 12BCB40, Year: 2012, PEL ratio: 0.04044, Grade: C\",\"StationNumber: 12BCB44, Year: 2012, PEL ratio: 0.03462, Grade: C\",\"StationNumber: 12BCB46, Year: 2012, PEL ratio: 0.03927, Grade: C\",\"StationNumber: 12BCB49, Year: 2012, PEL ratio: 0.04079, Grade: C\",\"StationNumber: 12HB27, Year: 2012, PEL ratio: 0.04713, Grade: C\",\"StationNumber: 12HB28, Year: 2012, PEL ratio: 0.0439, Grade: C\",\"StationNumber: 12HB31, Year: 2012, PEL ratio: 0.13887, Grade: D\",\"StationNumber: 12HB32, Year: 2012, PEL ratio: 0.04521, Grade: C\",\"StationNumber: 12HB38, Year: 2012, PEL ratio: 0.05609, Grade: C\",\"StationNumber: 12HB40, Year: 2012, PEL ratio: 0.03976, Grade: C\",\"StationNumber: 12HB45, Year: 2012, PEL ratio: 0.07001, Grade: C\",\"StationNumber: 12HB53, Year: 2012, PEL ratio: 0.045, Grade: C\",\"StationNumber: 12HB54, Year: 2012, PEL ratio: 0.04384, Grade: C\",\"StationNumber: 12LTB78, Year: 2012, PEL ratio: 0.04261, Grade: C\",\"StationNumber: 12LTB84, Year: 2012, PEL ratio: 0.03384, Grade: C\",\"StationNumber: 12LTB93, Year: 2012, PEL ratio: 0.03901, Grade: C\",\"StationNumber: 12MR08, Year: 2012, PEL ratio: 0.03605, Grade: C\",\"StationNumber: 12MR17, Year: 2012, PEL ratio: 0.03946, Grade: C\",\"StationNumber: 12MR33, Year: 2012, PEL ratio: 0.0386, Grade: C\",\"StationNumber: 12MR36, Year: 2012, PEL ratio: 0.0414, Grade: C\",\"StationNumber: 12MR43, Year: 2012, PEL ratio: 0.04657, Grade: C\",\"StationNumber: 12MR46, Year: 2012, PEL ratio: 0.0353, Grade: C\",\"StationNumber: 12MR54, Year: 2012, PEL ratio: 0.03951, Grade: C\",\"StationNumber: 12MTB47, Year: 2012, PEL ratio: 0.04162, Grade: C\",\"StationNumber: 12MTB53, Year: 2012, PEL ratio: 0.03721, Grade: C\",\"StationNumber: 12MTB58, Year: 2012, PEL ratio: 0.05309, Grade: C\",\"StationNumber: 12MTB63, Year: 2012, PEL ratio: 0.03957, Grade: C\",\"StationNumber: 12MTB64, Year: 2012, PEL ratio: 0.04165, Grade: C\",\"StationNumber: 12OTB04, Year: 2012, PEL ratio: 0.13065, Grade: D\",\"StationNumber: 12OTB08, Year: 2012, PEL ratio: 0.03843, Grade: C\",\"StationNumber: 12OTB13, Year: 2012, PEL ratio: 0.04154, Grade: C\",\"StationNumber: 12OTB14, Year: 2012, PEL ratio: 0.03612, Grade: C\",\"StationNumber: 12OTB18, Year: 2012, PEL ratio: 0.04305, Grade: C\",\"StationNumber: 12OTB19, Year: 2012, PEL ratio: 0.03486, Grade: C\",\"StationNumber: 12OTB20, Year: 2012, PEL ratio: 0.04146, Grade: C\",\"StationNumber: 12TCB05, Year: 2012, PEL ratio: 0.03318, Grade: C\",\"StationNumber: 12TCB13, Year: 2012, PEL ratio: 0.03331, Grade: C\",\"StationNumber: 13BCB05, Year: 2013, PEL ratio: 0.16727, Grade: D\",\"StationNumber: 13BCB07, Year: 2013, PEL ratio: 0.04534, Grade: C\",\"StationNumber: 13BCB09, Year: 2013, PEL ratio: 0.04449, Grade: C\",\"StationNumber: 13BCB10, Year: 2013, PEL ratio: 0.03598, Grade: C\",\"StationNumber: 13BCB11, Year: 2013, PEL ratio: 0.1881, Grade: D\",\"StationNumber: 13BCB17, Year: 2013, PEL ratio: 0.10487, Grade: D\",\"StationNumber: 13BCB22, Year: 2013, PEL ratio: 0.0432, Grade: C\",\"StationNumber: 13BCB30, Year: 2013, PEL ratio: 0.03594, Grade: C\",\"StationNumber: 13BCB41, Year: 2013, PEL ratio: 0.03671, Grade: C\",\"StationNumber: 13BCB43, Year: 2013, PEL ratio: 0.03609, Grade: C\",\"StationNumber: 13BCB48, Year: 2013, PEL ratio: 0.04681, Grade: C\",\"StationNumber: 13HB09, Year: 2013, PEL ratio: 0.07695, Grade: C\",\"StationNumber: 13HB13, Year: 2013, PEL ratio: 0.0831, Grade: C\",\"StationNumber: 13HB25, Year: 2013, PEL ratio: 0.03306, Grade: C\",\"StationNumber: 13HB26, Year: 2013, PEL ratio: 0.05412, Grade: C\",\"StationNumber: 13HB35, Year: 2013, PEL ratio: 0.03811, Grade: C\",\"StationNumber: 13HB36, Year: 2013, PEL ratio: 0.18861, Grade: D\",\"StationNumber: 13HB41, Year: 2013, PEL ratio: 0.03847, Grade: C\",\"StationNumber: 13HB44, Year: 2013, PEL ratio: 0.09625, Grade: D\",\"StationNumber: 13HB48, Year: 2013, PEL ratio: 0.0373, Grade: C\",\"StationNumber: 13LTB79, Year: 2013, PEL ratio: 0.03872, Grade: C\",\"StationNumber: 13LTB82, Year: 2013, PEL ratio: 0.03513, Grade: C\",\"StationNumber: 13LTB86, Year: 2013, PEL ratio: 0.03287, Grade: C\",\"StationNumber: 13MR09, Year: 2013, PEL ratio: 0.03565, Grade: C\",\"StationNumber: 13MR24, Year: 2013, PEL ratio: 0.03695, Grade: C\",\"StationNumber: 13MR31, Year: 2013, PEL ratio: 0.34066, Grade: F\",\"StationNumber: 13MR44, Year: 2013, PEL ratio: 0.09108, Grade: D\",\"StationNumber: 13MR45, Year: 2013, PEL ratio: 0.06721, Grade: C\",\"StationNumber: 13MR48, Year: 2013, PEL ratio: 0.0568, Grade: C\",\"StationNumber: 13MTB34, Year: 2013, PEL ratio: 0.03171, Grade: C\",\"StationNumber: 13MTB35, Year: 2013, PEL ratio: 0.05215, Grade: C\",\"StationNumber: 13MTB41, Year: 2013, PEL ratio: 0.03838, Grade: C\",\"StationNumber: 13MTB45, Year: 2013, PEL ratio: 0.03368, Grade: C\",\"StationNumber: 13MTB55, Year: 2013, PEL ratio: 0.06478, Grade: C\",\"StationNumber: 13OTB12, Year: 2013, PEL ratio: 0.04515, Grade: C\",\"StationNumber: 13OTB15, Year: 2013, PEL ratio: 0.03702, Grade: C\",\"StationNumber: 13OTB16, Year: 2013, PEL ratio: 0.04069, Grade: C\",\"StationNumber: 13OTB21, Year: 2013, PEL ratio: 0.04235, Grade: C\",\"StationNumber: 13OTB27, Year: 2013, PEL ratio: 0.03527, Grade: C\",\"StationNumber: 13OTB28, Year: 2013, PEL ratio: 0.03653, Grade: C\",\"StationNumber: 13OTB29, Year: 2013, PEL ratio: 0.04087, Grade: C\",\"StationNumber: 13TCB01, Year: 2013, PEL ratio: 0.03209, Grade: C\",\"StationNumber: 13TCB11, Year: 2013, PEL ratio: 0.03349, Grade: C\",\"StationNumber: 13TCB14, Year: 2013, PEL ratio: 0.03452, Grade: C\",\"StationNumber: 14BCB03, Year: 2014, PEL ratio: 0.07223, Grade: C\",\"StationNumber: 14BCB12, Year: 2014, PEL ratio: 0.03971, Grade: C\",\"StationNumber: 14BCB15, Year: 2014, PEL ratio: 0.12267, Grade: D\",\"StationNumber: 14BCB17, Year: 2014, PEL ratio: 0.03495, Grade: C\",\"StationNumber: 14BCB20, Year: 2014, PEL ratio: 0.04709, Grade: C\",\"StationNumber: 14BCB25, Year: 2014, PEL ratio: 0.01763, Grade: B\",\"StationNumber: 14BCB29, Year: 2014, PEL ratio: 0.01869, Grade: B\",\"StationNumber: 14BCB33, Year: 2014, PEL ratio: 0.03039, Grade: C\",\"StationNumber: 14BCB35, Year: 2014, PEL ratio: 0.08684, Grade: D\",\"StationNumber: 14BCB41, Year: 2014, PEL ratio: 0.03173, Grade: C\",\"StationNumber: 14BCB47, Year: 2014, PEL ratio: 0.02445, Grade: C\",\"StationNumber: 14HB20, Year: 2014, PEL ratio: 0.02692, Grade: C\",\"StationNumber: 14HB21, Year: 2014, PEL ratio: 0.11022, Grade: D\",\"StationNumber: 14HB26, Year: 2014, PEL ratio: 0.04422, Grade: C\",\"StationNumber: 14HB33, Year: 2014, PEL ratio: 0.04596, Grade: C\",\"StationNumber: 14HB43, Year: 2014, PEL ratio: 0.02882, Grade: C\",\"StationNumber: 14HB44, Year: 2014, PEL ratio: 0.02425, Grade: C\",\"StationNumber: 14HB46, Year: 2014, PEL ratio: 0.02682, Grade: C\",\"StationNumber: 14HB47, Year: 2014, PEL ratio: 0.02598, Grade: C\",\"StationNumber: 14HB54, Year: 2014, PEL ratio: 0.0288, Grade: C\",\"StationNumber: 14LTB71, Year: 2014, PEL ratio: 0.02041, Grade: B\",\"StationNumber: 14LTB81, Year: 2014, PEL ratio: 0.02037, Grade: B\",\"StationNumber: 14LTB90, Year: 2014, PEL ratio: 0.01877, Grade: B\",\"StationNumber: 14MR29, Year: 2014, PEL ratio: 0.01907, Grade: B\",\"StationNumber: 14MR35, Year: 2014, PEL ratio: 0.0555, Grade: C\",\"StationNumber: 14MR37, Year: 2014, PEL ratio: 0.09494, Grade: D\",\"StationNumber: 14MR38, Year: 2014, PEL ratio: 0.1108, Grade: D\",\"StationNumber: 14MR47, Year: 2014, PEL ratio: 0.01791, Grade: B\",\"StationNumber: 14MTB39, Year: 2014, PEL ratio: 0.02273, Grade: C\",\"StationNumber: 14MTB41, Year: 2014, PEL ratio: 0.03062, Grade: C\",\"StationNumber: 14MTB46, Year: 2014, PEL ratio: 0.02094, Grade: C\",\"StationNumber: 14MTB54, Year: 2014, PEL ratio: 0.02078, Grade: C\",\"StationNumber: 14MTB63, Year: 2014, PEL ratio: 0.02282, Grade: C\",\"StationNumber: 14OTB04, Year: 2014, PEL ratio: 0.02755, Grade: C\",\"StationNumber: 14OTB08, Year: 2014, PEL ratio: 0.03792, Grade: C\",\"StationNumber: 14OTB14, Year: 2014, PEL ratio: 0.04277, Grade: C\",\"StationNumber: 14OTB18, Year: 2014, PEL ratio: 2.41188, Grade: F\",\"StationNumber: 14OTB19, Year: 2014, PEL ratio: 0.01969, Grade: B\",\"StationNumber: 14OTB21, Year: 2014, PEL ratio: 0.02613, Grade: C\",\"StationNumber: 14OTB25, Year: 2014, PEL ratio: 0.02671, Grade: C\",\"StationNumber: 14TCB15, Year: 2014, PEL ratio: 0.03044, Grade: C\",\"StationNumber: 14TCB20, Year: 2014, PEL ratio: 0.02875, Grade: C\",\"StationNumber: 14TCB21, Year: 2014, PEL ratio: 0.0283, Grade: C\",\"StationNumber: 14TCB22, Year: 2014, PEL ratio: 0.01653, Grade: B\",\"StationNumber: 15BCB09, Year: 2015, PEL ratio: 0.03637, Grade: C\",\"StationNumber: 15BCB12, Year: 2015, PEL ratio: 0.04372, Grade: C\",\"StationNumber: 15BCB15, Year: 2015, PEL ratio: 0.04656, Grade: C\",\"StationNumber: 15BCB26, Year: 2015, PEL ratio: 0.05585, Grade: C\",\"StationNumber: 15BCB30, Year: 2015, PEL ratio: 0.04815, Grade: C\",\"StationNumber: 15BCB31, Year: 2015, PEL ratio: 0.13946, Grade: D\",\"StationNumber: 15BCB34, Year: 2015, PEL ratio: 0.03182, Grade: C\",\"StationNumber: 15BCB39, Year: 2015, PEL ratio: 0.03826, Grade: C\",\"StationNumber: 15BCB43, Year: 2015, PEL ratio: 0.03861, Grade: C\",\"StationNumber: 15BCB47, Year: 2015, PEL ratio: 0.06181, Grade: C\",\"StationNumber: 15BCB48, Year: 2015, PEL ratio: 0.03381, Grade: C\",\"StationNumber: 15HB09, Year: 2015, PEL ratio: 0.15218, Grade: D\",\"StationNumber: 15HB14, Year: 2015, PEL ratio: 0.08241, Grade: C\",\"StationNumber: 15HB27, Year: 2015, PEL ratio: 0.07462, Grade: C\",\"StationNumber: 15HB36, Year: 2015, PEL ratio: 0.04156, Grade: C\",\"StationNumber: 15HB37, Year: 2015, PEL ratio: 0.03697, Grade: C\",\"StationNumber: 15HB39, Year: 2015, PEL ratio: 0.03681, Grade: C\",\"StationNumber: 15HB40, Year: 2015, PEL ratio: 0.03913, Grade: C\",\"StationNumber: 15HB41, Year: 2015, PEL ratio: 0.03531, Grade: C\",\"StationNumber: 15HB48, Year: 2015, PEL ratio: 0.038, Grade: C\",\"StationNumber: 15LTB70, Year: 2015, PEL ratio: 0.03226, Grade: C\",\"StationNumber: 15LTB76, Year: 2015, PEL ratio: 0.03036, Grade: C\",\"StationNumber: 15LTB94, Year: 2015, PEL ratio: 0.03816, Grade: C\",\"StationNumber: 15MR08, Year: 2015, PEL ratio: 0.03832, Grade: C\",\"StationNumber: 15MR28, Year: 2015, PEL ratio: 0.03623, Grade: C\",\"StationNumber: 15MR30, Year: 2015, PEL ratio: 0.03637, Grade: C\",\"StationNumber: 15MR33, Year: 2015, PEL ratio: 0.15657, Grade: D\",\"StationNumber: 15MR42, Year: 2015, PEL ratio: 0.04571, Grade: C\",\"StationNumber: 15MR52, Year: 2015, PEL ratio: 0.03954, Grade: C\",\"StationNumber: 15MTB40, Year: 2015, PEL ratio: 0.0354, Grade: C\",\"StationNumber: 15MTB49, Year: 2015, PEL ratio: 0.04217, Grade: C\",\"StationNumber: 15MTB52, Year: 2015, PEL ratio: 0.03085, Grade: C\",\"StationNumber: 15MTB55, Year: 2015, PEL ratio: 0.0351, Grade: C\",\"StationNumber: 15MTB62, Year: 2015, PEL ratio: 0.03246, Grade: C\",\"StationNumber: 15OTB12, Year: 2015, PEL ratio: 0.04593, Grade: C\",\"StationNumber: 15OTB15, Year: 2015, PEL ratio: 0.05137, Grade: C\",\"StationNumber: 15OTB20, Year: 2015, PEL ratio: 0.05337, Grade: C\",\"StationNumber: 15OTB24, Year: 2015, PEL ratio: 0.04, Grade: C\",\"StationNumber: 15OTB26, Year: 2015, PEL ratio: 0.03346, Grade: C\",\"StationNumber: 15OTB28, Year: 2015, PEL ratio: 0.03812, Grade: C\",\"StationNumber: 15OTB29, Year: 2015, PEL ratio: 0.05653, Grade: C\",\"StationNumber: 15TCB01, Year: 2015, PEL ratio: 0.02764, Grade: C\",\"StationNumber: 15TCB11, Year: 2015, PEL ratio: 0.03474, Grade: C\",\"StationNumber: 15TCB12, Year: 2015, PEL ratio: 0.04456, Grade: C\",\"StationNumber: 16BCB20, Year: 2016, PEL ratio: 0.02494, Grade: C\",\"StationNumber: 16BCB22, Year: 2016, PEL ratio: 0.01314, Grade: B\",\"StationNumber: 16BCB25, Year: 2016, PEL ratio: 0.03973, Grade: C\",\"StationNumber: 16BCB29, Year: 2016, PEL ratio: 0.00699, Grade: A\",\"StationNumber: 16BCB34, Year: 2016, PEL ratio: 0.01356, Grade: B\",\"StationNumber: 16BCB35, Year: 2016, PEL ratio: 0.01331, Grade: B\",\"StationNumber: 16BCB36, Year: 2016, PEL ratio: 0.03548, Grade: C\",\"StationNumber: 16BCB37, Year: 2016, PEL ratio: 0.02852, Grade: C\",\"StationNumber: 16BCB41, Year: 2016, PEL ratio: 0.01322, Grade: B\",\"StationNumber: 16BCB42, Year: 2016, PEL ratio: 0.01254, Grade: B\",\"StationNumber: 16BCB43, Year: 2016, PEL ratio: 0.0166, Grade: B\",\"StationNumber: 16DH07-1, Year: 2016, PEL ratio: 0.18391, Grade: D\",\"StationNumber: 16DH07-2, Year: 2016, PEL ratio: 0.13524, Grade: D\",\"StationNumber: 16DH07-3, Year: 2016, PEL ratio: 0.20542, Grade: D\",\"StationNumber: 16DH07-4, Year: 2016, PEL ratio: 0.01549, Grade: B\",\"StationNumber: 16HB19, Year: 2016, PEL ratio: 0.05887, Grade: C\",\"StationNumber: 16HB20, Year: 2016, PEL ratio: 0.04907, Grade: C\",\"StationNumber: 16HB21, Year: 2016, PEL ratio: 0.0132, Grade: B\",\"StationNumber: 16HB27, Year: 2016, PEL ratio: 0.02076, Grade: C\",\"StationNumber: 16HB28, Year: 2016, PEL ratio: 0.9678, Grade: F\",\"StationNumber: 16HB32, Year: 2016, PEL ratio: 0.08862, Grade: D\",\"StationNumber: 16HB33, Year: 2016, PEL ratio: 0.01043, Grade: B\",\"StationNumber: 16HB37, Year: 2016, PEL ratio: 0.02529, Grade: C\",\"StationNumber: 16HB48, Year: 2016, PEL ratio: 0.00834, Grade: B\",\"StationNumber: 16DH04-1, Year: 2016, PEL ratio: 0.01392, Grade: B\",\"StationNumber: 16DH04-2, Year: 2016, PEL ratio: 0.01391, Grade: B\",\"StationNumber: 16DH04-3, Year: 2016, PEL ratio: 0.0173, Grade: B\",\"StationNumber: 16DH04-4, Year: 2016, PEL ratio: 0.01483, Grade: B\",\"StationNumber: 16DH08-1, Year: 2016, PEL ratio: 0.01209, Grade: B\",\"StationNumber: 16DH08-2, Year: 2016, PEL ratio: 0.01315, Grade: B\",\"StationNumber: 16DH08-3, Year: 2016, PEL ratio: 0.01495, Grade: B\",\"StationNumber: 16DH08-4, Year: 2016, PEL ratio: 0.0073, Grade: A\",\"StationNumber: 16DH09-1, Year: 2016, PEL ratio: 0.0417, Grade: C\",\"StationNumber: 16DH09-2, Year: 2016, PEL ratio: 0.0163, Grade: B\",\"StationNumber: 16DH09-3, Year: 2016, PEL ratio: 0.01326, Grade: B\",\"StationNumber: 16DH09-4, Year: 2016, PEL ratio: 0.01211, Grade: B\",\"StationNumber: 16LTB71, Year: 2016, PEL ratio: 0.02031, Grade: B\",\"StationNumber: 16LTB79, Year: 2016, PEL ratio: 0.03301, Grade: C\",\"StationNumber: 16LTB85, Year: 2016, PEL ratio: 0.01936, Grade: B\",\"StationNumber: 16MR17, Year: 2016, PEL ratio: 0.01448, Grade: B\",\"StationNumber: 16MR25, Year: 2016, PEL ratio: 0.01518, Grade: B\",\"StationNumber: 16MR29, Year: 2016, PEL ratio: 0.02155, Grade: C\",\"StationNumber: 16MR33, Year: 2016, PEL ratio: 0.04406, Grade: C\",\"StationNumber: 16MR43, Year: 2016, PEL ratio: 0.03343, Grade: C\",\"StationNumber: 16MR44, Year: 2016, PEL ratio: 0.01835, Grade: B\",\"StationNumber: 16MR45, Year: 2016, PEL ratio: 0.09741, Grade: D\",\"StationNumber: 16DH06-1, Year: 2016, PEL ratio: 0.03826, Grade: C\",\"StationNumber: 16DH06-2, Year: 2016, PEL ratio: 0.03293, Grade: C\",\"StationNumber: 16DH06-3, Year: 2016, PEL ratio: 0.0963, Grade: D\",\"StationNumber: 16DH06-4, Year: 2016, PEL ratio: 0.04943, Grade: C\",\"StationNumber: 16DH10-1, Year: 2016, PEL ratio: 0.0172, Grade: B\",\"StationNumber: 16DH10-2, Year: 2016, PEL ratio: 0.0164, Grade: B\",\"StationNumber: 16DH10-3, Year: 2016, PEL ratio: 0.01826, Grade: B\",\"StationNumber: 16DH10-4, Year: 2016, PEL ratio: 0.01494, Grade: B\",\"StationNumber: 16MTB41, Year: 2016, PEL ratio: 0.04661, Grade: C\",\"StationNumber: 16MTB47, Year: 2016, PEL ratio: 0.01915, Grade: B\",\"StationNumber: 16MTB48, Year: 2016, PEL ratio: 0.02853, Grade: C\",\"StationNumber: 16MTB53, Year: 2016, PEL ratio: 0.01875, Grade: B\",\"StationNumber: 16MTB72, Year: 2016, PEL ratio: 0.01874, Grade: B\",\"StationNumber: 16DH01-1, Year: 2016, PEL ratio: 0.12523, Grade: D\",\"StationNumber: 16DH01-2, Year: 2016, PEL ratio: 0.02653, Grade: C\",\"StationNumber: 16DH01-3, Year: 2016, PEL ratio: 0.14601, Grade: D\",\"StationNumber: 16DH01-4, Year: 2016, PEL ratio: 0.02374, Grade: C\",\"StationNumber: 16DH02-1, Year: 2016, PEL ratio: 0.02317, Grade: C\",\"StationNumber: 16DH02-2, Year: 2016, PEL ratio: 0.01762, Grade: B\",\"StationNumber: 16DH02-3, Year: 2016, PEL ratio: 0.14359, Grade: D\",\"StationNumber: 16DH02-4, Year: 2016, PEL ratio: 0.015, Grade: B\",\"StationNumber: 16DH03-1, Year: 2016, PEL ratio: 0.08286, Grade: C\",\"StationNumber: 16DH03-2, Year: 2016, PEL ratio: 0.12405, Grade: D\",\"StationNumber: 16DH03-3, Year: 2016, PEL ratio: 0.08808, Grade: D\",\"StationNumber: 16DH03-4, Year: 2016, PEL ratio: 0.01809, Grade: B\",\"StationNumber: 16DH05-1, Year: 2016, PEL ratio: 0.05878, Grade: C\",\"StationNumber: 16DH05-2, Year: 2016, PEL ratio: 0.04695, Grade: C\",\"StationNumber: 16DH05-3, Year: 2016, PEL ratio: 0.02045, Grade: B\",\"StationNumber: 16DH05-4, Year: 2016, PEL ratio: 0.01988, Grade: B\",\"StationNumber: 16OTB08, Year: 2016, PEL ratio: 0.02621, Grade: C\",\"StationNumber: 16OTB09, Year: 2016, PEL ratio: 0.03233, Grade: C\",\"StationNumber: 16OTB13, Year: 2016, PEL ratio: 0.04697, Grade: C\",\"StationNumber: 16OTB14, Year: 2016, PEL ratio: 0.02479, Grade: C\",\"StationNumber: 16OTB18, Year: 2016, PEL ratio: 0.01902, Grade: B\",\"StationNumber: 16OTB22, Year: 2016, PEL ratio: 0.02164, Grade: C\",\"StationNumber: 16OTB25, Year: 2016, PEL ratio: 0.01921, Grade: B\",\"StationNumber: 16TCB14, Year: 2016, PEL ratio: 0.01957, Grade: B\",\"StationNumber: 16TCB20, Year: 2016, PEL ratio: 0.01605, Grade: B\",\"StationNumber: 17BCB15, Year: 2017, PEL ratio: 0.05574, Grade: C\",\"StationNumber: 17BCB26, Year: 2017, PEL ratio: 0.04395, Grade: C\",\"StationNumber: 17BCB27, Year: 2017, PEL ratio: 0.05204, Grade: C\",\"StationNumber: 17BCB30, Year: 2017, PEL ratio: 0.03789, Grade: C\",\"StationNumber: 17BCB35, Year: 2017, PEL ratio: 0.0452, Grade: C\",\"StationNumber: 17BCB36, Year: 2017, PEL ratio: 0.03869, Grade: C\",\"StationNumber: 17BCB40, Year: 2017, PEL ratio: 0.04165, Grade: C\",\"StationNumber: 17BCB42, Year: 2017, PEL ratio: 0.03888, Grade: C\",\"StationNumber: 17BCB43, Year: 2017, PEL ratio: 0.0479, Grade: C\",\"StationNumber: 17BCB44, Year: 2017, PEL ratio: 0.04568, Grade: C\",\"StationNumber: 17BCB48, Year: 2017, PEL ratio: 0.04356, Grade: C\",\"StationNumber: 17HB10, Year: 2017, PEL ratio: 0.07514, Grade: C\",\"StationNumber: 17HB13, Year: 2017, PEL ratio: 0.09007, Grade: D\",\"StationNumber: 17HB15, Year: 2017, PEL ratio: 0.20221, Grade: D\",\"StationNumber: 17HB26, Year: 2017, PEL ratio: 0.04364, Grade: C\",\"StationNumber: 17HB34, Year: 2017, PEL ratio: 2.58424, Grade: F\",\"StationNumber: 17HB36, Year: 2017, PEL ratio: 0.06844, Grade: C\",\"StationNumber: 17HB41, Year: 2017, PEL ratio: 0.04206, Grade: C\",\"StationNumber: 17HB42, Year: 2017, PEL ratio: 0.04424, Grade: C\",\"StationNumber: 17HB43, Year: 2017, PEL ratio: 0.04021, Grade: C\",\"StationNumber: 17LTB70, Year: 2017, PEL ratio: 0.03897, Grade: C\",\"StationNumber: 17LTB83, Year: 2017, PEL ratio: 0.03803, Grade: C\",\"StationNumber: 17LTB89, Year: 2017, PEL ratio: 0.03834, Grade: C\",\"StationNumber: 17TCP01, Year: 2017, PEL ratio: 0.05508, Grade: C\",\"StationNumber: 17TCP02, Year: 2017, PEL ratio: 0.05287, Grade: C\",\"StationNumber: 17TCP03, Year: 2017, PEL ratio: 0.05051, Grade: C\",\"StationNumber: 17TCP04, Year: 2017, PEL ratio: 0.05089, Grade: C\",\"StationNumber: 17TCP05, Year: 2017, PEL ratio: 0.04678, Grade: C\",\"StationNumber: 17TCP06, Year: 2017, PEL ratio: 0.07589, Grade: C\",\"StationNumber: 17TCP07, Year: 2017, PEL ratio: 0.051, Grade: C\",\"StationNumber: 17TCP08, Year: 2017, PEL ratio: 0.05778, Grade: C\",\"StationNumber: 17TCP09, Year: 2017, PEL ratio: 0.04474, Grade: C\",\"StationNumber: 17TCP10, Year: 2017, PEL ratio: 0.04683, Grade: C\",\"StationNumber: 17MR09, Year: 2017, PEL ratio: 0.03927, Grade: C\",\"StationNumber: 17MR18, Year: 2017, PEL ratio: 0.04076, Grade: C\",\"StationNumber: 17MR24, Year: 2017, PEL ratio: 0.03902, Grade: C\",\"StationNumber: 17MR32, Year: 2017, PEL ratio: 0.03951, Grade: C\",\"StationNumber: 17MR35, Year: 2017, PEL ratio: 0.0913, Grade: D\",\"StationNumber: 17MR37, Year: 2017, PEL ratio: 0.04193, Grade: C\",\"StationNumber: 17MTB34, Year: 2017, PEL ratio: 0.03827, Grade: C\",\"StationNumber: 17MTB35, Year: 2017, PEL ratio: 0.05891, Grade: C\",\"StationNumber: 17MTB46, Year: 2017, PEL ratio: 0.04189, Grade: C\",\"StationNumber: 17MTB55, Year: 2017, PEL ratio: 0.04047, Grade: C\",\"StationNumber: 17MTB63, Year: 2017, PEL ratio: 0.04197, Grade: C\",\"StationNumber: 17OTB04, Year: 2017, PEL ratio: 0.0536, Grade: C\",\"StationNumber: 17OTB07, Year: 2017, PEL ratio: 0.05219, Grade: C\",\"StationNumber: 17OTB12, Year: 2017, PEL ratio: 0.10245, Grade: D\",\"StationNumber: 17OTB19, Year: 2017, PEL ratio: 0.04286, Grade: C\",\"StationNumber: 17OTB21, Year: 2017, PEL ratio: 0.04087, Grade: C\",\"StationNumber: 17OTB28, Year: 2017, PEL ratio: 0.04793, Grade: C\",\"StationNumber: 17OTB32, Year: 2017, PEL ratio: 0.04013, Grade: C\",\"StationNumber: 17TCB12, Year: 2017, PEL ratio: 0.03885, Grade: C\",\"StationNumber: 17TCB13, Year: 2017, PEL ratio: 0.04488, Grade: C\",\"StationNumber: 17TCB21, Year: 2017, PEL ratio: 0.04358, Grade: C\",\"StationNumber: 18BCB11, Year: 2018, PEL ratio: 0.37337, Grade: F\",\"StationNumber: 18BCB15, Year: 2018, PEL ratio: 0.21905, Grade: D\",\"StationNumber: 18BCB19, Year: 2018, PEL ratio: 0.00266, Grade: A\",\"StationNumber: 18BCB20, Year: 2018, PEL ratio: 0.21369, Grade: D\",\"StationNumber: 18BCB22, Year: 2018, PEL ratio: 0.17683, Grade: D\",\"StationNumber: 18BCB24, Year: 2018, PEL ratio: 0.01165, Grade: B\",\"StationNumber: 18BCB26, Year: 2018, PEL ratio: 0.28634, Grade: F\",\"StationNumber: 18BCB37, Year: 2018, PEL ratio: 0.00425, Grade: A\",\"StationNumber: 18BCB42, Year: 2018, PEL ratio: 0.00155, Grade: A\",\"StationNumber: 18BCB44, Year: 2018, PEL ratio: 0.00316, Grade: A\",\"StationNumber: 18BCB46, Year: 2018, PEL ratio: 0.01455, Grade: B\",\"StationNumber: 18HB14, Year: 2018, PEL ratio: 0.04307, Grade: C\",\"StationNumber: 18HB20, Year: 2018, PEL ratio: 0.05365, Grade: C\",\"StationNumber: 18HB21, Year: 2018, PEL ratio: 0.03344, Grade: C\",\"StationNumber: 18HB26, Year: 2018, PEL ratio: 0.03348, Grade: C\",\"StationNumber: 18HB29, Year: 2018, PEL ratio: 0.0738, Grade: C\",\"StationNumber: 18HB33, Year: 2018, PEL ratio: 0.05804, Grade: C\",\"StationNumber: 18HB38, Year: 2018, PEL ratio: 0.03293, Grade: C\",\"StationNumber: 18HB41, Year: 2018, PEL ratio: 0.00774, Grade: B\",\"StationNumber: 18HB46, Year: 2018, PEL ratio: 1.04973, Grade: F\",\"StationNumber: 18LTB75, Year: 2018, PEL ratio: 0.12361, Grade: D\",\"StationNumber: 18LTB79, Year: 2018, PEL ratio: 0.03143, Grade: C\",\"StationNumber: 18LTB81, Year: 2018, PEL ratio: 0.09621, Grade: D\",\"StationNumber: 18LTB82, Year: 2018, PEL ratio: 0.0782, Grade: C\",\"StationNumber: 18MR25, Year: 2018, PEL ratio: 0.04013, Grade: C\",\"StationNumber: 18MR37, Year: 2018, PEL ratio: 0.06345, Grade: C\",\"StationNumber: 18MR46, Year: 2018, PEL ratio: 0.03519, Grade: C\",\"StationNumber: 18MTB41, Year: 2018, PEL ratio: 0.01539, Grade: B\",\"StationNumber: 18MTB42, Year: 2018, PEL ratio: 0.18686, Grade: D\",\"StationNumber: 18MTB48, Year: 2018, PEL ratio: 0.00879, Grade: B\",\"StationNumber: 18MTB56, Year: 2018, PEL ratio: 0.0139, Grade: B\",\"StationNumber: 18OTB04, Year: 2018, PEL ratio: 0.06233, Grade: C\",\"StationNumber: 18OTB08, Year: 2018, PEL ratio: 0.003, Grade: A\",\"StationNumber: 18OTB13, Year: 2018, PEL ratio: 0.01252, Grade: B\",\"StationNumber: 18OTB14, Year: 2018, PEL ratio: 0.04092, Grade: C\",\"StationNumber: 18OTB15, Year: 2018, PEL ratio: 0.01682, Grade: B\",\"StationNumber: 18OTB21, Year: 2018, PEL ratio: 0.00898, Grade: B\",\"StationNumber: 18OTB24, Year: 2018, PEL ratio: 0.00579, Grade: A\",\"StationNumber: 18TCB05, Year: 2018, PEL ratio: 0.03777, Grade: C\",\"StationNumber: 18TCB11, Year: 2018, PEL ratio: 0.02078, Grade: C\",\"StationNumber: 18TCB14, Year: 2018, PEL ratio: 0.05688, Grade: C\",\"StationNumber: 18TCB15, Year: 2018, PEL ratio: 0.05947, Grade: C\",\"StationNumber: 18TCB21, Year: 2018, PEL ratio: 0.11579, Grade: D\",\"StationNumber: 18TCB22, Year: 2018, PEL ratio: 0.02805, Grade: C\",\"StationNumber: 19BCB27, Year: 2019, PEL ratio: 0.04772, Grade: C\",\"StationNumber: 19BCB29, Year: 2019, PEL ratio: 0.04849, Grade: C\",\"StationNumber: 19BCB30, Year: 2019, PEL ratio: 0.1321, Grade: D\",\"StationNumber: 19BCB34, Year: 2019, PEL ratio: 0.51859, Grade: F\",\"StationNumber: 19BCB35, Year: 2019, PEL ratio: 0.05839, Grade: C\",\"StationNumber: 19BCB36, Year: 2019, PEL ratio: 0.11644, Grade: D\",\"StationNumber: 19BCB40, Year: 2019, PEL ratio: 0.00368, Grade: A\",\"StationNumber: 19BCB41, Year: 2019, PEL ratio: 0.0436, Grade: C\",\"StationNumber: 19BCB43, Year: 2019, PEL ratio: 0.09295, Grade: D\",\"StationNumber: 19BCB49, Year: 2019, PEL ratio: 0.05207, Grade: C\",\"StationNumber: 19BCB50, Year: 2019, PEL ratio: 0.0513, Grade: C\",\"StationNumber: 19HB09, Year: 2019, PEL ratio: 0.01191, Grade: B\",\"StationNumber: 19HB16, Year: 2019, PEL ratio: 0.69077, Grade: F\",\"StationNumber: 19HB25, Year: 2019, PEL ratio: 0.0126, Grade: B\",\"StationNumber: 19HB27, Year: 2019, PEL ratio: 0.05811, Grade: C\",\"StationNumber: 19HB32, Year: 2019, PEL ratio: 0.03805, Grade: C\",\"StationNumber: 19HB37, Year: 2019, PEL ratio: 0.06339, Grade: C\",\"StationNumber: 19HB39, Year: 2019, PEL ratio: 0.00598, Grade: A\",\"StationNumber: 19HB40, Year: 2019, PEL ratio: 0.0131, Grade: B\",\"StationNumber: 19HB47, Year: 2019, PEL ratio: 0.00395, Grade: A\",\"StationNumber: 19LTB76, Year: 2019, PEL ratio: 0.00985, Grade: B\",\"StationNumber: 19LTB78, Year: 2019, PEL ratio: 0.01215, Grade: B\",\"StationNumber: 19LTB88, Year: 2019, PEL ratio: 0.11037, Grade: D\",\"StationNumber: 19LTB90, Year: 2019, PEL ratio: 0.00656, Grade: A\",\"StationNumber: 19MR17, Year: 2019, PEL ratio: 0.01119, Grade: B\",\"StationNumber: 19MR18, Year: 2019, PEL ratio: 0.02367, Grade: C\",\"StationNumber: 19MR29, Year: 2019, PEL ratio: 0.02627, Grade: C\",\"StationNumber: 19MR33, Year: 2019, PEL ratio: 0.00769, Grade: B\",\"StationNumber: 19MR43, Year: 2019, PEL ratio: 0.17714, Grade: D\",\"StationNumber: 19MR44, Year: 2019, PEL ratio: 0.15675, Grade: D\",\"StationNumber: 19MR52, Year: 2019, PEL ratio: 0.0116, Grade: B\",\"StationNumber: 19MTB36, Year: 2019, PEL ratio: 0.08261, Grade: C\",\"StationNumber: 19MTB47, Year: 2019, PEL ratio: 0.01131, Grade: B\",\"StationNumber: 19MTB54, Year: 2019, PEL ratio: 0.00976, Grade: B\",\"StationNumber: 19MTB62, Year: 2019, PEL ratio: 0.00484, Grade: A\",\"StationNumber: 19OTB07, Year: 2019, PEL ratio: 0.01928, Grade: B\",\"StationNumber: 19OTB18, Year: 2019, PEL ratio: 0.05206, Grade: C\",\"StationNumber: 19OTB20, Year: 2019, PEL ratio: 0.02767, Grade: C\",\"StationNumber: 19OTB23, Year: 2019, PEL ratio: 0.01054, Grade: B\",\"StationNumber: 19OTB25, Year: 2019, PEL ratio: 0.04412, Grade: C\",\"StationNumber: 19OTB29, Year: 2019, PEL ratio: 0.04422, Grade: C\",\"StationNumber: 19OTB31, Year: 2019, PEL ratio: 0.01124, Grade: B\",\"StationNumber: 19TCB01, Year: 2019, PEL ratio: 0.01901, Grade: B\",\"StationNumber: 19TCB20, Year: 2019, PEL ratio: 0.01996, Grade: B\",\"StationNumber: 20BCB10, Year: 2020, PEL ratio: 0.02055, Grade: C\",\"StationNumber: 20BCB17, Year: 2020, PEL ratio: 0.0044, Grade: A\",\"StationNumber: 20BCB22, Year: 2020, PEL ratio: 0.20992, Grade: D\",\"StationNumber: 20BCB23, Year: 2020, PEL ratio: 0.00683, Grade: A\",\"StationNumber: 20BCB35, Year: 2020, PEL ratio: 0.04529, Grade: C\",\"StationNumber: 20BCB37, Year: 2020, PEL ratio: 0.01213, Grade: B\",\"StationNumber: 20BCB40, Year: 2020, PEL ratio: 0.00479, Grade: A\",\"StationNumber: 20BCB43, Year: 2020, PEL ratio: 0.00747, Grade: A\",\"StationNumber: 20BCB47, Year: 2020, PEL ratio: 0.01811, Grade: B\",\"StationNumber: 20BCB48, Year: 2020, PEL ratio: 0.02267, Grade: C\",\"StationNumber: 20BCB49, Year: 2020, PEL ratio: 0.01004, Grade: B\",\"StationNumber: 20HB09, Year: 2020, PEL ratio: 0.04899, Grade: C\",\"StationNumber: 20HB10, Year: 2020, PEL ratio: 0.06714, Grade: C\",\"StationNumber: 20HB21, Year: 2020, PEL ratio: 0.1516, Grade: D\",\"StationNumber: 20HB26, Year: 2020, PEL ratio: 0.03401, Grade: C\",\"StationNumber: 20HB38, Year: 2020, PEL ratio: 0.04319, Grade: C\",\"StationNumber: 20HB41, Year: 2020, PEL ratio: 0.01592, Grade: B\",\"StationNumber: 20HB46, Year: 2020, PEL ratio: 0.01143, Grade: B\",\"StationNumber: 20HB47, Year: 2020, PEL ratio: 0.00625, Grade: A\",\"StationNumber: 20HB52, Year: 2020, PEL ratio: 0.0242, Grade: C\",\"StationNumber: 20LTB70, Year: 2020, PEL ratio: 0.01567, Grade: B\",\"StationNumber: 20LTB71, Year: 2020, PEL ratio: 0.03189, Grade: C\",\"StationNumber: 20LTB77, Year: 2020, PEL ratio: 0.01505, Grade: B\",\"StationNumber: 20LTB85, Year: 2020, PEL ratio: 0.02098, Grade: C\",\"StationNumber: 20MR08, Year: 2020, PEL ratio: 0.07608, Grade: C\",\"StationNumber: 20MR09, Year: 2020, PEL ratio: 0.09408, Grade: D\",\"StationNumber: 20MR33, Year: 2020, PEL ratio: 0.18328, Grade: D\",\"StationNumber: 20MR36, Year: 2020, PEL ratio: 0.01558, Grade: B\",\"StationNumber: 20MR44, Year: 2020, PEL ratio: 0.10315, Grade: D\",\"StationNumber: 20MR49, Year: 2020, PEL ratio: 0.12139, Grade: D\",\"StationNumber: 20MTB35, Year: 2020, PEL ratio: 0.02267, Grade: C\",\"StationNumber: 20MTB46, Year: 2020, PEL ratio: 0.00585, Grade: A\",\"StationNumber: 20MTB52, Year: 2020, PEL ratio: 0.0217, Grade: C\",\"StationNumber: 20MTB63, Year: 2020, PEL ratio: 0.00437, Grade: A\",\"StationNumber: 20OTB13, Year: 2020, PEL ratio: 0.11907, Grade: D\",\"StationNumber: 20OTB14, Year: 2020, PEL ratio: 0.09905, Grade: D\",\"StationNumber: 20OTB15, Year: 2020, PEL ratio: 0.00718, Grade: A\",\"StationNumber: 20OTB19, Year: 2020, PEL ratio: 0.01134, Grade: B\",\"StationNumber: 20OTB21, Year: 2020, PEL ratio: 0.00212, Grade: A\",\"StationNumber: 20OTB24, Year: 2020, PEL ratio: 0.00213, Grade: A\",\"StationNumber: 20OTB32, Year: 2020, PEL ratio: 0.00435, Grade: A\",\"StationNumber: 20TCB10, Year: 2020, PEL ratio: 0.04695, Grade: C\",\"StationNumber: 20TCB12, Year: 2020, PEL ratio: 0.03948, Grade: C\",\"StationNumber: 20TCB20, Year: 2020, PEL ratio: 0.058, Grade: C\",\"StationNumber: 21BCB09, Year: 2021, PEL ratio: 0.11558, Grade: D\",\"StationNumber: 21BCB12, Year: 2021, PEL ratio: 0.01683, Grade: B\",\"StationNumber: 21BCB15, Year: 2021, PEL ratio: 0.05873, Grade: C\",\"StationNumber: 21BCB22, Year: 2021, PEL ratio: 0.01386, Grade: B\",\"StationNumber: 21BCB25, Year: 2021, PEL ratio: 0.00971, Grade: B\",\"StationNumber: 21BCB26, Year: 2021, PEL ratio: 0.03044, Grade: C\",\"StationNumber: 21BCB29, Year: 2021, PEL ratio: 0.02821, Grade: C\",\"StationNumber: 21BCB36, Year: 2021, PEL ratio: 0.00915, Grade: B\",\"StationNumber: 21BCB41, Year: 2021, PEL ratio: 0.00501, Grade: A\",\"StationNumber: 21BCB44, Year: 2021, PEL ratio: 0.01104, Grade: B\",\"StationNumber: 21BCB50, Year: 2021, PEL ratio: 0.00475, Grade: A\",\"StationNumber: 21HB13, Year: 2021, PEL ratio: 0.05335, Grade: C\",\"StationNumber: 21HB19, Year: 2021, PEL ratio: 0.08665, Grade: D\",\"StationNumber: 21HB20, Year: 2021, PEL ratio: 0.02175, Grade: C\",\"StationNumber: 21HB27, Year: 2021, PEL ratio: 0.04735, Grade: C\",\"StationNumber: 21HB34, Year: 2021, PEL ratio: 0.01341, Grade: B\",\"StationNumber: 21HB36, Year: 2021, PEL ratio: 0.03474, Grade: C\",\"StationNumber: 21HB37, Year: 2021, PEL ratio: 0.04959, Grade: C\",\"StationNumber: 21HB40, Year: 2021, PEL ratio: 0.01943, Grade: B\",\"StationNumber: 21HB43, Year: 2021, PEL ratio: 0.03012, Grade: C\",\"StationNumber: 21LTB78, Year: 2021, PEL ratio: 0.02074, Grade: C\",\"StationNumber: 21LTB83, Year: 2021, PEL ratio: 0.00875, Grade: B\",\"StationNumber: 21LTB84, Year: 2021, PEL ratio: 0.01135, Grade: B\",\"StationNumber: 21LTB89, Year: 2021, PEL ratio: 0.01185, Grade: B\",\"StationNumber: 21MR24, Year: 2021, PEL ratio: 0.0078, Grade: B\",\"StationNumber: 21MR29, Year: 2021, PEL ratio: 0.01739, Grade: B\",\"StationNumber: 21MR45, Year: 2021, PEL ratio: 0.06525, Grade: C\",\"StationNumber: 21MR47, Year: 2021, PEL ratio: 0.01081, Grade: B\",\"StationNumber: 21MR52, Year: 2021, PEL ratio: 0.01768, Grade: B\",\"StationNumber: 21MTB40, Year: 2021, PEL ratio: 0.01151, Grade: B\",\"StationNumber: 21MTB43, Year: 2021, PEL ratio: 0.03909, Grade: C\",\"StationNumber: 21MTB48, Year: 2021, PEL ratio: 0.01998, Grade: B\",\"StationNumber: 21MTB62, Year: 2021, PEL ratio: 0.01841, Grade: B\",\"StationNumber: 21OTB08, Year: 2021, PEL ratio: 0.00752, Grade: A\",\"StationNumber: 21OTB12, Year: 2021, PEL ratio: 0.05583, Grade: C\",\"StationNumber: 21OTB13, Year: 2021, PEL ratio: 0.00736, Grade: A\",\"StationNumber: 21OTB18, Year: 2021, PEL ratio: 0.01239, Grade: B\",\"StationNumber: 21OTB21, Year: 2021, PEL ratio: 0.00717, Grade: A\",\"StationNumber: 21OTB25, Year: 2021, PEL ratio: 0.00346, Grade: A\",\"StationNumber: 21OTB28, Year: 2021, PEL ratio: 0.00379, Grade: A\",\"StationNumber: 21TCB02, Year: 2021, PEL ratio: 0.03339, Grade: C\",\"StationNumber: 21TCB13, Year: 2021, PEL ratio: 0.04086, Grade: C\",\"StationNumber: 21TCB22, Year: 2021, PEL ratio: 0.01641, Grade: B\",\"StationNumber: 21TCB26, Year: 2021, PEL ratio: 0.01436, Grade: B\",\"StationNumber: 22BCB02, Year: 2022, PEL ratio: 0.10158, Grade: D\",\"StationNumber: 22BCB05, Year: 2022, PEL ratio: 0.00823, Grade: B\",\"StationNumber: 22BCB11, Year: 2022, PEL ratio: 0.03092, Grade: C\",\"StationNumber: 22BCB12, Year: 2022, PEL ratio: 0.01548, Grade: B\",\"StationNumber: 22BCB17, Year: 2022, PEL ratio: 0.02981, Grade: C\",\"StationNumber: 22BCB27, Year: 2022, PEL ratio: 0.02323, Grade: C\",\"StationNumber: 22BCB30, Year: 2022, PEL ratio: 0.00915, Grade: B\",\"StationNumber: 22BCB34, Year: 2022, PEL ratio: 0.00532, Grade: A\",\"StationNumber: 22BCB35, Year: 2022, PEL ratio: 0.00406, Grade: A\",\"StationNumber: 22BCB45, Year: 2022, PEL ratio: 0.011, Grade: B\",\"StationNumber: 22BCB47, Year: 2022, PEL ratio: 0.01696, Grade: B\",\"StationNumber: 22HB10, Year: 2022, PEL ratio: 0.01656, Grade: B\",\"StationNumber: 22HB19, Year: 2022, PEL ratio: 0.00725, Grade: A\",\"StationNumber: 22HB21, Year: 2022, PEL ratio: 0.00943, Grade: B\",\"StationNumber: 22HB25, Year: 2022, PEL ratio: 0.03897, Grade: C\",\"StationNumber: 22HB26, Year: 2022, PEL ratio: 0.07429, Grade: C\",\"StationNumber: 22HB28, Year: 2022, PEL ratio: 0.01322, Grade: B\",\"StationNumber: 22HB32, Year: 2022, PEL ratio: 0.06511, Grade: C\",\"StationNumber: 22HB40, Year: 2022, PEL ratio: 0.014, Grade: B\",\"StationNumber: 22HB46, Year: 2022, PEL ratio: 0.01842, Grade: B\",\"StationNumber: 22LTB70, Year: 2022, PEL ratio: 0.01965, Grade: B\",\"StationNumber: 22LTB79, Year: 2022, PEL ratio: 0.02208, Grade: C\",\"StationNumber: 22LTB81, Year: 2022, PEL ratio: 0.01111, Grade: B\",\"StationNumber: 22LTB90, Year: 2022, PEL ratio: 0.00235, Grade: A\",\"StationNumber: 22MR17, Year: 2022, PEL ratio: 0.0139, Grade: B\",\"StationNumber: 22MR25, Year: 2022, PEL ratio: 0.02261, Grade: C\",\"StationNumber: 22MR32, Year: 2022, PEL ratio: 0.07513, Grade: C\",\"StationNumber: 22MR37, Year: 2022, PEL ratio: 0.01282, Grade: B\",\"StationNumber: 22MR42, Year: 2022, PEL ratio: 0.04052, Grade: C\",\"StationNumber: 22MR44, Year: 2022, PEL ratio: 0.01954, Grade: B\",\"StationNumber: 22MR46, Year: 2022, PEL ratio: 0.0097, Grade: B\",\"StationNumber: 22MR52, Year: 2022, PEL ratio: 0.05693, Grade: C\",\"StationNumber: 22MTB35, Year: 2022, PEL ratio: 0.02359, Grade: C\",\"StationNumber: 22MTB37, Year: 2022, PEL ratio: 0.01478, Grade: B\",\"StationNumber: 22MTB41, Year: 2022, PEL ratio: 0.0351, Grade: C\",\"StationNumber: 22MTB55, Year: 2022, PEL ratio: 0.00667, Grade: A\",\"StationNumber: 22OTB02, Year: 2022, PEL ratio: 0.02605, Grade: C\",\"StationNumber: 22OTB07, Year: 2022, PEL ratio: 0.03873, Grade: C\",\"StationNumber: 22OTB19, Year: 2022, PEL ratio: 0.0321, Grade: C\",\"StationNumber: 22OTB22, Year: 2022, PEL ratio: 0.01763, Grade: B\",\"StationNumber: 22OTB28, Year: 2022, PEL ratio: 0.02167, Grade: C\",\"StationNumber: 22OTB29, Year: 2022, PEL ratio: 0.0061, Grade: A\",\"StationNumber: 22OTB32, Year: 2022, PEL ratio: 0.01368, Grade: B\",\"StationNumber: 22TCB20, Year: 2022, PEL ratio: 0.01157, Grade: B\"],{\"interactive\":false,\"permanent\":false,\"direction\":\"auto\",\"opacity\":1,\"offset\":[0,0],\"textsize\":\"10px\",\"textOnly\":false,\"className\":\"\",\"sticky\":true},null]}],\"limits\":{\"lat\":[27.4934,28.03793],\"lng\":[-82.84670300000001,-82.323427]}},\"evals\":[],\"jsHooks\":{\"render\":[{\"code\":\"function(el, x, data) {\\n return (\\n function(el, x) {\\n var myMap = this;\\n myMap.on('baselayerchange',\\n function (e) {\\n myMap.minimap.changeLayer(L.tileLayer.provider(e.name));\\n })\\n }).call(this.getMap(), el, x, data);\\n}\",\"data\":null}]}}"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_segmatrix.html","id":null,"dir":"Reference","previous_headings":"","what":"Create a colorized table for water quality outcomes and exceedances by segment — show_segmatrix","title":"Create a colorized table for water quality outcomes and exceedances by segment — show_segmatrix","text":"Create colorized table water quality outcomes segment includes management action chlorophyll, light attenuation exceedances","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_segmatrix.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Create a colorized table for water quality outcomes and exceedances by segment — show_segmatrix","text":"","code":"show_segmatrix( epcdata, txtsz = 3, trgs = NULL, yrrng = c(1975, 2023), bay_segment = c(\"OTB\", \"HB\", \"MTB\", \"LTB\"), abbrev = FALSE, family = NA, historic = TRUE, plotly = FALSE, partialyr = FALSE, width = NULL, height = NULL )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_segmatrix.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Create a colorized table for water quality outcomes and exceedances by segment — show_segmatrix","text":"epcdata data frame epc data returned read_importwq txtsz numeric size text plot, applies tab = FALSE trgs optional data.frame annual bay segment water quality targets, defaults targets yrrng numeric vector indicating min, max years include bay_segment chr string bay segments include, one \"OTB\", \"HB\", \"MTB\", \"LTB\" abbrev logical indicating text labels plot abbreviated first letter family optional chr string indicating font family text labels historic logical historic data used 2005 earlier plotly logical matrix created using plotly partialyr logical indicating incomplete annual data recent year approximated five year monthly averages parameter width numeric width plot pixels, applies plotly = TRUE height numeric height plot pixels, applies plotly = TRUE","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_segmatrix.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Create a colorized table for water quality outcomes and exceedances by segment — show_segmatrix","text":"static ggplot object returned","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_segmatrix.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Create a colorized table for water quality outcomes and exceedances by segment — show_segmatrix","text":"function provides combined output show_wqmatrix show_matrix functions. one bay segment can plotted function call.","code":""},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_segmatrix.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Create a colorized table for water quality outcomes and exceedances by segment — show_segmatrix","text":"","code":"show_segmatrix(epcdata, bay_segment = 'OTB')"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_segplotly.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot chlorophyll and secchi data together with matrix outcomes — show_segplotly","title":"Plot chlorophyll and secchi data together with matrix outcomes — show_segplotly","text":"Plot chlorophyll secchi data together matrix outcomes","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_segplotly.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot chlorophyll and secchi data together with matrix outcomes — show_segplotly","text":"","code":"show_segplotly( epcdata, bay_segment = c(\"OTB\", \"HB\", \"MTB\", \"LTB\"), yrrng = c(1975, 2023), family = NULL, partialyr = FALSE, width = NULL, height = NULL )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_segplotly.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot chlorophyll and secchi data together with matrix outcomes — show_segplotly","text":"epcdata data frame epc data returned read_importwq bay_segment chr string bay segment, one \"OTB\", \"HB\", \"MTB\", \"LTB\" yrrng numeric year range plot family optional chr string indicating font family text labels partialyr logical indicating incomplete annual data recent year approximated five year monthly averages parameter width numeric width plot pixels height numeric height plot pixels","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_segplotly.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot chlorophyll and secchi data together with matrix outcomes — show_segplotly","text":"interactive plotly object","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_segplotly.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Plot chlorophyll and secchi data together with matrix outcomes — show_segplotly","text":"function combines outputs show_thrplot show_segmatrix selected bay segment. plot interactive can zoomed dragging mouse pointer section plot. Information cell value can seen hovering location plot.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_segplotly.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot chlorophyll and secchi data together with matrix outcomes — show_segplotly","text":"","code":"show_segplotly(epcdata) {\"x\":{\"data\":[{\"x\":[1975,1976,1977,1978,1979,1980,1981,1982,1983,1984,1985,1986,1987,1988,1989,1990,1991,1992,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013,2014,2015,2016,2017,2018,2019,2020,2021,2022,2023],\"y\":[13.207539682539682,10.882222222222222,11.403666666666666,9.5151515151515156,17.99818181818182,13.870909090909091,12.029090909090909,12.989629629629629,17.540303030303029,9.1606666666666676,11.164333333333333,10.586619047619047,9.3042424242424246,8.1594444444444445,9.3469444444444445,9.3352696969696964,8.2859822510822507,7.8752870370370367,7.5887388888888889,9.4349166666666662,11.520738888888889,6.8479555555555551,8.3613944444444446,11.226705555555556,8.1310083333333338,7.1674944444444444,8.602955555555555,7.8252563492063487,11.717811538461538,11.810648015873015,8.4276190476190482,6.2816666666666663,8.637777777777778,9.2711111111111109,12.121111111111111,7.4423809523809528,11.413333333333334,7.8305555555555557,8.6644444444444453,7.8627777777777776,10.671111111111111,8.9866666666666664,9.5355555555555558,9.2166666666666668,9.7838888888888889,9.5346666666666664,9.4472222222222229,7.1233333333333331,6.2105555555555556],\"text\":[\"yr: 1975
yval: 13.207540
\",\"yr: 1976
yval: 10.882222
\",\"yr: 1977
yval: 11.403667
\",\"yr: 1978
yval: 9.515152
\",\"yr: 1979
yval: 17.998182
\",\"yr: 1980
yval: 13.870909
\",\"yr: 1981
yval: 12.029091
\",\"yr: 1982
yval: 12.989630
\",\"yr: 1983
yval: 17.540303
\",\"yr: 1984
yval: 9.160667
\",\"yr: 1985
yval: 11.164333
\",\"yr: 1986
yval: 10.586619
\",\"yr: 1987
yval: 9.304242
\",\"yr: 1988
yval: 8.159444
\",\"yr: 1989
yval: 9.346944
\",\"yr: 1990
yval: 9.335270
\",\"yr: 1991
yval: 8.285982
\",\"yr: 1992
yval: 7.875287
\",\"yr: 1993
yval: 7.588739
\",\"yr: 1994
yval: 9.434917
\",\"yr: 1995
yval: 11.520739
\",\"yr: 1996
yval: 6.847956
\",\"yr: 1997
yval: 8.361394
\",\"yr: 1998
yval: 11.226706
\",\"yr: 1999
yval: 8.131008
\",\"yr: 2000
yval: 7.167494
\",\"yr: 2001
yval: 8.602956
\",\"yr: 2002
yval: 7.825256
\",\"yr: 2003
yval: 11.717812
\",\"yr: 2004
yval: 11.810648
\",\"yr: 2005
yval: 8.427619
\",\"yr: 2006
yval: 6.281667
\",\"yr: 2007
yval: 8.637778
\",\"yr: 2008
yval: 9.271111
\",\"yr: 2009
yval: 12.121111
\",\"yr: 2010
yval: 7.442381
\",\"yr: 2011
yval: 11.413333
\",\"yr: 2012
yval: 7.830556
\",\"yr: 2013
yval: 8.664444
\",\"yr: 2014
yval: 7.862778
\",\"yr: 2015
yval: 10.671111
\",\"yr: 2016
yval: 8.986667
\",\"yr: 2017
yval: 9.535556
\",\"yr: 2018
yval: 9.216667
\",\"yr: 2019
yval: 9.783889
\",\"yr: 2020
yval: 9.534667
\",\"yr: 2021
yval: 9.447222
\",\"yr: 2022
yval: 7.123333
\",\"yr: 2023
yval: 6.210556
\"],\"type\":\"scatter\",\"mode\":\"markers+lines\",\"marker\":{\"autocolorscale\":false,\"color\":\"rgba(255,0,0,1)\",\"opacity\":1,\"size\":11.338582677165356,\"symbol\":\"circle\",\"line\":{\"width\":1.8897637795275593,\"color\":\"rgba(255,0,0,1)\"}},\"hoveron\":\"points\",\"name\":\"Annual Mean\",\"legendgroup\":\"Annual Mean\",\"showlegend\":true,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"line\":{\"width\":2.8346456692913389,\"color\":\"rgba(255,0,0,1)\",\"dash\":\"solid\"},\"frame\":null},{\"x\":[1974.51,2023.49],\"y\":[8.5,8.5],\"text\":\"trgnum: 8.5
colour: Management Target\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":1.8897637795275593,\"color\":\"rgba(0,0,255,1)\",\"dash\":\"solid\"},\"hoveron\":\"points\",\"name\":\"Management Target\",\"legendgroup\":\"Management Target\",\"showlegend\":true,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1974.51,2023.49],\"y\":[8.9000000000000004,8.9000000000000004],\"text\":\"smlnum: 8.9
colour: +1 se (small exceedance)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":1.8897637795275593,\"color\":\"rgba(0,0,255,1)\",\"dash\":\"dash\"},\"hoveron\":\"points\",\"name\":\"+1 se (small exceedance)\",\"legendgroup\":\"+1 se (small exceedance)\",\"showlegend\":true,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1974.51,2023.49],\"y\":[9.3000000000000007,9.3000000000000007],\"text\":\"thrnum: 9.3
colour: +2 se (large exceedance)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":1.8897637795275593,\"color\":\"rgba(0,0,255,1)\",\"dash\":\"dot\"},\"hoveron\":\"points\",\"name\":\"+2 se (large exceedance)\",\"legendgroup\":\"+2 se (large exceedance)\",\"showlegend\":true,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1986.5,1987.5,1987.5,1986.5,1986.5,null,1987.5,1988.5,1988.5,1987.5,1987.5,null,1989.5,1990.5,1990.5,1989.5,1989.5],\"y\":[0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5],\"text\":\"Action: Outcome: 0, Exceedance: none (size), long (length)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y2\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2007.5,2008.5,2008.5,2007.5,2007.5,null,2008.5,2009.5,2009.5,2008.5,2008.5,null,2014.5,2015.5,2015.5,2014.5,2014.5,null,2015.5,2016.5,2016.5,2015.5,2015.5,null,2016.5,2017.5,2017.5,2016.5,2016.5,null,2017.5,2018.5,2018.5,2017.5,2017.5,null,2018.5,2019.5,2019.5,2018.5,2018.5,null,2019.5,2020.5,2020.5,2019.5,2019.5,null,2020.5,2021.5,2021.5,2020.5,2020.5,null,2021.5,2022.5,2022.5,2021.5,2021.5,null,2022.5,2023.5,2023.5,2022.5,2022.5],\"y\":[0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5],\"text\":\"Action: Outcome: 0, Exceedance: none (size), none (length)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y2\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1987.5,1988.5,1988.5,1987.5,1987.5,null,1990.5,1991.5,1991.5,1990.5,1990.5,null,1991.5,1992.5,1992.5,1991.5,1991.5,null,1992.5,1993.5,1993.5,1992.5,1992.5,null,1995.5,1996.5,1996.5,1995.5,1995.5,null,1996.5,1997.5,1997.5,1996.5,1996.5,null,1998.5,1999.5,1999.5,1998.5,1998.5,null,1999.5,2000.5,2000.5,1999.5,1999.5,null,2000.5,2001.5,2001.5,2000.5,2000.5,null,2001.5,2002.5,2002.5,2001.5,2001.5,null,2004.5,2005.5,2005.5,2004.5,2004.5,null,2005.5,2006.5,2006.5,2005.5,2005.5,null,2006.5,2007.5,2007.5,2006.5,2006.5,null,2009.5,2010.5,2010.5,2009.5,2009.5,null,2011.5,2012.5,2012.5,2011.5,2011.5,null,2012.5,2013.5,2013.5,2012.5,2012.5,null,2013.5,2014.5,2014.5,2013.5,2013.5,null,2021.5,2022.5,2022.5,2021.5,2021.5,null,2022.5,2023.5,2023.5,2022.5,2022.5,null,1990.5,1991.5,1991.5,1990.5,1990.5,null,1991.5,1992.5,1992.5,1991.5,1991.5,null,1993.5,1994.5,1994.5,1993.5,1993.5,null,1996.5,1997.5,1997.5,1996.5,1996.5,null,1999.5,2000.5,2000.5,1999.5,1999.5,null,2004.5,2005.5,2005.5,2004.5,2004.5,null,2005.5,2006.5,2006.5,2005.5,2005.5,null,2006.5,2007.5,2007.5,2006.5,2006.5,null,2009.5,2010.5,2010.5,2009.5,2009.5,null,2011.5,2012.5,2012.5,2011.5,2011.5,null,2012.5,2013.5,2013.5,2012.5,2012.5,null,2013.5,2014.5,2014.5,2013.5,2013.5],\"y\":[2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5,null,0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5],\"text\":\"Action: Outcome: 0, Exceedance: none (size), short (length)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y2\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2007.5,2008.5,2008.5,2007.5,2007.5,null,2015.5,2016.5,2016.5,2015.5,2015.5],\"y\":[2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5],\"text\":\"Action: Outcome: 1, Exceedance: small (size), short (length)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y2\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1983.5,1984.5,1984.5,1983.5,1983.5,null,2017.5,2018.5,2018.5,2017.5,2017.5,null,2003.5,2004.5,2004.5,2003.5,2003.5],\"y\":[2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5,null,0.5,0.5,1.5,1.5,0.5],\"text\":\"Action: Outcome: 2, Exceedance: small (size), long (length)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y2\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1990.5,1991.5,1991.5,1990.5,1990.5,null,1999.5,2000.5,2000.5,1999.5,1999.5,null,2004.5,2005.5,2005.5,2004.5,2004.5,null,2005.5,2006.5,2006.5,2005.5,2005.5,null,2006.5,2007.5,2007.5,2006.5,2006.5,null,2009.5,2010.5,2010.5,2009.5,2009.5,null,2011.5,2012.5,2012.5,2011.5,2011.5,null,2012.5,2013.5,2013.5,2012.5,2012.5,null,2013.5,2014.5,2014.5,2013.5,2013.5,null,2021.5,2022.5,2022.5,2021.5,2021.5,null,2022.5,2023.5,2023.5,2022.5,2022.5],\"y\":[1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5],\"text\":\"Action: Stay the Course (chla: 0, la: 0)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y2\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1989.5,1990.5,1990.5,1989.5,1989.5],\"y\":[1.5,1.5,2.5,2.5,1.5],\"text\":\"Action: On Alert (chla: 2, la: 0)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y2\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1994.5,1995.5,1995.5,1994.5,1994.5,null,2002.5,2003.5,2003.5,2002.5,2002.5,null,2003.5,2004.5,2004.5,2003.5,2003.5,null,2010.5,2011.5,2011.5,2010.5,2010.5],\"y\":[1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5],\"text\":\"Action: On Alert (chla: 2, la: 2)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y2\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1983.5,1984.5,1984.5,1983.5,1983.5,null,1988.5,1989.5,1989.5,1988.5,1988.5,null,1997.5,1998.5,1998.5,1997.5,1997.5],\"y\":[1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5],\"text\":\"Action: On Alert (chla: 2, la: 3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y2\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1986.5,1987.5,1987.5,1986.5,1986.5],\"y\":[1.5,1.5,2.5,2.5,1.5],\"text\":\"Action: On Alert (chla: 3, la: 0)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y2\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1974.5,1975.5,1975.5,1974.5,1974.5],\"y\":[1.5,1.5,2.5,2.5,1.5],\"text\":\"Action: On Alert (chla: 3, la: 2)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y2\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1975.5,1976.5,1976.5,1975.5,1975.5,null,1976.5,1977.5,1977.5,1976.5,1976.5,null,1977.5,1978.5,1978.5,1977.5,1977.5,null,1978.5,1979.5,1979.5,1978.5,1978.5,null,1979.5,1980.5,1980.5,1979.5,1979.5,null,1980.5,1981.5,1981.5,1980.5,1980.5,null,1981.5,1982.5,1982.5,1981.5,1981.5,null,1982.5,1983.5,1983.5,1982.5,1982.5,null,1984.5,1985.5,1985.5,1984.5,1984.5,null,1985.5,1986.5,1986.5,1985.5,1985.5],\"y\":[1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5],\"text\":\"Action: On Alert (chla: 3, la: 3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y2\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1988.5,1989.5,1989.5,1988.5,1988.5,null,1989.5,1990.5,1990.5,1989.5,1989.5,null,1993.5,1994.5,1994.5,1993.5,1993.5,null,1994.5,1995.5,1995.5,1994.5,1994.5,null,1997.5,1998.5,1998.5,1997.5,1997.5,null,2002.5,2003.5,2003.5,2002.5,2002.5,null,2003.5,2004.5,2004.5,2003.5,2003.5,null,2008.5,2009.5,2009.5,2008.5,2008.5,null,2010.5,2011.5,2011.5,2010.5,2010.5,null,2014.5,2015.5,2015.5,2014.5,2014.5,null,2016.5,2017.5,2017.5,2016.5,2016.5,null,1974.5,1975.5,1975.5,1974.5,1974.5,null,1992.5,1993.5,1993.5,1992.5,1992.5,null,1994.5,1995.5,1995.5,1994.5,1994.5,null,1995.5,1996.5,1996.5,1995.5,1995.5,null,2000.5,2001.5,2001.5,2000.5,2000.5,null,2001.5,2002.5,2002.5,2001.5,2001.5,null,2002.5,2003.5,2003.5,2002.5,2002.5,null,2010.5,2011.5,2011.5,2010.5,2010.5],\"y\":[2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5,null,0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5],\"text\":\"Action: Outcome: 2, Exceedance: large (size), short (length)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y2\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1974.5,1975.5,1975.5,1974.5,1974.5,null,1975.5,1976.5,1976.5,1975.5,1975.5],\"y\":[2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5],\"text\":\"Action: Outcome: 3, Exceedance: large (size), NA 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1975
yval: 0.9780952
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yval: 1.1759318
\",\"yr: 1977
yval: 1.1896016
\",\"yr: 1978
yval: 1.1682173
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yval: 1.7595230
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yval: 1.3836268
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yval: 1.0469025
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yval: 1.0583860
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yval: 1.1152678
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yval: 1.1617502
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yval: 0.9534905
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yval: 0.8929313
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yval: 0.8536198
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yval: 0.8558599
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yval: 0.9374651
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yval: 0.8353229
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yval: 0.8031788
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yval: 0.8166729
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yval: 0.9133746
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yval: 0.7481484
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yval: 0.9379637
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yval: 0.9202700
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yval: 0.8473840
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yval: 1.0612729
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yval: 0.8801655
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yval: 0.7328166
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yval: 0.9512714
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yval: 0.9272802
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yval: 1.0370998
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yval: 0.8777406
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yval: 0.7693579
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yval: 0.6204267
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yval: 0.6771304
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yval: 0.6962244
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yval: 0.8076962
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yval: 0.8419635
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yval: 0.9122183
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yval: 0.6867633
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yval: 0.5674502
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yval: 0.6056886
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yval: 0.5604978
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yval: 0.5747356
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yval: 0.6821210
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yval: 0.6780425
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yval: 0.7396049
\",\"yr: 2020
yval: 0.7686231
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yval: 0.7783039
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yval: 0.7871073
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yval: 0.7344259
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(m-1)\",\"font\":{\"color\":\"rgba(0,0,0,1)\",\"family\":\"\",\"size\":14.611872146118724}},\"hoverformat\":\".2f\"},\"yaxis2\":{\"domain\":[0.41999999999999993,0.57999999999999996],\"automargin\":true,\"type\":\"linear\",\"autorange\":false,\"range\":[0.5,3.5],\"tickmode\":\"array\",\"ticktext\":[\"Light attenuation\",\"Management outcome\",\"Chlorophyll-a\"],\"tickvals\":[1,2,3],\"categoryorder\":\"array\",\"categoryarray\":[\"Light attenuation\",\"Management outcome\",\"Chlorophyll-a\"],\"nticks\":null,\"ticks\":\"outside\",\"tickcolor\":\"rgba(51,51,51,1)\",\"ticklen\":3.6529680365296811,\"tickwidth\":0.66417600664176002,\"showticklabels\":true,\"tickfont\":{\"color\":\"rgba(77,77,77,1)\",\"family\":\"\",\"size\":15.940224159402243},\"tickangle\":-0,\"showline\":false,\"linecolor\":null,\"linewidth\":0,\"showgrid\":true,\"gridcolor\":\"rgba(235,235,235,1)\",\"gridwidth\":0.66417600664176002,\"zeroline\":false,\"anchor\":\"x\",\"title\":{\"text\":\"\",\"font\":{\"color\":null,\"family\":null,\"size\":0}},\"hoverformat\":\".2f\"},\"yaxis\":{\"domain\":[0.62,1],\"automargin\":true,\"type\":\"linear\",\"autorange\":false,\"range\":[5.6211742424242424,18.587563131313132],\"tickmode\":\"array\",\"ticktext\":[\"6\",\"9\",\"12\",\"15\",\"18\"],\"tickvals\":[6,9,12,15,18],\"categoryorder\":\"array\",\"categoryarray\":[\"6\",\"9\",\"12\",\"15\",\"18\"],\"nticks\":null,\"ticks\":\"outside\",\"tickcolor\":\"rgba(51,51,51,1)\",\"ticklen\":3.6529680365296811,\"tickwidth\":0.66417600664176002,\"showticklabels\":true,\"tickfont\":{\"color\":\"rgba(77,77,77,1)\",\"family\":\"\",\"size\":11.68949771689498},\"tickangle\":-0,\"showline\":false,\"linecolor\":null,\"linewidth\":0,\"showgrid\":false,\"gridcolor\":null,\"gridwidth\":0,\"zeroline\":false,\"anchor\":\"x\",\"title\":{\"text\":\"Mean Ann. 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Adding new coordinate system, which will #> replace the existing one."},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sitesegmap.html","id":null,"dir":"Reference","previous_headings":"","what":"Map site and bay segment attainment categories for a selected year — show_sitesegmap","title":"Map site and bay segment attainment categories for a selected year — show_sitesegmap","text":"Map site bay segment attainment categories selected year","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sitesegmap.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Map site and bay segment attainment categories for a selected year — show_sitesegmap","text":"","code":"show_sitesegmap( epcdata, yrsel, param = c(\"chla\", \"la\"), trgs = NULL, thrs = FALSE, partialyr = FALSE, base_size = 12, family = NA )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sitesegmap.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Map site and bay segment attainment categories for a selected year — show_sitesegmap","text":"epcdata data frame epc data returned read_importwq yrsel numeric year plot param chr string parameter plot, one \"chla\" chlorophyll \"la\" light attenuation trgs optional data.frame annual bay segment water quality targets, defaults targets thrs logical indicating attainment category relative targets (default) thresholds, passed anlz_attainsite partialyr logical indicating incomplete annual data recent year approximated five year monthly averages parameter base_size numeric indicating text scaling size plot family optional chr string indicating font family text labels","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sitesegmap.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Map site and bay segment attainment categories for a selected year — show_sitesegmap","text":"static ggplot object returned","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sitesegmap.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Map site and bay segment attainment categories for a selected year — show_sitesegmap","text":"map similar returned show_sitemap addition polygons bay segment colored annual attainment category site points sized relative selected parameter param.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sitesegmap.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Map site and bay segment attainment categories for a selected year — show_sitesegmap","text":"","code":"show_sitesegmap(epcdata, yrsel = 2023) #> Coordinate system already present. Adding new coordinate system, which will #> replace the existing one."},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbbimatrix.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot a matrix of Tampa Bay Benthic Index scores over time by bay segment — show_tbbimatrix","title":"Plot a matrix of Tampa Bay Benthic Index scores over time by bay segment — show_tbbimatrix","text":"Plot matrix Tampa Bay Benthic Index scores time bay segment","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbbimatrix.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot a matrix of Tampa Bay Benthic Index scores over time by bay segment — show_tbbimatrix","text":"","code":"show_tbbimatrix( tbbiscr, bay_segment = c(\"HB\", \"OTB\", \"MTB\", \"LTB\", \"TCB\", \"MR\", \"BCB\", \"All\", \"All (wt)\"), yrrng = c(1993, 2022), alph = 1, txtsz = 3, family = NA, rev = FALSE, position = \"top\", plotly = FALSE, width = NULL, height = NULL )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbbimatrix.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot a matrix of Tampa Bay Benthic Index scores over time by bay segment — show_tbbimatrix","text":"tbbiscr input data frame returned anlz_tbbiscr bay_segment chr string bay segment, one many \"HB\", \"OTB\", \"MTB\", \"LTB\", \"TCB\", \"MR\", \"BCB\", \"\", \"(wt)\" yrrng numeric indicating year ranges evaluate alph numeric indicating alpha value score category colors txtsz numeric size text plot family optional chr string indicating font family text labels rev logical factor levels bay segments reversed position chr string location bay segment labels, default top, passed scale_x_discrete plotly logical matrix created using plotly width numeric width plot pixels, applies plotly = TRUE height numeric height plot pixels, applies plotly = TRUE","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbbimatrix.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot a matrix of Tampa Bay Benthic Index scores over time by bay segment — show_tbbimatrix","text":"ggplot object showing trends time TBBI scores bay segment plotly = FALSE, otherwise plotly object","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbbimatrix.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Plot a matrix of Tampa Bay Benthic Index scores over time by bay segment — show_tbbimatrix","text":"Additional summaries provided entire bay, summary across categories (\"\") summary weighted across relative sizes bay segment (\"(wt)\").","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbbimatrix.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot a matrix of Tampa Bay Benthic Index scores over time by bay segment — show_tbbimatrix","text":"","code":"tbbiscr <- anlz_tbbiscr(benthicdata) show_tbbimatrix(tbbiscr)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbnimatrix.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot a matrix of Tampa Bay Nekton Index scores over time by bay segment — show_tbnimatrix","title":"Plot a matrix of Tampa Bay Nekton Index scores over time by bay segment — show_tbnimatrix","text":"Plot matrix Tampa Bay Nekton Index scores time bay segment","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbnimatrix.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot a matrix of Tampa Bay Nekton Index scores over time by bay segment — show_tbnimatrix","text":"","code":"show_tbnimatrix( tbniscr, bay_segment = c(\"OTB\", \"HB\", \"MTB\", \"LTB\"), perc = c(32, 46), alph = 1, txtsz = 3, family = NA, rev = FALSE, position = \"top\", plotly = FALSE, width = NULL, height = NULL )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbnimatrix.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot a matrix of Tampa Bay Nekton Index scores over time by bay segment — show_tbnimatrix","text":"tbniscr input data frame returned anlz_tbniscr bay_segment chr string bay segment, one many \"OTB\", \"HB\", \"MTB\", \"LTB\" perc numeric values indicating break points score categories alph numeric indicating alpha value score category colors txtsz numeric size text plot family optional chr string indicating font family text labels rev logical factor levels bay segments reversed position chr string location bay segment labels, default top, passed scale_x_discrete plotly logical matrix created using plotly width numeric width plot pixels, applies plotly = TRUE height numeric height plot pixels, applies plotly = TRUE","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbnimatrix.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot a matrix of Tampa Bay Nekton Index scores over time by bay segment — show_tbnimatrix","text":"ggplot object showing trends time TBNI scores bay segment","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbnimatrix.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot a matrix of Tampa Bay Nekton Index scores over time by bay segment — show_tbnimatrix","text":"","code":"tbniscr <- anlz_tbniscr(fimdata) show_tbnimatrix(tbniscr)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbniscr.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot Tampa Bay Nekton Index scores over time by bay segment — show_tbniscr","title":"Plot Tampa Bay Nekton Index scores over time by bay segment — show_tbniscr","text":"Plot Tampa Bay Nekton Index scores time bay segment","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbniscr.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot Tampa Bay Nekton Index scores over time by bay segment — show_tbniscr","text":"","code":"show_tbniscr( tbniscr, bay_segment = c(\"OTB\", \"HB\", \"MTB\", \"LTB\"), perc = c(32, 46), alph = 1, ylim = c(22, 58), rev = FALSE, plotly = FALSE, family = NA, width = NULL, height = NULL )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbniscr.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot Tampa Bay Nekton Index scores over time by bay segment — show_tbniscr","text":"tbniscr input dat frame returned anlz_tbniscr bay_segment chr string bay segment, one many \"OTB\", \"HB\", \"MTB\", \"LTB\" perc numeric values indicating break points score categories alph numeric indicating alpha value score category colors ylim numeric y axis limits rev logical factor levels bay segments reversed plotly logical matrix created using plotly family optional chr string indicating font family text labels width numeric width plot pixels, applies plotly = TRUE height numeric height plot pixels, applies plotly = TRUE","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbniscr.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot Tampa Bay Nekton Index scores over time by bay segment — show_tbniscr","text":"ggplot object showing trends time TBNI scores bay segment plotly object plotly = TRUE","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbniscr.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot Tampa Bay Nekton Index scores over time by bay segment — show_tbniscr","text":"","code":"tbniscr <- anlz_tbniscr(fimdata) show_tbniscr(tbniscr)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbniscrall.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot Tampa Bay Nekton Index scores over time as average across bay segments — show_tbniscrall","title":"Plot Tampa Bay Nekton Index scores over time as average across bay segments — show_tbniscrall","text":"Plot Tampa Bay Nekton Index scores time average across bay segments","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbniscrall.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot Tampa Bay Nekton Index scores over time as average across bay segments — show_tbniscrall","text":"","code":"show_tbniscrall( tbniscr, perc = c(32, 46), alph = 1, ylim = c(22, 58), rev = FALSE, plotly = FALSE )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbniscrall.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot Tampa Bay Nekton Index scores over time as average across bay segments — show_tbniscrall","text":"tbniscr input dat frame returned anlz_tbniscr perc numeric values indicating break points score categories alph numeric indicating alpha value score category colors ylim numeric y axis limits rev logical factor levels bay segments reversed plotly logical matrix created using plotly","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbniscrall.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot Tampa Bay Nekton Index scores over time as average across bay segments — show_tbniscrall","text":"ggplot object showing trends time TBNI scores bay segment plotly object plotly = TRUE","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbniscrall.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot Tampa Bay Nekton Index scores over time as average across bay segments — show_tbniscrall","text":"","code":"tbniscr <- anlz_tbniscr(fimdata) show_tbniscrall(tbniscr)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbniscrplotly.html","id":null,"dir":"Reference","previous_headings":"","what":"Creates a plotly object for TBNI score plots — show_tbniscrplotly","title":"Creates a plotly object for TBNI score plots — show_tbniscrplotly","text":"Creates plotly object TBNI score plots","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbniscrplotly.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Creates a plotly object for TBNI score plots — show_tbniscrplotly","text":"","code":"show_tbniscrplotly(p, width = NULL, height = NULL)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbniscrplotly.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Creates a plotly object for TBNI score plots — show_tbniscrplotly","text":"p ggplot object output show_tbniscr show_tbniscrall width numeric width plot pixels height numeric height plot pixels","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbniscrplotly.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Creates a plotly object for TBNI score plots — show_tbniscrplotly","text":"plotly data object","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbniscrplotly.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Creates a plotly object for TBNI score plots — show_tbniscrplotly","text":"","code":"tbniscr <- anlz_tbniscr(fimdata) p <- show_tbniscrall(tbniscr) show_tbniscrplotly(p) {\"x\":{\"data\":[{\"x\":[null,null,null,null,null],\"y\":[null,32,32,null,null],\"text\":\"\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":1.8897637795275593,\"color\":\"transparent\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[null,null,null,null,null],\"y\":[32,46,46,32,32],\"text\":\"\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":1.8897637795275593,\"color\":\"transparent\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(233,195,24,1)\",\"hoveron\":\"fills\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[null,null,null,null,null],\"y\":[46,null,null,46,46],\"text\":\"\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":1.8897637795275593,\"color\":\"transparent\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013,2014,2015,2016,2017,2018,2019,2020,2021,2022,2022,2022,2021,2020,2019,2018,2017,2016,2015,2014,2013,2012,2011,2010,2009,2008,2007,2006,2005,2004,2003,2002,2001,2000,1999,1998,1998],\"y\":[48.174950433812491,46.192337273030297,44.217869520888684,44.229008941917506,43.204367555768769,44.148572079700592,46.152576099067943,35.683114999086001,40.584732027839848,41.632627529473545,41.549822206241068,43.557168715487762,47.609344686978943,46.5018316384119,43.507500585323129,45.544100152872986,47.54256747670842,50.540419554927652,50.541400523731063,47.53002481033797,46.513396602793662,44.524343009674809,46.471601172555538,40.588221540118596,40.635566525640456,40.635566525640456,43.364433474359544,43.411778459881404,49.528398827444462,47.475656990325191,49.486603397206338,50.46997518966203,53.458599476268937,53.459580445072348,50.45743252329158,48.455899847127014,46.492499414676871,49.4981683615881,50.390655313021057,46.442831284512238,44.450177793758932,44.367372470526455,43.415267972160152,38.316885000913999,49.847423900932057,47.851427920299408,46.795632444231231,47.770991058082494,47.782130479111316,49.807662726969703,51.825049566187509,48.174950433812491],\"text\":[\"Year: 1998
TBNI_Score - seval: 48.17495
TBNI_Score + seval: 51.82505\",\"Year: 1999
TBNI_Score - seval: 46.19234
TBNI_Score + seval: 49.80766\",\"Year: 2000
TBNI_Score - seval: 44.21787
TBNI_Score + seval: 47.78213\",\"Year: 2001
TBNI_Score - seval: 44.22901
TBNI_Score + seval: 47.77099\",\"Year: 2002
TBNI_Score - seval: 43.20437
TBNI_Score + seval: 46.79563\",\"Year: 2003
TBNI_Score - seval: 44.14857
TBNI_Score + seval: 47.85143\",\"Year: 2004
TBNI_Score - seval: 46.15258
TBNI_Score + seval: 49.84742\",\"Year: 2005
TBNI_Score - seval: 35.68311
TBNI_Score + seval: 38.31689\",\"Year: 2006
TBNI_Score - seval: 40.58473
TBNI_Score + seval: 43.41527\",\"Year: 2007
TBNI_Score - seval: 41.63263
TBNI_Score + seval: 44.36737\",\"Year: 2008
TBNI_Score - seval: 41.54982
TBNI_Score + seval: 44.45018\",\"Year: 2009
TBNI_Score - seval: 43.55717
TBNI_Score + seval: 46.44283\",\"Year: 2010
TBNI_Score - seval: 47.60934
TBNI_Score + seval: 50.39066\",\"Year: 2011
TBNI_Score - seval: 46.50183
TBNI_Score + seval: 49.49817\",\"Year: 2012
TBNI_Score - seval: 43.50750
TBNI_Score + seval: 46.49250\",\"Year: 2013
TBNI_Score - seval: 45.54410
TBNI_Score + seval: 48.45590\",\"Year: 2014
TBNI_Score - seval: 47.54257
TBNI_Score + seval: 50.45743\",\"Year: 2015
TBNI_Score - seval: 50.54042
TBNI_Score + seval: 53.45958\",\"Year: 2016
TBNI_Score - seval: 50.54140
TBNI_Score + seval: 53.45860\",\"Year: 2017
TBNI_Score - seval: 47.53002
TBNI_Score + seval: 50.46998\",\"Year: 2018
TBNI_Score - seval: 46.51340
TBNI_Score + seval: 49.48660\",\"Year: 2019
TBNI_Score - seval: 44.52434
TBNI_Score + seval: 47.47566\",\"Year: 2020
TBNI_Score - seval: 46.47160
TBNI_Score + seval: 49.52840\",\"Year: 2021
TBNI_Score - seval: 40.58822
TBNI_Score + seval: 43.41178\",\"Year: 2022
TBNI_Score - seval: 40.63557
TBNI_Score + seval: 43.36443\",\"Year: 2022
TBNI_Score - seval: 40.63557
TBNI_Score + seval: 43.36443\",\"Year: 2022
TBNI_Score - seval: 40.63557
TBNI_Score + seval: 43.36443\",\"Year: 2021
TBNI_Score - seval: 40.58822
TBNI_Score + seval: 43.41178\",\"Year: 2020
TBNI_Score - seval: 46.47160
TBNI_Score + seval: 49.52840\",\"Year: 2019
TBNI_Score - seval: 44.52434
TBNI_Score + seval: 47.47566\",\"Year: 2018
TBNI_Score - seval: 46.51340
TBNI_Score + seval: 49.48660\",\"Year: 2017
TBNI_Score - seval: 47.53002
TBNI_Score + seval: 50.46998\",\"Year: 2016
TBNI_Score - seval: 50.54140
TBNI_Score + seval: 53.45860\",\"Year: 2015
TBNI_Score - seval: 50.54042
TBNI_Score + seval: 53.45958\",\"Year: 2014
TBNI_Score - seval: 47.54257
TBNI_Score + seval: 50.45743\",\"Year: 2013
TBNI_Score - seval: 45.54410
TBNI_Score + seval: 48.45590\",\"Year: 2012
TBNI_Score - seval: 43.50750
TBNI_Score + seval: 46.49250\",\"Year: 2011
TBNI_Score - seval: 46.50183
TBNI_Score + seval: 49.49817\",\"Year: 2010
TBNI_Score - seval: 47.60934
TBNI_Score + seval: 50.39066\",\"Year: 2009
TBNI_Score - seval: 43.55717
TBNI_Score + seval: 46.44283\",\"Year: 2008
TBNI_Score - seval: 41.54982
TBNI_Score + seval: 44.45018\",\"Year: 2007
TBNI_Score - seval: 41.63263
TBNI_Score + seval: 44.36737\",\"Year: 2006
TBNI_Score - seval: 40.58473
TBNI_Score + seval: 43.41527\",\"Year: 2005
TBNI_Score - seval: 35.68311
TBNI_Score + seval: 38.31689\",\"Year: 2004
TBNI_Score - seval: 46.15258
TBNI_Score + seval: 49.84742\",\"Year: 2003
TBNI_Score - seval: 44.14857
TBNI_Score + seval: 47.85143\",\"Year: 2002
TBNI_Score - seval: 43.20437
TBNI_Score + seval: 46.79563\",\"Year: 2001
TBNI_Score - seval: 44.22901
TBNI_Score + seval: 47.77099\",\"Year: 2000
TBNI_Score - seval: 44.21787
TBNI_Score + seval: 47.78213\",\"Year: 1999
TBNI_Score - seval: 46.19234
TBNI_Score + seval: 49.80766\",\"Year: 1998
TBNI_Score - seval: 48.17495
TBNI_Score + seval: 51.82505\",\"Year: 1998
TBNI_Score - seval: 48.17495
TBNI_Score + seval: 51.82505\"],\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":1.8897637795275593,\"color\":\"transparent\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(224,224,224,1)\",\"hoveron\":\"points\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013,2014,2015,2016,2017,2018,2019,2020,2021,2022],\"y\":[50,48,46,46,45,46,48,37,42,43,43,45,49,48,45,47,49,52,52,49,48,46,48,42,42],\"text\":[\"Year: 1998
TBNI_Score: 50\",\"Year: 1999
TBNI_Score: 48\",\"Year: 2000
TBNI_Score: 46\",\"Year: 2001
TBNI_Score: 46\",\"Year: 2002
TBNI_Score: 45\",\"Year: 2003
TBNI_Score: 46\",\"Year: 2004
TBNI_Score: 48\",\"Year: 2005
TBNI_Score: 37\",\"Year: 2006
TBNI_Score: 42\",\"Year: 2007
TBNI_Score: 43\",\"Year: 2008
TBNI_Score: 43\",\"Year: 2009
TBNI_Score: 45\",\"Year: 2010
TBNI_Score: 49\",\"Year: 2011
TBNI_Score: 48\",\"Year: 2012
TBNI_Score: 45\",\"Year: 2013
TBNI_Score: 47\",\"Year: 2014
TBNI_Score: 49\",\"Year: 2015
TBNI_Score: 52\",\"Year: 2016
TBNI_Score: 52\",\"Year: 2017
TBNI_Score: 49\",\"Year: 2018
TBNI_Score: 48\",\"Year: 2019
TBNI_Score: 46\",\"Year: 2020
TBNI_Score: 48\",\"Year: 2021
TBNI_Score: 42\",\"Year: 2022
TBNI_Score: 42\"],\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":4.7244094488188981,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"hoveron\":\"points\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1997.375,1997.375,1997.375,1997.375,1997.375,1997.375,1997.375,1997.375,1997.375,1997.375,1997.375,1997.375,1997.375,1997.375,1997.375,1997.375,1997.375,1997.375,1997.375,1997.375,1997.375,1997.375,1997.375,1997.375,1997.375,2022.625,2022.625,2022.625,2022.625,2022.625,2022.625,2022.625,2022.625,2022.625,2022.625,2022.625,2022.625,2022.625,2022.625,2022.625,2022.625,2022.625,2022.625,2022.625,2022.625,2022.625,2022.625,2022.625,2022.625,2022.625],\"y\":[32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32],\"text\":\"perc[1]: 32\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":1.8897637795275593,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"dot\"},\"hoveron\":\"points\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1997.375,1997.375,1997.375,1997.375,1997.375,1997.375,1997.375,1997.375,1997.375,1997.375,1997.375,1997.375,1997.375,1997.375,1997.375,1997.375,1997.375,1997.375,1997.375,1997.375,1997.375,1997.375,1997.375,1997.375,1997.375,2022.625,2022.625,2022.625,2022.625,2022.625,2022.625,2022.625,2022.625,2022.625,2022.625,2022.625,2022.625,2022.625,2022.625,2022.625,2022.625,2022.625,2022.625,2022.625,2022.625,2022.625,2022.625,2022.625,2022.625,2022.625],\"y\":[46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46],\"text\":\"perc[2]: 46\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":1.8897637795275593,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"dot\"},\"hoveron\":\"points\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null}],\"layout\":{\"margin\":{\"t\":23.305936073059364,\"r\":7.3059360730593621,\"b\":42.839352428393525,\"l\":41.511000415110004},\"plot_bgcolor\":\"rgba(235,235,235,1)\",\"paper_bgcolor\":\"rgba(255,255,255,1)\",\"font\":{\"color\":\"rgba(0,0,0,1)\",\"family\":\"\",\"size\":14.611872146118724},\"xaxis\":{\"domain\":[0,1],\"automargin\":true,\"type\":\"linear\",\"autorange\":false,\"range\":[1997.375,2022.625],\"tickmode\":\"array\",\"ticktext\":[\"1998\",\"1999\",\"2000\",\"2001\",\"2002\",\"2003\",\"2004\",\"2005\",\"2006\",\"2007\",\"2008\",\"2009\",\"2010\",\"2011\",\"2012\",\"2013\",\"2014\",\"2015\",\"2016\",\"2017\",\"2018\",\"2019\",\"2020\",\"2021\",\"2022\"],\"tickvals\":[1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013,2014,2015,2016,2017,2018,2019,2020,2021,2022],\"categoryorder\":\"array\",\"categoryarray\":[\"1998\",\"1999\",\"2000\",\"2001\",\"2002\",\"2003\",\"2004\",\"2005\",\"2006\",\"2007\",\"2008\",\"2009\",\"2010\",\"2011\",\"2012\",\"2013\",\"2014\",\"2015\",\"2016\",\"2017\",\"2018\",\"2019\",\"2020\",\"2021\",\"2022\"],\"nticks\":null,\"ticks\":\"outside\",\"tickcolor\":\"rgba(51,51,51,1)\",\"ticklen\":3.6529680365296811,\"tickwidth\":0.66417600664176002,\"showticklabels\":true,\"tickfont\":{\"color\":\"rgba(77,77,77,1)\",\"family\":\"\",\"size\":15.940224159402243},\"tickangle\":-90,\"showline\":false,\"linecolor\":null,\"linewidth\":0,\"showgrid\":false,\"gridcolor\":null,\"gridwidth\":0,\"zeroline\":false,\"anchor\":\"y\",\"title\":{\"text\":\"\",\"font\":{\"color\":null,\"family\":null,\"size\":0}},\"hoverformat\":\".2f\"},\"yaxis\":{\"domain\":[0,1],\"automargin\":true,\"type\":\"linear\",\"autorange\":false,\"range\":[20.199999999999999,59.799999999999997],\"tickmode\":\"array\",\"ticktext\":[\"22\",\"26\",\"30\",\"34\",\"38\",\"42\",\"46\",\"50\",\"54\",\"58\"],\"tickvals\":[22,26,30,34,38,42,46,50,54,58],\"categoryorder\":\"array\",\"categoryarray\":[\"22\",\"26\",\"30\",\"34\",\"38\",\"42\",\"46\",\"50\",\"54\",\"58\"],\"nticks\":null,\"ticks\":\"outside\",\"tickcolor\":\"rgba(51,51,51,1)\",\"ticklen\":3.6529680365296811,\"tickwidth\":0.66417600664176002,\"showticklabels\":true,\"tickfont\":{\"color\":\"rgba(77,77,77,1)\",\"family\":\"\",\"size\":15.940224159402243},\"tickangle\":-0,\"showline\":false,\"linecolor\":null,\"linewidth\":0,\"showgrid\":false,\"gridcolor\":null,\"gridwidth\":0,\"zeroline\":false,\"anchor\":\"x\",\"title\":{\"text\":\"TBNI 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show_tdlcrk","text":"Make map tidal creek report card","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrk.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Make a map for tidal creek report card — show_tdlcrk","text":"","code":"show_tdlcrk(dat, weight = 1.5)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrk.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Make a map for tidal creek report card — show_tdlcrk","text":"dat input creek score data returned anlz_tdlcrk weight numeric weight polylines, passed addPolylines","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrk.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Make a map for tidal creek report card — show_tdlcrk","text":"leaflet object","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrk.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Make a map for tidal creek report card — show_tdlcrk","text":"","code":"dat <- anlz_tdlcrk(tidalcreeks, iwrraw, yr = 2023) show_tdlcrk(dat) 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Monitor\",\"WBID: 2073, JEI: CC110, Name: NA, Creek score: No Data\",\"WBID: 2065B, JEI: CC111, Name: NA, Creek score: No Data\",\"WBID: 2074B, JEI: CC111, Name: NA, Creek score: No Data\",\"WBID: 2077, JEI: CC111, Name: NA, Creek score: No Data\",\"WBID: 1991B, JEI: CC15, Name: Rock Creek, Creek score: No Data\",\"WBID: 2045, JEI: CC15, Name: Rock Creek, Creek score: Monitor\",\"WBID: 1991B, JEI: CC16, Name: Apollo Waterway, Creek score: No Data\",\"WBID: 2010B, JEI: CC16, Name: Apollo Waterway, Creek score: No Data\",\"WBID: 2025, JEI: CC16, Name: Apollo Waterway, Creek score: No Data\",\"WBID: 2043, JEI: CC16, Name: Apollo Waterway, Creek score: Monitor\",\"WBID: 1991A, JEI: CC17, Name: NA, Creek score: No Data\",\"WBID: 1991B, JEI: CC17, Name: NA, Creek score: No Data\",\"WBID: 2048A, JEI: CC18, Name: Sam Knight Creek, Creek score: Monitor\",\"WBID: 2055, JEI: CC18, Name: Sam Knight Creek, Creek score: No Data\",\"WBID: 2048A, JEI: CC19, Name: Sam Knight Creek, Creek score: No Data\",\"WBID: 2055, JEI: CC19, Name: Sam Knight Creek, Creek score: No Data\",\"WBID: 2048A, JEI: CC20, Name: NA, Creek score: No Data\",\"WBID: 2055, JEI: CC20, Name: NA, Creek score: No Data\",\"WBID: 2048B, JEI: CC21, Name: Huckaby Creek, Creek score: No Data\",\"WBID: 2055, JEI: CC21, Name: Huckaby Creek, Creek score: No Data\",\"WBID: 2048C, JEI: CC22, Name: NA, Creek score: No Data\",\"WBID: 2055, JEI: CC22, Name: NA, Creek score: No Data\",\"WBID: 2047, JEI: CC23, Name: NA, Creek score: No Data\",\"WBID: 2055, JEI: CC23, Name: NA, Creek score: No Data\",\"WBID: 2047, JEI: CC24, Name: NA, Creek score: No Data\",\"WBID: 2055, JEI: CC24, Name: NA, Creek score: No Data\",\"WBID: 2060A1, JEI: CC25, Name: NA, Creek score: Investigate\",\"WBID: 2060A1, JEI: CC26, Name: NA, Creek score: No Data\",\"WBID: 2060A1, JEI: CC27, Name: NA, Creek score: No Data\",\"WBID: 2060A2, JEI: CC27, Name: NA, Creek score: No Data\",\"WBID: 2060, JEI: CC28, Name: NA, Creek score: No Data\",\"WBID: 2047, JEI: CC29, Name: NA, Creek score: No Data\",\"WBID: 2060, JEI: CC29, Name: NA, Creek score: No Data\",\"WBID: 2047, JEI: CC30, Name: NA, Creek score: No Data\",\"WBID: 2056D, JEI: CC30, Name: NA, Creek score: No Data\",\"WBID: 2060, JEI: CC30, Name: NA, Creek score: No Data\",\"WBID: 2046, JEI: CC31, Name: NA, Creek score: Monitor\",\"WBID: 2056D, JEI: CC34, Name: Little Alligator Creek, Creek score: No Data\",\"WBID: 2056E, JEI: CC34, Name: Little Alligator Creek, Creek score: Monitor\",\"WBID: 2056D, JEI: CC36, Name: NA, Creek score: No Data\",\"WBID: 2056E, JEI: CC36, Name: NA, Creek score: Monitor\",\"WBID: 2056E, JEI: CC37, Name: NA, Creek score: Monitor\",\"WBID: 2056E, JEI: CC40, Name: NA, Creek score: No Data\",\"WBID: 2056E, JEI: CC41, Name: NA, Creek score: No Data\",\"WBID: 2056B, JEI: CC42, Name: NA, Creek score: No Data\",\"WBID: 2056E, JEI: CC42, Name: NA, Creek score: Monitor\",\"WBID: 2056C2, JEI: CC44, Name: NA, Creek score: No Data\",\"WBID: 2056C2, JEI: CC45, Name: NA, Creek score: Prioritize\",\"WBID: 2056E, JEI: CC45, Name: NA, Creek score: No Data\",\"WBID: 2056C2, JEI: CC46, Name: NA, Creek score: No Data\",\"WBID: 2056C1, JEI: CC47, Name: NA, Creek score: No Data\",\"WBID: 2065C, JEI: CC48, Name: NA, Creek score: No Data\",\"WBID: 2080, JEI: CC48, Name: NA, Creek score: No Data\",\"WBID: 2087, JEI: CC48, Name: NA, Creek score: No Data\",\"WBID: 1991B, JEI: CC49, Name: NA, Creek score: No Data\",\"WBID: 1991A, JEI: CC50, Name: NA, Creek score: No Data\",\"WBID: 2053, JEI: CC50, Name: NA, Creek score: Monitor\",\"WBID: 2055, JEI: CC50, Name: NA, Creek score: No Data\",\"WBID: 2041A, JEI: CC51, Name: NA, Creek score: No Data\",\"WBID: 2041A, JEI: CC52, Name: NA, Creek score: No Data\",\"WBID: 2041A, JEI: CC53, Name: Myrtle Slough, Creek score: No Data\",\"WBID: 2054, JEI: CC53, Name: Myrtle Slough, Creek score: Monitor\",\"WBID: 2041A, JEI: CC54, Name: NA, Creek score: No Data\",\"WBID: 2059, JEI: CC55, Name: NA, Creek score: Monitor\",\"WBID: 2059, JEI: CC56, Name: NA, Creek score: Investigate\",\"WBID: 2062, JEI: CC57, Name: North Fork Alligator Creek, Creek score: No Data\",\"WBID: 2063, JEI: CC57, Name: North Fork Alligator Creek, Creek score: No Data\",\"WBID: 2065A, JEI: CC61, Name: NA, Creek score: No Data\",\"WBID: 2073, JEI: CC61, Name: NA, Creek score: No Data\",\"WBID: 2073, JEI: CC62, Name: NA, Creek score: No Data\",\"WBID: 2065B, JEI: CC63, Name: NA, Creek score: No Data\",\"WBID: 2073, JEI: CC63, Name: NA, Creek score: No Data\",\"WBID: 2063, JEI: CC64, Name: North Fork Alligator Creek, Creek score: Monitor\",\"WBID: 2074B, JEI: CC64, Name: North Fork Alligator Creek, Creek score: No Data\",\"WBID: 2074, JEI: CC65, Name: Alligator Creek, Creek score: Monitor\",\"WBID: 2074B, JEI: CC65, Name: Alligator Creek, Creek score: Monitor\",\"WBID: 2077, JEI: CC65, Name: Alligator Creek, Creek score: No Data\",\"WBID: 2065B, JEI: CC66, Name: Whidden Branch/Alligator Creek, Creek score: No Data\",\"WBID: 2074B, JEI: CC66, Name: Whidden Branch/Alligator Creek, Creek score: No Data\",\"WBID: 2077, JEI: CC66, Name: Whidden Branch/Alligator Creek, Creek score: No Data\",\"WBID: 2081, JEI: CC66, Name: Whidden Branch/Alligator Creek, Creek score: No Data\",\"WBID: 2065B, JEI: CC67, Name: South Silcox Creek, Creek score: Monitor\",\"WBID: 2081, JEI: CC67, Name: South Silcox Creek, Creek score: Monitor\",\"WBID: 2084, JEI: CC67, Name: South Silcox Creek, Creek score: No Data\",\"WBID: 2065B, JEI: CC68, Name: Big Mound Creek, Creek score: No Data\",\"WBID: 2084, JEI: CC68, Name: Big Mound Creek, Creek score: No Data\",\"WBID: 2084, JEI: CC69, Name: NA, Creek score: No Data\",\"WBID: 2086, JEI: CC69, Name: NA, Creek score: No Data\",\"WBID: 2088, JEI: CC69, Name: NA, Creek score: No Data\",\"WBID: 2065B, JEI: CC70, Name: Pirate Canal, Creek score: No Data\",\"WBID: 2082A, JEI: CC70, Name: Pirate Canal, Creek score: Monitor\",\"WBID: 2065B, JEI: CC71, Name: NA, Creek score: No Data\",\"WBID: 2094, JEI: CC72, Name: Bear Branch, Creek score: No Data\",\"WBID: 2093A, JEI: CC73, Name: Hog Branch, Creek score: No Data\",\"WBID: 2079, JEI: CC74, Name: Whidden Creek, Creek score: Monitor\",\"WBID: 2065B, JEI: CC75, Name: NA, Creek score: No Data\",\"WBID: 2065B, JEI: CC76, Name: NA, Creek score: No Data\",\"WBID: 2066, JEI: CC76, Name: NA, Creek score: No Data\",\"WBID: 1983B, JEI: CC77, Name: Lemon Creek, Creek score: Monitor\",\"WBID: 2076, JEI: CC77, Name: Lemon Creek, Creek score: Prioritize\",\"WBID: 2089, JEI: CC78, Name: NA, Creek score: No Data\",\"WBID: 2065C, JEI: CC79, Name: NA, Creek score: No Data\",\"WBID: 2066, JEI: CC79, Name: NA, Creek score: No Data\",\"WBID: 2065C, JEI: CC80, Name: NA, Creek score: No Data\",\"WBID: 2065C, JEI: CC81, Name: NA, Creek score: No Data\",\"WBID: 2065C, JEI: CC82, Name: NA, Creek score: No Data\",\"WBID: 2065C, JEI: CC83, Name: NA, Creek score: No Data\",\"WBID: 2065B, JEI: CC84, Name: NA, Creek score: No Data\",\"WBID: 2065B, JEI: CC85, Name: NA, Creek score: No Data\",\"WBID: 2065A, JEI: CC86, Name: NA, Creek score: No Data\",\"WBID: 2066, JEI: CC86, Name: NA, Creek score: No Data\",\"WBID: 2066, JEI: CC87, Name: NA, Creek score: No Data\",\"WBID: 1991B, JEI: CC88, Name: NA, Creek score: No Data\",\"WBID: 1991B, JEI: CC89, Name: NA, Creek score: No Data\",\"WBID: 2055, JEI: CC90, Name: NA, Creek score: No Data\",\"WBID: 2048B, JEI: CC91, Name: NA, Creek score: No Data\",\"WBID: 2048A, JEI: CC91, Name: NA, Creek score: No Data\",\"WBID: 2055, JEI: CC91, Name: NA, Creek score: No Data\",\"WBID: 2048C, JEI: CC92, Name: Flopbuck Creek, Creek score: No Data\",\"WBID: 2055, JEI: CC92, Name: Flopbuck Creek, Creek score: No Data\",\"WBID: 2048C, JEI: CC93, Name: NA, Creek score: No Data\",\"WBID: 2055, JEI: CC93, Name: NA, Creek score: No Data\",\"WBID: 2047, JEI: CC94, Name: NA, Creek score: No Data\",\"WBID: 2055, JEI: CC94, Name: NA, Creek score: No Data\",\"WBID: 2060A2, JEI: CC95, Name: NA, Creek score: No Data\",\"WBID: 2056E, JEI: CC96, Name: NA, Creek score: No Data\",\"WBID: 2056E, JEI: CC97, Name: NA, Creek score: No Data\",\"WBID: 2056D, JEI: CC98, Name: NA, Creek score: No Data\",\"WBID: 2056E, JEI: CC98, Name: NA, Creek score: No Data\",\"WBID: 2056E, JEI: CC99, Name: NA, Creek score: No Data\",\"WBID: 1623A, JEI: DC01, Name: NA, Creek score: No Data\",\"WBID: 2033, JEI: DC01, Name: NA, Creek score: Monitor\",\"WBID: 1623A, JEI: DC02, Name: NA, Creek score: No Data\",\"WBID: 1623A, JEI: DC03, Name: NA, Creek score: No Data\",\"WBID: 2028, JEI: DC03, Name: NA, Creek score: Prioritize\",\"WBID: 1623A, JEI: DC04, Name: NA, Creek score: No Data\",\"WBID: 1623B, JEI: DC04, Name: NA, Creek score: No Data\",\"WBID: 1787A2, JEI: DC04, Name: NA, Creek score: No Data\",\"WBID: 1787A2, JEI: DC05, Name: NA, Creek score: No Data\",\"WBID: 2003, JEI: DC05, Name: NA, Creek score: No Data\",\"WBID: 1787A2, JEI: DC06, Name: NA, Creek score: No Data\",\"WBID: 2003, JEI: DC06, Name: NA, Creek score: No Data\",\"WBID: 1623B, JEI: DC07, Name: NA, Creek score: No Data\",\"WBID: 1623A, JEI: DC08, Name: NA, Creek score: No Data\",\"WBID: 1623A, JEI: DC09, Name: NA, Creek score: No Data\",\"WBID: 2008, JEI: DC09, Name: NA, Creek score: No Data\",\"WBID: 2008, JEI: DC10, Name: Thornton Branch, Creek score: No Data\",\"WBID: 2035, JEI: DC10, Name: Thornton Branch, Creek score: No Data\",\"WBID: 2056C1, JEI: DC11, Name: NA, Creek score: No Data\",\"WBID: 1513E, JEI: HC01, Name: Double Branch Creek, Creek score: Monitor\",\"WBID: 1513F, JEI: HC01, Name: Double Branch Creek, Creek score: No Data\",\"WBID: 1513E, JEI: HC02, Name: NA, Creek score: Monitor\",\"WBID: 1513F, JEI: HC02, Name: NA, Creek score: No Data\",\"WBID: 1507, JEI: HC03, Name: Channel A, Creek score: No Data\",\"WBID: 1507A, JEI: HC03, Name: Channel A, Creek score: Monitor\",\"WBID: 1563, JEI: HC04, Name: NA, Creek score: No Data\",\"WBID: 1581, JEI: HC04, Name: NA, Creek score: No Data\",\"WBID: 1507, JEI: HC05, Name: Rocky Creek/Channel G, Creek score: Monitor\",\"WBID: 1516, JEI: HC05, Name: Rocky Creek/Channel G, Creek score: No Data\",\"WBID: 1558I, JEI: HC05, Name: Rocky Creek/Channel G, Creek score: No Data\",\"WBID: 1563, JEI: HC05, Name: Rocky Creek/Channel G, Creek score: Monitor\",\"WBID: 1558I, JEI: HC06, Name: Woods Creek, Creek score: No Data\",\"WBID: 1563, JEI: HC06, Name: Woods Creek, Creek score: No Data\",\"WBID: 1587A, JEI: HC06, Name: Woods Creek, Creek score: Monitor\",\"WBID: 1558I, JEI: HC07, Name: Peppermound Creek, Creek score: No Data\",\"WBID: 1577A, JEI: HC07, Name: Peppermound Creek, Creek score: Monitor\",\"WBID: 1570, JEI: HC08, Name: Sweetwater Creek, Creek score: Monitor\",\"WBID: 1570A, JEI: HC08, Name: Sweetwater Creek, Creek score: Monitor\",\"WBID: 1601A, JEI: HC08, Name: Sweetwater Creek, Creek score: No Data\",\"WBID: 1594, JEI: HC09, Name: Fish Creek, Creek score: Monitor\",\"WBID: 1606, JEI: HC10, Name: Lemon Street Ditch, Creek score: No Data\",\"WBID: 1536E, JEI: HC13, Name: NA, Creek score: No Data\",\"WBID: 1584A1, JEI: HC13, Name: NA, Creek score: No Data\",\"WBID: 1536A, JEI: HC14, Name: NA, Creek score: No Data\",\"WBID: 1536E, JEI: HC14, Name: NA, Creek score: No Data\",\"WBID: 1536E, JEI: HC15, Name: NA, Creek score: No Data\",\"WBID: 1615, JEI: HC15, Name: NA, Creek score: No Data\",\"WBID: 1615, JEI: HC16, Name: Ironhead Creek, Creek score: Prioritize\",\"WBID: 1605, JEI: HC17, Name: Delaney Creek, Creek score: Monitor\",\"WBID: 1605D, JEI: HC17, Name: Delaney Creek, Creek score: Investigate\",\"WBID: 1636, JEI: HC18, Name: Port Sutton Ditch, Creek score: Prioritize\",\"WBID: 1637, JEI: HC18, Name: Port Sutton Ditch, Creek score: No Data\",\"WBID: 1636, JEI: HC19, Name: Verger Creek, Creek score: No Data\",\"WBID: 1637, JEI: HC19, Name: Verger Creek, Creek score: No Data\",\"WBID: 1558E, JEI: HC20, Name: Delaney Creek Popoff, Creek score: No Data\",\"WBID: 1605, JEI: HC20, Name: Delaney Creek Popoff, Creek score: No Data\",\"WBID: 1628, JEI: HC20, Name: Delaney Creek Popoff, Creek score: No Data\",\"WBID: 1632, JEI: HC20, Name: Delaney Creek Popoff, Creek score: Monitor\",\"WBID: 1558E, JEI: HC21, Name: North Archie Creek, Creek score: No Data\",\"WBID: 1628, JEI: HC21, Name: North Archie Creek, Creek score: No Data\",\"WBID: 1628A, JEI: HC21, Name: North Archie Creek, Creek score: Monitor\",\"WBID: 1632, JEI: HC21, Name: North Archie Creek, Creek score: No Data\",\"WBID: 1558E, JEI: HC22, Name: South Archie Creek, Creek score: No Data\",\"WBID: 1628, JEI: HC22, Name: South Archie Creek, Creek score: Investigate\",\"WBID: 1628A, JEI: HC22, Name: South Archie Creek, Creek score: Monitor\",\"WBID: 1635B, JEI: HC23, Name: Buckhorn Creek, Creek score: Monitor\",\"WBID: 1659, JEI: HC24, Name: Rice Creek, Creek score: Monitor\",\"WBID: 1558D, JEI: HC25, Name: Bullfrog Creek, Creek score: No Data\",\"WBID: 1666, JEI: HC25, Name: Bullfrog Creek, Creek score: Monitor\",\"WBID: 1666A, JEI: HC25, Name: Bullfrog Creek, Creek score: Monitor\",\"WBID: 1686, JEI: HC25, Name: Bullfrog Creek, Creek score: Prioritize\",\"WBID: 1688, JEI: HC25, Name: Bullfrog Creek, Creek score: No Data\",\"WBID: 1693, JEI: HC26, Name: Jackson Branch, Creek score: No Data\",\"WBID: 1693, JEI: HC27, Name: Newman Branch, Creek score: No Data\",\"WBID: 1708, JEI: HC27, Name: Newman Branch, Creek score: No Data\",\"WBID: 1712, JEI: HC28, Name: Beever Creek, Creek score: No Data\",\"WBID: 1719, JEI: HC29, Name: NA, Creek score: Prioritize\",\"WBID: 1725, JEI: HC30, Name: NA, Creek score: No Data\",\"WBID: 1725, JEI: HC31, Name: NA, Creek score: No Data\",\"WBID: 1736, JEI: HC31, Name: NA, Creek score: No Data\",\"WBID: 1558C, JEI: HC32, Name: Wolf Branch, Creek score: No Data\",\"WBID: 1725, JEI: HC32, Name: Wolf Branch, Creek score: No Data\",\"WBID: 1736, JEI: HC32, Name: Wolf Branch, Creek score: Monitor\",\"WBID: 1742A1, JEI: HC33, Name: Marsh Branch, Creek score: No Data\",\"WBID: 1747A, JEI: HC33, Name: Marsh Branch, Creek score: No Data\",\"WBID: 1747B, JEI: HC33, Name: Marsh Branch, Creek score: Prioritize\",\"WBID: 1742C1, JEI: HC34, Name: Curiosity Creek, Creek score: No Data\",\"WBID: 1792, JEI: HC34, Name: Curiosity Creek, Creek score: Investigate\",\"WBID: 1798, JEI: HC34, Name: Curiosity Creek, Creek score: No Data\",\"WBID: 1780, JEI: HC35, Name: NA, Creek score: Caution\",\"WBID: 1779, JEI: HC36, Name: Wildcat Creek, Creek score: No Data\",\"WBID: 1780, JEI: HC36, Name: Wildcat Creek, Creek score: No Data\",\"WBID: 1742C1, JEI: HC37, Name: Sun City Slough, Creek score: No Data\",\"WBID: 1771, JEI: HC37, Name: Sun City Slough, Creek score: Caution\",\"WBID: 1778, JEI: HC38, Name: Cockroach Creek, Creek score: No Data\",\"WBID: 1788, JEI: HC38, Name: Cockroach Creek, Creek score: Prioritize\",\"WBID: 1789, JEI: HC38, Name: Cockroach Creek, Creek score: No Data\",\"WBID: 1792, JEI: HC39, Name: Piney Point Creek, Creek score: No Data\",\"WBID: 1789, JEI: HC39, Name: Piney Point Creek, Creek score: Prioritize\",\"WBID: 1797B, JEI: HC39, Name: Piney Point Creek, Creek score: No Data\",\"WBID: 1816, JEI: HC39, Name: Piney Point Creek, Creek score: No Data\",\"WBID: 1609, JEI: HC40, Name: Coon Hammock Creek\\r\\n, Creek score: No Data\",\"WBID: 1621G, JEI: HC41, Name: NA, Creek score: No Data\",\"WBID: 1558I, JEI: HC42, Name: Boat Bayou, Creek score: No Data\",\"WBID: 1566, JEI: HC42, Name: Boat Bayou, Creek score: No Data\",\"WBID: 1609, JEI: HC44, Name: Gun Branch, Creek score: No Data\",\"WBID: 1558G, JEI: HC45, Name: John Branch, Creek score: No Data\",\"WBID: 1609, JEI: HC45, Name: John Branch, Creek score: No Data\",\"WBID: 1584A1, JEI: HC46, Name: Multicolor Creek, Creek score: No Data\",\"WBID: 1584B, JEI: HC46, Name: Multicolor Creek, Creek score: No Data\",\"WBID: 1558E, JEI: HC47, Name: Lee Creek, Creek score: No Data\",\"WBID: 1637, JEI: HC47, Name: Lee Creek, Creek score: No Data\",\"WBID: 1664, JEI: HC48, Name: Gibsonton Creek, Creek score: No Data\",\"WBID: 1558D, JEI: HC49, Name: Dug Creek, Creek score: No Data\",\"WBID: 1676A, JEI: HC49, Name: Dug Creek, Creek score: Caution\",\"WBID: 1682, JEI: HC50, Name: Kitchen Branch, Creek score: Monitor\",\"WBID: 1691, JEI: HC51, Name: Sims Branch, Creek score: No Data\",\"WBID: 1778, JEI: HC52, Name: Andrews Creek, Creek score: No Data\",\"WBID: 1682, JEI: HC53, Name: NA, Creek score: Monitor\",\"WBID: 1558C, JEI: HC54, Name: Broad Creek, Creek score: No Data\",\"WBID: 1609, JEI: HC54, Name: Broad Creek, Creek score: No Data\",\"WBID: 2065D, JEI: LC01, Name: NA, Creek score: Monitor\",\"WBID: 2082B, JEI: LC01, Name: NA, Creek score: No Data\",\"WBID: 2082B1, JEI: LC01, Name: NA, Creek score: Monitor\",\"WBID: 2093A, JEI: LC01, Name: NA, Creek score: No Data\",\"WBID: 2082B, JEI: LC02, Name: Yucca Pen Creek, Creek score: Prioritize\",\"WBID: 2082B2, JEI: LC02, Name: Yucca Pen Creek, Creek score: Monitor\",\"WBID: 2065D, JEI: LC03, Name: Durden Creek, Creek score: No Data\",\"WBID: 2082C, JEI: LC03, Name: Durden Creek, Creek score: Investigate\",\"WBID: 2082C1, JEI: LC03, Name: Durden Creek, Creek score: Monitor\",\"WBID: 2082C2, JEI: LC03, Name: Durden Creek, Creek score: Monitor\",\"WBID: 2065D, JEI: LC04, Name: NA, Creek score: No Data\",\"WBID: 2082C1, JEI: LC04, Name: NA, Creek score: No Data\",\"WBID: 2065F, JEI: LC05, Name: Gator Slough, Creek score: No Data\",\"WBID: 2082C1, JEI: LC05, Name: Gator Slough, Creek score: No Data\",\"WBID: 2065F, JEI: LC06, Name: NA, Creek score: No Data\",\"WBID: 2082C1, JEI: LC06, Name: NA, Creek score: No Data\",\"WBID: 2065F, JEI: LC07, Name: NA, Creek score: No Data\",\"WBID: 2082C1, JEI: LC08, Name: NA, Creek score: No Data\",\"WBID: 2065F, JEI: LC09, Name: NA, Creek score: No Data\",\"WBID: 3240S, JEI: LC09, Name: NA, Creek score: No Data\",\"WBID: 2065F, JEI: LC10, Name: NA, Creek score: No Data\",\"WBID: 2065F, JEI: LC11, Name: NA, Creek score: No Data\",\"WBID: 3240S, JEI: LC11, Name: NA, Creek score: No Data\",\"WBID: 3240A, JEI: LC13, Name: NA, Creek score: No Data\",\"WBID: 3240A1, JEI: LC13, Name: NA, Creek score: No Data\",\"WBID: 3240A, JEI: LC17, Name: NA, Creek score: No Data\",\"WBID: 3240A1, JEI: LC17, Name: NA, Creek score: No Data\",\"WBID: 3240A, JEI: LC19, Name: NA, Creek score: Monitor\",\"WBID: 3240A1, JEI: LC19, Name: NA, Creek score: Monitor\",\"WBID: 3240EA, JEI: LC20, Name: Hancock Creek/Yellow Fever Creek, Creek score: Monitor\",\"WBID: 3240E1, JEI: LC20, Name: Hancock Creek/Yellow Fever Creek, Creek score: Monitor\",\"WBID: 3240EB, JEI: LC20, Name: Hancock Creek/Yellow Fever Creek, Creek score: Monitor\",\"WBID: 3240B, JEI: LC21, Name: Powell Creek, Creek score: No Data\",\"WBID: 3240EA, JEI: LC21, Name: Powell Creek, Creek score: Investigate\",\"WBID: 3240L, JEI: LC21, Name: Powell Creek, Creek score: Monitor\",\"WBID: 2082C, JEI: LC21, Name: Powell Creek, Creek score: No Data\",\"WBID: 3240B, JEI: LC22, Name: NA, Creek score: Monitor\",\"WBID: 3240B2, JEI: LC23, Name: Daughtrey Creek, Creek score: No Data\",\"WBID: 3240F, JEI: LC23, Name: Daughtrey Creek, Creek score: Monitor\",\"WBID: 3240B1, JEI: LC24, Name: NA, Creek score: Monitor\",\"WBID: 3240B2, JEI: LC24, Name: NA, Creek score: Monitor\",\"WBID: 3240F, JEI: LC24, Name: NA, Creek score: No Data\",\"WBID: 3240B1, JEI: LC25, Name: NA, Creek score: Monitor\",\"WBID: 3240B2, JEI: LC25, Name: NA, Creek score: No Data\",\"WBID: 3240Q, JEI: LC26, Name: Popash Creek, Creek score: Monitor\",\"WBID: 3240C, JEI: LC27, Name: Stroud Creek, Creek score: No Data\",\"WBID: 3240M, JEI: LC27, Name: Stroud Creek, Creek score: Monitor\",\"WBID: 3240Q, JEI: LC27, Name: Stroud Creek, Creek score: No Data\",\"WBID: 3240C, JEI: LC28, Name: Palm Creek, Creek score: No Data\",\"WBID: 3240C1, JEI: LC28, Name: Palm Creek, Creek score: Monitor\",\"WBID: 3240G, JEI: LC29, Name: Owl Creek, Creek score: No Data\",\"WBID: 3240N, JEI: LC29, Name: Owl Creek, Creek score: Monitor\",\"WBID: 3240C, JEI: LC30, Name: Trout Creek, Creek score: No Data\",\"WBID: 3240G, JEI: LC30, Name: Trout Creek, Creek score: Monitor\",\"WBID: 3236A, JEI: LC31, Name: Telegraph Creek, Creek score: Monitor\",\"WBID: 3240C, JEI: LC33, Name: Orange River, Creek score: No Data\",\"WBID: 3240K, JEI: LC33, Name: Orange River, Creek score: Monitor\",\"WBID: 3240B, JEI: LC35, Name: Billy Creek, Creek score: No Data\",\"WBID: 3240J1, JEI: LC35, Name: Billy Creek, Creek score: Monitor\",\"WBID: 3240J2, JEI: LC35, Name: Billy Creek, Creek score: Investigate\",\"WBID: 3240J3, JEI: LC35, Name: Billy Creek, Creek score: Monitor\",\"WBID: 3240J4, JEI: LC35, Name: Billy Creek, Creek score: Monitor\",\"WBID: 3240A, JEI: LC36, Name: Manuel Branch, Creek score: No Data\",\"WBID: 3240V, JEI: LC36, Name: Manuel Branch, Creek score: Monitor\",\"WBID: 3240H1, JEI: LC39, Name: Whiskey Creek, Creek score: Monitor\",\"WBID: 3240A, JEI: LC40, Name: NA, Creek score: Monitor\",\"WBID: 3240A4, JEI: LC40, Name: NA, Creek score: Caution\",\"WBID: 3240A4, JEI: LC43, Name: NA, Creek score: No Data\",\"WBID: 3240O, JEI: LC44, Name: NA, Creek score: No Data\",\"WBID: 3258A1, JEI: LC45, Name: Cow Creek, Creek score: No Data\",\"WBID: 3258B2, JEI: LC46, Name: Hendry Creek, Creek score: Caution\",\"WBID: 3258X, JEI: LC46, Name: Hendry Creek, Creek score: No Data\",\"WBID: 3258C2, JEI: LC47, Name: Mullock Creek, Creek score: Monitor\",\"WBID: 3258C4, JEI: LC47, Name: Mullock Creek, Creek score: Monitor\",\"WBID: 3258D3, JEI: LC47, Name: Mullock Creek, Creek score: No Data\",\"WBID: 3258D1, JEI: LC48, Name: Estero River/Halfway Creek, Creek score: Monitor\",\"WBID: 3258D3, JEI: LC48, Name: Estero River/Halfway Creek, Creek score: Monitor\",\"WBID: 3258D4, JEI: LC48, Name: Estero River/Halfway Creek, Creek score: Monitor\",\"WBID: 3258I, JEI: LC48, Name: Estero River/Halfway Creek, Creek score: Monitor\",\"WBID: 3258H2, JEI: LC49, Name: NA, Creek score: No Data\",\"WBID: 3258H2, JEI: LC50, Name: Spring Creek, Creek score: Caution\",\"WBID: 3258H3, JEI: LC50, Name: Spring Creek, Creek score: Monitor\",\"WBID: 3258EB, JEI: LC51, Name: Imperial River/Oak Creek, Creek score: Monitor\",\"WBID: 3258EC, JEI: LC51, Name: Imperial River/Oak Creek, Creek score: Monitor\",\"WBID: 3258ED, JEI: LC51, Name: Imperial River/Oak Creek, Creek score: Monitor\",\"WBID: 3258EG, JEI: LC51, Name: Imperial River/Oak Creek, Creek score: No Data\",\"WBID: 3258F, JEI: LC51, Name: Imperial River/Oak Creek, Creek score: Monitor\",\"WBID: 2065F, JEI: LC53, Name: NA, Creek score: No Data\",\"WBID: 3240S, JEI: LC53, Name: NA, Creek score: No Data\",\"WBID: 2065F, JEI: LC54, Name: NA, Creek score: No Data\",\"WBID: 2065F, JEI: LC55, Name: Underhill Creek, Creek score: No Data\",\"WBID: 2065F, JEI: LC56, Name: NA, Creek score: No Data\",\"WBID: 2065F, JEI: LC57, Name: NA, Creek score: No Data\",\"WBID: 2065H1, JEI: LC57, Name: NA, Creek score: No Data\",\"WBID: 2065H1, JEI: LC58, Name: NA, Creek score: No Data\",\"WBID: 3258C4, JEI: LC59, Name: Mud Creek, Creek score: Monitor\",\"WBID: 3258I, JEI: LC59, Name: Mud Creek, Creek score: No Data\",\"WBID: 3258C4, JEI: LC60, Name: NA, Creek score: No Data\",\"WBID: 1792, JEI: MC01, Name: Clark Creek, Creek score: No Data\",\"WBID: 1797B, JEI: MC01, Name: Clark Creek, Creek score: No Data\",\"WBID: 1816, JEI: MC01, Name: Clark Creek, Creek score: No Data\",\"WBID: 1797A, JEI: MC02, Name: Frog Creek, Creek score: No Data\",\"WBID: 1797B, JEI: MC02, Name: Frog Creek, Creek score: No Data\",\"WBID: 1816, JEI: MC02, Name: Frog Creek, Creek score: No Data\",\"WBID: 1823, JEI: MC02, Name: Frog Creek, Creek score: No Data\",\"WBID: 1825A, JEI: MC02, Name: Frog Creek, Creek score: Investigate\",\"WBID: 1825B, JEI: MC02, Name: Frog Creek, Creek score: Prioritize\",\"WBID: 1797A, JEI: MC03, Name: NA, Creek score: No Data\",\"WBID: 1841, JEI: MC03, Name: NA, Creek score: No Data\",\"WBID: 1797A, JEI: MC04, Name: McMullen Creek, Creek score: No Data\",\"WBID: 1841, JEI: MC04, Name: McMullen Creek, Creek score: Monitor\",\"WBID: 1797A, JEI: MC05, Name: NA, Creek score: No Data\",\"WBID: 1797A, JEI: MC06, Name: Palmetto Creek, Creek score: No Data\",\"WBID: 1797A, JEI: MC07, Name: King Creek, Creek score: No Data\",\"WBID: 1797A, JEI: MC08, Name: Memphis Creek, Creek score: No Data\",\"WBID: 1848A, JEI: MC09, Name: NA, Creek score: Prioritize\",\"WBID: 1797A, JEI: MC09, Name: NA, Creek score: No Data\",\"WBID: 1848A, JEI: MC10, Name: NA, Creek score: Prioritize\",\"WBID: 1848B, JEI: MC10, Name: NA, Creek score: No Data\",\"WBID: 1848B, JEI: MC11, Name: NA, Creek score: No Data\",\"WBID: 1841, JEI: MC11, Name: NA, Creek score: No Data\",\"WBID: 1848B, JEI: MC12, Name: NA, Creek score: No Data\",\"WBID: 1850, JEI: MC12, Name: NA, Creek score: No Data\",\"WBID: 1807G, JEI: MC13, Name: Mill Creek, Creek score: Monitor\",\"WBID: 1872B, JEI: MC13, Name: Mill Creek, Creek score: Monitor\",\"WBID: 1909, JEI: MC13, Name: Mill Creek, Creek score: No Data\",\"WBID: 1872A, JEI: MC13, Name: Mill Creek, Creek score: Monitor\",\"WBID: 1807G, JEI: MC14, Name: Gates Creek, Creek score: No Data\",\"WBID: 1874, JEI: MC14, Name: Gates Creek, Creek score: Monitor\",\"WBID: 1807G, JEI: MC15, Name: NA, Creek score: No Data\",\"WBID: 1807G, JEI: MC16, Name: NA, Creek score: No Data\",\"WBID: 1807G, JEI: MC17, Name: NA, Creek score: No Data\",\"WBID: 1848B, JEI: MC17, Name: NA, Creek score: No Data\",\"WBID: 1875, JEI: MC17, Name: NA, Creek score: No Data\",\"WBID: 1807G, JEI: MC19, Name: NA, Creek score: No Data\",\"WBID: 1848B, JEI: MC19, Name: NA, Creek score: No Data\",\"WBID: 1848B, JEI: MC20, Name: NA, Creek score: No Data\",\"WBID: 1848B, JEI: MC21, Name: NA, Creek score: No Data\",\"WBID: 1875, JEI: MC21, Name: NA, Creek score: No Data\",\"WBID: 1848B, JEI: MC22, Name: NA, Creek score: No Data\",\"WBID: 1875, JEI: MC22, Name: NA, Creek score: No Data\",\"WBID: 1848B, JEI: MC23, Name: Cypress Strand, Creek score: No Data\",\"WBID: 1875, JEI: MC23, Name: Cypress Strand, Creek score: No Data\",\"WBID: 1876, JEI: MC23, Name: Cypress Strand, Creek score: No Data\",\"WBID: 1848B, JEI: MC24, Name: NA, Creek score: No Data\",\"WBID: 1875, JEI: MC24, Name: NA, Creek score: No Data\",\"WBID: 1876, JEI: MC26, Name: NA, Creek score: No Data\",\"WBID: 1876, JEI: MC27, Name: NA, Creek score: No Data\",\"WBID: 1876, JEI: MC28, Name: NA, Creek score: No Data\",\"WBID: 1876, JEI: MC29, Name: Gap Creek, Creek score: No Data\",\"WBID: 1876A, JEI: MC29, Name: Gap Creek, Creek score: No Data\",\"WBID: 1899, JEI: MC29, Name: Gap Creek, Creek score: Monitor\",\"WBID: 1848A, JEI: MC30, Name: Sugarhouse Creek, Creek score: No Data\",\"WBID: 1848D1, JEI: MC30, Name: Sugarhouse Creek, Creek score: No Data\",\"WBID: 1848D2, JEI: MC30, Name: Sugarhouse Creek, Creek score: No Data\",\"WBID: 1876, JEI: MC30, Name: Sugarhouse Creek, Creek score: No Data\",\"WBID: 1887, JEI: MC30, Name: Sugarhouse Creek, Creek score: Monitor\",\"WBID: 1876, JEI: MC31, Name: NA, Creek score: No Data\",\"WBID: 1888A, JEI: MC32, Name: Wares Creek, Creek score: No Data\",\"WBID: 1848A, JEI: MC32, Name: Wares Creek, Creek score: No Data\",\"WBID: 1848D1, JEI: MC32, Name: Wares Creek, Creek score: Monitor\",\"WBID: 1848D2, JEI: MC32, Name: Wares Creek, Creek score: Monitor\",\"WBID: 1848A, JEI: MC33, Name: NA, Creek score: No Data\",\"WBID: 1885A, JEI: MC34, Name: Wares Creek, Creek score: Caution\",\"WBID: 1888A, JEI: MC34, Name: Wares Creek, Creek score: No Data\",\"WBID: 1888B, JEI: MC35, Name: Palma Sola Creek, Creek score: No Data\",\"WBID: 1883, JEI: MC36, Name: NA, Creek score: No Data\",\"WBID: 1888A, JEI: MC36, Name: NA, Creek score: No Data\",\"WBID: 1888A, JEI: MC37, Name: NA, Creek score: No Data\",\"WBID: 1888A, JEI: MC38, Name: Cedar Hammock Creek, Creek score: No Data\",\"WBID: 1896, JEI: MC39, Name: Bowlees Creek, Creek score: Monitor\",\"WBID: 1899, JEI: MC39, Name: Bowlees Creek, Creek score: Monitor\",\"WBID: 1888A, JEI: MC40, Name: NA, Creek score: No Data\",\"WBID: 1968B, JEI: MC40, Name: NA, Creek score: No Data\",\"WBID: 1888A, JEI: MC41, Name: NA, Creek score: No Data\",\"WBID: 1888A, JEI: MC42, Name: NA, Creek score: No Data\",\"WBID: 1868, JEI: MC43, Name: NA, Creek score: No Data\",\"WBID: 1883, JEI: MC43, Name: NA, Creek score: No Data\",\"WBID: 1901, JEI: MC44, Name: Williams Creek, Creek score: Monitor\",\"WBID: 1797B, JEI: MC45, Name: Little Redfish Creek, Creek score: No Data\",\"WBID: 1797A, JEI: MC46, Name: Peterson Creek, Creek score: No Data\",\"WBID: 1888A, JEI: MC47, Name: NA, Creek score: No Data\",\"WBID: 1888A, JEI: MC48, Name: NA, Creek score: No Data\",\"WBID: 1968B, JEI: MC48, Name: NA, Creek score: No Data\",\"WBID: 1618C, JEI: PC01, Name: NA, Creek score: Monitor\",\"WBID: 1618D, JEI: PC01, Name: NA, Creek score: Monitor\",\"WBID: 1625, JEI: PC02, Name: Cross Bayou, Creek score: No Data\",\"WBID: 1641, JEI: PC02, Name: Cross Bayou, Creek score: Caution\",\"WBID: 1662, JEI: PC02, Name: Cross Bayou, Creek score: No Data\",\"WBID: 1662, JEI: PC03, Name: NA, Creek score: Caution\",\"WBID: 1662A, JEI: PC03, Name: NA, Creek score: Monitor\",\"WBID: 1641, JEI: PC04, Name: Saint Joes Creek, Creek score: No Data\",\"WBID: 1668A, JEI: PC04, Name: Saint Joes Creek, Creek score: Monitor\",\"WBID: 1668B, JEI: PC04, Name: Saint Joes Creek, Creek score: Monitor\",\"WBID: 1668D, JEI: PC04, Name: Saint Joes Creek, Creek score: Monitor\",\"WBID: 1668E, JEI: PC04, Name: Saint Joes Creek, Creek score: Prioritize\",\"WBID: 1701A, JEI: PC05, Name: Bear Creek, Creek score: Monitor\",\"WBID: 1701B, JEI: PC05, Name: Bear Creek, Creek score: Monitor\",\"WBID: 1716B, JEI: PC06, Name: NA, Creek score: Monitor\",\"WBID: 1716D, JEI: PC06, Name: NA, Creek score: Monitor\",\"WBID: 1716A, JEI: PC07, Name: NA, Creek score: Investigate\",\"WBID: 1716C1, JEI: PC07, Name: NA, Creek score: No Data\",\"WBID: 1716D, JEI: PC07, Name: NA, Creek score: Monitor\",\"WBID: 1731, JEI: PC08, Name: NA, Creek score: No Data\",\"WBID: 1731A, JEI: PC08, Name: NA, Creek score: No Data\",\"WBID: 1716C1, JEI: PC08, Name: NA, Creek score: Caution\",\"WBID: 1716D, JEI: PC08, Name: NA, Creek score: Monitor\",\"WBID: 1709D, JEI: PC09, Name: Bayou Creek, Creek score: Investigate\",\"WBID: 1558B, JEI: PC10, Name: Salt Creek, Creek score: No Data\",\"WBID: 1709, JEI: PC10, Name: Salt Creek, Creek score: No Data\",\"WBID: 1731, JEI: PC10, Name: Salt Creek, Creek score: No Data\",\"WBID: 1731B, JEI: PC10, Name: Salt Creek, Creek score: Monitor\",\"WBID: 1696, JEI: PC12, Name: Booker Creek, Creek score: Monitor\",\"WBID: 1709B, JEI: PC12, Name: Booker Creek, Creek score: No Data\",\"WBID: 1661B, JEI: PC13, Name: NA, Creek score: No Data\",\"WBID: 1661G, JEI: PC13, Name: NA, Creek score: No Data\",\"WBID: 1661A, JEI: PC14, Name: Turners Creek, Creek score: No Data\",\"WBID: 1661E, JEI: PC14, Name: Turners Creek, Creek score: No Data\",\"WBID: 1661H, JEI: PC14, Name: Turners Creek, Creek score: No Data\",\"WBID: 1661I, JEI: PC14, Name: Turners Creek, Creek score: No Data\",\"WBID: 1661D, JEI: PC15, Name: Tinney Creek, Creek score: No Data\",\"WBID: 1661E, JEI: PC15, Name: Tinney Creek, Creek score: No Data\",\"WBID: 1625, JEI: PC16, Name: Cross Bayou, Creek score: Monitor\",\"WBID: 1627, JEI: PC17, Name: Long Branch, Creek score: Monitor\",\"WBID: 1627B, JEI: PC17, Name: Long Branch, Creek score: Caution\",\"WBID: 1558H, JEI: PC18, Name: Allen Creek, Creek score: No Data\",\"WBID: 1604, JEI: PC18, Name: Allen Creek, Creek score: Monitor\",\"WBID: 1604B1, JEI: PC18, Name: Allen Creek, Creek score: Monitor\",\"WBID: 1604B2, JEI: PC18, Name: Allen Creek, Creek score: Monitor\",\"WBID: 1575, JEI: PC19, Name: Mullet Creek, Creek score: Monitor\",\"WBID: 1575A, JEI: PC19, Name: Mullet Creek, Creek score: Monitor\",\"WBID: 1569, JEI: PC20, Name: Bishop Creek, Creek score: Monitor\",\"WBID: 1569A, JEI: PC20, Name: Bishop Creek, Creek score: Monitor\",\"WBID: 1546, JEI: PC21, Name: Mobbly Bayou, Creek score: No Data\",\"WBID: 1558I, JEI: PC21, Name: Mobbly Bayou, Creek score: No Data\",\"WBID: 1528B, JEI: PC22, Name: NA, Creek score: No Data\",\"WBID: 1668F, JEI: PC23, Name: NA, Creek score: Monitor\",\"WBID: 1694B, JEI: PC23, Name: NA, Creek score: No Data\",\"WBID: 1530, JEI: PC24, Name: Moccasin Creek, Creek score: Caution\",\"WBID: 1558H, JEI: PC25, Name: Grassy Creek, Creek score: No Data\",\"WBID: 1541A, JEI: PC26, Name: Briar Creek, Creek score: No Data\",\"WBID: 1541C, JEI: PC26, Name: Briar Creek, Creek score: Monitor\",\"WBID: 1479, JEI: PC27, Name: Snead Creek, Creek score: No Data\",\"WBID: 8045G, JEI: PC27, Name: Snead Creek, Creek score: No Data\",\"WBID: 1538, JEI: PC28, Name: Curlew Creek, Creek score: Prioritize\",\"WBID: 1538A, JEI: PC28, Name: Curlew Creek, Creek score: Prioritize\",\"WBID: 1550, JEI: PC28, Name: Curlew Creek, Creek score: No Data\",\"WBID: 1556, JEI: PC29, Name: Cedar Creek, Creek score: Caution\",\"WBID: 1556A, JEI: PC29, Name: Cedar Creek, Creek score: Monitor\",\"WBID: 1567, JEI: PC30, Name: Stevenson Creek, Creek score: Monitor\",\"WBID: 1567C, JEI: PC30, Name: Stevenson Creek, Creek score: Monitor\",\"WBID: 1633, JEI: PC31, Name: McKay Creek, Creek score: Monitor\",\"WBID: 1633E, JEI: PC31, Name: McKay Creek, Creek score: Monitor\",\"WBID: 1643, JEI: PC32, Name: Church Creek, Creek score: Prioritize\",\"WBID: 1508, JEI: PC33, Name: Innisbrook Canal, Creek score: Prioritize\",\"WBID: 1508A, JEI: PC33, Name: Innisbrook Canal, Creek score: Prioritize\",\"WBID: 1527A, JEI: PC34, Name: Bee Branch, Creek score: No Data\",\"WBID: 1527B, JEI: PC34, Name: Bee Branch, Creek score: Monitor\",\"WBID: 1535, JEI: PC35, Name: Minnow Creek, Creek score: Monitor\",\"WBID: 1567, JEI: PC36, Name: Spring Branch, Creek score: No Data\",\"WBID: 1567B, JEI: PC36, Name: Spring Branch, Creek score: Monitor\",\"WBID: 1528, JEI: PC37, Name: Rattlesnake Creek, Creek score: No Data\",\"WBID: 1614, JEI: PC37, Name: Rattlesnake Creek, Creek score: Prioritize\",\"WBID: 1936, JEI: SC01, Name: Whitaker Bayou, Creek score: Monitor\",\"WBID: 1936A, JEI: SC01, Name: Whitaker Bayou, Creek score: Monitor\",\"WBID: 1953, JEI: SC02, Name: Hudson Bayou, Creek score: Monitor\",\"WBID: 1953A, JEI: SC02, Name: Hudson Bayou, Creek score: Monitor\",\"WBID: 1968C, JEI: SC02, Name: Hudson Bayou, Creek score: No Data\",\"WBID: 1937, JEI: SC03, Name: Phillippi Creek, Creek score: Monitor\",\"WBID: 1947, JEI: SC03, Name: Phillippi Creek, Creek score: Monitor\",\"WBID: 1975D, JEI: SC04, Name: Mathaney Creek, Creek score: No Data\",\"WBID: 1975C, JEI: SC04, Name: Mathaney Creek, Creek score: No Data\",\"WBID: 1975A, JEI: SC06, Name: Clower Creek, Creek score: Investigate\",\"WBID: 1984A, JEI: SC07, Name: Catfish/North Creek, Creek score: Prioritize\",\"WBID: 1984AB, JEI: SC07, Name: Catfish/North Creek, Creek score: Prioritize\",\"WBID: 1984B, JEI: SC07, Name: Catfish/North Creek, Creek score: Monitor\",\"WBID: 1982, JEI: SC08, Name: South Creek, Creek score: Investigate\",\"WBID: 1982A, JEI: SC08, Name: South Creek, Creek score: No Data\",\"WBID: 1982B, JEI: SC08, Name: South Creek, Creek score: Prioritize\",\"WBID: 1985, JEI: SC08, Name: South Creek, Creek score: No Data\",\"WBID: 1924, JEI: SC12, Name: Shakett Creek, Creek score: No Data\",\"WBID: 1924A, JEI: SC12, Name: Shakett Creek, Creek score: No Data\",\"WBID: 1924B, JEI: SC12, Name: Shakett Creek, Creek score: No Data\",\"WBID: 1994A, JEI: SC12, Name: Shakett Creek, Creek score: No Data\",\"WBID: 1994B, JEI: SC12, Name: Shakett Creek, Creek score: Monitor\",\"WBID: 2002, JEI: SC12, Name: Shakett Creek, Creek score: Caution\",\"WBID: 2009B, JEI: SC14, Name: Curry Creek, Creek score: Caution\",\"WBID: 2009C, JEI: SC14, Name: Curry Creek, Creek score: No Data\",\"WBID: 2016, JEI: SC14, Name: Curry Creek, Creek score: No Data\",\"WBID: 2018A, JEI: SC14, Name: Curry Creek, Creek score: Monitor\",\"WBID: 2015, JEI: SC15, Name: Hatchett Creek, Creek score: Monitor\",\"WBID: 2015A, JEI: SC15, Name: Hatchett Creek, Creek score: Monitor\",\"WBID: 1983A1, JEI: SC17, Name: Alligator Creek Sarasota, Creek score: No Data\",\"WBID: 2030, JEI: SC17, Name: Alligator Creek Sarasota, Creek score: Caution\",\"WBID: 1983A1, JEI: SC20, Name: NA, Creek score: No Data\",\"WBID: 2042, JEI: SC20, Name: NA, Creek score: No Data\",\"WBID: 2039, JEI: SC22, Name: Forked Creek, Creek score: Monitor\",\"WBID: 1983B, JEI: SC25, Name: Gottfried Creek, Creek score: No Data\",\"WBID: 2049, JEI: SC25, Name: Gottfried Creek, Creek score: Caution\",\"WBID: 1991C, JEI: SC26, Name: NA, Creek score: No Data\",\"WBID: 1991E, JEI: SC27, Name: NA, Creek score: No Data\",\"WBID: 1991E, JEI: SC28, Name: NA, Creek score: No Data\",\"WBID: 2038, JEI: SC28, Name: NA, Creek score: No Data\",\"WBID: 1991E, JEI: SC29, Name: NA, Creek score: No Data\",\"WBID: 2037, JEI: SC29, Name: NA, Creek score: No Data\",\"WBID: 1991E, JEI: SC30, Name: NA, Creek score: No Data\",\"WBID: 2036, JEI: SC30, Name: NA, Creek score: No Data\",\"WBID: 1991E, JEI: SC31, Name: NA, Creek score: No Data\",\"WBID: 2034, JEI: SC31, Name: NA, Creek score: No Data\",\"WBID: 1991E, JEI: SC32, Name: NA, Creek score: No Data\",\"WBID: 2031, JEI: SC32, Name: NA, Creek score: Investigate\",\"WBID: 1991E, JEI: SC33, Name: NA, Creek score: No Data\",\"WBID: 2029, JEI: SC33, Name: NA, Creek score: No Data\",\"WBID: 2031, JEI: SC33, Name: NA, Creek score: No Data\",\"WBID: 1991G, JEI: SC34, Name: NA, Creek score: No Data\",\"WBID: 2011, JEI: SC34, Name: NA, Creek score: Monitor\",\"WBID: 2006, JEI: SC35, Name: NA, Creek score: No Data\",\"WBID: 1978, JEI: SC36, Name: Deer Prairie Creek, Creek score: Monitor\",\"WBID: 1991E, JEI: SC36, Name: Deer Prairie Creek, Creek score: No Data\",\"WBID: 1991C, JEI: SC37, Name: NA, Creek score: No Data\",\"WBID: 1991E, JEI: SC37, Name: NA, Creek score: No Data\",\"WBID: 1991C, JEI: SC38, Name: Little Salt Creek (warm mineral Sping), Creek score: No Data\",\"WBID: 2014, JEI: SC38, Name: Little Salt Creek (warm mineral Sping), Creek score: No Data\",\"WBID: 2026, JEI: SC38, Name: Little Salt Creek (warm mineral Sping), Creek score: Monitor\",\"WBID: 2026A, JEI: SC38, Name: Little Salt Creek (warm mineral Sping), Creek score: Monitor\",\"WBID: 1991C, JEI: SC39, Name: NA, Creek score: No Data\",\"WBID: 1976B, JEI: SC40, Name: Big Slough Canal, Creek score: Investigate\",\"WBID: 1976C, JEI: SC40, Name: Big Slough Canal, Creek score: Monitor\",\"WBID: 2014, JEI: SC40, Name: Big Slough Canal, Creek score: No Data\",\"WBID: 1991B, JEI: SC41, Name: NA, Creek score: No Data\",\"WBID: 1991B, JEI: SC42, Name: NA, Creek score: No Data\",\"WBID: 1991B, JEI: SC43, Name: NA, Creek score: No Data\",\"WBID: 2057, JEI: SC43, Name: NA, Creek score: No Data\"],{\"interactive\":false,\"permanent\":false,\"direction\":\"auto\",\"opacity\":1,\"offset\":[0,0],\"textsize\":\"10px\",\"textOnly\":false,\"className\":\"\",\"sticky\":true},null]}],\"limits\":{\"lat\":[26.32829183658335,28.12975168603929],\"lng\":[-82.83757582032332,-81.68445583408415]}},\"evals\":[],\"jsHooks\":{\"render\":[{\"code\":\"function(el, x, data) {\\n return (\\n function(el, x) {\\n var myMap = this;\\n myMap.on('baselayerchange',\\n function (e) {\\n myMap.minimap.changeLayer(L.tileLayer.provider(e.name));\\n })\\n }).call(this.getMap(), el, x, data);\\n}\",\"data\":null}]}}"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkindic.html","id":null,"dir":"Reference","previous_headings":"","what":"Plotly barplots of tidal creek context indicators — show_tdlcrkindic","title":"Plotly barplots of tidal creek context indicators — show_tdlcrkindic","text":"Plotly barplots tidal creek context indicators","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkindic.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plotly barplots of tidal creek context indicators — show_tdlcrkindic","text":"","code":"show_tdlcrkindic( id, cntdat, yr = 2023, thrsel = FALSE, pal = c(\"#5C4A42\", \"#427355\", \"#004F7E\") )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkindic.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plotly barplots of tidal creek context indicators — show_tdlcrkindic","text":"id numeric indicating id number tidal creek plot cntdat output anlz_tdlcrkindic yr numeric indicating reference year thrsel logical threshold lines annotations shown plots pal vector colors palette","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkindic.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plotly barplots of tidal creek context indicators — show_tdlcrkindic","text":"plotly object","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkindic.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plotly barplots of tidal creek context indicators — show_tdlcrkindic","text":"","code":"cntdat <- anlz_tdlcrkindic(tidalcreeks, iwrraw, yr = 2023) set.seed(123) id <- sample(unique(cntdat$id), 1) show_tdlcrkindic(id, cntdat, thrsel = TRUE) 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empirical CDF plots of tidal creek context indicators — show_tdlcrkindiccdf","title":"Plotly empirical CDF plots of tidal creek context indicators — show_tdlcrkindiccdf","text":"Plotly empirical CDF plots tidal creek context indicators","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkindiccdf.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plotly empirical CDF plots of tidal creek context indicators — show_tdlcrkindiccdf","text":"","code":"show_tdlcrkindiccdf( id, cntdat, yr = 2023, thrsel = FALSE, pal = c(\"#5C4A42\", \"#427355\", \"#004F7E\") )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkindiccdf.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plotly empirical CDF plots of tidal creek context indicators — show_tdlcrkindiccdf","text":"id numeric indicating id number tidal creek plot cntdat output anlz_tdlcrkindic yr numeric indicating reference year thrsel logical threshold lines annotations shown plots pal vector colors palette","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkindiccdf.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plotly empirical CDF plots of tidal creek context indicators — show_tdlcrkindiccdf","text":"plotly object","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkindiccdf.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Plotly empirical CDF plots of tidal creek context indicators — show_tdlcrkindiccdf","text":"function returns several empirical cumulative distribution plots tidal creek context indicators. Points plot indicate observed values percentiles creek specified id. percentiles CDF values defined \"population\" creeks cntdat. Points plots color-coded sample year evaluate temporal trends, .","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkindiccdf.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plotly empirical CDF plots of tidal creek context indicators — show_tdlcrkindiccdf","text":"","code":"cntdat <- anlz_tdlcrkindic(tidalcreeks, iwrraw, yr = 2023) set.seed(123) id <- sample(unique(cntdat$id), 1) show_tdlcrkindiccdf(id, cntdat, thrsel = TRUE) 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a line or annotation to a plotly graph — show_tdlcrkline","title":"Add a line or annotation to a plotly graph — show_tdlcrkline","text":"Add line annotation plotly graph tidal creek indicators","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkline.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Add a line or annotation to a plotly graph — show_tdlcrkline","text":"","code":"show_tdlcrkline( varin = c(\"CHLAC\", \"TN\", \"chla_tn_ratio\", \"DO\", \"tsi\", \"no23_ratio\"), thrsel = FALSE, horiz = TRUE, annotate = FALSE )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkline.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Add a line or annotation to a plotly graph — show_tdlcrkline","text":"varin chr string indicator thrsel logical something returned, otherwise NULL, hack working plotly output horiz logical indicating output horizontal vertical annotate logical indicating output line annotation text","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkline.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Add a line or annotation to a plotly graph — show_tdlcrkline","text":"list object passed layout argument plotly, either shapes annotate depending user input","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkline.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Add a line or annotation to a plotly graph — show_tdlcrkline","text":"function used internally within show_tdlcrkindic show_tdlcrkindiccdf","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkline.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Add a line or annotation to a plotly graph — show_tdlcrkline","text":"","code":"# code for vertical line output, chloropyll show_tdlcrkline('CHLAC', thrsel = TRUE) #> [[1]] #> [[1]]$type #> [1] \"line\" #> #> [[1]]$x0 #> [1] 0 #> #> [[1]]$x1 #> [1] 1 #> #> [[1]]$xref #> [1] \"paper\" #> #> [[1]]$y0 #> [1] 11 #> #> [[1]]$y1 #> [1] 11 #> #> [[1]]$line #> [[1]]$line$color #> [1] \"red\" #> #> [[1]]$line$dash #> [1] 10 #> #> #>"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkmatrix.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot the tidal creek report card matrix — show_tdlcrkmatrix","title":"Plot the tidal creek report card matrix — show_tdlcrkmatrix","text":"Plot tidal creek report card matrix","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkmatrix.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot the tidal creek report card matrix — show_tdlcrkmatrix","text":"","code":"show_tdlcrkmatrix( dat, class = c(\"3M\", \"2\"), score = c(\"Prioritize\", \"Investigate\", \"Caution\", \"Monitor\"), family = NA, size = 11 )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkmatrix.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot the tidal creek report card matrix — show_tdlcrkmatrix","text":"dat input creek score data returned anlz_tdlcrk class character vector indicating creek classes show, one many '3M', '2', '3F', '1'. Defaults marine ('3M', '2'). score character vector score categories include, one many 'Prioritize', 'Investigate', 'Caution', 'Monitor'. Defaults . family optional chr string indicating font family text labels size numeric text line scaling","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkmatrix.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot the tidal creek report card matrix — show_tdlcrkmatrix","text":"static ggplot object returned.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkmatrix.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Plot the tidal creek report card matrix — show_tdlcrkmatrix","text":"plot shows matrix rows individual creeks columns overall creek score. columns show overall creek score number years prior ten years nitrogen values creek assigned four score categories. Number years mapped cell transparency.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkmatrix.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot the tidal creek report card matrix — show_tdlcrkmatrix","text":"","code":"dat <- anlz_tdlcrk(tidalcreeks, iwrraw, yr = 2023) show_tdlcrkmatrix(dat)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkradar.html","id":null,"dir":"Reference","previous_headings":"","what":"Radar plots for tidal creek indicators — show_tdlcrkradar","title":"Radar plots for tidal creek indicators — show_tdlcrkradar","text":"Radar plots tidal creek indicators","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkradar.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Radar plots for tidal creek indicators — show_tdlcrkradar","text":"","code":"show_tdlcrkradar( id, cntdat, col = \"#338080E6\", ptsz = 1, lbsz = 0.8, valsz = 1, brdwd = 5 )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkradar.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Radar plots for tidal creek indicators — show_tdlcrkradar","text":"id numeric indicating id number tidal creek plot cntdat output anlz_tdlcrkindic col color input polygon line portions ptsz numeric size points lbsz numeric size text labels valsz numeric size numeric value labels brdwd numeric polygon border width","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkradar.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Radar plots for tidal creek indicators — show_tdlcrkradar","text":"radar plot","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkradar.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Radar plots for tidal creek indicators — show_tdlcrkradar","text":"See details anlz_tdlcrkindic explanation indicators Internal code borrowed heavily radarchart function fmsb package.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkradar.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Radar plots for tidal creek indicators — show_tdlcrkradar","text":"","code":"cntdat <- anlz_tdlcrkindic(tidalcreeks, iwrraw, yr = 2023, radar = TRUE) set.seed(123) id <- sample(unique(cntdat$id), 1) show_tdlcrkradar(id, cntdat)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_thrplot.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot annual water quality values, targets, and thresholds for a segment — show_thrplot","title":"Plot annual water quality values, targets, and thresholds for a segment — show_thrplot","text":"Plot annual water quality values, targets, thresholds bay segment","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_thrplot.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot annual water quality values, targets, and thresholds for a segment — show_thrplot","text":"","code":"show_thrplot( epcdata, bay_segment = c(\"OTB\", \"HB\", \"MTB\", \"LTB\"), thr = c(\"chla\", \"la\"), trgs = NULL, yrrng = c(1975, 2023), family = NA, labelexp = TRUE, txtlab = TRUE, thrs = FALSE, partialyr = FALSE )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_thrplot.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot annual water quality values, targets, and thresholds for a segment — show_thrplot","text":"epcdata data frame epc data returned read_importwq bay_segment chr string bay segment, one \"OTB\", \"HB\", \"MTB\", \"LTB\" thr chr string indicating water quality value appropriate target/threshold plot, one \"chl\" chlorophyll \"la\" light availability trgs optional data.frame annual bay segment water quality targets/thresholds, defaults targets yrrng numeric vector indicating min, max years include family optional chr string indicating font family text labels labelexp logical indicating y axis target labels plotted expressions, default TRUE txtlab logical indicating text label target value shown plot thrs logical indicating reference lines shown regulatory threshold partialyr logical indicating incomplete annual data recent year approximated five year monthly averages parameter","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_thrplot.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot annual water quality values, targets, and thresholds for a segment — show_thrplot","text":"ggplot object","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_thrplot.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot annual water quality values, targets, and thresholds for a segment — show_thrplot","text":"","code":"show_thrplot(epcdata, bay_segment = 'OTB', thr = 'chl')"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transect.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot results for a seagrass transect by time and location — show_transect","title":"Plot results for a seagrass transect by time and location — show_transect","text":"Plot results seagrass transect time location","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transect.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot results for a seagrass transect by time and location — show_transect","text":"","code":"show_transect( transect, site, species = 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plot pixels, applies plotly = TRUE height numeric height plot pixels, applies plotly = TRUE sppcol character vector alternative colors use species, must length six","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transect.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot results for a seagrass transect by time and location — show_transect","text":"ggplot object","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transect.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Plot results for a seagrass transect by time and location — show_transect","text":"sites along transect surveyed shown plot, including selected species found. latter colored grey hollow points. Species options include Halodule, Syringodium, Thalassia, Halophila, Ruppia, Caulerpa (attached macroalgae), /Dapis (cyanobacteria). Drift attached macroalgae cyanobacteria (Dapis) estimates may accurate prior 2021. Note plotly = TRUE, size legend shown.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transect.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot results for a seagrass transect by time and location — show_transect","text":"","code":"if (FALSE) { transect <- read_transect() } # one species show_transect(transect, site = 'S3T10', species = 'Halodule', varplo = 'Abundance') # multiple species, one plot show_transect(transect, site = 'S3T10', species = c('Halodule', 'Syringodium', 'Thalassia', 'Halophila', 'Ruppia', 'Caulerpa', 'Dapis'), varplo = 'Abundance') # multiple species, multiple plots show_transect(transect, site = 'S3T10', species = c('Halodule', 'Syringodium', 'Thalassia', 'Halophila', 'Ruppia', 'Caulerpa', 'Dapis'), varplo = 'Abundance', facet = TRUE)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transectavespp.html","id":null,"dir":"Reference","previous_headings":"","what":"Show annual averages of seagrass frequency occurrence by bay segments, year, and species — show_transectavespp","title":"Show annual averages of seagrass frequency occurrence by bay segments, year, and species — show_transectavespp","text":"Show annual averages seagrass frequency occurrence bay segments, year, species","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transectavespp.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Show annual averages of seagrass frequency occurrence by bay segments, year, and species — show_transectavespp","text":"","code":"show_transectavespp( transectocc, bay_segment = c(\"OTB\", \"HB\", \"MTB\", \"LTB\", \"BCB\"), yrrng = c(1998, 2023), species = c(\"Halodule\", \"Syringodium\", \"Thalassia\", \"Halophila\", \"Ruppia\", \"Caulerpa\", \"Dapis\"), total = TRUE, alph = 1, family = NA, plotly = FALSE, asreact = FALSE, width = NULL, height = NULL, sppcol = NULL )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transectavespp.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Show annual averages of seagrass frequency occurrence by bay segments, year, and species — show_transectavespp","text":"transectocc data frame returned anlz_transectocc bay_segment chr string bay segment, one many \"OTB\", \"HB\", \"MTB\", \"LTB\", \"BCB\" yrrng numeric indicating year ranges evaluate species chr string species summarize, one many \"Halodule\", \"Syringodium\", \"Thalassia\", \"Ruppia\", \"Halophila\", \"Caulerpa\", \"Dapis\" total logical indicating total frequency occurrence species also returned, applies asreact = FALSE alph numeric indicating alpha value score category colors family optional chr string indicating font family text labels plotly logical matrix created using plotly asreact logical reactable table returned instead plot width numeric width plot pixels, applies plotly = TRUE height numeric height plot pixels, applies plotly = TRUE sppcol character vector alternative colors use species, must length six","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transectavespp.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Show annual averages of seagrass frequency occurrence by bay segments, year, and species — show_transectavespp","text":"asreact = F, ggplot plotly (plotly = T) object returned showing trends time species selected bay segments. asreact = T, reactable table showing results year, segment, species returned.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transectavespp.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Show annual averages of seagrass frequency occurrence by bay segments, year, and species — show_transectavespp","text":"Results based averages across species date transect bay segment. Drift attached macroalgae (e.g., Caulerpa) cyanobacteria (Dapis) estimates may accurate prior 2021.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transectavespp.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Show annual averages of seagrass frequency occurrence by bay segments, year, and species — show_transectavespp","text":"plot representation figure 2 Johansson, R. (2016) Seagrass Transect Monitoring Tampa Bay: Summary Findings 1997 2015, Technical report #08-16, Tampa Bay Estuary Program, St. Petersburg, Florida. table representation table 2, p. 163 Yarbro, L. ., P. R. Carlson, Jr., eds. 2016. Seagrass Integrated Mapping Monitoring Program: Mapping Monitoring Report . 2. Fish Wildlife Research Institute Technical Report TR-17 version 2. vi + 281 p.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transectavespp.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Show annual averages of seagrass frequency occurrence by bay segments, year, and species — show_transectavespp","text":"","code":"if (FALSE) { transect <- read_transect() } transectocc <- anlz_transectocc(transect) show_transectavespp(transectocc)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transectmatrix.html","id":null,"dir":"Reference","previous_headings":"","what":"Show matrix of seagrass frequency occurrence by bay segments and year — show_transectmatrix","title":"Show matrix of seagrass frequency occurrence by bay segments and year — show_transectmatrix","text":"Show matrix seagrass frequency occurrence bay segments year","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transectmatrix.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Show matrix of seagrass frequency occurrence by bay segments and year — show_transectmatrix","text":"","code":"show_transectmatrix( transectocc, bay_segment = c(\"OTB\", \"HB\", \"MTB\", \"LTB\", \"BCB\"), total = TRUE, neutral = FALSE, yrrng = c(1998, 2023), alph = 1, txtsz = 3, family = NA, rev = FALSE, position = \"top\", plotly = FALSE, width = NULL, height = NULL )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transectmatrix.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Show matrix of seagrass frequency occurrence by bay segments and year — show_transectmatrix","text":"transectocc data frame returned anlz_transectocc bay_segment chr string bay segment, one many \"HB\", \"OTB\", \"MTB\", \"LTB\", \"TCB\", \"MR\", \"BCB\" total logical indicating average frequency occurrence calculated entire bay across segments neutral logical indicating neutral continuous color scheme used yrrng numeric indicating year ranges evaluate alph numeric indicating alpha value score category colors txtsz numeric size text plot family optional chr string indicating font family text labels rev logical factor levels bay segments reversed position chr string location bay segment labels, default top, passed scale_x_discrete plotly logical matrix created using plotly width numeric width plot pixels, applies plotly = TRUE height numeric height plot pixels, applies plotly = TRUE","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transectmatrix.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Show matrix of seagrass frequency occurrence by bay segments and year — show_transectmatrix","text":"ggplot object showing trends time bay segment plotly = FALSE, otherwise plotly object","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transectmatrix.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Show matrix of seagrass frequency occurrence by bay segments and year — show_transectmatrix","text":"Results based averages across species date transect bay segment color scheme based arbitrary breaks 25, 50, 75 percent frequency occurrence. necessarily translate ecological breakpoints. Use neutral = TRUE use neutral continuous color palette.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transectmatrix.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Show matrix of seagrass frequency occurrence by bay segments and year — show_transectmatrix","text":"plot representation Table 1 R. Johansson (2016) Seagrass Transect Monitoring Tampa Bay: Summary Findings 1997 2015, Technical report #08-16, Tampa Bay Estuary Program, St. Petersburg, Florida.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transectmatrix.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Show matrix of seagrass frequency occurrence by bay segments and year — show_transectmatrix","text":"","code":"if (FALSE) { transect <- read_transect() } transectocc <- anlz_transectocc(transect) show_transectmatrix(transectocc)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transectsum.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot frequency occurrence for a seagrass transect by time for all species — show_transectsum","title":"Plot frequency occurrence for a seagrass transect by time for all species — show_transectsum","text":"Plot frequency occurrence seagrass transect time species","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transectsum.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot frequency occurrence for a seagrass transect by time for all species — show_transectsum","text":"","code":"show_transectsum( transectocc, site, species = c(\"Halodule\", \"Syringodium\", \"Thalassia\", \"Halophila\", \"Ruppia\", \"Caulerpa\", \"Dapis\"), yrrng = c(1998, 2023), abund = FALSE, sppcol = NULL )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transectsum.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot frequency occurrence for a seagrass transect by time for all species — show_transectsum","text":"transectocc data frame returned anlz_transectocc site chr string indicating site results plot species chr string indicating species plot yrrng numeric indicating year ranges evaluate abund logical indicating abundance averages plotted instead frequency occurrence sppcol character vector alternative colors use species, must length six","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transectsum.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot frequency occurrence for a seagrass transect by time for all species — show_transectsum","text":"plotly object","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transectsum.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Plot frequency occurrence for a seagrass transect by time for all species — show_transectsum","text":"plot provides quick visual assessment frequency occurrence abundance multiple species changed time selected transect. Drift attached macroalgae (e.g., Caulerpa) cyanobacteria (Dapis) estimates may accurate prior 2021.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transectsum.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot frequency occurrence for a seagrass transect by time for all species — show_transectsum","text":"","code":"if (FALSE) { transect <- read_transect() } transectocc <- anlz_transectocc(transect) show_transectsum(transectocc, site = 'S3T10') {\"x\":{\"visdat\":{\"1a8b42bfed2a\":[\"function () 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a colorized table for chlorophyll or light attenuation exceedances — show_wqmatrix","title":"Create a colorized table for chlorophyll or light attenuation exceedances — show_wqmatrix","text":"Create colorized table chlorophyll light attenuation exceedances","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_wqmatrix.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Create a colorized table for chlorophyll or light attenuation exceedances — show_wqmatrix","text":"","code":"show_wqmatrix( epcdata, param = c(\"chla\", \"la\"), txtsz = 3, trgs = NULL, yrrng = c(1975, 2023), bay_segment = c(\"OTB\", \"HB\", \"MTB\", \"LTB\"), asreact = FALSE, nrows = 10, abbrev = FALSE, family = NA, plotly = FALSE, partialyr = FALSE, width = NULL, height = NULL )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_wqmatrix.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Create a colorized table for chlorophyll or light attenuation exceedances — show_wqmatrix","text":"epcdata data frame epc data returned read_importwq param chr string parameter plot, one \"chla\" chlorophyll \"la\" light attenuation txtsz numeric size text plot, applies tab = FALSE trgs optional data.frame annual bay segment water quality targets, defaults targets yrrng numeric vector indicating min, max years include bay_segment chr string bay segments include, one \"OTB\", \"HB\", \"MTB\", \"LTB\" asreact logical indicating reactable object returned nrows asreact = TRUE, numeric specifying number rows table abbrev logical indicating text labels plot abbreviated first letter family optional chr string indicating font family text labels plotly logical matrix created using plotly partialyr logical indicating incomplete annual data recent year approximated five year monthly averages parameter width numeric width plot pixels, applies plotly = TRUE height numeric height plot pixels, applies plotly = TRUE","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_wqmatrix.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Create a colorized table for chlorophyll or light attenuation exceedances — show_wqmatrix","text":"static ggplot object returned asreact = FALSE, otherwise reactable table returned","code":""},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_wqmatrix.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Create a colorized table for chlorophyll or light attenuation exceedances — show_wqmatrix","text":"","code":"show_wqmatrix(epcdata)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/stations.html","id":null,"dir":"Reference","previous_headings":"","what":"Bay stations by segment — stations","title":"Bay stations by segment — stations","text":"Bay stations segment","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/stations.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Bay stations by segment — stations","text":"","code":"stations"},{"path":"https://tbep-tech.github.io/tbeptools/reference/stations.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Bay stations by segment — stations","text":"data frame 45 rows 4 variables: bay_segment chr epchc_station num Latitude num Longitude num","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/subtacres.html","id":null,"dir":"Reference","previous_headings":"","what":"Tampa Bay subtidal cover — subtacres","title":"Tampa Bay subtidal cover — subtacres","text":"Tampa Bay subtidal cover Habitat Master Plan reporting","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/subtacres.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tampa Bay subtidal cover — subtacres","text":"","code":"subtacres"},{"path":"https://tbep-tech.github.io/tbeptools/reference/subtacres.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Tampa Bay subtidal cover — subtacres","text":"data frame","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/subtacres.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tampa Bay subtidal cover — subtacres","text":"","code":"if (FALSE) { load(url(\"https://github.com/tbep-tech/hmpu-workflow/raw/master/data/subtacres.RData\")) save(subtacres, file = 'data/subtacres.RData', compress = 'xz') }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/swfwmdtbseg.html","id":null,"dir":"Reference","previous_headings":"","what":"Spatial data object of SWFWMD Tampa Bay segments — swfwmdtbseg","title":"Spatial data object of SWFWMD Tampa Bay segments — swfwmdtbseg","text":"Spatial data object SWFWMD Tampa Bay segments","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/swfwmdtbseg.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Spatial data object of SWFWMD Tampa Bay segments — swfwmdtbseg","text":"","code":"swfwmdtbseg"},{"path":"https://tbep-tech.github.io/tbeptools/reference/swfwmdtbseg.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Spatial data object of SWFWMD Tampa Bay segments — swfwmdtbseg","text":"simple features sf object (MULTIPOLYGON) 7 features 1 fields, +proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/swfwmdtbseg.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Spatial data object of SWFWMD Tampa Bay segments — swfwmdtbseg","text":"","code":"if (FALSE) { library(sf) library(dplyr) levs <- c('oldTampaBay', 'hillsboroughBay', 'middleTampaBay', 'lowerTampaBay', 'bocaCiegaBay', 'terraCieaBay', 'manateeRiver') labs <- c('Old Tampa Bay', 'Hillsborough Bay', 'Middle Tampa Bay', 'Lower Tampa Bay', 'Boca Ciega Bay', 'Terra Ceia Bay', 'Manatee River') swfwmdtbseg <- st_read( dsn = 'T:/05_GIS/SWFWMD/Seagrass/2022_Seagrass/DraftMaps2022_1130.gdb', layer = 'suncoastSeagrassSegments' ) %>% filter(waterbodyName %in% levs) %>% mutate( waterbodyName = factor(waterbodyName, levels = levs, labels = labs) ) %>% select(segment = waterbodyName) %>% st_transform(crs = 4326) save(swfwmdtbseg, file = 'data/swfwmdtbseg.RData', compress = 'xz') }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/targets.html","id":null,"dir":"Reference","previous_headings":"","what":"Bay segment targets — targets","title":"Bay segment targets — targets","text":"Bay segment specific management targets including low high magnitude exceedance thresholds","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/targets.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Bay segment targets — targets","text":"","code":"targets"},{"path":"https://tbep-tech.github.io/tbeptools/reference/targets.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Bay segment targets — targets","text":"data frame 4 rows 8 variables: bay_segment chr name chr chla_target num chla_smallex num chla_thresh num la_target num la_smallex num la_thresh num","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/targets.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Bay segment targets — targets","text":"","code":"if (FALSE) { targets <- structure(list( bay_segment = c(\"OTB\", \"HB\", \"MTB\", \"LTB\", \"BCBN\", \"BCBS\", \"TCB\", \"MR\", \"RALTB\"), name = c(\"Old Tampa Bay\", \"Hillsborough Bay\", \"Middle Tampa Bay\", \"Lower Tampa Bay\", \"Boca Ciega Bay North\", \"Boca Ciega Bay South\", \"Terra Ceia Bay\", \"Manatee River\", \"Remainder Lower Tampa Bay\"), chla_target = c(8.5, 13.2, 7.4, 4.6, 7.7, 6.1, 7.5, 7.3, NaN), chla_smallex = c(8.9, 14.1, 7.9, 4.8, NaN, NaN, NaN, NaN, NaN), chla_thresh = c(9.3, 15, 8.5, 5.1, 8.3, 6.3, 8.7, 8.8, 5.1), la_target = c(0.83, 1.58, 0.83, 0.63, NaN, NaN, NaN, NaN, NaN), la_smallex = c(0.86, 1.63, 0.87, 0.66, NaN, NaN, NaN, NaN, NaN), la_thresh = c(0.88, 1.67, 0.91, 0.68, NaN, NaN, NaN, NaN, NaN)), class = \"data.frame\", row.names = c(NA, -9L) ) save(targets, file = 'data/targets.RData') }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbniref.html","id":null,"dir":"Reference","previous_headings":"","what":"Reference conditions for Tampa Bay Nekton Index metrics — tbniref","title":"Reference conditions for Tampa Bay Nekton Index metrics — tbniref","text":"Reference conditions Tampa Bay Nekton Index metrics","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbniref.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Reference conditions for Tampa Bay Nekton Index metrics — tbniref","text":"","code":"tbniref"},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbniref.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Reference conditions for Tampa Bay Nekton Index metrics — tbniref","text":"data frame 16 rows 12 variables: bay_segment chr Season chr NumTaxa_P5 num NumTaxa_P95 num BenthicTaxa_P5 num BenthicTaxa_P95 num TaxaSelect_P5 num TaxaSelect_P95 num NumGuilds_P5 num NumGuilds_P95 num Shannon_P5 num Shannon_P95 num","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbniref.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Reference conditions for Tampa Bay Nekton Index metrics — tbniref","text":"","code":"if (FALSE) { library(tbeptools) tbniref <- anlz_tbnimet(fimdata) %>% dplyr::filter(between(Year, 1998, 2015)) %>% dplyr::select(Season, bay_segment, NumTaxa, BenthicTaxa, TaxaSelect, NumGuilds, Shannon) %>% dplyr::group_by(bay_segment, Season) %>% dplyr::summarize(NumTaxa_P5 = round(quantile(NumTaxa, probs = 0.05)), NumTaxa_P95 = round(quantile(NumTaxa, probs = 0.95)), BenthicTaxa_P5 = round(quantile(BenthicTaxa, probs = 0.05)), BenthicTaxa_P95 = round(quantile(BenthicTaxa, probs = 0.95)), TaxaSelect_P5 = round(quantile(TaxaSelect, probs = 0.05)), TaxaSelect_P95 = round(quantile(TaxaSelect, probs = 0.95)), NumGuilds_P5 = round(quantile(NumGuilds, probs = 0.05)), NumGuilds_P95 = round(quantile(NumGuilds, probs = 0.95)), Shannon_P5 = quantile(Shannon, probs = 0.05), Shannon_P95 = quantile(Shannon, probs = 0.95)) save(tbniref, file = 'data/tbniref.RData', compress = 'xz') }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbnispp.html","id":null,"dir":"Reference","previous_headings":"","what":"Reference table for Tampa Bay Nekton Index species classifications — tbnispp","title":"Reference table for Tampa Bay Nekton Index species classifications — tbnispp","text":"Reference table Tampa Bay Nekton Index species classifications","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbnispp.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Reference table for Tampa Bay Nekton Index species classifications — tbnispp","text":"","code":"tbnispp"},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbnispp.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Reference table for Tampa Bay Nekton Index species classifications — tbnispp","text":"data frame 196 rows 9 variables: NODCCODE chr ScientificName chr Include_TB_Index chr Hab_Cat chr Est_Cat chr Est_Use chr Feeding_Cat chr Feeding_Guild chr Selected_Taxa chr","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbnispp.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Reference table for Tampa Bay Nekton Index species classifications — tbnispp","text":"","code":"if (FALSE) { library(dplyr) # import and clean tbnispp <- read.csv('../tbni-proc/data/TBIndex_spp_codes.csv', header = TRUE, stringsAsFactors = FALSE) %>% mutate( NODCCODE = as.character(NODCCODE), NODCCODE = case_when(NODCCODE == \"9.998e+09\" ~ \"9998000000\", TRUE ~ NODCCODE) ) save(tbnispp, file = 'data/tbnispp.RData', compress = 'xz') }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbseg.html","id":null,"dir":"Reference","previous_headings":"","what":"Spatial data object of Tampa Bay segments — tbseg","title":"Spatial data object of Tampa Bay segments — tbseg","text":"Note boundaries used formal analysis used visual aids mapping.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbseg.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Spatial data object of Tampa Bay segments — tbseg","text":"","code":"tbseg"},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbseg.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Spatial data object of Tampa Bay segments — tbseg","text":"simple features sf object (POLYGON) 4 features 2 fields, +proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs long_name chr bay_segment chr","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbseg.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Spatial data object of Tampa Bay segments — tbseg","text":"Spatial data object Tampa Bay segments","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbseg.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Spatial data object of Tampa Bay segments — tbseg","text":"","code":"library(sf) #> Linking to GEOS 3.10.2, GDAL 3.4.1, PROJ 8.2.1; sf_use_s2() is TRUE plot(st_geometry(tbseg))"},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbseglines.html","id":null,"dir":"Reference","previous_headings":"","what":"Spatial data object of lines defining major Tampa Bay segments — tbseglines","title":"Spatial data object of lines defining major Tampa Bay segments — tbseglines","text":"Spatial data object lines defining major Tampa Bay segments","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbseglines.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Spatial data object of lines defining major Tampa Bay segments — tbseglines","text":"","code":"tbseglines"},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbseglines.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Spatial data object of lines defining major Tampa Bay segments — tbseglines","text":"simple features sf object (LINESTRING) 3 features 1 field, +proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbseglines.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Spatial data object of lines defining major Tampa Bay segments — tbseglines","text":"","code":"library(sf) plot(st_geometry(tbseglines))"},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbsegshed.html","id":null,"dir":"Reference","previous_headings":"","what":"Spatial data object of Tampa Bay segments plus watersheds — tbsegshed","title":"Spatial data object of Tampa Bay segments plus watersheds — tbsegshed","text":"Spatial data object Tampa Bay segments plus waterhseds","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbsegshed.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Spatial data object of Tampa Bay segments plus watersheds — tbsegshed","text":"","code":"tbsegshed"},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbsegshed.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Spatial data object of Tampa Bay segments plus watersheds — tbsegshed","text":"simple features sf object (POLYGON) 7 features 2 fields, +proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs long_name chr bay_segment chr","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbsegshed.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Spatial data object of Tampa Bay segments plus watersheds — tbsegshed","text":"","code":"library(sf) plot(st_geometry(tbsegshed))"},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbshed.html","id":null,"dir":"Reference","previous_headings":"","what":"Spatial data object of Tampa Bay watershed — tbshed","title":"Spatial data object of Tampa Bay watershed — tbshed","text":"Spatial data object Tampa Bay watershed, includes bay proper","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbshed.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Spatial data object of Tampa Bay watershed — tbshed","text":"","code":"tbshed"},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbshed.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Spatial data object of Tampa Bay watershed — tbshed","text":"simple features sf object (POLYGON) 1 feature 0 fields, +proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbshed.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Spatial data object of Tampa Bay watershed — tbshed","text":"","code":"library(sf) if (FALSE) { library(dplyr) tbshed <- st_read('T:/05_GIS/BOUNDARIES/TBEP_Watershed_Correct_Projection.shp') %>% select(-Id, -Name, -Area_m, -Hectares) %>% st_transform(crs = 4326) save(tbshed, file = 'data/tbshed.RData', compress = 'xz') } plot(st_geometry(tbshed))"},{"path":"https://tbep-tech.github.io/tbeptools/reference/tidalcreeks.html","id":null,"dir":"Reference","previous_headings":"","what":"Spatial data object of tidal creeks in Impaired Waters Rule, Run 65 — tidalcreeks","title":"Spatial data object of tidal creeks in Impaired Waters Rule, Run 65 — tidalcreeks","text":"Spatial data object tidal creeks Impaired Waters Rule, Run 65","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/tidalcreeks.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Spatial data object of tidal creeks in Impaired Waters Rule, Run 65 — tidalcreeks","text":"","code":"tidalcreeks"},{"path":"https://tbep-tech.github.io/tbeptools/reference/tidalcreeks.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Spatial data object of tidal creeks in Impaired Waters Rule, Run 65 — tidalcreeks","text":"simple features sf object (MULTILINESTRING) 615 features fields, +proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs id num wbid chr JEI chr class chr name chr Creek_Length_m num","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/tidalcreeks.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Spatial data object of tidal creeks in Impaired Waters Rule, Run 65 — tidalcreeks","text":"File created using workflow , example old Run 61.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/tidalcreeks.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Spatial data object of tidal creeks in Impaired Waters Rule, Run 65 — tidalcreeks","text":"","code":"if (FALSE) { library(sf) library(dplyr) prj <- 4326 # create sf object of creek population, join with creek length data tidalcreeks <- st_read( dsn = '../../02_DOCUMENTS/tidal_creeks/TidalCreek_ALL_Line_WBID61.shp', drivers = 'ESRI Shapefile' ) %>% st_transform(crs = prj) %>% mutate( id = 1:nrow(.) ) %>% select(id, name = Name, JEI = CreekID, wbid = WBID, class = CLASS, Creek_Length_m = Total_m) # save save(tidalcreeks, file = 'data/tidalcreeks.RData', compress = 'xz') }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/tidaltargets.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidal creek nitrogen targets — tidaltargets","title":"Tidal creek nitrogen targets — tidaltargets","text":"Tidal creek nitrogen targets","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/tidaltargets.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidal creek nitrogen targets — tidaltargets","text":"","code":"tidaltargets"},{"path":"https://tbep-tech.github.io/tbeptools/reference/tidaltargets.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Tidal creek nitrogen targets — tidaltargets","text":"data frame 2 rows 4 variables: region chr prioritize num investigate num caution num","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/transect.html","id":null,"dir":"Reference","previous_headings":"","what":"Seagrass transect data for Tampa Bay current as of 04122024 — transect","title":"Seagrass transect data for Tampa Bay current as of 04122024 — transect","text":"Seagrass transect data Tampa Bay current 04122024","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/transect.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Seagrass transect data for Tampa Bay current as of 04122024 — transect","text":"","code":"transect"},{"path":"https://tbep-tech.github.io/tbeptools/reference/transect.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Seagrass transect data for Tampa Bay current as of 04122024 — transect","text":"data frame 152580 rows 11 variables: Crew chr MonitoringAgency chr Date Date Transect chr Site chr Depth int Savspecies chr SeagrassEdge num var chr aveval num sdval num","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/transect.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Seagrass transect data for Tampa Bay current as of 04122024 — transect","text":"","code":"if (FALSE) { transect <- read_transect() save(transect, file = 'data/transect.RData', compress = 'xz') }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/trnlns.html","id":null,"dir":"Reference","previous_headings":"","what":"Seagrass transect locations — trnlns","title":"Seagrass transect locations — trnlns","text":"Seagrass transect locations","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/trnlns.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Seagrass transect locations — trnlns","text":"","code":"trnlns"},{"path":"https://tbep-tech.github.io/tbeptools/reference/trnlns.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Seagrass transect locations — trnlns","text":"sf LINESTRING object","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/trnlns.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Seagrass transect locations — trnlns","text":"","code":"if (FALSE) { library(sf) library(dplyr) trnlns <- st_read('T:/05_GIS/SEAGRASS_TRANSECTS/transect_routes.shp') %>% st_transform(crs = 4326) %>% dplyr::filter(!as.character(Site) %in% c('S8T1', 'S8T2', 'S8T3', 'S3T2')) %>% dplyr::mutate_if(is.factor, as.character) %>% dplyr::filter(Site %in% trnpts$TRAN_ID) # add bearing, positive counter-clockwise from east bearing <- lapply(trnlns$geometry, function(x) geosphere::bearing(x[, c(1:2)])[[1]]) %>% unlist() trnlns$bearing <- bearing save(trnlns, file = 'data/trnlns.RData', compress = 'xz') }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/trnpts.html","id":null,"dir":"Reference","previous_headings":"","what":"Seagrass transect starting locations — trnpts","title":"Seagrass transect starting locations — trnpts","text":"Seagrass transect starting locations","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/trnpts.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Seagrass transect starting locations — trnpts","text":"","code":"trnpts"},{"path":"https://tbep-tech.github.io/tbeptools/reference/trnpts.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Seagrass transect starting locations — trnpts","text":"sf POINT object","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/trnpts.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Seagrass transect starting locations — trnpts","text":"","code":"if (FALSE) { library(sf) library(dplyr) library(tbeptools) trnpts <- st_read('T:/05_GIS/SEAGRASS_TRANSECTS/TransectBasics2019.shp') %>% st_transform(crs = 4326) %>% dplyr::rename(MonAgency = 'MON_AGENCY') %>% dplyr::filter(!as.character(TRAN_ID) %in% c('S8T1', 'S8T2', 'S8T3', 'S3T2')) # s4t10 is slightly outside boundary for lower tampa bay s4t10 <- trnpts %>% dplyr::filter(TRAN_ID %in% 'S4T10') %>% dplyr::mutate(bay_segment = 'LTB') trnpts <- trnpts %>% sf::st_intersection(sf::st_make_valid(tbsegshed)) %>% dplyr::select(-long_name) %>% dplyr::mutate_if(is.factor, as.character) %>% dplyr::bind_rows(s4t10) save(trnpts, file = 'data/trnpts.RData', compress = 'xz') }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/util_fiblevs.html","id":null,"dir":"Reference","previous_headings":"","what":"A list of Fecal Indicator Bacteria (FIB) category breakpoints and labels — util_fiblevs","title":"A list of Fecal Indicator Bacteria (FIB) category breakpoints and labels — util_fiblevs","text":"list Fecal Indicator Bacteria (FIB) category breakpoints labels","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/util_fiblevs.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"A list of Fecal Indicator Bacteria (FIB) category breakpoints and labels — util_fiblevs","text":"","code":"util_fiblevs()"},{"path":"https://tbep-tech.github.io/tbeptools/reference/util_fiblevs.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"A list of Fecal Indicator Bacteria (FIB) category breakpoints and labels — util_fiblevs","text":"list showing cut points labels FIB categories","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/util_fiblevs.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"A list of Fecal Indicator Bacteria (FIB) category breakpoints and labels — util_fiblevs","text":"","code":"util_fiblevs() #> $ecolilev #> [1] -Inf 126 410 1000 Inf #> #> $ecolilbs #> [1] \"< 126\" \"126 - 409\" \"410 - 999\" \"> 999\" #> #> $ecoccilev #> [1] -Inf 35 130 1000 Inf #> #> $ecoccilbs #> [1] \"< 35\" \"35 - 129\" \"130 - 999\" \"> 999\" #>"},{"path":"https://tbep-tech.github.io/tbeptools/reference/util_html.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert character string to html class — util_html","title":"Convert character string to html class — util_html","text":"Convert character string html class","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/util_html.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert character string to html class — util_html","text":"","code":"util_html(text)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/util_html.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert character string to html class — util_html","text":"text character string input","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/util_html.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert character string to html class — util_html","text":"input character string html class","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/util_html.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Convert character string to html class — util_html","text":"Adapted HTML","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/util_html.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Convert character string to html class — util_html","text":"","code":"util_html('abd') #> abd"},{"path":"https://tbep-tech.github.io/tbeptools/reference/util_map.html","id":null,"dir":"Reference","previous_headings":"","what":"Create an empty leaflet map from sf input — util_map","title":"Create an empty leaflet map from sf input — util_map","text":"Create empty leaflet map sf input","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/util_map.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Create an empty leaflet map from sf input — util_map","text":"","code":"util_map(tomap, minimap = \"bottomleft\")"},{"path":"https://tbep-tech.github.io/tbeptools/reference/util_map.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Create an empty leaflet map from sf input — util_map","text":"tomap sf input object minimap character string indicating location minimap, use minimap = NULL suppress","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/util_map.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Create an empty leaflet map from sf input — util_map","text":"leaflet object optional minimap ESRI provider tiles","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/util_map.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Create an empty leaflet map from sf input — util_map","text":"","code":"tomap <- tibble::tibble( lon = -82.6365, lat = 27.75822 ) tomap <- sf::st_as_sf(tomap, coords = c('lon', 'lat'), crs = 4326) util_map(tomap) {\"x\":{\"options\":{\"crs\":{\"crsClass\":\"L.CRS.EPSG3857\",\"code\":null,\"proj4def\":null,\"projectedBounds\":null,\"options\":{}}},\"fitBounds\":[27.75822,-82.6365,27.75822,-82.6365,[]],\"calls\":[{\"method\":\"addProviderTiles\",\"args\":[\"Esri.WorldGrayCanvas\",null,\"Esri.WorldGrayCanvas\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.NatGeoWorldMap\",null,\"Esri.NatGeoWorldMap\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.OceanBasemap\",null,\"Esri.OceanBasemap\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.WorldPhysical\",null,\"Esri.WorldPhysical\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.WorldShadedRelief\",null,\"Esri.WorldShadedRelief\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.WorldTerrain\",null,\"Esri.WorldTerrain\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.WorldImagery\",null,\"Esri.WorldImagery\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.WorldTopoMap\",null,\"Esri.WorldTopoMap\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.DeLorme\",null,\"Esri.DeLorme\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.WorldStreetMap\",null,\"Esri.WorldStreetMap\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri\",null,\"Esri\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addLayersControl\",\"args\":[[\"Esri.WorldGrayCanvas\",\"Esri.NatGeoWorldMap\",\"Esri.OceanBasemap\",\"Esri.WorldPhysical\",\"Esri.WorldShadedRelief\",\"Esri.WorldTerrain\",\"Esri.WorldImagery\",\"Esri.WorldTopoMap\",\"Esri.DeLorme\",\"Esri.WorldStreetMap\",\"Esri\"],[],{\"collapsed\":true,\"autoZIndex\":true,\"position\":\"topleft\"}]},{\"method\":\"addMiniMap\",\"args\":[null,\"Esri.WorldGrayCanvas\",\"bottomleft\",150,150,19,19,-5,false,false,false,true,false,true,{\"color\":\"#ff7800\",\"weight\":1,\"clickable\":false},{\"color\":\"#000000\",\"weight\":1,\"clickable\":false,\"opacity\":0,\"fillOpacity\":0},{\"hideText\":\"Hide MiniMap\",\"showText\":\"Show MiniMap\"},[]]}]},\"evals\":[],\"jsHooks\":{\"render\":[{\"code\":\"function(el, x, data) {\\n return (\\n function(el, x) {\\n var myMap = this;\\n myMap.on('baselayerchange',\\n function (e) {\\n myMap.minimap.changeLayer(L.tileLayer.provider(e.name));\\n })\\n }).call(this.getMap(), el, x, data);\\n}\",\"data\":null}]}}"},{"path":"https://tbep-tech.github.io/tbeptools/reference/util_orgin.html","id":null,"dir":"Reference","previous_headings":"","what":"Get organization name from organization identifier in USEPA Water Quality Portal — util_orgin","title":"Get organization name from organization identifier in USEPA Water Quality Portal — util_orgin","text":"Get organization name organization identifier USEPA Water Quality Portal","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/util_orgin.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get organization name from organization identifier in USEPA Water Quality Portal — util_orgin","text":"","code":"util_orgin(org, stanm = FALSE)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/util_orgin.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get organization name from organization identifier in USEPA Water Quality Portal — util_orgin","text":"org chr string indicating organization identifier, see read_importwqp valid entries stanm logical indicating character string column name specific organization returned","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/util_orgin.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get organization name from organization identifier in USEPA Water Quality Portal — util_orgin","text":"character string organization name corresponds organization identifier column name station identifier specific organization stanm = TRUE","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/util_orgin.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get organization name from organization identifier in USEPA Water Quality Portal — util_orgin","text":"","code":"util_orgin('21FLHILL_WQX') #> [1] \"Hillsborough\" util_orgin('21FLPASC_WQX', stanm = TRUE) #> [1] \"pasco_station\""}] +[{"path":"https://tbep-tech.github.io/tbeptools/CONTRIBUTING.html","id":null,"dir":"","previous_headings":"","what":"Contributing to tbeptools","title":"Contributing to tbeptools","text":"outlines propose change tbeptools. detailed info contributing , please see development contributing guide.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/CONTRIBUTING.html","id":"fixing-typos","dir":"","previous_headings":"","what":"Fixing typos","title":"Contributing to tbeptools","text":"Small typos grammatical errors documentation may edited directly using GitHub web interface, long changes made source file. YES: edit roxygen comment .R file R/. : edit .Rd file man/.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/CONTRIBUTING.html","id":"prerequisites","dir":"","previous_headings":"","what":"Prerequisites","title":"Contributing to tbeptools","text":"make substantial pull request, always file issue make sure someone team agrees ’s problem. ’ve found bug, create associated issue illustrate bug minimal reprex.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/CONTRIBUTING.html","id":"pull-request-process","dir":"","previous_headings":"","what":"Pull request process","title":"Contributing to tbeptools","text":"recommend create Git branch pull request (PR). Look Travis AppVeyor build status making changes. README contain badges continuous integration services used package. New code follow tidyverse style guide. can use styler package apply styles, please don’t restyle code nothing PR. use roxygen2, Markdown syntax, documentation. use testthat. Contributions test cases included easier accept. user-facing changes, add bullet top NEWS.md current development version header describing changes made followed GitHub username, links relevant issue(s)/PR(s).","code":""},{"path":"https://tbep-tech.github.io/tbeptools/CONTRIBUTING.html","id":"code-of-conduct","dir":"","previous_headings":"","what":"Code of Conduct","title":"Contributing to tbeptools","text":"Please note tbeptools project released Contributor Code Conduct. contributing project agree abide terms.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/CONTRIBUTING.html","id":"see-tidyverse-development-contributing-guide","dir":"","previous_headings":"","what":"See tidyverse development contributing guide","title":"Contributing to tbeptools","text":"details.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/ISSUE_TEMPLATE.html","id":null,"dir":"","previous_headings":"","what":"Issues reporting guide","title":"Issues reporting guide","text":"Please briefly describe problem output expect. question, please don’t use form. Instead, ask https://stackoverflow.com/ https://community.rstudio.com/. Please include minimal reproducible example (AKA reprex). ’ve never heard reprex , start reading https://www.tidyverse.org/help/#reprex. Brief description problem","code":"# insert reprex here"},{"path":"https://tbep-tech.github.io/tbeptools/LICENSE.html","id":null,"dir":"","previous_headings":"","what":"MIT License","title":"MIT License","text":"Copyright (c) 2024 tbeptools authors Permission hereby granted, free charge, person obtaining copy software associated documentation files (“Software”), deal Software without restriction, including without limitation rights use, copy, modify, merge, publish, distribute, sublicense, /sell copies Software, permit persons Software furnished , subject following conditions: copyright notice permission notice shall included copies substantial portions Software. SOFTWARE PROVIDED “”, WITHOUT WARRANTY KIND, EXPRESS IMPLIED, INCLUDING LIMITED WARRANTIES MERCHANTABILITY, FITNESS PARTICULAR PURPOSE NONINFRINGEMENT. EVENT SHALL AUTHORS COPYRIGHT HOLDERS LIABLE CLAIM, DAMAGES LIABILITY, WHETHER ACTION CONTRACT, TORT OTHERWISE, ARISING , CONNECTION SOFTWARE USE DEALINGS SOFTWARE.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/articles/fib.html","id":"background","dir":"Articles","previous_headings":"","what":"Background","title":"Fecal Indicator Bacteria","text":"Fecal Indicator Bacteria (FIB) used track concentrations pathogens surface waters may detrimental human health environment. commonly measured select indicators present human gut can enter environment wastewater discharges illicit sources. Common indicators include concentrations E. coli, Enterococcus, Fecal Coliform number colony forming units (CFU) per 100 mL water. Many monitoring programs routinely measure FIB concentrations select locations. Environmental Protection Commission (EPC) Hillsborough County tracking FIB indicators several decades part long-term monitoring. Functions tbeptools can used download EPC FIB data, analyze results, create summary maps plots. vignette describes use functions. functions focused reporting Hillsborough River fecal coliform impairment associated Basin Management Action Plan (BMAP). tools can used track long-term changes FIBs basin assess progress reducing fecal coliform levels. Data collected monitoring program processed maintained spreadsheet titled RWMDataSpreadsheet_ThroughCurrentReportMonth.xlsx https://epcbocc.sharepoint.com/:x:/s/Share/EWKgPirIkoxMp9Hm_wVEICsBk6avI9iSRjFiOxX58wXzIQ?e=kAWZXl&download=1 (viewable ). data include observations stations parameters throughout period record. FIB data collected stations additional water quality data collected. dataset used reporting water quality indicators Tampa Bay (see water quality data vignette).","code":""},{"path":"https://tbep-tech.github.io/tbeptools/articles/fib.html","id":"read","dir":"Articles","previous_headings":"","what":"Read","title":"Fecal Indicator Bacteria","text":"main function importing FIB data read_importfib(). function downloads latest file one already available location specified xlsx input argument. function operates similarly read_importwq() importing water quality data. Please refer see water quality data vignette additional details import function. FIB data can downloaded follows: data object called fibdata also provided package, although may contain current data available EPC. View help file download date. fibdata object includes monthly samples FIB data select stations Hillsborough River basin. stations include samples beginning 1972. default output read_importwq() returns stations FIB data EPC. = F read_importfib(), stations AreaName source data Hillsborough River, Hillsborough River Tributary, Alafia River, Alafia River Tributary, Lake Thonotosassa, Lake Thonotosassa Tributary, Lake Roberta. Values returned E. coli (ecoli), Enterococcus (ecocci), Fecal Coliform (fcolif), Total Coliform (totcol). Values shown # colonies per 100 mL water (#/100mL). Qualifier columns also returned _q suffix. Qualifier codes can interpreted source spreadsheet. Concentrations noted < > raw data reported , numeric value shown. Samples notation can determined qualifier columns. fibdata object can used remaining FIB functions.","code":"fibdata <- read_importfib('vignettes/current_data.xlsx', download_latest = T) fibdata #> # A tibble: 76,502 × 18 #> area epchc_station class SampleTime yr mo Latitude Longitude #> #> 1 Hills… 2 3M 2024-01-08 14:46:00 2024 1 27.9 -82.5 #> 2 Hills… 6 3M 2024-01-16 09:50:00 2024 1 27.9 -82.5 #> 3 Hills… 7 3M 2024-01-16 10:07:00 2024 1 27.9 -82.5 #> 4 Hills… 8 3M 2024-01-16 12:50:00 2024 1 27.9 -82.4 #> 5 Middl… 9 2 2024-01-16 11:58:00 2024 1 27.8 -82.4 #> 6 Middl… 11 2 2024-01-16 10:20:00 2024 1 27.8 -82.5 #> 7 Middl… 13 2 2024-01-16 10:36:00 2024 1 27.8 -82.5 #> 8 Middl… 14 2 2024-01-16 11:26:00 2024 1 27.8 -82.5 #> 9 Middl… 16 2 2024-01-30 09:10:00 2024 1 27.7 -82.5 #> 10 Middl… 19 2 2024-01-30 09:25:00 2024 1 27.7 -82.6 #> # ℹ 76,492 more rows #> # ℹ 10 more variables: Total_Depth_m , Sample_Depth_m , ecoli , #> # ecoli_q , ecocci , ecocci_q , fcolif , fcolif_q , #> # totcol , totcol_q "},{"path":"https://tbep-tech.github.io/tbeptools/articles/fib.html","id":"retrieving-additional-fib-data","dir":"Articles","previous_headings":"Read","what":"Retrieving additional FIB data","title":"Fecal Indicator Bacteria","text":"FIB functions tbeptools developed work long-term monitoring data Environmental Protection Commission Hillsborough County. Additional monitoring programs Tampa Bay can also used develop complete description FIB data. read_importwqp() function can used retrieve data USEPA Water Quality Portal data monitoring organizations around Tampa Bay watershed. function retrieves additional FIB data using type = 'fib' specified organization identified. data can retrieved follows typically take less one minute download.","code":"# get Manatee County data mancodata <- read_importwqp(org = '21FLMANA_WQX', type = 'fib', trace = T) # get Pinellas County data pincodata <- read_importwqp(org = '21FLPDEM_WQX', type = 'fib', trace = T)"},{"path":"https://tbep-tech.github.io/tbeptools/articles/fib.html","id":"analyze","dir":"Articles","previous_headings":"","what":"Analyze","title":"Fecal Indicator Bacteria","text":"anlz_fibmap() function assigns categories observation fibdata selected month year. results mapped using anlz_fibmap() (see ). categories specific E. coli Enterococcus assigned based station class freshwater (class 1 3F) marine (class 2 3M), respectively. station categorized one four ranges defined thresholds noted cat column output, corresponding colors appropriate range noted col column output. thresholds EPC follows E. coli Enterococcus. yrsel mosel arguments can used filter results year month. specifying arguments return results entire period record. areasel argument can indicate either \"Alafia\" \"Hillsborough\" select data corresponding river basins, rows fibdata filtered based selection. stations returned argument set NULL (default). Alafia River basin includes values area column fibdata \"Alafia River\" \"Alafia River Tributary\". Hillsborough River basin includes values area column fibdat \"Hillsborough River\", \"Hillsborough River Tributary\", \"Lake Thonotosassa\", \"Lake Thonotosassa Tributary\", \"Lake Roberta\". areas may present based selection yrsel mosel. valid options areasel include \"Alafia River\", \"Hillsborough River\", \"Big Bend\", \"Cockroach Bay\", \"East Lake Outfall\", \"Hillsborough Bay\", \"Little Manatee\", \"Lower Tampa Bay\", \"McKay Bay\", \"Middle Tampa Bay\", \"Old Tampa Bay\", \"Palm River\", \"Tampa Bypass Canal\", \"Valrico Lake\". anlz_fibmatrix() function creates summary FIB categories station year output show_fibmatrix() function described . function assigns Microbial Water Quality Assessment (MWQA) letter categories station year based likelihood fecal coliform concentrations exceed 400 CFU / 100 mL given year. default, results year based right-centered window uses previous two years current year calculate probabilities monthly samples (lagyr = 3). columns station year include estimated geometric mean fecal coliform concentrations (gmean) category indicating letter outcome based likelihood exceedences (cat).","code":"anlz_fibmap(fibdata) #> # A tibble: 76,502 × 12 #> area epchc_station class yr mo Latitude Longitude ecoli ecocci ind #> #> 1 Hillsb… 2 3M 2024 1 27.9 -82.5 NA 24 Ente… #> 2 Hillsb… 6 3M 2024 1 27.9 -82.5 NA 2 Ente… #> 3 Hillsb… 7 3M 2024 1 27.9 -82.5 NA 2 Ente… #> 4 Hillsb… 8 3M 2024 1 27.9 -82.4 NA 10 Ente… #> 5 Middle… 9 2 2024 1 27.8 -82.4 NA 2 Ente… #> 6 Middle… 11 2 2024 1 27.8 -82.5 NA 2 Ente… #> 7 Middle… 13 2 2024 1 27.8 -82.5 NA 2 Ente… #> 8 Middle… 14 2 2024 1 27.8 -82.5 NA 2 Ente… #> 9 Middle… 16 2 2024 1 27.7 -82.5 NA 2 Ente… #> 10 Middle… 19 2 2024 1 27.7 -82.6 NA 2 Ente… #> # ℹ 76,492 more rows #> # ℹ 2 more variables: cat , col anlz_fibmap(fibdata, yrsel = 2023, mosel = 7) #> # A tibble: 207 × 12 #> area epchc_station class yr mo Latitude Longitude ecoli ecocci ind #> #> 1 Hillsb… 2 3M 2023 7 27.9 -82.5 NA 800 Ente… #> 2 Hillsb… 6 3M 2023 7 27.9 -82.5 NA 2 Ente… #> 3 Hillsb… 7 3M 2023 7 27.9 -82.5 NA 2 Ente… #> 4 Hillsb… 8 3M 2023 7 27.9 -82.4 NA 2 Ente… #> 5 Middle… 9 2 2023 7 27.8 -82.4 NA 2 Ente… #> 6 Middle… 11 2 2023 7 27.8 -82.5 NA 2 Ente… #> 7 Middle… 13 2 2023 7 27.8 -82.5 NA 2 Ente… #> 8 Middle… 14 2 2023 7 27.8 -82.5 NA 2 Ente… #> 9 Middle… 16 2 2023 7 27.7 -82.5 NA 2 Ente… #> 10 Middle… 19 2 2023 7 27.7 -82.6 NA 2 Ente… #> # ℹ 197 more rows #> # ℹ 2 more variables: cat , col anlz_fibmap(fibdata, yrsel = 2023, mosel = 7, areasel = 'Hillsborough River') #> # A tibble: 47 × 12 #> area epchc_station class yr mo Latitude Longitude ecoli ecocci ind #> #> 1 Hillsb… 2 3M 2023 7 27.9 -82.5 NA 800 Ente… #> 2 Hillsb… 105 3M 2023 7 28.0 -82.4 NA 128 Ente… #> 3 Hillsb… 106 1 2023 7 28.1 -82.4 144 232 E. c… #> 4 Lake T… 107 3F 2023 7 28.0 -82.3 570 1550 E. c… #> 5 Hillsb… 108 3F 2023 7 28.1 -82.2 187 276 E. c… #> 6 Lake T… 118 3F 2023 7 28.1 -82.3 4 7 E. c… #> 7 Hillsb… 120 3F 2023 7 28.1 -82.4 100 410 E. c… #> 8 Lake T… 135 3F 2023 7 28.1 -82.3 4 4 E. c… #> 9 Hillsb… 137 3M 2023 7 28.0 -82.5 NA 680 Ente… #> 10 Hillsb… 143 3F 2023 7 28.1 -82.1 800 1333 E. c… #> # ℹ 37 more rows #> # ℹ 2 more variables: cat , col anlz_fibmatrix(fibdata) #> # A tibble: 8,800 × 4 #> yr epchc_station gmean cat #> #> 1 1985 2 52.4 B #> 2 1985 6 7.21 A #> 3 1985 7 4.64 A #> 4 1985 8 9.49 A #> 5 1985 9 6.32 A #> 6 1985 11 5.18 A #> 7 1985 13 4 A #> 8 1985 14 6.35 A #> 9 1985 16 4 A #> 10 1985 19 4 A #> # ℹ 8,790 more rows"},{"path":"https://tbep-tech.github.io/tbeptools/articles/fib.html","id":"show","dir":"Articles","previous_headings":"","what":"Show","title":"Fecal Indicator Bacteria","text":"show_fibmap() function creates map FIB sites thresholds based output anlz_fibmap(). arguments apply anlz_fibmap() also apply show_fibmap() freshwater marine stations categorized relevant thresholds plotted selected year, month, area. Unlike anlz_fibmap(), yrsel mosel arguments required. Sites Hillsborough Alafia river basins can shown using areasel argument. Additional information site can seen placing cursor location. map inset can also seen clicking arrow button left. show_fibmatrix() function creates stoplight graphic summarized FIB data selected stations year available data [1]. matrix colors based likelihood fecal indicator bacteria concentrations exceed 400 CFU / 100 mL given year (using Fecal Coliform, fcolif fibdata). likelihoods categorized , B, C, D, E (Microbial Water Quality Assessment MWQA categories) corresponding colors, breakpoints category <10%, 10-30%, 30-50%, 50-75%, >75% (right-closed). Methods rationale categorization scheme provided Florida Department Environmental Protection, Figure 8 [2] [1]. default, results year based right-centered window uses previous two years current year calculate probabilities monthly samples (lagyr = 3). example shows results using monthly observations year. default stations used TBEP report #05-13 [3] Hillsborough River Basin Management Action Plan (BMAP) subbasins. include Blackwater Creek (WBID 1482, EPC stations 143, 108), Baker Creek (WBID 1522C, EPC station 107), Lake Thonotosassa (WBID 1522B, EPC stations 135, 118), Flint Creek (WBID 1522A, EPC station 148), Lower Hillsborough River (WBID 1443E, EPC stations 105, 152, 137). stations fibdata can plotted using stas argument. yrrng argument can also used select year range, default 1985 current year data fibdata. preferred, matrix can also returned HTML table can sorted scrolled. first ten rows shown default. default number rows (10) can changed nrows argument. Use sufficiently large number show rows. plotly (interactive, dynamic plot) can returned setting plotly argument TRUE. plots, can view locations general trends FIB data Hillsborough Alafia river basins. Additional functions may added future evaluate FIB data locations.","code":"show_fibmap(fibdata, yrsel = 2023, mosel = 7, areasel = NULL) show_fibmap(fibdata, yrsel = 2023, mosel = 7, areasel = 'Hillsborough River') show_fibmap(fibdata, yrsel = 2023, mosel = 7, areasel = 'Alafia River') show_fibmatrix(fibdata) show_fibmatrix(fibdata, lagyr = 1) show_fibmatrix(fibdata, stas = c(115, 116)) show_fibmatrix(fibdata, yrrng = c(1990, 2020)) show_fibmatrix(fibdata, asreact = TRUE) show_fibmatrix(fibdata, plotly = TRUE)"},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/articles/habitatmasterplan.html","id":"background","dir":"Articles","previous_headings":"","what":"Background","title":"Habitat Master Plan","text":"Dashboard: https://shiny.tbep.org/landuse-change/ habitats Tampa Bay provide food, shelter, important services support birds, fish, mammals, invertebrates. Significant habitat alteration loss occurred development activities. address challenges, Habitat Master Plan (2020 Update) [1] provides set targets goals , achieved, provide healthy balanced coverage native habitats Tampa Bay watershed. update builds previous Habitat Master Plan [2] several ways. target goal setting approach informed past changes forty years habitat restoration experience region. approach also identifies possible today rather replicating past ecological conditions accounts potential future effects sea-level rise, climate change, development. Habitat Master Plan defines 10-year (2030) habitat protection restoration targets 30-year (2050) goals. Maps habitat protection restoration opportunity areas targets goals can attained additional products available new plan. Please visit https://tbep.org/habitat-master-plan-update/ additional information.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/articles/habitatmasterplan.html","id":"datasets","dir":"Articles","previous_headings":"","what":"Datasets","title":"Habitat Master Plan","text":"Three internal datasets tbeptools provide necessary information create Habitat Master Plan report card. Summary annual acreage estimates major habitat type intertidal supratidal strata. Summary annual acreage estimates major habitat type subtidal stratam. table targets goals major habitat type, developed Habitat Master Plan 2020 update [1] (select columns shown). datasets created repository https://github.com/tbep-tech/hmpu-workflow require updates land use cover datasets produced every two three years Southwest Florida Water Management District.","code":"acres #> # A tibble: 90 × 3 #> # Groups: name [9] #> name HMPU_TARGETS Acres #> #> 1 1990 Coastal Uplands 5078. #> 2 1990 Developed 372438. #> 3 1990 Forested Freshwater Wetlands 159561. #> 4 1990 Mangrove Forests 13522. #> 5 1990 Native Uplands 229990. #> 6 1990 Non-Forested Freshwater Wetlands 54454. #> 7 1990 Open Water 38357. #> 8 1990 Restorable 571513. #> 9 1990 Salt Barrens 468 #> 10 1990 Salt Marshes 4482. #> # ℹ 80 more rows subtacres #> # A tibble: 65 × 3 #> name HMPU_TARGETS Acres #> #> 1 1988 Open Water 197802. #> 2 1988 Restorable 72.9 #> 3 1988 Seagrasses 23279. #> 4 1988 Tidal Flats 21686. #> 5 1990 Open Water 197058. #> 6 1990 Restorable 67.0 #> 7 1990 Seagrasses 25218. #> 8 1990 Tidal Flats 20433. #> 9 1992 Open Water 195908. #> 10 1992 Restorable 86.0 #> # ℹ 55 more rows hmptrgs[, c(\"Category\", \"HMPU_TARGETS\", \"Target2030\", \"Goal2050\")] #> Category HMPU_TARGETS Target2030 Goal2050 #> 1 Subtidal Hard Bottom 423.0 423.0 #> 2 Subtidal Artificial Reefs 166.0 166.0 #> 3 Subtidal Tidal Flats 16220.0 16220.0 #> 4 Subtidal Seagrasses 40000.0 40000.0 #> 5 Subtidal Oyster Bars 221.0 471.0 #> 6 Intertidal Living Shorelines 21.3 56.3 #> 7 Intertidal Total Intertidal 21353.0 23803.0 #> 8 Intertidal Mangrove Forests 15300.0 15300.0 #> 9 Intertidal Salt Barrens 546.0 796.0 #> 10 Intertidal Salt Marshes 4807.0 5457.0 #> 11 Intertidal Tidal Tributaries 4.0 18.0 #> 12 Supratidal Coastal Uplands 3769.0 4219.0 #> 13 Supratidal Non-Forested Freshwater Wetlands 68937.0 71787.0 #> 14 Supratidal Forested Freshwater Wetlands 152282.0 152732.0 #> 15 Supratidal Native Uplands 141050.0 142100.0"},{"path":"https://tbep-tech.github.io/tbeptools/articles/habitatmasterplan.html","id":"report-card-summary","dir":"Articles","previous_headings":"","what":"Report card summary","title":"Habitat Master Plan","text":"important reporting product Habitat Master Plan report card summarizes attainment targets goals evaluates prior trends identify coverages trending targets goals. Two functions provided tbeptools create report card. anlz_hmpreport() summarizes datasets provide necessary information creating report card. show_hmpreport() generates plot report card. latter can used former provided need view data behind report card. Using anlz_hmpreport() function summarizes acreage coverage estimates habitat type, compares targets goals year data, assesses coverage trend year pairs determine changes trending targets goals. columns follows: year: Year assessment metric: Habitat type assessed Acres: Coverage estimate year lacres: Coverage estimate previous set available data lyr: Year previous set available data category: Strata habitat type Target: 2030 target habitat type Habitat Master Plan Goal: 2050 goal habitat type Habitat Master Plan acresdiff: Difference acres current year previous set available data yeardiff: Difference years current year previous set available data changerate: Acreage change per year current year relative previous set available data targetrate: Annual rate required achieve 2030 target goalrate: Annual rate required achieve 2050 goal targetprop: Proportion target met current year goalprop: Proportion goal met current year targeteval: number indicating target status current year report card goaleval: number indicating goal status current year report card important columns output targetprop, goalprop, targeteval, goaleval. targetprop goalprop columns indicate proportion target goal met habitat type current assessment year. targeteval goaleval columns one four values, -1, 0, 0.5, 1, habitat type year. numbers define habitat status assessment year: -1: target goal met, trending 0: target goal met, trending 0.5: target goal met, trending 1: target goal met, trending ","code":"anlz_hmpreport(acres = acres, subtacres = subtacres, hmptrgs = hmptrgs) #> # A tibble: 150 × 17 #> year metric Acres lacres lyr category Target Goal acresdiff yeardiff #> #> 1 1990 Seagrasses 25218. 23279. 1988 Subtidal 40000 40000 1939. 2 #> 2 1990 Tidal Fla… 20433. 21686. 1988 Subtidal 16220 16220 -1253. 2 #> 3 1992 Seagrasses 25746. 25218. 1990 Subtidal 40000 40000 528. 2 #> 4 1992 Tidal Fla… 20594. 20433. 1990 Subtidal 16220 16220 161. 2 #> 5 1994 Seagrasses 26524. 25746. 1992 Subtidal 40000 40000 778. 2 #> 6 1994 Tidal Fla… 20244. 20594. 1992 Subtidal 16220 16220 -349. 2 #> 7 1996 Seagrasses 26924. 26524. 1994 Subtidal 40000 40000 400. 2 #> 8 1996 Tidal Fla… 20443. 20244. 1994 Subtidal 16220 16220 199. 2 #> 9 1999 Seagrasses 24840. 26924. 1996 Subtidal 40000 40000 -2083. 3 #> 10 1999 Tidal Fla… 27085. 20443. 1996 Subtidal 16220 16220 6642. 3 #> # ℹ 140 more rows #> # ℹ 7 more variables: changerate , targetrate , goalrate , #> # targetprop , goalprop , targeteval , goaleval "},{"path":"https://tbep-tech.github.io/tbeptools/articles/habitatmasterplan.html","id":"report-card-plot","dir":"Articles","previous_headings":"","what":"Report card plot","title":"Habitat Master Plan","text":"show_hmpreport() can used create Habitat Master Plan report card. anlz_hmpreport() function used internally need used separately. input files . plot shows report card 2030 targets, using typ = \"targets\". colors cell correspond numbers targeteval column (goaleval typ = \"goals\") returned anlz_hmpreport(). numbers cell indicate proportion target targetprop (goal goalprop typ = \"goals\") met habitat type assessment year. Note creation datasets generate summaries continuous year varies subtidal inter/supratidal habitat. 2050 goals report card can shown using typ = \"goals\". subtidal data subtacres inter/supratidal data acres provided different datasets Southwest Florida Water Management District. years dataset typically match dataset collected approximate 2 3 year intervals. default, year y-axis shown continuous variable, gaps shown years dataset unavailable. Use ycollapse = TRUE remove years without data. Different strata can also selected using strata argument. Note use ycollapse = T remove years without data. strata can combined single plot collapsed years using patchwork library. text showing proportion target goal met year can suppressed using text = NULL. size text can changed entering numeric value (default text = 2.5). alternative form report card can returned attainment targets goals likelihood attainment shown differently using colors shapes, respectively. plotted using twocol = T, red shows target goal met, green shows target goal met, arrow shows target goal likely met, arrow shows target goal likely met. report card provides information artificial reefs, living shorelines, hard bottom habitats. habitats assessed routine data products Southwest Florida Water Management District, although targets goals provided Habitat Master Plan.","code":"show_hmpreport(acres = acres, subtacres = subtacres, hmptrgs = hmptrgs, typ = 'targets') show_hmpreport(acres = acres, subtacres = subtacres, hmptrgs = hmptrgs, typ = 'goals') show_hmpreport(acres = acres, subtacres = subtacres, hmptrgs = hmptrgs, typ = 'targets', ycollapse = T) show_hmpreport(acres = acres, subtacres = subtacres, hmptrgs = hmptrgs, typ = 'targets', strata = c('Intertidal', 'Supratidal'), ycollapse = T) library(patchwork) library(ggplot2) p1 <- show_hmpreport(acres = acres, subtacres = subtacres, hmptrgs = hmptrgs, typ = 'targets', strata = 'Subtidal', ycollapse = T) p2 <- show_hmpreport(acres = acres, subtacres = subtacres, hmptrgs = hmptrgs, typ = 'targets', strata = c('Intertidal', 'Supratidal'), ycollapse = T) + labs(title = NULL) p1 + p2 + plot_layout(ncol = 2, guides = 'collect') show_hmpreport(acres = acres, subtacres = subtacres, hmptrgs = hmptrgs, typ = 'targets', text = NULL) show_hmpreport(acres = acres, subtacres = subtacres, hmptrgs = hmptrgs, typ = 'targets', twocol = T)"},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/articles/intro.html","id":"background","dir":"Articles","previous_headings":"","what":"Background","title":"Water Quality Data","text":"Dashboard: https://shiny.tbep.org/wq-dash vignette provides overview functions tbeptools can used work water quality data Tampa Bay. View vignettes topical introductions reporting products (e.g., seagrasess, tidal creeks, etc.). environmental recovery Tampa Bay exceptional success story coastal water quality management. Nitrogen loads mid 1970s estimated 8.2 million kg/yr, approximately 5.5 million kg/yr entering upper Bay alone [2]. Reduced water clarity associated phytoplankton biomass contributed dramatic reduction areal coverage seagrass [3] development hypoxic events, causing decline benthic faunal production [4]. Extensive efforts reduce nutrient loads Bay occurred late 1970s, notable improvements infrastructure wastewater treatment 1979. Improvements water clarity decreases chlorophyll concentrations observed Bay-wide 1980s, conditions generally remaining constant present day [5]. Tracking changes environmental condition past present day possible without long-term monitoring dataset. Data collected monthly Environmental Protection Commission Hillsborough County since 1974 [6,7]. Samples taken forty-five stations water collection monitoring sonde bottom, mid- surface depths, depending parameter. locations monitoring stations fixed cover entire Bay uppermost mesohaline sections lowermost euhaline portions direct interaction Gulf Mexico. 515 observations available different parameters station, e.g., nitrogen, chlorophyll-, secchi depth. Data collected monitoring program processed maintained spreadsheet titled RWMDataSpreadsheet_ThroughCurrentReportMonth.xlsx https://epcbocc.sharepoint.com/:x:/s/Share/EWKgPirIkoxMp9Hm_wVEICsBk6avI9iSRjFiOxX58wXzIQ?e=kAWZXl&download=1 (viewable ). data include observations stations parameters throughout period record. date, systematic tools importing, analyzing, reporting information data. tbeptools package provides developed address need. Locations long-term monitoring stations Tampa Bay. Bay separated four segments defined chemical, physical, geopolitical boundaries.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/articles/intro.html","id":"read","dir":"Articles","previous_headings":"","what":"Read","title":"Water Quality Data","text":"main function importing water quality data read_importwq(). function downloads latest file one already available location specified xlsx input argument. First, create character path location file. one exist, specify desired location name downloaded file. , want put file vignettes folder name current_results.xls. Note file path relative root working directly current R session. can view working directory getwd(). Now pass xlsx object read_importwq() function. get error message function indicating file found. makes sense file doesn’t exist yet, need tell function download latest file. done changing download_latest argument TRUE (default FALSE). Now get message, indication file server downloaded. ’ll data downloaded saved epcdata object finishes downloading. try run function downloading data server, get following message. check done make sure data unnecessarily downloaded current file matches file server. Every time tbeptools used work monitoring data, read_importwq() used import data. always receive message File current... local file matches one server. However, new data regularly collected posted server. download_latest = TRUE local file date, receive following message: argument na indicates fields downloaded spreadsheet treated blank values assigned NA. number strings can added function replace fields NA values. data successfully imported, can view assigned object: data include bay segment name, station number, sample time, year, month, latitude, longitude, station depth, sample depth, total nitrogen, secchi depth, chlorophyll, salinity, water temperature, turbidity, water color. parameters can included setting = TRUE read_importwq(). import function also available download format phytoplankton cell count data. read_importphyto() function works similarly import function water quality data. Start specifying path data downloaded set download_latest TRUE. function download summarize data file PlanktonDataList_ThroughCurrentReportMonth.xlsx EPC website. phytoplankton data successfully imported, can view assigned object: data highly summarized raw data file available online. Cell counts (number cells per 0.1mL) selected taxa summed station quarters (.e., Jan/Feb/Mar, Apr/May/Jun, etc.). quarter indicated yrqrt column specified starting date quarter (e.g., 1975-07-01 quarter Jul/Aug/Sep 1975). data primarily used support analyses water quality dashboard: https://shiny.tbep.org/wq-dash/","code":"xlsx <- 'vignettes/current_results.xlsx' epcdata <- read_importwq(xlsx) epcdata <- read_importwq(xlsx, download_latest = TRUE) #> File vignettes/current_results.xlsx does not exist, replacing with downloaded file... #> trying URL 'https://epcbocc.sharepoint.com/:x:/s/Share/EYXZ5t16UlFGk1rzIU91VogBa8U37lh8z_Hftf2KJISSHg?e=8r1SUL&download=1' length 24562051 bytes (23.4 MB) epcdata <- read_importwq(xlsx, download_latest = TRUE) #> File is current... #> Replacing local file with current... epcdata #> # A tibble: 27,961 × 26 #> bay_segment epchc_station SampleTime yr mo Latitude Longitude #> #> 1 HB 6 2023-12-19 10:01:00 2023 12 27.9 -82.5 #> 2 HB 7 2023-12-19 10:12:00 2023 12 27.9 -82.5 #> 3 HB 8 2023-12-19 12:39:00 2023 12 27.9 -82.4 #> 4 MTB 9 2023-12-19 11:54:00 2023 12 27.8 -82.4 #> 5 MTB 11 2023-12-19 10:25:00 2023 12 27.8 -82.5 #> 6 MTB 13 2023-12-19 10:38:00 2023 12 27.8 -82.5 #> 7 MTB 14 2023-12-19 11:24:00 2023 12 27.8 -82.5 #> 8 MTB 16 2023-12-20 09:35:00 2023 12 27.7 -82.5 #> 9 MTB 19 2023-12-20 09:49:00 2023 12 27.7 -82.6 #> 10 LTB 23 2023-12-20 13:16:00 2023 12 27.7 -82.6 #> # ℹ 27,951 more rows #> # ℹ 19 more variables: Total_Depth_m , Sample_Depth_m , tn , #> # tn_q , sd_m , sd_raw_m , sd_q , chla , #> # chla_q , Sal_Top_ppth , Sal_Mid_ppth , #> # Sal_Bottom_ppth , Temp_Water_Top_degC , #> # Temp_Water_Mid_degC , Temp_Water_Bottom_degC , #> # `Turbidity_JTU-NTU` , Turbidity_Q , Color_345_F45_PCU , … xlsx <- 'phyto_data.xlsx' phytodata <- read_importphyto(xlsx, download_latest = T) #> File vignettes/phyto_data.xlsx does not exist, replacing with downloaded file... #> trying URL 'https://epcbocc.sharepoint.com/:x:/s/Share/ETAfRQ5drmRHntDd1O8s3FQB180Fumed4nQ99w-OIVDxrA?e=eSmtxD&download=1' length 12319508 bytes (11.7 MB) phytodata #> # A tibble: 21,143 × 8 #> epchc_station Date name units count yrqrt yr mo #> #> 1 11 1975-07-23 other /0.1mL 0 1975-07-01 1975 Jul #> 2 11 1976-01-07 other /0.1mL 1 1976-01-01 1976 Jan #> 3 11 1977-01-05 other /0.1mL 1 1977-01-01 1977 Jan #> 4 11 1977-04-20 Tripos hircus /0.1mL 1 1977-04-01 1977 Apr #> 5 11 1977-04-20 other /0.1mL 1 1977-04-01 1977 Apr #> 6 11 1977-07-13 other /0.1mL 12 1977-07-01 1977 Jul #> 7 11 1978-01-11 other /0.1mL 16 1978-01-01 1978 Jan #> 8 11 1979-02-08 other /0.1mL 1 1979-01-01 1979 Feb #> 9 11 1979-05-02 Karenia brevis /0.1mL 1 1979-04-01 1979 May #> 10 11 1979-05-30 other /0.1mL 1 1979-04-01 1979 May #> # ℹ 21,133 more rows"},{"path":"https://tbep-tech.github.io/tbeptools/articles/intro.html","id":"retrieving-additional-water-quality-data","dir":"Articles","previous_headings":"Read","what":"Retrieving additional water quality data","title":"Water Quality Data","text":"water quality functions tbeptools developed work long-term monitoring data Environmental Protection Commission Hillsborough County. Additional monitoring programs Tampa Bay can also used develop complete description water quality. read_importwqp() function can used retrieve data USEPA Water Quality Portal data monitoring organizations around Tampa Bay watershed. function retrieves nutrient, chlorophyll, secchi, temperature, salinity, turbidity data available estuarine stations monitored organization type = 'wq'. data can retrieved follows typically take less one minute download.","code":"# get Manatee County data mancodata <- read_importwqp(org = '21FLMANA_WQX', type = 'wq', trace = T) # get Pinellas County data pincodata <- read_importwqp(org = '21FLPDEM_WQX', type = 'wq', trace = T)"},{"path":"https://tbep-tech.github.io/tbeptools/articles/intro.html","id":"analyze","dir":"Articles","previous_headings":"","what":"Analyze","title":"Water Quality Data","text":"functions anlz_avedat() anlz_avedatsite() summarize station data bay segments sites, respectively. functions return annual means chlorophyll light attenuation (based Secchi depth measurements) monthly means year chlorophyll light attenuation. summaries used determine bay segment targets water quality met using anlz_attain() anlz_attainsite() function. use anlz_avedat() summarize data bay segment estimate annual monthly means chlorophyll light attenuation. output two-element list annual (ann) monthly (mos) means segment. output can analyzed anlz_attain() determine bay segment outcomes met year. results used plotting functions described . short, chl_la column indicates categorical outcome chlorophyll light attenuation segment. outcomes integer values zero three. relative exceedances water quality thresholds segment, duration magnitude, indicated higher integer values. Similar information can obtained individual sites using anlz_avedatsite() anlz_attainsite(). main difference yes/column metis added indicates target segment threshold site.","code":"avedat <- anlz_avedat(epcdata) avedat #> $ann #> # A tibble: 608 × 4 #> yr bay_segment var val #> #> 1 1974 HB mean_chla 22.4 #> 2 1974 LTB mean_chla 4.24 #> 3 1974 MTB mean_chla 9.66 #> 4 1974 OTB mean_chla 10.2 #> 5 1975 HB mean_chla 27.9 #> 6 1975 LTB mean_chla 4.93 #> 7 1975 MTB mean_chla 11.4 #> 8 1975 OTB mean_chla 13.2 #> 9 1976 HB mean_chla 29.5 #> 10 1976 LTB mean_chla 5.08 #> # ℹ 598 more rows #> #> $mos #> # A tibble: 4,724 × 5 #> bay_segment yr mo var val #> #> 1 HB 1974 1 mean_chla 36.2 #> 2 LTB 1974 1 mean_chla 1.75 #> 3 MTB 1974 1 mean_chla 11.5 #> 4 OTB 1974 1 mean_chla 4.4 #> 5 HB 1974 2 mean_chla 42.4 #> 6 LTB 1974 2 mean_chla 5.5 #> 7 MTB 1974 2 mean_chla 9.35 #> 8 OTB 1974 2 mean_chla 4.07 #> 9 HB 1974 3 mean_chla 14.9 #> 10 LTB 1974 3 mean_chla 5.88 #> # ℹ 4,714 more rows anlz_attain(avedat) #> # A tibble: 200 × 4 #> bay_segment yr chl_la outcome #> #> 1 HB 1974 3_0 yellow #> 2 HB 1975 3_2 red #> 3 HB 1976 3_2 red #> 4 HB 1977 3_2 red #> 5 HB 1978 3_3 red #> 6 HB 1979 3_3 red #> 7 HB 1980 3_3 red #> 8 HB 1981 3_3 red #> 9 HB 1982 3_3 red #> 10 HB 1983 3_0 yellow #> # ℹ 190 more rows anlz_avedatsite(epcdata) %>% anlz_attainsite #> # A tibble: 2,250 × 9 #> yr bay_segment epchc_station var val target smallex thresh met #> #> 1 1974 HB 6 chla 25.6 13.2 14.1 15 no #> 2 1974 HB 7 chla 21.6 13.2 14.1 15 no #> 3 1974 HB 8 chla 22.6 13.2 14.1 15 no #> 4 1974 HB 44 chla 23.4 13.2 14.1 15 no #> 5 1974 HB 52 chla 23.5 13.2 14.1 15 no #> 6 1974 HB 55 chla 20.2 13.2 14.1 15 no #> 7 1974 HB 70 chla 33.1 13.2 14.1 15 no #> 8 1974 HB 71 chla 25.8 13.2 14.1 15 no #> 9 1974 HB 73 chla 17.6 13.2 14.1 15 no #> 10 1974 HB 80 chla 10.5 13.2 14.1 15 yes #> # ℹ 2,240 more rows"},{"path":"https://tbep-tech.github.io/tbeptools/articles/intro.html","id":"show","dir":"Articles","previous_headings":"","what":"Show","title":"Water Quality Data","text":"External package libraries R can used plot time series data. ’s example using popular ggplot2 package. data wrangling dplyr done first filter data want plot. show_thrplot() function provides descriptive assessment annual trends chosen bay segment relative defined targets thresholds. plot show annual averages across stations Old Tampa bay (bay_segment = \"OTB\") chlorophyll (thr = \"chla\"). red line shows annual trends horizontal blue lines indicate thresholds targets chlorophyll-specific Old Tampa Bay. dashed dotted blue lines indicate +1 +2 standard errors management target shown filled line. target standard errors considered identifying annual segment outcome chlorophyll. can show plot light attenuation changing thr = \"chla\" thr = \"la\". Note change horizontal reference lines light attenuation target. year range plot can also specified using yrrng argument, default year range epcdata. show_thrplot() function uses results anlz_avedat() function. example, can retrieve values plot follows: Similarly, show_boxplot() function provides assessment seasonal changes chlorophyll light attenuation values bay segment. recent year highlighted red default. allows simple evaluation recent year compared historical averages. large exceedance value shown blue text dotted line. corresponds “large” magnitude change +2 standard errors bay segment threshold dotted line shown show_thrplot(). different subset years selected year interest can also viewed changing yrrng yrsel arguments. show 1980 compared monthly averages 2008 2018. show_thrplot() function useful understand annual variation chlorophyll light attenuation relative management targets bay segment. information plots can provide understanding annual reporting outcomes determined. noted , outcome integer zero three assigned bay segment annual estimate chlorophyll light attenuation. outcomes based exceedance annual estimate threshold target (blue lines show_thrplot()) duration exceedance years prior. following graphic describes logic [8]. Outcomes annual estimates water quality assigned integer value zero three depending magnitude duration exceedence. outcomes assigned chlorophyll light attenuation. duration criteria determined based whether exceedance observed years prior current year. exceedance criteria chlorophyll light-attenuation specific segment. tbeptools package contains targets data file reference determining annual outcomes. file loaded automatically package can viewed command line. final plotting function show_matrix(), creates annual reporting matrix reflects combined outcomes chlorophyll light attenuation. Tracking attainment bay segment specific targets indicators provides framework bay management actions developed initiated. year segment, color-coded management action assigned: Stay Course: Continue planned projects. Report data via annual progress reports Baywide Environmental Monitoring Report. Caution: Review monitoring data nitrogen loading estimates. Begin/continue TAC Management Board development specific management recommendations. Alert: Finalize development implement appropriate management actions get back track. management category action based combination outcomes chlorophyll light attenuation [8]. Management action categories assigned bay segment year based chlorophyll light attenuation outcomes. results can viewed show_matrix(). matrix also ggplot object layout can changed using ggplot elements. Note use txtsz = NULL remove color labels. preferred, matrix can also returned HTML table can sorted scrolled. first ten rows shown default. default number rows (10) can changed nrows argument. Use sufficiently large number show rows. plotly (interactive, dynamic plot) can returned setting plotly argument TRUE. Results can also obtained selected year. Outcomes can returned tabular format anlz_yrattain(). table also shows segment averages chlorophyll light attenuation, including associated targets. map showing individual sites achieved chlorophyll targets can obtained show_sitemap(). station averages chlorophyll selected year shown next point. Stations red failed meet segment target. show_sitemap() function also includes argument specify particular monthly range selected year. option chosen, averages shown continuous values station. Another map can created show_sitesegmap() similar show_sitemap(), except bay segments shown colored annual outcome. map useful understand site data correspond bay segment. Bay segment exceedances can also viewed matrix using show_wqmatrix(). thresholds values correspond Florida DEP criteria (large exceedance defined +2 standard errors segment target). default, show_wqmatrix() function returns chlorophyll exceedances segment. Light attenuation exceedances can viewed changing param argument. results show_matrix() show_wqmatrix() can combined individual segment using show_segmatrix() function. useful understand water quality parameter driving management outcome given year. plot shows light attenuation chlorophyll outcomes show_wqmatrix() next segment management outcomes show_matrix(). one segment can plotted function call. Finally, segment plots can shown together using show_segplotly() function combines chlorophyll secchi data given segment. function combines outputs show_thrplot() show_segmatrix(). final plot interactive can zoomed dragging mouse pointer section plot. Information cell value can seen hovering location plot. plots, can quickly view summary environmental history water quality Tampa Bay. Degraded conditions common early period record, particularly Old Tampa Bay Hillsborough Bay. Conditions began improve late 1980s early 1990s, good conditions persisting present day. However, recent trends Old Tampa Bay shown conditions changing “stay course” “caution”.","code":"toplo <- epcdata %>% filter(epchc_station == '52') ggplot(toplo, aes(x = SampleTime, y = chla)) + geom_line() + geom_point() + scale_y_log10() + labs( y = 'Chlorophyll-a concentration (ug/L)', x = NULL, title = 'Chlorophyll trends', subtitle = 'Hillsborough Bay station 52, all dates' ) + theme_bw() show_thrplot(epcdata, bay_segment = \"OTB\", thr = \"chla\") show_thrplot(epcdata, bay_segment = \"OTB\", thr = \"la\") show_thrplot(epcdata, bay_segment = \"OTB\", thr = \"la\", yrrng = c(2000, 2018)) epcdata %>% anlz_avedat %>% .[['ann']] %>% filter(bay_segment == 'OTB') %>% filter(var == 'mean_la') %>% filter(yr >= 2000 & yr <= 2018) #> # A tibble: 19 × 4 #> yr bay_segment var val #> #> 1 2000 OTB mean_la 0.733 #> 2 2001 OTB mean_la 0.951 #> 3 2002 OTB mean_la 0.927 #> 4 2003 OTB mean_la 1.04 #> 5 2004 OTB mean_la 0.878 #> 6 2005 OTB mean_la 0.769 #> 7 2006 OTB mean_la 0.620 #> 8 2007 OTB mean_la 0.677 #> 9 2008 OTB mean_la 0.696 #> 10 2009 OTB mean_la 0.808 #> 11 2010 OTB mean_la 0.842 #> 12 2011 OTB mean_la 0.912 #> 13 2012 OTB mean_la 0.687 #> 14 2013 OTB mean_la 0.567 #> 15 2014 OTB mean_la 0.606 #> 16 2015 OTB mean_la 0.560 #> 17 2016 OTB mean_la 0.575 #> 18 2017 OTB mean_la 0.682 #> 19 2018 OTB mean_la 0.678 show_boxplot(epcdata, param = 'chla', bay_segment = \"OTB\") show_boxplot(epcdata, param = 'la', bay_segment = \"HB\") show_boxplot(epcdata, param = 'chla', bay_segment = \"OTB\", yrrng = c(2008, 2018), yrsel = 1980) targets #> bay_segment name chla_target chla_smallex chla_thresh #> 1 OTB Old Tampa Bay 8.5 8.9 9.3 #> 2 HB Hillsborough Bay 13.2 14.1 15.0 #> 3 MTB Middle Tampa Bay 7.4 7.9 8.5 #> 4 LTB Lower Tampa Bay 4.6 4.8 5.1 #> 5 BCBN Boca Ciega Bay North 7.7 NaN 8.3 #> 6 BCBS Boca Ciega Bay South 6.1 NaN 6.3 #> 7 TCB Terra Ceia Bay 7.5 NaN 8.7 #> 8 MR Manatee River 7.3 NaN 8.8 #> 9 RALTB Remainder Lower Tampa Bay NaN NaN 5.1 #> la_target la_smallex la_thresh #> 1 0.83 0.86 0.88 #> 2 1.58 1.63 1.67 #> 3 0.83 0.87 0.91 #> 4 0.63 0.66 0.68 #> 5 NaN NaN NaN #> 6 NaN NaN NaN #> 7 NaN NaN NaN #> 8 NaN NaN NaN #> 9 NaN NaN NaN show_matrix(epcdata) show_matrix(epcdata, txtsz = NULL) + scale_y_continuous(expand = c(0,0), breaks = sort(unique(epcdata$yr))) + coord_flip() + theme(axis.text.x = element_text(angle = 45, hjust = 1, size = 7)) show_matrix(epcdata, asreact = TRUE) show_matrix(epcdata, plotly = TRUE) anlz_yrattain(epcdata, yrsel = 2018) #> # A tibble: 4 × 6 #> bay_segment chla_val chla_target la_val la_target outcome #> #> 1 OTB 9.22 8.5 0.678 0.83 yellow #> 2 HB 13.9 13.2 1.09 1.58 green #> 3 MTB 7.05 7.4 0.570 0.83 green #> 4 LTB 4.65 4.6 0.593 0.63 green show_sitemap(epcdata, yrsel = 2018) show_sitemap(epcdata, yrsel = 2018, mosel = c(7, 9)) show_sitesegmap(epcdata, yrsel = 2018) show_wqmatrix(epcdata) show_wqmatrix(epcdata, param = 'la') show_segmatrix(epcdata, bay_segment = 'OTB') show_segplotly(epcdata, width = 1000, height = 600)"},{"path":"https://tbep-tech.github.io/tbeptools/articles/intro.html","id":"reasonable-assurance-reporting","dir":"Articles","previous_headings":"Show","what":"Reasonable Assurance reporting","title":"Water Quality Data","text":"TBEP collaboration Tampa Bay Nitrogen Management Consortium (NMC) reports annually water quality conditions Tampa Bay Reasonable Assurance (RA) plan Florida Department Environmental Protection (FDEP). plan comprehensive approach managing nitrogen pollution Tampa Bay provides “reasonable assurance” designated uses waterbody segments bay maintained restored response potential nutrient impairments. Annual reports FDEP critical part plan tbeptools package includes functions facilitate reporting. functions previously described (e.g., show_wqmatrix()). First, show_annualassess() function can create simple table annual management outcome assessments chlorophyll-light attenuation bay segment. provides summary results given year, including segment-averaged chlorophyll-light attenuation bay segment names colored management outcome. required inputs EPC dataset selected year. Segment Chl-(ug/L) Light Penetration (m-1) 2023 target 2023 target OTB 6.2 8.5 0.73 0.83 HB 6.9 13.2 0.79 1.58 MTB 3.7 7.4 0.47 0.83 LTB 2.6 4.6 0.54 0.63 default caption can also included setting caption = TRUE. Water quality outcomes 2023. Segment Chl-(ug/L) Light Penetration (m-1) 2023 target 2023 target OTB 6.2 8.5 0.73 0.83 HB 6.9 13.2 0.79 1.58 MTB 3.7 7.4 0.47 0.83 LTB 2.6 4.6 0.54 0.63 Second, show_ratab() function provides table annual water quality outcomes relative five-year RA reporting period. table includes associated NMC actions followed based water quality outcomes, actions provide reasonable assurance water quality maintained restored following outcomes. results specific four bay segments. Bay Segment Reasonable Assurance Assessment Steps DATA USED ASSESS ANNUAL REASONABLE ASSURANCE OUTCOME Year 1 (2022) Year 2 (2023) Year 3 (2024) Year 4 (2025) Year 5 (2026) NMC Action 1: Determine observed chlorophyll-exceeds FDEP threshold 9.3 ug/L (7.1) (6.2) years threshold far, necessary NMC Actions 2-5 NMC Action 2: Determine observed chlorophyll-exceedences occurred 2 consecutive years years met threshold, necessary NMC Actions 3-5 NMC Action 3: Determine observed hydrologically-normalized total load exceeds federally-recognized TMDL 486 tons/year N/N/ necessary due observed water quality seagrass conditions bay segment NMC Actions 4-5: Determine entity/source/facility specific exceedences 5-yr average allocation occurred implementation period necessary chlorophyll-threshold met show_ratab() function developed 2022-2026 RA period currently work previous RA periods. function may updated future accommodate different periods.","code":"show_annualassess(epcdata, yrsel = 2023) show_annualassess(epcdata, yrsel = 2023, caption = TRUE) show_ratab(epcdata, yrsel = 2023, bay_segment = 'OTB')"},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/articles/seagrasstransect.html","id":"data-import-and-included-datasets","dir":"Articles","previous_headings":"","what":"Data import and included datasets","title":"Seagrass Transect Data","text":"two datasets included tbeptools show actively monitored transect locations Tampa Bay. trnpts dataset point object starting location transect trnlns dataset line object showing approximate direction length transect beginning point trnpts. dataset also includes MonAgency column indicates monitoring agency collects data transect. two datasets sf() (simple features) objects easily mapped mapview() view locations. transect data can downloaded Water Atlas using read_transect() function. required argument function training, indicates want download training data complete dataset, .e., training = TRUE training = FALSE (default). former case, small dataset downloaded includes data collected annual training event. primarily used internally TBEP staff assess precision among different training crews. data downloaded JSON object formatted internally using read_formtransect() function. Shoot density reported number shoots per square meter corrected quadrat size entered raw data. Abundance reported numeric value 0 -5 Braun-Blanquet coverage estimates blade length cm. Change training argument FALSE download entire transect database. may take seconds. columns complete transect database describe crew (Crew), monitoring agency (MonitoringAgency), sample date (Date), transect name (Transect), meter location quadrat along transect (Site, m), depth site (Depth, cm), Seagrass species (Savspecies), distance seagrass edge transect (SeagrassEdge, m), seagrass variable (var), average value variable (aveval), standard deviation variable appropriate (sdval). raw, unformatted transect data preferred, use raw = TRUE argument read_transect().","code":"trnpts #> Simple feature collection with 66 features and 11 fields #> Geometry type: POINT #> Dimension: XY #> Bounding box: xmin: -82.8089 ymin: 27.49925 xmax: -82.39305 ymax: 28.0001 #> Geodetic CRS: WGS 84 #> First 10 features: #> SEGMENT TRANSECT TRAN_ID Metermark ID LAT_DD LONG_DD MonAgency STATUS #> 1 1 1 S1T1 0 START 27.99498 -82.68325 EPCHC ACTIVE #> 2 1 3 S1T3 0 START 28.00010 -82.66417 EPCHC ACTIVE #> 3 1 5 S1T5 0 START 27.95788 -82.54663 FDEP ACTIVE #> 4 1 6 S1T6 0 START 27.91348 -82.53282 EPCHC ACTIVE #> 5 1 8 S1T8 0 START 27.86233 -82.56867 EPCHC ACTIVE #> 6 1 13 S1T13 0 START 27.92428 -82.70232 EPCHC ACTIVE #> 7 1 14 S1T14 0 START 27.85533 -82.59738 EPCHC ACTIVE #> 8 1 15 S1T15 0 START 27.87408 -82.53098 EPCHC ACTIVE #> 9 1 16 S1T16 0 START 27.88228 -82.62015 PCDEM ACTIVE #> 10 1 17 S1T17 0 START 27.90498 -82.64793 PCDEM ACTIVE #> Comments bay_segment geometry #> 1 OTB POINT (-82.68325 27.99498) #> 2 OTB POINT (-82.66417 28.0001) #> 3 OTB POINT (-82.54663 27.95788) #> 4 OTB POINT (-82.53282 27.91348) #> 5 OTB POINT (-82.56867 27.86233) #> 6 OTB POINT (-82.70232 27.92428) #> 7 OTB POINT (-82.59738 27.85533) #> 8 OTB POINT (-82.53098 27.87408) #> 9 OTB POINT (-82.62015 27.88228) #> 10 OTB POINT (-82.64793 27.90498) trnlns #> Simple feature collection with 61 features and 7 fields #> Geometry type: LINESTRING #> Dimension: XYM #> Bounding box: xmin: -82.8118 ymin: 27.49807 xmax: -82.39306 ymax: 28.0001 #> m_range: mmin: 0 mmax: 2700 #> Geodetic CRS: WGS 84 #> First 10 features: #> OBJECTID Site Shape_Leng MonAgency ActiveYN Comments #> 1 1 S1T1 300.1400 EPCHC YES #> 2 5 S1T13 1102.6182 EPCHC YES #> 3 6 S1T14 800.4500 EPCHC YES #> 4 7 S1T15 701.0075 EPCHC YES #> 5 8 S1T16 998.9961 PCDEM YES #> 6 9 S1T17 2698.5773 PCDEM YES #> 7 10 S1T18 997.5451 EPCHC YES #> 8 12 S1T3 401.5991 EPCHC YES #> 9 14 S1T5 457.5927 FDEP YES #> 10 15 S1T6 398.6606 EPCHC YES #> geometry bearing #> 1 LINESTRING M (-82.68325 27.... 116.533756 #> 2 LINESTRING M (-82.70232 27.... -4.689701 #> 3 LINESTRING M (-82.59738 27.... 109.402541 #> 4 LINESTRING M (-82.53098 27.... -85.765142 #> 5 LINESTRING M (-82.62015 27.... 13.913960 #> 6 LINESTRING M (-82.64791 27.... -21.165576 #> 7 LINESTRING M (-82.61143 27.... -123.050914 #> 8 LINESTRING M (-82.66417 28.... -128.034327 #> 9 LINESTRING M (-82.54663 27.... -121.861907 #> 10 LINESTRING M (-82.53282 27.... -89.362036 cols <- c(\"#E16A86\", \"#CB7F2F\", \"#9F9400\", \"#50A315\", \"#00AC79\", \"#00AAB7\", \"#009ADE\", \"#A87BE4\", \"#DA65C3\") mapview(trnpts, zcol = 'MonAgency', lwd = 0, legend = F, homebutton = F, col.regions = cols) + mapview(trnlns, zcol = 'MonAgency', homebutton = F, layer.name = 'Monitoring Agency', lwd = 4, color = cols) # import training data traindat <- read_transect(training = TRUE) # view the data traindat #> # A tibble: 957 × 11 #> yr grp grpact Crew MonitoringAgency Site Depth Savspecies var aveval #> #> 1 2020 A 2020:… K. H… MCNRD 1 -50 Halodule Abun… 3 #> 2 2020 A 2020:… K. H… MCNRD 1 -50 Halodule Blad… 0 #> 3 2020 A 2020:… K. H… MCNRD 1 -50 Halodule Shor… 0 #> 4 2020 A 2020:… K. H… MCNRD 3 -60 Halodule Abun… 5 #> 5 2020 A 2020:… K. H… MCNRD 3 -60 Halodule Blad… 22 #> 6 2020 A 2020:… K. H… MCNRD 3 -60 Halodule Shor… 27.3 #> 7 2020 A 2020:… K. H… MCNRD 3 -60 Thalassia Abun… 1 #> 8 2020 A 2020:… K. H… MCNRD 3 -60 Thalassia Blad… 45.2 #> 9 2020 A 2020:… K. H… MCNRD 3 -60 Thalassia Shor… 0.667 #> 10 2020 A 2020:… K. H… MCNRD 4 -90 Halodule Abun… 1 #> # ℹ 947 more rows #> # ℹ 1 more variable: sdval # import entire transct dataset as JSON transect <- read_transect(training = FALSE) # view the data transect #> # A tibble: 152,580 × 11 #> Crew MonitoringAgency Date Transect Site Depth Savspecies #> #> 1 Ali Mauer, Melis… PCDEM 2020-11-04 S5T8 0 -5 No Cover #> 2 Ali Mauer, Melis… PCDEM 2020-11-04 S5T8 0 -5 No Cover #> 3 Ali Mauer, Melis… PCDEM 2020-11-04 S5T8 0 -5 No Cover #> 4 Ali Mauer, Melis… PCDEM 2020-11-04 S5T8 10 -12 Halodule #> 5 Ali Mauer, Melis… PCDEM 2020-11-04 S5T8 10 -12 Halodule #> 6 Ali Mauer, Melis… PCDEM 2020-11-04 S5T8 10 -12 Halodule #> 7 Ali Mauer, Melis… PCDEM 2020-11-04 S5T8 100 -180 Syringodi… #> 8 Ali Mauer, Melis… PCDEM 2020-11-04 S5T8 100 -180 Syringodi… #> 9 Ali Mauer, Melis… PCDEM 2020-11-04 S5T8 100 -180 Syringodi… #> 10 Ali Mauer, Melis… PCDEM 2020-11-04 S5T8 11 -20 Halodule #> # ℹ 152,570 more rows #> # ℹ 4 more variables: SeagrassEdge , var , aveval , sdval # raw transect data transectraw <- read_transect(training = FALSE, raw = TRUE) # view the data transectraw #> # A tibble: 51,174 × 46 #> IDall AssessmentYear CreatedAt Crew CountingTech SeagrassEdge Secchi Sonde #> #> 1 2 1998 1998-10-15… NA NA NA NA FALSE #> 2 2 1998 1998-10-15… NA NA NA NA FALSE #> 3 2 1998 1998-10-15… NA NA NA NA FALSE #> 4 2 1998 1998-10-15… NA NA NA NA FALSE #> 5 2 1998 1998-10-15… NA NA NA NA FALSE #> 6 2 1998 1998-10-15… NA NA NA NA FALSE #> 7 2 1998 1998-10-15… NA NA NA NA FALSE #> 8 2 1998 1998-10-15… NA NA NA NA FALSE #> 9 2 1998 1998-10-15… NA NA NA NA FALSE #> 10 2 1998 1998-10-15… NA NA NA NA FALSE #> # ℹ 51,164 more rows #> # ℹ 38 more variables: Weather , Hidden , HiddenReason , #> # IsComplete , QASubmittedAt , ReadyForQA , #> # QACompletedAt , MonitoringAgency , Transect , #> # BaySegment , ID , ObservationDate , Site , #> # Species , SpeciesAbundance , Appearance , #> # BladeLength_1 , BladeLength_2 , BladeLength_3 , …"},{"path":"https://tbep-tech.github.io/tbeptools/articles/seagrasstransect.html","id":"calculating-seagrass-frequency-occurrence","dir":"Articles","previous_headings":"","what":"Calculating seagrass frequency occurrence","title":"Seagrass Transect Data","text":"rest seagrass functions tbeptools developed work complete database. show_complot() function (see ) developed training data. rest functions can used estimate plot frequency occurrence data. anlz_transectocc() function summarizes frequency occurrence transects dates collapsing species results across quadrats within transect. Abundance frequency occurrence estimated Sherwood et al. 2017, equations 1 2 [1]. short, frequency occurrence estimated number instances species observed along transect divided number placements along transect average abundance estimated sum species-specific Braun-Blanquet scores divided number placements along transect. estimates obtained seagrass species, including Caulerpa spp. (attached macroalgae) Dapis (cyanobacteria), whereas attached drift algae species aggregated. Drift attached macroalgae cyanobacteria (Dapis) estimates may accurate prior 2021. second function, anlz_transectave(), takes results anlz_transectocc() estimates annual results across major bay segments seagrass species averaging frequency occurrence across transects. function used internally within show_transectmatrix() function create summary plots. frequency occurrence estimates also binned categories simple trend assessments, e.g., red < 25%, orange 25-50%, yellow 50-75%, green > 75%. Results specific bay segments annual ranges can filtered bay_segment yrrng arguments. third function, anlz_transectavespp(), takes results anlz_transectocc() estimates annual averages across major bay segments last function, results retained individual species. function used internally within show_transectavespp() function create summary plots. summaries aggregated across selected bay segments, .e., default average species/year across segments. Results individual bay segment can returned appropriate argument, e.g., using bay_segment = 'OTB' select Old Tampa Bay. Results can also filtered specific species using species argument, default return . Caulerpa spp. Dapis spp. also included. Results individual bay segments anlz_transectavespp() can retained setting by_seg argument TRUE. Note totals returned case.","code":"transectocc <- anlz_transectocc(transect) transectocc #> # A tibble: 37,625 × 6 #> # Groups: Date, Transect [1,505] #> Date Transect Savspecies nsites foest bbest #> #> 1 1997-10-11 S2T3 \"AA\" 41 0 0 #> 2 1997-10-11 S2T3 \"Caulerpa\" 41 0 0 #> 3 1997-10-11 S2T3 \"DA\" 41 0 0 #> 4 1997-10-11 S2T3 \"DB: Dictyota\\r\\n\" 41 0 0 #> 5 1997-10-11 S2T3 \"DB: Drift Brown\\r\\n\" 41 0 0 #> 6 1997-10-11 S2T3 \"DG: Chaetomorpha\\r\\n\" 41 0 0 #> 7 1997-10-11 S2T3 \"DG: Drift Green\" 41 0 0 #> 8 1997-10-11 S2T3 \"DG: Ulva\" 41 0 0 #> 9 1997-10-11 S2T3 \"DG: Ulva fasciata\\r\\n\" 41 0 0 #> 10 1997-10-11 S2T3 \"DR: Acanthophora\" 41 0 0 #> # ℹ 37,615 more rows transectave <- anlz_transectave(transectocc) transectave #> # A tibble: 156 × 4 #> # Groups: bay_segment [6] #> bay_segment yr foest focat #> #> 1 Tampa Bay 1998 58.0 #E9C318 #> 2 OTB 1998 65.5 #E9C318 #> 3 HB 1998 15.0 #CC3231 #> 4 MTB 1998 53.7 #E9C318 #> 5 LTB 1998 80.8 #2DC938 #> 6 BCB 1998 81.0 #2DC938 #> 7 Tampa Bay 1999 51.5 #E9C318 #> 8 OTB 1999 64.7 #E9C318 #> 9 HB 1999 10.1 #CC3231 #> 10 MTB 1999 51.8 #E9C318 #> # ℹ 146 more rows transectavespp <- anlz_transectavespp(transectocc) transectavespp #> # A tibble: 208 × 3 #> yr Savspecies foest #> #> 1 1998 Caulerpa 0.0166 #> 2 1998 Dapis 0 #> 3 1998 Halodule 0.361 #> 4 1998 Halophila 0 #> 5 1998 Ruppia 0.0112 #> 6 1998 Syringodium 0.0451 #> 7 1998 Thalassia 0.254 #> 8 1998 total 0.580 #> 9 1999 Caulerpa 0.0277 #> 10 1999 Dapis 0 #> # ℹ 198 more rows transectavespp <- anlz_transectavespp(transectocc, by_seg = TRUE) transectavespp #> # A tibble: 1,170 × 5 #> yr bay_segment Savspecies foest nsites #> #> 1 1998 BCB Caulerpa 0 96 #> 2 1998 BCB Dapis 0 96 #> 3 1998 BCB Halodule 0.613 96 #> 4 1998 BCB Halophila 0 96 #> 5 1998 BCB No Cover 0.190 96 #> 6 1998 BCB Ruppia 0 96 #> 7 1998 BCB Syringodium 0 96 #> 8 1998 BCB Thalassia 0.304 96 #> 9 1998 BCB total 0.810 96 #> 10 1998 HB Caulerpa 0 285 #> # ℹ 1,160 more rows"},{"path":"https://tbep-tech.github.io/tbeptools/articles/seagrasstransect.html","id":"plotting-results","dir":"Articles","previous_headings":"","what":"Plotting results","title":"Seagrass Transect Data","text":"one plotting function training data. show_compplot() function used compare training data crews selected species (species argument) variable (varplo argument). rest plotting functions work complete transect data. Data individual transect can viewed show_transect() function entering transect (site) number, species (one many), variable plot. plot shows relative values selected species variable distance along transect (x-axis) year sampling (y-axis). plots provide overall summary temporal spatial changes selected seagrass metric individual location. plot can also produced plotly interactive plot setting plotly = TRUE inside function. Note size legend merged species legend, point size average abundance species. sizes can viewed mouseover point. show_transect() function can also used plot multiple species. One many species can provided species argument. plots can also separated facets species using facet = TRUE. useful reduce overplotting multiple species found location. show_transectsum() function provides alternative summary data individual transect. plot provides quick visual assessment frequency occurrence abundance multiple species changed time selected transect. Unlike show_transect(), plot shows aggregated results across quadrats along transect uses summarized data anlz_transectocc() function input. summary matrix frequency occurrence estimates across species can plotted show_transectmatrix(). uses results anlz_transectocc() anlz_transectave() functions estimate annual averages bay segment. continuous frequency occurrence estimates binned color categories described , Table 1 [2]. default color scheme based arbitrary breaks 25, 50, 75 percent frequency occurrence. don’t necessarily translate ecological breakpoints. Use neutral = TRUE use neutral continuous color palette. matrix can also produced plotly interactive plot setting plotly = TRUE inside function. Time series plots annual averages frequency occurrence estimates species can shown show_transectavespp() function. default, estimates averaged across bay segments species. plot representation Figure 2 [2]. Results individual segments species can returned bay_segment species arguments. Use argument total = FALSE omit total frequency occurrence plot. plot can also produced plotly interactive plot setting plotly = TRUE inside function. alternative plotting species averages time show_transectavespp(), table can created setting asreact = TRUE. Filtering options apply plot also apply table, e.g., filtering four major bay segments specific year ranges. Also note totals returned table. describes methods tbeptools working transect monitoring data. Seagrass coverage maps also created approximately biennially Southwest Florida Water Management District, available https://data-swfwmd.opendata.arcgis.com/. seagrass data object included package shows Tampa Bay coverage total year available data, including 1950s reference estimate. show_seagrasscoverage() function creates flagship seagrass coverage graphic report changes time data.","code":"show_compplot(traindat, yr = 2023, site = '2', species = 'Halodule', varplo = 'Abundance', base_size = 14) show_transect(transect, site = 'S3T10', species = 'Halodule', varplo = 'Abundance') show_transect(transect, site = 'S3T10', species = 'Halodule', varplo = 'Abundance', plotly = T) show_transect(transect, site = 'S3T10', species = c('Halodule', 'Syringodium', 'Thalassia'), varplo = 'Abundance') show_transect(transect, site = 'S3T10', species = c('Halodule', 'Syringodium', 'Thalassia'), varplo = 'Abundance', facet = TRUE) show_transectsum(transectocc, site = 'S3T10') show_transectmatrix(transectocc) show_transectmatrix(transectocc, neutral = T) show_transectmatrix(transectocc, plotly = T) show_transectavespp(transectocc) show_transectavespp(transectocc, bay_segment = 'LTB', species = c('Syringodium', 'Thalassia'), total = FALSE) show_transectavespp(transectocc, bay_segment = 'LTB', species = c('Syringodium', 'Thalassia'), plotly = T) show_transectavespp(transectocc, asreact = T, bay_segment = c('HB', 'OTB', 'MTB', 'LTB'), yrrng = c(2006, 2012)) show_seagrasscoverage(seagrass)"},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/articles/tbbi.html","id":"background","dir":"Articles","previous_headings":"","what":"Background","title":"Tampa Bay Benthic Index","text":"Tampa Bay Benthic Index (TBBI) [1,2]) assessment method quantifies ecological health benthic community Tampa Bay. index provides complementary approach evaluating environmental condition supported assessment methods currently available region (e.g., water quality report card, nekton index, etc.). tbeptools package includes several functions described import data required index plot results view trends time. functions described detail . TBBI uses data Tampa Bay Benthic Monitoring Program part Environmental Protection Commission (EPC) Hillsborough Country. data updated annually public site maintained EPC, typically December Summer/Fall sampling. website hosts water quality data used water quality report card. required data TBBI extensive water quality report card data made available zipped folder csv files, available . process downloading working data similar functions tbeptools.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/articles/tbbi.html","id":"data-import-and-included-datasets","dir":"Articles","previous_headings":"","what":"Data import and included datasets","title":"Tampa Bay Benthic Index","text":"Data calculating TBBI scores can imported current R session using read_importbenthic() function. function downloads zipped folder base tables used TBBI EPC site data already downloaded location specified input arguments. download data tbeptools, first create character path location want download zipped files. one exist, specify location name downloaded file. , name folder benthic.zip download desktop. Running code return following error: get error message function indicating file found. makes sense file exist yet, need tell function download latest file. done changing download_latest argument TRUE (default FALSE). Now get indication file server downloaded. download complete, ’ll data downloaded saved benthicdata object current R session. try run function downloading data, get following message. check done make sure data unnecessarily downloaded current file matches file server. Every time tbeptools used work benthic data, read_importbenthic() used import data. always receive message File current... local file matches one server. However, data periodically updated posted server. download_latest = TRUE local file date, receive following message:","code":"path <- '~/Desktop/benthic.zip' benthicdata <- read_importbenthic(path) #> Error in read_importbenthic() : File at path does not exist, use download_latest = TRUE benthicdata <- read_importbenthic(path, download_latest = T) #> File ~/Desktop/benthic.zip does not exist, replacing with downloaded file... #> trying URL 'https://epcbocc.sharepoint.com/:u:/s/Share/EQUCWBuwCNdGuMREYAyAD1gBKC98mYtCHMWX0FYLrbT4KA?e=nDfnnQ&download=1' length 37122877 bytes (35.4 MB) benthicdata <- read_importbenthic(path, download_latest = T) #> File is current.. #> Replacing local file with current..."},{"path":"https://tbep-tech.github.io/tbeptools/articles/tbbi.html","id":"calculating-tbbi-scores","dir":"Articles","previous_headings":"","what":"Calculating TBBI scores","title":"Tampa Bay Benthic Index","text":"data imported, can view assigned object. data provided nested tibble includes three different datasets: station information, field sample data (salinity), detailed taxa information. individual datasets can viewed extracting parent object using deframe() function tibble package. anlz_tbbiscr() function uses nested benthicdata estimate TBBI scores site. TBBI scores typically range 0 100 grouped categories describe general condition benthic community. Scores less 73 considered “degraded”, scores 73 87 “intermediate”, scores greater 87 “healthy”. Locations sampled organisms found assigned score zero category “empty sample”. total abundance (TotalAbundance, organisms/m2), species richness (SpeciesRichness) bottom salinity (Salinity, psu) also provided. metrics TBBI corrected salinity bottom measurements taken time sampling required accurate calculation TBBI.","code":"benthicdata #> # A tibble: 3 × 2 #> name value #> #> 1 stations #> 2 fieldsamples #> 3 taxacounts # see all deframe(benthicdata) #> $stations #> # A tibble: 4,787 × 10 #> StationID StationNumber AreaAbbr FundingProject ProgramID ProgramName #> #> 1 448 02BBs301 MTB Apollo Beach 4 Benthic Monitoring #> 2 449 02BBs305 MTB Apollo Beach 4 Benthic Monitoring #> 3 450 02BBs307 MTB Apollo Beach 4 Benthic Monitoring #> 4 451 02BBs364 MTB Apollo Beach 4 Benthic Monitoring #> 5 452 02BBs369 MTB Apollo Beach 4 Benthic Monitoring #> 6 453 02BBs395 MTB Apollo Beach 4 Benthic Monitoring #> 7 454 02BBs397 MTB Apollo Beach 4 Benthic Monitoring #> 8 455 02BBs398 MTB Apollo Beach 4 Benthic Monitoring #> 9 456 02BBs401 MTB Apollo Beach 4 Benthic Monitoring #> 10 457 02BBs402 MTB Apollo Beach 4 Benthic Monitoring #> # ℹ 4,777 more rows #> # ℹ 4 more variables: Latitude , Longitude , date , yr #> #> $fieldsamples #> # A tibble: 5,197 × 3 #> StationID date Salinity #> #> 1 448 2002-05-21 30.5 #> 2 449 2002-05-20 30.8 #> 3 450 2002-05-21 30.5 #> 4 451 2002-05-21 30.6 #> 5 452 2002-05-20 30 #> 6 453 2002-05-21 30.6 #> 7 454 2002-05-21 30.5 #> 8 455 2002-05-21 30.3 #> 9 456 2002-05-20 30.0 #> 10 457 2002-05-20 29.9 #> # ℹ 5,187 more rows #> #> $taxacounts #> # A tibble: 149,657 × 7 #> StationID TaxaCountID TaxaListID FAMILY NAME TaxaCount AdjCount #> #> 1 11321 152055 1198 Anomiidae Anomia … 1 25 #> 2 11321 152056 1224 Carditidae Cardite… 1 25 #> 3 584 233277 624 Cirratulidae Chaetoz… 1 25 #> 4 11321 152057 1306 Veneridae Chione … 3 75 #> 5 3132 239443 352 Pilargidae Sigambr… 14 350 #> 6 11321 152058 1088 Pyramidellidae Turboni… 6 150 #> 7 2541 140530 258 NULL NEMERTEA 8 200 #> 8 2542 140531 258 NULL NEMERTEA 2 50 #> 9 2992 140631 262 NULL Palaeon… 4 100 #> 10 3003 140635 285 Tetrastemmatidae Tetrast… 2 50 #> # ℹ 149,647 more rows # get only station dat deframe(benthicdata)[['stations']] #> # A tibble: 4,787 × 10 #> StationID StationNumber AreaAbbr FundingProject ProgramID ProgramName #> #> 1 448 02BBs301 MTB Apollo Beach 4 Benthic Monitoring #> 2 449 02BBs305 MTB Apollo Beach 4 Benthic Monitoring #> 3 450 02BBs307 MTB Apollo Beach 4 Benthic Monitoring #> 4 451 02BBs364 MTB Apollo Beach 4 Benthic Monitoring #> 5 452 02BBs369 MTB Apollo Beach 4 Benthic Monitoring #> 6 453 02BBs395 MTB Apollo Beach 4 Benthic Monitoring #> 7 454 02BBs397 MTB Apollo Beach 4 Benthic Monitoring #> 8 455 02BBs398 MTB Apollo Beach 4 Benthic Monitoring #> 9 456 02BBs401 MTB Apollo Beach 4 Benthic Monitoring #> 10 457 02BBs402 MTB Apollo Beach 4 Benthic Monitoring #> # ℹ 4,777 more rows #> # ℹ 4 more variables: Latitude , Longitude , date , yr tbbiscr <- anlz_tbbiscr(benthicdata) tbbiscr #> # A tibble: 4,787 × 15 #> StationID StationNumber AreaAbbr FundingProject ProgramID ProgramName #> #> 1 448 02BBs301 MTB Apollo Beach 4 Benthic Monitoring #> 2 449 02BBs305 MTB Apollo Beach 4 Benthic Monitoring #> 3 450 02BBs307 MTB Apollo Beach 4 Benthic Monitoring #> 4 451 02BBs364 MTB Apollo Beach 4 Benthic Monitoring #> 5 452 02BBs369 MTB Apollo Beach 4 Benthic Monitoring #> 6 453 02BBs395 MTB Apollo Beach 4 Benthic Monitoring #> 7 454 02BBs397 MTB Apollo Beach 4 Benthic Monitoring #> 8 455 02BBs398 MTB Apollo Beach 4 Benthic Monitoring #> 9 456 02BBs401 MTB Apollo Beach 4 Benthic Monitoring #> 10 457 02BBs402 MTB Apollo Beach 4 Benthic Monitoring #> # ℹ 4,777 more rows #> # ℹ 9 more variables: Latitude , Longitude , date , yr , #> # TotalAbundance , SpeciesRichness , TBBI , TBBICat , #> # Salinity "},{"path":"https://tbep-tech.github.io/tbeptools/articles/tbbi.html","id":"plotting-results","dir":"Articles","previous_headings":"","what":"Plotting results","title":"Tampa Bay Benthic Index","text":"TBBI scores can viewed annual averages bay segment using show_tbbimatrix() function. show_tbbimatrix() plots annual bay segment averages categorical values conventional “stoplight” graphic. baywide estimate also returned, one based samples across locations (“”) another weighted relative surface areas bay segment (“(wt)”). input show_tbbimatrix() function output anlz_tbbiscr() function. matrix can also produced plotly interactive plot setting plotly = TRUE inside function.","code":"show_tbbimatrix(tbbiscr) show_tbbimatrix(tbbiscr, plotly = T)"},{"path":"https://tbep-tech.github.io/tbeptools/articles/tbbi.html","id":"additional-sediment-data","dir":"Articles","previous_headings":"","what":"Additional sediment data","title":"Tampa Bay Benthic Index","text":"addition biological data, sediment contaminant concentrations measured sites within Tampa Bay. include 100 different constituents grouped broadly metals, organics, physical, . concentrations constituents can compared relative Threshold Effects Levels (TEL) Potential Effects Levels (PEL), available, relative indications likelihood concentrations toxic effects invertebrates inhabit sediments. functions tbeptools can used retrieve sediment data provide indication concentrations relative TEL PEL thresholds. read_importsediment() function retrieve sediment data Tampa Bay collected annually Environmental Protection Commission Hillsborough County. data retrieved location biological data used calculate TBBI. data imported, can view assigned object. show_sedimentmap() function can used create maps selected parameters relative TEL PEL values. Green points show concentrations TEL, yellow points show concentrations TEL PEL, red points show concentrations PEL. applicable TEL PEL values parameter indicated legend. selected stations sampled years within yrrng argument. single year data can shown well. map showing concentrations returned TEL PEL values available parameter. Maps total contaminant values (e.g., Total DDT, Total PAH, Total PCB, Total LMW PAH, Total HMW PAH) can also returned. Although totals included sedimentdata object, calculated tbeptools using anlz_sedimentaddtot() function. Simply entering name total parameter show_sedimentmap() function produce summary map. PEL ratio can also used assess relative sediment quality given measured contaminants. show_sedimentpelmap() function creates map average PEL ratios graded F benthic stations monitored Tampa Bay. PEL ratio contaminant concentration divided Potential Effects Levels (PEL) applies contaminant, available. Higher ratios lower grades indicate sediment conditions likely unfavorable invertebrates. station average combines PEL ratios across contaminants measured station. average PEL ratios grades used create map can also returned data frame using anlz_sedimentpel(). Plots bay segment averages sediment concentrations selected parameters can created show_sedimentave(). plot includes appropriate lines TEL PEL values, well grand mean across segments. former omitted plot unavailable selected parameter. plot can returned interactive plotly object using plotly = T. values used plot can returned anlz_sedimentave(). , total contaminant values (e.g., Total DDT, Total PAH, Total PCB, Total LMW PAH, Total HMW PAH) can also returned even though included sedimentdata object. anlz_sedimentaddtot() function used calculate totals within anlz_sedimentave(). similar plot bay segment averages average PEL ratios can created show_sedimentpelave(). colors indicate grades (green) F (red). plot can returned interactive plotly object using plotly = T. values used plot can returned anlz_sedimentpelave(). show_sedimentalratio() function creates plot selected metal parameter Aluminum. plot provides information concentration parameter relative background levels, Aluminum present common metal Earth’s crust. elevated ratio metal parameter relative aluminum suggests higher background concentrations [3]. linear fit log-log model shown solid black line, 95% prediction intervals. TEL/PEL values, available, also shown horizontal red lines. plot can returned interactive plotly object using plotly = T.","code":"path <- '~/Desktop/sediment.zip' sedimentdata <- read_importsediment(path, download_latest = T) sedimentdata #> # A tibble: 221,597 × 24 #> ProgramId ProgramName FundingProject yr AreaAbbr StationID StationNumber #> #> 1 4 Benthic Moni… TBEP 1993 HB 2463 93HB15 #> 2 4 Benthic Moni… TBEP 1993 HB 2463 93HB15 #> 3 4 Benthic Moni… TBEP 1993 HB 2463 93HB15 #> 4 4 Benthic Moni… TBEP 1993 HB 2463 93HB15 #> 5 4 Benthic Moni… TBEP 1993 HB 2463 93HB15 #> 6 4 Benthic Moni… TBEP 1993 HB 2463 93HB15 #> 7 4 Benthic Moni… TBEP 1993 HB 2463 93HB15 #> 8 4 Benthic Moni… TBEP 1993 HB 2463 93HB15 #> 9 4 Benthic Moni… TBEP 1993 HB 2463 93HB15 #> 10 4 Benthic Moni… TBEP 1993 HB 2463 93HB15 #> # ℹ 221,587 more rows #> # ℹ 17 more variables: Latitude , Longitude , Replicate , #> # SedResultsType , Parameter , ValueAdjusted , Units , #> # Qualifier , MDLnum , PQLnum , TEL , PEL , #> # BetweenTELPEL , ExceedsPEL , PELRatio , #> # PreparationDate , AnalysisTimeMerge show_sedimentmap(sedimentdata, param = 'Arsenic', yrrng = c(1993, 2022)) show_sedimentmap(sedimentdata, param = 'Arsenic', yrrng = 2022) show_sedimentmap(sedimentdata, param = 'Selenium', yrrng = c(1993, 2022)) show_sedimentmap(sedimentdata, param = 'Total DDT', yrrng = c(1993, 2022)) show_sedimentpelmap(sedimentdata, yrrng = c(1993, 2022)) anlz_sedimentpel(sedimentdata, yrrng = c(1993, 2022)) #> # A tibble: 2,233 × 7 #> yr AreaAbbr StationNumber Latitude Longitude PELRatio Grade #> #> 1 1993 HB 93HB15 27.8 -82.4 0.0157 B #> 2 1993 HB 93HB16 27.8 -82.5 0.0261 C #> 3 1993 HB 93HB23 27.9 -82.4 0.0174 B #> 4 1993 LTB 93LTB24 27.7 -82.6 0.0124 B #> 5 1993 LTB 93LTB25 27.6 -82.6 0.0189 B #> 6 1993 LTB 93LTB26 27.6 -82.7 0.00997 B #> 7 1993 LTB 93LTB27 27.6 -82.7 0.0125 B #> 8 1993 LTB 93LTB28 27.6 -82.7 0.0887 D #> 9 1993 LTB 93LTB29 27.6 -82.6 0.0350 C #> 10 1993 LTB 93LTB30 27.6 -82.6 0.0496 C #> # ℹ 2,223 more rows show_sedimentave(sedimentdata, param = 'Arsenic', yrrng = c(1993, 2022)) show_sedimentave(sedimentdata, param = 'Arsenic', yrrng = c(1993, 2022), plotly = T) anlz_sedimentave(sedimentdata, param = 'Arsenic', yrrng = c(1993, 2022)) #> # A tibble: 7 × 8 #> AreaAbbr TEL PEL Units ave lov hiv grandave #> #> 1 BCB 7.24 41.6 mg/kg 2.64 2.34 2.94 2.57 #> 2 HB 7.24 41.6 mg/kg 2.93 0.665 5.20 2.57 #> 3 LTB 7.24 41.6 mg/kg 2.93 2.47 3.40 2.57 #> 4 MR 7.24 41.6 mg/kg 1.66 1.37 1.95 2.57 #> 5 MTB 7.24 41.6 mg/kg 2.17 1.86 2.48 2.57 #> 6 OTB 7.24 41.6 mg/kg 3.24 0.707 5.78 2.57 #> 7 TCB 7.24 41.6 mg/kg 2.40 1.92 2.88 2.57 anlz_sedimentave(sedimentdata, param = 'Total DDT', yrrng = c(1993, 2022)) #> # A tibble: 7 × 8 #> AreaAbbr TEL PEL Units ave lov hiv grandave #> #> 1 BCB 3.89 51.7 ug/kg 0.570 0.382 0.757 0.700 #> 2 HB 3.89 51.7 ug/kg 1.77 0.870 2.67 0.700 #> 3 LTB 3.89 51.7 ug/kg 0.218 0.105 0.332 0.700 #> 4 MR 3.89 51.7 ug/kg 0.838 0.517 1.16 0.700 #> 5 MTB 3.89 51.7 ug/kg 0.434 0.285 0.582 0.700 #> 6 OTB 3.89 51.7 ug/kg 0.490 0.274 0.706 0.700 #> 7 TCB 3.89 51.7 ug/kg 0.582 0.202 0.962 0.700 show_sedimentpelave(sedimentdata, yrrng = c(1993, 2022)) show_sedimentpelave(sedimentdata, yrrng = c(1993, 2022), plotly = T) anlz_sedimentpelave(sedimentdata, yrrng = c(1993, 2022)) #> # A tibble: 7 × 5 #> AreaAbbr ave lov hiv grandave #> #> 1 BCB 0.0535 0.0445 0.0625 0.0522 #> 2 HB 0.118 0.0663 0.169 0.0522 #> 3 LTB 0.0281 0.0247 0.0315 0.0522 #> 4 MR 0.0446 0.0375 0.0516 0.0522 #> 5 MTB 0.0374 0.0327 0.0421 0.0522 #> 6 OTB 0.0506 0.0371 0.0642 0.0522 #> 7 TCB 0.0337 0.0265 0.0409 0.0522 show_sedimentalratio(sedimentdata, param = 'Zinc', bay_segment = c('HB', 'LTB')) show_sedimentalratio(sedimentdata, param = 'Zinc', bay_segment = c('HB', 'LTB'), plotly = T)"},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/articles/tbni.html","id":"background","dir":"Articles","previous_headings":"","what":"Background","title":"Tampa Bay Nekton Index","text":"Tampa Bay Nekton Index (TBNI) [1,2]) multimetric assessment method quantifies ecological health nekton community Tampa Bay. index provides complementary approach evaluating environmental condition supported assessment methods currently available Tampa Bay (e.g., water quality report card, Benthic index, etc.). tbeptools package includes several functions described import data required index, analyze data calculate metrics index scores, plot results view trends time. functions described detail . TBNI uses catch data Florida Fish Wildlife Conservation Commission (FWC) Fish Wildlife Research Institute’s (FWRI) Fisheries-Independent Monitoring (FIM) program. Catch results center-bag seine longest consistent record FIM database used develop TBNI. include counts taxa identification individuals caught near shore areas, generally early recruits, juveniles, smaller-bodied nekton. fish selected invertebrates identified lowest possible taxon (usually species), counted, subset measured. Current protocols established 1998 TBNI estimates unavailable prior date.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/articles/tbni.html","id":"data-import-and-included-datasets","dir":"Articles","previous_headings":"","what":"Data import and included datasets","title":"Tampa Bay Nekton Index","text":"Data required calculating TBNI scores can imported current R session using read_importfim() function. function downloads latest FIM file FTP site data already downloaded location specified input arguments. download data, first create character path location file. one exist, specify desired location name downloaded file. , want put file desktop home directory name fimdata.csv. Running code return following error: get error message function indicating file found. makes sense file doesn’t exist yet, need tell function download latest file. done changing download_latest argument TRUE (default FALSE). Now get indication file server downloaded. download complete, ’ll data downloaded saved fimdata object current R session. try run function downloading data server, get following message. check done make sure data unnecessarily downloaded current matches file server. Every time tbeptools used work FIM data, read_importfim() used import data. always receive message File current... local file matches one server. However, new data regularly collected posted server. download_latest = TRUE local file date, receive following message: data successfully imported, can view assigned object: imported data formatted calculating TBNI. columns include Reference FIM sampling site, sampling date, sampling Zone, sampling Grid, NODCCODE unique identifier species, sample year, sample month, total catch Total_N, scientific name, column indicating species included index, several columns indicating species-specific information required metrics. final columns, separate lookup table provided package merged imported FIM data. file, tbnispp, can viewed anytime package loaded: read_importfim() function can also return simple features object sampled stations raw FIM data setting . data matched appropriate bay segments tabulating TBNI scores. resulting dataset indicates sampling occurred can mapped mapview() function. ease use, dataset named fimstations included tbeptools. read_importfim() function processes observed data needed TBNI, including merging rows tbnispp fimstations data. imported, metrics scores can calculated.","code":"csv <- '~/Desktop/fimdata.csv' fimdata <- read_importfim(csv) #> Error in read_importfim(csv) : file.exists(csv) is not TRUE fimdata <- read_importfim(csv, download_latest = T) #> File ~/Desktop/fimdata.csv does not exist, replacing with downloaded file... #> trying URL 'ftp://ftp.floridamarine.org/users/fim/tmac/NektonIndex/TampaBay_NektonIndexData.csv' length 11083878 bytes (10.6 MB) fimdata <- read_importfim(csv, download_latest = T) #> File is current.. #> Replacing local file with current... head(fimdata) #> # A tibble: 6 × 19 #> Reference Sampling_Date Latitude Longitude Zone Grid NODCCODE Year Month #> #> 1 TBM19980109… 1998-01-09 28.0 -82.7 A 31 8747020… 1998 1 #> 2 TBM19980109… 1998-01-09 28.0 -82.7 A 31 8805020… 1998 1 #> 3 TBM19980109… 1998-01-09 27.9 -82.7 A 62 6177010… 1998 1 #> 4 TBM19980109… 1998-01-09 27.9 -82.7 A 63 9998000… 1998 1 #> 5 TBM19980109… 1998-01-09 27.9 -82.6 A 65 8820020… 1998 1 #> 6 TBM19980109… 1998-01-09 27.9 -82.6 A 65 8826020… 1998 1 #> # ℹ 10 more variables: Total_N , ScientificName , #> # Include_TB_Index , Hab_Cat , Est_Cat , Est_Use , #> # Feeding_Cat , Feeding_Guild , Selected_Taxa , #> # bay_segment head(tbnispp) #> NODCCODE ScientificName Include_TB_Index Hab_Cat Est_Cat #> 1 8860030201 Acanthostracion quadricornis Y B MS #> 2 8858010000 Achiridae spp. N B ES #> 3 8858030202 Achirus lineatus Y B ES #> 4 8804040401 Adinia xenica Y B ES #> 5 8713070101 Aetobatus narinari Y B MS #> 6 8739010101 Albula vulpes Y P MS #> Est_Use Feeding_Cat Feeding_Guild Selected_Taxa #> 1 O TS ZB N #> 2 O TS ZB N #> 3 O TS ZB N #> 4 O TS ZP N #> 5 F TS ZB N #> 6 S TS ZB Y fimstations <- read_importfim(csv, download_latest = TRUE, locs = TRUE) mapview(fimstations, zcol = 'bay_segment')"},{"path":"https://tbep-tech.github.io/tbeptools/articles/tbni.html","id":"calculating-metrics-and-tbni-scores","dir":"Articles","previous_headings":"","what":"Calculating metrics and TBNI scores","title":"Tampa Bay Nekton Index","text":"Metrics scores Tampa Bay Nekton Index can calculated using two functions. anlz_tbnimet() function calculates raw metrics anlz_tbniscr() function calculates scored metrics final TBNI score. functions use imported formatted FIM data input. TBNI includes five metrics sensitive stressor gradients provide unique information Nekton community response environmental conditions. metrics include: NumTaxa: Species richness BenthicTaxa: Species richness benthic taxa TaxaSelect: Number “selected” species (.e., commercially /recreationally important) NumGuilds: Number trophic guilds Shannon: Shannon Diversity (H) Raw metrics first calculated observed data scaled standard score 0 - 10 accounting expected relationships environmental gradients 5th/95th percentiles distributions. final TBNI score summed average scores ranging 0 - 100. raw metrics, scored metrics, final TBNI score returned anlz_tbniscr() function. five metrics chosen TBNI appropriate Tampa Bay dataset selected larger pool candidate metrics. potential metrics can calculated using anlz_tbnimet() function. metrics can used standalone assessments developing Nekton index outside Tampa Bay. argument = TRUE must used return metrics, otherwise selected five TBNI returned.","code":"tbniscr <- anlz_tbniscr(fimdata) head(tbniscr) #> # A tibble: 6 × 16 #> Reference Year Month Season bay_segment TBNI_Score NumTaxa ScoreNumTaxa #> #> 1 TBM1998010906 1998 1 Winter OTB 18 2 2 #> 2 TBM1998010910 1998 1 Winter OTB 14 1 1 #> 3 TBM1998010912 1998 1 Winter OTB 0 0 0 #> 4 TBM1998010914 1998 1 Winter OTB 20 2 2 #> 5 TBM1998010915 1998 1 Winter MTB 46 4 4 #> 6 TBM1998010917 1998 1 Winter MTB 24 2 2 #> # ℹ 8 more variables: BenthicTaxa , ScoreBenthicTaxa , #> # TaxaSelect , ScoreTaxaSelect , NumGuilds , #> # ScoreNumGuilds , Shannon , ScoreShannon tbnimet <- anlz_tbnimet(fimdata, all = T) head(tbnimet) #> # A tibble: 6 × 37 #> Reference Year Month Season bay_segment NumTaxa NumIndiv Shannon Simpson #> #> 1 TBM1998010906 1998 1 Winter OTB 2 17 0.362 1.26 #> 2 TBM1998010910 1998 1 Winter OTB 1 1 0 1 #> 3 TBM1998010912 1998 1 Winter OTB 0 0 0 0 #> 4 TBM1998010914 1998 1 Winter OTB 2 2 0.693 2 #> 5 TBM1998010915 1998 1 Winter MTB 4 11 1.16 2.81 #> 6 TBM1998010917 1998 1 Winter MTB 2 5 0.500 1.47 #> # ℹ 28 more variables: Pielou , TaxaSelect , NumGuilds , #> # TSTaxa , TGTaxa , BenthicTaxa , PelagicTaxa , #> # OblTaxa , MSTaxa , ESTaxa , SelectIndiv , Taxa90 , #> # TSAbund , TGAbund , BenthicAbund , PelagicAbund , #> # OblAbund , ESAbund , MSAbund , Num_LR , PropTG , #> # PropTS , PropBenthic , PropPelagic , PropObl , #> # PropMS , PropES , PropSelect "},{"path":"https://tbep-tech.github.io/tbeptools/articles/tbni.html","id":"plotting-results","dir":"Articles","previous_headings":"","what":"Plotting results","title":"Tampa Bay Nekton Index","text":"TBNI scores can viewed annual averages using show_tbniscr(), show_tbniscrall() show_tbnimatrix() functions. show_tbniscr() creates line graph values time bay segment, whereas show_tbniscrall() function plots overall average across bay segments time. show_tbnimatrix() plots annual bay segment averages categorical values conventional “stoplight” graphic. input function output anlz_tbniscr() function. plots can also produced plotly interactive plots setting plotly = TRUE inside function. breakpoints categorical outcomes TBNI scores shown colors graph based 33rd 50th percentiles distribution TBNI scores calculated Tampa Bay. plotting option provided consistency existing TBEP reporting tools, e.g., water quality report card returned show_matrix(). categorical outcomes serve management guidelines year activities support environmental resources Bay: Stay Course, Caution, Alert [3]. graphs returned plotting functions ggplot objects can modified. can combined using patchwork single graphic showing trends time categorical outcomes matrix continuous scores bottom plot.","code":"show_tbniscr(tbniscr) show_tbniscrall(tbniscr) show_tbnimatrix(tbniscr) show_tbniscr(tbniscr, plotly = T) show_tbniscrall(tbniscr, plotly = T) show_tbnimatrix(tbniscr, plotly = T) p1 <- show_tbnimatrix(tbniscr, txtsz = NULL, rev = TRUE, position = 'bottom') + scale_y_continuous(expand = c(0,0), breaks = c(1998:2020)) + coord_flip() + theme(axis.text.x = element_blank()) p2 <- show_tbniscr(tbniscr) p1 + p2 + plot_layout(ncol = 1, heights = c(0.3, 1))"},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/articles/tidalcreeks.html","id":"background","dir":"Articles","previous_headings":"","what":"Background","title":"Tidal Creek Assessment","text":"Dashboard: https://shiny.tbep.org/tidalcreek-dash/ Tidal creeks (aka tributaries) essential habitats Tampa Bay Estuary serve important focal points understanding watershed inputs affect water quality. fundamental goal Tampa Bay Estuary Program develop effective nutrient management strategies support ecological function tidal creeks. partnership Sarasota Bay NEP, Coastal & Heartland NEP, local government agency stakeholders, open science framework developed assessing tidal creek condition based host commonly collected water quality data [1–3]. assessments can support tracking water quality management goals can help refine restoration management plans priority tributaries, including need hydrologic restoration can support critical nursery habitats sportfishes. tbeptools package includes simple features spatial data object population tidal creeks southwest Florida, called tidalcreeks(). includes 615 polyline features designated water body ID (WBID), creek id (JEI), FDEP class (class, 1 potable water, 2 shellfish harvesting propagation, 3F/3M freshwater/marine fish consumption, recreation, propagation maintenance healthy, well-balanced population fish wildlife). tidal creek assessment framework established based data FDEP Impaired Waters Rule database run 56 available includes data collected January 10th 2019. However, framework intends link future IWR databases refresh site new data becomes available. Raw updated data IWR database required assessment provided tbeptools package iwrraw() data object.","code":"mapview(tidalcreeks, homebutton = F, legend = F)"},{"path":"https://tbep-tech.github.io/tbeptools/articles/tidalcreeks.html","id":"assessment","dir":"Articles","previous_headings":"","what":"Assessment","title":"Tidal Creek Assessment","text":"tidal creek assessment framework includes “report card” “indicators” assessment provided separate tabs dashboard. report card provides assessment total nitrogen concentrations (limiting nutrient creeks) based annual geometric average concentrations relative standards developed contributing freshwater streams. indicators based several water quality metrics derived outcomes study describe tidal creek condition provide insights site specific attributes creeks may govern overall creek health.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/articles/tidalcreeks.html","id":"report-card","dir":"Articles","previous_headings":"","what":"Report card","title":"Tidal Creek Assessment","text":"report card similar TBEP water quality report card tidal creeks assigned categories within assessment framework intended serve mechanism evaluating data relative need management action, identify stewardship goals , properly pursued, may preclude need regulatory actions. categories established based principally fish biological response indicator. Tidal creeks assigned one five categories: Data: Data unavailable evaluation. Monitor: Creek nitrogen concentrations protect individual creek types within larger population creeks. Caution: Creek nutrients showing signs elevated nutrient concentrations may increase risk eutrophic condition. Investigate: Creek nutrient concentrations margin safety protect creek potential impairment. Prioritize: Creek nutrient concentrations exceeded regulatory standard associated freshwater portion tributary indicating actions needed identify remediative measures reduce nutrients creek. Conceptually, thresholds appear figure . Scoring rubrik tidal creeks based nitrogen thresholds. Prioritize category defined based Florida’s freshwater stream numeric nutrient criteria (NNC).Two different freshwater stream NNC applicable region; West Central NNC 1.65 mg/l Peninsular region NNC 1.54 mg/l. histograms figure represent range annual geometric mean (AGM) nitrogen concentrations associated Prioritize Investigate categories based NNC. example , maximum expected distribution AGMs exceed 1.65 mg/l 1:3 exceedence probability (defined F..C. 62-303) generated using monte carlo simulation highest observed standard deviation data collected first creeks study. Investigate category defined explicit margin safety adjusting distribution find grand geometric average result 1:20 chance exceeding 1.65 mg/l. Assignment creek Caution category depended creek length adjustment described protect smaller creeks elevated nutrient concentrations. tidaltargets() data object included tbeptools includes thresholds. Note “Caution” category function creek length. scoring algorithm derived define final report card outcome creek using entire ten year record available data based following criteria. single exceedance Prioritize Investigate categories year ten year record result classification creek respective category unless least three years data threshold level category. Creeks assigned next lower category one AGM TN given level multiple years (.e., two) given levels defining cutoff points category. example, creek least 4 years data single exceedance Prioritize threshold assigned Investigate category. Outcomes exemplified .","code":"tidaltargets #> region prioritize investigate #> 1 West Central 1.65 1.38 #> 2 Peninsula 1.54 1.30 #> caution #> 1 1.38 - 0.0174 * (23.78 - (Creek_Length_m / 1000)) #> 2 1.30 - 0.0174 * (23.78 - (Creek_Length_m / 1000))"},{"path":"https://tbep-tech.github.io/tbeptools/articles/tidalcreeks.html","id":"report-card-functions","dir":"Articles","previous_headings":"Report card","what":"Report card functions","title":"Tidal Creek Assessment","text":"two primary functions tidal creek assessments anlz_tdlcrk() obtain scores show_tdlcrk() view interactive map results. anlz_tdlcrk() function uses included tidalcreeks() iwrraw() datasets estimate scores: results include unique creek identifier (id, based wbid JEI fields), waterbody id (wbid), creek ID (JEI), FDEP class (class), results assessment remaining columns. columns monitor, caution, investigate, prioritize indicate number years 2012 2021 nitrogen values within ranges appropriate creek type specified within tidaltargets(). score column indicates overall category assigned creek period record. Note many creeks assigned Data value sufficient data unavailable. summation four component columns (monitor, caution, investigate, prioritize) provides number years data available creek. show_tdlcrk() function can used output anlz_tdlcrk() view interactive map results. Creeks color-coded exceedance categories, “Data” creeks shown light blue. report card style matrix can plotted using show_tdlcrkmatrix() function shows overall creek score number years data used estimate overall score. plot shows matrix rows individual creeks columns overall creek score. columns show overall creek score number years prior ten years nitrogen values creek assigned four score categories. Number years mapped cell transparency. default, plot shows creeks marine WBID (water body identifier) designation 3M 2. can changed class argument (.e., class c('3M', '2', '3F', '1') marine freshwater WBIDs).","code":"results <- anlz_tdlcrk(tidalcreeks, iwrraw) results #> # A tibble: 615 × 10 #> id wbid JEI name class monitor caution investigate prioritize score #> #> 1 1 1983B CC01 Rock Cr… 2 NA NA NA NA No D… #> 2 2 2052 CC01 Rock Cr… 3M 10 NA NA NA Moni… #> 3 3 1983B CC02 Oyster … 2 NA NA NA NA No D… #> 4 4 2067 CC02 Oyster … 3M 10 NA NA NA Moni… #> 5 5 1983B CC03 Buck Cr… 2 NA NA NA NA No D… #> 6 6 2068 CC03 Buck Cr… 3M 9 1 NA NA Moni… #> 7 7 2078A CC04 Buck Cr… 2 NA NA 1 NA Inve… #> 8 8 2078A CC05 Coral C… 2 NA NA NA NA No D… #> 9 9 2078B CC05 Coral C… 2 4 1 NA NA Moni… #> 10 10 2065C CC06 Catfish… 2 NA NA NA NA No D… #> # ℹ 605 more rows show_tdlcrk(results) show_tdlcrkmatrix(results)"},{"path":"https://tbep-tech.github.io/tbeptools/articles/tidalcreeks.html","id":"indicator-functions","dir":"Articles","previous_headings":"Report card","what":"Indicator functions","title":"Tidal Creek Assessment","text":"Water quality Indicators developed provide context interpreting report card outcomes described detail Wessel et al. 2021 include thresholds total nitrogen (>1.1 mg/l), chlorophyll (>11 ug/l), dissolved oxygen (< 42 % saturation), trophic state index score (>55), chlorophyll/nitrogen ratio (>15) ratio nitrates tidal freshwater portion creek (>1) (data available). results indicator relative established thresholds calculated annual basis synthesized 10 year period calculating percentage annual outcomes exceeding identified threshold indicator values total number years available data. integrative summary indicators presented using standardized polar coordinate system Radar Charts provide single multi-metric summary plot results across indicators. anlz_tdlcrkindic() function generates annual outcomes wbid/JEI combination. Individual creek indicators summarized using multivariate response plot called “radar plot” indicates percentage years indicator exceeded respective threshold value. plots created using radar = TRUE argument anlz_tdlcrkindic() function using results show_tdlcrkradar() function. radar plots apply marine WBIDs tidal creeks (Florida DEP class 2, 3M). Indicators without data creek point plot. General descriptive plots annual outcomes provided interactive plotly graphics using show_tdlcrkindic() show_tdlcrkindiccdf() functions. show_tdlcrindic() function produces bar plots annual outcomes selected creek. creek plot selected id argument integer used filter results anlz_tdlcrkindic() function, latter passed cntdat argument. thrsel argument plots dotted red lines based threshold values. year unique color. show_tdlcrkindiccdf() function similar except empirical cumulative distribution functions (CDF) plotted evaluate outcomes specific creek relative entire distribution creeks southwest Florida. indicator year selected creek plotted CDF curves. Location points indicate comparison population trajectory indicators time (.e., brown older observations blue recent). Holding mouse cursor point shows year holding cursor line shows percentile value CDF.","code":"results <- anlz_tdlcrkindic(tidalcreeks, iwrraw) head(results) #> id name JEI wbid class year CHLAC COLOR COND DO DOSAT #> 1 2 Rock Creek CC01 2052 3M 2014 2.380249 14.69473 NA 3.308289 60.31523 #> 2 2 Rock Creek CC01 2052 3M 2015 2.647817 21.91113 NA 4.034172 55.41609 #> 3 2 Rock Creek CC01 2052 3M 2016 2.265462 19.13080 NA 3.980251 55.96637 #> 4 2 Rock Creek CC01 2052 3M 2017 2.851726 15.39576 NA 4.157777 60.18017 #> 5 2 Rock Creek CC01 2052 3M 2018 1.934899 11.65500 NA 4.219790 63.32630 #> 6 2 Rock Creek CC01 2052 3M 2019 2.071003 7.21425 NA 3.015847 44.90322 #> NO23 ORGN SALIN TKN TN TP TSS TURB #> 1 0.007575792 NA 26.63714 0.6161702 0.6228782 0.06938150 NA 2.044623 #> 2 0.009361504 NA 19.10494 0.6465161 0.5678241 0.07602770 NA 1.814818 #> 3 0.008532522 NA 25.84531 0.5813818 0.5408161 0.08330509 NA 2.082253 #> 4 0.007447260 NA 24.86909 0.6255197 0.6326848 0.07566682 NA 1.802161 #> 5 0.006994714 NA 31.32419 0.5668727 0.5734574 0.07432007 NA 2.454007 #> 6 0.007047106 NA 31.63214 0.5053022 0.4577485 0.06300538 NA 1.831953 #> chla_tn_ratio tn_tp_ratio chla_tsi tn_tsi tn2_tsi tp_tsi tp2_tsi #> 1 3.821371 8.977584 29.28775 46.62660 49.42526 60.45694 76.25504 #> 2 4.663093 7.468648 30.82179 44.79432 47.43600 62.15842 78.41391 #> 3 4.188970 6.491994 28.57601 43.82942 46.38844 63.85868 80.57123 #> 4 4.507341 8.361456 31.89011 46.93590 49.76107 62.06992 78.30162 #> 5 3.374095 7.716050 26.30480 44.98978 47.64821 61.73589 77.87779 #> 6 4.524324 7.265229 27.28367 40.52758 42.80384 58.66389 73.97999 #> nut_tsi tsi no23_source no23_tidal no23_ratio do_bnml do_prop #> 1 49.42526 39.35651 NA NA NA 0 1 #> 2 47.43600 39.12890 NA NA NA 0 1 #> 3 46.38844 37.48223 NA NA NA 0 1 #> 4 49.76107 40.82559 NA NA NA 0 0 #> 5 47.64821 36.97650 NA NA NA 0 1 #> 6 42.80384 35.04375 NA NA NA 1 1 cntdat <- anlz_tdlcrkindic(tidalcreeks, iwrraw, yr = 2023, radar = T) # get random creek id set.seed(123) id <- sample(unique(cntdat$id), 1) show_tdlcrkradar(id = id, cntdat = cntdat) cntdat <- anlz_tdlcrkindic(tidalcreeks, iwrraw, yr = 2023) show_tdlcrkindic(id = id, cntdat = cntdat, thrsel = TRUE) show_tdlcrkindiccdf(id = id, cntdat = cntdat, thrsel = TRUE)"},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/authors.html","id":null,"dir":"","previous_headings":"","what":"Authors","title":"Authors and Citation","text":"Marcus Beck. Author, maintainer. Meagan Schrandt. Author. Mike Wessel. Author. Ed Sherwood. Author. Gary Raulerson. Author. Adhokshaja Achar Budihal Prasad. Author. Benjamin Best. Author.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/authors.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Authors and Citation","text":"Beck, M.W., Schrandt, M.N., Wessel, M.R., Sherwood, E.T., Raulerson, G.E., Budihal Prasad, .., Best, B.D., (2021). tbeptools: R package synthesizing estuarine data environmental research. Journal Open Source Software, 6(65), 3485, https://doi.org/10.21105/joss.03485","code":"@Article{, title = {{t}beptools: An {R} package for synthesizing estuarine data for environmental research}, author = {Marcus Beck and Meagan Schrandt and Mike Wessel and Ed Sherwood and Gary Raulerson and Adhokshaja Achar {Budihal Prasad} and Benjamin Best}, journal = {Journal of Open Source Software}, year = {2021}, volume = {6}, number = {65}, pages = {3485}, doi = {10.21105/joss.03485}, }"},{"path":"https://tbep-tech.github.io/tbeptools/index.html","id":"tbeptools","dir":"","previous_headings":"","what":"Data and Indicators for the Tampa Bay Estuary Program","title":"Data and Indicators for the Tampa Bay Estuary Program","text":"R package Tampa Bay Estuary Program functions. Please see vignettes full description.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/index.html","id":"installation","dir":"","previous_headings":"","what":"Installation","title":"Data and Indicators for the Tampa Bay Estuary Program","text":"package can installed r-universe. source code available tbep-tech GitHub group web page: https://github.com/tbep-tech/tbeptools. Note tbeptools needs installed , needs loaded every new R session (.e., library(tbeptools)). package loaded, can view help files function typing question mark followed function name, e.g., ?read_importwq, console. help files provide brief description function required arguments needed run function.","code":"# enable repos options(repos = c( tbeptech = 'https://tbep-tech.r-universe.dev', CRAN = 'https://cloud.r-project.org')) # install tbeptools install.packages('tbeptools') # load tbeptools library(tbeptools)"},{"path":"https://tbep-tech.github.io/tbeptools/index.html","id":"package-vignettes","dir":"","previous_headings":"","what":"Package vignettes","title":"Data and Indicators for the Tampa Bay Estuary Program","text":"vignettes organized topic excellent place start understanding use package. Currently, six vignettes available tbeptools: Water Quality Data: Overview functions working water quality data water quality report card Tampa Bay Nekton Index: Overview functions import, analyze, plot results Tampa Bay Nekton Index Tampa Bay Benthic Index: Overview functions import data Tampa Bay Benthic Index, development Tidal Creeks Assessment: Overview functions import, analyze, plot results assessment tidal creeks southwest Florida Seagrass Transect Data: Overview functions import, analyze, plot results seagrass transect data collected Tampa Bay Habitat Master Plan: Overview functions analyze create report card Tampa Bay Habitat Master Plan 2020 update Fecal Indicator Bacteria: Overview functions import, analyze, plot results Fecal Indicator Bacteria (FIB)","code":""},{"path":"https://tbep-tech.github.io/tbeptools/index.html","id":"usage","dir":"","previous_headings":"","what":"Usage","title":"Data and Indicators for the Tampa Bay Estuary Program","text":"core functions tbeptools three categories based mode use. function named using prefix mode use, followed function . prefixes : read: Import current data main site. anlz: Analyze summarize imported data. show: Create plot analyzed data. functions can easily found RStudio loading package typing prefix command line. autofill dialog box pop showing functions apply prefix. eliminates need searching individual functions know category function need (e.g., read, anlz, show). function also includes semi-descriptive suffix generally describes category applies (e.g, water quality, seagrass) (e.g., imports, formats). follow loose convention attempts strike balance description brevity. optimal balance often hard achieve. aid understanding, provide brief description suffixes used . Suffix descriptions: attain: Analyze functions summarize data relative attainment categories specific bay segments ave, med: Analyze functions summarize data averages medians benthic: Applies benthic monitoring data used Tampa Bay Benthic Index fim: Applies data Fisheries Independent Monitoring program used Tampa Bay Nekton Index form: intermediate function formatting imported data downstream analysis hmp: Functions work Habitat Master Plan data import: function used import data source external package indic: function analyzes plots individual tidal creek indicator values, opposed integrated creek scores iwr: Functions data apply Impaired Waters Rule (IWR) data maintained Florida Department Environmental Protection used source data tidal creek functions matrix: plotting function creates report card style matrix met: function analyses plots individual metrics integrated indices, e.g., TBBI, TBNI phyto: Applies phytoplankton data Hillsborough County Environmental Protection Commission plotly: plotting function returns interactive plotly object scr: function analyses plots summary scores integrated indices, e.g., TBBI, TBNI seg, site: Functions analyze plot results relative bay segments individual monitoring sites tbbi: Applies Tampa Bay Benthic Index (TBBI) tbni: Applies Tampa Bay Nekton Index (TBNI) tdlcrk: Applies tidal creeks transect: Applies seagrass transect data wq: Applies water quality function reference page can also viewed complete list functions organized category, description , links help files. following example demonstrates use subset functions water quality data read file Hillsborough County Environmental Protection Commission long-term monitoring dataset (available https://www.tampabay.wateratlas.usf.edu/), analyze monthly annual averages major bay segments Tampa Bay, plot annual time series one bay segments. Functions tbeptools also support creation content interactive, online dashboards can facilitate informed decisions without requiring intimate understanding R programming language methods analysis. dashboards include assessments water quality, seagrasses, nekton communities, tidal creeks.","code":"# load the package library(tbeptools) # read current data wqdat <- read_importwq(xlsx = \"wqdata.xlsx\", download_latest = TRUE) wqdat ## # A tibble: 26,611 x 22 ## bay_segment epchc_station SampleTime yr mo ## ## 1 HB 6 2021-06-08 10:59:00 2021 6 ## 2 HB 7 2021-06-08 11:13:00 2021 6 ## 3 HB 8 2021-06-08 14:15:00 2021 6 ## 4 MTB 9 2021-06-08 13:14:00 2021 6 ## 5 MTB 11 2021-06-08 11:30:00 2021 6 ## # ... with 26,606 more rows, and 17 more variables: ## # Latitude , Longitude , Total_Depth_m , ## # Sample_Depth_m , tn , tn_q , sd_m , ## # sd_raw_m , sd_q , chla , chla_q , ## # Sal_Top_ppth , Sal_Mid_ppth , ## # Sal_Bottom_ppth , Temp_Water_Top_degC , ## # Temp_Water_Mid_degC , ... # analyze monthly and annual means by bay segment avedat <- anlz_avedat(wqdat) avedat ## $ann ## # A tibble: 584 x 4 ## yr bay_segment var val ## ## 1 1974 HB mean_chla 22.4 ## 2 1974 LTB mean_chla 4.24 ## 3 1974 MTB mean_chla 9.66 ## 4 1974 OTB mean_chla 10.2 ## 5 1975 HB mean_chla 27.9 ## # ... with 579 more rows ## ## $mos ## # A tibble: 4,484 x 5 ## bay_segment yr mo var val ## ## 1 HB 1974 1 mean_chla 36.2 ## 2 LTB 1974 1 mean_chla 1.75 ## 3 MTB 1974 1 mean_chla 11.5 ## 4 OTB 1974 1 mean_chla 4.4 ## 5 HB 1974 2 mean_chla 42.4 ## # ... with 4,479 more rows # show annual time series of chlorophyll for Hillsborough bay segment show_thrplot(wqdat, bay_segment = \"HB\", yrrng = c(1975, 2020))"},{"path":"https://tbep-tech.github.io/tbeptools/index.html","id":"issues-and-suggestions","dir":"","previous_headings":"","what":"Issues and suggestions","title":"Data and Indicators for the Tampa Bay Estuary Program","text":"Please report issues suggestions issues link repository. guide posting issues can found .","code":""},{"path":"https://tbep-tech.github.io/tbeptools/index.html","id":"contributing","dir":"","previous_headings":"","what":"Contributing","title":"Data and Indicators for the Tampa Bay Estuary Program","text":"Please view contributing guidelines changes pull requests.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/acres.html","id":null,"dir":"Reference","previous_headings":"","what":"Tampa Bay intertidal and supratidal land use and cover — acres","title":"Tampa Bay intertidal and supratidal land use and cover — acres","text":"Tampa Bay intertidal supratidal land use cover Habitat Master Plan reporting","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/acres.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tampa Bay intertidal and supratidal land use and cover — acres","text":"","code":"acres"},{"path":"https://tbep-tech.github.io/tbeptools/reference/acres.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Tampa Bay intertidal and supratidal land use and cover — acres","text":"data frame","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/acres.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tampa Bay intertidal and supratidal land use and cover — acres","text":"","code":"if (FALSE) { load(url(\"https://github.com/tbep-tech/hmpu-workflow/raw/master/data/acres.RData\")) save(acres, file = 'data/acres.RData', compress = 'xz') }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_attain.html","id":null,"dir":"Reference","previous_headings":"","what":"Get attainment categories — anlz_attain","title":"Get attainment categories — anlz_attain","text":"Get attainment categories year bay segment using chlorophyll light attenuation","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_attain.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get attainment categories — anlz_attain","text":"","code":"anlz_attain(avedat, magdurout = FALSE, trgs = NULL)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_attain.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get attainment categories — anlz_attain","text":"avedat result returned anlz_avedat magdurout logical indicating separate magnitude duration estimates returned trgs optional data.frame annual bay segment water quality targets, defaults targets","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_attain.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get attainment categories — anlz_attain","text":"data.frame year bay segment showing attainment category","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_attain.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get attainment categories — anlz_attain","text":"","code":"avedat <- anlz_avedat(epcdata) anlz_attain(avedat) #> # A tibble: 200 × 4 #> bay_segment yr chl_la outcome #> #> 1 HB 1974 3_0 yellow #> 2 HB 1975 3_2 red #> 3 HB 1976 3_2 red #> 4 HB 1977 3_2 red #> 5 HB 1978 3_3 red #> 6 HB 1979 3_3 red #> 7 HB 1980 3_3 red #> 8 HB 1981 3_3 red #> 9 HB 1982 3_3 red #> 10 HB 1983 3_0 yellow #> # ℹ 190 more rows"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_attainsite.html","id":null,"dir":"Reference","previous_headings":"","what":"Get site attainments — anlz_attainsite","title":"Get site attainments — anlz_attainsite","text":"Get site attainment categories chlorophyll light attenuation","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_attainsite.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get site attainments — anlz_attainsite","text":"","code":"anlz_attainsite( avedatsite, thr = c(\"chla\", \"la\"), trgs = NULL, yrrng = NULL, thrs = FALSE )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_attainsite.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get site attainments — anlz_attainsite","text":"avedatsite result returned anlz_avedatsite thr chr string indicating water quality value appropriate threshold plot, one \"chl\" chlorophyll \"la\" light availability trgs optional data.frame annual bay segment water quality targets, defaults targets yrrng optional numeric value year return, defaults thrs logical indicating attainment category relative targets (default) thresholds","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_attainsite.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get site attainments — anlz_attainsite","text":"data.frame year site showing attainment category","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_attainsite.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Get site attainments — anlz_attainsite","text":"function simplication attainment categories returned anlz_attain. Sites compared targets/thresholds apply separately chlorophyll light attenuation.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_attainsite.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get site attainments — anlz_attainsite","text":"","code":"avedatsite <- anlz_avedatsite(epcdata) anlz_attainsite(avedatsite) #> # A tibble: 2,250 × 9 #> yr bay_segment epchc_station var val target smallex thresh met #> #> 1 1974 HB 6 chla 25.6 13.2 14.1 15 no #> 2 1974 HB 7 chla 21.6 13.2 14.1 15 no #> 3 1974 HB 8 chla 22.6 13.2 14.1 15 no #> 4 1974 HB 44 chla 23.4 13.2 14.1 15 no #> 5 1974 HB 52 chla 23.5 13.2 14.1 15 no #> 6 1974 HB 55 chla 20.2 13.2 14.1 15 no #> 7 1974 HB 70 chla 33.1 13.2 14.1 15 no #> 8 1974 HB 71 chla 25.8 13.2 14.1 15 no #> 9 1974 HB 73 chla 17.6 13.2 14.1 15 no #> 10 1974 HB 80 chla 10.5 13.2 14.1 15 yes #> # ℹ 2,240 more rows"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_avedat.html","id":null,"dir":"Reference","previous_headings":"","what":"Estimate annual means — anlz_avedat","title":"Estimate annual means — anlz_avedat","text":"Estimate annual means chlorophyll secchi data","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_avedat.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Estimate annual means — anlz_avedat","text":"","code":"anlz_avedat(epcdata, partialyr = FALSE)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_avedat.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Estimate annual means — anlz_avedat","text":"epcdata data.frame formatted read_importwq partialyr logical indicating incomplete annual data recent year approximated five year monthly averages parameter","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_avedat.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Estimate annual means — anlz_avedat","text":"Mean estimates chlorophyll secchi","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_avedat.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Estimate annual means — anlz_avedat","text":"","code":"# view average estimates anlz_avedat(epcdata) #> $ann #> # A tibble: 608 × 4 #> yr bay_segment var val #> #> 1 1974 HB mean_chla 22.4 #> 2 1974 LTB mean_chla 4.24 #> 3 1974 MTB mean_chla 9.66 #> 4 1974 OTB mean_chla 10.2 #> 5 1975 HB mean_chla 27.9 #> 6 1975 LTB mean_chla 4.93 #> 7 1975 MTB mean_chla 11.4 #> 8 1975 OTB mean_chla 13.2 #> 9 1976 HB mean_chla 29.5 #> 10 1976 LTB mean_chla 5.08 #> # ℹ 598 more rows #> #> $mos #> # A tibble: 4,724 × 5 #> bay_segment yr mo var val #> #> 1 HB 1974 1 mean_chla 36.2 #> 2 LTB 1974 1 mean_chla 1.75 #> 3 MTB 1974 1 mean_chla 11.5 #> 4 OTB 1974 1 mean_chla 4.4 #> 5 HB 1974 2 mean_chla 42.4 #> 6 LTB 1974 2 mean_chla 5.5 #> 7 MTB 1974 2 mean_chla 9.35 #> 8 OTB 1974 2 mean_chla 4.07 #> 9 HB 1974 3 mean_chla 14.9 #> 10 LTB 1974 3 mean_chla 5.88 #> # ℹ 4,714 more rows #>"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_avedatsite.html","id":null,"dir":"Reference","previous_headings":"","what":"Estimate annual means by site — anlz_avedatsite","title":"Estimate annual means by site — anlz_avedatsite","text":"Estimate annual means site chlorophyll secchi data","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_avedatsite.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Estimate annual means by site — anlz_avedatsite","text":"","code":"anlz_avedatsite(epcdata, partialyr = FALSE)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_avedatsite.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Estimate annual means by site — anlz_avedatsite","text":"epcdata data.frame formatted read_importwq partialyr logical indicating incomplete annual data recent year approximated five year monthly averages parameter","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_avedatsite.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Estimate annual means by site — anlz_avedatsite","text":"Mean estimates chlorophyll secchi","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_avedatsite.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Estimate annual means by site — anlz_avedatsite","text":"","code":"# view average estimates anlz_avedatsite(epcdata) #> $ann #> # A tibble: 6,838 × 5 #> yr bay_segment epchc_station var val #> #> 1 1974 HB 6 mean_chla 25.6 #> 2 1974 HB 7 mean_chla 21.6 #> 3 1974 HB 8 mean_chla 22.6 #> 4 1974 HB 44 mean_chla 23.4 #> 5 1974 HB 52 mean_chla 23.5 #> 6 1974 HB 55 mean_chla 20.2 #> 7 1974 HB 70 mean_chla 33.1 #> 8 1974 HB 71 mean_chla 25.8 #> 9 1974 HB 73 mean_chla 17.6 #> 10 1974 HB 80 mean_chla 10.5 #> # ℹ 6,828 more rows #> #> $mos #> # A tibble: 48,727 × 6 #> bay_segment epchc_station yr mo var val #> #> 1 HB 6 1974 1 mean_chla 53 #> 2 HB 7 1974 1 mean_chla 19 #> 3 HB 8 1974 1 mean_chla 46 #> 4 HB 44 1974 1 mean_chla 24 #> 5 HB 52 1974 1 mean_chla 28 #> 6 HB 55 1974 1 mean_chla 33 #> 7 HB 70 1974 1 mean_chla 58 #> 8 HB 71 1974 1 mean_chla 73 #> 9 HB 73 1974 1 mean_chla 17 #> 10 HB 80 1974 1 mean_chla 11 #> # ℹ 48,717 more rows #>"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_fibmap.html","id":null,"dir":"Reference","previous_headings":"","what":"Assign threshold categories to Fecal Indicator Bacteria (FIB) data — anlz_fibmap","title":"Assign threshold categories to Fecal Indicator Bacteria (FIB) data — anlz_fibmap","text":"Assign threshold categories Fecal Indicator Bacteria (FIB) data","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_fibmap.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Assign threshold categories to Fecal Indicator Bacteria (FIB) data — anlz_fibmap","text":"","code":"anlz_fibmap(fibdata, yrsel = NULL, mosel = NULL, areasel = NULL)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_fibmap.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Assign threshold categories to Fecal Indicator Bacteria (FIB) data — anlz_fibmap","text":"fibdata input FIB data.frame returned read_importfib yrsel optional numeric value filter output years fibdata mosel optional numeric value filter output month fibdata areasel optional character string filter output stations area column fibdata, see details","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_fibmap.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Assign threshold categories to Fecal Indicator Bacteria (FIB) data — anlz_fibmap","text":"data.frame similar fibdata additional columns describing station categories optionally filtered arguments passed function","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_fibmap.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Assign threshold categories to Fecal Indicator Bacteria (FIB) data — anlz_fibmap","text":"function used create FIB categories mapping using show_fibmap. Categories based relevant thresholds assigned observation. categories specific E. coli Enterococcus assigned based station class freshwater (class 1 3F) marine (class 2 3M), respectively. station categorized one four ranges defined thresholds noted cat column output, corresponding colors appropriate range noted col column output. areasel argument can indicate valid entries area column fibdata. example, use either \"Alafia River\" \"Hillsborough River\" corresponding river basins, rows fibdata filtered based selection. stations returned argument set NULL (default). Alafia River basin includes values area column fibdata \"Alafia River\" \"Alafia River Tributary\". Hillsborough River basin includes values area column fibdat \"Hillsborough River\", \"Hillsborough River Tributary\", \"Lake Thonotosassa\", \"Lake Thonotosassa Tributary\", \"Lake Roberta\". areas may present based selection. valid options areasel include \"Alafia River\", \"Hillsborough River\", \"Big Bend\", \"Cockroach Bay\", \"East Lake Outfall\", \"Hillsborough Bay\", \"Little Manatee\", \"Lower Tampa Bay\", \"McKay Bay\", \"Middle Tampa Bay\", \"Old Tampa Bay\", \"Palm River\", \"Tampa Bypass Canal\", \"Valrico Lake\".","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_fibmap.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Assign threshold categories to Fecal Indicator Bacteria (FIB) data — anlz_fibmap","text":"","code":"# assign categories to all anlz_fibmap(fibdata) #> # A tibble: 76,502 × 12 #> area epchc_station class yr mo Latitude Longitude ecoli ecocci ind #> #> 1 Hillsb… 2 3M 2024 1 27.9 -82.5 NA 24 Ente… #> 2 Hillsb… 6 3M 2024 1 27.9 -82.5 NA 2 Ente… #> 3 Hillsb… 7 3M 2024 1 27.9 -82.5 NA 2 Ente… #> 4 Hillsb… 8 3M 2024 1 27.9 -82.4 NA 10 Ente… #> 5 Middle… 9 2 2024 1 27.8 -82.4 NA 2 Ente… #> 6 Middle… 11 2 2024 1 27.8 -82.5 NA 2 Ente… #> 7 Middle… 13 2 2024 1 27.8 -82.5 NA 2 Ente… #> 8 Middle… 14 2 2024 1 27.8 -82.5 NA 2 Ente… #> 9 Middle… 16 2 2024 1 27.7 -82.5 NA 2 Ente… #> 10 Middle… 19 2 2024 1 27.7 -82.6 NA 2 Ente… #> # ℹ 76,492 more rows #> # ℹ 2 more variables: cat , col # filter by year, month, and area anlz_fibmap(fibdata, yrsel = 2020, mosel = 7, areasel = 'Alafia River') #> # A tibble: 24 × 12 #> area epchc_station class yr mo Latitude Longitude ecoli ecocci ind #> #> 1 Alafia… 74 3M 2020 7 27.9 -82.4 NA 168 Ente… #> 2 Alafia… 111 3F 2020 7 27.9 -82.2 50 7000 E. c… #> 3 Alafia… 114 3F 2020 7 27.9 -82.3 447 1560 E. c… #> 4 Alafia… 115 3F 2020 7 27.9 -82.1 80 260 E. c… #> 5 Alafia… 116 3F 2020 7 27.9 -82.1 30 367 E. c… #> 6 Alafia… 139 3F 2020 7 27.7 -82.1 47 100 E. c… #> 7 Alafia… 151 3F 2020 7 27.9 -82.2 90 25 E. c… #> 8 Alafia… 153 3M 2020 7 27.9 -82.3 NA 4000 Ente… #> 9 Alafia… 154 3F 2020 7 27.9 -82.1 433 1367 E. c… #> 10 Alafia… 155 3F 2020 7 27.9 -82.2 170 233 E. c… #> # ℹ 14 more rows #> # ℹ 2 more variables: cat , col "},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_fibmatrix.html","id":null,"dir":"Reference","previous_headings":"","what":"Analyze Fecal Indicator Bacteria categories over time by station — anlz_fibmatrix","title":"Analyze Fecal Indicator Bacteria categories over time by station — anlz_fibmatrix","text":"Analyze Fecal Indicator Bacteria categories time station","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_fibmatrix.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Analyze Fecal Indicator Bacteria categories over time by station — anlz_fibmatrix","text":"","code":"anlz_fibmatrix(fibdata, yrrng = NULL, stas = NULL, lagyr = 3)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_fibmatrix.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Analyze Fecal Indicator Bacteria categories over time by station — anlz_fibmatrix","text":"fibdata input data frame returned read_importfib yrrng numeric vector indicating min, max years include, defaults range years epcdata stas optional numeric vector stations include, see details lagyr numeric year lag calculate categories, see details","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_fibmatrix.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Analyze Fecal Indicator Bacteria categories over time by station — anlz_fibmatrix","text":"tibble object FIB summaries year station, including columns estimated geometric mean fecal coliform concentrations (gmean), proportions samples exceeding 400 CFU / 100 mL (exced), count samples (cnt), category indicating letter outcome based proportion exceedences (cat).","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_fibmatrix.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Analyze Fecal Indicator Bacteria categories over time by station — anlz_fibmatrix","text":"function used create output plotting matrix stoplight graphic FIB categories station year. station year combination categorized based likelihood fecal indicator bacteria concentrations exceeding 400 CFU / 100 mL given year (using Fecal Coliform, fcolif fibdata). proportions categorized , B, C, D, E (Microbial Water Quality Assessment MWQA categories) corresponding colors, breakpoints category <10%, 10-30%, 30-50%, 50-75%, >75% (right-closed). default, results year based right-centered window uses previous two years current year calculate probabilities using monthly samples (lagyr = 3). See show_fibmatrix additional details.","code":""},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_fibmatrix.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Analyze Fecal Indicator Bacteria categories over time by station — anlz_fibmatrix","text":"","code":"anlz_fibmatrix(fibdata) #> # A tibble: 8,800 × 4 #> yr epchc_station gmean cat #> #> 1 1985 2 52.4 B #> 2 1985 6 7.21 A #> 3 1985 7 4.64 A #> 4 1985 8 9.49 A #> 5 1985 9 6.32 A #> 6 1985 11 5.18 A #> 7 1985 13 4 A #> 8 1985 14 6.35 A #> 9 1985 16 4 A #> 10 1985 19 4 A #> # ℹ 8,790 more rows"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_hmpreport.html","id":null,"dir":"Reference","previous_headings":"","what":"Evaluate Habitat Master Plan progress for report card — anlz_hmpreport","title":"Evaluate Habitat Master Plan progress for report card — anlz_hmpreport","text":"Evaluate Habitat Master Plan progress report card","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_hmpreport.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Evaluate Habitat Master Plan progress for report card — anlz_hmpreport","text":"","code":"anlz_hmpreport(acres, subtacres, hmptrgs)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_hmpreport.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Evaluate Habitat Master Plan progress for report card — anlz_hmpreport","text":"acres data.frame intertidal supratidal land use cover habitat types year data subtacres data.frame subtidal cover habitat types year data hmptrgs data.frame Habitat Master Plan targets goals","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_hmpreport.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Evaluate Habitat Master Plan progress for report card — anlz_hmpreport","text":"summarized data.frame appropriate creating report card","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_hmpreport.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Evaluate Habitat Master Plan progress for report card — anlz_hmpreport","text":"relevant output columns targeteval goaleval indicate numeric values -1 (target met, trending ), 0 (target met, trending ), 0.5 (target met, trending ), 1 (target met, trending ). Columns output follows: year Year assessment metric Habitat type assessed Acres Coverage estimate year lacres Coverage estimate previous set available data lyr Year previous set available data category Strata habitat type Target 2030 target habitat type Habitat Master Plan Goal 2050 goal habitat type Habitat Master Plan acresdiff Difference acres current year previous set available data yeardiff Difference years current year previous set available data changerate Acreage change per year current year relative previous set available data targetrate Annual rate required achieve 2030 target goalrate Annual rate required achieve 2050 goal targetprop Proportion target met current year goalprop Proportion goal met current year targeteval number indicating target status current year report card goaleval number indicating goal status current year report card numbers targeteval goaleval one four values -1, 0, 0.5, 1. numbers define status assessment year: -1 target goal met, trending 0 target goal met, trending 0.5 target goal met, trending 1 target goal met, trending ","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_hmpreport.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Evaluate Habitat Master Plan progress for report card — anlz_hmpreport","text":"","code":"# view summarized data for report card anlz_hmpreport(acres, subtacres, hmptrgs) #> # A tibble: 150 × 17 #> year metric Acres lacres lyr category Target Goal acresdiff yeardiff #> #> 1 1990 Seagrasses 25218. 23279. 1988 Subtidal 40000 40000 1939. 2 #> 2 1990 Tidal Fla… 20433. 21686. 1988 Subtidal 16220 16220 -1253. 2 #> 3 1992 Seagrasses 25746. 25218. 1990 Subtidal 40000 40000 528. 2 #> 4 1992 Tidal Fla… 20594. 20433. 1990 Subtidal 16220 16220 161. 2 #> 5 1994 Seagrasses 26524. 25746. 1992 Subtidal 40000 40000 778. 2 #> 6 1994 Tidal Fla… 20244. 20594. 1992 Subtidal 16220 16220 -349. 2 #> 7 1996 Seagrasses 26924. 26524. 1994 Subtidal 40000 40000 400. 2 #> 8 1996 Tidal Fla… 20443. 20244. 1994 Subtidal 16220 16220 199. 2 #> 9 1999 Seagrasses 24840. 26924. 1996 Subtidal 40000 40000 -2083. 3 #> 10 1999 Tidal Fla… 27085. 20443. 1996 Subtidal 16220 16220 6642. 3 #> # ℹ 140 more rows #> # ℹ 7 more variables: changerate , targetrate , goalrate , #> # targetprop , goalprop , targeteval , goaleval "},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_hydroload.html","id":null,"dir":"Reference","previous_headings":"","what":"Estimate hydrological estimates and adjustment factors for bay segments — anlz_hydroload","title":"Estimate hydrological estimates and adjustment factors for bay segments — anlz_hydroload","text":"Estimate hydrological estimates adjustment factors bay segments","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_hydroload.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Estimate hydrological estimates and adjustment factors for bay segments — anlz_hydroload","text":"","code":"anlz_hydroload(yrs, noaa_key = NULL, trace = FALSE)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_hydroload.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Estimate hydrological estimates and adjustment factors for bay segments — anlz_hydroload","text":"yrs numeric vector indicating years return noaa_key user-supplied NOAA key, see details trace logical indicating function progress printed consol","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_hydroload.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Estimate hydrological estimates and adjustment factors for bay segments — anlz_hydroload","text":"data frame hydrological load estimates bay segments requested years","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_hydroload.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Estimate hydrological estimates and adjustment factors for bay segments — anlz_hydroload","text":"function uses rainfall streamflow data NOAA USGS requires API key. See \"Authentication\" section help file ncdc defunct rnoaa package. key can added R environment file called later use, see examples. estimates used annual compliance assessment reports produced Tampa Bay Nitrogen Management Consortium. Load estimates adjustment factors based regression models https://drive.google.com/file/d/11NT0NQ2WbPO6pVZaD7P7Z6qjcwO1jxHw/view?usp=drivesdk","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_hydroload.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Estimate hydrological estimates and adjustment factors for bay segments — anlz_hydroload","text":"","code":"if (FALSE) { # this function requires an API key # save it to the R environment file (only once) # save the key, do only once cat(\"NOAA_KEY=XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX\\n\", file=file.path(normalizePath(\"~/\"), \".Renviron\"), append=TRUE) # retrieve the key after saving, may need to restart R noaa_key <- Sys.getenv('NOAA_key') # get estimates for 2021 anlz_hydroload(2021, noaa_key) }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_iwrraw.html","id":null,"dir":"Reference","previous_headings":"","what":"Format raw IWR data — anlz_iwrraw","title":"Format raw IWR data — anlz_iwrraw","text":"Format raw IWR data","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_iwrraw.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Format raw IWR data — anlz_iwrraw","text":"","code":"anlz_iwrraw(iwrraw, tidalcreeks, yr = 2023)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_iwrraw.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Format raw IWR data — anlz_iwrraw","text":"iwrraw FDEP impaired waters rule data base data.frame tidalcreeks sf object population tidal creeks yr numeric reference year evaluate, scores based ten years data using yr last year","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_iwrraw.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Format raw IWR data — anlz_iwrraw","text":"data.frame formatted data","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_iwrraw.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Format raw IWR data — anlz_iwrraw","text":"function subsets raw IWR data ten years starting value yr subsets creek population tidalcreeks. Select water quality parameters masterCode filtered names combined continuity.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_iwrraw.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Format raw IWR data — anlz_iwrraw","text":"","code":"anlz_iwrraw(iwrraw, tidalcreeks, yr = 2023) #> wbid class JEI year date masterCode result rCode #> 1 2052 3M CC01 2014 2014-03-03 CHLAC 0.5877866649 #> 2 2052 3M CC01 2014 2014-03-03 COLOR 0.9162907319 U #> 3 2052 3M CC01 2014 2014-03-03 DOSAT 4.1835756960 + #> 4 2052 3M CC01 2014 2014-03-03 NO23 -5.5214609179 U #> 5 2052 3M CC01 2014 2014-03-03 SALIN 3.5292973843 #> 6 2052 3M CC01 2014 2014-03-03 TKN -0.6733445533 #> 7 2052 3M CC01 2014 2014-03-03 TN -0.6694306539 + #> 8 2052 3M CC01 2014 2014-03-03 TP -2.7968814148 #> 9 2052 3M CC01 2014 2014-03-03 TURB 1.2527629685 #> 10 2052 3M CC01 2014 2014-04-07 CHLAC 0.2623642645 I #> 11 2052 3M CC01 2014 2014-04-07 COLOR 0.9162907319 U #> 12 2052 3M CC01 2014 2014-04-07 DO 1.3862943611 #> 13 2052 3M CC01 2014 2014-04-07 DOSAT 4.0656020934 + #> 14 2052 3M CC01 2014 2014-04-07 NO23 -5.2983173665 I #> 15 2052 3M CC01 2014 2014-04-07 SALIN 3.5582011305 #> 16 2052 3M CC01 2014 2014-04-07 TKN -0.6733445533 #> 17 2052 3M CC01 2014 2014-04-07 TN -0.6655320135 + #> 18 2052 3M CC01 2014 2014-04-07 TP -2.6882475738 #> 19 2052 3M CC01 2014 2014-04-07 TURB 0.7884573604 #> 20 2052 3M CC01 2014 2014-05-05 CHLAC 0.8754687374 #> 21 2052 3M CC01 2014 2014-05-05 COLOR 3.4011973817 #> 22 2052 3M CC01 2014 2014-05-05 DO 1.5040773968 #> 23 2052 3M CC01 2014 2014-05-05 DOSAT 4.1399550735 + #> 24 2052 3M CC01 2014 2014-05-05 NO23 -4.7105307016 I #> 25 2052 3M CC01 2014 2014-05-05 SALIN 3.3032169733 #> 26 2052 3M CC01 2014 2014-05-05 TKN -0.3856624808 #> 27 2052 3M CC01 2014 2014-05-05 TN -0.3797973614 + #> 28 2052 3M CC01 2014 2014-05-05 TP -2.2072749132 #> 29 2052 3M CC01 2014 2014-05-05 TURB 1.2237754316 A #> 30 2052 3M CC01 2014 2014-06-02 CHLAC 0.8754687374 #> 31 2052 3M CC01 2014 2014-06-02 COLOR 2.7080502011 #> 32 2052 3M CC01 2014 2014-06-02 DO 0.9555114450 #> 33 2052 3M CC01 2014 2014-06-02 DOSAT 3.6635616461 + #> 34 2052 3M CC01 2014 2014-06-02 NO23 -4.9618451299 I #> 35 2052 3M CC01 2014 2014-06-02 SALIN 3.4719664526 #> 36 2052 3M CC01 2014 2014-06-02 TKN -0.6348782724 #> 37 2052 3M CC01 2014 2014-06-02 TN -0.6273594400 + #> 38 2052 3M CC01 2014 2014-06-02 TP -2.6592600369 #> 39 2052 3M CC01 2014 2014-06-02 TURB 0.7419373447 #> 40 2052 3M CC01 2014 2014-07-07 CHLAC 1.0986122887 #> 41 2052 3M CC01 2014 2014-07-07 COLOR 2.2512917986 #> 42 2052 3M CC01 2014 2014-07-07 DO 1.4350845253 #> 43 2052 3M CC01 2014 2014-07-07 NO23 -5.5214609179 U #> 44 2052 3M CC01 2014 2014-07-07 TKN -0.5621189182 #> 45 2052 3M CC01 2014 2014-07-07 TN -0.5586162876 + #> 46 2052 3M CC01 2014 2014-07-07 TP -2.9565115604 #> 47 2052 3M CC01 2014 2014-07-07 TURB 1.0986122887 #> 48 2052 3M CC01 2014 2014-08-04 CHLAC 1.0296194172 #> 49 2052 3M CC01 2014 2014-08-04 COLOR 2.3025850930 #> 50 2052 3M CC01 2014 2014-08-04 DO 1.0647107370 #> 51 2052 3M CC01 2014 2014-08-04 DOSAT 3.8543938926 + #> 52 2052 3M CC01 2014 2014-08-04 NO23 -5.5214609179 U #> 53 2052 3M CC01 2014 2014-08-04 SALIN 3.5292973843 #> 54 2052 3M CC01 2014 2014-08-04 TN -0.4748151862 + #> 55 2052 3M CC01 2014 2014-08-04 TURB 0.5877866649 #> 56 2052 3M CC01 2014 2014-09-08 CHLAC 1.4350845253 #> 57 2052 3M CC01 2014 2014-09-08 COLOR 2.8332133441 #> 58 2052 3M CC01 2014 2014-09-08 DO 0.8329091229 #> 59 2052 3M CC01 2014 2014-09-08 DOSAT 3.5779478934 + #> 60 2052 3M CC01 2014 2014-09-08 NO23 -4.7105307016 I #> 61 2052 3M CC01 2014 2014-09-08 SALIN 3.4965075615 #> 62 2052 3M CC01 2014 2014-09-08 TKN -0.3424903089 #> 63 2052 3M CC01 2014 2014-09-08 TN -0.3368723166 + #> 64 2052 3M CC01 2014 2014-09-08 TP -2.7030626596 #> 65 2052 3M CC01 2014 2014-09-08 TURB 0.4700036292 #> 66 2052 3M CC01 2014 2014-10-06 CHLAC 1.1314021115 #> 67 2052 3M CC01 2014 2014-10-06 COLOR 5.2470240722 #> 68 2052 3M CC01 2014 2014-10-06 DOSAT 4.1141471895 + #> 69 2052 3M CC01 2014 2014-10-06 NO23 -3.8167128256 #> 70 2052 3M CC01 2014 2014-10-06 SALIN 2.0918640617 #> 71 2052 3M CC01 2014 2014-10-06 TKN 0.0953101798 #> 72 2052 3M CC01 2014 2014-10-06 TN 0.1151128071 + #> 73 2052 3M CC01 2014 2014-10-06 TP -2.3025850930 #> 74 2052 3M CC01 2014 2014-10-06 TURB 0.3364722366 #> 75 2052 3M CC01 2014 2014-11-03 CHLAC 0.7884573604 A #> 76 2052 3M CC01 2014 2014-11-03 COLOR 3.5263605246 A #> 77 2052 3M CC01 2014 2014-11-03 DOSAT 4.8698394841 + #> 78 2052 3M CC01 2014 2014-11-03 NO23 -4.4228486292 #> 79 2052 3M CC01 2014 2014-11-03 SALIN 3.2425923515 #> 80 2052 3M CC01 2014 2014-11-03 TKN -0.5276327421 #> 81 2052 3M CC01 2014 2014-11-03 TN -0.5074978337 + #> 82 2052 3M CC01 2014 2014-11-03 TP -2.7806208939 #> 83 2052 3M CC01 2014 2014-11-03 TURB 0.1823215568 #> 84 2052 3M CC01 2014 2014-12-01 CHLAC 0.5877866649 #> 85 2052 3M CC01 2014 2014-12-01 COLOR 2.7725887222 A #> 86 2052 3M CC01 2014 2014-12-01 DOSAT 4.4272389775 + #> 87 2052 3M CC01 2014 2014-12-01 NO23 -4.3428059215 #> 88 2052 3M CC01 2014 2014-12-01 SALIN 3.3178157727 #> 89 2052 3M CC01 2014 2014-12-01 TKN -0.6539264674 #> 90 2052 3M CC01 2014 2014-12-01 TN -0.6292338548 + #> 91 2052 3M CC01 2014 2014-12-01 TP -2.9187712324 #> 92 2052 3M CC01 2014 2014-12-01 TURB 0.4700036292 #> 93 2052 3M CC01 2015 2015-01-05 CHLAC 0.9932517730 #> 94 2052 3M CC01 2015 2015-01-05 COLOR 1.8405496334 #> 95 2052 3M CC01 2015 2015-01-05 DO 1.5260563035 #> 96 2052 3M CC01 2015 2015-01-05 DOSAT 4.1835756960 + #> 97 2052 3M CC01 2015 2015-01-05 NO23 -4.9618451299 I #> 98 2052 3M CC01 2015 2015-01-05 SALIN 3.5438536821 #> 99 2052 3M CC01 2015 2015-01-05 TKN -0.8675005677 #> 100 2052 3M CC01 2015 2015-01-05 TN -0.8580218238 + #> 101 2052 3M CC01 2015 2015-01-05 TP -2.6310891600 #> 102 2052 3M CC01 2015 2015-01-05 TURB 0.7419373447 #> 103 2052 3M CC01 2015 2015-02-02 CHLAC 0.4700036292 I #> 104 2052 3M CC01 2015 2015-02-02 COLOR 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#> 433 2052 3M CC01 2019 2019-03-04 TP -2.6172958378 #> 434 2052 3M CC01 2019 2019-03-04 TURB 0.4700036292 #> 435 2052 3M CC01 2019 2019-04-01 CHLAC 0.9162907319 #> 436 2052 3M CC01 2019 2019-04-01 COLOR 2.0014800002 #> 437 2052 3M CC01 2019 2019-04-01 DO 1.4883995841 #> 438 2052 3M CC01 2019 2019-04-01 DOSAT 4.1620032107 #> 439 2052 3M CC01 2019 2019-04-01 NO23 -5.5214609179 I #> 440 2052 3M CC01 2019 2019-04-01 SALIN 3.4094961845 #> 441 2052 3M CC01 2019 2019-04-01 TKN -0.9162907319 I #> 442 2052 3M CC01 2019 2019-04-01 TN -1.8078888512 + #> 443 2052 3M CC01 2019 2019-04-01 TP -2.5510464523 #> 444 2052 3M CC01 2019 2019-04-01 TURB 0.2623642645 #> 445 2052 3M CC01 2019 2019-06-03 CHLAC 0.4700036292 I #> 446 2052 3M CC01 2019 2019-06-03 COLOR 1.4586150227 I #> 447 2052 3M CC01 2019 2019-06-03 DO 0.3001045925 #> 448 2052 3M CC01 2019 2019-06-03 DOSAT 3.1267605360 #> 449 2052 3M CC01 2019 2019-06-03 NO23 -5.5214609179 I #> 450 2052 3M CC01 2019 2019-06-03 SALIN 3.5871235452 #> 451 2052 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3.5234150144 #> 961 2067 3M CC02 2017 2017-02-06 TKN -0.5108256238 #> 962 2067 3M CC02 2017 2017-02-06 TN -0.4861330112 + #> 963 2067 3M CC02 2017 2017-02-06 TP -2.5383074265 #> 964 2067 3M CC02 2017 2017-02-06 TURB 0.9162907319 #> 965 2067 3M CC02 2017 2017-03-06 CHLAC 0.2623642645 I #> 966 2067 3M CC02 2017 2017-03-06 COLOR 2.7080502011 #> 967 2067 3M CC02 2017 2017-03-06 DO 1.3862943611 #> 968 2067 3M CC02 2017 2017-03-06 DOSAT 3.9778107460 + #> 969 2067 3M CC02 2017 2017-03-06 NO23 -4.9618451299 I #> 970 2067 3M CC02 2017 2017-03-06 SALIN 3.5174978374 #> 971 2067 3M CC02 2017 2017-03-06 TKN -0.5798184953 #> 972 2067 3M CC02 2017 2017-03-06 TN -0.5727010275 + #> 973 2067 3M CC02 2017 2017-03-06 TP -2.6882475738 #> 974 2067 3M CC02 2017 2017-03-06 TURB 1.3083328197 #> 975 2067 3M CC02 2017 2017-04-03 CHLAC 0.6931471806 #> 976 2067 3M CC02 2017 2017-04-03 COLOR 2.3978952728 #> 977 2067 3M CC02 2017 2017-04-03 DO 1.2809338455 #> 978 2067 3M CC02 2017 2017-04-03 DOSAT 4.0000338828 + #> 979 2067 3M CC02 2017 2017-04-03 NO23 -4.9618451299 I #> 980 2067 3M CC02 2017 2017-04-03 SALIN 3.5835189385 #> 981 2067 3M CC02 2017 2017-04-03 TKN -0.4155154440 #> 982 2067 3M CC02 2017 2017-04-03 TN -0.4094731295 + #> 983 2067 3M CC02 2017 2017-04-03 TP -2.6592600369 #> 984 2067 3M CC02 2017 2017-04-03 TURB 1.3862943611 #> 985 2067 3M CC02 2017 2017-05-01 CHLAC 0.7884573604 #> 986 2067 3M CC02 2017 2017-05-01 COLOR 1.5040773968 I #> 987 2067 3M CC02 2017 2017-05-01 DO 1.2527629685 #> 988 2067 3M CC02 2017 2017-05-01 DOSAT 3.9852734672 + #> 989 2067 3M CC02 2017 2017-05-01 NO23 -5.5214609179 U #> 990 2067 3M CC02 2017 2017-05-01 SALIN 3.5918177413 #> 991 2067 3M CC02 2017 2017-05-01 TKN -0.4462871026 #> 992 2067 3M CC02 2017 2017-05-01 TN -0.4431669753 + #> 993 2067 3M CC02 2017 2017-05-01 TP -3.1010927892 #> 994 2067 3M CC02 2017 2017-05-01 TURB 0.8754687374 #> 995 2067 3M CC02 2017 2017-07-10 CHLAC 1.0296194172 #> 996 2067 3M CC02 2017 2017-07-10 COLOR 3.1354942159 #> 997 2067 3M CC02 2017 2017-07-10 DO 1.1314021115 #> 998 2067 3M CC02 2017 2017-07-10 DOSAT 3.8938590348 + #> 999 2067 3M CC02 2017 2017-07-10 NO23 -4.4228486292 #> 1000 2067 3M CC02 2017 2017-07-10 SALIN 3.3978584804 #> 1001 2067 3M CC02 2017 2017-07-10 TKN -0.4620354596 #> 1002 2067 3M CC02 2017 2017-07-10 TN -0.4431669753 + #> 1003 2067 3M CC02 2017 2017-07-10 TP -2.7181005370 #> 1004 2067 3M CC02 2017 2017-07-10 TURB 1.4586150227 #> 1005 2067 3M CC02 2017 2017-08-07 CHLAC 1.1631508098 #> 1006 2067 3M CC02 2017 2017-08-07 COLOR 3.8712010109 #> 1007 2067 3M CC02 2017 2017-08-07 DO 0.8754687374 #> 1008 2067 3M CC02 2017 2017-08-07 DOSAT 3.6216707044 + #> 1009 2067 3M CC02 2017 2017-08-07 NO23 -4.5098600062 #> 1010 2067 3M CC02 2017 2017-08-07 SALIN 3.2542429687 #> 1011 2067 3M CC02 2017 2017-08-07 TKN -0.4307829161 #> 1012 2067 3M CC02 2017 2017-08-07 TN -0.4140014391 + #> 1013 2067 3M CC02 2017 2017-08-07 TP -2.5639498571 #> 1014 2067 3M CC02 2017 2017-08-07 TURB 0.5306282511 #> 1015 2067 3M CC02 2017 2017-10-02 CHLAC 1.0986122887 #> 1016 2067 3M CC02 2017 2017-10-02 COLOR 3.6888794541 #> 1017 2067 3M CC02 2017 2017-10-02 NO23 -5.2983173665 I #> 1018 2067 3M CC02 2017 2017-10-02 TKN -0.5276327421 #> 1019 2067 3M CC02 2017 2017-10-02 TN -0.5208759596 + #> 1020 2067 3M CC02 2017 2017-10-02 TP -2.3025850930 #> 1021 2067 3M CC02 2017 2017-10-02 TURB 1.0296194172 #> 1022 2067 3M CC02 2017 2017-11-06 CHLAC 0.9162907319 #> 1023 2067 3M CC02 2017 2017-11-06 COLOR 3.2188758249 #> 1024 2067 3M CC02 2017 2017-11-06 DO 1.2527629685 #> 1025 2067 3M CC02 2017 2017-11-06 DOSAT 3.8938590348 + #> 1026 2067 3M CC02 2017 2017-11-06 NO23 -4.6051701860 #> 1027 2067 3M CC02 2017 2017-11-06 SALIN 3.3499040873 #> 1028 2067 3M CC02 2017 2017-11-06 TKN -0.4620354596 #> 1029 2067 3M CC02 2017 2017-11-06 TN -0.4462871026 + #> 1030 2067 3M CC02 2017 2017-11-06 TP -2.6036901858 #> 1031 2067 3M CC02 2017 2017-11-06 TURB 0.8754687374 A #> 1032 2067 3M CC02 2017 2017-12-04 CHLAC 0.7884573604 #> 1033 2067 3M CC02 2017 2017-12-04 COLOR 2.5649493575 #> 1034 2067 3M CC02 2017 2017-12-04 DO 1.3862943611 #> 1035 2067 3M CC02 2017 2017-12-04 DOSAT 4.0181832013 + #> 1036 2067 3M CC02 2017 2017-12-04 NO23 -4.9618451299 I #> 1037 2067 3M CC02 2017 2017-12-04 SALIN 3.5025498759 #> 1038 2067 3M CC02 2017 2017-12-04 TKN -0.4780358009 #> 1039 2067 3M CC02 2017 2017-12-04 TN -0.4716049106 + #> 1040 2067 3M CC02 2017 2017-12-04 TP -2.6882475738 #> 1041 2067 3M CC02 2017 2017-12-04 TURB 1.3862943611 A #> 1042 2067 3M CC02 2018 2018-01-02 CHLAC 0.9932517730 #> 1043 2067 3M CC02 2018 2018-01-02 COLOR 2.5649493575 #> 1044 2067 3M CC02 2018 2018-01-02 DO 0.7884573604 #> 1045 2067 3M CC02 2018 2018-01-02 DOSAT 3.2580965380 + #> 1046 2067 3M CC02 2018 2018-01-02 NO23 -4.2686979494 #> 1047 2067 3M CC02 2018 2018-01-02 SALIN 3.4688560301 #> 1048 2067 3M CC02 2018 2018-01-02 TKN -0.6348782724 #> 1049 2067 3M CC02 2018 2018-01-02 TN -0.6088060321 + #> 1050 2067 3M CC02 2018 2018-01-02 TP -2.3434070875 #> 1051 2067 3M CC02 2018 2018-01-02 TURB 1.5260563035 #> 1052 2067 3M CC02 2018 2018-02-05 CHLAC 0.0953101798 I #> 1053 2067 3M CC02 2018 2018-02-05 COLOR 2.6390573296 #> 1054 2067 3M CC02 2018 2018-02-05 DO 1.5040773968 #> 1055 2067 3M CC02 2018 2018-02-05 DOSAT 4.0724397268 + #> 1056 2067 3M CC02 2018 2018-02-05 NO23 -4.1351665567 #> 1057 2067 3M CC02 2018 2018-02-05 SALIN 3.3877743613 #> 1058 2067 3M CC02 2018 2018-02-05 TKN -0.7339691751 #> 1059 2067 3M CC02 2018 2018-02-05 TN -0.7011793523 + #> 1060 2067 3M CC02 2018 2018-02-05 TP -2.7030626596 #> 1061 2067 3M CC02 2018 2018-02-05 TURB 1.2809338455 #> 1062 2067 3M CC02 2018 2018-03-05 CHLAC 0.6931471806 #> 1063 2067 3M CC02 2018 2018-03-05 COLOR 2.0014800002 #> 1064 2067 3M CC02 2018 2018-03-05 DO 1.5475625087 #> 1065 2067 3M CC02 2018 2018-03-05 DOSAT 4.1351665567 + #> 1066 2067 3M CC02 2018 2018-03-05 NO23 -5.1159958098 I #> 1067 2067 3M CC02 2018 2018-03-05 SALIN 3.5835189385 #> 1068 2067 3M CC02 2018 2018-03-05 TKN -0.7339691751 #> 1069 2067 3M CC02 2018 2018-03-05 TN -0.7256703723 + #> 1070 2067 3M CC02 2018 2018-03-05 TP -2.7333680091 #> 1071 2067 3M CC02 2018 2018-03-05 TURB 1.5892352051 A #> 1072 2067 3M CC02 2018 2018-04-02 CHLAC 0.6931471806 #> 1073 2067 3M CC02 2018 2018-04-02 COLOR 1.2527629685 I #> 1074 2067 3M CC02 2018 2018-04-02 DO 1.4109869737 #> 1075 2067 3M CC02 2018 2018-04-02 DOSAT 4.0926765051 + #> 1076 2067 3M CC02 2018 2018-04-02 NO23 -4.7105307016 I #> 1077 2067 3M CC02 2018 2018-04-02 SALIN 3.5945687746 #> 1078 2067 3M CC02 2018 2018-04-02 TKN -0.6539264674 #> 1079 2067 3M CC02 2018 2018-04-02 TN -0.6462635947 + #> 1080 2067 3M CC02 2018 2018-04-02 TP -2.5510464523 #> 1081 2067 3M CC02 2018 2018-04-02 TURB 1.7227665977 #> 1082 2067 3M CC02 2018 2018-05-07 CHLAC 0.5306282511 #> 1083 2067 3M CC02 2018 2018-05-07 COLOR 1.8245492921 #> 1084 2067 3M CC02 2018 2018-05-07 DO 1.3609765531 #> 1085 2067 3M CC02 2018 2018-05-07 DOSAT 3.9608131696 #> 1086 2067 3M CC02 2018 2018-05-07 NO23 -5.2983173665 I #> 1087 2067 3M CC02 2018 2018-05-07 SALIN 3.6027767551 #> 1088 2067 3M CC02 2018 2018-05-07 TKN -0.3147107448 #> 1089 2067 3M CC02 2018 2018-05-07 TN -0.3092462504 + #> 1090 2067 3M CC02 2018 2018-05-07 TP -2.7488721956 #> 1091 2067 3M CC02 2018 2018-05-07 TURB 1.3083328197 #> 1092 2067 3M CC02 2018 2018-07-09 CHLAC 1.6094379124 #> 1093 2067 3M CC02 2018 2018-07-09 COLOR 2.7725887222 #> 1094 2067 3M CC02 2018 2018-07-09 DO 1.0818051704 #> 1095 2067 3M CC02 2018 2018-07-09 DOSAT 3.8308129500 #> 1096 2067 3M CC02 2018 2018-07-09 NO23 -5.2983173665 I #> 1097 2067 3M CC02 2018 2018-07-09 SALIN 3.4741380061 #> 1098 2067 3M CC02 2018 2018-07-09 TKN -0.5276327421 #> 1099 2067 3M CC02 2018 2018-07-09 TN -0.5208759596 + #> 1100 2067 3M CC02 2018 2018-07-09 TURB 0.9932517730 #> 1101 2067 3M CC02 2018 2018-08-06 CHLAC 1.8562979904 #> 1102 2067 3M CC02 2018 2018-08-06 COLOR 3.5263605246 A #> 1103 2067 3M CC02 2018 2018-08-06 DO 0.8586616190 #> 1104 2067 3M CC02 2018 2018-08-06 DOSAT 3.6270040504 #> 1105 2067 3M CC02 2018 2018-08-06 NO23 -5.1159958098 I #> 1106 2067 3M CC02 2018 2018-08-06 SALIN 3.4968105459 #> 1107 2067 3M CC02 2018 2018-08-06 TKN -0.2107210313 #> 1108 2067 3M CC02 2018 2018-08-06 TN -0.2057949130 + #> 1109 2067 3M CC02 2018 2018-08-06 TP -2.3968957725 #> 1110 2067 3M CC02 2018 2018-08-06 TURB 1.0296194172 A #> 1111 2067 3M CC02 2019 2019-02-04 CHLAC -0.1984509387 I #> 1112 2067 3M CC02 2019 2019-02-04 COLOR 3.1354942159 #> 1113 2067 3M CC02 2019 2019-02-04 DO 1.3323660191 #> 1114 2067 3M CC02 2019 2019-02-04 DOSAT 3.8999504242 #> 1115 2067 3M CC02 2019 2019-02-04 NO23 -4.1997050779 #> 1116 2067 3M CC02 2019 2019-02-04 SALIN 3.2669037939 #> 1117 2067 3M CC02 2019 2019-02-04 TKN -0.6931471806 #> 1118 2067 3M CC02 2019 2019-02-04 TN -0.6635883783 + #> 1119 2067 3M CC02 2019 2019-02-04 TP -2.7181005370 #> 1120 2067 3M CC02 2019 2019-02-04 TURB 0.9932517730 #> 1121 2067 3M CC02 2019 2019-03-04 CHLAC 0.2623642645 I #> 1122 2067 3M CC02 2019 2019-03-04 COLOR 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NO23 -4.8283137373 I #> 1141 2067 3M CC02 2019 2019-05-06 SALIN 3.5522002552 #> 1142 2067 3M CC02 2019 2019-05-06 TKN -0.5108256238 #> 1143 2067 3M CC02 2019 2019-05-06 TN -0.5041810810 + #> 1144 2067 3M CC02 2019 2019-05-06 TP -2.7030626596 #> 1145 2067 3M CC02 2019 2019-05-06 TURB 1.0647107370 #> 1146 2067 3M CC02 2019 2019-06-03 CHLAC 0.6418538862 I #> 1147 2067 3M CC02 2019 2019-06-03 COLOR 1.3350010667 I #> 1148 2067 3M CC02 2019 2019-06-03 DO 0.4700036292 #> 1149 2067 3M CC02 2019 2019-06-03 DOSAT 3.2771447330 #> 1150 2067 3M CC02 2019 2019-06-03 NO23 -4.3428059215 #> 1151 2067 3M CC02 2019 2019-06-03 SALIN 3.5882300460 #> 1152 2067 3M CC02 2019 2019-06-03 TKN -0.5447271754 #> 1153 2067 3M CC02 2019 2019-06-03 TN -0.5225608800 + #> 1154 2067 3M CC02 2019 2019-06-03 TP -2.6172958378 #> 1155 2067 3M CC02 2019 2019-06-03 TURB 0.6931471806 #> 1156 2067 3M CC02 2019 2019-07-01 CHLAC 0.7419373447 I #> 1157 2067 3M CC02 2019 2019-07-01 COLOR 1.9315214116 #> 1158 2067 3M CC02 2019 2019-07-01 NO23 -4.8283137373 I #> 1159 2067 3M CC02 2019 2019-07-01 SALIN 3.5424075502 #> 1160 2067 3M CC02 2019 2019-07-01 TKN -0.5621189182 #> 1161 2067 3M CC02 2019 2019-07-01 TN -0.5551258827 + #> 1162 2067 3M CC02 2019 2019-07-01 TP -3.1941832123 #> 1163 2067 3M CC02 2019 2019-07-01 TURB 0.8329091229 #> 1164 2067 3M CC02 2019 2019-08-05 CHLAC 0.6418538862 I #> 1165 2067 3M CC02 2019 2019-08-05 COLOR 3.7841896339 A #> 1166 2067 3M CC02 2019 2019-08-05 DO 0.6312717768 #> 1167 2067 3M CC02 2019 2019-08-05 DOSAT 3.3775875160 #> 1168 2067 3M CC02 2019 2019-08-05 NO23 -4.7105307016 I #> 1169 2067 3M CC02 2019 2019-08-05 SALIN 3.3617633124 #> 1170 2067 3M CC02 2019 2019-08-05 TKN -0.4780358009 #> 1171 2067 3M CC02 2019 2019-08-05 TN -0.4716049106 + #> 1172 2067 3M CC02 2019 2019-08-05 TP -3.1010927892 #> 1173 2067 3M CC02 2019 2019-08-05 TURB 0.4054651081 #> 1174 2067 3M CC02 2019 2019-10-07 CHLAC 1.3350010667 #> 1175 2067 3M CC02 2019 2019-10-07 COLOR 1.2809338455 I #> 1176 2067 3M CC02 2019 2019-10-07 DO 1.0508216248 #> 1177 2067 3M CC02 2019 2019-10-07 DOSAT 3.7750571504 #> 1178 2067 3M CC02 2019 2019-10-07 NO23 -5.2983173665 I #> 1179 2067 3M CC02 2019 2019-10-07 SALIN 3.5389282774 #> 1180 2067 3M CC02 2019 2019-10-07 TKN -0.6733445533 #> 1181 2067 3M CC02 2019 2019-10-07 TN -0.6655320135 + #> 1182 2067 3M CC02 2019 2019-10-07 TP -2.9759296463 #> 1183 2067 3M CC02 2019 2019-10-07 TURB 1.1314021115 #> 1184 2067 3M CC02 2019 2019-11-04 CHLAC 1.6292405397 #> 1185 2067 3M CC02 2019 2019-11-04 COLOR 1.4816045409 I #> 1186 2067 3M CC02 2019 2019-11-04 DO 0.4762341790 #> 1187 2067 3M CC02 2019 2019-11-04 DOSAT 3.2464909919 #> 1188 2067 3M CC02 2019 2019-11-04 NO23 -4.4228486292 #> 1189 2067 3M CC02 2019 2019-11-04 SALIN 3.5177945292 #> 1190 2067 3M CC02 2019 2019-11-04 TKN -0.4307829161 #> 1191 2067 3M CC02 2019 2019-11-04 TN -0.4124897230 + #> 1192 2067 3M CC02 2019 2019-11-04 TP -2.5257286443 #> 1193 2067 3M CC02 2019 2019-11-04 TURB 1.2809338455 #> 1194 2067 3M CC02 2019 2019-12-02 CHLAC 0.0953101798 I #> 1195 2067 3M CC02 2019 2019-12-02 COLOR 0.9162907319 U #> 1196 2067 3M CC02 2019 2019-12-02 DO 0.9932517730 #> 1197 2067 3M CC02 2019 2019-12-02 DOSAT 3.6454498962 #> 1198 2067 3M CC02 2019 2019-12-02 NO23 -4.4228486292 #> 1199 2067 3M CC02 2019 2019-12-02 SALIN 3.5133348816 #> 1200 2067 3M CC02 2019 2019-12-02 TKN -0.7765287895 #> 1201 2067 3M CC02 2019 2019-12-02 TN -0.7507762934 + #> 1202 2067 3M CC02 2019 2019-12-02 TP -2.9374633654 #> 1203 2067 3M CC02 2019 2019-12-02 TURB 0.7419373447 #> 1204 2067 3M CC02 2020 2020-01-06 CHLAC 0.6931471806 I #> 1205 2067 3M CC02 2020 2020-01-06 COLOR 2.5649493575 #> 1206 2067 3M CC02 2020 2020-01-06 NO23 -4.2686979494 #> 1207 2067 3M CC02 2020 2020-01-06 SALIN 3.4775409482 #> 1208 2067 3M CC02 2020 2020-01-06 TKN -0.4620354596 #> 1209 2067 3M CC02 2020 2020-01-06 TN -0.4400565529 + #> 1210 2067 3M CC02 2020 2020-01-06 TP -2.3859667019 #> 1211 2067 3M CC02 2020 2020-01-06 TURB 1.2809338455 #> 1212 2067 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2067 3M CC02 2020 2020-03-02 TURB 1.7749523509 A #> 1231 2067 3M CC02 2020 2020-09-08 CHLAC 1.4350845253 #> 1232 2067 3M CC02 2020 2020-09-08 COLOR 3.9318256327 A #> 1233 2067 3M CC02 2020 2020-09-08 DO 0.6259384309 #> 1234 2067 3M CC02 2020 2020-09-08 DOSAT 3.3214324132 #> 1235 2067 3M CC02 2020 2020-09-08 NO23 -4.2686979494 #> 1236 2067 3M CC02 2020 2020-09-08 SALIN 3.2268439945 #> 1237 2067 3M CC02 2020 2020-09-08 TKN -0.3856624808 #> 1238 2067 3M CC02 2020 2020-09-08 TN -0.3652833185 + #> 1239 2067 3M CC02 2020 2020-09-08 TP -2.5639498571 #> 1240 2067 3M CC02 2020 2020-09-08 TURB 0.7419373447 #> 1241 2067 3M CC02 2020 2020-10-05 CHLAC 0.8754687374 I #> 1242 2067 3M CC02 2020 2020-10-05 COLOR 3.4339872045 A #> 1243 2067 3M CC02 2020 2020-10-05 DO 0.7793248768 #> 1244 2067 3M CC02 2020 2020-10-05 DOSAT 3.4038604991 #> 1245 2067 3M CC02 2020 2020-10-05 NO23 -3.6496587410 #> 1246 2067 3M CC02 2020 2020-10-05 SALIN 3.3769046891 #> 1247 2067 3M CC02 2020 2020-10-05 TKN -0.5447271754 #> 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NO23 -5.5214609179 U #> 1481 2067 3M CC02 2023 2023-01-03 SALIN 3.4249139083 #> 1482 2067 3M CC02 2023 2023-01-03 TKN -0.5798184953 #> 1483 2067 3M CC02 2023 2023-01-03 TN -0.5762534291 + #> 1484 2067 3M CC02 2023 2023-01-03 TP -2.5383074265 #> 1485 2067 3M CC02 2023 2023-01-03 TURB 1.0296194172 #> 1486 2067 3M CC02 2023 2023-02-06 CHLAC 0.8754687374 I #> 1487 2067 3M CC02 2023 2023-02-06 COLOR 2.1747517215 #> 1488 2067 3M CC02 2023 2023-02-06 DO 1.8017098001 #> 1489 2067 3M CC02 2023 2023-02-06 DOSAT 4.4260435201 #> 1490 2067 3M CC02 2023 2023-02-06 NO23 -5.1159958098 I #> 1491 2067 3M CC02 2023 2023-02-06 SALIN 3.4895134627 #> 1492 2067 3M CC02 2023 2023-02-06 TKN -0.7765287895 #> 1493 2067 3M CC02 2023 2023-02-06 TN -0.7678707268 + #> 1494 2067 3M CC02 2023 2023-02-06 TP -2.6882475738 #> 1495 2067 3M CC02 2023 2023-02-06 TURB 0.9932517730 #> 1496 2067 3M CC02 2023 2023-03-06 DO 1.7369512327 #> 1497 2067 3M CC02 2023 2023-03-06 DOSAT 4.4555094114 #> 1498 2067 3M CC02 2023 2023-03-06 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2018-05-08 TKN -0.4462871026 #> 1517 2067 3M CC02 2018 2018-05-08 TN -0.4431669753 + #> 1518 2067 3M CC02 2018 2018-05-08 TP -2.7181005370 #> 1519 2067 3M CC02 2018 2018-05-08 TSS 1.6094379124 I #> 1520 2067 3M CC02 2018 2018-05-08 TURB 1.2237754316 #> 1521 2067 3M CC02 2018 2018-06-26 CHLAC 2.5649493575 #> 1522 2067 3M CC02 2018 2018-06-26 COND 10.6878456131 #> 1523 2067 3M CC02 2018 2018-06-26 DO 1.2947271676 #> 1524 2067 3M CC02 2018 2018-06-26 DOSAT 4.0395363257 #> 1525 2067 3M CC02 2018 2018-06-26 NO23 -4.9618451299 I #> 1526 2067 3M CC02 2018 2018-06-26 TKN -0.3566749439 #> 1527 2067 3M CC02 2018 2018-06-26 TN -0.3509769228 + #> 1528 2067 3M CC02 2018 2018-06-26 TP -2.3025850930 #> 1529 2067 3M CC02 2018 2018-06-26 TSS 2.0794415417 I #> 1530 2067 3M CC02 2018 2018-06-26 TURB 1.0647107370 A #> 1531 2067 3M CC02 2018 2018-09-18 CHLAC 2.3978952728 #> 1532 2067 3M CC02 2018 2018-09-18 COND 10.2632925926 #> 1533 2067 3M CC02 2018 2018-09-18 DO 0.9745596400 #> 1534 2067 3M CC02 2018 2018-09-18 DOSAT 3.6963514690 #> 1535 2067 3M CC02 2018 2018-09-18 NO23 -3.2188758249 #> 1536 2067 3M CC02 2018 2018-09-18 TKN -0.2231435513 #> 1537 2067 3M CC02 2018 2018-09-18 TN -0.1743533871 + #> 1538 2067 3M CC02 2018 2018-09-18 TP -2.0402208285 #> 1539 2067 3M CC02 2018 2018-09-18 TSS 1.3862943611 I #> 1540 2067 3M CC02 2018 2018-09-18 TURB 0.7884573604 #> 1541 2067 3M CC02 2018 2018-12-04 CHLAC 1.2809338455 #> 1542 2067 3M CC02 2018 2018-12-04 COND 10.8257007122 #> 1543 2067 3M CC02 2018 2018-12-04 DO 1.6272778306 #> 1544 2067 3M CC02 2018 2018-12-04 DOSAT 4.3107991254 #> 1545 2067 3M CC02 2018 2018-12-04 NO23 -1.9661128564 G #> 1546 2067 3M CC02 2018 2018-12-04 SALIN 3.4949912609 #> 1547 2067 3M CC02 2018 2018-12-04 TKN -0.4155154440 #> 1548 2067 3M CC02 2018 2018-12-04 TN -0.2231435513 + #> 1549 2067 3M CC02 2018 2018-12-04 TP -2.5010360317 #> 1550 2067 3M CC02 2018 2018-12-04 TSS 2.3025850930 I #> 1551 2067 3M CC02 2018 2018-12-04 TURB 0.4054651081 #> 1552 2068 3M CC03 2014 2014-01-06 CHLAC 0.3364722366 I #> 1553 2068 3M CC03 2014 2014-01-06 COLOR 2.5649493575 #> 1554 2068 3M CC03 2014 2014-01-06 DO 1.3862943611 #> 1555 2068 3M CC03 2014 2014-01-06 DOSAT 3.9963641539 + #> 1556 2068 3M CC03 2014 2014-01-06 NO23 -4.7105307016 I #> 1557 2068 3M CC03 2014 2014-01-06 SALIN 3.4904285154 #> 1558 2068 3M CC03 2014 2014-01-06 TKN -0.6161861394 #> 1559 2068 3M CC03 2014 2014-01-06 TN -0.6088060321 + #> 1560 2068 3M CC03 2014 2014-01-06 TP -3.1010927892 #> 1561 2068 3M CC03 2014 2014-01-06 TURB 0.4054651081 #> 1562 2068 3M CC03 2014 2014-02-03 CHLAC 1.8870696490 #> 1563 2068 3M CC03 2014 2014-02-03 COLOR 3.5263605246 #> 1564 2068 3M CC03 2014 2014-02-03 DO 0.7884573604 #> 1565 2068 3M CC03 2014 2014-02-03 DOSAT 3.2921262866 + #> 1566 2068 3M CC03 2014 2014-02-03 NO23 -3.6888794541 #> 1567 2068 3M CC03 2014 2014-02-03 SALIN 2.6602595373 #> 1568 2068 3M CC03 2014 2014-02-03 TKN 0.0000000000 #> 1569 2068 3M CC03 2014 2014-02-03 TN 0.0246926126 + #> 1570 2068 3M CC03 2014 2014-02-03 TP -2.3025850930 #> 1571 2068 3M CC03 2014 2014-02-03 TURB 0.8329091229 #> 1572 2068 3M CC03 2014 2014-03-03 CHLAC 1.0986122887 #> 1573 2068 3M CC03 2014 2014-03-03 COLOR 2.8332133441 #> 1574 2068 3M CC03 2014 2014-03-03 DO 0.7884573604 #> 1575 2068 3M CC03 2014 2014-03-03 DOSAT 3.3638415951 + #> 1576 2068 3M CC03 2014 2014-03-03 NO23 -5.5214609179 I #> 1577 2068 3M CC03 2014 2014-03-03 SALIN 3.2657594108 #> 1578 2068 3M CC03 2014 2014-03-03 TKN -0.4462871026 #> 1579 2068 3M CC03 2014 2014-03-03 TN -0.4400565529 + #> 1580 2068 3M CC03 2014 2014-03-03 TP -2.6592600369 #> 1581 2068 3M CC03 2014 2014-03-03 TURB 0.7884573604 #> 1582 2068 3M CC03 2014 2014-04-07 CHLAC 1.2237754316 #> 1583 2068 3M CC03 2014 2014-04-07 COLOR 3.4011973817 A #> 1584 2068 3M CC03 2014 2014-04-07 DO 0.6418538862 #> 1585 2068 3M CC03 2014 2014-04-07 DOSAT 3.2580965380 + #> 1586 2068 3M CC03 2014 2014-04-07 NO23 -4.3428059215 #> 1587 2068 3M CC03 2014 2014-04-07 SALIN 3.1000922889 #> 1588 2068 3M 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3M CC03 2014 2014-06-02 NO23 -5.2983173665 I #> 1607 2068 3M CC03 2014 2014-06-02 SALIN 3.0633909220 #> 1608 2068 3M CC03 2014 2014-06-02 TKN -0.2744368457 #> 1609 2068 3M CC03 2014 2014-06-02 TN -0.2691874898 + #> 1610 2068 3M CC03 2014 2014-06-02 TP -2.9957322736 #> 1611 2068 3M CC03 2014 2014-06-02 TURB 0.5877866649 #> 1612 2068 3M CC03 2014 2014-07-07 CHLAC 1.4350845253 #> 1613 2068 3M CC03 2014 2014-07-07 COLOR 3.6375861597 A #> 1614 2068 3M CC03 2014 2014-07-07 DO -0.9162907319 #> 1615 2068 3M CC03 2014 2014-07-07 DOSAT 1.8562979904 + #> 1616 2068 3M CC03 2014 2014-07-07 NO23 -5.5214609179 I #> 1617 2068 3M CC03 2014 2014-07-07 SALIN 3.5438536821 #> 1618 2068 3M CC03 2014 2014-07-07 TKN -0.2357223335 #> 1619 2068 3M CC03 2014 2014-07-07 TN -0.2306718177 + #> 1620 2068 3M CC03 2014 2014-07-07 TP -3.1235656451 #> 1621 2068 3M CC03 2014 2014-07-07 TURB 1.8082887712 #> 1622 2068 3M CC03 2014 2014-08-04 CHLAC 1.6292405397 #> 1623 2068 3M CC03 2014 2014-08-04 COLOR 3.6375861597 #> 1624 2068 3M CC03 2014 2014-08-04 DO -0.3566749439 #> 1625 2068 3M CC03 2014 2014-08-04 DOSAT 2.3887627892 + #> 1626 2068 3M CC03 2014 2014-08-04 NO23 -5.5214609179 I #> 1627 2068 3M CC03 2014 2014-08-04 SALIN 3.4242626546 #> 1628 2068 3M CC03 2014 2014-08-04 TKN -0.1508228897 #> 1629 2068 3M CC03 2014 2014-08-04 TN -0.1461825102 + #> 1630 2068 3M CC03 2014 2014-08-04 TP -2.9565115604 #> 1631 2068 3M CC03 2014 2014-08-04 TURB 1.2809338455 #> 1632 2068 3M CC03 2014 2014-09-08 CHLAC 2.3025850930 #> 1633 2068 3M CC03 2014 2014-09-08 COLOR 3.2958368660 #> 1634 2068 3M CC03 2014 2014-09-08 DO -1.2039728043 #> 1635 2068 3M CC03 2014 2014-09-08 DOSAT 1.5040773968 + #> 1636 2068 3M CC03 2014 2014-09-08 NO23 -5.5214609179 U #> 1637 2068 3M CC03 2014 2014-09-08 SALIN 3.4011973817 #> 1638 2068 3M CC03 2014 2014-09-08 TKN -0.1508228897 #> 1639 2068 3M CC03 2014 2014-09-08 TN -0.1485000083 + #> 1640 2068 3M CC03 2014 2014-09-08 TP -2.8824035882 #> 1641 2068 3M CC03 2014 2014-09-08 TURB 1.1631508098 #> 1642 2068 3M CC03 2014 2014-10-06 CHLAC 2.3025850930 #> 1643 2068 3M CC03 2014 2014-10-06 COLOR 4.1588830834 #> 1644 2068 3M CC03 2014 2014-10-06 DO 0.6931471806 #> 1645 2068 3M CC03 2014 2014-10-06 DOSAT 3.2464909919 + #> 1646 2068 3M CC03 2014 2014-10-06 NO23 -4.7105307016 I #> 1647 2068 3M CC03 2014 2014-10-06 SALIN 2.7080502011 #> 1648 2068 3M CC03 2014 2014-10-06 TKN -0.1165338163 #> 1649 2068 3M CC03 2014 2014-10-06 TN -0.1120495038 + #> 1650 2068 3M CC03 2014 2014-10-06 TP -1.9661128564 #> 1651 2068 3M CC03 2014 2014-10-06 TURB 1.1631508098 #> 1652 2068 3M CC03 2014 2014-11-03 CHLAC 2.3978952728 #> 1653 2068 3M CC03 2014 2014-11-03 COLOR 3.5835189385 #> 1654 2068 3M CC03 2014 2014-11-03 DO 1.3862943611 #> 1655 2068 3M CC03 2014 2014-11-03 DOSAT 3.8543938926 + #> 1656 2068 3M CC03 2014 2014-11-03 NO23 -4.5098600062 #> 1657 2068 3M CC03 2014 2014-11-03 SALIN 3.1612467120 #> 1658 2068 3M CC03 2014 2014-11-03 TKN -0.1743533871 #> 1659 2068 3M CC03 2014 2014-11-03 TN -0.1613431504 + #> 1660 2068 3M CC03 2014 2014-11-03 TP -2.6036901858 #> 1661 2068 3M CC03 2014 2014-11-03 TURB 1.0647107370 #> 1662 2068 3M CC03 2015 2015-01-05 CHLAC 2.0281482473 #> 1663 2068 3M CC03 2015 2015-01-05 COLOR 3.2188758249 #> 1664 2068 3M CC03 2015 2015-01-05 DO 0.9162907319 #> 1665 2068 3M CC03 2015 2015-01-05 DOSAT 3.5438536821 + #> 1666 2068 3M CC03 2015 2015-01-05 NO23 -4.4228486292 #> 1667 2068 3M CC03 2015 2015-01-05 SALIN 3.2995337279 #> 1668 2068 3M CC03 2015 2015-01-05 TKN -0.0512932944 #> 1669 2068 3M CC03 2015 2015-01-05 TN -0.0387408283 + #> 1670 2068 3M CC03 2015 2015-01-05 TP -2.5383074265 #> 1671 2068 3M CC03 2015 2015-01-05 TURB 0.6418538862 #> 1672 2068 3M CC03 2015 2015-02-02 CHLAC 0.6418538862 #> 1673 2068 3M CC03 2015 2015-02-02 COLOR 2.3025850930 #> 1674 2068 3M CC03 2015 2015-02-02 DO 1.4109869737 #> 1675 2068 3M CC03 2015 2015-02-02 DOSAT 3.9778107460 + #> 1676 2068 3M CC03 2015 2015-02-02 NO23 -5.1159958098 I #> 1677 2068 3M CC03 2015 2015-02-02 SALIN 3.3911470458 #> 1678 2068 3M CC03 2015 2015-02-02 TKN -0.7765287895 #> 1679 2068 3M CC03 2015 2015-02-02 TN -0.7678707268 + #> 1680 2068 3M CC03 2015 2015-02-02 TP -2.9957322736 #> 1681 2068 3M CC03 2015 2015-02-02 TURB 0.3364722366 #> 1682 2068 3M CC03 2015 2015-03-02 CHLAC 1.6677068206 A #> 1683 2068 3M CC03 2015 2015-03-02 COLOR 3.1354942159 #> 1684 2068 3M CC03 2015 2015-03-02 DO 0.9932517730 #> 1685 2068 3M CC03 2015 2015-03-02 DOSAT 3.5862928653 + #> 1686 2068 3M CC03 2015 2015-03-02 NO23 -4.5098600062 #> 1687 2068 3M CC03 2015 2015-03-02 SALIN 3.1311369106 #> 1688 2068 3M CC03 2015 2015-03-02 TKN -0.4780358009 #> 1689 2068 3M CC03 2015 2015-03-02 TN -0.4604494164 + #> 1690 2068 3M CC03 2015 2015-03-02 TP -2.8824035882 #> 1691 2068 3M CC03 2015 2015-03-02 TURB 0.3364722366 #> 1692 2068 3M CC03 2015 2015-04-06 CHLAC 0.8754687374 #> 1693 2068 3M CC03 2015 2015-04-06 COLOR 3.0910424534 #> 1694 2068 3M CC03 2015 2015-04-06 DO -0.1053605157 #> 1695 2068 3M CC03 2015 2015-04-06 DOSAT 2.5494451709 + #> 1696 2068 3M CC03 2015 2015-04-06 NO23 -5.5214609179 U #> 1697 2068 3M CC03 2015 2015-04-06 SALIN 3.4011973817 #> 1698 2068 3M CC03 2015 2015-04-06 TKN -0.3566749439 #> 1699 2068 3M CC03 2015 2015-04-06 TN -0.3538218750 + #> 1700 2068 3M CC03 2015 2015-04-06 TP -3.2188758249 #> 1701 2068 3M CC03 2015 2015-04-06 TURB 0.4700036292 #> 1702 2068 3M CC03 2015 2015-05-04 CHLAC 0.9932517730 #> 1703 2068 3M CC03 2015 2015-05-04 COLOR 3.2188758249 #> 1704 2068 3M CC03 2015 2015-05-04 DO 0.1823215568 #> 1705 2068 3M CC03 2015 2015-05-04 DOSAT 2.8622008809 + #> 1706 2068 3M CC03 2015 2015-05-04 NO23 -4.8283137373 I #> 1707 2068 3M CC03 2015 2015-05-04 SALIN 3.4904285154 #> 1708 2068 3M CC03 2015 2015-05-04 TKN -0.3856624808 #> 1709 2068 3M CC03 2015 2015-05-04 TN -0.3797973614 + #> 1710 2068 3M CC03 2015 2015-05-04 TP -3.2968373663 #> 1711 2068 3M CC03 2015 2015-05-04 TURB 0.6931471806 #> 1712 2068 3M CC03 2015 2015-06-01 CHLAC 1.7749523509 #> 1713 2068 3M CC03 2015 2015-06-01 COLOR 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TURB 1.5892352051 #> 1732 2068 3M CC03 2015 2015-09-08 CHLAC 1.7227665977 #> 1733 2068 3M CC03 2015 2015-09-08 COLOR 3.8286413965 #> 1734 2068 3M CC03 2015 2015-09-08 DO 0.0000000000 #> 1735 2068 3M CC03 2015 2015-09-08 DOSAT 2.6602595373 + #> 1736 2068 3M CC03 2015 2015-09-08 NO23 -4.8283137373 I #> 1737 2068 3M CC03 2015 2015-09-08 SALIN 2.9014215941 #> 1738 2068 3M CC03 2015 2015-09-08 TKN -0.2357223335 #> 1739 2068 3M CC03 2015 2015-09-08 TN -0.2306718177 + #> 1740 2068 3M CC03 2015 2015-09-08 TP -3.0159349809 #> 1741 2068 3M CC03 2015 2015-09-08 TURB 0.6931471806 #> 1742 2068 3M CC03 2015 2015-10-05 CHLAC 1.4586150227 #> 1743 2068 3M CC03 2015 2015-10-05 COLOR 3.2958368660 A #> 1744 2068 3M CC03 2015 2015-10-05 DO 0.6418538862 #> 1745 2068 3M CC03 2015 2015-10-05 DOSAT 3.3214324132 + #> 1746 2068 3M CC03 2015 2015-10-05 NO23 -5.5214609179 U #> 1747 2068 3M CC03 2015 2015-10-05 SALIN 3.3741687093 #> 1748 2068 3M CC03 2015 2015-10-05 TKN -0.4307829161 #> 1749 2068 3M CC03 2015 2015-10-05 TN -0.4277107171 + #> 1750 2068 3M CC03 2015 2015-10-05 TP -3.0576076773 #> 1751 2068 3M CC03 2015 2015-10-05 TURB 0.8754687374 #> 1752 2068 3M CC03 2015 2015-12-07 CHLAC 1.3609765531 #> 1753 2068 3M CC03 2015 2015-12-07 COLOR 3.2188758249 #> 1754 2068 3M CC03 2015 2015-12-07 DO 1.1314021115 #> 1755 2068 3M CC03 2015 2015-12-07 DOSAT 3.7447870861 + #> 1756 2068 3M CC03 2015 2015-12-07 NO23 -4.5098600062 #> 1757 2068 3M CC03 2015 2015-12-07 SALIN 3.4144426084 #> 1758 2068 3M CC03 2015 2015-12-07 TKN -0.4462871026 #> 1759 2068 3M CC03 2015 2015-12-07 TN -0.4292456368 + #> 1760 2068 3M CC03 2015 2015-12-07 TP -2.8473122684 #> 1761 2068 3M CC03 2015 2015-12-07 TURB 1.1939224685 #> 1762 2068 3M CC03 2016 2016-01-04 CHLAC 1.3083328197 #> 1763 2068 3M CC03 2016 2016-01-04 COLOR 3.3672958300 #> 1764 2068 3M CC03 2016 2016-01-04 DO 0.0000000000 #> 1765 2068 3M CC03 2016 2016-01-04 DOSAT 2.5176964726 + #> 1766 2068 3M CC03 2016 2016-01-04 NO23 -4.0173835211 #> 1767 2068 3M CC03 2016 2016-01-04 SALIN 3.1904763503 #> 1768 2068 3M CC03 2016 2016-01-04 TKN -0.3566749439 #> 1769 2068 3M CC03 2016 2016-01-04 TN -0.3312857099 + #> 1770 2068 3M CC03 2016 2016-01-04 TP -2.6172958378 #> 1771 2068 3M CC03 2016 2016-01-04 TURB 0.8754687374 #> 1772 2068 3M CC03 2016 2016-02-01 CHLAC 1.0647107370 #> 1773 2068 3M CC03 2016 2016-02-01 COLOR 3.6635616461 #> 1774 2068 3M CC03 2016 2016-02-01 DOSAT 3.7256934272 + #> 1775 2068 3M CC03 2016 2016-02-01 NO23 -2.7030626596 #> 1776 2068 3M CC03 2016 2016-02-01 SALIN 2.7850112422 #> 1777 2068 3M CC03 2016 2016-02-01 TKN -0.2357223335 #> 1778 2068 3M CC03 2016 2016-02-01 TN -0.1543173604 + #> 1779 2068 3M CC03 2016 2016-02-01 TP -2.0402208285 #> 1780 2068 3M CC03 2016 2016-02-01 TURB 0.6418538862 #> 1781 2068 3M CC03 2016 2016-03-07 CHLAC 1.7227665977 #> 1782 2068 3M CC03 2016 2016-03-07 COLOR 3.5835189385 #> 1783 2068 3M CC03 2016 2016-03-07 DO 0.8329091229 #> 1784 2068 3M CC03 2016 2016-03-07 DOSAT 3.2995337279 + #> 1785 2068 3M CC03 2016 2016-03-07 NO23 -4.7105307016 I #> 1786 2068 3M CC03 2016 2016-03-07 SALIN 2.7080502011 #> 1787 2068 3M CC03 2016 2016-03-07 TKN -0.3011050928 #> 1788 2068 3M CC03 2016 2016-03-07 TN -0.2957142441 + #> 1789 2068 3M CC03 2016 2016-03-07 TP -2.3025850930 #> 1790 2068 3M CC03 2016 2016-03-07 TURB 1.1631508098 A #> 1791 2068 3M CC03 2016 2016-04-04 CHLAC 0.9932517730 #> 1792 2068 3M CC03 2016 2016-04-04 COLOR 3.5263605246 #> 1793 2068 3M CC03 2016 2016-04-04 DO 0.9555114450 #> 1794 2068 3M CC03 2016 2016-04-04 DOSAT 3.5263605246 + #> 1795 2068 3M CC03 2016 2016-04-04 NO23 -4.5098600062 #> 1796 2068 3M CC03 2016 2016-04-04 SALIN 3.0007198151 #> 1797 2068 3M CC03 2016 2016-04-04 TKN -0.3566749439 #> 1798 2068 3M CC03 2016 2016-04-04 TN -0.3410828492 + #> 1799 2068 3M CC03 2016 2016-04-04 TP -2.3859667019 #> 1800 2068 3M CC03 2016 2016-04-04 TURB 1.0296194172 #> 1801 2068 3M CC03 2016 2016-05-02 CHLAC 0.3364722366 I #> 1802 2068 3M CC03 2016 2016-05-02 COLOR 3.2580965380 #> 1803 2068 3M CC03 2016 2016-05-02 DO 0.7884573604 #> 1804 2068 3M CC03 2016 2016-05-02 DOSAT 3.5234150144 + #> 1805 2068 3M CC03 2016 2016-05-02 NO23 -5.5214609179 U #> 1806 2068 3M CC03 2016 2016-05-02 SALIN 3.6270040504 #> 1807 2068 3M CC03 2016 2016-05-02 TKN -0.3566749439 #> 1808 2068 3M CC03 2016 2016-05-02 TN -0.3538218750 + #> 1809 2068 3M CC03 2016 2016-05-02 TP -2.5639498571 #> 1810 2068 3M CC03 2016 2016-05-02 TURB 0.0953101798 #> 1811 2068 3M CC03 2017 2017-08-07 CHLAC 2.3978952728 #> 1812 2068 3M CC03 2017 2017-08-07 COLOR 4.2195077052 #> 1813 2068 3M CC03 2017 2017-08-07 DOSAT 2.3513752572 + #> 1814 2068 3M CC03 2017 2017-08-07 NO23 -5.5214609179 U #> 1815 2068 3M CC03 2017 2017-08-07 SALIN 1.4350845253 #> 1816 2068 3M CC03 2017 2017-08-07 TKN 0.5306282511 #> 1817 2068 3M CC03 2017 2017-08-07 TN 0.5318040302 + #> 1818 2068 3M CC03 2017 2017-08-07 TP -2.7030626596 #> 1819 2068 3M CC03 2017 2017-08-07 TURB 0.9162907319 #> 1820 2068 3M CC03 2017 2017-09-05 CHLAC 2.7080502011 #> 1821 2068 3M CC03 2017 2017-09-05 COLOR 5.0106352941 #> 1822 2068 3M CC03 2017 2017-09-05 DO 0.6931471806 #> 1823 2068 3M CC03 2017 2017-09-05 DOSAT 3.2884018875 + #> 1824 2068 3M CC03 2017 2017-09-05 NO23 -4.4228486292 #> 1825 2068 3M CC03 2017 2017-09-05 SALIN 2.2721258855 #> 1826 2068 3M CC03 2017 2017-09-05 TKN 0.1823215568 #> 1827 2068 3M CC03 2017 2017-09-05 TN 0.1922718876 + #> 1828 2068 3M CC03 2017 2017-09-05 TP -1.7719568419 #> 1829 2068 3M CC03 2017 2017-09-05 TURB 1.3350010667 #> 1830 2068 3M CC03 2017 2017-10-02 CHLAC 2.5649493575 #> 1831 2068 3M CC03 2017 2017-10-02 COLOR 4.0943445622 A #> 1832 2068 3M CC03 2017 2017-10-02 NO23 -5.5214609179 U #> 1833 2068 3M CC03 2017 2017-10-02 TKN -0.0725706928 #> 1834 2068 3M CC03 2017 2017-10-02 TN -0.0704224643 + #> 1835 2068 3M CC03 2017 2017-10-02 TP -2.3025850930 #> 1836 2068 3M CC03 2017 2017-10-02 TURB 1.8870696490 #> 1837 2068 3M CC03 2017 2017-11-06 CHLAC 1.1631508098 #> 1838 2068 3M CC03 2017 2017-11-06 COLOR 3.5835189385 #> 1839 2068 3M CC03 2017 2017-11-06 DO 1.3083328197 #> 1840 2068 3M CC03 2017 2017-11-06 DOSAT 3.9080149840 + #> 1841 2068 3M CC03 2017 2017-11-06 NO23 -5.2983173665 I #> 1842 2068 3M CC03 2017 2017-11-06 SALIN 3.1354942159 #> 1843 2068 3M CC03 2017 2017-11-06 TKN -0.2744368457 #> 1844 2068 3M CC03 2017 2017-11-06 TN -0.2691874898 + #> 1845 2068 3M CC03 2017 2017-11-06 TP -2.4418471603 #> 1846 2068 3M CC03 2017 2017-11-06 TURB 1.2237754316 #> 1847 2068 3M CC03 2018 2018-01-02 CHLAC 1.0647107370 #> 1848 2068 3M CC03 2018 2018-01-02 COLOR 3.0445224377 #> 1849 2068 3M CC03 2018 2018-01-02 NO23 -4.9618451299 I #> 1850 2068 3M CC03 2018 2018-01-02 SALIN 3.4563166809 #> 1851 2068 3M CC03 2018 2018-01-02 TKN -0.4780358009 #> 1852 2068 3M CC03 2018 2018-01-02 TN -0.4716049106 + #> 1853 2068 3M CC03 2018 2018-01-02 TP -2.4079456087 #> 1854 2068 3M CC03 2018 2018-01-02 TURB 1.1314021115 #> 1855 2068 3M CC03 2018 2018-02-05 CHLAC 0.9932517730 A #> 1856 2068 3M CC03 2018 2018-02-05 COLOR 3.2188758249 #> 1857 2068 3M CC03 2018 2018-02-05 DO 1.3609765531 #> 1858 2068 3M CC03 2018 2018-02-05 DOSAT 3.8979240810 + #> 1859 2068 3M CC03 2018 2018-02-05 NO23 -4.3428059215 #> 1860 2068 3M CC03 2018 2018-02-05 SALIN 3.0587070727 #> 1861 2068 3M CC03 2018 2018-02-05 TKN -0.4780358009 #> 1862 2068 3M CC03 2018 2018-02-05 TN -0.4572848568 + #> 1863 2068 3M CC03 2018 2018-02-05 TP -2.6310891600 #> 1864 2068 3M CC03 2018 2018-02-05 TURB 0.8754687374 #> 1865 2068 3M CC03 2018 2018-03-05 CHLAC 0.6418538862 #> 1866 2068 3M CC03 2018 2018-03-05 COLOR 2.5649493575 #> 1867 2068 3M CC03 2018 2018-03-05 DO 1.5686159179 #> 1868 2068 3M CC03 2018 2018-03-05 DOSAT 4.0517849478 + #> 1869 2068 3M CC03 2018 2018-03-05 NO23 -5.2983173665 I #> 1870 2068 3M CC03 2018 2018-03-05 SALIN 3.4781584228 #> 1871 2068 3M CC03 2018 2018-03-05 TKN -0.5798184953 #> 1872 2068 3M CC03 2018 2018-03-05 TN -0.5727010275 + #> 1873 2068 3M CC03 2018 2018-03-05 TP -2.7488721956 #> 1874 2068 3M CC03 2018 2018-03-05 TURB 2.2407096893 #> 1875 2068 3M CC03 2018 2018-04-02 CHLAC -0.5978370008 U #> 1876 2068 3M CC03 2018 2018-04-02 COLOR 0.9162907319 U #> 1877 2068 3M CC03 2018 2018-04-02 DO 1.2237754316 #> 1878 2068 3M CC03 2018 2018-04-02 DOSAT 3.8877303129 + #> 1879 2068 3M CC03 2018 2018-04-02 NO23 -3.7297014486 #> 1880 2068 3M CC03 2018 2018-04-02 SALIN 3.5553480615 #> 1881 2068 3M CC03 2018 2018-04-02 TKN 1.0296194172 #> 1882 2068 3M CC03 2018 2018-04-02 TN 1.0381543196 + #> 1883 2068 3M CC03 2018 2018-04-02 TP -1.7719568419 #> 1884 2068 3M CC03 2018 2018-04-02 TURB 1.3862943611 #> 1885 2068 3M CC03 2018 2018-05-07 CHLAC 0.4054651081 I #> 1886 2068 3M CC03 2018 2018-05-07 COLOR 2.6390573296 #> 1887 2068 3M CC03 2018 2018-05-07 DO -0.1984509387 #> 1888 2068 3M CC03 2018 2018-05-07 DOSAT 2.5416019935 #> 1889 2068 3M CC03 2018 2018-05-07 NO23 -5.5214609179 U #> 1890 2068 3M CC03 2018 2018-05-07 SALIN 3.6109179126 #> 1891 2068 3M CC03 2018 2018-05-07 TKN -0.6161861394 #> 1892 2068 3M CC03 2018 2018-05-07 TN -0.6124892775 + #> 1893 2068 3M CC03 2018 2018-05-07 TP -2.8824035882 #> 1894 2068 3M CC03 2018 2018-05-07 TURB 0.8754687374 #> 1895 2068 3M CC03 2018 2018-08-06 CHLAC 1.5475625087 #> 1896 2068 3M CC03 2018 2018-08-06 COLOR 3.8918202981 #> 1897 2068 3M CC03 2018 2018-08-06 DO -0.9162907319 #> 1898 2068 3M CC03 2018 2018-08-06 DOSAT 1.8245492921 #> 1899 2068 3M CC03 2018 2018-08-06 NO23 -5.5214609179 I #> 1900 2068 3M CC03 2018 2018-08-06 SALIN 3.3332753652 #> 1901 2068 3M CC03 2018 2018-08-06 TKN 0.2623642645 #> 1902 2068 3M CC03 2018 2018-08-06 TN 0.2654364635 + #> 1903 2068 3M CC03 2018 2018-08-06 TP -2.4191189092 #> 1904 2068 3M CC03 2018 2018-08-06 TURB 1.6486586256 #> 1905 2068 3M CC03 2019 2019-03-04 CHLAC 0.2623642645 I #> 1906 2068 3M CC03 2019 2019-03-04 COLOR 3.6635616461 #> 1907 2068 3M CC03 2019 2019-03-04 DO 1.0919233005 #> 1908 2068 3M CC03 2019 2019-03-04 DOSAT 3.6506582413 #> 1909 2068 3M CC03 2019 2019-03-04 NO23 -5.5214609179 U #> 1910 2068 3M CC03 2019 2019-03-04 SALIN 2.3105532626 #> 1911 2068 3M CC03 2019 2019-03-04 TKN -0.3147107448 #> 1912 2068 3M CC03 2019 2019-03-04 TN -0.3119747650 + #> 1913 2068 3M CC03 2019 2019-03-04 TP -2.3025850930 #> 1914 2068 3M CC03 2019 2019-03-04 TURB 0.8754687374 #> 1915 2068 3M CC03 2019 2019-05-06 CHLAC 1.3862943611 #> 1916 2068 3M CC03 2019 2019-05-06 COLOR 3.4965075615 #> 1917 2068 3M CC03 2019 2019-05-06 DO -1.8325814637 #> 1918 2068 3M CC03 2019 2019-05-06 DOSAT 0.9932517730 #> 1919 2068 3M CC03 2019 2019-05-06 NO23 -5.5214609179 U #> 1920 2068 3M CC03 2019 2019-05-06 SALIN 3.3809946743 #> 1921 2068 3M CC03 2019 2019-05-06 TKN -0.3566749439 #> 1922 2068 3M CC03 2019 2019-05-06 TN -0.3538218750 + #> 1923 2068 3M CC03 2019 2019-05-06 TP -3.0159349809 #> 1924 2068 3M CC03 2019 2019-05-06 TURB 0.6418538862 #> 1925 2068 3M CC03 2019 2019-06-03 CHLAC 1.0986122887 #> 1926 2068 3M CC03 2019 2019-06-03 COLOR 2.9957322736 #> 1927 2068 3M CC03 2019 2019-06-03 DO -0.8675005677 #> 1928 2068 3M CC03 2019 2019-06-03 DOSAT 1.8870696490 #> 1929 2068 3M CC03 2019 2019-06-03 NO23 -5.5214609179 U #> 1930 2068 3M CC03 2019 2019-06-03 SALIN 3.6068556186 #> 1931 2068 3M CC03 2019 2019-06-03 TKN -0.3424903089 #> 1932 2068 3M CC03 2019 2019-06-03 TN -0.3396773676 + #> 1933 2068 3M CC03 2019 2019-06-03 TP -3.0791138825 #> 1934 2068 3M CC03 2019 2019-06-03 TURB 0.9555114450 #> 1935 2068 3M CC03 2019 2019-07-01 CHLAC 1.9740810260 #> 1936 2068 3M CC03 2019 2019-07-01 COLOR 3.2958368660 A #> 1937 2068 3M CC03 2019 2019-07-01 DO -0.5978370008 #> 1938 2068 3M CC03 2019 2019-07-01 DOSAT 2.1517622033 #> 1939 2068 3M CC03 2019 2019-07-01 NO23 -5.5214609179 U #> 1940 2068 3M CC03 2019 2019-07-01 SALIN 3.5160130561 #> 1941 2068 3M CC03 2019 2019-07-01 TKN -0.2613647641 #> 1942 2068 3M CC03 2019 2019-07-01 TN -0.2587707290 + #> 1943 2068 3M CC03 2019 2019-07-01 TP -3.0159349809 #> 1944 2068 3M CC03 2019 2019-07-01 TURB 1.6486586256 A #> 1945 2068 3M CC03 2019 2019-10-07 TN -0.6462635947 + #> 1946 2068 3M CC03 2019 2019-10-07 CHLAC 1.0647107370 I #> 1947 2068 3M CC03 2019 2019-10-07 COLOR 1.9169226122 #> 1948 2068 3M CC03 2019 2019-10-07 DO 0.6931471806 #> 1949 2068 3M CC03 2019 2019-10-07 DOSAT 3.4436180975 #> 1950 2068 3M CC03 2019 2019-10-07 NO23 -5.1159958098 I #> 1951 2068 3M CC03 2019 2019-10-07 SALIN 3.5392186796 #> 1952 2068 3M CC03 2019 2019-10-07 TKN -0.6539264674 #> 1953 2068 3M CC03 2019 2019-10-07 TP -2.5902671654 #> 1954 2068 3M CC03 2019 2019-10-07 TURB 0.7884573604 #> 1955 2068 3M CC03 2019 2019-11-04 CHLAC 1.7227665977 #> 1956 2068 3M CC03 2019 2019-11-04 COLOR 2.8903717579 #> 1957 2068 3M CC03 2019 2019-11-04 DO 0.3646431136 #> 1958 2068 3M CC03 2019 2019-11-04 DOSAT 3.0349529867 #> 1959 2068 3M CC03 2019 2019-11-04 NO23 -4.3428059215 #> 1960 2068 3M CC03 2019 2019-11-04 SALIN 3.6030491975 #> 1961 2068 3M CC03 2019 2019-11-04 TKN -0.3566749439 #> 1962 2068 3M CC03 2019 2019-11-04 TN -0.3382738586 + #> 1963 2068 3M CC03 2019 2019-11-04 TP -2.7488721956 #> 1964 2068 3M CC03 2019 2019-11-04 TURB 1.1631508098 #> 1965 2068 3M CC03 2019 2019-12-02 CHLAC 0.8754687374 I #> 1966 2068 3M CC03 2019 2019-12-02 COLOR 2.1860512767 #> 1967 2068 3M CC03 2019 2019-12-02 DO 1.0367368850 #> 1968 2068 3M CC03 2019 2019-12-02 DOSAT 3.6988297850 #> 1969 2068 3M CC03 2019 2019-12-02 NO23 -4.1997050779 #> 1970 2068 3M CC03 2019 2019-12-02 SALIN 3.4977189487 #> 1971 2068 3M CC03 2019 2019-12-02 TKN -0.4620354596 #> 1972 2068 3M CC03 2019 2019-12-02 TN -0.4385049622 + #> 1973 2068 3M CC03 2019 2019-12-02 TP -2.9187712324 #> 1974 2068 3M CC03 2019 2019-12-02 TURB 0.6418538862 #> 1975 2068 3M CC03 2020 2020-01-06 CHLAC 1.2237754316 #> 1976 2068 3M CC03 2020 2020-01-06 COLOR 3.5263605246 A #> 1977 2068 3M CC03 2020 2020-01-06 DO 1.1184149160 #> 1978 2068 3M CC03 2020 2020-01-06 DOSAT 3.5862928653 #> 1979 2068 3M CC03 2020 2020-01-06 NO23 -4.1997050779 #> 1980 2068 3M CC03 2020 2020-01-06 SALIN 2.7491921444 #> 1981 2068 3M CC03 2020 2020-01-06 TKN 0.0953101798 #> 1982 2068 3M CC03 2020 2020-01-06 TN 0.1088544049 + #> 1983 2068 3M CC03 2020 2020-01-06 TP -2.5510464523 #> 1984 2068 3M CC03 2020 2020-01-06 TURB 1.4350845253 #> 1985 2068 3M CC03 2020 2020-02-03 CHLAC 0.5877866649 I #> 1986 2068 3M CC03 2020 2020-02-03 COLOR 3.3672958300 #> 1987 2068 3M CC03 2020 2020-02-03 DO 1.4011829736 #> 1988 2068 3M CC03 2020 2020-02-03 DOSAT 3.7909846771 #> 1989 2068 3M CC03 2020 2020-02-03 NO23 -4.9618451299 I #> 1990 2068 3M CC03 2020 2020-02-03 SALIN 3.0819099698 #> 1991 2068 3M CC03 2020 2020-02-03 TKN -0.2107210313 #> 1992 2068 3M CC03 2020 2020-02-03 TN -0.2057949130 + #> 1993 2068 3M CC03 2020 2020-02-03 TP -2.7968814148 #> 1994 2068 3M CC03 2020 2020-02-03 TURB 0.5877866649 #> 1995 2068 3M CC03 2020 2020-03-02 CHLAC 0.6931471806 I #> 1996 2068 3M CC03 2020 2020-03-02 COLOR 2.6390573296 #> 1997 2068 3M CC03 2020 2020-03-02 DO 1.4951487660 #> 1998 2068 3M CC03 2020 2020-03-02 DOSAT 4.0360089852 #> 1999 2068 3M CC03 2020 2020-03-02 NO23 -5.2983173665 I #> 2000 2068 3M CC03 2020 2020-03-02 SALIN 3.4600950229 #> 2001 2068 3M CC03 2020 2020-03-02 TKN -0.5108256238 #> 2002 2068 3M CC03 2020 2020-03-02 TN -0.5041810810 + #> 2003 2068 3M CC03 2020 2020-03-02 TP -2.6450754019 #> 2004 2068 3M CC03 2020 2020-03-02 TURB 1.5040773968 #> 2005 2068 3M CC03 2020 2020-09-08 CHLAC 2.7725887222 #> 2006 2068 3M CC03 2020 2020-09-08 COLOR 4.8675344505 #> 2007 2068 3M CC03 2020 2020-09-08 DO 0.4510756194 #> 2008 2068 3M CC03 2020 2020-09-08 DOSAT 3.0155349009 #> 2009 2068 3M CC03 2020 2020-09-08 NO23 -5.5214609179 U #> 2010 2068 3M CC03 2020 2020-09-08 SALIN 1.5151272330 #> 2011 2068 3M CC03 2020 2020-09-08 TKN 0.0953101798 #> 2012 2068 3M CC03 2020 2020-09-08 TN 0.0971267107 + #> 2013 2068 3M CC03 2020 2020-09-08 TP -2.2072749132 #> 2014 2068 3M CC03 2020 2020-09-08 TURB 1.3862943611 #> 2015 2068 3M CC03 2020 2020-10-05 CHLAC 2.0918640617 #> 2016 2068 3M CC03 2020 2020-10-05 COLOR 4.2046926194 #> 2017 2068 3M CC03 2020 2020-10-05 DO 0.4121096508 #> 2018 2068 3M CC03 2020 2020-10-05 DOSAT 3.0587070727 #> 2019 2068 3M CC03 2020 2020-10-05 NO23 -4.7105307016 I #> 2020 2068 3M CC03 2020 2020-10-05 SALIN 3.2027464429 #> 2021 2068 3M CC03 2020 2020-10-05 TKN -0.3147107448 #> 2022 2068 3M CC03 2020 2020-10-05 TN -0.3092462504 + #> 2023 2068 3M CC03 2020 2020-10-05 TP -2.5133061243 #> 2024 2068 3M CC03 2020 2020-10-05 TURB 1.3350010667 #> 2025 2068 3M CC03 2020 2020-11-02 CHLAC 1.4816045409 #> 2026 2068 3M CC03 2020 2020-11-02 COLOR 3.6888794541 #> 2027 2068 3M CC03 2020 2020-11-02 DO 0.6523251860 #> 2028 2068 3M CC03 2020 2020-11-02 DOSAT 3.3428618046 #> 2029 2068 3M CC03 2020 2020-11-02 NO23 -4.7105307016 I #> 2030 2068 3M CC03 2020 2020-11-02 SALIN 3.3721118008 #> 2031 2068 3M CC03 2020 2020-11-02 TKN -0.1984509387 #> 2032 2068 3M CC03 2020 2020-11-02 TN -0.1935847491 + #> 2033 2068 3M CC03 2020 2020-11-02 TP -2.6882475738 #> 2034 2068 3M CC03 2020 2020-11-02 TURB 1.1939224685 #> 2035 2068 3M CC03 2020 2020-12-07 CHLAC 0.4054651081 I #> 2036 2068 3M CC03 2020 2020-12-07 COLOR 3.2958368660 A #> 2037 2068 3M CC03 2020 2020-12-07 DO 1.3480731483 #> 2038 2068 3M CC03 2020 2020-12-07 DOSAT 3.9278963546 #> 2039 2068 3M CC03 2020 2020-12-07 NO23 -3.6119184130 #> 2040 2068 3M CC03 2020 2020-12-07 SALIN 3.3641875560 #> 2041 2068 3M CC03 2020 2020-12-07 TKN -0.5276327421 #> 2042 2068 3M CC03 2020 2020-12-07 TN -0.4828862551 + #> 2043 2068 3M CC03 2020 2020-12-07 TP -2.6036901858 #> 2044 2068 3M CC03 2020 2020-12-07 TURB 0.7419373447 #> 2045 2068 3M CC03 2021 2021-01-04 CHLAC 1.3609765531 #> 2046 2068 3M CC03 2021 2021-01-04 COLOR 3.1780538303 A #> 2047 2068 3M CC03 2021 2021-01-04 DO 0.7701082217 #> 2048 2068 3M CC03 2021 2021-01-04 DOSAT 3.3393219779 #> 2049 2068 3M CC03 2021 2021-01-04 NO23 -4.3428059215 #> 2050 2068 3M CC03 2021 2021-01-04 SALIN 3.2638491905 #> 2051 2068 3M CC03 2021 2021-01-04 TKN -0.4780358009 #> 2052 2068 3M CC03 2021 2021-01-04 TN -0.4572848568 + #> 2053 2068 3M CC03 2021 2021-01-04 TP -2.3025850930 #> 2054 2068 3M CC03 2021 2021-01-04 TURB 0.8329091229 #> 2055 2068 3M CC03 2021 2021-02-01 CHLAC 0.3364722366 I #> 2056 2068 3M CC03 2021 2021-02-01 COLOR 1.9878743482 #> 2057 2068 3M CC03 2021 2021-02-01 DO 1.3454723666 #> 2058 2068 3M CC03 2021 2021-02-01 DOSAT 3.9156165409 #> 2059 2068 3M CC03 2021 2021-02-01 NO23 -4.4228486292 #> 2060 2068 3M CC03 2021 2021-02-01 SALIN 3.4937765630 #> 2061 2068 3M CC03 2021 2021-02-01 TKN -0.7133498879 #> 2062 2068 3M CC03 2021 2021-02-01 TN -0.6891551593 + #> 2063 2068 3M CC03 2021 2021-02-01 TP -2.7646205526 #> 2064 2068 3M CC03 2021 2021-02-01 TURB 1.0647107370 #> 2065 2068 3M CC03 2021 2021-04-05 CHLAC 0.5877866649 I #> 2066 2068 3M CC03 2021 2021-04-05 COLOR 2.5649493575 #> 2067 2068 3M CC03 2021 2021-04-05 DO 0.9932517730 #> 2068 2068 3M CC03 2021 2021-04-05 DOSAT 3.6323091026 #> 2069 2068 3M CC03 2021 2021-04-05 NO23 -5.5214609179 U #> 2070 2068 3M CC03 2021 2021-04-05 SALIN 3.5984075509 #> 2071 2068 3M CC03 2021 2021-04-05 TKN -0.6348782724 #> 2072 2068 3M CC03 2021 2021-04-05 TN -0.6311117896 + #> 2073 2068 3M CC03 2021 2021-04-05 TP -2.9374633654 #> 2074 2068 3M CC03 2021 2021-04-05 TURB 0.9162907319 #> 2075 2068 3M CC03 2021 2021-05-03 CHLAC 0.4054651081 I #> 2076 2068 3M CC03 2021 2021-05-03 COLOR 3.0910424534 A #> 2077 2068 3M CC03 2021 2021-05-03 DO -0.4307829161 #> 2078 2068 3M CC03 2021 2021-05-03 DOSAT 2.3125354238 #> 2079 2068 3M CC03 2021 2021-05-03 NO23 -5.5214609179 U #> 2080 2068 3M CC03 2021 2021-05-03 SALIN 3.5931942040 #> 2081 2068 3M CC03 2021 2021-05-03 TKN -0.6348782724 #> 2082 2068 3M CC03 2021 2021-05-03 TN -0.6311117896 + #> 2083 2068 3M CC03 2021 2021-05-03 TP -3.1010927892 #> 2084 2068 3M CC03 2021 2021-05-03 TURB 1.6094379124 A #> 2085 2068 3M CC03 2021 2021-06-07 CHLAC 0.8754687374 I #> 2086 2068 3M CC03 2021 2021-06-07 COLOR 2.9444389792 #> 2087 2068 3M CC03 2021 2021-06-07 DO -0.4462871026 #> 2088 2068 3M CC03 2021 2021-06-07 DOSAT 2.3418058061 #> 2089 2068 3M CC03 2021 2021-06-07 NO23 -5.5214609179 U #> 2090 2068 3M 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2068 3M CC03 2022 2022-02-07 TN -0.8818893052 + #> 2163 2068 3M CC03 2022 2022-02-07 TP -2.6736487744 #> 2164 2068 3M CC03 2022 2022-02-07 TURB 0.4054651081 #> 2165 2068 3M CC03 2022 2022-03-07 CHLAC 0.7419373447 I #> 2166 2068 3M CC03 2022 2022-03-07 COLOR 2.3025850930 A #> 2167 2068 3M CC03 2022 2022-03-07 DO 0.5306282511 #> 2168 2068 3M CC03 2022 2022-03-07 DOSAT 3.1863526332 #> 2169 2068 3M CC03 2022 2022-03-07 NO23 -5.1159958098 I #> 2170 2068 3M CC03 2022 2022-03-07 SALIN 3.5331024525 #> 2171 2068 3M CC03 2022 2022-03-07 TKN -0.4307829161 #> 2172 2068 3M CC03 2022 2022-03-07 TN -0.4246479275 + #> 2173 2068 3M CC03 2022 2022-03-07 TP -2.8647040111 #> 2174 2068 3M CC03 2022 2022-03-07 TURB 0.9555114450 #> 2175 2068 3M CC03 2022 2022-04-04 CHLAC 0.0000000000 I #> 2176 2068 3M CC03 2022 2022-04-04 COLOR 2.5649493575 #> 2177 2068 3M CC03 2022 2022-04-04 DO -0.2107210313 #> 2178 2068 3M CC03 2022 2022-04-04 DOSAT 2.5416019935 #> 2179 2068 3M CC03 2022 2022-04-04 NO23 -5.1159958098 I #> 2180 2068 3M CC03 2022 2022-04-04 TKN -0.6161861394 #> 2181 2068 3M CC03 2022 2022-04-04 TN -0.6088060321 + #> 2182 2068 3M CC03 2022 2022-04-04 TP -2.9957322736 #> 2183 2068 3M CC03 2022 2022-04-04 TURB 1.0986122887 #> 2184 2068 3M CC03 2022 2022-05-02 CHLAC 0.3364722366 U #> 2185 2068 3M CC03 2022 2022-05-02 DO -0.5108256238 #> 2186 2068 3M CC03 2022 2022-05-02 DOSAT 2.2082744135 #> 2187 2068 3M CC03 2022 2022-05-02 NO23 -5.5214609179 U #> 2188 2068 3M CC03 2022 2022-05-02 SALIN 3.5366020187 #> 2189 2068 3M CC03 2022 2022-05-02 TN -0.5762534291 + #> 2190 2068 3M CC03 2022 2022-06-06 CHLAC 1.7047480922 #> 2191 2068 3M CC03 2022 2022-06-06 COLOR 4.0430512678 #> 2192 2068 3M CC03 2022 2022-06-06 DO -0.4462871026 #> 2193 2068 3M CC03 2022 2022-06-06 DOSAT 2.1972245773 #> 2194 2068 3M CC03 2022 2022-06-06 NO23 -4.6051701860 I #> 2195 2068 3M CC03 2022 2022-06-06 SALIN 2.9210087274 #> 2196 2068 3M CC03 2022 2022-06-06 TKN 0.1823215568 #> 2197 2068 3M CC03 2022 2022-06-06 TN 0.1856493469 + #> 2198 2068 3M CC03 2022 2022-06-06 TP -2.9374633654 #> 2199 2068 3M CC03 2022 2022-06-06 TURB 1.3609765531 #> 2200 2068 3M CC03 2022 2022-07-05 CHLAC 2.0541237337 #> 2201 2068 3M CC03 2022 2022-07-05 COLOR 3.8501476017 A #> 2202 2068 3M CC03 2022 2022-07-05 DO -0.5447271754 #> 2203 2068 3M CC03 2022 2022-07-05 DOSAT 2.1860512767 #> 2204 2068 3M CC03 2022 2022-07-05 NO23 -3.9120230054 #> 2205 2068 3M CC03 2022 2022-07-05 SALIN 3.2327787300 #> 2206 2068 3M CC03 2022 2022-07-05 TKN 0.0953101798 #> 2207 2068 3M CC03 2022 2022-07-05 TN 0.1133286853 + #> 2208 2068 3M CC03 2022 2022-07-05 TP -2.6036901858 #> 2209 2068 3M CC03 2022 2022-07-05 TURB 2.0149030205 #> 2210 2068 3M CC03 2022 2022-08-01 CHLAC 1.8082887712 #> 2211 2068 3M CC03 2022 2022-08-01 COLOR 3.5553480615 A #> 2212 2068 3M CC03 2022 2022-08-01 DO -0.8209805521 #> 2213 2068 3M CC03 2022 2022-08-01 DOSAT 1.9315214116 #> 2214 2068 3M CC03 2022 2022-08-01 NO23 -5.2983173665 I #> 2215 2068 3M CC03 2022 2022-08-01 SALIN 3.3904734183 #> 2216 2068 3M CC03 2022 2022-08-01 TKN -0.3011050928 #> 2217 2068 3M CC03 2022 2022-08-01 TN -0.2957142441 + #> 2218 2068 3M CC03 2022 2022-08-01 TP -2.9004220937 #> 2219 2068 3M CC03 2022 2022-08-01 TURB 1.0296194172 #> 2220 2068 3M CC03 2022 2022-11-07 CHLAC 2.7725887222 #> 2221 2068 3M CC03 2022 2022-11-07 COLOR 3.9889840466 A #> 2222 2068 3M CC03 2022 2022-11-07 DO -0.4462871026 #> 2223 2068 3M CC03 2022 2022-11-07 DOSAT 2.2192034841 #> 2224 2068 3M CC03 2022 2022-11-07 NO23 -5.5214609179 I #> 2225 2068 3M CC03 2022 2022-11-07 SALIN 3.1945831323 #> 2226 2068 3M CC03 2022 2022-11-07 TKN 0.0000000000 #> 2227 2068 3M CC03 2022 2022-11-07 TN 0.0039920213 + #> 2228 2068 3M CC03 2022 2022-11-07 TP -1.5606477483 #> 2229 2068 3M CC03 2022 2022-11-07 TURB 2.7725887222 #> 2230 2068 3M CC03 2022 2022-12-05 CHLAC 2.7725887222 #> 2231 2068 3M CC03 2022 2022-12-05 COLOR 4.0430512678 #> 2232 2068 3M CC03 2022 2022-12-05 DO 0.5766133643 #> 2233 2068 3M CC03 2022 2022-12-05 DOSAT 3.1863526332 #> 2234 2068 3M CC03 2022 2022-12-05 NO23 -5.5214609179 U #> 2235 2068 3M CC03 2022 2022-12-05 SALIN 3.0223742045 #> 2236 2068 3M CC03 2022 2022-12-05 TKN -0.1625189295 #> 2237 2068 3M CC03 2022 2022-12-05 TN -0.1601687522 + #> 2238 2068 3M CC03 2022 2022-12-05 TP -1.1394342832 #> 2239 2068 3M CC03 2022 2022-12-05 TURB 1.5040773968 #> 2240 2068 3M CC03 2023 2023-01-03 CHLAC 1.6486586256 #> 2241 2068 3M CC03 2023 2023-01-03 COLOR 4.0604430105 #> 2242 2068 3M CC03 2023 2023-01-03 DO 0.7080357931 #> 2243 2068 3M CC03 2023 2023-01-03 DOSAT 3.2884018875 #> 2244 2068 3M CC03 2023 2023-01-03 NO23 -4.2686979494 #> 2245 2068 3M CC03 2023 2023-01-03 TKN -0.0512932944 #> 2246 2068 3M CC03 2023 2023-01-03 TN -0.0366639844 + #> 2247 2068 3M CC03 2023 2023-01-03 TP -0.7133498879 #> 2248 2068 3M CC03 2023 2023-01-03 TURB 0.3364722366 #> 2249 2068 3M CC03 2023 2023-02-06 CHLAC 1.6292405397 #> 2250 2068 3M CC03 2023 2023-02-06 COLOR 2.7080502011 A #> 2251 2068 3M CC03 2023 2023-02-06 DO 1.2781522025 #> 2252 2068 3M CC03 2023 2023-02-06 DOSAT 3.8958936235 #> 2253 2068 3M CC03 2023 2023-02-06 NO23 -4.6051701860 I #> 2254 2068 3M CC03 2023 2023-02-06 SALIN 3.4404180948 #> 2255 2068 3M CC03 2023 2023-02-06 TKN -0.3566749439 #> 2256 2068 3M CC03 2023 2023-02-06 TN -0.3509769228 + #> 2257 2068 3M CC03 2023 2023-02-06 TP -2.2072749132 #> 2258 2068 3M CC03 2023 2023-02-06 TURB 1.1314021115 #> 2259 2068 3M CC03 2023 2023-03-06 DO 0.1570037488 #> 2260 2068 3M CC03 2023 2023-03-06 DOSAT 2.8791984573 #> 2261 2068 3M CC03 2023 2023-03-06 SALIN 3.5962157693 #> 2262 2068 3M CC03 2018 2018-03-13 CHLAC 0.9555114450 #> 2263 2068 3M CC03 2018 2018-03-13 COND 10.8817948782 #> 2264 2068 3M CC03 2018 2018-03-13 DO 2.0794415417 #> 2265 2068 3M CC03 2018 2018-03-13 DOSAT 4.6812048723 #> 2266 2068 3M CC03 2018 2018-03-13 NO23 -4.7105307016 I #> 2267 2068 3M CC03 2018 2018-03-13 SALIN 3.6778185068 + #> 2268 2068 3M CC03 2018 2018-03-13 TKN -0.4942963218 #> 2269 2068 3M CC03 2018 2018-03-13 TN -0.4877603508 + #> 2270 2068 3M CC03 2018 2018-03-13 TP -2.4191189092 #> 2271 2068 3M CC03 2018 2018-03-13 TSS 1.3862943611 I #> 2272 2068 3M CC03 2018 2018-03-13 TURB 1.0647107370 #> 2273 2068 3M CC03 2018 2018-05-08 CHLAC 1.1631508098 #> 2274 2068 3M CC03 2018 2018-05-08 COND 10.9254527508 #> 2275 2068 3M CC03 2018 2018-05-08 DO 1.4973884086 #> 2276 2068 3M CC03 2018 2018-05-08 DOSAT 4.2091602367 #> 2277 2068 3M CC03 2018 2018-05-08 NO23 -5.5214609179 U #> 2278 2068 3M CC03 2018 2018-05-08 SALIN 3.5973122606 + #> 2279 2068 3M CC03 2018 2018-05-08 TKN -0.5108256238 #> 2280 2068 3M CC03 2018 2018-05-08 TN -0.5074978337 + #> 2281 2068 3M CC03 2018 2018-05-08 TP -3.2441936329 #> 2282 2068 3M CC03 2018 2018-05-08 TSS 2.0794415417 I #> 2283 2068 3M CC03 2018 2018-05-08 TURB 1.3083328197 #> 2284 2068 3M CC03 2018 2018-06-26 CHLAC 2.4849066498 #> 2285 2068 3M CC03 2018 2018-06-26 COND 10.7823463704 #> 2286 2068 3M CC03 2018 2018-06-26 DO 1.1118575154 #> 2287 2068 3M CC03 2018 2018-06-26 DOSAT 3.8628327612 #> 2288 2068 3M CC03 2018 2018-06-26 NO23 -5.5214609179 U #> 2289 2068 3M CC03 2018 2018-06-26 SALIN 3.3414473773 + #> 2290 2068 3M CC03 2018 2018-06-26 TKN -0.4155154440 #> 2291 2068 3M CC03 2018 2018-06-26 TN -0.4124897230 + #> 2292 2068 3M CC03 2018 2018-06-26 TSS 2.0794415417 I #> 2293 2068 3M CC03 2018 2018-06-26 TURB 1.4816045409 #> 2294 2068 3M CC03 2018 2018-09-18 CHLAC 2.2617630985 #> 2295 2068 3M CC03 2018 2018-09-18 COND 9.9966590834 #> 2296 2068 3M CC03 2018 2018-09-18 DO 0.8020015855 #> 2297 2068 3M CC03 2018 2018-09-18 DOSAT 3.4812400893 #> 2298 2068 3M CC03 2018 2018-09-18 NO23 -4.7105307016 I #> 2299 2068 3M CC03 2018 2018-09-18 TKN -0.0833816089 #> 2300 2068 3M CC03 2018 2018-09-18 TN -0.0790432073 + #> 2301 2068 3M CC03 2018 2018-09-18 TP -2.3227878003 #> 2302 2068 3M CC03 2018 2018-09-18 TSS 1.0986122887 U #> 2303 2068 3M CC03 2018 2018-09-18 TURB 1.2809338455 A #> 2304 2068 3M CC03 2018 2018-12-04 CHLAC 1.6486586256 #> 2305 2068 3M CC03 2018 2018-12-04 COND 10.7489265434 #> 2306 2068 3M CC03 2018 2018-12-04 DO 1.5644405465 #> 2307 2068 3M CC03 2018 2018-12-04 DOSAT 4.2239097666 #> 2308 2068 3M CC03 2018 2018-12-04 NO23 -1.8971199849 G #> 2309 2068 3M CC03 2018 2018-12-04 SALIN 3.4094961845 #> 2310 2068 3M CC03 2018 2018-12-04 TKN -0.3285040670 #> 2311 2068 3M CC03 2018 2018-12-04 TN -0.1392620673 + #> 2312 2068 3M CC03 2018 2018-12-04 TP -2.6450754019 #> 2313 2068 3M CC03 2018 2018-12-04 TSS 2.1972245773 I #> 2314 2068 3M CC03 2018 2018-12-04 TURB 0.5306282511 #> 2315 2078A 2 CC04 2019 2019-08-13 CHLAC 3.1780538303 #> 2316 2078A 2 CC04 2019 2019-08-13 COND 9.8642788393 #> 2317 2078A 2 CC04 2019 2019-08-13 DO 1.7647307968 #> 2318 2078A 2 CC04 2019 2019-08-13 DOSAT 4.4176350621 #> 2319 2078A 2 CC04 2019 2019-08-13 NO23 -5.2983173665 I #> 2320 2078A 2 CC04 2019 2019-08-13 SALIN 2.4274540750 #> 2321 2078A 2 CC04 2019 2019-08-13 TKN 0.3364722366 #> 2322 2078A 2 CC04 2019 2019-08-13 TN 0.3393253056 + #> 2323 2078A 2 CC04 2019 2019-08-13 TP -2.9759296463 #> 2324 2078A 2 CC04 2019 2019-08-13 TSS 1.6094379124 I #> 2325 2078A 2 CC04 2019 2019-08-13 TURB 0.7419373447 #> 2326 2078B 2 CC05 2019 2019-01-17 COND 10.7433722892 #> 2327 2078B 2 CC05 2019 2019-01-17 DO 1.9065751437 #> 2328 2078B 2 CC05 2019 2019-01-17 DOSAT 4.4030540019 #> 2329 2078B 2 CC05 2019 2019-01-17 SALIN 3.4045251718 #> 2330 2078B 2 CC05 2019 2019-01-17 TN -0.3827256211 + #> 2331 2078B 2 CC05 2019 2019-01-24 CHLAC 0.2623642645 I #> 2332 2078B 2 CC05 2019 2019-01-24 COND 10.7763069502 #> 2333 2078B 2 CC05 2019 2019-01-24 DO 1.8702625307 #> 2334 2078B 2 CC05 2019 2019-01-24 DOSAT 4.4531838290 #> 2335 2078B 2 CC05 2019 2019-01-24 NO23 -5.1159958098 I #> 2336 2078B 2 CC05 2019 2019-01-24 SALIN 3.4413791713 #> 2337 2078B 2 CC05 2019 2019-01-24 TKN -0.7985076962 #> 2338 2078B 2 CC05 2019 2019-01-24 TN -0.7896580809 + #> 2339 2078B 2 CC05 2019 2019-01-24 TP -3.5065578973 #> 2340 2078B 2 CC05 2019 2019-01-24 TSS 1.0986122887 I #> 2341 2078B 2 CC05 2019 2019-01-24 TURB 0.2623642645 #> 2342 2078B 2 CC05 2019 2019-03-12 CHLAC 1.2809338455 #> 2343 2078B 2 CC05 2019 2019-03-12 COND 10.4768935315 #> 2344 2078B 2 CC05 2019 2019-03-12 DO 1.6992786164 #> 2345 2078B 2 CC05 2019 2019-03-12 DOSAT 4.3412046402 #> 2346 2078B 2 CC05 2019 2019-03-12 NO23 -5.5214609179 U #> 2347 2078B 2 CC05 2019 2019-03-12 SALIN 3.1059310659 #> 2348 2078B 2 CC05 2019 2019-03-12 TKN -0.3424903089 #> 2349 2078B 2 CC05 2019 2019-03-12 TN -0.3396773676 + #> 2350 2078B 2 CC05 2019 2019-03-12 TP -3.2441936329 #> 2351 2078B 2 CC05 2019 2019-03-12 TSS 2.1972245773 I #> 2352 2078B 2 CC05 2019 2019-03-12 TURB 0.6931471806 #> 2353 2078B 2 CC05 2019 2019-04-16 CHLAC 1.4816045409 #> 2354 2078B 2 CC05 2019 2019-04-16 COND 10.7360705353 #> 2355 2078B 2 CC05 2019 2019-04-16 DO 1.6505798558 #> 2356 2078B 2 CC05 2019 2019-04-16 DOSAT 4.3094559418 #> 2357 2078B 2 CC05 2019 2019-04-16 NO23 -5.5214609179 U #> 2358 2078B 2 CC05 2019 2019-04-16 SALIN 3.3951793093 #> 2359 2078B 2 CC05 2019 2019-04-16 TKN -0.2484613593 #> 2360 2078B 2 CC05 2019 2019-04-16 TN -0.2459005384 + #> 2361 2078B 2 CC05 2019 2019-04-16 TP -3.7722610631 #> 2362 2078B 2 CC05 2019 2019-04-16 TSS 1.6094379124 I #> 2363 2078B 2 CC05 2019 2019-04-16 TURB 0.6418538862 #> 2364 2078B 2 CC05 2019 2019-06-11 CHLAC 1.1314021115 #> 2365 2078B 2 CC05 2019 2019-06-11 COND 10.8909447918 #> 2366 2078B 2 CC05 2019 2019-06-11 DO 1.2059708070 #> 2367 2078B 2 CC05 2019 2019-06-11 DOSAT 4.0127729085 #> 2368 2078B 2 CC05 2019 2019-06-11 NO23 -5.5214609179 I #> 2369 2078B 2 CC05 2019 2019-06-11 SALIN 3.5635996377 #> 2370 2078B 2 CC05 2019 2019-06-11 TKN -0.3285040670 #> 2371 2078B 2 CC05 2019 2019-06-11 TN -0.3229638866 + #> 2372 2078B 2 CC05 2019 2019-06-11 TP -3.3242363405 #> 2373 2078B 2 CC05 2019 2019-06-11 TSS 1.0986122887 U #> 2374 2078B 2 CC05 2019 2019-06-11 TURB 0.3364722366 #> 2375 2078B 2 CC05 2019 2019-08-13 CHLAC 2.8332133441 #> 2376 2078B 2 CC05 2019 2019-08-13 COND 10.2219412837 #> 2377 2078B 2 CC05 2019 2019-08-13 DO 1.4036429995 #> 2378 2078B 2 CC05 2019 2019-08-13 DOSAT 4.0926765051 #> 2379 2078B 2 CC05 2019 2019-08-13 NO23 -4.6051701860 I #> 2380 2078B 2 CC05 2019 2019-08-13 SALIN 2.8195915758 #> 2381 2078B 2 CC05 2019 2019-08-13 TKN 0.6418538862 #> 2382 2078B 2 CC05 2019 2019-08-13 TN 0.6439569364 + #> 2383 2078B 2 CC05 2019 2019-08-13 TP -2.9759296463 #> 2384 2078B 2 CC05 2019 2019-08-13 TSS 1.7917594692 I #> 2385 2078B 2 CC05 2019 2019-08-13 TURB 0.7884573604 #> 2386 2078B 2 CC05 2019 2019-08-13 COND 10.3244650523 #> 2387 2078B 2 CC05 2019 2019-08-13 DO 1.0543120298 #> 2388 2078B 2 CC05 2019 2019-08-13 DOSAT 3.7541989202 #> 2389 2078B 2 CC05 2019 2019-08-13 SALIN 2.9322598506 #> 2390 2078B 2 CC05 2019 2019-10-01 COND 10.7304660807 #> 2391 2078B 2 CC05 2019 2019-10-01 DO 1.5644405465 #> 2392 2078B 2 CC05 2019 2019-10-01 DOSAT 4.2724907476 #> 2393 2078B 2 CC05 2019 2019-10-01 SALIN 3.3864220961 #> 2394 2078B 2 CC05 2019 2019-11-04 COND 10.7792062586 #> 2395 2078B 2 CC05 2019 2019-11-04 DO 1.5151272330 #> 2396 2078B 2 CC05 2019 2019-11-04 DOSAT 4.2061840440 #> 2397 2078B 2 CC05 2019 2019-11-04 SALIN 3.4423393250 #> 2398 2078B 2 CC05 2019 2019-11-19 CHLAC 2.6390573296 #> 2399 2078B 2 CC05 2019 2019-11-19 COND 10.8493565039 #> 2400 2078B 2 CC05 2019 2019-11-19 DO 2.0135687975 #> 2401 2078B 2 CC05 2019 2019-11-19 DOSAT 4.6298627986 #> 2402 2078B 2 CC05 2019 2019-11-19 NO23 -5.5214609179 U #> 2403 2078B 2 CC05 2019 2019-11-19 SALIN 3.5234150144 #> 2404 2078B 2 CC05 2019 2019-11-19 TKN -0.3011050928 #> 2405 2078B 2 CC05 2019 2019-11-19 TN -0.2984060358 + #> 2406 2078B 2 CC05 2019 2019-11-19 TP -2.8302178351 #> 2407 2078B 2 CC05 2019 2019-11-19 TSS 2.0794415417 I #> 2408 2078B 2 CC05 2019 2019-11-19 TURB 1.0296194172 A #> 2409 2078B 2 CC05 2020 2020-02-13 CHLAC 2.1400661635 A #> 2410 2078B 2 CC05 2020 2020-02-13 COND 10.7287588860 #> 2411 2078B 2 CC05 2020 2020-02-13 DO 1.8961194846 #> 2412 2078B 2 CC05 2020 2020-02-13 DOSAT 4.5747109785 #> 2413 2078B 2 CC05 2020 2020-02-13 NO23 -5.5214609179 U #> 2414 2078B 2 CC05 2020 2020-02-13 SALIN 3.3857452771 #> 2415 2078B 2 CC05 2020 2020-02-13 TKN -0.3424903089 #> 2416 2078B 2 CC05 2020 2020-02-13 TN -0.3396773676 + #> 2417 2078B 2 CC05 2020 2020-02-13 TP -3.3242363405 #> 2418 2078B 2 CC05 2020 2020-02-13 TSS 2.2617630985 I #> 2419 2078B 2 CC05 2020 2020-02-13 TURB 1.0296194172 #> 2420 2078B 2 CC05 2020 2020-03-24 CHLAC 2.2617630985 #> 2421 2078B 2 CC05 2020 2020-03-24 COND 10.9026109427 #> 2422 2078B 2 CC05 2020 2020-03-24 DO 1.8357763546 #> 2423 2078B 2 CC05 2020 2020-03-24 DOSAT 4.5900565482 #> 2424 2078B 2 CC05 2020 2020-03-24 NO23 -5.5214609179 U #> 2425 2078B 2 CC05 2020 2020-03-24 SALIN 3.5787855313 #> 2426 2078B 2 CC05 2020 2020-03-24 TKN -0.6161861394 #> 2427 2078B 2 CC05 2020 2020-03-24 TN -0.6124892775 + #> 2428 2078B 2 CC05 2020 2020-03-24 TP -2.5902671654 #> 2429 2078B 2 CC05 2020 2020-03-24 TSS 2.4849066498 A #> 2430 2078B 2 CC05 2020 2020-03-24 TURB 1.0647107370 #> 2431 2078B 2 CC05 2020 2020-06-15 CHLAC 2.8332133441 #> 2432 2078B 2 CC05 2020 2020-06-15 COND 10.3780433051 #> 2433 2078B 2 CC05 2020 2020-06-15 DO 1.2325602612 #> 2434 2078B 2 CC05 2020 2020-06-15 DOSAT 3.9199911751 #> 2435 2078B 2 CC05 2020 2020-06-15 NO23 -5.5214609179 I #> 2436 2078B 2 CC05 2020 2020-06-15 SALIN 2.9907197317 #> 2437 2078B 2 CC05 2020 2020-06-15 TKN 0.1823215568 #> 2438 2078B 2 CC05 2020 2020-06-15 TN 0.1856493469 + #> 2439 2078B 2 CC05 2020 2020-06-15 TP -3.0159349809 #> 2440 2078B 2 CC05 2020 2020-06-15 TSS 1.6094379124 I #> 2441 2078B 2 CC05 2020 2020-06-15 TURB 0.9932517730 #> 2442 2078B 2 CC05 2020 2020-07-27 CHLAC 2.5649493575 A #> 2443 2078B 2 CC05 2020 2020-07-27 COND 10.7499993898 #> 2444 2078B 2 CC05 2020 2020-07-27 DO 1.4422019931 #> 2445 2078B 2 CC05 2020 2020-07-27 DOSAT 4.2150861799 #> 2446 2078B 2 CC05 2020 2020-07-27 NO23 -5.5214609179 U #> 2447 2078B 2 CC05 2020 2020-07-27 SALIN 3.4041928906 #> 2448 2078B 2 CC05 2020 2020-07-27 TKN -0.3424903089 #> 2449 2078B 2 CC05 2020 2020-07-27 TN -0.3396773676 + #> 2450 2078B 2 CC05 2020 2020-07-27 TP -3.1010927892 #> 2451 2078B 2 CC05 2020 2020-07-27 TSS 1.6094379124 I #> 2452 2078B 2 CC05 2020 2020-07-27 TURB 1.1631508098 #> 2453 2078B 2 CC05 2020 2020-08-26 CHLAC 2.8903717579 #> 2454 2078B 2 CC05 2020 2020-08-26 COND 10.1730947543 #> 2455 2078B 2 CC05 2020 2020-08-26 DO 1.5062971535 #> 2456 2078B 2 CC05 2020 2020-08-26 DOSAT 4.1972019477 #> 2457 2078B 2 CC05 2020 2020-08-26 NO23 -5.5214609179 U #> 2458 2078B 2 CC05 2020 2020-08-26 SALIN 2.7625383864 #> 2459 2078B 2 CC05 2020 2020-08-26 TKN -0.0618754037 #> 2460 2078B 2 CC05 2020 2020-08-26 TN -0.0597500044 + #> 2461 2078B 2 CC05 2020 2020-08-26 TP -2.9565115604 #> 2462 2078B 2 CC05 2020 2020-08-26 TSS 1.7917594692 I #> 2463 2078B 2 CC05 2020 2020-08-26 TURB 1.0647107370 #> 2464 2078B 2 CC05 2021 2021-01-14 CHLAC 0.9162907319 #> 2465 2078B 2 CC05 2021 2021-01-14 COND 10.6789517756 #> 2466 2078B 2 CC05 2021 2021-01-14 DO 1.7422190237 #> 2467 2078B 2 CC05 2021 2021-01-14 DOSAT 4.2427645673 #> 2468 2078B 2 CC05 2021 2021-01-14 NO23 -4.6051701860 #> 2469 2078B 2 CC05 2021 2021-01-14 SALIN 3.3339886320 #> 2470 2078B 2 CC05 2021 2021-01-14 TKN -0.6348782724 #> 2471 2078B 2 CC05 2021 2021-01-14 TN -0.6161861394 + #> 2472 2078B 2 CC05 2021 2021-01-14 TP -3.4420193762 #> 2473 2078B 2 CC05 2021 2021-01-14 TSS 1.0986122887 I #> 2474 2078B 2 CC05 2021 2021-01-14 TURB 0.5306282511 #> 2475 2078B 2 CC05 2021 2021-02-24 COND 10.7448823096 #> 2476 2078B 2 CC05 2021 2021-02-24 DO 1.5518087996 #> 2477 2078B 2 CC05 2021 2021-02-24 DOSAT 4.1987045775 #> 2478 2078B 2 CC05 2021 2021-02-24 NO23 -4.6051701860 I #> 2479 2078B 2 CC05 2021 2021-02-24 SALIN 3.4061849232 #> 2480 2078B 2 CC05 2021 2021-02-24 TKN -0.8915981193 #> 2481 2078B 2 CC05 2021 2021-02-24 TN -0.8818893052 + #> 2482 2078B 2 CC05 2021 2021-02-24 TP -3.2441936329 #> 2483 2078B 2 CC05 2021 2021-02-24 TSS 1.0986122887 I #> 2484 2078B 2 CC05 2021 2021-03-23 CHLAC 1.1939224685 #> 2485 2078B 2 CC05 2021 2021-03-23 COND 10.8800451952 #> 2486 2078B 2 CC05 2021 2021-03-23 DO 1.7783364489 #> 2487 2078B 2 CC05 2021 2021-03-23 DOSAT 4.4042772436 #> 2488 2078B 2 CC05 2021 2021-03-23 NO23 -4.9618451299 I #> 2489 2078B 2 CC05 2021 2021-03-23 SALIN 3.5579161896 #> 2490 2078B 2 CC05 2021 2021-03-23 TKN -0.5447271754 #> 2491 2078B 2 CC05 2021 2021-03-23 TN -0.5378542962 + #> 2492 2078B 2 CC05 2021 2021-03-23 TP -2.8134107168 #> 2493 2078B 2 CC05 2021 2021-03-23 TSS 2.4849066498 #> 2494 2078B 2 CC05 2021 2021-03-23 TURB 1.6863989536 #> 2495 2078B 2 CC05 2021 2021-07-28 CHLAC 2.5649493575 #> 2496 2078B 2 CC05 2021 2021-07-28 COND 10.0731881321 #> 2497 2078B 2 CC05 2021 2021-07-28 DO 0.9001613499 #> 2498 2078B 2 CC05 2021 2021-07-28 DOSAT 3.6027767551 #> 2499 2078B 2 CC05 2021 2021-07-28 NO23 -5.5214609179 U #> 2500 2078B 2 CC05 2021 2021-07-28 SALIN 2.6665335209 #> 2501 2078B 2 CC05 2021 2021-07-28 TKN 0.0000000000 #> 2502 2078B 2 CC05 2021 2021-07-28 TN 0.0019980027 + #> 2503 2078B 2 CC05 2021 2021-07-28 TP -3.1010927892 #> 2504 2078B 2 CC05 2021 2021-07-28 TSS 1.3862943611 I #> 2505 2078B 2 CC05 2021 2021-07-28 TURB 1.0296194172 #> 2506 2078B 2 CC05 2021 2021-08-26 CHLAC 2.4849066498 #> 2507 2078B 2 CC05 2021 2021-08-26 COND 10.2519942268 #> 2508 2078B 2 CC05 2021 2021-08-26 DO 1.3737155789 #> 2509 2078B 2 CC05 2021 2021-08-26 DOSAT 4.0324691585 #> 2510 2078B 2 CC05 2021 2021-08-26 NO23 -5.5214609179 U #> 2511 2078B 2 CC05 2021 2021-08-26 SALIN 2.8553201198 #> 2512 2078B 2 CC05 2021 2021-08-26 TKN -0.2231435513 #> 2513 2078B 2 CC05 2021 2021-08-26 TN -0.2206466711 + #> 2514 2078B 2 CC05 2021 2021-08-26 TP -2.8134107168 #> 2515 2078B 2 CC05 2021 2021-08-26 TSS 1.9459101491 I #> 2516 2078B 2 CC05 2021 2021-08-26 TURB 0.8754687374 #> 2517 2078B 2 CC05 2021 2021-09-13 CHLAC 2.5649493575 #> 2518 2078B 2 CC05 2021 2021-09-13 COND 10.4619312252 #> 2519 2078B 2 CC05 2021 2021-09-13 DO 1.4929040962 #> 2520 2078B 2 CC05 2021 2021-09-13 DOSAT 4.2091602367 #> 2521 2078B 2 CC05 2021 2021-09-13 NO23 -5.5214609179 U #> 2522 2078B 2 CC05 2021 2021-09-13 SALIN 3.0842009215 #> 2523 2078B 2 CC05 2021 2021-09-13 TKN -0.0943106795 #> 2524 2078B 2 CC05 2021 2021-09-13 TN -0.0921152889 + #> 2525 2078B 2 CC05 2021 2021-09-13 TP -2.9565115604 #> 2526 2078B 2 CC05 2021 2021-09-13 TSS 2.0794415417 I #> 2527 2078B 2 CC05 2021 2021-09-13 TURB 1.0986122887 A #> 2528 2078B 2 CC05 2022 2022-04-19 CHLAC 2.3978952728 #> 2529 2078B 2 CC05 2022 2022-04-19 COND 10.9594532665 #> 2530 2078B 2 CC05 2022 2022-04-19 DO 1.6486586256 #> 2531 2078B 2 CC05 2022 2022-04-19 DOSAT 4.3845235149 #> 2532 2078B 2 CC05 2022 2022-04-19 NO23 -5.5214609179 U #> 2533 2078B 2 CC05 2022 2022-04-19 SALIN 3.6449275666 #> 2534 2078B 2 CC05 2022 2022-04-19 TKN -0.4462871026 #> 2535 2078B 2 CC05 2022 2022-04-19 TN -0.4431669753 + #> 2536 2078B 2 CC05 2022 2022-04-19 TP -2.6592600369 #> 2537 2078B 2 CC05 2022 2022-04-19 TSS 3.0910424534 #> 2538 2078B 2 CC05 2022 2022-04-19 TURB 1.5892352051 A #> 2539 2078B 2 CC05 2022 2022-05-10 CHLAC 1.9021075264 #> 2540 2078B 2 CC05 2022 2022-05-10 COND 10.8257603561 #> 2541 2078B 2 CC05 2022 2022-05-10 DO 1.6114359151 #> 2542 2078B 2 CC05 2022 2022-05-10 DOSAT 4.3148178850 #> 2543 2078B 2 CC05 2022 2022-05-10 NO23 -5.5214609179 U #> 2544 2078B 2 CC05 2022 2022-05-10 SALIN 3.4943840964 #> 2545 2078B 2 CC05 2022 2022-05-10 TKN -0.1984509387 #> 2546 2078B 2 CC05 2022 2022-05-10 TN -0.1960148839 + #> 2547 2078B 2 CC05 2022 2022-05-10 TP -2.6450754019 #> 2548 2078B 2 CC05 2022 2022-05-10 TSS 2.1972245773 I #> 2549 2078B 2 CC05 2022 2022-05-10 TURB 1.6486586256 #> 2550 2078B 2 CC05 2022 2022-09-20 CHLAC 2.2082744135 #> 2551 2078B 2 CC05 2022 2022-09-20 COND 10.0045990539 #> 2552 2078B 2 CC05 2022 2022-09-20 DO 0.9001613499 #> 2553 2078B 2 CC05 2022 2022-09-20 DOSAT 3.5695326965 #> 2554 2078B 2 CC05 2022 2022-09-20 NO23 -5.5214609179 U #> 2555 2078B 2 CC05 2022 2022-09-20 SALIN 2.5832425505 #> 2556 2078B 2 CC05 2022 2022-09-20 TKN 0.0953101798 #> 2557 2078B 2 CC05 2022 2022-09-20 TN 0.0971267107 + #> 2558 2078B 2 CC05 2022 2022-09-20 TP -2.7333680091 #> 2559 2078B 2 CC05 2022 2022-09-20 TSS 1.3862943611 I #> 2560 2078B 2 CC05 2022 2022-09-20 TURB 0.4054651081 A #> 2561 2078B 2 CC05 2022 2022-10-31 CHLAC 2.7725887222 #> 2562 2078B 2 CC05 2022 2022-10-31 COND 10.6157508503 #> 2563 2078B 2 CC05 2022 2022-10-31 DO 1.1505720276 #> 2564 2078B 2 CC05 2022 2022-10-31 DOSAT 3.8329797981 #> 2565 2078B 2 CC05 2022 2022-10-31 NO23 -5.5214609179 U #> 2566 2078B 2 CC05 2022 2022-10-31 SALIN 3.2584810795 #> 2567 2078B 2 CC05 2022 2022-10-31 TKN -1.8325814637 U #> 2568 2078B 2 CC05 2022 2022-10-31 TN -2.5010360317 + #> 2569 2078B 2 CC05 2022 2022-10-31 TP -2.9374633654 #> 2570 2078B 2 CC05 2022 2022-10-31 TSS 1.7917594692 I #> 2571 2078B 2 CC05 2022 2022-10-31 TURB 1.2237754316 #> 2572 2078B 2 CC05 2021 2021-03-23 CHLAC 1.5892352051 #> 2573 2078B 2 CC05 2021 2021-03-23 COND 10.8660128047 #> 2574 2078B 2 CC05 2021 2021-03-23 DO 2.0162354658 #> 2575 2078B 2 CC05 2021 2021-03-23 DOSAT 4.6802776585 #> 2576 2078B 2 CC05 2021 2021-03-23 NO23 -5.5214609179 U #> 2577 2078B 2 CC05 2021 2021-03-23 SALIN 3.5415388662 #> 2578 2078B 2 CC05 2021 2021-03-23 TKN 0.0953101798 #> 2579 2078B 2 CC05 2021 2021-03-23 TN 0.0971267107 + #> 2580 2078B 2 CC05 2021 2021-03-23 TP -3.2968373663 #> 2581 2078B 2 CC05 2021 2021-03-23 TSS 1.0986122887 I #> 2582 2078B 2 CC05 2021 2021-03-23 TURB 0.7884573604 #> 2583 2078B 2 CC05 2021 2021-07-28 CHLAC 1.5686159179 I #> 2584 2078B 2 CC05 2021 2021-07-28 COND 9.6616070559 #> 2585 2078B 2 CC05 2021 2021-07-28 DO -0.3566749439 #> 2586 2078B 2 CC05 2021 2021-07-28 DOSAT 2.3418058061 #> 2587 2078B 2 CC05 2021 2021-07-28 NO23 -5.5214609179 U #> 2588 2078B 2 CC05 2021 2021-07-28 SALIN 2.2049722641 #> 2589 2078B 2 CC05 2021 2021-07-28 TKN 0.0953101798 #> 2590 2078B 2 CC05 2021 2021-07-28 TN 0.0971267107 + #> 2591 2078B 2 CC05 2021 2021-07-28 TP -3.3242363405 #> 2592 2078B 2 CC05 2021 2021-07-28 TSS 1.0986122887 U #> 2593 2078B 2 CC05 2021 2021-07-28 TURB 0.5306282511 #> 2594 2078B 2 CC05 2021 2021-08-26 CHLAC 2.5649493575 #> 2595 2078B 2 CC05 2021 2021-08-26 COND 9.7645702533 #> 2596 2078B 2 CC05 2021 2021-08-26 DO 0.7030975114 #> 2597 2078B 2 CC05 2021 2021-08-26 DOSAT 3.3141860047 #> 2598 2078B 2 CC05 2021 2021-08-26 NO23 -5.5214609179 U #> 2599 2078B 2 CC05 2021 2021-08-26 SALIN 2.3223877203 #> 2600 2078B 2 CC05 2021 2021-08-26 TKN 0.2623642645 #> 2601 2078B 2 CC05 2021 2021-08-26 TN 0.2639015438 + #> 2602 2078B 2 CC05 2021 2021-08-26 TP -2.9565115604 #> 2603 2078B 2 CC05 2021 2021-08-26 TSS 2.3025850930 I #> 2604 2078B 2 CC05 2021 2021-08-26 TURB 2.3978952728 #> 2605 2078B 2 CC05 2021 2021-09-13 CHLAC 2.8332133441 A #> 2606 2078B 2 CC05 2021 2021-09-13 COND 10.1916695000 #> 2607 2078B 2 CC05 2021 2021-09-13 DO 1.2296405511 #> 2608 2078B 2 CC05 2021 2021-09-13 DOSAT 3.9239515763 #> 2609 2078B 2 CC05 2021 2021-09-13 NO23 -5.5214609179 U #> 2610 2078B 2 CC05 2021 2021-09-13 SALIN 2.7868613815 #> 2611 2078B 2 CC05 2021 2021-09-13 TKN 0.0953101798 #> 2612 2078B 2 CC05 2021 2021-09-13 TN 0.0971267107 + #> 2613 2078B 2 CC05 2021 2021-09-13 TP -2.9957322736 #> 2614 2078B 2 CC05 2021 2021-09-13 TSS 1.6094379124 I #> 2615 2078B 2 CC05 2021 2021-09-13 TURB 1.7578579176 #> 2616 2078B 2 CC05 2021 2021-10-20 CHLAC 2.7725887222 #> 2617 2078B 2 CC05 2021 2021-10-20 COND 10.4756810512 #> 2618 2078B 2 CC05 2021 2021-10-20 DO 0.2700271372 #> 2619 2078B 2 CC05 2021 2021-10-20 DOSAT 2.9391619221 #> 2620 2078B 2 CC05 2021 2021-10-20 NO23 -5.5214609179 U #> 2621 2078B 2 CC05 2021 2021-10-20 SALIN 3.1099534176 #> 2622 2078B 2 CC05 2021 2021-10-20 TKN 0.0953101798 #> 2623 2078B 2 CC05 2021 2021-10-20 TN 0.0971267107 + #> 2624 2078B 2 CC05 2021 2021-10-20 TP -3.1235656451 #> 2625 2078B 2 CC05 2021 2021-10-20 TSS 1.9459101491 I #> 2626 2078B 2 CC05 2021 2021-10-20 TURB 1.4109869737 #> 2627 2078B 2 CC05 2022 2022-04-06 CHLAC 1.8718021769 #> 2628 2078B 2 CC05 2022 2022-04-06 COND 11.0061250625 #> 2629 2078B 2 CC05 2022 2022-04-06 DO 0.6365768291 #> 2630 2078B 2 CC05 2022 2022-04-06 DOSAT 3.3911470458 #> 2631 2078B 2 CC05 2022 2022-04-06 NO23 -5.5214609179 U #> 2632 2078B 2 CC05 2022 2022-04-06 SALIN 3.6980869349 #> 2633 2078B 2 CC05 2022 2022-04-06 TKN -0.0512932944 #> 2634 2078B 2 CC05 2022 2022-04-06 TN -0.0491902442 + #> 2635 2078B 2 CC05 2022 2022-04-06 TP -3.1700856607 #> 2636 2078B 2 CC05 2022 2022-04-06 TSS 1.3862943611 I #> 2637 2078B 2 CC05 2022 2022-04-06 TURB 0.0953101798 #> 2638 2078B 2 CC05 2022 2022-05-10 CHLAC 2.5649493575 #> 2639 2078B 2 CC05 2022 2022-05-10 COND 10.7027274806 #> 2640 2078B 2 CC05 2022 2022-05-10 DO 1.1281710909 #> 2641 2078B 2 CC05 2022 2022-05-10 DOSAT 3.7841896339 #> 2642 2078B 2 CC05 2022 2022-05-10 NO23 -5.5214609179 U #> 2643 2078B 2 CC05 2022 2022-05-10 SALIN 3.3579418730 #> 2644 2078B 2 CC05 2022 2022-05-10 TKN -0.0512932944 #> 2645 2078B 2 CC05 2022 2022-05-10 TN -0.0491902442 + #> 2646 2078B 2 CC05 2022 2022-05-10 TP -3.1010927892 #> 2647 2078B 2 CC05 2022 2022-05-10 TSS 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CC104 2023 2023-05-10 COND 9.6875057942 #> 2914 2035 3F CC104 2023 2023-05-10 DO 1.1216775616 #> 2915 2035 3F CC104 2023 2023-05-10 DOSAT 3.6913763343 #> 2916 2035 3F CC104 2023 2023-05-10 SALIN 2.2417729536 #> 2917 2035 3F CC104 2022 2022-01-24 COND 8.4487001950 #> 2918 2035 3F CC104 2022 2022-01-24 DO 2.1447610078 #> 2919 2035 3F CC104 2022 2022-01-24 DOSAT 4.4624538838 #> 2920 2035 3F CC104 2022 2022-01-24 SALIN 0.9202827531 #> 2921 2035 3F CC104 2022 2022-03-03 COND 9.6867608690 #> 2922 2035 3F CC104 2022 2022-03-03 DO 1.4516138272 #> 2923 2035 3F CC104 2022 2022-03-03 DOSAT 3.9608131696 #> 2924 2035 3F CC104 2022 2022-03-03 SALIN 2.2449559802 #> 2925 2035 3F CC104 2022 2022-05-23 COND 10.0031066176 #> 2926 2035 3F CC104 2022 2022-05-23 DO 1.0986122887 #> 2927 2035 3F CC104 2022 2022-05-23 DOSAT 3.7518542533 #> 2928 2035 3F CC104 2022 2022-05-23 SALIN 2.9019708937 #> 2929 2035 3F CC104 2022 2022-06-27 COND 7.9745328441 #> 2930 2035 3F CC104 2022 2022-06-27 DO 1.6544112781 #> 2931 2035 3F CC104 2022 2022-06-27 DOSAT 4.2150861799 #> 2932 2035 3F CC104 2022 2022-06-27 SALIN 0.4054651081 #> 2933 2035 3F CC104 2023 2023-01-09 COND 7.0958932211 #> 2934 2035 3F CC104 2023 2023-01-09 DO 2.1575593209 #> 2935 2035 3F CC104 2023 2023-01-09 DOSAT 4.5464811896 #> 2936 2035 3F CC104 2023 2023-01-09 SALIN -0.5108256238 #> 2937 2035 3F CC104 2023 2023-03-14 COND 9.4841009891 #> 2938 2035 3F CC104 2023 2023-03-14 DO 0.9820784724 #> 2939 2035 3F CC104 2023 2023-03-14 DOSAT 3.5292973843 #> 2940 2035 3F CC104 2023 2023-03-14 SALIN 2.0215475633 #> 2941 2035 3F CC104 2023 2023-05-10 COND 9.8215722593 #> 2942 2035 3F CC104 2023 2023-05-10 DO 1.3660916538 #> 2943 2035 3F CC104 2023 2023-05-10 DOSAT 3.9627161197 #> 2944 2035 3F CC104 2023 2023-05-10 SALIN 2.3860067011 #> 2945 2035 3F CC104 2014 2014-05-28 COND 7.0817085861 #> 2946 2035 3F CC104 2014 2014-05-28 DO 1.5560371357 #> 2947 2035 3F CC104 2014 2014-05-28 DOSAT 4.0145795938 + #> 2948 2035 3F CC104 2014 2014-05-28 SALIN -0.5276327421 #> 2949 2035 3F CC104 2014 2014-10-02 COND 5.9506425526 #> 2950 2035 3F CC104 2014 2014-10-02 DO 1.6770965609 #> 2951 2035 3F CC104 2014 2014-10-02 DOSAT 4.2061840440 + #> 2952 2035 3F CC104 2014 2014-10-02 SALIN -1.7147984281 #> 2953 2035 3F CC104 2016 2016-06-02 COND 6.8068293604 #> 2954 2035 3F CC104 2016 2016-06-02 DO 1.3837912309 #> 2955 2035 3F CC104 2016 2016-06-02 DOSAT 3.8501476017 + #> 2956 2035 3F CC104 2016 2016-06-02 SALIN -0.8209805521 #> 2957 2035 3F CC104 2016 2016-09-21 COND 6.3664704477 #> 2958 2035 3F CC104 2016 2016-09-21 DO 1.6389967147 #> 2959 2035 3F CC104 2016 2016-09-21 DOSAT 4.1697612015 + #> 2960 2035 3F CC104 2016 2016-09-21 SALIN -1.2729656758 #> 2961 2035 3F CC104 2017 2017-05-09 COND 6.9791452751 #> 2962 2035 3F CC104 2017 2017-05-09 DO 1.4134230285 #> 2963 2035 3F CC104 2017 2017-05-09 DOSAT 3.8220982979 + #> 2964 2035 3F CC104 2017 2017-05-09 SALIN -0.6348782724 #> 2965 2035 3F CC104 2017 2017-09-27 COND 6.1654178542 #> 2966 2035 3F CC104 2017 2017-09-27 DO 1.6937790609 #> 2967 2035 3F CC104 2017 2017-09-27 DOSAT 4.2195077052 + #> 2968 2035 3F CC104 2017 2017-09-27 SALIN -1.4696759701 #> 2969 2035 3F CC104 2018 2018-06-04 COND 6.2672005485 #> 2970 2035 3F CC104 2018 2018-06-04 DO 1.6808279085 #> 2971 2035 3F CC104 2018 2018-06-04 DOSAT 4.2209772132 + #> 2972 2035 3F CC104 2018 2018-06-04 SALIN -1.3862943611 #> 2973 2035 3F CC104 2018 2018-09-12 COND 6.2265366693 #> 2974 2035 3F CC104 2018 2018-09-12 DO 1.7749523509 #> 2975 2035 3F CC104 2018 2018-09-12 DOSAT 4.3040650932 + #> 2976 2035 3F CC104 2018 2018-09-12 SALIN -1.4271163556 #> 2977 2045 3M CC15 2018 2018-03-07 CHLAC 2.2617630985 #> 2978 2045 3M CC15 2018 2018-03-07 COND 10.0150289273 #> 2979 2045 3M CC15 2018 2018-03-07 DO 2.0281482473 #> 2980 2045 3M CC15 2018 2018-03-07 DOSAT 4.5475410732 #> 2981 2045 3M CC15 2018 2018-03-07 NO23 -5.5214609179 U #> 2982 2045 3M CC15 2018 2018-03-07 SALIN 2.6595599919 + #> 2983 2045 3M CC15 2018 2018-03-07 TKN -0.1743533871 #> 2984 2045 3M CC15 2018 2018-03-07 TN -0.1719752647 + #> 2985 2045 3M CC15 2018 2018-03-07 TP -1.8325814637 #> 2986 2045 3M CC15 2018 2018-03-07 TSS 1.0986122887 U #> 2987 2045 3M CC15 2018 2018-03-07 TURB 1.2809338455 #> 2988 2045 3M CC15 2018 2018-04-09 CHLAC 1.8870696490 #> 2989 2045 3M CC15 2018 2018-04-09 COND 10.4012279368 #> 2990 2045 3M CC15 2018 2018-04-09 DO 1.7227665977 #> 2991 2045 3M CC15 2018 2018-04-09 DOSAT 4.3438054219 #> 2992 2045 3M CC15 2018 2018-04-09 NO23 -5.5214609179 I #> 2993 2045 3M CC15 2018 2018-04-09 SALIN 3.0017143452 + #> 2994 2045 3M CC15 2018 2018-04-09 TKN -0.2357223335 #> 2995 2045 3M CC15 2018 2018-04-09 TN -0.2306718177 + #> 2996 2045 3M CC15 2018 2018-04-09 TP -1.5606477483 #> 2997 2045 3M CC15 2018 2018-04-09 TSS 2.7080502011 #> 2998 2045 3M CC15 2018 2018-04-09 TURB 1.8718021769 A #> 2999 2045 3M CC15 2018 2018-05-24 CHLAC 2.3978952728 #> 3000 2045 3M CC15 2018 2018-05-24 COND 9.3056505518 #> 3001 2045 3M CC15 2018 2018-05-24 DO 1.9198594719 #> 3002 2045 3M CC15 2018 2018-05-24 DOSAT 4.4589876758 #> 3003 2045 3M CC15 2018 2018-05-24 NO23 -3.3524072175 #> 3004 2045 3M CC15 2018 2018-05-24 SALIN 1.7833912196 + #> 3005 2045 3M CC15 2018 2018-05-24 TKN -0.1392620673 #> 3006 2045 3M CC15 2018 2018-05-24 TN -0.0998203353 + #> 3007 2045 3M CC15 2018 2018-05-24 TP -1.6094379124 #> 3008 2045 3M CC15 2018 2018-05-24 TSS 1.7917594692 I #> 3009 2045 3M CC15 2018 2018-05-24 TURB 1.3350010667 #> 3010 2045 3M CC15 2018 2018-05-24 SALIN 1.8991179875 + #> 3011 2045 3M CC15 2018 2018-05-24 COND 9.4091912307 #> 3012 2045 3M CC15 2018 2018-05-24 DO 1.7833912196 #> 3013 2045 3M CC15 2018 2018-05-24 DOSAT 4.3630986248 #> 3014 2045 3M CC15 2018 2018-05-24 COND 9.3056505518 #> 3015 2045 3M CC15 2018 2018-05-24 DO 1.9198594719 #> 3016 2045 3M CC15 2018 2018-05-24 DOSAT 4.4589876758 #> 3017 2045 3M CC15 2018 2018-05-24 SALIN 1.7833912196 + #> 3018 2045 3M CC15 2018 2018-07-23 CHLAC 2.0149030205 #> 3019 2045 3M CC15 2018 2018-07-23 COND 6.5087691370 #> 3020 2045 3M CC15 2018 2018-07-23 DO 1.7800242130 #> 3021 2045 3M CC15 2018 2018-07-23 DOSAT 4.3567088267 #> 3022 2045 3M CC15 2018 2018-07-23 NO23 -1.9661128564 #> 3023 2045 3M CC15 2018 2018-07-23 SALIN -1.1394342832 #> 3024 2045 3M CC15 2018 2018-07-23 TKN 0.1823215568 #> 3025 2045 3M CC15 2018 2018-07-23 TN 0.2926696140 + #> 3026 2045 3M CC15 2018 2018-07-23 TP -1.1394342832 #> 3027 2045 3M CC15 2018 2018-07-23 TSS 1.3862943611 I #> 3028 2045 3M CC15 2018 2018-07-23 TURB 1.3083328197 #> 3029 2045 3M CC15 2018 2018-08-21 CHLAC 2.0794415417 #> 3030 2045 3M CC15 2018 2018-08-21 COND 6.4393503711 #> 3031 2045 3M CC15 2018 2018-08-21 DO 1.6601310267 #> 3032 2045 3M CC15 2018 2018-08-21 DOSAT 4.2341065046 #> 3033 2045 3M CC15 2018 2018-08-21 NO23 -2.6736487744 #> 3034 2045 3M CC15 2018 2018-08-21 SALIN -1.2039728043 #> 3035 2045 3M CC15 2018 2018-08-21 TKN 0.0953101798 #> 3036 2045 3M CC15 2018 2018-08-21 TN 0.1561486825 + #> 3037 2045 3M CC15 2018 2018-08-21 TP -1.2378743560 #> 3038 2045 3M CC15 2018 2018-08-21 TSS 1.0986122887 I #> 3039 2045 3M CC15 2018 2018-08-21 TURB 1.0986122887 #> 3040 2045 3M CC15 2018 2018-08-21 COND 6.4264884575 #> 3041 2045 3M CC15 2018 2018-08-21 DO 1.6114359151 #> 3042 2045 3M CC15 2018 2018-08-21 DOSAT 4.1774594689 #> 3043 2045 3M CC15 2018 2018-08-21 SALIN -1.2039728043 #> 3044 2045 3M CC15 2019 2019-02-07 CHLAC 3.2188758249 A #> 3045 2045 3M CC15 2019 2019-02-07 COND 8.6916505732 #> 3046 2045 3M CC15 2019 2019-02-07 NO23 -5.1159958098 I #> 3047 2045 3M CC15 2019 2019-02-07 SALIN 1.1755733298 #> 3048 2045 3M CC15 2019 2019-02-07 TKN 0.0953101798 #> 3049 2045 3M CC15 2019 2019-02-07 TN 0.0989399479 + #> 3050 2045 3M CC15 2019 2019-02-07 TP -1.6607312068 #> 3051 2045 3M CC15 2019 2019-02-07 TSS 2.3025850930 I #> 3052 2045 3M CC15 2019 2019-02-07 TURB 2.0281482473 #> 3053 2045 3M CC15 2019 2019-03-13 CHLAC 1.8870696490 #> 3054 2045 3M CC15 2019 2019-03-13 COND 9.4304392931 #> 3055 2045 3M CC15 2019 2019-03-13 DO 1.8961194846 #> 3056 2045 3M CC15 2019 2019-03-13 DOSAT 4.4188406078 #> 3057 2045 3M CC15 2019 2019-03-13 NO23 -5.2983173665 I #> 3058 2045 3M CC15 2019 2019-03-13 SALIN 1.9657127764 #> 3059 2045 3M CC15 2019 2019-03-13 TKN -0.1625189295 #> 3060 2045 3M CC15 2019 2019-03-13 TN -0.1578240852 + #> 3061 2045 3M CC15 2019 2019-03-13 TP -1.8325814637 #> 3062 2045 3M CC15 2019 2019-03-13 TSS 2.0794415417 I #> 3063 2045 3M CC15 2019 2019-03-13 TURB 1.5892352051 #> 3064 2045 3M CC15 2019 2019-04-23 CHLAC 1.7749523509 #> 3065 2045 3M CC15 2019 2019-04-23 COND 9.9110588180 #> 3066 2045 3M CC15 2019 2019-04-23 DO 1.8562979904 #> 3067 2045 3M CC15 2019 2019-04-23 DOSAT 4.3845235149 #> 3068 2045 3M CC15 2019 2019-04-23 NO23 -5.5214609179 U #> 3069 2045 3M CC15 2019 2019-04-23 SALIN 2.4882344399 #> 3070 2045 3M CC15 2019 2019-04-23 TKN -0.2744368457 #> 3071 2045 3M CC15 2019 2019-04-23 TN -0.2718087233 + #> 3072 2045 3M CC15 2019 2019-04-23 TP -1.6607312068 #> 3073 2045 3M CC15 2019 2019-04-23 TSS 2.0794415417 I #> 3074 2045 3M CC15 2019 2019-04-23 TURB 1.4586150227 #> 3075 2045 3M CC15 2019 2019-07-22 CHLAC 2.4849066498 #> 3076 2045 3M CC15 2019 2019-07-22 COND 8.5083542427 #> 3077 2045 3M CC15 2019 2019-07-22 DO 1.7227665977 #> 3078 2045 3M CC15 2019 2019-07-22 DOSAT 4.3174881135 #> 3079 2045 3M CC15 2019 2019-07-22 NO23 -3.5065578973 #> 3080 2045 3M CC15 2019 2019-07-22 SALIN 0.9707789172 #> 3081 2045 3M CC15 2019 2019-07-22 TKN -0.0512932944 #> 3082 2045 3M CC15 2019 2019-07-22 TN -0.0202027073 + #> 3083 2045 3M CC15 2019 2019-07-22 TP -1.1086626245 #> 3084 2045 3M CC15 2019 2019-07-22 TSS 1.6094379124 I #> 3085 2045 3M CC15 2019 2019-07-22 TURB 1.3862943611 #> 3086 2045 3M CC15 2019 2019-09-04 COND 7.2896105215 #> 3087 2045 3M CC15 2019 2019-09-04 DO 1.6213664833 #> 3088 2045 3M CC15 2019 2019-09-04 DOSAT 4.2061840440 #> 3089 2045 3M CC15 2019 2019-09-04 NO23 -2.4191189092 #> 3090 2045 3M CC15 2019 2019-09-04 SALIN -0.3147107448 #> 3091 2045 3M CC15 2019 2019-09-04 TKN 0.1823215568 #> 3092 2045 3M CC15 2019 2019-09-04 TN 0.2538667240 + #> 3093 2045 3M CC15 2019 2019-09-04 TP -0.9675840263 #> 3094 2045 3M CC15 2019 2019-09-04 TSS 1.0986122887 I #> 3095 2045 3M CC15 2019 2019-09-04 TURB 1.0986122887 #> 3096 2045 3M CC15 2020 2020-02-18 CHLAC 2.7080502011 #> 3097 2045 3M CC15 2020 2020-02-18 COND 10.0136863448 #> 3098 2045 3M CC15 2020 2020-02-18 DO 1.9358598132 #> 3099 2045 3M CC15 2020 2020-02-18 DOSAT 4.5272086445 #> 3100 2045 3M CC15 2020 2020-02-18 NO23 -4.8283137373 I #> 3101 2045 3M CC15 2020 2020-02-18 SALIN 2.5967461315 #> 3102 2045 3M CC15 2020 2020-02-18 TKN -0.1165338163 #> 3103 2045 3M CC15 2020 2020-02-18 TN -0.1120495038 + #> 3104 2045 3M CC15 2020 2020-02-18 TP -1.6094379124 #> 3105 2045 3M CC15 2020 2020-02-18 TSS 2.7080502011 #> 3106 2045 3M CC15 2020 2020-02-18 TURB 1.7227665977 #> 3107 2045 3M CC15 2020 2020-02-18 COND 10.0120728629 #> 3108 2045 3M CC15 2020 2020-02-18 DO 1.9227877316 #> 3109 2045 3M CC15 2020 2020-02-18 DOSAT 4.5086592856 #> 3110 2045 3M CC15 2020 2020-02-18 SALIN 2.5952547070 #> 3111 2045 3M CC15 2020 2020-06-09 CHLAC 2.4849066498 #> 3112 2045 3M CC15 2020 2020-06-09 COND 9.2513863414 #> 3113 2045 3M CC15 2020 2020-06-09 DO 1.9315214116 #> 3114 2045 3M CC15 2020 2020-06-09 DOSAT 4.5239601306 #> 3115 2045 3M CC15 2020 2020-06-09 NO23 -3.3813947544 #> 3116 2045 3M CC15 2020 2020-06-09 SALIN 1.7664416612 #> 3117 2045 3M CC15 2020 2020-06-09 TKN -0.0304592075 #> 3118 2045 3M CC15 2020 2020-06-09 TN 0.0039920213 + #> 3119 2045 3M CC15 2020 2020-06-09 TP -1.4696759701 #> 3120 2045 3M CC15 2020 2020-06-09 TSS 1.0986122887 I #> 3121 2045 3M CC15 2020 2020-06-09 TURB 0.9162907319 #> 3122 2045 3M CC15 2020 2020-06-09 COND 9.5815590414 #> 3123 2045 3M CC15 2020 2020-06-09 DO 1.6544112781 #> 3124 2045 3M CC15 2020 2020-06-09 DOSAT 4.2076732475 #> 3125 2045 3M CC15 2020 2020-06-09 SALIN 2.1552445051 #> 3126 2045 3M CC15 2020 2020-08-10 COND 9.2688922589 #> 3127 2045 3M CC15 2020 2020-08-10 DO 1.6370530795 #> 3128 2045 3M CC15 2020 2020-08-10 DOSAT 4.2710950740 #> 3129 2045 3M CC15 2020 2020-08-10 SALIN -1.4567168254 #> 3130 2045 3M CC15 2020 2020-08-10 COND 9.4812068515 #> 3131 2045 3M CC15 2020 2020-08-10 DO 1.4398351280 #> 3132 2045 3M CC15 2020 2020-08-10 DOSAT 4.0758410907 #> 3133 2045 3M CC15 2020 2020-08-10 SALIN 0.2207406667 #> 3134 2045 3M CC15 2020 2020-09-22 CHLAC 2.2192034841 #> 3135 2045 3M CC15 2020 2020-09-22 COND 6.5750758406 #> 3136 2045 3M CC15 2020 2020-09-22 DO 1.7934247485 #> 3137 2045 3M CC15 2020 2020-09-22 DOSAT 4.3359826962 #> 3138 2045 3M CC15 2020 2020-09-22 NO23 -2.7968814148 #> 3139 2045 3M CC15 2020 2020-09-22 SALIN -1.0498221245 #> 3140 2045 3M CC15 2020 2020-09-22 TKN 0.2623642645 #> 3141 2045 3M CC15 2020 2020-09-22 TN 0.3082197237 + #> 3142 2045 3M CC15 2020 2020-09-22 TP -0.9942522733 #> 3143 2045 3M CC15 2020 2020-09-22 TSS 1.3862943611 I #> 3144 2045 3M CC15 2020 2020-09-22 TURB 1.2809338455 #> 3145 2045 3M CC15 2020 2020-10-20 CHLAC 3.0445224377 #> 3146 2045 3M CC15 2020 2020-10-20 COND 8.3209349689 #> 3147 2045 3M CC15 2020 2020-10-20 DO 1.7119945008 #> 3148 2045 3M CC15 2020 2020-10-20 DOSAT 4.2640873368 #> 3149 2045 3M CC15 2020 2020-10-20 NO23 -2.5010360317 #> 3150 2045 3M CC15 2020 2020-10-20 SALIN 0.7747271676 #> 3151 2045 3M CC15 2020 2020-10-20 TKN 0.2623642645 #> 3152 2045 3M CC15 2020 2020-10-20 TN 0.3235317253 + #> 3153 2045 3M CC15 2020 2020-10-20 TP -0.9942522733 #> 3154 2045 3M CC15 2020 2020-10-20 TSS 1.6094379124 I #> 3155 2045 3M CC15 2020 2020-10-20 TURB 1.2809338455 #> 3156 2045 3M CC15 2020 2020-12-14 CHLAC 2.6390573296 #> 3157 2045 3M CC15 2020 2020-12-14 COND 9.2314166976 #> 3158 2045 3M CC15 2020 2020-12-14 DO 2.0930978681 #> 3159 2045 3M CC15 2020 2020-12-14 DOSAT 4.5695430083 #> 3160 2045 3M CC15 2020 2020-12-14 NO23 -4.9618451299 I #> 3161 2045 3M CC15 2020 2020-12-14 SALIN 1.7526720805 #> 3162 2045 3M CC15 2020 2020-12-14 TKN 0.0000000000 #> 3163 2045 3M CC15 2020 2020-12-14 TN 0.0039920213 + #> 3164 2045 3M CC15 2020 2020-12-14 TP -1.4696759701 #> 3165 2045 3M CC15 2020 2020-12-14 TSS 1.6094379124 I #> 3166 2045 3M CC15 2020 2020-12-14 TURB 1.3609765531 A #> 3167 2045 3M CC15 2021 2021-02-03 CHLAC 1.7404661748 #> 3168 2045 3M CC15 2021 2021-02-03 COND 9.8506140629 #> 3169 2045 3M CC15 2021 2021-02-03 DO 2.1424163408 #> 3170 2045 3M CC15 2021 2021-02-03 DOSAT 4.5528237056 #> 3171 2045 3M CC15 2021 2021-02-03 NO23 -5.5214609179 U #> 3172 2045 3M CC15 2021 2021-02-03 SALIN 2.4248027257 #> 3173 2045 3M CC15 2021 2021-02-03 TKN -0.3424903089 #> 3174 2045 3M CC15 2021 2021-02-03 TN -0.3396773676 + #> 3175 2045 3M CC15 2021 2021-02-03 TP -1.9661128564 #> 3176 2045 3M CC15 2021 2021-02-03 TSS 1.3862943611 I #> 3177 2045 3M CC15 2021 2021-02-03 TURB 1.0296194172 #> 3178 2045 3M CC15 2021 2021-03-09 CHLAC 2.4849066498 #> 3179 2045 3M CC15 2021 2021-03-09 COND 9.8787336881 #> 3180 2045 3M CC15 2021 2021-03-09 DO 2.1690537004 #> 3181 2045 3M CC15 2021 2021-03-09 DOSAT 4.6510991179 #> 3182 2045 3M CC15 2021 2021-03-09 NO23 -5.5214609179 I #> 3183 2045 3M CC15 2021 2021-03-09 SALIN 2.4544474423 #> 3184 2045 3M CC15 2021 2021-03-09 TKN 0.0000000000 #> 3185 2045 3M CC15 2021 2021-03-09 TN 0.0039920213 + #> 3186 2045 3M CC15 2021 2021-03-09 TP -1.4696759701 #> 3187 2045 3M CC15 2021 2021-03-09 TSS 3.2958368660 #> 3188 2045 3M CC15 2021 2021-03-09 TURB 2.3978952728 A #> 3189 2045 3M CC15 2021 2021-05-05 CHLAC 1.8082887712 #> 3190 2045 3M CC15 2021 2021-05-05 COND 10.2487071336 #> 3191 2045 3M CC15 2021 2021-05-05 DO 1.8082887712 #> 3192 2045 3M CC15 2021 2021-05-05 DOSAT 4.4986979415 #> 3193 2045 3M CC15 2021 2021-05-05 NO23 -5.5214609179 U #> 3194 2045 3M CC15 2021 2021-05-05 SALIN 2.8489708922 #> 3195 2045 3M CC15 2021 2021-05-05 TKN -0.2231435513 #> 3196 2045 3M CC15 2021 2021-05-05 TN -0.2206466711 + #> 3197 2045 3M CC15 2021 2021-05-05 TP -1.6094379124 #> 3198 2045 3M CC15 2021 2021-05-05 TSS 1.9459101491 I #> 3199 2045 3M CC15 2021 2021-05-05 TURB 1.3350010667 #> 3200 2045 3M CC15 2021 2021-06-03 CHLAC 1.8245492921 #> 3201 2045 3M CC15 2021 2021-06-03 COND 10.3770473511 #> 3202 2045 3M CC15 2021 2021-06-03 DO 1.7715567619 #> 3203 2045 3M CC15 2021 2021-06-03 DOSAT 4.4331949212 #> 3204 2045 3M CC15 2021 2021-06-03 NO23 -5.5214609179 U #> 3205 2045 3M CC15 2021 2021-06-03 SALIN 2.9937302709 #> 3206 2045 3M CC15 2021 2021-06-03 TKN -0.1743533871 #> 3207 2045 3M CC15 2021 2021-06-03 TN -0.1719752647 + #> 3208 2045 3M CC15 2021 2021-06-03 TP -1.5606477483 #> 3209 2045 3M CC15 2021 2021-06-03 TSS 1.7917594692 I #> 3210 2045 3M CC15 2021 2021-06-03 TURB 1.2237754316 #> 3211 2045 3M CC15 2021 2021-07-01 CHLAC 2.1860512767 #> 3212 2045 3M CC15 2021 2021-07-01 COND 10.1292277297 #> 3213 2045 3M CC15 2021 2021-07-01 DO 1.7351891177 #> 3214 2045 3M CC15 2021 2021-07-01 DOSAT 4.3541414312 #> 3215 2045 3M CC15 2021 2021-07-01 NO23 -5.5214609179 U #> 3216 2045 3M CC15 2021 2021-07-01 SALIN 2.7232671669 #> 3217 2045 3M CC15 2021 2021-07-01 TKN -0.4155154440 #> 3218 2045 3M CC15 2021 2021-07-01 TN -0.4124897230 + #> 3219 2045 3M CC15 2021 2021-07-01 TP -1.5606477483 #> 3220 2045 3M CC15 2021 2021-07-01 TSS 1.0986122887 U #> 3221 2045 3M CC15 2021 2021-07-01 TURB 1.3083328197 #> 3222 2045 3M CC15 2021 2021-07-29 CHLAC 1.5892352051 #> 3223 2045 3M CC15 2021 2021-07-29 COND 7.4764723812 #> 3224 2045 3M CC15 2021 2021-07-29 DO 1.4303112465 #> 3225 2045 3M CC15 2021 2021-07-29 DOSAT 4.0145795938 #> 3226 2045 3M CC15 2021 2021-07-29 NO23 -2.4769384801 #> 3227 2045 3M CC15 2021 2021-07-29 SALIN -0.1165338163 #> 3228 2045 3M CC15 2021 2021-07-29 TKN 0.3364722366 #> 3229 2045 3M CC15 2021 2021-07-29 TN 0.3947411447 + #> 3230 2045 3M CC15 2021 2021-07-29 TP -0.4780358009 #> 3231 2045 3M CC15 2021 2021-07-29 TSS 1.7917594692 I #> 3232 2045 3M CC15 2021 2021-07-29 TURB 1.6292405397 #> 3233 2045 3M CC15 2021 2021-08-25 CHLAC 2.7725887222 #> 3234 2045 3M CC15 2021 2021-08-25 COND 6.9107507880 #> 3235 2045 3M CC15 2021 2021-08-25 DO 1.3376291891 #> 3236 2045 3M CC15 2021 2021-08-25 DOSAT 3.9120230054 #> 3237 2045 3M CC15 2021 2021-08-25 NO23 -2.9565115604 #> 3238 2045 3M CC15 2021 2021-08-25 SALIN -0.7133498879 #> 3239 2045 3M CC15 2021 2021-08-25 TKN 0.0953101798 #> 3240 2045 3M CC15 2021 2021-08-25 TN 0.1414995623 + #> 3241 2045 3M CC15 2021 2021-08-25 TP -0.8915981193 #> 3242 2045 3M CC15 2021 2021-08-25 TSS 1.0986122887 I #> 3243 2045 3M CC15 2021 2021-08-25 TURB 1.0647107370 #> 3244 2045 3M CC15 2021 2021-09-23 CHLAC 2.2300144002 #> 3245 2045 3M CC15 2021 2021-09-23 COND 6.2653012127 #> 3246 2045 3M CC15 2021 2021-09-23 DO 1.4060969884 #> 3247 2045 3M CC15 2021 2021-09-23 DOSAT 3.9550824949 #> 3248 2045 3M CC15 2021 2021-09-23 NO23 -3.0365542681 #> 3249 2045 3M CC15 2021 2021-09-23 SALIN -1.3862943611 #> 3250 2045 3M CC15 2021 2021-09-23 TKN 0.0953101798 #> 3251 2045 3M CC15 2021 2021-09-23 TN 0.1380212979 + #> 3252 2045 3M CC15 2021 2021-09-23 TP -1.3093333200 #> 3253 2045 3M CC15 2021 2021-09-23 TSS 1.3862943611 I #> 3254 2045 3M CC15 2021 2021-09-23 TURB 1.2527629685 #> 3255 2045 3M CC15 2021 2021-10-21 CHLAC 3.5263605246 #> 3256 2045 3M CC15 2021 2021-10-21 COND 8.7135820054 #> 3257 2045 3M CC15 2021 2021-10-21 DO 1.7732559977 #> 3258 2045 3M CC15 2021 2021-10-21 DOSAT 4.2918283668 #> 3259 2045 3M CC15 2021 2021-10-21 NO23 -2.9957322736 #> 3260 2045 3M CC15 2021 2021-10-21 SALIN 1.1939224685 #> 3261 2045 3M CC15 2021 2021-10-21 TKN 0.2623642645 #> 3262 2045 3M CC15 2021 2021-10-21 TN 0.3001045925 + #> 3263 2045 3M CC15 2021 2021-10-21 TP -1.1711829815 #> 3264 2045 3M CC15 2021 2021-10-21 TSS 1.6094379124 I #> 3265 2045 3M CC15 2021 2021-10-21 TURB 1.2809338455 #> 3266 2045 3M CC15 2021 2021-11-22 COND 9.2692694395 #> 3267 2045 3M CC15 2021 2021-11-22 DO 1.9516081702 #> 3268 2045 3M CC15 2021 2021-11-22 DOSAT 4.4647580323 #> 3269 2045 3M CC15 2021 2021-11-22 NO23 -4.7105307016 I #> 3270 2045 3M CC15 2021 2021-11-22 SALIN 1.7917594692 #> 3271 2045 3M CC15 2021 2021-11-22 TKN -0.1863295782 #> 3272 2045 3M CC15 2021 2021-11-22 TN -0.1815218766 + #> 3273 2045 3M CC15 2021 2021-11-22 TP -1.7147984281 #> 3274 2045 3M CC15 2021 2021-11-22 TSS 1.0986122887 I #> 3275 2045 3M CC15 2021 2021-11-22 TURB 0.9932517730 #> 3276 2045 3M CC15 2022 2022-02-22 CHLAC 1.5040773968 #> 3277 2045 3M CC15 2022 2022-02-22 COND 10.3013572215 #> 3278 2045 3M CC15 2022 2022-02-22 DO 1.9169226122 #> 3279 2045 3M CC15 2022 2022-02-22 DOSAT 4.4986979415 #> 3280 2045 3M CC15 2022 2022-02-22 NO23 -5.5214609179 U #> 3281 2045 3M CC15 2022 2022-02-22 SALIN 2.9139797717 #> 3282 2045 3M CC15 2022 2022-02-22 TKN -0.3285040670 #> 3283 2045 3M CC15 2022 2022-02-22 TN -0.3257301401 + #> 3284 2045 3M CC15 2022 2022-02-22 TP -2.0402208285 #> 3285 2045 3M CC15 2022 2022-02-22 TSS 2.3978952728 #> 3286 2045 3M CC15 2022 2022-02-22 TURB 1.3083328197 #> 3287 2045 3M CC15 2022 2022-04-20 CHLAC 0.4700036292 U #> 3288 2045 3M CC15 2022 2022-04-20 COND 10.5349454823 #> 3289 2045 3M CC15 2022 2022-04-20 DO 1.6919391339 #> 3290 2045 3M CC15 2022 2022-04-20 DOSAT 4.2972854062 #> 3291 2045 3M CC15 2022 2022-04-20 NO23 -5.5214609179 U #> 3292 2045 3M CC15 2022 2022-04-20 SALIN 3.1722034167 #> 3293 2045 3M CC15 2022 2022-04-20 TKN -0.1508228897 #> 3294 2045 3M CC15 2022 2022-04-20 TN -0.1485000083 + #> 3295 2045 3M CC15 2022 2022-04-20 TP -1.9661128564 #> 3296 2045 3M CC15 2022 2022-04-20 TSS 2.5649493575 #> 3297 2045 3M CC15 2022 2022-04-20 TURB 1.8082887712 #> 3298 2045 3M CC15 2022 2022-06-07 CHLAC 1.5260563035 #> 3299 2045 3M CC15 2022 2022-06-07 COND 10.2575891884 #> 3300 2045 3M CC15 2022 2022-06-07 DO 1.7137979278 #> 3301 2045 3M CC15 2022 2022-06-07 DOSAT 4.3870141762 #> 3302 2045 3M CC15 2022 2022-06-07 NO23 -4.8283137373 I #> 3303 2045 3M CC15 2022 2022-06-07 SALIN 2.8604851241 #> 3304 2045 3M CC15 2022 2022-06-07 TKN -0.3710636814 #> 3305 2045 3M CC15 2022 2022-06-07 TN -0.3652833185 + #> 3306 2045 3M CC15 2022 2022-06-07 TP -1.5606477483 #> 3307 2045 3M CC15 2022 2022-06-07 TSS 2.3025850930 #> 3308 2045 3M CC15 2022 2022-06-07 TURB 0.9932517730 #> 3309 2045 3M CC15 2022 2022-08-15 CHLAC 3.2188758249 #> 3310 2045 3M CC15 2022 2022-08-15 COND 8.2671921859 #> 3311 2045 3M CC15 2022 2022-08-15 DO 1.6094379124 #> 3312 2045 3M CC15 2022 2022-08-15 DOSAT 4.2136079830 #> 3313 2045 3M CC15 2022 2022-08-15 NO23 -4.7105307016 I #> 3314 2045 3M CC15 2022 2022-08-15 SALIN 0.7129498079 #> 3315 2045 3M CC15 2022 2022-08-15 TKN 0.0000000000 #> 3316 2045 3M CC15 2022 2022-08-15 TN 0.0039920213 + #> 3317 2045 3M CC15 2022 2022-08-15 TP -1.2378743560 #> 3318 2045 3M CC15 2022 2022-08-15 TSS 1.3862943611 I #> 3319 2045 3M CC15 2022 2022-08-15 TURB 1.0296194172 #> 3320 2045 3M CC15 2022 2022-12-15 CHLAC 4.9416424226 #> 3321 2045 3M CC15 2022 2022-12-15 COND 9.5450252980 #> 3322 2045 3M CC15 2022 2022-12-15 DO 1.8531680974 #> 3323 2045 3M CC15 2022 2022-12-15 DOSAT 4.3681812279 #> 3324 2045 3M CC15 2022 2022-12-15 NO23 -5.5214609179 U #> 3325 2045 3M CC15 2022 2022-12-15 SALIN 2.0881534823 #> 3326 2045 3M CC15 2022 2022-12-15 TKN 0.5306282511 #> 3327 2045 3M CC15 2022 2022-12-15 TN 0.5318040302 + #> 3328 2045 3M CC15 2022 2022-12-15 TP -1.0788096614 #> 3329 2045 3M CC15 2022 2022-12-15 TSS 2.8332133441 #> 3330 2045 3M CC15 2022 2022-12-15 TURB 2.1400661635 #> 3331 2045 3M CC15 2023 2023-01-11 CHLAC 2.1400661635 #> 3332 2045 3M CC15 2023 2023-01-11 COND 9.5500929367 #> 3333 2045 3M CC15 2023 2023-01-11 DO 1.9125010869 #> 3334 2045 3M CC15 2023 2023-01-11 DOSAT 4.3630986248 #> 3335 2045 3M CC15 2023 2023-01-11 NO23 -4.2686979494 #> 3336 2045 3M CC15 2023 2023-01-11 SALIN 2.0992441690 #> 3337 2045 3M CC15 2023 2023-01-11 TKN -0.2876820725 #> 3338 2045 3M CC15 2023 2023-01-11 TN -0.2691874898 + #> 3339 2045 3M CC15 2023 2023-01-11 TP -1.6607312068 #> 3340 2045 3M CC15 2023 2023-01-11 TSS 1.7917594692 I #> 3341 2045 3M CC15 2023 2023-01-11 TURB 0.8754687374 #> 3342 2045 3M CC15 2023 2023-03-23 CHLAC 1.4109869737 I #> 3343 2045 3M CC15 2023 2023-03-23 COND 10.2374208545 #> 3344 2045 3M CC15 2023 2023-03-23 DO 1.8609745382 #> 3345 2045 3M CC15 2023 2023-03-23 DOSAT 4.4030540019 #> 3346 2045 3M CC15 2023 2023-03-23 NO23 -5.5214609179 U #> 3347 2045 3M CC15 2023 2023-03-23 SALIN 2.8449093838 #> 3348 2045 3M CC15 2023 2023-03-23 TKN -0.3424903089 #> 3349 2045 3M CC15 2023 2023-03-23 TN -0.3396773676 + #> 3350 2045 3M CC15 2023 2023-03-23 TP -1.5606477483 #> 3351 2045 3M CC15 2023 2023-03-23 TSS 1.7917594692 I #> 3352 2045 3M CC15 2023 2023-03-23 TURB 1.2809338455 #> 3353 2045 3M CC15 2023 2023-05-08 CHLAC 1.1314021115 #> 3354 2045 3M CC15 2023 2023-05-08 COND 10.4129822911 #> 3355 2045 3M CC15 2023 2023-05-08 DO 1.6992786164 #> 3356 2045 3M CC15 2023 2023-05-08 DOSAT 4.3148178850 #> 3357 2045 3M CC15 2023 2023-05-08 NO23 -5.5214609179 U #> 3358 2045 3M CC15 2023 2023-05-08 SALIN 3.0359140632 #> 3359 2045 3M CC15 2023 2023-05-08 TKN -0.3147107448 #> 3360 2045 3M CC15 2023 2023-05-08 TN -0.3119747650 + #> 3361 2045 3M CC15 2023 2023-05-08 TP -1.6607312068 #> 3362 2045 3M CC15 2023 2023-05-08 TSS 2.6390573296 #> 3363 2045 3M CC15 2023 2023-05-08 TURB 1.3350010667 #> 3364 2043 3M CC16 2014 2014-06-26 COND 9.8119751520 #> 3365 2043 3M CC16 2014 2014-06-26 DO 2.4230312461 #> 3366 2043 3M CC16 2014 2014-06-26 DOSAT 5.0801613567 #> 3367 2043 3M CC16 2014 2014-06-26 COND 9.5792797987 #> 3368 2043 3M CC16 2014 2014-06-26 DO 1.2441545940 #> 3369 2043 3M CC16 2014 2014-06-26 DOSAT 3.9852734672 #> 3370 2043 3M CC16 2018 2018-03-07 CHLAC 1.8870696490 #> 3371 2043 3M CC16 2018 2018-03-07 COND 10.1527665775 #> 3372 2043 3M CC16 2018 2018-03-07 DO 1.9878743482 #> 3373 2043 3M CC16 2018 2018-03-07 DOSAT 4.5347477217 #> 3374 2043 3M CC16 2018 2018-03-07 NO23 -5.5214609179 U #> 3375 2043 3M CC16 2018 2018-03-07 SALIN 2.8081971497 + #> 3376 2043 3M CC16 2018 2018-03-07 TKN -0.3424903089 #> 3377 2043 3M CC16 2018 2018-03-07 TN -0.3396773676 + #> 3378 2043 3M CC16 2018 2018-03-07 TP -1.7719568419 #> 3379 2043 3M CC16 2018 2018-03-07 TSS 1.6094379124 I #> 3380 2043 3M CC16 2018 2018-03-07 TURB 1.0986122887 #> 3381 2043 3M CC16 2018 2018-03-07 COND 10.2049615773 #> 3382 2043 3M CC16 2018 2018-03-07 DO 2.0281482473 #> 3383 2043 3M CC16 2018 2018-03-07 DOSAT 4.5653893160 #> 3384 2043 3M CC16 2018 2018-03-07 SALIN 2.8701690506 + #> 3385 2043 3M CC16 2018 2018-04-09 CHLAC 1.9315214116 #> 3386 2043 3M CC16 2018 2018-04-09 COND 10.4399809231 #> 3387 2043 3M CC16 2018 2018-04-09 DO 1.8082887712 #> 3388 2043 3M CC16 2018 2018-04-09 DOSAT 4.4426512565 #> 3389 2043 3M CC16 2018 2018-04-09 NO23 -5.2983173665 I #> 3390 2043 3M CC16 2018 2018-04-09 SALIN 3.0445224377 + #> 3391 2043 3M CC16 2018 2018-04-09 TKN -0.3011050928 #> 3392 2043 3M CC16 2018 2018-04-09 TN -0.2957142441 + #> 3393 2043 3M CC16 2018 2018-04-09 TP -1.6607312068 #> 3394 2043 3M CC16 2018 2018-04-09 TSS 2.0794415417 I #> 3395 2043 3M CC16 2018 2018-04-09 TURB 1.4816045409 #> 3396 2043 3M CC16 2018 2018-05-24 CHLAC 2.2925347571 #> 3397 2043 3M CC16 2018 2018-05-24 COND 9.8201059436 #> 3398 2043 3M CC16 2018 2018-05-24 DO 1.7749523509 #> 3399 2043 3M CC16 2018 2018-05-24 DOSAT 4.3719762988 #> 3400 2043 3M CC16 2018 2018-05-24 NO23 -4.4228486292 #> 3401 2043 3M CC16 2018 2018-05-24 SALIN 2.3360198691 + #> 3402 2043 3M CC16 2018 2018-05-24 TKN -0.1984509387 #> 3403 2043 3M CC16 2018 2018-05-24 TN -0.1839228382 + #> 3404 2043 3M CC16 2018 2018-05-24 TP -1.6094379124 #> 3405 2043 3M CC16 2018 2018-05-24 TSS 2.3025850930 I #> 3406 2043 3M CC16 2018 2018-05-24 TURB 1.6863989536 #> 3407 2043 3M CC16 2018 2018-05-24 COND 9.8362788028 #> 3408 2043 3M CC16 2018 2018-05-24 DO 1.7698546338 #> 3409 2043 3M CC16 2018 2018-05-24 DOSAT 4.3681812279 #> 3410 2043 3M CC16 2018 2018-05-24 SALIN 2.3532782073 + #> 3411 2043 3M CC16 2018 2018-07-23 CHLAC 2.4849066498 #> 3412 2043 3M CC16 2018 2018-07-23 COND 7.2034055211 #> 3413 2043 3M CC16 2018 2018-07-23 DO 1.7833912196 #> 3414 2043 3M CC16 2018 2018-07-23 DOSAT 4.3694478525 #> 3415 2043 3M CC16 2018 2018-07-23 NO23 -2.1202635362 #> 3416 2043 3M CC16 2018 2018-07-23 SALIN -0.4004775666 #> 3417 2043 3M CC16 2018 2018-07-23 TKN 0.1823215568 #> 3418 2043 3M CC16 2018 2018-07-23 TN 0.2776317366 + #> 3419 2043 3M CC16 2018 2018-07-23 TP -1.1394342832 #> 3420 2043 3M CC16 2018 2018-07-23 TSS 1.0986122887 I #> 3421 2043 3M CC16 2018 2018-07-23 TURB 1.0986122887 #> 3422 2043 3M CC16 2018 2018-07-23 COND 7.2034055211 #> 3423 2043 3M CC16 2018 2018-07-23 DO 1.7578579176 #> 3424 2043 3M CC16 2018 2018-07-23 DOSAT 4.3438054219 #> 3425 2043 3M CC16 2018 2018-07-23 SALIN -0.4155154440 #> 3426 2043 3M CC16 2018 2018-08-21 CHLAC 2.8332133441 A #> 3427 2043 3M CC16 2018 2018-08-21 COND 6.5308776277 #> 3428 2043 3M CC16 2018 2018-08-21 DO 1.7083778603 #> 3429 2043 3M CC16 2018 2018-08-21 DOSAT 4.2931954210 #> 3430 2043 3M CC16 2018 2018-08-21 NO23 -2.8824035882 #> 3431 2043 3M CC16 2018 2018-08-21 SALIN -1.1086626245 #> 3432 2043 3M CC16 2018 2018-08-21 TKN 0.0953101798 #> 3433 2043 3M CC16 2018 2018-08-21 TN 0.1449657703 + #> 3434 2043 3M CC16 2018 2018-08-21 TP -1.2378743560 #> 3435 2043 3M CC16 2018 2018-08-21 TSS 1.0986122887 I #> 3436 2043 3M CC16 2018 2018-08-21 TURB 1.2809338455 #> 3437 2043 3M CC16 2018 2018-08-21 COND 6.5337888379 #> 3438 2043 3M CC16 2018 2018-08-21 DO 1.6882490929 #> 3439 2043 3M CC16 2018 2018-08-21 DOSAT 4.2724907476 #> 3440 2043 3M CC16 2018 2018-08-21 SALIN -1.1086626245 #> 3441 2043 3M CC16 2019 2019-02-07 CHLAC 3.1354942159 #> 3442 2043 3M CC16 2019 2019-02-07 COND 9.1573614472 #> 3443 2043 3M CC16 2019 2019-02-07 NO23 -5.5214609179 U #> 3444 2043 3M CC16 2019 2019-02-07 SALIN 1.6733512382 #> 3445 2043 3M CC16 2019 2019-02-07 TKN -0.0725706928 #> 3446 2043 3M CC16 2019 2019-02-07 TN -0.0704224643 + #> 3447 2043 3M CC16 2019 2019-02-07 TP -1.8325814637 #> 3448 2043 3M CC16 2019 2019-02-07 TSS 1.9459101491 I #> 3449 2043 3M CC16 2019 2019-02-07 TURB 1.6863989536 #> 3450 2043 3M CC16 2019 2019-03-13 CHLAC 2.1517622033 #> 3451 2043 3M CC16 2019 2019-03-13 COND 9.7229244488 #> 3452 2043 3M CC16 2019 2019-03-13 DO 1.7369512327 #> 3453 2043 3M CC16 2019 2019-03-13 DOSAT 4.2780540443 + #> 3454 2043 3M CC16 2019 2019-03-13 NO23 -5.5214609179 U #> 3455 2043 3M CC16 2019 2019-03-13 SALIN 2.2823823857 #> 3456 2043 3M CC16 2019 2019-03-13 TKN -0.2613647641 #> 3457 2043 3M CC16 2019 2019-03-13 TN -0.2587707290 + #> 3458 2043 3M CC16 2019 2019-03-13 TP -1.8971199849 #> 3459 2043 3M CC16 2019 2019-03-13 TSS 1.6094379124 I #> 3460 2043 3M CC16 2019 2019-03-13 TURB 1.2527629685 #> 3461 2043 3M CC16 2019 2019-03-13 COND 9.7228046524 #> 3462 2043 3M CC16 2019 2019-03-13 DO 1.6992786164 #> 3463 2043 3M CC16 2019 2019-03-13 DOSAT 4.2398868675 #> 3464 2043 3M CC16 2019 2019-03-13 SALIN 2.2823823857 #> 3465 2043 3M CC16 2019 2019-04-23 CHLAC 2.3978952728 #> 3466 2043 3M CC16 2019 2019-04-23 COND 9.9710060043 #> 3467 2043 3M CC16 2019 2019-04-23 DO 1.8341801851 #> 3468 2043 3M CC16 2019 2019-04-23 DOSAT 4.3707128748 #> 3469 2043 3M CC16 2019 2019-04-23 NO23 -5.5214609179 U #> 3470 2043 3M CC16 2019 2019-04-23 SALIN 2.5533438113 #> 3471 2043 3M CC16 2019 2019-04-23 TKN -0.1863295782 #> 3472 2043 3M CC16 2019 2019-04-23 TN -0.1839228382 + #> 3473 2043 3M CC16 2019 2019-04-23 TP -1.7147984281 #> 3474 2043 3M CC16 2019 2019-04-23 TSS 1.6094379124 I #> 3475 2043 3M CC16 2019 2019-04-23 TURB 1.0296194172 #> 3476 2043 3M CC16 2019 2019-07-22 CHLAC 2.4849066498 #> 3477 2043 3M CC16 2019 2019-07-22 COND 8.7887458819 #> 3478 2043 3M CC16 2019 2019-07-22 DO 1.7850704811 #> 3479 2043 3M CC16 2019 2019-07-22 DOSAT 4.3969152472 #> 3480 2043 3M CC16 2019 2019-07-22 NO23 -5.5214609179 U #> 3481 2043 3M CC16 2019 2019-07-22 SALIN 1.2669476035 #> 3482 2043 3M CC16 2019 2019-07-22 TKN -0.0833816089 #> 3483 2043 3M CC16 2019 2019-07-22 TN -0.0812100554 + #> 3484 2043 3M CC16 2019 2019-07-22 TP -1.2378743560 #> 3485 2043 3M CC16 2019 2019-07-22 TSS 1.0986122887 I #> 3486 2043 3M CC16 2019 2019-07-22 TURB 1.0986122887 #> 3487 2043 3M CC16 2019 2019-09-04 CHLAC 2.3025850930 #> 3488 2043 3M CC16 2019 2019-09-04 COND 7.9875244798 #> 3489 2043 3M CC16 2019 2019-09-04 DO 1.7101878155 #> 3490 2043 3M CC16 2019 2019-09-04 DOSAT 4.2972854062 #> 3491 2043 3M CC16 2019 2019-09-04 NO23 -2.3025850930 #> 3492 2043 3M CC16 2019 2019-09-04 SALIN 0.4187103349 #> 3493 2043 3M CC16 2019 2019-09-04 TKN 0.1823215568 #> 3494 2043 3M CC16 2019 2019-09-04 TN 0.2623642645 + #> 3495 2043 3M CC16 2019 2019-09-04 TP -0.9162907319 #> 3496 2043 3M CC16 2019 2019-09-04 TSS 1.7917594692 I #> 3497 2043 3M CC16 2019 2019-09-04 TURB 1.3350010667 #> 3498 2043 3M CC16 2020 2020-02-18 CHLAC 2.3978952728 #> 3499 2043 3M CC16 2020 2020-02-18 COND 10.0826374182 #> 3500 2043 3M CC16 2020 2020-02-18 DO 2.0202221820 #> 3501 2043 3M CC16 2020 2020-02-18 DOSAT 4.6170987569 #> 3502 2043 3M CC16 2020 2020-02-18 NO23 -5.5214609179 U #> 3503 2043 3M CC16 2020 2020-02-18 SALIN 2.6720775406 #> 3504 2043 3M CC16 2020 2020-02-18 TKN -0.1984509387 #> 3505 2043 3M CC16 2020 2020-02-18 TN -0.1960148839 + #> 3506 2043 3M CC16 2020 2020-02-18 TP -1.7147984281 #> 3507 2043 3M CC16 2020 2020-02-18 TSS 2.4849066498 #> 3508 2043 3M CC16 2020 2020-02-18 TURB 1.5260563035 #> 3509 2043 3M CC16 2020 2020-02-18 COND 10.0856841015 #> 3510 2043 3M CC16 2020 2020-02-18 DO 2.0055258587 #> 3511 2043 3M CC16 2020 2020-02-18 DOSAT 4.6001576442 #> 3512 2043 3M CC16 2020 2020-02-18 SALIN 2.6755270094 #> 3513 2043 3M CC16 2020 2020-06-09 CHLAC 1.9459101491 #> 3514 2043 3M CC16 2020 2020-06-09 COND 9.1632487644 #> 3515 2043 3M CC16 2020 2020-06-09 DO 1.8779371655 #> 3516 2043 3M CC16 2020 2020-06-09 DOSAT 4.4716387934 #> 3517 2043 3M CC16 2020 2020-06-09 NO23 -3.5404594490 #> 3518 2043 3M CC16 2020 2020-06-09 SALIN 1.6695918353 #> 3519 2043 3M CC16 2020 2020-06-09 TKN -0.1743533871 #> 3520 2043 3M CC16 2020 2020-06-09 TN -0.1404121537 + #> 3521 2043 3M CC16 2020 2020-06-09 TP -1.5606477483 #> 3522 2043 3M CC16 2020 2020-06-09 TSS 1.0986122887 I #> 3523 2043 3M CC16 2020 2020-06-09 TURB 0.8329091229 #> 3524 2043 3M CC16 2020 2020-06-09 COND 9.4707797080 #> 3525 2043 3M CC16 2020 2020-06-09 DO 1.8855533485 #> 3526 2043 3M CC16 2020 2020-06-09 DOSAT 4.4986979415 #> 3527 2043 3M CC16 2020 2020-06-09 SALIN 2.0041790572 #> 3528 2043 3M CC16 2020 2020-08-10 COND 9.6776528834 #> 3529 2043 3M CC16 2020 2020-08-10 DO 1.5973653312 #> 3530 2043 3M CC16 2020 2020-08-10 DOSAT 4.2541932632 #> 3531 2043 3M CC16 2020 2020-08-10 SALIN 2.2093727113 #> 3532 2043 3M CC16 2020 2020-09-22 CHLAC 2.1041341543 #> 3533 2043 3M CC16 2020 2020-09-22 COND 6.8012830345 #> 3534 2043 3M CC16 2020 2020-09-22 DO 1.8500283774 #> 3535 2043 3M CC16 2020 2020-09-22 DOSAT 4.3932138241 #> 3536 2043 3M CC16 2020 2020-09-22 NO23 -2.6882475738 #> 3537 2043 3M CC16 2020 2020-09-22 SALIN -0.8209805521 #> 3538 2043 3M CC16 2020 2020-09-22 TKN 0.1823215568 #> 3539 2043 3M CC16 2020 2020-09-22 TN 0.2374408560 + #> 3540 2043 3M CC16 2020 2020-09-22 TP -1.0498221245 #> 3541 2043 3M CC16 2020 2020-09-22 TSS 1.3862943611 I #> 3542 2043 3M CC16 2020 2020-09-22 TURB 1.1314021115 A #> 3543 2043 3M CC16 2020 2020-10-20 CHLAC 2.3978952728 #> 3544 2043 3M CC16 2020 2020-10-20 COND 8.8590793179 #> 3545 2043 3M CC16 2020 2020-10-20 DO 1.7281094422 #> 3546 2043 3M CC16 2020 2020-10-20 DOSAT 4.2835865619 #> 3547 2043 3M CC16 2020 2020-10-20 NO23 -2.2072749132 #> 3548 2043 3M CC16 2020 2020-10-20 SALIN 1.3480731483 #> 3549 2043 3M CC16 2020 2020-10-20 TKN 0.1823215568 #> 3550 2043 3M CC16 2020 2020-10-20 TN 0.2700271372 + #> 3551 2043 3M CC16 2020 2020-10-20 TP -1.1086626245 #> 3552 2043 3M CC16 2020 2020-10-20 TSS 1.7917594692 I #> 3553 2043 3M CC16 2020 2020-10-20 TURB 1.3350010667 #> 3554 2043 3M CC16 2020 2020-12-14 CHLAC 2.6390573296 #> 3555 2043 3M CC16 2020 2020-12-14 COND 9.3722891390 #> 3556 2043 3M CC16 2020 2020-12-14 DO 2.0554049639 #> 3557 2043 3M CC16 2020 2020-12-14 DOSAT 4.5261269786 #> 3558 2043 3M CC16 2020 2020-12-14 NO23 -5.5214609179 U #> 3559 2043 3M CC16 2020 2020-12-14 SALIN 1.9035989510 #> 3560 2043 3M CC16 2020 2020-12-14 TKN -0.0408219945 #> 3561 2043 3M CC16 2020 2020-12-14 TN -0.0387408283 + #> 3562 2043 3M CC16 2020 2020-12-14 TP -1.6094379124 #> 3563 2043 3M CC16 2020 2020-12-14 TSS 1.6094379124 I #> 3564 2043 3M CC16 2020 2020-12-14 TURB 1.2237754316 #> 3565 2043 3M CC16 2021 2021-02-03 CHLAC 2.3978952728 #> 3566 2043 3M CC16 2021 2021-02-03 COND 9.8437906253 #> 3567 2043 3M CC16 2021 2021-02-03 DO 2.0360119838 #> 3568 2043 3M CC16 2021 2021-02-03 DOSAT 4.4379342666 #> 3569 2043 3M CC16 2021 2021-02-03 NO23 -5.5214609179 U #> 3570 2043 3M CC16 2021 2021-02-03 SALIN 2.4185887688 #> 3571 2043 3M CC16 2021 2021-02-03 TKN -0.2484613593 #> 3572 2043 3M CC16 2021 2021-02-03 TN -0.2459005384 + #> 3573 2043 3M CC16 2021 2021-02-03 TP -2.2072749132 #> 3574 2043 3M CC16 2021 2021-02-03 TSS 1.3862943611 I #> 3575 2043 3M CC16 2021 2021-02-03 TURB 1.0986122887 #> 3576 2043 3M CC16 2021 2021-03-23 CHLAC 2.5649493575 #> 3577 2043 3M CC16 2021 2021-03-23 COND 10.0172179429 #> 3578 2043 3M CC16 2021 2021-03-23 DO 1.8484548129 #> 3579 2043 3M CC16 2021 2021-03-23 DOSAT 4.3320482649 #> 3580 2043 3M CC16 2021 2021-03-23 NO23 -5.5214609179 U #> 3581 2043 3M CC16 2021 2021-03-23 SALIN 2.6056482675 #> 3582 2043 3M CC16 2021 2021-03-23 TKN -0.1165338163 #> 3583 2043 3M CC16 2021 2021-03-23 TN -0.1142891464 + #> 3584 2043 3M CC16 2021 2021-03-23 TP -1.8971199849 #> 3585 2043 3M CC16 2021 2021-03-23 TSS 1.7917594692 I #> 3586 2043 3M CC16 2021 2021-03-23 TURB 1.3862943611 #> 3587 2043 3M CC16 2021 2021-05-05 CHLAC 2.2823823857 #> 3588 2043 3M CC16 2021 2021-05-05 COND 10.2634321453 #> 3589 2043 3M CC16 2021 2021-05-05 DO 1.7263316639 #> 3590 2043 3M CC16 2021 2021-05-05 DOSAT 4.4200447019 #> 3591 2043 3M CC16 2021 2021-05-05 NO23 -5.5214609179 I #> 3592 2043 3M CC16 2021 2021-05-05 SALIN 2.8650539499 #> 3593 2043 3M CC16 2021 2021-05-05 TKN -0.0833816089 #> 3594 2043 3M CC16 2021 2021-05-05 TN -0.0790432073 + #> 3595 2043 3M CC16 2021 2021-05-05 TP -1.5606477483 #> 3596 2043 3M CC16 2021 2021-05-05 TSS 2.0794415417 I #> 3597 2043 3M CC16 2021 2021-05-05 TURB 1.4816045409 #> 3598 2043 3M CC16 2021 2021-06-03 CHLAC 2.4849066498 #> 3599 2043 3M CC16 2021 2021-06-03 COND 10.3258753278 #> 3600 2043 3M CC16 2021 2021-06-03 DO 1.6524974019 #> 3601 2043 3M CC16 2021 2021-06-03 DOSAT 4.3094559418 #> 3602 2043 3M CC16 2021 2021-06-03 NO23 -5.5214609179 U #> 3603 2043 3M CC16 2021 2021-06-03 SALIN 2.9375733594 #> 3604 2043 3M CC16 2021 2021-06-03 TKN 0.0000000000 #> 3605 2043 3M CC16 2021 2021-06-03 TN 0.0019980027 + #> 3606 2043 3M CC16 2021 2021-06-03 TP -1.6607312068 #> 3607 2043 3M CC16 2021 2021-06-03 TSS 2.0794415417 I #> 3608 2043 3M CC16 2021 2021-06-03 TURB 1.4109869737 #> 3609 2043 3M CC16 2021 2021-07-01 CHLAC 3.0910424534 #> 3610 2043 3M CC16 2021 2021-07-01 COND 10.1819522754 #> 3611 2043 3M CC16 2021 2021-07-01 DO 1.6956156087 #> 3612 2043 3M CC16 2021 2021-07-01 DOSAT 4.3567088267 #> 3613 2043 3M CC16 2021 2021-07-01 NO23 -3.0791138825 #> 3614 2043 3M CC16 2021 2021-07-01 SALIN 2.7775762638 #> 3615 2043 3M CC16 2021 2021-07-01 TKN -0.2357223335 #> 3616 2043 3M CC16 2021 2021-07-01 TN -0.1791266659 + #> 3617 2043 3M CC16 2021 2021-07-01 TP -1.5606477483 #> 3618 2043 3M CC16 2021 2021-07-01 TSS 2.3025850930 #> 3619 2043 3M CC16 2021 2021-07-01 TURB 1.7404661748 #> 3620 2043 3M CC16 2022 2022-02-22 CHLAC 1.0986122887 #> 3621 2043 3M CC16 2022 2022-02-22 COND 10.3057809695 #> 3622 2043 3M CC16 2022 2022-02-22 DO 1.8794650496 #> 3623 2043 3M CC16 2022 2022-02-22 DOSAT 4.4543472963 #> 3624 2043 3M CC16 2022 2022-02-22 NO23 -4.9618451299 I #> 3625 2043 3M CC16 2022 2022-02-22 SALIN 2.9199305601 #> 3626 2043 3M CC16 2022 2022-02-22 TKN -0.4307829161 #> 3627 2043 3M CC16 2022 2022-02-22 TN -0.4246479275 + #> 3628 2043 3M CC16 2022 2022-02-22 TP -2.3859667019 #> 3629 2043 3M CC16 2022 2022-02-22 TSS 2.3025850930 I #> 3630 2043 3M CC16 2022 2022-02-22 TURB 0.6931471806 #> 3631 2043 3M CC16 2022 2022-06-07 CHLAC 2.7080502011 #> 3632 2043 3M CC16 2022 2022-06-07 COND 10.2345882454 #> 3633 2043 3M CC16 2022 2022-06-07 DO 1.4182774070 #> 3634 2043 3M CC16 2022 2022-06-07 DOSAT 4.1026433650 #> 3635 2043 3M CC16 2022 2022-06-07 NO23 -5.5214609179 U #> 3636 2043 3M CC16 2022 2022-06-07 SALIN 2.8361502037 #> 3637 2043 3M CC16 2022 2022-06-07 TKN -0.1165338163 #> 3638 2043 3M CC16 2022 2022-06-07 TN -0.1142891464 + #> 3639 2043 3M CC16 2022 2022-06-07 TP -1.6607312068 #> 3640 2043 3M CC16 2022 2022-06-07 TSS 2.5649493575 #> 3641 2043 3M CC16 2022 2022-06-07 TURB 1.6863989536 #> 3642 2043 3M CC16 2022 2022-08-15 CHLAC 2.9957322736 A #> 3643 2043 3M CC16 2022 2022-08-15 COND 8.1639409548 #> 3644 2043 3M CC16 2022 2022-08-15 DO 1.4350845253 #> 3645 2043 3M CC16 2022 2022-08-15 DOSAT 4.0145795938 #> 3646 2043 3M CC16 2022 2022-08-15 NO23 -4.7105307016 I #> 3647 2043 3M CC16 2022 2022-08-15 SALIN 0.6043159669 #> 3648 2043 3M CC16 2022 2022-08-15 TKN -0.1278333715 #> 3649 2043 3M CC16 2022 2022-08-15 TN -0.1232982163 + #> 3650 2043 3M CC16 2022 2022-08-15 TP -1.3093333200 #> 3651 2043 3M CC16 2022 2022-08-15 TSS 1.3862943611 I #> 3652 2043 3M CC16 2022 2022-08-15 TURB 1.2527629685 #> 3653 2043 3M CC16 2022 2022-12-15 CHLAC 4.8675344505 #> 3654 2043 3M CC16 2022 2022-12-15 COND 9.6068992706 #> 3655 2043 3M CC16 2022 2022-12-15 DO 2.1781550146 #> 3656 2043 3M CC16 2022 2022-12-15 DOSAT 4.6950108900 #> 3657 2043 3M CC16 2022 2022-12-15 NO23 -5.5214609179 U #> 3658 2043 3M CC16 2022 2022-12-15 SALIN 2.1575593209 #> 3659 2043 3M CC16 2022 2022-12-15 TKN 0.5306282511 #> 3660 2043 3M CC16 2022 2022-12-15 TN 0.5318040302 + #> 3661 2043 3M CC16 2022 2022-12-15 TP -1.1711829815 #> 3662 2043 3M CC16 2022 2022-12-15 TSS 2.8903717579 #> 3663 2043 3M CC16 2022 2022-12-15 TURB 1.8562979904 #> 3664 2043 3M CC16 2021 2021-02-03 CHLAC 3.1354942159 #> 3665 2043 3M CC16 2021 2021-02-03 COND 9.5834200199 #> 3666 2043 3M CC16 2021 2021-02-03 DO 2.0041790572 #> 3667 2043 3M CC16 2021 2021-02-03 DOSAT 4.4042772436 #> 3668 2043 3M CC16 2021 2021-02-03 NO23 -5.5214609179 U #> 3669 2043 3M CC16 2021 2021-02-03 SALIN 2.1365305087 #> 3670 2043 3M CC16 2021 2021-02-03 TKN -0.1278333715 #> 3671 2043 3M CC16 2021 2021-02-03 TN -0.1255632230 + #> 3672 2043 3M CC16 2021 2021-02-03 TP -2.1202635362 #> 3673 2043 3M CC16 2021 2021-02-03 TSS 1.9459101491 I #> 3674 2043 3M CC16 2021 2021-02-03 TURB 1.7578579176 #> 3675 2043 3M CC16 2021 2021-03-23 CHLAC 3.2188758249 #> 3676 2043 3M CC16 2021 2021-03-23 COND 9.8242819944 #> 3677 2043 3M CC16 2021 2021-03-23 DO 1.7867469274 #> 3678 2043 3M CC16 2021 2021-03-23 DOSAT 4.2640873368 #> 3679 2043 3M CC16 2021 2021-03-23 NO23 -5.5214609179 U #> 3680 2043 3M CC16 2021 2021-03-23 SALIN 2.3951642743 #> 3681 2043 3M CC16 2021 2021-03-23 TKN 0.0953101798 #> 3682 2043 3M CC16 2021 2021-03-23 TN 0.0971267107 + #> 3683 2043 3M CC16 2021 2021-03-23 TP -1.6094379124 #> 3684 2043 3M CC16 2021 2021-03-23 TSS 2.3978952728 #> 3685 2043 3M CC16 2021 2021-03-23 TURB 2.0412203289 #> 3686 2043 3M CC16 2021 2021-05-05 CHLAC 2.7725887222 #> 3687 2043 3M CC16 2021 2021-05-05 COND 10.1696522784 #> 3688 2043 3M CC16 2021 2021-05-05 DO 1.3711807233 #> 3689 2043 3M CC16 2021 2021-05-05 DOSAT 4.0342406382 #> 3690 2043 3M CC16 2021 2021-05-05 NO23 -5.5214609179 U #> 3691 2043 3M CC16 2021 2021-05-05 SALIN 2.7638002162 #> 3692 2043 3M CC16 2021 2021-05-05 TKN -0.0304592075 #> 3693 2043 3M CC16 2021 2021-05-05 TN -0.0283994745 + #> 3694 2043 3M CC16 2021 2021-05-05 TP -1.5606477483 #> 3695 2043 3M CC16 2021 2021-05-05 TSS 1.7917594692 I #> 3696 2043 3M CC16 2021 2021-05-05 TURB 1.5260563035 #> 3697 2043 3M CC16 2021 2021-06-03 CHLAC 2.8903717579 #> 3698 2043 3M CC16 2021 2021-06-03 COND 10.2473963549 #> 3699 2043 3M CC16 2021 2021-06-03 DO 1.5475625087 #> 3700 2043 3M CC16 2021 2021-06-03 DOSAT 4.2002049529 #> 3701 2043 3M CC16 2021 2021-06-03 NO23 -4.9618451299 I #> 3702 2043 3M CC16 2021 2021-06-03 SALIN 2.8518619031 #> 3703 2043 3M CC16 2021 2021-06-03 TKN 0.1823215568 #> 3704 2043 3M CC16 2021 2021-06-03 TN 0.1856493469 + #> 3705 2043 3M CC16 2021 2021-06-03 TP -1.5606477483 #> 3706 2043 3M CC16 2021 2021-06-03 TSS 2.3978952728 #> 3707 2043 3M CC16 2021 2021-06-03 TURB 1.6486586256 #> 3708 2043 3M CC16 2021 2021-07-01 CHLAC 3.4339872045 #> 3709 2043 3M CC16 2021 2021-07-01 COND 10.0458547938 #> 3710 2043 3M CC16 2021 2021-07-01 DO 1.9837562915 #> 3711 2043 3M CC16 2021 2021-07-01 DOSAT 4.6091622073 #> 3712 2043 3M CC16 2021 2021-07-01 NO23 -3.4420193762 #> 3713 2043 3M CC16 2021 2021-07-01 SALIN 2.6304489551 #> 3714 2043 3M CC16 2021 2021-07-01 TKN -0.0304592075 #> 3715 2043 3M CC16 2021 2021-07-01 TN 0.0019980027 + #> 3716 2043 3M CC16 2021 2021-07-01 TP -1.3862943611 #> 3717 2043 3M CC16 2021 2021-07-01 TSS 1.7917594692 I #> 3718 2043 3M CC16 2021 2021-07-01 TURB 1.6677068206 #> 3719 2043 3M CC16 2022 2022-02-22 CHLAC 1.6094379124 #> 3720 2043 3M CC16 2022 2022-02-22 COND 10.1823685085 #> 3721 2043 3M CC16 2022 2022-02-22 DO 1.7422190237 #> 3722 2043 3M CC16 2022 2022-02-22 DOSAT 4.3148178850 #> 3723 2043 3M CC16 2022 2022-02-22 NO23 -4.6051701860 I #> 3724 2043 3M CC16 2022 2022-02-22 SALIN 2.7788192720 #> 3725 2043 3M CC16 2022 2022-02-22 TKN -0.2484613593 #> 3726 2043 3M CC16 2022 2022-02-22 TN -0.2433462586 + #> 3727 2043 3M CC16 2022 2022-02-22 TP -2.3025850930 #> 3728 2043 3M CC16 2022 2022-02-22 TSS 2.4849066498 #> 3729 2043 3M CC16 2022 2022-02-22 TURB 1.6486586256 #> 3730 2043 3M CC16 2022 2022-06-07 CHLAC 2.1400661635 #> 3731 2043 3M CC16 2022 2022-06-07 COND 10.2020724724 #> 3732 2043 3M CC16 2022 2022-06-07 DO 1.5151272330 #> 3733 2043 3M CC16 2022 2022-06-07 DOSAT 4.1713056034 #> 3734 2043 3M CC16 2022 2022-06-07 NO23 -3.9633162998 #> 3735 2043 3M CC16 2022 2022-06-07 SALIN 2.7997173896 #> 3736 2043 3M CC16 2022 2022-06-07 TKN -0.1625189295 #> 3737 2043 3M CC16 2022 2022-06-07 TN -0.1404121537 + #> 3738 2043 3M CC16 2022 2022-06-07 TP -1.4271163556 #> 3739 2043 3M CC16 2022 2022-06-07 TSS 2.3025850930 #> 3740 2043 3M CC16 2022 2022-06-07 TURB 1.3350010667 #> 3741 2043 3M CC16 2022 2022-08-15 CHLAC 3.0445224377 #> 3742 2043 3M CC16 2022 2022-08-15 COND 7.8363697605 #> 3743 2043 3M CC16 2022 2022-08-15 DO 1.5539252025 #> 3744 2043 3M CC16 2022 2022-08-15 DOSAT 4.1319614258 #> 3745 2043 3M CC16 2022 2022-08-15 NO23 -4.0173835211 #> 3746 2043 3M CC16 2022 2022-08-15 SALIN 0.2623642645 #> 3747 2043 3M CC16 2022 2022-08-15 TKN -0.1863295782 #> 3748 2043 3M CC16 2022 2022-08-15 TN -0.1648746432 + #> 3749 2043 3M CC16 2022 2022-08-15 TP -1.6094379124 #> 3750 2043 3M CC16 2022 2022-08-15 TSS 2.0794415417 I #> 3751 2043 3M CC16 2022 2022-08-15 TURB 1.4109869737 #> 3752 2043 3M CC16 2022 2022-12-15 CHLAC 3.6109179126 #> 3753 2043 3M CC16 2022 2022-12-15 COND 9.5544264071 #> 3754 2043 3M CC16 2022 2022-12-15 DO 1.8405496334 #> 3755 2043 3M CC16 2022 2022-12-15 DOSAT 4.3554259529 #> 3756 2043 3M CC16 2022 2022-12-15 NO23 -5.5214609179 U #> 3757 2043 3M CC16 2022 2022-12-15 SALIN 2.0992441690 #> 3758 2043 3M CC16 2022 2022-12-15 TKN -0.1743533871 #> 3759 2043 3M CC16 2022 2022-12-15 TN -0.1719752647 + #> 3760 2043 3M CC16 2022 2022-12-15 TP -1.7719568419 #> 3761 2043 3M CC16 2022 2022-12-15 TSS 1.7917594692 I #> 3762 2043 3M CC16 2022 2022-12-15 TURB 1.2809338455 #> 3763 2048A 3M CC18 2014 2014-01-06 DO 1.7917594692 #> 3764 2048A 3M CC18 2014 2014-01-06 DOSAT 4.3107991254 + #> 3765 2048A 3M CC18 2014 2014-01-06 NO23 -4.7105307016 I #> 3766 2048A 3M CC18 2014 2014-01-06 SALIN 3.0819099698 #> 3767 2048A 3M CC18 2014 2014-01-06 TKN -0.3011050928 #> 3768 2048A 3M CC18 2014 2014-01-06 TN -0.2957142441 + #> 3769 2048A 3M CC18 2014 2014-01-06 TP -2.7333680091 #> 3770 2048A 3M CC18 2014 2014-02-03 CHLAC 1.3350010667 #> 3771 2048A 3M CC18 2014 2014-02-03 COLOR 3.2188758249 #> 3772 2048A 3M CC18 2014 2014-02-03 DO 1.6677068206 #> 3773 2048A 3M CC18 2014 2014-02-03 DOSAT 4.1820501426 + #> 3774 2048A 3M CC18 2014 2014-02-03 NO23 -4.5098600062 #> 3775 2048A 3M CC18 2014 2014-02-03 SALIN 2.9496883351 #> 3776 2048A 3M CC18 2014 2014-02-03 TKN -0.6348782724 #> 3777 2048A 3M CC18 2014 2014-02-03 TN -0.6143360001 + #> 3778 2048A 3M CC18 2014 2014-02-03 TP -2.5133061243 #> 3779 2048A 3M CC18 2014 2014-02-03 TURB 0.4700036292 #> 3780 2048A 3M CC18 2014 2014-03-03 CHLAC 1.0296194172 #> 3781 2048A 3M CC18 2014 2014-03-03 COLOR 3.2580965380 #> 3782 2048A 3M CC18 2014 2014-03-03 DOSAT 4.3201512310 + #> 3783 2048A 3M CC18 2014 2014-03-03 NO23 -5.5214609179 I #> 3784 2048A 3M CC18 2014 2014-03-03 SALIN 3.0349529867 #> 3785 2048A 3M CC18 2014 2014-03-03 TKN -0.4155154440 #> 3786 2048A 3M CC18 2014 2014-03-03 TN -0.4094731295 + #> 3787 2048A 3M CC18 2014 2014-03-03 TP -2.3859667019 #> 3788 2048A 3M CC18 2014 2014-03-03 TURB 0.6418538862 #> 3789 2048A 3M CC18 2014 2014-04-07 CHLAC 1.5892352051 #> 3790 2048A 3M CC18 2014 2014-04-07 COLOR 3.3322045102 #> 3791 2048A 3M CC18 2014 2014-04-07 DO 2.2082744135 #> 3792 2048A 3M CC18 2014 2014-04-07 DOSAT 4.7492705300 + #> 3793 2048A 3M CC18 2014 2014-04-07 NO23 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CC18 2014 2014-06-02 NO23 -4.6051701860 #> 3812 2048A 3M CC18 2014 2014-06-02 SALIN 3.1441522787 #> 3813 2048A 3M CC18 2014 2014-06-02 TKN -0.4004775666 #> 3814 2048A 3M CC18 2014 2014-06-02 TN -0.3856624808 + #> 3815 2048A 3M CC18 2014 2014-06-02 TP -1.5606477483 #> 3816 2048A 3M CC18 2014 2014-06-02 TURB 0.9555114450 #> 3817 2048A 3M CC18 2014 2014-08-04 CHLAC 1.9740810260 #> 3818 2048A 3M CC18 2014 2014-08-04 COLOR 4.7874917428 #> 3819 2048A 3M CC18 2014 2014-08-04 DO 0.7371640660 #> 3820 2048A 3M CC18 2014 2014-08-04 DOSAT 3.3568971228 + #> 3821 2048A 3M CC18 2014 2014-08-04 NO23 -4.8283137373 I #> 3822 2048A 3M CC18 2014 2014-08-04 TKN 0.0953101798 #> 3823 2048A 3M CC18 2014 2014-08-04 TN 0.0989399479 + #> 3824 2048A 3M CC18 2014 2014-08-04 TP -1.3862943611 #> 3825 2048A 3M CC18 2014 2014-08-04 TURB 1.2527629685 #> 3826 2048A 3M CC18 2014 2014-09-08 CHLAC 1.8082887712 #> 3827 2048A 3M CC18 2014 2014-09-08 COLOR 4.1108738642 #> 3828 2048A 3M CC18 2014 2014-09-08 DO 1.3083328197 #> 3829 2048A 3M CC18 2014 2014-09-08 DOSAT 3.8958936235 + #> 3830 2048A 3M CC18 2014 2014-09-08 NO23 -4.5098600062 #> 3831 2048A 3M CC18 2014 2014-09-08 SALIN 2.1162555148 #> 3832 2048A 3M CC18 2014 2014-09-08 TKN -0.0833816089 #> 3833 2048A 3M CC18 2014 2014-09-08 TN -0.0714960017 + #> 3834 2048A 3M CC18 2014 2014-09-08 TP -1.4696759701 #> 3835 2048A 3M CC18 2014 2014-09-08 TURB 0.5877866649 #> 3836 2048A 3M CC18 2014 2014-10-06 CHLAC 2.3978952728 #> 3837 2048A 3M CC18 2014 2014-10-06 COLOR 5.1929568509 #> 3838 2048A 3M CC18 2014 2014-10-06 DO 2.1400661635 #> 3839 2048A 3M CC18 2014 2014-10-06 DOSAT 4.6376373761 + #> 3840 2048A 3M CC18 2014 2014-10-06 NO23 -3.9633162998 #> 3841 2048A 3M CC18 2014 2014-10-06 SALIN 0.5877866649 #> 3842 2048A 3M CC18 2014 2014-10-06 TKN -0.0943106795 #> 3843 2048A 3M CC18 2014 2014-10-06 TN -0.0736465402 + #> 3844 2048A 3M CC18 2014 2014-10-06 TP -1.8971199849 #> 3845 2048A 3M CC18 2014 2014-10-06 TURB 0.4700036292 A #> 3846 2048A 3M CC18 2014 2014-11-03 CHLAC 1.8405496334 #> 3847 2048A 3M CC18 2014 2014-11-03 COLOR 4.5325994932 #> 3848 2048A 3M CC18 2014 2014-11-03 NO23 -4.2686979494 #> 3849 2048A 3M CC18 2014 2014-11-03 SALIN 2.5726122302 #> 3850 2048A 3M CC18 2014 2014-11-03 TKN -0.1743533871 #> 3851 2048A 3M CC18 2014 2014-11-03 TN -0.1578240852 + #> 3852 2048A 3M CC18 2014 2014-11-03 TP -1.6607312068 #> 3853 2048A 3M CC18 2014 2014-11-03 TURB 0.5306282511 A #> 3854 2048A 3M CC18 2014 2014-12-01 CHLAC 0.6418538862 #> 3855 2048A 3M CC18 2014 2014-12-01 COLOR 3.8712010109 A #> 3856 2048A 3M CC18 2014 2014-12-01 DO 1.7047480922 #> 3857 2048A 3M CC18 2014 2014-12-01 SALIN 2.6100697927 #> 3858 2048A 3M CC18 2014 2014-12-01 TN -0.0899247075 + #> 3859 2048A 3M CC18 2014 2014-12-01 TURB 0.0000000000 #> 3860 2048A 3M CC18 2015 2015-01-05 CHLAC 2.0149030205 #> 3861 2048A 3M CC18 2015 2015-01-05 COLOR 3.5835189385 #> 3862 2048A 3M CC18 2015 2015-01-05 DO 1.7578579176 #> 3863 2048A 3M CC18 2015 2015-01-05 DOSAT 4.3333614627 + #> 3864 2048A 3M 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2.9285235239 #> 3882 2048A 3M CC18 2015 2015-03-02 TN -0.3147107448 + #> 3883 2048A 3M CC18 2015 2015-03-02 TURB 0.7884573604 #> 3884 2048A 3M CC18 2015 2015-04-06 CHLAC 3.2580965380 A #> 3885 2048A 3M CC18 2015 2015-04-06 COLOR 3.6109179126 #> 3886 2048A 3M CC18 2015 2015-04-06 DO 2.3025850930 #> 3887 2048A 3M CC18 2015 2015-04-06 DOSAT 4.8706066495 + #> 3888 2048A 3M CC18 2015 2015-04-06 NO23 -4.5098600062 #> 3889 2048A 3M CC18 2015 2015-04-06 SALIN 2.7278528284 #> 3890 2048A 3M CC18 2015 2015-04-06 TKN 0.4700036292 #> 3891 2048A 3M CC18 2015 2015-04-06 TN 0.4768551042 + #> 3892 2048A 3M CC18 2015 2015-04-06 TP -1.2378743560 #> 3893 2048A 3M CC18 2015 2015-04-06 TURB 1.5892352051 #> 3894 2048A 3M CC18 2015 2015-06-01 CHLAC 1.3083328197 #> 3895 2048A 3M CC18 2015 2015-06-01 COLOR 3.6109179126 #> 3896 2048A 3M CC18 2015 2015-06-01 DO 1.3609765531 #> 3897 2048A 3M CC18 2015 2015-06-01 DOSAT 3.9834130015 + #> 3898 2048A 3M CC18 2015 2015-06-01 NO23 -4.7105307016 I #> 3899 2048A 3M CC18 2015 2015-06-01 SALIN 2.9285235239 #> 3900 2048A 3M CC18 2015 2015-06-01 TKN -0.3710636814 #> 3901 2048A 3M CC18 2015 2015-06-01 TN -0.3652833185 + #> 3902 2048A 3M CC18 2015 2015-06-01 TP -1.5141277326 #> 3903 2048A 3M CC18 2015 2015-06-01 TURB 0.9555114450 #> 3904 2048A 3M CC18 2015 2015-08-03 CHLAC 1.6677068206 #> 3905 2048A 3M CC18 2015 2015-08-03 COLOR 5.1929568509 #> 3906 2048A 3M CC18 2015 2015-08-03 NO23 -4.5098600062 #> 3907 2048A 3M CC18 2015 2015-08-03 SALIN 2.1282317058 #> 3908 2048A 3M CC18 2015 2015-08-03 TKN -0.0618754037 #> 3909 2048A 3M CC18 2015 2015-08-03 TN -0.0502412164 + #> 3910 2048A 3M CC18 2015 2015-08-03 TP -1.4271163556 #> 3911 2048A 3M CC18 2015 2015-08-03 TURB 0.7884573604 #> 3912 2048A 3M CC18 2015 2015-09-08 CHLAC 1.7749523509 #> 3913 2048A 3M CC18 2015 2015-09-08 COLOR 5.0751738152 #> 3914 2048A 3M CC18 2015 2015-09-08 DO 1.2527629685 #> 3915 2048A 3M CC18 2015 2015-09-08 DOSAT 3.6163087613 + #> 3916 2048A 3M CC18 2015 2015-09-08 NO23 -2.9374633654 #> 3917 2048A 3M CC18 2015 2015-09-08 SALIN 1.0647107370 #> 3918 2048A 3M CC18 2015 2015-09-08 TKN 0.0000000000 #> 3919 2048A 3M CC18 2015 2015-09-08 TN 0.0516432332 + #> 3920 2048A 3M CC18 2015 2015-09-08 TP -1.5606477483 #> 3921 2048A 3M CC18 2015 2015-09-08 TURB 0.0953101798 #> 3922 2048A 3M CC18 2015 2015-10-05 CHLAC 0.6418538862 #> 3923 2048A 3M CC18 2015 2015-10-05 COLOR 5.0751738152 #> 3924 2048A 3M CC18 2015 2015-10-05 DOSAT 4.6091622073 + #> 3925 2048A 3M CC18 2015 2015-10-05 NO23 -3.0576076773 #> 3926 2048A 3M CC18 2015 2015-10-05 SALIN 1.9459101491 #> 3927 2048A 3M CC18 2015 2015-10-05 TKN -0.0304592075 #> 3928 2048A 3M CC18 2015 2015-10-05 TN 0.0168571171 + #> 3929 2048A 3M CC18 2015 2015-10-05 TP -1.2039728043 #> 3930 2048A 3M CC18 2015 2015-10-05 TURB 0.6418538862 #> 3931 2048A 3M CC18 2015 2015-12-07 CHLAC 0.8754687374 #> 3932 2048A 3M CC18 2015 2015-12-07 COLOR 3.9120230054 #> 3933 2048A 3M CC18 2015 2015-12-07 DO 2.5416019935 #> 3934 2048A 3M CC18 2015 2015-12-07 NO23 -3.4420193762 #> 3935 2048A 3M CC18 2015 2015-12-07 TKN -0.2876820725 #> 3936 2048A 3M CC18 2015 2015-12-07 TN -0.2459005384 + #> 3937 2048A 3M CC18 2015 2015-12-07 TP -2.2072749132 #> 3938 2048A 3M CC18 2015 2015-12-07 TURB 0.1823215568 #> 3939 2048A 3M CC18 2016 2016-01-04 CHLAC 4.4188406078 #> 3940 2048A 3M CC18 2016 2016-01-04 COLOR 3.6888794541 A #> 3941 2048A 3M CC18 2016 2016-01-04 DOSAT 3.6888794541 + #> 3942 2048A 3M CC18 2016 2016-01-04 NO23 -3.2968373663 #> 3943 2048A 3M CC18 2016 2016-01-04 SALIN 2.8094026954 #> 3944 2048A 3M CC18 2016 2016-01-04 TKN -0.1863295782 #> 3945 2048A 3M CC18 2016 2016-01-04 TN -0.1427163022 + #> 3946 2048A 3M CC18 2016 2016-01-04 TP -2.3025850930 #> 3947 2048A 3M CC18 2016 2016-01-04 TURB 0.6931471806 #> 3948 2048A 3M CC18 2016 2016-02-01 CHLAC 0.8329091229 #> 3949 2048A 3M CC18 2016 2016-02-01 COLOR 4.4659081187 #> 3950 2048A 3M CC18 2016 2016-02-01 DO 1.5686159179 #> 3951 2048A 3M CC18 2016 2016-02-01 DOSAT 4.0018637094 + #> 3952 2048A 3M CC18 2016 2016-02-01 NO23 -4.8283137373 I #> 3953 2048A 3M CC18 2016 2016-02-01 SALIN 2.0281482473 #> 3954 2048A 3M CC18 2016 2016-02-01 TKN -0.4155154440 #> 3955 2048A 3M CC18 2016 2016-02-01 TN -0.4094731295 + #> 3956 2048A 3M CC18 2016 2016-02-01 TP -2.4304184645 #> 3957 2048A 3M CC18 2016 2016-02-01 TURB 0.2623642645 A #> 3958 2048A 3M CC18 2016 2016-03-07 CHLAC 0.0953101798 I #> 3959 2048A 3M CC18 2016 2016-03-07 COLOR 4.1108738642 #> 3960 2048A 3M CC18 2016 2016-03-07 DOSAT 4.2076732475 + #> 3961 2048A 3M CC18 2016 2016-03-07 NO23 -4.8283137373 U #> 3962 2048A 3M CC18 2016 2016-03-07 SALIN 1.9740810260 #> 3963 2048A 3M CC18 2016 2016-03-07 TN -0.0790432073 + #> 3964 2048A 3M CC18 2016 2016-03-07 TURB 0.6931471806 #> 3965 2048A 3M CC18 2016 2016-04-04 CHLAC 1.6677068206 #> 3966 2048A 3M CC18 2016 2016-04-04 COLOR 3.8918202981 #> 3967 2048A 3M CC18 2016 2016-04-04 DO 1.6677068206 #> 3968 2048A 3M CC18 2016 2016-04-04 DOSAT 4.1941898972 + #> 3969 2048A 3M CC18 2016 2016-04-04 NO23 -5.2983173665 I #> 3970 2048A 3M CC18 2016 2016-04-04 SALIN 2.3978952728 #> 3971 2048A 3M CC18 2016 2016-04-04 TKN -0.3011050928 #> 3972 2048A 3M CC18 2016 2016-04-04 TN -0.2957142441 + #> 3973 2048A 3M CC18 2016 2016-04-04 TP -1.9661128564 #> 3974 2048A 3M CC18 2016 2016-04-04 TURB 1.0647107370 #> 3975 2048A 3M CC18 2016 2016-05-02 CHLAC 1.1314021115 #> 3976 2048A 3M CC18 2016 2016-05-02 COLOR 3.8918202981 A #> 3977 2048A 3M CC18 2016 2016-05-02 DO 1.3862943611 #> 3978 2048A 3M CC18 2016 2016-05-02 DOSAT 4.0109629533 + #> 3979 2048A 3M CC18 2016 2016-05-02 NO23 -5.5214609179 I #> 3980 2048A 3M CC18 2016 2016-05-02 SALIN 2.7850112422 #> 3981 2048A 3M CC18 2016 2016-05-02 TKN -0.1984509387 #> 3982 2048A 3M CC18 2016 2016-05-02 TN -0.1935847491 + #> 3983 2048A 3M CC18 2016 2016-05-02 TP -1.8325814637 #> 3984 2048A 3M CC18 2016 2016-05-02 TURB 0.3364722366 #> 3985 2048A 3M CC18 2016 2016-07-05 CHLAC 1.4586150227 #> 3986 2048A 3M CC18 2016 2016-07-05 COLOR 4.5747109785 #> 3987 2048A 3M CC18 2016 2016-07-05 DOSAT 4.0758410907 + #> 3988 2048A 3M CC18 2016 2016-07-05 NO23 -5.5214609179 I #> 3989 2048A 3M CC18 2016 2016-07-05 SALIN 2.1400661635 #> 3990 2048A 3M CC18 2016 2016-07-05 TKN 0.0000000000 #> 3991 2048A 3M CC18 2016 2016-07-05 TN 0.0039920213 + #> 3992 2048A 3M CC18 2016 2016-07-05 TP -0.9162907319 #> 3993 2048A 3M CC18 2016 2016-07-05 TURB 0.6931471806 #> 3994 2048A 3M CC18 2016 2016-08-01 CHLAC 1.9878743482 #> 3995 2048A 3M CC18 2016 2016-08-01 COLOR 4.4659081187 #> 3996 2048A 3M CC18 2016 2016-08-01 NO23 -5.2983173665 I #> 3997 2048A 3M CC18 2016 2016-08-01 SALIN 1.9878743482 #> 3998 2048A 3M CC18 2016 2016-08-01 TN 0.0989399479 + #> 3999 2048A 3M CC18 2016 2016-08-01 TURB 0.6931471806 #> 4000 2048A 3M CC18 2016 2016-10-03 CHLAC 1.9740810260 #> 4001 2048A 3M CC18 2016 2016-10-03 COLOR 4.7004803658 #> 4002 2048A 3M CC18 2016 2016-10-03 DO 1.8870696490 #> 4003 2048A 3M CC18 2016 2016-10-03 DOSAT 4.4438270356 + #> 4004 2048A 3M CC18 2016 2016-10-03 NO23 -4.8283137373 I #> 4005 2048A 3M CC18 2016 2016-10-03 SALIN 1.4158531634 #> 4006 2048A 3M CC18 2016 2016-10-03 TKN -0.1625189295 #> 4007 2048A 3M CC18 2016 2016-10-03 TN -0.1578240852 + #> 4008 2048A 3M CC18 2016 2016-10-03 TP -1.6607312068 #> 4009 2048A 3M CC18 2016 2016-10-03 TURB 0.5306282511 #> 4010 2048A 3M CC18 2016 2016-11-07 CHLAC 0.9932517730 #> 4011 2048A 3M CC18 2016 2016-11-07 COLOR 3.8918202981 #> 4012 2048A 3M CC18 2016 2016-11-07 DOSAT 3.8501476017 + #> 4013 2048A 3M CC18 2016 2016-11-07 NO23 -4.1997050779 #> 4014 2048A 3M CC18 2016 2016-11-07 SALIN 3.0773122605 #> 4015 2048A 3M CC18 2016 2016-11-07 TKN -0.3011050928 #> 4016 2048A 3M CC18 2016 2016-11-07 TN -0.2810375297 + #> 4017 2048A 3M CC18 2016 2016-11-07 TP -1.8971199849 #> 4018 2048A 3M CC18 2016 2016-11-07 TURB 1.1939224685 #> 4019 2048A 3M CC18 2016 2016-12-05 CHLAC 0.9555114450 I #> 4020 2048A 3M CC18 2016 2016-12-05 COLOR 3.4657359028 #> 4021 2048A 3M CC18 2016 2016-12-05 DO 0.9555114450 #> 4022 2048A 3M CC18 2016 2016-12-05 DOSAT 3.5263605246 + #> 4023 2048A 3M CC18 2016 2016-12-05 NO23 -4.2686979494 #> 4024 2048A 3M CC18 2016 2016-12-05 SALIN 3.0726933147 #> 4025 2048A 3M CC18 2016 2016-12-05 TKN -0.4780358009 #> 4026 2048A 3M CC18 2016 2016-12-05 TN -0.4557063245 + #> 4027 2048A 3M CC18 2016 2016-12-05 TP -2.4191189092 #> 4028 2048A 3M CC18 2016 2016-12-05 TURB 0.6418538862 #> 4029 2048A 3M CC18 2017 2017-01-03 CHLAC 0.7884573604 #> 4030 2048A 3M CC18 2017 2017-01-03 COLOR 3.2580965380 A #> 4031 2048A 3M CC18 2017 2017-01-03 DOSAT 3.7999735016 + #> 4032 2048A 3M CC18 2017 2017-01-03 NO23 -4.3428059215 #> 4033 2048A 3M CC18 2017 2017-01-03 SALIN 3.1135153092 #> 4034 2048A 3M CC18 2017 2017-01-03 TKN -0.4004775666 #> 4035 2048A 3M CC18 2017 2017-01-03 TN -0.3812604194 + #> 4036 2048A 3M CC18 2017 2017-01-03 TP -2.1202635362 #> 4037 2048A 3M CC18 2017 2017-01-03 TURB 1.2809338455 #> 4038 2048A 3M CC18 2017 2017-02-06 CHLAC 1.4816045409 #> 4039 2048A 3M CC18 2017 2017-02-06 COLOR 3.2188758249 #> 4040 2048A 3M CC18 2017 2017-02-06 DOSAT 3.7999735016 + #> 4041 2048A 3M CC18 2017 2017-02-06 NO23 -4.7105307016 I #> 4042 2048A 3M CC18 2017 2017-02-06 SALIN 3.1135153092 #> 4043 2048A 3M CC18 2017 2017-02-06 TKN -0.3011050928 #> 4044 2048A 3M CC18 2017 2017-02-06 TN -0.2957142441 + #> 4045 2048A 3M CC18 2017 2017-02-06 TP -2.3126354288 #> 4046 2048A 3M CC18 2017 2017-02-06 TURB 1.0647107370 #> 4047 2048A 3M CC18 2017 2017-03-06 CHLAC 1.6677068206 #> 4048 2048A 3M CC18 2017 2017-03-06 COLOR 3.0445224377 #> 4049 2048A 3M CC18 2017 2017-03-06 DO 2.0541237337 #> 4050 2048A 3M CC18 2017 2017-03-06 DOSAT 4.6071681887 + #> 4051 2048A 3M CC18 2017 2017-03-06 NO23 -5.5214609179 U #> 4052 2048A 3M CC18 2017 2017-03-06 SALIN 3.2921262866 #> 4053 2048A 3M CC18 2017 2017-03-06 TKN -0.3011050928 #> 4054 2048A 3M CC18 2017 2017-03-06 TN -0.2984060358 + #> 4055 2048A 3M CC18 2017 2017-03-06 TP -2.6592600369 #> 4056 2048A 3M CC18 2017 2017-03-06 TURB 1.0986122887 #> 4057 2048A 3M CC18 2017 2017-04-03 CHLAC 1.5892352051 #> 4058 2048A 3M CC18 2017 2017-04-03 COLOR 3.1354942159 #> 4059 2048A 3M CC18 2017 2017-04-03 DO 1.7749523509 #> 4060 2048A 3M CC18 2017 2017-04-03 DOSAT 4.3040650932 + #> 4061 2048A 3M CC18 2017 2017-04-03 NO23 -4.7105307016 I #> 4062 2048A 3M CC18 2017 2017-04-03 SALIN 1.5260563035 #> 4063 2048A 3M CC18 2017 2017-04-03 TN -0.2691874898 + #> 4064 2048A 3M CC18 2017 2017-04-03 TURB 0.9555114450 #> 4065 2048A 3M CC18 2017 2017-05-01 CHLAC 2.2407096893 A #> 4066 2048A 3M CC18 2017 2017-05-01 COLOR 3.4011973817 A #> 4067 2048A 3M CC18 2017 2017-05-01 DO 1.9169226122 #> 4068 2048A 3M CC18 2017 2017-05-01 DOSAT 4.6061696863 + #> 4069 2048A 3M CC18 2017 2017-05-01 NO23 -5.5214609179 U #> 4070 2048A 3M CC18 2017 2017-05-01 SALIN 3.4210000090 #> 4071 2048A 3M CC18 2017 2017-05-01 TKN 0.0953101798 #> 4072 2048A 3M CC18 2017 2017-05-01 TN 0.0971267107 + #> 4073 2048A 3M CC18 2017 2017-05-01 TP -2.1202635362 #> 4074 2048A 3M CC18 2017 2017-05-01 TURB 1.3609765531 #> 4075 2048A 3M CC18 2017 2017-06-05 CHLAC 1.4350845253 #> 4076 2048A 3M CC18 2017 2017-06-05 COLOR 3.6635616461 #> 4077 2048A 3M CC18 2017 2017-06-05 DO 1.8870696490 #> 4078 2048A 3M CC18 2017 2017-06-05 DOSAT 4.6141299274 + #> 4079 2048A 3M CC18 2017 2017-06-05 NO23 -5.2983173665 I #> 4080 2048A 3M CC18 2017 2017-06-05 SALIN 3.4843122884 #> 4081 2048A 3M CC18 2017 2017-06-05 TN -0.1461825102 + #> 4082 2048A 3M CC18 2017 2017-06-05 TURB 0.8754687374 #> 4083 2048A 3M CC18 2017 2017-07-10 CHLAC 2.0281482473 #> 4084 2048A 3M CC18 2017 2017-07-10 COLOR 5.1357984371 #> 4085 2048A 3M CC18 2017 2017-07-10 DO 0.8754687374 #> 4086 2048A 3M CC18 2017 2017-07-10 DOSAT 3.4904285154 + #> 4087 2048A 3M CC18 2017 2017-07-10 SALIN 2.3513752572 #> 4088 2048A 3M CC18 2017 2017-07-10 TN 0.2768738737 + #> 4089 2048A 3M CC18 2017 2017-07-10 TURB 0.6931471806 #> 4090 2048A 3M CC18 2017 2017-08-07 CHLAC 0.7419373447 #> 4091 2048A 3M CC18 2017 2017-08-07 COLOR 5.3471075307 #> 4092 2048A 3M CC18 2017 2017-08-07 DOSAT 2.9123506646 + #> 4093 2048A 3M CC18 2017 2017-08-07 NO23 -2.6592600369 #> 4094 2048A 3M CC18 2017 2017-08-07 SALIN 0.9162907319 #> 4095 2048A 3M CC18 2017 2017-08-07 TKN 0.1823215568 #> 4096 2048A 3M CC18 2017 2017-08-07 TN 0.2390169005 + #> 4097 2048A 3M CC18 2017 2017-08-07 TP -1.3470736480 #> 4098 2048A 3M CC18 2017 2017-08-07 TURB 1.0296194172 #> 4099 2048A 3M CC18 2017 2017-09-05 CHLAC 2.2512917986 #> 4100 2048A 3M CC18 2017 2017-09-05 COLOR 5.2470240722 #> 4101 2048A 3M CC18 2017 2017-09-05 DO 2.2721258855 #> 4102 2048A 3M CC18 2017 2017-09-05 DOSAT 4.8354879411 + #> 4103 2048A 3M CC18 2017 2017-09-05 NO23 -3.2968373663 #> 4104 2048A 3M CC18 2017 2017-09-05 SALIN 1.1631508098 #> 4105 2048A 3M CC18 2017 2017-09-05 TKN 0.0000000000 #> 4106 2048A 3M CC18 2017 2017-09-05 TN 0.0363319292 + #> 4107 2048A 3M CC18 2017 2017-09-05 TP -1.8971199849 #> 4108 2048A 3M CC18 2017 2017-09-05 TURB 0.7419373447 #> 4109 2048A 3M CC18 2017 2017-11-06 CHLAC 1.2809338455 #> 4110 2048A 3M CC18 2017 2017-11-06 COLOR 4.3307333403 #> 4111 2048A 3M CC18 2017 2017-11-06 DO 2.0412203289 #> 4112 2048A 3M CC18 2017 2017-11-06 NO23 -4.3428059215 #> 4113 2048A 3M CC18 2017 2017-11-06 SALIN 2.2721258855 #> 4114 2048A 3M CC18 2017 2017-11-06 TKN -0.3285040670 #> 4115 2048A 3M CC18 2017 2017-11-06 TN -0.3106095771 + #> 4116 2048A 3M CC18 2017 2017-11-06 TP -1.8325814637 #> 4117 2048A 3M CC18 2017 2017-11-06 TURB 0.3364722366 #> 4118 2048A 3M CC18 2017 2017-12-04 CHLAC 0.8329091229 #> 4119 2048A 3M CC18 2017 2017-12-04 COLOR 3.8066624898 #> 4120 2048A 3M CC18 2017 2017-12-04 DO 2.0794415417 #> 4121 2048A 3M CC18 2017 2017-12-04 DOSAT 4.6700211583 + #> 4122 2048A 3M CC18 2017 2017-12-04 NO23 -5.5214609179 U #> 4123 2048A 3M CC18 2017 2017-12-04 SALIN 3.3214324132 #> 4124 2048A 3M CC18 2017 2017-12-04 TKN -0.2876820725 #> 4125 2048A 3M CC18 2017 2017-12-04 TN -0.2850189550 + #> 4126 2048A 3M CC18 2017 2017-12-04 TP -2.2072749132 #> 4127 2048A 3M CC18 2017 2017-12-04 TURB -0.1625189295 #> 4128 2048A 3M CC18 2018 2018-01-02 CHLAC 1.5475625087 #> 4129 2048A 3M CC18 2018 2018-01-02 COLOR 3.4965075615 #> 4130 2048A 3M CC18 2018 2018-01-02 DOSAT 4.3161538905 + #> 4131 2048A 3M CC18 2018 2018-01-02 NO23 -5.5214609179 U #> 4132 2048A 3M CC18 2018 2018-01-02 SALIN 2.4248027257 #> 4133 2048A 3M CC18 2018 2018-01-02 TN -0.4910229965 + #> 4134 2048A 3M CC18 2018 2018-01-02 TURB 0.5877866649 #> 4135 2048A 3M CC18 2018 2018-03-05 CHLAC 0.8329091229 #> 4136 2048A 3M CC18 2018 2018-03-05 COLOR 3.5835189385 #> 4137 2048A 3M CC18 2018 2018-03-05 NO23 -5.5214609179 U #> 4138 2048A 3M CC18 2018 2018-03-05 TKN -0.3011050928 #> 4139 2048A 3M CC18 2018 2018-03-05 TN -0.2984060358 + #> 4140 2048A 3M CC18 2018 2018-03-05 TP -1.8971199849 #> 4141 2048A 3M CC18 2018 2018-03-05 TURB 1.0296194172 #> 4142 2048A 3M CC18 2018 2018-04-02 CHLAC 1.6677068206 #> 4143 2048A 3M CC18 2018 2018-04-02 COLOR 3.3322045102 #> 4144 2048A 3M CC18 2018 2018-04-02 DOSAT 4.2513483110 + #> 4145 2048A 3M CC18 2018 2018-04-02 NO23 -5.2983173665 I #> 4146 2048A 3M CC18 2018 2018-04-02 SALIN 3.2027464429 #> 4147 2048A 3M CC18 2018 2018-04-02 TKN -0.2613647641 #> 4148 2048A 3M CC18 2018 2018-04-02 TN -0.2561834054 + #> 4149 2048A 3M CC18 2018 2018-04-02 TP -1.9661128564 #> 4150 2048A 3M CC18 2018 2018-04-02 TURB 1.3083328197 #> 4151 2048A 3M CC18 2018 2018-05-07 CHLAC 1.8562979904 #> 4152 2048A 3M CC18 2018 2018-05-07 COLOR 3.3322045102 A #> 4153 2048A 3M CC18 2018 2018-05-07 DO 2.1016921506 #> 4154 2048A 3M CC18 2018 2018-05-07 DOSAT 4.6051701860 #> 4155 2048A 3M CC18 2018 2018-05-07 NO23 -5.5214609179 I #> 4156 2048A 3M CC18 2018 2018-05-07 SALIN 3.2812870850 #> 4157 2048A 3M CC18 2018 2018-05-07 TKN -0.0943106795 #> 4158 2048A 3M CC18 2018 2018-05-07 TN -0.0899247075 + #> 4159 2048A 3M CC18 2018 2018-05-07 TP -2.2072749132 #> 4160 2048A 3M CC18 2018 2018-05-07 TURB 1.2527629685 #> 4161 2048A 3M CC18 2018 2018-06-04 CHLAC 1.8405496334 #> 4162 2048A 3M CC18 2018 2018-06-04 COLOR 4.6051701860 #> 4163 2048A 3M CC18 2018 2018-06-04 DO 2.0906287311 #> 4164 2048A 3M CC18 2018 2018-06-04 DOSAT 4.6011621646 #> 4165 2048A 3M CC18 2018 2018-06-04 NO23 -4.6051701860 I #> 4166 2048A 3M CC18 2018 2018-06-04 SALIN 1.8115620965 #> 4167 2048A 3M CC18 2018 2018-06-04 TKN -0.0725706928 #> 4168 2048A 3M CC18 2018 2018-06-04 TN -0.0682788408 + #> 4169 2048A 3M CC18 2018 2018-06-04 TP -1.6094379124 #> 4170 2048A 3M CC18 2018 2018-06-04 TURB 0.5306282511 #> 4171 2048A 3M CC18 2018 2018-07-09 CHLAC 2.4849066498 #> 4172 2048A 3M CC18 2018 2018-07-09 COLOR 4.9416424226 #> 4173 2048A 3M CC18 2018 2018-07-09 DO 1.4929040962 #> 4174 2048A 3M CC18 2018 2018-07-09 DOSAT 4.1415461637 #> 4175 2048A 3M CC18 2018 2018-07-09 NO23 -4.9618451299 I #> 4176 2048A 3M CC18 2018 2018-07-09 SALIN 1.3402504226 #> 4177 2048A 3M CC18 2018 2018-07-09 TKN -0.2231435513 #> 4178 2048A 3M CC18 2018 2018-07-09 TN -0.2181560098 + #> 4179 2048A 3M CC18 2018 2018-07-09 TP -1.7719568419 #> 4180 2048A 3M CC18 2018 2018-07-09 TURB 0.8754687374 #> 4181 2048A 3M CC18 2019 2019-05-06 CHLAC 0.9555114450 #> 4182 2048A 3M CC18 2019 2019-05-06 COLOR 3.6109179126 #> 4183 2048A 3M CC18 2019 2019-05-06 DO 0.8837675402 #> 4184 2048A 3M CC18 2019 2019-05-06 DOSAT 3.5351453542 #> 4185 2048A 3M CC18 2019 2019-05-06 NO23 -5.2983173665 I #> 4186 2048A 3M CC18 2019 2019-05-06 SALIN 2.9719517449 #> 4187 2048A 3M CC18 2019 2019-05-06 TKN -0.2744368457 #> 4188 2048A 3M CC18 2019 2019-05-06 TN -0.2691874898 + #> 4189 2048A 3M CC18 2019 2019-05-06 TP -1.7719568419 #> 4190 2048A 3M CC18 2019 2019-05-06 TURB 0.7419373447 #> 4191 2048A 3M CC18 2019 2019-06-03 CHLAC 1.5686159179 #> 4192 2048A 3M CC18 2019 2019-06-03 COLOR 3.7376696183 #> 4193 2048A 3M CC18 2019 2019-06-03 DO 0.6418538862 #> 4194 2048A 3M CC18 2019 2019-06-03 DOSAT 3.3322045102 #> 4195 2048A 3M CC18 2019 2019-06-03 NO23 -5.5214609179 U #> 4196 2048A 3M CC18 2019 2019-06-03 SALIN 3.0363942553 #> 4197 2048A 3M CC18 2019 2019-06-03 TKN -0.0725706928 #> 4198 2048A 3M CC18 2019 2019-06-03 TN -0.0704224643 + #> 4199 2048A 3M CC18 2019 2019-06-03 TP -1.3470736480 #> 4200 2048A 3M CC18 2019 2019-06-03 TURB 1.4586150227 A #> 4201 2048A 3M CC18 2019 2019-07-01 CHLAC 1.6863989536 #> 4202 2048A 3M CC18 2019 2019-07-01 COLOR 3.6635616461 #> 4203 2048A 3M CC18 2019 2019-07-01 DO 0.9162907319 #> 4204 2048A 3M CC18 2019 2019-07-01 DOSAT 3.4483989831 #> 4205 2048A 3M CC18 2019 2019-07-01 NO23 -5.5214609179 U #> 4206 2048A 3M CC18 2019 2019-07-01 SALIN 2.9678470701 #> 4207 2048A 3M CC18 2019 2019-07-01 TKN -0.2484613593 #> 4208 2048A 3M CC18 2019 2019-07-01 TN -0.2459005384 + #> 4209 2048A 3M CC18 2019 2019-07-01 TP -1.2729656758 #> 4210 2048A 3M CC18 2019 2019-07-01 TURB 0.4054651081 #> 4211 2048A 3M CC18 2019 2019-08-05 CHLAC 1.4109869737 #> 4212 2048A 3M CC18 2019 2019-08-05 COLOR 5.0751738152 #> 4213 2048A 3M CC18 2019 2019-08-05 DO 1.1378330018 #> 4214 2048A 3M CC18 2019 2019-08-05 DOSAT 3.7305011288 #> 4215 2048A 3M CC18 2019 2019-08-05 NO23 -5.5214609179 I #> 4216 2048A 3M CC18 2019 2019-08-05 SALIN 1.6134299337 #> 4217 2048A 3M CC18 2019 2019-08-05 TKN -0.0618754037 #> 4218 2048A 3M CC18 2019 2019-08-05 TN -0.0576291128 + #> 4219 2048A 3M CC18 2019 2019-08-05 TP -1.5606477483 #> 4220 2048A 3M CC18 2019 2019-08-05 TURB 0.8754687374 #> 4221 2048A 3M CC18 2019 2019-10-07 CHLAC 1.0986122887 I #> 4222 2048A 3M CC18 2019 2019-10-07 COLOR 4.3820266347 #> 4223 2048A 3M CC18 2019 2019-10-07 DO 1.0152306797 #> 4224 2048A 3M CC18 2019 2019-10-07 DOSAT 3.6375861597 #> 4225 2048A 3M CC18 2019 2019-10-07 NO23 -4.9618451299 I #> 4226 2048A 3M CC18 2019 2019-10-07 SALIN 2.7389026646 #> 4227 2048A 3M CC18 2019 2019-10-07 TKN -0.1278333715 #> 4228 2048A 3M CC18 2019 2019-10-07 TN -0.1232982163 + #> 4229 2048A 3M CC18 2019 2019-10-07 TP -1.3862943611 #> 4230 2048A 3M CC18 2019 2019-10-07 TURB 0.4054651081 #> 4231 2048A 3M CC18 2019 2019-11-04 CHLAC 1.0296194172 #> 4232 2048A 3M CC18 2019 2019-11-04 COLOR 4.1431347264 #> 4233 2048A 3M CC18 2019 2019-11-04 DO 1.2267122913 #> 4234 2048A 3M CC18 2019 2019-11-04 DOSAT 3.8177123260 #> 4235 2048A 3M CC18 2019 2019-11-04 NO23 -5.5214609179 I #> 4236 2048A 3M CC18 2019 2019-11-04 SALIN 2.8075938314 #> 4237 2048A 3M CC18 2019 2019-11-04 TKN -0.1508228897 #> 4238 2048A 3M CC18 2019 2019-11-04 TN -0.1461825102 + #> 4239 2048A 3M CC18 2019 2019-11-04 TP -1.6094379124 #> 4240 2048A 3M CC18 2019 2019-11-04 TURB 0.2623642645 A #> 4241 2048A 3M CC18 2019 2019-11-04 DO 1.2267122913 #> 4242 2048A 3M CC18 2019 2019-11-04 DOSAT 3.8177123260 #> 4243 2048A 3M CC18 2019 2019-11-04 SALIN 2.8075938314 #> 4244 2048A 3M CC18 2019 2019-12-02 CHLAC 1.2809338455 #> 4245 2048A 3M CC18 2019 2019-12-02 COLOR 3.6888794541 A #> 4246 2048A 3M CC18 2019 2019-12-02 DO 1.5518087996 #> 4247 2048A 3M CC18 2019 2019-12-02 DOSAT 4.1059436981 #> 4248 2048A 3M CC18 2019 2019-12-02 NO23 -5.5214609179 U #> 4249 2048A 3M CC18 2019 2019-12-02 SALIN 2.9412760878 #> 4250 2048A 3M CC18 2019 2019-12-02 TKN -0.2613647641 #> 4251 2048A 3M CC18 2019 2019-12-02 TN -0.2587707290 + #> 4252 2048A 3M CC18 2019 2019-12-02 TP -2.2072749132 #> 4253 2048A 3M CC18 2019 2019-12-02 TURB 0.0953101798 #> 4254 2048A 3M CC18 2020 2020-01-06 CHLAC 1.7578579176 #> 4255 2048A 3M CC18 2020 2020-01-06 COLOR 3.5263605246 #> 4256 2048A 3M CC18 2020 2020-01-06 DO 1.6770965609 #> 4257 2048A 3M CC18 2020 2020-01-06 DOSAT 4.1541845626 #> 4258 2048A 3M CC18 2020 2020-01-06 NO23 -5.5214609179 U #> 4259 2048A 3M CC18 2020 2020-01-06 SALIN 2.8713021952 #> 4260 2048A 3M CC18 2020 2020-01-06 TKN -0.5276327421 #> 4261 2048A 3M CC18 2020 2020-01-06 TN -0.5242486441 + #> 4262 2048A 3M CC18 2020 2020-01-06 TP -1.8971199849 #> 4263 2048A 3M CC18 2020 2020-01-06 TURB 0.3364722366 #> 4264 2048A 3M CC18 2020 2020-02-03 CHLAC 2.6390573296 #> 4265 2048A 3M CC18 2020 2020-02-03 COLOR 3.3672958300 #> 4266 2048A 3M CC18 2020 2020-02-03 DO 1.7137979278 #> 4267 2048A 3M CC18 2020 2020-02-03 DOSAT 4.1941898972 #> 4268 2048A 3M CC18 2020 2020-02-03 NO23 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#> 4357 2048A 3M CC18 2021 2021-05-03 NO23 -5.5214609179 I #> 4358 2048A 3M CC18 2021 2021-05-03 SALIN 3.1726224404 #> 4359 2048A 3M CC18 2021 2021-05-03 TKN -0.3566749439 #> 4360 2048A 3M CC18 2021 2021-05-03 TN -0.3509769228 + #> 4361 2048A 3M CC18 2021 2021-05-03 TP -1.8325814637 #> 4362 2048A 3M CC18 2021 2021-05-03 TURB 0.5877866649 #> 4363 2048A 3M CC18 2021 2021-06-07 CHLAC 1.5686159179 I #> 4364 2048A 3M CC18 2021 2021-06-07 COLOR 3.5835189385 #> 4365 2048A 3M CC18 2021 2021-06-07 DO 1.0508216248 #> 4366 2048A 3M CC18 2021 2021-06-07 DOSAT 4.2918283668 #> 4367 2048A 3M CC18 2021 2021-06-07 NO23 -5.2983173665 I #> 4368 2048A 3M CC18 2021 2021-06-07 SALIN 3.2476576263 #> 4369 2048A 3M CC18 2021 2021-06-07 TKN -0.2484613593 #> 4370 2048A 3M CC18 2021 2021-06-07 TN -0.2433462586 + #> 4371 2048A 3M CC18 2021 2021-06-07 TP -1.5141277326 #> 4372 2048A 3M CC18 2021 2021-06-07 TURB 0.5306282511 #> 4373 2048A 3M CC18 2021 2021-08-02 CHLAC 1.8082887712 #> 4374 2048A 3M CC18 2021 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TURB 0.5306282511 #> 4498 2048A 3M CC18 2022 2022-12-05 CHLAC 1.1314021115 #> 4499 2048A 3M CC18 2022 2022-12-05 COLOR 4.2341065046 #> 4500 2048A 3M CC18 2022 2022-12-05 DO 1.7119945008 #> 4501 2048A 3M CC18 2022 2022-12-05 DOSAT 4.2046926194 #> 4502 2048A 3M CC18 2022 2022-12-05 NO23 -4.6051701860 #> 4503 2048A 3M CC18 2022 2022-12-05 SALIN 2.4475508632 #> 4504 2048A 3M CC18 2022 2022-12-05 TKN -0.1984509387 #> 4505 2048A 3M CC18 2022 2022-12-05 TN -0.1863295782 + #> 4506 2048A 3M CC18 2022 2022-12-05 TP -1.7719568419 #> 4507 2048A 3M CC18 2022 2022-12-05 TURB -0.0512932944 I #> 4508 2048A 3M CC18 2023 2023-02-06 CHLAC 1.5260563035 #> 4509 2048A 3M CC18 2023 2023-02-06 COLOR 3.4657359028 #> 4510 2048A 3M CC18 2023 2023-02-06 DO 1.6863989536 #> 4511 2048A 3M CC18 2023 2023-02-06 DOSAT 4.2341065046 #> 4512 2048A 3M CC18 2023 2023-02-06 NO23 -5.2983173665 I #> 4513 2048A 3M CC18 2023 2023-02-06 SALIN 2.9269179576 #> 4514 2048A 3M CC18 2023 2023-02-06 TKN -0.4155154440 #> 4515 2048A 3M CC18 2023 2023-02-06 TN -0.4094731295 + #> 4516 2048A 3M CC18 2023 2023-02-06 TP -2.1202635362 #> 4517 2048A 3M CC18 2023 2023-02-06 TURB 0.6931471806 #> 4518 2048A 3M CC18 2023 2023-03-06 CHLAC 1.8718021769 #> 4519 2048A 3M CC18 2023 2023-03-06 COLOR 3.3672958300 #> 4520 2048A 3M CC18 2023 2023-03-06 DO 1.1442227999 #> 4521 2048A 3M CC18 2023 2023-03-06 DOSAT 3.7977338590 #> 4522 2048A 3M CC18 2023 2023-03-06 NO23 -4.4228486292 #> 4523 2048A 3M CC18 2023 2023-03-06 SALIN 3.0199369623 #> 4524 2048A 3M CC18 2023 2023-03-06 TKN 0.1823215568 #> 4525 2048A 3M CC18 2023 2023-03-06 TN 0.1922718876 + #> 4526 2048A 3M CC18 2023 2023-03-06 TP -1.9661128564 #> 4527 2048A 3M CC18 2023 2023-03-06 TURB 0.7884573604 #> 4528 2060A1 2 CC25 2014 2014-02-12 CHLAC 1.4109869737 #> 4529 2060A1 2 CC25 2014 2014-02-12 COLOR 3.2188758249 #> 4530 2060A1 2 CC25 2014 2014-02-12 COND 10.5921245776 #> 4531 2060A1 2 CC25 2014 2014-02-12 DO 1.9933388426 #> 4532 2060A1 2 CC25 2014 2014-02-12 DOSAT 4.5570298107 + #> 4533 2060A1 2 CC25 2014 2014-02-12 NO23 -5.5214609179 U #> 4534 2060A1 2 CC25 2014 2014-02-12 SALIN 3.2367157430 #> 4535 2060A1 2 CC25 2014 2014-02-12 TKN -0.7657178734 #> 4536 2060A1 2 CC25 2014 2014-02-12 TN -0.7657178734 #> 4537 2060A1 2 CC25 2014 2014-02-12 TP -2.0099154790 #> 4538 2060A1 2 CC25 2014 2014-02-12 TSS 1.7917594692 #> 4539 2060A1 2 CC25 2014 2014-02-12 TURB 0.1823215568 #> 4540 2060A1 2 CC25 2014 2014-02-12 COND 10.5938809449 #> 4541 2060A1 2 CC25 2014 2014-02-12 DO 1.9919755159 #> 4542 2060A1 2 CC25 2014 2014-02-12 DOSAT 4.5559799418 + #> 4543 2060A1 2 CC25 2014 2014-02-12 SALIN 3.2386784522 #> 4544 2060A1 2 CC25 2014 2014-07-09 CHLAC 2.1838015570 #> 4545 2060A1 2 CC25 2014 2014-07-09 COLOR 3.8066624898 #> 4546 2060A1 2 CC25 2014 2014-07-09 COND 10.5001238327 #> 4547 2060A1 2 CC25 2014 2014-07-09 DO 1.7047480922 #> 4548 2060A1 2 CC25 2014 2014-07-09 DOSAT 4.4164280614 + #> 4549 2060A1 2 CC25 2014 2014-07-09 NO23 -5.5214609179 U #> 4550 2060A1 2 CC25 2014 2014-07-09 SALIN 3.1271990363 #> 4551 2060A1 2 CC25 2014 2014-07-09 TKN -0.2319320573 #> 4552 2060A1 2 CC25 2014 2014-07-09 TN -0.2319320573 #> 4553 2060A1 2 CC25 2014 2014-07-09 TP -1.3167682985 #> 4554 2060A1 2 CC25 2014 2014-07-09 TSS 1.9286186519 #> 4555 2060A1 2 CC25 2014 2014-07-09 TURB 0.8329091229 #> 4556 2060A1 2 CC25 2014 2014-07-09 COND 10.5012245483 #> 4557 2060A1 2 CC25 2014 2014-07-09 DO 1.7029282555 #> 4558 2060A1 2 CC25 2014 2014-07-09 DOSAT 4.4115854369 + #> 4559 2060A1 2 CC25 2014 2014-07-09 SALIN 3.1285133848 #> 4560 2060A1 2 CC25 2014 2014-08-12 CHLAC 3.6558396000 #> 4561 2060A1 2 CC25 2014 2014-08-12 COLOR 4.3820266347 #> 4562 2060A1 2 CC25 2014 2014-08-12 COND 9.9744118909 #> 4563 2060A1 2 CC25 2014 2014-08-12 DO 1.9643112344 #> 4564 2060A1 2 CC25 2014 2014-08-12 DOSAT 4.6424659707 + #> 4565 2060A1 2 CC25 2014 2014-08-12 NO23 -5.5214609179 U #> 4566 2060A1 2 CC25 2014 2014-08-12 SALIN 2.5478814489 #> 4567 2060A1 2 CC25 2014 2014-08-12 TKN 0.1484200051 #> 4568 2060A1 2 CC25 2014 2014-08-12 TN 0.1484200051 #> 4569 2060A1 2 CC25 2014 2014-08-12 TP -0.9808292530 #> 4570 2060A1 2 CC25 2014 2014-08-12 TSS 2.3887627892 #> 4571 2060A1 2 CC25 2014 2014-08-12 TURB 1.6292405397 #> 4572 2060A1 2 CC25 2014 2014-08-12 COND 9.9753429896 #> 4573 2060A1 2 CC25 2014 2014-08-12 DO 1.9586853405 #> 4574 2060A1 2 CC25 2014 2014-08-12 DOSAT 4.6366688530 + #> 4575 2060A1 2 CC25 2014 2014-08-12 SALIN 2.5486636156 #> 4576 2060A1 2 CC25 2014 2014-08-12 COND 9.9753429896 #> 4577 2060A1 2 CC25 2014 2014-08-12 DO 1.9530276168 #> 4578 2060A1 2 CC25 2014 2014-08-12 DOSAT 4.6308379327 + #> 4579 2060A1 2 CC25 2014 2014-08-12 SALIN 2.5486636156 #> 4580 2060A1 2 CC25 2014 2014-10-21 CHLAC 0.9555114450 #> 4581 2060A1 2 CC25 2014 2014-10-21 COLOR 4.7874917428 #> 4582 2060A1 2 CC25 2014 2014-10-21 COND 10.1330107108 #> 4583 2060A1 2 CC25 2014 2014-10-21 DO 1.4701758451 #> 4584 2060A1 2 CC25 2014 2014-10-21 DOSAT 4.0809215419 + #> 4585 2060A1 2 CC25 2014 2014-10-21 NO23 -3.1941832123 #> 4586 2060A1 2 CC25 2014 2014-10-21 SALIN 2.7258901192 #> 4587 2060A1 2 CC25 2014 2014-10-21 TKN -0.1053605157 #> 4588 2060A1 2 CC25 2014 2014-10-21 TN -0.0608121394 #> 4589 2060A1 2 CC25 2014 2014-10-21 TP -1.4354846053 #> 4590 2060A1 2 CC25 2014 2014-10-21 TSS 1.5973653312 #> 4591 2060A1 2 CC25 2014 2014-10-21 TURB 0.8329091229 #> 4592 2060A1 2 CC25 2014 2014-10-21 COND 10.1472177375 #> 4593 2060A1 2 CC25 2014 2014-10-21 DO 1.4182774070 #> 4594 2060A1 2 CC25 2014 2014-10-21 DOSAT 4.0271358125 + #> 4595 2060A1 2 CC25 2014 2014-10-21 SALIN 2.7414849772 #> 4596 2060A1 2 CC25 2014 2014-10-21 COND 10.1612257486 #> 4597 2060A1 2 CC25 2014 2014-10-21 DO 1.3862943611 #> 4598 2060A1 2 CC25 2014 2014-10-21 DOSAT 3.9963641539 + #> 4599 2060A1 2 CC25 2014 2014-10-21 SALIN 2.7581094010 #> 4600 2060A1 2 CC25 2015 2015-02-03 CHLAC 1.7209792872 #> 4601 2060A1 2 CC25 2015 2015-02-03 COLOR 3.8066624898 #> 4602 2060A1 2 CC25 2015 2015-02-03 COND 10.4795389612 #> 4603 2060A1 2 CC25 2015 2015-02-03 DO 2.1758874399 #> 4604 2060A1 2 CC25 2015 2015-02-03 DOSAT 4.6596583713 + #> 4605 2060A1 2 CC25 2015 2015-02-03 NO23 -5.5214609179 U #> 4606 2060A1 2 CC25 2015 2015-02-03 SALIN 3.1130707660 #> 4607 2060A1 2 CC25 2015 2015-02-03 TKN -0.4975803970 #> 4608 2060A1 2 CC25 2015 2015-02-03 TN -0.4975803970 #> 4609 2060A1 2 CC25 2015 2015-02-03 TP -2.1037342342 #> 4610 2060A1 2 CC25 2015 2015-02-03 TSS 2.6100697927 #> 4611 2060A1 2 CC25 2015 2015-02-03 TURB 0.7884573604 #> 4612 2060A1 2 CC25 2015 2015-02-03 COND 10.4887710872 #> 4613 2060A1 2 CC25 2015 2015-02-03 DO 2.1644717909 #> 4614 2060A1 2 CC25 2015 2015-02-03 DOSAT 4.6482296754 + #> 4615 2060A1 2 CC25 2015 2015-02-03 SALIN 3.1232455939 #> 4616 2060A1 2 CC25 2015 2015-02-03 COND 10.4921072037 #> 4617 2060A1 2 CC25 2015 2015-02-03 DO 2.1621729393 #> 4618 2060A1 2 CC25 2015 2015-02-03 DOSAT 4.6463121293 + #> 4619 2060A1 2 CC25 2015 2015-02-03 SALIN 3.1267605360 #> 4620 2060A1 2 CC25 2016 2016-09-13 CHLAC 1.4206957878 #> 4621 2060A1 2 CC25 2016 2016-09-13 COND 8.8724871823 #> 4622 2060A1 2 CC25 2016 2016-09-13 DO 1.7191887764 #> 4623 2060A1 2 CC25 2016 2016-09-13 DOSAT 4.3346729383 + #> 4624 2060A1 2 CC25 2016 2016-09-13 NO23 -2.7333680091 #> 4625 2060A1 2 CC25 2016 2016-09-13 SALIN 1.3584091576 #> 4626 2060A1 2 CC25 2016 2016-09-13 TKN 0.2851789422 #> 4627 2060A1 2 CC25 2016 2016-09-13 TN 0.3364722366 #> 4628 2060A1 2 CC25 2016 2016-09-13 TP -1.2207799226 #> 4629 2060A1 2 CC25 2016 2016-09-13 TSS 0.4700036292 I #> 4630 2060A1 2 CC25 2016 2016-09-13 TURB 0.6418538862 #> 4631 2060A1 2 CC25 2016 2016-09-13 COND 9.4834162920 #> 4632 2060A1 2 CC25 2016 2016-09-13 DO 1.6882490929 #> 4633 2060A1 2 CC25 2016 2016-09-13 DOSAT 4.3134800921 + #> 4634 2060A1 2 CC25 2016 2016-09-13 SALIN 2.0162354658 #> 4635 2060A1 2 CC25 2016 2016-09-13 COND 9.6395220067 #> 4636 2060A1 2 CC25 2016 2016-09-13 DO 1.6544112781 #> 4637 2060A1 2 CC25 2016 2016-09-13 DOSAT 4.2835865619 + #> 4638 2060A1 2 CC25 2016 2016-09-13 SALIN 2.1849270495 #> 4639 2046 3M CC31 2018 2018-03-07 CHLAC 1.6094379124 #> 4640 2046 3M CC31 2018 2018-03-07 COND 10.3531928066 #> 4641 2046 3M CC31 2018 2018-03-07 DO 1.9021075264 #> 4642 2046 3M CC31 2018 2018-03-07 DOSAT 4.4670568839 #> 4643 2046 3M CC31 2018 2018-03-07 NO23 -4.7105307016 I #> 4644 2046 3M CC31 2018 2018-03-07 SALIN 3.0170044088 + #> 4645 2046 3M CC31 2018 2018-03-07 TKN -0.3710636814 #> 4646 2046 3M CC31 2018 2018-03-07 TN -0.3652833185 + #> 4647 2046 3M CC31 2018 2018-03-07 TP -1.8971199849 #> 4648 2046 3M CC31 2018 2018-03-07 TSS 1.3862943611 I #> 4649 2046 3M CC31 2018 2018-03-07 TURB 0.8754687374 #> 4650 2046 3M CC31 2018 2018-04-09 CHLAC 1.2809338455 A #> 4651 2046 3M CC31 2018 2018-04-09 COND 10.6261935353 #> 4652 2046 3M CC31 2018 2018-04-09 DO 1.3083328197 #> 4653 2046 3M CC31 2018 2018-04-09 DOSAT 3.9702919136 #> 4654 2046 3M CC31 2018 2018-04-09 NO23 -3.7297014486 #> 4655 2046 3M CC31 2018 2018-04-09 SALIN 3.2484346271 + #> 4656 2046 3M CC31 2018 2018-04-09 TKN -0.3147107448 #> 4657 2046 3M CC31 2018 2018-04-09 TN -0.2823629110 + #> 4658 2046 3M CC31 2018 2018-04-09 TP -1.7147984281 #> 4659 2046 3M CC31 2018 2018-04-09 TSS 1.6094379124 I #> 4660 2046 3M CC31 2018 2018-04-09 TURB 0.6931471806 #> 4661 2046 3M CC31 2018 2018-05-24 CHLAC 2.7080502011 #> 4662 2046 3M CC31 2018 2018-05-24 COND 9.7756541810 #> 4663 2046 3M CC31 2018 2018-05-24 DO 1.5303947051 #> 4664 2046 3M CC31 2018 2018-05-24 DOSAT 4.1009891049 #> 4665 2046 3M CC31 2018 2018-05-24 NO23 -3.1010927892 #> 4666 2046 3M CC31 2018 2018-05-24 SALIN 2.3065771143 + #> 4667 2046 3M CC31 2018 2018-05-24 TKN -0.2613647641 #> 4668 2046 3M CC31 2018 2018-05-24 TN -0.2045671657 + #> 4669 2046 3M CC31 2018 2018-05-24 TP -1.4271163556 #> 4670 2046 3M CC31 2018 2018-05-24 TSS 1.6094379124 I #> 4671 2046 3M CC31 2018 2018-05-24 TURB 0.9932517730 #> 4672 2046 3M CC31 2018 2018-07-23 CHLAC 1.4350845253 #> 4673 2046 3M CC31 2018 2018-07-23 COND 8.9291703831 #> 4674 2046 3M CC31 2018 2018-07-23 DO 1.6937790609 #> 4675 2046 3M CC31 2018 2018-07-23 DOSAT 4.3040650932 #> 4676 2046 3M CC31 2018 2018-07-23 NO23 -2.0402208285 #> 4677 2046 3M CC31 2018 2018-07-23 SALIN 1.4182774070 #> 4678 2046 3M CC31 2018 2018-07-23 TKN 0.0000000000 #> 4679 2046 3M CC31 2018 2018-07-23 TN 0.1222176327 + #> 4680 2046 3M CC31 2018 2018-07-23 TP -0.9162907319 #> 4681 2046 3M CC31 2018 2018-07-23 TSS 1.3862943611 I #> 4682 2046 3M CC31 2018 2018-07-23 TURB 0.9162907319 A #> 4683 2046 3M CC31 2018 2018-08-21 CHLAC 2.7080502011 #> 4684 2046 3M CC31 2018 2018-08-21 COND 8.6210125201 #> 4685 2046 3M CC31 2018 2018-08-21 DO 1.4586150227 #> 4686 2046 3M CC31 2018 2018-08-21 DOSAT 4.0724397268 #> 4687 2046 3M CC31 2018 2018-08-21 NO23 -3.4737680745 #> 4688 2046 3M CC31 2018 2018-08-21 SALIN 1.0885619528 #> 4689 2046 3M CC31 2018 2018-08-21 TKN 1.7047480922 #> 4690 2046 3M CC31 2018 2018-08-21 TN 1.7103686310 + #> 4691 2046 3M CC31 2018 2018-08-21 TSS 1.6094379124 I #> 4692 2046 3M CC31 2018 2018-08-21 TURB 1.3350010667 #> 4693 2046 3M CC31 2018 2018-11-12 CHLAC 1.5686159179 #> 4694 2046 3M CC31 2018 2018-11-12 COND 10.1213773269 #> 4695 2046 3M CC31 2018 2018-11-12 DO 1.6695918353 #> 4696 2046 3M CC31 2018 2018-11-12 DOSAT 4.3121405072 #> 4697 2046 3M CC31 2018 2018-11-12 NO23 -3.4112477175 #> 4698 2046 3M CC31 2018 2018-11-12 SALIN 2.7127060126 #> 4699 2046 3M CC31 2018 2018-11-12 TKN -0.3011050928 #> 4700 2046 3M CC31 2018 2018-11-12 TN -0.2574762304 + #> 4701 2046 3M CC31 2018 2018-11-12 TP -1.8325814637 #> 4702 2046 3M CC31 2018 2018-11-12 TSS 1.3862943611 I #> 4703 2046 3M CC31 2018 2018-11-12 TURB 0.4700036292 #> 4704 2046 3M CC31 2018 2018-11-12 COND 10.3160937688 #> 4705 2046 3M CC31 2018 2018-11-12 DO 1.5581446180 #> 4706 2046 3M CC31 2018 2018-11-12 DOSAT 4.2076732475 #> 4707 2046 3M CC31 2018 2018-11-12 SALIN 2.9269179576 #> 4708 2046 3M CC31 2019 2019-02-07 CHLAC 3.3672958300 #> 4709 2046 3M CC31 2019 2019-02-07 COND 9.8807305654 #> 4710 2046 3M CC31 2019 2019-02-07 NO23 -5.5214609179 U #> 4711 2046 3M CC31 2019 2019-02-07 SALIN 2.4544474423 #> 4712 2046 3M CC31 2019 2019-02-07 TKN -0.3710636814 #> 4713 2046 3M CC31 2019 2019-02-07 TN -0.3681693234 + #> 4714 2046 3M CC31 2019 2019-02-07 TP -1.6607312068 #> 4715 2046 3M CC31 2019 2019-02-07 TSS 3.3322045102 A #> 4716 2046 3M CC31 2019 2019-02-07 TURB 2.4849066498 A #> 4717 2046 3M CC31 2019 2019-03-13 CHLAC 2.3978952728 #> 4718 2046 3M CC31 2019 2019-03-13 COND 10.1587109973 #> 4719 2046 3M CC31 2019 2019-03-13 DO 1.5830939371 #> 4720 2046 3M CC31 2019 2019-03-13 DOSAT 4.1588830834 #> 4721 2046 3M CC31 2019 2019-03-13 NO23 -5.5214609179 U #> 4722 2046 3M CC31 2019 2019-03-13 SALIN 2.7568403653 #> 4723 2046 3M CC31 2019 2019-03-13 TKN -0.2876820725 #> 4724 2046 3M CC31 2019 2019-03-13 TN -0.2850189550 + #> 4725 2046 3M CC31 2019 2019-03-13 TP -1.7719568419 #> 4726 2046 3M CC31 2019 2019-03-13 TSS 1.3862943611 I #> 4727 2046 3M CC31 2019 2019-03-13 TURB 0.8754687374 #> 4728 2046 3M CC31 2019 2019-04-23 CHLAC 1.8562979904 #> 4729 2046 3M CC31 2019 2019-04-23 COND 10.2120745857 #> 4730 2046 3M CC31 2019 2019-04-23 DO 1.8389610707 #> 4731 2046 3M CC31 2019 2019-04-23 DOSAT 4.4188406078 #> 4732 2046 3M CC31 2019 2019-04-23 NO23 -5.5214609179 U #> 4733 2046 3M CC31 2019 2019-04-23 SALIN 2.8154087194 #> 4734 2046 3M CC31 2019 2019-04-23 TKN -0.4307829161 #> 4735 2046 3M CC31 2019 2019-04-23 TN -0.4277107171 + #> 4736 2046 3M CC31 2019 2019-04-23 TP -1.6094379124 #> 4737 2046 3M CC31 2019 2019-04-23 TSS 2.5649493575 #> 4738 2046 3M CC31 2019 2019-04-23 TURB 1.4350845253 #> 4739 2046 3M CC31 2019 2019-07-22 CHLAC 2.0281482473 #> 4740 2046 3M CC31 2019 2019-07-22 COND 9.5882287123 #> 4741 2046 3M CC31 2019 2019-07-22 DO 1.6808279085 #> 4742 2046 3M CC31 2019 2019-07-22 DOSAT 4.3174881135 #> 4743 2046 3M CC31 2019 2019-07-22 NO23 -5.1159958098 I #> 4744 2046 3M CC31 2019 2019-07-22 SALIN 2.1282317058 #> 4745 2046 3M CC31 2019 2019-07-22 TKN -0.2484613593 #> 4746 2046 3M CC31 2019 2019-07-22 TN -0.2433462586 + #> 4747 2046 3M CC31 2019 2019-07-22 TP -1.3862943611 #> 4748 2046 3M CC31 2019 2019-07-22 TSS 0.6931471806 I #> 4749 2046 3M CC31 2019 2019-07-22 TURB 0.7419373447 #> 4750 2046 3M CC31 2019 2019-09-04 CHLAC 2.6390573296 #> 4751 2046 3M CC31 2019 2019-09-04 COND 9.5618419571 #> 4752 2046 3M CC31 2019 2019-09-04 DO 1.6486586256 #> 4753 2046 3M CC31 2019 2019-09-04 DOSAT 4.2752762647 #> 4754 2046 3M CC31 2019 2019-09-04 NO23 -3.1465551633 #> 4755 2046 3M CC31 2019 2019-09-04 SALIN 2.1004689089 #> 4756 2046 3M CC31 2019 2019-09-04 TKN -0.1863295782 #> 4757 2046 3M CC31 2019 2019-09-04 TN -0.1358197231 + #> 4758 2046 3M CC31 2019 2019-09-04 TP -1.5141277326 #> 4759 2046 3M CC31 2019 2019-09-04 TSS 1.3862943611 I #> 4760 2046 3M CC31 2019 2019-09-04 TURB 0.6418538862 #> 4761 2046 3M CC31 2020 2020-01-14 COND 10.2603574775 #> 4762 2046 3M CC31 2020 2020-01-14 DO 1.8341801851 #> 4763 2046 3M CC31 2020 2020-01-14 DOSAT 4.4140096805 #> 4764 2046 3M CC31 2020 2020-01-14 SALIN 2.8690346205 #> 4765 2046 3M CC31 2020 2020-02-18 CHLAC 0.8329091229 I #> 4766 2046 3M CC31 2020 2020-02-18 COND 10.3879178649 #> 4767 2046 3M CC31 2020 2020-02-18 DO 1.8976198599 #> 4768 2046 3M CC31 2020 2020-02-18 DOSAT 4.5075573571 #> 4769 2046 3M CC31 2020 2020-02-18 NO23 -4.8283137373 I #> 4770 2046 3M CC31 2020 2020-02-18 SALIN 3.0106208860 #> 4771 2046 3M CC31 2020 2020-02-18 TKN -0.5447271754 #> 4772 2046 3M CC31 2020 2020-02-18 TN -0.5378542962 + #> 4773 2046 3M CC31 2020 2020-02-18 TP -2.0402208285 #> 4774 2046 3M CC31 2020 2020-02-18 TSS 1.0986122887 I #> 4775 2046 3M CC31 2020 2020-02-18 TURB 0.4700036292 #> 4776 2046 3M CC31 2020 2020-06-09 CHLAC 2.9444389792 #> 4777 2046 3M CC31 2020 2020-06-09 COND 10.1025842827 #> 4778 2046 3M CC31 2020 2020-06-09 DO 1.5973653312 #> 4779 2046 3M CC31 2020 2020-06-09 DOSAT 4.2297491992 #> 4780 2046 3M CC31 2020 2020-06-09 NO23 -4.9618451299 I #> 4781 2046 3M CC31 2020 2020-06-09 SALIN 2.6919208192 #> 4782 2046 3M CC31 2020 2020-06-09 TKN 0.0000000000 #> 4783 2046 3M CC31 2020 2020-06-09 TN 0.0039920213 + #> 4784 2046 3M CC31 2020 2020-06-09 TP -1.2729656758 #> 4785 2046 3M CC31 2020 2020-06-09 TSS 1.3862943611 I #> 4786 2046 3M CC31 2020 2020-06-09 TURB 0.5306282511 #> 4787 2046 3M CC31 2020 2020-08-10 COND 10.0585663729 #> 4788 2046 3M CC31 2020 2020-08-10 DO 0.7419373447 #> 4789 2046 3M CC31 2020 2020-08-10 DOSAT 3.4177266836 #> 4790 2046 3M CC31 2020 2020-08-10 SALIN 2.6426223958 #> 4791 2046 3M CC31 2020 2020-09-22 CHLAC 2.4849066498 #> 4792 2046 3M CC31 2020 2020-09-22 COND 9.3350328159 #> 4793 2046 3M CC31 2020 2020-09-22 DO 1.5789787049 #> 4794 2046 3M CC31 2020 2020-09-22 DOSAT 4.1573193614 #> 4795 2046 3M CC31 2020 2020-09-22 NO23 -3.0791138825 #> 4796 2046 3M CC31 2020 2020-09-22 SALIN 1.8578592709 #> 4797 2046 3M CC31 2020 2020-09-22 TKN -0.0408219945 #> 4798 2046 3M CC31 2020 2020-09-22 TN 0.0059820717 + #> 4799 2046 3M CC31 2020 2020-09-22 TP -1.4271163556 #> 4800 2046 3M CC31 2020 2020-09-22 TSS 1.0986122887 I #> 4801 2046 3M CC31 2020 2020-09-22 TURB 0.9932517730 #> 4802 2046 3M CC31 2020 2020-10-20 CHLAC 1.4586150227 #> 4803 2046 3M CC31 2020 2020-10-20 COND 9.7670949276 #> 4804 2046 3M CC31 2020 2020-10-20 DO 1.4085449701 #> 4805 2046 3M CC31 2020 2020-10-20 DOSAT 4.0000338828 #> 4806 2046 3M CC31 2020 2020-10-20 NO23 -2.5510464523 #> 4807 2046 3M CC31 2020 2020-10-20 SALIN 2.3282528397 #> 4808 2046 3M CC31 2020 2020-10-20 TKN -0.0833816089 #> 4809 2046 3M CC31 2020 2020-10-20 TN -0.0020020027 + #> 4810 2046 3M CC31 2020 2020-10-20 TP -1.5141277326 #> 4811 2046 3M CC31 2020 2020-10-20 TSS 1.0986122887 I #> 4812 2046 3M CC31 2020 2020-10-20 TURB 0.5877866649 #> 4813 2046 3M CC31 2020 2020-12-14 CHLAC 1.0647107370 #> 4814 2046 3M CC31 2020 2020-12-14 COND 9.9551782679 #> 4815 2046 3M CC31 2020 2020-12-14 DO 1.8293763328 #> 4816 2046 3M CC31 2020 2020-12-14 DOSAT 4.3528552574 #> 4817 2046 3M CC31 2020 2020-12-14 NO23 -2.7181005370 #> 4818 2046 3M CC31 2020 2020-12-14 SALIN 2.5360749364 #> 4819 2046 3M CC31 2020 2020-12-14 TKN -0.2107210313 #> 4820 2046 3M CC31 2020 2020-12-14 TN -0.1323891880 + #> 4821 2046 3M CC31 2020 2020-12-14 TP -2.1202635362 #> 4822 2046 3M CC31 2020 2020-12-14 TSS 1.6094379124 I #> 4823 2046 3M CC31 2020 2020-12-14 TURB 0.5306282511 #> 4824 2046 3M CC31 2021 2021-02-03 CHLAC 0.9932517730 #> 4825 2046 3M CC31 2021 2021-02-03 COND 10.2269830978 #> 4826 2046 3M CC31 2021 2021-02-03 DO 2.0655961349 #> 4827 2046 3M CC31 2021 2021-02-03 DOSAT 4.5130548971 #> 4828 2046 3M CC31 2021 2021-02-03 NO23 -4.0745419349 #> 4829 2046 3M CC31 2021 2021-02-03 SALIN 2.8355635214 #> 4830 2046 3M CC31 2021 2021-02-03 TKN -0.4780358009 #> 4831 2046 3M CC31 2021 2021-02-03 TN -0.4509856234 + #> 4832 2046 3M CC31 2021 2021-02-03 TP -2.3025850930 #> 4833 2046 3M CC31 2021 2021-02-03 TSS 1.7917594692 I #> 4834 2046 3M CC31 2021 2021-02-03 TURB 0.5306282511 #> 4835 2046 3M CC31 2021 2021-03-09 CHLAC 2.0918640617 #> 4836 2046 3M CC31 2021 2021-03-09 COND 10.3281668796 #> 4837 2046 3M CC31 2021 2021-03-09 DO 2.2523438766 #> 4838 2046 3M CC31 2021 2021-03-09 DOSAT 4.7757564866 #> 4839 2046 3M CC31 2021 2021-03-09 NO23 -5.5214609179 U #> 4840 2046 3M CC31 2021 2021-03-09 SALIN 2.9460166813 #> 4841 2046 3M CC31 2021 2021-03-09 TKN -0.1863295782 #> 4842 2046 3M CC31 2021 2021-03-09 TN -0.1839228382 + #> 4843 2046 3M CC31 2021 2021-03-09 TP -1.5606477483 #> 4844 2046 3M CC31 2021 2021-03-09 TSS 2.8332133441 #> 4845 2046 3M CC31 2021 2021-03-09 TURB 2.0412203289 #> 4846 2046 3M CC31 2021 2021-05-05 CHLAC 0.9555114450 #> 4847 2046 3M CC31 2021 2021-05-05 COND 10.5683895677 #> 4848 2046 3M CC31 2021 2021-05-05 DO 1.3402504226 #> 4849 2046 3M CC31 2021 2021-05-05 DOSAT 4.0465538984 #> 4850 2046 3M CC31 2021 2021-05-05 NO23 -5.5214609179 U #> 4851 2046 3M CC31 2021 2021-05-05 SALIN 3.2043711387 #> 4852 2046 3M CC31 2021 2021-05-05 TKN -0.4620354596 #> 4853 2046 3M CC31 2021 2021-05-05 TN -0.4588658848 + #> 4854 2046 3M CC31 2021 2021-05-05 TP -1.5141277326 #> 4855 2046 3M CC31 2021 2021-05-05 TSS 1.7917594692 I #> 4856 2046 3M CC31 2021 2021-05-05 TURB 0.4700036292 #> 4857 2046 3M CC31 2021 2021-06-03 CHLAC 0.9932517730 I #> 4858 2046 3M CC31 2021 2021-06-03 COND 10.6275033568 #> 4859 2046 3M CC31 2021 2021-06-03 DO 0.8329091229 #> 4860 2046 3M CC31 2021 2021-06-03 DOSAT 3.5322256441 #> 4861 2046 3M CC31 2021 2021-06-03 NO23 -5.5214609179 U #> 4862 2046 3M CC31 2021 2021-06-03 SALIN 3.2718477096 #> 4863 2046 3M CC31 2021 2021-06-03 TKN -0.3285040670 #> 4864 2046 3M CC31 2021 2021-06-03 TN -0.3257301401 + #> 4865 2046 3M CC31 2021 2021-06-03 TP -1.4271163556 #> 4866 2046 3M CC31 2021 2021-06-03 TSS 1.0986122887 I #> 4867 2046 3M CC31 2021 2021-06-03 TURB 0.5306282511 #> 4868 2046 3M CC31 2021 2021-07-01 CHLAC 2.7080502011 #> 4869 2046 3M CC31 2021 2021-07-01 COND 10.4739019677 #> 4870 2046 3M CC31 2021 2021-07-01 DO 1.6770965609 #> 4871 2046 3M CC31 2021 2021-07-01 DOSAT 4.3107991254 #> 4872 2046 3M CC31 2021 2021-07-01 NO23 -5.2983173665 I #> 4873 2046 3M CC31 2021 2021-07-01 SALIN 3.1014427280 #> 4874 2046 3M CC31 2021 2021-07-01 TKN -0.4462871026 #> 4875 2046 3M CC31 2021 2021-07-01 TN -0.4400565529 + #> 4876 2046 3M CC31 2021 2021-07-01 TP -1.2729656758 #> 4877 2046 3M CC31 2021 2021-07-01 TSS 1.7917594692 I #> 4878 2046 3M CC31 2021 2021-07-01 TURB 0.4054651081 #> 4879 2046 3M CC31 2021 2021-07-29 CHLAC 2.9444389792 #> 4880 2046 3M CC31 2021 2021-07-29 COND 9.3783094225 #> 4881 2046 3M CC31 2021 2021-07-29 DO 1.3558351536 #> 4882 2046 3M CC31 2021 2021-07-29 DOSAT 3.9646154555 #> 4883 2046 3M CC31 2021 2021-07-29 NO23 -3.3242363405 #> 4884 2046 3M CC31 2021 2021-07-29 SALIN 1.9021075264 #> 4885 2046 3M CC31 2021 2021-07-29 TKN 0.0953101798 #> 4886 2046 3M CC31 2021 2021-07-29 TN 0.1275133203 + #> 4887 2046 3M CC31 2021 2021-07-29 TP -0.9942522733 #> 4888 2046 3M CC31 2021 2021-07-29 TSS 1.6094379124 I #> 4889 2046 3M CC31 2021 2021-07-29 TURB 1.6094379124 #> 4890 2046 3M CC31 2021 2021-08-25 CHLAC 2.4849066498 #> 4891 2046 3M CC31 2021 2021-08-25 COND 9.4766200382 #> 4892 2046 3M CC31 2021 2021-08-25 DO 0.8153648133 #> 4893 2046 3M CC31 2021 2021-08-25 DOSAT 3.4404180948 #> 4894 2046 3M CC31 2021 2021-08-25 NO23 -4.0745419349 #> 4895 2046 3M CC31 2021 2021-08-25 SALIN 2.0095554142 #> 4896 2046 3M CC31 2021 2021-08-25 TKN 0.0000000000 #> 4897 2046 3M CC31 2021 2021-08-25 TN 0.0168571171 + #> 4898 2046 3M CC31 2021 2021-08-25 TP -1.1086626245 #> 4899 2046 3M CC31 2021 2021-08-25 TSS 1.7917594692 I #> 4900 2046 3M CC31 2021 2021-08-25 TURB 1.1939224685 #> 4901 2046 3M CC31 2021 2021-09-23 CHLAC 3.0445224377 #> 4902 2046 3M CC31 2021 2021-09-23 COND 8.7826296549 #> 4903 2046 3M CC31 2021 2021-09-23 DO 1.4747630091 #> 4904 2046 3M CC31 2021 2021-09-23 DOSAT 4.0483006237 #> 4905 2046 3M CC31 2021 2021-09-23 NO23 -3.0576076773 #> 4906 2046 3M CC31 2021 2021-09-23 SALIN 1.2641267271 #> 4907 2046 3M CC31 2021 2021-09-23 TKN -0.0943106795 #> 4908 2046 3M CC31 2021 2021-09-23 TN -0.0439518875 + #> 4909 2046 3M CC31 2021 2021-09-23 TP -1.4271163556 #> 4910 2046 3M CC31 2021 2021-09-23 TSS 1.3862943611 I #> 4911 2046 3M CC31 2021 2021-09-23 TURB 1.1631508098 #> 4912 2046 3M CC31 2021 2021-10-21 CHLAC 2.3025850930 #> 4913 2046 3M CC31 2021 2021-10-21 COND 9.9156631285 #> 4914 2046 3M CC31 2021 2021-10-21 DO 1.5040773968 #> 4915 2046 3M CC31 2021 2021-10-21 DOSAT 4.0690267542 #> 4916 2046 3M CC31 2021 2021-10-21 NO23 -3.1465551633 #> 4917 2046 3M CC31 2021 2021-10-21 SALIN 2.4907230351 #> 4918 2046 3M CC31 2021 2021-10-21 TKN -0.1278333715 #> 4919 2046 3M CC31 2021 2021-10-21 TN -0.0801260445 + #> 4920 2046 3M CC31 2021 2021-10-21 TP -1.5141277326 #> 4921 2046 3M CC31 2021 2021-10-21 TSS 1.0986122887 U #> 4922 2046 3M CC31 2021 2021-10-21 TURB 0.4700036292 A #> 4923 2046 3M CC31 2021 2021-11-22 COND 10.1079374614 #> 4924 2046 3M CC31 2021 2021-11-22 DO 1.7316555452 #> 4925 2046 3M CC31 2021 2021-11-22 DOSAT 4.2877159552 #> 4926 2046 3M CC31 2021 2021-11-22 NO23 -2.8134107168 #> 4927 2046 3M CC31 2021 2021-11-22 SALIN 2.7020321288 #> 4928 2046 3M CC31 2021 2021-11-22 TKN -0.6733445533 #> 4929 2046 3M CC31 2021 2021-11-22 TN -0.5621189182 + #> 4930 2046 3M CC31 2021 2021-11-22 TP -2.3025850930 #> 4931 2046 3M CC31 2021 2021-11-22 TSS 1.6094379124 I #> 4932 2046 3M CC31 2021 2021-11-22 TURB 0.1823215568 A #> 4933 2046 3M CC31 2022 2022-02-22 CHLAC 1.3083328197 #> 4934 2046 3M CC31 2022 2022-02-22 COND 10.5165899421 #> 4935 2046 3M CC31 2022 2022-02-22 DO 1.8547342684 #> 4936 2046 3M CC31 2022 2022-02-22 DOSAT 4.4320065670 #> 4937 2046 3M CC31 2022 2022-02-22 NO23 -5.5214609179 U #> 4938 2046 3M CC31 2022 2022-02-22 SALIN 3.1527360224 #> 4939 2046 3M CC31 2022 2022-02-22 TKN -0.6931471806 #> 4940 2046 3M CC31 2022 2022-02-22 TN -0.6891551593 + #> 4941 2046 3M CC31 2022 2022-02-22 TP -2.4304184645 #> 4942 2046 3M CC31 2022 2022-02-22 TSS 2.0794415417 I #> 4943 2046 3M CC31 2022 2022-02-22 TURB 0.4054651081 A #> 4944 2046 3M CC31 2022 2022-04-20 CHLAC 1.5260563035 #> 4945 2046 3M CC31 2022 2022-04-20 COND 10.6492271832 #> 4946 2046 3M CC31 2022 2022-04-20 DO 1.5581446180 #> 4947 2046 3M CC31 2022 2022-04-20 DOSAT 4.1805222585 #> 4948 2046 3M CC31 2022 2022-04-20 NO23 -5.5214609179 U #> 4949 2046 3M CC31 2022 2022-04-20 SALIN 3.2987954480 #> 4950 2046 3M CC31 2022 2022-04-20 TKN -0.5447271754 #> 4951 2046 3M CC31 2022 2022-04-20 TN -0.5412848313 + #> 4952 2046 3M CC31 2022 2022-04-20 TP -1.8325814637 #> 4953 2046 3M CC31 2022 2022-04-20 TSS 2.0794415417 I #> 4954 2046 3M CC31 2022 2022-04-20 TURB 1.0296194172 #> 4955 2046 3M CC31 2022 2022-06-07 CHLAC 1.9021075264 #> 4956 2046 3M CC31 2022 2022-06-07 COND 10.4903571304 #> 4957 2046 3M CC31 2022 2022-06-07 DO 1.2412685891 #> 4958 2046 3M CC31 2022 2022-06-07 DOSAT 3.9318256327 #> 4959 2046 3M CC31 2022 2022-06-07 NO23 -5.2983173665 I #> 4960 2046 3M CC31 2022 2022-06-07 SALIN 3.1188344707 #> 4961 2046 3M CC31 2022 2022-06-07 TKN -0.4942963218 #> 4962 2046 3M CC31 2022 2022-06-07 TN -0.4877603508 + #> 4963 2046 3M CC31 2022 2022-06-07 TP -1.4696759701 #> 4964 2046 3M CC31 2022 2022-06-07 TSS 2.0794415417 I #> 4965 2046 3M CC31 2022 2022-06-07 TURB 0.1823215568 #> 4966 2046 3M CC31 2022 2022-08-15 CHLAC 2.1282317058 #> 4967 2046 3M CC31 2022 2022-08-15 COND 9.6188009891 #> 4968 2046 3M CC31 2022 2022-08-15 DO 0.9895411936 #> 4969 2046 3M CC31 2022 2022-08-15 DOSAT 3.6054978452 #> 4970 2046 3M CC31 2022 2022-08-15 NO23 -3.4737680745 #> 4971 2046 3M CC31 2022 2022-08-15 SALIN 2.1667653699 #> 4972 2046 3M CC31 2022 2022-08-15 TKN -0.0833816089 #> 4973 2046 3M CC31 2022 2022-08-15 TN -0.0502412164 + #> 4974 2046 3M CC31 2022 2022-08-15 TP -1.4696759701 #> 4975 2046 3M CC31 2022 2022-08-15 TSS 1.0986122887 I #> 4976 2046 3M CC31 2022 2022-08-15 TURB 0.6931471806 #> 4977 2046 3M CC31 2022 2022-12-15 CHLAC 0.9555114450 #> 4978 2046 3M CC31 2022 2022-12-15 COND 10.2729108893 #> 4979 2046 3M CC31 2022 2022-12-15 DO 1.7630170004 #> 4980 2046 3M CC31 2022 2022-12-15 DOSAT 4.3267781604 #> 4981 2046 3M CC31 2022 2022-12-15 NO23 -2.9759296463 #> 4982 2046 3M CC31 2022 2022-12-15 SALIN 2.8836827697 #> 4983 2046 3M CC31 2022 2022-12-15 TKN -0.4942963218 #> 4984 2046 3M CC31 2022 2022-12-15 TN -0.4140014391 + #> 4985 2046 3M CC31 2022 2022-12-15 TP -1.6094379124 #> 4986 2046 3M CC31 2022 2022-12-15 TSS 2.0794415417 I #> 4987 2046 3M CC31 2022 2022-12-15 TURB 0.0000000000 #> 4988 2046 3M CC31 2023 2023-01-11 CHLAC 2.0668627595 #> 4989 2046 3M CC31 2023 2023-01-11 COND 10.2352702390 #> 4990 2046 3M CC31 2023 2023-01-11 DO 1.7984040119 #> 4991 2046 3M CC31 2023 2023-01-11 DOSAT 4.2849649218 #> 4992 2046 3M CC31 2023 2023-01-11 NO23 -3.9633162998 #> 4993 2046 3M CC31 2023 2023-01-11 SALIN 2.8443278194 #> 4994 2046 3M CC31 2023 2023-01-11 TKN -0.5798184953 #> 4995 2046 3M CC31 2023 2023-01-11 TN -0.5464528014 + #> 4996 2046 3M CC31 2023 2023-01-11 TP -1.8325814637 #> 4997 2046 3M CC31 2023 2023-01-11 TSS 1.7917594692 I #> 4998 2046 3M CC31 2023 2023-01-11 TURB 0.7419373447 #> 4999 2046 3M CC31 2023 2023-03-23 CHLAC 1.7578579176 #> 5000 2046 3M CC31 2023 2023-03-23 COND 10.4503364755 #> 5001 2046 3M CC31 2023 2023-03-23 DO 1.8840347453 #> 5002 2046 3M CC31 2023 2023-03-23 DOSAT 4.4461744545 #> 5003 2046 3M CC31 2023 2023-03-23 NO23 -5.5214609179 U #> 5004 2046 3M CC31 2023 2023-03-23 SALIN 3.0796137575 #> 5005 2046 3M CC31 2023 2023-03-23 TKN -0.1984509387 #> 5006 2046 3M CC31 2023 2023-03-23 TN -0.1960148839 + #> 5007 2046 3M CC31 2023 2023-03-23 TP -1.1711829815 #> 5008 2046 3M CC31 2023 2023-03-23 TSS 2.7725887222 #> 5009 2046 3M CC31 2023 2023-03-23 TURB 1.7047480922 #> 5010 2046 3M CC31 2023 2023-05-08 CHLAC 1.2809338455 #> 5011 2046 3M CC31 2023 2023-05-08 COND 10.5443145959 #> 5012 2046 3M CC31 2023 2023-05-08 DO 1.6014057407 #> 5013 2046 3M CC31 2023 2023-05-08 DOSAT 4.2370008626 #> 5014 2046 3M CC31 2023 2023-05-08 NO23 -4.7105307016 I #> 5015 2046 3M CC31 2023 2023-05-08 SALIN 3.1813816204 #> 5016 2046 3M CC31 2023 2023-05-08 TKN -0.3710636814 #> 5017 2046 3M CC31 2023 2023-05-08 TN -0.3652833185 + #> 5018 2046 3M CC31 2023 2023-05-08 TP -1.6094379124 #> 5019 2046 3M CC31 2023 2023-05-08 TSS 1.7917594692 I #> 5020 2046 3M CC31 2023 2023-05-08 TURB 0.0953101798 #> 5021 2056E 3M CC34 2015 2015-04-06 CHLAC 1.5040773968 #> 5022 2056E 3M CC34 2015 2015-04-06 COLOR 3.8066624898 #> 5023 2056E 3M CC34 2015 2015-04-06 COND 10.4003156667 #> 5024 2056E 3M CC34 2015 2015-04-06 DO 2.1317967720 #> 5025 2056E 3M CC34 2015 2015-04-06 DOSAT 4.7899886230 + #> 5026 2056E 3M CC34 2015 2015-04-06 NO23 -5.5214609179 U #> 5027 2056E 3M CC34 2015 2015-04-06 SALIN 3.0194488002 #> 5028 2056E 3M CC34 2015 2015-04-06 TKN -0.3509769228 #> 5029 2056E 3M CC34 2015 2015-04-06 TN -0.3509769228 #> 5030 2056E 3M CC34 2015 2015-04-06 TP -1.6928195214 #> 5031 2056E 3M CC34 2015 2015-04-06 TSS 1.6253112616 #> 5032 2056E 3M CC34 2015 2015-04-06 TURB 1.0647107370 #> 5033 2056E 3M CC34 2015 2015-04-06 COND 10.4033533361 #> 5034 2056E 3M CC34 2015 2015-04-06 DO 2.1341664414 #> 5035 2056E 3M CC34 2015 2015-04-06 DOSAT 4.7899886230 + #> 5036 2056E 3M CC34 2015 2015-04-06 SALIN 3.0233474406 #> 5037 2056E 3M CC34 2015 2015-04-06 COND 10.4069864009 #> 5038 2056E 3M CC34 2015 2015-04-06 DO 2.1435893615 #> 5039 2056E 3M CC34 2015 2015-04-06 DOSAT 4.7949637576 + #> 5040 2056E 3M CC34 2015 2015-04-06 SALIN 3.0272309406 #> 5041 2056E 3M CC36 2015 2015-04-06 CHLAC 1.5040773968 #> 5042 2056E 3M CC36 2015 2015-04-06 COLOR 3.8066624898 #> 5043 2056E 3M CC36 2015 2015-04-06 COND 10.4003156667 #> 5044 2056E 3M CC36 2015 2015-04-06 DO 2.1317967720 #> 5045 2056E 3M CC36 2015 2015-04-06 DOSAT 4.7899886230 + #> 5046 2056E 3M CC36 2015 2015-04-06 NO23 -5.5214609179 U #> 5047 2056E 3M CC36 2015 2015-04-06 SALIN 3.0194488002 #> 5048 2056E 3M CC36 2015 2015-04-06 TKN -0.3509769228 #> 5049 2056E 3M CC36 2015 2015-04-06 TN -0.3509769228 #> 5050 2056E 3M CC36 2015 2015-04-06 TP -1.6928195214 #> 5051 2056E 3M CC36 2015 2015-04-06 TSS 1.6253112616 #> 5052 2056E 3M CC36 2015 2015-04-06 TURB 1.0647107370 #> 5053 2056E 3M CC36 2015 2015-04-06 COND 10.4033533361 #> 5054 2056E 3M CC36 2015 2015-04-06 DO 2.1341664414 #> 5055 2056E 3M CC36 2015 2015-04-06 DOSAT 4.7899886230 + #> 5056 2056E 3M CC36 2015 2015-04-06 SALIN 3.0233474406 #> 5057 2056E 3M CC36 2015 2015-04-06 COND 10.4069864009 #> 5058 2056E 3M CC36 2015 2015-04-06 DO 2.1435893615 #> 5059 2056E 3M CC36 2015 2015-04-06 DOSAT 4.7949637576 + #> 5060 2056E 3M CC36 2015 2015-04-06 SALIN 3.0272309406 #> 5061 2056E 3M CC37 2014 2014-01-06 CHLAC 1.5686159179 #> 5062 2056E 3M CC37 2014 2014-01-06 COLOR 2.9957322736 A #> 5063 2056E 3M CC37 2014 2014-01-06 DOSAT 4.3832758541 + #> 5064 2056E 3M CC37 2014 2014-01-06 NO23 -4.3428059215 #> 5065 2056E 3M CC37 2014 2014-01-06 SALIN 3.3032169733 #> 5066 2056E 3M CC37 2014 2014-01-06 TKN -0.5978370008 #> 5067 2056E 3M CC37 2014 2014-01-06 TN -0.5744756508 + #> 5068 2056E 3M CC37 2014 2014-01-06 TP -2.3025850930 #> 5069 2056E 3M CC37 2014 2014-01-06 TURB 0.2623642645 #> 5070 2056E 3M CC37 2014 2014-02-03 CHLAC 1.4816045409 #> 5071 2056E 3M CC37 2014 2014-02-03 COLOR 2.7725887222 #> 5072 2056E 3M CC37 2014 2014-02-03 DO 1.8562979904 #> 5073 2056E 3M CC37 2014 2014-02-03 DOSAT 4.3502779364 + #> 5074 2056E 3M CC37 2014 2014-02-03 NO23 -3.2968373663 #> 5075 2056E 3M CC37 2014 2014-02-03 SALIN 2.6461747974 #> 5076 2056E 3M CC37 2014 2014-02-03 TKN -0.1743533871 #> 5077 2056E 3M CC37 2014 2014-02-03 TN -0.1312482866 + #> 5078 2056E 3M CC37 2014 2014-02-03 TP -2.3025850930 #> 5079 2056E 3M CC37 2014 2014-02-03 TURB 0.7419373447 #> 5080 2056E 3M CC37 2014 2014-03-03 CHLAC 1.7578579176 #> 5081 2056E 3M CC37 2014 2014-03-03 COLOR 2.8903717579 A #> 5082 2056E 3M CC37 2014 2014-03-03 DO 1.8082887712 #> 5083 2056E 3M CC37 2014 2014-03-03 DOSAT 4.3579900568 + #> 5084 2056E 3M CC37 2014 2014-03-03 NO23 -4.5098600062 #> 5085 2056E 3M CC37 2014 2014-03-03 SALIN 3.1000922889 #> 5086 2056E 3M CC37 2014 2014-03-03 TKN -0.2744368457 #> 5087 2056E 3M CC37 2014 2014-03-03 TN -0.2600669054 + #> 5088 2056E 3M CC37 2014 2014-03-03 TP -1.8971199849 #> 5089 2056E 3M CC37 2014 2014-03-03 TURB 1.0296194172 #> 5090 2056E 3M CC37 2014 2014-04-07 CHLAC 2.2721258855 #> 5091 2056E 3M CC37 2014 2014-04-07 COLOR 2.9444389792 #> 5092 2056E 3M CC37 2014 2014-04-07 DO 1.8718021769 #> 5093 2056E 3M CC37 2014 2014-04-07 DOSAT 4.4953553200 + #> 5094 2056E 3M CC37 2014 2014-04-07 NO23 -4.9618451299 I #> 5095 2056E 3M CC37 2014 2014-04-07 SALIN 3.1000922889 #> 5096 2056E 3M CC37 2014 2014-04-07 TKN -0.4942963218 #> 5097 2056E 3M CC37 2014 2014-04-07 TN -0.4877603508 + #> 5098 2056E 3M CC37 2014 2014-04-07 TP -1.7147984281 #> 5099 2056E 3M CC37 2014 2014-04-07 TURB 1.2237754316 #> 5100 2056E 3M CC37 2014 2014-05-05 CHLAC 3.0445224377 #> 5101 2056E 3M CC37 2014 2014-05-05 COLOR 3.0910424534 #> 5102 2056E 3M CC37 2014 2014-05-05 DO 1.7917594692 #> 5103 2056E 3M CC37 2014 2014-05-05 DOSAT 4.4152196020 + #> 5104 2056E 3M CC37 2014 2014-05-05 NO23 -5.1159958098 I #> 5105 2056E 3M CC37 2014 2014-05-05 SALIN 3.2068032436 #> 5106 2056E 3M CC37 2014 2014-05-05 TKN -0.0100503359 #> 5107 2056E 3M CC37 2014 2014-05-05 TN -0.0060180723 + #> 5108 2056E 3M CC37 2014 2014-05-05 TP -1.2729656758 #> 5109 2056E 3M CC37 2014 2014-05-05 TURB 1.9315214116 #> 5110 2056E 3M CC37 2014 2014-06-02 CHLAC 2.2617630985 #> 5111 2056E 3M CC37 2014 2014-06-02 COLOR 3.2188758249 #> 5112 2056E 3M CC37 2014 2014-06-02 DO 1.6292405397 #> 5113 2056E 3M CC37 2014 2014-06-02 DOSAT 4.3040650932 + #> 5114 2056E 3M CC37 2014 2014-06-02 NO23 -5.1159958098 I #> 5115 2056E 3M CC37 2014 2014-06-02 SALIN 3.2425923515 #> 5116 2056E 3M CC37 2014 2014-06-02 TKN -0.1625189295 #> 5117 2056E 3M CC37 2014 2014-06-02 TN -0.1578240852 + #> 5118 2056E 3M CC37 2014 2014-06-02 TP -1.0216512475 #> 5119 2056E 3M CC37 2014 2014-06-02 TURB 1.4816045409 #> 5120 2056E 3M CC37 2014 2014-07-07 CHLAC 2.5649493575 #> 5121 2056E 3M CC37 2014 2014-07-07 COLOR 3.3672958300 A #> 5122 2056E 3M CC37 2014 2014-07-07 NO23 -5.5214609179 I #> 5123 2056E 3M CC37 2014 2014-07-07 SALIN 3.1398326175 #> 5124 2056E 3M CC37 2014 2014-07-07 TKN -0.0304592075 #> 5125 2056E 3M CC37 2014 2014-07-07 TN -0.0263439753 + #> 5126 2056E 3M CC37 2014 2014-07-07 TP -0.9675840263 #> 5127 2056E 3M CC37 2014 2014-07-07 TURB 1.5260563035 #> 5128 2056E 3M CC37 2014 2014-08-04 CHLAC 2.7080502011 #> 5129 2056E 3M CC37 2014 2014-08-04 COLOR 4.0073331852 A #> 5130 2056E 3M CC37 2014 2014-08-04 DO 1.7047480922 #> 5131 2056E 3M CC37 2014 2014-08-04 DOSAT 4.3214801348 + #> 5132 2056E 3M CC37 2014 2014-08-04 NO23 -4.5098600062 #> 5133 2056E 3M CC37 2014 2014-08-04 SALIN 2.4336133554 #> 5134 2056E 3M CC37 2014 2014-08-04 TKN 0.0953101798 #> 5135 2056E 3M CC37 2014 2014-08-04 TN 0.1052605107 + #> 5136 2056E 3M CC37 2014 2014-08-04 TP -0.7550225843 #> 5137 2056E 3M CC37 2014 2014-08-04 TURB 1.0296194172 #> 5138 2056E 3M CC37 2014 2014-09-08 CHLAC 0.5877866649 #> 5139 2056E 3M CC37 2014 2014-09-08 COLOR 3.6375861597 A #> 5140 2056E 3M CC37 2014 2014-09-08 DOSAT 3.7588718259 + #> 5141 2056E 3M CC37 2014 2014-09-08 NO23 -4.1997050779 #> 5142 2056E 3M CC37 2014 2014-09-08 SALIN 2.6318888401 #> 5143 2056E 3M CC37 2014 2014-09-08 TKN -0.1743533871 #> 5144 2056E 3M CC37 2014 2014-09-08 TN -0.1566538100 + #> 5145 2056E 3M CC37 2014 2014-09-08 TP -1.0498221245 #> 5146 2056E 3M CC37 2014 2014-09-08 TURB 0.6931471806 A #> 5147 2056E 3M CC37 2014 2014-10-06 CHLAC 1.7917594692 #> 5148 2056E 3M CC37 2014 2014-10-06 COLOR 4.1588830834 A #> 5149 2056E 3M CC37 2014 2014-10-06 DO 1.3350010667 #> 5150 2056E 3M CC37 2014 2014-10-06 DOSAT 3.8458832029 + #> 5151 2056E 3M CC37 2014 2014-10-06 NO23 -2.9957322736 #> 5152 2056E 3M CC37 2014 2014-10-06 SALIN 1.9600947840 #> 5153 2056E 3M CC37 2014 2014-10-06 TKN -0.1508228897 #> 5154 2056E 3M CC37 2014 2014-10-06 TN -0.0943106795 + #> 5155 2056E 3M CC37 2014 2014-10-06 TP -1.1086626245 #> 5156 2056E 3M CC37 2014 2014-10-06 TURB 0.8754687374 #> 5157 2056E 3M CC37 2014 2014-11-03 CHLAC 2.1517622033 #> 5158 2056E 3M CC37 2014 2014-11-03 COLOR 3.9318256327 A #> 5159 2056E 3M CC37 2014 2014-11-03 DO 1.8245492921 #> 5160 2056E 3M CC37 2014 2014-11-03 DOSAT 4.2499227940 + #> 5161 2056E 3M CC37 2014 2014-11-03 NO23 -4.2686979494 #> 5162 2056E 3M CC37 2014 2014-11-03 SALIN 2.7600099400 #> 5163 2056E 3M CC37 2014 2014-11-03 TKN -0.1508228897 #> 5164 2056E 3M CC37 2014 2014-11-03 TN -0.1346749033 + #> 5165 2056E 3M CC37 2014 2014-11-03 TP -1.5606477483 #> 5166 2056E 3M CC37 2014 2014-11-03 TURB 0.7884573604 #> 5167 2056E 3M CC37 2014 2014-12-01 CHLAC 2.1633230257 #> 5168 2056E 3M CC37 2014 2014-12-01 COLOR 3.4657359028 #> 5169 2056E 3M CC37 2014 2014-12-01 DO 1.9600947840 #> 5170 2056E 3M CC37 2014 2014-12-01 DOSAT 4.4343818650 + #> 5171 2056E 3M CC37 2014 2014-12-01 NO23 -3.4737680745 #> 5172 2056E 3M CC37 2014 2014-12-01 SALIN 2.8622008809 #> 5173 2056E 3M CC37 2014 2014-12-01 TKN -0.3147107448 #> 5174 2056E 3M CC37 2014 2014-12-01 TN -0.2731219211 + #> 5175 2056E 3M CC37 2014 2014-12-01 TP -1.9661128564 #> 5176 2056E 3M CC37 2014 2014-12-01 TURB 0.7884573604 #> 5177 2056E 3M CC37 2015 2015-01-05 CHLAC 1.8870696490 #> 5178 2056E 3M CC37 2015 2015-01-05 COLOR 3.2958368660 A #> 5179 2056E 3M CC37 2015 2015-01-05 DO 1.7917594692 #> 5180 2056E 3M CC37 2015 2015-01-05 DOSAT 4.3732381286 + #> 5181 2056E 3M CC37 2015 2015-01-05 NO23 -3.9633162998 #> 5182 2056E 3M CC37 2015 2015-01-05 SALIN 2.9549102790 #> 5183 2056E 3M CC37 2015 2015-01-05 TKN -0.4780358009 #> 5184 2056E 3M CC37 2015 2015-01-05 TN -0.4478508246 + #> 5185 2056E 3M CC37 2015 2015-01-05 TP -2.1202635362 #> 5186 2056E 3M CC37 2015 2015-01-05 TURB 0.8754687374 #> 5187 2056E 3M CC37 2015 2015-02-02 CHLAC 1.6094379124 #> 5188 2056E 3M CC37 2015 2015-02-02 COLOR 2.8332133441 A #> 5189 2056E 3M CC37 2015 2015-02-02 DO 1.8245492921 #> 5190 2056E 3M CC37 2015 2015-02-02 DOSAT 4.3333614627 + #> 5191 2056E 3M CC37 2015 2015-02-02 NO23 -4.6051701860 #> 5192 2056E 3M CC37 2015 2015-02-02 SALIN 3.0773122605 #> 5193 2056E 3M CC37 2015 2015-02-02 TKN -0.6733445533 #> 5194 2056E 3M CC37 2015 2015-02-02 TN -0.6539264674 + #> 5195 2056E 3M CC37 2015 2015-02-02 TP -2.1202635362 #> 5196 2056E 3M CC37 2015 2015-02-02 TURB 0.9162907319 #> 5197 2056E 3M CC37 2015 2015-03-02 CHLAC 2.0014800002 #> 5198 2056E 3M CC37 2015 2015-03-02 COLOR 3.2958368660 #> 5199 2056E 3M CC37 2015 2015-03-02 DO 1.6486586256 #> 5200 2056E 3M CC37 2015 2015-03-02 DOSAT 4.2002049529 + #> 5201 2056E 3M CC37 2015 2015-03-02 NO23 -2.9759296463 #> 5202 2056E 3M CC37 2015 2015-03-02 SALIN 2.9285235239 #> 5203 2056E 3M CC37 2015 2015-03-02 TKN -0.3566749439 #> 5204 2056E 3M CC37 2015 2015-03-02 TN -0.2863496272 + #> 5205 2056E 3M CC37 2015 2015-03-02 TP -2.0402208285 #> 5206 2056E 3M CC37 2015 2015-03-02 TURB 0.7419373447 #> 5207 2056E 3M CC37 2015 2015-04-06 CHLAC 1.8245492921 #> 5208 2056E 3M CC37 2015 2015-04-06 COLOR 3.2188758249 A #> 5209 2056E 3M CC37 2015 2015-04-06 DO 1.6292405397 #> 5210 2056E 3M CC37 2015 2015-04-06 DOSAT 4.2297491992 + #> 5211 2056E 3M CC37 2015 2015-04-06 NO23 -4.5098600062 #> 5212 2056E 3M CC37 2015 2015-04-06 SALIN 3.0252910758 #> 5213 2056E 3M CC37 2015 2015-04-06 TKN -0.1165338163 #> 5214 2056E 3M CC37 2015 2015-04-06 TN -0.1042500214 + #> 5215 2056E 3M CC37 2015 2015-04-06 TP -1.6094379124 #> 5216 2056E 3M CC37 2015 2015-04-06 TURB 1.3083328197 #> 5217 2056E 3M CC37 2015 2015-05-04 CHLAC 1.7917594692 #> 5218 2056E 3M CC37 2015 2015-05-04 COLOR 3.2958368660 A #> 5219 2056E 3M CC37 2015 2015-05-04 DO 1.4816045409 #> 5220 2056E 3M CC37 2015 2015-05-04 DOSAT 4.0724397268 + #> 5221 2056E 3M CC37 2015 2015-05-04 NO23 -5.2983173665 I #> 5222 2056E 3M CC37 2015 2015-05-04 SALIN 3.0773122605 #> 5223 2056E 3M CC37 2015 2015-05-04 TKN -0.3856624808 #> 5224 2056E 3M CC37 2015 2015-05-04 TN -0.3797973614 + #> 5225 2056E 3M CC37 2015 2015-05-04 TP -2.0402208285 #> 5226 2056E 3M CC37 2015 2015-05-04 TURB 1.3350010667 #> 5227 2056E 3M CC37 2015 2015-06-01 CHLAC 2.7080502011 #> 5228 2056E 3M CC37 2015 2015-06-01 COLOR 3.2188758249 A #> 5229 2056E 3M CC37 2015 2015-06-01 DOSAT 4.0587173846 + #> 5230 2056E 3M CC37 2015 2015-06-01 NO23 -5.1159958098 I #> 5231 2056E 3M CC37 2015 2015-06-01 SALIN 2.8332133441 #> 5232 2056E 3M CC37 2015 2015-06-01 TKN 0.0000000000 #> 5233 2056E 3M CC37 2015 2015-06-01 TN 0.0039920213 + #> 5234 2056E 3M CC37 2015 2015-06-01 TP -1.1711829815 #> 5235 2056E 3M CC37 2015 2015-06-01 TURB 1.5475625087 A #> 5236 2056E 3M CC37 2015 2015-08-03 CHLAC 3.2580965380 #> 5237 2056E 3M CC37 2015 2015-08-03 COLOR 3.8286413965 #> 5238 2056E 3M CC37 2015 2015-08-03 DO 1.9169226122 #> 5239 2056E 3M CC37 2015 2015-08-03 DOSAT 4.4784725329 + #> 5240 2056E 3M CC37 2015 2015-08-03 NO23 -4.0173835211 #> 5241 2056E 3M CC37 2015 2015-08-03 SALIN 1.9021075264 #> 5242 2056E 3M CC37 2015 2015-08-03 TKN 0.0000000000 #> 5243 2056E 3M CC37 2015 2015-08-03 TN 0.0178399181 + #> 5244 2056E 3M CC37 2015 2015-08-03 TP -0.8439700703 #> 5245 2056E 3M CC37 2015 2015-08-03 TURB 1.0986122887 A #> 5246 2056E 3M CC37 2015 2015-09-08 CHLAC 2.7080502011 #> 5247 2056E 3M CC37 2015 2015-09-08 COLOR 4.7004803658 A #> 5248 2056E 3M CC37 2015 2015-09-08 DO 1.7227665977 #> 5249 2056E 3M CC37 2015 2015-09-08 DOSAT 4.3067641502 + #> 5250 2056E 3M CC37 2015 2015-09-08 NO23 -3.3242363405 #> 5251 2056E 3M CC37 2015 2015-09-08 SALIN 1.7749523509 #> 5252 2056E 3M CC37 2015 2015-09-08 TKN 0.1823215568 #> 5253 2056E 3M CC37 2015 2015-09-08 TN 0.2118803590 + #> 5254 2056E 3M CC37 2015 2015-09-08 TP -0.2613647641 #> 5255 2056E 3M CC37 2015 2015-09-08 TURB 1.3083328197 #> 5256 2056E 3M CC37 2015 2015-10-05 CHLAC 2.3978952728 #> 5257 2056E 3M CC37 2015 2015-10-05 COLOR 4.5643481915 A #> 5258 2056E 3M CC37 2015 2015-10-05 DO 1.8562979904 #> 5259 2056E 3M CC37 2015 2015-10-05 DOSAT 4.3732381286 + #> 5260 2056E 3M CC37 2015 2015-10-05 NO23 -3.7722610631 #> 5261 2056E 3M CC37 2015 2015-10-05 SALIN 2.2721258855 #> 5262 2056E 3M CC37 2015 2015-10-05 TKN -0.2876820725 #> 5263 2056E 3M CC37 2015 2015-10-05 TN -0.2574762304 + #> 5264 2056E 3M CC37 2015 2015-10-05 TP -0.9416085399 #> 5265 2056E 3M CC37 2015 2015-10-05 TURB 0.4054651081 #> 5266 2056E 3M CC37 2016 2016-02-01 CHLAC 2.6390573296 #> 5267 2056E 3M CC37 2016 2016-02-01 COLOR 4.5217885770 A #> 5268 2056E 3M CC37 2016 2016-02-01 NO23 -1.9661128564 #> 5269 2056E 3M CC37 2016 2016-02-01 TKN -0.3285040670 #> 5270 2056E 3M CC37 2016 2016-02-01 TN -0.1508228897 + #> 5271 2056E 3M CC37 2016 2016-02-01 TP -1.0216512475 #> 5272 2056E 3M CC37 2016 2016-02-01 TURB 0.9162907319 #> 5273 2056E 3M CC37 2016 2016-03-07 CHLAC 2.4849066498 #> 5274 2056E 3M CC37 2016 2016-03-07 COLOR 3.8918202981 A #> 5275 2056E 3M CC37 2016 2016-03-07 DO 1.6331544391 #> 5276 2056E 3M CC37 2016 2016-03-07 DOSAT 4.0859763126 + #> 5277 2056E 3M CC37 2016 2016-03-07 NO23 -4.1997050779 #> 5278 2056E 3M CC37 2016 2016-03-07 SALIN 2.7040421797 #> 5279 2056E 3M CC37 2016 2016-03-07 TKN -0.3011050928 #> 5280 2056E 3M CC37 2016 2016-03-07 TN -0.2810375297 + #> 5281 2056E 3M CC37 2016 2016-03-07 TP -1.5141277326 #> 5282 2056E 3M CC37 2016 2016-03-07 TURB 1.2527629685 #> 5283 2056E 3M CC37 2016 2016-04-04 CHLAC 2.3978952728 #> 5284 2056E 3M CC37 2016 2016-04-04 COLOR 3.6635616461 #> 5285 2056E 3M CC37 2016 2016-04-04 DO 1.3711807233 #> 5286 2056E 3M CC37 2016 2016-04-04 DOSAT 3.9512437186 + #> 5287 2056E 3M CC37 2016 2016-04-04 NO23 -3.5065578973 #> 5288 2056E 3M CC37 2016 2016-04-04 SALIN 2.6905648868 #> 5289 2056E 3M CC37 2016 2016-04-04 TKN -0.0202027073 #> 5290 2056E 3M CC37 2016 2016-04-04 TN 0.0099503309 + #> 5291 2056E 3M CC37 2016 2016-04-04 TP -1.3470736480 #> 5292 2056E 3M CC37 2016 2016-04-04 TURB 1.5260563035 #> 5293 2056E 3M CC37 2017 2017-02-06 CHLAC 2.8903717579 #> 5294 2056E 3M CC37 2017 2017-02-06 COLOR 2.9444389792 A #> 5295 2056E 3M CC37 2017 2017-02-06 DO 1.6311994042 #> 5296 2056E 3M CC37 2017 2017-02-06 DOSAT 4.2239097666 + #> 5297 2056E 3M CC37 2017 2017-02-06 NO23 -5.5214609179 U #> 5298 2056E 3M CC37 2017 2017-02-06 SALIN 3.3138223022 #> 5299 2056E 3M CC37 2017 2017-02-06 TKN -0.0943106795 #> 5300 2056E 3M CC37 2017 2017-02-06 TN -0.0921152889 + #> 5301 2056E 3M CC37 2017 2017-02-06 TP -1.7147984281 #> 5302 2056E 3M CC37 2017 2017-02-06 TURB 1.8562979904 #> 5303 2056E 3M CC37 2017 2017-03-06 CHLAC 2.1517622033 #> 5304 2056E 3M CC37 2017 2017-03-06 COLOR 2.7080502011 #> 5305 2056E 3M CC37 2017 2017-03-06 DO 1.7191887764 #> 5306 2056E 3M CC37 2017 2017-03-06 DOSAT 4.2931954210 + #> 5307 2056E 3M CC37 2017 2017-03-06 NO23 -5.5214609179 U #> 5308 2056E 3M CC37 2017 2017-03-06 SALIN 3.3279095859 #> 5309 2056E 3M CC37 2017 2017-03-06 TKN -0.1743533871 #> 5310 2056E 3M CC37 2017 2017-03-06 TN -0.1719752647 + #> 5311 2056E 3M CC37 2017 2017-03-06 TP -1.9661128564 #> 5312 2056E 3M CC37 2017 2017-03-06 TURB 1.3862943611 #> 5313 2056E 3M CC37 2017 2017-04-03 CHLAC 2.3978952728 #> 5314 2056E 3M CC37 2017 2017-04-03 COLOR 2.7080502011 A #> 5315 2056E 3M CC37 2017 2017-04-03 DO 1.5727739281 #> 5316 2056E 3M CC37 2017 2017-04-03 DOSAT 4.2640873368 + #> 5317 2056E 3M CC37 2017 2017-04-03 NO23 -5.5214609179 U #> 5318 2056E 3M CC37 2017 2017-04-03 SALIN 3.3914836895 #> 5319 2056E 3M CC37 2017 2017-04-03 TKN -0.1508228897 #> 5320 2056E 3M CC37 2017 2017-04-03 TN -0.1485000083 + #> 5321 2056E 3M CC37 2017 2017-04-03 TP -1.6607312068 #> 5322 2056E 3M CC37 2017 2017-04-03 TURB 1.3862943611 A #> 5323 2056E 3M CC37 2017 2017-07-10 CHLAC 2.7080502011 #> 5324 2056E 3M CC37 2017 2017-07-10 COLOR 4.7874917428 A #> 5325 2056E 3M CC37 2017 2017-07-10 DO 0.8415671857 #> 5326 2056E 3M CC37 2017 2017-07-10 DOSAT 3.4965075615 + #> 5327 2056E 3M CC37 2017 2017-07-10 NO23 -5.1159958098 I #> 5328 2056E 3M CC37 2017 2017-07-10 TKN 0.1823215568 #> 5329 2056E 3M CC37 2017 2017-07-10 TN 0.1856493469 + #> 5330 2056E 3M CC37 2017 2017-07-10 TP -0.4780358009 #> 5331 2056E 3M CC37 2017 2017-07-10 TURB 1.1939224685 #> 5332 2056E 3M CC37 2017 2017-08-07 CHLAC 1.6863989536 #> 5333 2056E 3M CC37 2017 2017-08-07 COLOR 4.7004803658 #> 5334 2056E 3M CC37 2017 2017-08-07 DO 0.7793248768 #> 5335 2056E 3M CC37 2017 2017-08-07 DOSAT 3.4144426084 + #> 5336 2056E 3M CC37 2017 2017-08-07 NO23 -2.2072749132 #> 5337 2056E 3M CC37 2017 2017-08-07 SALIN 1.7647307968 #> 5338 2056E 3M CC37 2017 2017-08-07 TKN 0.1823215568 #> 5339 2056E 3M CC37 2017 2017-08-07 TN 0.2700271372 + #> 5340 2056E 3M CC37 2017 2017-08-07 TP -0.8209805521 #> 5341 2056E 3M CC37 2017 2017-08-07 TURB 0.7884573604 #> 5342 2056E 3M CC37 2017 2017-09-05 CHLAC 2.8332133441 #> 5343 2056E 3M CC37 2017 2017-09-05 COLOR 4.4998096703 #> 5344 2056E 3M CC37 2017 2017-09-05 DO 1.4516138272 #> 5345 2056E 3M CC37 2017 2017-09-05 DOSAT 4.0377742107 + #> 5346 2056E 3M CC37 2017 2017-09-05 NO23 -2.4889146712 #> 5347 2056E 3M CC37 2017 2017-09-05 SALIN 0.1906203596 #> 5348 2056E 3M CC37 2017 2017-09-05 TKN -0.0725706928 #> 5349 2056E 3M CC37 2017 2017-09-05 TN 0.0129162253 + #> 5350 2056E 3M CC37 2017 2017-09-05 TP -0.9675840263 #> 5351 2056E 3M CC37 2017 2017-09-05 TURB 1.0986122887 #> 5352 2056E 3M CC37 2017 2017-10-02 CHLAC 1.9169226122 #> 5353 2056E 3M CC37 2017 2017-10-02 COLOR 4.4886363697 A #> 5354 2056E 3M CC37 2017 2017-10-02 NO23 -2.9565115604 #> 5355 2056E 3M CC37 2017 2017-10-02 TKN -0.8675005677 #> 5356 2056E 3M CC37 2017 2017-10-02 TN -0.7507762934 + #> 5357 2056E 3M CC37 2017 2017-10-02 TP -0.6348782724 #> 5358 2056E 3M CC37 2017 2017-10-02 TURB 0.7419373447 #> 5359 2056E 3M CC37 2017 2017-11-06 CHLAC 1.6292405397 #> 5360 2056E 3M CC37 2017 2017-11-06 COLOR 3.8918202981 A #> 5361 2056E 3M CC37 2017 2017-11-06 DO 1.7595805709 #> 5362 2056E 3M CC37 2017 2017-11-06 DOSAT 4.3605476030 #> 5363 2056E 3M CC37 2017 2017-11-06 NO23 -3.7722610631 #> 5364 2056E 3M CC37 2017 2017-11-06 SALIN 2.9549102790 #> 5365 2056E 3M CC37 2017 2017-11-06 TKN -0.4620354596 #> 5366 2056E 3M CC37 2017 2017-11-06 TN -0.4261781497 + #> 5367 2056E 3M CC37 2017 2017-11-06 TP -1.4696759701 #> 5368 2056E 3M CC37 2017 2017-11-06 TURB 0.2623642645 #> 5369 2056E 3M CC37 2017 2017-12-04 CHLAC 1.6677068206 #> 5370 2056E 3M CC37 2017 2017-12-04 COLOR 3.4657359028 #> 5371 2056E 3M CC37 2017 2017-12-04 DO 1.5686159179 #> 5372 2056E 3M CC37 2017 2017-12-04 DOSAT 4.1541845626 #> 5373 2056E 3M CC37 2017 2017-12-04 NO23 -5.5214609179 U #> 5374 2056E 3M CC37 2017 2017-12-04 SALIN 3.0914968955 #> 5375 2056E 3M CC37 2017 2017-12-04 TKN -0.1743533871 #> 5376 2056E 3M CC37 2017 2017-12-04 TN -0.1719752647 + #> 5377 2056E 3M CC37 2017 2017-12-04 TP -1.2039728043 #> 5378 2056E 3M CC37 2017 2017-12-04 TURB 1.0647107370 #> 5379 2056E 3M CC37 2018 2018-01-02 CHLAC 2.8332133441 #> 5380 2056E 3M CC37 2018 2018-01-02 COLOR 3.2188758249 #> 5381 2056E 3M CC37 2018 2018-01-02 DO 1.7101878155 #> 5382 2056E 3M CC37 2018 2018-01-02 DOSAT 4.1789920363 + #> 5383 2056E 3M CC37 2018 2018-01-02 NO23 -5.2983173665 I #> 5384 2056E 3M CC37 2018 2018-01-02 SALIN 3.1045866785 #> 5385 2056E 3M CC37 2018 2018-01-02 TKN -0.1278333715 #> 5386 2056E 3M CC37 2018 2018-01-02 TN -0.1232982163 + #> 5387 2056E 3M CC37 2018 2018-01-02 TP -0.6348782724 #> 5388 2056E 3M CC37 2018 2018-01-02 TURB 1.5040773968 #> 5389 2056E 3M CC37 2018 2018-02-05 CHLAC 3.0445224377 #> 5390 2056E 3M CC37 2018 2018-02-05 COLOR 3.0910424534 #> 5391 2056E 3M CC37 2018 2018-02-05 DO 1.7227665977 #> 5392 2056E 3M CC37 2018 2018-02-05 DOSAT 4.3067641502 #> 5393 2056E 3M CC37 2018 2018-02-05 NO23 -4.1351665567 #> 5394 2056E 3M CC37 2018 2018-02-05 SALIN 3.1311369106 #> 5395 2056E 3M CC37 2018 2018-02-05 TKN -0.5108256238 #> 5396 2056E 3M CC37 2018 2018-02-05 TN -0.4845083154 + #> 5397 2056E 3M CC37 2018 2018-02-05 TP -2.0402208285 #> 5398 2056E 3M CC37 2018 2018-02-05 TURB 1.3609765531 #> 5399 2056E 3M CC37 2018 2018-03-05 CHLAC 1.9315214116 #> 5400 2056E 3M CC37 2018 2018-03-05 COLOR 3.1780538303 A #> 5401 2056E 3M CC37 2018 2018-03-05 DO 1.4973884086 #> 5402 2056E 3M CC37 2018 2018-03-05 DOSAT 4.0656020934 #> 5403 2056E 3M CC37 2018 2018-03-05 NO23 -5.2983173665 I #> 5404 2056E 3M CC37 2018 2018-03-05 SALIN 3.1540172525 #> 5405 2056E 3M CC37 2018 2018-03-05 TKN -0.2613647641 #> 5406 2056E 3M CC37 2018 2018-03-05 TN -0.2561834054 + #> 5407 2056E 3M CC37 2018 2018-03-05 TP -1.6607312068 #> 5408 2056E 3M CC37 2018 2018-03-05 TURB 1.3083328197 #> 5409 2056E 3M CC37 2018 2018-04-02 CHLAC 2.3978952728 #> 5410 2056E 3M CC37 2018 2018-04-02 COLOR 2.9444389792 A #> 5411 2056E 3M CC37 2018 2018-04-02 DO 1.3660916538 #> 5412 2056E 3M CC37 2018 2018-04-02 DOSAT 3.9963641539 #> 5413 2056E 3M CC37 2018 2018-04-02 NO23 -4.8283137373 I #> 5414 2056E 3M CC37 2018 2018-04-02 SALIN 3.2461018111 #> 5415 2056E 3M CC37 2018 2018-04-02 TKN -0.2613647641 #> 5416 2056E 3M CC37 2018 2018-04-02 TN -0.2561834054 + #> 5417 2056E 3M CC37 2018 2018-04-02 TP -1.6607312068 #> 5418 2056E 3M CC37 2018 2018-04-02 TURB 1.4109869737 A #> 5419 2056E 3M CC37 2018 2018-05-07 CHLAC 2.6390573296 #> 5420 2056E 3M CC37 2018 2018-05-07 COLOR 3.0445224377 #> 5421 2056E 3M CC37 2018 2018-05-07 DO 1.4011829736 #> 5422 2056E 3M CC37 2018 2018-05-07 DOSAT 4.0656020934 #> 5423 2056E 3M CC37 2018 2018-05-07 NO23 -5.2983173665 I #> 5424 2056E 3M CC37 2018 2018-05-07 SALIN 3.3225148596 #> 5425 2056E 3M CC37 2018 2018-05-07 TKN -0.0833816089 #> 5426 2056E 3M CC37 2018 2018-05-07 TN -0.0790432073 + #> 5427 2056E 3M CC37 2018 2018-05-07 TP -1.5606477483 #> 5428 2056E 3M CC37 2018 2018-05-07 TURB 1.5260563035 #> 5429 2056E 3M CC37 2018 2018-06-04 CHLAC 3.2958368660 #> 5430 2056E 3M CC37 2018 2018-06-04 COLOR 4.4773368145 #> 5431 2056E 3M CC37 2018 2018-06-04 DO 1.9286186519 #> 5432 2056E 3M CC37 2018 2018-06-04 DOSAT 4.5390303835 #> 5433 2056E 3M CC37 2018 2018-06-04 NO23 -4.0745419349 #> 5434 2056E 3M CC37 2018 2018-06-04 SALIN 1.9095425049 #> 5435 2056E 3M CC37 2018 2018-06-04 TKN 0.1823215568 #> 5436 2056E 3M CC37 2018 2018-06-04 TN 0.1963888140 + #> 5437 2056E 3M CC37 2018 2018-06-04 TP -0.9942522733 #> 5438 2056E 3M CC37 2018 2018-06-04 TURB 1.3862943611 #> 5439 2056E 3M CC37 2018 2018-07-09 CHLAC 2.6390573296 #> 5440 2056E 3M CC37 2018 2018-07-09 COLOR 4.8675344505 #> 5441 2056E 3M CC37 2018 2018-07-09 DO 1.2919836816 #> 5442 2056E 3M CC37 2018 2018-07-09 DOSAT 3.7977338590 #> 5443 2056E 3M CC37 2018 2018-07-09 NO23 -2.6310891600 #> 5444 2056E 3M CC37 2018 2018-07-09 SALIN 1.8148247422 #> 5445 2056E 3M CC37 2018 2018-07-09 TKN 0.1823215568 #> 5446 2056E 3M CC37 2018 2018-07-09 TN 0.2405904649 + #> 5447 2056E 3M CC37 2018 2018-07-09 TP -0.8675005677 #> 5448 2056E 3M CC37 2018 2018-07-09 TURB 0.6931471806 A #> 5449 2056E 3M CC37 2018 2018-08-06 CHLAC 1.8562979904 #> 5450 2056E 3M CC37 2018 2018-08-06 COLOR 4.8675344505 #> 5451 2056E 3M CC37 2018 2018-08-06 DO 1.3428648032 #> 5452 2056E 3M CC37 2018 2018-08-06 DOSAT 3.9435216725 #> 5453 2056E 3M CC37 2018 2018-08-06 NO23 -1.8325814637 #> 5454 2056E 3M CC37 2018 2018-08-06 SALIN 1.1281710909 #> 5455 2056E 3M CC37 2018 2018-08-06 TKN 0.0953101798 #> 5456 2056E 3M CC37 2018 2018-08-06 TN 0.2311117210 + #> 5457 2056E 3M CC37 2018 2018-08-06 TP -0.8209805521 #> 5458 2056E 3M CC37 2018 2018-08-06 TURB 0.5877866649 #> 5459 2056E 3M CC37 2019 2019-02-04 CHLAC 1.9878743482 A #> 5460 2056E 3M CC37 2019 2019-02-04 COLOR 3.3322045102 #> 5461 2056E 3M CC37 2019 2019-02-04 DO 2.0438143640 #> 5462 2056E 3M CC37 2019 2019-02-04 DOSAT 4.5622626850 #> 5463 2056E 3M CC37 2019 2019-02-04 NO23 -5.2983173665 I #> 5464 2056E 3M CC37 2019 2019-02-04 SALIN 2.7447035188 #> 5465 2056E 3M CC37 2019 2019-02-04 TKN -0.4780358009 #> 5466 2056E 3M CC37 2019 2019-02-04 TN -0.4716049106 + #> 5467 2056E 3M CC37 2019 2019-02-04 TP -1.7147984281 #> 5468 2056E 3M CC37 2019 2019-02-04 TURB 0.7884573604 #> 5469 2056E 3M CC37 2019 2019-05-06 CHLAC 2.3978952728 #> 5470 2056E 3M CC37 2019 2019-05-06 COLOR 3.1780538303 A #> 5471 2056E 3M CC37 2019 2019-05-06 DO 1.3110318766 #> 5472 2056E 3M CC37 2019 2019-05-06 DOSAT 3.9759363312 #> 5473 2056E 3M CC37 2019 2019-05-06 NO23 -5.5214609179 U #> 5474 2056E 3M CC37 2019 2019-05-06 SALIN 3.0320642028 #> 5475 2056E 3M CC37 2019 2019-05-06 TN -0.2331938872 + #> 5476 2056E 3M CC37 2019 2019-05-06 TP -1.4696759701 #> 5477 2056E 3M CC37 2019 2019-05-06 TURB 1.3350010667 #> 5478 2056E 3M CC37 2019 2019-06-03 CHLAC 2.0281482473 #> 5479 2056E 3M CC37 2019 2019-06-03 COLOR 3.2188758249 A #> 5480 2056E 3M CC37 2019 2019-06-03 DO 1.2864740258 #> 5481 2056E 3M CC37 2019 2019-06-03 DOSAT 3.9815490681 #> 5482 2056E 3M CC37 2019 2019-06-03 NO23 -5.5214609179 U #> 5483 2056E 3M CC37 2019 2019-06-03 SALIN 2.9982291538 #> 5484 2056E 3M CC37 2019 2019-06-03 TKN -0.0512932944 #> 5485 2056E 3M CC37 2019 2019-06-03 TN -0.0491902442 + #> 5486 2056E 3M CC37 2019 2019-06-03 TP -0.9416085399 #> 5487 2056E 3M CC37 2019 2019-06-03 TURB 0.8754687374 #> 5488 2056E 3M CC37 2019 2019-07-01 CHLAC 3.1354942159 #> 5489 2056E 3M CC37 2019 2019-07-01 COLOR 3.5553480615 A #> 5490 2056E 3M CC37 2019 2019-07-01 DO 0.6259384309 #> 5491 2056E 3M CC37 2019 2019-07-01 DOSAT 3.1441522787 #> 5492 2056E 3M CC37 2019 2019-07-01 NO23 -5.5214609179 I #> 5493 2056E 3M CC37 2019 2019-07-01 SALIN 2.7825390531 #> 5494 2056E 3M CC37 2019 2019-07-01 TKN -0.1278333715 #> 5495 2056E 3M CC37 2019 2019-07-01 TN -0.1232982163 + #> 5496 2056E 3M CC37 2019 2019-07-01 TP -0.5798184953 #> 5497 2056E 3M CC37 2019 2019-07-01 TURB 1.0296194172 #> 5498 2056E 3M CC37 2019 2019-08-05 CHLAC 3.1354942159 #> 5499 2056E 3M CC37 2019 2019-08-05 COLOR 4.2341065046 A #> 5500 2056E 3M CC37 2019 2019-08-05 DO 1.9685099810 #> 5501 2056E 3M CC37 2019 2019-08-05 DOSAT 4.5880240272 #> 5502 2056E 3M CC37 2019 2019-08-05 NO23 -4.9618451299 I #> 5503 2056E 3M CC37 2019 2019-08-05 SALIN 2.0744289999 #> 5504 2056E 3M CC37 2019 2019-08-05 TKN -0.1053605157 #> 5505 2056E 3M CC37 2019 2019-08-05 TN -0.1009259186 + #> 5506 2056E 3M CC37 2019 2019-08-05 TP -1.1086626245 #> 5507 2056E 3M CC37 2019 2019-08-05 TURB 1.1314021115 #> 5508 2056E 3M CC37 2019 2019-10-07 CHLAC 2.0794415417 #> 5509 2056E 3M CC37 2019 2019-10-07 COLOR 3.7376696183 A #> 5510 2056E 3M CC37 2019 2019-10-07 DO 1.4036429995 #> 5511 2056E 3M CC37 2019 2019-10-07 DOSAT 4.0910056610 #> 5512 2056E 3M CC37 2019 2019-10-07 NO23 -5.5214609179 U #> 5513 2056E 3M CC37 2019 2019-10-07 SALIN 3.0842009215 #> 5514 2056E 3M CC37 2019 2019-10-07 TKN -0.3566749439 #> 5515 2056E 3M CC37 2019 2019-10-07 TN -0.3538218750 + #> 5516 2056E 3M CC37 2019 2019-10-07 TP -1.6607312068 #> 5517 2056E 3M CC37 2019 2019-10-07 TURB 0.4054651081 #> 5518 2056E 3M CC37 2019 2019-11-04 CHLAC 1.1939224685 #> 5519 2056E 3M CC37 2019 2019-11-04 COLOR 3.5835189385 #> 5520 2056E 3M CC37 2019 2019-11-04 DO 1.6034198401 #> 5521 2056E 3M CC37 2019 2019-11-04 DOSAT 4.2470656492 #> 5522 2056E 3M CC37 2019 2019-11-04 NO23 -4.4228486292 #> 5523 2056E 3M CC37 2019 2019-11-04 SALIN 2.9922261342 #> 5524 2056E 3M CC37 2019 2019-11-04 TKN -0.3285040670 #> 5525 2056E 3M CC37 2019 2019-11-04 TN -0.3119747650 + #> 5526 2056E 3M CC37 2019 2019-11-04 TP -1.4271163556 #> 5527 2056E 3M CC37 2019 2019-11-04 TURB 0.0000000000 #> 5528 2056E 3M CC37 2019 2019-12-02 CHLAC 1.8245492921 A #> 5529 2056E 3M CC37 2019 2019-12-02 COLOR 3.3322045102 #> 5530 2056E 3M CC37 2019 2019-12-02 DO 1.3532545070 #> 5531 2056E 3M CC37 2019 2019-12-02 DOSAT 3.9740583963 #> 5532 2056E 3M CC37 2019 2019-12-02 NO23 -5.2983173665 I #> 5533 2056E 3M CC37 2019 2019-12-02 SALIN 3.1363634033 #> 5534 2056E 3M CC37 2019 2019-12-02 TKN -0.4942963218 #> 5535 2056E 3M CC37 2019 2019-12-02 TN -0.4877603508 + #> 5536 2056E 3M CC37 2019 2019-12-02 TP -1.8325814637 #> 5537 2056E 3M CC37 2019 2019-12-02 TURB 0.7884573604 #> 5538 2056E 3M CC37 2020 2020-01-06 CHLAC 2.7080502011 #> 5539 2056E 3M CC37 2020 2020-01-06 COLOR 3.1354942159 A #> 5540 2056E 3M CC37 2020 2020-01-06 DO 2.0055258587 #> 5541 2056E 3M CC37 2020 2020-01-06 DOSAT 4.5347477217 #> 5542 2056E 3M CC37 2020 2020-01-06 NO23 -4.7105307016 I #> 5543 2056E 3M CC37 2020 2020-01-06 SALIN 3.0387917630 #> 5544 2056E 3M CC37 2020 2020-01-06 TKN -0.3710636814 #> 5545 2056E 3M CC37 2020 2020-01-06 TN -0.3652833185 + #> 5546 2056E 3M CC37 2020 2020-01-06 TP -1.6607312068 #> 5547 2056E 3M CC37 2020 2020-01-06 TURB 1.0647107370 #> 5548 2056E 3M CC37 2020 2020-02-03 CHLAC 2.5649493575 #> 5549 2056E 3M CC37 2020 2020-02-03 COLOR 2.9957322736 #> 5550 2056E 3M CC37 2020 2020-02-03 DO 1.8148247422 #> 5551 2056E 3M CC37 2020 2020-02-03 DOSAT 4.2808241292 #> 5552 2056E 3M CC37 2020 2020-02-03 NO23 -4.3428059215 #> 5553 2056E 3M CC37 2020 2020-02-03 SALIN 3.1175073305 #> 5554 2056E 3M CC37 2020 2020-02-03 TKN -0.3856624808 #> 5555 2056E 3M CC37 2020 2020-02-03 TN -0.3667252798 + #> 5556 2056E 3M CC37 2020 2020-02-03 TP -1.9661128564 #> 5557 2056E 3M CC37 2020 2020-02-03 TURB 1.4109869737 A #> 5558 2056E 3M CC37 2020 2020-03-02 CHLAC 1.9740810260 #> 5559 2056E 3M CC37 2020 2020-03-02 COLOR 2.8903717579 #> 5560 2056E 3M CC37 2020 2020-03-02 DO 1.8484548129 #> 5561 2056E 3M CC37 2020 2020-03-02 DOSAT 4.3832758541 #> 5562 2056E 3M CC37 2020 2020-03-02 NO23 -5.2983173665 I #> 5563 2056E 3M CC37 2020 2020-03-02 SALIN 3.1320098918 #> 5564 2056E 3M CC37 2020 2020-03-02 TKN -0.4004775666 #> 5565 2056E 3M CC37 2020 2020-03-02 TN -0.3945251681 + #> 5566 2056E 3M CC37 2020 2020-03-02 TP -1.9661128564 #> 5567 2056E 3M CC37 2020 2020-03-02 TURB 1.2809338455 A #> 5568 2056E 3M CC37 2020 2020-09-08 CHLAC 1.6486586256 #> 5569 2056E 3M CC37 2020 2020-09-08 COLOR 4.4998096703 #> 5570 2056E 3M CC37 2020 2020-09-08 DO 0.8837675402 #> 5571 2056E 3M CC37 2020 2020-09-08 DOSAT 3.5085559000 #> 5572 2056E 3M CC37 2020 2020-09-08 NO23 -3.1465551633 #> 5573 2056E 3M CC37 2020 2020-09-08 SALIN 2.2428350886 #> 5574 2056E 3M CC37 2020 2020-09-08 TKN -0.1743533871 #> 5575 2056E 3M CC37 2020 2020-09-08 TN -0.1244300784 + #> 5576 2056E 3M CC37 2020 2020-09-08 TP -0.9162907319 #> 5577 2056E 3M CC37 2020 2020-09-08 TURB 0.4700036292 #> 5578 2056E 3M CC37 2020 2020-10-05 CHLAC 1.7047480922 #> 5579 2056E 3M CC37 2020 2020-10-05 COLOR 4.5951198501 A #> 5580 2056E 3M CC37 2020 2020-10-05 DO 0.8837675402 #> 5581 2056E 3M CC37 2020 2020-10-05 DOSAT 3.4657359028 #> 5582 2056E 3M CC37 2020 2020-10-05 NO23 -3.2701691193 #> 5583 2056E 3M CC37 2020 2020-10-05 SALIN 2.6181254936 #> 5584 2056E 3M CC37 2020 2020-10-05 TKN 0.1823215568 #> 5585 2056E 3M CC37 2020 2020-10-05 TN 0.2134971743 + #> 5586 2056E 3M CC37 2020 2020-10-05 TP -0.7765287895 #> 5587 2056E 3M CC37 2020 2020-10-05 TURB 0.3364722366 #> 5588 2056E 3M CC37 2020 2020-11-02 CHLAC 2.1400661635 #> 5589 2056E 3M CC37 2020 2020-11-02 COLOR 4.2046926194 #> 5590 2056E 3M CC37 2020 2020-11-02 DO 1.8468787684 #> 5591 2056E 3M CC37 2020 2020-11-02 DOSAT 4.4670568839 #> 5592 2056E 3M CC37 2020 2020-11-02 NO23 -3.2968373663 #> 5593 2056E 3M CC37 2020 2020-11-02 SALIN 2.6525374912 #> 5594 2056E 3M CC37 2020 2020-11-02 TKN -0.3147107448 #> 5595 2056E 3M CC37 2020 2020-11-02 TN -0.2652684776 + #> 5596 2056E 3M CC37 2020 2020-11-02 TP -1.3093333200 #> 5597 2056E 3M CC37 2020 2020-11-02 TURB 0.6931471806 A #> 5598 2056E 3M CC37 2020 2020-12-07 CHLAC 1.6677068206 #> 5599 2056E 3M CC37 2020 2020-12-07 COLOR 3.8712010109 #> 5600 2056E 3M CC37 2020 2020-12-07 DO 1.9050881545 #> 5601 2056E 3M CC37 2020 2020-12-07 DOSAT 4.4164280614 #> 5602 2056E 3M CC37 2020 2020-12-07 NO23 -3.9633162998 #> 5603 2056E 3M CC37 2020 2020-12-07 SALIN 2.8735646396 #> 5604 2056E 3M CC37 2020 2020-12-07 TKN -0.4942963218 #> 5605 2056E 3M CC37 2020 2020-12-07 TN -0.4636240223 + #> 5606 2056E 3M CC37 2020 2020-12-07 TP -1.8325814637 #> 5607 2056E 3M CC37 2020 2020-12-07 TURB 0.1823215568 #> 5608 2056E 3M CC37 2021 2021-01-04 CHLAC 0.8754687374 I #> 5609 2056E 3M CC37 2021 2021-01-04 COLOR 3.5835189385 #> 5610 2056E 3M CC37 2021 2021-01-04 DO 1.4279160358 #> 5611 2056E 3M CC37 2021 2021-01-04 DOSAT 3.9569963711 #> 5612 2056E 3M CC37 2021 2021-01-04 NO23 -4.1351665567 #> 5613 2056E 3M CC37 2021 2021-01-04 SALIN 2.8249439526 #> 5614 2056E 3M CC37 2021 2021-01-04 TKN -0.3285040670 #> 5615 2056E 3M CC37 2021 2021-01-04 TN -0.3065251603 + #> 5616 2056E 3M CC37 2021 2021-01-04 TP -1.8971199849 #> 5617 2056E 3M CC37 2021 2021-01-04 TURB 0.6418538862 #> 5618 2056E 3M CC37 2021 2021-02-01 CHLAC 1.0986122887 #> 5619 2056E 3M CC37 2021 2021-02-01 COLOR 3.2958368660 A #> 5620 2056E 3M CC37 2021 2021-02-01 DO 2.0464016876 #> 5621 2056E 3M CC37 2021 2021-02-01 DOSAT 4.5767707115 #> 5622 2056E 3M CC37 2021 2021-02-01 NO23 -5.1159958098 I #> 5623 2056E 3M CC37 2021 2021-02-01 SALIN 2.9957322736 #> 5624 2056E 3M CC37 2021 2021-02-01 TKN -0.5108256238 #> 5625 2056E 3M CC37 2021 2021-02-01 TN -0.5041810810 + #> 5626 2056E 3M CC37 2021 2021-02-01 TP -2.1202635362 #> 5627 2056E 3M CC37 2021 2021-02-01 TURB 0.6418538862 #> 5628 2056E 3M CC37 2021 2021-03-01 CHLAC 1.5260563035 #> 5629 2056E 3M CC37 2021 2021-03-01 COLOR 3.2580965380 A #> 5630 2056E 3M CC37 2021 2021-03-01 DO 1.4134230285 #> 5631 2056E 3M CC37 2021 2021-03-01 DOSAT 4.0412953411 #> 5632 2056E 3M CC37 2021 2021-03-01 NO23 -5.1159958098 I #> 5633 2056E 3M CC37 2021 2021-03-01 SALIN 3.0445224377 #> 5634 2056E 3M CC37 2021 2021-03-01 TKN -0.6161861394 #> 5635 2056E 3M CC37 2021 2021-03-01 TN -0.6088060321 + #> 5636 2056E 3M CC37 2021 2021-03-01 TP -1.9661128564 #> 5637 2056E 3M CC37 2021 2021-03-01 TURB 1.1314021115 A #> 5638 2056E 3M CC37 2021 2021-04-05 CHLAC 1.7917594692 #> 5639 2056E 3M CC37 2021 2021-04-05 COLOR 3.1354942159 #> 5640 2056E 3M CC37 2021 2021-04-05 DO 1.5040773968 #> 5641 2056E 3M CC37 2021 2021-04-05 DOSAT 4.0604430105 #> 5642 2056E 3M CC37 2021 2021-04-05 NO23 -4.5098600062 #> 5643 2056E 3M CC37 2021 2021-04-05 SALIN 3.1599747169 #> 5644 2056E 3M CC37 2021 2021-04-05 TKN -0.1984509387 #> 5645 2056E 3M CC37 2021 2021-04-05 TN -0.1851254841 + #> 5646 2056E 3M CC37 2021 2021-04-05 TP -1.7719568419 #> 5647 2056E 3M CC37 2021 2021-04-05 TURB 1.7047480922 #> 5648 2056E 3M CC37 2021 2021-05-03 CHLAC 2.0149030205 #> 5649 2056E 3M CC37 2021 2021-05-03 COLOR 3.1354942159 #> 5650 2056E 3M CC37 2021 2021-05-03 DO 1.1314021115 #> 5651 2056E 3M CC37 2021 2021-05-03 DOSAT 3.8286413965 #> 5652 2056E 3M CC37 2021 2021-05-03 NO23 -4.8283137373 I #> 5653 2056E 3M CC37 2021 2021-05-03 SALIN 3.2196755050 #> 5654 2056E 3M CC37 2021 2021-05-03 TKN -0.3011050928 #> 5655 2056E 3M CC37 2021 2021-05-03 TN -0.2957142441 + #> 5656 2056E 3M CC37 2021 2021-05-03 TP -1.4696759701 #> 5657 2056E 3M CC37 2021 2021-05-03 TURB 1.5260563035 #> 5658 2056E 3M CC37 2021 2021-06-07 CHLAC 2.2617630985 #> 5659 2056E 3M CC37 2021 2021-06-07 COLOR 2.8903717579 #> 5660 2056E 3M CC37 2021 2021-06-07 DO 1.1314021115 #> 5661 2056E 3M CC37 2021 2021-06-07 DOSAT 3.8286413965 #> 5662 2056E 3M CC37 2021 2021-06-07 NO23 -5.5214609179 U #> 5663 2056E 3M CC37 2021 2021-06-07 SALIN 3.2196755050 #> 5664 2056E 3M CC37 2021 2021-06-07 TKN 0.0953101798 #> 5665 2056E 3M CC37 2021 2021-06-07 TN 0.0971267107 + #> 5666 2056E 3M CC37 2021 2021-06-07 TP -1.3093333200 #> 5667 2056E 3M CC37 2021 2021-06-07 TURB 1.2809338455 #> 5668 2056E 3M CC37 2021 2021-08-02 CHLAC 2.7080502011 #> 5669 2056E 3M CC37 2021 2021-08-02 COLOR 4.5217885770 #> 5670 2056E 3M CC37 2021 2021-08-02 DO 1.6034198401 #> 5671 2056E 3M CC37 2021 2021-08-02 DOSAT 4.2766661190 #> 5672 2056E 3M CC37 2021 2021-08-02 NO23 -5.5214609179 U #> 5673 2056E 3M CC37 2021 2021-08-02 SALIN 2.1871742415 #> 5674 2056E 3M CC37 2021 2021-08-02 TKN -0.1053605157 #> 5675 2056E 3M CC37 2021 2021-08-02 TN -0.1031407589 + #> 5676 2056E 3M CC37 2021 2021-08-02 TP -0.6733445533 #> 5677 2056E 3M CC37 2021 2021-08-02 TURB 0.8754687374 #> 5678 2056E 3M CC37 2021 2021-09-07 CHLAC 1.8405496334 #> 5679 2056E 3M CC37 2021 2021-09-07 COLOR 4.2341065046 #> 5680 2056E 3M CC37 2021 2021-09-07 DO 1.5260563035 #> 5681 2056E 3M CC37 2021 2021-09-07 DOSAT 4.1447207695 #> 5682 2056E 3M CC37 2021 2021-09-07 NO23 -3.6119184130 #> 5683 2056E 3M CC37 2021 2021-09-07 SALIN 2.0041790572 #> 5684 2056E 3M CC37 2021 2021-09-07 TKN -0.0943106795 #> 5685 2056E 3M CC37 2021 2021-09-07 TN -0.0650719967 + #> 5686 2056E 3M CC37 2021 2021-09-07 TP -1.0788096614 #> 5687 2056E 3M CC37 2021 2021-09-07 TURB 0.5306282511 A #> 5688 2056E 3M CC37 2021 2021-10-04 CHLAC 2.4849066498 #> 5689 2056E 3M CC37 2021 2021-10-04 COLOR 4.5643481915 A #> 5690 2056E 3M CC37 2021 2021-10-04 DO 0.4446858213 #> 5691 2056E 3M CC37 2021 2021-10-04 DOSAT 3.0587070727 #> 5692 2056E 3M CC37 2021 2021-10-04 NO23 -3.0576076773 #> 5693 2056E 3M CC37 2021 2021-10-04 SALIN 2.4932054526 #> 5694 2056E 3M CC37 2021 2021-10-04 TKN 0.0953101798 #> 5695 2056E 3M CC37 2021 2021-10-04 TN 0.1371498381 + #> 5696 2056E 3M CC37 2021 2021-10-04 TP -0.7985076962 #> 5697 2056E 3M CC37 2021 2021-10-04 TURB 0.4054651081 #> 5698 2056E 3M CC37 2021 2021-11-01 CHLAC 1.7749523509 #> 5699 2056E 3M CC37 2021 2021-11-01 COLOR 3.7612001157 A #> 5700 2056E 3M CC37 2021 2021-11-01 DO 1.2325602612 #> 5701 2056E 3M CC37 2021 2021-11-01 DOSAT 3.8177123260 #> 5702 2056E 3M CC37 2021 2021-11-01 NO23 -3.5065578973 #> 5703 2056E 3M CC37 2021 2021-11-01 SALIN 2.9444389792 #> 5704 2056E 3M CC37 2021 2021-11-01 TKN -0.2231435513 #> 5705 2056E 3M CC37 2021 2021-11-01 TN -0.1863295782 + #> 5706 2056E 3M CC37 2021 2021-11-01 TP -1.6094379124 #> 5707 2056E 3M CC37 2021 2021-11-01 TURB 0.2623642645 #> 5708 2056E 3M CC37 2021 2021-12-06 CHLAC 1.7578579176 #> 5709 2056E 3M CC37 2021 2021-12-06 COLOR 3.0445224377 #> 5710 2056E 3M CC37 2021 2021-12-06 DO 1.5260563035 #> 5711 2056E 3M CC37 2021 2021-12-06 DOSAT 4.1157798429 #> 5712 2056E 3M CC37 2021 2021-12-06 NO23 -4.7105307016 I #> 5713 2056E 3M CC37 2021 2021-12-06 SALIN 3.1471649773 #> 5714 2056E 3M CC37 2021 2021-12-06 TKN -0.5978370008 #> 5715 2056E 3M CC37 2021 2021-12-06 TN -0.5905905922 + #> 5716 2056E 3M CC37 2021 2021-12-06 TP -2.1202635362 #> 5717 2056E 3M CC37 2021 2021-12-06 TURB 0.4700036292 #> 5718 2056E 3M CC37 2022 2022-01-03 CHLAC 2.1162555148 #> 5719 2056E 3M CC37 2022 2022-01-03 COLOR 2.8903717579 #> 5720 2056E 3M CC37 2022 2022-01-03 DO 1.2974631474 #> 5721 2056E 3M CC37 2022 2022-01-03 DOSAT 3.9160150267 #> 5722 2056E 3M CC37 2022 2022-01-03 NO23 -4.9618451299 I #> 5723 2056E 3M CC37 2022 2022-01-03 SALIN 3.1289511173 #> 5724 2056E 3M CC37 2022 2022-01-03 TKN -0.4780358009 #> 5725 2056E 3M CC37 2022 2022-01-03 TN -0.4716049106 + #> 5726 2056E 3M CC37 2022 2022-01-03 TP -1.9661128564 #> 5727 2056E 3M CC37 2022 2022-01-03 TURB 1.2809338455 A #> 5728 2056E 3M CC37 2022 2022-02-07 CHLAC 2.0918640617 #> 5729 2056E 3M CC37 2022 2022-02-07 COLOR 2.6390573296 #> 5730 2056E 3M CC37 2022 2022-02-07 DO 1.5518087996 #> 5731 2056E 3M CC37 2022 2022-02-07 DOSAT 4.1075897890 #> 5732 2056E 3M CC37 2022 2022-02-07 NO23 -4.1351665567 #> 5733 2056E 3M CC37 2022 2022-02-07 SALIN 3.2323841749 #> 5734 2056E 3M CC37 2022 2022-02-07 TKN -0.2484613593 #> 5735 2056E 3M CC37 2022 2022-02-07 TN -0.2281560931 + #> 5736 2056E 3M CC37 2022 2022-02-07 TP -2.1202635362 #> 5737 2056E 3M CC37 2022 2022-02-07 TURB 0.5877866649 #> 5738 2056E 3M CC37 2022 2022-03-07 CHLAC 1.3350010667 #> 5739 2056E 3M CC37 2022 2022-03-07 COLOR 2.3978952728 #> 5740 2056E 3M CC37 2022 2022-03-07 DO 1.5769147207 #> 5741 2056E 3M CC37 2022 2022-03-07 DOSAT 4.2150861799 #> 5742 2056E 3M CC37 2022 2022-03-07 NO23 -5.5214609179 I #> 5743 2056E 3M CC37 2022 2022-03-07 SALIN 3.2820383998 #> 5744 2056E 3M CC37 2022 2022-03-07 TKN -0.4004775666 #> 5745 2056E 3M CC37 2022 2022-03-07 TN -0.3945251681 + #> 5746 2056E 3M CC37 2022 2022-03-07 TP -2.0402208285 #> 5747 2056E 3M CC37 2022 2022-03-07 TURB 1.0647107370 #> 5748 2056E 3M CC37 2022 2022-04-04 CHLAC 1.6863989536 #> 5749 2056E 3M CC37 2022 2022-04-04 COLOR 2.5649493575 #> 5750 2056E 3M CC37 2022 2022-04-04 DO 1.4816045409 #> 5751 2056E 3M CC37 2022 2022-04-04 DOSAT 4.1319614258 #> 5752 2056E 3M CC37 2022 2022-04-04 NO23 -4.5098600062 #> 5753 2056E 3M CC37 2022 2022-04-04 SALIN 3.3311325072 #> 5754 2056E 3M CC37 2022 2022-04-04 TN -0.6520052372 + #> 5755 2056E 3M CC37 2022 2022-04-04 TP -1.7719568419 #> 5756 2056E 3M CC37 2022 2022-04-04 TURB 1.1631508098 #> 5757 2056E 3M CC37 2022 2022-05-02 CHLAC 1.5892352051 #> 5758 2056E 3M CC37 2022 2022-05-02 COLOR 2.7080502011 #> 5759 2056E 3M CC37 2022 2022-05-02 DO 1.3660916538 #> 5760 2056E 3M CC37 2022 2022-05-02 DOSAT 4.0500443033 #> 5761 2056E 3M CC37 2022 2022-05-02 NO23 -5.2983173665 I #> 5762 2056E 3M CC37 2022 2022-05-02 SALIN 3.3755376349 #> 5763 2056E 3M CC37 2022 2022-05-02 TKN -0.2744368457 #> 5764 2056E 3M CC37 2022 2022-05-02 TN -0.2691874898 + #> 5765 2056E 3M CC37 2022 2022-05-02 TP -1.6094379124 #> 5766 2056E 3M CC37 2022 2022-05-02 TURB 1.2527629685 A #> 5767 2056E 3M CC37 2022 2022-06-06 CHLAC 2.9444389792 #> 5768 2056E 3M CC37 2022 2022-06-06 COLOR 3.0910424534 #> 5769 2056E 3M CC37 2022 2022-06-06 DO 1.1019400788 #> 5770 2056E 3M CC37 2022 2022-06-06 DOSAT 3.7909846771 #> 5771 2056E 3M CC37 2022 2022-06-06 NO23 -5.1159958098 I #> 5772 2056E 3M CC37 2022 2022-06-06 SALIN 3.1851121947 #> 5773 2056E 3M CC37 2022 2022-06-06 TKN -0.0725706928 #> 5774 2056E 3M CC37 2022 2022-06-06 TN -0.0682788408 + #> 5775 2056E 3M CC37 2022 2022-06-06 TP -1.1711829815 #> 5776 2056E 3M CC37 2022 2022-06-06 TURB 1.3609765531 A #> 5777 2056E 3M CC37 2022 2022-07-05 CHLAC 1.7047480922 #> 5778 2056E 3M CC37 2022 2022-07-05 COLOR 3.6635616461 #> 5779 2056E 3M CC37 2022 2022-07-05 DO 1.3056264581 #> 5780 2056E 3M CC37 2022 2022-07-05 DOSAT 3.9684033389 #> 5781 2056E 3M CC37 2022 2022-07-05 NO23 -5.5214609179 U #> 5782 2056E 3M CC37 2022 2022-07-05 SALIN 2.7047112998 #> 5783 2056E 3M CC37 2022 2022-07-05 TKN -0.2613647641 #> 5784 2056E 3M CC37 2022 2022-07-05 TN -0.2587707290 + #> 5785 2056E 3M CC37 2022 2022-07-05 TP -1.3093333200 #> 5786 2056E 3M CC37 2022 2022-07-05 TURB 0.5877866649 A #> 5787 2056E 3M CC37 2022 2022-08-01 CHLAC 1.9459101491 #> 5788 2056E 3M CC37 2022 2022-08-01 COLOR 4.1588830834 #> 5789 2056E 3M CC37 2022 2022-08-01 DO 1.2029723040 #> 5790 2056E 3M CC37 2022 2022-08-01 DOSAT 3.8501476017 #> 5791 2056E 3M CC37 2022 2022-08-01 NO23 -5.5214609179 I #> 5792 2056E 3M CC37 2022 2022-08-01 SALIN 2.5201129055 #> 5793 2056E 3M CC37 2022 2022-08-01 TKN 0.0000000000 #> 5794 2056E 3M CC37 2022 2022-08-01 TN 0.0039920213 + #> 5795 2056E 3M CC37 2022 2022-08-01 TP -1.1394342832 #> 5796 2056E 3M CC37 2022 2022-08-01 TURB 0.7419373447 #> 5797 2056E 3M CC37 2022 2022-09-06 CHLAC 2.5649493575 #> 5798 2056E 3M CC37 2022 2022-09-06 COLOR 4.3694478525 A #> 5799 2056E 3M CC37 2022 2022-09-06 NO23 -5.1159958098 I #> 5800 2056E 3M CC37 2022 2022-09-06 SALIN 2.2955604781 #> 5801 2056E 3M CC37 2022 2022-09-06 TKN -0.1508228897 #> 5802 2056E 3M CC37 2022 2022-09-06 TN -0.1461825102 + #> 5803 2056E 3M CC37 2022 2022-09-06 TP -1.1086626245 #> 5804 2056E 3M CC37 2022 2022-09-06 TURB 0.6418538862 #> 5805 2056E 3M CC37 2022 2022-11-07 COLOR 4.2046926194 A #> 5806 2056E 3M CC37 2022 2022-11-07 DO 1.5238800241 #> 5807 2056E 3M CC37 2022 2022-11-07 DOSAT 4.1383614476 #> 5808 2056E 3M CC37 2022 2022-11-07 NO23 -3.0159349809 #> 5809 2056E 3M CC37 2022 2022-11-07 SALIN 2.7744619666 #> 5810 2056E 3M CC37 2022 2022-11-07 TKN -0.0725706928 #> 5811 2056E 3M CC37 2022 2022-11-07 TN -0.0212236365 + #> 5812 2056E 3M CC37 2022 2022-11-07 TP -0.9416085399 #> 5813 2056E 3M CC37 2022 2022-11-07 TURB 0.5306282511 #> 5814 2056E 3M CC37 2022 2022-11-07 CHLAC 2.1517622033 #> 5815 2056E 3M CC37 2022 2022-11-07 COLOR 4.1431347264 #> 5816 2056E 3M CC37 2022 2022-11-07 DO 1.5238800241 #> 5817 2056E 3M CC37 2022 2022-11-07 DOSAT 4.1383614476 #> 5818 2056E 3M CC37 2022 2022-11-07 NO23 -2.9957322736 #> 5819 2056E 3M CC37 2022 2022-11-07 SALIN 2.7744619666 #> 5820 2056E 3M CC37 2022 2022-11-07 TKN 0.0000000000 #> 5821 2056E 3M CC37 2022 2022-11-07 TN 0.0487901642 + #> 5822 2056E 3M CC37 2022 2022-11-07 TP -0.9162907319 #> 5823 2056E 3M CC37 2022 2022-11-07 TURB 0.6418538862 #> 5824 2056E 3M CC37 2022 2022-12-05 CHLAC 2.3025850930 #> 5825 2056E 3M CC37 2022 2022-12-05 COLOR 3.8918202981 A #> 5826 2056E 3M CC37 2022 2022-12-05 DO 1.3812818193 #> 5827 2056E 3M CC37 2022 2022-12-05 DOSAT 3.9337844972 #> 5828 2056E 3M CC37 2022 2022-12-05 NO23 -2.8824035882 #> 5829 2056E 3M CC37 2022 2022-12-05 SALIN 2.8219739474 #> 5830 2056E 3M CC37 2022 2022-12-05 TKN -0.3147107448 #> 5831 2056E 3M CC37 2022 2022-12-05 TN -0.2407984866 + #> 5832 2056E 3M CC37 2022 2022-12-05 TP -1.4696759701 #> 5833 2056E 3M CC37 2022 2022-12-05 TURB 0.5306282511 #> 5834 2056E 3M CC37 2023 2023-01-03 CHLAC 2.8903717579 #> 5835 2056E 3M CC37 2023 2023-01-03 COLOR 3.4011973817 A #> 5836 2056E 3M CC37 2023 2023-01-03 DO 1.5953389881 #> 5837 2056E 3M CC37 2023 2023-01-03 DOSAT 4.1510399059 #> 5838 2056E 3M CC37 2023 2023-01-03 NO23 -3.8167128256 #> 5839 2056E 3M CC37 2023 2023-01-03 SALIN 2.9699015135 #> 5840 2056E 3M CC37 2023 2023-01-03 TKN -0.1984509387 #> 5841 2056E 3M CC37 2023 2023-01-03 TN -0.1719752647 + #> 5842 2056E 3M CC37 2023 2023-01-03 TP -1.6094379124 #> 5843 2056E 3M CC37 2023 2023-01-03 TURB 1.4109869737 #> 5844 2056E 3M CC37 2023 2023-02-06 CHLAC 1.8082887712 #> 5845 2056E 3M CC37 2023 2023-02-06 COLOR 3.1780538303 #> 5846 2056E 3M CC37 2023 2023-02-06 DO 1.5953389881 #> 5847 2056E 3M CC37 2023 2023-02-06 DOSAT 4.1510399059 #> 5848 2056E 3M CC37 2023 2023-02-06 NO23 -5.5214609179 U #> 5849 2056E 3M CC37 2023 2023-02-06 SALIN 2.9699015135 #> 5850 2056E 3M CC37 2023 2023-02-06 TKN -0.3011050928 #> 5851 2056E 3M CC37 2023 2023-02-06 TN -0.2984060358 + #> 5852 2056E 3M CC37 2023 2023-02-06 TP -1.7147984281 #> 5853 2056E 3M CC37 2023 2023-02-06 TURB 0.6418538862 #> 5854 2056E 3M CC37 2023 2023-03-06 DO 1.1085626195 #> 5855 2056E 3M CC37 2023 2023-03-06 DOSAT 3.7727609381 #> 5856 2056E 3M CC37 2023 2023-03-06 SALIN 3.0905878046 #> 5857 2056E 3M CC42 2019 2019-10-10 CHLAC 1.5892352051 #> 5858 2056E 3M CC42 2019 2019-10-10 COND 9.8078573215 #> 5859 2056E 3M CC42 2019 2019-10-10 NO23 -3.7722610631 #> 5860 2056E 3M CC42 2019 2019-10-10 SALIN 2.3721111556 #> 5861 2056E 3M CC42 2019 2019-10-10 TKN -0.3566749439 #> 5862 2056E 3M CC42 2019 2019-10-10 TN -0.3243460568 + #> 5863 2056E 3M CC42 2019 2019-10-10 TP -1.0498221245 #> 5864 2056E 3M CC42 2019 2019-10-10 TSS 1.7917594692 I #> 5865 2056E 3M CC42 2019 2019-10-10 TURB 1.0647107370 #> 5866 2056C2 3M CC45 2014 2014-06-10 COND 9.8892364868 #> 5867 2056C2 3M CC45 2014 2014-06-10 DO 1.9344157696 #> 5868 2056C2 3M CC45 2014 2014-06-10 DOSAT 4.5920849464 + #> 5869 2056C2 3M CC45 2014 2014-06-10 SALIN 2.4595888418 #> 5870 2056C2 3M CC45 2014 2014-06-10 NO23 -5.5214609179 U #> 5871 2056C2 3M CC45 2014 2014-06-10 TKN 1.2809338455 #> 5872 2056C2 3M CC45 2014 2014-06-10 TN 1.2809338455 #> 5873 2056C2 3M CC45 2014 2014-06-10 TSS 2.3513752572 #> 5874 2056C2 3M CC45 2014 2014-06-10 COND 9.8874597915 #> 5875 2056C2 3M CC45 2014 2014-06-10 DO 2.0014800002 #> 5876 2056C2 3M CC45 2014 2014-06-10 DOSAT 4.6587109529 + #> 5877 2056C2 3M CC45 2014 2014-06-10 SALIN 2.4587337755 #> 5878 2056C2 3M CC45 2014 2014-06-10 COND 9.9269599087 #> 5879 2056C2 3M CC45 2014 2014-06-10 DO 1.9933388426 #> 5880 2056C2 3M CC45 2014 2014-06-10 DOSAT 4.6510991179 + #> 5881 2056C2 3M CC45 2014 2014-06-10 SALIN 2.5014359517 #> 5882 2056C2 3M CC45 2014 2014-06-10 COND 9.9782238987 #> 5883 2056C2 3M CC45 2014 2014-06-10 DO 1.8916048042 #> 5884 2056C2 3M CC45 2014 2014-06-10 DOSAT 4.5475410732 + #> 5885 2056C2 3M CC45 2014 2014-06-10 SALIN 2.5572273114 #> 5886 2056C2 3M CC45 2014 2014-06-10 COND 10.0037852739 #> 5887 2056C2 3M CC45 2014 2014-06-10 DO 1.8017098001 #> 5888 2056C2 3M CC45 2014 2014-06-10 DOSAT 4.4578295981 + #> 5889 2056C2 3M CC45 2014 2014-06-10 SALIN 2.5862591440 #> 5890 2056C2 3M CC45 2014 2014-06-10 COND 10.0950165901 #> 5891 2056C2 3M CC45 2014 2014-06-10 DO 1.5475625087 #> 5892 2056C2 3M CC45 2014 2014-06-10 DOSAT 4.2061840440 + #> 5893 2056C2 3M CC45 2014 2014-06-10 SALIN 2.6932749155 #> 5894 2056C2 3M CC45 2014 2014-06-10 COND 10.1085078656 #> 5895 2056C2 3M CC45 2014 2014-06-10 DO 1.4562867329 #> 5896 2056C2 3M CC45 2014 2014-06-10 DOSAT 4.1141471895 + #> 5897 2056C2 3M CC45 2014 2014-06-10 SALIN 2.6932749155 #> 5898 2056C2 3M CC45 2014 2014-06-10 COND 10.1103391071 #> 5899 2056C2 3M CC45 2014 2014-06-10 DO 1.4182774070 #> 5900 2056C2 3M CC45 2014 2014-06-10 DOSAT 4.0775374439 + #> 5901 2056C2 3M CC45 2014 2014-06-10 SALIN 2.7020321288 #> 5902 2056C2 3M CC45 2014 2014-06-10 COND 10.1112331617 #> 5903 2056C2 3M CC45 2014 2014-06-10 DO 1.4109869737 #> 5904 2056C2 3M CC45 2014 2014-06-10 DOSAT 4.0690267542 + #> 5905 2056C2 3M CC45 2014 2014-06-10 SALIN 2.7027025948 #> 5906 2056C2 3M CC45 2014 2014-06-10 COND 10.1134242764 #> 5907 2056C2 3M CC45 2014 2014-06-10 DO 1.3787660947 #> 5908 2056C2 3M CC45 2014 2014-06-10 DOSAT 4.0377742107 + #> 5909 2056C2 3M CC45 2014 2014-06-10 SALIN 2.7053799725 #> 5910 2056C2 3M CC45 2014 2014-07-10 COND 9.9863570304 #> 5911 2056C2 3M CC45 2014 2014-07-10 DO 2.9204697891 #> 5912 2056C2 3M CC45 2014 2014-07-10 DOSAT 5.6028565561 + #> 5913 2056C2 3M CC45 2014 2014-07-10 SALIN 2.5664866368 #> 5914 2056C2 3M CC45 2014 2014-07-10 NO23 -4.1351665567 I #> 5915 2056C2 3M CC45 2014 2014-07-10 TKN 0.5933268453 #> 5916 2056C2 3M CC45 2014 2014-07-10 TN 0.5988365011 #> 5917 2056C2 3M CC45 2014 2014-07-10 TSS 2.6602595373 #> 5918 2056C2 3M CC45 2014 2014-07-10 COND 10.2631181243 #> 5919 2056C2 3M CC45 2014 2014-07-10 DO 2.5136560631 #> 5920 2056C2 3M CC45 2014 2014-07-10 DOSAT 5.1935122522 + #> 5921 2056C2 3M CC45 2014 2014-07-10 SALIN 2.7219531063 #> 5922 2056C2 3M CC45 2014 2014-07-10 COND 10.5858012624 #> 5923 2056C2 3M CC45 2014 2014-07-10 DO 1.3584091576 #> 5924 2056C2 3M CC45 2014 2014-07-10 DOSAT 4.0893320204 + #> 5925 2056C2 3M CC45 2014 2014-07-10 SALIN 3.2284300377 #> 5926 2056C2 3M CC45 2014 2014-07-10 COND 10.5893079577 #> 5927 2056C2 3M CC45 2014 2014-07-10 DO 1.2383742310 #> 5928 2056C2 3M CC45 2014 2014-07-10 DOSAT 3.9702919136 + #> 5929 2056C2 3M CC45 2014 2014-07-10 SALIN 3.2327787300 #> 5930 2056C2 3M CC45 2014 2014-07-10 COND 10.5894086880 #> 5931 2056C2 3M CC45 2014 2014-07-10 DO 1.2178757095 #> 5932 2056C2 3M CC45 2014 2014-07-10 DOSAT 3.9493187902 + #> 5933 2056C2 3M CC45 2014 2014-07-10 SALIN 3.2335673736 #> 5934 2056C2 3M CC45 2014 2014-07-10 COND 10.5868621364 #> 5935 2056C2 3M CC45 2014 2014-07-10 DO 0.7654678421 #> 5936 2056C2 3M CC45 2014 2014-07-10 DOSAT 3.4965075615 + #> 5937 2056C2 3M CC45 2014 2014-07-10 SALIN 3.2331731296 #> 5938 2053 2 CC50 2018 2018-03-15 CHLAC 0.9932517730 #> 5939 2053 2 CC50 2018 2018-03-15 COND 10.6964800681 #> 5940 2053 2 CC50 2018 2018-03-15 DO 2.0918640617 #> 5941 2053 2 CC50 2018 2018-03-15 DOSAT 4.6249728133 #> 5942 2053 2 CC50 2018 2018-03-15 NO23 -5.5214609179 U #> 5943 2053 2 CC50 2018 2018-03-15 SALIN 3.5010427166 + #> 5944 2053 2 CC50 2018 2018-03-15 TKN -0.5108256238 #> 5945 2053 2 CC50 2018 2018-03-15 TN -0.5074978337 + #> 5946 2053 2 CC50 2018 2018-03-15 TP -1.8325814637 #> 5947 2053 2 CC50 2018 2018-03-15 TSS 1.7917594692 I #> 5948 2053 2 CC50 2018 2018-03-15 TURB 1.1631508098 A #> 5949 2053 2 CC50 2018 2018-03-29 CHLAC 1.9459101491 #> 5950 2053 2 CC50 2018 2018-03-29 COND 10.6310361598 #> 5951 2053 2 CC50 2018 2018-03-29 DO 1.8405496334 #> 5952 2053 2 CC50 2018 2018-03-29 DOSAT 4.4426512565 #> 5953 2053 2 CC50 2018 2018-03-29 NO23 -5.5214609179 U #> 5954 2053 2 CC50 2018 2018-03-29 SALIN 3.3382575819 + #> 5955 2053 2 CC50 2018 2018-03-29 TKN 0.4054651081 #> 5956 2053 2 CC50 2018 2018-03-29 TN 0.4067975533 + #> 5957 2053 2 CC50 2018 2018-03-29 TP -1.8325814637 #> 5958 2053 2 CC50 2018 2018-03-29 TSS 2.6390573296 #> 5959 2053 2 CC50 2018 2018-03-29 TURB 1.7047480922 #> 5960 2053 2 CC50 2018 2018-04-23 CHLAC 2.0794415417 #> 5961 2053 2 CC50 2018 2018-04-23 COND 10.6468524493 #> 5962 2053 2 CC50 2018 2018-04-23 DO 1.9459101491 #> 5963 2053 2 CC50 2018 2018-04-23 DOSAT 4.6249728133 #> 5964 2053 2 CC50 2018 2018-04-23 NO23 -5.5214609179 U #> 5965 2053 2 CC50 2018 2018-04-23 SALIN 3.2649957605 + #> 5966 2053 2 CC50 2018 2018-04-23 TKN -0.3710636814 #> 5967 2053 2 CC50 2018 2018-04-23 TN -0.3681693234 + #> 5968 2053 2 CC50 2018 2018-04-23 TP -1.5141277326 #> 5969 2053 2 CC50 2018 2018-04-23 TSS 3.3322045102 A #> 5970 2053 2 CC50 2018 2018-04-23 TURB 1.8718021769 #> 5971 2053 2 CC50 2018 2018-05-10 CHLAC 1.7917594692 #> 5972 2053 2 CC50 2018 2018-05-10 COND 10.6712318713 #> 5973 2053 2 CC50 2018 2018-05-10 DO 1.5040773968 #> 5974 2053 2 CC50 2018 2018-05-10 DOSAT 4.1588830834 #> 5975 2053 2 CC50 2018 2018-05-10 NO23 -5.2983173665 I #> 5976 2053 2 CC50 2018 2018-05-10 SALIN 3.3214324132 #> 5977 2053 2 CC50 2018 2018-05-10 TKN -0.1165338163 #> 5978 2053 2 CC50 2018 2018-05-10 TN -0.1120495038 + #> 5979 2053 2 CC50 2018 2018-05-10 TP -1.3862943611 #> 5980 2053 2 CC50 2018 2018-05-10 TSS 2.7080502011 #> 5981 2053 2 CC50 2018 2018-05-10 TURB 1.9021075264 #> 5982 2053 2 CC50 2018 2018-06-11 CHLAC 2.6390573296 #> 5983 2053 2 CC50 2018 2018-06-11 COND 9.5468126086 #> 5984 2053 2 CC50 2018 2018-06-11 DO 1.6094379124 #> 5985 2053 2 CC50 2018 2018-06-11 DOSAT 4.2341065046 #> 5986 2053 2 CC50 2018 2018-06-11 NO23 -2.7806208939 #> 5987 2053 2 CC50 2018 2018-06-11 SALIN 2.0918640617 #> 5988 2053 2 CC50 2018 2018-06-11 TKN 0.1823215568 #> 5989 2053 2 CC50 2018 2018-06-11 TN 0.2326977641 + #> 5990 2053 2 CC50 2018 2018-06-11 TP -0.7133498879 #> 5991 2053 2 CC50 2018 2018-06-11 TSS 1.3862943611 I #> 5992 2053 2 CC50 2018 2018-06-11 TURB 0.7419373447 #> 5993 2053 2 CC50 2018 2018-06-25 CHLAC 3.4011973817 #> 5994 2053 2 CC50 2018 2018-06-25 COND 10.0243768698 #> 5995 2053 2 CC50 2018 2018-06-25 DO 1.7209792872 #> 5996 2053 2 CC50 2018 2018-06-25 DOSAT 4.3719762988 #> 5997 2053 2 CC50 2018 2018-06-25 NO23 -2.9374633654 #> 5998 2053 2 CC50 2018 2018-06-25 SALIN 2.5055259370 + #> 5999 2053 2 CC50 2018 2018-06-25 TKN 0.0953101798 #> 6000 2053 2 CC50 2018 2018-06-25 TN 0.1423672413 + #> 6001 2053 2 CC50 2018 2018-06-25 TP -0.9162907319 #> 6002 2053 2 CC50 2018 2018-06-25 TSS 1.3862943611 I #> 6003 2053 2 CC50 2018 2018-06-25 TURB 0.9932517730 #> 6004 2053 2 CC50 2018 2018-08-07 CHLAC 2.8332133441 #> 6005 2053 2 CC50 2018 2018-08-07 COND 7.3382381501 #> 6006 2053 2 CC50 2018 2018-08-07 DO 1.7698546338 #> 6007 2053 2 CC50 2018 2018-08-07 DOSAT 4.3438054219 #> 6008 2053 2 CC50 2018 2018-08-07 NO23 -3.1235656451 #> 6009 2053 2 CC50 2018 2018-08-07 SALIN -0.2613647641 #> 6010 2053 2 CC50 2018 2018-08-07 TKN 0.0953101798 #> 6011 2053 2 CC50 2018 2018-08-07 TN 0.1345308930 + #> 6012 2053 2 CC50 2018 2018-08-07 TP -1.2378743560 #> 6013 2053 2 CC50 2018 2018-08-07 TSS 1.3862943611 I #> 6014 2053 2 CC50 2018 2018-08-07 TURB 0.9162907319 A #> 6015 2053 2 CC50 2018 2018-09-06 CHLAC 2.0014800002 #> 6016 2053 2 CC50 2018 2018-09-06 COND 8.6513743729 #> 6017 2053 2 CC50 2018 2018-09-06 DO 1.8341801851 #> 6018 2053 2 CC50 2018 2018-09-06 DOSAT 4.4236483094 #> 6019 2053 2 CC50 2018 2018-09-06 NO23 -2.5383074265 #> 6020 2053 2 CC50 2018 2018-09-06 SALIN 1.1281710909 #> 6021 2053 2 CC50 2018 2018-09-06 TKN 0.1823215568 #> 6022 2053 2 CC50 2018 2018-09-06 TN 0.2460785226 + #> 6023 2053 2 CC50 2018 2018-09-06 TP -1.2378743560 #> 6024 2053 2 CC50 2018 2018-09-06 TSS 1.3862943611 I #> 6025 2053 2 CC50 2018 2018-09-06 TURB 0.6931471806 #> 6026 2053 2 CC50 2018 2018-09-20 CHLAC 2.5649493575 #> 6027 2053 2 CC50 2018 2018-09-20 COND 9.3369730229 #> 6028 2053 2 CC50 2018 2018-09-20 DO 1.6582280766 #> 6029 2053 2 CC50 2018 2018-09-20 DOSAT 4.1682144108 #> 6030 2053 2 CC50 2018 2018-09-20 NO23 -4.1351665567 #> 6031 2053 2 CC50 2018 2018-09-20 SALIN 1.8562979904 #> 6032 2053 2 CC50 2018 2018-09-20 TKN -0.0725706928 #> 6033 2053 2 CC50 2018 2018-09-20 TN -0.0555127099 + #> 6034 2053 2 CC50 2018 2018-09-20 TP -1.1394342832 #> 6035 2053 2 CC50 2018 2018-09-20 TSS 1.3862943611 I #> 6036 2053 2 CC50 2018 2018-09-20 TURB 0.4700036292 #> 6037 2053 2 CC50 2018 2018-10-24 CHLAC 1.9600947840 #> 6038 2053 2 CC50 2018 2018-10-24 COND 10.0400269167 #> 6039 2053 2 CC50 2018 2018-10-24 DO 1.9430489168 #> 6040 2053 2 CC50 2018 2018-10-24 DOSAT 4.5496574761 #> 6041 2053 2 CC50 2018 2018-10-24 NO23 -2.7488721956 #> 6042 2053 2 CC50 2018 2018-10-24 SALIN 2.6246685922 #> 6043 2053 2 CC50 2018 2018-10-24 TKN -0.3011050928 #> 6044 2053 2 CC50 2018 2018-10-24 TN -0.2181560098 + #> 6045 2053 2 CC50 2018 2018-10-24 TP -1.4271163556 #> 6046 2053 2 CC50 2018 2018-10-24 TSS 1.6094379124 I #> 6047 2053 2 CC50 2018 2018-10-24 TURB 0.9162907319 #> 6048 2053 2 CC50 2019 2019-04-17 CHLAC 1.5892352051 I #> 6049 2053 2 CC50 2019 2019-04-17 COND 10.3074515345 #> 6050 2053 2 CC50 2019 2019-04-17 DO 1.9878743482 #> 6051 2053 2 CC50 2019 2019-04-17 DOSAT 4.5981455711 #> 6052 2053 2 CC50 2019 2019-04-17 NO23 -5.5214609179 U #> 6053 2053 2 CC50 2019 2019-04-17 SALIN 2.9193910403 #> 6054 2053 2 CC50 2019 2019-04-17 TKN -0.4462871026 #> 6055 2053 2 CC50 2019 2019-04-17 TN -0.4431669753 + #> 6056 2053 2 CC50 2019 2019-04-17 TP -1.6607312068 #> 6057 2053 2 CC50 2019 2019-04-17 TSS 2.9444389792 A #> 6058 2053 2 CC50 2019 2019-04-17 TURB 1.0296194172 #> 6059 2053 2 CC50 2019 2019-07-15 CHLAC 3.0910424534 #> 6060 2053 2 CC50 2019 2019-07-15 COND 10.0506999322 #> 6061 2053 2 CC50 2019 2019-07-15 DO 1.9430489168 #> 6062 2053 2 CC50 2019 2019-07-15 DOSAT 4.5971380143 #> 6063 2053 2 CC50 2019 2019-07-15 NO23 -5.5214609179 U #> 6064 2053 2 CC50 2019 2019-07-15 SALIN 2.6333266549 #> 6065 2053 2 CC50 2019 2019-07-15 TKN -0.2107210313 #> 6066 2053 2 CC50 2019 2019-07-15 TN -0.2082549388 + #> 6067 2053 2 CC50 2019 2019-07-15 TP -1.4696759701 #> 6068 2053 2 CC50 2019 2019-07-15 TSS 2.0794415417 I #> 6069 2053 2 CC50 2019 2019-07-15 TURB 0.9932517730 #> 6070 2053 2 CC50 2019 2019-08-19 CHLAC 1.4816045409 #> 6071 2053 2 CC50 2019 2019-08-19 COND 7.3530819205 #> 6072 2053 2 CC50 2019 2019-08-19 DO 1.5665304114 #> 6073 2053 2 CC50 2019 2019-08-19 DOSAT 4.1367652781 #> 6074 2053 2 CC50 2019 2019-08-19 NO23 -2.6036901858 #> 6075 2053 2 CC50 2019 2019-08-19 SALIN -0.2484613593 #> 6076 2053 2 CC50 2019 2019-08-19 TKN 0.3364722366 #> 6077 2053 2 CC50 2019 2019-08-19 TN 0.3879797938 + #> 6078 2053 2 CC50 2019 2019-08-19 TP -0.8209805521 #> 6079 2053 2 CC50 2019 2019-08-19 TSS 1.0986122887 I #> 6080 2053 2 CC50 2019 2019-08-19 TURB 0.7884573604 #> 6081 2053 2 CC50 2019 2019-09-11 CHLAC 3.0910424534 #> 6082 2053 2 CC50 2019 2019-09-11 COND 9.8378817954 #> 6083 2053 2 CC50 2019 2019-09-11 DO 1.9139771020 #> 6084 2053 2 CC50 2019 2019-09-11 DOSAT 4.5475410732 #> 6085 2053 2 CC50 2019 2019-09-11 NO23 -4.0173835211 #> 6086 2053 2 CC50 2019 2019-09-11 SALIN 2.4015250408 #> 6087 2053 2 CC50 2019 2019-09-11 TKN -0.0725706928 #> 6088 2053 2 CC50 2019 2019-09-11 TN -0.0534007767 + #> 6089 2053 2 CC50 2019 2019-09-11 TP -1.2039728043 #> 6090 2053 2 CC50 2019 2019-09-11 TSS 1.6094379124 I #> 6091 2053 2 CC50 2019 2019-09-11 TURB 0.7884573604 #> 6092 2053 2 CC50 2019 2019-10-09 CHLAC 1.1939224685 #> 6093 2053 2 CC50 2019 2019-10-09 COND 10.2652793829 #> 6094 2053 2 CC50 2019 2019-10-09 DO 1.7065646232 #> 6095 2053 2 CC50 2019 2019-10-09 DOSAT 4.3554259529 #> 6096 2053 2 CC50 2019 2019-10-09 NO23 -5.5214609179 I #> 6097 2053 2 CC50 2019 2019-10-09 SALIN 2.8713021952 #> 6098 2053 2 CC50 2019 2019-10-09 TKN -0.4155154440 #> 6099 2053 2 CC50 2019 2019-10-09 TN -0.4094731295 + #> 6100 2053 2 CC50 2019 2019-10-09 TP -1.5141277326 #> 6101 2053 2 CC50 2019 2019-10-09 TSS 1.0986122887 U #> 6102 2053 2 CC50 2019 2019-10-09 TURB -0.1625189295 #> 6103 2053 2 CC50 2020 2020-02-13 CHLAC 1.5475625087 #> 6104 2053 2 CC50 2020 2020-02-13 COND 10.4652439050 #> 6105 2053 2 CC50 2020 2020-02-13 DO 1.8017098001 #> 6106 2053 2 CC50 2020 2020-02-13 DOSAT 4.4067192473 #> 6107 2053 2 CC50 2020 2020-02-13 NO23 -5.5214609179 U #> 6108 2053 2 CC50 2020 2020-02-13 SALIN 3.0946722214 #> 6109 2053 2 CC50 2020 2020-02-13 TKN -0.4620354596 #> 6110 2053 2 CC50 2020 2020-02-13 TN -0.4588658848 + #> 6111 2053 2 CC50 2020 2020-02-13 TP -1.8325814637 #> 6112 2053 2 CC50 2020 2020-02-13 TSS 2.7080502011 #> 6113 2053 2 CC50 2020 2020-02-13 TURB 2.0014800002 A #> 6114 2053 2 CC50 2020 2020-03-24 CHLAC 1.3350010667 #> 6115 2053 2 CC50 2020 2020-03-24 COND 10.5688523521 #> 6116 2053 2 CC50 2020 2020-03-24 DO 1.9401794743 #> 6117 2053 2 CC50 2020 2020-03-24 DOSAT 4.6434288981 #> 6118 2053 2 CC50 2020 2020-03-24 NO23 -5.5214609179 U #> 6119 2053 2 CC50 2020 2020-03-24 SALIN 3.2047769005 #> 6120 2053 2 CC50 2020 2020-03-24 TKN -0.4462871026 #> 6121 2053 2 CC50 2020 2020-03-24 TN -0.4431669753 + #> 6122 2053 2 CC50 2020 2020-03-24 TP -1.8325814637 #> 6123 2053 2 CC50 2020 2020-03-24 TSS 2.7725887222 #> 6124 2053 2 CC50 2020 2020-03-24 TURB 1.5260563035 #> 6125 2053 2 CC50 2020 2020-06-22 CHLAC 3.1780538303 #> 6126 2053 2 CC50 2020 2020-06-22 COND 9.9972510823 #> 6127 2053 2 CC50 2020 2020-06-22 DO 1.7173950539 #> 6128 2053 2 CC50 2020 2020-06-22 DOSAT 4.3795235045 #> 6129 2053 2 CC50 2020 2020-06-22 NO23 -4.5098600062 #> 6130 2053 2 CC50 2020 2020-06-22 SALIN 2.5718485799 #> 6131 2053 2 CC50 2020 2020-06-22 TKN -0.0100503359 #> 6132 2053 2 CC50 2020 2020-06-22 TN 0.0009995003 + #> 6133 2053 2 CC50 2020 2020-06-22 TP -1.2039728043 #> 6134 2053 2 CC50 2020 2020-06-22 TSS 1.7917594692 I #> 6135 2053 2 CC50 2020 2020-06-22 TURB 0.7884573604 A #> 6136 2053 2 CC50 2020 2020-07-27 CHLAC 1.7578579176 #> 6137 2053 2 CC50 2020 2020-07-27 COND 10.1123293191 #> 6138 2053 2 CC50 2020 2020-07-27 DO 1.5644405465 #> 6139 2053 2 CC50 2020 2020-07-27 DOSAT 4.2239097666 #> 6140 2053 2 CC50 2020 2020-07-27 NO23 -4.1351665567 #> 6141 2053 2 CC50 2020 2020-07-27 SALIN 2.7006898467 #> 6142 2053 2 CC50 2020 2020-07-27 TN -0.3481400415 + #> 6143 2053 2 CC50 2020 2020-07-27 TP -1.3093333200 #> 6144 2053 2 CC50 2020 2020-07-27 TSS 1.0986122887 U #> 6145 2053 2 CC50 2020 2020-07-27 TURB 0.5306282511 #> 6146 2053 2 CC50 2020 2020-08-26 CHLAC 2.2300144002 #> 6147 2053 2 CC50 2020 2020-08-26 COND 9.8854254097 #> 6148 2053 2 CC50 2020 2020-08-26 DO 1.7850704811 #> 6149 2053 2 CC50 2020 2020-08-26 DOSAT 4.4188406078 #> 6150 2053 2 CC50 2020 2020-08-26 NO23 -5.5214609179 U #> 6151 2053 2 CC50 2020 2020-08-26 SALIN 2.4535879665 #> 6152 2053 2 CC50 2020 2020-08-26 TKN -0.1984509387 #> 6153 2053 2 CC50 2020 2020-08-26 TN -0.1960148839 + #> 6154 2053 2 CC50 2020 2020-08-26 TP -1.3862943611 #> 6155 2053 2 CC50 2020 2020-08-26 TSS 1.0986122887 U #> 6156 2053 2 CC50 2020 2020-08-26 TURB 0.0953101798 #> 6157 2053 2 CC50 2021 2021-01-14 CHLAC 1.6094379124 A #> 6158 2053 2 CC50 2021 2021-01-14 COND 10.2228136303 #> 6159 2053 2 CC50 2021 2021-01-14 DO 2.0967901800 #> 6160 2053 2 CC50 2021 2021-01-14 DOSAT 4.5580785785 #> 6161 2053 2 CC50 2021 2021-01-14 NO23 -5.5214609179 I #> 6162 2053 2 CC50 2021 2021-01-14 SALIN 2.8314470792 #> 6163 2053 2 CC50 2021 2021-01-14 TKN -0.2876820725 #> 6164 2053 2 CC50 2021 2021-01-14 TN -0.2823629110 + #> 6165 2053 2 CC50 2021 2021-01-14 TP -1.7147984281 #> 6166 2053 2 CC50 2021 2021-01-14 TSS 2.5649493575 A #> 6167 2053 2 CC50 2021 2021-01-14 TURB 1.4586150227 #> 6168 2053 2 CC50 2021 2021-02-24 COND 10.2486009183 #> 6169 2053 2 CC50 2021 2021-02-24 DO 2.0955609236 #> 6170 2053 2 CC50 2021 2021-02-24 DOSAT 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6189 2053 2 CC50 2021 2021-07-28 COND 9.4095190458 #> 6190 2053 2 CC50 2021 2021-07-28 DO 0.9516578757 #> 6191 2053 2 CC50 2021 2021-07-28 DOSAT 3.5638829639 #> 6192 2053 2 CC50 2021 2021-07-28 NO23 -3.1700856607 #> 6193 2053 2 CC50 2021 2021-07-28 SALIN 1.9373017745 #> 6194 2053 2 CC50 2021 2021-07-28 TKN 0.1823215568 #> 6195 2053 2 CC50 2021 2021-07-28 TN 0.2167229835 + #> 6196 2053 2 CC50 2021 2021-07-28 TP -0.7550225843 #> 6197 2053 2 CC50 2021 2021-07-28 TSS 1.3862943611 I #> 6198 2053 2 CC50 2021 2021-07-28 TURB 1.7404661748 #> 6199 2053 2 CC50 2021 2021-08-26 CHLAC 1.5260563035 #> 6200 2053 2 CC50 2021 2021-08-26 COND 9.2069345788 #> 6201 2053 2 CC50 2021 2021-08-26 DO 1.0296194172 #> 6202 2053 2 CC50 2021 2021-08-26 DOSAT 3.6270040504 #> 6203 2053 2 CC50 2021 2021-08-26 NO23 -2.7488721956 #> 6204 2053 2 CC50 2021 2021-08-26 SALIN 1.7191887764 #> 6205 2053 2 CC50 2021 2021-08-26 TKN -0.3285040670 #> 6206 2053 2 CC50 2021 2021-08-26 TN -0.2433462586 + #> 6207 2053 2 CC50 2021 2021-08-26 TP -1.0216512475 #> 6208 2053 2 CC50 2021 2021-08-26 TSS 1.0986122887 I #> 6209 2053 2 CC50 2021 2021-08-26 TURB 0.9555114450 #> 6210 2053 2 CC50 2021 2021-09-13 CHLAC 1.7578579176 #> 6211 2053 2 CC50 2021 2021-09-13 COND 9.5941731800 #> 6212 2053 2 CC50 2021 2021-09-13 DO 1.4422019931 #> 6213 2053 2 CC50 2021 2021-09-13 DOSAT 4.0707346966 #> 6214 2053 2 CC50 2021 2021-09-13 NO23 -2.7806208939 #> 6215 2053 2 CC50 2021 2021-09-13 SALIN 2.1365305087 #> 6216 2053 2 CC50 2021 2021-09-13 TKN -0.0618754037 #> 6217 2053 2 CC50 2021 2021-09-13 TN 0.0019980027 + #> 6218 2053 2 CC50 2021 2021-09-13 TP -1.2039728043 #> 6219 2053 2 CC50 2021 2021-09-13 TSS 1.0986122887 I #> 6220 2053 2 CC50 2021 2021-09-13 TURB 0.5877866649 #> 6221 2053 2 CC50 2022 2022-03-16 COND 10.6209126256 #> 6222 2053 2 CC50 2022 2022-03-16 DO 1.9080599249 #> 6223 2053 2 CC50 2022 2022-03-16 DOSAT 4.5152454785 #> 6224 2053 2 CC50 2022 2022-03-16 SALIN 3.2676659890 #> 6225 2053 2 CC50 2022 2022-05-04 COND 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#> 6244 2054 3F CC53 2014 2014-01-06 TN -0.0714960017 + #> 6245 2054 3F CC53 2014 2014-01-06 TP -2.9565115604 #> 6246 2054 3F CC53 2014 2014-01-06 TURB 1.1939224685 A #> 6247 2054 3F CC53 2014 2014-02-03 CHLAC 2.5649493575 #> 6248 2054 3F CC53 2014 2014-02-03 COLOR 4.0073331852 #> 6249 2054 3F CC53 2014 2014-02-03 DO 2.0014800002 #> 6250 2054 3F CC53 2014 2014-02-03 DOSAT 4.3956829611 + #> 6251 2054 3F CC53 2014 2014-02-03 NO23 -2.1202635362 #> 6252 2054 3F CC53 2014 2014-02-03 SALIN -0.3566749439 #> 6253 2054 3F CC53 2014 2014-02-03 TKN 0.0953101798 #> 6254 2054 3F CC53 2014 2014-02-03 TN 0.1988508587 + #> 6255 2054 3F CC53 2014 2014-02-03 TP -1.9661128564 #> 6256 2054 3F CC53 2014 2014-02-03 TURB 1.3350010667 #> 6257 2054 3F CC53 2014 2014-03-03 CHLAC 2.4849066498 #> 6258 2054 3F CC53 2014 2014-03-03 COLOR 4.1271343850 #> 6259 2054 3F CC53 2014 2014-03-03 DO 1.8082887712 #> 6260 2054 3F CC53 2014 2014-03-03 DOSAT 4.2398868675 + #> 6261 2054 3F CC53 2014 2014-03-03 NO23 -5.5214609179 U #> 6262 2054 3F CC53 2014 2014-03-03 SALIN 0.8754687374 #> 6263 2054 3F CC53 2014 2014-03-03 TKN 0.0953101798 #> 6264 2054 3F CC53 2014 2014-03-03 TN 0.0971267107 + #> 6265 2054 3F CC53 2014 2014-03-03 TP -2.0402208285 #> 6266 2054 3F CC53 2014 2014-03-03 TURB 1.7227665977 #> 6267 2054 3F CC53 2014 2014-04-07 CHLAC 2.3978952728 #> 6268 2054 3F CC53 2014 2014-04-07 COLOR 4.0253516907 #> 6269 2054 3F CC53 2014 2014-04-07 DO 1.6292405397 #> 6270 2054 3F CC53 2014 2014-04-07 DOSAT 4.0960098415 + #> 6271 2054 3F CC53 2014 2014-04-07 NO23 -4.3428059215 #> 6272 2054 3F CC53 2014 2014-04-07 TKN -0.0943106795 #> 6273 2054 3F CC53 2014 2014-04-07 TN -0.0801260445 + #> 6274 2054 3F CC53 2014 2014-04-07 TP -2.1202635362 #> 6275 2054 3F CC53 2014 2014-04-07 TURB 1.1939224685 #> 6276 2054 3F CC53 2014 2014-05-05 CHLAC 2.4849066498 #> 6277 2054 3F CC53 2014 2014-05-05 COLOR 4.0073331852 #> 6278 2054 3F CC53 2014 2014-05-05 DO 1.9459101491 #> 6279 2054 3F CC53 2014 2014-05-05 DOSAT 4.4006030202 + #> 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-2.9187712324 #> 6388 2054 3F CC53 2015 2015-05-04 TKN 0.1823215568 #> 6389 2054 3F CC53 2015 2015-05-04 TN 0.2263384422 + #> 6390 2054 3F CC53 2015 2015-05-04 TP -2.3968957725 #> 6391 2054 3F CC53 2015 2015-05-04 TURB 1.2809338455 #> 6392 2054 3F CC53 2015 2015-06-01 CHLAC 2.3025850930 #> 6393 2054 3F CC53 2015 2015-06-01 COLOR 4.2766661190 #> 6394 2054 3F CC53 2015 2015-06-01 DO 1.3711807233 #> 6395 2054 3F CC53 2015 2015-06-01 DOSAT 3.9259259106 + #> 6396 2054 3F CC53 2015 2015-06-01 NO23 -4.6051701860 #> 6397 2054 3F CC53 2015 2015-06-01 SALIN 1.2059708070 #> 6398 2054 3F CC53 2015 2015-06-01 TKN -0.0100503359 #> 6399 2054 3F CC53 2015 2015-06-01 TN 0.0000000000 + #> 6400 2054 3F CC53 2015 2015-06-01 TP -1.5141277326 #> 6401 2054 3F CC53 2015 2015-06-01 TURB 0.7419373447 #> 6402 2054 3F CC53 2015 2015-08-03 CHLAC 0.5877866649 #> 6403 2054 3F CC53 2015 2015-08-03 COLOR 4.9416424226 #> 6404 2054 3F CC53 2015 2015-08-03 DO 1.3428648032 #> 6405 2054 3F CC53 2015 2015-08-03 DOSAT 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2016-02-01 TP -2.6592600369 #> 6460 2054 3F CC53 2016 2016-02-01 TURB 0.5877866649 A #> 6461 2054 3F CC53 2016 2016-03-07 CHLAC 0.4054651081 I #> 6462 2054 3F CC53 2016 2016-03-07 COLOR 4.3174881135 #> 6463 2054 3F CC53 2016 2016-03-07 DO 1.6074359098 #> 6464 2054 3F CC53 2016 2016-03-07 DOSAT 4.0127729085 + #> 6465 2054 3F CC53 2016 2016-03-07 NO23 -3.6119184130 #> 6466 2054 3F CC53 2016 2016-03-07 SALIN -2.3025850930 #> 6467 2054 3F CC53 2016 2016-03-07 TKN -0.3147107448 #> 6468 2054 3F CC53 2016 2016-03-07 TN -0.2783920255 + #> 6469 2054 3F CC53 2016 2016-03-07 TP -2.9004220937 #> 6470 2054 3F CC53 2016 2016-03-07 TURB 0.5306282511 A #> 6471 2054 3F CC53 2016 2016-04-04 CHLAC 2.0149030205 #> 6472 2054 3F CC53 2016 2016-04-04 COLOR 4.0604430105 #> 6473 2054 3F CC53 2016 2016-04-04 DO 1.5454325825 #> 6474 2054 3F CC53 2016 2016-04-04 DOSAT 4.0253516907 + #> 6475 2054 3F CC53 2016 2016-04-04 NO23 -3.7722610631 #> 6476 2054 3F CC53 2016 2016-04-04 SALIN -1.3093333200 #> 6477 2054 3F 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CC53 2017 2017-01-03 CHLAC 2.1633230257 #> 6550 2054 3F CC53 2017 2017-01-03 COLOR 3.7841896339 A #> 6551 2054 3F CC53 2017 2017-01-03 DO 1.5892352051 #> 6552 2054 3F CC53 2017 2017-01-03 DOSAT 4.0638853547 + #> 6553 2054 3F CC53 2017 2017-01-03 NO23 -5.1159958098 I #> 6554 2054 3F CC53 2017 2017-01-03 SALIN 1.8405496334 #> 6555 2054 3F CC53 2017 2017-01-03 TKN -0.3710636814 #> 6556 2054 3F CC53 2017 2017-01-03 TN -0.3652833185 + #> 6557 2054 3F CC53 2017 2017-01-03 TP -1.9661128564 #> 6558 2054 3F CC53 2017 2017-01-03 TURB 0.9555114450 #> 6559 2054 3F CC53 2017 2017-02-06 CHLAC 1.7047480922 #> 6560 2054 3F CC53 2017 2017-02-06 COLOR 3.6635616461 #> 6561 2054 3F CC53 2017 2017-02-06 DO 1.3609765531 #> 6562 2054 3F CC53 2017 2017-02-06 DOSAT 3.7819143201 + #> 6563 2054 3F CC53 2017 2017-02-06 NO23 -2.6310891600 #> 6564 2054 3F CC53 2017 2017-02-06 SALIN 1.2527629685 #> 6565 2054 3F CC53 2017 2017-02-06 TKN -0.2876820725 #> 6566 2054 3F CC53 2017 2017-02-06 TN -0.1960148839 + #> 6567 2054 3F CC53 2017 2017-02-06 TP -2.1202635362 #> 6568 2054 3F CC53 2017 2017-02-06 TURB 1.1939224685 A #> 6569 2054 3F CC53 2017 2017-03-06 CHLAC 1.0986122887 #> 6570 2054 3F CC53 2017 2017-03-06 COLOR 3.7135720667 #> 6571 2054 3F CC53 2017 2017-03-06 DO 1.5789787049 #> 6572 2054 3F CC53 2017 2017-03-06 DOSAT 4.0145795938 + #> 6573 2054 3F CC53 2017 2017-03-06 NO23 -2.5770219387 #> 6574 2054 3F CC53 2017 2017-03-06 SALIN 1.4445632692 #> 6575 2054 3F CC53 2017 2017-03-06 TKN -0.3856624808 #> 6576 2054 3F CC53 2017 2017-03-06 TN -0.2797139028 + #> 6577 2054 3F CC53 2017 2017-03-06 TP -1.6094379124 #> 6578 2054 3F CC53 2017 2017-03-06 TURB 0.9932517730 #> 6579 2054 3F CC53 2017 2017-04-03 CHLAC 2.0149030205 #> 6580 2054 3F CC53 2017 2017-04-03 COLOR 3.8286413965 #> 6581 2054 3F CC53 2017 2017-04-03 DO 1.0612565021 #> 6582 2054 3F CC53 2017 2017-04-03 DOSAT 3.6163087613 + #> 6583 2054 3F CC53 2017 2017-04-03 NO23 -3.4112477175 #> 6584 2054 3F CC53 2017 2017-04-03 SALIN 2.1610215287 #> 6585 2054 3F CC53 2017 2017-04-03 TKN -0.0725706928 #> 6586 2054 3F CC53 2017 2017-04-03 TN -0.0377018672 + #> 6587 2054 3F CC53 2017 2017-04-03 TP -1.4271163556 #> 6588 2054 3F CC53 2017 2017-04-03 TURB 1.0296194172 A #> 6589 2054 3F CC53 2017 2017-05-01 CHLAC 2.2512917986 #> 6590 2054 3F CC53 2017 2017-05-01 COLOR 4.0253516907 A #> 6591 2054 3F CC53 2017 2017-05-01 DO 1.1817271954 #> 6592 2054 3F CC53 2017 2017-05-01 DOSAT 3.7796338174 + #> 6593 2054 3F CC53 2017 2017-05-01 NO23 -4.7105307016 I #> 6594 2054 3F CC53 2017 2017-05-01 SALIN 2.6049094422 #> 6595 2054 3F CC53 2017 2017-05-01 TKN 0.5306282511 #> 6596 2054 3F CC53 2017 2017-05-01 TN 0.5329784284 + #> 6597 2054 3F CC53 2017 2017-05-01 TP -1.5141277326 #> 6598 2054 3F CC53 2017 2017-05-01 TURB 0.7884573604 #> 6599 2054 3F CC53 2017 2017-06-05 COLOR 4.0430512678 A #> 6600 2054 3F CC53 2017 2017-06-05 NO23 -4.0173835211 #> 6601 2054 3F CC53 2017 2017-06-05 TKN 0.0000000000 #> 6602 2054 3F CC53 2017 2017-06-05 TN 0.0178399181 + #> 6603 2054 3F CC53 2017 2017-06-05 TP -1.2378743560 #> 6604 2054 3F CC53 2017 2017-07-10 CHLAC 1.0986122887 #> 6605 2054 3F CC53 2017 2017-07-10 COLOR 5.2983173665 #> 6606 2054 3F CC53 2017 2017-07-10 DO 0.8020015855 #> 6607 2054 3F CC53 2017 2017-07-10 DOSAT 3.3707381742 + #> 6608 2054 3F CC53 2017 2017-07-10 NO23 -1.9661128564 #> 6609 2054 3F CC53 2017 2017-07-10 SALIN -1.2378743560 #> 6610 2054 3F CC53 2017 2017-07-10 TKN 0.3364722366 #> 6611 2054 3F CC53 2017 2017-07-10 TN 0.4317824164 + #> 6612 2054 3F CC53 2017 2017-07-10 TP -1.4696759701 #> 6613 2054 3F CC53 2017 2017-07-10 TURB 1.1939224685 #> 6614 2054 3F CC53 2017 2017-11-06 CHLAC 1.8870696490 #> 6615 2054 3F CC53 2017 2017-11-06 COLOR 4.9416424226 #> 6616 2054 3F CC53 2017 2017-11-06 DO 1.5973653312 #> 6617 2054 3F CC53 2017 2017-11-06 DOSAT 4.0621656639 #> 6618 2054 3F CC53 2017 2017-11-06 NO23 -1.3470736480 #> 6619 2054 3F CC53 2017 2017-11-06 SALIN -1.4696759701 #> 6620 2054 3F CC53 2017 2017-11-06 TKN 0.0953101798 #> 6621 2054 3F CC53 2017 2017-11-06 TN 0.3074846997 + #> 6622 2054 3F CC53 2017 2017-11-06 TP -2.0402208285 #> 6623 2054 3F CC53 2017 2017-11-06 TURB 1.3609765531 #> 6624 2054 3F CC53 2017 2017-12-04 CHLAC 2.7080502011 #> 6625 2054 3F CC53 2017 2017-12-04 COLOR 4.2341065046 #> 6626 2054 3F CC53 2017 2017-12-04 DO 1.7422190237 #> 6627 2054 3F CC53 2017 2017-12-04 DOSAT 4.1759245492 #> 6628 2054 3F CC53 2017 2017-12-04 NO23 -1.6094379124 #> 6629 2054 3F CC53 2017 2017-12-04 SALIN -0.7133498879 #> 6630 2054 3F CC53 2017 2017-12-04 TKN -0.0202027073 #> 6631 2054 3F CC53 2017 2017-12-04 TN 0.1655144385 + #> 6632 2054 3F CC53 2017 2017-12-04 TP -2.0402208285 #> 6633 2054 3F CC53 2017 2017-12-04 TURB 1.2809338455 A #> 6634 2054 3F CC53 2018 2018-01-02 CHLAC 3.2188758249 #> 6635 2054 3F CC53 2018 2018-01-02 COLOR 4.0253516907 #> 6636 2054 3F CC53 2018 2018-01-02 DO 1.7298840655 #> 6637 2054 3F CC53 2018 2018-01-02 DOSAT 4.0758410907 + #> 6638 2054 3F CC53 2018 2018-01-02 NO23 -2.0402208285 #> 6639 2054 3F CC53 2018 2018-01-02 SALIN -0.8915981193 #> 6640 2054 3F CC53 2018 2018-01-02 TKN 0.0000000000 #> 6641 2054 3F CC53 2018 2018-01-02 TN 0.1222176327 + #> 6642 2054 3F CC53 2018 2018-01-02 TP -1.9661128564 #> 6643 2054 3F CC53 2018 2018-01-02 TURB 1.8245492921 #> 6644 2054 3F CC53 2018 2018-02-05 CHLAC 3.5263605246 #> 6645 2054 3F CC53 2018 2018-02-05 COLOR 4.2484952420 #> 6646 2054 3F CC53 2018 2018-02-05 DO 1.9712993831 #> 6647 2054 3F CC53 2018 2018-02-05 DOSAT 4.3681812279 #> 6648 2054 3F CC53 2018 2018-02-05 NO23 -0.9416085399 #> 6649 2054 3F CC53 2018 2018-02-05 SALIN -0.9416085399 #> 6650 2054 3F CC53 2018 2018-02-05 TKN 0.1823215568 #> 6651 2054 3F CC53 2018 2018-02-05 TN 0.4637340162 + #> 6652 2054 3F CC53 2018 2018-02-05 TP -1.7719568419 #> 6653 2054 3F CC53 2018 2018-02-05 TURB 1.8870696490 #> 6654 2054 3F CC53 2018 2018-05-07 CHLAC 2.6390573296 #> 6655 2054 3F CC53 2018 2018-05-07 COLOR 3.9318256327 #> 6656 2054 3F CC53 2018 2018-05-07 DO 1.3217558400 #> 6657 2054 3F CC53 2018 2018-05-07 DOSAT 3.8877303129 #> 6658 2054 3F CC53 2018 2018-05-07 NO23 -5.1159958098 I #> 6659 2054 3F CC53 2018 2018-05-07 SALIN 1.9974177062 #> 6660 2054 3F CC53 2018 2018-05-07 TKN -0.0100503359 #> 6661 2054 3F CC53 2018 2018-05-07 TN -0.0060180723 + #> 6662 2054 3F CC53 2018 2018-05-07 TP -1.3862943611 #> 6663 2054 3F CC53 2018 2018-05-07 TURB 1.1939224685 #> 6664 2054 3F CC53 2018 2018-07-09 CHLAC 0.9162907319 #> 6665 2054 3F CC53 2018 2018-07-09 COLOR 5.0106352941 #> 6666 2054 3F CC53 2018 2018-07-09 DO 1.3532545070 #> 6667 2054 3F CC53 2018 2018-07-09 DOSAT 3.9435216725 #> 6668 2054 3F CC53 2018 2018-07-09 NO23 -4.3428059215 #> 6669 2054 3F CC53 2018 2018-07-09 SALIN -3.2188758249 #> 6670 2054 3F CC53 2018 2018-07-09 TKN 0.0953101798 #> 6671 2054 3F CC53 2018 2018-07-09 TN 0.1070590723 + #> 6672 2054 3F CC53 2018 2018-07-09 TP -2.5510464523 #> 6673 2054 3F CC53 2018 2018-07-09 TURB 0.9555114450 #> 6674 2054 3F CC53 2019 2019-02-04 CHLAC 1.2527629685 #> 6675 2054 3F 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2019 2019-03-04 TURB 2.0918640617 #> 6694 2054 3F CC53 2019 2019-04-01 CHLAC 2.0794415417 #> 6695 2054 3F CC53 2019 2019-04-01 COLOR 4.1896547420 #> 6696 2054 3F CC53 2019 2019-04-01 DO 1.6074359098 #> 6697 2054 3F CC53 2019 2019-04-01 DOSAT 4.0775374439 #> 6698 2054 3F CC53 2019 2019-04-01 NO23 -4.8283137373 I #> 6699 2054 3F CC53 2019 2019-04-01 SALIN -0.9675840263 #> 6700 2054 3F CC53 2019 2019-04-01 TKN 0.0000000000 #> 6701 2054 3F CC53 2019 2019-04-01 TN 0.0039920213 + #> 6702 2054 3F CC53 2019 2019-04-01 TP -2.3434070875 #> 6703 2054 3F CC53 2019 2019-04-01 TURB 1.0986122887 #> 6704 2054 3F CC53 2019 2019-05-06 CHLAC 2.1400661635 #> 6705 2054 3F CC53 2019 2019-05-06 COLOR 4.2046926194 A #> 6706 2054 3F CC53 2019 2019-05-06 DO 1.4182774070 #> 6707 2054 3F CC53 2019 2019-05-06 DOSAT 3.9608131696 #> 6708 2054 3F CC53 2019 2019-05-06 NO23 -4.8283137373 I #> 6709 2054 3F CC53 2019 2019-05-06 SALIN 0.7371640660 #> 6710 2054 3F CC53 2019 2019-05-06 TKN 0.0953101798 #> 6711 2054 3F CC53 2019 2019-05-06 TN 0.0989399479 + #> 6712 2054 3F CC53 2019 2019-05-06 TP -1.8325814637 #> 6713 2054 3F CC53 2019 2019-05-06 TURB 1.0647107370 #> 6714 2054 3F CC53 2019 2019-08-05 CHLAC 0.4700036292 I #> 6715 2054 3F CC53 2019 2019-08-05 COLOR 5.3936275464 #> 6716 2054 3F CC53 2019 2019-08-05 DO 1.2383742310 #> 6717 2054 3F CC53 2019 2019-08-05 DOSAT 3.7750571504 #> 6718 2054 3F CC53 2019 2019-08-05 NO23 -2.3859667019 #> 6719 2054 3F CC53 2019 2019-08-05 SALIN -1.7719568419 #> 6720 2054 3F CC53 2019 2019-08-05 TKN 0.4700036292 #> 6721 2054 3F CC53 2019 2019-08-05 TN 0.5259112612 + #> 6722 2054 3F CC53 2019 2019-08-05 TP -1.3862943611 #> 6723 2054 3F CC53 2019 2019-08-05 TURB 0.9162907319 #> 6724 2054 3F CC53 2020 2020-01-06 CHLAC 1.8405496334 #> 6725 2054 3F CC53 2020 2020-01-06 COLOR 3.8712010109 A #> 6726 2054 3F CC53 2020 2020-01-06 DO 1.7439688054 #> 6727 2054 3F CC53 2020 2020-01-06 DOSAT 4.1255201797 #> 6728 2054 3F CC53 2020 2020-01-06 NO23 -2.8824035882 #> 6729 2054 3F CC53 2020 2020-01-06 SALIN -0.5276327421 #> 6730 2054 3F CC53 2020 2020-01-06 TKN -0.4155154440 #> 6731 2054 3F CC53 2020 2020-01-06 TN -0.3340751120 + #> 6732 2054 3F CC53 2020 2020-01-06 TP -2.3644604967 #> 6733 2054 3F CC53 2020 2020-01-06 TURB 0.7884573604 #> 6734 2054 3F CC53 2020 2020-02-03 CHLAC 1.6292405397 #> 6735 2054 3F CC53 2020 2020-02-03 COLOR 3.7612001157 #> 6736 2054 3F CC53 2020 2020-02-03 DO 1.6808279085 #> 6737 2054 3F CC53 2020 2020-02-03 DOSAT 4.0395363257 #> 6738 2054 3F CC53 2020 2020-02-03 NO23 -2.6450754019 #> 6739 2054 3F CC53 2020 2020-02-03 SALIN -0.1053605157 #> 6740 2054 3F CC53 2020 2020-02-03 TKN -0.2613647641 #> 6741 2054 3F CC53 2020 2020-02-03 TN -0.1731636190 + #> 6742 2054 3F CC53 2020 2020-02-03 TP -2.2072749132 #> 6743 2054 3F CC53 2020 2020-02-03 TURB 0.7419373447 #> 6744 2054 3F CC53 2020 2020-03-02 CHLAC 2.7080502011 #> 6745 2054 3F CC53 2020 2020-03-02 COLOR 3.8501476017 #> 6746 2054 3F CC53 2020 2020-03-02 DO 1.9657127764 #> 6747 2054 3F CC53 2020 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2020-12-07 COLOR 4.7874917428 #> 6766 2054 3F CC53 2020 2020-12-07 DO 1.9344157696 #> 6767 2054 3F CC53 2020 2020-12-07 DOSAT 4.3280982926 #> 6768 2054 3F CC53 2020 2020-12-07 NO23 -1.8971199849 #> 6769 2054 3F CC53 2020 2020-12-07 SALIN -1.3470736480 #> 6770 2054 3F CC53 2020 2020-12-07 TKN 0.1823215568 #> 6771 2054 3F CC53 2020 2020-12-07 TN 0.3001045925 + #> 6772 2054 3F CC53 2020 2020-12-07 TP -2.0402208285 #> 6773 2054 3F CC53 2020 2020-12-07 TURB 0.8754687374 #> 6774 2054 3F CC53 2021 2021-01-04 CHLAC 1.6863989536 #> 6775 2054 3F CC53 2021 2021-01-04 COLOR 4.4773368145 A #> 6776 2054 3F CC53 2021 2021-01-04 DO 1.7766458314 #> 6777 2054 3F CC53 2021 2021-01-04 DOSAT 4.1866198383 #> 6778 2054 3F CC53 2021 2021-01-04 NO23 -2.2072749132 #> 6779 2054 3F CC53 2021 2021-01-04 SALIN -1.3470736480 #> 6780 2054 3F CC53 2021 2021-01-04 TN 0.1906203596 + #> 6781 2054 3F CC53 2021 2021-01-04 TP -2.3025850930 #> 6782 2054 3F CC53 2021 2021-01-04 TURB 0.9932517730 #> 6783 2054 3F CC53 2021 2021-02-01 CHLAC 2.6390573296 #> 6784 2054 3F CC53 2021 2021-02-01 COLOR 4.2046926194 A #> 6785 2054 3F CC53 2021 2021-02-01 DO 1.8779371655 #> 6786 2054 3F CC53 2021 2021-02-01 DOSAT 4.2822062994 #> 6787 2054 3F CC53 2021 2021-02-01 NO23 -5.5214609179 U #> 6788 2054 3F CC53 2021 2021-02-01 SALIN 0.1739533071 #> 6789 2054 3F CC53 2021 2021-02-01 TKN -0.0408219945 #> 6790 2054 3F CC53 2021 2021-02-01 TN -0.0387408283 + #> 6791 2054 3F CC53 2021 2021-02-01 TP -2.0402208285 #> 6792 2054 3F CC53 2021 2021-02-01 TURB 1.4350845253 A #> 6793 2054 3F CC53 2021 2021-03-01 CHLAC 2.6390573296 #> 6794 2054 3F CC53 2021 2021-03-01 COLOR 4.0604430105 #> 6795 2054 3F CC53 2021 2021-03-01 DO 1.7369512327 #> 6796 2054 3F CC53 2021 2021-03-01 DOSAT 4.2239097666 #> 6797 2054 3F CC53 2021 2021-03-01 NO23 -5.5214609179 U #> 6798 2054 3F CC53 2021 2021-03-01 SALIN -0.5108256238 #> 6799 2054 3F CC53 2021 2021-03-01 TKN 0.0953101798 #> 6800 2054 3F CC53 2021 2021-03-01 TN 0.0971267107 + #> 6801 2054 3F CC53 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2021-10-04 NO23 -2.9004220937 #> 6856 2054 3F CC53 2021 2021-10-04 SALIN -2.0402208285 #> 6857 2054 3F CC53 2021 2021-10-04 TKN -0.0725706928 #> 6858 2054 3F CC53 2021 2021-10-04 TN -0.0151136378 + #> 6859 2054 3F CC53 2021 2021-10-04 TP -1.7719568419 #> 6860 2054 3F CC53 2021 2021-10-04 TURB 0.7419373447 A #> 6861 2054 3F CC53 2021 2021-11-01 CHLAC 2.1282317058 #> 6862 2054 3F CC53 2021 2021-11-01 COLOR 4.2766661190 #> 6863 2054 3F CC53 2021 2021-11-01 DO 1.0681530812 #> 6864 2054 3F CC53 2021 2021-11-01 DOSAT 3.5322256441 #> 6865 2054 3F CC53 2021 2021-11-01 NO23 -2.6450754019 #> 6866 2054 3F CC53 2021 2021-11-01 SALIN -1.4696759701 #> 6867 2054 3F CC53 2021 2021-11-01 TKN -0.0304592075 #> 6868 2054 3F CC53 2021 2021-11-01 TN 0.0401817896 + #> 6869 2054 3F CC53 2021 2021-11-01 TP -1.8971199849 #> 6870 2054 3F CC53 2021 2021-11-01 TURB 0.5306282511 #> 6871 2054 3F CC53 2021 2021-12-06 CHLAC 2.1282317058 #> 6872 2054 3F CC53 2021 2021-12-06 COLOR 4.3174881135 #> 6873 2054 3F CC53 2021 2021-12-06 NO23 -2.9957322736 #> 6874 2054 3F CC53 2021 2021-12-06 TKN 0.0953101798 #> 6875 2054 3F CC53 2021 2021-12-06 TN 0.1397619424 + #> 6876 2054 3F CC53 2021 2021-12-06 TP -2.3025850930 #> 6877 2054 3F CC53 2021 2021-12-06 TURB 0.7419373447 #> 6878 2054 3F CC53 2022 2022-01-03 CHLAC 1.2527629685 #> 6879 2054 3F CC53 2022 2022-01-03 COLOR 4.0943445622 A #> 6880 2054 3F CC53 2022 2022-01-03 DO 1.3402504226 #> 6881 2054 3F CC53 2022 2022-01-03 DOSAT 3.8286413965 #> 6882 2054 3F CC53 2022 2022-01-03 NO23 -4.1997050779 #> 6883 2054 3F CC53 2022 2022-01-03 SALIN 1.3376291891 #> 6884 2054 3F CC53 2022 2022-01-03 TKN -0.1053605157 #> 6885 2054 3F CC53 2022 2022-01-03 TN -0.0888312137 + #> 6886 2054 3F CC53 2022 2022-01-03 TP -1.7719568419 #> 6887 2054 3F CC53 2022 2022-01-03 TURB 0.6418538862 #> 6888 2054 3F CC53 2022 2022-02-07 CHLAC 2.2082744135 #> 6889 2054 3F CC53 2022 2022-02-07 COLOR 3.8286413965 #> 6890 2054 3F CC53 2022 2022-02-07 DO 1.7047480922 #> 6891 2054 3F CC53 2022 2022-02-07 DOSAT 4.1541845626 #> 6892 2054 3F CC53 2022 2022-02-07 NO23 -4.9618451299 I #> 6893 2054 3F CC53 2022 2022-02-07 SALIN 1.3270750015 #> 6894 2054 3F CC53 2022 2022-02-07 TKN -0.1863295782 #> 6895 2054 3F CC53 2022 2022-02-07 TN -0.1815218766 + #> 6896 2054 3F CC53 2022 2022-02-07 TP -1.8325814637 #> 6897 2054 3F CC53 2022 2022-02-07 TURB 1.2237754316 #> 6898 2054 3F CC53 2022 2022-03-07 CHLAC 2.3025850930 #> 6899 2054 3F CC53 2022 2022-03-07 COLOR 3.8066624898 A #> 6900 2054 3F CC53 2022 2022-03-07 NO23 -5.2983173665 I #> 6901 2054 3F CC53 2022 2022-03-07 TKN -0.1278333715 #> 6902 2054 3F CC53 2022 2022-03-07 TN -0.1232982163 + #> 6903 2054 3F CC53 2022 2022-03-07 TP -1.6094379124 #> 6904 2054 3F CC53 2022 2022-03-07 TURB 1.0296194172 #> 6905 2054 3F CC53 2022 2022-04-04 CHLAC 2.7725887222 #> 6906 2054 3F CC53 2022 2022-04-04 COLOR 3.9702919136 A #> 6907 2054 3F CC53 2022 2022-04-04 DO 1.1908875648 #> 6908 2054 3F CC53 2022 2022-04-04 DOSAT 3.7208625000 #> 6909 2054 3F CC53 2022 2022-04-04 NO23 -4.1997050779 #> 6910 2054 3F CC53 2022 2022-04-04 SALIN 2.1860512767 #> 6911 2054 3F CC53 2022 2022-04-04 TKN -0.3147107448 #> 6912 2054 3F CC53 2022 2022-04-04 TN -0.2943710606 + #> 6913 2054 3F CC53 2022 2022-04-04 TP -1.2378743560 #> 6914 2054 3F CC53 2022 2022-04-04 TURB 1.0296194172 #> 6915 2054 3F CC53 2022 2022-05-02 CHLAC 2.4849066498 #> 6916 2054 3F CC53 2022 2022-05-02 COLOR 4.0073331852 #> 6917 2054 3F CC53 2022 2022-05-02 NO23 -3.9120230054 #> 6918 2054 3F CC53 2022 2022-05-02 SALIN 2.5152741864 #> 6919 2054 3F CC53 2022 2022-05-02 TKN 0.0953101798 #> 6920 2054 3F CC53 2022 2022-05-02 TN 0.1133286853 + #> 6921 2054 3F CC53 2022 2022-05-02 TP -1.1394342832 #> 6922 2054 3F CC53 2022 2022-05-02 TURB 1.0986122887 #> 6923 2054 3F CC53 2022 2022-12-05 CHLAC 1.6094379124 #> 6924 2054 3F CC53 2022 2022-12-05 COLOR 4.7004803658 #> 6925 2054 3F CC53 2022 2022-12-05 NO23 -1.4696759701 #> 6926 2054 3F CC53 2022 2022-12-05 SALIN -1.3862943611 #> 6927 2054 3F CC53 2022 2022-12-05 TKN -0.0833816089 #> 6928 2054 3F CC53 2022 2022-12-05 TN 0.1397619424 + #> 6929 2054 3F CC53 2022 2022-12-05 TP -1.8971199849 #> 6930 2054 3F CC53 2022 2022-12-05 TURB 1.3350010667 #> 6931 2054 3F CC53 2023 2023-01-03 CHLAC 2.3978952728 #> 6932 2054 3F CC53 2023 2023-01-03 COLOR 4.2484952420 A #> 6933 2054 3F CC53 2023 2023-01-03 DO 2.1090003439 #> 6934 2054 3F CC53 2023 2023-01-03 DOSAT 4.5261269786 #> 6935 2054 3F CC53 2023 2023-01-03 NO23 -1.4271163556 #> 6936 2054 3F CC53 2023 2023-01-03 SALIN -1.1086626245 #> 6937 2054 3F CC53 2023 2023-01-03 TKN -0.1625189295 #> 6938 2054 3F CC53 2023 2023-01-03 TN 0.0861776962 + #> 6939 2054 3F CC53 2023 2023-01-03 TP -2.3025850930 #> 6940 2054 3F CC53 2023 2023-01-03 TURB 0.7884573604 #> 6941 2054 3F CC53 2023 2023-02-06 CHLAC 3.4965075615 #> 6942 2054 3F CC53 2023 2023-02-06 COLOR 4.0253516907 #> 6943 2054 3F CC53 2023 2023-02-06 DO 1.9740810260 #> 6944 2054 3F CC53 2023 2023-02-06 DOSAT 4.3919769655 #> 6945 2054 3F CC53 2023 2023-02-06 NO23 -5.2983173665 I #> 6946 2054 3F CC53 2023 2023-02-06 SALIN -0.4780358009 #> 6947 2054 3F CC53 2023 2023-02-06 TKN 0.0953101798 #> 6948 2054 3F CC53 2023 2023-02-06 TN 0.0989399479 + #> 6949 2054 3F CC53 2023 2023-02-06 TP -1.8325814637 #> 6950 2054 3F CC53 2023 2023-02-06 TURB 1.6863989536 #> 6951 2054 3F CC53 2023 2023-03-06 DO 1.5623463049 #> 6952 2054 3F CC53 2023 2023-03-06 DOSAT 4.0253516907 #> 6953 2054 3F CC53 2023 2023-03-06 SALIN 0.8501509294 #> 6954 2054 3F CC53 2014 2014-04-07 CHLAC 1.0986122887 #> 6955 2054 3F CC53 2014 2014-04-07 COLOR 5.0751738152 #> 6956 2054 3F CC53 2014 2014-04-07 COND 7.1701195434 #> 6957 2054 3F CC53 2014 2014-04-07 DO 1.7029282555 #> 6958 2054 3F CC53 2014 2014-04-07 DOSAT 4.0976723523 #> 6959 2054 3F CC53 2014 2014-04-07 NO23 -3.1700856607 #> 6960 2054 3F CC53 2014 2014-04-07 SALIN -0.3566749439 + #> 6961 2054 3F CC53 2014 2014-04-07 TKN 0.6418538862 #> 6962 2054 3F CC53 2014 2014-04-07 TN 0.6637183699 + #> 6963 2054 3F CC53 2014 2014-04-07 TP 0.0953101798 #> 6964 2054 3F CC53 2014 2014-04-07 TSS 2.9444389792 #> 6965 2054 3F CC53 2014 2014-04-07 TURB 2.7725887222 #> 6966 2054 3F CC53 2015 2015-05-21 COND 7.9291264873 #> 6967 2054 3F CC53 2015 2015-05-21 DO 1.4109869737 #> 6968 2054 3F CC53 2015 2015-05-21 DOSAT 3.9702919136 #> 6969 2054 3F CC53 2015 2015-05-21 SALIN 0.2851789422 + #> 6970 2054 3F CC53 2015 2015-07-15 COND 6.5439118456 #> 6971 2054 3F CC53 2015 2015-07-15 COND 6.5453496603 #> 6972 2054 3F CC53 2015 2015-07-15 SALIN -1.1711829815 + #> 6973 2054 3F CC53 2015 2015-08-06 COND 4.9052747784 #> 6974 2054 3F CC53 2015 2015-08-06 DO 1.4109869737 #> 6975 2054 3F CC53 2015 2015-08-06 DOSAT 3.9702919136 #> 6976 2054 3F CC53 2015 2015-08-19 COND 4.8751973232 #> 6977 2054 3F CC53 2015 2015-08-19 DO 1.2527629685 #> 6978 2054 3F CC53 2015 2015-08-19 DOSAT 3.8501476017 #> 6979 2054 3F CC53 2015 2015-09-15 COND 5.4764635519 #> 6980 2054 3F CC53 2015 2015-09-15 DO 1.1314021115 #> 6981 2054 3F CC53 2015 2015-09-15 DOSAT 3.6888794541 #> 6982 2054 3F CC53 2015 2015-09-15 SALIN -2.2072749132 + #> 6983 2054 3F CC53 2015 2015-09-15 COND 5.4764635519 #> 6984 2054 3F CC53 2015 2015-09-15 DO 1.0986122887 #> 6985 2054 3F CC53 2015 2015-09-15 DOSAT 3.6635616461 #> 6986 2054 3F CC53 2015 2015-09-15 SALIN -2.2072749132 + #> 6987 2054 3F CC53 2015 2015-11-25 COND 6.2225762681 #> 6988 2054 3F CC53 2015 2015-11-25 DO 1.7047480922 #> 6989 2054 3F CC53 2015 2015-11-25 DOSAT 4.1431347264 #> 6990 2054 3F CC53 2015 2015-11-25 SALIN -1.3470736480 + #> 6991 2054 3F CC53 2015 2015-11-25 COND 6.2285110036 #> 6992 2054 3F CC53 2015 2015-11-25 DO 1.6863989536 #> 6993 2054 3F CC53 2015 2015-11-25 DOSAT 4.1431347264 #> 6994 2054 3F CC53 2015 2015-11-25 SALIN -1.3470736480 + #> 6995 2054 3F CC53 2021 2021-02-02 COND 7.0184017991 #> 6996 2054 3F CC53 2021 2021-02-02 DO 1.9183921202 #> 6997 2054 3F CC53 2021 2021-02-02 DOSAT 4.2822062994 #> 6998 2054 3F CC53 2021 2021-02-02 SALIN -0.5798184953 #> 6999 2054 3F CC53 2021 2021-03-16 COND 7.8504931809 #> 7000 2054 3F CC53 2021 2021-03-16 DO 1.7783364489 #> 7001 2054 3F CC53 2021 2021-03-16 DOSAT 4.2527717988 #> 7002 2054 3F CC53 2021 2021-03-16 SALIN 0.2776317366 #> 7003 2054 3F CC53 2021 2021-09-30 COND 4.8880909413 #> 7004 2054 3F CC53 2021 2021-09-30 DO 1.3532545070 #> 7005 2054 3F CC53 2021 2021-09-30 DOSAT 3.8774315607 #> 7006 2054 3F CC53 2021 2021-09-30 SALIN -2.8134107168 #> 7007 2054 3F CC53 2021 2021-09-30 COND 4.8797670189 #> 7008 2054 3F CC53 2021 2021-09-30 DO 1.2412685891 #> 7009 2054 3F CC53 2021 2021-09-30 DOSAT 3.7750571504 #> 7010 2054 3F CC53 2021 2021-09-30 SALIN -2.8134107168 #> 7011 2054 3F CC53 2021 2021-10-27 COND 6.5250296578 #> 7012 2054 3F CC53 2021 2021-10-27 DO 1.5195132049 #> 7013 2054 3F CC53 2021 2021-10-27 DOSAT 4.0412953411 #> 7014 2054 3F CC53 2021 2021-10-27 SALIN -1.1086626245 #> 7015 2054 3F CC53 2021 2021-10-27 COND 6.5264948596 #> 7016 2054 3F CC53 2021 2021-10-27 DO 1.5129270121 #> 7017 2054 3F CC53 2021 2021-10-27 DOSAT 4.0342406382 #> 7018 2054 3F CC53 2021 2021-10-27 SALIN -1.1086626245 #> 7019 2054 3F CC53 2021 2021-11-18 COND 4.7104306966 #> 7020 2054 3F CC53 2021 2021-11-18 DO 1.8578592709 #> 7021 2054 3F CC53 2021 2021-11-18 DOSAT 4.2682978693 #> 7022 2054 3F CC53 2021 2021-11-18 SALIN -2.9957322736 #> 7023 2059 3M CC55 2015 2015-05-21 COND 9.9007337643 #> 7024 2059 3M CC55 2015 2015-05-21 DO 1.2237754316 #> 7025 2059 3M CC55 2015 2015-05-21 DOSAT 3.8286413965 #> 7026 2059 3M CC55 2015 2015-05-21 SALIN 2.4105422345 + #> 7027 2059 3M CC55 2015 2015-07-15 COND 6.7190131544 #> 7028 2059 3M CC55 2015 2015-07-15 SALIN -0.9416085399 + #> 7029 2059 3M CC55 2015 2015-08-06 COND 6.4019171967 #> 7030 2059 3M CC55 2015 2015-08-06 DO 1.6292405397 #> 7031 2059 3M CC55 2015 2015-08-06 DOSAT 4.1896547420 #> 7032 2059 3M CC55 2015 2015-08-06 SALIN -1.3093333200 + #> 7033 2059 3M CC55 2015 2015-08-19 COND 6.2785214242 #> 7034 2059 3M CC55 2015 2015-08-19 DO 1.6094379124 #> 7035 2059 3M CC55 2015 2015-08-19 DOSAT 4.1431347264 #> 7036 2059 3M CC55 2015 2015-08-19 SALIN -1.3862943611 + #> 7037 2059 3M CC55 2015 2015-09-15 COND 6.2205901701 #> 7038 2059 3M CC55 2015 2015-09-15 DO 1.4816045409 #> 7039 2059 3M CC55 2015 2015-09-15 DOSAT 4.0073331852 #> 7040 2059 3M CC55 2015 2015-09-15 SALIN -1.4271163556 + #> 7041 2059 3M CC55 2015 2015-10-08 CHLAC 0.2623642645 I #> 7042 2059 3M CC55 2015 2015-10-08 COND 6.3969296552 #> 7043 2059 3M CC55 2015 2015-10-08 DO 1.6486586256 #> 7044 2059 3M CC55 2015 2015-10-08 DOSAT 4.2046926194 #> 7045 2059 3M CC55 2015 2015-10-08 NO23 -2.7646205526 #> 7046 2059 3M CC55 2015 2015-10-08 SALIN -1.2378743560 + #> 7047 2059 3M CC55 2015 2015-10-08 TKN -0.1625189295 #> 7048 2059 3M CC55 2015 2015-10-08 TN -0.0910193984 + #> 7049 2059 3M CC55 2015 2015-10-08 TP -2.6310891600 #> 7050 2059 3M CC55 2015 2015-10-08 TSS 1.9459101491 I #> 7051 2059 3M CC55 2015 2015-10-08 TURB 2.0794415417 #> 7052 2059 3M CC55 2015 2015-11-05 CHLAC 0.5877866649 #> 7053 2059 3M CC55 2015 2015-11-05 COND 6.6982680541 #> 7054 2059 3M CC55 2015 2015-11-05 DO 1.9600947840 #> 7055 2059 3M CC55 2015 2015-11-05 DOSAT 4.4773368145 #> 7056 2059 3M CC55 2015 2015-11-05 SALIN -0.9416085399 + #> 7057 2059 3M CC55 2015 2015-11-05 TN -0.0693500781 + #> 7058 2059 3M CC55 2015 2015-11-05 TSS 1.7917594692 I #> 7059 2059 3M CC55 2015 2015-11-05 TURB 2.2721258855 #> 7060 2059 3M CC55 2015 2015-11-25 COND 6.7007311095 #> 7061 2059 3M CC55 2015 2015-11-25 DO 2.0014800002 #> 7062 2059 3M CC55 2015 2015-11-25 DOSAT 4.4188406078 #> 7063 2059 3M CC55 2015 2015-11-25 SALIN -0.8209805521 + #> 7064 2059 3M CC55 2015 2015-12-03 CHLAC 0.5306282511 #> 7065 2059 3M CC55 2015 2015-12-03 COLOR 4.7004803658 #> 7066 2059 3M CC55 2015 2015-12-03 COND 6.8448154792 #> 7067 2059 3M CC55 2015 2015-12-03 DO 1.8900953699 #> 7068 2059 3M CC55 2015 2015-12-03 DOSAT 4.3694478525 #> 7069 2059 3M CC55 2015 2015-12-03 NO23 -2.7488721956 #> 7070 2059 3M CC55 2015 2015-12-03 SALIN -0.7550225843 + #> 7071 2059 3M CC55 2015 2015-12-03 TKN -0.2357223335 #> 7072 2059 3M CC55 2015 2015-12-03 TN -0.1578240852 + #> 7073 2059 3M CC55 2015 2015-12-03 TP -2.8647040111 #> 7074 2059 3M CC55 2015 2015-12-03 TSS 1.3862943611 I #> 7075 2059 3M CC55 2015 2015-12-03 TURB 2.1282317058 #> 7076 2059 3M CC55 2015 2015-05-21 COND 7.3472997007 #> 7077 2059 3M CC55 2015 2015-05-21 DO 0.9932517730 #> 7078 2059 3M CC55 2015 2015-05-21 DOSAT 3.4657359028 #> 7079 2059 3M CC55 2015 2015-05-21 SALIN -0.3285040670 + #> 7080 2059 3M CC55 2015 2015-07-15 COND 9.6044074351 #> 7081 2059 3M CC55 2015 2015-08-06 COND 6.4068799861 #> 7082 2059 3M CC55 2015 2015-08-06 DO 1.6486586256 #> 7083 2059 3M CC55 2015 2015-08-06 DOSAT 4.2195077052 #> 7084 2059 3M CC55 2015 2015-08-06 SALIN -1.3093333200 + #> 7085 2059 3M CC55 2015 2015-08-19 COND 6.2653012127 #> 7086 2059 3M CC55 2015 2015-08-19 DO 1.3862943611 #> 7087 2059 3M CC55 2015 2015-08-19 DOSAT 4.0604430105 #> 7088 2059 3M CC55 2015 2015-08-19 SALIN -1.4271163556 + #> 7089 2059 3M CC55 2015 2015-09-15 COND 6.2519038832 #> 7090 2059 3M CC55 2015 2015-09-15 DO 1.6863989536 #> 7091 2059 3M CC55 2015 2015-09-15 DOSAT 4.1271343850 #> 7092 2059 3M CC55 2015 2015-09-15 SALIN -1.4271163556 + #> 7093 2059 3M CC55 2015 2015-11-25 COND 8.4348979487 #> 7094 2059 3M CC55 2015 2015-11-25 DO -0.1053605157 #> 7095 2059 3M CC55 2015 2015-11-25 DOSAT 2.3025850930 #> 7096 2059 3M CC55 2015 2015-11-25 SALIN 1.0152306797 + #> 7097 2059 3M CC56 2015 2015-05-21 COND 9.6019769721 #> 7098 2059 3M CC56 2015 2015-05-21 DO 0.6931471806 #> 7099 2059 3M CC56 2015 2015-05-21 DOSAT 3.1780538303 #> 7100 2059 3M CC56 2015 2015-05-21 SALIN 2.1459312829 + #> 7101 2059 3M CC56 2015 2015-07-15 COND 8.4859089014 #> 7102 2059 3M CC56 2015 2015-07-15 SALIN 0.9001613499 + #> 7103 2059 3M CC56 2015 2015-08-06 COND 6.3952615981 #> 7104 2059 3M CC56 2015 2015-08-06 DO 0.9932517730 #> 7105 2059 3M CC56 2015 2015-08-06 DOSAT 3.4657359028 #> 7106 2059 3M CC56 2015 2015-08-06 SALIN -1.3093333200 + #> 7107 2059 3M CC56 2015 2015-08-19 COND 6.1820849067 #> 7108 2059 3M CC56 2015 2015-08-19 DO 0.9932517730 #> 7109 2059 3M CC56 2015 2015-08-19 DOSAT 3.4965075615 #> 7110 2059 3M CC56 2015 2015-08-19 SALIN -1.5141277326 + #> 7111 2059 3M CC56 2015 2015-09-15 COND 6.2576675879 #> 7112 2059 3M CC56 2015 2015-09-15 DO 0.0953101798 #> 7113 2059 3M CC56 2015 2015-09-15 DOSAT 2.5649493575 #> 7114 2059 3M CC56 2015 2015-09-15 SALIN -1.4271163556 + #> 7115 2059 3M CC56 2015 2015-11-25 COND 7.6343372356 #> 7116 2059 3M CC56 2015 2015-11-25 DO 0.9555114450 #> 7117 2059 3M CC56 2015 2015-11-25 DOSAT 3.4011973817 #> 7118 2059 3M CC56 2015 2015-11-25 SALIN 0.1570037488 + #> 7119 2059 3M CC56 2015 2015-05-21 COND 9.9350831141 #> 7120 2059 3M CC56 2015 2015-05-21 DO 0.7884573604 #> 7121 2059 3M CC56 2015 2015-05-21 DOSAT 3.3672958300 #> 7122 2059 3M CC56 2015 2015-05-21 SALIN 2.4865719291 + #> 7123 2059 3M CC56 2015 2015-07-15 CHLAC 1.0986122887 #> 7124 2059 3M CC56 2015 2015-07-15 COND 9.6128678361 #> 7125 2059 3M CC56 2015 2015-07-15 NO23 -5.5214609179 U #> 7126 2059 3M CC56 2015 2015-07-15 SALIN 2.0881534823 + #> 7127 2059 3M CC56 2015 2015-07-15 TKN 0.2623642645 #> 7128 2059 3M CC56 2015 2015-07-15 TN 0.2639015438 + #> 7129 2059 3M CC56 2015 2015-07-15 TP -0.9416085399 #> 7130 2059 3M CC56 2015 2015-07-15 TSS 1.0986122887 U #> 7131 2059 3M CC56 2015 2015-07-15 TURB 1.3862943611 #> 7132 2059 3M CC56 2015 2015-08-06 COND 6.5366915976 #> 7133 2059 3M CC56 2015 2015-08-06 DO 0.2623642645 #> 7134 2059 3M CC56 2015 2015-08-06 DOSAT 2.7725887222 #> 7135 2059 3M CC56 2015 2015-08-06 SALIN -1.1394342832 + #> 7136 2059 3M CC56 2015 2015-08-19 CHLAC 1.0296194172 #> 7137 2059 3M CC56 2015 2015-08-19 COLOR 5.4380793089 #> 7138 2059 3M CC56 2015 2015-08-19 COND 6.4488893941 #> 7139 2059 3M CC56 2015 2015-08-19 DO 0.1823215568 #> 7140 2059 3M CC56 2015 2015-08-19 DOSAT 2.7725887222 #> 7141 2059 3M CC56 2015 2015-08-19 NO23 -5.5214609179 U #> 7142 2059 3M CC56 2015 2015-08-19 SALIN -1.2378743560 + #> 7143 2059 3M CC56 2015 2015-08-19 TKN 0.4054651081 #> 7144 2059 3M CC56 2015 2015-08-19 TN 0.4067975533 + #> 7145 2059 3M CC56 2015 2015-08-19 TP -0.0304592075 #> 7146 2059 3M CC56 2015 2015-08-19 TSS 1.7917594692 I #> 7147 2059 3M CC56 2015 2015-08-19 TURB 1.5686159179 #> 7148 2059 3M CC56 2015 2015-09-15 COND 6.8134445995 #> 7149 2059 3M CC56 2015 2015-09-15 DO 0.0000000000 #> 7150 2059 3M CC56 2015 2015-09-15 DOSAT 2.3025850930 #> 7151 2059 3M CC56 2015 2015-09-15 SALIN -0.8439700703 + #> 7152 2059 3M CC56 2015 2015-11-25 COND 7.8038433035 #> 7153 2059 3M CC56 2015 2015-11-25 DO 1.8718021769 #> 7154 2059 3M CC56 2015 2015-11-25 DOSAT 4.2626798770 #> 7155 2059 3M CC56 2015 2015-11-25 SALIN 0.3576744443 + #> 7156 2059 3M CC56 2018 2018-03-06 CHLAC 1.7917594692 #> 7157 2059 3M CC56 2018 2018-03-06 COND 9.8471817163 #> 7158 2059 3M CC56 2018 2018-03-06 DO 0.6205764877 #> 7159 2059 3M CC56 2018 2018-03-06 DOSAT 3.0445224377 #> 7160 2059 3M CC56 2018 2018-03-06 NO23 -2.6592600369 #> 7161 2059 3M CC56 2018 2018-03-06 SALIN 2.5748996883 + #> 7162 2059 3M CC56 2018 2018-03-06 TKN -0.0833816089 #> 7163 2059 3M CC56 2018 2018-03-06 TN -0.0100503359 + #> 7164 2059 3M CC56 2018 2018-03-06 TP -1.2378743560 #> 7165 2059 3M CC56 2018 2018-03-06 TSS 1.0986122887 U #> 7166 2059 3M CC56 2018 2018-03-06 TURB 0.1823215568 #> 7167 2059 3M CC56 2018 2018-03-29 CHLAC 2.1747517215 #> 7168 2059 3M CC56 2018 2018-03-29 COND 10.2506170836 #> 7169 2059 3M CC56 2018 2018-03-29 DO 1.3083328197 #> 7170 2059 3M CC56 2018 2018-03-29 DOSAT 3.8501476017 #> 7171 2059 3M CC56 2018 2018-03-29 NO23 -4.7105307016 I #> 7172 2059 3M CC56 2018 2018-03-29 SALIN 2.9156062291 + #> 7173 2059 3M CC56 2018 2018-03-29 TKN -0.2484613593 #> 7174 2059 3M CC56 2018 2018-03-29 TN -0.2433462586 + #> 7175 2059 3M CC56 2018 2018-03-29 TP -1.2039728043 #> 7176 2059 3M CC56 2018 2018-03-29 TSS 1.3862943611 I #> 7177 2059 3M CC56 2018 2018-03-29 TURB 0.8754687374 #> 7178 2059 3M CC56 2018 2018-04-12 COND 10.0096027833 #> 7179 2059 3M CC56 2018 2018-04-12 DO -0.3566749439 #> 7180 2059 3M CC56 2018 2018-04-12 DOSAT 2.0794415417 #> 7181 2059 3M CC56 2018 2018-04-12 SALIN 2.6932749155 + #> 7182 2059 3M CC56 2018 2018-04-19 CHLAC 0.0953101798 I #> 7183 2059 3M CC56 2018 2018-04-19 COND 10.2545668701 #> 7184 2059 3M CC56 2018 2018-04-19 DO 1.0260415958 #> 7185 2059 3M CC56 2018 2018-04-19 DOSAT 3.5025498759 #> 7186 2059 3M CC56 2018 2018-04-19 NO23 -4.6051701860 I #> 7187 2059 3M CC56 2018 2018-04-19 SALIN 2.9150643705 + #> 7188 2059 3M CC56 2018 2018-04-19 TKN -0.1863295782 #> 7189 2059 3M CC56 2018 2018-04-19 TN -0.1815218766 + #> 7190 2059 3M CC56 2018 2018-04-19 TP -1.0788096614 #> 7191 2059 3M CC56 2018 2018-04-19 TSS 1.3862943611 I #> 7192 2059 3M CC56 2018 2018-04-19 TURB 0.1823215568 #> 7193 2059 3M CC56 2018 2018-05-10 CHLAC 1.0296194172 #> 7194 2059 3M CC56 2018 2018-05-10 COND 10.2722540975 #> 7195 2059 3M CC56 2018 2018-05-10 DO -0.1053605157 #> 7196 2059 3M CC56 2018 2018-05-10 DOSAT 2.4849066498 #> 7197 2059 3M CC56 2018 2018-05-10 NO23 -5.5214609179 U #> 7198 2059 3M CC56 2018 2018-05-10 SALIN 2.8848007128 #> 7199 2059 3M CC56 2018 2018-05-10 TKN -0.0725706928 #> 7200 2059 3M CC56 2018 2018-05-10 TN -0.0704224643 + #> 7201 2059 3M CC56 2018 2018-05-10 TP -0.8209805521 #> 7202 2059 3M CC56 2018 2018-05-10 TSS 1.0986122887 I #> 7203 2059 3M CC56 2018 2018-05-10 TURB 0.5306282511 #> 7204 2059 3M CC56 2018 2018-06-25 CHLAC 0.6931471806 #> 7205 2059 3M CC56 2018 2018-06-25 COND 7.7536235466 #> 7206 2059 3M CC56 2018 2018-06-25 DO 1.0296194172 #> 7207 2059 3M CC56 2018 2018-06-25 DOSAT 3.2695689392 #> 7208 2059 3M CC56 2018 2018-06-25 NO23 -5.5214609179 U #> 7209 2059 3M CC56 2018 2018-06-25 SALIN 0.1397619424 + #> 7210 2059 3M CC56 2018 2018-06-25 TKN 0.2623642645 #> 7211 2059 3M CC56 2018 2018-06-25 TN 0.2639015438 + #> 7212 2059 3M CC56 2018 2018-06-25 TP -1.4696759701 #> 7213 2059 3M CC56 2018 2018-06-25 TSS 1.0986122887 I #> 7214 2059 3M CC56 2018 2018-06-25 TURB 1.3862943611 #> 7215 2059 3M CC56 2018 2018-07-17 CHLAC 0.9932517730 #> 7216 2059 3M CC56 2018 2018-07-17 COND 6.8437499490 #> 7217 2059 3M CC56 2018 2018-07-17 DO -0.1863295782 #> 7218 2059 3M CC56 2018 2018-07-17 DOSAT 2.3418058061 #> 7219 2059 3M CC56 2018 2018-07-17 NO23 -3.3524072175 #> 7220 2059 3M CC56 2018 2018-07-17 SALIN -0.8439700703 + #> 7221 2059 3M CC56 2018 2018-07-17 TKN 0.2623642645 #> 7222 2059 3M CC56 2018 2018-07-17 TN 0.2889312919 + #> 7223 2059 3M CC56 2018 2018-07-17 TP -1.3093333200 #> 7224 2059 3M CC56 2018 2018-07-17 TSS 1.0986122887 I #> 7225 2059 3M CC56 2018 2018-07-17 TURB 0.0953101798 #> 7226 2059 3M CC56 2018 2018-08-01 CHLAC 0.8754687374 #> 7227 2059 3M CC56 2018 2018-08-01 COND 6.0038870671 #> 7228 2059 3M CC56 2018 2018-08-01 DO 0.7129498079 #> 7229 2059 3M CC56 2018 2018-08-01 DOSAT 3.2580965380 #> 7230 2059 3M CC56 2018 2018-08-01 NO23 -3.6119184130 #> 7231 2059 3M CC56 2018 2018-08-01 SALIN -1.6607312068 #> 7232 2059 3M CC56 2018 2018-08-01 TKN 0.0953101798 #> 7233 2059 3M CC56 2018 2018-08-01 TN 0.1195592351 + #> 7234 2059 3M CC56 2018 2018-08-01 TP -1.7719568419 #> 7235 2059 3M CC56 2018 2018-08-01 TSS 0.6931471806 U #> 7236 2059 3M CC56 2018 2018-08-01 TURB 0.0953101798 #> 7237 2059 3M CC56 2018 2018-08-20 CHLAC 0.4054651081 I #> 7238 2059 3M CC56 2018 2018-08-20 NO23 -1.4696759701 #> 7239 2059 3M CC56 2018 2018-08-20 TKN -0.3147107448 #> 7240 2059 3M CC56 2018 2018-08-20 TN -0.0408219945 + #> 7241 2059 3M CC56 2018 2018-08-20 TP -0.9416085399 #> 7242 2059 3M CC56 2018 2018-08-20 TSS 1.0986122887 U #> 7243 2059 3M CC56 2018 2018-08-20 TURB 0.7419373447 #> 7244 2059 3M CC56 2018 2018-08-21 CHLAC 0.7419373447 #> 7245 2059 3M CC56 2018 2018-08-21 COND 5.9401712527 #> 7246 2059 3M CC56 2018 2018-08-21 DO 0.9516578757 #> 7247 2059 3M CC56 2018 2018-08-21 DOSAT 3.4436180975 #> 7248 2059 3M CC56 2018 2018-08-21 NO23 -3.7297014486 #> 7249 2059 3M CC56 2018 2018-08-21 SALIN -1.7147984281 #> 7250 2059 3M CC56 2018 2018-08-21 TKN 0.0000000000 #> 7251 2059 3M CC56 2018 2018-08-21 TN 0.0237165266 + #> 7252 2059 3M CC56 2018 2018-08-21 TP -1.8325814637 #> 7253 2059 3M CC56 2018 2018-08-21 TSS 1.0986122887 I #> 7254 2059 3M CC56 2018 2018-08-21 TURB 0.3364722366 A #> 7255 2059 3M CC56 2018 2018-09-20 CHLAC 1.5040773968 #> 7256 2059 3M CC56 2018 2018-09-20 COND 7.2661287796 #> 7257 2059 3M CC56 2018 2018-09-20 DO 0.9555114450 #> 7258 2059 3M CC56 2018 2018-09-20 DOSAT 3.5862928653 #> 7259 2059 3M CC56 2018 2018-09-20 NO23 -3.1010927892 #> 7260 2059 3M CC56 2018 2018-09-20 SALIN -0.3424903089 #> 7261 2059 3M CC56 2018 2018-09-20 TKN 0.1823215568 #> 7262 2059 3M CC56 2018 2018-09-20 TN 0.2191355299 + #> 7263 2059 3M CC56 2018 2018-09-20 TP -1.0788096614 #> 7264 2059 3M CC56 2018 2018-09-20 TSS 1.0986122887 I #> 7265 2059 3M CC56 2018 2018-09-20 TURB 0.9162907319 #> 7266 2059 3M CC56 2018 2018-10-24 CHLAC 1.1314021115 #> 7267 2059 3M CC56 2018 2018-10-24 COND 9.4323632956 #> 7268 2059 3M CC56 2018 2018-10-24 DO 0.5068176024 #> 7269 2059 3M CC56 2018 2018-10-24 DOSAT 3.0726933147 #> 7270 2059 3M CC56 2018 2018-10-24 NO23 -3.4737680745 #> 7271 2059 3M CC56 2018 2018-10-24 SALIN 1.9671123567 #> 7272 2059 3M CC56 2018 2018-10-24 TKN -0.0408219945 #> 7273 2059 3M CC56 2018 2018-10-24 TN -0.0090407447 + #> 7274 2059 3M CC56 2018 2018-10-24 TP -1.2039728043 #> 7275 2059 3M CC56 2018 2018-10-24 TSS 0.6931471806 I #> 7276 2059 3M CC56 2018 2018-10-24 TURB 1.7227665977 #> 7277 2059 3M CC56 2019 2019-01-16 CHLAC -0.1053605157 I #> 7278 2059 3M CC56 2019 2019-01-16 COND 9.0122552200 #> 7279 2059 3M CC56 2019 2019-01-16 DO 0.3852624008 #> 7280 2059 3M CC56 2019 2019-01-16 DOSAT 2.7080502011 #> 7281 2059 3M CC56 2019 2019-01-16 NO23 -2.5010360317 #> 7282 2059 3M CC56 2019 2019-01-16 SALIN 1.5216989981 #> 7283 2059 3M CC56 2019 2019-01-16 TKN -0.0618754037 #> 7284 2059 3M CC56 2019 2019-01-16 TN 0.0217614918 + #> 7285 2059 3M CC56 2019 2019-01-16 TP -1.3862943611 #> 7286 2059 3M CC56 2019 2019-01-16 TSS 0.6931471806 U #> 7287 2059 3M CC56 2019 2019-01-16 TURB 0.0000000000 #> 7288 2059 3M CC56 2019 2019-01-24 COND 9.8578100390 #> 7289 2059 3M CC56 2019 2019-01-24 DO 1.6770965609 #> 7290 2059 3M CC56 2019 2019-01-24 DOSAT 4.1588830834 #> 7291 2059 3M CC56 2019 2019-01-24 NO23 -3.2968373663 #> 7292 2059 3M CC56 2019 2019-01-24 SALIN 2.4327357775 #> 7293 2059 3M CC56 2019 2019-01-24 TKN -0.3147107448 #> 7294 2059 3M CC56 2019 2019-01-24 TN -0.2652684776 + #> 7295 2059 3M CC56 2019 2019-01-24 TP -1.3470736480 #> 7296 2059 3M CC56 2019 2019-01-24 TSS 1.0986122887 U #> 7297 2059 3M CC56 2019 2019-01-24 TURB 0.6418538862 #> 7298 2059 3M CC56 2019 2019-03-12 CHLAC 0.1823215568 I #> 7299 2059 3M CC56 2019 2019-03-12 COND 9.1291303166 #> 7300 2059 3M CC56 2019 2019-03-12 DO 0.4824261492 #> 7301 2059 3M CC56 2019 2019-03-12 DOSAT 2.9496883351 #> 7302 2059 3M CC56 2019 2019-03-12 NO23 -3.2968373663 #> 7303 2059 3M CC56 2019 2019-03-12 SALIN 1.6114359151 #> 7304 2059 3M CC56 2019 2019-03-12 TKN -0.0408219945 #> 7305 2059 3M CC56 2019 2019-03-12 TN -0.0030045090 + #> 7306 2059 3M CC56 2019 2019-03-12 TP -1.0498221245 #> 7307 2059 3M CC56 2019 2019-03-12 TSS 0.6931471806 I #> 7308 2059 3M CC56 2019 2019-03-12 TURB 0.0000000000 #> 7309 2059 3M CC56 2019 2019-04-23 CHLAC 1.1939224685 #> 7310 2059 3M CC56 2019 2019-04-23 COND 9.4766200382 #> 7311 2059 3M CC56 2019 2019-04-23 DO 0.7929925155 #> 7312 2059 3M CC56 2019 2019-04-23 DOSAT 3.3286266888 #> 7313 2059 3M CC56 2019 2019-04-23 NO23 -3.5755507688 #> 7314 2059 3M CC56 2019 2019-04-23 SALIN 2.0175661380 #> 7315 2059 3M CC56 2019 2019-04-23 TKN -0.1984509387 #> 7316 2059 3M CC56 2019 2019-04-23 TN -0.1648746432 + #> 7317 2059 3M CC56 2019 2019-04-23 TP -1.1086626245 #> 7318 2059 3M CC56 2019 2019-04-23 TSS 0.6931471806 I #> 7319 2059 3M CC56 2019 2019-04-23 TURB 0.2623642645 #> 7320 2059 3M CC56 2019 2019-06-11 CHLAC 1.8245492921 I #> 7321 2059 3M CC56 2019 2019-06-11 COND 9.8113722636 #> 7322 2059 3M CC56 2019 2019-06-11 DO 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2014 2014-06-02 COLOR 2.3978952728 #> 7521 2063 3M CC64 2014 2014-06-02 DO 1.0116009117 #> 7522 2063 3M CC64 2014 2014-06-02 DOSAT 3.7111300630 + #> 7523 2063 3M CC64 2014 2014-06-02 NO23 -5.1159958098 I #> 7524 2063 3M CC64 2014 2014-06-02 SALIN 3.3347013904 #> 7525 2063 3M CC64 2014 2014-06-02 TKN -0.4462871026 #> 7526 2063 3M CC64 2014 2014-06-02 TN -0.4400565529 + #> 7527 2063 3M CC64 2014 2014-06-02 TP -2.0402208285 #> 7528 2063 3M CC64 2014 2014-06-02 TURB 0.6931471806 #> 7529 2063 3M CC64 2014 2014-07-07 CHLAC 1.7047480922 #> 7530 2063 3M CC64 2014 2014-07-07 COLOR 3.1354942159 #> 7531 2063 3M CC64 2014 2014-07-07 DOSAT 3.7495040759 + #> 7532 2063 3M CC64 2014 2014-07-07 NO23 -4.5098600062 #> 7533 2063 3M CC64 2014 2014-07-07 SALIN 3.2611687371 #> 7534 2063 3M CC64 2014 2014-07-07 TKN -0.1863295782 #> 7535 2063 3M CC64 2014 2014-07-07 TN -0.1731636190 + #> 7536 2063 3M CC64 2014 2014-07-07 TP -2.0402208285 #> 7537 2063 3M CC64 2014 2014-07-07 TURB 0.6931471806 #> 7538 2063 3M 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2063 3M CC64 2015 2015-01-05 TKN -0.5621189182 #> 7593 2063 3M CC64 2015 2015-01-05 TN -0.4684049079 + #> 7594 2063 3M CC64 2015 2015-01-05 TP -2.3025850930 #> 7595 2063 3M CC64 2015 2015-01-05 TURB 0.6931471806 #> 7596 2063 3M CC64 2015 2015-02-02 CHLAC 0.2623642645 I #> 7597 2063 3M CC64 2015 2015-02-02 COLOR 2.3025850930 #> 7598 2063 3M CC64 2015 2015-02-02 DOSAT 4.3932138241 + #> 7599 2063 3M CC64 2015 2015-02-02 NO23 -4.3428059215 #> 7600 2063 3M CC64 2015 2015-02-02 SALIN 3.3214324132 #> 7601 2063 3M CC64 2015 2015-02-02 TKN -0.9942522733 I #> 7602 2063 3M CC64 2015 2015-02-02 TN -1.7544636845 + #> 7603 2063 3M CC64 2015 2015-02-02 TP -2.4534079827 #> 7604 2063 3M CC64 2015 2015-02-02 TURB 0.7884573604 A #> 7605 2063 3M CC64 2015 2015-03-02 CHLAC 1.1631508098 A #> 7606 2063 3M CC64 2015 2015-03-02 COLOR 2.8903717579 #> 7607 2063 3M CC64 2015 2015-03-02 DO 1.9430489168 #> 7608 2063 3M CC64 2015 2015-03-02 DOSAT 4.5152454785 + #> 7609 2063 3M CC64 2015 2015-03-02 NO23 -3.1941832123 #> 7610 2063 3M CC64 2015 2015-03-02 SALIN 3.2136622578 #> 7611 2063 3M CC64 2015 2015-03-02 TKN -0.4942963218 #> 7612 2063 3M CC64 2015 2015-03-02 TN -0.4292456368 + #> 7613 2063 3M CC64 2015 2015-03-02 TP -2.2072749132 #> 7614 2063 3M CC64 2015 2015-03-02 TURB 0.8754687374 #> 7615 2063 3M CC64 2015 2015-04-06 CHLAC 0.9162907319 #> 7616 2063 3M CC64 2015 2015-04-06 COLOR 2.9957322736 #> 7617 2063 3M CC64 2015 2015-04-06 DO 1.3558351536 #> 7618 2063 3M CC64 2015 2015-04-06 DOSAT 4.0036901940 + #> 7619 2063 3M CC64 2015 2015-04-06 NO23 -4.6051701860 #> 7620 2063 3M CC64 2015 2015-04-06 SALIN 3.2268439945 #> 7621 2063 3M CC64 2015 2015-04-06 TKN -0.4462871026 #> 7622 2063 3M CC64 2015 2015-04-06 TN -0.4307829161 + #> 7623 2063 3M CC64 2015 2015-04-06 TP -2.3025850930 #> 7624 2063 3M CC64 2015 2015-04-06 TURB 0.6931471806 #> 7625 2063 3M CC64 2015 2015-05-04 CHLAC 1.2809338455 #> 7626 2063 3M CC64 2015 2015-05-04 COLOR 2.9444389792 #> 7627 2063 3M CC64 2015 2015-05-04 DOSAT 4.0673158898 + #> 7628 2063 3M CC64 2015 2015-05-04 NO23 -4.8283137373 I #> 7629 2063 3M CC64 2015 2015-05-04 SALIN 3.2820383998 #> 7630 2063 3M CC64 2015 2015-05-04 TKN -0.7133498879 #> 7631 2063 3M CC64 2015 2015-05-04 TN -0.7052197618 + #> 7632 2063 3M CC64 2015 2015-05-04 TP -2.7806208939 #> 7633 2063 3M CC64 2015 2015-05-04 TURB 0.7884573604 #> 7634 2063 3M CC64 2015 2015-06-01 CHLAC 1.1631508098 #> 7635 2063 3M CC64 2015 2015-06-01 COLOR 2.8332133441 #> 7636 2063 3M CC64 2015 2015-06-01 DO 1.0647107370 #> 7637 2063 3M CC64 2015 2015-06-01 DOSAT 3.7773481021 + #> 7638 2063 3M CC64 2015 2015-06-01 NO23 -4.6051701860 I #> 7639 2063 3M CC64 2015 2015-06-01 SALIN 3.3214324132 #> 7640 2063 3M CC64 2015 2015-06-01 TKN -0.5621189182 #> 7641 2063 3M CC64 2015 2015-06-01 TN -0.5551258827 + #> 7642 2063 3M CC64 2015 2015-06-01 TP -2.3025850930 #> 7643 2063 3M CC64 2015 2015-06-01 TURB 0.4700036292 #> 7644 2063 3M CC64 2015 2015-08-03 CHLAC 2.2407096893 #> 7645 2063 3M CC64 2015 2015-08-03 COLOR 4.1588830834 #> 7646 2063 3M CC64 2015 2015-08-03 DO 0.7654678421 #> 7647 2063 3M CC64 2015 2015-08-03 DOSAT 3.4045251718 + #> 7648 2063 3M CC64 2015 2015-08-03 NO23 -4.6051701860 I #> 7649 2063 3M CC64 2015 2015-08-03 SALIN 2.8039662579 #> 7650 2063 3M CC64 2015 2015-08-03 TKN -0.0512932944 #> 7651 2063 3M CC64 2015 2015-08-03 TN -0.0470916075 + #> 7652 2063 3M CC64 2015 2015-08-03 TP -2.0402208285 #> 7653 2063 3M CC64 2015 2015-08-03 TURB 0.5877866649 #> 7654 2063 3M CC64 2015 2015-09-08 CHLAC 1.3609765531 #> 7655 2063 3M CC64 2015 2015-09-08 COLOR 4.5432947823 #> 7656 2063 3M CC64 2015 2015-09-08 NO23 -3.6888794541 #> 7657 2063 3M CC64 2015 2015-09-08 SALIN 1.3584091576 #> 7658 2063 3M CC64 2015 2015-09-08 TKN -0.1743533871 #> 7659 2063 3M CC64 2015 2015-09-08 TN -0.1450257721 + #> 7660 2063 3M CC64 2015 2015-09-08 TP -2.2072749132 #> 7661 2063 3M CC64 2015 2015-09-08 TURB 0.5306282511 #> 7662 2063 3M CC64 2015 2015-10-05 CHLAC 1.5892352051 #> 7663 2063 3M CC64 2015 2015-10-05 COLOR 4.5643481915 #> 7664 2063 3M CC64 2015 2015-10-05 DO 1.1085626195 #> 7665 2063 3M CC64 2015 2015-10-05 DOSAT 3.6888794541 + #> 7666 2063 3M CC64 2015 2015-10-05 NO23 -3.3524072175 #> 7667 2063 3M CC64 2015 2015-10-05 SALIN 2.4069451083 #> 7668 2063 3M CC64 2015 2015-10-05 TKN -0.1984509387 #> 7669 2063 3M CC64 2015 2015-10-05 TN -0.1566538100 + #> 7670 2063 3M CC64 2015 2015-10-05 TP -1.5606477483 #> 7671 2063 3M CC64 2015 2015-10-05 TURB 0.3364722366 A #> 7672 2063 3M CC64 2015 2015-12-07 CHLAC 0.9555114450 #> 7673 2063 3M CC64 2015 2015-12-07 COLOR 3.4965075615 #> 7674 2063 3M CC64 2015 2015-12-07 DO 1.1314021115 #> 7675 2063 3M CC64 2015 2015-12-07 DOSAT 3.6988297850 + #> 7676 2063 3M CC64 2015 2015-12-07 NO23 -2.8824035882 #> 7677 2063 3M CC64 2015 2015-12-07 SALIN 3.0540011817 #> 7678 2063 3M CC64 2015 2015-12-07 TKN -0.4780358009 #> 7679 2063 3M CC64 2015 2015-12-07 TN -0.3915622029 + #> 7680 2063 3M CC64 2015 2015-12-07 TP -2.2072749132 #> 7681 2063 3M CC64 2015 2015-12-07 TURB 0.7884573604 #> 7682 2063 3M CC64 2016 2016-01-04 CHLAC 0.4700036292 I #> 7683 2063 3M CC64 2016 2016-01-04 COLOR 3.1780538303 #> 7684 2063 3M CC64 2016 2016-01-04 DO 1.1631508098 #> 7685 2063 3M CC64 2016 2016-01-04 DOSAT 3.7281001673 + #> 7686 2063 3M CC64 2016 2016-01-04 NO23 -2.7030626596 #> 7687 2063 3M CC64 2016 2016-01-04 SALIN 3.1112906142 #> 7688 2063 3M CC64 2016 2016-01-04 TKN -0.3011050928 #> 7689 2063 3M CC64 2016 2016-01-04 TN -0.2144316107 + #> 7690 2063 3M CC64 2016 2016-01-04 TP -2.0402208285 #> 7691 2063 3M CC64 2016 2016-01-04 TURB 0.9162907319 #> 7692 2063 3M CC64 2016 2016-02-01 COLOR 4.1896547420 A #> 7693 2063 3M CC64 2016 2016-02-01 DOSAT 4.5053498507 + #> 7694 2063 3M CC64 2016 2016-02-01 NO23 -4.1997050779 #> 7695 2063 3M CC64 2016 2016-02-01 SALIN 1.9810014689 #> 7696 2063 3M CC64 2016 2016-02-01 TKN -0.5447271754 #> 7697 2063 3M CC64 2016 2016-02-01 TN -0.5191938734 + #> 7698 2063 3M CC64 2016 2016-02-01 TP -2.8473122684 #> 7699 2063 3M CC64 2016 2016-02-01 TURB 0.5877866649 #> 7700 2063 3M CC64 2016 2016-03-07 CHLAC 0.6418538862 I #> 7701 2063 3M CC64 2016 2016-03-07 COLOR 3.7841896339 #> 7702 2063 3M CC64 2016 2016-03-07 NO23 -4.1997050779 #> 7703 2063 3M CC64 2016 2016-03-07 SALIN 2.6159349122 #> 7704 2063 3M CC64 2016 2016-03-07 TKN -0.2231435513 #> 7705 2063 3M CC64 2016 2016-03-07 TN -0.2045671657 + #> 7706 2063 3M CC64 2016 2016-03-07 TP -2.3538783874 #> 7707 2063 3M CC64 2016 2016-03-07 TURB 0.4700036292 #> 7708 2063 3M CC64 2016 2016-04-04 CHLAC 1.2237754316 #> 7709 2063 3M CC64 2016 2016-04-04 COLOR 3.3322045102 A #> 7710 2063 3M CC64 2016 2016-04-04 DO 1.6094379124 #> 7711 2063 3M CC64 2016 2016-04-04 DOSAT 4.2061840440 + #> 7712 2063 3M CC64 2016 2016-04-04 NO23 -3.7297014486 #> 7713 2063 3M CC64 2016 2016-04-04 SALIN 2.9236990707 #> 7714 2063 3M CC64 2016 2016-04-04 TN -0.3092462504 + #> 7715 2063 3M CC64 2016 2016-04-04 TP -2.2072749132 #> 7716 2063 3M CC64 2016 2016-04-04 TURB 0.7419373447 #> 7717 2063 3M CC64 2016 2016-05-02 CHLAC 0.8754687374 #> 7718 2063 3M CC64 2016 2016-05-02 COLOR 3.1780538303 #> 7719 2063 3M CC64 2016 2016-05-02 DO 1.1631508098 #> 7720 2063 3M CC64 2016 2016-05-02 DOSAT 3.8394523126 + #> 7721 2063 3M CC64 2016 2016-05-02 NO23 -4.5098600062 #> 7722 2063 3M CC64 2016 2016-05-02 SALIN 3.1428583384 #> 7723 2063 3M CC64 2016 2016-05-02 TKN -0.5276327421 #> 7724 2063 3M CC64 2016 2016-05-02 TN -0.5091603444 + #> 7725 2063 3M CC64 2016 2016-05-02 TP -2.3025850930 #> 7726 2063 3M CC64 2016 2016-05-02 TURB 0.6931471806 #> 7727 2063 3M CC64 2016 2016-06-06 NO23 -4.6051701860 I #> 7728 2063 3M CC64 2016 2016-06-06 SALIN 3.2120525995 #> 7729 2063 3M CC64 2016 2016-06-06 TKN -0.4462871026 #> 7730 2063 3M CC64 2016 2016-06-06 TN -0.4400565529 + #> 7731 2063 3M CC64 2016 2016-06-06 TP -2.1202635362 #> 7732 2063 3M CC64 2016 2016-07-05 CHLAC 1.0296194172 #> 7733 2063 3M CC64 2016 2016-07-05 COLOR 3.9702919136 #> 7734 2063 3M CC64 2016 2016-07-05 DO 0.5596157879 #> 7735 2063 3M CC64 2016 2016-07-05 DOSAT 3.2503744919 + #> 7736 2063 3M CC64 2016 2016-07-05 NO23 -5.5214609179 U #> 7737 2063 3M CC64 2016 2016-07-05 SALIN 2.8864752876 #> 7738 2063 3M CC64 2016 2016-07-05 TKN -0.2484613593 #> 7739 2063 3M CC64 2016 2016-07-05 TN -0.2459005384 + #> 7740 2063 3M CC64 2016 2016-07-05 TP -1.6607312068 #> 7741 2063 3M CC64 2016 2016-07-05 TURB 0.6418538862 #> 7742 2063 3M CC64 2016 2016-08-01 CHLAC 0.7884573604 #> 7743 2063 3M CC64 2016 2016-08-01 COLOR 4.0073331852 A #> 7744 2063 3M CC64 2016 2016-08-01 DO 0.9669838462 #> 7745 2063 3M CC64 2016 2016-08-01 DOSAT 3.6428355156 + #> 7746 2063 3M CC64 2016 2016-08-01 NO23 -4.3428059215 #> 7747 2063 3M CC64 2016 2016-08-01 SALIN 2.6232182656 #> 7748 2063 3M CC64 2016 2016-08-01 TKN -0.1625189295 #> 7749 2063 3M CC64 2016 2016-08-01 TN -0.1473405879 + #> 7750 2063 3M CC64 2016 2016-08-01 TP -1.9661128564 #> 7751 2063 3M CC64 2016 2016-08-01 TURB 0.3364722366 #> 7752 2063 3M CC64 2016 2016-10-03 CHLAC 1.3350010667 #> 7753 2063 3M CC64 2016 2016-10-03 COLOR 3.9702919136 #> 7754 2063 3M CC64 2016 2016-10-03 DO 0.7178397932 #> 7755 2063 3M CC64 2016 2016-10-03 DOSAT 3.3568971228 + #> 7756 2063 3M CC64 2016 2016-10-03 NO23 -4.1351665567 #> 7757 2063 3M CC64 2016 2016-10-03 SALIN 2.5892666651 #> 7758 2063 3M CC64 2016 2016-10-03 TKN -0.4620354596 #> 7759 2063 3M CC64 2016 2016-10-03 TN -0.4369557752 + #> 7760 2063 3M CC64 2016 2016-10-03 TP -1.8325814637 #> 7761 2063 3M CC64 2016 2016-10-03 TURB 0.1823215568 #> 7762 2063 3M CC64 2016 2016-11-07 CHLAC 0.8754687374 #> 7763 2063 3M CC64 2016 2016-11-07 COLOR 2.8332133441 A #> 7764 2063 3M CC64 2016 2016-11-07 DO 1.3402504226 #> 7765 2063 3M CC64 2016 2016-11-07 DOSAT 3.9473901493 + #> 7766 2063 3M CC64 2016 2016-11-07 NO23 -4.7105307016 I #> 7767 2063 3M CC64 2016 2016-11-07 SALIN 3.3178157727 #> 7768 2063 3M CC64 2016 2016-11-07 TKN -0.4155154440 #> 7769 2063 3M CC64 2016 2016-11-07 TN -0.4094731295 + #> 7770 2063 3M CC64 2016 2016-11-07 TP -2.3330443005 #> 7771 2063 3M CC64 2016 2016-11-07 TURB 0.6418538862 #> 7772 2063 3M CC64 2016 2016-12-05 CHLAC 2.6390573296 #> 7773 2063 3M CC64 2016 2016-12-05 COLOR 2.7080502011 #> 7774 2063 3M CC64 2016 2016-12-05 DO 1.6094379124 #> 7775 2063 3M CC64 2016 2016-12-05 DOSAT 4.2165621949 + #> 7776 2063 3M CC64 2016 2016-12-05 NO23 -5.5214609179 U #> 7777 2063 3M CC64 2016 2016-12-05 SALIN 3.3792925463 #> 7778 2063 3M CC64 2016 2016-12-05 TKN -0.3285040670 #> 7779 2063 3M CC64 2016 2016-12-05 TN -0.3257301401 + #> 7780 2063 3M CC64 2016 2016-12-05 TP -1.7147984281 #> 7781 2063 3M CC64 2016 2016-12-05 TURB 0.8329091229 #> 7782 2063 3M CC64 2017 2017-01-03 CHLAC 0.7419373447 #> 7783 2063 3M CC64 2017 2017-01-03 COLOR 2.1860512767 #> 7784 2063 3M CC64 2017 2017-01-03 DO 1.6292405397 #> 7785 2063 3M CC64 2017 2017-01-03 DOSAT 4.2370008626 + #> 7786 2063 3M CC64 2017 2017-01-03 NO23 -5.5214609179 U #> 7787 2063 3M CC64 2017 2017-01-03 SALIN 3.3911470458 #> 7788 2063 3M CC64 2017 2017-01-03 TKN -0.6733445533 #> 7789 2063 3M CC64 2017 2017-01-03 TN -0.6694306539 + #> 7790 2063 3M CC64 2017 2017-01-03 TP -2.3751557858 #> 7791 2063 3M CC64 2017 2017-01-03 TURB 0.4700036292 #> 7792 2063 3M CC64 2017 2017-02-06 CHLAC 1.3083328197 #> 7793 2063 3M CC64 2017 2017-02-06 COLOR 2.2300144002 #> 7794 2063 3M CC64 2017 2017-02-06 DO 1.6770965609 #> 7795 2063 3M CC64 2017 2017-02-06 DOSAT 4.2654928184 + #> 7796 2063 3M CC64 2017 2017-02-06 NO23 -3.3242363405 #> 7797 2063 3M CC64 2017 2017-02-06 SALIN 3.3965197921 #> 7798 2063 3M CC64 2017 2017-02-06 TKN -0.3566749439 #> 7799 2063 3M CC64 2017 2017-02-06 TN -0.3065251603 + #> 7800 2063 3M CC64 2017 2017-02-06 TP -2.4418471603 #> 7801 2063 3M CC64 2017 2017-02-06 TURB 0.9555114450 #> 7802 2063 3M CC64 2017 2017-03-06 CHLAC 1.2237754316 #> 7803 2063 3M CC64 2017 2017-03-06 COLOR 1.7917594692 #> 7804 2063 3M CC64 2017 2017-03-06 DO 1.6770965609 #> 7805 2063 3M CC64 2017 2017-03-06 DOSAT 4.2598590007 + #> 7806 2063 3M CC64 2017 2017-03-06 NO23 -5.1159958098 I #> 7807 2063 3M CC64 2017 2017-03-06 SALIN 3.4124669739 #> 7808 2063 3M CC64 2017 2017-03-06 TKN -0.5798184953 #> 7809 2063 3M CC64 2017 2017-03-06 TN -0.5727010275 + #> 7810 2063 3M CC64 2017 2017-03-06 TP -2.5257286443 #> 7811 2063 3M CC64 2017 2017-03-06 TURB 0.9932517730 #> 7812 2063 3M CC64 2017 2017-04-03 CHLAC 1.4586150227 #> 7813 2063 3M CC64 2017 2017-04-03 COLOR 2.3978952728 #> 7814 2063 3M CC64 2017 2017-04-03 DO 1.3635373740 #> 7815 2063 3M CC64 2017 2017-04-03 DOSAT 4.0638853547 + #> 7816 2063 3M CC64 2017 2017-04-03 NO23 -4.9618451299 I #> 7817 2063 3M CC64 2017 2017-04-03 SALIN 3.5115454388 #> 7818 2063 3M CC64 2017 2017-04-03 TKN -0.3424903089 #> 7819 2063 3M CC64 2017 2017-04-03 TN -0.3368723166 + #> 7820 2063 3M CC64 2017 2017-04-03 TP -2.4769384801 #> 7821 2063 3M CC64 2017 2017-04-03 TURB 0.8754687374 #> 7822 2063 3M CC64 2017 2017-05-01 CHLAC 1.0296194172 #> 7823 2063 3M CC64 2017 2017-05-01 COLOR 2.6390573296 #> 7824 2063 3M CC64 2017 2017-05-01 DO 1.3480731483 #> 7825 2063 3M CC64 2017 2017-05-01 DOSAT 4.0604430105 + #> 7826 2063 3M CC64 2017 2017-05-01 NO23 -5.5214609179 U #> 7827 2063 3M CC64 2017 2017-05-01 SALIN 3.5377658244 #> 7828 2063 3M CC64 2017 2017-05-01 TKN -0.2876820725 #> 7829 2063 3M CC64 2017 2017-05-01 TN -0.2850189550 + #> 7830 2063 3M CC64 2017 2017-05-01 TP -2.6736487744 #> 7831 2063 3M CC64 2017 2017-05-01 TURB 0.7419373447 #> 7832 2063 3M CC64 2017 2017-06-05 CHLAC 1.3862943611 A #> 7833 2063 3M CC64 2017 2017-06-05 COLOR 2.7080502011 #> 7834 2063 3M CC64 2017 2017-06-05 DO 2.1294214740 #> 7835 2063 3M CC64 2017 2017-06-05 DOSAT 4.8835592115 + #> 7836 2063 3M CC64 2017 2017-06-05 NO23 -4.5098600062 #> 7837 2063 3M CC64 2017 2017-06-05 SALIN 3.5322256441 #> 7838 2063 3M CC64 2017 2017-06-05 TKN -0.3147107448 #> 7839 2063 3M CC64 2017 2017-06-05 TN -0.2997546537 + #> 7840 2063 3M CC64 2017 2017-06-05 TP -2.5639498571 #> 7841 2063 3M CC64 2017 2017-06-05 TURB 0.8754687374 #> 7842 2063 3M CC64 2017 2017-07-10 CHLAC 2.2512917986 #> 7843 2063 3M CC64 2017 2017-07-10 COLOR 4.4426512565 #> 7844 2063 3M CC64 2017 2017-07-10 DO 0.8458682676 #> 7845 2063 3M CC64 2017 2017-07-10 DOSAT 3.5292973843 + #> 7846 2063 3M CC64 2017 2017-07-10 NO23 -4.6051701860 I #> 7847 2063 3M CC64 2017 2017-07-10 SALIN 2.7408400239 #> 7848 2063 3M CC64 2017 2017-07-10 TKN 0.0000000000 #> 7849 2063 3M CC64 2017 2017-07-10 TN 0.0039920213 + #> 7850 2063 3M CC64 2017 2017-07-10 TP -1.5141277326 #> 7851 2063 3M CC64 2017 2017-07-10 TURB 0.4054651081 #> 7852 2063 3M CC64 2017 2017-08-07 CHLAC 1.5892352051 #> 7853 2063 3M CC64 2017 2017-08-07 COLOR 4.5747109785 A #> 7854 2063 3M CC64 2017 2017-08-07 DO 0.4121096508 #> 7855 2063 3M CC64 2017 2017-08-07 DOSAT 3.0349529867 + #> 7856 2063 3M CC64 2017 2017-08-07 NO23 -3.7297014486 #> 7857 2063 3M CC64 2017 2017-08-07 SALIN 2.0693912058 #> 7858 2063 3M CC64 2017 2017-08-07 TKN -0.0202027073 #> 7859 2063 3M CC64 2017 2017-08-07 TN 0.0039920213 + #> 7860 2063 3M CC64 2017 2017-08-07 TP -1.6607312068 #> 7861 2063 3M CC64 2017 2017-08-07 TURB 0.6931471806 #> 7862 2063 3M CC64 2017 2017-09-05 CHLAC 1.6094379124 #> 7863 2063 3M CC64 2017 2017-09-05 COLOR 4.7874917428 #> 7864 2063 3M CC64 2017 2017-09-05 DO 0.8586616190 #> 7865 2063 3M CC64 2017 2017-09-05 DOSAT 3.4404180948 + #> 7866 2063 3M CC64 2017 2017-09-05 NO23 -3.0159349809 #> 7867 2063 3M CC64 2017 2017-09-05 SALIN 0.9001613499 #> 7868 2063 3M CC64 2017 2017-09-05 TKN -0.1508228897 #> 7869 2063 3M CC64 2017 2017-09-05 TN -0.0954101848 + #> 7870 2063 3M CC64 2017 2017-09-05 TP -2.0402208285 #> 7871 2063 3M CC64 2017 2017-09-05 TURB 0.5877866649 #> 7872 2063 3M CC64 2017 2017-10-02 CHLAC 1.3083328197 #> 7873 2063 3M CC64 2017 2017-10-02 COLOR 4.4998096703 #> 7874 2063 3M CC64 2017 2017-10-02 NO23 -3.1465551633 #> 7875 2063 3M CC64 2017 2017-10-02 TKN -0.9675840263 #> 7876 2063 3M CC64 2017 2017-10-02 TN -0.8603830999 + #> 7877 2063 3M CC64 2017 2017-10-02 TP -1.6094379124 #> 7878 2063 3M CC64 2017 2017-10-02 TURB 0.3364722366 #> 7879 2063 3M CC64 2017 2017-11-06 CHLAC 0.7419373447 #> 7880 2063 3M CC64 2017 2017-11-06 COLOR 3.5835189385 #> 7881 2063 3M CC64 2017 2017-11-06 DO 2.0014800002 #> 7882 2063 3M CC64 2017 2017-11-06 DOSAT 4.5890408041 + #> 7883 2063 3M CC64 2017 2017-11-06 NO23 -3.4420193762 #> 7884 2063 3M CC64 2017 2017-11-06 SALIN 3.0864866368 #> 7885 2063 3M CC64 2017 2017-11-06 TKN -0.5798184953 #> 7886 2063 3M CC64 2017 2017-11-06 TN -0.5242486441 + #> 7887 2063 3M CC64 2017 2017-11-06 TP -1.8971199849 #> 7888 2063 3M CC64 2017 2017-11-06 TURB 0.3364722366 #> 7889 2063 3M CC64 2017 2017-12-04 CHLAC 0.9162907319 #> 7890 2063 3M CC64 2017 2017-12-04 COLOR 3.1780538303 #> 7891 2063 3M CC64 2017 2017-12-04 DO 1.5644405465 #> 7892 2063 3M CC64 2017 2017-12-04 DOSAT 4.1287459889 #> 7893 2063 3M CC64 2017 2017-12-04 NO23 -4.5098600062 #> 7894 2063 3M CC64 2017 2017-12-04 SALIN 3.3403852423 #> 7895 2063 3M CC64 2017 2017-12-04 TKN -0.5276327421 #> 7896 2063 3M CC64 2017 2017-12-04 TN -0.5091603444 + #> 7897 2063 3M CC64 2017 2017-12-04 TP -2.2072749132 #> 7898 2063 3M CC64 2017 2017-12-04 TURB 0.3364722366 #> 7899 2063 3M CC64 2018 2018-01-02 CHLAC 2.7725887222 #> 7900 2063 3M CC64 2018 2018-01-02 COLOR 3.0910424534 #> 7901 2063 3M CC64 2018 2018-01-02 DOSAT 4.0360089852 + #> 7902 2063 3M CC64 2018 2018-01-02 NO23 -5.5214609179 U #> 7903 2063 3M CC64 2018 2018-01-02 SALIN 3.2657594108 #> 7904 2063 3M CC64 2018 2018-01-02 TKN -0.3147107448 #> 7905 2063 3M CC64 2018 2018-01-02 TN -0.3119747650 + #> 7906 2063 3M CC64 2018 2018-01-02 TP -1.6607312068 #> 7907 2063 3M CC64 2018 2018-01-02 TURB 2.3978952728 #> 7908 2063 3M CC64 2018 2018-03-05 CHLAC 0.5306282511 I #> 7909 2063 3M CC64 2018 2018-03-05 COLOR 2.6390573296 #> 7910 2063 3M CC64 2018 2018-03-05 DOSAT 4.2416144810 #> 7911 2063 3M CC64 2018 2018-03-05 NO23 -5.5214609179 I #> 7912 2063 3M CC64 2018 2018-03-05 SALIN 3.3467411959 #> 7913 2063 3M CC64 2018 2018-03-05 TKN -0.5621189182 #> 7914 2063 3M CC64 2018 2018-03-05 TN -0.5551258827 + #> 7915 2063 3M CC64 2018 2018-03-05 TP -2.1202635362 #> 7916 2063 3M CC64 2018 2018-03-05 TURB 0.4700036292 #> 7917 2063 3M CC64 2018 2018-04-02 CHLAC 0.7419373447 #> 7918 2063 3M CC64 2018 2018-04-02 COLOR 2.3978952728 #> 7919 2063 3M CC64 2018 2018-04-02 DO 1.5040773968 #> 7920 2063 3M CC64 2018 2018-04-02 DOSAT 3.4307561839 #> 7921 2063 3M CC64 2018 2018-04-02 NO23 -4.9618451299 I #> 7922 2063 3M CC64 2018 2018-04-02 SALIN 3.4330189940 #> 7923 2063 3M CC64 2018 2018-04-02 TKN -0.6539264674 #> 7924 2063 3M CC64 2018 2018-04-02 TN -0.6462635947 + #> 7925 2063 3M CC64 2018 2018-04-02 TP -2.2072749132 #> 7926 2063 3M CC64 2018 2018-04-02 TURB 0.7884573604 #> 7927 2063 3M CC64 2018 2018-05-07 CHLAC 1.4350845253 #> 7928 2063 3M CC64 2018 2018-05-07 COLOR 2.5649493575 #> 7929 2063 3M CC64 2018 2018-05-07 DO 1.3962446920 #> 7930 2063 3M CC64 2018 2018-05-07 DOSAT 4.0842942264 #> 7931 2063 3M CC64 2018 2018-05-07 NO23 -5.1159958098 I #> 7932 2063 3M CC64 2018 2018-05-07 SALIN 3.4388142452 #> 7933 2063 3M CC64 2018 2018-05-07 TKN -0.3424903089 #> 7934 2063 3M CC64 2018 2018-05-07 TN -0.3368723166 + #> 7935 2063 3M CC64 2018 2018-05-07 TP -2.0402208285 #> 7936 2063 3M CC64 2018 2018-05-07 TURB 1.0986122887 #> 7937 2063 3M CC64 2018 2018-07-09 CHLAC 0.9555114450 #> 7938 2063 3M CC64 2018 2018-07-09 COLOR 4.5747109785 #> 7939 2063 3M CC64 2018 2018-07-09 DO 0.6312717768 #> 7940 2063 3M CC64 2018 2018-07-09 DOSAT 3.2308043957 #> 7941 2063 3M CC64 2018 2018-07-09 NO23 -3.6119184130 #> 7942 2063 3M CC64 2018 2018-07-09 SALIN 1.8640801308 #> 7943 2063 3M CC64 2018 2018-07-09 TKN 0.0000000000 #> 7944 2063 3M CC64 2018 2018-07-09 TN 0.0266419309 + #> 7945 2063 3M CC64 2018 2018-07-09 TP -2.3025850930 #> 7946 2063 3M CC64 2018 2018-07-09 TURB 0.1823215568 #> 7947 2063 3M CC64 2018 2018-08-06 CHLAC 1.0986122887 #> 7948 2063 3M CC64 2018 2018-08-06 COLOR 4.5951198501 #> 7949 2063 3M CC64 2018 2018-08-06 DO 0.8796267475 #> 7950 2063 3M CC64 2018 2018-08-06 DOSAT 3.4339872045 #> 7951 2063 3M CC64 2018 2018-08-06 NO23 -3.4737680745 #> 7952 2063 3M CC64 2018 2018-08-06 SALIN 1.6448050563 #> 7953 2063 3M CC64 2018 2018-08-06 TKN -0.1508228897 #> 7954 2063 3M CC64 2018 2018-08-06 TN -0.1154108515 + #> 7955 2063 3M CC64 2018 2018-08-06 TP -2.3227878003 #> 7956 2063 3M CC64 2018 2018-08-06 TURB 0.5877866649 #> 7957 2063 3M CC64 2019 2019-02-04 CHLAC 1.1314021115 #> 7958 2063 3M CC64 2019 2019-02-04 COLOR 3.0910424534 #> 7959 2063 3M CC64 2019 2019-02-04 DO 1.8764069433 #> 7960 2063 3M CC64 2019 2019-02-04 DOSAT 4.4200447019 #> 7961 2063 3M CC64 2019 2019-02-04 NO23 -4.8283137373 I #> 7962 2063 3M CC64 2019 2019-02-04 SALIN 3.0928589843 #> 7963 2063 3M CC64 2019 2019-02-04 TKN -0.7765287895 #> 7964 2063 3M CC64 2019 2019-02-04 TN -0.7678707268 + #> 7965 2063 3M CC64 2019 2019-02-04 TP -2.3025850930 #> 7966 2063 3M CC64 2019 2019-02-04 TURB 0.6418538862 #> 7967 2063 3M CC64 2019 2019-03-04 CHLAC 0.8329091229 #> 7968 2063 3M CC64 2019 2019-03-04 COLOR 3.1354942159 #> 7969 2063 3M CC64 2019 2019-03-04 DO 1.6014057407 #> 7970 2063 3M CC64 2019 2019-03-04 DOSAT 4.2297491992 #> 7971 2063 3M CC64 2019 2019-03-04 NO23 -4.8283137373 I #> 7972 2063 3M CC64 2019 2019-03-04 SALIN 2.9992261628 #> 7973 2063 3M CC64 2019 2019-03-04 TKN -0.5798184953 #> 7974 2063 3M CC64 2019 2019-03-04 TN -0.5727010275 + #> 7975 2063 3M CC64 2019 2019-03-04 TP -2.3025850930 #> 7976 2063 3M CC64 2019 2019-03-04 TURB 0.5306282511 #> 7977 2063 3M CC64 2019 2019-04-01 CHLAC 0.4700036292 I #> 7978 2063 3M CC64 2019 2019-04-01 COLOR 2.7725887222 #> 7979 2063 3M CC64 2019 2019-04-01 DO 1.3962446920 #> 7980 2063 3M CC64 2019 2019-04-01 DOSAT 3.9889840466 #> 7981 2063 3M CC64 2019 2019-04-01 NO23 -4.5098600062 #> 7982 2063 3M CC64 2019 2019-04-01 SALIN 3.1210424645 #> 7983 2063 3M CC64 2019 2019-04-01 TKN -0.5276327421 #> 7984 2063 3M CC64 2019 2019-04-01 TN -0.5091603444 + #> 7985 2063 3M CC64 2019 2019-04-01 TP -2.3126354288 #> 7986 2063 3M CC64 2019 2019-04-01 TURB 0.4700036292 #> 7987 2063 3M CC64 2019 2019-05-06 CHLAC 0.6931471806 I #> 7988 2063 3M CC64 2019 2019-05-06 COLOR 2.9444389792 #> 7989 2063 3M CC64 2019 2019-05-06 DO 0.8372475245 #> 7990 2063 3M CC64 2019 2019-05-06 DOSAT 3.5292973843 #> 7991 2063 3M CC64 2019 2019-05-06 NO23 -4.6051701860 I #> 7992 2063 3M CC64 2019 2019-05-06 SALIN 3.2331731296 #> 7993 2063 3M CC64 2019 2019-05-06 TKN -0.5621189182 #> 7994 2063 3M CC64 2019 2019-05-06 TN -0.5551258827 + #> 7995 2063 3M CC64 2019 2019-05-06 TP -2.2072749132 #> 7996 2063 3M CC64 2019 2019-05-06 TURB 0.2623642645 #> 7997 2063 3M CC64 2019 2019-06-03 CHLAC 0.7419373447 I #> 7998 2063 3M CC64 2019 2019-06-03 COLOR 2.8903717579 #> 7999 2063 3M CC64 2019 2019-06-03 DO 1.2974631474 #> 8000 2063 3M CC64 2019 2019-06-03 DOSAT 3.7220724215 #> 8001 2063 3M CC64 2019 2019-06-03 NO23 -5.2983173665 I #> 8002 2063 3M CC64 2019 2019-06-03 SALIN 3.2703291065 #> 8003 2063 3M CC64 2019 2019-06-03 TKN -0.3856624808 #> 8004 2063 3M CC64 2019 2019-06-03 TN -0.3797973614 + #> 8005 2063 3M CC64 2019 2019-06-03 TP -2.3025850930 #> 8006 2063 3M CC64 2019 2019-06-03 TURB 0.2623642645 #> 8007 2063 3M CC64 2019 2019-07-01 CHLAC 1.0986122887 #> 8008 2063 3M CC64 2019 2019-07-01 COLOR 2.8903717579 #> 8009 2063 3M CC64 2019 2019-07-01 DO 1.4036429995 #> 8010 2063 3M CC64 2019 2019-07-01 DOSAT 4.1108738642 #> 8011 2063 3M CC64 2019 2019-07-01 NO23 -5.1159958098 I #> 8012 2063 3M CC64 2019 2019-07-01 SALIN 3.1675825305 #> 8013 2063 3M CC64 2019 2019-07-01 TKN -0.4780358009 #> 8014 2063 3M CC64 2019 2019-07-01 TN -0.4716049106 + #> 8015 2063 3M CC64 2019 2019-07-01 TP -2.2072749132 #> 8016 2063 3M CC64 2019 2019-07-01 TURB 0.5877866649 #> 8017 2063 3M CC64 2019 2019-08-05 CHLAC 1.7578579176 #> 8018 2063 3M CC64 2019 2019-08-05 COLOR 3.9120230054 #> 8019 2063 3M CC64 2019 2019-08-05 DO 1.3001916621 #> 8020 2063 3M CC64 2019 2019-08-05 DOSAT 3.9702919136 #> 8021 2063 3M CC64 2019 2019-08-05 NO23 -5.5214609179 U #> 8022 2063 3M CC64 2019 2019-08-05 SALIN 2.8273136219 #> 8023 2063 3M CC64 2019 2019-08-05 TKN -0.1863295782 #> 8024 2063 3M CC64 2019 2019-08-05 TN -0.1839228382 + #> 8025 2063 3M CC64 2019 2019-08-05 TP -1.8325814637 #> 8026 2063 3M CC64 2019 2019-08-05 TURB 0.4700036292 #> 8027 2063 3M CC64 2019 2019-10-07 CHLAC 1.1939224685 #> 8028 2063 3M CC64 2019 2019-10-07 COLOR 3.2958368660 #> 8029 2063 3M CC64 2019 2019-10-07 DO 1.6863989536 #> 8030 2063 3M CC64 2019 2019-10-07 DOSAT 4.3412046402 #> 8031 2063 3M CC64 2019 2019-10-07 NO23 -5.1159958098 I #> 8032 2063 3M CC64 2019 2019-10-07 SALIN 3.2672849641 #> 8033 2063 3M CC64 2019 2019-10-07 TKN -0.4780358009 #> 8034 2063 3M CC64 2019 2019-10-07 TN -0.4716049106 + #> 8035 2063 3M CC64 2019 2019-10-07 TP -2.1202635362 #> 8036 2063 3M CC64 2019 2019-10-07 TURB 0.2623642645 #> 8037 2063 3M CC64 2019 2019-11-04 CHLAC 1.1939224685 #> 8038 2063 3M CC64 2019 2019-11-04 COLOR 3.1354942159 #> 8039 2063 3M CC64 2019 2019-11-04 DO 1.3110318766 #> 8040 2063 3M CC64 2019 2019-11-04 DOSAT 3.9646154555 #> 8041 2063 3M CC64 2019 2019-11-04 NO23 -4.6051701860 #> 8042 2063 3M CC64 2019 2019-11-04 SALIN 3.2503744919 #> 8043 2063 3M CC64 2019 2019-11-04 TKN -0.4307829161 #> 8044 2063 3M CC64 2019 2019-11-04 TN -0.4155154440 + #> 8045 2063 3M CC64 2019 2019-11-04 TP -2.1202635362 #> 8046 2063 3M CC64 2019 2019-11-04 TURB 0.0953101798 #> 8047 2063 3M CC64 2020 2020-01-06 CHLAC 1.0296194172 #> 8048 2063 3M CC64 2020 2020-01-06 COLOR 2.8332133441 #> 8049 2063 3M CC64 2020 2020-01-06 DO 1.6937790609 #> 8050 2063 3M CC64 2020 2020-01-06 DOSAT 4.2312037449 #> 8051 2063 3M CC64 2020 2020-01-06 NO23 -4.0745419349 #> 8052 2063 3M CC64 2020 2020-01-06 SALIN 3.2188758249 #> 8053 2063 3M CC64 2020 2020-01-06 TKN -0.4155154440 #> 8054 2063 3M CC64 2020 2020-01-06 TN -0.3900840061 + #> 8055 2063 3M CC64 2020 2020-01-06 TP -2.2072749132 #> 8056 2063 3M CC64 2020 2020-01-06 TURB 0.6931471806 #> 8057 2063 3M CC64 2020 2020-02-03 CHLAC 0.2623642645 I #> 8058 2063 3M CC64 2020 2020-02-03 COLOR 2.8332133441 #> 8059 2063 3M CC64 2020 2020-02-03 DO 1.5789787049 #> 8060 2063 3M CC64 2020 2020-02-03 DOSAT 4.0842942264 #> 8061 2063 3M CC64 2020 2020-02-03 NO23 -3.5755507688 #> 8062 2063 3M CC64 2020 2020-02-03 SALIN 3.2104403460 #> 8063 2063 3M CC64 2020 2020-02-03 TKN -0.6539264674 #> 8064 2063 3M CC64 2020 2020-02-03 TN -0.6014799920 + #> 8065 2063 3M CC64 2020 2020-02-03 TP -2.3434070875 #> 8066 2063 3M CC64 2020 2020-02-03 TURB 0.9162907319 #> 8067 2063 3M CC64 2020 2020-03-02 CHLAC 0.6931471806 I #> 8068 2063 3M CC64 2020 2020-03-02 COLOR 2.5649493575 A #> 8069 2063 3M CC64 2020 2020-03-02 DO 1.7749523509 #> 8070 2063 3M CC64 2020 2020-03-02 DOSAT 4.3067641502 #> 8071 2063 3M CC64 2020 2020-03-02 NO23 -5.5214609179 I #> 8072 2063 3M CC64 2020 2020-03-02 SALIN 3.2924979647 #> 8073 2063 3M CC64 2020 2020-03-02 TKN -0.8915981193 #> 8074 2063 3M CC64 2020 2020-03-02 TN -0.8818893052 + #> 8075 2063 3M CC64 2020 2020-03-02 TP -2.3968957725 #> 8076 2063 3M CC64 2020 2020-03-02 TURB 0.2623642645 #> 8077 2063 3M CC64 2020 2020-09-08 CHLAC 2.3025850930 A #> 8078 2063 3M CC64 2020 2020-09-08 COLOR 4.0253516907 #> 8079 2063 3M CC64 2020 2020-09-08 DO 0.1484200051 #> 8080 2063 3M CC64 2020 2020-09-08 DOSAT 2.8332133441 #> 8081 2063 3M CC64 2020 2020-09-08 NO23 -5.1159958098 I #> 8082 2063 3M CC64 2020 2020-09-08 SALIN 2.9693882982 #> 8083 2063 3M CC64 2020 2020-09-08 TKN -0.2231435513 #> 8084 2063 3M CC64 2020 2020-09-08 TN -0.2181560098 + #> 8085 2063 3M CC64 2020 2020-09-08 TP -1.5141277326 #> 8086 2063 3M CC64 2020 2020-09-08 TURB 0.5306282511 #> 8087 2063 3M CC64 2020 2020-10-05 CHLAC 1.5040773968 #> 8088 2063 3M CC64 2020 2020-10-05 COLOR 4.2626798770 #> 8089 2063 3M CC64 2020 2020-10-05 DO 1.1600209168 #> 8090 2063 3M CC64 2020 2020-10-05 DOSAT 3.7495040759 #> 8091 2063 3M CC64 2020 2020-10-05 NO23 -3.0365542681 #> 8092 2063 3M CC64 2020 2020-10-05 SALIN 2.5649493575 #> 8093 2063 3M CC64 2020 2020-10-05 TKN -0.0408219945 #> 8094 2063 3M CC64 2020 2020-10-05 TN 0.0079681696 + #> 8095 2063 3M CC64 2020 2020-10-05 TP -1.8971199849 #> 8096 2063 3M CC64 2020 2020-10-05 TURB 0.0953101798 #> 8097 2063 3M CC64 2020 2020-11-02 CHLAC 1.1631508098 I #> 8098 2063 3M CC64 2020 2020-11-02 COLOR 4.0073331852 A #> 8099 2063 3M CC64 2020 2020-11-02 NO23 -3.9633162998 #> 8100 2063 3M CC64 2020 2020-11-02 SALIN 2.7562052430 #> 8101 2063 3M CC64 2020 2020-11-02 TKN -0.3710636814 #> 8102 2063 3M CC64 2020 2020-11-02 TN -0.3438997525 + #> 8103 2063 3M CC64 2020 2020-11-02 TP -2.0402208285 #> 8104 2063 3M CC64 2020 2020-11-02 TURB 0.2623642645 #> 8105 2063 3M CC64 2020 2020-12-07 CHLAC 0.3364722366 I #> 8106 2063 3M CC64 2020 2020-12-07 COLOR 3.6635616461 #> 8107 2063 3M CC64 2020 2020-12-07 DO 1.6677068206 #> 8108 2063 3M CC64 2020 2020-12-07 DOSAT 4.1743872699 #> 8109 2063 3M CC64 2020 2020-12-07 NO23 -3.8167128256 #> 8110 2063 3M CC64 2020 2020-12-07 SALIN 2.9982291538 #> 8111 2063 3M CC64 2020 2020-12-07 TKN -0.3856624808 #> 8112 2063 3M CC64 2020 2020-12-07 TN -0.3538218750 + #> 8113 2063 3M CC64 2020 2020-12-07 TP -2.4769384801 #> 8114 2063 3M CC64 2020 2020-12-07 TURB 0.1823215568 #> 8115 2063 3M CC64 2021 2021-01-04 CHLAC 0.3364722366 I #> 8116 2063 3M CC64 2021 2021-01-04 COLOR 3.1780538303 #> 8117 2063 3M CC64 2021 2021-01-04 DO 1.4816045409 #> 8118 2063 3M CC64 2021 2021-01-04 DOSAT 4.0271358125 #> 8119 2063 3M CC64 2021 2021-01-04 NO23 -4.1351665567 #> 8120 2063 3M CC64 2021 2021-01-04 SALIN 3.1376657694 #> 8121 2063 3M CC64 2021 2021-01-04 TKN -0.5276327421 #> 8122 2063 3M CC64 2021 2021-01-04 TN -0.5008752929 + #> 8123 2063 3M CC64 2021 2021-01-04 TP -2.3025850930 #> 8124 2063 3M CC64 2021 2021-01-04 TURB 0.2623642645 #> 8125 2063 3M CC64 2021 2021-02-01 CHLAC 0.9932517730 #> 8126 2063 3M CC64 2021 2021-02-01 COLOR 2.8332133441 #> 8127 2063 3M CC64 2021 2021-02-01 DO 1.8082887712 #> 8128 2063 3M CC64 2021 2021-02-01 DOSAT 4.3489867806 #> 8129 2063 3M CC64 2021 2021-02-01 NO23 -4.9618451299 I #> 8130 2063 3M CC64 2021 2021-02-01 SALIN 3.2120525995 #> 8131 2063 3M CC64 2021 2021-02-01 TKN -0.5276327421 #> 8132 2063 3M CC64 2021 2021-02-01 TN -0.5208759596 + #> 8133 2063 3M CC64 2021 2021-02-01 TP -2.3751557858 #> 8134 2063 3M CC64 2021 2021-02-01 TURB 1.1631508098 #> 8135 2063 3M CC64 2021 2021-03-01 CHLAC 0.6418538862 I #> 8136 2063 3M CC64 2021 2021-03-01 COLOR 2.6390573296 #> 8137 2063 3M CC64 2021 2021-03-01 DO 1.5454325825 #> 8138 2063 3M CC64 2021 2021-03-01 DOSAT 4.1956970565 #> 8139 2063 3M CC64 2021 2021-03-01 NO23 -4.8283137373 I #> 8140 2063 3M CC64 2021 2021-03-01 SALIN 3.2861605717 #> 8141 2063 3M CC64 2021 2021-03-01 TKN -0.9675840263 I #> 8142 2063 3M CC64 2021 2021-03-01 TN -1.8078888512 + #> 8143 2063 3M CC64 2021 2021-03-01 TP -2.3859667019 #> 8144 2063 3M CC64 2021 2021-03-01 TURB 0.6931471806 A #> 8145 2063 3M CC64 2021 2021-04-05 CHLAC 1.5475625087 #> 8146 2063 3M CC64 2021 2021-04-05 COLOR 2.7080502011 #> 8147 2063 3M CC64 2021 2021-04-05 DO 1.6505798558 #> 8148 2063 3M CC64 2021 2021-04-05 DOSAT 4.2370008626 #> 8149 2063 3M CC64 2021 2021-04-05 NO23 -5.5214609179 U #> 8150 2063 3M CC64 2021 2021-04-05 SALIN 3.3010086544 #> 8151 2063 3M CC64 2021 2021-04-05 TN -0.4277107171 + #> 8152 2063 3M CC64 2021 2021-04-05 TP -2.2072749132 #> 8153 2063 3M CC64 2021 2021-04-05 TURB 1.2527629685 #> 8154 2063 3M CC64 2021 2021-05-03 CHLAC 0.9932517730 #> 8155 2063 3M CC64 2021 2021-05-03 COLOR 2.9957322736 #> 8156 2063 3M CC64 2021 2021-05-03 DO 1.2584609896 #> 8157 2063 3M CC64 2021 2021-05-03 DOSAT 3.9740583963 #> 8158 2063 3M CC64 2021 2021-05-03 NO23 -5.5214609179 U #> 8159 2063 3M CC64 2021 2021-05-03 SALIN 3.3641875560 #> 8160 2063 3M CC64 2021 2021-05-03 TKN -0.7133498879 #> 8161 2063 3M CC64 2021 2021-05-03 TN -0.7092765625 + #> 8162 2063 3M CC64 2021 2021-05-03 TP -2.3227878003 #> 8163 2063 3M CC64 2021 2021-05-03 TURB 0.7419373447 #> 8164 2063 3M CC64 2021 2021-06-07 CHLAC 1.7578579176 #> 8165 2063 3M CC64 2021 2021-06-07 COLOR 2.8332133441 #> 8166 2063 3M CC64 2021 2021-06-07 DO 0.9707789172 #> 8167 2063 3M CC64 2021 2021-06-07 DOSAT 3.6788291183 #> 8168 2063 3M CC64 2021 2021-06-07 NO23 -4.3428059215 #> 8169 2063 3M CC64 2021 2021-06-07 SALIN 3.2839142210 #> 8170 2063 3M CC64 2021 2021-06-07 TKN -0.4620354596 #> 8171 2063 3M CC64 2021 2021-06-07 TN -0.4416105547 + #> 8172 2063 3M CC64 2021 2021-06-07 TP -2.4304184645 #> 8173 2063 3M CC64 2021 2021-06-07 TURB 0.4054651081 #> 8174 2063 3M CC64 2021 2021-08-02 CHLAC 1.6094379124 #> 8175 2063 3M CC64 2021 2021-08-02 COLOR 4.3438054219 #> 8176 2063 3M CC64 2021 2021-08-02 DO 1.4255150743 #> 8177 2063 3M CC64 2021 2021-08-02 DOSAT 4.1092331747 #> 8178 2063 3M CC64 2021 2021-08-02 NO23 -4.8283137373 I #> 8179 2063 3M CC64 2021 2021-08-02 SALIN 2.4292177439 #> 8180 2063 3M CC64 2021 2021-08-02 TKN -0.1278333715 #> 8181 2063 3M CC64 2021 2021-08-02 TN -0.1232982163 + #> 8182 2063 3M CC64 2021 2021-08-02 TP -1.7719568419 #> 8183 2063 3M CC64 2021 2021-08-02 TURB 0.6418538862 #> 8184 2063 3M CC64 2021 2021-09-07 CHLAC 0.9555114450 #> 8185 2063 3M CC64 2021 2021-09-07 COLOR 4.1271343850 #> 8186 2063 3M CC64 2021 2021-09-07 DO 0.9820784724 #> 8187 2063 3M CC64 2021 2021-09-07 DOSAT 3.6375861597 #> 8188 2063 3M CC64 2021 2021-09-07 NO23 -3.8167128256 #> 8189 2063 3M CC64 2021 2021-09-07 SALIN 2.5687881338 #> 8190 2063 3M CC64 2021 2021-09-07 TKN -0.1053605157 #> 8191 2063 3M CC64 2021 2021-09-07 TN -0.0812100554 + #> 8192 2063 3M CC64 2021 2021-09-07 TP -1.8325814637 #> 8193 2063 3M CC64 2021 2021-09-07 TURB 0.0953101798 #> 8194 2063 3M CC64 2021 2021-10-04 CHLAC 1.1939224685 #> 8195 2063 3M CC64 2021 2021-10-04 COLOR 3.7841896339 #> 8196 2063 3M CC64 2021 2021-10-04 DO 1.0577902941 #> 8197 2063 3M CC64 2021 2021-10-04 DOSAT 3.7135720667 #> 8198 2063 3M CC64 2021 2021-10-04 NO23 -4.7105307016 I #> 8199 2063 3M CC64 2021 2021-10-04 SALIN 2.9069010598 #> 8200 2063 3M CC64 2021 2021-10-04 TKN -0.3566749439 #> 8201 2063 3M CC64 2021 2021-10-04 TN -0.3509769228 + #> 8202 2063 3M CC64 2021 2021-10-04 TP -1.8325814637 #> 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2022 2022-06-06 CHLAC 1.9459101491 #> 8275 2063 3M CC64 2022 2022-06-06 COLOR 3.7612001157 A #> 8276 2063 3M CC64 2022 2022-06-06 DO 1.3987168811 #> 8277 2063 3M CC64 2022 2022-06-06 DOSAT 4.0775374439 #> 8278 2063 3M CC64 2022 2022-06-06 NO23 -4.7105307016 I #> 8279 2063 3M CC64 2022 2022-06-06 SALIN 3.2588654731 #> 8280 2063 3M CC64 2022 2022-06-06 TKN -0.1165338163 #> 8281 2063 3M CC64 2022 2022-06-06 TN -0.1120495038 + #> 8282 2063 3M CC64 2022 2022-06-06 TP -2.4304184645 #> 8283 2063 3M CC64 2022 2022-06-06 TURB 1.0647107370 #> 8284 2063 3M CC64 2022 2022-07-05 CHLAC 1.6292405397 #> 8285 2063 3M CC64 2022 2022-07-05 COLOR 2.8903717579 #> 8286 2063 3M CC64 2022 2022-07-05 NO23 -5.2983173665 I #> 8287 2063 3M CC64 2022 2022-07-05 SALIN 3.2534704696 #> 8288 2063 3M CC64 2022 2022-07-05 TKN -0.5447271754 #> 8289 2063 3M CC64 2022 2022-07-05 TN -0.5378542962 + #> 8290 2063 3M CC64 2022 2022-07-05 TP -2.1202635362 #> 8291 2063 3M CC64 2022 2022-07-05 TURB 0.0953101798 #> 8292 2063 3M 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3M CC64 2022 2022-09-06 TP -1.8325814637 #> 8311 2063 3M CC64 2022 2022-09-06 TURB 0.7419373447 #> 8312 2063 3M CC64 2022 2022-11-07 CHLAC 0.8754687374 I #> 8313 2063 3M CC64 2022 2022-11-07 COLOR 4.2341065046 #> 8314 2063 3M CC64 2022 2022-11-07 DO 0.9360933592 #> 8315 2063 3M CC64 2022 2022-11-07 DOSAT 3.5263605246 #> 8316 2063 3M CC64 2022 2022-11-07 NO23 -3.2968373663 #> 8317 2063 3M CC64 2022 2022-11-07 SALIN 2.6049094422 #> 8318 2063 3M CC64 2022 2022-11-07 TKN -0.2744368457 #> 8319 2063 3M CC64 2022 2022-11-07 TN -0.2269006002 + #> 8320 2063 3M CC64 2022 2022-11-07 TP -1.7147984281 #> 8321 2063 3M CC64 2022 2022-11-07 TURB 0.1823215568 #> 8322 2063 3M CC64 2022 2022-12-05 CHLAC 1.0296194172 #> 8323 2063 3M CC64 2022 2022-12-05 COLOR 3.6109179126 #> 8324 2063 3M CC64 2022 2022-12-05 DO 1.3190856114 #> 8325 2063 3M CC64 2022 2022-12-05 DOSAT 3.8918202981 #> 8326 2063 3M CC64 2022 2022-12-05 NO23 -2.8647040111 #> 8327 2063 3M CC64 2022 2022-12-05 SALIN 2.9992261628 #> 8328 2063 3M CC64 2022 2022-12-05 TKN -0.4004775666 #> 8329 2063 3M CC64 2022 2022-12-05 TN -0.3188288014 + #> 8330 2063 3M CC64 2022 2022-12-05 TP -1.7719568419 #> 8331 2063 3M CC64 2022 2022-12-05 TURB 1.0296194172 #> 8332 2063 3M CC64 2023 2023-01-03 CHLAC 1.3083328197 #> 8333 2063 3M CC64 2023 2023-01-03 COLOR 2.7080502011 #> 8334 2063 3M CC64 2023 2023-01-03 DO 1.6524974019 #> 8335 2063 3M CC64 2023 2023-01-03 DOSAT 3.6133473915 #> 8336 2063 3M CC64 2023 2023-01-03 NO23 -3.2188758249 #> 8337 2063 3M CC64 2023 2023-01-03 SALIN 3.1582762027 #> 8338 2063 3M CC64 2023 2023-01-03 TKN -0.7133498879 #> 8339 2063 3M CC64 2023 2023-01-03 TN -0.6348782724 + #> 8340 2063 3M CC64 2023 2023-01-03 TP -1.9661128564 #> 8341 2063 3M CC64 2023 2023-01-03 TURB 0.2623642645 #> 8342 2063 3M CC64 2023 2023-02-06 CHLAC 1.0986122887 #> 8343 2063 3M CC64 2023 2023-02-06 COLOR 2.7725887222 #> 8344 2063 3M CC64 2023 2023-02-06 DO 1.4586150227 #> 8345 2063 3M CC64 2023 2023-02-06 DOSAT 4.0430512678 #> 8346 2063 3M CC64 2023 2023-02-06 NO23 -4.2686979494 #> 8347 2063 3M CC64 2023 2023-02-06 SALIN 3.2284300377 #> 8348 2063 3M CC64 2023 2023-02-06 TKN -0.4942963218 #> 8349 2063 3M CC64 2023 2023-02-06 TN -0.4716049106 + #> 8350 2063 3M CC64 2023 2023-02-06 TP -2.0402208285 #> 8351 2063 3M CC64 2023 2023-02-06 TURB 0.6418538862 #> 8352 2063 3M CC64 2023 2023-03-06 CHLAC 0.9932517730 #> 8353 2063 3M CC64 2023 2023-03-06 COLOR 2.7725887222 #> 8354 2063 3M CC64 2023 2023-03-06 DO 1.3962446920 #> 8355 2063 3M CC64 2023 2023-03-06 DOSAT 4.0758410907 #> 8356 2063 3M CC64 2023 2023-03-06 NO23 -4.9618451299 I #> 8357 2063 3M CC64 2023 2023-03-06 SALIN 3.3170908724 #> 8358 2063 3M CC64 2023 2023-03-06 TKN -0.6161861394 #> 8359 2063 3M CC64 2023 2023-03-06 TN -0.6088060321 + #> 8360 2063 3M CC64 2023 2023-03-06 TP -2.0402208285 #> 8361 2063 3M CC64 2023 2023-03-06 TURB 0.8754687374 #> 8362 2063 3M CC64 2014 2014-01-07 CHLAC 1.0986122887 #> 8363 2063 3M CC64 2014 2014-01-07 TN -0.9942522733 #> 8364 2063 3M CC64 2014 2014-01-07 TP -2.5510464523 #> 8365 2063 3M CC64 2014 2014-02-04 CHLAC 0.0000000000 #> 8366 2063 3M CC64 2014 2014-02-04 TN -1.0498221245 #> 8367 2063 3M CC64 2014 2014-02-04 TP -2.6310891600 #> 8368 2063 3M CC64 2014 2014-03-04 CHLAC 1.3862943611 #> 8369 2063 3M CC64 2014 2014-03-04 TN -0.5978370008 #> 8370 2063 3M CC64 2014 2014-03-04 TP -2.7333680091 #> 8371 2063 3M CC64 2014 2014-04-01 CHLAC 1.0986122887 #> 8372 2063 3M CC64 2014 2014-04-01 TN -1.0788096614 #> 8373 2063 3M CC64 2014 2014-04-01 TP -2.7181005370 #> 8374 2063 3M CC64 2014 2014-06-03 CHLAC 1.3862943611 #> 8375 2063 3M CC64 2014 2014-06-03 TN -0.5798184953 #> 8376 2063 3M CC64 2014 2014-06-03 TP -2.2072749132 #> 8377 2063 3M CC64 2014 2014-09-02 CHLAC 3.1354942159 #> 8378 2063 3M CC64 2014 2014-09-02 TP -2.3126354288 #> 8379 2063 3M CC64 2014 2014-11-04 CHLAC 0.6931471806 #> 8380 2063 3M CC64 2014 2014-11-04 TN -0.5798184953 #> 8381 2063 3M CC64 2014 2014-11-04 TP -2.6310891600 #> 8382 2063 3M CC64 2014 2014-12-02 CHLAC 0.0000000000 #> 8383 2063 3M CC64 2014 2014-12-02 TN -0.4942963218 #> 8384 2063 3M CC64 2014 2014-12-02 TP -2.3751557858 #> 8385 2063 3M CC64 2015 2015-01-03 CHLAC 0.0000000000 #> 8386 2063 3M CC64 2015 2015-01-03 TN -0.3011050928 #> 8387 2063 3M CC64 2015 2015-01-03 TP -1.8018098051 #> 8388 2063 3M CC64 2015 2015-02-02 CHLAC 0.6931471806 #> 8389 2063 3M CC64 2015 2015-03-03 CHLAC 0.0000000000 #> 8390 2063 3M CC64 2015 2015-03-03 TN -0.5798184953 #> 8391 2063 3M CC64 2015 2015-03-03 TP -2.2730262908 #> 8392 2063 3M CC64 2015 2015-04-02 CHLAC 0.6931471806 #> 8393 2063 3M CC64 2015 2015-04-02 TN -0.4462871026 #> 8394 2063 3M CC64 2015 2015-04-02 TP -2.2926347621 #> 8395 2063 3M CC64 2015 2015-05-05 CHLAC 1.0986122887 #> 8396 2063 3M CC64 2015 2015-05-05 TN -0.8209805521 #> 8397 2063 3M CC64 2015 2015-05-05 TP -2.5257286443 #> 8398 2063 3M CC64 2015 2015-09-09 CHLAC 1.0986122887 #> 8399 2063 3M CC64 2015 2015-09-09 TN -0.5978370008 #> 8400 2063 3M CC64 2015 2015-09-09 TP -2.9759296463 #> 8401 2063 3M CC64 2015 2015-10-07 CHLAC 1.6094379124 #> 8402 2063 3M CC64 2015 2015-11-04 CHLAC 1.0986122887 #> 8403 2063 3M CC64 2015 2015-11-04 TN -0.6539264674 #> 8404 2063 3M CC64 2015 2015-11-04 TP -2.6172958378 #> 8405 2063 3M CC64 2015 2015-11-15 CHLAC 1.6094379124 #> 8406 2063 3M CC64 2015 2015-11-15 TN -0.8439700703 #> 8407 2063 3M CC64 2015 2015-11-15 TP -2.7968814148 #> 8408 2063 3M CC64 2016 2016-01-06 TN -0.1053605157 #> 8409 2063 3M CC64 2016 2016-01-06 TP -2.3126354288 #> 8410 2063 3M CC64 2016 2016-02-02 CHLAC 1.6094379124 #> 8411 2063 3M CC64 2016 2016-02-02 TN -0.2231435513 #> 8412 2063 3M CC64 2016 2016-02-02 TP -2.9957322736 #> 8413 2063 3M CC64 2016 2016-06-11 CHLAC 2.5649493575 #> 8414 2063 3M CC64 2016 2016-06-11 TN -0.8439700703 #> 8415 2063 3M CC64 2016 2016-06-11 TP -2.7488721956 #> 8416 2063 3M CC64 2016 2016-07-08 CHLAC 1.0986122887 #> 8417 2063 3M CC64 2016 2016-07-08 TN -0.7765287895 #> 8418 2063 3M CC64 2016 2016-07-08 TP -3.7722610631 #> 8419 2063 3M CC64 2016 2016-10-03 CHLAC 1.0986122887 #> 8420 2063 3M CC64 2016 2016-10-03 TN -0.2231435513 #> 8421 2063 3M CC64 2016 2016-10-03 TP -2.0874737134 #> 8422 2063 3M CC64 2018 2018-12-04 CHLAC 1.0986122887 #> 8423 2063 3M CC64 2018 2018-12-04 TN -0.7985076962 #> 8424 2063 3M CC64 2018 2018-12-04 TP -2.3644604967 #> 8425 2063 3M CC64 2019 2019-01-09 CHLAC 0.6931471806 I #> 8426 2063 3M CC64 2019 2019-01-09 TN -1.2039728043 #> 8427 2063 3M CC64 2019 2019-01-09 TP -2.7333680091 #> 8428 2065B 2 CC67 2015 2015-04-07 CHLAC 0.6931471806 #> 8429 2065B 2 CC67 2015 2015-04-07 COLOR 3.4011973817 #> 8430 2065B 2 CC67 2015 2015-04-07 COND 10.6960274770 #> 8431 2065B 2 CC67 2015 2015-04-07 DO 1.8164520818 #> 8432 2065B 2 CC67 2015 2015-04-07 DOSAT 4.4931206822 + #> 8433 2065B 2 CC67 2015 2015-04-07 NO23 -5.1159958098 I #> 8434 2065B 2 CC67 2015 2015-04-07 SALIN 3.3492020865 #> 8435 2065B 2 CC67 2015 2015-04-07 TKN -0.2587707290 #> 8436 2065B 2 CC67 2015 2015-04-07 TN -0.2510287548 #> 8437 2065B 2 CC67 2015 2015-04-07 TP -2.4079456087 #> 8438 2065B 2 CC67 2015 2015-04-07 TSS 2.2257040487 #> 8439 2065B 2 CC67 2015 2015-04-07 TURB 0.2623642645 #> 8440 2065B 2 CC67 2015 2015-04-07 COND 10.6958011046 #> 8441 2065B 2 CC67 2015 2015-04-07 DO 1.8033586051 #> 8442 2065B 2 CC67 2015 2015-04-07 DOSAT 4.4796069630 + #> 8443 2065B 2 CC67 2015 2015-04-07 SALIN 3.3488509013 #> 8444 2065B 2 CC67 2015 2015-11-03 CHLAC 2.0476928434 #> 8445 2065B 2 CC67 2015 2015-11-03 COLOR 4.0073331852 #> 8446 2065B 2 CC67 2015 2015-11-03 COND 10.5339611386 #> 8447 2065B 2 CC67 2015 2015-11-03 DO 2.0731719287 #> 8448 2065B 2 CC67 2015 2015-11-03 DOSAT 4.7723781050 + #> 8449 2065B 2 CC67 2015 2015-11-03 NO23 -5.5214609179 U #> 8450 2065B 2 CC67 2015 2015-11-03 SALIN 3.1658969001 #> 8451 2065B 2 CC67 2015 2015-11-03 TKN -0.4557063245 #> 8452 2065B 2 CC67 2015 2015-11-03 TN -0.4557063245 #> 8453 2065B 2 CC67 2015 2015-11-03 TP -2.0557250151 #> 8454 2065B 2 CC67 2015 2015-11-03 TSS 1.7369512327 #> 8455 2065B 2 CC67 2015 2015-11-03 TURB -0.3566749439 #> 8456 2065B 2 CC67 2015 2015-11-03 COND 10.5312958918 #> 8457 2065B 2 CC67 2015 2015-11-03 DO 2.0955609236 #> 8458 2065B 2 CC67 2015 2015-11-03 DOSAT 4.7966166506 + #> 8459 2065B 2 CC67 2015 2015-11-03 SALIN 3.1629401925 #> 8460 2065B 2 CC67 2017 2017-04-05 CHLAC -0.0502412164 I #> 8461 2065B 2 CC67 2017 2017-04-05 COND 10.7904503955 #> 8462 2065B 2 CC67 2017 2017-04-05 DO 1.9586853405 #> 8463 2065B 2 CC67 2017 2017-04-05 DOSAT 4.6653241088 + #> 8464 2065B 2 CC67 2017 2017-04-05 NO23 -4.8283137373 I #> 8465 2065B 2 CC67 2017 2017-04-05 SALIN 3.4541060373 #> 8466 2065B 2 CC67 2017 2017-04-05 TKN -0.4261781497 #> 8467 2065B 2 CC67 2017 2017-04-05 TN -0.4140014391 #> 8468 2065B 2 CC67 2017 2017-04-05 TP -2.7030626596 #> 8469 2065B 2 CC67 2017 2017-04-05 TSS 2.1972245773 #> 8470 2065B 2 CC67 2017 2017-04-05 TURB 0.0000000000 #> 8471 2065B 2 CC67 2017 2017-04-05 COND 10.7904771690 #> 8472 2065B 2 CC67 2017 2017-04-05 DO 1.9699056546 #> 8473 2065B 2 CC67 2017 2017-04-05 DOSAT 4.6784206477 + #> 8474 2065B 2 CC67 2017 2017-04-05 SALIN 3.4541060373 #> 8475 2065B 2 CC67 2017 2017-04-05 COND 10.7905760186 #> 8476 2065B 2 CC67 2017 2017-04-05 DO 1.9712993831 #> 8477 2065B 2 CC67 2017 2017-04-05 DOSAT 4.6802776585 + #> 8478 2065B 2 CC67 2017 2017-04-05 SALIN 3.4541060373 #> 8479 2065B 2 CC67 2017 2017-04-05 COND 10.7905821964 #> 8480 2065B 2 CC67 2017 2017-04-05 DO 1.9726911717 #> 8481 2065B 2 CC67 2017 2017-04-05 DOSAT 4.6812048723 + #> 8482 2065B 2 CC67 2017 2017-04-05 SALIN 3.4541060373 #> 8483 2065B 2 CC67 2017 2017-06-05 CHLAC 1.3686394259 #> 8484 2065B 2 CC67 2017 2017-06-05 NO23 -4.1351665567 #> 8485 2065B 2 CC67 2017 2017-06-05 TKN -0.2600669054 #> 8486 2065B 2 CC67 2017 2017-06-05 TN -0.2395270306 #> 8487 2065B 2 CC67 2017 2017-06-05 TP -2.5770219387 #> 8488 2065B 2 CC67 2017 2017-06-05 TSS 2.4595888418 #> 8489 2065B 2 CC67 2017 2017-06-05 TURB 0.0000000000 #> 8490 2065B 2 CC67 2017 2017-06-05 COND 10.8045448425 #> 8491 2065B 2 CC67 2017 2017-06-05 DO 1.6134299337 #> 8492 2065B 2 CC67 2017 2017-06-05 DOSAT 4.3592696476 + #> 8493 2065B 2 CC67 2017 2017-06-05 SALIN 3.4679210137 #> 8494 2065B 2 CC67 2017 2017-06-05 COND 10.8049143616 #> 8495 2065B 2 CC67 2017 2017-06-05 DO 1.6524974019 #> 8496 2065B 2 CC67 2017 2017-06-05 DOSAT 4.3981460166 + #> 8497 2065B 2 CC67 2017 2017-06-05 SALIN 3.4682327830 #> 8498 2065B 2 CC67 2017 2017-06-05 COND 10.8052533058 #> 8499 2065B 2 CC67 2017 2017-06-05 DO 1.6677068206 #> 8500 2065B 2 CC67 2017 2017-06-05 DOSAT 4.4140096805 + #> 8501 2065B 2 CC67 2017 2017-06-05 SALIN 3.4685444551 #> 8502 2065B 2 CC67 2017 2017-08-15 CHLAC 2.7850112422 #> 8503 2065B 2 CC67 2017 2017-08-15 COND 10.0070409363 #> 8504 2065B 2 CC67 2017 2017-08-15 DO 1.7474592103 #> 8505 2065B 2 CC67 2017 2017-08-15 DOSAT 4.4693504628 + #> 8506 2065B 2 CC67 2017 2017-08-15 NO23 -3.2968373663 #> 8507 2065B 2 CC67 2017 2017-08-15 SALIN 2.5794589667 #> 8508 2065B 2 CC67 2017 2017-08-15 TKN 0.0953101798 #> 8509 2065B 2 CC67 2017 2017-08-15 TN 0.1310282624 #> 8510 2065B 2 CC67 2017 2017-08-15 TP -1.0555527992 #> 8511 2065B 2 CC67 2017 2017-08-15 TSS 0.8458682676 #> 8512 2065B 2 CC67 2017 2017-08-15 TURB 0.6931471806 #> 8513 2065B 2 CC67 2017 2017-08-15 COND 10.1682757999 #> 8514 2065B 2 CC67 2017 2017-08-15 DO 0.5822156199 #> 8515 2065B 2 CC67 2017 2017-08-15 DOSAT 3.2771447330 + #> 8516 2065B 2 CC67 2017 2017-08-15 SALIN 2.7593768283 #> 8517 2065B 2 CC67 2017 2017-08-15 COND 10.1784604545 #> 8518 2065B 2 CC67 2017 2017-08-15 DO 0.5306282511 #> 8519 2065B 2 CC67 2017 2017-08-15 DOSAT 3.2268439945 + #> 8520 2065B 2 CC67 2017 2017-08-15 SALIN 2.7707119622 #> 8521 2065B 2 CC67 2018 2018-04-09 CHLAC 0.8109302162 #> 8522 2065B 2 CC67 2018 2018-04-09 COND 10.7756173069 #> 8523 2065B 2 CC67 2018 2018-04-09 DO 1.9387416596 #> 8524 2065B 2 CC67 2018 2018-04-09 DOSAT 4.6395716127 + #> 8525 2065B 2 CC67 2018 2018-04-09 NO23 -4.8283137373 I #> 8526 2065B 2 CC67 2018 2018-04-09 SALIN 3.4375293109 #> 8527 2065B 2 CC67 2018 2018-04-09 TKN -0.3945251681 #> 8528 2065B 2 CC67 2018 2018-04-09 TN -0.3827256211 #> 8529 2065B 2 CC67 2018 2018-04-09 TP -2.5902671654 #> 8530 2065B 2 CC67 2018 2018-04-09 TSS 1.4816045409 #> 8531 2065B 2 CC67 2018 2018-04-09 TURB 0.0953101798 #> 8532 2065B 2 CC67 2018 2018-04-09 COND 10.7754082549 #> 8533 2065B 2 CC67 2018 2018-04-09 DO 1.9473377010 #> 8534 2065B 2 CC67 2018 2018-04-09 DOSAT 4.6482296754 + #> 8535 2065B 2 CC67 2018 2018-04-09 SALIN 3.4375293109 #> 8536 2065B 2 CC67 2018 2018-04-09 COND 10.7754082549 #> 8537 2065B 2 CC67 2018 2018-04-09 DO 1.9487632180 #> 8538 2065B 2 CC67 2018 2018-04-09 DOSAT 4.6501435516 + #> 8539 2065B 2 CC67 2018 2018-04-09 SALIN 3.4375293109 #> 8540 2065B 2 CC67 2018 2018-05-23 CHLAC 1.1216775616 #> 8541 2065B 2 CC67 2018 2018-05-23 COND 10.7435212354 #> 8542 2065B 2 CC67 2018 2018-05-23 DO 1.8885836539 #> 8543 2065B 2 CC67 2018 2018-05-23 DOSAT 4.5910712616 + #> 8544 2065B 2 CC67 2018 2018-05-23 NO23 -4.6051701860 I #> 8545 2065B 2 CC67 2018 2018-05-23 SALIN 3.4011973817 #> 8546 2065B 2 CC67 2018 2018-05-23 TKN -0.1696027844 #> 8547 2065B 2 CC67 2018 2018-05-23 TN -0.1578240852 #> 8548 2065B 2 CC67 2018 2018-05-23 TP -2.0794415417 #> 8549 2065B 2 CC67 2018 2018-05-23 TSS 1.5686159179 #> 8550 2065B 2 CC67 2018 2018-05-23 TURB 1.0647107370 #> 8551 2065B 2 CC67 2018 2018-05-23 DOSAT 4.6793495842 + #> 8552 2065B 2 CC67 2018 2018-05-23 COND 10.7527727226 #> 8553 2065B 2 CC67 2018 2018-05-23 DO 1.9782390362 #> 8554 2065B 2 CC67 2018 2018-05-23 SALIN 3.4118075608 #> 8555 2065B 2 CC67 2018 2018-10-11 CHLAC 1.4109869737 #> 8556 2065B 2 CC67 2018 2018-10-11 COND 10.5316641186 #> 8557 2065B 2 CC67 2018 2018-10-11 DO 1.6467336972 #> 8558 2065B 2 CC67 2018 2018-10-11 DOSAT 4.3148178850 + #> 8559 2065B 2 CC67 2018 2018-10-11 NO23 -4.9618451299 I #> 8560 2065B 2 CC67 2018 2018-10-11 SALIN 3.1654750481 #> 8561 2065B 2 CC67 2018 2018-10-11 TKN -0.1960148839 #> 8562 2065B 2 CC67 2018 2018-10-11 TN -0.1875351238 #> 8563 2065B 2 CC67 2018 2018-10-11 TP -2.1202635362 #> 8564 2065B 2 CC67 2018 2018-10-11 TSS 1.8453002362 #> 8565 2065B 2 CC67 2018 2018-10-11 TURB 0.6931471806 #> 8566 2065B 2 CC67 2018 2018-10-11 COND 10.5317548204 #> 8567 2065B 2 CC67 2018 2018-10-11 DO 1.6448050563 #> 8568 2065B 2 CC67 2018 2018-10-11 DOSAT 4.3121405072 + #> 8569 2065B 2 CC67 2018 2018-10-11 SALIN 3.1654750481 #> 8570 2065B 2 CC67 2018 2018-10-11 COND 10.5326214074 #> 8571 2065B 2 CC67 2018 2018-10-11 DO 1.6370530795 #> 8572 2065B 2 CC67 2018 2018-10-11 DOSAT 4.3054155323 + #> 8573 2065B 2 CC67 2018 2018-10-11 SALIN 3.1663185741 #> 8574 2065B 2 CC67 2019 2019-03-05 CHLAC 1.6094379124 #> 8575 2065B 2 CC67 2019 2019-03-05 COND 10.4627604245 #> 8576 2065B 2 CC67 2019 2019-03-05 DO 1.8325814637 #> 8577 2065B 2 CC67 2019 2019-03-05 DOSAT 4.5163389723 + #> 8578 2065B 2 CC67 2019 2019-03-05 NO23 -5.1159958098 U #> 8579 2065B 2 CC67 2019 2019-03-05 SALIN 3.5550051456 #> 8580 2065B 2 CC67 2019 2019-03-05 TKN -0.2691874898 #> 8581 2065B 2 CC67 2019 2019-03-05 TN -0.2691874898 #> 8582 2065B 2 CC67 2019 2019-03-05 TP -2.3644604967 #> 8583 2065B 2 CC67 2019 2019-03-05 TSS 1.9919755159 #> 8584 2065B 2 CC67 2019 2019-03-05 TURB 0.8754687374 #> 8585 2065B 2 CC67 2019 2019-03-05 COND 10.4628461645 #> 8586 2065B 2 CC67 2019 2019-03-05 DO 1.8309801824 #> 8587 2065B 2 CC67 2019 2019-03-05 DOSAT 4.5152454785 + #> 8588 2065B 2 CC67 2019 2019-03-05 SALIN 3.5550908856 #> 8589 2065B 2 CC67 2019 2019-03-05 COND 10.4631604817 #> 8590 2065B 2 CC67 2019 2019-03-05 DO 1.8277699068 #> 8591 2065B 2 CC67 2019 2019-03-05 DOSAT 4.5119578043 + #> 8592 2065B 2 CC67 2019 2019-03-05 SALIN 3.5554052027 #> 8593 2065B 2 CC67 2020 2020-01-15 COND 10.6506753751 #> 8594 2065B 2 CC67 2020 2020-01-15 DO 2.0592388344 #> 8595 2065B 2 CC67 2020 2020-01-15 DOSAT 4.6737629775 + #> 8596 2065B 2 CC67 2020 2020-01-15 NO23 -5.1159958098 U #> 8597 2065B 2 CC67 2020 2020-01-15 SALIN 3.3010086544 #> 8598 2065B 2 CC67 2020 2020-01-15 TKN -0.4109802888 #> 8599 2065B 2 CC67 2020 2020-01-15 TN -0.4109802888 #> 8600 2065B 2 CC67 2020 2020-01-15 TP -2.4304184645 #> 8601 2065B 2 CC67 2020 2020-01-15 TSS 1.4816045409 #> 8602 2065B 2 CC67 2020 2020-01-15 TURB 0.0000000000 #> 8603 2065B 2 CC67 2020 2020-01-15 COND 10.6625933392 #> 8604 2065B 2 CC67 2020 2020-01-15 DO 2.0630580624 #> 8605 2065B 2 CC67 2020 2020-01-15 DOSAT 4.6756286496 + #> 8606 2065B 2 CC67 2020 2020-01-15 SALIN 3.3141860047 #> 8607 2065B 2 CC67 2020 2020-02-11 COND 10.6620033783 #> 8608 2065B 2 CC67 2020 2020-02-11 NO23 -5.1159958098 U #> 8609 2065B 2 CC67 2020 2020-02-11 SALIN 3.3141860047 #> 8610 2065B 2 CC67 2020 2020-02-11 TKN -0.3538218750 #> 8611 2065B 2 CC67 2020 2020-02-11 TN -0.3495574762 + #> 8612 2065B 2 CC67 2020 2020-02-11 TP -2.6036901858 #> 8613 2065B 2 CC67 2020 2020-02-11 TSS 1.2029723040 #> 8614 2065B 2 CC67 2020 2020-02-11 TURB -0.2613647641 #> 8615 2065B 2 CC67 2020 2020-02-11 COND 10.6633887669 #> 8616 2065B 2 CC67 2020 2020-02-11 SALIN 3.3156394933 #> 8617 2065B 2 CC67 2020 2020-11-04 COND 10.4405071004 #> 8618 2065B 2 CC67 2020 2020-11-04 DO 1.8033586051 #> 8619 2065B 2 CC67 2020 2020-11-04 DOSAT 4.3782695858 + #> 8620 2065B 2 CC67 2020 2020-11-04 NO23 -5.1159958098 U #> 8621 2065B 2 CC67 2020 2020-11-04 SALIN 3.0685179433 #> 8622 2065B 2 CC67 2020 2020-11-04 TKN -0.9808292530 #> 8623 2065B 2 CC67 2020 2020-11-04 TN -0.9808292530 #> 8624 2065B 2 CC67 2020 2020-11-04 TP -1.9173226922 #> 8625 2065B 2 CC67 2020 2020-11-04 TSS 3.3322045102 #> 8626 2065B 2 CC67 2020 2020-11-04 TURB 0.5306282511 #> 8627 2065B 2 CC67 2020 2020-11-04 COND 10.4404486499 #> 8628 2065B 2 CC67 2020 2020-11-04 DO 1.8000582720 #> 8629 2065B 2 CC67 2020 2020-11-04 DOSAT 4.3744983683 + #> 8630 2065B 2 CC67 2020 2020-11-04 SALIN 3.0685179433 #> 8631 2065B 2 CC67 2020 2020-11-04 COND 10.4404778756 #> 8632 2065B 2 CC67 2020 2020-11-04 DO 1.7984040119 #> 8633 2065B 2 CC67 2020 2020-11-04 DOSAT 4.3732381286 + #> 8634 2065B 2 CC67 2020 2020-11-04 SALIN 3.0685179433 #> 8635 2065B 2 CC67 2021 2021-05-17 COND 10.7266756661 #> 8636 2065B 2 CC67 2021 2021-05-17 DO 1.8976198599 #> 8637 2065B 2 CC67 2021 2021-05-17 DOSAT 4.5859873666 + #> 8638 2065B 2 CC67 2021 2021-05-17 NO23 -5.1159958098 U #> 8639 2065B 2 CC67 2021 2021-05-17 SALIN 3.3830334110 #> 8640 2065B 2 CC67 2021 2021-05-17 TKN -0.6520052372 #> 8641 2065B 2 CC67 2021 2021-05-17 TN -0.6520052372 #> 8642 2065B 2 CC67 2021 2021-05-17 TP -2.2926347621 #> 8643 2065B 2 CC67 2021 2021-05-17 TSS 2.7343675094 #> 8644 2065B 2 CC67 2021 2021-05-17 TURB -0.4416105547 #> 8645 2065B 2 CC67 2021 2021-05-17 COND 10.7266317622 #> 8646 2065B 2 CC67 2021 2021-05-17 DO 1.9110228901 #> 8647 2065B 2 CC67 2021 2021-05-17 DOSAT 4.5991521137 + #> 8648 2065B 2 CC67 2021 2021-05-17 SALIN 3.3830334110 #> 8649 2065B 2 CC67 2021 2021-05-17 COND 10.7261267283 #> 8650 2065B 2 CC67 2021 2021-05-17 DO 1.9110228901 #> 8651 2065B 2 CC67 2021 2021-05-17 DOSAT 4.5991521137 + #> 8652 2065B 2 CC67 2021 2021-05-17 SALIN 3.3823542939 #> 8653 2081 3F CC67 2016 2016-04-27 CHLAC 1.7404661748 #> 8654 2081 3F CC67 2016 2016-04-27 COLOR 4.2046926194 #> 8655 2081 3F CC67 2016 2016-04-27 COND 6.3135480463 #> 8656 2081 3F CC67 2016 2016-04-27 DO 2.0918640617 #> 8657 2081 3F CC67 2016 2016-04-27 DOSAT 4.5849674787 #> 8658 2081 3F CC67 2016 2016-04-27 NO23 -4.3428059215 #> 8659 2081 3F CC67 2016 2016-04-27 SALIN -1.3093333200 + #> 8660 2081 3F CC67 2016 2016-04-27 TKN -0.1625189295 #> 8661 2081 3F CC67 2016 2016-04-27 TN -0.1473405879 + #> 8662 2081 3F CC67 2016 2016-04-27 TP -2.9187712324 #> 8663 2081 3F CC67 2016 2016-04-27 TSS 1.0986122887 I #> 8664 2081 3F CC67 2016 2016-04-27 TURB 1.8870696490 #> 8665 2081 3F CC67 2016 2016-09-21 CHLAC 2.2082744135 A #> 8666 2081 3F CC67 2016 2016-09-21 COLOR 4.9416424226 #> 8667 2081 3F CC67 2016 2016-09-21 COND 5.8636311756 #> 8668 2081 3F CC67 2016 2016-09-21 DO 1.7227665977 #> 8669 2081 3F CC67 2016 2016-09-21 DOSAT 4.3040650932 #> 8670 2081 3F CC67 2016 2016-09-21 NO23 -2.9565115604 #> 8671 2081 3F CC67 2016 2016-09-21 SALIN -1.6094379124 #> 8672 2081 3F CC67 2016 2016-09-21 TKN -0.1863295782 #> 8673 2081 3F CC67 2016 2016-09-21 TN -0.1255632230 + #> 8674 2081 3F CC67 2016 2016-09-21 TP -2.3025850930 #> 8675 2081 3F CC67 2016 2016-09-21 TSS 2.8332133441 #> 8676 2081 3F CC67 2016 2016-09-21 TURB 2.3025850930 #> 8677 2081 3F CC67 2016 2016-12-13 CHLAC 0.5306282511 I #> 8678 2081 3F CC67 2016 2016-12-13 COLOR 4.0253516907 #> 8679 2081 3F CC67 2016 2016-12-13 COND 6.2709884319 #> 8680 2081 3F CC67 2016 2016-12-13 DO 2.1860512767 #> 8681 2081 3F CC67 2016 2016-12-13 DOSAT 4.5951198501 #> 8682 2081 3F CC67 2016 2016-12-13 NO23 -1.8971199849 #> 8683 2081 3F CC67 2016 2016-12-13 SALIN -1.6094379124 #> 8684 2081 3F CC67 2016 2016-12-13 TKN -0.4942963218 #> 8685 2081 3F CC67 2016 2016-12-13 TN -0.2744368457 + #> 8686 2081 3F CC67 2016 2016-12-13 TP -2.9759296463 #> 8687 2081 3F CC67 2016 2016-12-13 TSS 1.3862943611 I #> 8688 2081 3F CC67 2016 2016-12-13 TURB 1.6486586256 #> 8689 2081 3F CC67 2016 2016-12-28 CHLAC 1.0296194172 #> 8690 2081 3F CC67 2016 2016-12-28 COLOR 4.1896547420 A #> 8691 2081 3F CC67 2016 2016-12-28 COND 6.2747620212 #> 8692 2081 3F CC67 2016 2016-12-28 NO23 -2.2072749132 #> 8693 2081 3F CC67 2016 2016-12-28 SALIN -1.3093333200 + #> 8694 2081 3F CC67 2016 2016-12-28 TKN -0.4004775666 #> 8695 2081 3F CC67 2016 2016-12-28 TN -0.2484613593 + #> 8696 2081 3F CC67 2016 2016-12-28 TP -2.6882475738 #> 8697 2081 3F CC67 2016 2016-12-28 TSS 1.7917594692 I #> 8698 2081 3F CC67 2016 2016-12-28 TURB 1.9878743482 A #> 8699 2081 3F CC67 2017 2017-07-26 CHLAC 2.3025850930 #> 8700 2081 3F CC67 2017 2017-07-26 COLOR 5.3471075307 #> 8701 2081 3F CC67 2017 2017-07-26 COND 5.8435444170 #> 8702 2081 3F CC67 2017 2017-07-26 DO 1.6486586256 #> 8703 2081 3F CC67 2017 2017-07-26 DOSAT 4.2626798770 #> 8704 2081 3F CC67 2017 2017-07-26 NO23 -3.3813947544 #> 8705 2081 3F CC67 2017 2017-07-26 TKN 0.0953101798 #> 8706 2081 3F CC67 2017 2017-07-26 TN 0.1257512053 + #> 8707 2081 3F CC67 2017 2017-07-26 TP -2.4191189092 #> 8708 2081 3F CC67 2017 2017-07-26 TSS 2.4849066498 #> 8709 2081 3F CC67 2017 2017-07-26 TURB 1.9315214116 #> 8710 2081 3F CC67 2017 2017-08-21 CHLAC 1.4350845253 #> 8711 2081 3F CC67 2017 2017-08-21 COLOR 4.7874917428 #> 8712 2081 3F CC67 2017 2017-08-21 COND 6.0497334552 #> 8713 2081 3F CC67 2017 2017-08-21 DO 1.9169226122 #> 8714 2081 3F CC67 2017 2017-08-21 DOSAT 4.5108595065 #> 8715 2081 3F CC67 2017 2017-08-21 NO23 -2.9957322736 #> 8716 2081 3F CC67 2017 2017-08-21 TKN -0.1984509387 #> 8717 2081 3F CC67 2017 2017-08-21 TN -0.1392620673 + #> 8718 2081 3F CC67 2017 2017-08-21 TP -2.7488721956 #> 8719 2081 3F CC67 2017 2017-08-21 TSS 2.3025850930 I #> 8720 2081 3F CC67 2017 2017-08-21 TURB 1.9740810260 A #> 8721 2081 3F CC67 2017 2017-10-04 CHLAC 2.0014800002 #> 8722 2081 3F CC67 2017 2017-10-04 COLOR 4.7874917428 #> 8723 2081 3F CC67 2017 2017-10-04 COND 5.9188938543 #> 8724 2081 3F CC67 2017 2017-10-04 DO 1.8718021769 #> 8725 2081 3F CC67 2017 2017-10-04 DOSAT 4.3944491547 #> 8726 2081 3F CC67 2017 2017-10-04 NO23 -3.1235656451 #> 8727 2081 3F CC67 2017 2017-10-04 SALIN -1.7719568419 + #> 8728 2081 3F CC67 2017 2017-10-04 TKN -0.2231435513 #> 8729 2081 3F CC67 2017 2017-10-04 TN -0.1696027844 + #> 8730 2081 3F CC67 2017 2017-10-04 TP -2.7488721956 #> 8731 2081 3F CC67 2017 2017-10-04 TSS 2.0794415417 I #> 8732 2081 3F CC67 2017 2017-10-04 TURB 1.6486586256 A #> 8733 2081 3F CC67 2017 2017-11-08 CHLAC 1.7404661748 #> 8734 2081 3F CC67 2017 2017-11-08 COLOR 4.2341065046 #> 8735 2081 3F CC67 2017 2017-11-08 COND 6.1377270541 #> 8736 2081 3F CC67 2017 2017-11-08 DO 2.1747517215 #> 8737 2081 3F CC67 2017 2017-11-08 DOSAT 4.6634390941 #> 8738 2081 3F CC67 2017 2017-11-08 NO23 -2.7030626596 #> 8739 2081 3F CC67 2017 2017-11-08 SALIN -1.4696759701 + #> 8740 2081 3F CC67 2017 2017-11-08 TKN -0.4942963218 #> 8741 2081 3F CC67 2017 2017-11-08 TN -0.3900840061 + #> 8742 2081 3F CC67 2017 2017-11-08 TP -3.1235656451 #> 8743 2081 3F CC67 2017 2017-11-08 TSS 1.0986122887 I #> 8744 2081 3F CC67 2017 2017-11-08 TURB 1.5686159179 #> 8745 2081 3F CC67 2017 2017-11-30 CHLAC 1.6677068206 #> 8746 2081 3F CC67 2017 2017-11-30 COLOR 4.1271343850 A #> 8747 2081 3F CC67 2017 2017-11-30 COND 6.2519038832 #> 8748 2081 3F CC67 2017 2017-11-30 DO 2.3025850930 #> 8749 2081 3F CC67 2017 2017-11-30 DOSAT 4.7535901911 #> 8750 2081 3F CC67 2017 2017-11-30 NO23 -3.2188758249 #> 8751 2081 3F CC67 2017 2017-11-30 SALIN -1.3470736480 + #> 8752 2081 3F CC67 2017 2017-11-30 TKN -0.5798184953 #> 8753 2081 3F CC67 2017 2017-11-30 TN -0.5108256238 + #> 8754 2081 3F CC67 2017 2017-11-30 TP -3.1700856607 #> 8755 2081 3F CC67 2017 2017-11-30 TSS 1.3862943611 I #> 8756 2081 3F CC67 2017 2017-11-30 TURB 1.5475625087 #> 8757 2081 3F CC67 2018 2018-04-12 COND 6.1717005974 #> 8758 2081 3F CC67 2018 2018-04-12 DO 2.6461747974 #> 8759 2081 3F CC67 2018 2018-04-12 DOSAT 5.1239639794 #> 8760 2081 3F CC67 2018 2018-04-12 SALIN -1.4696759701 + #> 8761 2081 3F CC67 2018 2018-04-19 CHLAC 2.2512917986 #> 8762 2081 3F CC67 2018 2018-04-19 COLOR 4.0943445622 #> 8763 2081 3F CC67 2018 2018-04-19 COND 6.0980742822 #> 8764 2081 3F CC67 2018 2018-04-19 DO 2.7317667277 #> 8765 2081 3F CC67 2018 2018-04-19 DOSAT 5.3107398865 #> 8766 2081 3F CC67 2018 2018-04-19 NO23 -5.5214609179 U #> 8767 2081 3F CC67 2018 2018-04-19 SALIN -1.6094379124 + #> 8768 2081 3F CC67 2018 2018-04-19 TKN -0.3424903089 #> 8769 2081 3F CC67 2018 2018-04-19 TN -0.3396773676 + #> 8770 2081 3F CC67 2018 2018-04-19 TP -4.2686979494 #> 8771 2081 3F CC67 2018 2018-04-19 TSS 1.0986122887 I #> 8772 2081 3F CC67 2018 2018-04-19 TURB 0.4054651081 #> 8773 2081 3F CC67 2018 2018-07-17 CHLAC 2.3978952728 #> 8774 2081 3F CC67 2018 2018-07-17 COLOR 5.2470240722 #> 8775 2081 3F CC67 2018 2018-07-17 COND 5.6559918108 #> 8776 2081 3F CC67 2018 2018-07-17 DO 1.6677068206 #> 8777 2081 3F CC67 2018 2018-07-17 DOSAT 4.2541932632 #> 8778 2081 3F CC67 2018 2018-07-17 NO23 -3.8167128256 #> 8779 2081 3F CC67 2018 2018-07-17 TKN -0.0304592075 #> 8780 2081 3F CC67 2018 2018-07-17 TN -0.0080321717 + #> 8781 2081 3F CC67 2018 2018-07-17 TP -2.7968814148 #> 8782 2081 3F CC67 2018 2018-07-17 TSS 1.7917594692 I #> 8783 2081 3F CC67 2018 2018-07-17 TURB 1.7047480922 #> 8784 2081 3F CC67 2018 2018-08-01 CHLAC 2.0014800002 #> 8785 2081 3F CC67 2018 2018-08-01 COLOR 4.9416424226 #> 8786 2081 3F CC67 2018 2018-08-01 COND 5.9269260260 #> 8787 2081 3F CC67 2018 2018-08-01 DO 1.8900953699 #> 8788 2081 3F CC67 2018 2018-08-01 DOSAT 4.4624538838 #> 8789 2081 3F CC67 2018 2018-08-01 NO23 -3.2188758249 #> 8790 2081 3F CC67 2018 2018-08-01 SALIN -1.7147984281 #> 8791 2081 3F CC67 2018 2018-08-01 TKN -0.2613647641 #> 8792 2081 3F CC67 2018 2018-08-01 TN -0.2107210313 + #> 8793 2081 3F CC67 2018 2018-08-01 TP -2.8824035882 #> 8794 2081 3F CC67 2018 2018-08-01 TSS 1.7917594692 I #> 8795 2081 3F CC67 2018 2018-08-01 TURB 1.7404661748 #> 8796 2081 3F CC67 2018 2018-08-01 COND 5.9269260260 #> 8797 2081 3F CC67 2018 2018-08-01 DO 1.8900953699 #> 8798 2081 3F CC67 2018 2018-08-01 DOSAT 4.4624538838 #> 8799 2081 3F CC67 2018 2018-08-01 SALIN -1.7147984281 #> 8800 2081 3F CC67 2018 2018-08-20 CHLAC 2.2407096893 #> 8801 2081 3F CC67 2018 2018-08-20 COLOR 5.0751738152 #> 8802 2081 3F CC67 2018 2018-08-20 COND 5.3706380281 #> 8803 2081 3F CC67 2018 2018-08-20 DO 1.5216989981 #> 8804 2081 3F CC67 2018 2018-08-20 DOSAT 4.0758410907 #> 8805 2081 3F CC67 2018 2018-08-20 NO23 -3.4420193762 #> 8806 2081 3F CC67 2018 2018-08-20 SALIN -2.3025850930 #> 8807 2081 3F CC67 2018 2018-08-20 TKN -0.0618754037 #> 8808 2081 3F CC67 2018 2018-08-20 TN -0.0283994745 + #> 8809 2081 3F CC67 2018 2018-08-20 TP -2.4534079827 #> 8810 2081 3F CC67 2018 2018-08-20 TSS 2.1972245773 I #> 8811 2081 3F CC67 2018 2018-08-20 TURB 1.9315214116 #> 8812 2081 3F CC67 2018 2018-09-10 CHLAC 1.5260563035 #> 8813 2081 3F CC67 2018 2018-09-10 COLOR 4.4998096703 A #> 8814 2081 3F CC67 2018 2018-09-10 COND 6.0520891689 #> 8815 2081 3F CC67 2018 2018-09-10 DO 1.9865035460 #> 8816 2081 3F CC67 2018 2018-09-10 DOSAT 4.5941092386 #> 8817 2081 3F CC67 2018 2018-09-10 SALIN -1.6094379124 #> 8818 2081 3F CC67 2018 2018-09-10 TN -0.2057949130 + #> 8819 2081 3F CC67 2018 2018-09-10 TSS 2.3025850930 A #> 8820 2081 3F CC67 2018 2018-09-10 TURB 2.0281482473 #> 8821 2081 3F CC67 2018 2018-11-12 CHLAC 2.2300144002 #> 8822 2081 3F CC67 2018 2018-11-12 COLOR 3.9120230054 #> 8823 2081 3F CC67 2018 2018-11-12 COND 6.2595814641 #> 8824 2081 3F CC67 2018 2018-11-12 DO 2.1174596089 #> 8825 2081 3F CC67 2018 2018-11-12 DOSAT 4.6180864113 #> 8826 2081 3F CC67 2018 2018-11-12 NO23 -2.3751557858 #> 8827 2081 3F CC67 2018 2018-11-12 SALIN -1.3862943611 #> 8828 2081 3F CC67 2018 2018-11-12 TKN -0.2484613593 #> 8829 2081 3F CC67 2018 2018-11-12 TN -0.1358197231 + #> 8830 2081 3F CC67 2018 2018-11-12 TP -2.8473122684 #> 8831 2081 3F CC67 2018 2018-11-12 TSS 2.1972245773 I #> 8832 2081 3F CC67 2018 2018-11-12 TURB 2.0014800002 A #> 8833 2082A 3F CC70 2018 2018-10-18 CHLAC 0.9932517730 #> 8834 2082A 3F CC70 2018 2018-10-18 COLOR 4.2484952420 #> 8835 2082A 3F CC70 2018 2018-10-18 COND 5.5721540322 #> 8836 2082A 3F CC70 2018 2018-10-18 DO 1.7681496036 #> 8837 2082A 3F CC70 2018 2018-10-18 DOSAT 4.3148178850 #> 8838 2082A 3F CC70 2018 2018-10-18 NO23 -2.1202635362 #> 8839 2082A 3F CC70 2018 2018-10-18 SALIN -2.1202635362 #> 8840 2082A 3F CC70 2018 2018-10-18 TKN 0.1823215568 #> 8841 2082A 3F CC70 2018 2018-10-18 TN 0.2776317366 + #> 8842 2082A 3F CC70 2018 2018-10-18 TP -3.0365542681 #> 8843 2082A 3F CC70 2018 2018-10-18 TSS 2.3978952728 A #> 8844 2082A 3F CC70 2018 2018-10-18 TURB 1.9600947840 #> 8845 2082A 3F CC70 2019 2019-05-08 CHLAC 0.4054651081 I #> 8846 2082A 3F CC70 2019 2019-05-08 COLOR 3.5263605246 A #> 8847 2082A 3F CC70 2019 2019-05-08 COND 6.4167322825 #> 8848 2082A 3F CC70 2019 2019-05-08 DO 1.6900958155 #> 8849 2082A 3F CC70 2019 2019-05-08 DOSAT 4.2384449062 #> 8850 2082A 3F CC70 2019 2019-05-08 NO23 -5.5214609179 U #> 8851 2082A 3F CC70 2019 2019-05-08 SALIN -1.2039728043 #> 8852 2082A 3F CC70 2019 2019-05-08 TKN -0.3011050928 #> 8853 2082A 3F CC70 2019 2019-05-08 TN -0.2984060358 + #> 8854 2082A 3F CC70 2019 2019-05-08 TP -3.1941832123 #> 8855 2082A 3F CC70 2019 2019-05-08 TSS 0.6931471806 I #> 8856 2082A 3F CC70 2019 2019-05-08 TURB 1.2527629685 #> 8857 2079 2 CC74 2017 2017-03-13 COND 11.1102514581 #> 8858 2079 2 CC74 2017 2017-03-13 DO 2.0668627595 #> 8859 2079 2 CC74 2017 2017-03-13 DOSAT 4.8362819070 #> 8860 2079 2 CC74 2017 2017-03-13 SALIN 3.8066624898 #> 8861 2079 2 CC74 2017 2017-05-15 CHLAC 0.9162907319 #> 8862 2079 2 CC74 2017 2017-05-15 COND 10.9460055668 #> 8863 2079 2 CC74 2017 2017-05-15 DO 1.7917594692 #> 8864 2079 2 CC74 2017 2017-05-15 DOSAT 4.2341065046 #> 8865 2079 2 CC74 2017 2017-05-15 NO23 -4.8283137373 U #> 8866 2079 2 CC74 2017 2017-05-15 SALIN 3.5759906720 + #> 8867 2079 2 CC74 2017 2017-05-15 TKN -0.3011050928 #> 8868 2079 2 CC74 2017 2017-05-15 TN -0.2957142441 + #> 8869 2079 2 CC74 2017 2017-05-15 TP -3.6888794541 #> 8870 2079 2 CC74 2017 2017-05-15 TSS 1.3862943611 I #> 8871 2079 2 CC74 2017 2017-05-15 TURB 0.0000000000 #> 8872 2079 2 CC74 2017 2017-07-20 CHLAC 1.5475625087 #> 8873 2079 2 CC74 2017 2017-07-20 COND 10.6434228946 #> 8874 2079 2 CC74 2017 2017-07-20 DO 1.5040773968 #> 8875 2079 2 CC74 2017 2017-07-20 DOSAT 4.2484952420 #> 8876 2079 2 CC74 2017 2017-07-20 NO23 -5.5214609179 U #> 8877 2079 2 CC74 2017 2017-07-20 TKN -0.0943106795 #> 8878 2079 2 CC74 2017 2017-07-20 TN -0.0921152889 + #> 8879 2079 2 CC74 2017 2017-07-20 TP -3.4112477175 #> 8880 2079 2 CC74 2017 2017-07-20 TSS 1.0986122887 U #> 8881 2079 2 CC74 2017 2017-07-20 TURB 0.4054651081 #> 8882 2079 2 CC74 2017 2017-10-24 COND 10.5655567775 #> 8883 2079 2 CC74 2017 2017-10-24 DO 1.4586150227 #> 8884 2079 2 CC74 2017 2017-10-24 DOSAT 4.1431347264 #> 8885 2079 2 CC74 2017 2017-10-24 SALIN 3.1531632815 + #> 8886 2079 2 CC74 2018 2018-03-15 CHLAC 2.0918640617 #> 8887 2079 2 CC74 2018 2018-03-15 COND 11.0381102787 #> 8888 2079 2 CC74 2018 2018-03-15 DO 2.2407096893 #> 8889 2079 2 CC74 2018 2018-03-15 DOSAT 4.9972122738 #> 8890 2079 2 CC74 2018 2018-03-15 NO23 -4.1997050779 #> 8891 2079 2 CC74 2018 2018-03-15 TKN -0.1508228897 #> 8892 2079 2 CC74 2018 2018-03-15 TN -0.1335313926 + #> 8893 2079 2 CC74 2018 2018-03-15 TP -3.1941832123 #> 8894 2079 2 CC74 2018 2018-03-15 TSS 1.9459101491 I #> 8895 2079 2 CC74 2018 2018-03-15 TURB 1.0986122887 #> 8896 2079 2 CC74 2018 2018-04-23 CHLAC 2.7725887222 #> 8897 2079 2 CC74 2018 2018-04-23 COND 10.9748485413 #> 8898 2079 2 CC74 2018 2018-04-23 DO 2.2823823857 #> 8899 2079 2 CC74 2018 2018-04-23 DOSAT 5.0498560072 #> 8900 2079 2 CC74 2018 2018-04-23 NO23 -5.5214609179 U #> 8901 2079 2 CC74 2018 2018-04-23 SALIN 3.5937442590 + #> 8902 2079 2 CC74 2018 2018-04-23 TKN -0.1984509387 #> 8903 2079 2 CC74 2018 2018-04-23 TN -0.1960148839 + #> 8904 2079 2 CC74 2018 2018-04-23 TP -3.2441936329 #> 8905 2079 2 CC74 2018 2018-04-23 TSS 2.4849066498 #> 8906 2079 2 CC74 2018 2018-04-23 TURB 0.6931471806 #> 8907 2079 2 CC74 2018 2018-06-11 CHLAC 3.1780538303 #> 8908 2079 2 CC74 2018 2018-06-11 COND 10.6286177789 #> 8909 2079 2 CC74 2018 2018-06-11 DO 1.8245492921 #> 8910 2079 2 CC74 2018 2018-06-11 DOSAT 4.5643481915 #> 8911 2079 2 CC74 2018 2018-06-11 NO23 -5.5214609179 U #> 8912 2079 2 CC74 2018 2018-06-11 SALIN 3.2695689392 #> 8913 2079 2 CC74 2018 2018-06-11 TKN -0.0943106795 #> 8914 2079 2 CC74 2018 2018-06-11 TN -0.0921152889 + #> 8915 2079 2 CC74 2018 2018-06-11 TP -2.9957322736 #> 8916 2079 2 CC74 2018 2018-06-11 TSS 1.7917594692 I #> 8917 2079 2 CC74 2018 2018-06-11 TURB 1.1314021115 #> 8918 2079 2 CC74 2018 2018-08-07 CHLAC 1.9600947840 #> 8919 2079 2 CC74 2018 2018-08-07 COND 10.5844609322 #> 8920 2079 2 CC74 2018 2018-08-07 DO 1.9387416596 #> 8921 2079 2 CC74 2018 2018-08-07 DOSAT 4.6709579265 #> 8922 2079 2 CC74 2018 2018-08-07 NO23 -5.5214609179 U #> 8923 2079 2 CC74 2018 2018-08-07 SALIN 3.2200751054 #> 8924 2079 2 CC74 2018 2018-08-07 TKN -0.0202027073 #> 8925 2079 2 CC74 2018 2018-08-07 TN -0.0181639706 + #> 8926 2079 2 CC74 2018 2018-08-07 TP -2.6882475738 #> 8927 2079 2 CC74 2018 2018-08-07 TSS 1.0986122887 U #> 8928 2079 2 CC74 2018 2018-08-07 TURB 0.4054651081 #> 8929 2079 2 CC74 2018 2018-09-06 CHLAC 1.6486586256 #> 8930 2079 2 CC74 2018 2018-09-06 COND 10.3441267357 #> 8931 2079 2 CC74 2018 2018-09-06 DO 1.4231083342 #> 8932 2079 2 CC74 2018 2018-09-06 DOSAT 4.1026433650 #> 8933 2079 2 CC74 2018 2018-09-06 NO23 -5.5214609179 U #> 8934 2079 2 CC74 2018 2018-09-06 SALIN 2.9559514035 #> 8935 2079 2 CC74 2018 2018-09-06 TKN 0.7419373447 #> 8936 2079 2 CC74 2018 2018-09-06 TN 0.7428892725 + #> 8937 2079 2 CC74 2018 2018-09-06 TP -2.5770219387 #> 8938 2079 2 CC74 2018 2018-09-06 TSS 1.0986122887 I #> 8939 2079 2 CC74 2018 2018-09-06 TURB 0.0953101798 #> 8940 2079 2 CC74 2019 2019-04-17 CHLAC 2.1162555148 #> 8941 2079 2 CC74 2019 2019-04-17 COND 10.8549137412 #> 8942 2079 2 CC74 2019 2019-04-17 DO 2.2159372863 #> 8943 2079 2 CC74 2019 2019-04-17 DOSAT 4.9236239171 #> 8944 2079 2 CC74 2019 2019-04-17 NO23 -5.5214609179 U #> 8945 2079 2 CC74 2019 2019-04-17 SALIN 3.5269485870 #> 8946 2079 2 CC74 2019 2019-04-17 TKN -0.1278333715 #> 8947 2079 2 CC74 2019 2019-04-17 TN -0.1255632230 + #> 8948 2079 2 CC74 2019 2019-04-17 TP -3.4737680745 #> 8949 2079 2 CC74 2019 2019-04-17 TSS 3.4011973817 #> 8950 2079 2 CC74 2019 2019-04-17 TURB -0.2231435513 #> 8951 2079 2 CC74 2019 2019-07-15 CHLAC 3.7612001157 #> 8952 2079 2 CC74 2019 2019-07-15 COND 10.6353745614 #> 8953 2079 2 CC74 2019 2019-07-15 DO 1.9796212064 #> 8954 2079 2 CC74 2019 2019-07-15 DOSAT 4.7104306966 #> 8955 2079 2 CC74 2019 2019-07-15 NO23 -5.5214609179 U #> 8956 2079 2 CC74 2019 2019-07-15 SALIN 3.2782761681 #> 8957 2079 2 CC74 2019 2019-07-15 TKN 0.0953101798 #> 8958 2079 2 CC74 2019 2019-07-15 TN 0.0971267107 + #> 8959 2079 2 CC74 2019 2019-07-15 TP -2.7806208939 #> 8960 2079 2 CC74 2019 2019-07-15 TSS 2.8332133441 #> 8961 2079 2 CC74 2019 2019-07-15 TURB 1.6094379124 #> 8962 2079 2 CC74 2019 2019-08-19 CHLAC 2.4849066498 #> 8963 2079 2 CC74 2019 2019-08-19 COND 10.4673514473 #> 8964 2079 2 CC74 2019 2019-08-19 DO 1.3635373740 #> 8965 2079 2 CC74 2019 2019-08-19 DOSAT 4.0826093060 #> 8966 2079 2 CC74 2019 2019-08-19 NO23 -5.5214609179 U #> 8967 2079 2 CC74 2019 2019-08-19 SALIN 3.0901329490 #> 8968 2079 2 CC74 2019 2019-08-19 TKN 0.4054651081 #> 8969 2079 2 CC74 2019 2019-08-19 TN 0.4067975533 + #> 8970 2079 2 CC74 2019 2019-08-19 TP -3.2968373663 #> 8971 2079 2 CC74 2019 2019-08-19 TSS 2.4849066498 #> 8972 2079 2 CC74 2019 2019-08-19 TURB 0.7419373447 #> 8973 2079 2 CC74 2019 2019-09-11 CHLAC 2.9444389792 #> 8974 2079 2 CC74 2019 2019-09-11 COND 10.7330214205 #> 8975 2079 2 CC74 2019 2019-09-11 DO 1.7783364489 #> 8976 2079 2 CC74 2019 2019-09-11 DOSAT 4.5152454785 #> 8977 2079 2 CC74 2019 2019-09-11 NO23 -5.5214609179 U #> 8978 2079 2 CC74 2019 2019-09-11 SALIN 3.3874364664 #> 8979 2079 2 CC74 2019 2019-09-11 TKN -0.0100503359 #> 8980 2079 2 CC74 2019 2019-09-11 TN -0.0080321717 + #> 8981 2079 2 CC74 2019 2019-09-11 TP -2.8647040111 #> 8982 2079 2 CC74 2019 2019-09-11 TSS 1.3862943611 I #> 8983 2079 2 CC74 2019 2019-09-11 TURB 0.7884573604 #> 8984 2079 2 CC74 2019 2019-10-09 CHLAC 3.4339872045 #> 8985 2079 2 CC74 2019 2019-10-09 COND 10.7419897010 #> 8986 2079 2 CC74 2019 2019-10-09 DO 1.5432981099 #> 8987 2079 2 CC74 2019 2019-10-09 DOSAT 4.2640873368 #> 8988 2079 2 CC74 2019 2019-10-09 NO23 -5.5214609179 U #> 8989 2079 2 CC74 2019 2019-10-09 SALIN 3.3981928726 #> 8990 2079 2 CC74 2019 2019-10-09 TKN -0.1278333715 #> 8991 2079 2 CC74 2019 2019-10-09 TN -0.1255632230 + #> 8992 2079 2 CC74 2019 2019-10-09 TP -2.8302178351 #> 8993 2079 2 CC74 2019 2019-10-09 TSS 1.9459101491 I #> 8994 2079 2 CC74 2019 2019-10-09 TURB 0.6931471806 #> 8995 2079 2 CC74 2020 2020-02-13 CHLAC 2.3978952728 #> 8996 2079 2 CC74 2020 2020-02-13 COND 10.7930235471 #> 8997 2079 2 CC74 2020 2020-02-13 DO 2.0464016876 #> 8998 2079 2 CC74 2020 2020-02-13 DOSAT 4.7388265708 #> 8999 2079 2 CC74 2020 2020-02-13 NO23 -5.5214609179 U #> 9000 2079 2 CC74 2020 2020-02-13 SALIN 3.4575777151 #> 9001 2079 2 CC74 2020 2020-02-13 TKN -0.0512932944 #> 9002 2079 2 CC74 2020 2020-02-13 TN -0.0491902442 + #> 9003 2079 2 CC74 2020 2020-02-13 TP -3.0365542681 #> 9004 2079 2 CC74 2020 2020-02-13 TSS 2.3025850930 I #> 9005 2079 2 CC74 2020 2020-02-13 TURB 0.6931471806 #> 9006 2079 2 CC74 2020 2020-03-24 CHLAC 2.0014800002 #> 9007 2079 2 CC74 2020 2020-03-24 COND 10.9585136130 #> 9008 2079 2 CC74 2020 2020-03-24 DO 1.8115620965 #> 9009 2079 2 CC74 2020 2020-03-24 DOSAT 4.5664293577 #> 9010 2079 2 CC74 2020 2020-03-24 NO23 -5.5214609179 U #> 9011 2079 2 CC74 2020 2020-03-24 SALIN 3.6425737012 #> 9012 2079 2 CC74 2020 2020-03-24 TKN -0.0512932944 #> 9013 2079 2 CC74 2020 2020-03-24 TN -0.0491902442 + #> 9014 2079 2 CC74 2020 2020-03-24 TP -3.3242363405 #> 9015 2079 2 CC74 2020 2020-03-24 TSS 1.6094379124 I #> 9016 2079 2 CC74 2020 2020-03-24 TURB 0.7419373447 #> 9017 2079 2 CC74 2020 2020-06-15 CHLAC 3.1354942159 #> 9018 2079 2 CC74 2020 2020-06-15 COND 10.7369834598 #> 9019 2079 2 CC74 2020 2020-06-15 DO 0.5822156199 #> 9020 2079 2 CC74 2020 2020-06-15 DOSAT 3.3141860047 #> 9021 2079 2 CC74 2020 2020-06-15 NO23 -5.5214609179 U #> 9022 2079 2 CC74 2020 2020-06-15 SALIN 3.3924929410 #> 9023 2079 2 CC74 2020 2020-06-15 TKN 0.3364722366 #> 9024 2079 2 CC74 2020 2020-06-15 TN 0.3378997886 + #> 9025 2079 2 CC74 2020 2020-06-15 TP -2.7488721956 #> 9026 2079 2 CC74 2020 2020-06-15 TSS 1.3862943611 I #> 9027 2079 2 CC74 2020 2020-06-15 TURB 2.0668627595 #> 9028 2079 2 CC74 2020 2020-07-27 CHLAC 3.4339872045 #> 9029 2079 2 CC74 2020 2020-07-27 COND 10.7988201898 #> 9030 2079 2 CC74 2020 2020-07-27 DO 1.9572739077 #> 9031 2079 2 CC74 2020 2020-07-27 DOSAT 4.7326835063 #> 9032 2079 2 CC74 2020 2020-07-27 NO23 -5.5214609179 U #> 9033 2079 2 CC74 2020 2020-07-27 SALIN 3.4594662898 #> 9034 2079 2 CC74 2020 2020-07-27 TKN 0.0000000000 #> 9035 2079 2 CC74 2020 2020-07-27 TN 0.0019980027 + #> 9036 2079 2 CC74 2020 2020-07-27 TP -3.1700856607 #> 9037 2079 2 CC74 2020 2020-07-27 TSS 1.7917594692 I #> 9038 2079 2 CC74 2020 2020-07-27 TURB 1.2809338455 #> 9039 2079 2 CC74 2023 2023-02-13 CHLAC 3.3672958300 #> 9040 2079 2 CC74 2023 2023-02-13 COND 10.8175959048 #> 9041 2079 2 CC74 2023 2023-02-13 DO 1.8277699068 #> 9042 2079 2 CC74 2023 2023-02-13 DOSAT 4.4091553021 #> 9043 2079 2 CC74 2023 2023-02-13 NO23 -5.5214609179 U #> 9044 2079 2 CC74 2023 2023-02-13 SALIN 3.4879865117 #> 9045 2079 2 CC74 2023 2023-02-13 TKN 0.2623642645 #> 9046 2079 2 CC74 2023 2023-02-13 TN 0.2639015438 + #> 9047 2079 2 CC74 2023 2023-02-13 TP -2.2072749132 #> 9048 2079 2 CC74 2023 2023-02-13 TSS 2.8903717579 A #> 9049 2079 2 CC74 2023 2023-02-13 TURB 1.4350845253 #> 9050 2079 2 CC74 2023 2023-04-10 COND 10.9901959367 #> 9051 2079 2 CC74 2023 2023-04-10 DO 1.6714733034 #> 9052 2079 2 CC74 2023 2023-04-10 DOSAT 4.3770140929 #> 9053 2079 2 CC74 2023 2023-04-10 NO23 -5.5214609179 U #> 9054 2079 2 CC74 2023 2023-04-10 SALIN 3.6810992668 #> 9055 2079 2 CC74 2023 2023-04-10 TKN -0.0618754037 #> 9056 2079 2 CC74 2023 2023-04-10 TN -0.0597500044 + #> 9057 2079 2 CC74 2023 2023-04-10 TP -3.4737680745 #> 9058 2079 2 CC74 2023 2023-04-10 TSS 1.3862943611 I #> 9059 2079 2 CC74 2014 2014-03-26 SALIN 3.5351453542 #> 9060 2079 2 CC74 2014 2014-03-26 SALIN 3.5351453542 #> 9061 2079 2 CC74 2014 2014-07-22 SALIN 3.4719664526 #> 9062 2079 2 CC74 2014 2014-07-22 SALIN 3.4719664526 #> 9063 2079 2 CC74 2014 2014-09-11 DO 1.5475625087 #> 9064 2079 2 CC74 2014 2014-09-11 DOSAT 4.3280982926 + #> 9065 2079 2 CC74 2014 2014-09-11 SALIN 3.4011973817 #> 9066 2079 2 CC74 2015 2015-09-14 SALIN 3.1986731176 #> 9067 2079 2 CC74 2015 2015-09-14 SALIN 3.1986731176 #> 9068 2079 2 CC74 2016 2016-05-18 DO 2.1282317058 #> 9069 2079 2 CC74 2016 2016-05-18 DOSAT 4.8933521335 + #> 9070 2079 2 CC74 2016 2016-05-18 SALIN 3.5145260670 #> 9071 2079 2 CC74 2016 2016-05-18 DO 2.2721258855 #> 9072 2079 2 CC74 2016 2016-05-18 DOSAT 5.0395466376 + #> 9073 2079 2 CC74 2016 2016-05-18 SALIN 3.5174978374 #> 9074 2079 2 CC74 2016 2016-08-01 DO 2.1282317058 #> 9075 2079 2 CC74 2016 2016-08-01 DOSAT 4.9243509255 + #> 9076 2079 2 CC74 2016 2016-08-01 SALIN 3.4531571206 #> 9077 2079 2 CC74 2016 2016-08-01 DO 2.1162555148 #> 9078 2079 2 CC74 2016 2016-08-01 DOSAT 4.9170569471 + #> 9079 2079 2 CC74 2016 2016-08-01 SALIN 3.4995332824 #> 9080 2079 2 CC74 2016 2016-08-17 DO 2.0014800002 #> 9081 2079 2 CC74 2016 2016-08-17 DOSAT 4.7578912730 + #> 9082 2079 2 CC74 2016 2016-08-17 SALIN 3.3357695763 #> 9083 2079 2 CC74 2016 2016-08-17 DO 1.9021075264 #> 9084 2079 2 CC74 2016 2016-08-17 DOSAT 4.6672055769 + #> 9085 2079 2 CC74 2016 2016-08-17 SALIN 3.4111477125 #> 9086 2079 2 CC74 2016 2016-09-08 DO 1.9459101491 #> 9087 2079 2 CC74 2016 2016-09-08 DOSAT 4.6463121293 + #> 9088 2079 2 CC74 2016 2016-09-08 SALIN 3.0492730405 #> 9089 2079 2 CC74 2016 2016-09-08 DO 1.7749523509 #> 9090 2079 2 CC74 2016 2016-09-08 DOSAT 4.5009201646 + #> newComment disqual disqual2 #> 1 NA NA #> 2 U NA NA #> 3 + NA NA #> 4 U NA NA #> 5 NA NA #> 6 NA NA #> 7 + NA NA #> 8 NA NA #> 9 NA NA #> 10 I NA NA #> 11 U NA NA #> 12 NA NA #> 13 + NA NA #> 14 I NA NA #> 15 NA NA #> 16 NA NA #> 17 + NA NA #> 18 NA NA #> 19 NA NA #> 20 NA NA #> 21 NA NA #> 22 NA NA #> 23 + NA NA #> 24 I NA NA #> 25 NA NA #> 26 NA NA #> 27 + NA NA #> 28 NA NA #> 29 A NA NA #> 30 NA NA #> 31 NA NA #> 32 NA NA #> 33 + NA NA #> 34 I NA NA #> 35 NA NA #> 36 NA NA #> 37 + NA NA #> 38 NA NA #> 39 NA NA #> 40 NA NA #> 41 NA NA #> 42 NA NA #> 43 U NA NA #> 44 NA NA #> 45 + NA NA #> 46 NA NA #> 47 NA NA #> 48 NA NA #> 49 NA NA #> 50 NA NA #> 51 + NA NA #> 52 U NA NA #> 53 NA NA #> 54 + NA NA #> 55 NA NA #> 56 NA NA #> 57 NA NA #> 58 NA NA #> 59 + NA NA #> 60 I NA NA #> 61 NA NA #> 62 NA NA #> 63 + NA NA #> 64 NA NA #> 65 NA NA #> 66 NA NA #> 67 NA NA #> 68 + NA NA #> 69 NA NA #> 70 NA NA #> 71 NA NA #> 72 + NA NA #> 73 NA NA #> 74 NA NA #> 75 A NA NA #> 76 A NA NA #> 77 + NA NA #> 78 NA NA #> 79 NA NA #> 80 NA NA #> 81 + NA NA #> 82 NA NA #> 83 NA NA #> 84 NA NA #> 85 A NA NA #> 86 + NA NA #> 87 NA NA #> 88 NA NA #> 89 NA NA #> 90 + NA NA #> 91 NA NA #> 92 NA NA #> 93 NA NA #> 94 NA NA #> 95 NA NA #> 96 + NA NA #> 97 I NA NA #> 98 NA NA #> 99 NA NA #> 100 + NA NA #> 101 NA NA #> 102 NA NA #> 103 I NA NA #> 104 U NA NA #> 105 NA NA #> 106 + NA NA #> 107 I NA NA #> 108 NA NA #> 109 I NA NA #> 110 + NA NA #> 111 NA NA #> 112 NA NA #> 113 NA NA #> 114 NA NA #> 115 NA NA #> 116 + NA NA #> 117 U NA NA #> 118 NA NA #> 119 NA NA #> 120 + NA NA #> 121 NA NA #> 122 NA NA #> 123 NA NA #> 124 NA NA #> 125 NA NA #> 126 + NA NA #> 127 U NA NA #> 128 NA NA #> 129 I NA NA #> 130 + NA NA #> 131 NA NA #> 132 NA NA #> 133 NA NA #> 134 NA NA #> 135 NA NA #> 136 + NA NA #> 137 NA NA #> 138 NA NA #> 139 NA NA #> 140 + NA NA #> 141 NA NA #> 142 NA NA #> 143 NA NA #> 144 NA NA #> 145 NA NA #> 146 + NA NA #> 147 NA NA #> 148 NA NA #> 149 NA NA #> 150 + NA NA #> 151 NA NA #> 152 NA NA #> 153 NA NA #> 154 NA NA #> 155 NA NA #> 156 + NA NA #> 157 NA NA #> 158 NA NA #> 159 NA NA #> 160 + NA NA #> 161 NA NA #> 162 NA NA #> 163 NA NA #> 164 NA NA #> 165 NA NA #> 166 + NA NA #> 167 NA NA #> 168 NA NA #> 169 NA NA #> 170 + NA NA #> 171 NA NA #> 172 NA NA #> 173 NA NA #> 174 NA NA #> 175 NA NA #> 176 + NA NA #> 177 NA NA #> 178 NA NA #> 179 NA NA #> 180 + NA NA #> 181 NA NA #> 182 NA NA #> 183 NA NA #> 184 NA NA #> 185 NA NA #> 186 + NA NA #> 187 I NA NA #> 188 NA NA #> 189 NA NA #> 190 + NA NA #> 191 NA NA #> 192 NA NA #> 193 NA NA #> 194 NA NA #> 195 NA NA #> 196 + NA NA #> 197 NA NA #> 198 NA NA #> 199 NA NA #> 200 + NA NA #> 201 NA NA #> 202 NA NA #> 203 I NA NA #> 204 NA NA #> 205 NA NA #> 206 + NA NA #> 207 U NA NA #> 208 NA NA #> 209 I NA NA #> 210 + NA NA #> 211 NA NA #> 212 NA NA #> 213 NA NA #> 214 NA NA #> 215 NA NA #> 216 + NA NA #> 217 I NA NA #> 218 NA NA #> 219 NA NA #> 220 + NA NA #> 221 NA NA #> 222 NA NA #> 223 NA NA #> 224 NA NA #> 225 NA NA #> 226 + NA NA #> 227 NA NA #> 228 NA NA #> 229 NA NA #> 230 + NA NA #> 231 NA NA #> 232 NA NA #> 233 NA NA #> 234 NA NA #> 235 NA NA #> 236 + NA NA #> 237 I NA NA #> 238 NA NA #> 239 NA NA #> 240 + NA NA #> 241 NA NA #> 242 NA NA #> 243 NA NA #> 244 NA NA #> 245 NA NA #> 246 + NA NA #> 247 NA NA #> 248 NA NA #> 249 NA NA #> 250 + NA NA #> 251 NA NA #> 252 NA NA #> 253 I NA NA #> 254 U NA NA #> 255 NA NA #> 256 + NA NA #> 257 I NA NA #> 258 NA NA #> 259 NA NA #> 260 + NA NA #> 261 NA NA #> 262 NA NA #> 263 NA NA #> 264 I NA NA #> 265 NA NA #> 266 + NA NA #> 267 NA NA #> 268 NA NA #> 269 NA NA #> 270 + NA NA #> 271 NA NA #> 272 NA NA #> 273 I NA NA #> 274 U NA NA #> 275 NA NA #> 276 + NA NA #> 277 U NA NA #> 278 NA NA #> 279 NA NA #> 280 + NA NA #> 281 NA NA #> 282 NA NA #> 283 NA NA #> 284 NA NA #> 285 + NA NA #> 286 NA NA #> 287 I NA NA #> 288 NA NA #> 289 NA NA #> 290 + NA NA #> 291 I NA NA #> 292 NA NA #> 293 NA NA #> 294 + NA NA #> 295 NA NA #> 296 NA NA #> 297 NA NA #> 298 + NA NA #> 299 NA NA #> 300 NA NA #> 301 A NA NA #> 302 NA NA #> 303 + NA NA #> 304 I NA NA #> 305 NA NA #> 306 NA NA #> 307 + NA NA #> 308 NA NA #> 309 NA NA #> 310 NA NA #> 311 NA NA #> 312 NA NA #> 313 + NA NA #> 314 NA NA #> 315 NA NA #> 316 NA NA #> 317 + NA NA #> 318 NA NA #> 319 A NA NA #> 320 NA NA #> 321 NA NA #> 322 I NA NA #> 323 NA NA #> 324 + NA NA #> 325 NA NA #> 326 NA NA #> 327 NA NA #> 328 NA NA #> 329 NA NA #> 330 + NA NA #> 331 NA NA #> 332 NA NA #> 333 NA NA #> 334 + NA NA #> 335 NA NA #> 336 NA NA #> 337 I NA NA #> 338 NA NA #> 339 NA NA #> 340 + NA NA #> 341 I NA NA #> 342 NA NA #> 343 NA NA #> 344 + NA NA #> 345 NA NA #> 346 NA NA #> 347 I NA NA #> 348 NA NA #> 349 NA NA #> 350 + NA NA #> 351 NA NA #> 352 NA NA #> 353 NA NA #> 354 + NA NA #> 355 NA NA #> 356 NA NA #> 357 NA NA #> 358 NA NA #> 359 NA NA #> 360 + NA NA #> 361 NA NA #> 362 NA NA #> 363 NA NA #> 364 + NA NA #> 365 NA NA #> 366 A NA NA #> 367 I NA NA #> 368 NA NA #> 369 NA NA #> 370 + NA NA #> 371 U NA NA #> 372 NA NA #> 373 NA NA #> 374 + NA NA #> 375 NA NA #> 376 NA NA #> 377 I NA NA #> 378 I NA NA #> 379 + NA NA #> 380 U NA NA #> 381 NA NA #> 382 NA NA #> 383 + NA NA #> 384 NA NA #> 385 NA NA #> 386 NA NA #> 387 NA NA #> 388 NA NA #> 389 NA NA #> 390 U NA NA #> 391 NA NA #> 392 NA NA #> 393 + NA NA #> 394 NA NA #> 395 NA NA #> 396 NA NA #> 397 NA NA #> 398 NA NA #> 399 NA NA #> 400 NA NA #> 401 NA NA #> 402 NA NA #> 403 + NA NA #> 404 NA NA #> 405 NA NA #> 406 NA NA #> 407 NA NA #> 408 NA NA #> 409 NA NA #> 410 I NA NA #> 411 NA NA #> 412 NA NA #> 413 + NA NA #> 414 NA NA #> 415 NA NA #> 416 I NA NA #> 417 NA NA #> 418 NA NA #> 419 NA NA #> 420 NA NA #> 421 NA NA #> 422 NA NA #> 423 + NA NA #> 424 NA NA #> 425 NA NA #> 426 I NA NA #> 427 NA NA #> 428 NA NA #> 429 NA NA #> 430 I NA NA #> 431 NA NA #> 432 + NA NA #> 433 NA NA #> 434 NA NA #> 435 NA NA #> 436 NA NA #> 437 NA NA #> 438 NA NA #> 439 I NA NA #> 440 NA NA #> 441 I NA NA #> 442 + NA NA #> 443 NA NA #> 444 NA NA #> 445 I NA NA #> 446 I NA NA #> 447 NA NA #> 448 NA NA #> 449 I NA NA #> 450 NA NA #> 451 NA NA #> 452 + NA NA #> 453 NA NA #> 454 NA NA #> 455 I NA NA #> 456 NA NA #> 457 NA NA #> 458 NA NA #> 459 I NA NA #> 460 NA NA #> 461 NA NA #> 462 + NA NA #> 463 NA NA #> 464 NA NA #> 465 NA NA #> 466 I NA NA #> 467 NA NA #> 468 NA NA #> 469 I NA NA #> 470 NA NA #> 471 NA NA #> 472 + NA NA #> 473 NA NA #> 474 NA NA #> 475 NA NA #> 476 I NA NA #> 477 NA NA #> 478 NA NA #> 479 NA NA #> 480 NA NA #> 481 NA NA #> 482 + NA NA #> 483 NA NA #> 484 NA NA #> 485 I NA NA #> 486 U NA NA #> 487 I NA NA #> 488 NA NA #> 489 + NA NA #> 490 NA NA #> 491 NA NA #> 492 I NA NA #> 493 NA NA #> 494 NA NA #> 495 NA NA #> 496 NA NA #> 497 NA NA #> 498 NA NA #> 499 + NA NA #> 500 NA NA #> 501 NA NA #> 502 U NA NA #> 503 I NA NA #> 504 NA NA #> 505 NA NA #> 506 NA NA #> 507 NA NA #> 508 NA NA #> 509 + NA NA #> 510 NA NA #> 511 NA NA #> 512 I NA NA #> 513 I NA NA #> 514 NA NA #> 515 NA NA #> 516 U NA NA #> 517 NA NA #> 518 I NA NA #> 519 + NA NA #> 520 NA NA #> 521 NA NA #> 522 I NA NA #> 523 I NA NA #> 524 NA NA #> 525 NA NA #> 526 NA NA #> 527 + NA NA #> 528 NA NA #> 529 A NA NA #> 530 I NA NA #> 531 I NA NA #> 532 NA NA #> 533 NA NA #> 534 U NA NA #> 535 NA NA #> 536 I NA NA #> 537 + NA NA #> 538 NA NA #> 539 NA NA #> 540 NA NA #> 541 I NA NA #> 542 NA NA #> 543 NA NA #> 544 U NA NA #> 545 NA NA #> 546 NA NA #> 547 + NA NA #> 548 NA NA #> 549 NA NA #> 550 NA NA #> 551 NA NA #> 552 NA NA #> 553 NA NA #> 554 I NA NA #> 555 NA NA #> 556 NA NA #> 557 + NA NA #> 558 NA NA #> 559 NA NA #> 560 NA NA #> 561 NA NA #> 562 NA NA #> 563 NA NA #> 564 NA NA #> 565 NA NA #> 566 NA NA #> 567 + NA NA #> 568 NA NA #> 569 NA NA #> 570 NA NA #> 571 NA NA #> 572 NA NA #> 573 NA NA #> 574 U NA NA #> 575 NA NA #> 576 NA NA #> 577 + NA NA #> 578 NA NA #> 579 NA NA #> 580 NA NA #> 581 NA NA #> 582 NA NA #> 583 NA NA #> 584 NA NA #> 585 NA NA #> 586 NA NA #> 587 + NA NA #> 588 NA NA #> 589 NA NA #> 590 I NA NA #> 591 U NA NA #> 592 NA NA #> 593 NA NA #> 594 I NA NA #> 595 NA NA #> 596 NA NA #> 597 + NA NA #> 598 NA NA #> 599 NA NA #> 600 I NA NA #> 601 U NA NA #> 602 NA NA #> 603 NA NA #> 604 I NA NA #> 605 NA NA #> 606 I NA NA #> 607 + NA NA #> 608 NA NA #> 609 A NA NA #> 610 I NA NA #> 611 U NA NA #> 612 NA NA #> 613 NA NA #> 614 I NA NA #> 615 NA NA #> 616 NA NA #> 617 + NA NA #> 618 NA NA #> 619 NA NA #> 620 I NA NA #> 621 U NA NA #> 622 NA NA #> 623 NA NA #> 624 U NA NA #> 625 NA NA #> 626 + NA NA #> 627 NA NA #> 628 NA NA #> 629 I NA NA #> 630 U NA NA #> 631 NA NA #> 632 NA NA #> 633 U NA NA #> 634 NA NA #> 635 NA NA #> 636 + NA NA #> 637 NA NA #> 638 NA NA #> 639 I NA NA #> 640 U NA NA #> 641 NA NA #> 642 NA NA #> 643 U NA NA #> 644 NA NA #> 645 NA NA #> 646 + NA NA #> 647 NA NA #> 648 NA NA #> 649 NA NA #> 650 NA NA #> 651 NA NA #> 652 NA NA #> 653 U NA NA #> 654 NA NA #> 655 NA NA #> 656 + NA NA #> 657 NA NA #> 658 NA NA #> 659 NA NA #> 660 NA NA #> 661 NA NA #> 662 NA NA #> 663 I NA NA #> 664 NA NA #> 665 NA NA #> 666 + NA NA #> 667 NA NA #> 668 NA NA #> 669 NA NA #> 670 NA NA #> 671 NA NA #> 672 NA NA #> 673 I NA NA #> 674 NA NA #> 675 NA NA #> 676 + NA NA #> 677 NA NA #> 678 NA NA #> 679 NA NA #> 680 I NA NA #> 681 NA NA #> 682 NA NA #> 683 I NA NA #> 684 NA NA #> 685 NA NA #> 686 + NA NA #> 687 NA NA #> 688 NA NA #> 689 NA NA #> 690 NA NA #> 691 NA NA #> 692 NA NA #> 693 NA NA #> 694 NA NA #> 695 NA NA #> 696 + NA NA #> 697 NA NA #> 698 NA NA #> 699 NA NA #> 700 NA NA #> 701 NA NA #> 702 NA NA #> 703 I NA NA #> 704 NA NA #> 705 NA NA #> 706 + NA NA #> 707 NA NA #> 708 NA NA #> 709 I NA NA #> 710 U NA NA #> 711 NA NA #> 712 NA NA #> 713 I NA NA #> 714 NA NA #> 715 I NA NA #> 716 + NA NA #> 717 NA NA #> 718 NA NA #> 719 NA NA #> 720 I NA NA #> 721 U NA NA #> 722 NA NA #> 723 NA NA #> 724 + NA NA #> 725 NA NA #> 726 NA NA #> 727 NA NA #> 728 A NA NA #> 729 NA NA #> 730 + NA NA #> 731 NA NA #> 732 NA NA #> 733 NA NA #> 734 + NA NA #> 735 NA NA #> 736 NA NA #> 737 NA NA #> 738 I NA NA #> 739 NA NA #> 740 I NA NA #> 741 NA NA #> 742 NA NA #> 743 + NA NA #> 744 NA NA #> 745 NA NA #> 746 NA NA #> 747 I NA NA #> 748 NA NA #> 749 + NA NA #> 750 I NA NA #> 751 NA NA #> 752 NA NA #> 753 + NA NA #> 754 NA NA #> 755 NA NA #> 756 NA NA #> 757 NA NA #> 758 + NA NA #> 759 I NA NA #> 760 NA NA #> 761 NA NA #> 762 + NA NA #> 763 NA NA #> 764 NA NA #> 765 NA NA #> 766 NA NA #> 767 NA NA #> 768 + NA NA #> 769 I NA NA #> 770 NA NA #> 771 NA NA #> 772 + NA NA #> 773 NA NA #> 774 NA NA #> 775 NA NA #> 776 NA NA #> 777 + NA NA #> 778 NA NA #> 779 NA NA #> 780 NA NA #> 781 + NA NA #> 782 NA NA #> 783 NA NA #> 784 I NA NA #> 785 NA NA #> 786 + NA NA #> 787 NA NA #> 788 NA NA #> 789 NA NA #> 790 + NA NA #> 791 NA NA #> 792 NA NA #> 793 I NA NA #> 794 I NA NA #> 795 NA NA #> 796 I NA NA #> 797 NA NA #> 798 I NA NA #> 799 + NA NA #> 800 NA NA #> 801 NA NA #> 802 NA NA #> 803 NA NA #> 804 NA NA #> 805 + NA NA #> 806 NA NA #> 807 NA NA #> 808 NA NA #> 809 + NA NA #> 810 NA NA #> 811 NA NA #> 812 NA NA #> 813 NA NA #> 814 NA NA #> 815 NA NA #> 816 NA NA #> 817 NA NA #> 818 + NA NA #> 819 NA NA #> 820 NA NA #> 821 NA NA #> 822 NA NA #> 823 + NA NA #> 824 NA NA #> 825 NA NA #> 826 NA NA #> 827 + NA NA #> 828 NA NA #> 829 NA NA #> 830 NA NA #> 831 NA NA #> 832 I NA NA #> 833 NA NA #> 834 NA NA #> 835 + NA NA #> 836 NA NA #> 837 A NA NA #> 838 I NA NA #> 839 NA NA #> 840 NA NA #> 841 NA NA #> 842 NA NA #> 843 NA NA #> 844 + NA NA #> 845 NA NA #> 846 NA NA #> 847 NA NA #> 848 A NA NA #> 849 NA NA #> 850 + NA NA #> 851 I NA NA #> 852 NA NA #> 853 NA NA #> 854 + NA NA #> 855 NA NA #> 856 NA NA #> 857 NA NA #> 858 NA NA #> 859 NA NA #> 860 + NA NA #> 861 NA NA #> 862 NA NA #> 863 NA NA #> 864 + NA NA #> 865 NA NA #> 866 NA NA #> 867 NA NA #> 868 NA NA #> 869 NA NA #> 870 NA NA #> 871 NA NA #> 872 + NA NA #> 873 NA NA #> 874 NA NA #> 875 I NA NA #> 876 NA NA #> 877 NA NA #> 878 + NA NA #> 879 NA NA #> 880 NA NA #> 881 NA NA #> 882 + NA NA #> 883 NA NA #> 884 A NA NA #> 885 I NA NA #> 886 NA NA #> 887 NA NA #> 888 + NA NA #> 889 I NA NA #> 890 NA NA #> 891 NA NA #> 892 + NA NA #> 893 NA NA #> 894 NA NA #> 895 I NA NA #> 896 NA NA #> 897 NA NA #> 898 + NA NA #> 899 I NA NA #> 900 NA NA #> 901 NA NA #> 902 + NA NA #> 903 NA NA #> 904 NA NA #> 905 NA NA #> 906 NA NA #> 907 NA NA #> 908 + NA NA #> 909 I NA NA #> 910 NA NA #> 911 NA NA #> 912 + NA NA #> 913 NA NA #> 914 NA NA #> 915 NA NA #> 916 NA NA #> 917 NA NA #> 918 + NA NA #> 919 NA NA #> 920 NA NA #> 921 NA NA #> 922 + NA NA #> 923 NA NA #> 924 NA NA #> 925 NA NA #> 926 NA NA #> 927 NA NA #> 928 + NA NA #> 929 NA NA #> 930 NA NA #> 931 NA NA #> 932 + NA NA #> 933 NA NA #> 934 NA NA #> 935 I NA NA #> 936 U NA NA #> 937 NA NA #> 938 + NA NA #> 939 NA NA #> 940 NA NA #> 941 NA NA #> 942 + NA NA #> 943 NA NA #> 944 A NA NA #> 945 NA NA #> 946 I NA NA #> 947 NA NA #> 948 + NA NA #> 949 NA NA #> 950 NA NA #> 951 NA NA #> 952 + NA NA #> 953 NA NA #> 954 NA NA #> 955 NA NA #> 956 A NA NA #> 957 NA NA #> 958 + NA NA #> 959 NA NA #> 960 NA NA #> 961 NA NA #> 962 + NA NA #> 963 NA NA #> 964 NA NA #> 965 I NA NA #> 966 NA NA #> 967 NA NA #> 968 + NA NA #> 969 I NA NA #> 970 NA NA #> 971 NA NA #> 972 + NA NA #> 973 NA NA #> 974 NA NA #> 975 NA NA #> 976 NA NA #> 977 NA NA #> 978 + NA NA #> 979 I NA NA #> 980 NA NA #> 981 NA NA #> 982 + NA NA #> 983 NA NA #> 984 NA NA #> 985 NA NA #> 986 I NA NA #> 987 NA NA #> 988 + NA NA #> 989 U NA NA #> 990 NA NA #> 991 NA NA #> 992 + NA NA #> 993 NA NA #> 994 NA NA #> 995 NA NA #> 996 NA NA #> 997 NA NA #> 998 + NA NA #> 999 NA NA #> 1000 NA NA #> 1001 NA NA #> 1002 + NA NA #> 1003 NA NA #> 1004 NA NA #> 1005 NA NA #> 1006 NA NA #> 1007 NA NA #> 1008 + NA NA #> 1009 NA NA #> 1010 NA NA #> 1011 NA NA #> 1012 + NA NA #> 1013 NA NA #> 1014 NA NA #> 1015 NA NA #> 1016 NA NA #> 1017 I NA NA #> 1018 NA NA #> 1019 + NA NA #> 1020 NA NA #> 1021 NA NA #> 1022 NA NA #> 1023 NA NA #> 1024 NA NA #> 1025 + NA NA #> 1026 NA NA #> 1027 NA NA #> 1028 NA NA #> 1029 + NA NA #> 1030 NA NA #> 1031 A NA NA #> 1032 NA NA #> 1033 NA NA #> 1034 NA NA #> 1035 + NA NA #> 1036 I NA NA #> 1037 NA NA #> 1038 NA NA #> 1039 + NA NA #> 1040 NA NA #> 1041 A NA NA #> 1042 NA NA #> 1043 NA NA #> 1044 NA NA #> 1045 + NA NA #> 1046 NA NA #> 1047 NA NA #> 1048 NA NA #> 1049 + NA NA #> 1050 NA NA #> 1051 NA NA #> 1052 I NA NA #> 1053 NA NA #> 1054 NA NA #> 1055 + NA NA #> 1056 NA NA #> 1057 NA NA #> 1058 NA NA #> 1059 + NA NA #> 1060 NA NA #> 1061 NA NA #> 1062 NA NA #> 1063 NA NA #> 1064 NA NA #> 1065 + NA NA #> 1066 I NA NA #> 1067 NA NA #> 1068 NA NA #> 1069 + NA NA #> 1070 NA NA #> 1071 A NA NA #> 1072 NA NA #> 1073 I NA NA #> 1074 NA NA #> 1075 + NA NA #> 1076 I NA NA #> 1077 NA NA #> 1078 NA NA #> 1079 + NA NA #> 1080 NA NA #> 1081 NA NA #> 1082 NA NA #> 1083 NA NA #> 1084 NA NA #> 1085 NA NA #> 1086 I NA NA #> 1087 NA NA #> 1088 NA NA #> 1089 + NA NA #> 1090 NA NA #> 1091 NA NA #> 1092 NA NA #> 1093 NA NA #> 1094 NA NA #> 1095 NA NA #> 1096 I NA NA #> 1097 NA NA #> 1098 NA NA #> 1099 + NA NA #> 1100 NA NA #> 1101 NA NA #> 1102 A NA NA #> 1103 NA NA #> 1104 NA NA #> 1105 I NA NA #> 1106 NA NA #> 1107 NA NA #> 1108 + NA NA #> 1109 NA NA #> 1110 A NA NA #> 1111 I NA NA #> 1112 NA NA #> 1113 NA NA #> 1114 NA NA #> 1115 NA NA #> 1116 NA NA #> 1117 NA NA #> 1118 + NA NA #> 1119 NA NA #> 1120 NA NA #> 1121 I NA NA #> 1122 NA NA #> 1123 I NA NA #> 1124 NA NA #> 1125 NA NA #> 1126 + NA NA #> 1127 NA NA #> 1128 NA NA #> 1129 I NA NA #> 1130 NA NA #> 1131 U NA NA #> 1132 NA NA #> 1133 + NA NA #> 1134 NA NA #> 1135 NA NA #> 1136 I NA NA #> 1137 NA NA #> 1138 NA NA #> 1139 NA NA #> 1140 I NA NA #> 1141 NA NA #> 1142 NA NA #> 1143 + NA NA #> 1144 NA NA #> 1145 NA NA #> 1146 I NA NA #> 1147 I NA NA #> 1148 NA NA #> 1149 NA NA #> 1150 NA NA #> 1151 NA NA #> 1152 NA NA #> 1153 + NA NA #> 1154 NA NA #> 1155 NA NA #> 1156 I NA NA #> 1157 NA NA #> 1158 I NA NA #> 1159 NA NA #> 1160 NA NA #> 1161 + NA NA #> 1162 NA NA #> 1163 NA NA #> 1164 I NA NA #> 1165 A NA NA #> 1166 NA NA #> 1167 NA NA #> 1168 I NA NA #> 1169 NA NA #> 1170 NA NA #> 1171 + NA NA #> 1172 NA NA #> 1173 NA NA #> 1174 NA NA #> 1175 I NA NA #> 1176 NA NA #> 1177 NA NA #> 1178 I NA NA #> 1179 NA NA #> 1180 NA NA #> 1181 + NA NA #> 1182 NA NA #> 1183 NA NA #> 1184 NA NA #> 1185 I NA NA #> 1186 NA NA #> 1187 NA NA #> 1188 NA NA #> 1189 NA NA #> 1190 NA NA #> 1191 + NA NA #> 1192 NA NA #> 1193 NA NA #> 1194 I NA NA #> 1195 U NA NA #> 1196 NA NA #> 1197 NA NA #> 1198 NA NA #> 1199 NA NA #> 1200 NA NA #> 1201 + NA NA #> 1202 NA NA #> 1203 NA NA #> 1204 I NA NA #> 1205 NA NA #> 1206 NA NA #> 1207 NA NA #> 1208 NA NA #> 1209 + NA NA #> 1210 NA NA #> 1211 NA NA #> 1212 I NA NA #> 1213 NA NA #> 1214 NA NA #> 1215 NA NA #> 1216 NA NA #> 1217 NA NA #> 1218 NA NA #> 1219 + NA NA #> 1220 NA NA #> 1221 NA NA #> 1222 I NA NA #> 1223 U NA NA #> 1224 NA NA #> 1225 NA NA #> 1226 I NA NA #> 1227 NA NA #> 1228 + NA NA #> 1229 NA NA #> 1230 A NA NA #> 1231 NA NA #> 1232 A NA NA #> 1233 NA NA #> 1234 NA NA #> 1235 NA NA #> 1236 NA NA #> 1237 NA NA #> 1238 + NA NA #> 1239 NA NA #> 1240 NA NA #> 1241 I NA NA #> 1242 A NA NA #> 1243 NA NA #> 1244 NA NA #> 1245 NA NA #> 1246 NA NA #> 1247 NA NA #> 1248 + NA NA #> 1249 NA NA #> 1250 A NA NA #> 1251 + NA NA #> 1252 NA NA #> 1253 NA NA #> 1254 NA NA #> 1255 NA NA #> 1256 NA NA #> 1257 NA NA #> 1258 NA NA #> 1259 NA NA #> 1260 NA NA #> 1261 U NA NA #> 1262 NA NA #> 1263 NA NA #> 1264 NA NA #> 1265 NA NA #> 1266 NA NA #> 1267 + NA NA #> 1268 NA NA #> 1269 NA NA #> 1270 I NA NA #> 1271 U NA NA #> 1272 NA NA #> 1273 NA NA #> 1274 I NA NA #> 1275 NA NA #> 1276 NA NA #> 1277 + NA NA #> 1278 NA NA #> 1279 NA NA #> 1280 I NA NA #> 1281 I NA NA #> 1282 NA NA #> 1283 NA NA #> 1284 I NA NA #> 1285 NA NA #> 1286 NA NA #> 1287 + NA NA #> 1288 NA NA #> 1289 NA NA #> 1290 + NA NA #> 1291 I NA NA #> 1292 NA NA #> 1293 NA NA #> 1294 NA NA #> 1295 I NA NA #> 1296 NA NA #> 1297 I NA NA #> 1298 NA NA #> 1299 NA NA #> 1300 I NA NA #> 1301 NA NA #> 1302 NA NA #> 1303 NA NA #> 1304 I NA NA #> 1305 NA NA #> 1306 NA NA #> 1307 + NA NA #> 1308 NA NA #> 1309 NA NA #> 1310 I NA NA #> 1311 I NA NA #> 1312 NA NA #> 1313 NA NA #> 1314 I NA NA #> 1315 NA NA #> 1316 NA NA #> 1317 + NA NA #> 1318 NA NA #> 1319 NA NA #> 1320 NA NA #> 1321 NA NA #> 1322 NA NA #> 1323 NA NA #> 1324 U NA NA #> 1325 NA NA #> 1326 NA NA #> 1327 + NA NA #> 1328 NA NA #> 1329 NA NA #> 1330 NA NA #> 1331 NA NA #> 1332 NA NA #> 1333 NA NA #> 1334 I NA NA #> 1335 NA NA #> 1336 NA NA #> 1337 + NA NA #> 1338 NA NA #> 1339 NA NA #> 1340 NA NA #> 1341 NA NA #> 1342 NA NA #> 1343 NA NA #> 1344 I NA NA #> 1345 NA NA #> 1346 NA NA #> 1347 + NA NA #> 1348 NA NA #> 1349 A NA NA #> 1350 NA NA #> 1351 NA NA #> 1352 NA NA #> 1353 NA NA #> 1354 NA NA #> 1355 NA NA #> 1356 NA NA #> 1357 + NA NA #> 1358 NA NA #> 1359 NA NA #> 1360 I NA NA #> 1361 U NA NA #> 1362 NA NA #> 1363 NA NA #> 1364 I NA NA #> 1365 NA NA #> 1366 NA NA #> 1367 + NA NA #> 1368 NA NA #> 1369 NA NA #> 1370 I NA NA #> 1371 I NA NA #> 1372 NA NA #> 1373 NA NA #> 1374 NA NA #> 1375 NA NA #> 1376 NA NA #> 1377 + NA NA #> 1378 NA NA #> 1379 NA NA #> 1380 I NA NA #> 1381 U NA NA #> 1382 NA NA #> 1383 NA NA #> 1384 NA NA #> 1385 NA NA #> 1386 NA NA #> 1387 + NA NA #> 1388 NA NA #> 1389 NA NA #> 1390 I NA NA #> 1391 U NA NA #> 1392 NA NA #> 1393 NA NA #> 1394 U NA NA #> 1395 NA NA #> 1396 I NA NA #> 1397 + NA NA #> 1398 NA NA #> 1399 NA NA #> 1400 I NA NA #> 1401 U NA NA #> 1402 NA NA #> 1403 NA NA #> 1404 I NA NA #> 1405 NA NA #> 1406 I NA NA #> 1407 + NA NA #> 1408 NA NA #> 1409 A NA NA #> 1410 I NA NA #> 1411 U NA NA #> 1412 NA NA #> 1413 NA NA #> 1414 I NA NA #> 1415 NA NA #> 1416 NA NA #> 1417 + NA NA #> 1418 NA NA #> 1419 NA NA #> 1420 I NA NA #> 1421 NA NA #> 1422 NA NA #> 1423 NA NA #> 1424 I NA NA #> 1425 NA NA #> 1426 NA NA #> 1427 + NA NA #> 1428 NA NA #> 1429 NA NA #> 1430 NA NA #> 1431 I NA NA #> 1432 NA NA #> 1433 NA NA #> 1434 I NA NA #> 1435 NA NA #> 1436 NA NA #> 1437 + NA NA #> 1438 NA NA #> 1439 A NA NA #> 1440 I NA NA #> 1441 I NA NA #> 1442 NA NA #> 1443 NA NA #> 1444 NA NA #> 1445 NA NA #> 1446 NA NA #> 1447 + NA NA #> 1448 NA NA #> 1449 NA NA #> 1450 NA NA #> 1451 NA NA #> 1452 I NA NA #> 1453 NA NA #> 1454 NA NA #> 1455 + NA NA #> 1456 NA NA #> 1457 NA NA #> 1458 NA NA #> 1459 A NA NA #> 1460 NA NA #> 1461 NA NA #> 1462 U NA NA #> 1463 NA NA #> 1464 NA NA #> 1465 + NA NA #> 1466 NA NA #> 1467 A NA NA #> 1468 NA NA #> 1469 A NA NA #> 1470 I NA NA #> 1471 NA NA #> 1472 NA NA #> 1473 + NA NA #> 1474 NA NA #> 1475 NA NA #> 1476 NA NA #> 1477 NA NA #> 1478 NA NA #> 1479 NA NA #> 1480 U NA NA #> 1481 NA NA #> 1482 NA NA #> 1483 + NA NA #> 1484 NA NA #> 1485 NA NA #> 1486 I NA NA #> 1487 NA NA #> 1488 NA NA #> 1489 NA NA #> 1490 I NA NA #> 1491 NA NA #> 1492 NA NA #> 1493 + NA NA #> 1494 NA NA #> 1495 NA NA #> 1496 NA NA #> 1497 NA NA #> 1498 NA NA #> 1499 NA NA #> 1500 NA NA #> 1501 NA NA #> 1502 NA NA #> 1503 U NA NA #> 1504 + NA NA #> 1505 I NA NA #> 1506 + NA NA #> 1507 NA NA #> 1508 NA NA #> 1509 NA NA #> 1510 NA NA #> 1511 NA NA #> 1512 NA NA #> 1513 NA NA #> 1514 U NA NA #> 1515 + NA NA #> 1516 NA NA #> 1517 + NA NA #> 1518 NA NA #> 1519 I NA NA #> 1520 NA NA #> 1521 NA NA #> 1522 NA NA #> 1523 NA NA #> 1524 NA NA #> 1525 I NA NA #> 1526 NA NA #> 1527 + NA NA #> 1528 NA NA #> 1529 I NA NA #> 1530 A NA NA #> 1531 NA NA #> 1532 NA NA #> 1533 NA NA #> 1534 NA NA #> 1535 NA NA #> 1536 NA NA #> 1537 + NA NA #> 1538 NA NA #> 1539 I NA NA #> 1540 NA NA #> 1541 NA NA #> 1542 NA NA #> 1543 NA NA #> 1544 NA NA #> 1545 G NA NA #> 1546 NA NA #> 1547 NA NA #> 1548 + NA NA #> 1549 NA NA #> 1550 I NA NA #> 1551 NA NA #> 1552 I NA NA #> 1553 NA NA #> 1554 NA NA #> 1555 + NA NA #> 1556 I NA NA #> 1557 NA NA #> 1558 NA NA #> 1559 + NA NA #> 1560 NA NA #> 1561 NA NA #> 1562 NA NA #> 1563 NA NA #> 1564 NA NA #> 1565 + NA NA #> 1566 NA NA #> 1567 NA NA #> 1568 NA NA #> 1569 + NA NA #> 1570 NA NA #> 1571 NA NA #> 1572 NA NA #> 1573 NA NA #> 1574 NA NA #> 1575 + NA NA #> 1576 I NA NA #> 1577 NA NA #> 1578 NA NA #> 1579 + NA NA #> 1580 NA NA #> 1581 NA NA #> 1582 NA NA #> 1583 A NA NA #> 1584 NA NA #> 1585 + NA NA #> 1586 NA NA #> 1587 NA NA #> 1588 NA NA #> 1589 + NA NA #> 1590 NA NA #> 1591 A NA NA #> 1592 NA NA #> 1593 NA NA #> 1594 NA NA #> 1595 + NA NA #> 1596 NA NA #> 1597 NA NA #> 1598 NA NA #> 1599 + NA NA #> 1600 NA NA #> 1601 NA NA #> 1602 NA NA #> 1603 A NA NA #> 1604 NA NA #> 1605 + NA NA #> 1606 I NA NA #> 1607 NA NA #> 1608 NA NA #> 1609 + NA NA #> 1610 NA NA #> 1611 NA NA #> 1612 NA NA #> 1613 A NA NA #> 1614 NA NA #> 1615 + NA NA #> 1616 I NA NA #> 1617 NA NA #> 1618 NA NA #> 1619 + NA NA #> 1620 NA NA #> 1621 NA NA #> 1622 NA NA #> 1623 NA NA #> 1624 NA NA #> 1625 + NA NA #> 1626 I NA NA #> 1627 NA NA #> 1628 NA NA #> 1629 + NA NA #> 1630 NA NA #> 1631 NA NA #> 1632 NA NA #> 1633 NA NA #> 1634 NA NA #> 1635 + NA NA #> 1636 U NA NA #> 1637 NA NA #> 1638 NA NA #> 1639 + NA NA #> 1640 NA NA #> 1641 NA NA #> 1642 NA NA #> 1643 NA NA #> 1644 NA NA #> 1645 + NA NA #> 1646 I NA NA #> 1647 NA NA #> 1648 NA NA #> 1649 + NA NA #> 1650 NA NA #> 1651 NA NA #> 1652 NA NA #> 1653 NA NA #> 1654 NA NA #> 1655 + NA NA #> 1656 NA NA #> 1657 NA NA #> 1658 NA NA #> 1659 + NA NA #> 1660 NA NA #> 1661 NA NA #> 1662 NA NA #> 1663 NA NA #> 1664 NA NA #> 1665 + NA NA #> 1666 NA NA #> 1667 NA NA #> 1668 NA NA #> 1669 + NA NA #> 1670 NA NA #> 1671 NA NA #> 1672 NA NA #> 1673 NA NA #> 1674 NA NA #> 1675 + NA NA #> 1676 I NA NA #> 1677 NA NA #> 1678 NA NA #> 1679 + NA NA #> 1680 NA NA #> 1681 NA NA #> 1682 A NA NA #> 1683 NA NA #> 1684 NA NA #> 1685 + NA NA #> 1686 NA NA #> 1687 NA NA #> 1688 NA NA #> 1689 + NA NA #> 1690 NA NA #> 1691 NA NA #> 1692 NA NA #> 1693 NA NA #> 1694 NA NA #> 1695 + NA NA #> 1696 U NA NA #> 1697 NA NA #> 1698 NA NA #> 1699 + NA NA #> 1700 NA NA #> 1701 NA NA #> 1702 NA NA #> 1703 NA NA #> 1704 NA NA #> 1705 + NA NA #> 1706 I NA NA #> 1707 NA NA #> 1708 NA NA #> 1709 + NA NA #> 1710 NA NA #> 1711 NA NA #> 1712 NA NA #> 1713 NA NA #> 1714 NA NA #> 1715 + NA NA #> 1716 I NA NA #> 1717 NA NA #> 1718 NA NA #> 1719 + NA NA #> 1720 NA NA #> 1721 NA NA #> 1722 NA NA #> 1723 NA NA #> 1724 NA NA #> 1725 + NA NA #> 1726 I NA NA #> 1727 NA NA #> 1728 NA NA #> 1729 + NA NA #> 1730 NA NA #> 1731 NA NA #> 1732 NA NA #> 1733 NA NA #> 1734 NA NA #> 1735 + NA NA #> 1736 I NA NA #> 1737 NA NA #> 1738 NA NA #> 1739 + NA NA #> 1740 NA NA #> 1741 NA NA #> 1742 NA NA #> 1743 A NA NA #> 1744 NA NA #> 1745 + NA NA #> 1746 U NA NA #> 1747 NA NA #> 1748 NA NA #> 1749 + NA NA #> 1750 NA NA #> 1751 NA NA #> 1752 NA NA #> 1753 NA NA #> 1754 NA NA #> 1755 + NA NA #> 1756 NA NA #> 1757 NA NA #> 1758 NA NA #> 1759 + NA NA #> 1760 NA NA #> 1761 NA NA #> 1762 NA NA #> 1763 NA NA #> 1764 NA NA #> 1765 + NA NA #> 1766 NA NA #> 1767 NA NA #> 1768 NA NA #> 1769 + NA NA #> 1770 NA NA #> 1771 NA NA #> 1772 NA NA #> 1773 NA NA #> 1774 + NA NA #> 1775 NA NA #> 1776 NA NA #> 1777 NA NA #> 1778 + NA NA #> 1779 NA NA #> 1780 NA NA #> 1781 NA NA #> 1782 NA NA #> 1783 NA NA #> 1784 + NA NA #> 1785 I NA NA #> 1786 NA NA #> 1787 NA NA #> 1788 + NA NA #> 1789 NA NA #> 1790 A NA NA #> 1791 NA NA #> 1792 NA NA #> 1793 NA NA #> 1794 + NA NA #> 1795 NA NA #> 1796 NA NA #> 1797 NA NA #> 1798 + NA NA #> 1799 NA NA #> 1800 NA NA #> 1801 I NA NA #> 1802 NA NA #> 1803 NA NA #> 1804 + NA NA #> 1805 U NA NA #> 1806 NA NA #> 1807 NA NA #> 1808 + NA NA #> 1809 NA NA #> 1810 NA NA #> 1811 NA NA #> 1812 NA NA #> 1813 + NA NA #> 1814 U NA NA #> 1815 NA NA #> 1816 NA NA #> 1817 + NA NA #> 1818 NA NA #> 1819 NA NA #> 1820 NA NA #> 1821 NA NA #> 1822 NA NA #> 1823 + NA NA #> 1824 NA NA #> 1825 NA NA #> 1826 NA NA #> 1827 + NA NA #> 1828 NA NA #> 1829 NA NA #> 1830 NA NA #> 1831 A NA NA #> 1832 U NA NA #> 1833 NA NA #> 1834 + NA NA #> 1835 NA NA #> 1836 NA NA #> 1837 NA NA #> 1838 NA NA #> 1839 NA NA #> 1840 + NA NA #> 1841 I NA NA #> 1842 NA NA #> 1843 NA NA #> 1844 + NA NA #> 1845 NA NA #> 1846 NA NA #> 1847 NA NA #> 1848 NA NA #> 1849 I NA NA #> 1850 NA NA #> 1851 NA NA #> 1852 + NA NA #> 1853 NA NA #> 1854 NA NA #> 1855 A NA NA #> 1856 NA NA #> 1857 NA NA #> 1858 + NA NA #> 1859 NA NA #> 1860 NA NA #> 1861 NA NA #> 1862 + NA NA #> 1863 NA NA #> 1864 NA NA #> 1865 NA NA #> 1866 NA NA #> 1867 NA NA #> 1868 + NA NA #> 1869 I NA NA #> 1870 NA NA #> 1871 NA NA #> 1872 + NA NA #> 1873 NA NA #> 1874 NA NA #> 1875 U NA NA #> 1876 U NA NA #> 1877 NA NA #> 1878 + NA NA #> 1879 NA NA #> 1880 NA NA #> 1881 NA NA #> 1882 + NA NA #> 1883 NA NA #> 1884 NA NA #> 1885 I NA NA #> 1886 NA NA #> 1887 NA NA #> 1888 NA NA #> 1889 U NA NA #> 1890 NA NA #> 1891 NA NA #> 1892 + NA NA #> 1893 NA NA #> 1894 NA NA #> 1895 NA NA #> 1896 NA NA #> 1897 NA NA #> 1898 NA NA #> 1899 I NA NA #> 1900 NA NA #> 1901 NA NA #> 1902 + NA NA #> 1903 NA NA #> 1904 NA NA #> 1905 I NA NA #> 1906 NA NA #> 1907 NA NA #> 1908 NA NA #> 1909 U NA NA #> 1910 NA NA #> 1911 NA NA #> 1912 + NA NA #> 1913 NA NA #> 1914 NA NA #> 1915 NA NA #> 1916 NA NA #> 1917 NA NA #> 1918 NA NA #> 1919 U NA NA #> 1920 NA NA #> 1921 NA NA #> 1922 + NA NA #> 1923 NA NA #> 1924 NA NA #> 1925 NA NA #> 1926 NA NA #> 1927 NA NA #> 1928 NA NA #> 1929 U NA NA #> 1930 NA NA #> 1931 NA NA #> 1932 + NA NA #> 1933 NA NA #> 1934 NA NA #> 1935 NA NA #> 1936 A NA NA #> 1937 NA NA #> 1938 NA NA #> 1939 U NA NA #> 1940 NA NA #> 1941 NA NA #> 1942 + NA NA #> 1943 NA NA #> 1944 A NA NA #> 1945 + NA NA #> 1946 I NA NA #> 1947 NA NA #> 1948 NA NA #> 1949 NA NA #> 1950 I NA NA #> 1951 NA NA #> 1952 NA NA #> 1953 NA NA #> 1954 NA NA #> 1955 NA NA #> 1956 NA NA #> 1957 NA NA #> 1958 NA NA #> 1959 NA NA #> 1960 NA NA #> 1961 NA NA #> 1962 + NA NA #> 1963 NA NA #> 1964 NA NA #> 1965 I NA NA #> 1966 NA NA #> 1967 NA NA #> 1968 NA NA #> 1969 NA NA #> 1970 NA NA #> 1971 NA NA #> 1972 + NA NA #> 1973 NA NA #> 1974 NA NA #> 1975 NA NA #> 1976 A NA NA #> 1977 NA NA #> 1978 NA NA #> 1979 NA NA #> 1980 NA NA #> 1981 NA NA #> 1982 + NA NA #> 1983 NA NA #> 1984 NA NA #> 1985 I NA NA #> 1986 NA NA #> 1987 NA NA #> 1988 NA NA #> 1989 I NA NA #> 1990 NA NA #> 1991 NA NA #> 1992 + NA NA #> 1993 NA NA #> 1994 NA NA #> 1995 I NA NA #> 1996 NA NA #> 1997 NA NA #> 1998 NA NA #> 1999 I NA NA #> 2000 NA NA #> 2001 NA NA #> 2002 + NA NA #> 2003 NA NA #> 2004 NA NA #> 2005 NA NA #> 2006 NA NA #> 2007 NA NA #> 2008 NA NA #> 2009 U NA NA #> 2010 NA NA #> 2011 NA NA #> 2012 + NA NA #> 2013 NA NA #> 2014 NA NA #> 2015 NA NA #> 2016 NA NA #> 2017 NA NA #> 2018 NA NA #> 2019 I NA NA #> 2020 NA NA #> 2021 NA NA #> 2022 + NA NA #> 2023 NA NA #> 2024 NA NA #> 2025 NA NA #> 2026 NA NA #> 2027 NA NA #> 2028 NA NA #> 2029 I NA NA #> 2030 NA NA #> 2031 NA NA #> 2032 + NA NA #> 2033 NA NA #> 2034 NA NA #> 2035 I NA NA #> 2036 A NA NA #> 2037 NA NA #> 2038 NA NA #> 2039 NA NA #> 2040 NA NA #> 2041 NA NA #> 2042 + NA NA #> 2043 NA NA #> 2044 NA NA #> 2045 NA NA #> 2046 A NA NA #> 2047 NA NA #> 2048 NA NA #> 2049 NA NA #> 2050 NA NA #> 2051 NA NA #> 2052 + NA NA #> 2053 NA NA #> 2054 NA NA #> 2055 I NA NA #> 2056 NA NA #> 2057 NA NA #> 2058 NA NA #> 2059 NA NA #> 2060 NA NA #> 2061 NA NA #> 2062 + NA NA #> 2063 NA NA #> 2064 NA NA #> 2065 I NA NA #> 2066 NA NA #> 2067 NA NA #> 2068 NA NA #> 2069 U NA NA #> 2070 NA NA #> 2071 NA NA #> 2072 + NA NA #> 2073 NA NA #> 2074 NA NA #> 2075 I NA NA #> 2076 A NA NA #> 2077 NA NA #> 2078 NA NA #> 2079 U NA NA #> 2080 NA NA #> 2081 NA NA #> 2082 + NA NA #> 2083 NA NA #> 2084 A NA NA #> 2085 I NA NA #> 2086 NA NA #> 2087 NA NA #> 2088 NA NA #> 2089 U NA NA #> 2090 NA NA #> 2091 NA NA #> 2092 + NA NA #> 2093 NA NA #> 2094 NA NA #> 2095 NA NA #> 2096 NA NA #> 2097 NA NA #> 2098 NA NA #> 2099 U NA NA #> 2100 NA NA #> 2101 NA NA #> 2102 + NA NA #> 2103 NA NA #> 2104 NA NA #> 2105 NA NA #> 2106 NA NA #> 2107 NA NA #> 2108 NA NA #> 2109 U NA NA #> 2110 NA NA #> 2111 NA NA #> 2112 + NA NA #> 2113 NA NA #> 2114 NA NA #> 2115 NA NA #> 2116 A NA NA #> 2117 NA NA #> 2118 NA NA #> 2119 I NA NA #> 2120 NA NA #> 2121 NA NA #> 2122 + NA NA #> 2123 NA NA #> 2124 NA NA #> 2125 I NA NA #> 2126 NA NA #> 2127 NA NA #> 2128 NA NA #> 2129 I NA NA #> 2130 NA NA #> 2131 NA NA #> 2132 + NA NA #> 2133 NA NA #> 2134 A NA NA #> 2135 I NA NA #> 2136 NA NA #> 2137 NA NA #> 2138 NA NA #> 2139 NA NA #> 2140 NA NA #> 2141 NA NA #> 2142 + NA NA #> 2143 NA NA #> 2144 NA NA #> 2145 NA NA #> 2146 NA NA #> 2147 NA NA #> 2148 NA NA #> 2149 I NA NA #> 2150 NA NA #> 2151 NA NA #> 2152 + NA NA #> 2153 NA NA #> 2154 NA NA #> 2155 U NA NA #> 2156 A NA NA #> 2157 NA NA #> 2158 NA NA #> 2159 I NA NA #> 2160 NA NA #> 2161 NA NA #> 2162 + NA NA #> 2163 NA NA #> 2164 NA NA #> 2165 I NA NA #> 2166 A NA NA #> 2167 NA NA #> 2168 NA NA #> 2169 I NA NA #> 2170 NA NA #> 2171 NA NA #> 2172 + NA NA #> 2173 NA NA #> 2174 NA NA #> 2175 I NA NA #> 2176 NA NA #> 2177 NA NA #> 2178 NA NA #> 2179 I NA NA #> 2180 NA NA #> 2181 + NA NA #> 2182 NA NA #> 2183 NA NA #> 2184 U NA NA #> 2185 NA NA #> 2186 NA NA #> 2187 U NA NA #> 2188 NA NA #> 2189 + NA NA #> 2190 NA NA #> 2191 NA NA #> 2192 NA NA #> 2193 NA NA #> 2194 I NA NA #> 2195 NA NA #> 2196 NA NA #> 2197 + NA NA #> 2198 NA NA #> 2199 NA NA #> 2200 NA NA #> 2201 A NA NA #> 2202 NA NA #> 2203 NA NA #> 2204 NA NA #> 2205 NA NA #> 2206 NA NA #> 2207 + NA NA #> 2208 NA NA #> 2209 NA NA #> 2210 NA NA #> 2211 A NA NA #> 2212 NA NA #> 2213 NA NA #> 2214 I NA NA #> 2215 NA NA #> 2216 NA NA #> 2217 + NA NA #> 2218 NA NA #> 2219 NA NA #> 2220 NA NA #> 2221 A NA NA #> 2222 NA NA #> 2223 NA NA #> 2224 I NA NA #> 2225 NA NA #> 2226 NA NA #> 2227 + NA NA #> 2228 NA NA #> 2229 NA NA #> 2230 NA NA #> 2231 NA NA #> 2232 NA NA #> 2233 NA NA #> 2234 U NA NA #> 2235 NA NA #> 2236 NA NA #> 2237 + NA NA #> 2238 NA NA #> 2239 NA NA #> 2240 NA NA #> 2241 NA NA #> 2242 NA NA #> 2243 NA NA #> 2244 NA NA #> 2245 NA NA #> 2246 + NA NA #> 2247 NA NA #> 2248 NA NA #> 2249 NA NA #> 2250 A NA NA #> 2251 NA NA #> 2252 NA NA #> 2253 I NA NA #> 2254 NA NA #> 2255 NA NA #> 2256 + NA NA #> 2257 NA NA #> 2258 NA NA #> 2259 NA NA #> 2260 NA NA #> 2261 NA NA #> 2262 NA NA #> 2263 NA NA #> 2264 NA NA #> 2265 NA NA #> 2266 I NA NA #> 2267 + NA NA #> 2268 NA NA #> 2269 + NA NA #> 2270 NA NA #> 2271 I NA NA #> 2272 NA NA #> 2273 NA NA #> 2274 NA NA #> 2275 NA NA #> 2276 NA NA #> 2277 U NA NA #> 2278 + NA NA #> 2279 NA NA #> 2280 + NA NA #> 2281 NA NA #> 2282 I NA NA #> 2283 NA NA #> 2284 NA NA #> 2285 NA NA #> 2286 NA NA #> 2287 NA NA #> 2288 U NA NA #> 2289 + NA NA #> 2290 NA NA #> 2291 + NA NA #> 2292 I NA NA #> 2293 NA NA #> 2294 NA NA #> 2295 NA NA #> 2296 NA NA #> 2297 NA NA #> 2298 I NA NA #> 2299 NA NA #> 2300 + NA NA #> 2301 NA NA #> 2302 U NA NA #> 2303 A NA NA #> 2304 NA NA #> 2305 NA NA #> 2306 NA NA #> 2307 NA NA #> 2308 G NA NA #> 2309 NA NA #> 2310 NA NA #> 2311 + NA NA #> 2312 NA NA #> 2313 I NA NA #> 2314 NA NA #> 2315 NA NA #> 2316 NA NA #> 2317 NA NA #> 2318 NA NA #> 2319 I NA NA #> 2320 NA NA #> 2321 NA NA #> 2322 + NA NA #> 2323 NA NA #> 2324 I NA NA #> 2325 NA NA #> 2326 NA NA #> 2327 NA NA #> 2328 NA NA #> 2329 NA NA #> 2330 + NA NA #> 2331 I NA NA #> 2332 NA NA #> 2333 NA NA #> 2334 NA NA #> 2335 I NA NA #> 2336 NA NA #> 2337 NA NA #> 2338 + NA NA #> 2339 NA NA #> 2340 I NA NA #> 2341 NA NA #> 2342 NA NA #> 2343 NA NA #> 2344 NA NA #> 2345 NA NA #> 2346 U NA NA #> 2347 NA NA #> 2348 NA NA #> 2349 + NA NA #> 2350 NA NA #> 2351 I NA NA #> 2352 NA NA #> 2353 NA NA #> 2354 NA NA #> 2355 NA NA #> 2356 NA NA #> 2357 U NA NA #> 2358 NA NA #> 2359 NA NA #> 2360 + NA NA #> 2361 NA NA #> 2362 I NA NA #> 2363 NA NA #> 2364 NA NA #> 2365 NA NA #> 2366 NA NA #> 2367 NA NA #> 2368 I NA NA #> 2369 NA NA #> 2370 NA NA #> 2371 + NA NA #> 2372 NA NA #> 2373 U NA NA #> 2374 NA NA #> 2375 NA NA #> 2376 NA NA #> 2377 NA NA #> 2378 NA NA #> 2379 I NA NA #> 2380 NA NA #> 2381 NA NA #> 2382 + NA NA #> 2383 NA NA #> 2384 I NA NA #> 2385 NA NA #> 2386 NA NA #> 2387 NA NA #> 2388 NA NA #> 2389 NA NA #> 2390 NA NA #> 2391 NA NA #> 2392 NA NA #> 2393 NA NA #> 2394 NA NA #> 2395 NA NA #> 2396 NA NA #> 2397 NA NA #> 2398 NA NA #> 2399 NA NA #> 2400 NA NA #> 2401 NA NA #> 2402 U NA NA #> 2403 NA NA #> 2404 NA NA #> 2405 + NA NA #> 2406 NA NA #> 2407 I NA NA #> 2408 A NA NA #> 2409 A NA NA #> 2410 NA NA #> 2411 NA NA #> 2412 NA NA #> 2413 U NA NA #> 2414 NA NA #> 2415 NA NA #> 2416 + NA NA #> 2417 NA NA #> 2418 I NA NA #> 2419 NA NA #> 2420 NA NA #> 2421 NA NA #> 2422 NA NA #> 2423 NA NA #> 2424 U NA NA #> 2425 NA NA #> 2426 NA NA #> 2427 + NA NA #> 2428 NA NA #> 2429 A NA NA #> 2430 NA NA #> 2431 NA NA #> 2432 NA NA #> 2433 NA NA #> 2434 NA NA #> 2435 I NA NA #> 2436 NA NA #> 2437 NA NA #> 2438 + NA NA #> 2439 NA NA #> 2440 I NA NA #> 2441 NA NA #> 2442 A NA NA #> 2443 NA NA #> 2444 NA NA #> 2445 NA NA #> 2446 U NA NA #> 2447 NA NA #> 2448 NA NA #> 2449 + NA NA #> 2450 NA NA #> 2451 I NA NA #> 2452 NA NA #> 2453 NA NA #> 2454 NA NA #> 2455 NA NA #> 2456 NA NA #> 2457 U NA NA #> 2458 NA NA #> 2459 NA NA #> 2460 + NA NA #> 2461 NA NA #> 2462 I NA NA #> 2463 NA NA #> 2464 NA NA #> 2465 NA NA #> 2466 NA NA #> 2467 NA NA #> 2468 NA NA #> 2469 NA NA #> 2470 NA NA #> 2471 + NA NA #> 2472 NA NA #> 2473 I NA NA #> 2474 NA NA #> 2475 NA NA #> 2476 NA NA #> 2477 NA NA #> 2478 I NA NA #> 2479 NA NA #> 2480 NA NA #> 2481 + NA NA #> 2482 NA NA #> 2483 I NA NA #> 2484 NA NA #> 2485 NA NA #> 2486 NA NA #> 2487 NA NA #> 2488 I NA NA #> 2489 NA NA #> 2490 NA NA #> 2491 + NA NA #> 2492 NA NA #> 2493 NA NA #> 2494 NA NA #> 2495 NA NA #> 2496 NA NA #> 2497 NA NA #> 2498 NA NA #> 2499 U NA NA #> 2500 NA NA #> 2501 NA NA #> 2502 + NA NA #> 2503 NA NA #> 2504 I NA NA #> 2505 NA NA #> 2506 NA NA #> 2507 NA NA #> 2508 NA NA #> 2509 NA NA #> 2510 U NA NA #> 2511 NA NA #> 2512 NA NA #> 2513 + NA NA #> 2514 NA NA #> 2515 I NA NA #> 2516 NA NA #> 2517 NA NA #> 2518 NA NA #> 2519 NA NA #> 2520 NA NA #> 2521 U NA NA #> 2522 NA NA #> 2523 NA NA #> 2524 + NA NA #> 2525 NA NA #> 2526 I NA NA #> 2527 A NA NA #> 2528 NA NA #> 2529 NA NA #> 2530 NA NA #> 2531 NA NA #> 2532 U NA NA #> 2533 NA NA #> 2534 NA NA #> 2535 + NA NA #> 2536 NA NA #> 2537 NA NA #> 2538 A NA NA #> 2539 NA NA #> 2540 NA NA #> 2541 NA NA #> 2542 NA NA #> 2543 U NA NA #> 2544 NA NA #> 2545 NA NA #> 2546 + NA NA #> 2547 NA NA #> 2548 I NA NA #> 2549 NA NA #> 2550 NA NA #> 2551 NA NA #> 2552 NA NA #> 2553 NA NA #> 2554 U NA NA #> 2555 NA NA #> 2556 NA NA #> 2557 + NA NA #> 2558 NA NA #> 2559 I NA NA #> 2560 A NA NA #> 2561 NA NA #> 2562 NA NA #> 2563 NA NA #> 2564 NA NA #> 2565 U NA NA #> 2566 NA NA #> 2567 U NA NA #> 2568 + NA NA #> 2569 NA NA #> 2570 I NA NA #> 2571 NA NA #> 2572 NA NA #> 2573 NA NA #> 2574 NA NA #> 2575 NA NA #> 2576 U NA NA #> 2577 NA NA #> 2578 NA NA #> 2579 + NA NA #> 2580 NA NA #> 2581 I NA NA #> 2582 NA NA #> 2583 I NA NA #> 2584 NA NA #> 2585 NA NA #> 2586 NA NA #> 2587 U NA NA #> 2588 NA NA #> 2589 NA NA #> 2590 + NA NA #> 2591 NA NA #> 2592 U NA NA #> 2593 NA NA #> 2594 NA NA #> 2595 NA NA #> 2596 NA NA #> 2597 NA NA #> 2598 U NA NA #> 2599 NA NA #> 2600 NA NA #> 2601 + NA NA #> 2602 NA NA #> 2603 I NA NA #> 2604 NA NA #> 2605 A NA NA #> 2606 NA NA #> 2607 NA NA #> 2608 NA NA #> 2609 U NA NA #> 2610 NA NA #> 2611 NA NA #> 2612 + NA NA #> 2613 NA NA #> 2614 I NA NA #> 2615 NA NA #> 2616 NA NA #> 2617 NA NA #> 2618 NA NA #> 2619 NA NA #> 2620 U NA NA #> 2621 NA NA #> 2622 NA NA #> 2623 + NA NA #> 2624 NA NA #> 2625 I NA NA #> 2626 NA NA #> 2627 NA NA #> 2628 NA NA #> 2629 NA NA #> 2630 NA NA #> 2631 U NA NA #> 2632 NA NA #> 2633 NA NA #> 2634 + NA NA #> 2635 NA NA #> 2636 I NA NA #> 2637 NA NA #> 2638 NA NA #> 2639 NA NA #> 2640 NA NA #> 2641 NA NA #> 2642 U NA NA #> 2643 NA NA #> 2644 NA NA #> 2645 + NA NA #> 2646 NA NA #> 2647 I NA NA #> 2648 NA NA #> 2649 I NA NA #> 2650 NA NA #> 2651 NA NA #> 2652 NA NA #> 2653 U NA NA #> 2654 NA NA #> 2655 NA NA #> 2656 + NA NA #> 2657 NA NA #> 2658 I NA NA #> 2659 I NA NA #> 2660 A NA NA #> 2661 NA NA #> 2662 NA NA #> 2663 NA NA #> 2664 U NA NA #> 2665 NA NA #> 2666 NA NA #> 2667 + NA NA #> 2668 NA NA #> 2669 I NA NA #> 2670 NA NA #> 2671 NA NA #> 2672 NA NA #> 2673 NA NA #> 2674 NA NA #> 2675 U NA NA #> 2676 NA NA #> 2677 NA NA #> 2678 + NA NA #> 2679 NA NA #> 2680 NA NA #> 2681 NA NA #> 2682 NA NA #> 2683 NA NA #> 2684 NA NA #> 2685 U NA NA #> 2686 NA NA #> 2687 NA NA #> 2688 + NA NA #> 2689 NA NA #> 2690 I NA NA #> 2691 I NA NA #> 2692 I NA NA #> 2693 NA NA #> 2694 + NA NA #> 2695 NA NA #> 2696 NA NA #> 2697 NA NA #> 2698 NA NA #> 2699 + NA NA #> 2700 NA NA #> 2701 NA NA #> 2702 NA NA #> 2703 + NA NA #> 2704 NA NA #> 2705 NA NA #> 2706 NA NA #> 2707 + NA NA #> 2708 NA NA #> 2709 NA NA #> 2710 NA NA #> 2711 + NA NA #> 2712 NA NA #> 2713 NA NA #> 2714 NA NA #> 2715 + NA NA #> 2716 NA NA #> 2717 NA NA #> 2718 NA NA #> 2719 + NA NA #> 2720 NA NA #> 2721 NA NA #> 2722 NA NA #> 2723 + NA NA #> 2724 NA NA #> 2725 NA NA #> 2726 NA NA #> 2727 + NA NA #> 2728 NA NA #> 2729 + NA NA #> 2730 NA NA #> 2731 NA NA #> 2732 NA NA #> 2733 + NA NA #> 2734 NA NA #> 2735 NA NA #> 2736 NA NA #> 2737 + NA NA #> 2738 NA NA #> 2739 NA NA #> 2740 NA NA #> 2741 + NA NA #> 2742 NA NA #> 2743 NA NA #> 2744 NA NA #> 2745 + NA NA #> 2746 NA NA #> 2747 NA NA #> 2748 NA NA #> 2749 + NA NA #> 2750 NA NA #> 2751 NA NA #> 2752 NA NA #> 2753 + NA NA #> 2754 NA NA #> 2755 NA NA #> 2756 NA NA #> 2757 + NA NA #> 2758 NA NA #> 2759 + NA NA #> 2760 NA NA #> 2761 NA NA #> 2762 NA NA #> 2763 + NA NA #> 2764 NA NA #> 2765 NA NA #> 2766 NA NA #> 2767 + NA NA #> 2768 NA NA #> 2769 NA NA #> 2770 NA NA #> 2771 + NA NA #> 2772 NA NA #> 2773 NA NA #> 2774 NA NA #> 2775 + NA NA #> 2776 NA NA #> 2777 NA NA #> 2778 NA NA #> 2779 + NA NA #> 2780 NA NA #> 2781 NA NA #> 2782 NA NA #> 2783 NA NA #> 2784 NA NA #> 2785 NA NA #> 2786 NA NA #> 2787 NA NA #> 2788 NA NA #> 2789 NA NA #> 2790 NA NA #> 2791 NA NA #> 2792 NA NA #> 2793 NA NA #> 2794 NA NA #> 2795 NA NA #> 2796 NA NA #> 2797 NA NA #> 2798 NA NA #> 2799 NA NA #> 2800 NA NA #> 2801 NA NA #> 2802 NA NA #> 2803 NA NA #> 2804 NA NA #> 2805 NA NA #> 2806 NA NA #> 2807 NA NA #> 2808 I NA NA #> 2809 NA NA #> 2810 NA NA #> 2811 NA NA #> 2812 NA NA #> 2813 NA NA #> 2814 NA NA #> 2815 NA NA #> 2816 + NA NA #> 2817 NA NA #> 2818 I NA NA #> 2819 NA NA #> 2820 I NA NA #> 2821 A NA NA #> 2822 NA NA #> 2823 NA NA #> 2824 NA NA #> 2825 NA NA #> 2826 NA NA #> 2827 NA NA #> 2828 + NA NA #> 2829 NA NA #> 2830 I NA NA #> 2831 A NA NA #> 2832 NA NA #> 2833 A NA NA #> 2834 NA NA #> 2835 NA NA #> 2836 NA NA #> 2837 NA NA #> 2838 NA NA #> 2839 NA NA #> 2840 + NA NA #> 2841 NA NA #> 2842 I NA NA #> 2843 A NA NA #> 2844 I NA NA #> 2845 A NA NA #> 2846 NA NA #> 2847 NA NA #> 2848 NA NA #> 2849 NA NA #> 2850 NA NA #> 2851 NA NA #> 2852 + NA NA #> 2853 NA NA #> 2854 NA NA #> 2855 NA NA #> 2856 NA NA #> 2857 NA NA #> 2858 NA NA #> 2859 NA NA #> 2860 NA NA #> 2861 NA NA #> 2862 NA NA #> 2863 + NA NA #> 2864 NA NA #> 2865 I NA NA #> 2866 NA NA #> 2867 NA NA #> 2868 NA NA #> 2869 NA NA #> 2870 NA NA #> 2871 NA NA #> 2872 NA NA #> 2873 NA NA #> 2874 + NA NA #> 2875 NA NA #> 2876 I NA NA #> 2877 NA NA #> 2878 NA NA #> 2879 NA NA #> 2880 NA NA #> 2881 NA NA #> 2882 NA NA #> 2883 NA NA #> 2884 NA NA #> 2885 + NA NA #> 2886 NA NA #> 2887 I NA NA #> 2888 NA NA #> 2889 NA NA #> 2890 NA NA #> 2891 NA NA #> 2892 NA NA #> 2893 NA NA #> 2894 NA NA #> 2895 NA NA #> 2896 NA NA #> 2897 NA NA #> 2898 NA NA #> 2899 NA NA #> 2900 NA NA #> 2901 NA NA #> 2902 NA NA #> 2903 NA NA #> 2904 NA NA #> 2905 NA NA #> 2906 NA NA #> 2907 NA NA #> 2908 NA NA #> 2909 NA NA #> 2910 NA NA #> 2911 NA NA #> 2912 NA NA #> 2913 NA NA #> 2914 NA NA #> 2915 NA NA #> 2916 NA NA #> 2917 NA NA #> 2918 NA NA #> 2919 NA NA #> 2920 NA NA #> 2921 NA NA #> 2922 NA NA #> 2923 NA NA #> 2924 NA NA #> 2925 NA NA #> 2926 NA NA #> 2927 NA NA #> 2928 NA NA #> 2929 NA NA #> 2930 NA NA #> 2931 NA NA #> 2932 NA NA #> 2933 NA NA #> 2934 NA NA #> 2935 NA NA #> 2936 NA NA #> 2937 NA NA #> 2938 NA NA #> 2939 NA NA #> 2940 NA NA #> 2941 NA NA #> 2942 NA NA #> 2943 NA NA #> 2944 NA NA #> 2945 NA NA #> 2946 NA NA #> 2947 + NA NA #> 2948 NA NA #> 2949 NA NA #> 2950 NA NA #> 2951 + NA NA #> 2952 NA NA #> 2953 NA NA #> 2954 NA NA #> 2955 + NA NA #> 2956 NA NA #> 2957 NA NA #> 2958 NA NA #> 2959 + NA NA #> 2960 NA NA #> 2961 NA NA #> 2962 NA NA #> 2963 + NA NA #> 2964 NA NA #> 2965 NA NA #> 2966 NA NA #> 2967 + NA NA #> 2968 NA NA #> 2969 NA NA #> 2970 NA NA #> 2971 + NA NA #> 2972 NA NA #> 2973 NA NA #> 2974 NA NA #> 2975 + NA NA #> 2976 NA NA #> 2977 NA NA #> 2978 NA NA #> 2979 NA NA #> 2980 NA NA #> 2981 U NA NA #> 2982 + NA NA #> 2983 NA NA #> 2984 + NA NA #> 2985 NA NA #> 2986 U NA NA #> 2987 NA NA #> 2988 NA NA #> 2989 NA NA #> 2990 NA NA #> 2991 NA NA #> 2992 I NA NA #> 2993 + NA NA #> 2994 NA NA #> 2995 + NA NA #> 2996 NA NA #> 2997 NA NA #> 2998 A NA NA #> 2999 NA NA #> 3000 NA NA #> 3001 NA NA #> 3002 NA NA #> 3003 NA NA #> 3004 + NA NA #> 3005 NA NA #> 3006 + NA NA #> 3007 NA NA #> 3008 I NA NA #> 3009 NA NA #> 3010 + NA NA #> 3011 NA NA #> 3012 NA NA #> 3013 NA NA #> 3014 NA NA #> 3015 NA NA #> 3016 NA NA #> 3017 + NA NA #> 3018 NA NA #> 3019 NA NA #> 3020 NA NA #> 3021 NA NA #> 3022 NA NA #> 3023 NA NA #> 3024 NA NA #> 3025 + NA NA #> 3026 NA NA #> 3027 I NA NA #> 3028 NA NA #> 3029 NA NA #> 3030 NA NA #> 3031 NA NA #> 3032 NA NA #> 3033 NA NA #> 3034 NA NA #> 3035 NA NA #> 3036 + NA NA #> 3037 NA NA #> 3038 I NA NA #> 3039 NA NA #> 3040 NA NA #> 3041 NA NA #> 3042 NA NA #> 3043 NA NA #> 3044 A NA NA #> 3045 NA NA #> 3046 I NA NA #> 3047 NA NA #> 3048 NA NA #> 3049 + NA NA #> 3050 NA NA #> 3051 I NA NA #> 3052 NA NA #> 3053 NA NA #> 3054 NA NA #> 3055 NA NA #> 3056 NA NA #> 3057 I NA NA #> 3058 NA NA #> 3059 NA NA #> 3060 + NA NA #> 3061 NA NA #> 3062 I NA NA #> 3063 NA NA #> 3064 NA NA #> 3065 NA NA #> 3066 NA NA #> 3067 NA NA #> 3068 U NA NA #> 3069 NA NA #> 3070 NA NA #> 3071 + NA NA #> 3072 NA NA #> 3073 I NA NA #> 3074 NA NA #> 3075 NA NA #> 3076 NA NA #> 3077 NA NA #> 3078 NA NA #> 3079 NA NA #> 3080 NA NA #> 3081 NA NA #> 3082 + NA NA #> 3083 NA NA #> 3084 I NA NA #> 3085 NA NA #> 3086 NA NA #> 3087 NA NA #> 3088 NA NA #> 3089 NA NA #> 3090 NA NA #> 3091 NA NA #> 3092 + NA NA #> 3093 NA NA #> 3094 I NA NA #> 3095 NA NA #> 3096 NA NA #> 3097 NA NA #> 3098 NA NA #> 3099 NA NA #> 3100 I NA NA #> 3101 NA NA #> 3102 NA NA #> 3103 + NA NA #> 3104 NA NA #> 3105 NA NA #> 3106 NA NA #> 3107 NA NA #> 3108 NA NA #> 3109 NA NA #> 3110 NA NA #> 3111 NA NA #> 3112 NA NA #> 3113 NA NA #> 3114 NA NA #> 3115 NA NA #> 3116 NA NA #> 3117 NA NA #> 3118 + NA NA #> 3119 NA NA #> 3120 I NA NA #> 3121 NA NA #> 3122 NA NA #> 3123 NA NA #> 3124 NA NA #> 3125 NA NA #> 3126 NA NA #> 3127 NA NA #> 3128 NA NA #> 3129 NA NA #> 3130 NA NA #> 3131 NA NA #> 3132 NA NA #> 3133 NA NA #> 3134 NA NA #> 3135 NA NA #> 3136 NA NA #> 3137 NA NA #> 3138 NA NA #> 3139 NA NA #> 3140 NA NA #> 3141 + NA NA #> 3142 NA NA #> 3143 I NA NA #> 3144 NA NA #> 3145 NA NA #> 3146 NA NA #> 3147 NA NA #> 3148 NA NA #> 3149 NA NA #> 3150 NA NA #> 3151 NA NA #> 3152 + NA NA #> 3153 NA NA #> 3154 I NA NA #> 3155 NA NA #> 3156 NA NA #> 3157 NA NA #> 3158 NA NA #> 3159 NA NA #> 3160 I NA NA #> 3161 NA NA #> 3162 NA NA #> 3163 + NA NA #> 3164 NA NA #> 3165 I NA NA #> 3166 A NA NA #> 3167 NA NA #> 3168 NA NA #> 3169 NA NA #> 3170 NA NA #> 3171 U NA NA #> 3172 NA NA #> 3173 NA NA #> 3174 + NA NA #> 3175 NA NA #> 3176 I NA NA #> 3177 NA NA #> 3178 NA NA #> 3179 NA NA #> 3180 NA NA #> 3181 NA NA #> 3182 I NA NA #> 3183 NA NA #> 3184 NA NA #> 3185 + NA NA #> 3186 NA NA #> 3187 NA NA #> 3188 A NA NA #> 3189 NA NA #> 3190 NA NA #> 3191 NA NA #> 3192 NA NA #> 3193 U NA NA #> 3194 NA NA #> 3195 NA NA #> 3196 + NA NA #> 3197 NA NA #> 3198 I NA NA #> 3199 NA NA #> 3200 NA NA #> 3201 NA NA #> 3202 NA NA #> 3203 NA NA #> 3204 U NA NA #> 3205 NA NA #> 3206 NA NA #> 3207 + NA NA #> 3208 NA NA #> 3209 I NA NA #> 3210 NA NA #> 3211 NA NA #> 3212 NA NA #> 3213 NA NA #> 3214 NA NA #> 3215 U NA NA #> 3216 NA NA #> 3217 NA NA #> 3218 + NA NA #> 3219 NA NA #> 3220 U NA NA #> 3221 NA NA #> 3222 NA NA #> 3223 NA NA #> 3224 NA NA #> 3225 NA NA #> 3226 NA NA #> 3227 NA NA #> 3228 NA NA #> 3229 + NA NA #> 3230 NA NA #> 3231 I NA NA #> 3232 NA NA #> 3233 NA NA #> 3234 NA NA #> 3235 NA NA #> 3236 NA NA #> 3237 NA NA #> 3238 NA NA #> 3239 NA NA #> 3240 + NA NA #> 3241 NA NA #> 3242 I NA NA #> 3243 NA NA #> 3244 NA NA #> 3245 NA NA #> 3246 NA NA #> 3247 NA NA #> 3248 NA NA #> 3249 NA NA #> 3250 NA NA #> 3251 + NA NA #> 3252 NA NA #> 3253 I NA NA #> 3254 NA NA #> 3255 NA NA #> 3256 NA NA #> 3257 NA NA #> 3258 NA NA #> 3259 NA NA #> 3260 NA NA #> 3261 NA NA #> 3262 + NA NA #> 3263 NA NA #> 3264 I NA NA #> 3265 NA NA #> 3266 NA NA #> 3267 NA NA #> 3268 NA NA #> 3269 I NA NA #> 3270 NA NA #> 3271 NA NA #> 3272 + NA NA #> 3273 NA NA #> 3274 I NA NA #> 3275 NA NA #> 3276 NA NA #> 3277 NA NA #> 3278 NA NA #> 3279 NA NA #> 3280 U NA NA #> 3281 NA NA #> 3282 NA NA #> 3283 + NA NA #> 3284 NA NA #> 3285 NA NA #> 3286 NA NA #> 3287 U NA NA #> 3288 NA NA #> 3289 NA NA #> 3290 NA NA #> 3291 U NA NA #> 3292 NA NA #> 3293 NA NA #> 3294 + NA NA #> 3295 NA NA #> 3296 NA NA #> 3297 NA NA #> 3298 NA NA #> 3299 NA NA #> 3300 NA NA #> 3301 NA NA #> 3302 I NA NA #> 3303 NA NA #> 3304 NA NA #> 3305 + NA NA #> 3306 NA NA #> 3307 NA NA #> 3308 NA NA #> 3309 NA NA #> 3310 NA NA #> 3311 NA NA #> 3312 NA NA #> 3313 I NA NA #> 3314 NA NA #> 3315 NA NA #> 3316 + NA NA #> 3317 NA NA #> 3318 I NA NA #> 3319 NA NA #> 3320 NA NA #> 3321 NA NA #> 3322 NA NA #> 3323 NA NA #> 3324 U NA NA #> 3325 NA NA #> 3326 NA NA #> 3327 + NA NA #> 3328 NA NA #> 3329 NA NA #> 3330 NA NA #> 3331 NA NA #> 3332 NA NA #> 3333 NA NA #> 3334 NA NA #> 3335 NA NA #> 3336 NA NA #> 3337 NA NA #> 3338 + NA NA #> 3339 NA NA #> 3340 I NA NA #> 3341 NA NA #> 3342 I NA NA #> 3343 NA NA #> 3344 NA NA #> 3345 NA NA #> 3346 U NA NA #> 3347 NA NA #> 3348 NA NA #> 3349 + NA NA #> 3350 NA NA #> 3351 I NA NA #> 3352 NA NA #> 3353 NA NA #> 3354 NA NA #> 3355 NA NA #> 3356 NA NA #> 3357 U NA NA #> 3358 NA NA #> 3359 NA NA #> 3360 + NA NA #> 3361 NA NA #> 3362 NA NA #> 3363 NA NA #> 3364 NA NA #> 3365 NA NA #> 3366 NA NA #> 3367 NA NA #> 3368 NA NA #> 3369 NA NA #> 3370 NA NA #> 3371 NA NA #> 3372 NA NA #> 3373 NA NA #> 3374 U NA NA #> 3375 + NA NA #> 3376 NA NA #> 3377 + NA NA #> 3378 NA NA #> 3379 I NA NA #> 3380 NA NA #> 3381 NA NA #> 3382 NA NA #> 3383 NA NA #> 3384 + NA NA #> 3385 NA NA #> 3386 NA NA #> 3387 NA NA #> 3388 NA NA #> 3389 I NA NA #> 3390 + NA NA #> 3391 NA NA #> 3392 + NA NA #> 3393 NA NA #> 3394 I NA NA #> 3395 NA NA #> 3396 NA NA #> 3397 NA NA #> 3398 NA NA #> 3399 NA NA #> 3400 NA NA #> 3401 + NA NA #> 3402 NA NA #> 3403 + NA NA #> 3404 NA NA #> 3405 I NA NA #> 3406 NA NA #> 3407 NA NA #> 3408 NA NA #> 3409 NA NA #> 3410 + NA NA #> 3411 NA NA #> 3412 NA NA #> 3413 NA NA #> 3414 NA NA #> 3415 NA NA #> 3416 NA NA #> 3417 NA NA #> 3418 + NA NA #> 3419 NA NA #> 3420 I NA NA #> 3421 NA NA #> 3422 NA NA #> 3423 NA NA #> 3424 NA NA #> 3425 NA NA #> 3426 A NA NA #> 3427 NA NA #> 3428 NA NA #> 3429 NA NA #> 3430 NA NA #> 3431 NA NA #> 3432 NA NA #> 3433 + NA NA #> 3434 NA NA #> 3435 I NA NA #> 3436 NA NA #> 3437 NA NA #> 3438 NA NA #> 3439 NA NA #> 3440 NA NA #> 3441 NA NA #> 3442 NA NA #> 3443 U NA NA #> 3444 NA NA #> 3445 NA NA #> 3446 + NA NA #> 3447 NA NA #> 3448 I NA NA #> 3449 NA NA #> 3450 NA NA #> 3451 NA NA #> 3452 NA NA #> 3453 + NA NA #> 3454 U NA NA #> 3455 NA NA #> 3456 NA NA #> 3457 + NA NA #> 3458 NA NA #> 3459 I NA NA #> 3460 NA NA #> 3461 NA NA #> 3462 NA NA #> 3463 NA NA #> 3464 NA NA #> 3465 NA NA #> 3466 NA NA #> 3467 NA NA #> 3468 NA NA #> 3469 U NA NA #> 3470 NA NA #> 3471 NA NA #> 3472 + NA NA #> 3473 NA NA #> 3474 I NA NA #> 3475 NA NA #> 3476 NA NA #> 3477 NA NA #> 3478 NA NA #> 3479 NA NA #> 3480 U NA NA #> 3481 NA NA #> 3482 NA NA #> 3483 + NA NA #> 3484 NA NA #> 3485 I NA NA #> 3486 NA NA #> 3487 NA NA #> 3488 NA NA #> 3489 NA NA #> 3490 NA NA #> 3491 NA NA #> 3492 NA NA #> 3493 NA NA #> 3494 + NA NA #> 3495 NA NA #> 3496 I NA NA #> 3497 NA NA #> 3498 NA NA #> 3499 NA NA #> 3500 NA NA #> 3501 NA NA #> 3502 U NA NA #> 3503 NA NA #> 3504 NA NA #> 3505 + NA NA #> 3506 NA NA #> 3507 NA NA #> 3508 NA NA #> 3509 NA NA #> 3510 NA NA #> 3511 NA NA #> 3512 NA NA #> 3513 NA NA #> 3514 NA NA #> 3515 NA NA #> 3516 NA NA #> 3517 NA NA #> 3518 NA NA #> 3519 NA NA #> 3520 + NA NA #> 3521 NA NA #> 3522 I NA NA #> 3523 NA NA #> 3524 NA NA #> 3525 NA NA #> 3526 NA NA #> 3527 NA NA #> 3528 NA NA #> 3529 NA NA #> 3530 NA NA #> 3531 NA NA #> 3532 NA NA #> 3533 NA NA #> 3534 NA NA #> 3535 NA NA #> 3536 NA NA #> 3537 NA NA #> 3538 NA NA #> 3539 + NA NA #> 3540 NA NA #> 3541 I NA NA #> 3542 A NA NA #> 3543 NA NA #> 3544 NA NA #> 3545 NA NA #> 3546 NA NA #> 3547 NA NA #> 3548 NA NA #> 3549 NA NA #> 3550 + NA NA #> 3551 NA NA #> 3552 I NA NA #> 3553 NA NA #> 3554 NA NA #> 3555 NA NA #> 3556 NA NA #> 3557 NA NA #> 3558 U NA NA #> 3559 NA NA #> 3560 NA NA #> 3561 + NA NA #> 3562 NA NA #> 3563 I NA NA #> 3564 NA NA #> 3565 NA NA #> 3566 NA NA #> 3567 NA NA #> 3568 NA NA #> 3569 U NA NA #> 3570 NA NA #> 3571 NA NA #> 3572 + NA NA #> 3573 NA NA #> 3574 I NA NA #> 3575 NA NA #> 3576 NA NA #> 3577 NA NA #> 3578 NA NA #> 3579 NA NA #> 3580 U NA NA #> 3581 NA NA #> 3582 NA NA #> 3583 + NA NA #> 3584 NA NA #> 3585 I NA NA #> 3586 NA NA #> 3587 NA NA #> 3588 NA NA #> 3589 NA NA #> 3590 NA NA #> 3591 I NA NA #> 3592 NA NA #> 3593 NA NA #> 3594 + NA NA #> 3595 NA NA #> 3596 I NA NA #> 3597 NA NA #> 3598 NA NA #> 3599 NA NA #> 3600 NA NA #> 3601 NA NA #> 3602 U NA NA #> 3603 NA NA #> 3604 NA NA #> 3605 + NA NA #> 3606 NA NA #> 3607 I NA NA #> 3608 NA NA #> 3609 NA NA #> 3610 NA NA #> 3611 NA NA #> 3612 NA NA #> 3613 NA NA #> 3614 NA NA #> 3615 NA NA #> 3616 + NA NA #> 3617 NA NA #> 3618 NA NA #> 3619 NA NA #> 3620 NA NA #> 3621 NA NA #> 3622 NA NA #> 3623 NA NA #> 3624 I NA NA #> 3625 NA NA #> 3626 NA NA #> 3627 + NA NA #> 3628 NA NA #> 3629 I NA NA #> 3630 NA NA #> 3631 NA NA #> 3632 NA NA #> 3633 NA NA #> 3634 NA NA #> 3635 U NA NA #> 3636 NA NA #> 3637 NA NA #> 3638 + NA NA #> 3639 NA NA #> 3640 NA NA #> 3641 NA NA #> 3642 A NA NA #> 3643 NA NA #> 3644 NA NA #> 3645 NA NA #> 3646 I NA NA #> 3647 NA NA #> 3648 NA NA #> 3649 + NA NA #> 3650 NA NA #> 3651 I NA NA #> 3652 NA NA #> 3653 NA NA #> 3654 NA NA #> 3655 NA NA #> 3656 NA NA #> 3657 U NA NA #> 3658 NA NA #> 3659 NA NA #> 3660 + NA NA #> 3661 NA NA #> 3662 NA NA #> 3663 NA NA #> 3664 NA NA #> 3665 NA NA #> 3666 NA NA #> 3667 NA NA #> 3668 U NA NA #> 3669 NA NA #> 3670 NA NA #> 3671 + NA NA #> 3672 NA NA #> 3673 I NA NA #> 3674 NA NA #> 3675 NA NA #> 3676 NA NA #> 3677 NA NA #> 3678 NA NA #> 3679 U NA NA #> 3680 NA NA #> 3681 NA NA #> 3682 + NA NA #> 3683 NA NA #> 3684 NA NA #> 3685 NA NA #> 3686 NA NA #> 3687 NA NA #> 3688 NA NA #> 3689 NA NA #> 3690 U NA NA #> 3691 NA NA #> 3692 NA NA #> 3693 + NA NA #> 3694 NA NA #> 3695 I NA NA #> 3696 NA NA #> 3697 NA NA #> 3698 NA NA #> 3699 NA NA #> 3700 NA NA #> 3701 I NA NA #> 3702 NA NA #> 3703 NA NA #> 3704 + NA NA #> 3705 NA NA #> 3706 NA NA #> 3707 NA NA #> 3708 NA NA #> 3709 NA NA #> 3710 NA NA #> 3711 NA NA #> 3712 NA NA #> 3713 NA NA #> 3714 NA NA #> 3715 + NA NA #> 3716 NA NA #> 3717 I NA NA #> 3718 NA NA #> 3719 NA NA #> 3720 NA NA #> 3721 NA NA #> 3722 NA NA #> 3723 I NA NA #> 3724 NA NA #> 3725 NA NA #> 3726 + NA NA #> 3727 NA NA #> 3728 NA NA #> 3729 NA NA #> 3730 NA NA #> 3731 NA NA #> 3732 NA NA #> 3733 NA NA #> 3734 NA NA #> 3735 NA NA #> 3736 NA NA #> 3737 + NA NA #> 3738 NA NA #> 3739 NA NA #> 3740 NA NA #> 3741 NA NA #> 3742 NA NA #> 3743 NA NA #> 3744 NA NA #> 3745 NA NA #> 3746 NA NA #> 3747 NA NA #> 3748 + NA NA #> 3749 NA NA #> 3750 I NA NA #> 3751 NA NA #> 3752 NA NA #> 3753 NA NA #> 3754 NA NA #> 3755 NA NA #> 3756 U NA NA #> 3757 NA NA #> 3758 NA NA #> 3759 + NA NA #> 3760 NA NA #> 3761 I NA NA #> 3762 NA NA #> 3763 NA NA #> 3764 + NA NA #> 3765 I NA NA #> 3766 NA NA #> 3767 NA NA #> 3768 + NA NA #> 3769 NA NA #> 3770 NA NA #> 3771 NA NA #> 3772 NA NA #> 3773 + NA NA #> 3774 NA NA #> 3775 NA NA #> 3776 NA NA #> 3777 + NA NA #> 3778 NA NA #> 3779 NA NA #> 3780 NA NA #> 3781 NA NA #> 3782 + NA NA #> 3783 I NA NA #> 3784 NA NA #> 3785 NA NA #> 3786 + NA NA #> 3787 NA NA #> 3788 NA NA #> 3789 NA NA #> 3790 NA NA #> 3791 NA NA #> 3792 + NA NA #> 3793 I NA NA #> 3794 NA NA #> 3795 NA NA #> 3796 + NA NA #> 3797 NA NA #> 3798 NA NA #> 3799 NA NA #> 3800 A NA NA #> 3801 NA NA #> 3802 + NA NA #> 3803 NA NA #> 3804 NA NA #> 3805 NA NA #> 3806 + NA NA #> 3807 NA NA #> 3808 A NA NA #> 3809 NA NA #> 3810 A NA NA #> 3811 NA NA #> 3812 NA NA #> 3813 NA NA #> 3814 + NA NA #> 3815 NA NA #> 3816 NA NA #> 3817 NA NA #> 3818 NA NA #> 3819 NA NA #> 3820 + NA NA #> 3821 I NA NA #> 3822 NA NA #> 3823 + NA NA #> 3824 NA NA #> 3825 NA NA #> 3826 NA NA #> 3827 NA NA #> 3828 NA NA #> 3829 + NA NA #> 3830 NA NA #> 3831 NA NA #> 3832 NA NA #> 3833 + NA NA #> 3834 NA NA #> 3835 NA NA #> 3836 NA NA #> 3837 NA NA #> 3838 NA NA #> 3839 + NA NA #> 3840 NA NA #> 3841 NA NA #> 3842 NA NA #> 3843 + NA NA #> 3844 NA NA #> 3845 A NA NA #> 3846 NA NA #> 3847 NA NA #> 3848 NA NA #> 3849 NA NA #> 3850 NA NA #> 3851 + NA NA #> 3852 NA NA #> 3853 A NA NA #> 3854 NA NA #> 3855 A NA NA #> 3856 NA NA #> 3857 NA NA #> 3858 + NA NA #> 3859 NA NA #> 3860 NA NA #> 3861 NA NA #> 3862 NA NA #> 3863 + NA NA #> 3864 NA NA #> 3865 NA NA #> 3866 NA NA #> 3867 + NA NA #> 3868 NA NA #> 3869 NA NA #> 3870 NA NA #> 3871 NA NA #> 3872 + NA NA #> 3873 I NA NA #> 3874 NA NA #> 3875 + NA NA #> 3876 NA NA #> 3877 NA NA #> 3878 NA NA #> 3879 NA NA #> 3880 + NA NA #> 3881 NA NA #> 3882 + NA NA #> 3883 NA NA #> 3884 A NA NA #> 3885 NA NA #> 3886 NA NA #> 3887 + NA NA #> 3888 NA NA #> 3889 NA NA #> 3890 NA NA #> 3891 + NA NA #> 3892 NA NA #> 3893 NA NA #> 3894 NA NA #> 3895 NA NA #> 3896 NA NA #> 3897 + NA NA #> 3898 I NA NA #> 3899 NA NA #> 3900 NA NA #> 3901 + NA NA #> 3902 NA NA #> 3903 NA NA #> 3904 NA NA #> 3905 NA NA #> 3906 NA NA #> 3907 NA NA #> 3908 NA NA #> 3909 + NA NA #> 3910 NA NA #> 3911 NA NA #> 3912 NA NA #> 3913 NA NA #> 3914 NA NA #> 3915 + NA NA #> 3916 NA NA #> 3917 NA NA #> 3918 NA NA #> 3919 + NA NA #> 3920 NA NA #> 3921 NA NA #> 3922 NA NA #> 3923 NA NA #> 3924 + NA NA #> 3925 NA NA #> 3926 NA NA #> 3927 NA NA #> 3928 + NA NA #> 3929 NA NA #> 3930 NA NA #> 3931 NA NA #> 3932 NA NA #> 3933 NA NA #> 3934 NA NA #> 3935 NA NA #> 3936 + NA NA #> 3937 NA NA #> 3938 NA NA #> 3939 NA NA #> 3940 A NA NA #> 3941 + NA NA #> 3942 NA NA #> 3943 NA NA #> 3944 NA NA #> 3945 + NA NA #> 3946 NA NA #> 3947 NA NA #> 3948 NA NA #> 3949 NA NA #> 3950 NA NA #> 3951 + NA NA #> 3952 I NA NA #> 3953 NA NA #> 3954 NA NA #> 3955 + NA NA #> 3956 NA NA #> 3957 A NA NA #> 3958 I NA NA #> 3959 NA NA #> 3960 + NA NA #> 3961 U NA NA #> 3962 NA NA #> 3963 + NA NA #> 3964 NA NA #> 3965 NA NA #> 3966 NA NA #> 3967 NA NA #> 3968 + NA NA #> 3969 I NA NA #> 3970 NA NA #> 3971 NA NA #> 3972 + NA NA #> 3973 NA NA #> 3974 NA NA #> 3975 NA NA #> 3976 A NA NA #> 3977 NA NA #> 3978 + NA NA #> 3979 I NA NA #> 3980 NA NA #> 3981 NA NA #> 3982 + NA NA #> 3983 NA NA #> 3984 NA NA #> 3985 NA NA #> 3986 NA NA #> 3987 + NA NA #> 3988 I NA NA #> 3989 NA NA #> 3990 NA NA #> 3991 + NA NA #> 3992 NA NA #> 3993 NA NA #> 3994 NA NA #> 3995 NA NA #> 3996 I NA NA #> 3997 NA NA #> 3998 + NA NA #> 3999 NA NA #> 4000 NA NA #> 4001 NA NA #> 4002 NA NA #> 4003 + NA NA #> 4004 I NA NA #> 4005 NA NA #> 4006 NA NA #> 4007 + NA NA #> 4008 NA NA #> 4009 NA NA #> 4010 NA NA #> 4011 NA NA #> 4012 + NA NA #> 4013 NA NA #> 4014 NA NA #> 4015 NA NA #> 4016 + NA NA #> 4017 NA NA #> 4018 NA NA #> 4019 I NA NA #> 4020 NA NA #> 4021 NA NA #> 4022 + NA NA #> 4023 NA NA #> 4024 NA NA #> 4025 NA NA #> 4026 + NA NA #> 4027 NA NA #> 4028 NA NA #> 4029 NA NA #> 4030 A NA NA #> 4031 + NA NA #> 4032 NA NA #> 4033 NA NA #> 4034 NA NA #> 4035 + NA NA #> 4036 NA NA #> 4037 NA NA #> 4038 NA NA #> 4039 NA NA #> 4040 + NA NA #> 4041 I NA NA #> 4042 NA NA #> 4043 NA NA #> 4044 + NA NA #> 4045 NA NA #> 4046 NA NA #> 4047 NA NA #> 4048 NA NA #> 4049 NA NA #> 4050 + NA NA #> 4051 U NA NA #> 4052 NA NA #> 4053 NA NA #> 4054 + NA NA #> 4055 NA NA #> 4056 NA NA #> 4057 NA NA #> 4058 NA NA #> 4059 NA NA #> 4060 + NA NA #> 4061 I NA NA #> 4062 NA NA #> 4063 + NA NA #> 4064 NA NA #> 4065 A NA NA #> 4066 A NA NA #> 4067 NA NA #> 4068 + NA NA #> 4069 U NA NA #> 4070 NA NA #> 4071 NA NA #> 4072 + NA NA #> 4073 NA NA #> 4074 NA NA #> 4075 NA NA #> 4076 NA NA #> 4077 NA NA #> 4078 + NA NA #> 4079 I NA NA #> 4080 NA NA #> 4081 + NA NA #> 4082 NA NA #> 4083 NA NA #> 4084 NA NA #> 4085 NA NA #> 4086 + NA NA #> 4087 NA NA #> 4088 + NA NA #> 4089 NA NA #> 4090 NA NA #> 4091 NA NA #> 4092 + NA NA #> 4093 NA NA #> 4094 NA NA #> 4095 NA NA #> 4096 + NA NA #> 4097 NA NA #> 4098 NA NA #> 4099 NA NA #> 4100 NA NA #> 4101 NA NA #> 4102 + NA NA #> 4103 NA NA #> 4104 NA NA #> 4105 NA NA #> 4106 + NA NA #> 4107 NA NA #> 4108 NA NA #> 4109 NA NA #> 4110 NA NA #> 4111 NA NA #> 4112 NA NA #> 4113 NA NA #> 4114 NA NA #> 4115 + NA NA #> 4116 NA NA #> 4117 NA NA #> 4118 NA NA #> 4119 NA NA #> 4120 NA NA #> 4121 + NA NA #> 4122 U NA NA #> 4123 NA NA #> 4124 NA NA #> 4125 + NA NA #> 4126 NA NA #> 4127 NA NA #> 4128 NA NA #> 4129 NA NA #> 4130 + NA NA #> 4131 U NA NA #> 4132 NA NA #> 4133 + NA NA #> 4134 NA NA #> 4135 NA NA #> 4136 NA NA #> 4137 U NA NA #> 4138 NA NA #> 4139 + NA NA #> 4140 NA NA #> 4141 NA NA #> 4142 NA NA #> 4143 NA NA #> 4144 + NA NA #> 4145 I NA NA #> 4146 NA NA #> 4147 NA NA #> 4148 + NA NA #> 4149 NA NA #> 4150 NA NA #> 4151 NA NA #> 4152 A NA NA #> 4153 NA NA #> 4154 NA NA #> 4155 I NA NA #> 4156 NA NA #> 4157 NA NA #> 4158 + NA NA #> 4159 NA NA #> 4160 NA NA #> 4161 NA NA #> 4162 NA NA #> 4163 NA NA #> 4164 NA NA #> 4165 I NA NA #> 4166 NA NA #> 4167 NA NA #> 4168 + NA NA #> 4169 NA NA #> 4170 NA NA #> 4171 NA NA #> 4172 NA NA #> 4173 NA NA #> 4174 NA NA #> 4175 I NA NA #> 4176 NA NA #> 4177 NA NA #> 4178 + NA NA #> 4179 NA NA #> 4180 NA NA #> 4181 NA NA #> 4182 NA NA #> 4183 NA NA #> 4184 NA NA #> 4185 I NA NA #> 4186 NA NA #> 4187 NA NA #> 4188 + NA NA #> 4189 NA NA #> 4190 NA NA #> 4191 NA NA #> 4192 NA NA #> 4193 NA NA #> 4194 NA NA #> 4195 U NA NA #> 4196 NA NA #> 4197 NA NA #> 4198 + NA NA #> 4199 NA NA #> 4200 A NA NA #> 4201 NA NA #> 4202 NA NA #> 4203 NA NA #> 4204 NA NA #> 4205 U NA NA #> 4206 NA NA #> 4207 NA NA #> 4208 + NA NA #> 4209 NA NA #> 4210 NA NA #> 4211 NA NA #> 4212 NA NA #> 4213 NA NA #> 4214 NA NA #> 4215 I NA NA #> 4216 NA NA #> 4217 NA NA #> 4218 + NA NA #> 4219 NA NA #> 4220 NA NA #> 4221 I NA NA #> 4222 NA NA #> 4223 NA NA #> 4224 NA NA #> 4225 I NA NA #> 4226 NA NA #> 4227 NA NA #> 4228 + NA NA #> 4229 NA NA #> 4230 NA NA #> 4231 NA NA #> 4232 NA NA #> 4233 NA NA #> 4234 NA NA #> 4235 I NA NA #> 4236 NA NA #> 4237 NA NA #> 4238 + NA NA #> 4239 NA NA #> 4240 A NA NA #> 4241 NA NA #> 4242 NA NA #> 4243 NA NA #> 4244 NA NA #> 4245 A NA NA #> 4246 NA NA #> 4247 NA NA #> 4248 U NA NA #> 4249 NA NA #> 4250 NA NA #> 4251 + NA NA #> 4252 NA NA #> 4253 NA NA #> 4254 NA NA #> 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NA #> 6187 NA NA #> 6188 NA NA #> 6189 NA NA #> 6190 NA NA #> 6191 NA NA #> 6192 NA NA #> 6193 NA NA #> 6194 NA NA #> 6195 + NA NA #> 6196 NA NA #> 6197 I NA NA #> 6198 NA NA #> 6199 NA NA #> 6200 NA NA #> 6201 NA NA #> 6202 NA NA #> 6203 NA NA #> 6204 NA NA #> 6205 NA NA #> 6206 + NA NA #> 6207 NA NA #> 6208 I NA NA #> 6209 NA NA #> 6210 NA NA #> 6211 NA NA #> 6212 NA NA #> 6213 NA NA #> 6214 NA NA #> 6215 NA NA #> 6216 NA NA #> 6217 + NA NA #> 6218 NA NA #> 6219 I NA NA #> 6220 NA NA #> 6221 NA NA #> 6222 NA NA #> 6223 NA NA #> 6224 NA NA #> 6225 NA NA #> 6226 NA NA #> 6227 NA NA #> 6228 NA NA #> 6229 NA NA #> 6230 NA NA #> 6231 NA NA #> 6232 NA NA #> 6233 NA NA #> 6234 NA NA #> 6235 NA NA #> 6236 NA NA #> 6237 NA NA #> 6238 A NA NA #> 6239 NA NA #> 6240 + NA NA #> 6241 NA NA #> 6242 NA NA #> 6243 NA NA #> 6244 + NA NA #> 6245 NA NA #> 6246 A NA NA #> 6247 NA NA #> 6248 NA NA #> 6249 NA NA #> 6250 + NA NA #> 6251 NA NA #> 6252 NA NA #> 6253 NA NA #> 6254 + NA NA #> 6255 NA NA #> 6256 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7911 I NA NA #> 7912 NA NA #> 7913 NA NA #> 7914 + NA NA #> 7915 NA NA #> 7916 NA NA #> 7917 NA NA #> 7918 NA NA #> 7919 NA NA #> 7920 NA NA #> 7921 I NA NA #> 7922 NA NA #> 7923 NA NA #> 7924 + NA NA #> 7925 NA NA #> 7926 NA NA #> 7927 NA NA #> 7928 NA NA #> 7929 NA NA #> 7930 NA NA #> 7931 I NA NA #> 7932 NA NA #> 7933 NA NA #> 7934 + NA NA #> 7935 NA NA #> 7936 NA NA #> 7937 NA NA #> 7938 NA NA #> 7939 NA NA #> 7940 NA NA #> 7941 NA NA #> 7942 NA NA #> 7943 NA NA #> 7944 + NA NA #> 7945 NA NA #> 7946 NA NA #> 7947 NA NA #> 7948 NA NA #> 7949 NA NA #> 7950 NA NA #> 7951 NA NA #> 7952 NA NA #> 7953 NA NA #> 7954 + NA NA #> 7955 NA NA #> 7956 NA NA #> 7957 NA NA #> 7958 NA NA #> 7959 NA NA #> 7960 NA NA #> 7961 I NA NA #> 7962 NA NA #> 7963 NA NA #> 7964 + NA NA #> 7965 NA NA #> 7966 NA NA #> 7967 NA NA #> 7968 NA NA #> 7969 NA NA #> 7970 NA NA #> 7971 I NA NA #> 7972 NA NA #> 7973 NA NA #> 7974 + NA NA #> 7975 NA NA #> 7976 NA NA #> 7977 I NA NA #> 7978 NA NA #> 7979 NA NA #> 7980 NA NA #> 7981 NA NA #> 7982 NA NA #> 7983 NA NA #> 7984 + NA NA #> 7985 NA NA #> 7986 NA NA #> 7987 I NA NA #> 7988 NA NA #> 7989 NA NA #> 7990 NA NA #> 7991 I NA NA #> 7992 NA NA #> 7993 NA NA #> 7994 + NA NA #> 7995 NA NA #> 7996 NA NA #> 7997 I NA NA #> 7998 NA NA #> 7999 NA NA #> 8000 NA NA #> 8001 I NA NA #> 8002 NA NA #> 8003 NA NA #> 8004 + NA NA #> 8005 NA NA #> 8006 NA NA #> 8007 NA NA #> 8008 NA NA #> 8009 NA NA #> 8010 NA NA #> 8011 I NA NA #> 8012 NA NA #> 8013 NA NA #> 8014 + NA NA #> 8015 NA NA #> 8016 NA NA #> 8017 NA NA #> 8018 NA NA #> 8019 NA NA #> 8020 NA NA #> 8021 U NA NA #> 8022 NA NA #> 8023 NA NA #> 8024 + NA NA #> 8025 NA NA #> 8026 NA NA #> 8027 NA NA #> 8028 NA NA #> 8029 NA NA #> 8030 NA NA #> 8031 I NA NA #> 8032 NA NA #> 8033 NA NA #> 8034 + NA NA #> 8035 NA NA #> 8036 NA NA #> 8037 NA NA #> 8038 NA NA #> 8039 NA NA #> 8040 NA NA #> 8041 NA NA #> 8042 NA NA #> 8043 NA NA #> 8044 + NA NA #> 8045 NA NA #> 8046 NA NA #> 8047 NA NA #> 8048 NA NA #> 8049 NA NA #> 8050 NA NA #> 8051 NA NA #> 8052 NA NA #> 8053 NA NA #> 8054 + NA NA #> 8055 NA NA #> 8056 NA NA #> 8057 I NA NA #> 8058 NA NA #> 8059 NA NA #> 8060 NA NA #> 8061 NA NA #> 8062 NA NA #> 8063 NA NA #> 8064 + NA NA #> 8065 NA NA #> 8066 NA NA #> 8067 I NA NA #> 8068 A NA NA #> 8069 NA NA #> 8070 NA NA #> 8071 I NA NA #> 8072 NA NA #> 8073 NA NA #> 8074 + NA NA #> 8075 NA NA #> 8076 NA NA #> 8077 A NA NA #> 8078 NA NA #> 8079 NA NA #> 8080 NA NA #> 8081 I NA NA #> 8082 NA NA #> 8083 NA NA #> 8084 + NA NA #> 8085 NA NA #> 8086 NA NA #> 8087 NA NA #> 8088 NA NA #> 8089 NA NA #> 8090 NA NA #> 8091 NA NA #> 8092 NA NA #> 8093 NA NA #> 8094 + NA NA #> 8095 NA NA #> 8096 NA NA #> 8097 I NA NA #> 8098 A NA NA #> 8099 NA NA #> 8100 NA NA #> 8101 NA NA #> 8102 + NA NA #> 8103 NA NA #> 8104 NA NA #> 8105 I NA NA #> 8106 NA NA #> 8107 NA NA #> 8108 NA NA #> 8109 NA NA #> 8110 NA NA #> 8111 NA NA #> 8112 + NA NA #> 8113 NA NA #> 8114 NA NA #> 8115 I NA NA #> 8116 NA NA #> 8117 NA NA #> 8118 NA NA #> 8119 NA NA #> 8120 NA NA #> 8121 NA NA #> 8122 + NA NA #> 8123 NA NA #> 8124 NA NA #> 8125 NA NA #> 8126 NA NA #> 8127 NA NA #> 8128 NA NA #> 8129 I NA NA #> 8130 NA NA #> 8131 NA NA #> 8132 + NA NA #> 8133 NA NA #> 8134 NA NA #> 8135 I NA NA #> 8136 NA NA #> 8137 NA NA #> 8138 NA NA #> 8139 I NA NA #> 8140 NA NA #> 8141 I NA NA #> 8142 + NA NA #> 8143 NA NA #> 8144 A NA NA #> 8145 NA NA #> 8146 NA NA #> 8147 NA NA #> 8148 NA NA #> 8149 U NA NA #> 8150 NA NA #> 8151 + NA NA #> 8152 NA NA #> 8153 NA NA #> 8154 NA NA #> 8155 NA NA #> 8156 NA NA #> 8157 NA NA #> 8158 U NA NA #> 8159 NA NA #> 8160 NA NA #> 8161 + NA NA #> 8162 NA NA #> 8163 NA NA #> 8164 NA NA #> 8165 NA NA #> 8166 NA NA #> 8167 NA NA #> 8168 NA NA #> 8169 NA NA #> 8170 NA NA #> 8171 + NA NA #> 8172 NA NA #> 8173 NA NA #> 8174 NA NA #> 8175 NA NA #> 8176 NA NA #> 8177 NA NA #> 8178 I NA NA #> 8179 NA NA #> 8180 NA NA #> 8181 + NA NA #> 8182 NA NA #> 8183 NA NA #> 8184 NA NA #> 8185 NA NA #> 8186 NA NA #> 8187 NA NA #> 8188 NA NA #> 8189 NA NA #> 8190 NA NA #> 8191 + NA NA #> 8192 NA NA #> 8193 NA NA #> 8194 NA NA #> 8195 NA NA #> 8196 NA NA #> 8197 NA NA #> 8198 I NA NA #> 8199 NA NA #> 8200 NA NA #> 8201 + NA NA #> 8202 NA NA #> 8203 NA NA #> 8204 I NA NA #> 8205 A NA NA #> 8206 NA NA #> 8207 NA NA #> 8208 NA NA #> 8209 NA NA #> 8210 NA NA #> 8211 + NA NA #> 8212 NA NA #> 8213 NA NA #> 8214 I NA NA #> 8215 A NA NA #> 8216 NA NA #> 8217 + NA NA #> 8218 NA NA #> 8219 NA NA #> 8220 NA NA #> 8221 + NA NA #> 8222 NA NA #> 8223 NA NA #> 8224 NA NA #> 8225 NA NA #> 8226 NA NA #> 8227 NA NA #> 8228 NA NA #> 8229 NA NA #> 8230 NA NA #> 8231 + NA NA #> 8232 NA NA #> 8233 NA NA #> 8234 I NA NA #> 8235 I NA NA #> 8236 NA NA #> 8237 NA NA #> 8238 I NA NA #> 8239 NA NA #> 8240 NA NA #> 8241 + NA NA #> 8242 NA NA #> 8243 I NA NA #> 8244 I NA NA #> 8245 I NA NA #> 8246 NA NA #> 8247 NA NA #> 8248 U NA NA #> 8249 NA NA #> 8250 NA NA #> 8251 + NA NA #> 8252 NA NA #> 8253 NA NA #> 8254 NA NA #> 8255 NA NA #> 8256 NA NA #> 8257 NA NA #> 8258 I NA NA #> 8259 NA NA #> 8260 I NA NA #> 8261 + NA NA #> 8262 NA NA #> 8263 NA NA #> 8264 NA NA #> 8265 I NA NA #> 8266 NA NA #> 8267 NA NA #> 8268 I NA NA #> 8269 NA NA #> 8270 NA NA #> 8271 + NA NA #> 8272 NA NA #> 8273 I NA NA #> 8274 NA NA #> 8275 A NA NA #> 8276 NA NA #> 8277 NA NA #> 8278 I NA NA #> 8279 NA NA #> 8280 NA NA #> 8281 + NA NA #> 8282 NA NA #> 8283 NA NA #> 8284 NA NA #> 8285 NA NA #> 8286 I NA NA #> 8287 NA NA #> 8288 NA NA #> 8289 + NA NA #> 8290 NA NA #> 8291 NA NA #> 8292 NA NA #> 8293 A NA NA #> 8294 NA NA #> 8295 NA NA #> 8296 I NA NA #> 8297 NA NA #> 8298 NA NA #> 8299 + NA NA #> 8300 NA NA #> 8301 NA NA #> 8302 NA NA #> 8303 NA NA #> 8304 NA NA #> 8305 NA NA #> 8306 I NA NA #> 8307 NA NA #> 8308 NA NA #> 8309 + NA NA #> 8310 NA NA #> 8311 NA NA #> 8312 I NA NA #> 8313 NA NA #> 8314 NA NA #> 8315 NA NA #> 8316 NA NA #> 8317 NA NA #> 8318 NA NA #> 8319 + NA NA #> 8320 NA NA #> 8321 NA NA #> 8322 NA NA #> 8323 NA NA #> 8324 NA NA #> 8325 NA NA #> 8326 NA NA #> 8327 NA NA #> 8328 NA NA #> 8329 + NA NA #> 8330 NA NA #> 8331 NA NA #> 8332 NA NA #> 8333 NA NA #> 8334 NA NA #> 8335 NA NA #> 8336 NA NA #> 8337 NA NA #> 8338 NA NA #> 8339 + NA NA #> 8340 NA NA #> 8341 NA NA #> 8342 NA NA #> 8343 NA NA #> 8344 NA NA #> 8345 NA NA #> 8346 NA NA #> 8347 NA NA #> 8348 NA NA #> 8349 + NA NA #> 8350 NA NA #> 8351 NA NA #> 8352 NA NA #> 8353 NA NA #> 8354 NA NA #> 8355 NA NA #> 8356 I NA NA #> 8357 NA NA #> 8358 NA NA #> 8359 + NA NA #> 8360 NA NA #> 8361 NA NA #> 8362 NA NA #> 8363 NA NA #> 8364 NA NA #> 8365 NA NA #> 8366 NA NA #> 8367 NA NA #> 8368 NA NA #> 8369 NA NA #> 8370 NA NA #> 8371 NA NA #> 8372 NA NA #> 8373 NA NA #> 8374 NA NA #> 8375 NA NA #> 8376 NA NA #> 8377 NA NA #> 8378 NA NA #> 8379 NA NA #> 8380 NA NA #> 8381 NA NA #> 8382 NA NA #> 8383 NA NA #> 8384 NA NA #> 8385 NA NA #> 8386 NA NA #> 8387 NA NA #> 8388 NA NA #> 8389 NA NA #> 8390 NA NA #> 8391 NA NA #> 8392 NA NA #> 8393 NA NA #> 8394 NA NA #> 8395 NA NA #> 8396 NA NA #> 8397 NA NA #> 8398 NA NA #> 8399 NA NA #> 8400 NA NA #> 8401 NA NA #> 8402 NA NA #> 8403 NA NA #> 8404 NA NA #> 8405 NA NA #> 8406 NA NA #> 8407 NA NA #> 8408 NA NA #> 8409 NA NA #> 8410 NA NA #> 8411 NA NA #> 8412 NA NA #> 8413 NA NA #> 8414 NA NA #> 8415 NA NA #> 8416 NA NA #> 8417 NA NA #> 8418 NA NA #> 8419 NA NA #> 8420 NA NA #> 8421 NA NA #> 8422 NA NA #> 8423 NA NA #> 8424 NA NA #> 8425 I NA NA #> 8426 NA NA #> 8427 NA NA #> 8428 NA NA #> 8429 NA NA #> 8430 NA NA #> 8431 NA NA #> 8432 + NA NA #> 8433 I NA NA #> 8434 NA NA #> 8435 NA NA #> 8436 NA NA #> 8437 NA NA #> 8438 NA NA #> 8439 NA NA #> 8440 NA NA #> 8441 NA NA #> 8442 + NA NA #> 8443 NA NA #> 8444 NA NA #> 8445 NA NA #> 8446 NA NA #> 8447 NA NA #> 8448 + NA NA #> 8449 U NA NA #> 8450 NA NA #> 8451 NA NA #> 8452 NA NA #> 8453 NA NA #> 8454 NA NA #> 8455 NA NA #> 8456 NA NA #> 8457 NA NA #> 8458 + NA NA #> 8459 NA NA #> 8460 I NA NA #> 8461 NA NA #> 8462 NA NA #> 8463 + NA NA #> 8464 I NA NA #> 8465 NA NA #> 8466 NA NA #> 8467 NA NA #> 8468 NA NA #> 8469 NA NA #> 8470 NA NA #> 8471 NA NA #> 8472 NA NA #> 8473 + NA NA #> 8474 NA NA #> 8475 NA NA #> 8476 NA NA #> 8477 + NA NA #> 8478 NA NA #> 8479 NA NA #> 8480 NA NA #> 8481 + NA NA #> 8482 NA NA #> 8483 NA NA #> 8484 NA NA #> 8485 NA NA #> 8486 NA NA #> 8487 NA NA #> 8488 NA NA #> 8489 NA NA #> 8490 NA NA #> 8491 NA NA #> 8492 + NA NA #> 8493 NA NA #> 8494 NA NA #> 8495 NA NA #> 8496 + NA NA #> 8497 NA NA #> 8498 NA NA #> 8499 NA NA #> 8500 + NA NA #> 8501 NA NA #> 8502 NA NA #> 8503 NA NA #> 8504 NA NA #> 8505 + NA NA #> 8506 NA NA #> 8507 NA NA #> 8508 NA NA #> 8509 NA NA #> 8510 NA NA #> 8511 NA NA #> 8512 NA NA #> 8513 NA NA #> 8514 NA NA #> 8515 + NA NA #> 8516 NA NA #> 8517 NA NA #> 8518 NA NA #> 8519 + NA NA #> 8520 NA NA #> 8521 NA NA #> 8522 NA NA #> 8523 NA NA #> 8524 + NA NA #> 8525 I NA NA #> 8526 NA NA #> 8527 NA NA #> 8528 NA NA #> 8529 NA NA #> 8530 NA NA #> 8531 NA NA #> 8532 NA NA #> 8533 NA NA #> 8534 + NA NA #> 8535 NA NA #> 8536 NA NA #> 8537 NA NA #> 8538 + NA NA #> 8539 NA NA #> 8540 NA NA #> 8541 NA NA #> 8542 NA NA #> 8543 + NA NA #> 8544 I NA NA #> 8545 NA NA #> 8546 NA NA #> 8547 NA NA #> 8548 NA NA #> 8549 NA NA #> 8550 NA NA #> 8551 + NA NA #> 8552 NA NA #> 8553 NA NA #> 8554 NA NA #> 8555 NA NA #> 8556 NA NA #> 8557 NA NA #> 8558 + NA NA #> 8559 I NA NA #> 8560 NA NA #> 8561 NA NA #> 8562 NA NA #> 8563 NA NA #> 8564 NA NA #> 8565 NA NA #> 8566 NA NA #> 8567 NA NA #> 8568 + NA NA #> 8569 NA NA #> 8570 NA NA #> 8571 NA NA #> 8572 + NA NA #> 8573 NA NA #> 8574 NA NA #> 8575 NA NA #> 8576 NA NA #> 8577 + NA NA #> 8578 U NA NA #> 8579 NA NA #> 8580 NA NA #> 8581 NA NA #> 8582 NA NA #> 8583 NA NA #> 8584 NA NA #> 8585 NA NA #> 8586 NA NA #> 8587 + NA NA #> 8588 NA NA #> 8589 NA NA #> 8590 NA NA #> 8591 + NA NA #> 8592 NA NA #> 8593 NA NA #> 8594 NA NA #> 8595 + NA NA #> 8596 U NA NA #> 8597 NA NA #> 8598 NA NA #> 8599 NA NA #> 8600 NA NA #> 8601 NA NA #> 8602 NA NA #> 8603 NA NA #> 8604 NA NA #> 8605 + NA NA #> 8606 NA NA #> 8607 NA NA #> 8608 U NA NA #> 8609 NA NA #> 8610 NA NA #> 8611 + NA NA #> 8612 NA NA #> 8613 NA NA #> 8614 NA NA #> 8615 NA NA #> 8616 NA NA #> 8617 NA NA #> 8618 NA NA #> 8619 + NA NA #> 8620 U NA NA #> 8621 NA NA #> 8622 NA NA #> 8623 NA NA #> 8624 NA NA #> 8625 NA NA #> 8626 NA NA #> 8627 NA NA #> 8628 NA NA #> 8629 + NA NA #> 8630 NA NA #> 8631 NA NA #> 8632 NA NA #> 8633 + NA NA #> 8634 NA NA #> 8635 NA NA #> 8636 NA NA #> 8637 + NA NA #> 8638 U NA NA #> 8639 NA NA #> 8640 NA NA #> 8641 NA NA #> 8642 NA NA #> 8643 NA NA #> 8644 NA NA #> 8645 NA NA #> 8646 NA NA #> 8647 + NA NA #> 8648 NA NA #> 8649 NA NA #> 8650 NA NA #> 8651 + NA NA #> 8652 NA NA #> 8653 NA NA #> 8654 NA NA #> 8655 NA NA #> 8656 NA NA #> 8657 NA NA #> 8658 NA NA #> 8659 + NA NA #> 8660 NA NA #> 8661 + NA NA #> 8662 NA NA #> 8663 I NA NA #> 8664 NA NA #> 8665 A NA NA #> 8666 NA NA #> 8667 NA NA #> 8668 NA NA #> 8669 NA NA #> 8670 NA NA #> 8671 NA NA #> 8672 NA NA #> 8673 + NA NA #> 8674 NA NA #> 8675 NA NA #> 8676 NA NA #> 8677 I NA NA #> 8678 NA NA #> 8679 NA NA #> 8680 NA NA #> 8681 NA NA #> 8682 NA NA #> 8683 NA NA #> 8684 NA NA #> 8685 + NA NA #> 8686 NA NA #> 8687 I NA NA #> 8688 NA NA #> 8689 NA NA #> 8690 A NA NA #> 8691 NA NA #> 8692 NA NA #> 8693 + NA NA #> 8694 NA NA #> 8695 + NA NA #> 8696 NA NA #> 8697 I NA NA #> 8698 A NA NA #> 8699 NA NA #> 8700 NA NA #> 8701 NA NA #> 8702 NA NA #> 8703 NA NA #> 8704 NA NA #> 8705 NA NA #> 8706 + NA NA #> 8707 NA NA #> 8708 NA NA #> 8709 NA NA #> 8710 NA NA #> 8711 NA NA #> 8712 NA NA #> 8713 NA NA #> 8714 NA NA #> 8715 NA NA #> 8716 NA NA #> 8717 + NA NA #> 8718 NA NA #> 8719 I NA NA #> 8720 A NA NA #> 8721 NA NA #> 8722 NA NA #> 8723 NA NA #> 8724 NA NA #> 8725 NA NA #> 8726 NA NA #> 8727 + NA NA #> 8728 NA NA #> 8729 + NA NA #> 8730 NA NA #> 8731 I NA NA #> 8732 A NA NA #> 8733 NA NA #> 8734 NA NA #> 8735 NA NA #> 8736 NA NA #> 8737 NA NA #> 8738 NA NA #> 8739 + NA NA #> 8740 NA NA #> 8741 + NA NA #> 8742 NA NA #> 8743 I NA NA #> 8744 NA NA #> 8745 NA NA #> 8746 A NA NA #> 8747 NA NA #> 8748 NA NA #> 8749 NA NA #> 8750 NA NA #> 8751 + NA NA #> 8752 NA NA #> 8753 + NA NA #> 8754 NA NA #> 8755 I NA NA #> 8756 NA NA #> 8757 NA NA #> 8758 NA NA #> 8759 NA NA #> 8760 + NA NA #> 8761 NA NA #> 8762 NA NA #> 8763 NA NA #> 8764 NA NA #> 8765 NA NA #> 8766 U NA NA #> 8767 + NA NA #> 8768 NA NA #> 8769 + NA NA #> 8770 NA NA #> 8771 I NA NA #> 8772 NA NA #> 8773 NA NA #> 8774 NA NA #> 8775 NA NA #> 8776 NA NA #> 8777 NA NA #> 8778 NA NA #> 8779 NA NA #> 8780 + NA NA #> 8781 NA NA #> 8782 I NA NA #> 8783 NA NA #> 8784 NA NA #> 8785 NA NA #> 8786 NA NA #> 8787 NA NA #> 8788 NA NA #> 8789 NA NA #> 8790 NA NA #> 8791 NA NA #> 8792 + NA NA #> 8793 NA NA #> 8794 I NA NA #> 8795 NA NA #> 8796 NA NA #> 8797 NA NA #> 8798 NA NA #> 8799 NA NA #> 8800 NA NA #> 8801 NA NA #> 8802 NA NA #> 8803 NA NA #> 8804 NA NA #> 8805 NA NA #> 8806 NA NA #> 8807 NA NA #> 8808 + NA NA #> 8809 NA NA #> 8810 I NA NA #> 8811 NA NA #> 8812 NA NA 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9088 NA NA #> 9089 NA NA #> 9090 + NA NA #> [ reached 'max' / getOption(\"max.print\") -- omitted 165157 rows ]"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_refs.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert references csv to bib — anlz_refs","title":"Convert references csv to bib — anlz_refs","text":"Convert references csv bib","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_refs.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert references csv to bib — anlz_refs","text":"","code":"anlz_refs(path)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_refs.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert references csv to bib — anlz_refs","text":"path chr string path reference csv file data frame object","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_refs.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert references csv to bib — anlz_refs","text":"data frame references formatted bib entries","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_refs.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Convert references csv to bib — anlz_refs","text":"","code":"# input and format path <- 'https://raw.githubusercontent.com/tbep-tech/tbep-refs/master/tbep-refs.csv' bibs <- anlz_refs(path) if (FALSE) { # save output writeLines(bibs, 'formatted.bib') }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_sedimentaddtot.html","id":null,"dir":"Reference","previous_headings":"","what":"Add contaminant totals to sediment data — anlz_sedimentaddtot","title":"Add contaminant totals to sediment data — anlz_sedimentaddtot","text":"Add contaminant totals sediment data","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_sedimentaddtot.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Add contaminant totals to sediment data — anlz_sedimentaddtot","text":"","code":"anlz_sedimentaddtot( sedimentdata, yrrng = c(1993, 2022), bay_segment = c(\"HB\", \"OTB\", \"MTB\", \"LTB\", \"TCB\", \"MR\", \"BCB\"), funding_proj = \"TBEP\", param = NULL, pelave = TRUE )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_sedimentaddtot.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Add contaminant totals to sediment data — anlz_sedimentaddtot","text":"sedimentdata input sediment data.frame returned read_importsediment yrrng numeric vector indicating min, max years include, use single year one year data bay_segment chr string bay segment, one many \"HB\", \"OTB\", \"MTB\", \"LTB\", \"TCB\", \"MR\", \"BCB\" funding_proj chr string funding project, one many \"TBEP\" (default), \"TBEP-Special\", \"Apollo Beach\", \"Janicki Contract\", \"Rivers\", \"Tidal Streams\" param optional character string parameter filter results pelave logical indicating output used anlz_sedimentpel","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_sedimentaddtot.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Add contaminant totals to sediment data — anlz_sedimentaddtot","text":"data.frame object similar input, filtered arguments contaminant totals added. Replicate samples also removed.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_sedimentaddtot.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Add contaminant totals to sediment data — anlz_sedimentaddtot","text":"function adds totals sedimentdata input total PCBs, total DDT, total LMW PAH, total HMW PAH, total PAH. Appropriate TEL/PEL values totals also added.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_sedimentaddtot.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Add contaminant totals to sediment data — anlz_sedimentaddtot","text":"","code":"anlz_sedimentaddtot(sedimentdata) #> # A tibble: 62,667 × 24 #> ProgramId ProgramName FundingProject yr AreaAbbr StationID StationNumber #> #> 1 4 Benthic Moni… TBEP 1993 HB 2463 93HB15 #> 2 4 Benthic Moni… TBEP 1993 HB 2463 93HB15 #> 3 4 Benthic Moni… TBEP 1993 HB 2463 93HB15 #> 4 4 Benthic Moni… TBEP 1993 HB 2463 93HB15 #> 5 4 Benthic Moni… TBEP 1993 HB 2463 93HB15 #> 6 4 Benthic Moni… TBEP 1993 HB 2463 93HB15 #> 7 4 Benthic Moni… TBEP 1993 HB 2463 93HB15 #> 8 4 Benthic Moni… TBEP 1993 HB 2463 93HB15 #> 9 4 Benthic Moni… TBEP 1993 HB 2463 93HB15 #> 10 4 Benthic Moni… TBEP 1993 HB 2464 93HB16 #> # ℹ 62,657 more rows #> # ℹ 17 more variables: Latitude , Longitude , Replicate , #> # SedResultsType , Parameter , ValueAdjusted , Units , #> # Qualifier , MDLnum , PQLnum , TEL , PEL , #> # BetweenTELPEL , ExceedsPEL , PELRatio , #> # PreparationDate , AnalysisTimeMerge "},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_sedimentave.html","id":null,"dir":"Reference","previous_headings":"","what":"Get average concentrations for a sediment parameter by bay segment — anlz_sedimentave","title":"Get average concentrations for a sediment parameter by bay segment — anlz_sedimentave","text":"Get average concentrations sediment parameter bay segment","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_sedimentave.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get average concentrations for a sediment parameter by bay segment — anlz_sedimentave","text":"","code":"anlz_sedimentave( sedimentdata, param, yrrng = c(1993, 2022), bay_segment = c(\"HB\", \"OTB\", \"MTB\", \"LTB\", \"TCB\", \"MR\", \"BCB\"), funding_proj = \"TBEP\" )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_sedimentave.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get average concentrations for a sediment parameter by bay segment — anlz_sedimentave","text":"sedimentdata input sediment data.frame returned read_importsediment param chr string parameter plot yrrng numeric vector indicating min, max years include, use single year one year data bay_segment chr string bay segment, one many \"HB\", \"OTB\", \"MTB\", \"LTB\", \"TCB\", \"MR\", \"BCB\" funding_proj chr string funding project, one many \"TBEP\" (default), \"TBEP-Special\", \"Apollo Beach\", \"Janicki Contract\", \"Rivers\", \"Tidal Streams\"","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_sedimentave.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get average concentrations for a sediment parameter by bay segment — anlz_sedimentave","text":"data.frame object average sediment concentrations selected parameter bay segment","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_sedimentave.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Get average concentrations for a sediment parameter by bay segment — anlz_sedimentave","text":"Summaries bay segments returned default. averages confidence intervals specific year ranges yrrng.","code":""},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_sedimentave.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get average concentrations for a sediment parameter by bay segment — anlz_sedimentave","text":"","code":"anlz_sedimentave(sedimentdata, param = 'Arsenic') #> # A tibble: 7 × 8 #> AreaAbbr TEL PEL Units ave lov hiv grandave #> #> 1 BCB 7.24 41.6 mg/kg 2.64 2.34 2.94 2.57 #> 2 HB 7.24 41.6 mg/kg 2.93 0.665 5.20 2.57 #> 3 LTB 7.24 41.6 mg/kg 2.93 2.47 3.40 2.57 #> 4 MR 7.24 41.6 mg/kg 1.66 1.37 1.95 2.57 #> 5 MTB 7.24 41.6 mg/kg 2.17 1.86 2.48 2.57 #> 6 OTB 7.24 41.6 mg/kg 3.24 0.707 5.78 2.57 #> 7 TCB 7.24 41.6 mg/kg 2.40 1.92 2.88 2.57"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_sedimentpel.html","id":null,"dir":"Reference","previous_headings":"","what":"Get sediment PEL ratios at stations in Tampa Bay — anlz_sedimentpel","title":"Get sediment PEL ratios at stations in Tampa Bay — anlz_sedimentpel","text":"Get sediment PEL ratios stations Tampa Bay","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_sedimentpel.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get sediment PEL ratios at stations in Tampa Bay — anlz_sedimentpel","text":"","code":"anlz_sedimentpel( sedimentdata, yrrng = c(1993, 2022), bay_segment = c(\"HB\", \"OTB\", \"MTB\", \"LTB\", \"TCB\", \"MR\", \"BCB\"), funding_proj = \"TBEP\" )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_sedimentpel.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get sediment PEL ratios at stations in Tampa Bay — anlz_sedimentpel","text":"sedimentdata input sediment data.frame returned read_importsediment yrrng numeric vector indicating min, max years include, use single year one year data bay_segment chr string bay segment, one many \"HB\", \"OTB\", \"MTB\", \"LTB\", \"TCB\", \"MR\", \"BCB\" funding_proj chr string funding project, one many \"TBEP\" (default), \"TBEP-Special\", \"Apollo Beach\", \"Janicki Contract\", \"Rivers\", \"Tidal Streams\"","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_sedimentpel.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get sediment PEL ratios at stations in Tampa Bay — anlz_sedimentpel","text":"data.frame object average PEL ratios grades station","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_sedimentpel.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Get sediment PEL ratios at stations in Tampa Bay — anlz_sedimentpel","text":"Average PEL ratios contaminants graded F benthic stations monitored Tampa Bay estimated. PEL measure likely contaminant toxic effect invertebrates inhabit sediment. PEL ratio contaminant concentration divided Potential Effects Levels (PEL) applies contaminant, available. Higher ratios lower grades indicate sediment conditions likely unfavorable invertebrates. station average combines PEL ratios across contaminants measured station grade applies average. grade breaks PEL ratio 0.00756, 0.02052, 0.08567, 0.28026, lower grades assigned higher breaks.","code":""},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_sedimentpel.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get sediment PEL ratios at stations in Tampa Bay — anlz_sedimentpel","text":"","code":"anlz_sedimentpel(sedimentdata) #> # A tibble: 2,233 × 7 #> yr AreaAbbr StationNumber Latitude Longitude PELRatio Grade #> #> 1 1993 HB 93HB15 27.8 -82.4 0.0157 B #> 2 1993 HB 93HB16 27.8 -82.5 0.0261 C #> 3 1993 HB 93HB23 27.9 -82.4 0.0174 B #> 4 1993 LTB 93LTB24 27.7 -82.6 0.0124 B #> 5 1993 LTB 93LTB25 27.6 -82.6 0.0189 B #> 6 1993 LTB 93LTB26 27.6 -82.7 0.00997 B #> 7 1993 LTB 93LTB27 27.6 -82.7 0.0125 B #> 8 1993 LTB 93LTB28 27.6 -82.7 0.0887 D #> 9 1993 LTB 93LTB29 27.6 -82.6 0.0350 C #> 10 1993 LTB 93LTB30 27.6 -82.6 0.0496 C #> # ℹ 2,223 more rows"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_sedimentpelave.html","id":null,"dir":"Reference","previous_headings":"","what":"Get average concentrations for a sediment parameter by bay segment — anlz_sedimentpelave","title":"Get average concentrations for a sediment parameter by bay segment — anlz_sedimentpelave","text":"Get average concentrations sediment parameter bay segment","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_sedimentpelave.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get average concentrations for a sediment parameter by bay segment — anlz_sedimentpelave","text":"","code":"anlz_sedimentpelave( sedimentdata, yrrng = c(1993, 2022), bay_segment = c(\"HB\", \"OTB\", \"MTB\", \"LTB\", \"TCB\", \"MR\", \"BCB\"), funding_proj = \"TBEP\" )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_sedimentpelave.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get average concentrations for a sediment parameter by bay segment — anlz_sedimentpelave","text":"sedimentdata input sediment data.frame returned read_importsediment yrrng numeric vector indicating min, max years include, use single year one year data bay_segment chr string bay segment, one many \"HB\", \"OTB\", \"MTB\", \"LTB\", \"TCB\", \"MR\", \"BCB\" funding_proj chr string funding project, one many \"TBEP\" (default), \"TBEP-Special\", \"Apollo Beach\", \"Janicki Contract\", \"Rivers\", \"Tidal Streams\"","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_sedimentpelave.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get average concentrations for a sediment parameter by bay segment — anlz_sedimentpelave","text":"data.frame average average PEL ratios bay segment","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_sedimentpelave.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Get average concentrations for a sediment parameter by bay segment — anlz_sedimentpelave","text":"Summaries bay segments returned default. averages confidence intervals specific year ranges yrrng.","code":""},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_sedimentpelave.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get average concentrations for a sediment parameter by bay segment — anlz_sedimentpelave","text":"","code":"anlz_sedimentpelave(sedimentdata) #> # A tibble: 7 × 5 #> AreaAbbr ave lov hiv grandave #> #> 1 BCB 0.0535 0.0445 0.0625 0.0522 #> 2 HB 0.118 0.0663 0.169 0.0522 #> 3 LTB 0.0281 0.0247 0.0315 0.0522 #> 4 MR 0.0446 0.0375 0.0516 0.0522 #> 5 MTB 0.0374 0.0327 0.0421 0.0522 #> 6 OTB 0.0506 0.0371 0.0642 0.0522 #> 7 TCB 0.0337 0.0265 0.0409 0.0522"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbbimed.html","id":null,"dir":"Reference","previous_headings":"","what":"Get annual medians of Tampa Bay Benthic Index scores by bay segment — anlz_tbbimed","title":"Get annual medians of Tampa Bay Benthic Index scores by bay segment — anlz_tbbimed","text":"Get annual medians Tampa Bay Benthic Index scores bay segment","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbbimed.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get annual medians of Tampa Bay Benthic Index scores by bay segment — anlz_tbbimed","text":"","code":"anlz_tbbimed( tbbiscr, bay_segment = c(\"HB\", \"OTB\", \"MTB\", \"LTB\", \"TCB\", \"MR\", \"BCB\", \"All\", \"All (wt)\"), rev = FALSE, yrrng = c(1993, 2022) )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbbimed.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get annual medians of Tampa Bay Benthic Index scores by bay segment — anlz_tbbimed","text":"tbbiscr input data frame returned anlz_tbbiscr bay_segment chr string bay segment, one many \"HB\", \"OTB\", \"MTB\", \"LTB\", \"TCB\", \"MR\", \"BCB\", \"\", \"(wt)\" rev logical factor levels bay segments reversed yrrng numeric indicating year ranges evaluate","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbbimed.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get annual medians of Tampa Bay Benthic Index scores by bay segment — anlz_tbbimed","text":"data frame annual medians bay segment","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbbimed.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Get annual medians of Tampa Bay Benthic Index scores by bay segment — anlz_tbbimed","text":"Additional summaries provided entire bay, summary across categories (\"\") summary weighted across relative sizes bay segment (\"(wt)\"). sampling funded TBEP part routine EPC benthic monitoring program included final categories.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbbimed.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get annual medians of Tampa Bay Benthic Index scores by bay segment — anlz_tbbimed","text":"","code":"tbbiscr <- anlz_tbbiscr(benthicdata) anlz_tbbimed(tbbiscr) #> # A tibble: 268 × 6 #> # Rowwise: #> bay_segment yr Degraded Healthy Intermediate TBBICat #> #> 1 All 1993 0.3 0.244 0.456 Poor #> 2 All 1994 0.449 0.180 0.371 Poor #> 3 All 1995 0.133 0.508 0.359 Fair #> 4 All 1996 0.138 0.569 0.292 Fair #> 5 All 1997 0.157 0.421 0.421 Fair #> 6 All 1998 0.231 0.316 0.453 Poor #> 7 All 1999 0.107 0.377 0.516 Fair #> 8 All 2000 0.163 0.407 0.430 Fair #> 9 All 2001 0.231 0.321 0.449 Poor #> 10 All 2002 0.2 0.425 0.375 Poor #> # ℹ 258 more rows"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbbiscr.html","id":null,"dir":"Reference","previous_headings":"","what":"Get Tampa Bay Benthic Index scores — anlz_tbbiscr","title":"Get Tampa Bay Benthic Index scores — anlz_tbbiscr","text":"Get Tampa Bay Benthic Index scores","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbbiscr.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get Tampa Bay Benthic Index scores — anlz_tbbiscr","text":"","code":"anlz_tbbiscr(benthicdata)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbbiscr.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get Tampa Bay Benthic Index scores — anlz_tbbiscr","text":"benthicdata nested tibble formatted read_importbenthic","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbbiscr.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get Tampa Bay Benthic Index scores — anlz_tbbiscr","text":"single data frame TBBI scores site.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbbiscr.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Get Tampa Bay Benthic Index scores — anlz_tbbiscr","text":"function calculates scores TBBI based station, taxa, field sample data. total TBBI scores returned TBBI TBBICat, latter categorical description scores.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbbiscr.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get Tampa Bay Benthic Index scores — anlz_tbbiscr","text":"","code":"anlz_tbbiscr(benthicdata) #> # A tibble: 4,787 × 15 #> StationID StationNumber AreaAbbr FundingProject ProgramID ProgramName #> #> 1 448 02BBs301 MTB Apollo Beach 4 Benthic Monitoring #> 2 449 02BBs305 MTB Apollo Beach 4 Benthic Monitoring #> 3 450 02BBs307 MTB Apollo Beach 4 Benthic Monitoring #> 4 451 02BBs364 MTB Apollo Beach 4 Benthic Monitoring #> 5 452 02BBs369 MTB Apollo Beach 4 Benthic Monitoring #> 6 453 02BBs395 MTB Apollo Beach 4 Benthic Monitoring #> 7 454 02BBs397 MTB Apollo Beach 4 Benthic Monitoring #> 8 455 02BBs398 MTB Apollo Beach 4 Benthic Monitoring #> 9 456 02BBs401 MTB Apollo Beach 4 Benthic Monitoring #> 10 457 02BBs402 MTB Apollo Beach 4 Benthic Monitoring #> # ℹ 4,777 more rows #> # ℹ 9 more variables: Latitude , Longitude , date , yr , #> # TotalAbundance , SpeciesRichness , TBBI , TBBICat , #> # Salinity "},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbniave.html","id":null,"dir":"Reference","previous_headings":"","what":"Get annual averages of Tampa Bay Nekton Index scores by bay segment — anlz_tbniave","title":"Get annual averages of Tampa Bay Nekton Index scores by bay segment — anlz_tbniave","text":"Get annual averages Tampa Bay Nekton Index scores bay segment","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbniave.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get annual averages of Tampa Bay Nekton Index scores by bay segment — anlz_tbniave","text":"","code":"anlz_tbniave( tbniscr, bay_segment = c(\"OTB\", \"HB\", \"MTB\", \"LTB\"), rev = FALSE, perc = c(32, 46) )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbniave.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get annual averages of Tampa Bay Nekton Index scores by bay segment — anlz_tbniave","text":"tbniscr input data frame returned anlz_tbniscr bay_segment chr string bay segment, one many \"OTB\", \"HB\", \"MTB\", \"LTB\" rev logical factor levels bay segments reversed perc numeric values indicating break points score categories","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbniave.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get annual averages of Tampa Bay Nekton Index scores by bay segment — anlz_tbniave","text":"data frame annual averages bay segment","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbniave.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get annual averages of Tampa Bay Nekton Index scores by bay segment — anlz_tbniave","text":"","code":"tbniscr <- anlz_tbniscr(fimdata) anlz_tbniave(tbniscr) #> # A tibble: 100 × 5 #> bay_segment Year Segment_TBNI Action outcome #> #> 1 HB 1998 47 Stay the Course green #> 2 HB 1999 47 Stay the Course green #> 3 HB 2000 44 Caution yellow #> 4 HB 2001 44 Caution yellow #> 5 HB 2002 39 Caution yellow #> 6 HB 2003 41 Caution yellow #> 7 HB 2004 41 Caution yellow #> 8 HB 2005 32 Caution yellow #> 9 HB 2006 41 Caution yellow #> 10 HB 2007 42 Caution yellow #> # ℹ 90 more rows"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbnimet.html","id":null,"dir":"Reference","previous_headings":"","what":"Get all raw metrics for Tampa Bay Nekton Index — anlz_tbnimet","title":"Get all raw metrics for Tampa Bay Nekton Index — anlz_tbnimet","text":"Get raw metrics Tampa Bay Nekton Index","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbnimet.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get all raw metrics for Tampa Bay Nekton Index — anlz_tbnimet","text":"","code":"anlz_tbnimet(fimdata, all = FALSE)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbnimet.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get all raw metrics for Tampa Bay Nekton Index — anlz_tbnimet","text":"fimdata data.frame formatted read_importfim logical indicating TBNI metrics returned (default), otherwise calcualted","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbnimet.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get all raw metrics for Tampa Bay Nekton Index — anlz_tbnimet","text":"data frame raw metrics wide fomat. = TRUE, metrics returned, otherwise NumTaxa, BenthicTaxa, TaxaSelect, NumGuilds, Shannon returned.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbnimet.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Get all raw metrics for Tampa Bay Nekton Index — anlz_tbnimet","text":"raw metrics returned addition required TBNI. row shows metric values station, year, month fish catch data available.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbnimet.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get all raw metrics for Tampa Bay Nekton Index — anlz_tbnimet","text":"","code":"anlz_tbnimet(fimdata) #> # A tibble: 7,445 × 10 #> Reference Year Month Season bay_segment NumTaxa Shannon TaxaSelect NumGuilds #> #> 1 TBM19980… 1998 1 Winter OTB 2 0.362 0 2 #> 2 TBM19980… 1998 1 Winter OTB 1 0 1 1 #> 3 TBM19980… 1998 1 Winter OTB 0 0 0 0 #> 4 TBM19980… 1998 1 Winter OTB 2 0.693 0 1 #> 5 TBM19980… 1998 1 Winter MTB 4 1.16 1 2 #> 6 TBM19980… 1998 1 Winter MTB 2 0.500 1 1 #> 7 TBM19980… 1998 1 Winter MTB 5 0.426 2 3 #> 8 TBM19980… 1998 1 Winter OTB 0 0 0 0 #> 9 TBM19980… 1998 1 Winter HB 4 0.794 1 4 #> 10 TBM19980… 1998 1 Winter HB 1 0 0 1 #> # ℹ 7,435 more rows #> # ℹ 1 more variable: BenthicTaxa "},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbniscr.html","id":null,"dir":"Reference","previous_headings":"","what":"Get Tampa Bay Nekton Index scores — anlz_tbniscr","title":"Get Tampa Bay Nekton Index scores — anlz_tbniscr","text":"Get Tampa Bay Nekton Index scores","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbniscr.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get Tampa Bay Nekton Index scores — anlz_tbniscr","text":"","code":"anlz_tbniscr(fimdata, raw = TRUE)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbniscr.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get Tampa Bay Nekton Index scores — anlz_tbniscr","text":"fimdata data.frame formatted read_importfim raw logical indicating raw metric values also returned","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbniscr.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get Tampa Bay Nekton Index scores — anlz_tbniscr","text":"data frame metrics TBNI scores wide format.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbniscr.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Get Tampa Bay Nekton Index scores — anlz_tbniscr","text":"function calculates raw scored metrics TBNI, including NumTaxa, BenthicTaxa, TaxaSelect, NumGuilds, Shannon. total TBNI score returned TBNI_Score.","code":""},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tbniscr.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get Tampa Bay Nekton Index scores — anlz_tbniscr","text":"","code":"anlz_tbniscr(fimdata) #> # A tibble: 7,445 × 16 #> Reference Year Month Season bay_segment TBNI_Score NumTaxa ScoreNumTaxa #> #> 1 TBM1998010906 1998 1 Winter OTB 18 2 2 #> 2 TBM1998010910 1998 1 Winter OTB 14 1 1 #> 3 TBM1998010912 1998 1 Winter OTB 0 0 0 #> 4 TBM1998010914 1998 1 Winter OTB 20 2 2 #> 5 TBM1998010915 1998 1 Winter MTB 46 4 4 #> 6 TBM1998010917 1998 1 Winter MTB 24 2 2 #> 7 TBM1998010920 1998 1 Winter MTB 50 5 5 #> 8 TBM1998010922 1998 1 Winter OTB 0 0 0 #> 9 TBM1998010926 1998 1 Winter HB 48 4 4 #> 10 TBM1998010928 1998 1 Winter HB 8 1 1 #> # ℹ 7,435 more rows #> # ℹ 8 more variables: BenthicTaxa , ScoreBenthicTaxa , #> # TaxaSelect , ScoreTaxaSelect , NumGuilds , #> # ScoreNumGuilds , Shannon , ScoreShannon "},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tdlcrk.html","id":null,"dir":"Reference","previous_headings":"","what":"Estimate tidal creek report card scores — anlz_tdlcrk","title":"Estimate tidal creek report card scores — anlz_tdlcrk","text":"Estimate tidal creek report card scores","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tdlcrk.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Estimate tidal creek report card scores — anlz_tdlcrk","text":"","code":"anlz_tdlcrk(tidalcreeks, iwrraw, tidtrgs = NULL, yr = 2023)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tdlcrk.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Estimate tidal creek report card scores — anlz_tdlcrk","text":"tidalcreeks sf object population tidal creeks iwrraw FDEP impaired waters data base data.frame tidtrgs optional data.frame tidal creek nitrogen targets, defaults tidaltargets yr numeric reference year evaluate, scores based planning period beginning ten years prior date","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tdlcrk.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Estimate tidal creek report card scores — anlz_tdlcrk","text":"data.frame report card scores creek, prioritize, investigate, caution, monitor, data","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tdlcrk.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Estimate tidal creek report card scores — anlz_tdlcrk","text":"","code":"anlz_tdlcrk(tidalcreeks, iwrraw, yr = 2023) #> # A tibble: 615 × 10 #> id wbid JEI name class monitor caution investigate prioritize score #> #> 1 1 1983B CC01 Rock Cr… 2 NA NA NA NA No D… #> 2 2 2052 CC01 Rock Cr… 3M 10 NA NA NA Moni… #> 3 3 1983B CC02 Oyster … 2 NA NA NA NA No D… #> 4 4 2067 CC02 Oyster … 3M 10 NA NA NA Moni… #> 5 5 1983B CC03 Buck Cr… 2 NA NA NA NA No D… #> 6 6 2068 CC03 Buck Cr… 3M 9 1 NA NA Moni… #> 7 7 2078A CC04 Buck Cr… 2 NA NA 1 NA Inve… #> 8 8 2078A CC05 Coral C… 2 NA NA NA NA No D… #> 9 9 2078B CC05 Coral C… 2 4 1 NA NA Moni… #> 10 10 2065C CC06 Catfish… 2 NA NA NA NA No D… #> # ℹ 605 more rows"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tdlcrkindic.html","id":null,"dir":"Reference","previous_headings":"","what":"Analyze tidal creek water quality indicators — anlz_tdlcrkindic","title":"Analyze tidal creek water quality indicators — anlz_tdlcrkindic","text":"Estimate tidal creek water quality indicators support report card scores","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tdlcrkindic.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Analyze tidal creek water quality indicators — anlz_tdlcrkindic","text":"","code":"anlz_tdlcrkindic(tidalcreeks, iwrraw, yr = 2023, radar = FALSE)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tdlcrkindic.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Analyze tidal creek water quality indicators — anlz_tdlcrkindic","text":"tidalcreeks sf object population tidal creeks iwrraw FDEP impaired waters rule data base data.frame yr numeric reference year evaluate, scores based planning period beginning ten years prior date radar logical indicating output show_tdlcrkradar, see details","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tdlcrkindic.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Analyze tidal creek water quality indicators — anlz_tdlcrkindic","text":"data.frame indicator values tidal creek","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tdlcrkindic.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Analyze tidal creek water quality indicators — anlz_tdlcrkindic","text":"Annual geometric means additional water quality data available wbid, JEI combination. Florida trophic state index values also estimated data available. Nitrogen ratios estimated JEIs cover source (upstream, freshwater) tidal (downstream) WBIDs, defined ratio concentrations two (.e., ratios > 1 mean source higher concentrations). Nitrogen ratios given year reflect ratio median nitrogen concentrations measured source tidal segment day. Note ratio one can obtained source tidal segments minimum detection. Indicators years 10% observations exceed saturation criteria also estimated. do_bnml do_prop columns show 1 0 given year indicate ten percent observations percent saturation 42. first column based binomial probability exceedance takes account number observations year second column based simple proportional estimate raw data. radar = TRUE, output returned format use show_tdlcrkradar Specifically, results calculated percentage years indicator exceeds relevant threshold. applies marine WBIDs tidal creeks (Florida DEP class 2, 3M). Six indicators returned percentage exceedances based total nitrogen (tn_ind) greater 1.1 mg/L, chlorophyll (chla_ind) greater 11 ug/L, trophic state index (tsi_ind) greater 55 (100), nitrate/nitrite ratio marine upstream segments (nox_ind) greater one, chlorophyll total nitrogen ratios > 15, percentage years ten percent observations percent saturation 42.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_tdlcrkindic.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Analyze tidal creek water quality indicators — anlz_tdlcrkindic","text":"","code":"dat <- anlz_tdlcrkindic(tidalcreeks, iwrraw, yr = 2023) head(dat) #> id name JEI wbid class year CHLAC COLOR COND DO DOSAT #> 1 2 Rock Creek CC01 2052 3M 2014 2.380249 14.69473 NA 3.308289 60.31523 #> 2 2 Rock Creek CC01 2052 3M 2015 2.647817 21.91113 NA 4.034172 55.41609 #> 3 2 Rock Creek CC01 2052 3M 2016 2.265462 19.13080 NA 3.980251 55.96637 #> 4 2 Rock Creek CC01 2052 3M 2017 2.851726 15.39576 NA 4.157777 60.18017 #> 5 2 Rock Creek CC01 2052 3M 2018 1.934899 11.65500 NA 4.219790 63.32630 #> 6 2 Rock Creek CC01 2052 3M 2019 2.071003 7.21425 NA 3.015847 44.90322 #> NO23 ORGN SALIN TKN TN TP TSS TURB #> 1 0.007575792 NA 26.63714 0.6161702 0.6228782 0.06938150 NA 2.044623 #> 2 0.009361504 NA 19.10494 0.6465161 0.5678241 0.07602770 NA 1.814818 #> 3 0.008532522 NA 25.84531 0.5813818 0.5408161 0.08330509 NA 2.082253 #> 4 0.007447260 NA 24.86909 0.6255197 0.6326848 0.07566682 NA 1.802161 #> 5 0.006994714 NA 31.32419 0.5668727 0.5734574 0.07432007 NA 2.454007 #> 6 0.007047106 NA 31.63214 0.5053022 0.4577485 0.06300538 NA 1.831953 #> chla_tn_ratio tn_tp_ratio chla_tsi tn_tsi tn2_tsi tp_tsi tp2_tsi #> 1 3.821371 8.977584 29.28775 46.62660 49.42526 60.45694 76.25504 #> 2 4.663093 7.468648 30.82179 44.79432 47.43600 62.15842 78.41391 #> 3 4.188970 6.491994 28.57601 43.82942 46.38844 63.85868 80.57123 #> 4 4.507341 8.361456 31.89011 46.93590 49.76107 62.06992 78.30162 #> 5 3.374095 7.716050 26.30480 44.98978 47.64821 61.73589 77.87779 #> 6 4.524324 7.265229 27.28367 40.52758 42.80384 58.66389 73.97999 #> nut_tsi tsi no23_source no23_tidal no23_ratio do_bnml do_prop #> 1 49.42526 39.35651 NA NA NA 0 1 #> 2 47.43600 39.12890 NA NA NA 0 1 #> 3 46.38844 37.48223 NA NA NA 0 1 #> 4 49.76107 40.82559 NA NA NA 0 0 #> 5 47.64821 36.97650 NA NA NA 0 1 #> 6 42.80384 35.04375 NA NA NA 1 1"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_transectave.html","id":null,"dir":"Reference","previous_headings":"","what":"Get annual averages of seagrass frequency occurrence by bay segments and year — anlz_transectave","title":"Get annual averages of seagrass frequency occurrence by bay segments and year — anlz_transectave","text":"Get annual averages seagrass frequency occurrence bay segments year","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_transectave.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get annual averages of seagrass frequency occurrence by bay segments and year — anlz_transectave","text":"","code":"anlz_transectave( transectocc, bay_segment = c(\"OTB\", \"HB\", \"MTB\", \"LTB\", \"BCB\"), total = TRUE, yrrng = c(1998, 2023), rev = FALSE )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_transectave.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get annual averages of seagrass frequency occurrence by bay segments and year — anlz_transectave","text":"transectocc data frame returned anlz_transectocc bay_segment chr string bay segment, one many \"OTB\", \"HB\", \"MTB\", \"LTB\", \"BCB\" total logical indicating average frequency occurrence calculated entire bay across segments yrrng numeric indicating year ranges evaluate rev logical factor levels bay segments reversed","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_transectave.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get annual averages of seagrass frequency occurrence by bay segments and year — anlz_transectave","text":"data frame annual averages bay segment","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_transectave.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Get annual averages of seagrass frequency occurrence by bay segments and year — anlz_transectave","text":"focat column returned results shows color category based arbitrary breaks frequency occurrence estimates (foest) 25, 50, 75 percent. necessarily translate ecological breakpoints.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_transectave.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get annual averages of seagrass frequency occurrence by bay segments and year — anlz_transectave","text":"","code":"if (FALSE) { transect <- read_transect() } transectocc <- anlz_transectocc(transect) anlz_transectave(transectocc) #> # A tibble: 156 × 4 #> # Groups: bay_segment [6] #> bay_segment yr foest focat #> #> 1 Tampa Bay 1998 58.0 #E9C318 #> 2 OTB 1998 65.5 #E9C318 #> 3 HB 1998 15.0 #CC3231 #> 4 MTB 1998 53.7 #E9C318 #> 5 LTB 1998 80.8 #2DC938 #> 6 BCB 1998 81.0 #2DC938 #> 7 Tampa Bay 1999 51.5 #E9C318 #> 8 OTB 1999 64.7 #E9C318 #> 9 HB 1999 10.1 #CC3231 #> 10 MTB 1999 51.8 #E9C318 #> # ℹ 146 more rows"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_transectavespp.html","id":null,"dir":"Reference","previous_headings":"","what":"Get annual averages of seagrass frequency occurrence by bay segments, year, and species — anlz_transectavespp","title":"Get annual averages of seagrass frequency occurrence by bay segments, year, and species — anlz_transectavespp","text":"Get annual averages seagrass frequency occurrence bay segments, year, species","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_transectavespp.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get annual averages of seagrass frequency occurrence by bay segments, year, and species — anlz_transectavespp","text":"","code":"anlz_transectavespp( transectocc, bay_segment = c(\"OTB\", \"HB\", \"MTB\", \"LTB\", \"BCB\"), yrrng = c(1998, 2023), species = c(\"Halodule\", \"Syringodium\", \"Thalassia\", \"Ruppia\", \"Halophila\", \"Caulerpa\", \"Dapis\"), total = TRUE, by_seg = FALSE )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_transectavespp.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get annual averages of seagrass frequency occurrence by bay segments, year, and species — anlz_transectavespp","text":"transectocc data frame returned anlz_transectocc bay_segment chr string bay segment, one many \"OTB\", \"HB\", \"MTB\", \"LTB\", \"BCB\" yrrng numeric indicating year ranges evaluate species chr string species summarize, one many \"Halodule\", \"Syringodium\", \"Thalassia\", \"Ruppia\", \"Halophila\", \"Caulerpa\", \"Dapis\" total logical indicating total frequency occurrence species also returned by_seg logical indicating separate results bay segments retained","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_transectavespp.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get annual averages of seagrass frequency occurrence by bay segments, year, and species — anlz_transectavespp","text":"data frame annual averages bay segment","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_transectavespp.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Get annual averages of seagrass frequency occurrence by bay segments, year, and species — anlz_transectavespp","text":"Frequency occurrence estimates averaged across segments bay_segment by_seg = F, .e., separate results location returned. Results retained bay segment by_seg = T. Also note totals across species (total = T) returned by_seg = T.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_transectavespp.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get annual averages of seagrass frequency occurrence by bay segments, year, and species — anlz_transectavespp","text":"","code":"if (FALSE) { transect <- read_transect() } transectocc <- anlz_transectocc(transect) anlz_transectavespp(transectocc) #> # A tibble: 208 × 3 #> yr Savspecies foest #> #> 1 1998 Caulerpa 0.0166 #> 2 1998 Dapis 0 #> 3 1998 Halodule 0.361 #> 4 1998 Halophila 0 #> 5 1998 Ruppia 0.0112 #> 6 1998 Syringodium 0.0451 #> 7 1998 Thalassia 0.254 #> 8 1998 total 0.580 #> 9 1999 Caulerpa 0.0277 #> 10 1999 Dapis 0 #> # ℹ 198 more rows"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_transectocc.html","id":null,"dir":"Reference","previous_headings":"","what":"Get seagrass average abundance and occurrence across transects — anlz_transectocc","title":"Get seagrass average abundance and occurrence across transects — anlz_transectocc","text":"Get seagrass average abundance occurrence across transects","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_transectocc.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get seagrass average abundance and occurrence across transects — anlz_transectocc","text":"","code":"anlz_transectocc(transect)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_transectocc.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get seagrass average abundance and occurrence across transects — anlz_transectocc","text":"transect data frame returned read_transect","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_transectocc.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get seagrass average abundance and occurrence across transects — anlz_transectocc","text":"data frame abundance frequency occurrence estimates aggregated species, transect, date. nsites column total number placements sampled along transect particular date.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_transectocc.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Get seagrass average abundance and occurrence across transects — anlz_transectocc","text":"Abundance frequency occurrence estimated Sherwood et al. 2017, equations 1 2. short, frequency occurrence estimated number instances species observed along transect divided number placements along transect average abundance estimated sum species-specific Braun-Blanquet scores divided number placements along transect. estimates obtained seagrass species including Caulerpa (attached macroalgae) Dapis (cyanobacteria), whereas attached drift algae species aggregated. Drift attached macroalgae cyanobacteria (Dapis) estimates may accurate prior 2021.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_transectocc.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Get seagrass average abundance and occurrence across transects — anlz_transectocc","text":"Sherwood, E.T., Greening, H.S., Johansson, J.O.R., Kaufman, K., Raulerson, G.E. 2017. Tampa Bay (Florida, USA): Documenting seagrass recovery since 1980's reviewing benefits. Southeastern Geographer. 57(3):294-319.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_transectocc.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get seagrass average abundance and occurrence across transects — anlz_transectocc","text":"","code":"if (FALSE) { transect <- read_transect() } anlz_transectocc(transect) #> # A tibble: 37,625 × 6 #> # Groups: Date, Transect [1,505] #> Date Transect Savspecies nsites foest bbest #> #> 1 1997-10-11 S2T3 \"AA\" 41 0 0 #> 2 1997-10-11 S2T3 \"Caulerpa\" 41 0 0 #> 3 1997-10-11 S2T3 \"DA\" 41 0 0 #> 4 1997-10-11 S2T3 \"DB: Dictyota\\r\\n\" 41 0 0 #> 5 1997-10-11 S2T3 \"DB: Drift Brown\\r\\n\" 41 0 0 #> 6 1997-10-11 S2T3 \"DG: Chaetomorpha\\r\\n\" 41 0 0 #> 7 1997-10-11 S2T3 \"DG: Drift Green\" 41 0 0 #> 8 1997-10-11 S2T3 \"DG: Ulva\" 41 0 0 #> 9 1997-10-11 S2T3 \"DG: Ulva fasciata\\r\\n\" 41 0 0 #> 10 1997-10-11 S2T3 \"DR: Acanthophora\" 41 0 0 #> # ℹ 37,615 more rows"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_yrattain.html","id":null,"dir":"Reference","previous_headings":"","what":"Get attainment categories for a chosen year — anlz_yrattain","title":"Get attainment categories for a chosen year — anlz_yrattain","text":"Get attainment categories chosen year","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_yrattain.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get attainment categories for a chosen year — anlz_yrattain","text":"","code":"anlz_yrattain(epcdata, yrsel, partialyr = FALSE)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_yrattain.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get attainment categories for a chosen year — anlz_yrattain","text":"epcdata data frame epc data returned read_importwq yrsel numeric indicating chosen year partialyr logical indicating incomplete annual data recent year approximated five year monthly averages parameter","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_yrattain.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get attainment categories for a chosen year — anlz_yrattain","text":"data.frame chosen year bay segments showing bay segment averages chloropyll concentration, light attenuations, segment targets, attainment categories.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/anlz_yrattain.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get attainment categories for a chosen year — anlz_yrattain","text":"","code":"# defaults to current year anlz_yrattain(epcdata, yrsel = 2023) #> # A tibble: 4 × 6 #> bay_segment chla_val chla_target la_val la_target outcome #> #> 1 OTB 6.21 8.5 0.734 0.83 green #> 2 HB 6.93 13.2 0.791 1.58 green #> 3 MTB 3.68 7.4 0.472 0.83 green #> 4 LTB 2.60 4.6 0.536 0.63 green"},{"path":"https://tbep-tech.github.io/tbeptools/reference/benthicdata.html","id":null,"dir":"Reference","previous_headings":"","what":"Benthic data for the Tampa Bay Benthic Index current as of 03132024 — benthicdata","title":"Benthic data for the Tampa Bay Benthic Index current as of 03132024 — benthicdata","text":"Benthic data Tampa Bay Benthic Index current 03132024","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/benthicdata.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Benthic data for the Tampa Bay Benthic Index current as of 03132024 — benthicdata","text":"","code":"benthicdata"},{"path":"https://tbep-tech.github.io/tbeptools/reference/benthicdata.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Benthic data for the Tampa Bay Benthic Index current as of 03132024 — benthicdata","text":"nested tibble 3 rows 2 variables: name chr identifying dataset stations, fieldsamples, taxacounts value list dataframes dataset","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/benthicdata.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Benthic data for the Tampa Bay Benthic Index current as of 03132024 — benthicdata","text":"Index corresponding list element value column view dataset. example, stations data first row can viewed benthicdata$value[[1]].","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/benthicdata.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Benthic data for the Tampa Bay Benthic Index current as of 03132024 — benthicdata","text":"","code":"if (FALSE) { # location to download data path <- '~/Desktop/benthic.zip' # load and assign to object benthicdata <- read_importbenthic(path, download_latest = TRUE, remove = TRUE) save(benthicdata, file = 'data/benthicdata.RData', compress = 'xz') }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/bsmap.html","id":null,"dir":"Reference","previous_headings":"","what":"Terrain basemap — bsmap","title":"Terrain basemap — bsmap","text":"Terrain basemap","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/bsmap.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Terrain basemap — bsmap","text":"","code":"bsmap"},{"path":"https://tbep-tech.github.io/tbeptools/reference/bsmap.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Terrain basemap — bsmap","text":"ggmap object","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/epcdata.html","id":null,"dir":"Reference","previous_headings":"","what":"All bay data as of 20240201 — epcdata","title":"All bay data as of 20240201 — epcdata","text":"bay data 20240201","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/epcdata.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"All bay data as of 20240201 — epcdata","text":"","code":"epcdata"},{"path":"https://tbep-tech.github.io/tbeptools/reference/epcdata.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"All bay data as of 20240201 — epcdata","text":"data frame 27961 rows 26 variables: bay_segment chr epchc_station num SampleTime POSIXct yr num mo num Latitude num Longitude num Total_Depth_m num Sample_Depth_m num tn num tn_q chr sd_m num sd_raw_m num sd_q chr chla num chla_q chr Sal_Top_ppth num Sal_Mid_ppth num Sal_Bottom_ppth num Temp_Water_Top_degC num Temp_Water_Mid_degC num Temp_Water_Bottom_degC num Turbidity_JTU-NTU num Turbidity_Q num Color_345_F45_PCU num Color_345_F45_Q num","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/epcdata.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"All bay data as of 20240201 — epcdata","text":"","code":"if (FALSE) { xlsx <- '~/Desktop/epcdata.xlsx' epcdata <- read_importwq(xlsx, download_latest = TRUE) nrow(epcdata) ncol(epcdata) save(epcdata, file = 'data/epcdata.RData', compress = 'xz') }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/fibdata.html","id":null,"dir":"Reference","previous_headings":"","what":"All Fecal Indicator Bacteria (FIB) data as of 20240320 — fibdata","title":"All Fecal Indicator Bacteria (FIB) data as of 20240320 — fibdata","text":"Fecal Indicator Bacteria (FIB) data 20240320","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/fibdata.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"All Fecal Indicator Bacteria (FIB) data as of 20240320 — fibdata","text":"","code":"fibdata"},{"path":"https://tbep-tech.github.io/tbeptools/reference/fibdata.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"All Fecal Indicator Bacteria (FIB) data as of 20240320 — fibdata","text":"data frame 76502 rows 18 variables: area chr epchc_station num class chr SampleTime POSIXct yr num mo num Latitude num Longitude num Total_Depth_m num Sample_Depth_m num ecoli num ecoli_q chr ecocci num ecocci_q chr fcolif num fcolif_q chr totcol num totcol_q chr","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/fibdata.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"All Fecal Indicator Bacteria (FIB) data as of 20240320 — fibdata","text":"","code":"if (FALSE) { xlsx <- tempfile(fileext = '.xlsx') fibdata <- read_importfib(xlsx, download_latest = TRUE) nrow(fibdata) ncol(fibdata) save(fibdata, file = 'data/fibdata.RData', compress = 'xz') file.remove(xlsx) }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/fimdata.html","id":null,"dir":"Reference","previous_headings":"","what":"FIM data for Tampa Bay Nekton Index current as of 08232023 — fimdata","title":"FIM data for Tampa Bay Nekton Index current as of 08232023 — fimdata","text":"FIM data Tampa Bay Nekton Index current 08232023","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/fimdata.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"FIM data for Tampa Bay Nekton Index current as of 08232023 — fimdata","text":"","code":"fimdata"},{"path":"https://tbep-tech.github.io/tbeptools/reference/fimdata.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"FIM data for Tampa Bay Nekton Index current as of 08232023 — fimdata","text":"data frame 49874 rows 19 variables: Reference chr Sampling_Date Date Latitude num Longitude num Zone chr Grid int NODCCODE chr Year num Month num Total_N num ScientificName chr Include_TB_Index chr Hab_Cat chr Est_Cat chr Est_Use chr Feeding_Cat chr Feeding_Guild chr Selected_Taxa chr bay_segment chr","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/fimdata.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"FIM data for Tampa Bay Nekton Index current as of 08232023 — fimdata","text":"","code":"if (FALSE) { csv <- '~/Desktop/fimdata.csv' fimdata <- read_importfim(csv, download_latest = TRUE) save(fimdata, file = 'data/fimdata.RData', compress = 'xz') }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/fimstations.html","id":null,"dir":"Reference","previous_headings":"","what":"Spatial data object of FIM stations including Tampa Bay segments — fimstations","title":"Spatial data object of FIM stations including Tampa Bay segments — fimstations","text":"Spatial data object FIM stations including Tampa Bay segments","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/fimstations.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Spatial data object of FIM stations including Tampa Bay segments — fimstations","text":"","code":"fimstations"},{"path":"https://tbep-tech.github.io/tbeptools/reference/fimstations.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Spatial data object of FIM stations including Tampa Bay segments — fimstations","text":"simple features sf object (POINT) 7450 features 2 fields, +proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs Reference num bay_segment chr","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/fimstations.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Spatial data object of FIM stations including Tampa Bay segments — fimstations","text":"","code":"if (FALSE) { # file path csv <- '~/Desktop/fimraw.csv' # load and assign to object fimstations <- read_importfim(csv, download_latest = TRUE, locs = TRUE) save(fimstations, file = 'data/fimstations.RData', compress = 'xz') }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/hmptrgs.html","id":null,"dir":"Reference","previous_headings":"","what":"Habitat Master Plan targets and goals — hmptrgs","title":"Habitat Master Plan targets and goals — hmptrgs","text":"Habitat Master Plan targets goals","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/hmptrgs.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Habitat Master Plan targets and goals — hmptrgs","text":"","code":"hmptrgs"},{"path":"https://tbep-tech.github.io/tbeptools/reference/hmptrgs.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Habitat Master Plan targets and goals — hmptrgs","text":"data frame showing 2030 targets 2050 goals","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/hmptrgs.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Habitat Master Plan targets and goals — hmptrgs","text":"","code":"if (FALSE) { library(dplyr) load(url(\"https://github.com/tbep-tech/hmpu-workflow/raw/master/data/trgs.RData\")) hmptrgs <- trgs %>% rename(Goal2050 = Target2050) save(hmptrgs, file = 'data/hmptrgs.RData', compress = 'xz') }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/iwrraw.html","id":null,"dir":"Reference","previous_headings":"","what":"FDEP IWR run 65 — iwrraw","title":"FDEP IWR run 65 — iwrraw","text":"Florida Department Environmental Protection, Impaired Waters Rule, Run 65","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/iwrraw.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"FDEP IWR run 65 — iwrraw","text":"","code":"iwrraw"},{"path":"https://tbep-tech.github.io/tbeptools/reference/iwrraw.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"FDEP IWR run 65 — iwrraw","text":"data frame 537946 rows 11 variables","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/iwrraw.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"FDEP IWR run 65 — iwrraw","text":"File created using workflow , example old Run 61.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/iwrraw.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"FDEP IWR run 65 — iwrraw","text":"","code":"if (FALSE) { library(dplyr) load(file = '../../02_DOCUMENTS/tidal_creeks/iwrraw_run61.RData') iwrraw <- sf::st_set_geometry(iwrraw, NULL) %>% rename(JEI = jei) save(iwrraw, file = 'data/iwrraw.RData', compress = 'xz') }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/phytodata.html","id":null,"dir":"Reference","previous_headings":"","what":"Phytoplankton data current as of 03202024 — phytodata","title":"Phytoplankton data current as of 03202024 — phytodata","text":"Phytoplankton data current 03202024","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/phytodata.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Phytoplankton data current as of 03202024 — phytodata","text":"","code":"phytodata"},{"path":"https://tbep-tech.github.io/tbeptools/reference/phytodata.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Phytoplankton data current as of 03202024 — phytodata","text":"nested tibble 21143 rows 8 variables: epchc_station chr Date Date name chr units chr count num yrqrt Date yr num mo Ord.factor","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/phytodata.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Phytoplankton data current as of 03202024 — phytodata","text":"","code":"if (FALSE) { # location to download data path <- tempfile(fileext = '.xlsx') # load and assign to object phytodata <- read_importphyto(path, download_latest = TRUE) nrow(phytodata) ncol(phytodata) save(phytodata, file = 'data/phytodata.RData', compress = 'xz') file.remove(path) }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_dlcurrent.html","id":null,"dir":"Reference","previous_headings":"","what":"Download latest file from epchc.org — read_dlcurrent","title":"Download latest file from epchc.org — read_dlcurrent","text":"Download latest file epchc.org","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_dlcurrent.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Download latest file from epchc.org — read_dlcurrent","text":"","code":"read_dlcurrent(locin, download_latest = TRUE, urlin)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_dlcurrent.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Download latest file from epchc.org — read_dlcurrent","text":"locin chr string path local file, overwrite current download_latest logical download latest file regardless local copy urlin url file location","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_dlcurrent.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Download latest file from epchc.org — read_dlcurrent","text":"local copy specified path locin overwritten new file current download_latest = TRUE. function nothing download_latest = FALSE.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_dlcurrent.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Download latest file from epchc.org — read_dlcurrent","text":"local copy checked temporary file downloaded location specified urlin. local file replaced downloaded file MD5 hashes different.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_dlcurrent.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Download latest file from epchc.org — read_dlcurrent","text":"","code":"if (FALSE) { locin <- '~/Desktop/RWMDataSpreadsheet_ThroughCurrentReportMonth.xlsx' urlin1 <- 'https://epcbocc.sharepoint.com/:x:/s/Share/' urlin2 <- 'EYXZ5t16UlFGk1rzIU91VogBa8U37lh8z_Hftf2KJISSHg?e=8r1SUL' urlin <- paste0(urlin1, urlin2, '&download=1') read_dlcurrent(locin = locin, urlin = urlin) }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formbenthic.html","id":null,"dir":"Reference","previous_headings":"","what":"Format benthic data for the Tampa Bay Benthic Index — read_formbenthic","title":"Format benthic data for the Tampa Bay Benthic Index — read_formbenthic","text":"Format benthic data Tampa Bay Benthic Index","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formbenthic.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Format benthic data for the Tampa Bay Benthic Index — read_formbenthic","text":"","code":"read_formbenthic(pathin)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formbenthic.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Format benthic data for the Tampa Bay Benthic Index — read_formbenthic","text":"pathin path unzipped csv files base tables used calculate benthic index","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formbenthic.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Format benthic data for the Tampa Bay Benthic Index — read_formbenthic","text":"nested tibble station, field sample, taxa data","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formbenthic.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Format benthic data for the Tampa Bay Benthic Index — read_formbenthic","text":"Function used internally within read_importbenthic","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formbenthic.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Format benthic data for the Tampa Bay Benthic Index — read_formbenthic","text":"","code":"if (FALSE) { # location to download data path <- '~/Desktop/benthic.zip' # download urlin1 <- 'https://epcbocc.sharepoint.com/:x:/s/Share/' urlin2 <- 'EQUCWBuwCNdGuMREYAyAD1gBKC98mYtCHMWX0FYLrbT4KA?e=nDfnnQ' urlin <- paste0(urlin1, urlin2, '&download=1') read_dlcurrent(path, download_latest = TRUE, urlin = urlin) # unzip tmppth <- tempfile() utils::unzip(path, exdir = tmppth, overwrite = TRUE) # format benthic data read_formbenthic(pathin = tmppth) # remove temporary path unlink(tmppth, recursive = TRUE) }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formfib.html","id":null,"dir":"Reference","previous_headings":"","what":"Format Fecal Indicator Bacteria (FIB) data — read_formfib","title":"Format Fecal Indicator Bacteria (FIB) data — read_formfib","text":"Format Fecal Indicator Bacteria (FIB) data","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formfib.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Format Fecal Indicator Bacteria (FIB) data — read_formfib","text":"","code":"read_formfib(datin, all = FALSE)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formfib.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Format Fecal Indicator Bacteria (FIB) data — read_formfib","text":"datin input data.frame loaded read_importepc logical indicating stations FIB data returned, default FALSE","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formfib.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Format Fecal Indicator Bacteria (FIB) data — read_formfib","text":"lightly formatted data.frame FIB data","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formfib.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Format Fecal Indicator Bacteria (FIB) data — read_formfib","text":"Formats input data read_importepc appropriate FIB results, see details read_importfib information.","code":""},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formfib.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Format Fecal Indicator Bacteria (FIB) data — read_formfib","text":"","code":"if (FALSE) { # file path xlsx <- '~/Desktop/RWMDataSpreadsheet_ThroughCurrentReportMonth.xlsx' # load raw data and assign to object epcall <- read_importepc(xlsx, download_latest = T) # final formatting fibdata <- read_formfib(epcall) }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formfim.html","id":null,"dir":"Reference","previous_headings":"","what":"Format FIM data for the Tampa Bay Nekton Index — read_formfim","title":"Format FIM data for the Tampa Bay Nekton Index — read_formfim","text":"Format FIM data Tampa Bay Nekton Index","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formfim.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Format FIM data for the Tampa Bay Nekton Index — read_formfim","text":"","code":"read_formfim(datin, locs = FALSE)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formfim.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Format FIM data for the Tampa Bay Nekton Index — read_formfim","text":"datin input data.frame loaded read_importfim locs logical indicating spatial features object returned locations FIM sampling station","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formfim.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Format FIM data for the Tampa Bay Nekton Index — read_formfim","text":"formatted data.frame FIM data locs = FALSE, otherwise simple features object locs = TRUE","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formfim.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Format FIM data for the Tampa Bay Nekton Index — read_formfim","text":"Function used internally within read_importfim","code":""},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formfim.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Format FIM data for the Tampa Bay Nekton Index — read_formfim","text":"","code":"if (FALSE) { # file path csv <- '~/Desktop/fimraw.csv' # load and assign to object fimdata <- read_importfim(csv) }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formphyto.html","id":null,"dir":"Reference","previous_headings":"","what":"Format phytoplankton data — read_formphyto","title":"Format phytoplankton data — read_formphyto","text":"Format phytoplankton data","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formphyto.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Format phytoplankton data — read_formphyto","text":"","code":"read_formphyto(datin)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formphyto.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Format phytoplankton data — read_formphyto","text":"datin input data.frame loaded read_importphyto","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formphyto.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Format phytoplankton data — read_formphyto","text":"formatted data.frame phytoplankton count data","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formphyto.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Format phytoplankton data — read_formphyto","text":"seven taxonomic groups summarized. Pyrodinium bahamense, Karenia brevis, Tripos hircus, Pseudo-nitzschia sp., Pseudo-nitzschia pungens retained species level. Bacillariophyta Cyanobacteria retained phylum level. taxa grouped \"\" category.","code":""},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formphyto.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Format phytoplankton data — read_formphyto","text":"","code":"if (FALSE) { # file path xlsx <- '~/Desktop/phyto_data.xlsx' # load and assign to object phytodata <- read_importphyto(xlsx) }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formsediment.html","id":null,"dir":"Reference","previous_headings":"","what":"Format sediment data — read_formsediment","title":"Format sediment data — read_formsediment","text":"Format sediment data","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formsediment.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Format sediment data — read_formsediment","text":"","code":"read_formsediment(pathin)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formsediment.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Format sediment data — read_formsediment","text":"pathin path unzipped csv files sediment result tables","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formsediment.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Format sediment data — read_formsediment","text":"data.frame sediment data Tampa Bay","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formsediment.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Format sediment data — read_formsediment","text":"Function used internally within read_importsediment","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formsediment.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Format sediment data — read_formsediment","text":"","code":"if (FALSE) { # location to download data path <- '~/Desktop/sediment.zip' # download urlin1 <- 'https://epcbocc.sharepoint.com/:x:/s/Share/' urlin2 <- 'Ef9utuKCHD9LliarsOPKCJwB5kxgCObf0tY5x5wX20JQUA?e=DuTseb' urlin <- paste0(urlin1, urlin2, '&download=1') read_dlcurrent(path, download_latest = TRUE, urlin = urlin) # unzip tmppth <- tempfile() utils::unzip(path, exdir = tmppth, overwrite = TRUE) # format sediment data read_formsediment(pathin = tmppth) # remove temporary path unlink(tmppth, recursive = TRUE) }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formtransect.html","id":null,"dir":"Reference","previous_headings":"","what":"Format seagrass transect data from Water Atlas — read_formtransect","title":"Format seagrass transect data from Water Atlas — read_formtransect","text":"Format seagrass transect data Water Atlas","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formtransect.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Format seagrass transect data from Water Atlas — read_formtransect","text":"","code":"read_formtransect(jsn, training = FALSE, raw = FALSE)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formtransect.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Format seagrass transect data from Water Atlas — read_formtransect","text":"jsn data frame returned fromJSON training logical input transect training data complete database raw logical indicating raw, unformatted data returned, see details","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formtransect.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Format seagrass transect data from Water Atlas — read_formtransect","text":"data frame long format","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formtransect.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Format seagrass transect data from Water Atlas — read_formtransect","text":"Shoot density reported number shoots per square meter corrected quadrat size entered raw data. Shoot density blade height (cm) based averages across random observations transect point entered separately data form. Abundance reported numeric value 0 - 5 Braun-Blanquet coverage estimates. raw = TRUE, unformatted data returned. default use formatting allows raw data used downstream functions. raw data may extra information may use outside plotting functions package.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formtransect.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Format seagrass transect data from Water Atlas — read_formtransect","text":"","code":"library(jsonlite) if (FALSE) { # all transect data url <- 'http://dev.seagrass.wateratlas.usf.edu/api/assessments/all__use-with-care' jsn <- fromJSON(url) trndat <- read_formtransect(jsn) } # training transect data url <- 'http://dev.seagrass.wateratlas.usf.edu/api/assessments/training' jsn <- fromJSON(url) trndat <- read_formtransect(jsn, training = TRUE)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formwq.html","id":null,"dir":"Reference","previous_headings":"","what":"Format water quality data — read_formwq","title":"Format water quality data — read_formwq","text":"Format water quality data","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formwq.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Format water quality data — read_formwq","text":"","code":"read_formwq(datin, all = FALSE)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formwq.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Format water quality data — read_formwq","text":"datin input data.frame loaded read_importepc logical indicating water quality parameters returned, see details","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formwq.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Format water quality data — read_formwq","text":"lightly formatted data.frame chloropyll secchi observations","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formwq.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Format water quality data — read_formwq","text":"Secchi data VOB depths secchis < 0.5 ft bottom assigned NA, function used internally within read_importwq","code":""},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formwq.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Format water quality data — read_formwq","text":"","code":"if (FALSE) { # file path xlsx <- '~/Desktop/RWMDataSpreadsheet_ThroughCurrentReportMonth.xlsx' # load raw data and assign to object epcall <- read_importepc(xlsx, download_latest = T) # final formatting epcdata <- read_formwq(epcall) }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formwqp.html","id":null,"dir":"Reference","previous_headings":"","what":"Format data and station metadata from the Water Quality Portal — read_formwqp","title":"Format data and station metadata from the Water Quality Portal — read_formwqp","text":"Format data station metadata Water Quality Portal","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formwqp.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Format data and station metadata from the Water Quality Portal — read_formwqp","text":"","code":"read_formwqp(res, sta, org, type, trace = F)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formwqp.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Format data and station metadata from the Water Quality Portal — read_formwqp","text":"res data frame containing results obtained API sta data frame containing station metadata obtained API org chr string indicating organization identifier type chr string indicating data type download, one \"wq\" \"fib\" trace Logical indicating whether display progress messages, default FALSE","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formwqp.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Format data and station metadata from the Water Quality Portal — read_formwqp","text":"data frame containing formatted water quality station metadata","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formwqp.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Format data and station metadata from the Water Quality Portal — read_formwqp","text":"function used read_importwqp combine, format, process data (res) station metadata (sta) obtained Water Quality Portal selected county data type. resulting data frame includes date, time, station identifier, latitude, longitude, variable name, value, unit, quality flag.","code":""},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_formwqp.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Format data and station metadata from the Water Quality Portal — read_formwqp","text":"","code":"if (FALSE) { url <- list( Result = \"https://www.waterqualitydata.us/data/Result/search?mimeType=csv&zip=no\", Station = \"https://www.waterqualitydata.us/data/Station/search?mimeType=csv&zip=no\" ) headers <- c( \"Content-Type\" = \"application/json\", \"Accept\" = \"application/zip\" ) body <- list( organization = c(\"21FLMANA_WQX\"), sampleMedia = c(\"Water\"), characteristicType = c(\"Information\", \"Nutrient\", \"Biological, Algae, Phytoplankton, Photosynthetic Pigments\"), providers = c(\"STORET\"), siteType = c(\"Estuary\") ) res <- url[['Result']] %>% httr::POST(httr::add_headers(headers), body = jsonlite::toJSON(body)) %>% httr::content('text') %>% read.csv(text = .) sta <- url[['Station']] %>% httr::POST(httr::add_headers(headers), body = jsonlite::toJSON(body)) %>% httr::content('text') %>% read.csv(text = .) # combine and format read_formwqp(res, sta, '21FLMANA_WQX', type = 'wq') }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importbenthic.html","id":null,"dir":"Reference","previous_headings":"","what":"Download and import benthic data for Tampa Bay — read_importbenthic","title":"Download and import benthic data for Tampa Bay — read_importbenthic","text":"Download import benthic data Tampa Bay","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importbenthic.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Download and import benthic data for Tampa Bay — read_importbenthic","text":"","code":"read_importbenthic(path, download_latest = FALSE, remove = FALSE)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importbenthic.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Download and import benthic data for Tampa Bay — read_importbenthic","text":"path chr string local path zipped folder downloaded, must include .zip extension download_latest logical download latest recent dataset available remove logical downloaded folder removed unzipping","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importbenthic.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Download and import benthic data for Tampa Bay — read_importbenthic","text":"nested tibble station, taxa, field sample data.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importbenthic.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Download and import benthic data for Tampa Bay — read_importbenthic","text":"function downloads unzips folder base tables used calculate benthic index https://epcbocc.sharepoint.com/:u:/s/Share/EQUCWBuwCNdGuMREYAyAD1gBKC98mYtCHMWX0FYLrbT4KA?e=nDfnnQ&download=1 (viewable https://epcbocc.sharepoint.com/:f:/s/Share/EtOJfziTTa9FliL1oROb9OsBRZU-nO60fu_0NRC162hHjQ?e=4gUXgJ). Index corresponding list element value column view dataset. example, stations data first row can viewed benthicdata$value[[1]].","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importbenthic.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Download and import benthic data for Tampa Bay — read_importbenthic","text":"","code":"if (FALSE) { # location to download data path <- '~/Desktop/benthic.zip' # load and assign to object benthicdata <- read_importbenthic(path, download_latest = TRUE) }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importepc.html","id":null,"dir":"Reference","previous_headings":"","what":"Download and/or import local water quality file for internal use — read_importepc","title":"Download and/or import local water quality file for internal use — read_importepc","text":"Download /import local water quality file internal use","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importepc.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Download and/or import local water quality file for internal use — read_importepc","text":"","code":"read_importepc(xlsx, download_latest = FALSE, na = c(\"\", \"NULL\"))"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importepc.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Download and/or import local water quality file for internal use — read_importepc","text":"xlsx chr string path local excel file, overwrite current download_latest logical passed read_dlcurrent download raw data compare existing xlsx available na chr vector strings interpret NA, passed read_xlsx","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importepc.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Download and/or import local water quality file for internal use — read_importepc","text":"unformatted data.frame EPC","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importepc.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Download and/or import local water quality file for internal use — read_importepc","text":"Loads \"RWMDataSpreadsheet\" worksheet file located xlsx. file downloaded https://epcbocc.sharepoint.com/:x:/s/Share/EYXZ5t16UlFGk1rzIU91VogBa8U37lh8z_Hftf2KJISSHg?e=8r1SUL&download=1. files can viewed https://epcbocc.sharepoint.com/:f:/s/Share/EiypSSYdsEFCi84Sv_6-t7kBUYaXiIqN0B1n2w57Z_V3kQ?e=NdZQcU. function used internally read_importwq read_importfib use source data Environmental Protection Commission Hillsborough County.","code":""},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importepc.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Download and/or import local water quality file for internal use — read_importepc","text":"","code":"if (FALSE) { # file path xlsx <- '~/Desktop/RWMDataSpreadsheet_ThroughCurrentReportMonth.xlsx' # load and assign to object epcall <- read_importepc(xlsx, download_latest = T) }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importfib.html","id":null,"dir":"Reference","previous_headings":"","what":"Load local water quality file for Fecal Indicator Bacteria (FIB) — read_importfib","title":"Load local water quality file for Fecal Indicator Bacteria (FIB) — read_importfib","text":"Load local water quality file Fecal Indicator Bacteria (FIB)","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importfib.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Load local water quality file for Fecal Indicator Bacteria (FIB) — read_importfib","text":"","code":"read_importfib(xlsx, download_latest = FALSE, na = c(\"\", \"NULL\"), all = TRUE)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importfib.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Load local water quality file for Fecal Indicator Bacteria (FIB) — read_importfib","text":"xlsx chr string path local excel file, overwrite current download_latest logical passed read_dlcurrent download raw data compare existing xlsx available na chr vector strings interpret NA, passed read_xlsx logical indicating stations FIB data returned, default TRUE, see details","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importfib.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Load local water quality file for Fecal Indicator Bacteria (FIB) — read_importfib","text":"data.frame formatted FIB data.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importfib.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Load local water quality file for Fecal Indicator Bacteria (FIB) — read_importfib","text":"Loads \"RWMDataSpreadsheet\" worksheet file located xlsx. file downloaded https://epcbocc.sharepoint.com/:x:/s/Share/EYXZ5t16UlFGk1rzIU91VogBa8U37lh8z_Hftf2KJISSHg?e=8r1SUL&download=1. files can viewed https://epcbocc.sharepoint.com/:f:/s/Share/EiypSSYdsEFCi84Sv_6-t7kBUYaXiIqN0B1n2w57Z_V3kQ?e=NdZQcU. Returns FIB data including E. coli, Enterococcus, Fecal Coliform, Total Coliform concentrations waterbody class (freshwater 1 3F, marine 2 3M) stations sample dates, function used internally within read_importfib Values returned E. coli (ecoli), Enterococcus (ecocci), Fecal Coliform (fcolif), Total Coliform (totcol). Values shown # colonies per 100 mL water (#/100mL). Qualifier columns also returned _q suffix. Qualifier codes can interpreted source spreadsheet. Concentrations noted < > raw data reported , numeric value shown. Samples notation can determined qualifier columns. = FALSE, stations AreaName source data Hillsborough River, Hillsborough River Tributary, Alafia River, Alafia River Tributary, Lake Thonotosassa, Lake Thonotosassa Tributary, Lake Roberta.","code":""},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importfib.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Load local water quality file for Fecal Indicator Bacteria (FIB) — read_importfib","text":"","code":"if (FALSE) { # file path xlsx <- '~/Desktop/RWMDataSpreadsheet_ThroughCurrentReportMonth.xlsx' # load and assign to object fibdata <- read_importfib(xlsx, download_latest = T) }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importfim.html","id":null,"dir":"Reference","previous_headings":"","what":"Load local FIM data for the Tampa Bay Nekton Index — read_importfim","title":"Load local FIM data for the Tampa Bay Nekton Index — read_importfim","text":"Load local FIM data Tampa Bay Nekton Index","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importfim.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Load local FIM data for the Tampa Bay Nekton Index — read_importfim","text":"","code":"read_importfim(csv, download_latest = FALSE, locs = FALSE)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importfim.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Load local FIM data for the Tampa Bay Nekton Index — read_importfim","text":"csv chr string path local csv file, overwrite current download_latest logical passed read_dlcurrent download raw data compare existing csv available locs logical indicating spatial features object returned locations FIM sampling station","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importfim.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Load local FIM data for the Tampa Bay Nekton Index — read_importfim","text":"formatted data.frame FIM data locs = FALSE, otherwise simple features object locs = TRUE","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importfim.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Load local FIM data for the Tampa Bay Nekton Index — read_importfim","text":"Data downloaded ftp://ftp.floridamarine.org/users/fim/tmac/NektonIndex/TampaBay_NektonIndexData.csv.","code":""},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importfim.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Load local FIM data for the Tampa Bay Nekton Index — read_importfim","text":"","code":"if (FALSE) { # file path csv <- '~/Desktop/fimraw.csv' # load and assign to object fimdata <- read_importfim(csv, download_latest = TRUE) }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importphyto.html","id":null,"dir":"Reference","previous_headings":"","what":"Load local phytoplankton cell count file — read_importphyto","title":"Load local phytoplankton cell count file — read_importphyto","text":"Load local phytoplankton cell count file","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importphyto.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Load local phytoplankton cell count file — read_importphyto","text":"","code":"read_importphyto(xlsx, download_latest = FALSE, na = c(\"\", \"NULL\"))"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importphyto.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Load local phytoplankton cell count file — read_importphyto","text":"xlsx chr string path local excel file, overwrite current download_latest logical passed read_dlcurrent download raw data compare existing xlsx available na chr vector strings interpret NA, passed read_xlsx","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importphyto.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Load local phytoplankton cell count file — read_importphyto","text":"data.frame formatted water quality data.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importphyto.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Load local phytoplankton cell count file — read_importphyto","text":"Phytoplankton cell count data downloaded https://epcbocc.sharepoint.com/:x:/s/Share/ETAfRQ5drmRHntDd1O8s3FQB180Fumed4nQ99w-OIVDxrA?e=eSmtxD&download=1","code":""},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importphyto.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Load local phytoplankton cell count file — read_importphyto","text":"","code":"if (FALSE) { # file path xlsx <- '~/Desktop/phyto_data.xlsx' # load and assign to object phytodata <- read_importphyto(xlsx, download_latest = T) }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importsediment.html","id":null,"dir":"Reference","previous_headings":"","what":"Download and import sediment data for Tampa Bay — read_importsediment","title":"Download and import sediment data for Tampa Bay — read_importsediment","text":"Download import sediment data Tampa Bay","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importsediment.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Download and import sediment data for Tampa Bay — read_importsediment","text":"","code":"read_importsediment(path, download_latest = FALSE, remove = FALSE)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importsediment.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Download and import sediment data for Tampa Bay — read_importsediment","text":"path chr string local path zipped folder downloaded, must include .zip extension download_latest logical download latest recent dataset available remove logical downloaded folder removed unzipping","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importsediment.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Download and import sediment data for Tampa Bay — read_importsediment","text":"data.frame sediment data Tampa Bay","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importsediment.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Download and import sediment data for Tampa Bay — read_importsediment","text":"function downloads unzips folder results tables https://epcbocc.sharepoint.com/:u:/s/Share/Ef9utuKCHD9LliarsOPKCJwB5kxgCObf0tY5x5wX20JQUA?e=DuTseb&download=1 (viewable https://epcbocc.sharepoint.com/:f:/s/Share/EtOJfziTTa9FliL1oROb9OsBRZU-nO60fu_0NRC162hHjQ?e=4gUXgJ). row entries columns \"BetweenTELPEL\" \"ExceedsPEL\" rows \"Qualifier\" column \"U\" \"T\" (detection, detected) assigned NA, regardless entry source data.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importsediment.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Download and import sediment data for Tampa Bay — read_importsediment","text":"","code":"if (FALSE) { # location to download data path <- '~/Desktop/sediment.zip' # load and assign to object sedimentdata <- read_importsediment(path, download_latest = TRUE) }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importwq.html","id":null,"dir":"Reference","previous_headings":"","what":"Load local water quality file — read_importwq","title":"Load local water quality file — read_importwq","text":"Load local water quality file","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importwq.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Load local water quality file — read_importwq","text":"","code":"read_importwq(xlsx, download_latest = FALSE, na = c(\"\", \"NULL\"), all = FALSE)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importwq.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Load local water quality file — read_importwq","text":"xlsx chr string path local excel file, overwrite current download_latest logical passed read_dlcurrent download raw data compare existing xlsx available na chr vector strings interpret NA, passed read_xlsx logical indicating water quality parameters returned, see details","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importwq.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Load local water quality file — read_importwq","text":"data.frame formatted water quality data.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importwq.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Load local water quality file — read_importwq","text":"Loads \"RWMDataSpreadsheet\" worksheet file located xlsx. file downloaded https://epcbocc.sharepoint.com/:x:/s/Share/EYXZ5t16UlFGk1rzIU91VogBa8U37lh8z_Hftf2KJISSHg?e=8r1SUL&download=1. files can viewed https://epcbocc.sharepoint.com/:f:/s/Share/EiypSSYdsEFCi84Sv_6-t7kBUYaXiIqN0B1n2w57Z_V3kQ?e=NdZQcU. Water quality parameters returned default total nitrogen (tn), Secchi depth (sd), chlorophyll-(chla), salinity (top, mid, bottom depths, Sal_ prefix), water temperature (top, mid, bottom depths, Temp_Water_ prefix), turbidity (Turbidity_JTU-NTU), water color (Color_345_F45). Additional qualifier columns include _Q suffix also returned, excluding salinity water temperature. water quality parameters qualifiers can returned setting = T.","code":""},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importwq.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Load local water quality file — read_importwq","text":"","code":"if (FALSE) { # file path xlsx <- '~/Desktop/RWMDataSpreadsheet_ThroughCurrentReportMonth.xlsx' # load and assign to object epcdata <- read_importwq(xlsx, download_latest = T) # get all water quality parameters epcdataall <- read_importwq(xlsx, download_latest = T, all = T) }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importwqp.html","id":null,"dir":"Reference","previous_headings":"","what":"Import data from the Water Quality Portal — read_importwqp","title":"Import data from the Water Quality Portal — read_importwqp","text":"Import data Water Quality Portal","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importwqp.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Import data from the Water Quality Portal — read_importwqp","text":"","code":"read_importwqp(org, type, trace = F)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importwqp.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Import data from the Water Quality Portal — read_importwqp","text":"org chr string indicating organization identifier, see details type chr string indicating data type download, one \"wq\" \"fib\" trace logical indicating whether display progress messages, default FALSE","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importwqp.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Import data from the Water Quality Portal — read_importwqp","text":"data frame containing imported data selected county","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importwqp.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Import data from the Water Quality Portal — read_importwqp","text":"function retrieves data Water Quality Portal API (https://www.waterqualitydata.us/) selected counties around Tampa Bay watershed. type data returned defined type argument either \"wq\" \"fib\" water quality Fecal Indicator Bacteria data, respectively. org argument retrieves data specific organization. Valid entries org include \"21FLCOSP_WQX\" (City St. Petersburg), \"21FLDOH_WQX\" (Florida Department Health), \"21FLHILL_WQX\" (Hillsborough County), \"21FLMANA_WQX\" (Manatee County), \"21FLPASC_WQX\" (Pasco County), \"21FLPDEM_WQX\" (Pinellas County), \"21FLPOLK_WQX\" (Polk County), \"21FLTPA_WQX\" (Florida Department Environmental Protection, Southwest District). naming convention follows Organization ID Water Quality Portal. function fetches results station metadata, combines formats using read_formwqp function, returns processed data data frame. Parameters specific type argument.","code":""},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_importwqp.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Import data from the Water Quality Portal — read_importwqp","text":"","code":"if (FALSE) { # get Manatee County water quality data mancodata <- read_importwqp(org = '21FLMANA_WQX', type = 'wq', trace = T) # get Pinellas County FIB data pincodata <- read_importwqp(org = '21FLPDEM_WQX', type = 'fib', trace = T) }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_transect.html","id":null,"dir":"Reference","previous_headings":"","what":"Import JSON seagrass transect data from Water Atlas — read_transect","title":"Import JSON seagrass transect data from Water Atlas — read_transect","text":"Import JSON seagrass transect data Water Atlas","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_transect.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Import JSON seagrass transect data from Water Atlas — read_transect","text":"","code":"read_transect(training = FALSE, raw = FALSE)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_transect.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Import JSON seagrass transect data from Water Atlas — read_transect","text":"training logical training data imported complete database raw logical indicating raw, unformatted data returned, see details","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_transect.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Import JSON seagrass transect data from Water Atlas — read_transect","text":"data frame","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_transect.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Import JSON seagrass transect data from Water Atlas — read_transect","text":"function imports JSON file USF Water Atlas. training = TRUE, dataset TBEP training survey imported http://dev.seagrass.wateratlas.usf.edu/api/assessments/training. training = FALSE, entire transect survey database imported http://dev.seagrass.wateratlas.usf.edu/api/assessments/all__use--care. Abundance reported numeric value 0 -5 Braun-Blanquet coverage estimates, blade length cm, short shoot density number shoots per square meter. short density corrected quadrat size included raw data. raw = TRUE, unformatted data returned. default use formatting allows raw data used downstream functions. raw data may extra information may use outside plotting functions package.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/read_transect.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Import JSON seagrass transect data from Water Atlas — read_transect","text":"","code":"if (FALSE) { # get training data transect <- read_transect(training = TRUE) # import all transect data transect <- read_transect() }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/seagrass.html","id":null,"dir":"Reference","previous_headings":"","what":"Seagrass coverage by year — seagrass","title":"Seagrass coverage by year — seagrass","text":"Seagrass coverage year","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/seagrass.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Seagrass coverage by year — seagrass","text":"","code":"seagrass"},{"path":"https://tbep-tech.github.io/tbeptools/reference/seagrass.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Seagrass coverage by year — seagrass","text":"data frame used create flagship seagrass coverage graphic: Year int Acres num Hectares num","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/seagrass.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Seagrass coverage by year — seagrass","text":"Original data Southwest Florida Water Management District available online . Totals Tampa Bay.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/seagrass.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Seagrass coverage by year — seagrass","text":"","code":"if (FALSE) { seagrass <- structure(list( Year = c(1950L, 1982L, 1988L, 1990L, 1992L, 1994L, 1996L, 1999L, 2001L, 2004L, 2006L, 2008L, 2010L, 2012L, 2014L, 2016L, 2018L, 2020L, 2022L), Acres = c(40420, 21650, 23285, 25226, 25753, 26518, 26916, 24841, 26078, 27021, 28299, 29647, 32897, 34642, 40294.71, 41655.16, 40651.55, 34298, 30137), Hectares = c(16357.39, 8761.44, 9423.11, 10208.6, 10421.87, 10731.45, 10892.52, 10052.8, 10553.39, 10935.01, 11452.2, 11997.72, 13312.94, 14019.27, 16306.69, 16857.25, 16451.1, 13880, 12196) ), class = \"data.frame\", row.names = c(NA, -19L)) save(seagrass, file = 'data/seagrass.RData', compress = 'xz') }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/sedimentdata.html","id":null,"dir":"Reference","previous_headings":"","what":"Sediment data for the Tampa Bay current as of 12142023 — sedimentdata","title":"Sediment data for the Tampa Bay current as of 12142023 — sedimentdata","text":"Sediment data Tampa Bay current 12142023","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/sedimentdata.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Sediment data for the Tampa Bay current as of 12142023 — sedimentdata","text":"","code":"sedimentdata"},{"path":"https://tbep-tech.github.io/tbeptools/reference/sedimentdata.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Sediment data for the Tampa Bay current as of 12142023 — sedimentdata","text":"data.frame 216627 rows 24 variables: ProgramId int ProgramName chr FundingProject chr yr int AreaAbbr chr StationID int StationNumber chr Latitude num Longitude num Replicate chr SedResultsType chr Parameter chr ValueAdjusted num Units chr Qualifier chr MDLnum num PQLnum num TEL num PEL num BetweenTELPEL chr ExceedsPEL chr PreparationDate chr AnalysisTimeMerge chr PELGrade Factor","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/sedimentdata.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Sediment data for the Tampa Bay current as of 12142023 — sedimentdata","text":"","code":"if (FALSE) { # location to download data path <- '~/Desktop/sediment.zip' # load and assign to object sedimentdata <- read_importsediment(path, download_latest = TRUE, remove = TRUE) save(sedimentdata, file = 'data/sedimentdata.RData', compress = 'xz') }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/sgmanagement.html","id":null,"dir":"Reference","previous_headings":"","what":"Seagrass management areas for Tampa Bay — sgmanagement","title":"Seagrass management areas for Tampa Bay — sgmanagement","text":"Seagrass management areas Tampa Bay","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/sgmanagement.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Seagrass management areas for Tampa Bay — sgmanagement","text":"","code":"sgmanagement"},{"path":"https://tbep-tech.github.io/tbeptools/reference/sgmanagement.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Seagrass management areas for Tampa Bay — sgmanagement","text":"simple features sf object (MULTIPOLYGON) 30 features 1 field, +proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs areas int","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/sgmanagement.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Seagrass management areas for Tampa Bay — sgmanagement","text":"polygons seagrass management areas Tampa Bay provide finer division areas within major segments (tbseg) relevance locations seagrass beds.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/sgmanagement.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Seagrass management areas for Tampa Bay — sgmanagement","text":"","code":"if (FALSE) { library(sf) library(dplyr) library(tools) # NAD83(HARN) / Florida West (ftUS) # same as sgseg prj <- 2882 # create sf object of boundaries sgmanagement <- st_read( dsn = '~/Desktop/TBEP/GISboundaries/Seagrass_Management_Areas/TBEP_SG_MA_FINAL_Projectfix.shp', drivers = 'ESRI Shapefile' ) %>% select(areas = TBEP_SG_MA) %>% st_zm() %>% st_transform(prj) # save save(sgmanagement, file = 'data/sgmanagement.RData', compress = 'xz') }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/sgseg.html","id":null,"dir":"Reference","previous_headings":"","what":"Seagrass segment reporting boundaries for southwest Florida — sgseg","title":"Seagrass segment reporting boundaries for southwest Florida — sgseg","text":"Seagrass segment reporting boundaries southwest Florida","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/sgseg.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Seagrass segment reporting boundaries for southwest Florida — sgseg","text":"","code":"sgseg"},{"path":"https://tbep-tech.github.io/tbeptools/reference/sgseg.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Seagrass segment reporting boundaries for southwest Florida — sgseg","text":"simple features sf object (POLYGON) 22 features 1 field, +proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs segment chr","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/sgseg.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Seagrass segment reporting boundaries for southwest Florida — sgseg","text":"polygons used Southwest Florida Water Management District summarizing seagrass coverage estimates major coastal estuarine boundaries.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/sgseg.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Seagrass segment reporting boundaries for southwest Florida — sgseg","text":"","code":"if (FALSE) { library(sf) library(dplyr) library(tools) # create sf object of boundaries # make sure projection does not change sgseg <- st_read( dsn = '~/Desktop/TBEP/GISboundaries/Seagrass_Segment_Boundaries/Seagrass_Segment_Boundaries.shp', drivers = 'ESRI Shapefile' ) %>% select(segment = SEAGRASSSE) %>% mutate( segment = tolower(segment), segment = case_when( segment == 'terra ciea bay' ~ 'Terra Ceia Bay', T ~ segment ), segment = toTitleCase(segment) ) # save save(sgseg, file = 'data/sgseg.RData', compress = 'xz') }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_annualassess.html","id":null,"dir":"Reference","previous_headings":"","what":"Create a table for the annual management outcome assessments — show_annualassess","title":"Create a table for the annual management outcome assessments — show_annualassess","text":"Create table annual management outcome assessments chlorophyll-light attenuation bay segment","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_annualassess.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Create a table for the annual management outcome assessments — show_annualassess","text":"","code":"show_annualassess( epcdata, yrsel, partialyr = F, caption = F, family = \"Arial\", txtsz = 12, width = NULL )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_annualassess.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Create a table for the annual management outcome assessments — show_annualassess","text":"epcdata data frame epc data returned read_importwq yrsel numeric indicating chosen year partialyr logical indicating incomplete annual data recent year approximated five year monthly averages parameter caption logical indicating caption added using set_caption family chr string indicating font family text labels txtsz numeric indicating font size width optional numeric value indicating width inches","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_annualassess.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Create a table for the annual management outcome assessments — show_annualassess","text":"flextable object showing segment-averaged chlorophyll-light attenuation selected year, bay segment names colored management outcome used show_matrix.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_annualassess.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Create a table for the annual management outcome assessments — show_annualassess","text":"Segment Chl-(ug/L) Light Penetration (m-1) 2023 target 2023 target OTB 6.2 8.5 0.73 0.83 HB 6.9 13.2 0.79 1.58 MTB 3.7 7.4 0.47 0.83 LTB 2.6 4.6 0.54 0.63 Water quality outcomes 2023. Segment Chl-(ug/L) Light Penetration (m-1) 2023 target 2023 target OTB 6.2 8.5 0.73 0.83 HB 6.9 13.2 0.79 1.58 MTB 3.7 7.4 0.47 0.83 LTB 2.6 4.6 0.54 0.63","code":"show_annualassess(epcdata, yrsel = 2023) .cl-4da0ff90{}.cl-4d99bbae{font-family:'Arial';font-size:12pt;font-weight:normal;font-style:normal;text-decoration:none;color:rgba(0, 0, 0, 1.00);background-color:transparent;}.cl-4d99bbc2{font-family:'Arial';font-size:7.2pt;font-weight:normal;font-style:normal;text-decoration:none;color:rgba(0, 0, 0, 1.00);background-color:transparent;position: relative;bottom:3.6pt;}.cl-4d9c317c{margin:0;text-align:left;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);padding-bottom:5pt;padding-top:5pt;padding-left:5pt;padding-right:5pt;line-height: 1;background-color:transparent;}.cl-4d9c3186{margin:0;text-align:center;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);padding-bottom:5pt;padding-top:5pt;padding-left:5pt;padding-right:5pt;line-height: 1;background-color:transparent;}.cl-4d9c45cc{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 1.5pt solid rgba(102, 102, 102, 1.00);border-top: 1.5pt solid rgba(102, 102, 102, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-4d9c45d6{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 1.5pt solid rgba(102, 102, 102, 1.00);border-top: 1.5pt solid rgba(102, 102, 102, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-4d9c45d7{width:0.75in;background-color:rgba(45, 201, 56, 1.00);vertical-align: middle;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-4d9c45e0{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-4d9c45e1{width:0.75in;background-color:rgba(45, 201, 56, 1.00);vertical-align: middle;border-bottom: 1.5pt solid rgba(102, 102, 102, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-4d9c45ea{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 1.5pt solid rgba(102, 102, 102, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}SegmentChl-a (ug/L)Light Penetration (m-1)2023target2023targetOTB6.28.50.730.83HB6.913.20.791.58MTB3.77.40.470.83LTB2.64.60.540.63show_annualassess(epcdata, yrsel = 2023, caption = TRUE) .cl-4dd462e0{}.cl-4dcf07dc{font-family:'Arial';font-size:12pt;font-weight:normal;font-style:normal;text-decoration:none;color:rgba(0, 0, 0, 1.00);background-color:transparent;}.cl-4dcf07e6{font-family:'Arial';font-size:7.2pt;font-weight:normal;font-style:normal;text-decoration:none;color:rgba(0, 0, 0, 1.00);background-color:transparent;position: relative;bottom:3.6pt;}.cl-4dd14556{margin:0;text-align:left;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);padding-bottom:5pt;padding-top:5pt;padding-left:5pt;padding-right:5pt;line-height: 1;background-color:transparent;}.cl-4dd14560{margin:0;text-align:center;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);padding-bottom:5pt;padding-top:5pt;padding-left:5pt;padding-right:5pt;line-height: 1;background-color:transparent;}.cl-4dd1571c{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 1.5pt solid rgba(102, 102, 102, 1.00);border-top: 1.5pt solid rgba(102, 102, 102, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-4dd15726{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 1.5pt solid rgba(102, 102, 102, 1.00);border-top: 1.5pt solid rgba(102, 102, 102, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-4dd15727{width:0.75in;background-color:rgba(45, 201, 56, 1.00);vertical-align: middle;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-4dd15730{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-4dd15731{width:0.75in;background-color:rgba(45, 201, 56, 1.00);vertical-align: middle;border-bottom: 1.5pt solid rgba(102, 102, 102, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-4dd15732{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 1.5pt solid rgba(102, 102, 102, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-4dca6c0e{font-family:'Arial';font-size:12pt;font-weight:normal;font-style:normal;text-decoration:none;color:rgba(0, 0, 0, 1.00);background-color:transparent;}Water quality outcomes for 2023.SegmentChl-a (ug/L)Light Penetration (m-1)2023target2023targetOTB6.28.50.730.83HB6.913.20.791.58MTB3.77.40.470.83LTB2.64.60.540.63"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_boxplot.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot monthly chlorophyll or light attenuation values for a segment — show_boxplot","title":"Plot monthly chlorophyll or light attenuation values for a segment — show_boxplot","text":"Plot monthly chlorophyll light attenuation values bay segment","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_boxplot.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot monthly chlorophyll or light attenuation values for a segment — show_boxplot","text":"","code":"show_boxplot( epcdata, param = c(\"chla\", \"la\"), yrsel = NULL, yrrng = c(1975, 2023), ptsz = 0.5, bay_segment = c(\"OTB\", \"HB\", \"MTB\", \"LTB\"), trgs = NULL, family = NA, labelexp = TRUE, txtlab = TRUE, partialyr = FALSE )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_boxplot.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot monthly chlorophyll or light attenuation values for a segment — show_boxplot","text":"epcdata data frame epc data returned read_importwq param chr string parameter plot, one \"chla\" chlorophyll \"la\" light attenuation yrsel numeric year emphasize, shown separate red points plot yrrng numeric vector indicating min, max years include ptsz numeric indicating point size observations yrsel bay_segment chr string bay segment, one \"OTB\", \"HB\", \"MTB\", \"LTB\" trgs optional data.frame annual bay segment water quality targets, defaults targets family optional chr string indicating font family text labels labelexp logical indicating y axis target labels plotted expressions, default TRUE txtlab logical indicating text label target value shown plot partialyr logical indicating incomplete annual data recent year approximated five year monthly averages parameter","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_boxplot.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot monthly chlorophyll or light attenuation values for a segment — show_boxplot","text":"ggplot object","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_boxplot.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Plot monthly chlorophyll or light attenuation values for a segment — show_boxplot","text":"Points included yrsel plotted box plots using position_jitter. Use ptsz = -1 suppress. dotted line plot shows large exceedance value.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_boxplot.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot monthly chlorophyll or light attenuation values for a segment — show_boxplot","text":"","code":"show_boxplot(epcdata, bay_segment = 'OTB')"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_compplot.html","id":null,"dir":"Reference","previous_headings":"","what":"Make a bar plot for transect training group comparisons — show_compplot","title":"Make a bar plot for transect training group comparisons — show_compplot","text":"Make bar plot transect training group comparisons","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_compplot.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Make a bar plot for transect training group comparisons — show_compplot","text":"","code":"show_compplot( transect, yr, site, species = c(\"Halodule\", \"Syringodium\", \"Thalassia\", \"Halophila\", \"Ruppia\"), varplo = c(\"Abundance\", \"Blade Length\", \"Short Shoot Density\"), base_size = 18, xtxt = 10, size = 1 )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_compplot.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Make a bar plot for transect training group comparisons — show_compplot","text":"transect data frame returned read_transect yr numeric year training data plot site chr string indicating site results plot species chr string indicating species plot varplo chr string indicating variable plot base_size numeric indicating text scaling size plot xtxt numeric indicating text size x-axis labels size numeric indicating line size","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_compplot.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Make a bar plot for transect training group comparisons — show_compplot","text":"ggplot object","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_compplot.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Make a bar plot for transect training group comparisons — show_compplot","text":"","code":"transect <- read_transect(training = TRUE) show_compplot(transect, yr = 2023, site = '2', species = 'Halodule', varplo = 'Abundance')"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_fibmap.html","id":null,"dir":"Reference","previous_headings":"","what":"Map Fecal Indicator Bacteria (FIB) results by month, year, and location — show_fibmap","title":"Map Fecal Indicator Bacteria (FIB) results by month, year, and location — show_fibmap","text":"Map Fecal Indicator Bacteria (FIB) results month, year, location","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_fibmap.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Map Fecal Indicator Bacteria (FIB) results by month, year, and location — show_fibmap","text":"","code":"show_fibmap(fibdata, yrsel, mosel, areasel = NULL)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_fibmap.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Map Fecal Indicator Bacteria (FIB) results by month, year, and location — show_fibmap","text":"fibdata input FIB data.frame returned read_importfib yrsel optional numeric value filter output years fibdata mosel optional numeric value filter output month fibdata areasel optional character string filter output stations area column fibdata, see details","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_fibmap.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Map Fecal Indicator Bacteria (FIB) results by month, year, and location — show_fibmap","text":"leaflet map selected year, month, area showing stations FIB concentration category","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_fibmap.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Map Fecal Indicator Bacteria (FIB) results by month, year, and location — show_fibmap","text":"Placing mouse cursor item map reveal additional information station.","code":""},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_fibmap.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Map Fecal Indicator Bacteria (FIB) results by month, year, and location — show_fibmap","text":"","code":"# show selected year, month show_fibmap(fibdata, yrsel = 2023, mosel = 8) {\"x\":{\"options\":{\"crs\":{\"crsClass\":\"L.CRS.EPSG3857\",\"code\":null,\"proj4def\":null,\"projectedBounds\":null,\"options\":{}}},\"fitBounds\":[27.53248,-82.783203,28.149932,-82.061156,[]],\"calls\":[{\"method\":\"addProviderTiles\",\"args\":[\"Esri.WorldGrayCanvas\",null,\"Esri.WorldGrayCanvas\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.NatGeoWorldMap\",null,\"Esri.NatGeoWorldMap\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.OceanBasemap\",null,\"Esri.OceanBasemap\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.WorldPhysical\",null,\"Esri.WorldPhysical\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.WorldShadedRelief\",null,\"Esri.WorldShadedRelief\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.WorldTerrain\",null,\"Esri.WorldTerrain\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.WorldImagery\",null,\"Esri.WorldImagery\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.WorldTopoMap\",null,\"Esri.WorldTopoMap\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.DeLorme\",null,\"Esri.DeLorme\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.WorldStreetMap\",null,\"Esri.WorldStreetMap\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri\",null,\"Esri\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addLayersControl\",\"args\":[[\"Esri.WorldGrayCanvas\",\"Esri.NatGeoWorldMap\",\"Esri.OceanBasemap\",\"Esri.WorldPhysical\",\"Esri.WorldShadedRelief\",\"Esri.WorldTerrain\",\"Esri.WorldImagery\",\"Esri.WorldTopoMap\",\"Esri.DeLorme\",\"Esri.WorldStreetMap\",\"Esri\"],[],{\"collapsed\":true,\"autoZIndex\":true,\"position\":\"topleft\"}]},{\"method\":\"addMiniMap\",\"args\":[null,\"Esri.WorldGrayCanvas\",\"bottomleft\",150,150,19,19,-5,false,false,false,true,false,true,{\"color\":\"#ff7800\",\"weight\":1,\"clickable\":false},{\"color\":\"#000000\",\"weight\":1,\"clickable\":false,\"opacity\":0,\"fillOpacity\":0},{\"hideText\":\"Hide MiniMap\",\"showText\":\"Show 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\",\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAq4AAAK5CAYAAAB+LKwlAAAAAXNSR0IArs4c6QAAAARnQU1BAACxjwv8YQUAAAAJcEhZcwAAMsAAADLAAShkWtsAAFpGSURBVHhe7d0NtJ1VfefxdHXUcYaZsY7TaR2dlxrf7tnPjTZw9z4BGmap89I1bae60FYdh9VaX1bV6Yyt08pyDatj7az60o50fCsoSCEFEgIEoqAQgXDPfp4bQCBCBGlARRHFCEoD9W3+/3M3TfKcf5J7c+85z36e8/2t9VlBktyc8zx77/8v18M5awghZNqyftf6J82UJ/zMbNV3vYE/Zbbyr3AxvLGowjvF+4rSn+nK8FEX/Tny7zcVMWyRf3dFUYar5d9dJz83kB9vlp/bLf/+bnGf/NwD8u/2yb97VH78waLhP+/Tn1v8Nf5u/T3D37v4Na7Trzn82vJn6J8l/+4c/bPl3505fCwxvFP+/RtnB/IYq7Bx9sa+08euzyE9HUIIIYQQ0pZs/PHGv/eigX9uUfZ/oVf5lxfRv0FK3h9I6Xu/q/w5Ug6vkPIXF4vjsEj+uAsWn8uwDOtzk+coz1Wfc5TnXvrfGl4LuSZ6bfQapctFCCGEEELGmV51/LOLOHfybAyvk2L2v6SYfkIK6ueEfrfTLHao0Wsl10yvnV5DvZZ6TfXapstMCCGEEEKOlvW71j+jV/VPcGV4ZRHDO6RgfdhF/2n533vkfz9uFjGsHrnGeq31muu113ug90Lvid6bdJsIIYQQQqYnz5oPT123EOakLL2+qML/lR93FKV/6JAShQwN79GOdM9er/dQ72W6rYQQQggh7c66gf/Xs1X4JSk9pxfRXyiF544DRQgdccfivfWn673We55uPyGEEEJIfgnz4amzA++lxLxeSswHxef4Luo0k3u/+PrjD8r/fr2uDV0jabkQQgghhEwuRXXSz/Xi3H+RYvJhKSa3HlpagMO6VdfMcO1Ux/9cWk6EEEIIIauXYj78vIvhLa4MFxSlv9coJMAx8Pe60l+ga0vXWFpuhBBCCCFLy9rta5/Si3P/Vl+zKOXiSikV3xktHMDqk78Y6XvsXqlrT9egrsW0LAkhhBBC1qyZvbH/0y72/7Mr/Z9IYdhZLxNAs/xOXZu6RnWtpmVLCCGEkGlJbyGcWMTwhy760i4LQJ6Ga1bWrq7htJwJIYQQ0qW86OaT/pmr/Gtl4J8ng/9BqxAAbTNcy7qmZW3rGk/LnRBCCCFti75BvBv4d8lw5//+x1TQta5rXtd+2gaEEEIIyTHrbln3tN7Av6qI4eOu9F+1BjswLYZ7QPaC7gndG2mbEEIIIaSpzFZ95wb+92VQX1sf3AAOca3uFd0zafsQQgghZNyZuSmsHZbV6BeM4QzgaGTv6B7SvZS2FSGEEEJWK73q+GcXMfyOK8MN5iAGcEyGe0r2lu6xtN0IIYQQstwM3wmgDG9y0X/GGrgAVpfuNd1zvEMBIYQQsoQ8f+eGf1SU/rQi+m3WYAUwIcM96E/TPZm2JyGEEELW71r/pCLO/bqLYbM5QAE0arg3ZY/qXk3blhBCCJmuFGX/F4rSn11Ev98algAyM9yrsmdl76ZtTAghhHQ3a+PcP3ZleKsMwV0jQxFAm+zSvax7Om1vQgghpBsp4tzJrvRnuei/bwxAAC2le1r3tu7xtN0JIYSQ9kX/ow4Xw1v0PSOtgQegY/T9YWXP8x90EUIIaU1mB/4kF/1fyCB7fGSwAZgGj+sZoGdBOhYIIYSQfDKzY+NxRZz7bVf60hhiAKbU8EyQs0HPiHRcEEIIIc1kptzwIleGjxalf8waWgCwyD+mZ4WeGen4IIQQQiaTouy/pIhhiz2gAOAIhmdH/yXpOCGEEELGExk2pxbRf84cRgCwHMOzpH9qOl4IIYSQ1Yl+frkr/W3m8AGAFdCzRc+YdNwQQgghy8+6WzY+rSj96S76+61hAwCrafGs8afr2ZOOIUIIIeTI6S1seE4Rw/uLyH9wBaABevbIGaRnUTqWCCGEkEMzMx/mXPTnmIMEABqgZ5KeTemYIoQQMu3pDfwpRfTbrKEBAFmQM0rPqnRsEUIImbasWwhzrgybzSEBABnSM0vPrnSMEUII6XqK+VAUMZxnDQUAaAU9w+QsS8caIYSQrmVmPqzVT64xhwCm1X4Xw3fkxwdc6e+Vf97jqvB5+d9R/vf18uOOovTXyI9Xu6r/KSkLV7rYv1z+91axpaj8RW4hbHLRny//+5Pyc/oa6bNnF/ofU/rP6d/Jz/nz9dfq7xn+Xvkaw6+lX1O/tvwZ6c/akf7sqI9l+Jjkscn/fiA91v3Cei6YQnqm6dmWjjlCCCFtz4tv2vBMOdz/zDr00T1S7r4nvi7/fJe4VQpjKQXwOvnnq2bLcFlR9S8U50qJ/KgO/VaSx67PQZ/L8DnJc9PnqM9Vn7M+d70Gei3kn83rhG6Re/1netalY48QQkjbUtxw0k8VMfxxUfofWAc9Wku/4/iglLR7ht+RLMMNYnsR+xe6qn/WIQUPH9VrMrw2co3EDYvfxfX36DVM19K6xmglPev679GzLx2DhBBCcs/au/7DU1zp31VE/137cEcL7Je/dOgHP9zuBmEgZesqV/Y3uxg+cUgpw8oNr6lcW73Gcq31mqdrT6ltKzn79AzUszAdi4QQQnJML879rhzY3zAPc2RJytO3pSh9SQpUpa/1dLF//ki5QjP0XgzvSaiG90jvlXEPkSc9C/VMTMcjIYSQXDIbw+tkqO61Dm9kY7/co/ulBN0urutV/Utcyf+13z79s4b3Tu7h8F7KPdV7W7vXyIjcIz0b/2s6LgkhhDQVV27oF1H/a2z7wEZDYvih/Hi/K/3Nw+/YVXwXtfP0Huu9lnuu9z6tAXt9oClX65mZjk9CCCGTyvN2rX+Gi+H/GQczGiBlZb8r+/pdnSgl5rJW/xf7WB2La0Df8UDWRH+vrpGD1wyao2fnejlD03FKCCFknCkq/9/k4NX3szQPZUzEw64KX3SVv17KycWHFBbg8GStyJqRtaNrqLamMEHDMzTO/U46VgkhhKx23MD/YhHDgnUIY7xkyH1Tfrxdiupnh2+kb5cSYHl0LcmaGq6txTVmrj+MkZypbsH/YjpmCSGErDQvHPjnSmm9wDx0MRZSIv5WisU98uN1vD4VE6PvYqBrbnHt/a21NjEervQXvEjO2nTsEkIIOZYUpT/DOmQxDv6hXpy7tajCFSOFAmiArMsr9AMTdG2OrleMhz8jHb+EEEKWGhlarymi/5J9sGJVRP8DF4efga+fPLXp4MIAZCeGTYtrtb9X1+4haxmrS85eueavSccxIYSQw2X2xv6LpUx9yjxMsWJybfdJAdDXE24XHxspB0Ab6NpdXMOylv0+a61j5fQs1jM5Hc+EEEIOTlH6063DEyvjSimr+t6aMWwxSwDQcotr29+sa93aA1gpf3o6pgkhhPSq/oYi+nn7wMSxkAH+SFGFW2WoX1of8kDHXbq49mUPGHsDx8rfqGd1OrYJIWQ6I8Plj+xDEssWw6Ou8rtd9NuMYQ5MH90Lsid0b5h7BsvmYnh3Or4JIWR6UsyHl8pQucU6GLEM0T9elP7O4ev9rMENYJHsEd0ri3vG2EtYssWzu/+SdJwTQkiHc9GpP+lK/wHrMMQS6WfAR3+3q8JV5oAGcGSyd3QPDfeStcewJHqW65meTndCCOlWZqvwS/I39T3WAYil8A8WZX+n/PPHzWEMYFl0Ly3uKd1b1p7D0eiZrmd7OuYJIaT9mdm98bgi+g9bhx6OTIbrD3ulv3N2IVxWH7oAVo/uMd1r8s98F/ZYyBmvZ3069gkhpJ3pDfyr5ED7snnQ4bDcQD+3vb+zWOC7q8AkDfdc9Dcu7kF7f+Jw/H165qfjnxBC2pN1t2x8miv9ufbhBosb+B/p/+3mYv9ya6ACmDTZi7onZW9aexY2Pft1BqRxQAgheUcO+V+UQ3+vdaBhlIvhm8Pv8FThE6ODE0DjdG/qHpW9au1hjJLrtldnQRoLhBCSZ+Rg/9/WIQaDvjMA310F2kX27PAdCaw9jRE6E9J4IISQfDJbnvA8F/1nrYMLB8g1+lERw+3yz39lDkUAraB7WPfycE8bex0HDGfDzuOfn8YFIYQ0m2LgT5O/VfPJNEfgSv838uMuV/lzrSEIoKVkTxdVWEh73Nz/GH7nVWaEPy2NDUIImXxO/fGpP+kGc/qdB/OgwvA7Dfv03QHcgjHwAHSH7PHhXh/uefs8gP4lPnxUZ0caI4QQMpkUce5kV/rbrIMJogpflx+vGRluADpP934Rh2eAfT5MueHskBmSxgkhhIw3ciC/wzqMMDyQ7+2V/SutYQZgushfYOUs8PdaZwWEzJI0VgghZPXzgoWTf7Yo/VbzAJpyLoYv9qK/xBpeAKbb8GyQM8I6O+C3Pn/nhmemMUMIIauT2YF/hRwyD4weOlPvS2KLNawA4GDprNAzwzpLptkDOmPSuCGEkJXFDfyfGAfNVHPR3+tiuKw+mADgqIZnR58PaanRWZPGDiGELD8zu8PTpaBdbh0w08pV4StFFa4whxEALEM6S75inTXTSmeOzp40hgghZGnpVf0NcqDeZR0s08jpfyEcw6cPHjoAsBqGZwvvQvB35JrcpTMojSNCCDlyXNX/DeswmUYyTL7pov9sfdAAwKrTs0bOHOssmkY6i9JYIoQQO67k9axKBoi+ifgOc7gAwBgNzx4+yGBIZ1IaT4QQciAvKE/4p3JATP3rWeUa6Mc23mANEwCYpMWziI+S1dmkMyqNK0LItKe3EE6Uw4HXs5bh1mIhnG0NEABogp5JRSVnk31mTZO7dFalsUUImdb0YvhN44CYKvK3+XuLyHuxAsjX4hnFp3DpzErjixAybZFD4L31Q2Ga6GvIXNn/jDUkACBPcmbx+tf3pjFGCJmGrN+1/hlF9NuMw2AquIH/kfxY2UMBAPI3PMMWzzLznOs8mWE6y9JYI4R0NTMDf1JR+rvNg2AKuBi+OFuGC6xBAABtMjzL5Eyzzrrp4O/WmZbGGyGka5mt/Mtd6b9vHwAdV4UHihiutA5/AGgzPdvknHtg5NybAjrTdLalMUcI6UpmS/9ma9N3nYthv5RW3t4KQOcNzzo984yzsOt0xqVxRwhpe4rSn2Ft9K6Tv4nvcbF/jnXAA0AnDc88v8c6E7vPn5HGHiGkrSmi/7C9wbtLDu1H5MerzUMdAKbA4hk4PAvNc7KzZOal8UcIaVPW71r/JNnAl5gbu8Nc9Ltd1T/LOsgBYKroWShnonVWdprMPp2BaRwSQnJPEeeeVZR+p7mhO8rF8G05qLePHNwAgO16RlpnZ3fJDJRZmMYiISTXyN801+tbhNgbuZtcFT5vHNQAgIPJWWmdod0ls1BmYhqPhJDcUlT+P8pGnabXND3oot9mHtAAgFGLHz7zYO0s7TCZiTIb05gkhOQS2Zyn2Zu2m1zpbzIPZQDA0UV/k3W2dpc/LY1LQkjTkRL3P+2N2j0uhq/Lj1vNgxgAsGTDs3TxTDXP267RWZnGJiGkqchG/IC1QbuoV4Zd1uELADh2erZaZ24X6cxM45MQMunI35Q/ZG3MDnpY8HGtADAmesams9Y6g7uF93olZPKRvzWeZW7I7rlLfNw6aAEAq0fP2nTmWmdxx/iz0jglhIw7UlrPtTdi59xgHa4AgPHRs7d2FnfTwH8yjVVCyLgih8omcwN2ywOu7G+uH6YAgEnpb9azuHY2d448101pvBJCVjsuhi3WxuuUKtw6eoACAJqgZ7J5VneIztY0Zgkhq5Ifr/kJF/3l1obrCnl+fyM/Xm0dnACA5gzP5sUz2jy/u0BnrM7aNHUJIceamd0zT5YN9Wlro3WFHIx7i7J/Xv2wBADkIZ3Rclbb53gX6KzVmZvGLyFkuZnZsfE4OSiusTZYh8SDD0cAQL70zK6d4Z3iSn+Nzt40hgkhS01x20k/5WKH/8vOGB6VQ3B7/VAEAGRvu57h5tneAfL8rtcZnMYxIeRocQP/z2XjdPlvtffPluGCgw5BAECL6BmuZ3ntbO8MeY5RZ3Eay4SQw6VXHf9sF/3N1kbqiC/UD0AAQDvpmV474ztDZ7HO5DSeCSH1zJQn/IxslNusDdQN/kbr4AMAtJee7faZ3346k3U2pzFNCHkiM7s3HldEP29tnA54tCj7V1oHHgCg/fSMXzzrzRnQbjKbdUancU0I0cjmuHpks3TD/a7qn28ddACADpGzXs/82gzoiqvTuCaEFKXfamyS9qt4PSsATBs9+82Z0Hp+axrbhExvZDOcN7o52s9FXs8KAFNLZoA1GzrgvDS+CZm+yN/ePmJsinaL/tFeGXg9KwBMOZ0FOhPMWdFq/iNpjBMyPSlieJ+9IdrMP+jKuU3WAQYAmEZzm3Q22DOjxWSGp3FOSPcjm/gMcyO0mr+vWAhn2wcXAGBa6WwYzghzdrSZPyONdUK6G/lb2u/ZG6C9XOn3WIcVAAAH+D3WDGk1melpvBPSvcyW/s3mwm+z6G+xDygAAA6lM8OcJS2msz2NeUK6k14Mr7MWfLvxzgEAgOXR2WHPlPbSGZ/GPSHtT6/yL7cWepvNRv9Z60ACAOBodIZYs6XNdNansU9Ie9Nb8KdYC7ytXPT7i+i3WQcRAABLNZwlOlOMWdNWOvPT+CekfZmZD2tlY37NWtzt5B8SF1kHEAAAy6UzZXG2WDOnhWTm6+xPNYCQ9mTt9rVPkb9JlubCbiFX+q+Kc62DBwCAY6ezxX/Vmj1tpLNfO0CqA4S0I7IZN1sLup383aMHDQAAq0dnjT2D2keez+ZUBwjJP/I3xz+1FnI7+TvrhwsAAOOgM8eeRe2jXSDVAkLyjRv4t1sLuKW+YB0sAACMi86e2ixqLe0EqR4Qkl9kw73SWritFMPt9cMEAIBJ0BlkzqYWkufzylQTCMknrtzQd6X/vrVoW+jW+iECAMAk6SyqzaZW0m6gHSHVBUKaTxHnniWb7K+tBds6fIQrACATOpPMWdUy8lz+WrtCqg2ENBtZkNdbC7WFdh18YAAA0DSdTbVZ1UryXK5PtYGQ5uKiP99aoC1U1Q8LAAByoDOqNrNaSTtDqg+ETD5FDP/HWpitE0O0DgoAAHKhs8qcYW0j3SHVCEIml6Lq/7a5INsm+nnrgAAAIDc6s8xZ1jbSIVKdIGT8KebDS82F2DZVuME6GAAAyJXOLnOmtY10iVQrCBlfZm/s/7RsnL3mImwTSisAoKW6UF5d9Pdqp0j1gpDxRBba5dYCbBle0woAaDWdZbXZ1jraKVK9IGT142J4t7Xw2sSV/ibrAAAAoH38TdasaxPtFqlmELJ6kQ3ShY9z5ROxAACdorOtNutaR54HHwtLVi9uV/8FRekfsRZbi9xR3+wAAHSBzrjazGsZ/4h2jVQ7CFlZZEHttBdaS0R/t7XRAQDoCp115gxsDb8z1Q5Cjj0uhg/ZC6wdXOzvtTY4AAAd1O53/anCh1L9IGT5kQ3wJnNhtYSL/qtuwdzYAAB0j848mX3WTGwLeR5vSjWEkKWnV/U3WAuqLVzpvyE/fnxkUwMA0GGLs284A8352AbaQVIdIeTomdm98bgi+jutxdQO/qFeGc6zNjQAAF2nM1BnoT0jW0A6iHaRVEsIOXJkwVxoLqQWkL9lPiKbdlN9EwMAMGVkFrb4HYGki6RaQsjhI39DO91cQK3gf9Cr+pcYmxcAgKmjM1Fnoz0z28CfnuoJIaNxC/5l9sJph14ZrrY2LgAA00pnozUz28IN/MtSTSHkQGZ2zzxZ/mbT3te1Rn+jtWEBAJh2OiPN2dkK+nrXmSenukLIYtxgTv9LRGPBtAIf5QoAwBHorKzNzhbxH0l1hRB9XWt49egiaQcX/T3WBgUAADUyM61Z2hKvTrWFTHPWzYd/UcTwLWOB5K8KD8wu9D9mbk4AAHAInZk6O82ZmjvpKtpZUn0h0xpZCFvMBZK/786W4QJrYwIAAJvOTp2htZnaCk46S6ovZBrjSv82a2G0gWy8y6wNCQAAjkxnqDVb20C7S6oxZJrSi3PrrAXRBrLprqlvQgAAsCzXWDO2DbTDpDpDpiUu+uusxZA7+ZtWaWw+AACwbL60Zm3utMOkOkOmIUUV/tBaCLmThbrb3ngAAOCYyGy1Zm72pMukWkO6nGI+vNRcAPn7srnhAADAiuiMrc3cdpBOk+oN6WLW71r/pCKGO8ybnzHZVN8ryv559Y0GAABWLs1YmbX2HM6WdBrtNqnmkK6liP7D5o3PnGym7QdvMAAAsOq2WzM4e9JtUs0hXcrswP+aecPzF43NBQAAVpnO3NoMbgXtOKnukC5k/a71/6CILXz9SvR3WxsLAACMh85ecybnTDqOdp1Ue0jbU5T+TPNG5yz6h1zVP8vaVAAAYExk9uoMNmdzzqL/YKo9pM0pyv5LzBucuV7Vv8TcUAAAYKx0BluzOX/9l6T6Q9qaIoYF++bmy8VwnbWRAADAhMgstmZ01qTzpPpD2pii9KebNzZnMdxubiAAADBROpPNWZ01f3qqQaRNmb2x7+wbmrX7rY0DAACaobO5Nquzt648sZfqEGlLiui3WTczX/4x2SCb6hsGAAA0apPOaHt2Z0o6UKpDpA2Rm/b6kZuYOVeFq4zNAgAAmiYz2prdWZsPr0+1iOSc9bvWP6OI4VvmTcxVDLeYGwUAAGRBZ7U5w3MlXeh50olSPSK5pij9WeYNzNcD1gYBAAB50Zldm+FZc9KJUj0iOaZX9v+TdeMyt8XaHAAAIC86s2szPHvajVJNIrnFxbDbumm5kk0wqG8KAACQtYE103Ol3SjVJJJT3MD/kXXDcuWiv9fYDAAAIHcyw63Znispr+9OdYnkkF7VP8G6UdmK4XEX++ebmwEAAORNZrjOcnPGZ0q7UqpNpOnI3yS2WzcpV/J4d5gbAQAAtMW11ozPlXalVJtIkynK/qnWDcqXv9NY/AAAoGV0ptuzPlf9U1N9Ik3FRd+mzxF+WJxtLX4AANAuOtPTbLdmfna0M6X6RJqIK/3/sG5MrvTb9NbCBwAALdW2lytKd0o1ikwyM/Ph6bJYvmPdlCzx6VgAAHRSmz5VS7uTdqhUp8ikIn9j+FPrhuRIHus3rIUOAAC6wn/D6gA50g6V6hSZRHpxbp11IzK21V7kAACgC3TW12Z/1rRLpVpFxh1ZIJutm5ClgeclAgAATAGd+WYXyJA83s2pVpFxRj9z17oBOXIDv6++qAEAQIfJ7Lc6QY60U6V6RcYVV/rSuvhZiuHT5qIGAACdpLPf7AQZ0k6V6hUZR3qlf7N14XMki2GPtaABAEDn7bG6QY60W6WaRVYz/2rvxr8vF/hr9QueJ/9YUfXPNRYyAADoOO0Awy5gdoTsfE07VqpbZLUiC+A9xsXOkqvCddZCBgAAU0K6gNUR8uTfk+oWWY286Gb/XPtCZyiG+8wFDAAApor0gvtGekKmtGul2kVWGimD51kXOUeyUC+uL1wAADCVLra6Qpaka6XaRVaSIvr15gXOUfQLxqIFAABTSruB2RlyJJ0r1S9yrHHRn29e3My4GL5pLVgAADDlpCNY3SE32rlS/SLHElduON66sFmqwhXmYgUAAFNNO4LZHTKk3SvVMLLcyM3eZF3U3LjK764vUgAAgL8jXcHqELmRx7op1TCynKxbCHPWBc1ODI+72D9nZIECAAA8QbqCdgazS2RGO1iqY2SpKaK/0LqYuZHFOBhZnAAAAKMGVpfIjnSwVMfIUlLEuWBeyOz4h4xFCQAAYNLuYHeKzEgXS7WMHC1yUy8yL2JmXNn/jLUoAQAAbP3PWJ0iP/6iVMvIkeLKDX37AmYmhi/bCxIAAODwtEOY3SIz2slSPSOHi9zQzdbFy9DW+kIEAAA4Gu0QtU6RJXmsm1M9I1Z6C+FE68JlJ4Y76osQAABgqbRLmB0jM9rNUk0j9RTRX2JdtKzE8EN5nH9pLUIAAICl0C4x7BRW18iJdLNU08jBKeLcyeYFy83AL1gLEAAAYDm0U5hdIzfS0VJdI0+kKH0bXu/xsLXwAAAAjoV2i1rXyJDfmuoa0bTmu61l2GEtOgAAgGOh3aLWNfLEd10PpKj8X5oXKS/3WwsOAABgJbRj1DpHfqSrpdo23ektbHiOeYFyU/lt1mIDAABYCe0YZvfIjHa2VN+mN27g32tdnJy40t9jLTQAAIBVco/VQXKinS3Vt+lMmA9PLUr/iHVxMsOHDQAAgLHRrlHrHhnyj2h3SzVu+lLE8N/tC5MPF/luKwAAmASf/XddtbulGjd9kVK4x7woeeG7rQAAYOy0c9Q6SHa0u6UaN13pDfyrrAuSmS9ZCwsAAGAcihi+ZPSRrGiHS3VueiJP/Nr6hchNr+pfYi0qAACAcdDuYXWSzFyb6tx0pA0fOOBKf7e1oAAAAMbL3211k6xM0wcStOQDB7bYiwkAAGB8ioWwxegleZmWDyRoxQcORL7bCgAAmlO04LuuU/GBBG34wIEi8t1WAADQHO0iZkfJSOc/kKAlHzhwl7WAAAAAJkk7Sa2jZKbjH0jQig8cKPubrcUDAAAwSYV0EqurZKXLH0ggNyHrDxxwVfhifdEAAAA0RrqJ1VlyIY+xmx9IUMS5X7GecE56Zbh6ZMEAAAA0JfrPWJ0lK9LxUt3rTlzpLzafbCZc7O81FwwAAECTpKNY3SUX8hgvTnWvG3n+zg3PtJ5oTuSibz9kkQAAAORhu9VdcqJdL9W+9qeI4R3Wk8xG9A8aiwQAACAL2lXMDpML6Xqp9rU/LvrbzCeZi+g/Zy0SAACAHGhXMTtMJrTrpdrX7vQW/CnWE8yFi+F71gIBAADIinQWq8vkQjtfqn/tTVH6s6wnl43oF8zFAQAAkBHtLGaXycXAn53qXzsz+/nZf1jE8Lj55PLwo6Ly51qLAwAAICfaWYbdxe40zZPOp90v1cD2xcXwRvOJZUIWwRfqiwIAACBjX7A6TS60+6Ua2L7Ixb3BelK5kMd38UELAQAAIHd5vy++dL9UA9uVYj78vPWEcsEHDgAAgFbK/AMJtAOmOtieuNJ/wHwymZAbzwcOAACANsr6Awm0A6Y62J7Ig873jXL5wAEAANBi2mXMjpMB7YCpDrYjs5X/NeuJZIMPHAAAAC2mXcbsOLmIc7+eamH+kQd85cgTyIT8LWC/tQAAAADaxe+3uk4mrky1MO/0FjY8x3jw2ZCbfJt98wEAANok74/U106Y6mG+KWJ4h/XgsxHDFvvmAwAAtId2GrPr5EI6YaqH+UYe5Lz54DPgYvi6deMBAABaSbqN1XmyIJ0w1cM888KBf675wDMhN/j6kRsOAADQXtdbnScXL5JumGpifimq8HvWg85CDD8sFsLZxg0HAABoJe02w45jdZ8c5PxygSL6jF8m4PdYNxwAAKDNitLfaXWfLEg3TDUxr2T/MoHKb7NuNgAAQKtJx7G6Ty60I6a6mE+KmPPLBPxD5o0GAADoAO06ZgfKgXTEVBfzSVH6G80Hm4do3WQAAIAu0K5T6z75yO3lAjPzYa35QDPRK/vnWTcZAACgC7TrWB0oF9oVU21sPjm/TEBu5j31mwsAANA9/h6rC2Uhp5cLFDHnlwn4q+ybCwAA0B3aeewulAHpiqk2Npu8Xybgv2vdWAAAgC7S7mN3ouZl8XKBXjX3u9aDy0IMt1g3FQAAoIu0+5idKAPaGVN9bC55v0wgbLVuKgAAQBdp96l1oXw0/XKB3sKG55gPLAOu9PusGwoAANBtfp/VjXKg3THVyMmnFzN+mUDFywQAAMD00Q5kdqMMaHdMNXLykYtzrfWgMsHLBAAAwNTRDlTrRNmQx3dtqpGTzczujcdZDygHvEwAAABMt3xfLqAdMtXJyUUuyq9aDyYLvJsAAACYYjm/u4A8vl9NdXJycTF8yHowWah4mQAAAJhe2oXMjpQB7ZCpTk4uRfR3Ww+maXIxvmPdQAAAgKkincjqSo2TDpnq5GTSG/gXmg8kB7xMAAAAIO8PI5AumWrl+ONK/zbrQWSClwkAAICpp52o1pGyoV0y1crxp4h+m/UgmsbLBAAAAA6S78sFtqVaOeb8eM1PFKXfbz6IhskN+vzIDQMAAJhen7c6U/P8fu2UqV2OL7049+/sB5AFXiYAAACQaDeqdaVsaKdM9XJ8cQP/XusPbxovEwAAADBk+nIB7ZSpXo4vuX7+rYt+t3mzAAAAppl0JKs7NS6GW1K9HE9mdp34L80/OAdV+LR5swAAAKaYdiSzO2VAu2WqmaufXgy/af2hmTjbulkAAADTTDtSrTNlQ7tlqpmrH/kDNtX/wBy46L9q3SgAAACIKnzF6lAZ2JRq5uqniOFbxh+Yg2jeJAAAAOh3XWOtO+VBumWqmaub3nw40fwDcxDDFusmAQAAYFhct4z0p0xox0x1c/XiBv7t1h/WNBfD96wbBAAAgAOKKnzX6lJNc6V/e6qbqxd5whdbf1jT5HHtOfimAAAAwBDDHqtLNU0e28Wpbq5e5Itm+aJeeVzX/N0NAQAAgEl60zX1HpUD/Y/sU91cnfQWNjzH+oPy0D/XujkAAAA4QDuT3aWaNzMf1qbaufK4gX+t9Ydk4AHrxgAAAGCUdqdal8qCq/xrU+1ceVzp/9z6Q5omj+sm66YAAADA4m+yOlXT5LH9eaqdK4+LeT7J2TJcNnpDAAAAYNHuZHWqpmnXTLVzZZnZvfE46w9onn/MuiEAAAA4PO1QdrdqlnbOVD+PPW7gX2Z98aZJM7/HuhkAAAA4AulQVrdqmnbOVD+PPfJF3mV98cZVYd68GQAAADgs7VBmt2qYK/vvSvXz2ONi2G598QxstW4GAAAADk87VK1TZUE7Z6qfxx5X+m9bX7xhP7BuBAAAAI5Ou1StWzVOO2eqn8eWYiEU1hduXPRfs24CAAAAjk67lNmxGuYGfjbV0OVHntQbrC/auCrcYt0EAAAAHJ12KbNjNa3yb0g1dPlxMXzC/KKN81dZNwEAAABHp13K7ljN0u6ZaujyI0/qTuuLNm4hfNK6CQAAADg67VJmx2qcvzPV0OXlebvWP8P+gs1y0e+zbgAAAACWQTqV1bWaph001dGlpzfwp1hfrGlyofeMXHgAAAAs1x6razVNO2iqo0uPi+Et1hdrmiv99caFBwAAwLL4662u1TTtoKmOLj1F6T9ifbGmuSpcbF98AAAALJl0KqtrNc9/JNXRpUd+0077izXJP2ZeeAAAACybdiu7czXJ70x1dOmRJ/Ow/cUadV/9ggMAAODYaLeqda3GyeN6ONXRpWU2zv0b6ws1LvqF+gUHAADAsdFuZXauhmkXTbX06CkG/petL9K4KlxhXXQAAAAsn3Yrs3M1TbpoqqVHTy+Gd5pfpGlV/1zrogMAAGD5tFuZnath2kVTLT16XOkvsL5Ik9zAP2pdcAAAAKzI96zu1STtoqmWHj0u+tusL9IkeQJfMS40AAAAVsR/xepeTdIummrpUXLRqT9ZxPAj64s0qgq32hcbAAAAx0o7ltm9miRdVDtpaqeHTy/OrTO/QPN2WBcbAAAAx047Vq1zZUE7aaqnh488gddYv7lpvegvqV9oAAAArIx2LKt7NU0e22tSPT18iir8sfWbm+bK/ln1Cw0AAICV6p9lda/GSSdN9fTwKaLfZv7mBrnS77MvNAAAAFbO77M6WKOkk6Z6evjIg99r/uYGyWO659CLCwAAgFV0j9XBmiSPaW+qp3bW7Vj3NOs3ZmBX7eICAABglWjXqnWvLGg3TTV1NBm/o8DV1kUGAADAymnXqnWvLBzxnQWKOPcr1m9q3MBfaF1kAAAArJx2LbODNU26aaqpo3Glf5v5mxokj+n71gUGAADAavLft7pYk7Sbppo6GvnJD1i/qVHRP2hfXAAAAKwW7VxmF2uQdtNUU0cjv2BL/Tc0zcWwx7q4AAAAWEXSuawu1rAtqaaORlrtTcZvaJQ8ptK8uAAAAFhFvrS6WJO0m6aaOpqi9A9Zv6lJs5X/rH1xAQAAsFq0c1ldrFHRP5Rq6qFZv2v9PzF/Q8OkaV9qXVwAAACsJn+p1cWaph011dUDyfU9XHtlOM++uAAAAFgt2rmsLtY0871ci8r/svWLmyTNn7fCAgAAmJj83hJLO2qqqwciDzS/93CNfp99UQEAALDqpHtZnaxJ2lFTXT0Q+ZcZvodr+LJ5UQEAALDqtHuZnaxJVXh/qqsHIg80u/dwFXdYFxUAAACrT7tXrYs1TzpqqqsH4iLv4QoAADDdMnwvV+moqa4eiLTZb1m/uEm8hysAAMDk5PleruFbqa4uhvdwBQAAgHYvq5M17ZD3cnU3+VnrFzWN93AFAACYnFzfy9UN/GyqrWvW9Mr+v7d+UZNc9D+wLigAAADGSDqY1c2apF011dY1a+RfvLr+C5qm7yNmXkwAAACMT4bv5SpenWqrvodreKvxC5rFe7gCAABMnHYws5s1SB7XW1Nt1ZcK+DOsX9Qw3sMVAABgwrSD1TpZBvwZqbbqW2H5D9q/qDmu6t9kXUwAAACMkXQwq5s1y5+ZauvwwwfOt39Rg6owb15MAAAAjI12MLObNciV/oJUW4fF9dPWL2qSq8K11sUEAADAGEkHs7pZw65KtXX4qVkLxi9olKv8p8yLCQAAgPGRDmZ1s0bFsCvVVv2Oa9hr/qImVWGreTEBAAAwNtrBzG7WIO2qqbYO/+OsR6xf1CS3EDZZFxMAAABjJB3M6maNkq46LK0zu2eebP6Chrmqf455MQEAADA+0sGsbta0tdvXPmXNCxZO/lnrJxsV/Y/MCwkAAICx0y5mdrQGvXjnhmeuma36zvrJJrno91sXEQAAABMgXczqaI2aD8UaV4WN5k82SD8j17yIAAAAGD/pYlZHa1Jv4E9ZM1v5l1s/2SQXw9fNiwgAAIDxky5mdbQmzQ78K9YUpf8t6yeb5Mr+XvMiAgAAYPyiv9fqaI2K/g1rXOl/3/zJBknL32NeRAAAAIyfdDGrozVJHtMfrJF/eG/9J5rWi3O3mhcRAAAAY6ddzOpojYrhffpSgTPNn2yQi760LiIAAAAmQLqY1dGa5c9cow/O/snmuCpcN3IBAQAAMBnSxayO1iR9XGukUef46Qg7Ri4gAAAAJkK7WK2bNU47q/7HWRdYP9mk2cp/1rqIAAAAGD/tYlZHa5J2Vn2pwGbrJxt2df0CAgAAYDK0i9W6WePkcW1eU0S/zfrJJrmq/6n6BQQAAMCESBezOlqjpLPq22FdNfITzbvSvIgAAAAYO+1itW6Wg6u0uOb34tuyf7l1EQEAADAJ/cutjtawHfpSgXnjJxrlSn+pfREBAAAwfv5Sq6M1Sjqrfsd118hPNG+LfREBAAAwbtrFat0sB7v0fVxvN36iUXLBLq5fQAAAAEzMxVZHa5J2Vimu4YvWTzbsr4wLCAAAgAnQLlbrZo3Tzqrv47rX+skmzZbhgvoFBAAAwGRoF7M6WpPkce3Vlwp8zfrJJvXK/nn1CwgAAIDJ0C5mdbQmaWddU8TwLesnm+RKf651EQEAADAJ/lyrozVKOuuaovSPmD/ZrI/bFxEAAADjpl2s1s0y4B/R77g+bv9kc1zl/8K6iAAAAJgA6WJWR2uUdFZ9H1f7JxtkXkAAAABMjNXRmsZ3XAEAAHCofL/jymtcAQAAcIB2sVo3y8Dia1x5VwEAAAAcJNN3FcjzfVwD7+MKAADQkGzfx1UeHJ+cBQAAgL+T8SdnhS9aP9mwv6pfQAAAAEyGdrFaN2ucdlZ9qcDt1k82SS7YxfULCAAAgIm52OpoTdLOqu/juqv+ExnYYlxAAAAATIB2sVo3y8GuNUX088ZPNMqV/lLrIgIAAGAS/KVWR2uUdFb9juuOkZ9omCv7l9sXEQAAAOPXv9zqaA3bocX1qtq/zMGV9kUEAADAuGkXq3WzHFylLxXYZvxEo1zV/5R1EQEAADAB0sWsjtYo6az6Pq6bzZ9sUK8MV49cQAAAAEyE9LGr6/2safK4Nktx9dm9wexs5T9bv4AAAACYDO1iVkdrknZWfR/Xc6yfbNgO6yICAABg/LSL1bpZ47Sz6ksF9MGZv6AprgrX1S8gAAAAJkS6mNXRmqSPa01R+jOtn2ySNOpy5AICAABgMqSLWR2tWf5MfTus947+RLN6ce5W8yICAABg7LSLWR2tUTG8T//jrN83f7JBLoY91kUEAADABEgXszpak+Qx/YG+VOC3rJ9skov+XvMiAgAAYAL6e62O1qjo37BmtvIvN3+yQdKov25fRAAAAIyddDGrozVpduBfscZVYaP1k01y0e8zLyIAAADGT7qY1dGa1Bv4U9bMVn1n/WST5GLtNy8iAAAAxk+6mNXRGjUfijUvWDj5Z82fbFL0PzIvIgAAAMZOu5jZ0Rr04p0bnrlmZvfMk62fbJqr+udYFxIAAABjJB3M6mZNW7t97VPWaKRVP2L9gia5hbDJvJgAAAAYH+lgVjdrlHTVYWnVuBjye8uDKmw1LyYAAADGRjuY2c0apF011Vb9jmvYZf2iJrnKf8q6mAAAABgj6WBWN2uUdNVUW6W4luGqkV/QMFeFa82LCQAAgPGRDmZ1s4ZdlWrrGv3Y1wuMX9CsKsybFxMAAABjox3M7GYN0q6aaqt+x9Wfaf2iJrmqf5N1MQEAADBG0sGsbtYsf2aqrcPieob9ixp1h3kxAQAAMDbawWqdLAP+jFRb9aUC4a32L2pQDF+uX0gAAACMl3Yws5s1SB7XW1NtHf7HWa+u/4Km6Wfk1i8kAAAAxkw6mNXNGvbqVFvXrOmV/X9v/IJGyUX7gXkxAQAAMD7Swaxu1iTtqqm2rlnjBn7W+kVN65XhPPOCAgAAYNVp97I6WdO0q6baumbN+l3r/4n1i5rmSn+pdVEBAAAwDv5Sq5M1Tbtqqq2LKWL4lvULmzRb+c/aFxUAAACrTbuX1ckaJR011dUDcdFn955d0vpL66ICAABgHHxpdbImaUdNdfVApM1usX5xw3gvVwAAgAnR7lXrYs2Tjprq6oEUVXi/+YubxHu5AgAATIx2L7OTNUk6aqqrB+JK/zbzFzdI30fMuqgAAAAYgwzfw1U7aqqrB1JU/petX9wkeaDfNy8qAAAAxsB/3+pkjZKOmurqgfTi3DrzFzeM93IFAAAYv1zfw1U7aqqrB8J7uQIAAEyzlryH6xMpon/I+g1N4r1cAQAAxi/P93D1D6WaOhpp2ryXKwAAwFTK8D1cpZummjoa+QXZvZeri2GPfXEBAACwaqRzWV2sYaPv4fpEpNV+wPgNzYr+QfPiAgAAYNVo5zK7WIO0m6aaOhr5yfzey5W3xAIAAJiA/N4KS7tpqqmjKeLcr1i/qXEDf6F9gQEAALBS2rXMDtY06aappo4m1/dyFVdbFxkAAAArp12r1r2yYL6H6xNZt2Pd06zflIFd1kUGAADAymnXqnWvLGg3TTXVjjz4vdZvbJI8pnsOvrgAAABYVfdYHaxJ8pj2pnp6+BTRb7N+c5Nc6ffVLi4AAABWjd9ndbBGSSdN9fTwKarwx+Zvbpgr+2fZFxoAAADHrn+W1b0aJ5001dPDR57Aa8zf3LBe9JeMXmgAAACshHYsq3s1TR7ba1I9PXwyfmeBHfULDQAAgJXRjlXrXFk44jsK/F0uOvUnixh+ZH2BRlXhVutiAwAA4NhpxzK7V5Oki2onTe30yHHR32Z+kQa50n/FutgAAABYCf8Vq3s1SbtoqqVHjzyBC6wv0iS5sN8bvdAAAABYkYF/1OpeTdIummrp0dOL4Z3WF2lc1T/XvOAAAABYNu1WZudqmHbRVEuPnmLgf9n6Io2rwhXWRQcAAMDyabcyO1fTpIumWnr0zMa5f2N+kaZFv2BddAAAACyfdiuzczVMu2iqpUuLPJmHrS/UsPvqFxwAAADHRrtVrWs1Th7Xw6mOLj1F6XdaX6xZ/rH6BQcAAMCx0W5ld64m+Z2pji498ps+Yn+xZrkqXGxdeAAAACyDdCqrazXPfyTV0aXHxfAW+4s1y5X+evPiAwAAYBn89VbXapp20FRHl57ewJ9ifbGmyYXeM3rhAQAAsEx7rK7VNO2gqY4uPc/btf4Z1hdrmot+n3HhAQAAsBzSqayu1TTtoKmOLi9F6e+0vmDjFsInzRsAAACAo9IuZXasxvk7Uw1dflwMn7C/aNP8VdZNAAAAwNFpl7I7VrO0e6YauvwUlX+D9UUbV4VbrJsAAACAo9MuZXaspkX/hlRDlx838LPmF21a9F+zbgIAAACOTruU2bGathCKVEOPLa703za/cLN+YN0EAAAAHJ12qVq3apx2zlQ/jz0uhu3WF8/AVutGAAAA4PC0Q9U6VRa0c6b6eexxZf9d1hdvXBXmrZsBAACAw9MOZXarhrmBf1eqn8ce+SIvs75401z091g3AwAAAEcgHcrqVk3Tzpnq57FnZvfG46wv3jz/mHkzAAAAcFjaoexu1SztnKl+rizSzG+y/oCmzZbhMuuGAAAAYJR2J6tTNU27ZqqdK4880T+3/pCmudLfVL8hAAAAOJw8vxkpj+vPU+1ceVzlX2v9IRl4wL4pAAAAqNPuVOtSWXAD/9pUO1eemfmw1vpD8tA/17oxAAAAOEA7k92lmtdb2PCcVDtXJy76r1p/UAausW4OAAAADnGN0aMaJ4/rK6lurl7ki15s/WFNczHsOeiGAAAAwLbH6lJNk8d1caqbqxdX+rdbf1jjqvDd2k0BAABAXQzfM7tUw9zAvz3VzdVLbz6caP1hmdhi3iAAAAB8tIhhi9GfsqAdM9XN1Y086W9Zf2AGonWTAAAAMHw3gVjrTnmQbplq5upH/oBNI39gBlwVvmLdJAAAAIh8/yP7Talmrn56Mfym8Qfm4mzzRgEAAEwx7Ui1zpQN7ZapZq5+Znad+C+tPzQLVfi0dbMAAACmmXYksztlQLtlqpnjSRHDLdYf3DQX/W7rZgEAAEw16UhWd2qcdMpUL8cXN/DvNf/whrkYvmPeLAAAgGkmHcnqTk3TTpnq5fjSi3P/zvrDM7HVvGEAAABTSLtRrStlQztlqpdjzI/X/ERR+v3WA2ia3KDP128YAADAFPu81Zma5/drp0ztcrwpot9mP4hm8XIBAACAg2T6MgHtkqlWjj+u9G8zH0QeeLkAAACYetqJah0pG9olU60cf3oD/0LrQWQhhlusmwcAADBNcn0nKKVdMtXKyaSI/m7rgTSNlwsAAACIfF8mcHeqk5OLXIwPmQ8mBxUvFwAAANNLu5DZkTKgHTLVyclFLsqvWg8mC7xcAAAATLGcXyYgj+9XU52cXGZ2bzzOejA5cKXfV7+BAAAA08PvszpSDrRDpjo52ciFudZ6QJng5QIAAGDqaAeqdaJsyOO7NtXIyacX537XelBZqHi5AAAAmD7agcxulAHtjqlGTj69hQ3PsR5UDni5AAAAmE75vkxAu2Oqkc2kKP1O64FlgpcLAACAqaHdp9aFMuJ3pvrYXLJ+uQDvLgAAAKZI1h860OTLBJ7IzHxYaz24PPjvWjcVAACgi7T72J2oedoZU31sNkX0N1oPMA/+KuvGAgAAdIl2HrsLZUC6YqqNzWe26mf7cgFX+nusmwsAANAx91hdKAfaFVNtbD55v1wg/LhX9s8zbi4AAEAnaNexOlAusnmZwBMpypxfLhCidZMBAAC6QLtOrftkJKOXCTyRIobfsx9sBqJ/yLrJAAAAXaBdx+xAOZCOmOpiPnnhwD/XfLCZcJXfZt1oAACAVpOOY3WfXGhHTHUxr0jbn7cecB78nebNBgAAaLPo99jdJwPSDVNNzC9FlfPLBcIPi4VwtnnDAQAAWki7zbDjWN0nB9INU03ML9m/XKAM19dvOAAAQItdb3WeXGT7MoEnIq0/25cLuBi+btxwAACAdpJuY3WeLEgnTPUw38iDfIf54HMRwxbzxgMAALSIdhqz6+RCOmGqh/mmt7DhOeaDz4Qr/W3WzQcAAGgXf5vVdXKhnTDVw7wjD/bK+oPPhdzk/fbNBwAAaBO/3+o6mbgy1cL8U8S5XzeeQD6i/5y9AAAAAPKnXcbsOJmYrfyvpVrYjsjfAh60nkgWon/QWgQAAABtoF3G7DgZ0A6Y6mB7Ig/6A9aTyYXc9O31RQAAANAC261ukwvtgKkOtifFfPh568nkwpX9vcZCAAAAyFx/r9VtsiEdMNXBdkUu7g3mE8qEq8LFo4sBAAAgU9JdrE6TC3mMN6Qa2L64GN5oPalcyMX9wiGLAQAAIG9fsDpNLrT7pRrYvsx+fvYfFjE8bj2xLET90Z9rLAoAAICsaGdZ7C6Zks6n3S/VwHamGPizzSeXi+gXrMUBAACQE+0sZpfJhj8r1b/2prfgT7GfXB5cDN+zFgcAAEBWpLNYXSYX2vlS/Wt3XMz7I8mK2OcDCQAAQLa0q5gdJhPa9VLta3+KGN5hPcls8IEEAAAgYzl/4MCQdL1U+9qf5+/c8EzzSWZEFgUfSAAAAHKU9QcOKO16qfZ1I3LRM3/fMT6QAAAA5CjvDxxwpb841b3upIhzv2I92Zz0Sv8Ze8EAAABMnnYTq7NkRTpeqnvdityAPeYTzoSrwhfrCwYAAKAx0k2szpILeYx7Us3rXooY/rv1pPPS3zyyaAAAACauv9nuKhmRbpdqXvcS5sNTi9I/Yj7xfNxlLx4AAIDJ0U5S6yiZ8Y9ot0s1r5txA/9e+8lnJIYt1gICAACYBO0iZkfJiHa6VO+6m97ChudYTz4v/m5rEQEAAExCEf3ddkfJh3a6VO+6naLyf2ldgKws8F1XAAAwedJDsv9uq3a5VOu6nyLOnWxehIw4vusKAAAakf93W7XLpVo3HZEnfe3IRchMr+pfYi8oAACA1afdw+okmbk21bnpSW/gX2VciLzE8CVrUQEAAIyDdg+zk2REO1yqc9MVF33WH0iQbLUWFgAAwGrSzlHrINnR7pZq3PRF37TWuig5caW/x1pcAAAAqyr6e6wukpUuf+DA0dKSDyRQfNcVAACMjXaNWvfI0BR84MDR0oYPJJAFxXddAQDAGOX/3dap+MCBo6UdH0ggKr/NXmgAAADHTjuG2T0yMzUfOHC0tOIDCcpwv7XYAAAAVkI7Rq1z5GeaPnDgaGnDBxIkO6wFBwAAcCy0W9S6Rp6m7QMHjpai9C14UXJ42Fp0AAAAx0K7Ra1rZMhvTXWNPJHWfNd14BeshQcAALAc2inMrpEbvttqp4g+/485i+GH8jj/0lqAAAAAS6FdYtgprK6RE+lmqaaRenoL4UTzouUmhjusRQgAALAU2iXMjpEZ7WapphErcjM3WxcuQ3woAQAAWDbtELVOkSV5rJtTPSOHiys39K2Ll50YvlxfiAAAAEejHcLsFpnRTpbqGTlSitJfZF3A3Liy/xlrQQIAANj6n7E6RX78RamWkaOliHPBvoi58Q/ZixIAAGCUdge7U2RGuliqZWQpKaK/0LyQmZFFOKgvSgAAAMPA6hLZkQ6W6hhZatYthDnzYuYmhsdd7J9jLE4AAIBF0hW0M5hdIjPawVIdI8uJ3OhN1gXNjav87pEFCgAA8ATpClaHyI081k2phpHlxpUbjrcuapaqcMXIIgUAAFNPO4LZHTKk3SvVMHIscdGfb13Y3LgYvmktVgAAMOWkI1jdITfauVL9IseaIvr11sXNUvQL5oIFAABTSbuB2RlyJJ0r1S+ykhQxnGde4AzJIr24vmgBAMBUutjqClmSrpVqF1lpXnSzf655kfN0n7FwAQDAlJEyeJ/RE7KkXSvVLrIaKUr/HutC58hV4TprAQMAgCkhXcDqCHny70l1i6xW/tXejX9fLu7XRi92jvxjRdU/11zIAACg07QDDLuA2RGy8zXtWKlukdVMr/RvNi54lmTh7qkvZAAAMA38Hqsb5Ei7VapZZByRxVBaFz5LMXzaXtAAAKCLdPabnSBD2qlSvSLjSq/s/yfr4ufIDfw+a1EDAICOktlvdYIcaadK9YqMM7IwNls3IEsDf8vIogYAAJ2jM9/sAhmSx7s51Soy7vTi3DrrJmRsa31xAwCA7tBZX5v9WdMulWoVmURc6f/UuhE5ksf6DWuRAwCArvDfsDpAjrRDpTpFJpWZ+fB0F8N3rBuSpRh4yQAAAB2kM96c/RnS7qQdKtUpMsnI3xj+h3VTciWLZbu14AEAQEvJbLdmfq60O6UaRZqIi/5268Zk6mFxtrnwAQBAq+hMT7PdmvnZ0c6U6hNpKkXZP9W6Ofnyd1qLHwAAtIvOdHvW56p/aqpPpMm079v04dr64gcAAC0Sww5rxudKu1KqTaTp9Kr+CdZNylYMj7vYP9/cCAAAIG8yw3WWmzM+U9qVUm0iOUT+JvFu60blykV/r7kZAABA3mSGW7M9V27g/yjVJZJTpLzutm5YrmTxD0Y2AwAAyNnAmum50m6UahLJLfqZu9ZNy9wWY1MAAIDM6MyuzfDsaTdKNYnkGFf6s6wbl7EHrM0BAADyojO7NsMz589K9YjkmuftWv+MIoZv2TcwU3yqFgAAWWvTp2MNSRdaL50o1SOSc4r58HrzJmbMVeEqa6MAAICGyYy2ZnfmXp9qEWlDiui3GTcxY/4x2RybRjYLAABo0iad0fbszpR0oFSHSFuyrjyxZ97MvN1vbBgAANAQnc21WZ292Rv7LtUh0qbI35BOt25o1mK43do4AABgsnQmm7M6a/70VINIGyOLbsG+sflyMVxnbSAAADAhMoutGZ016Typ/pC2pij7LzFvbuZ6Vf8ScyMBAICx0hlszeb89V+S6g9pc4roP2jf4IxF/5Cr+mdZGwoAAIyJzF6dweZszpo/M9Ue0vas37X+HxQxfNm+0RmL/m5zUwEAgLHQ2WvO5JxJx9Guk2oP6UJmB/7XzJudv2htLAAAsLp05tZmcCtox0l1h3Qp8reoD1s3PHeymbbXNxcAAFhV260ZnD3pNqnmkK5l/a71TypiuMO88RmTzfS9ouyfV9tgAABgFaQZK7PWnsPZkk6j3SbVHNLFFPPhpebNz9+X6xsNAACsnM7Y2sxtB+k0qd6QLqeowh+aCyBzLvrd1oYDAADHSGarNXOzJ10m1RoyDZGF2r43Fhau9KW58QAAwDL50pq1udMOk+oMmZb04tw6azG0gWy2a0Y3HwAAWIZrrBnbBtphUp0h0xT5m9bbrAXRBrNluMzYhAAA4Ch0hlqztQ20u6QaQ6YxLoYt1sJoge/KxrvA2pAAAMCms1NnaG2mtoN0llRfyLRm3Xz4F7IQvmUukNxV4YHZhf7HrI0JAAAOpTNTZ6c5U3MnXUU7S6ovZJojC+LVIwukJVz091ibEwAA1MjMtGZpS7w61RZCtLz6jxiLpC1uNTcoAAAY0llZm52t4QZzH011hZDFzOyeebKU1zutBdMK0d9obVQAAKadzkhzdraCv1M7SqorhByIG/iX2YumHXpluNrasAAATCudjdbMbAu34F+Wagoho5G/2ZxuLZx28D/oVf1LrI0LAMC00Zmos9GemW3gT0/1hJDDp4j+QnsB5c+V/hHZrJvqmxcAgCkjs9A/Ys3KVpAukmoJIUfOzO6Nx8mCae/rXUv/UK8M5xmbGACAztMZqLPQnpEtIB1Eu0iqJYQcPb2qv8FcTC0hf8v8hvz4cWtDAwDQVYuzbzgDzfnYBtpBUh0hZOmRDfAma0G1hYv+q27B3tgAAHSOzjyZfdZMbAt5Hm9KNYSQ5aeowoeshdUWsgH2HrKpAQDoqtjfa83CtnAxfCjVD0KOPUXpd1oLrDWiv9vc4AAAdITOOnMGtobfmWoHISuL29V/gSyo9v6XiYvusDY6AABtpzOuNvNaxj+iXSPVDkJWHtkYr7QXW6vw0bAAgE7R2Vabda0jz+OVqW4QsnpxMbzbWnBt4kp/U33TAwDQTv4ma9a1iXaLVDMIWf246C+3Fl7LRPsAAACgHXSW1WZb62inSPWCkPFk9sb+T8tCu9dagK1ShRusgwAAgNzpDDNnW4vI89irnSLVC0LGl2I+vNRahK1DeQUAtEwXSuuQdIlUKwgZf4qq/9vmQmyb6OetgwEAgNzozDJnWdtIh0h1gpDJpYjh/5gLsm0ir3kFAORNZ5U5w9pGukOqEYRMPi76882F2T6VdVAAANA0nVG1mdVK2hlSfSCkucimut5aoC20q35YAADQJJ1NtVnVSvJcrk+1gZBmU8S5Z8mC/GtrobZO9LccfGAAANAUnUnmrGoZeS5/rV0h1QZCmo8rN/Rd6b9vLdgW4hO2AACN0llUm02tpN1AO0KqC4TkE9loXfhY2EUx3F4/RAAAmASdQeZsaiF5PnycK8k3buDfbi3clvpC/TABAGCcdPbUZlFraSdI9YCQfONK/6fWAm4nf6d1sAAAsNp05tizqH20C6RaQEj+kQ242VrI7eTvrh8uAACsJp019gxqH3k+m1MdIKQdWbt97VNc9KW1oNtI/ub4VXFu/aABAGBldLb4r1qzp4109msHSHWAkPZkZj6sLaL/mrWw28k/JC6yDx4AAJZHZ8ribLFmTgvJzNfZn2oAIe1Lb8GfYi7ulpK/Se6XjbnNOoAAAFiq4SzRmWLMmrbSmZ/GPyHtTa/yL7cWeJvNRv9Z6yACAOBodIZYs6XNdNansU9I+9OL4XXWQm83f6N1IAEAcDg6O+yZ0l4649O4J6Q7mS39m60F32p8RCwAYIl0ZpizpMV0tqcxT0j3UsTwe9bCbzNX+j3WAQUAwAF+jzVDWk1mehrvhHQ3RenPMDdAq/n7ioVwtn1YAQCmlc6G4YwwZ0eb+TPSWCek+5G/pb3P3ght5h905dwm6+ACAEyjuU06G+yZ0WIyw9M4J2R6Ipv5I+aGaLPoH+2V4Ur7AAMATAudBToTzFnRav4jaYwTMn2RTXDe6KZoPxd5xwEAmFoyA6zZ0AHnpfFNyPRG/va21dgc7VeFL5gHGgCgs/TsN2dC6/mtaWwTQmRTXD26STrhflf1z7cONwBAh8hZr2d+bQZ0xdVpXBNCNDO7Nx5XRD9vbJYueLQo+7zuFQA6Ss/4xbPenAHtJrNZZ3Qa14SQJzJTnvAzLvrbzI3TCbzuFQC6Rs92+8xvP53JOpvTmCaE1NOrjn+2bJSbrQ3UEbzuFQA6Qs/02hnfGTqLdSan8UwIOVzcwP9zORCitZE64v7ZMlxQPwABAO2gZ7ie5bWzvTPkOUadxWksE0KOluK2k35KNs711obqhBgelee3/YlDEADQGtv1DDfP9g6Q53fDzHx4ehrHhJClZmbHxuNc6a+xNlaHxNqBCADIlJ7ZtTO8U+Q5XqOzN41hQshyM7N75smu8p+yNlhXyEGxtyj75x18OAIA8pHOaDmr7XO8C1z0n9aZm8YvIeSY8+M1PyEb6nJro3WFPL+/kR+vrh+WAIBmDc/mxTPaPL+7wJX+cp21aeoSQlYjcoBstjZcp1Th1vqhCQBohp7J5lndJTFsSWOWELLacTFsMjdetzzgyv5m6xAFAExCX79R8kDtbO6iTWm8EkLGFVf6c43N10U32AcqAGBc9OytncVd9ck0Vgkh446U17OMTdhFd4mPW4crAGD16FmbzlzrLO4Yf1Yap4SQScXF8CF7Q3bOw+JK66AFAKycnrHprLXO4G6J/sNpjBJCJh1X+g+YG7ODemXYZR24AIBjp2erdeZ2kc7MND4JIU1FNuL/tDZoF7kYvi4/brUOXwDA0g3P0sUz1Txvu0ZnZRqbhJCmU5T+NGujdpWL/ibrIAYALIW/yTpbu8uflsYlISSXFJX/j7I5H7E3bSc9KAV2m30oAwBGyJmpZ2ftLO0wmYkyG9OYJITklmIh/Lxs1LvtDdxNrgqfNw9oAMABclZaZ2h3ySyMfn0aj4SQXFPEuWfJht1pb+RucjF8Ww7m7SMHNQBgu56R1tnZXTIDZRamsUgIyT3rd61/kmzeLaObudtc9Ltd1T/LOLgBYLroWShnonVWdlr0l+gMTOOQENKm6PvVmRu7w9zi63yvNg9yAJgCi2fgVP03D4t4j1ZC2p+i9GeYG7zj5NDe42L/HOtQB4BOGp55fo91JnafPyONPUJI29Mr/Zvtjd5tLob9RRVuMA94AOiQ4VmnZ55xFnbdrMy4NO4IIV3JbOVfLn8T/7616afAA0XkY2MBdI+ebVJaHzDOvc7TmaazLY05QkjXMjPwJw3fIsQ4AKaBi+GLs2W4wDr8AaBNhmeZnGnWWTcd/N0609J4I4R0NS8oT/inxeKbUBsHQfe5gf+R/FhZgwAA2mB4hi2eZeY513kyw3SWpbFGCJmGyOZ/78hhMEVc9Ptc2f+MNRQAIE9yZsnZZZ1p00Kuw3vTGCOETFt6MfymdTBME1f6e4sYtowOCADIw+IZJWeVcYZNE51ZaXwRQqY1vYVwohwId9UPiKlThVuLhXC2NTQAoAl6Jsn5dOvIeTVl5Frc1ZsPJ6axRQiZ9uhrheRv85dbB8Y0kWvwN/Ijb58FoHGLZ9HwTDLPq2nhor+c17MSQszIIfkn1sExbdJryHZYwwQAxml49kz561ifoDMpjSdCCLHjqv5vWAfINHIxfFMGyGet4QIAq0rPGjlzrLNoGrnY/400lggh5MjpVf0NcpDyutdEhsnXixg+PTJoAGCFhmeLnjHG2TON9L1pdQalcUQIIUvLzO7wdH1tkXWwTCtXha8UVbjCGj4AsBzpLPmKddZMK7kel83Mh6enMUQIIcuPG/C61zop9Pe6GC47eAgBwJIMz47+XutsmWY6a9LYIYSQlWV24F8hB8tUfhb2UXxJ8B6wAI4qnRV6ZlhnyTR7QGdMGjeEELI6ef7ODc8sSr/VOHSm3vA1WdFfUh9UADA8G+SMsM4O+K0vWDj5Z9OYIYSQ1U8RwzvsAwiu9Pf2ynClNbwATJei0rOAT7s6LJklaawQQsh4U8S5k+VAvs08jKCfwqX/hfA11jAD0G2696WU8S4BhzGcHTJD0jghhJDJ5NQfn/qT6ZA2DycM/yOufUXZ3+kW7AEHoCNkjw/3Oh8ccERuMPdRnR1pjBBCyORTlP40F8Oj1iGFRU4/trEKC67y55pDD0A7yZ4e7m0+mvWIhjNi4E9LY4MQQppNsfP45+unvlgHFg6Qa/SjIobb5Z//yhyCAFpB97Du5eGeNvY6DtDZMFue8Lw0LgghJJ/I36r/t3VwwRD93a7sX24NRQC56l+ue9fc0xihMyGNB0IIyTNu4H9RDnjeXHuJ5GD/piv9ja4KnxgdkgAaN9ybskdlr1p7GKPkuu3VWZDGAiGE5J11t2x8mhz051oHGmxyyP9IrtkevgsL5EL2YpQ9KXvT2rOw6dmvMyCNA0IIaU96A/+qovT3WYcbDm/4Xdg4/A4P34UFJkn3nO69Ad9dXbbov6xnfjr+CSGknZnZvfE4OdA+bB50OCIZpD+U4n/nbKmfbW4MWQCrYnYhXNaTvSb/LHvO3o84Ajnj9axPxz4hhLQ/s1X4Jf2/3cxDD0vxoL5PpPz48frQBbB8upcW95SXvWXuORyFnul6tqdjnhBCOpaL9EML/AesAxBLFMMPh+9IUIWrrGEM4Chk7wzfGUD3krXHsCR6luuZnk53Qgjpboqy/xL5m/ot1mGIZYj+cX0pgYthuzmgASySPaJ7ZXHPGHsJSzY8u+fDS9NxTggh0xMZJu+2DkYcgxgedZXfLUNlmzm4gWmje0H2hO4Nc89g2Vzp/ygd34QQMp3pVf0NRelvtA5JHBsZLo8UVbhVhvelI8Mc6LZLF9e+7AFjb+AYRT+vZ3U6tgkhhEh5Pd08MLEiMsD3iZuLGLYYQx5ovcW17W/WtW7tAayUPz0d04QQQg7O7I39F7voP2Ufnlgpubb73PDz1cN28TGrBADZ07W7uIZlLVNWx0XPYj2T0/FMCCHkcJHh9Joi+i9ZhylWSfQ/cGVfP5r3BikAm0bKAZCXTYtr1d+ra/eQtYzVJWevXO/XpOOYEELIUlOU/gzzYMUY+IdcFT4v/3xFrTAAjSiqcEUvzt2qa3N0vWI8/Bnp+CWEEHIseeHAP9cN/AX2IYtxcDH8rRSHe+TH61zsn18vFMBYVLLWdM0trr2/tdYmxkPPWD1r07FLCCFkpZGD9ReLGBasQxfjJSVCP7f9dlf5z7roKbJYHbqWZE0N19biGjPXH8ZIzlQ9W9MxSwghZLVTVP6/yZD7jnkIY1IedlX4oiv99VJALh4pJIDtYimq1+va0TVUW1OYoOEZKmdpOlYJIYSMM8/btf4ZcvD+P+tAxuRJgd2f/kOvKOXkMrdglhZMk8U1cNnimujv1TVy8JpBc/TsXC9naDpOCSGETCqu3NAvYrjaOpzRoMXPgL9/+N6aVf9Tw9cuWuUG3aH3WO+1vmew3Pu0Buz1gWbIWalnZjo+CSGENJXZGF4nw1O/42cf2MjBfrlH97vF95G9rlf1L3Fl/6xDyg9aoH/W8N4N/8M9uZdaUuXe1u41MiL3SM/G/5qOS0IIIbmkF+d+15X+G/WDG/mSofrtIoYvSQmqht+x410M8qH3YnhPQjW8R3qvjHuIPOlZqGdiOh4JIYTkmLV3/YenyIH9riL671qHOVphvxQl/U7e7W4QBq4KV7myv1kK1CdGyhVWZnhN5drqNZZrrdc8XXu+i9pWcvbpGahnYToWCSGE5J7ihpN+qij77ylKPmWnY7RQPeiiv0c/MEHK1w1iexH7F7qKlx6MkGsyvDZyjcQNw2sm106vYbqW1jVGK8lZF8Mf69mXjkFCCCFty4tv2vBMF8Of2Qc9ukbu9ffE1+Wf7xK3SkkrpaxdJ/981az+V+5V/0Jxbqvf+UAeuz4HfS7D5yTPTZ+jPld9zvrc9RrotZB/Nq8TukXWxZ/pWZeOPUIIIW3PzHxYq0PfOvQxtfZLudP3BH7Alf5e+ec9+h1J+d9R/vf18uOOovTXyI9X62s9ixiudLF/ufzvrWJLUfmLpERu0jfSl//9Sfm5c+THs2cX+h9T+s/p38nP+fP11+rvGf5e+RrDr6VfU7+2/Bnpz9qR/uy4+N1ReUzy2OR/P5AeK98lxd/RM03PtnTMEUII6VqK+VBIWTjPGgIA0Ap6hslZlo41QgghXc+6hTDnyrDZHAoAkCE9s/TsSscYIYSQaUtv4E8pot9mDQkAyIKcUXpWpWOLEELItGdmPsy56PX1iPbgAIAJ0zNJz6Z0TBFCCCGHprew4TlFDO8von/MGiQAMFZ69sgZpGdROpYIIYSQI2fdLRufVpT+dBe9vhm7PWAAYJUsnjX+dD170jFECCGELD+uDG9ypb/NGjYAsBJ6tugZk44bQgghZHVSlP1Ti+g/Zw0fAFiW4VnSPzUdL4QQQsh4IsPmJUUcvom8PZAA4HCGZ0f/Jek4IYQQQiaTmXLDi/STa4qS/5ALwJH4x/Ss0DMjHR+EEEJIM5nZsfG4Is79tiuHnxVvDC0A02h4JsjZoGdEOi4IIYSQfDI78Ce56P9Chtbj9SEGYCo8rmeAngXpWCCEEELyzvN3bvhHLoa3FNEvGIMNQNfIXtc9r3s/HQOEEEJI+1LEuZNd6c9y0X/fHHgAWkn3tO5t3eNpuxNCCCHdyNo4949dGd4qA29XfQACaJVdupd1T6ftTQghhHQ3Rdn/haL0ZxfR7zeGIoDcDPeq7FnZu2kbE0IIIdOV9bvWP6mIc7/uYthsDksAjRruTdmjulfTtiWEEEKI/kcdRelPK6LfZg1QABMy3IP+NP5DK0IIIWQJedHNJ/0z/fxyF/1nzMEKYFXpXtM9p3svbUNCCCGELDe96vhnFzH8jgzVG6yBC+DYDPeU7C3dY2m7EUIIIWS1MnNTWOsG/vf1PSOtQQzgKPT9VmUP6V5K24oQQggh485s1XfDEluGa0eGM4CDXat7RfdM2j6EEEIIaSrrbln3tN7Av6qI4eOu9F81BjcwNYZ7QPaC7gndG2mbEEIIISTHrFsIc27g3+Wi32kNdqBrdK3rmte1n7YBIYQQQtqW4TsUVP61RQznyXB/0Br6QNsM17KuaVnbvBMAIYQQ0tH0FsKJMvD/UAZ/aRUCIFfDNStrV9dwWs6EEEIImZbM3tj/aRf7/9mV/k+KkpcVIDd+p65NXaO6VtOyJYQQQghZs2bt9rVP6cW5fyuF4XQpDle6MuwbLRPA6nMxfEd+vFLXnq5BXYtpWRJCCCGELC3FfPh5KRVvcaW/QErFvfXCARwbf6/8xegCXVu6xtJyI4QQQghZvRTV8T/Xi3P/pYj+w1JAbh0tJIDpVl0zw7VTnfRzaTkRQgghhEwuYT48dXbgvRST10sx+aD4XFH6h2qlBVND7r2uAV0LsiZ0begaScuFEEIIISS/rBv4fz1bhV/S1yxKiblQSswdhxYcdMAdi/fWn673Wu95uv2EEEIIIe3Os+bDU/UN4qXwvL6owv+VH3fw3dk2GN6jHemevV7vod7LdFsJIYQQQqYn63etf0av6p/gyvDKIoZ3FNF/2EX/afnfe+R/P35oicKqk2us11qvuV57vQd6L/Se6L1Jt4kQQgghhBwtver4Zxdx7uTZGF7nYvhfrgqfkIKlr6O8zyxiGKXXSq6ZXju9hnot9ZrqtU2XmRBCCCGEjDMbf7zx771o4J9blP1f6FX+5UXpf0uK2R8UMbzfRX+O/O8r5H9H+fFu+d+deV/axeeiz0mfW7jCVfJc9TlX+tz9GxavRf8X9NroNUqXixBCCCGEtCXrd61/0kx5ws/M3th3UvI2zg78K6T8vVFK3zuLKrxPyuCZrgwf1dIr/36T/PstWn6lHF4t/+46+bmB/Hiz/NxuLY5Cv+v7gBZJ+XePyo8/WDT8Zy3KDyz+mmHJ3D38vYtf4zr9msOvLX+G/lny787RP1v+3ZnDx1KFd8q/f+Ns5V/RG/hTZqu+08euzyE9HUIImZKsWfP/AavTKnLZzH5HAAAAAElFTkSuQmCC\",\"data:image/png;base64,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\",\"data:image/png;base64,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\",\"data:image/png;base64,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\",\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAroAAAJkCAYAAAD+yYJGAAAAAXNSR0IArs4c6QAAAARnQU1BAACxjwv8YQUAAAAJcEhZcwAAMsAAADLAAShkWtsAAEc4SURBVHhe7d0LvKVXedfxUavVUluBzF7vCQja0tZqFa1apVCtVq1WqW2tVq1Sq9bSUkUrVNFqW1tR2lJbq2IJIYRcIZALIZArM3u9eyYJuZGEJCQ0CbnM7LX35AoEEkIS1/POE5Ps85/JOWfOPvt59/79Pp/vh36YZOac/b7rWc+kJNlFRETb372j47+pDJvXl7Z5W2nTWSWnayY5PWDs/7b/bmo/Vv8Y+2P9TyMiIiIiilkZDb63LrPnTtrmqU2pf479uf7TEBERERHFaDJKb67L6i1yid0M+znqz+U/LRERERHRYprs2f3VdUE9Y93CeuzOsJ/bfxkiIiIiop1rktdePWnTzWJJ3Sb15867X+2/HBERERHR/Jvk5if0cjoH9dfyX5aIiIiIaH5Nhru/XS6k81R/Tf/liYiIiIi2vwNXr31VadNNchmdI/s17df2L4OIiIiIaHub5OY0tYjuiPpr+5dBRERERLR9df8IMbWA7iT+0WNEREREtJ1N9uxu6qL5+XWL5877vH0t/mURERERER1bk5zeIZbOxahfi39ZRERERERbr+wdvEounAtkX5N/eUREREREW6vkdKFaNhfJvib/8oiIiIiINl9pB/9QLZoR2NfmXyYRERER0eYqbbpVLZkR2NfmXyYRERER0cYrufmPasGMxL5G/3KJiIiIiJ6/e4fH/8GS05fUchmJfY32tfqXTURERER09Ca5eZdaLEOqX6t/2URERERER246bP6CXCgDs6/Zv3wiIiIiIl1dHC+bXSR74DL/8omIiIiI1lcXxh+ZWSD75Ef82yAiIiIieqanntr1O+qyeMfM8tgnd9j34N8OEREREdHhJm36ebE89kz6ef92iIiIiIi6fwPa1+nFsX/se/Fvi4iIiIhWvZLTyWpp7CP7XvzbIiIiIqJV7tC+wXephbHP7Hvyb4+IiIiIVrVJm7JaFvstZf/2iIiIiGgVK3nwY3pR7D/73vzbJCIiIqJV6raPvOIrJ226Ry2JR1LEfxdXuse+R/92iYiIiGhVKrl5q14Qj6xfi679Vd3mrf7tEhEREdEqdGDP2h9Ri+FG9G3Zte/Vv20iIiIiWvbKsDlDLYXLyL5X/7aJiIiIaJmbts3fUAvhZtSfQ/73Udn37N8+ERERES1rdfG7YnYR3CxbdKftmvyxoK7wb5+IiIiIlrFJbn5SLIFb0re/qmvfu38MRERERLRMTfbs/uq67E3kErhFvVp27Xuvn4F/HERERES0LJWcfkUugMdiJP67wOwz8I+DiIiIiJahsnfwx9Xit4rss/CPhYiIiIj6XmnTB9TSt4rss/CPhYiIiIj6XBkNvlctfKvMPhP/eIiIiIior5U2XaOWvVVmn4l/PERERETUx6bt4I1q0YP9EyMGb/SPiYiIiIj61EPty144yekBteShqp+NfUb+cRERERFRX5rk5tflgjdHJev/Pqz6GfnHRURERER9aLp/7VvlYrcDivjvIrPPyj82IiIiIopeXeDOm13ocETn+cdGRERERJE7mJsfFMscjsI+M//4iIiIiChqJTc3qmVuJ027fzVwWvffR2WfmX98RERERBSxyTC9WS1yi3B42e2R+tn5x0hEREREkSqXDtIkN5+XSxyeX/3s7DP0j5OIiIiIolTa9H/kAocNs8/QP04iIiIiilBpB39eLW7YPPss/WMlIiIiokVX2vRRtbRh8+yz9I+ViIiIiBZZyYN/oBY2bJ19pv7xEhEREdGiKjl9Si1r2Dr7TP3jJSIiIqJFNM2D/6AWNRw7+2z9YyYiIiKiney+K17y0klOj6klLaTcHOioH4uofrb2GfvHTUREREQ7VV3GTli3nEWWmw911I/FdYJ/3ERERES0E01Ha98hlrKwuv8dcU6/Zfr2vym2z9o/diIiIiKad3UBu3R2IYuqtM0TdcE97elF1/7v7r8Tf2xQl/rHTkRERETzrC5er5tZxEIrOV31rCX36b+qe5X6YwN7nX/8RERERDSvJrm5XSxiIZU2PTS75D6t+zHx54RUP3P/+ImIiIhoHpXc/JxcxKLKzWVqyT2s/pj6c4Kyz94fAxERERFtZ6UdfF1pmyfVEhZRyekeveA+o/tjxJ8bkX329gz8cRARERHRdlWXwpPVAhZWTufOLrbCufLPDcqegT8OIiIiItqOSh58l1q8wsrp5pmF9mhulj9HUPYs/LEQERER0bFWcspq6YqotOnxSZtOEQutVv/Yw3+O/vmisWfhj4WIiIiIjqUyHPxztXCFNWqukAvt0difo36uoOyZ+OMhIiIioq30yffv+j29+hu2hukBuchuQPfnip8zInsm9mz8MRERERHRZhu36b+qRSusnC6ZXWA34RL5cwZlz8YfExERERFtpkOj479JLVhh5XTXzOK6FXfJnzsoe0b+uIiIiIhoo9VF6vTZxSq0nM6eWVq34mz5c8d1uj8uIiIiItpIk9z8dbFUhTVtmxvF0rol3c8lfo2w6rPyx0ZEREREz1ddni6XS1VMj9m/SEEtrVvR/Vz155z5NeKqz8ofGxEREREdrbo4/YRcqKLKzX61sB6b+nOqXyuq+sz88RERERGRavyJ9IK6NBW5TAVUcrpPL6rHrvu5xa8ZUn1m9uz8MRIRERHRbKVtflkuUkHVZfQitaRuh+7nFr9mVPbs/DESERER0bO7f1/6FrVARVXy4E61oG6n7tcQv3ZU9gz9cRIRERHR003bdJZanqKqS+gH1HK6nbpfQ/zaUdkz9MdJRERERNahNr1WLU5R1YXuerWYzkP3a4mvISp7lv5YiYiIiGjSpqvV0hRT+uLBPDhJLaXz0P1a9dfUX0tE6Wp/rERERESrXWkHb9QLU0xlmEZqIZ2n7tcUX0tU9kz98RIRERGtZne1L3thyekBtSxFVBfOqVpEd0L3a4uvKSJ7pvZs/TETERERrV7j3Py6WpSiKm36qFpCd0L3a4uvKSp7tv6YiYiIiFarA8O1b1ULUlTjYXO7WkB3Uvc1iK8tKnvG/riJiIiIVqdxbs5Ty1FYo+Z9avncUfY1qK8tKHvG/riJiIiIVqPJsPk7ajGKato218nFcwG6r0V8jWHVZ+2PnYiIiGj5m+TmBrkURZTTI/Xrfdfswrk43dfyiPxaI6rP2h87ERER0XJXl583rVuGAis55fXL5mJ1X5P4WgN7kz9+IiIiouVsvC8NStt8TixCIZU2jdWiGUH3tYmvOSJ75vbs/TUgIiIiWr7qcva/1SIUVcmDC9SSGUH3tYmvOSp79v4aEBERES1X45z+nFqA4kq3qQUzFPsa5dcek70D/joQERERLU8lp4+o5SeuwRlyuYzEvkb5tcdk74C/DkRERETL0TSnv68Wn7ByumbdUhnXNfJ7CMreBX8tiIiIiPrfpE23qKUnopLtb5ZL7xQLZUz1az38NevvJ550i78WRERERP2uLjZv0QtPUMO0Vy6UkdnXrL6XsNJb/PUgIiIi6mf37X/pS+pS86heduIpuTkgF8ke6L528T3FlB61d8NfEyIiIqL+VZead65fcuIq7eB8tUT2Qfe1i+8psHf6a0JERETUrw7sXfsOsdyEVdr0KbVA9kn3PYjvLSp7R/x1ISIiIupP42FzqVpuIiq5ebIuiqfNLo49dFr3vYjvMSJ7R/x1ISIiIupHdYl53exSE1nJ6SqxNPZS972I7zGw1/lrQ0RERBS/SW5uFwtNSCU3D6uFsc+670l8ryHVd8VfGyIiIqLY1SXr5+RCE9S0bS5Ty2Kfdd+T+F6jsnfGXx8iIiKimI2H6Q/36X8jOmnTPWpRXAr2vcnvOR57Z+zd8deIiIiIKF4lp/eoRSaudK5cEpeBfW/ye47J3h1/jYiIiIhiNR6mv6wWmLjSzXJBXCb2PcrvPSZ7h/x1IiIiIopTyWmolpeY0uPVKXI5XCb2PXbfq/oM4rF3yF8nIiIiohiN2/TP1OISVh5cKRfDpVS/V/UZBGXvkr9WRERERIvtqat3/e7SprvV0hJSTg+sXwaX3gPyswjI3iV7p/z1IiIiIlpckzb9klpYopqO0iViEVxq3fcsPou40i/560VERES0mKb5+G/Ui0pQOd01uwSukLvkZxKUvVv+mhERERHtfJPcnKaWlLByOntm+VslZ8vPJKr6bvlrRkRERLSzTfatfbdcUIIqufmkWP5WSvcZiM8mrPqO+etGREREtHPVRWT/usUkqtw8VnI6WS1/q+TwZ9A8Jj+jmPb760ZERES0M5VR83qxlIQ1zs3lavFbRd1nIT6jqOxd89eOiIiIaL6NL0ovKG0zVktJUPephW+l2WeiP6tw7F2zd85fPyIiIqL5NW2bt6mFJKr69V4kl70V1n0m4rOKyt45f/2IiIiI5tN4T/oWtYjENbhTLXqo7LORn1lM9u75a0hERES0/ZVhOkstIVGVPPiAXPLwW91nIz6zqOzd89eQiIiIaHsbt+m1agGJapzTDWrBwzO6z0h8dlHZO+ivIxEREdH2Vdp0tVo+Iqpf6xdLOzhJLXd4hn1G9lmpzzAiewf9dSQiIiLansY5/Su1eEQ1bdNILXZYr/usxGcYlb2L/loSERERHVsP7vnaP1Byul8tHTGlqVrocBT2mcnPMh57F+2d9NeTiIiIaOvVReh/qIUjqukofXTdIoej6j4z8VmGVd9Jfz2JiIiIttZ07/F/Si4aUQ2b22eXOGyQfXbqMw3K3k1/TYmIiIg2X10ozp1dMCIrbfN+ucTheXWfnfhMAzvXX1MiIiKizVUXiR+YWSxCq4vadWqBw8Z1n6H4bAP7AX9diYiIiDZeXSKun1kq4srpkZKbE2cXN2yOf4aPyM84puv9dSUiIiLaWKVt/q1YKsIqbcqzSxu2pvssxWcclb2r/toSERERHb2DudldcvNZtVQEVdTChmNgn6n+rMOxd9XeWX99iYiIiI5cXRz+l1oowsrpgnWLGo7VBfKzDsreWX99iYiIiHT37U/fphaJqEpOnxZLGrZB99mKzzwqe3f9NSYiIiJa36Tt11/Jm+TBmWpJw3aon636zMNKF/hrTERERPTcpqP0Q3qBiCpdoxc0bBv7jOVnH5O9w/46ExERET1TXWpuVstDROO2+dw4pxPkcoZtY5+xfdbqGcSUbvbXmYiIiOhw42F6i14cYipt2qsWM2y/7rMWzyAqe5f9tSYiIqJV7+5LX/SSktOjammIqC5eB9VChvnpPnPxLCKyd9neaX+9iYiIaJUbD9M71cIQ1+B8tYxhjuwzl88iJnun/fUmIiKiVW3Srr1GLQpRlWG6VS5imLvusxfPJK611/hrTkRERKvYJDeX6CUhnpKbJ6ejdJpawjB/9tnbM1DPJqT6bvtrTkRERKtWXQT+sVwQwkpXqQUMO8iegXw2QdV33F93IiIiWqVKbn5bLgcxPSwXL+w8exb6GYVj77i/7kRERLQq1QXgP6vFIKrSNh+TSxd2XPcsxDOKyt51f+2JiIho2Rtfnv5QvfyfUEtBTOketXBhgeyZyGcVj73r9s77609ERETLXGmbk9RCEFZuzpPLFhaoPhP1rIKyd95ffyIiIlrWDo3SX1KLQFzpZr1oYeF69K+MNvbu+zEgIiKiZaxP/zrX+rV+edqmU+SShYWzZ2PPSD27iOzd92NAREREy1ZdTP6pWgDiGlypFiwEYs9IPruY7Az4cSAiIqJl6ak9u76iLiZ3qcs/pvTguqUKMdmzks8woHoG7Cz4sSAiIqJlqF7wvygv/qDGw3Tpc5YphNU9K/EMw6pnwY8FERER9b3p5cd9g7zwo7K/8iwWKoTWo/9vQfOUnQk/HkRERNTnJm06VV32UY2H6RyxSCGw7pmJZxlXOtWPBxEREfW1A8O179YXfVC5+aRapNAH9dmpZxqUnQ0/JkRERNTHStvsU5d8RCU3Xyo5nayXKERnz86eoXq2EdnZ8GNCREREfasMm9erCz6s3FyuFij0SX2G6tkGZWfEjwsRERH1pQMfWvuqkpuxutwjql/r/XpxQt90z1I844jsjNhZ8WNDREREfai0zdvUxR7VtG0uUksT+qd7luIZR2VnxY8NERERRW/cpj+mLvS4BneqhQk9Zs9UPuuY7Mz48SEiIqLIlbZ5v7rMo5q26QNyWUJvdc9UPOuo7Mz48SEiIqKojXP6W+oijyvdoBYlLAF7tvKZx2Rnx48RERERRazkdJW6xEMapS9O28FJcklC73XPtj5j+ewDsrPjx4iIiIiiVZeLf6ku8KjqYrFvdjnCcumesXj2YdUz5MeJiIiIovTA1S/82npJ3ycv74CmbZo+eyHC8uqetXgHQqpnyM6SHysiIiKK0KRNvyYv7qBKmz46uxBhOXXPWrwDcaVf82NFREREi24y2v0n9YUdVG5uVwsRlll95updiKqeKT9eREREtMgmbTpHXtZBdf/4M7kMYVn17R95Z2fKjxcREREtqtKufb++qGMqOX1CLUJYft2zF+9EVHa2/JgRERHRIiq56dHykB6ZDAcnqiUIK8Cevb0D8t2Ix86WHzMiIiLa6aa5+Wl1QUdVhqmVCxBWRvcOiHcjKjtjftyIiIhop/rs1WvH1Yv44dmLOazcFLX4YBXVd0G9IzE9bGfNjx0RERHtRNNR85viUo4rpwvWLzxYURfIdyQoO2t+7IiIiGjejYfp29SFHFXJzafFsoMV1r0T4l2Jys6cHz8iIiKaZ6Vnf0Vs0g7OVMsOVpi9E/JdicnOnB8/IiIimlfjYfohdRFHVReEa+Wig5XXvRvinYnKzp4fQyIiIppHdTm4WV3CEZW2+VxdaE6YXXAAd0L3joh3JyI7e34MiYiIaLsbt+nfqws4rrRXLDfAM+wdke9OTHYG/TgSERHRdnVo9OLjS5u+qC7fmNJBudgAs+xdke9QPHYG7Sz6sSQiIqLt6PBCoC/fmAbnr1toAMXeFfkOBVW/Zj+WREREdKxN8tqr5YUbVrp13TIDHI29M/JdCqqeST+eREREdCzVReBiednG9OS4TaevW2SAo+jemfruzLxLcdUz6ceTiIiItlrJzT+SF21UOV317AUG2ISr5DsVlJ1NP6ZERES0lfr0b5CqX+vDYnkBNqx7h8S7FZGdTT+mREREtNlK2/wndcGGlZuPqeUF2Lj6Dql3Kyg7o35ciYiIaKM9sK95eb1Ev6wu14hKbu7ViwuwOd27JN6xiOyM2ln1Y0tEREQbado271YXa1i5OU8tLcDm1XdJvWNB2Vn1Y0tERETP16E2fae6UKMqOd2iFxZga7p3SrxrUdmZ9eNLRERER2uSmz3qMo0pfXmc06lqWQG2qnun6rul37mA6pn140tERERHarIv/ai8SKPKgyvVogIcu/puqXcuqnp2/RgTERHRbHv27PqKSZs+Iy/RgEpOD+oFBdge3Tsm3r2Y0mfsDPtxJiIiomc3zukX9QUaVbpULSfAtrF3TL57MdkZ9uNMRERET3fP3uO+QV2cUZWc7paLCbDNundNvINR2Vn2Y01ERERWvdBPVZdmXOmc2YUEmAt71+Q7GFQ9y36siYiIaDJc+2vywgyqtOmmdcsIMEfdOyfexbDqmfbjTUREtNqVnPbJyzKmL9Wv92S1jADz0r1z9d2beRfDsjPtx5uIiGh1K23z4+qiDCs3l6tFBJi/+u6pdzIoO9t+zImIiFavu/e/9PfVy/CguiQjKrm5Xy8gwM7o3kHxbkZkZ9vOuB93IiKi1apehP9dXZBh5XTx7OIB7LCL5bsZlJ1xP+5ERESr08Hc/FF1MQZ2p1g6gJ1n76J+R0Oys+7HnoiIaDUquXmfuhSjKqP0Qbl0ADusexfFOxqVnXU/9kRERMvfdJj+proQw8rphtllA1iwG+S7GpSdeT/+REREy92kTR9Xl2FIOT06bQcnzSwZwEL5O/mofGdDSh/3409ERLS81Qvvp/RFGFNp077ZJQOIoHs3xTsbV/opHwNERETL131XvOhr6mV3SF+C8ZRcv1axYABRdO+oeHdjSodsBvg4ICIiWq7qRfd2fQHGVNp0oVougCi6d1S8u3Glt/s4ICIiWp4m7e5X6osvqFFzu1osgHDsXVXvcFi7X+ljgYiIaDmqF/LZ+tKLqQzTWesWCiCg7l0V73BYdRb4WCAiIup/pV37fnnhBVVy+sTsMgFE1r2z4l2O6tC+te/z8UBERNTvpm26Tl12IeX0hUkenDi7SACxde/sF+Q7HZDNBB8PRERE/a3k5qfVRRdVyaldv0QA8XXvrnino7LZ4GOCiIiofx3Ys3ZcvcweVpdcRPVrnagFAuiL7h0W73ZENhtsRvi4ICIi6lf1IvtNdcHFlS5QywPQG/YOy3c7JpsRPi6IiIj608G9zZ9VF1tUpW0+LRcHoGe6d1m841HZrPCxQURE1I9Kbj6sLrXAzlRLA9A79i7rdzwkmxU+NoiIiOI3bdPfUxdaWDldu25ZAPrtWvmuB2Uzw8cHERFR7EqbblKXWUTTtvncpE0niEUB6K/6Th9+t/V7H43NDB8fREREcauX7L9TF1lcabhuSQCWgb3b8p0Pqs4OHyNERETxmg6PW6uXVW/+ofV1ETj4nMUAWDb2jst3P6A6O2yG+DghIiKKVb2o/q+8wMIanP+cpQBYNvaOy3c/qDpDfJwQERHFabJv97fLiyuo0qZb1y0FwBLq3nVxBsKqs8THChERUYzqZXqRvLQiyvaf6XS1FABLp3vXZ85AYDZLfKwQEREtvjJa+2F1YUVVL9Kr5UIALKnunRdnISqbKT5eiIiIFltpm9vUZRXUw2oRAJaevfv6TIRjM8XHCxER0eKats3PqosqqpKbPXIJAJZc9+6LMxGVzRYfM0RERDvfwcual9cL6fHZCyqwe9UCAKwMOwP6bET0uM0YHzdEREQ7Wxk27xaXU1y5OU9e/sDKqGdAnY2gbMb4uCEiItq5xm36TnUxRVVyukVf/MBq6c6COCNR2azxsUNERLQz9el/7zfO6Yn6n6eqSx9YOfUs+JmQ5yUamzU+doiIiOZfvSR/VF1IUZU8+Li88IEV1Z0JcVaispnj44eIiGh+PfX+Xb+r5PQZdRlFVNr0oLrogVXXnQ1xZiKymWOzx8cQERHRfKoX5H9RF1FU01G6dPaCB5B+qzsb4syEVWePjyEiIqLtb7Jn9yvkBRRWunv2cgfwLHZG5NkJqs4gH0dERETbW70UT5GXT1jpHHm5AzjMzog8O1GlU3wcERERbV+lHfxVffHEVNp0k7zYATxHd1bEGYrKZpGPJSIiou2pXoYjdekE9aX69b5XXeoAnqs7K/XMzJyhsGwW+VgiIiI69kq79i/UhRPWqLlcXegAjsDOjDpLQdlM8vFERES09e7c8/LfW3JzQF02MaX75UUO4Ojs7MgzFY/NJJtNPqaIiIi21jQ3/01dNGHldPG6CxzARlwsz1RQNpt8TBEREW2++y5vvlldMGHZv8hCX+AANqY3/zIYYzPKxxUREdHmqhfJmbMXS2TTnD4oLm4AG9SdIXG2AjvTxxUREdHGm46a7xGXSlglNzeqixvA5nRnSZyxqGxW+dgiIiLaWPUCuXL2QomqtOnRktN71KUNYHPsLNmZUmctqCt9bBERET1/kza9QVwmYdVLeZ+6sAFsTXemxFmLK73BxxcREdGRu+0jL/qaemlM9WUST72QD6mLGsCx6c6WOHMxpanNLh9jREREuvEwvV1fJDGVnC5UlzSAY9OdLXHmorLZ5WOMiIhofZN29yvVBRJWbu5QFzSA7VLPmDp7Ye1+pY8zIiKi51YvtrP15RHTtE1nrb+YAWyX7oyJsxdWnWE+zoiIiJ6p5MH3yYsjqmG6fvZSBjAHdtbUGQzKZpmPNSIiosOVnK5Tl0ZE9Wv9wmQ0OFFeygC2Vz1r3ZkTZzEim2U+1oiIiGzJbf6NujCiKqPUygsZwFx0Z06cxahspvl4IyKiVe7eK49/cb0UHlKXRUi5maiLGMC81bOnzmRANtNstvmYIyKiVa20zf9UF0VUJaeP6EsYwDx1Z0+cyahstvmYIyKiVezQqPkz6oKIato2n1YXMICd0Z1BcTajshnn446IiFatehGcP3sxhJab96nLF8BOqWdQnc24zvdxR0REq9S0bf6uuBQiu1ZfvAB2lJ1FfUZDslnnY4+IiFalSW4+qS6FoD5fL9gT1l24ABbhhO5M6rMaT511PvaIiGgVqhfVz8gLIaiS03DmogWwQN2ZFGc1rDrzfPwREdEyN7lydzNp0yPyMghonNN49pIFsHjd2RRnNqY68+rs8zFIRETLWh3479AXQUwlDz6sLlkAi9WdTXFm40rv8DFIRETLWBkNXqUvgKjSreqCBRCEnVF5dmOyGejjkIiIlq1pmy5Uwz+qMhycIS9XACF0Z1Sc3ahsBvo4JCKiZapeSD+sBn9c6Wp1sQIIxs6qPMMx2Sz0sUhERMtSyek2NfQjKrn5rLxQAYTUnVlxliOyWehjkYiIlqHSNj+rBn5UZdjsUZcpgJi6MyvOclQ2E308EhFRnzvQrr2sDvXH1bCPaDxsDqiLFEBs3dkVZzoim4k2G31MEhFRXyu5OVEN+qimbXOeukQBxNadXXGmo7LZ6GOSiIj62MHc/EU14ONKt6gLFEBP2BmWZzsmm5E+LomIqG+V3HxMDfeISk5PTNt0qrw8AfSCnWE7y+qMR2Qz0sclERH1qckw/RM12OMafFxdnAB6xs6yPONB1VnpY5OIiPrQU0/t+p2T3Nwph3pI6UF5YQLoJzvT8qwHVGelzUwfn0REFL16yfyCHOhBlTy4TF6WAHqpO9PirMeVfsHHJxERRW4y2v31epBHle5WFyWAnrOzLc98UHV2+hglIqKolTa9Vw7xsNI58pIE0G92tuWZj8lmp49RIiKKWGkHf0UN8LjSTfKCBLAc7IzLsx+TzVAfp0REFK2SU6uGd0T2byYqw/ReeTkCWAp2xvv0b2a0GerjlIiIIjXNaz+mBndYw+YKdTECWDJ21tUMCMpmqY9VIiKK0JO3veIrJ226Vw3tkHK6f91lCGCZ3S9nQUjpXpupPl6JiGjRTUfNW/XADmqYLhEXIYBlZWdezYKgbKb6eCUiokV2cG/zzWpQR1Vy+oy8CAEste7si5kQlc1WH7NERLSo6kA+Y3ZAR1ZG6YPqEgSw3LqzL2ZCYGf4mCUiokV0cG/zPWI4h1Vyc6O6AAGshm4GiNkQlc1YH7dERLTT1UvjSjWcIyo5PTbN6T3q8gOwGmwG2CxQMyIim7E+bomIaCcbt+kNajCHldP+2UsPwEraL2dEUDZrfewSEdFOdGj04t9f2jRVQzmknA7NXHQAVtshOSsCsllrM9fHLxERzbt6SfyqGshRTdt04cwlB2CFdTNBzIqw6sz18UtERPOs5MGfkIM4qGnb3DF7yQFANxvEzIjKZq+PYSIimlcl9+sf0VPadJa65ACstm42iJkRlc1eH8NERDSPynDwt9UAjitdry44AOjYjJCzIyabwT6OiYhouyttulYN35By+kK9FN697mIDAOcz4gtyhgRkM9jHMRERbWelXfvXavBGNc2pnb3UAGBWNyvEDInKZrGPZSIi2o4e2v/SF5U2PaiGbki5magLDQC0OjPULAnIZrHNZB/PRER0rNXh+huzwza0UfqIvswAQLCZoWZJXL/h45mIiI6lQ+3anxZDNqySm9+WFxkAHEU3O8RMicpms49pIiLaapPcfEgN2ajqZfU+dYkBwNF0s0PMlLDqbPYxTUREW6kO0h+UAzaocW6uUxcYAGxEN0PEbAmrzmgf10REtNnqIL1x3WCNKg8+X3LzLnV5AcBGHJ4hg8/LGRPTjT6uiYhoM01G6c1iqAY2GKqLCwA2xWaJnDFB1VntY5uIiDbSZM/upg7Q3vxVjdKmsbywAGALupkiZk1Qn7eZ7eObiIierzro3yGGaWCDD89eVACwZTZT5KwJqs5sH99ERHS0yt7Bq+QgDaq06bZ1lxQAHKNutoiZE5XNbh/jRER0pEpOF6ohGlUZDs5QlxQAHItutoiZE5XNbh/jRESkKu3gH6oBGle6Wl1QALAtbMbI2ROTzXAf50RENFtp061qeEZUcvPZyUhcTACwXeqM6WaNmEER2Qz3cU5ERM+uDvP/qAZnWLnZIy8mANhWddaoGRSUzXIf60REZN07PP4Plpy+pIZmRHWQH9AXEgBsv27miFkUkc1ym+k+3omIaGL/NiAxMMMaNR9SlxEAzIXNHDWLoqoz3cc7EdFqNx02f0EOyqhyumXdJQQA83eLnElB2Wz3MU9EtLrVgXjZ7IAMKzdP1MvmtJnLBwB2Qp09dQap2RTTZT7miYhWszoIf2RmMIZW2vRxcfkAwI7oZpCYTYH9iI97IqLV6qmndv2OOgTvmBmKYZWcHlIXDwDspG4WiRkV1B02633sExGtTpM2/bwYioENLlOXDgDsKJtFckZFlX7exz4R0WpU2sHX6YEYU2nTPfLCAYAF6GaSmFVR2cz38U9EtPyVnE5WwzCsnM6dvWgAYIHOlbMqKJv5Pv6JiJa7Q/sG36UGYVzpJnHJAMBi2WySMysmm/1+DRARLW91OGc1BCMqbfP4ZJhOkZcMACxSnU3djBKzK6aU/RogIlrOSh78mB6AYV0hLxgAiMBmlJ5dIdkd4NcBEdFyddtHXvGV9Xf0vfkbKEpOD8iLBQAC6WaVmGExpXvsLvBrgYhoeSq5easefDGNc7pEXSoAEEk3q8QMi8ruAr8WiIiWowN71v6IGnhRlZzuUhcKAETUzSwxy6KyO8GvByKi/leGzRlq2EU1HaUPqssEACLqZpaYZVHZneDXAxFRv5u2zd9Qgy6s3NyoLhIAiK3OLjXTgrK7wa8JIqL+Vgdaf/6u4Nw8Nh2l9+hLBADiOjy7msfkbIvpCr8miIj6WR26PymGW1jTttmvLhAA6INuhonZFla9I/y6ICLqV5M9u7+6DrGJHG4BTdt0SF0cANAn3SwTMy4kuyPqXeHXBhFRfyo5/YocbEGVNl2kLg0A6JNulokZF5XdFX5tEBH1o7J38MfVQAvsDnVhAEAv2UzTsy4kuzP8+iAiil9p0wfUMItq2g7OkpcFAPRQN9PErIvK7gy/PoiIYldGg+9VgyyudL26KACg12y2yZkXk90dfo0QEcWt/s78GjXEYkpfnLaDd8tLAgB6rJttdcbp2ReP3R1+jRARxawO1jeqARZVHawjdUEAwDLoZpyYfVHZHeLXCRFRrB5qX/bCOlgfUMMromnbTGYvBQBYNt2sEzMwpHqH2F3i1woRUZwmufl1ObiCGg/TR2cvBABYNt2sEzMwrHqX+LVCRBSj6f61b5UDK6iSm99WFwIALKNu5olZGJXdKX69EBEtvjqYzpsdVJHVof8+dRkAwDLqZp6YhYGd59cLEdFiO5ibHxRDKqw68K9TFwEALLNu9omZGJXdLX7NEBEtrjo8b1RDKqKSB49MRs271CUAAEutzr5uBorZGJHdLX7NEBEtpskwvVkNqKgOjdJQXgAAsAK6GShmY1j1jvHrhohoZyuXDtIkN5+Xwymg0qaxGvwAsEq6WShmZEj1jrG7xq8dIqKdqw7L/yMHU1iDD6uhDwArxWahnJEx2V3j1w4R0c5U2sGfVwMpqjoob5MDHwBWUDcTxayMyu4cv36IiOZfHZL9+geQt4Mz1LAHgJVkM1HOypjszvHrh4hovpU8+AdqEEVVB+Q1ctADwArrZqOYmVHZ3ePXEBHR/Co5fUoNoaA+O2nTO9WQB4CVZrOxm5FydoZjd49fQ0RE82maB/9BDaCwcrNHDngAQFVnpJqdQdkd5NcREdH2dt8VL3lpHYyPqeETUm4OrB/qAIDnqrNSzdCI6h1kd5FfS0RE21cdMiesGzqR5eZD6wc6AOC56qxUMzSuE/xaIiLanqajte8Qwyas7n9HLAc6AGBWz/7ei6fsTvLriYjo2KuD5dLZQRNVaZsn6uA+bXaQAwCO6LRudoqZGtSlfj0RER1bdaC8bmbAhFZyukoMcQDAUXSzU8zUwF7n1xQR0dab5OZ2MWBCKm16SA1wAMDz62aomK0h1bvJrykioq1VcvNzcsBElZvL1PAGAGxEnaFqtgZld5RfV0REm6u0g68rbfOkGi4RlZzu0YMbALBR3SwVMzYiu6PsrvJri4ho49Vhd7IaLGHldO7swAYAbNq5csYGZXeVX1tERBur5MF3qYESVk43zwxqAMDW3SxnbVB2Z/n1RUT0/NXfIWc1TCIqbXp80qZTxKAGAGxFnamHZ6ueu9HYneXXFxHR0SvDwT9XgySsUXOFHNQAgK2z2apmblB2d/k1RkSk++T7d/2eXv2NCMP0gBzQAIBj1s1YMXsjsrvL7jC/zoiI1jdu039VAySsnC6ZHcwAgG1ziZy9Qdkd5tcZEdFzOzQ6/pvU4Agrp7tmBjIAYPvdJWdwUHaX+bVGRPRMdUCcPjswQsvp7JlhDADYfmfLGRzX6X6tEREdbpKbvy6GRVjTtrlRDGMAwBx0M1fM4rDqnebXGxFRt+heLodFTI/ZPyBcDWMAwPbrZm6dvTOzOK56p/n1RkSrXh0IPyEHRVS52a8GMQBgnursVTM5qnq3+TVHRKva+BPpBXUYFDkkAio53acHMABg3roZLGZzSPVuszvOrzsiWsVK2/yyHBBB1SF7kRq+AID562awmM1R2R3n1x0RrVr370vfogZDVCUP7lSDFwCwc7pZLGZ0VHbX+bVHRKvUtE1nqaEQVR2uH1BDFwCwc7pZLGZ0VHbX+bVHRKvSoTa9Vg2EqOqgul4NXADAzutmspjVUdmd59cfEa1CkzZdrYZBTOmLB/PgJDVsAQA7r5vJdTbrmR1RutqvPyJa9ko7eKMeBDGVYRqpQQsAWJxuNouZHZXdfX4NEtGydlf7sheWnB5QQyCiOkinasACABavm9Fidkdkd5/dgX4dEtEyNs7Nr6sBEFVp00fVcAUALF43o8XsjsruQL8OiWjZOjBc+1Z18KMaD5vb1WAFAMTRzWoxw6Oyu9CvRSJapurvZM9Thz6sUfM+NVQBAIHYrFYzPCi7C/1aJKJlaTJs/o468FFN2+Y6OVABAOF0M1vM8rDqnejXIxEtQ5Pc3CAPe0Q5PVK/3nfNDlIAQFTdzH5EzvSI6p3o1yMR9b16qN+07pAHVnLK64coACCybnaLmR7Ym/yaJKK+Nt6XBqVtPicOeEilTWM1QAEA8XUzXMz2iOxutDvSr0si6mN16PxvdcCjKnlwgRqeAID4uhkuZntUdkf6dUlEfWuc059TBzuudJsanACAHrFZLmd8THZX+rVJRH2q5PQRdajjGpwhhyYAoD9slssZH5PdlX5tElFfmub099WBDiuna9YNSwBAX10jZ31Qdmf69UlEfWjSplvUYY6oZPub5dI7xaAEAPRRnemHZ7ue+/GkW/z6JKLo1QP7Fn2QgxqmvXJQAgD6y2a7mvlhpbf4NUpEUbtv/0tfUg/ro/oQx1N/x39ADkgAQO91M17M/pjSo3aH+nVKRBGrh/Wd6w9vXKUdnK+GIwCg/7oZL2Z/YO/065SIonVg79p3iEMbVmnTp9RgBAAsj27WizsgKrtL/VolokiNh82l6tBGVHLzZB2Ap80ORADA0jmtm/niLojI7lK/VokoSvVwvm72sEZWcrpKDEMAwBLqZr64CwJ7nV+vRBShSW5uFwc1pPo7+4fVIAQALK9u9os7IaR6p/r1SkSLrg6Pn5MHNahp21ymhiAAYHl1s1/cCVHZ3erXLBEtqvEw/eE+/W+fJm26Rw1AAMAKsDtA3g3x2N1qd6xft0S0iEpO71EHNK50rhx+AIDlZ3eAvBtisjvWr1si2unq7zT/sjqYcaWb5eADAKwOuwvkHRGT3bV+7RLRTlZ/pzlUhzKm9Hh1ihx6AIDVYXdBdyeouyIeu2v92iWinWrcpn+mDmRYeXClHHgAgBVU7wR1VwRld65fv0Q07566etfvLm26Wx3GkHJ6YP2QAwCsuAfknRGQ3bl29/o1TETzbNKmX1IHMarpKF0iBhwAYIV1d4O4M+JKv+TXMBHNq2k+/hv1AQwqp7tmhxsAAO4ueXcEZXewX8dENI8muTlNHb6wcjp7ZqgBAPC0s+XdEVW9g/06JqLtbrJv7bvlwQuq5OaTYqgBAPD/dXeFuEPCqnexX8tEtJ3VA7Z/3YGLKjePlZxOVkMNAICnHb4rmsfkXRLTfr+WiWi7KqPm9eKwhTXOzeVqoAEAMKu7M8RdEpXdyX49E9GxNr4ovaC0zVgdtqDuU4MMAIAjsrtD3ynh2J1sd7Nf00R0LE3b5m3qoEVVv96L5BADAOAIurtD3ClR2d3s1zQRbbXxnvQt6oDFNbhTDTAAAJ6X3SHybonJ7mi/roloK5VhOksdrqhKHnxADi8AAJ5Hd4eIuyUqu6P9uiaizTZu02vVwYpqnNMNanABALBR3V0i7pio7K72a5uINlNp09XqUEVUv9YvlnZwkhpaAABslN0ldqeouyYiu6v92iaijVZ/R/uv1IGKatqmkRpYAABsVneniLsmKruz/fomoufrwT1f+wdKTverwxRTmqpBBQDAltndIu+ceOzOtrvbr3EiOlr1gP8PdZCimo7SR9cNKAAAjkF3t4g7J6x6d/s1TkRHarr3+D8lD1BUw+b22eEEAMC2sDtG3T1B2R3u1zkRqepBOXf24ERW2ub9cjgBAHCMujtG3D2BnevXORHNVg/ID8wcmNDqALpODSYAALZLd9eIOyiwH/BrnYieXT0c188clrhyeqTk5sTZgQQAwHbyu+YReRfFdL1f60T0dPV3rP9WHJawSpvy7DACAGAeujtH3EVR2Z3u1zsRHczN7vo71s+qwxJUUYMIAIC5sbtH30nh2J1ud7tf80SrXT0Q/0sdlLByumDdAAIAYL4ukHdSUHa3+zVPtLrdtz99mzogUZWcPi2GDwAAc9fdQeJuisrueL/uiVazSduv36FO8uBMNXwAAJi/egepuymsdIFf90Sr13SUfkgfjKjSNXrwAACwQ+wukndUTHbX+7VPtFrVw3qzOhQRjdvmc+OcTpBDBwCAHWJ3kd1J6q6KKd3s1z7R6jQeprfoAxFTadNeNXAAANhp3Z0k7qqo7M73659o+bv70he9pOT0qDoMEdWBclANGgAAFqW7m8SdFZHd+Xb3+xpAtNzV39m9Ux2EuAbnqyEDAMDC2N0k76yY7O73NYBoeZu0a69RByCqMky3ygEDAMCCdXeUuLviWnuNrwNEy9kkN5folz+ekpsnp6N0mhouAAAsmt1RdlepOyykugP4OkC0fNUX/B/LFz+sdJUaLAAAhGF3lbzDgqq7gK8FRMtV/V3nb8uXPqaH5UABACAau7P0XRaO7QK+FhAtT/XF/s/qhY+qtM3H5DABACCY7s4Sd1lUthP4ekDU/8aXpz9UX+on1MseU7pHDRIAAMKyu0veafHYTmC7ga8JRP2u/k7zJPWih5Wb8+QQAQAgrHp3qTstKNsNfE0g6m+HRukvqRc8rnSzHiAAAATXo3+1vrEdwdcFon5WD11v/jWFpU1fnrbpFDk8AAAIzu4wu8vUHRdT2uvrAlH/qgfun+oXO6rBlWpwAADQG3aXyTsuJtsVfG0g6k9P7dn1FfXA3aVe6pjSg+uGBQAAfWR3mrzrAqq7gu0Mvj4Q9aP64v6ifKGDGg/Tpc8ZEgAA9FR3p4m7Lqy6M/j6QBS/6eXHfYN8kaOyv/IsBgUAAD3Wo/+vavOU7Q6+RhDFbtKmU9VLHFX9ne85YkAAANBb3d0m7ry40qm+RhDF7cBw7bv1CxxUbj6pBgQAAP1X7zh19wVlO4SvE0QxK22zT728EZXcfKnkdLIeDgAA9JvdcXbXqTswItshfJ0gilcZNq9XL25YublcDQYAAJZHvevUHRiU7RK+VhDF6cCH1r6q/q5xrF7aiOrXer8eCAAALJfuzhN3YUS2S9hO4esFUYxK27xNvbBRTdvmIjUMAABYNt2dJ+7CqGyn8PWCaPGN2/TH1Isa1+BONQgAAFhadvfJOzEm2y18zSBabPV3Xu9XL2lU0zZ9QA4BAACWVHf3iTsxKtstfM0gWlzjnP6WekHjSjeoAQAAwNKzO1DejTHZjuHrBtFiKjldpV7OkEbpi9N2cJI8/AAALLnuDqx3obwjA7Idw9cNop2vHpp/qV7MqOqB2Td76AEAWCXdXSjuyLDqruFrB9HO9cDVL/za+vLdJ1/KgKZtmj77oAMAsKq6O1HclSHVXcN2Dl8/iHamSZt+Tb6QQZU2fXT2oAMAsIq6O1HclXGlX/P1g2j+TUa7/6R+EYPKze3qoAMAsLrq3ajuzKjq7uFrCNF8q7+zOke+hEF1//gzecgBAFhNfftHg9ru4WsI0fwq7dr36xcwppLTJ9QBBwBg1XV3pLg7o7IdxNcRovlUctOjQ5EemQwHJ6rDDQDAyrM70u5KeYfGYzuIryNE2980Nz+tXryoyjC18mADAIBOd1eKOzQq20V8LSHavj579dpx9QV7ePaFCys3RR1oAAAwq96Z6i6N6WHbSXw9IdqepqPmN8XLFldOF6w/yAAAQLhA3qVB2U7i6wnRsTcepm9TL1pUJTefFocYAAAcQXd3ijs1KttNfE0hOrZKz36nN2kHZ6pDDAAAjsDuTnmnxmS7ia8pRFuv/o7ph9QLFlV98a+VBxgAABxVd4eKuzUq21F8XSHaWvWlv1m9XBGVtvlcPagnzB5cAACwISd0d6m4YyOyHcXXFaLNN27Tv1cvVlxprzi0AABgo+wulXdsTLar+NpCtPEOjV58fGnTF9VLFVM6KA8sAADYHLtT5V0bj+0qtrP4+kK0sQ6/6Pqlimlw/rqDCgAANs/uVHnXBlW/Zl9fiJ6/SV57tXyRwkq3rjukAABg6+xulXduUHV38TWG6OjVF/xi+RLF9OS4TaevO6AAAGDLuru13rEzd25cdXfxNYboyJXc/CP5AkWV01XPPpgAAGDbXCXv3qBsh/F1hkjXp38zSv1aHxaHEgAAbJPurhV3cES2w/g6Q7S+0jb/Sb04YeXmY+pQAgCA7VLvWnUHB2W7jK81RM/0wL7m5fXl+LJ6aSKqv2u7Vx9IAACwnbo7V9zFEdkuYzuNrzdEh5u2zbvVCxNWbs5ThxEAAGy3euequzgo22l8vSHatetQm75TvShRlZxu0QcRAADMQ3f3ijs5KtttfM2hVa/+Tm2PekliSl8e53SqOoQAAGA+uru33sH6bg6o7ja+5tAqN9mXflS+IFHlwZXqAAIAgHmrd7C6m6OqO46vO7SK7dmz6yvq784+I1+OgEpOD+qDBwAAdkJ3F4s7Oqb0Gdt1fO2hVWuc0y/qFyOqdKk6dAAAYIfYXSzv6Jhs1/G1h1ape/Ye9w3qhYiq/g7ybnngAADAjuruZHFXR2U7j68/tCrVF/VU9TLElc6ZPWgAAGAB7E6Wd3VQdefx9YdWoclw7a/JFyGo0qab1h0yAACwMN3dLO7ssOru42sQLXslp33yJYjpS/XrPVkdMgAAsBjd3Vzv6Jk7OyzbfXwNomWutM2PqxcgrNxcrg4YAABYtHpHq7s7KNuBfB2iZezu/S/9ffUhH1QPP6KSm/v1wQIAABF0d7W4wyOyHch2IV+LaNmqD/i/qwcfVk4Xzx4oAAAQysXyDg/KdiFfi2iZOpibP6oeeGB3isMEAACisTtb3+Uh2U7k6xEtSyU371MPO6oySh+UhwkAAITS3dniLo/KdiJfj2gZmg7T31QPOqycbpg9RAAAILQb5J0elO1GviZR35u06ePqIYeU06PTdnDSzOEBAACB+d39qLzbQ0of9zWJ+lx9kD+lH3BMpU37Zg8PAACIr7vDxd0eV/opX5eoj913xYu+pj7EQ/rhxlNy/VrFwQEAAP3Q3eXijo8pHbJdydcm6lv1Ab5dP9iY6u8EL1SHBgAA9EN3l4s7Pq70dl+bqE9N2t2v1A80qFFzuzowAACgZ+xOV3d9WLtf6esT9aX6op2tH2ZMZZjOWndQAABA73R3urjrw6o7k69P1IdKu/b98kEGVXL6xOwhAQAA/dXd7eLOj8p2J1+jKHrTNl2nHmJIOX1hkgcnzh4QAADQZ93d/gV59wdku5OvURS5kpufVg8wqvo7vnb94QAAAH3X3fHi7o/KdihfpyhiB/asHVcf0sPq4YWUm4k6GAAAYDnUvWQid4CAbIeyXcrXKopWfUC/qR5cXOkCdSgAAMCSsLte7gAx2S7laxVF6uDe5s+qBxZVaZtPywMBAACWSnfni10gKtupfL2iKNXfgXxYPazAzlSHAQAALBm78/UuEJLtVL5eUYSmbfp76kGFldO16w4BAABYZtfKnSAo2618zaJFV9p0k3pIEU3b5nOTNp0gDgAAAFhW9e4/vAPo/SAa2618zaJFVl+ef6ceUFxpuO7lBwAAy892ALkbBFV3LF+3aBFNh8et1YfQm38Yc33BDz7nhQcAAKvFdgG5IwRUdyzbtXztop2uPoD/Kx9MWIPzn/OyAwCA1WK7gNwRgqq7lq9dtJNN9u3+dvlAgiptunXdyw4AAFZOtxOIXSGsunP5+kU7VX1JLpIPI6Js/5lOVy87AABYMd1OMLMrBGY7l69ftBOV0doPqwcRVX1BrpYvOgAAWEndbiB2hqhs9/I1jOZdaZvb1EMI6mH1ggMAgBVnO4LeHcKx3cvXMJpn07b5WfUAoiq52SNfbgAAsNK6HUHsDlHZDubrGM2jg5c1L68f9OOzH3xg96oXGwAAoGO7gt4hInrcdjFfy2i7K8Pm3eJDjys358mXGgAAoFN3BbVDBGW7mK9ltJ2N2/Sd6gOPquR0i36hAQAAntHtDGKXiMp2Ml/PaLvq0/+OZZzTE/U/T1UvMwAAwHPUncF3B7lXRGM7ma9ntB3Vh/+j6oOOquTBx+WLDAAAIHS7g9gporLdzNc0Opaeev+u31Vy+oz6kCMqbXpQvcAAAABH0+0QYreIyHYz29F8XaOtVh/8f1EfcFTTUbp09sUFAAB4Pt0OIXaLsOqO5usabaXJnt2vkB9sWOnu2ZcWAABgw2yXkDtGUHVX87WNNlt92KfIDzWsdI58aQEAADbCdgm5Y0SVTvG1jTZTaQd/VX+gMZU23SRfWAAAgE3odgqxa0RlO5uvb7TR6kMeqQ8zqC/Vr/e96mUFAADYjG6nqLvFzK4Rlu1svr7RRirt2r9QH2RYo+Zy9aICAABsie0WaucIynY3X+PoaN255+W/t+TmgPoQY0r3yxcUAADgWNiOIXePeGx3sx3O1zk6UtPc/Df1AYaV08XrXkwAAIBjd7HcPYKyHc7XOVLdd3nzzeqDC8v+RRb6xQQAANgOvfmXZhnb5Xyto9nqB3Tm7AcW2TSnD4oXEgAAYFt0u4bYQQI709c6enbTUfM94sMKq+TmRvVCAgAAbKdu5xC7SFS20/l6R09XP5grZz+oqEqbHi05vUe9jAAAANvJdg7bPdROEtSVvt6RNWnTG8SHFFZ92fapFxEAAGAeut1D7CRxpTf4mrfa3faRF31N/TCm+kOKp75oh9QLCAAAME/dDiJ2k5jS1HY8X/dWt/EwvV1/QDGVnC5ULx8AAMA8dTuI2E2ish3P173VbNLufqX6YMLKzR3qxQMAANgZdRdRO0pYu1/pa9/qVR/Y2fpDiWnaprPWv3AAAAA7o9tFxI4SVt31fO1brUoefJ/8QKIaputnXzYAAIAdZzuJ2lWCsp3P17/VqeR0nfowIqpf6xcmo8GJ8mUDAADYSXUn6XYTsbNEZDufr3+rUcnNv1EfRFRllFr5ogEAACxAt5uInSUq2/18DVzu7r3y+BfXb/Yh9SGElJuJesEAAAAWq+4oancJyHY/2wF9HVzeStv8T/UBRFVy+oh+uQAAABan21HE7hKV7YC+Di5nh0bNn1HfeFTTtvm0erEAAAAi6HYVscNEZbugr4XLV/0Gz5/9hkPLzfvUSwUAABBD3VXUDhPX+b4WLlf1dxx/V3yzkV2rXygAAIBAbGfRu0xIthP6erg81d9xfFJ9s0F9vr44J6x7kQAAAOI5odtd9E4TT90JfT1cjuoD+Bn5jQZVchrOvEAAAABhdbuL2GnCqruhr4n9bnLl7mbSpkfkNxnQOKfx7MsDAAAQXbfDiN0mprob1h3R18X+Vr+Rd+hvMKaSBx9WLw8AAEBk3Q4jdpu40jt8XexnZTR4lf7Gokq3qhcHAACgF2yXkTtOTLYr+trYv6ZtulB9U1GV4eAM+dIAAAD0QLfLiB0nKtsVfW3sV/WD/mH1DcWVrlYvDAAAQK/YTiN3nZhsZ/T1sT+VnG5T30xEJTeflS8KAABAD3W7jdh5IrKd0dfHflTa5mfVNxJVGTZ71EsCAADQR91uI3aeqGx39DUydgfatZfVL/Zx9U1ENB42B9QLAgAA0GfdjiN2n4hsd7Qd0tfJuJXcnKi+gaimbXOeejkAAAD6rNtxxO4Tle2Qvk7G7GBu/qL6wuNKt6gXAwAAYCnYriN3oJhsl/S1Ml51E/+Y+qIjKjk9MW3TqfKlAAAAWAK269jOo3ahiGyX9LUyVpNh+ifqC45r8HH1QgAAACwV23nkLhRU3Sl9vYzRU0/t+p2T3Nwpv9iQ0oPyRQAAAFhGtvvInSigulPabulr5uKrH94vyC80qJIHl8mXAAAAYAl1u4/YieJKv+Br5mKbjHZ/vf4Co0p3qxcAAABgqdkOJHejoOqO6evm4ipteq/84sJK58iHDwAAsMxsB5K7UUy2Y/q6uZhKO/gr6guLK90kHzwAAMAqsF1I7kgx2a7pa+fOV3Jq1RcVkf0bN8owvVc+dAAAgBVgu1Cf/g22tmv62rmzTfPaj6kvKKxhc4V64AAAACvFdiK1KwVlO6evnzvTk7e94isnbbpXfTEh5XT/uocMAACwuu6XO1NI6V7bPX0NnX/TUfNW/YUENUyXiAcMAACwmmw3UjtTULZ7+ho63w7ubb5ZfQFRlZw+Ix8wAADACut2JLE7RWU7qK+j86v+QmfM/sKRlVH6oHq4AAAAq6zbkcTuFNgZvo7Op7pJf4/4RcMqublRPVgAAADYX9Wtu5LYoaKyXdTX0u2vfhhXql80opLTY9Oc3qMeKgAAANJv2a5kO5PapSKyXdTX0u1t3KY3qF8wrJz2zz5MAAAArLNf7lJB2U7q6+n2dGj04t9f2jRVv1hIOR2aeYAAAAA4skNypwrIdlLbTX1NPfbqN/+r6heKatqmC2ceHgAAAI6g253EThVW3U19TT22Sh78CfkLBDVtmztmHx4AAACOrtuhxG4Vle2ovq5uvZL79Y+eKG06Sz08AAAAHFm3Q4ndKirbUX1d3VplOPjb6icGAAAAFs12VV9bN1/d7K9VPykAAACwaLar+tq6uUq79q/VTwgAAABEYTurr68b66H9L31R3ZAfVD8ZAAAAEIXtrLa7+hr7/NU/6TdmfxIAAAAgqN/wNfboHWrX/rT4kwEAAICwbIf1dfbITXLzIfUnAwAAAGHVHdbXWV39A35Q/okAAABAdHWX9bV2ffUPuHHdnwAAAAD0w42+1j63ySi9WfzBAAAAQH/UndbX22cqOX1K/sEAAABAT9hO6+vt4Q616bXqDwQAAAD6xnZbX3Ptb0JLZ6s/CAAAAOidutseXnJHu79e/gEAAABAX9Udd9ekTW+QPwgAAAD0VnqD/c8WflX/IAAAANBTdce1f9rCB+UPAgAAAD01bdMHdpU2XaN+EAAAAOgr23Htr+g+oH4QAAAA6Cvbce1vRntQ/SAAAADQX+lB+yu61+ofBAAAAPrJdlz+ZjQAAAAsncN/M1pOv6J+EAAAAOgr23F3TXLzk+oHAQAAgN6qO+6uyf7dr5A/CAAAAPRV3XF3WZOczpZ/AAAAANAz42E6p1tyrXGbXqv+IAAAAKBvbLf1NfdwJadb1B8IAAAA9IXttL7ePlP9gTfN/oEAAABAz7zJ19vnVn/g9Jk/EAAAAOiL032tXd/4ovSCSW4+Kf4kAAAAIKzSpptsl/W1VldGg1epPxkAAACIynZYX2eP3qG2+XH1EwAAAADR2O7qa+zGOtCuvWbSppvVTwYAAAAsXt1V89qrfX3dXJM9u7+6tM0Z+icGAAAAFqMM645ad1VfW7feJKefKTl9Sv0iAAAAwI6xnbTupr6mbl9lNPje+hOfK39RAAAAYH7OPVR3UV9L59c0H/+NZdS8vuTml6dtOqu06Zq6AD8gviAAAABg4+pOabtldZbtmrZz3js6/pt8Dd1Eu3b9P+Yf5RrHMhfgAAAAAElFTkSuQmCC\",\"data:image/png;base64,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\",\"data:image/png;base64,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Number: 2
Class: Marine (Enterococcus<\\/i>)
Category: 35 - 129 (42/100mL)<\\/html>\",\"Station Number: 6
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 7
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 8
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (6/100mL)<\\/html>\",\"Station Number: 9
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 11
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 13
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 14
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 16
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 19
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 21
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 22
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 23
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 24
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 25
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 28
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 32
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 33
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 36
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 38
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 40
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 41
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 42
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 44
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 46
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 47
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 50
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 51
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 52
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 54
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (8/100mL)<\\/html>\",\"Station Number: 55
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 58
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 60
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 61
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (4/100mL)<\\/html>\",\"Station Number: 62
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 63
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 64
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 65
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (8/100mL)<\\/html>\",\"Station Number: 66
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 67
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 68
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 70
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 71
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 73
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 74
Class: Marine (Enterococcus<\\/i>)
Category: 130 - 999 (472/100mL)<\\/html>\",\"Station Number: 80
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 81
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 82
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 84
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 90
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 91
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 92
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 93
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 94
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 95
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 96
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 97
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 101
Class: Marine (Enterococcus<\\/i>)
Category: 130 - 999 (412/100mL)<\\/html>\",\"Station Number: 102
Class: Marine (Enterococcus<\\/i>)
Category: 130 - 999 (327/100mL)<\\/html>\",\"Station Number: 103
Class: Marine (Enterococcus<\\/i>)
Category: 130 - 999 (173/100mL)<\\/html>\",\"Station Number: 104
Class: Marine (Enterococcus<\\/i>)
Category: > 999 (1020/100mL)<\\/html>\",\"Station Number: 105
Class: Marine (Enterococcus<\\/i>)
Category: 35 - 129 (50/100mL)<\\/html>\",\"Station Number: 106
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (48/100mL)<\\/html>\",\"Station Number: 107
Class: Freshwater (E. coli<\\/i>)
Category: 126 - 409 (150/100mL)<\\/html>\",\"Station Number: 108
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (123/100mL)<\\/html>\",\"Station Number: 109
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 110
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (4/100mL)<\\/html>\",\"Station Number: 111
Class: Freshwater (E. coli<\\/i>)
Category: > 999 (1033/100mL)<\\/html>\",\"Station Number: 112
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 113
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (20/100mL)<\\/html>\",\"Station Number: 114
Class: Freshwater (E. coli<\\/i>)
Category: 126 - 409 (140/100mL)<\\/html>\",\"Station Number: 115
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (100/100mL)<\\/html>\",\"Station Number: 116
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (53/100mL)<\\/html>\",\"Station Number: 118
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (33/100mL)<\\/html>\",\"Station Number: 120
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (73/100mL)<\\/html>\",\"Station Number: 129
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (92/100mL)<\\/html>\",\"Station Number: 132
Class: Freshwater (E. coli<\\/i>)
Category: 410 - 999 (467/100mL)<\\/html>\",\"Station Number: 133
Class: Marine (Enterococcus<\\/i>)
Category: > 999 (1500/100mL)<\\/html>\",\"Station Number: 135
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (7/100mL)<\\/html>\",\"Station Number: 137
Class: Marine (Enterococcus<\\/i>)
Category: 35 - 129 (80/100mL)<\\/html>\",\"Station Number: 138
Class: Freshwater (E. coli<\\/i>)
Category: 126 - 409 (333/100mL)<\\/html>\",\"Station Number: 139
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (96/100mL)<\\/html>\",\"Station Number: 140
Class: Freshwater (E. coli<\\/i>)
Category: 126 - 409 (273/100mL)<\\/html>\",\"Station Number: 141
Class: Freshwater (E. coli<\\/i>)
Category: 126 - 409 (287/100mL)<\\/html>\",\"Station Number: 142
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (96/100mL)<\\/html>\",\"Station Number: 143
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (90/100mL)<\\/html>\",\"Station Number: 144
Class: Marine (Enterococcus<\\/i>)
Category: 35 - 129 (120/100mL)<\\/html>\",\"Station Number: 145
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (20/100mL)<\\/html>\",\"Station Number: 146
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (10/100mL)<\\/html>\",\"Station Number: 147
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (100/100mL)<\\/html>\",\"Station Number: 148
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (30/100mL)<\\/html>\",\"Station Number: 149
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (56/100mL)<\\/html>\",\"Station Number: 151
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (70/100mL)<\\/html>\",\"Station Number: 152
Class: Marine (Enterococcus<\\/i>)
Category: 130 - 999 (144/100mL)<\\/html>\",\"Station Number: 153
Class: Marine (Enterococcus<\\/i>)
Category: 130 - 999 (700/100mL)<\\/html>\",\"Station Number: 154
Class: Freshwater (E. coli<\\/i>)
Category: 126 - 409 (260/100mL)<\\/html>\",\"Station Number: 155
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (110/100mL)<\\/html>\",\"Station Number: 158
Class: Freshwater (E. coli<\\/i>)
Category: 126 - 409 (220/100mL)<\\/html>\",\"Station Number: 160
Class: Freshwater (E. coli<\\/i>)
Category: 126 - 409 (270/100mL)<\\/html>\",\"Station Number: 161
Class: Freshwater (E. coli<\\/i>)
Category: 126 - 409 (187/100mL)<\\/html>\",\"Station Number: 163
Class: Freshwater (E. coli<\\/i>)
Category: 126 - 409 (180/100mL)<\\/html>\",\"Station Number: 164
Class: Freshwater (E. coli<\\/i>)
Category: 126 - 409 (140/100mL)<\\/html>\",\"Station Number: 165
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (60/100mL)<\\/html>\",\"Station Number: 166
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (107/100mL)<\\/html>\",\"Station Number: 167
Class: Freshwater (E. coli<\\/i>)
Category: 410 - 999 (460/100mL)<\\/html>\",\"Station Number: 168
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (40/100mL)<\\/html>\",\"Station Number: 169
Class: Freshwater (E. coli<\\/i>)
Category: 410 - 999 (575/100mL)<\\/html>\",\"Station Number: 170
Class: Freshwater (E. coli<\\/i>)
Category: 126 - 409 (310/100mL)<\\/html>\",\"Station Number: 171
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (42/100mL)<\\/html>\",\"Station Number: 172
Class: Freshwater (E. coli<\\/i>)
Category: 126 - 409 (280/100mL)<\\/html>\",\"Station Number: 173
Class: Freshwater (E. coli<\\/i>)
Category: 126 - 409 (210/100mL)<\\/html>\",\"Station Number: 174
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (34/100mL)<\\/html>\",\"Station Number: 175
Class: Freshwater (E. coli<\\/i>)
Category: 410 - 999 (980/100mL)<\\/html>\",\"Station Number: 176
Class: Marine (Enterococcus<\\/i>)
Category: 35 - 129 (128/100mL)<\\/html>\",\"Station Number: 177
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 178
Class: Marine (Enterococcus<\\/i>)
Category: 130 - 999 (630/100mL)<\\/html>\",\"Station Number: 179
Class: Marine (Enterococcus<\\/i>)
Category: 130 - 999 (240/100mL)<\\/html>\",\"Station Number: 180
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 181
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (4/100mL)<\\/html>\",\"Station Number: 182
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (32/100mL)<\\/html>\",\"Station Number: 264
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (28/100mL)<\\/html>\",\"Station Number: 265
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (90/100mL)<\\/html>\",\"Station Number: 266
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (60/100mL)<\\/html>\",\"Station Number: 267
Class: Freshwater (E. coli<\\/i>)
Category: 126 - 409 (340/100mL)<\\/html>\",\"Station Number: 268
Class: Freshwater (E. coli<\\/i>)
Category: 410 - 999 (560/100mL)<\\/html>\",\"Station Number: 269
Class: Freshwater (E. coli<\\/i>)
Category: 126 - 409 (147/100mL)<\\/html>\",\"Station Number: 270
Class: Marine (Enterococcus<\\/i>)
Category: 35 - 129 (117/100mL)<\\/html>\",\"Station Number: 271
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (90/100mL)<\\/html>\",\"Station Number: 1510
Class: Marine (Enterococcus<\\/i>)
Category: 35 - 129 (110/100mL)<\\/html>\"],{\"interactive\":false,\"permanent\":false,\"direction\":\"auto\",\"opacity\":1,\"offset\":[0,0],\"textsize\":\"10px\",\"textOnly\":false,\"className\":\"\",\"sticky\":true},null]},{\"method\":\"addControl\",\"args\":[\"Marine (Enterococcus<\\/em>)<\\/b>
#/100mL
< 35
35 - 129
130 - 999
> 999\",\"topright\",null,\"info legend\"]},{\"method\":\"addControl\",\"args\":[\"Freshwater (E. Coli<\\/em>)<\\/b>
#/100mL
< 126
126 - 409
410 - 999
> 999\",\"topright\",null,\"info legend\"]}],\"limits\":{\"lat\":[27.53248,28.149932],\"lng\":[-82.783203,-82.061156]}},\"evals\":[],\"jsHooks\":{\"render\":[{\"code\":\"function(el, x, data) {\\n return (\\n function(el, x) {\\n var myMap = this;\\n myMap.on('baselayerchange',\\n function (e) {\\n myMap.minimap.changeLayer(L.tileLayer.provider(e.name));\\n })\\n }).call(this.getMap(), el, x, data);\\n}\",\"data\":null}]}} # show selected year, month, and area show_fibmap(fibdata, yrsel = 2020, mosel = 7, areasel = 'Alafia River') {\"x\":{\"options\":{\"crs\":{\"crsClass\":\"L.CRS.EPSG3857\",\"code\":null,\"proj4def\":null,\"projectedBounds\":null,\"options\":{}}},\"fitBounds\":[27.722349,-82.383348,27.937863,-82.061156,[]],\"calls\":[{\"method\":\"addProviderTiles\",\"args\":[\"Esri.WorldGrayCanvas\",null,\"Esri.WorldGrayCanvas\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.NatGeoWorldMap\",null,\"Esri.NatGeoWorldMap\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.OceanBasemap\",null,\"Esri.OceanBasemap\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.WorldPhysical\",null,\"Esri.WorldPhysical\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.WorldShadedRelief\",null,\"Esri.WorldShadedRelief\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.WorldTerrain\",null,\"Esri.WorldTerrain\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.WorldImagery\",null,\"Esri.WorldImagery\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.WorldTopoMap\",null,\"Esri.WorldTopoMap\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.DeLorme\",null,\"Esri.DeLorme\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.WorldStreetMap\",null,\"Esri.WorldStreetMap\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri\",null,\"Esri\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addLayersControl\",\"args\":[[\"Esri.WorldGrayCanvas\",\"Esri.NatGeoWorldMap\",\"Esri.OceanBasemap\",\"Esri.WorldPhysical\",\"Esri.WorldShadedRelief\",\"Esri.WorldTerrain\",\"Esri.WorldImagery\",\"Esri.WorldTopoMap\",\"Esri.DeLorme\",\"Esri.WorldStreetMap\",\"Esri\"],[],{\"collapsed\":true,\"autoZIndex\":true,\"position\":\"topleft\"}]},{\"method\":\"addMiniMap\",\"args\":[null,\"Esri.WorldGrayCanvas\",\"bottomleft\",150,150,19,19,-5,false,false,false,true,false,true,{\"color\":\"#ff7800\",\"weight\":1,\"clickable\":false},{\"color\":\"#000000\",\"weight\":1,\"clickable\":false,\"opacity\":0,\"fillOpacity\":0},{\"hideText\":\"Hide 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MiniMap\"},[]]},{\"method\":\"addMarkers\",\"args\":[[27.859145,27.937863,27.857283,27.862966,27.862607,27.722349,27.908457,27.869101,27.926909,27.854094,27.872697,27.857382,27.884933],[-82.383348,-82.193917,-82.269149,-82.13696899999999,-82.136984,-82.061156,-82.189373,-82.326401,-82.065258,-82.24644600000001,-82.211276,-82.35382199999999,-82.30665],{\"iconUrl\":{\"data\":[\"data:image/png;base64,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\",\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAroAAAJkCAYAAAD+yYJGAAAAAXNSR0IArs4c6QAAAARnQU1BAACxjwv8YQUAAAAJcEhZcwAAMsAAADLAAShkWtsAAEb3SURBVHhe7d0LuOVXfdf/qNVqqdVq1WpVtE2BzFm/E8qQs9YOaVNFba1Si5ZWi/aixabFWq2lWou2tYpSWkWptn8ghABhIAm5EBISchlIMnPWb8/kThKSkAuEW4AkJIFyCYH/93tmAZPf+WRyzplz+f72fr+f5/WkT5OZs8/e67e+38OTyzFERLT5dVc/++mpL6ekPr/cnJVqvsb++MCKlf+7nHXoz5VT/K9tv4yIiIiIKGbdcv5BW17P6/ry5fVY+TX2a9tvQ0REREQUo66Wl3R9vlUtsetjv4f9Xu23JSIiIiLamXbtPfkbU1/26KV14/z39N+7fRkiIiIiou1rYX95ji2ltwyX1E10i3+N9uWIiIiIiLa+hT7/rFhMt4R/rfZliYiIiIi2roV9kxPVQrqV/Gu2L09EREREtPntPrj7G2zxvHm4iG6Dm/1rt5dBRERERLS5pZrPEEvotvCv3V4GEREREdHmdehfIaaX0G3Dv3qMiIiIiDazXf0J35r68mm5fG4jfw3+WtrLIiIiIiI6urqaf08tnjvCXkt7WUREREREGy/1J0zkwrmD/DW1l0dEREREtLFSzRerZXMn+WtqL4+IiIiIaP3ZUvljwyUzkB9rL5OIiIiIaH2lWm4TC2YI/trayyQiIiIiWntdn39VLZix5F9tL5eIiIiI6MlbmD77r6RavqCXyzj8NfprbS+biIiIiOjIdX1+rVosY8qvbS+biIiIiOiJ6/rJ9+iFMrLJ97SXT0RERESkS32+XC+Tcflrbi+fiIiIiGh1tjT+xHCJHJGfaN8GEREREdFhffmYP5T6cpdYIEfBX7t/D+27ISIiIiI6VNfnX1cL5LjkX2/fDhERERGRLbnTk75dL44jZN9L+7aIiIiIaN5LfT5dLo0j5N9L+7aIiIiIaJ7r+slz1cI4bpPntm+PiIiIiOa11Jcr9bI4Xv49tW+PiIiIiOaxbjm/SC2KM8G+t/ZtEhEREdE8dexFx3596su9ckmcAf69+ffYvl0iIiIimpe65fwytSDOFPse27dLRERERPNQ2jd5hlwMZ5B/r+3bJiIiIqJZL9WyRy2Fs8i/1/ZtExEREdEs1y3nv6sWwnWZiv9fZPY9t2+fiIiIiGa11Jcql8H1mk70/z8g/57bt09EREREs1i3nH9OLYIbMr7/Vffn2ttARERERLPUrr0nf2Pq831yCdyoES27/r37e9DeDiIiIiKalWzZe8Vw+ZtDr2hvBxERERHNQt2B0omlb3OM7W9hsPeivS1ERERENPZSX86WS98c8veivS1ERERENOa6af5BtfDNNXtP2ttDRERERGMt9fkauexttnH9g2nXtLeHiIiIiMZYN82/oBY9GHtv2ttERERERGOqu/Gkb059fkAuefD/VfcBf4/a20VEREREYyn15ZVqwcPX+HvU3i4iIiIiGkPdgfIstdhBsPeqvW1EREREFL3Ul/PlUodV/L1qbxsRERERRa6rSz+sFjocgb1n7e0jIiIioqilmm+Sy9x2q+L/F5S/Z+3tIyIiIqKI2XL5ErXIYQ3svWtvIxERERFFKi3nv5Bq/rRc4nZIEv+/qPy98/ewvZ1EREREFKVUy/9TCxzWzt/D9nYSERERUYS6ulTU4oYNsPeyva1EREREtNOlmt8plzasm7+X7W0lIiIiop2sq5N/ohY2HAV7T9vbS0REREQ7Var5fXJZw4b5e9reXiIiIiLaibpa/qNa1LAJ7L1tbzMRERERbWddXfrLtox9Xi5pMX24UX8uHn9v7T1ubzcRERERbVep5tfIBS2o1E/e7tSfi8rf4/Z2ExEREdF21NWl71aLWVSpz+9Lffn/DhnZ31Ns73V724mIiIhoq0s1XyaXsoBsuX0s1ckZX110D/3fj6m/NiJ/r9vbTkRERERb2WItP64WsrBqPvDVJbfx/5/8a4Py97y9/URERES0VaVa7lTLWES21H5quOQe5lPq10Tk73l7+4mIiIhoK7KF69fUIhaVLbOXD5bbw12ufk1U/t63j4GIiIiINrPuqmd/uy1cXxouYFHZInvvYLFV7lW/Nqgv+WfQPg4iIiIi2qxSn08Xy1dYabmcJxbbx7O/Rv3aqPwzaB8HEREREW1GXT95rlq8ArtFLraC/7WDXxvc5LntYyEiIiKio80Wwiv10hVP6vOjC31543ChfSKH/tr8qPq9IrLXfGX7WIiIiIjoaLLl6qeHy1ZwdbjMPhn/NYPfI7qfbh8PEREREW2kXe/d9cdsERzNP7C10JcHhkvsWvmvVb9nRPZ67/XPpn1MRERERLTeUp//m1q0okr95NLhArt2k0vV7xmVfzbtYyIiIiKi9dRNT3y6WrDCqvkDeoFdO/895O8dlX1G7eMiIiIiorWW+vxmuVwFtVDzOWp5XQ//PdTvHZV/Ru3jIiIiIqK1tNiX71eLVWA3qcV1I/z3Gvzeofln1T42IiIiInqybOFbVktVSLV8PvX59OHCunH5dP895dcKyF7zcvvYiIiIiOhILfb5Z9VCFVYt+1cvq0fHf0/5tYLyz6x9fERERESkWrx+8Sm2OH1suEiFVfMn1aK6Gfz3ll8zpo/5Z9c+RiIiIiIalvr8W2KJiuwStaRuBv+9B18rNP/s2sdIRERERIe3OJ0ktUCFVcvdakHdTP415NcOyj/D9nESERER0Veyxe4stTxFZa/37MOX0i1ytvraUdnrPat9nERERETkLU7L89TiFNgNg4V0y/jXGnzt0PyzbB8rEREREdmCdHC4MEWVavmsOU0tpVvCv5Z9TfVagjrYPlYiIiKi+W5hOf+CWJYCm1wtF9It5F9Tv5aY/DNtHy8RERHRfNZdddI3p5ofUMtSSDV/XC2i28G/tnxNAa18pvbZto+ZiIiIaP5KtbxSLUpR2QL3TrWEbgv72uo1ReWfbfuYiYiIiOarbn95llqQorJF8065gG4new3qtYVln3H7uImIiIjmp1TL+XI5iurA5K1y+dxG/hrkawvKP+P2cRMRERHNR4vL+R+pxSisablOLZ47wV+LfI1B+WfdPnYiIiKi2S/VfKNaiiKy1/qZ1E9eq5bOnWGvxV6Teq0R+WfdPnYiIiKi2W6hLv2SWoiiStN8pV44d5C9JvVao/LPvH38RERERLPZ4r7Jn+9qfkQtQyFNy0flohmAvzb5miOyz9w/+3YMiIiIiGavVMv/lYtQVLVcqJbMCPy1ydcclH/27RgQERERzVaLyzmrBSisabldLZiR+GuUrz0oPwPtOBARERHNTraYXaSWn6js9e45fKkMao967VHZ672oHQciIiKi2Whxmv+xWnyiSnVyzWChjMteq/oeovKz0I4FERER0fjr+nyrWnpiyo+k6eTVcqmMyF6rv2b9vUSUb23HgoiIiGjcpWn5Fb3wBFXzu+VCGZi/Zvm9BOVnoh0PIiIionF2/HXl27o+f04tOyHV8mG1SI6Bv3b5PYWUP+dnox0TIiIiovGVpuXVetGJKdV8gVoiR8Feu/qeovKz0Y4JERER0bjq6tJ3qwUnqlTL++QCOSb2PajvLSw7I+24EBEREY2nVPNlcrkJyF7rl1KdnCGXxzHx78G+F/U9RuRnpB0XIiIionG0UMuPq8UmrJoPyMVxhPx7kd9jUH5W2rEhIiIiil+q+U611IS0XB5SC+OY+fckv9eA/Ky0Y0NEREQUu1TLr6mFJqo0LZerZXHU7HtS32tUfmba8SEiIiKK2WJd+utdLeP5e0T7cu+qJXF23Ku+55DszPjZaceIiIiIKF6p5tfLRSYoWwbPGyyHs+Q89T1H5WenHSMiIiKiWC3Wpb+pFpjAbhHL4Uzx73HwPYfmZ6gdJyIiIqI4pZrfo5aXiFKfH13oyxvVcjhLDn2P+VH1HkTkZ6gdJyIiIqIYLdTyL9TiEpUtf71aDGdT7tV7EJWfpXasiIiIiHa23Qd3/9Gulg+qpSUiW/4eWL0MzrwH1HsRkp0lP1PteBERERHtXKmW/yoXlqBSP7lULIIzbnKpei+i8jPVjhcRERHRzrTYn/A0tagE9gG9CM4+/94H70VofrbaMSMiIiLa/lLNZ6glJaqF6eQctQTOA//e1XsSlZ+tdsyIiIiItrfFfvJ9akGJyhan96oFcK7Ye6Dem6j8jLXjRkRERLR9dbXsV8tJUJ9P03y6XP7mib0H/l4M3pu47Iy140ZERES0PdnSdIpcTIKy17v8uIVvvi2r9ygqe72ntGNHREREtLUtXrL4lK6Wj6qlJKRaPjlY9OaevyfyvYrIzpqfuXb8iIiIiLau1OeXy4UkqDQtl6hlb67Ze6Leq6j8zLXjR0RERLQ1Le6bJLWIRGVL3d2rljx8xd3qPYvKz147hkRERESbX1rOZ6klJKpUy9liwYOz90a9Z1H52WvHkIiIiGhzW9xfnqcWkKhSn2+UCx4Ok29U711UfgbbcSQiIiLavLpaDqrlI6jPplpO08sdvsreI3+vBu9dXHYG23EkIiIi2pxSn/+1XDzCmlwtFzus4u+Vfg9j8rPYjiURERHR0XX8dcf/6a7P96ulI6b8cbXQ4Yn5e6bfy4jy/X4m2/EkIiIi2nipz/9LLxwxpZrfqZY5HIG9Z+q9jMrPZDueRERERBtrcTr5LrVoRGUL251ykcOTs/dOvadR+dlsx5SIiIho/dkCdJ5aMuLKZ65a4LAm/t7p9zQme83ntWNKREREtL4WpvkfqgUjrFquGy5vWB9/D+V7G5Sf0XZciYiIiNaeLRI3DBeLsGr5jP3xVLW8Ye38PWzvpX6f47mhHVciIiKitZX6/O/EUhGWLWlXDpc2bNiV6j2Oys9qO7ZERERER+6Z157057o+P6yWiqA+JpY1HAV/TwfvcWD5YT+z7fgSERERPXG26PyuXijCunC4qOHo+Hs6eI9Ds9f8u+34EhEREemOP1CW1CIRVs13DJc0bA5/b+V7HpSf3XaMiYiIiFZnC8O4/pe8Wt6iljRsAntv1Xse2IXtGBMRERE9voVp/lGxPISV+sk1ckHDJppco977qPwMt+NMRERE9LVsUbhluDiEVfMjizW/Ri9n2Cz+Hvt7LT+DmG5px5mIiIjoUKku/YpYGuKq+d1qMcPm8/dafgZB+Vlux5qIiIjmveP3l2+zZeZzamkIqeaPqIUMW8ffc/lZRGRn2c90O95EREQ0z6VaXi0XhqDSNF+gljFsIXvP1WcRlZ/pdryJiIhoXltcziepRSEqW2Buk4sYtp699+ozicrPdjvmRERENI+lmi9VS0JINX8pTSdnyCUMW8/ee/8M5GcTkJ/tdsyJiIho3lqoS/9MLQhhTcsBuYBh2/hnID+boPyMt+NORERE81RX8/vVchDUQ2rxwvbzz2Lw2cRlZ7wddyIiIpqXUi3/WS4GQdmCdcVw4cKOuUJ9RlH5WW/HnoiIiGa945fzX+tqeUwtBRGlablXLFvYSfaZqM8qJDvrfubb8SciIqJZLtVymlwIgrLF6vxVixZ22vnqs4rKz3w7/kRERDSrLdSlv6EWgbgmt4glCwH4Z6M/s5j87LfHgIiIiGaxblT/Odf8RVum3qiWLOw8/2wOfUbqswvIzn57DIiIiGjWSnXyz+UCEFTqc68WLESSe/XZReXPQHsciIiIaFY6ee/JX9fV/AE1/CNKNT+oFyuEY5+V+gxDsmfAn4X2WBAREdEslGr5TTn4g7Ll6TK5VCEe+6zUZxiVPwvtsSAiIqKx98xr83eqgR/YB+RChbD8Mxt8hqH5M9EeDyIiIhpz3TS/SQ37qBaWy7lqmUJc/pmpzzIseyba40FERERjbaE/4fvkoA8q1fxetUhhBOyzU59pVP5stMeEiIiIxljX531qyEeUavmCvd7T5RKF8FY+u5XPUH++8eR97TEhIiKisWXLxyl6wMeUlsvycHnCyNhnqD7bqOw1n9IeFyIiIhpLuw/u/oaulo+q4R5SzfevWpowSv5Zys84IntG/Flpjw0RERGNodTnl8vBHlSalkvU0oQRss9SfcZR+bPSHhsiIiKK3vH9CQtqoEeV+sndcmHCiE3uVp91VP7MtMeHiIiIItf1+Uw1zOOanK2XJYzX5Gz9WUeVz2yPDxEREUVtoZ/8fT3IY0p9vlEvShi/fKP6zKPyZ6c9RkRERBSxrpYDaogH9dk0LafpJQmjZ5+tf8aDzzwue3baY0RERETRsuXi5+UADyrVvG/VcoTZYp+x+uyjstf88+1xIiIioijtPrj7T3W1fFIN76A+vmopwkzyz3rw2cdlz5A/S+2xIiIiogilPv9PObiDStPJO9VShBlkn7U6A1H5s9QeKyIiItrpdvUnPlMN7KhSzXfKhQizyz5zdRai8meqPV5ERES0k3V9PlcN67Cm+Uy5DGFm+Wcuz0JY+dz2eBEREdFOZUvE8/Wgjsle7/WHL0CYK9erMxGVvd7nt8eMiIiIdiIbyONZHmr5jP3x1MHygznhn307A/p8xHN9e8yIiIhou0t9/kUxnMOyZeeq4fKDuXOVOhtR+TPWHjciIiLarnYf3P0tNogfGg7mwD4mlh7MIT8Lg7MR2UP+rLXHjoiIiLajrs+vEkM5rIV+cqFaejB//CyoMxJXflV77IiIiGir27W/LOmBHFW+Qy08mF9+JvRZicmfufb4ERER0VbW1TKy/0WsvEUtO5hffiYGZyQ2e+ba40dERERb1cJy/lE5iINKNV+rFh3Az4Y6M1H5s9ceQyIiItqKulpuUUM4qEcWa36NXHIw9/xs+BkZnJm47NlrjyERERFtdmk5/wc5gMOavFstOMBX+BnRZycmfwbb40hERESb1XddfeJf6mr+rBq+MeWPqMUGGPKzos9QQPYM+rPYHksiIiLajNLyyj/Ao4dvRDVfoJYaYMjPijxDQfmz2B5LIiIiOtoWDpTnqIEbVZqW29RCAzwhOzPqLEXlz2R7PImIiOhossH6ruGgDexLi315s1xmgCfgZ8bPzuAsRfau9ngSERHRRkvT/E/FkI2rlgNqkQGejJ8deaaC8mezPaZERES0kUb1X5CalofUAgOslZ8hebZCyne0x5SIiIjWW+rzf9IDNiZbVK4YLi7AOl2hzlZU/oy2x5WIiIjW2nHXTJ5qQ/SLarhGlGr+kFhagPWzs6TOWET+jPqz2h5bIiIiWks2RF83HKqRLfblfLm0AOvkZ0mdscBe1x5bIiIierIWDuTvFcM0rppvVQsLsFF+puRZC8qf2fb4EhER0ZGywbl3OEjDqvmL5k1qWQE2ys/UytlSZy6mve3xJSIioicqTfNPiSEaVuonvVpUgKM36dWZi8qf3fYYExER0bCT9578dV2f71FDNKJU84N6QQE2iZ0xdfZiyvf4M9weZyIiIjq8VMtv6gEaky0hl8nlBNgsdsbU2YvKn+H2OBMREdFXOm45f6canGHV8kG5mACbzM+aPINB+bPcHmsiIiLyVv7hGzE0AztXLSXAZvOzNjh7sdmz3B5rIiIiWqhLf0cOzKDScrlZLSTAlrEzp85iVP5Mt8ebiIhovutq3qeGZUSpli9008npchkBtsjKmfOzJ85kSPZMt8ebiIhofrPh/TNyUAZlS8fycAkBtsmyOpNR+bPdHnMiIqL5q+wvf6Kr+SNqSMaU7xfLB7Bt/AzqsxmQPdv+jLfHnYiIaL7qavkfckDG9S61fADbxc/g4EzGZs94e9yJiIjmp111aZccjEGlfnK3WjyA7Te5W53RqPxZb489ERHRfNTV/FY1FAN7m146gO3lZ3FwNmOzZ7099kRERLNfqkt/Tw7EoFKfb1QLB7Bz8o3qrEblz3x7/ImIiGa7ruapGoYx5c+laTlNLxvADrEz6WdTn9mA7Jlvjz8REdHslmr5V3IQBpX6vE8uGsCOG8+/f9r5s9+uASIiotnr2Lr0TTbsPqGGYET+WvWCAQQxsufJ74B2HRAREc1WXS2/owZgWLVcLJcLIAg/o/LsRmV3QLsOiIiIZqeFunS8HHxBpT7fqRYLIJ58pzrDUfld0K4FIiKi2air+Rw19KJKy+UsvVQAwdhZVWc4LLsL2rVAREQ0/tL+8nw58IJK03K9XCiAqOzMqrMcVaqTH2rXAxER0bjrpuU6NewiSn3+A/vjqXKZAII6dGZXzq481+HYndCuByIiovFmw/cX5aALKtVylVokgPDs7KozHZXfDe2aICIiGl9PO7j7W2wAP6SGXEQ2eO9btTwAo5LvU2c7Inu9D/kd0a4LIiKicdX1+VVqwMU1uXD14gCMh59hfbajyq9q1wUREdF4WphOTtCDLap8h1ocgLHxs6zPeEx+V7Rrg4iIaBzZsH2HGmqBvUUtDcDY+FkenO3g8jvatUFERBQ/G7Y/ogdaTKnma4fLAjBqdqbVWY/KXvOPtOuDiIgodja4bh4OssAeSdP8mlWLAjBmdqb9bA/OemQ3t+uDiIgobqnP/14MsbBSLe+RiwIwdna21ZmPyu+Odo0QERHF6xkHnvUXbViN519aX/NH5IIAzAg/4/LsB+R3h98h7TohIiKKVdfn31cDLKxpuUAtB8Cs8DMuz35Y+ffbdUJERBSnhenkRD24Ykq13KYWA2Dm2FlXz0BUfpe0a4WIiChGNqAuGQ6ssGr58mJf3iyXAmDG+Fn3My+fhZguadcKERHRzmfD9IViWEV2cLgMALPMz/zgGQjNXvML2/VCRES0s9lQul0Nq6AeOnwBAOaFn/3BsxCWvd7b2/VCRES0c3V9fqkaVFGlWvYOFwBgLtjZV89EXPml7ZohIiLa/o7bN3lq6vOjekjFY6/1Q3IBAOZG/pB6NiLyu8XvmHbdEBERbW9dLa9TAyqqxb6cr4c/MB/8GVDPRlh2x7TrhoiIaPtaWM7fKwdTVDXfqgY/MG/8WZDPSFB+17Rrh4iIaHvqxvT3+9XyWDfNb1JDH5g3/iysPBPqWYnI7pp27RAREW19aTn/lBxIQaVapmrgA3PLngn1rETld067foiIiLawM1/wR1LN96hhFFHq84Ny0ANzLz+onpmI/M7xu6fdQkRERFtTV5f+ixpEUS1O82V6yAPzzZ8N9cyEZXdPu4aIiIg2v137y7FyAMX1QTXgARziz8jgmQnN76B2HREREW1uXS1vVMMnrGk5Vw13AIf4MyKfnajsDmrXERER0eaVlvPfloMnKBviNw+HOgDpZvUMReV3UbuWiIiINqeu5qvV0InIBvcX7I9vGAxzAEJ7VvyZkc9TOHYXtWuJiIjo6LPB8i/lwAkqTcvycJgDOAJ7ZtSzFJbdSe16IiIi2nhP3XvyH099/rAcNiHl++UgB3BE/uzoZyoev5P8bmrXFBER0cbqpuW/q0ET2LvUEAdwZP7sDJ6l2OxuatcUERHR+lu4Jh8nB0xQqc/3qAEOYK3G8x+DcX5HteuKiIhofdkgectwsIRWy9v08AawFv4MyWcrrre064qIiGjtpQP5B8RQCSvVcpMa3ADWyZ4l9YxF5XdVu7aIiIjWVupzr4ZKTPlzqU5eL4c2gPWxZ8mfKf2sxeN3Vbu2iIiInrxuOnmxGihh1bxPDmwAG+LPlHzWorI7q11fRERET9yxdembUp8/LodJQKmWT6hBDeAo2bOlnrmI/M7yu6tdY0RERLqult9RgySsWi6WQxrAUfFnSz5zUdnd1a4xIiKi1S3UpePlAAkqLZe71IAGsEnsGVPPXlR+h7XrjIiI6PF1NZ+jhkdUNojPWjWYAWyms9SzF5bdYe06IyIi+lqpLv2QHBxBLdSlG8RQBrDJ/FlTz2BUfpe1a42IiOhQqebr1NCIyF7rH3QHyqlqKAPYXCvPmj9z4lmMyO+ydq0RERGt/ANo/1YNjMCuUgMZwNbwZ27wDMZmd1q73oiIaJ57Rn/Cn021fEoOi4BSn+9TgxjAVsv3qWcyIr/T/G5r1xwREc1rXc3/Rw2KqGzgXrR6AAPYBhepZzIsu9vaNUdERPNY6k94thwQQaU+3yGGL4Btk+9Qz2ZUfse1646IiOatruYL1HAIq07eqocvgO3gz6B8NqOyO65dd0RENE91/eQFcjAElfp8rRq8ALZbvlY9o3FNXtCuPSIimpdSLe/VQyEee62fTtP8Gj10AWwrfxbtmVTPakR+17Vrj4iI5qGull9WAyGqNC3vkQMXwM6wZ1I9q2HZndeuPyIimuV29Sd8a6rlM3IYBGSv9aNy0ALYWfZsqmc2Ir/z/O5r1yAREc1qXc2/pwZBYO+QQxbAjvJnc/CsxmZ3X7sGiYhoFkv9iRM5AIJK03KbGrAAgrBnVD27Ufkd2K5DIiKatVLNF6vLP6rUL+2RwxVAEEt71LMbld+B7TokIqJZKu0vL1QXf2AH9WAFEIk/q4NnNzS/C9u1SEREs1Kq5XZ16UeU+vywGqgAosoPq2c5Ir8L27VIRESzULecX6ou/MD26mEKICJ/ZgfPcGx2J7brkYiIxtyuq57zV1OfH5WXfUCp5g+rQQogOHt21TMdkd+Jfje2a5KIiMZa1+dT1UUf1WJfzpdDFEBo/uyqZzqufGq7JomIaIyl/eVkfcFHlW9VAxTAOPgzrJ/tmPyObNclERGNLRs8V6jLPaRaHuum+U3DwQlgPPwZXnmW1TMekL3mK9p1SUREY6rr80+qiz2sWqbDoQlgfPxZls94WPkn27VJRESj6MvH/GEbOHfrSz2eNC0PDoclgBGzZ1o96xHZ673b78x2exIRUfS6Pv+GutADu3zVoAQwWv5MD57x4PJvtOuTiIgit3DgxO/QF3lQtXxQDUoA4+bPtnzmg/K7s12jREQUNbuw3zC8wIM7Vw1JAOPmz/bgWY/uDe0aJSKiiHXT8rfE5R2WDcObh8MRwEy5WT37Ydkd2q5TIiKKlg2Vq+TlHVCqK/+1tjcMhiKAGbLyjB961uU9EI295qvadUpERJHq+vwidXGHVUsdDkUAs8efdXkHhJVf1K5VIiKK0LG3f//Xpz5/SF/aEeX71UAEMJv8mdd3QTx+l/qd2q5XIiLa6bp+8jJ1YUeVar5UDUMAM8qeeXUXxDV5WbteiYhoJ1tYzsfpizqm1Od75CAEMOPyPepOiMrv1nbNEhHRTmUX8p7hBR3c2/QQBDDL/Nkf3AXR7WnXLBER7URpOf+AuJzjquUmNQABzAe/A+TdEJTfse26JSKi7S7V3KvLOaSaP5+mk9er4QdgTtgd4HeBvCMC8ju2XbdERLSddXXpxepiDqvm/XLwAZgrfhfIOyIqu2vbtUtERNvR068+8U+mmj8uL+WAUi2fUAMPwJyyO0HdFRH5Xet3brt+iYhoq+tq+W11IYc1LRfLYQdgLvmdIO+KqOzObdcvERFtZWk5L8qLOCgbancNhxwAmLvUnRGV373tGiYioq2qq+P6V/SkaTlLDDgA887uBnVnhGV3b7uGiYhoK+rq0j+QF3BcN8gBBwDG74jBnRGb3cHtOiYios0u1XytvHwDSn3+A/vj69RwAwB36I5YuSvkPRKN38HtOiYios2sq+XfqIs3rGm5Sg02ADic3xXyDonK7uJ2LRMR0Wa0a3/5M6nmB+WlG1Dq831qoAGAlu9Td0lEfhf7ndyuZyIiOtq6Wv63unCjssF10epBBgBP6CJ1l4Rld3K7nomI6Gjqat4tL9qgbGC9fzDAAGAt3q/ulLDsbm7XNBERbbTU57fLSzaqOnmrGGAAcER+d8g7JSi/m9s1TUREG6mrSz+sLtiwar5ODTAAWAu/Q+TdEpXd0e26JiKi9Zb6fJO8XAOyIfVpe72vHQ4uAFi7lTvk0+qOicjv6HZdExHReuqm5SXqYo0q1fKe1UMLANbJ7hJ1x4Rld3W7tomIaC3t6k/4Vrvwx/O/atTy0VXDCgA2yu4UdddEZK/3035nt+ubiIierK7m31MXamDvWDWoAGCD/E4Z3DGx2Z3drm8iIjpSqT9hIi/SqOrS7WpQAcDR8LtF3jlB+d3drnEiInqiUs0Xq0s0KhtIe4YDCgA2wR5150Tld3e7xomISGWX5Y8NL8/gDorhBACbwu+YwZ0T3Y+165yIiIalWm4TF2dIqeaH0wE9nABgU/gdY3eNuoMi8ju8XedERHR4XZ9/VV2cge2VgwkANpHfNYO7J7j8q+1aJyIib2H67L+SavmCvjTjsdf6YTWQAGBL2J2j7qKI/C73O71d70RE1PX5terCjCr1k7fLYQQAW2LydnUXxZVf2653IqL5rusn36MvyqjyrXoQAcDW8btH30lRTb6nXfNERPNb6vPl+pIMqJbHUs1nqCEEAFvK7h6/g+TdFJDf7e2aJyKaz+wy/Inh5RjcVA4gANgGfgcN7qTofqJd90REc9aXj/lDdnHfJS7GkFItnxoOHQDYdnYXqTsqInu9d/ld3259IqL5qevzr6uLMSq7sC9/3LABgJ0xnr/da0X+9XbtExHNR930pG/XF2JMqc/3imEDADsk36vuqrDszm/XPxHR7GeX9OnyMgzKXu95etgAwE7I56m7Kiq/89v1T0Q023X95LnqIgzsZj1oAGDn+N00uKuCmzy3jQEiotnNLugr9SUYT+rzowt9eeNwwADATjt0N+VH1d0Vkb3mK9sYICKazbrl/CJ1AQZWh8MFAKLwO2pwZ8VmM6CNAyKi2erYi479eruYR/MPUKRaHhgOFQAIx+4qdYdFZK/3Xp8FbSwQEc1O9pP8y9TFF1XqJ5euGigAEM7kUnWHhWWzoI0FIqLZKO2bPENeeFHV/AE9UAAgHr+z5F0WlM+ENh6IiMZfqmWPuuwCe5saJgAQkd9ZgzssNJ8JbTwQEY27bjn/XXXRBXaTGiQAEJnfXYO7LDabDW1MEBGNN7uAx/RPBX8+1cnrhwMEAMKzu8vvsMGdFpa95trGBBHROLOf2H9OXXBhTcv+VcMDAEbC7zB5t0VlM6KNCyKicbVr78nfmPp8n7zcArIh8Ynh0ACAEfqEuuMi8hnhs6KNDSKi8WSX2CuGl1ps+RIxMABgVPwu03dcWK9oY4OIaBx1B0onLrO4puUuNTAAYIz8TpN3XVQ2M9r4ICKKn120Z8vLLCh7vWcdPiQAYOTOUnddVPZ6z27jg4godt00/6C6yAK7YTAgAGD0/G4b3HWx2exoY4SIKG6pz9fISywge62ftT++Tg0JABizQ3fbyh0n779ofHa0MUJEFDP7ifwX1AUWVs1XqwEBALPA7zh590VlM6SNEyKiWHU3nvTN9hP5A/LyCshe631qMADAbBnTv+bRZojNkjZWiIjiZBfqK9XFFVWq+Z2rBwIAzBi769QdGJW95le2sUJEFKPuQHmWurDCquX9q4YBAMwov/PkXRiVzZQ2XoiIdj67SM+Xl1VU08lbh4MAAGaV33nyLgzKXvP5bbwQEe1sXV36YXVRhVXLdcMhAACzzu8+eSdGZbOljRkiop0r1XyTvKQCSsv5M2k6ea0aAgAw0/zusztQ3Y0R+WxpY4aIaGfqanmJuqCiStPyHjkAAGAe2B2o7sawbMa0cUNEtL2l5fwX7CfuT8vLKaBUy0flxQ8A88TuQnVHRuQzxmdNGztERNuXXZb/T11MYU3LO+SlDwBzxO9CeUcG5bOmjR0iou2pq0tFXUiB3a4ufACYR34nDu7I2GzmtPFDRLT1jfBfQL5neNEDwBzbo+7KqHzmtPFDRLS1dXXyT9RFFFXq8zXikgeAOZevUXdmWDZ72hgiItq67Cfr98lLKCC7yB9O0/JqfckDwBxbuRvzw+rujMhnTxtDRERbU1fLf1QXUGB75QUPAPC/V3fv4M6MzWZQG0dERJtbV5f+sl0yn5eXT0wfVhc7AOBr/K4c3J1x+QyyWdTGEhHR5pVqfo28eIJK/eTt6lIHABxu8nZ1h0bls6iNJSKizcl+gv5udeFElfr8Pn2hAwBWG88/e7HCZlIbT0RER5/9BH2ZvGwCskv7sVQnZ6y+yAEA0qE78zF1p0bkM6mNJyKio2uxlh9XF01YNR9YdYkDAI7I7055pwbls6mNKSKijZdquVNdMhHZZf2p4eUNAFizT6m7NSKfTW1MERFtLLtIfk1dMFHZJX354NIGAKzd5epujcpnVBtXRETrq7vq2d9uF8mXhhdLVHZB3zu4sAEA63evumOD+pLPqja2iIjWXurz6eJSCSstl/PEhQ0AWA+7S9UdG5XPqja2iIjWVtdPnqsulMBukRc2AGDd/E4d3LHBTZ7bxhcR0ZNnF92V+jKJx36af3ShL28cXtQAgI05dKfmR9WdG5G95ivb+CIiOnJ2afz08BIJrg4vaQDA0fG7dXDXRvfTbYwREel2vXfXH7MLbjT/IMJCXx4YXs4AgM3hd6y6eyOy13uvz7A2zoiIVpf6/N/UBRJV6ieXDi9mAMBmmVyq7t6ofIa1cUZE9Pi66YlPVxdHWDV/QF/MAIDN4netvIOjslnWxhoR0deyn4TfLC+NoBZqPkddygCAzeN3rbqDo/JZ1sYaEdGhFvvy/erCCOwmdSEDADaf37mDOzg0n2ltvBERrfzrxJbVZRFSLZ+3n9hPH17EAICtkk/3u1feyQHZa15u442I5r3FPv+suijCqmX/6ksYALCV/O6Vd3JQPtvamCOieW3x+sWn2IXwseEFEVbNn1QXMABg6/kdLO/mmD7mM66NOyKax1Kff0tcDpFdoi5fAMDW8zt4cCeH5jOujTsimrcWp5OkLoawarlbXbwAgO3jd7G8o4PyWdfGHhHNU3ZhnaUuhajs9Z59+GULANgRZ6s7Oip7vWe1sUdE89LitDxPXQiB3TC4aAEAO8Tv5MEdHZrPvDb+iGgesgf/4PAiiCrV8llzmrpsAQA7wO9ku5vVnR3UwTb+iGjWW1jOvyAugcAmV8uLFgCwY/xu1nd2TD772hgkolmtu+qkb041P6AugZBq/ri6YAEAO8/vaHl3B7Qy+2wGtnFIRLNYquWV6gKIyi6md6rLFQAQgN3R6u6OymdgG4dENGt1+8uz1IMflV2gd8qLFQAQh93V6g4Py2ZhG4tENEvZT7Lny4c+qgOTt8pLFQAQht/V8g4PymdhG4tENCstLud/pB74sKblOnWhAgDi8Ttb3uVB+Uxs45GIZqFU843qYY/IXutnUj95rbpMAQAR2Z1td7e60yPymdjGIxGNvYW69EvqQY8qTfOV+iIFAIRld7e606Py2djGJBGNtcV9kz/f1fyIeshDmpaPygsUABCe3+Hybo/IZqPPyDYuiWiMpVr+r3zAo6rlQnV5AgDi8ztc3u1B+Yxs45KIxtbics7qwQ5rWm5XFycAYDz8Lpd3fFA+K9vYJKIxZRfOReqhjspe757DL0sAwCjtUXd8VPZ6L2pjk4jG0uI0/2P1QEeV6uSawUUJABgru9PVXR+Vz8w2PoloDHV9vlU9zDHlR9J08mp5WQIAxsfudL/b9Z0fUb61jU8iil6all/RD3JQNb9bXpQAgNHyu13e+UH57GxjlIiidvx15dvsJ9PPqYc4pFo+rC5IAMD4+R0v7/6Q8ud8hrZxSkQRs59IX60f4JhSzReoyxEAMAPsjld3f1Q+Q9s4JaJodXXpu9WDG1Wq5X3yYgQAzA6769UMCMtmaRurRBQp+8n5MvnQBmSv9UupTs6QlyIAYHb4XW93vpoFEfksbWOViKK0UMuPqwc2rJoPyAsRADBz/M6XsyAon6ltvBJRhOwn0DvVwxrScnlIXYQAgNnld7+cCQH5TG3jlYh2ulTLr6kHNao0LZerSxAAMMPs7lczISqfrW3MEtFOtViX/npXy3j+3qe+3Lvq8gMAzIt71WwIyWarz9g2boloJ0o1v14+oEHZJXfe4NIDAMyP89RsiMpnbBu3RLTd2U+af1M9mIHdIi49AMAc8VkwmA2h+axtY5eItjP7SfM96qGMKPX50YW+vFFdegCA+XFoFuRH1ayIyGdtG7tEtF0t1PIv1AMZlV1qvbrwAADzKPdqVkTlM7eNXyLa6nYf3P1Hu1o+qB7GiOxSe2D1JQcAmHMPqJkRks1cn71tDBPRVpZq+a/yQQwq9ZNLxQUHAJhrk0vVzIjKZ28bw0S0VS32JzxNPYCBfUBfcACAeeczYjAzQvMZ3MYxEW1FqeYz1MMX1cJ0co663AAA8BmhZkdUPoPbOCaizW6xn3yfevCisgvhvepiAwDgq2xWqBkSlc/iNpaJaDPratmvHrqgPp+m+XR5qQEA8BU2K3xmDGZIXDaL21gmos3KLoNT5AMXlL3e5cddZAAAPLFlNUuistd7ShvPRHS0LV6y+BT7CfKj6mELqZZPDi4wAACOyGeHnCkR2Uz22dzGNBEdTanPL5cPWlBpWi5RlxgAAE/IZoeaKVH5bG5jmog22uK+SVIPWFR2Wd296vICAGBt7lazJSqf0W1cE9FGSsv5LPVwRZVqOVtcXAAAPDmbIWq2ROUzuo1rIlpvi/vL89SDFVXq843y4gIAYM3yjWrGROWzuo1tIlpPXS0H1UMV1GftJ/HT9KUFAMAa2SzxmTKYMXHZrG5jm4jWmv1E+6/lAxXW5Gp5YQEAsE4+U/SsiclndhvfRPRkHX/d8X+66/P96mGKKX9cXVQAAGyUzxY9cyLK9/vsbmOciI6U/WT4v/SDFFOq+Z3qkgIAYMNstqiZE5XP7jbGieiJWpxOvks9QFHZRXSnvKAAADhaNmPU7InKZ3gb50Sksgf7PPXwxJXPXHUxAQCwCXzG6NkTk73m89o4J6JhC9P8D9WDE1Yt1w0vJQAANpPPGjmDgvJZ3sY6ER2ePSA3DB+YsGr5jP3xVHUpAQCwWXzWtJmj51E8N7SxTkRfKfX534mHJSy7fK4cXkYAAGyRK9UsispnehvvRPTMa0/6c12fH1YPS1AfE5cQAABbxmfPYBYFlh/22d7GPNF8Zw/w7+oHJawLhxcQAABbyWfPYBaFZq/5d9uYJ5rfjj9QltQDElbNdwwvHwAAtoPPIDmbgvIZ38Y90XxmD8K4fkKt5S3q8gEAYMvZDFKzKbAL27gnmr8WpvlHxUMRVuon18iLBwCAbTO5Rs2oqHzWt7FPNF/ZA3DL8IEIq+ZHFmt+jb50AADYHj6LfCbJWRXTLW3sE81PqS79ingY4qr53erCAQBgu/lMkrMqKJ/5bfwTzX7H7y/fZg/p59TDEFLNH1EXDQAAO8Vnk5xZEdnM99nf1gCi2S7V8mr5IASVpvkCdckAALBjbDapmRWVz/62BhDNbovL+ST1AERlD+Zt8oIBAGCn2YxSsysq3wHaOkA0m6WaL1WHP6Sav5SmkzPk5QIAwE6zGeWzSs6wgHwHaOsA0ey1UJf+mTr4YU3LAXmxAAAQhM8qOcOC8l2grQVEs5X91Pl+deiDekhdKAAAROMzazDD4rJdoK0FRLNTquU/ywMflF0cVwwvEgAAgrpCzbKofCdo6wHR+Dt+Of+1rpbH1GGPKE3LveISAQAgLptdaqaFZDuB7wZtTSAad/aT22nyoAdlF8b5qy4QAABiO1/NtKh8N2hrAtF4W6hLf0Md8Lgmt4jLAwCA8HyG6dkWk+8IbV0gGmfdqP4zhfmLdkm8UV0eAABE5zPs0CxTMy4g2xHaukA0vlKd/HN5sINKfe7VxQEAwHjkXs24qHxXaGsD0Xg6ee/JX2c/qX1AHeqIUs0P6gsDAICRsZmmZl1Itiv4ztDWB6JxlGr5TXmgg7JL4TJ5WQAAMDY209Ssi8p3hrY+EMXvmdfm71QHObAPyIsCAICR8tk2mHWh+e7Q1gii2HXT/CZ1iKNaWC7nqksCAICx8tmmZl5Ytju0NYIobgv9Cd8nD3BQqeb3qgsCAIDRsxmnZl9UvkO0dYIoZl2f96nDG1Gq5Qv2ek+XlwMAACO3MuNWZp2eg/HkfW2dIIqXPVSn6IMbU1ouy8NLAQCAmWKzTs3AqOw1n9LWCqI47T64+xu6Wj6qDm1INd+/6jIAAGAG+cyTszAi2yV8p2jrBVGMUp9fLg9sUGlaLlGXAQAAM8dmnpqFUflO0dYLop3v+P6EBXVQo0r95G55EQAAMLMmd6uZGJXvFm3NINrZuj6fqQ5pXJOz9SUAAMCsmpytZ2JU+cy2ZhDtXAv95O/rAxpT6vON+gIAAGDW5RvVbIzKd4y2bhDtTF0tB9ThDOqzaVpO0w8/AAAzzmagz8LBbIzLdoy2bhBtf/bQ/Lw8mEGlmveteugBAJgnNgvVjIzKXvPPt7WDaPvafXD3n7KftD6pDmVQH1/1sAMAMId8Jg5mZFy2a/jO0dYPou0p9fl/ygMZVJpO3qkedgAA5o7NRDUro/Kdo60fRFvfrv7EZ6qDGFWq+U75oAMAMK9sNqqZGZXvHm0NIdrauj6fqw5hWNN8pnzIAQCYUz4b5cwMK5/b1hCircsejufrAxiTvd7rD3+wAQDAV12vZmdU9nqf39YRoq3JDtp4HopaPmN/PHXwUAMAAOMzss1KPUfjub6tI0SbX+rzL4pDF5Y9xFcNH2oAAPA4V6kZGpXvIm0tIdq8dh/c/S12wB4aHrjAPiYeZgAAMOAzczBDI3vId5K2nhBtTl2fXyUOW1gL/eRC9TADAIDH85mpZmlc+VVtPSE6+nbtL0v6oEWV71APMgAA0Hx26pkak+8mbU0hOrq6Wkb2k155i3qIAQCA5rNzMEtjs92krSlEG29hOf+oPGBBpZqvVQ8wAAB4EjZD1WyNyneUtq4QbSz7iekWdbiCemSx5tfIhxcAAByRz1CfpYPZGpftKG1dIVp/aTn/B3mwwpq8Wz24AABgbXyW6hkbk+8qbW0hWnvfdfWJf6mr+bPqUMWUP6IeWAAAsD4+U/WsDch2Fd9Z2vpCtLbS8srfmK4PVUQ1X6AeVgAAsD4+U+WsDcp3lra+ED15CwfKc9RBiipNy23qQQUAABtks1XN3Kh8d2lrDNGRswPzruEBCuxLi315s3xIAQDAhvhs9Rk7mLmRvautMURPXJrmfyoOT1y1HFAPKAAAODo+Y+XsDcp3mLbOEOlG9V9GmZaH1IMJAAA2h89aOYNDyne0dYZodanP/0kfnJjsAbxi+EACAIBNdYWawVH5LtPWGqKvddw1k6fa4fiiOjQRpZo/JB5GAACw2Wzmqlkcke8yvtO09YboUHY4Xjc8LJEt9uV8+TACAIBN5TNXzeLAXtfWGyL/14nl7xWHJK6ab1UPIgAA2Bo+e+VMDsp3m7bm0LxnB2Lv8ICEVfMXzZvUQwgAALaGz96VGaxmc0x725pD81ya5p8ShyOs1E969QACAICtNunVbI7Kd5y27tA8dvLek7+u6/M96nBElGp+UD94AABgW9gsVjM6pnyP7zpt7aF5K9Xym/pgxGQP12XyoQMAANvDZrGa0VH5rtPWHpqnjlvO36kORFi1fFA+cAAAYFv5TJazOijfedr6Q/PSyt9ULg5DYOeqhw0AAGwvn8mDGR2b7Txt/aF5aKEu/R15EIJKy+Vm9aABAIAdYrNZzeyofPdpaxDNevaTzT51CCJKtXyhm05Olw8ZAADYESuz2We0mN0h2e7T1iCa5exQ/ow8AEHZw7Q8fLgAAEAIy2p2R+U7UFuHaBYr+8ufsJ9oPqI+/Jjy/eKhAgAAQfis1jM8INuBfBdqaxHNWl0t/0N+8HG9Sz1UAAAgBp/Vg9kdm+1CbS2iWWpXXdolP/CgUj+5Wz1QAAAgmsndapZH5TtRW49oVupqfqv6sAN7m36YAABAJD6zBzM8NtuJ2npEs1CqS39PftBBpT7fqB4kAAAQVb5RzfSofDdqaxKNPfvJZao+5Jjy59K0nKYfIgAAEJLNbp/herYHZLtRW5NozKVa/pX8gIOynwj3yQcIAAAEN55/T7/zHamtSzTGjq1L32Qf4ifUhxuRv1b94AAAgFEY2d7hu1Jbm2hsdbX8jvpgw6rlYvnQAACAUfBZLmd8VLYrtbWJxtRCXTpefqBBpT7fqR4YAAAwNvlONeuj8p2prU80lrqaz1EfZlRpuZylHxYAADAqNtPVrA/Ldqa2PtEYSvvL8+UHGVSaluvlgwIAAMbJZrua+VH57tTWKIpeNy3XqQ8xotTnP7A/niofEgAAMEqHZvvKjJfzPxzbndoaRZGzQ/WL8gMMKtVylXpAAADAyNmMV7M/Kt+h2jpFEXvawd3fYgfrIfXhRWQH6r5VDwUAAJgh+T61A0Rkr/ch36XaWkXR6vr8KvXBxTW5cPUDAQAAZoXPer0DRJVf1dYqitTCdHKC/sCiyneoBwIAAMwWn/l6F4jJd6q2XlGU7BC9Q31Ygb1FPQwAAGC2+Mwf7ADB5Xe09YoiZIfoR/QHFVOq+drhQwAAAGaYzX61E0Rlr/lH2ppFO519IDcPP6DAHknT/JpVDwAAAJhdNvt9BxjsBJHd3NYs2slSn/+9+HDCSrW8Rz4AAABgttkOoHaDqHzHausW7UTPOPCsv2gfwnj+Zcw1f0QefAAAMBd8F5A7QkC+Y/mu1dYu2u66Pv+++mDCmpYL1KEHAADzwXcBuSOElX+/rV20nS1MJyfqDySmVMtt6sADAIA5YzuB2hWi8p2rrV+0Xdkbf8nwgwirli8v9uXN8rADAIC54juB7wZyZ4jpkrZ+0XZkh+SF4kOI7ODwkAMAgPnlu8FgVwjNXvML2xpGW5292berDyGohw4/2AAAAM53hMHOEJa93tvbGkZbWdfnl6oPIKpUy97hwQYAAPAdQe0OceWXtnWMtqLj9k2emvr8qH7z47HX+iF5sAEAAFbkD6kdIiLfwXwXa2sZbXZdLa9Tb3xUi305Xx9qAACAlX8w7Xy1Q4Rlu1hby2gzW1jO3yvf8KhqvlUdaAAAgMP5ziB3iaB8J2vrGW1W9hPEeP4+lloe66b5TeowAwAAHM53hpXdQe0UEdlO1tYz2ozScv4p+UYHlWqZqoMMAAAg2e6gdoqofDdraxodVWe+4I+kmu9Rb3JEqc8PygMMAABwRPlBtVtE5LuZ72htW6ON1tWl/6Le4KgWp/kyfXgBAACemO8QarcIy3a0tq7RRtq1vxwr39i4PqgOLgAAwFr4LjHYLULzXa2tbbTeulreqN7UsKblXHVoAQAA1sJ3CbljRGW7WlvbaD2l5fy35RsalB3Om4eHFQAAYANuVrtGVL6ztfWN1lpX89XqzYzIDuQX7I9vGBxSAACAdWs7he8Wcu8Ix3a2tr7RWrI37F/KNzKoNC3Lw0MKAACwYbZbqJ0jLNvd2hpHR+qpe0/+46nPH5ZvYkj5fnlAAQAAjoLvGHr3iMd3N9/h2jpHT1Q3Lf9dvYGBvUsdTgAAgKPhO8Zg54jNdri2zpFq4Zp8nHzjgrKfXu5RBxMAAGBzjOc/muV8l2trHQ2zN+gtwzcstFrepg8lAADA0fNdQ+4gcb2lrXV0eOlA/gHxZoWVarlJHUgAAIBNZTuH2kWi8p2urXf0lVKfe/VmxZQ/l+rk9fIwAgAAbCbbOXz30DtJPL7TtfWOvG46ebF6o8KqeZ88iAAAAFvAdw+5k0Rlu11b8+a7Y+vSN9nm/3H5JgWUavmEOoAAAABbynYQtZtE5Lud73ht3Zvfulp+R71BYdVysTx8AAAAW8h3ELmbRGU7Xlv35rOFunS8fGOCSsvlLnXwAAAAtoXtImpHicp3vbb2zV9dzeeoNyUqO2BnrTpwAAAA2+cstaOEZbteW/vmq1SXfki+IUHZTyQ3iMMGAACwrXwnUbtKVL7ztfVvfko1X6fejIjstf5Bd6Ccqg4bAADAdlrZSXw3ETtLRL7ztfVvPupq+bfqjQjsKnXQAAAAdoLvJoNdJTbb/doaONs9oz/hz6ZaPiXfhIBSn+9TBwwAAGBn5fvU7hKR736+A7Z1cHbrav4/6g2Iyg7SRasPFgAAwI67SO0uYdkO2NbB2Sz1JzxbfuNB2U9Kd4hDBQAAEES+Q+0wUfku2NbC2cs2+QvUNx1WnbxVHyoAAICd57uK3GGisl2wrYWzVddPXiC/4aDsJ6Rr1YECAACIJV+rdpm4Ji9o6+HslGp5r/5m47HX+uk0za/RhwkAACAQ31lsd1E7TUS+E7b1cDbqavll9Y1GlablPfIgAQAARGS7i9ppwrLdsK2J425Xf8K32ub+GflNBmSv9aPyAAEAAERmO4zabSLy3dB3xLYujreu5t9T32Bg75CHBwAAIDDfYQY7TWy2I7Z1cZyl/sSJ/MaCStNymzo4AAAAo2C7jNpxovJdsa2N4yvVfLH6pqJK/dIeeWgAAABGYWmP2nGi8l2xrY3jKu0vL1TfUGAH9YEBAAAYD99pBjtOaL4ztvVxPKVablffTESpzw+rgwIAADBO+WG180TkO2NbH8dRt5xfqr6RwPbqQwIAADA+vtsMdp3YbHdsa2Tsdl31nL9qP0U8Kr+JgFLNH1YHBAAAYNRsx1G7T0S+O/oO2dbJuHV9PlV9A1Et9uV8eTgAAABGzHcctfvElU9t62TM0v5ysn7hUeVb1cEAAACYBb7r6B0oJt8l21oZL3tDr1AvOqRaHuum+U3DAwEAADArfNdZ2XnULhSQveYr2loZK/uJ4SfVCw6rlunwMAAAAMwa33nkLhRW/sm2Xgbpy8f8YXsj79YvNp40LQ8ODwEAAMDMst1H7UQR2eu923fLtmXufLZ5/4Z6oYFdvuoAAAAAzCjffQa7UHD5N9qaubMtHDjxO/QLDKqWD6oDAAAAMMt8B5K7UVC+Y7Z1c+eyF/KG4QsL7lz14QMAAMwy34EGO1F0b2jr5s7UTcvfEi8qLPuQbx5+6AAAAHPkZrUjhWW7Zls7tz97s66SLyqgVFf+a21vGHzYAAAAc2NlFzq0E8l9KRp7zVe1tXN76/r8IvWCwqqlDj9sAACAeeM7kdyVwsovauvn9nTs7d//9anPH9IvJqJ8v/qgAQAA5pHvRnpnisd3Tt892xq69XX95GXqhUSVar5UfcgAAABzyXYjtTPFNXlZW0O3toXlfJx+ATHZTwH3yA8YAABgruV71O4Ule+gbR3duuwL7Rl+4eDepj9cAACA+eU70mBnim5PW0e3prScf0B80bhquUl9sAAAAFj5B9NukjtUUL6LtrV080s19+qLhlTz59N08nr1oQIAAMDYruQ7k9ylAvJdtK2lm1tXl16svmBYNe+XHygAAAC+yncmuUtFZTtpW083p6dffeKftA364/KLBZRq+YT6IAEAACDY7qR2qoh8J/XdtK2pR19Xy2+rLxTWtFwsP0QAAACs4ruT3Kmist20ralHV1rOi/ILBGUf1l3DDw8AAABP6i61W0XlO2pbVzeebcyj+ldPpGk5S3xwAAAAOBLbodRuFZbtqG1d3VhdXfoH8jcGAAAAdprtqm1tXX+p5mvlbwoAAADsMN9V29q6vrpa/o36DQEAAIAwbGdt6+va2rW//BnbkB+UvxkAAAAQhO+svru2NfbJs834f6vfCAAAAAjHdte2xh65rubd8jcAAAAAorIdtq2zT1zq89vlLwYAAACC8h22rbO6ri79sPqFAAAAQHi2y7a1dnW2Cd8kfxEAAAAQnO+yba19fN20vET9AgAAAGA0bKdt6+3XSjW/T/7FAAAAwEj4TtvW20MtTsvz1F8IAAAAjI3vtm3NXflXip2j/iIAAABgdGy3XVlyFw6c+B3yLwAAAABGynfcY7rp5MXqTwIAAACjZTuu/+d+f1v+SQAAAGCsbMc9JtXyNvknAQAAgJFKfTnb/yMR16g/CQAAAIyV77j+7899QP1JAAAAYKx8x/X/RfdB9ScBAACAsfId1/8X3WvVnwQAAADGyndc/mE0AAAAzJyVfxjN/o9XDP8EAAAAMHKvOKZbzj8n/gQAAAAwXrbjHrPrmnKs/JMAAADASPmOe4zX1XyO+gsAAACA8cnnriy53uL+8jz9FwEAAADjsjgtz2tr7qG6mm9VfyEAAAAwGrbTtvX2ay1MJ78k/2IAAABgJHynbevt40t9frP6BQAAAEB0vsu2tXZ1i5csPiXV8l71CwEAAICoUl9u9l22rbW61J84Ub8YAAAAiMp32LbOHrl0oPyM+g0AAACAaHx3bWvs2tq1nE+yX3jL8DcCAAAAgrhl4UB5Tltf19euvSd/Y+rLHvGbAgAAADsm1bLHd9W2tm68rpZfTjW/T30RAAAAYLus7KS2m7Y1dfPqpvkHU1/OU18UAAAA2CorO6jtom0t3boW+xOeZl/slNTn37I/nmWb9TX2fz+gXhQAAACwVr5THtotbcc8tGue0l397Ke3NXQdHXPM/w+LdBQvQyJLdgAAAABJRU5ErkJggg==\",\"data:image/png;base64,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\",\"data:image/png;base64,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\",\"data:image/png;base64,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Number: 74
Class: Marine (Enterococcus<\\/i>)
Category: 130 - 999 (168/100mL)<\\/html>\",\"Station Number: 111
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (50/100mL)<\\/html>\",\"Station Number: 114
Class: Freshwater (E. coli<\\/i>)
Category: 410 - 999 (447/100mL)<\\/html>\",\"Station Number: 115
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (80/100mL)<\\/html>\",\"Station Number: 116
Class: Freshwater (E. coli<\\/i>)
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Class: Freshwater (E. coli<\\/i>)
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Class: Freshwater (E. coli<\\/i>)
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Class: Marine (Enterococcus<\\/i>)
Category: > 999 (4000/100mL)<\\/html>\",\"Station Number: 154
Class: Freshwater (E. coli<\\/i>)
Category: 410 - 999 (433/100mL)<\\/html>\",\"Station Number: 155
Class: Freshwater (E. coli<\\/i>)
Category: 126 - 409 (170/100mL)<\\/html>\",\"Station Number: 166
Class: Freshwater (E. coli<\\/i>)
Category: 126 - 409 (310/100mL)<\\/html>\",\"Station Number: 178
Class: Marine (Enterococcus<\\/i>)
Category: 130 - 999 (650/100mL)<\\/html>\",\"Station Number: 179
Class: Marine (Enterococcus<\\/i>)
Category: > 999 (1010/100mL)<\\/html>\"],{\"interactive\":false,\"permanent\":false,\"direction\":\"auto\",\"opacity\":1,\"offset\":[0,0],\"textsize\":\"10px\",\"textOnly\":false,\"className\":\"\",\"sticky\":true},null]},{\"method\":\"addControl\",\"args\":[\"Marine (Enterococcus<\\/em>)<\\/b>
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> 999\",\"topright\",null,\"info legend\"]},{\"method\":\"addControl\",\"args\":[\"Freshwater (E. Coli<\\/em>)<\\/b>
#/100mL
< 126
126 - 409
410 - 999
> 999\",\"topright\",null,\"info legend\"]}],\"limits\":{\"lat\":[27.722349,27.937863],\"lng\":[-82.383348,-82.061156]}},\"evals\":[],\"jsHooks\":{\"render\":[{\"code\":\"function(el, x, data) {\\n return (\\n function(el, x) {\\n var myMap = this;\\n myMap.on('baselayerchange',\\n function (e) {\\n myMap.minimap.changeLayer(L.tileLayer.provider(e.name));\\n })\\n }).call(this.getMap(), el, x, data);\\n}\",\"data\":null}]}}"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_fibmatrix.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot a matrix of Fecal Indicator Bacteria categories over time by station — show_fibmatrix","title":"Plot a matrix of Fecal Indicator Bacteria categories over time by station — show_fibmatrix","text":"Plot matrix Fecal Indicator Bacteria categories time station","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_fibmatrix.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot a matrix of Fecal Indicator Bacteria categories over time by station — show_fibmatrix","text":"","code":"show_fibmatrix( fibdata, yrrng = NULL, stas = c(143, 108, 107, 135, 118, 148, 105, 152, 137), lagyr = 3, txtsz = 3, asreact = FALSE, nrows = 10, family = NA, plotly = FALSE, width = NULL, height = NULL )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_fibmatrix.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot a matrix of Fecal Indicator Bacteria categories over time by station — show_fibmatrix","text":"fibdata input data frame returned read_importfib yrrng numeric vector indicating min, max years include, defaults range years epcdata stas optional numeric vector stations include, see details lagyr numeric year lag calculate categories, see details txtsz numeric size text plot, applies tab = FALSE. Use txtsz = NULL suppress. asreact logical indicating reactable object returned nrows asreact = TRUE, numeric specifying number rows table family optional chr string indicating font family text labels plotly logical matrix created using plotly width numeric width plot pixels, applies plotly = TRUE height numeric height plot pixels, applies plotly = TRUE","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_fibmatrix.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot a matrix of Fecal Indicator Bacteria categories over time by station — show_fibmatrix","text":"static ggplot object returned default. reactable table returned asreact = TRUE. interactive plotly object returned plotly = TRUE.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_fibmatrix.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Plot a matrix of Fecal Indicator Bacteria categories over time by station — show_fibmatrix","text":"matrix color codes years stations based likelihood fecal indicator bacteria concentrations exceeding 400 CFU / 100 mL (using Fecal Coliform, fcolif fibdata). likelihoods categorized , B, C, D, E (Microbial Water Quality Assessment MWQA categories) corresponding colors, breakpoints category <10%, 10-30%, 30-50%, 50-75%, >75% (right-closed). default, results year based right-centered window uses previous two years current year calculate probabilities monthly samples (lagyr = 3). Methods rationale categorization scheme provided Florida Department Environmental Protection, Figure 8 document http://publicfiles.dep.state.fl.us/DEAR/BMAP/Tampa/MST%20Report/Fecal%20BMAP%20DST%20Final%20Report%20--%20June%202008.pdf Morrison et al. 2009 BASIS 5 proceedings. default stations used TBEP report #05-13 (https://drive.google.com/file/d/1MZnK3cMzV7LRg6dTbCKX8AOZU0GNurJJ/view) Hillsborough River Basin Management Action Plan (BMAP) subbasins. include Blackwater Creek (WBID 1482, EPC stations 143, 108), Baker Creek (WBID 1522C, EPC station 107), Lake Thonotosassa (WBID 1522B, EPC stations 135, 118), Flint Creek (WBID 1522A, EPC station 148), Lower Hillsborough River (WBID 1443E, EPC stations 105, 152, 137). stations fibdata can plotted using stas argument.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_fibmatrix.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot a matrix of Fecal Indicator Bacteria categories over time by station — show_fibmatrix","text":"","code":"show_fibmatrix(fibdata)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_hmpreport.html","id":null,"dir":"Reference","previous_headings":"","what":"Show Habitat Master Plan progress report card — show_hmpreport","title":"Show Habitat Master Plan progress report card — show_hmpreport","text":"Show Habitat Master Plan progress report card","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_hmpreport.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Show Habitat Master Plan progress report card — show_hmpreport","text":"","code":"show_hmpreport( acres, subtacres, hmptrgs, typ, twocol = FALSE, strata = c(\"Subtidal\", \"Intertidal\", \"Supratidal\"), ycollapse = FALSE, text = 2.5, xang = 25, family = NA, width = NULL, height = NULL )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_hmpreport.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Show Habitat Master Plan progress report card — show_hmpreport","text":"acres data.frame intertidal supratidal land use cover habitat types year data subtacres data.frame subtidal cover habitat types year data hmptrgs data.frame Habitat Master Plan targets goals typ character string indicating \"targets\" \"goals\" twocol logical indicating two colors show target goals met symbols indicate likelihood attaining targets goals, see details strata character string indicating strata plot, one many \"Subtidal\", \"Intertidal\", \"Supratidal\" ycollapse logical indicating y-axis collapsed year data, see details text numeric indicating text size proportion target goal met habitat types shown cell types symbols twocol = T, use NULL suppress xang numeric angle habitat labels x-axis (top) family optional chr string indicating font family text labels width numeric width plot pixels, applies plotly = TRUE height numeric height plot pixels, applies plotly = TRUE","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_hmpreport.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Show Habitat Master Plan progress report card — show_hmpreport","text":"ggplot2 object showing overall progress attaining Habitat Master Plan targets goals.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_hmpreport.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Show Habitat Master Plan progress report card — show_hmpreport","text":"twocol = F, colors indicate target/goal met likelihood attaining target/goal 2030/2050. Red indicates target/goal met likely met 2030/2050 (trending target/goal), yellow indicates target/goal met although likely met 2030/2050 (trending target/goal), light green indicates target/goal met although likely met 2030/2050 (trending target/goal), green indicates target/goal met likely met 2030/2050 (trending target/goal). Numbers cell show proportion target goal met year data available. twocol = T, colors indicate goal met (green) met (red) symbols cell indicate goal likely met (arrow) (arrow) 2030/2050. cases, colors trends relative 2030 targets 2050 goals using typ argument. report card provides information artificial reefs, living shorelines, hard bottom habitats. habitats assessed routine data products Southwest Florida Water Management District, although targets goals provided Habitat Master Plan. subtidal data subtacres inter/supratidal data acres provided different datasets Southwest Florida Water Management District. years dataset typically match dataset collected approximate 2 3 year intervals. default, year y-axis shown continuous variable, gaps shown years dataset unavailable. Use ycollapse = TRUE remove years without data.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_hmpreport.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Show Habitat Master Plan progress report card — show_hmpreport","text":"","code":"# view summarized data for report card, targets show_hmpreport(acres, subtacres, hmptrgs, typ = \"targets\") # view summarized data for report card, goals show_hmpreport(acres, subtacres, hmptrgs, typ = \"goals\") # remove empty years show_hmpreport(acres, subtacres, hmptrgs, typ = \"targets\", ycollapse = TRUE) # select only subtidal show_hmpreport(acres, subtacres, hmptrgs, typ = \"targets\", ycollapse = TRUE, strata = 'Subtidal')"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_matrix.html","id":null,"dir":"Reference","previous_headings":"","what":"Create a colorized table for indicator reporting — show_matrix","title":"Create a colorized table for indicator reporting — show_matrix","text":"Create colorized table indicator reporting","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_matrix.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Create a colorized table for indicator reporting — show_matrix","text":"","code":"show_matrix( epcdata, txtsz = 3, trgs = NULL, yrrng = NULL, bay_segment = c(\"OTB\", \"HB\", \"MTB\", \"LTB\"), asreact = FALSE, nrows = 10, abbrev = FALSE, family = NA, historic = TRUE, plotly = FALSE, partialyr = FALSE, width = NULL, height = NULL )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_matrix.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Create a colorized table for indicator reporting — show_matrix","text":"epcdata data frame epc data returned read_importwq txtsz numeric size text plot, applies tab = FALSE trgs optional data.frame annual bay segment water quality targets, defaults targets yrrng numeric vector indicating min, max years include, defaults range years epcdata bay_segment chr string bay segments include, one \"OTB\", \"HB\", \"MTB\", \"LTB\" asreact logical indicating reactable object returned nrows asreact = TRUE, numeric specifying number rows table abbrev logical indicating text labels plot abbreviated first letter family optional chr string indicating font family text labels historic logical historic data used 2005 earlier plotly logical matrix created using plotly partialyr logical indicating incomplete annual data recent year approximated five year monthly averages parameter width numeric width plot pixels, applies plotly = TRUE height numeric height plot pixels, applies plotly = TRUE","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_matrix.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Create a colorized table for indicator reporting — show_matrix","text":"static ggplot object returned asreact = FALSE, otherwise reactable table returned","code":""},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_matrix.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Create a colorized table for indicator reporting — show_matrix","text":"","code":"show_matrix(epcdata)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_matrixplotly.html","id":null,"dir":"Reference","previous_headings":"","what":"Creates a plotly matrix from any matrix function input — show_matrixplotly","title":"Creates a plotly matrix from any matrix function input — show_matrixplotly","text":"Creates plotly matrix matrix function input","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_matrixplotly.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Creates a plotly matrix from any matrix function input — show_matrixplotly","text":"","code":"show_matrixplotly( mat, family = NA, tooltip = \"Result\", width = NULL, height = NULL )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_matrixplotly.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Creates a plotly matrix from any matrix function input — show_matrixplotly","text":"mat input matrix output show_matrix, show_segmatrix, show_wqmatrix, show_tbnimatrix family optional chr string indicating font family text labels tooltip chr string indicating column name tooltip width numeric width plot pixels height numeric height plot pixels","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_matrixplotly.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Creates a plotly matrix from any matrix function input — show_matrixplotly","text":"plotly data object","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_matrixplotly.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Creates a plotly matrix from any matrix function input — show_matrixplotly","text":"","code":"mat <- show_wqmatrix(epcdata) show_matrixplotly(mat) {\"x\":{\"data\":[{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-2001.5,-2000.5,-2000.5,-2001.5,-2001.5],\"text\":\"Result: Below (Average: 10.1, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":true,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-1999.5,-1998.5,-1998.5,-1999.5,-1999.5],\"text\":\"Result: Below (Average: 10.3, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-2020.5,-2019.5,-2019.5,-2020.5,-2020.5],\"text\":\"Result: Below (Average: 10.5, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-2006.5,-2005.5,-2005.5,-2006.5,-2006.5],\"text\":\"Result: Below (Average: 10.9, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-2019.5,-2018.5,-2018.5,-2019.5,-2019.5],\"text\":\"Result: Below (Average: 11, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-1992.5,-1991.5,-1991.5,-1992.5,-1992.5],\"text\":\"Result: Below (Average: 11.1, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-2011.5,-2010.5,-2010.5,-2011.5,-2011.5],\"text\":\"Result: Below (Average: 11.2, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-2016.5,-2015.5,-2015.5,-2016.5,-2016.5],\"text\":\"Result: Below (Average: 11.4, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-2008.5,-2007.5,-2007.5,-2008.5,-2008.5],\"text\":\"Result: Below (Average: 11.6, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-2004.5,-2003.5,-2003.5,-2004.5,-2004.5],\"text\":\"Result: Below (Average: 11.9, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-1997.5,-1996.5,-1996.5,-1997.5,-1997.5],\"text\":\"Result: Below (Average: 12, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-2003.5,-2002.5,-2002.5,-2003.5,-2003.5],\"text\":\"Result: Below (Average: 12.4, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-2012.5,-2011.5,-2011.5,-2012.5,-2012.5],\"text\":\"Result: Below (Average: 12.6, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-1990.5,-1989.5,-1989.5,-1990.5,-1990.5],\"text\":\"Result: Below (Average: 12.8, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-2013.5,-2012.5,-2012.5,-2013.5,-2013.5],\"text\":\"Result: Below (Average: 12.9, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-1988.5,-1987.5,-1987.5,-1988.5,-1988.5],\"text\":\"Result: Below (Average: 13, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5],\"y\":[-1984.5,-1983.5,-1983.5,-1984.5,-1984.5,null,-2005.5,-2004.5,-2004.5,-2005.5,-2005.5,null,-2014.5,-2013.5,-2013.5,-2014.5,-2014.5],\"text\":\"Result: Below (Average: 13.1, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-2002.5,-2001.5,-2001.5,-2002.5,-2002.5],\"text\":\"Result: Below (Average: 13.7, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-2018.5,-2017.5,-2017.5,-2018.5,-2018.5],\"text\":\"Result: Below (Average: 13.9, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-1991.5,-1990.5,-1990.5,-1991.5,-1991.5],\"text\":\"Result: Below (Average: 14.1, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5],\"y\":[-1987.5,-1986.5,-1986.5,-1987.5,-1987.5,null,-1989.5,-1988.5,-1988.5,-1989.5,-1989.5],\"text\":\"Result: Below (Average: 14.2, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-2009.5,-2008.5,-2008.5,-2009.5,-2009.5],\"text\":\"Result: Below (Average: 14.6, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5],\"y\":[-1996.5,-1995.5,-1995.5,-1996.5,-1996.5],\"text\":\"Result: Below (Average: 2.2, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5],\"y\":[-2023.5,-2022.5,-2022.5,-2023.5,-2023.5],\"text\":\"Result: Below (Average: 2.6, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5,null,3.5,3.5,4.5,4.5,3.5],\"y\":[-2008.5,-2007.5,-2007.5,-2008.5,-2008.5,null,-2020.5,-2019.5,-2019.5,-2020.5,-2020.5],\"text\":\"Result: Below (Average: 2.8, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5],\"y\":[-2016.5,-2015.5,-2015.5,-2016.5,-2016.5],\"text\":\"Result: Below (Average: 3, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5],\"y\":[-2007.5,-2006.5,-2006.5,-2007.5,-2007.5],\"text\":\"Result: Below (Average: 3.1, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5],\"y\":[-2021.5,-2020.5,-2020.5,-2021.5,-2021.5],\"text\":\"Result: Below (Average: 3.2, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5],\"y\":[-2017.5,-2016.5,-2016.5,-2017.5,-2017.5],\"text\":\"Result: Below (Average: 3.3, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5,null,3.5,3.5,4.5,4.5,3.5],\"y\":[-2003.5,-2002.5,-2002.5,-2003.5,-2003.5,null,-2014.5,-2013.5,-2013.5,-2014.5,-2014.5],\"text\":\"Result: Below (Average: 3.4, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5],\"y\":[-1988.5,-1987.5,-1987.5,-1988.5,-1988.5],\"text\":\"Result: Below (Average: 3.5, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5,null,3.5,3.5,4.5,4.5,3.5,null,3.5,3.5,4.5,4.5,3.5,null,3.5,3.5,4.5,4.5,3.5],\"y\":[-1987.5,-1986.5,-1986.5,-1987.5,-1987.5,null,-1991.5,-1990.5,-1990.5,-1991.5,-1991.5,null,-1993.5,-1992.5,-1992.5,-1993.5,-1993.5,null,-2022.5,-2021.5,-2021.5,-2022.5,-2022.5],\"text\":\"Result: Below (Average: 3.6, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5],\"y\":[-2006.5,-2005.5,-2005.5,-2006.5,-2006.5],\"text\":\"Result: Below (Average: 3.7, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-2023.5,-2022.5,-2022.5,-2023.5,-2023.5],\"text\":\"Result: Below (Average: 3.7, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5],\"y\":[-2002.5,-2001.5,-2001.5,-2002.5,-2002.5],\"text\":\"Result: Below (Average: 3.8, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5,null,3.5,3.5,4.5,4.5,3.5,null,3.5,3.5,4.5,4.5,3.5,null,3.5,3.5,4.5,4.5,3.5,null,3.5,3.5,4.5,4.5,3.5,null,3.5,3.5,4.5,4.5,3.5],\"y\":[-1984.5,-1983.5,-1983.5,-1984.5,-1984.5,null,-1986.5,-1985.5,-1985.5,-1986.5,-1986.5,null,-2010.5,-2009.5,-2009.5,-2010.5,-2010.5,null,-2013.5,-2012.5,-2012.5,-2013.5,-2013.5,null,-2015.5,-2014.5,-2014.5,-2015.5,-2015.5,null,-2019.5,-2018.5,-2018.5,-2019.5,-2019.5],\"text\":\"Result: Below (Average: 3.9, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5],\"y\":[-1992.5,-1991.5,-1991.5,-1992.5,-1992.5],\"text\":\"Result: Below (Average: 4, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5],\"y\":[-1990.5,-1989.5,-1989.5,-1990.5,-1990.5],\"text\":\"Result: Below (Average: 4.1, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5],\"y\":[-1999.5,-1998.5,-1998.5,-1999.5,-1999.5],\"text\":\"Result: Below (Average: 4.2, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5],\"y\":[-2011.5,-2010.5,-2010.5,-2011.5,-2011.5],\"text\":\"Result: Below (Average: 4.3, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5,null,3.5,3.5,4.5,4.5,3.5,null,3.5,3.5,4.5,4.5,3.5],\"y\":[-1995.5,-1994.5,-1994.5,-1995.5,-1995.5,null,-2009.5,-2008.5,-2008.5,-2009.5,-2009.5,null,-2012.5,-2011.5,-2011.5,-2012.5,-2012.5],\"text\":\"Result: Below (Average: 4.4, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5],\"y\":[-2000.5,-1999.5,-1999.5,-2000.5,-2000.5],\"text\":\"Result: Below (Average: 4.5, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5],\"y\":[-1997.5,-1996.5,-1996.5,-1997.5,-1997.5],\"text\":\"Result: Below (Average: 4.6, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5],\"y\":[-2018.5,-2017.5,-2017.5,-2018.5,-2018.5],\"text\":\"Result: Below (Average: 4.7, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5,null,3.5,3.5,4.5,4.5,3.5,null,3.5,3.5,4.5,4.5,3.5],\"y\":[-1978.5,-1977.5,-1977.5,-1978.5,-1978.5,null,-1985.5,-1984.5,-1984.5,-1985.5,-1985.5,null,-2001.5,-2000.5,-2000.5,-2001.5,-2001.5],\"text\":\"Result: Below (Average: 4.8, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5],\"y\":[-1975.5,-1974.5,-1974.5,-1975.5,-1975.5],\"text\":\"Result: Below (Average: 4.9, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5],\"y\":[-2021.5,-2020.5,-2020.5,-2021.5,-2021.5,null,-2022.5,-2021.5,-2021.5,-2022.5,-2022.5],\"text\":\"Result: Below (Average: 5, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5,null,3.5,3.5,4.5,4.5,3.5,null,3.5,3.5,4.5,4.5,3.5],\"y\":[-1976.5,-1975.5,-1975.5,-1976.5,-1976.5,null,-1989.5,-1988.5,-1988.5,-1989.5,-1989.5,null,-2004.5,-2003.5,-2003.5,-2004.5,-2004.5],\"text\":\"Result: Below (Average: 5.1, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-2006.5,-2005.5,-2005.5,-2006.5,-2006.5],\"text\":\"Result: Below (Average: 5.1, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-1996.5,-1995.5,-1995.5,-1996.5,-1996.5],\"text\":\"Result: Below (Average: 5.3, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5],\"y\":[-2007.5,-2006.5,-2006.5,-2007.5,-2007.5,null,-2020.5,-2019.5,-2019.5,-2020.5,-2020.5],\"text\":\"Result: Below (Average: 5.5, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5],\"y\":[-2008.5,-2007.5,-2007.5,-2008.5,-2008.5,null,-2016.5,-2015.5,-2015.5,-2016.5,-2016.5,null,-2019.5,-2018.5,-2018.5,-2019.5,-2019.5],\"text\":\"Result: Below (Average: 5.7, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-2017.5,-2016.5,-2016.5,-2017.5,-2017.5],\"text\":\"Result: Below (Average: 5.8, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5],\"y\":[-2000.5,-1999.5,-1999.5,-2000.5,-2000.5,null,-2002.5,-2001.5,-2001.5,-2002.5,-2002.5,null,-2010.5,-2009.5,-2009.5,-2010.5,-2010.5],\"text\":\"Result: Below (Average: 6.1, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-2023.5,-2022.5,-2022.5,-2023.5,-2023.5],\"text\":\"Result: Below (Average: 6.2, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-2006.5,-2005.5,-2005.5,-2006.5,-2006.5],\"text\":\"Result: Below (Average: 6.3, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5],\"y\":[-1992.5,-1991.5,-1991.5,-1992.5,-1992.5,null,-2009.5,-2008.5,-2008.5,-2009.5,-2009.5],\"text\":\"Result: Below (Average: 6.5, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5],\"y\":[-1993.5,-1992.5,-1992.5,-1993.5,-1993.5,null,-2004.5,-2003.5,-2003.5,-2004.5,-2004.5],\"text\":\"Result: Below (Average: 6.6, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5],\"y\":[-2013.5,-2012.5,-2012.5,-2013.5,-2013.5,null,-2014.5,-2013.5,-2013.5,-2014.5,-2014.5],\"text\":\"Result: Below (Average: 6.8, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-1996.5,-1995.5,-1995.5,-1996.5,-1996.5],\"text\":\"Result: Below (Average: 6.8, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-2023.5,-2022.5,-2022.5,-2023.5,-2023.5],\"text\":\"Result: Below (Average: 6.9, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-2018.5,-2017.5,-2017.5,-2018.5,-2018.5],\"text\":\"Result: Below (Average: 7, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-2022.5,-2021.5,-2021.5,-2022.5,-2022.5],\"text\":\"Result: Below (Average: 7.1, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-1999.5,-1998.5,-1998.5,-1999.5,-1999.5],\"text\":\"Result: Below (Average: 7.2, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-2000.5,-1999.5,-1999.5,-2000.5,-2000.5],\"text\":\"Result: Below (Average: 7.2, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-2010.5,-2009.5,-2009.5,-2010.5,-2010.5],\"text\":\"Result: Below (Average: 7.4, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-2005.5,-2004.5,-2004.5,-2005.5,-2005.5],\"text\":\"Result: Below (Average: 7.6, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-1993.5,-1992.5,-1992.5,-1993.5,-1993.5],\"text\":\"Result: Below (Average: 7.6, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5],\"y\":[-1988.5,-1987.5,-1987.5,-1988.5,-1988.5,null,-2001.5,-2000.5,-2000.5,-2001.5,-2001.5],\"text\":\"Result: Below (Average: 7.7, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5],\"y\":[-2003.5,-2002.5,-2002.5,-2003.5,-2003.5,null,-2012.5,-2011.5,-2011.5,-2012.5,-2012.5],\"text\":\"Result: Below (Average: 7.8, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5],\"y\":[-2002.5,-2001.5,-2001.5,-2002.5,-2002.5,null,-2012.5,-2011.5,-2011.5,-2012.5,-2012.5],\"text\":\"Result: Below (Average: 7.8, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-1991.5,-1990.5,-1990.5,-1991.5,-1991.5],\"text\":\"Result: Below (Average: 7.9, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5],\"y\":[-1992.5,-1991.5,-1991.5,-1992.5,-1992.5,null,-2014.5,-2013.5,-2013.5,-2014.5,-2014.5],\"text\":\"Result: Below (Average: 7.9, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5],\"y\":[-1997.5,-1996.5,-1996.5,-1997.5,-1997.5,null,-2011.5,-2010.5,-2010.5,-2011.5,-2011.5],\"text\":\"Result: Below (Average: 8, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-2015.5,-2014.5,-2014.5,-2015.5,-2015.5],\"text\":\"Result: Below (Average: 8.1, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-1999.5,-1998.5,-1998.5,-1999.5,-1999.5],\"text\":\"Result: Below (Average: 8.1, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-1986.5,-1985.5,-1985.5,-1986.5,-1986.5],\"text\":\"Result: Below (Average: 8.2, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-1988.5,-1987.5,-1987.5,-1988.5,-1988.5],\"text\":\"Result: Below (Average: 8.2, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-2007.5,-2006.5,-2006.5,-2007.5,-2007.5],\"text\":\"Result: Below (Average: 8.3, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-1991.5,-1990.5,-1990.5,-1991.5,-1991.5],\"text\":\"Result: Below (Average: 8.3, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5],\"y\":[-1989.5,-1988.5,-1988.5,-1989.5,-1989.5,null,-1990.5,-1989.5,-1989.5,-1990.5,-1990.5],\"text\":\"Result: Below (Average: 8.4, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5],\"y\":[-1997.5,-1996.5,-1996.5,-1997.5,-1997.5,null,-2005.5,-2004.5,-2004.5,-2005.5,-2005.5],\"text\":\"Result: Below (Average: 8.4, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5],\"y\":[-2001.5,-2000.5,-2000.5,-2001.5,-2001.5,null,-2007.5,-2006.5,-2006.5,-2007.5,-2007.5],\"text\":\"Result: Below (Average: 8.6, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-2013.5,-2012.5,-2012.5,-2013.5,-2013.5],\"text\":\"Result: Below (Average: 8.7, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-2000.5,-1999.5,-1999.5,-2000.5,-2000.5],\"text\":\"Result: Below (Average: 8.8, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-2022.5,-2021.5,-2021.5,-2022.5,-2022.5],\"text\":\"Result: Below (Average: 8.9, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-2015.5,-2014.5,-2014.5,-2015.5,-2015.5],\"text\":\"Result: Below (Average: 9, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-2016.5,-2015.5,-2015.5,-2016.5,-2016.5],\"text\":\"Result: Below (Average: 9, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5],\"y\":[-1984.5,-1983.5,-1983.5,-1984.5,-1984.5,null,-2018.5,-2017.5,-2017.5,-2018.5,-2018.5],\"text\":\"Result: Below (Average: 9.2, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-2008.5,-2007.5,-2007.5,-2008.5,-2008.5],\"text\":\"Result: Below (Average: 9.3, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-1996.5,-1995.5,-1995.5,-1996.5,-1996.5],\"text\":\"Result: Below (Average: 9.6, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-2017.5,-2016.5,-2016.5,-2017.5,-2017.5],\"text\":\"Result: Below (Average: 9.7, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5],\"y\":[-1993.5,-1992.5,-1992.5,-1993.5,-1993.5,null,-2010.5,-2009.5,-2009.5,-2010.5,-2010.5],\"text\":\"Result: Below (Average: 9.8, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-2021.5,-2020.5,-2020.5,-2021.5,-2021.5],\"text\":\"Result: Below (Average: 9.9, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-1976.5,-1975.5,-1975.5,-1976.5,-1976.5],\"text\":\"Result: Above (Average: 10, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":true,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-1995.5,-1994.5,-1994.5,-1995.5,-1995.5],\"text\":\"Result: Above (Average: 10.3, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-1986.5,-1985.5,-1985.5,-1986.5,-1986.5],\"text\":\"Result: Above (Average: 10.6, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-2015.5,-2014.5,-2014.5,-2015.5,-2015.5],\"text\":\"Result: Above (Average: 10.7, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-1976.5,-1975.5,-1975.5,-1976.5,-1976.5],\"text\":\"Result: Above (Average: 10.9, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-1994.5,-1993.5,-1993.5,-1994.5,-1994.5],\"text\":\"Result: Above (Average: 11, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5],\"y\":[-1985.5,-1984.5,-1984.5,-1985.5,-1985.5,null,-1998.5,-1997.5,-1997.5,-1998.5,-1998.5],\"text\":\"Result: Above (Average: 11.2, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-1978.5,-1977.5,-1977.5,-1978.5,-1978.5],\"text\":\"Result: Above (Average: 11.3, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-1975.5,-1974.5,-1974.5,-1975.5,-1975.5],\"text\":\"Result: Above (Average: 11.4, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5],\"y\":[-1977.5,-1976.5,-1976.5,-1977.5,-1977.5,null,-2011.5,-2010.5,-2010.5,-2011.5,-2011.5],\"text\":\"Result: Above (Average: 11.4, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-1995.5,-1994.5,-1994.5,-1995.5,-1995.5],\"text\":\"Result: Above (Average: 11.5, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-2003.5,-2002.5,-2002.5,-2003.5,-2003.5],\"text\":\"Result: Above (Average: 11.7, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-2004.5,-2003.5,-2003.5,-2004.5,-2004.5],\"text\":\"Result: Above (Average: 11.8, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-1981.5,-1980.5,-1980.5,-1981.5,-1981.5],\"text\":\"Result: Above (Average: 12, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-2009.5,-2008.5,-2008.5,-2009.5,-2009.5],\"text\":\"Result: Above (Average: 12.1, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-1998.5,-1997.5,-1997.5,-1998.5,-1998.5],\"text\":\"Result: Above (Average: 12.2, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-1985.5,-1984.5,-1984.5,-1985.5,-1985.5],\"text\":\"Result: Above (Average: 13, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-1982.5,-1981.5,-1981.5,-1982.5,-1982.5],\"text\":\"Result: Above (Average: 13, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-1977.5,-1976.5,-1976.5,-1977.5,-1977.5],\"text\":\"Result: Above (Average: 13.1, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-1975.5,-1974.5,-1974.5,-1975.5,-1975.5],\"text\":\"Result: Above (Average: 13.2, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-1981.5,-1980.5,-1980.5,-1981.5,-1981.5],\"text\":\"Result: Above (Average: 13.6, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-1980.5,-1979.5,-1979.5,-1980.5,-1980.5],\"text\":\"Result: Above (Average: 13.9, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-1980.5,-1979.5,-1979.5,-1980.5,-1980.5],\"text\":\"Result: Above (Average: 14.7, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-1986.5,-1985.5,-1985.5,-1986.5,-1986.5],\"text\":\"Result: Above (Average: 16.8, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-1983.5,-1982.5,-1982.5,-1983.5,-1983.5],\"text\":\"Result: Above (Average: 17.5, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-1979.5,-1978.5,-1978.5,-1979.5,-1979.5],\"text\":\"Result: Above (Average: 17.7, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5],\"y\":[-1979.5,-1978.5,-1978.5,-1979.5,-1979.5],\"text\":\"Result: Above (Average: 18, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5],\"y\":[-1994.5,-1993.5,-1993.5,-1994.5,-1994.5,null,-1995.5,-1994.5,-1994.5,-1995.5,-1995.5],\"text\":\"Result: Above (Average: 18.7, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-1982.5,-1981.5,-1981.5,-1982.5,-1982.5],\"text\":\"Result: Above (Average: 18.8, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-1985.5,-1984.5,-1984.5,-1985.5,-1985.5],\"text\":\"Result: Above (Average: 19.3, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-1983.5,-1982.5,-1982.5,-1983.5,-1983.5],\"text\":\"Result: Above (Average: 19.3, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-1998.5,-1997.5,-1997.5,-1998.5,-1998.5],\"text\":\"Result: Above (Average: 20.7, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-1978.5,-1977.5,-1977.5,-1978.5,-1978.5],\"text\":\"Result: Above (Average: 22, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-1980.5,-1979.5,-1979.5,-1980.5,-1980.5],\"text\":\"Result: Above (Average: 22.6, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-1983.5,-1982.5,-1982.5,-1983.5,-1983.5],\"text\":\"Result: Above (Average: 25.9, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-1975.5,-1974.5,-1974.5,-1975.5,-1975.5],\"text\":\"Result: Above (Average: 27.9, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-1976.5,-1975.5,-1975.5,-1976.5,-1976.5],\"text\":\"Result: Above (Average: 29.5, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-1979.5,-1978.5,-1978.5,-1979.5,-1979.5],\"text\":\"Result: Above (Average: 29.7, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-1981.5,-1980.5,-1980.5,-1981.5,-1981.5],\"text\":\"Result: Above (Average: 31.1, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-1977.5,-1976.5,-1976.5,-1977.5,-1977.5],\"text\":\"Result: Above (Average: 32.5, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1.5,1.5,2.5,2.5,1.5],\"y\":[-1982.5,-1981.5,-1981.5,-1982.5,-1982.5],\"text\":\"Result: Above (Average: 36.1, Threshold: 15)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5],\"y\":[-1977.5,-1976.5,-1976.5,-1977.5,-1977.5],\"text\":\"Result: Above (Average: 5.3, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5],\"y\":[-1994.5,-1993.5,-1993.5,-1994.5,-1994.5],\"text\":\"Result: Above (Average: 5.5, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5],\"y\":[-1998.5,-1997.5,-1997.5,-1998.5,-1998.5],\"text\":\"Result: Above (Average: 5.9, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5,null,3.5,3.5,4.5,4.5,3.5],\"y\":[-1980.5,-1979.5,-1979.5,-1980.5,-1980.5,null,-1982.5,-1981.5,-1981.5,-1982.5,-1982.5],\"text\":\"Result: Above (Average: 6.1, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5,null,3.5,3.5,4.5,4.5,3.5],\"y\":[-1981.5,-1980.5,-1980.5,-1981.5,-1981.5,null,-2005.5,-2004.5,-2004.5,-2005.5,-2005.5],\"text\":\"Result: Above (Average: 6.2, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[3.5,3.5,4.5,4.5,3.5,null,3.5,3.5,4.5,4.5,3.5],\"y\":[-1979.5,-1978.5,-1978.5,-1979.5,-1979.5,null,-1983.5,-1982.5,-1982.5,-1983.5,-1983.5],\"text\":\"Result: Above (Average: 7.3, Threshold: 5.1)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-1987.5,-1986.5,-1986.5,-1987.5,-1987.5],\"text\":\"Result: Above (Average: 8.6, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2.5,2.5,3.5,3.5,2.5],\"y\":[-1984.5,-1983.5,-1983.5,-1984.5,-1984.5],\"text\":\"Result: Above (Average: 8.8, Threshold: 8.5)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5],\"y\":[-1987.5,-1986.5,-1986.5,-1987.5,-1987.5,null,-1989.5,-1988.5,-1988.5,-1989.5,-1989.5,null,-1990.5,-1989.5,-1989.5,-1990.5,-1990.5],\"text\":\"Result: Above (Average: 9.3, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5],\"y\":[-1994.5,-1993.5,-1993.5,-1994.5,-1994.5,null,-2021.5,-2020.5,-2020.5,-2021.5,-2021.5],\"text\":\"Result: Above (Average: 9.4, Threshold: 9.3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5],\"y\":[-1978.5,-1977.5,-1977.5,-1978.5,-1978.5,null,-2017.5,-2016.5,-2016.5,-2017.5,-2017.5,null,-2020.5,-2019.5,-2019.5,-2020.5,-2020.5],\"text\":\"Result: Above (Average: 9.5, Threshold: 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approximated five year monthly averages parameter outtxt1 optional text NMC action 1, added outcome column outtxt2 optional text NMC action 2, added outcome column outtxt3 optional text NMC action 3, added outcome column outtxt45 optional text NMC actions 4 5, added outcome column txtsz numeric indicating font size width optional numeric value indicating width inches","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_ratab.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Create a bay segment assessment table for the 2022-2026 reasonable assurance period — show_ratab","text":"flextable object showing reasonable assurance compliance bay segment selected year within five-year period.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_ratab.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Create a bay segment assessment table for the 2022-2026 reasonable assurance period — show_ratab","text":"Choosing bay_segment = 'RALTB' work epcdata additional data needed use option.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_ratab.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Create a bay segment assessment table for the 2022-2026 reasonable assurance period — show_ratab","text":"Bay Segment Reasonable Assurance Assessment Steps DATA USED ASSESS ANNUAL REASONABLE ASSURANCE OUTCOME Year 1 (2022) Year 2 (2023) Year 3 (2024) Year 4 (2025) Year 5 (2026) NMC Action 1: Determine observed chlorophyll-exceeds FDEP threshold 9.3 ug/L (7.1) (6.2) years threshold far, necessary NMC Actions 2-5 NMC Action 2: Determine observed chlorophyll-exceedences occurred 2 consecutive years years met threshold, necessary NMC Actions 3-5 NMC Action 3: Determine observed hydrologically-normalized total load exceeds federally-recognized TMDL 486 tons/year N/N/ necessary due observed water quality seagrass 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1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-52d09174{width:0.6in;background-color:rgba(173, 216, 230, 1.00);vertical-align: middle;border-bottom: 1pt solid rgba(102, 102, 102, 1.00);border-top: 1pt solid rgba(102, 102, 102, 1.00);border-left: 1pt solid rgba(102, 102, 102, 1.00);border-right: 1pt solid rgba(102, 102, 102, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}Bay Segment Reasonable Assurance Assessment StepsDATA USED TO ASSESS ANNUAL REASONABLE ASSURANCEOUTCOMEYear 1 (2022)Year 2 (2023)Year 3 (2024)Year 4 (2025)Year 5 (2026)NMC Action 1: Determine if observed chlorophyll-a exceeds FDEP threshold of 9.3 ug/LNo (7.1)No (6.2)All years below threshold so far, not necessary for NMC Actions 2-5NMC Action 2: Determine if any observed chlorophyll-a exceedences occurred for 2 consecutive yearsNoNoAll years met threshold, not necessary for NMC Actions 3-5NMC Action 3: Determine if observed hydrologically-normalized total load exceeds federally-recognized TMDL of 486 tons/yearN/AN/ANot necessary due to observed water quality and seagrass conditions in the bay segmentNMC Actions 4-5: Determine if any entity/source/facility specific exceedences of 5-yr average allocation occurred during implementation periodNot necessary when chlorophyll-a threshold met"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_reactable.html","id":null,"dir":"Reference","previous_headings":"","what":"Create reactable table from matrix data — show_reactable","title":"Create reactable table from matrix data — show_reactable","text":"Create reactable table matrix data","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_reactable.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Create reactable table from matrix data — show_reactable","text":"","code":"show_reactable(totab, colfun, nrows = 10, txtsz = 3)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_reactable.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Create reactable table from matrix data — show_reactable","text":"totab data frame wide format summarized results colfun Function specifying colors treated cell background nrows numeric specifying number rows table txtsz numeric indicating text size cells, use txtsz = NULL suppress","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_reactable.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Create reactable table from matrix data — show_reactable","text":"reactable table","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_reactable.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Create reactable table from matrix data — show_reactable","text":"function used internally within show_matrix show_wqmatrix","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_reactable.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Create reactable table from matrix data — show_reactable","text":"","code":"data(targets) data(epcdata) library(tidyr) library(dplyr) #> #> Attaching package: ‘dplyr’ #> The following objects are masked from ‘package:stats’: #> #> filter, lag #> The following objects are masked from ‘package:base’: #> #> intersect, setdiff, setequal, union # data totab <- anlz_avedat(epcdata) %>% .$ann %>% filter(var %in% 'mean_chla') %>% left_join(targets, by = 'bay_segment') %>% select(bay_segment, yr, val, chla_thresh) %>% mutate( bay_segment = factor(bay_segment, levels = c('OTB', 'HB', 'MTB', 'LTB')), outcome = case_when( val < chla_thresh ~ 'green', val >= chla_thresh ~ 'red' ) ) %>% select(bay_segment, yr, outcome) %>% spread(bay_segment, outcome) # color function colfun <- function(x){ out <- case_when( x == 'red' ~ '#FF3333', x == 'green' ~ '#33FF3B' ) return(out) } show_reactable(totab, colfun) {\"x\":{\"tag\":{\"name\":\"Reactable\",\"attribs\":{\"data\":{\"yr\":[1974,1975,1976,1977,1978,1979,1980,1981,1982,1983,1984,1985,1986,1987,1988,1989,1990,1991,1992,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013,2014,2015,2016,2017,2018,2019,2020,2021,2022,2023],\"OTB\":[\"red\",\"red\",\"red\",\"red\",\"red\",\"red\",\"red\",\"red\",\"red\",\"red\",\"green\",\"red\",\"red\",\"red\",\"green\",\"red\",\"red\",\"green\",\"green\",\"green\",\"red\",\"red\",\"green\",\"green\",\"red\",\"green\",\"green\",\"green\",\"green\",\"red\",\"red\",\"green\",\"green\",\"green\",\"green\",\"red\",\"green\",\"red\",\"green\",\"green\",\"green\",\"red\",\"green\",\"red\",\"green\",\"red\",\"red\",\"red\",\"green\",\"green\"],\"HB\":[\"red\",\"red\",\"red\",\"red\",\"red\",\"red\",\"red\",\"red\",\"red\",\"red\",\"green\",\"red\",\"red\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"red\",\"red\",\"green\",\"green\",\"red\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\"],\"MTB\":[\"red\",\"red\",\"red\",\"red\",\"red\",\"red\",\"red\",\"red\",\"red\",\"red\",\"red\",\"red\",\"green\",\"red\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"red\",\"red\",\"green\",\"green\",\"red\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\"],\"LTB\":[\"green\",\"green\",\"green\",\"red\",\"green\",\"red\",\"red\",\"red\",\"red\",\"red\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"red\",\"green\",\"green\",\"green\",\"red\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"red\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\",\"green\"]},\"columns\":[{\"id\":\"yr\",\"name\":\"Year\",\"type\":\"numeric\",\"style\":{\"fontSize\":\"16px\"}},{\"id\":\"OTB\",\"name\":\"OTB\",\"type\":\"character\",\"style\":[{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#33FF3B\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"background\":\"#FF3333\",\"fontSize\":\"15.99px\"},{\"backgrou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a barplot of seagrass coverage over time in Tampa Bay — show_seagrasscoverage","title":"Create a barplot of seagrass coverage over time in Tampa Bay — show_seagrasscoverage","text":"Create barplot seagrass coverage time Tampa Bay","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_seagrasscoverage.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Create a barplot of seagrass coverage over time in Tampa Bay — show_seagrasscoverage","text":"","code":"show_seagrasscoverage( seagrass, maxyr = 2022, family = NA, lastlab = \"acres\", axsbrk = c(0.08, 0.1) )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_seagrasscoverage.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Create a barplot of seagrass coverage over time in Tampa Bay — show_seagrasscoverage","text":"seagrass input data.frame included package seagrass maxyr numeric maximum year plot family optional chr string indicating font family text labels lastlab chr string text append label last bar barplot axsbrk numeric vector length two indicating x-axis break occurs","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_seagrasscoverage.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Create a barplot of seagrass coverage over time in Tampa Bay — show_seagrasscoverage","text":"grid object showing acres total seagrass coverage Tampa Bay time.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_seagrasscoverage.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Create a barplot of seagrass coverage over time in Tampa Bay — show_seagrasscoverage","text":"function creates flagship seagrass coverage graphic report coverage changes time. data pre-processed included package seagrass dataset. Original data Southwest Florida Water Management District available online https://data-swfwmd.opendata.arcgis.com/. function data used create plot distinct used transect monitoring program.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_seagrasscoverage.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Create a barplot of seagrass coverage over time in Tampa Bay — show_seagrasscoverage","text":"","code":"show_seagrasscoverage(seagrass)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentalratio.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot metal concentrations against aluminum — show_sedimentalratio","title":"Plot metal concentrations against aluminum — show_sedimentalratio","text":"Plot metal concentrations aluminum","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentalratio.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot metal concentrations against aluminum — show_sedimentalratio","text":"","code":"show_sedimentalratio( sedimentdata, param, yrrng = c(1993, 2022), bay_segment = c(\"HB\", \"OTB\", \"MTB\", \"LTB\", \"TCB\", \"MR\", \"BCB\"), funding_proj = \"TBEP\", lnsz = 1, base_size = 12, plotly = FALSE, family = NA, width = NULL, height = NULL )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentalratio.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot metal concentrations against aluminum — show_sedimentalratio","text":"sedimentdata input sediment data.frame returned read_importsediment param chr string parameter plot, must metal yrrng numeric vector indicating min, max years include, use single year one year data bay_segment chr string bay segment, one many \"HB\", \"OTB\", \"MTB\", \"LTB\", \"TCB\", \"MR\", \"BCB\" funding_proj chr string funding project, one many \"TBEP\" (default), \"TBEP-Special\", \"Apollo Beach\", \"Janicki Contract\", \"Rivers\", \"Tidal Streams\" lnsz numeric line size base_size numeric indicating text scaling size plot plotly logical matrix created using plotly family optional chr string indicating font family text labels width numeric width plot pixels, applies plotly = TRUE height numeric height plot pixels, applies plotly = TRUE","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentalratio.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot metal concentrations against aluminum — show_sedimentalratio","text":"ggplot object plotly object plotly = TRUE showing ratio selected parameter plotted aluminum concentrations collected site. Black lines show linear fit log-log model 95","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentalratio.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Plot metal concentrations against aluminum — show_sedimentalratio","text":"plot shows selected contaminant concentration relative aluminum, latter present common metal Earth's crust. elevated ratio metal parameter relative aluminum suggests higher background concentrations. Lines Threshold Effect Level (TEL) Potential Effect Level (PEL) shown parameter, available.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentalratio.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Plot metal concentrations against aluminum — show_sedimentalratio","text":"Schropp, S. J., Graham Lewis, F., Windom, H. L., Ryan, J. D., Calder, F. D., & Burney, L. C. 1990. Interpretation metal concentrations estuarine sediments Florida using aluminum reference element. Estuaries. 13:227-235.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentalratio.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot metal concentrations against aluminum — show_sedimentalratio","text":"","code":"show_sedimentalratio(sedimentdata, param = 'Arsenic') #> Warning: log-10 transformation introduced infinite values. #> Warning: log-10 transformation introduced infinite values."},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentave.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot sediment concentration averages by bay segment — show_sedimentave","title":"Plot sediment concentration averages by bay segment — show_sedimentave","text":"Plot sediment concentration averages bay segment","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentave.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot sediment concentration averages by bay segment — show_sedimentave","text":"","code":"show_sedimentave( sedimentdata, param, yrrng = c(1993, 2022), bay_segment = c(\"HB\", \"OTB\", \"MTB\", \"LTB\", \"TCB\", \"MR\", \"BCB\"), funding_proj = \"TBEP\", lnsz = 1, base_size = 12, plotly = FALSE, family = NA, width = NULL, height = NULL )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentave.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot sediment concentration averages by bay segment — show_sedimentave","text":"sedimentdata input sediment data.frame returned read_importsediment param chr string parameter plot yrrng numeric vector indicating min, max years include, use single year one year data bay_segment chr string bay segment, one many \"HB\", \"OTB\", \"MTB\", \"LTB\", \"TCB\", \"MR\", \"BCB\" funding_proj chr string funding project, one many \"TBEP\" (default), \"TBEP-Special\", \"Apollo Beach\", \"Janicki Contract\", \"Rivers\", \"Tidal Streams\" lnsz numeric line size base_size numeric indicating text scaling size plot plotly logical matrix created using plotly family optional chr string indicating font family text labels width numeric width plot pixels, applies plotly = TRUE height numeric height plot pixels, applies plotly = TRUE","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentave.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot sediment concentration averages by bay segment — show_sedimentave","text":"ggplot object plotly object plotly = TRUE showing sediment averages 95","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentave.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Plot sediment concentration averages by bay segment — show_sedimentave","text":"Lines Threshold Effect Level (TEL) Potential Effect Level (PEL) shown parameter, available. Confidence intervals may shown segments insufficient data.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentave.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot sediment concentration averages by bay segment — show_sedimentave","text":"","code":"show_sedimentave(sedimentdata, param = 'Arsenic')"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentmap.html","id":null,"dir":"Reference","previous_headings":"","what":"Make a map for sediment contaminants at stations in Tampa Bay — show_sedimentmap","title":"Make a map for sediment contaminants at stations in Tampa Bay — show_sedimentmap","text":"Make map sediment contaminants stations Tampa Bay","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentmap.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Make a map for sediment contaminants at stations in Tampa Bay — show_sedimentmap","text":"","code":"show_sedimentmap( sedimentdata, param, yrrng = c(1993, 2022), funding_proj = \"TBEP\", weight = 1.5 )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentmap.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Make a map for sediment contaminants at stations in Tampa Bay — show_sedimentmap","text":"sedimentdata input sediment data.frame returned read_importsediment param chr string parameter plot yrrng numeric vector indicating min, max years include, use single year one year data funding_proj chr string funding project, one many \"TBEP\" (default), \"TBEP-Special\", \"Apollo Beach\", \"Janicki Contract\", \"Rivers\", \"Tidal Streams\" weight numeric outline width station points map","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentmap.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Make a map for sediment contaminants at stations in Tampa Bay — show_sedimentmap","text":"leaflet object","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentmap.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Make a map for sediment contaminants at stations in Tampa Bay — show_sedimentmap","text":"map shows sediment contaminant concentrations selected parameter relative Threshold Effects Levels (TEL) Potential Effects Levels (PEL), available. Green points show concentrations TEL, yellow points show concentrations TEL PEL, red points show concentrations PEL. applicable TEL PEL values parameter indicated legend. TEL PEL thresholds available, map sediment concentrations shown warning returned console.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentmap.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Make a map for sediment contaminants at stations in Tampa Bay — show_sedimentmap","text":"","code":"show_sedimentmap(sedimentdata, param = 'Arsenic') 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mg/kg\",\"StationNumber: 93LTB39, Year: 1993, Value: 0.1 mg/kg\",\"StationNumber: 93LTB40, Year: 1993, Value: 10.3 mg/kg\",\"StationNumber: 93MTB41, Year: 1993, Value: 1.1 mg/kg\",\"StationNumber: 93MTB42, Year: 1993, Value: 1.4 mg/kg\",\"StationNumber: 93MTB43, Year: 1993, Value: 2.2 mg/kg\",\"StationNumber: 93MTB44, Year: 1993, Value: 0.2 mg/kg\",\"StationNumber: 93MTB45, Year: 1993, Value: 1 mg/kg\",\"StationNumber: 93MTB47, Year: 1993, Value: 0.8 mg/kg\",\"StationNumber: 93MTB48, Year: 1993, Value: 1.2 mg/kg\",\"StationNumber: 93MTB49, Year: 1993, Value: 0.1 mg/kg\",\"StationNumber: 93MTB50, Year: 1993, Value: 0.4 mg/kg\",\"StationNumber: 93MTB51, Year: 1993, Value: 0.2 mg/kg\",\"StationNumber: 93MTB52, Year: 1993, Value: 0.01 mg/kg\",\"StationNumber: 93MTB53, Year: 1993, Value: 0.2 mg/kg\",\"StationNumber: 93MTB54, Year: 1993, Value: 0.8 mg/kg\",\"StationNumber: 93MTB55, Year: 1993, Value: 5.4 mg/kg\",\"StationNumber: 93MTB56, Year: 1993, Value: 1.1 mg/kg\",\"StationNumber: 93MTB57, Year: 1993, Value: 1.4 mg/kg\",\"StationNumber: 93MTB58, Year: 1993, Value: 0.01 mg/kg\",\"StationNumber: 93MTB59, Year: 1993, Value: 1.7 mg/kg\",\"StationNumber: 93MTB60, Year: 1993, Value: 2.4 mg/kg\",\"StationNumber: 93MTB61, Year: 1993, Value: 3.6 mg/kg\",\"StationNumber: 93OTB63, Year: 1993, Value: 5.5 mg/kg\",\"StationNumber: 93OTB64, Year: 1993, Value: 0.1 mg/kg\",\"StationNumber: 93OTB65, Year: 1993, Value: 1 mg/kg\",\"StationNumber: 93OTB66, Year: 1993, Value: 0.9 mg/kg\",\"StationNumber: 93OTB67, Year: 1993, Value: 0.9 mg/kg\",\"StationNumber: 93OTB68, Year: 1993, Value: 1.1 mg/kg\",\"StationNumber: 93OTB69, Year: 1993, Value: 1 mg/kg\",\"StationNumber: 93OTB70, Year: 1993, Value: 1.2 mg/kg\",\"StationNumber: 93OTB71, Year: 1993, Value: 1.1 mg/kg\",\"StationNumber: 93OTB72, Year: 1993, Value: 1.3 mg/kg\",\"StationNumber: 93OTB73, Year: 1993, Value: 0.7 mg/kg\",\"StationNumber: 93OTB76, Year: 1993, Value: 1.8 mg/kg\",\"StationNumber: 93OTB77, Year: 1993, Value: 0.3 mg/kg\",\"StationNumber: 93OTB78, Year: 1993, Value: 0.01 mg/kg\",\"StationNumber: 93OTB79, Year: 1993, Value: 3.7 mg/kg\",\"StationNumber: 93OTB80, Year: 1993, Value: 1.1 mg/kg\",\"StationNumber: 93OTB83, Year: 1993, Value: 0.6 mg/kg\",\"StationNumber: 94HB03, Year: 1994, Value: 11.53 mg/kg\",\"StationNumber: 94HB04, Year: 1994, Value: 8.831 mg/kg\",\"StationNumber: 94HB05, Year: 1994, Value: 0.01 mg/kg\",\"StationNumber: 94HB06, Year: 1994, Value: 0.469 mg/kg\",\"StationNumber: 94HB07, Year: 1994, Value: 18.34 mg/kg\",\"StationNumber: 94HB08, Year: 1994, Value: 6.249 mg/kg\",\"StationNumber: 94HB09, Year: 1994, Value: 3.867 mg/kg\",\"StationNumber: 94HB10, Year: 1994, Value: 0.01 mg/kg\",\"StationNumber: 94HB12, Year: 1994, Value: 2.244 mg/kg\",\"StationNumber: 94HB13, Year: 1994, Value: 0.523 mg/kg\",\"StationNumber: 94HB14, Year: 1994, Value: 1.158 mg/kg\",\"StationNumber: 94HB15, Year: 1994, Value: 1.3 mg/kg\",\"StationNumber: 94HB16, Year: 1994, Value: 0.01 mg/kg\",\"StationNumber: 94HB18, Year: 1994, Value: 0.785 mg/kg\",\"StationNumber: 94HB19, Year: 1994, Value: 2.992 mg/kg\",\"StationNumber: 94HB20, Year: 1994, Value: 6.697 mg/kg\",\"StationNumber: 94HB21, Year: 1994, Value: 4.794 mg/kg\",\"StationNumber: 94HB22, Year: 1994, Value: 0.559 mg/kg\",\"StationNumber: 94HB23, Year: 1994, Value: 5.137 mg/kg\",\"StationNumber: 94LTB24, Year: 1994, Value: 2.557 mg/kg\",\"StationNumber: 94LTB25, Year: 1994, Value: 10.23 mg/kg\",\"StationNumber: 94LTB26, Year: 1994, Value: 0.982 mg/kg\",\"StationNumber: 94LTB27, Year: 1994, Value: 2.211 mg/kg\",\"StationNumber: 94LTB28, Year: 1994, Value: 3.464 mg/kg\",\"StationNumber: 94LTB29, Year: 1994, Value: 2.906 mg/kg\",\"StationNumber: 94LTB30, Year: 1994, Value: 3.515 mg/kg\",\"StationNumber: 94LTB31, Year: 1994, Value: 1.09 mg/kg\",\"StationNumber: 94LTB32, Year: 1994, Value: 0.538 mg/kg\",\"StationNumber: 94LTB33, Year: 1994, Value: 4.454 mg/kg\",\"StationNumber: 94LTB34, Year: 1994, Value: 1.975 mg/kg\",\"StationNumber: 94LTB35, Year: 1994, Value: 0.164 mg/kg\",\"StationNumber: 94LTB36, Year: 1994, Value: 4.695 mg/kg\",\"StationNumber: 94LTB37, Year: 1994, Value: 5.033 mg/kg\",\"StationNumber: 94LTB38, Year: 1994, Value: 2.197 mg/kg\",\"StationNumber: 94LTB39, Year: 1994, Value: 12.93 mg/kg\",\"StationNumber: 94LTB40, Year: 1994, Value: 8.954 mg/kg\",\"StationNumber: 94MR23, Year: 1994, Value: 0 mg/kg\",\"StationNumber: 94MR24, Year: 1994, Value: 0 mg/kg\",\"StationNumber: 94MR26, Year: 1994, Value: 0 mg/kg\",\"StationNumber: 94MR27, Year: 1994, Value: 0 mg/kg\",\"StationNumber: 94MR28, Year: 1994, Value: 0 mg/kg\",\"StationNumber: 94MR29, Year: 1994, Value: 0 mg/kg\",\"StationNumber: 94MR31, Year: 1994, Value: 0 mg/kg\",\"StationNumber: 94MR32, Year: 1994, Value: 0 mg/kg\",\"StationNumber: 94MR34, Year: 1994, Value: 0 mg/kg\",\"StationNumber: 94MR43, Year: 1994, Value: 0 mg/kg\",\"StationNumber: 94MTB41, Year: 1994, Value: 0.465 mg/kg\",\"StationNumber: 94MTB42, Year: 1994, Value: 0.074 mg/kg\",\"StationNumber: 94MTB43, Year: 1994, Value: 6.242 mg/kg\",\"StationNumber: 94MTB44, Year: 1994, Value: 3.975 mg/kg\",\"StationNumber: 94MTB45, Year: 1994, Value: 0.417 mg/kg\",\"StationNumber: 94MTB47, Year: 1994, Value: 6.591 mg/kg\",\"StationNumber: 94MTB48, Year: 1994, Value: 0.209 mg/kg\",\"StationNumber: 94MTB49, Year: 1994, Value: 9.619 mg/kg\",\"StationNumber: 94MTB50, Year: 1994, Value: 1.634 mg/kg\",\"StationNumber: 94MTB51, Year: 1994, Value: 1.203 mg/kg\",\"StationNumber: 94MTB52, Year: 1994, Value: 0.01 mg/kg\",\"StationNumber: 94MTB53, Year: 1994, Value: 0.173 mg/kg\",\"StationNumber: 94MTB54, Year: 1994, Value: 2.975 mg/kg\",\"StationNumber: 94MTB55, Year: 1994, Value: 0.01 mg/kg\",\"StationNumber: 94MTB56, Year: 1994, Value: 0.028 mg/kg\",\"StationNumber: 94MTB57, Year: 1994, Value: 0.01 mg/kg\",\"StationNumber: 94MTB58, Year: 1994, Value: 11.58 mg/kg\",\"StationNumber: 94MTB59, Year: 1994, Value: 1.603 mg/kg\",\"StationNumber: 94MTB60, Year: 1994, Value: 0.01 mg/kg\",\"StationNumber: 94MTB61, Year: 1994, Value: 2.096 mg/kg\",\"StationNumber: 94OTB63, Year: 1994, Value: 8.811 mg/kg\",\"StationNumber: 94OTB64, Year: 1994, Value: 0.01 mg/kg\",\"StationNumber: 94OTB65, Year: 1994, Value: 0.01 mg/kg\",\"StationNumber: 94OTB66, Year: 1994, Value: 0.01 mg/kg\",\"StationNumber: 94OTB67, Year: 1994, Value: 1.513 mg/kg\",\"StationNumber: 94OTB68, Year: 1994, Value: 0.01 mg/kg\",\"StationNumber: 94OTB69, Year: 1994, Value: 0.01 mg/kg\",\"StationNumber: 94OTB70, Year: 1994, Value: 0.01 mg/kg\",\"StationNumber: 94OTB71, Year: 1994, Value: 1.415 mg/kg\",\"StationNumber: 94OTB72, Year: 1994, Value: 0.159 mg/kg\",\"StationNumber: 94OTB73, Year: 1994, Value: 1.64 mg/kg\",\"StationNumber: 94OTB76, Year: 1994, Value: 0.683 mg/kg\",\"StationNumber: 94OTB77, Year: 1994, Value: 0.111 mg/kg\",\"StationNumber: 94OTB78, Year: 1994, Value: 4.152 mg/kg\",\"StationNumber: 94OTB79, Year: 1994, Value: 0.086 mg/kg\",\"StationNumber: 94OTB80, Year: 1994, Value: 0.01 mg/kg\",\"StationNumber: 94OTB83, Year: 1994, Value: 0.01 mg/kg\",\"StationNumber: 94TCB22, Year: 1994, Value: 0 mg/kg\",\"StationNumber: 94TCB37, Year: 1994, Value: 0 mg/kg\",\"StationNumber: 94TCB38, Year: 1994, Value: 0 mg/kg\",\"StationNumber: 94TCB39, Year: 1994, Value: 0 mg/kg\",\"StationNumber: 94TCB40, Year: 1994, Value: 0 mg/kg\",\"StationNumber: 94TCB41, Year: 1994, Value: 0 mg/kg\",\"StationNumber: 94TCB42, Year: 1994, Value: 0 mg/kg\",\"StationNumber: 95BCB01, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95BCB02, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95BCB03, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95BCB04, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95BCB05, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95BCB06, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95BCB07, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95BCB08, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95BCB09, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95BCB10, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95BCB11, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95BCB12, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95BCB13, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95BCB14, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95BCB15, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95BCB16, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95BCB17, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95BCB18, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95BCB19, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95BCB20, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95BCB21, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95HB14, Year: 1995, Value: 0.565 mg/kg\",\"StationNumber: 95HB16, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95HB17, Year: 1995, Value: 0.844 mg/kg\",\"StationNumber: 95HB18, Year: 1995, Value: 2.685 mg/kg\",\"StationNumber: 95HB19, Year: 1995, Value: 0.011 mg/kg\",\"StationNumber: 95HB22, Year: 1995, Value: 0.134 mg/kg\",\"StationNumber: 95HB23, Year: 1995, Value: 2.499 mg/kg\",\"StationNumber: 95HB24, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95HB25, Year: 1995, Value: 0.258 mg/kg\",\"StationNumber: 95HB26, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95HB27, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95HB28, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95HB29, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95HB37, Year: 1995, Value: 1.482 mg/kg\",\"StationNumber: 95HB38, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95HB40, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95HB41, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95HB42, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95HB43, Year: 1995, Value: 0.432 mg/kg\",\"StationNumber: 95HB44, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95HB45, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95HB46, Year: 1995, Value: 3.023 mg/kg\",\"StationNumber: 95HB48, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95HB49, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95HB51, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95HB52, Year: 1995, Value: 1.696 mg/kg\",\"StationNumber: 95HB54, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95HB55, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95HB56, Year: 1995, Value: 4.81 mg/kg\",\"StationNumber: 95LTB01, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95LTB02, Year: 1995, Value: 0.076 mg/kg\",\"StationNumber: 95LTB04, Year: 1995, Value: 1.513 mg/kg\",\"StationNumber: 95LTB05, Year: 1995, Value: 1.347 mg/kg\",\"StationNumber: 95LTB06, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95LTB07, Year: 1995, Value: 0.876 mg/kg\",\"StationNumber: 95LTB08, Year: 1995, Value: 2.389 mg/kg\",\"StationNumber: 95LTB09, Year: 1995, Value: 1.187 mg/kg\",\"StationNumber: 95LTB10, Year: 1995, Value: 1.839 mg/kg\",\"StationNumber: 95LTB11, Year: 1995, Value: 2.845 mg/kg\",\"StationNumber: 95LTB12, Year: 1995, Value: 0.953 mg/kg\",\"StationNumber: 95LTB13, Year: 1995, Value: 1.192 mg/kg\",\"StationNumber: 95LTB15, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95LTB17, Year: 1995, Value: 1.678 mg/kg\",\"StationNumber: 95LTB18, Year: 1995, Value: 1.29 mg/kg\",\"StationNumber: 95LTB19, Year: 1995, Value: 0.872 mg/kg\",\"StationNumber: 95LTB20, Year: 1995, Value: 0.139 mg/kg\",\"StationNumber: 95LTB21, Year: 1995, Value: 0.009 mg/kg\",\"StationNumber: 95LTB23, Year: 1995, Value: 1.475 mg/kg\",\"StationNumber: 95LTB25, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95LTB26, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95LTB29, Year: 1995, Value: 0.225 mg/kg\",\"StationNumber: 95MR23, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95MR24, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95MR25, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95MR26, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95MR27, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95MR28, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95MR29, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95MR31, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95MR32, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95MR34, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95MR43, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95MTB03, Year: 1995, Value: 0.098 mg/kg\",\"StationNumber: 95MTB04, Year: 1995, Value: 0.296 mg/kg\",\"StationNumber: 95MTB06, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95MTB07, Year: 1995, Value: 2.145 mg/kg\",\"StationNumber: 95MTB08, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95MTB10, Year: 1995, Value: 0.254 mg/kg\",\"StationNumber: 95MTB15, Year: 1995, Value: 0.107 mg/kg\",\"StationNumber: 95MTB16, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95MTB17, Year: 1995, Value: 9.688 mg/kg\",\"StationNumber: 95MTB18, Year: 1995, Value: 5.681 mg/kg\",\"StationNumber: 95MTB19, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95MTB21, Year: 1995, Value: 0.19 mg/kg\",\"StationNumber: 95MTB24, Year: 1995, Value: 0.144 mg/kg\",\"StationNumber: 95MTB25, Year: 1995, Value: 0.264 mg/kg\",\"StationNumber: 95MTB26, Year: 1995, Value: 0.067 mg/kg\",\"StationNumber: 95MTB29, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95MTB30, Year: 1995, Value: 0.738 mg/kg\",\"StationNumber: 95MTB31, Year: 1995, Value: 0.483 mg/kg\",\"StationNumber: 95MTB32, Year: 1995, Value: 0.445 mg/kg\",\"StationNumber: 95MTB34, Year: 1995, Value: 1.065 mg/kg\",\"StationNumber: 95MTB35, Year: 1995, Value: 0.129 mg/kg\",\"StationNumber: 95OTB02, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95OTB03, Year: 1995, Value: 0.259 mg/kg\",\"StationNumber: 95OTB05, Year: 1995, Value: 0.772 mg/kg\",\"StationNumber: 95OTB06, Year: 1995, Value: 0.84 mg/kg\",\"StationNumber: 95OTB07, Year: 1995, Value: 0.274 mg/kg\",\"StationNumber: 95OTB08, Year: 1995, Value: 0.087 mg/kg\",\"StationNumber: 95OTB11, Year: 1995, Value: 0.214 mg/kg\",\"StationNumber: 95OTB12, Year: 1995, Value: 0.344 mg/kg\",\"StationNumber: 95OTB13, Year: 1995, Value: 0.269 mg/kg\",\"StationNumber: 95OTB14, Year: 1995, Value: 0.451 mg/kg\",\"StationNumber: 95OTB15, Year: 1995, Value: 7.62 mg/kg\",\"StationNumber: 95OTB17, Year: 1995, Value: 0.59 mg/kg\",\"StationNumber: 95OTB18, Year: 1995, Value: 0.356 mg/kg\",\"StationNumber: 95OTB19, Year: 1995, Value: 3.07 mg/kg\",\"StationNumber: 95OTB20, Year: 1995, Value: 0.314 mg/kg\",\"StationNumber: 95OTB22, Year: 1995, Value: 0.522 mg/kg\",\"StationNumber: 95OTB23, Year: 1995, Value: 0.135 mg/kg\",\"StationNumber: 95OTB24, Year: 1995, Value: 0.476 mg/kg\",\"StationNumber: 95OTB25, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95OTB26, Year: 1995, Value: 0.226 mg/kg\",\"StationNumber: 95OTB27, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95OTB29, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95OTB30, Year: 1995, Value: 0.01 mg/kg\",\"StationNumber: 95TCB22, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95TCB37, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95TCB38, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95TCB39, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95TCB40, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95TCB41, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 95TCB42, Year: 1995, Value: 0 mg/kg\",\"StationNumber: 96BCB02, Year: 1996, Value: 1.681 mg/kg\",\"StationNumber: 96BCB04, Year: 1996, Value: 4.387 mg/kg\",\"StationNumber: 96BCB07, Year: 1996, Value: 1.51 mg/kg\",\"StationNumber: 96BCB08, Year: 1996, Value: 2.112 mg/kg\",\"StationNumber: 96BCB12, Year: 1996, Value: 1.308 mg/kg\",\"StationNumber: 96BCB13, Year: 1996, Value: 5.299 mg/kg\",\"StationNumber: 96BCB15, Year: 1996, Value: 3.323 mg/kg\",\"StationNumber: 96BCB19, Year: 1996, Value: 0.7 mg/kg\",\"StationNumber: 96BCB24, Year: 1996, Value: 0.754 mg/kg\",\"StationNumber: 96BCB26, Year: 1996, Value: 0.16 mg/kg\",\"StationNumber: 96BCB27, Year: 1996, Value: 0.783 mg/kg\",\"StationNumber: 96BCB30, Year: 1996, Value: 0.546 mg/kg\",\"StationNumber: 96BCB31, Year: 1996, Value: 0.256 mg/kg\",\"StationNumber: 96BCB34, Year: 1996, Value: 0.29 mg/kg\",\"StationNumber: 96BCB36, Year: 1996, Value: 0.591 mg/kg\",\"StationNumber: 96BCB39, Year: 1996, Value: 0.25 mg/kg\",\"StationNumber: 96BCB40, Year: 1996, Value: 1.148 mg/kg\",\"StationNumber: 96BCB41, Year: 1996, Value: 0.01 mg/kg\",\"StationNumber: 96BCB44, Year: 1996, Value: 0.98 mg/kg\",\"StationNumber: 96BCB46, Year: 1996, Value: 0.339 mg/kg\",\"StationNumber: 96BCB49, Year: 1996, Value: 0.01 mg/kg\",\"StationNumber: 96HB13, Year: 1996, Value: 2.778 mg/kg\",\"StationNumber: 96HB16, Year: 1996, Value: 0.534 mg/kg\",\"StationNumber: 96HB18, Year: 1996, Value: 1.303 mg/kg\",\"StationNumber: 96HB20, Year: 1996, Value: 4.202 mg/kg\",\"StationNumber: 96HB22, Year: 1996, Value: 3.994 mg/kg\",\"StationNumber: 96HB23, Year: 1996, Value: 2.264 mg/kg\",\"StationNumber: 96HB24, Year: 1996, Value: 0.182 mg/kg\",\"StationNumber: 96HB26, Year: 1996, Value: 0.077 mg/kg\",\"StationNumber: 96HB27, Year: 1996, Value: 2.885 mg/kg\",\"StationNumber: 96HB29, Year: 1996, Value: 1.112 mg/kg\",\"StationNumber: 96HB36, Year: 1996, Value: 1.771 mg/kg\",\"StationNumber: 96HB37, Year: 1996, Value: 1.839 mg/kg\",\"StationNumber: 96HB38, Year: 1996, Value: 2.504 mg/kg\",\"StationNumber: 96HB39, Year: 1996, Value: 1.465 mg/kg\",\"StationNumber: 96HB42, Year: 1996, Value: 2.318 mg/kg\",\"StationNumber: 96HB43, Year: 1996, Value: 2.562 mg/kg\",\"StationNumber: 96HB44, Year: 1996, Value: 1.521 mg/kg\",\"StationNumber: 96HB45, Year: 1996, Value: 0.167 mg/kg\",\"StationNumber: 96HB46, Year: 1996, Value: 7.157 mg/kg\",\"StationNumber: 96HB47, Year: 1996, Value: 0.464 mg/kg\",\"StationNumber: 96HB48, Year: 1996, Value: 4.527 mg/kg\",\"StationNumber: 96HB50, Year: 1996, Value: 0.914 mg/kg\",\"StationNumber: 96HB51, Year: 1996, Value: 0.333 mg/kg\",\"StationNumber: 96HB52, Year: 1996, Value: 0.158 mg/kg\",\"StationNumber: 96HB53, Year: 1996, Value: 0.597 mg/kg\",\"StationNumber: 96HB54, Year: 1996, Value: 0.378 mg/kg\",\"StationNumber: 96HB56, Year: 1996, Value: 5.858 mg/kg\",\"StationNumber: 96LTB01, Year: 1996, Value: 0.01 mg/kg\",\"StationNumber: 96LTB02, Year: 1996, Value: 1.027 mg/kg\",\"StationNumber: 96LTB03, Year: 1996, Value: 1.366 mg/kg\",\"StationNumber: 96LTB04, Year: 1996, Value: 2.045 mg/kg\",\"StationNumber: 96LTB05, Year: 1996, Value: 1.675 mg/kg\",\"StationNumber: 96LTB06, Year: 1996, Value: 0.221 mg/kg\",\"StationNumber: 96LTB07, Year: 1996, Value: 0.01 mg/kg\",\"StationNumber: 96LTB08, Year: 1996, Value: 0.48 mg/kg\",\"StationNumber: 96LTB09, Year: 1996, Value: 0.01 mg/kg\",\"StationNumber: 96LTB10, Year: 1996, Value: 11.04 mg/kg\",\"StationNumber: 96LTB11, Year: 1996, Value: 1.949 mg/kg\",\"StationNumber: 96LTB12, Year: 1996, Value: 0.571 mg/kg\",\"StationNumber: 96LTB13, Year: 1996, Value: 2.568 mg/kg\",\"StationNumber: 96LTB15, Year: 1996, Value: 0.01 mg/kg\",\"StationNumber: 96LTB17, Year: 1996, Value: 6.999 mg/kg\",\"StationNumber: 96LTB18, Year: 1996, Value: 2.186 mg/kg\",\"StationNumber: 96LTB19, Year: 1996, Value: 2.416 mg/kg\",\"StationNumber: 96LTB20, Year: 1996, Value: 0.01 mg/kg\",\"StationNumber: 96LTB21, Year: 1996, Value: 0.131 mg/kg\",\"StationNumber: 96LTB23, Year: 1996, Value: 2.988 mg/kg\",\"StationNumber: 96LTB24, Year: 1996, Value: 1.609 mg/kg\",\"StationNumber: 96LTB25, Year: 1996, Value: 0.876 mg/kg\",\"StationNumber: 96LTB26, Year: 1996, Value: 0.241 mg/kg\",\"StationNumber: 96LTB27, Year: 1996, Value: 2.428 mg/kg\",\"StationNumber: 96MR20, Year: 1996, Value: 0.485 mg/kg\",\"StationNumber: 96MR21, Year: 1996, Value: 0.319 mg/kg\",\"StationNumber: 96MR23, Year: 1996, Value: 0.042 mg/kg\",\"StationNumber: 96MR24, Year: 1996, Value: 0.449 mg/kg\",\"StationNumber: 96MR25, Year: 1996, Value: 0.192 mg/kg\",\"StationNumber: 96MR26, Year: 1996, Value: 0.486 mg/kg\",\"StationNumber: 96MR27, Year: 1996, Value: 0.302 mg/kg\",\"StationNumber: 96MR28, Year: 1996, Value: 0.01 mg/kg\",\"StationNumber: 96MR29, Year: 1996, Value: 0.596 mg/kg\",\"StationNumber: 96MR30, Year: 1996, Value: 0.01 mg/kg\",\"StationNumber: 96MR31, Year: 1996, Value: 0.01 mg/kg\",\"StationNumber: 96MR32, Year: 1996, Value: 0.716 mg/kg\",\"StationNumber: 96MR43, Year: 1996, Value: 0.01 mg/kg\",\"StationNumber: 96MTB04, Year: 1996, Value: 0.503 mg/kg\",\"StationNumber: 96MTB05, Year: 1996, Value: 0.329 mg/kg\",\"StationNumber: 96MTB07, Year: 1996, Value: 0.458 mg/kg\",\"StationNumber: 96MTB09, Year: 1996, Value: 2.141 mg/kg\",\"StationNumber: 96MTB10, Year: 1996, Value: 0.591 mg/kg\",\"StationNumber: 96MTB11, Year: 1996, Value: 1.049 mg/kg\",\"StationNumber: 96MTB12, Year: 1996, Value: 0.633 mg/kg\",\"StationNumber: 96MTB13, Year: 1996, Value: 0 mg/kg\",\"StationNumber: 96MTB14, Year: 1996, Value: 6.52 mg/kg\",\"StationNumber: 96MTB15, Year: 1996, Value: 0.01 mg/kg\",\"StationNumber: 96MTB16, Year: 1996, Value: 0.063 mg/kg\",\"StationNumber: 96MTB17, Year: 1996, Value: 1.839 mg/kg\",\"StationNumber: 96MTB18, Year: 1996, Value: 0.01 mg/kg\",\"StationNumber: 96MTB19, Year: 1996, Value: 0.119 mg/kg\",\"StationNumber: 96MTB20, Year: 1996, Value: 4.526 mg/kg\",\"StationNumber: 96MTB23, Year: 1996, Value: 0.01 mg/kg\",\"StationNumber: 96MTB24, Year: 1996, Value: 0.485 mg/kg\",\"StationNumber: 96MTB25, Year: 1996, Value: 0.756 mg/kg\",\"StationNumber: 96MTB26, Year: 1996, Value: 0.01 mg/kg\",\"StationNumber: 96MTB30, Year: 1996, Value: 0.024 mg/kg\",\"StationNumber: 96MTB31, Year: 1996, Value: 0.827 mg/kg\",\"StationNumber: 96MTB32, Year: 1996, Value: 5.666 mg/kg\",\"StationNumber: 96MTB34, Year: 1996, Value: 0.664 mg/kg\",\"StationNumber: 96MTB35, Year: 1996, Value: 0.206 mg/kg\",\"StationNumber: 96OTB07, Year: 1996, Value: 0.477 mg/kg\",\"StationNumber: 96OTB11, Year: 1996, Value: 0.239 mg/kg\",\"StationNumber: 96OTB12, Year: 1996, Value: 1.951 mg/kg\",\"StationNumber: 96OTB13, Year: 1996, Value: 0.721 mg/kg\",\"StationNumber: 96OTB14, Year: 1996, Value: 1.631 mg/kg\",\"StationNumber: 96OTB17, Year: 1996, Value: 1.716 mg/kg\",\"StationNumber: 96OTB18, Year: 1996, Value: 1.202 mg/kg\",\"StationNumber: 96OTB19, Year: 1996, Value: 1.134 mg/kg\",\"StationNumber: 96OTB20, Year: 1996, Value: 1.832 mg/kg\",\"StationNumber: 96OTB23, Year: 1996, Value: 0.698 mg/kg\",\"StationNumber: 96OTB24, Year: 1996, Value: 0.749 mg/kg\",\"StationNumber: 96OTB26, Year: 1996, Value: 0.526 mg/kg\",\"StationNumber: 96OTB27, Year: 1996, Value: 0.629 mg/kg\",\"StationNumber: 96OTB29, Year: 1996, Value: 0.574 mg/kg\",\"StationNumber: 96OTB30, Year: 1996, Value: 0.106 mg/kg\",\"StationNumber: 96TCB22, Year: 1996, Value: 3.557 mg/kg\",\"StationNumber: 96TCB36, Year: 1996, Value: 1.001 mg/kg\",\"StationNumber: 96TCB37, Year: 1996, Value: 5.738 mg/kg\",\"StationNumber: 96TCB38, Year: 1996, Value: 2.784 mg/kg\",\"StationNumber: 96TCB39, Year: 1996, Value: 1.919 mg/kg\",\"StationNumber: 96TCB40, Year: 1996, Value: 1.242 mg/kg\",\"StationNumber: 96TCB41, Year: 1996, Value: 1.244 mg/kg\",\"StationNumber: 96TCB42, Year: 1996, Value: 0.01 mg/kg\",\"StationNumber: 97BCB02, Year: 1997, Value: 0.9 mg/kg\",\"StationNumber: 97BCB08, Year: 1997, Value: 3.79 mg/kg\",\"StationNumber: 97BCB10, Year: 1997, Value: 1.504 mg/kg\",\"StationNumber: 97BCB13, Year: 1997, Value: 1.11 mg/kg\",\"StationNumber: 97BCB17, Year: 1997, Value: 3.833 mg/kg\",\"StationNumber: 97BCB18, Year: 1997, Value: 0.053 mg/kg\",\"StationNumber: 97BCB27, Year: 1997, Value: 7.606 mg/kg\",\"StationNumber: 97BCB30, Year: 1997, Value: 1.439 mg/kg\",\"StationNumber: 97BCB31, Year: 1997, Value: 0.01 mg/kg\",\"StationNumber: 97BCB36, Year: 1997, Value: 0.548 mg/kg\",\"StationNumber: 97BCB37, Year: 1997, Value: 0.041 mg/kg\",\"StationNumber: 97BCB40, Year: 1997, Value: 2.312 mg/kg\",\"StationNumber: 97BCB46, Year: 1997, Value: 1.153 mg/kg\",\"StationNumber: 97BCB50, Year: 1997, Value: 3.046 mg/kg\",\"StationNumber: 97BCB57-1, Year: 1997, Value: 4.964 mg/kg\",\"StationNumber: 97BCB58-1, Year: 1997, Value: 8.192 mg/kg\",\"StationNumber: 97BCB58-2, Year: 1997, Value: 1.739 mg/kg\",\"StationNumber: 97BCB59-1, Year: 1997, Value: 1.017 mg/kg\",\"StationNumber: 97BCB59-2, Year: 1997, Value: 1.042 mg/kg\",\"StationNumber: 97BCB60-2, Year: 1997, Value: 0.932 mg/kg\",\"StationNumber: 97BCB60-4, Year: 1997, Value: 1.016 mg/kg\",\"StationNumber: 97HB10, Year: 1997, Value: 2.262 mg/kg\",\"StationNumber: 97HB13, Year: 1997, Value: 3.367 mg/kg\",\"StationNumber: 97HB18, Year: 1997, Value: 0.393 mg/kg\",\"StationNumber: 97HB22, Year: 1997, Value: 1.588 mg/kg\",\"StationNumber: 97HB23, Year: 1997, Value: 0.17 mg/kg\",\"StationNumber: 97HB24, Year: 1997, Value: 0.01 mg/kg\",\"StationNumber: 97HB27, Year: 1997, Value: 0.01 mg/kg\",\"StationNumber: 97HB29, Year: 1997, Value: 1.632 mg/kg\",\"StationNumber: 97HB36, Year: 1997, Value: 0.01 mg/kg\",\"StationNumber: 97HB37, Year: 1997, Value: 1.131 mg/kg\",\"StationNumber: 97HB38, Year: 1997, Value: 0.753 mg/kg\",\"StationNumber: 97HB39, Year: 1997, Value: 1.737 mg/kg\",\"StationNumber: 97HB43, Year: 1997, Value: 0.107 mg/kg\",\"StationNumber: 97HB44, Year: 1997, Value: 0.576 mg/kg\",\"StationNumber: 97HB45, Year: 1997, Value: 0.888 mg/kg\",\"StationNumber: 97HB46, Year: 1997, Value: 0.424 mg/kg\",\"StationNumber: 97HB48, Year: 1997, Value: 0.494 mg/kg\",\"StationNumber: 97HB50, Year: 1997, Value: 2.002 mg/kg\",\"StationNumber: 97HB53, Year: 1997, Value: 0.349 mg/kg\",\"StationNumber: 97HB54, Year: 1997, Value: 0.918 mg/kg\",\"StationNumber: 97HB55, Year: 1997, Value: 0.597 mg/kg\",\"StationNumber: 97HB56, Year: 1997, Value: 0.564 mg/kg\",\"StationNumber: 97LTB01, Year: 1997, Value: 0.364 mg/kg\",\"StationNumber: 97LTB02, Year: 1997, Value: 0.667 mg/kg\",\"StationNumber: 97LTB03, Year: 1997, Value: 1.481 mg/kg\",\"StationNumber: 97LTB06, Year: 1997, Value: 1.145 mg/kg\",\"StationNumber: 97LTB07, Year: 1997, Value: 1.822 mg/kg\",\"StationNumber: 97LTB09, Year: 1997, Value: 5.154 mg/kg\",\"StationNumber: 97LTB10, Year: 1997, Value: 9.854 mg/kg\",\"StationNumber: 97LTB11, Year: 1997, Value: 10.221 mg/kg\",\"StationNumber: 97LTB12, Year: 1997, Value: 2.644 mg/kg\",\"StationNumber: 97LTB13, Year: 1997, Value: 1.991 mg/kg\",\"StationNumber: 97LTB15, Year: 1997, Value: 0.607 mg/kg\",\"StationNumber: 97LTB17, Year: 1997, Value: 3.416 mg/kg\",\"StationNumber: 97LTB18, Year: 1997, Value: 2.814 mg/kg\",\"StationNumber: 97LTB19, Year: 1997, Value: 2.16 mg/kg\",\"StationNumber: 97LTB20, Year: 1997, Value: 0.558 mg/kg\",\"StationNumber: 97LTB21, Year: 1997, Value: 1.584 mg/kg\",\"StationNumber: 97LTB23, Year: 1997, Value: 2.302 mg/kg\",\"StationNumber: 97LTB24, Year: 1997, Value: 0.57 mg/kg\",\"StationNumber: 97LTB25, Year: 1997, Value: 0.538 mg/kg\",\"StationNumber: 97LTB26, Year: 1997, Value: 0.1 mg/kg\",\"StationNumber: 97LTB28, Year: 1997, Value: 0.01 mg/kg\",\"StationNumber: 97MR09, Year: 1997, Value: 0.458 mg/kg\",\"StationNumber: 97MR10, Year: 1997, Value: 0.672 mg/kg\",\"StationNumber: 97MR11, Year: 1997, Value: 2.184 mg/kg\",\"StationNumber: 97MR12, Year: 1997, Value: 1.339 mg/kg\",\"StationNumber: 97MR13, Year: 1997, Value: 1.416 mg/kg\",\"StationNumber: 97MR14, Year: 1997, Value: 1.886 mg/kg\",\"StationNumber: 97MR15, Year: 1997, Value: 1.079 mg/kg\",\"StationNumber: 97MR16, Year: 1997, Value: 1.293 mg/kg\",\"StationNumber: 97MR17, Year: 1997, Value: 0.902 mg/kg\",\"StationNumber: 97MR18, Year: 1997, Value: 1.223 mg/kg\",\"StationNumber: 97MR19, Year: 1997, Value: 1.164 mg/kg\",\"StationNumber: 97MR20, Year: 1997, Value: 1.285 mg/kg\",\"StationNumber: 97MR21, Year: 1997, Value: 1.766 mg/kg\",\"StationNumber: 97MTB02, Year: 1997, Value: 0.086 mg/kg\",\"StationNumber: 97MTB03, Year: 1997, Value: 0.01 mg/kg\",\"StationNumber: 97MTB04, Year: 1997, Value: 0.531 mg/kg\",\"StationNumber: 97MTB05, Year: 1997, Value: 0.01 mg/kg\",\"StationNumber: 97MTB07, Year: 1997, Value: 1.425 mg/kg\",\"StationNumber: 97MTB09, Year: 1997, Value: 0.514 mg/kg\",\"StationNumber: 97MTB10, Year: 1997, Value: 1.592 mg/kg\",\"StationNumber: 97MTB12, Year: 1997, Value: 0.718 mg/kg\",\"StationNumber: 97MTB14, Year: 1997, Value: 1.277 mg/kg\",\"StationNumber: 97MTB15, Year: 1997, Value: 0.612 mg/kg\",\"StationNumber: 97MTB16, Year: 1997, Value: 1.06 mg/kg\",\"StationNumber: 97MTB17, Year: 1997, Value: 1.021 mg/kg\",\"StationNumber: 97MTB18, Year: 1997, Value: 0.336 mg/kg\",\"StationNumber: 97MTB19, Year: 1997, Value: 0.112 mg/kg\",\"StationNumber: 97MTB23, Year: 1997, Value: 0.992 mg/kg\",\"StationNumber: 97MTB24, Year: 1997, Value: 6.807 mg/kg\",\"StationNumber: 97MTB25, Year: 1997, Value: 1.392 mg/kg\",\"StationNumber: 97MTB26, Year: 1997, Value: 0.193 mg/kg\",\"StationNumber: 97MTB30, Year: 1997, Value: 0.442 mg/kg\",\"StationNumber: 97MTB31, Year: 1997, Value: 0.756 mg/kg\",\"StationNumber: 97MTB32, Year: 1997, Value: 8.261 mg/kg\",\"StationNumber: 97MTB35, Year: 1997, Value: 0.47 mg/kg\",\"StationNumber: 97OTB03, Year: 1997, Value: 3.828 mg/kg\",\"StationNumber: 97OTB06, Year: 1997, Value: 0.01 mg/kg\",\"StationNumber: 97OTB07, Year: 1997, Value: 0.01 mg/kg\",\"StationNumber: 97OTB11, Year: 1997, Value: 0.142 mg/kg\",\"StationNumber: 97OTB12, Year: 1997, Value: 0.01 mg/kg\",\"StationNumber: 97OTB13, Year: 1997, Value: 0.724 mg/kg\",\"StationNumber: 97OTB17, Year: 1997, Value: 0.01 mg/kg\",\"StationNumber: 97OTB18, Year: 1997, Value: 0.029 mg/kg\",\"StationNumber: 97OTB19, Year: 1997, Value: 0.012 mg/kg\",\"StationNumber: 97OTB20, Year: 1997, Value: 0.01 mg/kg\",\"StationNumber: 97OTB22, Year: 1997, Value: 0.13 mg/kg\",\"StationNumber: 97OTB23, Year: 1997, Value: 0.01 mg/kg\",\"StationNumber: 97OTB24, Year: 1997, Value: 0.01 mg/kg\",\"StationNumber: 97OTB26, Year: 1997, Value: 0.01 mg/kg\",\"StationNumber: 97OTB27, Year: 1997, Value: 0.01 mg/kg\",\"StationNumber: 97OTB29, Year: 1997, Value: 0.01 mg/kg\",\"StationNumber: 97TCB01, Year: 1997, Value: 2.943 mg/kg\",\"StationNumber: 97TCB02, Year: 1997, Value: 2.221 mg/kg\",\"StationNumber: 97TCB03, Year: 1997, Value: 4.341 mg/kg\",\"StationNumber: 97TCB04, Year: 1997, Value: 3.585 mg/kg\",\"StationNumber: 97TCB05, Year: 1997, Value: 2.998 mg/kg\",\"StationNumber: 97TCB06, Year: 1997, Value: 1.551 mg/kg\",\"StationNumber: 97TCB07, Year: 1997, Value: 3.303 mg/kg\",\"StationNumber: 97TCB08, Year: 1997, Value: 0.787 mg/kg\",\"StationNumber: 98BCB06, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98BCB09, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98BCB11, Year: 1998, Value: 0.445 mg/kg\",\"StationNumber: 98BCB12, Year: 1998, Value: 2.509 mg/kg\",\"StationNumber: 98BCB15, Year: 1998, Value: 0.358 mg/kg\",\"StationNumber: 98BCB17, Year: 1998, Value: 1.517 mg/kg\",\"StationNumber: 98BCB21, Year: 1998, Value: 0.54 mg/kg\",\"StationNumber: 98BCB27, Year: 1998, Value: 0.102 mg/kg\",\"StationNumber: 98BCB28, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98BCB32, Year: 1998, Value: 0.09 mg/kg\",\"StationNumber: 98BCB38, Year: 1998, Value: 0.595 mg/kg\",\"StationNumber: 98BCB40, Year: 1998, Value: 0.392 mg/kg\",\"StationNumber: 98BCB43, Year: 1998, Value: 0.065 mg/kg\",\"StationNumber: 98BCB46, Year: 1998, Value: 1.568 mg/kg\",\"StationNumber: 98BCB57/1, Year: 1998, Value: 4.454 mg/kg\",\"StationNumber: 98BCB58/1, Year: 1998, Value: 4.341 mg/kg\",\"StationNumber: 98BCB58/2, Year: 1998, Value: 3.761 mg/kg\",\"StationNumber: 98BCB59/1, Year: 1998, Value: 0.088 mg/kg\",\"StationNumber: 98BCB59/2, Year: 1998, Value: 1.103 mg/kg\",\"StationNumber: 98BCB60/2, Year: 1998, Value: 0.999 mg/kg\",\"StationNumber: 98BCB60/4, Year: 1998, Value: 1.03 mg/kg\",\"StationNumber: 98HB003, Year: 1998, Value: 0.036 mg/kg\",\"StationNumber: 98HB006, Year: 1998, Value: 3.089 mg/kg\",\"StationNumber: 98HB014, Year: 1998, Value: 2.09 mg/kg\",\"StationNumber: 98HB016, Year: 1998, Value: 1.995 mg/kg\",\"StationNumber: 98HB017, Year: 1998, Value: 0.072 mg/kg\",\"StationNumber: 98HB024, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98HB030, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98HB049, Year: 1998, Value: 2.146 mg/kg\",\"StationNumber: 98HB052, Year: 1998, Value: 0.64 mg/kg\",\"StationNumber: 98HB056, Year: 1998, Value: 1.656 mg/kg\",\"StationNumber: 98HB059, Year: 1998, Value: 0.534 mg/kg\",\"StationNumber: 98HB069, Year: 1998, Value: 0.785 mg/kg\",\"StationNumber: 98HB080, Year: 1998, Value: 3.475 mg/kg\",\"StationNumber: 98HB089, Year: 1998, Value: 0.435 mg/kg\",\"StationNumber: 98HB130, Year: 1998, Value: 0.358 mg/kg\",\"StationNumber: 98HB153, Year: 1998, Value: 0.777 mg/kg\",\"StationNumber: 98HB171, Year: 1998, Value: 0.842 mg/kg\",\"StationNumber: 98HB180, Year: 1998, Value: 1.348 mg/kg\",\"StationNumber: 98HB224, Year: 1998, Value: 1.942 mg/kg\",\"StationNumber: 98HB237, Year: 1998, Value: 0.471 mg/kg\",\"StationNumber: 98HB245, Year: 1998, Value: 0.642 mg/kg\",\"StationNumber: 98HB252, Year: 1998, Value: 1.898 mg/kg\",\"StationNumber: 98HB280, Year: 1998, Value: 0.134 mg/kg\",\"StationNumber: 98HB789, Year: 1998, Value: 2.42 mg/kg\",\"StationNumber: 98HBDIcanal, Year: 1998, Value: 0.931 mg/kg\",\"StationNumber: 98HBspark, Year: 1998, Value: 0.258 mg/kg\",\"StationNumber: 98LTB0014, Year: 1998, Value: 2.93 mg/kg\",\"StationNumber: 98LTB0025, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98LTB0049, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98LTB0095, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98LTB0123, Year: 1998, Value: 0.56 mg/kg\",\"StationNumber: 98LTB0144, Year: 1998, Value: 0.476 mg/kg\",\"StationNumber: 98LTB0151, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98LTB0168, Year: 1998, Value: 0.441 mg/kg\",\"StationNumber: 98LTB0183, Year: 1998, Value: 0.828 mg/kg\",\"StationNumber: 98LTB0223, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98LTB0244, Year: 1998, Value: 0.078 mg/kg\",\"StationNumber: 98LTB0273, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98LTB0307, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98LTB0364, Year: 1998, Value: 0.105 mg/kg\",\"StationNumber: 98LTB0393, Year: 1998, Value: 0.397 mg/kg\",\"StationNumber: 98LTB0762, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98LTB1057, Year: 1998, Value: 0.673 mg/kg\",\"StationNumber: 98MR09, Year: 1998, Value: 0.125 mg/kg\",\"StationNumber: 98MR10, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98MR11, Year: 1998, Value: 0.99 mg/kg\",\"StationNumber: 98MR12, Year: 1998, Value: 0.198 mg/kg\",\"StationNumber: 98MR13, Year: 1998, Value: 1.029 mg/kg\",\"StationNumber: 98MR14, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98MR15, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98MR16, Year: 1998, Value: 0.352 mg/kg\",\"StationNumber: 98MR17, Year: 1998, Value: 0.36 mg/kg\",\"StationNumber: 98MR18, Year: 1998, Value: 0.322 mg/kg\",\"StationNumber: 98MR19, Year: 1998, Value: 0.176 mg/kg\",\"StationNumber: 98MR20, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98MR21, Year: 1998, Value: 2.438 mg/kg\",\"StationNumber: 98MTB0032, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98MTB0035, Year: 1998, Value: 0.482 mg/kg\",\"StationNumber: 98MTB0052, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98MTB0067, Year: 1998, Value: 1.03 mg/kg\",\"StationNumber: 98MTB0090, Year: 1998, Value: 0.747 mg/kg\",\"StationNumber: 98MTB0103, Year: 1998, Value: 0.073 mg/kg\",\"StationNumber: 98MTB0133, Year: 1998, Value: 0.164 mg/kg\",\"StationNumber: 98MTB0187, Year: 1998, Value: 1.46 mg/kg\",\"StationNumber: 98MTB0191, Year: 1998, Value: 0.192 mg/kg\",\"StationNumber: 98MTB0208, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98MTB0270, Year: 1998, Value: 0.016 mg/kg\",\"StationNumber: 98MTB0275, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98MTB0283, Year: 1998, Value: 0.376 mg/kg\",\"StationNumber: 98MTB0322, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98MTB0331, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98MTB0416, Year: 1998, Value: 3.312 mg/kg\",\"StationNumber: 98MTB0460, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98MTB0688, Year: 1998, Value: 0.769 mg/kg\",\"StationNumber: 98MTB0694, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98MTB1036, Year: 1998, Value: 0.018 mg/kg\",\"StationNumber: 98OTB0036, Year: 1998, Value: 0.256 mg/kg\",\"StationNumber: 98OTB0039, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98OTB0048, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98OTB0056, Year: 1998, Value: 0.499 mg/kg\",\"StationNumber: 98OTB0125, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98OTB0177, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98OTB0185, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98OTB0199, Year: 1998, Value: 2.325 mg/kg\",\"StationNumber: 98OTB0232, Year: 1998, Value: 0.301 mg/kg\",\"StationNumber: 98OTB0239, Year: 1998, Value: 1.557 mg/kg\",\"StationNumber: 98OTB0274, Year: 1998, Value: 2.028 mg/kg\",\"StationNumber: 98OTB0425, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98OTB0596, Year: 1998, Value: 8.041 mg/kg\",\"StationNumber: 98OTB0721, Year: 1998, Value: 0.397 mg/kg\",\"StationNumber: 98OTB1140, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98OTB1227, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98TCB01, Year: 1998, Value: 1.816 mg/kg\",\"StationNumber: 98TCB02, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 98TCB04, Year: 1998, Value: 1.3 mg/kg\",\"StationNumber: 98TCB05, Year: 1998, Value: 0.903 mg/kg\",\"StationNumber: 98TCB06, Year: 1998, Value: 1.118 mg/kg\",\"StationNumber: 98TCB07, Year: 1998, Value: 0.966 mg/kg\",\"StationNumber: 98TCB08, Year: 1998, Value: 0.01 mg/kg\",\"StationNumber: 99BCB2025, Year: 1999, Value: 0.194 mg/kg\",\"StationNumber: 99BCB2041, Year: 1999, Value: 0.553 mg/kg\",\"StationNumber: 99BCB2063, Year: 1999, Value: 1.16 mg/kg\",\"StationNumber: 99BCB2069, Year: 1999, Value: 0.715 mg/kg\",\"StationNumber: 99BCB2070, Year: 1999, Value: 0.693 mg/kg\",\"StationNumber: 99BCB2086, Year: 1999, Value: 0.348 mg/kg\",\"StationNumber: 99BCB2094, Year: 1999, Value: 1.893 mg/kg\",\"StationNumber: 99BCB2115, Year: 1999, Value: 1.48 mg/kg\",\"StationNumber: 99BCB2132, Year: 1999, Value: 0.09 mg/kg\",\"StationNumber: 99BCB2295, Year: 1999, Value: 0.01 mg/kg\",\"StationNumber: 99BCB2358, Year: 1999, Value: 0.627 mg/kg\",\"StationNumber: 99BCB2423, Year: 1999, Value: 0.758 mg/kg\",\"StationNumber: 99BCB2514, Year: 1999, Value: 0.18 mg/kg\",\"StationNumber: 99BCB2585, Year: 1999, Value: 0.374 mg/kg\",\"StationNumber: 99BCB57/1, Year: 1999, Value: 3.215 mg/kg\",\"StationNumber: 99BCB58/1, Year: 1999, Value: 2.112 mg/kg\",\"StationNumber: 99BCB58/2, Year: 1999, Value: 1.224 mg/kg\",\"StationNumber: 99BCB59/1, Year: 1999, Value: 0.044 mg/kg\",\"StationNumber: 99BCB59/2, Year: 1999, Value: 0.787 mg/kg\",\"StationNumber: 99BCB60/2, Year: 1999, Value: 0.589 mg/kg\",\"StationNumber: 99BCB60/4, Year: 1999, Value: 1.162 mg/kg\",\"StationNumber: 99HB2001, Year: 1999, Value: 0.01 mg/kg\",\"StationNumber: 99HB2012, Year: 1999, Value: 1.721 mg/kg\",\"StationNumber: 99HB2013, Year: 1999, Value: 0.197 mg/kg\",\"StationNumber: 99HB2019, Year: 1999, Value: 0.01 mg/kg\",\"StationNumber: 99HB2040, Year: 1999, Value: 0.331 mg/kg\",\"StationNumber: 99HB2041, Year: 1999, Value: 0.988 mg/kg\",\"StationNumber: 99HB2043, Year: 1999, Value: 0.235 mg/kg\",\"StationNumber: 99HB2044, Year: 1999, Value: 0.82 mg/kg\",\"StationNumber: 99HB2051, Year: 1999, Value: 0.847 mg/kg\",\"StationNumber: 99HB2055, Year: 1999, Value: 1.08 mg/kg\",\"StationNumber: 99HB2058, Year: 1999, Value: 3.832 mg/kg\",\"StationNumber: 99HB2061, Year: 1999, Value: 5.185 mg/kg\",\"StationNumber: 99HB2085, Year: 1999, Value: 3.395 mg/kg\",\"StationNumber: 99HB2094, Year: 1999, Value: 0.205 mg/kg\",\"StationNumber: 99HB2124, Year: 1999, Value: 2.804 mg/kg\",\"StationNumber: 99HB2157, Year: 1999, Value: 0.252 mg/kg\",\"StationNumber: 99HB2176, Year: 1999, Value: 0.468 mg/kg\",\"StationNumber: 99HB2207, Year: 1999, Value: 2.127 mg/kg\",\"StationNumber: 99HB2214, Year: 1999, Value: 0.649 mg/kg\",\"StationNumber: 99HB2233, Year: 1999, Value: 2.896 mg/kg\",\"StationNumber: 99HB2393, Year: 1999, Value: 1.265 mg/kg\",\"StationNumber: 99HB2445, Year: 1999, Value: 1.072 mg/kg\",\"StationNumber: 99HB2757, Year: 1999, Value: 1.051 mg/kg\",\"StationNumber: 99LTB2014, Year: 1999, Value: 0.01 mg/kg\",\"StationNumber: 99LTB2021, Year: 1999, Value: 11.552 mg/kg\",\"StationNumber: 99LTB2041, Year: 1999, Value: 4.997 mg/kg\",\"StationNumber: 99LTB2071, Year: 1999, Value: 5.805 mg/kg\",\"StationNumber: 99LTB2112, Year: 1999, Value: 3.993 mg/kg\",\"StationNumber: 99LTB2124, Year: 1999, Value: 0.035 mg/kg\",\"StationNumber: 99LTB2203, Year: 1999, Value: 0.664 mg/kg\",\"StationNumber: 99LTB2214, Year: 1999, Value: 0.098 mg/kg\",\"StationNumber: 99LTB2247, Year: 1999, Value: 0.297 mg/kg\",\"StationNumber: 99LTB2267, Year: 1999, Value: 1.444 mg/kg\",\"StationNumber: 99LTB2277, Year: 1999, Value: 0.692 mg/kg\",\"StationNumber: 99LTB2290, Year: 1999, Value: 1.374 mg/kg\",\"StationNumber: 99LTB2327, Year: 1999, Value: 0.362 mg/kg\",\"StationNumber: 99LTB2546, Year: 1999, Value: 0.994 mg/kg\",\"StationNumber: 99LTB2617, Year: 1999, Value: 3.167 mg/kg\",\"StationNumber: 99LTB3020, Year: 1999, Value: 0.368 mg/kg\",\"StationNumber: 99MR09, Year: 1999, Value: 0.375 mg/kg\",\"StationNumber: 99MR10, Year: 1999, Value: 0.445 mg/kg\",\"StationNumber: 99MR11, Year: 1999, Value: 1.258 mg/kg\",\"StationNumber: 99MR12, Year: 1999, Value: 0.538 mg/kg\",\"StationNumber: 99MR13, Year: 1999, Value: 0.57 mg/kg\",\"StationNumber: 99MR14, Year: 1999, Value: 0.402 mg/kg\",\"StationNumber: 99MR15, Year: 1999, Value: 0.668 mg/kg\",\"StationNumber: 99MR16, Year: 1999, Value: 0.087 mg/kg\",\"StationNumber: 99MR17, Year: 1999, Value: 0.01 mg/kg\",\"StationNumber: 99MR18, Year: 1999, Value: 0.01 mg/kg\",\"StationNumber: 99MR19, Year: 1999, Value: 0.01 mg/kg\",\"StationNumber: 99MR20, Year: 1999, Value: 0.01 mg/kg\",\"StationNumber: 99MR21, Year: 1999, Value: 0.01 mg/kg\",\"StationNumber: 99MTB2029, Year: 1999, Value: 1.088 mg/kg\",\"StationNumber: 99MTB2059, Year: 1999, Value: 0.528 mg/kg\",\"StationNumber: 99MTB2060, Year: 1999, Value: 0.709 mg/kg\",\"StationNumber: 99MTB2108, Year: 1999, Value: 0.57 mg/kg\",\"StationNumber: 99MTB2109, Year: 1999, Value: 0.25 mg/kg\",\"StationNumber: 99MTB2116, Year: 1999, Value: 0.479 mg/kg\",\"StationNumber: 99MTB2129, Year: 1999, Value: 1.833 mg/kg\",\"StationNumber: 99MTB2149, Year: 1999, Value: 0.968 mg/kg\",\"StationNumber: 99MTB2165, Year: 1999, Value: 0.712 mg/kg\",\"StationNumber: 99MTB2240, Year: 1999, Value: 0.188 mg/kg\",\"StationNumber: 99MTB2243, Year: 1999, Value: 1.994 mg/kg\",\"StationNumber: 99MTB2244, Year: 1999, Value: 2.396 mg/kg\",\"StationNumber: 99MTB2253, Year: 1999, Value: 1.24 mg/kg\",\"StationNumber: 99MTB2268, Year: 1999, Value: 1.218 mg/kg\",\"StationNumber: 99MTB2274, Year: 1999, Value: 2.485 mg/kg\",\"StationNumber: 99MTB2291, Year: 1999, Value: 0.01 mg/kg\",\"StationNumber: 99MTB2358, Year: 1999, Value: 0.699 mg/kg\",\"StationNumber: 99MTB2385, Year: 1999, Value: 0.269 mg/kg\",\"StationNumber: 99MTB2554, Year: 1999, Value: 0.524 mg/kg\",\"StationNumber: 99MTB2598, Year: 1999, Value: 1.573 mg/kg\",\"StationNumber: 99MTB2642, Year: 1999, Value: 0.016 mg/kg\",\"StationNumber: 99OTB2002, Year: 1999, Value: 0.452 mg/kg\",\"StationNumber: 99OTB2005, Year: 1999, Value: 0.022 mg/kg\",\"StationNumber: 99OTB2009, Year: 1999, Value: 0.41 mg/kg\",\"StationNumber: 99OTB2010, Year: 1999, Value: 0.29 mg/kg\",\"StationNumber: 99OTB2022, Year: 1999, Value: 0.836 mg/kg\",\"StationNumber: 99OTB2045, Year: 1999, Value: 0.166 mg/kg\",\"StationNumber: 99OTB2067, Year: 1999, Value: 0.055 mg/kg\",\"StationNumber: 99OTB2111, Year: 1999, Value: 0.071 mg/kg\",\"StationNumber: 99OTB2121, Year: 1999, Value: 0.29 mg/kg\",\"StationNumber: 99OTB2225, Year: 1999, Value: 0.203 mg/kg\",\"StationNumber: 99OTB2296, Year: 1999, Value: 0.839 mg/kg\",\"StationNumber: 99OTB2313, Year: 1999, Value: 0.875 mg/kg\",\"StationNumber: 99OTB2316, Year: 1999, Value: 1.126 mg/kg\",\"StationNumber: 99OTB2331, Year: 1999, Value: 0.353 mg/kg\",\"StationNumber: 99OTB2395, Year: 1999, Value: 0.233 mg/kg\",\"StationNumber: 99OTB2482, Year: 1999, Value: 1.236 mg/kg\",\"StationNumber: 99OTB2908, Year: 1999, Value: 0.307 mg/kg\",\"StationNumber: 99OTB2994, Year: 1999, Value: 0.038 mg/kg\",\"StationNumber: 99OTB3046, Year: 1999, Value: 0.397 mg/kg\",\"StationNumber: 99TCB01, Year: 1999, Value: 1.95 mg/kg\",\"StationNumber: 99TCB02, Year: 1999, Value: 0.225 mg/kg\",\"StationNumber: 99TCB03, Year: 1999, Value: 4.578 mg/kg\",\"StationNumber: 99TCB04, Year: 1999, Value: 2.024 mg/kg\",\"StationNumber: 99TCB05, Year: 1999, Value: 1.134 mg/kg\",\"StationNumber: 99TCB06, Year: 1999, Value: 1.082 mg/kg\",\"StationNumber: 99TCB07, Year: 1999, Value: 1.652 mg/kg\",\"StationNumber: 99TCB08, Year: 1999, Value: 0.01 mg/kg\",\"StationNumber: 00BCB4000, Year: 2000, Value: 7.05 mg/kg\",\"StationNumber: 00BCB4001, Year: 2000, Value: 8.917 mg/kg\",\"StationNumber: 00BCB4004, Year: 2000, Value: 5.717 mg/kg\",\"StationNumber: 00BCB4033, Year: 2000, Value: 6.44 mg/kg\",\"StationNumber: 00BCB4034, Year: 2000, Value: 6.595 mg/kg\",\"StationNumber: 00BCB4037, Year: 2000, Value: 5.573 mg/kg\",\"StationNumber: 00BCB4038, Year: 2000, Value: 7.398 mg/kg\",\"StationNumber: 00BCB4041, Year: 2000, Value: 8.081 mg/kg\",\"StationNumber: 00BCB4042, Year: 2000, Value: 8.315 mg/kg\",\"StationNumber: 00BCB4046, Year: 2000, Value: 7.3 mg/kg\",\"StationNumber: 00BCB4079, Year: 2000, Value: 5.898 mg/kg\",\"StationNumber: 00BCB4084, Year: 2000, Value: 6.968 mg/kg\",\"StationNumber: 00BCB4090, Year: 2000, Value: 8.108 mg/kg\",\"StationNumber: 00BCB4100, Year: 2000, Value: 7.966 mg/kg\",\"StationNumber: 00BCB4124, Year: 2000, Value: 5.814 mg/kg\",\"StationNumber: 00BCB4165, Year: 2000, Value: 5.405 mg/kg\",\"StationNumber: 00BCB4174, Year: 2000, Value: 8.747 mg/kg\",\"StationNumber: 00BCB4207, Year: 2000, Value: 7.704 mg/kg\",\"StationNumber: 00BCB4268, Year: 2000, Value: 7.855 mg/kg\",\"StationNumber: 00BCB4299, Year: 2000, Value: 8.06 mg/kg\",\"StationNumber: 00BCB4312, Year: 2000, Value: 8.316 mg/kg\",\"StationNumber: 00BCB58/1, Year: 2000, Value: 5.498 mg/kg\",\"StationNumber: 00BCB58/2, Year: 2000, Value: 4.644 mg/kg\",\"StationNumber: 00BCB59/1, Year: 2000, Value: 6.148 mg/kg\",\"StationNumber: 00BCB59/2, Year: 2000, Value: 5.036 mg/kg\",\"StationNumber: 00BCB60/2, Year: 2000, Value: 5.003 mg/kg\",\"StationNumber: 00BCB60/4, Year: 2000, Value: 4.842 mg/kg\",\"StationNumber: 00HB4002, Year: 2000, Value: 5.886 mg/kg\",\"StationNumber: 00HB4006, Year: 2000, Value: 6.219 mg/kg\",\"StationNumber: 00HB4019, Year: 2000, Value: 3.684 mg/kg\",\"StationNumber: 00HB4023, Year: 2000, Value: 5.729 mg/kg\",\"StationNumber: 00HB4032, Year: 2000, Value: 5.767 mg/kg\",\"StationNumber: 00HB4033, Year: 2000, Value: 4.768 mg/kg\",\"StationNumber: 00HB4038, Year: 2000, Value: 6.182 mg/kg\",\"StationNumber: 00HB4047, Year: 2000, Value: 5.84 mg/kg\",\"StationNumber: 00HB4058, Year: 2000, Value: 3.097 mg/kg\",\"StationNumber: 00HB4077, Year: 2000, Value: 6.608 mg/kg\",\"StationNumber: 00HB4082, Year: 2000, Value: 6.717 mg/kg\",\"StationNumber: 00HB4083, Year: 2000, Value: 7.399 mg/kg\",\"StationNumber: 00HB4093, Year: 2000, Value: 1.936 mg/kg\",\"StationNumber: 00HB4094, Year: 2000, Value: 2.189 mg/kg\",\"StationNumber: 00HB4100, Year: 2000, Value: 4.324 mg/kg\",\"StationNumber: 00HB4106, Year: 2000, Value: 2.128 mg/kg\",\"StationNumber: 00HB4144, Year: 2000, Value: 1.909 mg/kg\",\"StationNumber: 00HB4152, Year: 2000, Value: 7.008 mg/kg\",\"StationNumber: 00HB4267, Year: 2000, Value: 4.486 mg/kg\",\"StationNumber: 00HB4291, Year: 2000, Value: 4.846 mg/kg\",\"StationNumber: 00HB4316, Year: 2000, Value: 6.769 mg/kg\",\"StationNumber: 00HB4505, Year: 2000, Value: 4.805 mg/kg\",\"StationNumber: 00LTB4039, Year: 2000, Value: 2.434 mg/kg\",\"StationNumber: 00LTB4051, Year: 2000, Value: 4.039 mg/kg\",\"StationNumber: 00LTB4066, Year: 2000, Value: 1.702 mg/kg\",\"StationNumber: 00LTB4117, Year: 2000, Value: 3.904 mg/kg\",\"StationNumber: 00LTB4151, Year: 2000, Value: 5.587 mg/kg\",\"StationNumber: 00LTB4185, Year: 2000, Value: 3.635 mg/kg\",\"StationNumber: 00LTB4286, Year: 2000, Value: 5.878 mg/kg\",\"StationNumber: 00LTB4340, Year: 2000, Value: 2.792 mg/kg\",\"StationNumber: 00LTB4484, Year: 2000, Value: 2.7 mg/kg\",\"StationNumber: 00LTB4487, Year: 2000, Value: 1.721 mg/kg\",\"StationNumber: 00LTB4513, Year: 2000, Value: 1.915 mg/kg\",\"StationNumber: 00LTB4529, Year: 2000, Value: 5.51 mg/kg\",\"StationNumber: 00LTB4536, Year: 2000, Value: 6.17 mg/kg\",\"StationNumber: 00LTB4637, Year: 2000, Value: 9.27 mg/kg\",\"StationNumber: 00LTB4677, Year: 2000, Value: 1.76 mg/kg\",\"StationNumber: 00LTB4730, Year: 2000, Value: 9.63 mg/kg\",\"StationNumber: 00LTB4749, Year: 2000, Value: 1.727 mg/kg\",\"StationNumber: 00MR09, Year: 2000, Value: 7.262 mg/kg\",\"StationNumber: 00MR10, Year: 2000, Value: 7.28 mg/kg\",\"StationNumber: 00MR11, Year: 2000, Value: 7.022 mg/kg\",\"StationNumber: 00MR12, Year: 2000, Value: 6.682 mg/kg\",\"StationNumber: 00MR13, Year: 2000, Value: 6.746 mg/kg\",\"StationNumber: 00MR14, Year: 2000, Value: 5.791 mg/kg\",\"StationNumber: 00MR15, Year: 2000, Value: 5.559 mg/kg\",\"StationNumber: 00MR16, Year: 2000, Value: 4.961 mg/kg\",\"StationNumber: 00MR17, Year: 2000, Value: 5.02 mg/kg\",\"StationNumber: 00MR18, Year: 2000, Value: 5.104 mg/kg\",\"StationNumber: 00MR19, Year: 2000, Value: 7.434 mg/kg\",\"StationNumber: 00MR20, Year: 2000, Value: 2.837 mg/kg\",\"StationNumber: 00MR21, Year: 2000, Value: 4.022 mg/kg\",\"StationNumber: 00MTB4030, Year: 2000, Value: 4.501 mg/kg\",\"StationNumber: 00MTB4032, Year: 2000, Value: 8.919 mg/kg\",\"StationNumber: 00MTB4041, Year: 2000, Value: 2.068 mg/kg\",\"StationNumber: 00MTB4061, Year: 2000, Value: 2.284 mg/kg\",\"StationNumber: 00MTB4072, Year: 2000, Value: 1.826 mg/kg\",\"StationNumber: 00MTB4086, Year: 2000, Value: 1.935 mg/kg\",\"StationNumber: 00MTB4090, Year: 2000, Value: 9.376 mg/kg\",\"StationNumber: 00MTB4098, Year: 2000, Value: 19.11 mg/kg\",\"StationNumber: 00MTB4100, Year: 2000, Value: 5.523 mg/kg\",\"StationNumber: 00MTB4106, Year: 2000, Value: 2.373 mg/kg\",\"StationNumber: 00MTB4159, Year: 2000, Value: 2.926 mg/kg\",\"StationNumber: 00MTB4181, Year: 2000, Value: 5.332 mg/kg\",\"StationNumber: 00MTB4193, Year: 2000, Value: 2.564 mg/kg\",\"StationNumber: 00MTB4201, Year: 2000, Value: 5.145 mg/kg\",\"StationNumber: 00MTB4249, Year: 2000, Value: 5.123 mg/kg\",\"StationNumber: 00MTB4265, Year: 2000, Value: 18.11 mg/kg\",\"StationNumber: 00MTB4310, Year: 2000, Value: 4.749 mg/kg\",\"StationNumber: 00MTB4363, Year: 2000, Value: 5.988 mg/kg\",\"StationNumber: 00MTB4504, Year: 2000, Value: 1.819 mg/kg\",\"StationNumber: 00MTB4584, Year: 2000, Value: 4.649 mg/kg\",\"StationNumber: 00MTB4653, Year: 2000, Value: 6.862 mg/kg\",\"StationNumber: 00MTB4845, Year: 2000, Value: 6.98 mg/kg\",\"StationNumber: 00MTB5125, Year: 2000, Value: 6.297 mg/kg\",\"StationNumber: 00OTB4011, Year: 2000, Value: 6.398 mg/kg\",\"StationNumber: 00OTB4019, Year: 2000, Value: 5.242 mg/kg\",\"StationNumber: 00OTB4037, Year: 2000, Value: 5.554 mg/kg\",\"StationNumber: 00OTB4040, Year: 2000, Value: 6.998 mg/kg\",\"StationNumber: 00OTB4044, Year: 2000, Value: 6.455 mg/kg\",\"StationNumber: 00OTB4096, Year: 2000, Value: 6.509 mg/kg\",\"StationNumber: 00OTB4105, Year: 2000, Value: 4.904 mg/kg\",\"StationNumber: 00OTB4123, Year: 2000, Value: 6.756 mg/kg\",\"StationNumber: 00OTB4132, Year: 2000, Value: 4.869 mg/kg\",\"StationNumber: 00OTB4138, Year: 2000, Value: 5.793 mg/kg\",\"StationNumber: 00OTB4149, Year: 2000, Value: 6.974 mg/kg\",\"StationNumber: 00OTB4192, Year: 2000, Value: 4.798 mg/kg\",\"StationNumber: 00OTB4217, Year: 2000, Value: 6.639 mg/kg\",\"StationNumber: 00OTB4254, Year: 2000, Value: 8.763 mg/kg\",\"StationNumber: 00OTB4278, Year: 2000, Value: 2.048 mg/kg\",\"StationNumber: 00OTB4402, Year: 2000, Value: 7.662 mg/kg\",\"StationNumber: 00OTB4407, Year: 2000, Value: 8.601 mg/kg\",\"StationNumber: 00OTB4650, Year: 2000, Value: 8.558 mg/kg\",\"StationNumber: 00OTB4946, Year: 2000, Value: 7.083 mg/kg\",\"StationNumber: 00TCB01, Year: 2000, Value: 5.933 mg/kg\",\"StationNumber: 00TCB02, Year: 2000, Value: 3.519 mg/kg\",\"StationNumber: 00TCB03, Year: 2000, Value: 9.862 mg/kg\",\"StationNumber: 00TCB04, Year: 2000, Value: 4.401 mg/kg\",\"StationNumber: 00TCB05, Year: 2000, Value: 6.928 mg/kg\",\"StationNumber: 00TCB06, Year: 2000, Value: 6.186 mg/kg\",\"StationNumber: 00TCB07, Year: 2000, Value: 6.023 mg/kg\",\"StationNumber: 00TCB08, Year: 2000, Value: 5.912 mg/kg\",\"StationNumber: 01BCB57/1, Year: 2001, Value: 2.985 mg/kg\",\"StationNumber: 01BCB58/1, Year: 2001, Value: 4.108 mg/kg\",\"StationNumber: 01BCB58/2, Year: 2001, Value: 4.081 mg/kg\",\"StationNumber: 01BCB59/1, Year: 2001, Value: 2.709 mg/kg\",\"StationNumber: 01BCB59/2, Year: 2001, Value: 2.059 mg/kg\",\"StationNumber: 01BCB60/2, Year: 2001, Value: 3.449 mg/kg\",\"StationNumber: 01BCB60/4, Year: 2001, Value: 0.432 mg/kg\",\"StationNumber: 01BCB6001, Year: 2001, Value: 4.072 mg/kg\",\"StationNumber: 01BCB6009, Year: 2001, Value: 3.178 mg/kg\",\"StationNumber: 01BCB6018, Year: 2001, Value: 2.845 mg/kg\",\"StationNumber: 01BCB6019, Year: 2001, Value: 3.296 mg/kg\",\"StationNumber: 01BCB6031, Year: 2001, Value: 3.409 mg/kg\",\"StationNumber: 01BCB6063, Year: 2001, Value: 0.01 mg/kg\",\"StationNumber: 01BCB6072, Year: 2001, Value: 3.246 mg/kg\",\"StationNumber: 01BCB6089, Year: 2001, Value: 2.207 mg/kg\",\"StationNumber: 01BCB6109, Year: 2001, Value: 2.415 mg/kg\",\"StationNumber: 01BCB6114, Year: 2001, Value: 2.628 mg/kg\",\"StationNumber: 01BCB6152, Year: 2001, Value: 2.854 mg/kg\",\"StationNumber: 01BCB6178, Year: 2001, Value: 2.596 mg/kg\",\"StationNumber: 01BCB6190, Year: 2001, Value: 2.145 mg/kg\",\"StationNumber: 01BCB6230, Year: 2001, Value: 3.755 mg/kg\",\"StationNumber: 01BCB6263, Year: 2001, Value: 1.707 mg/kg\",\"StationNumber: 01BCB6359, Year: 2001, Value: 1.433 mg/kg\",\"StationNumber: 01HB6019, Year: 2001, Value: 0.01 mg/kg\",\"StationNumber: 01HB6022, Year: 2001, Value: 1.909 mg/kg\",\"StationNumber: 01HB6032, Year: 2001, Value: 2.588 mg/kg\",\"StationNumber: 01HB6035, Year: 2001, Value: 0.01 mg/kg\",\"StationNumber: 01HB6045, Year: 2001, Value: 0.325 mg/kg\",\"StationNumber: 01HB6064, Year: 2001, Value: 0.01 mg/kg\",\"StationNumber: 01HB6066, Year: 2001, Value: 1.155 mg/kg\",\"StationNumber: 01HB6087, Year: 2001, Value: 0.01 mg/kg\",\"StationNumber: 01HB6093, Year: 2001, Value: 2.265 mg/kg\",\"StationNumber: 01HB6102, Year: 2001, Value: 2.313 mg/kg\",\"StationNumber: 01HB6108, Year: 2001, Value: 0.01 mg/kg\",\"StationNumber: 01HB6131, Year: 2001, Value: 0.71 mg/kg\",\"StationNumber: 01HB6140, Year: 2001, Value: 2.982 mg/kg\",\"StationNumber: 01HB6145, Year: 2001, Value: 2.677 mg/kg\",\"StationNumber: 01HB6159, Year: 2001, Value: 2.869 mg/kg\",\"StationNumber: 01HB6186, Year: 2001, Value: 0.01 mg/kg\",\"StationNumber: 01HB6187, Year: 2001, Value: 3.434 mg/kg\",\"StationNumber: 01HB6249, Year: 2001, Value: 0.01 mg/kg\",\"StationNumber: 01HB6261, Year: 2001, Value: 3.626 mg/kg\",\"StationNumber: 01HB6264, Year: 2001, Value: 1.742 mg/kg\",\"StationNumber: 01HB6283, Year: 2001, Value: 1.357 mg/kg\",\"StationNumber: 01HB6305, Year: 2001, Value: 2.006 mg/kg\",\"StationNumber: 01HB6374, Year: 2001, Value: 0.01 mg/kg\",\"StationNumber: 01HB6453, Year: 2001, Value: 2.977 mg/kg\",\"StationNumber: 01HB6537, Year: 2001, Value: 3.517 mg/kg\",\"StationNumber: 01LTB6026, Year: 2001, Value: 14.165 mg/kg\",\"StationNumber: 01LTB6027, Year: 2001, Value: 1.328 mg/kg\",\"StationNumber: 01LTB6050, Year: 2001, Value: 0.606 mg/kg\",\"StationNumber: 01LTB6104, Year: 2001, Value: 0.01 mg/kg\",\"StationNumber: 01LTB6120, Year: 2001, Value: 0.01 mg/kg\",\"StationNumber: 01LTB6122, Year: 2001, Value: 0.66 mg/kg\",\"StationNumber: 01LTB6158, Year: 2001, Value: 5.092 mg/kg\",\"StationNumber: 01LTB6302, Year: 2001, Value: 0.01 mg/kg\",\"StationNumber: 01LTB6346, Year: 2001, Value: 0 mg/kg\",\"StationNumber: 01LTB6380, Year: 2001, Value: 0.874 mg/kg\",\"StationNumber: 01LTB6595, Year: 2001, Value: 3.852 mg/kg\",\"StationNumber: 01LTB6869, Year: 2001, Value: 0.01 mg/kg\",\"StationNumber: 01MR09, Year: 2001, Value: 0 mg/kg\",\"StationNumber: 01MR12, Year: 2001, Value: 0 mg/kg\",\"StationNumber: 01MR13, Year: 2001, Value: 0 mg/kg\",\"StationNumber: 01MR14, Year: 2001, Value: 0 mg/kg\",\"StationNumber: 01MR17, Year: 2001, Value: 0 mg/kg\",\"StationNumber: 01MR18, Year: 2001, Value: 0 mg/kg\",\"StationNumber: 01MR19, Year: 2001, Value: 0 mg/kg\",\"StationNumber: 01MR20, Year: 2001, Value: 0 mg/kg\",\"StationNumber: 01MR21, Year: 2001, Value: 0 mg/kg\",\"StationNumber: 01MTB6002, Year: 2001, Value: 0.981 mg/kg\",\"StationNumber: 01MTB6011, Year: 2001, Value: 0.416 mg/kg\",\"StationNumber: 01MTB6014, Year: 2001, Value: 0.01 mg/kg\",\"StationNumber: 01MTB6049, Year: 2001, Value: 0.168 mg/kg\",\"StationNumber: 01MTB6059, Year: 2001, Value: 5.14 mg/kg\",\"StationNumber: 01MTB6064, Year: 2001, Value: 3.241 mg/kg\",\"StationNumber: 01MTB6068, Year: 2001, Value: 5.837 mg/kg\",\"StationNumber: 01MTB6080, Year: 2001, Value: 3.556 mg/kg\",\"StationNumber: 01MTB6133, Year: 2001, Value: 2.453 mg/kg\",\"StationNumber: 01MTB6154, Year: 2001, Value: 0.963 mg/kg\",\"StationNumber: 01MTB6188, Year: 2001, Value: 0.797 mg/kg\",\"StationNumber: 01MTB6189, Year: 2001, Value: 2.868 mg/kg\",\"StationNumber: 01MTB6196, Year: 2001, Value: 2.703 mg/kg\",\"StationNumber: 01MTB6229, Year: 2001, Value: 2.698 mg/kg\",\"StationNumber: 01MTB6257, Year: 2001, Value: 0.988 mg/kg\",\"StationNumber: 01MTB6265, Year: 2001, Value: 4.324 mg/kg\",\"StationNumber: 01MTB6290, Year: 2001, Value: 3.339 mg/kg\",\"StationNumber: 01MTB6325, Year: 2001, Value: 2.765 mg/kg\",\"StationNumber: 01MTB6327, Year: 2001, Value: 4.862 mg/kg\",\"StationNumber: 01MTB6328, Year: 2001, Value: 3.179 mg/kg\",\"StationNumber: 01MTB6464, Year: 2001, Value: 3.707 mg/kg\",\"StationNumber: 01MTB6495, Year: 2001, Value: 3.297 mg/kg\",\"StationNumber: 01MTB6527, Year: 2001, Value: 3.538 mg/kg\",\"StationNumber: 01MTB6638, Year: 2001, Value: 4.338 mg/kg\",\"StationNumber: 01MTB6699, Year: 2001, Value: 4.171 mg/kg\",\"StationNumber: 01MTB7153, Year: 2001, Value: 3.938 mg/kg\",\"StationNumber: 01OTB6010, Year: 2001, Value: 3.892 mg/kg\",\"StationNumber: 01OTB6017, Year: 2001, Value: 3.183 mg/kg\",\"StationNumber: 01OTB6021, Year: 2001, Value: 2.793 mg/kg\",\"StationNumber: 01OTB6022, Year: 2001, Value: 1.206 mg/kg\",\"StationNumber: 01OTB6025, Year: 2001, Value: 0.01 mg/kg\",\"StationNumber: 01OTB6028, Year: 2001, Value: 5.384 mg/kg\",\"StationNumber: 01OTB6078, Year: 2001, Value: 3.845 mg/kg\",\"StationNumber: 01OTB6103, Year: 2001, Value: 5.634 mg/kg\",\"StationNumber: 01OTB6135, Year: 2001, Value: 2.772 mg/kg\",\"StationNumber: 01OTB6152, Year: 2001, Value: 28.868 mg/kg\",\"StationNumber: 01OTB6178, Year: 2001, Value: 9.713 mg/kg\",\"StationNumber: 01OTB6186, Year: 2001, Value: 5.55 mg/kg\",\"StationNumber: 01OTB6234, Year: 2001, Value: 5.199 mg/kg\",\"StationNumber: 01OTB6239, Year: 2001, Value: 0.01 mg/kg\",\"StationNumber: 01OTB6441, Year: 2001, Value: 5.652 mg/kg\",\"StationNumber: 01OTB6784, Year: 2001, Value: 10.207 mg/kg\",\"StationNumber: 01OTB6830, Year: 2001, Value: 5.184 mg/kg\",\"StationNumber: 01SAFHAB, Year: 2001, Value: 0.01 mg/kg\",\"StationNumber: 01TCB02, Year: 2001, Value: 0 mg/kg\",\"StationNumber: 01TCB03, Year: 2001, Value: 0 mg/kg\",\"StationNumber: 01TCB04, Year: 2001, Value: 0 mg/kg\",\"StationNumber: 01TCB06, Year: 2001, Value: 0 mg/kg\",\"StationNumber: 01TCB07, Year: 2001, Value: 0 mg/kg\",\"StationNumber: 02BCB05, Year: 2002, Value: 5.202 mg/kg\",\"StationNumber: 02BCB20, Year: 2002, Value: 1.257 mg/kg\",\"StationNumber: 02BCB32, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02BCB52, Year: 2002, Value: 0.407 mg/kg\",\"StationNumber: 02BCB62, Year: 2002, Value: 3.401 mg/kg\",\"StationNumber: 02BCB69, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02BCB74, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02BCB83, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02BCB90, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH03-2, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH03-4, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH03-5, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH05-3, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH05-4, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH05-5, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH07-1, Year: 2002, Value: 0.426 mg/kg\",\"StationNumber: 02DH07-2, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH07-3, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH08-1, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH08-2, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH08-3, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH09-1, Year: 2002, Value: 2.957 mg/kg\",\"StationNumber: 02DH09-2, Year: 2002, Value: 1.154 mg/kg\",\"StationNumber: 02DH09-3, Year: 2002, Value: 3.812 mg/kg\",\"StationNumber: 02DH11A-1, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH11A-2, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH11A-3, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH11B-1, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH11B-4, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH11B-5, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH14-1, Year: 2002, Value: 1.74 mg/kg\",\"StationNumber: 02DH14-3, Year: 2002, Value: 1.197 mg/kg\",\"StationNumber: 02DH14-4, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH15-1, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH15-2, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH15-5, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH18-1, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH18-2, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH18-3, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH20-3, Year: 2002, Value: 0.146 mg/kg\",\"StationNumber: 02DH20-4, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH20-5, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH21A-1, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH21A-3, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH21A-5, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH21B-1, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02DH21B-3, Year: 2002, Value: 0.323 mg/kg\",\"StationNumber: 02DH21B-4, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02HB09, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02HB20, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02HB21, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02HB27, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02HB39, Year: 2002, Value: 0.328 mg/kg\",\"StationNumber: 02HB42, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02HB49, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02HB50, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02HB51, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02HB55, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02LTB01, Year: 2002, Value: 3.105 mg/kg\",\"StationNumber: 02LTB02, Year: 2002, Value: 4.432 mg/kg\",\"StationNumber: 02LTB03, Year: 2002, Value: 0.925 mg/kg\",\"StationNumber: 02LTB04, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02LTB05, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02LTB06, Year: 2002, Value: 0.657 mg/kg\",\"StationNumber: 02LTB07, Year: 2002, Value: 0.376 mg/kg\",\"StationNumber: 02LTB08, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02LTB09, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02MR02, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02MR04, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02MR06, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02MR08, Year: 2002, Value: 0.022 mg/kg\",\"StationNumber: 02MR10, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02MR11, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02MR12, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02MTB11, Year: 2002, Value: 0.563 mg/kg\",\"StationNumber: 02MTB12, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02MTB18, Year: 2002, Value: 1.634 mg/kg\",\"StationNumber: 02MTB19, Year: 2002, Value: 6.859 mg/kg\",\"StationNumber: 02MTB21, Year: 2002, Value: 0.379 mg/kg\",\"StationNumber: 02MTB23, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02MTB27, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02MTB29, Year: 2002, Value: 4.363 mg/kg\",\"StationNumber: 02MTB32, Year: 2002, Value: 0.595 mg/kg\",\"StationNumber: 02MTB34, Year: 2002, Value: 0.126 mg/kg\",\"StationNumber: 02OTB02, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02OTB04, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02OTB27, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02OTB49, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02OTB50, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02OTB52, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02OTB60, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02OTB66, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02TCB03, Year: 2002, Value: 1.409 mg/kg\",\"StationNumber: 02TCB05, Year: 2002, Value: 0.01 mg/kg\",\"StationNumber: 02TCB07, Year: 2002, Value: 3.347 mg/kg\",\"StationNumber: 02TCB09, Year: 2002, Value: 0.612 mg/kg\",\"StationNumber: 03BCB107, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03BCB120, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03BCB126, Year: 2003, Value: 0.086 mg/kg\",\"StationNumber: 03BCB190, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03BCB230, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03BCB242, Year: 2003, Value: 2.439 mg/kg\",\"StationNumber: 03BCB278, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03BCB287, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03BCB338, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03BCB439, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03HB01, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03HB02, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03HB04, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03HB06, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03HB09, Year: 2003, Value: 5.878 mg/kg\",\"StationNumber: 03HB10, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03HB11, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03HB12, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03HB14, Year: 2003, Value: 0.176 mg/kg\",\"StationNumber: 03HB16, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03HB18, Year: 2003, Value: 1.028 mg/kg\",\"StationNumber: 03HB21, Year: 2003, Value: 3.834 mg/kg\",\"StationNumber: 03HB27, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03HB28, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03HB30, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03HB32, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03HB33, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03HB34, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03HB37, Year: 2003, Value: 0.988 mg/kg\",\"StationNumber: 03HB38, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03HB41, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03HB42, Year: 2003, Value: 1.908 mg/kg\",\"StationNumber: 03HB44, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03HB47, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03HB50, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03HB51, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03HB52, Year: 2003, Value: 3.438 mg/kg\",\"StationNumber: 03HB53, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03LTB01, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03LTB02, Year: 2003, Value: 7.824 mg/kg\",\"StationNumber: 03LTB03, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03LTB04, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03LTB05, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03LTB06, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03LTB07, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03LTB08, Year: 2003, Value: 1.746 mg/kg\",\"StationNumber: 03LTB09, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03LTB10, Year: 2003, Value: 3.726 mg/kg\",\"StationNumber: 03LTB11, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03LTB12, Year: 2003, Value: 5.634 mg/kg\",\"StationNumber: 03MR02, Year: 2003, Value: 0.283 mg/kg\",\"StationNumber: 03MR04, Year: 2003, Value: 0.17 mg/kg\",\"StationNumber: 03MR06, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03MR07, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03MR08, Year: 2003, Value: 0.608 mg/kg\",\"StationNumber: 03MR09, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03MR10, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03MTB03, Year: 2003, Value: 1.161 mg/kg\",\"StationNumber: 03MTB08, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03MTB10, Year: 2003, Value: 1.265 mg/kg\",\"StationNumber: 03MTB11, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03MTB13, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03MTB14, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03MTB15, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03MTB16, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03MTB17, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03MTB18, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03MTB19, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03MTB21, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03MTB24, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03MTB25, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03MTB27, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03MTB28, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03MTB30, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03MTB31, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03MTB32, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03MTB33, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03MTB34, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03MTB35, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03OTB157, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03OTB200, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03OTB413, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03OTB414, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03OTB507, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03OTB623, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03OTB706, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03OTB794, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03OTB929, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03TCB01, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03TCB03, Year: 2003, Value: 0.01 mg/kg\",\"StationNumber: 03TCB05, Year: 2003, Value: 3.05 mg/kg\",\"StationNumber: 04BCB01, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04BCB02, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04BCB03, Year: 2004, Value: 2.501 mg/kg\",\"StationNumber: 04BCB04, Year: 2004, Value: 0.51 mg/kg\",\"StationNumber: 04BCB05, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04BCB06, Year: 2004, Value: 0.839 mg/kg\",\"StationNumber: 04BCB07, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04BCB08, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04BCB09, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04BCB10, Year: 2004, Value: 2.332 mg/kg\",\"StationNumber: 04HB01, Year: 2004, Value: 0.523 mg/kg\",\"StationNumber: 04HB02, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04HB03, Year: 2004, Value: 0.552 mg/kg\",\"StationNumber: 04HB04, Year: 2004, Value: 1.214 mg/kg\",\"StationNumber: 04HB05, Year: 2004, Value: 0.346 mg/kg\",\"StationNumber: 04HB06, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04HB07, Year: 2004, Value: 1.338 mg/kg\",\"StationNumber: 04HB08, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04HB09, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04HB10, Year: 2004, Value: 2.967 mg/kg\",\"StationNumber: 04HB11, Year: 2004, Value: 0.026 mg/kg\",\"StationNumber: 04HB12, Year: 2004, Value: 0.348 mg/kg\",\"StationNumber: 04HB13, Year: 2004, Value: 0.431 mg/kg\",\"StationNumber: 04HB14, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04HB15, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04HB16, Year: 2004, Value: 0.477 mg/kg\",\"StationNumber: 04HB17, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04HB18, Year: 2004, Value: 2.08 mg/kg\",\"StationNumber: 04HB19, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04HB20, Year: 2004, Value: 0.117 mg/kg\",\"StationNumber: 04HB21, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04HB23, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04HB24, Year: 2004, Value: 0.37 mg/kg\",\"StationNumber: 04HB25, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04HB26, Year: 2004, Value: 0.004 mg/kg\",\"StationNumber: 04LTB01, Year: 2004, Value: 3.535 mg/kg\",\"StationNumber: 04LTB02, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04LTB03, Year: 2004, Value: 0.715 mg/kg\",\"StationNumber: 04LTB04, Year: 2004, Value: 2.723 mg/kg\",\"StationNumber: 04LTB05, Year: 2004, Value: 0.562 mg/kg\",\"StationNumber: 04LTB06, Year: 2004, Value: 3.492 mg/kg\",\"StationNumber: 04LTB07, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04LTB08, Year: 2004, Value: 4.848 mg/kg\",\"StationNumber: 04LTB09, Year: 2004, Value: 0.25 mg/kg\",\"StationNumber: 04LTB10, Year: 2004, Value: 1.579 mg/kg\",\"StationNumber: 04LTB11, Year: 2004, Value: 1.156 mg/kg\",\"StationNumber: 04MR01, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04MR02, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04MR03, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04MR04, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04MR05, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04MR06, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04MR08, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04MR09, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04MR10, Year: 2004, Value: 0.32 mg/kg\",\"StationNumber: 04MR11, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04MTB01, Year: 2004, Value: 2.748 mg/kg\",\"StationNumber: 04MTB02, Year: 2004, Value: 2.306 mg/kg\",\"StationNumber: 04MTB04, Year: 2004, Value: 0.557 mg/kg\",\"StationNumber: 04MTB05, Year: 2004, Value: 1.049 mg/kg\",\"StationNumber: 04MTB06, Year: 2004, Value: 1.363 mg/kg\",\"StationNumber: 04MTB07, Year: 2004, Value: 0.169 mg/kg\",\"StationNumber: 04MTB08, Year: 2004, Value: 0.219 mg/kg\",\"StationNumber: 04MTB09, Year: 2004, Value: 1.226 mg/kg\",\"StationNumber: 04MTB10, Year: 2004, Value: 1.518 mg/kg\",\"StationNumber: 04MTB11, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04MTB12, Year: 2004, Value: 1.075 mg/kg\",\"StationNumber: 04MTB13, Year: 2004, Value: 0.444 mg/kg\",\"StationNumber: 04MTB14, Year: 2004, Value: 0.936 mg/kg\",\"StationNumber: 04MTB15, Year: 2004, Value: 0.83 mg/kg\",\"StationNumber: 04MTB16, Year: 2004, Value: 1.378 mg/kg\",\"StationNumber: 04MTB17, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04MTB18, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04MTB19, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04MTB20, Year: 2004, Value: 0.469 mg/kg\",\"StationNumber: 04MTB21, Year: 2004, Value: 16.571 mg/kg\",\"StationNumber: 04MTB22, Year: 2004, Value: 0.19 mg/kg\",\"StationNumber: 04MTB24, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04OTB01, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04OTB02, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04OTB03, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04OTB04, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04OTB05, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04OTB06, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04OTB07, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04OTB08, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04OTB09, Year: 2004, Value: 0.01 mg/kg\",\"StationNumber: 04TCB07, Year: 2004, Value: 1.789 mg/kg\",\"StationNumber: 05BCB01, Year: 2005, Value: 0.505 mg/kg\",\"StationNumber: 05BCB02, Year: 2005, Value: 0.245 mg/kg\",\"StationNumber: 05BCB03, Year: 2005, Value: 0.638 mg/kg\",\"StationNumber: 05BCB04, Year: 2005, Value: 0.791 mg/kg\",\"StationNumber: 05BCB05, Year: 2005, Value: 6.022 mg/kg\",\"StationNumber: 05BCB06, Year: 2005, Value: 2.432 mg/kg\",\"StationNumber: 05BCB07, Year: 2005, Value: 0.357 mg/kg\",\"StationNumber: 05BCB08, Year: 2005, Value: 1.489 mg/kg\",\"StationNumber: 05BCB09, Year: 2005, Value: 0.987 mg/kg\",\"StationNumber: 05BCB10, Year: 2005, Value: 0.021 mg/kg\",\"StationNumber: 05HB01, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05HB02, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05HB03, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05HB04, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05HB05, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05HB06, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05HB07, Year: 2005, Value: 0.733 mg/kg\",\"StationNumber: 05HB08, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05HB09, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05HB10, Year: 2005, Value: 0.598 mg/kg\",\"StationNumber: 05HB11, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05HB12, Year: 2005, Value: 3.811 mg/kg\",\"StationNumber: 05HB13, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05HB14, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05HB15, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05HB16, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05HB17, Year: 2005, Value: 0.036 mg/kg\",\"StationNumber: 05HB18, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05HB19, Year: 2005, Value: 0.322 mg/kg\",\"StationNumber: 05HB20, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05HB21, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05HB22, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05HB23, Year: 2005, Value: 0.616 mg/kg\",\"StationNumber: 05HB24, Year: 2005, Value: 2.172 mg/kg\",\"StationNumber: 05LTB01, Year: 2005, Value: 5.537 mg/kg\",\"StationNumber: 05LTB02, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05LTB03, Year: 2005, Value: 2.554 mg/kg\",\"StationNumber: 05LTB04, Year: 2005, Value: 2.548 mg/kg\",\"StationNumber: 05LTB05, Year: 2005, Value: 1.008 mg/kg\",\"StationNumber: 05LTB06, Year: 2005, Value: 2.134 mg/kg\",\"StationNumber: 05LTB07, Year: 2005, Value: 3.24 mg/kg\",\"StationNumber: 05LTB08, Year: 2005, Value: 2.144 mg/kg\",\"StationNumber: 05LTB09, Year: 2005, Value: 4.455 mg/kg\",\"StationNumber: 05LTB10, Year: 2005, Value: 0.116 mg/kg\",\"StationNumber: 05LTB11, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05MR02, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05MR04, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05MR06, Year: 2005, Value: 1.085 mg/kg\",\"StationNumber: 05MR08, Year: 2005, Value: 0.372 mg/kg\",\"StationNumber: 05MR09, Year: 2005, Value: 0.97 mg/kg\",\"StationNumber: 05MR11, Year: 2005, Value: 0.271 mg/kg\",\"StationNumber: 05MTB01, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05MTB02, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05MTB03, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05MTB04, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05MTB05, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05MTB06, Year: 2005, Value: 0.691 mg/kg\",\"StationNumber: 05MTB07, Year: 2005, Value: 0.685 mg/kg\",\"StationNumber: 05MTB08, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05MTB09, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05MTB10, Year: 2005, Value: 0.871 mg/kg\",\"StationNumber: 05MTB11, Year: 2005, Value: 0.609 mg/kg\",\"StationNumber: 05MTB12, Year: 2005, Value: 0.585 mg/kg\",\"StationNumber: 05MTB13, Year: 2005, Value: 1.943 mg/kg\",\"StationNumber: 05MTB14, Year: 2005, Value: 8.527 mg/kg\",\"StationNumber: 05MTB15, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05MTB16, Year: 2005, Value: 0.45 mg/kg\",\"StationNumber: 05MTB17, Year: 2005, Value: 0.043 mg/kg\",\"StationNumber: 05MTB18, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05MTB19, Year: 2005, Value: 0.177 mg/kg\",\"StationNumber: 05MTB20, Year: 2005, Value: 2.689 mg/kg\",\"StationNumber: 05MTB21, Year: 2005, Value: 0.156 mg/kg\",\"StationNumber: 05MTB22, Year: 2005, Value: 0.31 mg/kg\",\"StationNumber: 05OTB01, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05OTB02, Year: 2005, Value: 0.308 mg/kg\",\"StationNumber: 05OTB03, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05OTB04, Year: 2005, Value: 0.154 mg/kg\",\"StationNumber: 05OTB05, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05OTB06, Year: 2005, Value: 0.727 mg/kg\",\"StationNumber: 05OTB07, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05OTB08, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05OTB09, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05OTB10, Year: 2005, Value: 0.348 mg/kg\",\"StationNumber: 05TCB01, Year: 2005, Value: 0.01 mg/kg\",\"StationNumber: 05TCB03, Year: 2005, Value: 1.689 mg/kg\",\"StationNumber: 05TCB05, Year: 2005, Value: 1.313 mg/kg\",\"StationNumber: 05TCB07, Year: 2005, Value: 0.98 mg/kg\",\"StationNumber: 05TCB10, Year: 2005, Value: 2.404 mg/kg\",\"StationNumber: 06BCB01, Year: 2006, Value: 10.76 mg/kg\",\"StationNumber: 06BCB02, Year: 2006, Value: 7.6 mg/kg\",\"StationNumber: 06BCB03, Year: 2006, Value: 6.966 mg/kg\",\"StationNumber: 06BCB04, Year: 2006, Value: 6.49 mg/kg\",\"StationNumber: 06BCB05, Year: 2006, Value: 1.041 mg/kg\",\"StationNumber: 06BCB06, Year: 2006, Value: 5.932 mg/kg\",\"StationNumber: 06BCB07, Year: 2006, Value: 0.01 mg/kg\",\"StationNumber: 06BCB08, Year: 2006, Value: 2.144 mg/kg\",\"StationNumber: 06BCB09, Year: 2006, Value: 6.173 mg/kg\",\"StationNumber: 06HB01, Year: 2006, Value: 0.768 mg/kg\",\"StationNumber: 06HB02, Year: 2006, Value: 6.388 mg/kg\",\"StationNumber: 06HB03, Year: 2006, Value: 0.01 mg/kg\",\"StationNumber: 06HB04, Year: 2006, Value: 5.29 mg/kg\",\"StationNumber: 06HB05, Year: 2006, Value: 0.01 mg/kg\",\"StationNumber: 06HB06, Year: 2006, Value: 8.423 mg/kg\",\"StationNumber: 06HB08, Year: 2006, Value: 4.515 mg/kg\",\"StationNumber: 06HB09, Year: 2006, Value: 0.01 mg/kg\",\"StationNumber: 06HB10, Year: 2006, Value: 9.296 mg/kg\",\"StationNumber: 06HB11, Year: 2006, Value: 9.144 mg/kg\",\"StationNumber: 06HB12, Year: 2006, Value: 1.668 mg/kg\",\"StationNumber: 06HB13, Year: 2006, Value: 0.01 mg/kg\",\"StationNumber: 06HB14, Year: 2006, Value: 0.01 mg/kg\",\"StationNumber: 06HB15, Year: 2006, Value: 3.641 mg/kg\",\"StationNumber: 06HB16, Year: 2006, Value: 3.091 mg/kg\",\"StationNumber: 06HB17, Year: 2006, Value: 0.01 mg/kg\",\"StationNumber: 06HB18, Year: 2006, Value: 0.01 mg/kg\",\"StationNumber: 06HB19, Year: 2006, Value: 0.01 mg/kg\",\"StationNumber: 06HB20, Year: 2006, Value: 0.01 mg/kg\",\"StationNumber: 06HB21, Year: 2006, Value: 0.01 mg/kg\",\"StationNumber: 06HB22, Year: 2006, Value: 0.958 mg/kg\",\"StationNumber: 06HB23, Year: 2006, Value: 0.01 mg/kg\",\"StationNumber: 06HB24, Year: 2006, Value: 0.867 mg/kg\",\"StationNumber: 06HB25, Year: 2006, Value: 3.199 mg/kg\",\"StationNumber: 06LTB01, Year: 2006, Value: 5.442 mg/kg\",\"StationNumber: 06LTB02, Year: 2006, Value: 6.614 mg/kg\",\"StationNumber: 06LTB03, Year: 2006, Value: 13.302 mg/kg\",\"StationNumber: 06LTB04, Year: 2006, Value: 9.592 mg/kg\",\"StationNumber: 06LTB05, Year: 2006, Value: 6.313 mg/kg\",\"StationNumber: 06LTB06, Year: 2006, Value: 8.886 mg/kg\",\"StationNumber: 06LTB07, Year: 2006, Value: 7.536 mg/kg\",\"StationNumber: 06LTB08, Year: 2006, Value: 6.973 mg/kg\",\"StationNumber: 06MR05, Year: 2006, Value: 0.01 mg/kg\",\"StationNumber: 06MR06, Year: 2006, Value: 6.076 mg/kg\",\"StationNumber: 06MR07, Year: 2006, Value: 1.121 mg/kg\",\"StationNumber: 06MR08, Year: 2006, Value: 6.41 mg/kg\",\"StationNumber: 06MR10, Year: 2006, Value: 0.01 mg/kg\",\"StationNumber: 06MTB01, Year: 2006, Value: 21.691 mg/kg\",\"StationNumber: 06MTB02, Year: 2006, Value: 7.887 mg/kg\",\"StationNumber: 06MTB03, Year: 2006, Value: 0.01 mg/kg\",\"StationNumber: 06MTB04, Year: 2006, Value: 5.141 mg/kg\",\"StationNumber: 06MTB05, Year: 2006, Value: 6.599 mg/kg\",\"StationNumber: 06MTB06, Year: 2006, Value: 0.01 mg/kg\",\"StationNumber: 06MTB07, Year: 2006, Value: 8.465 mg/kg\",\"StationNumber: 06MTB08, Year: 2006, Value: 7.305 mg/kg\",\"StationNumber: 06MTB09, Year: 2006, Value: 9.749 mg/kg\",\"StationNumber: 06MTB10, Year: 2006, Value: 7.082 mg/kg\",\"StationNumber: 06MTB11, Year: 2006, Value: 4.9 mg/kg\",\"StationNumber: 06MTB12, Year: 2006, Value: 5.42 mg/kg\",\"StationNumber: 06MTB13, Year: 2006, Value: 2.843 mg/kg\",\"StationNumber: 06MTB14, Year: 2006, Value: 6.476 mg/kg\",\"StationNumber: 06MTB15, Year: 2006, Value: 6.64 mg/kg\",\"StationNumber: 06MTB16, Year: 2006, Value: 5.146 mg/kg\",\"StationNumber: 06MTB17, Year: 2006, Value: 8.46 mg/kg\",\"StationNumber: 06MTB18, Year: 2006, Value: 1.724 mg/kg\",\"StationNumber: 06MTB19, Year: 2006, Value: 5.701 mg/kg\",\"StationNumber: 06OTB01, Year: 2006, Value: 5.045 mg/kg\",\"StationNumber: 06OTB02, Year: 2006, Value: 6.294 mg/kg\",\"StationNumber: 06OTB03, Year: 2006, Value: 5.32 mg/kg\",\"StationNumber: 06OTB04, Year: 2006, Value: 5.697 mg/kg\",\"StationNumber: 06OTB05, Year: 2006, Value: 2.581 mg/kg\",\"StationNumber: 06OTB06, Year: 2006, Value: 0.01 mg/kg\",\"StationNumber: 06OTB07, Year: 2006, Value: 2.085 mg/kg\",\"StationNumber: 06OTB08, Year: 2006, Value: 5.097 mg/kg\",\"StationNumber: 06TCB01, Year: 2006, Value: 0.01 mg/kg\",\"StationNumber: 06TCB02, Year: 2006, Value: 0.01 mg/kg\",\"StationNumber: 06TCB03, Year: 2006, Value: 0.01 mg/kg\",\"StationNumber: 06TCB04, Year: 2006, Value: 0.01 mg/kg\",\"StationNumber: 06TCB09, Year: 2006, Value: 0.189 mg/kg\",\"StationNumber: 07BCB06, Year: 2007, Value: 0.01 mg/kg\",\"StationNumber: 07BCB09, Year: 2007, Value: 0.01 mg/kg\",\"StationNumber: 07BCB15, Year: 2007, Value: 7.27 mg/kg\",\"StationNumber: 07BCB28, Year: 2007, Value: 6.46 mg/kg\",\"StationNumber: 07BCB29, Year: 2007, Value: 0.61 mg/kg\",\"StationNumber: 07BCB30, Year: 2007, Value: 9.62 mg/kg\",\"StationNumber: 07BCB41, Year: 2007, Value: 6.85 mg/kg\",\"StationNumber: 07BCB42, Year: 2007, Value: 11.82 mg/kg\",\"StationNumber: 07BCB44, Year: 2007, Value: 7.13 mg/kg\",\"StationNumber: 07BCB45, Year: 2007, Value: 8.32 mg/kg\",\"StationNumber: 07HB13, Year: 2007, Value: 0.01 mg/kg\",\"StationNumber: 07HB21, Year: 2007, Value: 0.01 mg/kg\",\"StationNumber: 07HB34, Year: 2007, Value: 0.01 mg/kg\",\"StationNumber: 07HB37, Year: 2007, Value: 0.01 mg/kg\",\"StationNumber: 07HB38, Year: 2007, Value: 0.01 mg/kg\",\"StationNumber: 07HB41, Year: 2007, Value: 0.01 mg/kg\",\"StationNumber: 07HB42, Year: 2007, Value: 0.01 mg/kg\",\"StationNumber: 07HB44, Year: 2007, Value: 0.01 mg/kg\",\"StationNumber: 07HB53, Year: 2007, Value: 0.01 mg/kg\",\"StationNumber: 07LTB91, Year: 2007, Value: 0.01 mg/kg\",\"StationNumber: 07MR09, Year: 2007, Value: 0.11 mg/kg\",\"StationNumber: 07MR28, Year: 2007, Value: 0.01 mg/kg\",\"StationNumber: 07MR42, Year: 2007, Value: 0.01 mg/kg\",\"StationNumber: 07MR46, Year: 2007, Value: 0.01 mg/kg\",\"StationNumber: 07MR50, Year: 2007, Value: 0.01 mg/kg\",\"StationNumber: 07MTB34, Year: 2007, Value: 9.44 mg/kg\",\"StationNumber: 07MTB39, Year: 2007, Value: 4.6 mg/kg\",\"StationNumber: 07MTB40, Year: 2007, Value: 0.01 mg/kg\",\"StationNumber: 07MTB43, Year: 2007, Value: 0.51 mg/kg\",\"StationNumber: 07MTB44, Year: 2007, Value: 0.01 mg/kg\",\"StationNumber: 07MTB47, Year: 2007, Value: 10.84 mg/kg\",\"StationNumber: 07MTB54, Year: 2007, Value: 13.61 mg/kg\",\"StationNumber: 07OTB04, Year: 2007, Value: 0.01 mg/kg\",\"StationNumber: 07OTB08, Year: 2007, Value: 7.25 mg/kg\",\"StationNumber: 07OTB18, Year: 2007, Value: 0.01 mg/kg\",\"StationNumber: 07OTB21, Year: 2007, Value: 2.99 mg/kg\",\"StationNumber: 07OTB24, Year: 2007, Value: 3.72 mg/kg\",\"StationNumber: 07OTB25, Year: 2007, Value: 7.21 mg/kg\",\"StationNumber: 07OTB31, Year: 2007, Value: 10.48 mg/kg\",\"StationNumber: 07TCB14, Year: 2007, Value: 0.01 mg/kg\",\"StationNumber: 07TCB15, Year: 2007, Value: 0.01 mg/kg\",\"StationNumber: 07TCB20, Year: 2007, Value: 8.27 mg/kg\",\"StationNumber: 07TCB22, Year: 2007, Value: 1.55 mg/kg\",\"StationNumber: 08BCB02, Year: 2008, Value: 2.25 mg/kg\",\"StationNumber: 08BCB05, Year: 2008, Value: 0.01 mg/kg\",\"StationNumber: 08BCB12, Year: 2008, Value: 0.01 mg/kg\",\"StationNumber: 08BCB15, Year: 2008, Value: 0.01 mg/kg\",\"StationNumber: 08BCB16, Year: 2008, Value: 4.4 mg/kg\",\"StationNumber: 08BCB17, Year: 2008, Value: 3.34 mg/kg\",\"StationNumber: 08BCB23, Year: 2008, Value: 0.01 mg/kg\",\"StationNumber: 08BCB26, Year: 2008, Value: 9.9 mg/kg\",\"StationNumber: 08BCB29, Year: 2008, Value: 7.8 mg/kg\",\"StationNumber: 08BCB35, Year: 2008, Value: 7.83 mg/kg\",\"StationNumber: 08BCB38, Year: 2008, Value: 6.95 mg/kg\",\"StationNumber: 08HB13, Year: 2008, Value: 0.01 mg/kg\",\"StationNumber: 08HB14, Year: 2008, Value: 0.01 mg/kg\",\"StationNumber: 08HB17, Year: 2008, Value: 0.01 mg/kg\",\"StationNumber: 08HB21, Year: 2008, Value: 0.01 mg/kg\",\"StationNumber: 08HB27, Year: 2008, Value: 0.01 mg/kg\",\"StationNumber: 08HB34, Year: 2008, Value: 4.62 mg/kg\",\"StationNumber: 08HB43, Year: 2008, Value: 4.15 mg/kg\",\"StationNumber: 08HB44, Year: 2008, Value: 6.35 mg/kg\",\"StationNumber: 08HB48, Year: 2008, Value: 7.51 mg/kg\",\"StationNumber: 08LTB69, Year: 2008, Value: 9.07 mg/kg\",\"StationNumber: 08LTB79, Year: 2008, Value: 22.19 mg/kg\",\"StationNumber: 08LTB82, Year: 2008, Value: 9.06 mg/kg\",\"StationNumber: 08MR08, Year: 2008, Value: 11.03 mg/kg\",\"StationNumber: 08MR35, Year: 2008, Value: 6.78 mg/kg\",\"StationNumber: 08MR40, Year: 2008, Value: 2.73 mg/kg\",\"StationNumber: 08MR43, Year: 2008, Value: 0.01 mg/kg\",\"StationNumber: 08MR53, Year: 2008, Value: 4.18 mg/kg\",\"StationNumber: 08MR54, Year: 2008, Value: 5.54 mg/kg\",\"StationNumber: 08MTB37, Year: 2008, Value: 6.6 mg/kg\",\"StationNumber: 08MTB47, Year: 2008, Value: 8.06 mg/kg\",\"StationNumber: 08MTB53, Year: 2008, Value: 0 mg/kg\",\"StationNumber: 08MTB62, Year: 2008, Value: 11.22 mg/kg\",\"StationNumber: 08MTB73, Year: 2008, Value: 4.04 mg/kg\",\"StationNumber: 08OTB05, Year: 2008, Value: 0.01 mg/kg\",\"StationNumber: 08OTB07, Year: 2008, Value: 0.46 mg/kg\",\"StationNumber: 08OTB13, Year: 2008, Value: 6.98 mg/kg\",\"StationNumber: 08OTB15, Year: 2008, Value: 3.77 mg/kg\",\"StationNumber: 08OTB17, Year: 2008, Value: 8.33 mg/kg\",\"StationNumber: 08OTB23, Year: 2008, Value: 11.18 mg/kg\",\"StationNumber: 08OTB27, Year: 2008, Value: 9.44 mg/kg\",\"StationNumber: 08TCB01, Year: 2008, Value: 1.91 mg/kg\",\"StationNumber: 08TCB07, Year: 2008, Value: 0.01 mg/kg\",\"StationNumber: 08TCB26, Year: 2008, Value: 0.07 mg/kg\",\"StationNumber: 10BCB06, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10BCB11, Year: 2010, Value: 5.82 mg/kg\",\"StationNumber: 10BCB17, Year: 2010, Value: 5.65 mg/kg\",\"StationNumber: 10BCB25, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10BCB28, Year: 2010, Value: 7.31 mg/kg\",\"StationNumber: 10BCB30, Year: 2010, Value: 8.9 mg/kg\",\"StationNumber: 10BCB37, Year: 2010, Value: 5.2 mg/kg\",\"StationNumber: 10BCB41, Year: 2010, Value: 4.55 mg/kg\",\"StationNumber: 10BCB46, Year: 2010, Value: 5.05 mg/kg\",\"StationNumber: 10BCB47, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10BCB49, Year: 2010, Value: 6.65 mg/kg\",\"StationNumber: 10HB21, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10HB22, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10HB25, Year: 2010, Value: 10.85 mg/kg\",\"StationNumber: 10HB26, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10HB34, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10HB44, Year: 2010, Value: 6.34 mg/kg\",\"StationNumber: 10HB46, Year: 2010, Value: 5.15 mg/kg\",\"StationNumber: 10HB48, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10HB54, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10LTB71, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10LTB76, Year: 2010, Value: 4.59 mg/kg\",\"StationNumber: 10LTB89, Year: 2010, Value: 9.22 mg/kg\",\"StationNumber: 10MR25, Year: 2010, Value: 7.48 mg/kg\",\"StationNumber: 10MR29, Year: 2010, Value: 9.82 mg/kg\",\"StationNumber: 10MR33, Year: 2010, Value: 4.36 mg/kg\",\"StationNumber: 10MR40, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10MR44, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10MTB30, Year: 2010, Value: 9.2 mg/kg\",\"StationNumber: 10MTB35, Year: 2010, Value: 5.93 mg/kg\",\"StationNumber: 10MTB43, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10MTB53, Year: 2010, Value: 9.06 mg/kg\",\"StationNumber: 10MTB56, Year: 2010, Value: 9.26 mg/kg\",\"StationNumber: 10OTB04, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10OTB05, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10OTB07, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10OTB08, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10OTB09, Year: 2010, Value: 4.65 mg/kg\",\"StationNumber: 10OTB12, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10OTB13, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10OTB14, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10OTB15, Year: 2010, Value: 9.77 mg/kg\",\"StationNumber: 10OTB16, Year: 2010, Value: 9.77 mg/kg\",\"StationNumber: 10OTB18, Year: 2010, Value: 8.82 mg/kg\",\"StationNumber: 10OTB19, Year: 2010, Value: 4.94 mg/kg\",\"StationNumber: 10OTB20, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10OTB21, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10OTB24, Year: 2010, Value: 6.72 mg/kg\",\"StationNumber: 10OTB25, Year: 2010, Value: 7.91 mg/kg\",\"StationNumber: 10OTB26, Year: 2010, Value: 8.22 mg/kg\",\"StationNumber: 10OTB28, Year: 2010, Value: 10.09 mg/kg\",\"StationNumber: 10OTB29, Year: 2010, Value: 9.46 mg/kg\",\"StationNumber: 10OTB96, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10OTB97, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10OTB98, Year: 2010, Value: 9.71 mg/kg\",\"StationNumber: 10TCB01, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10TCB11, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10TCB13, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 10TCB20, Year: 2010, Value: 2.02 mg/kg\",\"StationNumber: 11BCB05, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11BCB09, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11BCB12, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11BCB20, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11BCB22, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11BCB26, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11BCB35, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11BCB42, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11BCB43, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11BCB44, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11BCB48, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11HB09, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11HB13, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11HB29, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11HB31, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11HB35, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11HB36, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11HB38, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11HB40, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11HB47, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11LTB69, Year: 2011, Value: 4.07 mg/kg\",\"StationNumber: 11LTB75, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11LTB80, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11MR18, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11MR32, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11MR35, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11MR37, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11MR43, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11MR45, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11MR52, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11MTB39, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11MTB44, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11MTB46, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11MTB54, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11MTB72, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11OTB08, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11OTB09, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11OTB18, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11OTB24, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11OTB26, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11OTB31, Year: 2011, Value: 4.24 mg/kg\",\"StationNumber: 11OTB32, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11TCB10, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 11TCB12, Year: 2011, Value: 2.02 mg/kg\",\"StationNumber: 12BCB06, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12BCB14, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12BCB19, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12BCB23, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12BCB25, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12BCB27, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12BCB35, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12BCB40, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12BCB44, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12BCB46, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12BCB49, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12HB27, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12HB28, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12HB31, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12HB32, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12HB38, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12HB40, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12HB45, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12HB53, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12HB54, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12LTB78, Year: 2012, Value: 10.58 mg/kg\",\"StationNumber: 12LTB84, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12LTB93, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12MR08, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12MR17, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12MR33, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12MR36, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12MR43, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12MR46, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12MR54, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12MTB47, Year: 2012, Value: 4.25 mg/kg\",\"StationNumber: 12MTB53, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12MTB58, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12MTB63, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12MTB64, Year: 2012, Value: 4.45 mg/kg\",\"StationNumber: 12OTB04, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12OTB08, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12OTB13, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12OTB14, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12OTB18, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12OTB19, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12OTB20, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12TCB05, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 12TCB13, Year: 2012, Value: 2.02 mg/kg\",\"StationNumber: 13BCB05, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13BCB07, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13BCB09, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13BCB10, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13BCB11, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13BCB17, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13BCB22, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13BCB30, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13BCB41, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13BCB43, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13BCB48, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13HB09, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13HB13, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13HB25, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13HB26, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13HB35, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13HB36, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13HB41, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13HB44, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13HB48, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13LTB79, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13LTB82, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13LTB86, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13MR09, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13MR24, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13MR31, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13MR44, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13MR45, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13MR48, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13MTB34, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13MTB35, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13MTB41, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13MTB45, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13MTB55, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13OTB12, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13OTB15, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13OTB16, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13OTB21, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13OTB27, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13OTB28, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13OTB29, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13TCB01, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13TCB11, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 13TCB14, Year: 2013, Value: 2.785 mg/kg\",\"StationNumber: 14BCB03, Year: 2014, Value: 2.785 mg/kg\",\"StationNumber: 14BCB12, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14BCB15, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14BCB17, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14BCB20, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14BCB25, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14BCB29, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14BCB33, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14BCB35, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14BCB41, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14BCB47, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14HB20, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14HB21, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14HB26, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14HB33, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14HB43, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14HB44, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14HB46, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14HB47, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14HB54, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14LTB71, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14LTB81, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14LTB90, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14MR29, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14MR35, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14MR37, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14MR38, Year: 2014, Value: 2.785 mg/kg\",\"StationNumber: 14MR47, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14MTB39, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14MTB41, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14MTB46, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14MTB54, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14MTB63, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14OTB04, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14OTB08, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14OTB14, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14OTB18, Year: 2014, Value: 463.9 mg/kg\",\"StationNumber: 14OTB19, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14OTB21, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14OTB25, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14TCB15, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14TCB20, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14TCB21, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 14TCB22, Year: 2014, Value: 2.02 mg/kg\",\"StationNumber: 15BCB09, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15BCB12, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15BCB15, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15BCB26, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15BCB30, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15BCB31, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15BCB34, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15BCB39, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15BCB43, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15BCB47, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15BCB48, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15HB09, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15HB14, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15HB27, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15HB36, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15HB37, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15HB39, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15HB40, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15HB41, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15HB48, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15LTB70, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15LTB76, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15LTB94, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15MR08, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15MR28, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15MR30, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15MR33, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15MR42, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15MR52, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15MTB40, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15MTB49, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15MTB52, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15MTB55, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15MTB62, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15OTB12, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15OTB15, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15OTB20, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15OTB24, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15OTB26, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15OTB28, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15OTB29, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15TCB01, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15TCB11, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 15TCB12, Year: 2015, Value: 5.8 mg/kg\",\"StationNumber: 16BCB20, Year: 2016, Value: 3.32 mg/kg\",\"StationNumber: 16BCB22, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16BCB25, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16BCB29, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16BCB34, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16BCB35, Year: 2016, Value: 3.05 mg/kg\",\"StationNumber: 16BCB36, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16BCB37, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16BCB41, Year: 2016, Value: 2.42 mg/kg\",\"StationNumber: 16BCB42, Year: 2016, Value: 1.18 mg/kg\",\"StationNumber: 16BCB43, Year: 2016, Value: 3.21 mg/kg\",\"StationNumber: 16DH01-1, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH01-2, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH01-3, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH01-4, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH02-1, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH02-2, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH02-3, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH02-4, Year: 2016, Value: 3.25 mg/kg\",\"StationNumber: 16DH03-1, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH03-2, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH03-3, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH03-4, Year: 2016, Value: 0.76 mg/kg\",\"StationNumber: 16DH04-1, Year: 2016, Value: 2.53 mg/kg\",\"StationNumber: 16DH04-2, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH04-3, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH04-4, Year: 2016, Value: 3.5 mg/kg\",\"StationNumber: 16DH05-1, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH05-2, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH05-3, Year: 2016, Value: 1.87 mg/kg\",\"StationNumber: 16DH05-4, Year: 2016, Value: 2.91 mg/kg\",\"StationNumber: 16DH06-1, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH06-2, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH06-3, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH06-4, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH07-1, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH07-2, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH07-3, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH07-4, Year: 2016, Value: 1.85 mg/kg\",\"StationNumber: 16DH08-1, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH08-2, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH08-3, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH08-4, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH09-1, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH09-2, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH09-3, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH09-4, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH10-1, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16DH10-2, Year: 2016, Value: 2.25 mg/kg\",\"StationNumber: 16DH10-3, Year: 2016, Value: 1.16 mg/kg\",\"StationNumber: 16DH10-4, Year: 2016, Value: 3.43 mg/kg\",\"StationNumber: 16HB19, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16HB20, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16HB21, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16HB27, Year: 2016, Value: 2.44 mg/kg\",\"StationNumber: 16HB28, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16HB32, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16HB33, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16HB37, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16HB48, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16LTB71, Year: 2016, Value: 3.21 mg/kg\",\"StationNumber: 16LTB79, Year: 2016, Value: 8.12 mg/kg\",\"StationNumber: 16LTB85, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16MR17, Year: 2016, Value: 2.41 mg/kg\",\"StationNumber: 16MR25, Year: 2016, Value: 1.84 mg/kg\",\"StationNumber: 16MR29, Year: 2016, Value: 0.62 mg/kg\",\"StationNumber: 16MR33, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16MR43, Year: 2016, Value: 2.1 mg/kg\",\"StationNumber: 16MR44, Year: 2016, Value: 0.09 mg/kg\",\"StationNumber: 16MR45, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16MTB41, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16MTB47, Year: 2016, Value: 3.95 mg/kg\",\"StationNumber: 16MTB48, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16MTB53, Year: 2016, Value: 4.34 mg/kg\",\"StationNumber: 16MTB72, Year: 2016, Value: 1.69 mg/kg\",\"StationNumber: 16OTB08, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16OTB09, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16OTB13, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16OTB14, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16OTB18, Year: 2016, Value: 1.78 mg/kg\",\"StationNumber: 16OTB22, Year: 2016, Value: 3.79 mg/kg\",\"StationNumber: 16OTB25, Year: 2016, Value: 1.02 mg/kg\",\"StationNumber: 16TCB14, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 16TCB20, Year: 2016, Value: 0.01 mg/kg\",\"StationNumber: 17BCB15, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17BCB26, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17BCB27, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17BCB30, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17BCB35, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17BCB36, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17BCB40, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17BCB42, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17BCB43, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17BCB44, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17BCB48, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17BCB48, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17HB10, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17HB13, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17HB15, Year: 2017, Value: 8.39 mg/kg\",\"StationNumber: 17HB26, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17HB34, Year: 2017, Value: 524.32 mg/kg\",\"StationNumber: 17HB36, Year: 2017, Value: 8.91 mg/kg\",\"StationNumber: 17HB41, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17HB42, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17HB43, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17LTB70, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17LTB83, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17LTB89, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17MR09, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17MR18, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17MR24, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17MR32, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17MR35, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17MR37, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17MTB34, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17MTB35, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17MTB46, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17MTB55, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17MTB63, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17OTB04, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17OTB07, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17OTB12, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17OTB19, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17OTB21, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17OTB28, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17OTB32, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17TCB12, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17TCB13, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17TCB21, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17TCP01, Year: 2017, Value: 20.64 mg/kg\",\"StationNumber: 17TCP02, Year: 2017, Value: 17.43 mg/kg\",\"StationNumber: 17TCP03, Year: 2017, Value: 15.42 mg/kg\",\"StationNumber: 17TCP04, Year: 2017, Value: 14.89 mg/kg\",\"StationNumber: 17TCP05, Year: 2017, Value: 9.77 mg/kg\",\"StationNumber: 17TCP06, Year: 2017, Value: 27.33 mg/kg\",\"StationNumber: 17TCP07, Year: 2017, Value: 11.7 mg/kg\",\"StationNumber: 17TCP08, Year: 2017, Value: 3.675 mg/kg\",\"StationNumber: 17TCP09, Year: 2017, Value: 8.06 mg/kg\",\"StationNumber: 17TCP10, Year: 2017, Value: 8.39 mg/kg\",\"StationNumber: 18BCB11, Year: 2018, Value: 24.7 mg/kg\",\"StationNumber: 18BCB15, Year: 2018, Value: 1.51 mg/kg\",\"StationNumber: 18BCB19, Year: 2018, Value: 0.01 mg/kg\",\"StationNumber: 18BCB20, Year: 2018, Value: 1.19 mg/kg\",\"StationNumber: 18BCB22, Year: 2018, Value: 1.43 mg/kg\",\"StationNumber: 18BCB24, Year: 2018, Value: 0.01 mg/kg\",\"StationNumber: 18BCB26, Year: 2018, Value: 1.76 mg/kg\",\"StationNumber: 18BCB37, Year: 2018, Value: 0.01 mg/kg\",\"StationNumber: 18BCB42, Year: 2018, Value: 0.01 mg/kg\",\"StationNumber: 18BCB44, Year: 2018, Value: 0.01 mg/kg\",\"StationNumber: 18BCB46, Year: 2018, Value: 0.01 mg/kg\",\"StationNumber: 18HB14, Year: 2018, Value: 2.7 mg/kg\",\"StationNumber: 18HB20, Year: 2018, Value: 4.74 mg/kg\",\"StationNumber: 18HB21, Year: 2018, Value: 1.96 mg/kg\",\"StationNumber: 18HB26, Year: 2018, Value: 2.48 mg/kg\",\"StationNumber: 18HB29, Year: 2018, Value: 1.98 mg/kg\",\"StationNumber: 18HB33, Year: 2018, Value: 3.56 mg/kg\",\"StationNumber: 18HB38, Year: 2018, Value: 3.23 mg/kg\",\"StationNumber: 18HB41, Year: 2018, Value: 1.26 mg/kg\",\"StationNumber: 18HB46, Year: 2018, Value: 1.05 mg/kg\",\"StationNumber: 18LTB75, Year: 2018, Value: 0.01 mg/kg\",\"StationNumber: 18LTB79, Year: 2018, Value: 14.24 mg/kg\",\"StationNumber: 18LTB81, Year: 2018, Value: 0.01 mg/kg\",\"StationNumber: 18LTB82, Year: 2018, Value: 0.1 mg/kg\",\"StationNumber: 18MR25, Year: 2018, Value: 7.31 mg/kg\",\"StationNumber: 18MR37, Year: 2018, Value: 0.78 mg/kg\",\"StationNumber: 18MR46, Year: 2018, Value: 0.07 mg/kg\",\"StationNumber: 18MTB41, Year: 2018, Value: 1.08 mg/kg\",\"StationNumber: 18MTB42, Year: 2018, Value: 2.2 mg/kg\",\"StationNumber: 18MTB48, Year: 2018, Value: 1.01 mg/kg\",\"StationNumber: 18MTB56, Year: 2018, Value: 1.63 mg/kg\",\"StationNumber: 18OTB04, Year: 2018, Value: 0.01 mg/kg\",\"StationNumber: 18OTB08, Year: 2018, Value: 0.01 mg/kg\",\"StationNumber: 18OTB13, Year: 2018, Value: 0.01 mg/kg\",\"StationNumber: 18OTB14, Year: 2018, Value: 0.01 mg/kg\",\"StationNumber: 18OTB15, Year: 2018, Value: 0.01 mg/kg\",\"StationNumber: 18OTB21, Year: 2018, Value: 0.01 mg/kg\",\"StationNumber: 18OTB24, Year: 2018, Value: 0.01 mg/kg\",\"StationNumber: 18TCB05, Year: 2018, Value: 9.11 mg/kg\",\"StationNumber: 18TCB11, Year: 2018, Value: 6.79 mg/kg\",\"StationNumber: 18TCB14, Year: 2018, Value: 5.34 mg/kg\",\"StationNumber: 18TCB15, Year: 2018, Value: 6.28 mg/kg\",\"StationNumber: 18TCB21, Year: 2018, Value: 15.39 mg/kg\",\"StationNumber: 18TCB22, Year: 2018, Value: 5.61 mg/kg\",\"StationNumber: 19BCB27, Year: 2019, Value: 5.22 mg/kg\",\"StationNumber: 19BCB29, Year: 2019, Value: 5.87 mg/kg\",\"StationNumber: 19BCB30, Year: 2019, Value: 12.82 mg/kg\",\"StationNumber: 19BCB34, Year: 2019, Value: 0.26 mg/kg\",\"StationNumber: 19BCB35, Year: 2019, Value: 5.29 mg/kg\",\"StationNumber: 19BCB36, Year: 2019, Value: 0.01 mg/kg\",\"StationNumber: 19BCB40, Year: 2019, Value: 0.86 mg/kg\",\"StationNumber: 19BCB41, Year: 2019, Value: 0.61 mg/kg\",\"StationNumber: 19BCB43, Year: 2019, Value: 0.3 mg/kg\",\"StationNumber: 19BCB49, Year: 2019, Value: 1.28 mg/kg\",\"StationNumber: 19BCB50, Year: 2019, Value: 0.01 mg/kg\",\"StationNumber: 19HB09, Year: 2019, Value: 0.5 mg/kg\",\"StationNumber: 19HB16, Year: 2019, Value: 15.28 mg/kg\",\"StationNumber: 19HB25, Year: 2019, Value: 0.59 mg/kg\",\"StationNumber: 19HB27, Year: 2019, Value: 3.02 mg/kg\",\"StationNumber: 19HB32, Year: 2019, Value: 3.82 mg/kg\",\"StationNumber: 19HB37, Year: 2019, Value: 3.57 mg/kg\",\"StationNumber: 19HB39, Year: 2019, Value: 0.66 mg/kg\",\"StationNumber: 19HB40, Year: 2019, Value: 1.14 mg/kg\",\"StationNumber: 19HB47, Year: 2019, Value: 0.06 mg/kg\",\"StationNumber: 19LTB76, Year: 2019, Value: 1.06 mg/kg\",\"StationNumber: 19LTB78, Year: 2019, Value: 0.74 mg/kg\",\"StationNumber: 19LTB88, Year: 2019, Value: 6.12 mg/kg\",\"StationNumber: 19LTB90, Year: 2019, Value: 0.55 mg/kg\",\"StationNumber: 19MR17, Year: 2019, Value: 1.46 mg/kg\",\"StationNumber: 19MR18, Year: 2019, Value: 1.44 mg/kg\",\"StationNumber: 19MR29, Year: 2019, Value: 2.28 mg/kg\",\"StationNumber: 19MR33, Year: 2019, Value: 0.66 mg/kg\",\"StationNumber: 19MR43, Year: 2019, Value: 5.07 mg/kg\",\"StationNumber: 19MR44, Year: 2019, Value: 6.22 mg/kg\",\"StationNumber: 19MR52, Year: 2019, Value: 1.98 mg/kg\",\"StationNumber: 19MTB36, Year: 2019, Value: 2.26 mg/kg\",\"StationNumber: 19MTB47, Year: 2019, Value: 0.31 mg/kg\",\"StationNumber: 19MTB54, Year: 2019, Value: 1.61 mg/kg\",\"StationNumber: 19MTB54, Year: 2019, Value: 2.2 mg/kg\",\"StationNumber: 19MTB62, Year: 2019, Value: 0.55 mg/kg\",\"StationNumber: 19OTB07, Year: 2019, Value: 1.5 mg/kg\",\"StationNumber: 19OTB18, Year: 2019, Value: 1.2 mg/kg\",\"StationNumber: 19OTB20, Year: 2019, Value: 0.38 mg/kg\",\"StationNumber: 19OTB23, Year: 2019, Value: 0.9 mg/kg\",\"StationNumber: 19OTB25, Year: 2019, Value: 0.94 mg/kg\",\"StationNumber: 19OTB29, Year: 2019, Value: 1.32 mg/kg\",\"StationNumber: 19OTB31, Year: 2019, Value: 2.03 mg/kg\",\"StationNumber: 19TCB01, Year: 2019, Value: 4.92 mg/kg\",\"StationNumber: 19TCB20, Year: 2019, Value: 3.89 mg/kg\",\"StationNumber: 20BCB10, Year: 2020, Value: 0.63 mg/kg\",\"StationNumber: 20BCB17, Year: 2020, Value: 0.92 mg/kg\",\"StationNumber: 20BCB22, Year: 2020, Value: 15.76 mg/kg\",\"StationNumber: 20BCB23, Year: 2020, Value: 0.99 mg/kg\",\"StationNumber: 20BCB35, Year: 2020, Value: 3.19 mg/kg\",\"StationNumber: 20BCB37, Year: 2020, Value: 1.91 mg/kg\",\"StationNumber: 20BCB40, Year: 2020, Value: 0.63 mg/kg\",\"StationNumber: 20BCB43, Year: 2020, Value: 1.81 mg/kg\",\"StationNumber: 20BCB47, Year: 2020, Value: 1.65 mg/kg\",\"StationNumber: 20BCB48, Year: 2020, Value: 0.78 mg/kg\",\"StationNumber: 20BCB49, Year: 2020, Value: 1.3 mg/kg\",\"StationNumber: 20HB09, Year: 2020, Value: 0.01 mg/kg\",\"StationNumber: 20HB10, Year: 2020, Value: 0.01 mg/kg\",\"StationNumber: 20HB21, Year: 2020, Value: 0.01 mg/kg\",\"StationNumber: 20HB26, Year: 2020, Value: 8.35 mg/kg\",\"StationNumber: 20HB38, Year: 2020, Value: 3.49 mg/kg\",\"StationNumber: 20HB41, Year: 2020, Value: 3.54 mg/kg\",\"StationNumber: 20HB46, Year: 2020, Value: 1.16 mg/kg\",\"StationNumber: 20HB47, Year: 2020, Value: 0.34 mg/kg\",\"StationNumber: 20HB52, Year: 2020, Value: 2.28 mg/kg\",\"StationNumber: 20LTB70, Year: 2020, Value: 0.79 mg/kg\",\"StationNumber: 20LTB71, Year: 2020, Value: 0.96 mg/kg\",\"StationNumber: 20LTB77, Year: 2020, Value: 2.21 mg/kg\",\"StationNumber: 20LTB85, Year: 2020, Value: 10.94 mg/kg\",\"StationNumber: 20MR08, Year: 2020, Value: 1.25 mg/kg\",\"StationNumber: 20MR09, Year: 2020, Value: 1.22 mg/kg\",\"StationNumber: 20MR33, Year: 2020, Value: 1.25 mg/kg\",\"StationNumber: 20MR36, Year: 2020, Value: 1.24 mg/kg\",\"StationNumber: 20MR44, Year: 2020, Value: 6.25 mg/kg\",\"StationNumber: 20MR49, Year: 2020, Value: 0.94 mg/kg\",\"StationNumber: 20MTB35, Year: 2020, Value: 3.65 mg/kg\",\"StationNumber: 20MTB46, Year: 2020, Value: 0.23 mg/kg\",\"StationNumber: 20MTB52, Year: 2020, Value: 1.12 mg/kg\",\"StationNumber: 20MTB63, Year: 2020, Value: 0.48 mg/kg\",\"StationNumber: 20OTB13, Year: 2020, Value: 0.01 mg/kg\",\"StationNumber: 20OTB14, Year: 2020, Value: 0.01 mg/kg\",\"StationNumber: 20OTB15, Year: 2020, Value: 0.01 mg/kg\",\"StationNumber: 20OTB19, Year: 2020, Value: 0.01 mg/kg\",\"StationNumber: 20OTB21, Year: 2020, Value: 0.01 mg/kg\",\"StationNumber: 20OTB24, Year: 2020, Value: 0.01 mg/kg\",\"StationNumber: 20OTB32, Year: 2020, Value: 0.01 mg/kg\",\"StationNumber: 20TCB10, Year: 2020, Value: 4.53 mg/kg\",\"StationNumber: 20TCB12, Year: 2020, Value: 3.28 mg/kg\",\"StationNumber: 20TCB20, Year: 2020, Value: 3.03 mg/kg\",\"StationNumber: 21BCB09, Year: 2021, Value: 11.03 mg/kg\",\"StationNumber: 21BCB12, Year: 2021, Value: 4.15 mg/kg\",\"StationNumber: 21BCB15, Year: 2021, Value: 8.58 mg/kg\",\"StationNumber: 21BCB22, Year: 2021, Value: 1.46 mg/kg\",\"StationNumber: 21BCB25, Year: 2021, Value: 3.25 mg/kg\",\"StationNumber: 21BCB26, Year: 2021, Value: 5.19 mg/kg\",\"StationNumber: 21BCB29, Year: 2021, Value: 2.06 mg/kg\",\"StationNumber: 21BCB36, Year: 2021, Value: 0.98 mg/kg\",\"StationNumber: 21BCB41, Year: 2021, Value: 1.48 mg/kg\",\"StationNumber: 21BCB44, Year: 2021, Value: 4.08 mg/kg\",\"StationNumber: 21BCB50, Year: 2021, Value: 0.79 mg/kg\",\"StationNumber: 21HB13, Year: 2021, Value: 3.05 mg/kg\",\"StationNumber: 21HB19, Year: 2021, Value: 3.23 mg/kg\",\"StationNumber: 21HB20, Year: 2021, Value: 0.39 mg/kg\",\"StationNumber: 21HB27, Year: 2021, Value: 2.12 mg/kg\",\"StationNumber: 21HB34, Year: 2021, Value: 0.2 mg/kg\",\"StationNumber: 21HB36, Year: 2021, Value: 1.6 mg/kg\",\"StationNumber: 21HB37, Year: 2021, Value: 2.04 mg/kg\",\"StationNumber: 21HB40, Year: 2021, Value: 1.21 mg/kg\",\"StationNumber: 21HB43, Year: 2021, Value: 1.09 mg/kg\",\"StationNumber: 21LTB78, Year: 2021, Value: 3.26 mg/kg\",\"StationNumber: 21LTB83, Year: 2021, Value: 1.43 mg/kg\",\"StationNumber: 21LTB84, Year: 2021, Value: 5.27 mg/kg\",\"StationNumber: 21LTB89, Year: 2021, Value: 0.38 mg/kg\",\"StationNumber: 21MR24, Year: 2021, Value: 1.29 mg/kg\",\"StationNumber: 21MR29, Year: 2021, Value: 1.72 mg/kg\",\"StationNumber: 21MR45, Year: 2021, Value: 4.29 mg/kg\",\"StationNumber: 21MR47, Year: 2021, Value: 1.64 mg/kg\",\"StationNumber: 21MR52, Year: 2021, Value: 1.92 mg/kg\",\"StationNumber: 21MTB40, Year: 2021, Value: 0.15 mg/kg\",\"StationNumber: 21MTB43, Year: 2021, Value: 3.11 mg/kg\",\"StationNumber: 21MTB48, Year: 2021, Value: 1.12 mg/kg\",\"StationNumber: 21MTB62, Year: 2021, Value: 3.19 mg/kg\",\"StationNumber: 21OTB08, Year: 2021, Value: 0.22 mg/kg\",\"StationNumber: 21OTB12, Year: 2021, Value: 4.8 mg/kg\",\"StationNumber: 21OTB13, Year: 2021, Value: 0.45 mg/kg\",\"StationNumber: 21OTB18, Year: 2021, Value: 2.44 mg/kg\",\"StationNumber: 21OTB21, Year: 2021, Value: 0.24 mg/kg\",\"StationNumber: 21OTB25, Year: 2021, Value: 0.32 mg/kg\",\"StationNumber: 21OTB28, Year: 2021, Value: 0.16 mg/kg\",\"StationNumber: 21TCB02, Year: 2021, Value: 11.5 mg/kg\",\"StationNumber: 21TCB13, Year: 2021, Value: 7.11 mg/kg\",\"StationNumber: 21TCB22, Year: 2021, Value: 4.36 mg/kg\",\"StationNumber: 21TCB26, Year: 2021, Value: 2.49 mg/kg\",\"StationNumber: 22BCB02, Year: 2022, Value: 5.83 mg/kg\",\"StationNumber: 22BCB05, Year: 2022, Value: 1.17 mg/kg\",\"StationNumber: 22BCB11, Year: 2022, Value: 1.49 mg/kg\",\"StationNumber: 22BCB12, Year: 2022, Value: 1.1 mg/kg\",\"StationNumber: 22BCB17, Year: 2022, Value: 2.31 mg/kg\",\"StationNumber: 22BCB27, Year: 2022, Value: 1.33 mg/kg\",\"StationNumber: 22BCB30, Year: 2022, Value: 0.91 mg/kg\",\"StationNumber: 22BCB34, Year: 2022, Value: 0.62 mg/kg\",\"StationNumber: 22BCB35, Year: 2022, Value: 0.48 mg/kg\",\"StationNumber: 22BCB45, Year: 2022, Value: 1.24 mg/kg\",\"StationNumber: 22BCB47, Year: 2022, Value: 3.19 mg/kg\",\"StationNumber: 22HB10, Year: 2022, Value: 0.54 mg/kg\",\"StationNumber: 22HB19, Year: 2022, Value: 0.13 mg/kg\",\"StationNumber: 22HB21, Year: 2022, Value: 0.22 mg/kg\",\"StationNumber: 22HB25, Year: 2022, Value: 1.8 mg/kg\",\"StationNumber: 22HB26, Year: 2022, Value: 4.73 mg/kg\",\"StationNumber: 22HB28, Year: 2022, Value: 0.27 mg/kg\",\"StationNumber: 22HB32, Year: 2022, Value: 3.93 mg/kg\",\"StationNumber: 22HB40, Year: 2022, Value: 0.56 mg/kg\",\"StationNumber: 22HB46, Year: 2022, Value: 0.97 mg/kg\",\"StationNumber: 22LTB70, Year: 2022, Value: 2.91 mg/kg\",\"StationNumber: 22LTB79, Year: 2022, Value: 10.38 mg/kg\",\"StationNumber: 22LTB81, Year: 2022, Value: 0.9 mg/kg\",\"StationNumber: 22LTB90, Year: 2022, Value: 0.01 mg/kg\",\"StationNumber: 22MR17, Year: 2022, Value: 1.62 mg/kg\",\"StationNumber: 22MR25, Year: 2022, Value: 1.11 mg/kg\",\"StationNumber: 22MR32, Year: 2022, Value: 2.35 mg/kg\",\"StationNumber: 22MR37, Year: 2022, Value: 1.94 mg/kg\",\"StationNumber: 22MR42, Year: 2022, Value: 0.87 mg/kg\",\"StationNumber: 22MR44, Year: 2022, Value: 1.16 mg/kg\",\"StationNumber: 22MR46, Year: 2022, Value: 0.24 mg/kg\",\"StationNumber: 22MR52, Year: 2022, Value: 4.05 mg/kg\",\"StationNumber: 22MTB35, Year: 2022, Value: 1.69 mg/kg\",\"StationNumber: 22MTB37, Year: 2022, Value: 0.46 mg/kg\",\"StationNumber: 22MTB41, Year: 2022, Value: 2.4 mg/kg\",\"StationNumber: 22MTB55, Year: 2022, Value: 0.8 mg/kg\",\"StationNumber: 22OTB02, Year: 2022, Value: 1.05 mg/kg\",\"StationNumber: 22OTB07, Year: 2022, Value: 2.48 mg/kg\",\"StationNumber: 22OTB19, Year: 2022, Value: 1.75 mg/kg\",\"StationNumber: 22OTB22, Year: 2022, Value: 0.22 mg/kg\",\"StationNumber: 22OTB28, Year: 2022, Value: 0.25 mg/kg\",\"StationNumber: 22OTB29, Year: 2022, Value: 0.19 mg/kg\",\"StationNumber: 22OTB32, Year: 2022, Value: 0.15 mg/kg\",\"StationNumber: 22TCB20, Year: 2022, Value: 2.86 mg/kg\"],{\"interactive\":false,\"permanent\":false,\"direction\":\"auto\",\"opacity\":1,\"offset\":[0,0],\"textsize\":\"10px\",\"textOnly\":false,\"className\":\"\",\"sticky\":true},null]}],\"limits\":{\"lat\":[27.4934,28.03793],\"lng\":[-82.84670300000001,-82.343422]}},\"evals\":[],\"jsHooks\":{\"render\":[{\"code\":\"function(el, x, data) {\\n return (\\n function(el, x) {\\n var myMap = this;\\n myMap.on('baselayerchange',\\n function (e) {\\n myMap.minimap.changeLayer(L.tileLayer.provider(e.name));\\n })\\n }).call(this.getMap(), el, x, data);\\n}\",\"data\":null}]}}"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentpelave.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot summary of PEL averages by bay segment — show_sedimentpelave","title":"Plot summary of PEL averages by bay segment — show_sedimentpelave","text":"Plot summary PEL averages bay segment","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentpelave.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot summary of PEL averages by bay segment — show_sedimentpelave","text":"","code":"show_sedimentpelave( sedimentdata, yrrng = c(1993, 2022), bay_segment = c(\"HB\", \"OTB\", \"MTB\", \"LTB\", \"TCB\", \"MR\", \"BCB\"), funding_proj = \"TBEP\", alph = 1, ylim = c(0, 0.4), lnsz = 1, base_size = 12, plotly = FALSE, family = NA, width = NULL, height = NULL )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentpelave.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot summary of PEL averages by bay segment — show_sedimentpelave","text":"sedimentdata input sediment data.frame returned read_importsediment yrrng numeric vector indicating min, max years include, use single year one year data bay_segment chr string bay segment, one many \"HB\", \"OTB\", \"MTB\", \"LTB\", \"TCB\", \"MR\", \"BCB\" funding_proj chr string funding project, one many \"TBEP\" (default), \"TBEP-Special\", \"Apollo Beach\", \"Janicki Contract\", \"Rivers\", \"Tidal Streams\" alph numeric indicating alpha value score category colors ylim numeric y axis limits lnsz numeric line size base_size numeric indicating text scaling size plot plotly logical matrix created using plotly family optional chr string indicating font family text labels width numeric width plot pixels, applies plotly = TRUE height numeric height plot pixels, applies plotly = TRUE","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentpelave.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot summary of PEL averages by bay segment — show_sedimentpelave","text":"ggplot object plotly object plotly = TRUE showing PEL averages (average averages) 95","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentpelave.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Plot summary of PEL averages by bay segment — show_sedimentpelave","text":"Lines grades shown plot. Confidence intervals may shown segments insufficient data.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentpelave.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot summary of PEL averages by bay segment — show_sedimentpelave","text":"","code":"show_sedimentpelave(sedimentdata)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentpelaveplotly.html","id":null,"dir":"Reference","previous_headings":"","what":"Creates a plotly object for average PEL plots — show_sedimentpelaveplotly","title":"Creates a plotly object for average PEL plots — show_sedimentpelaveplotly","text":"Creates plotly object average PEL plots","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentpelaveplotly.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Creates a plotly object for average PEL plots — show_sedimentpelaveplotly","text":"","code":"show_sedimentpelaveplotly(p, width = NULL, height = NULL)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentpelaveplotly.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Creates a plotly object for average PEL plots — show_sedimentpelaveplotly","text":"p ggplot object output show_sedimentpelave width numeric width plot pixels height numeric height plot pixels","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentpelaveplotly.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Creates a plotly object for average PEL plots — show_sedimentpelaveplotly","text":"plotly data object","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sedimentpelaveplotly.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Creates a plotly object for average PEL plots — show_sedimentpelaveplotly","text":"","code":"p <- show_sedimentpelave(sedimentdata) show_sedimentpelaveplotly(p) {\"x\":{\"data\":[{\"x\":[null,null,null,null,null],\"y\":[null,0.0075599999999999999,0.0075599999999999999,null,null],\"text\":\"\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":1.8897637795275593,\"color\":\"transparent\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[null,null,null,null,null],\"y\":[0.0075599999999999999,0.02052,0.02052,0.0075599999999999999,0.0075599999999999999],\"text\":\"\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":1.8897637795275593,\"color\":\"transparent\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(162,253,122,1)\",\"hoveron\":\"fills\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[null,null,null,null,null],\"y\":[0.02052,0.085669999999999996,0.085669999999999996,0.02052,0.02052],\"text\":\"\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":1.8897637795275593,\"color\":\"transparent\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(233,195,24,1)\",\"hoveron\":\"fills\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[null,null,null,null,null],\"y\":[0.085669999999999996,0.28026000000000001,0.28026000000000001,0.085669999999999996,0.085669999999999996],\"text\":\"\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":1.8897637795275593,\"color\":\"transparent\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(238,118,0,1)\",\"hoveron\":\"fills\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[null,null,null,null,null],\"y\":[0.28026000000000001,null,null,0.28026000000000001,0.28026000000000001],\"text\":\"\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":1.8897637795275593,\"color\":\"transparent\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[7,1,4,6,3,2,5],\"y\":[0.053520437964741263,0.11766095904182264,0.028110742831749039,0.044553811438690069,0.037404087404364364,0.050639528194187294,0.03365804003727018],\"text\":[\"AreaAbbr: BCB
ave: 0.05352044\",\"AreaAbbr: HB
ave: 0.11766096\",\"AreaAbbr: LTB
ave: 0.02811074\",\"AreaAbbr: MR
ave: 0.04455381\",\"AreaAbbr: MTB
ave: 0.03740409\",\"AreaAbbr: OTB
ave: 0.05063953\",\"AreaAbbr: TCB
ave: 0.03365804\"],\"type\":\"scatter\",\"mode\":\"markers\",\"marker\":{\"autocolorscale\":false,\"color\":\"rgba(0,0,0,1)\",\"opacity\":1,\"size\":11.338582677165356,\"symbol\":\"circle\",\"line\":{\"width\":1.8897637795275593,\"color\":\"rgba(0,0,0,1)\"}},\"hoveron\":\"points\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[7,1,4,6,3,2,5],\"y\":[0.053520437964741263,0.11766095904182264,0.028110742831749039,0.044553811438690069,0.037404087404364364,0.050639528194187294,0.03365804003727018],\"text\":[\"AreaAbbr: BCB
ave: 0.05352044
lov: 0.04450421
hiv: 0.06253667\",\"AreaAbbr: HB
ave: 0.11766096
lov: 0.06630981
hiv: 0.16901211\",\"AreaAbbr: LTB
ave: 0.02811074
lov: 0.02473974
hiv: 0.03148174\",\"AreaAbbr: MR
ave: 0.04455381
lov: 0.03754802
hiv: 0.05155960\",\"AreaAbbr: MTB
ave: 0.03740409
lov: 0.03268379
hiv: 0.04212438\",\"AreaAbbr: OTB
ave: 0.05063953
lov: 0.03706261
hiv: 0.06421645\",\"AreaAbbr: TCB
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C\",\"StationNumber: 94LTB35, Year: 1994, PEL ratio: 0.01209, Grade: B\",\"StationNumber: 94LTB36, Year: 1994, PEL ratio: 0.04666, Grade: C\",\"StationNumber: 94LTB37, Year: 1994, PEL ratio: 0.10165, Grade: D\",\"StationNumber: 94LTB38, Year: 1994, PEL ratio: 0.02221, Grade: C\",\"StationNumber: 94LTB39, Year: 1994, PEL ratio: 0.08637, Grade: D\",\"StationNumber: 94LTB40, Year: 1994, PEL ratio: 0.06117, Grade: C\",\"StationNumber: 94MR23, Year: 1994, PEL ratio: 0, Grade: A\",\"StationNumber: 94MR24, Year: 1994, PEL ratio: 0, Grade: A\",\"StationNumber: 94MR26, Year: 1994, PEL ratio: 0, Grade: A\",\"StationNumber: 94MR27, Year: 1994, PEL ratio: 0, Grade: A\",\"StationNumber: 94MR28, Year: 1994, PEL ratio: 0, Grade: A\",\"StationNumber: 94MR29, Year: 1994, PEL ratio: 0, Grade: A\",\"StationNumber: 94MR31, Year: 1994, PEL ratio: 0, Grade: A\",\"StationNumber: 94MR32, Year: 1994, PEL ratio: 0, Grade: A\",\"StationNumber: 94MR34, Year: 1994, PEL ratio: 0, Grade: A\",\"StationNumber: 94MR43, Year: 1994, PEL ratio: 0, Grade: A\",\"StationNumber: 94MTB41, Year: 1994, PEL ratio: 0.00869, Grade: B\",\"StationNumber: 94MTB42, Year: 1994, PEL ratio: 0.00546, Grade: A\",\"StationNumber: 94MTB43, Year: 1994, PEL ratio: 0.07634, Grade: C\",\"StationNumber: 94MTB44, Year: 1994, PEL ratio: 0.09942, Grade: D\",\"StationNumber: 94MTB45, Year: 1994, PEL ratio: 0.03607, Grade: C\",\"StationNumber: 94MTB47, Year: 1994, PEL ratio: 0.03786, Grade: C\",\"StationNumber: 94MTB48, Year: 1994, PEL ratio: 0.00958, Grade: B\",\"StationNumber: 94MTB49, Year: 1994, PEL ratio: 0.08992, Grade: D\",\"StationNumber: 94MTB50, Year: 1994, PEL ratio: 0.04484, Grade: C\",\"StationNumber: 94MTB51, Year: 1994, PEL ratio: 0.01764, Grade: B\",\"StationNumber: 94MTB52, Year: 1994, PEL ratio: 0.01808, Grade: B\",\"StationNumber: 94MTB53, Year: 1994, PEL ratio: 0.01368, Grade: B\",\"StationNumber: 94MTB54, Year: 1994, PEL ratio: 0.05744, Grade: C\",\"StationNumber: 94MTB55, Year: 1994, PEL ratio: 0.00805, Grade: B\",\"StationNumber: 94MTB56, Year: 1994, PEL ratio: 0.03262, Grade: C\",\"StationNumber: 94MTB57, Year: 1994, PEL ratio: 0.03071, Grade: C\",\"StationNumber: 94MTB58, Year: 1994, PEL ratio: 0.10823, Grade: D\",\"StationNumber: 94MTB59, Year: 1994, PEL ratio: 0.0237, Grade: C\",\"StationNumber: 94MTB60, Year: 1994, PEL ratio: 0.00788, Grade: B\",\"StationNumber: 94MTB61, Year: 1994, PEL ratio: 0.14417, Grade: D\",\"StationNumber: 94OTB63, Year: 1994, PEL ratio: 0.16877, Grade: D\",\"StationNumber: 94OTB64, Year: 1994, PEL ratio: 0.01051, Grade: B\",\"StationNumber: 94OTB65, Year: 1994, PEL ratio: 0.02364, Grade: C\",\"StationNumber: 94OTB66, Year: 1994, PEL ratio: 0.0106, Grade: B\",\"StationNumber: 94OTB67, Year: 1994, PEL ratio: 0.03548, Grade: C\",\"StationNumber: 94OTB68, Year: 1994, PEL ratio: 0.01448, Grade: B\",\"StationNumber: 94OTB69, Year: 1994, PEL ratio: 0.01953, Grade: B\",\"StationNumber: 94OTB70, Year: 1994, PEL ratio: 0.00537, Grade: A\",\"StationNumber: 94OTB71, Year: 1994, PEL ratio: 0.0663, Grade: C\",\"StationNumber: 94OTB72, Year: 1994, PEL ratio: 0.01765, Grade: B\",\"StationNumber: 94OTB73, Year: 1994, PEL ratio: 0.09561, Grade: D\",\"StationNumber: 94OTB76, Year: 1994, PEL ratio: 0.01769, Grade: B\",\"StationNumber: 94OTB77, Year: 1994, PEL ratio: 0.00515, Grade: A\",\"StationNumber: 94OTB78, Year: 1994, PEL ratio: 0.15079, Grade: D\",\"StationNumber: 94OTB79, Year: 1994, PEL ratio: 0.02344, Grade: C\",\"StationNumber: 94OTB80, Year: 1994, PEL ratio: 0.02606, Grade: C\",\"StationNumber: 94OTB83, Year: 1994, PEL ratio: 0.01552, Grade: B\",\"StationNumber: 94TCB22, Year: 1994, PEL ratio: 0, Grade: A\",\"StationNumber: 94TCB37, Year: 1994, PEL ratio: 0, Grade: A\",\"StationNumber: 94TCB38, Year: 1994, PEL ratio: 0, Grade: A\",\"StationNumber: 94TCB39, Year: 1994, PEL ratio: 0, Grade: A\",\"StationNumber: 94TCB40, Year: 1994, PEL ratio: 0, Grade: A\",\"StationNumber: 94TCB41, Year: 1994, PEL ratio: 0, Grade: A\",\"StationNumber: 94TCB42, Year: 1994, PEL ratio: 0, Grade: A\",\"StationNumber: 95BCB01, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95BCB02, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95BCB03, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95BCB04, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95BCB05, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95BCB06, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95BCB07, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95BCB08, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95BCB09, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95BCB10, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95BCB11, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95BCB12, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95BCB13, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95BCB14, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95BCB15, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95BCB16, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95BCB17, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95BCB18, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95BCB19, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95BCB20, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95BCB21, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95HB14, Year: 1995, PEL ratio: 0.27004, Grade: D\",\"StationNumber: 95HB16, Year: 1995, PEL ratio: 0.46027, Grade: F\",\"StationNumber: 95HB17, Year: 1995, PEL ratio: 0.04182, Grade: C\",\"StationNumber: 95HB18, Year: 1995, PEL ratio: 0.25744, Grade: D\",\"StationNumber: 95HB19, Year: 1995, PEL ratio: 0.02669, Grade: C\",\"StationNumber: 95HB22, Year: 1995, PEL ratio: 0.08766, Grade: D\",\"StationNumber: 95HB23, Year: 1995, PEL ratio: 0.17389, Grade: D\",\"StationNumber: 95HB24, Year: 1995, PEL ratio: 0.00709, Grade: A\",\"StationNumber: 95HB25, Year: 1995, PEL ratio: 0.10295, Grade: D\",\"StationNumber: 95HB26, Year: 1995, PEL ratio: 0.00947, Grade: B\",\"StationNumber: 95HB27, Year: 1995, PEL ratio: 0.00545, Grade: A\",\"StationNumber: 95HB28, Year: 1995, PEL ratio: 0.00784, Grade: B\",\"StationNumber: 95HB29, Year: 1995, PEL ratio: 0.06887, Grade: C\",\"StationNumber: 95HB37, Year: 1995, PEL ratio: 0.07591, Grade: C\",\"StationNumber: 95HB38, Year: 1995, PEL ratio: 0.00626, Grade: A\",\"StationNumber: 95HB40, Year: 1995, PEL ratio: 0.00642, Grade: A\",\"StationNumber: 95HB41, Year: 1995, PEL ratio: 0.00725, Grade: A\",\"StationNumber: 95HB42, Year: 1995, PEL ratio: 0.00695, Grade: A\",\"StationNumber: 95HB43, Year: 1995, PEL ratio: 0.07978, Grade: C\",\"StationNumber: 95HB44, Year: 1995, PEL ratio: 0.00487, Grade: A\",\"StationNumber: 95HB45, Year: 1995, PEL ratio: 0.0044, Grade: A\",\"StationNumber: 95HB46, Year: 1995, PEL ratio: 0.11769, Grade: D\",\"StationNumber: 95HB48, Year: 1995, PEL ratio: 0.01232, Grade: B\",\"StationNumber: 95HB49, Year: 1995, PEL ratio: 0.00484, Grade: A\",\"StationNumber: 95HB51, Year: 1995, PEL ratio: 0.00683, Grade: A\",\"StationNumber: 95HB52, Year: 1995, PEL ratio: 0.12448, Grade: D\",\"StationNumber: 95HB54, Year: 1995, PEL ratio: 0.00769, Grade: B\",\"StationNumber: 95HB55, Year: 1995, PEL ratio: 0.00545, Grade: A\",\"StationNumber: 95HB56, Year: 1995, PEL ratio: 0.19484, Grade: D\",\"StationNumber: 95LTB01, Year: 1995, PEL ratio: 0.00385, Grade: A\",\"StationNumber: 95LTB02, Year: 1995, PEL ratio: 0.00483, Grade: A\",\"StationNumber: 95LTB04, Year: 1995, PEL ratio: 0.01579, Grade: B\",\"StationNumber: 95LTB05, Year: 1995, PEL ratio: 0.02646, Grade: C\",\"StationNumber: 95LTB06, Year: 1995, PEL ratio: 0.00405, Grade: A\",\"StationNumber: 95LTB07, Year: 1995, PEL ratio: 0.00392, Grade: A\",\"StationNumber: 95LTB08, Year: 1995, PEL ratio: 0.00633, Grade: A\",\"StationNumber: 95LTB09, Year: 1995, PEL ratio: 0.00764, Grade: B\",\"StationNumber: 95LTB10, Year: 1995, PEL ratio: 0.00838, Grade: B\",\"StationNumber: 95LTB11, Year: 1995, PEL ratio: 0.01854, Grade: B\",\"StationNumber: 95LTB12, Year: 1995, PEL ratio: 0.05258, Grade: C\",\"StationNumber: 95LTB13, Year: 1995, PEL ratio: 0.03364, Grade: C\",\"StationNumber: 95LTB15, Year: 1995, PEL ratio: 0.00223, Grade: A\",\"StationNumber: 95LTB17, Year: 1995, PEL ratio: 0.00912, Grade: B\",\"StationNumber: 95LTB18, Year: 1995, PEL ratio: 0.00937, Grade: B\",\"StationNumber: 95LTB19, Year: 1995, PEL ratio: 0.00514, Grade: A\",\"StationNumber: 95LTB20, Year: 1995, PEL ratio: 0.00586, Grade: A\",\"StationNumber: 95LTB21, Year: 1995, PEL ratio: 0.00346, Grade: A\",\"StationNumber: 95LTB23, Year: 1995, PEL ratio: 0.01403, Grade: B\",\"StationNumber: 95LTB25, Year: 1995, PEL ratio: 0.002, Grade: A\",\"StationNumber: 95LTB26, Year: 1995, PEL ratio: 0.00213, Grade: A\",\"StationNumber: 95LTB29, Year: 1995, PEL ratio: 0.00364, Grade: A\",\"StationNumber: 95MR23, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95MR24, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95MR25, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95MR26, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95MR27, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95MR28, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95MR29, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95MR31, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95MR32, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95MR34, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95MR43, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95MTB03, Year: 1995, PEL ratio: 0.00465, Grade: A\",\"StationNumber: 95MTB04, Year: 1995, PEL ratio: 0.008, Grade: B\",\"StationNumber: 95MTB06, Year: 1995, PEL ratio: 0.00235, Grade: A\",\"StationNumber: 95MTB07, Year: 1995, PEL ratio: 0.12807, Grade: D\",\"StationNumber: 95MTB08, Year: 1995, PEL ratio: 0.00916, Grade: B\",\"StationNumber: 95MTB10, Year: 1995, PEL ratio: 0.00729, Grade: A\",\"StationNumber: 95MTB15, Year: 1995, PEL ratio: 0.00246, Grade: A\",\"StationNumber: 95MTB16, Year: 1995, PEL ratio: 0.00155, Grade: A\",\"StationNumber: 95MTB17, Year: 1995, PEL ratio: 0.01668, Grade: B\",\"StationNumber: 95MTB18, Year: 1995, PEL ratio: 0.03443, Grade: C\",\"StationNumber: 95MTB19, Year: 1995, PEL ratio: 0.00365, Grade: A\",\"StationNumber: 95MTB21, Year: 1995, PEL ratio: 0.02294, Grade: C\",\"StationNumber: 95MTB24, Year: 1995, PEL ratio: 0.00408, Grade: A\",\"StationNumber: 95MTB25, Year: 1995, PEL ratio: 0.0049, Grade: A\",\"StationNumber: 95MTB26, Year: 1995, PEL ratio: 0.00385, Grade: A\",\"StationNumber: 95MTB29, Year: 1995, PEL ratio: 0.0045, Grade: A\",\"StationNumber: 95MTB30, Year: 1995, PEL ratio: 0.00748, Grade: A\",\"StationNumber: 95MTB31, Year: 1995, PEL ratio: 0.0045, Grade: A\",\"StationNumber: 95MTB32, Year: 1995, PEL ratio: 0.00689, Grade: A\",\"StationNumber: 95MTB34, Year: 1995, PEL ratio: 0.01326, Grade: B\",\"StationNumber: 95MTB35, Year: 1995, PEL ratio: 0.00817, Grade: B\",\"StationNumber: 95OTB02, Year: 1995, PEL ratio: 0.01655, Grade: B\",\"StationNumber: 95OTB03, Year: 1995, PEL ratio: 0.00572, Grade: A\",\"StationNumber: 95OTB05, Year: 1995, PEL ratio: 0.02432, Grade: C\",\"StationNumber: 95OTB06, Year: 1995, PEL ratio: 0.00961, Grade: B\",\"StationNumber: 95OTB07, Year: 1995, PEL ratio: 0.00772, Grade: B\",\"StationNumber: 95OTB08, Year: 1995, PEL ratio: 0.00541, Grade: A\",\"StationNumber: 95OTB11, Year: 1995, PEL ratio: 0.01187, Grade: B\",\"StationNumber: 95OTB12, Year: 1995, PEL ratio: 0.01178, Grade: B\",\"StationNumber: 95OTB13, Year: 1995, PEL ratio: 0.00594, Grade: A\",\"StationNumber: 95OTB14, Year: 1995, PEL ratio: 0.00796, Grade: B\",\"StationNumber: 95OTB15, Year: 1995, PEL ratio: 0.28594, Grade: F\",\"StationNumber: 95OTB17, Year: 1995, PEL ratio: 0.00668, Grade: A\",\"StationNumber: 95OTB18, Year: 1995, PEL ratio: 0.00656, Grade: A\",\"StationNumber: 95OTB19, Year: 1995, PEL ratio: 0.04972, Grade: C\",\"StationNumber: 95OTB20, Year: 1995, PEL ratio: 0.00788, Grade: B\",\"StationNumber: 95OTB22, Year: 1995, PEL ratio: 0.01855, Grade: B\",\"StationNumber: 95OTB23, Year: 1995, PEL ratio: 0.00383, Grade: A\",\"StationNumber: 95OTB24, Year: 1995, PEL ratio: 0.00477, Grade: A\",\"StationNumber: 95OTB25, Year: 1995, PEL ratio: 0.00588, Grade: A\",\"StationNumber: 95OTB26, Year: 1995, PEL ratio: 0.00476, Grade: A\",\"StationNumber: 95OTB27, Year: 1995, PEL ratio: 0.0039, Grade: A\",\"StationNumber: 95OTB29, Year: 1995, PEL ratio: 0.00722, Grade: A\",\"StationNumber: 95OTB30, Year: 1995, PEL ratio: 0.00191, Grade: A\",\"StationNumber: 95TCB22, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95TCB37, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95TCB38, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95TCB39, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95TCB40, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95TCB41, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 95TCB42, Year: 1995, PEL ratio: 0, Grade: A\",\"StationNumber: 96BCB02, Year: 1996, PEL ratio: 0.02981, Grade: C\",\"StationNumber: 96BCB04, Year: 1996, PEL ratio: 0.21792, Grade: D\",\"StationNumber: 96BCB07, Year: 1996, PEL ratio: 0.04432, Grade: C\",\"StationNumber: 96BCB08, Year: 1996, PEL ratio: 0.02026, Grade: B\",\"StationNumber: 96BCB12, Year: 1996, PEL ratio: 0.03692, Grade: C\",\"StationNumber: 96BCB13, Year: 1996, PEL ratio: 0.31368, Grade: F\",\"StationNumber: 96BCB15, Year: 1996, PEL ratio: 0.18237, Grade: D\",\"StationNumber: 96BCB19, Year: 1996, PEL ratio: 0.01925, Grade: B\",\"StationNumber: 96BCB24, Year: 1996, PEL ratio: 0.03429, Grade: C\",\"StationNumber: 96BCB26, Year: 1996, PEL ratio: 0.01638, Grade: B\",\"StationNumber: 96BCB27, Year: 1996, PEL ratio: 0.02494, Grade: C\",\"StationNumber: 96BCB30, Year: 1996, PEL ratio: 0.01775, Grade: B\",\"StationNumber: 96BCB31, Year: 1996, PEL ratio: 0.26305, Grade: D\",\"StationNumber: 96BCB34, Year: 1996, PEL ratio: 0.01272, Grade: B\",\"StationNumber: 96BCB36, Year: 1996, PEL ratio: 0.00987, Grade: B\",\"StationNumber: 96BCB39, Year: 1996, PEL ratio: 0.01263, Grade: B\",\"StationNumber: 96BCB40, Year: 1996, PEL ratio: 0.01665, Grade: B\",\"StationNumber: 96BCB41, Year: 1996, PEL ratio: 0.00563, Grade: A\",\"StationNumber: 96BCB44, Year: 1996, PEL ratio: 0.02696, Grade: C\",\"StationNumber: 96BCB46, Year: 1996, PEL ratio: 0.00262, Grade: A\",\"StationNumber: 96BCB49, Year: 1996, PEL ratio: 0.00173, Grade: A\",\"StationNumber: 96HB13, Year: 1996, PEL ratio: 0.28424, Grade: F\",\"StationNumber: 96HB16, Year: 1996, PEL ratio: 0.01524, Grade: B\",\"StationNumber: 96HB18, Year: 1996, PEL ratio: 0.52049, Grade: F\",\"StationNumber: 96HB20, Year: 1996, PEL ratio: 0.14092, Grade: D\",\"StationNumber: 96HB22, Year: 1996, PEL ratio: 0.16443, Grade: D\",\"StationNumber: 96HB23, Year: 1996, PEL ratio: 0.07935, Grade: C\",\"StationNumber: 96HB24, Year: 1996, PEL ratio: 0.00728, Grade: A\",\"StationNumber: 96HB26, Year: 1996, PEL ratio: 0.00701, Grade: A\",\"StationNumber: 96HB27, Year: 1996, PEL ratio: 0.05771, Grade: C\",\"StationNumber: 96HB29, Year: 1996, PEL ratio: 0.01207, Grade: B\",\"StationNumber: 96HB36, Year: 1996, PEL ratio: 0.03241, Grade: C\",\"StationNumber: 96HB37, Year: 1996, PEL ratio: 0.03752, Grade: C\",\"StationNumber: 96HB38, Year: 1996, PEL ratio: 0.10492, Grade: D\",\"StationNumber: 96HB39, Year: 1996, PEL ratio: 0.01913, Grade: B\",\"StationNumber: 96HB42, Year: 1996, PEL ratio: 0.05108, Grade: C\",\"StationNumber: 96HB43, Year: 1996, PEL ratio: 0.08509, Grade: C\",\"StationNumber: 96HB44, Year: 1996, PEL ratio: 0.02579, Grade: C\",\"StationNumber: 96HB45, Year: 1996, PEL ratio: 0.00593, Grade: A\",\"StationNumber: 96HB46, Year: 1996, PEL ratio: 11.28998, Grade: F\",\"StationNumber: 96HB47, Year: 1996, PEL ratio: 0.01428, Grade: B\",\"StationNumber: 96HB48, Year: 1996, PEL ratio: 0.1139, Grade: D\",\"StationNumber: 96HB50, Year: 1996, PEL ratio: 0.02802, Grade: C\",\"StationNumber: 96HB51, Year: 1996, PEL ratio: 0.00781, Grade: B\",\"StationNumber: 96HB52, Year: 1996, PEL ratio: 0.00565, Grade: A\",\"StationNumber: 96HB53, Year: 1996, PEL ratio: 0.00529, Grade: A\",\"StationNumber: 96HB54, Year: 1996, PEL ratio: 0.00646, Grade: A\",\"StationNumber: 96HB56, Year: 1996, PEL ratio: 0.15168, Grade: D\",\"StationNumber: 96LTB01, Year: 1996, PEL ratio: 0.07215, Grade: C\",\"StationNumber: 96LTB02, Year: 1996, PEL ratio: 0.01176, Grade: B\",\"StationNumber: 96LTB03, Year: 1996, PEL ratio: 0.01258, Grade: B\",\"StationNumber: 96LTB04, Year: 1996, PEL ratio: 0.00388, Grade: A\",\"StationNumber: 96LTB05, Year: 1996, PEL ratio: 0.00328, Grade: A\",\"StationNumber: 96LTB06, Year: 1996, PEL ratio: 0.01863, Grade: B\",\"StationNumber: 96LTB07, Year: 1996, PEL ratio: 0.01085, Grade: B\",\"StationNumber: 96LTB08, Year: 1996, PEL ratio: 0.00503, Grade: A\",\"StationNumber: 96LTB09, Year: 1996, PEL ratio: 0.00497, Grade: A\",\"StationNumber: 96LTB10, Year: 1996, PEL ratio: 0.01922, Grade: B\",\"StationNumber: 96LTB11, Year: 1996, PEL ratio: 0.02443, Grade: C\",\"StationNumber: 96LTB12, Year: 1996, PEL ratio: 0.01365, Grade: B\",\"StationNumber: 96LTB13, Year: 1996, PEL ratio: 0.05548, Grade: C\",\"StationNumber: 96LTB15, Year: 1996, PEL ratio: 0.00203, Grade: A\",\"StationNumber: 96LTB17, Year: 1996, PEL ratio: 0.01376, Grade: B\",\"StationNumber: 96LTB18, Year: 1996, PEL ratio: 0.01093, Grade: B\",\"StationNumber: 96LTB19, Year: 1996, PEL ratio: 0.00533, Grade: A\",\"StationNumber: 96LTB20, Year: 1996, PEL ratio: 0.00274, Grade: A\",\"StationNumber: 96LTB21, Year: 1996, PEL ratio: 0.00191, Grade: A\",\"StationNumber: 96LTB23, Year: 1996, PEL ratio: 0.00883, Grade: B\",\"StationNumber: 96LTB24, Year: 1996, PEL ratio: 0.00966, Grade: B\",\"StationNumber: 96LTB25, Year: 1996, PEL ratio: 0.0028, Grade: A\",\"StationNumber: 96LTB26, Year: 1996, PEL ratio: 0.00167, Grade: A\",\"StationNumber: 96LTB27, Year: 1996, PEL ratio: 0.00845, Grade: B\",\"StationNumber: 96MR20, Year: 1996, PEL ratio: 0.0375, Grade: C\",\"StationNumber: 96MR21, Year: 1996, PEL ratio: 0.01873, Grade: B\",\"StationNumber: 96MR23, Year: 1996, PEL ratio: 0.03078, Grade: C\",\"StationNumber: 96MR24, Year: 1996, PEL ratio: 0.04434, Grade: C\",\"StationNumber: 96MR25, Year: 1996, PEL ratio: 0.0361, Grade: C\",\"StationNumber: 96MR26, Year: 1996, PEL ratio: 0.02689, Grade: C\",\"StationNumber: 96MR27, Year: 1996, PEL ratio: 0.02357, Grade: C\",\"StationNumber: 96MR28, Year: 1996, PEL ratio: 0.00874, Grade: B\",\"StationNumber: 96MR29, Year: 1996, PEL ratio: 0.04221, Grade: C\",\"StationNumber: 96MR30, Year: 1996, PEL ratio: 0.03112, Grade: C\",\"StationNumber: 96MR31, Year: 1996, PEL ratio: 0.01702, Grade: B\",\"StationNumber: 96MR32, Year: 1996, PEL ratio: 0.0686, Grade: C\",\"StationNumber: 96MR43, Year: 1996, PEL ratio: 0.00642, Grade: A\",\"StationNumber: 96MTB04, Year: 1996, PEL ratio: 0.00399, Grade: A\",\"StationNumber: 96MTB05, Year: 1996, PEL ratio: 0.00738, Grade: A\",\"StationNumber: 96MTB07, Year: 1996, PEL ratio: 0.01865, Grade: B\",\"StationNumber: 96MTB09, Year: 1996, PEL ratio: 0.04135, Grade: C\",\"StationNumber: 96MTB10, Year: 1996, PEL ratio: 0.00598, Grade: A\",\"StationNumber: 96MTB11, Year: 1996, PEL ratio: 0.0094, Grade: B\",\"StationNumber: 96MTB12, Year: 1996, PEL ratio: 0.01296, Grade: B\",\"StationNumber: 96MTB13, Year: 1996, PEL ratio: 0.00054, Grade: A\",\"StationNumber: 96MTB14, Year: 1996, PEL ratio: 0.21228, Grade: D\",\"StationNumber: 96MTB15, Year: 1996, PEL ratio: 0.00246, Grade: A\",\"StationNumber: 96MTB16, Year: 1996, PEL ratio: 0.00187, Grade: A\",\"StationNumber: 96MTB17, Year: 1996, PEL ratio: 0.02882, Grade: C\",\"StationNumber: 96MTB18, Year: 1996, PEL ratio: 0.00511, Grade: A\",\"StationNumber: 96MTB19, Year: 1996, PEL ratio: 0.00327, Grade: A\",\"StationNumber: 96MTB20, Year: 1996, PEL ratio: 0.07168, Grade: C\",\"StationNumber: 96MTB23, Year: 1996, PEL ratio: 0.00289, Grade: A\",\"StationNumber: 96MTB24, Year: 1996, PEL ratio: 0.0044, Grade: A\",\"StationNumber: 96MTB25, Year: 1996, PEL ratio: 0.00302, Grade: A\",\"StationNumber: 96MTB26, Year: 1996, PEL ratio: 0.00717, Grade: A\",\"StationNumber: 96MTB30, Year: 1996, PEL ratio: 0.00823, Grade: B\",\"StationNumber: 96MTB31, Year: 1996, PEL ratio: 0.01583, Grade: B\",\"StationNumber: 96MTB32, Year: 1996, PEL ratio: 0.02658, Grade: C\",\"StationNumber: 96MTB34, Year: 1996, PEL ratio: 0.01453, Grade: B\",\"StationNumber: 96MTB35, Year: 1996, PEL ratio: 0.00178, Grade: A\",\"StationNumber: 96OTB07, Year: 1996, PEL ratio: 0.00525, Grade: A\",\"StationNumber: 96OTB11, Year: 1996, PEL ratio: 0.0031, Grade: A\",\"StationNumber: 96OTB12, Year: 1996, PEL ratio: 0.01689, Grade: B\",\"StationNumber: 96OTB13, Year: 1996, PEL ratio: 0.00455, Grade: A\",\"StationNumber: 96OTB14, Year: 1996, PEL ratio: 0.01495, Grade: B\",\"StationNumber: 96OTB17, Year: 1996, PEL ratio: 0.00886, Grade: B\",\"StationNumber: 96OTB18, Year: 1996, PEL ratio: 0.01434, Grade: B\",\"StationNumber: 96OTB19, Year: 1996, PEL ratio: 0.01141, Grade: B\",\"StationNumber: 96OTB20, Year: 1996, PEL ratio: 0.09948, Grade: D\",\"StationNumber: 96OTB23, Year: 1996, PEL ratio: 0.00414, Grade: A\",\"StationNumber: 96OTB24, Year: 1996, PEL ratio: 0.00798, Grade: B\",\"StationNumber: 96OTB26, Year: 1996, PEL ratio: 0.00414, Grade: A\",\"StationNumber: 96OTB27, Year: 1996, PEL ratio: 0.00358, Grade: A\",\"StationNumber: 96OTB29, Year: 1996, PEL ratio: 0.00299, Grade: A\",\"StationNumber: 96OTB30, Year: 1996, PEL ratio: 0.01598, Grade: B\",\"StationNumber: 96TCB22, Year: 1996, PEL ratio: 0.03815, Grade: C\",\"StationNumber: 96TCB36, Year: 1996, PEL ratio: 0.0182, Grade: B\",\"StationNumber: 96TCB37, Year: 1996, PEL ratio: 0.06747, Grade: C\",\"StationNumber: 96TCB38, Year: 1996, PEL ratio: 0.04811, Grade: C\",\"StationNumber: 96TCB39, Year: 1996, PEL ratio: 0.03235, Grade: C\",\"StationNumber: 96TCB40, Year: 1996, PEL ratio: 0.02086, Grade: C\",\"StationNumber: 96TCB41, Year: 1996, PEL ratio: 0.02591, Grade: C\",\"StationNumber: 96TCB42, Year: 1996, PEL ratio: 0.01431, Grade: B\",\"StationNumber: 97BCB02, Year: 1997, PEL ratio: 0.02654, Grade: C\",\"StationNumber: 97BCB08, Year: 1997, PEL ratio: 0.06243, Grade: C\",\"StationNumber: 97BCB10, Year: 1997, PEL ratio: 0.07472, Grade: C\",\"StationNumber: 97BCB13, Year: 1997, PEL ratio: 0.02112, Grade: C\",\"StationNumber: 97BCB17, Year: 1997, PEL ratio: 0.06466, Grade: C\",\"StationNumber: 97BCB18, Year: 1997, PEL ratio: 0.03013, Grade: C\",\"StationNumber: 97BCB27, Year: 1997, PEL ratio: 0.25161, Grade: D\",\"StationNumber: 97BCB30, Year: 1997, PEL ratio: 0.02293, Grade: C\",\"StationNumber: 97BCB31, Year: 1997, PEL ratio: 0.00973, Grade: B\",\"StationNumber: 97BCB36, Year: 1997, PEL ratio: 0.01281, Grade: B\",\"StationNumber: 97BCB37, Year: 1997, PEL ratio: 0.01861, Grade: B\",\"StationNumber: 97BCB40, Year: 1997, PEL ratio: 0.03448, Grade: C\",\"StationNumber: 97BCB46, Year: 1997, PEL ratio: 0.01276, Grade: B\",\"StationNumber: 97BCB50, Year: 1997, PEL ratio: 0.0087, Grade: B\",\"StationNumber: 97BCB57-1, Year: 1997, PEL ratio: 0.12797, Grade: D\",\"StationNumber: 97BCB58-1, Year: 1997, PEL ratio: 0.29199, Grade: F\",\"StationNumber: 97BCB58-2, Year: 1997, PEL ratio: 0.04357, Grade: C\",\"StationNumber: 97BCB59-1, Year: 1997, PEL ratio: 0.0167, Grade: B\",\"StationNumber: 97BCB59-2, Year: 1997, PEL ratio: 0.02798, Grade: C\",\"StationNumber: 97BCB60-2, Year: 1997, PEL ratio: 0.00469, Grade: A\",\"StationNumber: 97BCB60-4, Year: 1997, PEL ratio: 0.00523, Grade: A\",\"StationNumber: 97HB10, Year: 1997, PEL ratio: 1.45751, Grade: F\",\"StationNumber: 97HB13, Year: 1997, PEL ratio: 0.20993, Grade: D\",\"StationNumber: 97HB18, Year: 1997, PEL ratio: 0.0395, Grade: C\",\"StationNumber: 97HB22, Year: 1997, PEL ratio: 0.23185, Grade: D\",\"StationNumber: 97HB23, Year: 1997, PEL ratio: 0.01374, Grade: B\",\"StationNumber: 97HB24, Year: 1997, PEL ratio: 0.00515, Grade: A\",\"StationNumber: 97HB27, Year: 1997, PEL ratio: 0.00494, Grade: A\",\"StationNumber: 97HB29, Year: 1997, PEL ratio: 0.18186, Grade: D\",\"StationNumber: 97HB36, Year: 1997, PEL ratio: 0.00827, Grade: B\",\"StationNumber: 97HB37, Year: 1997, PEL ratio: 0.06009, Grade: C\",\"StationNumber: 97HB38, Year: 1997, PEL ratio: 0.04075, Grade: C\",\"StationNumber: 97HB39, Year: 1997, PEL ratio: 0.08084, Grade: C\",\"StationNumber: 97HB43, Year: 1997, PEL ratio: 0.0066, Grade: A\",\"StationNumber: 97HB44, Year: 1997, PEL ratio: 0.01905, Grade: B\",\"StationNumber: 97HB45, Year: 1997, PEL ratio: 0.03887, Grade: C\",\"StationNumber: 97HB46, Year: 1997, PEL ratio: 0.00974, Grade: B\",\"StationNumber: 97HB48, Year: 1997, PEL ratio: 0.00871, Grade: B\",\"StationNumber: 97HB50, Year: 1997, PEL ratio: 0.08114, Grade: C\",\"StationNumber: 97HB53, Year: 1997, PEL ratio: 0.00914, Grade: B\",\"StationNumber: 97HB54, Year: 1997, PEL ratio: 0.01088, Grade: B\",\"StationNumber: 97HB55, Year: 1997, PEL ratio: 0.02004, Grade: B\",\"StationNumber: 97HB56, Year: 1997, PEL ratio: 0.01339, Grade: B\",\"StationNumber: 97LTB01, Year: 1997, PEL ratio: 0.0117, Grade: B\",\"StationNumber: 97LTB02, Year: 1997, PEL ratio: 0.01631, Grade: B\",\"StationNumber: 97LTB03, Year: 1997, PEL ratio: 0.01214, Grade: B\",\"StationNumber: 97LTB06, Year: 1997, PEL ratio: 0.01536, Grade: B\",\"StationNumber: 97LTB07, Year: 1997, PEL ratio: 0.00826, Grade: B\",\"StationNumber: 97LTB09, Year: 1997, PEL ratio: 0.01935, Grade: B\",\"StationNumber: 97LTB10, Year: 1997, PEL ratio: 0.02574, Grade: C\",\"StationNumber: 97LTB11, Year: 1997, PEL ratio: 0.0151, Grade: B\",\"StationNumber: 97LTB12, Year: 1997, PEL ratio: 0.01318, Grade: B\",\"StationNumber: 97LTB13, Year: 1997, PEL ratio: 0.00402, Grade: A\",\"StationNumber: 97LTB15, Year: 1997, PEL ratio: 0.00573, Grade: A\",\"StationNumber: 97LTB17, Year: 1997, PEL ratio: 0.00975, Grade: B\",\"StationNumber: 97LTB18, Year: 1997, PEL ratio: 0.00942, Grade: B\",\"StationNumber: 97LTB19, Year: 1997, PEL ratio: 0.00972, Grade: B\",\"StationNumber: 97LTB20, Year: 1997, PEL ratio: 0.00464, Grade: A\",\"StationNumber: 97LTB21, Year: 1997, PEL ratio: 0.00565, Grade: A\",\"StationNumber: 97LTB23, Year: 1997, PEL ratio: 0.01146, Grade: B\",\"StationNumber: 97LTB24, Year: 1997, PEL ratio: 0.00376, Grade: A\",\"StationNumber: 97LTB25, Year: 1997, PEL ratio: 0.00699, Grade: A\",\"StationNumber: 97LTB26, Year: 1997, PEL ratio: 0.00218, Grade: A\",\"StationNumber: 97LTB28, Year: 1997, PEL ratio: 0.00444, Grade: A\",\"StationNumber: 97MR09, Year: 1997, PEL ratio: 0.01198, Grade: B\",\"StationNumber: 97MR10, Year: 1997, PEL ratio: 0.02239, Grade: C\",\"StationNumber: 97MR11, Year: 1997, PEL ratio: 0.04743, Grade: C\",\"StationNumber: 97MR12, Year: 1997, PEL ratio: 0.04395, Grade: C\",\"StationNumber: 97MR13, Year: 1997, PEL ratio: 0.0476, Grade: C\",\"StationNumber: 97MR14, Year: 1997, PEL ratio: 0.08134, Grade: C\",\"StationNumber: 97MR15, Year: 1997, PEL ratio: 0.02453, Grade: C\",\"StationNumber: 97MR16, Year: 1997, PEL ratio: 0.05074, Grade: C\",\"StationNumber: 97MR17, Year: 1997, PEL ratio: 0.02537, Grade: C\",\"StationNumber: 97MR18, Year: 1997, PEL ratio: 0.00736, Grade: A\",\"StationNumber: 97MR19, Year: 1997, PEL ratio: 0.04387, Grade: C\",\"StationNumber: 97MR20, Year: 1997, PEL ratio: 0.05581, Grade: C\",\"StationNumber: 97MR21, Year: 1997, PEL ratio: 0.04083, Grade: C\",\"StationNumber: 97MTB02, Year: 1997, PEL ratio: 0.02552, Grade: C\",\"StationNumber: 97MTB03, Year: 1997, PEL ratio: 0.00549, Grade: A\",\"StationNumber: 97MTB04, Year: 1997, PEL ratio: 0.0071, Grade: A\",\"StationNumber: 97MTB05, Year: 1997, PEL ratio: 0.00589, Grade: A\",\"StationNumber: 97MTB07, Year: 1997, PEL ratio: 0.01701, Grade: B\",\"StationNumber: 97MTB09, Year: 1997, PEL ratio: 0.01016, Grade: B\",\"StationNumber: 97MTB10, Year: 1997, PEL ratio: 0.01151, Grade: B\",\"StationNumber: 97MTB12, Year: 1997, PEL ratio: 0.01224, Grade: B\",\"StationNumber: 97MTB14, Year: 1997, PEL ratio: 0.04718, Grade: C\",\"StationNumber: 97MTB15, Year: 1997, PEL ratio: 0.00923, Grade: B\",\"StationNumber: 97MTB16, Year: 1997, PEL ratio: 0.02076, Grade: C\",\"StationNumber: 97MTB17, Year: 1997, PEL ratio: 0.01049, Grade: B\",\"StationNumber: 97MTB18, Year: 1997, PEL ratio: 0.00491, Grade: A\",\"StationNumber: 97MTB19, Year: 1997, PEL ratio: 0.00548, Grade: A\",\"StationNumber: 97MTB23, Year: 1997, PEL ratio: 0.01245, Grade: B\",\"StationNumber: 97MTB24, Year: 1997, PEL ratio: 0.01036, Grade: B\",\"StationNumber: 97MTB25, Year: 1997, PEL ratio: 0.0052, Grade: A\",\"StationNumber: 97MTB26, Year: 1997, PEL ratio: 0.00284, Grade: A\",\"StationNumber: 97MTB30, Year: 1997, PEL ratio: 0.00464, Grade: A\",\"StationNumber: 97MTB31, Year: 1997, PEL ratio: 0.00402, Grade: A\",\"StationNumber: 97MTB32, Year: 1997, PEL ratio: 0.02691, Grade: C\",\"StationNumber: 97MTB35, Year: 1997, PEL ratio: 0.00417, Grade: A\",\"StationNumber: 97OTB03, Year: 1997, PEL ratio: 0.08428, Grade: C\",\"StationNumber: 97OTB06, Year: 1997, PEL ratio: 0.00508, Grade: A\",\"StationNumber: 97OTB07, Year: 1997, PEL ratio: 0.04147, Grade: C\",\"StationNumber: 97OTB11, Year: 1997, PEL ratio: 0.01536, Grade: B\",\"StationNumber: 97OTB12, Year: 1997, PEL ratio: 0.00901, Grade: B\",\"StationNumber: 97OTB13, Year: 1997, PEL ratio: 0.02195, Grade: C\",\"StationNumber: 97OTB17, Year: 1997, PEL ratio: 0.02135, Grade: C\",\"StationNumber: 97OTB18, Year: 1997, PEL ratio: 0.01639, Grade: B\",\"StationNumber: 97OTB19, Year: 1997, PEL ratio: 0.00365, Grade: A\",\"StationNumber: 97OTB20, Year: 1997, PEL ratio: 0.0108, Grade: B\",\"StationNumber: 97OTB22, Year: 1997, PEL ratio: 0.00594, Grade: A\",\"StationNumber: 97OTB23, Year: 1997, PEL ratio: 0.00358, Grade: A\",\"StationNumber: 97OTB24, Year: 1997, PEL ratio: 0.01809, Grade: B\",\"StationNumber: 97OTB26, Year: 1997, PEL ratio: 0.00369, Grade: A\",\"StationNumber: 97OTB27, Year: 1997, PEL ratio: 0.0027, Grade: A\",\"StationNumber: 97OTB29, Year: 1997, PEL ratio: 0.00729, Grade: A\",\"StationNumber: 97TCB01, Year: 1997, PEL ratio: 0.03736, Grade: C\",\"StationNumber: 97TCB02, Year: 1997, PEL ratio: 0.05752, Grade: C\",\"StationNumber: 97TCB03, Year: 1997, PEL ratio: 0.07413, Grade: C\",\"StationNumber: 97TCB04, Year: 1997, PEL ratio: 0.0463, Grade: C\",\"StationNumber: 97TCB05, Year: 1997, PEL ratio: 0.03402, Grade: C\",\"StationNumber: 97TCB06, Year: 1997, PEL ratio: 0.03071, Grade: C\",\"StationNumber: 97TCB07, Year: 1997, PEL ratio: 0.06132, Grade: C\",\"StationNumber: 97TCB08, Year: 1997, PEL ratio: 0.0461, Grade: C\",\"StationNumber: 98BCB06, Year: 1998, PEL ratio: 0.00538, Grade: A\",\"StationNumber: 98BCB09, Year: 1998, PEL ratio: 0.00305, Grade: A\",\"StationNumber: 98BCB11, Year: 1998, PEL ratio: 0.00393, Grade: A\",\"StationNumber: 98BCB12, Year: 1998, PEL ratio: 0.02037, Grade: B\",\"StationNumber: 98BCB15, Year: 1998, PEL ratio: 0.0045, Grade: A\",\"StationNumber: 98BCB17, Year: 1998, PEL ratio: 0.01586, Grade: B\",\"StationNumber: 98BCB21, Year: 1998, PEL ratio: 0.0041, Grade: A\",\"StationNumber: 98BCB27, Year: 1998, PEL ratio: 0.01015, Grade: B\",\"StationNumber: 98BCB28, Year: 1998, PEL ratio: 0.0098, Grade: B\",\"StationNumber: 98BCB32, Year: 1998, PEL ratio: 0.00254, Grade: A\",\"StationNumber: 98BCB38, Year: 1998, PEL ratio: 0.00578, Grade: A\",\"StationNumber: 98BCB40, Year: 1998, PEL ratio: 0.00383, Grade: A\",\"StationNumber: 98BCB43, Year: 1998, PEL ratio: 0.00199, Grade: A\",\"StationNumber: 98BCB46, Year: 1998, PEL ratio: 0.01378, Grade: B\",\"StationNumber: 98BCB57/1, Year: 1998, PEL ratio: 0.06999, Grade: C\",\"StationNumber: 98BCB58/1, Year: 1998, PEL ratio: 0.1367, Grade: D\",\"StationNumber: 98BCB58/2, Year: 1998, PEL ratio: 0.02526, Grade: C\",\"StationNumber: 98BCB59/1, Year: 1998, PEL ratio: 0.00363, Grade: A\",\"StationNumber: 98BCB59/2, Year: 1998, PEL ratio: 0.02915, Grade: C\",\"StationNumber: 98BCB60/2, Year: 1998, PEL ratio: 0.00939, Grade: B\",\"StationNumber: 98BCB60/4, Year: 1998, PEL ratio: 0.02529, Grade: C\",\"StationNumber: 98HB003, Year: 1998, PEL ratio: 0.0024, Grade: A\",\"StationNumber: 98HB006, Year: 1998, PEL ratio: 0.97324, Grade: F\",\"StationNumber: 98HB014, Year: 1998, PEL ratio: 0.0317, Grade: C\",\"StationNumber: 98HB016, Year: 1998, PEL ratio: 0.11511, Grade: D\",\"StationNumber: 98HB017, Year: 1998, PEL ratio: 0.00283, Grade: A\",\"StationNumber: 98HB024, Year: 1998, PEL ratio: 0.03375, Grade: C\",\"StationNumber: 98HB030, Year: 1998, PEL ratio: 0.00478, Grade: A\",\"StationNumber: 98HB049, Year: 1998, PEL ratio: 0.00685, Grade: A\",\"StationNumber: 98HB052, Year: 1998, PEL ratio: 0.04381, Grade: C\",\"StationNumber: 98HB056, Year: 1998, PEL ratio: 0.00367, Grade: A\",\"StationNumber: 98HB059, Year: 1998, PEL ratio: 0.00786, Grade: B\",\"StationNumber: 98HB069, Year: 1998, PEL ratio: 0.01266, Grade: B\",\"StationNumber: 98HB080, Year: 1998, PEL ratio: 0.10159, Grade: D\",\"StationNumber: 98HB089, Year: 1998, PEL ratio: 0.01263, Grade: B\",\"StationNumber: 98HB130, Year: 1998, PEL ratio: 0.00708, Grade: A\",\"StationNumber: 98HB153, Year: 1998, PEL ratio: 0.00364, Grade: A\",\"StationNumber: 98HB171, Year: 1998, PEL ratio: 0.07363, Grade: C\",\"StationNumber: 98HB180, Year: 1998, PEL ratio: 0.02965, Grade: C\",\"StationNumber: 98HB224, Year: 1998, PEL ratio: 0.0387, Grade: C\",\"StationNumber: 98HB237, Year: 1998, PEL ratio: 0.00906, Grade: B\",\"StationNumber: 98HB245, Year: 1998, PEL ratio: 0.02123, Grade: C\",\"StationNumber: 98HB252, Year: 1998, PEL ratio: 0.04475, Grade: C\",\"StationNumber: 98HB280, Year: 1998, PEL ratio: 0.01676, Grade: B\",\"StationNumber: 98HB789, Year: 1998, PEL ratio: 0.07519, Grade: C\",\"StationNumber: 98HBDIcanal, Year: 1998, PEL ratio: 0.0396, Grade: C\",\"StationNumber: 98HBspark, Year: 1998, PEL ratio: 0.12448, Grade: D\",\"StationNumber: 98LTB0014, Year: 1998, PEL ratio: 0.01019, Grade: B\",\"StationNumber: 98LTB0025, Year: 1998, PEL ratio: 0.00349, Grade: A\",\"StationNumber: 98LTB0049, Year: 1998, PEL ratio: 0.0015, Grade: A\",\"StationNumber: 98LTB0095, Year: 1998, PEL ratio: 0.00272, Grade: A\",\"StationNumber: 98LTB0123, Year: 1998, PEL ratio: 0.0128, Grade: B\",\"StationNumber: 98LTB0144, Year: 1998, PEL ratio: 0.00354, Grade: A\",\"StationNumber: 98LTB0151, Year: 1998, PEL ratio: 0.01302, Grade: B\",\"StationNumber: 98LTB0168, Year: 1998, PEL ratio: 0.00254, Grade: A\",\"StationNumber: 98LTB0183, Year: 1998, PEL ratio: 0.00534, Grade: A\",\"StationNumber: 98LTB0223, Year: 1998, PEL ratio: 0.00257, Grade: A\",\"StationNumber: 98LTB0244, Year: 1998, PEL ratio: 0.00145, Grade: A\",\"StationNumber: 98LTB0273, Year: 1998, PEL ratio: 0.00217, Grade: A\",\"StationNumber: 98LTB0307, Year: 1998, PEL ratio: 0.00156, Grade: A\",\"StationNumber: 98LTB0364, Year: 1998, PEL ratio: 0.00282, Grade: A\",\"StationNumber: 98LTB0393, Year: 1998, PEL ratio: 0.00144, Grade: A\",\"StationNumber: 98LTB0762, Year: 1998, PEL ratio: 0.00278, Grade: A\",\"StationNumber: 98LTB1057, Year: 1998, PEL ratio: 0.00277, Grade: A\",\"StationNumber: 98MR09, Year: 1998, PEL ratio: 0.00264, Grade: A\",\"StationNumber: 98MR10, Year: 1998, PEL ratio: 0.00747, Grade: A\",\"StationNumber: 98MR11, Year: 1998, PEL ratio: 0.02354, Grade: C\",\"StationNumber: 98MR12, Year: 1998, PEL ratio: 0.01409, Grade: B\",\"StationNumber: 98MR13, Year: 1998, PEL ratio: 0.04647, Grade: C\",\"StationNumber: 98MR14, Year: 1998, PEL ratio: 0.01126, Grade: B\",\"StationNumber: 98MR15, Year: 1998, PEL ratio: 0.01005, Grade: B\",\"StationNumber: 98MR16, Year: 1998, PEL ratio: 0.0221, Grade: C\",\"StationNumber: 98MR17, Year: 1998, PEL ratio: 0.01136, Grade: B\",\"StationNumber: 98MR18, Year: 1998, PEL ratio: 0.00778, Grade: B\",\"StationNumber: 98MR19, Year: 1998, PEL ratio: 0.00838, Grade: B\",\"StationNumber: 98MR20, Year: 1998, PEL ratio: 0.00821, Grade: B\",\"StationNumber: 98MR21, Year: 1998, PEL ratio: 0.18896, Grade: D\",\"StationNumber: 98MTB0032, Year: 1998, PEL ratio: 0.0044, Grade: A\",\"StationNumber: 98MTB0035, Year: 1998, PEL ratio: 0.02315, Grade: C\",\"StationNumber: 98MTB0052, Year: 1998, PEL ratio: 0.01441, Grade: B\",\"StationNumber: 98MTB0067, Year: 1998, PEL ratio: 0.00681, Grade: A\",\"StationNumber: 98MTB0090, Year: 1998, PEL ratio: 0.00845, Grade: B\",\"StationNumber: 98MTB0103, Year: 1998, PEL ratio: 0.00342, Grade: A\",\"StationNumber: 98MTB0133, Year: 1998, PEL ratio: 0.00293, Grade: A\",\"StationNumber: 98MTB0187, Year: 1998, PEL ratio: 0.0175, Grade: B\",\"StationNumber: 98MTB0191, Year: 1998, PEL ratio: 0.29254, Grade: F\",\"StationNumber: 98MTB0208, Year: 1998, PEL ratio: 0.00527, Grade: A\",\"StationNumber: 98MTB0270, Year: 1998, PEL ratio: 0.00339, Grade: A\",\"StationNumber: 98MTB0275, Year: 1998, PEL ratio: 0.00228, Grade: A\",\"StationNumber: 98MTB0283, Year: 1998, PEL ratio: 0.00476, Grade: A\",\"StationNumber: 98MTB0322, Year: 1998, PEL ratio: 0.00756, Grade: B\",\"StationNumber: 98MTB0331, Year: 1998, PEL ratio: 0.00226, Grade: A\",\"StationNumber: 98MTB0416, Year: 1998, PEL ratio: 0.01759, Grade: B\",\"StationNumber: 98MTB0460, Year: 1998, PEL ratio: 0.00109, Grade: A\",\"StationNumber: 98MTB0688, Year: 1998, PEL ratio: 0.00187, Grade: A\",\"StationNumber: 98MTB0694, Year: 1998, PEL ratio: 0.00183, Grade: A\",\"StationNumber: 98MTB1036, Year: 1998, PEL ratio: 0.00193, Grade: A\",\"StationNumber: 98OTB0036, Year: 1998, PEL ratio: 0.0377, Grade: C\",\"StationNumber: 98OTB0039, Year: 1998, PEL ratio: 0.01561, Grade: B\",\"StationNumber: 98OTB0048, Year: 1998, PEL ratio: 0.00858, Grade: B\",\"StationNumber: 98OTB0056, Year: 1998, PEL ratio: 0.01204, Grade: B\",\"StationNumber: 98OTB0125, Year: 1998, PEL ratio: 0.00279, Grade: A\",\"StationNumber: 98OTB0177, Year: 1998, PEL ratio: 0.00429, Grade: A\",\"StationNumber: 98OTB0185, Year: 1998, PEL ratio: 0.00276, Grade: A\",\"StationNumber: 98OTB0199, Year: 1998, PEL ratio: 0.0051, Grade: A\",\"StationNumber: 98OTB0232, Year: 1998, PEL ratio: 0.00966, Grade: B\",\"StationNumber: 98OTB0239, Year: 1998, PEL ratio: 0.00934, Grade: B\",\"StationNumber: 98OTB0274, Year: 1998, PEL ratio: 0.00653, Grade: A\",\"StationNumber: 98OTB0425, Year: 1998, PEL ratio: 0.00388, Grade: A\",\"StationNumber: 98OTB0596, Year: 1998, PEL ratio: 0.13969, Grade: D\",\"StationNumber: 98OTB0721, Year: 1998, PEL ratio: 0.01378, Grade: B\",\"StationNumber: 98OTB1140, Year: 1998, PEL ratio: 0.01913, Grade: B\",\"StationNumber: 98OTB1227, Year: 1998, PEL ratio: 0.00236, Grade: A\",\"StationNumber: 98TCB01, Year: 1998, PEL ratio: 0.00905, Grade: B\",\"StationNumber: 98TCB02, Year: 1998, PEL ratio: 0.00594, Grade: A\",\"StationNumber: 98TCB04, Year: 1998, PEL ratio: 0.0067, Grade: A\",\"StationNumber: 98TCB05, Year: 1998, PEL ratio: 0.00686, Grade: A\",\"StationNumber: 98TCB06, Year: 1998, PEL ratio: 0.00741, Grade: A\",\"StationNumber: 98TCB07, Year: 1998, PEL ratio: 0.0084, Grade: B\",\"StationNumber: 98TCB08, Year: 1998, PEL ratio: 0.02781, Grade: C\",\"StationNumber: 99BCB2025, Year: 1999, PEL ratio: 0.005, Grade: A\",\"StationNumber: 99BCB2041, Year: 1999, PEL ratio: 0.00537, Grade: A\",\"StationNumber: 99BCB2063, Year: 1999, PEL ratio: 0.01586, Grade: B\",\"StationNumber: 99BCB2069, Year: 1999, PEL ratio: 0.00888, Grade: B\",\"StationNumber: 99BCB2070, Year: 1999, PEL ratio: 0.00858, Grade: B\",\"StationNumber: 99BCB2086, Year: 1999, PEL ratio: 0.00471, Grade: A\",\"StationNumber: 99BCB2094, Year: 1999, PEL ratio: 0.02788, Grade: C\",\"StationNumber: 99BCB2115, Year: 1999, PEL ratio: 0.01214, Grade: B\",\"StationNumber: 99BCB2132, Year: 1999, PEL ratio: 0.00326, Grade: A\",\"StationNumber: 99BCB2295, Year: 1999, PEL ratio: 0.00282, Grade: A\",\"StationNumber: 99BCB2358, Year: 1999, PEL ratio: 0.00626, Grade: A\",\"StationNumber: 99BCB2423, Year: 1999, PEL ratio: 0.00676, Grade: A\",\"StationNumber: 99BCB2514, Year: 1999, PEL ratio: 0.00801, Grade: B\",\"StationNumber: 99BCB2585, Year: 1999, PEL ratio: 0.00657, Grade: A\",\"StationNumber: 99BCB57/1, Year: 1999, PEL ratio: 0.05417, Grade: C\",\"StationNumber: 99BCB58/1, Year: 1999, PEL ratio: 0.09826, Grade: D\",\"StationNumber: 99BCB58/2, Year: 1999, PEL ratio: 0.01409, Grade: B\",\"StationNumber: 99BCB59/1, Year: 1999, PEL ratio: 0.0028, Grade: A\",\"StationNumber: 99BCB59/2, Year: 1999, PEL ratio: 0.02713, Grade: C\",\"StationNumber: 99BCB60/2, Year: 1999, PEL ratio: 0.0045, Grade: A\",\"StationNumber: 99BCB60/4, Year: 1999, PEL ratio: 0.0094, Grade: B\",\"StationNumber: 99HB2001, Year: 1999, PEL ratio: 0.00875, Grade: B\",\"StationNumber: 99HB2012, Year: 1999, PEL ratio: 0.05472, Grade: C\",\"StationNumber: 99HB2013, Year: 1999, PEL ratio: 0.01091, Grade: B\",\"StationNumber: 99HB2019, Year: 1999, PEL ratio: 0.01342, Grade: B\",\"StationNumber: 99HB2040, Year: 1999, PEL ratio: 0.00861, Grade: B\",\"StationNumber: 99HB2041, Year: 1999, PEL ratio: 0.00984, Grade: B\",\"StationNumber: 99HB2043, Year: 1999, PEL ratio: 0.00514, Grade: A\",\"StationNumber: 99HB2044, Year: 1999, PEL ratio: 0.01258, Grade: B\",\"StationNumber: 99HB2051, Year: 1999, PEL ratio: 0.04843, Grade: C\",\"StationNumber: 99HB2055, Year: 1999, PEL ratio: 0.01863, Grade: B\",\"StationNumber: 99HB2058, Year: 1999, PEL ratio: 0.1295, Grade: D\",\"StationNumber: 99HB2061, Year: 1999, PEL ratio: 0.66795, Grade: F\",\"StationNumber: 99HB2085, Year: 1999, PEL ratio: 0.11485, Grade: D\",\"StationNumber: 99HB2094, Year: 1999, PEL ratio: 0.00687, Grade: A\",\"StationNumber: 99HB2124, Year: 1999, PEL ratio: 0.08012, Grade: C\",\"StationNumber: 99HB2157, Year: 1999, PEL ratio: 0.01348, Grade: B\",\"StationNumber: 99HB2176, Year: 1999, PEL ratio: 0.07747, Grade: C\",\"StationNumber: 99HB2207, Year: 1999, PEL ratio: 0.09551, Grade: D\",\"StationNumber: 99HB2214, Year: 1999, PEL ratio: 0.00568, Grade: A\",\"StationNumber: 99HB2233, Year: 1999, PEL ratio: 0.04361, Grade: C\",\"StationNumber: 99HB2393, Year: 1999, PEL ratio: 0.01757, Grade: B\",\"StationNumber: 99HB2445, Year: 1999, PEL ratio: 0.0179, Grade: B\",\"StationNumber: 99HB2757, Year: 1999, PEL ratio: 0.01124, Grade: B\",\"StationNumber: 99LTB2014, Year: 1999, PEL ratio: 0.00357, Grade: A\",\"StationNumber: 99LTB2021, Year: 1999, PEL ratio: 0.02082, Grade: C\",\"StationNumber: 99LTB2041, Year: 1999, PEL ratio: 0.01184, Grade: B\",\"StationNumber: 99LTB2071, Year: 1999, PEL ratio: 0.04983, Grade: C\",\"StationNumber: 99LTB2112, Year: 1999, PEL ratio: 0.01, Grade: B\",\"StationNumber: 99LTB2124, Year: 1999, PEL ratio: 0.00203, Grade: A\",\"StationNumber: 99LTB2203, Year: 1999, PEL ratio: 0.03476, Grade: C\",\"StationNumber: 99LTB2214, Year: 1999, PEL ratio: 0.00338, Grade: A\",\"StationNumber: 99LTB2247, Year: 1999, PEL ratio: 0.00398, Grade: A\",\"StationNumber: 99LTB2267, Year: 1999, PEL ratio: 0.00762, Grade: B\",\"StationNumber: 99LTB2277, Year: 1999, PEL ratio: 0.00489, Grade: A\",\"StationNumber: 99LTB2290, Year: 1999, PEL ratio: 0.00641, Grade: A\",\"StationNumber: 99LTB2327, Year: 1999, PEL ratio: 0.00354, Grade: A\",\"StationNumber: 99LTB2546, Year: 1999, PEL ratio: 0.00355, Grade: A\",\"StationNumber: 99LTB2617, Year: 1999, PEL ratio: 0.0074, Grade: A\",\"StationNumber: 99LTB3020, Year: 1999, PEL ratio: 0.00328, Grade: A\",\"StationNumber: 99MR09, Year: 1999, PEL ratio: 0.00455, Grade: A\",\"StationNumber: 99MR10, Year: 1999, PEL ratio: 0.00816, Grade: B\",\"StationNumber: 99MR11, Year: 1999, PEL ratio: 0.01449, Grade: B\",\"StationNumber: 99MR12, Year: 1999, PEL ratio: 0.00376, Grade: A\",\"StationNumber: 99MR13, Year: 1999, PEL ratio: 0.00522, Grade: A\",\"StationNumber: 99MR14, Year: 1999, PEL ratio: 0.00891, Grade: B\",\"StationNumber: 99MR15, Year: 1999, PEL ratio: 0.00463, Grade: A\",\"StationNumber: 99MR16, Year: 1999, PEL ratio: 0.00967, Grade: B\",\"StationNumber: 99MR17, Year: 1999, PEL ratio: 0.00407, Grade: A\",\"StationNumber: 99MR18, Year: 1999, PEL ratio: 0.00432, Grade: A\",\"StationNumber: 99MR19, Year: 1999, PEL ratio: 0.007, Grade: A\",\"StationNumber: 99MR20, Year: 1999, PEL ratio: 0.00696, Grade: A\",\"StationNumber: 99MR21, Year: 1999, PEL ratio: 0.00917, Grade: B\",\"StationNumber: 99MTB2029, Year: 1999, PEL ratio: 0.00978, Grade: B\",\"StationNumber: 99MTB2059, Year: 1999, PEL ratio: 0.00849, Grade: B\",\"StationNumber: 99MTB2060, Year: 1999, PEL ratio: 0.00498, Grade: A\",\"StationNumber: 99MTB2108, Year: 1999, PEL ratio: 0.01361, Grade: B\",\"StationNumber: 99MTB2109, Year: 1999, PEL ratio: 0.00725, Grade: A\",\"StationNumber: 99MTB2116, Year: 1999, PEL ratio: 0.01071, Grade: B\",\"StationNumber: 99MTB2129, Year: 1999, PEL ratio: 0.00543, Grade: A\",\"StationNumber: 99MTB2149, Year: 1999, PEL ratio: 0.00588, Grade: A\",\"StationNumber: 99MTB2165, Year: 1999, PEL ratio: 0.00463, Grade: A\",\"StationNumber: 99MTB2240, Year: 1999, PEL ratio: 0.00258, Grade: A\",\"StationNumber: 99MTB2243, Year: 1999, PEL ratio: 0.00684, Grade: A\",\"StationNumber: 99MTB2244, Year: 1999, PEL ratio: 0.00704, Grade: A\",\"StationNumber: 99MTB2253, Year: 1999, PEL ratio: 0.00506, Grade: A\",\"StationNumber: 99MTB2268, Year: 1999, PEL ratio: 0.00697, Grade: A\",\"StationNumber: 99MTB2274, Year: 1999, PEL ratio: 0.00654, Grade: A\",\"StationNumber: 99MTB2291, Year: 1999, PEL ratio: 0.00339, Grade: A\",\"StationNumber: 99MTB2358, Year: 1999, PEL ratio: 0.02137, Grade: C\",\"StationNumber: 99MTB2385, Year: 1999, PEL ratio: 0.00448, Grade: A\",\"StationNumber: 99MTB2554, Year: 1999, PEL ratio: 0.00369, Grade: A\",\"StationNumber: 99MTB2598, Year: 1999, PEL ratio: 0.00643, Grade: A\",\"StationNumber: 99MTB2642, Year: 1999, PEL ratio: 0.00161, Grade: A\",\"StationNumber: 99OTB2002, Year: 1999, PEL ratio: 0.00876, Grade: B\",\"StationNumber: 99OTB2005, Year: 1999, PEL ratio: 0.00294, Grade: A\",\"StationNumber: 99OTB2009, Year: 1999, PEL ratio: 0.00343, Grade: A\",\"StationNumber: 99OTB2010, Year: 1999, PEL ratio: 0.00216, Grade: A\",\"StationNumber: 99OTB2022, Year: 1999, PEL ratio: 0.00491, Grade: A\",\"StationNumber: 99OTB2045, Year: 1999, PEL ratio: 0.00455, Grade: A\",\"StationNumber: 99OTB2067, Year: 1999, PEL ratio: 0.00573, Grade: A\",\"StationNumber: 99OTB2111, Year: 1999, PEL ratio: 0.00613, Grade: A\",\"StationNumber: 99OTB2121, Year: 1999, PEL ratio: 0.00637, Grade: A\",\"StationNumber: 99OTB2225, Year: 1999, PEL ratio: 0.00677, Grade: A\",\"StationNumber: 99OTB2296, Year: 1999, PEL ratio: 0.0151, Grade: B\",\"StationNumber: 99OTB2313, Year: 1999, PEL ratio: 0.01389, Grade: B\",\"StationNumber: 99OTB2316, Year: 1999, PEL ratio: 0.02452, Grade: C\",\"StationNumber: 99OTB2331, Year: 1999, PEL ratio: 0.00962, Grade: B\",\"StationNumber: 99OTB2395, Year: 1999, PEL ratio: 0.00307, Grade: A\",\"StationNumber: 99OTB2482, Year: 1999, PEL ratio: 0.02893, Grade: C\",\"StationNumber: 99OTB2908, Year: 1999, PEL ratio: 0.00461, Grade: A\",\"StationNumber: 99OTB2994, Year: 1999, PEL ratio: 0.00236, Grade: A\",\"StationNumber: 99OTB3046, Year: 1999, PEL ratio: 0.01179, Grade: B\",\"StationNumber: 99TCB01, Year: 1999, PEL ratio: 0.00891, Grade: B\",\"StationNumber: 99TCB02, Year: 1999, PEL ratio: 0.00618, Grade: A\",\"StationNumber: 99TCB03, Year: 1999, PEL ratio: 0.01419, Grade: B\",\"StationNumber: 99TCB04, Year: 1999, PEL ratio: 0.00915, Grade: B\",\"StationNumber: 99TCB05, Year: 1999, PEL ratio: 0.00868, Grade: B\",\"StationNumber: 99TCB06, Year: 1999, PEL ratio: 0.01238, Grade: B\",\"StationNumber: 99TCB07, Year: 1999, PEL ratio: 0.01057, Grade: B\",\"StationNumber: 99TCB08, Year: 1999, PEL ratio: 0.00285, Grade: A\",\"StationNumber: 00BCB4000, Year: 2000, PEL ratio: 0.03235, Grade: C\",\"StationNumber: 00BCB4001, Year: 2000, PEL ratio: 0.03269, Grade: C\",\"StationNumber: 00BCB4004, Year: 2000, PEL ratio: 0.02038, Grade: B\",\"StationNumber: 00BCB4033, Year: 2000, PEL ratio: 0.08678, Grade: D\",\"StationNumber: 00BCB4034, Year: 2000, PEL ratio: 0.03197, Grade: C\",\"StationNumber: 00BCB4037, Year: 2000, PEL ratio: 0.02797, Grade: C\",\"StationNumber: 00BCB4038, Year: 2000, PEL ratio: 0.81297, Grade: F\",\"StationNumber: 00BCB4041, Year: 2000, PEL ratio: 0.03473, Grade: C\",\"StationNumber: 00BCB4042, Year: 2000, PEL ratio: 0.03588, Grade: C\",\"StationNumber: 00BCB4046, Year: 2000, PEL ratio: 0.03579, Grade: C\",\"StationNumber: 00BCB4079, Year: 2000, PEL ratio: 0.02888, Grade: C\",\"StationNumber: 00BCB4084, Year: 2000, PEL ratio: 0.03169, Grade: C\",\"StationNumber: 00BCB4090, Year: 2000, PEL ratio: 0.0329, Grade: C\",\"StationNumber: 00BCB4100, Year: 2000, PEL ratio: 0.03654, Grade: C\",\"StationNumber: 00BCB4124, Year: 2000, PEL ratio: 0.0309, Grade: C\",\"StationNumber: 00BCB4165, Year: 2000, PEL ratio: 0.03378, Grade: C\",\"StationNumber: 00BCB4174, Year: 2000, PEL ratio: 0.03618, Grade: C\",\"StationNumber: 00BCB4207, Year: 2000, PEL ratio: 0.03283, Grade: C\",\"StationNumber: 00BCB4268, Year: 2000, PEL ratio: 0.03803, Grade: C\",\"StationNumber: 00BCB4299, Year: 2000, PEL ratio: 0.04446, Grade: C\",\"StationNumber: 00BCB4312, Year: 2000, PEL ratio: 0.03143, Grade: C\",\"StationNumber: 00BCB58/1, Year: 2000, PEL ratio: 0.18329, Grade: D\",\"StationNumber: 00BCB58/2, Year: 2000, PEL ratio: 0.04382, Grade: C\",\"StationNumber: 00BCB59/1, Year: 2000, PEL ratio: 0.04353, Grade: C\",\"StationNumber: 00BCB59/2, Year: 2000, PEL ratio: 0.06279, Grade: C\",\"StationNumber: 00BCB60/2, Year: 2000, PEL ratio: 0.04105, Grade: C\",\"StationNumber: 00BCB60/4, Year: 2000, PEL ratio: 0.04149, Grade: C\",\"StationNumber: 00HB4002, Year: 2000, PEL ratio: 0.04724, Grade: C\",\"StationNumber: 00HB4006, Year: 2000, PEL ratio: 0.04834, Grade: C\",\"StationNumber: 00HB4019, Year: 2000, PEL ratio: 0.10805, Grade: D\",\"StationNumber: 00HB4023, Year: 2000, PEL ratio: 0.0462, Grade: C\",\"StationNumber: 00HB4032, Year: 2000, PEL ratio: 0.04776, Grade: C\",\"StationNumber: 00HB4033, Year: 2000, PEL ratio: 0.05791, Grade: C\",\"StationNumber: 00HB4038, Year: 2000, PEL ratio: 0.04416, Grade: C\",\"StationNumber: 00HB4047, Year: 2000, PEL ratio: 0.04742, Grade: C\",\"StationNumber: 00HB4058, Year: 2000, PEL ratio: 0.01604, Grade: B\",\"StationNumber: 00HB4077, Year: 2000, PEL ratio: 0.05066, Grade: C\",\"StationNumber: 00HB4082, Year: 2000, PEL ratio: 0.04468, Grade: C\",\"StationNumber: 00HB4083, Year: 2000, PEL ratio: 0.04996, Grade: C\",\"StationNumber: 00HB4093, Year: 2000, PEL ratio: 0.06406, Grade: C\",\"StationNumber: 00HB4094, Year: 2000, PEL ratio: 0.06062, Grade: C\",\"StationNumber: 00HB4100, Year: 2000, PEL ratio: 0.04297, Grade: C\",\"StationNumber: 00HB4106, Year: 2000, PEL ratio: 0.09251, Grade: D\",\"StationNumber: 00HB4144, Year: 2000, PEL ratio: 0.53451, Grade: F\",\"StationNumber: 00HB4152, Year: 2000, PEL ratio: 0.04469, Grade: C\",\"StationNumber: 00HB4267, Year: 2000, PEL ratio: 0.06204, Grade: C\",\"StationNumber: 00HB4291, Year: 2000, PEL ratio: 0.05424, Grade: C\",\"StationNumber: 00HB4316, Year: 2000, PEL ratio: 0.05501, Grade: C\",\"StationNumber: 00HB4505, Year: 2000, PEL ratio: 0.06045, Grade: C\",\"StationNumber: 00LTB4039, Year: 2000, PEL ratio: 0.04606, Grade: C\",\"StationNumber: 00LTB4051, Year: 2000, PEL ratio: 0.19124, Grade: D\",\"StationNumber: 00LTB4066, Year: 2000, PEL ratio: 0.05414, Grade: C\",\"StationNumber: 00LTB4117, Year: 2000, PEL ratio: 0.05562, Grade: C\",\"StationNumber: 00LTB4151, Year: 2000, PEL ratio: 0.03939, Grade: C\",\"StationNumber: 00LTB4185, Year: 2000, PEL ratio: 0.04507, Grade: C\",\"StationNumber: 00LTB4286, Year: 2000, PEL ratio: 0.05463, Grade: C\",\"StationNumber: 00LTB4340, Year: 2000, PEL ratio: 0.05064, Grade: C\",\"StationNumber: 00LTB4484, Year: 2000, PEL ratio: 0.0517, Grade: C\",\"StationNumber: 00LTB4487, Year: 2000, PEL ratio: 0.04958, Grade: C\",\"StationNumber: 00LTB4513, Year: 2000, PEL ratio: 0.05351, Grade: C\",\"StationNumber: 00LTB4529, Year: 2000, PEL ratio: 0.049, Grade: C\",\"StationNumber: 00LTB4536, Year: 2000, PEL ratio: 0.05145, Grade: C\",\"StationNumber: 00LTB4637, Year: 2000, PEL ratio: 0.04148, Grade: C\",\"StationNumber: 00LTB4677, Year: 2000, PEL ratio: 0.04906, Grade: C\",\"StationNumber: 00LTB4730, Year: 2000, PEL ratio: 0.04835, Grade: C\",\"StationNumber: 00LTB4749, Year: 2000, PEL ratio: 0.04495, Grade: C\",\"StationNumber: 00MR09, Year: 2000, PEL ratio: 0.04919, Grade: C\",\"StationNumber: 00MR10, Year: 2000, PEL ratio: 0.06403, Grade: C\",\"StationNumber: 00MR11, Year: 2000, PEL ratio: 0.05939, Grade: C\",\"StationNumber: 00MR12, Year: 2000, PEL ratio: 0.05823, Grade: C\",\"StationNumber: 00MR13, Year: 2000, PEL ratio: 0.06481, Grade: C\",\"StationNumber: 00MR14, Year: 2000, PEL ratio: 0.0737, Grade: C\",\"StationNumber: 00MR15, Year: 2000, PEL ratio: 0.0527, Grade: C\",\"StationNumber: 00MR16, Year: 2000, PEL ratio: 0.08249, Grade: C\",\"StationNumber: 00MR17, Year: 2000, PEL ratio: 0.08444, Grade: C\",\"StationNumber: 00MR18, Year: 2000, PEL ratio: 0.08809, Grade: D\",\"StationNumber: 00MR19, Year: 2000, PEL ratio: 0.08127, Grade: C\",\"StationNumber: 00MR20, Year: 2000, PEL ratio: 0.11393, Grade: D\",\"StationNumber: 00MR21, Year: 2000, PEL ratio: 0.07841, Grade: C\",\"StationNumber: 00MTB4030, Year: 2000, PEL ratio: 0.07289, Grade: C\",\"StationNumber: 00MTB4032, Year: 2000, PEL ratio: 0.04097, Grade: C\",\"StationNumber: 00MTB4041, Year: 2000, PEL ratio: 0.04387, Grade: C\",\"StationNumber: 00MTB4061, Year: 2000, PEL ratio: 0.05053, Grade: C\",\"StationNumber: 00MTB4072, Year: 2000, PEL ratio: 0.04819, Grade: C\",\"StationNumber: 00MTB4086, Year: 2000, PEL ratio: 0.03955, Grade: C\",\"StationNumber: 00MTB4090, Year: 2000, PEL ratio: 0.33753, Grade: F\",\"StationNumber: 00MTB4098, Year: 2000, PEL ratio: 0.0477, Grade: C\",\"StationNumber: 00MTB4100, Year: 2000, PEL ratio: 0.05472, Grade: C\",\"StationNumber: 00MTB4106, Year: 2000, PEL ratio: 0.04444, Grade: C\",\"StationNumber: 00MTB4159, Year: 2000, PEL ratio: 0.0458, Grade: C\",\"StationNumber: 00MTB4181, Year: 2000, PEL ratio: 0.05132, Grade: C\",\"StationNumber: 00MTB4193, Year: 2000, PEL ratio: 0.03968, Grade: C\",\"StationNumber: 00MTB4201, Year: 2000, PEL ratio: 0.05155, Grade: C\",\"StationNumber: 00MTB4249, Year: 2000, PEL ratio: 0.033, Grade: C\",\"StationNumber: 00MTB4265, Year: 2000, PEL ratio: 0.04253, Grade: C\",\"StationNumber: 00MTB4310, Year: 2000, PEL ratio: 0.04594, Grade: C\",\"StationNumber: 00MTB4363, Year: 2000, PEL ratio: 0.07539, Grade: C\",\"StationNumber: 00MTB4504, Year: 2000, PEL ratio: 0.04349, Grade: C\",\"StationNumber: 00MTB4584, Year: 2000, PEL ratio: 0.04498, Grade: C\",\"StationNumber: 00MTB4653, Year: 2000, PEL ratio: 0.04232, Grade: C\",\"StationNumber: 00MTB4845, Year: 2000, PEL ratio: 0.04253, Grade: C\",\"StationNumber: 00MTB5125, Year: 2000, PEL ratio: 0.03946, Grade: C\",\"StationNumber: 00OTB4011, Year: 2000, PEL ratio: 0.03964, Grade: C\",\"StationNumber: 00OTB4019, Year: 2000, PEL ratio: 0.04292, Grade: C\",\"StationNumber: 00OTB4037, Year: 2000, PEL ratio: 0.05343, Grade: C\",\"StationNumber: 00OTB4040, Year: 2000, PEL ratio: 0.04909, Grade: C\",\"StationNumber: 00OTB4044, Year: 2000, PEL ratio: 0.04244, Grade: C\",\"StationNumber: 00OTB4096, Year: 2000, PEL ratio: 0.03974, Grade: C\",\"StationNumber: 00OTB4105, Year: 2000, PEL ratio: 0.04131, Grade: C\",\"StationNumber: 00OTB4123, Year: 2000, PEL ratio: 0.06385, Grade: C\",\"StationNumber: 00OTB4132, Year: 2000, PEL ratio: 0.06645, Grade: C\",\"StationNumber: 00OTB4138, Year: 2000, PEL ratio: 0.05762, Grade: C\",\"StationNumber: 00OTB4149, Year: 2000, PEL ratio: 0.0568, Grade: C\",\"StationNumber: 00OTB4192, Year: 2000, PEL ratio: 0.03756, Grade: C\",\"StationNumber: 00OTB4217, Year: 2000, PEL ratio: 0.05579, Grade: C\",\"StationNumber: 00OTB4254, Year: 2000, PEL ratio: 0.0437, Grade: C\",\"StationNumber: 00OTB4278, Year: 2000, PEL ratio: 0.25534, Grade: D\",\"StationNumber: 00OTB4402, Year: 2000, PEL ratio: 0.0459, Grade: C\",\"StationNumber: 00OTB4407, Year: 2000, PEL ratio: 0.04964, Grade: C\",\"StationNumber: 00OTB4650, Year: 2000, PEL ratio: 0.04792, Grade: C\",\"StationNumber: 00OTB4946, Year: 2000, PEL ratio: 0.05067, Grade: C\",\"StationNumber: 00TCB01, Year: 2000, PEL ratio: 0.04699, Grade: C\",\"StationNumber: 00TCB02, Year: 2000, PEL ratio: 0.04205, Grade: C\",\"StationNumber: 00TCB03, Year: 2000, PEL ratio: 0.03651, Grade: C\",\"StationNumber: 00TCB04, Year: 2000, PEL ratio: 0.04109, Grade: C\",\"StationNumber: 00TCB05, Year: 2000, PEL ratio: 0.04353, Grade: C\",\"StationNumber: 00TCB06, Year: 2000, PEL ratio: 0.04342, Grade: C\",\"StationNumber: 00TCB07, Year: 2000, PEL ratio: 0.04274, Grade: C\",\"StationNumber: 00TCB08, Year: 2000, PEL ratio: 0.04303, Grade: C\",\"StationNumber: 01BCB57/1, Year: 2001, PEL ratio: 0.05374, Grade: C\",\"StationNumber: 01BCB58/1, Year: 2001, PEL ratio: 0.12193, Grade: D\",\"StationNumber: 01BCB58/2, Year: 2001, PEL ratio: 0.027, Grade: C\",\"StationNumber: 01BCB59/1, Year: 2001, PEL ratio: 0.02094, Grade: C\",\"StationNumber: 01BCB59/2, Year: 2001, PEL ratio: 0.04048, Grade: C\",\"StationNumber: 01BCB60/2, Year: 2001, PEL ratio: 0.01653, Grade: B\",\"StationNumber: 01BCB60/4, Year: 2001, PEL ratio: 0.01424, Grade: B\",\"StationNumber: 01BCB6001, Year: 2001, PEL ratio: 0.0563, Grade: C\",\"StationNumber: 01BCB6009, Year: 2001, PEL ratio: 0.04348, Grade: C\",\"StationNumber: 01BCB6018, Year: 2001, PEL ratio: 0.01682, Grade: B\",\"StationNumber: 01BCB6019, Year: 2001, PEL ratio: 0.01532, Grade: B\",\"StationNumber: 01BCB6031, Year: 2001, PEL ratio: 0.02161, Grade: C\",\"StationNumber: 01BCB6063, Year: 2001, PEL ratio: 0.0077, Grade: B\",\"StationNumber: 01BCB6072, Year: 2001, PEL ratio: 0.03264, Grade: C\",\"StationNumber: 01BCB6089, Year: 2001, PEL ratio: 0.02463, Grade: C\",\"StationNumber: 01BCB6109, Year: 2001, PEL ratio: 0.02845, Grade: C\",\"StationNumber: 01BCB6114, Year: 2001, PEL ratio: 0.02671, Grade: C\",\"StationNumber: 01BCB6152, Year: 2001, PEL ratio: 0.0269, Grade: C\",\"StationNumber: 01BCB6178, Year: 2001, PEL ratio: 0.02377, Grade: C\",\"StationNumber: 01BCB6190, Year: 2001, PEL ratio: 0.02239, Grade: C\",\"StationNumber: 01BCB6230, Year: 2001, PEL ratio: 0.05637, Grade: C\",\"StationNumber: 01BCB6263, Year: 2001, PEL ratio: 0.04428, Grade: C\",\"StationNumber: 01BCB6359, Year: 2001, PEL ratio: 0.04232, Grade: C\",\"StationNumber: 01HB6019, Year: 2001, PEL ratio: 0.13163, Grade: D\",\"StationNumber: 01HB6022, Year: 2001, PEL ratio: 0.07712, Grade: C\",\"StationNumber: 01HB6032, Year: 2001, PEL ratio: 0.03892, Grade: C\",\"StationNumber: 01HB6035, Year: 2001, PEL ratio: 0.06366, Grade: C\",\"StationNumber: 01HB6045, Year: 2001, PEL ratio: 0.04136, Grade: C\",\"StationNumber: 01HB6064, Year: 2001, PEL ratio: 0.08868, Grade: D\",\"StationNumber: 01HB6066, Year: 2001, PEL ratio: 0.04113, Grade: C\",\"StationNumber: 01HB6087, Year: 2001, PEL ratio: 0.07944, Grade: C\",\"StationNumber: 01HB6093, Year: 2001, PEL ratio: 0.0345, Grade: C\",\"StationNumber: 01HB6102, Year: 2001, PEL ratio: 0.04233, Grade: C\",\"StationNumber: 01HB6108, Year: 2001, PEL ratio: 0.07274, Grade: C\",\"StationNumber: 01HB6131, Year: 2001, PEL ratio: 0.03937, Grade: C\",\"StationNumber: 01HB6140, Year: 2001, PEL ratio: 0.03728, Grade: C\",\"StationNumber: 01HB6145, Year: 2001, PEL ratio: 0.03711, Grade: C\",\"StationNumber: 01HB6159, Year: 2001, PEL ratio: 0.05123, Grade: C\",\"StationNumber: 01HB6186, Year: 2001, PEL ratio: 0.11466, Grade: D\",\"StationNumber: 01HB6187, Year: 2001, PEL ratio: 0.03548, Grade: C\",\"StationNumber: 01HB6249, Year: 2001, PEL ratio: 0.02319, Grade: C\",\"StationNumber: 01HB6261, Year: 2001, PEL ratio: 0.04047, Grade: C\",\"StationNumber: 01HB6264, Year: 2001, PEL ratio: 0.03946, Grade: C\",\"StationNumber: 01HB6283, Year: 2001, PEL ratio: 0.03557, Grade: C\",\"StationNumber: 01HB6305, Year: 2001, PEL ratio: 0.0378, Grade: C\",\"StationNumber: 01HB6374, Year: 2001, PEL ratio: 0.09193, Grade: D\",\"StationNumber: 01HB6453, Year: 2001, PEL ratio: 0.05442, Grade: C\",\"StationNumber: 01HB6537, Year: 2001, PEL ratio: 0.03766, Grade: C\",\"StationNumber: 01LTB6026, Year: 2001, PEL ratio: 0.05204, Grade: C\",\"StationNumber: 01LTB6027, Year: 2001, PEL ratio: 0.03496, Grade: C\",\"StationNumber: 01LTB6050, Year: 2001, PEL ratio: 0.04404, Grade: C\",\"StationNumber: 01LTB6104, Year: 2001, PEL ratio: 0.0209, Grade: C\",\"StationNumber: 01LTB6120, Year: 2001, PEL ratio: 0.04069, Grade: C\",\"StationNumber: 01LTB6122, Year: 2001, PEL ratio: 0.05444, Grade: C\",\"StationNumber: 01LTB6158, Year: 2001, PEL ratio: 0.09951, Grade: D\",\"StationNumber: 01LTB6302, Year: 2001, PEL ratio: 0.04098, Grade: C\",\"StationNumber: 01LTB6346, Year: 2001, PEL ratio: 0.00189, Grade: A\",\"StationNumber: 01LTB6380, Year: 2001, PEL ratio: 0.04602, Grade: C\",\"StationNumber: 01LTB6595, Year: 2001, PEL ratio: 0.04587, Grade: C\",\"StationNumber: 01LTB6869, Year: 2001, PEL ratio: 0.03876, Grade: C\",\"StationNumber: 01MR09, Year: 2001, PEL ratio: 0.00085, Grade: A\",\"StationNumber: 01MR12, Year: 2001, PEL ratio: 0.00214, Grade: A\",\"StationNumber: 01MR13, Year: 2001, PEL ratio: 0.0031, Grade: A\",\"StationNumber: 01MR14, Year: 2001, PEL ratio: 0, Grade: A\",\"StationNumber: 01MR17, Year: 2001, PEL ratio: 0, Grade: A\",\"StationNumber: 01MR18, Year: 2001, PEL ratio: 0, Grade: A\",\"StationNumber: 01MR19, Year: 2001, PEL ratio: 0, Grade: A\",\"StationNumber: 01MR20, Year: 2001, PEL ratio: 0, Grade: A\",\"StationNumber: 01MR21, Year: 2001, PEL ratio: 0, Grade: A\",\"StationNumber: 01MTB6002, Year: 2001, PEL ratio: 0.04429, Grade: C\",\"StationNumber: 01MTB6011, Year: 2001, PEL ratio: 0.03017, Grade: C\",\"StationNumber: 01MTB6014, Year: 2001, PEL ratio: 0.03931, Grade: C\",\"StationNumber: 01MTB6049, Year: 2001, PEL ratio: 0.04162, Grade: C\",\"StationNumber: 01MTB6059, Year: 2001, PEL ratio: 0.03202, Grade: C\",\"StationNumber: 01MTB6064, Year: 2001, PEL ratio: 0.02866, Grade: C\",\"StationNumber: 01MTB6068, Year: 2001, PEL ratio: 0.03092, Grade: C\",\"StationNumber: 01MTB6080, Year: 2001, PEL ratio: 0.03134, Grade: C\",\"StationNumber: 01MTB6133, Year: 2001, PEL ratio: 0.03877, Grade: C\",\"StationNumber: 01MTB6154, Year: 2001, PEL ratio: 0.03081, Grade: C\",\"StationNumber: 01MTB6188, Year: 2001, PEL ratio: 0.04865, Grade: C\",\"StationNumber: 01MTB6189, Year: 2001, PEL ratio: 0.04606, Grade: C\",\"StationNumber: 01MTB6196, Year: 2001, PEL ratio: 0.03661, Grade: C\",\"StationNumber: 01MTB6229, Year: 2001, PEL ratio: 0.03253, Grade: C\",\"StationNumber: 01MTB6257, Year: 2001, PEL ratio: 0.04035, Grade: C\",\"StationNumber: 01MTB6265, Year: 2001, PEL ratio: 0.03247, Grade: C\",\"StationNumber: 01MTB6290, Year: 2001, PEL ratio: 0.03227, Grade: C\",\"StationNumber: 01MTB6325, Year: 2001, PEL ratio: 0.03135, Grade: C\",\"StationNumber: 01MTB6327, Year: 2001, PEL ratio: 0.0343, Grade: C\",\"StationNumber: 01MTB6328, Year: 2001, PEL ratio: 0.0383, Grade: C\",\"StationNumber: 01MTB6464, Year: 2001, PEL ratio: 0.03323, Grade: C\",\"StationNumber: 01MTB6495, Year: 2001, PEL ratio: 0.03374, Grade: C\",\"StationNumber: 01MTB6527, Year: 2001, PEL ratio: 0.0365, Grade: C\",\"StationNumber: 01MTB6638, Year: 2001, PEL ratio: 0.03712, Grade: C\",\"StationNumber: 01MTB6699, Year: 2001, PEL ratio: 0.03196, Grade: C\",\"StationNumber: 01MTB7153, Year: 2001, PEL ratio: 0.02961, Grade: C\",\"StationNumber: 01OTB6010, Year: 2001, PEL ratio: 0.0366, Grade: C\",\"StationNumber: 01OTB6017, Year: 2001, PEL ratio: 0.0392, Grade: C\",\"StationNumber: 01OTB6021, Year: 2001, PEL ratio: 0.035, Grade: C\",\"StationNumber: 01OTB6022, Year: 2001, PEL ratio: 0.03556, Grade: C\",\"StationNumber: 01OTB6025, Year: 2001, PEL ratio: 0.0835, Grade: C\",\"StationNumber: 01OTB6028, Year: 2001, PEL ratio: 0.04087, Grade: C\",\"StationNumber: 01OTB6078, Year: 2001, PEL ratio: 0.03835, Grade: C\",\"StationNumber: 01OTB6103, Year: 2001, PEL ratio: 0.04375, Grade: C\",\"StationNumber: 01OTB6135, Year: 2001, PEL ratio: 0.1479, Grade: D\",\"StationNumber: 01OTB6152, Year: 2001, PEL ratio: 0.17372, Grade: D\",\"StationNumber: 01OTB6178, Year: 2001, PEL ratio: 0.04426, Grade: C\",\"StationNumber: 01OTB6186, Year: 2001, PEL ratio: 0.03888, Grade: C\",\"StationNumber: 01OTB6234, Year: 2001, PEL ratio: 0.03095, Grade: C\",\"StationNumber: 01OTB6239, Year: 2001, PEL ratio: 0.07735, Grade: C\",\"StationNumber: 01OTB6441, Year: 2001, PEL ratio: 0.03373, Grade: C\",\"StationNumber: 01OTB6784, Year: 2001, PEL ratio: 0.03879, Grade: C\",\"StationNumber: 01OTB6830, Year: 2001, PEL ratio: 0.03885, Grade: C\",\"StationNumber: 01SAFHAB, Year: 2001, PEL ratio: 0.05562, Grade: C\",\"StationNumber: 01TCB02, Year: 2001, PEL ratio: 0, Grade: A\",\"StationNumber: 01TCB03, Year: 2001, PEL ratio: 0, Grade: A\",\"StationNumber: 01TCB04, Year: 2001, PEL ratio: 0.00149, Grade: A\",\"StationNumber: 01TCB06, Year: 2001, PEL ratio: 0, Grade: A\",\"StationNumber: 01TCB07, Year: 2001, PEL ratio: 0, Grade: A\",\"StationNumber: 02BCB05, Year: 2002, PEL ratio: 0.09921, Grade: D\",\"StationNumber: 02BCB20, Year: 2002, PEL ratio: 0.03895, Grade: C\",\"StationNumber: 02BCB32, Year: 2002, PEL ratio: 0.02428, Grade: C\",\"StationNumber: 02BCB52, Year: 2002, PEL ratio: 0.03041, Grade: C\",\"StationNumber: 02BCB62, Year: 2002, PEL ratio: 0.07542, Grade: C\",\"StationNumber: 02BCB69, Year: 2002, PEL ratio: 0.02783, Grade: C\",\"StationNumber: 02BCB74, Year: 2002, PEL ratio: 0.02301, Grade: C\",\"StationNumber: 02BCB83, Year: 2002, PEL ratio: 0.02746, Grade: C\",\"StationNumber: 02BCB90, Year: 2002, PEL ratio: 0.02852, Grade: C\",\"StationNumber: 02DH09-1, Year: 2002, PEL ratio: 0.19807, Grade: D\",\"StationNumber: 02DH09-2, Year: 2002, PEL ratio: 0.12272, Grade: D\",\"StationNumber: 02DH09-3, Year: 2002, PEL ratio: 0.30626, Grade: F\",\"StationNumber: 02DH11A-1, Year: 2002, PEL ratio: 0.10175, Grade: D\",\"StationNumber: 02DH11A-2, Year: 2002, PEL ratio: 0.11172, Grade: D\",\"StationNumber: 02DH11A-3, Year: 2002, PEL ratio: 0.14465, Grade: D\",\"StationNumber: 02DH11B-1, Year: 2002, PEL ratio: 0.10113, Grade: D\",\"StationNumber: 02DH11B-4, Year: 2002, PEL ratio: 0.12537, Grade: D\",\"StationNumber: 02DH11B-5, Year: 2002, PEL ratio: 0.13789, Grade: D\",\"StationNumber: 02HB09, Year: 2002, PEL ratio: 0.16733, Grade: D\",\"StationNumber: 02HB20, Year: 2002, PEL ratio: 0.02678, Grade: C\",\"StationNumber: 02HB21, Year: 2002, PEL ratio: 0.02244, Grade: C\",\"StationNumber: 02HB27, Year: 2002, PEL ratio: 0.03078, Grade: C\",\"StationNumber: 02HB39, Year: 2002, PEL ratio: 0.21706, Grade: D\",\"StationNumber: 02HB42, Year: 2002, PEL ratio: 0.02683, Grade: C\",\"StationNumber: 02HB49, Year: 2002, PEL ratio: 0.03845, Grade: C\",\"StationNumber: 02HB50, Year: 2002, PEL ratio: 0.32514, Grade: F\",\"StationNumber: 02HB51, Year: 2002, PEL ratio: 0.06603, Grade: C\",\"StationNumber: 02HB55, Year: 2002, PEL ratio: 0.05778, Grade: C\",\"StationNumber: 02LTB01, Year: 2002, PEL ratio: 0.02663, Grade: C\",\"StationNumber: 02LTB02, Year: 2002, PEL ratio: 0.02978, Grade: C\",\"StationNumber: 02LTB03, Year: 2002, PEL ratio: 0.02042, Grade: B\",\"StationNumber: 02LTB04, Year: 2002, PEL ratio: 0.02782, Grade: C\",\"StationNumber: 02LTB05, Year: 2002, PEL ratio: 0.02348, Grade: C\",\"StationNumber: 02LTB06, Year: 2002, PEL ratio: 0.04038, Grade: C\",\"StationNumber: 02LTB07, Year: 2002, PEL ratio: 0.03048, Grade: C\",\"StationNumber: 02LTB08, Year: 2002, PEL ratio: 0.02061, Grade: C\",\"StationNumber: 02LTB09, Year: 2002, PEL ratio: 0.02023, Grade: B\",\"StationNumber: 02MR02, Year: 2002, PEL ratio: 0.03322, Grade: C\",\"StationNumber: 02MR04, Year: 2002, PEL ratio: 0.03337, Grade: C\",\"StationNumber: 02MR06, Year: 2002, PEL ratio: 0.14519, Grade: D\",\"StationNumber: 02MR08, Year: 2002, PEL ratio: 0.02507, Grade: C\",\"StationNumber: 02MR10, Year: 2002, PEL ratio: 0.04251, Grade: C\",\"StationNumber: 02MR11, Year: 2002, PEL ratio: 0.03906, Grade: C\",\"StationNumber: 02MR12, Year: 2002, PEL ratio: 0.03873, Grade: C\",\"StationNumber: 02DH08-1, Year: 2002, PEL ratio: 0.09017, Grade: D\",\"StationNumber: 02DH08-2, Year: 2002, PEL ratio: 0.10363, Grade: D\",\"StationNumber: 02DH08-3, Year: 2002, PEL ratio: 0.08051, Grade: C\",\"StationNumber: 02DH14-1, Year: 2002, PEL ratio: 0.18895, Grade: D\",\"StationNumber: 02DH14-3, Year: 2002, PEL ratio: 0.12398, Grade: D\",\"StationNumber: 02DH14-4, Year: 2002, PEL ratio: 0.13475, Grade: D\",\"StationNumber: 02DH15-1, Year: 2002, PEL ratio: 0.03722, Grade: C\",\"StationNumber: 02DH15-2, Year: 2002, PEL ratio: 0.03193, Grade: C\",\"StationNumber: 02DH15-5, Year: 2002, PEL ratio: 0.10865, Grade: D\",\"StationNumber: 02MTB11, Year: 2002, PEL ratio: 0.03207, Grade: C\",\"StationNumber: 02MTB12, Year: 2002, PEL ratio: 0.03458, Grade: C\",\"StationNumber: 02MTB18, Year: 2002, PEL ratio: 0.06402, Grade: C\",\"StationNumber: 02MTB19, Year: 2002, PEL ratio: 0.02845, Grade: C\",\"StationNumber: 02MTB21, Year: 2002, PEL ratio: 0.07645, Grade: C\",\"StationNumber: 02MTB23, Year: 2002, PEL ratio: 0.04157, Grade: C\",\"StationNumber: 02MTB27, Year: 2002, PEL ratio: 0.03517, Grade: C\",\"StationNumber: 02MTB29, Year: 2002, PEL ratio: 0.03409, Grade: C\",\"StationNumber: 02MTB32, Year: 2002, PEL ratio: 0.03217, Grade: C\",\"StationNumber: 02MTB34, Year: 2002, PEL ratio: 0.0336, Grade: C\",\"StationNumber: 02DH03-2, Year: 2002, PEL ratio: 0.15, Grade: D\",\"StationNumber: 02DH03-4, Year: 2002, PEL ratio: 0.15355, Grade: D\",\"StationNumber: 02DH03-5, Year: 2002, PEL ratio: 0.18194, Grade: D\",\"StationNumber: 02DH05-3, Year: 2002, PEL ratio: 0.02701, Grade: C\",\"StationNumber: 02DH05-4, Year: 2002, PEL ratio: 0.08347, Grade: C\",\"StationNumber: 02DH05-5, Year: 2002, PEL ratio: 0.03648, Grade: C\",\"StationNumber: 02DH07-1, Year: 2002, PEL ratio: 0.08738, Grade: D\",\"StationNumber: 02DH07-2, Year: 2002, PEL ratio: 0.09842, Grade: D\",\"StationNumber: 02DH07-3, Year: 2002, PEL ratio: 0.09265, Grade: D\",\"StationNumber: 02DH18-1, Year: 2002, PEL ratio: 0.03811, Grade: C\",\"StationNumber: 02DH18-2, Year: 2002, PEL ratio: 0.04678, Grade: C\",\"StationNumber: 02DH18-3, Year: 2002, PEL ratio: 0.0332, Grade: C\",\"StationNumber: 02DH20-3, Year: 2002, PEL ratio: 0.09118, Grade: D\",\"StationNumber: 02DH20-4, Year: 2002, PEL ratio: 0.0982, Grade: D\",\"StationNumber: 02DH20-5, Year: 2002, PEL ratio: 0.08451, Grade: C\",\"StationNumber: 02DH21A-1, Year: 2002, PEL ratio: 0.08952, Grade: D\",\"StationNumber: 02DH21A-3, Year: 2002, PEL ratio: 0.10866, Grade: D\",\"StationNumber: 02DH21A-5, Year: 2002, PEL ratio: 0.11684, Grade: D\",\"StationNumber: 02DH21B-1, Year: 2002, PEL ratio: 0.13203, Grade: D\",\"StationNumber: 02DH21B-3, Year: 2002, PEL ratio: 0.12143, Grade: D\",\"StationNumber: 02DH21B-4, Year: 2002, PEL ratio: 0.1119, Grade: D\",\"StationNumber: 02OTB02, Year: 2002, PEL ratio: 0.02894, Grade: C\",\"StationNumber: 02OTB04, Year: 2002, PEL ratio: 0.03118, Grade: C\",\"StationNumber: 02OTB27, Year: 2002, PEL ratio: 0.02515, Grade: C\",\"StationNumber: 02OTB49, Year: 2002, PEL ratio: 0.0374, Grade: C\",\"StationNumber: 02OTB50, Year: 2002, PEL ratio: 0.04422, Grade: C\",\"StationNumber: 02OTB52, Year: 2002, PEL ratio: 0.03468, Grade: C\",\"StationNumber: 02OTB60, Year: 2002, PEL ratio: 0.0399, Grade: C\",\"StationNumber: 02OTB66, Year: 2002, PEL ratio: 0.04346, Grade: C\",\"StationNumber: 02TCB03, Year: 2002, PEL ratio: 0.02956, Grade: C\",\"StationNumber: 02TCB05, Year: 2002, PEL ratio: 0.05723, Grade: C\",\"StationNumber: 02TCB07, Year: 2002, PEL ratio: 0.04305, Grade: C\",\"StationNumber: 02TCB09, Year: 2002, PEL ratio: 0.041, Grade: C\",\"StationNumber: 03BCB107, Year: 2003, PEL ratio: 0.04845, Grade: C\",\"StationNumber: 03BCB120, Year: 2003, PEL ratio: 0.07755, Grade: C\",\"StationNumber: 03BCB126, Year: 2003, PEL ratio: 0.05955, Grade: C\",\"StationNumber: 03BCB190, Year: 2003, PEL ratio: 0.07526, Grade: C\",\"StationNumber: 03BCB230, Year: 2003, PEL ratio: 0.04192, Grade: C\",\"StationNumber: 03BCB242, Year: 2003, PEL ratio: 0.1701, Grade: D\",\"StationNumber: 03BCB278, Year: 2003, PEL ratio: 0.04954, Grade: C\",\"StationNumber: 03BCB287, Year: 2003, PEL ratio: 0.0426, Grade: C\",\"StationNumber: 03BCB338, Year: 2003, PEL ratio: 0.05523, Grade: C\",\"StationNumber: 03BCB439, Year: 2003, PEL ratio: 0.05588, Grade: C\",\"StationNumber: 03HB01, Year: 2003, PEL ratio: 0.05953, Grade: C\",\"StationNumber: 03HB02, Year: 2003, PEL ratio: 0.09513, Grade: D\",\"StationNumber: 03HB04, Year: 2003, PEL ratio: 0.05264, Grade: C\",\"StationNumber: 03HB06, Year: 2003, PEL ratio: 0.2787, Grade: D\",\"StationNumber: 03HB09, Year: 2003, PEL ratio: 2.62709, Grade: F\",\"StationNumber: 03HB10, Year: 2003, PEL ratio: 0.07527, Grade: C\",\"StationNumber: 03HB11, Year: 2003, PEL ratio: 0.05917, Grade: C\",\"StationNumber: 03HB12, Year: 2003, PEL ratio: 0.08962, Grade: D\",\"StationNumber: 03HB14, Year: 2003, PEL ratio: 0.05233, Grade: C\",\"StationNumber: 03HB16, Year: 2003, PEL ratio: 0.08913, Grade: D\",\"StationNumber: 03HB18, Year: 2003, PEL ratio: 0.07056, Grade: C\",\"StationNumber: 03HB21, Year: 2003, PEL ratio: 0.02956, Grade: C\",\"StationNumber: 03HB27, Year: 2003, PEL ratio: 0.11208, Grade: D\",\"StationNumber: 03HB28, Year: 2003, PEL ratio: 0.13538, Grade: D\",\"StationNumber: 03HB30, Year: 2003, PEL ratio: 0.05101, Grade: C\",\"StationNumber: 03HB32, Year: 2003, PEL ratio: 0.08584, Grade: D\",\"StationNumber: 03HB33, Year: 2003, PEL ratio: 0.04992, Grade: C\",\"StationNumber: 03HB34, Year: 2003, PEL ratio: 0.05096, Grade: C\",\"StationNumber: 03HB37, Year: 2003, PEL ratio: 0.17023, Grade: D\",\"StationNumber: 03HB38, Year: 2003, PEL ratio: 0.04877, Grade: C\",\"StationNumber: 03HB41, Year: 2003, PEL ratio: 0.07016, Grade: C\",\"StationNumber: 03HB42, Year: 2003, PEL ratio: 0.11971, Grade: D\",\"StationNumber: 03HB44, Year: 2003, PEL ratio: 0.04723, Grade: C\",\"StationNumber: 03HB47, Year: 2003, PEL ratio: 0.0484, Grade: C\",\"StationNumber: 03HB50, Year: 2003, PEL ratio: 0.04892, Grade: C\",\"StationNumber: 03HB51, Year: 2003, PEL ratio: 0.07784, Grade: C\",\"StationNumber: 03HB52, Year: 2003, PEL ratio: 0.10156, Grade: D\",\"StationNumber: 03HB53, Year: 2003, PEL ratio: 0.04264, Grade: C\",\"StationNumber: 03LTB01, Year: 2003, PEL ratio: 0.0462, Grade: C\",\"StationNumber: 03LTB02, Year: 2003, PEL ratio: 0.0405, Grade: C\",\"StationNumber: 03LTB03, Year: 2003, PEL ratio: 0.04888, Grade: C\",\"StationNumber: 03LTB04, Year: 2003, PEL ratio: 0.05672, Grade: C\",\"StationNumber: 03LTB05, Year: 2003, PEL ratio: 0.03249, Grade: C\",\"StationNumber: 03LTB06, Year: 2003, PEL ratio: 0.04582, Grade: C\",\"StationNumber: 03LTB07, Year: 2003, PEL ratio: 0.05602, Grade: C\",\"StationNumber: 03LTB08, Year: 2003, PEL ratio: 0.02753, Grade: C\",\"StationNumber: 03LTB09, Year: 2003, PEL ratio: 0.04842, Grade: C\",\"StationNumber: 03LTB10, Year: 2003, PEL ratio: 0.03141, Grade: C\",\"StationNumber: 03LTB11, Year: 2003, PEL ratio: 0.05041, Grade: C\",\"StationNumber: 03LTB12, Year: 2003, PEL ratio: 0.04109, Grade: C\",\"StationNumber: 03MR02, Year: 2003, PEL ratio: 0.07551, Grade: C\",\"StationNumber: 03MR04, Year: 2003, PEL ratio: 0.06186, Grade: C\",\"StationNumber: 03MR06, Year: 2003, PEL ratio: 0.11177, Grade: D\",\"StationNumber: 03MR07, Year: 2003, PEL ratio: 0.04271, Grade: C\",\"StationNumber: 03MR08, Year: 2003, PEL ratio: 0.04877, Grade: C\",\"StationNumber: 03MR09, Year: 2003, PEL ratio: 0.04126, Grade: C\",\"StationNumber: 03MR10, Year: 2003, PEL ratio: 0.05761, Grade: C\",\"StationNumber: 03MTB03, Year: 2003, PEL ratio: 0.05627, Grade: C\",\"StationNumber: 03MTB08, Year: 2003, PEL ratio: 0.06744, Grade: C\",\"StationNumber: 03MTB10, Year: 2003, PEL ratio: 0.04607, Grade: C\",\"StationNumber: 03MTB11, Year: 2003, PEL ratio: 0.0679, Grade: C\",\"StationNumber: 03MTB13, Year: 2003, PEL ratio: 0.08571, Grade: D\",\"StationNumber: 03MTB14, Year: 2003, PEL ratio: 0.07424, Grade: C\",\"StationNumber: 03MTB15, Year: 2003, PEL ratio: 0.07661, Grade: C\",\"StationNumber: 03MTB16, Year: 2003, PEL ratio: 0.07141, Grade: C\",\"StationNumber: 03MTB17, Year: 2003, PEL ratio: 0.04297, Grade: C\",\"StationNumber: 03MTB18, Year: 2003, PEL ratio: 0.06047, Grade: C\",\"StationNumber: 03MTB19, Year: 2003, PEL ratio: 0.0635, Grade: C\",\"StationNumber: 03MTB21, Year: 2003, PEL ratio: 0.06752, Grade: C\",\"StationNumber: 03MTB24, Year: 2003, PEL ratio: 0.05516, Grade: C\",\"StationNumber: 03MTB25, Year: 2003, PEL ratio: 0.06373, Grade: C\",\"StationNumber: 03MTB27, Year: 2003, PEL ratio: 0.05651, Grade: C\",\"StationNumber: 03MTB28, Year: 2003, PEL ratio: 0.06933, Grade: C\",\"StationNumber: 03MTB30, Year: 2003, PEL ratio: 0.43636, Grade: F\",\"StationNumber: 03MTB31, Year: 2003, PEL ratio: 0.07005, Grade: C\",\"StationNumber: 03MTB32, Year: 2003, PEL ratio: 0.05667, Grade: C\",\"StationNumber: 03MTB33, Year: 2003, PEL ratio: 0.07011, Grade: C\",\"StationNumber: 03MTB34, Year: 2003, PEL ratio: 0.06682, Grade: C\",\"StationNumber: 03MTB35, Year: 2003, PEL ratio: 0.07621, Grade: C\",\"StationNumber: 03OTB157, Year: 2003, PEL ratio: 0.05915, Grade: C\",\"StationNumber: 03OTB200, Year: 2003, PEL ratio: 0.16694, Grade: D\",\"StationNumber: 03OTB413, Year: 2003, PEL ratio: 0.05894, Grade: C\",\"StationNumber: 03OTB414, Year: 2003, PEL ratio: 0.04976, Grade: C\",\"StationNumber: 03OTB507, Year: 2003, PEL ratio: 0.07151, Grade: C\",\"StationNumber: 03OTB623, Year: 2003, PEL ratio: 0.19749, Grade: D\",\"StationNumber: 03OTB706, Year: 2003, PEL ratio: 0.11944, Grade: D\",\"StationNumber: 03OTB794, Year: 2003, PEL ratio: 0.05991, Grade: C\",\"StationNumber: 03OTB929, Year: 2003, PEL ratio: 0.09521, Grade: D\",\"StationNumber: 03TCB01, Year: 2003, PEL ratio: 0.03963, Grade: C\",\"StationNumber: 03TCB03, Year: 2003, PEL ratio: 0.04315, Grade: C\",\"StationNumber: 03TCB05, Year: 2003, PEL ratio: 0.04569, Grade: C\",\"StationNumber: 04BCB01, Year: 2004, PEL ratio: 0.03545, Grade: C\",\"StationNumber: 04BCB02, Year: 2004, PEL ratio: 0.03051, Grade: C\",\"StationNumber: 04BCB03, Year: 2004, PEL ratio: 0.1299, Grade: D\",\"StationNumber: 04BCB04, Year: 2004, PEL ratio: 0.04849, Grade: C\",\"StationNumber: 04BCB05, Year: 2004, PEL ratio: 0.02806, Grade: C\",\"StationNumber: 04BCB06, Year: 2004, PEL ratio: 0.05131, Grade: C\",\"StationNumber: 04BCB07, Year: 2004, PEL ratio: 0.02049, Grade: B\",\"StationNumber: 04BCB08, Year: 2004, PEL ratio: 0.03435, Grade: C\",\"StationNumber: 04BCB09, Year: 2004, PEL ratio: 0.0386, Grade: C\",\"StationNumber: 04BCB10, Year: 2004, PEL ratio: 0.03223, Grade: C\",\"StationNumber: 04HB01, Year: 2004, PEL ratio: 0.01651, Grade: B\",\"StationNumber: 04HB02, Year: 2004, PEL ratio: 0.0358, Grade: C\",\"StationNumber: 04HB03, Year: 2004, PEL ratio: 0.12867, Grade: D\",\"StationNumber: 04HB04, Year: 2004, PEL ratio: 0.08639, Grade: D\",\"StationNumber: 04HB05, Year: 2004, PEL ratio: 0.02012, Grade: B\",\"StationNumber: 04HB06, Year: 2004, PEL ratio: 0.02029, Grade: B\",\"StationNumber: 04HB07, Year: 2004, PEL ratio: 0.02572, Grade: C\",\"StationNumber: 04HB08, Year: 2004, PEL ratio: 0.02404, Grade: C\",\"StationNumber: 04HB09, Year: 2004, PEL ratio: 0.04005, Grade: C\",\"StationNumber: 04HB10, Year: 2004, PEL ratio: 0.18388, Grade: D\",\"StationNumber: 04HB11, Year: 2004, PEL ratio: 0.02011, Grade: B\",\"StationNumber: 04HB12, Year: 2004, PEL ratio: 0.11403, Grade: D\",\"StationNumber: 04HB13, Year: 2004, PEL ratio: 0.14349, Grade: D\",\"StationNumber: 04HB14, Year: 2004, PEL ratio: 0.02109, Grade: C\",\"StationNumber: 04HB15, Year: 2004, PEL ratio: 0.02016, Grade: B\",\"StationNumber: 04HB16, Year: 2004, PEL ratio: 0.01749, Grade: B\",\"StationNumber: 04HB17, Year: 2004, PEL ratio: 0.18354, Grade: D\",\"StationNumber: 04HB18, Year: 2004, PEL ratio: 0.4013, Grade: F\",\"StationNumber: 04HB19, Year: 2004, PEL ratio: 0.12724, Grade: D\",\"StationNumber: 04HB20, Year: 2004, PEL ratio: 0.02398, Grade: C\",\"StationNumber: 04HB21, Year: 2004, PEL ratio: 0.02873, Grade: C\",\"StationNumber: 04HB23, Year: 2004, PEL ratio: 0.02633, Grade: C\",\"StationNumber: 04HB24, Year: 2004, PEL ratio: 0.02717, Grade: C\",\"StationNumber: 04HB25, Year: 2004, PEL ratio: 0.05102, Grade: C\",\"StationNumber: 04HB26, Year: 2004, PEL ratio: 0.14601, Grade: D\",\"StationNumber: 04LTB01, Year: 2004, PEL ratio: 0.01329, Grade: B\",\"StationNumber: 04LTB02, Year: 2004, PEL ratio: 0.02081, Grade: C\",\"StationNumber: 04LTB03, Year: 2004, PEL ratio: 0.02025, Grade: B\",\"StationNumber: 04LTB04, Year: 2004, PEL ratio: 0.01177, Grade: B\",\"StationNumber: 04LTB05, Year: 2004, PEL ratio: 0.0211, Grade: C\",\"StationNumber: 04LTB06, Year: 2004, PEL ratio: 0.01694, Grade: B\",\"StationNumber: 04LTB07, Year: 2004, PEL ratio: 0.01745, Grade: B\",\"StationNumber: 04LTB08, Year: 2004, PEL ratio: 0.03084, Grade: C\",\"StationNumber: 04LTB09, Year: 2004, PEL ratio: 0.02538, Grade: C\",\"StationNumber: 04LTB10, Year: 2004, PEL ratio: 0.02293, Grade: C\",\"StationNumber: 04LTB11, Year: 2004, PEL ratio: 0.03789, Grade: C\",\"StationNumber: 04MR01, Year: 2004, PEL ratio: 0.08777, Grade: D\",\"StationNumber: 04MR02, Year: 2004, PEL ratio: 0.02688, Grade: C\",\"StationNumber: 04MR03, Year: 2004, PEL ratio: 0.01966, Grade: B\",\"StationNumber: 04MR04, Year: 2004, PEL ratio: 0.04362, Grade: C\",\"StationNumber: 04MR05, Year: 2004, PEL ratio: 0.03869, Grade: C\",\"StationNumber: 04MR06, Year: 2004, PEL ratio: 0.01585, Grade: B\",\"StationNumber: 04MR08, Year: 2004, PEL ratio: 0.06183, Grade: C\",\"StationNumber: 04MR09, Year: 2004, PEL ratio: 0.03834, Grade: C\",\"StationNumber: 04MR10, Year: 2004, PEL ratio: 0.02989, Grade: C\",\"StationNumber: 04MR11, Year: 2004, PEL ratio: 0.04141, Grade: C\",\"StationNumber: 04MTB01, Year: 2004, PEL ratio: 0.0143, Grade: B\",\"StationNumber: 04MTB02, Year: 2004, PEL ratio: 0.0336, Grade: C\",\"StationNumber: 04MTB04, Year: 2004, PEL ratio: 0.02691, Grade: C\",\"StationNumber: 04MTB05, Year: 2004, PEL ratio: 0.02789, Grade: C\",\"StationNumber: 04MTB06, Year: 2004, PEL ratio: 0.01916, Grade: B\",\"StationNumber: 04MTB07, Year: 2004, PEL ratio: 0.01837, Grade: B\",\"StationNumber: 04MTB08, Year: 2004, PEL ratio: 0.02226, Grade: C\",\"StationNumber: 04MTB09, Year: 2004, PEL ratio: 0.0162, Grade: B\",\"StationNumber: 04MTB10, Year: 2004, PEL ratio: 0.02033, Grade: B\",\"StationNumber: 04MTB11, Year: 2004, PEL ratio: 0.02662, Grade: C\",\"StationNumber: 04MTB12, Year: 2004, PEL ratio: 0.0287, Grade: C\",\"StationNumber: 04MTB13, Year: 2004, PEL ratio: 0.03236, Grade: C\",\"StationNumber: 04MTB14, Year: 2004, PEL ratio: 0.03029, Grade: C\",\"StationNumber: 04MTB15, Year: 2004, PEL ratio: 0.01749, Grade: B\",\"StationNumber: 04MTB16, Year: 2004, PEL ratio: 0.01835, Grade: B\",\"StationNumber: 04MTB17, Year: 2004, PEL ratio: 0.02028, Grade: B\",\"StationNumber: 04MTB18, Year: 2004, PEL ratio: 0.01928, Grade: B\",\"StationNumber: 04MTB19, Year: 2004, PEL ratio: 0.03315, Grade: C\",\"StationNumber: 04MTB20, Year: 2004, PEL ratio: 0.02831, Grade: C\",\"StationNumber: 04MTB21, Year: 2004, PEL ratio: 0.03321, Grade: C\",\"StationNumber: 04MTB22, Year: 2004, PEL ratio: 0.02665, Grade: C\",\"StationNumber: 04MTB24, Year: 2004, PEL ratio: 0.0288, Grade: C\",\"StationNumber: 04OTB01, Year: 2004, PEL ratio: 0.02555, Grade: C\",\"StationNumber: 04OTB02, Year: 2004, PEL ratio: 0.02935, Grade: C\",\"StationNumber: 04OTB03, Year: 2004, PEL ratio: 0.03106, Grade: C\",\"StationNumber: 04OTB04, Year: 2004, PEL ratio: 0.02777, Grade: C\",\"StationNumber: 04OTB05, Year: 2004, PEL ratio: 0.12197, Grade: D\",\"StationNumber: 04OTB06, Year: 2004, PEL ratio: 0.02194, Grade: C\",\"StationNumber: 04OTB07, Year: 2004, PEL ratio: 0.10091, Grade: D\",\"StationNumber: 04OTB08, Year: 2004, PEL ratio: 0.0248, Grade: C\",\"StationNumber: 04OTB09, Year: 2004, PEL ratio: 0.0243, Grade: C\",\"StationNumber: 04TCB07, Year: 2004, PEL ratio: 0.03924, Grade: C\",\"StationNumber: 05BCB01, Year: 2005, PEL ratio: 0.02056, Grade: C\",\"StationNumber: 05BCB02, Year: 2005, PEL ratio: 0.01422, Grade: B\",\"StationNumber: 05BCB03, Year: 2005, PEL ratio: 0.0279, Grade: C\",\"StationNumber: 05BCB04, Year: 2005, PEL ratio: 0.01565, Grade: B\",\"StationNumber: 05BCB05, Year: 2005, PEL ratio: 0.94385, Grade: F\",\"StationNumber: 05BCB06, Year: 2005, PEL ratio: 0.03608, Grade: C\",\"StationNumber: 05BCB07, Year: 2005, PEL ratio: 0.01302, Grade: B\",\"StationNumber: 05BCB08, Year: 2005, PEL ratio: 0.0183, Grade: B\",\"StationNumber: 05BCB09, Year: 2005, PEL ratio: 0.02383, Grade: C\",\"StationNumber: 05BCB10, Year: 2005, PEL ratio: 0.01397, Grade: B\",\"StationNumber: 05HB01, Year: 2005, PEL ratio: 0.02071, Grade: C\",\"StationNumber: 05HB02, Year: 2005, PEL ratio: 0.01836, Grade: B\",\"StationNumber: 05HB03, Year: 2005, PEL ratio: 0.01997, Grade: B\",\"StationNumber: 05HB04, Year: 2005, PEL ratio: 0.0672, Grade: C\",\"StationNumber: 05HB05, Year: 2005, PEL ratio: 0.10587, Grade: D\",\"StationNumber: 05HB06, Year: 2005, PEL ratio: 0.07366, Grade: C\",\"StationNumber: 05HB07, Year: 2005, PEL ratio: 0.01737, Grade: B\",\"StationNumber: 05HB08, Year: 2005, PEL ratio: 0.01899, Grade: B\",\"StationNumber: 05HB09, Year: 2005, PEL ratio: 0.03392, Grade: C\",\"StationNumber: 05HB10, Year: 2005, PEL ratio: 0.03834, Grade: C\",\"StationNumber: 05HB11, Year: 2005, PEL ratio: 0.01724, Grade: B\",\"StationNumber: 05HB12, Year: 2005, PEL ratio: 1.00876, Grade: F\",\"StationNumber: 05HB13, Year: 2005, PEL ratio: 0.03924, Grade: C\",\"StationNumber: 05HB14, Year: 2005, PEL ratio: 0.15213, Grade: D\",\"StationNumber: 05HB15, Year: 2005, PEL ratio: 0.07682, Grade: C\",\"StationNumber: 05HB16, Year: 2005, PEL ratio: 0.11966, Grade: D\",\"StationNumber: 05HB17, Year: 2005, PEL ratio: 0.28594, Grade: F\",\"StationNumber: 05HB18, Year: 2005, PEL ratio: 0.02303, Grade: C\",\"StationNumber: 05HB19, Year: 2005, PEL ratio: 0.01643, Grade: B\",\"StationNumber: 05HB20, Year: 2005, PEL ratio: 0.01686, Grade: B\",\"StationNumber: 05HB21, Year: 2005, PEL ratio: 0.0478, Grade: C\",\"StationNumber: 05HB22, Year: 2005, PEL ratio: 0.04996, Grade: C\",\"StationNumber: 05HB23, Year: 2005, PEL ratio: 0.02946, Grade: C\",\"StationNumber: 05HB24, Year: 2005, PEL ratio: 0.01751, Grade: B\",\"StationNumber: 05LTB01, Year: 2005, PEL ratio: 0.02599, Grade: C\",\"StationNumber: 05LTB02, Year: 2005, PEL ratio: 0.01545, Grade: B\",\"StationNumber: 05LTB03, Year: 2005, PEL ratio: 0.01154, Grade: B\",\"StationNumber: 05LTB04, Year: 2005, PEL ratio: 0.03654, Grade: C\",\"StationNumber: 05LTB05, Year: 2005, PEL ratio: 0.01619, Grade: B\",\"StationNumber: 05LTB06, Year: 2005, PEL ratio: 0.0193, Grade: B\",\"StationNumber: 05LTB07, Year: 2005, PEL ratio: 0.01402, Grade: B\",\"StationNumber: 05LTB08, Year: 2005, PEL ratio: 0.0167, Grade: B\",\"StationNumber: 05LTB09, Year: 2005, PEL ratio: 0.02347, Grade: C\",\"StationNumber: 05LTB10, Year: 2005, PEL ratio: 0.01211, Grade: B\",\"StationNumber: 05LTB11, Year: 2005, PEL ratio: 0.01356, Grade: B\",\"StationNumber: 05MR02, Year: 2005, PEL ratio: 0.01442, Grade: B\",\"StationNumber: 05MR04, Year: 2005, PEL ratio: 0.02173, Grade: C\",\"StationNumber: 05MR06, Year: 2005, PEL ratio: 0.01537, Grade: B\",\"StationNumber: 05MR08, Year: 2005, PEL ratio: 0.01574, Grade: B\",\"StationNumber: 05MR09, Year: 2005, PEL ratio: 0.01971, Grade: B\",\"StationNumber: 05MR11, Year: 2005, PEL ratio: 0.08271, Grade: C\",\"StationNumber: 05MTB01, Year: 2005, PEL ratio: 0.02214, Grade: C\",\"StationNumber: 05MTB02, Year: 2005, PEL ratio: 0.0218, Grade: C\",\"StationNumber: 05MTB03, Year: 2005, PEL ratio: 0.01836, Grade: B\",\"StationNumber: 05MTB04, Year: 2005, PEL ratio: 0.01475, Grade: B\",\"StationNumber: 05MTB05, Year: 2005, PEL ratio: 0.01741, Grade: B\",\"StationNumber: 05MTB06, Year: 2005, PEL ratio: 0.01714, Grade: B\",\"StationNumber: 05MTB07, Year: 2005, PEL ratio: 0.03643, Grade: C\",\"StationNumber: 05MTB08, Year: 2005, PEL ratio: 0.02875, Grade: C\",\"StationNumber: 05MTB09, Year: 2005, PEL ratio: 0.01427, Grade: B\",\"StationNumber: 05MTB10, Year: 2005, PEL ratio: 0.01804, Grade: B\",\"StationNumber: 05MTB11, Year: 2005, PEL ratio: 0.01786, Grade: B\",\"StationNumber: 05MTB12, Year: 2005, PEL ratio: 0.01943, Grade: B\",\"StationNumber: 05MTB13, Year: 2005, PEL ratio: 0.01404, Grade: B\",\"StationNumber: 05MTB14, Year: 2005, PEL ratio: 0.02263, Grade: C\",\"StationNumber: 05MTB15, Year: 2005, PEL ratio: 0.10298, Grade: D\",\"StationNumber: 05MTB16, Year: 2005, PEL ratio: 0.01322, Grade: B\",\"StationNumber: 05MTB17, Year: 2005, PEL ratio: 0.01324, Grade: B\",\"StationNumber: 05MTB18, Year: 2005, PEL ratio: 0.01423, Grade: B\",\"StationNumber: 05MTB19, Year: 2005, PEL ratio: 0.01217, Grade: B\",\"StationNumber: 05MTB20, Year: 2005, PEL ratio: 0.01481, Grade: B\",\"StationNumber: 05MTB21, Year: 2005, PEL ratio: 0.03798, Grade: C\",\"StationNumber: 05MTB22, Year: 2005, PEL ratio: 0.0196, Grade: B\",\"StationNumber: 05OTB01, Year: 2005, PEL ratio: 0.01507, Grade: B\",\"StationNumber: 05OTB02, Year: 2005, PEL ratio: 0.02508, Grade: C\",\"StationNumber: 05OTB03, Year: 2005, PEL ratio: 0.01587, Grade: B\",\"StationNumber: 05OTB04, Year: 2005, PEL ratio: 0.02237, Grade: C\",\"StationNumber: 05OTB05, Year: 2005, PEL ratio: 0.0268, Grade: C\",\"StationNumber: 05OTB06, Year: 2005, PEL ratio: 0.05287, Grade: C\",\"StationNumber: 05OTB07, Year: 2005, PEL ratio: 0.02997, Grade: C\",\"StationNumber: 05OTB08, Year: 2005, PEL ratio: 0.01315, Grade: B\",\"StationNumber: 05OTB09, Year: 2005, PEL ratio: 0.04264, Grade: C\",\"StationNumber: 05OTB10, Year: 2005, PEL ratio: 0.01673, Grade: B\",\"StationNumber: 05TCB01, Year: 2005, PEL ratio: 0.02249, Grade: C\",\"StationNumber: 05TCB03, Year: 2005, PEL ratio: 0.01896, Grade: B\",\"StationNumber: 05TCB05, Year: 2005, PEL ratio: 0.01899, Grade: B\",\"StationNumber: 05TCB07, Year: 2005, PEL ratio: 0.11125, Grade: D\",\"StationNumber: 05TCB10, Year: 2005, PEL ratio: 0.01684, Grade: B\",\"StationNumber: 06BCB01, Year: 2006, PEL ratio: 0.04257, Grade: C\",\"StationNumber: 06BCB02, Year: 2006, PEL ratio: 0.03339, Grade: C\",\"StationNumber: 06BCB03, Year: 2006, PEL ratio: 0.03085, Grade: C\",\"StationNumber: 06BCB04, Year: 2006, PEL ratio: 0.04285, Grade: C\",\"StationNumber: 06BCB05, Year: 2006, PEL ratio: 0.02977, Grade: C\",\"StationNumber: 06BCB06, Year: 2006, PEL ratio: 0.03224, Grade: C\",\"StationNumber: 06BCB07, Year: 2006, PEL ratio: 0.05354, Grade: C\",\"StationNumber: 06BCB08, Year: 2006, PEL ratio: 0.03691, Grade: C\",\"StationNumber: 06BCB09, Year: 2006, PEL ratio: 0.02935, Grade: C\",\"StationNumber: 06HB01, Year: 2006, PEL ratio: 0.05456, Grade: C\",\"StationNumber: 06HB02, Year: 2006, PEL ratio: 0.07105, Grade: C\",\"StationNumber: 06HB03, Year: 2006, PEL ratio: 0.09993, Grade: D\",\"StationNumber: 06HB04, Year: 2006, PEL ratio: 0.04056, Grade: C\",\"StationNumber: 06HB05, Year: 2006, PEL ratio: 0.05604, Grade: C\",\"StationNumber: 06HB06, Year: 2006, PEL ratio: 0.05301, Grade: C\",\"StationNumber: 06HB08, Year: 2006, PEL ratio: 0.04385, Grade: C\",\"StationNumber: 06HB09, Year: 2006, PEL ratio: 0.326, Grade: F\",\"StationNumber: 06HB10, Year: 2006, PEL ratio: 0.03664, Grade: C\",\"StationNumber: 06HB11, Year: 2006, PEL ratio: 0.04268, Grade: C\",\"StationNumber: 06HB12, Year: 2006, PEL ratio: 0.04913, Grade: C\",\"StationNumber: 06HB13, Year: 2006, PEL ratio: 0.03765, Grade: C\",\"StationNumber: 06HB14, Year: 2006, PEL ratio: 0.04626, Grade: C\",\"StationNumber: 06HB15, Year: 2006, PEL ratio: 0.02753, Grade: C\",\"StationNumber: 06HB16, Year: 2006, PEL ratio: 0.02342, Grade: C\",\"StationNumber: 06HB17, Year: 2006, PEL ratio: 0.04712, Grade: C\",\"StationNumber: 06HB18, Year: 2006, PEL ratio: 0.14179, Grade: D\",\"StationNumber: 06HB19, Year: 2006, PEL ratio: 0.05858, Grade: C\",\"StationNumber: 06HB20, Year: 2006, PEL ratio: 0.10134, Grade: D\",\"StationNumber: 06HB21, Year: 2006, PEL ratio: 0.08326, Grade: C\",\"StationNumber: 06HB22, Year: 2006, PEL ratio: 0.033, Grade: C\",\"StationNumber: 06HB23, Year: 2006, PEL ratio: 0.02427, Grade: C\",\"StationNumber: 06HB24, Year: 2006, PEL ratio: 0.04327, Grade: C\",\"StationNumber: 06HB25, Year: 2006, PEL ratio: 0.01783, Grade: B\",\"StationNumber: 06LTB01, Year: 2006, PEL ratio: 0.03721, Grade: C\",\"StationNumber: 06LTB02, Year: 2006, PEL ratio: 0.0323, Grade: C\",\"StationNumber: 06LTB03, Year: 2006, PEL ratio: 0.03756, Grade: C\",\"StationNumber: 06LTB04, Year: 2006, PEL ratio: 0.03755, Grade: C\",\"StationNumber: 06LTB05, Year: 2006, PEL ratio: 0.02195, Grade: C\",\"StationNumber: 06LTB06, Year: 2006, PEL ratio: 0.0252, Grade: C\",\"StationNumber: 06LTB07, Year: 2006, PEL ratio: 0.02677, Grade: C\",\"StationNumber: 06LTB08, Year: 2006, PEL ratio: 0.034, Grade: C\",\"StationNumber: 06MR05, Year: 2006, PEL ratio: 0.06293, Grade: C\",\"StationNumber: 06MR06, Year: 2006, PEL ratio: 0.0353, Grade: C\",\"StationNumber: 06MR07, Year: 2006, PEL ratio: 0.03329, Grade: C\",\"StationNumber: 06MR08, Year: 2006, PEL ratio: 0.02817, Grade: C\",\"StationNumber: 06MR10, Year: 2006, PEL ratio: 0.0606, Grade: C\",\"StationNumber: 06MTB01, Year: 2006, PEL ratio: 0.0429, Grade: C\",\"StationNumber: 06MTB02, Year: 2006, PEL ratio: 0.03147, Grade: C\",\"StationNumber: 06MTB03, Year: 2006, PEL ratio: 0.07411, Grade: C\",\"StationNumber: 06MTB04, Year: 2006, PEL ratio: 0.03457, Grade: C\",\"StationNumber: 06MTB05, Year: 2006, PEL ratio: 0.04597, Grade: C\",\"StationNumber: 06MTB06, Year: 2006, PEL ratio: 0.04758, Grade: C\",\"StationNumber: 06MTB07, Year: 2006, PEL ratio: 0.03733, Grade: C\",\"StationNumber: 06MTB08, Year: 2006, PEL ratio: 0.02422, Grade: C\",\"StationNumber: 06MTB09, Year: 2006, PEL ratio: 0.03151, Grade: C\",\"StationNumber: 06MTB10, Year: 2006, PEL ratio: 0.03838, Grade: C\",\"StationNumber: 06MTB11, Year: 2006, PEL ratio: 0.05121, Grade: C\",\"StationNumber: 06MTB12, Year: 2006, PEL ratio: 0.03322, Grade: C\",\"StationNumber: 06MTB13, Year: 2006, PEL ratio: 0.04635, Grade: C\",\"StationNumber: 06MTB14, Year: 2006, PEL ratio: 0.02936, Grade: C\",\"StationNumber: 06MTB15, Year: 2006, PEL ratio: 0.04074, Grade: C\",\"StationNumber: 06MTB16, Year: 2006, PEL ratio: 0.02985, Grade: C\",\"StationNumber: 06MTB17, Year: 2006, PEL ratio: 0.04129, Grade: C\",\"StationNumber: 06MTB18, Year: 2006, PEL ratio: 0.02464, Grade: C\",\"StationNumber: 06MTB19, Year: 2006, PEL ratio: 0.03277, Grade: C\",\"StationNumber: 06OTB01, Year: 2006, PEL ratio: 0.03793, Grade: C\",\"StationNumber: 06OTB02, Year: 2006, PEL ratio: 0.03026, Grade: C\",\"StationNumber: 06OTB03, Year: 2006, PEL ratio: 0.02375, Grade: C\",\"StationNumber: 06OTB04, Year: 2006, PEL ratio: 0.03499, Grade: C\",\"StationNumber: 06OTB05, Year: 2006, PEL ratio: 0.03108, Grade: C\",\"StationNumber: 06OTB06, Year: 2006, PEL ratio: 0.03693, Grade: C\",\"StationNumber: 06OTB07, Year: 2006, PEL ratio: 0.03414, Grade: C\",\"StationNumber: 06OTB08, Year: 2006, PEL ratio: 0.03241, Grade: C\",\"StationNumber: 06TCB01, Year: 2006, PEL ratio: 0.01865, Grade: B\",\"StationNumber: 06TCB02, Year: 2006, PEL ratio: 0.02033, Grade: B\",\"StationNumber: 06TCB03, Year: 2006, PEL ratio: 0.02258, Grade: C\",\"StationNumber: 06TCB04, Year: 2006, PEL ratio: 0.02342, Grade: C\",\"StationNumber: 06TCB09, Year: 2006, PEL ratio: 0.02164, Grade: C\",\"StationNumber: 07BCB06, Year: 2007, PEL ratio: 0.03022, Grade: C\",\"StationNumber: 07BCB09, Year: 2007, PEL ratio: 0.04305, Grade: C\",\"StationNumber: 07BCB15, Year: 2007, PEL ratio: 0.03284, Grade: C\",\"StationNumber: 07BCB28, Year: 2007, PEL ratio: 0.0147, Grade: B\",\"StationNumber: 07BCB29, Year: 2007, PEL ratio: 0.03304, Grade: C\",\"StationNumber: 07BCB30, Year: 2007, PEL ratio: 0.02747, Grade: C\",\"StationNumber: 07BCB41, Year: 2007, PEL ratio: 0.02363, Grade: C\",\"StationNumber: 07BCB42, Year: 2007, PEL ratio: 0.03369, Grade: C\",\"StationNumber: 07BCB44, Year: 2007, PEL ratio: 0.02609, Grade: C\",\"StationNumber: 07BCB45, Year: 2007, PEL ratio: 0.04507, Grade: C\",\"StationNumber: 07HB13, Year: 2007, PEL ratio: 0.02193, Grade: C\",\"StationNumber: 07HB21, Year: 2007, PEL ratio: 0.64118, Grade: F\",\"StationNumber: 07HB34, Year: 2007, PEL ratio: 0.02191, Grade: C\",\"StationNumber: 07HB37, Year: 2007, PEL ratio: 0.03607, Grade: C\",\"StationNumber: 07HB38, Year: 2007, PEL ratio: 0.01243, Grade: B\",\"StationNumber: 07HB41, Year: 2007, PEL ratio: 0.00402, Grade: A\",\"StationNumber: 07HB42, Year: 2007, PEL ratio: 0.04791, Grade: C\",\"StationNumber: 07HB44, Year: 2007, PEL ratio: 0.05993, Grade: C\",\"StationNumber: 07HB53, Year: 2007, PEL ratio: 0.04356, Grade: C\",\"StationNumber: 07LTB91, Year: 2007, PEL ratio: 0.01736, Grade: B\",\"StationNumber: 07MR09, Year: 2007, PEL ratio: 0.00426, Grade: A\",\"StationNumber: 07MR28, Year: 2007, PEL ratio: 0.01592, Grade: B\",\"StationNumber: 07MR42, Year: 2007, PEL ratio: 0.01369, Grade: B\",\"StationNumber: 07MR46, Year: 2007, PEL ratio: 0.01441, Grade: B\",\"StationNumber: 07MR50, Year: 2007, PEL ratio: 0.00928, Grade: B\",\"StationNumber: 07MTB34, Year: 2007, PEL ratio: 0.03749, Grade: C\",\"StationNumber: 07MTB39, Year: 2007, PEL ratio: 0.02821, Grade: C\",\"StationNumber: 07MTB40, Year: 2007, PEL ratio: 0.03116, Grade: C\",\"StationNumber: 07MTB43, Year: 2007, PEL ratio: 0.03052, Grade: C\",\"StationNumber: 07MTB44, Year: 2007, PEL ratio: 0.0747, Grade: C\",\"StationNumber: 07MTB47, Year: 2007, PEL ratio: 0.04289, Grade: C\",\"StationNumber: 07MTB54, Year: 2007, PEL ratio: 0.03469, Grade: C\",\"StationNumber: 07OTB04, Year: 2007, PEL ratio: 0.0814, Grade: C\",\"StationNumber: 07OTB08, Year: 2007, PEL ratio: 0.03439, Grade: C\",\"StationNumber: 07OTB18, Year: 2007, PEL ratio: 0.03309, Grade: C\",\"StationNumber: 07OTB21, Year: 2007, PEL ratio: 0.05054, Grade: C\",\"StationNumber: 07OTB24, Year: 2007, PEL ratio: 0.03054, Grade: C\",\"StationNumber: 07OTB25, Year: 2007, PEL ratio: 0.02688, Grade: C\",\"StationNumber: 07OTB31, Year: 2007, PEL ratio: 0.03368, Grade: C\",\"StationNumber: 07TCB14, Year: 2007, PEL ratio: 0.02992, Grade: C\",\"StationNumber: 07TCB15, Year: 2007, PEL ratio: 0.0222, Grade: C\",\"StationNumber: 07TCB20, Year: 2007, PEL ratio: 0.01955, Grade: B\",\"StationNumber: 07TCB22, Year: 2007, PEL ratio: 0.01339, Grade: B\",\"StationNumber: 08BCB02, Year: 2008, PEL ratio: 0.02083, Grade: C\",\"StationNumber: 08BCB05, Year: 2008, PEL ratio: 0.02657, Grade: C\",\"StationNumber: 08BCB12, Year: 2008, PEL ratio: 0.02728, Grade: C\",\"StationNumber: 08BCB15, Year: 2008, PEL ratio: 0.06515, Grade: C\",\"StationNumber: 08BCB16, Year: 2008, PEL ratio: 0.03082, Grade: C\",\"StationNumber: 08BCB17, Year: 2008, PEL ratio: 0.09679, Grade: D\",\"StationNumber: 08BCB23, Year: 2008, PEL ratio: 0.1008, Grade: D\",\"StationNumber: 08BCB26, Year: 2008, PEL ratio: 0.0274, Grade: C\",\"StationNumber: 08BCB29, Year: 2008, PEL ratio: 0.0277, Grade: C\",\"StationNumber: 08BCB35, Year: 2008, PEL ratio: 0.03788, Grade: C\",\"StationNumber: 08BCB38, Year: 2008, PEL ratio: 0.02984, Grade: C\",\"StationNumber: 08HB13, Year: 2008, PEL ratio: 0.07748, Grade: C\",\"StationNumber: 08HB14, Year: 2008, PEL ratio: 0.03813, Grade: C\",\"StationNumber: 08HB17, Year: 2008, PEL ratio: 0.24554, Grade: D\",\"StationNumber: 08HB21, Year: 2008, PEL ratio: 0.15288, Grade: D\",\"StationNumber: 08HB27, Year: 2008, PEL ratio: 0.05295, Grade: C\",\"StationNumber: 08HB34, Year: 2008, PEL ratio: 0.02555, Grade: C\",\"StationNumber: 08HB43, Year: 2008, PEL ratio: 0.02778, Grade: C\",\"StationNumber: 08HB44, Year: 2008, PEL ratio: 0.02327, Grade: C\",\"StationNumber: 08HB48, Year: 2008, PEL ratio: 0.02752, Grade: C\",\"StationNumber: 08LTB69, Year: 2008, PEL ratio: 0.02295, Grade: C\",\"StationNumber: 08LTB79, Year: 2008, PEL ratio: 0.04396, Grade: C\",\"StationNumber: 08LTB82, Year: 2008, PEL ratio: 0.02777, Grade: C\",\"StationNumber: 08MR08, Year: 2008, PEL ratio: 0.03334, Grade: C\",\"StationNumber: 08MR35, Year: 2008, PEL ratio: 0.02726, Grade: C\",\"StationNumber: 08MR40, Year: 2008, PEL ratio: 0.03952, Grade: C\",\"StationNumber: 08MR43, Year: 2008, PEL ratio: 0.08724, Grade: D\",\"StationNumber: 08MR53, Year: 2008, PEL ratio: 0.02561, Grade: C\",\"StationNumber: 08MR54, Year: 2008, PEL ratio: 0.02649, Grade: C\",\"StationNumber: 08MTB37, Year: 2008, PEL ratio: 0.02715, Grade: C\",\"StationNumber: 08MTB47, Year: 2008, PEL ratio: 0.02945, Grade: C\",\"StationNumber: 08MTB53, Year: 2008, PEL ratio: 0, Grade: A\",\"StationNumber: 08MTB62, Year: 2008, PEL ratio: 0.03147, Grade: C\",\"StationNumber: 08MTB73, Year: 2008, PEL ratio: 0.085, Grade: C\",\"StationNumber: 08OTB05, Year: 2008, PEL ratio: 0.02469, Grade: C\",\"StationNumber: 08OTB07, Year: 2008, PEL ratio: 0.03217, Grade: C\",\"StationNumber: 08OTB13, Year: 2008, PEL ratio: 0.02418, Grade: C\",\"StationNumber: 08OTB15, Year: 2008, PEL ratio: 0.03404, Grade: C\",\"StationNumber: 08OTB17, Year: 2008, PEL ratio: 0.02613, Grade: C\",\"StationNumber: 08OTB23, Year: 2008, PEL ratio: 0.03692, Grade: C\",\"StationNumber: 08OTB27, Year: 2008, PEL ratio: 0.03973, Grade: C\",\"StationNumber: 08TCB01, Year: 2008, PEL ratio: 0.02193, Grade: C\",\"StationNumber: 08TCB07, Year: 2008, PEL ratio: 0.02717, Grade: C\",\"StationNumber: 08TCB26, Year: 2008, PEL ratio: 0.03977, Grade: C\",\"StationNumber: 09BCB06, Year: 2009, PEL ratio: 0.2271, Grade: D\",\"StationNumber: 09BCB07, Year: 2009, PEL ratio: 0.22765, Grade: D\",\"StationNumber: 09BCB10, Year: 2009, PEL ratio: 0.22887, Grade: D\",\"StationNumber: 09BCB18, Year: 2009, PEL ratio: 0.22738, Grade: D\",\"StationNumber: 09BCB20, Year: 2009, PEL ratio: 0.2271, Grade: D\",\"StationNumber: 09BCB22, Year: 2009, PEL ratio: 0.22745, Grade: D\",\"StationNumber: 09BCB25, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 09BCB31, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 09BCB34, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 09BCB36, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 09BCB43, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 09HB05, Year: 2009, PEL ratio: 0.2648, Grade: D\",\"StationNumber: 09HB11, Year: 2009, PEL ratio: 0.23926, Grade: D\",\"StationNumber: 09HB15, Year: 2009, PEL ratio: 0.2285, Grade: D\",\"StationNumber: 09HB23, Year: 2009, PEL ratio: 0.22717, Grade: D\",\"StationNumber: 09HB24, Year: 2009, PEL ratio: 0.22751, Grade: D\",\"StationNumber: 09HB32, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 09HB35, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 09HB53, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 09HB56, Year: 2009, PEL ratio: 0.24223, Grade: D\",\"StationNumber: 09LTB77, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 09LTB90, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 09MR17, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 09MR30, Year: 2009, PEL ratio: 0.22715, Grade: D\",\"StationNumber: 09MR36, Year: 2009, PEL ratio: 0.23016, Grade: D\",\"StationNumber: 09MR46, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 09MR49, Year: 2009, PEL ratio: 0.22727, Grade: D\",\"StationNumber: 09MTB42, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 09MTB44, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 09MTB48, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 09MTB50, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 09MTB63, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 09MTB72, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 09OTB09, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 09OTB10, Year: 2009, PEL ratio: 0.23279, Grade: D\",\"StationNumber: 09OTB14, Year: 2009, PEL ratio: 0.22724, Grade: D\",\"StationNumber: 09OTB16, Year: 2009, PEL ratio: 0.2271, Grade: D\",\"StationNumber: 09OTB20, Year: 2009, PEL ratio: 0.22738, Grade: D\",\"StationNumber: 09OTB28, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 09OTB29, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 09TCB10, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 09TCB13, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 09TCB14, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 09TCB22, Year: 2009, PEL ratio: 0.22706, Grade: D\",\"StationNumber: 10BCB06, Year: 2010, PEL ratio: 0.05418, Grade: C\",\"StationNumber: 10BCB11, Year: 2010, PEL ratio: 0.06776, Grade: C\",\"StationNumber: 10BCB17, Year: 2010, PEL ratio: 0.05636, Grade: C\",\"StationNumber: 10BCB25, Year: 2010, PEL ratio: 0.04525, Grade: C\",\"StationNumber: 10BCB28, Year: 2010, PEL ratio: 0.058, Grade: C\",\"StationNumber: 10BCB30, Year: 2010, PEL ratio: 0.05066, Grade: C\",\"StationNumber: 10BCB37, Year: 2010, PEL ratio: 0.05759, Grade: C\",\"StationNumber: 10BCB41, Year: 2010, PEL ratio: 0.16956, Grade: D\",\"StationNumber: 10BCB46, Year: 2010, PEL ratio: 0.04398, Grade: C\",\"StationNumber: 10BCB47, Year: 2010, PEL ratio: 0.05076, Grade: C\",\"StationNumber: 10BCB49, Year: 2010, PEL ratio: 0.04946, Grade: C\",\"StationNumber: 10HB21, Year: 2010, PEL ratio: 0.11698, Grade: D\",\"StationNumber: 10HB22, Year: 2010, PEL ratio: 0.1448, Grade: D\",\"StationNumber: 10HB25, Year: 2010, PEL ratio: 0.06694, Grade: C\",\"StationNumber: 10HB26, Year: 2010, PEL ratio: 0.09827, Grade: D\",\"StationNumber: 10HB34, Year: 2010, PEL ratio: 0.05702, Grade: C\",\"StationNumber: 10HB44, Year: 2010, PEL ratio: 0.05266, Grade: C\",\"StationNumber: 10HB46, Year: 2010, PEL ratio: 0.05934, Grade: C\",\"StationNumber: 10HB48, Year: 2010, PEL ratio: 0.05189, Grade: C\",\"StationNumber: 10HB54, Year: 2010, PEL ratio: 0.06254, Grade: C\",\"StationNumber: 10LTB71, Year: 2010, PEL ratio: 0.03978, Grade: C\",\"StationNumber: 10LTB76, Year: 2010, PEL ratio: 0.04208, Grade: C\",\"StationNumber: 10LTB89, Year: 2010, PEL ratio: 0.04389, Grade: C\",\"StationNumber: 10MR25, Year: 2010, PEL ratio: 0.04098, Grade: C\",\"StationNumber: 10MR29, Year: 2010, PEL ratio: 0.04883, Grade: C\",\"StationNumber: 10MR33, Year: 2010, PEL ratio: 0.04098, Grade: C\",\"StationNumber: 10MR40, Year: 2010, PEL ratio: 0.05975, Grade: C\",\"StationNumber: 10MR44, Year: 2010, PEL ratio: 0.05334, Grade: C\",\"StationNumber: 10MTB30, Year: 2010, PEL ratio: 0.11699, Grade: D\",\"StationNumber: 10MTB35, Year: 2010, PEL ratio: 0.0404, Grade: C\",\"StationNumber: 10MTB43, Year: 2010, PEL ratio: 0.05591, Grade: C\",\"StationNumber: 10MTB53, Year: 2010, PEL ratio: 0.05385, Grade: C\",\"StationNumber: 10MTB56, Year: 2010, PEL ratio: 0.04796, Grade: C\",\"StationNumber: 10OTB04, Year: 2010, PEL ratio: 0.06327, Grade: C\",\"StationNumber: 10OTB05, Year: 2010, PEL ratio: 0.04514, Grade: C\",\"StationNumber: 10OTB07, Year: 2010, PEL ratio: 0.0966, Grade: D\",\"StationNumber: 10OTB08, Year: 2010, PEL ratio: 0.05185, Grade: C\",\"StationNumber: 10OTB09, Year: 2010, PEL ratio: 0.0499, Grade: C\",\"StationNumber: 10OTB12, Year: 2010, PEL ratio: 0.04749, Grade: C\",\"StationNumber: 10OTB13, Year: 2010, PEL ratio: 0.09096, Grade: D\",\"StationNumber: 10OTB14, Year: 2010, PEL ratio: 0.05743, Grade: C\",\"StationNumber: 10OTB15, Year: 2010, PEL ratio: 0.0503, Grade: C\",\"StationNumber: 10OTB16, Year: 2010, PEL ratio: 0.04904, Grade: C\",\"StationNumber: 10OTB18, Year: 2010, PEL ratio: 0.04797, Grade: C\",\"StationNumber: 10OTB19, Year: 2010, PEL ratio: 0.04649, Grade: C\",\"StationNumber: 10OTB20, Year: 2010, PEL ratio: 0.05188, Grade: C\",\"StationNumber: 10OTB21, Year: 2010, PEL ratio: 0.09696, Grade: D\",\"StationNumber: 10OTB24, Year: 2010, PEL ratio: 0.04571, Grade: C\",\"StationNumber: 10OTB25, Year: 2010, PEL ratio: 0.04516, Grade: C\",\"StationNumber: 10OTB26, Year: 2010, PEL ratio: 0.06229, Grade: C\",\"StationNumber: 10OTB28, Year: 2010, PEL ratio: 0.05494, Grade: C\",\"StationNumber: 10OTB29, Year: 2010, PEL ratio: 0.0463, Grade: C\",\"StationNumber: 10OTB96, Year: 2010, PEL ratio: 0.09566, Grade: D\",\"StationNumber: 10OTB97, Year: 2010, PEL ratio: 0.0741, Grade: C\",\"StationNumber: 10OTB98, Year: 2010, PEL ratio: 0.057, Grade: C\",\"StationNumber: 10TCB01, Year: 2010, PEL ratio: 0.03856, Grade: C\",\"StationNumber: 10TCB11, Year: 2010, PEL ratio: 0.04704, Grade: C\",\"StationNumber: 10TCB13, Year: 2010, PEL ratio: 0.04199, Grade: C\",\"StationNumber: 10TCB20, Year: 2010, PEL ratio: 0.03693, Grade: C\",\"StationNumber: 11BCB05, Year: 2011, PEL ratio: 0.03406, Grade: C\",\"StationNumber: 11BCB09, Year: 2011, PEL ratio: 0.07696, Grade: C\",\"StationNumber: 11BCB12, Year: 2011, PEL ratio: 0.03876, Grade: C\",\"StationNumber: 11BCB20, Year: 2011, PEL ratio: 0.0708, Grade: C\",\"StationNumber: 11BCB22, Year: 2011, PEL ratio: 0.03401, Grade: C\",\"StationNumber: 11BCB26, Year: 2011, PEL ratio: 0.05588, Grade: C\",\"StationNumber: 11BCB35, Year: 2011, PEL ratio: 0.0405, Grade: C\",\"StationNumber: 11BCB42, Year: 2011, PEL ratio: 0.05499, Grade: C\",\"StationNumber: 11BCB43, Year: 2011, PEL ratio: 0.03362, Grade: C\",\"StationNumber: 11BCB44, Year: 2011, PEL ratio: 0.03382, Grade: C\",\"StationNumber: 11BCB48, Year: 2011, PEL ratio: 0.03412, Grade: C\",\"StationNumber: 11HB09, Year: 2011, PEL ratio: 0.04257, Grade: C\",\"StationNumber: 11HB13, Year: 2011, PEL ratio: 0.05996, Grade: C\",\"StationNumber: 11HB29, Year: 2011, PEL ratio: 0.0821, Grade: C\",\"StationNumber: 11HB31, Year: 2011, PEL ratio: 0.0332, Grade: C\",\"StationNumber: 11HB35, Year: 2011, PEL ratio: 0.03838, Grade: C\",\"StationNumber: 11HB36, Year: 2011, PEL ratio: 0.04301, Grade: C\",\"StationNumber: 11HB38, Year: 2011, PEL ratio: 0.03229, Grade: C\",\"StationNumber: 11HB40, Year: 2011, PEL ratio: 0.04344, Grade: C\",\"StationNumber: 11HB47, Year: 2011, PEL ratio: 0.07343, Grade: C\",\"StationNumber: 11LTB69, Year: 2011, PEL ratio: 0.03431, Grade: C\",\"StationNumber: 11LTB75, Year: 2011, PEL ratio: 0.03175, Grade: C\",\"StationNumber: 11LTB80, Year: 2011, PEL ratio: 0.02849, Grade: C\",\"StationNumber: 11MR18, Year: 2011, PEL ratio: 0.03158, Grade: C\",\"StationNumber: 11MR32, Year: 2011, PEL ratio: 0.08626, Grade: D\",\"StationNumber: 11MR35, Year: 2011, PEL ratio: 0.2895, Grade: F\",\"StationNumber: 11MR37, Year: 2011, PEL ratio: 0.04922, Grade: C\",\"StationNumber: 11MR43, Year: 2011, PEL ratio: 0.22016, Grade: D\",\"StationNumber: 11MR45, Year: 2011, PEL ratio: 0.05964, Grade: C\",\"StationNumber: 11MR52, Year: 2011, PEL ratio: 0.05915, Grade: C\",\"StationNumber: 11MTB39, Year: 2011, PEL ratio: 0.03658, Grade: C\",\"StationNumber: 11MTB44, Year: 2011, PEL ratio: 0.03276, Grade: C\",\"StationNumber: 11MTB46, Year: 2011, PEL ratio: 0.03321, Grade: C\",\"StationNumber: 11MTB54, Year: 2011, PEL ratio: 0.03421, Grade: C\",\"StationNumber: 11MTB72, Year: 2011, PEL ratio: 0.03547, Grade: C\",\"StationNumber: 11OTB08, Year: 2011, PEL ratio: 0.05594, Grade: C\",\"StationNumber: 11OTB09, Year: 2011, PEL ratio: 0.03373, Grade: C\",\"StationNumber: 11OTB18, Year: 2011, PEL ratio: 0.03456, Grade: C\",\"StationNumber: 11OTB24, Year: 2011, PEL ratio: 0.03411, Grade: C\",\"StationNumber: 11OTB26, Year: 2011, PEL ratio: 0.03346, Grade: C\",\"StationNumber: 11OTB31, Year: 2011, PEL ratio: 0.03496, Grade: C\",\"StationNumber: 11OTB32, Year: 2011, PEL ratio: 0.03287, Grade: C\",\"StationNumber: 11TCB10, Year: 2011, PEL ratio: 0.02871, Grade: C\",\"StationNumber: 11TCB12, Year: 2011, PEL ratio: 0.03385, Grade: C\",\"StationNumber: 12BCB06, Year: 2012, PEL ratio: 0.04452, Grade: C\",\"StationNumber: 12BCB14, Year: 2012, PEL ratio: 0.38368, Grade: F\",\"StationNumber: 12BCB19, Year: 2012, PEL ratio: 0.03721, Grade: C\",\"StationNumber: 12BCB23, Year: 2012, PEL ratio: 0.04469, Grade: C\",\"StationNumber: 12BCB25, Year: 2012, PEL ratio: 0.03922, Grade: C\",\"StationNumber: 12BCB27, Year: 2012, PEL ratio: 0.07968, Grade: C\",\"StationNumber: 12BCB35, Year: 2012, PEL ratio: 0.04033, Grade: C\",\"StationNumber: 12BCB40, Year: 2012, PEL ratio: 0.04044, Grade: C\",\"StationNumber: 12BCB44, Year: 2012, PEL ratio: 0.03462, Grade: C\",\"StationNumber: 12BCB46, Year: 2012, PEL ratio: 0.03927, Grade: C\",\"StationNumber: 12BCB49, Year: 2012, PEL ratio: 0.04079, Grade: C\",\"StationNumber: 12HB27, Year: 2012, PEL ratio: 0.04713, Grade: C\",\"StationNumber: 12HB28, Year: 2012, PEL ratio: 0.0439, Grade: C\",\"StationNumber: 12HB31, Year: 2012, PEL ratio: 0.13887, Grade: D\",\"StationNumber: 12HB32, Year: 2012, PEL ratio: 0.04521, Grade: C\",\"StationNumber: 12HB38, Year: 2012, PEL ratio: 0.05609, Grade: C\",\"StationNumber: 12HB40, Year: 2012, PEL ratio: 0.03976, Grade: C\",\"StationNumber: 12HB45, Year: 2012, PEL ratio: 0.07001, Grade: C\",\"StationNumber: 12HB53, Year: 2012, PEL ratio: 0.045, Grade: C\",\"StationNumber: 12HB54, Year: 2012, PEL ratio: 0.04384, Grade: C\",\"StationNumber: 12LTB78, Year: 2012, PEL ratio: 0.04261, Grade: C\",\"StationNumber: 12LTB84, Year: 2012, PEL ratio: 0.03384, Grade: C\",\"StationNumber: 12LTB93, Year: 2012, PEL ratio: 0.03901, Grade: C\",\"StationNumber: 12MR08, Year: 2012, PEL ratio: 0.03605, Grade: C\",\"StationNumber: 12MR17, Year: 2012, PEL ratio: 0.03946, Grade: C\",\"StationNumber: 12MR33, Year: 2012, PEL ratio: 0.0386, Grade: C\",\"StationNumber: 12MR36, Year: 2012, PEL ratio: 0.0414, Grade: C\",\"StationNumber: 12MR43, Year: 2012, PEL ratio: 0.04657, Grade: C\",\"StationNumber: 12MR46, Year: 2012, PEL ratio: 0.0353, Grade: C\",\"StationNumber: 12MR54, Year: 2012, PEL ratio: 0.03951, Grade: C\",\"StationNumber: 12MTB47, Year: 2012, PEL ratio: 0.04162, Grade: C\",\"StationNumber: 12MTB53, Year: 2012, PEL ratio: 0.03721, Grade: C\",\"StationNumber: 12MTB58, Year: 2012, PEL ratio: 0.05309, Grade: C\",\"StationNumber: 12MTB63, Year: 2012, PEL ratio: 0.03957, Grade: C\",\"StationNumber: 12MTB64, Year: 2012, PEL ratio: 0.04165, Grade: C\",\"StationNumber: 12OTB04, Year: 2012, PEL ratio: 0.13065, Grade: D\",\"StationNumber: 12OTB08, Year: 2012, PEL ratio: 0.03843, Grade: C\",\"StationNumber: 12OTB13, Year: 2012, PEL ratio: 0.04154, Grade: C\",\"StationNumber: 12OTB14, Year: 2012, PEL ratio: 0.03612, Grade: C\",\"StationNumber: 12OTB18, Year: 2012, PEL ratio: 0.04305, Grade: C\",\"StationNumber: 12OTB19, Year: 2012, PEL ratio: 0.03486, Grade: C\",\"StationNumber: 12OTB20, Year: 2012, PEL ratio: 0.04146, Grade: C\",\"StationNumber: 12TCB05, Year: 2012, PEL ratio: 0.03318, Grade: C\",\"StationNumber: 12TCB13, Year: 2012, PEL ratio: 0.03331, Grade: C\",\"StationNumber: 13BCB05, Year: 2013, PEL ratio: 0.16727, Grade: D\",\"StationNumber: 13BCB07, Year: 2013, PEL ratio: 0.04534, Grade: C\",\"StationNumber: 13BCB09, Year: 2013, PEL ratio: 0.04449, Grade: C\",\"StationNumber: 13BCB10, Year: 2013, PEL ratio: 0.03598, Grade: C\",\"StationNumber: 13BCB11, Year: 2013, PEL ratio: 0.1881, Grade: D\",\"StationNumber: 13BCB17, Year: 2013, PEL ratio: 0.10487, Grade: D\",\"StationNumber: 13BCB22, Year: 2013, PEL ratio: 0.0432, Grade: C\",\"StationNumber: 13BCB30, Year: 2013, PEL ratio: 0.03594, Grade: C\",\"StationNumber: 13BCB41, Year: 2013, PEL ratio: 0.03671, Grade: C\",\"StationNumber: 13BCB43, Year: 2013, PEL ratio: 0.03609, Grade: C\",\"StationNumber: 13BCB48, Year: 2013, PEL ratio: 0.04681, Grade: C\",\"StationNumber: 13HB09, Year: 2013, PEL ratio: 0.07695, Grade: C\",\"StationNumber: 13HB13, Year: 2013, PEL ratio: 0.0831, Grade: C\",\"StationNumber: 13HB25, Year: 2013, PEL ratio: 0.03306, Grade: C\",\"StationNumber: 13HB26, Year: 2013, PEL ratio: 0.05412, Grade: C\",\"StationNumber: 13HB35, Year: 2013, PEL ratio: 0.03811, Grade: C\",\"StationNumber: 13HB36, Year: 2013, PEL ratio: 0.18861, Grade: D\",\"StationNumber: 13HB41, Year: 2013, PEL ratio: 0.03847, Grade: C\",\"StationNumber: 13HB44, Year: 2013, PEL ratio: 0.09625, Grade: D\",\"StationNumber: 13HB48, Year: 2013, PEL ratio: 0.0373, Grade: C\",\"StationNumber: 13LTB79, Year: 2013, PEL ratio: 0.03872, Grade: C\",\"StationNumber: 13LTB82, Year: 2013, PEL ratio: 0.03513, Grade: C\",\"StationNumber: 13LTB86, Year: 2013, PEL ratio: 0.03287, Grade: C\",\"StationNumber: 13MR09, Year: 2013, PEL ratio: 0.03565, Grade: C\",\"StationNumber: 13MR24, Year: 2013, PEL ratio: 0.03695, Grade: C\",\"StationNumber: 13MR31, Year: 2013, PEL ratio: 0.34066, Grade: F\",\"StationNumber: 13MR44, Year: 2013, PEL ratio: 0.09108, Grade: D\",\"StationNumber: 13MR45, Year: 2013, PEL ratio: 0.06721, Grade: C\",\"StationNumber: 13MR48, Year: 2013, PEL ratio: 0.0568, Grade: C\",\"StationNumber: 13MTB34, Year: 2013, PEL ratio: 0.03171, Grade: C\",\"StationNumber: 13MTB35, Year: 2013, PEL ratio: 0.05215, Grade: C\",\"StationNumber: 13MTB41, Year: 2013, PEL ratio: 0.03838, Grade: C\",\"StationNumber: 13MTB45, Year: 2013, PEL ratio: 0.03368, Grade: C\",\"StationNumber: 13MTB55, Year: 2013, PEL ratio: 0.06478, Grade: C\",\"StationNumber: 13OTB12, Year: 2013, PEL ratio: 0.04515, Grade: C\",\"StationNumber: 13OTB15, Year: 2013, PEL ratio: 0.03702, Grade: C\",\"StationNumber: 13OTB16, Year: 2013, PEL ratio: 0.04069, Grade: C\",\"StationNumber: 13OTB21, Year: 2013, PEL ratio: 0.04235, Grade: C\",\"StationNumber: 13OTB27, Year: 2013, PEL ratio: 0.03527, Grade: C\",\"StationNumber: 13OTB28, Year: 2013, PEL ratio: 0.03653, Grade: C\",\"StationNumber: 13OTB29, Year: 2013, PEL ratio: 0.04087, Grade: C\",\"StationNumber: 13TCB01, Year: 2013, PEL ratio: 0.03209, Grade: C\",\"StationNumber: 13TCB11, Year: 2013, PEL ratio: 0.03349, Grade: C\",\"StationNumber: 13TCB14, Year: 2013, PEL ratio: 0.03452, Grade: C\",\"StationNumber: 14BCB03, Year: 2014, PEL ratio: 0.07223, Grade: C\",\"StationNumber: 14BCB12, Year: 2014, PEL ratio: 0.03971, Grade: C\",\"StationNumber: 14BCB15, Year: 2014, PEL ratio: 0.12267, Grade: D\",\"StationNumber: 14BCB17, Year: 2014, PEL ratio: 0.03495, Grade: C\",\"StationNumber: 14BCB20, Year: 2014, PEL ratio: 0.04709, Grade: C\",\"StationNumber: 14BCB25, Year: 2014, PEL ratio: 0.01763, Grade: B\",\"StationNumber: 14BCB29, Year: 2014, PEL ratio: 0.01869, Grade: B\",\"StationNumber: 14BCB33, Year: 2014, PEL ratio: 0.03039, Grade: C\",\"StationNumber: 14BCB35, Year: 2014, PEL ratio: 0.08684, Grade: D\",\"StationNumber: 14BCB41, Year: 2014, PEL ratio: 0.03173, Grade: C\",\"StationNumber: 14BCB47, Year: 2014, PEL ratio: 0.02445, Grade: C\",\"StationNumber: 14HB20, Year: 2014, PEL ratio: 0.02692, Grade: C\",\"StationNumber: 14HB21, Year: 2014, PEL ratio: 0.11022, Grade: D\",\"StationNumber: 14HB26, Year: 2014, PEL ratio: 0.04422, Grade: C\",\"StationNumber: 14HB33, Year: 2014, PEL ratio: 0.04596, Grade: C\",\"StationNumber: 14HB43, Year: 2014, PEL ratio: 0.02882, Grade: C\",\"StationNumber: 14HB44, Year: 2014, PEL ratio: 0.02425, Grade: C\",\"StationNumber: 14HB46, Year: 2014, PEL ratio: 0.02682, Grade: C\",\"StationNumber: 14HB47, Year: 2014, PEL ratio: 0.02598, Grade: C\",\"StationNumber: 14HB54, Year: 2014, PEL ratio: 0.0288, Grade: C\",\"StationNumber: 14LTB71, Year: 2014, PEL ratio: 0.02041, Grade: B\",\"StationNumber: 14LTB81, Year: 2014, PEL ratio: 0.02037, Grade: B\",\"StationNumber: 14LTB90, Year: 2014, PEL ratio: 0.01877, Grade: B\",\"StationNumber: 14MR29, Year: 2014, PEL ratio: 0.01907, Grade: B\",\"StationNumber: 14MR35, Year: 2014, PEL ratio: 0.0555, Grade: C\",\"StationNumber: 14MR37, Year: 2014, PEL ratio: 0.09494, Grade: D\",\"StationNumber: 14MR38, Year: 2014, PEL ratio: 0.1108, Grade: D\",\"StationNumber: 14MR47, Year: 2014, PEL ratio: 0.01791, Grade: B\",\"StationNumber: 14MTB39, Year: 2014, PEL ratio: 0.02273, Grade: C\",\"StationNumber: 14MTB41, Year: 2014, PEL ratio: 0.03062, Grade: C\",\"StationNumber: 14MTB46, Year: 2014, PEL ratio: 0.02094, Grade: C\",\"StationNumber: 14MTB54, Year: 2014, PEL ratio: 0.02078, Grade: C\",\"StationNumber: 14MTB63, Year: 2014, PEL ratio: 0.02282, Grade: C\",\"StationNumber: 14OTB04, Year: 2014, PEL ratio: 0.02755, Grade: C\",\"StationNumber: 14OTB08, Year: 2014, PEL ratio: 0.03792, Grade: C\",\"StationNumber: 14OTB14, Year: 2014, PEL ratio: 0.04277, Grade: C\",\"StationNumber: 14OTB18, Year: 2014, PEL ratio: 2.41188, Grade: F\",\"StationNumber: 14OTB19, Year: 2014, PEL ratio: 0.01969, Grade: B\",\"StationNumber: 14OTB21, Year: 2014, PEL ratio: 0.02613, Grade: C\",\"StationNumber: 14OTB25, Year: 2014, PEL ratio: 0.02671, Grade: C\",\"StationNumber: 14TCB15, Year: 2014, PEL ratio: 0.03044, Grade: C\",\"StationNumber: 14TCB20, Year: 2014, PEL ratio: 0.02875, Grade: C\",\"StationNumber: 14TCB21, Year: 2014, PEL ratio: 0.0283, Grade: C\",\"StationNumber: 14TCB22, Year: 2014, PEL ratio: 0.01653, Grade: B\",\"StationNumber: 15BCB09, Year: 2015, PEL ratio: 0.03637, Grade: C\",\"StationNumber: 15BCB12, Year: 2015, PEL ratio: 0.04372, Grade: C\",\"StationNumber: 15BCB15, Year: 2015, PEL ratio: 0.04656, Grade: C\",\"StationNumber: 15BCB26, Year: 2015, PEL ratio: 0.05585, Grade: C\",\"StationNumber: 15BCB30, Year: 2015, PEL ratio: 0.04815, Grade: C\",\"StationNumber: 15BCB31, Year: 2015, PEL ratio: 0.13946, Grade: D\",\"StationNumber: 15BCB34, Year: 2015, PEL ratio: 0.03182, Grade: C\",\"StationNumber: 15BCB39, Year: 2015, PEL ratio: 0.03826, Grade: C\",\"StationNumber: 15BCB43, Year: 2015, PEL ratio: 0.03861, Grade: C\",\"StationNumber: 15BCB47, Year: 2015, PEL ratio: 0.06181, Grade: C\",\"StationNumber: 15BCB48, Year: 2015, PEL ratio: 0.03381, Grade: C\",\"StationNumber: 15HB09, Year: 2015, PEL ratio: 0.15218, Grade: D\",\"StationNumber: 15HB14, Year: 2015, PEL ratio: 0.08241, Grade: C\",\"StationNumber: 15HB27, Year: 2015, PEL ratio: 0.07462, Grade: C\",\"StationNumber: 15HB36, Year: 2015, PEL ratio: 0.04156, Grade: C\",\"StationNumber: 15HB37, Year: 2015, PEL ratio: 0.03697, Grade: C\",\"StationNumber: 15HB39, Year: 2015, PEL ratio: 0.03681, Grade: C\",\"StationNumber: 15HB40, Year: 2015, PEL ratio: 0.03913, Grade: C\",\"StationNumber: 15HB41, Year: 2015, PEL ratio: 0.03531, Grade: C\",\"StationNumber: 15HB48, Year: 2015, PEL ratio: 0.038, Grade: C\",\"StationNumber: 15LTB70, Year: 2015, PEL ratio: 0.03226, Grade: C\",\"StationNumber: 15LTB76, Year: 2015, PEL ratio: 0.03036, Grade: C\",\"StationNumber: 15LTB94, Year: 2015, PEL ratio: 0.03816, Grade: C\",\"StationNumber: 15MR08, Year: 2015, PEL ratio: 0.03832, Grade: C\",\"StationNumber: 15MR28, Year: 2015, PEL ratio: 0.03623, Grade: C\",\"StationNumber: 15MR30, Year: 2015, PEL ratio: 0.03637, Grade: C\",\"StationNumber: 15MR33, Year: 2015, PEL ratio: 0.15657, Grade: D\",\"StationNumber: 15MR42, Year: 2015, PEL ratio: 0.04571, Grade: C\",\"StationNumber: 15MR52, Year: 2015, PEL ratio: 0.03954, Grade: C\",\"StationNumber: 15MTB40, Year: 2015, PEL ratio: 0.0354, Grade: C\",\"StationNumber: 15MTB49, Year: 2015, PEL ratio: 0.04217, Grade: C\",\"StationNumber: 15MTB52, Year: 2015, PEL ratio: 0.03085, Grade: C\",\"StationNumber: 15MTB55, Year: 2015, PEL ratio: 0.0351, Grade: C\",\"StationNumber: 15MTB62, Year: 2015, PEL ratio: 0.03246, Grade: C\",\"StationNumber: 15OTB12, Year: 2015, PEL ratio: 0.04593, Grade: C\",\"StationNumber: 15OTB15, Year: 2015, PEL ratio: 0.05137, Grade: C\",\"StationNumber: 15OTB20, Year: 2015, PEL ratio: 0.05337, Grade: C\",\"StationNumber: 15OTB24, Year: 2015, PEL ratio: 0.04, Grade: C\",\"StationNumber: 15OTB26, Year: 2015, PEL ratio: 0.03346, Grade: C\",\"StationNumber: 15OTB28, Year: 2015, PEL ratio: 0.03812, Grade: C\",\"StationNumber: 15OTB29, Year: 2015, PEL ratio: 0.05653, Grade: C\",\"StationNumber: 15TCB01, Year: 2015, PEL ratio: 0.02764, Grade: C\",\"StationNumber: 15TCB11, Year: 2015, PEL ratio: 0.03474, Grade: C\",\"StationNumber: 15TCB12, Year: 2015, PEL ratio: 0.04456, Grade: C\",\"StationNumber: 16BCB20, Year: 2016, PEL ratio: 0.02494, Grade: C\",\"StationNumber: 16BCB22, Year: 2016, PEL ratio: 0.01314, Grade: B\",\"StationNumber: 16BCB25, Year: 2016, PEL ratio: 0.03973, Grade: C\",\"StationNumber: 16BCB29, Year: 2016, PEL ratio: 0.00699, Grade: A\",\"StationNumber: 16BCB34, Year: 2016, PEL ratio: 0.01356, Grade: B\",\"StationNumber: 16BCB35, Year: 2016, PEL ratio: 0.01331, Grade: B\",\"StationNumber: 16BCB36, Year: 2016, PEL ratio: 0.03548, Grade: C\",\"StationNumber: 16BCB37, Year: 2016, PEL ratio: 0.02852, Grade: C\",\"StationNumber: 16BCB41, Year: 2016, PEL ratio: 0.01322, Grade: B\",\"StationNumber: 16BCB42, Year: 2016, PEL ratio: 0.01254, Grade: B\",\"StationNumber: 16BCB43, Year: 2016, PEL ratio: 0.0166, Grade: B\",\"StationNumber: 16DH07-1, Year: 2016, PEL ratio: 0.18391, Grade: D\",\"StationNumber: 16DH07-2, Year: 2016, PEL ratio: 0.13524, Grade: D\",\"StationNumber: 16DH07-3, Year: 2016, PEL ratio: 0.20542, Grade: D\",\"StationNumber: 16DH07-4, Year: 2016, PEL ratio: 0.01549, Grade: B\",\"StationNumber: 16HB19, Year: 2016, PEL ratio: 0.05887, Grade: C\",\"StationNumber: 16HB20, Year: 2016, PEL ratio: 0.04907, Grade: C\",\"StationNumber: 16HB21, Year: 2016, PEL ratio: 0.0132, Grade: B\",\"StationNumber: 16HB27, Year: 2016, PEL ratio: 0.02076, Grade: C\",\"StationNumber: 16HB28, Year: 2016, PEL ratio: 0.9678, Grade: F\",\"StationNumber: 16HB32, Year: 2016, PEL ratio: 0.08862, Grade: D\",\"StationNumber: 16HB33, Year: 2016, PEL ratio: 0.01043, Grade: B\",\"StationNumber: 16HB37, Year: 2016, PEL ratio: 0.02529, Grade: C\",\"StationNumber: 16HB48, Year: 2016, PEL ratio: 0.00834, Grade: B\",\"StationNumber: 16DH04-1, Year: 2016, PEL ratio: 0.01392, Grade: B\",\"StationNumber: 16DH04-2, Year: 2016, PEL ratio: 0.01391, Grade: B\",\"StationNumber: 16DH04-3, Year: 2016, PEL ratio: 0.0173, Grade: B\",\"StationNumber: 16DH04-4, Year: 2016, PEL ratio: 0.01483, Grade: B\",\"StationNumber: 16DH08-1, Year: 2016, PEL ratio: 0.01209, Grade: B\",\"StationNumber: 16DH08-2, Year: 2016, PEL ratio: 0.01315, Grade: B\",\"StationNumber: 16DH08-3, Year: 2016, PEL ratio: 0.01495, Grade: B\",\"StationNumber: 16DH08-4, Year: 2016, PEL ratio: 0.0073, Grade: A\",\"StationNumber: 16DH09-1, Year: 2016, PEL ratio: 0.0417, Grade: C\",\"StationNumber: 16DH09-2, Year: 2016, PEL ratio: 0.0163, Grade: B\",\"StationNumber: 16DH09-3, Year: 2016, PEL ratio: 0.01326, Grade: B\",\"StationNumber: 16DH09-4, Year: 2016, PEL ratio: 0.01211, Grade: B\",\"StationNumber: 16LTB71, Year: 2016, PEL ratio: 0.02031, Grade: B\",\"StationNumber: 16LTB79, Year: 2016, PEL ratio: 0.03301, Grade: C\",\"StationNumber: 16LTB85, Year: 2016, PEL ratio: 0.01936, Grade: B\",\"StationNumber: 16MR17, Year: 2016, PEL ratio: 0.01448, Grade: B\",\"StationNumber: 16MR25, Year: 2016, PEL ratio: 0.01518, Grade: B\",\"StationNumber: 16MR29, Year: 2016, PEL ratio: 0.02155, Grade: C\",\"StationNumber: 16MR33, Year: 2016, PEL ratio: 0.04406, Grade: C\",\"StationNumber: 16MR43, Year: 2016, PEL ratio: 0.03343, Grade: C\",\"StationNumber: 16MR44, Year: 2016, PEL ratio: 0.01835, Grade: B\",\"StationNumber: 16MR45, Year: 2016, PEL ratio: 0.09741, Grade: D\",\"StationNumber: 16DH06-1, Year: 2016, PEL ratio: 0.03826, Grade: C\",\"StationNumber: 16DH06-2, Year: 2016, PEL ratio: 0.03293, Grade: C\",\"StationNumber: 16DH06-3, Year: 2016, PEL ratio: 0.0963, Grade: D\",\"StationNumber: 16DH06-4, Year: 2016, PEL ratio: 0.04943, Grade: C\",\"StationNumber: 16DH10-1, Year: 2016, PEL ratio: 0.0172, Grade: B\",\"StationNumber: 16DH10-2, Year: 2016, PEL ratio: 0.0164, Grade: B\",\"StationNumber: 16DH10-3, Year: 2016, PEL ratio: 0.01826, Grade: B\",\"StationNumber: 16DH10-4, Year: 2016, PEL ratio: 0.01494, Grade: B\",\"StationNumber: 16MTB41, Year: 2016, PEL ratio: 0.04661, Grade: C\",\"StationNumber: 16MTB47, Year: 2016, PEL ratio: 0.01915, Grade: B\",\"StationNumber: 16MTB48, Year: 2016, PEL ratio: 0.02853, Grade: C\",\"StationNumber: 16MTB53, Year: 2016, PEL ratio: 0.01875, Grade: B\",\"StationNumber: 16MTB72, Year: 2016, PEL ratio: 0.01874, Grade: B\",\"StationNumber: 16DH01-1, Year: 2016, PEL ratio: 0.12523, Grade: D\",\"StationNumber: 16DH01-2, Year: 2016, PEL ratio: 0.02653, Grade: C\",\"StationNumber: 16DH01-3, Year: 2016, PEL ratio: 0.14601, Grade: D\",\"StationNumber: 16DH01-4, Year: 2016, PEL ratio: 0.02374, Grade: C\",\"StationNumber: 16DH02-1, Year: 2016, PEL ratio: 0.02317, Grade: C\",\"StationNumber: 16DH02-2, Year: 2016, PEL ratio: 0.01762, Grade: B\",\"StationNumber: 16DH02-3, Year: 2016, PEL ratio: 0.14359, Grade: D\",\"StationNumber: 16DH02-4, Year: 2016, PEL ratio: 0.015, Grade: B\",\"StationNumber: 16DH03-1, Year: 2016, PEL ratio: 0.08286, Grade: C\",\"StationNumber: 16DH03-2, Year: 2016, PEL ratio: 0.12405, Grade: D\",\"StationNumber: 16DH03-3, Year: 2016, PEL ratio: 0.08808, Grade: D\",\"StationNumber: 16DH03-4, Year: 2016, PEL ratio: 0.01809, Grade: B\",\"StationNumber: 16DH05-1, Year: 2016, PEL ratio: 0.05878, Grade: C\",\"StationNumber: 16DH05-2, Year: 2016, PEL ratio: 0.04695, Grade: C\",\"StationNumber: 16DH05-3, Year: 2016, PEL ratio: 0.02045, Grade: B\",\"StationNumber: 16DH05-4, Year: 2016, PEL ratio: 0.01988, Grade: B\",\"StationNumber: 16OTB08, Year: 2016, PEL ratio: 0.02621, Grade: C\",\"StationNumber: 16OTB09, Year: 2016, PEL ratio: 0.03233, Grade: C\",\"StationNumber: 16OTB13, Year: 2016, PEL ratio: 0.04697, Grade: C\",\"StationNumber: 16OTB14, Year: 2016, PEL ratio: 0.02479, Grade: C\",\"StationNumber: 16OTB18, Year: 2016, PEL ratio: 0.01902, Grade: B\",\"StationNumber: 16OTB22, Year: 2016, PEL ratio: 0.02164, Grade: C\",\"StationNumber: 16OTB25, Year: 2016, PEL ratio: 0.01921, Grade: B\",\"StationNumber: 16TCB14, Year: 2016, PEL ratio: 0.01957, Grade: B\",\"StationNumber: 16TCB20, Year: 2016, PEL ratio: 0.01605, Grade: B\",\"StationNumber: 17BCB15, Year: 2017, PEL ratio: 0.05574, Grade: C\",\"StationNumber: 17BCB26, Year: 2017, PEL ratio: 0.04395, Grade: C\",\"StationNumber: 17BCB27, Year: 2017, PEL ratio: 0.05204, Grade: C\",\"StationNumber: 17BCB30, Year: 2017, PEL ratio: 0.03789, Grade: C\",\"StationNumber: 17BCB35, Year: 2017, PEL ratio: 0.0452, Grade: C\",\"StationNumber: 17BCB36, Year: 2017, PEL ratio: 0.03869, Grade: C\",\"StationNumber: 17BCB40, Year: 2017, PEL ratio: 0.04165, Grade: C\",\"StationNumber: 17BCB42, Year: 2017, PEL ratio: 0.03888, Grade: C\",\"StationNumber: 17BCB43, Year: 2017, PEL ratio: 0.0479, Grade: C\",\"StationNumber: 17BCB44, Year: 2017, PEL ratio: 0.04568, Grade: C\",\"StationNumber: 17BCB48, Year: 2017, PEL ratio: 0.04356, Grade: C\",\"StationNumber: 17HB10, Year: 2017, PEL ratio: 0.07514, Grade: C\",\"StationNumber: 17HB13, Year: 2017, PEL ratio: 0.09007, Grade: D\",\"StationNumber: 17HB15, Year: 2017, PEL ratio: 0.20221, Grade: D\",\"StationNumber: 17HB26, Year: 2017, PEL ratio: 0.04364, Grade: C\",\"StationNumber: 17HB34, Year: 2017, PEL ratio: 2.58424, Grade: F\",\"StationNumber: 17HB36, Year: 2017, PEL ratio: 0.06844, Grade: C\",\"StationNumber: 17HB41, Year: 2017, PEL ratio: 0.04206, Grade: C\",\"StationNumber: 17HB42, Year: 2017, PEL ratio: 0.04424, Grade: C\",\"StationNumber: 17HB43, Year: 2017, PEL ratio: 0.04021, Grade: C\",\"StationNumber: 17LTB70, Year: 2017, PEL ratio: 0.03897, Grade: C\",\"StationNumber: 17LTB83, Year: 2017, PEL ratio: 0.03803, Grade: C\",\"StationNumber: 17LTB89, Year: 2017, PEL ratio: 0.03834, Grade: C\",\"StationNumber: 17TCP01, Year: 2017, PEL ratio: 0.05508, Grade: C\",\"StationNumber: 17TCP02, Year: 2017, PEL ratio: 0.05287, Grade: C\",\"StationNumber: 17TCP03, Year: 2017, PEL ratio: 0.05051, Grade: C\",\"StationNumber: 17TCP04, Year: 2017, PEL ratio: 0.05089, Grade: C\",\"StationNumber: 17TCP05, Year: 2017, PEL ratio: 0.04678, Grade: C\",\"StationNumber: 17TCP06, Year: 2017, PEL ratio: 0.07589, Grade: C\",\"StationNumber: 17TCP07, Year: 2017, PEL ratio: 0.051, Grade: C\",\"StationNumber: 17TCP08, Year: 2017, PEL ratio: 0.05778, Grade: C\",\"StationNumber: 17TCP09, Year: 2017, PEL ratio: 0.04474, Grade: C\",\"StationNumber: 17TCP10, Year: 2017, PEL ratio: 0.04683, Grade: C\",\"StationNumber: 17MR09, Year: 2017, PEL ratio: 0.03927, Grade: C\",\"StationNumber: 17MR18, Year: 2017, PEL ratio: 0.04076, Grade: C\",\"StationNumber: 17MR24, Year: 2017, PEL ratio: 0.03902, Grade: C\",\"StationNumber: 17MR32, Year: 2017, PEL ratio: 0.03951, Grade: C\",\"StationNumber: 17MR35, Year: 2017, PEL ratio: 0.0913, Grade: D\",\"StationNumber: 17MR37, Year: 2017, PEL ratio: 0.04193, Grade: C\",\"StationNumber: 17MTB34, Year: 2017, PEL ratio: 0.03827, Grade: C\",\"StationNumber: 17MTB35, Year: 2017, PEL ratio: 0.05891, Grade: C\",\"StationNumber: 17MTB46, Year: 2017, PEL ratio: 0.04189, Grade: C\",\"StationNumber: 17MTB55, Year: 2017, PEL ratio: 0.04047, Grade: C\",\"StationNumber: 17MTB63, Year: 2017, PEL ratio: 0.04197, Grade: C\",\"StationNumber: 17OTB04, Year: 2017, PEL ratio: 0.0536, Grade: C\",\"StationNumber: 17OTB07, Year: 2017, PEL ratio: 0.05219, Grade: C\",\"StationNumber: 17OTB12, Year: 2017, PEL ratio: 0.10245, Grade: D\",\"StationNumber: 17OTB19, Year: 2017, PEL ratio: 0.04286, Grade: C\",\"StationNumber: 17OTB21, Year: 2017, PEL ratio: 0.04087, Grade: C\",\"StationNumber: 17OTB28, Year: 2017, PEL ratio: 0.04793, Grade: C\",\"StationNumber: 17OTB32, Year: 2017, PEL ratio: 0.04013, Grade: C\",\"StationNumber: 17TCB12, Year: 2017, PEL ratio: 0.03885, Grade: C\",\"StationNumber: 17TCB13, Year: 2017, PEL ratio: 0.04488, Grade: C\",\"StationNumber: 17TCB21, Year: 2017, PEL ratio: 0.04358, Grade: C\",\"StationNumber: 18BCB11, Year: 2018, PEL ratio: 0.37337, Grade: F\",\"StationNumber: 18BCB15, Year: 2018, PEL ratio: 0.21905, Grade: D\",\"StationNumber: 18BCB19, Year: 2018, PEL ratio: 0.00266, Grade: A\",\"StationNumber: 18BCB20, Year: 2018, PEL ratio: 0.21369, Grade: D\",\"StationNumber: 18BCB22, Year: 2018, PEL ratio: 0.17683, Grade: D\",\"StationNumber: 18BCB24, Year: 2018, PEL ratio: 0.01165, Grade: B\",\"StationNumber: 18BCB26, Year: 2018, PEL ratio: 0.28634, Grade: F\",\"StationNumber: 18BCB37, Year: 2018, PEL ratio: 0.00425, Grade: A\",\"StationNumber: 18BCB42, Year: 2018, PEL ratio: 0.00155, Grade: A\",\"StationNumber: 18BCB44, Year: 2018, PEL ratio: 0.00316, Grade: A\",\"StationNumber: 18BCB46, Year: 2018, PEL ratio: 0.01455, Grade: B\",\"StationNumber: 18HB14, Year: 2018, PEL ratio: 0.04307, Grade: C\",\"StationNumber: 18HB20, Year: 2018, PEL ratio: 0.05365, Grade: C\",\"StationNumber: 18HB21, Year: 2018, PEL ratio: 0.03344, Grade: C\",\"StationNumber: 18HB26, Year: 2018, PEL ratio: 0.03348, Grade: C\",\"StationNumber: 18HB29, Year: 2018, PEL ratio: 0.0738, Grade: C\",\"StationNumber: 18HB33, Year: 2018, PEL ratio: 0.05804, Grade: C\",\"StationNumber: 18HB38, Year: 2018, PEL ratio: 0.03293, Grade: C\",\"StationNumber: 18HB41, Year: 2018, PEL ratio: 0.00774, Grade: B\",\"StationNumber: 18HB46, Year: 2018, PEL ratio: 1.04973, Grade: F\",\"StationNumber: 18LTB75, Year: 2018, PEL ratio: 0.12361, Grade: D\",\"StationNumber: 18LTB79, Year: 2018, PEL ratio: 0.03143, Grade: C\",\"StationNumber: 18LTB81, Year: 2018, PEL ratio: 0.09621, Grade: D\",\"StationNumber: 18LTB82, Year: 2018, PEL ratio: 0.0782, Grade: C\",\"StationNumber: 18MR25, Year: 2018, PEL ratio: 0.04013, Grade: C\",\"StationNumber: 18MR37, Year: 2018, PEL ratio: 0.06345, Grade: C\",\"StationNumber: 18MR46, Year: 2018, PEL ratio: 0.03519, Grade: C\",\"StationNumber: 18MTB41, Year: 2018, PEL ratio: 0.01539, Grade: B\",\"StationNumber: 18MTB42, Year: 2018, PEL ratio: 0.18686, Grade: D\",\"StationNumber: 18MTB48, Year: 2018, PEL ratio: 0.00879, Grade: B\",\"StationNumber: 18MTB56, Year: 2018, PEL ratio: 0.0139, Grade: B\",\"StationNumber: 18OTB04, Year: 2018, PEL ratio: 0.06233, Grade: C\",\"StationNumber: 18OTB08, Year: 2018, PEL ratio: 0.003, Grade: A\",\"StationNumber: 18OTB13, Year: 2018, PEL ratio: 0.01252, Grade: B\",\"StationNumber: 18OTB14, Year: 2018, PEL ratio: 0.04092, Grade: C\",\"StationNumber: 18OTB15, Year: 2018, PEL ratio: 0.01682, Grade: B\",\"StationNumber: 18OTB21, Year: 2018, PEL ratio: 0.00898, Grade: B\",\"StationNumber: 18OTB24, Year: 2018, PEL ratio: 0.00579, Grade: A\",\"StationNumber: 18TCB05, Year: 2018, PEL ratio: 0.03777, Grade: C\",\"StationNumber: 18TCB11, Year: 2018, PEL ratio: 0.02078, Grade: C\",\"StationNumber: 18TCB14, Year: 2018, PEL ratio: 0.05688, Grade: C\",\"StationNumber: 18TCB15, Year: 2018, PEL ratio: 0.05947, Grade: C\",\"StationNumber: 18TCB21, Year: 2018, PEL ratio: 0.11579, Grade: D\",\"StationNumber: 18TCB22, Year: 2018, PEL ratio: 0.02805, Grade: C\",\"StationNumber: 19BCB27, Year: 2019, PEL ratio: 0.04772, Grade: C\",\"StationNumber: 19BCB29, Year: 2019, PEL ratio: 0.04849, Grade: C\",\"StationNumber: 19BCB30, Year: 2019, PEL ratio: 0.1321, Grade: D\",\"StationNumber: 19BCB34, Year: 2019, PEL ratio: 0.51859, Grade: F\",\"StationNumber: 19BCB35, Year: 2019, PEL ratio: 0.05839, Grade: C\",\"StationNumber: 19BCB36, Year: 2019, PEL ratio: 0.11644, Grade: D\",\"StationNumber: 19BCB40, Year: 2019, PEL ratio: 0.00368, Grade: A\",\"StationNumber: 19BCB41, Year: 2019, PEL ratio: 0.0436, Grade: C\",\"StationNumber: 19BCB43, Year: 2019, PEL ratio: 0.09295, Grade: D\",\"StationNumber: 19BCB49, Year: 2019, PEL ratio: 0.05207, Grade: C\",\"StationNumber: 19BCB50, Year: 2019, PEL ratio: 0.0513, Grade: C\",\"StationNumber: 19HB09, Year: 2019, PEL ratio: 0.01191, Grade: B\",\"StationNumber: 19HB16, Year: 2019, PEL ratio: 0.69077, Grade: F\",\"StationNumber: 19HB25, Year: 2019, PEL ratio: 0.0126, Grade: B\",\"StationNumber: 19HB27, Year: 2019, PEL ratio: 0.05811, Grade: C\",\"StationNumber: 19HB32, Year: 2019, PEL ratio: 0.03805, Grade: C\",\"StationNumber: 19HB37, Year: 2019, PEL ratio: 0.06339, Grade: C\",\"StationNumber: 19HB39, Year: 2019, PEL ratio: 0.00598, Grade: A\",\"StationNumber: 19HB40, Year: 2019, PEL ratio: 0.0131, Grade: B\",\"StationNumber: 19HB47, Year: 2019, PEL ratio: 0.00395, Grade: A\",\"StationNumber: 19LTB76, Year: 2019, PEL ratio: 0.00985, Grade: B\",\"StationNumber: 19LTB78, Year: 2019, PEL ratio: 0.01215, Grade: B\",\"StationNumber: 19LTB88, Year: 2019, PEL ratio: 0.11037, Grade: D\",\"StationNumber: 19LTB90, Year: 2019, PEL ratio: 0.00656, Grade: A\",\"StationNumber: 19MR17, Year: 2019, PEL ratio: 0.01119, Grade: B\",\"StationNumber: 19MR18, Year: 2019, PEL ratio: 0.02367, Grade: C\",\"StationNumber: 19MR29, Year: 2019, PEL ratio: 0.02627, Grade: C\",\"StationNumber: 19MR33, Year: 2019, PEL ratio: 0.00769, Grade: B\",\"StationNumber: 19MR43, Year: 2019, PEL ratio: 0.17714, Grade: D\",\"StationNumber: 19MR44, Year: 2019, PEL ratio: 0.15675, Grade: D\",\"StationNumber: 19MR52, Year: 2019, PEL ratio: 0.0116, Grade: B\",\"StationNumber: 19MTB36, Year: 2019, PEL ratio: 0.08261, Grade: C\",\"StationNumber: 19MTB47, Year: 2019, PEL ratio: 0.01131, Grade: B\",\"StationNumber: 19MTB54, Year: 2019, PEL ratio: 0.00976, Grade: B\",\"StationNumber: 19MTB62, Year: 2019, PEL ratio: 0.00484, Grade: A\",\"StationNumber: 19OTB07, Year: 2019, PEL ratio: 0.01928, Grade: B\",\"StationNumber: 19OTB18, Year: 2019, PEL ratio: 0.05206, Grade: C\",\"StationNumber: 19OTB20, Year: 2019, PEL ratio: 0.02767, Grade: C\",\"StationNumber: 19OTB23, Year: 2019, PEL ratio: 0.01054, Grade: B\",\"StationNumber: 19OTB25, Year: 2019, PEL ratio: 0.04412, Grade: C\",\"StationNumber: 19OTB29, Year: 2019, PEL ratio: 0.04422, Grade: C\",\"StationNumber: 19OTB31, Year: 2019, PEL ratio: 0.01124, Grade: B\",\"StationNumber: 19TCB01, Year: 2019, PEL ratio: 0.01901, Grade: B\",\"StationNumber: 19TCB20, Year: 2019, PEL ratio: 0.01996, Grade: B\",\"StationNumber: 20BCB10, Year: 2020, PEL ratio: 0.02055, Grade: C\",\"StationNumber: 20BCB17, Year: 2020, PEL ratio: 0.0044, Grade: A\",\"StationNumber: 20BCB22, Year: 2020, PEL ratio: 0.20992, Grade: D\",\"StationNumber: 20BCB23, Year: 2020, PEL ratio: 0.00683, Grade: A\",\"StationNumber: 20BCB35, Year: 2020, PEL ratio: 0.04529, Grade: C\",\"StationNumber: 20BCB37, Year: 2020, PEL ratio: 0.01213, Grade: B\",\"StationNumber: 20BCB40, Year: 2020, PEL ratio: 0.00479, Grade: A\",\"StationNumber: 20BCB43, Year: 2020, PEL ratio: 0.00747, Grade: A\",\"StationNumber: 20BCB47, Year: 2020, PEL ratio: 0.01811, Grade: B\",\"StationNumber: 20BCB48, Year: 2020, PEL ratio: 0.02267, Grade: C\",\"StationNumber: 20BCB49, Year: 2020, PEL ratio: 0.01004, Grade: B\",\"StationNumber: 20HB09, Year: 2020, PEL ratio: 0.04899, Grade: C\",\"StationNumber: 20HB10, Year: 2020, PEL ratio: 0.06714, Grade: C\",\"StationNumber: 20HB21, Year: 2020, PEL ratio: 0.1516, Grade: D\",\"StationNumber: 20HB26, Year: 2020, PEL ratio: 0.03401, Grade: C\",\"StationNumber: 20HB38, Year: 2020, PEL ratio: 0.04319, Grade: C\",\"StationNumber: 20HB41, Year: 2020, PEL ratio: 0.01592, Grade: B\",\"StationNumber: 20HB46, Year: 2020, PEL ratio: 0.01143, Grade: B\",\"StationNumber: 20HB47, Year: 2020, PEL ratio: 0.00625, Grade: A\",\"StationNumber: 20HB52, Year: 2020, PEL ratio: 0.0242, Grade: C\",\"StationNumber: 20LTB70, Year: 2020, PEL ratio: 0.01567, Grade: B\",\"StationNumber: 20LTB71, Year: 2020, PEL ratio: 0.03189, Grade: C\",\"StationNumber: 20LTB77, Year: 2020, PEL ratio: 0.01505, Grade: B\",\"StationNumber: 20LTB85, Year: 2020, PEL ratio: 0.02098, Grade: C\",\"StationNumber: 20MR08, Year: 2020, PEL ratio: 0.07608, Grade: C\",\"StationNumber: 20MR09, Year: 2020, PEL ratio: 0.09408, Grade: D\",\"StationNumber: 20MR33, Year: 2020, PEL ratio: 0.18328, Grade: D\",\"StationNumber: 20MR36, Year: 2020, PEL ratio: 0.01558, Grade: B\",\"StationNumber: 20MR44, Year: 2020, PEL ratio: 0.10315, Grade: D\",\"StationNumber: 20MR49, Year: 2020, PEL ratio: 0.12139, Grade: D\",\"StationNumber: 20MTB35, Year: 2020, PEL ratio: 0.02267, Grade: C\",\"StationNumber: 20MTB46, Year: 2020, PEL ratio: 0.00585, Grade: A\",\"StationNumber: 20MTB52, Year: 2020, PEL ratio: 0.0217, Grade: C\",\"StationNumber: 20MTB63, Year: 2020, PEL ratio: 0.00437, Grade: A\",\"StationNumber: 20OTB13, Year: 2020, PEL ratio: 0.11907, Grade: D\",\"StationNumber: 20OTB14, Year: 2020, PEL ratio: 0.09905, Grade: D\",\"StationNumber: 20OTB15, Year: 2020, PEL ratio: 0.00718, Grade: A\",\"StationNumber: 20OTB19, Year: 2020, PEL ratio: 0.01134, Grade: B\",\"StationNumber: 20OTB21, Year: 2020, PEL ratio: 0.00212, Grade: A\",\"StationNumber: 20OTB24, Year: 2020, PEL ratio: 0.00213, Grade: A\",\"StationNumber: 20OTB32, Year: 2020, PEL ratio: 0.00435, Grade: A\",\"StationNumber: 20TCB10, Year: 2020, PEL ratio: 0.04695, Grade: C\",\"StationNumber: 20TCB12, Year: 2020, PEL ratio: 0.03948, Grade: C\",\"StationNumber: 20TCB20, Year: 2020, PEL ratio: 0.058, Grade: C\",\"StationNumber: 21BCB09, Year: 2021, PEL ratio: 0.11558, Grade: D\",\"StationNumber: 21BCB12, Year: 2021, PEL ratio: 0.01683, Grade: B\",\"StationNumber: 21BCB15, Year: 2021, PEL ratio: 0.05873, Grade: C\",\"StationNumber: 21BCB22, Year: 2021, PEL ratio: 0.01386, Grade: B\",\"StationNumber: 21BCB25, Year: 2021, PEL ratio: 0.00971, Grade: B\",\"StationNumber: 21BCB26, Year: 2021, PEL ratio: 0.03044, Grade: C\",\"StationNumber: 21BCB29, Year: 2021, PEL ratio: 0.02821, Grade: C\",\"StationNumber: 21BCB36, Year: 2021, PEL ratio: 0.00915, Grade: B\",\"StationNumber: 21BCB41, Year: 2021, PEL ratio: 0.00501, Grade: A\",\"StationNumber: 21BCB44, Year: 2021, PEL ratio: 0.01104, Grade: B\",\"StationNumber: 21BCB50, Year: 2021, PEL ratio: 0.00475, Grade: A\",\"StationNumber: 21HB13, Year: 2021, PEL ratio: 0.05335, Grade: C\",\"StationNumber: 21HB19, Year: 2021, PEL ratio: 0.08665, Grade: D\",\"StationNumber: 21HB20, Year: 2021, PEL ratio: 0.02175, Grade: C\",\"StationNumber: 21HB27, Year: 2021, PEL ratio: 0.04735, Grade: C\",\"StationNumber: 21HB34, Year: 2021, PEL ratio: 0.01341, Grade: B\",\"StationNumber: 21HB36, Year: 2021, PEL ratio: 0.03474, Grade: C\",\"StationNumber: 21HB37, Year: 2021, PEL ratio: 0.04959, Grade: C\",\"StationNumber: 21HB40, Year: 2021, PEL ratio: 0.01943, Grade: B\",\"StationNumber: 21HB43, Year: 2021, PEL ratio: 0.03012, Grade: C\",\"StationNumber: 21LTB78, Year: 2021, PEL ratio: 0.02074, Grade: C\",\"StationNumber: 21LTB83, Year: 2021, PEL ratio: 0.00875, Grade: B\",\"StationNumber: 21LTB84, Year: 2021, PEL ratio: 0.01135, Grade: B\",\"StationNumber: 21LTB89, Year: 2021, PEL ratio: 0.01185, Grade: B\",\"StationNumber: 21MR24, Year: 2021, PEL ratio: 0.0078, Grade: B\",\"StationNumber: 21MR29, Year: 2021, PEL ratio: 0.01739, Grade: B\",\"StationNumber: 21MR45, Year: 2021, PEL ratio: 0.06525, Grade: C\",\"StationNumber: 21MR47, Year: 2021, PEL ratio: 0.01081, Grade: B\",\"StationNumber: 21MR52, Year: 2021, PEL ratio: 0.01768, Grade: B\",\"StationNumber: 21MTB40, Year: 2021, PEL ratio: 0.01151, Grade: B\",\"StationNumber: 21MTB43, Year: 2021, PEL ratio: 0.03909, Grade: C\",\"StationNumber: 21MTB48, Year: 2021, PEL ratio: 0.01998, Grade: B\",\"StationNumber: 21MTB62, Year: 2021, PEL ratio: 0.01841, Grade: B\",\"StationNumber: 21OTB08, Year: 2021, PEL ratio: 0.00752, Grade: A\",\"StationNumber: 21OTB12, Year: 2021, PEL ratio: 0.05583, Grade: C\",\"StationNumber: 21OTB13, Year: 2021, PEL ratio: 0.00736, Grade: A\",\"StationNumber: 21OTB18, Year: 2021, PEL ratio: 0.01239, Grade: B\",\"StationNumber: 21OTB21, Year: 2021, PEL ratio: 0.00717, Grade: A\",\"StationNumber: 21OTB25, Year: 2021, PEL ratio: 0.00346, Grade: A\",\"StationNumber: 21OTB28, Year: 2021, PEL ratio: 0.00379, Grade: A\",\"StationNumber: 21TCB02, Year: 2021, PEL ratio: 0.03339, Grade: C\",\"StationNumber: 21TCB13, Year: 2021, PEL ratio: 0.04086, Grade: C\",\"StationNumber: 21TCB22, Year: 2021, PEL ratio: 0.01641, Grade: B\",\"StationNumber: 21TCB26, Year: 2021, PEL ratio: 0.01436, Grade: B\",\"StationNumber: 22BCB02, Year: 2022, PEL ratio: 0.10158, Grade: D\",\"StationNumber: 22BCB05, Year: 2022, PEL ratio: 0.00823, Grade: B\",\"StationNumber: 22BCB11, Year: 2022, PEL ratio: 0.03092, Grade: C\",\"StationNumber: 22BCB12, Year: 2022, PEL ratio: 0.01548, Grade: B\",\"StationNumber: 22BCB17, Year: 2022, PEL ratio: 0.02981, Grade: C\",\"StationNumber: 22BCB27, Year: 2022, PEL ratio: 0.02323, Grade: C\",\"StationNumber: 22BCB30, Year: 2022, PEL ratio: 0.00915, Grade: B\",\"StationNumber: 22BCB34, Year: 2022, PEL ratio: 0.00532, Grade: A\",\"StationNumber: 22BCB35, Year: 2022, PEL ratio: 0.00406, Grade: A\",\"StationNumber: 22BCB45, Year: 2022, PEL ratio: 0.011, Grade: B\",\"StationNumber: 22BCB47, Year: 2022, PEL ratio: 0.01696, Grade: B\",\"StationNumber: 22HB10, Year: 2022, PEL ratio: 0.01656, Grade: B\",\"StationNumber: 22HB19, Year: 2022, PEL ratio: 0.00725, Grade: A\",\"StationNumber: 22HB21, Year: 2022, PEL ratio: 0.00943, Grade: B\",\"StationNumber: 22HB25, Year: 2022, PEL ratio: 0.03897, Grade: C\",\"StationNumber: 22HB26, Year: 2022, PEL ratio: 0.07429, Grade: C\",\"StationNumber: 22HB28, Year: 2022, PEL ratio: 0.01322, Grade: B\",\"StationNumber: 22HB32, Year: 2022, PEL ratio: 0.06511, Grade: C\",\"StationNumber: 22HB40, Year: 2022, PEL ratio: 0.014, Grade: B\",\"StationNumber: 22HB46, Year: 2022, PEL ratio: 0.01842, Grade: B\",\"StationNumber: 22LTB70, Year: 2022, PEL ratio: 0.01965, Grade: B\",\"StationNumber: 22LTB79, Year: 2022, PEL ratio: 0.02208, Grade: C\",\"StationNumber: 22LTB81, Year: 2022, PEL ratio: 0.01111, Grade: B\",\"StationNumber: 22LTB90, Year: 2022, PEL ratio: 0.00235, Grade: A\",\"StationNumber: 22MR17, Year: 2022, PEL ratio: 0.0139, Grade: B\",\"StationNumber: 22MR25, Year: 2022, PEL ratio: 0.02261, Grade: C\",\"StationNumber: 22MR32, Year: 2022, PEL ratio: 0.07513, Grade: C\",\"StationNumber: 22MR37, Year: 2022, PEL ratio: 0.01282, Grade: B\",\"StationNumber: 22MR42, Year: 2022, PEL ratio: 0.04052, Grade: C\",\"StationNumber: 22MR44, Year: 2022, PEL ratio: 0.01954, Grade: B\",\"StationNumber: 22MR46, Year: 2022, PEL ratio: 0.0097, Grade: B\",\"StationNumber: 22MR52, Year: 2022, PEL ratio: 0.05693, Grade: C\",\"StationNumber: 22MTB35, Year: 2022, PEL ratio: 0.02359, Grade: C\",\"StationNumber: 22MTB37, Year: 2022, PEL ratio: 0.01478, Grade: B\",\"StationNumber: 22MTB41, Year: 2022, PEL ratio: 0.0351, Grade: C\",\"StationNumber: 22MTB55, Year: 2022, PEL ratio: 0.00667, Grade: A\",\"StationNumber: 22OTB02, Year: 2022, PEL ratio: 0.02605, Grade: C\",\"StationNumber: 22OTB07, Year: 2022, PEL ratio: 0.03873, Grade: C\",\"StationNumber: 22OTB19, Year: 2022, PEL ratio: 0.0321, Grade: C\",\"StationNumber: 22OTB22, Year: 2022, PEL ratio: 0.01763, Grade: B\",\"StationNumber: 22OTB28, Year: 2022, PEL ratio: 0.02167, Grade: C\",\"StationNumber: 22OTB29, Year: 2022, PEL ratio: 0.0061, Grade: A\",\"StationNumber: 22OTB32, Year: 2022, PEL ratio: 0.01368, Grade: B\",\"StationNumber: 22TCB20, Year: 2022, PEL ratio: 0.01157, Grade: B\"],{\"interactive\":false,\"permanent\":false,\"direction\":\"auto\",\"opacity\":1,\"offset\":[0,0],\"textsize\":\"10px\",\"textOnly\":false,\"className\":\"\",\"sticky\":true},null]}],\"limits\":{\"lat\":[27.4934,28.03793],\"lng\":[-82.84670300000001,-82.323427]}},\"evals\":[],\"jsHooks\":{\"render\":[{\"code\":\"function(el, x, data) {\\n return (\\n function(el, x) {\\n var myMap = this;\\n myMap.on('baselayerchange',\\n function (e) {\\n myMap.minimap.changeLayer(L.tileLayer.provider(e.name));\\n })\\n }).call(this.getMap(), el, x, data);\\n}\",\"data\":null}]}}"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_segmatrix.html","id":null,"dir":"Reference","previous_headings":"","what":"Create a colorized table for water quality outcomes and exceedances by segment — show_segmatrix","title":"Create a colorized table for water quality outcomes and exceedances by segment — show_segmatrix","text":"Create colorized table water quality outcomes segment includes management action chlorophyll, light attenuation exceedances","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_segmatrix.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Create a colorized table for water quality outcomes and exceedances by segment — show_segmatrix","text":"","code":"show_segmatrix( epcdata, txtsz = 3, trgs = NULL, yrrng = c(1975, 2023), bay_segment = c(\"OTB\", \"HB\", \"MTB\", \"LTB\"), abbrev = FALSE, family = NA, historic = TRUE, plotly = FALSE, partialyr = FALSE, width = NULL, height = NULL )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_segmatrix.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Create a colorized table for water quality outcomes and exceedances by segment — show_segmatrix","text":"epcdata data frame epc data returned read_importwq txtsz numeric size text plot, applies tab = FALSE trgs optional data.frame annual bay segment water quality targets, defaults targets yrrng numeric vector indicating min, max years include bay_segment chr string bay segments include, one \"OTB\", \"HB\", \"MTB\", \"LTB\" abbrev logical indicating text labels plot abbreviated first letter family optional chr string indicating font family text labels historic logical historic data used 2005 earlier plotly logical matrix created using plotly partialyr logical indicating incomplete annual data recent year approximated five year monthly averages parameter width numeric width plot pixels, applies plotly = TRUE height numeric height plot pixels, applies plotly = TRUE","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_segmatrix.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Create a colorized table for water quality outcomes and exceedances by segment — show_segmatrix","text":"static ggplot object returned","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_segmatrix.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Create a colorized table for water quality outcomes and exceedances by segment — show_segmatrix","text":"function provides combined output show_wqmatrix show_matrix functions. one bay segment can plotted function call.","code":""},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_segmatrix.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Create a colorized table for water quality outcomes and exceedances by segment — show_segmatrix","text":"","code":"show_segmatrix(epcdata, bay_segment = 'OTB')"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_segplotly.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot chlorophyll and secchi data together with matrix outcomes — show_segplotly","title":"Plot chlorophyll and secchi data together with matrix outcomes — show_segplotly","text":"Plot chlorophyll secchi data together matrix outcomes","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_segplotly.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot chlorophyll and secchi data together with matrix outcomes — show_segplotly","text":"","code":"show_segplotly( epcdata, bay_segment = c(\"OTB\", \"HB\", \"MTB\", \"LTB\"), yrrng = c(1975, 2023), family = NULL, partialyr = FALSE, width = NULL, height = NULL )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_segplotly.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot chlorophyll and secchi data together with matrix outcomes — show_segplotly","text":"epcdata data frame epc data returned read_importwq bay_segment chr string bay segment, one \"OTB\", \"HB\", \"MTB\", \"LTB\" yrrng numeric year range plot family optional chr string indicating font family text labels partialyr logical indicating incomplete annual data recent year approximated five year monthly averages parameter width numeric width plot pixels height numeric height plot pixels","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_segplotly.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot chlorophyll and secchi data together with matrix outcomes — show_segplotly","text":"interactive plotly object","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_segplotly.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Plot chlorophyll and secchi data together with matrix outcomes — show_segplotly","text":"function combines outputs show_thrplot show_segmatrix selected bay segment. plot interactive can zoomed dragging mouse pointer section plot. Information cell value can seen hovering location plot.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_segplotly.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot chlorophyll and secchi data together with matrix outcomes — show_segplotly","text":"","code":"show_segplotly(epcdata) {\"x\":{\"data\":[{\"x\":[1975,1976,1977,1978,1979,1980,1981,1982,1983,1984,1985,1986,1987,1988,1989,1990,1991,1992,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013,2014,2015,2016,2017,2018,2019,2020,2021,2022,2023],\"y\":[13.207539682539682,10.882222222222222,11.403666666666666,9.5151515151515156,17.99818181818182,13.870909090909091,12.029090909090909,12.989629629629629,17.540303030303029,9.1606666666666676,11.164333333333333,10.586619047619047,9.3042424242424246,8.1594444444444445,9.3469444444444445,9.3352696969696964,8.2859822510822507,7.8752870370370367,7.5887388888888889,9.4349166666666662,11.520738888888889,6.8479555555555551,8.3613944444444446,11.226705555555556,8.1310083333333338,7.1674944444444444,8.602955555555555,7.8252563492063487,11.717811538461538,11.810648015873015,8.4276190476190482,6.2816666666666663,8.637777777777778,9.2711111111111109,12.121111111111111,7.4423809523809528,11.413333333333334,7.8305555555555557,8.6644444444444453,7.8627777777777776,10.671111111111111,8.9866666666666664,9.5355555555555558,9.2166666666666668,9.7838888888888889,9.5346666666666664,9.4472222222222229,7.1233333333333331,6.2105555555555556],\"text\":[\"yr: 1975
yval: 13.207540
\",\"yr: 1976
yval: 10.882222
\",\"yr: 1977
yval: 11.403667
\",\"yr: 1978
yval: 9.515152
\",\"yr: 1979
yval: 17.998182
\",\"yr: 1980
yval: 13.870909
\",\"yr: 1981
yval: 12.029091
\",\"yr: 1982
yval: 12.989630
\",\"yr: 1983
yval: 17.540303
\",\"yr: 1984
yval: 9.160667
\",\"yr: 1985
yval: 11.164333
\",\"yr: 1986
yval: 10.586619
\",\"yr: 1987
yval: 9.304242
\",\"yr: 1988
yval: 8.159444
\",\"yr: 1989
yval: 9.346944
\",\"yr: 1990
yval: 9.335270
\",\"yr: 1991
yval: 8.285982
\",\"yr: 1992
yval: 7.875287
\",\"yr: 1993
yval: 7.588739
\",\"yr: 1994
yval: 9.434917
\",\"yr: 1995
yval: 11.520739
\",\"yr: 1996
yval: 6.847956
\",\"yr: 1997
yval: 8.361394
\",\"yr: 1998
yval: 11.226706
\",\"yr: 1999
yval: 8.131008
\",\"yr: 2000
yval: 7.167494
\",\"yr: 2001
yval: 8.602956
\",\"yr: 2002
yval: 7.825256
\",\"yr: 2003
yval: 11.717812
\",\"yr: 2004
yval: 11.810648
\",\"yr: 2005
yval: 8.427619
\",\"yr: 2006
yval: 6.281667
\",\"yr: 2007
yval: 8.637778
\",\"yr: 2008
yval: 9.271111
\",\"yr: 2009
yval: 12.121111
\",\"yr: 2010
yval: 7.442381
\",\"yr: 2011
yval: 11.413333
\",\"yr: 2012
yval: 7.830556
\",\"yr: 2013
yval: 8.664444
\",\"yr: 2014
yval: 7.862778
\",\"yr: 2015
yval: 10.671111
\",\"yr: 2016
yval: 8.986667
\",\"yr: 2017
yval: 9.535556
\",\"yr: 2018
yval: 9.216667
\",\"yr: 2019
yval: 9.783889
\",\"yr: 2020
yval: 9.534667
\",\"yr: 2021
yval: 9.447222
\",\"yr: 2022
yval: 7.123333
\",\"yr: 2023
yval: 6.210556
\"],\"type\":\"scatter\",\"mode\":\"markers+lines\",\"marker\":{\"autocolorscale\":false,\"color\":\"rgba(255,0,0,1)\",\"opacity\":1,\"size\":11.338582677165356,\"symbol\":\"circle\",\"line\":{\"width\":1.8897637795275593,\"color\":\"rgba(255,0,0,1)\"}},\"hoveron\":\"points\",\"name\":\"Annual Mean\",\"legendgroup\":\"Annual Mean\",\"showlegend\":true,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"line\":{\"width\":2.8346456692913389,\"color\":\"rgba(255,0,0,1)\",\"dash\":\"solid\"},\"frame\":null},{\"x\":[1974.51,2023.49],\"y\":[8.5,8.5],\"text\":\"trgnum: 8.5
colour: Management Target\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":1.8897637795275593,\"color\":\"rgba(0,0,255,1)\",\"dash\":\"solid\"},\"hoveron\":\"points\",\"name\":\"Management Target\",\"legendgroup\":\"Management Target\",\"showlegend\":true,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1974.51,2023.49],\"y\":[8.9000000000000004,8.9000000000000004],\"text\":\"smlnum: 8.9
colour: +1 se (small exceedance)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":1.8897637795275593,\"color\":\"rgba(0,0,255,1)\",\"dash\":\"dash\"},\"hoveron\":\"points\",\"name\":\"+1 se (small exceedance)\",\"legendgroup\":\"+1 se (small exceedance)\",\"showlegend\":true,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1974.51,2023.49],\"y\":[9.3000000000000007,9.3000000000000007],\"text\":\"thrnum: 9.3
colour: +2 se (large exceedance)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":1.8897637795275593,\"color\":\"rgba(0,0,255,1)\",\"dash\":\"dot\"},\"hoveron\":\"points\",\"name\":\"+2 se (large exceedance)\",\"legendgroup\":\"+2 se (large exceedance)\",\"showlegend\":true,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1986.5,1987.5,1987.5,1986.5,1986.5,null,1987.5,1988.5,1988.5,1987.5,1987.5,null,1989.5,1990.5,1990.5,1989.5,1989.5],\"y\":[0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5],\"text\":\"Action: Outcome: 0, Exceedance: none (size), long (length)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y2\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2007.5,2008.5,2008.5,2007.5,2007.5,null,2008.5,2009.5,2009.5,2008.5,2008.5,null,2014.5,2015.5,2015.5,2014.5,2014.5,null,2015.5,2016.5,2016.5,2015.5,2015.5,null,2016.5,2017.5,2017.5,2016.5,2016.5,null,2017.5,2018.5,2018.5,2017.5,2017.5,null,2018.5,2019.5,2019.5,2018.5,2018.5,null,2019.5,2020.5,2020.5,2019.5,2019.5,null,2020.5,2021.5,2021.5,2020.5,2020.5,null,2021.5,2022.5,2022.5,2021.5,2021.5,null,2022.5,2023.5,2023.5,2022.5,2022.5],\"y\":[0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5],\"text\":\"Action: Outcome: 0, Exceedance: none (size), none (length)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y2\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1987.5,1988.5,1988.5,1987.5,1987.5,null,1990.5,1991.5,1991.5,1990.5,1990.5,null,1991.5,1992.5,1992.5,1991.5,1991.5,null,1992.5,1993.5,1993.5,1992.5,1992.5,null,1995.5,1996.5,1996.5,1995.5,1995.5,null,1996.5,1997.5,1997.5,1996.5,1996.5,null,1998.5,1999.5,1999.5,1998.5,1998.5,null,1999.5,2000.5,2000.5,1999.5,1999.5,null,2000.5,2001.5,2001.5,2000.5,2000.5,null,2001.5,2002.5,2002.5,2001.5,2001.5,null,2004.5,2005.5,2005.5,2004.5,2004.5,null,2005.5,2006.5,2006.5,2005.5,2005.5,null,2006.5,2007.5,2007.5,2006.5,2006.5,null,2009.5,2010.5,2010.5,2009.5,2009.5,null,2011.5,2012.5,2012.5,2011.5,2011.5,null,2012.5,2013.5,2013.5,2012.5,2012.5,null,2013.5,2014.5,2014.5,2013.5,2013.5,null,2021.5,2022.5,2022.5,2021.5,2021.5,null,2022.5,2023.5,2023.5,2022.5,2022.5,null,1990.5,1991.5,1991.5,1990.5,1990.5,null,1991.5,1992.5,1992.5,1991.5,1991.5,null,1993.5,1994.5,1994.5,1993.5,1993.5,null,1996.5,1997.5,1997.5,1996.5,1996.5,null,1999.5,2000.5,2000.5,1999.5,1999.5,null,2004.5,2005.5,2005.5,2004.5,2004.5,null,2005.5,2006.5,2006.5,2005.5,2005.5,null,2006.5,2007.5,2007.5,2006.5,2006.5,null,2009.5,2010.5,2010.5,2009.5,2009.5,null,2011.5,2012.5,2012.5,2011.5,2011.5,null,2012.5,2013.5,2013.5,2012.5,2012.5,null,2013.5,2014.5,2014.5,2013.5,2013.5],\"y\":[2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5,null,0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5],\"text\":\"Action: Outcome: 0, Exceedance: none (size), short (length)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y2\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[2007.5,2008.5,2008.5,2007.5,2007.5,null,2015.5,2016.5,2016.5,2015.5,2015.5],\"y\":[2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5],\"text\":\"Action: Outcome: 1, Exceedance: small (size), short (length)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y2\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1983.5,1984.5,1984.5,1983.5,1983.5,null,2017.5,2018.5,2018.5,2017.5,2017.5,null,2003.5,2004.5,2004.5,2003.5,2003.5],\"y\":[2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5,null,0.5,0.5,1.5,1.5,0.5],\"text\":\"Action: Outcome: 2, Exceedance: small (size), long (length)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y2\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1990.5,1991.5,1991.5,1990.5,1990.5,null,1999.5,2000.5,2000.5,1999.5,1999.5,null,2004.5,2005.5,2005.5,2004.5,2004.5,null,2005.5,2006.5,2006.5,2005.5,2005.5,null,2006.5,2007.5,2007.5,2006.5,2006.5,null,2009.5,2010.5,2010.5,2009.5,2009.5,null,2011.5,2012.5,2012.5,2011.5,2011.5,null,2012.5,2013.5,2013.5,2012.5,2012.5,null,2013.5,2014.5,2014.5,2013.5,2013.5,null,2021.5,2022.5,2022.5,2021.5,2021.5,null,2022.5,2023.5,2023.5,2022.5,2022.5],\"y\":[1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5],\"text\":\"Action: Stay the Course (chla: 0, la: 0)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"name\":\"green\",\"legendgroup\":\"green\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y2\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1989.5,1990.5,1990.5,1989.5,1989.5],\"y\":[1.5,1.5,2.5,2.5,1.5],\"text\":\"Action: On Alert (chla: 2, la: 0)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y2\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1994.5,1995.5,1995.5,1994.5,1994.5,null,2002.5,2003.5,2003.5,2002.5,2002.5,null,2003.5,2004.5,2004.5,2003.5,2003.5,null,2010.5,2011.5,2011.5,2010.5,2010.5],\"y\":[1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5],\"text\":\"Action: On Alert (chla: 2, la: 2)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y2\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1983.5,1984.5,1984.5,1983.5,1983.5,null,1988.5,1989.5,1989.5,1988.5,1988.5,null,1997.5,1998.5,1998.5,1997.5,1997.5],\"y\":[1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5],\"text\":\"Action: On Alert (chla: 2, la: 3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y2\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1986.5,1987.5,1987.5,1986.5,1986.5],\"y\":[1.5,1.5,2.5,2.5,1.5],\"text\":\"Action: On Alert (chla: 3, la: 0)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y2\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1974.5,1975.5,1975.5,1974.5,1974.5],\"y\":[1.5,1.5,2.5,2.5,1.5],\"text\":\"Action: On Alert (chla: 3, la: 2)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y2\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1975.5,1976.5,1976.5,1975.5,1975.5,null,1976.5,1977.5,1977.5,1976.5,1976.5,null,1977.5,1978.5,1978.5,1977.5,1977.5,null,1978.5,1979.5,1979.5,1978.5,1978.5,null,1979.5,1980.5,1980.5,1979.5,1979.5,null,1980.5,1981.5,1981.5,1980.5,1980.5,null,1981.5,1982.5,1982.5,1981.5,1981.5,null,1982.5,1983.5,1983.5,1982.5,1982.5,null,1984.5,1985.5,1985.5,1984.5,1984.5,null,1985.5,1986.5,1986.5,1985.5,1985.5],\"y\":[1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5,null,1.5,1.5,2.5,2.5,1.5],\"text\":\"Action: On Alert (chla: 3, la: 3)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y2\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1988.5,1989.5,1989.5,1988.5,1988.5,null,1989.5,1990.5,1990.5,1989.5,1989.5,null,1993.5,1994.5,1994.5,1993.5,1993.5,null,1994.5,1995.5,1995.5,1994.5,1994.5,null,1997.5,1998.5,1998.5,1997.5,1997.5,null,2002.5,2003.5,2003.5,2002.5,2002.5,null,2003.5,2004.5,2004.5,2003.5,2003.5,null,2008.5,2009.5,2009.5,2008.5,2008.5,null,2010.5,2011.5,2011.5,2010.5,2010.5,null,2014.5,2015.5,2015.5,2014.5,2014.5,null,2016.5,2017.5,2017.5,2016.5,2016.5,null,1974.5,1975.5,1975.5,1974.5,1974.5,null,1992.5,1993.5,1993.5,1992.5,1992.5,null,1994.5,1995.5,1995.5,1994.5,1994.5,null,1995.5,1996.5,1996.5,1995.5,1995.5,null,2000.5,2001.5,2001.5,2000.5,2000.5,null,2001.5,2002.5,2002.5,2001.5,2001.5,null,2002.5,2003.5,2003.5,2002.5,2002.5,null,2010.5,2011.5,2011.5,2010.5,2010.5],\"y\":[2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5,null,0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5],\"text\":\"Action: Outcome: 2, Exceedance: large (size), short (length)\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":0.37795275590551186,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"name\":\"red\",\"legendgroup\":\"red\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y2\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1974.5,1975.5,1975.5,1974.5,1974.5,null,1975.5,1976.5,1976.5,1975.5,1975.5],\"y\":[2.5,2.5,3.5,3.5,2.5,null,2.5,2.5,3.5,3.5,2.5],\"text\":\"Action: Outcome: 3, Exceedance: large (size), NA 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1975
yval: 0.9780952
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yval: 1.1759318
\",\"yr: 1977
yval: 1.1896016
\",\"yr: 1978
yval: 1.1682173
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yval: 1.7595230
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yval: 1.3836268
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yval: 1.0469025
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yval: 1.0583860
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yval: 1.1152678
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yval: 1.1617502
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yval: 0.9534905
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yval: 0.8929313
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yval: 0.8536198
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yval: 0.8558599
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yval: 0.9374651
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yval: 0.8353229
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yval: 0.8031788
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yval: 0.8166729
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yval: 0.9133746
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yval: 0.7481484
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yval: 0.9379637
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yval: 0.9202700
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yval: 0.8473840
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yval: 1.0612729
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yval: 0.8801655
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yval: 0.7328166
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yval: 0.9512714
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yval: 0.9272802
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yval: 1.0370998
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yval: 0.8777406
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yval: 0.7693579
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yval: 0.6204267
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yval: 0.6771304
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yval: 0.6962244
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yval: 0.8076962
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yval: 0.8419635
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yval: 0.9122183
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yval: 0.6867633
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yval: 0.5674502
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yval: 0.6056886
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yval: 0.5604978
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yval: 0.5747356
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yval: 0.6821210
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yval: 0.6780425
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yval: 0.7396049
\",\"yr: 2020
yval: 0.7686231
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yval: 0.7783039
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yval: 0.7871073
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yval: 0.7344259
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Adding new coordinate system, which will #> replace the existing one."},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sitesegmap.html","id":null,"dir":"Reference","previous_headings":"","what":"Map site and bay segment attainment categories for a selected year — show_sitesegmap","title":"Map site and bay segment attainment categories for a selected year — show_sitesegmap","text":"Map site bay segment attainment categories selected year","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sitesegmap.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Map site and bay segment attainment categories for a selected year — show_sitesegmap","text":"","code":"show_sitesegmap( epcdata, yrsel, param = c(\"chla\", \"la\"), trgs = NULL, thrs = FALSE, partialyr = FALSE, base_size = 12, family = NA )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sitesegmap.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Map site and bay segment attainment categories for a selected year — show_sitesegmap","text":"epcdata data frame epc data returned read_importwq yrsel numeric year plot param chr string parameter plot, one \"chla\" chlorophyll \"la\" light attenuation trgs optional data.frame annual bay segment water quality targets, defaults targets thrs logical indicating attainment category relative targets (default) thresholds, passed anlz_attainsite partialyr logical indicating incomplete annual data recent year approximated five year monthly averages parameter base_size numeric indicating text scaling size plot family optional chr string indicating font family text labels","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sitesegmap.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Map site and bay segment attainment categories for a selected year — show_sitesegmap","text":"static ggplot object returned","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sitesegmap.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Map site and bay segment attainment categories for a selected year — show_sitesegmap","text":"map similar returned show_sitemap addition polygons bay segment colored annual attainment category site points sized relative selected parameter param.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_sitesegmap.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Map site and bay segment attainment categories for a selected year — show_sitesegmap","text":"","code":"show_sitesegmap(epcdata, yrsel = 2023) #> Coordinate system already present. Adding new coordinate system, which will #> replace the existing one."},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbbimatrix.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot a matrix of Tampa Bay Benthic Index scores over time by bay segment — show_tbbimatrix","title":"Plot a matrix of Tampa Bay Benthic Index scores over time by bay segment — show_tbbimatrix","text":"Plot matrix Tampa Bay Benthic Index scores time bay segment","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbbimatrix.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot a matrix of Tampa Bay Benthic Index scores over time by bay segment — show_tbbimatrix","text":"","code":"show_tbbimatrix( tbbiscr, bay_segment = c(\"HB\", \"OTB\", \"MTB\", \"LTB\", \"TCB\", \"MR\", \"BCB\", \"All\", \"All (wt)\"), yrrng = c(1993, 2022), alph = 1, txtsz = 3, family = NA, rev = FALSE, position = \"top\", plotly = FALSE, width = NULL, height = NULL )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbbimatrix.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot a matrix of Tampa Bay Benthic Index scores over time by bay segment — show_tbbimatrix","text":"tbbiscr input data frame returned anlz_tbbiscr bay_segment chr string bay segment, one many \"HB\", \"OTB\", \"MTB\", \"LTB\", \"TCB\", \"MR\", \"BCB\", \"\", \"(wt)\" yrrng numeric indicating year ranges evaluate alph numeric indicating alpha value score category colors txtsz numeric size text plot family optional chr string indicating font family text labels rev logical factor levels bay segments reversed position chr string location bay segment labels, default top, passed scale_x_discrete plotly logical matrix created using plotly width numeric width plot pixels, applies plotly = TRUE height numeric height plot pixels, applies plotly = TRUE","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbbimatrix.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot a matrix of Tampa Bay Benthic Index scores over time by bay segment — show_tbbimatrix","text":"ggplot object showing trends time TBBI scores bay segment plotly = FALSE, otherwise plotly object","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbbimatrix.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Plot a matrix of Tampa Bay Benthic Index scores over time by bay segment — show_tbbimatrix","text":"Additional summaries provided entire bay, summary across categories (\"\") summary weighted across relative sizes bay segment (\"(wt)\").","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbbimatrix.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot a matrix of Tampa Bay Benthic Index scores over time by bay segment — show_tbbimatrix","text":"","code":"tbbiscr <- anlz_tbbiscr(benthicdata) show_tbbimatrix(tbbiscr)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbnimatrix.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot a matrix of Tampa Bay Nekton Index scores over time by bay segment — show_tbnimatrix","title":"Plot a matrix of Tampa Bay Nekton Index scores over time by bay segment — show_tbnimatrix","text":"Plot matrix Tampa Bay Nekton Index scores time bay segment","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbnimatrix.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot a matrix of Tampa Bay Nekton Index scores over time by bay segment — show_tbnimatrix","text":"","code":"show_tbnimatrix( tbniscr, bay_segment = c(\"OTB\", \"HB\", \"MTB\", \"LTB\"), perc = c(32, 46), alph = 1, txtsz = 3, family = NA, rev = FALSE, position = \"top\", plotly = FALSE, width = NULL, height = NULL )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbnimatrix.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot a matrix of Tampa Bay Nekton Index scores over time by bay segment — show_tbnimatrix","text":"tbniscr input data frame returned anlz_tbniscr bay_segment chr string bay segment, one many \"OTB\", \"HB\", \"MTB\", \"LTB\" perc numeric values indicating break points score categories alph numeric indicating alpha value score category colors txtsz numeric size text plot family optional chr string indicating font family text labels rev logical factor levels bay segments reversed position chr string location bay segment labels, default top, passed scale_x_discrete plotly logical matrix created using plotly width numeric width plot pixels, applies plotly = TRUE height numeric height plot pixels, applies plotly = TRUE","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbnimatrix.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot a matrix of Tampa Bay Nekton Index scores over time by bay segment — show_tbnimatrix","text":"ggplot object showing trends time TBNI scores bay segment","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbnimatrix.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot a matrix of Tampa Bay Nekton Index scores over time by bay segment — show_tbnimatrix","text":"","code":"tbniscr <- anlz_tbniscr(fimdata) show_tbnimatrix(tbniscr)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbniscr.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot Tampa Bay Nekton Index scores over time by bay segment — show_tbniscr","title":"Plot Tampa Bay Nekton Index scores over time by bay segment — show_tbniscr","text":"Plot Tampa Bay Nekton Index scores time bay segment","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbniscr.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot Tampa Bay Nekton Index scores over time by bay segment — show_tbniscr","text":"","code":"show_tbniscr( tbniscr, bay_segment = c(\"OTB\", \"HB\", \"MTB\", \"LTB\"), perc = c(32, 46), alph = 1, ylim = c(22, 58), rev = FALSE, plotly = FALSE, family = NA, width = NULL, height = NULL )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbniscr.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot Tampa Bay Nekton Index scores over time by bay segment — show_tbniscr","text":"tbniscr input dat frame returned anlz_tbniscr bay_segment chr string bay segment, one many \"OTB\", \"HB\", \"MTB\", \"LTB\" perc numeric values indicating break points score categories alph numeric indicating alpha value score category colors ylim numeric y axis limits rev logical factor levels bay segments reversed plotly logical matrix created using plotly family optional chr string indicating font family text labels width numeric width plot pixels, applies plotly = TRUE height numeric height plot pixels, applies plotly = TRUE","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbniscr.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot Tampa Bay Nekton Index scores over time by bay segment — show_tbniscr","text":"ggplot object showing trends time TBNI scores bay segment plotly object plotly = TRUE","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbniscr.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot Tampa Bay Nekton Index scores over time by bay segment — show_tbniscr","text":"","code":"tbniscr <- anlz_tbniscr(fimdata) show_tbniscr(tbniscr)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbniscrall.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot Tampa Bay Nekton Index scores over time as average across bay segments — show_tbniscrall","title":"Plot Tampa Bay Nekton Index scores over time as average across bay segments — show_tbniscrall","text":"Plot Tampa Bay Nekton Index scores time average across bay segments","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbniscrall.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot Tampa Bay Nekton Index scores over time as average across bay segments — show_tbniscrall","text":"","code":"show_tbniscrall( tbniscr, perc = c(32, 46), alph = 1, ylim = c(22, 58), rev = FALSE, plotly = FALSE )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbniscrall.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot Tampa Bay Nekton Index scores over time as average across bay segments — show_tbniscrall","text":"tbniscr input dat frame returned anlz_tbniscr perc numeric values indicating break points score categories alph numeric indicating alpha value score category colors ylim numeric y axis limits rev logical factor levels bay segments reversed plotly logical matrix created using plotly","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbniscrall.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot Tampa Bay Nekton Index scores over time as average across bay segments — show_tbniscrall","text":"ggplot object showing trends time TBNI scores bay segment plotly object plotly = TRUE","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbniscrall.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot Tampa Bay Nekton Index scores over time as average across bay segments — show_tbniscrall","text":"","code":"tbniscr <- anlz_tbniscr(fimdata) show_tbniscrall(tbniscr)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbniscrplotly.html","id":null,"dir":"Reference","previous_headings":"","what":"Creates a plotly object for TBNI score plots — show_tbniscrplotly","title":"Creates a plotly object for TBNI score plots — show_tbniscrplotly","text":"Creates plotly object TBNI score plots","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbniscrplotly.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Creates a plotly object for TBNI score plots — show_tbniscrplotly","text":"","code":"show_tbniscrplotly(p, width = NULL, height = NULL)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbniscrplotly.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Creates a plotly object for TBNI score plots — show_tbniscrplotly","text":"p ggplot object output show_tbniscr show_tbniscrall width numeric width plot pixels height numeric height plot pixels","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbniscrplotly.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Creates a plotly object for TBNI score plots — show_tbniscrplotly","text":"plotly data object","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tbniscrplotly.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Creates a plotly object for TBNI score plots — show_tbniscrplotly","text":"","code":"tbniscr <- anlz_tbniscr(fimdata) p <- show_tbniscrall(tbniscr) show_tbniscrplotly(p) {\"x\":{\"data\":[{\"x\":[null,null,null,null,null],\"y\":[null,32,32,null,null],\"text\":\"\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":1.8897637795275593,\"color\":\"transparent\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(204,50,49,1)\",\"hoveron\":\"fills\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[null,null,null,null,null],\"y\":[32,46,46,32,32],\"text\":\"\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":1.8897637795275593,\"color\":\"transparent\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(233,195,24,1)\",\"hoveron\":\"fills\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[null,null,null,null,null],\"y\":[46,null,null,46,46],\"text\":\"\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":1.8897637795275593,\"color\":\"transparent\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(45,201,56,1)\",\"hoveron\":\"fills\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013,2014,2015,2016,2017,2018,2019,2020,2021,2022,2022,2022,2021,2020,2019,2018,2017,2016,2015,2014,2013,2012,2011,2010,2009,2008,2007,2006,2005,2004,2003,2002,2001,2000,1999,1998,1998],\"y\":[48.174950433812491,46.192337273030297,44.217869520888684,44.229008941917506,43.204367555768769,44.148572079700592,46.152576099067943,35.683114999086001,40.584732027839848,41.632627529473545,41.549822206241068,43.557168715487762,47.609344686978943,46.5018316384119,43.507500585323129,45.544100152872986,47.54256747670842,50.540419554927652,50.541400523731063,47.53002481033797,46.513396602793662,44.524343009674809,46.471601172555538,40.588221540118596,40.635566525640456,40.635566525640456,43.364433474359544,43.411778459881404,49.528398827444462,47.475656990325191,49.486603397206338,50.46997518966203,53.458599476268937,53.459580445072348,50.45743252329158,48.455899847127014,46.492499414676871,49.4981683615881,50.390655313021057,46.442831284512238,44.450177793758932,44.367372470526455,43.415267972160152,38.316885000913999,49.847423900932057,47.851427920299408,46.795632444231231,47.770991058082494,47.782130479111316,49.807662726969703,51.825049566187509,48.174950433812491],\"text\":[\"Year: 1998
TBNI_Score - seval: 48.17495
TBNI_Score + seval: 51.82505\",\"Year: 1999
TBNI_Score - seval: 46.19234
TBNI_Score + seval: 49.80766\",\"Year: 2000
TBNI_Score - seval: 44.21787
TBNI_Score + seval: 47.78213\",\"Year: 2001
TBNI_Score - seval: 44.22901
TBNI_Score + seval: 47.77099\",\"Year: 2002
TBNI_Score - seval: 43.20437
TBNI_Score + seval: 46.79563\",\"Year: 2003
TBNI_Score - seval: 44.14857
TBNI_Score + seval: 47.85143\",\"Year: 2004
TBNI_Score - seval: 46.15258
TBNI_Score + seval: 49.84742\",\"Year: 2005
TBNI_Score - seval: 35.68311
TBNI_Score + seval: 38.31689\",\"Year: 2006
TBNI_Score - seval: 40.58473
TBNI_Score + seval: 43.41527\",\"Year: 2007
TBNI_Score - seval: 41.63263
TBNI_Score + seval: 44.36737\",\"Year: 2008
TBNI_Score - seval: 41.54982
TBNI_Score + seval: 44.45018\",\"Year: 2009
TBNI_Score - seval: 43.55717
TBNI_Score + seval: 46.44283\",\"Year: 2010
TBNI_Score - seval: 47.60934
TBNI_Score + seval: 50.39066\",\"Year: 2011
TBNI_Score - seval: 46.50183
TBNI_Score + seval: 49.49817\",\"Year: 2012
TBNI_Score - seval: 43.50750
TBNI_Score + seval: 46.49250\",\"Year: 2013
TBNI_Score - seval: 45.54410
TBNI_Score + seval: 48.45590\",\"Year: 2014
TBNI_Score - seval: 47.54257
TBNI_Score + seval: 50.45743\",\"Year: 2015
TBNI_Score - seval: 50.54042
TBNI_Score + seval: 53.45958\",\"Year: 2016
TBNI_Score - seval: 50.54140
TBNI_Score + seval: 53.45860\",\"Year: 2017
TBNI_Score - seval: 47.53002
TBNI_Score + seval: 50.46998\",\"Year: 2018
TBNI_Score - seval: 46.51340
TBNI_Score + seval: 49.48660\",\"Year: 2019
TBNI_Score - seval: 44.52434
TBNI_Score + seval: 47.47566\",\"Year: 2020
TBNI_Score - seval: 46.47160
TBNI_Score + seval: 49.52840\",\"Year: 2021
TBNI_Score - seval: 40.58822
TBNI_Score + seval: 43.41178\",\"Year: 2022
TBNI_Score - seval: 40.63557
TBNI_Score + seval: 43.36443\",\"Year: 2022
TBNI_Score - seval: 40.63557
TBNI_Score + seval: 43.36443\",\"Year: 2022
TBNI_Score - seval: 40.63557
TBNI_Score + seval: 43.36443\",\"Year: 2021
TBNI_Score - seval: 40.58822
TBNI_Score + seval: 43.41178\",\"Year: 2020
TBNI_Score - seval: 46.47160
TBNI_Score + seval: 49.52840\",\"Year: 2019
TBNI_Score - seval: 44.52434
TBNI_Score + seval: 47.47566\",\"Year: 2018
TBNI_Score - seval: 46.51340
TBNI_Score + seval: 49.48660\",\"Year: 2017
TBNI_Score - seval: 47.53002
TBNI_Score + seval: 50.46998\",\"Year: 2016
TBNI_Score - seval: 50.54140
TBNI_Score + seval: 53.45860\",\"Year: 2015
TBNI_Score - seval: 50.54042
TBNI_Score + seval: 53.45958\",\"Year: 2014
TBNI_Score - seval: 47.54257
TBNI_Score + seval: 50.45743\",\"Year: 2013
TBNI_Score - seval: 45.54410
TBNI_Score + seval: 48.45590\",\"Year: 2012
TBNI_Score - seval: 43.50750
TBNI_Score + seval: 46.49250\",\"Year: 2011
TBNI_Score - seval: 46.50183
TBNI_Score + seval: 49.49817\",\"Year: 2010
TBNI_Score - seval: 47.60934
TBNI_Score + seval: 50.39066\",\"Year: 2009
TBNI_Score - seval: 43.55717
TBNI_Score + seval: 46.44283\",\"Year: 2008
TBNI_Score - seval: 41.54982
TBNI_Score + seval: 44.45018\",\"Year: 2007
TBNI_Score - seval: 41.63263
TBNI_Score + seval: 44.36737\",\"Year: 2006
TBNI_Score - seval: 40.58473
TBNI_Score + seval: 43.41527\",\"Year: 2005
TBNI_Score - seval: 35.68311
TBNI_Score + seval: 38.31689\",\"Year: 2004
TBNI_Score - seval: 46.15258
TBNI_Score + seval: 49.84742\",\"Year: 2003
TBNI_Score - seval: 44.14857
TBNI_Score + seval: 47.85143\",\"Year: 2002
TBNI_Score - seval: 43.20437
TBNI_Score + seval: 46.79563\",\"Year: 2001
TBNI_Score - seval: 44.22901
TBNI_Score + seval: 47.77099\",\"Year: 2000
TBNI_Score - seval: 44.21787
TBNI_Score + seval: 47.78213\",\"Year: 1999
TBNI_Score - seval: 46.19234
TBNI_Score + seval: 49.80766\",\"Year: 1998
TBNI_Score - seval: 48.17495
TBNI_Score + seval: 51.82505\",\"Year: 1998
TBNI_Score - seval: 48.17495
TBNI_Score + seval: 51.82505\"],\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":1.8897637795275593,\"color\":\"transparent\",\"dash\":\"solid\"},\"fill\":\"toself\",\"fillcolor\":\"rgba(224,224,224,1)\",\"hoveron\":\"points\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013,2014,2015,2016,2017,2018,2019,2020,2021,2022],\"y\":[50,48,46,46,45,46,48,37,42,43,43,45,49,48,45,47,49,52,52,49,48,46,48,42,42],\"text\":[\"Year: 1998
TBNI_Score: 50\",\"Year: 1999
TBNI_Score: 48\",\"Year: 2000
TBNI_Score: 46\",\"Year: 2001
TBNI_Score: 46\",\"Year: 2002
TBNI_Score: 45\",\"Year: 2003
TBNI_Score: 46\",\"Year: 2004
TBNI_Score: 48\",\"Year: 2005
TBNI_Score: 37\",\"Year: 2006
TBNI_Score: 42\",\"Year: 2007
TBNI_Score: 43\",\"Year: 2008
TBNI_Score: 43\",\"Year: 2009
TBNI_Score: 45\",\"Year: 2010
TBNI_Score: 49\",\"Year: 2011
TBNI_Score: 48\",\"Year: 2012
TBNI_Score: 45\",\"Year: 2013
TBNI_Score: 47\",\"Year: 2014
TBNI_Score: 49\",\"Year: 2015
TBNI_Score: 52\",\"Year: 2016
TBNI_Score: 52\",\"Year: 2017
TBNI_Score: 49\",\"Year: 2018
TBNI_Score: 48\",\"Year: 2019
TBNI_Score: 46\",\"Year: 2020
TBNI_Score: 48\",\"Year: 2021
TBNI_Score: 42\",\"Year: 2022
TBNI_Score: 42\"],\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":4.7244094488188981,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"solid\"},\"hoveron\":\"points\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1997.375,1997.375,1997.375,1997.375,1997.375,1997.375,1997.375,1997.375,1997.375,1997.375,1997.375,1997.375,1997.375,1997.375,1997.375,1997.375,1997.375,1997.375,1997.375,1997.375,1997.375,1997.375,1997.375,1997.375,1997.375,2022.625,2022.625,2022.625,2022.625,2022.625,2022.625,2022.625,2022.625,2022.625,2022.625,2022.625,2022.625,2022.625,2022.625,2022.625,2022.625,2022.625,2022.625,2022.625,2022.625,2022.625,2022.625,2022.625,2022.625,2022.625],\"y\":[32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32],\"text\":\"perc[1]: 32\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":1.8897637795275593,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"dot\"},\"hoveron\":\"points\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null},{\"x\":[1997.375,1997.375,1997.375,1997.375,1997.375,1997.375,1997.375,1997.375,1997.375,1997.375,1997.375,1997.375,1997.375,1997.375,1997.375,1997.375,1997.375,1997.375,1997.375,1997.375,1997.375,1997.375,1997.375,1997.375,1997.375,2022.625,2022.625,2022.625,2022.625,2022.625,2022.625,2022.625,2022.625,2022.625,2022.625,2022.625,2022.625,2022.625,2022.625,2022.625,2022.625,2022.625,2022.625,2022.625,2022.625,2022.625,2022.625,2022.625,2022.625,2022.625],\"y\":[46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46],\"text\":\"perc[2]: 46\",\"type\":\"scatter\",\"mode\":\"lines\",\"line\":{\"width\":1.8897637795275593,\"color\":\"rgba(0,0,0,1)\",\"dash\":\"dot\"},\"hoveron\":\"points\",\"showlegend\":false,\"xaxis\":\"x\",\"yaxis\":\"y\",\"hoverinfo\":\"text\",\"frame\":null}],\"layout\":{\"margin\":{\"t\":23.305936073059364,\"r\":7.3059360730593621,\"b\":42.839352428393525,\"l\":41.511000415110004},\"plot_bgcolor\":\"rgba(235,235,235,1)\",\"paper_bgcolor\":\"rgba(255,255,255,1)\",\"font\":{\"color\":\"rgba(0,0,0,1)\",\"family\":\"\",\"size\":14.611872146118724},\"xaxis\":{\"domain\":[0,1],\"automargin\":true,\"type\":\"linear\",\"autorange\":false,\"range\":[1997.375,2022.625],\"tickmode\":\"array\",\"ticktext\":[\"1998\",\"1999\",\"2000\",\"2001\",\"2002\",\"2003\",\"2004\",\"2005\",\"2006\",\"2007\",\"2008\",\"2009\",\"2010\",\"2011\",\"2012\",\"2013\",\"2014\",\"2015\",\"2016\",\"2017\",\"2018\",\"2019\",\"2020\",\"2021\",\"2022\"],\"tickvals\":[1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013,2014,2015,2016,2017,2018,2019,2020,2021,2022],\"categoryorder\":\"array\",\"categoryarray\":[\"1998\",\"1999\",\"2000\",\"2001\",\"2002\",\"2003\",\"2004\",\"2005\",\"2006\",\"2007\",\"2008\",\"2009\",\"2010\",\"2011\",\"2012\",\"2013\",\"2014\",\"2015\",\"2016\",\"2017\",\"2018\",\"2019\",\"2020\",\"2021\",\"2022\"],\"nticks\":null,\"ticks\":\"outside\",\"tickcolor\":\"rgba(51,51,51,1)\",\"ticklen\":3.6529680365296811,\"tickwidth\":0.66417600664176002,\"showticklabels\":true,\"tickfont\":{\"color\":\"rgba(77,77,77,1)\",\"family\":\"\",\"size\":15.940224159402243},\"tickangle\":-90,\"showline\":false,\"linecolor\":null,\"linewidth\":0,\"showgrid\":false,\"gridcolor\":null,\"gridwidth\":0,\"zeroline\":false,\"anchor\":\"y\",\"title\":{\"text\":\"\",\"font\":{\"color\":null,\"family\":null,\"size\":0}},\"hoverformat\":\".2f\"},\"yaxis\":{\"domain\":[0,1],\"automargin\":true,\"type\":\"linear\",\"autorange\":false,\"range\":[20.199999999999999,59.799999999999997],\"tickmode\":\"array\",\"ticktext\":[\"22\",\"26\",\"30\",\"34\",\"38\",\"42\",\"46\",\"50\",\"54\",\"58\"],\"tickvals\":[22,26,30,34,38,42,46,50,54,58],\"categoryorder\":\"array\",\"categoryarray\":[\"22\",\"26\",\"30\",\"34\",\"38\",\"42\",\"46\",\"50\",\"54\",\"58\"],\"nticks\":null,\"ticks\":\"outside\",\"tickcolor\":\"rgba(51,51,51,1)\",\"ticklen\":3.6529680365296811,\"tickwidth\":0.66417600664176002,\"showticklabels\":true,\"tickfont\":{\"color\":\"rgba(77,77,77,1)\",\"family\":\"\",\"size\":15.940224159402243},\"tickangle\":-0,\"showline\":false,\"linecolor\":null,\"linewidth\":0,\"showgrid\":false,\"gridcolor\":null,\"gridwidth\":0,\"zeroline\":false,\"anchor\":\"x\",\"title\":{\"text\":\"TBNI 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show_tdlcrk","text":"Make map tidal creek report card","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrk.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Make a map for tidal creek report card — show_tdlcrk","text":"","code":"show_tdlcrk(dat, weight = 1.5)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrk.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Make a map for tidal creek report card — show_tdlcrk","text":"dat input creek score data returned anlz_tdlcrk weight numeric weight polylines, passed addPolylines","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrk.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Make a map for tidal creek report card — show_tdlcrk","text":"leaflet object","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrk.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Make a map for tidal creek report card — show_tdlcrk","text":"","code":"dat <- anlz_tdlcrk(tidalcreeks, iwrraw, yr = 2023) show_tdlcrk(dat) 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Monitor\",\"WBID: 2073, JEI: CC110, Name: NA, Creek score: No Data\",\"WBID: 2065B, JEI: CC111, Name: NA, Creek score: No Data\",\"WBID: 2074B, JEI: CC111, Name: NA, Creek score: No Data\",\"WBID: 2077, JEI: CC111, Name: NA, Creek score: No Data\",\"WBID: 1991B, JEI: CC15, Name: Rock Creek, Creek score: No Data\",\"WBID: 2045, JEI: CC15, Name: Rock Creek, Creek score: Monitor\",\"WBID: 1991B, JEI: CC16, Name: Apollo Waterway, Creek score: No Data\",\"WBID: 2010B, JEI: CC16, Name: Apollo Waterway, Creek score: No Data\",\"WBID: 2025, JEI: CC16, Name: Apollo Waterway, Creek score: No Data\",\"WBID: 2043, JEI: CC16, Name: Apollo Waterway, Creek score: Monitor\",\"WBID: 1991A, JEI: CC17, Name: NA, Creek score: No Data\",\"WBID: 1991B, JEI: CC17, Name: NA, Creek score: No Data\",\"WBID: 2048A, JEI: CC18, Name: Sam Knight Creek, Creek score: Monitor\",\"WBID: 2055, JEI: CC18, Name: Sam Knight Creek, Creek score: No Data\",\"WBID: 2048A, JEI: CC19, Name: Sam Knight Creek, Creek score: No Data\",\"WBID: 2055, JEI: CC19, Name: Sam Knight Creek, Creek score: No Data\",\"WBID: 2048A, JEI: CC20, Name: NA, Creek score: No Data\",\"WBID: 2055, JEI: CC20, Name: NA, Creek score: No Data\",\"WBID: 2048B, JEI: CC21, Name: Huckaby Creek, Creek score: No Data\",\"WBID: 2055, JEI: CC21, Name: Huckaby Creek, Creek score: No Data\",\"WBID: 2048C, JEI: CC22, Name: NA, Creek score: No Data\",\"WBID: 2055, JEI: CC22, Name: NA, Creek score: No Data\",\"WBID: 2047, JEI: CC23, Name: NA, Creek score: No Data\",\"WBID: 2055, JEI: CC23, Name: NA, Creek score: No Data\",\"WBID: 2047, JEI: CC24, Name: NA, Creek score: No Data\",\"WBID: 2055, JEI: CC24, Name: NA, Creek score: No Data\",\"WBID: 2060A1, JEI: CC25, Name: NA, Creek score: Investigate\",\"WBID: 2060A1, JEI: CC26, Name: NA, Creek score: No Data\",\"WBID: 2060A1, JEI: CC27, Name: NA, Creek score: No Data\",\"WBID: 2060A2, JEI: CC27, Name: NA, Creek score: No Data\",\"WBID: 2060, JEI: CC28, Name: NA, Creek score: No Data\",\"WBID: 2047, JEI: CC29, Name: NA, Creek score: No Data\",\"WBID: 2060, JEI: CC29, Name: NA, Creek score: No Data\",\"WBID: 2047, JEI: CC30, Name: NA, Creek score: No Data\",\"WBID: 2056D, JEI: CC30, Name: NA, Creek score: No Data\",\"WBID: 2060, JEI: CC30, Name: NA, Creek score: No Data\",\"WBID: 2046, JEI: CC31, Name: NA, Creek score: Monitor\",\"WBID: 2056D, JEI: CC34, Name: Little Alligator Creek, Creek score: No Data\",\"WBID: 2056E, JEI: CC34, Name: Little Alligator Creek, Creek score: Monitor\",\"WBID: 2056D, JEI: CC36, Name: NA, Creek score: No Data\",\"WBID: 2056E, JEI: CC36, Name: NA, Creek score: Monitor\",\"WBID: 2056E, JEI: CC37, Name: NA, Creek score: Monitor\",\"WBID: 2056E, JEI: CC40, Name: NA, Creek score: No Data\",\"WBID: 2056E, JEI: CC41, Name: NA, Creek score: No Data\",\"WBID: 2056B, JEI: CC42, Name: NA, Creek score: No Data\",\"WBID: 2056E, JEI: CC42, Name: NA, Creek score: Monitor\",\"WBID: 2056C2, JEI: CC44, Name: NA, Creek score: No Data\",\"WBID: 2056C2, JEI: CC45, Name: NA, Creek score: Prioritize\",\"WBID: 2056E, JEI: CC45, Name: NA, Creek score: No Data\",\"WBID: 2056C2, JEI: CC46, Name: NA, Creek score: No Data\",\"WBID: 2056C1, JEI: CC47, Name: NA, Creek score: No Data\",\"WBID: 2065C, JEI: CC48, Name: NA, Creek score: No Data\",\"WBID: 2080, JEI: CC48, Name: NA, Creek score: No Data\",\"WBID: 2087, JEI: CC48, Name: NA, Creek score: No Data\",\"WBID: 1991B, JEI: CC49, Name: NA, Creek score: No Data\",\"WBID: 1991A, JEI: CC50, Name: NA, Creek score: No Data\",\"WBID: 2053, JEI: CC50, Name: NA, Creek score: Monitor\",\"WBID: 2055, JEI: CC50, Name: NA, Creek score: No Data\",\"WBID: 2041A, JEI: CC51, Name: NA, Creek score: No Data\",\"WBID: 2041A, JEI: CC52, Name: NA, Creek score: No Data\",\"WBID: 2041A, JEI: CC53, Name: Myrtle Slough, Creek score: No Data\",\"WBID: 2054, JEI: CC53, Name: Myrtle Slough, Creek score: Monitor\",\"WBID: 2041A, JEI: CC54, Name: NA, Creek score: No Data\",\"WBID: 2059, JEI: CC55, Name: NA, Creek score: Monitor\",\"WBID: 2059, JEI: CC56, Name: NA, Creek score: Investigate\",\"WBID: 2062, JEI: CC57, Name: North Fork Alligator Creek, Creek score: No Data\",\"WBID: 2063, JEI: CC57, Name: North Fork Alligator Creek, Creek score: No Data\",\"WBID: 2065A, JEI: CC61, Name: NA, Creek score: No Data\",\"WBID: 2073, JEI: CC61, Name: NA, Creek score: No Data\",\"WBID: 2073, JEI: CC62, Name: NA, Creek score: No Data\",\"WBID: 2065B, JEI: CC63, Name: NA, Creek score: No Data\",\"WBID: 2073, JEI: CC63, Name: NA, Creek score: No Data\",\"WBID: 2063, JEI: CC64, Name: North Fork Alligator Creek, Creek score: Monitor\",\"WBID: 2074B, JEI: CC64, Name: North Fork Alligator Creek, Creek score: No Data\",\"WBID: 2074, JEI: CC65, Name: Alligator Creek, Creek score: Monitor\",\"WBID: 2074B, JEI: CC65, Name: Alligator Creek, Creek score: Monitor\",\"WBID: 2077, JEI: CC65, Name: Alligator Creek, Creek score: No Data\",\"WBID: 2065B, JEI: CC66, Name: Whidden Branch/Alligator Creek, Creek score: No Data\",\"WBID: 2074B, JEI: CC66, Name: Whidden Branch/Alligator Creek, Creek score: No Data\",\"WBID: 2077, JEI: CC66, Name: Whidden Branch/Alligator Creek, Creek score: No Data\",\"WBID: 2081, JEI: CC66, Name: Whidden Branch/Alligator Creek, Creek score: No Data\",\"WBID: 2065B, JEI: CC67, Name: South Silcox Creek, Creek score: Monitor\",\"WBID: 2081, JEI: CC67, Name: South Silcox Creek, Creek score: Monitor\",\"WBID: 2084, JEI: CC67, Name: South Silcox Creek, Creek score: No Data\",\"WBID: 2065B, JEI: CC68, Name: Big Mound Creek, Creek score: No Data\",\"WBID: 2084, JEI: CC68, Name: Big Mound Creek, Creek score: No Data\",\"WBID: 2084, JEI: CC69, Name: NA, Creek score: No Data\",\"WBID: 2086, JEI: CC69, Name: NA, Creek score: No Data\",\"WBID: 2088, JEI: CC69, Name: NA, Creek score: No Data\",\"WBID: 2065B, JEI: CC70, Name: Pirate Canal, Creek score: No Data\",\"WBID: 2082A, JEI: CC70, Name: Pirate Canal, Creek score: Monitor\",\"WBID: 2065B, JEI: CC71, Name: NA, Creek score: No Data\",\"WBID: 2094, JEI: CC72, Name: Bear Branch, Creek score: No Data\",\"WBID: 2093A, JEI: CC73, Name: Hog Branch, Creek score: No Data\",\"WBID: 2079, JEI: CC74, Name: Whidden Creek, Creek score: Monitor\",\"WBID: 2065B, JEI: CC75, Name: NA, Creek score: No Data\",\"WBID: 2065B, JEI: CC76, Name: NA, Creek score: No Data\",\"WBID: 2066, JEI: CC76, Name: NA, Creek score: No Data\",\"WBID: 1983B, JEI: CC77, Name: Lemon Creek, Creek score: Monitor\",\"WBID: 2076, JEI: CC77, Name: Lemon Creek, Creek score: Prioritize\",\"WBID: 2089, JEI: CC78, Name: NA, Creek score: No Data\",\"WBID: 2065C, JEI: CC79, Name: NA, Creek score: No Data\",\"WBID: 2066, JEI: CC79, Name: NA, Creek score: No Data\",\"WBID: 2065C, JEI: CC80, Name: NA, Creek score: No Data\",\"WBID: 2065C, JEI: CC81, Name: NA, Creek score: No Data\",\"WBID: 2065C, JEI: CC82, Name: NA, Creek score: No Data\",\"WBID: 2065C, JEI: CC83, Name: NA, Creek score: No Data\",\"WBID: 2065B, JEI: CC84, Name: NA, Creek score: No Data\",\"WBID: 2065B, JEI: CC85, Name: NA, Creek score: No Data\",\"WBID: 2065A, JEI: CC86, Name: NA, Creek score: No Data\",\"WBID: 2066, JEI: CC86, Name: NA, Creek score: No Data\",\"WBID: 2066, JEI: CC87, Name: NA, Creek score: No Data\",\"WBID: 1991B, JEI: CC88, Name: NA, Creek score: No Data\",\"WBID: 1991B, JEI: CC89, Name: NA, Creek score: No Data\",\"WBID: 2055, JEI: CC90, Name: NA, Creek score: No Data\",\"WBID: 2048B, JEI: CC91, Name: NA, Creek score: No Data\",\"WBID: 2048A, JEI: CC91, Name: NA, Creek score: No Data\",\"WBID: 2055, JEI: CC91, Name: NA, Creek score: No Data\",\"WBID: 2048C, JEI: CC92, Name: Flopbuck Creek, Creek score: No Data\",\"WBID: 2055, JEI: CC92, Name: Flopbuck Creek, Creek score: No Data\",\"WBID: 2048C, JEI: CC93, Name: NA, Creek score: No Data\",\"WBID: 2055, JEI: CC93, Name: NA, Creek score: No Data\",\"WBID: 2047, JEI: CC94, Name: NA, Creek score: No Data\",\"WBID: 2055, JEI: CC94, Name: NA, Creek score: No Data\",\"WBID: 2060A2, JEI: CC95, Name: NA, Creek score: No Data\",\"WBID: 2056E, JEI: CC96, Name: NA, Creek score: No Data\",\"WBID: 2056E, JEI: CC97, Name: NA, Creek score: No Data\",\"WBID: 2056D, JEI: CC98, Name: NA, Creek score: No Data\",\"WBID: 2056E, JEI: CC98, Name: NA, Creek score: No Data\",\"WBID: 2056E, JEI: CC99, Name: NA, Creek score: No Data\",\"WBID: 1623A, JEI: DC01, Name: NA, Creek score: No Data\",\"WBID: 2033, JEI: DC01, Name: NA, Creek score: Monitor\",\"WBID: 1623A, JEI: DC02, Name: NA, Creek score: No Data\",\"WBID: 1623A, JEI: DC03, Name: NA, Creek score: No Data\",\"WBID: 2028, JEI: DC03, Name: NA, Creek score: Prioritize\",\"WBID: 1623A, JEI: DC04, Name: NA, Creek score: No Data\",\"WBID: 1623B, JEI: DC04, Name: NA, Creek score: No Data\",\"WBID: 1787A2, JEI: DC04, Name: NA, Creek score: No Data\",\"WBID: 1787A2, JEI: DC05, Name: NA, Creek score: No Data\",\"WBID: 2003, JEI: DC05, Name: NA, Creek score: No Data\",\"WBID: 1787A2, JEI: DC06, Name: NA, Creek score: No Data\",\"WBID: 2003, JEI: DC06, Name: NA, Creek score: No Data\",\"WBID: 1623B, JEI: DC07, Name: NA, Creek score: No Data\",\"WBID: 1623A, JEI: DC08, Name: NA, Creek score: No Data\",\"WBID: 1623A, JEI: DC09, Name: NA, Creek score: No Data\",\"WBID: 2008, JEI: DC09, Name: NA, Creek score: No Data\",\"WBID: 2008, JEI: DC10, Name: Thornton Branch, Creek score: No Data\",\"WBID: 2035, JEI: DC10, Name: Thornton Branch, Creek score: No Data\",\"WBID: 2056C1, JEI: DC11, Name: NA, Creek score: No Data\",\"WBID: 1513E, JEI: HC01, Name: Double Branch Creek, Creek score: Monitor\",\"WBID: 1513F, JEI: HC01, Name: Double Branch Creek, Creek score: No Data\",\"WBID: 1513E, JEI: HC02, Name: NA, Creek score: Monitor\",\"WBID: 1513F, JEI: HC02, Name: NA, Creek score: No Data\",\"WBID: 1507, JEI: HC03, Name: Channel A, Creek score: No Data\",\"WBID: 1507A, JEI: HC03, Name: Channel A, Creek score: Monitor\",\"WBID: 1563, JEI: HC04, Name: NA, Creek score: No Data\",\"WBID: 1581, JEI: HC04, Name: NA, Creek score: No Data\",\"WBID: 1507, JEI: HC05, Name: Rocky Creek/Channel G, Creek score: Monitor\",\"WBID: 1516, JEI: HC05, Name: Rocky Creek/Channel G, Creek score: No Data\",\"WBID: 1558I, JEI: HC05, Name: Rocky Creek/Channel G, Creek score: No Data\",\"WBID: 1563, JEI: HC05, Name: Rocky Creek/Channel G, Creek score: Monitor\",\"WBID: 1558I, JEI: HC06, Name: Woods Creek, Creek score: No Data\",\"WBID: 1563, JEI: HC06, Name: Woods Creek, Creek score: No Data\",\"WBID: 1587A, JEI: HC06, Name: Woods Creek, Creek score: Monitor\",\"WBID: 1558I, JEI: HC07, Name: Peppermound Creek, Creek score: No Data\",\"WBID: 1577A, JEI: HC07, Name: Peppermound Creek, Creek score: Monitor\",\"WBID: 1570, JEI: HC08, Name: Sweetwater Creek, Creek score: Monitor\",\"WBID: 1570A, JEI: HC08, Name: Sweetwater Creek, Creek score: Monitor\",\"WBID: 1601A, JEI: HC08, Name: Sweetwater Creek, Creek score: No Data\",\"WBID: 1594, JEI: HC09, Name: Fish Creek, Creek score: Monitor\",\"WBID: 1606, JEI: HC10, Name: Lemon Street Ditch, Creek score: No Data\",\"WBID: 1536E, JEI: HC13, Name: NA, Creek score: No Data\",\"WBID: 1584A1, JEI: HC13, Name: NA, Creek score: No Data\",\"WBID: 1536A, JEI: HC14, Name: NA, Creek score: No Data\",\"WBID: 1536E, JEI: HC14, Name: NA, Creek score: No Data\",\"WBID: 1536E, JEI: HC15, Name: NA, Creek score: No Data\",\"WBID: 1615, JEI: HC15, Name: NA, Creek score: No Data\",\"WBID: 1615, JEI: HC16, Name: Ironhead Creek, Creek score: Prioritize\",\"WBID: 1605, JEI: HC17, Name: Delaney Creek, Creek score: Monitor\",\"WBID: 1605D, JEI: HC17, Name: Delaney Creek, Creek score: Investigate\",\"WBID: 1636, JEI: HC18, Name: Port Sutton Ditch, Creek score: Prioritize\",\"WBID: 1637, JEI: HC18, Name: Port Sutton Ditch, Creek score: No Data\",\"WBID: 1636, JEI: HC19, Name: Verger Creek, Creek score: No Data\",\"WBID: 1637, JEI: HC19, Name: Verger Creek, Creek score: No Data\",\"WBID: 1558E, JEI: HC20, Name: Delaney Creek Popoff, Creek score: No Data\",\"WBID: 1605, JEI: HC20, Name: Delaney Creek Popoff, Creek score: No Data\",\"WBID: 1628, JEI: HC20, Name: Delaney Creek Popoff, Creek score: No Data\",\"WBID: 1632, JEI: HC20, Name: Delaney Creek Popoff, Creek score: Monitor\",\"WBID: 1558E, JEI: HC21, Name: North Archie Creek, Creek score: No Data\",\"WBID: 1628, JEI: HC21, Name: North Archie Creek, Creek score: No Data\",\"WBID: 1628A, JEI: HC21, Name: North Archie Creek, Creek score: Monitor\",\"WBID: 1632, JEI: HC21, Name: North Archie Creek, Creek score: No Data\",\"WBID: 1558E, JEI: HC22, Name: South Archie Creek, Creek score: No Data\",\"WBID: 1628, JEI: HC22, Name: South Archie Creek, Creek score: Investigate\",\"WBID: 1628A, JEI: HC22, Name: South Archie Creek, Creek score: Monitor\",\"WBID: 1635B, JEI: HC23, Name: Buckhorn Creek, Creek score: Monitor\",\"WBID: 1659, JEI: HC24, Name: Rice Creek, Creek score: Monitor\",\"WBID: 1558D, JEI: HC25, Name: Bullfrog Creek, Creek score: No Data\",\"WBID: 1666, JEI: HC25, Name: Bullfrog Creek, Creek score: Monitor\",\"WBID: 1666A, JEI: HC25, Name: Bullfrog Creek, Creek score: Monitor\",\"WBID: 1686, JEI: HC25, Name: Bullfrog Creek, Creek score: Prioritize\",\"WBID: 1688, JEI: HC25, Name: Bullfrog Creek, Creek score: No Data\",\"WBID: 1693, JEI: HC26, Name: Jackson Branch, Creek score: No Data\",\"WBID: 1693, JEI: HC27, Name: Newman Branch, Creek score: No Data\",\"WBID: 1708, JEI: HC27, Name: Newman Branch, Creek score: No Data\",\"WBID: 1712, JEI: HC28, Name: Beever Creek, Creek score: No Data\",\"WBID: 1719, JEI: HC29, Name: NA, Creek score: Prioritize\",\"WBID: 1725, JEI: HC30, Name: NA, Creek score: No Data\",\"WBID: 1725, JEI: HC31, Name: NA, Creek score: No Data\",\"WBID: 1736, JEI: HC31, Name: NA, Creek score: No Data\",\"WBID: 1558C, JEI: HC32, Name: Wolf Branch, Creek score: No Data\",\"WBID: 1725, JEI: HC32, Name: Wolf Branch, Creek score: No Data\",\"WBID: 1736, JEI: HC32, Name: Wolf Branch, Creek score: Monitor\",\"WBID: 1742A1, JEI: HC33, Name: Marsh Branch, Creek score: No Data\",\"WBID: 1747A, JEI: HC33, Name: Marsh Branch, Creek score: No Data\",\"WBID: 1747B, JEI: HC33, Name: Marsh Branch, Creek score: Prioritize\",\"WBID: 1742C1, JEI: HC34, Name: Curiosity Creek, Creek score: No Data\",\"WBID: 1792, JEI: HC34, Name: Curiosity Creek, Creek score: Investigate\",\"WBID: 1798, JEI: HC34, Name: Curiosity Creek, Creek score: No Data\",\"WBID: 1780, JEI: HC35, Name: NA, Creek score: Caution\",\"WBID: 1779, JEI: HC36, Name: Wildcat Creek, Creek score: No Data\",\"WBID: 1780, JEI: HC36, Name: Wildcat Creek, Creek score: No Data\",\"WBID: 1742C1, JEI: HC37, Name: Sun City Slough, Creek score: No Data\",\"WBID: 1771, JEI: HC37, Name: Sun City Slough, Creek score: Caution\",\"WBID: 1778, JEI: HC38, Name: Cockroach Creek, Creek score: No Data\",\"WBID: 1788, JEI: HC38, Name: Cockroach Creek, Creek score: Prioritize\",\"WBID: 1789, JEI: HC38, Name: Cockroach Creek, Creek score: No Data\",\"WBID: 1792, JEI: HC39, Name: Piney Point Creek, Creek score: No Data\",\"WBID: 1789, JEI: HC39, Name: Piney Point Creek, Creek score: Prioritize\",\"WBID: 1797B, JEI: HC39, Name: Piney Point Creek, Creek score: No Data\",\"WBID: 1816, JEI: HC39, Name: Piney Point Creek, Creek score: No Data\",\"WBID: 1609, JEI: HC40, Name: Coon Hammock Creek\\r\\n, Creek score: No Data\",\"WBID: 1621G, JEI: HC41, Name: NA, Creek score: No Data\",\"WBID: 1558I, JEI: HC42, Name: Boat Bayou, Creek score: No Data\",\"WBID: 1566, JEI: HC42, Name: Boat Bayou, Creek score: No Data\",\"WBID: 1609, JEI: HC44, Name: Gun Branch, Creek score: No Data\",\"WBID: 1558G, JEI: HC45, Name: John Branch, Creek score: No Data\",\"WBID: 1609, JEI: HC45, Name: John Branch, Creek score: No Data\",\"WBID: 1584A1, JEI: HC46, Name: Multicolor Creek, Creek score: No Data\",\"WBID: 1584B, JEI: HC46, Name: Multicolor Creek, Creek score: No Data\",\"WBID: 1558E, JEI: HC47, Name: Lee Creek, Creek score: No Data\",\"WBID: 1637, JEI: HC47, Name: Lee Creek, Creek score: No Data\",\"WBID: 1664, JEI: HC48, Name: Gibsonton Creek, Creek score: No Data\",\"WBID: 1558D, JEI: HC49, Name: Dug Creek, Creek score: No Data\",\"WBID: 1676A, JEI: HC49, Name: Dug Creek, Creek score: Caution\",\"WBID: 1682, JEI: HC50, Name: Kitchen Branch, Creek score: Monitor\",\"WBID: 1691, JEI: HC51, Name: Sims Branch, Creek score: No Data\",\"WBID: 1778, JEI: HC52, Name: Andrews Creek, Creek score: No Data\",\"WBID: 1682, JEI: HC53, Name: NA, Creek score: Monitor\",\"WBID: 1558C, JEI: HC54, Name: Broad Creek, Creek score: No Data\",\"WBID: 1609, JEI: HC54, Name: Broad Creek, Creek score: No Data\",\"WBID: 2065D, JEI: LC01, Name: NA, Creek score: Monitor\",\"WBID: 2082B, JEI: LC01, Name: NA, Creek score: No Data\",\"WBID: 2082B1, JEI: LC01, Name: NA, Creek score: Monitor\",\"WBID: 2093A, JEI: LC01, Name: NA, Creek score: No Data\",\"WBID: 2082B, JEI: LC02, Name: Yucca Pen Creek, Creek score: Prioritize\",\"WBID: 2082B2, JEI: LC02, Name: Yucca Pen Creek, Creek score: Monitor\",\"WBID: 2065D, JEI: LC03, Name: Durden Creek, Creek score: No Data\",\"WBID: 2082C, JEI: LC03, Name: Durden Creek, Creek score: Investigate\",\"WBID: 2082C1, JEI: LC03, Name: Durden Creek, Creek score: Monitor\",\"WBID: 2082C2, JEI: LC03, Name: Durden Creek, Creek score: Monitor\",\"WBID: 2065D, JEI: LC04, Name: NA, Creek score: No Data\",\"WBID: 2082C1, JEI: LC04, Name: NA, Creek score: No Data\",\"WBID: 2065F, JEI: LC05, Name: Gator Slough, Creek score: No Data\",\"WBID: 2082C1, JEI: LC05, Name: Gator Slough, Creek score: No Data\",\"WBID: 2065F, JEI: LC06, Name: NA, Creek score: No Data\",\"WBID: 2082C1, JEI: LC06, Name: NA, Creek score: No Data\",\"WBID: 2065F, JEI: LC07, Name: NA, Creek score: No Data\",\"WBID: 2082C1, JEI: LC08, Name: NA, Creek score: No Data\",\"WBID: 2065F, JEI: LC09, Name: NA, Creek score: No Data\",\"WBID: 3240S, JEI: LC09, Name: NA, Creek score: No Data\",\"WBID: 2065F, JEI: LC10, Name: NA, Creek score: No Data\",\"WBID: 2065F, JEI: LC11, Name: NA, Creek score: No Data\",\"WBID: 3240S, JEI: LC11, Name: NA, Creek score: No Data\",\"WBID: 3240A, JEI: LC13, Name: NA, Creek score: No Data\",\"WBID: 3240A1, JEI: LC13, Name: NA, Creek score: No Data\",\"WBID: 3240A, JEI: LC17, Name: NA, Creek score: No Data\",\"WBID: 3240A1, JEI: LC17, Name: NA, Creek score: No Data\",\"WBID: 3240A, JEI: LC19, Name: NA, Creek score: Monitor\",\"WBID: 3240A1, JEI: LC19, Name: NA, Creek score: Monitor\",\"WBID: 3240EA, JEI: LC20, Name: Hancock Creek/Yellow Fever Creek, Creek score: Monitor\",\"WBID: 3240E1, JEI: LC20, Name: Hancock Creek/Yellow Fever Creek, Creek score: Monitor\",\"WBID: 3240EB, JEI: LC20, Name: Hancock Creek/Yellow Fever Creek, Creek score: Monitor\",\"WBID: 3240B, JEI: LC21, Name: Powell Creek, Creek score: No Data\",\"WBID: 3240EA, JEI: LC21, Name: Powell Creek, Creek score: Investigate\",\"WBID: 3240L, JEI: LC21, Name: Powell Creek, Creek score: Monitor\",\"WBID: 2082C, JEI: LC21, Name: Powell Creek, Creek score: No Data\",\"WBID: 3240B, JEI: LC22, Name: NA, Creek score: Monitor\",\"WBID: 3240B2, JEI: LC23, Name: Daughtrey Creek, Creek score: No Data\",\"WBID: 3240F, JEI: LC23, Name: Daughtrey Creek, Creek score: Monitor\",\"WBID: 3240B1, JEI: LC24, Name: NA, Creek score: Monitor\",\"WBID: 3240B2, JEI: LC24, Name: NA, Creek score: Monitor\",\"WBID: 3240F, JEI: LC24, Name: NA, Creek score: No Data\",\"WBID: 3240B1, JEI: LC25, Name: NA, Creek score: Monitor\",\"WBID: 3240B2, JEI: LC25, Name: NA, Creek score: No Data\",\"WBID: 3240Q, JEI: LC26, Name: Popash Creek, Creek score: Monitor\",\"WBID: 3240C, JEI: LC27, Name: Stroud Creek, Creek score: No Data\",\"WBID: 3240M, JEI: LC27, Name: Stroud Creek, Creek score: Monitor\",\"WBID: 3240Q, JEI: LC27, Name: Stroud Creek, Creek score: No Data\",\"WBID: 3240C, JEI: LC28, Name: Palm Creek, Creek score: No Data\",\"WBID: 3240C1, JEI: LC28, Name: Palm Creek, Creek score: Monitor\",\"WBID: 3240G, JEI: LC29, Name: Owl Creek, Creek score: No Data\",\"WBID: 3240N, JEI: LC29, Name: Owl Creek, Creek score: Monitor\",\"WBID: 3240C, JEI: LC30, Name: Trout Creek, Creek score: No Data\",\"WBID: 3240G, JEI: LC30, Name: Trout Creek, Creek score: Monitor\",\"WBID: 3236A, JEI: LC31, Name: Telegraph Creek, Creek score: Monitor\",\"WBID: 3240C, JEI: LC33, Name: Orange River, Creek score: No Data\",\"WBID: 3240K, JEI: LC33, Name: Orange River, Creek score: Monitor\",\"WBID: 3240B, JEI: LC35, Name: Billy Creek, Creek score: No Data\",\"WBID: 3240J1, JEI: LC35, Name: Billy Creek, Creek score: Monitor\",\"WBID: 3240J2, JEI: LC35, Name: Billy Creek, Creek score: Investigate\",\"WBID: 3240J3, JEI: LC35, Name: Billy Creek, Creek score: Monitor\",\"WBID: 3240J4, JEI: LC35, Name: Billy Creek, Creek score: Monitor\",\"WBID: 3240A, JEI: LC36, Name: Manuel Branch, Creek score: No Data\",\"WBID: 3240V, JEI: LC36, Name: Manuel Branch, Creek score: Monitor\",\"WBID: 3240H1, JEI: LC39, Name: Whiskey Creek, Creek score: Monitor\",\"WBID: 3240A, JEI: LC40, Name: NA, Creek score: Monitor\",\"WBID: 3240A4, JEI: LC40, Name: NA, Creek score: Caution\",\"WBID: 3240A4, JEI: LC43, Name: NA, Creek score: No Data\",\"WBID: 3240O, JEI: LC44, Name: NA, Creek score: No Data\",\"WBID: 3258A1, JEI: LC45, Name: Cow Creek, Creek score: No Data\",\"WBID: 3258B2, JEI: LC46, Name: Hendry Creek, Creek score: Caution\",\"WBID: 3258X, JEI: LC46, Name: Hendry Creek, Creek score: No Data\",\"WBID: 3258C2, JEI: LC47, Name: Mullock Creek, Creek score: Monitor\",\"WBID: 3258C4, JEI: LC47, Name: Mullock Creek, Creek score: Monitor\",\"WBID: 3258D3, JEI: LC47, Name: Mullock Creek, Creek score: No Data\",\"WBID: 3258D1, JEI: LC48, Name: Estero River/Halfway Creek, Creek score: Monitor\",\"WBID: 3258D3, JEI: LC48, Name: Estero River/Halfway Creek, Creek score: Monitor\",\"WBID: 3258D4, JEI: LC48, Name: Estero River/Halfway Creek, Creek score: Monitor\",\"WBID: 3258I, JEI: LC48, Name: Estero River/Halfway Creek, Creek score: Monitor\",\"WBID: 3258H2, JEI: LC49, Name: NA, Creek score: No Data\",\"WBID: 3258H2, JEI: LC50, Name: Spring Creek, Creek score: Caution\",\"WBID: 3258H3, JEI: LC50, Name: Spring Creek, Creek score: Monitor\",\"WBID: 3258EB, JEI: LC51, Name: Imperial River/Oak Creek, Creek score: Monitor\",\"WBID: 3258EC, JEI: LC51, Name: Imperial River/Oak Creek, Creek score: Monitor\",\"WBID: 3258ED, JEI: LC51, Name: Imperial River/Oak Creek, Creek score: Monitor\",\"WBID: 3258EG, JEI: LC51, Name: Imperial River/Oak Creek, Creek score: No Data\",\"WBID: 3258F, JEI: LC51, Name: Imperial River/Oak Creek, Creek score: Monitor\",\"WBID: 2065F, JEI: LC53, Name: NA, Creek score: No Data\",\"WBID: 3240S, JEI: LC53, Name: NA, Creek score: No Data\",\"WBID: 2065F, JEI: LC54, Name: NA, Creek score: No Data\",\"WBID: 2065F, JEI: LC55, Name: Underhill Creek, Creek score: No Data\",\"WBID: 2065F, JEI: LC56, Name: NA, Creek score: No Data\",\"WBID: 2065F, JEI: LC57, Name: NA, Creek score: No Data\",\"WBID: 2065H1, JEI: LC57, Name: NA, Creek score: No Data\",\"WBID: 2065H1, JEI: LC58, Name: NA, Creek score: No Data\",\"WBID: 3258C4, JEI: LC59, Name: Mud Creek, Creek score: Monitor\",\"WBID: 3258I, JEI: LC59, Name: Mud Creek, Creek score: No Data\",\"WBID: 3258C4, JEI: LC60, Name: NA, Creek score: No Data\",\"WBID: 1792, JEI: MC01, Name: Clark Creek, Creek score: No Data\",\"WBID: 1797B, JEI: MC01, Name: Clark Creek, Creek score: No Data\",\"WBID: 1816, JEI: MC01, Name: Clark Creek, Creek score: No Data\",\"WBID: 1797A, JEI: MC02, Name: Frog Creek, Creek score: No Data\",\"WBID: 1797B, JEI: MC02, Name: Frog Creek, Creek score: No Data\",\"WBID: 1816, JEI: MC02, Name: Frog Creek, Creek score: No Data\",\"WBID: 1823, JEI: MC02, Name: Frog Creek, Creek score: No Data\",\"WBID: 1825A, JEI: MC02, Name: Frog Creek, Creek score: Investigate\",\"WBID: 1825B, JEI: MC02, Name: Frog Creek, Creek score: Prioritize\",\"WBID: 1797A, JEI: MC03, Name: NA, Creek score: No Data\",\"WBID: 1841, JEI: MC03, Name: NA, Creek score: No Data\",\"WBID: 1797A, JEI: MC04, Name: McMullen Creek, Creek score: No Data\",\"WBID: 1841, JEI: MC04, Name: McMullen Creek, Creek score: Monitor\",\"WBID: 1797A, JEI: MC05, Name: NA, Creek score: No Data\",\"WBID: 1797A, JEI: MC06, Name: Palmetto Creek, Creek score: No Data\",\"WBID: 1797A, JEI: MC07, Name: King Creek, Creek score: No Data\",\"WBID: 1797A, JEI: MC08, Name: Memphis Creek, Creek score: No Data\",\"WBID: 1848A, JEI: MC09, Name: NA, Creek score: Prioritize\",\"WBID: 1797A, JEI: MC09, Name: NA, Creek score: No Data\",\"WBID: 1848A, JEI: MC10, Name: NA, Creek score: Prioritize\",\"WBID: 1848B, JEI: MC10, Name: NA, Creek score: No Data\",\"WBID: 1848B, JEI: MC11, Name: NA, Creek score: No Data\",\"WBID: 1841, JEI: MC11, Name: NA, Creek score: No Data\",\"WBID: 1848B, JEI: MC12, Name: NA, Creek score: No Data\",\"WBID: 1850, JEI: MC12, Name: NA, Creek score: No Data\",\"WBID: 1807G, JEI: MC13, Name: Mill Creek, Creek score: Monitor\",\"WBID: 1872B, JEI: MC13, Name: Mill Creek, Creek score: Monitor\",\"WBID: 1909, JEI: MC13, Name: Mill Creek, Creek score: No Data\",\"WBID: 1872A, JEI: MC13, Name: Mill Creek, Creek score: Monitor\",\"WBID: 1807G, JEI: MC14, Name: Gates Creek, Creek score: No Data\",\"WBID: 1874, JEI: MC14, Name: Gates Creek, Creek score: Monitor\",\"WBID: 1807G, JEI: MC15, Name: NA, Creek score: No Data\",\"WBID: 1807G, JEI: MC16, Name: NA, Creek score: No Data\",\"WBID: 1807G, JEI: MC17, Name: NA, Creek score: No Data\",\"WBID: 1848B, JEI: MC17, Name: NA, Creek score: No Data\",\"WBID: 1875, JEI: MC17, Name: NA, Creek score: No Data\",\"WBID: 1807G, JEI: MC19, Name: NA, Creek score: No Data\",\"WBID: 1848B, JEI: MC19, Name: NA, Creek score: No Data\",\"WBID: 1848B, JEI: MC20, Name: NA, Creek score: No Data\",\"WBID: 1848B, JEI: MC21, Name: NA, Creek score: No Data\",\"WBID: 1875, JEI: MC21, Name: NA, Creek score: No Data\",\"WBID: 1848B, JEI: MC22, Name: NA, Creek score: No Data\",\"WBID: 1875, JEI: MC22, Name: NA, Creek score: No Data\",\"WBID: 1848B, JEI: MC23, Name: Cypress Strand, Creek score: No Data\",\"WBID: 1875, JEI: MC23, Name: Cypress Strand, Creek score: No Data\",\"WBID: 1876, JEI: MC23, Name: Cypress Strand, Creek score: No Data\",\"WBID: 1848B, JEI: MC24, Name: NA, Creek score: No Data\",\"WBID: 1875, JEI: MC24, Name: NA, Creek score: No Data\",\"WBID: 1876, JEI: MC26, Name: NA, Creek score: No Data\",\"WBID: 1876, JEI: MC27, Name: NA, Creek score: No Data\",\"WBID: 1876, JEI: MC28, Name: NA, Creek score: No Data\",\"WBID: 1876, JEI: MC29, Name: Gap Creek, Creek score: No Data\",\"WBID: 1876A, JEI: MC29, Name: Gap Creek, Creek score: No Data\",\"WBID: 1899, JEI: MC29, Name: Gap Creek, Creek score: Monitor\",\"WBID: 1848A, JEI: MC30, Name: Sugarhouse Creek, Creek score: No Data\",\"WBID: 1848D1, JEI: MC30, Name: Sugarhouse Creek, Creek score: No Data\",\"WBID: 1848D2, JEI: MC30, Name: Sugarhouse Creek, Creek score: No Data\",\"WBID: 1876, JEI: MC30, Name: Sugarhouse Creek, Creek score: No Data\",\"WBID: 1887, JEI: MC30, Name: Sugarhouse Creek, Creek score: Monitor\",\"WBID: 1876, JEI: MC31, Name: NA, Creek score: No Data\",\"WBID: 1888A, JEI: MC32, Name: Wares Creek, Creek score: No Data\",\"WBID: 1848A, JEI: MC32, Name: Wares Creek, Creek score: No Data\",\"WBID: 1848D1, JEI: MC32, Name: Wares Creek, Creek score: Monitor\",\"WBID: 1848D2, JEI: MC32, Name: Wares Creek, Creek score: Monitor\",\"WBID: 1848A, JEI: MC33, Name: NA, Creek score: No Data\",\"WBID: 1885A, JEI: MC34, Name: Wares Creek, Creek score: Caution\",\"WBID: 1888A, JEI: MC34, Name: Wares Creek, Creek score: No Data\",\"WBID: 1888B, JEI: MC35, Name: Palma Sola Creek, Creek score: No Data\",\"WBID: 1883, JEI: MC36, Name: NA, Creek score: No Data\",\"WBID: 1888A, JEI: MC36, Name: NA, Creek score: No Data\",\"WBID: 1888A, JEI: MC37, Name: NA, Creek score: No Data\",\"WBID: 1888A, JEI: MC38, Name: Cedar Hammock Creek, Creek score: No Data\",\"WBID: 1896, JEI: MC39, Name: Bowlees Creek, Creek score: Monitor\",\"WBID: 1899, JEI: MC39, Name: Bowlees Creek, Creek score: Monitor\",\"WBID: 1888A, JEI: MC40, Name: NA, Creek score: No Data\",\"WBID: 1968B, JEI: MC40, Name: NA, Creek score: No Data\",\"WBID: 1888A, JEI: MC41, Name: NA, Creek score: No Data\",\"WBID: 1888A, JEI: MC42, Name: NA, Creek score: No Data\",\"WBID: 1868, JEI: MC43, Name: NA, Creek score: No Data\",\"WBID: 1883, JEI: MC43, Name: NA, Creek score: No Data\",\"WBID: 1901, JEI: MC44, Name: Williams Creek, Creek score: Monitor\",\"WBID: 1797B, JEI: MC45, Name: Little Redfish Creek, Creek score: No Data\",\"WBID: 1797A, JEI: MC46, Name: Peterson Creek, Creek score: No Data\",\"WBID: 1888A, JEI: MC47, Name: NA, Creek score: No Data\",\"WBID: 1888A, JEI: MC48, Name: NA, Creek score: No Data\",\"WBID: 1968B, JEI: MC48, Name: NA, Creek score: No Data\",\"WBID: 1618C, JEI: PC01, Name: NA, Creek score: Monitor\",\"WBID: 1618D, JEI: PC01, Name: NA, Creek score: Monitor\",\"WBID: 1625, JEI: PC02, Name: Cross Bayou, Creek score: No Data\",\"WBID: 1641, JEI: PC02, Name: Cross Bayou, Creek score: Caution\",\"WBID: 1662, JEI: PC02, Name: Cross Bayou, Creek score: No Data\",\"WBID: 1662, JEI: PC03, Name: NA, Creek score: Caution\",\"WBID: 1662A, JEI: PC03, Name: NA, Creek score: Monitor\",\"WBID: 1641, JEI: PC04, Name: Saint Joes Creek, Creek score: No Data\",\"WBID: 1668A, JEI: PC04, Name: Saint Joes Creek, Creek score: Monitor\",\"WBID: 1668B, JEI: PC04, Name: Saint Joes Creek, Creek score: Monitor\",\"WBID: 1668D, JEI: PC04, Name: Saint Joes Creek, Creek score: Monitor\",\"WBID: 1668E, JEI: PC04, Name: Saint Joes Creek, Creek score: Prioritize\",\"WBID: 1701A, JEI: PC05, Name: Bear Creek, Creek score: Monitor\",\"WBID: 1701B, JEI: PC05, Name: Bear Creek, Creek score: Monitor\",\"WBID: 1716B, JEI: PC06, Name: NA, Creek score: Monitor\",\"WBID: 1716D, JEI: PC06, Name: NA, Creek score: Monitor\",\"WBID: 1716A, JEI: PC07, Name: NA, Creek score: Investigate\",\"WBID: 1716C1, JEI: PC07, Name: NA, Creek score: No Data\",\"WBID: 1716D, JEI: PC07, Name: NA, Creek score: Monitor\",\"WBID: 1731, JEI: PC08, Name: NA, Creek score: No Data\",\"WBID: 1731A, JEI: PC08, Name: NA, Creek score: No Data\",\"WBID: 1716C1, JEI: PC08, Name: NA, Creek score: Caution\",\"WBID: 1716D, JEI: PC08, Name: NA, Creek score: Monitor\",\"WBID: 1709D, JEI: PC09, Name: Bayou Creek, Creek score: Investigate\",\"WBID: 1558B, JEI: PC10, Name: Salt Creek, Creek score: No Data\",\"WBID: 1709, JEI: PC10, Name: Salt Creek, Creek score: No Data\",\"WBID: 1731, JEI: PC10, Name: Salt Creek, Creek score: No Data\",\"WBID: 1731B, JEI: PC10, Name: Salt Creek, Creek score: Monitor\",\"WBID: 1696, JEI: PC12, Name: Booker Creek, Creek score: Monitor\",\"WBID: 1709B, JEI: PC12, Name: Booker Creek, Creek score: No Data\",\"WBID: 1661B, JEI: PC13, Name: NA, Creek score: No Data\",\"WBID: 1661G, JEI: PC13, Name: NA, Creek score: No Data\",\"WBID: 1661A, JEI: PC14, Name: Turners Creek, Creek score: No Data\",\"WBID: 1661E, JEI: PC14, Name: Turners Creek, Creek score: No Data\",\"WBID: 1661H, JEI: PC14, Name: Turners Creek, Creek score: No Data\",\"WBID: 1661I, JEI: PC14, Name: Turners Creek, Creek score: No Data\",\"WBID: 1661D, JEI: PC15, Name: Tinney Creek, Creek score: No Data\",\"WBID: 1661E, JEI: PC15, Name: Tinney Creek, Creek score: No Data\",\"WBID: 1625, JEI: PC16, Name: Cross Bayou, Creek score: Monitor\",\"WBID: 1627, JEI: PC17, Name: Long Branch, Creek score: Monitor\",\"WBID: 1627B, JEI: PC17, Name: Long Branch, Creek score: Caution\",\"WBID: 1558H, JEI: PC18, Name: Allen Creek, Creek score: No Data\",\"WBID: 1604, JEI: PC18, Name: Allen Creek, Creek score: Monitor\",\"WBID: 1604B1, JEI: PC18, Name: Allen Creek, Creek score: Monitor\",\"WBID: 1604B2, JEI: PC18, Name: Allen Creek, Creek score: Monitor\",\"WBID: 1575, JEI: PC19, Name: Mullet Creek, Creek score: Monitor\",\"WBID: 1575A, JEI: PC19, Name: Mullet Creek, Creek score: Monitor\",\"WBID: 1569, JEI: PC20, Name: Bishop Creek, Creek score: Monitor\",\"WBID: 1569A, JEI: PC20, Name: Bishop Creek, Creek score: Monitor\",\"WBID: 1546, JEI: PC21, Name: Mobbly Bayou, Creek score: No Data\",\"WBID: 1558I, JEI: PC21, Name: Mobbly Bayou, Creek score: No Data\",\"WBID: 1528B, JEI: PC22, Name: NA, Creek score: No Data\",\"WBID: 1668F, JEI: PC23, Name: NA, Creek score: Monitor\",\"WBID: 1694B, JEI: PC23, Name: NA, Creek score: No Data\",\"WBID: 1530, JEI: PC24, Name: Moccasin Creek, Creek score: Caution\",\"WBID: 1558H, JEI: PC25, Name: Grassy Creek, Creek score: No Data\",\"WBID: 1541A, JEI: PC26, Name: Briar Creek, Creek score: No Data\",\"WBID: 1541C, JEI: PC26, Name: Briar Creek, Creek score: Monitor\",\"WBID: 1479, JEI: PC27, Name: Snead Creek, Creek score: No Data\",\"WBID: 8045G, JEI: PC27, Name: Snead Creek, Creek score: No Data\",\"WBID: 1538, JEI: PC28, Name: Curlew Creek, Creek score: Prioritize\",\"WBID: 1538A, JEI: PC28, Name: Curlew Creek, Creek score: Prioritize\",\"WBID: 1550, JEI: PC28, Name: Curlew Creek, Creek score: No Data\",\"WBID: 1556, JEI: PC29, Name: Cedar Creek, Creek score: Caution\",\"WBID: 1556A, JEI: PC29, Name: Cedar Creek, Creek score: Monitor\",\"WBID: 1567, JEI: PC30, Name: Stevenson Creek, Creek score: Monitor\",\"WBID: 1567C, JEI: PC30, Name: Stevenson Creek, Creek score: Monitor\",\"WBID: 1633, JEI: PC31, Name: McKay Creek, Creek score: Monitor\",\"WBID: 1633E, JEI: PC31, Name: McKay Creek, Creek score: Monitor\",\"WBID: 1643, JEI: PC32, Name: Church Creek, Creek score: Prioritize\",\"WBID: 1508, JEI: PC33, Name: Innisbrook Canal, Creek score: Prioritize\",\"WBID: 1508A, JEI: PC33, Name: Innisbrook Canal, Creek score: Prioritize\",\"WBID: 1527A, JEI: PC34, Name: Bee Branch, Creek score: No Data\",\"WBID: 1527B, JEI: PC34, Name: Bee Branch, Creek score: Monitor\",\"WBID: 1535, JEI: PC35, Name: Minnow Creek, Creek score: Monitor\",\"WBID: 1567, JEI: PC36, Name: Spring Branch, Creek score: No Data\",\"WBID: 1567B, JEI: PC36, Name: Spring Branch, Creek score: Monitor\",\"WBID: 1528, JEI: PC37, Name: Rattlesnake Creek, Creek score: No Data\",\"WBID: 1614, JEI: PC37, Name: Rattlesnake Creek, Creek score: Prioritize\",\"WBID: 1936, JEI: SC01, Name: Whitaker Bayou, Creek score: Monitor\",\"WBID: 1936A, JEI: SC01, Name: Whitaker Bayou, Creek score: Monitor\",\"WBID: 1953, JEI: SC02, Name: Hudson Bayou, Creek score: Monitor\",\"WBID: 1953A, JEI: SC02, Name: Hudson Bayou, Creek score: Monitor\",\"WBID: 1968C, JEI: SC02, Name: Hudson Bayou, Creek score: No Data\",\"WBID: 1937, JEI: SC03, Name: Phillippi Creek, Creek score: Monitor\",\"WBID: 1947, JEI: SC03, Name: Phillippi Creek, Creek score: Monitor\",\"WBID: 1975D, JEI: SC04, Name: Mathaney Creek, Creek score: No Data\",\"WBID: 1975C, JEI: SC04, Name: Mathaney Creek, Creek score: No Data\",\"WBID: 1975A, JEI: SC06, Name: Clower Creek, Creek score: Investigate\",\"WBID: 1984A, JEI: SC07, Name: Catfish/North Creek, Creek score: Prioritize\",\"WBID: 1984AB, JEI: SC07, Name: Catfish/North Creek, Creek score: Prioritize\",\"WBID: 1984B, JEI: SC07, Name: Catfish/North Creek, Creek score: Monitor\",\"WBID: 1982, JEI: SC08, Name: South Creek, Creek score: Investigate\",\"WBID: 1982A, JEI: SC08, Name: South Creek, Creek score: No Data\",\"WBID: 1982B, JEI: SC08, Name: South Creek, Creek score: Prioritize\",\"WBID: 1985, JEI: SC08, Name: South Creek, Creek score: No Data\",\"WBID: 1924, JEI: SC12, Name: Shakett Creek, Creek score: No Data\",\"WBID: 1924A, JEI: SC12, Name: Shakett Creek, Creek score: No Data\",\"WBID: 1924B, JEI: SC12, Name: Shakett Creek, Creek score: No Data\",\"WBID: 1994A, JEI: SC12, Name: Shakett Creek, Creek score: No Data\",\"WBID: 1994B, JEI: SC12, Name: Shakett Creek, Creek score: Monitor\",\"WBID: 2002, JEI: SC12, Name: Shakett Creek, Creek score: Caution\",\"WBID: 2009B, JEI: SC14, Name: Curry Creek, Creek score: Caution\",\"WBID: 2009C, JEI: SC14, Name: Curry Creek, Creek score: No Data\",\"WBID: 2016, JEI: SC14, Name: Curry Creek, Creek score: No Data\",\"WBID: 2018A, JEI: SC14, Name: Curry Creek, Creek score: Monitor\",\"WBID: 2015, JEI: SC15, Name: Hatchett Creek, Creek score: Monitor\",\"WBID: 2015A, JEI: SC15, Name: Hatchett Creek, Creek score: Monitor\",\"WBID: 1983A1, JEI: SC17, Name: Alligator Creek Sarasota, Creek score: No Data\",\"WBID: 2030, JEI: SC17, Name: Alligator Creek Sarasota, Creek score: Caution\",\"WBID: 1983A1, JEI: SC20, Name: NA, Creek score: No Data\",\"WBID: 2042, JEI: SC20, Name: NA, Creek score: No Data\",\"WBID: 2039, JEI: SC22, Name: Forked Creek, Creek score: Monitor\",\"WBID: 1983B, JEI: SC25, Name: Gottfried Creek, Creek score: No Data\",\"WBID: 2049, JEI: SC25, Name: Gottfried Creek, Creek score: Caution\",\"WBID: 1991C, JEI: SC26, Name: NA, Creek score: No Data\",\"WBID: 1991E, JEI: SC27, Name: NA, Creek score: No Data\",\"WBID: 1991E, JEI: SC28, Name: NA, Creek score: No Data\",\"WBID: 2038, JEI: SC28, Name: NA, Creek score: No Data\",\"WBID: 1991E, JEI: SC29, Name: NA, Creek score: No Data\",\"WBID: 2037, JEI: SC29, Name: NA, Creek score: No Data\",\"WBID: 1991E, JEI: SC30, Name: NA, Creek score: No Data\",\"WBID: 2036, JEI: SC30, Name: NA, Creek score: No Data\",\"WBID: 1991E, JEI: SC31, Name: NA, Creek score: No Data\",\"WBID: 2034, JEI: SC31, Name: NA, Creek score: No Data\",\"WBID: 1991E, JEI: SC32, Name: NA, Creek score: No Data\",\"WBID: 2031, JEI: SC32, Name: NA, Creek score: Investigate\",\"WBID: 1991E, JEI: SC33, Name: NA, Creek score: No Data\",\"WBID: 2029, JEI: SC33, Name: NA, Creek score: No Data\",\"WBID: 2031, JEI: SC33, Name: NA, Creek score: No Data\",\"WBID: 1991G, JEI: SC34, Name: NA, Creek score: No Data\",\"WBID: 2011, JEI: SC34, Name: NA, Creek score: Monitor\",\"WBID: 2006, JEI: SC35, Name: NA, Creek score: No Data\",\"WBID: 1978, JEI: SC36, Name: Deer Prairie Creek, Creek score: Monitor\",\"WBID: 1991E, JEI: SC36, Name: Deer Prairie Creek, Creek score: No Data\",\"WBID: 1991C, JEI: SC37, Name: NA, Creek score: No Data\",\"WBID: 1991E, JEI: SC37, Name: NA, Creek score: No Data\",\"WBID: 1991C, JEI: SC38, Name: Little Salt Creek (warm mineral Sping), Creek score: No Data\",\"WBID: 2014, JEI: SC38, Name: Little Salt Creek (warm mineral Sping), Creek score: No Data\",\"WBID: 2026, JEI: SC38, Name: Little Salt Creek (warm mineral Sping), Creek score: Monitor\",\"WBID: 2026A, JEI: SC38, Name: Little Salt Creek (warm mineral Sping), Creek score: Monitor\",\"WBID: 1991C, JEI: SC39, Name: NA, Creek score: No Data\",\"WBID: 1976B, JEI: SC40, Name: Big Slough Canal, Creek score: Investigate\",\"WBID: 1976C, JEI: SC40, Name: Big Slough Canal, Creek score: Monitor\",\"WBID: 2014, JEI: SC40, Name: Big Slough Canal, Creek score: No Data\",\"WBID: 1991B, JEI: SC41, Name: NA, Creek score: No Data\",\"WBID: 1991B, JEI: SC42, Name: NA, Creek score: No Data\",\"WBID: 1991B, JEI: SC43, Name: NA, Creek score: No Data\",\"WBID: 2057, JEI: SC43, Name: NA, Creek score: No Data\"],{\"interactive\":false,\"permanent\":false,\"direction\":\"auto\",\"opacity\":1,\"offset\":[0,0],\"textsize\":\"10px\",\"textOnly\":false,\"className\":\"\",\"sticky\":true},null]}],\"limits\":{\"lat\":[26.32829183658335,28.12975168603929],\"lng\":[-82.83757582032332,-81.68445583408415]}},\"evals\":[],\"jsHooks\":{\"render\":[{\"code\":\"function(el, x, data) {\\n return (\\n function(el, x) {\\n var myMap = this;\\n myMap.on('baselayerchange',\\n function (e) {\\n myMap.minimap.changeLayer(L.tileLayer.provider(e.name));\\n })\\n }).call(this.getMap(), el, x, data);\\n}\",\"data\":null}]}}"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkindic.html","id":null,"dir":"Reference","previous_headings":"","what":"Plotly barplots of tidal creek context indicators — show_tdlcrkindic","title":"Plotly barplots of tidal creek context indicators — show_tdlcrkindic","text":"Plotly barplots tidal creek context indicators","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkindic.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plotly barplots of tidal creek context indicators — show_tdlcrkindic","text":"","code":"show_tdlcrkindic( id, cntdat, yr = 2023, thrsel = FALSE, pal = c(\"#5C4A42\", \"#427355\", \"#004F7E\") )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkindic.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plotly barplots of tidal creek context indicators — show_tdlcrkindic","text":"id numeric indicating id number tidal creek plot cntdat output anlz_tdlcrkindic yr numeric indicating reference year thrsel logical threshold lines annotations shown plots pal vector colors palette","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkindic.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plotly barplots of tidal creek context indicators — show_tdlcrkindic","text":"plotly object","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkindic.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plotly barplots of tidal creek context indicators — show_tdlcrkindic","text":"","code":"cntdat <- anlz_tdlcrkindic(tidalcreeks, iwrraw, yr = 2023) set.seed(123) id <- sample(unique(cntdat$id), 1) show_tdlcrkindic(id, cntdat, thrsel = TRUE) 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empirical CDF plots of tidal creek context indicators — show_tdlcrkindiccdf","title":"Plotly empirical CDF plots of tidal creek context indicators — show_tdlcrkindiccdf","text":"Plotly empirical CDF plots tidal creek context indicators","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkindiccdf.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plotly empirical CDF plots of tidal creek context indicators — show_tdlcrkindiccdf","text":"","code":"show_tdlcrkindiccdf( id, cntdat, yr = 2023, thrsel = FALSE, pal = c(\"#5C4A42\", \"#427355\", \"#004F7E\") )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkindiccdf.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plotly empirical CDF plots of tidal creek context indicators — show_tdlcrkindiccdf","text":"id numeric indicating id number tidal creek plot cntdat output anlz_tdlcrkindic yr numeric indicating reference year thrsel logical threshold lines annotations shown plots pal vector colors palette","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkindiccdf.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plotly empirical CDF plots of tidal creek context indicators — show_tdlcrkindiccdf","text":"plotly object","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkindiccdf.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Plotly empirical CDF plots of tidal creek context indicators — show_tdlcrkindiccdf","text":"function returns several empirical cumulative distribution plots tidal creek context indicators. Points plot indicate observed values percentiles creek specified id. percentiles CDF values defined \"population\" creeks cntdat. Points plots color-coded sample year evaluate temporal trends, .","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkindiccdf.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plotly empirical CDF plots of tidal creek context indicators — show_tdlcrkindiccdf","text":"","code":"cntdat <- anlz_tdlcrkindic(tidalcreeks, iwrraw, yr = 2023) set.seed(123) id <- sample(unique(cntdat$id), 1) show_tdlcrkindiccdf(id, cntdat, thrsel = TRUE) 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a line or annotation to a plotly graph — show_tdlcrkline","title":"Add a line or annotation to a plotly graph — show_tdlcrkline","text":"Add line annotation plotly graph tidal creek indicators","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkline.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Add a line or annotation to a plotly graph — show_tdlcrkline","text":"","code":"show_tdlcrkline( varin = c(\"CHLAC\", \"TN\", \"chla_tn_ratio\", \"DO\", \"tsi\", \"no23_ratio\"), thrsel = FALSE, horiz = TRUE, annotate = FALSE )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkline.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Add a line or annotation to a plotly graph — show_tdlcrkline","text":"varin chr string indicator thrsel logical something returned, otherwise NULL, hack working plotly output horiz logical indicating output horizontal vertical annotate logical indicating output line annotation text","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkline.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Add a line or annotation to a plotly graph — show_tdlcrkline","text":"list object passed layout argument plotly, either shapes annotate depending user input","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkline.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Add a line or annotation to a plotly graph — show_tdlcrkline","text":"function used internally within show_tdlcrkindic show_tdlcrkindiccdf","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkline.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Add a line or annotation to a plotly graph — show_tdlcrkline","text":"","code":"# code for vertical line output, chloropyll show_tdlcrkline('CHLAC', thrsel = TRUE) #> [[1]] #> [[1]]$type #> [1] \"line\" #> #> [[1]]$x0 #> [1] 0 #> #> [[1]]$x1 #> [1] 1 #> #> [[1]]$xref #> [1] \"paper\" #> #> [[1]]$y0 #> [1] 11 #> #> [[1]]$y1 #> [1] 11 #> #> [[1]]$line #> [[1]]$line$color #> [1] \"red\" #> #> [[1]]$line$dash #> [1] 10 #> #> #>"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkmatrix.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot the tidal creek report card matrix — show_tdlcrkmatrix","title":"Plot the tidal creek report card matrix — show_tdlcrkmatrix","text":"Plot tidal creek report card matrix","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkmatrix.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot the tidal creek report card matrix — show_tdlcrkmatrix","text":"","code":"show_tdlcrkmatrix( dat, class = c(\"3M\", \"2\"), score = c(\"Prioritize\", \"Investigate\", \"Caution\", \"Monitor\"), family = NA, size = 11 )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkmatrix.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot the tidal creek report card matrix — show_tdlcrkmatrix","text":"dat input creek score data returned anlz_tdlcrk class character vector indicating creek classes show, one many '3M', '2', '3F', '1'. Defaults marine ('3M', '2'). score character vector score categories include, one many 'Prioritize', 'Investigate', 'Caution', 'Monitor'. Defaults . family optional chr string indicating font family text labels size numeric text line scaling","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkmatrix.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot the tidal creek report card matrix — show_tdlcrkmatrix","text":"static ggplot object returned.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkmatrix.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Plot the tidal creek report card matrix — show_tdlcrkmatrix","text":"plot shows matrix rows individual creeks columns overall creek score. columns show overall creek score number years prior ten years nitrogen values creek assigned four score categories. Number years mapped cell transparency.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkmatrix.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot the tidal creek report card matrix — show_tdlcrkmatrix","text":"","code":"dat <- anlz_tdlcrk(tidalcreeks, iwrraw, yr = 2023) show_tdlcrkmatrix(dat)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkradar.html","id":null,"dir":"Reference","previous_headings":"","what":"Radar plots for tidal creek indicators — show_tdlcrkradar","title":"Radar plots for tidal creek indicators — show_tdlcrkradar","text":"Radar plots tidal creek indicators","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkradar.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Radar plots for tidal creek indicators — show_tdlcrkradar","text":"","code":"show_tdlcrkradar( id, cntdat, col = \"#338080E6\", ptsz = 1, lbsz = 0.8, valsz = 1, brdwd = 5 )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkradar.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Radar plots for tidal creek indicators — show_tdlcrkradar","text":"id numeric indicating id number tidal creek plot cntdat output anlz_tdlcrkindic col color input polygon line portions ptsz numeric size points lbsz numeric size text labels valsz numeric size numeric value labels brdwd numeric polygon border width","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkradar.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Radar plots for tidal creek indicators — show_tdlcrkradar","text":"radar plot","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkradar.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Radar plots for tidal creek indicators — show_tdlcrkradar","text":"See details anlz_tdlcrkindic explanation indicators Internal code borrowed heavily radarchart function fmsb package.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_tdlcrkradar.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Radar plots for tidal creek indicators — show_tdlcrkradar","text":"","code":"cntdat <- anlz_tdlcrkindic(tidalcreeks, iwrraw, yr = 2023, radar = TRUE) set.seed(123) id <- sample(unique(cntdat$id), 1) show_tdlcrkradar(id, cntdat)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_thrplot.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot annual water quality values, targets, and thresholds for a segment — show_thrplot","title":"Plot annual water quality values, targets, and thresholds for a segment — show_thrplot","text":"Plot annual water quality values, targets, thresholds bay segment","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_thrplot.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot annual water quality values, targets, and thresholds for a segment — show_thrplot","text":"","code":"show_thrplot( epcdata, bay_segment = c(\"OTB\", \"HB\", \"MTB\", \"LTB\"), thr = c(\"chla\", \"la\"), trgs = NULL, yrrng = c(1975, 2023), family = NA, labelexp = TRUE, txtlab = TRUE, thrs = FALSE, partialyr = FALSE )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_thrplot.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot annual water quality values, targets, and thresholds for a segment — show_thrplot","text":"epcdata data frame epc data returned read_importwq bay_segment chr string bay segment, one \"OTB\", \"HB\", \"MTB\", \"LTB\" thr chr string indicating water quality value appropriate target/threshold plot, one \"chl\" chlorophyll \"la\" light availability trgs optional data.frame annual bay segment water quality targets/thresholds, defaults targets yrrng numeric vector indicating min, max years include family optional chr string indicating font family text labels labelexp logical indicating y axis target labels plotted expressions, default TRUE txtlab logical indicating text label target value shown plot thrs logical indicating reference lines shown regulatory threshold partialyr logical indicating incomplete annual data recent year approximated five year monthly averages parameter","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_thrplot.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot annual water quality values, targets, and thresholds for a segment — show_thrplot","text":"ggplot object","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_thrplot.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot annual water quality values, targets, and thresholds for a segment — show_thrplot","text":"","code":"show_thrplot(epcdata, bay_segment = 'OTB', thr = 'chl')"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transect.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot results for a seagrass transect by time and location — show_transect","title":"Plot results for a seagrass transect by time and location — show_transect","text":"Plot results seagrass transect time location","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transect.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot results for a seagrass transect by time and location — show_transect","text":"","code":"show_transect( transect, site, species = 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plot pixels, applies plotly = TRUE height numeric height plot pixels, applies plotly = TRUE sppcol character vector alternative colors use species, must length six","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transect.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot results for a seagrass transect by time and location — show_transect","text":"ggplot object","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transect.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Plot results for a seagrass transect by time and location — show_transect","text":"sites along transect surveyed shown plot, including selected species found. latter colored grey hollow points. Species options include Halodule, Syringodium, Thalassia, Halophila, Ruppia, Caulerpa (attached macroalgae), /Dapis (cyanobacteria). Drift attached macroalgae cyanobacteria (Dapis) estimates may accurate prior 2021. Note plotly = TRUE, size legend shown.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transect.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot results for a seagrass transect by time and location — show_transect","text":"","code":"if (FALSE) { transect <- read_transect() } # one species show_transect(transect, site = 'S3T10', species = 'Halodule', varplo = 'Abundance') # multiple species, one plot show_transect(transect, site = 'S3T10', species = c('Halodule', 'Syringodium', 'Thalassia', 'Halophila', 'Ruppia', 'Caulerpa', 'Dapis'), varplo = 'Abundance') # multiple species, multiple plots show_transect(transect, site = 'S3T10', species = c('Halodule', 'Syringodium', 'Thalassia', 'Halophila', 'Ruppia', 'Caulerpa', 'Dapis'), varplo = 'Abundance', facet = TRUE)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transectavespp.html","id":null,"dir":"Reference","previous_headings":"","what":"Show annual averages of seagrass frequency occurrence by bay segments, year, and species — show_transectavespp","title":"Show annual averages of seagrass frequency occurrence by bay segments, year, and species — show_transectavespp","text":"Show annual averages seagrass frequency occurrence bay segments, year, species","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transectavespp.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Show annual averages of seagrass frequency occurrence by bay segments, year, and species — show_transectavespp","text":"","code":"show_transectavespp( transectocc, bay_segment = c(\"OTB\", \"HB\", \"MTB\", \"LTB\", \"BCB\"), yrrng = c(1998, 2023), species = c(\"Halodule\", \"Syringodium\", \"Thalassia\", \"Halophila\", \"Ruppia\", \"Caulerpa\", \"Dapis\"), total = TRUE, alph = 1, family = NA, plotly = FALSE, asreact = FALSE, width = NULL, height = NULL, sppcol = NULL )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transectavespp.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Show annual averages of seagrass frequency occurrence by bay segments, year, and species — show_transectavespp","text":"transectocc data frame returned anlz_transectocc bay_segment chr string bay segment, one many \"OTB\", \"HB\", \"MTB\", \"LTB\", \"BCB\" yrrng numeric indicating year ranges evaluate species chr string species summarize, one many \"Halodule\", \"Syringodium\", \"Thalassia\", \"Ruppia\", \"Halophila\", \"Caulerpa\", \"Dapis\" total logical indicating total frequency occurrence species also returned, applies asreact = FALSE alph numeric indicating alpha value score category colors family optional chr string indicating font family text labels plotly logical matrix created using plotly asreact logical reactable table returned instead plot width numeric width plot pixels, applies plotly = TRUE height numeric height plot pixels, applies plotly = TRUE sppcol character vector alternative colors use species, must length six","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transectavespp.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Show annual averages of seagrass frequency occurrence by bay segments, year, and species — show_transectavespp","text":"asreact = F, ggplot plotly (plotly = T) object returned showing trends time species selected bay segments. asreact = T, reactable table showing results year, segment, species returned.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transectavespp.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Show annual averages of seagrass frequency occurrence by bay segments, year, and species — show_transectavespp","text":"Results based averages across species date transect bay segment. Drift attached macroalgae (e.g., Caulerpa) cyanobacteria (Dapis) estimates may accurate prior 2021.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transectavespp.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Show annual averages of seagrass frequency occurrence by bay segments, year, and species — show_transectavespp","text":"plot representation figure 2 Johansson, R. (2016) Seagrass Transect Monitoring Tampa Bay: Summary Findings 1997 2015, Technical report #08-16, Tampa Bay Estuary Program, St. Petersburg, Florida. table representation table 2, p. 163 Yarbro, L. ., P. R. Carlson, Jr., eds. 2016. Seagrass Integrated Mapping Monitoring Program: Mapping Monitoring Report . 2. Fish Wildlife Research Institute Technical Report TR-17 version 2. vi + 281 p.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transectavespp.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Show annual averages of seagrass frequency occurrence by bay segments, year, and species — show_transectavespp","text":"","code":"if (FALSE) { transect <- read_transect() } transectocc <- anlz_transectocc(transect) show_transectavespp(transectocc)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transectmatrix.html","id":null,"dir":"Reference","previous_headings":"","what":"Show matrix of seagrass frequency occurrence by bay segments and year — show_transectmatrix","title":"Show matrix of seagrass frequency occurrence by bay segments and year — show_transectmatrix","text":"Show matrix seagrass frequency occurrence bay segments year","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transectmatrix.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Show matrix of seagrass frequency occurrence by bay segments and year — show_transectmatrix","text":"","code":"show_transectmatrix( transectocc, bay_segment = c(\"OTB\", \"HB\", \"MTB\", \"LTB\", \"BCB\"), total = TRUE, neutral = FALSE, yrrng = c(1998, 2023), alph = 1, txtsz = 3, family = NA, rev = FALSE, position = \"top\", plotly = FALSE, width = NULL, height = NULL )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transectmatrix.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Show matrix of seagrass frequency occurrence by bay segments and year — show_transectmatrix","text":"transectocc data frame returned anlz_transectocc bay_segment chr string bay segment, one many \"HB\", \"OTB\", \"MTB\", \"LTB\", \"TCB\", \"MR\", \"BCB\" total logical indicating average frequency occurrence calculated entire bay across segments neutral logical indicating neutral continuous color scheme used yrrng numeric indicating year ranges evaluate alph numeric indicating alpha value score category colors txtsz numeric size text plot family optional chr string indicating font family text labels rev logical factor levels bay segments reversed position chr string location bay segment labels, default top, passed scale_x_discrete plotly logical matrix created using plotly width numeric width plot pixels, applies plotly = TRUE height numeric height plot pixels, applies plotly = TRUE","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transectmatrix.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Show matrix of seagrass frequency occurrence by bay segments and year — show_transectmatrix","text":"ggplot object showing trends time bay segment plotly = FALSE, otherwise plotly object","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transectmatrix.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Show matrix of seagrass frequency occurrence by bay segments and year — show_transectmatrix","text":"Results based averages across species date transect bay segment color scheme based arbitrary breaks 25, 50, 75 percent frequency occurrence. necessarily translate ecological breakpoints. Use neutral = TRUE use neutral continuous color palette.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transectmatrix.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Show matrix of seagrass frequency occurrence by bay segments and year — show_transectmatrix","text":"plot representation Table 1 R. Johansson (2016) Seagrass Transect Monitoring Tampa Bay: Summary Findings 1997 2015, Technical report #08-16, Tampa Bay Estuary Program, St. Petersburg, Florida.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transectmatrix.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Show matrix of seagrass frequency occurrence by bay segments and year — show_transectmatrix","text":"","code":"if (FALSE) { transect <- read_transect() } transectocc <- anlz_transectocc(transect) show_transectmatrix(transectocc)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transectsum.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot frequency occurrence for a seagrass transect by time for all species — show_transectsum","title":"Plot frequency occurrence for a seagrass transect by time for all species — show_transectsum","text":"Plot frequency occurrence seagrass transect time species","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transectsum.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot frequency occurrence for a seagrass transect by time for all species — show_transectsum","text":"","code":"show_transectsum( transectocc, site, species = c(\"Halodule\", \"Syringodium\", \"Thalassia\", \"Halophila\", \"Ruppia\", \"Caulerpa\", \"Dapis\"), yrrng = c(1998, 2023), abund = FALSE, sppcol = NULL )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transectsum.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot frequency occurrence for a seagrass transect by time for all species — show_transectsum","text":"transectocc data frame returned anlz_transectocc site chr string indicating site results plot species chr string indicating species plot yrrng numeric indicating year ranges evaluate abund logical indicating abundance averages plotted instead frequency occurrence sppcol character vector alternative colors use species, must length six","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transectsum.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot frequency occurrence for a seagrass transect by time for all species — show_transectsum","text":"plotly object","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transectsum.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Plot frequency occurrence for a seagrass transect by time for all species — show_transectsum","text":"plot provides quick visual assessment frequency occurrence abundance multiple species changed time selected transect. Drift attached macroalgae (e.g., Caulerpa) cyanobacteria (Dapis) estimates may accurate prior 2021.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transectsum.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot frequency occurrence for a seagrass transect by time for all species — show_transectsum","text":"","code":"if (FALSE) { transect <- read_transect() } transectocc <- anlz_transectocc(transect) show_transectsum(transectocc, site = 'S3T10') {\"x\":{\"visdat\":{\"1a5d414b807a\":[\"function () 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a colorized table for chlorophyll or light attenuation exceedances — show_wqmatrix","title":"Create a colorized table for chlorophyll or light attenuation exceedances — show_wqmatrix","text":"Create colorized table chlorophyll light attenuation exceedances","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_wqmatrix.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Create a colorized table for chlorophyll or light attenuation exceedances — show_wqmatrix","text":"","code":"show_wqmatrix( epcdata, param = c(\"chla\", \"la\"), txtsz = 3, trgs = NULL, yrrng = c(1975, 2023), bay_segment = c(\"OTB\", \"HB\", \"MTB\", \"LTB\"), asreact = FALSE, nrows = 10, abbrev = FALSE, family = NA, plotly = FALSE, partialyr = FALSE, width = NULL, height = NULL )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_wqmatrix.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Create a colorized table for chlorophyll or light attenuation exceedances — show_wqmatrix","text":"epcdata data frame epc data returned read_importwq param chr string parameter plot, one \"chla\" chlorophyll \"la\" light attenuation txtsz numeric size text plot, applies tab = FALSE trgs optional data.frame annual bay segment water quality targets, defaults targets yrrng numeric vector indicating min, max years include bay_segment chr string bay segments include, one \"OTB\", \"HB\", \"MTB\", \"LTB\" asreact logical indicating reactable object returned nrows asreact = TRUE, numeric specifying number rows table abbrev logical indicating text labels plot abbreviated first letter family optional chr string indicating font family text labels plotly logical matrix created using plotly partialyr logical indicating incomplete annual data recent year approximated five year monthly averages parameter width numeric width plot pixels, applies plotly = TRUE height numeric height plot pixels, applies plotly = TRUE","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_wqmatrix.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Create a colorized table for chlorophyll or light attenuation exceedances — show_wqmatrix","text":"static ggplot object returned asreact = FALSE, otherwise reactable table returned","code":""},{"path":[]},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_wqmatrix.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Create a colorized table for chlorophyll or light attenuation exceedances — show_wqmatrix","text":"","code":"show_wqmatrix(epcdata)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/stations.html","id":null,"dir":"Reference","previous_headings":"","what":"Bay stations by segment — stations","title":"Bay stations by segment — stations","text":"Bay stations segment","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/stations.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Bay stations by segment — stations","text":"","code":"stations"},{"path":"https://tbep-tech.github.io/tbeptools/reference/stations.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Bay stations by segment — stations","text":"data frame 45 rows 4 variables: bay_segment chr epchc_station num Latitude num Longitude num","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/subtacres.html","id":null,"dir":"Reference","previous_headings":"","what":"Tampa Bay subtidal cover — subtacres","title":"Tampa Bay subtidal cover — subtacres","text":"Tampa Bay subtidal cover Habitat Master Plan reporting","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/subtacres.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tampa Bay subtidal cover — subtacres","text":"","code":"subtacres"},{"path":"https://tbep-tech.github.io/tbeptools/reference/subtacres.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Tampa Bay subtidal cover — subtacres","text":"data frame","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/subtacres.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tampa Bay subtidal cover — subtacres","text":"","code":"if (FALSE) { load(url(\"https://github.com/tbep-tech/hmpu-workflow/raw/master/data/subtacres.RData\")) save(subtacres, file = 'data/subtacres.RData', compress = 'xz') }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/swfwmdtbseg.html","id":null,"dir":"Reference","previous_headings":"","what":"Spatial data object of SWFWMD Tampa Bay segments — swfwmdtbseg","title":"Spatial data object of SWFWMD Tampa Bay segments — swfwmdtbseg","text":"Spatial data object SWFWMD Tampa Bay segments","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/swfwmdtbseg.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Spatial data object of SWFWMD Tampa Bay segments — swfwmdtbseg","text":"","code":"swfwmdtbseg"},{"path":"https://tbep-tech.github.io/tbeptools/reference/swfwmdtbseg.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Spatial data object of SWFWMD Tampa Bay segments — swfwmdtbseg","text":"simple features sf object (MULTIPOLYGON) 7 features 1 fields, +proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/swfwmdtbseg.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Spatial data object of SWFWMD Tampa Bay segments — swfwmdtbseg","text":"","code":"if (FALSE) { library(sf) library(dplyr) levs <- c('oldTampaBay', 'hillsboroughBay', 'middleTampaBay', 'lowerTampaBay', 'bocaCiegaBay', 'terraCieaBay', 'manateeRiver') labs <- c('Old Tampa Bay', 'Hillsborough Bay', 'Middle Tampa Bay', 'Lower Tampa Bay', 'Boca Ciega Bay', 'Terra Ceia Bay', 'Manatee River') swfwmdtbseg <- st_read( dsn = 'T:/05_GIS/SWFWMD/Seagrass/2022_Seagrass/DraftMaps2022_1130.gdb', layer = 'suncoastSeagrassSegments' ) %>% filter(waterbodyName %in% levs) %>% mutate( waterbodyName = factor(waterbodyName, levels = levs, labels = labs) ) %>% select(segment = waterbodyName) %>% st_transform(crs = 4326) save(swfwmdtbseg, file = 'data/swfwmdtbseg.RData', compress = 'xz') }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/targets.html","id":null,"dir":"Reference","previous_headings":"","what":"Bay segment targets — targets","title":"Bay segment targets — targets","text":"Bay segment specific management targets including low high magnitude exceedance thresholds","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/targets.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Bay segment targets — targets","text":"","code":"targets"},{"path":"https://tbep-tech.github.io/tbeptools/reference/targets.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Bay segment targets — targets","text":"data frame 4 rows 8 variables: bay_segment chr name chr chla_target num chla_smallex num chla_thresh num la_target num la_smallex num la_thresh num","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/targets.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Bay segment targets — targets","text":"","code":"if (FALSE) { targets <- structure(list( bay_segment = c(\"OTB\", \"HB\", \"MTB\", \"LTB\", \"BCBN\", \"BCBS\", \"TCB\", \"MR\", \"RALTB\"), name = c(\"Old Tampa Bay\", \"Hillsborough Bay\", \"Middle Tampa Bay\", \"Lower Tampa Bay\", \"Boca Ciega Bay North\", \"Boca Ciega Bay South\", \"Terra Ceia Bay\", \"Manatee River\", \"Remainder Lower Tampa Bay\"), chla_target = c(8.5, 13.2, 7.4, 4.6, 7.7, 6.1, 7.5, 7.3, NaN), chla_smallex = c(8.9, 14.1, 7.9, 4.8, NaN, NaN, NaN, NaN, NaN), chla_thresh = c(9.3, 15, 8.5, 5.1, 8.3, 6.3, 8.7, 8.8, 5.1), la_target = c(0.83, 1.58, 0.83, 0.63, NaN, NaN, NaN, NaN, NaN), la_smallex = c(0.86, 1.63, 0.87, 0.66, NaN, NaN, NaN, NaN, NaN), la_thresh = c(0.88, 1.67, 0.91, 0.68, NaN, NaN, NaN, NaN, NaN)), class = \"data.frame\", row.names = c(NA, -9L) ) save(targets, file = 'data/targets.RData') }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbniref.html","id":null,"dir":"Reference","previous_headings":"","what":"Reference conditions for Tampa Bay Nekton Index metrics — tbniref","title":"Reference conditions for Tampa Bay Nekton Index metrics — tbniref","text":"Reference conditions Tampa Bay Nekton Index metrics","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbniref.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Reference conditions for Tampa Bay Nekton Index metrics — tbniref","text":"","code":"tbniref"},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbniref.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Reference conditions for Tampa Bay Nekton Index metrics — tbniref","text":"data frame 16 rows 12 variables: bay_segment chr Season chr NumTaxa_P5 num NumTaxa_P95 num BenthicTaxa_P5 num BenthicTaxa_P95 num TaxaSelect_P5 num TaxaSelect_P95 num NumGuilds_P5 num NumGuilds_P95 num Shannon_P5 num Shannon_P95 num","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbniref.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Reference conditions for Tampa Bay Nekton Index metrics — tbniref","text":"","code":"if (FALSE) { library(tbeptools) tbniref <- anlz_tbnimet(fimdata) %>% dplyr::filter(between(Year, 1998, 2015)) %>% dplyr::select(Season, bay_segment, NumTaxa, BenthicTaxa, TaxaSelect, NumGuilds, Shannon) %>% dplyr::group_by(bay_segment, Season) %>% dplyr::summarize(NumTaxa_P5 = round(quantile(NumTaxa, probs = 0.05)), NumTaxa_P95 = round(quantile(NumTaxa, probs = 0.95)), BenthicTaxa_P5 = round(quantile(BenthicTaxa, probs = 0.05)), BenthicTaxa_P95 = round(quantile(BenthicTaxa, probs = 0.95)), TaxaSelect_P5 = round(quantile(TaxaSelect, probs = 0.05)), TaxaSelect_P95 = round(quantile(TaxaSelect, probs = 0.95)), NumGuilds_P5 = round(quantile(NumGuilds, probs = 0.05)), NumGuilds_P95 = round(quantile(NumGuilds, probs = 0.95)), Shannon_P5 = quantile(Shannon, probs = 0.05), Shannon_P95 = quantile(Shannon, probs = 0.95)) save(tbniref, file = 'data/tbniref.RData', compress = 'xz') }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbnispp.html","id":null,"dir":"Reference","previous_headings":"","what":"Reference table for Tampa Bay Nekton Index species classifications — tbnispp","title":"Reference table for Tampa Bay Nekton Index species classifications — tbnispp","text":"Reference table Tampa Bay Nekton Index species classifications","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbnispp.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Reference table for Tampa Bay Nekton Index species classifications — tbnispp","text":"","code":"tbnispp"},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbnispp.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Reference table for Tampa Bay Nekton Index species classifications — tbnispp","text":"data frame 196 rows 9 variables: NODCCODE chr ScientificName chr Include_TB_Index chr Hab_Cat chr Est_Cat chr Est_Use chr Feeding_Cat chr Feeding_Guild chr Selected_Taxa chr","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbnispp.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Reference table for Tampa Bay Nekton Index species classifications — tbnispp","text":"","code":"if (FALSE) { library(dplyr) # import and clean tbnispp <- read.csv('../tbni-proc/data/TBIndex_spp_codes.csv', header = TRUE, stringsAsFactors = FALSE) %>% mutate( NODCCODE = as.character(NODCCODE), NODCCODE = case_when(NODCCODE == \"9.998e+09\" ~ \"9998000000\", TRUE ~ NODCCODE) ) save(tbnispp, file = 'data/tbnispp.RData', compress = 'xz') }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbseg.html","id":null,"dir":"Reference","previous_headings":"","what":"Spatial data object of Tampa Bay segments — tbseg","title":"Spatial data object of Tampa Bay segments — tbseg","text":"Note boundaries used formal analysis used visual aids mapping.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbseg.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Spatial data object of Tampa Bay segments — tbseg","text":"","code":"tbseg"},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbseg.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Spatial data object of Tampa Bay segments — tbseg","text":"simple features sf object (POLYGON) 4 features 2 fields, +proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs long_name chr bay_segment chr","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbseg.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Spatial data object of Tampa Bay segments — tbseg","text":"Spatial data object Tampa Bay segments","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbseg.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Spatial data object of Tampa Bay segments — tbseg","text":"","code":"library(sf) #> Linking to GEOS 3.10.2, GDAL 3.4.1, PROJ 8.2.1; sf_use_s2() is TRUE plot(st_geometry(tbseg))"},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbseglines.html","id":null,"dir":"Reference","previous_headings":"","what":"Spatial data object of lines defining major Tampa Bay segments — tbseglines","title":"Spatial data object of lines defining major Tampa Bay segments — tbseglines","text":"Spatial data object lines defining major Tampa Bay segments","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbseglines.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Spatial data object of lines defining major Tampa Bay segments — tbseglines","text":"","code":"tbseglines"},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbseglines.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Spatial data object of lines defining major Tampa Bay segments — tbseglines","text":"simple features sf object (LINESTRING) 3 features 1 field, +proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbseglines.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Spatial data object of lines defining major Tampa Bay segments — tbseglines","text":"","code":"library(sf) plot(st_geometry(tbseglines))"},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbsegshed.html","id":null,"dir":"Reference","previous_headings":"","what":"Spatial data object of Tampa Bay segments plus watersheds — tbsegshed","title":"Spatial data object of Tampa Bay segments plus watersheds — tbsegshed","text":"Spatial data object Tampa Bay segments plus waterhseds","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbsegshed.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Spatial data object of Tampa Bay segments plus watersheds — tbsegshed","text":"","code":"tbsegshed"},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbsegshed.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Spatial data object of Tampa Bay segments plus watersheds — tbsegshed","text":"simple features sf object (POLYGON) 7 features 2 fields, +proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs long_name chr bay_segment chr","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbsegshed.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Spatial data object of Tampa Bay segments plus watersheds — tbsegshed","text":"","code":"library(sf) plot(st_geometry(tbsegshed))"},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbshed.html","id":null,"dir":"Reference","previous_headings":"","what":"Spatial data object of Tampa Bay watershed — tbshed","title":"Spatial data object of Tampa Bay watershed — tbshed","text":"Spatial data object Tampa Bay watershed, includes bay proper","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbshed.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Spatial data object of Tampa Bay watershed — tbshed","text":"","code":"tbshed"},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbshed.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Spatial data object of Tampa Bay watershed — tbshed","text":"simple features sf object (POLYGON) 1 feature 0 fields, +proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/tbshed.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Spatial data object of Tampa Bay watershed — tbshed","text":"","code":"library(sf) if (FALSE) { library(dplyr) tbshed <- st_read('T:/05_GIS/BOUNDARIES/TBEP_Watershed_Correct_Projection.shp') %>% select(-Id, -Name, -Area_m, -Hectares) %>% st_transform(crs = 4326) save(tbshed, file = 'data/tbshed.RData', compress = 'xz') } plot(st_geometry(tbshed))"},{"path":"https://tbep-tech.github.io/tbeptools/reference/tidalcreeks.html","id":null,"dir":"Reference","previous_headings":"","what":"Spatial data object of tidal creeks in Impaired Waters Rule, Run 65 — tidalcreeks","title":"Spatial data object of tidal creeks in Impaired Waters Rule, Run 65 — tidalcreeks","text":"Spatial data object tidal creeks Impaired Waters Rule, Run 65","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/tidalcreeks.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Spatial data object of tidal creeks in Impaired Waters Rule, Run 65 — tidalcreeks","text":"","code":"tidalcreeks"},{"path":"https://tbep-tech.github.io/tbeptools/reference/tidalcreeks.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Spatial data object of tidal creeks in Impaired Waters Rule, Run 65 — tidalcreeks","text":"simple features sf object (MULTILINESTRING) 615 features fields, +proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs id num wbid chr JEI chr class chr name chr Creek_Length_m num","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/tidalcreeks.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Spatial data object of tidal creeks in Impaired Waters Rule, Run 65 — tidalcreeks","text":"File created using workflow , example old Run 61.","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/tidalcreeks.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Spatial data object of tidal creeks in Impaired Waters Rule, Run 65 — tidalcreeks","text":"","code":"if (FALSE) { library(sf) library(dplyr) prj <- 4326 # create sf object of creek population, join with creek length data tidalcreeks <- st_read( dsn = '../../02_DOCUMENTS/tidal_creeks/TidalCreek_ALL_Line_WBID61.shp', drivers = 'ESRI Shapefile' ) %>% st_transform(crs = prj) %>% mutate( id = 1:nrow(.) ) %>% select(id, name = Name, JEI = CreekID, wbid = WBID, class = CLASS, Creek_Length_m = Total_m) # save save(tidalcreeks, file = 'data/tidalcreeks.RData', compress = 'xz') }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/tidaltargets.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidal creek nitrogen targets — tidaltargets","title":"Tidal creek nitrogen targets — tidaltargets","text":"Tidal creek nitrogen targets","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/tidaltargets.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidal creek nitrogen targets — tidaltargets","text":"","code":"tidaltargets"},{"path":"https://tbep-tech.github.io/tbeptools/reference/tidaltargets.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Tidal creek nitrogen targets — tidaltargets","text":"data frame 2 rows 4 variables: region chr prioritize num investigate num caution num","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/transect.html","id":null,"dir":"Reference","previous_headings":"","what":"Seagrass transect data for Tampa Bay current as of 04122024 — transect","title":"Seagrass transect data for Tampa Bay current as of 04122024 — transect","text":"Seagrass transect data Tampa Bay current 04122024","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/transect.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Seagrass transect data for Tampa Bay current as of 04122024 — transect","text":"","code":"transect"},{"path":"https://tbep-tech.github.io/tbeptools/reference/transect.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Seagrass transect data for Tampa Bay current as of 04122024 — transect","text":"data frame 152580 rows 11 variables: Crew chr MonitoringAgency chr Date Date Transect chr Site chr Depth int Savspecies chr SeagrassEdge num var chr aveval num sdval num","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/transect.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Seagrass transect data for Tampa Bay current as of 04122024 — transect","text":"","code":"if (FALSE) { transect <- read_transect() save(transect, file = 'data/transect.RData', compress = 'xz') }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/trnlns.html","id":null,"dir":"Reference","previous_headings":"","what":"Seagrass transect locations — trnlns","title":"Seagrass transect locations — trnlns","text":"Seagrass transect locations","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/trnlns.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Seagrass transect locations — trnlns","text":"","code":"trnlns"},{"path":"https://tbep-tech.github.io/tbeptools/reference/trnlns.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Seagrass transect locations — trnlns","text":"sf LINESTRING object","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/trnlns.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Seagrass transect locations — trnlns","text":"","code":"if (FALSE) { library(sf) library(dplyr) trnlns <- st_read('T:/05_GIS/SEAGRASS_TRANSECTS/transect_routes.shp') %>% st_transform(crs = 4326) %>% dplyr::filter(!as.character(Site) %in% c('S8T1', 'S8T2', 'S8T3', 'S3T2')) %>% dplyr::mutate_if(is.factor, as.character) %>% dplyr::filter(Site %in% trnpts$TRAN_ID) # add bearing, positive counter-clockwise from east bearing <- lapply(trnlns$geometry, function(x) geosphere::bearing(x[, c(1:2)])[[1]]) %>% unlist() trnlns$bearing <- bearing save(trnlns, file = 'data/trnlns.RData', compress = 'xz') }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/trnpts.html","id":null,"dir":"Reference","previous_headings":"","what":"Seagrass transect starting locations — trnpts","title":"Seagrass transect starting locations — trnpts","text":"Seagrass transect starting locations","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/trnpts.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Seagrass transect starting locations — trnpts","text":"","code":"trnpts"},{"path":"https://tbep-tech.github.io/tbeptools/reference/trnpts.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Seagrass transect starting locations — trnpts","text":"sf POINT object","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/trnpts.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Seagrass transect starting locations — trnpts","text":"","code":"if (FALSE) { library(sf) library(dplyr) library(tbeptools) trnpts <- st_read('T:/05_GIS/SEAGRASS_TRANSECTS/TransectBasics2019.shp') %>% st_transform(crs = 4326) %>% dplyr::rename(MonAgency = 'MON_AGENCY') %>% dplyr::filter(!as.character(TRAN_ID) %in% c('S8T1', 'S8T2', 'S8T3', 'S3T2')) # s4t10 is slightly outside boundary for lower tampa bay s4t10 <- trnpts %>% dplyr::filter(TRAN_ID %in% 'S4T10') %>% dplyr::mutate(bay_segment = 'LTB') trnpts <- trnpts %>% sf::st_intersection(sf::st_make_valid(tbsegshed)) %>% dplyr::select(-long_name) %>% dplyr::mutate_if(is.factor, as.character) %>% dplyr::bind_rows(s4t10) save(trnpts, file = 'data/trnpts.RData', compress = 'xz') }"},{"path":"https://tbep-tech.github.io/tbeptools/reference/util_fiblevs.html","id":null,"dir":"Reference","previous_headings":"","what":"A list of Fecal Indicator Bacteria (FIB) category breakpoints and labels — util_fiblevs","title":"A list of Fecal Indicator Bacteria (FIB) category breakpoints and labels — util_fiblevs","text":"list Fecal Indicator Bacteria (FIB) category breakpoints labels","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/util_fiblevs.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"A list of Fecal Indicator Bacteria (FIB) category breakpoints and labels — util_fiblevs","text":"","code":"util_fiblevs()"},{"path":"https://tbep-tech.github.io/tbeptools/reference/util_fiblevs.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"A list of Fecal Indicator Bacteria (FIB) category breakpoints and labels — util_fiblevs","text":"list showing cut points labels FIB categories","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/util_fiblevs.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"A list of Fecal Indicator Bacteria (FIB) category breakpoints and labels — util_fiblevs","text":"","code":"util_fiblevs() #> $ecolilev #> [1] -Inf 126 410 1000 Inf #> #> $ecolilbs #> [1] \"< 126\" \"126 - 409\" \"410 - 999\" \"> 999\" #> #> $ecoccilev #> [1] -Inf 35 130 1000 Inf #> #> $ecoccilbs #> [1] \"< 35\" \"35 - 129\" \"130 - 999\" \"> 999\" #>"},{"path":"https://tbep-tech.github.io/tbeptools/reference/util_html.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert character string to html class — util_html","title":"Convert character string to html class — util_html","text":"Convert character string html class","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/util_html.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert character string to html class — util_html","text":"","code":"util_html(text)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/util_html.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert character string to html class — util_html","text":"text character string input","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/util_html.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert character string to html class — util_html","text":"input character string html class","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/util_html.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Convert character string to html class — util_html","text":"Adapted HTML","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/util_html.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Convert character string to html class — util_html","text":"","code":"util_html('abd') #> abd"},{"path":"https://tbep-tech.github.io/tbeptools/reference/util_map.html","id":null,"dir":"Reference","previous_headings":"","what":"Create an empty leaflet map from sf input — util_map","title":"Create an empty leaflet map from sf input — util_map","text":"Create empty leaflet map sf input","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/util_map.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Create an empty leaflet map from sf input — util_map","text":"","code":"util_map(tomap, minimap = \"bottomleft\")"},{"path":"https://tbep-tech.github.io/tbeptools/reference/util_map.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Create an empty leaflet map from sf input — util_map","text":"tomap sf input object minimap character string indicating location minimap, use minimap = NULL suppress","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/util_map.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Create an empty leaflet map from sf input — util_map","text":"leaflet object optional minimap ESRI provider tiles","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/util_map.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Create an empty leaflet map from sf input — util_map","text":"","code":"tomap <- tibble::tibble( lon = -82.6365, lat = 27.75822 ) tomap <- sf::st_as_sf(tomap, coords = c('lon', 'lat'), crs = 4326) util_map(tomap) {\"x\":{\"options\":{\"crs\":{\"crsClass\":\"L.CRS.EPSG3857\",\"code\":null,\"proj4def\":null,\"projectedBounds\":null,\"options\":{}}},\"fitBounds\":[27.75822,-82.6365,27.75822,-82.6365,[]],\"calls\":[{\"method\":\"addProviderTiles\",\"args\":[\"Esri.WorldGrayCanvas\",null,\"Esri.WorldGrayCanvas\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.NatGeoWorldMap\",null,\"Esri.NatGeoWorldMap\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.OceanBasemap\",null,\"Esri.OceanBasemap\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.WorldPhysical\",null,\"Esri.WorldPhysical\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.WorldShadedRelief\",null,\"Esri.WorldShadedRelief\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.WorldTerrain\",null,\"Esri.WorldTerrain\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.WorldImagery\",null,\"Esri.WorldImagery\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.WorldTopoMap\",null,\"Esri.WorldTopoMap\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.DeLorme\",null,\"Esri.DeLorme\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri.WorldStreetMap\",null,\"Esri.WorldStreetMap\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addProviderTiles\",\"args\":[\"Esri\",null,\"Esri\",{\"errorTileUrl\":\"\",\"noWrap\":false,\"detectRetina\":false}]},{\"method\":\"addLayersControl\",\"args\":[[\"Esri.WorldGrayCanvas\",\"Esri.NatGeoWorldMap\",\"Esri.OceanBasemap\",\"Esri.WorldPhysical\",\"Esri.WorldShadedRelief\",\"Esri.WorldTerrain\",\"Esri.WorldImagery\",\"Esri.WorldTopoMap\",\"Esri.DeLorme\",\"Esri.WorldStreetMap\",\"Esri\"],[],{\"collapsed\":true,\"autoZIndex\":true,\"position\":\"topleft\"}]},{\"method\":\"addMiniMap\",\"args\":[null,\"Esri.WorldGrayCanvas\",\"bottomleft\",150,150,19,19,-5,false,false,false,true,false,true,{\"color\":\"#ff7800\",\"weight\":1,\"clickable\":false},{\"color\":\"#000000\",\"weight\":1,\"clickable\":false,\"opacity\":0,\"fillOpacity\":0},{\"hideText\":\"Hide MiniMap\",\"showText\":\"Show MiniMap\"},[]]}]},\"evals\":[],\"jsHooks\":{\"render\":[{\"code\":\"function(el, x, data) {\\n return (\\n function(el, x) {\\n var myMap = this;\\n myMap.on('baselayerchange',\\n function (e) {\\n myMap.minimap.changeLayer(L.tileLayer.provider(e.name));\\n })\\n }).call(this.getMap(), el, x, data);\\n}\",\"data\":null}]}}"},{"path":"https://tbep-tech.github.io/tbeptools/reference/util_orgin.html","id":null,"dir":"Reference","previous_headings":"","what":"Get organization name from organization identifier in USEPA Water Quality Portal — util_orgin","title":"Get organization name from organization identifier in USEPA Water Quality Portal — util_orgin","text":"Get organization name organization identifier USEPA Water Quality Portal","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/util_orgin.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get organization name from organization identifier in USEPA Water Quality Portal — util_orgin","text":"","code":"util_orgin(org, stanm = FALSE)"},{"path":"https://tbep-tech.github.io/tbeptools/reference/util_orgin.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get organization name from organization identifier in USEPA Water Quality Portal — util_orgin","text":"org chr string indicating organization identifier, see read_importwqp valid entries stanm logical indicating character string column name specific organization returned","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/util_orgin.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get organization name from organization identifier in USEPA Water Quality Portal — util_orgin","text":"character string organization name corresponds organization identifier column name station identifier specific organization stanm = TRUE","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/util_orgin.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get organization name from organization identifier in USEPA Water Quality Portal — util_orgin","text":"","code":"util_orgin('21FLHILL_WQX') #> [1] \"Hillsborough\" util_orgin('21FLPASC_WQX', stanm = TRUE) #> [1] \"pasco_station\""}]