From 52b7b5e87ab497afa7817d43aee14672f712dadd Mon Sep 17 00:00:00 2001 From: fawda123 Date: Mon, 12 Feb 2024 14:03:09 +0000 Subject: [PATCH] =?UTF-8?q?Deploying=20to=20gh-pages=20from=20@=20tbep-tec?= =?UTF-8?q?h/tbeptools@11894ae87f9aff651b28bb7b705d0ce08303c177=20?= =?UTF-8?q?=F0=9F=9A=80?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- apple-touch-icon-120x120.png | Bin 14412 -> 14412 bytes apple-touch-icon-152x152.png | Bin 21250 -> 21250 bytes apple-touch-icon-180x180.png | Bin 28277 -> 28277 bytes apple-touch-icon-60x60.png | Bin 4822 -> 4822 bytes apple-touch-icon-76x76.png | Bin 6929 -> 6929 bytes apple-touch-icon.png | Bin 28277 -> 28277 bytes articles/fib.html | 22 +- articles/habitatmasterplan.html | 2 +- articles/intro.html | 202 +++++++++--------- .../figure-html/unnamed-chunk-17-1.png | Bin 134002 -> 133021 bytes .../figure-html/unnamed-chunk-17-2.png | Bin 138139 -> 138781 bytes .../figure-html/unnamed-chunk-18-1.png | Bin 85791 -> 86133 bytes .../figure-html/unnamed-chunk-27-1.png | Bin 559981 -> 560992 bytes .../figure-html/unnamed-chunk-28-1.png | Bin 556671 -> 556037 bytes articles/seagrasstransect.html | 26 +-- articles/tbbi.html | 38 ++-- articles/tbni.html | 18 +- articles/tidalcreeks.html | 18 +- favicon-16x16.png | Bin 1220 -> 1220 bytes favicon-32x32.png | Bin 2150 -> 2150 bytes pkgdown.yml | 2 +- reference/index.html | 2 +- reference/read_importwqp.html | 2 +- reference/show_annualassess.html | 4 +- reference/show_matrixplotly.html | 2 +- reference/show_ratab.html | 2 +- reference/show_sedimentpelaveplotly.html | 2 +- reference/show_segplotly.html | 2 +- reference/show_tbniscrplotly.html | 2 +- reference/show_tdlcrkindic.html | 2 +- reference/show_tdlcrkindiccdf.html | 2 +- reference/show_transectsum.html | 2 +- reference/util_orgin.html | 10 +- search.json | 2 +- 34 files changed, 182 insertions(+), 182 deletions(-) diff --git a/apple-touch-icon-120x120.png b/apple-touch-icon-120x120.png index 853c0110af8925e7086034622af161b9f2fa7b1e..d3b9fa2ad1d1799ddd79297f86063c331eefe46c 100644 GIT binary patch delta 70 zcmX?8aHe2FKL-!5mHe_b^F0<$Hy1TD3NbXcGPSTWHqyvAGxQ^r33 K#IebD&GP{$+!j0l delta 70 zcmX?8aHe2FKL?YrG4oW8M)rl%%|#82LJTdfObx9JjI|96tPBjq&OMNyyvAGxQzm_K K#Nx?!&GP~8hZQXV diff --git a/apple-touch-icon-152x152.png b/apple-touch-icon-152x152.png index bbeddc2fc104410326da84d40ff777b46d12b8e0..968588b35ed452fdbe8f52ef19c417653d183c08 100644 GIT binary patch delta 96 zcmZo##@MusaY8=_53iMiz^P588>epzbTc#xF*LR^wXiZa(l#)#GBBvWmGzu~fkCyz lHKHUXu_V1UfBZ=9}~>t<*aVrXn-YGGw;tZiUmWnge~ZDKG31A}Ub mYeY#(Vo9o1ZhlH;S|x*#fsu)>fsrnTh7})fzMssNmk$6$ryr>R delta 96 zcmex*hwegLx)~US7+PAH8d@2cY8x0>85oqxT~%dZU{Eb_ mjVMV;EJ?M>%}>cpt7I@TFf!3KFajbp4J^*NGbgj<sP3=FCzt`Q|E ii6yC4x%nxXX_X8{21X{j21Y=HrXj4_$!>DGP(A=0c^XOp diff --git a/apple-touch-icon-76x76.png b/apple-touch-icon-76x76.png index cec6586d6472d476520656a5235ff53ca5c45173..001932c988a11f7dbce1eb490578ccd3a7eb42fe 100644 GIT binary patch delta 71 zcmbPeHqmTCKL-!5m8{32e<>TMAC(j}Gzu{^wlcM_GP2Y*Ft9Q(*jR4YJh@Ox22n#+U diff --git a/apple-touch-icon.png b/apple-touch-icon.png index bd2a18fec27ec0f4a35f81cab057cbe58ced3ddb..81811cf168604b8512f895a154806147e244a963 100644 GIT binary patch delta 96 zcmex*hwfsrnThTQPyiIds#@&PDT9n}B; delta 96 zcmex*hwfbu%yuF|@QYHMBA?*ETS)GB9}5c!Y<6fkCyz mHKHUXu_V

Fecal Indicator Bacteria

-

2024-02-02

+

2024-02-12

Source: vignettes/fib.Rmd
fib.Rmd
@@ -381,16 +381,16 @@

Show yrsel and mosel arguments are required.

 show_fibmap(fibdata, yrsel = 2022, mosel = 7, areasel = NULL)
-
-

Sites for the Hillsborough or Alafia river basins can be shown using +

+

Sites for the Hillsborough or Alafia river basins can be shown using areasel argument.

 show_fibmap(fibdata, yrsel = 2022, mosel = 7, areasel = 'Hillsborough River')
-
-
+

+
 show_fibmap(fibdata, yrsel = 2021, mosel = 6, areasel = 'Alafia River')

-

-
Additional information about a site can be seen by placing the cursor
+

+
Additional information about a site can be seen by placing the cursor
 over a location. A map inset can also be seen by clicking the arrow in
 the button left.

 
The show_fibmatrix() function creates a stoplight
@@ -439,13 +439,13 @@ 
Show
 rows.

 
 show_fibmatrix(fibdata, asreact = TRUE)

-

-
A plotly (interactive, dynamic plot) can be returned by setting the
+

+
A plotly (interactive, dynamic plot) can be returned by setting the
 plotly argument to TRUE.

 
 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 92c8aabb..7a76993c 100644 --- a/articles/habitatmasterplan.html +++ b/articles/habitatmasterplan.html @@ -83,7 +83,7 @@

Habitat Master Plan

-

2024-02-02

+

2024-02-12

Source: vignettes/habitatmasterplan.Rmd
habitatmasterplan.Rmd
diff --git a/articles/intro.html b/articles/intro.html index 5ed796d4..4896a8d1 100644 --- a/articles/intro.html +++ b/articles/intro.html @@ -86,7 +86,7 @@

Water Quality Data

-

2024-02-02

+

2024-02-12

Source: vignettes/intro.Rmd
intro.Rmd
@@ -574,13 +574,13 @@

Show rows.

 show_matrix(epcdata, asreact = TRUE)
-
-

A plotly (interactive, dynamic plot) can be returned by setting the +

+

A plotly (interactive, dynamic plot) can be returned by setting the plotly argument to TRUE.

 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.

@@ -646,8 +646,8 @@

Show by hovering over a location in the plot.

 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 @@ -678,50 +678,50 @@

Reasonable Assurance reporting
 show_annualassess(epcdata, yrsel = 2022)

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

Segment

Chl-a (ug/L)

Light Penetration (m-1)

Segment

Chl-a (ug/L)

Light Penetration (m-1)

2022

target

2022

target

2022

target

2022

target

OTB

7.1

8.5

0.79

0.83

OTB

7.1

8.5

0.79

0.83

HB

8.9

13.2

0.92

1.58

HB

8.9

13.2

0.92

1.58

MTB

5.0

7.4

0.55

0.83

MTB

5.0

7.4

0.55

0.83

LTB

3.6

4.6

0.66

0.63

LTB

3.6

4.6

0.66

0.63
@@ -731,51 +731,51 @@

Reasonable Assurance reporting
 show_annualassess(epcdata, yrsel = 2022, caption = TRUE)

- - - + +
Water quality outcomes for 2022.
+ - - - + + + - - - - - + + + + + - - - - - + + + + + - - - - - + + + + + - - - - - + + + + + - - - - - + + + + +
Water quality outcomes for 2022.

Segment

Chl-a (ug/L)

Light Penetration (m-1)

Segment

Chl-a (ug/L)

Light Penetration (m-1)

2022

target

2022

target

2022

target

2022

target

OTB

7.1

8.5

0.79

0.83

OTB

7.1

8.5

0.79

0.83

HB

8.9

13.2

0.92

1.58

HB

8.9

13.2

0.92

1.58

MTB

5.0

7.4

0.55

0.83

MTB

5.0

7.4

0.55

0.83

LTB

3.6

4.6

0.66

0.63

LTB

3.6

4.6

0.66

0.63
@@ -790,50 +790,50 @@

Reasonable Assurance reporting
 show_ratab(epcdata, yrsel = 2022, 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)

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)

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

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

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

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

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
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a/articles/seagrasstransect.html +++ b/articles/seagrasstransect.html @@ -90,7 +90,7 @@

      Seagrass Transect Data

      -

      2024-02-02

      +

      2024-02-12

      Source:       vignettes/seagrasstransect.Rmd
      seagrasstransect.Rmd
      @@ -183,8 +183,8 @@

      Data import and included datasets 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)

      -
      -

      The transect data can be downloaded from the Water Atlas using the +

      +

      The transect data can be downloaded from the Water Atlas using the read_transect() function. The only required argument for this function is training, which indicates if you want to download training data or the complete dataset, i.e., @@ -425,8 +425,8 @@

      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.

      @@ -447,8 +447,8 @@ 
      Plotting resultsanlz_transectocc() function as input.
      
 
       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
@@ -468,8 +468,8 @@ 
      Plotting resultsplotly = TRUE inside the function.
      
 
       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
@@ -488,8 +488,8 @@ 
      Plotting resultsplotly = TRUE inside the function.
      
 
       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
@@ -497,8 +497,8 @@ 
      Plotting results
 
       show_transectavespp(transectocc, asreact = T, bay_segment = c('HB', 'OTB', 'MTB', 'LTB'), yrrng = c(2006, 2012))
      
-
      
-
      All of the above describes methods in tbeptools for working with
+
      
+
      All of the above describes methods in tbeptools for working with
 transect monitoring data. Seagrass coverage maps are also created
 approximately biennially by the Southwest Florida Water Management
 District, available at https://data-swfwmd.opendata.arcgis.com/.
diff --git a/articles/tbbi.html b/articles/tbbi.html
index 21ab18c4..f21df12d 100644
--- a/articles/tbbi.html
+++ b/articles/tbbi.html
@@ -88,7 +88,7 @@
   
      
       
      Tampa Bay Benthic Index
      
             
-            
      2024-02-02
      
+            
      2024-02-12
      
       
       Source: vignettes/tbbi.Rmd
       
      tbbi.Rmd
      
@@ -310,8 +310,8 @@ 
      Plotting resultsplotly = TRUE inside the function.
      
 
       show_tbbimatrix(tbbiscr, plotly = T)
      
-
      
-
+
      
+
 
      
 
      
 
      Additional sediment data
@@ -366,17 +366,17 @@ 
      Additional sediment datayrrng argument.
      
 
       show_sedimentmap(sedimentdata, param = 'Arsenic', yrrng = c(1993, 2022))
      
-
      
-
      A single year of data can be shown as well.
      
+
      
+
      A single year of data can be shown as well.
      
 
       show_sedimentmap(sedimentdata, param = 'Arsenic', yrrng = 2022)
      
-
      
-
      A map showing only the concentrations is returned if TEL and PEL
+
      
+
      A map showing only the concentrations is returned if TEL and PEL
 values are not available for a parameter.
      
 
       show_sedimentmap(sedimentdata, param = 'Selenium', yrrng = c(1993, 2022))
      
-
      
-
      Maps for total contaminant values (e.g., Total DDT, Total PAH, Total
+
      
+
      Maps for total contaminant values (e.g., Total DDT, Total PAH, Total
 PCB, Total LMW PAH, Total HMW PAH) can also be returned. Although the
 totals are not included in the sedimentdata object, they
 are calculated by tbeptools using the anlz_sedimentaddtot()
@@ -385,8 +385,8 @@ 
      Additional sediment data
 
       show_sedimentmap(sedimentdata, param = 'Total DDT', yrrng = c(1993, 2022))
      
-
      
-
      The PEL ratio can also be used to assess relative sediment quality
+
      
+
      The PEL ratio can also be used to assess relative sediment quality
 given the measured contaminants. The show_sedimentpelmap()
 function creates a map of average PEL ratios graded from A to F for
 benthic stations monitored in Tampa Bay. The PEL ratio is the
@@ -397,8 +397,8 @@ 
      Additional sediment data
 
       show_sedimentpelmap(sedimentdata, yrrng = c(1993, 2022))
      
-
      
-
      The average PEL ratios and grades used to create the map can also be
+
      
+
      The average PEL ratios and grades used to create the map can also be
 returned as a data frame using anlz_sedimentpel().
      
 
       anlz_sedimentpel(sedimentdata, yrrng = c(1993, 2022))
@@ -428,8 +428,8 @@ 
      Additional sediment dataplotly = T.
      
 
       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))
@@ -470,8 +470,8 @@ 
      Additional sediment dataplotly = T.
      
 
       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))
@@ -500,8 +500,8 @@ 
      Additional sediment dataplotly = T.
      
 
       show_sedimentalratio(sedimentdata, param = 'Zinc', bay_segment = c('HB', 'LTB'), plotly = T)
      
-
      
-
+
      
+
 
      
 
      
 
      References
diff --git a/articles/tbni.html b/articles/tbni.html
index 7dc2701e..17304cc6 100644
--- a/articles/tbni.html
+++ b/articles/tbni.html
@@ -90,7 +90,7 @@
   
      
       
      Tampa Bay Nekton Index
      
             
-            
      2024-02-02
      
+            
      2024-02-12
      
       
       Source: vignettes/tbni.Rmd
       
      tbni.Rmd
      
@@ -226,8 +226,8 @@ 
      Data import and included datasets
       fimstations <- read_importfim(csv, download_latest = TRUE, locs = TRUE)
 mapview(fimstations, zcol = 'bay_segment')
      
-
      
-
      The read_importfim() function processes the observed
+
      
+
      The read_importfim() function processes the observed
 data as needed for the TBNI, including merging the rows with the
 tbnispp and fimstations data. Once imported,
 the metrics and scores can be calculated.
      
@@ -327,14 +327,14 @@ 
      Plotting resultsplotly = TRUE inside each function.
      
 
       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 ce4aec34..db0650bc 100644
--- a/articles/tidalcreeks.html
+++ b/articles/tidalcreeks.html
@@ -90,7 +90,7 @@
   
      
       
      Tidal Creek Assessment
      
             
-            
      2024-02-02
      
+            
      2024-02-12
      
       
       Source: vignettes/tidalcreeks.Rmd
       
      tidalcreeks.Rmd
      
@@ -126,8 +126,8 @@ 
      Background
       mapview(tidalcreeks, homebutton = F, legend = F)
      
-
      
-
      The tidal creek assessment framework was established based on data
+
      
+
      The tidal creek assessment framework was established based on data
 from the FDEP Impaired
 Waters Rule database run 56 available here which
 includes data collected through January 10th 2019. However, the this
@@ -269,8 +269,8 @@ 
      Report card functions
 
       show_tdlcrk(results)
      
-
      
-
      A report card style matrix can be plotted using the
+
      
+
      A report card style matrix can be plotted using the
 show_tdlcrkmatrix() function that shows the overall creek
 score and the number of years of data that were used to estimate the
 overall score. The plot shows a matrix with rows for individual creeks
@@ -368,8 +368,8 @@ 
      Indicator functions
       cntdat <- anlz_tdlcrkindic(tidalcreeks, iwrraw, yr = 2022)
 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
@@ -381,8 +381,8 @@ 
      Indicator functions
       show_tdlcrkindiccdf(id = id, cntdat = cntdat, thrsel = TRUE)
      
-
      
-
+
      
+
 
      
 
      
 
      
diff --git a/favicon-16x16.png b/favicon-16x16.png
index e8a1e1d714ccaf9596568d249bb1d27dbb6bb7b5..68e9822316a880bec80893ace6b2ffd3a2cb5610 100644
GIT binary patch
delta 96
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mYeY#(Vo9o1ZhlH;S|x*#fsu)>fsrnThE?BtMJI={q-|heWnfSv{MwX(fkCyz
mHKHUXu_V8d8ig1dTbWu|8Cz-_7+4t?)ZVp|Wnf@XEpd$~
jNl7e8waU#;$xN$cFfuSQ(KRsA#n8ah(6(^$clLY$J%1a9

delta 94
zcmaDR@JwJrKL?YrF>ld^H4Gc4OR>8d7=;*GTA3PJ85(OF7+4t?+)8=S$iTp$TH+c}
kl9E`GYL%Oxl9^V?U}RuqqHACTL}(gTTSnMU{?48c06!TUk^lez

diff --git a/pkgdown.yml b/pkgdown.yml
index 34be02a6..c5413564 100644
--- a/pkgdown.yml
+++ b/pkgdown.yml
@@ -9,7 +9,7 @@ articles:
   tbbi: tbbi.html
   tbni: tbni.html
   tidalcreeks: tidalcreeks.html
-last_built: 2024-02-02T19:51Z
+last_built: 2024-02-12T13:58Z
 urls:
   reference: https://tbep-tech.github.io/tbeptools/reference
   article: https://tbep-tech.github.io/tbeptools/articles
diff --git a/reference/index.html b/reference/index.html
index 71cf78e6..445f67c3 100644
--- a/reference/index.html
+++ b/reference/index.html
@@ -676,7 +676,7 @@ 
      Utility functionsutil_orgin() 
         
-        
      Get county name from organization identifier
      
+        
      Get organization name from organization identifier
      diff --git a/reference/read_importwqp.html b/reference/read_importwqp.html index bde77ecd..e45fcf74 100644 --- a/reference/read_importwqp.html +++ b/reference/read_importwqp.html @@ -86,7 +86,7 @@

      Value

      Details

      This function retrieves data from the Water Quality Portal API (https://www.waterqualitydata.us/) for selected counties in or around the Tampa Bay watershed. The type of data returned are defined by the type argument as either "wq" or "fib" for water quality of Fecal Indicator Bacteria data, respectively.

      -

      The org argument retrieves data for the specific organization. Valid entries for org include "21FLHILL_WQX" (Hillsborough County), "21FLMANA_WQX" (Manatee County), "21FLPASC_WQX" (Pasco County), "21FLPDEM_WQX" (Pinellas County), or "21FLPOLK_WQX" (Polk County). The naming convention follows the Organization ID in the Water Quality Portal.

      +

      The org argument retrieves data for the specific organization. Valid entries for org include "21FLDOH_WQX" (Florida Department of Health), "21FLHILL_WQX" (Hillsborough County), "21FLMANA_WQX" (Manatee County), "21FLPASC_WQX" (Pasco County), "21FLPDEM_WQX" (Pinellas County), or "21FLPOLK_WQX" (Polk County). The naming convention follows the Organization ID in the Water Quality Portal.

      The function fetches results and station metadata, combines and formats them using the read_formwqp function, and returns the processed data as a data frame. Parameters are specific to the type argument.

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diff --git a/reference/show_annualassess.html b/reference/show_annualassess.html index 22786e84..87b35c0a 100644 --- a/reference/show_annualassess.html +++ b/reference/show_annualassess.html @@ -111,8 +111,8 @@

Value

Examples

show_annualassess(epcdata, yrsel = 2022)
-
Segment
Chl-a (ug/L)
Light Penetration (m-1)
2022
target
2022
target
OTB
7.1
8.5
0.79
0.83
HB
8.9
13.2
0.92
1.58
MTB
5.0
7.4
0.55
0.83
LTB
3.6
4.6
0.66
0.63
show_annualassess(epcdata, yrsel = 2022, caption = TRUE)
-
Water quality outcomes for 2022.
Segment
Chl-a (ug/L)
Light Penetration (m-1)
2022
target
2022
target
OTB
7.1
8.5
0.79
0.83
HB
8.9
13.2
0.92
1.58
MTB
5.0
7.4
0.55
0.83
LTB
3.6
4.6
0.66
0.63
+

Segment

Chl-a (ug/L)

Light Penetration (m-1)

2022

target

2022

target

OTB

7.1

8.5

0.79

0.83

HB

8.9

13.2

0.92

1.58

MTB

5.0

7.4

0.55

0.83

LTB

3.6

4.6

0.66

0.63

show_annualassess(epcdata, yrsel = 2022, caption = TRUE) +
Water quality outcomes for 2022.

Segment

Chl-a (ug/L)

Light Penetration (m-1)

2022

target

2022

target

OTB

7.1

8.5

0.79

0.83

HB

8.9

13.2

0.92

1.58

MTB

5.0

7.4

0.55

0.83

LTB

3.6

4.6

0.66

0.63

diff --git a/reference/show_matrixplotly.html b/reference/show_matrixplotly.html index 9b32d54d..c5c7f178 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 d1589bf6..74edea2b 100644 --- a/reference/show_ratab.html +++ b/reference/show_ratab.html @@ -134,7 +134,7 @@

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)

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

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

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)

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

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

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 c371eb6f..0be09526 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 2eff8ffb..6fb6a1d1 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 f6532f2f..996d5449 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 661f24cb..f542712c 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 4a82dd93..bd4d466e 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 084798d0..7a21355f 100644 --- a/reference/show_transectsum.html +++ b/reference/show_transectsum.html @@ -115,7 +115,7 @@

Examplestransectocc <- anlz_transectocc(transect) show_transectsum(transectocc, site = 'S3T10')
- + diff --git a/reference/util_orgin.html b/reference/util_orgin.html index c974fb98..4c44cfb2 100644 --- a/reference/util_orgin.html +++ b/reference/util_orgin.html @@ -1,5 +1,5 @@ -Get county name from organization identifier — util_orgin • tbeptoolsGet organization name from organization identifier — util_orgin • tbeptools @@ -49,13 +49,13 @@
-

Get county name from organization identifier

+

Get organization name from organization identifier

Source: R/util_orgin.R
util_orgin.Rd
-

Get county name from organization identifier

+

Get organization name from organization identifier

@@ -70,14 +70,14 @@

Arguments

Value

-

A character string of the county name that correspond to the organization identifier or a column name for the station identfier specific to the county if stanm = TRUE

+

A character string of the organization name that corresponds to the organization identifier or a column name for the station identifier specific to the organization if stanm = TRUE

diff --git a/search.json b/search.json index 67c98114..21c8c981 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) 2022 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: 74,872 × 18 #> area epchc_station class SampleTime yr mo Latitude Longitude #> #> 1 Hills… 2 3M 2023-05-10 13:48:00 2023 5 27.9 -82.5 #> 2 Hills… 6 3M 2023-05-16 09:32:00 2023 5 27.9 -82.5 #> 3 Hills… 7 3M 2023-05-16 09:41:00 2023 5 27.9 -82.5 #> 4 Hills… 8 3M 2023-05-16 11:50:00 2023 5 27.9 -82.4 #> 5 Middl… 9 2 2023-05-16 11:12:00 2023 5 27.8 -82.4 #> 6 Middl… 11 2 2023-05-16 09:55:00 2023 5 27.8 -82.5 #> 7 Middl… 13 2 2023-05-16 10:07:00 2023 5 27.8 -82.5 #> 8 Middl… 14 2 2023-05-16 10:49:00 2023 5 27.8 -82.5 #> 9 Middl… 16 2 2023-05-23 10:19:00 2023 5 27.7 -82.5 #> 10 Middl… 19 2 2023-05-23 10:36:00 2023 5 27.7 -82.6 #> # ℹ 74,862 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 monitoring data counties 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: 74,872 × 12 #> area epchc_station class yr mo Latitude Longitude ecoli ecocci ind #> #> 1 Hillsb… 2 3M 2023 5 27.9 -82.5 NA 4 Ente… #> 2 Hillsb… 6 3M 2023 5 27.9 -82.5 NA 2 Ente… #> 3 Hillsb… 7 3M 2023 5 27.9 -82.5 NA 2 Ente… #> 4 Hillsb… 8 3M 2023 5 27.9 -82.4 NA 2 Ente… #> 5 Middle… 9 2 2023 5 27.8 -82.4 NA 2 Ente… #> 6 Middle… 11 2 2023 5 27.8 -82.5 NA 2 Ente… #> 7 Middle… 13 2 2023 5 27.8 -82.5 NA 2 Ente… #> 8 Middle… 14 2 2023 5 27.8 -82.5 NA 2 Ente… #> 9 Middle… 16 2 2023 5 27.7 -82.5 NA 2 Ente… #> 10 Middle… 19 2 2023 5 27.7 -82.6 NA 2 Ente… #> # ℹ 74,862 more rows #> # ℹ 2 more variables: cat , col anlz_fibmap(fibdata, yrsel = 2022, mosel = 7) #> # A tibble: 195 × 12 #> area epchc_station class yr mo Latitude Longitude ecoli ecocci ind #> #> 1 Hillsb… 2 3M 2022 7 27.9 -82.5 NA 20 Ente… #> 2 Hillsb… 6 3M 2022 7 27.9 -82.5 NA 2 Ente… #> 3 Hillsb… 7 3M 2022 7 27.9 -82.5 NA 2 Ente… #> 4 Hillsb… 8 3M 2022 7 27.9 -82.4 NA 2 Ente… #> 5 Middle… 9 2 2022 7 27.8 -82.4 NA 2 Ente… #> 6 Middle… 11 2 2022 7 27.8 -82.5 NA 2 Ente… #> 7 Middle… 13 2 2022 7 27.8 -82.5 NA 2 Ente… #> 8 Middle… 14 2 2022 7 27.8 -82.5 NA 2 Ente… #> 9 Middle… 16 2 2022 7 27.7 -82.5 NA 2 Ente… #> 10 Middle… 19 2 2022 7 27.7 -82.6 NA 2 Ente… #> # ℹ 185 more rows #> # ℹ 2 more variables: cat , col anlz_fibmap(fibdata, yrsel = 2022, mosel = 7, areasel = 'Hillsborough River') #> # A tibble: 38 × 12 #> area epchc_station class yr mo Latitude Longitude ecoli ecocci ind #> #> 1 Hillsb… 2 3M 2022 7 27.9 -82.5 NA 20 Ente… #> 2 Hillsb… 105 3M 2022 7 28.0 -82.4 NA 7 Ente… #> 3 Hillsb… 106 1 2022 7 28.1 -82.4 73 80 E. c… #> 4 Lake T… 107 3F 2022 7 28.0 -82.3 240 700 E. c… #> 5 Hillsb… 108 3F 2022 7 28.1 -82.2 60 210 E. c… #> 6 Lake T… 118 3F 2022 7 28.1 -82.3 7 10 E. c… #> 7 Hillsb… 120 3F 2022 7 28.1 -82.4 220 300 E. c… #> 8 Lake T… 135 3F 2022 7 28.1 -82.3 7 7 E. c… #> 9 Hillsb… 137 3M 2022 7 28.0 -82.5 NA 40 Ente… #> 10 Hillsb… 143 3F 2022 7 28.1 -82.1 327 1240 E. c… #> # ℹ 28 more rows #> # ℹ 2 more variables: cat , col anlz_fibmatrix(fibdata) #> # A tibble: 8,541 × 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 8,531 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 = 2022, mosel = 7, areasel = NULL) show_fibmap(fibdata, yrsel = 2022, mosel = 7, areasel = 'Hillsborough River') show_fibmap(fibdata, yrsel = 2021, mosel = 6, 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. Finally, text showing proportion target goal met year can suppressed using text = NULL. size text can changed entering numeric value (default text = 2.5). 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)"},{"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: 23,848 × 8 #> epchc_station Date name units count yrqrt yr mo #> #> 1 11 1975-07-23 Cyanobacteria /0.1mL 0 1975-07-01 1975 Jul #> 2 11 1976-01-07 Cyanobacteria /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 other /0.1mL 1 1977-04-01 1977 Apr #> 5 11 1977-04-20 Tripos hircus /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 23,838 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 monitoring data counties around Tampa Bay watershed. function retrieves nutrient, chlorophyll, secchi, temperature, salinity, turbidity data available estuarine stations monitored county 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) 2022 target 2022 target OTB 7.1 8.5 0.79 0.83 HB 8.9 13.2 0.92 1.58 MTB 5.0 7.4 0.55 0.83 LTB 3.6 4.6 0.66 0.63 default caption can also included setting caption = TRUE. Water quality outcomes 2022. Segment Chl-(ug/L) Light Penetration (m-1) 2022 target 2022 target OTB 7.1 8.5 0.79 0.83 HB 8.9 13.2 0.92 1.58 MTB 5.0 7.4 0.55 0.83 LTB 3.6 4.6 0.66 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) 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/ 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 = 2022) show_annualassess(epcdata, yrsel = 2022, caption = TRUE) show_ratab(epcdata, yrsel = 2022, 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., whereas attached drift algae species aggregated. 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. 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 \"CYAN: Lyngbya/Dapis\" 41 0 0 #> 3 1997-10-11 S2T3 \"Caulerpa\" 41 0 0 #> 4 1997-10-11 S2T3 \"DA\" 41 0 0 #> 5 1997-10-11 S2T3 \"DB: Dictyota\\r\\n\" 41 0 0 #> 6 1997-10-11 S2T3 \"DB: Drift Brown\\r\\n\" 41 0 0 #> 7 1997-10-11 S2T3 \"DG: Chaetomorpha\\r\\n\" 41 0 0 #> 8 1997-10-11 S2T3 \"DG: Drift Green\" 41 0 0 #> 9 1997-10-11 S2T3 \"DG: Ulva\" 41 0 0 #> 10 1997-10-11 S2T3 \"DG: Ulva fasciata\\r\\n\" 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: 182 × 3 #> yr Savspecies foest #> #> 1 1998 Caulerpa 0.0166 #> 2 1998 Halodule 0.361 #> 3 1998 Halophila 0 #> 4 1998 Ruppia 0.0112 #> 5 1998 Syringodium 0.0451 #> 6 1998 Thalassia 0.254 #> 7 1998 total 0.580 #> 8 1999 Caulerpa 0.0277 #> 9 1999 Halodule 0.306 #> 10 1999 Halophila 0.00118 #> # ℹ 172 more rows transectavespp <- anlz_transectavespp(transectocc, by_seg = TRUE) transectavespp #> # A tibble: 1,040 × 5 #> yr bay_segment Savspecies foest nsites #> #> 1 1998 BCB Caulerpa 0 96 #> 2 1998 BCB Halodule 0.613 96 #> 3 1998 BCB Halophila 0 96 #> 4 1998 BCB No Cover 0.190 96 #> 5 1998 BCB Ruppia 0 96 #> 6 1998 BCB Syringodium 0 96 #> 7 1998 BCB Thalassia 0.304 96 #> 8 1998 BCB total 0.810 96 #> 9 1998 HB Caulerpa 0 285 #> 10 1998 HB Halodule 0.147 285 #> # ℹ 1,030 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 = 2022, 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: 149,066 × 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 149,056 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 NA 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 2013 2.725391 9.607368 NA 6.819091 73.50770 #> 2 2 Rock Creek CC01 2052 3M 2014 2.380249 14.694735 NA 3.308289 60.31523 #> 3 2 Rock Creek CC01 2052 3M 2015 2.647817 21.911128 NA 4.034172 55.41609 #> 4 2 Rock Creek CC01 2052 3M 2016 2.265462 19.130797 NA 3.980251 55.96637 #> 5 2 Rock Creek CC01 2052 3M 2017 2.851726 15.395763 NA 4.157777 60.18017 #> 6 2 Rock Creek CC01 2052 3M 2018 1.934899 11.655004 NA 4.219790 63.32630 #> NO23 ORGN SALIN TKN TN TP TSS TURB #> 1 0.009781633 NA 30.90561 0.6510575 0.7108146 0.06842811 NA 1.698004 #> 2 0.007575792 NA 26.63714 0.6161702 0.6228782 0.06938150 NA 2.044623 #> 3 0.009361504 NA 19.10494 0.6465161 0.5678241 0.07602770 NA 1.814818 #> 4 0.008532522 NA 25.84531 0.5813818 0.5408161 0.08330509 NA 2.082253 #> 5 0.007447260 NA 24.86909 0.6255197 0.6326848 0.07566682 NA 1.802161 #> 6 0.006994714 NA 31.32419 0.5668727 0.5734574 0.07432007 NA 2.454007 #> chla_tn_ratio tn_tp_ratio chla_tsi tn_tsi tn2_tsi tp_tsi tp2_tsi #> 1 3.834180 10.387756 31.23761 49.24140 52.26414 60.19958 75.92850 #> 2 3.821371 8.977584 29.28775 46.62660 49.42526 60.45694 76.25504 #> 3 4.663093 7.468648 30.82179 44.79432 47.43600 62.15842 78.41391 #> 4 4.188970 6.491994 28.57601 43.82942 46.38844 63.85868 80.57123 #> 5 4.507341 8.361456 31.89011 46.93590 49.76107 62.06992 78.30162 #> 6 3.374095 7.716050 26.30480 44.98978 47.64821 61.73589 77.87779 #> nut_tsi tsi no23_source no23_tidal no23_ratio do_bnml do_prop #> 1 54.72049 42.97905 NA NA NA 0 0 #> 2 49.42526 39.35651 NA NA NA 0 1 #> 3 47.43600 39.12890 NA NA NA 0 1 #> 4 46.38844 37.48223 NA NA NA 0 1 #> 5 49.76107 40.82559 NA NA NA 0 0 #> 6 47.64821 36.97650 NA NA NA 0 1 cntdat <- anlz_tdlcrkindic(tidalcreeks, iwrraw, yr = 2022, 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 = 2022) 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: 74,872 × 12 #> area epchc_station class yr mo Latitude Longitude ecoli ecocci ind #> #> 1 Hillsb… 2 3M 2023 5 27.9 -82.5 NA 4 Ente… #> 2 Hillsb… 6 3M 2023 5 27.9 -82.5 NA 2 Ente… #> 3 Hillsb… 7 3M 2023 5 27.9 -82.5 NA 2 Ente… #> 4 Hillsb… 8 3M 2023 5 27.9 -82.4 NA 2 Ente… #> 5 Middle… 9 2 2023 5 27.8 -82.4 NA 2 Ente… #> 6 Middle… 11 2 2023 5 27.8 -82.5 NA 2 Ente… #> 7 Middle… 13 2 2023 5 27.8 -82.5 NA 2 Ente… #> 8 Middle… 14 2 2023 5 27.8 -82.5 NA 2 Ente… #> 9 Middle… 16 2 2023 5 27.7 -82.5 NA 2 Ente… #> 10 Middle… 19 2 2023 5 27.7 -82.6 NA 2 Ente… #> # ℹ 74,862 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: 8,541 × 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 8,531 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. 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 = 2022)"},{"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 = 2022) #> wbid class JEI year date masterCode result rCode #> 1 2052 3M CC01 2013 2013-02-04 CHLAC -0.0100503359 I #> 2 2052 3M CC01 2013 2013-02-04 COLOR 0.9162907319 U #> 3 2052 3M CC01 2013 2013-02-04 DOSAT 3.8066624898 + #> 4 2052 3M CC01 2013 2013-02-04 NO23 -4.4228486292 #> 5 2052 3M CC01 2013 2013-02-04 SALIN 3.5085559000 #> 6 2052 3M CC01 2013 2013-02-04 TKN -0.6161861394 #> 7 2052 3M CC01 2013 2013-02-04 TN -0.5942072327 + #> 8 2052 3M CC01 2013 2013-02-04 TP -3.0365542681 #> 9 2052 3M CC01 2013 2013-02-04 TURB 0.1823215568 #> 10 2052 3M CC01 2013 2013-03-04 CHLAC -0.0100503359 I #> 11 2052 3M CC01 2013 2013-03-04 COLOR 0.9162907319 I #> 12 2052 3M CC01 2013 2013-03-04 NO23 -4.0745419349 #> 13 2052 3M CC01 2013 2013-03-04 SALIN 3.6054978452 #> 14 2052 3M CC01 2013 2013-03-04 TKN -0.1508228897 #> 15 2052 3M CC01 2013 2013-03-04 TN -0.1312482866 + #> 16 2052 3M CC01 2013 2013-03-04 TP -2.7488721956 #> 17 2052 3M CC01 2013 2013-03-04 TURB 0.0000000000 #> 18 2052 3M CC01 2013 2013-06-03 CHLAC 0.3364722366 I #> 19 2052 3M CC01 2013 2013-06-03 COLOR 1.3083328197 I #> 20 2052 3M CC01 2013 2013-06-03 NO23 -5.2983173665 I #> 21 2052 3M CC01 2013 2013-06-03 SALIN 3.5779478934 #> 22 2052 3M CC01 2013 2013-06-03 TKN -0.7550225843 #> 23 2052 3M CC01 2013 2013-06-03 TN -0.7465479573 + #> 24 2052 3M CC01 2013 2013-06-03 TP -2.9187712324 #> 25 2052 3M CC01 2013 2013-06-03 TURB 0.4700036292 #> 26 2052 3M CC01 2013 2013-08-05 CHLAC 2.6390573296 #> 27 2052 3M CC01 2013 2013-08-05 COLOR 4.0073331852 #> 28 2052 3M CC01 2013 2013-08-05 NO23 -5.1159958098 I #> 29 2052 3M CC01 2013 2013-08-05 TN 0.0989399479 + #> 30 2052 3M CC01 2013 2013-08-05 TURB 0.8329091229 A #> 31 2052 3M CC01 2013 2013-09-09 CHLAC 2.1400661635 #> 32 2052 3M CC01 2013 2013-09-09 COLOR 4.5951198501 #> 33 2052 3M CC01 2013 2013-09-09 DO 2.0149030205 #> 34 2052 3M CC01 2013 2013-09-09 DOSAT 4.6849051540 + #> 35 2052 3M CC01 2013 2013-09-09 NO23 -4.2686979494 #> 36 2052 3M CC01 2013 2013-09-09 SALIN 2.9907197317 #> 37 2052 3M CC01 2013 2013-09-09 TKN 0.0953101798 #> 38 2052 3M CC01 2013 2013-09-09 TN 0.1079571415 + #> 39 2052 3M CC01 2013 2013-09-09 TP -2.2072749132 #> 40 2052 3M CC01 2013 2013-09-09 TURB 0.8754687374 #> 41 2052 3M CC01 2013 2013-11-04 CHLAC 1.2809338455 #> 42 2052 3M CC01 2013 2013-11-04 COLOR 3.1780538303 #> 43 2052 3M CC01 2013 2013-11-04 NO23 -4.6051701860 #> 44 2052 3M CC01 2013 2013-11-04 TKN -0.4942963218 #> 45 2052 3M CC01 2013 2013-11-04 TN -0.4780358009 + #> 46 2052 3M CC01 2013 2013-11-04 TP -2.3330443005 #> 47 2052 3M CC01 2013 2013-11-04 TURB 0.8754687374 #> 48 2052 3M CC01 2013 2013-12-02 CHLAC 0.6418538862 #> 49 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DO 0.8241754430 #> 342 2052 3M CC01 2017 2017-06-05 DOSAT 3.4210000090 + #> 343 2052 3M CC01 2017 2017-06-05 SALIN 2.2533948488 #> 344 2052 3M CC01 2017 2017-06-05 CHLAC 0.4054651081 I #> 345 2052 3M CC01 2017 2017-06-05 COLOR 1.9878743482 #> 346 2052 3M CC01 2017 2017-06-05 DO 1.2527629685 #> 347 2052 3M CC01 2017 2017-06-05 DOSAT 4.0360089852 + #> 348 2052 3M CC01 2017 2017-06-05 NO23 -4.9618451299 I #> 349 2052 3M CC01 2017 2017-06-05 SALIN 3.6506582413 #> 350 2052 3M CC01 2017 2017-06-05 TKN -0.6539264674 #> 351 2052 3M CC01 2017 2017-06-05 TN -0.6462635947 + #> 352 2052 3M CC01 2017 2017-06-05 TP -2.8473122684 #> 353 2052 3M CC01 2017 2017-06-05 TURB 0.2623642645 #> 354 2052 3M CC01 2017 2017-06-05 DO 1.4655675420 #> 355 2052 3M CC01 2017 2017-06-05 DOSAT 4.1866198383 + #> 356 2052 3M CC01 2017 2017-06-05 SALIN 3.5115454388 #> 357 2052 3M CC01 2017 2017-07-10 CHLAC 0.9162907319 #> 358 2052 3M CC01 2017 2017-07-10 COLOR 3.7376696183 A #> 359 2052 3M CC01 2017 2017-07-10 DO 1.9021075264 #> 360 2052 3M CC01 2017 2017-07-10 DOSAT 4.6482296754 + #> 361 2052 3M CC01 2017 2017-07-10 NO23 -5.5214609179 I #> 362 2052 3M CC01 2017 2017-07-10 SALIN 3.3214324132 #> 363 2052 3M CC01 2017 2017-07-10 TKN -0.3566749439 #> 364 2052 3M CC01 2017 2017-07-10 TN -0.3509769228 + #> 365 2052 3M CC01 2017 2017-07-10 TP -2.4418471603 #> 366 2052 3M CC01 2017 2017-07-10 TURB 0.4700036292 #> 367 2052 3M CC01 2017 2017-09-05 CHLAC 2.7725887222 #> 368 2052 3M CC01 2017 2017-09-05 COLOR 5.2470240722 #> 369 2052 3M CC01 2017 2017-09-05 DO 1.4350845253 #> 370 2052 3M CC01 2017 2017-09-05 DOSAT 4.0517849478 + #> 371 2052 3M CC01 2017 2017-09-05 NO23 -4.1351665567 #> 372 2052 3M CC01 2017 2017-09-05 SALIN 2.1282317058 #> 373 2052 3M CC01 2017 2017-09-05 TKN 0.1823215568 #> 374 2052 3M CC01 2017 2017-09-05 TN 0.1955667835 + #> 375 2052 3M CC01 2017 2017-09-05 TP -2.1202635362 #> 376 2052 3M CC01 2017 2017-09-05 TURB 0.6418538862 A #> 377 2052 3M CC01 2017 2017-10-02 CHLAC 2.1633230257 #> 378 2052 3M CC01 2017 2017-10-02 COLOR 3.8066624898 #> 379 2052 3M CC01 2017 2017-10-02 NO23 -4.8283137373 I #> 380 2052 3M CC01 2017 2017-10-02 TKN -0.5276327421 #> 381 2052 3M CC01 2017 2017-10-02 TN -0.5208759596 + #> 382 2052 3M CC01 2017 2017-10-02 TP -2.3025850930 #> 383 2052 3M CC01 2017 2017-10-02 TURB 0.6418538862 #> 384 2052 3M CC01 2017 2017-11-06 CHLAC 0.6418538862 #> 385 2052 3M CC01 2017 2017-11-06 COLOR 2.5649493575 #> 386 2052 3M CC01 2017 2017-11-06 DO 1.6863989536 #> 387 2052 3M CC01 2017 2017-11-06 DOSAT 4.3241326563 + #> 388 2052 3M CC01 2017 2017-11-06 NO23 -4.5098600062 #> 389 2052 3M CC01 2017 2017-11-06 SALIN 3.2809112158 #> 390 2052 3M CC01 2017 2017-11-06 TKN -0.5108256238 #> 391 2052 3M CC01 2017 2017-11-06 TN -0.4926583198 + #> 392 2052 3M CC01 2017 2017-11-06 TP -2.5770219387 #> 393 2052 3M CC01 2017 2017-11-06 TURB 0.4700036292 #> 394 2052 3M CC01 2017 2017-12-04 CHLAC 0.4054651081 I #> 395 2052 3M CC01 2017 2017-12-04 COLOR 2.2512917986 #> 396 2052 3M CC01 2017 2017-12-04 DO 1.6486586256 #> 397 2052 3M CC01 2017 2017-12-04 DOSAT 4.2835865619 + #> 398 2052 3M CC01 2017 2017-12-04 NO23 -5.5214609179 I #> 399 2052 3M CC01 2017 2017-12-04 SALIN 3.4843122884 #> 400 2052 3M CC01 2017 2017-12-04 TKN -0.6348782724 #> 401 2052 3M CC01 2017 2017-12-04 TN -0.6273594400 + #> 402 2052 3M CC01 2017 2017-12-04 TP -2.7968814148 #> 403 2052 3M CC01 2017 2017-12-04 TURB 0.7419373447 #> 404 2052 3M CC01 2018 2018-01-02 CHLAC 0.3364722366 I #> 405 2052 3M CC01 2018 2018-01-02 COLOR 2.3025850930 #> 406 2052 3M CC01 2018 2018-01-02 DO 1.8718021769 #> 407 2052 3M CC01 2018 2018-01-02 DOSAT 4.3214801348 + #> 408 2052 3M CC01 2018 2018-01-02 NO23 -4.6051701860 #> 409 2052 3M CC01 2018 2018-01-02 SALIN 3.3214324132 #> 410 2052 3M CC01 2018 2018-01-02 TKN -0.7765287895 #> 411 2052 3M CC01 2018 2018-01-02 TN -0.7550225843 + #> 412 2052 3M CC01 2018 2018-01-02 TP -2.6450754019 #> 413 2052 3M CC01 2018 2018-01-02 TURB 0.7884573604 #> 414 2052 3M CC01 2018 2018-02-05 CHLAC 0.6418538862 #> 415 2052 3M CC01 2018 2018-02-05 COLOR 2.1633230257 #> 416 2052 3M CC01 2018 2018-02-05 DO 1.9600947840 #> 417 2052 3M CC01 2018 2018-02-05 DOSAT 4.5358201079 + #> 418 2052 3M CC01 2018 2018-02-05 NO23 -4.1351665567 #> 419 2052 3M CC01 2018 2018-02-05 SALIN 3.3877743613 #> 420 2052 3M CC01 2018 2018-02-05 TKN -0.6348782724 #> 421 2052 3M CC01 2018 2018-02-05 TN -0.6051363032 + #> 422 2052 3M CC01 2018 2018-02-05 TP -2.4304184645 #> 423 2052 3M CC01 2018 2018-02-05 TURB 1.8405496334 A #> 424 2052 3M CC01 2018 2018-03-05 CHLAC 0.3364722366 I #> 425 2052 3M CC01 2018 2018-03-05 COLOR 1.9459101491 #> 426 2052 3M CC01 2018 2018-03-05 DO 2.0412203289 #> 427 2052 3M CC01 2018 2018-03-05 DOSAT 4.5890408041 + #> 428 2052 3M CC01 2018 2018-03-05 NO23 -5.5214609179 U #> 429 2052 3M CC01 2018 2018-03-05 SALIN 3.4372078192 #> 430 2052 3M CC01 2018 2018-03-05 TKN -0.7985076962 #> 431 2052 3M CC01 2018 2018-03-05 TN -0.7940730991 + #> 432 2052 3M CC01 2018 2018-03-05 TP -2.8134107168 #> 433 2052 3M CC01 2018 2018-03-05 TURB 0.9932517730 #> 434 2052 3M CC01 2018 2018-04-02 CHLAC 0.5306282511 I #> 435 2052 3M CC01 2018 2018-04-02 COLOR 1.0986122887 I #> 436 2052 3M CC01 2018 2018-04-02 DOSAT 4.5538768916 + #> 437 2052 3M CC01 2018 2018-04-02 NO23 -5.5214609179 U #> 438 2052 3M CC01 2018 2018-04-02 SALIN 3.5025498759 #> 439 2052 3M CC01 2018 2018-04-02 TKN -0.7550225843 #> 440 2052 3M CC01 2018 2018-04-02 TN -0.7507762934 + #> 441 2052 3M CC01 2018 2018-04-02 TP -2.8473122684 #> 442 2052 3M CC01 2018 2018-04-02 TURB 1.1314021115 #> 443 2052 3M CC01 2018 2018-05-07 CHLAC 0.5877866649 #> 444 2052 3M CC01 2018 2018-05-07 COLOR 2.1041341543 #> 445 2052 3M CC01 2018 2018-05-07 DO 0.8285518176 #> 446 2052 3M CC01 2018 2018-05-07 DOSAT 3.5292973843 #> 447 2052 3M CC01 2018 2018-05-07 NO23 -5.5214609179 U #> 448 2052 3M CC01 2018 2018-05-07 SALIN 3.5743099994 #> 449 2052 3M CC01 2018 2018-05-07 TKN -0.5621189182 #> 450 2052 3M CC01 2018 2018-05-07 TN -0.5586162876 + #> 451 2052 3M CC01 2018 2018-05-07 TP -2.6310891600 #> 452 2052 3M CC01 2018 2018-05-07 TURB 0.7884573604 #> 453 2052 3M CC01 2018 2018-07-09 CHLAC 0.9932517730 #> 454 2052 3M CC01 2018 2018-07-09 COLOR 4.1743872699 #> 455 2052 3M CC01 2018 2018-07-09 DO 1.1216775616 #> 456 2052 3M CC01 2018 2018-07-09 DOSAT 3.9140210081 #> 457 2052 3M CC01 2018 2018-07-09 NO23 -4.6051701860 #> 458 2052 3M CC01 2018 2018-07-09 SALIN 3.4339872045 #> 459 2052 3M CC01 2018 2018-07-09 TKN -0.2231435513 #> 460 2052 3M CC01 2018 2018-07-09 TN -0.2107210313 + #> 461 2052 3M CC01 2018 2018-07-09 TP -2.3025850930 #> 462 2052 3M CC01 2018 2018-07-09 TURB 0.4054651081 #> 463 2052 3M CC01 2018 2018-08-06 CHLAC 1.1939224685 #> 464 2052 3M CC01 2018 2018-08-06 COLOR 3.4011973817 #> 465 2052 3M CC01 2018 2018-08-06 DO 0.8153648133 #> 466 2052 3M CC01 2018 2018-08-06 DOSAT 3.5945687746 #> 467 2052 3M CC01 2018 2018-08-06 NO23 -4.8283137373 I #> 468 2052 3M CC01 2018 2018-08-06 SALIN 3.4534735262 #> 469 2052 3M CC01 2018 2018-08-06 TKN -0.2231435513 #> 470 2052 3M CC01 2018 2018-08-06 TN -0.2181560098 + #> 471 2052 3M CC01 2018 2018-08-06 TP -2.5257286443 #> 472 2052 3M CC01 2018 2018-08-06 TURB 0.3364722366 #> 473 2052 3M CC01 2019 2019-02-04 CHLAC -0.3285040670 I #> 474 2052 3M CC01 2019 2019-02-04 COLOR 3.4339872045 #> 475 2052 3M CC01 2019 2019-02-04 DO 1.6213664833 #> 476 2052 3M CC01 2019 2019-02-04 DOSAT 4.1431347264 #> 477 2052 3M CC01 2019 2019-02-04 NO23 -3.7297014486 #> 478 2052 3M CC01 2019 2019-02-04 SALIN 3.1805507105 #> 479 2052 3M CC01 2019 2019-02-04 TKN -0.5978370008 #> 480 2052 3M CC01 2019 2019-02-04 TN -0.5551258827 + #> 481 2052 3M CC01 2019 2019-02-04 TP -2.5902671654 #> 482 2052 3M CC01 2019 2019-02-04 TURB 0.5306282511 #> 483 2052 3M CC01 2019 2019-03-04 CHLAC 0.4054651081 I #> 484 2052 3M CC01 2019 2019-03-04 COLOR 2.7080502011 #> 485 2052 3M CC01 2019 2019-03-04 DO 1.2781522025 #> 486 2052 3M CC01 2019 2019-03-04 DOSAT 3.9531649488 #> 487 2052 3M CC01 2019 2019-03-04 NO23 -4.8283137373 I #> 488 2052 3M CC01 2019 2019-03-04 TKN -0.7985076962 #> 489 2052 3M CC01 2019 2019-03-04 TN -0.7896580809 + #> 490 2052 3M CC01 2019 2019-03-04 TP -2.6172958378 #> 491 2052 3M CC01 2019 2019-03-04 TURB 0.4700036292 #> 492 2052 3M CC01 2019 2019-04-01 CHLAC 0.9162907319 #> 493 2052 3M CC01 2019 2019-04-01 COLOR 2.0014800002 #> 494 2052 3M CC01 2019 2019-04-01 DO 1.4883995841 #> 495 2052 3M CC01 2019 2019-04-01 DOSAT 4.1620032107 #> 496 2052 3M CC01 2019 2019-04-01 NO23 -5.5214609179 I #> 497 2052 3M CC01 2019 2019-04-01 SALIN 3.4094961845 #> 498 2052 3M CC01 2019 2019-04-01 TKN -0.9162907319 I #> 499 2052 3M CC01 2019 2019-04-01 TN -1.8078888512 + #> 500 2052 3M CC01 2019 2019-04-01 TP -2.5510464523 #> 501 2052 3M CC01 2019 2019-04-01 TURB 0.2623642645 #> 502 2052 3M CC01 2019 2019-06-03 CHLAC 0.4700036292 I #> 503 2052 3M CC01 2019 2019-06-03 COLOR 1.4586150227 I #> 504 2052 3M CC01 2019 2019-06-03 DO 0.3001045925 #> 505 2052 3M CC01 2019 2019-06-03 DOSAT 3.1267605360 #> 506 2052 3M CC01 2019 2019-06-03 NO23 -5.5214609179 I #> 507 2052 3M CC01 2019 2019-06-03 SALIN 3.5871235452 #> 508 2052 3M CC01 2019 2019-06-03 TKN -0.7133498879 #> 509 2052 3M CC01 2019 2019-06-03 TN -0.7052197618 + #> 510 2052 3M CC01 2019 2019-06-03 TP -3.1700856607 #> 511 2052 3M CC01 2019 2019-06-03 TURB 0.3364722366 #> 512 2052 3M CC01 2019 2019-07-01 CHLAC 0.5306282511 I #> 513 2052 3M CC01 2019 2019-07-01 COLOR 2.2823823857 #> 514 2052 3M CC01 2019 2019-07-01 DO 0.9593502213 #> 515 2052 3M CC01 2019 2019-07-01 DOSAT 3.7208625000 #> 516 2052 3M CC01 2019 2019-07-01 NO23 -5.1159958098 I #> 517 2052 3M CC01 2019 2019-07-01 SALIN 3.5237099561 #> 518 2052 3M CC01 2019 2019-07-01 TKN -0.5978370008 #> 519 2052 3M CC01 2019 2019-07-01 TN -0.5905905922 + #> 520 2052 3M CC01 2019 2019-07-01 TP -2.9957322736 #> 521 2052 3M CC01 2019 2019-07-01 TURB 0.4700036292 #> 522 2052 3M CC01 2019 2019-10-07 CHLAC 1.8562979904 #> 523 2052 3M CC01 2019 2019-10-07 COLOR 1.5260563035 I #> 524 2052 3M CC01 2019 2019-10-07 DO 1.1755733298 #> 525 2052 3M CC01 2019 2019-10-07 DOSAT 3.9120230054 #> 526 2052 3M CC01 2019 2019-10-07 NO23 -5.2983173665 I #> 527 2052 3M CC01 2019 2019-10-07 SALIN 3.5231199856 #> 528 2052 3M CC01 2019 2019-10-07 TKN -0.5108256238 #> 529 2052 3M CC01 2019 2019-10-07 TN -0.5041810810 + #> 530 2052 3M CC01 2019 2019-10-07 TP -2.5510464523 #> 531 2052 3M CC01 2019 2019-10-07 TURB 0.9555114450 #> 532 2052 3M CC01 2019 2019-11-04 CHLAC 1.0986122887 #> 533 2052 3M CC01 2019 2019-11-04 COLOR 1.4816045409 I #> 534 2052 3M CC01 2019 2019-11-04 DO 0.9042181506 #> 535 2052 3M CC01 2019 2019-11-04 DOSAT 3.6136169696 #> 536 2052 3M CC01 2019 2019-11-04 NO23 -4.5098600062 #> 537 2052 3M CC01 2019 2019-11-04 SALIN 3.5010427166 #> 538 2052 3M CC01 2019 2019-11-04 TKN -0.5276327421 #> 539 2052 3M CC01 2019 2019-11-04 TN -0.5091603444 + #> 540 2052 3M CC01 2019 2019-11-04 TP -2.6450754019 #> 541 2052 3M CC01 2019 2019-11-04 TURB 0.7884573604 #> 542 2052 3M CC01 2019 2019-11-04 CHLAC 1.2237754316 #> 543 2052 3M CC01 2019 2019-11-04 COLOR 1.5475625087 I #> 544 2052 3M CC01 2019 2019-11-04 NO23 -4.5098600062 #> 545 2052 3M CC01 2019 2019-11-04 TKN -0.5447271754 #> 546 2052 3M CC01 2019 2019-11-04 TN -0.5259392616 + #> 547 2052 3M CC01 2019 2019-11-04 TP -2.6036901858 #> 548 2052 3M CC01 2019 2019-11-04 TURB 0.9162907319 #> 549 2052 3M CC01 2019 2019-12-02 CHLAC 0.8754687374 I #> 550 2052 3M CC01 2019 2019-12-02 COLOR 0.9162907319 U #> 551 2052 3M CC01 2019 2019-12-02 NO23 -5.1159958098 I #> 552 2052 3M CC01 2019 2019-12-02 TKN -0.7985076962 #> 553 2052 3M CC01 2019 2019-12-02 TN -0.7896580809 + #> 554 2052 3M CC01 2019 2019-12-02 TP -2.9957322736 #> 555 2052 3M CC01 2019 2019-12-02 TURB 1.0296194172 #> 556 2052 3M CC01 2020 2020-01-06 CHLAC 0.1823215568 I #> 557 2052 3M CC01 2020 2020-01-06 COLOR 2.3978952728 #> 558 2052 3M CC01 2020 2020-01-06 DO 1.8196988379 #> 559 2052 3M CC01 2020 2020-01-06 DOSAT 4.3554259529 #> 560 2052 3M CC01 2020 2020-01-06 NO23 -3.9120230054 #> 561 2052 3M CC01 2020 2020-01-06 SALIN 3.4075107437 #> 562 2052 3M CC01 2020 2020-01-06 TKN -0.4942963218 #> 563 2052 3M CC01 2020 2020-01-06 TN -0.4620354596 + #> 564 2052 3M CC01 2020 2020-01-06 TP -2.4889146712 #> 565 2052 3M CC01 2020 2020-01-06 TURB 0.5877866649 #> 566 2052 3M CC01 2020 2020-02-03 CHLAC 0.4700036292 U #> 567 2052 3M CC01 2020 2020-02-03 COLOR 1.6677068206 I #> 568 2052 3M CC01 2020 2020-02-03 DO 1.7647307968 #> 569 2052 3M CC01 2020 2020-02-03 DOSAT 4.2959239356 #> 570 2052 3M CC01 2020 2020-02-03 NO23 -4.5098600062 #> 571 2052 3M CC01 2020 2020-02-03 SALIN 3.4992311219 #> 572 2052 3M CC01 2020 2020-02-03 TKN -0.7985076962 #> 573 2052 3M CC01 2020 2020-02-03 TN -0.7743572360 + #> 574 2052 3M CC01 2020 2020-02-03 TP -2.7488721956 #> 575 2052 3M CC01 2020 2020-02-03 TURB 0.6931471806 #> 576 2052 3M CC01 2020 2020-03-02 CHLAC 0.0953101798 I #> 577 2052 3M CC01 2020 2020-03-02 COLOR 1.5040773968 I #> 578 2052 3M CC01 2020 2020-03-02 DO 1.7191887764 #> 579 2052 3M CC01 2020 2020-03-02 DOSAT 4.3000027992 #> 580 2052 3M CC01 2020 2020-03-02 NO23 -5.5214609179 U #> 581 2052 3M CC01 2020 2020-03-02 SALIN 3.6730041050 #> 582 2052 3M CC01 2020 2020-03-02 TKN -0.9942522733 I #> 583 2052 3M CC01 2020 2020-03-02 TN -1.8201589437 + #> 584 2052 3M CC01 2020 2020-03-02 TP -2.8647040111 #> 585 2052 3M CC01 2020 2020-03-02 TURB 1.0647107370 #> 586 2052 3M CC01 2021 2021-01-04 CHLAC 0.5877866649 I #> 587 2052 3M CC01 2021 2021-01-04 COLOR 1.6094379124 I #> 588 2052 3M CC01 2021 2021-01-04 NO23 -4.1997050779 #> 589 2052 3M CC01 2021 2021-01-04 SALIN 3.4200191359 #> 590 2052 3M CC01 2021 2021-01-04 TKN -0.7339691751 #> 591 2052 3M CC01 2021 2021-01-04 TN -0.7031975164 + #> 592 2052 3M CC01 2021 2021-01-04 TP -2.6882475738 #> 593 2052 3M CC01 2021 2021-01-04 TURB 1.0296194172 A #> 594 2052 3M CC01 2021 2021-04-05 CHLAC 0.4054651081 I #> 595 2052 3M CC01 2021 2021-04-05 COLOR 1.7227665977 I #> 596 2052 3M CC01 2021 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2015 2015-09-08 CHLAC 1.1631508098 #> 925 2067 3M CC02 2015 2015-09-08 COLOR 3.3672958300 A #> 926 2067 3M CC02 2015 2015-09-08 DO 1.1631508098 #> 927 2067 3M CC02 2015 2015-09-08 DOSAT 3.8877303129 + #> 928 2067 3M CC02 2015 2015-09-08 NO23 -5.1159958098 I #> 929 2067 3M CC02 2015 2015-09-08 SALIN 3.4078419244 #> 930 2067 3M CC02 2015 2015-09-08 TKN -0.3424903089 #> 931 2067 3M CC02 2015 2015-09-08 TN -0.3368723166 + #> 932 2067 3M CC02 2015 2015-09-08 TP -1.3862943611 #> 933 2067 3M CC02 2015 2015-09-08 TURB 1.0296194172 #> 934 2067 3M CC02 2016 2016-02-01 CHLAC 0.6931471806 #> 935 2067 3M CC02 2016 2016-02-01 COLOR 3.2188758249 #> 936 2067 3M CC02 2016 2016-02-01 DO 1.4350845253 #> 937 2067 3M CC02 2016 2016-02-01 DOSAT 3.9665111907 + #> 938 2067 3M CC02 2016 2016-02-01 NO23 -3.7297014486 #> 939 2067 3M CC02 2016 2016-02-01 SALIN 3.3286266888 #> 940 2067 3M CC02 2016 2016-02-01 TKN -0.4942963218 #> 941 2067 3M CC02 2016 2016-02-01 TN -0.4557063245 + #> 942 2067 3M CC02 2016 2016-02-01 TP -2.3227878003 #> 943 2067 3M CC02 2016 2016-02-01 TURB 0.8754687374 #> 944 2067 3M CC02 2016 2016-03-07 CHLAC 0.8754687374 #> 945 2067 3M CC02 2016 2016-03-07 COLOR 3.2188758249 #> 946 2067 3M CC02 2016 2016-03-07 NO23 -4.1351665567 #> 947 2067 3M CC02 2016 2016-03-07 SALIN 3.3357695763 #> 948 2067 3M CC02 2016 2016-03-07 TKN -0.2357223335 #> 949 2067 3M CC02 2016 2016-03-07 TN -0.2156715365 + #> 950 2067 3M CC02 2016 2016-03-07 TP -2.3025850930 #> 951 2067 3M CC02 2016 2016-03-07 TURB 1.9315214116 #> 952 2067 3M CC02 2016 2016-04-04 CHLAC 0.3364722366 I #> 953 2067 3M CC02 2016 2016-04-04 COLOR 2.6390573296 #> 954 2067 3M CC02 2016 2016-04-04 DO 1.1314021115 #> 955 2067 3M CC02 2016 2016-04-04 DOSAT 3.7400477407 + #> 956 2067 3M CC02 2016 2016-04-04 NO23 -3.9120230054 #> 957 2067 3M CC02 2016 2016-04-04 SALIN 3.3809946743 #> 958 2067 3M CC02 2016 2016-04-04 TKN -0.7133498879 #> 959 2067 3M CC02 2016 2016-04-04 TN -0.6733445533 + #> 960 2067 3M CC02 2016 2016-04-04 TP -2.3434070875 #> 961 2067 3M CC02 2016 2016-04-04 TURB 1.1939224685 A #> 962 2067 3M CC02 2016 2016-05-02 CHLAC 0.0953101798 I #> 963 2067 3M CC02 2016 2016-05-02 COLOR 2.4849066498 #> 964 2067 3M CC02 2016 2016-05-02 DO 0.7419373447 #> 965 2067 3M CC02 2016 2016-05-02 DOSAT 3.4812400893 + #> 966 2067 3M CC02 2016 2016-05-02 NO23 -4.9618451299 I #> 967 2067 3M CC02 2016 2016-05-02 SALIN 3.5582011305 #> 968 2067 3M CC02 2016 2016-05-02 TKN -0.7339691751 #> 969 2067 3M CC02 2016 2016-05-02 TN -0.7256703723 + #> 970 2067 3M CC02 2016 2016-05-02 TP -2.5257286443 #> 971 2067 3M CC02 2016 2016-05-02 TURB 0.9555114450 #> 972 2067 3M CC02 2016 2016-06-06 CHLAC 0.2623642645 I #> 973 2067 3M CC02 2016 2016-06-06 COLOR 3.3672958300 #> 974 2067 3M CC02 2016 2016-06-06 DO 0.7884573604 #> 975 2067 3M CC02 2016 2016-06-06 DOSAT 3.5351453542 + #> 976 2067 3M CC02 2016 2016-06-06 NO23 -4.8283137373 I #> 977 2067 3M CC02 2016 2016-06-06 SALIN 3.4934726578 #> 978 2067 3M CC02 2016 2016-06-06 TKN -0.7339691751 #> 979 2067 3M CC02 2016 2016-06-06 TN -0.7256703723 + #> 980 2067 3M CC02 2016 2016-06-06 TP -1.0788096614 #> 981 2067 3M CC02 2016 2016-06-06 TURB 0.4700036292 #> 982 2067 3M CC02 2016 2016-07-05 CHLAC 1.7047480922 #> 983 2067 3M CC02 2016 2016-07-05 COLOR 2.8332133441 #> 984 2067 3M CC02 2016 2016-07-05 DO 0.0000000000 #> 985 2067 3M CC02 2016 2016-07-05 DOSAT 2.7788192720 + #> 986 2067 3M CC02 2016 2016-07-05 NO23 -4.7105307016 I #> 987 2067 3M CC02 2016 2016-07-05 SALIN 3.5174978374 #> 988 2067 3M CC02 2016 2016-07-05 TKN 0.6418538862 #> 989 2067 3M CC02 2016 2016-07-05 TN 0.6439569364 + #> 990 2067 3M CC02 2016 2016-07-05 TP -1.7147984281 #> 991 2067 3M CC02 2016 2016-07-05 TURB 2.9957322736 #> 992 2067 3M CC02 2016 2016-08-01 CHLAC 0.8754687374 #> 993 2067 3M CC02 2016 2016-08-01 COLOR 2.7080502011 #> 994 2067 3M CC02 2016 2016-08-01 DO 0.4054651081 #> 995 2067 3M CC02 2016 2016-08-01 DOSAT 3.1696855807 + #> 996 2067 3M CC02 2016 2016-08-01 NO23 -4.3428059215 #> 997 2067 3M CC02 2016 2016-08-01 SALIN 3.4688560301 #> 998 2067 3M CC02 2016 2016-08-01 TKN -0.6161861394 #> 999 2067 3M CC02 2016 2016-08-01 TN -0.5923972775 + #> 1000 2067 3M CC02 2016 2016-08-01 TP -2.6310891600 #> 1001 2067 3M CC02 2016 2016-08-01 TURB 0.9932517730 #> 1002 2067 3M CC02 2016 2016-10-03 CHLAC 1.1631508098 #> 1003 2067 3M CC02 2016 2016-10-03 COLOR 4.1271343850 #> 1004 2067 3M CC02 2016 2016-10-03 DO 0.8754687374 #> 1005 2067 3M CC02 2016 2016-10-03 DOSAT 3.5174978374 + #> 1006 2067 3M CC02 2016 2016-10-03 NO23 -4.6051701860 #> 1007 2067 3M CC02 2016 2016-10-03 SALIN 2.7343675094 #> 1008 2067 3M CC02 2016 2016-10-03 TKN -0.1392620673 #> 1009 2067 3M CC02 2016 2016-10-03 TN -0.1278333715 + #> 1010 2067 3M CC02 2016 2016-10-03 TP -2.4304184645 #> 1011 2067 3M CC02 2016 2016-10-03 TURB 0.7419373447 #> 1012 2067 3M CC02 2016 2016-12-05 CHLAC 0.6418538862 I #> 1013 2067 3M CC02 2016 2016-12-05 COLOR 0.9162907319 U #> 1014 2067 3M CC02 2016 2016-12-05 DO 1.3862943611 #> 1015 2067 3M CC02 2016 2016-12-05 DOSAT 4.0289167569 + #> 1016 2067 3M CC02 2016 2016-12-05 NO23 -4.1351665567 #> 1017 2067 3M CC02 2016 2016-12-05 SALIN 3.5438536821 #> 1018 2067 3M CC02 2016 2016-12-05 TKN -0.3424903089 #> 1019 2067 3M CC02 2016 2016-12-05 TN -0.3202052642 + #> 1020 2067 3M CC02 2016 2016-12-05 TP -2.5770219387 #> 1021 2067 3M CC02 2016 2016-12-05 TURB 1.8870696490 A #> 1022 2067 3M CC02 2017 2017-01-03 CHLAC 1.0986122887 #> 1023 2067 3M CC02 2017 2017-01-03 COLOR 1.5686159179 I #> 1024 2067 3M CC02 2017 2017-01-03 DO 1.3083328197 #> 1025 2067 3M CC02 2017 2017-01-03 DOSAT 3.9512437186 + #> 1026 2067 3M CC02 2017 2017-01-03 NO23 -3.9633162998 #> 1027 2067 3M CC02 2017 2017-01-03 SALIN 3.5438536821 #> 1028 2067 3M CC02 2017 2017-01-03 TKN -0.4780358009 #> 1029 2067 3M CC02 2017 2017-01-03 TN -0.4478508246 + #> 1030 2067 3M CC02 2017 2017-01-03 TP -2.3025850930 #> 1031 2067 3M CC02 2017 2017-01-03 TURB 2.3025850930 #> 1032 2067 3M CC02 2017 2017-02-06 CHLAC 0.5306282511 #> 1033 2067 3M CC02 2017 2017-02-06 COLOR 3.3322045102 A #> 1034 2067 3M CC02 2017 2017-02-06 DO 1.0986122887 #> 1035 2067 3M CC02 2017 2017-02-06 DOSAT 3.6988297850 + #> 1036 2067 3M CC02 2017 2017-02-06 NO23 -4.1997050779 #> 1037 2067 3M CC02 2017 2017-02-06 SALIN 3.5234150144 #> 1038 2067 3M CC02 2017 2017-02-06 TKN -0.5108256238 #> 1039 2067 3M CC02 2017 2017-02-06 TN -0.4861330112 + #> 1040 2067 3M CC02 2017 2017-02-06 TP -2.5383074265 #> 1041 2067 3M CC02 2017 2017-02-06 TURB 0.9162907319 #> 1042 2067 3M CC02 2017 2017-03-06 CHLAC 0.2623642645 I #> 1043 2067 3M CC02 2017 2017-03-06 COLOR 2.7080502011 #> 1044 2067 3M CC02 2017 2017-03-06 DO 1.3862943611 #> 1045 2067 3M CC02 2017 2017-03-06 DOSAT 3.9778107460 + #> 1046 2067 3M CC02 2017 2017-03-06 NO23 -4.9618451299 I #> 1047 2067 3M CC02 2017 2017-03-06 SALIN 3.5174978374 #> 1048 2067 3M CC02 2017 2017-03-06 TKN -0.5798184953 #> 1049 2067 3M CC02 2017 2017-03-06 TN -0.5727010275 + #> 1050 2067 3M CC02 2017 2017-03-06 TP -2.6882475738 #> 1051 2067 3M CC02 2017 2017-03-06 TURB 1.3083328197 #> 1052 2067 3M CC02 2017 2017-04-03 CHLAC 0.6931471806 #> 1053 2067 3M CC02 2017 2017-04-03 COLOR 2.3978952728 #> 1054 2067 3M CC02 2017 2017-04-03 DO 1.2809338455 #> 1055 2067 3M CC02 2017 2017-04-03 DOSAT 4.0000338828 + #> 1056 2067 3M CC02 2017 2017-04-03 NO23 -4.9618451299 I #> 1057 2067 3M CC02 2017 2017-04-03 SALIN 3.5835189385 #> 1058 2067 3M CC02 2017 2017-04-03 TKN -0.4155154440 #> 1059 2067 3M CC02 2017 2017-04-03 TN -0.4094731295 + #> 1060 2067 3M CC02 2017 2017-04-03 TP -2.6592600369 #> 1061 2067 3M CC02 2017 2017-04-03 TURB 1.3862943611 #> 1062 2067 3M CC02 2017 2017-05-01 CHLAC 0.7884573604 #> 1063 2067 3M CC02 2017 2017-05-01 COLOR 1.5040773968 I #> 1064 2067 3M CC02 2017 2017-05-01 DO 1.2527629685 #> 1065 2067 3M CC02 2017 2017-05-01 DOSAT 3.9852734672 + #> 1066 2067 3M CC02 2017 2017-05-01 NO23 -5.5214609179 U #> 1067 2067 3M CC02 2017 2017-05-01 SALIN 3.5918177413 #> 1068 2067 3M CC02 2017 2017-05-01 TKN -0.4462871026 #> 1069 2067 3M CC02 2017 2017-05-01 TN -0.4431669753 + #> 1070 2067 3M CC02 2017 2017-05-01 TP -3.1010927892 #> 1071 2067 3M CC02 2017 2017-05-01 TURB 0.8754687374 #> 1072 2067 3M CC02 2017 2017-07-10 CHLAC 1.0296194172 #> 1073 2067 3M CC02 2017 2017-07-10 COLOR 3.1354942159 #> 1074 2067 3M CC02 2017 2017-07-10 DO 1.1314021115 #> 1075 2067 3M CC02 2017 2017-07-10 DOSAT 3.8938590348 + #> 1076 2067 3M CC02 2017 2017-07-10 NO23 -4.4228486292 #> 1077 2067 3M CC02 2017 2017-07-10 SALIN 3.3978584804 #> 1078 2067 3M CC02 2017 2017-07-10 TKN -0.4620354596 #> 1079 2067 3M CC02 2017 2017-07-10 TN -0.4431669753 + #> 1080 2067 3M CC02 2017 2017-07-10 TP -2.7181005370 #> 1081 2067 3M CC02 2017 2017-07-10 TURB 1.4586150227 #> 1082 2067 3M CC02 2017 2017-08-07 CHLAC 1.1631508098 #> 1083 2067 3M CC02 2017 2017-08-07 COLOR 3.8712010109 #> 1084 2067 3M CC02 2017 2017-08-07 DO 0.8754687374 #> 1085 2067 3M CC02 2017 2017-08-07 DOSAT 3.6216707044 + #> 1086 2067 3M CC02 2017 2017-08-07 NO23 -4.5098600062 #> 1087 2067 3M CC02 2017 2017-08-07 SALIN 3.2542429687 #> 1088 2067 3M CC02 2017 2017-08-07 TKN -0.4307829161 #> 1089 2067 3M CC02 2017 2017-08-07 TN -0.4140014391 + #> 1090 2067 3M CC02 2017 2017-08-07 TP -2.5639498571 #> 1091 2067 3M CC02 2017 2017-08-07 TURB 0.5306282511 #> 1092 2067 3M CC02 2017 2017-10-02 CHLAC 1.0986122887 #> 1093 2067 3M CC02 2017 2017-10-02 COLOR 3.6888794541 #> 1094 2067 3M CC02 2017 2017-10-02 NO23 -5.2983173665 I #> 1095 2067 3M CC02 2017 2017-10-02 TKN -0.5276327421 #> 1096 2067 3M CC02 2017 2017-10-02 TN -0.5208759596 + #> 1097 2067 3M CC02 2017 2017-10-02 TP -2.3025850930 #> 1098 2067 3M CC02 2017 2017-10-02 TURB 1.0296194172 #> 1099 2067 3M CC02 2017 2017-11-06 CHLAC 0.9162907319 #> 1100 2067 3M CC02 2017 2017-11-06 COLOR 3.2188758249 #> 1101 2067 3M CC02 2017 2017-11-06 DO 1.2527629685 #> 1102 2067 3M CC02 2017 2017-11-06 DOSAT 3.8938590348 + #> 1103 2067 3M CC02 2017 2017-11-06 NO23 -4.6051701860 #> 1104 2067 3M CC02 2017 2017-11-06 SALIN 3.3499040873 #> 1105 2067 3M CC02 2017 2017-11-06 TKN -0.4620354596 #> 1106 2067 3M CC02 2017 2017-11-06 TN -0.4462871026 + #> 1107 2067 3M CC02 2017 2017-11-06 TP -2.6036901858 #> 1108 2067 3M CC02 2017 2017-11-06 TURB 0.8754687374 A #> 1109 2067 3M CC02 2017 2017-12-04 CHLAC 0.7884573604 #> 1110 2067 3M CC02 2017 2017-12-04 COLOR 2.5649493575 #> 1111 2067 3M CC02 2017 2017-12-04 DO 1.3862943611 #> 1112 2067 3M CC02 2017 2017-12-04 DOSAT 4.0181832013 + #> 1113 2067 3M CC02 2017 2017-12-04 NO23 -4.9618451299 I #> 1114 2067 3M CC02 2017 2017-12-04 SALIN 3.5025498759 #> 1115 2067 3M CC02 2017 2017-12-04 TKN -0.4780358009 #> 1116 2067 3M CC02 2017 2017-12-04 TN -0.4716049106 + #> 1117 2067 3M CC02 2017 2017-12-04 TP -2.6882475738 #> 1118 2067 3M CC02 2017 2017-12-04 TURB 1.3862943611 A #> 1119 2067 3M CC02 2018 2018-01-02 CHLAC 0.9932517730 #> 1120 2067 3M CC02 2018 2018-01-02 COLOR 2.5649493575 #> 1121 2067 3M CC02 2018 2018-01-02 DO 0.7884573604 #> 1122 2067 3M CC02 2018 2018-01-02 DOSAT 3.2580965380 + #> 1123 2067 3M CC02 2018 2018-01-02 NO23 -4.2686979494 #> 1124 2067 3M CC02 2018 2018-01-02 SALIN 3.4688560301 #> 1125 2067 3M CC02 2018 2018-01-02 TKN -0.6348782724 #> 1126 2067 3M CC02 2018 2018-01-02 TN -0.6088060321 + #> 1127 2067 3M CC02 2018 2018-01-02 TP -2.3434070875 #> 1128 2067 3M CC02 2018 2018-01-02 TURB 1.5260563035 #> 1129 2067 3M CC02 2018 2018-02-05 CHLAC 0.0953101798 I #> 1130 2067 3M CC02 2018 2018-02-05 COLOR 2.6390573296 #> 1131 2067 3M CC02 2018 2018-02-05 DO 1.5040773968 #> 1132 2067 3M CC02 2018 2018-02-05 DOSAT 4.0724397268 + #> 1133 2067 3M CC02 2018 2018-02-05 NO23 -4.1351665567 #> 1134 2067 3M CC02 2018 2018-02-05 SALIN 3.3877743613 #> 1135 2067 3M CC02 2018 2018-02-05 TKN -0.7339691751 #> 1136 2067 3M CC02 2018 2018-02-05 TN -0.7011793523 + #> 1137 2067 3M CC02 2018 2018-02-05 TP -2.7030626596 #> 1138 2067 3M CC02 2018 2018-02-05 TURB 1.2809338455 #> 1139 2067 3M CC02 2018 2018-03-05 CHLAC 0.6931471806 #> 1140 2067 3M CC02 2018 2018-03-05 COLOR 2.0014800002 #> 1141 2067 3M CC02 2018 2018-03-05 DO 1.5475625087 #> 1142 2067 3M CC02 2018 2018-03-05 DOSAT 4.1351665567 + #> 1143 2067 3M CC02 2018 2018-03-05 NO23 -5.1159958098 I #> 1144 2067 3M CC02 2018 2018-03-05 SALIN 3.5835189385 #> 1145 2067 3M CC02 2018 2018-03-05 TKN -0.7339691751 #> 1146 2067 3M CC02 2018 2018-03-05 TN -0.7256703723 + #> 1147 2067 3M CC02 2018 2018-03-05 TP -2.7333680091 #> 1148 2067 3M CC02 2018 2018-03-05 TURB 1.5892352051 A #> 1149 2067 3M CC02 2018 2018-04-02 CHLAC 1.3350010667 A #> 1150 2067 3M CC02 2018 2018-04-02 COLOR 1.4816045409 I #> 1151 2067 3M CC02 2018 2018-04-02 DO 1.4109869737 #> 1152 2067 3M CC02 2018 2018-04-02 DOSAT 4.0926765051 + #> 1153 2067 3M CC02 2018 2018-04-02 NO23 -4.5098600062 #> 1154 2067 3M CC02 2018 2018-04-02 SALIN 3.5945687746 #> 1155 2067 3M CC02 2018 2018-04-02 TKN -0.2613647641 #> 1156 2067 3M CC02 2018 2018-04-02 TN -0.2471801291 + #> 1157 2067 3M CC02 2018 2018-04-02 TP -2.1202635362 #> 1158 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2067 3M CC02 2018 2018-07-09 TN -0.5208759596 + #> 1177 2067 3M CC02 2018 2018-07-09 TURB 0.9932517730 #> 1178 2067 3M CC02 2018 2018-08-06 CHLAC 1.8562979904 #> 1179 2067 3M CC02 2018 2018-08-06 COLOR 3.5263605246 A #> 1180 2067 3M CC02 2018 2018-08-06 DO 0.8586616190 #> 1181 2067 3M CC02 2018 2018-08-06 DOSAT 3.6270040504 #> 1182 2067 3M CC02 2018 2018-08-06 NO23 -5.1159958098 I #> 1183 2067 3M CC02 2018 2018-08-06 SALIN 3.4968105459 #> 1184 2067 3M CC02 2018 2018-08-06 TKN -0.2107210313 #> 1185 2067 3M CC02 2018 2018-08-06 TN -0.2057949130 + #> 1186 2067 3M CC02 2018 2018-08-06 TP -2.3968957725 #> 1187 2067 3M CC02 2018 2018-08-06 TURB 1.0296194172 A #> 1188 2067 3M CC02 2019 2019-02-04 CHLAC -0.1984509387 I #> 1189 2067 3M CC02 2019 2019-02-04 COLOR 3.1354942159 #> 1190 2067 3M CC02 2019 2019-02-04 DO 1.3323660191 #> 1191 2067 3M CC02 2019 2019-02-04 DOSAT 3.8999504242 #> 1192 2067 3M CC02 2019 2019-02-04 NO23 -4.1997050779 #> 1193 2067 3M CC02 2019 2019-02-04 SALIN 3.2669037939 #> 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-2.9759296463 #> 1212 2067 3M CC02 2019 2019-04-01 TURB 0.4700036292 #> 1213 2067 3M CC02 2019 2019-05-06 CHLAC 0.5877866649 I #> 1214 2067 3M CC02 2019 2019-05-06 COLOR 2.2617630985 #> 1215 2067 3M CC02 2019 2019-05-06 DO 0.5877866649 #> 1216 2067 3M CC02 2019 2019-05-06 DOSAT 3.3250360207 #> 1217 2067 3M CC02 2019 2019-05-06 NO23 -4.8283137373 I #> 1218 2067 3M CC02 2019 2019-05-06 SALIN 3.5522002552 #> 1219 2067 3M CC02 2019 2019-05-06 TKN -0.5108256238 #> 1220 2067 3M CC02 2019 2019-05-06 TN -0.5041810810 + #> 1221 2067 3M CC02 2019 2019-05-06 TP -2.7030626596 #> 1222 2067 3M CC02 2019 2019-05-06 TURB 1.0647107370 #> 1223 2067 3M CC02 2019 2019-06-03 CHLAC 0.6418538862 I #> 1224 2067 3M CC02 2019 2019-06-03 COLOR 1.3350010667 I #> 1225 2067 3M CC02 2019 2019-06-03 DO 0.4700036292 #> 1226 2067 3M CC02 2019 2019-06-03 DOSAT 3.2771447330 #> 1227 2067 3M CC02 2019 2019-06-03 NO23 -4.3428059215 #> 1228 2067 3M CC02 2019 2019-06-03 SALIN 3.5882300460 #> 1229 2067 3M CC02 2019 2019-06-03 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#> 1373 2067 3M CC02 2021 2021-03-01 TURB 1.2527629685 #> 1374 2067 3M CC02 2021 2021-04-05 TN -1.8078888512 + #> 1375 2067 3M CC02 2021 2021-04-05 CHLAC 0.4054651081 I #> 1376 2067 3M CC02 2021 2021-04-05 COLOR 1.9021075264 #> 1377 2067 3M CC02 2021 2021-04-05 DO 1.1631508098 #> 1378 2067 3M CC02 2021 2021-04-05 DOSAT 3.7977338590 #> 1379 2067 3M CC02 2021 2021-04-05 NO23 -4.9618451299 I #> 1380 2067 3M CC02 2021 2021-04-05 SALIN 3.5325179990 #> 1381 2067 3M CC02 2021 2021-04-05 TKN -0.9416085399 I #> 1382 2067 3M CC02 2021 2021-04-05 TP -2.7030626596 #> 1383 2067 3M CC02 2021 2021-04-05 TURB 1.1939224685 #> 1384 2067 3M CC02 2021 2021-05-03 CHLAC 0.2623642645 I #> 1385 2067 3M CC02 2021 2021-05-03 COLOR 1.9021075264 #> 1386 2067 3M CC02 2021 2021-05-03 DO 0.8064758659 #> 1387 2067 3M CC02 2021 2021-05-03 DOSAT 3.5553480615 #> 1388 2067 3M CC02 2021 2021-05-03 NO23 -5.5214609179 I #> 1389 2067 3M CC02 2021 2021-05-03 SALIN 3.5487549460 #> 1390 2067 3M CC02 2021 2021-05-03 TKN -0.8439700703 #> 1391 2067 3M CC02 2021 2021-05-03 TN -0.8347107449 + #> 1392 2067 3M CC02 2021 2021-05-03 TP -2.8134107168 #> 1393 2067 3M CC02 2021 2021-05-03 TURB 1.2527629685 #> 1394 2067 3M CC02 2021 2021-06-07 CHLAC 0.5306282511 I #> 1395 2067 3M CC02 2021 2021-06-07 COLOR 1.7749523509 I #> 1396 2067 3M CC02 2021 2021-06-07 DO 1.1999647829 #> 1397 2067 3M CC02 2021 2021-06-07 DOSAT 3.9852734672 #> 1398 2067 3M CC02 2021 2021-06-07 NO23 -4.8283137373 I #> 1399 2067 3M CC02 2021 2021-06-07 SALIN 3.6103772260 #> 1400 2067 3M CC02 2021 2021-06-07 TKN -0.6733445533 #> 1401 2067 3M CC02 2021 2021-06-07 TN -0.6655320135 + #> 1402 2067 3M CC02 2021 2021-06-07 TP -3.0159349809 #> 1403 2067 3M CC02 2021 2021-06-07 TURB 0.6418538862 #> 1404 2067 3M CC02 2021 2021-08-02 CHLAC 2.0668627595 #> 1405 2067 3M CC02 2021 2021-08-02 COLOR 4.2626798770 #> 1406 2067 3M CC02 2021 2021-08-02 DO 0.5128236264 #> 1407 2067 3M CC02 2021 2021-08-02 DOSAT 3.2657594108 #> 1408 2067 3M CC02 2021 2021-08-02 NO23 -5.5214609179 U #> 1409 2067 3M CC02 2021 2021-08-02 SALIN 3.2846635654 #> 1410 2067 3M CC02 2021 2021-08-02 TKN -0.1984509387 #> 1411 2067 3M CC02 2021 2021-08-02 TN -0.1960148839 + #> 1412 2067 3M CC02 2021 2021-08-02 TP -2.5639498571 #> 1413 2067 3M CC02 2021 2021-08-02 TURB 0.9555114450 #> 1414 2067 3M CC02 2021 2021-09-07 CHLAC 2.1633230257 #> 1415 2067 3M CC02 2021 2021-09-07 COLOR 3.7841896339 #> 1416 2067 3M CC02 2021 2021-09-07 DO 1.6863989536 #> 1417 2067 3M CC02 2021 2021-09-07 DOSAT 4.4236483094 #> 1418 2067 3M CC02 2021 2021-09-07 NO23 -5.2983173665 I #> 1419 2067 3M CC02 2021 2021-09-07 SALIN 3.2771447330 #> 1420 2067 3M CC02 2021 2021-09-07 TKN -0.1863295782 #> 1421 2067 3M CC02 2021 2021-09-07 TN -0.1815218766 + #> 1422 2067 3M CC02 2021 2021-09-07 TP -2.6310891600 #> 1423 2067 3M CC02 2021 2021-09-07 TURB 0.9932517730 #> 1424 2067 3M CC02 2021 2021-10-04 CHLAC 1.8718021769 #> 1425 2067 3M CC02 2021 2021-10-04 COLOR 2.9444389792 #> 1426 2067 3M CC02 2021 2021-10-04 DO 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2068 3M CC03 2014 2014-08-04 TP -2.9565115604 #> 1732 2068 3M CC03 2014 2014-08-04 TURB 1.2809338455 #> 1733 2068 3M CC03 2014 2014-09-08 CHLAC 2.3025850930 #> 1734 2068 3M CC03 2014 2014-09-08 COLOR 3.2958368660 #> 1735 2068 3M CC03 2014 2014-09-08 DO -1.2039728043 #> 1736 2068 3M CC03 2014 2014-09-08 DOSAT 1.5040773968 + #> 1737 2068 3M CC03 2014 2014-09-08 NO23 -5.5214609179 U #> 1738 2068 3M CC03 2014 2014-09-08 SALIN 3.4011973817 #> 1739 2068 3M CC03 2014 2014-09-08 TKN -0.1508228897 #> 1740 2068 3M CC03 2014 2014-09-08 TN -0.1485000083 + #> 1741 2068 3M CC03 2014 2014-09-08 TP -2.8824035882 #> 1742 2068 3M CC03 2014 2014-09-08 TURB 1.1631508098 #> 1743 2068 3M CC03 2014 2014-10-06 CHLAC 2.3025850930 #> 1744 2068 3M CC03 2014 2014-10-06 COLOR 4.1588830834 #> 1745 2068 3M CC03 2014 2014-10-06 DO 0.6931471806 #> 1746 2068 3M CC03 2014 2014-10-06 DOSAT 3.2464909919 + #> 1747 2068 3M CC03 2014 2014-10-06 NO23 -4.7105307016 I #> 1748 2068 3M CC03 2014 2014-10-06 SALIN 2.7080502011 #> 1749 2068 3M CC03 2014 2014-10-06 TKN -0.1165338163 #> 1750 2068 3M CC03 2014 2014-10-06 TN -0.1120495038 + #> 1751 2068 3M CC03 2014 2014-10-06 TP -1.9661128564 #> 1752 2068 3M CC03 2014 2014-10-06 TURB 1.1631508098 #> 1753 2068 3M CC03 2014 2014-11-03 CHLAC 2.3978952728 #> 1754 2068 3M CC03 2014 2014-11-03 COLOR 3.5835189385 #> 1755 2068 3M CC03 2014 2014-11-03 DO 1.3862943611 #> 1756 2068 3M CC03 2014 2014-11-03 DOSAT 3.8543938926 + #> 1757 2068 3M CC03 2014 2014-11-03 NO23 -4.5098600062 #> 1758 2068 3M CC03 2014 2014-11-03 SALIN 3.1612467120 #> 1759 2068 3M CC03 2014 2014-11-03 TKN -0.1743533871 #> 1760 2068 3M CC03 2014 2014-11-03 TN -0.1613431504 + #> 1761 2068 3M CC03 2014 2014-11-03 TP -2.6036901858 #> 1762 2068 3M CC03 2014 2014-11-03 TURB 1.0647107370 #> 1763 2068 3M CC03 2015 2015-01-05 CHLAC 2.0281482473 #> 1764 2068 3M CC03 2015 2015-01-05 COLOR 3.2188758249 #> 1765 2068 3M CC03 2015 2015-01-05 DO 0.9162907319 #> 1766 2068 3M CC03 2015 2015-01-05 DOSAT 3.5438536821 + #> 1767 2068 3M CC03 2015 2015-01-05 NO23 -4.4228486292 #> 1768 2068 3M CC03 2015 2015-01-05 SALIN 3.2995337279 #> 1769 2068 3M CC03 2015 2015-01-05 TKN -0.0512932944 #> 1770 2068 3M CC03 2015 2015-01-05 TN -0.0387408283 + #> 1771 2068 3M CC03 2015 2015-01-05 TP -2.5383074265 #> 1772 2068 3M CC03 2015 2015-01-05 TURB 0.6418538862 #> 1773 2068 3M CC03 2015 2015-02-02 CHLAC 0.6418538862 #> 1774 2068 3M CC03 2015 2015-02-02 COLOR 2.3025850930 #> 1775 2068 3M CC03 2015 2015-02-02 DO 1.4109869737 #> 1776 2068 3M CC03 2015 2015-02-02 DOSAT 3.9778107460 + #> 1777 2068 3M CC03 2015 2015-02-02 NO23 -5.1159958098 I #> 1778 2068 3M CC03 2015 2015-02-02 SALIN 3.3911470458 #> 1779 2068 3M CC03 2015 2015-02-02 TKN -0.7765287895 #> 1780 2068 3M CC03 2015 2015-02-02 TN -0.7678707268 + #> 1781 2068 3M CC03 2015 2015-02-02 TP -2.9957322736 #> 1782 2068 3M CC03 2015 2015-02-02 TURB 0.3364722366 #> 1783 2068 3M CC03 2015 2015-03-02 CHLAC 1.6677068206 A #> 1784 2068 3M CC03 2015 2015-03-02 COLOR 3.1354942159 #> 1785 2068 3M CC03 2015 2015-03-02 DO 0.9932517730 #> 1786 2068 3M CC03 2015 2015-03-02 DOSAT 3.5862928653 + #> 1787 2068 3M CC03 2015 2015-03-02 NO23 -4.5098600062 #> 1788 2068 3M CC03 2015 2015-03-02 SALIN 3.1311369106 #> 1789 2068 3M CC03 2015 2015-03-02 TKN -0.4780358009 #> 1790 2068 3M CC03 2015 2015-03-02 TN -0.4604494164 + #> 1791 2068 3M CC03 2015 2015-03-02 TP -2.8824035882 #> 1792 2068 3M CC03 2015 2015-03-02 TURB 0.3364722366 #> 1793 2068 3M CC03 2015 2015-04-06 CHLAC 0.8754687374 #> 1794 2068 3M CC03 2015 2015-04-06 COLOR 3.0910424534 #> 1795 2068 3M CC03 2015 2015-04-06 DO -0.1053605157 #> 1796 2068 3M CC03 2015 2015-04-06 DOSAT 2.5494451709 + #> 1797 2068 3M CC03 2015 2015-04-06 NO23 -5.5214609179 U #> 1798 2068 3M CC03 2015 2015-04-06 SALIN 3.4011973817 #> 1799 2068 3M CC03 2015 2015-04-06 TKN -0.3566749439 #> 1800 2068 3M CC03 2015 2015-04-06 TN -0.3538218750 + #> 1801 2068 3M CC03 2015 2015-04-06 TP -3.2188758249 #> 1802 2068 3M CC03 2015 2015-04-06 TURB 0.4700036292 #> 1803 2068 3M CC03 2015 2015-05-04 CHLAC 0.9932517730 #> 1804 2068 3M CC03 2015 2015-05-04 COLOR 3.2188758249 #> 1805 2068 3M CC03 2015 2015-05-04 DO 0.1823215568 #> 1806 2068 3M CC03 2015 2015-05-04 DOSAT 2.8622008809 + #> 1807 2068 3M CC03 2015 2015-05-04 NO23 -4.8283137373 I #> 1808 2068 3M CC03 2015 2015-05-04 SALIN 3.4904285154 #> 1809 2068 3M CC03 2015 2015-05-04 TKN -0.3856624808 #> 1810 2068 3M CC03 2015 2015-05-04 TN -0.3797973614 + #> 1811 2068 3M CC03 2015 2015-05-04 TP -3.2968373663 #> 1812 2068 3M CC03 2015 2015-05-04 TURB 0.6931471806 #> 1813 2068 3M CC03 2015 2015-06-01 CHLAC 1.7749523509 #> 1814 2068 3M CC03 2015 2015-06-01 COLOR 3.3322045102 #> 1815 2068 3M CC03 2015 2015-06-01 DO -0.6931471806 #> 1816 2068 3M CC03 2015 2015-06-01 DOSAT 2.0149030205 + #> 1817 2068 3M CC03 2015 2015-06-01 NO23 -5.1159958098 I #> 1818 2068 3M CC03 2015 2015-06-01 SALIN 3.3945083935 #> 1819 2068 3M CC03 2015 2015-06-01 TKN -0.1625189295 #> 1820 2068 3M CC03 2015 2015-06-01 TN -0.1578240852 + #> 1821 2068 3M CC03 2015 2015-06-01 TP -2.9759296463 #> 1822 2068 3M CC03 2015 2015-06-01 TURB 0.9555114450 #> 1823 2068 3M CC03 2015 2015-08-03 CHLAC 3.1354942159 #> 1824 2068 3M CC03 2015 2015-08-03 COLOR 4.1108738642 #> 1825 2068 3M CC03 2015 2015-08-03 DO -0.6931471806 #> 1826 2068 3M CC03 2015 2015-08-03 DOSAT 1.9021075264 + #> 1827 2068 3M CC03 2015 2015-08-03 NO23 -4.6051701860 I #> 1828 2068 3M CC03 2015 2015-08-03 SALIN 2.3887627892 #> 1829 2068 3M CC03 2015 2015-08-03 TKN 0.3364722366 #> 1830 2068 3M CC03 2015 2015-08-03 TN 0.3393253056 + #> 1831 2068 3M CC03 2015 2015-08-03 TP -2.4418471603 #> 1832 2068 3M CC03 2015 2015-08-03 TURB 1.5892352051 #> 1833 2068 3M CC03 2015 2015-09-08 CHLAC 1.7227665977 #> 1834 2068 3M CC03 2015 2015-09-08 COLOR 3.8286413965 #> 1835 2068 3M CC03 2015 2015-09-08 DO 0.0000000000 #> 1836 2068 3M CC03 2015 2015-09-08 DOSAT 2.6602595373 + #> 1837 2068 3M CC03 2015 2015-09-08 NO23 -4.8283137373 I #> 1838 2068 3M CC03 2015 2015-09-08 SALIN 2.9014215941 #> 1839 2068 3M CC03 2015 2015-09-08 TKN -0.2357223335 #> 1840 2068 3M CC03 2015 2015-09-08 TN -0.2306718177 + #> 1841 2068 3M CC03 2015 2015-09-08 TP -3.0159349809 #> 1842 2068 3M CC03 2015 2015-09-08 TURB 0.6931471806 #> 1843 2068 3M CC03 2015 2015-10-05 CHLAC 1.4586150227 #> 1844 2068 3M CC03 2015 2015-10-05 COLOR 3.2958368660 A #> 1845 2068 3M CC03 2015 2015-10-05 DO 0.6418538862 #> 1846 2068 3M CC03 2015 2015-10-05 DOSAT 3.3214324132 + #> 1847 2068 3M CC03 2015 2015-10-05 NO23 -5.5214609179 U #> 1848 2068 3M CC03 2015 2015-10-05 SALIN 3.3741687093 #> 1849 2068 3M CC03 2015 2015-10-05 TKN -0.4307829161 #> 1850 2068 3M CC03 2015 2015-10-05 TN -0.4277107171 + #> 1851 2068 3M CC03 2015 2015-10-05 TP -3.0576076773 #> 1852 2068 3M CC03 2015 2015-10-05 TURB 0.8754687374 #> 1853 2068 3M CC03 2015 2015-12-07 CHLAC 1.3609765531 #> 1854 2068 3M CC03 2015 2015-12-07 COLOR 3.2188758249 #> 1855 2068 3M CC03 2015 2015-12-07 DO 1.1314021115 #> 1856 2068 3M CC03 2015 2015-12-07 DOSAT 3.7447870861 + #> 1857 2068 3M CC03 2015 2015-12-07 NO23 -4.5098600062 #> 1858 2068 3M CC03 2015 2015-12-07 SALIN 3.4144426084 #> 1859 2068 3M CC03 2015 2015-12-07 TKN -0.4462871026 #> 1860 2068 3M CC03 2015 2015-12-07 TN -0.4292456368 + #> 1861 2068 3M CC03 2015 2015-12-07 TP -2.8473122684 #> 1862 2068 3M CC03 2015 2015-12-07 TURB 1.1939224685 #> 1863 2068 3M CC03 2016 2016-01-04 CHLAC 1.3083328197 #> 1864 2068 3M CC03 2016 2016-01-04 COLOR 3.3672958300 #> 1865 2068 3M CC03 2016 2016-01-04 DO 0.0000000000 #> 1866 2068 3M CC03 2016 2016-01-04 DOSAT 2.5176964726 + #> 1867 2068 3M CC03 2016 2016-01-04 NO23 -4.0173835211 #> 1868 2068 3M CC03 2016 2016-01-04 SALIN 3.1904763503 #> 1869 2068 3M CC03 2016 2016-01-04 TKN -0.3566749439 #> 1870 2068 3M CC03 2016 2016-01-04 TN -0.3312857099 + #> 1871 2068 3M CC03 2016 2016-01-04 TP -2.6172958378 #> 1872 2068 3M CC03 2016 2016-01-04 TURB 0.8754687374 #> 1873 2068 3M CC03 2016 2016-02-01 CHLAC 1.0647107370 #> 1874 2068 3M CC03 2016 2016-02-01 COLOR 3.6635616461 #> 1875 2068 3M CC03 2016 2016-02-01 DOSAT 3.7256934272 + #> 1876 2068 3M CC03 2016 2016-02-01 NO23 -2.7030626596 #> 1877 2068 3M CC03 2016 2016-02-01 SALIN 2.7850112422 #> 1878 2068 3M CC03 2016 2016-02-01 TKN -0.2357223335 #> 1879 2068 3M CC03 2016 2016-02-01 TN -0.1543173604 + #> 1880 2068 3M CC03 2016 2016-02-01 TP -2.0402208285 #> 1881 2068 3M CC03 2016 2016-02-01 TURB 0.6418538862 #> 1882 2068 3M CC03 2016 2016-03-07 CHLAC 1.7227665977 #> 1883 2068 3M CC03 2016 2016-03-07 COLOR 3.5835189385 #> 1884 2068 3M CC03 2016 2016-03-07 DO 0.8329091229 #> 1885 2068 3M CC03 2016 2016-03-07 DOSAT 3.2995337279 + #> 1886 2068 3M CC03 2016 2016-03-07 NO23 -4.7105307016 I #> 1887 2068 3M CC03 2016 2016-03-07 SALIN 2.7080502011 #> 1888 2068 3M CC03 2016 2016-03-07 TKN -0.3011050928 #> 1889 2068 3M CC03 2016 2016-03-07 TN -0.2957142441 + #> 1890 2068 3M CC03 2016 2016-03-07 TP -2.3025850930 #> 1891 2068 3M CC03 2016 2016-03-07 TURB 1.1631508098 A #> 1892 2068 3M CC03 2016 2016-04-04 CHLAC 0.9932517730 #> 1893 2068 3M CC03 2016 2016-04-04 COLOR 3.5263605246 #> 1894 2068 3M CC03 2016 2016-04-04 DO 0.9555114450 #> 1895 2068 3M CC03 2016 2016-04-04 DOSAT 3.5263605246 + #> 1896 2068 3M CC03 2016 2016-04-04 NO23 -4.5098600062 #> 1897 2068 3M CC03 2016 2016-04-04 SALIN 3.0007198151 #> 1898 2068 3M CC03 2016 2016-04-04 TKN -0.3566749439 #> 1899 2068 3M CC03 2016 2016-04-04 TN -0.3410828492 + #> 1900 2068 3M CC03 2016 2016-04-04 TP -2.3859667019 #> 1901 2068 3M CC03 2016 2016-04-04 TURB 1.0296194172 #> 1902 2068 3M CC03 2016 2016-05-02 CHLAC 0.3364722366 I #> 1903 2068 3M CC03 2016 2016-05-02 COLOR 3.2580965380 #> 1904 2068 3M CC03 2016 2016-05-02 DO 0.7884573604 #> 1905 2068 3M CC03 2016 2016-05-02 DOSAT 3.5234150144 + #> 1906 2068 3M CC03 2016 2016-05-02 NO23 -5.5214609179 U #> 1907 2068 3M CC03 2016 2016-05-02 SALIN 3.6270040504 #> 1908 2068 3M CC03 2016 2016-05-02 TKN -0.3566749439 #> 1909 2068 3M CC03 2016 2016-05-02 TN -0.3538218750 + #> 1910 2068 3M CC03 2016 2016-05-02 TP -2.5639498571 #> 1911 2068 3M CC03 2016 2016-05-02 TURB 0.0953101798 #> 1912 2068 3M CC03 2017 2017-08-07 CHLAC 2.3978952728 #> 1913 2068 3M CC03 2017 2017-08-07 COLOR 4.2195077052 #> 1914 2068 3M CC03 2017 2017-08-07 DOSAT 2.3513752572 + #> 1915 2068 3M CC03 2017 2017-08-07 NO23 -5.5214609179 U #> 1916 2068 3M CC03 2017 2017-08-07 SALIN 1.4350845253 #> 1917 2068 3M CC03 2017 2017-08-07 TKN 0.5306282511 #> 1918 2068 3M CC03 2017 2017-08-07 TN 0.5318040302 + #> 1919 2068 3M CC03 2017 2017-08-07 TP -2.7030626596 #> 1920 2068 3M CC03 2017 2017-08-07 TURB 0.9162907319 #> 1921 2068 3M CC03 2017 2017-09-05 CHLAC 2.7080502011 #> 1922 2068 3M CC03 2017 2017-09-05 COLOR 5.0106352941 #> 1923 2068 3M CC03 2017 2017-09-05 DO 0.6931471806 #> 1924 2068 3M CC03 2017 2017-09-05 DOSAT 3.2884018875 + #> 1925 2068 3M CC03 2017 2017-09-05 NO23 -4.4228486292 #> 1926 2068 3M CC03 2017 2017-09-05 SALIN 2.2721258855 #> 1927 2068 3M CC03 2017 2017-09-05 TKN 0.1823215568 #> 1928 2068 3M CC03 2017 2017-09-05 TN 0.1922718876 + #> 1929 2068 3M CC03 2017 2017-09-05 TP -1.7719568419 #> 1930 2068 3M CC03 2017 2017-09-05 TURB 1.3350010667 #> 1931 2068 3M CC03 2017 2017-10-02 CHLAC 2.5649493575 #> 1932 2068 3M CC03 2017 2017-10-02 COLOR 4.0943445622 A #> 1933 2068 3M CC03 2017 2017-10-02 NO23 -5.5214609179 U #> 1934 2068 3M CC03 2017 2017-10-02 TKN -0.0725706928 #> 1935 2068 3M CC03 2017 2017-10-02 TN -0.0704224643 + #> 1936 2068 3M CC03 2017 2017-10-02 TP -2.3025850930 #> 1937 2068 3M CC03 2017 2017-10-02 TURB 1.8870696490 #> 1938 2068 3M CC03 2017 2017-11-06 CHLAC 1.1631508098 #> 1939 2068 3M CC03 2017 2017-11-06 COLOR 3.5835189385 #> 1940 2068 3M CC03 2017 2017-11-06 DO 1.3083328197 #> 1941 2068 3M CC03 2017 2017-11-06 DOSAT 3.9080149840 + #> 1942 2068 3M CC03 2017 2017-11-06 NO23 -5.2983173665 I #> 1943 2068 3M CC03 2017 2017-11-06 SALIN 3.1354942159 #> 1944 2068 3M CC03 2017 2017-11-06 TKN -0.2744368457 #> 1945 2068 3M CC03 2017 2017-11-06 TN -0.2691874898 + #> 1946 2068 3M CC03 2017 2017-11-06 TP -2.4418471603 #> 1947 2068 3M CC03 2017 2017-11-06 TURB 1.2237754316 #> 1948 2068 3M CC03 2017 2017-11-06 CHLAC 1.3350010667 #> 1949 2068 3M CC03 2017 2017-11-06 COLOR 3.5835189385 #> 1950 2068 3M CC03 2017 2017-11-06 NO23 -5.1159958098 I #> 1951 2068 3M CC03 2017 2017-11-06 TKN -0.3011050928 #> 1952 2068 3M CC03 2017 2017-11-06 TN -0.2957142441 + #> 1953 2068 3M CC03 2017 2017-11-06 TP -2.4079456087 #> 1954 2068 3M CC03 2017 2017-11-06 TURB 1.2237754316 #> 1955 2068 3M CC03 2018 2018-01-02 CHLAC 1.0647107370 #> 1956 2068 3M CC03 2018 2018-01-02 COLOR 3.0445224377 #> 1957 2068 3M CC03 2018 2018-01-02 NO23 -4.9618451299 I #> 1958 2068 3M CC03 2018 2018-01-02 SALIN 3.4563166809 #> 1959 2068 3M CC03 2018 2018-01-02 TKN -0.4780358009 #> 1960 2068 3M CC03 2018 2018-01-02 TN -0.4716049106 + #> 1961 2068 3M CC03 2018 2018-01-02 TP -2.4079456087 #> 1962 2068 3M CC03 2018 2018-01-02 TURB 1.1314021115 #> 1963 2068 3M CC03 2018 2018-02-05 CHLAC 0.9932517730 A #> 1964 2068 3M CC03 2018 2018-02-05 COLOR 3.2188758249 #> 1965 2068 3M CC03 2018 2018-02-05 DO 1.3609765531 #> 1966 2068 3M CC03 2018 2018-02-05 DOSAT 3.8979240810 + #> 1967 2068 3M CC03 2018 2018-02-05 NO23 -4.3428059215 #> 1968 2068 3M CC03 2018 2018-02-05 SALIN 3.0587070727 #> 1969 2068 3M CC03 2018 2018-02-05 TKN -0.4780358009 #> 1970 2068 3M CC03 2018 2018-02-05 TN -0.4572848568 + #> 1971 2068 3M CC03 2018 2018-02-05 TP -2.6310891600 #> 1972 2068 3M CC03 2018 2018-02-05 TURB 0.8754687374 #> 1973 2068 3M CC03 2018 2018-03-05 CHLAC 0.6418538862 #> 1974 2068 3M CC03 2018 2018-03-05 COLOR 2.5649493575 #> 1975 2068 3M CC03 2018 2018-03-05 DO 1.5686159179 #> 1976 2068 3M CC03 2018 2018-03-05 DOSAT 4.0517849478 + #> 1977 2068 3M CC03 2018 2018-03-05 NO23 -5.2983173665 I #> 1978 2068 3M CC03 2018 2018-03-05 SALIN 3.4781584228 #> 1979 2068 3M CC03 2018 2018-03-05 TKN -0.5798184953 #> 1980 2068 3M CC03 2018 2018-03-05 TN -0.5727010275 + #> 1981 2068 3M CC03 2018 2018-03-05 TP -2.7488721956 #> 1982 2068 3M CC03 2018 2018-03-05 TURB 2.2407096893 #> 1983 2068 3M CC03 2018 2018-04-02 CHLAC -0.5978370008 U #> 1984 2068 3M CC03 2018 2018-04-02 COLOR 0.9162907319 U #> 1985 2068 3M CC03 2018 2018-04-02 DO 1.2237754316 #> 1986 2068 3M CC03 2018 2018-04-02 DOSAT 3.8877303129 + #> 1987 2068 3M CC03 2018 2018-04-02 NO23 -3.7297014486 #> 1988 2068 3M CC03 2018 2018-04-02 SALIN 3.5553480615 #> 1989 2068 3M CC03 2018 2018-04-02 TKN 1.0296194172 #> 1990 2068 3M CC03 2018 2018-04-02 TN 1.0381543196 + #> 1991 2068 3M CC03 2018 2018-04-02 TP -1.7719568419 #> 1992 2068 3M CC03 2018 2018-04-02 TURB 1.3862943611 #> 1993 2068 3M CC03 2018 2018-05-07 CHLAC 0.4054651081 I #> 1994 2068 3M CC03 2018 2018-05-07 COLOR 2.6390573296 #> 1995 2068 3M CC03 2018 2018-05-07 DO -0.1984509387 #> 1996 2068 3M CC03 2018 2018-05-07 DOSAT 2.5416019935 #> 1997 2068 3M CC03 2018 2018-05-07 NO23 -5.5214609179 U #> 1998 2068 3M CC03 2018 2018-05-07 SALIN 3.6109179126 #> 1999 2068 3M CC03 2018 2018-05-07 TKN -0.6161861394 #> 2000 2068 3M CC03 2018 2018-05-07 TN -0.6124892775 + #> 2001 2068 3M CC03 2018 2018-05-07 TP -2.8824035882 #> 2002 2068 3M CC03 2018 2018-05-07 TURB 0.8754687374 #> 2003 2068 3M CC03 2018 2018-08-06 CHLAC 1.5475625087 #> 2004 2068 3M CC03 2018 2018-08-06 COLOR 3.8918202981 #> 2005 2068 3M CC03 2018 2018-08-06 DO -0.9162907319 #> 2006 2068 3M CC03 2018 2018-08-06 DOSAT 1.8245492921 #> 2007 2068 3M CC03 2018 2018-08-06 NO23 -5.5214609179 I #> 2008 2068 3M CC03 2018 2018-08-06 SALIN 3.3332753652 #> 2009 2068 3M CC03 2018 2018-08-06 TKN 0.2623642645 #> 2010 2068 3M CC03 2018 2018-08-06 TN 0.2654364635 + #> 2011 2068 3M CC03 2018 2018-08-06 TP -2.4191189092 #> 2012 2068 3M CC03 2018 2018-08-06 TURB 1.6486586256 #> 2013 2068 3M CC03 2019 2019-03-04 CHLAC 0.2623642645 I #> 2014 2068 3M CC03 2019 2019-03-04 COLOR 3.6635616461 #> 2015 2068 3M CC03 2019 2019-03-04 DO 1.0919233005 #> 2016 2068 3M CC03 2019 2019-03-04 DOSAT 3.6506582413 #> 2017 2068 3M CC03 2019 2019-03-04 NO23 -5.5214609179 U #> 2018 2068 3M CC03 2019 2019-03-04 SALIN 2.3105532626 #> 2019 2068 3M CC03 2019 2019-03-04 TKN -0.3147107448 #> 2020 2068 3M CC03 2019 2019-03-04 TN -0.3119747650 + #> 2021 2068 3M CC03 2019 2019-03-04 TP -2.3025850930 #> 2022 2068 3M CC03 2019 2019-03-04 TURB 0.8754687374 #> 2023 2068 3M CC03 2019 2019-05-06 CHLAC 1.3862943611 #> 2024 2068 3M CC03 2019 2019-05-06 COLOR 3.4965075615 #> 2025 2068 3M CC03 2019 2019-05-06 DO -1.8325814637 #> 2026 2068 3M CC03 2019 2019-05-06 DOSAT 0.9932517730 #> 2027 2068 3M CC03 2019 2019-05-06 NO23 -5.5214609179 U #> 2028 2068 3M CC03 2019 2019-05-06 SALIN 3.3809946743 #> 2029 2068 3M CC03 2019 2019-05-06 TKN -0.3566749439 #> 2030 2068 3M CC03 2019 2019-05-06 TN -0.3538218750 + #> 2031 2068 3M CC03 2019 2019-05-06 TP -3.0159349809 #> 2032 2068 3M CC03 2019 2019-05-06 TURB 0.6418538862 #> 2033 2068 3M CC03 2019 2019-06-03 CHLAC 1.0986122887 #> 2034 2068 3M CC03 2019 2019-06-03 COLOR 2.9957322736 #> 2035 2068 3M CC03 2019 2019-06-03 DO -0.8675005677 #> 2036 2068 3M CC03 2019 2019-06-03 DOSAT 1.8870696490 #> 2037 2068 3M CC03 2019 2019-06-03 NO23 -5.5214609179 U #> 2038 2068 3M CC03 2019 2019-06-03 SALIN 3.6068556186 #> 2039 2068 3M CC03 2019 2019-06-03 TKN -0.3424903089 #> 2040 2068 3M CC03 2019 2019-06-03 TN -0.3396773676 + #> 2041 2068 3M CC03 2019 2019-06-03 TP -3.0791138825 #> 2042 2068 3M CC03 2019 2019-06-03 TURB 0.9555114450 #> 2043 2068 3M CC03 2019 2019-07-01 CHLAC 1.9740810260 #> 2044 2068 3M CC03 2019 2019-07-01 COLOR 3.2958368660 A #> 2045 2068 3M CC03 2019 2019-07-01 DO -0.5978370008 #> 2046 2068 3M CC03 2019 2019-07-01 DOSAT 2.1517622033 #> 2047 2068 3M CC03 2019 2019-07-01 NO23 -5.5214609179 U #> 2048 2068 3M CC03 2019 2019-07-01 SALIN 3.5160130561 #> 2049 2068 3M CC03 2019 2019-07-01 TKN -0.2613647641 #> 2050 2068 3M CC03 2019 2019-07-01 TN -0.2587707290 + #> 2051 2068 3M CC03 2019 2019-07-01 TP -3.0159349809 #> 2052 2068 3M CC03 2019 2019-07-01 TURB 1.6486586256 A #> 2053 2068 3M CC03 2019 2019-10-07 TN -0.6462635947 + #> 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#> 2072 2068 3M CC03 2019 2019-11-04 DO 0.3646431136 #> 2073 2068 3M CC03 2019 2019-11-04 DOSAT 3.0349529867 #> 2074 2068 3M CC03 2019 2019-11-04 NO23 -4.3428059215 #> 2075 2068 3M CC03 2019 2019-11-04 SALIN 3.6030491975 #> 2076 2068 3M CC03 2019 2019-11-04 TKN -0.3566749439 #> 2077 2068 3M CC03 2019 2019-11-04 TN -0.3382738586 + #> 2078 2068 3M CC03 2019 2019-11-04 TP -2.7488721956 #> 2079 2068 3M CC03 2019 2019-11-04 TURB 1.1631508098 #> 2080 2068 3M CC03 2019 2019-12-02 CHLAC 0.8754687374 I #> 2081 2068 3M CC03 2019 2019-12-02 COLOR 2.1860512767 #> 2082 2068 3M CC03 2019 2019-12-02 DO 1.0367368850 #> 2083 2068 3M CC03 2019 2019-12-02 DOSAT 3.6988297850 #> 2084 2068 3M CC03 2019 2019-12-02 NO23 -4.1997050779 #> 2085 2068 3M CC03 2019 2019-12-02 SALIN 3.4977189487 #> 2086 2068 3M CC03 2019 2019-12-02 TKN -0.4620354596 #> 2087 2068 3M CC03 2019 2019-12-02 TN -0.4385049622 + #> 2088 2068 3M CC03 2019 2019-12-02 TP -2.9187712324 #> 2089 2068 3M CC03 2019 2019-12-02 TURB 0.6418538862 #> 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#> 2198 2068 3M CC03 2021 2021-05-03 TP -3.1010927892 #> 2199 2068 3M CC03 2021 2021-05-03 TURB 1.6094379124 A #> 2200 2068 3M CC03 2021 2021-06-07 CHLAC 0.8754687374 I #> 2201 2068 3M CC03 2021 2021-06-07 COLOR 2.9444389792 #> 2202 2068 3M CC03 2021 2021-06-07 DO -0.4462871026 #> 2203 2068 3M CC03 2021 2021-06-07 DOSAT 2.3418058061 #> 2204 2068 3M CC03 2021 2021-06-07 NO23 -5.5214609179 U #> 2205 2068 3M CC03 2021 2021-06-07 SALIN 3.6444049640 #> 2206 2068 3M CC03 2021 2021-06-07 TKN -0.4462871026 #> 2207 2068 3M CC03 2021 2021-06-07 TN -0.4431669753 + #> 2208 2068 3M CC03 2021 2021-06-07 TP -3.1941832123 #> 2209 2068 3M CC03 2021 2021-06-07 TURB 0.8754687374 #> 2210 2068 3M CC03 2021 2021-08-02 CHLAC 3.2188758249 #> 2211 2068 3M CC03 2021 2021-08-02 COLOR 4.4308167988 #> 2212 2068 3M CC03 2021 2021-08-02 DO -0.5108256238 #> 2213 2068 3M CC03 2021 2021-08-02 DOSAT -0.9162907319 #> 2214 2068 3M CC03 2021 2021-08-02 NO23 -5.5214609179 U #> 2215 2068 3M CC03 2021 2021-08-02 SALIN 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-4.6051701860 I #> 2252 2068 3M CC03 2021 2021-11-01 SALIN 3.1797191097 #> 2253 2068 3M CC03 2021 2021-11-01 TKN -0.3856624808 #> 2254 2068 3M CC03 2021 2021-11-01 TN -0.3797973614 + #> 2255 2068 3M CC03 2021 2021-11-01 TP -2.4418471603 #> 2256 2068 3M CC03 2021 2021-11-01 TURB 0.4054651081 A #> 2257 2068 3M CC03 2021 2021-12-06 CHLAC 0.7419373447 I #> 2258 2068 3M CC03 2021 2021-12-06 COLOR 2.7725887222 #> 2259 2068 3M CC03 2021 2021-12-06 DO 1.1249295970 #> 2260 2068 3M CC03 2021 2021-12-06 DOSAT 3.7495040759 #> 2261 2068 3M CC03 2021 2021-12-06 NO23 -4.4228486292 #> 2262 2068 3M CC03 2021 2021-12-06 SALIN 3.3931652100 #> 2263 2068 3M CC03 2021 2021-12-06 TKN -0.4004775666 #> 2264 2068 3M CC03 2021 2021-12-06 TN -0.3827256211 + #> 2265 2068 3M CC03 2021 2021-12-06 TP -2.4889146712 #> 2266 2068 3M CC03 2021 2021-12-06 TURB 1.1631508098 #> 2267 2068 3M CC03 2022 2022-01-03 CHLAC 1.2527629685 #> 2268 2068 3M CC03 2022 2022-01-03 COLOR 2.6390573296 #> 2269 2068 3M CC03 2022 2022-01-03 DO 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2022-04-04 TURB 1.0986122887 #> 2306 2068 3M CC03 2022 2022-05-02 CHLAC 0.3364722366 U #> 2307 2068 3M CC03 2022 2022-05-02 DO -0.5108256238 #> 2308 2068 3M CC03 2022 2022-05-02 DOSAT 2.2082744135 #> 2309 2068 3M CC03 2022 2022-05-02 NO23 -5.5214609179 U #> 2310 2068 3M CC03 2022 2022-05-02 SALIN 3.5366020187 #> 2311 2068 3M CC03 2022 2022-05-02 TN -0.5762534291 + #> 2312 2068 3M CC03 2018 2018-03-13 CHLAC 0.9555114450 #> 2313 2068 3M CC03 2018 2018-03-13 COND 10.8817948782 #> 2314 2068 3M CC03 2018 2018-03-13 DO 2.0794415417 #> 2315 2068 3M CC03 2018 2018-03-13 DOSAT 4.6812048723 #> 2316 2068 3M CC03 2018 2018-03-13 NO23 -4.7105307016 I #> 2317 2068 3M CC03 2018 2018-03-13 SALIN 3.6778185068 + #> 2318 2068 3M CC03 2018 2018-03-13 TKN -0.4942963218 #> 2319 2068 3M CC03 2018 2018-03-13 TN -0.4877603508 + #> 2320 2068 3M CC03 2018 2018-03-13 TP -2.4191189092 #> 2321 2068 3M CC03 2018 2018-03-13 TSS 1.3862943611 I #> 2322 2068 3M CC03 2018 2018-03-13 TURB 1.0647107370 #> 2323 2068 3M CC03 2018 2018-05-08 CHLAC 1.1631508098 #> 2324 2068 3M CC03 2018 2018-05-08 COND 10.9254527508 #> 2325 2068 3M CC03 2018 2018-05-08 DO 1.4973884086 #> 2326 2068 3M CC03 2018 2018-05-08 DOSAT 4.2091602367 #> 2327 2068 3M CC03 2018 2018-05-08 NO23 -5.5214609179 U #> 2328 2068 3M CC03 2018 2018-05-08 SALIN 3.5973122606 + #> 2329 2068 3M CC03 2018 2018-05-08 TKN -0.5108256238 #> 2330 2068 3M CC03 2018 2018-05-08 TN -0.5074978337 + #> 2331 2068 3M CC03 2018 2018-05-08 TP -3.2441936329 #> 2332 2068 3M CC03 2018 2018-05-08 TSS 2.0794415417 I #> 2333 2068 3M CC03 2018 2018-05-08 TURB 1.3083328197 #> 2334 2068 3M CC03 2018 2018-06-26 CHLAC 2.4849066498 #> 2335 2068 3M CC03 2018 2018-06-26 COND 10.7823463704 #> 2336 2068 3M CC03 2018 2018-06-26 DO 1.1118575154 #> 2337 2068 3M CC03 2018 2018-06-26 DOSAT 3.8628327612 #> 2338 2068 3M CC03 2018 2018-06-26 NO23 -5.5214609179 U #> 2339 2068 3M CC03 2018 2018-06-26 SALIN 3.3414473773 + #> 2340 2068 3M CC03 2018 2018-06-26 TKN -0.4155154440 #> 2341 2068 3M CC03 2018 2018-06-26 TN -0.4124897230 + #> 2342 2068 3M CC03 2018 2018-06-26 TSS 2.0794415417 I #> 2343 2068 3M CC03 2018 2018-06-26 TURB 1.4816045409 #> 2344 2068 3M CC03 2018 2018-09-18 CHLAC 2.2617630985 #> 2345 2068 3M CC03 2018 2018-09-18 COND 9.9966590834 #> 2346 2068 3M CC03 2018 2018-09-18 DO 0.8020015855 #> 2347 2068 3M CC03 2018 2018-09-18 DOSAT 3.4812400893 #> 2348 2068 3M CC03 2018 2018-09-18 NO23 -4.7105307016 I #> 2349 2068 3M CC03 2018 2018-09-18 TKN -0.0833816089 #> 2350 2068 3M CC03 2018 2018-09-18 TN -0.0790432073 + #> 2351 2068 3M CC03 2018 2018-09-18 TP -2.3227878003 #> 2352 2068 3M CC03 2018 2018-09-18 TSS 1.0986122887 U #> 2353 2068 3M CC03 2018 2018-09-18 TURB 1.2809338455 A #> 2354 2068 3M CC03 2018 2018-12-04 CHLAC 1.6486586256 #> 2355 2068 3M CC03 2018 2018-12-04 COND 10.7489265434 #> 2356 2068 3M CC03 2018 2018-12-04 DO 1.5644405465 #> 2357 2068 3M CC03 2018 2018-12-04 DOSAT 4.2239097666 #> 2358 2068 3M CC03 2018 2018-12-04 NO23 -1.8971199849 #> 2359 2068 3M CC03 2018 2018-12-04 SALIN 3.4094961845 #> 2360 2068 3M CC03 2018 2018-12-04 TKN -0.3285040670 #> 2361 2068 3M CC03 2018 2018-12-04 TN -0.1392620673 + #> 2362 2068 3M CC03 2018 2018-12-04 TP -2.6450754019 #> 2363 2068 3M CC03 2018 2018-12-04 TSS 2.1972245773 I #> 2364 2068 3M CC03 2018 2018-12-04 TURB 0.5306282511 #> 2365 2078A 2 CC04 2019 2019-08-13 CHLAC 3.1780538303 #> 2366 2078A 2 CC04 2019 2019-08-13 COND 9.8642788393 #> 2367 2078A 2 CC04 2019 2019-08-13 DO 1.7647307968 #> 2368 2078A 2 CC04 2019 2019-08-13 DOSAT 4.4176350621 #> 2369 2078A 2 CC04 2019 2019-08-13 NO23 -5.2983173665 I #> 2370 2078A 2 CC04 2019 2019-08-13 SALIN 2.4274540750 #> 2371 2078A 2 CC04 2019 2019-08-13 TKN 0.3364722366 #> 2372 2078A 2 CC04 2019 2019-08-13 TN 0.3393253056 + #> 2373 2078A 2 CC04 2019 2019-08-13 TP -2.9759296463 #> 2374 2078A 2 CC04 2019 2019-08-13 TSS 1.6094379124 I #> 2375 2078A 2 CC04 2019 2019-08-13 TURB 0.7419373447 #> 2376 2078B 2 CC05 2019 2019-01-17 COND 10.7433722892 #> 2377 2078B 2 CC05 2019 2019-01-17 DO 1.9065751437 #> 2378 2078B 2 CC05 2019 2019-01-17 DOSAT 4.4030540019 #> 2379 2078B 2 CC05 2019 2019-01-17 SALIN 3.4045251718 #> 2380 2078B 2 CC05 2019 2019-01-17 TN -0.3827256211 + #> 2381 2078B 2 CC05 2019 2019-01-24 CHLAC 0.2623642645 I #> 2382 2078B 2 CC05 2019 2019-01-24 COND 10.7763069502 #> 2383 2078B 2 CC05 2019 2019-01-24 DO 1.8702625307 #> 2384 2078B 2 CC05 2019 2019-01-24 DOSAT 4.4531838290 #> 2385 2078B 2 CC05 2019 2019-01-24 NO23 -5.1159958098 I #> 2386 2078B 2 CC05 2019 2019-01-24 SALIN 3.4413791713 #> 2387 2078B 2 CC05 2019 2019-01-24 TKN -0.7985076962 #> 2388 2078B 2 CC05 2019 2019-01-24 TN -0.7896580809 + #> 2389 2078B 2 CC05 2019 2019-01-24 TP -3.5065578973 #> 2390 2078B 2 CC05 2019 2019-01-24 TSS 1.0986122887 I #> 2391 2078B 2 CC05 2019 2019-01-24 TURB 0.2623642645 #> 2392 2078B 2 CC05 2019 2019-03-12 CHLAC 1.2809338455 #> 2393 2078B 2 CC05 2019 2019-03-12 COND 10.4768935315 #> 2394 2078B 2 CC05 2019 2019-03-12 DO 1.6992786164 #> 2395 2078B 2 CC05 2019 2019-03-12 DOSAT 4.3412046402 #> 2396 2078B 2 CC05 2019 2019-03-12 NO23 -5.5214609179 U #> 2397 2078B 2 CC05 2019 2019-03-12 SALIN 3.1059310659 #> 2398 2078B 2 CC05 2019 2019-03-12 TKN -0.3424903089 #> 2399 2078B 2 CC05 2019 2019-03-12 TN -0.3396773676 + #> 2400 2078B 2 CC05 2019 2019-03-12 TP -3.2441936329 #> 2401 2078B 2 CC05 2019 2019-03-12 TSS 2.1972245773 I #> 2402 2078B 2 CC05 2019 2019-03-12 TURB 0.6931471806 #> 2403 2078B 2 CC05 2019 2019-04-16 CHLAC 1.4816045409 #> 2404 2078B 2 CC05 2019 2019-04-16 COND 10.7360705353 #> 2405 2078B 2 CC05 2019 2019-04-16 DO 1.6505798558 #> 2406 2078B 2 CC05 2019 2019-04-16 DOSAT 4.3094559418 #> 2407 2078B 2 CC05 2019 2019-04-16 NO23 -5.5214609179 U #> 2408 2078B 2 CC05 2019 2019-04-16 SALIN 3.3951793093 #> 2409 2078B 2 CC05 2019 2019-04-16 TKN -0.2484613593 #> 2410 2078B 2 CC05 2019 2019-04-16 TN -0.2459005384 + #> 2411 2078B 2 CC05 2019 2019-04-16 TP -3.7722610631 #> 2412 2078B 2 CC05 2019 2019-04-16 TSS 1.6094379124 I #> 2413 2078B 2 CC05 2019 2019-04-16 TURB 0.6418538862 #> 2414 2078B 2 CC05 2019 2019-06-11 CHLAC 1.1314021115 #> 2415 2078B 2 CC05 2019 2019-06-11 COND 10.8909447918 #> 2416 2078B 2 CC05 2019 2019-06-11 DO 1.2059708070 #> 2417 2078B 2 CC05 2019 2019-06-11 DOSAT 4.0127729085 #> 2418 2078B 2 CC05 2019 2019-06-11 NO23 -5.5214609179 I #> 2419 2078B 2 CC05 2019 2019-06-11 SALIN 3.5635996377 #> 2420 2078B 2 CC05 2019 2019-06-11 TKN -0.3285040670 #> 2421 2078B 2 CC05 2019 2019-06-11 TN -0.3229638866 + #> 2422 2078B 2 CC05 2019 2019-06-11 TP -3.3242363405 #> 2423 2078B 2 CC05 2019 2019-06-11 TSS 1.0986122887 U #> 2424 2078B 2 CC05 2019 2019-06-11 TURB 0.3364722366 #> 2425 2078B 2 CC05 2019 2019-08-13 CHLAC 2.8332133441 #> 2426 2078B 2 CC05 2019 2019-08-13 COND 10.2219412837 #> 2427 2078B 2 CC05 2019 2019-08-13 DO 1.4036429995 #> 2428 2078B 2 CC05 2019 2019-08-13 DOSAT 4.0926765051 #> 2429 2078B 2 CC05 2019 2019-08-13 NO23 -4.6051701860 I #> 2430 2078B 2 CC05 2019 2019-08-13 SALIN 2.8195915758 #> 2431 2078B 2 CC05 2019 2019-08-13 TKN 0.6418538862 #> 2432 2078B 2 CC05 2019 2019-08-13 TN 0.6439569364 + #> 2433 2078B 2 CC05 2019 2019-08-13 TP -2.9759296463 #> 2434 2078B 2 CC05 2019 2019-08-13 TSS 1.7917594692 I #> 2435 2078B 2 CC05 2019 2019-08-13 TURB 0.7884573604 #> 2436 2078B 2 CC05 2019 2019-08-13 COND 10.3244650523 #> 2437 2078B 2 CC05 2019 2019-08-13 DO 1.0543120298 #> 2438 2078B 2 CC05 2019 2019-08-13 DOSAT 3.7541989202 #> 2439 2078B 2 CC05 2019 2019-08-13 SALIN 2.9322598506 #> 2440 2078B 2 CC05 2019 2019-10-01 COND 10.7304660807 #> 2441 2078B 2 CC05 2019 2019-10-01 DO 1.5644405465 #> 2442 2078B 2 CC05 2019 2019-10-01 DOSAT 4.2724907476 #> 2443 2078B 2 CC05 2019 2019-10-01 SALIN 3.3864220961 #> 2444 2078B 2 CC05 2019 2019-11-04 COND 10.7792062586 #> 2445 2078B 2 CC05 2019 2019-11-04 DO 1.5151272330 #> 2446 2078B 2 CC05 2019 2019-11-04 DOSAT 4.2061840440 #> 2447 2078B 2 CC05 2019 2019-11-04 SALIN 3.4423393250 #> 2448 2078B 2 CC05 2019 2019-11-19 CHLAC 2.6390573296 #> 2449 2078B 2 CC05 2019 2019-11-19 COND 10.8493565039 #> 2450 2078B 2 CC05 2019 2019-11-19 DO 2.0135687975 #> 2451 2078B 2 CC05 2019 2019-11-19 DOSAT 4.6298627986 #> 2452 2078B 2 CC05 2019 2019-11-19 NO23 -5.5214609179 U #> 2453 2078B 2 CC05 2019 2019-11-19 SALIN 3.5234150144 #> 2454 2078B 2 CC05 2019 2019-11-19 TKN -0.3011050928 #> 2455 2078B 2 CC05 2019 2019-11-19 TN -0.2984060358 + #> 2456 2078B 2 CC05 2019 2019-11-19 TP -2.8302178351 #> 2457 2078B 2 CC05 2019 2019-11-19 TSS 2.0794415417 I #> 2458 2078B 2 CC05 2019 2019-11-19 TURB 1.0296194172 A #> 2459 2078B 2 CC05 2020 2020-02-13 CHLAC 2.1400661635 A #> 2460 2078B 2 CC05 2020 2020-02-13 COND 10.7287588860 #> 2461 2078B 2 CC05 2020 2020-02-13 DO 1.8961194846 #> 2462 2078B 2 CC05 2020 2020-02-13 DOSAT 4.5747109785 #> 2463 2078B 2 CC05 2020 2020-02-13 NO23 -5.5214609179 U #> 2464 2078B 2 CC05 2020 2020-02-13 SALIN 3.3857452771 #> 2465 2078B 2 CC05 2020 2020-02-13 TKN -0.3424903089 #> 2466 2078B 2 CC05 2020 2020-02-13 TN -0.3396773676 + #> 2467 2078B 2 CC05 2020 2020-02-13 TP -3.3242363405 #> 2468 2078B 2 CC05 2020 2020-02-13 TSS 2.2617630985 I #> 2469 2078B 2 CC05 2020 2020-02-13 TURB 1.0296194172 #> 2470 2078B 2 CC05 2020 2020-03-24 CHLAC 2.2617630985 #> 2471 2078B 2 CC05 2020 2020-03-24 COND 10.9026109427 #> 2472 2078B 2 CC05 2020 2020-03-24 DO 1.8357763546 #> 2473 2078B 2 CC05 2020 2020-03-24 DOSAT 4.5900565482 #> 2474 2078B 2 CC05 2020 2020-03-24 NO23 -5.5214609179 U #> 2475 2078B 2 CC05 2020 2020-03-24 SALIN 3.5787855313 #> 2476 2078B 2 CC05 2020 2020-03-24 TKN -0.6161861394 #> 2477 2078B 2 CC05 2020 2020-03-24 TN -0.6124892775 + #> 2478 2078B 2 CC05 2020 2020-03-24 TP -2.5902671654 #> 2479 2078B 2 CC05 2020 2020-03-24 TSS 2.4849066498 A #> 2480 2078B 2 CC05 2020 2020-03-24 TURB 1.0647107370 #> 2481 2078B 2 CC05 2020 2020-06-15 CHLAC 2.8332133441 #> 2482 2078B 2 CC05 2020 2020-06-15 COND 10.3780433051 #> 2483 2078B 2 CC05 2020 2020-06-15 DO 1.2325602612 #> 2484 2078B 2 CC05 2020 2020-06-15 DOSAT 3.9199911751 #> 2485 2078B 2 CC05 2020 2020-06-15 NO23 -5.5214609179 I #> 2486 2078B 2 CC05 2020 2020-06-15 SALIN 2.9907197317 #> 2487 2078B 2 CC05 2020 2020-06-15 TKN 0.1823215568 #> 2488 2078B 2 CC05 2020 2020-06-15 TN 0.1856493469 + #> 2489 2078B 2 CC05 2020 2020-06-15 TP -3.0159349809 #> 2490 2078B 2 CC05 2020 2020-06-15 TSS 1.6094379124 I #> 2491 2078B 2 CC05 2020 2020-06-15 TURB 0.9932517730 #> 2492 2078B 2 CC05 2020 2020-07-27 CHLAC 2.5649493575 A #> 2493 2078B 2 CC05 2020 2020-07-27 COND 10.7499993898 #> 2494 2078B 2 CC05 2020 2020-07-27 DO 1.4422019931 #> 2495 2078B 2 CC05 2020 2020-07-27 DOSAT 4.2150861799 #> 2496 2078B 2 CC05 2020 2020-07-27 NO23 -5.5214609179 U #> 2497 2078B 2 CC05 2020 2020-07-27 SALIN 3.4041928906 #> 2498 2078B 2 CC05 2020 2020-07-27 TKN -0.3424903089 #> 2499 2078B 2 CC05 2020 2020-07-27 TN -0.3396773676 + #> 2500 2078B 2 CC05 2020 2020-07-27 TP -3.1010927892 #> 2501 2078B 2 CC05 2020 2020-07-27 TSS 1.6094379124 I #> 2502 2078B 2 CC05 2020 2020-07-27 TURB 1.1631508098 #> 2503 2078B 2 CC05 2020 2020-08-26 CHLAC 2.8903717579 #> 2504 2078B 2 CC05 2020 2020-08-26 COND 10.1730947543 #> 2505 2078B 2 CC05 2020 2020-08-26 DO 1.5062971535 #> 2506 2078B 2 CC05 2020 2020-08-26 DOSAT 4.1972019477 #> 2507 2078B 2 CC05 2020 2020-08-26 NO23 -5.5214609179 U #> 2508 2078B 2 CC05 2020 2020-08-26 SALIN 2.7625383864 #> 2509 2078B 2 CC05 2020 2020-08-26 TKN -0.0618754037 #> 2510 2078B 2 CC05 2020 2020-08-26 TN -0.0597500044 + #> 2511 2078B 2 CC05 2020 2020-08-26 TP -2.9565115604 #> 2512 2078B 2 CC05 2020 2020-08-26 TSS 1.7917594692 I #> 2513 2078B 2 CC05 2020 2020-08-26 TURB 1.0647107370 #> 2514 2078B 2 CC05 2021 2021-01-14 CHLAC 0.9162907319 #> 2515 2078B 2 CC05 2021 2021-01-14 COND 10.6789517756 #> 2516 2078B 2 CC05 2021 2021-01-14 DO 1.7422190237 #> 2517 2078B 2 CC05 2021 2021-01-14 DOSAT 4.2427645673 #> 2518 2078B 2 CC05 2021 2021-01-14 NO23 -4.6051701860 #> 2519 2078B 2 CC05 2021 2021-01-14 SALIN 3.3339886320 #> 2520 2078B 2 CC05 2021 2021-01-14 TKN -0.6348782724 #> 2521 2078B 2 CC05 2021 2021-01-14 TN -0.6161861394 + #> 2522 2078B 2 CC05 2021 2021-01-14 TP -3.4420193762 #> 2523 2078B 2 CC05 2021 2021-01-14 TSS 1.0986122887 I #> 2524 2078B 2 CC05 2021 2021-01-14 TURB 0.5306282511 #> 2525 2078B 2 CC05 2021 2021-02-24 COND 10.7448823096 #> 2526 2078B 2 CC05 2021 2021-02-24 DO 1.5518087996 #> 2527 2078B 2 CC05 2021 2021-02-24 DOSAT 4.1987045775 #> 2528 2078B 2 CC05 2021 2021-02-24 NO23 -4.6051701860 I #> 2529 2078B 2 CC05 2021 2021-02-24 SALIN 3.4061849232 #> 2530 2078B 2 CC05 2021 2021-02-24 TKN -0.8915981193 #> 2531 2078B 2 CC05 2021 2021-02-24 TN -0.8818893052 + #> 2532 2078B 2 CC05 2021 2021-02-24 TP -3.2441936329 #> 2533 2078B 2 CC05 2021 2021-02-24 TSS 1.0986122887 I #> 2534 2078B 2 CC05 2021 2021-03-23 CHLAC 1.1939224685 #> 2535 2078B 2 CC05 2021 2021-03-23 COND 10.8800451952 #> 2536 2078B 2 CC05 2021 2021-03-23 DO 1.7783364489 #> 2537 2078B 2 CC05 2021 2021-03-23 DOSAT 4.4042772436 #> 2538 2078B 2 CC05 2021 2021-03-23 NO23 -4.9618451299 I #> 2539 2078B 2 CC05 2021 2021-03-23 SALIN 3.5579161896 #> 2540 2078B 2 CC05 2021 2021-03-23 TKN -0.5447271754 #> 2541 2078B 2 CC05 2021 2021-03-23 TN -0.5378542962 + #> 2542 2078B 2 CC05 2021 2021-03-23 TP -2.8134107168 #> 2543 2078B 2 CC05 2021 2021-03-23 TSS 2.4849066498 #> 2544 2078B 2 CC05 2021 2021-03-23 TURB 1.6863989536 #> 2545 2078B 2 CC05 2021 2021-07-28 CHLAC 2.5649493575 #> 2546 2078B 2 CC05 2021 2021-07-28 COND 10.0731881321 #> 2547 2078B 2 CC05 2021 2021-07-28 DO 0.9001613499 #> 2548 2078B 2 CC05 2021 2021-07-28 DOSAT 3.6027767551 #> 2549 2078B 2 CC05 2021 2021-07-28 NO23 -5.5214609179 U #> 2550 2078B 2 CC05 2021 2021-07-28 SALIN 2.6665335209 #> 2551 2078B 2 CC05 2021 2021-07-28 TKN 0.0000000000 #> 2552 2078B 2 CC05 2021 2021-07-28 TN 0.0019980027 + #> 2553 2078B 2 CC05 2021 2021-07-28 TP -3.1010927892 #> 2554 2078B 2 CC05 2021 2021-07-28 TSS 1.3862943611 I #> 2555 2078B 2 CC05 2021 2021-07-28 TURB 1.0296194172 #> 2556 2078B 2 CC05 2021 2021-08-26 CHLAC 2.4849066498 #> 2557 2078B 2 CC05 2021 2021-08-26 COND 10.2519942268 #> 2558 2078B 2 CC05 2021 2021-08-26 DO 1.3737155789 #> 2559 2078B 2 CC05 2021 2021-08-26 DOSAT 4.0324691585 #> 2560 2078B 2 CC05 2021 2021-08-26 NO23 -5.5214609179 U #> 2561 2078B 2 CC05 2021 2021-08-26 SALIN 2.8553201198 #> 2562 2078B 2 CC05 2021 2021-08-26 TKN -0.2231435513 #> 2563 2078B 2 CC05 2021 2021-08-26 TN -0.2206466711 + #> 2564 2078B 2 CC05 2021 2021-08-26 TP -2.8134107168 #> 2565 2078B 2 CC05 2021 2021-08-26 TSS 1.9459101491 I #> 2566 2078B 2 CC05 2021 2021-08-26 TURB 0.8754687374 #> 2567 2078B 2 CC05 2021 2021-09-13 CHLAC 2.5649493575 #> 2568 2078B 2 CC05 2021 2021-09-13 COND 10.4619312252 #> 2569 2078B 2 CC05 2021 2021-09-13 DO 1.4929040962 #> 2570 2078B 2 CC05 2021 2021-09-13 DOSAT 4.2091602367 #> 2571 2078B 2 CC05 2021 2021-09-13 NO23 -5.5214609179 U #> 2572 2078B 2 CC05 2021 2021-09-13 SALIN 3.0842009215 #> 2573 2078B 2 CC05 2021 2021-09-13 TKN -0.0943106795 #> 2574 2078B 2 CC05 2021 2021-09-13 TN -0.0921152889 + #> 2575 2078B 2 CC05 2021 2021-09-13 TP -2.9565115604 #> 2576 2078B 2 CC05 2021 2021-09-13 TSS 2.0794415417 I #> 2577 2078B 2 CC05 2021 2021-09-13 TURB 1.0986122887 A #> 2578 2078B 2 CC05 2022 2022-04-19 CHLAC 2.3978952728 #> 2579 2078B 2 CC05 2022 2022-04-19 COND 10.9594532665 #> 2580 2078B 2 CC05 2022 2022-04-19 DO 1.6486586256 #> 2581 2078B 2 CC05 2022 2022-04-19 DOSAT 4.3845235149 #> 2582 2078B 2 CC05 2022 2022-04-19 NO23 -5.5214609179 U #> 2583 2078B 2 CC05 2022 2022-04-19 SALIN 3.6449275666 #> 2584 2078B 2 CC05 2022 2022-04-19 TKN -0.4462871026 #> 2585 2078B 2 CC05 2022 2022-04-19 TN -0.4431669753 + #> 2586 2078B 2 CC05 2022 2022-04-19 TP -2.6592600369 #> 2587 2078B 2 CC05 2022 2022-04-19 TSS 3.0910424534 #> 2588 2078B 2 CC05 2022 2022-04-19 TURB 1.5892352051 A #> 2589 2078B 2 CC05 2022 2022-05-10 CHLAC 1.9021075264 #> 2590 2078B 2 CC05 2022 2022-05-10 COND 10.8257603561 #> 2591 2078B 2 CC05 2022 2022-05-10 DO 1.6114359151 #> 2592 2078B 2 CC05 2022 2022-05-10 DOSAT 4.3148178850 #> 2593 2078B 2 CC05 2022 2022-05-10 NO23 -5.5214609179 U #> 2594 2078B 2 CC05 2022 2022-05-10 SALIN 3.4943840964 #> 2595 2078B 2 CC05 2022 2022-05-10 TKN -0.1984509387 #> 2596 2078B 2 CC05 2022 2022-05-10 TN -0.1960148839 + #> 2597 2078B 2 CC05 2022 2022-05-10 TP -2.6450754019 #> 2598 2078B 2 CC05 2022 2022-05-10 TSS 2.1972245773 I #> 2599 2078B 2 CC05 2022 2022-05-10 TURB 1.6486586256 #> 2600 2078B 2 CC05 2021 2021-03-23 CHLAC 1.5892352051 #> 2601 2078B 2 CC05 2021 2021-03-23 COND 10.8660128047 #> 2602 2078B 2 CC05 2021 2021-03-23 DO 2.0162354658 #> 2603 2078B 2 CC05 2021 2021-03-23 DOSAT 4.6802776585 #> 2604 2078B 2 CC05 2021 2021-03-23 NO23 -5.5214609179 U #> 2605 2078B 2 CC05 2021 2021-03-23 SALIN 3.5415388662 #> 2606 2078B 2 CC05 2021 2021-03-23 TKN 0.0953101798 #> 2607 2078B 2 CC05 2021 2021-03-23 TN 0.0971267107 + #> 2608 2078B 2 CC05 2021 2021-03-23 TP -3.2968373663 #> 2609 2078B 2 CC05 2021 2021-03-23 TSS 1.0986122887 I #> 2610 2078B 2 CC05 2021 2021-03-23 TURB 0.7884573604 #> 2611 2078B 2 CC05 2021 2021-07-28 CHLAC 1.5686159179 I #> 2612 2078B 2 CC05 2021 2021-07-28 COND 9.6616070559 #> 2613 2078B 2 CC05 2021 2021-07-28 DO -0.3566749439 #> 2614 2078B 2 CC05 2021 2021-07-28 DOSAT 2.3418058061 #> 2615 2078B 2 CC05 2021 2021-07-28 NO23 -5.5214609179 U #> 2616 2078B 2 CC05 2021 2021-07-28 SALIN 2.2049722641 #> 2617 2078B 2 CC05 2021 2021-07-28 TKN 0.0953101798 #> 2618 2078B 2 CC05 2021 2021-07-28 TN 0.0971267107 + #> 2619 2078B 2 CC05 2021 2021-07-28 TP -3.3242363405 #> 2620 2078B 2 CC05 2021 2021-07-28 TSS 1.0986122887 U #> 2621 2078B 2 CC05 2021 2021-07-28 TURB 0.5306282511 #> 2622 2078B 2 CC05 2021 2021-08-26 CHLAC 2.5649493575 #> 2623 2078B 2 CC05 2021 2021-08-26 COND 9.7645702533 #> 2624 2078B 2 CC05 2021 2021-08-26 DO 0.7030975114 #> 2625 2078B 2 CC05 2021 2021-08-26 DOSAT 3.3141860047 #> 2626 2078B 2 CC05 2021 2021-08-26 NO23 -5.5214609179 U #> 2627 2078B 2 CC05 2021 2021-08-26 SALIN 2.3223877203 #> 2628 2078B 2 CC05 2021 2021-08-26 TKN 0.2623642645 #> 2629 2078B 2 CC05 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2035 3F CC104 2015 2015-11-25 COND 7.2584121506 #> 2702 2035 3F CC104 2015 2015-11-25 DO 1.8082887712 #> 2703 2035 3F CC104 2015 2015-11-25 DOSAT 4.2046926194 #> 2704 2035 3F CC104 2015 2015-11-25 SALIN -0.2231435513 + #> 2705 2035 3F CC104 2015 2015-12-30 COND 7.6563371664 #> 2706 2035 3F CC104 2015 2015-12-30 DO 1.8562979904 #> 2707 2035 3F CC104 2015 2015-12-30 DOSAT 4.3040650932 #> 2708 2035 3F CC104 2015 2015-12-30 SALIN 0.1310282624 + #> 2709 2035 3F CC104 2015 2015-05-21 COND 8.9299648747 #> 2710 2035 3F CC104 2015 2015-05-21 DO 1.6292405397 #> 2711 2035 3F CC104 2015 2015-05-21 DOSAT 4.1743872699 #> 2712 2035 3F CC104 2015 2015-05-21 SALIN 1.3787660947 + #> 2713 2035 3F CC104 2015 2015-06-04 COND 9.1162494486 #> 2714 2035 3F CC104 2015 2015-06-04 DO 1.5686159179 #> 2715 2035 3F CC104 2015 2015-06-04 DOSAT 4.1108738642 #> 2716 2035 3F CC104 2015 2015-06-04 SALIN 1.6054298910 + #> 2717 2035 3F CC104 2015 2015-07-15 COND 7.5559050936 #> 2718 2035 3F CC104 2015 2015-07-15 SALIN 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CC104 2018 2018-09-12 COND 6.2265366693 #> 2878 2035 3F CC104 2018 2018-09-12 DO 1.7749523509 #> 2879 2035 3F CC104 2018 2018-09-12 DOSAT 4.3040650932 + #> 2880 2035 3F CC104 2018 2018-09-12 SALIN -1.4271163556 #> 2881 2045 3M CC15 2018 2018-03-07 CHLAC 2.2617630985 #> 2882 2045 3M CC15 2018 2018-03-07 COND 10.0150289273 #> 2883 2045 3M CC15 2018 2018-03-07 DO 2.0281482473 #> 2884 2045 3M CC15 2018 2018-03-07 DOSAT 4.5475410732 #> 2885 2045 3M CC15 2018 2018-03-07 NO23 -5.5214609179 U #> 2886 2045 3M CC15 2018 2018-03-07 SALIN 2.6595599919 + #> 2887 2045 3M CC15 2018 2018-03-07 TKN -0.1743533871 #> 2888 2045 3M CC15 2018 2018-03-07 TN -0.1719752647 + #> 2889 2045 3M CC15 2018 2018-03-07 TP -1.8325814637 #> 2890 2045 3M CC15 2018 2018-03-07 TSS 1.0986122887 U #> 2891 2045 3M CC15 2018 2018-03-07 TURB 1.2809338455 #> 2892 2045 3M CC15 2018 2018-04-09 CHLAC 1.8870696490 #> 2893 2045 3M CC15 2018 2018-04-09 COND 10.4012279368 #> 2894 2045 3M CC15 2018 2018-04-09 DO 1.7227665977 #> 2895 2045 3M CC15 2018 2018-04-09 DOSAT 4.3438054219 #> 2896 2045 3M CC15 2018 2018-04-09 NO23 -5.5214609179 I #> 2897 2045 3M CC15 2018 2018-04-09 SALIN 3.0017143452 + #> 2898 2045 3M CC15 2018 2018-04-09 TKN -0.2357223335 #> 2899 2045 3M CC15 2018 2018-04-09 TN -0.2306718177 + #> 2900 2045 3M CC15 2018 2018-04-09 TP -1.5606477483 #> 2901 2045 3M CC15 2018 2018-04-09 TSS 2.7080502011 #> 2902 2045 3M CC15 2018 2018-04-09 TURB 1.8718021769 A #> 2903 2045 3M CC15 2018 2018-05-24 CHLAC 2.3978952728 #> 2904 2045 3M CC15 2018 2018-05-24 COND 9.3056505518 #> 2905 2045 3M CC15 2018 2018-05-24 DO 1.9198594719 #> 2906 2045 3M CC15 2018 2018-05-24 DOSAT 4.4589876758 #> 2907 2045 3M CC15 2018 2018-05-24 NO23 -3.3524072175 #> 2908 2045 3M CC15 2018 2018-05-24 SALIN 1.7833912196 + #> 2909 2045 3M CC15 2018 2018-05-24 TKN -0.1392620673 #> 2910 2045 3M CC15 2018 2018-05-24 TN -0.0998203353 + #> 2911 2045 3M CC15 2018 2018-05-24 TP -1.6094379124 #> 2912 2045 3M CC15 2018 2018-05-24 TSS 1.7917594692 I #> 2913 2045 3M CC15 2018 2018-05-24 TURB 1.3350010667 #> 2914 2045 3M CC15 2018 2018-05-24 SALIN 1.8991179875 + #> 2915 2045 3M CC15 2018 2018-05-24 COND 9.4091912307 #> 2916 2045 3M CC15 2018 2018-05-24 DO 1.7833912196 #> 2917 2045 3M CC15 2018 2018-05-24 DOSAT 4.3630986248 #> 2918 2045 3M CC15 2018 2018-05-24 CHLAC 2.2925347571 #> 2919 2045 3M CC15 2018 2018-05-24 COND 9.3056505518 #> 2920 2045 3M CC15 2018 2018-05-24 DO 1.9198594719 #> 2921 2045 3M CC15 2018 2018-05-24 DOSAT 4.4589876758 #> 2922 2045 3M CC15 2018 2018-05-24 NO23 -3.4737680745 #> 2923 2045 3M CC15 2018 2018-05-24 SALIN 1.7833912196 + #> 2924 2045 3M CC15 2018 2018-05-24 TKN -0.1053605157 #> 2925 2045 3M CC15 2018 2018-05-24 TN -0.0714960017 + #> 2926 2045 3M CC15 2018 2018-05-24 TP -1.6094379124 #> 2927 2045 3M CC15 2018 2018-05-24 TSS 1.7917594692 I #> 2928 2045 3M CC15 2018 2018-05-24 TURB 1.2237754316 #> 2929 2045 3M CC15 2018 2018-07-23 CHLAC 2.0149030205 #> 2930 2045 3M CC15 2018 2018-07-23 COND 6.5087691370 #> 2931 2045 3M CC15 2018 2018-07-23 DO 1.7800242130 #> 2932 2045 3M CC15 2018 2018-07-23 DOSAT 4.3567088267 #> 2933 2045 3M CC15 2018 2018-07-23 NO23 -1.9661128564 #> 2934 2045 3M CC15 2018 2018-07-23 SALIN -1.1394342832 #> 2935 2045 3M CC15 2018 2018-07-23 TKN 0.1823215568 #> 2936 2045 3M CC15 2018 2018-07-23 TN 0.2926696140 + #> 2937 2045 3M CC15 2018 2018-07-23 TP -1.1394342832 #> 2938 2045 3M CC15 2018 2018-07-23 TSS 1.3862943611 I #> 2939 2045 3M CC15 2018 2018-07-23 TURB 1.3083328197 #> 2940 2045 3M CC15 2018 2018-08-21 CHLAC 2.0794415417 #> 2941 2045 3M CC15 2018 2018-08-21 COND 6.4393503711 #> 2942 2045 3M CC15 2018 2018-08-21 DO 1.6601310267 #> 2943 2045 3M CC15 2018 2018-08-21 DOSAT 4.2341065046 #> 2944 2045 3M CC15 2018 2018-08-21 NO23 -2.6736487744 #> 2945 2045 3M CC15 2018 2018-08-21 SALIN -1.2039728043 #> 2946 2045 3M CC15 2018 2018-08-21 TKN 0.0953101798 #> 2947 2045 3M CC15 2018 2018-08-21 TN 0.1561486825 + #> 2948 2045 3M CC15 2018 2018-08-21 TP -1.2378743560 #> 2949 2045 3M CC15 2018 2018-08-21 TSS 1.0986122887 I #> 2950 2045 3M CC15 2018 2018-08-21 TURB 1.0986122887 #> 2951 2045 3M CC15 2018 2018-08-21 COND 6.4264884575 #> 2952 2045 3M CC15 2018 2018-08-21 DO 1.6114359151 #> 2953 2045 3M CC15 2018 2018-08-21 DOSAT 4.1774594689 #> 2954 2045 3M CC15 2018 2018-08-21 SALIN -1.2039728043 #> 2955 2045 3M CC15 2019 2019-02-07 CHLAC 3.2188758249 A #> 2956 2045 3M CC15 2019 2019-02-07 COND 8.6916505732 #> 2957 2045 3M CC15 2019 2019-02-07 NO23 -5.1159958098 I #> 2958 2045 3M CC15 2019 2019-02-07 SALIN 1.1755733298 #> 2959 2045 3M CC15 2019 2019-02-07 TKN 0.0953101798 #> 2960 2045 3M CC15 2019 2019-02-07 TN 0.0989399479 + #> 2961 2045 3M CC15 2019 2019-02-07 TP -1.6607312068 #> 2962 2045 3M CC15 2019 2019-02-07 TSS 2.3025850930 I #> 2963 2045 3M CC15 2019 2019-02-07 TURB 2.0281482473 #> 2964 2045 3M CC15 2019 2019-03-13 CHLAC 1.8870696490 #> 2965 2045 3M CC15 2019 2019-03-13 COND 9.4304392931 #> 2966 2045 3M CC15 2019 2019-03-13 DO 1.8961194846 #> 2967 2045 3M CC15 2019 2019-03-13 DOSAT 4.4188406078 #> 2968 2045 3M CC15 2019 2019-03-13 NO23 -5.2983173665 I #> 2969 2045 3M CC15 2019 2019-03-13 SALIN 1.9657127764 #> 2970 2045 3M CC15 2019 2019-03-13 TKN -0.1625189295 #> 2971 2045 3M CC15 2019 2019-03-13 TN -0.1578240852 + #> 2972 2045 3M CC15 2019 2019-03-13 TP -1.8325814637 #> 2973 2045 3M CC15 2019 2019-03-13 TSS 2.0794415417 I #> 2974 2045 3M CC15 2019 2019-03-13 TURB 1.5892352051 #> 2975 2045 3M CC15 2019 2019-04-23 CHLAC 1.7749523509 #> 2976 2045 3M CC15 2019 2019-04-23 COND 9.9110588180 #> 2977 2045 3M CC15 2019 2019-04-23 DO 1.8562979904 #> 2978 2045 3M CC15 2019 2019-04-23 DOSAT 4.3845235149 #> 2979 2045 3M CC15 2019 2019-04-23 NO23 -5.5214609179 U #> 2980 2045 3M CC15 2019 2019-04-23 SALIN 2.4882344399 #> 2981 2045 3M CC15 2019 2019-04-23 TKN -0.2744368457 #> 2982 2045 3M CC15 2019 2019-04-23 TN -0.2718087233 + #> 2983 2045 3M CC15 2019 2019-04-23 TP -1.6607312068 #> 2984 2045 3M CC15 2019 2019-04-23 TSS 2.0794415417 I #> 2985 2045 3M CC15 2019 2019-04-23 TURB 1.4586150227 #> 2986 2045 3M CC15 2019 2019-04-23 CHLAC 1.1631508098 #> 2987 2045 3M CC15 2019 2019-04-23 NO23 -5.5214609179 U #> 2988 2045 3M CC15 2019 2019-04-23 TKN -0.2876820725 #> 2989 2045 3M CC15 2019 2019-04-23 TN -0.2850189550 + #> 2990 2045 3M CC15 2019 2019-04-23 TP -1.7147984281 #> 2991 2045 3M CC15 2019 2019-04-23 TSS 1.9459101491 I #> 2992 2045 3M CC15 2019 2019-04-23 TURB 1.0296194172 #> 2993 2045 3M CC15 2019 2019-07-22 CHLAC 2.4849066498 #> 2994 2045 3M CC15 2019 2019-07-22 COND 8.5083542427 #> 2995 2045 3M CC15 2019 2019-07-22 DO 1.7227665977 #> 2996 2045 3M CC15 2019 2019-07-22 DOSAT 4.3174881135 #> 2997 2045 3M CC15 2019 2019-07-22 NO23 -3.5065578973 #> 2998 2045 3M CC15 2019 2019-07-22 SALIN 0.9707789172 #> 2999 2045 3M CC15 2019 2019-07-22 TKN -0.0512932944 #> 3000 2045 3M CC15 2019 2019-07-22 TN -0.0202027073 + #> 3001 2045 3M CC15 2019 2019-07-22 TP -1.1086626245 #> 3002 2045 3M CC15 2019 2019-07-22 TSS 1.6094379124 I #> 3003 2045 3M CC15 2019 2019-07-22 TURB 1.3862943611 #> 3004 2045 3M CC15 2019 2019-09-04 COND 7.2896105215 #> 3005 2045 3M CC15 2019 2019-09-04 DO 1.6213664833 #> 3006 2045 3M CC15 2019 2019-09-04 DOSAT 4.2061840440 #> 3007 2045 3M CC15 2019 2019-09-04 NO23 -2.4191189092 #> 3008 2045 3M CC15 2019 2019-09-04 SALIN -0.3147107448 #> 3009 2045 3M CC15 2019 2019-09-04 TKN 0.1823215568 #> 3010 2045 3M CC15 2019 2019-09-04 TN 0.2538667240 + #> 3011 2045 3M CC15 2019 2019-09-04 TP -0.9675840263 #> 3012 2045 3M CC15 2019 2019-09-04 TSS 1.0986122887 I #> 3013 2045 3M CC15 2019 2019-09-04 TURB 1.0986122887 #> 3014 2045 3M CC15 2020 2020-02-18 CHLAC 2.7080502011 #> 3015 2045 3M CC15 2020 2020-02-18 COND 10.0136863448 #> 3016 2045 3M CC15 2020 2020-02-18 DO 1.9358598132 #> 3017 2045 3M CC15 2020 2020-02-18 DOSAT 4.5272086445 #> 3018 2045 3M CC15 2020 2020-02-18 NO23 -4.8283137373 I #> 3019 2045 3M CC15 2020 2020-02-18 SALIN 2.5967461315 #> 3020 2045 3M CC15 2020 2020-02-18 TKN -0.1165338163 #> 3021 2045 3M CC15 2020 2020-02-18 TN -0.1120495038 + #> 3022 2045 3M CC15 2020 2020-02-18 TP -1.6094379124 #> 3023 2045 3M CC15 2020 2020-02-18 TSS 2.7080502011 #> 3024 2045 3M CC15 2020 2020-02-18 TURB 1.7227665977 #> 3025 2045 3M CC15 2020 2020-02-18 COND 10.0120728629 #> 3026 2045 3M CC15 2020 2020-02-18 DO 1.9227877316 #> 3027 2045 3M CC15 2020 2020-02-18 DOSAT 4.5086592856 #> 3028 2045 3M CC15 2020 2020-02-18 SALIN 2.5952547070 #> 3029 2045 3M CC15 2020 2020-06-09 CHLAC 2.4849066498 #> 3030 2045 3M CC15 2020 2020-06-09 COND 9.2513863414 #> 3031 2045 3M CC15 2020 2020-06-09 DO 1.9315214116 #> 3032 2045 3M CC15 2020 2020-06-09 DOSAT 4.5239601306 #> 3033 2045 3M CC15 2020 2020-06-09 NO23 -3.3813947544 #> 3034 2045 3M CC15 2020 2020-06-09 SALIN 1.7664416612 #> 3035 2045 3M CC15 2020 2020-06-09 TKN -0.0304592075 #> 3036 2045 3M CC15 2020 2020-06-09 TN 0.0039920213 + #> 3037 2045 3M CC15 2020 2020-06-09 TP -1.4696759701 #> 3038 2045 3M CC15 2020 2020-06-09 TSS 1.0986122887 I #> 3039 2045 3M CC15 2020 2020-06-09 TURB 0.9162907319 #> 3040 2045 3M CC15 2020 2020-06-09 COND 9.5815590414 #> 3041 2045 3M CC15 2020 2020-06-09 DO 1.6544112781 #> 3042 2045 3M CC15 2020 2020-06-09 DOSAT 4.2076732475 #> 3043 2045 3M CC15 2020 2020-06-09 SALIN 2.1552445051 #> 3044 2045 3M CC15 2020 2020-08-10 COND 9.2688922589 #> 3045 2045 3M CC15 2020 2020-08-10 DO 1.6370530795 #> 3046 2045 3M CC15 2020 2020-08-10 DOSAT 4.2710950740 #> 3047 2045 3M CC15 2020 2020-08-10 SALIN -1.4567168254 #> 3048 2045 3M CC15 2020 2020-08-10 COND 9.4812068515 #> 3049 2045 3M CC15 2020 2020-08-10 DO 1.4398351280 #> 3050 2045 3M CC15 2020 2020-08-10 DOSAT 4.0758410907 #> 3051 2045 3M CC15 2020 2020-08-10 SALIN 0.2207406667 #> 3052 2045 3M CC15 2020 2020-09-22 CHLAC 2.2192034841 #> 3053 2045 3M CC15 2020 2020-09-22 COND 6.5750758406 #> 3054 2045 3M CC15 2020 2020-09-22 DO 1.7934247485 #> 3055 2045 3M CC15 2020 2020-09-22 DOSAT 4.3359826962 #> 3056 2045 3M CC15 2020 2020-09-22 NO23 -2.7968814148 #> 3057 2045 3M CC15 2020 2020-09-22 SALIN -1.0498221245 #> 3058 2045 3M CC15 2020 2020-09-22 TKN 0.2623642645 #> 3059 2045 3M CC15 2020 2020-09-22 TN 0.3082197237 + #> 3060 2045 3M CC15 2020 2020-09-22 TP -0.9942522733 #> 3061 2045 3M CC15 2020 2020-09-22 TSS 1.3862943611 I #> 3062 2045 3M CC15 2020 2020-09-22 TURB 1.2809338455 #> 3063 2045 3M CC15 2020 2020-10-20 CHLAC 3.0445224377 #> 3064 2045 3M CC15 2020 2020-10-20 COND 8.3209349689 #> 3065 2045 3M CC15 2020 2020-10-20 DO 1.7119945008 #> 3066 2045 3M CC15 2020 2020-10-20 DOSAT 4.2640873368 #> 3067 2045 3M CC15 2020 2020-10-20 NO23 -2.5010360317 #> 3068 2045 3M CC15 2020 2020-10-20 SALIN 0.7747271676 #> 3069 2045 3M CC15 2020 2020-10-20 TKN 0.2623642645 #> 3070 2045 3M CC15 2020 2020-10-20 TN 0.3235317253 + #> 3071 2045 3M CC15 2020 2020-10-20 TP -0.9942522733 #> 3072 2045 3M CC15 2020 2020-10-20 TSS 1.6094379124 I #> 3073 2045 3M CC15 2020 2020-10-20 TURB 1.2809338455 #> 3074 2045 3M CC15 2020 2020-12-14 CHLAC 2.6390573296 #> 3075 2045 3M CC15 2020 2020-12-14 COND 9.2314166976 #> 3076 2045 3M CC15 2020 2020-12-14 DO 2.0930978681 #> 3077 2045 3M CC15 2020 2020-12-14 DOSAT 4.5695430083 #> 3078 2045 3M CC15 2020 2020-12-14 NO23 -4.9618451299 I #> 3079 2045 3M CC15 2020 2020-12-14 SALIN 1.7526720805 #> 3080 2045 3M CC15 2020 2020-12-14 TKN 0.0000000000 #> 3081 2045 3M CC15 2020 2020-12-14 TN 0.0039920213 + #> 3082 2045 3M CC15 2020 2020-12-14 TP -1.4696759701 #> 3083 2045 3M CC15 2020 2020-12-14 TSS 1.6094379124 I #> 3084 2045 3M CC15 2020 2020-12-14 TURB 1.3609765531 A #> 3085 2045 3M CC15 2021 2021-02-03 CHLAC 1.7404661748 #> 3086 2045 3M CC15 2021 2021-02-03 COND 9.8506140629 #> 3087 2045 3M CC15 2021 2021-02-03 DO 2.1424163408 #> 3088 2045 3M CC15 2021 2021-02-03 DOSAT 4.5528237056 #> 3089 2045 3M CC15 2021 2021-02-03 NO23 -5.5214609179 U #> 3090 2045 3M CC15 2021 2021-02-03 SALIN 2.4248027257 #> 3091 2045 3M CC15 2021 2021-02-03 TKN -0.3424903089 #> 3092 2045 3M CC15 2021 2021-02-03 TN -0.3396773676 + #> 3093 2045 3M CC15 2021 2021-02-03 TP -1.9661128564 #> 3094 2045 3M CC15 2021 2021-02-03 TSS 1.3862943611 I #> 3095 2045 3M CC15 2021 2021-02-03 TURB 1.0296194172 #> 3096 2045 3M CC15 2021 2021-03-09 CHLAC 2.4849066498 #> 3097 2045 3M CC15 2021 2021-03-09 COND 9.8787336881 #> 3098 2045 3M CC15 2021 2021-03-09 DO 2.1690537004 #> 3099 2045 3M CC15 2021 2021-03-09 DOSAT 4.6510991179 #> 3100 2045 3M CC15 2021 2021-03-09 NO23 -5.5214609179 I #> 3101 2045 3M CC15 2021 2021-03-09 SALIN 2.4544474423 #> 3102 2045 3M CC15 2021 2021-03-09 TKN 0.0000000000 #> 3103 2045 3M CC15 2021 2021-03-09 TN 0.0039920213 + #> 3104 2045 3M CC15 2021 2021-03-09 TP -1.4696759701 #> 3105 2045 3M CC15 2021 2021-03-09 TSS 3.2958368660 #> 3106 2045 3M CC15 2021 2021-03-09 TURB 2.3978952728 A #> 3107 2045 3M CC15 2021 2021-05-05 CHLAC 1.8082887712 #> 3108 2045 3M CC15 2021 2021-05-05 COND 10.2487071336 #> 3109 2045 3M CC15 2021 2021-05-05 DO 1.8082887712 #> 3110 2045 3M CC15 2021 2021-05-05 DOSAT 4.4986979415 #> 3111 2045 3M CC15 2021 2021-05-05 NO23 -5.5214609179 U #> 3112 2045 3M CC15 2021 2021-05-05 SALIN 2.8489708922 #> 3113 2045 3M CC15 2021 2021-05-05 TKN -0.2231435513 #> 3114 2045 3M CC15 2021 2021-05-05 TN -0.2206466711 + #> 3115 2045 3M CC15 2021 2021-05-05 TP -1.6094379124 #> 3116 2045 3M CC15 2021 2021-05-05 TSS 1.9459101491 I #> 3117 2045 3M CC15 2021 2021-05-05 TURB 1.3350010667 #> 3118 2045 3M CC15 2021 2021-06-03 CHLAC 1.8245492921 #> 3119 2045 3M CC15 2021 2021-06-03 COND 10.3770473511 #> 3120 2045 3M CC15 2021 2021-06-03 DO 1.7715567619 #> 3121 2045 3M CC15 2021 2021-06-03 DOSAT 4.4331949212 #> 3122 2045 3M CC15 2021 2021-06-03 NO23 -5.5214609179 U #> 3123 2045 3M CC15 2021 2021-06-03 SALIN 2.9937302709 #> 3124 2045 3M CC15 2021 2021-06-03 TKN -0.1743533871 #> 3125 2045 3M CC15 2021 2021-06-03 TN -0.1719752647 + #> 3126 2045 3M CC15 2021 2021-06-03 TP -1.5606477483 #> 3127 2045 3M CC15 2021 2021-06-03 TSS 1.7917594692 I #> 3128 2045 3M CC15 2021 2021-06-03 TURB 1.2237754316 #> 3129 2045 3M CC15 2021 2021-07-01 CHLAC 2.1860512767 #> 3130 2045 3M CC15 2021 2021-07-01 COND 10.1292277297 #> 3131 2045 3M CC15 2021 2021-07-01 DO 1.7351891177 #> 3132 2045 3M CC15 2021 2021-07-01 DOSAT 4.3541414312 #> 3133 2045 3M CC15 2021 2021-07-01 NO23 -5.5214609179 U #> 3134 2045 3M CC15 2021 2021-07-01 SALIN 2.7232671669 #> 3135 2045 3M CC15 2021 2021-07-01 TKN -0.4155154440 #> 3136 2045 3M CC15 2021 2021-07-01 TN -0.4124897230 + #> 3137 2045 3M CC15 2021 2021-07-01 TP -1.5606477483 #> 3138 2045 3M CC15 2021 2021-07-01 TSS 1.0986122887 U #> 3139 2045 3M CC15 2021 2021-07-01 TURB 1.3083328197 #> 3140 2045 3M CC15 2021 2021-07-29 CHLAC 1.5892352051 #> 3141 2045 3M CC15 2021 2021-07-29 COND 7.4764723812 #> 3142 2045 3M CC15 2021 2021-07-29 DO 1.4303112465 #> 3143 2045 3M CC15 2021 2021-07-29 DOSAT 4.0145795938 #> 3144 2045 3M CC15 2021 2021-07-29 NO23 -2.4769384801 #> 3145 2045 3M CC15 2021 2021-07-29 SALIN -0.1165338163 #> 3146 2045 3M CC15 2021 2021-07-29 TKN 0.3364722366 #> 3147 2045 3M CC15 2021 2021-07-29 TN 0.3947411447 + #> 3148 2045 3M CC15 2021 2021-07-29 TP -0.4780358009 #> 3149 2045 3M CC15 2021 2021-07-29 TSS 1.7917594692 I #> 3150 2045 3M CC15 2021 2021-07-29 TURB 1.6292405397 #> 3151 2045 3M CC15 2021 2021-08-25 CHLAC 2.7725887222 #> 3152 2045 3M CC15 2021 2021-08-25 COND 6.9107507880 #> 3153 2045 3M CC15 2021 2021-08-25 DO 1.3376291891 #> 3154 2045 3M CC15 2021 2021-08-25 DOSAT 3.9120230054 #> 3155 2045 3M CC15 2021 2021-08-25 NO23 -2.9565115604 #> 3156 2045 3M CC15 2021 2021-08-25 SALIN -0.7133498879 #> 3157 2045 3M CC15 2021 2021-08-25 TKN 0.0953101798 #> 3158 2045 3M CC15 2021 2021-08-25 TN 0.1414995623 + #> 3159 2045 3M CC15 2021 2021-08-25 TP -0.8915981193 #> 3160 2045 3M CC15 2021 2021-08-25 TSS 1.0986122887 I #> 3161 2045 3M CC15 2021 2021-08-25 TURB 1.0647107370 #> 3162 2045 3M CC15 2021 2021-09-23 CHLAC 2.2300144002 #> 3163 2045 3M CC15 2021 2021-09-23 COND 6.2653012127 #> 3164 2045 3M CC15 2021 2021-09-23 DO 1.4060969884 #> 3165 2045 3M CC15 2021 2021-09-23 DOSAT 3.9550824949 #> 3166 2045 3M CC15 2021 2021-09-23 NO23 -3.0365542681 #> 3167 2045 3M CC15 2021 2021-09-23 SALIN -1.3862943611 #> 3168 2045 3M CC15 2021 2021-09-23 TKN 0.0953101798 #> 3169 2045 3M CC15 2021 2021-09-23 TN 0.1380212979 + #> 3170 2045 3M CC15 2021 2021-09-23 TP -1.3093333200 #> 3171 2045 3M CC15 2021 2021-09-23 TSS 1.3862943611 I #> 3172 2045 3M CC15 2021 2021-09-23 TURB 1.2527629685 #> 3173 2045 3M CC15 2021 2021-10-21 CHLAC 3.5263605246 #> 3174 2045 3M CC15 2021 2021-10-21 COND 8.7135820054 #> 3175 2045 3M CC15 2021 2021-10-21 DO 1.7732559977 #> 3176 2045 3M CC15 2021 2021-10-21 DOSAT 4.2918283668 #> 3177 2045 3M CC15 2021 2021-10-21 NO23 -2.9957322736 #> 3178 2045 3M CC15 2021 2021-10-21 SALIN 1.1939224685 #> 3179 2045 3M CC15 2021 2021-10-21 TKN 0.2623642645 #> 3180 2045 3M CC15 2021 2021-10-21 TN 0.3001045925 + #> 3181 2045 3M CC15 2021 2021-10-21 TP -1.1711829815 #> 3182 2045 3M CC15 2021 2021-10-21 TSS 1.6094379124 I #> 3183 2045 3M CC15 2021 2021-10-21 TURB 1.2809338455 #> 3184 2045 3M CC15 2021 2021-11-22 COND 9.2692694395 #> 3185 2045 3M CC15 2021 2021-11-22 DO 1.9516081702 #> 3186 2045 3M CC15 2021 2021-11-22 DOSAT 4.4647580323 #> 3187 2045 3M CC15 2021 2021-11-22 NO23 -4.7105307016 I #> 3188 2045 3M CC15 2021 2021-11-22 SALIN 1.7917594692 #> 3189 2045 3M CC15 2021 2021-11-22 TKN -0.1863295782 #> 3190 2045 3M CC15 2021 2021-11-22 TN -0.1815218766 + #> 3191 2045 3M CC15 2021 2021-11-22 TP -1.7147984281 #> 3192 2045 3M CC15 2021 2021-11-22 TSS 1.0986122887 I #> 3193 2045 3M CC15 2021 2021-11-22 TURB 0.9932517730 #> 3194 2045 3M CC15 2022 2022-02-22 CHLAC 1.5040773968 #> 3195 2045 3M CC15 2022 2022-02-22 COND 10.3013572215 #> 3196 2045 3M CC15 2022 2022-02-22 DO 1.9169226122 #> 3197 2045 3M CC15 2022 2022-02-22 DOSAT 4.4986979415 #> 3198 2045 3M CC15 2022 2022-02-22 NO23 -5.5214609179 U #> 3199 2045 3M CC15 2022 2022-02-22 SALIN 2.9139797717 #> 3200 2045 3M CC15 2022 2022-02-22 TKN -0.3285040670 #> 3201 2045 3M CC15 2022 2022-02-22 TN -0.3257301401 + #> 3202 2045 3M CC15 2022 2022-02-22 TP -2.0402208285 #> 3203 2045 3M CC15 2022 2022-02-22 TSS 2.3978952728 #> 3204 2045 3M CC15 2022 2022-02-22 TURB 1.3083328197 #> 3205 2045 3M CC15 2022 2022-04-20 CHLAC 0.4700036292 U #> 3206 2045 3M CC15 2022 2022-04-20 COND 10.5349454823 #> 3207 2045 3M CC15 2022 2022-04-20 DO 1.6919391339 #> 3208 2045 3M CC15 2022 2022-04-20 DOSAT 4.2972854062 #> 3209 2045 3M CC15 2022 2022-04-20 NO23 -5.5214609179 U #> 3210 2045 3M CC15 2022 2022-04-20 SALIN 3.1722034167 #> 3211 2045 3M CC15 2022 2022-04-20 TKN -0.1508228897 #> 3212 2045 3M CC15 2022 2022-04-20 TN -0.1485000083 + #> 3213 2045 3M CC15 2022 2022-04-20 TP -1.9661128564 #> 3214 2045 3M CC15 2022 2022-04-20 TSS 2.5649493575 #> 3215 2045 3M CC15 2022 2022-04-20 TURB 1.8082887712 #> 3216 2043 3M CC16 2013 2013-02-26 CHLAC 2.9444389792 #> 3217 2043 3M CC16 2013 2013-02-26 COND 10.3228226922 #> 3218 2043 3M CC16 2013 2013-02-26 DO 1.7833912196 #> 3219 2043 3M CC16 2013 2013-02-26 DOSAT 4.3894986495 #> 3220 2043 3M CC16 2013 2013-02-26 NO23 -5.5214609179 U #> 3221 2043 3M CC16 2013 2013-02-26 SALIN 2.9301265165 + #> 3222 2043 3M CC16 2013 2013-02-26 TKN -0.0408219945 #> 3223 2043 3M CC16 2013 2013-02-26 TN -0.0387408283 + #> 3224 2043 3M CC16 2013 2013-02-26 TP -2.2072749132 #> 3225 2043 3M CC16 2013 2013-02-26 TSS 2.1972245773 I #> 3226 2043 3M CC16 2013 2013-02-26 TURB 1.6863989536 #> 3227 2043 3M CC16 2013 2013-04-08 CHLAC 2.9444389792 #> 3228 2043 3M CC16 2013 2013-04-08 COND 10.2957323225 #> 3229 2043 3M CC16 2013 2013-04-08 DO 2.0955609236 #> 3230 2043 3M CC16 2013 2013-04-08 DOSAT 4.6913478822 #> 3231 2043 3M CC16 2013 2013-04-08 NO23 -4.9618451299 I #> 3232 2043 3M CC16 2013 2013-04-08 SALIN 2.9096295745 + #> 3233 2043 3M CC16 2013 2013-04-08 TKN -0.0833816089 #> 3234 2043 3M CC16 2013 2013-04-08 TN -0.0790432073 + #> 3235 2043 3M CC16 2013 2013-04-08 TP -1.9661128564 #> 3236 2043 3M CC16 2013 2013-04-08 TSS 2.4849066498 #> 3237 2043 3M CC16 2013 2013-04-08 TURB 2.0014800002 #> 3238 2043 3M CC16 2013 2013-07-02 CHLAC 2.2300144002 #> 3239 2043 3M CC16 2013 2013-07-02 COND 7.4798641312 #> 3240 2043 3M CC16 2013 2013-07-02 DO 1.6114359151 #> 3241 2043 3M CC16 2013 2013-07-02 DOSAT 4.1351665567 #> 3242 2043 3M CC16 2013 2013-07-02 NO23 -3.7297014486 #> 3243 2043 3M CC16 2013 2013-07-02 SALIN -0.1392620673 + #> 3244 2043 3M CC16 2013 2013-07-02 TKN -0.0304592075 #> 3245 2043 3M CC16 2013 2013-07-02 TN -0.0060180723 + #> 3246 2043 3M CC16 2013 2013-07-02 TP -1.5606477483 #> 3247 2043 3M CC16 2013 2013-07-02 TSS 2.5649493575 #> 3248 2043 3M CC16 2013 2013-07-02 TURB 1.9169226122 #> 3249 2043 3M CC16 2013 2013-02-26 CHLAC 2.7080502011 #> 3250 2043 3M CC16 2013 2013-02-26 COND 10.4025037183 #> 3251 2043 3M CC16 2013 2013-02-26 DO 1.8405496334 #> 3252 2043 3M CC16 2013 2013-02-26 DOSAT 4.4612998156 #> 3253 2043 3M CC16 2013 2013-02-26 NO23 -3.9120230054 U #> 3254 2043 3M CC16 2013 2013-02-26 SALIN 3.0116056227 + #> 3255 2043 3M CC16 2013 2013-02-26 TKN -0.1278333715 #> 3256 2043 3M CC16 2013 2013-02-26 TN -0.1165338163 + #> 3257 2043 3M CC16 2013 2013-02-26 TP -1.8325814637 #> 3258 2043 3M CC16 2013 2013-02-26 TSS 2.6390573296 #> 3259 2043 3M CC16 2013 2013-02-26 TURB 2.0412203289 A #> 3260 2043 3M CC16 2013 2013-04-08 CHLAC 2.2407096893 #> 3261 2043 3M CC16 2013 2013-04-08 COND 10.3623670373 #> 3262 2043 3M CC16 2013 2013-04-08 DO 2.1871742415 #> 3263 2043 3M CC16 2013 2013-04-08 DOSAT 4.8023803553 #> 3264 2043 3M CC16 2013 2013-04-08 NO23 -4.5098600062 #> 3265 2043 3M CC16 2013 2013-04-08 SALIN 2.9678470701 + #> 3266 2043 3M CC16 2013 2013-04-08 TKN -0.2231435513 #> 3267 2043 3M CC16 2013 2013-04-08 TN -0.2094872249 + #> 3268 2043 3M CC16 2013 2013-04-08 TP -2.1202635362 #> 3269 2043 3M CC16 2013 2013-04-08 TSS 2.0794415417 I #> 3270 2043 3M CC16 2013 2013-04-08 TURB 1.3862943611 #> 3271 2043 3M CC16 2013 2013-07-02 CHLAC 2.6390573296 A #> 3272 2043 3M CC16 2013 2013-07-02 COND 6.1025585946 #> 3273 2043 3M CC16 2013 2013-07-02 DO 1.6253112616 #> 3274 2043 3M CC16 2013 2013-07-02 DOSAT 4.1399550735 #> 3275 2043 3M CC16 2013 2013-07-02 NO23 -3.6496587410 #> 3276 2043 3M CC16 2013 2013-07-02 SALIN -1.5606477483 + #> 3277 2043 3M CC16 2013 2013-07-02 TKN 1.3350010667 #> 3278 2043 3M CC16 2013 2013-07-02 TN 1.3418198710 + #> 3279 2043 3M CC16 2013 2013-07-02 TP -1.7147984281 #> 3280 2043 3M CC16 2013 2013-07-02 TSS 1.9459101491 I #> 3281 2043 3M CC16 2013 2013-07-02 TURB 1.2237754316 #> 3282 2043 3M CC16 2013 2013-02-26 CHLAC 2.1282317058 #> 3283 2043 3M CC16 2013 2013-02-26 NO23 -5.5214609179 U #> 3284 2043 3M CC16 2013 2013-02-26 TKN -0.2357223335 #> 3285 2043 3M CC16 2013 2013-02-26 TN -0.2331938872 + #> 3286 2043 3M CC16 2013 2013-02-26 TP -1.7147984281 #> 3287 2043 3M CC16 2013 2013-02-26 TSS 2.6390573296 #> 3288 2043 3M CC16 2013 2013-02-26 TURB 2.0014800002 #> 3289 2043 3M CC16 2013 2013-04-08 CHLAC 2.0014800002 #> 3290 2043 3M CC16 2013 2013-04-08 COND 10.4457827732 #> 3291 2043 3M CC16 2013 2013-04-08 DO 2.1222615389 #> 3292 2043 3M CC16 2013 2013-04-08 DOSAT 4.7229532216 #> 3293 2043 3M CC16 2013 2013-04-08 NO23 -5.1159958098 I #> 3294 2043 3M CC16 2013 2013-04-08 SALIN 3.0914968955 + #> 3295 2043 3M CC16 2013 2013-04-08 TKN -0.1984509387 #> 3296 2043 3M CC16 2013 2013-04-08 TN -0.1935847491 + #> 3297 2043 3M CC16 2013 2013-04-08 TP -2.0402208285 #> 3298 2043 3M CC16 2013 2013-04-08 TSS 2.1972245773 I #> 3299 2043 3M CC16 2013 2013-04-08 TURB 1.6094379124 #> 3300 2043 3M CC16 2013 2013-07-02 CHLAC 3.5835189385 #> 3301 2043 3M CC16 2013 2013-07-02 COND 7.3051882154 #> 3302 2043 3M CC16 2013 2013-07-02 DO 1.6752256530 #> 3303 2043 3M CC16 2013 2013-07-02 DOSAT 4.1956970565 #> 3304 2043 3M CC16 2013 2013-07-02 NO23 -3.8167128256 #> 3305 2043 3M CC16 2013 2013-07-02 SALIN -0.3285040670 + #> 3306 2043 3M CC16 2013 2013-07-02 TKN 0.1823215568 #> 3307 2043 3M CC16 2013 2013-07-02 TN 0.2004888607 + #> 3308 2043 3M CC16 2013 2013-07-02 TP -0.9942522733 #> 3309 2043 3M CC16 2013 2013-07-02 TSS 1.7917594692 I #> 3310 2043 3M CC16 2013 2013-07-02 TURB 1.6486586256 #> 3311 2043 3M CC16 2013 2013-10-07 CHLAC 3.7841896339 A #> 3312 2043 3M CC16 2013 2013-10-07 COND 6.6411821697 #> 3313 2043 3M CC16 2013 2013-10-07 NO23 -4.7105307016 I #> 3314 2043 3M CC16 2013 2013-10-07 SALIN -1.0498221245 + #> 3315 2043 3M CC16 2013 2013-10-07 TKN 0.1823215568 #> 3316 2043 3M CC16 2013 2013-10-07 TN 0.1856493469 + #> 3317 2043 3M CC16 2013 2013-10-07 TP -1.2729656758 #> 3318 2043 3M CC16 2013 2013-10-07 TSS 2.1972245773 I #> 3319 2043 3M CC16 2013 2013-10-07 TURB 1.7404661748 #> 3320 2043 3M CC16 2014 2014-06-26 COND 9.8119751520 #> 3321 2043 3M CC16 2014 2014-06-26 DO 2.4230312461 #> 3322 2043 3M CC16 2014 2014-06-26 DOSAT 5.0801613567 #> 3323 2043 3M CC16 2014 2014-06-26 COND 9.5792797987 #> 3324 2043 3M CC16 2014 2014-06-26 DO 1.2441545940 #> 3325 2043 3M CC16 2014 2014-06-26 DOSAT 3.9852734672 #> 3326 2043 3M CC16 2018 2018-03-07 CHLAC 1.8870696490 #> 3327 2043 3M CC16 2018 2018-03-07 COND 10.1527665775 #> 3328 2043 3M CC16 2018 2018-03-07 DO 1.9878743482 #> 3329 2043 3M CC16 2018 2018-03-07 DOSAT 4.5347477217 #> 3330 2043 3M CC16 2018 2018-03-07 NO23 -5.5214609179 U #> 3331 2043 3M CC16 2018 2018-03-07 SALIN 2.8081971497 + #> 3332 2043 3M CC16 2018 2018-03-07 TKN -0.3424903089 #> 3333 2043 3M CC16 2018 2018-03-07 TN -0.3396773676 + #> 3334 2043 3M CC16 2018 2018-03-07 TP -1.7719568419 #> 3335 2043 3M CC16 2018 2018-03-07 TSS 1.6094379124 I #> 3336 2043 3M CC16 2018 2018-03-07 TURB 1.0986122887 #> 3337 2043 3M CC16 2018 2018-03-07 COND 10.2049615773 #> 3338 2043 3M CC16 2018 2018-03-07 DO 2.0281482473 #> 3339 2043 3M CC16 2018 2018-03-07 DOSAT 4.5653893160 #> 3340 2043 3M CC16 2018 2018-03-07 SALIN 2.8701690506 + #> 3341 2043 3M CC16 2018 2018-04-09 CHLAC 1.9315214116 #> 3342 2043 3M CC16 2018 2018-04-09 COND 10.4399809231 #> 3343 2043 3M CC16 2018 2018-04-09 DO 1.8082887712 #> 3344 2043 3M CC16 2018 2018-04-09 DOSAT 4.4426512565 #> 3345 2043 3M CC16 2018 2018-04-09 NO23 -5.2983173665 I #> 3346 2043 3M CC16 2018 2018-04-09 SALIN 3.0445224377 + #> 3347 2043 3M CC16 2018 2018-04-09 TKN -0.3011050928 #> 3348 2043 3M CC16 2018 2018-04-09 TN -0.2957142441 + #> 3349 2043 3M CC16 2018 2018-04-09 TP -1.6607312068 #> 3350 2043 3M CC16 2018 2018-04-09 TSS 2.0794415417 I #> 3351 2043 3M CC16 2018 2018-04-09 TURB 1.4816045409 #> 3352 2043 3M CC16 2018 2018-05-24 CHLAC 2.2925347571 #> 3353 2043 3M CC16 2018 2018-05-24 COND 9.8201059436 #> 3354 2043 3M CC16 2018 2018-05-24 DO 1.7749523509 #> 3355 2043 3M CC16 2018 2018-05-24 DOSAT 4.3719762988 #> 3356 2043 3M CC16 2018 2018-05-24 NO23 -4.4228486292 #> 3357 2043 3M CC16 2018 2018-05-24 SALIN 2.3360198691 + #> 3358 2043 3M CC16 2018 2018-05-24 TKN -0.1984509387 #> 3359 2043 3M CC16 2018 2018-05-24 TN -0.1839228382 + #> 3360 2043 3M CC16 2018 2018-05-24 TP -1.6094379124 #> 3361 2043 3M CC16 2018 2018-05-24 TSS 2.3025850930 I #> 3362 2043 3M CC16 2018 2018-05-24 TURB 1.6863989536 #> 3363 2043 3M CC16 2018 2018-05-24 COND 9.8362788028 #> 3364 2043 3M CC16 2018 2018-05-24 DO 1.7698546338 #> 3365 2043 3M CC16 2018 2018-05-24 DOSAT 4.3681812279 #> 3366 2043 3M CC16 2018 2018-05-24 SALIN 2.3532782073 + #> 3367 2043 3M CC16 2018 2018-07-23 CHLAC 2.4849066498 #> 3368 2043 3M CC16 2018 2018-07-23 COND 7.2034055211 #> 3369 2043 3M CC16 2018 2018-07-23 DO 1.7833912196 #> 3370 2043 3M CC16 2018 2018-07-23 DOSAT 4.3694478525 #> 3371 2043 3M CC16 2018 2018-07-23 NO23 -2.1202635362 #> 3372 2043 3M CC16 2018 2018-07-23 SALIN -0.4004775666 #> 3373 2043 3M CC16 2018 2018-07-23 TKN 0.1823215568 #> 3374 2043 3M CC16 2018 2018-07-23 TN 0.2776317366 + #> 3375 2043 3M CC16 2018 2018-07-23 TP -1.1394342832 #> 3376 2043 3M CC16 2018 2018-07-23 TSS 1.0986122887 I #> 3377 2043 3M CC16 2018 2018-07-23 TURB 1.0986122887 #> 3378 2043 3M CC16 2018 2018-07-23 COND 7.2034055211 #> 3379 2043 3M CC16 2018 2018-07-23 DO 1.7578579176 #> 3380 2043 3M CC16 2018 2018-07-23 DOSAT 4.3438054219 #> 3381 2043 3M CC16 2018 2018-07-23 SALIN -0.4155154440 #> 3382 2043 3M CC16 2018 2018-08-21 CHLAC 2.8332133441 A #> 3383 2043 3M CC16 2018 2018-08-21 COND 6.5308776277 #> 3384 2043 3M CC16 2018 2018-08-21 DO 1.7083778603 #> 3385 2043 3M CC16 2018 2018-08-21 DOSAT 4.2931954210 #> 3386 2043 3M CC16 2018 2018-08-21 NO23 -2.8824035882 #> 3387 2043 3M CC16 2018 2018-08-21 SALIN -1.1086626245 #> 3388 2043 3M CC16 2018 2018-08-21 TKN 0.0953101798 #> 3389 2043 3M CC16 2018 2018-08-21 TN 0.1449657703 + #> 3390 2043 3M CC16 2018 2018-08-21 TP -1.2378743560 #> 3391 2043 3M CC16 2018 2018-08-21 TSS 1.0986122887 I #> 3392 2043 3M CC16 2018 2018-08-21 TURB 1.2809338455 #> 3393 2043 3M CC16 2018 2018-08-21 COND 6.5337888379 #> 3394 2043 3M CC16 2018 2018-08-21 DO 1.6882490929 #> 3395 2043 3M CC16 2018 2018-08-21 DOSAT 4.2724907476 #> 3396 2043 3M CC16 2018 2018-08-21 SALIN -1.1086626245 #> 3397 2043 3M CC16 2019 2019-02-07 CHLAC 3.1354942159 #> 3398 2043 3M CC16 2019 2019-02-07 COND 9.1573614472 #> 3399 2043 3M CC16 2019 2019-02-07 NO23 -5.5214609179 U #> 3400 2043 3M CC16 2019 2019-02-07 SALIN 1.6733512382 #> 3401 2043 3M CC16 2019 2019-02-07 TKN -0.0725706928 #> 3402 2043 3M CC16 2019 2019-02-07 TN -0.0704224643 + #> 3403 2043 3M CC16 2019 2019-02-07 TP -1.8325814637 #> 3404 2043 3M CC16 2019 2019-02-07 TSS 1.9459101491 I #> 3405 2043 3M CC16 2019 2019-02-07 TURB 1.6863989536 #> 3406 2043 3M CC16 2019 2019-03-13 CHLAC 2.1517622033 #> 3407 2043 3M CC16 2019 2019-03-13 COND 9.7229244488 #> 3408 2043 3M CC16 2019 2019-03-13 DO 1.7369512327 #> 3409 2043 3M CC16 2019 2019-03-13 DOSAT 4.2780540443 + #> 3410 2043 3M CC16 2019 2019-03-13 NO23 -5.5214609179 U #> 3411 2043 3M CC16 2019 2019-03-13 SALIN 2.2823823857 #> 3412 2043 3M CC16 2019 2019-03-13 TKN -0.2613647641 #> 3413 2043 3M CC16 2019 2019-03-13 TN -0.2587707290 + #> 3414 2043 3M CC16 2019 2019-03-13 TP -1.8971199849 #> 3415 2043 3M CC16 2019 2019-03-13 TSS 1.6094379124 I #> 3416 2043 3M CC16 2019 2019-03-13 TURB 1.2527629685 #> 3417 2043 3M CC16 2019 2019-03-13 COND 9.7228046524 #> 3418 2043 3M CC16 2019 2019-03-13 DO 1.6992786164 #> 3419 2043 3M CC16 2019 2019-03-13 DOSAT 4.2398868675 #> 3420 2043 3M CC16 2019 2019-03-13 SALIN 2.2823823857 #> 3421 2043 3M CC16 2019 2019-04-23 CHLAC 2.3978952728 #> 3422 2043 3M CC16 2019 2019-04-23 COND 9.9710060043 #> 3423 2043 3M CC16 2019 2019-04-23 DO 1.8341801851 #> 3424 2043 3M CC16 2019 2019-04-23 DOSAT 4.3707128748 #> 3425 2043 3M CC16 2019 2019-04-23 NO23 -5.5214609179 U #> 3426 2043 3M CC16 2019 2019-04-23 SALIN 2.5533438113 #> 3427 2043 3M CC16 2019 2019-04-23 TKN -0.1863295782 #> 3428 2043 3M CC16 2019 2019-04-23 TN -0.1839228382 + #> 3429 2043 3M CC16 2019 2019-04-23 TP -1.7147984281 #> 3430 2043 3M CC16 2019 2019-04-23 TSS 1.6094379124 I #> 3431 2043 3M CC16 2019 2019-04-23 TURB 1.0296194172 #> 3432 2043 3M CC16 2019 2019-07-22 CHLAC 2.4849066498 #> 3433 2043 3M CC16 2019 2019-07-22 COND 8.7887458819 #> 3434 2043 3M CC16 2019 2019-07-22 DO 1.7850704811 #> 3435 2043 3M CC16 2019 2019-07-22 DOSAT 4.3969152472 #> 3436 2043 3M CC16 2019 2019-07-22 NO23 -5.5214609179 U #> 3437 2043 3M CC16 2019 2019-07-22 SALIN 1.2669476035 #> 3438 2043 3M CC16 2019 2019-07-22 TKN -0.0833816089 #> 3439 2043 3M CC16 2019 2019-07-22 TN -0.0812100554 + #> 3440 2043 3M CC16 2019 2019-07-22 TP -1.2378743560 #> 3441 2043 3M CC16 2019 2019-07-22 TSS 1.0986122887 I #> 3442 2043 3M CC16 2019 2019-07-22 TURB 1.0986122887 #> 3443 2043 3M CC16 2019 2019-09-04 CHLAC 2.3025850930 #> 3444 2043 3M CC16 2019 2019-09-04 COND 7.9875244798 #> 3445 2043 3M CC16 2019 2019-09-04 DO 1.7101878155 #> 3446 2043 3M CC16 2019 2019-09-04 DOSAT 4.2972854062 #> 3447 2043 3M CC16 2019 2019-09-04 NO23 -2.3025850930 #> 3448 2043 3M CC16 2019 2019-09-04 SALIN 0.4187103349 #> 3449 2043 3M CC16 2019 2019-09-04 TKN 0.1823215568 #> 3450 2043 3M CC16 2019 2019-09-04 TN 0.2623642645 + #> 3451 2043 3M CC16 2019 2019-09-04 TP -0.9162907319 #> 3452 2043 3M CC16 2019 2019-09-04 TSS 1.7917594692 I #> 3453 2043 3M CC16 2019 2019-09-04 TURB 1.3350010667 #> 3454 2043 3M CC16 2020 2020-02-18 CHLAC 2.3978952728 #> 3455 2043 3M CC16 2020 2020-02-18 COND 10.0826374182 #> 3456 2043 3M CC16 2020 2020-02-18 DO 2.0202221820 #> 3457 2043 3M CC16 2020 2020-02-18 DOSAT 4.6170987569 #> 3458 2043 3M CC16 2020 2020-02-18 NO23 -5.5214609179 U #> 3459 2043 3M CC16 2020 2020-02-18 SALIN 2.6720775406 #> 3460 2043 3M CC16 2020 2020-02-18 TKN -0.1984509387 #> 3461 2043 3M CC16 2020 2020-02-18 TN -0.1960148839 + #> 3462 2043 3M CC16 2020 2020-02-18 TP -1.7147984281 #> 3463 2043 3M CC16 2020 2020-02-18 TSS 2.4849066498 #> 3464 2043 3M CC16 2020 2020-02-18 TURB 1.5260563035 #> 3465 2043 3M CC16 2020 2020-02-18 COND 10.0856841015 #> 3466 2043 3M CC16 2020 2020-02-18 DO 2.0055258587 #> 3467 2043 3M CC16 2020 2020-02-18 DOSAT 4.6001576442 #> 3468 2043 3M CC16 2020 2020-02-18 SALIN 2.6755270094 #> 3469 2043 3M CC16 2020 2020-06-09 CHLAC 1.9459101491 #> 3470 2043 3M CC16 2020 2020-06-09 COND 9.1632487644 #> 3471 2043 3M CC16 2020 2020-06-09 DO 1.8779371655 #> 3472 2043 3M CC16 2020 2020-06-09 DOSAT 4.4716387934 #> 3473 2043 3M CC16 2020 2020-06-09 NO23 -3.5404594490 #> 3474 2043 3M CC16 2020 2020-06-09 SALIN 1.6695918353 #> 3475 2043 3M CC16 2020 2020-06-09 TKN -0.1743533871 #> 3476 2043 3M CC16 2020 2020-06-09 TN -0.1404121537 + #> 3477 2043 3M CC16 2020 2020-06-09 TP -1.5606477483 #> 3478 2043 3M CC16 2020 2020-06-09 TSS 1.0986122887 I #> 3479 2043 3M CC16 2020 2020-06-09 TURB 0.8329091229 #> 3480 2043 3M CC16 2020 2020-06-09 COND 9.4707797080 #> 3481 2043 3M CC16 2020 2020-06-09 DO 1.8855533485 #> 3482 2043 3M CC16 2020 2020-06-09 DOSAT 4.4986979415 #> 3483 2043 3M CC16 2020 2020-06-09 SALIN 2.0041790572 #> 3484 2043 3M CC16 2020 2020-08-10 COND 9.6776528834 #> 3485 2043 3M CC16 2020 2020-08-10 DO 1.5973653312 #> 3486 2043 3M CC16 2020 2020-08-10 DOSAT 4.2541932632 #> 3487 2043 3M CC16 2020 2020-08-10 SALIN 2.2093727113 #> 3488 2043 3M CC16 2020 2020-09-22 CHLAC 2.1041341543 #> 3489 2043 3M CC16 2020 2020-09-22 COND 6.8012830345 #> 3490 2043 3M CC16 2020 2020-09-22 DO 1.8500283774 #> 3491 2043 3M CC16 2020 2020-09-22 DOSAT 4.3932138241 #> 3492 2043 3M CC16 2020 2020-09-22 NO23 -2.6882475738 #> 3493 2043 3M CC16 2020 2020-09-22 SALIN -0.8209805521 #> 3494 2043 3M CC16 2020 2020-09-22 TKN 0.1823215568 #> 3495 2043 3M CC16 2020 2020-09-22 TN 0.2374408560 + #> 3496 2043 3M CC16 2020 2020-09-22 TP -1.0498221245 #> 3497 2043 3M CC16 2020 2020-09-22 TSS 1.3862943611 I #> 3498 2043 3M CC16 2020 2020-09-22 TURB 1.1314021115 A #> 3499 2043 3M CC16 2020 2020-10-20 CHLAC 2.3978952728 #> 3500 2043 3M CC16 2020 2020-10-20 COND 8.8590793179 #> 3501 2043 3M CC16 2020 2020-10-20 DO 1.7281094422 #> 3502 2043 3M CC16 2020 2020-10-20 DOSAT 4.2835865619 #> 3503 2043 3M CC16 2020 2020-10-20 NO23 -2.2072749132 #> 3504 2043 3M CC16 2020 2020-10-20 SALIN 1.3480731483 #> 3505 2043 3M CC16 2020 2020-10-20 TKN 0.1823215568 #> 3506 2043 3M CC16 2020 2020-10-20 TN 0.2700271372 + #> 3507 2043 3M CC16 2020 2020-10-20 TP -1.1086626245 #> 3508 2043 3M CC16 2020 2020-10-20 TSS 1.7917594692 I #> 3509 2043 3M CC16 2020 2020-10-20 TURB 1.3350010667 #> 3510 2043 3M CC16 2020 2020-12-14 CHLAC 2.6390573296 #> 3511 2043 3M CC16 2020 2020-12-14 COND 9.3722891390 #> 3512 2043 3M CC16 2020 2020-12-14 DO 2.0554049639 #> 3513 2043 3M CC16 2020 2020-12-14 DOSAT 4.5261269786 #> 3514 2043 3M CC16 2020 2020-12-14 NO23 -5.5214609179 U #> 3515 2043 3M CC16 2020 2020-12-14 SALIN 1.9035989510 #> 3516 2043 3M CC16 2020 2020-12-14 TKN -0.0408219945 #> 3517 2043 3M CC16 2020 2020-12-14 TN -0.0387408283 + #> 3518 2043 3M CC16 2020 2020-12-14 TP -1.6094379124 #> 3519 2043 3M CC16 2020 2020-12-14 TSS 1.6094379124 I #> 3520 2043 3M CC16 2020 2020-12-14 TURB 1.2237754316 #> 3521 2043 3M CC16 2021 2021-02-03 CHLAC 2.3978952728 #> 3522 2043 3M CC16 2021 2021-02-03 COND 9.8437906253 #> 3523 2043 3M CC16 2021 2021-02-03 DO 2.0360119838 #> 3524 2043 3M CC16 2021 2021-02-03 DOSAT 4.4379342666 #> 3525 2043 3M CC16 2021 2021-02-03 NO23 -5.5214609179 U #> 3526 2043 3M CC16 2021 2021-02-03 SALIN 2.4185887688 #> 3527 2043 3M CC16 2021 2021-02-03 TKN -0.2484613593 #> 3528 2043 3M CC16 2021 2021-02-03 TN -0.2459005384 + #> 3529 2043 3M CC16 2021 2021-02-03 TP -2.2072749132 #> 3530 2043 3M CC16 2021 2021-02-03 TSS 1.3862943611 I #> 3531 2043 3M CC16 2021 2021-02-03 TURB 1.0986122887 #> 3532 2043 3M CC16 2021 2021-03-23 CHLAC 2.5649493575 #> 3533 2043 3M CC16 2021 2021-03-23 COND 10.0172179429 #> 3534 2043 3M CC16 2021 2021-03-23 DO 1.8484548129 #> 3535 2043 3M CC16 2021 2021-03-23 DOSAT 4.3320482649 #> 3536 2043 3M CC16 2021 2021-03-23 NO23 -5.5214609179 U #> 3537 2043 3M CC16 2021 2021-03-23 SALIN 2.6056482675 #> 3538 2043 3M CC16 2021 2021-03-23 TKN -0.1165338163 #> 3539 2043 3M CC16 2021 2021-03-23 TN -0.1142891464 + #> 3540 2043 3M CC16 2021 2021-03-23 TP -1.8971199849 #> 3541 2043 3M CC16 2021 2021-03-23 TSS 1.7917594692 I #> 3542 2043 3M CC16 2021 2021-03-23 TURB 1.3862943611 #> 3543 2043 3M CC16 2021 2021-05-05 CHLAC 2.2823823857 #> 3544 2043 3M CC16 2021 2021-05-05 COND 10.2634321453 #> 3545 2043 3M CC16 2021 2021-05-05 DO 1.7263316639 #> 3546 2043 3M CC16 2021 2021-05-05 DOSAT 4.4200447019 #> 3547 2043 3M CC16 2021 2021-05-05 NO23 -5.5214609179 I #> 3548 2043 3M CC16 2021 2021-05-05 SALIN 2.8650539499 #> 3549 2043 3M CC16 2021 2021-05-05 TKN -0.0833816089 #> 3550 2043 3M CC16 2021 2021-05-05 TN -0.0790432073 + #> 3551 2043 3M CC16 2021 2021-05-05 TP -1.5606477483 #> 3552 2043 3M CC16 2021 2021-05-05 TSS 2.0794415417 I #> 3553 2043 3M CC16 2021 2021-05-05 TURB 1.4816045409 #> 3554 2043 3M CC16 2021 2021-06-03 CHLAC 2.4849066498 #> 3555 2043 3M CC16 2021 2021-06-03 COND 10.3258753278 #> 3556 2043 3M CC16 2021 2021-06-03 DO 1.6524974019 #> 3557 2043 3M CC16 2021 2021-06-03 DOSAT 4.3094559418 #> 3558 2043 3M CC16 2021 2021-06-03 NO23 -5.5214609179 U #> 3559 2043 3M CC16 2021 2021-06-03 SALIN 2.9375733594 #> 3560 2043 3M CC16 2021 2021-06-03 TKN 0.0000000000 #> 3561 2043 3M CC16 2021 2021-06-03 TN 0.0019980027 + #> 3562 2043 3M CC16 2021 2021-06-03 TP -1.6607312068 #> 3563 2043 3M CC16 2021 2021-06-03 TSS 2.0794415417 I #> 3564 2043 3M CC16 2021 2021-06-03 TURB 1.4109869737 #> 3565 2043 3M CC16 2021 2021-07-01 CHLAC 3.0910424534 #> 3566 2043 3M CC16 2021 2021-07-01 COND 10.1819522754 #> 3567 2043 3M CC16 2021 2021-07-01 DO 1.6956156087 #> 3568 2043 3M CC16 2021 2021-07-01 DOSAT 4.3567088267 #> 3569 2043 3M CC16 2021 2021-07-01 NO23 -3.0791138825 #> 3570 2043 3M CC16 2021 2021-07-01 SALIN 2.7775762638 #> 3571 2043 3M CC16 2021 2021-07-01 TKN -0.2357223335 #> 3572 2043 3M CC16 2021 2021-07-01 TN -0.1791266659 + #> 3573 2043 3M CC16 2021 2021-07-01 TP -1.5606477483 #> 3574 2043 3M CC16 2021 2021-07-01 TSS 2.3025850930 #> 3575 2043 3M CC16 2021 2021-07-01 TURB 1.7404661748 #> 3576 2043 3M CC16 2022 2022-02-22 CHLAC 1.0986122887 #> 3577 2043 3M CC16 2022 2022-02-22 COND 10.3057809695 #> 3578 2043 3M CC16 2022 2022-02-22 DO 1.8794650496 #> 3579 2043 3M CC16 2022 2022-02-22 DOSAT 4.4543472963 #> 3580 2043 3M CC16 2022 2022-02-22 NO23 -4.9618451299 I #> 3581 2043 3M CC16 2022 2022-02-22 SALIN 2.9199305601 #> 3582 2043 3M CC16 2022 2022-02-22 TKN -0.4307829161 #> 3583 2043 3M CC16 2022 2022-02-22 TN -0.4246479275 + #> 3584 2043 3M CC16 2022 2022-02-22 TP -2.3859667019 #> 3585 2043 3M CC16 2022 2022-02-22 TSS 2.3025850930 I #> 3586 2043 3M CC16 2022 2022-02-22 TURB 0.6931471806 #> 3587 2043 3M CC16 2021 2021-02-03 CHLAC 3.1354942159 #> 3588 2043 3M CC16 2021 2021-02-03 COND 9.5834200199 #> 3589 2043 3M CC16 2021 2021-02-03 DO 2.0041790572 #> 3590 2043 3M CC16 2021 2021-02-03 DOSAT 4.4042772436 #> 3591 2043 3M CC16 2021 2021-02-03 NO23 -5.5214609179 U #> 3592 2043 3M CC16 2021 2021-02-03 SALIN 2.1365305087 #> 3593 2043 3M CC16 2021 2021-02-03 TKN -0.1278333715 #> 3594 2043 3M CC16 2021 2021-02-03 TN -0.1255632230 + #> 3595 2043 3M CC16 2021 2021-02-03 TP -2.1202635362 #> 3596 2043 3M CC16 2021 2021-02-03 TSS 1.9459101491 I #> 3597 2043 3M CC16 2021 2021-02-03 TURB 1.7578579176 #> 3598 2043 3M CC16 2021 2021-03-23 CHLAC 3.2188758249 #> 3599 2043 3M CC16 2021 2021-03-23 COND 9.8242819944 #> 3600 2043 3M CC16 2021 2021-03-23 DO 1.7867469274 #> 3601 2043 3M CC16 2021 2021-03-23 DOSAT 4.2640873368 #> 3602 2043 3M CC16 2021 2021-03-23 NO23 -5.5214609179 U #> 3603 2043 3M CC16 2021 2021-03-23 SALIN 2.3951642743 #> 3604 2043 3M CC16 2021 2021-03-23 TKN 0.0953101798 #> 3605 2043 3M CC16 2021 2021-03-23 TN 0.0971267107 + #> 3606 2043 3M CC16 2021 2021-03-23 TP -1.6094379124 #> 3607 2043 3M CC16 2021 2021-03-23 TSS 2.3978952728 #> 3608 2043 3M CC16 2021 2021-03-23 TURB 2.0412203289 #> 3609 2043 3M CC16 2021 2021-05-05 CHLAC 2.7725887222 #> 3610 2043 3M CC16 2021 2021-05-05 COND 10.1696522784 #> 3611 2043 3M CC16 2021 2021-05-05 DO 1.3711807233 #> 3612 2043 3M CC16 2021 2021-05-05 DOSAT 4.0342406382 #> 3613 2043 3M CC16 2021 2021-05-05 NO23 -5.5214609179 U #> 3614 2043 3M CC16 2021 2021-05-05 SALIN 2.7638002162 #> 3615 2043 3M CC16 2021 2021-05-05 TKN -0.0304592075 #> 3616 2043 3M CC16 2021 2021-05-05 TN -0.0283994745 + #> 3617 2043 3M CC16 2021 2021-05-05 TP -1.5606477483 #> 3618 2043 3M CC16 2021 2021-05-05 TSS 1.7917594692 I #> 3619 2043 3M CC16 2021 2021-05-05 TURB 1.5260563035 #> 3620 2043 3M CC16 2021 2021-06-03 CHLAC 2.8903717579 #> 3621 2043 3M CC16 2021 2021-06-03 COND 10.2473963549 #> 3622 2043 3M CC16 2021 2021-06-03 DO 1.5475625087 #> 3623 2043 3M CC16 2021 2021-06-03 DOSAT 4.2002049529 #> 3624 2043 3M CC16 2021 2021-06-03 NO23 -4.9618451299 I #> 3625 2043 3M CC16 2021 2021-06-03 SALIN 2.8518619031 #> 3626 2043 3M CC16 2021 2021-06-03 TKN 0.1823215568 #> 3627 2043 3M CC16 2021 2021-06-03 TN 0.1856493469 + #> 3628 2043 3M CC16 2021 2021-06-03 TP -1.5606477483 #> 3629 2043 3M CC16 2021 2021-06-03 TSS 2.3978952728 #> 3630 2043 3M CC16 2021 2021-06-03 TURB 1.6486586256 #> 3631 2043 3M CC16 2021 2021-07-01 CHLAC 3.4339872045 #> 3632 2043 3M CC16 2021 2021-07-01 COND 10.0458547938 #> 3633 2043 3M CC16 2021 2021-07-01 DO 1.9837562915 #> 3634 2043 3M CC16 2021 2021-07-01 DOSAT 4.6091622073 #> 3635 2043 3M CC16 2021 2021-07-01 NO23 -3.4420193762 #> 3636 2043 3M CC16 2021 2021-07-01 SALIN 2.6304489551 #> 3637 2043 3M CC16 2021 2021-07-01 TKN -0.0304592075 #> 3638 2043 3M CC16 2021 2021-07-01 TN 0.0019980027 + #> 3639 2043 3M CC16 2021 2021-07-01 TP -1.3862943611 #> 3640 2043 3M CC16 2021 2021-07-01 TSS 1.7917594692 I #> 3641 2043 3M CC16 2021 2021-07-01 TURB 1.6677068206 #> 3642 2043 3M CC16 2022 2022-02-22 CHLAC 1.6094379124 #> 3643 2043 3M CC16 2022 2022-02-22 COND 10.1823685085 #> 3644 2043 3M CC16 2022 2022-02-22 DO 1.7422190237 #> 3645 2043 3M CC16 2022 2022-02-22 DOSAT 4.3148178850 #> 3646 2043 3M CC16 2022 2022-02-22 NO23 -4.6051701860 I #> 3647 2043 3M CC16 2022 2022-02-22 SALIN 2.7788192720 #> 3648 2043 3M CC16 2022 2022-02-22 TKN -0.2484613593 #> 3649 2043 3M CC16 2022 2022-02-22 TN -0.2433462586 + #> 3650 2043 3M CC16 2022 2022-02-22 TP -2.3025850930 #> 3651 2043 3M CC16 2022 2022-02-22 TSS 2.4849066498 #> 3652 2043 3M CC16 2022 2022-02-22 TURB 1.6486586256 #> 3653 2048A 3M CC18 2013 2013-01-07 CHLAC 1.4816045409 #> 3654 2048A 3M CC18 2013 2013-01-07 COLOR 3.4011973817 #> 3655 2048A 3M CC18 2013 2013-01-07 DO 1.8082887712 #> 3656 2048A 3M CC18 2013 2013-01-07 DOSAT 4.3669129969 + #> 3657 2048A 3M CC18 2013 2013-01-07 NO23 -4.7105307016 I #> 3658 2048A 3M CC18 2013 2013-01-07 SALIN 3.1045866785 #> 3659 2048A 3M CC18 2013 2013-01-07 TKN -0.2876820725 #> 3660 2048A 3M CC18 2013 2013-01-07 TN -0.2823629110 + #> 3661 2048A 3M CC18 2013 2013-01-07 TP -2.4769384801 #> 3662 2048A 3M CC18 2013 2013-01-07 TURB 0.2623642645 #> 3663 2048A 3M CC18 2013 2013-02-04 CHLAC 1.3862943611 #> 3664 2048A 3M CC18 2013 2013-02-04 COLOR 3.1354942159 A #> 3665 2048A 3M CC18 2013 2013-02-04 DOSAT 4.3502779364 + #> 3666 2048A 3M CC18 2013 2013-02-04 NO23 -5.2983173665 I #> 3667 2048A 3M CC18 2013 2013-02-04 SALIN 3.1354942159 #> 3668 2048A 3M CC18 2013 2013-02-04 TKN -0.4942963218 #> 3669 2048A 3M CC18 2013 2013-02-04 TN -0.4877603508 + #> 3670 2048A 3M CC18 2013 2013-02-04 TP -3.4112477175 #> 3671 2048A 3M CC18 2013 2013-02-04 TURB 0.4700036292 #> 3672 2048A 3M CC18 2013 2013-03-04 CHLAC 1.8562979904 A #> 3673 2048A 3M CC18 2013 2013-03-04 COLOR 3.0910424534 A #> 3674 2048A 3M CC18 2013 2013-03-04 DO 1.7404661748 #> 3675 2048A 3M CC18 2013 2013-03-04 DOSAT 4.1926804629 + #> 3676 2048A 3M CC18 2013 2013-03-04 NO23 -3.6496587410 #> 3677 2048A 3M CC18 2013 2013-03-04 SALIN 3.2386784522 #> 3678 2048A 3M CC18 2013 2013-03-04 TKN 0.0000000000 #> 3679 2048A 3M CC18 2013 2013-03-04 TN 0.0256677467 + #> 3680 2048A 3M CC18 2013 2013-03-04 TP -2.4769384801 #> 3681 2048A 3M CC18 2013 2013-03-04 TURB 0.8329091229 #> 3682 2048A 3M CC18 2013 2013-04-01 CHLAC 1.5040773968 #> 3683 2048A 3M CC18 2013 2013-04-01 COLOR 2.8903717579 #> 3684 2048A 3M CC18 2013 2013-04-01 DO 1.4109869737 #> 3685 2048A 3M CC18 2013 2013-04-01 DOSAT 4.0000338828 + #> 3686 2048A 3M CC18 2013 2013-04-01 NO23 -4.9618451299 I #> 3687 2048A 3M CC18 2013 2013-04-01 SALIN 3.3105430134 #> 3688 2048A 3M CC18 2013 2013-04-01 TKN -0.2231435513 #> 3689 2048A 3M CC18 2013 2013-04-01 TN -0.2181560098 + #> 3690 2048A 3M CC18 2013 2013-04-01 TP -2.3025850930 #> 3691 2048A 3M CC18 2013 2013-04-01 TURB 1.0986122887 #> 3692 2048A 3M CC18 2013 2013-05-06 CHLAC 2.2617630985 #> 3693 2048A 3M CC18 2013 2013-05-06 COLOR 3.4339872045 #> 3694 2048A 3M CC18 2013 2013-05-06 DO 1.6677068206 #> 3695 2048A 3M CC18 2013 2013-05-06 DOSAT 4.2972854062 + #> 3696 2048A 3M CC18 2013 2013-05-06 NO23 -5.1159958098 I #> 3697 2048A 3M CC18 2013 2013-05-06 SALIN 3.2884018875 #> 3698 2048A 3M CC18 2013 2013-05-06 TKN -0.2876820725 #> 3699 2048A 3M CC18 2013 2013-05-06 TN -0.2823629110 + #> 3700 2048A 3M CC18 2013 2013-05-06 TP -1.8325814637 #> 3701 2048A 3M CC18 2013 2013-05-06 TURB 1.0647107370 #> 3702 2048A 3M CC18 2013 2013-06-03 CHLAC 2.0014800002 #> 3703 2048A 3M CC18 2013 2013-06-03 COLOR 3.5263605246 #> 3704 2048A 3M CC18 2013 2013-06-03 NO23 -5.2983173665 I #> 3705 2048A 3M CC18 2013 2013-06-03 TKN -0.0833816089 #> 3706 2048A 3M CC18 2013 2013-06-03 TN -0.0790432073 + #> 3707 2048A 3M CC18 2013 2013-06-03 TP -1.4271163556 #> 3708 2048A 3M CC18 2013 2013-06-03 TURB 0.9555114450 #> 3709 2048A 3M CC18 2013 2013-07-08 CHLAC 2.7080502011 #> 3710 2048A 3M CC18 2013 2013-07-08 COLOR 5.1929568509 #> 3711 2048A 3M CC18 2013 2013-07-08 DO 1.0296194172 #> 3712 2048A 3M CC18 2013 2013-07-08 DOSAT 3.5862928653 + #> 3713 2048A 3M CC18 2013 2013-07-08 NO23 -4.8283137373 I #> 3714 2048A 3M CC18 2013 2013-07-08 SALIN 1.0647107370 #> 3715 2048A 3M CC18 2013 2013-07-08 TKN 0.0000000000 #> 3716 2048A 3M CC18 2013 2013-07-08 TN 0.0039920213 + #> 3717 2048A 3M CC18 2013 2013-07-08 TP -1.8971199849 #> 3718 2048A 3M CC18 2013 2013-07-08 TURB 0.5877866649 A #> 3719 2048A 3M CC18 2013 2013-08-05 CHLAC 2.5649493575 #> 3720 2048A 3M CC18 2013 2013-08-05 COLOR 5.1357984371 #> 3721 2048A 3M CC18 2013 2013-08-05 DOSAT 3.3877743613 + #> 3722 2048A 3M CC18 2013 2013-08-05 NO23 -4.1997050779 #> 3723 2048A 3M CC18 2013 2013-08-05 SALIN 1.3083328197 #> 3724 2048A 3M CC18 2013 2013-08-05 TKN 0.2623642645 #> 3725 2048A 3M CC18 2013 2013-08-05 TN 0.2738366656 + #> 3726 2048A 3M CC18 2013 2013-08-05 TP -1.3862943611 #> 3727 2048A 3M CC18 2013 2013-08-05 TURB 0.8329091229 #> 3728 2048A 3M CC18 2013 2013-10-07 CHLAC 2.2617630985 #> 3729 2048A 3M CC18 2013 2013-10-07 COLOR 5.0106352941 #> 3730 2048A 3M CC18 2013 2013-10-07 DO 1.8562979904 #> 3731 2048A 3M CC18 2013 2013-10-07 DOSAT 4.4079380165 + #> 3732 2048A 3M CC18 2013 2013-10-07 NO23 -4.6051701860 #> 3733 2048A 3M CC18 2013 2013-10-07 SALIN 1.1631508098 #> 3734 2048A 3M CC18 2013 2013-10-07 TKN -0.1863295782 #> 3735 2048A 3M CC18 2013 2013-10-07 TN -0.1743533871 + #> 3736 2048A 3M CC18 2013 2013-10-07 TP -1.9661128564 #> 3737 2048A 3M CC18 2013 2013-10-07 TURB 0.4700036292 #> 3738 2048A 3M CC18 2013 2013-11-04 CHLAC 2.0541237337 #> 3739 2048A 3M CC18 2013 2013-11-04 COLOR 4.3820266347 #> 3740 2048A 3M CC18 2013 2013-11-04 DO 1.5892352051 #> 3741 2048A 3M CC18 2013 2013-11-04 DOSAT 4.0893320204 + #> 3742 2048A 3M CC18 2013 2013-11-04 NO23 -4.2686979494 #> 3743 2048A 3M CC18 2013 2013-11-04 SALIN 2.5176964726 #> 3744 2048A 3M CC18 2013 2013-11-04 TKN -0.4462871026 #> 3745 2048A 3M CC18 2013 2013-11-04 TN -0.4246479275 + #> 3746 2048A 3M CC18 2013 2013-11-04 TP -1.6607312068 #> 3747 2048A 3M CC18 2013 2013-11-04 TURB 0.4700036292 #> 3748 2048A 3M CC18 2013 2013-12-02 CHLAC 1.9878743482 #> 3749 2048A 3M CC18 2013 2013-12-02 COLOR 3.7612001157 #> 3750 2048A 3M CC18 2013 2013-12-02 DO 1.9459101491 #> 3751 2048A 3M CC18 2013 2013-12-02 DOSAT 4.4461744545 + #> 3752 2048A 3M CC18 2013 2013-12-02 NO23 -4.3428059215 #> 3753 2048A 3M CC18 2013 2013-12-02 SALIN 2.9444389792 #> 3754 2048A 3M CC18 2013 2013-12-02 TKN -0.4462871026 #> 3755 2048A 3M CC18 2013 2013-12-02 TN -0.4261781497 + #> 3756 2048A 3M CC18 2013 2013-12-02 TP -2.3227878003 #> 3757 2048A 3M CC18 2013 2013-12-02 TURB 0.5877866649 A #> 3758 2048A 3M CC18 2014 2014-01-06 DO 1.7917594692 #> 3759 2048A 3M CC18 2014 2014-01-06 DOSAT 4.3107991254 + #> 3760 2048A 3M CC18 2014 2014-01-06 NO23 -4.7105307016 I #> 3761 2048A 3M CC18 2014 2014-01-06 SALIN 3.0819099698 #> 3762 2048A 3M CC18 2014 2014-01-06 TKN -0.3011050928 #> 3763 2048A 3M CC18 2014 2014-01-06 TN -0.2957142441 + #> 3764 2048A 3M CC18 2014 2014-01-06 TP -2.7333680091 #> 3765 2048A 3M CC18 2014 2014-02-03 CHLAC 1.3350010667 #> 3766 2048A 3M CC18 2014 2014-02-03 COLOR 3.2188758249 #> 3767 2048A 3M CC18 2014 2014-02-03 DO 1.6677068206 #> 3768 2048A 3M CC18 2014 2014-02-03 DOSAT 4.1820501426 + #> 3769 2048A 3M CC18 2014 2014-02-03 NO23 -4.5098600062 #> 3770 2048A 3M CC18 2014 2014-02-03 SALIN 2.9496883351 #> 3771 2048A 3M CC18 2014 2014-02-03 TKN -0.6348782724 #> 3772 2048A 3M CC18 2014 2014-02-03 TN -0.6143360001 + #> 3773 2048A 3M CC18 2014 2014-02-03 TP -2.5133061243 #> 3774 2048A 3M CC18 2014 2014-02-03 TURB 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CC18 2016 2016-10-03 TP -1.6607312068 #> 4004 2048A 3M CC18 2016 2016-10-03 TURB 0.5306282511 #> 4005 2048A 3M CC18 2016 2016-11-07 CHLAC 0.9932517730 #> 4006 2048A 3M CC18 2016 2016-11-07 COLOR 3.8918202981 #> 4007 2048A 3M CC18 2016 2016-11-07 DOSAT 3.8501476017 + #> 4008 2048A 3M CC18 2016 2016-11-07 NO23 -4.1997050779 #> 4009 2048A 3M CC18 2016 2016-11-07 SALIN 3.0773122605 #> 4010 2048A 3M CC18 2016 2016-11-07 TKN -0.3011050928 #> 4011 2048A 3M CC18 2016 2016-11-07 TN -0.2810375297 + #> 4012 2048A 3M CC18 2016 2016-11-07 TP -1.8971199849 #> 4013 2048A 3M CC18 2016 2016-11-07 TURB 1.1939224685 #> 4014 2048A 3M CC18 2016 2016-12-05 CHLAC 0.9555114450 I #> 4015 2048A 3M CC18 2016 2016-12-05 COLOR 3.4657359028 #> 4016 2048A 3M CC18 2016 2016-12-05 DO 0.9555114450 #> 4017 2048A 3M CC18 2016 2016-12-05 DOSAT 3.5263605246 + #> 4018 2048A 3M CC18 2016 2016-12-05 NO23 -4.2686979494 #> 4019 2048A 3M CC18 2016 2016-12-05 SALIN 3.0726933147 #> 4020 2048A 3M CC18 2016 2016-12-05 TKN -0.4780358009 #> 4021 2048A 3M CC18 2016 2016-12-05 TN -0.4557063245 + #> 4022 2048A 3M CC18 2016 2016-12-05 TP -2.4191189092 #> 4023 2048A 3M CC18 2016 2016-12-05 TURB 0.6418538862 #> 4024 2048A 3M CC18 2017 2017-01-03 CHLAC 0.7884573604 #> 4025 2048A 3M CC18 2017 2017-01-03 COLOR 3.2580965380 A #> 4026 2048A 3M CC18 2017 2017-01-03 DOSAT 3.7999735016 + #> 4027 2048A 3M CC18 2017 2017-01-03 NO23 -4.3428059215 #> 4028 2048A 3M CC18 2017 2017-01-03 SALIN 3.1135153092 #> 4029 2048A 3M CC18 2017 2017-01-03 TKN -0.4004775666 #> 4030 2048A 3M CC18 2017 2017-01-03 TN -0.3812604194 + #> 4031 2048A 3M CC18 2017 2017-01-03 TP -2.1202635362 #> 4032 2048A 3M CC18 2017 2017-01-03 TURB 1.2809338455 #> 4033 2048A 3M CC18 2017 2017-02-06 CHLAC 1.4816045409 #> 4034 2048A 3M CC18 2017 2017-02-06 COLOR 3.2188758249 #> 4035 2048A 3M CC18 2017 2017-02-06 DOSAT 3.7999735016 + #> 4036 2048A 3M CC18 2017 2017-02-06 NO23 -4.7105307016 I #> 4037 2048A 3M CC18 2017 2017-02-06 SALIN 3.1135153092 #> 4038 2048A 3M CC18 2017 2017-02-06 TKN -0.3011050928 #> 4039 2048A 3M CC18 2017 2017-02-06 TN -0.2957142441 + #> 4040 2048A 3M CC18 2017 2017-02-06 TP -2.3126354288 #> 4041 2048A 3M CC18 2017 2017-02-06 TURB 1.0647107370 #> 4042 2048A 3M CC18 2017 2017-03-06 CHLAC 1.6677068206 #> 4043 2048A 3M CC18 2017 2017-03-06 COLOR 3.0445224377 #> 4044 2048A 3M CC18 2017 2017-03-06 DO 2.0541237337 #> 4045 2048A 3M CC18 2017 2017-03-06 DOSAT 4.6071681887 + #> 4046 2048A 3M CC18 2017 2017-03-06 NO23 -5.5214609179 U #> 4047 2048A 3M CC18 2017 2017-03-06 SALIN 3.2921262866 #> 4048 2048A 3M CC18 2017 2017-03-06 TKN -0.3011050928 #> 4049 2048A 3M CC18 2017 2017-03-06 TN -0.2984060358 + #> 4050 2048A 3M CC18 2017 2017-03-06 TP -2.6592600369 #> 4051 2048A 3M CC18 2017 2017-03-06 TURB 1.0986122887 #> 4052 2048A 3M CC18 2017 2017-04-03 CHLAC 1.5892352051 #> 4053 2048A 3M CC18 2017 2017-04-03 COLOR 3.1354942159 #> 4054 2048A 3M CC18 2017 2017-04-03 DO 1.7749523509 #> 4055 2048A 3M CC18 2017 2017-04-03 DOSAT 4.3040650932 + #> 4056 2048A 3M CC18 2017 2017-04-03 NO23 -4.7105307016 I #> 4057 2048A 3M CC18 2017 2017-04-03 SALIN 1.5260563035 #> 4058 2048A 3M CC18 2017 2017-04-03 TN -0.2691874898 + #> 4059 2048A 3M CC18 2017 2017-04-03 TURB 0.9555114450 #> 4060 2048A 3M CC18 2017 2017-05-01 CHLAC 2.2407096893 A #> 4061 2048A 3M CC18 2017 2017-05-01 COLOR 3.4011973817 A #> 4062 2048A 3M CC18 2017 2017-05-01 DO 1.9169226122 #> 4063 2048A 3M CC18 2017 2017-05-01 DOSAT 4.6061696863 + #> 4064 2048A 3M CC18 2017 2017-05-01 NO23 -5.5214609179 U #> 4065 2048A 3M CC18 2017 2017-05-01 SALIN 3.4210000090 #> 4066 2048A 3M CC18 2017 2017-05-01 TKN 0.0953101798 #> 4067 2048A 3M CC18 2017 2017-05-01 TN 0.0971267107 + #> 4068 2048A 3M CC18 2017 2017-05-01 TP -2.1202635362 #> 4069 2048A 3M CC18 2017 2017-05-01 TURB 1.3609765531 #> 4070 2048A 3M CC18 2017 2017-06-05 CHLAC 1.4350845253 #> 4071 2048A 3M CC18 2017 2017-06-05 COLOR 3.6635616461 #> 4072 2048A 3M CC18 2017 2017-06-05 DO 1.8870696490 #> 4073 2048A 3M CC18 2017 2017-06-05 DOSAT 4.6141299274 + #> 4074 2048A 3M CC18 2017 2017-06-05 NO23 -5.2983173665 I #> 4075 2048A 3M CC18 2017 2017-06-05 SALIN 3.4843122884 #> 4076 2048A 3M CC18 2017 2017-06-05 TN -0.1461825102 + #> 4077 2048A 3M CC18 2017 2017-06-05 TURB 0.8754687374 #> 4078 2048A 3M CC18 2017 2017-07-10 CHLAC 2.0281482473 #> 4079 2048A 3M CC18 2017 2017-07-10 COLOR 5.1357984371 #> 4080 2048A 3M CC18 2017 2017-07-10 DO 0.8754687374 #> 4081 2048A 3M CC18 2017 2017-07-10 DOSAT 3.4904285154 + #> 4082 2048A 3M CC18 2017 2017-07-10 SALIN 2.3513752572 #> 4083 2048A 3M CC18 2017 2017-07-10 TN 0.2768738737 + #> 4084 2048A 3M CC18 2017 2017-07-10 TURB 0.6931471806 #> 4085 2048A 3M CC18 2017 2017-08-07 CHLAC 0.7419373447 #> 4086 2048A 3M CC18 2017 2017-08-07 COLOR 5.3471075307 #> 4087 2048A 3M CC18 2017 2017-08-07 DOSAT 2.9123506646 + #> 4088 2048A 3M CC18 2017 2017-08-07 NO23 -2.6592600369 #> 4089 2048A 3M CC18 2017 2017-08-07 SALIN 0.9162907319 #> 4090 2048A 3M CC18 2017 2017-08-07 TKN 0.1823215568 #> 4091 2048A 3M CC18 2017 2017-08-07 TN 0.2390169005 + #> 4092 2048A 3M CC18 2017 2017-08-07 TP -1.3470736480 #> 4093 2048A 3M CC18 2017 2017-08-07 TURB 1.0296194172 #> 4094 2048A 3M CC18 2017 2017-09-05 CHLAC 2.2512917986 #> 4095 2048A 3M CC18 2017 2017-09-05 COLOR 5.2470240722 #> 4096 2048A 3M CC18 2017 2017-09-05 DO 2.2721258855 #> 4097 2048A 3M CC18 2017 2017-09-05 DOSAT 4.8354879411 + #> 4098 2048A 3M CC18 2017 2017-09-05 NO23 -3.2968373663 #> 4099 2048A 3M CC18 2017 2017-09-05 SALIN 1.1631508098 #> 4100 2048A 3M CC18 2017 2017-09-05 TKN 0.0000000000 #> 4101 2048A 3M CC18 2017 2017-09-05 TN 0.0363319292 + #> 4102 2048A 3M CC18 2017 2017-09-05 TP -1.8971199849 #> 4103 2048A 3M CC18 2017 2017-09-05 TURB 0.7419373447 #> 4104 2048A 3M CC18 2017 2017-11-06 CHLAC 1.2809338455 #> 4105 2048A 3M CC18 2017 2017-11-06 COLOR 4.3307333403 #> 4106 2048A 3M CC18 2017 2017-11-06 DO 2.0412203289 #> 4107 2048A 3M CC18 2017 2017-11-06 NO23 -4.3428059215 #> 4108 2048A 3M CC18 2017 2017-11-06 SALIN 2.2721258855 #> 4109 2048A 3M CC18 2017 2017-11-06 TKN -0.3285040670 #> 4110 2048A 3M CC18 2017 2017-11-06 TN -0.3106095771 + #> 4111 2048A 3M CC18 2017 2017-11-06 TP -1.8325814637 #> 4112 2048A 3M CC18 2017 2017-11-06 TURB 0.3364722366 #> 4113 2048A 3M CC18 2017 2017-12-04 CHLAC 0.8329091229 #> 4114 2048A 3M CC18 2017 2017-12-04 COLOR 3.8066624898 #> 4115 2048A 3M CC18 2017 2017-12-04 DO 2.0794415417 #> 4116 2048A 3M CC18 2017 2017-12-04 DOSAT 4.6700211583 + #> 4117 2048A 3M CC18 2017 2017-12-04 NO23 -5.5214609179 U #> 4118 2048A 3M CC18 2017 2017-12-04 SALIN 3.3214324132 #> 4119 2048A 3M CC18 2017 2017-12-04 TKN -0.2876820725 #> 4120 2048A 3M CC18 2017 2017-12-04 TN -0.2850189550 + #> 4121 2048A 3M CC18 2017 2017-12-04 TP -2.2072749132 #> 4122 2048A 3M CC18 2017 2017-12-04 TURB -0.1625189295 #> 4123 2048A 3M CC18 2018 2018-01-02 CHLAC 1.5475625087 #> 4124 2048A 3M CC18 2018 2018-01-02 COLOR 3.4965075615 #> 4125 2048A 3M CC18 2018 2018-01-02 DOSAT 4.3161538905 + #> 4126 2048A 3M CC18 2018 2018-01-02 NO23 -5.5214609179 U #> 4127 2048A 3M CC18 2018 2018-01-02 SALIN 2.4248027257 #> 4128 2048A 3M CC18 2018 2018-01-02 TN -0.4910229965 + #> 4129 2048A 3M CC18 2018 2018-01-02 TURB 0.5877866649 #> 4130 2048A 3M CC18 2018 2018-03-05 CHLAC 0.8329091229 #> 4131 2048A 3M CC18 2018 2018-03-05 COLOR 3.5835189385 #> 4132 2048A 3M CC18 2018 2018-03-05 NO23 -5.5214609179 U #> 4133 2048A 3M CC18 2018 2018-03-05 TKN -0.3011050928 #> 4134 2048A 3M CC18 2018 2018-03-05 TN -0.2984060358 + #> 4135 2048A 3M CC18 2018 2018-03-05 TP -1.8971199849 #> 4136 2048A 3M CC18 2018 2018-03-05 TURB 1.0296194172 #> 4137 2048A 3M CC18 2018 2018-04-02 CHLAC 1.6677068206 #> 4138 2048A 3M CC18 2018 2018-04-02 COLOR 3.3322045102 #> 4139 2048A 3M CC18 2018 2018-04-02 DOSAT 4.2513483110 + #> 4140 2048A 3M CC18 2018 2018-04-02 NO23 -5.2983173665 I #> 4141 2048A 3M CC18 2018 2018-04-02 SALIN 3.2027464429 #> 4142 2048A 3M CC18 2018 2018-04-02 TKN -0.2613647641 #> 4143 2048A 3M CC18 2018 2018-04-02 TN -0.2561834054 + #> 4144 2048A 3M CC18 2018 2018-04-02 TP -1.9661128564 #> 4145 2048A 3M CC18 2018 2018-04-02 TURB 1.3083328197 #> 4146 2048A 3M CC18 2018 2018-05-07 CHLAC 1.8562979904 #> 4147 2048A 3M CC18 2018 2018-05-07 COLOR 3.3322045102 A #> 4148 2048A 3M CC18 2018 2018-05-07 DO 2.1016921506 #> 4149 2048A 3M CC18 2018 2018-05-07 DOSAT 4.6051701860 #> 4150 2048A 3M CC18 2018 2018-05-07 NO23 -5.5214609179 I #> 4151 2048A 3M CC18 2018 2018-05-07 SALIN 3.2812870850 #> 4152 2048A 3M CC18 2018 2018-05-07 TKN -0.0943106795 #> 4153 2048A 3M CC18 2018 2018-05-07 TN -0.0899247075 + #> 4154 2048A 3M CC18 2018 2018-05-07 TP -2.2072749132 #> 4155 2048A 3M CC18 2018 2018-05-07 TURB 1.2527629685 #> 4156 2048A 3M CC18 2018 2018-06-04 CHLAC 1.8405496334 #> 4157 2048A 3M CC18 2018 2018-06-04 COLOR 4.6051701860 #> 4158 2048A 3M CC18 2018 2018-06-04 DO 2.0906287311 #> 4159 2048A 3M CC18 2018 2018-06-04 DOSAT 4.6011621646 #> 4160 2048A 3M CC18 2018 2018-06-04 NO23 -4.6051701860 I #> 4161 2048A 3M CC18 2018 2018-06-04 SALIN 1.8115620965 #> 4162 2048A 3M CC18 2018 2018-06-04 TKN -0.0725706928 #> 4163 2048A 3M CC18 2018 2018-06-04 TN -0.0682788408 + #> 4164 2048A 3M CC18 2018 2018-06-04 TP -1.6094379124 #> 4165 2048A 3M CC18 2018 2018-06-04 TURB 0.5306282511 #> 4166 2048A 3M CC18 2018 2018-07-09 CHLAC 2.4849066498 #> 4167 2048A 3M CC18 2018 2018-07-09 COLOR 4.9416424226 #> 4168 2048A 3M CC18 2018 2018-07-09 DO 1.4929040962 #> 4169 2048A 3M CC18 2018 2018-07-09 DOSAT 4.1415461637 #> 4170 2048A 3M CC18 2018 2018-07-09 NO23 -4.9618451299 I #> 4171 2048A 3M CC18 2018 2018-07-09 SALIN 1.3402504226 #> 4172 2048A 3M CC18 2018 2018-07-09 TKN -0.2231435513 #> 4173 2048A 3M CC18 2018 2018-07-09 TN -0.2181560098 + #> 4174 2048A 3M CC18 2018 2018-07-09 TP -1.7719568419 #> 4175 2048A 3M CC18 2018 2018-07-09 TURB 0.8754687374 #> 4176 2048A 3M CC18 2019 2019-05-06 CHLAC 0.9555114450 #> 4177 2048A 3M CC18 2019 2019-05-06 COLOR 3.6109179126 #> 4178 2048A 3M CC18 2019 2019-05-06 DO 0.8837675402 #> 4179 2048A 3M CC18 2019 2019-05-06 DOSAT 3.5351453542 #> 4180 2048A 3M CC18 2019 2019-05-06 NO23 -5.2983173665 I #> 4181 2048A 3M CC18 2019 2019-05-06 SALIN 2.9719517449 #> 4182 2048A 3M CC18 2019 2019-05-06 TKN -0.2744368457 #> 4183 2048A 3M CC18 2019 2019-05-06 TN -0.2691874898 + #> 4184 2048A 3M CC18 2019 2019-05-06 TP -1.7719568419 #> 4185 2048A 3M CC18 2019 2019-05-06 TURB 0.7419373447 #> 4186 2048A 3M CC18 2019 2019-06-03 CHLAC 1.5686159179 #> 4187 2048A 3M CC18 2019 2019-06-03 COLOR 3.7376696183 #> 4188 2048A 3M CC18 2019 2019-06-03 DO 0.6418538862 #> 4189 2048A 3M CC18 2019 2019-06-03 DOSAT 3.3322045102 #> 4190 2048A 3M CC18 2019 2019-06-03 NO23 -5.5214609179 U #> 4191 2048A 3M CC18 2019 2019-06-03 SALIN 3.0363942553 #> 4192 2048A 3M CC18 2019 2019-06-03 TKN -0.0725706928 #> 4193 2048A 3M CC18 2019 2019-06-03 TN -0.0704224643 + #> 4194 2048A 3M CC18 2019 2019-06-03 TP -1.3470736480 #> 4195 2048A 3M CC18 2019 2019-06-03 TURB 1.4586150227 A #> 4196 2048A 3M CC18 2019 2019-07-01 CHLAC 1.6863989536 #> 4197 2048A 3M CC18 2019 2019-07-01 COLOR 3.6635616461 #> 4198 2048A 3M CC18 2019 2019-07-01 DO 0.9162907319 #> 4199 2048A 3M CC18 2019 2019-07-01 DOSAT 3.4483989831 #> 4200 2048A 3M CC18 2019 2019-07-01 NO23 -5.5214609179 U #> 4201 2048A 3M CC18 2019 2019-07-01 SALIN 2.9678470701 #> 4202 2048A 3M CC18 2019 2019-07-01 TKN -0.2484613593 #> 4203 2048A 3M CC18 2019 2019-07-01 TN -0.2459005384 + #> 4204 2048A 3M CC18 2019 2019-07-01 TP -1.2729656758 #> 4205 2048A 3M CC18 2019 2019-07-01 TURB 0.4054651081 #> 4206 2048A 3M CC18 2019 2019-08-05 CHLAC 1.4109869737 #> 4207 2048A 3M CC18 2019 2019-08-05 COLOR 5.0751738152 #> 4208 2048A 3M CC18 2019 2019-08-05 DO 1.1378330018 #> 4209 2048A 3M CC18 2019 2019-08-05 DOSAT 3.7305011288 #> 4210 2048A 3M CC18 2019 2019-08-05 NO23 -5.5214609179 I #> 4211 2048A 3M CC18 2019 2019-08-05 SALIN 1.6134299337 #> 4212 2048A 3M CC18 2019 2019-08-05 TKN -0.0618754037 #> 4213 2048A 3M CC18 2019 2019-08-05 TN -0.0576291128 + #> 4214 2048A 3M CC18 2019 2019-08-05 TP -1.5606477483 #> 4215 2048A 3M CC18 2019 2019-08-05 TURB 0.8754687374 #> 4216 2048A 3M CC18 2019 2019-10-07 CHLAC 1.0986122887 I #> 4217 2048A 3M CC18 2019 2019-10-07 COLOR 4.3820266347 #> 4218 2048A 3M CC18 2019 2019-10-07 DO 1.0152306797 #> 4219 2048A 3M CC18 2019 2019-10-07 DOSAT 3.6375861597 #> 4220 2048A 3M CC18 2019 2019-10-07 NO23 -4.9618451299 I #> 4221 2048A 3M CC18 2019 2019-10-07 SALIN 2.7389026646 #> 4222 2048A 3M CC18 2019 2019-10-07 TKN -0.1278333715 #> 4223 2048A 3M CC18 2019 2019-10-07 TN -0.1232982163 + #> 4224 2048A 3M CC18 2019 2019-10-07 TP -1.3862943611 #> 4225 2048A 3M CC18 2019 2019-10-07 TURB 0.4054651081 #> 4226 2048A 3M CC18 2019 2019-11-04 CHLAC 1.0296194172 #> 4227 2048A 3M CC18 2019 2019-11-04 COLOR 4.1431347264 #> 4228 2048A 3M CC18 2019 2019-11-04 DO 1.2267122913 #> 4229 2048A 3M CC18 2019 2019-11-04 DOSAT 3.8177123260 #> 4230 2048A 3M CC18 2019 2019-11-04 NO23 -5.5214609179 I #> 4231 2048A 3M CC18 2019 2019-11-04 SALIN 2.8075938314 #> 4232 2048A 3M CC18 2019 2019-11-04 TKN -0.1508228897 #> 4233 2048A 3M CC18 2019 2019-11-04 TN -0.1461825102 + #> 4234 2048A 3M CC18 2019 2019-11-04 TP -1.6094379124 #> 4235 2048A 3M CC18 2019 2019-11-04 TURB 0.2623642645 A #> 4236 2048A 3M CC18 2019 2019-11-04 CHLAC 1.2809338455 #> 4237 2048A 3M CC18 2019 2019-11-04 COLOR 4.1431347264 A #> 4238 2048A 3M CC18 2019 2019-11-04 DO 1.2267122913 #> 4239 2048A 3M CC18 2019 2019-11-04 DOSAT 3.8177123260 #> 4240 2048A 3M CC18 2019 2019-11-04 NO23 -5.2983173665 I #> 4241 2048A 3M CC18 2019 2019-11-04 SALIN 2.8075938314 #> 4242 2048A 3M CC18 2019 2019-11-04 TKN -0.2231435513 #> 4243 2048A 3M CC18 2019 2019-11-04 TN -0.2181560098 + #> 4244 2048A 3M CC18 2019 2019-11-04 TP -1.7147984281 #> 4245 2048A 3M CC18 2019 2019-11-04 TURB 0.0953101798 #> 4246 2048A 3M CC18 2019 2019-12-02 CHLAC 1.2809338455 #> 4247 2048A 3M CC18 2019 2019-12-02 COLOR 3.6888794541 A #> 4248 2048A 3M CC18 2019 2019-12-02 DO 1.5518087996 #> 4249 2048A 3M CC18 2019 2019-12-02 DOSAT 4.1059436981 #> 4250 2048A 3M CC18 2019 2019-12-02 NO23 -5.5214609179 U #> 4251 2048A 3M CC18 2019 2019-12-02 SALIN 2.9412760878 #> 4252 2048A 3M CC18 2019 2019-12-02 TKN -0.2613647641 #> 4253 2048A 3M CC18 2019 2019-12-02 TN -0.2587707290 + #> 4254 2048A 3M CC18 2019 2019-12-02 TP -2.2072749132 #> 4255 2048A 3M CC18 2019 2019-12-02 TURB 0.0953101798 #> 4256 2048A 3M CC18 2020 2020-01-06 CHLAC 1.7578579176 #> 4257 2048A 3M CC18 2020 2020-01-06 COLOR 3.5263605246 #> 4258 2048A 3M CC18 2020 2020-01-06 DO 1.6770965609 #> 4259 2048A 3M CC18 2020 2020-01-06 DOSAT 4.1541845626 #> 4260 2048A 3M CC18 2020 2020-01-06 NO23 -5.5214609179 U #> 4261 2048A 3M CC18 2020 2020-01-06 SALIN 2.8713021952 #> 4262 2048A 3M CC18 2020 2020-01-06 TKN -0.5276327421 #> 4263 2048A 3M CC18 2020 2020-01-06 TN -0.5242486441 + #> 4264 2048A 3M CC18 2020 2020-01-06 TP -1.8971199849 #> 4265 2048A 3M CC18 2020 2020-01-06 TURB 0.3364722366 #> 4266 2048A 3M CC18 2020 2020-02-03 CHLAC 2.6390573296 #> 4267 2048A 3M CC18 2020 2020-02-03 COLOR 3.3672958300 #> 4268 2048A 3M CC18 2020 2020-02-03 DO 1.7137979278 #> 4269 2048A 3M CC18 2020 2020-02-03 DOSAT 4.1941898972 #> 4270 2048A 3M CC18 2020 2020-02-03 NO23 -4.8283137373 I #> 4271 2048A 3M CC18 2020 2020-02-03 SALIN 2.9538680695 #> 4272 2048A 3M CC18 2020 2020-02-03 TKN -0.0725706928 #> 4273 2048A 3M CC18 2020 2020-02-03 TN -0.0682788408 + #> 4274 2048A 3M CC18 2020 2020-02-03 TP -1.9661128564 #> 4275 2048A 3M CC18 2020 2020-02-03 TURB 2.1400661635 #> 4276 2048A 3M CC18 2020 2020-03-02 CHLAC 1.8562979904 #> 4277 2048A 3M CC18 2020 2020-03-02 COLOR 3.2958368660 #> 4278 2048A 3M CC18 2020 2020-03-02 DO 2.1388890003 #> 4279 2048A 3M CC18 2020 2020-03-02 DOSAT 4.6530075154 #> 4280 2048A 3M CC18 2020 2020-03-02 NO23 -5.5214609179 I #> 4281 2048A 3M CC18 2020 2020-03-02 SALIN 3.0061775314 #> 4282 2048A 3M CC18 2020 2020-03-02 TKN -0.3710636814 #> 4283 2048A 3M CC18 2020 2020-03-02 TN -0.3652833185 + #> 4284 2048A 3M CC18 2020 2020-03-02 TP -2.3025850930 #> 4285 2048A 3M CC18 2020 2020-03-02 TURB 1.3609765531 #> 4286 2048A 3M CC18 2020 2020-09-08 CHLAC 1.2809338455 #> 4287 2048A 3M CC18 2020 2020-09-08 COLOR 4.5432947823 #> 4288 2048A 3M CC18 2020 2020-09-08 DO 0.6418538862 #> 4289 2048A 3M CC18 2020 2020-09-08 DOSAT 3.2809112158 #> 4290 2048A 3M CC18 2020 2020-09-08 NO23 -4.3428059215 #> 4291 2048A 3M CC18 2020 2020-09-08 SALIN 2.8237570088 #> 4292 2048A 3M CC18 2020 2020-09-08 TKN -0.2231435513 #> 4293 2048A 3M CC18 2020 2020-09-08 TN -0.2070241694 + #> 4294 2048A 3M CC18 2020 2020-09-08 TP -1.3470736480 #> 4295 2048A 3M CC18 2020 2020-09-08 TURB 0.9555114450 #> 4296 2048A 3M CC18 2020 2020-10-05 DO 1.0885619528 #> 4297 2048A 3M CC18 2020 2020-10-05 DOSAT 3.6323091026 #> 4298 2048A 3M CC18 2020 2020-10-05 NO23 -3.3524072175 #> 4299 2048A 3M CC18 2020 2020-10-05 TKN 0.0000000000 #> 4300 2048A 3M CC18 2020 2020-10-05 TN 0.0344014267 + #> 4301 2048A 3M CC18 2020 2020-10-05 TP -1.4696759701 #> 4302 2048A 3M CC18 2020 2020-11-02 CHLAC 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2022-02-07 NO23 -4.7105307016 I #> 4444 2048A 3M CC18 2022 2022-02-07 SALIN 3.1144038033 #> 4445 2048A 3M CC18 2022 2022-02-07 TKN -0.4620354596 #> 4446 2048A 3M CC18 2022 2022-02-07 TN -0.4557063245 + #> 4447 2048A 3M CC18 2022 2022-02-07 TP -2.4418471603 #> 4448 2048A 3M CC18 2022 2022-02-07 TURB 0.6931471806 #> 4449 2048A 3M CC18 2022 2022-03-07 CHLAC 1.0647107370 I #> 4450 2048A 3M CC18 2022 2022-03-07 COLOR 3.2580965380 #> 4451 2048A 3M CC18 2022 2022-03-07 DO 1.3217558400 #> 4452 2048A 3M CC18 2022 2022-03-07 DOSAT 3.9318256327 #> 4453 2048A 3M CC18 2022 2022-03-07 NO23 -4.7105307016 I #> 4454 2048A 3M CC18 2022 2022-03-07 SALIN 3.2216719122 #> 4455 2048A 3M CC18 2022 2022-03-07 TKN -0.0304592075 #> 4456 2048A 3M CC18 2022 2022-03-07 TN -0.0263439753 + #> 4457 2048A 3M CC18 2022 2022-03-07 TP -2.1202635362 #> 4458 2048A 3M CC18 2022 2022-03-07 TURB 1.3083328197 #> 4459 2048A 3M CC18 2022 2022-04-04 CHLAC 1.7227665977 #> 4460 2048A 3M CC18 2022 2022-04-04 COLOR 3.2580965380 A #> 4461 2048A 3M CC18 2022 2022-04-04 DO 1.3244189574 #> 4462 2048A 3M CC18 2022 2022-04-04 DOSAT 3.9415818077 #> 4463 2048A 3M CC18 2022 2022-04-04 NO23 -4.6051701860 #> 4464 2048A 3M CC18 2022 2022-04-04 SALIN 3.2928695048 #> 4465 2048A 3M CC18 2022 2022-04-04 TKN -0.3856624808 #> 4466 2048A 3M CC18 2022 2022-04-04 TN -0.3710636814 + #> 4467 2048A 3M CC18 2022 2022-04-04 TP -1.8325814637 #> 4468 2048A 3M CC18 2022 2022-04-04 TURB 1.3350010667 #> 4469 2048A 3M CC18 2022 2022-05-02 CHLAC 0.9162907319 I #> 4470 2048A 3M CC18 2022 2022-05-02 COLOR 3.4965075615 A #> 4471 2048A 3M CC18 2022 2022-05-02 DO 1.3164082337 #> 4472 2048A 3M CC18 2022 2022-05-02 DOSAT 3.9550824949 #> 4473 2048A 3M CC18 2022 2022-05-02 NO23 -4.1997050779 #> 4474 2048A 3M CC18 2022 2022-05-02 SALIN 3.2343553957 #> 4475 2048A 3M CC18 2022 2022-05-02 TKN -0.3566749439 #> 4476 2048A 3M CC18 2022 2022-05-02 TN -0.3354727363 + #> 4477 2048A 3M CC18 2022 2022-05-02 TP -1.8971199849 #> 4478 2048A 3M CC18 2022 2022-05-02 TURB 0.8329091229 #> 4479 2060A1 2 CC25 2013 2013-01-09 CHLAC 1.3737155789 #> 4480 2060A1 2 CC25 2013 2013-01-09 COLOR 3.4011973817 #> 4481 2060A1 2 CC25 2013 2013-01-09 COND 10.5416504248 #> 4482 2060A1 2 CC25 2013 2013-01-09 DO 2.1126345090 #> 4483 2060A1 2 CC25 2013 2013-01-09 DOSAT 4.7022968967 + #> 4484 2060A1 2 CC25 2013 2013-01-09 NO23 -5.2983173665 I #> 4485 2060A1 2 CC25 2013 2013-01-09 SALIN 3.1805507105 #> 4486 2060A1 2 CC25 2013 2013-01-09 TKN -0.7635696449 #> 4487 2060A1 2 CC25 2013 2013-01-09 TN -0.7528971850 #> 4488 2060A1 2 CC25 2013 2013-01-09 TP -2.0099154790 #> 4489 2060A1 2 CC25 2013 2013-01-09 TSS 1.5644405465 #> 4490 2060A1 2 CC25 2013 2013-01-09 TURB 0.5306282511 #> 4491 2060A1 2 CC25 2013 2013-01-09 COND 10.5421785473 #> 4492 2060A1 2 CC25 2013 2013-01-09 DO 2.1138429684 #> 4493 2060A1 2 CC25 2013 2013-01-09 DOSAT 4.7022968967 + #> 4494 2060A1 2 CC25 2013 2013-01-09 SALIN 3.1809662518 #> 4495 2060A1 2 CC25 2013 2013-06-13 CHLAC 1.9344157696 #> 4496 2060A1 2 CC25 2013 2013-06-13 COLOR 4.2484952420 #> 4497 2060A1 2 CC25 2013 2013-06-13 COND 9.6434206471 #> 4498 2060A1 2 CC25 2013 2013-06-13 DO 1.7298840655 #> 4499 2060A1 2 CC25 2013 2013-06-13 DOSAT 4.3438054219 + #> 4500 2060A1 2 CC25 2013 2013-06-13 NO23 -4.1351665567 I #> 4501 2060A1 2 CC25 2013 2013-06-13 SALIN 2.1905355892 #> 4502 2060A1 2 CC25 2013 2013-06-13 TKN -0.9493305860 #> 4503 2060A1 2 CC25 2013 2013-06-13 TN -0.9088187170 #> 4504 2060A1 2 CC25 2013 2013-06-13 TP -1.7372712839 #> 4505 2060A1 2 CC25 2013 2013-06-13 TSS 0.9400072585 #> 4506 2060A1 2 CC25 2013 2013-06-13 TURB 0.3364722366 #> 4507 2060A1 2 CC25 2013 2013-06-13 COND 10.3019280457 #> 4508 2060A1 2 CC25 2013 2013-06-13 DO 1.5195132049 #> 4509 2060A1 2 CC25 2013 2013-06-13 DOSAT 4.1896547420 + #> 4510 2060A1 2 CC25 2013 2013-06-13 SALIN 2.9096295745 #> 4511 2060A1 2 CC25 2013 2013-06-13 COND 10.3862222961 #> 4512 2060A1 2 CC25 2013 2013-06-13 DO 1.5195132049 #> 4513 2060A1 2 CC25 2013 2013-06-13 DOSAT 4.1956970565 + #> 4514 2060A1 2 CC25 2013 2013-06-13 SALIN 3.0027078873 #> 4515 2060A1 2 CC25 2013 2013-11-06 CHLAC 0.6981347221 #> 4516 2060A1 2 CC25 2013 2013-11-06 COLOR 4.2484952420 #> 4517 2060A1 2 CC25 2013 2013-11-06 COND 10.4234711141 #> 4518 2060A1 2 CC25 2013 2013-11-06 DO 1.7526720805 #> 4519 2060A1 2 CC25 2013 2013-11-06 DOSAT 4.3359826962 + #> 4520 2060A1 2 CC25 2013 2013-11-06 NO23 -4.7105307016 I #> 4521 2060A1 2 CC25 2013 2013-11-06 SALIN 3.0492730405 #> 4522 2060A1 2 CC25 2013 2013-11-06 TKN -0.4812668215 #> 4523 2060A1 2 CC25 2013 2013-11-06 TN -0.4668087383 #> 4524 2060A1 2 CC25 2013 2013-11-06 TP -1.8643301621 #> 4525 2060A1 2 CC25 2013 2013-11-06 TSS 2.1747517215 #> 4526 2060A1 2 CC25 2013 2013-11-06 TURB 0.7419373447 #> 4527 2060A1 2 CC25 2013 2013-11-06 COND 10.4222813460 #> 4528 2060A1 2 CC25 2013 2013-11-06 DO 1.7509374747 #> 4529 2060A1 2 CC25 2013 2013-11-06 DOSAT 4.3333614627 + #> 4530 2060A1 2 CC25 2013 2013-11-06 SALIN 3.0478502278 #> 4531 2060A1 2 CC25 2014 2014-02-12 CHLAC 1.4109869737 #> 4532 2060A1 2 CC25 2014 2014-02-12 COLOR 3.2188758249 #> 4533 2060A1 2 CC25 2014 2014-02-12 COND 10.5921245776 #> 4534 2060A1 2 CC25 2014 2014-02-12 DO 1.9933388426 #> 4535 2060A1 2 CC25 2014 2014-02-12 DOSAT 4.5570298107 + #> 4536 2060A1 2 CC25 2014 2014-02-12 NO23 -5.5214609179 U #> 4537 2060A1 2 CC25 2014 2014-02-12 SALIN 3.2367157430 #> 4538 2060A1 2 CC25 2014 2014-02-12 TKN -0.7657178734 #> 4539 2060A1 2 CC25 2014 2014-02-12 TN -0.7657178734 #> 4540 2060A1 2 CC25 2014 2014-02-12 TP -2.0099154790 #> 4541 2060A1 2 CC25 2014 2014-02-12 TSS 1.7917594692 #> 4542 2060A1 2 CC25 2014 2014-02-12 TURB 0.1823215568 #> 4543 2060A1 2 CC25 2014 2014-02-12 COND 10.5938809449 #> 4544 2060A1 2 CC25 2014 2014-02-12 DO 1.9919755159 #> 4545 2060A1 2 CC25 2014 2014-02-12 DOSAT 4.5559799418 + #> 4546 2060A1 2 CC25 2014 2014-02-12 SALIN 3.2386784522 #> 4547 2060A1 2 CC25 2014 2014-07-09 CHLAC 2.1838015570 #> 4548 2060A1 2 CC25 2014 2014-07-09 COLOR 3.8066624898 #> 4549 2060A1 2 CC25 2014 2014-07-09 COND 10.5001238327 #> 4550 2060A1 2 CC25 2014 2014-07-09 DO 1.7047480922 #> 4551 2060A1 2 CC25 2014 2014-07-09 DOSAT 4.4164280614 + #> 4552 2060A1 2 CC25 2014 2014-07-09 NO23 -5.5214609179 U #> 4553 2060A1 2 CC25 2014 2014-07-09 SALIN 3.1271990363 #> 4554 2060A1 2 CC25 2014 2014-07-09 TKN -0.2319320573 #> 4555 2060A1 2 CC25 2014 2014-07-09 TN -0.2319320573 #> 4556 2060A1 2 CC25 2014 2014-07-09 TP -1.3167682985 #> 4557 2060A1 2 CC25 2014 2014-07-09 TSS 1.9286186519 #> 4558 2060A1 2 CC25 2014 2014-07-09 TURB 0.8329091229 #> 4559 2060A1 2 CC25 2014 2014-07-09 COND 10.5012245483 #> 4560 2060A1 2 CC25 2014 2014-07-09 DO 1.7029282555 #> 4561 2060A1 2 CC25 2014 2014-07-09 DOSAT 4.4115854369 + #> 4562 2060A1 2 CC25 2014 2014-07-09 SALIN 3.1285133848 #> 4563 2060A1 2 CC25 2014 2014-08-12 CHLAC 3.6558396000 #> 4564 2060A1 2 CC25 2014 2014-08-12 COLOR 4.3820266347 #> 4565 2060A1 2 CC25 2014 2014-08-12 COND 9.9744118909 #> 4566 2060A1 2 CC25 2014 2014-08-12 DO 1.9643112344 #> 4567 2060A1 2 CC25 2014 2014-08-12 DOSAT 4.6424659707 + #> 4568 2060A1 2 CC25 2014 2014-08-12 NO23 -5.5214609179 U #> 4569 2060A1 2 CC25 2014 2014-08-12 SALIN 2.5478814489 #> 4570 2060A1 2 CC25 2014 2014-08-12 TKN 0.1484200051 #> 4571 2060A1 2 CC25 2014 2014-08-12 TN 0.1484200051 #> 4572 2060A1 2 CC25 2014 2014-08-12 TP -0.9808292530 #> 4573 2060A1 2 CC25 2014 2014-08-12 TSS 2.3887627892 #> 4574 2060A1 2 CC25 2014 2014-08-12 TURB 1.6292405397 #> 4575 2060A1 2 CC25 2014 2014-08-12 COND 9.9753429896 #> 4576 2060A1 2 CC25 2014 2014-08-12 DO 1.9586853405 #> 4577 2060A1 2 CC25 2014 2014-08-12 DOSAT 4.6366688530 + #> 4578 2060A1 2 CC25 2014 2014-08-12 SALIN 2.5486636156 #> 4579 2060A1 2 CC25 2014 2014-08-12 COND 9.9753429896 #> 4580 2060A1 2 CC25 2014 2014-08-12 DO 1.9530276168 #> 4581 2060A1 2 CC25 2014 2014-08-12 DOSAT 4.6308379327 + #> 4582 2060A1 2 CC25 2014 2014-08-12 SALIN 2.5486636156 #> 4583 2060A1 2 CC25 2014 2014-10-21 CHLAC 0.9555114450 #> 4584 2060A1 2 CC25 2014 2014-10-21 COLOR 4.7874917428 #> 4585 2060A1 2 CC25 2014 2014-10-21 COND 10.1330107108 #> 4586 2060A1 2 CC25 2014 2014-10-21 DO 1.4701758451 #> 4587 2060A1 2 CC25 2014 2014-10-21 DOSAT 4.0809215419 + #> 4588 2060A1 2 CC25 2014 2014-10-21 NO23 -3.1941832123 #> 4589 2060A1 2 CC25 2014 2014-10-21 SALIN 2.7258901192 #> 4590 2060A1 2 CC25 2014 2014-10-21 TKN -0.1053605157 #> 4591 2060A1 2 CC25 2014 2014-10-21 TN -0.0608121394 #> 4592 2060A1 2 CC25 2014 2014-10-21 TP -1.4354846053 #> 4593 2060A1 2 CC25 2014 2014-10-21 TSS 1.5973653312 #> 4594 2060A1 2 CC25 2014 2014-10-21 TURB 0.8329091229 #> 4595 2060A1 2 CC25 2014 2014-10-21 COND 10.1472177375 #> 4596 2060A1 2 CC25 2014 2014-10-21 DO 1.4182774070 #> 4597 2060A1 2 CC25 2014 2014-10-21 DOSAT 4.0271358125 + #> 4598 2060A1 2 CC25 2014 2014-10-21 SALIN 2.7414849772 #> 4599 2060A1 2 CC25 2014 2014-10-21 COND 10.1612257486 #> 4600 2060A1 2 CC25 2014 2014-10-21 DO 1.3862943611 #> 4601 2060A1 2 CC25 2014 2014-10-21 DOSAT 3.9963641539 + #> 4602 2060A1 2 CC25 2014 2014-10-21 SALIN 2.7581094010 #> 4603 2060A1 2 CC25 2015 2015-02-03 CHLAC 1.7209792872 #> 4604 2060A1 2 CC25 2015 2015-02-03 COLOR 3.8066624898 #> 4605 2060A1 2 CC25 2015 2015-02-03 COND 10.4795389612 #> 4606 2060A1 2 CC25 2015 2015-02-03 DO 2.1758874399 #> 4607 2060A1 2 CC25 2015 2015-02-03 DOSAT 4.6596583713 + #> 4608 2060A1 2 CC25 2015 2015-02-03 NO23 -5.5214609179 U #> 4609 2060A1 2 CC25 2015 2015-02-03 SALIN 3.1130707660 #> 4610 2060A1 2 CC25 2015 2015-02-03 TKN -0.4975803970 #> 4611 2060A1 2 CC25 2015 2015-02-03 TN -0.4975803970 #> 4612 2060A1 2 CC25 2015 2015-02-03 TP -2.1037342342 #> 4613 2060A1 2 CC25 2015 2015-02-03 TSS 2.6100697927 #> 4614 2060A1 2 CC25 2015 2015-02-03 TURB 0.7884573604 #> 4615 2060A1 2 CC25 2015 2015-02-03 COND 10.4887710872 #> 4616 2060A1 2 CC25 2015 2015-02-03 DO 2.1644717909 #> 4617 2060A1 2 CC25 2015 2015-02-03 DOSAT 4.6482296754 + #> 4618 2060A1 2 CC25 2015 2015-02-03 SALIN 3.1232455939 #> 4619 2060A1 2 CC25 2015 2015-02-03 COND 10.4921072037 #> 4620 2060A1 2 CC25 2015 2015-02-03 DO 2.1621729393 #> 4621 2060A1 2 CC25 2015 2015-02-03 DOSAT 4.6463121293 + #> 4622 2060A1 2 CC25 2015 2015-02-03 SALIN 3.1267605360 #> 4623 2060A1 2 CC25 2016 2016-09-13 CHLAC 1.4206957878 #> 4624 2060A1 2 CC25 2016 2016-09-13 COND 8.8724871823 #> 4625 2060A1 2 CC25 2016 2016-09-13 DO 1.7191887764 #> 4626 2060A1 2 CC25 2016 2016-09-13 DOSAT 4.3346729383 + #> 4627 2060A1 2 CC25 2016 2016-09-13 NO23 -2.7333680091 #> 4628 2060A1 2 CC25 2016 2016-09-13 SALIN 1.3584091576 #> 4629 2060A1 2 CC25 2016 2016-09-13 TKN 0.2851789422 #> 4630 2060A1 2 CC25 2016 2016-09-13 TN 0.3364722366 #> 4631 2060A1 2 CC25 2016 2016-09-13 TP -1.2207799226 #> 4632 2060A1 2 CC25 2016 2016-09-13 TSS 0.4700036292 I #> 4633 2060A1 2 CC25 2016 2016-09-13 TURB 0.6418538862 #> 4634 2060A1 2 CC25 2016 2016-09-13 COND 9.4834162920 #> 4635 2060A1 2 CC25 2016 2016-09-13 DO 1.6882490929 #> 4636 2060A1 2 CC25 2016 2016-09-13 DOSAT 4.3134800921 + #> 4637 2060A1 2 CC25 2016 2016-09-13 SALIN 2.0162354658 #> 4638 2060A1 2 CC25 2016 2016-09-13 COND 9.6395220067 #> 4639 2060A1 2 CC25 2016 2016-09-13 DO 1.6544112781 #> 4640 2060A1 2 CC25 2016 2016-09-13 DOSAT 4.2835865619 + #> 4641 2060A1 2 CC25 2016 2016-09-13 SALIN 2.1849270495 #> 4642 2046 3M CC31 2018 2018-03-07 CHLAC 1.6094379124 #> 4643 2046 3M CC31 2018 2018-03-07 COND 10.3531928066 #> 4644 2046 3M CC31 2018 2018-03-07 DO 1.9021075264 #> 4645 2046 3M CC31 2018 2018-03-07 DOSAT 4.4670568839 #> 4646 2046 3M CC31 2018 2018-03-07 NO23 -4.7105307016 I #> 4647 2046 3M CC31 2018 2018-03-07 SALIN 3.0170044088 + #> 4648 2046 3M CC31 2018 2018-03-07 TKN -0.3710636814 #> 4649 2046 3M CC31 2018 2018-03-07 TN -0.3652833185 + #> 4650 2046 3M CC31 2018 2018-03-07 TP -1.8971199849 #> 4651 2046 3M CC31 2018 2018-03-07 TSS 1.3862943611 I #> 4652 2046 3M CC31 2018 2018-03-07 TURB 0.8754687374 #> 4653 2046 3M CC31 2018 2018-04-09 CHLAC 1.2809338455 A #> 4654 2046 3M CC31 2018 2018-04-09 COND 10.6261935353 #> 4655 2046 3M CC31 2018 2018-04-09 DO 1.3083328197 #> 4656 2046 3M CC31 2018 2018-04-09 DOSAT 3.9702919136 #> 4657 2046 3M CC31 2018 2018-04-09 NO23 -3.7297014486 #> 4658 2046 3M CC31 2018 2018-04-09 SALIN 3.2484346271 + #> 4659 2046 3M CC31 2018 2018-04-09 TKN -0.3147107448 #> 4660 2046 3M CC31 2018 2018-04-09 TN -0.2823629110 + #> 4661 2046 3M CC31 2018 2018-04-09 TP -1.7147984281 #> 4662 2046 3M CC31 2018 2018-04-09 TSS 1.6094379124 I #> 4663 2046 3M CC31 2018 2018-04-09 TURB 0.6931471806 #> 4664 2046 3M CC31 2018 2018-05-24 CHLAC 2.7080502011 #> 4665 2046 3M CC31 2018 2018-05-24 COND 9.7756541810 #> 4666 2046 3M CC31 2018 2018-05-24 DO 1.5303947051 #> 4667 2046 3M CC31 2018 2018-05-24 DOSAT 4.1009891049 #> 4668 2046 3M CC31 2018 2018-05-24 NO23 -3.1010927892 #> 4669 2046 3M CC31 2018 2018-05-24 SALIN 2.3065771143 + #> 4670 2046 3M CC31 2018 2018-05-24 TKN -0.2613647641 #> 4671 2046 3M CC31 2018 2018-05-24 TN -0.2045671657 + #> 4672 2046 3M CC31 2018 2018-05-24 TP -1.4271163556 #> 4673 2046 3M CC31 2018 2018-05-24 TSS 1.6094379124 I #> 4674 2046 3M CC31 2018 2018-05-24 TURB 0.9932517730 #> 4675 2046 3M CC31 2018 2018-07-23 CHLAC 1.4350845253 #> 4676 2046 3M CC31 2018 2018-07-23 COND 8.9291703831 #> 4677 2046 3M CC31 2018 2018-07-23 DO 1.6937790609 #> 4678 2046 3M CC31 2018 2018-07-23 DOSAT 4.3040650932 #> 4679 2046 3M CC31 2018 2018-07-23 NO23 -2.0402208285 #> 4680 2046 3M CC31 2018 2018-07-23 SALIN 1.4182774070 #> 4681 2046 3M CC31 2018 2018-07-23 TKN 0.0000000000 #> 4682 2046 3M CC31 2018 2018-07-23 TN 0.1222176327 + #> 4683 2046 3M CC31 2018 2018-07-23 TP -0.9162907319 #> 4684 2046 3M CC31 2018 2018-07-23 TSS 1.3862943611 I #> 4685 2046 3M CC31 2018 2018-07-23 TURB 0.9162907319 A #> 4686 2046 3M CC31 2018 2018-08-21 CHLAC 2.7080502011 #> 4687 2046 3M CC31 2018 2018-08-21 COND 8.6210125201 #> 4688 2046 3M CC31 2018 2018-08-21 DO 1.4586150227 #> 4689 2046 3M CC31 2018 2018-08-21 DOSAT 4.0724397268 #> 4690 2046 3M CC31 2018 2018-08-21 NO23 -3.4737680745 #> 4691 2046 3M CC31 2018 2018-08-21 SALIN 1.0885619528 #> 4692 2046 3M CC31 2018 2018-08-21 TKN 1.7047480922 #> 4693 2046 3M CC31 2018 2018-08-21 TN 1.7103686310 + #> 4694 2046 3M CC31 2018 2018-08-21 TSS 1.6094379124 I #> 4695 2046 3M CC31 2018 2018-08-21 TURB 1.3350010667 #> 4696 2046 3M CC31 2018 2018-11-12 CHLAC 1.5686159179 #> 4697 2046 3M CC31 2018 2018-11-12 COND 10.1213773269 #> 4698 2046 3M CC31 2018 2018-11-12 DO 1.6695918353 #> 4699 2046 3M CC31 2018 2018-11-12 DOSAT 4.3121405072 #> 4700 2046 3M CC31 2018 2018-11-12 NO23 -3.4112477175 #> 4701 2046 3M CC31 2018 2018-11-12 SALIN 2.7127060126 #> 4702 2046 3M CC31 2018 2018-11-12 TKN -0.3011050928 #> 4703 2046 3M CC31 2018 2018-11-12 TN -0.2574762304 + #> 4704 2046 3M CC31 2018 2018-11-12 TP -1.8325814637 #> 4705 2046 3M CC31 2018 2018-11-12 TSS 1.3862943611 I #> 4706 2046 3M CC31 2018 2018-11-12 TURB 0.4700036292 #> 4707 2046 3M CC31 2018 2018-11-12 COND 10.3160937688 #> 4708 2046 3M CC31 2018 2018-11-12 DO 1.5581446180 #> 4709 2046 3M CC31 2018 2018-11-12 DOSAT 4.2076732475 #> 4710 2046 3M CC31 2018 2018-11-12 SALIN 2.9269179576 #> 4711 2046 3M CC31 2019 2019-02-07 CHLAC 3.3672958300 #> 4712 2046 3M CC31 2019 2019-02-07 COND 9.8807305654 #> 4713 2046 3M CC31 2019 2019-02-07 NO23 -5.5214609179 U #> 4714 2046 3M CC31 2019 2019-02-07 SALIN 2.4544474423 #> 4715 2046 3M CC31 2019 2019-02-07 TKN -0.3710636814 #> 4716 2046 3M CC31 2019 2019-02-07 TN -0.3681693234 + #> 4717 2046 3M CC31 2019 2019-02-07 TP -1.6607312068 #> 4718 2046 3M CC31 2019 2019-02-07 TSS 3.3322045102 A #> 4719 2046 3M CC31 2019 2019-02-07 TURB 2.4849066498 A #> 4720 2046 3M CC31 2019 2019-03-13 CHLAC 2.3978952728 #> 4721 2046 3M CC31 2019 2019-03-13 COND 10.1587109973 #> 4722 2046 3M CC31 2019 2019-03-13 DO 1.5830939371 #> 4723 2046 3M CC31 2019 2019-03-13 DOSAT 4.1588830834 #> 4724 2046 3M CC31 2019 2019-03-13 NO23 -5.5214609179 U #> 4725 2046 3M CC31 2019 2019-03-13 SALIN 2.7568403653 #> 4726 2046 3M CC31 2019 2019-03-13 TKN -0.2876820725 #> 4727 2046 3M CC31 2019 2019-03-13 TN -0.2850189550 + #> 4728 2046 3M CC31 2019 2019-03-13 TP -1.7719568419 #> 4729 2046 3M CC31 2019 2019-03-13 TSS 1.3862943611 I #> 4730 2046 3M CC31 2019 2019-03-13 TURB 0.8754687374 #> 4731 2046 3M CC31 2019 2019-03-13 CHLAC 2.3978952728 #> 4732 2046 3M CC31 2019 2019-03-13 NO23 -5.5214609179 U #> 4733 2046 3M CC31 2019 2019-03-13 TKN -0.4004775666 #> 4734 2046 3M CC31 2019 2019-03-13 TN -0.3974969385 + #> 4735 2046 3M CC31 2019 2019-03-13 TP -1.7147984281 #> 4736 2046 3M CC31 2019 2019-03-13 TSS 1.3862943611 I #> 4737 2046 3M CC31 2019 2019-03-13 TURB 1.0647107370 #> 4738 2046 3M CC31 2019 2019-04-23 CHLAC 1.8562979904 #> 4739 2046 3M CC31 2019 2019-04-23 COND 10.2120745857 #> 4740 2046 3M CC31 2019 2019-04-23 DO 1.8389610707 #> 4741 2046 3M CC31 2019 2019-04-23 DOSAT 4.4188406078 #> 4742 2046 3M CC31 2019 2019-04-23 NO23 -5.5214609179 U #> 4743 2046 3M CC31 2019 2019-04-23 SALIN 2.8154087194 #> 4744 2046 3M CC31 2019 2019-04-23 TKN -0.4307829161 #> 4745 2046 3M CC31 2019 2019-04-23 TN -0.4277107171 + #> 4746 2046 3M CC31 2019 2019-04-23 TP -1.6094379124 #> 4747 2046 3M CC31 2019 2019-04-23 TSS 2.5649493575 #> 4748 2046 3M CC31 2019 2019-04-23 TURB 1.4350845253 #> 4749 2046 3M CC31 2019 2019-07-22 CHLAC 2.0281482473 #> 4750 2046 3M CC31 2019 2019-07-22 COND 9.5882287123 #> 4751 2046 3M CC31 2019 2019-07-22 DO 1.6808279085 #> 4752 2046 3M CC31 2019 2019-07-22 DOSAT 4.3174881135 #> 4753 2046 3M CC31 2019 2019-07-22 NO23 -5.1159958098 I #> 4754 2046 3M CC31 2019 2019-07-22 SALIN 2.1282317058 #> 4755 2046 3M CC31 2019 2019-07-22 TKN -0.2484613593 #> 4756 2046 3M CC31 2019 2019-07-22 TN -0.2433462586 + #> 4757 2046 3M CC31 2019 2019-07-22 TP -1.3862943611 #> 4758 2046 3M CC31 2019 2019-07-22 TSS 0.6931471806 I #> 4759 2046 3M CC31 2019 2019-07-22 TURB 0.7419373447 #> 4760 2046 3M CC31 2019 2019-09-04 CHLAC 2.6390573296 #> 4761 2046 3M CC31 2019 2019-09-04 COND 9.5618419571 #> 4762 2046 3M CC31 2019 2019-09-04 DO 1.6486586256 #> 4763 2046 3M CC31 2019 2019-09-04 DOSAT 4.2752762647 #> 4764 2046 3M CC31 2019 2019-09-04 NO23 -3.1465551633 #> 4765 2046 3M CC31 2019 2019-09-04 SALIN 2.1004689089 #> 4766 2046 3M CC31 2019 2019-09-04 TKN -0.1863295782 #> 4767 2046 3M CC31 2019 2019-09-04 TN -0.1358197231 + #> 4768 2046 3M CC31 2019 2019-09-04 TP -1.5141277326 #> 4769 2046 3M CC31 2019 2019-09-04 TSS 1.3862943611 I #> 4770 2046 3M CC31 2019 2019-09-04 TURB 0.6418538862 #> 4771 2046 3M CC31 2020 2020-01-14 COND 10.2603574775 #> 4772 2046 3M CC31 2020 2020-01-14 DO 1.8341801851 #> 4773 2046 3M CC31 2020 2020-01-14 DOSAT 4.4140096805 #> 4774 2046 3M CC31 2020 2020-01-14 SALIN 2.8690346205 #> 4775 2046 3M CC31 2020 2020-02-18 CHLAC 0.8329091229 I #> 4776 2046 3M CC31 2020 2020-02-18 COND 10.3879178649 #> 4777 2046 3M CC31 2020 2020-02-18 DO 1.8976198599 #> 4778 2046 3M CC31 2020 2020-02-18 DOSAT 4.5075573571 #> 4779 2046 3M CC31 2020 2020-02-18 NO23 -4.8283137373 I #> 4780 2046 3M CC31 2020 2020-02-18 SALIN 3.0106208860 #> 4781 2046 3M CC31 2020 2020-02-18 TKN -0.5447271754 #> 4782 2046 3M CC31 2020 2020-02-18 TN -0.5378542962 + #> 4783 2046 3M CC31 2020 2020-02-18 TP -2.0402208285 #> 4784 2046 3M CC31 2020 2020-02-18 TSS 1.0986122887 I #> 4785 2046 3M CC31 2020 2020-02-18 TURB 0.4700036292 #> 4786 2046 3M CC31 2020 2020-06-09 CHLAC 2.9444389792 #> 4787 2046 3M CC31 2020 2020-06-09 COND 10.1025842827 #> 4788 2046 3M CC31 2020 2020-06-09 DO 1.5973653312 #> 4789 2046 3M CC31 2020 2020-06-09 DOSAT 4.2297491992 #> 4790 2046 3M CC31 2020 2020-06-09 NO23 -4.9618451299 I #> 4791 2046 3M CC31 2020 2020-06-09 SALIN 2.6919208192 #> 4792 2046 3M CC31 2020 2020-06-09 TKN 0.0000000000 #> 4793 2046 3M CC31 2020 2020-06-09 TN 0.0039920213 + #> 4794 2046 3M CC31 2020 2020-06-09 TP -1.2729656758 #> 4795 2046 3M CC31 2020 2020-06-09 TSS 1.3862943611 I #> 4796 2046 3M CC31 2020 2020-06-09 TURB 0.5306282511 #> 4797 2046 3M CC31 2020 2020-08-10 COND 10.0585663729 #> 4798 2046 3M CC31 2020 2020-08-10 DO 0.7419373447 #> 4799 2046 3M CC31 2020 2020-08-10 DOSAT 3.4177266836 #> 4800 2046 3M CC31 2020 2020-08-10 SALIN 2.6426223958 #> 4801 2046 3M CC31 2020 2020-09-22 CHLAC 2.4849066498 #> 4802 2046 3M CC31 2020 2020-09-22 COND 9.3350328159 #> 4803 2046 3M CC31 2020 2020-09-22 DO 1.5789787049 #> 4804 2046 3M CC31 2020 2020-09-22 DOSAT 4.1573193614 #> 4805 2046 3M CC31 2020 2020-09-22 NO23 -3.0791138825 #> 4806 2046 3M CC31 2020 2020-09-22 SALIN 1.8578592709 #> 4807 2046 3M CC31 2020 2020-09-22 TKN -0.0408219945 #> 4808 2046 3M CC31 2020 2020-09-22 TN 0.0059820717 + #> 4809 2046 3M CC31 2020 2020-09-22 TP -1.4271163556 #> 4810 2046 3M CC31 2020 2020-09-22 TSS 1.0986122887 I #> 4811 2046 3M CC31 2020 2020-09-22 TURB 0.9932517730 #> 4812 2046 3M CC31 2020 2020-10-20 CHLAC 1.4586150227 #> 4813 2046 3M CC31 2020 2020-10-20 COND 9.7670949276 #> 4814 2046 3M CC31 2020 2020-10-20 DO 1.4085449701 #> 4815 2046 3M CC31 2020 2020-10-20 DOSAT 4.0000338828 #> 4816 2046 3M CC31 2020 2020-10-20 NO23 -2.5510464523 #> 4817 2046 3M CC31 2020 2020-10-20 SALIN 2.3282528397 #> 4818 2046 3M CC31 2020 2020-10-20 TKN -0.0833816089 #> 4819 2046 3M CC31 2020 2020-10-20 TN -0.0020020027 + #> 4820 2046 3M CC31 2020 2020-10-20 TP -1.5141277326 #> 4821 2046 3M CC31 2020 2020-10-20 TSS 1.0986122887 I #> 4822 2046 3M CC31 2020 2020-10-20 TURB 0.5877866649 #> 4823 2046 3M CC31 2020 2020-12-14 CHLAC 1.0647107370 #> 4824 2046 3M CC31 2020 2020-12-14 COND 9.9551782679 #> 4825 2046 3M CC31 2020 2020-12-14 DO 1.8293763328 #> 4826 2046 3M CC31 2020 2020-12-14 DOSAT 4.3528552574 #> 4827 2046 3M CC31 2020 2020-12-14 NO23 -2.7181005370 #> 4828 2046 3M CC31 2020 2020-12-14 SALIN 2.5360749364 #> 4829 2046 3M CC31 2020 2020-12-14 TKN -0.2107210313 #> 4830 2046 3M CC31 2020 2020-12-14 TN -0.1323891880 + #> 4831 2046 3M CC31 2020 2020-12-14 TP -2.1202635362 #> 4832 2046 3M CC31 2020 2020-12-14 TSS 1.6094379124 I #> 4833 2046 3M CC31 2020 2020-12-14 TURB 0.5306282511 #> 4834 2046 3M CC31 2021 2021-02-03 CHLAC 0.9932517730 #> 4835 2046 3M CC31 2021 2021-02-03 COND 10.2269830978 #> 4836 2046 3M CC31 2021 2021-02-03 DO 2.0655961349 #> 4837 2046 3M CC31 2021 2021-02-03 DOSAT 4.5130548971 #> 4838 2046 3M CC31 2021 2021-02-03 NO23 -4.0745419349 #> 4839 2046 3M CC31 2021 2021-02-03 SALIN 2.8355635214 #> 4840 2046 3M CC31 2021 2021-02-03 TKN -0.4780358009 #> 4841 2046 3M CC31 2021 2021-02-03 TN -0.4509856234 + #> 4842 2046 3M CC31 2021 2021-02-03 TP -2.3025850930 #> 4843 2046 3M CC31 2021 2021-02-03 TSS 1.7917594692 I #> 4844 2046 3M CC31 2021 2021-02-03 TURB 0.5306282511 #> 4845 2046 3M CC31 2021 2021-03-09 CHLAC 2.0918640617 #> 4846 2046 3M CC31 2021 2021-03-09 COND 10.3281668796 #> 4847 2046 3M CC31 2021 2021-03-09 DO 2.2523438766 #> 4848 2046 3M CC31 2021 2021-03-09 DOSAT 4.7757564866 #> 4849 2046 3M CC31 2021 2021-03-09 NO23 -5.5214609179 U #> 4850 2046 3M CC31 2021 2021-03-09 SALIN 2.9460166813 #> 4851 2046 3M CC31 2021 2021-03-09 TKN -0.1863295782 #> 4852 2046 3M CC31 2021 2021-03-09 TN -0.1839228382 + #> 4853 2046 3M CC31 2021 2021-03-09 TP -1.5606477483 #> 4854 2046 3M CC31 2021 2021-03-09 TSS 2.8332133441 #> 4855 2046 3M CC31 2021 2021-03-09 TURB 2.0412203289 #> 4856 2046 3M CC31 2021 2021-05-05 CHLAC 0.9555114450 #> 4857 2046 3M CC31 2021 2021-05-05 COND 10.5683895677 #> 4858 2046 3M CC31 2021 2021-05-05 DO 1.3402504226 #> 4859 2046 3M CC31 2021 2021-05-05 DOSAT 4.0465538984 #> 4860 2046 3M CC31 2021 2021-05-05 NO23 -5.5214609179 U #> 4861 2046 3M CC31 2021 2021-05-05 SALIN 3.2043711387 #> 4862 2046 3M CC31 2021 2021-05-05 TKN -0.4620354596 #> 4863 2046 3M CC31 2021 2021-05-05 TN -0.4588658848 + #> 4864 2046 3M CC31 2021 2021-05-05 TP -1.5141277326 #> 4865 2046 3M CC31 2021 2021-05-05 TSS 1.7917594692 I #> 4866 2046 3M CC31 2021 2021-05-05 TURB 0.4700036292 #> 4867 2046 3M CC31 2021 2021-06-03 CHLAC 0.9932517730 I #> 4868 2046 3M CC31 2021 2021-06-03 COND 10.6275033568 #> 4869 2046 3M CC31 2021 2021-06-03 DO 0.8329091229 #> 4870 2046 3M CC31 2021 2021-06-03 DOSAT 3.5322256441 #> 4871 2046 3M CC31 2021 2021-06-03 NO23 -5.5214609179 U #> 4872 2046 3M CC31 2021 2021-06-03 SALIN 3.2718477096 #> 4873 2046 3M CC31 2021 2021-06-03 TKN -0.3285040670 #> 4874 2046 3M CC31 2021 2021-06-03 TN -0.3257301401 + #> 4875 2046 3M CC31 2021 2021-06-03 TP -1.4271163556 #> 4876 2046 3M CC31 2021 2021-06-03 TSS 1.0986122887 I #> 4877 2046 3M CC31 2021 2021-06-03 TURB 0.5306282511 #> 4878 2046 3M CC31 2021 2021-07-01 CHLAC 2.7080502011 #> 4879 2046 3M CC31 2021 2021-07-01 COND 10.4739019677 #> 4880 2046 3M CC31 2021 2021-07-01 DO 1.6770965609 #> 4881 2046 3M CC31 2021 2021-07-01 DOSAT 4.3107991254 #> 4882 2046 3M CC31 2021 2021-07-01 NO23 -5.2983173665 I #> 4883 2046 3M CC31 2021 2021-07-01 SALIN 3.1014427280 #> 4884 2046 3M CC31 2021 2021-07-01 TKN -0.4462871026 #> 4885 2046 3M CC31 2021 2021-07-01 TN -0.4400565529 + #> 4886 2046 3M CC31 2021 2021-07-01 TP -1.2729656758 #> 4887 2046 3M CC31 2021 2021-07-01 TSS 1.7917594692 I #> 4888 2046 3M CC31 2021 2021-07-01 TURB 0.4054651081 #> 4889 2046 3M CC31 2021 2021-07-29 CHLAC 2.9444389792 #> 4890 2046 3M CC31 2021 2021-07-29 COND 9.3783094225 #> 4891 2046 3M CC31 2021 2021-07-29 DO 1.3558351536 #> 4892 2046 3M CC31 2021 2021-07-29 DOSAT 3.9646154555 #> 4893 2046 3M CC31 2021 2021-07-29 NO23 -3.3242363405 #> 4894 2046 3M CC31 2021 2021-07-29 SALIN 1.9021075264 #> 4895 2046 3M CC31 2021 2021-07-29 TKN 0.0953101798 #> 4896 2046 3M CC31 2021 2021-07-29 TN 0.1275133203 + #> 4897 2046 3M CC31 2021 2021-07-29 TP -0.9942522733 #> 4898 2046 3M CC31 2021 2021-07-29 TSS 1.6094379124 I #> 4899 2046 3M CC31 2021 2021-07-29 TURB 1.6094379124 #> 4900 2046 3M CC31 2021 2021-08-25 CHLAC 2.4849066498 #> 4901 2046 3M CC31 2021 2021-08-25 COND 9.4766200382 #> 4902 2046 3M CC31 2021 2021-08-25 DO 0.8153648133 #> 4903 2046 3M CC31 2021 2021-08-25 DOSAT 3.4404180948 #> 4904 2046 3M CC31 2021 2021-08-25 NO23 -4.0745419349 #> 4905 2046 3M CC31 2021 2021-08-25 SALIN 2.0095554142 #> 4906 2046 3M CC31 2021 2021-08-25 TKN 0.0000000000 #> 4907 2046 3M CC31 2021 2021-08-25 TN 0.0168571171 + #> 4908 2046 3M CC31 2021 2021-08-25 TP -1.1086626245 #> 4909 2046 3M CC31 2021 2021-08-25 TSS 1.7917594692 I #> 4910 2046 3M CC31 2021 2021-08-25 TURB 1.1939224685 #> 4911 2046 3M CC31 2021 2021-09-23 CHLAC 3.0445224377 #> 4912 2046 3M CC31 2021 2021-09-23 COND 8.7826296549 #> 4913 2046 3M CC31 2021 2021-09-23 DO 1.4747630091 #> 4914 2046 3M CC31 2021 2021-09-23 DOSAT 4.0483006237 #> 4915 2046 3M CC31 2021 2021-09-23 NO23 -3.0576076773 #> 4916 2046 3M CC31 2021 2021-09-23 SALIN 1.2641267271 #> 4917 2046 3M CC31 2021 2021-09-23 TKN -0.0943106795 #> 4918 2046 3M CC31 2021 2021-09-23 TN -0.0439518875 + #> 4919 2046 3M CC31 2021 2021-09-23 TP -1.4271163556 #> 4920 2046 3M CC31 2021 2021-09-23 TSS 1.3862943611 I #> 4921 2046 3M CC31 2021 2021-09-23 TURB 1.1631508098 #> 4922 2046 3M CC31 2021 2021-10-21 CHLAC 2.3025850930 #> 4923 2046 3M CC31 2021 2021-10-21 COND 9.9156631285 #> 4924 2046 3M CC31 2021 2021-10-21 DO 1.5040773968 #> 4925 2046 3M CC31 2021 2021-10-21 DOSAT 4.0690267542 #> 4926 2046 3M CC31 2021 2021-10-21 NO23 -3.1465551633 #> 4927 2046 3M CC31 2021 2021-10-21 SALIN 2.4907230351 #> 4928 2046 3M CC31 2021 2021-10-21 TKN -0.1278333715 #> 4929 2046 3M CC31 2021 2021-10-21 TN -0.0801260445 + #> 4930 2046 3M CC31 2021 2021-10-21 TP -1.5141277326 #> 4931 2046 3M CC31 2021 2021-10-21 TSS 1.0986122887 U #> 4932 2046 3M CC31 2021 2021-10-21 TURB 0.4700036292 A #> 4933 2046 3M CC31 2021 2021-11-22 COND 10.1079374614 #> 4934 2046 3M CC31 2021 2021-11-22 DO 1.7316555452 #> 4935 2046 3M CC31 2021 2021-11-22 DOSAT 4.2877159552 #> 4936 2046 3M CC31 2021 2021-11-22 NO23 -2.8134107168 #> 4937 2046 3M CC31 2021 2021-11-22 SALIN 2.7020321288 #> 4938 2046 3M CC31 2021 2021-11-22 TKN -0.6733445533 #> 4939 2046 3M CC31 2021 2021-11-22 TN -0.5621189182 + #> 4940 2046 3M CC31 2021 2021-11-22 TP -2.3025850930 #> 4941 2046 3M CC31 2021 2021-11-22 TSS 1.6094379124 I #> 4942 2046 3M CC31 2021 2021-11-22 TURB 0.1823215568 A #> 4943 2046 3M CC31 2022 2022-02-22 CHLAC 1.3083328197 #> 4944 2046 3M CC31 2022 2022-02-22 COND 10.5165899421 #> 4945 2046 3M CC31 2022 2022-02-22 DO 1.8547342684 #> 4946 2046 3M CC31 2022 2022-02-22 DOSAT 4.4320065670 #> 4947 2046 3M CC31 2022 2022-02-22 NO23 -5.5214609179 U #> 4948 2046 3M CC31 2022 2022-02-22 SALIN 3.1527360224 #> 4949 2046 3M CC31 2022 2022-02-22 TKN -0.6931471806 #> 4950 2046 3M CC31 2022 2022-02-22 TN -0.6891551593 + #> 4951 2046 3M CC31 2022 2022-02-22 TP -2.4304184645 #> 4952 2046 3M CC31 2022 2022-02-22 TSS 2.0794415417 I #> 4953 2046 3M CC31 2022 2022-02-22 TURB 0.4054651081 A #> 4954 2046 3M CC31 2022 2022-04-20 CHLAC 1.5260563035 #> 4955 2046 3M CC31 2022 2022-04-20 COND 10.6492271832 #> 4956 2046 3M CC31 2022 2022-04-20 DO 1.5581446180 #> 4957 2046 3M CC31 2022 2022-04-20 DOSAT 4.1805222585 #> 4958 2046 3M CC31 2022 2022-04-20 NO23 -5.5214609179 U #> 4959 2046 3M CC31 2022 2022-04-20 SALIN 3.2987954480 #> 4960 2046 3M CC31 2022 2022-04-20 TKN -0.5447271754 #> 4961 2046 3M CC31 2022 2022-04-20 TN -0.5412848313 + #> 4962 2046 3M CC31 2022 2022-04-20 TP -1.8325814637 #> 4963 2046 3M CC31 2022 2022-04-20 TSS 2.0794415417 I #> 4964 2046 3M CC31 2022 2022-04-20 TURB 1.0296194172 #> 4965 2056E 3M CC34 2015 2015-04-06 CHLAC 1.5040773968 #> 4966 2056E 3M CC34 2015 2015-04-06 COLOR 3.8066624898 #> 4967 2056E 3M CC34 2015 2015-04-06 COND 10.4003156667 #> 4968 2056E 3M CC34 2015 2015-04-06 DO 2.1317967720 #> 4969 2056E 3M CC34 2015 2015-04-06 DOSAT 4.7899886230 + #> 4970 2056E 3M CC34 2015 2015-04-06 NO23 -5.5214609179 U #> 4971 2056E 3M CC34 2015 2015-04-06 SALIN 3.0194488002 #> 4972 2056E 3M CC34 2015 2015-04-06 TKN -0.3509769228 #> 4973 2056E 3M CC34 2015 2015-04-06 TN -0.3509769228 #> 4974 2056E 3M CC34 2015 2015-04-06 TP -1.6928195214 #> 4975 2056E 3M CC34 2015 2015-04-06 TSS 1.6253112616 #> 4976 2056E 3M CC34 2015 2015-04-06 TURB 1.0647107370 #> 4977 2056E 3M CC34 2015 2015-04-06 COND 10.4033533361 #> 4978 2056E 3M CC34 2015 2015-04-06 DO 2.1341664414 #> 4979 2056E 3M CC34 2015 2015-04-06 DOSAT 4.7899886230 + #> 4980 2056E 3M CC34 2015 2015-04-06 SALIN 3.0233474406 #> 4981 2056E 3M CC34 2015 2015-04-06 COND 10.4069864009 #> 4982 2056E 3M CC34 2015 2015-04-06 DO 2.1435893615 #> 4983 2056E 3M CC34 2015 2015-04-06 DOSAT 4.7949637576 + #> 4984 2056E 3M CC34 2015 2015-04-06 SALIN 3.0272309406 #> 4985 2056E 3M CC36 2015 2015-04-06 CHLAC 1.5040773968 #> 4986 2056E 3M CC36 2015 2015-04-06 COLOR 3.8066624898 #> 4987 2056E 3M CC36 2015 2015-04-06 COND 10.4003156667 #> 4988 2056E 3M CC36 2015 2015-04-06 DO 2.1317967720 #> 4989 2056E 3M CC36 2015 2015-04-06 DOSAT 4.7899886230 + #> 4990 2056E 3M CC36 2015 2015-04-06 NO23 -5.5214609179 U #> 4991 2056E 3M CC36 2015 2015-04-06 SALIN 3.0194488002 #> 4992 2056E 3M CC36 2015 2015-04-06 TKN -0.3509769228 #> 4993 2056E 3M CC36 2015 2015-04-06 TN -0.3509769228 #> 4994 2056E 3M CC36 2015 2015-04-06 TP -1.6928195214 #> 4995 2056E 3M CC36 2015 2015-04-06 TSS 1.6253112616 #> 4996 2056E 3M CC36 2015 2015-04-06 TURB 1.0647107370 #> 4997 2056E 3M CC36 2015 2015-04-06 COND 10.4033533361 #> 4998 2056E 3M CC36 2015 2015-04-06 DO 2.1341664414 #> 4999 2056E 3M CC36 2015 2015-04-06 DOSAT 4.7899886230 + #> 5000 2056E 3M CC36 2015 2015-04-06 SALIN 3.0233474406 #> 5001 2056E 3M CC36 2015 2015-04-06 COND 10.4069864009 #> 5002 2056E 3M CC36 2015 2015-04-06 DO 2.1435893615 #> 5003 2056E 3M CC36 2015 2015-04-06 DOSAT 4.7949637576 + #> 5004 2056E 3M CC36 2015 2015-04-06 SALIN 3.0272309406 #> 5005 2056E 3M CC37 2013 2013-01-07 CHLAC 2.4849066498 #> 5006 2056E 3M CC37 2013 2013-01-07 COLOR 3.0445224377 A #> 5007 2056E 3M CC37 2013 2013-01-07 DO 1.8718021769 #> 5008 2056E 3M CC37 2013 2013-01-07 DOSAT 4.4379342666 + #> 5009 2056E 3M CC37 2013 2013-01-07 NO23 -4.9618451299 I #> 5010 2056E 3M CC37 2013 2013-01-07 SALIN 3.1612467120 #> 5011 2056E 3M CC37 2013 2013-01-07 TKN -0.2876820725 #> 5012 2056E 3M CC37 2013 2013-01-07 TN -0.2823629110 + #> 5013 2056E 3M CC37 2013 2013-01-07 TP -2.0402208285 #> 5014 2056E 3M CC37 2013 2013-01-07 TURB 1.0647107370 #> 5015 2056E 3M CC37 2013 2013-02-04 CHLAC 1.8870696490 #> 5016 2056E 3M CC37 2013 2013-02-04 COLOR 2.5649493575 #> 5017 2056E 3M CC37 2013 2013-02-04 DOSAT 4.4624538838 + #> 5018 2056E 3M CC37 2013 2013-02-04 NO23 -5.2983173665 I #> 5019 2056E 3M CC37 2013 2013-02-04 SALIN 3.2619353143 #> 5020 2056E 3M CC37 2013 2013-02-04 TKN -0.5798184953 #> 5021 2056E 3M CC37 2013 2013-02-04 TN -0.5727010275 + #> 5022 2056E 3M CC37 2013 2013-02-04 TP -2.9565115604 #> 5023 2056E 3M CC37 2013 2013-02-04 TURB 1.0296194172 A #> 5024 2056E 3M CC37 2013 2013-03-04 CHLAC 2.1282317058 #> 5025 2056E 3M CC37 2013 2013-03-04 COLOR 2.6390573296 A #> 5026 2056E 3M CC37 2013 2013-03-04 DOSAT 4.0073331852 + #> 5027 2056E 3M CC37 2013 2013-03-04 NO23 -3.5755507688 #> 5028 2056E 3M CC37 2013 2013-03-04 SALIN 3.2921262866 #> 5029 2056E 3M CC37 2013 2013-03-04 TKN -0.2231435513 #> 5030 2056E 3M CC37 2013 2013-03-04 TN -0.1887421246 + #> 5031 2056E 3M CC37 2013 2013-03-04 TP -1.8971199849 #> 5032 2056E 3M CC37 2013 2013-03-04 TURB 1.4109869737 #> 5033 2056E 3M CC37 2013 2013-04-01 CHLAC 1.7749523509 A #> 5034 2056E 3M CC37 2013 2013-04-01 COLOR 2.6390573296 #> 5035 2056E 3M CC37 2013 2013-04-01 DO 1.9021075264 #> 5036 2056E 3M CC37 2013 2013-04-01 DOSAT 4.4796069630 + #> 5037 2056E 3M CC37 2013 2013-04-01 NO23 -5.1159958098 I #> 5038 2056E 3M CC37 2013 2013-04-01 SALIN 3.3105430134 #> 5039 2056E 3M CC37 2013 2013-04-01 TKN -0.3147107448 #> 5040 2056E 3M CC37 2013 2013-04-01 TN -0.3092462504 + #> 5041 2056E 3M CC37 2013 2013-04-01 TP -2.2072749132 #> 5042 2056E 3M CC37 2013 2013-04-01 TURB 1.1939224685 #> 5043 2056E 3M CC37 2013 2013-05-06 CHLAC 3.0445224377 #> 5044 2056E 3M CC37 2013 2013-05-06 COLOR 3.1354942159 A #> 5045 2056E 3M CC37 2013 2013-05-06 DO 2.1282317058 #> 5046 2056E 3M CC37 2013 2013-05-06 DOSAT 4.7370752569 + #> 5047 2056E 3M CC37 2013 2013-05-06 NO23 -4.6051701860 I #> 5048 2056E 3M CC37 2013 2013-05-06 SALIN 3.1904763503 #> 5049 2056E 3M CC37 2013 2013-05-06 TKN -0.1392620673 #> 5050 2056E 3M CC37 2013 2013-05-06 TN -0.1346749033 + #> 5051 2056E 3M CC37 2013 2013-05-06 TP -1.3470736480 #> 5052 2056E 3M CC37 2013 2013-05-06 TURB 1.6486586256 A #> 5053 2056E 3M CC37 2013 2013-06-03 CHLAC 2.2823823857 #> 5054 2056E 3M CC37 2013 2013-06-03 COLOR 2.9957322736 #> 5055 2056E 3M CC37 2013 2013-06-03 DOSAT 4.2724907476 + #> 5056 2056E 3M CC37 2013 2013-06-03 NO23 -4.8283137373 I #> 5057 2056E 3M CC37 2013 2013-06-03 SALIN 3.2464909919 #> 5058 2056E 3M CC37 2013 2013-06-03 TKN -0.2231435513 #> 5059 2056E 3M CC37 2013 2013-06-03 TN -0.2181560098 + #> 5060 2056E 3M CC37 2013 2013-06-03 TP -1.2729656758 #> 5061 2056E 3M CC37 2013 2013-06-03 TURB 1.1939224685 #> 5062 2056E 3M CC37 2013 2013-07-08 CHLAC 2.4849066498 #> 5063 2056E 3M CC37 2013 2013-07-08 COLOR 4.5325994932 #> 5064 2056E 3M CC37 2013 2013-07-08 DO 1.6292405397 #> 5065 2056E 3M CC37 2013 2013-07-08 DOSAT 4.1805222585 + #> 5066 2056E 3M CC37 2013 2013-07-08 NO23 -2.3025850930 #> 5067 2056E 3M CC37 2013 2013-07-08 SALIN 1.0647107370 #> 5068 2056E 3M CC37 2013 2013-07-08 TKN 0.1823215568 #> 5069 2056E 3M CC37 2013 2013-07-08 TN 0.2623642645 + #> 5070 2056E 3M CC37 2013 2013-07-08 TP -0.6931471806 #> 5071 2056E 3M CC37 2013 2013-07-08 TURB 1.5686159179 #> 5072 2056E 3M CC37 2013 2013-08-05 CHLAC 2.3025850930 #> 5073 2056E 3M CC37 2013 2013-08-05 COLOR 5.4380793089 #> 5074 2056E 3M CC37 2013 2013-08-05 DO 1.5686159179 #> 5075 2056E 3M CC37 2013 2013-08-05 DOSAT 4.1557531904 + #> 5076 2056E 3M CC37 2013 2013-08-05 NO23 -2.9759296463 #> 5077 2056E 3M CC37 2013 2013-08-05 SALIN 1.5686159179 #> 5078 2056E 3M CC37 2013 2013-08-05 TKN 0.3364722366 #> 5079 2056E 3M CC37 2013 2013-08-05 TN 0.3722529739 + #> 5080 2056E 3M CC37 2013 2013-08-05 TP -0.5798184953 #> 5081 2056E 3M CC37 2013 2013-08-05 TURB 0.7884573604 #> 5082 2056E 3M CC37 2013 2013-09-09 CHLAC 1.5686159179 #> 5083 2056E 3M CC37 2013 2013-09-09 COLOR 4.4659081187 #> 5084 2056E 3M CC37 2013 2013-09-09 DOSAT 4.0127729085 + #> 5085 2056E 3M CC37 2013 2013-09-09 NO23 -3.2968373663 #> 5086 2056E 3M CC37 2013 2013-09-09 SALIN 1.9600947840 #> 5087 2056E 3M CC37 2013 2013-09-09 TKN 0.0000000000 #> 5088 2056E 3M CC37 2013 2013-09-09 TN 0.0363319292 + #> 5089 2056E 3M CC37 2013 2013-09-09 TP -0.7339691751 #> 5090 2056E 3M CC37 2013 2013-09-09 TURB 0.6418538862 #> 5091 2056E 3M CC37 2013 2013-10-07 CHLAC 0.8329091229 #> 5092 2056E 3M CC37 2013 2013-10-07 COLOR 4.5747109785 A #> 5093 2056E 3M CC37 2013 2013-10-07 DOSAT 4.1335652754 + #> 5094 2056E 3M CC37 2013 2013-10-07 NO23 -2.3025850930 #> 5095 2056E 3M CC37 2013 2013-10-07 SALIN 2.2617630985 #> 5096 2056E 3M CC37 2013 2013-10-07 TKN 0.0000000000 #> 5097 2056E 3M CC37 2013 2013-10-07 TN 0.0953101798 + #> 5098 2056E 3M CC37 2013 2013-10-07 TP -0.8439700703 #> 5099 2056E 3M CC37 2013 2013-10-07 TURB 0.3364722366 A #> 5100 2056E 3M CC37 2013 2013-11-04 CHLAC 1.2527629685 #> 5101 2056E 3M CC37 2013 2013-11-04 COLOR 3.8066624898 A #> 5102 2056E 3M CC37 2013 2013-11-04 DOSAT 4.1573193614 + #> 5103 2056E 3M CC37 2013 2013-11-04 NO23 -3.9633162998 #> 5104 2056E 3M CC37 2013 2013-11-04 SALIN 2.9704144656 #> 5105 2056E 3M CC37 2013 2013-11-04 TKN -0.5447271754 #> 5106 2056E 3M CC37 2013 2013-11-04 TN -0.5124936809 + #> 5107 2056E 3M CC37 2013 2013-11-04 TP -1.7147984281 #> 5108 2056E 3M CC37 2013 2013-11-04 TURB 0.5877866649 A #> 5109 2056E 3M CC37 2013 2013-12-02 CHLAC 1.3350010667 #> 5110 2056E 3M CC37 2013 2013-12-02 COLOR 3.0910424534 A #> 5111 2056E 3M CC37 2013 2013-12-02 DO 1.9169226122 #> 5112 2056E 3M CC37 2013 2013-12-02 DOSAT 4.4624538838 + #> 5113 2056E 3M CC37 2013 2013-12-02 NO23 -3.5404594490 #> 5114 2056E 3M CC37 2013 2013-12-02 SALIN 3.2188758249 #> 5115 2056E 3M CC37 2013 2013-12-02 TKN -0.4780358009 #> 5116 2056E 3M CC37 2013 2013-12-02 TN -0.4323225623 + #> 5117 2056E 3M CC37 2013 2013-12-02 TP -2.1202635362 #> 5118 2056E 3M CC37 2013 2013-12-02 TURB 0.3364722366 #> 5119 2056E 3M CC37 2014 2014-01-06 CHLAC 1.5686159179 #> 5120 2056E 3M CC37 2014 2014-01-06 COLOR 2.9957322736 A #> 5121 2056E 3M CC37 2014 2014-01-06 DOSAT 4.3832758541 + #> 5122 2056E 3M CC37 2014 2014-01-06 NO23 -4.3428059215 #> 5123 2056E 3M CC37 2014 2014-01-06 SALIN 3.3032169733 #> 5124 2056E 3M CC37 2014 2014-01-06 TKN -0.5978370008 #> 5125 2056E 3M CC37 2014 2014-01-06 TN -0.5744756508 + #> 5126 2056E 3M CC37 2014 2014-01-06 TP -2.3025850930 #> 5127 2056E 3M CC37 2014 2014-01-06 TURB 0.2623642645 #> 5128 2056E 3M CC37 2014 2014-02-03 CHLAC 1.4816045409 #> 5129 2056E 3M CC37 2014 2014-02-03 COLOR 2.7725887222 #> 5130 2056E 3M CC37 2014 2014-02-03 DO 1.8562979904 #> 5131 2056E 3M CC37 2014 2014-02-03 DOSAT 4.3502779364 + #> 5132 2056E 3M CC37 2014 2014-02-03 NO23 -3.2968373663 #> 5133 2056E 3M CC37 2014 2014-02-03 SALIN 2.6461747974 #> 5134 2056E 3M CC37 2014 2014-02-03 TKN -0.1743533871 #> 5135 2056E 3M CC37 2014 2014-02-03 TN -0.1312482866 + #> 5136 2056E 3M CC37 2014 2014-02-03 TP -2.3025850930 #> 5137 2056E 3M CC37 2014 2014-02-03 TURB 0.7419373447 #> 5138 2056E 3M CC37 2014 2014-03-03 CHLAC 1.7578579176 #> 5139 2056E 3M CC37 2014 2014-03-03 COLOR 2.8903717579 A #> 5140 2056E 3M CC37 2014 2014-03-03 DO 1.8082887712 #> 5141 2056E 3M CC37 2014 2014-03-03 DOSAT 4.3579900568 + #> 5142 2056E 3M CC37 2014 2014-03-03 NO23 -4.5098600062 #> 5143 2056E 3M CC37 2014 2014-03-03 SALIN 3.1000922889 #> 5144 2056E 3M CC37 2014 2014-03-03 TKN -0.2744368457 #> 5145 2056E 3M CC37 2014 2014-03-03 TN -0.2600669054 + #> 5146 2056E 3M CC37 2014 2014-03-03 TP -1.8971199849 #> 5147 2056E 3M CC37 2014 2014-03-03 TURB 1.0296194172 #> 5148 2056E 3M CC37 2014 2014-04-07 CHLAC 2.2721258855 #> 5149 2056E 3M CC37 2014 2014-04-07 COLOR 2.9444389792 #> 5150 2056E 3M CC37 2014 2014-04-07 DO 1.8718021769 #> 5151 2056E 3M CC37 2014 2014-04-07 DOSAT 4.4953553200 + #> 5152 2056E 3M CC37 2014 2014-04-07 NO23 -4.9618451299 I #> 5153 2056E 3M CC37 2014 2014-04-07 SALIN 3.1000922889 #> 5154 2056E 3M CC37 2014 2014-04-07 TKN -0.4942963218 #> 5155 2056E 3M CC37 2014 2014-04-07 TN -0.4877603508 + #> 5156 2056E 3M CC37 2014 2014-04-07 TP -1.7147984281 #> 5157 2056E 3M CC37 2014 2014-04-07 TURB 1.2237754316 #> 5158 2056E 3M CC37 2014 2014-05-05 CHLAC 3.0445224377 #> 5159 2056E 3M CC37 2014 2014-05-05 COLOR 3.0910424534 #> 5160 2056E 3M CC37 2014 2014-05-05 DO 1.7917594692 #> 5161 2056E 3M CC37 2014 2014-05-05 DOSAT 4.4152196020 + #> 5162 2056E 3M CC37 2014 2014-05-05 NO23 -5.1159958098 I #> 5163 2056E 3M CC37 2014 2014-05-05 SALIN 3.2068032436 #> 5164 2056E 3M CC37 2014 2014-05-05 TKN -0.0100503359 #> 5165 2056E 3M CC37 2014 2014-05-05 TN -0.0060180723 + #> 5166 2056E 3M CC37 2014 2014-05-05 TP -1.2729656758 #> 5167 2056E 3M CC37 2014 2014-05-05 TURB 1.9315214116 #> 5168 2056E 3M CC37 2014 2014-06-02 CHLAC 2.2617630985 #> 5169 2056E 3M CC37 2014 2014-06-02 COLOR 3.2188758249 #> 5170 2056E 3M CC37 2014 2014-06-02 DO 1.6292405397 #> 5171 2056E 3M CC37 2014 2014-06-02 DOSAT 4.3040650932 + #> 5172 2056E 3M CC37 2014 2014-06-02 NO23 -5.1159958098 I #> 5173 2056E 3M CC37 2014 2014-06-02 SALIN 3.2425923515 #> 5174 2056E 3M CC37 2014 2014-06-02 TKN -0.1625189295 #> 5175 2056E 3M CC37 2014 2014-06-02 TN -0.1578240852 + #> 5176 2056E 3M CC37 2014 2014-06-02 TP -1.0216512475 #> 5177 2056E 3M CC37 2014 2014-06-02 TURB 1.4816045409 #> 5178 2056E 3M CC37 2014 2014-07-07 CHLAC 2.5649493575 #> 5179 2056E 3M CC37 2014 2014-07-07 COLOR 3.3672958300 A #> 5180 2056E 3M CC37 2014 2014-07-07 NO23 -5.5214609179 I #> 5181 2056E 3M CC37 2014 2014-07-07 SALIN 3.1398326175 #> 5182 2056E 3M CC37 2014 2014-07-07 TKN -0.0304592075 #> 5183 2056E 3M CC37 2014 2014-07-07 TN -0.0263439753 + #> 5184 2056E 3M CC37 2014 2014-07-07 TP -0.9675840263 #> 5185 2056E 3M CC37 2014 2014-07-07 TURB 1.5260563035 #> 5186 2056E 3M CC37 2014 2014-08-04 CHLAC 2.7080502011 #> 5187 2056E 3M CC37 2014 2014-08-04 COLOR 4.0073331852 A #> 5188 2056E 3M CC37 2014 2014-08-04 DO 1.7047480922 #> 5189 2056E 3M CC37 2014 2014-08-04 DOSAT 4.3214801348 + #> 5190 2056E 3M CC37 2014 2014-08-04 NO23 -4.5098600062 #> 5191 2056E 3M CC37 2014 2014-08-04 SALIN 2.4336133554 #> 5192 2056E 3M CC37 2014 2014-08-04 TKN 0.0953101798 #> 5193 2056E 3M CC37 2014 2014-08-04 TN 0.1052605107 + #> 5194 2056E 3M CC37 2014 2014-08-04 TP -0.7550225843 #> 5195 2056E 3M CC37 2014 2014-08-04 TURB 1.0296194172 #> 5196 2056E 3M CC37 2014 2014-09-08 CHLAC 0.5877866649 #> 5197 2056E 3M CC37 2014 2014-09-08 COLOR 3.6375861597 A #> 5198 2056E 3M CC37 2014 2014-09-08 DOSAT 3.7588718259 + #> 5199 2056E 3M CC37 2014 2014-09-08 NO23 -4.1997050779 #> 5200 2056E 3M CC37 2014 2014-09-08 SALIN 2.6318888401 #> 5201 2056E 3M CC37 2014 2014-09-08 TKN -0.1743533871 #> 5202 2056E 3M CC37 2014 2014-09-08 TN -0.1566538100 + #> 5203 2056E 3M CC37 2014 2014-09-08 TP -1.0498221245 #> 5204 2056E 3M CC37 2014 2014-09-08 TURB 0.6931471806 A #> 5205 2056E 3M CC37 2014 2014-10-06 CHLAC 1.7917594692 #> 5206 2056E 3M CC37 2014 2014-10-06 COLOR 4.1588830834 A #> 5207 2056E 3M CC37 2014 2014-10-06 DO 1.3350010667 #> 5208 2056E 3M CC37 2014 2014-10-06 DOSAT 3.8458832029 + #> 5209 2056E 3M CC37 2014 2014-10-06 NO23 -2.9957322736 #> 5210 2056E 3M CC37 2014 2014-10-06 SALIN 1.9600947840 #> 5211 2056E 3M CC37 2014 2014-10-06 TKN -0.1508228897 #> 5212 2056E 3M CC37 2014 2014-10-06 TN -0.0943106795 + #> 5213 2056E 3M CC37 2014 2014-10-06 TP -1.1086626245 #> 5214 2056E 3M CC37 2014 2014-10-06 TURB 0.8754687374 #> 5215 2056E 3M CC37 2014 2014-11-03 CHLAC 2.1517622033 #> 5216 2056E 3M CC37 2014 2014-11-03 COLOR 3.9318256327 A #> 5217 2056E 3M CC37 2014 2014-11-03 DO 1.8245492921 #> 5218 2056E 3M CC37 2014 2014-11-03 DOSAT 4.2499227940 + #> 5219 2056E 3M CC37 2014 2014-11-03 NO23 -4.2686979494 #> 5220 2056E 3M CC37 2014 2014-11-03 SALIN 2.7600099400 #> 5221 2056E 3M CC37 2014 2014-11-03 TKN -0.1508228897 #> 5222 2056E 3M CC37 2014 2014-11-03 TN -0.1346749033 + #> 5223 2056E 3M CC37 2014 2014-11-03 TP -1.5606477483 #> 5224 2056E 3M CC37 2014 2014-11-03 TURB 0.7884573604 #> 5225 2056E 3M CC37 2014 2014-12-01 CHLAC 2.1633230257 #> 5226 2056E 3M CC37 2014 2014-12-01 COLOR 3.4657359028 #> 5227 2056E 3M CC37 2014 2014-12-01 DO 1.9600947840 #> 5228 2056E 3M CC37 2014 2014-12-01 DOSAT 4.4343818650 + #> 5229 2056E 3M CC37 2014 2014-12-01 NO23 -3.4737680745 #> 5230 2056E 3M CC37 2014 2014-12-01 SALIN 2.8622008809 #> 5231 2056E 3M CC37 2014 2014-12-01 TKN -0.3147107448 #> 5232 2056E 3M CC37 2014 2014-12-01 TN -0.2731219211 + #> 5233 2056E 3M CC37 2014 2014-12-01 TP -1.9661128564 #> 5234 2056E 3M CC37 2014 2014-12-01 TURB 0.7884573604 #> 5235 2056E 3M CC37 2015 2015-01-05 CHLAC 1.8870696490 #> 5236 2056E 3M CC37 2015 2015-01-05 COLOR 3.2958368660 A #> 5237 2056E 3M CC37 2015 2015-01-05 DO 1.7917594692 #> 5238 2056E 3M CC37 2015 2015-01-05 DOSAT 4.3732381286 + #> 5239 2056E 3M CC37 2015 2015-01-05 NO23 -3.9633162998 #> 5240 2056E 3M CC37 2015 2015-01-05 SALIN 2.9549102790 #> 5241 2056E 3M CC37 2015 2015-01-05 TKN -0.4780358009 #> 5242 2056E 3M CC37 2015 2015-01-05 TN -0.4478508246 + #> 5243 2056E 3M CC37 2015 2015-01-05 TP -2.1202635362 #> 5244 2056E 3M CC37 2015 2015-01-05 TURB 0.8754687374 #> 5245 2056E 3M CC37 2015 2015-02-02 CHLAC 1.6094379124 #> 5246 2056E 3M CC37 2015 2015-02-02 COLOR 2.8332133441 A #> 5247 2056E 3M CC37 2015 2015-02-02 DO 1.8245492921 #> 5248 2056E 3M CC37 2015 2015-02-02 DOSAT 4.3333614627 + #> 5249 2056E 3M CC37 2015 2015-02-02 NO23 -4.6051701860 #> 5250 2056E 3M CC37 2015 2015-02-02 SALIN 3.0773122605 #> 5251 2056E 3M CC37 2015 2015-02-02 TKN -0.6733445533 #> 5252 2056E 3M CC37 2015 2015-02-02 TN -0.6539264674 + #> 5253 2056E 3M CC37 2015 2015-02-02 TP -2.1202635362 #> 5254 2056E 3M CC37 2015 2015-02-02 TURB 0.9162907319 #> 5255 2056E 3M CC37 2015 2015-03-02 CHLAC 2.0014800002 #> 5256 2056E 3M CC37 2015 2015-03-02 COLOR 3.2958368660 #> 5257 2056E 3M CC37 2015 2015-03-02 DO 1.6486586256 #> 5258 2056E 3M CC37 2015 2015-03-02 DOSAT 4.2002049529 + #> 5259 2056E 3M CC37 2015 2015-03-02 NO23 -2.9759296463 #> 5260 2056E 3M CC37 2015 2015-03-02 SALIN 2.9285235239 #> 5261 2056E 3M CC37 2015 2015-03-02 TKN -0.3566749439 #> 5262 2056E 3M CC37 2015 2015-03-02 TN -0.2863496272 + #> 5263 2056E 3M CC37 2015 2015-03-02 TP -2.0402208285 #> 5264 2056E 3M CC37 2015 2015-03-02 TURB 0.7419373447 #> 5265 2056E 3M CC37 2015 2015-04-06 CHLAC 1.8245492921 #> 5266 2056E 3M CC37 2015 2015-04-06 COLOR 3.2188758249 A #> 5267 2056E 3M CC37 2015 2015-04-06 DO 1.6292405397 #> 5268 2056E 3M CC37 2015 2015-04-06 DOSAT 4.2297491992 + #> 5269 2056E 3M CC37 2015 2015-04-06 NO23 -4.5098600062 #> 5270 2056E 3M CC37 2015 2015-04-06 SALIN 3.0252910758 #> 5271 2056E 3M CC37 2015 2015-04-06 TKN -0.1165338163 #> 5272 2056E 3M CC37 2015 2015-04-06 TN -0.1042500214 + #> 5273 2056E 3M CC37 2015 2015-04-06 TP -1.6094379124 #> 5274 2056E 3M CC37 2015 2015-04-06 TURB 1.3083328197 #> 5275 2056E 3M CC37 2015 2015-05-04 CHLAC 1.7917594692 #> 5276 2056E 3M CC37 2015 2015-05-04 COLOR 3.2958368660 A #> 5277 2056E 3M CC37 2015 2015-05-04 DO 1.4816045409 #> 5278 2056E 3M CC37 2015 2015-05-04 DOSAT 4.0724397268 + #> 5279 2056E 3M CC37 2015 2015-05-04 NO23 -5.2983173665 I #> 5280 2056E 3M CC37 2015 2015-05-04 SALIN 3.0773122605 #> 5281 2056E 3M CC37 2015 2015-05-04 TKN -0.3856624808 #> 5282 2056E 3M CC37 2015 2015-05-04 TN -0.3797973614 + #> 5283 2056E 3M CC37 2015 2015-05-04 TP -2.0402208285 #> 5284 2056E 3M CC37 2015 2015-05-04 TURB 1.3350010667 #> 5285 2056E 3M CC37 2015 2015-06-01 CHLAC 2.7080502011 #> 5286 2056E 3M CC37 2015 2015-06-01 COLOR 3.2188758249 A #> 5287 2056E 3M CC37 2015 2015-06-01 DOSAT 4.0587173846 + #> 5288 2056E 3M CC37 2015 2015-06-01 NO23 -5.1159958098 I #> 5289 2056E 3M CC37 2015 2015-06-01 SALIN 2.8332133441 #> 5290 2056E 3M CC37 2015 2015-06-01 TKN 0.0000000000 #> 5291 2056E 3M CC37 2015 2015-06-01 TN 0.0039920213 + #> 5292 2056E 3M CC37 2015 2015-06-01 TP -1.1711829815 #> 5293 2056E 3M CC37 2015 2015-06-01 TURB 1.5475625087 A #> 5294 2056E 3M CC37 2015 2015-08-03 CHLAC 3.2580965380 #> 5295 2056E 3M CC37 2015 2015-08-03 COLOR 3.8286413965 #> 5296 2056E 3M CC37 2015 2015-08-03 DO 1.9169226122 #> 5297 2056E 3M CC37 2015 2015-08-03 DOSAT 4.4784725329 + #> 5298 2056E 3M CC37 2015 2015-08-03 NO23 -4.0173835211 #> 5299 2056E 3M CC37 2015 2015-08-03 SALIN 1.9021075264 #> 5300 2056E 3M CC37 2015 2015-08-03 TKN 0.0000000000 #> 5301 2056E 3M CC37 2015 2015-08-03 TN 0.0178399181 + #> 5302 2056E 3M CC37 2015 2015-08-03 TP -0.8439700703 #> 5303 2056E 3M CC37 2015 2015-08-03 TURB 1.0986122887 A #> 5304 2056E 3M CC37 2015 2015-09-08 CHLAC 2.7080502011 #> 5305 2056E 3M CC37 2015 2015-09-08 COLOR 4.7004803658 A #> 5306 2056E 3M CC37 2015 2015-09-08 DO 1.7227665977 #> 5307 2056E 3M CC37 2015 2015-09-08 DOSAT 4.3067641502 + #> 5308 2056E 3M CC37 2015 2015-09-08 NO23 -3.3242363405 #> 5309 2056E 3M CC37 2015 2015-09-08 SALIN 1.7749523509 #> 5310 2056E 3M CC37 2015 2015-09-08 TKN 0.1823215568 #> 5311 2056E 3M CC37 2015 2015-09-08 TN 0.2118803590 + #> 5312 2056E 3M CC37 2015 2015-09-08 TP -0.2613647641 #> 5313 2056E 3M CC37 2015 2015-09-08 TURB 1.3083328197 #> 5314 2056E 3M CC37 2015 2015-10-05 CHLAC 2.3978952728 #> 5315 2056E 3M CC37 2015 2015-10-05 COLOR 4.5643481915 A #> 5316 2056E 3M CC37 2015 2015-10-05 DO 1.8562979904 #> 5317 2056E 3M CC37 2015 2015-10-05 DOSAT 4.3732381286 + #> 5318 2056E 3M CC37 2015 2015-10-05 NO23 -3.7722610631 #> 5319 2056E 3M CC37 2015 2015-10-05 SALIN 2.2721258855 #> 5320 2056E 3M CC37 2015 2015-10-05 TKN -0.2876820725 #> 5321 2056E 3M CC37 2015 2015-10-05 TN -0.2574762304 + #> 5322 2056E 3M CC37 2015 2015-10-05 TP -0.9416085399 #> 5323 2056E 3M CC37 2015 2015-10-05 TURB 0.4054651081 #> 5324 2056E 3M CC37 2016 2016-02-01 CHLAC 2.6390573296 #> 5325 2056E 3M CC37 2016 2016-02-01 COLOR 4.5217885770 A #> 5326 2056E 3M CC37 2016 2016-02-01 NO23 -1.9661128564 #> 5327 2056E 3M CC37 2016 2016-02-01 TKN -0.3285040670 #> 5328 2056E 3M CC37 2016 2016-02-01 TN -0.1508228897 + #> 5329 2056E 3M CC37 2016 2016-02-01 TP -1.0216512475 #> 5330 2056E 3M CC37 2016 2016-02-01 TURB 0.9162907319 #> 5331 2056E 3M CC37 2016 2016-03-07 CHLAC 2.4849066498 #> 5332 2056E 3M CC37 2016 2016-03-07 COLOR 3.8918202981 A #> 5333 2056E 3M CC37 2016 2016-03-07 DO 1.6331544391 #> 5334 2056E 3M CC37 2016 2016-03-07 DOSAT 4.0859763126 + #> 5335 2056E 3M CC37 2016 2016-03-07 NO23 -4.1997050779 #> 5336 2056E 3M CC37 2016 2016-03-07 SALIN 2.7040421797 #> 5337 2056E 3M CC37 2016 2016-03-07 TKN -0.3011050928 #> 5338 2056E 3M CC37 2016 2016-03-07 TN -0.2810375297 + #> 5339 2056E 3M CC37 2016 2016-03-07 TP -1.5141277326 #> 5340 2056E 3M CC37 2016 2016-03-07 TURB 1.2527629685 #> 5341 2056E 3M CC37 2016 2016-04-04 CHLAC 2.3978952728 #> 5342 2056E 3M CC37 2016 2016-04-04 COLOR 3.6635616461 #> 5343 2056E 3M CC37 2016 2016-04-04 DO 1.3711807233 #> 5344 2056E 3M CC37 2016 2016-04-04 DOSAT 3.9512437186 + #> 5345 2056E 3M CC37 2016 2016-04-04 NO23 -3.5065578973 #> 5346 2056E 3M CC37 2016 2016-04-04 SALIN 2.6905648868 #> 5347 2056E 3M CC37 2016 2016-04-04 TKN -0.0202027073 #> 5348 2056E 3M CC37 2016 2016-04-04 TN 0.0099503309 + #> 5349 2056E 3M CC37 2016 2016-04-04 TP -1.3470736480 #> 5350 2056E 3M CC37 2016 2016-04-04 TURB 1.5260563035 #> 5351 2056E 3M CC37 2017 2017-02-06 CHLAC 2.8903717579 #> 5352 2056E 3M CC37 2017 2017-02-06 COLOR 2.9444389792 A #> 5353 2056E 3M CC37 2017 2017-02-06 DO 1.6311994042 #> 5354 2056E 3M CC37 2017 2017-02-06 DOSAT 4.2239097666 + #> 5355 2056E 3M CC37 2017 2017-02-06 NO23 -5.5214609179 U #> 5356 2056E 3M CC37 2017 2017-02-06 SALIN 3.3138223022 #> 5357 2056E 3M CC37 2017 2017-02-06 TKN -0.0943106795 #> 5358 2056E 3M CC37 2017 2017-02-06 TN -0.0921152889 + #> 5359 2056E 3M CC37 2017 2017-02-06 TP -1.7147984281 #> 5360 2056E 3M CC37 2017 2017-02-06 TURB 1.8562979904 #> 5361 2056E 3M CC37 2017 2017-03-06 CHLAC 2.1517622033 #> 5362 2056E 3M CC37 2017 2017-03-06 COLOR 2.7080502011 #> 5363 2056E 3M CC37 2017 2017-03-06 DO 1.7191887764 #> 5364 2056E 3M CC37 2017 2017-03-06 DOSAT 4.2931954210 + #> 5365 2056E 3M CC37 2017 2017-03-06 NO23 -5.5214609179 U #> 5366 2056E 3M CC37 2017 2017-03-06 SALIN 3.3279095859 #> 5367 2056E 3M CC37 2017 2017-03-06 TKN -0.1743533871 #> 5368 2056E 3M CC37 2017 2017-03-06 TN -0.1719752647 + #> 5369 2056E 3M CC37 2017 2017-03-06 TP -1.9661128564 #> 5370 2056E 3M CC37 2017 2017-03-06 TURB 1.3862943611 #> 5371 2056E 3M CC37 2017 2017-04-03 CHLAC 2.3978952728 #> 5372 2056E 3M CC37 2017 2017-04-03 COLOR 2.7080502011 A #> 5373 2056E 3M CC37 2017 2017-04-03 DO 1.5727739281 #> 5374 2056E 3M CC37 2017 2017-04-03 DOSAT 4.2640873368 + #> 5375 2056E 3M CC37 2017 2017-04-03 NO23 -5.5214609179 U #> 5376 2056E 3M CC37 2017 2017-04-03 SALIN 3.3914836895 #> 5377 2056E 3M CC37 2017 2017-04-03 TKN -0.1508228897 #> 5378 2056E 3M CC37 2017 2017-04-03 TN -0.1485000083 + #> 5379 2056E 3M CC37 2017 2017-04-03 TP -1.6607312068 #> 5380 2056E 3M CC37 2017 2017-04-03 TURB 1.3862943611 A #> 5381 2056E 3M CC37 2017 2017-07-10 CHLAC 2.7080502011 #> 5382 2056E 3M CC37 2017 2017-07-10 COLOR 4.7874917428 A #> 5383 2056E 3M CC37 2017 2017-07-10 DO 0.8415671857 #> 5384 2056E 3M CC37 2017 2017-07-10 DOSAT 3.4965075615 + #> 5385 2056E 3M CC37 2017 2017-07-10 NO23 -5.1159958098 I #> 5386 2056E 3M CC37 2017 2017-07-10 TKN 0.1823215568 #> 5387 2056E 3M CC37 2017 2017-07-10 TN 0.1856493469 + #> 5388 2056E 3M CC37 2017 2017-07-10 TP -0.4780358009 #> 5389 2056E 3M CC37 2017 2017-07-10 TURB 1.1939224685 #> 5390 2056E 3M CC37 2017 2017-08-07 CHLAC 1.6863989536 #> 5391 2056E 3M CC37 2017 2017-08-07 COLOR 4.7004803658 #> 5392 2056E 3M CC37 2017 2017-08-07 DO 0.7793248768 #> 5393 2056E 3M CC37 2017 2017-08-07 DOSAT 3.4144426084 + #> 5394 2056E 3M CC37 2017 2017-08-07 NO23 -2.2072749132 #> 5395 2056E 3M CC37 2017 2017-08-07 SALIN 1.7647307968 #> 5396 2056E 3M CC37 2017 2017-08-07 TKN 0.1823215568 #> 5397 2056E 3M CC37 2017 2017-08-07 TN 0.2700271372 + #> 5398 2056E 3M CC37 2017 2017-08-07 TP -0.8209805521 #> 5399 2056E 3M CC37 2017 2017-08-07 TURB 0.7884573604 #> 5400 2056E 3M CC37 2017 2017-09-05 CHLAC 2.8332133441 #> 5401 2056E 3M CC37 2017 2017-09-05 COLOR 4.4998096703 #> 5402 2056E 3M CC37 2017 2017-09-05 DO 1.4516138272 #> 5403 2056E 3M CC37 2017 2017-09-05 DOSAT 4.0377742107 + #> 5404 2056E 3M CC37 2017 2017-09-05 NO23 -2.4889146712 #> 5405 2056E 3M CC37 2017 2017-09-05 SALIN 0.1906203596 #> 5406 2056E 3M CC37 2017 2017-09-05 TKN -0.0725706928 #> 5407 2056E 3M CC37 2017 2017-09-05 TN 0.0129162253 + #> 5408 2056E 3M CC37 2017 2017-09-05 TP -0.9675840263 #> 5409 2056E 3M CC37 2017 2017-09-05 TURB 1.0986122887 #> 5410 2056E 3M CC37 2017 2017-10-02 CHLAC 1.9169226122 #> 5411 2056E 3M CC37 2017 2017-10-02 COLOR 4.4886363697 A #> 5412 2056E 3M CC37 2017 2017-10-02 NO23 -2.9565115604 #> 5413 2056E 3M CC37 2017 2017-10-02 TKN -0.8675005677 #> 5414 2056E 3M CC37 2017 2017-10-02 TN -0.7507762934 + #> 5415 2056E 3M CC37 2017 2017-10-02 TP -0.6348782724 #> 5416 2056E 3M CC37 2017 2017-10-02 TURB 0.7419373447 #> 5417 2056E 3M CC37 2017 2017-11-06 CHLAC 1.6292405397 #> 5418 2056E 3M CC37 2017 2017-11-06 COLOR 3.8918202981 A #> 5419 2056E 3M CC37 2017 2017-11-06 DO 1.7595805709 #> 5420 2056E 3M CC37 2017 2017-11-06 DOSAT 4.3605476030 #> 5421 2056E 3M CC37 2017 2017-11-06 NO23 -3.7722610631 #> 5422 2056E 3M CC37 2017 2017-11-06 SALIN 2.9549102790 #> 5423 2056E 3M CC37 2017 2017-11-06 TKN -0.4620354596 #> 5424 2056E 3M CC37 2017 2017-11-06 TN -0.4261781497 + #> 5425 2056E 3M CC37 2017 2017-11-06 TP -1.4696759701 #> 5426 2056E 3M CC37 2017 2017-11-06 TURB 0.2623642645 #> 5427 2056E 3M CC37 2017 2017-12-04 CHLAC 1.6677068206 #> 5428 2056E 3M CC37 2017 2017-12-04 COLOR 3.4657359028 #> 5429 2056E 3M CC37 2017 2017-12-04 DO 1.5686159179 #> 5430 2056E 3M CC37 2017 2017-12-04 DOSAT 4.1541845626 #> 5431 2056E 3M CC37 2017 2017-12-04 NO23 -5.5214609179 U #> 5432 2056E 3M CC37 2017 2017-12-04 SALIN 3.0914968955 #> 5433 2056E 3M CC37 2017 2017-12-04 TKN -0.1743533871 #> 5434 2056E 3M CC37 2017 2017-12-04 TN -0.1719752647 + #> 5435 2056E 3M CC37 2017 2017-12-04 TP -1.2039728043 #> 5436 2056E 3M CC37 2017 2017-12-04 TURB 1.0647107370 #> 5437 2056E 3M CC37 2018 2018-01-02 CHLAC 2.8332133441 #> 5438 2056E 3M CC37 2018 2018-01-02 COLOR 3.2188758249 #> 5439 2056E 3M CC37 2018 2018-01-02 DO 1.7101878155 #> 5440 2056E 3M CC37 2018 2018-01-02 DOSAT 4.1789920363 + #> 5441 2056E 3M CC37 2018 2018-01-02 NO23 -5.2983173665 I #> 5442 2056E 3M CC37 2018 2018-01-02 SALIN 3.1045866785 #> 5443 2056E 3M CC37 2018 2018-01-02 TKN -0.1278333715 #> 5444 2056E 3M CC37 2018 2018-01-02 TN -0.1232982163 + #> 5445 2056E 3M CC37 2018 2018-01-02 TP -0.6348782724 #> 5446 2056E 3M CC37 2018 2018-01-02 TURB 1.5040773968 #> 5447 2056E 3M CC37 2018 2018-02-05 CHLAC 3.0445224377 #> 5448 2056E 3M CC37 2018 2018-02-05 COLOR 3.0910424534 #> 5449 2056E 3M CC37 2018 2018-02-05 DO 1.7227665977 #> 5450 2056E 3M CC37 2018 2018-02-05 DOSAT 4.3067641502 #> 5451 2056E 3M CC37 2018 2018-02-05 NO23 -4.1351665567 #> 5452 2056E 3M CC37 2018 2018-02-05 SALIN 3.1311369106 #> 5453 2056E 3M CC37 2018 2018-02-05 TKN -0.5108256238 #> 5454 2056E 3M CC37 2018 2018-02-05 TN -0.4845083154 + #> 5455 2056E 3M CC37 2018 2018-02-05 TP -2.0402208285 #> 5456 2056E 3M CC37 2018 2018-02-05 TURB 1.3609765531 #> 5457 2056E 3M CC37 2018 2018-03-05 CHLAC 1.9315214116 #> 5458 2056E 3M CC37 2018 2018-03-05 COLOR 3.1780538303 A #> 5459 2056E 3M CC37 2018 2018-03-05 DO 1.4973884086 #> 5460 2056E 3M CC37 2018 2018-03-05 DOSAT 4.0656020934 #> 5461 2056E 3M CC37 2018 2018-03-05 NO23 -5.2983173665 I #> 5462 2056E 3M CC37 2018 2018-03-05 SALIN 3.1540172525 #> 5463 2056E 3M CC37 2018 2018-03-05 TKN -0.2613647641 #> 5464 2056E 3M CC37 2018 2018-03-05 TN -0.2561834054 + #> 5465 2056E 3M CC37 2018 2018-03-05 TP -1.6607312068 #> 5466 2056E 3M CC37 2018 2018-03-05 TURB 1.3083328197 #> 5467 2056E 3M CC37 2018 2018-04-02 CHLAC 2.3978952728 #> 5468 2056E 3M CC37 2018 2018-04-02 COLOR 2.9444389792 A #> 5469 2056E 3M CC37 2018 2018-04-02 DO 1.3660916538 #> 5470 2056E 3M CC37 2018 2018-04-02 DOSAT 3.9963641539 #> 5471 2056E 3M CC37 2018 2018-04-02 NO23 -4.8283137373 I #> 5472 2056E 3M CC37 2018 2018-04-02 SALIN 3.2461018111 #> 5473 2056E 3M CC37 2018 2018-04-02 TKN -0.2613647641 #> 5474 2056E 3M CC37 2018 2018-04-02 TN -0.2561834054 + #> 5475 2056E 3M CC37 2018 2018-04-02 TP -1.6607312068 #> 5476 2056E 3M CC37 2018 2018-04-02 TURB 1.4109869737 A #> 5477 2056E 3M CC37 2018 2018-05-07 CHLAC 2.6390573296 #> 5478 2056E 3M CC37 2018 2018-05-07 COLOR 3.0445224377 #> 5479 2056E 3M CC37 2018 2018-05-07 DO 1.4011829736 #> 5480 2056E 3M CC37 2018 2018-05-07 DOSAT 4.0656020934 #> 5481 2056E 3M CC37 2018 2018-05-07 NO23 -5.2983173665 I #> 5482 2056E 3M CC37 2018 2018-05-07 SALIN 3.3225148596 #> 5483 2056E 3M CC37 2018 2018-05-07 TKN -0.0833816089 #> 5484 2056E 3M CC37 2018 2018-05-07 TN -0.0790432073 + #> 5485 2056E 3M CC37 2018 2018-05-07 TP -1.5606477483 #> 5486 2056E 3M CC37 2018 2018-05-07 TURB 1.5260563035 #> 5487 2056E 3M CC37 2018 2018-06-04 CHLAC 3.2958368660 #> 5488 2056E 3M CC37 2018 2018-06-04 COLOR 4.4773368145 #> 5489 2056E 3M CC37 2018 2018-06-04 DO 1.9286186519 #> 5490 2056E 3M CC37 2018 2018-06-04 DOSAT 4.5390303835 #> 5491 2056E 3M CC37 2018 2018-06-04 NO23 -4.0745419349 #> 5492 2056E 3M CC37 2018 2018-06-04 SALIN 1.9095425049 #> 5493 2056E 3M CC37 2018 2018-06-04 TKN 0.1823215568 #> 5494 2056E 3M CC37 2018 2018-06-04 TN 0.1963888140 + #> 5495 2056E 3M CC37 2018 2018-06-04 TP -0.9942522733 #> 5496 2056E 3M CC37 2018 2018-06-04 TURB 1.3862943611 #> 5497 2056E 3M CC37 2018 2018-07-09 CHLAC 2.6390573296 #> 5498 2056E 3M CC37 2018 2018-07-09 COLOR 4.8675344505 #> 5499 2056E 3M CC37 2018 2018-07-09 DO 1.2919836816 #> 5500 2056E 3M CC37 2018 2018-07-09 DOSAT 3.7977338590 #> 5501 2056E 3M CC37 2018 2018-07-09 NO23 -2.6310891600 #> 5502 2056E 3M CC37 2018 2018-07-09 SALIN 1.8148247422 #> 5503 2056E 3M CC37 2018 2018-07-09 TKN 0.1823215568 #> 5504 2056E 3M CC37 2018 2018-07-09 TN 0.2405904649 + #> 5505 2056E 3M CC37 2018 2018-07-09 TP -0.8675005677 #> 5506 2056E 3M CC37 2018 2018-07-09 TURB 0.6931471806 A #> 5507 2056E 3M CC37 2018 2018-08-06 CHLAC 1.8562979904 #> 5508 2056E 3M CC37 2018 2018-08-06 COLOR 4.8675344505 #> 5509 2056E 3M CC37 2018 2018-08-06 DO 1.3428648032 #> 5510 2056E 3M CC37 2018 2018-08-06 DOSAT 3.9435216725 #> 5511 2056E 3M CC37 2018 2018-08-06 NO23 -1.8325814637 #> 5512 2056E 3M CC37 2018 2018-08-06 SALIN 1.1281710909 #> 5513 2056E 3M CC37 2018 2018-08-06 TKN 0.0953101798 #> 5514 2056E 3M CC37 2018 2018-08-06 TN 0.2311117210 + #> 5515 2056E 3M CC37 2018 2018-08-06 TP -0.8209805521 #> 5516 2056E 3M CC37 2018 2018-08-06 TURB 0.5877866649 #> 5517 2056E 3M CC37 2019 2019-02-04 CHLAC 1.9878743482 A #> 5518 2056E 3M CC37 2019 2019-02-04 COLOR 3.3322045102 #> 5519 2056E 3M CC37 2019 2019-02-04 DO 2.0438143640 #> 5520 2056E 3M CC37 2019 2019-02-04 DOSAT 4.5622626850 #> 5521 2056E 3M CC37 2019 2019-02-04 NO23 -5.2983173665 I #> 5522 2056E 3M CC37 2019 2019-02-04 SALIN 2.7447035188 #> 5523 2056E 3M CC37 2019 2019-02-04 TKN -0.4780358009 #> 5524 2056E 3M CC37 2019 2019-02-04 TN -0.4716049106 + #> 5525 2056E 3M CC37 2019 2019-02-04 TP -1.7147984281 #> 5526 2056E 3M CC37 2019 2019-02-04 TURB 0.7884573604 #> 5527 2056E 3M CC37 2019 2019-05-06 CHLAC 2.3978952728 #> 5528 2056E 3M CC37 2019 2019-05-06 COLOR 3.1780538303 A #> 5529 2056E 3M CC37 2019 2019-05-06 DO 1.3110318766 #> 5530 2056E 3M CC37 2019 2019-05-06 DOSAT 3.9759363312 #> 5531 2056E 3M CC37 2019 2019-05-06 NO23 -5.5214609179 U #> 5532 2056E 3M CC37 2019 2019-05-06 SALIN 3.0320642028 #> 5533 2056E 3M CC37 2019 2019-05-06 TN -0.2331938872 + #> 5534 2056E 3M CC37 2019 2019-05-06 TP -1.4696759701 #> 5535 2056E 3M CC37 2019 2019-05-06 TURB 1.3350010667 #> 5536 2056E 3M CC37 2019 2019-06-03 CHLAC 2.0281482473 #> 5537 2056E 3M CC37 2019 2019-06-03 COLOR 3.2188758249 A #> 5538 2056E 3M CC37 2019 2019-06-03 DO 1.2864740258 #> 5539 2056E 3M CC37 2019 2019-06-03 DOSAT 3.9815490681 #> 5540 2056E 3M CC37 2019 2019-06-03 NO23 -5.5214609179 U #> 5541 2056E 3M CC37 2019 2019-06-03 SALIN 2.9982291538 #> 5542 2056E 3M CC37 2019 2019-06-03 TKN -0.0512932944 #> 5543 2056E 3M CC37 2019 2019-06-03 TN -0.0491902442 + #> 5544 2056E 3M CC37 2019 2019-06-03 TP -0.9416085399 #> 5545 2056E 3M CC37 2019 2019-06-03 TURB 0.8754687374 #> 5546 2056E 3M CC37 2019 2019-07-01 CHLAC 3.1354942159 #> 5547 2056E 3M CC37 2019 2019-07-01 COLOR 3.5553480615 A #> 5548 2056E 3M CC37 2019 2019-07-01 DO 0.6259384309 #> 5549 2056E 3M CC37 2019 2019-07-01 DOSAT 3.1441522787 #> 5550 2056E 3M CC37 2019 2019-07-01 NO23 -5.5214609179 I #> 5551 2056E 3M CC37 2019 2019-07-01 SALIN 2.7825390531 #> 5552 2056E 3M CC37 2019 2019-07-01 TKN -0.1278333715 #> 5553 2056E 3M CC37 2019 2019-07-01 TN -0.1232982163 + #> 5554 2056E 3M CC37 2019 2019-07-01 TP -0.5798184953 #> 5555 2056E 3M CC37 2019 2019-07-01 TURB 1.0296194172 #> 5556 2056E 3M CC37 2019 2019-08-05 CHLAC 3.1354942159 #> 5557 2056E 3M CC37 2019 2019-08-05 COLOR 4.2341065046 A #> 5558 2056E 3M CC37 2019 2019-08-05 DO 1.9685099810 #> 5559 2056E 3M CC37 2019 2019-08-05 DOSAT 4.5880240272 #> 5560 2056E 3M CC37 2019 2019-08-05 NO23 -4.9618451299 I #> 5561 2056E 3M CC37 2019 2019-08-05 SALIN 2.0744289999 #> 5562 2056E 3M CC37 2019 2019-08-05 TKN -0.1053605157 #> 5563 2056E 3M CC37 2019 2019-08-05 TN -0.1009259186 + #> 5564 2056E 3M CC37 2019 2019-08-05 TP -1.1086626245 #> 5565 2056E 3M CC37 2019 2019-08-05 TURB 1.1314021115 #> 5566 2056E 3M CC37 2019 2019-10-07 CHLAC 2.0794415417 #> 5567 2056E 3M CC37 2019 2019-10-07 COLOR 3.7376696183 A #> 5568 2056E 3M CC37 2019 2019-10-07 DO 1.4036429995 #> 5569 2056E 3M CC37 2019 2019-10-07 DOSAT 4.0910056610 #> 5570 2056E 3M CC37 2019 2019-10-07 NO23 -5.5214609179 U #> 5571 2056E 3M CC37 2019 2019-10-07 SALIN 3.0842009215 #> 5572 2056E 3M CC37 2019 2019-10-07 TKN -0.3566749439 #> 5573 2056E 3M CC37 2019 2019-10-07 TN -0.3538218750 + #> 5574 2056E 3M CC37 2019 2019-10-07 TP -1.6607312068 #> 5575 2056E 3M CC37 2019 2019-10-07 TURB 0.4054651081 #> 5576 2056E 3M CC37 2019 2019-10-07 CHLAC 1.3609765531 #> 5577 2056E 3M CC37 2019 2019-10-07 COLOR 3.7612001157 A #> 5578 2056E 3M CC37 2019 2019-10-07 NO23 -5.5214609179 U #> 5579 2056E 3M CC37 2019 2019-10-07 TKN -0.3011050928 #> 5580 2056E 3M CC37 2019 2019-10-07 TN -0.2984060358 + #> 5581 2056E 3M CC37 2019 2019-10-07 TP -1.7147984281 #> 5582 2056E 3M CC37 2019 2019-10-07 TURB 0.4700036292 #> 5583 2056E 3M CC37 2019 2019-11-04 CHLAC 1.1939224685 #> 5584 2056E 3M CC37 2019 2019-11-04 COLOR 3.5835189385 #> 5585 2056E 3M CC37 2019 2019-11-04 DO 1.6034198401 #> 5586 2056E 3M CC37 2019 2019-11-04 DOSAT 4.2470656492 #> 5587 2056E 3M CC37 2019 2019-11-04 NO23 -4.4228486292 #> 5588 2056E 3M CC37 2019 2019-11-04 SALIN 2.9922261342 #> 5589 2056E 3M CC37 2019 2019-11-04 TKN -0.3285040670 #> 5590 2056E 3M CC37 2019 2019-11-04 TN -0.3119747650 + #> 5591 2056E 3M CC37 2019 2019-11-04 TP -1.4271163556 #> 5592 2056E 3M CC37 2019 2019-11-04 TURB 0.0000000000 #> 5593 2056E 3M CC37 2019 2019-12-02 CHLAC 1.8245492921 A #> 5594 2056E 3M CC37 2019 2019-12-02 COLOR 3.3322045102 #> 5595 2056E 3M CC37 2019 2019-12-02 DO 1.3532545070 #> 5596 2056E 3M CC37 2019 2019-12-02 DOSAT 3.9740583963 #> 5597 2056E 3M CC37 2019 2019-12-02 NO23 -5.2983173665 I #> 5598 2056E 3M CC37 2019 2019-12-02 SALIN 3.1363634033 #> 5599 2056E 3M CC37 2019 2019-12-02 TKN -0.4942963218 #> 5600 2056E 3M CC37 2019 2019-12-02 TN -0.4877603508 + #> 5601 2056E 3M CC37 2019 2019-12-02 TP -1.8325814637 #> 5602 2056E 3M CC37 2019 2019-12-02 TURB 0.7884573604 #> 5603 2056E 3M CC37 2020 2020-01-06 CHLAC 2.7080502011 #> 5604 2056E 3M CC37 2020 2020-01-06 COLOR 3.1354942159 A #> 5605 2056E 3M CC37 2020 2020-01-06 DO 2.0055258587 #> 5606 2056E 3M CC37 2020 2020-01-06 DOSAT 4.5347477217 #> 5607 2056E 3M CC37 2020 2020-01-06 NO23 -4.7105307016 I #> 5608 2056E 3M CC37 2020 2020-01-06 SALIN 3.0387917630 #> 5609 2056E 3M CC37 2020 2020-01-06 TKN -0.3710636814 #> 5610 2056E 3M CC37 2020 2020-01-06 TN -0.3652833185 + #> 5611 2056E 3M CC37 2020 2020-01-06 TP -1.6607312068 #> 5612 2056E 3M CC37 2020 2020-01-06 TURB 1.0647107370 #> 5613 2056E 3M CC37 2020 2020-02-03 CHLAC 2.5649493575 #> 5614 2056E 3M CC37 2020 2020-02-03 COLOR 2.9957322736 #> 5615 2056E 3M CC37 2020 2020-02-03 DO 1.8148247422 #> 5616 2056E 3M CC37 2020 2020-02-03 DOSAT 4.2808241292 #> 5617 2056E 3M CC37 2020 2020-02-03 NO23 -4.3428059215 #> 5618 2056E 3M CC37 2020 2020-02-03 SALIN 3.1175073305 #> 5619 2056E 3M CC37 2020 2020-02-03 TKN -0.3856624808 #> 5620 2056E 3M CC37 2020 2020-02-03 TN -0.3667252798 + #> 5621 2056E 3M CC37 2020 2020-02-03 TP -1.9661128564 #> 5622 2056E 3M CC37 2020 2020-02-03 TURB 1.4109869737 A #> 5623 2056E 3M CC37 2020 2020-03-02 CHLAC 1.9740810260 #> 5624 2056E 3M CC37 2020 2020-03-02 COLOR 2.8903717579 #> 5625 2056E 3M CC37 2020 2020-03-02 DO 1.8484548129 #> 5626 2056E 3M CC37 2020 2020-03-02 DOSAT 4.3832758541 #> 5627 2056E 3M CC37 2020 2020-03-02 NO23 -5.2983173665 I #> 5628 2056E 3M CC37 2020 2020-03-02 SALIN 3.1320098918 #> 5629 2056E 3M CC37 2020 2020-03-02 TKN -0.4004775666 #> 5630 2056E 3M CC37 2020 2020-03-02 TN -0.3945251681 + #> 5631 2056E 3M CC37 2020 2020-03-02 TP -1.9661128564 #> 5632 2056E 3M CC37 2020 2020-03-02 TURB 1.2809338455 A #> 5633 2056E 3M CC37 2020 2020-09-08 CHLAC 1.6486586256 #> 5634 2056E 3M CC37 2020 2020-09-08 COLOR 4.4998096703 #> 5635 2056E 3M CC37 2020 2020-09-08 DO 0.8837675402 #> 5636 2056E 3M CC37 2020 2020-09-08 DOSAT 3.5085559000 #> 5637 2056E 3M CC37 2020 2020-09-08 NO23 -3.1465551633 #> 5638 2056E 3M CC37 2020 2020-09-08 SALIN 2.2428350886 #> 5639 2056E 3M CC37 2020 2020-09-08 TKN -0.1743533871 #> 5640 2056E 3M CC37 2020 2020-09-08 TN -0.1244300784 + #> 5641 2056E 3M CC37 2020 2020-09-08 TP -0.9162907319 #> 5642 2056E 3M CC37 2020 2020-09-08 TURB 0.4700036292 #> 5643 2056E 3M CC37 2020 2020-10-05 CHLAC 1.7047480922 #> 5644 2056E 3M CC37 2020 2020-10-05 COLOR 4.5951198501 A #> 5645 2056E 3M CC37 2020 2020-10-05 DO 0.8837675402 #> 5646 2056E 3M CC37 2020 2020-10-05 DOSAT 3.4657359028 #> 5647 2056E 3M CC37 2020 2020-10-05 NO23 -3.2701691193 #> 5648 2056E 3M CC37 2020 2020-10-05 SALIN 2.6181254936 #> 5649 2056E 3M CC37 2020 2020-10-05 TKN 0.1823215568 #> 5650 2056E 3M CC37 2020 2020-10-05 TN 0.2134971743 + #> 5651 2056E 3M CC37 2020 2020-10-05 TP -0.7765287895 #> 5652 2056E 3M CC37 2020 2020-10-05 TURB 0.3364722366 #> 5653 2056E 3M CC37 2020 2020-10-05 CHLAC 1.8718021769 #> 5654 2056E 3M CC37 2020 2020-10-05 COLOR 4.6051701860 #> 5655 2056E 3M CC37 2020 2020-10-05 NO23 -3.5404594490 #> 5656 2056E 3M CC37 2020 2020-10-05 TKN 0.1823215568 #> 5657 2056E 3M CC37 2020 2020-10-05 TN 0.2062008306 + #> 5658 2056E 3M CC37 2020 2020-10-05 TP -0.7550225843 #> 5659 2056E 3M CC37 2020 2020-10-05 TURB 0.2623642645 #> 5660 2056E 3M CC37 2020 2020-11-02 CHLAC 2.1400661635 #> 5661 2056E 3M CC37 2020 2020-11-02 COLOR 4.2046926194 #> 5662 2056E 3M CC37 2020 2020-11-02 DO 1.8468787684 #> 5663 2056E 3M CC37 2020 2020-11-02 DOSAT 4.4670568839 #> 5664 2056E 3M CC37 2020 2020-11-02 NO23 -3.2968373663 #> 5665 2056E 3M CC37 2020 2020-11-02 SALIN 2.6525374912 #> 5666 2056E 3M CC37 2020 2020-11-02 TKN -0.3147107448 #> 5667 2056E 3M CC37 2020 2020-11-02 TN -0.2652684776 + #> 5668 2056E 3M CC37 2020 2020-11-02 TP -1.3093333200 #> 5669 2056E 3M CC37 2020 2020-11-02 TURB 0.6931471806 A #> 5670 2056E 3M CC37 2020 2020-12-07 CHLAC 1.6677068206 #> 5671 2056E 3M CC37 2020 2020-12-07 COLOR 3.8712010109 #> 5672 2056E 3M CC37 2020 2020-12-07 DO 1.9050881545 #> 5673 2056E 3M CC37 2020 2020-12-07 DOSAT 4.4164280614 #> 5674 2056E 3M CC37 2020 2020-12-07 NO23 -3.9633162998 #> 5675 2056E 3M CC37 2020 2020-12-07 SALIN 2.8735646396 #> 5676 2056E 3M CC37 2020 2020-12-07 TKN -0.4942963218 #> 5677 2056E 3M CC37 2020 2020-12-07 TN -0.4636240223 + #> 5678 2056E 3M CC37 2020 2020-12-07 TP -1.8325814637 #> 5679 2056E 3M CC37 2020 2020-12-07 TURB 0.1823215568 #> 5680 2056E 3M CC37 2021 2021-01-04 CHLAC 0.8754687374 I #> 5681 2056E 3M CC37 2021 2021-01-04 COLOR 3.5835189385 #> 5682 2056E 3M CC37 2021 2021-01-04 DO 1.4279160358 #> 5683 2056E 3M CC37 2021 2021-01-04 DOSAT 3.9569963711 #> 5684 2056E 3M CC37 2021 2021-01-04 NO23 -4.1351665567 #> 5685 2056E 3M CC37 2021 2021-01-04 SALIN 2.8249439526 #> 5686 2056E 3M CC37 2021 2021-01-04 TKN -0.3285040670 #> 5687 2056E 3M CC37 2021 2021-01-04 TN -0.3065251603 + #> 5688 2056E 3M CC37 2021 2021-01-04 TP -1.8971199849 #> 5689 2056E 3M CC37 2021 2021-01-04 TURB 0.6418538862 #> 5690 2056E 3M CC37 2021 2021-02-01 CHLAC 1.0986122887 #> 5691 2056E 3M CC37 2021 2021-02-01 COLOR 3.2958368660 A #> 5692 2056E 3M CC37 2021 2021-02-01 DO 2.0464016876 #> 5693 2056E 3M CC37 2021 2021-02-01 DOSAT 4.5767707115 #> 5694 2056E 3M CC37 2021 2021-02-01 NO23 -5.1159958098 I #> 5695 2056E 3M CC37 2021 2021-02-01 SALIN 2.9957322736 #> 5696 2056E 3M CC37 2021 2021-02-01 TKN -0.5108256238 #> 5697 2056E 3M CC37 2021 2021-02-01 TN -0.5041810810 + #> 5698 2056E 3M CC37 2021 2021-02-01 TP -2.1202635362 #> 5699 2056E 3M CC37 2021 2021-02-01 TURB 0.6418538862 #> 5700 2056E 3M CC37 2021 2021-03-01 CHLAC 1.5260563035 #> 5701 2056E 3M CC37 2021 2021-03-01 COLOR 3.2580965380 A #> 5702 2056E 3M CC37 2021 2021-03-01 DO 1.4134230285 #> 5703 2056E 3M CC37 2021 2021-03-01 DOSAT 4.0412953411 #> 5704 2056E 3M CC37 2021 2021-03-01 NO23 -5.1159958098 I #> 5705 2056E 3M CC37 2021 2021-03-01 SALIN 3.0445224377 #> 5706 2056E 3M CC37 2021 2021-03-01 TKN -0.6161861394 #> 5707 2056E 3M CC37 2021 2021-03-01 TN -0.6088060321 + #> 5708 2056E 3M CC37 2021 2021-03-01 TP -1.9661128564 #> 5709 2056E 3M CC37 2021 2021-03-01 TURB 1.1314021115 A #> 5710 2056E 3M CC37 2021 2021-04-05 CHLAC 1.7917594692 #> 5711 2056E 3M CC37 2021 2021-04-05 COLOR 3.1354942159 #> 5712 2056E 3M CC37 2021 2021-04-05 DO 1.5040773968 #> 5713 2056E 3M CC37 2021 2021-04-05 DOSAT 4.0604430105 #> 5714 2056E 3M CC37 2021 2021-04-05 NO23 -4.5098600062 #> 5715 2056E 3M CC37 2021 2021-04-05 SALIN 3.1599747169 #> 5716 2056E 3M CC37 2021 2021-04-05 TKN -0.1984509387 #> 5717 2056E 3M CC37 2021 2021-04-05 TN -0.1851254841 + #> 5718 2056E 3M CC37 2021 2021-04-05 TP -1.7719568419 #> 5719 2056E 3M CC37 2021 2021-04-05 TURB 1.7047480922 #> 5720 2056E 3M CC37 2021 2021-05-03 CHLAC 2.0149030205 #> 5721 2056E 3M CC37 2021 2021-05-03 COLOR 3.1354942159 #> 5722 2056E 3M CC37 2021 2021-05-03 DO 1.1314021115 #> 5723 2056E 3M CC37 2021 2021-05-03 DOSAT 3.8286413965 #> 5724 2056E 3M CC37 2021 2021-05-03 NO23 -4.8283137373 I #> 5725 2056E 3M CC37 2021 2021-05-03 SALIN 3.2196755050 #> 5726 2056E 3M CC37 2021 2021-05-03 TKN -0.3011050928 #> 5727 2056E 3M CC37 2021 2021-05-03 TN -0.2957142441 + #> 5728 2056E 3M CC37 2021 2021-05-03 TP -1.4696759701 #> 5729 2056E 3M CC37 2021 2021-05-03 TURB 1.5260563035 #> 5730 2056E 3M CC37 2021 2021-06-07 CHLAC 2.2617630985 #> 5731 2056E 3M CC37 2021 2021-06-07 COLOR 2.8903717579 #> 5732 2056E 3M CC37 2021 2021-06-07 DO 1.1314021115 #> 5733 2056E 3M CC37 2021 2021-06-07 DOSAT 3.8286413965 #> 5734 2056E 3M CC37 2021 2021-06-07 NO23 -5.5214609179 U #> 5735 2056E 3M CC37 2021 2021-06-07 SALIN 3.2196755050 #> 5736 2056E 3M CC37 2021 2021-06-07 TKN 0.0953101798 #> 5737 2056E 3M CC37 2021 2021-06-07 TN 0.0971267107 + #> 5738 2056E 3M CC37 2021 2021-06-07 TP -1.3093333200 #> 5739 2056E 3M CC37 2021 2021-06-07 TURB 1.2809338455 #> 5740 2056E 3M CC37 2021 2021-08-02 CHLAC 2.7080502011 #> 5741 2056E 3M CC37 2021 2021-08-02 COLOR 4.5217885770 #> 5742 2056E 3M CC37 2021 2021-08-02 DO 1.6034198401 #> 5743 2056E 3M CC37 2021 2021-08-02 DOSAT 4.2766661190 #> 5744 2056E 3M CC37 2021 2021-08-02 NO23 -5.5214609179 U #> 5745 2056E 3M CC37 2021 2021-08-02 SALIN 2.1871742415 #> 5746 2056E 3M CC37 2021 2021-08-02 TKN -0.1053605157 #> 5747 2056E 3M CC37 2021 2021-08-02 TN -0.1031407589 + #> 5748 2056E 3M CC37 2021 2021-08-02 TP -0.6733445533 #> 5749 2056E 3M CC37 2021 2021-08-02 TURB 0.8754687374 #> 5750 2056E 3M CC37 2021 2021-09-07 CHLAC 1.8405496334 #> 5751 2056E 3M CC37 2021 2021-09-07 COLOR 4.2341065046 #> 5752 2056E 3M CC37 2021 2021-09-07 DO 1.5260563035 #> 5753 2056E 3M CC37 2021 2021-09-07 DOSAT 4.1447207695 #> 5754 2056E 3M CC37 2021 2021-09-07 NO23 -3.6119184130 #> 5755 2056E 3M CC37 2021 2021-09-07 SALIN 2.0041790572 #> 5756 2056E 3M CC37 2021 2021-09-07 TKN -0.0943106795 #> 5757 2056E 3M CC37 2021 2021-09-07 TN -0.0650719967 + #> 5758 2056E 3M CC37 2021 2021-09-07 TP -1.0788096614 #> 5759 2056E 3M CC37 2021 2021-09-07 TURB 0.5306282511 A #> 5760 2056E 3M CC37 2021 2021-10-04 CHLAC 2.4849066498 #> 5761 2056E 3M CC37 2021 2021-10-04 COLOR 4.5643481915 A #> 5762 2056E 3M CC37 2021 2021-10-04 DO 0.4446858213 #> 5763 2056E 3M CC37 2021 2021-10-04 DOSAT 3.0587070727 #> 5764 2056E 3M CC37 2021 2021-10-04 NO23 -3.0576076773 #> 5765 2056E 3M CC37 2021 2021-10-04 SALIN 2.4932054526 #> 5766 2056E 3M CC37 2021 2021-10-04 TKN 0.0953101798 #> 5767 2056E 3M CC37 2021 2021-10-04 TN 0.1371498381 + #> 5768 2056E 3M CC37 2021 2021-10-04 TP -0.7985076962 #> 5769 2056E 3M CC37 2021 2021-10-04 TURB 0.4054651081 #> 5770 2056E 3M CC37 2021 2021-10-04 CHLAC 2.3978952728 A #> 5771 2056E 3M CC37 2021 2021-10-04 COLOR 4.5849674787 #> 5772 2056E 3M CC37 2021 2021-10-04 NO23 -3.0576076773 #> 5773 2056E 3M CC37 2021 2021-10-04 TKN 0.0000000000 #> 5774 2056E 3M CC37 2021 2021-10-04 TN 0.0459289319 + #> 5775 2056E 3M CC37 2021 2021-10-04 TP -0.8209805521 #> 5776 2056E 3M CC37 2021 2021-10-04 TURB 0.4700036292 #> 5777 2056E 3M CC37 2021 2021-11-01 CHLAC 1.7749523509 #> 5778 2056E 3M CC37 2021 2021-11-01 COLOR 3.7612001157 A #> 5779 2056E 3M CC37 2021 2021-11-01 DO 1.2325602612 #> 5780 2056E 3M CC37 2021 2021-11-01 DOSAT 3.8177123260 #> 5781 2056E 3M CC37 2021 2021-11-01 NO23 -3.5065578973 #> 5782 2056E 3M CC37 2021 2021-11-01 SALIN 2.9444389792 #> 5783 2056E 3M CC37 2021 2021-11-01 TKN -0.2231435513 #> 5784 2056E 3M CC37 2021 2021-11-01 TN -0.1863295782 + #> 5785 2056E 3M CC37 2021 2021-11-01 TP -1.6094379124 #> 5786 2056E 3M CC37 2021 2021-11-01 TURB 0.2623642645 #> 5787 2056E 3M CC37 2021 2021-12-06 CHLAC 1.7578579176 #> 5788 2056E 3M CC37 2021 2021-12-06 COLOR 3.0445224377 #> 5789 2056E 3M CC37 2021 2021-12-06 DO 1.5260563035 #> 5790 2056E 3M CC37 2021 2021-12-06 DOSAT 4.1157798429 #> 5791 2056E 3M CC37 2021 2021-12-06 NO23 -4.7105307016 I #> 5792 2056E 3M CC37 2021 2021-12-06 SALIN 3.1471649773 #> 5793 2056E 3M CC37 2021 2021-12-06 TKN -0.5978370008 #> 5794 2056E 3M CC37 2021 2021-12-06 TN -0.5905905922 + #> 5795 2056E 3M CC37 2021 2021-12-06 TP -2.1202635362 #> 5796 2056E 3M CC37 2021 2021-12-06 TURB 0.4700036292 #> 5797 2056E 3M CC37 2022 2022-01-03 CHLAC 2.1162555148 #> 5798 2056E 3M CC37 2022 2022-01-03 COLOR 2.8903717579 #> 5799 2056E 3M CC37 2022 2022-01-03 DO 1.2974631474 #> 5800 2056E 3M CC37 2022 2022-01-03 DOSAT 3.9160150267 #> 5801 2056E 3M CC37 2022 2022-01-03 NO23 -4.9618451299 I #> 5802 2056E 3M CC37 2022 2022-01-03 SALIN 3.1289511173 #> 5803 2056E 3M CC37 2022 2022-01-03 TKN -0.4780358009 #> 5804 2056E 3M CC37 2022 2022-01-03 TN -0.4716049106 + #> 5805 2056E 3M CC37 2022 2022-01-03 TP -1.9661128564 #> 5806 2056E 3M CC37 2022 2022-01-03 TURB 1.2809338455 A #> 5807 2056E 3M CC37 2022 2022-02-07 CHLAC 2.0918640617 #> 5808 2056E 3M CC37 2022 2022-02-07 COLOR 2.6390573296 #> 5809 2056E 3M CC37 2022 2022-02-07 DO 1.5518087996 #> 5810 2056E 3M CC37 2022 2022-02-07 DOSAT 4.1075897890 #> 5811 2056E 3M CC37 2022 2022-02-07 NO23 -4.1351665567 #> 5812 2056E 3M CC37 2022 2022-02-07 SALIN 3.2323841749 #> 5813 2056E 3M CC37 2022 2022-02-07 TKN -0.2484613593 #> 5814 2056E 3M CC37 2022 2022-02-07 TN -0.2281560931 + #> 5815 2056E 3M CC37 2022 2022-02-07 TP -2.1202635362 #> 5816 2056E 3M CC37 2022 2022-02-07 TURB 0.5877866649 #> 5817 2056E 3M CC37 2022 2022-03-07 CHLAC 1.3350010667 #> 5818 2056E 3M CC37 2022 2022-03-07 COLOR 2.3978952728 #> 5819 2056E 3M CC37 2022 2022-03-07 DO 1.5769147207 #> 5820 2056E 3M CC37 2022 2022-03-07 DOSAT 4.2150861799 #> 5821 2056E 3M CC37 2022 2022-03-07 NO23 -5.5214609179 I #> 5822 2056E 3M CC37 2022 2022-03-07 SALIN 3.2820383998 #> 5823 2056E 3M CC37 2022 2022-03-07 TKN -0.4004775666 #> 5824 2056E 3M CC37 2022 2022-03-07 TN -0.3945251681 + #> 5825 2056E 3M CC37 2022 2022-03-07 TP -2.0402208285 #> 5826 2056E 3M CC37 2022 2022-03-07 TURB 1.0647107370 #> 5827 2056E 3M CC37 2022 2022-04-04 CHLAC 1.6863989536 #> 5828 2056E 3M CC37 2022 2022-04-04 COLOR 2.5649493575 #> 5829 2056E 3M CC37 2022 2022-04-04 DO 1.4816045409 #> 5830 2056E 3M CC37 2022 2022-04-04 DOSAT 4.1319614258 #> 5831 2056E 3M CC37 2022 2022-04-04 NO23 -4.5098600062 #> 5832 2056E 3M CC37 2022 2022-04-04 SALIN 3.3311325072 #> 5833 2056E 3M CC37 2022 2022-04-04 TN -0.6520052372 + #> 5834 2056E 3M CC37 2022 2022-04-04 TP -1.7719568419 #> 5835 2056E 3M CC37 2022 2022-04-04 TURB 1.1631508098 #> 5836 2056E 3M CC37 2022 2022-05-02 CHLAC 1.5892352051 #> 5837 2056E 3M CC37 2022 2022-05-02 COLOR 2.7080502011 #> 5838 2056E 3M CC37 2022 2022-05-02 DO 1.3660916538 #> 5839 2056E 3M CC37 2022 2022-05-02 DOSAT 4.0500443033 #> 5840 2056E 3M CC37 2022 2022-05-02 NO23 -5.2983173665 I #> 5841 2056E 3M CC37 2022 2022-05-02 SALIN 3.3755376349 #> 5842 2056E 3M CC37 2022 2022-05-02 TKN -0.2744368457 #> 5843 2056E 3M CC37 2022 2022-05-02 TN -0.2691874898 + #> 5844 2056E 3M CC37 2022 2022-05-02 TP -1.6094379124 #> 5845 2056E 3M CC37 2022 2022-05-02 TURB 1.2527629685 A #> 5846 2056E 3M CC42 2019 2019-10-10 CHLAC 1.5892352051 #> 5847 2056E 3M CC42 2019 2019-10-10 COND 9.8078573215 #> 5848 2056E 3M CC42 2019 2019-10-10 NO23 -3.7722610631 #> 5849 2056E 3M CC42 2019 2019-10-10 SALIN 2.3721111556 #> 5850 2056E 3M CC42 2019 2019-10-10 TKN -0.3566749439 #> 5851 2056E 3M CC42 2019 2019-10-10 TN -0.3243460568 + #> 5852 2056E 3M CC42 2019 2019-10-10 TP -1.0498221245 #> 5853 2056E 3M CC42 2019 2019-10-10 TSS 1.7917594692 I #> 5854 2056E 3M CC42 2019 2019-10-10 TURB 1.0647107370 #> 5855 2056C2 3M CC45 2014 2014-06-10 COND 9.8892364868 #> 5856 2056C2 3M CC45 2014 2014-06-10 DO 1.9344157696 #> 5857 2056C2 3M CC45 2014 2014-06-10 DOSAT 4.5920849464 + #> 5858 2056C2 3M CC45 2014 2014-06-10 SALIN 2.4595888418 #> 5859 2056C2 3M CC45 2014 2014-06-10 NO23 -5.5214609179 U #> 5860 2056C2 3M CC45 2014 2014-06-10 TKN 1.2809338455 #> 5861 2056C2 3M CC45 2014 2014-06-10 TN 1.2809338455 #> 5862 2056C2 3M CC45 2014 2014-06-10 TSS 2.3513752572 #> 5863 2056C2 3M CC45 2014 2014-06-10 COND 9.8874597915 #> 5864 2056C2 3M CC45 2014 2014-06-10 DO 2.0014800002 #> 5865 2056C2 3M CC45 2014 2014-06-10 DOSAT 4.6587109529 + #> 5866 2056C2 3M CC45 2014 2014-06-10 SALIN 2.4587337755 #> 5867 2056C2 3M CC45 2014 2014-06-10 COND 9.9269599087 #> 5868 2056C2 3M CC45 2014 2014-06-10 DO 1.9933388426 #> 5869 2056C2 3M CC45 2014 2014-06-10 DOSAT 4.6510991179 + #> 5870 2056C2 3M CC45 2014 2014-06-10 SALIN 2.5014359517 #> 5871 2056C2 3M CC45 2014 2014-06-10 COND 9.9782238987 #> 5872 2056C2 3M CC45 2014 2014-06-10 DO 1.8916048042 #> 5873 2056C2 3M CC45 2014 2014-06-10 DOSAT 4.5475410732 + #> 5874 2056C2 3M CC45 2014 2014-06-10 SALIN 2.5572273114 #> 5875 2056C2 3M CC45 2014 2014-06-10 COND 10.0037852739 #> 5876 2056C2 3M CC45 2014 2014-06-10 DO 1.8017098001 #> 5877 2056C2 3M CC45 2014 2014-06-10 DOSAT 4.4578295981 + #> 5878 2056C2 3M CC45 2014 2014-06-10 SALIN 2.5862591440 #> 5879 2056C2 3M CC45 2014 2014-06-10 COND 10.0950165901 #> 5880 2056C2 3M CC45 2014 2014-06-10 DO 1.5475625087 #> 5881 2056C2 3M CC45 2014 2014-06-10 DOSAT 4.2061840440 + #> 5882 2056C2 3M CC45 2014 2014-06-10 SALIN 2.6932749155 #> 5883 2056C2 3M CC45 2014 2014-06-10 COND 10.1085078656 #> 5884 2056C2 3M CC45 2014 2014-06-10 DO 1.4562867329 #> 5885 2056C2 3M CC45 2014 2014-06-10 DOSAT 4.1141471895 + #> 5886 2056C2 3M CC45 2014 2014-06-10 SALIN 2.6932749155 #> 5887 2056C2 3M CC45 2014 2014-06-10 COND 10.1103391071 #> 5888 2056C2 3M CC45 2014 2014-06-10 DO 1.4182774070 #> 5889 2056C2 3M CC45 2014 2014-06-10 DOSAT 4.0775374439 + #> 5890 2056C2 3M CC45 2014 2014-06-10 SALIN 2.7020321288 #> 5891 2056C2 3M CC45 2014 2014-06-10 COND 10.1112331617 #> 5892 2056C2 3M CC45 2014 2014-06-10 DO 1.4109869737 #> 5893 2056C2 3M CC45 2014 2014-06-10 DOSAT 4.0690267542 + #> 5894 2056C2 3M CC45 2014 2014-06-10 SALIN 2.7027025948 #> 5895 2056C2 3M CC45 2014 2014-06-10 COND 10.1134242764 #> 5896 2056C2 3M CC45 2014 2014-06-10 DO 1.3787660947 #> 5897 2056C2 3M CC45 2014 2014-06-10 DOSAT 4.0377742107 + #> 5898 2056C2 3M CC45 2014 2014-06-10 SALIN 2.7053799725 #> 5899 2056C2 3M CC45 2014 2014-07-10 COND 9.9863570304 #> 5900 2056C2 3M CC45 2014 2014-07-10 DO 2.9204697891 #> 5901 2056C2 3M CC45 2014 2014-07-10 DOSAT 5.6028565561 + #> 5902 2056C2 3M CC45 2014 2014-07-10 SALIN 2.5664866368 #> 5903 2056C2 3M CC45 2014 2014-07-10 NO23 -4.1351665567 I #> 5904 2056C2 3M CC45 2014 2014-07-10 TKN 0.5933268453 #> 5905 2056C2 3M CC45 2014 2014-07-10 TN 0.5988365011 #> 5906 2056C2 3M CC45 2014 2014-07-10 TSS 2.6602595373 #> 5907 2056C2 3M CC45 2014 2014-07-10 COND 10.2631181243 #> 5908 2056C2 3M CC45 2014 2014-07-10 DO 2.5136560631 #> 5909 2056C2 3M CC45 2014 2014-07-10 DOSAT 5.1935122522 + #> 5910 2056C2 3M CC45 2014 2014-07-10 SALIN 2.7219531063 #> 5911 2056C2 3M CC45 2014 2014-07-10 COND 10.5858012624 #> 5912 2056C2 3M CC45 2014 2014-07-10 DO 1.3584091576 #> 5913 2056C2 3M CC45 2014 2014-07-10 DOSAT 4.0893320204 + #> 5914 2056C2 3M CC45 2014 2014-07-10 SALIN 3.2284300377 #> 5915 2056C2 3M CC45 2014 2014-07-10 COND 10.5893079577 #> 5916 2056C2 3M CC45 2014 2014-07-10 DO 1.2383742310 #> 5917 2056C2 3M CC45 2014 2014-07-10 DOSAT 3.9702919136 + #> 5918 2056C2 3M CC45 2014 2014-07-10 SALIN 3.2327787300 #> 5919 2056C2 3M CC45 2014 2014-07-10 COND 10.5894086880 #> 5920 2056C2 3M CC45 2014 2014-07-10 DO 1.2178757095 #> 5921 2056C2 3M CC45 2014 2014-07-10 DOSAT 3.9493187902 + #> 5922 2056C2 3M CC45 2014 2014-07-10 SALIN 3.2335673736 #> 5923 2056C2 3M CC45 2014 2014-07-10 COND 10.5868621364 #> 5924 2056C2 3M CC45 2014 2014-07-10 DO 0.7654678421 #> 5925 2056C2 3M CC45 2014 2014-07-10 DOSAT 3.4965075615 + #> 5926 2056C2 3M CC45 2014 2014-07-10 SALIN 3.2331731296 #> 5927 2053 2 CC50 2013 2013-02-26 CHLAC 2.0541237337 #> 5928 2053 2 CC50 2013 2013-02-26 COND 10.5960845818 #> 5929 2053 2 CC50 2013 2013-02-26 DO 1.8531680974 #> 5930 2053 2 CC50 2013 2013-02-26 DOSAT 4.4953553200 #> 5931 2053 2 CC50 2013 2013-02-26 NO23 -5.5214609179 I #> 5932 2053 2 CC50 2013 2013-02-26 SALIN 3.2347491740 + #> 5933 2053 2 CC50 2013 2013-02-26 TKN -0.4462871026 #> 5934 2053 2 CC50 2013 2013-02-26 TN -0.4400565529 + #> 5935 2053 2 CC50 2013 2013-02-26 TP -1.8971199849 #> 5936 2053 2 CC50 2013 2013-02-26 TSS 1.7917594692 I #> 5937 2053 2 CC50 2013 2013-02-26 TURB 0.8754687374 #> 5938 2053 2 CC50 2013 2013-04-08 CHLAC 1.9740810260 #> 5939 2053 2 CC50 2013 2013-04-08 COND 10.6030143401 #> 5940 2053 2 CC50 2013 2013-04-08 DO 2.1329823086 #> 5941 2053 2 CC50 2013 2013-04-08 DOSAT 4.7655869074 #> 5942 2053 2 CC50 2013 2013-04-08 NO23 -5.2983173665 I #> 5943 2053 2 CC50 2013 2013-04-08 SALIN 3.2557861789 + #> 5944 2053 2 CC50 2013 2013-04-08 TKN -0.3710636814 #> 5945 2053 2 CC50 2013 2013-04-08 TN -0.3652833185 + #> 5946 2053 2 CC50 2013 2013-04-08 TP -1.7719568419 #> 5947 2053 2 CC50 2013 2013-04-08 TSS 2.0794415417 I #> 5948 2053 2 CC50 2013 2013-04-08 TURB 1.1631508098 #> 5949 2053 2 CC50 2013 2013-05-15 COND 10.4100340338 #> 5950 2053 2 CC50 2013 2013-05-15 DO 1.7900914121 #> 5951 2053 2 CC50 2013 2013-05-15 DOSAT 4.4331949212 #> 5952 2053 2 CC50 2013 2013-05-15 SALIN 3.0223742045 + #> 5953 2053 2 CC50 2013 2013-07-02 CHLAC 1.6486586256 #> 5954 2053 2 CC50 2013 2013-07-02 COND 7.8062892893 #> 5955 2053 2 CC50 2013 2013-07-02 DO 1.5851452199 #> 5956 2053 2 CC50 2013 2013-07-02 DOSAT 4.1125118662 #> 5957 2053 2 CC50 2013 2013-07-02 NO23 -2.7968814148 #> 5958 2053 2 CC50 2013 2013-07-02 SALIN 0.1988508587 + #> 5959 2053 2 CC50 2013 2013-07-02 TKN -0.1743533871 #> 5960 2053 2 CC50 2013 2013-07-02 TN -0.1042500214 + #> 5961 2053 2 CC50 2013 2013-07-02 TP -1.5141277326 #> 5962 2053 2 CC50 2013 2013-07-02 TSS 1.7917594692 I #> 5963 2053 2 CC50 2013 2013-07-02 TURB 1.0647107370 #> 5964 2053 2 CC50 2013 2013-08-14 COND 8.7817089858 #> 5965 2053 2 CC50 2013 2013-08-14 DO 1.8261608959 #> 5966 2053 2 CC50 2013 2013-08-14 DOSAT 4.4693504628 #> 5967 2053 2 CC50 2013 2013-09-18 COND 8.7180093308 #> 5968 2053 2 CC50 2013 2013-09-18 DO 1.4011829736 #> 5969 2053 2 CC50 2013 2013-09-18 DOSAT 3.9493187902 #> 5970 2053 2 CC50 2013 2013-09-18 SALIN 1.1474024528 + #> 5971 2053 2 CC50 2013 2013-10-07 CHLAC 3.1780538303 #> 5972 2053 2 CC50 2013 2013-10-07 COND 8.9351137408 #> 5973 2053 2 CC50 2013 2013-10-07 NO23 -2.9374633654 #> 5974 2053 2 CC50 2013 2013-10-07 SALIN 1.3686394259 + #> 5975 2053 2 CC50 2013 2013-10-07 TKN 0.1823215568 #> 5976 2053 2 CC50 2013 2013-10-07 TN 0.2255406759 + #> 5977 2053 2 CC50 2013 2013-10-07 TP -1.2729656758 #> 5978 2053 2 CC50 2013 2013-10-07 TSS 2.0794415417 I #> 5979 2053 2 CC50 2013 2013-10-07 TURB 1.2527629685 #> 5980 2053 2 CC50 2013 2013-10-31 COND 10.0177978987 #> 5981 2053 2 CC50 2013 2013-10-31 DO 1.5411590717 #> 5982 2053 2 CC50 2013 2013-10-31 DOSAT 4.0976723523 #> 5983 2053 2 CC50 2013 2013-10-31 SALIN 2.6108048167 + #> 5984 2053 2 CC50 2013 2013-11-20 COND 10.3586313189 #> 5985 2053 2 CC50 2013 2013-11-20 DO 2.1459312829 #> 5986 2053 2 CC50 2013 2013-11-20 DOSAT 4.7655869074 #> 5987 2053 2 CC50 2013 2013-11-20 SALIN 2.9454910571 + #> 5988 2053 2 CC50 2013 2013-12-11 COND 10.4527066243 #> 5989 2053 2 CC50 2013 2013-12-11 SALIN 3.0731561705 + #> 5990 2053 2 CC50 2013 2013-02-26 CHLAC 2.3978952728 #> 5991 2053 2 CC50 2013 2013-02-26 COND 10.6059165237 #> 5992 2053 2 CC50 2013 2013-02-26 DO 1.7595805709 #> 5993 2053 2 CC50 2013 2013-02-26 DOSAT 4.3981460166 #> 5994 2053 2 CC50 2013 2013-02-26 NO23 -4.8283137373 I #> 5995 2053 2 CC50 2013 2013-02-26 SALIN 3.2530839962 + #> 5996 2053 2 CC50 2013 2013-02-26 TKN -0.3011050928 #> 5997 2053 2 CC50 2013 2013-02-26 TN -0.2957142441 + #> 5998 2053 2 CC50 2013 2013-02-26 TP -1.8971199849 #> 5999 2053 2 CC50 2013 2013-02-26 TSS 1.9459101491 I #> 6000 2053 2 CC50 2013 2013-02-26 TURB 0.9162907319 #> 6001 2053 2 CC50 2013 2013-04-08 CHLAC 1.8870696490 #> 6002 2053 2 CC50 2013 2013-04-08 COND 10.6120896877 #> 6003 2053 2 CC50 2013 2013-04-08 DO 2.2321626287 #> 6004 2053 2 CC50 2013 2013-04-08 DOSAT 4.8574841146 #> 6005 2053 2 CC50 2013 2013-04-08 NO23 -4.5098600062 #> 6006 2053 2 CC50 2013 2013-04-08 SALIN 3.2775220203 + #> 6007 2053 2 CC50 2013 2013-04-08 TKN -0.5108256238 #> 6008 2053 2 CC50 2013 2013-04-08 TN -0.4926583198 + #> 6009 2053 2 CC50 2013 2013-04-08 TP -1.9661128564 #> 6010 2053 2 CC50 2013 2013-04-08 TSS 1.3862943611 I #> 6011 2053 2 CC50 2013 2013-04-08 TURB 0.7419373447 A #> 6012 2053 2 CC50 2013 2013-05-15 COND 10.5088685258 #> 6013 2053 2 CC50 2013 2013-05-15 DO 1.7950872593 #> 6014 2053 2 CC50 2013 2013-05-15 DOSAT 4.4320065670 #> 6015 2053 2 CC50 2013 2013-05-15 SALIN 3.1245651454 + #> 6016 2053 2 CC50 2013 2013-07-02 CHLAC 1.2527629685 #> 6017 2053 2 CC50 2013 2013-07-02 COND 7.8355792467 #> 6018 2053 2 CC50 2013 2013-07-02 DO 1.7065646232 #> 6019 2053 2 CC50 2013 2013-07-02 DOSAT 4.2224445648 #> 6020 2053 2 CC50 2013 2013-07-02 NO23 -2.3025850930 #> 6021 2053 2 CC50 2013 2013-07-02 SALIN 0.2468600779 + #> 6022 2053 2 CC50 2013 2013-07-02 TKN 0.0000000000 #> 6023 2053 2 CC50 2013 2013-07-02 TN 0.0953101798 + #> 6024 2053 2 CC50 2013 2013-07-02 TP -0.5621189182 #> 6025 2053 2 CC50 2013 2013-07-02 TSS 1.6094379124 I #> 6026 2053 2 CC50 2013 2013-07-02 TURB 0.8754687374 #> 6027 2053 2 CC50 2013 2013-08-14 COND 8.7740036002 #> 6028 2053 2 CC50 2013 2013-08-14 DO 1.7387102481 #> 6029 2053 2 CC50 2013 2013-08-14 DOSAT 4.3795235045 #> 6030 2053 2 CC50 2013 2013-09-18 COND 8.6015343398 #> 6031 2053 2 CC50 2013 2013-09-18 DO 1.6937790609 #> 6032 2053 2 CC50 2013 2013-09-18 DOSAT 4.2297491992 #> 6033 2053 2 CC50 2013 2013-09-18 SALIN 1.0438040522 + #> 6034 2053 2 CC50 2013 2013-10-07 CHLAC 4.2341065046 #> 6035 2053 2 CC50 2013 2013-10-07 COND 8.5477223965 #> 6036 2053 2 CC50 2013 2013-10-07 NO23 -2.4304184645 #> 6037 2053 2 CC50 2013 2013-10-07 SALIN 0.9477893989 + #> 6038 2053 2 CC50 2013 2013-10-07 TKN 0.0953101798 #> 6039 2053 2 CC50 2013 2013-10-07 TN 0.1722712209 + #> 6040 2053 2 CC50 2013 2013-10-07 TP -1.0216512475 #> 6041 2053 2 CC50 2013 2013-10-07 TSS 2.0794415417 I #> 6042 2053 2 CC50 2013 2013-10-07 TURB 0.7884573604 #> 6043 2053 2 CC50 2013 2013-10-31 COND 9.9967046342 #> 6044 2053 2 CC50 2013 2013-10-31 DO 1.6789639751 #> 6045 2053 2 CC50 2013 2013-10-31 DOSAT 4.2268337453 #> 6046 2053 2 CC50 2013 2013-10-31 SALIN 2.6012071055 + #> 6047 2053 2 CC50 2013 2013-11-20 COND 10.3609123996 #> 6048 2053 2 CC50 2013 2013-11-20 DO 1.9974177062 #> 6049 2053 2 CC50 2013 2013-11-20 DOSAT 4.6131383556 #> 6050 2053 2 CC50 2013 2013-11-20 SALIN 2.9554309768 + #> 6051 2053 2 CC50 2013 2013-12-11 COND 10.4538030840 #> 6052 2053 2 CC50 2013 2013-12-11 SALIN 3.1009927842 + #> 6053 2053 2 CC50 2013 2013-02-26 CHLAC 1.0647107370 #> 6054 2053 2 CC50 2013 2013-02-26 COND 10.6206441856 #> 6055 2053 2 CC50 2013 2013-02-26 DO 1.9227877316 #> 6056 2053 2 CC50 2013 2013-02-26 DOSAT 4.5549289696 #> 6057 2053 2 CC50 2013 2013-02-26 NO23 -5.1159958098 I #> 6058 2053 2 CC50 2013 2013-02-26 SALIN 3.2786530289 + #> 6059 2053 2 CC50 2013 2013-02-26 TKN -0.4307829161 #> 6060 2053 2 CC50 2013 2013-02-26 TN -0.4246479275 + #> 6061 2053 2 CC50 2013 2013-02-26 TP -1.9661128564 #> 6062 2053 2 CC50 2013 2013-02-26 TSS 2.0794415417 I #> 6063 2053 2 CC50 2013 2013-02-26 TURB 1.4109869737 #> 6064 2053 2 CC50 2013 2013-04-08 CHLAC 0.9932517730 #> 6065 2053 2 CC50 2013 2013-04-08 COND 10.6384002823 #> 6066 2053 2 CC50 2013 2013-04-08 DO 2.1529243184 #> 6067 2053 2 CC50 2013 2013-04-08 DOSAT 4.7672890355 #> 6068 2053 2 CC50 2013 2013-04-08 NO23 -5.2983173665 I #> 6069 2053 2 CC50 2013 2013-04-08 SALIN 3.3250360207 + #> 6070 2053 2 CC50 2013 2013-04-08 TKN -0.2744368457 #> 6071 2053 2 CC50 2013 2013-04-08 TN -0.2691874898 + #> 6072 2053 2 CC50 2013 2013-04-08 TP -1.7719568419 #> 6073 2053 2 CC50 2013 2013-04-08 TSS 2.6390573296 #> 6074 2053 2 CC50 2013 2013-04-08 TURB 1.7749523509 #> 6075 2053 2 CC50 2013 2013-05-15 COND 10.5426800055 #> 6076 2053 2 CC50 2013 2013-05-15 DO 1.7526720805 #> 6077 2053 2 CC50 2013 2013-05-15 DOSAT 4.3907385753 #> 6078 2053 2 CC50 2013 2013-05-15 SALIN 3.1970391303 + #> 6079 2053 2 CC50 2013 2013-07-02 CHLAC 2.7725887222 #> 6080 2053 2 CC50 2013 2013-07-02 COND 8.2877800271 #> 6081 2053 2 CC50 2013 2013-07-02 DO 1.8131947499 #> 6082 2053 2 CC50 2013 2013-07-02 DOSAT 4.3567088267 #> 6083 2053 2 CC50 2013 2013-07-02 NO23 -3.4737680745 #> 6084 2053 2 CC50 2013 2013-07-02 SALIN 0.6981347221 + #> 6085 2053 2 CC50 2013 2013-07-02 TKN 0.1823215568 #> 6086 2053 2 CC50 2013 2013-07-02 TN 0.2078268472 + #> 6087 2053 2 CC50 2013 2013-07-02 TP -0.8439700703 #> 6088 2053 2 CC50 2013 2013-07-02 TSS 2.3025850930 I #> 6089 2053 2 CC50 2013 2013-07-02 TURB 1.8245492921 #> 6090 2053 2 CC50 2013 2013-08-14 COND 8.7295588696 #> 6091 2053 2 CC50 2013 2013-08-14 DO 1.6467336972 #> 6092 2053 2 CC50 2013 2013-08-14 DOSAT 4.2598590007 #> 6093 2053 2 CC50 2013 2013-09-18 COND 8.4191392509 #> 6094 2053 2 CC50 2013 2013-09-18 DO 1.8131947499 #> 6095 2053 2 CC50 2013 2013-09-18 DOSAT 4.3694478525 #> 6096 2053 2 CC50 2013 2013-09-18 SALIN 0.8241754430 + #> 6097 2053 2 CC50 2013 2013-10-07 CHLAC 3.6888794541 #> 6098 2053 2 CC50 2013 2013-10-07 COND 8.8189260871 #> 6099 2053 2 CC50 2013 2013-10-07 NO23 -2.6882475738 #> 6100 2053 2 CC50 2013 2013-10-07 SALIN 1.2470322938 + #> 6101 2053 2 CC50 2013 2013-10-07 TKN 0.0953101798 #> 6102 2053 2 CC50 2013 2013-10-07 TN 0.1552928844 + #> 6103 2053 2 CC50 2013 2013-10-07 TP -1.0498221245 #> 6104 2053 2 CC50 2013 2013-10-07 TSS 1.9459101491 I #> 6105 2053 2 CC50 2013 2013-10-07 TURB 1.0986122887 #> 6106 2053 2 CC50 2013 2013-10-31 COND 9.9927339301 #> 6107 2053 2 CC50 2013 2013-10-31 DO 1.8082887712 #> 6108 2053 2 CC50 2013 2013-10-31 DOSAT 4.3541414312 #> 6109 2053 2 CC50 2013 2013-10-31 SALIN 2.6049094422 + #> 6110 2053 2 CC50 2013 2013-11-20 COND 10.3246619543 #> 6111 2053 2 CC50 2013 2013-11-20 DO 2.1713368064 #> 6112 2053 2 CC50 2013 2013-11-20 DOSAT 4.7908195329 #> 6113 2053 2 CC50 2013 2013-11-20 SALIN 2.9123506646 + #> 6114 2053 2 CC50 2013 2013-12-11 COND 10.4566827727 #> 6115 2053 2 CC50 2013 2013-12-11 SALIN 3.1223649245 + #> 6116 2053 2 CC50 2018 2018-03-15 CHLAC 0.9932517730 #> 6117 2053 2 CC50 2018 2018-03-15 COND 10.6964800681 #> 6118 2053 2 CC50 2018 2018-03-15 DO 2.0918640617 #> 6119 2053 2 CC50 2018 2018-03-15 DOSAT 4.6249728133 #> 6120 2053 2 CC50 2018 2018-03-15 NO23 -5.5214609179 U #> 6121 2053 2 CC50 2018 2018-03-15 SALIN 3.5010427166 + #> 6122 2053 2 CC50 2018 2018-03-15 TKN -0.5108256238 #> 6123 2053 2 CC50 2018 2018-03-15 TN -0.5074978337 + #> 6124 2053 2 CC50 2018 2018-03-15 TP -1.8325814637 #> 6125 2053 2 CC50 2018 2018-03-15 TSS 1.7917594692 I #> 6126 2053 2 CC50 2018 2018-03-15 TURB 1.1631508098 A #> 6127 2053 2 CC50 2018 2018-03-29 CHLAC 1.9459101491 #> 6128 2053 2 CC50 2018 2018-03-29 COND 10.6310361598 #> 6129 2053 2 CC50 2018 2018-03-29 DO 1.8405496334 #> 6130 2053 2 CC50 2018 2018-03-29 DOSAT 4.4426512565 #> 6131 2053 2 CC50 2018 2018-03-29 NO23 -5.5214609179 U #> 6132 2053 2 CC50 2018 2018-03-29 SALIN 3.3382575819 + #> 6133 2053 2 CC50 2018 2018-03-29 TKN 0.4054651081 #> 6134 2053 2 CC50 2018 2018-03-29 TN 0.4067975533 + #> 6135 2053 2 CC50 2018 2018-03-29 TP -1.8325814637 #> 6136 2053 2 CC50 2018 2018-03-29 TSS 2.6390573296 #> 6137 2053 2 CC50 2018 2018-03-29 TURB 1.7047480922 #> 6138 2053 2 CC50 2018 2018-04-23 CHLAC 2.0794415417 #> 6139 2053 2 CC50 2018 2018-04-23 COND 10.6468524493 #> 6140 2053 2 CC50 2018 2018-04-23 DO 1.9459101491 #> 6141 2053 2 CC50 2018 2018-04-23 DOSAT 4.6249728133 #> 6142 2053 2 CC50 2018 2018-04-23 NO23 -5.5214609179 U #> 6143 2053 2 CC50 2018 2018-04-23 SALIN 3.2649957605 + #> 6144 2053 2 CC50 2018 2018-04-23 TKN -0.3710636814 #> 6145 2053 2 CC50 2018 2018-04-23 TN -0.3681693234 + #> 6146 2053 2 CC50 2018 2018-04-23 TP -1.5141277326 #> 6147 2053 2 CC50 2018 2018-04-23 TSS 3.3322045102 A #> 6148 2053 2 CC50 2018 2018-04-23 TURB 1.8718021769 #> 6149 2053 2 CC50 2018 2018-05-10 CHLAC 1.7917594692 #> 6150 2053 2 CC50 2018 2018-05-10 COND 10.6712318713 #> 6151 2053 2 CC50 2018 2018-05-10 DO 1.5040773968 #> 6152 2053 2 CC50 2018 2018-05-10 DOSAT 4.1588830834 #> 6153 2053 2 CC50 2018 2018-05-10 NO23 -5.2983173665 I #> 6154 2053 2 CC50 2018 2018-05-10 SALIN 3.3214324132 #> 6155 2053 2 CC50 2018 2018-05-10 TKN -0.1165338163 #> 6156 2053 2 CC50 2018 2018-05-10 TN -0.1120495038 + #> 6157 2053 2 CC50 2018 2018-05-10 TP -1.3862943611 #> 6158 2053 2 CC50 2018 2018-05-10 TSS 2.7080502011 #> 6159 2053 2 CC50 2018 2018-05-10 TURB 1.9021075264 #> 6160 2053 2 CC50 2018 2018-06-11 CHLAC 2.6390573296 #> 6161 2053 2 CC50 2018 2018-06-11 COND 9.5468126086 #> 6162 2053 2 CC50 2018 2018-06-11 DO 1.6094379124 #> 6163 2053 2 CC50 2018 2018-06-11 DOSAT 4.2341065046 #> 6164 2053 2 CC50 2018 2018-06-11 NO23 -2.7806208939 #> 6165 2053 2 CC50 2018 2018-06-11 SALIN 2.0918640617 #> 6166 2053 2 CC50 2018 2018-06-11 TKN 0.1823215568 #> 6167 2053 2 CC50 2018 2018-06-11 TN 0.2326977641 + #> 6168 2053 2 CC50 2018 2018-06-11 TP -0.7133498879 #> 6169 2053 2 CC50 2018 2018-06-11 TSS 1.3862943611 I #> 6170 2053 2 CC50 2018 2018-06-11 TURB 0.7419373447 #> 6171 2053 2 CC50 2018 2018-06-25 CHLAC 3.4011973817 #> 6172 2053 2 CC50 2018 2018-06-25 COND 10.0243768698 #> 6173 2053 2 CC50 2018 2018-06-25 DO 1.7209792872 #> 6174 2053 2 CC50 2018 2018-06-25 DOSAT 4.3719762988 #> 6175 2053 2 CC50 2018 2018-06-25 NO23 -2.9374633654 #> 6176 2053 2 CC50 2018 2018-06-25 SALIN 2.5055259370 + #> 6177 2053 2 CC50 2018 2018-06-25 TKN 0.0953101798 #> 6178 2053 2 CC50 2018 2018-06-25 TN 0.1423672413 + #> 6179 2053 2 CC50 2018 2018-06-25 TP -0.9162907319 #> 6180 2053 2 CC50 2018 2018-06-25 TSS 1.3862943611 I #> 6181 2053 2 CC50 2018 2018-06-25 TURB 0.9932517730 #> 6182 2053 2 CC50 2018 2018-08-07 CHLAC 2.8332133441 #> 6183 2053 2 CC50 2018 2018-08-07 COND 7.3382381501 #> 6184 2053 2 CC50 2018 2018-08-07 DO 1.7698546338 #> 6185 2053 2 CC50 2018 2018-08-07 DOSAT 4.3438054219 #> 6186 2053 2 CC50 2018 2018-08-07 NO23 -3.1235656451 #> 6187 2053 2 CC50 2018 2018-08-07 SALIN -0.2613647641 #> 6188 2053 2 CC50 2018 2018-08-07 TKN 0.0953101798 #> 6189 2053 2 CC50 2018 2018-08-07 TN 0.1345308930 + #> 6190 2053 2 CC50 2018 2018-08-07 TP -1.2378743560 #> 6191 2053 2 CC50 2018 2018-08-07 TSS 1.3862943611 I #> 6192 2053 2 CC50 2018 2018-08-07 TURB 0.9162907319 A #> 6193 2053 2 CC50 2018 2018-09-06 CHLAC 2.0014800002 #> 6194 2053 2 CC50 2018 2018-09-06 COND 8.6513743729 #> 6195 2053 2 CC50 2018 2018-09-06 DO 1.8341801851 #> 6196 2053 2 CC50 2018 2018-09-06 DOSAT 4.4236483094 #> 6197 2053 2 CC50 2018 2018-09-06 NO23 -2.5383074265 #> 6198 2053 2 CC50 2018 2018-09-06 SALIN 1.1281710909 #> 6199 2053 2 CC50 2018 2018-09-06 TKN 0.1823215568 #> 6200 2053 2 CC50 2018 2018-09-06 TN 0.2460785226 + #> 6201 2053 2 CC50 2018 2018-09-06 TP -1.2378743560 #> 6202 2053 2 CC50 2018 2018-09-06 TSS 1.3862943611 I #> 6203 2053 2 CC50 2018 2018-09-06 TURB 0.6931471806 #> 6204 2053 2 CC50 2018 2018-09-20 CHLAC 2.5649493575 #> 6205 2053 2 CC50 2018 2018-09-20 COND 9.3369730229 #> 6206 2053 2 CC50 2018 2018-09-20 DO 1.6582280766 #> 6207 2053 2 CC50 2018 2018-09-20 DOSAT 4.1682144108 #> 6208 2053 2 CC50 2018 2018-09-20 NO23 -4.1351665567 #> 6209 2053 2 CC50 2018 2018-09-20 SALIN 1.8562979904 #> 6210 2053 2 CC50 2018 2018-09-20 TKN -0.0725706928 #> 6211 2053 2 CC50 2018 2018-09-20 TN -0.0555127099 + #> 6212 2053 2 CC50 2018 2018-09-20 TP -1.1394342832 #> 6213 2053 2 CC50 2018 2018-09-20 TSS 1.3862943611 I #> 6214 2053 2 CC50 2018 2018-09-20 TURB 0.4700036292 #> 6215 2053 2 CC50 2018 2018-10-24 CHLAC 1.9600947840 #> 6216 2053 2 CC50 2018 2018-10-24 COND 10.0400269167 #> 6217 2053 2 CC50 2018 2018-10-24 DO 1.9430489168 #> 6218 2053 2 CC50 2018 2018-10-24 DOSAT 4.5496574761 #> 6219 2053 2 CC50 2018 2018-10-24 NO23 -2.7488721956 #> 6220 2053 2 CC50 2018 2018-10-24 SALIN 2.6246685922 #> 6221 2053 2 CC50 2018 2018-10-24 TKN -0.3011050928 #> 6222 2053 2 CC50 2018 2018-10-24 TN -0.2181560098 + #> 6223 2053 2 CC50 2018 2018-10-24 TP -1.4271163556 #> 6224 2053 2 CC50 2018 2018-10-24 TSS 1.6094379124 I #> 6225 2053 2 CC50 2018 2018-10-24 TURB 0.9162907319 #> 6226 2053 2 CC50 2019 2019-04-17 CHLAC 1.5892352051 I #> 6227 2053 2 CC50 2019 2019-04-17 COND 10.3074515345 #> 6228 2053 2 CC50 2019 2019-04-17 DO 1.9878743482 #> 6229 2053 2 CC50 2019 2019-04-17 DOSAT 4.5981455711 #> 6230 2053 2 CC50 2019 2019-04-17 NO23 -5.5214609179 U #> 6231 2053 2 CC50 2019 2019-04-17 SALIN 2.9193910403 #> 6232 2053 2 CC50 2019 2019-04-17 TKN -0.4462871026 #> 6233 2053 2 CC50 2019 2019-04-17 TN -0.4431669753 + #> 6234 2053 2 CC50 2019 2019-04-17 TP -1.6607312068 #> 6235 2053 2 CC50 2019 2019-04-17 TSS 2.9444389792 A #> 6236 2053 2 CC50 2019 2019-04-17 TURB 1.0296194172 #> 6237 2053 2 CC50 2019 2019-07-15 CHLAC 3.0910424534 #> 6238 2053 2 CC50 2019 2019-07-15 COND 10.0506999322 #> 6239 2053 2 CC50 2019 2019-07-15 DO 1.9430489168 #> 6240 2053 2 CC50 2019 2019-07-15 DOSAT 4.5971380143 #> 6241 2053 2 CC50 2019 2019-07-15 NO23 -5.5214609179 U #> 6242 2053 2 CC50 2019 2019-07-15 SALIN 2.6333266549 #> 6243 2053 2 CC50 2019 2019-07-15 TKN -0.2107210313 #> 6244 2053 2 CC50 2019 2019-07-15 TN -0.2082549388 + #> 6245 2053 2 CC50 2019 2019-07-15 TP -1.4696759701 #> 6246 2053 2 CC50 2019 2019-07-15 TSS 2.0794415417 I #> 6247 2053 2 CC50 2019 2019-07-15 TURB 0.9932517730 #> 6248 2053 2 CC50 2019 2019-08-19 CHLAC 1.4816045409 #> 6249 2053 2 CC50 2019 2019-08-19 COND 7.3530819205 #> 6250 2053 2 CC50 2019 2019-08-19 DO 1.5665304114 #> 6251 2053 2 CC50 2019 2019-08-19 DOSAT 4.1367652781 #> 6252 2053 2 CC50 2019 2019-08-19 NO23 -2.6036901858 #> 6253 2053 2 CC50 2019 2019-08-19 SALIN -0.2484613593 #> 6254 2053 2 CC50 2019 2019-08-19 TKN 0.3364722366 #> 6255 2053 2 CC50 2019 2019-08-19 TN 0.3879797938 + #> 6256 2053 2 CC50 2019 2019-08-19 TP -0.8209805521 #> 6257 2053 2 CC50 2019 2019-08-19 TSS 1.0986122887 I #> 6258 2053 2 CC50 2019 2019-08-19 TURB 0.7884573604 #> 6259 2053 2 CC50 2019 2019-09-11 CHLAC 3.0910424534 #> 6260 2053 2 CC50 2019 2019-09-11 COND 9.8378817954 #> 6261 2053 2 CC50 2019 2019-09-11 DO 1.9139771020 #> 6262 2053 2 CC50 2019 2019-09-11 DOSAT 4.5475410732 #> 6263 2053 2 CC50 2019 2019-09-11 NO23 -4.0173835211 #> 6264 2053 2 CC50 2019 2019-09-11 SALIN 2.4015250408 #> 6265 2053 2 CC50 2019 2019-09-11 TKN -0.0725706928 #> 6266 2053 2 CC50 2019 2019-09-11 TN -0.0534007767 + #> 6267 2053 2 CC50 2019 2019-09-11 TP -1.2039728043 #> 6268 2053 2 CC50 2019 2019-09-11 TSS 1.6094379124 I #> 6269 2053 2 CC50 2019 2019-09-11 TURB 0.7884573604 #> 6270 2053 2 CC50 2019 2019-10-09 CHLAC 1.1939224685 #> 6271 2053 2 CC50 2019 2019-10-09 COND 10.2652793829 #> 6272 2053 2 CC50 2019 2019-10-09 DO 1.7065646232 #> 6273 2053 2 CC50 2019 2019-10-09 DOSAT 4.3554259529 #> 6274 2053 2 CC50 2019 2019-10-09 NO23 -5.5214609179 I #> 6275 2053 2 CC50 2019 2019-10-09 SALIN 2.8713021952 #> 6276 2053 2 CC50 2019 2019-10-09 TKN -0.4155154440 #> 6277 2053 2 CC50 2019 2019-10-09 TN -0.4094731295 + #> 6278 2053 2 CC50 2019 2019-10-09 TP -1.5141277326 #> 6279 2053 2 CC50 2019 2019-10-09 TSS 1.0986122887 U #> 6280 2053 2 CC50 2019 2019-10-09 TURB -0.1625189295 #> 6281 2053 2 CC50 2020 2020-02-13 CHLAC 1.5475625087 #> 6282 2053 2 CC50 2020 2020-02-13 COND 10.4652439050 #> 6283 2053 2 CC50 2020 2020-02-13 DO 1.8017098001 #> 6284 2053 2 CC50 2020 2020-02-13 DOSAT 4.4067192473 #> 6285 2053 2 CC50 2020 2020-02-13 NO23 -5.5214609179 U #> 6286 2053 2 CC50 2020 2020-02-13 SALIN 3.0946722214 #> 6287 2053 2 CC50 2020 2020-02-13 TKN -0.4620354596 #> 6288 2053 2 CC50 2020 2020-02-13 TN -0.4588658848 + #> 6289 2053 2 CC50 2020 2020-02-13 TP -1.8325814637 #> 6290 2053 2 CC50 2020 2020-02-13 TSS 2.7080502011 #> 6291 2053 2 CC50 2020 2020-02-13 TURB 2.0014800002 A #> 6292 2053 2 CC50 2020 2020-03-24 CHLAC 1.3350010667 #> 6293 2053 2 CC50 2020 2020-03-24 COND 10.5688523521 #> 6294 2053 2 CC50 2020 2020-03-24 DO 1.9401794743 #> 6295 2053 2 CC50 2020 2020-03-24 DOSAT 4.6434288981 #> 6296 2053 2 CC50 2020 2020-03-24 NO23 -5.5214609179 U #> 6297 2053 2 CC50 2020 2020-03-24 SALIN 3.2047769005 #> 6298 2053 2 CC50 2020 2020-03-24 TKN -0.4462871026 #> 6299 2053 2 CC50 2020 2020-03-24 TN -0.4431669753 + #> 6300 2053 2 CC50 2020 2020-03-24 TP -1.8325814637 #> 6301 2053 2 CC50 2020 2020-03-24 TSS 2.7725887222 #> 6302 2053 2 CC50 2020 2020-03-24 TURB 1.5260563035 #> 6303 2053 2 CC50 2020 2020-06-22 CHLAC 3.1780538303 #> 6304 2053 2 CC50 2020 2020-06-22 COND 9.9972510823 #> 6305 2053 2 CC50 2020 2020-06-22 DO 1.7173950539 #> 6306 2053 2 CC50 2020 2020-06-22 DOSAT 4.3795235045 #> 6307 2053 2 CC50 2020 2020-06-22 NO23 -4.5098600062 #> 6308 2053 2 CC50 2020 2020-06-22 SALIN 2.5718485799 #> 6309 2053 2 CC50 2020 2020-06-22 TKN -0.0100503359 #> 6310 2053 2 CC50 2020 2020-06-22 TN 0.0009995003 + #> 6311 2053 2 CC50 2020 2020-06-22 TP -1.2039728043 #> 6312 2053 2 CC50 2020 2020-06-22 TSS 1.7917594692 I #> 6313 2053 2 CC50 2020 2020-06-22 TURB 0.7884573604 A #> 6314 2053 2 CC50 2020 2020-07-27 CHLAC 1.7578579176 #> 6315 2053 2 CC50 2020 2020-07-27 COND 10.1123293191 #> 6316 2053 2 CC50 2020 2020-07-27 DO 1.5644405465 #> 6317 2053 2 CC50 2020 2020-07-27 DOSAT 4.2239097666 #> 6318 2053 2 CC50 2020 2020-07-27 NO23 -4.1351665567 #> 6319 2053 2 CC50 2020 2020-07-27 SALIN 2.7006898467 #> 6320 2053 2 CC50 2020 2020-07-27 TN -0.3481400415 + #> 6321 2053 2 CC50 2020 2020-07-27 TP -1.3093333200 #> 6322 2053 2 CC50 2020 2020-07-27 TSS 1.0986122887 U #> 6323 2053 2 CC50 2020 2020-07-27 TURB 0.5306282511 #> 6324 2053 2 CC50 2020 2020-08-26 CHLAC 2.2300144002 #> 6325 2053 2 CC50 2020 2020-08-26 COND 9.8854254097 #> 6326 2053 2 CC50 2020 2020-08-26 DO 1.7850704811 #> 6327 2053 2 CC50 2020 2020-08-26 DOSAT 4.4188406078 #> 6328 2053 2 CC50 2020 2020-08-26 NO23 -5.5214609179 U #> 6329 2053 2 CC50 2020 2020-08-26 SALIN 2.4535879665 #> 6330 2053 2 CC50 2020 2020-08-26 TKN -0.1984509387 #> 6331 2053 2 CC50 2020 2020-08-26 TN -0.1960148839 + #> 6332 2053 2 CC50 2020 2020-08-26 TP -1.3862943611 #> 6333 2053 2 CC50 2020 2020-08-26 TSS 1.0986122887 U #> 6334 2053 2 CC50 2020 2020-08-26 TURB 0.0953101798 #> 6335 2053 2 CC50 2021 2021-01-14 CHLAC 1.6094379124 A #> 6336 2053 2 CC50 2021 2021-01-14 COND 10.2228136303 #> 6337 2053 2 CC50 2021 2021-01-14 DO 2.0967901800 #> 6338 2053 2 CC50 2021 2021-01-14 DOSAT 4.5580785785 #> 6339 2053 2 CC50 2021 2021-01-14 NO23 -5.5214609179 I #> 6340 2053 2 CC50 2021 2021-01-14 SALIN 2.8314470792 #> 6341 2053 2 CC50 2021 2021-01-14 TKN -0.2876820725 #> 6342 2053 2 CC50 2021 2021-01-14 TN -0.2823629110 + #> 6343 2053 2 CC50 2021 2021-01-14 TP -1.7147984281 #> 6344 2053 2 CC50 2021 2021-01-14 TSS 2.5649493575 A #> 6345 2053 2 CC50 2021 2021-01-14 TURB 1.4586150227 #> 6346 2053 2 CC50 2021 2021-02-24 COND 10.2486009183 #> 6347 2053 2 CC50 2021 2021-02-24 DO 2.0955609236 #> 6348 2053 2 CC50 2021 2021-02-24 DOSAT 4.6453519756 #> 6349 2053 2 CC50 2021 2021-02-24 NO23 -5.5214609179 U #> 6350 2053 2 CC50 2021 2021-02-24 SALIN 2.8581928595 #> 6351 2053 2 CC50 2021 2021-02-24 TKN -0.6733445533 #> 6352 2053 2 CC50 2021 2021-02-24 TN -0.6694306539 + #> 6353 2053 2 CC50 2021 2021-02-24 TP -1.8971199849 #> 6354 2053 2 CC50 2021 2021-02-24 TSS 1.0986122887 I #> 6355 2053 2 CC50 2021 2021-03-23 CHLAC 0.9555114450 #> 6356 2053 2 CC50 2021 2021-03-23 COND 10.5061901968 #> 6357 2053 2 CC50 2021 2021-03-23 DO 1.9685099810 #> 6358 2053 2 CC50 2021 2021-03-23 DOSAT 4.5119578043 #> 6359 2053 2 CC50 2021 2021-03-23 NO23 -5.2983173665 I #> 6360 2053 2 CC50 2021 2021-03-23 SALIN 3.1419947805 #> 6361 2053 2 CC50 2021 2021-03-23 TKN -0.4620354596 #> 6362 2053 2 CC50 2021 2021-03-23 TN -0.4557063245 + #> 6363 2053 2 CC50 2021 2021-03-23 TP -1.8971199849 #> 6364 2053 2 CC50 2021 2021-03-23 TSS 1.0986122887 U #> 6365 2053 2 CC50 2021 2021-03-23 TURB 0.6418538862 #> 6366 2053 2 CC50 2021 2021-07-28 CHLAC 2.2721258855 #> 6367 2053 2 CC50 2021 2021-07-28 COND 9.4095190458 #> 6368 2053 2 CC50 2021 2021-07-28 DO 0.9516578757 #> 6369 2053 2 CC50 2021 2021-07-28 DOSAT 3.5638829639 #> 6370 2053 2 CC50 2021 2021-07-28 NO23 -3.1700856607 #> 6371 2053 2 CC50 2021 2021-07-28 SALIN 1.9373017745 #> 6372 2053 2 CC50 2021 2021-07-28 TKN 0.1823215568 #> 6373 2053 2 CC50 2021 2021-07-28 TN 0.2167229835 + #> 6374 2053 2 CC50 2021 2021-07-28 TP -0.7550225843 #> 6375 2053 2 CC50 2021 2021-07-28 TSS 1.3862943611 I #> 6376 2053 2 CC50 2021 2021-07-28 TURB 1.7404661748 #> 6377 2053 2 CC50 2021 2021-08-26 CHLAC 1.5260563035 #> 6378 2053 2 CC50 2021 2021-08-26 COND 9.2069345788 #> 6379 2053 2 CC50 2021 2021-08-26 DO 1.0296194172 #> 6380 2053 2 CC50 2021 2021-08-26 DOSAT 3.6270040504 #> 6381 2053 2 CC50 2021 2021-08-26 NO23 -2.7488721956 #> 6382 2053 2 CC50 2021 2021-08-26 SALIN 1.7191887764 #> 6383 2053 2 CC50 2021 2021-08-26 TKN -0.3285040670 #> 6384 2053 2 CC50 2021 2021-08-26 TN -0.2433462586 + #> 6385 2053 2 CC50 2021 2021-08-26 TP -1.0216512475 #> 6386 2053 2 CC50 2021 2021-08-26 TSS 1.0986122887 I #> 6387 2053 2 CC50 2021 2021-08-26 TURB 0.9555114450 #> 6388 2053 2 CC50 2021 2021-09-13 CHLAC 1.7578579176 #> 6389 2053 2 CC50 2021 2021-09-13 COND 9.5941731800 #> 6390 2053 2 CC50 2021 2021-09-13 DO 1.4422019931 #> 6391 2053 2 CC50 2021 2021-09-13 DOSAT 4.0707346966 #> 6392 2053 2 CC50 2021 2021-09-13 NO23 -2.7806208939 #> 6393 2053 2 CC50 2021 2021-09-13 SALIN 2.1365305087 #> 6394 2053 2 CC50 2021 2021-09-13 TKN -0.0618754037 #> 6395 2053 2 CC50 2021 2021-09-13 TN 0.0019980027 + #> 6396 2053 2 CC50 2021 2021-09-13 TP -1.2039728043 #> 6397 2053 2 CC50 2021 2021-09-13 TSS 1.0986122887 I #> 6398 2053 2 CC50 2021 2021-09-13 TURB 0.5877866649 #> 6399 2053 2 CC50 2022 2022-03-16 COND 10.6209126256 #> 6400 2053 2 CC50 2022 2022-03-16 DO 1.9080599249 #> 6401 2053 2 CC50 2022 2022-03-16 DOSAT 4.5152454785 #> 6402 2053 2 CC50 2022 2022-03-16 SALIN 3.2676659890 #> 6403 2053 2 CC50 2022 2022-05-04 COND 10.6380165709 #> 6404 2053 2 CC50 2022 2022-05-04 DO 1.8748743759 #> 6405 2053 2 CC50 2022 2022-05-04 DOSAT 4.5622626850 #> 6406 2053 2 CC50 2022 2022-05-04 SALIN 3.2839142210 #> 6407 2054 3F CC53 2013 2013-01-07 CHLAC 2.3025850930 #> 6408 2054 3F CC53 2013 2013-01-07 COLOR 3.8501476017 #> 6409 2054 3F CC53 2013 2013-01-07 DO 1.6094379124 #> 6410 2054 3F CC53 2013 2013-01-07 NO23 -2.5639498571 #> 6411 2054 3F CC53 2013 2013-01-07 TKN -0.0833816089 #> 6412 2054 3F CC53 2013 2013-01-07 TN -0.0030045090 + #> 6413 2054 3F CC53 2013 2013-01-07 TP -2.0402208285 #> 6414 2054 3F CC53 2013 2013-01-07 TURB 1.2527629685 #> 6415 2054 3F CC53 2013 2013-02-04 CHLAC 2.7725887222 #> 6416 2054 3F CC53 2013 2013-02-04 COLOR 3.8066624898 #> 6417 2054 3F CC53 2013 2013-02-04 DOSAT 4.0000338828 + #> 6418 2054 3F CC53 2013 2013-02-04 NO23 -5.5214609179 U #> 6419 2054 3F CC53 2013 2013-02-04 SALIN 0.0953101798 #> 6420 2054 3F CC53 2013 2013-02-04 TKN -0.2744368457 #> 6421 2054 3F CC53 2013 2013-02-04 TN -0.2718087233 + #> 6422 2054 3F CC53 2013 2013-02-04 TP -1.9661128564 #> 6423 2054 3F CC53 2013 2013-02-04 TURB 0.8754687374 #> 6424 2054 3F CC53 2013 2013-03-04 CHLAC 2.1282317058 #> 6425 2054 3F CC53 2013 2013-03-04 COLOR 3.7376696183 #> 6426 2054 3F CC53 2013 2013-03-04 DO 1.9169226122 #> 6427 2054 3F CC53 2013 2013-03-04 DOSAT 4.2180360346 + #> 6428 2054 3F CC53 2013 2013-03-04 NO23 -3.0365542681 #> 6429 2054 3F CC53 2013 2013-03-04 TKN -0.3285040670 #> 6430 2054 3F CC53 2013 2013-03-04 TN -0.2639655458 + #> 6431 2054 3F CC53 2013 2013-03-04 TP -1.7719568419 #> 6432 2054 3F CC53 2013 2013-03-04 TURB 1.0986122887 #> 6433 2054 3F CC53 2013 2013-04-01 CHLAC 2.1633230257 #> 6434 2054 3F CC53 2013 2013-04-01 COLOR 3.7376696183 #> 6435 2054 3F CC53 2013 2013-04-01 DO 1.8082887712 #> 6436 2054 3F CC53 2013 2013-04-01 DOSAT 4.2570301445 + #> 6437 2054 3F CC53 2013 2013-04-01 NO23 -4.2686979494 #> 6438 2054 3F CC53 2013 2013-04-01 SALIN 1.6094379124 #> 6439 2054 3F CC53 2013 2013-04-01 TKN -0.2107210313 #> 6440 2054 3F CC53 2013 2013-04-01 TN -0.1935847491 + #> 6441 2054 3F CC53 2013 2013-04-01 TP -1.7719568419 #> 6442 2054 3F CC53 2013 2013-04-01 TURB 0.9555114450 #> 6443 2054 3F CC53 2013 2013-05-06 CHLAC 2.1400661635 #> 6444 2054 3F CC53 2013 2013-05-06 COLOR 3.8712010109 #> 6445 2054 3F CC53 2013 2013-05-06 DO 1.8562979904 #> 6446 2054 3F CC53 2013 2013-05-06 DOSAT 4.3294166844 + #> 6447 2054 3F CC53 2013 2013-05-06 NO23 -3.8167128256 #> 6448 2054 3F CC53 2013 2013-05-06 SALIN 0.5596157879 #> 6449 2054 3F CC53 2013 2013-05-06 TKN -0.2107210313 #> 6450 2054 3F CC53 2013 2013-05-06 TN -0.1839228382 + #> 6451 2054 3F CC53 2013 2013-05-06 TP -1.5606477483 #> 6452 2054 3F CC53 2013 2013-05-06 TURB 1.2527629685 #> 6453 2054 3F CC53 2013 2013-06-03 CHLAC 0.9162907319 #> 6454 2054 3F CC53 2013 2013-06-03 COLOR 4.0775374439 #> 6455 2054 3F CC53 2013 2013-06-03 DO 1.3862943611 #> 6456 2054 3F CC53 2013 2013-06-03 NO23 -2.4418471603 #> 6457 2054 3F CC53 2013 2013-06-03 TKN -0.2876820725 #> 6458 2054 3F CC53 2013 2013-06-03 TN -0.1779312085 + #> 6459 2054 3F CC53 2013 2013-06-03 TP -1.3862943611 #> 6460 2054 3F CC53 2013 2013-06-03 TURB 0.3364722366 #> 6461 2054 3F CC53 2013 2013-07-08 CHLAC 0.7884573604 #> 6462 2054 3F CC53 2013 2013-07-08 COLOR 5.1929568509 #> 6463 2054 3F CC53 2013 2013-07-08 DO 1.5260563035 #> 6464 2054 3F CC53 2013 2013-07-08 DOSAT 4.0943445622 + #> 6465 2054 3F CC53 2013 2013-07-08 NO23 -4.7105307016 I #> 6466 2054 3F CC53 2013 2013-07-08 TKN 0.0953101798 #> 6467 2054 3F CC53 2013 2013-07-08 TN 0.0989399479 + #> 6468 2054 3F CC53 2013 2013-07-08 TP -2.0402208285 #> 6469 2054 3F CC53 2013 2013-07-08 TURB 0.9162907319 A #> 6470 2054 3F CC53 2013 2013-08-05 CHLAC 1.0296194172 #> 6471 2054 3F CC53 2013 2013-08-05 COLOR 4.8675344505 #> 6472 2054 3F CC53 2013 2013-08-05 DO 1.1314021115 #> 6473 2054 3F CC53 2013 2013-08-05 DOSAT 3.6963514690 + #> 6474 2054 3F CC53 2013 2013-08-05 NO23 -3.5065578973 #> 6475 2054 3F CC53 2013 2013-08-05 TKN 0.2623642645 #> 6476 2054 3F CC53 2013 2013-08-05 TN 0.2851789422 + #> 6477 2054 3F CC53 2013 2013-08-05 TP -2.0402208285 #> 6478 2054 3F CC53 2013 2013-08-05 TURB 0.7884573604 #> 6479 2054 3F CC53 2013 2013-09-09 CHLAC 0.6418538862 #> 6480 2054 3F CC53 2013 2013-09-09 COLOR 4.7004803658 #> 6481 2054 3F CC53 2013 2013-09-09 DO 1.6094379124 #> 6482 2054 3F CC53 2013 2013-09-09 DOSAT 4.0775374439 + #> 6483 2054 3F CC53 2013 2013-09-09 NO23 -5.1159958098 I #> 6484 2054 3F CC53 2013 2013-09-09 TKN -0.0618754037 #> 6485 2054 3F CC53 2013 2013-09-09 TN -0.0576291128 + #> 6486 2054 3F CC53 2013 2013-09-09 TP -2.3751557858 #> 6487 2054 3F CC53 2013 2013-09-09 TURB 0.9932517730 #> 6488 2054 3F CC53 2013 2013-10-07 CHLAC 0.9932517730 #> 6489 2054 3F CC53 2013 2013-10-07 COLOR 4.8675344505 #> 6490 2054 3F CC53 2013 2013-10-07 DOSAT 3.9298629236 + #> 6491 2054 3F CC53 2013 2013-10-07 NO23 -2.2072749132 #> 6492 2054 3F CC53 2013 2013-10-07 SALIN 0.0000000000 #> 6493 2054 3F CC53 2013 2013-10-07 TKN -0.0304592075 #> 6494 2054 3F CC53 2013 2013-10-07 TN 0.0769610411 + #> 6495 2054 3F CC53 2013 2013-10-07 TP -1.8971199849 #> 6496 2054 3F CC53 2013 2013-10-07 TURB 1.2809338455 #> 6497 2054 3F CC53 2013 2013-11-04 CHLAC 3.0445224377 #> 6498 2054 3F CC53 2013 2013-11-04 COLOR 4.2904594411 #> 6499 2054 3F CC53 2013 2013-11-04 DO 1.8245492921 #> 6500 2054 3F CC53 2013 2013-11-04 DOSAT 4.2541932632 + #> 6501 2054 3F CC53 2013 2013-11-04 NO23 -2.1202635362 #> 6502 2054 3F CC53 2013 2013-11-04 TKN -0.1508228897 #> 6503 2054 3F CC53 2013 2013-11-04 TN -0.0202027073 + #> 6504 2054 3F CC53 2013 2013-11-04 TP -1.8971199849 #> 6505 2054 3F CC53 2013 2013-11-04 TURB 0.9555114450 A #> 6506 2054 3F CC53 2013 2013-12-02 CHLAC 2.4849066498 #> 6507 2054 3F CC53 2013 2013-12-02 COLOR 4.1108738642 #> 6508 2054 3F CC53 2013 2013-12-02 DO 1.9169226122 #> 6509 2054 3F CC53 2013 2013-12-02 DOSAT 4.3214801348 + #> 6510 2054 3F CC53 2013 2013-12-02 NO23 -1.7147984281 #> 6511 2054 3F CC53 2013 2013-12-02 SALIN -0.2231435513 #> 6512 2054 3F CC53 2013 2013-12-02 TKN -0.1863295782 #> 6513 2054 3F CC53 2013 2013-12-02 TN 0.0099503309 + #> 6514 2054 3F CC53 2013 2013-12-02 TP -1.9661128564 #> 6515 2054 3F CC53 2013 2013-12-02 TURB 0.9162907319 #> 6516 2054 3F CC53 2014 2014-01-06 CHLAC 3.3672958300 #> 6517 2054 3F CC53 2014 2014-01-06 COLOR 4.1271343850 A #> 6518 2054 3F CC53 2014 2014-01-06 DO 1.8245492921 #> 6519 2054 3F CC53 2014 2014-01-06 DOSAT 4.2209772132 + #> 6520 2054 3F CC53 2014 2014-01-06 NO23 -2.5133061243 #> 6521 2054 3F CC53 2014 2014-01-06 SALIN 0.3364722366 #> 6522 2054 3F CC53 2014 2014-01-06 TKN -0.1625189295 #> 6523 2054 3F CC53 2014 2014-01-06 TN -0.0714960017 + #> 6524 2054 3F CC53 2014 2014-01-06 TP -2.9565115604 #> 6525 2054 3F CC53 2014 2014-01-06 TURB 1.1939224685 A #> 6526 2054 3F CC53 2014 2014-02-03 CHLAC 2.5649493575 #> 6527 2054 3F CC53 2014 2014-02-03 COLOR 4.0073331852 #> 6528 2054 3F CC53 2014 2014-02-03 DO 2.0014800002 #> 6529 2054 3F CC53 2014 2014-02-03 DOSAT 4.3956829611 + #> 6530 2054 3F CC53 2014 2014-02-03 NO23 -2.1202635362 #> 6531 2054 3F 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2014 2014-04-07 DOSAT 4.0960098415 + #> 6550 2054 3F CC53 2014 2014-04-07 NO23 -4.3428059215 #> 6551 2054 3F CC53 2014 2014-04-07 TKN -0.0943106795 #> 6552 2054 3F CC53 2014 2014-04-07 TN -0.0801260445 + #> 6553 2054 3F CC53 2014 2014-04-07 TP -2.1202635362 #> 6554 2054 3F CC53 2014 2014-04-07 TURB 1.1939224685 #> 6555 2054 3F CC53 2014 2014-05-05 CHLAC 2.4849066498 #> 6556 2054 3F CC53 2014 2014-05-05 COLOR 4.0073331852 #> 6557 2054 3F CC53 2014 2014-05-05 DO 1.9459101491 #> 6558 2054 3F CC53 2014 2014-05-05 DOSAT 4.4006030202 + #> 6559 2054 3F CC53 2014 2014-05-05 NO23 -3.5755507688 #> 6560 2054 3F CC53 2014 2014-05-05 SALIN 0.4054651081 #> 6561 2054 3F CC53 2014 2014-05-05 TKN -0.1053605157 #> 6562 2054 3F CC53 2014 2014-05-05 TN -0.0747235462 + #> 6563 2054 3F CC53 2014 2014-05-05 TP -1.8325814637 #> 6564 2054 3F CC53 2014 2014-05-05 TURB 1.0296194172 #> 6565 2054 3F CC53 2014 2014-06-02 CHLAC 2.3978952728 #> 6566 2054 3F CC53 2014 2014-06-02 COLOR 4.1108738642 #> 6567 2054 3F CC53 2014 2014-06-02 DO 1.7578579176 #> 6568 2054 3F CC53 2014 2014-06-02 DOSAT 4.2780540443 + #> 6569 2054 3F CC53 2014 2014-06-02 NO23 -4.9618451299 I #> 6570 2054 3F CC53 2014 2014-06-02 TKN -0.0408219945 #> 6571 2054 3F CC53 2014 2014-06-02 TN -0.0366639844 + #> 6572 2054 3F CC53 2014 2014-06-02 TP -1.5141277326 #> 6573 2054 3F CC53 2014 2014-06-02 TURB 1.2527629685 #> 6574 2054 3F CC53 2014 2014-07-07 CHLAC 2.3025850930 #> 6575 2054 3F CC53 2014 2014-07-07 COLOR 4.8675344505 #> 6576 2054 3F CC53 2014 2014-07-07 NO23 -3.0365542681 #> 6577 2054 3F CC53 2014 2014-07-07 TKN 0.4054651081 #> 6578 2054 3F CC53 2014 2014-07-07 TN 0.4369637752 + #> 6579 2054 3F CC53 2014 2014-07-07 TP -1.0788096614 #> 6580 2054 3F CC53 2014 2014-07-07 TURB 1.3609765531 A #> 6581 2054 3F CC53 2014 2014-08-04 CHLAC 1.0647107370 #> 6582 2054 3F CC53 2014 2014-08-04 COLOR 5.2983173665 #> 6583 2054 3F CC53 2014 2014-08-04 DO 1.2837077723 #> 6584 2054 3F CC53 2014 2014-08-04 DOSAT 3.8565102955 + #> 6585 2054 3F CC53 2014 2014-08-04 NO23 -2.7030626596 #> 6586 2054 3F CC53 2014 2014-08-04 SALIN -1.8971199849 #> 6587 2054 3F CC53 2014 2014-08-04 TKN 0.4054651081 #> 6588 2054 3F CC53 2014 2014-08-04 TN 0.4491629634 + #> 6589 2054 3F CC53 2014 2014-08-04 TP -1.6607312068 #> 6590 2054 3F CC53 2014 2014-08-04 TURB 1.2237754316 #> 6591 2054 3F CC53 2014 2014-09-08 CHLAC 0.5877866649 #> 6592 2054 3F CC53 2014 2014-09-08 COLOR 4.4998096703 #> 6593 2054 3F CC53 2014 2014-09-08 DO 1.2527629685 #> 6594 2054 3F CC53 2014 2014-09-08 DOSAT 3.7887247891 + #> 6595 2054 3F CC53 2014 2014-09-08 NO23 -3.9120230054 #> 6596 2054 3F CC53 2014 2014-09-08 TKN -0.1984509387 #> 6597 2054 3F CC53 2014 2014-09-08 TN -0.1743533871 + #> 6598 2054 3F CC53 2014 2014-09-08 TP -2.6036901858 #> 6599 2054 3F CC53 2014 2014-09-08 TURB 0.6418538862 #> 6600 2054 3F CC53 2014 2014-10-06 CHLAC 0.5306282511 I #> 6601 2054 3F CC53 2014 2014-10-06 COLOR 4.6051701860 A #> 6602 2054 3F CC53 2014 2014-10-06 DO 1.3083328197 #> 6603 2054 3F CC53 2014 2014-10-06 DOSAT 3.7932394694 + #> 6604 2054 3F CC53 2014 2014-10-06 NO23 -3.8167128256 #> 6605 2054 3F CC53 2014 2014-10-06 TKN -0.0833816089 #> 6606 2054 3F CC53 2014 2014-10-06 TN -0.0597500044 + #> 6607 2054 3F CC53 2014 2014-10-06 TP -2.2072749132 #> 6608 2054 3F CC53 2014 2014-10-06 TURB 0.5306282511 A #> 6609 2054 3F CC53 2014 2014-11-03 CHLAC 2.0149030205 #> 6610 2054 3F CC53 2014 2014-11-03 COLOR 4.2046926194 A #> 6611 2054 3F CC53 2014 2014-11-03 DOSAT 4.4841318576 + #> 6612 2054 3F CC53 2014 2014-11-03 NO23 -2.3538783874 #> 6613 2054 3F CC53 2014 2014-11-03 SALIN -1.6094379124 #> 6614 2054 3F CC53 2014 2014-11-03 TKN -0.0725706928 #> 6615 2054 3F CC53 2014 2014-11-03 TN 0.0246926126 + #> 6616 2054 3F CC53 2014 2014-11-03 TP -2.3025850930 #> 6617 2054 3F CC53 2014 2014-11-03 TURB 0.9555114450 #> 6618 2054 3F CC53 2014 2014-12-01 CHLAC 3.2580965380 #> 6619 2054 3F CC53 2014 2014-12-01 COLOR 4.2626798770 #> 6620 2054 3F CC53 2014 2014-12-01 DO 1.7578579176 #> 6621 2054 3F 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3F CC53 2015 2015-02-02 SALIN -1.2039728043 #> 6640 2054 3F CC53 2015 2015-02-02 TKN -0.1625189295 #> 6641 2054 3F CC53 2015 2015-02-02 TN -0.1601687522 + #> 6642 2054 3F CC53 2015 2015-02-02 TP -2.2072749132 #> 6643 2054 3F CC53 2015 2015-02-02 TURB 1.0296194172 #> 6644 2054 3F CC53 2015 2015-03-02 CHLAC 2.7080502011 #> 6645 2054 3F CC53 2015 2015-03-02 COLOR 3.8712010109 #> 6646 2054 3F CC53 2015 2015-03-02 DO 1.9169226122 #> 6647 2054 3F CC53 2015 2015-03-02 DOSAT 4.3399017084 + #> 6648 2054 3F CC53 2015 2015-03-02 NO23 -3.9120230054 #> 6649 2054 3F CC53 2015 2015-03-02 TKN -0.1984509387 #> 6650 2054 3F CC53 2015 2015-03-02 TN -0.1743533871 + #> 6651 2054 3F CC53 2015 2015-03-02 TP -2.5770219387 #> 6652 2054 3F CC53 2015 2015-03-02 TURB 1.4109869737 #> 6653 2054 3F CC53 2015 2015-04-06 CHLAC 2.0412203289 #> 6654 2054 3F CC53 2015 2015-04-06 COLOR 4.1431347264 #> 6655 2054 3F CC53 2015 2015-04-06 DO 1.5260563035 #> 6656 2054 3F CC53 2015 2015-04-06 DOSAT 4.0018637094 + #> 6657 2054 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2054 3F CC53 2016 2016-01-04 TURB 0.7419373447 #> 6730 2054 3F CC53 2016 2016-02-01 CHLAC -0.1984509387 U #> 6731 2054 3F CC53 2016 2016-02-01 COLOR 4.5432947823 #> 6732 2054 3F CC53 2016 2016-02-01 DO 1.9974177062 #> 6733 2054 3F CC53 2016 2016-02-01 DOSAT 4.3630986248 + #> 6734 2054 3F CC53 2016 2016-02-01 NO23 -5.5214609179 I #> 6735 2054 3F CC53 2016 2016-02-01 SALIN -3.5065578973 #> 6736 2054 3F CC53 2016 2016-02-01 TKN -0.6161861394 #> 6737 2054 3F CC53 2016 2016-02-01 TN -0.6088060321 + #> 6738 2054 3F CC53 2016 2016-02-01 TP -2.6592600369 #> 6739 2054 3F CC53 2016 2016-02-01 TURB 0.5877866649 A #> 6740 2054 3F CC53 2016 2016-03-07 CHLAC 0.4054651081 I #> 6741 2054 3F CC53 2016 2016-03-07 COLOR 4.3174881135 #> 6742 2054 3F CC53 2016 2016-03-07 DO 1.6074359098 #> 6743 2054 3F CC53 2016 2016-03-07 DOSAT 4.0127729085 + #> 6744 2054 3F CC53 2016 2016-03-07 NO23 -3.6119184130 #> 6745 2054 3F CC53 2016 2016-03-07 SALIN -2.3025850930 #> 6746 2054 3F CC53 2016 2016-03-07 TKN -0.3147107448 #> 6747 2054 3F CC53 2016 2016-03-07 TN -0.2783920255 + #> 6748 2054 3F CC53 2016 2016-03-07 TP -2.9004220937 #> 6749 2054 3F CC53 2016 2016-03-07 TURB 0.5306282511 A #> 6750 2054 3F CC53 2016 2016-04-04 CHLAC 2.0149030205 #> 6751 2054 3F CC53 2016 2016-04-04 COLOR 4.0604430105 #> 6752 2054 3F CC53 2016 2016-04-04 DO 1.5454325825 #> 6753 2054 3F CC53 2016 2016-04-04 DOSAT 4.0253516907 + #> 6754 2054 3F CC53 2016 2016-04-04 NO23 -3.7722610631 #> 6755 2054 3F CC53 2016 2016-04-04 SALIN -1.3093333200 #> 6756 2054 3F CC53 2016 2016-04-04 TKN -0.1984509387 #> 6757 2054 3F CC53 2016 2016-04-04 TN -0.1707883210 + #> 6758 2054 3F CC53 2016 2016-04-04 TP -2.3330443005 #> 6759 2054 3F CC53 2016 2016-04-04 TURB 1.2527629685 #> 6760 2054 3F CC53 2016 2016-05-02 CHLAC 1.0647107370 #> 6761 2054 3F CC53 2016 2016-05-02 COLOR 4.1588830834 #> 6762 2054 3F CC53 2016 2016-05-02 DO 1.3164082337 #> 6763 2054 3F CC53 2016 2016-05-02 DOSAT 3.8372994592 + #> 6764 2054 3F CC53 2016 2016-05-02 NO23 -5.5214609179 U #> 6765 2054 3F CC53 2016 2016-05-02 SALIN 0.3220834992 #> 6766 2054 3F CC53 2016 2016-05-02 TKN -0.2107210313 #> 6767 2054 3F CC53 2016 2016-05-02 TN -0.2082549388 + #> 6768 2054 3F CC53 2016 2016-05-02 TP -2.0402208285 #> 6769 2054 3F CC53 2016 2016-05-02 TURB 0.1823215568 #> 6770 2054 3F CC53 2016 2016-06-06 CHLAC 2.2925347571 #> 6771 2054 3F CC53 2016 2016-06-06 COLOR 4.7004803658 #> 6772 2054 3F CC53 2016 2016-06-06 DO 0.9932517730 #> 6773 2054 3F CC53 2016 2016-06-06 DOSAT 3.5553480615 + #> 6774 2054 3F CC53 2016 2016-06-06 NO23 -3.8167128256 #> 6775 2054 3F CC53 2016 2016-06-06 TKN 0.2623642645 #> 6776 2054 3F CC53 2016 2016-06-06 TN 0.2791457414 + #> 6777 2054 3F CC53 2016 2016-06-06 TP -1.6607312068 #> 6778 2054 3F CC53 2016 2016-06-06 TURB 0.9555114450 #> 6779 2054 3F CC53 2016 2016-07-05 CHLAC 1.4350845253 #> 6780 2054 3F CC53 2016 2016-07-05 COLOR 4.9416424226 #> 6781 2054 3F CC53 2016 2016-07-05 DOSAT 3.9100210028 + #> 6782 2054 3F CC53 2016 2016-07-05 NO23 -2.5770219387 #> 6783 2054 3F CC53 2016 2016-07-05 SALIN -1.5606477483 #> 6784 2054 3F CC53 2016 2016-07-05 TKN 0.0953101798 #> 6785 2054 3F CC53 2016 2016-07-05 TN 0.1621188495 + #> 6786 2054 3F CC53 2016 2016-07-05 TP -1.7719568419 #> 6787 2054 3F CC53 2016 2016-07-05 TURB 0.9932517730 #> 6788 2054 3F CC53 2016 2016-08-01 CHLAC 0.6418538862 #> 6789 2054 3F CC53 2016 2016-08-01 COLOR 4.7004803658 #> 6790 2054 3F CC53 2016 2016-08-01 DO 1.0331844833 #> 6791 2054 3F CC53 2016 2016-08-01 DOSAT 3.6189933266 + #> 6792 2054 3F CC53 2016 2016-08-01 NO23 -3.8632328413 #> 6793 2054 3F CC53 2016 2016-08-01 SALIN -2.6592600369 #> 6794 2054 3F CC53 2016 2016-08-01 TKN -0.1984509387 #> 6795 2054 3F CC53 2016 2016-08-01 TN -0.1731636190 + #> 6796 2054 3F CC53 2016 2016-08-01 TP -2.0402208285 #> 6797 2054 3F CC53 2016 2016-08-01 TURB 0.5306282511 #> 6798 2054 3F CC53 2016 2016-10-03 CHLAC 0.9555114450 #> 6799 2054 3F CC53 2016 2016-10-03 COLOR 4.5217885770 #> 6800 2054 3F CC53 2016 2016-10-03 DO 1.2612978709 #> 6801 2054 3F CC53 2016 2016-10-03 DOSAT 3.7999735016 + #> 6802 2054 3F CC53 2016 2016-10-03 NO23 -3.8167128256 #> 6803 2054 3F CC53 2016 2016-10-03 SALIN -2.2072749132 #> 6804 2054 3F CC53 2016 2016-10-03 TKN 0.0953101798 #> 6805 2054 3F CC53 2016 2016-10-03 TN 0.1151128071 + #> 6806 2054 3F CC53 2016 2016-10-03 TP -2.3644604967 #> 6807 2054 3F CC53 2016 2016-10-03 TURB 0.7419373447 #> 6808 2054 3F CC53 2016 2016-11-07 CHLAC 2.1041341543 #> 6809 2054 3F CC53 2016 2016-11-07 COLOR 4.2341065046 #> 6810 2054 3F CC53 2016 2016-11-07 DO 2.2544447177 #> 6811 2054 3F CC53 2016 2016-11-07 DOSAT 4.7202829931 + #> 6812 2054 3F CC53 2016 2016-11-07 NO23 -3.2968373663 #> 6813 2054 3F CC53 2016 2016-11-07 SALIN -1.1086626245 #> 6814 2054 3F CC53 2016 2016-11-07 TKN 0.0000000000 #> 6815 2054 3F CC53 2016 2016-11-07 TN 0.0363319292 + #> 6816 2054 3F CC53 2016 2016-11-07 TP -2.4191189092 #> 6817 2054 3F CC53 2016 2016-11-07 TURB 0.9555114450 #> 6818 2054 3F CC53 2016 2016-12-05 CHLAC 2.4849066498 #> 6819 2054 3F CC53 2016 2016-12-05 COLOR 3.9702919136 #> 6820 2054 3F CC53 2016 2016-12-05 DO 1.5518087996 #> 6821 2054 3F CC53 2016 2016-12-05 DOSAT 4.0306945351 + #> 6822 2054 3F CC53 2016 2016-12-05 NO23 -4.6051701860 #> 6823 2054 3F CC53 2016 2016-12-05 SALIN 1.5706970841 #> 6824 2054 3F CC53 2016 2016-12-05 TKN 0.0000000000 #> 6825 2054 3F CC53 2016 2016-12-05 TN 0.0099503309 + #> 6826 2054 3F CC53 2016 2016-12-05 TP -1.8325814637 #> 6827 2054 3F CC53 2016 2016-12-05 TURB 1.3350010667 A #> 6828 2054 3F CC53 2017 2017-01-03 CHLAC 2.1633230257 #> 6829 2054 3F CC53 2017 2017-01-03 COLOR 3.7841896339 A #> 6830 2054 3F CC53 2017 2017-01-03 DO 1.5892352051 #> 6831 2054 3F CC53 2017 2017-01-03 DOSAT 4.0638853547 + #> 6832 2054 3F CC53 2017 2017-01-03 NO23 -5.1159958098 I #> 6833 2054 3F CC53 2017 2017-01-03 SALIN 1.8405496334 #> 6834 2054 3F CC53 2017 2017-01-03 TKN -0.3710636814 #> 6835 2054 3F CC53 2017 2017-01-03 TN -0.3652833185 + #> 6836 2054 3F CC53 2017 2017-01-03 TP -1.9661128564 #> 6837 2054 3F CC53 2017 2017-01-03 TURB 0.9555114450 #> 6838 2054 3F CC53 2017 2017-02-06 CHLAC 1.7047480922 #> 6839 2054 3F CC53 2017 2017-02-06 COLOR 3.6635616461 #> 6840 2054 3F CC53 2017 2017-02-06 DO 1.3609765531 #> 6841 2054 3F CC53 2017 2017-02-06 DOSAT 3.7819143201 + #> 6842 2054 3F CC53 2017 2017-02-06 NO23 -2.6310891600 #> 6843 2054 3F CC53 2017 2017-02-06 SALIN 1.2527629685 #> 6844 2054 3F CC53 2017 2017-02-06 TKN -0.2876820725 #> 6845 2054 3F CC53 2017 2017-02-06 TN -0.1960148839 + #> 6846 2054 3F CC53 2017 2017-02-06 TP -2.1202635362 #> 6847 2054 3F CC53 2017 2017-02-06 TURB 1.1939224685 A #> 6848 2054 3F CC53 2017 2017-03-06 CHLAC 1.0986122887 #> 6849 2054 3F CC53 2017 2017-03-06 COLOR 3.7135720667 #> 6850 2054 3F CC53 2017 2017-03-06 DO 1.5789787049 #> 6851 2054 3F CC53 2017 2017-03-06 DOSAT 4.0145795938 + #> 6852 2054 3F CC53 2017 2017-03-06 NO23 -2.5770219387 #> 6853 2054 3F CC53 2017 2017-03-06 SALIN 1.4445632692 #> 6854 2054 3F CC53 2017 2017-03-06 TKN -0.3856624808 #> 6855 2054 3F CC53 2017 2017-03-06 TN -0.2797139028 + #> 6856 2054 3F CC53 2017 2017-03-06 TP -1.6094379124 #> 6857 2054 3F CC53 2017 2017-03-06 TURB 0.9932517730 #> 6858 2054 3F CC53 2017 2017-04-03 CHLAC 2.0149030205 #> 6859 2054 3F CC53 2017 2017-04-03 COLOR 3.8286413965 #> 6860 2054 3F CC53 2017 2017-04-03 DO 1.0612565021 #> 6861 2054 3F CC53 2017 2017-04-03 DOSAT 3.6163087613 + #> 6862 2054 3F CC53 2017 2017-04-03 NO23 -3.4112477175 #> 6863 2054 3F CC53 2017 2017-04-03 SALIN 2.1610215287 #> 6864 2054 3F CC53 2017 2017-04-03 TKN -0.0725706928 #> 6865 2054 3F CC53 2017 2017-04-03 TN -0.0377018672 + #> 6866 2054 3F CC53 2017 2017-04-03 TP -1.4271163556 #> 6867 2054 3F CC53 2017 2017-04-03 TURB 1.0296194172 A #> 6868 2054 3F CC53 2017 2017-05-01 CHLAC 2.2512917986 #> 6869 2054 3F CC53 2017 2017-05-01 COLOR 4.0253516907 A #> 6870 2054 3F CC53 2017 2017-05-01 DO 1.1817271954 #> 6871 2054 3F CC53 2017 2017-05-01 DOSAT 3.7796338174 + #> 6872 2054 3F CC53 2017 2017-05-01 NO23 -4.7105307016 I #> 6873 2054 3F CC53 2017 2017-05-01 SALIN 2.6049094422 #> 6874 2054 3F CC53 2017 2017-05-01 TKN 0.5306282511 #> 6875 2054 3F CC53 2017 2017-05-01 TN 0.5329784284 + #> 6876 2054 3F CC53 2017 2017-05-01 TP -1.5141277326 #> 6877 2054 3F CC53 2017 2017-05-01 TURB 0.7884573604 #> 6878 2054 3F CC53 2017 2017-06-05 COLOR 4.0430512678 A #> 6879 2054 3F CC53 2017 2017-06-05 NO23 -4.0173835211 #> 6880 2054 3F CC53 2017 2017-06-05 TKN 0.0000000000 #> 6881 2054 3F CC53 2017 2017-06-05 TN 0.0178399181 + #> 6882 2054 3F CC53 2017 2017-06-05 TP -1.2378743560 #> 6883 2054 3F CC53 2017 2017-07-10 CHLAC 1.0986122887 #> 6884 2054 3F CC53 2017 2017-07-10 COLOR 5.2983173665 #> 6885 2054 3F CC53 2017 2017-07-10 DO 0.8020015855 #> 6886 2054 3F CC53 2017 2017-07-10 DOSAT 3.3707381742 + #> 6887 2054 3F CC53 2017 2017-07-10 NO23 -1.9661128564 #> 6888 2054 3F CC53 2017 2017-07-10 SALIN -1.2378743560 #> 6889 2054 3F CC53 2017 2017-07-10 TKN 0.3364722366 #> 6890 2054 3F CC53 2017 2017-07-10 TN 0.4317824164 + #> 6891 2054 3F CC53 2017 2017-07-10 TP -1.4696759701 #> 6892 2054 3F CC53 2017 2017-07-10 TURB 1.1939224685 #> 6893 2054 3F CC53 2017 2017-11-06 CHLAC 1.8870696490 #> 6894 2054 3F CC53 2017 2017-11-06 COLOR 4.9416424226 #> 6895 2054 3F CC53 2017 2017-11-06 DO 1.5973653312 #> 6896 2054 3F CC53 2017 2017-11-06 DOSAT 4.0621656639 #> 6897 2054 3F CC53 2017 2017-11-06 NO23 -1.3470736480 #> 6898 2054 3F CC53 2017 2017-11-06 SALIN -1.4696759701 #> 6899 2054 3F CC53 2017 2017-11-06 TKN 0.0953101798 #> 6900 2054 3F CC53 2017 2017-11-06 TN 0.3074846997 + #> 6901 2054 3F CC53 2017 2017-11-06 TP -2.0402208285 #> 6902 2054 3F CC53 2017 2017-11-06 TURB 1.3609765531 #> 6903 2054 3F CC53 2017 2017-12-04 CHLAC 2.7080502011 #> 6904 2054 3F CC53 2017 2017-12-04 COLOR 4.2341065046 #> 6905 2054 3F CC53 2017 2017-12-04 DO 1.7422190237 #> 6906 2054 3F CC53 2017 2017-12-04 DOSAT 4.1759245492 #> 6907 2054 3F CC53 2017 2017-12-04 NO23 -1.6094379124 #> 6908 2054 3F CC53 2017 2017-12-04 SALIN -0.7133498879 #> 6909 2054 3F CC53 2017 2017-12-04 TKN -0.0202027073 #> 6910 2054 3F CC53 2017 2017-12-04 TN 0.1655144385 + #> 6911 2054 3F CC53 2017 2017-12-04 TP -2.0402208285 #> 6912 2054 3F CC53 2017 2017-12-04 TURB 1.2809338455 A #> 6913 2054 3F CC53 2018 2018-01-02 CHLAC 3.2188758249 #> 6914 2054 3F CC53 2018 2018-01-02 COLOR 4.0253516907 #> 6915 2054 3F CC53 2018 2018-01-02 DO 1.7298840655 #> 6916 2054 3F CC53 2018 2018-01-02 DOSAT 4.0758410907 + #> 6917 2054 3F CC53 2018 2018-01-02 NO23 -2.0402208285 #> 6918 2054 3F CC53 2018 2018-01-02 SALIN -0.8915981193 #> 6919 2054 3F CC53 2018 2018-01-02 TKN 0.0000000000 #> 6920 2054 3F CC53 2018 2018-01-02 TN 0.1222176327 + #> 6921 2054 3F CC53 2018 2018-01-02 TP -1.9661128564 #> 6922 2054 3F CC53 2018 2018-01-02 TURB 1.8245492921 #> 6923 2054 3F CC53 2018 2018-02-05 CHLAC 3.5263605246 #> 6924 2054 3F CC53 2018 2018-02-05 COLOR 4.2484952420 #> 6925 2054 3F CC53 2018 2018-02-05 DO 1.9712993831 #> 6926 2054 3F CC53 2018 2018-02-05 DOSAT 4.3681812279 #> 6927 2054 3F CC53 2018 2018-02-05 NO23 -0.9416085399 #> 6928 2054 3F CC53 2018 2018-02-05 SALIN -0.9416085399 #> 6929 2054 3F CC53 2018 2018-02-05 TKN 0.1823215568 #> 6930 2054 3F CC53 2018 2018-02-05 TN 0.4637340162 + #> 6931 2054 3F CC53 2018 2018-02-05 TP -1.7719568419 #> 6932 2054 3F CC53 2018 2018-02-05 TURB 1.8870696490 #> 6933 2054 3F CC53 2018 2018-05-07 CHLAC 2.6390573296 #> 6934 2054 3F CC53 2018 2018-05-07 COLOR 3.9318256327 #> 6935 2054 3F CC53 2018 2018-05-07 DO 1.3217558400 #> 6936 2054 3F CC53 2018 2018-05-07 DOSAT 3.8877303129 #> 6937 2054 3F CC53 2018 2018-05-07 NO23 -5.1159958098 I #> 6938 2054 3F CC53 2018 2018-05-07 SALIN 1.9974177062 #> 6939 2054 3F CC53 2018 2018-05-07 TKN -0.0100503359 #> 6940 2054 3F CC53 2018 2018-05-07 TN -0.0060180723 + #> 6941 2054 3F CC53 2018 2018-05-07 TP -1.3862943611 #> 6942 2054 3F CC53 2018 2018-05-07 TURB 1.1939224685 #> 6943 2054 3F CC53 2018 2018-07-09 CHLAC 0.9162907319 #> 6944 2054 3F CC53 2018 2018-07-09 COLOR 5.0106352941 #> 6945 2054 3F CC53 2018 2018-07-09 DO 1.3532545070 #> 6946 2054 3F CC53 2018 2018-07-09 DOSAT 3.9435216725 #> 6947 2054 3F CC53 2018 2018-07-09 NO23 -4.3428059215 #> 6948 2054 3F CC53 2018 2018-07-09 SALIN -3.2188758249 #> 6949 2054 3F CC53 2018 2018-07-09 TKN 0.0953101798 #> 6950 2054 3F CC53 2018 2018-07-09 TN 0.1070590723 + #> 6951 2054 3F CC53 2018 2018-07-09 TP -2.5510464523 #> 6952 2054 3F CC53 2018 2018-07-09 TURB 0.9555114450 #> 6953 2054 3F CC53 2019 2019-02-04 CHLAC 1.2527629685 #> 6954 2054 3F CC53 2019 2019-02-04 COLOR 4.2766661190 #> 6955 2054 3F CC53 2019 2019-02-04 DO 1.7011051010 #> 6956 2054 3F CC53 2019 2019-02-04 DOSAT 4.0976723523 #> 6957 2054 3F CC53 2019 2019-02-04 NO23 -0.8439700703 #> 6958 2054 3F CC53 2019 2019-02-04 SALIN -1.1394342832 #> 6959 2054 3F CC53 2019 2019-02-04 TKN 0.2623642645 #> 6960 2054 3F CC53 2019 2019-02-04 TN 0.5481214085 + #> 6961 2054 3F CC53 2019 2019-02-04 TP -2.0402208285 #> 6962 2054 3F CC53 2019 2019-02-04 TURB 1.4350845253 #> 6963 2054 3F CC53 2019 2019-03-04 CHLAC 3.4657359028 #> 6964 2054 3F CC53 2019 2019-03-04 COLOR 4.3040650932 #> 6965 2054 3F CC53 2019 2019-03-04 DO 1.8115620965 #> 6966 2054 3F CC53 2019 2019-03-04 DOSAT 4.2986450257 #> 6967 2054 3F CC53 2019 2019-03-04 NO23 -2.9759296463 #> 6968 2054 3F CC53 2019 2019-03-04 SALIN -1.1711829815 #> 6969 2054 3F CC53 2019 2019-03-04 TKN 0.1823215568 #> 6970 2054 3F CC53 2019 2019-03-04 TN 0.2239432315 + #> 6971 2054 3F CC53 2019 2019-03-04 TP -2.2072749132 #> 6972 2054 3F CC53 2019 2019-03-04 TURB 2.0918640617 #> 6973 2054 3F CC53 2019 2019-04-01 CHLAC 2.0794415417 #> 6974 2054 3F CC53 2019 2019-04-01 COLOR 4.1896547420 #> 6975 2054 3F CC53 2019 2019-04-01 DO 1.6074359098 #> 6976 2054 3F CC53 2019 2019-04-01 DOSAT 4.0775374439 #> 6977 2054 3F CC53 2019 2019-04-01 NO23 -4.8283137373 I #> 6978 2054 3F CC53 2019 2019-04-01 SALIN -0.9675840263 #> 6979 2054 3F CC53 2019 2019-04-01 TKN 0.0000000000 #> 6980 2054 3F CC53 2019 2019-04-01 TN 0.0039920213 + #> 6981 2054 3F CC53 2019 2019-04-01 TP -2.3434070875 #> 6982 2054 3F CC53 2019 2019-04-01 TURB 1.0986122887 #> 6983 2054 3F CC53 2019 2019-05-06 CHLAC 2.1400661635 #> 6984 2054 3F CC53 2019 2019-05-06 COLOR 4.2046926194 A #> 6985 2054 3F CC53 2019 2019-05-06 DO 1.4182774070 #> 6986 2054 3F CC53 2019 2019-05-06 DOSAT 3.9608131696 #> 6987 2054 3F CC53 2019 2019-05-06 NO23 -4.8283137373 I #> 6988 2054 3F CC53 2019 2019-05-06 SALIN 0.7371640660 #> 6989 2054 3F CC53 2019 2019-05-06 TKN 0.0953101798 #> 6990 2054 3F CC53 2019 2019-05-06 TN 0.0989399479 + #> 6991 2054 3F CC53 2019 2019-05-06 TP -1.8325814637 #> 6992 2054 3F CC53 2019 2019-05-06 TURB 1.0647107370 #> 6993 2054 3F CC53 2019 2019-08-05 CHLAC 0.4700036292 I #> 6994 2054 3F CC53 2019 2019-08-05 COLOR 5.3936275464 #> 6995 2054 3F CC53 2019 2019-08-05 DO 1.2383742310 #> 6996 2054 3F CC53 2019 2019-08-05 DOSAT 3.7750571504 #> 6997 2054 3F CC53 2019 2019-08-05 NO23 -2.3859667019 #> 6998 2054 3F CC53 2019 2019-08-05 SALIN -1.7719568419 #> 6999 2054 3F CC53 2019 2019-08-05 TKN 0.4700036292 #> 7000 2054 3F CC53 2019 2019-08-05 TN 0.5259112612 + #> 7001 2054 3F CC53 2019 2019-08-05 TP -1.3862943611 #> 7002 2054 3F CC53 2019 2019-08-05 TURB 0.9162907319 #> 7003 2054 3F CC53 2020 2020-01-06 CHLAC 1.8405496334 #> 7004 2054 3F CC53 2020 2020-01-06 COLOR 3.8712010109 A #> 7005 2054 3F CC53 2020 2020-01-06 DO 1.7439688054 #> 7006 2054 3F CC53 2020 2020-01-06 DOSAT 4.1255201797 #> 7007 2054 3F CC53 2020 2020-01-06 NO23 -2.8824035882 #> 7008 2054 3F CC53 2020 2020-01-06 SALIN -0.5276327421 #> 7009 2054 3F CC53 2020 2020-01-06 TKN -0.4155154440 #> 7010 2054 3F CC53 2020 2020-01-06 TN -0.3340751120 + #> 7011 2054 3F CC53 2020 2020-01-06 TP -2.3644604967 #> 7012 2054 3F CC53 2020 2020-01-06 TURB 0.7884573604 #> 7013 2054 3F CC53 2020 2020-02-03 CHLAC 1.6292405397 #> 7014 2054 3F CC53 2020 2020-02-03 COLOR 3.7612001157 #> 7015 2054 3F CC53 2020 2020-02-03 DO 1.6808279085 #> 7016 2054 3F CC53 2020 2020-02-03 DOSAT 4.0395363257 #> 7017 2054 3F CC53 2020 2020-02-03 NO23 -2.6450754019 #> 7018 2054 3F CC53 2020 2020-02-03 SALIN -0.1053605157 #> 7019 2054 3F CC53 2020 2020-02-03 TKN -0.2613647641 #> 7020 2054 3F CC53 2020 2020-02-03 TN -0.1731636190 + #> 7021 2054 3F CC53 2020 2020-02-03 TP -2.2072749132 #> 7022 2054 3F CC53 2020 2020-02-03 TURB 0.7419373447 #> 7023 2054 3F CC53 2020 2020-03-02 CHLAC 2.7080502011 #> 7024 2054 3F CC53 2020 2020-03-02 COLOR 3.8501476017 #> 7025 2054 3F CC53 2020 2020-03-02 DO 1.9657127764 #> 7026 2054 3F CC53 2020 2020-03-02 DOSAT 4.3451032806 #> 7027 2054 3F CC53 2020 2020-03-02 NO23 -5.5214609179 U #> 7028 2054 3F CC53 2020 2020-03-02 SALIN -0.5621189182 #> 7029 2054 3F CC53 2020 2020-03-02 TKN 0.0000000000 #> 7030 2054 3F CC53 2020 2020-03-02 TN 0.0019980027 + #> 7031 2054 3F CC53 2020 2020-03-02 TP -1.9661128564 #> 7032 2054 3F CC53 2020 2020-03-02 TURB 1.4816045409 A #> 7033 2054 3F CC53 2020 2020-09-08 CHLAC 0.8754687374 I #> 7034 2054 3F CC53 2020 2020-09-08 COLOR 5.5214609179 #> 7035 2054 3F CC53 2020 2020-09-08 DO 1.5325568681 #> 7036 2054 3F CC53 2020 2020-09-08 DOSAT 4.0621656639 #> 7037 2054 3F CC53 2020 2020-09-08 NO23 -2.3025850930 #> 7038 2054 3F CC53 2020 2020-09-08 SALIN -1.5141277326 #> 7039 2054 3F CC53 2020 2020-09-08 TKN 0.4700036292 #> 7040 2054 3F CC53 2020 2020-09-08 TN 0.5306282511 + #> 7041 2054 3F CC53 2020 2020-09-08 TP -1.0498221245 #> 7042 2054 3F CC53 2020 2020-09-08 TURB 0.8754687374 #> 7043 2054 3F CC53 2020 2020-09-08 CHLAC 0.8754687374 I #> 7044 2054 3F CC53 2020 2020-09-08 COLOR 5.5214609179 #> 7045 2054 3F CC53 2020 2020-09-08 NO23 -2.3025850930 #> 7046 2054 3F CC53 2020 2020-09-08 TKN 0.4054651081 #> 7047 2054 3F CC53 2020 2020-09-08 TN 0.4700036292 + #> 7048 2054 3F CC53 2020 2020-09-08 TP -1.0788096614 #> 7049 2054 3F CC53 2020 2020-09-08 TURB 0.8754687374 #> 7050 2054 3F CC53 2020 2020-12-07 CHLAC 2.1747517215 #> 7051 2054 3F CC53 2020 2020-12-07 COLOR 4.7874917428 #> 7052 2054 3F CC53 2020 2020-12-07 DO 1.9344157696 #> 7053 2054 3F CC53 2020 2020-12-07 DOSAT 4.3280982926 #> 7054 2054 3F CC53 2020 2020-12-07 NO23 -1.8971199849 #> 7055 2054 3F CC53 2020 2020-12-07 SALIN -1.3470736480 #> 7056 2054 3F CC53 2020 2020-12-07 TKN 0.1823215568 #> 7057 2054 3F CC53 2020 2020-12-07 TN 0.3001045925 + #> 7058 2054 3F CC53 2020 2020-12-07 TP -2.0402208285 #> 7059 2054 3F CC53 2020 2020-12-07 TURB 0.8754687374 #> 7060 2054 3F CC53 2021 2021-01-04 CHLAC 1.6863989536 #> 7061 2054 3F CC53 2021 2021-01-04 COLOR 4.4773368145 A #> 7062 2054 3F CC53 2021 2021-01-04 DO 1.7766458314 #> 7063 2054 3F CC53 2021 2021-01-04 DOSAT 4.1866198383 #> 7064 2054 3F CC53 2021 2021-01-04 NO23 -2.2072749132 #> 7065 2054 3F CC53 2021 2021-01-04 SALIN -1.3470736480 #> 7066 2054 3F CC53 2021 2021-01-04 TN 0.1906203596 + #> 7067 2054 3F CC53 2021 2021-01-04 TP -2.3025850930 #> 7068 2054 3F CC53 2021 2021-01-04 TURB 0.9932517730 #> 7069 2054 3F CC53 2021 2021-02-01 CHLAC 2.6390573296 #> 7070 2054 3F CC53 2021 2021-02-01 COLOR 4.2046926194 A #> 7071 2054 3F CC53 2021 2021-02-01 DO 1.8779371655 #> 7072 2054 3F CC53 2021 2021-02-01 DOSAT 4.2822062994 #> 7073 2054 3F CC53 2021 2021-02-01 NO23 -5.5214609179 U #> 7074 2054 3F CC53 2021 2021-02-01 SALIN 0.1739533071 #> 7075 2054 3F CC53 2021 2021-02-01 TKN -0.0408219945 #> 7076 2054 3F CC53 2021 2021-02-01 TN -0.0387408283 + #> 7077 2054 3F CC53 2021 2021-02-01 TP -2.0402208285 #> 7078 2054 3F CC53 2021 2021-02-01 TURB 1.4350845253 A #> 7079 2054 3F CC53 2021 2021-03-01 CHLAC 2.6390573296 #> 7080 2054 3F CC53 2021 2021-03-01 COLOR 4.0604430105 #> 7081 2054 3F CC53 2021 2021-03-01 DO 1.7369512327 #> 7082 2054 3F CC53 2021 2021-03-01 DOSAT 4.2239097666 #> 7083 2054 3F CC53 2021 2021-03-01 NO23 -5.5214609179 U #> 7084 2054 3F CC53 2021 2021-03-01 SALIN -0.5108256238 #> 7085 2054 3F CC53 2021 2021-03-01 TKN 0.0953101798 #> 7086 2054 3F CC53 2021 2021-03-01 TN 0.0971267107 + #> 7087 2054 3F CC53 2021 2021-03-01 TP -2.0402208285 #> 7088 2054 3F CC53 2021 2021-03-01 TURB 1.2237754316 #> 7089 2054 3F CC53 2021 2021-04-05 CHLAC 1.7047480922 #> 7090 2054 3F CC53 2021 2021-04-05 COLOR 3.9889840466 A #> 7091 2054 3F CC53 2021 2021-04-05 NO23 -5.5214609179 I #> 7092 2054 3F CC53 2021 2021-04-05 SALIN 0.9122827105 #> 7093 2054 3F CC53 2021 2021-04-05 TKN -0.2484613593 #> 7094 2054 3F CC53 2021 2021-04-05 TN -0.2433462586 + #> 7095 2054 3F CC53 2021 2021-04-05 TP -1.8971199849 #> 7096 2054 3F CC53 2021 2021-04-05 TURB 0.8754687374 #> 7097 2054 3F CC53 2021 2021-05-03 CHLAC 1.4350845253 #> 7098 2054 3F CC53 2021 2021-05-03 COLOR 3.9702919136 A #> 7099 2054 3F CC53 2021 2021-05-03 DO 1.0438040522 #> 7100 2054 3F CC53 2021 2021-05-03 DOSAT 3.2771447330 #> 7101 2054 3F CC53 2021 2021-05-03 NO23 -3.7297014486 #> 7102 2054 3F CC53 2021 2021-05-03 SALIN 0.9042181506 #> 7103 2054 3F CC53 2021 2021-05-03 TKN -0.1625189295 #> 7104 2054 3F CC53 2021 2021-05-03 TN -0.1346749033 + #> 7105 2054 3F CC53 2021 2021-05-03 TP -1.6094379124 #> 7106 2054 3F 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2021 2021-10-04 SALIN -2.0402208285 #> 7143 2054 3F CC53 2021 2021-10-04 TKN -0.0725706928 #> 7144 2054 3F CC53 2021 2021-10-04 TN -0.0151136378 + #> 7145 2054 3F CC53 2021 2021-10-04 TP -1.7719568419 #> 7146 2054 3F CC53 2021 2021-10-04 TURB 0.7419373447 A #> 7147 2054 3F CC53 2021 2021-11-01 CHLAC 2.1282317058 #> 7148 2054 3F CC53 2021 2021-11-01 COLOR 4.2766661190 #> 7149 2054 3F CC53 2021 2021-11-01 DO 1.0681530812 #> 7150 2054 3F CC53 2021 2021-11-01 DOSAT 3.5322256441 #> 7151 2054 3F CC53 2021 2021-11-01 NO23 -2.6450754019 #> 7152 2054 3F CC53 2021 2021-11-01 SALIN -1.4696759701 #> 7153 2054 3F CC53 2021 2021-11-01 TKN -0.0304592075 #> 7154 2054 3F CC53 2021 2021-11-01 TN 0.0401817896 + #> 7155 2054 3F CC53 2021 2021-11-01 TP -1.8971199849 #> 7156 2054 3F CC53 2021 2021-11-01 TURB 0.5306282511 #> 7157 2054 3F CC53 2021 2021-12-06 CHLAC 2.1282317058 #> 7158 2054 3F CC53 2021 2021-12-06 COLOR 4.3174881135 #> 7159 2054 3F CC53 2021 2021-12-06 NO23 -2.9957322736 #> 7160 2054 3F CC53 2021 2021-12-06 TKN 0.0953101798 #> 7161 2054 3F CC53 2021 2021-12-06 TN 0.1397619424 + #> 7162 2054 3F CC53 2021 2021-12-06 TP -2.3025850930 #> 7163 2054 3F CC53 2021 2021-12-06 TURB 0.7419373447 #> 7164 2054 3F CC53 2022 2022-01-03 CHLAC 1.2527629685 #> 7165 2054 3F CC53 2022 2022-01-03 COLOR 4.0943445622 A #> 7166 2054 3F CC53 2022 2022-01-03 DO 1.3402504226 #> 7167 2054 3F CC53 2022 2022-01-03 DOSAT 3.8286413965 #> 7168 2054 3F CC53 2022 2022-01-03 NO23 -4.1997050779 #> 7169 2054 3F CC53 2022 2022-01-03 SALIN 1.3376291891 #> 7170 2054 3F CC53 2022 2022-01-03 TKN -0.1053605157 #> 7171 2054 3F CC53 2022 2022-01-03 TN -0.0888312137 + #> 7172 2054 3F CC53 2022 2022-01-03 TP -1.7719568419 #> 7173 2054 3F CC53 2022 2022-01-03 TURB 0.6418538862 #> 7174 2054 3F CC53 2022 2022-02-07 CHLAC 2.2082744135 #> 7175 2054 3F CC53 2022 2022-02-07 COLOR 3.8286413965 #> 7176 2054 3F CC53 2022 2022-02-07 DO 1.7047480922 #> 7177 2054 3F CC53 2022 2022-02-07 DOSAT 4.1541845626 #> 7178 2054 3F CC53 2022 2022-02-07 NO23 -4.9618451299 I #> 7179 2054 3F CC53 2022 2022-02-07 SALIN 1.3270750015 #> 7180 2054 3F CC53 2022 2022-02-07 TKN -0.1863295782 #> 7181 2054 3F CC53 2022 2022-02-07 TN -0.1815218766 + #> 7182 2054 3F CC53 2022 2022-02-07 TP -1.8325814637 #> 7183 2054 3F CC53 2022 2022-02-07 TURB 1.2237754316 #> 7184 2054 3F CC53 2022 2022-03-07 CHLAC 2.3025850930 #> 7185 2054 3F CC53 2022 2022-03-07 COLOR 3.8066624898 A #> 7186 2054 3F CC53 2022 2022-03-07 NO23 -5.2983173665 I #> 7187 2054 3F CC53 2022 2022-03-07 TKN -0.1278333715 #> 7188 2054 3F CC53 2022 2022-03-07 TN -0.1232982163 + #> 7189 2054 3F CC53 2022 2022-03-07 TP -1.6094379124 #> 7190 2054 3F CC53 2022 2022-03-07 TURB 1.0296194172 #> 7191 2054 3F CC53 2022 2022-04-04 CHLAC 2.7725887222 #> 7192 2054 3F CC53 2022 2022-04-04 COLOR 3.9702919136 A #> 7193 2054 3F CC53 2022 2022-04-04 DO 1.1908875648 #> 7194 2054 3F CC53 2022 2022-04-04 DOSAT 3.7208625000 #> 7195 2054 3F CC53 2022 2022-04-04 NO23 -4.1997050779 #> 7196 2054 3F CC53 2022 2022-04-04 SALIN 2.1860512767 #> 7197 2054 3F CC53 2022 2022-04-04 TKN -0.3147107448 #> 7198 2054 3F CC53 2022 2022-04-04 TN -0.2943710606 + #> 7199 2054 3F CC53 2022 2022-04-04 TP -1.2378743560 #> 7200 2054 3F CC53 2022 2022-04-04 TURB 1.0296194172 #> 7201 2054 3F CC53 2022 2022-05-02 CHLAC 2.4849066498 #> 7202 2054 3F CC53 2022 2022-05-02 COLOR 4.0073331852 #> 7203 2054 3F CC53 2022 2022-05-02 NO23 -3.9120230054 #> 7204 2054 3F CC53 2022 2022-05-02 SALIN 2.5152741864 #> 7205 2054 3F CC53 2022 2022-05-02 TKN 0.0953101798 #> 7206 2054 3F CC53 2022 2022-05-02 TN 0.1133286853 + #> 7207 2054 3F CC53 2022 2022-05-02 TP -1.1394342832 #> 7208 2054 3F CC53 2022 2022-05-02 TURB 1.0986122887 #> 7209 2054 3F CC53 2014 2014-04-07 CHLAC 1.0986122887 #> 7210 2054 3F CC53 2014 2014-04-07 COLOR 5.0751738152 #> 7211 2054 3F CC53 2014 2014-04-07 COND 7.1701195434 #> 7212 2054 3F CC53 2014 2014-04-07 DO 1.7029282555 #> 7213 2054 3F CC53 2014 2014-04-07 DOSAT 4.0976723523 #> 7214 2054 3F CC53 2014 2014-04-07 NO23 -3.1700856607 #> 7215 2054 3F CC53 2014 2014-04-07 SALIN -0.3566749439 + #> 7216 2054 3F CC53 2014 2014-04-07 TKN 0.6418538862 #> 7217 2054 3F CC53 2014 2014-04-07 TN 0.6637183699 + #> 7218 2054 3F CC53 2014 2014-04-07 TP 0.0953101798 #> 7219 2054 3F CC53 2014 2014-04-07 TSS 2.9444389792 #> 7220 2054 3F CC53 2014 2014-04-07 TURB 2.7725887222 #> 7221 2054 3F CC53 2015 2015-05-21 COND 7.9291264873 #> 7222 2054 3F CC53 2015 2015-05-21 DO 1.4109869737 #> 7223 2054 3F CC53 2015 2015-05-21 DOSAT 3.9702919136 #> 7224 2054 3F CC53 2015 2015-05-21 SALIN 0.2851789422 + #> 7225 2054 3F CC53 2015 2015-07-15 COND 6.5439118456 #> 7226 2054 3F CC53 2015 2015-07-15 COND 6.5453496603 #> 7227 2054 3F CC53 2015 2015-07-15 SALIN -1.1711829815 + #> 7228 2054 3F CC53 2015 2015-08-06 COND 4.9052747784 #> 7229 2054 3F CC53 2015 2015-08-06 DO 1.4109869737 #> 7230 2054 3F CC53 2015 2015-08-06 DOSAT 3.9702919136 #> 7231 2054 3F CC53 2015 2015-08-19 COND 4.8751973232 #> 7232 2054 3F CC53 2015 2015-08-19 DO 1.2527629685 #> 7233 2054 3F CC53 2015 2015-08-19 DOSAT 3.8501476017 #> 7234 2054 3F CC53 2015 2015-09-15 COND 5.4764635519 #> 7235 2054 3F CC53 2015 2015-09-15 DO 1.1314021115 #> 7236 2054 3F CC53 2015 2015-09-15 DOSAT 3.6888794541 #> 7237 2054 3F CC53 2015 2015-09-15 SALIN -2.2072749132 + #> 7238 2054 3F CC53 2015 2015-09-15 COND 5.4764635519 #> 7239 2054 3F CC53 2015 2015-09-15 DO 1.0986122887 #> 7240 2054 3F CC53 2015 2015-09-15 DOSAT 3.6635616461 #> 7241 2054 3F CC53 2015 2015-09-15 SALIN -2.2072749132 + #> 7242 2054 3F CC53 2015 2015-11-25 COND 6.2225762681 #> 7243 2054 3F CC53 2015 2015-11-25 DO 1.7047480922 #> 7244 2054 3F CC53 2015 2015-11-25 DOSAT 4.1431347264 #> 7245 2054 3F CC53 2015 2015-11-25 SALIN -1.3470736480 + #> 7246 2054 3F CC53 2015 2015-11-25 COND 6.2285110036 #> 7247 2054 3F CC53 2015 2015-11-25 DO 1.6863989536 #> 7248 2054 3F CC53 2015 2015-11-25 DOSAT 4.1431347264 #> 7249 2054 3F CC53 2015 2015-11-25 SALIN -1.3470736480 + #> 7250 2054 3F CC53 2021 2021-02-02 COND 7.0184017991 #> 7251 2054 3F CC53 2021 2021-02-02 DO 1.9183921202 #> 7252 2054 3F CC53 2021 2021-02-02 DOSAT 4.2822062994 #> 7253 2054 3F CC53 2021 2021-02-02 SALIN -0.5798184953 #> 7254 2054 3F CC53 2021 2021-03-16 COND 7.8504931809 #> 7255 2054 3F CC53 2021 2021-03-16 DO 1.7783364489 #> 7256 2054 3F CC53 2021 2021-03-16 DOSAT 4.2527717988 #> 7257 2054 3F CC53 2021 2021-03-16 SALIN 0.2776317366 #> 7258 2054 3F CC53 2021 2021-09-30 COND 4.8880909413 #> 7259 2054 3F CC53 2021 2021-09-30 DO 1.3532545070 #> 7260 2054 3F CC53 2021 2021-09-30 DOSAT 3.8774315607 #> 7261 2054 3F CC53 2021 2021-09-30 SALIN -2.8134107168 #> 7262 2054 3F CC53 2021 2021-09-30 COND 4.8797670189 #> 7263 2054 3F CC53 2021 2021-09-30 DO 1.2412685891 #> 7264 2054 3F CC53 2021 2021-09-30 DOSAT 3.7750571504 #> 7265 2054 3F CC53 2021 2021-09-30 SALIN -2.8134107168 #> 7266 2054 3F CC53 2021 2021-10-27 COND 6.5250296578 #> 7267 2054 3F CC53 2021 2021-10-27 DO 1.5195132049 #> 7268 2054 3F CC53 2021 2021-10-27 DOSAT 4.0412953411 #> 7269 2054 3F CC53 2021 2021-10-27 SALIN -1.1086626245 #> 7270 2054 3F CC53 2021 2021-10-27 COND 6.5264948596 #> 7271 2054 3F CC53 2021 2021-10-27 DO 1.5129270121 #> 7272 2054 3F CC53 2021 2021-10-27 DOSAT 4.0342406382 #> 7273 2054 3F CC53 2021 2021-10-27 SALIN -1.1086626245 #> 7274 2054 3F CC53 2021 2021-11-18 COND 4.7104306966 #> 7275 2054 3F CC53 2021 2021-11-18 DO 1.8578592709 #> 7276 2054 3F CC53 2021 2021-11-18 DOSAT 4.2682978693 #> 7277 2054 3F CC53 2021 2021-11-18 SALIN -2.9957322736 #> 7278 2059 3M CC55 2015 2015-05-21 COND 7.3472997007 #> 7279 2059 3M CC55 2015 2015-05-21 DO 0.9932517730 #> 7280 2059 3M CC55 2015 2015-05-21 DOSAT 3.4657359028 #> 7281 2059 3M CC55 2015 2015-05-21 SALIN -0.3285040670 + #> 7282 2059 3M CC55 2015 2015-07-15 COND 9.6044074351 #> 7283 2059 3M CC55 2015 2015-08-06 COND 6.4068799861 #> 7284 2059 3M CC55 2015 2015-08-06 DO 1.6486586256 #> 7285 2059 3M CC55 2015 2015-08-06 DOSAT 4.2195077052 #> 7286 2059 3M CC55 2015 2015-08-06 SALIN -1.3093333200 + #> 7287 2059 3M CC55 2015 2015-08-19 COND 6.2653012127 #> 7288 2059 3M CC55 2015 2015-08-19 DO 1.3862943611 #> 7289 2059 3M CC55 2015 2015-08-19 DOSAT 4.0604430105 #> 7290 2059 3M CC55 2015 2015-08-19 SALIN -1.4271163556 + #> 7291 2059 3M CC55 2015 2015-09-15 COND 6.2519038832 #> 7292 2059 3M CC55 2015 2015-09-15 DO 1.6863989536 #> 7293 2059 3M CC55 2015 2015-09-15 DOSAT 4.1271343850 #> 7294 2059 3M CC55 2015 2015-09-15 SALIN -1.4271163556 + #> 7295 2059 3M CC55 2015 2015-11-25 COND 8.4348979487 #> 7296 2059 3M CC55 2015 2015-11-25 DO -0.1053605157 #> 7297 2059 3M CC55 2015 2015-11-25 DOSAT 2.3025850930 #> 7298 2059 3M CC55 2015 2015-11-25 SALIN 1.0152306797 + #> 7299 2059 3M CC55 2015 2015-05-21 COND 9.9007337643 #> 7300 2059 3M CC55 2015 2015-05-21 DO 1.2237754316 #> 7301 2059 3M CC55 2015 2015-05-21 DOSAT 3.8286413965 #> 7302 2059 3M CC55 2015 2015-05-21 SALIN 2.4105422345 + #> 7303 2059 3M CC55 2015 2015-07-15 COND 6.7190131544 #> 7304 2059 3M CC55 2015 2015-07-15 SALIN -0.9416085399 + #> 7305 2059 3M CC55 2015 2015-08-06 COND 6.4019171967 #> 7306 2059 3M CC55 2015 2015-08-06 DO 1.6292405397 #> 7307 2059 3M CC55 2015 2015-08-06 DOSAT 4.1896547420 #> 7308 2059 3M CC55 2015 2015-08-06 SALIN -1.3093333200 + #> 7309 2059 3M CC55 2015 2015-08-19 COND 6.2785214242 #> 7310 2059 3M CC55 2015 2015-08-19 DO 1.6094379124 #> 7311 2059 3M CC55 2015 2015-08-19 DOSAT 4.1431347264 #> 7312 2059 3M CC55 2015 2015-08-19 SALIN -1.3862943611 + #> 7313 2059 3M CC55 2015 2015-09-15 COND 6.2205901701 #> 7314 2059 3M CC55 2015 2015-09-15 DO 1.4816045409 #> 7315 2059 3M CC55 2015 2015-09-15 DOSAT 4.0073331852 #> 7316 2059 3M CC55 2015 2015-09-15 SALIN -1.4271163556 + #> 7317 2059 3M CC55 2015 2015-10-08 CHLAC 0.2623642645 I #> 7318 2059 3M CC55 2015 2015-10-08 COND 6.3969296552 #> 7319 2059 3M CC55 2015 2015-10-08 DO 1.6486586256 #> 7320 2059 3M CC55 2015 2015-10-08 DOSAT 4.2046926194 #> 7321 2059 3M CC55 2015 2015-10-08 NO23 -2.7646205526 #> 7322 2059 3M CC55 2015 2015-10-08 SALIN -1.2378743560 + #> 7323 2059 3M CC55 2015 2015-10-08 TKN -0.1625189295 #> 7324 2059 3M CC55 2015 2015-10-08 TN -0.0910193984 + #> 7325 2059 3M CC55 2015 2015-10-08 TP -2.6310891600 #> 7326 2059 3M CC55 2015 2015-10-08 TSS 1.9459101491 I #> 7327 2059 3M CC55 2015 2015-10-08 TURB 2.0794415417 #> 7328 2059 3M CC55 2015 2015-11-05 CHLAC 0.5877866649 #> 7329 2059 3M CC55 2015 2015-11-05 COND 6.6982680541 #> 7330 2059 3M CC55 2015 2015-11-05 DO 1.9600947840 #> 7331 2059 3M CC55 2015 2015-11-05 DOSAT 4.4773368145 #> 7332 2059 3M CC55 2015 2015-11-05 SALIN -0.9416085399 + #> 7333 2059 3M CC55 2015 2015-11-05 TN -0.0693500781 + #> 7334 2059 3M CC55 2015 2015-11-05 TSS 1.7917594692 I #> 7335 2059 3M CC55 2015 2015-11-05 TURB 2.2721258855 #> 7336 2059 3M CC55 2015 2015-11-25 COND 6.7007311095 #> 7337 2059 3M CC55 2015 2015-11-25 DO 2.0014800002 #> 7338 2059 3M CC55 2015 2015-11-25 DOSAT 4.4188406078 #> 7339 2059 3M CC55 2015 2015-11-25 SALIN -0.8209805521 + #> 7340 2059 3M CC55 2015 2015-12-03 CHLAC 0.5306282511 #> 7341 2059 3M CC55 2015 2015-12-03 COLOR 4.7004803658 #> 7342 2059 3M CC55 2015 2015-12-03 COND 6.8448154792 #> 7343 2059 3M CC55 2015 2015-12-03 DO 1.8900953699 #> 7344 2059 3M CC55 2015 2015-12-03 DOSAT 4.3694478525 #> 7345 2059 3M CC55 2015 2015-12-03 NO23 -2.7488721956 #> 7346 2059 3M CC55 2015 2015-12-03 SALIN -0.7550225843 + #> 7347 2059 3M CC55 2015 2015-12-03 TKN -0.2357223335 #> 7348 2059 3M CC55 2015 2015-12-03 TN -0.1578240852 + #> 7349 2059 3M CC55 2015 2015-12-03 TP -2.8647040111 #> 7350 2059 3M CC55 2015 2015-12-03 TSS 1.3862943611 I #> 7351 2059 3M CC55 2015 2015-12-03 TURB 2.1282317058 #> 7352 2059 3M CC56 2015 2015-05-21 COND 9.6019769721 #> 7353 2059 3M CC56 2015 2015-05-21 DO 0.6931471806 #> 7354 2059 3M CC56 2015 2015-05-21 DOSAT 3.1780538303 #> 7355 2059 3M CC56 2015 2015-05-21 SALIN 2.1459312829 + #> 7356 2059 3M CC56 2015 2015-07-15 COND 8.4859089014 #> 7357 2059 3M CC56 2015 2015-07-15 SALIN 0.9001613499 + #> 7358 2059 3M CC56 2015 2015-08-06 COND 6.3952615981 #> 7359 2059 3M CC56 2015 2015-08-06 DO 0.9932517730 #> 7360 2059 3M CC56 2015 2015-08-06 DOSAT 3.4657359028 #> 7361 2059 3M CC56 2015 2015-08-06 SALIN -1.3093333200 + #> 7362 2059 3M CC56 2015 2015-08-19 COND 6.1820849067 #> 7363 2059 3M CC56 2015 2015-08-19 DO 0.9932517730 #> 7364 2059 3M CC56 2015 2015-08-19 DOSAT 3.4965075615 #> 7365 2059 3M CC56 2015 2015-08-19 SALIN -1.5141277326 + #> 7366 2059 3M CC56 2015 2015-09-15 COND 6.2576675879 #> 7367 2059 3M CC56 2015 2015-09-15 DO 0.0953101798 #> 7368 2059 3M CC56 2015 2015-09-15 DOSAT 2.5649493575 #> 7369 2059 3M CC56 2015 2015-09-15 SALIN -1.4271163556 + #> 7370 2059 3M CC56 2015 2015-11-25 COND 7.6343372356 #> 7371 2059 3M CC56 2015 2015-11-25 DO 0.9555114450 #> 7372 2059 3M CC56 2015 2015-11-25 DOSAT 3.4011973817 #> 7373 2059 3M CC56 2015 2015-11-25 SALIN 0.1570037488 + #> 7374 2059 3M CC56 2015 2015-05-21 COND 9.9350831141 #> 7375 2059 3M CC56 2015 2015-05-21 DO 0.7884573604 #> 7376 2059 3M CC56 2015 2015-05-21 DOSAT 3.3672958300 #> 7377 2059 3M CC56 2015 2015-05-21 SALIN 2.4865719291 + #> 7378 2059 3M CC56 2015 2015-07-15 CHLAC 1.0986122887 #> 7379 2059 3M CC56 2015 2015-07-15 COND 9.6128678361 #> 7380 2059 3M CC56 2015 2015-07-15 NO23 -5.5214609179 U #> 7381 2059 3M CC56 2015 2015-07-15 SALIN 2.0881534823 + #> 7382 2059 3M CC56 2015 2015-07-15 TKN 0.2623642645 #> 7383 2059 3M CC56 2015 2015-07-15 TN 0.2639015438 + #> 7384 2059 3M CC56 2015 2015-07-15 TP -0.9416085399 #> 7385 2059 3M CC56 2015 2015-07-15 TSS 1.0986122887 U #> 7386 2059 3M CC56 2015 2015-07-15 TURB 1.3862943611 #> 7387 2059 3M CC56 2015 2015-08-06 COND 6.5366915976 #> 7388 2059 3M CC56 2015 2015-08-06 DO 0.2623642645 #> 7389 2059 3M CC56 2015 2015-08-06 DOSAT 2.7725887222 #> 7390 2059 3M CC56 2015 2015-08-06 SALIN -1.1394342832 + #> 7391 2059 3M CC56 2015 2015-08-19 CHLAC 1.0296194172 #> 7392 2059 3M CC56 2015 2015-08-19 COLOR 5.4380793089 #> 7393 2059 3M CC56 2015 2015-08-19 COND 6.4488893941 #> 7394 2059 3M CC56 2015 2015-08-19 DO 0.1823215568 #> 7395 2059 3M CC56 2015 2015-08-19 DOSAT 2.7725887222 #> 7396 2059 3M CC56 2015 2015-08-19 NO23 -5.5214609179 U #> 7397 2059 3M CC56 2015 2015-08-19 SALIN -1.2378743560 + #> 7398 2059 3M CC56 2015 2015-08-19 TKN 0.4054651081 #> 7399 2059 3M CC56 2015 2015-08-19 TN 0.4067975533 + #> 7400 2059 3M CC56 2015 2015-08-19 TP -0.0304592075 #> 7401 2059 3M CC56 2015 2015-08-19 TSS 1.7917594692 I #> 7402 2059 3M CC56 2015 2015-08-19 TURB 1.5686159179 #> 7403 2059 3M CC56 2015 2015-09-15 COND 6.8134445995 #> 7404 2059 3M CC56 2015 2015-09-15 DO 0.0000000000 #> 7405 2059 3M CC56 2015 2015-09-15 DOSAT 2.3025850930 #> 7406 2059 3M CC56 2015 2015-09-15 SALIN -0.8439700703 + #> 7407 2059 3M CC56 2015 2015-11-25 COND 7.8038433035 #> 7408 2059 3M CC56 2015 2015-11-25 DO 1.8718021769 #> 7409 2059 3M CC56 2015 2015-11-25 DOSAT 4.2626798770 #> 7410 2059 3M CC56 2015 2015-11-25 SALIN 0.3576744443 + #> 7411 2059 3M CC56 2018 2018-03-06 CHLAC 1.7917594692 #> 7412 2059 3M CC56 2018 2018-03-06 COND 9.8471817163 #> 7413 2059 3M CC56 2018 2018-03-06 DO 0.6205764877 #> 7414 2059 3M CC56 2018 2018-03-06 DOSAT 3.0445224377 #> 7415 2059 3M CC56 2018 2018-03-06 NO23 -2.6592600369 #> 7416 2059 3M CC56 2018 2018-03-06 SALIN 2.5748996883 + #> 7417 2059 3M CC56 2018 2018-03-06 TKN -0.0833816089 #> 7418 2059 3M CC56 2018 2018-03-06 TN -0.0100503359 + #> 7419 2059 3M CC56 2018 2018-03-06 TP -1.2378743560 #> 7420 2059 3M CC56 2018 2018-03-06 TSS 1.0986122887 U #> 7421 2059 3M CC56 2018 2018-03-06 TURB 0.1823215568 #> 7422 2059 3M CC56 2018 2018-03-29 CHLAC 2.1747517215 #> 7423 2059 3M CC56 2018 2018-03-29 COND 10.2506170836 #> 7424 2059 3M CC56 2018 2018-03-29 DO 1.3083328197 #> 7425 2059 3M CC56 2018 2018-03-29 DOSAT 3.8501476017 #> 7426 2059 3M CC56 2018 2018-03-29 NO23 -4.7105307016 I #> 7427 2059 3M CC56 2018 2018-03-29 SALIN 2.9156062291 + #> 7428 2059 3M CC56 2018 2018-03-29 TKN -0.2484613593 #> 7429 2059 3M CC56 2018 2018-03-29 TN -0.2433462586 + #> 7430 2059 3M CC56 2018 2018-03-29 TP -1.2039728043 #> 7431 2059 3M CC56 2018 2018-03-29 TSS 1.3862943611 I #> 7432 2059 3M CC56 2018 2018-03-29 TURB 0.8754687374 #> 7433 2059 3M CC56 2018 2018-04-12 COND 10.0096027833 #> 7434 2059 3M CC56 2018 2018-04-12 DO -0.3566749439 #> 7435 2059 3M CC56 2018 2018-04-12 DOSAT 2.0794415417 #> 7436 2059 3M CC56 2018 2018-04-12 SALIN 2.6932749155 + #> 7437 2059 3M CC56 2018 2018-04-19 CHLAC 0.0953101798 I #> 7438 2059 3M CC56 2018 2018-04-19 COND 10.2545668701 #> 7439 2059 3M CC56 2018 2018-04-19 DO 1.0260415958 #> 7440 2059 3M CC56 2018 2018-04-19 DOSAT 3.5025498759 #> 7441 2059 3M CC56 2018 2018-04-19 NO23 -4.6051701860 I #> 7442 2059 3M CC56 2018 2018-04-19 SALIN 2.9150643705 + #> 7443 2059 3M CC56 2018 2018-04-19 TKN -0.1863295782 #> 7444 2059 3M CC56 2018 2018-04-19 TN -0.1815218766 + #> 7445 2059 3M CC56 2018 2018-04-19 TP -1.0788096614 #> 7446 2059 3M CC56 2018 2018-04-19 TSS 1.3862943611 I #> 7447 2059 3M CC56 2018 2018-04-19 TURB 0.1823215568 #> 7448 2059 3M CC56 2018 2018-05-10 CHLAC 1.0296194172 #> 7449 2059 3M CC56 2018 2018-05-10 COND 10.2722540975 #> 7450 2059 3M CC56 2018 2018-05-10 DO -0.1053605157 #> 7451 2059 3M CC56 2018 2018-05-10 DOSAT 2.4849066498 #> 7452 2059 3M CC56 2018 2018-05-10 NO23 -5.5214609179 U #> 7453 2059 3M CC56 2018 2018-05-10 SALIN 2.8848007128 #> 7454 2059 3M CC56 2018 2018-05-10 TKN -0.0725706928 #> 7455 2059 3M CC56 2018 2018-05-10 TN -0.0704224643 + #> 7456 2059 3M CC56 2018 2018-05-10 TP -0.8209805521 #> 7457 2059 3M CC56 2018 2018-05-10 TSS 1.0986122887 I #> 7458 2059 3M CC56 2018 2018-05-10 TURB 0.5306282511 #> 7459 2059 3M CC56 2018 2018-06-25 CHLAC 0.6931471806 #> 7460 2059 3M CC56 2018 2018-06-25 COND 7.7536235466 #> 7461 2059 3M CC56 2018 2018-06-25 DO 1.0296194172 #> 7462 2059 3M CC56 2018 2018-06-25 DOSAT 3.2695689392 #> 7463 2059 3M CC56 2018 2018-06-25 NO23 -5.5214609179 U #> 7464 2059 3M CC56 2018 2018-06-25 SALIN 0.1397619424 + #> 7465 2059 3M CC56 2018 2018-06-25 TKN 0.2623642645 #> 7466 2059 3M CC56 2018 2018-06-25 TN 0.2639015438 + #> 7467 2059 3M CC56 2018 2018-06-25 TP -1.4696759701 #> 7468 2059 3M CC56 2018 2018-06-25 TSS 1.0986122887 I #> 7469 2059 3M CC56 2018 2018-06-25 TURB 1.3862943611 #> 7470 2059 3M CC56 2018 2018-07-17 CHLAC 0.9932517730 #> 7471 2059 3M CC56 2018 2018-07-17 COND 6.8437499490 #> 7472 2059 3M CC56 2018 2018-07-17 DO -0.1863295782 #> 7473 2059 3M CC56 2018 2018-07-17 DOSAT 2.3418058061 #> 7474 2059 3M CC56 2018 2018-07-17 NO23 -3.3524072175 #> 7475 2059 3M CC56 2018 2018-07-17 SALIN -0.8439700703 + #> 7476 2059 3M CC56 2018 2018-07-17 TKN 0.2623642645 #> 7477 2059 3M CC56 2018 2018-07-17 TN 0.2889312919 + #> 7478 2059 3M CC56 2018 2018-07-17 TP -1.3093333200 #> 7479 2059 3M CC56 2018 2018-07-17 TSS 1.0986122887 I #> 7480 2059 3M CC56 2018 2018-07-17 TURB 0.0953101798 #> 7481 2059 3M CC56 2018 2018-08-01 CHLAC 0.8754687374 #> 7482 2059 3M CC56 2018 2018-08-01 COND 6.0038870671 #> 7483 2059 3M CC56 2018 2018-08-01 DO 0.7129498079 #> 7484 2059 3M CC56 2018 2018-08-01 DOSAT 3.2580965380 #> 7485 2059 3M CC56 2018 2018-08-01 NO23 -3.6119184130 #> 7486 2059 3M CC56 2018 2018-08-01 SALIN -1.6607312068 #> 7487 2059 3M CC56 2018 2018-08-01 TKN 0.0953101798 #> 7488 2059 3M CC56 2018 2018-08-01 TN 0.1195592351 + #> 7489 2059 3M CC56 2018 2018-08-01 TP -1.7719568419 #> 7490 2059 3M CC56 2018 2018-08-01 TSS 0.6931471806 U #> 7491 2059 3M CC56 2018 2018-08-01 TURB 0.0953101798 #> 7492 2059 3M CC56 2018 2018-08-20 CHLAC 0.4054651081 I #> 7493 2059 3M CC56 2018 2018-08-20 NO23 -1.4696759701 #> 7494 2059 3M CC56 2018 2018-08-20 TKN -0.3147107448 #> 7495 2059 3M CC56 2018 2018-08-20 TN -0.0408219945 + #> 7496 2059 3M CC56 2018 2018-08-20 TP -0.9416085399 #> 7497 2059 3M CC56 2018 2018-08-20 TSS 1.0986122887 U #> 7498 2059 3M CC56 2018 2018-08-20 TURB 0.7419373447 #> 7499 2059 3M CC56 2018 2018-08-21 CHLAC 0.7419373447 #> 7500 2059 3M CC56 2018 2018-08-21 COND 5.9401712527 #> 7501 2059 3M CC56 2018 2018-08-21 DO 0.9516578757 #> 7502 2059 3M CC56 2018 2018-08-21 DOSAT 3.4436180975 #> 7503 2059 3M CC56 2018 2018-08-21 NO23 -3.7297014486 #> 7504 2059 3M CC56 2018 2018-08-21 SALIN -1.7147984281 #> 7505 2059 3M CC56 2018 2018-08-21 TKN 0.0000000000 #> 7506 2059 3M CC56 2018 2018-08-21 TN 0.0237165266 + #> 7507 2059 3M CC56 2018 2018-08-21 TP -1.8325814637 #> 7508 2059 3M CC56 2018 2018-08-21 TSS 1.0986122887 I #> 7509 2059 3M CC56 2018 2018-08-21 TURB 0.3364722366 A #> 7510 2059 3M CC56 2018 2018-09-20 CHLAC 1.5040773968 #> 7511 2059 3M CC56 2018 2018-09-20 COND 7.2661287796 #> 7512 2059 3M CC56 2018 2018-09-20 DO 0.9555114450 #> 7513 2059 3M CC56 2018 2018-09-20 DOSAT 3.5862928653 #> 7514 2059 3M CC56 2018 2018-09-20 NO23 -3.1010927892 #> 7515 2059 3M CC56 2018 2018-09-20 SALIN -0.3424903089 #> 7516 2059 3M CC56 2018 2018-09-20 TKN 0.1823215568 #> 7517 2059 3M CC56 2018 2018-09-20 TN 0.2191355299 + #> 7518 2059 3M CC56 2018 2018-09-20 TP -1.0788096614 #> 7519 2059 3M CC56 2018 2018-09-20 TSS 1.0986122887 I #> 7520 2059 3M CC56 2018 2018-09-20 TURB 0.9162907319 #> 7521 2059 3M CC56 2018 2018-10-24 CHLAC 1.1314021115 #> 7522 2059 3M CC56 2018 2018-10-24 COND 9.4323632956 #> 7523 2059 3M CC56 2018 2018-10-24 DO 0.5068176024 #> 7524 2059 3M CC56 2018 2018-10-24 DOSAT 3.0726933147 #> 7525 2059 3M CC56 2018 2018-10-24 NO23 -3.4737680745 #> 7526 2059 3M CC56 2018 2018-10-24 SALIN 1.9671123567 #> 7527 2059 3M CC56 2018 2018-10-24 TKN -0.0408219945 #> 7528 2059 3M CC56 2018 2018-10-24 TN -0.0090407447 + #> 7529 2059 3M CC56 2018 2018-10-24 TP -1.2039728043 #> 7530 2059 3M CC56 2018 2018-10-24 TSS 0.6931471806 I #> 7531 2059 3M CC56 2018 2018-10-24 TURB 1.7227665977 #> 7532 2059 3M CC56 2019 2019-01-16 CHLAC -0.1053605157 I #> 7533 2059 3M CC56 2019 2019-01-16 COND 9.0122552200 #> 7534 2059 3M CC56 2019 2019-01-16 DO 0.3852624008 #> 7535 2059 3M CC56 2019 2019-01-16 DOSAT 2.7080502011 #> 7536 2059 3M CC56 2019 2019-01-16 NO23 -2.5010360317 #> 7537 2059 3M CC56 2019 2019-01-16 SALIN 1.5216989981 #> 7538 2059 3M CC56 2019 2019-01-16 TKN -0.0618754037 #> 7539 2059 3M CC56 2019 2019-01-16 TN 0.0217614918 + #> 7540 2059 3M CC56 2019 2019-01-16 TP -1.3862943611 #> 7541 2059 3M CC56 2019 2019-01-16 TSS 0.6931471806 U #> 7542 2059 3M CC56 2019 2019-01-16 TURB 0.0000000000 #> 7543 2059 3M CC56 2019 2019-01-24 COND 9.8578100390 #> 7544 2059 3M CC56 2019 2019-01-24 DO 1.6770965609 #> 7545 2059 3M CC56 2019 2019-01-24 DOSAT 4.1588830834 #> 7546 2059 3M CC56 2019 2019-01-24 NO23 -3.2968373663 #> 7547 2059 3M CC56 2019 2019-01-24 SALIN 2.4327357775 #> 7548 2059 3M CC56 2019 2019-01-24 TKN -0.3147107448 #> 7549 2059 3M CC56 2019 2019-01-24 TN -0.2652684776 + #> 7550 2059 3M CC56 2019 2019-01-24 TP -1.3470736480 #> 7551 2059 3M CC56 2019 2019-01-24 TSS 1.0986122887 U #> 7552 2059 3M CC56 2019 2019-01-24 TURB 0.6418538862 #> 7553 2059 3M CC56 2019 2019-03-12 CHLAC 0.1823215568 I #> 7554 2059 3M CC56 2019 2019-03-12 COND 9.1291303166 #> 7555 2059 3M CC56 2019 2019-03-12 DO 0.4824261492 #> 7556 2059 3M CC56 2019 2019-03-12 DOSAT 2.9496883351 #> 7557 2059 3M CC56 2019 2019-03-12 NO23 -3.2968373663 #> 7558 2059 3M CC56 2019 2019-03-12 SALIN 1.6114359151 #> 7559 2059 3M CC56 2019 2019-03-12 TKN -0.0408219945 #> 7560 2059 3M CC56 2019 2019-03-12 TN -0.0030045090 + #> 7561 2059 3M CC56 2019 2019-03-12 TP -1.0498221245 #> 7562 2059 3M CC56 2019 2019-03-12 TSS 0.6931471806 I #> 7563 2059 3M CC56 2019 2019-03-12 TURB 0.0000000000 #> 7564 2059 3M CC56 2019 2019-04-23 CHLAC 1.1939224685 #> 7565 2059 3M CC56 2019 2019-04-23 COND 9.4766200382 #> 7566 2059 3M CC56 2019 2019-04-23 DO 0.7929925155 #> 7567 2059 3M CC56 2019 2019-04-23 DOSAT 3.3286266888 #> 7568 2059 3M CC56 2019 2019-04-23 NO23 -3.5755507688 #> 7569 2059 3M CC56 2019 2019-04-23 SALIN 2.0175661380 #> 7570 2059 3M CC56 2019 2019-04-23 TKN -0.1984509387 #> 7571 2059 3M CC56 2019 2019-04-23 TN -0.1648746432 + #> 7572 2059 3M CC56 2019 2019-04-23 TP -1.1086626245 #> 7573 2059 3M CC56 2019 2019-04-23 TSS 0.6931471806 I #> 7574 2059 3M CC56 2019 2019-04-23 TURB 0.2623642645 #> 7575 2059 3M CC56 2019 2019-06-11 CHLAC 1.8245492921 I #> 7576 2059 3M CC56 2019 2019-06-11 COND 9.8113722636 #> 7577 2059 3M CC56 2019 2019-06-11 DO -1.0216512475 #> 7578 2059 3M CC56 2019 2019-06-11 DOSAT 1.6094379124 #> 7579 2059 3M CC56 2019 2019-06-11 NO23 -5.5214609179 U #> 7580 2059 3M CC56 2019 2019-06-11 SALIN 2.4221443281 #> 7581 2059 3M CC56 2019 2019-06-11 TKN 0.0000000000 #> 7582 2059 3M CC56 2019 2019-06-11 TN 0.0019980027 + #> 7583 2059 3M CC56 2019 2019-06-11 TP -1.0498221245 #> 7584 2059 3M CC56 2019 2019-06-11 TSS 1.3862943611 I #> 7585 2059 3M CC56 2019 2019-06-11 TURB 1.4350845253 A #> 7586 2059 3M CC56 2019 2019-08-13 CHLAC 0.4054651081 I #> 7587 2059 3M CC56 2019 2019-08-13 COND 6.6644090204 #> 7588 2059 3M CC56 2019 2019-08-13 DO -0.3285040670 #> 7589 2059 3M CC56 2019 2019-08-13 DOSAT 2.2192034841 #> 7590 2059 3M CC56 2019 2019-08-13 NO23 -2.7488721956 #> 7591 2059 3M CC56 2019 2019-08-13 SALIN -0.9675840263 #> 7592 2059 3M CC56 2019 2019-08-13 TKN 0.1823215568 #> 7593 2059 3M CC56 2019 2019-08-13 TN 0.2342812957 + #> 7594 2059 3M CC56 2019 2019-08-13 TP -1.3470736480 #> 7595 2059 3M CC56 2019 2019-08-13 TSS 0.6931471806 I #> 7596 2059 3M CC56 2019 2019-08-13 TURB 0.0000000000 #> 7597 2059 3M CC56 2019 2019-10-01 COND 8.7345600900 #> 7598 2059 3M CC56 2019 2019-10-01 DO 0.1310282624 #> 7599 2059 3M CC56 2019 2019-10-01 DOSAT 2.6532419646 #> 7600 2059 3M CC56 2019 2019-10-01 SALIN 1.2149127444 #> 7601 2059 3M CC56 2019 2019-11-04 COND 8.7934603611 #> 7602 2059 3M CC56 2019 2019-11-04 DO 0.0000000000 #> 7603 2059 3M CC56 2019 2019-11-04 DOSAT 2.5649493575 #> 7604 2059 3M CC56 2019 2019-11-04 SALIN 1.2809338455 #> 7605 2059 3M CC56 2019 2019-11-19 CHLAC 1.2809338455 #> 7606 2059 3M CC56 2019 2019-11-19 COND 9.6775902130 #> 7607 2059 3M CC56 2019 2019-11-19 DO 0.9631743178 #> 7608 2059 3M CC56 2019 2019-11-19 DOSAT 3.4078419244 #> 7609 2059 3M CC56 2019 2019-11-19 NO23 -2.9565115604 #> 7610 2059 3M CC56 2019 2019-11-19 SALIN 2.2364452905 #> 7611 2059 3M CC56 2019 2019-11-19 TKN -0.3011050928 #> 7612 2059 3M CC56 2019 2019-11-19 TN -0.2331938872 + #> 7613 2059 3M CC56 2019 2019-11-19 TP -1.2378743560 #> 7614 2059 3M CC56 2019 2019-11-19 TSS 1.0986122887 U #> 7615 2059 3M CC56 2019 2019-11-19 TURB 0.1823215568 #> 7616 2059 3M CC56 2020 2020-01-28 CHLAC 0.7419373447 U #> 7617 2059 3M CC56 2020 2020-01-28 COND 8.9703049530 #> 7618 2059 3M CC56 2020 2020-01-28 DO 1.0784095814 #> 7619 2059 3M CC56 2020 2020-01-28 DOSAT 3.4468078929 #> 7620 2059 3M CC56 2020 2020-01-28 NO23 -1.4271163556 #> 7621 2059 3M CC56 2020 2020-01-28 SALIN 1.4747630091 #> 7622 2059 3M CC56 2020 2020-01-28 TKN -0.2744368457 #> 7623 2059 3M CC56 2020 2020-01-28 TN 0.0000000000 + #> 7624 2059 3M CC56 2020 2020-01-28 TP -1.9661128564 #> 7625 2059 3M CC56 2020 2020-01-28 TSS 0.6931471806 U #> 7626 2059 3M CC56 2020 2020-01-28 TURB 0.0000000000 #> 7627 2059 3M CC56 2020 2020-03-05 CHLAC 0.6418538862 I #> 7628 2059 3M CC56 2020 2020-03-05 COND 10.0861423871 #> 7629 2059 3M CC56 2020 2020-03-05 DO 0.4700036292 #> 7630 2059 3M CC56 2020 2020-03-05 DOSAT 2.9957322736 #> 7631 2059 3M CC56 2020 2020-03-05 NO23 -2.9004220937 #> 7632 2059 3M CC56 2020 2020-03-05 SALIN 2.6817062258 #> 7633 2059 3M CC56 2020 2020-03-05 TKN -0.3424903089 #> 7634 2059 3M CC56 2020 2020-03-05 TN -0.2678794452 + #> 7635 2059 3M CC56 2020 2020-03-05 TP -1.2378743560 #> 7636 2059 3M CC56 2020 2020-03-05 TSS 1.3862943611 I #> 7637 2059 3M CC56 2020 2020-03-05 TURB 0.9932517730 #> 7638 2059 3M CC56 2020 2020-07-28 CHLAC 1.3083328197 #> 7639 2059 3M CC56 2020 2020-07-28 COND 9.3060141220 #> 7640 2059 3M CC56 2020 2020-07-28 DO -0.1053605157 #> 7641 2059 3M CC56 2020 2020-07-28 DOSAT 2.4849066498 #> 7642 2059 3M CC56 2020 2020-07-28 NO23 -3.6119184130 #> 7643 2059 3M CC56 2020 2020-07-28 SALIN 1.8261608959 #> 7644 2059 3M CC56 2020 2020-07-28 TKN 0.0000000000 #> 7645 2059 3M CC56 2020 2020-07-28 TN 0.0266419309 + #> 7646 2059 3M CC56 2020 2020-07-28 TP -0.6733445533 #> 7647 2059 3M CC56 2020 2020-07-28 TSS 0.6931471806 I #> 7648 2059 3M CC56 2020 2020-07-28 TURB 1.1939224685 #> 7649 2059 3M CC56 2020 2020-08-31 CHLAC 0.4700036292 U #> 7650 2059 3M CC56 2020 2020-08-31 COND 7.2751723195 #> 7651 2059 3M CC56 2020 2020-08-31 DO -1.2378743560 #> 7652 2059 3M CC56 2020 2020-08-31 DOSAT 1.3083328197 #> 7653 2059 3M CC56 2020 2020-08-31 NO23 -3.5404594490 #> 7654 2059 3M CC56 2020 2020-08-31 SALIN -0.3285040670 #> 7655 2059 3M CC56 2020 2020-08-31 TKN 0.3364722366 #> 7656 2059 3M CC56 2020 2020-08-31 TN 0.3569748989 + #> 7657 2059 3M CC56 2020 2020-08-31 TP -1.3862943611 #> 7658 2059 3M CC56 2020 2020-08-31 TSS 0.6931471806 U #> 7659 2059 3M CC56 2020 2020-08-31 TURB 0.4054651081 #> 7660 2059 3M CC56 2020 2020-09-16 CHLAC 0.4700036292 U #> 7661 2059 3M CC56 2020 2020-09-16 COND 6.8068293604 #> 7662 2059 3M CC56 2020 2020-09-16 DO 0.4054651081 #> 7663 2059 3M CC56 2020 2020-09-16 DOSAT 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NO23 -5.2983173665 I #> 7718 2063 3M CC64 2013 2013-04-01 SALIN 3.4499875458 #> 7719 2063 3M CC64 2013 2013-04-01 TKN -0.6161861394 #> 7720 2063 3M CC64 2013 2013-04-01 TN -0.6088060321 + #> 7721 2063 3M CC64 2013 2013-04-01 TP -2.4889146712 #> 7722 2063 3M CC64 2013 2013-04-01 TURB 0.5877866649 A #> 7723 2063 3M CC64 2013 2013-05-06 CHLAC 1.4816045409 #> 7724 2063 3M CC64 2013 2013-05-06 COLOR 2.8332133441 #> 7725 2063 3M CC64 2013 2013-05-06 DO 1.6292405397 #> 7726 2063 3M CC64 2013 2013-05-06 DOSAT 4.2822062994 + #> 7727 2063 3M CC64 2013 2013-05-06 NO23 -4.6051701860 #> 7728 2063 3M CC64 2013 2013-05-06 SALIN 3.4011973817 #> 7729 2063 3M CC64 2013 2013-05-06 TKN -0.6161861394 #> 7730 2063 3M CC64 2013 2013-05-06 TN -0.5978370008 + #> 7731 2063 3M CC64 2013 2013-05-06 TP -2.3025850930 #> 7732 2063 3M CC64 2013 2013-05-06 TURB 0.4700036292 #> 7733 2063 3M CC64 2013 2013-06-03 CHLAC 1.5686159179 #> 7734 2063 3M CC64 2013 2013-06-03 COLOR 2.2082744135 #> 7735 2063 3M CC64 2013 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2013 2013-10-07 COLOR 4.3820266347 #> 7772 2063 3M CC64 2013 2013-10-07 DO 1.6094379124 #> 7773 2063 3M CC64 2013 2013-10-07 DOSAT 4.2355547308 + #> 7774 2063 3M CC64 2013 2013-10-07 SALIN 2.5176964726 #> 7775 2063 3M CC64 2013 2013-10-07 TN -0.1707883210 + #> 7776 2063 3M CC64 2013 2013-10-07 TURB 0.5877866649 #> 7777 2063 3M CC64 2013 2013-11-04 CHLAC 0.7419373447 #> 7778 2063 3M CC64 2013 2013-11-04 COLOR 3.6375861597 #> 7779 2063 3M CC64 2013 2013-11-04 DO 1.5475625087 #> 7780 2063 3M CC64 2013 2013-11-04 DOSAT 4.1125118662 + #> 7781 2063 3M CC64 2013 2013-11-04 NO23 -3.0576076773 #> 7782 2063 3M CC64 2013 2013-11-04 SALIN 2.9601050959 #> 7783 2063 3M CC64 2013 2013-11-04 TKN -0.4155154440 #> 7784 2063 3M CC64 2013 2013-11-04 TN -0.3467246131 + #> 7785 2063 3M CC64 2013 2013-11-04 TP -1.9661128564 #> 7786 2063 3M CC64 2013 2013-11-04 TURB 0.2623642645 #> 7787 2063 3M CC64 2013 2013-12-02 CHLAC 0.9555114450 #> 7788 2063 3M CC64 2013 2013-12-02 COLOR 2.6390573296 #> 7789 2063 3M CC64 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2063 3M CC64 2014 2014-03-03 TURB 0.4054651081 #> 7826 2063 3M CC64 2014 2014-04-07 CHLAC 1.2237754316 #> 7827 2063 3M CC64 2014 2014-04-07 COLOR 2.6390573296 #> 7828 2063 3M CC64 2014 2014-04-07 DO 1.3244189574 #> 7829 2063 3M CC64 2014 2014-04-07 DOSAT 3.9759363312 + #> 7830 2063 3M CC64 2014 2014-04-07 NO23 -4.8283137373 I #> 7831 2063 3M CC64 2014 2014-04-07 SALIN 3.3246762438 #> 7832 2063 3M CC64 2014 2014-04-07 TKN -0.4942963218 #> 7833 2063 3M CC64 2014 2014-04-07 TN -0.4877603508 + #> 7834 2063 3M CC64 2014 2014-04-07 TP -2.3330443005 #> 7835 2063 3M CC64 2014 2014-04-07 TURB 0.8329091229 #> 7836 2063 3M CC64 2014 2014-05-05 CHLAC 1.3350010667 #> 7837 2063 3M CC64 2014 2014-05-05 COLOR 2.6390573296 #> 7838 2063 3M CC64 2014 2014-05-05 DO 1.4398351280 #> 7839 2063 3M CC64 2014 2014-05-05 DOSAT 4.0910056610 + #> 7840 2063 3M CC64 2014 2014-05-05 NO23 -4.9618451299 I #> 7841 2063 3M CC64 2014 2014-05-05 SALIN 3.3039519972 #> 7842 2063 3M CC64 2014 2014-05-05 TKN -0.4780358009 #> 7843 2063 3M CC64 2014 2014-05-05 TN -0.4716049106 + #> 7844 2063 3M CC64 2014 2014-05-05 TP -2.2072749132 #> 7845 2063 3M CC64 2014 2014-05-05 TURB 0.9555114450 #> 7846 2063 3M CC64 2014 2014-06-02 CHLAC 1.3083328197 #> 7847 2063 3M CC64 2014 2014-06-02 COLOR 2.3978952728 #> 7848 2063 3M CC64 2014 2014-06-02 DO 1.0116009117 #> 7849 2063 3M CC64 2014 2014-06-02 DOSAT 3.7111300630 + #> 7850 2063 3M CC64 2014 2014-06-02 NO23 -5.1159958098 I #> 7851 2063 3M CC64 2014 2014-06-02 SALIN 3.3347013904 #> 7852 2063 3M CC64 2014 2014-06-02 TKN -0.4462871026 #> 7853 2063 3M CC64 2014 2014-06-02 TN -0.4400565529 + #> 7854 2063 3M CC64 2014 2014-06-02 TP -2.0402208285 #> 7855 2063 3M CC64 2014 2014-06-02 TURB 0.6931471806 #> 7856 2063 3M CC64 2014 2014-07-07 CHLAC 1.7047480922 #> 7857 2063 3M CC64 2014 2014-07-07 COLOR 3.1354942159 #> 7858 2063 3M CC64 2014 2014-07-07 DOSAT 3.7495040759 + #> 7859 2063 3M CC64 2014 2014-07-07 NO23 -4.5098600062 #> 7860 2063 3M CC64 2014 2014-07-07 SALIN 3.2611687371 #> 7861 2063 3M CC64 2014 2014-07-07 TKN -0.1863295782 #> 7862 2063 3M CC64 2014 2014-07-07 TN -0.1731636190 + #> 7863 2063 3M CC64 2014 2014-07-07 TP -2.0402208285 #> 7864 2063 3M CC64 2014 2014-07-07 TURB 0.6931471806 #> 7865 2063 3M CC64 2014 2014-08-04 CHLAC 2.4849066498 #> 7866 2063 3M CC64 2014 2014-08-04 COLOR 3.7612001157 #> 7867 2063 3M CC64 2014 2014-08-04 DO 0.9932517730 #> 7868 2063 3M CC64 2014 2014-08-04 DOSAT 3.6863763239 + #> 7869 2063 3M CC64 2014 2014-08-04 NO23 -4.8283137373 I #> 7870 2063 3M CC64 2014 2014-08-04 SALIN 2.9439125248 #> 7871 2063 3M CC64 2014 2014-08-04 TKN -0.1743533871 #> 7872 2063 3M CC64 2014 2014-08-04 TN -0.1696027844 + #> 7873 2063 3M CC64 2014 2014-08-04 TP -1.6607312068 #> 7874 2063 3M CC64 2014 2014-08-04 TURB 1.0296194172 #> 7875 2063 3M CC64 2014 2014-09-08 CHLAC 0.9162907319 #> 7876 2063 3M CC64 2014 2014-09-08 COLOR 3.4011973817 #> 7877 2063 3M CC64 2014 2014-09-08 DO 0.7178397932 #> 7878 2063 3M CC64 2014 2014-09-08 DOSAT 3.3911470458 + #> 7879 2063 3M CC64 2014 2014-09-08 NO23 -4.1351665567 #> 7880 2063 3M CC64 2014 2014-09-08 SALIN 2.9242362718 #> 7881 2063 3M CC64 2014 2014-09-08 TKN -0.2231435513 #> 7882 2063 3M CC64 2014 2014-09-08 TN -0.2033409240 + #> 7883 2063 3M CC64 2014 2014-09-08 TP -1.9661128564 #> 7884 2063 3M CC64 2014 2014-09-08 TURB -0.0512932944 #> 7885 2063 3M CC64 2014 2014-10-06 CHLAC 1.5040773968 #> 7886 2063 3M CC64 2014 2014-10-06 COLOR 4.5951198501 #> 7887 2063 3M CC64 2014 2014-10-06 DO 0.9162907319 #> 7888 2063 3M CC64 2014 2014-10-06 DOSAT 3.4781584228 + #> 7889 2063 3M CC64 2014 2014-10-06 NO23 -3.3813947544 #> 7890 2063 3M CC64 2014 2014-10-06 SALIN 2.0819384219 #> 7891 2063 3M CC64 2014 2014-10-06 TKN -0.0408219945 #> 7892 2063 3M CC64 2014 2014-10-06 TN -0.0060180723 + #> 7893 2063 3M CC64 2014 2014-10-06 TP -1.8325814637 #> 7894 2063 3M CC64 2014 2014-10-06 TURB 0.4054651081 #> 7895 2063 3M CC64 2014 2014-11-03 CHLAC 0.9162907319 #> 7896 2063 3M CC64 2014 2014-11-03 COLOR 3.7841896339 #> 7897 2063 3M CC64 2014 2014-11-03 DO 1.5686159179 #> 7898 2063 3M CC64 2014 2014-11-03 DOSAT 4.0826093060 + #> 7899 2063 3M CC64 2014 2014-11-03 NO23 -3.5065578973 #> 7900 2063 3M CC64 2014 2014-11-03 SALIN 2.9423314968 #> 7901 2063 3M CC64 2014 2014-11-03 TKN -0.3285040670 #> 7902 2063 3M CC64 2014 2014-11-03 TN -0.2876820725 + #> 7903 2063 3M CC64 2014 2014-11-03 TP -1.9661128564 #> 7904 2063 3M CC64 2014 2014-11-03 TURB 0.5306282511 #> 7905 2063 3M CC64 2014 2014-12-01 CHLAC 0.4700036292 I #> 7906 2063 3M CC64 2014 2014-12-01 COLOR 3.4011973817 #> 7907 2063 3M CC64 2014 2014-12-01 DO 1.6956156087 #> 7908 2063 3M CC64 2014 2014-12-01 DOSAT 4.1941898972 + #> 7909 2063 3M CC64 2014 2014-12-01 NO23 -2.7181005370 #> 7910 2063 3M CC64 2014 2014-12-01 SALIN 3.0449985149 #> 7911 2063 3M CC64 2014 2014-12-01 TKN -0.3566749439 #> 7912 2063 3M CC64 2014 2014-12-01 TN -0.2665731092 + #> 7913 2063 3M CC64 2014 2014-12-01 TP -2.3025850930 #> 7914 2063 3M CC64 2014 2014-12-01 TURB 0.4700036292 #> 7915 2063 3M CC64 2015 2015-01-05 CHLAC 0.7884573604 A #> 7916 2063 3M CC64 2015 2015-01-05 COLOR 2.9444389792 #> 7917 2063 3M CC64 2015 2015-01-05 NO23 -2.8824035882 #> 7918 2063 3M CC64 2015 2015-01-05 SALIN 3.2592497190 #> 7919 2063 3M CC64 2015 2015-01-05 TKN -0.5621189182 #> 7920 2063 3M CC64 2015 2015-01-05 TN -0.4684049079 + #> 7921 2063 3M CC64 2015 2015-01-05 TP -2.3025850930 #> 7922 2063 3M CC64 2015 2015-01-05 TURB 0.6931471806 #> 7923 2063 3M CC64 2015 2015-02-02 CHLAC 0.2623642645 I #> 7924 2063 3M CC64 2015 2015-02-02 COLOR 2.3025850930 #> 7925 2063 3M CC64 2015 2015-02-02 DOSAT 4.3932138241 + #> 7926 2063 3M CC64 2015 2015-02-02 NO23 -4.3428059215 #> 7927 2063 3M CC64 2015 2015-02-02 SALIN 3.3214324132 #> 7928 2063 3M CC64 2015 2015-02-02 TKN -0.9942522733 I #> 7929 2063 3M CC64 2015 2015-02-02 TN -1.7544636845 + #> 7930 2063 3M CC64 2015 2015-02-02 TP -2.4534079827 #> 7931 2063 3M CC64 2015 2015-02-02 TURB 0.7884573604 A #> 7932 2063 3M CC64 2015 2015-03-02 CHLAC 1.1631508098 A #> 7933 2063 3M CC64 2015 2015-03-02 COLOR 2.8903717579 #> 7934 2063 3M CC64 2015 2015-03-02 DO 1.9430489168 #> 7935 2063 3M CC64 2015 2015-03-02 DOSAT 4.5152454785 + #> 7936 2063 3M CC64 2015 2015-03-02 NO23 -3.1941832123 #> 7937 2063 3M CC64 2015 2015-03-02 SALIN 3.2136622578 #> 7938 2063 3M CC64 2015 2015-03-02 TKN -0.4942963218 #> 7939 2063 3M CC64 2015 2015-03-02 TN -0.4292456368 + #> 7940 2063 3M CC64 2015 2015-03-02 TP -2.2072749132 #> 7941 2063 3M CC64 2015 2015-03-02 TURB 0.8754687374 #> 7942 2063 3M CC64 2015 2015-04-06 CHLAC 0.9162907319 #> 7943 2063 3M CC64 2015 2015-04-06 COLOR 2.9957322736 #> 7944 2063 3M CC64 2015 2015-04-06 DO 1.3558351536 #> 7945 2063 3M CC64 2015 2015-04-06 DOSAT 4.0036901940 + #> 7946 2063 3M CC64 2015 2015-04-06 NO23 -4.6051701860 #> 7947 2063 3M CC64 2015 2015-04-06 SALIN 3.2268439945 #> 7948 2063 3M CC64 2015 2015-04-06 TKN -0.4462871026 #> 7949 2063 3M CC64 2015 2015-04-06 TN -0.4307829161 + #> 7950 2063 3M CC64 2015 2015-04-06 TP -2.3025850930 #> 7951 2063 3M CC64 2015 2015-04-06 TURB 0.6931471806 #> 7952 2063 3M CC64 2015 2015-05-04 CHLAC 1.2809338455 #> 7953 2063 3M CC64 2015 2015-05-04 COLOR 2.9444389792 #> 7954 2063 3M CC64 2015 2015-05-04 DOSAT 4.0673158898 + #> 7955 2063 3M CC64 2015 2015-05-04 NO23 -4.8283137373 I #> 7956 2063 3M CC64 2015 2015-05-04 SALIN 3.2820383998 #> 7957 2063 3M CC64 2015 2015-05-04 TKN -0.7133498879 #> 7958 2063 3M CC64 2015 2015-05-04 TN -0.7052197618 + #> 7959 2063 3M CC64 2015 2015-05-04 TP -2.7806208939 #> 7960 2063 3M CC64 2015 2015-05-04 TURB 0.7884573604 #> 7961 2063 3M CC64 2015 2015-06-01 CHLAC 1.1631508098 #> 7962 2063 3M CC64 2015 2015-06-01 COLOR 2.8332133441 #> 7963 2063 3M CC64 2015 2015-06-01 DO 1.0647107370 #> 7964 2063 3M CC64 2015 2015-06-01 DOSAT 3.7773481021 + #> 7965 2063 3M CC64 2015 2015-06-01 NO23 -4.6051701860 I #> 7966 2063 3M CC64 2015 2015-06-01 SALIN 3.3214324132 #> 7967 2063 3M CC64 2015 2015-06-01 TKN -0.5621189182 #> 7968 2063 3M CC64 2015 2015-06-01 TN -0.5551258827 + #> 7969 2063 3M CC64 2015 2015-06-01 TP -2.3025850930 #> 7970 2063 3M CC64 2015 2015-06-01 TURB 0.4700036292 #> 7971 2063 3M CC64 2015 2015-08-03 CHLAC 2.2407096893 #> 7972 2063 3M CC64 2015 2015-08-03 COLOR 4.1588830834 #> 7973 2063 3M CC64 2015 2015-08-03 DO 0.7654678421 #> 7974 2063 3M CC64 2015 2015-08-03 DOSAT 3.4045251718 + #> 7975 2063 3M CC64 2015 2015-08-03 NO23 -4.6051701860 I #> 7976 2063 3M CC64 2015 2015-08-03 SALIN 2.8039662579 #> 7977 2063 3M CC64 2015 2015-08-03 TKN -0.0512932944 #> 7978 2063 3M CC64 2015 2015-08-03 TN -0.0470916075 + #> 7979 2063 3M CC64 2015 2015-08-03 TP -2.0402208285 #> 7980 2063 3M CC64 2015 2015-08-03 TURB 0.5877866649 #> 7981 2063 3M CC64 2015 2015-09-08 CHLAC 1.3609765531 #> 7982 2063 3M CC64 2015 2015-09-08 COLOR 4.5432947823 #> 7983 2063 3M CC64 2015 2015-09-08 NO23 -3.6888794541 #> 7984 2063 3M CC64 2015 2015-09-08 SALIN 1.3584091576 #> 7985 2063 3M CC64 2015 2015-09-08 TKN -0.1743533871 #> 7986 2063 3M CC64 2015 2015-09-08 TN -0.1450257721 + #> 7987 2063 3M CC64 2015 2015-09-08 TP -2.2072749132 #> 7988 2063 3M CC64 2015 2015-09-08 TURB 0.5306282511 #> 7989 2063 3M CC64 2015 2015-10-05 CHLAC 1.5892352051 #> 7990 2063 3M CC64 2015 2015-10-05 COLOR 4.5643481915 #> 7991 2063 3M CC64 2015 2015-10-05 DO 1.1085626195 #> 7992 2063 3M CC64 2015 2015-10-05 DOSAT 3.6888794541 + #> 7993 2063 3M CC64 2015 2015-10-05 NO23 -3.3524072175 #> 7994 2063 3M CC64 2015 2015-10-05 SALIN 2.4069451083 #> 7995 2063 3M CC64 2015 2015-10-05 TKN -0.1984509387 #> 7996 2063 3M CC64 2015 2015-10-05 TN -0.1566538100 + #> 7997 2063 3M CC64 2015 2015-10-05 TP -1.5606477483 #> 7998 2063 3M CC64 2015 2015-10-05 TURB 0.3364722366 A #> 7999 2063 3M CC64 2015 2015-12-07 CHLAC 0.9555114450 #> 8000 2063 3M CC64 2015 2015-12-07 COLOR 3.4965075615 #> 8001 2063 3M CC64 2015 2015-12-07 DO 1.1314021115 #> 8002 2063 3M CC64 2015 2015-12-07 DOSAT 3.6988297850 + #> 8003 2063 3M CC64 2015 2015-12-07 NO23 -2.8824035882 #> 8004 2063 3M CC64 2015 2015-12-07 SALIN 3.0540011817 #> 8005 2063 3M CC64 2015 2015-12-07 TKN -0.4780358009 #> 8006 2063 3M CC64 2015 2015-12-07 TN -0.3915622029 + #> 8007 2063 3M CC64 2015 2015-12-07 TP -2.2072749132 #> 8008 2063 3M CC64 2015 2015-12-07 TURB 0.7884573604 #> 8009 2063 3M CC64 2016 2016-01-04 CHLAC 0.4700036292 I #> 8010 2063 3M CC64 2016 2016-01-04 COLOR 3.1780538303 #> 8011 2063 3M CC64 2016 2016-01-04 DO 1.1631508098 #> 8012 2063 3M CC64 2016 2016-01-04 DOSAT 3.7281001673 + #> 8013 2063 3M CC64 2016 2016-01-04 NO23 -2.7030626596 #> 8014 2063 3M CC64 2016 2016-01-04 SALIN 3.1112906142 #> 8015 2063 3M CC64 2016 2016-01-04 TKN -0.3011050928 #> 8016 2063 3M CC64 2016 2016-01-04 TN -0.2144316107 + #> 8017 2063 3M CC64 2016 2016-01-04 TP -2.0402208285 #> 8018 2063 3M CC64 2016 2016-01-04 TURB 0.9162907319 #> 8019 2063 3M CC64 2016 2016-02-01 COLOR 4.1896547420 A #> 8020 2063 3M CC64 2016 2016-02-01 DOSAT 4.5053498507 + #> 8021 2063 3M CC64 2016 2016-02-01 NO23 -4.1997050779 #> 8022 2063 3M CC64 2016 2016-02-01 SALIN 1.9810014689 #> 8023 2063 3M CC64 2016 2016-02-01 TKN -0.5447271754 #> 8024 2063 3M CC64 2016 2016-02-01 TN -0.5191938734 + #> 8025 2063 3M CC64 2016 2016-02-01 TP -2.8473122684 #> 8026 2063 3M CC64 2016 2016-02-01 TURB 0.5877866649 #> 8027 2063 3M CC64 2016 2016-03-07 CHLAC 0.6418538862 I #> 8028 2063 3M CC64 2016 2016-03-07 COLOR 3.7841896339 #> 8029 2063 3M CC64 2016 2016-03-07 NO23 -4.1997050779 #> 8030 2063 3M CC64 2016 2016-03-07 SALIN 2.6159349122 #> 8031 2063 3M CC64 2016 2016-03-07 TKN -0.2231435513 #> 8032 2063 3M CC64 2016 2016-03-07 TN -0.2045671657 + #> 8033 2063 3M CC64 2016 2016-03-07 TP -2.3538783874 #> 8034 2063 3M CC64 2016 2016-03-07 TURB 0.4700036292 #> 8035 2063 3M CC64 2016 2016-04-04 CHLAC 1.2237754316 #> 8036 2063 3M CC64 2016 2016-04-04 COLOR 3.3322045102 A #> 8037 2063 3M CC64 2016 2016-04-04 DO 1.6094379124 #> 8038 2063 3M CC64 2016 2016-04-04 DOSAT 4.2061840440 + #> 8039 2063 3M CC64 2016 2016-04-04 NO23 -3.7297014486 #> 8040 2063 3M CC64 2016 2016-04-04 SALIN 2.9236990707 #> 8041 2063 3M CC64 2016 2016-04-04 TN -0.3092462504 + #> 8042 2063 3M CC64 2016 2016-04-04 TP -2.2072749132 #> 8043 2063 3M CC64 2016 2016-04-04 TURB 0.7419373447 #> 8044 2063 3M CC64 2016 2016-05-02 CHLAC 0.8754687374 #> 8045 2063 3M CC64 2016 2016-05-02 COLOR 3.1780538303 #> 8046 2063 3M CC64 2016 2016-05-02 DO 1.1631508098 #> 8047 2063 3M CC64 2016 2016-05-02 DOSAT 3.8394523126 + #> 8048 2063 3M CC64 2016 2016-05-02 NO23 -4.5098600062 #> 8049 2063 3M CC64 2016 2016-05-02 SALIN 3.1428583384 #> 8050 2063 3M CC64 2016 2016-05-02 TKN -0.5276327421 #> 8051 2063 3M CC64 2016 2016-05-02 TN -0.5091603444 + #> 8052 2063 3M CC64 2016 2016-05-02 TP -2.3025850930 #> 8053 2063 3M CC64 2016 2016-05-02 TURB 0.6931471806 #> 8054 2063 3M CC64 2016 2016-06-06 NO23 -4.6051701860 I #> 8055 2063 3M CC64 2016 2016-06-06 SALIN 3.2120525995 #> 8056 2063 3M CC64 2016 2016-06-06 TKN -0.4462871026 #> 8057 2063 3M CC64 2016 2016-06-06 TN -0.4400565529 + #> 8058 2063 3M CC64 2016 2016-06-06 TP -2.1202635362 #> 8059 2063 3M CC64 2016 2016-07-05 CHLAC 1.0296194172 #> 8060 2063 3M CC64 2016 2016-07-05 COLOR 3.9702919136 #> 8061 2063 3M CC64 2016 2016-07-05 DO 0.5596157879 #> 8062 2063 3M CC64 2016 2016-07-05 DOSAT 3.2503744919 + #> 8063 2063 3M CC64 2016 2016-07-05 NO23 -5.5214609179 U #> 8064 2063 3M CC64 2016 2016-07-05 SALIN 2.8864752876 #> 8065 2063 3M CC64 2016 2016-07-05 TKN -0.2484613593 #> 8066 2063 3M CC64 2016 2016-07-05 TN -0.2459005384 + #> 8067 2063 3M CC64 2016 2016-07-05 TP -1.6607312068 #> 8068 2063 3M CC64 2016 2016-07-05 TURB 0.6418538862 #> 8069 2063 3M CC64 2016 2016-08-01 CHLAC 0.7884573604 #> 8070 2063 3M CC64 2016 2016-08-01 COLOR 4.0073331852 A #> 8071 2063 3M CC64 2016 2016-08-01 DO 0.9669838462 #> 8072 2063 3M CC64 2016 2016-08-01 DOSAT 3.6428355156 + #> 8073 2063 3M CC64 2016 2016-08-01 NO23 -4.3428059215 #> 8074 2063 3M CC64 2016 2016-08-01 SALIN 2.6232182656 #> 8075 2063 3M CC64 2016 2016-08-01 TKN -0.1625189295 #> 8076 2063 3M CC64 2016 2016-08-01 TN -0.1473405879 + #> 8077 2063 3M CC64 2016 2016-08-01 TP -1.9661128564 #> 8078 2063 3M CC64 2016 2016-08-01 TURB 0.3364722366 #> 8079 2063 3M CC64 2016 2016-10-03 CHLAC 1.3350010667 #> 8080 2063 3M CC64 2016 2016-10-03 COLOR 3.9702919136 #> 8081 2063 3M CC64 2016 2016-10-03 DO 0.7178397932 #> 8082 2063 3M CC64 2016 2016-10-03 DOSAT 3.3568971228 + #> 8083 2063 3M CC64 2016 2016-10-03 NO23 -4.1351665567 #> 8084 2063 3M CC64 2016 2016-10-03 SALIN 2.5892666651 #> 8085 2063 3M CC64 2016 2016-10-03 TKN -0.4620354596 #> 8086 2063 3M CC64 2016 2016-10-03 TN -0.4369557752 + #> 8087 2063 3M CC64 2016 2016-10-03 TP -1.8325814637 #> 8088 2063 3M CC64 2016 2016-10-03 TURB 0.1823215568 #> 8089 2063 3M CC64 2016 2016-11-07 CHLAC 0.8754687374 #> 8090 2063 3M CC64 2016 2016-11-07 COLOR 2.8332133441 A #> 8091 2063 3M CC64 2016 2016-11-07 DO 1.3402504226 #> 8092 2063 3M CC64 2016 2016-11-07 DOSAT 3.9473901493 + #> 8093 2063 3M CC64 2016 2016-11-07 NO23 -4.7105307016 I #> 8094 2063 3M CC64 2016 2016-11-07 SALIN 3.3178157727 #> 8095 2063 3M CC64 2016 2016-11-07 TKN -0.4155154440 #> 8096 2063 3M CC64 2016 2016-11-07 TN -0.4094731295 + #> 8097 2063 3M CC64 2016 2016-11-07 TP -2.3330443005 #> 8098 2063 3M CC64 2016 2016-11-07 TURB 0.6418538862 #> 8099 2063 3M CC64 2016 2016-12-05 CHLAC 2.6390573296 #> 8100 2063 3M CC64 2016 2016-12-05 COLOR 2.7080502011 #> 8101 2063 3M CC64 2016 2016-12-05 DO 1.6094379124 #> 8102 2063 3M CC64 2016 2016-12-05 DOSAT 4.2165621949 + #> 8103 2063 3M CC64 2016 2016-12-05 NO23 -5.5214609179 U #> 8104 2063 3M CC64 2016 2016-12-05 SALIN 3.3792925463 #> 8105 2063 3M CC64 2016 2016-12-05 TKN -0.3285040670 #> 8106 2063 3M CC64 2016 2016-12-05 TN -0.3257301401 + #> 8107 2063 3M CC64 2016 2016-12-05 TP -1.7147984281 #> 8108 2063 3M CC64 2016 2016-12-05 TURB 0.8329091229 #> 8109 2063 3M CC64 2017 2017-01-03 CHLAC 0.7419373447 #> 8110 2063 3M CC64 2017 2017-01-03 COLOR 2.1860512767 #> 8111 2063 3M CC64 2017 2017-01-03 DO 1.6292405397 #> 8112 2063 3M CC64 2017 2017-01-03 DOSAT 4.2370008626 + #> 8113 2063 3M CC64 2017 2017-01-03 NO23 -5.5214609179 U #> 8114 2063 3M CC64 2017 2017-01-03 SALIN 3.3911470458 #> 8115 2063 3M CC64 2017 2017-01-03 TKN -0.6733445533 #> 8116 2063 3M CC64 2017 2017-01-03 TN -0.6694306539 + #> 8117 2063 3M CC64 2017 2017-01-03 TP -2.3751557858 #> 8118 2063 3M CC64 2017 2017-01-03 TURB 0.4700036292 #> 8119 2063 3M CC64 2017 2017-02-06 CHLAC 1.3083328197 #> 8120 2063 3M CC64 2017 2017-02-06 COLOR 2.2300144002 #> 8121 2063 3M CC64 2017 2017-02-06 DO 1.6770965609 #> 8122 2063 3M CC64 2017 2017-02-06 DOSAT 4.2654928184 + #> 8123 2063 3M CC64 2017 2017-02-06 NO23 -3.3242363405 #> 8124 2063 3M CC64 2017 2017-02-06 SALIN 3.3965197921 #> 8125 2063 3M CC64 2017 2017-02-06 TKN -0.3566749439 #> 8126 2063 3M CC64 2017 2017-02-06 TN -0.3065251603 + #> 8127 2063 3M CC64 2017 2017-02-06 TP -2.4418471603 #> 8128 2063 3M CC64 2017 2017-02-06 TURB 0.9555114450 #> 8129 2063 3M CC64 2017 2017-03-06 CHLAC 1.2237754316 #> 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#> 8148 2063 3M CC64 2017 2017-04-03 TURB 0.8754687374 #> 8149 2063 3M CC64 2017 2017-05-01 CHLAC 1.0296194172 #> 8150 2063 3M CC64 2017 2017-05-01 COLOR 2.6390573296 #> 8151 2063 3M CC64 2017 2017-05-01 DO 1.3480731483 #> 8152 2063 3M CC64 2017 2017-05-01 DOSAT 4.0604430105 + #> 8153 2063 3M CC64 2017 2017-05-01 NO23 -5.5214609179 U #> 8154 2063 3M CC64 2017 2017-05-01 SALIN 3.5377658244 #> 8155 2063 3M CC64 2017 2017-05-01 TKN -0.2876820725 #> 8156 2063 3M CC64 2017 2017-05-01 TN -0.2850189550 + #> 8157 2063 3M CC64 2017 2017-05-01 TP -2.6736487744 #> 8158 2063 3M CC64 2017 2017-05-01 TURB 0.7419373447 #> 8159 2063 3M CC64 2017 2017-06-05 CHLAC 1.3862943611 A #> 8160 2063 3M CC64 2017 2017-06-05 COLOR 2.7080502011 #> 8161 2063 3M CC64 2017 2017-06-05 DO 2.1294214740 #> 8162 2063 3M CC64 2017 2017-06-05 DOSAT 4.8835592115 + #> 8163 2063 3M CC64 2017 2017-06-05 NO23 -4.5098600062 #> 8164 2063 3M CC64 2017 2017-06-05 SALIN 3.5322256441 #> 8165 2063 3M CC64 2017 2017-06-05 TKN -0.3147107448 #> 8166 2063 3M CC64 2017 2017-06-05 TN -0.2997546537 + #> 8167 2063 3M CC64 2017 2017-06-05 TP -2.5639498571 #> 8168 2063 3M CC64 2017 2017-06-05 TURB 0.8754687374 #> 8169 2063 3M CC64 2017 2017-07-10 CHLAC 2.2512917986 #> 8170 2063 3M CC64 2017 2017-07-10 COLOR 4.4426512565 #> 8171 2063 3M CC64 2017 2017-07-10 DO 0.8458682676 #> 8172 2063 3M CC64 2017 2017-07-10 DOSAT 3.5292973843 + #> 8173 2063 3M CC64 2017 2017-07-10 NO23 -4.6051701860 I #> 8174 2063 3M CC64 2017 2017-07-10 SALIN 2.7408400239 #> 8175 2063 3M CC64 2017 2017-07-10 TKN 0.0000000000 #> 8176 2063 3M CC64 2017 2017-07-10 TN 0.0039920213 + #> 8177 2063 3M CC64 2017 2017-07-10 TP -1.5141277326 #> 8178 2063 3M CC64 2017 2017-07-10 TURB 0.4054651081 #> 8179 2063 3M CC64 2017 2017-08-07 CHLAC 1.5892352051 #> 8180 2063 3M CC64 2017 2017-08-07 COLOR 4.5747109785 A #> 8181 2063 3M CC64 2017 2017-08-07 DO 0.4121096508 #> 8182 2063 3M CC64 2017 2017-08-07 DOSAT 3.0349529867 + #> 8183 2063 3M CC64 2017 2017-08-07 NO23 -3.7297014486 #> 8184 2063 3M CC64 2017 2017-08-07 SALIN 2.0693912058 #> 8185 2063 3M CC64 2017 2017-08-07 TKN -0.0202027073 #> 8186 2063 3M CC64 2017 2017-08-07 TN 0.0039920213 + #> 8187 2063 3M CC64 2017 2017-08-07 TP -1.6607312068 #> 8188 2063 3M CC64 2017 2017-08-07 TURB 0.6931471806 #> 8189 2063 3M CC64 2017 2017-09-05 CHLAC 1.6094379124 #> 8190 2063 3M CC64 2017 2017-09-05 COLOR 4.7874917428 #> 8191 2063 3M CC64 2017 2017-09-05 DO 0.8586616190 #> 8192 2063 3M CC64 2017 2017-09-05 DOSAT 3.4404180948 + #> 8193 2063 3M CC64 2017 2017-09-05 NO23 -3.0159349809 #> 8194 2063 3M CC64 2017 2017-09-05 SALIN 0.9001613499 #> 8195 2063 3M CC64 2017 2017-09-05 TKN -0.1508228897 #> 8196 2063 3M CC64 2017 2017-09-05 TN -0.0954101848 + #> 8197 2063 3M CC64 2017 2017-09-05 TP -2.0402208285 #> 8198 2063 3M CC64 2017 2017-09-05 TURB 0.5877866649 #> 8199 2063 3M CC64 2017 2017-10-02 CHLAC 1.3083328197 #> 8200 2063 3M CC64 2017 2017-10-02 COLOR 4.4998096703 #> 8201 2063 3M CC64 2017 2017-10-02 NO23 -3.1465551633 #> 8202 2063 3M CC64 2017 2017-10-02 TKN -0.9675840263 #> 8203 2063 3M CC64 2017 2017-10-02 TN -0.8603830999 + #> 8204 2063 3M CC64 2017 2017-10-02 TP -1.6094379124 #> 8205 2063 3M CC64 2017 2017-10-02 TURB 0.3364722366 #> 8206 2063 3M CC64 2017 2017-11-06 CHLAC 0.7419373447 #> 8207 2063 3M CC64 2017 2017-11-06 COLOR 3.5835189385 #> 8208 2063 3M CC64 2017 2017-11-06 DO 2.0014800002 #> 8209 2063 3M CC64 2017 2017-11-06 DOSAT 4.5890408041 + #> 8210 2063 3M CC64 2017 2017-11-06 NO23 -3.4420193762 #> 8211 2063 3M CC64 2017 2017-11-06 SALIN 3.0864866368 #> 8212 2063 3M CC64 2017 2017-11-06 TKN -0.5798184953 #> 8213 2063 3M CC64 2017 2017-11-06 TN -0.5242486441 + #> 8214 2063 3M CC64 2017 2017-11-06 TP -1.8971199849 #> 8215 2063 3M CC64 2017 2017-11-06 TURB 0.3364722366 #> 8216 2063 3M CC64 2017 2017-11-06 CHLAC 0.8754687374 #> 8217 2063 3M CC64 2017 2017-11-06 COLOR 3.5553480615 #> 8218 2063 3M CC64 2017 2017-11-06 NO23 -3.4112477175 #> 8219 2063 3M CC64 2017 2017-11-06 TKN -0.6161861394 #> 8220 2063 3M CC64 2017 2017-11-06 TN -0.5568695623 + #> 8221 2063 3M CC64 2017 2017-11-06 TP -1.8971199849 #> 8222 2063 3M CC64 2017 2017-11-06 TURB 0.1823215568 #> 8223 2063 3M CC64 2017 2017-12-04 CHLAC 0.9162907319 #> 8224 2063 3M CC64 2017 2017-12-04 COLOR 3.1780538303 #> 8225 2063 3M CC64 2017 2017-12-04 DO 1.5644405465 #> 8226 2063 3M CC64 2017 2017-12-04 DOSAT 4.1287459889 #> 8227 2063 3M CC64 2017 2017-12-04 NO23 -4.5098600062 #> 8228 2063 3M CC64 2017 2017-12-04 SALIN 3.3403852423 #> 8229 2063 3M CC64 2017 2017-12-04 TKN -0.5276327421 #> 8230 2063 3M CC64 2017 2017-12-04 TN -0.5091603444 + #> 8231 2063 3M CC64 2017 2017-12-04 TP -2.2072749132 #> 8232 2063 3M CC64 2017 2017-12-04 TURB 0.3364722366 #> 8233 2063 3M CC64 2018 2018-01-02 CHLAC 2.7725887222 #> 8234 2063 3M CC64 2018 2018-01-02 COLOR 3.0910424534 #> 8235 2063 3M CC64 2018 2018-01-02 DOSAT 4.0360089852 + #> 8236 2063 3M CC64 2018 2018-01-02 NO23 -5.5214609179 U #> 8237 2063 3M CC64 2018 2018-01-02 SALIN 3.2657594108 #> 8238 2063 3M CC64 2018 2018-01-02 TKN -0.3147107448 #> 8239 2063 3M CC64 2018 2018-01-02 TN -0.3119747650 + #> 8240 2063 3M CC64 2018 2018-01-02 TP -1.6607312068 #> 8241 2063 3M CC64 2018 2018-01-02 TURB 2.3978952728 #> 8242 2063 3M CC64 2018 2018-03-05 CHLAC 0.5306282511 I #> 8243 2063 3M CC64 2018 2018-03-05 COLOR 2.6390573296 #> 8244 2063 3M CC64 2018 2018-03-05 DOSAT 4.2416144810 #> 8245 2063 3M CC64 2018 2018-03-05 NO23 -5.5214609179 I #> 8246 2063 3M CC64 2018 2018-03-05 SALIN 3.3467411959 #> 8247 2063 3M CC64 2018 2018-03-05 TKN -0.5621189182 #> 8248 2063 3M CC64 2018 2018-03-05 TN -0.5551258827 + #> 8249 2063 3M CC64 2018 2018-03-05 TP -2.1202635362 #> 8250 2063 3M CC64 2018 2018-03-05 TURB 0.4700036292 #> 8251 2063 3M CC64 2018 2018-04-02 CHLAC 0.7884573604 #> 8252 2063 3M CC64 2018 2018-04-02 COLOR 2.3978952728 #> 8253 2063 3M CC64 2018 2018-04-02 DO 1.5040773968 #> 8254 2063 3M CC64 2018 2018-04-02 DOSAT 3.4307561839 #> 8255 2063 3M CC64 2018 2018-04-02 NO23 -4.9618451299 I #> 8256 2063 3M CC64 2018 2018-04-02 SALIN 3.4330189940 #> 8257 2063 3M CC64 2018 2018-04-02 TKN -0.5798184953 #> 8258 2063 3M CC64 2018 2018-04-02 TN -0.5727010275 + #> 8259 2063 3M CC64 2018 2018-04-02 TP -2.2072749132 #> 8260 2063 3M CC64 2018 2018-04-02 TURB 0.7419373447 #> 8261 2063 3M CC64 2018 2018-05-07 CHLAC 1.4350845253 #> 8262 2063 3M CC64 2018 2018-05-07 COLOR 2.5649493575 #> 8263 2063 3M CC64 2018 2018-05-07 DO 1.3962446920 #> 8264 2063 3M CC64 2018 2018-05-07 DOSAT 4.0842942264 #> 8265 2063 3M CC64 2018 2018-05-07 NO23 -5.1159958098 I #> 8266 2063 3M CC64 2018 2018-05-07 SALIN 3.4388142452 #> 8267 2063 3M CC64 2018 2018-05-07 TKN -0.3424903089 #> 8268 2063 3M CC64 2018 2018-05-07 TN -0.3368723166 + #> 8269 2063 3M CC64 2018 2018-05-07 TP -2.0402208285 #> 8270 2063 3M CC64 2018 2018-05-07 TURB 1.0986122887 #> 8271 2063 3M CC64 2018 2018-07-09 CHLAC 0.9555114450 #> 8272 2063 3M CC64 2018 2018-07-09 COLOR 4.5747109785 #> 8273 2063 3M CC64 2018 2018-07-09 DO 0.6312717768 #> 8274 2063 3M CC64 2018 2018-07-09 DOSAT 3.2308043957 #> 8275 2063 3M CC64 2018 2018-07-09 NO23 -3.6119184130 #> 8276 2063 3M CC64 2018 2018-07-09 SALIN 1.8640801308 #> 8277 2063 3M CC64 2018 2018-07-09 TKN 0.0000000000 #> 8278 2063 3M CC64 2018 2018-07-09 TN 0.0266419309 + #> 8279 2063 3M CC64 2018 2018-07-09 TP -2.3025850930 #> 8280 2063 3M CC64 2018 2018-07-09 TURB 0.1823215568 #> 8281 2063 3M CC64 2018 2018-08-06 CHLAC 1.0986122887 #> 8282 2063 3M CC64 2018 2018-08-06 COLOR 4.5951198501 #> 8283 2063 3M CC64 2018 2018-08-06 DO 0.8796267475 #> 8284 2063 3M CC64 2018 2018-08-06 DOSAT 3.4339872045 #> 8285 2063 3M CC64 2018 2018-08-06 NO23 -3.4737680745 #> 8286 2063 3M CC64 2018 2018-08-06 SALIN 1.6448050563 #> 8287 2063 3M CC64 2018 2018-08-06 TKN -0.1508228897 #> 8288 2063 3M CC64 2018 2018-08-06 TN -0.1154108515 + #> 8289 2063 3M CC64 2018 2018-08-06 TP -2.3227878003 #> 8290 2063 3M CC64 2018 2018-08-06 TURB 0.5877866649 #> 8291 2063 3M CC64 2019 2019-02-04 CHLAC 1.1314021115 #> 8292 2063 3M CC64 2019 2019-02-04 COLOR 3.0910424534 #> 8293 2063 3M CC64 2019 2019-02-04 DO 1.8764069433 #> 8294 2063 3M CC64 2019 2019-02-04 DOSAT 4.4200447019 #> 8295 2063 3M CC64 2019 2019-02-04 NO23 -4.8283137373 I #> 8296 2063 3M CC64 2019 2019-02-04 SALIN 3.0928589843 #> 8297 2063 3M CC64 2019 2019-02-04 TKN -0.7765287895 #> 8298 2063 3M CC64 2019 2019-02-04 TN -0.7678707268 + #> 8299 2063 3M CC64 2019 2019-02-04 TP -2.3025850930 #> 8300 2063 3M CC64 2019 2019-02-04 TURB 0.6418538862 #> 8301 2063 3M CC64 2019 2019-03-04 CHLAC 0.8329091229 #> 8302 2063 3M CC64 2019 2019-03-04 COLOR 3.1354942159 #> 8303 2063 3M CC64 2019 2019-03-04 DO 1.6014057407 #> 8304 2063 3M CC64 2019 2019-03-04 DOSAT 4.2297491992 #> 8305 2063 3M CC64 2019 2019-03-04 NO23 -4.8283137373 I #> 8306 2063 3M CC64 2019 2019-03-04 SALIN 2.9992261628 #> 8307 2063 3M CC64 2019 2019-03-04 TKN -0.5798184953 #> 8308 2063 3M CC64 2019 2019-03-04 TN -0.5727010275 + #> 8309 2063 3M CC64 2019 2019-03-04 TP -2.3025850930 #> 8310 2063 3M CC64 2019 2019-03-04 TURB 0.5306282511 #> 8311 2063 3M CC64 2019 2019-04-01 CHLAC 0.4700036292 I #> 8312 2063 3M CC64 2019 2019-04-01 COLOR 2.7725887222 #> 8313 2063 3M CC64 2019 2019-04-01 DO 1.3962446920 #> 8314 2063 3M CC64 2019 2019-04-01 DOSAT 3.9889840466 #> 8315 2063 3M CC64 2019 2019-04-01 NO23 -4.5098600062 #> 8316 2063 3M CC64 2019 2019-04-01 SALIN 3.1210424645 #> 8317 2063 3M CC64 2019 2019-04-01 TKN -0.5276327421 #> 8318 2063 3M CC64 2019 2019-04-01 TN -0.5091603444 + #> 8319 2063 3M CC64 2019 2019-04-01 TP -2.3126354288 #> 8320 2063 3M CC64 2019 2019-04-01 TURB 0.4700036292 #> 8321 2063 3M CC64 2019 2019-05-06 CHLAC 0.6931471806 I #> 8322 2063 3M CC64 2019 2019-05-06 COLOR 2.9444389792 #> 8323 2063 3M CC64 2019 2019-05-06 DO 0.8372475245 #> 8324 2063 3M CC64 2019 2019-05-06 DOSAT 3.5292973843 #> 8325 2063 3M CC64 2019 2019-05-06 NO23 -4.6051701860 I #> 8326 2063 3M CC64 2019 2019-05-06 SALIN 3.2331731296 #> 8327 2063 3M CC64 2019 2019-05-06 TKN -0.5621189182 #> 8328 2063 3M CC64 2019 2019-05-06 TN -0.5551258827 + #> 8329 2063 3M CC64 2019 2019-05-06 TP -2.2072749132 #> 8330 2063 3M CC64 2019 2019-05-06 TURB 0.2623642645 #> 8331 2063 3M CC64 2019 2019-06-03 CHLAC 0.7419373447 I #> 8332 2063 3M CC64 2019 2019-06-03 COLOR 2.8903717579 #> 8333 2063 3M CC64 2019 2019-06-03 DO 1.2974631474 #> 8334 2063 3M CC64 2019 2019-06-03 DOSAT 3.7220724215 #> 8335 2063 3M CC64 2019 2019-06-03 NO23 -5.2983173665 I #> 8336 2063 3M CC64 2019 2019-06-03 SALIN 3.2703291065 #> 8337 2063 3M CC64 2019 2019-06-03 TKN -0.3856624808 #> 8338 2063 3M CC64 2019 2019-06-03 TN -0.3797973614 + #> 8339 2063 3M CC64 2019 2019-06-03 TP -2.3025850930 #> 8340 2063 3M CC64 2019 2019-06-03 TURB 0.2623642645 #> 8341 2063 3M CC64 2019 2019-07-01 CHLAC 1.0986122887 #> 8342 2063 3M CC64 2019 2019-07-01 COLOR 2.8903717579 #> 8343 2063 3M CC64 2019 2019-07-01 DO 1.4036429995 #> 8344 2063 3M CC64 2019 2019-07-01 DOSAT 4.1108738642 #> 8345 2063 3M CC64 2019 2019-07-01 NO23 -5.1159958098 I #> 8346 2063 3M CC64 2019 2019-07-01 SALIN 3.1675825305 #> 8347 2063 3M CC64 2019 2019-07-01 TKN -0.4780358009 #> 8348 2063 3M CC64 2019 2019-07-01 TN -0.4716049106 + #> 8349 2063 3M CC64 2019 2019-07-01 TP -2.2072749132 #> 8350 2063 3M CC64 2019 2019-07-01 TURB 0.5877866649 #> 8351 2063 3M CC64 2019 2019-08-05 CHLAC 1.7578579176 #> 8352 2063 3M CC64 2019 2019-08-05 COLOR 3.9120230054 #> 8353 2063 3M CC64 2019 2019-08-05 DO 1.3001916621 #> 8354 2063 3M CC64 2019 2019-08-05 DOSAT 3.9702919136 #> 8355 2063 3M CC64 2019 2019-08-05 NO23 -5.5214609179 U #> 8356 2063 3M CC64 2019 2019-08-05 SALIN 2.8273136219 #> 8357 2063 3M CC64 2019 2019-08-05 TKN -0.1863295782 #> 8358 2063 3M CC64 2019 2019-08-05 TN -0.1839228382 + #> 8359 2063 3M CC64 2019 2019-08-05 TP -1.8325814637 #> 8360 2063 3M CC64 2019 2019-08-05 TURB 0.4700036292 #> 8361 2063 3M CC64 2019 2019-10-07 CHLAC 1.1939224685 #> 8362 2063 3M CC64 2019 2019-10-07 COLOR 3.2958368660 #> 8363 2063 3M CC64 2019 2019-10-07 DO 1.6863989536 #> 8364 2063 3M CC64 2019 2019-10-07 DOSAT 4.3412046402 #> 8365 2063 3M CC64 2019 2019-10-07 NO23 -5.1159958098 I #> 8366 2063 3M CC64 2019 2019-10-07 SALIN 3.2672849641 #> 8367 2063 3M CC64 2019 2019-10-07 TKN -0.4780358009 #> 8368 2063 3M CC64 2019 2019-10-07 TN -0.4716049106 + #> 8369 2063 3M CC64 2019 2019-10-07 TP -2.1202635362 #> 8370 2063 3M CC64 2019 2019-10-07 TURB 0.2623642645 #> 8371 2063 3M CC64 2019 2019-11-04 CHLAC 1.1939224685 #> 8372 2063 3M CC64 2019 2019-11-04 COLOR 3.1354942159 #> 8373 2063 3M CC64 2019 2019-11-04 DO 1.3110318766 #> 8374 2063 3M CC64 2019 2019-11-04 DOSAT 3.9646154555 #> 8375 2063 3M CC64 2019 2019-11-04 NO23 -4.6051701860 #> 8376 2063 3M CC64 2019 2019-11-04 SALIN 3.2503744919 #> 8377 2063 3M CC64 2019 2019-11-04 TKN -0.4307829161 #> 8378 2063 3M CC64 2019 2019-11-04 TN -0.4155154440 + #> 8379 2063 3M CC64 2019 2019-11-04 TP -2.1202635362 #> 8380 2063 3M CC64 2019 2019-11-04 TURB 0.0953101798 #> 8381 2063 3M CC64 2020 2020-01-06 CHLAC 1.0296194172 #> 8382 2063 3M CC64 2020 2020-01-06 COLOR 2.8332133441 #> 8383 2063 3M CC64 2020 2020-01-06 DO 1.6937790609 #> 8384 2063 3M CC64 2020 2020-01-06 DOSAT 4.2312037449 #> 8385 2063 3M CC64 2020 2020-01-06 NO23 -4.0745419349 #> 8386 2063 3M CC64 2020 2020-01-06 SALIN 3.2188758249 #> 8387 2063 3M CC64 2020 2020-01-06 TKN -0.4155154440 #> 8388 2063 3M CC64 2020 2020-01-06 TN -0.3900840061 + #> 8389 2063 3M CC64 2020 2020-01-06 TP -2.2072749132 #> 8390 2063 3M CC64 2020 2020-01-06 TURB 0.6931471806 #> 8391 2063 3M CC64 2020 2020-02-03 CHLAC 0.2623642645 I #> 8392 2063 3M CC64 2020 2020-02-03 COLOR 2.8332133441 #> 8393 2063 3M CC64 2020 2020-02-03 DO 1.5789787049 #> 8394 2063 3M CC64 2020 2020-02-03 DOSAT 4.0842942264 #> 8395 2063 3M CC64 2020 2020-02-03 NO23 -3.5755507688 #> 8396 2063 3M CC64 2020 2020-02-03 SALIN 3.2104403460 #> 8397 2063 3M CC64 2020 2020-02-03 TKN -0.6539264674 #> 8398 2063 3M CC64 2020 2020-02-03 TN -0.6014799920 + #> 8399 2063 3M CC64 2020 2020-02-03 TP -2.3434070875 #> 8400 2063 3M CC64 2020 2020-02-03 TURB 0.9162907319 #> 8401 2063 3M CC64 2020 2020-02-03 CHLAC 0.4700036292 I #> 8402 2063 3M CC64 2020 2020-02-03 COLOR 2.8332133441 #> 8403 2063 3M CC64 2020 2020-02-03 NO23 -3.5404594490 #> 8404 2063 3M CC64 2020 2020-02-03 TKN -0.7339691751 #> 8405 2063 3M CC64 2020 2020-02-03 TN -0.6753072624 + #> 8406 2063 3M CC64 2020 2020-02-03 TP -2.3859667019 #> 8407 2063 3M CC64 2020 2020-02-03 TURB 0.7884573604 #> 8408 2063 3M CC64 2020 2020-03-02 CHLAC 0.6931471806 I #> 8409 2063 3M CC64 2020 2020-03-02 COLOR 2.5649493575 A #> 8410 2063 3M CC64 2020 2020-03-02 DO 1.7749523509 #> 8411 2063 3M CC64 2020 2020-03-02 DOSAT 4.3067641502 #> 8412 2063 3M CC64 2020 2020-03-02 NO23 -5.5214609179 I #> 8413 2063 3M CC64 2020 2020-03-02 SALIN 3.2924979647 #> 8414 2063 3M CC64 2020 2020-03-02 TKN -0.8915981193 #> 8415 2063 3M CC64 2020 2020-03-02 TN -0.8818893052 + #> 8416 2063 3M CC64 2020 2020-03-02 TP -2.3968957725 #> 8417 2063 3M CC64 2020 2020-03-02 TURB 0.2623642645 #> 8418 2063 3M CC64 2020 2020-09-08 CHLAC 2.3025850930 A #> 8419 2063 3M CC64 2020 2020-09-08 COLOR 4.0253516907 #> 8420 2063 3M CC64 2020 2020-09-08 DO 0.1484200051 #> 8421 2063 3M CC64 2020 2020-09-08 DOSAT 2.8332133441 #> 8422 2063 3M CC64 2020 2020-09-08 NO23 -5.1159958098 I #> 8423 2063 3M CC64 2020 2020-09-08 SALIN 2.9693882982 #> 8424 2063 3M CC64 2020 2020-09-08 TKN -0.2231435513 #> 8425 2063 3M CC64 2020 2020-09-08 TN -0.2181560098 + #> 8426 2063 3M CC64 2020 2020-09-08 TP -1.5141277326 #> 8427 2063 3M CC64 2020 2020-09-08 TURB 0.5306282511 #> 8428 2063 3M CC64 2020 2020-10-05 CHLAC 1.5040773968 #> 8429 2063 3M CC64 2020 2020-10-05 COLOR 4.2626798770 #> 8430 2063 3M CC64 2020 2020-10-05 DO 1.1600209168 #> 8431 2063 3M CC64 2020 2020-10-05 DOSAT 3.7495040759 #> 8432 2063 3M CC64 2020 2020-10-05 NO23 -3.0365542681 #> 8433 2063 3M CC64 2020 2020-10-05 SALIN 2.5649493575 #> 8434 2063 3M CC64 2020 2020-10-05 TKN -0.0408219945 #> 8435 2063 3M CC64 2020 2020-10-05 TN 0.0079681696 + #> 8436 2063 3M CC64 2020 2020-10-05 TP -1.8971199849 #> 8437 2063 3M CC64 2020 2020-10-05 TURB 0.0953101798 #> 8438 2063 3M CC64 2020 2020-11-02 CHLAC 1.1631508098 I #> 8439 2063 3M CC64 2020 2020-11-02 COLOR 4.0073331852 A #> 8440 2063 3M CC64 2020 2020-11-02 NO23 -3.9633162998 #> 8441 2063 3M CC64 2020 2020-11-02 SALIN 2.7562052430 #> 8442 2063 3M CC64 2020 2020-11-02 TKN -0.3710636814 #> 8443 2063 3M CC64 2020 2020-11-02 TN -0.3438997525 + #> 8444 2063 3M CC64 2020 2020-11-02 TP -2.0402208285 #> 8445 2063 3M CC64 2020 2020-11-02 TURB 0.2623642645 #> 8446 2063 3M CC64 2020 2020-12-07 CHLAC 0.3364722366 I #> 8447 2063 3M CC64 2020 2020-12-07 COLOR 3.6635616461 #> 8448 2063 3M CC64 2020 2020-12-07 DO 1.6677068206 #> 8449 2063 3M CC64 2020 2020-12-07 DOSAT 4.1743872699 #> 8450 2063 3M CC64 2020 2020-12-07 NO23 -3.8167128256 #> 8451 2063 3M CC64 2020 2020-12-07 SALIN 2.9982291538 #> 8452 2063 3M CC64 2020 2020-12-07 TKN -0.3856624808 #> 8453 2063 3M CC64 2020 2020-12-07 TN -0.3538218750 + #> 8454 2063 3M CC64 2020 2020-12-07 TP -2.4769384801 #> 8455 2063 3M CC64 2020 2020-12-07 TURB 0.1823215568 #> 8456 2063 3M CC64 2021 2021-01-04 CHLAC 0.3364722366 I #> 8457 2063 3M CC64 2021 2021-01-04 COLOR 3.1780538303 #> 8458 2063 3M CC64 2021 2021-01-04 DO 1.4816045409 #> 8459 2063 3M CC64 2021 2021-01-04 DOSAT 4.0271358125 #> 8460 2063 3M CC64 2021 2021-01-04 NO23 -4.1351665567 #> 8461 2063 3M CC64 2021 2021-01-04 SALIN 3.1376657694 #> 8462 2063 3M CC64 2021 2021-01-04 TKN -0.5276327421 #> 8463 2063 3M CC64 2021 2021-01-04 TN -0.5008752929 + #> 8464 2063 3M CC64 2021 2021-01-04 TP -2.3025850930 #> 8465 2063 3M CC64 2021 2021-01-04 TURB 0.2623642645 #> 8466 2063 3M CC64 2021 2021-02-01 CHLAC 0.9932517730 #> 8467 2063 3M CC64 2021 2021-02-01 COLOR 2.8332133441 #> 8468 2063 3M CC64 2021 2021-02-01 DO 1.8082887712 #> 8469 2063 3M CC64 2021 2021-02-01 DOSAT 4.3489867806 #> 8470 2063 3M CC64 2021 2021-02-01 NO23 -4.9618451299 I #> 8471 2063 3M CC64 2021 2021-02-01 SALIN 3.2120525995 #> 8472 2063 3M CC64 2021 2021-02-01 TKN -0.5276327421 #> 8473 2063 3M CC64 2021 2021-02-01 TN -0.5208759596 + #> 8474 2063 3M CC64 2021 2021-02-01 TP -2.3751557858 #> 8475 2063 3M CC64 2021 2021-02-01 TURB 1.1631508098 #> 8476 2063 3M CC64 2021 2021-03-01 CHLAC 0.6418538862 I #> 8477 2063 3M CC64 2021 2021-03-01 COLOR 2.6390573296 #> 8478 2063 3M CC64 2021 2021-03-01 DO 1.5454325825 #> 8479 2063 3M CC64 2021 2021-03-01 DOSAT 4.1956970565 #> 8480 2063 3M CC64 2021 2021-03-01 NO23 -4.8283137373 I #> 8481 2063 3M CC64 2021 2021-03-01 SALIN 3.2861605717 #> 8482 2063 3M CC64 2021 2021-03-01 TKN -0.9675840263 I #> 8483 2063 3M CC64 2021 2021-03-01 TN -1.8078888512 + #> 8484 2063 3M CC64 2021 2021-03-01 TP -2.3859667019 #> 8485 2063 3M CC64 2021 2021-03-01 TURB 0.6931471806 A #> 8486 2063 3M CC64 2021 2021-04-05 CHLAC 1.5475625087 #> 8487 2063 3M CC64 2021 2021-04-05 COLOR 2.7080502011 #> 8488 2063 3M CC64 2021 2021-04-05 DO 1.6505798558 #> 8489 2063 3M CC64 2021 2021-04-05 DOSAT 4.2370008626 #> 8490 2063 3M CC64 2021 2021-04-05 NO23 -5.5214609179 U #> 8491 2063 3M CC64 2021 2021-04-05 SALIN 3.3010086544 #> 8492 2063 3M CC64 2021 2021-04-05 TN -0.4277107171 + #> 8493 2063 3M CC64 2021 2021-04-05 TP -2.2072749132 #> 8494 2063 3M CC64 2021 2021-04-05 TURB 1.2527629685 #> 8495 2063 3M CC64 2021 2021-05-03 CHLAC 0.9932517730 #> 8496 2063 3M CC64 2021 2021-05-03 COLOR 2.9957322736 #> 8497 2063 3M CC64 2021 2021-05-03 DO 1.2584609896 #> 8498 2063 3M CC64 2021 2021-05-03 DOSAT 3.9740583963 #> 8499 2063 3M CC64 2021 2021-05-03 NO23 -5.5214609179 U #> 8500 2063 3M CC64 2021 2021-05-03 SALIN 3.3641875560 #> 8501 2063 3M CC64 2021 2021-05-03 TKN -0.7133498879 #> 8502 2063 3M CC64 2021 2021-05-03 TN -0.7092765625 + #> 8503 2063 3M CC64 2021 2021-05-03 TP -2.3227878003 #> 8504 2063 3M CC64 2021 2021-05-03 TURB 0.7419373447 #> 8505 2063 3M CC64 2021 2021-05-03 CHLAC 1.2809338455 #> 8506 2063 3M CC64 2021 2021-05-03 COLOR 2.9444389792 #> 8507 2063 3M CC64 2021 2021-05-03 NO23 -5.5214609179 U #> 8508 2063 3M CC64 2021 2021-05-03 TKN -0.5621189182 #> 8509 2063 3M CC64 2021 2021-05-03 TN -0.5586162876 + #> 8510 2063 3M CC64 2021 2021-05-03 TP -2.3227878003 #> 8511 2063 3M CC64 2021 2021-05-03 TURB 0.7884573604 #> 8512 2063 3M CC64 2021 2021-06-07 CHLAC 1.7578579176 #> 8513 2063 3M CC64 2021 2021-06-07 COLOR 2.8332133441 #> 8514 2063 3M CC64 2021 2021-06-07 DO 0.9707789172 #> 8515 2063 3M CC64 2021 2021-06-07 DOSAT 3.6788291183 #> 8516 2063 3M CC64 2021 2021-06-07 NO23 -4.3428059215 #> 8517 2063 3M CC64 2021 2021-06-07 SALIN 3.2839142210 #> 8518 2063 3M CC64 2021 2021-06-07 TKN -0.4620354596 #> 8519 2063 3M CC64 2021 2021-06-07 TN -0.4416105547 + #> 8520 2063 3M CC64 2021 2021-06-07 TP -2.4304184645 #> 8521 2063 3M CC64 2021 2021-06-07 TURB 0.4054651081 #> 8522 2063 3M CC64 2021 2021-08-02 CHLAC 1.6094379124 #> 8523 2063 3M CC64 2021 2021-08-02 COLOR 4.3438054219 #> 8524 2063 3M CC64 2021 2021-08-02 DO 1.4255150743 #> 8525 2063 3M 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8597 2063 3M CC64 2022 2022-03-07 SALIN 3.4170707308 #> 8598 2063 3M CC64 2022 2022-03-07 TKN -0.7339691751 #> 8599 2063 3M CC64 2022 2022-03-07 TN -0.7298111649 + #> 8600 2063 3M CC64 2022 2022-03-07 TP -2.7968814148 #> 8601 2063 3M CC64 2022 2022-03-07 TURB 0.4054651081 #> 8602 2063 3M CC64 2022 2022-04-04 CHLAC 1.4109869737 #> 8603 2063 3M CC64 2022 2022-04-04 COLOR 2.2823823857 #> 8604 2063 3M CC64 2022 2022-04-04 DO 1.3350010667 #> 8605 2063 3M CC64 2022 2022-04-04 DOSAT 3.9889840466 #> 8606 2063 3M CC64 2022 2022-04-04 NO23 -4.6051701860 I #> 8607 2063 3M CC64 2022 2022-04-04 SALIN 3.4157575330 #> 8608 2063 3M CC64 2022 2022-04-04 TKN -0.9942522733 I #> 8609 2063 3M CC64 2022 2022-04-04 TN -1.8078888512 + #> 8610 2063 3M CC64 2022 2022-04-04 TP -2.4079456087 #> 8611 2063 3M CC64 2022 2022-04-04 TURB 0.2623642645 #> 8612 2063 3M CC64 2022 2022-05-02 CHLAC 1.0986122887 #> 8613 2063 3M CC64 2022 2022-05-02 COLOR 1.0647107370 I #> 8614 2063 3M CC64 2022 2022-05-02 DO 1.3987168811 #> 8615 2063 3M CC64 2022 2022-05-02 DOSAT 4.0775374439 #> 8616 2063 3M CC64 2022 2022-05-02 NO23 -5.2983173665 I #> 8617 2063 3M CC64 2022 2022-05-02 SALIN 3.4229588734 #> 8618 2063 3M CC64 2022 2022-05-02 TKN -0.5447271754 #> 8619 2063 3M CC64 2022 2022-05-02 TN -0.5378542962 + #> 8620 2063 3M CC64 2022 2022-05-02 TP -2.4651040225 #> 8621 2063 3M CC64 2022 2022-05-02 TURB -0.0512932944 I #> 8622 2063 3M CC64 2013 2013-01-08 TN -0.7339691751 #> 8623 2063 3M CC64 2013 2013-01-08 TP -4.5098600062 #> 8624 2063 3M CC64 2013 2013-02-05 CHLAC 0.0000000000 I #> 8625 2063 3M CC64 2013 2013-03-05 CHLAC 0.6931471806 #> 8626 2063 3M CC64 2013 2013-03-05 TN -1.0788096614 #> 8627 2063 3M CC64 2013 2013-03-05 TP -2.6310891600 #> 8628 2063 3M CC64 2013 2013-04-02 CHLAC 1.0986122887 #> 8629 2063 3M CC64 2013 2013-04-02 TN -0.4620354596 #> 8630 2063 3M CC64 2013 2013-04-02 TP -2.4651040225 #> 8631 2063 3M CC64 2013 2013-05-07 CHLAC 1.0986122887 #> 8632 2063 3M CC64 2013 2013-05-07 TN -0.4942963218 #> 8633 2063 3M CC64 2013 2013-05-07 TP -2.2827824657 #> 8634 2063 3M CC64 2013 2013-06-04 CHLAC 0.6931471806 #> 8635 2063 3M CC64 2013 2013-06-04 TN -0.3285040670 #> 8636 2063 3M CC64 2013 2013-06-04 TP -2.5510464523 #> 8637 2063 3M CC64 2013 2013-07-03 CHLAC 0.6931471806 #> 8638 2063 3M CC64 2013 2013-07-03 TN -0.2107210313 #> 8639 2063 3M CC64 2013 2013-07-03 TP -2.6882475738 #> 8640 2063 3M CC64 2013 2013-08-06 CHLAC 1.0986122887 #> 8641 2063 3M CC64 2013 2013-08-06 TN -0.5276327421 #> 8642 2063 3M CC64 2013 2013-08-06 TP -2.2730262908 #> 8643 2063 3M CC64 2013 2013-09-10 CHLAC 1.3862943611 #> 8644 2063 3M CC64 2013 2013-09-10 TN -0.6733445533 #> 8645 2063 3M CC64 2013 2013-09-10 TP -2.5133061243 #> 8646 2063 3M CC64 2013 2013-10-01 CHLAC 1.9459101491 #> 8647 2063 3M CC64 2013 2013-10-01 TN -0.7765287895 #> 8648 2063 3M CC64 2013 2013-10-01 TP -3.1235656451 #> 8649 2063 3M CC64 2013 2013-11-05 CHLAC 1.0986122887 #> 8650 2063 3M CC64 2013 2013-11-05 TN -0.6733445533 #> 8651 2063 3M CC64 2013 2013-11-05 TP -2.2926347621 #> 8652 2063 3M CC64 2013 2013-12-03 TN -0.8209805521 #> 8653 2063 3M CC64 2013 2013-12-03 TP -2.3330443005 #> 8654 2063 3M CC64 2014 2014-01-07 CHLAC 1.0986122887 #> 8655 2063 3M CC64 2014 2014-01-07 TN -0.9942522733 #> 8656 2063 3M CC64 2014 2014-01-07 TP -2.5510464523 #> 8657 2063 3M CC64 2014 2014-02-04 CHLAC 0.0000000000 #> 8658 2063 3M CC64 2014 2014-02-04 TN -1.0498221245 #> 8659 2063 3M CC64 2014 2014-02-04 TP -2.6310891600 #> 8660 2063 3M CC64 2014 2014-03-04 CHLAC 1.3862943611 #> 8661 2063 3M CC64 2014 2014-03-04 TN -0.5978370008 #> 8662 2063 3M CC64 2014 2014-03-04 TP -2.7333680091 #> 8663 2063 3M CC64 2014 2014-04-01 CHLAC 1.0986122887 #> 8664 2063 3M CC64 2014 2014-04-01 TN -1.0788096614 #> 8665 2063 3M CC64 2014 2014-04-01 TP -2.7181005370 #> 8666 2063 3M CC64 2014 2014-06-03 CHLAC 1.3862943611 #> 8667 2063 3M CC64 2014 2014-06-03 TN -0.5798184953 #> 8668 2063 3M CC64 2014 2014-06-03 TP -2.2072749132 #> 8669 2063 3M CC64 2014 2014-09-02 CHLAC 3.1354942159 #> 8670 2063 3M CC64 2014 2014-09-02 TP -2.3126354288 #> 8671 2063 3M CC64 2014 2014-11-04 CHLAC 0.6931471806 #> 8672 2063 3M CC64 2014 2014-11-04 TN -0.5798184953 #> 8673 2063 3M CC64 2014 2014-11-04 TP -2.6310891600 #> 8674 2063 3M CC64 2014 2014-12-02 CHLAC 0.0000000000 #> 8675 2063 3M CC64 2014 2014-12-02 TN -0.4942963218 #> 8676 2063 3M CC64 2014 2014-12-02 TP -2.3751557858 #> 8677 2063 3M CC64 2015 2015-01-03 CHLAC 0.0000000000 #> 8678 2063 3M CC64 2015 2015-01-03 TN -0.3011050928 #> 8679 2063 3M CC64 2015 2015-01-03 TP -1.8018098051 #> 8680 2063 3M CC64 2015 2015-02-02 CHLAC 0.6931471806 #> 8681 2063 3M CC64 2015 2015-03-03 CHLAC 0.0000000000 #> 8682 2063 3M CC64 2015 2015-03-03 TN -0.5798184953 #> 8683 2063 3M CC64 2015 2015-03-03 TP -2.2730262908 #> 8684 2063 3M CC64 2015 2015-04-02 CHLAC 0.6931471806 #> 8685 2063 3M CC64 2015 2015-04-02 TN -0.4462871026 #> 8686 2063 3M CC64 2015 2015-04-02 TP -2.2926347621 #> 8687 2063 3M CC64 2015 2015-05-05 CHLAC 1.0986122887 #> 8688 2063 3M CC64 2015 2015-05-05 TN -0.8209805521 #> 8689 2063 3M CC64 2015 2015-05-05 TP -2.5257286443 #> 8690 2063 3M CC64 2015 2015-09-09 CHLAC 1.0986122887 #> 8691 2063 3M CC64 2015 2015-09-09 TN -0.5978370008 #> 8692 2063 3M CC64 2015 2015-09-09 TP -2.9759296463 #> 8693 2063 3M CC64 2015 2015-10-07 CHLAC 1.6094379124 #> 8694 2063 3M CC64 2015 2015-11-04 CHLAC 1.0986122887 #> 8695 2063 3M CC64 2015 2015-11-04 TN -0.6539264674 #> 8696 2063 3M CC64 2015 2015-11-04 TP -2.6172958378 #> 8697 2063 3M CC64 2015 2015-11-15 CHLAC 1.6094379124 #> 8698 2063 3M CC64 2015 2015-11-15 TN -0.8439700703 #> 8699 2063 3M CC64 2015 2015-11-15 TP -2.7968814148 #> 8700 2063 3M CC64 2016 2016-01-06 TN -0.1053605157 #> 8701 2063 3M CC64 2016 2016-01-06 TP -2.3126354288 #> 8702 2063 3M CC64 2016 2016-02-02 CHLAC 1.6094379124 #> 8703 2063 3M CC64 2016 2016-02-02 TN -0.2231435513 #> 8704 2063 3M CC64 2016 2016-02-02 TP -2.9957322736 #> 8705 2063 3M CC64 2016 2016-06-11 CHLAC 2.5649493575 #> 8706 2063 3M CC64 2016 2016-06-11 TN -0.8439700703 #> 8707 2063 3M CC64 2016 2016-06-11 TP -2.7488721956 #> 8708 2063 3M CC64 2016 2016-07-08 CHLAC 1.0986122887 #> 8709 2063 3M CC64 2016 2016-07-08 TN -0.7765287895 #> 8710 2063 3M CC64 2016 2016-07-08 TP -3.7722610631 #> 8711 2063 3M CC64 2016 2016-10-03 CHLAC 1.0986122887 #> 8712 2063 3M CC64 2016 2016-10-03 TN -0.2231435513 #> 8713 2063 3M CC64 2016 2016-10-03 TP -2.0874737134 #> 8714 2063 3M CC64 2018 2018-12-04 CHLAC 1.0986122887 #> 8715 2063 3M CC64 2018 2018-12-04 TN -0.7985076962 #> 8716 2063 3M CC64 2018 2018-12-04 TP -2.3644604967 #> 8717 2063 3M CC64 2019 2019-01-09 CHLAC 0.6931471806 I #> 8718 2063 3M CC64 2019 2019-01-09 TN -1.2039728043 #> 8719 2063 3M CC64 2019 2019-01-09 TP -2.7333680091 #> 8720 2081 3F CC67 2016 2016-04-27 CHLAC 1.7404661748 #> 8721 2081 3F CC67 2016 2016-04-27 COLOR 4.2046926194 #> 8722 2081 3F CC67 2016 2016-04-27 COND 6.3135480463 #> 8723 2081 3F CC67 2016 2016-04-27 DO 2.0918640617 #> 8724 2081 3F CC67 2016 2016-04-27 DOSAT 4.5849674787 #> 8725 2081 3F CC67 2016 2016-04-27 NO23 -4.3428059215 #> 8726 2081 3F CC67 2016 2016-04-27 SALIN -1.3093333200 + #> 8727 2081 3F CC67 2016 2016-04-27 TKN -0.1625189295 #> 8728 2081 3F CC67 2016 2016-04-27 TN -0.1473405879 + #> 8729 2081 3F CC67 2016 2016-04-27 TP -2.9187712324 #> 8730 2081 3F CC67 2016 2016-04-27 TSS 1.0986122887 I #> 8731 2081 3F CC67 2016 2016-04-27 TURB 1.8870696490 #> 8732 2081 3F CC67 2016 2016-09-21 CHLAC 2.2082744135 A #> 8733 2081 3F CC67 2016 2016-09-21 COLOR 4.9416424226 #> 8734 2081 3F CC67 2016 2016-09-21 COND 5.8636311756 #> 8735 2081 3F CC67 2016 2016-09-21 DO 1.7227665977 #> 8736 2081 3F CC67 2016 2016-09-21 DOSAT 4.3040650932 #> 8737 2081 3F CC67 2016 2016-09-21 NO23 -2.9565115604 #> 8738 2081 3F CC67 2016 2016-09-21 SALIN -1.6094379124 #> 8739 2081 3F CC67 2016 2016-09-21 TKN -0.1863295782 #> 8740 2081 3F CC67 2016 2016-09-21 TN -0.1255632230 + #> 8741 2081 3F CC67 2016 2016-09-21 TP -2.3025850930 #> 8742 2081 3F CC67 2016 2016-09-21 TSS 2.8332133441 #> 8743 2081 3F CC67 2016 2016-09-21 TURB 2.3025850930 #> 8744 2081 3F CC67 2016 2016-12-13 CHLAC 0.5306282511 I #> 8745 2081 3F CC67 2016 2016-12-13 COLOR 4.0253516907 #> 8746 2081 3F CC67 2016 2016-12-13 COND 6.2709884319 #> 8747 2081 3F CC67 2016 2016-12-13 DO 2.1860512767 #> 8748 2081 3F CC67 2016 2016-12-13 DOSAT 4.5951198501 #> 8749 2081 3F CC67 2016 2016-12-13 NO23 -1.8971199849 #> 8750 2081 3F CC67 2016 2016-12-13 SALIN -1.6094379124 #> 8751 2081 3F CC67 2016 2016-12-13 TKN -0.4942963218 #> 8752 2081 3F CC67 2016 2016-12-13 TN -0.2744368457 + #> 8753 2081 3F CC67 2016 2016-12-13 TP -2.9759296463 #> 8754 2081 3F CC67 2016 2016-12-13 TSS 1.3862943611 I #> 8755 2081 3F CC67 2016 2016-12-13 TURB 1.6486586256 #> 8756 2081 3F CC67 2016 2016-12-28 CHLAC 1.0296194172 #> 8757 2081 3F CC67 2016 2016-12-28 COLOR 4.1896547420 A #> 8758 2081 3F CC67 2016 2016-12-28 COND 6.2747620212 #> 8759 2081 3F CC67 2016 2016-12-28 NO23 -2.2072749132 #> 8760 2081 3F CC67 2016 2016-12-28 SALIN -1.3093333200 + #> 8761 2081 3F CC67 2016 2016-12-28 TKN -0.4004775666 #> 8762 2081 3F CC67 2016 2016-12-28 TN -0.2484613593 + #> 8763 2081 3F CC67 2016 2016-12-28 TP -2.6882475738 #> 8764 2081 3F CC67 2016 2016-12-28 TSS 1.7917594692 I #> 8765 2081 3F CC67 2016 2016-12-28 TURB 1.9878743482 A #> 8766 2081 3F CC67 2017 2017-07-26 CHLAC 2.3025850930 #> 8767 2081 3F CC67 2017 2017-07-26 COLOR 5.3471075307 #> 8768 2081 3F CC67 2017 2017-07-26 COND 5.8435444170 #> 8769 2081 3F CC67 2017 2017-07-26 DO 1.6486586256 #> 8770 2081 3F CC67 2017 2017-07-26 DOSAT 4.2626798770 #> 8771 2081 3F CC67 2017 2017-07-26 NO23 -3.3813947544 #> 8772 2081 3F CC67 2017 2017-07-26 TKN 0.0953101798 #> 8773 2081 3F CC67 2017 2017-07-26 TN 0.1257512053 + #> 8774 2081 3F CC67 2017 2017-07-26 TP -2.4191189092 #> 8775 2081 3F CC67 2017 2017-07-26 TSS 2.4849066498 #> 8776 2081 3F CC67 2017 2017-07-26 TURB 1.9315214116 #> 8777 2081 3F CC67 2017 2017-08-21 CHLAC 1.4350845253 #> 8778 2081 3F CC67 2017 2017-08-21 COLOR 4.7874917428 #> 8779 2081 3F CC67 2017 2017-08-21 COND 6.0497334552 #> 8780 2081 3F CC67 2017 2017-08-21 DO 1.9169226122 #> 8781 2081 3F CC67 2017 2017-08-21 DOSAT 4.5108595065 #> 8782 2081 3F CC67 2017 2017-08-21 NO23 -2.9957322736 #> 8783 2081 3F CC67 2017 2017-08-21 TKN -0.1984509387 #> 8784 2081 3F CC67 2017 2017-08-21 TN -0.1392620673 + #> 8785 2081 3F CC67 2017 2017-08-21 TP -2.7488721956 #> 8786 2081 3F CC67 2017 2017-08-21 TSS 2.3025850930 I #> 8787 2081 3F CC67 2017 2017-08-21 TURB 1.9740810260 A #> 8788 2081 3F CC67 2017 2017-10-04 CHLAC 2.0014800002 #> 8789 2081 3F CC67 2017 2017-10-04 COLOR 4.7874917428 #> 8790 2081 3F CC67 2017 2017-10-04 COND 5.9188938543 #> 8791 2081 3F CC67 2017 2017-10-04 DO 1.8718021769 #> 8792 2081 3F CC67 2017 2017-10-04 DOSAT 4.3944491547 #> 8793 2081 3F CC67 2017 2017-10-04 NO23 -3.1235656451 #> 8794 2081 3F CC67 2017 2017-10-04 SALIN -1.7719568419 + #> 8795 2081 3F CC67 2017 2017-10-04 TKN -0.2231435513 #> 8796 2081 3F CC67 2017 2017-10-04 TN -0.1696027844 + #> 8797 2081 3F CC67 2017 2017-10-04 TP -2.7488721956 #> 8798 2081 3F CC67 2017 2017-10-04 TSS 2.0794415417 I #> 8799 2081 3F CC67 2017 2017-10-04 TURB 1.6486586256 A #> 8800 2081 3F CC67 2017 2017-11-08 CHLAC 1.7404661748 #> 8801 2081 3F CC67 2017 2017-11-08 COLOR 4.2341065046 #> 8802 2081 3F CC67 2017 2017-11-08 COND 6.1377270541 #> 8803 2081 3F CC67 2017 2017-11-08 DO 2.1747517215 #> 8804 2081 3F CC67 2017 2017-11-08 DOSAT 4.6634390941 #> 8805 2081 3F CC67 2017 2017-11-08 NO23 -2.7030626596 #> 8806 2081 3F CC67 2017 2017-11-08 SALIN -1.4696759701 + #> 8807 2081 3F CC67 2017 2017-11-08 TKN -0.4942963218 #> 8808 2081 3F CC67 2017 2017-11-08 TN -0.3900840061 + #> 8809 2081 3F CC67 2017 2017-11-08 TP -3.1235656451 #> 8810 2081 3F CC67 2017 2017-11-08 TSS 1.0986122887 I #> 8811 2081 3F CC67 2017 2017-11-08 TURB 1.5686159179 #> 8812 2081 3F CC67 2017 2017-11-30 CHLAC 1.6677068206 #> 8813 2081 3F CC67 2017 2017-11-30 COLOR 4.1271343850 A #> 8814 2081 3F CC67 2017 2017-11-30 COND 6.2519038832 #> 8815 2081 3F CC67 2017 2017-11-30 DO 2.3025850930 #> 8816 2081 3F CC67 2017 2017-11-30 DOSAT 4.7535901911 #> 8817 2081 3F CC67 2017 2017-11-30 NO23 -3.2188758249 #> 8818 2081 3F CC67 2017 2017-11-30 SALIN -1.3470736480 + #> 8819 2081 3F CC67 2017 2017-11-30 TKN -0.5798184953 #> 8820 2081 3F CC67 2017 2017-11-30 TN -0.5108256238 + #> 8821 2081 3F CC67 2017 2017-11-30 TP -3.1700856607 #> 8822 2081 3F CC67 2017 2017-11-30 TSS 1.3862943611 I #> 8823 2081 3F CC67 2017 2017-11-30 TURB 1.5475625087 #> 8824 2081 3F CC67 2018 2018-04-12 COND 6.1717005974 #> 8825 2081 3F CC67 2018 2018-04-12 DO 2.6461747974 #> 8826 2081 3F CC67 2018 2018-04-12 DOSAT 5.1239639794 #> 8827 2081 3F CC67 2018 2018-04-12 SALIN -1.4696759701 + #> 8828 2081 3F CC67 2018 2018-04-19 CHLAC 2.2512917986 #> 8829 2081 3F CC67 2018 2018-04-19 COLOR 4.0943445622 #> 8830 2081 3F CC67 2018 2018-04-19 COND 6.0980742822 #> 8831 2081 3F CC67 2018 2018-04-19 DO 2.7317667277 #> 8832 2081 3F CC67 2018 2018-04-19 DOSAT 5.3107398865 #> 8833 2081 3F CC67 2018 2018-04-19 NO23 -5.5214609179 U #> 8834 2081 3F CC67 2018 2018-04-19 SALIN -1.6094379124 + #> 8835 2081 3F CC67 2018 2018-04-19 TKN -0.3424903089 #> 8836 2081 3F CC67 2018 2018-04-19 TN -0.3396773676 + #> 8837 2081 3F CC67 2018 2018-04-19 TP -4.2686979494 #> 8838 2081 3F CC67 2018 2018-04-19 TSS 1.0986122887 I #> 8839 2081 3F CC67 2018 2018-04-19 TURB 0.4054651081 #> 8840 2081 3F CC67 2018 2018-07-17 CHLAC 2.3978952728 #> 8841 2081 3F CC67 2018 2018-07-17 COLOR 5.2470240722 #> 8842 2081 3F CC67 2018 2018-07-17 COND 5.6559918108 #> 8843 2081 3F CC67 2018 2018-07-17 DO 1.6677068206 #> 8844 2081 3F CC67 2018 2018-07-17 DOSAT 4.2541932632 #> 8845 2081 3F CC67 2018 2018-07-17 NO23 -3.8167128256 #> 8846 2081 3F CC67 2018 2018-07-17 TKN -0.0304592075 #> 8847 2081 3F CC67 2018 2018-07-17 TN -0.0080321717 + #> 8848 2081 3F CC67 2018 2018-07-17 TP -2.7968814148 #> 8849 2081 3F CC67 2018 2018-07-17 TSS 1.7917594692 I #> 8850 2081 3F CC67 2018 2018-07-17 TURB 1.7047480922 #> 8851 2081 3F CC67 2018 2018-08-01 CHLAC 2.0014800002 #> 8852 2081 3F CC67 2018 2018-08-01 COLOR 4.9416424226 #> 8853 2081 3F CC67 2018 2018-08-01 COND 5.9269260260 #> 8854 2081 3F CC67 2018 2018-08-01 DO 1.8900953699 #> 8855 2081 3F CC67 2018 2018-08-01 DOSAT 4.4624538838 #> 8856 2081 3F CC67 2018 2018-08-01 NO23 -3.2188758249 #> 8857 2081 3F CC67 2018 2018-08-01 SALIN -1.7147984281 #> 8858 2081 3F CC67 2018 2018-08-01 TKN -0.2613647641 #> 8859 2081 3F CC67 2018 2018-08-01 TN -0.2107210313 + #> 8860 2081 3F CC67 2018 2018-08-01 TP -2.8824035882 #> 8861 2081 3F CC67 2018 2018-08-01 TSS 1.7917594692 I #> 8862 2081 3F CC67 2018 2018-08-01 TURB 1.7404661748 #> 8863 2081 3F CC67 2018 2018-08-01 CHLAC 2.1041341543 #> 8864 2081 3F CC67 2018 2018-08-01 COLOR 4.9416424226 #> 8865 2081 3F CC67 2018 2018-08-01 COND 5.9269260260 #> 8866 2081 3F CC67 2018 2018-08-01 DO 1.8900953699 #> 8867 2081 3F CC67 2018 2018-08-01 DOSAT 4.4624538838 #> 8868 2081 3F CC67 2018 2018-08-01 NO23 -3.2188758249 #> 8869 2081 3F CC67 2018 2018-08-01 SALIN -1.7147984281 #> 8870 2081 3F CC67 2018 2018-08-01 TKN -0.2357223335 #> 8871 2081 3F CC67 2018 2018-08-01 TN -0.1863295782 + #> 8872 2081 3F CC67 2018 2018-08-01 TP -2.8302178351 #> 8873 2081 3F CC67 2018 2018-08-01 TSS 1.7917594692 I #> 8874 2081 3F CC67 2018 2018-08-01 TURB 1.6863989536 #> 8875 2081 3F CC67 2018 2018-08-20 CHLAC 2.2407096893 #> 8876 2081 3F CC67 2018 2018-08-20 COLOR 5.0751738152 #> 8877 2081 3F CC67 2018 2018-08-20 COND 5.3706380281 #> 8878 2081 3F CC67 2018 2018-08-20 DO 1.5216989981 #> 8879 2081 3F CC67 2018 2018-08-20 DOSAT 4.0758410907 #> 8880 2081 3F CC67 2018 2018-08-20 NO23 -3.4420193762 #> 8881 2081 3F CC67 2018 2018-08-20 SALIN -2.3025850930 #> 8882 2081 3F CC67 2018 2018-08-20 TKN -0.0618754037 #> 8883 2081 3F CC67 2018 2018-08-20 TN -0.0283994745 + #> 8884 2081 3F CC67 2018 2018-08-20 TP -2.4534079827 #> 8885 2081 3F CC67 2018 2018-08-20 TSS 2.1972245773 I #> 8886 2081 3F CC67 2018 2018-08-20 TURB 1.9315214116 #> 8887 2081 3F CC67 2018 2018-09-10 CHLAC 1.5260563035 #> 8888 2081 3F CC67 2018 2018-09-10 COLOR 4.4998096703 A #> 8889 2081 3F CC67 2018 2018-09-10 COND 6.0520891689 #> 8890 2081 3F CC67 2018 2018-09-10 DO 1.9865035460 #> 8891 2081 3F CC67 2018 2018-09-10 DOSAT 4.5941092386 #> 8892 2081 3F CC67 2018 2018-09-10 SALIN -1.6094379124 #> 8893 2081 3F CC67 2018 2018-09-10 TN -0.2057949130 + #> 8894 2081 3F CC67 2018 2018-09-10 TSS 2.3025850930 A #> 8895 2081 3F CC67 2018 2018-09-10 TURB 2.0281482473 #> 8896 2081 3F CC67 2018 2018-11-12 CHLAC 2.2300144002 #> 8897 2081 3F CC67 2018 2018-11-12 COLOR 3.9120230054 #> 8898 2081 3F CC67 2018 2018-11-12 COND 6.2595814641 #> 8899 2081 3F CC67 2018 2018-11-12 DO 2.1174596089 #> 8900 2081 3F CC67 2018 2018-11-12 DOSAT 4.6180864113 #> 8901 2081 3F CC67 2018 2018-11-12 NO23 -2.3751557858 #> 8902 2081 3F CC67 2018 2018-11-12 SALIN -1.3862943611 #> 8903 2081 3F CC67 2018 2018-11-12 TKN -0.2484613593 #> 8904 2081 3F CC67 2018 2018-11-12 TN -0.1358197231 + #> 8905 2081 3F CC67 2018 2018-11-12 TP -2.8473122684 #> 8906 2081 3F CC67 2018 2018-11-12 TSS 2.1972245773 I #> 8907 2081 3F CC67 2018 2018-11-12 TURB 2.0014800002 A #> 8908 2065B 2 CC67 2013 2013-01-08 CHLAC 1.2809338455 #> 8909 2065B 2 CC67 2013 2013-01-08 COLOR 2.9957322736 #> 8910 2065B 2 CC67 2013 2013-01-08 COND 10.7359617983 #> 8911 2065B 2 CC67 2013 2013-01-08 DO 1.8870696490 #> 8912 2065B 2 CC67 2013 2013-01-08 DOSAT 4.4773368145 + #> 8913 2065B 2 CC67 2013 2013-01-08 NO23 -4.9618451299 I #> 8914 2065B 2 CC67 2013 2013-01-08 SALIN 3.3968546322 #> 8915 2065B 2 CC67 2013 2013-01-08 TKN -1.3093333200 #> 8916 2065B 2 CC67 2013 2013-01-08 TN -1.2837377728 #> 8917 2065B 2 CC67 2013 2013-01-08 TP -2.6172958378 #> 8918 2065B 2 CC67 2013 2013-01-08 TSS 0.9001613499 #> 8919 2065B 2 CC67 2013 2013-01-08 TURB -0.1053605157 #> 8920 2065B 2 CC67 2013 2013-01-08 COND 10.7368313636 #> 8921 2065B 2 CC67 2013 2013-01-08 DO 1.8946168547 #> 8922 2065B 2 CC67 2013 2013-01-08 DOSAT 4.4796069630 + #> 8923 2065B 2 CC67 2013 2013-01-08 SALIN 3.3981928726 #> 8924 2065B 2 CC67 2013 2013-01-08 COND 10.7435449784 #> 8925 2065B 2 CC67 2013 2013-01-08 DO 1.9021075264 #> 8926 2065B 2 CC67 2013 2013-01-08 DOSAT 4.4830025520 + #> 8927 2065B 2 CC67 2013 2013-01-08 SALIN 3.4055213531 #> 8928 2065B 2 CC67 2015 2015-04-07 CHLAC 0.6931471806 #> 8929 2065B 2 CC67 2015 2015-04-07 COLOR 3.4011973817 #> 8930 2065B 2 CC67 2015 2015-04-07 COND 10.6960274770 #> 8931 2065B 2 CC67 2015 2015-04-07 DO 1.8164520818 #> 8932 2065B 2 CC67 2015 2015-04-07 DOSAT 4.4931206822 + #> 8933 2065B 2 CC67 2015 2015-04-07 NO23 -5.1159958098 I #> 8934 2065B 2 CC67 2015 2015-04-07 SALIN 3.3492020865 #> 8935 2065B 2 CC67 2015 2015-04-07 TKN -0.2587707290 #> 8936 2065B 2 CC67 2015 2015-04-07 TN -0.2510287548 #> 8937 2065B 2 CC67 2015 2015-04-07 TP -2.4079456087 #> 8938 2065B 2 CC67 2015 2015-04-07 TSS 2.2257040487 #> 8939 2065B 2 CC67 2015 2015-04-07 TURB 0.2623642645 #> 8940 2065B 2 CC67 2015 2015-04-07 COND 10.6958011046 #> 8941 2065B 2 CC67 2015 2015-04-07 DO 1.8033586051 #> 8942 2065B 2 CC67 2015 2015-04-07 DOSAT 4.4796069630 + #> 8943 2065B 2 CC67 2015 2015-04-07 SALIN 3.3488509013 #> 8944 2065B 2 CC67 2015 2015-11-03 CHLAC 2.0476928434 #> 8945 2065B 2 CC67 2015 2015-11-03 COLOR 4.0073331852 #> 8946 2065B 2 CC67 2015 2015-11-03 COND 10.5339611386 #> 8947 2065B 2 CC67 2015 2015-11-03 DO 2.0731719287 #> 8948 2065B 2 CC67 2015 2015-11-03 DOSAT 4.7723781050 + #> 8949 2065B 2 CC67 2015 2015-11-03 NO23 -5.5214609179 U #> 8950 2065B 2 CC67 2015 2015-11-03 SALIN 3.1658969001 #> 8951 2065B 2 CC67 2015 2015-11-03 TKN -0.4557063245 #> 8952 2065B 2 CC67 2015 2015-11-03 TN -0.4557063245 #> 8953 2065B 2 CC67 2015 2015-11-03 TP -2.0557250151 #> 8954 2065B 2 CC67 2015 2015-11-03 TSS 1.7369512327 #> 8955 2065B 2 CC67 2015 2015-11-03 TURB -0.3566749439 #> 8956 2065B 2 CC67 2015 2015-11-03 COND 10.5312958918 #> 8957 2065B 2 CC67 2015 2015-11-03 DO 2.0955609236 #> 8958 2065B 2 CC67 2015 2015-11-03 DOSAT 4.7966166506 + #> 8959 2065B 2 CC67 2015 2015-11-03 SALIN 3.1629401925 #> 8960 2065B 2 CC67 2017 2017-04-05 CHLAC -0.0502412164 I #> 8961 2065B 2 CC67 2017 2017-04-05 COND 10.7904503955 #> 8962 2065B 2 CC67 2017 2017-04-05 DO 1.9586853405 #> 8963 2065B 2 CC67 2017 2017-04-05 DOSAT 4.6653241088 + #> 8964 2065B 2 CC67 2017 2017-04-05 NO23 -4.8283137373 I #> 8965 2065B 2 CC67 2017 2017-04-05 SALIN 3.4541060373 #> 8966 2065B 2 CC67 2017 2017-04-05 TKN -0.4261781497 #> 8967 2065B 2 CC67 2017 2017-04-05 TN -0.4140014391 #> 8968 2065B 2 CC67 2017 2017-04-05 TP -2.7030626596 #> 8969 2065B 2 CC67 2017 2017-04-05 TSS 2.1972245773 #> 8970 2065B 2 CC67 2017 2017-04-05 TURB 0.0000000000 #> 8971 2065B 2 CC67 2017 2017-04-05 COND 10.7904771690 #> 8972 2065B 2 CC67 2017 2017-04-05 DO 1.9699056546 #> 8973 2065B 2 CC67 2017 2017-04-05 DOSAT 4.6784206477 + #> 8974 2065B 2 CC67 2017 2017-04-05 SALIN 3.4541060373 #> 8975 2065B 2 CC67 2017 2017-04-05 COND 10.7905760186 #> 8976 2065B 2 CC67 2017 2017-04-05 DO 1.9712993831 #> 8977 2065B 2 CC67 2017 2017-04-05 DOSAT 4.6802776585 + #> 8978 2065B 2 CC67 2017 2017-04-05 SALIN 3.4541060373 #> 8979 2065B 2 CC67 2017 2017-04-05 COND 10.7905821964 #> 8980 2065B 2 CC67 2017 2017-04-05 DO 1.9726911717 #> 8981 2065B 2 CC67 2017 2017-04-05 DOSAT 4.6812048723 + #> 8982 2065B 2 CC67 2017 2017-04-05 SALIN 3.4541060373 #> 8983 2065B 2 CC67 2017 2017-06-05 CHLAC 1.3686394259 #> 8984 2065B 2 CC67 2017 2017-06-05 NO23 -4.1351665567 #> 8985 2065B 2 CC67 2017 2017-06-05 TKN -0.2600669054 #> 8986 2065B 2 CC67 2017 2017-06-05 TN -0.2395270306 #> 8987 2065B 2 CC67 2017 2017-06-05 TP -2.5770219387 #> 8988 2065B 2 CC67 2017 2017-06-05 TSS 2.4595888418 #> 8989 2065B 2 CC67 2017 2017-06-05 TURB 0.0000000000 #> 8990 2065B 2 CC67 2017 2017-06-05 COND 10.8045448425 #> 8991 2065B 2 CC67 2017 2017-06-05 DO 1.6134299337 #> 8992 2065B 2 CC67 2017 2017-06-05 DOSAT 4.3592696476 + #> 8993 2065B 2 CC67 2017 2017-06-05 SALIN 3.4679210137 #> 8994 2065B 2 CC67 2017 2017-06-05 COND 10.8049143616 #> 8995 2065B 2 CC67 2017 2017-06-05 DO 1.6524974019 #> 8996 2065B 2 CC67 2017 2017-06-05 DOSAT 4.3981460166 + #> 8997 2065B 2 CC67 2017 2017-06-05 SALIN 3.4682327830 #> 8998 2065B 2 CC67 2017 2017-06-05 COND 10.8052533058 #> 8999 2065B 2 CC67 2017 2017-06-05 DO 1.6677068206 #> 9000 2065B 2 CC67 2017 2017-06-05 DOSAT 4.4140096805 + #> 9001 2065B 2 CC67 2017 2017-06-05 SALIN 3.4685444551 #> 9002 2065B 2 CC67 2017 2017-08-15 CHLAC 2.7850112422 #> 9003 2065B 2 CC67 2017 2017-08-15 COND 10.0070409363 #> 9004 2065B 2 CC67 2017 2017-08-15 DO 1.7474592103 #> 9005 2065B 2 CC67 2017 2017-08-15 DOSAT 4.4693504628 + #> 9006 2065B 2 CC67 2017 2017-08-15 NO23 -3.2968373663 #> 9007 2065B 2 CC67 2017 2017-08-15 SALIN 2.5794589667 #> 9008 2065B 2 CC67 2017 2017-08-15 TKN 0.0953101798 #> 9009 2065B 2 CC67 2017 2017-08-15 TN 0.1310282624 #> 9010 2065B 2 CC67 2017 2017-08-15 TP -1.0555527992 #> 9011 2065B 2 CC67 2017 2017-08-15 TSS 0.8458682676 #> 9012 2065B 2 CC67 2017 2017-08-15 TURB 0.6931471806 #> 9013 2065B 2 CC67 2017 2017-08-15 COND 10.1682757999 #> 9014 2065B 2 CC67 2017 2017-08-15 DO 0.5822156199 #> 9015 2065B 2 CC67 2017 2017-08-15 DOSAT 3.2771447330 + #> 9016 2065B 2 CC67 2017 2017-08-15 SALIN 2.7593768283 #> 9017 2065B 2 CC67 2017 2017-08-15 COND 10.1784604545 #> 9018 2065B 2 CC67 2017 2017-08-15 DO 0.5306282511 #> 9019 2065B 2 CC67 2017 2017-08-15 DOSAT 3.2268439945 + #> 9020 2065B 2 CC67 2017 2017-08-15 SALIN 2.7707119622 #> 9021 2065B 2 CC67 2018 2018-04-09 CHLAC 0.8109302162 #> 9022 2065B 2 CC67 2018 2018-04-09 COND 10.7756173069 #> 9023 2065B 2 CC67 2018 2018-04-09 DO 1.9387416596 #> 9024 2065B 2 CC67 2018 2018-04-09 DOSAT 4.6395716127 + #> 9025 2065B 2 CC67 2018 2018-04-09 NO23 -4.8283137373 I #> 9026 2065B 2 CC67 2018 2018-04-09 SALIN 3.4375293109 #> 9027 2065B 2 CC67 2018 2018-04-09 TKN -0.3945251681 #> 9028 2065B 2 CC67 2018 2018-04-09 TN -0.3827256211 #> 9029 2065B 2 CC67 2018 2018-04-09 TP -2.5902671654 #> 9030 2065B 2 CC67 2018 2018-04-09 TSS 1.4816045409 #> 9031 2065B 2 CC67 2018 2018-04-09 TURB 0.0953101798 #> 9032 2065B 2 CC67 2018 2018-04-09 COND 10.7754082549 #> 9033 2065B 2 CC67 2018 2018-04-09 DO 1.9473377010 #> 9034 2065B 2 CC67 2018 2018-04-09 DOSAT 4.6482296754 + #> 9035 2065B 2 CC67 2018 2018-04-09 SALIN 3.4375293109 #> 9036 2065B 2 CC67 2018 2018-04-09 COND 10.7754082549 #> 9037 2065B 2 CC67 2018 2018-04-09 DO 1.9487632180 #> 9038 2065B 2 CC67 2018 2018-04-09 DOSAT 4.6501435516 + #> 9039 2065B 2 CC67 2018 2018-04-09 SALIN 3.4375293109 #> 9040 2065B 2 CC67 2018 2018-05-23 CHLAC 1.1216775616 #> 9041 2065B 2 CC67 2018 2018-05-23 COND 10.7435212354 #> 9042 2065B 2 CC67 2018 2018-05-23 DO 1.8885836539 #> 9043 2065B 2 CC67 2018 2018-05-23 DOSAT 4.5910712616 + #> 9044 2065B 2 CC67 2018 2018-05-23 NO23 -4.6051701860 I #> 9045 2065B 2 CC67 2018 2018-05-23 SALIN 3.4011973817 #> 9046 2065B 2 CC67 2018 2018-05-23 TKN -0.1696027844 #> 9047 2065B 2 CC67 2018 2018-05-23 TN -0.1578240852 #> 9048 2065B 2 CC67 2018 2018-05-23 TP -2.0794415417 #> 9049 2065B 2 CC67 2018 2018-05-23 TSS 1.5686159179 #> 9050 2065B 2 CC67 2018 2018-05-23 TURB 1.0647107370 #> 9051 2065B 2 CC67 2018 2018-05-23 DOSAT 4.6793495842 + #> 9052 2065B 2 CC67 2018 2018-05-23 COND 10.7527727226 #> 9053 2065B 2 CC67 2018 2018-05-23 DO 1.9782390362 #> 9054 2065B 2 CC67 2018 2018-05-23 SALIN 3.4118075608 #> 9055 2065B 2 CC67 2018 2018-10-11 CHLAC 1.4109869737 #> 9056 2065B 2 CC67 2018 2018-10-11 COND 10.5316641186 #> 9057 2065B 2 CC67 2018 2018-10-11 DO 1.6467336972 #> 9058 2065B 2 CC67 2018 2018-10-11 DOSAT 4.3148178850 + #> 9059 2065B 2 CC67 2018 2018-10-11 NO23 -4.9618451299 I #> 9060 2065B 2 CC67 2018 2018-10-11 SALIN 3.1654750481 #> 9061 2065B 2 CC67 2018 2018-10-11 TKN -0.1960148839 #> 9062 2065B 2 CC67 2018 2018-10-11 TN -0.1875351238 #> 9063 2065B 2 CC67 2018 2018-10-11 TP -2.1202635362 #> 9064 2065B 2 CC67 2018 2018-10-11 TSS 1.8453002362 #> 9065 2065B 2 CC67 2018 2018-10-11 TURB 0.6931471806 #> 9066 2065B 2 CC67 2018 2018-10-11 COND 10.5317548204 #> 9067 2065B 2 CC67 2018 2018-10-11 DO 1.6448050563 #> 9068 2065B 2 CC67 2018 2018-10-11 DOSAT 4.3121405072 + #> 9069 2065B 2 CC67 2018 2018-10-11 SALIN 3.1654750481 #> 9070 2065B 2 CC67 2018 2018-10-11 COND 10.5326214074 #> 9071 2065B 2 CC67 2018 2018-10-11 DO 1.6370530795 #> 9072 2065B 2 CC67 2018 2018-10-11 DOSAT 4.3054155323 + #> 9073 2065B 2 CC67 2018 2018-10-11 SALIN 3.1663185741 #> 9074 2065B 2 CC67 2019 2019-03-05 CHLAC 1.6094379124 #> 9075 2065B 2 CC67 2019 2019-03-05 COND 10.4627604245 #> 9076 2065B 2 CC67 2019 2019-03-05 DO 1.8325814637 #> 9077 2065B 2 CC67 2019 2019-03-05 DOSAT 4.5163389723 + #> 9078 2065B 2 CC67 2019 2019-03-05 NO23 -5.1159958098 U #> 9079 2065B 2 CC67 2019 2019-03-05 SALIN 3.5550051456 #> 9080 2065B 2 CC67 2019 2019-03-05 TKN -0.2691874898 #> 9081 2065B 2 CC67 2019 2019-03-05 TN -0.2691874898 #> 9082 2065B 2 CC67 2019 2019-03-05 TP -2.3644604967 #> 9083 2065B 2 CC67 2019 2019-03-05 TSS 1.9919755159 #> 9084 2065B 2 CC67 2019 2019-03-05 TURB 0.8754687374 #> 9085 2065B 2 CC67 2019 2019-03-05 COND 10.4628461645 #> 9086 2065B 2 CC67 2019 2019-03-05 DO 1.8309801824 #> 9087 2065B 2 CC67 2019 2019-03-05 DOSAT 4.5152454785 + #> 9088 2065B 2 CC67 2019 2019-03-05 SALIN 3.5550908856 #> 9089 2065B 2 CC67 2019 2019-03-05 COND 10.4631604817 #> 9090 2065B 2 CC67 2019 2019-03-05 DO 1.8277699068 #> newComment disqual disqual2 #> 1 I NA NA #> 2 U NA NA #> 3 + NA NA #> 4 NA NA #> 5 NA NA #> 6 NA NA #> 7 + NA NA #> 8 NA NA #> 9 NA NA #> 10 I NA NA #> 11 I NA NA #> 12 NA NA #> 13 NA NA #> 14 NA NA #> 15 + NA NA #> 16 NA NA #> 17 NA NA #> 18 I NA NA #> 19 I NA NA #> 20 I NA NA #> 21 NA NA #> 22 NA NA #> 23 + NA NA #> 24 NA NA #> 25 NA NA #> 26 NA NA #> 27 NA NA #> 28 I NA NA #> 29 + NA NA #> 30 A NA NA #> 31 NA NA #> 32 NA NA #> 33 NA NA #> 34 + 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 NA NA #> 44 NA NA #> 45 + NA NA #> 46 NA NA #> 47 NA NA #> 48 NA NA #> 49 U NA NA #> 50 NA NA #> 51 + NA NA #> 52 I NA NA #> 53 NA NA #> 54 NA NA #> 55 + NA NA #> 56 NA NA #> 57 NA NA #> 58 NA NA #> 59 U NA NA #> 60 + NA NA #> 61 U NA NA #> 62 NA NA #> 63 NA NA #> 64 + NA NA #> 65 NA NA #> 66 NA NA #> 67 I NA NA #> 68 U NA NA #> 69 NA NA #> 70 + NA NA #> 71 I NA NA #> 72 NA NA #> 73 NA NA #> 74 + NA NA #> 75 NA NA #> 76 NA NA #> 77 NA NA #> 78 NA NA #> 79 NA NA #> 80 + NA NA #> 81 I NA NA #> 82 NA NA #> 83 NA NA #> 84 + NA NA #> 85 NA NA #> 86 A NA NA #> 87 NA NA #> 88 NA NA #> 89 NA NA #> 90 + NA NA #> 91 I NA NA #> 92 NA NA #> 93 NA NA #> 94 + NA NA #> 95 NA NA #> 96 NA NA #> 97 NA NA #> 98 NA NA #> 99 NA NA #> 100 U NA NA #> 101 NA NA #> 102 + NA NA #> 103 NA NA #> 104 NA NA #> 105 NA NA #> 106 NA NA #> 107 NA NA #> 108 + NA NA #> 109 U NA NA #> 110 NA NA #> 111 + NA NA #> 112 NA NA #> 113 NA NA #> 114 NA NA #> 115 NA NA #> 116 + NA NA #> 117 I 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 NA NA #> 128 NA NA #> 129 + NA NA #> 130 NA NA #> 131 NA NA #> 132 A NA NA #> 133 A 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 A 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 I NA NA #> 155 NA NA #> 156 NA NA #> 157 + NA NA #> 158 NA NA #> 159 NA NA #> 160 I NA NA #> 161 U NA NA #> 162 NA NA #> 163 + NA NA #> 164 I NA NA #> 165 NA NA #> 166 I NA NA #> 167 + NA NA #> 168 NA NA #> 169 NA NA #> 170 NA NA #> 171 NA NA #> 172 NA NA #> 173 + NA NA #> 174 U 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 U NA NA #> 185 NA NA #> 186 I NA NA #> 187 + 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 + NA NA #> 204 NA NA #> 205 NA NA #> 206 NA NA #> 207 + NA NA #> 208 NA NA #> 209 NA NA #> 210 NA NA #> 211 NA NA #> 212 NA NA #> 213 + NA NA #> 214 NA NA #> 215 NA NA #> 216 NA NA #> 217 + 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 + NA NA #> 238 NA NA #> 239 NA NA #> 240 NA NA #> 241 NA NA #> 242 NA NA #> 243 + NA NA #> 244 I 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 + NA NA #> 254 NA NA #> 255 NA NA #> 256 NA NA #> 257 + NA NA #> 258 NA NA #> 259 NA NA #> 260 I NA NA #> 261 NA NA #> 262 NA NA #> 263 + NA NA #> 264 U NA NA #> 265 NA NA #> 266 I NA NA #> 267 + NA NA #> 268 NA NA #> 269 NA NA #> 270 NA NA #> 271 NA NA #> 272 NA NA #> 273 + NA NA #> 274 I NA NA #> 275 NA NA #> 276 NA NA #> 277 + 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 + NA NA #> 288 NA NA #> 289 NA NA #> 290 NA NA #> 291 NA NA #> 292 NA NA #> 293 + NA NA #> 294 I NA NA #> 295 NA NA #> 296 NA NA #> 297 + NA NA #> 298 NA NA #> 299 NA NA #> 300 NA NA #> 301 NA NA #> 302 NA NA #> 303 + NA NA #> 304 NA NA #> 305 NA NA #> 306 NA NA #> 307 + NA NA #> 308 NA NA #> 309 NA NA #> 310 I NA NA #> 311 U NA NA #> 312 NA NA #> 313 + NA NA #> 314 I NA NA #> 315 NA NA #> 316 NA NA #> 317 + NA NA #> 318 NA NA #> 319 NA NA #> 320 NA NA #> 321 I NA NA #> 322 NA NA #> 323 + NA NA #> 324 NA NA #> 325 NA NA #> 326 NA NA #> 327 + NA NA #> 328 NA NA #> 329 NA NA #> 330 I NA NA #> 331 U NA NA #> 332 NA NA #> 333 + NA NA #> 334 U NA NA #> 335 NA NA #> 336 NA NA #> 337 + NA NA #> 338 NA NA #> 339 NA NA #> 340 NA NA #> 341 NA NA #> 342 + NA NA #> 343 NA NA #> 344 I NA NA #> 345 NA NA #> 346 NA NA #> 347 + NA NA #> 348 I 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 A NA NA #> 359 NA NA #> 360 + NA NA #> 361 I NA NA #> 362 NA NA #> 363 NA NA #> 364 + NA NA #> 365 NA NA #> 366 NA NA #> 367 NA NA #> 368 NA NA #> 369 NA NA #> 370 + NA NA #> 371 NA NA #> 372 NA NA #> 373 NA NA #> 374 + NA NA #> 375 NA NA #> 376 A NA NA #> 377 NA NA #> 378 NA NA #> 379 I NA NA #> 380 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 NA NA #> 391 + NA NA #> 392 NA NA #> 393 NA NA #> 394 I NA NA #> 395 NA NA #> 396 NA NA #> 397 + NA NA #> 398 I NA NA #> 399 NA NA #> 400 NA NA #> 401 + NA NA #> 402 NA NA #> 403 NA NA #> 404 I NA NA #> 405 NA NA #> 406 NA NA #> 407 + NA NA #> 408 NA NA #> 409 NA NA #> 410 NA NA #> 411 + NA NA #> 412 NA NA #> 413 NA NA #> 414 NA NA #> 415 NA NA #> 416 NA NA #> 417 + NA NA #> 418 NA NA #> 419 NA NA #> 420 NA NA #> 421 + NA NA #> 422 NA NA #> 423 A NA NA #> 424 I NA NA #> 425 NA NA #> 426 NA NA #> 427 + NA NA #> 428 U NA NA #> 429 NA NA #> 430 NA NA #> 431 + NA NA #> 432 NA NA #> 433 NA NA #> 434 I NA NA #> 435 I NA NA #> 436 + NA NA #> 437 U NA NA #> 438 NA NA #> 439 NA NA #> 440 + NA NA #> 441 NA NA #> 442 NA NA #> 443 NA NA #> 444 NA NA #> 445 NA NA #> 446 NA NA #> 447 U NA NA #> 448 NA NA #> 449 NA NA #> 450 + NA NA #> 451 NA NA #> 452 NA NA #> 453 NA NA #> 454 NA NA #> 455 NA NA #> 456 NA NA #> 457 NA NA #> 458 NA NA #> 459 NA NA #> 460 + NA NA #> 461 NA NA #> 462 NA NA #> 463 NA NA #> 464 NA NA #> 465 NA NA #> 466 NA NA #> 467 I NA NA #> 468 NA NA #> 469 NA NA #> 470 + NA NA #> 471 NA NA #> 472 NA NA #> 473 I NA NA #> 474 NA NA #> 475 NA NA #> 476 NA NA #> 477 NA NA #> 478 NA NA #> 479 NA NA #> 480 + NA NA #> 481 NA NA #> 482 NA NA #> 483 I NA NA #> 484 NA NA #> 485 NA NA #> 486 NA NA #> 487 I NA NA #> 488 NA NA #> 489 + NA NA #> 490 NA NA #> 491 NA NA #> 492 NA NA #> 493 NA NA #> 494 NA NA #> 495 NA NA #> 496 I NA NA #> 497 NA NA #> 498 I NA NA #> 499 + NA NA #> 500 NA NA #> 501 NA NA #> 502 I NA NA #> 503 I NA NA #> 504 NA NA #> 505 NA NA #> 506 I NA NA #> 507 NA NA #> 508 NA NA #> 509 + NA NA #> 510 NA NA #> 511 NA NA #> 512 I NA NA #> 513 NA NA #> 514 NA NA #> 515 NA NA #> 516 I NA NA #> 517 NA NA #> 518 NA NA #> 519 + NA NA #> 520 NA NA #> 521 NA NA #> 522 NA NA #> 523 I NA NA #> 524 NA NA #> 525 NA NA #> 526 I NA NA #> 527 NA NA #> 528 NA NA #> 529 + NA NA #> 530 NA NA #> 531 NA NA #> 532 NA NA #> 533 I NA NA #> 534 NA NA #> 535 NA NA #> 536 NA NA #> 537 NA NA #> 538 NA NA #> 539 + NA NA #> 540 NA NA #> 541 NA NA #> 542 NA NA #> 543 I NA NA #> 544 NA NA #> 545 NA NA #> 546 + NA NA #> 547 NA NA #> 548 NA NA #> 549 I NA NA #> 550 U NA NA #> 551 I NA NA #> 552 NA NA #> 553 + NA NA #> 554 NA NA #> 555 NA NA #> 556 I 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 U NA NA #> 567 I NA NA #> 568 NA NA #> 569 NA NA #> 570 NA NA #> 571 NA NA #> 572 NA NA #> 573 + NA NA #> 574 NA NA #> 575 NA NA #> 576 I NA NA #> 577 I NA NA #> 578 NA NA #> 579 NA NA #> 580 U NA NA #> 581 NA NA #> 582 I NA NA #> 583 + NA NA #> 584 NA NA #> 585 NA NA #> 586 I NA NA #> 587 I NA NA #> 588 NA NA #> 589 NA NA #> 590 NA NA #> 591 + NA NA #> 592 NA NA #> 593 A NA NA #> 594 I NA NA #> 595 I NA NA #> 596 NA NA #> 597 NA NA #> 598 U NA NA #> 599 NA NA #> 600 I NA NA #> 601 + NA NA #> 602 NA NA #> 603 NA NA #> 604 NA NA #> 605 I NA NA #> 606 NA NA #> 607 NA NA #> 608 U NA NA #> 609 NA NA #> 610 NA NA #> 611 + NA NA #> 612 NA NA #> 613 NA NA #> 614 NA NA #> 615 NA NA #> 616 NA NA #> 617 NA NA #> 618 I NA NA #> 619 NA NA #> 620 NA NA #> 621 + NA NA #> 622 NA NA #> 623 NA NA #> 624 NA NA #> 625 NA NA #> 626 NA NA #> 627 NA NA #> 628 NA NA #> 629 NA NA #> 630 NA NA #> 631 + NA NA #> 632 NA NA #> 633 NA NA #> 634 NA NA #> 635 NA NA #> 636 NA NA #> 637 NA NA #> 638 U NA NA #> 639 NA NA #> 640 NA NA #> 641 + NA NA #> 642 NA NA #> 643 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 NA NA #> 654 I NA NA #> 655 U NA NA #> 656 NA NA #> 657 NA NA #> 658 I NA NA #> 659 NA NA #> 660 NA NA #> 661 + NA NA #> 662 NA NA #> 663 NA NA #> 664 I NA NA #> 665 U NA NA #> 666 NA NA #> 667 NA NA #> 668 I NA NA #> 669 NA NA #> 670 I NA NA #> 671 + NA NA #> 672 NA NA #> 673 A NA NA #> 674 I NA NA #> 675 U NA NA #> 676 NA NA #> 677 NA NA #> 678 I NA NA #> 679 NA NA #> 680 NA NA #> 681 + NA NA #> 682 NA NA #> 683 NA NA #> 684 I NA NA #> 685 U NA NA #> 686 NA NA #> 687 NA NA #> 688 U NA NA #> 689 NA NA #> 690 + NA NA #> 691 NA NA #> 692 NA NA #> 693 I NA NA #> 694 U NA NA #> 695 NA NA #> 696 NA NA #> 697 U NA NA #> 698 NA NA #> 699 NA NA #> 700 + NA NA #> 701 NA NA #> 702 NA NA #> 703 I NA NA #> 704 U NA NA #> 705 NA NA #> 706 NA NA #> 707 U NA NA #> 708 NA NA #> 709 NA NA #> 710 + NA NA #> 711 NA NA #> 712 NA NA #> 713 I NA NA #> 714 I NA NA #> 715 NA NA #> 716 NA NA #> 717 NA NA #> 718 + NA NA #> 719 NA NA #> 720 NA NA #> 721 I NA NA #> 722 U NA NA #> 723 + NA NA #> 724 NA NA #> 725 NA NA #> 726 NA NA #> 727 + NA NA #> 728 NA NA #> 729 NA NA #> 730 I NA NA #> 731 I NA NA #> 732 I NA NA #> 733 NA NA #> 734 NA NA #> 735 + NA NA #> 736 NA NA #> 737 NA NA #> 738 I NA NA #> 739 U NA NA #> 740 NA NA #> 741 + NA NA #> 742 I NA NA #> 743 NA NA #> 744 NA NA #> 745 + NA NA #> 746 NA NA #> 747 NA NA #> 748 NA NA #> 749 NA NA #> 750 + NA NA #> 751 NA NA #> 752 NA NA #> 753 NA NA #> 754 + NA NA #> 755 NA NA #> 756 A NA NA #> 757 NA NA #> 758 NA NA #> 759 + NA NA #> 760 I 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 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 NA NA #> 794 NA NA #> 795 NA NA #> 796 NA NA #> 797 NA NA #> 798 I NA NA #> 799 NA NA #> 800 NA NA #> 801 + NA NA #> 802 NA NA #> 803 A NA NA #> 804 NA NA #> 805 A 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 I NA NA #> 816 NA NA #> 817 I NA NA #> 818 NA NA #> 819 NA NA #> 820 + NA NA #> 821 NA NA #> 822 NA NA #> 823 NA NA #> 824 I NA NA #> 825 NA NA #> 826 + NA NA #> 827 I NA NA #> 828 NA NA #> 829 NA NA #> 830 + NA NA #> 831 NA NA #> 832 NA NA #> 833 NA NA #> 834 NA NA #> 835 + NA NA #> 836 I NA NA #> 837 NA NA #> 838 NA NA #> 839 + NA NA #> 840 NA NA #> 841 NA NA #> 842 NA NA #> 843 NA NA #> 844 NA NA #> 845 + NA NA #> 846 I NA NA #> 847 NA NA #> 848 NA NA #> 849 + NA NA #> 850 NA NA #> 851 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 I 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 I NA NA #> 871 I NA NA #> 872 NA NA #> 873 I 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 NA NA #> 885 NA NA #> 886 + NA NA #> 887 NA NA #> 888 NA NA #> 889 NA NA #> 890 NA NA #> 891 NA NA #> 892 NA NA #> 893 NA NA #> 894 NA NA #> 895 + NA NA #> 896 NA NA #> 897 NA NA #> 898 NA NA #> 899 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 A NA NA #> 915 I 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 A NA NA #> 926 NA NA #> 927 + NA NA #> 928 I NA NA #> 929 NA NA #> 930 NA NA #> 931 + NA NA #> 932 NA NA #> 933 NA NA #> 934 NA NA #> 935 NA NA #> 936 NA NA #> 937 + NA NA #> 938 NA NA #> 939 NA NA #> 940 NA NA #> 941 + NA NA #> 942 NA NA #> 943 NA NA #> 944 NA NA #> 945 NA NA #> 946 NA NA #> 947 NA NA #> 948 NA NA #> 949 + NA NA #> 950 NA NA #> 951 NA NA #> 952 I NA NA #> 953 NA NA #> 954 NA NA #> 955 + NA NA #> 956 NA NA #> 957 NA NA #> 958 NA NA #> 959 + NA NA #> 960 NA NA #> 961 A NA NA #> 962 I NA NA #> 963 NA NA #> 964 NA NA #> 965 + NA NA #> 966 I NA NA #> 967 NA NA #> 968 NA NA #> 969 + NA NA #> 970 NA NA #> 971 NA NA #> 972 I NA NA #> 973 NA NA #> 974 NA NA #> 975 + NA NA #> 976 I NA NA #> 977 NA NA #> 978 NA NA #> 979 + 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 + 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 I NA NA #> 1013 U NA NA #> 1014 NA NA #> 1015 + NA NA #> 1016 NA NA #> 1017 NA NA #> 1018 NA NA #> 1019 + NA NA #> 1020 NA NA #> 1021 A NA NA #> 1022 NA NA #> 1023 I NA NA #> 1024 NA NA #> 1025 + NA NA #> 1026 NA NA #> 1027 NA NA #> 1028 NA NA #> 1029 + NA NA #> 1030 NA NA #> 1031 NA NA #> 1032 NA NA #> 1033 A NA NA #> 1034 NA NA #> 1035 + NA NA #> 1036 NA NA #> 1037 NA NA #> 1038 NA NA #> 1039 + NA NA #> 1040 NA NA #> 1041 NA NA #> 1042 I NA NA #> 1043 NA NA #> 1044 NA NA #> 1045 + NA NA #> 1046 I NA NA #> 1047 NA NA #> 1048 NA NA #> 1049 + NA NA #> 1050 NA NA #> 1051 NA NA #> 1052 NA NA #> 1053 NA NA #> 1054 NA NA #> 1055 + NA NA #> 1056 I NA NA #> 1057 NA NA #> 1058 NA NA #> 1059 + NA NA #> 1060 NA NA #> 1061 NA NA #> 1062 NA NA #> 1063 I NA NA #> 1064 NA NA #> 1065 + NA NA #> 1066 U NA NA #> 1067 NA NA #> 1068 NA NA #> 1069 + NA NA #> 1070 NA NA #> 1071 NA NA #> 1072 NA NA #> 1073 NA NA #> 1074 NA NA #> 1075 + NA NA #> 1076 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 NA NA #> 1087 NA NA #> 1088 NA NA #> 1089 + NA NA #> 1090 NA NA #> 1091 NA NA #> 1092 NA NA #> 1093 NA NA #> 1094 I NA NA #> 1095 NA NA #> 1096 + NA NA #> 1097 NA NA #> 1098 NA NA #> 1099 NA NA #> 1100 NA NA #> 1101 NA NA #> 1102 + NA NA #> 1103 NA NA #> 1104 NA NA #> 1105 NA NA #> 1106 + NA NA #> 1107 NA NA #> 1108 A NA NA #> 1109 NA NA #> 1110 NA NA #> 1111 NA NA #> 1112 + NA NA #> 1113 I NA NA #> 1114 NA NA #> 1115 NA NA #> 1116 + NA NA #> 1117 NA NA #> 1118 A NA NA #> 1119 NA NA #> 1120 NA NA #> 1121 NA NA #> 1122 + NA NA #> 1123 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 NA NA #> 1132 + NA NA #> 1133 NA NA #> 1134 NA NA #> 1135 NA NA #> 1136 + NA NA #> 1137 NA NA #> 1138 NA NA #> 1139 NA NA #> 1140 NA NA #> 1141 NA NA #> 1142 + NA NA #> 1143 I NA NA #> 1144 NA NA #> 1145 NA NA #> 1146 + NA NA #> 1147 NA NA #> 1148 A NA NA #> 1149 A NA NA #> 1150 I NA NA #> 1151 NA NA #> 1152 + NA NA #> 1153 NA NA #> 1154 NA NA #> 1155 NA NA #> 1156 + NA NA #> 1157 NA NA #> 1158 NA NA #> 1159 NA NA #> 1160 NA NA #> 1161 NA NA #> 1162 NA NA #> 1163 I NA NA #> 1164 NA NA #> 1165 NA NA #> 1166 + NA NA #> 1167 NA NA #> 1168 NA NA #> 1169 NA NA #> 1170 NA NA #> 1171 NA NA #> 1172 NA NA #> 1173 I NA NA #> 1174 NA NA #> 1175 NA NA #> 1176 + NA NA #> 1177 NA NA #> 1178 NA NA #> 1179 A NA NA #> 1180 NA NA #> 1181 NA NA #> 1182 I NA NA #> 1183 NA NA #> 1184 NA NA #> 1185 + NA NA #> 1186 NA NA #> 1187 A NA NA #> 1188 I NA NA #> 1189 NA NA #> 1190 NA NA #> 1191 NA NA #> 1192 NA NA #> 1193 NA NA #> 1194 NA NA #> 1195 + NA NA #> 1196 NA NA #> 1197 NA NA #> 1198 I NA NA #> 1199 NA NA #> 1200 I NA NA #> 1201 NA NA #> 1202 NA NA #> 1203 + NA NA #> 1204 NA NA #> 1205 NA NA #> 1206 I NA NA #> 1207 NA NA #> 1208 U NA NA #> 1209 NA NA #> 1210 + NA NA #> 1211 NA NA #> 1212 NA NA #> 1213 I NA NA #> 1214 NA NA #> 1215 NA NA #> 1216 NA NA #> 1217 I NA NA #> 1218 NA NA #> 1219 NA NA #> 1220 + NA NA #> 1221 NA NA #> 1222 NA NA #> 1223 I NA NA #> 1224 I NA NA #> 1225 NA NA #> 1226 NA NA #> 1227 NA NA #> 1228 NA NA #> 1229 NA NA #> 1230 + NA NA #> 1231 NA NA #> 1232 NA NA #> 1233 I NA NA #> 1234 NA NA #> 1235 I 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 I NA NA #> 1246 NA NA #> 1247 NA NA #> 1248 + NA NA #> 1249 NA NA #> 1250 NA NA #> 1251 NA NA #> 1252 I NA NA #> 1253 NA NA #> 1254 NA NA #> 1255 I NA NA #> 1256 NA NA #> 1257 NA NA #> 1258 + NA NA #> 1259 NA NA #> 1260 NA NA #> 1261 NA NA #> 1262 I NA NA #> 1263 NA NA #> 1264 NA NA #> 1265 NA NA #> 1266 NA NA #> 1267 NA NA #> 1268 + NA NA #> 1269 NA NA #> 1270 NA NA #> 1271 I NA NA #> 1272 U NA NA #> 1273 NA NA #> 1274 NA NA #> 1275 NA NA #> 1276 NA NA #> 1277 NA NA #> 1278 + NA NA #> 1279 NA NA #> 1280 NA NA #> 1281 I NA NA #> 1282 NA NA #> 1283 NA NA #> 1284 NA NA #> 1285 NA NA #> 1286 + NA NA #> 1287 NA NA #> 1288 NA NA #> 1289 I NA NA #> 1290 NA NA #> 1291 NA NA #> 1292 NA NA #> 1293 NA NA #> 1294 NA NA #> 1295 NA NA #> 1296 + NA NA #> 1297 NA NA #> 1298 NA NA #> 1299 I NA NA #> 1300 U NA NA #> 1301 NA NA #> 1302 NA NA #> 1303 I NA NA #> 1304 NA NA #> 1305 + NA NA #> 1306 NA NA #> 1307 A NA NA #> 1308 NA NA #> 1309 A NA NA #> 1310 NA NA #> 1311 NA NA #> 1312 NA NA #> 1313 NA NA #> 1314 NA NA #> 1315 + NA NA #> 1316 NA NA #> 1317 NA NA #> 1318 I NA NA #> 1319 A NA NA #> 1320 NA NA #> 1321 NA NA #> 1322 NA NA #> 1323 NA NA #> 1324 NA NA #> 1325 + NA NA #> 1326 NA NA #> 1327 A NA NA #> 1328 + NA NA #> 1329 NA NA #> 1330 NA NA #> 1331 NA NA #> 1332 NA NA #> 1333 NA NA #> 1334 NA NA #> 1335 NA NA #> 1336 NA NA #> 1337 NA NA #> 1338 U NA NA #> 1339 NA NA #> 1340 NA NA #> 1341 NA NA #> 1342 NA NA #> 1343 NA NA #> 1344 + NA NA #> 1345 NA NA #> 1346 NA NA #> 1347 I NA NA #> 1348 U NA NA #> 1349 NA NA #> 1350 NA NA #> 1351 I NA NA #> 1352 NA NA #> 1353 NA NA #> 1354 + NA NA #> 1355 NA NA #> 1356 NA NA #> 1357 I NA NA #> 1358 I NA NA #> 1359 NA NA #> 1360 NA NA #> 1361 I NA NA #> 1362 NA NA #> 1363 NA NA #> 1364 + NA NA #> 1365 NA NA #> 1366 NA NA #> 1367 I NA NA #> 1368 I NA NA #> 1369 I NA NA #> 1370 NA NA #> 1371 + NA NA #> 1372 NA NA #> 1373 NA NA #> 1374 + NA NA #> 1375 I NA NA #> 1376 NA NA #> 1377 NA NA #> 1378 NA NA #> 1379 I NA NA #> 1380 NA NA #> 1381 I NA NA #> 1382 NA NA #> 1383 NA NA #> 1384 I NA NA #> 1385 NA NA #> 1386 NA NA #> 1387 NA NA #> 1388 I NA NA #> 1389 NA NA #> 1390 NA NA #> 1391 + NA NA #> 1392 NA NA #> 1393 NA NA #> 1394 I NA NA #> 1395 I NA NA #> 1396 NA NA #> 1397 NA NA #> 1398 I NA NA #> 1399 NA NA #> 1400 NA NA #> 1401 + NA NA #> 1402 NA NA #> 1403 NA NA #> 1404 NA NA #> 1405 NA NA #> 1406 NA NA #> 1407 NA NA #> 1408 U NA NA #> 1409 NA NA #> 1410 NA NA #> 1411 + NA NA #> 1412 NA NA #> 1413 NA NA #> 1414 NA NA #> 1415 NA NA #> 1416 NA NA #> 1417 NA NA #> 1418 I NA NA #> 1419 NA NA #> 1420 NA NA #> 1421 + NA NA #> 1422 NA NA #> 1423 NA NA #> 1424 NA NA #> 1425 NA NA #> 1426 NA NA #> 1427 NA NA #> 1428 I NA NA #> 1429 NA NA #> 1430 NA NA #> 1431 + NA NA #> 1432 NA NA #> 1433 A NA NA #> 1434 NA NA #> 1435 NA NA #> 1436 NA NA #> 1437 NA NA #> 1438 NA NA #> 1439 NA NA #> 1440 NA NA #> 1441 + NA NA #> 1442 NA NA #> 1443 NA NA #> 1444 I NA NA #> 1445 U NA NA #> 1446 NA NA #> 1447 NA NA #> 1448 I NA NA #> 1449 NA NA #> 1450 NA NA #> 1451 + NA NA #> 1452 NA NA #> 1453 NA NA #> 1454 I NA NA #> 1455 I NA NA #> 1456 NA NA #> 1457 NA NA #> 1458 NA NA #> 1459 NA NA #> 1460 NA NA #> 1461 + NA NA #> 1462 NA NA #> 1463 NA NA #> 1464 I NA NA #> 1465 U NA NA #> 1466 NA NA #> 1467 NA NA #> 1468 NA NA #> 1469 NA NA #> 1470 NA NA #> 1471 + NA NA #> 1472 NA NA #> 1473 NA NA #> 1474 I NA NA #> 1475 U NA NA #> 1476 NA NA #> 1477 NA NA #> 1478 U NA NA #> 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#> 1547 NA NA #> 1548 NA NA #> 1549 NA NA #> 1550 NA NA #> 1551 NA NA #> 1552 NA NA #> 1553 + NA NA #> 1554 NA NA #> 1555 I NA NA #> 1556 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 A NA NA #> 1567 A NA NA #> 1568 NA NA #> 1569 I NA NA #> 1570 NA NA #> 1571 NA NA #> 1572 + NA NA #> 1573 NA NA #> 1574 NA NA #> 1575 NA NA #> 1576 A NA NA #> 1577 + NA NA #> 1578 I NA NA #> 1579 NA NA #> 1580 NA NA #> 1581 + NA NA #> 1582 NA NA #> 1583 NA NA #> 1584 I NA NA #> 1585 NA NA #> 1586 + NA NA #> 1587 I NA NA #> 1588 NA NA #> 1589 NA NA #> 1590 + NA NA #> 1591 NA NA #> 1592 NA NA #> 1593 NA NA #> 1594 NA NA #> 1595 NA NA #> 1596 + NA NA #> 1597 I NA NA #> 1598 NA NA #> 1599 NA NA #> 1600 + NA NA #> 1601 NA NA #> 1602 NA NA #> 1603 NA NA #> 1604 NA NA #> 1605 NA NA #> 1606 + NA NA #> 1607 I NA NA #> 1608 NA NA #> 1609 NA NA #> 1610 + NA NA #> 1611 NA NA #> 1612 NA NA #> 1613 NA NA #> 1614 NA NA #> 1615 NA NA #> 1616 + 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 + 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 + 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 + NA NA #> 1647 I NA NA #> 1648 NA NA #> 1649 NA NA #> 1650 + NA NA #> 1651 NA NA #> 1652 NA NA #> 1653 I NA NA #> 1654 NA NA #> 1655 NA NA #> 1656 + NA NA #> 1657 I 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 + NA NA #> 1677 I NA NA #> 1678 NA NA #> 1679 NA NA #> 1680 + NA NA #> 1681 NA NA #> 1682 NA NA #> 1683 NA NA #> 1684 A NA NA #> 1685 NA NA #> 1686 + NA NA #> 1687 NA NA #> 1688 NA NA #> 1689 NA NA #> 1690 + NA NA #> 1691 NA NA #> 1692 A NA NA #> 1693 NA NA #> 1694 NA NA #> 1695 NA NA #> 1696 + NA NA #> 1697 NA NA #> 1698 NA NA #> 1699 NA NA #> 1700 + NA NA #> 1701 NA NA #> 1702 NA NA #> 1703 NA NA #> 1704 A NA NA #> 1705 NA NA #> 1706 + NA NA #> 1707 I NA NA #> 1708 NA NA #> 1709 NA NA #> 1710 + NA NA #> 1711 NA NA #> 1712 NA NA #> 1713 NA NA #> 1714 A NA NA #> 1715 NA NA #> 1716 + NA NA #> 1717 I 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 + NA NA #> 1727 I 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 + NA NA #> 1737 U NA NA #> 1738 NA NA #> 1739 NA NA #> 1740 + NA NA #> 1741 NA NA #> 1742 NA NA #> 1743 NA NA #> 1744 NA NA #> 1745 NA NA #> 1746 + NA NA #> 1747 I 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 I NA NA #> 1778 NA NA #> 1779 NA NA #> 1780 + NA NA #> 1781 NA NA #> 1782 NA NA #> 1783 A NA NA #> 1784 NA NA #> 1785 NA NA #> 1786 + NA NA #> 1787 NA NA #> 1788 NA NA #> 1789 NA NA #> 1790 + NA NA #> 1791 NA NA #> 1792 NA NA #> 1793 NA NA #> 1794 NA NA #> 1795 NA NA #> 1796 + NA NA #> 1797 U NA NA #> 1798 NA NA #> 1799 NA NA #> 1800 + NA NA #> 1801 NA NA #> 1802 NA NA #> 1803 NA NA #> 1804 NA NA #> 1805 NA NA #> 1806 + NA NA #> 1807 I NA NA #> 1808 NA NA #> 1809 NA NA #> 1810 + NA NA #> 1811 NA NA #> 1812 NA NA #> 1813 NA NA #> 1814 NA NA #> 1815 NA NA #> 1816 + NA NA #> 1817 I 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 I NA NA #> 1828 NA NA #> 1829 NA NA #> 1830 + NA NA #> 1831 NA NA #> 1832 NA NA #> 1833 NA NA #> 1834 NA NA #> 1835 NA NA #> 1836 + NA NA #> 1837 I NA NA #> 1838 NA NA #> 1839 NA NA #> 1840 + NA NA #> 1841 NA NA #> 1842 NA NA #> 1843 NA NA #> 1844 A NA NA #> 1845 NA NA #> 1846 + NA NA #> 1847 U NA NA #> 1848 NA NA #> 1849 NA NA #> 1850 + NA NA #> 1851 NA NA #> 1852 NA NA #> 1853 NA NA #> 1854 NA NA #> 1855 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 NA NA #> 1870 + NA NA #> 1871 NA NA #> 1872 NA NA #> 1873 NA NA #> 1874 NA NA #> 1875 + NA NA #> 1876 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 + NA NA #> 1886 I NA NA #> 1887 NA NA #> 1888 NA NA #> 1889 + NA NA #> 1890 NA NA #> 1891 A NA NA #> 1892 NA NA #> 1893 NA NA #> 1894 NA NA #> 1895 + NA NA #> 1896 NA NA #> 1897 NA NA #> 1898 NA NA #> 1899 + NA NA #> 1900 NA NA #> 1901 NA NA #> 1902 I NA NA #> 1903 NA NA #> 1904 NA NA #> 1905 + NA NA #> 1906 U NA NA #> 1907 NA NA #> 1908 NA NA #> 1909 + NA NA #> 1910 NA NA #> 1911 NA NA #> 1912 NA NA #> 1913 NA NA #> 1914 + NA NA #> 1915 U NA NA #> 1916 NA NA #> 1917 NA NA #> 1918 + NA NA #> 1919 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 NA NA #> 1930 NA NA #> 1931 NA NA #> 1932 A NA NA #> 1933 U NA NA #> 1934 NA NA #> 1935 + NA NA #> 1936 NA NA #> 1937 NA NA #> 1938 NA NA #> 1939 NA NA #> 1940 NA NA #> 1941 + NA NA #> 1942 I NA NA #> 1943 NA NA #> 1944 NA NA #> 1945 + NA NA #> 1946 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 I NA NA #> 1958 NA NA #> 1959 NA NA #> 1960 + NA NA #> 1961 NA NA #> 1962 NA NA #> 1963 A NA NA #> 1964 NA NA #> 1965 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 + NA NA #> 1977 I NA NA #> 1978 NA NA #> 1979 NA NA #> 1980 + NA NA #> 1981 NA NA #> 1982 NA NA #> 1983 U NA NA #> 1984 U NA NA #> 1985 NA NA #> 1986 + NA NA #> 1987 NA NA #> 1988 NA NA #> 1989 NA NA #> 1990 + NA NA #> 1991 NA NA #> 1992 NA NA #> 1993 I NA NA #> 1994 NA NA #> 1995 NA NA #> 1996 NA NA #> 1997 U NA NA #> 1998 NA NA #> 1999 NA NA #> 2000 + NA NA #> 2001 NA NA #> 2002 NA NA #> 2003 NA NA #> 2004 NA NA #> 2005 NA NA #> 2006 NA NA #> 2007 I NA NA #> 2008 NA NA #> 2009 NA NA #> 2010 + NA NA #> 2011 NA NA #> 2012 NA NA #> 2013 I NA NA #> 2014 NA NA #> 2015 NA NA #> 2016 NA NA #> 2017 U NA NA #> 2018 NA NA #> 2019 NA NA #> 2020 + NA NA #> 2021 NA NA #> 2022 NA NA #> 2023 NA NA #> 2024 NA NA #> 2025 NA NA #> 2026 NA NA #> 2027 U NA NA #> 2028 NA NA #> 2029 NA NA #> 2030 + NA NA #> 2031 NA NA #> 2032 NA NA #> 2033 NA NA #> 2034 NA NA #> 2035 NA NA #> 2036 NA NA #> 2037 U NA NA #> 2038 NA NA #> 2039 NA NA #> 2040 + NA NA #> 2041 NA NA #> 2042 NA NA #> 2043 NA NA #> 2044 A NA NA #> 2045 NA NA #> 2046 NA NA #> 2047 U NA NA #> 2048 NA NA #> 2049 NA NA #> 2050 + NA NA #> 2051 NA NA #> 2052 A NA NA #> 2053 + NA NA #> 2054 I NA NA #> 2055 NA NA #> 2056 NA NA #> 2057 NA NA #> 2058 I 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 NA NA #> 2070 NA NA #> 2071 NA NA #> 2072 NA NA #> 2073 NA NA #> 2074 NA NA #> 2075 NA NA #> 2076 NA NA #> 2077 + NA NA #> 2078 NA NA #> 2079 NA NA #> 2080 I NA NA #> 2081 NA NA #> 2082 NA NA #> 2083 NA NA #> 2084 NA NA #> 2085 NA NA #> 2086 NA NA #> 2087 + NA NA #> 2088 NA NA #> 2089 NA NA #> 2090 NA NA #> 2091 A NA NA #> 2092 NA NA #> 2093 NA NA #> 2094 NA NA #> 2095 NA NA #> 2096 NA NA #> 2097 + NA NA #> 2098 NA NA #> 2099 NA NA #> 2100 I NA NA #> 2101 NA NA #> 2102 NA NA #> 2103 NA NA #> 2104 I NA NA #> 2105 NA NA #> 2106 NA NA #> 2107 + NA NA #> 2108 NA NA #> 2109 NA NA #> 2110 I NA NA #> 2111 NA NA #> 2112 NA NA #> 2113 NA NA #> 2114 I NA NA #> 2115 NA NA #> 2116 NA NA #> 2117 + NA NA #> 2118 NA NA #> 2119 NA NA #> 2120 NA NA #> 2121 NA NA #> 2122 NA NA #> 2123 NA NA #> 2124 U NA NA #> 2125 NA NA #> 2126 NA NA #> 2127 + NA NA #> 2128 NA NA #> 2129 NA NA #> 2130 NA NA #> 2131 NA NA #> 2132 NA NA #> 2133 NA NA #> 2134 I NA NA #> 2135 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 I NA NA #> 2145 NA NA #> 2146 NA NA #> 2147 + NA NA #> 2148 NA NA #> 2149 NA NA #> 2150 I NA NA #> 2151 A NA NA #> 2152 NA NA #> 2153 NA NA #> 2154 NA NA #> 2155 NA NA #> 2156 NA NA #> 2157 + NA NA #> 2158 NA NA #> 2159 NA NA #> 2160 NA NA #> 2161 A NA NA #> 2162 NA NA #> 2163 NA NA #> 2164 NA NA #> 2165 NA NA #> 2166 NA NA #> 2167 + NA NA #> 2168 NA NA #> 2169 NA NA #> 2170 I NA NA #> 2171 NA NA #> 2172 NA NA #> 2173 NA NA #> 2174 NA NA #> 2175 NA NA #> 2176 NA NA #> 2177 + NA NA #> 2178 NA NA #> 2179 NA NA #> 2180 I NA NA #> 2181 NA NA #> 2182 NA NA #> 2183 NA NA #> 2184 U NA NA #> 2185 NA NA #> 2186 NA NA #> 2187 + NA NA #> 2188 NA NA #> 2189 NA NA #> 2190 I NA NA #> 2191 A NA NA #> 2192 NA NA #> 2193 NA NA #> 2194 U NA NA #> 2195 NA NA #> 2196 NA NA #> 2197 + NA NA #> 2198 NA NA #> 2199 A NA NA #> 2200 I NA NA #> 2201 NA NA #> 2202 NA NA #> 2203 NA NA #> 2204 U NA NA #> 2205 NA NA #> 2206 NA NA #> 2207 + NA NA #> 2208 NA NA #> 2209 NA NA #> 2210 NA NA #> 2211 NA NA #> 2212 NA NA #> 2213 NA NA #> 2214 U NA NA #> 2215 NA NA #> 2216 NA NA #> 2217 + NA NA #> 2218 NA NA #> 2219 NA NA #> 2220 NA NA #> 2221 NA NA #> 2222 U NA NA #> 2223 NA NA #> 2224 + NA NA #> 2225 NA NA #> 2226 NA NA #> 2227 NA NA #> 2228 NA NA #> 2229 NA NA #> 2230 NA NA #> 2231 U NA NA #> 2232 NA NA #> 2233 NA NA #> 2234 + NA NA #> 2235 NA NA #> 2236 NA NA #> 2237 NA NA #> 2238 A NA NA #> 2239 NA NA #> 2240 NA NA #> 2241 I NA NA #> 2242 NA NA #> 2243 NA NA #> 2244 + NA NA #> 2245 NA NA #> 2246 NA NA #> 2247 I NA NA #> 2248 NA NA #> 2249 NA NA #> 2250 NA NA #> 2251 I NA NA #> 2252 NA NA #> 2253 NA NA #> 2254 + NA NA #> 2255 NA NA #> 2256 A NA NA #> 2257 I 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 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 A NA NA #> 2279 NA NA #> 2280 NA NA #> 2281 I NA NA #> 2282 NA NA #> 2283 NA NA #> 2284 + NA NA #> 2285 NA NA #> 2286 NA NA #> 2287 I NA NA #> 2288 A NA NA #> 2289 NA NA #> 2290 NA NA #> 2291 I NA NA #> 2292 NA NA #> 2293 NA NA #> 2294 + NA NA #> 2295 NA NA #> 2296 NA NA #> 2297 I NA NA #> 2298 NA NA #> 2299 NA NA #> 2300 NA NA #> 2301 I NA NA #> 2302 NA NA #> 2303 + NA NA #> 2304 NA NA #> 2305 NA NA #> 2306 U NA NA #> 2307 NA NA #> 2308 NA NA #> 2309 U NA NA #> 2310 NA NA #> 2311 + NA NA #> 2312 NA NA #> 2313 NA NA #> 2314 NA NA #> 2315 NA NA #> 2316 I NA NA #> 2317 + NA NA #> 2318 NA NA #> 2319 + NA NA #> 2320 NA NA #> 2321 I NA NA #> 2322 NA NA #> 2323 NA NA #> 2324 NA NA #> 2325 NA NA #> 2326 NA NA #> 2327 U NA NA #> 2328 + NA NA #> 2329 NA NA #> 2330 + NA NA #> 2331 NA NA #> 2332 I NA NA #> 2333 NA NA #> 2334 NA NA #> 2335 NA NA #> 2336 NA NA #> 2337 NA NA #> 2338 U NA NA #> 2339 + NA NA #> 2340 NA NA #> 2341 + NA NA #> 2342 I NA NA #> 2343 NA NA #> 2344 NA NA #> 2345 NA NA #> 2346 NA NA #> 2347 NA NA #> 2348 I NA NA #> 2349 NA NA #> 2350 + NA NA #> 2351 NA NA #> 2352 U NA NA #> 2353 A NA NA #> 2354 NA NA #> 2355 NA NA #> 2356 NA NA #> 2357 NA NA #> 2358 NA NA #> 2359 NA NA #> 2360 NA NA #> 2361 + NA NA #> 2362 NA NA #> 2363 I NA NA #> 2364 NA NA #> 2365 NA NA #> 2366 NA NA #> 2367 NA NA #> 2368 NA NA #> 2369 I NA NA #> 2370 NA NA #> 2371 NA NA #> 2372 + NA NA #> 2373 NA NA #> 2374 I NA NA #> 2375 NA NA #> 2376 NA NA #> 2377 NA NA #> 2378 NA NA #> 2379 NA NA #> 2380 + NA NA #> 2381 I NA NA #> 2382 NA NA #> 2383 NA NA #> 2384 NA NA #> 2385 I NA NA #> 2386 NA NA #> 2387 NA NA #> 2388 + NA NA #> 2389 NA NA #> 2390 I NA NA #> 2391 NA NA #> 2392 NA NA #> 2393 NA NA #> 2394 NA NA #> 2395 NA NA #> 2396 U NA NA #> 2397 NA NA #> 2398 NA NA #> 2399 + NA NA #> 2400 NA NA #> 2401 I NA NA #> 2402 NA NA #> 2403 NA NA #> 2404 NA NA #> 2405 NA NA #> 2406 NA NA #> 2407 U NA NA #> 2408 NA NA #> 2409 NA NA #> 2410 + NA NA #> 2411 NA NA #> 2412 I NA NA #> 2413 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 U NA NA #> 2424 NA NA #> 2425 NA NA #> 2426 NA NA #> 2427 NA NA #> 2428 NA NA #> 2429 I NA NA #> 2430 NA NA #> 2431 NA NA #> 2432 + NA NA #> 2433 NA NA #> 2434 I NA NA #> 2435 NA NA #> 2436 NA NA #> 2437 NA NA #> 2438 NA NA #> 2439 NA NA #> 2440 NA NA #> 2441 NA NA #> 2442 NA NA #> 2443 NA NA #> 2444 NA NA #> 2445 NA NA #> 2446 NA NA #> 2447 NA NA #> 2448 NA NA #> 2449 NA NA #> 2450 NA NA #> 2451 NA NA #> 2452 U NA NA #> 2453 NA NA #> 2454 NA NA #> 2455 + NA NA #> 2456 NA NA #> 2457 I NA NA #> 2458 A NA NA #> 2459 A NA NA #> 2460 NA NA #> 2461 NA NA #> 2462 NA NA #> 2463 U NA NA #> 2464 NA NA #> 2465 NA NA #> 2466 + NA NA #> 2467 NA NA #> 2468 I NA NA #> 2469 NA NA #> 2470 NA NA #> 2471 NA NA #> 2472 NA NA #> 2473 NA NA #> 2474 U NA NA #> 2475 NA NA #> 2476 NA NA #> 2477 + NA NA #> 2478 NA NA #> 2479 A NA NA #> 2480 NA NA #> 2481 NA NA #> 2482 NA NA #> 2483 NA NA #> 2484 NA NA #> 2485 I NA NA #> 2486 NA NA #> 2487 NA NA #> 2488 + NA NA #> 2489 NA NA #> 2490 I NA NA #> 2491 NA NA #> 2492 A NA NA #> 2493 NA NA #> 2494 NA NA #> 2495 NA NA #> 2496 U NA NA #> 2497 NA NA #> 2498 NA NA #> 2499 + NA NA #> 2500 NA NA #> 2501 I NA NA #> 2502 NA NA #> 2503 NA NA #> 2504 NA NA #> 2505 NA NA #> 2506 NA NA #> 2507 U NA NA #> 2508 NA NA #> 2509 NA NA #> 2510 + NA NA #> 2511 NA NA #> 2512 I NA NA #> 2513 NA NA #> 2514 NA NA #> 2515 NA NA #> 2516 NA NA #> 2517 NA NA #> 2518 NA NA #> 2519 NA NA #> 2520 NA NA #> 2521 + NA NA #> 2522 NA NA #> 2523 I NA NA #> 2524 NA NA #> 2525 NA NA #> 2526 NA NA #> 2527 NA NA #> 2528 I NA NA #> 2529 NA NA #> 2530 NA NA #> 2531 + NA NA #> 2532 NA NA #> 2533 I NA NA #> 2534 NA NA #> 2535 NA NA #> 2536 NA NA #> 2537 NA NA #> 2538 I NA NA #> 2539 NA NA #> 2540 NA NA #> 2541 + NA NA #> 2542 NA NA #> 2543 NA NA #> 2544 NA NA #> 2545 NA NA #> 2546 NA NA #> 2547 NA NA #> 2548 NA NA #> 2549 U NA NA #> 2550 NA NA #> 2551 NA NA #> 2552 + NA NA #> 2553 NA NA #> 2554 I NA NA #> 2555 NA NA #> 2556 NA NA #> 2557 NA NA #> 2558 NA NA #> 2559 NA NA #> 2560 U NA NA #> 2561 NA NA #> 2562 NA NA #> 2563 + NA NA #> 2564 NA NA #> 2565 I NA NA #> 2566 NA NA #> 2567 NA NA #> 2568 NA NA #> 2569 NA NA #> 2570 NA NA #> 2571 U NA NA #> 2572 NA NA #> 2573 NA NA #> 2574 + NA NA #> 2575 NA NA #> 2576 I NA NA #> 2577 A NA NA #> 2578 NA NA #> 2579 NA NA #> 2580 NA NA #> 2581 NA NA #> 2582 U NA NA #> 2583 NA NA #> 2584 NA NA #> 2585 + NA NA #> 2586 NA NA #> 2587 NA NA #> 2588 A NA NA #> 2589 NA NA #> 2590 NA NA #> 2591 NA NA #> 2592 NA NA #> 2593 U NA NA #> 2594 NA NA #> 2595 NA NA #> 2596 + NA NA #> 2597 NA NA #> 2598 I NA NA #> 2599 NA NA #> 2600 NA NA #> 2601 NA NA #> 2602 NA NA #> 2603 NA NA #> 2604 U NA NA #> 2605 NA NA #> 2606 NA NA #> 2607 + NA NA #> 2608 NA NA #> 2609 I NA NA #> 2610 NA NA #> 2611 I NA NA #> 2612 NA NA #> 2613 NA NA #> 2614 NA NA #> 2615 U 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 NA NA #> 2626 U NA NA #> 2627 NA NA #> 2628 NA NA #> 2629 + NA NA #> 2630 NA NA #> 2631 I NA NA #> 2632 NA NA #> 2633 A NA NA #> 2634 NA NA #> 2635 NA NA #> 2636 NA NA #> 2637 U NA NA #> 2638 NA NA #> 2639 NA NA #> 2640 + NA NA #> 2641 NA NA #> 2642 I NA NA #> 2643 NA NA #> 2644 NA NA #> 2645 NA NA #> 2646 NA NA #> 2647 NA NA #> 2648 U NA NA #> 2649 NA NA #> 2650 NA NA #> 2651 + NA NA #> 2652 NA NA #> 2653 I NA NA #> 2654 NA NA #> 2655 NA NA #> 2656 NA NA #> 2657 NA NA #> 2658 NA NA #> 2659 U NA NA #> 2660 NA NA #> 2661 NA NA #> 2662 + NA NA #> 2663 NA NA #> 2664 I NA NA #> 2665 NA NA #> 2666 NA NA #> 2667 NA NA #> 2668 NA NA #> 2669 NA NA #> 2670 U NA NA #> 2671 NA NA #> 2672 NA NA #> 2673 + NA NA #> 2674 NA NA #> 2675 I NA NA #> 2676 NA NA #> 2677 I NA NA #> 2678 I NA NA #> 2679 NA NA #> 2680 + NA NA #> 2681 NA NA #> 2682 NA NA #> 2683 NA NA #> 2684 NA NA #> 2685 NA NA #> 2686 NA NA #> 2687 NA NA #> 2688 + NA NA #> 2689 NA NA #> 2690 NA NA #> 2691 NA NA #> 2692 + 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 I 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 I NA NA #> 2792 NA NA #> 2793 I NA NA #> 2794 A 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 I NA NA #> 2804 A NA NA #> 2805 NA NA #> 2806 A NA NA #> 2807 NA NA #> 2808 NA NA #> 2809 NA NA #> 2810 NA NA #> 2811 NA NA #> 2812 NA NA #> 2813 + NA NA #> 2814 NA NA #> 2815 I NA NA #> 2816 A NA NA #> 2817 NA NA #> 2818 NA NA #> 2819 NA NA #> 2820 NA NA #> 2821 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 NA NA #> 2831 NA NA #> 2832 NA NA #> 2833 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 NA NA #> 2843 + NA NA #> 2844 NA NA #> 2845 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 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 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 U NA NA #> 2886 + NA NA #> 2887 NA NA #> 2888 + NA NA #> 2889 NA NA #> 2890 U NA NA #> 2891 NA NA #> 2892 NA NA #> 2893 NA NA #> 2894 NA NA #> 2895 NA NA #> 2896 I NA NA #> 2897 + NA NA #> 2898 NA NA #> 2899 + NA NA #> 2900 NA NA #> 2901 NA NA #> 2902 A 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 I 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 I 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 I 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 I NA NA #> 2950 NA NA #> 2951 NA NA #> 2952 NA NA #> 2953 NA NA #> 2954 NA NA #> 2955 A NA NA #> 2956 NA NA #> 2957 I NA NA #> 2958 NA NA #> 2959 NA NA #> 2960 + NA NA #> 2961 NA NA #> 2962 I NA NA #> 2963 NA NA #> 2964 NA NA #> 2965 NA NA #> 2966 NA NA #> 2967 NA NA #> 2968 I NA NA #> 2969 NA NA #> 2970 NA NA #> 2971 + NA NA #> 2972 NA NA #> 2973 I NA NA #> 2974 NA NA #> 2975 NA NA #> 2976 NA NA #> 2977 NA NA #> 2978 NA NA #> 2979 U NA NA #> 2980 NA NA #> 2981 NA NA #> 2982 + NA NA #> 2983 NA NA #> 2984 I NA NA #> 2985 NA NA #> 2986 NA NA #> 2987 U NA NA #> 2988 NA NA #> 2989 + NA NA #> 2990 NA NA #> 2991 I NA NA #> 2992 NA NA #> 2993 NA NA #> 2994 NA NA #> 2995 NA NA #> 2996 NA NA #> 2997 NA NA #> 2998 NA NA #> 2999 NA NA #> 3000 + NA NA #> 3001 NA NA #> 3002 I NA NA #> 3003 NA NA #> 3004 NA NA #> 3005 NA NA #> 3006 NA NA #> 3007 NA NA #> 3008 NA NA #> 3009 NA NA #> 3010 + NA NA #> 3011 NA NA #> 3012 I NA NA #> 3013 NA NA #> 3014 NA NA #> 3015 NA NA #> 3016 NA NA #> 3017 NA NA #> 3018 I 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 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 NA NA #> 3045 NA NA #> 3046 NA NA #> 3047 NA NA #> 3048 NA NA #> 3049 NA NA #> 3050 NA NA #> 3051 NA NA #> 3052 NA NA #> 3053 NA NA #> 3054 NA NA #> 3055 NA NA #> 3056 NA NA #> 3057 NA NA #> 3058 NA NA #> 3059 + NA NA #> 3060 NA NA #> 3061 I NA NA #> 3062 NA NA #> 3063 NA NA #> 3064 NA NA #> 3065 NA NA #> 3066 NA NA #> 3067 NA NA #> 3068 NA NA #> 3069 NA NA #> 3070 + NA NA #> 3071 NA NA #> 3072 I NA NA #> 3073 NA NA #> 3074 NA NA #> 3075 NA NA #> 3076 NA NA #> 3077 NA NA #> 3078 I NA NA #> 3079 NA NA #> 3080 NA NA #> 3081 + NA NA #> 3082 NA NA #> 3083 I NA NA #> 3084 A NA NA #> 3085 NA NA #> 3086 NA NA #> 3087 NA NA #> 3088 NA NA #> 3089 U 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 A NA NA #> 3107 NA NA #> 3108 NA NA #> 3109 NA NA #> 3110 NA NA #> 3111 U NA NA #> 3112 NA NA #> 3113 NA NA #> 3114 + NA NA #> 3115 NA NA #> 3116 I NA NA #> 3117 NA NA #> 3118 NA NA #> 3119 NA NA #> 3120 NA NA #> 3121 NA NA #> 3122 U NA NA #> 3123 NA NA #> 3124 NA NA #> 3125 + NA NA #> 3126 NA NA #> 3127 I NA NA #> 3128 NA NA #> 3129 NA NA #> 3130 NA NA #> 3131 NA NA #> 3132 NA NA #> 3133 U NA NA #> 3134 NA NA #> 3135 NA NA #> 3136 + NA NA #> 3137 NA NA #> 3138 U NA NA #> 3139 NA NA #> 3140 NA NA #> 3141 NA NA #> 3142 NA NA #> 3143 NA NA #> 3144 NA NA #> 3145 NA NA #> 3146 NA NA #> 3147 + NA NA #> 3148 NA NA #> 3149 I NA NA #> 3150 NA NA #> 3151 NA NA #> 3152 NA NA #> 3153 NA NA #> 3154 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 NA NA #> 3166 NA NA #> 3167 NA NA #> 3168 NA NA #> 3169 + NA NA #> 3170 NA NA #> 3171 I NA NA #> 3172 NA NA #> 3173 NA NA #> 3174 NA NA #> 3175 NA NA #> 3176 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 I NA NA #> 3188 NA NA #> 3189 NA NA #> 3190 + NA NA #> 3191 NA NA #> 3192 I NA NA #> 3193 NA NA #> 3194 NA NA #> 3195 NA NA #> 3196 NA NA #> 3197 NA NA #> 3198 U NA NA #> 3199 NA NA #> 3200 NA NA #> 3201 + NA NA #> 3202 NA NA #> 3203 NA NA #> 3204 NA NA #> 3205 U NA NA #> 3206 NA NA #> 3207 NA NA #> 3208 NA NA #> 3209 U NA NA #> 3210 NA NA #> 3211 NA NA #> 3212 + NA NA #> 3213 NA NA #> 3214 NA NA #> 3215 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 I 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 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 U NA NA #> 3254 + NA NA #> 3255 NA NA #> 3256 + NA NA #> 3257 NA NA #> 3258 NA NA #> 3259 A NA NA #> 3260 NA NA #> 3261 NA NA #> 3262 NA NA #> 3263 NA NA #> 3264 NA NA #> 3265 + NA NA #> 3266 NA NA #> 3267 + NA NA #> 3268 NA NA #> 3269 I NA NA #> 3270 NA NA #> 3271 A NA NA #> 3272 NA NA #> 3273 NA NA #> 3274 NA NA #> 3275 NA NA #> 3276 + NA NA #> 3277 NA NA #> 3278 + NA NA #> 3279 NA NA #> 3280 I NA NA #> 3281 NA NA #> 3282 NA NA #> 3283 U NA NA #> 3284 NA NA #> 3285 + NA NA #> 3286 NA NA #> 3287 NA NA #> 3288 NA NA #> 3289 NA NA #> 3290 NA NA #> 3291 NA NA #> 3292 NA NA #> 3293 I NA NA #> 3294 + NA NA #> 3295 NA NA #> 3296 + NA NA #> 3297 NA NA #> 3298 I NA NA #> 3299 NA NA #> 3300 NA NA #> 3301 NA NA #> 3302 NA NA #> 3303 NA NA #> 3304 NA NA #> 3305 + NA NA #> 3306 NA NA #> 3307 + NA NA #> 3308 NA NA #> 3309 I NA NA #> 3310 NA NA #> 3311 A 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 NA NA #> 3325 NA NA #> 3326 NA NA #> 3327 NA NA #> 3328 NA NA #> 3329 NA NA #> 3330 U NA NA #> 3331 + NA NA #> 3332 NA NA #> 3333 + NA NA #> 3334 NA NA #> 3335 I NA NA #> 3336 NA NA #> 3337 NA NA #> 3338 NA NA #> 3339 NA NA #> 3340 + NA NA #> 3341 NA NA #> 3342 NA NA #> 3343 NA NA #> 3344 NA NA #> 3345 I NA NA #> 3346 + NA NA #> 3347 NA NA #> 3348 + NA NA #> 3349 NA NA #> 3350 I NA NA #> 3351 NA NA #> 3352 NA NA #> 3353 NA NA #> 3354 NA NA #> 3355 NA NA #> 3356 NA NA #> 3357 + NA NA #> 3358 NA NA #> 3359 + NA NA #> 3360 NA NA #> 3361 I 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 + NA NA #> 3375 NA NA #> 3376 I NA NA #> 3377 NA NA #> 3378 NA NA #> 3379 NA NA #> 3380 NA NA #> 3381 NA NA #> 3382 A NA NA #> 3383 NA NA #> 3384 NA NA #> 3385 NA NA #> 3386 NA NA #> 3387 NA NA #> 3388 NA NA #> 3389 + NA NA #> 3390 NA NA #> 3391 I NA NA #> 3392 NA NA #> 3393 NA NA #> 3394 NA NA #> 3395 NA NA #> 3396 NA NA #> 3397 NA NA #> 3398 NA NA #> 3399 U NA NA #> 3400 NA NA #> 3401 NA NA #> 3402 + NA NA #> 3403 NA NA #> 3404 I NA NA #> 3405 NA NA #> 3406 NA NA #> 3407 NA NA #> 3408 NA NA #> 3409 + NA NA #> 3410 U NA NA #> 3411 NA NA #> 3412 NA NA #> 3413 + NA NA #> 3414 NA NA #> 3415 I NA NA #> 3416 NA NA #> 3417 NA NA #> 3418 NA NA #> 3419 NA NA #> 3420 NA NA #> 3421 NA NA #> 3422 NA NA #> 3423 NA NA #> 3424 NA NA #> 3425 U NA NA #> 3426 NA NA #> 3427 NA NA #> 3428 + NA NA #> 3429 NA NA #> 3430 I NA NA #> 3431 NA NA #> 3432 NA NA #> 3433 NA NA #> 3434 NA NA #> 3435 NA NA #> 3436 U NA NA #> 3437 NA NA #> 3438 NA NA #> 3439 + NA NA #> 3440 NA NA #> 3441 I NA NA #> 3442 NA NA #> 3443 NA NA #> 3444 NA NA #> 3445 NA NA #> 3446 NA NA #> 3447 NA NA #> 3448 NA NA #> 3449 NA NA #> 3450 + NA NA #> 3451 NA NA #> 3452 I NA NA #> 3453 NA NA #> 3454 NA NA #> 3455 NA NA #> 3456 NA NA #> 3457 NA NA #> 3458 U NA NA #> 3459 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 NA NA #> 3470 NA NA #> 3471 NA NA #> 3472 NA NA #> 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#> 3886 + NA NA #> 3887 NA NA #> 3888 NA NA #> 3889 NA NA #> 3890 NA NA #> 3891 NA NA #> 3892 + NA NA #> 3893 I NA NA #> 3894 NA NA #> 3895 NA NA #> 3896 + NA NA #> 3897 NA NA #> 3898 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 A NA NA #> 3936 + NA NA #> 3937 NA NA #> 3938 NA NA #> 3939 NA NA #> 3940 + NA NA #> 3941 NA NA #> 3942 NA NA #> 3943 NA NA #> 3944 NA NA #> 3945 NA NA #> 3946 + NA NA #> 3947 I NA NA #> 3948 NA NA #> 3949 NA NA #> 3950 + NA NA #> 3951 NA NA #> 3952 A NA NA #> 3953 I NA NA #> 3954 NA NA #> 3955 + NA NA #> 3956 U NA NA #> 3957 NA NA #> 3958 + NA NA #> 3959 NA NA #> 3960 NA NA #> 3961 NA NA #> 3962 NA NA #> 3963 + NA NA #> 3964 I NA NA #> 3965 NA NA #> 3966 NA NA #> 3967 + NA NA #> 3968 NA NA #> 3969 NA NA #> 3970 NA NA #> 3971 A NA NA #> 3972 NA NA #> 3973 + NA NA #> 3974 I NA NA #> 3975 NA NA #> 3976 NA NA #> 3977 + NA NA #> 3978 NA NA #> 3979 NA NA #> 3980 NA NA #> 3981 NA NA #> 3982 + NA NA #> 3983 I NA NA #> 3984 NA NA #> 3985 NA NA #> 3986 + NA NA #> 3987 NA NA #> 3988 NA NA #> 3989 NA NA #> 3990 NA NA #> 3991 I NA NA #> 3992 NA NA #> 3993 + NA NA #> 3994 NA NA #> 3995 NA NA #> 3996 NA NA #> 3997 NA NA #> 3998 + NA NA #> 3999 I NA NA #> 4000 NA NA #> 4001 NA NA #> 4002 + NA NA #> 4003 NA NA #> 4004 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 I NA NA #> 4015 NA NA #> 4016 NA NA #> 4017 + NA NA #> 4018 NA NA #> 4019 NA NA #> 4020 NA NA #> 4021 + NA NA #> 4022 NA NA #> 4023 NA NA #> 4024 NA NA #> 4025 A NA NA #> 4026 + NA NA #> 4027 NA NA #> 4028 NA NA #> 4029 NA NA #> 4030 + NA NA #> 4031 NA NA #> 4032 NA NA #> 4033 NA NA #> 4034 NA NA #> 4035 + NA NA #> 4036 I NA NA #> 4037 NA NA #> 4038 NA NA #> 4039 + NA NA #> 4040 NA NA #> 4041 NA NA #> 4042 NA NA #> 4043 NA NA #> 4044 NA NA #> 4045 + NA NA #> 4046 U NA NA #> 4047 NA NA #> 4048 NA NA #> 4049 + NA NA #> 4050 NA NA #> 4051 NA NA #> 4052 NA NA #> 4053 NA NA #> 4054 NA NA #> 4055 + NA NA #> 4056 I NA NA #> 4057 NA NA #> 4058 + NA NA #> 4059 NA NA #> 4060 A NA NA #> 4061 A NA NA #> 4062 NA NA #> 4063 + NA NA #> 4064 U NA NA #> 4065 NA NA #> 4066 NA NA #> 4067 + NA NA #> 4068 NA NA #> 4069 NA NA #> 4070 NA NA #> 4071 NA NA #> 4072 NA NA #> 4073 + NA NA #> 4074 I NA NA #> 4075 NA NA #> 4076 + NA NA #> 4077 NA NA #> 4078 NA NA #> 4079 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 U NA NA #> 4118 NA NA #> 4119 NA NA #> 4120 + NA NA #> 4121 NA NA #> 4122 NA NA #> 4123 NA NA #> 4124 NA NA #> 4125 + NA NA #> 4126 U NA NA #> 4127 NA NA #> 4128 + NA NA #> 4129 NA NA #> 4130 NA NA #> 4131 NA NA #> 4132 U NA NA #> 4133 NA NA #> 4134 + NA NA #> 4135 NA NA #> 4136 NA NA #> 4137 NA NA #> 4138 NA NA #> 4139 + NA NA #> 4140 I NA NA #> 4141 NA NA #> 4142 NA NA #> 4143 + NA NA #> 4144 NA NA #> 4145 NA NA #> 4146 NA NA #> 4147 A NA NA #> 4148 NA NA #> 4149 NA NA #> 4150 I NA NA #> 4151 NA NA #> 4152 NA NA #> 4153 + NA NA #> 4154 NA NA #> 4155 NA NA #> 4156 NA NA #> 4157 NA NA #> 4158 NA NA #> 4159 NA NA #> 4160 I NA NA #> 4161 NA NA #> 4162 NA NA #> 4163 + NA NA #> 4164 NA NA #> 4165 NA NA #> 4166 NA NA #> 4167 NA NA #> 4168 NA NA #> 4169 NA NA #> 4170 I NA NA #> 4171 NA NA #> 4172 NA NA #> 4173 + NA NA #> 4174 NA NA #> 4175 NA NA #> 4176 NA NA #> 4177 NA NA #> 4178 NA NA #> 4179 NA NA #> 4180 I NA NA #> 4181 NA NA #> 4182 NA NA #> 4183 + NA NA #> 4184 NA NA #> 4185 NA NA #> 4186 NA NA #> 4187 NA NA #> 4188 NA NA #> 4189 NA NA #> 4190 U NA NA #> 4191 NA NA #> 4192 NA NA #> 4193 + NA NA #> 4194 NA NA #> 4195 A NA NA #> 4196 NA NA #> 4197 NA NA #> 4198 NA NA #> 4199 NA NA #> 4200 U NA NA #> 4201 NA NA #> 4202 NA NA #> 4203 + NA NA #> 4204 NA NA #> 4205 NA NA #> 4206 NA NA #> 4207 NA NA #> 4208 NA NA #> 4209 NA NA #> 4210 I NA NA #> 4211 NA NA #> 4212 NA NA #> 4213 + NA NA #> 4214 NA NA #> 4215 NA NA #> 4216 I NA NA #> 4217 NA NA #> 4218 NA NA #> 4219 NA NA #> 4220 I NA NA #> 4221 NA NA #> 4222 NA NA #> 4223 + NA NA #> 4224 NA NA #> 4225 NA NA #> 4226 NA NA #> 4227 NA NA #> 4228 NA NA #> 4229 NA NA #> 4230 I NA NA #> 4231 NA NA #> 4232 NA NA #> 4233 + NA NA #> 4234 NA NA #> 4235 A NA NA #> 4236 NA NA #> 4237 A NA NA #> 4238 NA NA #> 4239 NA NA #> 4240 I NA NA #> 4241 NA NA #> 4242 NA NA #> 4243 + NA NA #> 4244 NA NA #> 4245 NA NA #> 4246 NA NA #> 4247 A NA NA #> 4248 NA NA #> 4249 NA NA #> 4250 U NA NA #> 4251 NA NA #> 4252 NA NA #> 4253 + NA NA #> 4254 NA NA #> 4255 NA NA #> 4256 NA NA #> 4257 NA NA #> 4258 NA NA #> 4259 NA NA #> 4260 U NA NA #> 4261 NA NA #> 4262 NA NA #> 4263 + NA NA #> 4264 NA NA #> 4265 NA NA #> 4266 NA NA #> 4267 NA NA #> 4268 NA NA #> 4269 NA NA #> 4270 I NA NA #> 4271 NA NA #> 4272 NA NA #> 4273 + NA NA #> 4274 NA NA #> 4275 NA NA #> 4276 NA NA #> 4277 NA NA #> 4278 NA NA #> 4279 NA NA #> 4280 I NA NA #> 4281 NA NA #> 4282 NA NA #> 4283 + NA NA #> 4284 NA NA #> 4285 NA NA #> 4286 NA NA #> 4287 NA NA #> 4288 NA NA #> 4289 NA NA #> 4290 NA NA #> 4291 NA NA #> 4292 NA NA #> 4293 + NA NA #> 4294 NA NA #> 4295 NA NA #> 4296 NA NA #> 4297 NA NA #> 4298 NA NA #> 4299 NA NA #> 4300 + NA NA #> 4301 NA NA #> 4302 I NA NA #> 4303 NA NA #> 4304 NA NA #> 4305 NA NA #> 4306 NA NA #> 4307 NA NA #> 4308 NA NA #> 4309 + NA NA #> 4310 NA NA #> 4311 NA NA #> 4312 I NA NA #> 4313 NA NA #> 4314 NA NA #> 4315 NA NA #> 4316 NA NA #> 4317 NA NA #> 4318 NA NA #> 4319 + NA NA #> 4320 NA NA #> 4321 NA NA #> 4322 I NA NA #> 4323 NA NA #> 4324 I NA NA #> 4325 NA NA #> 4326 + NA NA #> 4327 NA NA #> 4328 NA NA #> 4329 I NA NA #> 4330 A NA NA #> 4331 I NA NA #> 4332 NA NA #> 4333 NA NA #> 4334 + NA NA #> 4335 NA NA #> 4336 NA NA #> 4337 I NA NA #> 4338 NA NA #> 4339 U NA NA #> 4340 NA NA #> 4341 NA NA #> 4342 + NA NA #> 4343 NA NA #> 4344 NA NA #> 4345 NA NA #> 4346 NA NA #> 4347 I NA NA #> 4348 NA NA #> 4349 + NA NA #> 4350 NA NA #> 4351 NA NA #> 4352 I NA NA #> 4353 NA NA #> 4354 NA NA #> 4355 NA NA #> 4356 I NA NA #> 4357 NA NA #> 4358 NA NA #> 4359 + NA NA #> 4360 NA NA #> 4361 NA NA #> 4362 NA NA #> 4363 A NA NA #> 4364 NA NA #> 4365 NA NA #> 4366 I NA NA #> 4367 NA NA #> 4368 NA NA #> 4369 + NA NA #> 4370 NA NA #> 4371 NA NA #> 4372 I NA NA #> 4373 NA NA #> 4374 NA NA #> 4375 NA NA #> 4376 I NA NA #> 4377 NA NA #> 4378 NA NA #> 4379 + NA NA #> 4380 NA NA #> 4381 NA NA #> 4382 NA NA #> 4383 NA NA #> 4384 NA NA #> 4385 NA NA #> 4386 U NA NA #> 4387 NA NA #> 4388 NA NA #> 4389 + NA NA #> 4390 NA NA #> 4391 A NA NA #> 4392 NA NA #> 4393 NA NA #> 4394 NA NA #> 4395 NA NA #> 4396 NA NA #> 4397 + NA NA #> 4398 NA NA #> 4399 NA NA #> 4400 NA NA #> 4401 NA NA #> 4402 NA NA #> 4403 NA NA #> 4404 NA NA #> 4405 NA NA #> 4406 NA NA #> 4407 + NA NA #> 4408 NA NA #> 4409 NA NA #> 4410 I NA NA #> 4411 NA NA #> 4412 NA NA #> 4413 NA NA #> 4414 NA NA #> 4415 NA NA #> 4416 + NA NA #> 4417 NA NA #> 4418 NA NA #> 4419 I NA NA #> 4420 NA NA #> 4421 NA NA #> 4422 NA NA #> 4423 I NA NA #> 4424 NA NA #> 4425 NA NA #> 4426 + NA NA #> 4427 NA NA #> 4428 NA NA #> 4429 I NA NA #> 4430 A NA NA #> 4431 NA NA #> 4432 NA NA #> 4433 I NA NA #> 4434 NA NA #> 4435 NA NA #> 4436 + NA NA #> 4437 NA NA #> 4438 NA NA #> 4439 I NA NA #> 4440 A NA NA #> 4441 NA NA #> 4442 NA NA #> 4443 I NA NA #> 4444 NA NA #> 4445 NA NA #> 4446 + NA NA #> 4447 NA NA #> 4448 NA NA #> 4449 I NA NA #> 4450 NA NA #> 4451 NA NA #> 4452 NA NA #> 4453 I NA NA #> 4454 NA NA #> 4455 NA NA #> 4456 + NA NA #> 4457 NA NA #> 4458 NA NA #> 4459 NA NA #> 4460 A NA NA #> 4461 NA NA #> 4462 NA NA #> 4463 NA NA #> 4464 NA NA #> 4465 NA NA #> 4466 + NA NA #> 4467 NA NA #> 4468 NA NA #> 4469 I NA NA #> 4470 A NA NA #> 4471 NA NA #> 4472 NA NA #> 4473 NA NA #> 4474 NA NA #> 4475 NA NA #> 4476 + NA NA #> 4477 NA NA #> 4478 NA NA #> 4479 NA NA #> 4480 NA NA #> 4481 NA NA #> 4482 NA NA #> 4483 + NA NA #> 4484 I NA NA #> 4485 NA NA #> 4486 NA NA #> 4487 NA NA #> 4488 NA NA #> 4489 NA NA #> 4490 NA NA #> 4491 NA NA #> 4492 NA NA #> 4493 + NA NA #> 4494 NA NA #> 4495 NA NA #> 4496 NA NA #> 4497 NA NA #> 4498 NA NA #> 4499 + NA NA #> 4500 I NA NA #> 4501 NA NA #> 4502 NA NA #> 4503 NA NA #> 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#> 8987 NA NA #> 8988 NA NA #> 8989 NA NA #> 8990 NA NA #> 8991 NA NA #> 8992 + NA NA #> 8993 NA NA #> 8994 NA NA #> 8995 NA NA #> 8996 + NA NA #> 8997 NA NA #> 8998 NA NA #> 8999 NA NA #> 9000 + NA NA #> 9001 NA NA #> 9002 NA NA #> 9003 NA NA #> 9004 NA NA #> 9005 + NA NA #> 9006 NA NA #> 9007 NA NA #> 9008 NA NA #> 9009 NA NA #> 9010 NA NA #> 9011 NA NA #> 9012 NA NA #> 9013 NA NA #> 9014 NA NA #> 9015 + NA NA #> 9016 NA NA #> 9017 NA NA #> 9018 NA NA #> 9019 + NA NA #> 9020 NA NA #> 9021 NA NA #> 9022 NA NA #> 9023 NA NA #> 9024 + NA NA #> 9025 I NA NA #> 9026 NA NA #> 9027 NA NA #> 9028 NA NA #> 9029 NA NA #> 9030 NA NA #> 9031 NA NA #> 9032 NA NA #> 9033 NA NA #> 9034 + NA NA #> 9035 NA NA #> 9036 NA NA #> 9037 NA NA #> 9038 + NA NA #> 9039 NA NA #> 9040 NA NA #> 9041 NA NA #> 9042 NA NA #> 9043 + NA NA #> 9044 I NA NA #> 9045 NA NA #> 9046 NA NA #> 9047 NA NA #> 9048 NA NA #> 9049 NA NA #> 9050 NA NA #> 9051 + NA NA #> 9052 NA NA #> 9053 NA NA #> 9054 NA NA #> 9055 NA NA #> 9056 NA NA #> 9057 NA NA #> 9058 + NA NA #> 9059 I NA NA #> 9060 NA NA #> 9061 NA NA #> 9062 NA NA #> 9063 NA NA #> 9064 NA NA #> 9065 NA NA #> 9066 NA NA #> 9067 NA NA #> 9068 + NA NA #> 9069 NA NA #> 9070 NA NA #> 9071 NA NA #> 9072 + NA NA #> 9073 NA NA #> 9074 NA NA #> 9075 NA NA #> 9076 NA NA #> 9077 + NA NA #> 9078 U NA NA #> 9079 NA NA #> 9080 NA NA #> 9081 NA NA #> 9082 NA NA #> 9083 NA NA #> 9084 NA NA #> 9085 NA NA #> 9086 NA NA #> 9087 + NA NA #> 9088 NA NA #> 9089 NA NA #> 9090 NA NA #> [ reached 'max' / getOption(\"max.print\") -- omitted 165566 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 = 2022)"},{"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 = 2022) #> # 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 NA 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 = 2022, 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 = 2022) head(dat) #> id name JEI wbid class year CHLAC COLOR COND DO DOSAT #> 1 2 Rock Creek CC01 2052 3M 2013 2.725391 9.607368 NA 6.819091 73.50770 #> 2 2 Rock Creek CC01 2052 3M 2014 2.380249 14.694735 NA 3.308289 60.31523 #> 3 2 Rock Creek CC01 2052 3M 2015 2.647817 21.911128 NA 4.034172 55.41609 #> 4 2 Rock Creek CC01 2052 3M 2016 2.265462 19.130797 NA 3.980251 55.96637 #> 5 2 Rock Creek CC01 2052 3M 2017 2.851726 15.395763 NA 4.157777 60.18017 #> 6 2 Rock Creek CC01 2052 3M 2018 1.934899 11.655004 NA 4.219790 63.32630 #> NO23 ORGN SALIN TKN TN TP TSS TURB #> 1 0.009781633 NA 30.90561 0.6510575 0.7108146 0.06842811 NA 1.698004 #> 2 0.007575792 NA 26.63714 0.6161702 0.6228782 0.06938150 NA 2.044623 #> 3 0.009361504 NA 19.10494 0.6465161 0.5678241 0.07602770 NA 1.814818 #> 4 0.008532522 NA 25.84531 0.5813818 0.5408161 0.08330509 NA 2.082253 #> 5 0.007447260 NA 24.86909 0.6255197 0.6326848 0.07566682 NA 1.802161 #> 6 0.006994714 NA 31.32419 0.5668727 0.5734574 0.07432007 NA 2.454007 #> chla_tn_ratio tn_tp_ratio chla_tsi tn_tsi tn2_tsi tp_tsi tp2_tsi #> 1 3.834180 10.387756 31.23761 49.24140 52.26414 60.19958 75.92850 #> 2 3.821371 8.977584 29.28775 46.62660 49.42526 60.45694 76.25504 #> 3 4.663093 7.468648 30.82179 44.79432 47.43600 62.15842 78.41391 #> 4 4.188970 6.491994 28.57601 43.82942 46.38844 63.85868 80.57123 #> 5 4.507341 8.361456 31.89011 46.93590 49.76107 62.06992 78.30162 #> 6 3.374095 7.716050 26.30480 44.98978 47.64821 61.73589 77.87779 #> nut_tsi tsi no23_source no23_tidal no23_ratio do_bnml do_prop #> 1 54.72049 42.97905 NA NA NA 0 0 #> 2 49.42526 39.35651 NA NA NA 0 1 #> 3 47.43600 39.12890 NA NA NA 0 1 #> 4 46.38844 37.48223 NA NA NA 0 1 #> 5 49.76107 40.82559 NA NA NA 0 0 #> 6 47.64821 36.97650 NA NA NA 0 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\"), 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\" 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: 182 × 3 #> yr Savspecies foest #> #> 1 1998 Caulerpa 0.0166 #> 2 1998 Halodule 0.361 #> 3 1998 Halophila 0 #> 4 1998 Ruppia 0.0112 #> 5 1998 Syringodium 0.0451 #> 6 1998 Thalassia 0.254 #> 7 1998 total 0.580 #> 8 1999 Caulerpa 0.0277 #> 9 1999 Halodule 0.306 #> 10 1999 Halophila 0.00118 #> # ℹ 172 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, whereas attached drift algae species aggregated.","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 \"CYAN: Lyngbya/Dapis\" 41 0 0 #> 3 1997-10-11 S2T3 \"Caulerpa\" 41 0 0 #> 4 1997-10-11 S2T3 \"DA\" 41 0 0 #> 5 1997-10-11 S2T3 \"DB: Dictyota\\r\\n\" 41 0 0 #> 6 1997-10-11 S2T3 \"DB: Drift Brown\\r\\n\" 41 0 0 #> 7 1997-10-11 S2T3 \"DG: Chaetomorpha\\r\\n\" 41 0 0 #> 8 1997-10-11 S2T3 \"DG: Drift Green\" 41 0 0 #> 9 1997-10-11 S2T3 \"DG: Ulva\" 41 0 0 #> 10 1997-10-11 S2T3 \"DG: Ulva fasciata\\r\\n\" 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 = 2022) #> # A tibble: 4 × 6 #> bay_segment chla_val chla_target la_val la_target outcome #> #> 1 OTB 7.12 8.5 0.787 0.83 green #> 2 HB 8.86 13.2 0.922 1.58 green #> 3 MTB 5.05 7.4 0.553 0.83 green #> 4 LTB 3.59 4.6 0.658 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 12142023 — benthicdata","title":"Benthic data for the Tampa Bay Benthic Index current as of 12142023 — benthicdata","text":"Benthic data Tampa Bay Benthic Index current 12142023","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 12142023 — 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 12142023 — 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 12142023 — 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 12142023 — 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 20230710 — fibdata","title":"All Fecal Indicator Bacteria (FIB) data as of 20230710 — fibdata","text":"Fecal Indicator Bacteria (FIB) data 20230710","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 20230710 — 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 20230710 — fibdata","text":"data frame 74872 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 20230710 — 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') }"},{"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 64 — iwrraw","title":"FDEP IWR run 64 — iwrraw","text":"Florida Department Environmental Protection, Impaired Waters Rule, Run 64","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/iwrraw.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"FDEP IWR run 64 — 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 64 — iwrraw","text":"data frame 194881 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 64 — 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 64 — 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 05192022 — phytodata","title":"Phytoplankton data current as of 05192022 — phytodata","text":"Phytoplankton data current 05192022","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 05192022 — 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 05192022 — phytodata","text":"nested tibble 23848 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 05192022 — phytodata","text":"","code":"if (FALSE) { # location to download data path <- '~/Desktop/phyto_data.xlsx' # load and assign to object phytodata <- read_importphyto(path, download_latest = TRUE) save(phytodata, file = 'data/phytodata.RData', compress = 'xz') }"},{"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 \"21FLHILL_WQX\" (Hillsborough County), \"21FLMANA_WQX\" (Manatee County), \"21FLPASC_WQX\" (Pasco County), \"21FLPDEM_WQX\" (Pinellas County), \"21FLPOLK_WQX\" (Polk County). 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) 2022 target 2022 target OTB 7.1 8.5 0.79 0.83 HB 8.9 13.2 0.92 1.58 MTB 5.0 7.4 0.55 0.83 LTB 3.6 4.6 0.66 0.63 Water quality outcomes 2022. Segment Chl-(ug/L) Light Penetration (m-1) 2022 target 2022 target OTB 7.1 8.5 0.79 0.83 HB 8.9 13.2 0.92 1.58 MTB 5.0 7.4 0.55 0.83 LTB 3.6 4.6 0.66 0.63","code":"show_annualassess(epcdata, yrsel = 2022) .cl-85d890be{}.cl-85d290c4{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-85d290ce{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-85d51e70{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-85d51e7a{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-85d5325c{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-85d5325d{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-85d53266{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-85d53267{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-85d53270{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-85d53271{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)2022target2022targetOTB7.18.50.790.83HB8.913.20.921.58MTB5.07.40.550.83LTB3.64.60.660.63show_annualassess(epcdata, yrsel = 2022, caption = TRUE) .cl-86108f6e{}.cl-860b3064{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-860b306e{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-860d787e{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-860d7888{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-860d8940{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-860d894a{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-860d894b{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-860d894c{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-860d8954{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-860d8955{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-86078036{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 2022.SegmentChl-a (ug/L)Light Penetration (m-1)2022target2022targetOTB7.18.50.790.83HB8.913.20.921.58MTB5.07.40.550.83LTB3.64.60.660.63"},{"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, 2022), 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 = 2022, 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 = 2022, mosel = 8) 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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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Class: Marine (Enterococcus<\\/i>)
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Class: Marine (Enterococcus<\\/i>)
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Class: Marine (Enterococcus<\\/i>)
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Class: Marine (Enterococcus<\\/i>)
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Class: Marine (Enterococcus<\\/i>)
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Class: Marine (Enterococcus<\\/i>)
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Class: Marine (Enterococcus<\\/i>)
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Class: Marine (Enterococcus<\\/i>)
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Class: Marine (Enterococcus<\\/i>)
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Class: Marine (Enterococcus<\\/i>)
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Class: Marine (Enterococcus<\\/i>)
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Class: Marine (Enterococcus<\\/i>)
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Class: Marine (Enterococcus<\\/i>)
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Class: Marine (Enterococcus<\\/i>)
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Class: Marine (Enterococcus<\\/i>)
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Class: Marine (Enterococcus<\\/i>)
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Class: Marine (Enterococcus<\\/i>)
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Class: Marine (Enterococcus<\\/i>)
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Class: Marine (Enterococcus<\\/i>)
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Class: Marine (Enterococcus<\\/i>)
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Class: Marine (Enterococcus<\\/i>)
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Class: Marine (Enterococcus<\\/i>)
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Class: Marine (Enterococcus<\\/i>)
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Class: Marine (Enterococcus<\\/i>)
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Class: Marine (Enterococcus<\\/i>)
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Class: Marine (Enterococcus<\\/i>)
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Class: Marine (Enterococcus<\\/i>)
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Class: Marine (Enterococcus<\\/i>)
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Class: Marine (Enterococcus<\\/i>)
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Class: Marine (Enterococcus<\\/i>)
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Class: Marine (Enterococcus<\\/i>)
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Class: Marine (Enterococcus<\\/i>)
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Class: Marine (Enterococcus<\\/i>)
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Class: Freshwater (E. coli<\\/i>)
Category: < 126 (100/100mL)<\\/html>\",\"Station Number: 132
Class: Freshwater (E. coli<\\/i>)
Category: > 999 (1367/100mL)<\\/html>\",\"Station Number: 133
Class: Marine (Enterococcus<\\/i>)
Category: 130 - 999 (550/100mL)<\\/html>\",\"Station Number: 135
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (4/100mL)<\\/html>\",\"Station Number: 137
Class: Marine (Enterococcus<\\/i>)
Category: 35 - 129 (128/100mL)<\\/html>\",\"Station Number: 138
Class: Freshwater (E. coli<\\/i>)
Category: 126 - 409 (267/100mL)<\\/html>\",\"Station Number: 139
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (73/100mL)<\\/html>\",\"Station Number: 140
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (80/100mL)<\\/html>\",\"Station Number: 141
Class: Freshwater (E. coli<\\/i>)
Category: 126 - 409 (307/100mL)<\\/html>\",\"Station Number: 142
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (7/100mL)<\\/html>\",\"Station Number: 143
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (76/100mL)<\\/html>\",\"Station Number: 144
Class: Marine (Enterococcus<\\/i>)
Category: 130 - 999 (380/100mL)<\\/html>\",\"Station Number: 145
Class: Freshwater (E. coli<\\/i>)
Category: 126 - 409 (180/100mL)<\\/html>\",\"Station Number: 146
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (32/100mL)<\\/html>\",\"Station Number: 147
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (6/100mL)<\\/html>\",\"Station Number: 148
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (92/100mL)<\\/html>\",\"Station Number: 149
Class: Freshwater (E. coli<\\/i>)
Category: 126 - 409 (180/100mL)<\\/html>\",\"Station Number: 151
Class: Freshwater (E. coli<\\/i>)
Category: 410 - 999 (527/100mL)<\\/html>\",\"Station Number: 152
Class: Marine (Enterococcus<\\/i>)
Category: > 999 (1010/100mL)<\\/html>\",\"Station Number: 153
Class: Marine (Enterococcus<\\/i>)
Category: 130 - 999 (550/100mL)<\\/html>\",\"Station Number: 154
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (80/100mL)<\\/html>\",\"Station Number: 155
Class: Freshwater (E. coli<\\/i>)
Category: 126 - 409 (170/100mL)<\\/html>\",\"Station Number: 158
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (53/100mL)<\\/html>\",\"Station Number: 160
Class: Freshwater (E. coli<\\/i>)
Category: 126 - 409 (140/100mL)<\\/html>\",\"Station Number: 161
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (100/100mL)<\\/html>\",\"Station Number: 163
Class: Freshwater (E. coli<\\/i>)
Category: 126 - 409 (240/100mL)<\\/html>\",\"Station Number: 164
Class: Freshwater (E. coli<\\/i>)
Category: 126 - 409 (160/100mL)<\\/html>\",\"Station Number: 165
Class: Freshwater (E. coli<\\/i>)
Category: 126 - 409 (287/100mL)<\\/html>\",\"Station Number: 166
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (60/100mL)<\\/html>\",\"Station Number: 168
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (47/100mL)<\\/html>\",\"Station Number: 169
Class: Freshwater (E. coli<\\/i>)
Category: 126 - 409 (240/100mL)<\\/html>\",\"Station Number: 170
Class: Freshwater (E. coli<\\/i>)
Category: 126 - 409 (140/100mL)<\\/html>\",\"Station Number: 171
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (14/100mL)<\\/html>\",\"Station Number: 172
Class: Freshwater (E. coli<\\/i>)
Category: 126 - 409 (240/100mL)<\\/html>\",\"Station Number: 173
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (107/100mL)<\\/html>\",\"Station Number: 174
Class: Marine (Enterococcus<\\/i>)
Category: 35 - 129 (63/100mL)<\\/html>\",\"Station Number: 175
Class: Freshwater (E. coli<\\/i>)
Category: 126 - 409 (400/100mL)<\\/html>\",\"Station Number: 176
Class: Marine (Enterococcus<\\/i>)
Category: 130 - 999 (377/100mL)<\\/html>\",\"Station Number: 177
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (12/100mL)<\\/html>\",\"Station Number: 178
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (20/100mL)<\\/html>\",\"Station Number: 179
Class: Marine (Enterococcus<\\/i>)
Category: 130 - 999 (130/100mL)<\\/html>\",\"Station Number: 180
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 181
Class: Marine (Enterococcus<\\/i>)
Category: 35 - 129 (78/100mL)<\\/html>\",\"Station Number: 182
Class: Marine (Enterococcus<\\/i>)
Category: 35 - 129 (128/100mL)<\\/html>\",\"Station Number: 264
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (20/100mL)<\\/html>\",\"Station Number: 265
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (100/100mL)<\\/html>\",\"Station Number: 266
Class: Freshwater (E. coli<\\/i>)
Category: 126 - 409 (135/100mL)<\\/html>\",\"Station Number: 267
Class: Freshwater (E. coli<\\/i>)
Category: > 999 (1700/100mL)<\\/html>\",\"Station Number: 268
Class: Freshwater (E. coli<\\/i>)
Category: > 999 (1400/100mL)<\\/html>\",\"Station Number: 269
Class: Freshwater (E. coli<\\/i>)
Category: > 999 (2400/100mL)<\\/html>\",\"Station Number: 270
Class: Marine (Enterococcus<\\/i>)
Category: > 999 (2600/100mL)<\\/html>\",\"Station Number: 271
Class: Freshwater (E. coli<\\/i>)
Category: > 999 (2400/100mL)<\\/html>\",\"Station Number: 520
Class: Freshwater (E. coli<\\/i>)
Category: 410 - 999 (700/100mL)<\\/html>\",\"Station Number: 523
Class: Freshwater (E. coli<\\/i>)
Category: 410 - 999 (670/100mL)<\\/html>\",\"Station Number: 528
Class: Freshwater (E. coli<\\/i>)
Category: 126 - 409 (400/100mL)<\\/html>\",\"Station Number: 529
Class: Freshwater (E. coli<\\/i>)
Category: 410 - 999 (880/100mL)<\\/html>\",\"Station Number: 533
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (90/100mL)<\\/html>\",\"Station Number: 534
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (60/100mL)<\\/html>\",\"Station Number: 536
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (82/100mL)<\\/html>\",\"Station Number: 541
Class: Freshwater (E. coli<\\/i>)
Category: 410 - 999 (650/100mL)<\\/html>\",\"Station Number: 543
Class: Freshwater (E. coli<\\/i>)
Category: 126 - 409 (200/100mL)<\\/html>\",\"Station Number: 545
Class: Freshwater (E. coli<\\/i>)
Category: 126 - 409 (160/100mL)<\\/html>\",\"Station Number: 547
Class: Freshwater (E. coli<\\/i>)
Category: 126 - 409 (400/100mL)<\\/html>\",\"Station Number: 548
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (28/100mL)<\\/html>\",\"Station Number: 549
Class: Freshwater (E. coli<\\/i>)
Category: > 999 (2100/100mL)<\\/html>\",\"Station Number: 550
Class: Freshwater (E. coli<\\/i>)
Category: > 999 (1800/100mL)<\\/html>\",\"Station Number: 551
Class: Freshwater (E. coli<\\/i>)
Category: 410 - 999 (500/100mL)<\\/html>\",\"Station Number: 552
Class: Freshwater (E. coli<\\/i>)
Category: > 999 (2220/100mL)<\\/html>\",\"Station Number: 553
Class: Freshwater (E. coli<\\/i>)
Category: 410 - 999 (433/100mL)<\\/html>\",\"Station Number: 554
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (4/100mL)<\\/html>\",\"Station Number: 555
Class: Freshwater (E. coli<\\/i>)
Category: > 999 (2733/100mL)<\\/html>\",\"Station Number: 556
Class: Freshwater (E. coli<\\/i>)
Category: 126 - 409 (140/100mL)<\\/html>\",\"Station Number: 557
Class: Freshwater (E. coli<\\/i>)
Category: > 999 (1700/100mL)<\\/html>\",\"Station Number: 558
Class: Freshwater (E. coli<\\/i>)
Category: 126 - 409 (170/100mL)<\\/html>\",\"Station Number: 559
Class: Freshwater (E. coli<\\/i>)
Category: 410 - 999 (500/100mL)<\\/html>\",\"Station Number: 573
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (100/100mL)<\\/html>\",\"Station Number: 574
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (90/100mL)<\\/html>\",\"Station Number: 575
Class: Freshwater (E. coli<\\/i>)
Category: 126 - 409 (240/100mL)<\\/html>\",\"Station Number: 576
Class: Freshwater (E. coli<\\/i>)
Category: 410 - 999 (833/100mL)<\\/html>\",\"Station Number: 604
Class: Freshwater (E. coli<\\/i>)
Category: 126 - 409 (350/100mL)<\\/html>\",\"Station Number: 605
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (76/100mL)<\\/html>\",\"Station Number: 606
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (80/100mL)<\\/html>\",\"Station Number: 607
Class: Freshwater (E. coli<\\/i>)
Category: 126 - 409 (150/100mL)<\\/html>\",\"Station Number: 612
Class: Freshwater (E. coli<\\/i>)
Category: > 999 (1160/100mL)<\\/html>\",\"Station Number: 615
Class: Freshwater (E. coli<\\/i>)
Category: 410 - 999 (600/100mL)<\\/html>\",\"Station Number: 618
Class: Freshwater (E. coli<\\/i>)
Category: 126 - 409 (250/100mL)<\\/html>\",\"Station Number: 623
Class: Freshwater (E. coli<\\/i>)
Category: 410 - 999 (680/100mL)<\\/html>\",\"Station Number: 625
Class: Freshwater (E. coli<\\/i>)
Category: 126 - 409 (240/100mL)<\\/html>\",\"Station Number: 626
Class: Freshwater (E. coli<\\/i>)
Category: 126 - 409 (380/100mL)<\\/html>\",\"Station Number: 627
Class: Freshwater (E. coli<\\/i>)
Category: 410 - 999 (560/100mL)<\\/html>\",\"Station Number: 1510
Class: Marine (Enterococcus<\\/i>)
Category: > 999 (1200/100mL)<\\/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\":[27.53248,28.16544],\"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') 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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: 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>)
Category: < 126 (30/100mL)<\\/html>\",\"Station Number: 139
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, 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\" 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, 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":"Colors indicate target goal met, trending (red), target goal met, trending (yellow), target goal met, trending (light green), target goal met, trending (green). Numbers cell show proportion target goal met year data available. 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,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\":[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\":[-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\":[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: 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show_ratab","text":"epcdata data frame epc data returned read_importwq yrsel numeric indicating chosen year bay_segment chr string bay segment, one \"OTB\", \"HB\", \"MTB\", \"LTB\", \"RALTB\" partialyr logical indicating incomplete annual data recent year 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) years threshold far, necessary NMC Actions 2-5 NMC Action 2: Determine observed chlorophyll-exceedences 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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;}.cl-8b3cf284{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)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 yearsNoAll 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/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: Transformation introduced infinite values in continuous y-axis #> Warning: Transformation introduced infinite values in continuous x-axis"},{"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, 2022), 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, 2022), 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],\"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],\"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
\"],\"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\":[1974.52,2022.48],\"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\":[1974.52,2022.48],\"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\":[1974.52,2022.48],\"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],\"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],\"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,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,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],\"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: 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
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yval: 1.1896016
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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
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yval: 0.7686231
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yval: 0.7783039
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yval: 0.7871073
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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\":[5.6958409090909088,18.584007575757578],\"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 = 2022) #> 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 = 2022) show_tdlcrk(dat) 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MiniMap\",\"showText\":\"Show MiniMap\"},[]]},{\"method\":\"addLegend\",\"args\":[{\"colors\":[\"#ADD8E6\",\"#2DC938\",\"#E9C318\",\"#EE7600\",\"#FF4040\"],\"labels\":[\"No Data\",\"Monitor\",\"Caution\",\"Investigate\",\"Prioritize\"],\"na_color\":null,\"na_label\":\"NA\",\"opacity\":1,\"position\":\"topright\",\"type\":\"factor\",\"title\":\"Creek scores\",\"extra\":null,\"layerId\":null,\"className\":\"info 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score: 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: Caution\",\"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: Caution\",\"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: Monitor\",\"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: Monitor\",\"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: Investigate\",\"WBID: 1725, JEI: HC31, Name: NA, Creek score: Monitor\",\"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: Monitor\",\"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: Monitor\",\"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: No Data\",\"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: Monitor\",\"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: Monitor\",\"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: No Data\",\"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: Caution\",\"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: Prioritize\",\"WBID: 3258D4, JEI: LC48, Name: Estero River/Halfway Creek, Creek score: No Data\",\"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: Monitor\",\"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: No Data\",\"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: Investigate\",\"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: Investigate\",\"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: Caution\",\"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: Monitor\",\"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: Investigate\",\"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 = 2022, 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 = 2022) 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 = 2022, 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 = 2022) 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 = 2022) 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 = 2022, 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, 2022), 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 = c(\"Halodule\", \"Syringodium\", \"Thalassia\", \"Halophila\", \"Ruppia\", \"Caulerpa\"), yrrng = c(1998, 2023), varplo = c(\"Abundance\", \"Blade Length\", \"Short Shoot Density\"), base_size = 12, facet = FALSE, ncol = NULL, plotly = FALSE, width = NULL, height = NULL, sppcol = NULL )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transect.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot results for a seagrass transect by time and location — show_transect","text":"transect data frame returned read_transect site chr string indicating site results plot species chr string indicating one many species plot yrrng numeric indicating year ranges evaluate varplo chr string indicating variable plot base_size numeric indicating text scaling size plot facet logical indicating plots separated facets species ncol numeric indicating number columns facet = TRUE plotly logical plot created using plotly 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_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. 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'), varplo = 'Abundance') # multiple species, multiple plots show_transect(transect, site = 'S3T10', species = c('Halodule', 'Syringodium', 'Thalassia', 'Halophila', 'Ruppia', 'Caulerpa'), 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\"), 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\" 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","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\"), 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.","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 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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, 2022), 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 64 — tidalcreeks","title":"Spatial data object of tidal creeks in Impaired Waters Rule, Run 64 — tidalcreeks","text":"Spatial data object tidal creeks Impaired Waters Rule, Run 64","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 64 — 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 64 — 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 64 — 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 64 — 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 12062023 — transect","title":"Seagrass transect data for Tampa Bay current as of 12062023 — transect","text":"Seagrass transect data Tampa Bay current 12062023","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 12062023 — 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 12062023 — 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 12062023 — 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 county name from organization identifier — util_orgin","title":"Get county name from organization identifier — util_orgin","text":"Get county name organization identifier","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/util_orgin.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get county name from organization identifier — 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 county name from organization identifier — util_orgin","text":"org chr string indicating organization identifier, see read_importwqp valid entries stanm logical indicating character string column name specific county returned","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/util_orgin.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get county name from organization identifier — util_orgin","text":"character string county name correspond organization identifier column name station identfier specific county 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 county name from organization identifier — 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) 2022 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: 74,872 × 18 #> area epchc_station class SampleTime yr mo Latitude Longitude #> #> 1 Hills… 2 3M 2023-05-10 13:48:00 2023 5 27.9 -82.5 #> 2 Hills… 6 3M 2023-05-16 09:32:00 2023 5 27.9 -82.5 #> 3 Hills… 7 3M 2023-05-16 09:41:00 2023 5 27.9 -82.5 #> 4 Hills… 8 3M 2023-05-16 11:50:00 2023 5 27.9 -82.4 #> 5 Middl… 9 2 2023-05-16 11:12:00 2023 5 27.8 -82.4 #> 6 Middl… 11 2 2023-05-16 09:55:00 2023 5 27.8 -82.5 #> 7 Middl… 13 2 2023-05-16 10:07:00 2023 5 27.8 -82.5 #> 8 Middl… 14 2 2023-05-16 10:49:00 2023 5 27.8 -82.5 #> 9 Middl… 16 2 2023-05-23 10:19:00 2023 5 27.7 -82.5 #> 10 Middl… 19 2 2023-05-23 10:36:00 2023 5 27.7 -82.6 #> # ℹ 74,862 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 monitoring data counties 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: 74,872 × 12 #> area epchc_station class yr mo Latitude Longitude ecoli ecocci ind #> #> 1 Hillsb… 2 3M 2023 5 27.9 -82.5 NA 4 Ente… #> 2 Hillsb… 6 3M 2023 5 27.9 -82.5 NA 2 Ente… #> 3 Hillsb… 7 3M 2023 5 27.9 -82.5 NA 2 Ente… #> 4 Hillsb… 8 3M 2023 5 27.9 -82.4 NA 2 Ente… #> 5 Middle… 9 2 2023 5 27.8 -82.4 NA 2 Ente… #> 6 Middle… 11 2 2023 5 27.8 -82.5 NA 2 Ente… #> 7 Middle… 13 2 2023 5 27.8 -82.5 NA 2 Ente… #> 8 Middle… 14 2 2023 5 27.8 -82.5 NA 2 Ente… #> 9 Middle… 16 2 2023 5 27.7 -82.5 NA 2 Ente… #> 10 Middle… 19 2 2023 5 27.7 -82.6 NA 2 Ente… #> # ℹ 74,862 more rows #> # ℹ 2 more variables: cat , col anlz_fibmap(fibdata, yrsel = 2022, mosel = 7) #> # A tibble: 195 × 12 #> area epchc_station class yr mo Latitude Longitude ecoli ecocci ind #> #> 1 Hillsb… 2 3M 2022 7 27.9 -82.5 NA 20 Ente… #> 2 Hillsb… 6 3M 2022 7 27.9 -82.5 NA 2 Ente… #> 3 Hillsb… 7 3M 2022 7 27.9 -82.5 NA 2 Ente… #> 4 Hillsb… 8 3M 2022 7 27.9 -82.4 NA 2 Ente… #> 5 Middle… 9 2 2022 7 27.8 -82.4 NA 2 Ente… #> 6 Middle… 11 2 2022 7 27.8 -82.5 NA 2 Ente… #> 7 Middle… 13 2 2022 7 27.8 -82.5 NA 2 Ente… #> 8 Middle… 14 2 2022 7 27.8 -82.5 NA 2 Ente… #> 9 Middle… 16 2 2022 7 27.7 -82.5 NA 2 Ente… #> 10 Middle… 19 2 2022 7 27.7 -82.6 NA 2 Ente… #> # ℹ 185 more rows #> # ℹ 2 more variables: cat , col anlz_fibmap(fibdata, yrsel = 2022, mosel = 7, areasel = 'Hillsborough River') #> # A tibble: 38 × 12 #> area epchc_station class yr mo Latitude Longitude ecoli ecocci ind #> #> 1 Hillsb… 2 3M 2022 7 27.9 -82.5 NA 20 Ente… #> 2 Hillsb… 105 3M 2022 7 28.0 -82.4 NA 7 Ente… #> 3 Hillsb… 106 1 2022 7 28.1 -82.4 73 80 E. c… #> 4 Lake T… 107 3F 2022 7 28.0 -82.3 240 700 E. c… #> 5 Hillsb… 108 3F 2022 7 28.1 -82.2 60 210 E. c… #> 6 Lake T… 118 3F 2022 7 28.1 -82.3 7 10 E. c… #> 7 Hillsb… 120 3F 2022 7 28.1 -82.4 220 300 E. c… #> 8 Lake T… 135 3F 2022 7 28.1 -82.3 7 7 E. c… #> 9 Hillsb… 137 3M 2022 7 28.0 -82.5 NA 40 Ente… #> 10 Hillsb… 143 3F 2022 7 28.1 -82.1 327 1240 E. c… #> # ℹ 28 more rows #> # ℹ 2 more variables: cat , col anlz_fibmatrix(fibdata) #> # A tibble: 8,541 × 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 8,531 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 = 2022, mosel = 7, areasel = NULL) show_fibmap(fibdata, yrsel = 2022, mosel = 7, areasel = 'Hillsborough River') show_fibmap(fibdata, yrsel = 2021, mosel = 6, 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. Finally, text showing proportion target goal met year can suppressed using text = NULL. size text can changed entering numeric value (default text = 2.5). 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)"},{"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: 23,848 × 8 #> epchc_station Date name units count yrqrt yr mo #> #> 1 11 1975-07-23 Cyanobacteria /0.1mL 0 1975-07-01 1975 Jul #> 2 11 1976-01-07 Cyanobacteria /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 other /0.1mL 1 1977-04-01 1977 Apr #> 5 11 1977-04-20 Tripos hircus /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 23,838 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 monitoring data counties around Tampa Bay watershed. function retrieves nutrient, chlorophyll, secchi, temperature, salinity, turbidity data available estuarine stations monitored county 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) 2022 target 2022 target OTB 7.1 8.5 0.79 0.83 HB 8.9 13.2 0.92 1.58 MTB 5.0 7.4 0.55 0.83 LTB 3.6 4.6 0.66 0.63 default caption can also included setting caption = TRUE. Water quality outcomes 2022. Segment Chl-(ug/L) Light Penetration (m-1) 2022 target 2022 target OTB 7.1 8.5 0.79 0.83 HB 8.9 13.2 0.92 1.58 MTB 5.0 7.4 0.55 0.83 LTB 3.6 4.6 0.66 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) 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/ 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 = 2022) show_annualassess(epcdata, yrsel = 2022, caption = TRUE) show_ratab(epcdata, yrsel = 2022, 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., whereas attached drift algae species aggregated. 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. 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 \"CYAN: Lyngbya/Dapis\" 41 0 0 #> 3 1997-10-11 S2T3 \"Caulerpa\" 41 0 0 #> 4 1997-10-11 S2T3 \"DA\" 41 0 0 #> 5 1997-10-11 S2T3 \"DB: Dictyota\\r\\n\" 41 0 0 #> 6 1997-10-11 S2T3 \"DB: Drift Brown\\r\\n\" 41 0 0 #> 7 1997-10-11 S2T3 \"DG: Chaetomorpha\\r\\n\" 41 0 0 #> 8 1997-10-11 S2T3 \"DG: Drift Green\" 41 0 0 #> 9 1997-10-11 S2T3 \"DG: Ulva\" 41 0 0 #> 10 1997-10-11 S2T3 \"DG: Ulva fasciata\\r\\n\" 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: 182 × 3 #> yr Savspecies foest #> #> 1 1998 Caulerpa 0.0166 #> 2 1998 Halodule 0.361 #> 3 1998 Halophila 0 #> 4 1998 Ruppia 0.0112 #> 5 1998 Syringodium 0.0451 #> 6 1998 Thalassia 0.254 #> 7 1998 total 0.580 #> 8 1999 Caulerpa 0.0277 #> 9 1999 Halodule 0.306 #> 10 1999 Halophila 0.00118 #> # ℹ 172 more rows transectavespp <- anlz_transectavespp(transectocc, by_seg = TRUE) transectavespp #> # A tibble: 1,040 × 5 #> yr bay_segment Savspecies foest nsites #> #> 1 1998 BCB Caulerpa 0 96 #> 2 1998 BCB Halodule 0.613 96 #> 3 1998 BCB Halophila 0 96 #> 4 1998 BCB No Cover 0.190 96 #> 5 1998 BCB Ruppia 0 96 #> 6 1998 BCB Syringodium 0 96 #> 7 1998 BCB Thalassia 0.304 96 #> 8 1998 BCB total 0.810 96 #> 9 1998 HB Caulerpa 0 285 #> 10 1998 HB Halodule 0.147 285 #> # ℹ 1,030 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 = 2022, 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: 149,066 × 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 149,056 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 NA 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 2013 2.725391 9.607368 NA 6.819091 73.50770 #> 2 2 Rock Creek CC01 2052 3M 2014 2.380249 14.694735 NA 3.308289 60.31523 #> 3 2 Rock Creek CC01 2052 3M 2015 2.647817 21.911128 NA 4.034172 55.41609 #> 4 2 Rock Creek CC01 2052 3M 2016 2.265462 19.130797 NA 3.980251 55.96637 #> 5 2 Rock Creek CC01 2052 3M 2017 2.851726 15.395763 NA 4.157777 60.18017 #> 6 2 Rock Creek CC01 2052 3M 2018 1.934899 11.655004 NA 4.219790 63.32630 #> NO23 ORGN SALIN TKN TN TP TSS TURB #> 1 0.009781633 NA 30.90561 0.6510575 0.7108146 0.06842811 NA 1.698004 #> 2 0.007575792 NA 26.63714 0.6161702 0.6228782 0.06938150 NA 2.044623 #> 3 0.009361504 NA 19.10494 0.6465161 0.5678241 0.07602770 NA 1.814818 #> 4 0.008532522 NA 25.84531 0.5813818 0.5408161 0.08330509 NA 2.082253 #> 5 0.007447260 NA 24.86909 0.6255197 0.6326848 0.07566682 NA 1.802161 #> 6 0.006994714 NA 31.32419 0.5668727 0.5734574 0.07432007 NA 2.454007 #> chla_tn_ratio tn_tp_ratio chla_tsi tn_tsi tn2_tsi tp_tsi tp2_tsi #> 1 3.834180 10.387756 31.23761 49.24140 52.26414 60.19958 75.92850 #> 2 3.821371 8.977584 29.28775 46.62660 49.42526 60.45694 76.25504 #> 3 4.663093 7.468648 30.82179 44.79432 47.43600 62.15842 78.41391 #> 4 4.188970 6.491994 28.57601 43.82942 46.38844 63.85868 80.57123 #> 5 4.507341 8.361456 31.89011 46.93590 49.76107 62.06992 78.30162 #> 6 3.374095 7.716050 26.30480 44.98978 47.64821 61.73589 77.87779 #> nut_tsi tsi no23_source no23_tidal no23_ratio do_bnml do_prop #> 1 54.72049 42.97905 NA NA NA 0 0 #> 2 49.42526 39.35651 NA NA NA 0 1 #> 3 47.43600 39.12890 NA NA NA 0 1 #> 4 46.38844 37.48223 NA NA NA 0 1 #> 5 49.76107 40.82559 NA NA NA 0 0 #> 6 47.64821 36.97650 NA NA NA 0 1 cntdat <- anlz_tdlcrkindic(tidalcreeks, iwrraw, yr = 2022, 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 = 2022) 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: 74,872 × 12 #> area epchc_station class yr mo Latitude Longitude ecoli ecocci ind #> #> 1 Hillsb… 2 3M 2023 5 27.9 -82.5 NA 4 Ente… #> 2 Hillsb… 6 3M 2023 5 27.9 -82.5 NA 2 Ente… #> 3 Hillsb… 7 3M 2023 5 27.9 -82.5 NA 2 Ente… #> 4 Hillsb… 8 3M 2023 5 27.9 -82.4 NA 2 Ente… #> 5 Middle… 9 2 2023 5 27.8 -82.4 NA 2 Ente… #> 6 Middle… 11 2 2023 5 27.8 -82.5 NA 2 Ente… #> 7 Middle… 13 2 2023 5 27.8 -82.5 NA 2 Ente… #> 8 Middle… 14 2 2023 5 27.8 -82.5 NA 2 Ente… #> 9 Middle… 16 2 2023 5 27.7 -82.5 NA 2 Ente… #> 10 Middle… 19 2 2023 5 27.7 -82.6 NA 2 Ente… #> # ℹ 74,862 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: 8,541 × 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 8,531 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. 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 = 2022)"},{"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 = 2022) #> wbid class JEI year date masterCode result rCode #> 1 2052 3M CC01 2013 2013-02-04 CHLAC -0.0100503359 I #> 2 2052 3M CC01 2013 2013-02-04 COLOR 0.9162907319 U #> 3 2052 3M CC01 2013 2013-02-04 DOSAT 3.8066624898 + #> 4 2052 3M CC01 2013 2013-02-04 NO23 -4.4228486292 #> 5 2052 3M CC01 2013 2013-02-04 SALIN 3.5085559000 #> 6 2052 3M CC01 2013 2013-02-04 TKN -0.6161861394 #> 7 2052 3M CC01 2013 2013-02-04 TN -0.5942072327 + #> 8 2052 3M CC01 2013 2013-02-04 TP -3.0365542681 #> 9 2052 3M CC01 2013 2013-02-04 TURB 0.1823215568 #> 10 2052 3M CC01 2013 2013-03-04 CHLAC -0.0100503359 I #> 11 2052 3M CC01 2013 2013-03-04 COLOR 0.9162907319 I #> 12 2052 3M CC01 2013 2013-03-04 NO23 -4.0745419349 #> 13 2052 3M CC01 2013 2013-03-04 SALIN 3.6054978452 #> 14 2052 3M CC01 2013 2013-03-04 TKN -0.1508228897 #> 15 2052 3M CC01 2013 2013-03-04 TN -0.1312482866 + #> 16 2052 3M CC01 2013 2013-03-04 TP -2.7488721956 #> 17 2052 3M CC01 2013 2013-03-04 TURB 0.0000000000 #> 18 2052 3M CC01 2013 2013-06-03 CHLAC 0.3364722366 I #> 19 2052 3M CC01 2013 2013-06-03 COLOR 1.3083328197 I #> 20 2052 3M CC01 2013 2013-06-03 NO23 -5.2983173665 I #> 21 2052 3M CC01 2013 2013-06-03 SALIN 3.5779478934 #> 22 2052 3M CC01 2013 2013-06-03 TKN -0.7550225843 #> 23 2052 3M CC01 2013 2013-06-03 TN -0.7465479573 + #> 24 2052 3M CC01 2013 2013-06-03 TP -2.9187712324 #> 25 2052 3M CC01 2013 2013-06-03 TURB 0.4700036292 #> 26 2052 3M CC01 2013 2013-08-05 CHLAC 2.6390573296 #> 27 2052 3M CC01 2013 2013-08-05 COLOR 4.0073331852 #> 28 2052 3M CC01 2013 2013-08-05 NO23 -5.1159958098 I #> 29 2052 3M CC01 2013 2013-08-05 TN 0.0989399479 + #> 30 2052 3M CC01 2013 2013-08-05 TURB 0.8329091229 A #> 31 2052 3M CC01 2013 2013-09-09 CHLAC 2.1400661635 #> 32 2052 3M CC01 2013 2013-09-09 COLOR 4.5951198501 #> 33 2052 3M CC01 2013 2013-09-09 DO 2.0149030205 #> 34 2052 3M CC01 2013 2013-09-09 DOSAT 4.6849051540 + #> 35 2052 3M CC01 2013 2013-09-09 NO23 -4.2686979494 #> 36 2052 3M CC01 2013 2013-09-09 SALIN 2.9907197317 #> 37 2052 3M CC01 2013 2013-09-09 TKN 0.0953101798 #> 38 2052 3M CC01 2013 2013-09-09 TN 0.1079571415 + #> 39 2052 3M CC01 2013 2013-09-09 TP -2.2072749132 #> 40 2052 3M CC01 2013 2013-09-09 TURB 0.8754687374 #> 41 2052 3M CC01 2013 2013-11-04 CHLAC 1.2809338455 #> 42 2052 3M CC01 2013 2013-11-04 COLOR 3.1780538303 #> 43 2052 3M CC01 2013 2013-11-04 NO23 -4.6051701860 #> 44 2052 3M CC01 2013 2013-11-04 TKN -0.4942963218 #> 45 2052 3M CC01 2013 2013-11-04 TN -0.4780358009 + #> 46 2052 3M CC01 2013 2013-11-04 TP -2.3330443005 #> 47 2052 3M CC01 2013 2013-11-04 TURB 0.8754687374 #> 48 2052 3M CC01 2013 2013-12-02 CHLAC 0.6418538862 #> 49 2052 3M CC01 2013 2013-12-02 COLOR 0.9162907319 U #> 50 2052 3M CC01 2013 2013-12-02 DO 1.8245492921 #> 51 2052 3M CC01 2013 2013-12-02 DOSAT 4.4006030202 + #> 52 2052 3M CC01 2013 2013-12-02 NO23 -4.6051701860 I #> 53 2052 3M CC01 2013 2013-12-02 SALIN 3.4719664526 #> 54 2052 3M CC01 2013 2013-12-02 TKN -0.6539264674 #> 55 2052 3M CC01 2013 2013-12-02 TN -0.6462635947 + #> 56 2052 3M CC01 2013 2013-12-02 TP -2.8473122684 #> 57 2052 3M CC01 2013 2013-12-02 TURB 0.4700036292 #> 58 2052 3M CC01 2014 2014-03-03 CHLAC 0.5877866649 #> 59 2052 3M CC01 2014 2014-03-03 COLOR 0.9162907319 U #> 60 2052 3M CC01 2014 2014-03-03 DOSAT 4.1835756960 + #> 61 2052 3M CC01 2014 2014-03-03 NO23 -5.5214609179 U #> 62 2052 3M CC01 2014 2014-03-03 SALIN 3.5292973843 #> 63 2052 3M CC01 2014 2014-03-03 TKN -0.6733445533 #> 64 2052 3M CC01 2014 2014-03-03 TN -0.6694306539 + #> 65 2052 3M CC01 2014 2014-03-03 TP -2.7968814148 #> 66 2052 3M CC01 2014 2014-03-03 TURB 1.2527629685 #> 67 2052 3M CC01 2014 2014-04-07 CHLAC 0.2623642645 I #> 68 2052 3M CC01 2014 2014-04-07 COLOR 0.9162907319 U #> 69 2052 3M CC01 2014 2014-04-07 DO 1.3862943611 #> 70 2052 3M CC01 2014 2014-04-07 DOSAT 4.0656020934 + #> 71 2052 3M CC01 2014 2014-04-07 NO23 -5.2983173665 I #> 72 2052 3M CC01 2014 2014-04-07 SALIN 3.5582011305 #> 73 2052 3M CC01 2014 2014-04-07 TKN -0.6733445533 #> 74 2052 3M CC01 2014 2014-04-07 TN -0.6655320135 + #> 75 2052 3M CC01 2014 2014-04-07 TP -2.6882475738 #> 76 2052 3M CC01 2014 2014-04-07 TURB 0.7884573604 #> 77 2052 3M CC01 2014 2014-05-05 CHLAC 0.8754687374 #> 78 2052 3M CC01 2014 2014-05-05 COLOR 3.4011973817 #> 79 2052 3M CC01 2014 2014-05-05 DO 1.5040773968 #> 80 2052 3M CC01 2014 2014-05-05 DOSAT 4.1399550735 + #> 81 2052 3M CC01 2014 2014-05-05 NO23 -4.7105307016 I #> 82 2052 3M CC01 2014 2014-05-05 SALIN 3.3032169733 #> 83 2052 3M CC01 2014 2014-05-05 TKN -0.3856624808 #> 84 2052 3M CC01 2014 2014-05-05 TN -0.3797973614 + #> 85 2052 3M CC01 2014 2014-05-05 TP -2.2072749132 #> 86 2052 3M CC01 2014 2014-05-05 TURB 1.2237754316 A #> 87 2052 3M CC01 2014 2014-06-02 CHLAC 0.8754687374 #> 88 2052 3M CC01 2014 2014-06-02 COLOR 2.7080502011 #> 89 2052 3M CC01 2014 2014-06-02 DO 0.9555114450 #> 90 2052 3M CC01 2014 2014-06-02 DOSAT 3.6635616461 + #> 91 2052 3M CC01 2014 2014-06-02 NO23 -4.9618451299 I #> 92 2052 3M CC01 2014 2014-06-02 SALIN 3.4719664526 #> 93 2052 3M CC01 2014 2014-06-02 TKN -0.6348782724 #> 94 2052 3M CC01 2014 2014-06-02 TN -0.6273594400 + #> 95 2052 3M CC01 2014 2014-06-02 TP -2.6592600369 #> 96 2052 3M CC01 2014 2014-06-02 TURB 0.7419373447 #> 97 2052 3M CC01 2014 2014-07-07 CHLAC 1.0986122887 #> 98 2052 3M CC01 2014 2014-07-07 COLOR 2.2512917986 #> 99 2052 3M CC01 2014 2014-07-07 DO 1.4350845253 #> 100 2052 3M CC01 2014 2014-07-07 NO23 -5.5214609179 U #> 101 2052 3M CC01 2014 2014-07-07 TKN -0.5621189182 #> 102 2052 3M CC01 2014 2014-07-07 TN -0.5586162876 + #> 103 2052 3M CC01 2014 2014-07-07 TP -2.9565115604 #> 104 2052 3M CC01 2014 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#> 287 2052 3M CC01 2016 2016-08-01 TN -0.5074978337 + #> 288 2052 3M CC01 2016 2016-08-01 TP -2.5510464523 #> 289 2052 3M CC01 2016 2016-08-01 TURB 0.2623642645 #> 290 2052 3M CC01 2016 2016-10-03 CHLAC 1.5686159179 #> 291 2052 3M CC01 2016 2016-10-03 COLOR 3.7135720667 #> 292 2052 3M CC01 2016 2016-10-03 DO 1.3083328197 #> 293 2052 3M CC01 2016 2016-10-03 DOSAT 3.9982007017 + #> 294 2052 3M CC01 2016 2016-10-03 NO23 -4.9618451299 I #> 295 2052 3M CC01 2016 2016-10-03 SALIN 3.1223649245 #> 296 2052 3M CC01 2016 2016-10-03 TKN -0.2613647641 #> 297 2052 3M CC01 2016 2016-10-03 TN -0.2561834054 + #> 298 2052 3M CC01 2016 2016-10-03 TP -2.3025850930 #> 299 2052 3M CC01 2016 2016-10-03 TURB 0.9555114450 #> 300 2052 3M CC01 2016 2016-11-07 CHLAC 1.0296194172 #> 301 2052 3M CC01 2016 2016-11-07 COLOR 1.8082887712 #> 302 2052 3M CC01 2016 2016-11-07 DO 1.3862943611 #> 303 2052 3M CC01 2016 2016-11-07 DOSAT 4.0289167569 + #> 304 2052 3M CC01 2016 2016-11-07 NO23 -4.6051701860 #> 305 2052 3M 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1.9021075264 #> 360 2052 3M CC01 2017 2017-07-10 DOSAT 4.6482296754 + #> 361 2052 3M CC01 2017 2017-07-10 NO23 -5.5214609179 I #> 362 2052 3M CC01 2017 2017-07-10 SALIN 3.3214324132 #> 363 2052 3M CC01 2017 2017-07-10 TKN -0.3566749439 #> 364 2052 3M CC01 2017 2017-07-10 TN -0.3509769228 + #> 365 2052 3M CC01 2017 2017-07-10 TP -2.4418471603 #> 366 2052 3M CC01 2017 2017-07-10 TURB 0.4700036292 #> 367 2052 3M CC01 2017 2017-09-05 CHLAC 2.7725887222 #> 368 2052 3M CC01 2017 2017-09-05 COLOR 5.2470240722 #> 369 2052 3M CC01 2017 2017-09-05 DO 1.4350845253 #> 370 2052 3M CC01 2017 2017-09-05 DOSAT 4.0517849478 + #> 371 2052 3M CC01 2017 2017-09-05 NO23 -4.1351665567 #> 372 2052 3M CC01 2017 2017-09-05 SALIN 2.1282317058 #> 373 2052 3M CC01 2017 2017-09-05 TKN 0.1823215568 #> 374 2052 3M CC01 2017 2017-09-05 TN 0.1955667835 + #> 375 2052 3M CC01 2017 2017-09-05 TP -2.1202635362 #> 376 2052 3M CC01 2017 2017-09-05 TURB 0.6418538862 A #> 377 2052 3M CC01 2017 2017-10-02 CHLAC 2.1633230257 #> 378 2052 3M CC01 2017 2017-10-02 COLOR 3.8066624898 #> 379 2052 3M CC01 2017 2017-10-02 NO23 -4.8283137373 I #> 380 2052 3M CC01 2017 2017-10-02 TKN -0.5276327421 #> 381 2052 3M CC01 2017 2017-10-02 TN -0.5208759596 + #> 382 2052 3M CC01 2017 2017-10-02 TP -2.3025850930 #> 383 2052 3M CC01 2017 2017-10-02 TURB 0.6418538862 #> 384 2052 3M CC01 2017 2017-11-06 CHLAC 0.6418538862 #> 385 2052 3M CC01 2017 2017-11-06 COLOR 2.5649493575 #> 386 2052 3M CC01 2017 2017-11-06 DO 1.6863989536 #> 387 2052 3M CC01 2017 2017-11-06 DOSAT 4.3241326563 + #> 388 2052 3M CC01 2017 2017-11-06 NO23 -4.5098600062 #> 389 2052 3M CC01 2017 2017-11-06 SALIN 3.2809112158 #> 390 2052 3M CC01 2017 2017-11-06 TKN -0.5108256238 #> 391 2052 3M CC01 2017 2017-11-06 TN -0.4926583198 + #> 392 2052 3M CC01 2017 2017-11-06 TP -2.5770219387 #> 393 2052 3M CC01 2017 2017-11-06 TURB 0.4700036292 #> 394 2052 3M CC01 2017 2017-12-04 CHLAC 0.4054651081 I #> 395 2052 3M CC01 2017 2017-12-04 COLOR 2.2512917986 #> 396 2052 3M CC01 2017 2017-12-04 DO 1.6486586256 #> 397 2052 3M CC01 2017 2017-12-04 DOSAT 4.2835865619 + #> 398 2052 3M CC01 2017 2017-12-04 NO23 -5.5214609179 I #> 399 2052 3M CC01 2017 2017-12-04 SALIN 3.4843122884 #> 400 2052 3M CC01 2017 2017-12-04 TKN -0.6348782724 #> 401 2052 3M CC01 2017 2017-12-04 TN -0.6273594400 + #> 402 2052 3M CC01 2017 2017-12-04 TP -2.7968814148 #> 403 2052 3M CC01 2017 2017-12-04 TURB 0.7419373447 #> 404 2052 3M CC01 2018 2018-01-02 CHLAC 0.3364722366 I #> 405 2052 3M CC01 2018 2018-01-02 COLOR 2.3025850930 #> 406 2052 3M CC01 2018 2018-01-02 DO 1.8718021769 #> 407 2052 3M CC01 2018 2018-01-02 DOSAT 4.3214801348 + #> 408 2052 3M CC01 2018 2018-01-02 NO23 -4.6051701860 #> 409 2052 3M CC01 2018 2018-01-02 SALIN 3.3214324132 #> 410 2052 3M CC01 2018 2018-01-02 TKN -0.7765287895 #> 411 2052 3M CC01 2018 2018-01-02 TN -0.7550225843 + #> 412 2052 3M CC01 2018 2018-01-02 TP -2.6450754019 #> 413 2052 3M CC01 2018 2018-01-02 TURB 0.7884573604 #> 414 2052 3M CC01 2018 2018-02-05 CHLAC 0.6418538862 #> 415 2052 3M CC01 2018 2018-02-05 COLOR 2.1633230257 #> 416 2052 3M CC01 2018 2018-02-05 DO 1.9600947840 #> 417 2052 3M CC01 2018 2018-02-05 DOSAT 4.5358201079 + #> 418 2052 3M CC01 2018 2018-02-05 NO23 -4.1351665567 #> 419 2052 3M CC01 2018 2018-02-05 SALIN 3.3877743613 #> 420 2052 3M CC01 2018 2018-02-05 TKN -0.6348782724 #> 421 2052 3M CC01 2018 2018-02-05 TN -0.6051363032 + #> 422 2052 3M CC01 2018 2018-02-05 TP -2.4304184645 #> 423 2052 3M CC01 2018 2018-02-05 TURB 1.8405496334 A #> 424 2052 3M CC01 2018 2018-03-05 CHLAC 0.3364722366 I #> 425 2052 3M CC01 2018 2018-03-05 COLOR 1.9459101491 #> 426 2052 3M CC01 2018 2018-03-05 DO 2.0412203289 #> 427 2052 3M CC01 2018 2018-03-05 DOSAT 4.5890408041 + #> 428 2052 3M CC01 2018 2018-03-05 NO23 -5.5214609179 U #> 429 2052 3M CC01 2018 2018-03-05 SALIN 3.4372078192 #> 430 2052 3M CC01 2018 2018-03-05 TKN -0.7985076962 #> 431 2052 3M CC01 2018 2018-03-05 TN -0.7940730991 + #> 432 2052 3M CC01 2018 2018-03-05 TP -2.8134107168 #> 433 2052 3M CC01 2018 2018-03-05 TURB 0.9932517730 #> 434 2052 3M CC01 2018 2018-04-02 CHLAC 0.5306282511 I #> 435 2052 3M CC01 2018 2018-04-02 COLOR 1.0986122887 I #> 436 2052 3M CC01 2018 2018-04-02 DOSAT 4.5538768916 + #> 437 2052 3M CC01 2018 2018-04-02 NO23 -5.5214609179 U #> 438 2052 3M CC01 2018 2018-04-02 SALIN 3.5025498759 #> 439 2052 3M CC01 2018 2018-04-02 TKN -0.7550225843 #> 440 2052 3M CC01 2018 2018-04-02 TN -0.7507762934 + #> 441 2052 3M CC01 2018 2018-04-02 TP -2.8473122684 #> 442 2052 3M CC01 2018 2018-04-02 TURB 1.1314021115 #> 443 2052 3M CC01 2018 2018-05-07 CHLAC 0.5877866649 #> 444 2052 3M CC01 2018 2018-05-07 COLOR 2.1041341543 #> 445 2052 3M CC01 2018 2018-05-07 DO 0.8285518176 #> 446 2052 3M CC01 2018 2018-05-07 DOSAT 3.5292973843 #> 447 2052 3M CC01 2018 2018-05-07 NO23 -5.5214609179 U #> 448 2052 3M CC01 2018 2018-05-07 SALIN 3.5743099994 #> 449 2052 3M CC01 2018 2018-05-07 TKN -0.5621189182 #> 450 2052 3M CC01 2018 2018-05-07 TN -0.5586162876 + #> 451 2052 3M CC01 2018 2018-05-07 TP -2.6310891600 #> 452 2052 3M CC01 2018 2018-05-07 TURB 0.7884573604 #> 453 2052 3M CC01 2018 2018-07-09 CHLAC 0.9932517730 #> 454 2052 3M CC01 2018 2018-07-09 COLOR 4.1743872699 #> 455 2052 3M CC01 2018 2018-07-09 DO 1.1216775616 #> 456 2052 3M CC01 2018 2018-07-09 DOSAT 3.9140210081 #> 457 2052 3M CC01 2018 2018-07-09 NO23 -4.6051701860 #> 458 2052 3M CC01 2018 2018-07-09 SALIN 3.4339872045 #> 459 2052 3M CC01 2018 2018-07-09 TKN -0.2231435513 #> 460 2052 3M CC01 2018 2018-07-09 TN -0.2107210313 + #> 461 2052 3M CC01 2018 2018-07-09 TP -2.3025850930 #> 462 2052 3M CC01 2018 2018-07-09 TURB 0.4054651081 #> 463 2052 3M CC01 2018 2018-08-06 CHLAC 1.1939224685 #> 464 2052 3M CC01 2018 2018-08-06 COLOR 3.4011973817 #> 465 2052 3M CC01 2018 2018-08-06 DO 0.8153648133 #> 466 2052 3M CC01 2018 2018-08-06 DOSAT 3.5945687746 #> 467 2052 3M CC01 2018 2018-08-06 NO23 -4.8283137373 I #> 468 2052 3M CC01 2018 2018-08-06 SALIN 3.4534735262 #> 469 2052 3M CC01 2018 2018-08-06 TKN -0.2231435513 #> 470 2052 3M CC01 2018 2018-08-06 TN -0.2181560098 + #> 471 2052 3M CC01 2018 2018-08-06 TP -2.5257286443 #> 472 2052 3M CC01 2018 2018-08-06 TURB 0.3364722366 #> 473 2052 3M CC01 2019 2019-02-04 CHLAC -0.3285040670 I #> 474 2052 3M CC01 2019 2019-02-04 COLOR 3.4339872045 #> 475 2052 3M CC01 2019 2019-02-04 DO 1.6213664833 #> 476 2052 3M CC01 2019 2019-02-04 DOSAT 4.1431347264 #> 477 2052 3M CC01 2019 2019-02-04 NO23 -3.7297014486 #> 478 2052 3M CC01 2019 2019-02-04 SALIN 3.1805507105 #> 479 2052 3M CC01 2019 2019-02-04 TKN -0.5978370008 #> 480 2052 3M CC01 2019 2019-02-04 TN -0.5551258827 + #> 481 2052 3M CC01 2019 2019-02-04 TP -2.5902671654 #> 482 2052 3M CC01 2019 2019-02-04 TURB 0.5306282511 #> 483 2052 3M CC01 2019 2019-03-04 CHLAC 0.4054651081 I #> 484 2052 3M CC01 2019 2019-03-04 COLOR 2.7080502011 #> 485 2052 3M CC01 2019 2019-03-04 DO 1.2781522025 #> 486 2052 3M CC01 2019 2019-03-04 DOSAT 3.9531649488 #> 487 2052 3M CC01 2019 2019-03-04 NO23 -4.8283137373 I #> 488 2052 3M CC01 2019 2019-03-04 TKN -0.7985076962 #> 489 2052 3M CC01 2019 2019-03-04 TN -0.7896580809 + #> 490 2052 3M CC01 2019 2019-03-04 TP -2.6172958378 #> 491 2052 3M CC01 2019 2019-03-04 TURB 0.4700036292 #> 492 2052 3M CC01 2019 2019-04-01 CHLAC 0.9162907319 #> 493 2052 3M CC01 2019 2019-04-01 COLOR 2.0014800002 #> 494 2052 3M CC01 2019 2019-04-01 DO 1.4883995841 #> 495 2052 3M CC01 2019 2019-04-01 DOSAT 4.1620032107 #> 496 2052 3M CC01 2019 2019-04-01 NO23 -5.5214609179 I #> 497 2052 3M CC01 2019 2019-04-01 SALIN 3.4094961845 #> 498 2052 3M CC01 2019 2019-04-01 TKN -0.9162907319 I #> 499 2052 3M CC01 2019 2019-04-01 TN -1.8078888512 + #> 500 2052 3M CC01 2019 2019-04-01 TP -2.5510464523 #> 501 2052 3M CC01 2019 2019-04-01 TURB 0.2623642645 #> 502 2052 3M CC01 2019 2019-06-03 CHLAC 0.4700036292 I #> 503 2052 3M CC01 2019 2019-06-03 COLOR 1.4586150227 I #> 504 2052 3M CC01 2019 2019-06-03 DO 0.3001045925 #> 505 2052 3M CC01 2019 2019-06-03 DOSAT 3.1267605360 #> 506 2052 3M CC01 2019 2019-06-03 NO23 -5.5214609179 I #> 507 2052 3M CC01 2019 2019-06-03 SALIN 3.5871235452 #> 508 2052 3M CC01 2019 2019-06-03 TKN -0.7133498879 #> 509 2052 3M CC01 2019 2019-06-03 TN -0.7052197618 + #> 510 2052 3M CC01 2019 2019-06-03 TP -3.1700856607 #> 511 2052 3M CC01 2019 2019-06-03 TURB 0.3364722366 #> 512 2052 3M CC01 2019 2019-07-01 CHLAC 0.5306282511 I #> 513 2052 3M CC01 2019 2019-07-01 COLOR 2.2823823857 #> 514 2052 3M CC01 2019 2019-07-01 DO 0.9593502213 #> 515 2052 3M CC01 2019 2019-07-01 DOSAT 3.7208625000 #> 516 2052 3M CC01 2019 2019-07-01 NO23 -5.1159958098 I #> 517 2052 3M CC01 2019 2019-07-01 SALIN 3.5237099561 #> 518 2052 3M CC01 2019 2019-07-01 TKN -0.5978370008 #> 519 2052 3M CC01 2019 2019-07-01 TN -0.5905905922 + #> 520 2052 3M CC01 2019 2019-07-01 TP -2.9957322736 #> 521 2052 3M CC01 2019 2019-07-01 TURB 0.4700036292 #> 522 2052 3M CC01 2019 2019-10-07 CHLAC 1.8562979904 #> 523 2052 3M CC01 2019 2019-10-07 COLOR 1.5260563035 I #> 524 2052 3M CC01 2019 2019-10-07 DO 1.1755733298 #> 525 2052 3M CC01 2019 2019-10-07 DOSAT 3.9120230054 #> 526 2052 3M CC01 2019 2019-10-07 NO23 -5.2983173665 I #> 527 2052 3M CC01 2019 2019-10-07 SALIN 3.5231199856 #> 528 2052 3M CC01 2019 2019-10-07 TKN -0.5108256238 #> 529 2052 3M CC01 2019 2019-10-07 TN -0.5041810810 + #> 530 2052 3M CC01 2019 2019-10-07 TP -2.5510464523 #> 531 2052 3M CC01 2019 2019-10-07 TURB 0.9555114450 #> 532 2052 3M CC01 2019 2019-11-04 CHLAC 1.0986122887 #> 533 2052 3M CC01 2019 2019-11-04 COLOR 1.4816045409 I #> 534 2052 3M CC01 2019 2019-11-04 DO 0.9042181506 #> 535 2052 3M CC01 2019 2019-11-04 DOSAT 3.6136169696 #> 536 2052 3M CC01 2019 2019-11-04 NO23 -4.5098600062 #> 537 2052 3M CC01 2019 2019-11-04 SALIN 3.5010427166 #> 538 2052 3M CC01 2019 2019-11-04 TKN -0.5276327421 #> 539 2052 3M CC01 2019 2019-11-04 TN -0.5091603444 + #> 540 2052 3M CC01 2019 2019-11-04 TP -2.6450754019 #> 541 2052 3M CC01 2019 2019-11-04 TURB 0.7884573604 #> 542 2052 3M CC01 2019 2019-11-04 CHLAC 1.2237754316 #> 543 2052 3M CC01 2019 2019-11-04 COLOR 1.5475625087 I #> 544 2052 3M CC01 2019 2019-11-04 NO23 -4.5098600062 #> 545 2052 3M CC01 2019 2019-11-04 TKN -0.5447271754 #> 546 2052 3M CC01 2019 2019-11-04 TN -0.5259392616 + #> 547 2052 3M CC01 2019 2019-11-04 TP -2.6036901858 #> 548 2052 3M CC01 2019 2019-11-04 TURB 0.9162907319 #> 549 2052 3M CC01 2019 2019-12-02 CHLAC 0.8754687374 I #> 550 2052 3M CC01 2019 2019-12-02 COLOR 0.9162907319 U #> 551 2052 3M CC01 2019 2019-12-02 NO23 -5.1159958098 I #> 552 2052 3M CC01 2019 2019-12-02 TKN -0.7985076962 #> 553 2052 3M CC01 2019 2019-12-02 TN -0.7896580809 + #> 554 2052 3M CC01 2019 2019-12-02 TP -2.9957322736 #> 555 2052 3M CC01 2019 2019-12-02 TURB 1.0296194172 #> 556 2052 3M CC01 2020 2020-01-06 CHLAC 0.1823215568 I #> 557 2052 3M CC01 2020 2020-01-06 COLOR 2.3978952728 #> 558 2052 3M CC01 2020 2020-01-06 DO 1.8196988379 #> 559 2052 3M CC01 2020 2020-01-06 DOSAT 4.3554259529 #> 560 2052 3M CC01 2020 2020-01-06 NO23 -3.9120230054 #> 561 2052 3M CC01 2020 2020-01-06 SALIN 3.4075107437 #> 562 2052 3M CC01 2020 2020-01-06 TKN -0.4942963218 #> 563 2052 3M CC01 2020 2020-01-06 TN -0.4620354596 + #> 564 2052 3M CC01 2020 2020-01-06 TP -2.4889146712 #> 565 2052 3M CC01 2020 2020-01-06 TURB 0.5877866649 #> 566 2052 3M CC01 2020 2020-02-03 CHLAC 0.4700036292 U #> 567 2052 3M CC01 2020 2020-02-03 COLOR 1.6677068206 I #> 568 2052 3M CC01 2020 2020-02-03 DO 1.7647307968 #> 569 2052 3M CC01 2020 2020-02-03 DOSAT 4.2959239356 #> 570 2052 3M CC01 2020 2020-02-03 NO23 -4.5098600062 #> 571 2052 3M CC01 2020 2020-02-03 SALIN 3.4992311219 #> 572 2052 3M CC01 2020 2020-02-03 TKN -0.7985076962 #> 573 2052 3M CC01 2020 2020-02-03 TN -0.7743572360 + #> 574 2052 3M CC01 2020 2020-02-03 TP -2.7488721956 #> 575 2052 3M CC01 2020 2020-02-03 TURB 0.6931471806 #> 576 2052 3M CC01 2020 2020-03-02 CHLAC 0.0953101798 I #> 577 2052 3M CC01 2020 2020-03-02 COLOR 1.5040773968 I #> 578 2052 3M CC01 2020 2020-03-02 DO 1.7191887764 #> 579 2052 3M CC01 2020 2020-03-02 DOSAT 4.3000027992 #> 580 2052 3M CC01 2020 2020-03-02 NO23 -5.5214609179 U #> 581 2052 3M CC01 2020 2020-03-02 SALIN 3.6730041050 #> 582 2052 3M CC01 2020 2020-03-02 TKN -0.9942522733 I #> 583 2052 3M CC01 2020 2020-03-02 TN -1.8201589437 + #> 584 2052 3M CC01 2020 2020-03-02 TP -2.8647040111 #> 585 2052 3M CC01 2020 2020-03-02 TURB 1.0647107370 #> 586 2052 3M CC01 2021 2021-01-04 CHLAC 0.5877866649 I #> 587 2052 3M CC01 2021 2021-01-04 COLOR 1.6094379124 I #> 588 2052 3M CC01 2021 2021-01-04 NO23 -4.1997050779 #> 589 2052 3M CC01 2021 2021-01-04 SALIN 3.4200191359 #> 590 2052 3M CC01 2021 2021-01-04 TKN -0.7339691751 #> 591 2052 3M CC01 2021 2021-01-04 TN -0.7031975164 + #> 592 2052 3M CC01 2021 2021-01-04 TP -2.6882475738 #> 593 2052 3M CC01 2021 2021-01-04 TURB 1.0296194172 A #> 594 2052 3M CC01 2021 2021-04-05 CHLAC 0.4054651081 I #> 595 2052 3M CC01 2021 2021-04-05 COLOR 1.7227665977 I #> 596 2052 3M CC01 2021 2021-04-05 DO 2.0605135318 #> 597 2052 3M CC01 2021 2021-04-05 DOSAT 4.6784206477 #> 598 2052 3M CC01 2021 2021-04-05 NO23 -5.5214609179 U #> 599 2052 3M CC01 2021 2021-04-05 SALIN 3.5579161896 #> 600 2052 3M CC01 2021 2021-04-05 TKN -1.0498221245 I #> 601 2052 3M CC01 2021 2021-04-05 TN -1.8201589437 + #> 602 2052 3M CC01 2021 2021-04-05 TP -2.6172958378 #> 603 2052 3M CC01 2021 2021-04-05 TURB 0.7419373447 #> 604 2052 3M CC01 2021 2021-06-07 CHLAC 1.5040773968 #> 605 2052 3M CC01 2021 2021-06-07 COLOR 1.0296194172 I #> 606 2052 3M CC01 2021 2021-06-07 DO 0.6678293726 #> 607 2052 3M CC01 2021 2021-06-07 DOSAT 3.5055573970 #> 608 2052 3M CC01 2021 2021-06-07 NO23 -5.5214609179 U #> 609 2052 3M CC01 2021 2021-06-07 SALIN 3.6301904578 #> 610 2052 3M CC01 2021 2021-06-07 TKN -0.6733445533 #> 611 2052 3M CC01 2021 2021-06-07 TN -0.6694306539 + #> 612 2052 3M CC01 2021 2021-06-07 TP -2.9565115604 #> 613 2052 3M CC01 2021 2021-06-07 TURB 0.5306282511 #> 614 2052 3M CC01 2021 2021-08-02 CHLAC 2.1162555148 #> 615 2052 3M CC01 2021 2021-08-02 COLOR 4.4886363697 #> 616 2052 3M CC01 2021 2021-08-02 DO 0.7929925155 #> 617 2052 3M CC01 2021 2021-08-02 DOSAT 3.5115454388 #> 618 2052 3M CC01 2021 2021-08-02 NO23 -4.9618451299 I #> 619 2052 3M CC01 2021 2021-08-02 SALIN 3.1280754605 #> 620 2052 3M CC01 2021 2021-08-02 TKN -0.0618754037 #> 621 2052 3M CC01 2021 2021-08-02 TN -0.0576291128 + #> 622 2052 3M CC01 2021 2021-08-02 TP -2.2072749132 #> 623 2052 3M CC01 2021 2021-08-02 TURB 0.9932517730 #> 624 2052 3M CC01 2021 2021-09-07 CHLAC 1.5892352051 #> 625 2052 3M CC01 2021 2021-09-07 COLOR 5.0106352941 #> 626 2052 3M CC01 2021 2021-09-07 DO 0.3364722366 #> 627 2052 3M CC01 2021 2021-09-07 DOSAT 2.9652730661 #> 628 2052 3M CC01 2021 2021-09-07 NO23 -4.6051701860 #> 629 2052 3M CC01 2021 2021-09-07 SALIN 2.9391619221 #> 630 2052 3M CC01 2021 2021-09-07 TKN -0.1392620673 #> 631 2052 3M CC01 2021 2021-09-07 TN -0.1278333715 + #> 632 2052 3M CC01 2021 2021-09-07 TP -2.3227878003 #> 633 2052 3M CC01 2021 2021-09-07 TURB 0.4054651081 #> 634 2052 3M CC01 2021 2021-10-04 CHLAC 3.3672958300 #> 635 2052 3M CC01 2021 2021-10-04 COLOR 3.8286413965 #> 636 2052 3M CC01 2021 2021-10-04 DO 0.6626879731 #> 637 2052 3M CC01 2021 2021-10-04 DOSAT 3.3638415951 #> 638 2052 3M CC01 2021 2021-10-04 NO23 -5.5214609179 U #> 639 2052 3M CC01 2021 2021-10-04 SALIN 3.3304171996 #> 640 2052 3M CC01 2021 2021-10-04 TKN -0.2357223335 #> 641 2052 3M CC01 2021 2021-10-04 TN -0.2331938872 + #> 642 2052 3M CC01 2021 2021-10-04 TP -2.3025850930 #> 643 2052 3M CC01 2021 2021-10-04 TURB 0.9932517730 #> 644 2052 3M CC01 2021 2021-11-01 CHLAC 1.1314021115 #> 645 2052 3M CC01 2021 2021-11-01 COLOR 2.7080502011 #> 646 2052 3M CC01 2021 2021-11-01 DO 1.2208299214 #> 647 2052 3M CC01 2021 2021-11-01 DOSAT 3.8329797981 #> 648 2052 3M CC01 2021 2021-11-01 NO23 -3.6888794541 #> 649 2052 3M CC01 2021 2021-11-01 SALIN 3.4604092413 #> 650 2052 3M CC01 2021 2021-11-01 TKN -0.4942963218 #> 651 2052 3M CC01 2021 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2016-02-01 TP -2.3227878003 #> 943 2067 3M CC02 2016 2016-02-01 TURB 0.8754687374 #> 944 2067 3M CC02 2016 2016-03-07 CHLAC 0.8754687374 #> 945 2067 3M CC02 2016 2016-03-07 COLOR 3.2188758249 #> 946 2067 3M CC02 2016 2016-03-07 NO23 -4.1351665567 #> 947 2067 3M CC02 2016 2016-03-07 SALIN 3.3357695763 #> 948 2067 3M CC02 2016 2016-03-07 TKN -0.2357223335 #> 949 2067 3M CC02 2016 2016-03-07 TN -0.2156715365 + #> 950 2067 3M CC02 2016 2016-03-07 TP -2.3025850930 #> 951 2067 3M CC02 2016 2016-03-07 TURB 1.9315214116 #> 952 2067 3M CC02 2016 2016-04-04 CHLAC 0.3364722366 I #> 953 2067 3M CC02 2016 2016-04-04 COLOR 2.6390573296 #> 954 2067 3M CC02 2016 2016-04-04 DO 1.1314021115 #> 955 2067 3M CC02 2016 2016-04-04 DOSAT 3.7400477407 + #> 956 2067 3M CC02 2016 2016-04-04 NO23 -3.9120230054 #> 957 2067 3M CC02 2016 2016-04-04 SALIN 3.3809946743 #> 958 2067 3M CC02 2016 2016-04-04 TKN -0.7133498879 #> 959 2067 3M CC02 2016 2016-04-04 TN -0.6733445533 + #> 960 2067 3M CC02 2016 2016-04-04 TP -2.3434070875 #> 961 2067 3M CC02 2016 2016-04-04 TURB 1.1939224685 A #> 962 2067 3M CC02 2016 2016-05-02 CHLAC 0.0953101798 I #> 963 2067 3M CC02 2016 2016-05-02 COLOR 2.4849066498 #> 964 2067 3M CC02 2016 2016-05-02 DO 0.7419373447 #> 965 2067 3M CC02 2016 2016-05-02 DOSAT 3.4812400893 + #> 966 2067 3M CC02 2016 2016-05-02 NO23 -4.9618451299 I #> 967 2067 3M CC02 2016 2016-05-02 SALIN 3.5582011305 #> 968 2067 3M CC02 2016 2016-05-02 TKN -0.7339691751 #> 969 2067 3M CC02 2016 2016-05-02 TN -0.7256703723 + #> 970 2067 3M CC02 2016 2016-05-02 TP -2.5257286443 #> 971 2067 3M CC02 2016 2016-05-02 TURB 0.9555114450 #> 972 2067 3M CC02 2016 2016-06-06 CHLAC 0.2623642645 I #> 973 2067 3M CC02 2016 2016-06-06 COLOR 3.3672958300 #> 974 2067 3M CC02 2016 2016-06-06 DO 0.7884573604 #> 975 2067 3M CC02 2016 2016-06-06 DOSAT 3.5351453542 + #> 976 2067 3M CC02 2016 2016-06-06 NO23 -4.8283137373 I #> 977 2067 3M CC02 2016 2016-06-06 SALIN 3.4934726578 #> 978 2067 3M CC02 2016 2016-06-06 TKN -0.7339691751 #> 979 2067 3M CC02 2016 2016-06-06 TN -0.7256703723 + #> 980 2067 3M CC02 2016 2016-06-06 TP -1.0788096614 #> 981 2067 3M CC02 2016 2016-06-06 TURB 0.4700036292 #> 982 2067 3M CC02 2016 2016-07-05 CHLAC 1.7047480922 #> 983 2067 3M CC02 2016 2016-07-05 COLOR 2.8332133441 #> 984 2067 3M CC02 2016 2016-07-05 DO 0.0000000000 #> 985 2067 3M CC02 2016 2016-07-05 DOSAT 2.7788192720 + #> 986 2067 3M CC02 2016 2016-07-05 NO23 -4.7105307016 I #> 987 2067 3M CC02 2016 2016-07-05 SALIN 3.5174978374 #> 988 2067 3M CC02 2016 2016-07-05 TKN 0.6418538862 #> 989 2067 3M CC02 2016 2016-07-05 TN 0.6439569364 + #> 990 2067 3M CC02 2016 2016-07-05 TP -1.7147984281 #> 991 2067 3M CC02 2016 2016-07-05 TURB 2.9957322736 #> 992 2067 3M CC02 2016 2016-08-01 CHLAC 0.8754687374 #> 993 2067 3M CC02 2016 2016-08-01 COLOR 2.7080502011 #> 994 2067 3M CC02 2016 2016-08-01 DO 0.4054651081 #> 995 2067 3M CC02 2016 2016-08-01 DOSAT 3.1696855807 + #> 996 2067 3M CC02 2016 2016-08-01 NO23 -4.3428059215 #> 997 2067 3M CC02 2016 2016-08-01 SALIN 3.4688560301 #> 998 2067 3M CC02 2016 2016-08-01 TKN -0.6161861394 #> 999 2067 3M CC02 2016 2016-08-01 TN -0.5923972775 + #> 1000 2067 3M CC02 2016 2016-08-01 TP -2.6310891600 #> 1001 2067 3M CC02 2016 2016-08-01 TURB 0.9932517730 #> 1002 2067 3M CC02 2016 2016-10-03 CHLAC 1.1631508098 #> 1003 2067 3M CC02 2016 2016-10-03 COLOR 4.1271343850 #> 1004 2067 3M CC02 2016 2016-10-03 DO 0.8754687374 #> 1005 2067 3M CC02 2016 2016-10-03 DOSAT 3.5174978374 + #> 1006 2067 3M CC02 2016 2016-10-03 NO23 -4.6051701860 #> 1007 2067 3M CC02 2016 2016-10-03 SALIN 2.7343675094 #> 1008 2067 3M CC02 2016 2016-10-03 TKN -0.1392620673 #> 1009 2067 3M CC02 2016 2016-10-03 TN -0.1278333715 + #> 1010 2067 3M CC02 2016 2016-10-03 TP -2.4304184645 #> 1011 2067 3M CC02 2016 2016-10-03 TURB 0.7419373447 #> 1012 2067 3M CC02 2016 2016-12-05 CHLAC 0.6418538862 I #> 1013 2067 3M CC02 2016 2016-12-05 COLOR 0.9162907319 U #> 1014 2067 3M CC02 2016 2016-12-05 DO 1.3862943611 #> 1015 2067 3M CC02 2016 2016-12-05 DOSAT 4.0289167569 + #> 1016 2067 3M CC02 2016 2016-12-05 NO23 -4.1351665567 #> 1017 2067 3M CC02 2016 2016-12-05 SALIN 3.5438536821 #> 1018 2067 3M CC02 2016 2016-12-05 TKN -0.3424903089 #> 1019 2067 3M CC02 2016 2016-12-05 TN -0.3202052642 + #> 1020 2067 3M CC02 2016 2016-12-05 TP -2.5770219387 #> 1021 2067 3M CC02 2016 2016-12-05 TURB 1.8870696490 A #> 1022 2067 3M CC02 2017 2017-01-03 CHLAC 1.0986122887 #> 1023 2067 3M CC02 2017 2017-01-03 COLOR 1.5686159179 I #> 1024 2067 3M CC02 2017 2017-01-03 DO 1.3083328197 #> 1025 2067 3M CC02 2017 2017-01-03 DOSAT 3.9512437186 + #> 1026 2067 3M CC02 2017 2017-01-03 NO23 -3.9633162998 #> 1027 2067 3M CC02 2017 2017-01-03 SALIN 3.5438536821 #> 1028 2067 3M CC02 2017 2017-01-03 TKN -0.4780358009 #> 1029 2067 3M CC02 2017 2017-01-03 TN -0.4478508246 + #> 1030 2067 3M CC02 2017 2017-01-03 TP -2.3025850930 #> 1031 2067 3M CC02 2017 2017-01-03 TURB 2.3025850930 #> 1032 2067 3M CC02 2017 2017-02-06 CHLAC 0.5306282511 #> 1033 2067 3M CC02 2017 2017-02-06 COLOR 3.3322045102 A #> 1034 2067 3M CC02 2017 2017-02-06 DO 1.0986122887 #> 1035 2067 3M CC02 2017 2017-02-06 DOSAT 3.6988297850 + #> 1036 2067 3M CC02 2017 2017-02-06 NO23 -4.1997050779 #> 1037 2067 3M CC02 2017 2017-02-06 SALIN 3.5234150144 #> 1038 2067 3M CC02 2017 2017-02-06 TKN -0.5108256238 #> 1039 2067 3M CC02 2017 2017-02-06 TN -0.4861330112 + #> 1040 2067 3M CC02 2017 2017-02-06 TP -2.5383074265 #> 1041 2067 3M CC02 2017 2017-02-06 TURB 0.9162907319 #> 1042 2067 3M CC02 2017 2017-03-06 CHLAC 0.2623642645 I #> 1043 2067 3M CC02 2017 2017-03-06 COLOR 2.7080502011 #> 1044 2067 3M CC02 2017 2017-03-06 DO 1.3862943611 #> 1045 2067 3M CC02 2017 2017-03-06 DOSAT 3.9778107460 + #> 1046 2067 3M CC02 2017 2017-03-06 NO23 -4.9618451299 I #> 1047 2067 3M CC02 2017 2017-03-06 SALIN 3.5174978374 #> 1048 2067 3M CC02 2017 2017-03-06 TKN -0.5798184953 #> 1049 2067 3M CC02 2017 2017-03-06 TN -0.5727010275 + #> 1050 2067 3M CC02 2017 2017-03-06 TP -2.6882475738 #> 1051 2067 3M CC02 2017 2017-03-06 TURB 1.3083328197 #> 1052 2067 3M CC02 2017 2017-04-03 CHLAC 0.6931471806 #> 1053 2067 3M CC02 2017 2017-04-03 COLOR 2.3978952728 #> 1054 2067 3M CC02 2017 2017-04-03 DO 1.2809338455 #> 1055 2067 3M CC02 2017 2017-04-03 DOSAT 4.0000338828 + #> 1056 2067 3M CC02 2017 2017-04-03 NO23 -4.9618451299 I #> 1057 2067 3M CC02 2017 2017-04-03 SALIN 3.5835189385 #> 1058 2067 3M CC02 2017 2017-04-03 TKN -0.4155154440 #> 1059 2067 3M CC02 2017 2017-04-03 TN -0.4094731295 + #> 1060 2067 3M CC02 2017 2017-04-03 TP -2.6592600369 #> 1061 2067 3M CC02 2017 2017-04-03 TURB 1.3862943611 #> 1062 2067 3M CC02 2017 2017-05-01 CHLAC 0.7884573604 #> 1063 2067 3M CC02 2017 2017-05-01 COLOR 1.5040773968 I #> 1064 2067 3M CC02 2017 2017-05-01 DO 1.2527629685 #> 1065 2067 3M CC02 2017 2017-05-01 DOSAT 3.9852734672 + #> 1066 2067 3M CC02 2017 2017-05-01 NO23 -5.5214609179 U #> 1067 2067 3M CC02 2017 2017-05-01 SALIN 3.5918177413 #> 1068 2067 3M CC02 2017 2017-05-01 TKN -0.4462871026 #> 1069 2067 3M CC02 2017 2017-05-01 TN -0.4431669753 + #> 1070 2067 3M CC02 2017 2017-05-01 TP -3.1010927892 #> 1071 2067 3M CC02 2017 2017-05-01 TURB 0.8754687374 #> 1072 2067 3M CC02 2017 2017-07-10 CHLAC 1.0296194172 #> 1073 2067 3M CC02 2017 2017-07-10 COLOR 3.1354942159 #> 1074 2067 3M CC02 2017 2017-07-10 DO 1.1314021115 #> 1075 2067 3M CC02 2017 2017-07-10 DOSAT 3.8938590348 + #> 1076 2067 3M CC02 2017 2017-07-10 NO23 -4.4228486292 #> 1077 2067 3M CC02 2017 2017-07-10 SALIN 3.3978584804 #> 1078 2067 3M CC02 2017 2017-07-10 TKN -0.4620354596 #> 1079 2067 3M CC02 2017 2017-07-10 TN -0.4431669753 + #> 1080 2067 3M CC02 2017 2017-07-10 TP -2.7181005370 #> 1081 2067 3M CC02 2017 2017-07-10 TURB 1.4586150227 #> 1082 2067 3M CC02 2017 2017-08-07 CHLAC 1.1631508098 #> 1083 2067 3M CC02 2017 2017-08-07 COLOR 3.8712010109 #> 1084 2067 3M CC02 2017 2017-08-07 DO 0.8754687374 #> 1085 2067 3M CC02 2017 2017-08-07 DOSAT 3.6216707044 + #> 1086 2067 3M CC02 2017 2017-08-07 NO23 -4.5098600062 #> 1087 2067 3M CC02 2017 2017-08-07 SALIN 3.2542429687 #> 1088 2067 3M CC02 2017 2017-08-07 TKN -0.4307829161 #> 1089 2067 3M CC02 2017 2017-08-07 TN -0.4140014391 + #> 1090 2067 3M CC02 2017 2017-08-07 TP -2.5639498571 #> 1091 2067 3M CC02 2017 2017-08-07 TURB 0.5306282511 #> 1092 2067 3M CC02 2017 2017-10-02 CHLAC 1.0986122887 #> 1093 2067 3M CC02 2017 2017-10-02 COLOR 3.6888794541 #> 1094 2067 3M CC02 2017 2017-10-02 NO23 -5.2983173665 I #> 1095 2067 3M CC02 2017 2017-10-02 TKN -0.5276327421 #> 1096 2067 3M CC02 2017 2017-10-02 TN -0.5208759596 + #> 1097 2067 3M CC02 2017 2017-10-02 TP -2.3025850930 #> 1098 2067 3M CC02 2017 2017-10-02 TURB 1.0296194172 #> 1099 2067 3M CC02 2017 2017-11-06 CHLAC 0.9162907319 #> 1100 2067 3M CC02 2017 2017-11-06 COLOR 3.2188758249 #> 1101 2067 3M CC02 2017 2017-11-06 DO 1.2527629685 #> 1102 2067 3M CC02 2017 2017-11-06 DOSAT 3.8938590348 + #> 1103 2067 3M CC02 2017 2017-11-06 NO23 -4.6051701860 #> 1104 2067 3M CC02 2017 2017-11-06 SALIN 3.3499040873 #> 1105 2067 3M CC02 2017 2017-11-06 TKN -0.4620354596 #> 1106 2067 3M CC02 2017 2017-11-06 TN -0.4462871026 + #> 1107 2067 3M CC02 2017 2017-11-06 TP -2.6036901858 #> 1108 2067 3M CC02 2017 2017-11-06 TURB 0.8754687374 A #> 1109 2067 3M CC02 2017 2017-12-04 CHLAC 0.7884573604 #> 1110 2067 3M CC02 2017 2017-12-04 COLOR 2.5649493575 #> 1111 2067 3M CC02 2017 2017-12-04 DO 1.3862943611 #> 1112 2067 3M CC02 2017 2017-12-04 DOSAT 4.0181832013 + #> 1113 2067 3M CC02 2017 2017-12-04 NO23 -4.9618451299 I #> 1114 2067 3M CC02 2017 2017-12-04 SALIN 3.5025498759 #> 1115 2067 3M CC02 2017 2017-12-04 TKN -0.4780358009 #> 1116 2067 3M CC02 2017 2017-12-04 TN -0.4716049106 + #> 1117 2067 3M CC02 2017 2017-12-04 TP -2.6882475738 #> 1118 2067 3M CC02 2017 2017-12-04 TURB 1.3862943611 A #> 1119 2067 3M CC02 2018 2018-01-02 CHLAC 0.9932517730 #> 1120 2067 3M CC02 2018 2018-01-02 COLOR 2.5649493575 #> 1121 2067 3M CC02 2018 2018-01-02 DO 0.7884573604 #> 1122 2067 3M CC02 2018 2018-01-02 DOSAT 3.2580965380 + #> 1123 2067 3M CC02 2018 2018-01-02 NO23 -4.2686979494 #> 1124 2067 3M CC02 2018 2018-01-02 SALIN 3.4688560301 #> 1125 2067 3M CC02 2018 2018-01-02 TKN -0.6348782724 #> 1126 2067 3M CC02 2018 2018-01-02 TN -0.6088060321 + #> 1127 2067 3M CC02 2018 2018-01-02 TP -2.3434070875 #> 1128 2067 3M CC02 2018 2018-01-02 TURB 1.5260563035 #> 1129 2067 3M CC02 2018 2018-02-05 CHLAC 0.0953101798 I #> 1130 2067 3M CC02 2018 2018-02-05 COLOR 2.6390573296 #> 1131 2067 3M CC02 2018 2018-02-05 DO 1.5040773968 #> 1132 2067 3M CC02 2018 2018-02-05 DOSAT 4.0724397268 + #> 1133 2067 3M CC02 2018 2018-02-05 NO23 -4.1351665567 #> 1134 2067 3M CC02 2018 2018-02-05 SALIN 3.3877743613 #> 1135 2067 3M CC02 2018 2018-02-05 TKN -0.7339691751 #> 1136 2067 3M CC02 2018 2018-02-05 TN -0.7011793523 + #> 1137 2067 3M CC02 2018 2018-02-05 TP -2.7030626596 #> 1138 2067 3M CC02 2018 2018-02-05 TURB 1.2809338455 #> 1139 2067 3M CC02 2018 2018-03-05 CHLAC 0.6931471806 #> 1140 2067 3M CC02 2018 2018-03-05 COLOR 2.0014800002 #> 1141 2067 3M CC02 2018 2018-03-05 DO 1.5475625087 #> 1142 2067 3M CC02 2018 2018-03-05 DOSAT 4.1351665567 + #> 1143 2067 3M CC02 2018 2018-03-05 NO23 -5.1159958098 I #> 1144 2067 3M CC02 2018 2018-03-05 SALIN 3.5835189385 #> 1145 2067 3M CC02 2018 2018-03-05 TKN -0.7339691751 #> 1146 2067 3M CC02 2018 2018-03-05 TN -0.7256703723 + #> 1147 2067 3M CC02 2018 2018-03-05 TP -2.7333680091 #> 1148 2067 3M CC02 2018 2018-03-05 TURB 1.5892352051 A #> 1149 2067 3M CC02 2018 2018-04-02 CHLAC 1.3350010667 A #> 1150 2067 3M CC02 2018 2018-04-02 COLOR 1.4816045409 I #> 1151 2067 3M CC02 2018 2018-04-02 DO 1.4109869737 #> 1152 2067 3M CC02 2018 2018-04-02 DOSAT 4.0926765051 + #> 1153 2067 3M CC02 2018 2018-04-02 NO23 -4.5098600062 #> 1154 2067 3M CC02 2018 2018-04-02 SALIN 3.5945687746 #> 1155 2067 3M CC02 2018 2018-04-02 TKN -0.2613647641 #> 1156 2067 3M CC02 2018 2018-04-02 TN -0.2471801291 + #> 1157 2067 3M CC02 2018 2018-04-02 TP -2.1202635362 #> 1158 2067 3M CC02 2018 2018-04-02 TURB 2.3978952728 #> 1159 2067 3M CC02 2018 2018-05-07 CHLAC 0.5306282511 #> 1160 2067 3M CC02 2018 2018-05-07 COLOR 1.8245492921 #> 1161 2067 3M CC02 2018 2018-05-07 DO 1.3609765531 #> 1162 2067 3M CC02 2018 2018-05-07 DOSAT 3.9608131696 #> 1163 2067 3M CC02 2018 2018-05-07 NO23 -5.2983173665 I #> 1164 2067 3M CC02 2018 2018-05-07 SALIN 3.6027767551 #> 1165 2067 3M CC02 2018 2018-05-07 TKN -0.3147107448 #> 1166 2067 3M CC02 2018 2018-05-07 TN -0.3092462504 + #> 1167 2067 3M CC02 2018 2018-05-07 TP -2.7488721956 #> 1168 2067 3M CC02 2018 2018-05-07 TURB 1.3083328197 #> 1169 2067 3M CC02 2018 2018-07-09 CHLAC 1.6094379124 #> 1170 2067 3M CC02 2018 2018-07-09 COLOR 2.7725887222 #> 1171 2067 3M CC02 2018 2018-07-09 DO 1.0818051704 #> 1172 2067 3M CC02 2018 2018-07-09 DOSAT 3.8308129500 #> 1173 2067 3M CC02 2018 2018-07-09 NO23 -5.2983173665 I #> 1174 2067 3M CC02 2018 2018-07-09 SALIN 3.4741380061 #> 1175 2067 3M CC02 2018 2018-07-09 TKN -0.5276327421 #> 1176 2067 3M CC02 2018 2018-07-09 TN -0.5208759596 + #> 1177 2067 3M CC02 2018 2018-07-09 TURB 0.9932517730 #> 1178 2067 3M CC02 2018 2018-08-06 CHLAC 1.8562979904 #> 1179 2067 3M CC02 2018 2018-08-06 COLOR 3.5263605246 A #> 1180 2067 3M CC02 2018 2018-08-06 DO 0.8586616190 #> 1181 2067 3M CC02 2018 2018-08-06 DOSAT 3.6270040504 #> 1182 2067 3M CC02 2018 2018-08-06 NO23 -5.1159958098 I #> 1183 2067 3M CC02 2018 2018-08-06 SALIN 3.4968105459 #> 1184 2067 3M CC02 2018 2018-08-06 TKN -0.2107210313 #> 1185 2067 3M CC02 2018 2018-08-06 TN -0.2057949130 + #> 1186 2067 3M CC02 2018 2018-08-06 TP -2.3968957725 #> 1187 2067 3M CC02 2018 2018-08-06 TURB 1.0296194172 A #> 1188 2067 3M CC02 2019 2019-02-04 CHLAC -0.1984509387 I #> 1189 2067 3M CC02 2019 2019-02-04 COLOR 3.1354942159 #> 1190 2067 3M CC02 2019 2019-02-04 DO 1.3323660191 #> 1191 2067 3M CC02 2019 2019-02-04 DOSAT 3.8999504242 #> 1192 2067 3M CC02 2019 2019-02-04 NO23 -4.1997050779 #> 1193 2067 3M CC02 2019 2019-02-04 SALIN 3.2669037939 #> 1194 2067 3M CC02 2019 2019-02-04 TKN -0.6931471806 #> 1195 2067 3M CC02 2019 2019-02-04 TN -0.6635883783 + #> 1196 2067 3M CC02 2019 2019-02-04 TP -2.7181005370 #> 1197 2067 3M CC02 2019 2019-02-04 TURB 0.9932517730 #> 1198 2067 3M CC02 2019 2019-03-04 CHLAC 0.2623642645 I #> 1199 2067 3M CC02 2019 2019-03-04 COLOR 3.0445224377 #> 1200 2067 3M CC02 2019 2019-03-04 NO23 -5.2983173665 I #> 1201 2067 3M CC02 2019 2019-03-04 SALIN 3.4381719845 #> 1202 2067 3M CC02 2019 2019-03-04 TKN -0.7550225843 #> 1203 2067 3M CC02 2019 2019-03-04 TN -0.7465479573 + #> 1204 2067 3M CC02 2019 2019-03-04 TP -2.7968814148 #> 1205 2067 3M CC02 2019 2019-03-04 TURB 0.5877866649 #> 1206 2067 3M CC02 2019 2019-04-01 CHLAC -0.2107210313 I #> 1207 2067 3M CC02 2019 2019-04-01 COLOR 2.0794415417 #> 1208 2067 3M CC02 2019 2019-04-01 NO23 -5.5214609179 U #> 1209 2067 3M CC02 2019 2019-04-01 TKN -0.6161861394 #> 1210 2067 3M CC02 2019 2019-04-01 TN -0.6124892775 + #> 1211 2067 3M CC02 2019 2019-04-01 TP -2.9759296463 #> 1212 2067 3M CC02 2019 2019-04-01 TURB 0.4700036292 #> 1213 2067 3M CC02 2019 2019-05-06 CHLAC 0.5877866649 I #> 1214 2067 3M CC02 2019 2019-05-06 COLOR 2.2617630985 #> 1215 2067 3M CC02 2019 2019-05-06 DO 0.5877866649 #> 1216 2067 3M CC02 2019 2019-05-06 DOSAT 3.3250360207 #> 1217 2067 3M CC02 2019 2019-05-06 NO23 -4.8283137373 I #> 1218 2067 3M CC02 2019 2019-05-06 SALIN 3.5522002552 #> 1219 2067 3M CC02 2019 2019-05-06 TKN -0.5108256238 #> 1220 2067 3M CC02 2019 2019-05-06 TN -0.5041810810 + #> 1221 2067 3M CC02 2019 2019-05-06 TP -2.7030626596 #> 1222 2067 3M CC02 2019 2019-05-06 TURB 1.0647107370 #> 1223 2067 3M CC02 2019 2019-06-03 CHLAC 0.6418538862 I #> 1224 2067 3M CC02 2019 2019-06-03 COLOR 1.3350010667 I #> 1225 2067 3M CC02 2019 2019-06-03 DO 0.4700036292 #> 1226 2067 3M CC02 2019 2019-06-03 DOSAT 3.2771447330 #> 1227 2067 3M CC02 2019 2019-06-03 NO23 -4.3428059215 #> 1228 2067 3M CC02 2019 2019-06-03 SALIN 3.5882300460 #> 1229 2067 3M CC02 2019 2019-06-03 TKN -0.5447271754 #> 1230 2067 3M CC02 2019 2019-06-03 TN -0.5225608800 + #> 1231 2067 3M CC02 2019 2019-06-03 TP -2.6172958378 #> 1232 2067 3M CC02 2019 2019-06-03 TURB 0.6931471806 #> 1233 2067 3M CC02 2019 2019-07-01 CHLAC 0.7419373447 I #> 1234 2067 3M CC02 2019 2019-07-01 COLOR 1.9315214116 #> 1235 2067 3M CC02 2019 2019-07-01 NO23 -4.8283137373 I #> 1236 2067 3M CC02 2019 2019-07-01 SALIN 3.5424075502 #> 1237 2067 3M CC02 2019 2019-07-01 TKN -0.5621189182 #> 1238 2067 3M CC02 2019 2019-07-01 TN -0.5551258827 + #> 1239 2067 3M CC02 2019 2019-07-01 TP -3.1941832123 #> 1240 2067 3M CC02 2019 2019-07-01 TURB 0.8329091229 #> 1241 2067 3M CC02 2019 2019-08-05 CHLAC 0.6418538862 I #> 1242 2067 3M CC02 2019 2019-08-05 COLOR 3.7841896339 A #> 1243 2067 3M CC02 2019 2019-08-05 DO 0.6312717768 #> 1244 2067 3M CC02 2019 2019-08-05 DOSAT 3.3775875160 #> 1245 2067 3M CC02 2019 2019-08-05 NO23 -4.7105307016 I #> 1246 2067 3M CC02 2019 2019-08-05 SALIN 3.3617633124 #> 1247 2067 3M CC02 2019 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#> 1373 2067 3M CC02 2021 2021-03-01 TURB 1.2527629685 #> 1374 2067 3M CC02 2021 2021-04-05 TN -1.8078888512 + #> 1375 2067 3M CC02 2021 2021-04-05 CHLAC 0.4054651081 I #> 1376 2067 3M CC02 2021 2021-04-05 COLOR 1.9021075264 #> 1377 2067 3M CC02 2021 2021-04-05 DO 1.1631508098 #> 1378 2067 3M CC02 2021 2021-04-05 DOSAT 3.7977338590 #> 1379 2067 3M CC02 2021 2021-04-05 NO23 -4.9618451299 I #> 1380 2067 3M CC02 2021 2021-04-05 SALIN 3.5325179990 #> 1381 2067 3M CC02 2021 2021-04-05 TKN -0.9416085399 I #> 1382 2067 3M CC02 2021 2021-04-05 TP -2.7030626596 #> 1383 2067 3M CC02 2021 2021-04-05 TURB 1.1939224685 #> 1384 2067 3M CC02 2021 2021-05-03 CHLAC 0.2623642645 I #> 1385 2067 3M CC02 2021 2021-05-03 COLOR 1.9021075264 #> 1386 2067 3M CC02 2021 2021-05-03 DO 0.8064758659 #> 1387 2067 3M CC02 2021 2021-05-03 DOSAT 3.5553480615 #> 1388 2067 3M CC02 2021 2021-05-03 NO23 -5.5214609179 I #> 1389 2067 3M CC02 2021 2021-05-03 SALIN 3.5487549460 #> 1390 2067 3M CC02 2021 2021-05-03 TKN -0.8439700703 #> 1391 2067 3M CC02 2021 2021-05-03 TN -0.8347107449 + #> 1392 2067 3M CC02 2021 2021-05-03 TP -2.8134107168 #> 1393 2067 3M CC02 2021 2021-05-03 TURB 1.2527629685 #> 1394 2067 3M CC02 2021 2021-06-07 CHLAC 0.5306282511 I #> 1395 2067 3M CC02 2021 2021-06-07 COLOR 1.7749523509 I #> 1396 2067 3M CC02 2021 2021-06-07 DO 1.1999647829 #> 1397 2067 3M CC02 2021 2021-06-07 DOSAT 3.9852734672 #> 1398 2067 3M CC02 2021 2021-06-07 NO23 -4.8283137373 I #> 1399 2067 3M CC02 2021 2021-06-07 SALIN 3.6103772260 #> 1400 2067 3M CC02 2021 2021-06-07 TKN -0.6733445533 #> 1401 2067 3M CC02 2021 2021-06-07 TN -0.6655320135 + #> 1402 2067 3M CC02 2021 2021-06-07 TP -3.0159349809 #> 1403 2067 3M CC02 2021 2021-06-07 TURB 0.6418538862 #> 1404 2067 3M CC02 2021 2021-08-02 CHLAC 2.0668627595 #> 1405 2067 3M CC02 2021 2021-08-02 COLOR 4.2626798770 #> 1406 2067 3M CC02 2021 2021-08-02 DO 0.5128236264 #> 1407 2067 3M CC02 2021 2021-08-02 DOSAT 3.2657594108 #> 1408 2067 3M CC02 2021 2021-08-02 NO23 -5.5214609179 U #> 1409 2067 3M CC02 2021 2021-08-02 SALIN 3.2846635654 #> 1410 2067 3M CC02 2021 2021-08-02 TKN -0.1984509387 #> 1411 2067 3M CC02 2021 2021-08-02 TN -0.1960148839 + #> 1412 2067 3M CC02 2021 2021-08-02 TP -2.5639498571 #> 1413 2067 3M CC02 2021 2021-08-02 TURB 0.9555114450 #> 1414 2067 3M CC02 2021 2021-09-07 CHLAC 2.1633230257 #> 1415 2067 3M CC02 2021 2021-09-07 COLOR 3.7841896339 #> 1416 2067 3M CC02 2021 2021-09-07 DO 1.6863989536 #> 1417 2067 3M CC02 2021 2021-09-07 DOSAT 4.4236483094 #> 1418 2067 3M CC02 2021 2021-09-07 NO23 -5.2983173665 I #> 1419 2067 3M CC02 2021 2021-09-07 SALIN 3.2771447330 #> 1420 2067 3M CC02 2021 2021-09-07 TKN -0.1863295782 #> 1421 2067 3M CC02 2021 2021-09-07 TN -0.1815218766 + #> 1422 2067 3M CC02 2021 2021-09-07 TP -2.6310891600 #> 1423 2067 3M CC02 2021 2021-09-07 TURB 0.9932517730 #> 1424 2067 3M CC02 2021 2021-10-04 CHLAC 1.8718021769 #> 1425 2067 3M CC02 2021 2021-10-04 COLOR 2.9444389792 #> 1426 2067 3M CC02 2021 2021-10-04 DO 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TP -2.6882475738 #> 1463 2067 3M CC02 2022 2022-01-03 TURB 0.7419373447 #> 1464 2067 3M CC02 2022 2022-02-07 CHLAC 0.2623642645 I #> 1465 2067 3M CC02 2022 2022-02-07 COLOR 0.9162907319 U #> 1466 2067 3M CC02 2022 2022-02-07 DO 1.4996230464 #> 1467 2067 3M CC02 2022 2022-02-07 DOSAT 4.0826093060 #> 1468 2067 3M CC02 2022 2022-02-07 NO23 -4.5098600062 #> 1469 2067 3M CC02 2022 2022-02-07 SALIN 3.5421180727 #> 1470 2067 3M CC02 2022 2022-02-07 TKN -0.7985076962 #> 1471 2067 3M CC02 2022 2022-02-07 TN -0.7743572360 + #> 1472 2067 3M CC02 2022 2022-02-07 TP -2.8134107168 #> 1473 2067 3M CC02 2022 2022-02-07 TURB 0.5877866649 #> 1474 2067 3M CC02 2022 2022-03-07 CHLAC 0.4054651081 I #> 1475 2067 3M CC02 2022 2022-03-07 COLOR 0.9162907319 U #> 1476 2067 3M CC02 2022 2022-03-07 DO 1.4206957878 #> 1477 2067 3M CC02 2022 2022-03-07 DOSAT 4.1059436981 #> 1478 2067 3M CC02 2022 2022-03-07 NO23 -5.5214609179 U #> 1479 2067 3M CC02 2022 2022-03-07 SALIN 3.5412491371 #> 1480 2067 3M CC02 2022 2022-03-07 TKN -0.9162907319 I #> 1481 2067 3M CC02 2022 2022-03-07 TN -1.8201589437 + #> 1482 2067 3M CC02 2022 2022-03-07 TP -2.9004220937 #> 1483 2067 3M CC02 2022 2022-03-07 TURB 0.9162907319 #> 1484 2067 3M CC02 2022 2022-04-04 CHLAC 0.5877866649 I #> 1485 2067 3M CC02 2022 2022-04-04 COLOR 0.9162907319 U #> 1486 2067 3M CC02 2022 2022-04-04 DO 1.9430489168 #> 1487 2067 3M CC02 2022 2022-04-04 DOSAT 4.6131383556 #> 1488 2067 3M CC02 2022 2022-04-04 NO23 -4.7105307016 I #> 1489 2067 3M CC02 2022 2022-04-04 SALIN 3.5599090728 #> 1490 2067 3M CC02 2022 2022-04-04 TKN -1.2729656758 I #> 1491 2067 3M CC02 2022 2022-04-04 TN -1.8078888512 + #> 1492 2067 3M CC02 2022 2022-04-04 TP -2.7488721956 #> 1493 2067 3M CC02 2022 2022-04-04 TURB 1.0296194172 A #> 1494 2067 3M CC02 2022 2022-05-02 CHLAC 0.1823215568 I #> 1495 2067 3M CC02 2022 2022-05-02 COLOR 0.9162907319 U #> 1496 2067 3M CC02 2022 2022-05-02 DO 1.3244189574 #> 1497 2067 3M CC02 2022 2022-05-02 DOSAT 4.0430512678 #> 1498 2067 3M 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#> 1785 2068 3M CC03 2015 2015-03-02 DO 0.9932517730 #> 1786 2068 3M CC03 2015 2015-03-02 DOSAT 3.5862928653 + #> 1787 2068 3M CC03 2015 2015-03-02 NO23 -4.5098600062 #> 1788 2068 3M CC03 2015 2015-03-02 SALIN 3.1311369106 #> 1789 2068 3M CC03 2015 2015-03-02 TKN -0.4780358009 #> 1790 2068 3M CC03 2015 2015-03-02 TN -0.4604494164 + #> 1791 2068 3M CC03 2015 2015-03-02 TP -2.8824035882 #> 1792 2068 3M CC03 2015 2015-03-02 TURB 0.3364722366 #> 1793 2068 3M CC03 2015 2015-04-06 CHLAC 0.8754687374 #> 1794 2068 3M CC03 2015 2015-04-06 COLOR 3.0910424534 #> 1795 2068 3M CC03 2015 2015-04-06 DO -0.1053605157 #> 1796 2068 3M CC03 2015 2015-04-06 DOSAT 2.5494451709 + #> 1797 2068 3M CC03 2015 2015-04-06 NO23 -5.5214609179 U #> 1798 2068 3M CC03 2015 2015-04-06 SALIN 3.4011973817 #> 1799 2068 3M CC03 2015 2015-04-06 TKN -0.3566749439 #> 1800 2068 3M CC03 2015 2015-04-06 TN -0.3538218750 + #> 1801 2068 3M CC03 2015 2015-04-06 TP -3.2188758249 #> 1802 2068 3M CC03 2015 2015-04-06 TURB 0.4700036292 #> 1803 2068 3M CC03 2015 2015-05-04 CHLAC 0.9932517730 #> 1804 2068 3M CC03 2015 2015-05-04 COLOR 3.2188758249 #> 1805 2068 3M CC03 2015 2015-05-04 DO 0.1823215568 #> 1806 2068 3M CC03 2015 2015-05-04 DOSAT 2.8622008809 + #> 1807 2068 3M CC03 2015 2015-05-04 NO23 -4.8283137373 I #> 1808 2068 3M CC03 2015 2015-05-04 SALIN 3.4904285154 #> 1809 2068 3M CC03 2015 2015-05-04 TKN -0.3856624808 #> 1810 2068 3M CC03 2015 2015-05-04 TN -0.3797973614 + #> 1811 2068 3M CC03 2015 2015-05-04 TP -3.2968373663 #> 1812 2068 3M CC03 2015 2015-05-04 TURB 0.6931471806 #> 1813 2068 3M CC03 2015 2015-06-01 CHLAC 1.7749523509 #> 1814 2068 3M CC03 2015 2015-06-01 COLOR 3.3322045102 #> 1815 2068 3M CC03 2015 2015-06-01 DO -0.6931471806 #> 1816 2068 3M CC03 2015 2015-06-01 DOSAT 2.0149030205 + #> 1817 2068 3M CC03 2015 2015-06-01 NO23 -5.1159958098 I #> 1818 2068 3M CC03 2015 2015-06-01 SALIN 3.3945083935 #> 1819 2068 3M CC03 2015 2015-06-01 TKN -0.1625189295 #> 1820 2068 3M CC03 2015 2015-06-01 TN -0.1578240852 + #> 1821 2068 3M CC03 2015 2015-06-01 TP -2.9759296463 #> 1822 2068 3M CC03 2015 2015-06-01 TURB 0.9555114450 #> 1823 2068 3M CC03 2015 2015-08-03 CHLAC 3.1354942159 #> 1824 2068 3M CC03 2015 2015-08-03 COLOR 4.1108738642 #> 1825 2068 3M CC03 2015 2015-08-03 DO -0.6931471806 #> 1826 2068 3M CC03 2015 2015-08-03 DOSAT 1.9021075264 + #> 1827 2068 3M CC03 2015 2015-08-03 NO23 -4.6051701860 I #> 1828 2068 3M CC03 2015 2015-08-03 SALIN 2.3887627892 #> 1829 2068 3M CC03 2015 2015-08-03 TKN 0.3364722366 #> 1830 2068 3M CC03 2015 2015-08-03 TN 0.3393253056 + #> 1831 2068 3M CC03 2015 2015-08-03 TP -2.4418471603 #> 1832 2068 3M CC03 2015 2015-08-03 TURB 1.5892352051 #> 1833 2068 3M CC03 2015 2015-09-08 CHLAC 1.7227665977 #> 1834 2068 3M CC03 2015 2015-09-08 COLOR 3.8286413965 #> 1835 2068 3M CC03 2015 2015-09-08 DO 0.0000000000 #> 1836 2068 3M CC03 2015 2015-09-08 DOSAT 2.6602595373 + #> 1837 2068 3M CC03 2015 2015-09-08 NO23 -4.8283137373 I #> 1838 2068 3M CC03 2015 2015-09-08 SALIN 2.9014215941 #> 1839 2068 3M CC03 2015 2015-09-08 TKN -0.2357223335 #> 1840 2068 3M CC03 2015 2015-09-08 TN -0.2306718177 + #> 1841 2068 3M CC03 2015 2015-09-08 TP -3.0159349809 #> 1842 2068 3M CC03 2015 2015-09-08 TURB 0.6931471806 #> 1843 2068 3M CC03 2015 2015-10-05 CHLAC 1.4586150227 #> 1844 2068 3M CC03 2015 2015-10-05 COLOR 3.2958368660 A #> 1845 2068 3M CC03 2015 2015-10-05 DO 0.6418538862 #> 1846 2068 3M CC03 2015 2015-10-05 DOSAT 3.3214324132 + #> 1847 2068 3M CC03 2015 2015-10-05 NO23 -5.5214609179 U #> 1848 2068 3M CC03 2015 2015-10-05 SALIN 3.3741687093 #> 1849 2068 3M CC03 2015 2015-10-05 TKN -0.4307829161 #> 1850 2068 3M CC03 2015 2015-10-05 TN -0.4277107171 + #> 1851 2068 3M CC03 2015 2015-10-05 TP -3.0576076773 #> 1852 2068 3M CC03 2015 2015-10-05 TURB 0.8754687374 #> 1853 2068 3M CC03 2015 2015-12-07 CHLAC 1.3609765531 #> 1854 2068 3M CC03 2015 2015-12-07 COLOR 3.2188758249 #> 1855 2068 3M CC03 2015 2015-12-07 DO 1.1314021115 #> 1856 2068 3M CC03 2015 2015-12-07 DOSAT 3.7447870861 + #> 1857 2068 3M CC03 2015 2015-12-07 NO23 -4.5098600062 #> 1858 2068 3M CC03 2015 2015-12-07 SALIN 3.4144426084 #> 1859 2068 3M CC03 2015 2015-12-07 TKN -0.4462871026 #> 1860 2068 3M CC03 2015 2015-12-07 TN -0.4292456368 + #> 1861 2068 3M CC03 2015 2015-12-07 TP -2.8473122684 #> 1862 2068 3M CC03 2015 2015-12-07 TURB 1.1939224685 #> 1863 2068 3M CC03 2016 2016-01-04 CHLAC 1.3083328197 #> 1864 2068 3M CC03 2016 2016-01-04 COLOR 3.3672958300 #> 1865 2068 3M CC03 2016 2016-01-04 DO 0.0000000000 #> 1866 2068 3M CC03 2016 2016-01-04 DOSAT 2.5176964726 + #> 1867 2068 3M CC03 2016 2016-01-04 NO23 -4.0173835211 #> 1868 2068 3M CC03 2016 2016-01-04 SALIN 3.1904763503 #> 1869 2068 3M CC03 2016 2016-01-04 TKN -0.3566749439 #> 1870 2068 3M CC03 2016 2016-01-04 TN -0.3312857099 + #> 1871 2068 3M CC03 2016 2016-01-04 TP -2.6172958378 #> 1872 2068 3M CC03 2016 2016-01-04 TURB 0.8754687374 #> 1873 2068 3M CC03 2016 2016-02-01 CHLAC 1.0647107370 #> 1874 2068 3M CC03 2016 2016-02-01 COLOR 3.6635616461 #> 1875 2068 3M CC03 2016 2016-02-01 DOSAT 3.7256934272 + #> 1876 2068 3M CC03 2016 2016-02-01 NO23 -2.7030626596 #> 1877 2068 3M CC03 2016 2016-02-01 SALIN 2.7850112422 #> 1878 2068 3M CC03 2016 2016-02-01 TKN -0.2357223335 #> 1879 2068 3M CC03 2016 2016-02-01 TN -0.1543173604 + #> 1880 2068 3M CC03 2016 2016-02-01 TP -2.0402208285 #> 1881 2068 3M CC03 2016 2016-02-01 TURB 0.6418538862 #> 1882 2068 3M CC03 2016 2016-03-07 CHLAC 1.7227665977 #> 1883 2068 3M CC03 2016 2016-03-07 COLOR 3.5835189385 #> 1884 2068 3M CC03 2016 2016-03-07 DO 0.8329091229 #> 1885 2068 3M CC03 2016 2016-03-07 DOSAT 3.2995337279 + #> 1886 2068 3M CC03 2016 2016-03-07 NO23 -4.7105307016 I #> 1887 2068 3M CC03 2016 2016-03-07 SALIN 2.7080502011 #> 1888 2068 3M CC03 2016 2016-03-07 TKN -0.3011050928 #> 1889 2068 3M CC03 2016 2016-03-07 TN -0.2957142441 + #> 1890 2068 3M CC03 2016 2016-03-07 TP -2.3025850930 #> 1891 2068 3M CC03 2016 2016-03-07 TURB 1.1631508098 A #> 1892 2068 3M CC03 2016 2016-04-04 CHLAC 0.9932517730 #> 1893 2068 3M CC03 2016 2016-04-04 COLOR 3.5263605246 #> 1894 2068 3M CC03 2016 2016-04-04 DO 0.9555114450 #> 1895 2068 3M CC03 2016 2016-04-04 DOSAT 3.5263605246 + #> 1896 2068 3M CC03 2016 2016-04-04 NO23 -4.5098600062 #> 1897 2068 3M CC03 2016 2016-04-04 SALIN 3.0007198151 #> 1898 2068 3M CC03 2016 2016-04-04 TKN -0.3566749439 #> 1899 2068 3M CC03 2016 2016-04-04 TN -0.3410828492 + #> 1900 2068 3M CC03 2016 2016-04-04 TP -2.3859667019 #> 1901 2068 3M CC03 2016 2016-04-04 TURB 1.0296194172 #> 1902 2068 3M CC03 2016 2016-05-02 CHLAC 0.3364722366 I #> 1903 2068 3M CC03 2016 2016-05-02 COLOR 3.2580965380 #> 1904 2068 3M CC03 2016 2016-05-02 DO 0.7884573604 #> 1905 2068 3M CC03 2016 2016-05-02 DOSAT 3.5234150144 + #> 1906 2068 3M CC03 2016 2016-05-02 NO23 -5.5214609179 U #> 1907 2068 3M CC03 2016 2016-05-02 SALIN 3.6270040504 #> 1908 2068 3M CC03 2016 2016-05-02 TKN -0.3566749439 #> 1909 2068 3M CC03 2016 2016-05-02 TN -0.3538218750 + #> 1910 2068 3M CC03 2016 2016-05-02 TP -2.5639498571 #> 1911 2068 3M CC03 2016 2016-05-02 TURB 0.0953101798 #> 1912 2068 3M CC03 2017 2017-08-07 CHLAC 2.3978952728 #> 1913 2068 3M CC03 2017 2017-08-07 COLOR 4.2195077052 #> 1914 2068 3M CC03 2017 2017-08-07 DOSAT 2.3513752572 + #> 1915 2068 3M CC03 2017 2017-08-07 NO23 -5.5214609179 U #> 1916 2068 3M CC03 2017 2017-08-07 SALIN 1.4350845253 #> 1917 2068 3M CC03 2017 2017-08-07 TKN 0.5306282511 #> 1918 2068 3M CC03 2017 2017-08-07 TN 0.5318040302 + #> 1919 2068 3M CC03 2017 2017-08-07 TP -2.7030626596 #> 1920 2068 3M CC03 2017 2017-08-07 TURB 0.9162907319 #> 1921 2068 3M CC03 2017 2017-09-05 CHLAC 2.7080502011 #> 1922 2068 3M CC03 2017 2017-09-05 COLOR 5.0106352941 #> 1923 2068 3M CC03 2017 2017-09-05 DO 0.6931471806 #> 1924 2068 3M CC03 2017 2017-09-05 DOSAT 3.2884018875 + #> 1925 2068 3M CC03 2017 2017-09-05 NO23 -4.4228486292 #> 1926 2068 3M CC03 2017 2017-09-05 SALIN 2.2721258855 #> 1927 2068 3M CC03 2017 2017-09-05 TKN 0.1823215568 #> 1928 2068 3M CC03 2017 2017-09-05 TN 0.1922718876 + #> 1929 2068 3M CC03 2017 2017-09-05 TP -1.7719568419 #> 1930 2068 3M CC03 2017 2017-09-05 TURB 1.3350010667 #> 1931 2068 3M CC03 2017 2017-10-02 CHLAC 2.5649493575 #> 1932 2068 3M CC03 2017 2017-10-02 COLOR 4.0943445622 A #> 1933 2068 3M CC03 2017 2017-10-02 NO23 -5.5214609179 U #> 1934 2068 3M CC03 2017 2017-10-02 TKN -0.0725706928 #> 1935 2068 3M CC03 2017 2017-10-02 TN -0.0704224643 + #> 1936 2068 3M CC03 2017 2017-10-02 TP -2.3025850930 #> 1937 2068 3M CC03 2017 2017-10-02 TURB 1.8870696490 #> 1938 2068 3M CC03 2017 2017-11-06 CHLAC 1.1631508098 #> 1939 2068 3M CC03 2017 2017-11-06 COLOR 3.5835189385 #> 1940 2068 3M CC03 2017 2017-11-06 DO 1.3083328197 #> 1941 2068 3M CC03 2017 2017-11-06 DOSAT 3.9080149840 + #> 1942 2068 3M CC03 2017 2017-11-06 NO23 -5.2983173665 I #> 1943 2068 3M CC03 2017 2017-11-06 SALIN 3.1354942159 #> 1944 2068 3M CC03 2017 2017-11-06 TKN -0.2744368457 #> 1945 2068 3M CC03 2017 2017-11-06 TN -0.2691874898 + #> 1946 2068 3M CC03 2017 2017-11-06 TP -2.4418471603 #> 1947 2068 3M CC03 2017 2017-11-06 TURB 1.2237754316 #> 1948 2068 3M CC03 2017 2017-11-06 CHLAC 1.3350010667 #> 1949 2068 3M CC03 2017 2017-11-06 COLOR 3.5835189385 #> 1950 2068 3M CC03 2017 2017-11-06 NO23 -5.1159958098 I #> 1951 2068 3M CC03 2017 2017-11-06 TKN -0.3011050928 #> 1952 2068 3M CC03 2017 2017-11-06 TN -0.2957142441 + #> 1953 2068 3M CC03 2017 2017-11-06 TP -2.4079456087 #> 1954 2068 3M CC03 2017 2017-11-06 TURB 1.2237754316 #> 1955 2068 3M CC03 2018 2018-01-02 CHLAC 1.0647107370 #> 1956 2068 3M CC03 2018 2018-01-02 COLOR 3.0445224377 #> 1957 2068 3M CC03 2018 2018-01-02 NO23 -4.9618451299 I #> 1958 2068 3M CC03 2018 2018-01-02 SALIN 3.4563166809 #> 1959 2068 3M CC03 2018 2018-01-02 TKN -0.4780358009 #> 1960 2068 3M CC03 2018 2018-01-02 TN -0.4716049106 + #> 1961 2068 3M CC03 2018 2018-01-02 TP -2.4079456087 #> 1962 2068 3M CC03 2018 2018-01-02 TURB 1.1314021115 #> 1963 2068 3M CC03 2018 2018-02-05 CHLAC 0.9932517730 A #> 1964 2068 3M CC03 2018 2018-02-05 COLOR 3.2188758249 #> 1965 2068 3M CC03 2018 2018-02-05 DO 1.3609765531 #> 1966 2068 3M CC03 2018 2018-02-05 DOSAT 3.8979240810 + #> 1967 2068 3M CC03 2018 2018-02-05 NO23 -4.3428059215 #> 1968 2068 3M CC03 2018 2018-02-05 SALIN 3.0587070727 #> 1969 2068 3M CC03 2018 2018-02-05 TKN -0.4780358009 #> 1970 2068 3M CC03 2018 2018-02-05 TN -0.4572848568 + #> 1971 2068 3M CC03 2018 2018-02-05 TP -2.6310891600 #> 1972 2068 3M CC03 2018 2018-02-05 TURB 0.8754687374 #> 1973 2068 3M CC03 2018 2018-03-05 CHLAC 0.6418538862 #> 1974 2068 3M CC03 2018 2018-03-05 COLOR 2.5649493575 #> 1975 2068 3M CC03 2018 2018-03-05 DO 1.5686159179 #> 1976 2068 3M CC03 2018 2018-03-05 DOSAT 4.0517849478 + #> 1977 2068 3M CC03 2018 2018-03-05 NO23 -5.2983173665 I #> 1978 2068 3M CC03 2018 2018-03-05 SALIN 3.4781584228 #> 1979 2068 3M CC03 2018 2018-03-05 TKN -0.5798184953 #> 1980 2068 3M CC03 2018 2018-03-05 TN -0.5727010275 + #> 1981 2068 3M CC03 2018 2018-03-05 TP -2.7488721956 #> 1982 2068 3M CC03 2018 2018-03-05 TURB 2.2407096893 #> 1983 2068 3M CC03 2018 2018-04-02 CHLAC -0.5978370008 U #> 1984 2068 3M CC03 2018 2018-04-02 COLOR 0.9162907319 U #> 1985 2068 3M CC03 2018 2018-04-02 DO 1.2237754316 #> 1986 2068 3M CC03 2018 2018-04-02 DOSAT 3.8877303129 + #> 1987 2068 3M CC03 2018 2018-04-02 NO23 -3.7297014486 #> 1988 2068 3M CC03 2018 2018-04-02 SALIN 3.5553480615 #> 1989 2068 3M CC03 2018 2018-04-02 TKN 1.0296194172 #> 1990 2068 3M CC03 2018 2018-04-02 TN 1.0381543196 + #> 1991 2068 3M CC03 2018 2018-04-02 TP -1.7719568419 #> 1992 2068 3M CC03 2018 2018-04-02 TURB 1.3862943611 #> 1993 2068 3M CC03 2018 2018-05-07 CHLAC 0.4054651081 I #> 1994 2068 3M CC03 2018 2018-05-07 COLOR 2.6390573296 #> 1995 2068 3M CC03 2018 2018-05-07 DO -0.1984509387 #> 1996 2068 3M CC03 2018 2018-05-07 DOSAT 2.5416019935 #> 1997 2068 3M CC03 2018 2018-05-07 NO23 -5.5214609179 U #> 1998 2068 3M CC03 2018 2018-05-07 SALIN 3.6109179126 #> 1999 2068 3M CC03 2018 2018-05-07 TKN -0.6161861394 #> 2000 2068 3M CC03 2018 2018-05-07 TN -0.6124892775 + #> 2001 2068 3M CC03 2018 2018-05-07 TP -2.8824035882 #> 2002 2068 3M CC03 2018 2018-05-07 TURB 0.8754687374 #> 2003 2068 3M CC03 2018 2018-08-06 CHLAC 1.5475625087 #> 2004 2068 3M CC03 2018 2018-08-06 COLOR 3.8918202981 #> 2005 2068 3M CC03 2018 2018-08-06 DO -0.9162907319 #> 2006 2068 3M CC03 2018 2018-08-06 DOSAT 1.8245492921 #> 2007 2068 3M CC03 2018 2018-08-06 NO23 -5.5214609179 I #> 2008 2068 3M CC03 2018 2018-08-06 SALIN 3.3332753652 #> 2009 2068 3M CC03 2018 2018-08-06 TKN 0.2623642645 #> 2010 2068 3M CC03 2018 2018-08-06 TN 0.2654364635 + #> 2011 2068 3M CC03 2018 2018-08-06 TP -2.4191189092 #> 2012 2068 3M CC03 2018 2018-08-06 TURB 1.6486586256 #> 2013 2068 3M CC03 2019 2019-03-04 CHLAC 0.2623642645 I #> 2014 2068 3M CC03 2019 2019-03-04 COLOR 3.6635616461 #> 2015 2068 3M CC03 2019 2019-03-04 DO 1.0919233005 #> 2016 2068 3M CC03 2019 2019-03-04 DOSAT 3.6506582413 #> 2017 2068 3M CC03 2019 2019-03-04 NO23 -5.5214609179 U #> 2018 2068 3M CC03 2019 2019-03-04 SALIN 2.3105532626 #> 2019 2068 3M CC03 2019 2019-03-04 TKN -0.3147107448 #> 2020 2068 3M CC03 2019 2019-03-04 TN -0.3119747650 + #> 2021 2068 3M CC03 2019 2019-03-04 TP -2.3025850930 #> 2022 2068 3M CC03 2019 2019-03-04 TURB 0.8754687374 #> 2023 2068 3M CC03 2019 2019-05-06 CHLAC 1.3862943611 #> 2024 2068 3M CC03 2019 2019-05-06 COLOR 3.4965075615 #> 2025 2068 3M CC03 2019 2019-05-06 DO -1.8325814637 #> 2026 2068 3M CC03 2019 2019-05-06 DOSAT 0.9932517730 #> 2027 2068 3M CC03 2019 2019-05-06 NO23 -5.5214609179 U #> 2028 2068 3M CC03 2019 2019-05-06 SALIN 3.3809946743 #> 2029 2068 3M CC03 2019 2019-05-06 TKN -0.3566749439 #> 2030 2068 3M CC03 2019 2019-05-06 TN -0.3538218750 + #> 2031 2068 3M CC03 2019 2019-05-06 TP -3.0159349809 #> 2032 2068 3M CC03 2019 2019-05-06 TURB 0.6418538862 #> 2033 2068 3M CC03 2019 2019-06-03 CHLAC 1.0986122887 #> 2034 2068 3M CC03 2019 2019-06-03 COLOR 2.9957322736 #> 2035 2068 3M CC03 2019 2019-06-03 DO -0.8675005677 #> 2036 2068 3M CC03 2019 2019-06-03 DOSAT 1.8870696490 #> 2037 2068 3M CC03 2019 2019-06-03 NO23 -5.5214609179 U #> 2038 2068 3M CC03 2019 2019-06-03 SALIN 3.6068556186 #> 2039 2068 3M CC03 2019 2019-06-03 TKN -0.3424903089 #> 2040 2068 3M CC03 2019 2019-06-03 TN -0.3396773676 + #> 2041 2068 3M CC03 2019 2019-06-03 TP -3.0791138825 #> 2042 2068 3M CC03 2019 2019-06-03 TURB 0.9555114450 #> 2043 2068 3M CC03 2019 2019-07-01 CHLAC 1.9740810260 #> 2044 2068 3M CC03 2019 2019-07-01 COLOR 3.2958368660 A #> 2045 2068 3M CC03 2019 2019-07-01 DO -0.5978370008 #> 2046 2068 3M CC03 2019 2019-07-01 DOSAT 2.1517622033 #> 2047 2068 3M CC03 2019 2019-07-01 NO23 -5.5214609179 U #> 2048 2068 3M CC03 2019 2019-07-01 SALIN 3.5160130561 #> 2049 2068 3M CC03 2019 2019-07-01 TKN -0.2613647641 #> 2050 2068 3M CC03 2019 2019-07-01 TN -0.2587707290 + #> 2051 2068 3M CC03 2019 2019-07-01 TP -3.0159349809 #> 2052 2068 3M CC03 2019 2019-07-01 TURB 1.6486586256 A #> 2053 2068 3M CC03 2019 2019-10-07 TN -0.6462635947 + #> 2054 2068 3M CC03 2019 2019-10-07 CHLAC 1.0647107370 I #> 2055 2068 3M CC03 2019 2019-10-07 COLOR 1.9169226122 #> 2056 2068 3M CC03 2019 2019-10-07 DO 0.6931471806 #> 2057 2068 3M CC03 2019 2019-10-07 DOSAT 3.4436180975 #> 2058 2068 3M CC03 2019 2019-10-07 NO23 -5.1159958098 I #> 2059 2068 3M CC03 2019 2019-10-07 SALIN 3.5392186796 #> 2060 2068 3M CC03 2019 2019-10-07 TKN -0.6539264674 #> 2061 2068 3M CC03 2019 2019-10-07 TP -2.5902671654 #> 2062 2068 3M CC03 2019 2019-10-07 TURB 0.7884573604 #> 2063 2068 3M CC03 2019 2019-10-07 CHLAC 1.0986122887 #> 2064 2068 3M CC03 2019 2019-10-07 COLOR 1.8405496334 #> 2065 2068 3M CC03 2019 2019-10-07 NO23 -4.9618451299 I #> 2066 2068 3M CC03 2019 2019-10-07 TKN -0.5108256238 #> 2067 2068 3M CC03 2019 2019-10-07 TN -0.5041810810 + #> 2068 2068 3M CC03 2019 2019-10-07 TP -2.8647040111 #> 2069 2068 3M CC03 2019 2019-10-07 TURB 1.0647107370 #> 2070 2068 3M CC03 2019 2019-11-04 CHLAC 1.7227665977 #> 2071 2068 3M CC03 2019 2019-11-04 COLOR 2.8903717579 #> 2072 2068 3M CC03 2019 2019-11-04 DO 0.3646431136 #> 2073 2068 3M CC03 2019 2019-11-04 DOSAT 3.0349529867 #> 2074 2068 3M CC03 2019 2019-11-04 NO23 -4.3428059215 #> 2075 2068 3M CC03 2019 2019-11-04 SALIN 3.6030491975 #> 2076 2068 3M CC03 2019 2019-11-04 TKN -0.3566749439 #> 2077 2068 3M CC03 2019 2019-11-04 TN -0.3382738586 + #> 2078 2068 3M CC03 2019 2019-11-04 TP -2.7488721956 #> 2079 2068 3M CC03 2019 2019-11-04 TURB 1.1631508098 #> 2080 2068 3M CC03 2019 2019-12-02 CHLAC 0.8754687374 I #> 2081 2068 3M CC03 2019 2019-12-02 COLOR 2.1860512767 #> 2082 2068 3M CC03 2019 2019-12-02 DO 1.0367368850 #> 2083 2068 3M CC03 2019 2019-12-02 DOSAT 3.6988297850 #> 2084 2068 3M CC03 2019 2019-12-02 NO23 -4.1997050779 #> 2085 2068 3M CC03 2019 2019-12-02 SALIN 3.4977189487 #> 2086 2068 3M CC03 2019 2019-12-02 TKN -0.4620354596 #> 2087 2068 3M CC03 2019 2019-12-02 TN -0.4385049622 + #> 2088 2068 3M CC03 2019 2019-12-02 TP -2.9187712324 #> 2089 2068 3M CC03 2019 2019-12-02 TURB 0.6418538862 #> 2090 2068 3M CC03 2020 2020-01-06 CHLAC 1.2237754316 #> 2091 2068 3M CC03 2020 2020-01-06 COLOR 3.5263605246 A #> 2092 2068 3M CC03 2020 2020-01-06 DO 1.1184149160 #> 2093 2068 3M CC03 2020 2020-01-06 DOSAT 3.5862928653 #> 2094 2068 3M CC03 2020 2020-01-06 NO23 -4.1997050779 #> 2095 2068 3M CC03 2020 2020-01-06 SALIN 2.7491921444 #> 2096 2068 3M CC03 2020 2020-01-06 TKN 0.0953101798 #> 2097 2068 3M CC03 2020 2020-01-06 TN 0.1088544049 + #> 2098 2068 3M CC03 2020 2020-01-06 TP -2.5510464523 #> 2099 2068 3M CC03 2020 2020-01-06 TURB 1.4350845253 #> 2100 2068 3M CC03 2020 2020-02-03 CHLAC 0.5877866649 I #> 2101 2068 3M CC03 2020 2020-02-03 COLOR 3.3672958300 #> 2102 2068 3M CC03 2020 2020-02-03 DO 1.4011829736 #> 2103 2068 3M CC03 2020 2020-02-03 DOSAT 3.7909846771 #> 2104 2068 3M CC03 2020 2020-02-03 NO23 -4.9618451299 I #> 2105 2068 3M CC03 2020 2020-02-03 SALIN 3.0819099698 #> 2106 2068 3M CC03 2020 2020-02-03 TKN -0.2107210313 #> 2107 2068 3M CC03 2020 2020-02-03 TN -0.2057949130 + #> 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#> 2198 2068 3M CC03 2021 2021-05-03 TP -3.1010927892 #> 2199 2068 3M CC03 2021 2021-05-03 TURB 1.6094379124 A #> 2200 2068 3M CC03 2021 2021-06-07 CHLAC 0.8754687374 I #> 2201 2068 3M CC03 2021 2021-06-07 COLOR 2.9444389792 #> 2202 2068 3M CC03 2021 2021-06-07 DO -0.4462871026 #> 2203 2068 3M CC03 2021 2021-06-07 DOSAT 2.3418058061 #> 2204 2068 3M CC03 2021 2021-06-07 NO23 -5.5214609179 U #> 2205 2068 3M CC03 2021 2021-06-07 SALIN 3.6444049640 #> 2206 2068 3M CC03 2021 2021-06-07 TKN -0.4462871026 #> 2207 2068 3M CC03 2021 2021-06-07 TN -0.4431669753 + #> 2208 2068 3M CC03 2021 2021-06-07 TP -3.1941832123 #> 2209 2068 3M CC03 2021 2021-06-07 TURB 0.8754687374 #> 2210 2068 3M CC03 2021 2021-08-02 CHLAC 3.2188758249 #> 2211 2068 3M CC03 2021 2021-08-02 COLOR 4.4308167988 #> 2212 2068 3M CC03 2021 2021-08-02 DO -0.5108256238 #> 2213 2068 3M CC03 2021 2021-08-02 DOSAT -0.9162907319 #> 2214 2068 3M CC03 2021 2021-08-02 NO23 -5.5214609179 U #> 2215 2068 3M CC03 2021 2021-08-02 SALIN 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-4.6051701860 I #> 2252 2068 3M CC03 2021 2021-11-01 SALIN 3.1797191097 #> 2253 2068 3M CC03 2021 2021-11-01 TKN -0.3856624808 #> 2254 2068 3M CC03 2021 2021-11-01 TN -0.3797973614 + #> 2255 2068 3M CC03 2021 2021-11-01 TP -2.4418471603 #> 2256 2068 3M CC03 2021 2021-11-01 TURB 0.4054651081 A #> 2257 2068 3M CC03 2021 2021-12-06 CHLAC 0.7419373447 I #> 2258 2068 3M CC03 2021 2021-12-06 COLOR 2.7725887222 #> 2259 2068 3M CC03 2021 2021-12-06 DO 1.1249295970 #> 2260 2068 3M CC03 2021 2021-12-06 DOSAT 3.7495040759 #> 2261 2068 3M CC03 2021 2021-12-06 NO23 -4.4228486292 #> 2262 2068 3M CC03 2021 2021-12-06 SALIN 3.3931652100 #> 2263 2068 3M CC03 2021 2021-12-06 TKN -0.4004775666 #> 2264 2068 3M CC03 2021 2021-12-06 TN -0.3827256211 + #> 2265 2068 3M CC03 2021 2021-12-06 TP -2.4889146712 #> 2266 2068 3M CC03 2021 2021-12-06 TURB 1.1631508098 #> 2267 2068 3M CC03 2022 2022-01-03 CHLAC 1.2527629685 #> 2268 2068 3M CC03 2022 2022-01-03 COLOR 2.6390573296 #> 2269 2068 3M CC03 2022 2022-01-03 DO 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CHLAC 0.7419373447 I #> 2288 2068 3M CC03 2022 2022-03-07 COLOR 2.3025850930 A #> 2289 2068 3M CC03 2022 2022-03-07 DO 0.5306282511 #> 2290 2068 3M CC03 2022 2022-03-07 DOSAT 3.1863526332 #> 2291 2068 3M CC03 2022 2022-03-07 NO23 -5.1159958098 I #> 2292 2068 3M CC03 2022 2022-03-07 SALIN 3.5331024525 #> 2293 2068 3M CC03 2022 2022-03-07 TKN -0.4307829161 #> 2294 2068 3M CC03 2022 2022-03-07 TN -0.4246479275 + #> 2295 2068 3M CC03 2022 2022-03-07 TP -2.8647040111 #> 2296 2068 3M CC03 2022 2022-03-07 TURB 0.9555114450 #> 2297 2068 3M CC03 2022 2022-04-04 CHLAC 0.0000000000 I #> 2298 2068 3M CC03 2022 2022-04-04 COLOR 2.5649493575 #> 2299 2068 3M CC03 2022 2022-04-04 DO -0.2107210313 #> 2300 2068 3M CC03 2022 2022-04-04 DOSAT 2.5416019935 #> 2301 2068 3M CC03 2022 2022-04-04 NO23 -5.1159958098 I #> 2302 2068 3M CC03 2022 2022-04-04 TKN -0.6161861394 #> 2303 2068 3M CC03 2022 2022-04-04 TN -0.6088060321 + #> 2304 2068 3M CC03 2022 2022-04-04 TP -2.9957322736 #> 2305 2068 3M CC03 2022 2022-04-04 TURB 1.0986122887 #> 2306 2068 3M CC03 2022 2022-05-02 CHLAC 0.3364722366 U #> 2307 2068 3M CC03 2022 2022-05-02 DO -0.5108256238 #> 2308 2068 3M CC03 2022 2022-05-02 DOSAT 2.2082744135 #> 2309 2068 3M CC03 2022 2022-05-02 NO23 -5.5214609179 U #> 2310 2068 3M CC03 2022 2022-05-02 SALIN 3.5366020187 #> 2311 2068 3M CC03 2022 2022-05-02 TN -0.5762534291 + #> 2312 2068 3M CC03 2018 2018-03-13 CHLAC 0.9555114450 #> 2313 2068 3M CC03 2018 2018-03-13 COND 10.8817948782 #> 2314 2068 3M CC03 2018 2018-03-13 DO 2.0794415417 #> 2315 2068 3M CC03 2018 2018-03-13 DOSAT 4.6812048723 #> 2316 2068 3M CC03 2018 2018-03-13 NO23 -4.7105307016 I #> 2317 2068 3M CC03 2018 2018-03-13 SALIN 3.6778185068 + #> 2318 2068 3M CC03 2018 2018-03-13 TKN -0.4942963218 #> 2319 2068 3M CC03 2018 2018-03-13 TN -0.4877603508 + #> 2320 2068 3M CC03 2018 2018-03-13 TP -2.4191189092 #> 2321 2068 3M CC03 2018 2018-03-13 TSS 1.3862943611 I #> 2322 2068 3M CC03 2018 2018-03-13 TURB 1.0647107370 #> 2323 2068 3M CC03 2018 2018-05-08 CHLAC 1.1631508098 #> 2324 2068 3M CC03 2018 2018-05-08 COND 10.9254527508 #> 2325 2068 3M CC03 2018 2018-05-08 DO 1.4973884086 #> 2326 2068 3M CC03 2018 2018-05-08 DOSAT 4.2091602367 #> 2327 2068 3M CC03 2018 2018-05-08 NO23 -5.5214609179 U #> 2328 2068 3M CC03 2018 2018-05-08 SALIN 3.5973122606 + #> 2329 2068 3M CC03 2018 2018-05-08 TKN -0.5108256238 #> 2330 2068 3M CC03 2018 2018-05-08 TN -0.5074978337 + #> 2331 2068 3M CC03 2018 2018-05-08 TP -3.2441936329 #> 2332 2068 3M CC03 2018 2018-05-08 TSS 2.0794415417 I #> 2333 2068 3M CC03 2018 2018-05-08 TURB 1.3083328197 #> 2334 2068 3M CC03 2018 2018-06-26 CHLAC 2.4849066498 #> 2335 2068 3M CC03 2018 2018-06-26 COND 10.7823463704 #> 2336 2068 3M CC03 2018 2018-06-26 DO 1.1118575154 #> 2337 2068 3M CC03 2018 2018-06-26 DOSAT 3.8628327612 #> 2338 2068 3M CC03 2018 2018-06-26 NO23 -5.5214609179 U #> 2339 2068 3M CC03 2018 2018-06-26 SALIN 3.3414473773 + #> 2340 2068 3M CC03 2018 2018-06-26 TKN -0.4155154440 #> 2341 2068 3M CC03 2018 2018-06-26 TN -0.4124897230 + #> 2342 2068 3M CC03 2018 2018-06-26 TSS 2.0794415417 I #> 2343 2068 3M CC03 2018 2018-06-26 TURB 1.4816045409 #> 2344 2068 3M CC03 2018 2018-09-18 CHLAC 2.2617630985 #> 2345 2068 3M CC03 2018 2018-09-18 COND 9.9966590834 #> 2346 2068 3M CC03 2018 2018-09-18 DO 0.8020015855 #> 2347 2068 3M CC03 2018 2018-09-18 DOSAT 3.4812400893 #> 2348 2068 3M CC03 2018 2018-09-18 NO23 -4.7105307016 I #> 2349 2068 3M CC03 2018 2018-09-18 TKN -0.0833816089 #> 2350 2068 3M CC03 2018 2018-09-18 TN -0.0790432073 + #> 2351 2068 3M CC03 2018 2018-09-18 TP -2.3227878003 #> 2352 2068 3M CC03 2018 2018-09-18 TSS 1.0986122887 U #> 2353 2068 3M CC03 2018 2018-09-18 TURB 1.2809338455 A #> 2354 2068 3M CC03 2018 2018-12-04 CHLAC 1.6486586256 #> 2355 2068 3M CC03 2018 2018-12-04 COND 10.7489265434 #> 2356 2068 3M CC03 2018 2018-12-04 DO 1.5644405465 #> 2357 2068 3M CC03 2018 2018-12-04 DOSAT 4.2239097666 #> 2358 2068 3M CC03 2018 2018-12-04 NO23 -1.8971199849 #> 2359 2068 3M CC03 2018 2018-12-04 SALIN 3.4094961845 #> 2360 2068 3M CC03 2018 2018-12-04 TKN -0.3285040670 #> 2361 2068 3M CC03 2018 2018-12-04 TN -0.1392620673 + #> 2362 2068 3M CC03 2018 2018-12-04 TP -2.6450754019 #> 2363 2068 3M CC03 2018 2018-12-04 TSS 2.1972245773 I #> 2364 2068 3M CC03 2018 2018-12-04 TURB 0.5306282511 #> 2365 2078A 2 CC04 2019 2019-08-13 CHLAC 3.1780538303 #> 2366 2078A 2 CC04 2019 2019-08-13 COND 9.8642788393 #> 2367 2078A 2 CC04 2019 2019-08-13 DO 1.7647307968 #> 2368 2078A 2 CC04 2019 2019-08-13 DOSAT 4.4176350621 #> 2369 2078A 2 CC04 2019 2019-08-13 NO23 -5.2983173665 I #> 2370 2078A 2 CC04 2019 2019-08-13 SALIN 2.4274540750 #> 2371 2078A 2 CC04 2019 2019-08-13 TKN 0.3364722366 #> 2372 2078A 2 CC04 2019 2019-08-13 TN 0.3393253056 + #> 2373 2078A 2 CC04 2019 2019-08-13 TP -2.9759296463 #> 2374 2078A 2 CC04 2019 2019-08-13 TSS 1.6094379124 I #> 2375 2078A 2 CC04 2019 2019-08-13 TURB 0.7419373447 #> 2376 2078B 2 CC05 2019 2019-01-17 COND 10.7433722892 #> 2377 2078B 2 CC05 2019 2019-01-17 DO 1.9065751437 #> 2378 2078B 2 CC05 2019 2019-01-17 DOSAT 4.4030540019 #> 2379 2078B 2 CC05 2019 2019-01-17 SALIN 3.4045251718 #> 2380 2078B 2 CC05 2019 2019-01-17 TN -0.3827256211 + #> 2381 2078B 2 CC05 2019 2019-01-24 CHLAC 0.2623642645 I #> 2382 2078B 2 CC05 2019 2019-01-24 COND 10.7763069502 #> 2383 2078B 2 CC05 2019 2019-01-24 DO 1.8702625307 #> 2384 2078B 2 CC05 2019 2019-01-24 DOSAT 4.4531838290 #> 2385 2078B 2 CC05 2019 2019-01-24 NO23 -5.1159958098 I #> 2386 2078B 2 CC05 2019 2019-01-24 SALIN 3.4413791713 #> 2387 2078B 2 CC05 2019 2019-01-24 TKN -0.7985076962 #> 2388 2078B 2 CC05 2019 2019-01-24 TN -0.7896580809 + #> 2389 2078B 2 CC05 2019 2019-01-24 TP -3.5065578973 #> 2390 2078B 2 CC05 2019 2019-01-24 TSS 1.0986122887 I #> 2391 2078B 2 CC05 2019 2019-01-24 TURB 0.2623642645 #> 2392 2078B 2 CC05 2019 2019-03-12 CHLAC 1.2809338455 #> 2393 2078B 2 CC05 2019 2019-03-12 COND 10.4768935315 #> 2394 2078B 2 CC05 2019 2019-03-12 DO 1.6992786164 #> 2395 2078B 2 CC05 2019 2019-03-12 DOSAT 4.3412046402 #> 2396 2078B 2 CC05 2019 2019-03-12 NO23 -5.5214609179 U #> 2397 2078B 2 CC05 2019 2019-03-12 SALIN 3.1059310659 #> 2398 2078B 2 CC05 2019 2019-03-12 TKN -0.3424903089 #> 2399 2078B 2 CC05 2019 2019-03-12 TN -0.3396773676 + #> 2400 2078B 2 CC05 2019 2019-03-12 TP -3.2441936329 #> 2401 2078B 2 CC05 2019 2019-03-12 TSS 2.1972245773 I #> 2402 2078B 2 CC05 2019 2019-03-12 TURB 0.6931471806 #> 2403 2078B 2 CC05 2019 2019-04-16 CHLAC 1.4816045409 #> 2404 2078B 2 CC05 2019 2019-04-16 COND 10.7360705353 #> 2405 2078B 2 CC05 2019 2019-04-16 DO 1.6505798558 #> 2406 2078B 2 CC05 2019 2019-04-16 DOSAT 4.3094559418 #> 2407 2078B 2 CC05 2019 2019-04-16 NO23 -5.5214609179 U #> 2408 2078B 2 CC05 2019 2019-04-16 SALIN 3.3951793093 #> 2409 2078B 2 CC05 2019 2019-04-16 TKN -0.2484613593 #> 2410 2078B 2 CC05 2019 2019-04-16 TN -0.2459005384 + #> 2411 2078B 2 CC05 2019 2019-04-16 TP -3.7722610631 #> 2412 2078B 2 CC05 2019 2019-04-16 TSS 1.6094379124 I #> 2413 2078B 2 CC05 2019 2019-04-16 TURB 0.6418538862 #> 2414 2078B 2 CC05 2019 2019-06-11 CHLAC 1.1314021115 #> 2415 2078B 2 CC05 2019 2019-06-11 COND 10.8909447918 #> 2416 2078B 2 CC05 2019 2019-06-11 DO 1.2059708070 #> 2417 2078B 2 CC05 2019 2019-06-11 DOSAT 4.0127729085 #> 2418 2078B 2 CC05 2019 2019-06-11 NO23 -5.5214609179 I #> 2419 2078B 2 CC05 2019 2019-06-11 SALIN 3.5635996377 #> 2420 2078B 2 CC05 2019 2019-06-11 TKN -0.3285040670 #> 2421 2078B 2 CC05 2019 2019-06-11 TN -0.3229638866 + #> 2422 2078B 2 CC05 2019 2019-06-11 TP -3.3242363405 #> 2423 2078B 2 CC05 2019 2019-06-11 TSS 1.0986122887 U #> 2424 2078B 2 CC05 2019 2019-06-11 TURB 0.3364722366 #> 2425 2078B 2 CC05 2019 2019-08-13 CHLAC 2.8332133441 #> 2426 2078B 2 CC05 2019 2019-08-13 COND 10.2219412837 #> 2427 2078B 2 CC05 2019 2019-08-13 DO 1.4036429995 #> 2428 2078B 2 CC05 2019 2019-08-13 DOSAT 4.0926765051 #> 2429 2078B 2 CC05 2019 2019-08-13 NO23 -4.6051701860 I #> 2430 2078B 2 CC05 2019 2019-08-13 SALIN 2.8195915758 #> 2431 2078B 2 CC05 2019 2019-08-13 TKN 0.6418538862 #> 2432 2078B 2 CC05 2019 2019-08-13 TN 0.6439569364 + #> 2433 2078B 2 CC05 2019 2019-08-13 TP -2.9759296463 #> 2434 2078B 2 CC05 2019 2019-08-13 TSS 1.7917594692 I #> 2435 2078B 2 CC05 2019 2019-08-13 TURB 0.7884573604 #> 2436 2078B 2 CC05 2019 2019-08-13 COND 10.3244650523 #> 2437 2078B 2 CC05 2019 2019-08-13 DO 1.0543120298 #> 2438 2078B 2 CC05 2019 2019-08-13 DOSAT 3.7541989202 #> 2439 2078B 2 CC05 2019 2019-08-13 SALIN 2.9322598506 #> 2440 2078B 2 CC05 2019 2019-10-01 COND 10.7304660807 #> 2441 2078B 2 CC05 2019 2019-10-01 DO 1.5644405465 #> 2442 2078B 2 CC05 2019 2019-10-01 DOSAT 4.2724907476 #> 2443 2078B 2 CC05 2019 2019-10-01 SALIN 3.3864220961 #> 2444 2078B 2 CC05 2019 2019-11-04 COND 10.7792062586 #> 2445 2078B 2 CC05 2019 2019-11-04 DO 1.5151272330 #> 2446 2078B 2 CC05 2019 2019-11-04 DOSAT 4.2061840440 #> 2447 2078B 2 CC05 2019 2019-11-04 SALIN 3.4423393250 #> 2448 2078B 2 CC05 2019 2019-11-19 CHLAC 2.6390573296 #> 2449 2078B 2 CC05 2019 2019-11-19 COND 10.8493565039 #> 2450 2078B 2 CC05 2019 2019-11-19 DO 2.0135687975 #> 2451 2078B 2 CC05 2019 2019-11-19 DOSAT 4.6298627986 #> 2452 2078B 2 CC05 2019 2019-11-19 NO23 -5.5214609179 U #> 2453 2078B 2 CC05 2019 2019-11-19 SALIN 3.5234150144 #> 2454 2078B 2 CC05 2019 2019-11-19 TKN -0.3011050928 #> 2455 2078B 2 CC05 2019 2019-11-19 TN -0.2984060358 + #> 2456 2078B 2 CC05 2019 2019-11-19 TP -2.8302178351 #> 2457 2078B 2 CC05 2019 2019-11-19 TSS 2.0794415417 I #> 2458 2078B 2 CC05 2019 2019-11-19 TURB 1.0296194172 A #> 2459 2078B 2 CC05 2020 2020-02-13 CHLAC 2.1400661635 A #> 2460 2078B 2 CC05 2020 2020-02-13 COND 10.7287588860 #> 2461 2078B 2 CC05 2020 2020-02-13 DO 1.8961194846 #> 2462 2078B 2 CC05 2020 2020-02-13 DOSAT 4.5747109785 #> 2463 2078B 2 CC05 2020 2020-02-13 NO23 -5.5214609179 U #> 2464 2078B 2 CC05 2020 2020-02-13 SALIN 3.3857452771 #> 2465 2078B 2 CC05 2020 2020-02-13 TKN -0.3424903089 #> 2466 2078B 2 CC05 2020 2020-02-13 TN -0.3396773676 + #> 2467 2078B 2 CC05 2020 2020-02-13 TP -3.3242363405 #> 2468 2078B 2 CC05 2020 2020-02-13 TSS 2.2617630985 I #> 2469 2078B 2 CC05 2020 2020-02-13 TURB 1.0296194172 #> 2470 2078B 2 CC05 2020 2020-03-24 CHLAC 2.2617630985 #> 2471 2078B 2 CC05 2020 2020-03-24 COND 10.9026109427 #> 2472 2078B 2 CC05 2020 2020-03-24 DO 1.8357763546 #> 2473 2078B 2 CC05 2020 2020-03-24 DOSAT 4.5900565482 #> 2474 2078B 2 CC05 2020 2020-03-24 NO23 -5.5214609179 U #> 2475 2078B 2 CC05 2020 2020-03-24 SALIN 3.5787855313 #> 2476 2078B 2 CC05 2020 2020-03-24 TKN -0.6161861394 #> 2477 2078B 2 CC05 2020 2020-03-24 TN -0.6124892775 + #> 2478 2078B 2 CC05 2020 2020-03-24 TP -2.5902671654 #> 2479 2078B 2 CC05 2020 2020-03-24 TSS 2.4849066498 A #> 2480 2078B 2 CC05 2020 2020-03-24 TURB 1.0647107370 #> 2481 2078B 2 CC05 2020 2020-06-15 CHLAC 2.8332133441 #> 2482 2078B 2 CC05 2020 2020-06-15 COND 10.3780433051 #> 2483 2078B 2 CC05 2020 2020-06-15 DO 1.2325602612 #> 2484 2078B 2 CC05 2020 2020-06-15 DOSAT 3.9199911751 #> 2485 2078B 2 CC05 2020 2020-06-15 NO23 -5.5214609179 I #> 2486 2078B 2 CC05 2020 2020-06-15 SALIN 2.9907197317 #> 2487 2078B 2 CC05 2020 2020-06-15 TKN 0.1823215568 #> 2488 2078B 2 CC05 2020 2020-06-15 TN 0.1856493469 + #> 2489 2078B 2 CC05 2020 2020-06-15 TP -3.0159349809 #> 2490 2078B 2 CC05 2020 2020-06-15 TSS 1.6094379124 I #> 2491 2078B 2 CC05 2020 2020-06-15 TURB 0.9932517730 #> 2492 2078B 2 CC05 2020 2020-07-27 CHLAC 2.5649493575 A #> 2493 2078B 2 CC05 2020 2020-07-27 COND 10.7499993898 #> 2494 2078B 2 CC05 2020 2020-07-27 DO 1.4422019931 #> 2495 2078B 2 CC05 2020 2020-07-27 DOSAT 4.2150861799 #> 2496 2078B 2 CC05 2020 2020-07-27 NO23 -5.5214609179 U #> 2497 2078B 2 CC05 2020 2020-07-27 SALIN 3.4041928906 #> 2498 2078B 2 CC05 2020 2020-07-27 TKN -0.3424903089 #> 2499 2078B 2 CC05 2020 2020-07-27 TN -0.3396773676 + #> 2500 2078B 2 CC05 2020 2020-07-27 TP -3.1010927892 #> 2501 2078B 2 CC05 2020 2020-07-27 TSS 1.6094379124 I #> 2502 2078B 2 CC05 2020 2020-07-27 TURB 1.1631508098 #> 2503 2078B 2 CC05 2020 2020-08-26 CHLAC 2.8903717579 #> 2504 2078B 2 CC05 2020 2020-08-26 COND 10.1730947543 #> 2505 2078B 2 CC05 2020 2020-08-26 DO 1.5062971535 #> 2506 2078B 2 CC05 2020 2020-08-26 DOSAT 4.1972019477 #> 2507 2078B 2 CC05 2020 2020-08-26 NO23 -5.5214609179 U #> 2508 2078B 2 CC05 2020 2020-08-26 SALIN 2.7625383864 #> 2509 2078B 2 CC05 2020 2020-08-26 TKN -0.0618754037 #> 2510 2078B 2 CC05 2020 2020-08-26 TN -0.0597500044 + #> 2511 2078B 2 CC05 2020 2020-08-26 TP -2.9565115604 #> 2512 2078B 2 CC05 2020 2020-08-26 TSS 1.7917594692 I #> 2513 2078B 2 CC05 2020 2020-08-26 TURB 1.0647107370 #> 2514 2078B 2 CC05 2021 2021-01-14 CHLAC 0.9162907319 #> 2515 2078B 2 CC05 2021 2021-01-14 COND 10.6789517756 #> 2516 2078B 2 CC05 2021 2021-01-14 DO 1.7422190237 #> 2517 2078B 2 CC05 2021 2021-01-14 DOSAT 4.2427645673 #> 2518 2078B 2 CC05 2021 2021-01-14 NO23 -4.6051701860 #> 2519 2078B 2 CC05 2021 2021-01-14 SALIN 3.3339886320 #> 2520 2078B 2 CC05 2021 2021-01-14 TKN -0.6348782724 #> 2521 2078B 2 CC05 2021 2021-01-14 TN -0.6161861394 + #> 2522 2078B 2 CC05 2021 2021-01-14 TP -3.4420193762 #> 2523 2078B 2 CC05 2021 2021-01-14 TSS 1.0986122887 I #> 2524 2078B 2 CC05 2021 2021-01-14 TURB 0.5306282511 #> 2525 2078B 2 CC05 2021 2021-02-24 COND 10.7448823096 #> 2526 2078B 2 CC05 2021 2021-02-24 DO 1.5518087996 #> 2527 2078B 2 CC05 2021 2021-02-24 DOSAT 4.1987045775 #> 2528 2078B 2 CC05 2021 2021-02-24 NO23 -4.6051701860 I #> 2529 2078B 2 CC05 2021 2021-02-24 SALIN 3.4061849232 #> 2530 2078B 2 CC05 2021 2021-02-24 TKN -0.8915981193 #> 2531 2078B 2 CC05 2021 2021-02-24 TN -0.8818893052 + #> 2532 2078B 2 CC05 2021 2021-02-24 TP -3.2441936329 #> 2533 2078B 2 CC05 2021 2021-02-24 TSS 1.0986122887 I #> 2534 2078B 2 CC05 2021 2021-03-23 CHLAC 1.1939224685 #> 2535 2078B 2 CC05 2021 2021-03-23 COND 10.8800451952 #> 2536 2078B 2 CC05 2021 2021-03-23 DO 1.7783364489 #> 2537 2078B 2 CC05 2021 2021-03-23 DOSAT 4.4042772436 #> 2538 2078B 2 CC05 2021 2021-03-23 NO23 -4.9618451299 I #> 2539 2078B 2 CC05 2021 2021-03-23 SALIN 3.5579161896 #> 2540 2078B 2 CC05 2021 2021-03-23 TKN -0.5447271754 #> 2541 2078B 2 CC05 2021 2021-03-23 TN -0.5378542962 + #> 2542 2078B 2 CC05 2021 2021-03-23 TP -2.8134107168 #> 2543 2078B 2 CC05 2021 2021-03-23 TSS 2.4849066498 #> 2544 2078B 2 CC05 2021 2021-03-23 TURB 1.6863989536 #> 2545 2078B 2 CC05 2021 2021-07-28 CHLAC 2.5649493575 #> 2546 2078B 2 CC05 2021 2021-07-28 COND 10.0731881321 #> 2547 2078B 2 CC05 2021 2021-07-28 DO 0.9001613499 #> 2548 2078B 2 CC05 2021 2021-07-28 DOSAT 3.6027767551 #> 2549 2078B 2 CC05 2021 2021-07-28 NO23 -5.5214609179 U #> 2550 2078B 2 CC05 2021 2021-07-28 SALIN 2.6665335209 #> 2551 2078B 2 CC05 2021 2021-07-28 TKN 0.0000000000 #> 2552 2078B 2 CC05 2021 2021-07-28 TN 0.0019980027 + #> 2553 2078B 2 CC05 2021 2021-07-28 TP -3.1010927892 #> 2554 2078B 2 CC05 2021 2021-07-28 TSS 1.3862943611 I #> 2555 2078B 2 CC05 2021 2021-07-28 TURB 1.0296194172 #> 2556 2078B 2 CC05 2021 2021-08-26 CHLAC 2.4849066498 #> 2557 2078B 2 CC05 2021 2021-08-26 COND 10.2519942268 #> 2558 2078B 2 CC05 2021 2021-08-26 DO 1.3737155789 #> 2559 2078B 2 CC05 2021 2021-08-26 DOSAT 4.0324691585 #> 2560 2078B 2 CC05 2021 2021-08-26 NO23 -5.5214609179 U #> 2561 2078B 2 CC05 2021 2021-08-26 SALIN 2.8553201198 #> 2562 2078B 2 CC05 2021 2021-08-26 TKN -0.2231435513 #> 2563 2078B 2 CC05 2021 2021-08-26 TN -0.2206466711 + #> 2564 2078B 2 CC05 2021 2021-08-26 TP -2.8134107168 #> 2565 2078B 2 CC05 2021 2021-08-26 TSS 1.9459101491 I #> 2566 2078B 2 CC05 2021 2021-08-26 TURB 0.8754687374 #> 2567 2078B 2 CC05 2021 2021-09-13 CHLAC 2.5649493575 #> 2568 2078B 2 CC05 2021 2021-09-13 COND 10.4619312252 #> 2569 2078B 2 CC05 2021 2021-09-13 DO 1.4929040962 #> 2570 2078B 2 CC05 2021 2021-09-13 DOSAT 4.2091602367 #> 2571 2078B 2 CC05 2021 2021-09-13 NO23 -5.5214609179 U #> 2572 2078B 2 CC05 2021 2021-09-13 SALIN 3.0842009215 #> 2573 2078B 2 CC05 2021 2021-09-13 TKN -0.0943106795 #> 2574 2078B 2 CC05 2021 2021-09-13 TN -0.0921152889 + #> 2575 2078B 2 CC05 2021 2021-09-13 TP -2.9565115604 #> 2576 2078B 2 CC05 2021 2021-09-13 TSS 2.0794415417 I #> 2577 2078B 2 CC05 2021 2021-09-13 TURB 1.0986122887 A #> 2578 2078B 2 CC05 2022 2022-04-19 CHLAC 2.3978952728 #> 2579 2078B 2 CC05 2022 2022-04-19 COND 10.9594532665 #> 2580 2078B 2 CC05 2022 2022-04-19 DO 1.6486586256 #> 2581 2078B 2 CC05 2022 2022-04-19 DOSAT 4.3845235149 #> 2582 2078B 2 CC05 2022 2022-04-19 NO23 -5.5214609179 U #> 2583 2078B 2 CC05 2022 2022-04-19 SALIN 3.6449275666 #> 2584 2078B 2 CC05 2022 2022-04-19 TKN -0.4462871026 #> 2585 2078B 2 CC05 2022 2022-04-19 TN -0.4431669753 + #> 2586 2078B 2 CC05 2022 2022-04-19 TP -2.6592600369 #> 2587 2078B 2 CC05 2022 2022-04-19 TSS 3.0910424534 #> 2588 2078B 2 CC05 2022 2022-04-19 TURB 1.5892352051 A #> 2589 2078B 2 CC05 2022 2022-05-10 CHLAC 1.9021075264 #> 2590 2078B 2 CC05 2022 2022-05-10 COND 10.8257603561 #> 2591 2078B 2 CC05 2022 2022-05-10 DO 1.6114359151 #> 2592 2078B 2 CC05 2022 2022-05-10 DOSAT 4.3148178850 #> 2593 2078B 2 CC05 2022 2022-05-10 NO23 -5.5214609179 U #> 2594 2078B 2 CC05 2022 2022-05-10 SALIN 3.4943840964 #> 2595 2078B 2 CC05 2022 2022-05-10 TKN -0.1984509387 #> 2596 2078B 2 CC05 2022 2022-05-10 TN -0.1960148839 + #> 2597 2078B 2 CC05 2022 2022-05-10 TP -2.6450754019 #> 2598 2078B 2 CC05 2022 2022-05-10 TSS 2.1972245773 I #> 2599 2078B 2 CC05 2022 2022-05-10 TURB 1.6486586256 #> 2600 2078B 2 CC05 2021 2021-03-23 CHLAC 1.5892352051 #> 2601 2078B 2 CC05 2021 2021-03-23 COND 10.8660128047 #> 2602 2078B 2 CC05 2021 2021-03-23 DO 2.0162354658 #> 2603 2078B 2 CC05 2021 2021-03-23 DOSAT 4.6802776585 #> 2604 2078B 2 CC05 2021 2021-03-23 NO23 -5.5214609179 U #> 2605 2078B 2 CC05 2021 2021-03-23 SALIN 3.5415388662 #> 2606 2078B 2 CC05 2021 2021-03-23 TKN 0.0953101798 #> 2607 2078B 2 CC05 2021 2021-03-23 TN 0.0971267107 + #> 2608 2078B 2 CC05 2021 2021-03-23 TP -3.2968373663 #> 2609 2078B 2 CC05 2021 2021-03-23 TSS 1.0986122887 I #> 2610 2078B 2 CC05 2021 2021-03-23 TURB 0.7884573604 #> 2611 2078B 2 CC05 2021 2021-07-28 CHLAC 1.5686159179 I #> 2612 2078B 2 CC05 2021 2021-07-28 COND 9.6616070559 #> 2613 2078B 2 CC05 2021 2021-07-28 DO -0.3566749439 #> 2614 2078B 2 CC05 2021 2021-07-28 DOSAT 2.3418058061 #> 2615 2078B 2 CC05 2021 2021-07-28 NO23 -5.5214609179 U #> 2616 2078B 2 CC05 2021 2021-07-28 SALIN 2.2049722641 #> 2617 2078B 2 CC05 2021 2021-07-28 TKN 0.0953101798 #> 2618 2078B 2 CC05 2021 2021-07-28 TN 0.0971267107 + #> 2619 2078B 2 CC05 2021 2021-07-28 TP -3.3242363405 #> 2620 2078B 2 CC05 2021 2021-07-28 TSS 1.0986122887 U #> 2621 2078B 2 CC05 2021 2021-07-28 TURB 0.5306282511 #> 2622 2078B 2 CC05 2021 2021-08-26 CHLAC 2.5649493575 #> 2623 2078B 2 CC05 2021 2021-08-26 COND 9.7645702533 #> 2624 2078B 2 CC05 2021 2021-08-26 DO 0.7030975114 #> 2625 2078B 2 CC05 2021 2021-08-26 DOSAT 3.3141860047 #> 2626 2078B 2 CC05 2021 2021-08-26 NO23 -5.5214609179 U #> 2627 2078B 2 CC05 2021 2021-08-26 SALIN 2.3223877203 #> 2628 2078B 2 CC05 2021 2021-08-26 TKN 0.2623642645 #> 2629 2078B 2 CC05 2021 2021-08-26 TN 0.2639015438 + #> 2630 2078B 2 CC05 2021 2021-08-26 TP -2.9565115604 #> 2631 2078B 2 CC05 2021 2021-08-26 TSS 2.3025850930 I #> 2632 2078B 2 CC05 2021 2021-08-26 TURB 2.3978952728 #> 2633 2078B 2 CC05 2021 2021-09-13 CHLAC 2.8332133441 A #> 2634 2078B 2 CC05 2021 2021-09-13 COND 10.1916695000 #> 2635 2078B 2 CC05 2021 2021-09-13 DO 1.2296405511 #> 2636 2078B 2 CC05 2021 2021-09-13 DOSAT 3.9239515763 #> 2637 2078B 2 CC05 2021 2021-09-13 NO23 -5.5214609179 U #> 2638 2078B 2 CC05 2021 2021-09-13 SALIN 2.7868613815 #> 2639 2078B 2 CC05 2021 2021-09-13 TKN 0.0953101798 #> 2640 2078B 2 CC05 2021 2021-09-13 TN 0.0971267107 + #> 2641 2078B 2 CC05 2021 2021-09-13 TP -2.9957322736 #> 2642 2078B 2 CC05 2021 2021-09-13 TSS 1.6094379124 I #> 2643 2078B 2 CC05 2021 2021-09-13 TURB 1.7578579176 #> 2644 2078B 2 CC05 2021 2021-10-20 CHLAC 2.7725887222 #> 2645 2078B 2 CC05 2021 2021-10-20 COND 10.4756810512 #> 2646 2078B 2 CC05 2021 2021-10-20 DO 0.2700271372 #> 2647 2078B 2 CC05 2021 2021-10-20 DOSAT 2.9391619221 #> 2648 2078B 2 CC05 2021 2021-10-20 NO23 -5.5214609179 U #> 2649 2078B 2 CC05 2021 2021-10-20 SALIN 3.1099534176 #> 2650 2078B 2 CC05 2021 2021-10-20 TKN 0.0953101798 #> 2651 2078B 2 CC05 2021 2021-10-20 TN 0.0971267107 + #> 2652 2078B 2 CC05 2021 2021-10-20 TP -3.1235656451 #> 2653 2078B 2 CC05 2021 2021-10-20 TSS 1.9459101491 I #> 2654 2078B 2 CC05 2021 2021-10-20 TURB 1.4109869737 #> 2655 2078B 2 CC05 2022 2022-04-06 CHLAC 1.8718021769 #> 2656 2078B 2 CC05 2022 2022-04-06 COND 11.0061250625 #> 2657 2078B 2 CC05 2022 2022-04-06 DO 0.6365768291 #> 2658 2078B 2 CC05 2022 2022-04-06 DOSAT 3.3911470458 #> 2659 2078B 2 CC05 2022 2022-04-06 NO23 -5.5214609179 U #> 2660 2078B 2 CC05 2022 2022-04-06 SALIN 3.6980869349 #> 2661 2078B 2 CC05 2022 2022-04-06 TKN -0.0512932944 #> 2662 2078B 2 CC05 2022 2022-04-06 TN -0.0491902442 + #> 2663 2078B 2 CC05 2022 2022-04-06 TP -3.1700856607 #> 2664 2078B 2 CC05 2022 2022-04-06 TSS 1.3862943611 I #> 2665 2078B 2 CC05 2022 2022-04-06 TURB 0.0953101798 #> 2666 2078B 2 CC05 2022 2022-05-10 CHLAC 2.5649493575 #> 2667 2078B 2 CC05 2022 2022-05-10 COND 10.7027274806 #> 2668 2078B 2 CC05 2022 2022-05-10 DO 1.1281710909 #> 2669 2078B 2 CC05 2022 2022-05-10 DOSAT 3.7841896339 #> 2670 2078B 2 CC05 2022 2022-05-10 NO23 -5.5214609179 U #> 2671 2078B 2 CC05 2022 2022-05-10 SALIN 3.3579418730 #> 2672 2078B 2 CC05 2022 2022-05-10 TKN -0.0512932944 #> 2673 2078B 2 CC05 2022 2022-05-10 TN -0.0491902442 + #> 2674 2078B 2 CC05 2022 2022-05-10 TP -3.1010927892 #> 2675 2078B 2 CC05 2022 2022-05-10 TSS 2.1972245773 I #> 2676 2078B 2 CC05 2022 2022-05-10 TURB 1.2237754316 #> 2677 2078B 2 CC05 2019 2019-06-06 CHLAC 0.7419373447 I #> 2678 2078B 2 CC05 2019 2019-06-06 NO23 -5.2983173665 I #> 2679 2078B 2 CC05 2019 2019-06-06 TKN -0.4004775666 #> 2680 2078B 2 CC05 2019 2019-06-06 TN -0.3945251681 + #> 2681 2078B 2 CC05 2019 2019-06-06 TP -3.4420193762 #> 2682 2066 3M CC10 2013 2013-05-28 CHLAC 2.7080502011 #> 2683 2066 3M CC10 2013 2013-05-28 TN 0.3220834992 #> 2684 2066 3M CC10 2013 2013-05-28 TP -2.6172958378 #> 2685 2035 3F CC104 2015 2015-06-04 COND 7.8336002237 #> 2686 2035 3F CC104 2015 2015-06-04 DO 1.6292405397 #> 2687 2035 3F CC104 2015 2015-06-04 DOSAT 4.1108738642 #> 2688 2035 3F CC104 2015 2015-06-04 SALIN 0.2926696140 + #> 2689 2035 3F CC104 2015 2015-08-06 COND 6.3868793194 #> 2690 2035 3F CC104 2015 2015-08-06 DO 1.7047480922 #> 2691 2035 3F CC104 2015 2015-08-06 DOSAT 4.2046926194 #> 2692 2035 3F CC104 2015 2015-08-06 SALIN -1.2729656758 + #> 2693 2035 3F CC104 2015 2015-08-19 COND 6.8351845861 #> 2694 2035 3F CC104 2015 2015-08-19 DO 1.4109869737 #> 2695 2035 3F CC104 2015 2015-08-19 DOSAT 3.9318256327 #> 2696 2035 3F CC104 2015 2015-08-19 SALIN -0.7985076962 + #> 2697 2035 3F CC104 2015 2015-09-15 COND 6.4583382833 #> 2698 2035 3F CC104 2015 2015-09-15 DO 1.6677068206 #> 2699 2035 3F CC104 2015 2015-09-15 DOSAT 4.1896547420 #> 2700 2035 3F CC104 2015 2015-09-15 SALIN -1.2039728043 + #> 2701 2035 3F CC104 2015 2015-11-25 COND 7.2584121506 #> 2702 2035 3F CC104 2015 2015-11-25 DO 1.8082887712 #> 2703 2035 3F CC104 2015 2015-11-25 DOSAT 4.2046926194 #> 2704 2035 3F CC104 2015 2015-11-25 SALIN -0.2231435513 + #> 2705 2035 3F CC104 2015 2015-12-30 COND 7.6563371664 #> 2706 2035 3F CC104 2015 2015-12-30 DO 1.8562979904 #> 2707 2035 3F CC104 2015 2015-12-30 DOSAT 4.3040650932 #> 2708 2035 3F CC104 2015 2015-12-30 SALIN 0.1310282624 + #> 2709 2035 3F CC104 2015 2015-05-21 COND 8.9299648747 #> 2710 2035 3F CC104 2015 2015-05-21 DO 1.6292405397 #> 2711 2035 3F CC104 2015 2015-05-21 DOSAT 4.1743872699 #> 2712 2035 3F CC104 2015 2015-05-21 SALIN 1.3787660947 + #> 2713 2035 3F CC104 2015 2015-06-04 COND 9.1162494486 #> 2714 2035 3F CC104 2015 2015-06-04 DO 1.5686159179 #> 2715 2035 3F CC104 2015 2015-06-04 DOSAT 4.1108738642 #> 2716 2035 3F CC104 2015 2015-06-04 SALIN 1.6054298910 + #> 2717 2035 3F CC104 2015 2015-07-15 COND 7.5559050936 #> 2718 2035 3F CC104 2015 2015-07-15 SALIN -0.0833816089 + #> 2719 2035 3F CC104 2015 2015-08-06 COND 6.8057225534 #> 2720 2035 3F CC104 2015 2015-08-06 DO 1.6486586256 #> 2721 2035 3F CC104 2015 2015-08-06 DOSAT 4.1431347264 #> 2722 2035 3F CC104 2015 2015-08-06 SALIN -0.8209805521 + #> 2723 2035 3F CC104 2015 2015-08-19 COND 6.6200732065 #> 2724 2035 3F CC104 2015 2015-08-19 DO 1.4586150227 #> 2725 2035 3F CC104 2015 2015-08-19 DOSAT 3.9889840466 #> 2726 2035 3F CC104 2015 2015-08-19 SALIN -1.0216512475 + #> 2727 2035 3F CC104 2015 2015-09-15 COND 6.3315018499 #> 2728 2035 3F CC104 2015 2015-09-15 DO 1.6677068206 #> 2729 2035 3F CC104 2015 2015-09-15 DOSAT 4.1588830834 #> 2730 2035 3F CC104 2015 2015-09-15 SALIN -1.3470736480 + #> 2731 2035 3F CC104 2015 2015-11-25 COND 6.9147308927 #> 2732 2035 3F CC104 2015 2015-11-25 DO 2.0281482473 #> 2733 2035 3F CC104 2015 2015-11-25 DOSAT 4.4188406078 #> 2734 2035 3F CC104 2015 2015-11-25 SALIN -0.5798184953 + #> 2735 2035 3F CC104 2015 2015-12-30 COND 7.5267175614 #> 2736 2035 3F CC104 2015 2015-12-30 DO 1.8245492921 #> 2737 2035 3F CC104 2015 2015-12-30 DOSAT 4.2766661190 #> 2738 2035 3F CC104 2015 2015-12-30 SALIN 0.0000000000 + #> 2739 2035 3F CC104 2015 2015-05-21 COND 9.3336193881 #> 2740 2035 3F CC104 2015 2015-05-21 DO 1.4109869737 #> 2741 2035 3F CC104 2015 2015-05-21 DOSAT 4.0073331852 #> 2742 2035 3F CC104 2015 2015-05-21 SALIN 1.7664416612 + #> 2743 2035 3F CC104 2015 2015-06-04 COND 9.1775072149 #> 2744 2035 3F CC104 2015 2015-06-04 DO 1.3350010667 #> 2745 2035 3F CC104 2015 2015-06-04 DOSAT 3.8712010109 #> 2746 2035 3F CC104 2015 2015-06-04 SALIN 1.6677068206 + #> 2747 2035 3F CC104 2015 2015-07-15 COND 7.9024874372 #> 2748 2035 3F CC104 2015 2015-07-15 SALIN 0.2546422184 + #> 2749 2035 3F CC104 2015 2015-08-06 COND 6.7765069924 #> 2750 2035 3F CC104 2015 2015-08-06 DO 1.3350010667 #> 2751 2035 3F CC104 2015 2015-08-06 DOSAT 3.8918202981 #> 2752 2035 3F CC104 2015 2015-08-06 SALIN -0.8915981193 + #> 2753 2035 3F CC104 2015 2015-08-19 COND 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2035 3F CC104 2022 2022-01-24 TN -0.2744368457 + #> 2790 2035 3F CC104 2022 2022-01-24 TP -1.0788096614 #> 2791 2035 3F CC104 2022 2022-01-24 TSS 1.3862943611 I #> 2792 2035 3F CC104 2022 2022-01-24 TURB 2.0541237337 #> 2793 2035 3F CC104 2022 2022-03-03 CHLAC 0.6418538862 I #> 2794 2035 3F CC104 2022 2022-03-03 COLOR 3.4657359028 A #> 2795 2035 3F CC104 2022 2022-03-03 COND 7.7336835708 #> 2796 2035 3F CC104 2022 2022-03-03 DO 1.8991179875 #> 2797 2035 3F CC104 2022 2022-03-03 DOSAT 4.2918283668 #> 2798 2035 3F CC104 2022 2022-03-03 NO23 -2.3538783874 #> 2799 2035 3F CC104 2022 2022-03-03 SALIN 0.1655144385 #> 2800 2035 3F CC104 2022 2022-03-03 TKN -0.4307829161 #> 2801 2035 3F CC104 2022 2022-03-03 TN -0.2943710606 + #> 2802 2035 3F CC104 2022 2022-03-03 TP -0.9416085399 #> 2803 2035 3F CC104 2022 2022-03-03 TSS 1.3862943611 I #> 2804 2035 3F CC104 2022 2022-03-03 TURB 2.2407096893 A #> 2805 2035 3F CC104 2022 2022-05-23 CHLAC 3.6109179126 #> 2806 2035 3F CC104 2022 2022-05-23 COLOR 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2022-03-03 SALIN 1.4770487244 #> 2825 2035 3F CC104 2022 2022-05-23 COND 9.9213274707 #> 2826 2035 3F CC104 2022 2022-05-23 DO 1.2383742310 #> 2827 2035 3F CC104 2022 2022-05-23 DOSAT 3.8877303129 #> 2828 2035 3F CC104 2022 2022-05-23 SALIN 2.4923786646 #> 2829 2035 3F CC104 2022 2022-01-24 COND 8.4487001950 #> 2830 2035 3F CC104 2022 2022-01-24 DO 2.1447610078 #> 2831 2035 3F CC104 2022 2022-01-24 DOSAT 4.4624538838 #> 2832 2035 3F CC104 2022 2022-01-24 SALIN 0.9202827531 #> 2833 2035 3F CC104 2022 2022-03-03 COND 9.6867608690 #> 2834 2035 3F CC104 2022 2022-03-03 DO 1.4516138272 #> 2835 2035 3F CC104 2022 2022-03-03 DOSAT 3.9608131696 #> 2836 2035 3F CC104 2022 2022-03-03 SALIN 2.2449559802 #> 2837 2035 3F CC104 2022 2022-05-23 COND 10.0031066176 #> 2838 2035 3F CC104 2022 2022-05-23 DO 1.0986122887 #> 2839 2035 3F CC104 2022 2022-05-23 DOSAT 3.7518542533 #> 2840 2035 3F CC104 2022 2022-05-23 SALIN 2.9019708937 #> 2841 2035 3F CC104 2013 2013-05-21 COND 7.0379059634 #> 2842 2035 3F CC104 2013 2013-05-21 DO 1.7334238922 #> 2843 2035 3F CC104 2013 2013-05-21 DOSAT 4.1743872699 + #> 2844 2035 3F CC104 2013 2013-05-21 SALIN -0.5621189182 #> 2845 2035 3F CC104 2013 2013-09-25 COND 5.2522734280 #> 2846 2035 3F CC104 2013 2013-09-25 DO 1.5282278570 #> 2847 2035 3F CC104 2013 2013-09-25 DOSAT 4.0055133485 + #> 2848 2035 3F CC104 2013 2013-09-25 SALIN -2.4079456087 #> 2849 2035 3F CC104 2014 2014-05-28 COND 7.0817085861 #> 2850 2035 3F CC104 2014 2014-05-28 DO 1.5560371357 #> 2851 2035 3F CC104 2014 2014-05-28 DOSAT 4.0145795938 + #> 2852 2035 3F CC104 2014 2014-05-28 SALIN -0.5276327421 #> 2853 2035 3F CC104 2014 2014-10-02 COND 5.9506425526 #> 2854 2035 3F CC104 2014 2014-10-02 DO 1.6770965609 #> 2855 2035 3F CC104 2014 2014-10-02 DOSAT 4.2061840440 + #> 2856 2035 3F CC104 2014 2014-10-02 SALIN -1.7147984281 #> 2857 2035 3F CC104 2016 2016-06-02 COND 6.8068293604 #> 2858 2035 3F CC104 2016 2016-06-02 DO 1.3837912309 #> 2859 2035 3F CC104 2016 2016-06-02 DOSAT 3.8501476017 + #> 2860 2035 3F CC104 2016 2016-06-02 SALIN -0.8209805521 #> 2861 2035 3F CC104 2016 2016-09-21 COND 6.3664704477 #> 2862 2035 3F CC104 2016 2016-09-21 DO 1.6389967147 #> 2863 2035 3F CC104 2016 2016-09-21 DOSAT 4.1697612015 + #> 2864 2035 3F CC104 2016 2016-09-21 SALIN -1.2729656758 #> 2865 2035 3F CC104 2017 2017-05-09 COND 6.9791452751 #> 2866 2035 3F CC104 2017 2017-05-09 DO 1.4134230285 #> 2867 2035 3F CC104 2017 2017-05-09 DOSAT 3.8220982979 + #> 2868 2035 3F CC104 2017 2017-05-09 SALIN -0.6348782724 #> 2869 2035 3F CC104 2017 2017-09-27 COND 6.1654178542 #> 2870 2035 3F CC104 2017 2017-09-27 DO 1.6937790609 #> 2871 2035 3F CC104 2017 2017-09-27 DOSAT 4.2195077052 + #> 2872 2035 3F CC104 2017 2017-09-27 SALIN -1.4696759701 #> 2873 2035 3F CC104 2018 2018-06-04 COND 6.2672005485 #> 2874 2035 3F CC104 2018 2018-06-04 DO 1.6808279085 #> 2875 2035 3F CC104 2018 2018-06-04 DOSAT 4.2209772132 + #> 2876 2035 3F CC104 2018 2018-06-04 SALIN -1.3862943611 #> 2877 2035 3F CC104 2018 2018-09-12 COND 6.2265366693 #> 2878 2035 3F CC104 2018 2018-09-12 DO 1.7749523509 #> 2879 2035 3F CC104 2018 2018-09-12 DOSAT 4.3040650932 + #> 2880 2035 3F CC104 2018 2018-09-12 SALIN -1.4271163556 #> 2881 2045 3M CC15 2018 2018-03-07 CHLAC 2.2617630985 #> 2882 2045 3M CC15 2018 2018-03-07 COND 10.0150289273 #> 2883 2045 3M CC15 2018 2018-03-07 DO 2.0281482473 #> 2884 2045 3M CC15 2018 2018-03-07 DOSAT 4.5475410732 #> 2885 2045 3M CC15 2018 2018-03-07 NO23 -5.5214609179 U #> 2886 2045 3M CC15 2018 2018-03-07 SALIN 2.6595599919 + #> 2887 2045 3M CC15 2018 2018-03-07 TKN -0.1743533871 #> 2888 2045 3M CC15 2018 2018-03-07 TN -0.1719752647 + #> 2889 2045 3M CC15 2018 2018-03-07 TP -1.8325814637 #> 2890 2045 3M CC15 2018 2018-03-07 TSS 1.0986122887 U #> 2891 2045 3M CC15 2018 2018-03-07 TURB 1.2809338455 #> 2892 2045 3M CC15 2018 2018-04-09 CHLAC 1.8870696490 #> 2893 2045 3M CC15 2018 2018-04-09 COND 10.4012279368 #> 2894 2045 3M CC15 2018 2018-04-09 DO 1.7227665977 #> 2895 2045 3M CC15 2018 2018-04-09 DOSAT 4.3438054219 #> 2896 2045 3M CC15 2018 2018-04-09 NO23 -5.5214609179 I #> 2897 2045 3M CC15 2018 2018-04-09 SALIN 3.0017143452 + #> 2898 2045 3M CC15 2018 2018-04-09 TKN -0.2357223335 #> 2899 2045 3M CC15 2018 2018-04-09 TN -0.2306718177 + #> 2900 2045 3M CC15 2018 2018-04-09 TP -1.5606477483 #> 2901 2045 3M CC15 2018 2018-04-09 TSS 2.7080502011 #> 2902 2045 3M CC15 2018 2018-04-09 TURB 1.8718021769 A #> 2903 2045 3M CC15 2018 2018-05-24 CHLAC 2.3978952728 #> 2904 2045 3M CC15 2018 2018-05-24 COND 9.3056505518 #> 2905 2045 3M CC15 2018 2018-05-24 DO 1.9198594719 #> 2906 2045 3M CC15 2018 2018-05-24 DOSAT 4.4589876758 #> 2907 2045 3M CC15 2018 2018-05-24 NO23 -3.3524072175 #> 2908 2045 3M CC15 2018 2018-05-24 SALIN 1.7833912196 + #> 2909 2045 3M CC15 2018 2018-05-24 TKN -0.1392620673 #> 2910 2045 3M CC15 2018 2018-05-24 TN -0.0998203353 + #> 2911 2045 3M CC15 2018 2018-05-24 TP -1.6094379124 #> 2912 2045 3M CC15 2018 2018-05-24 TSS 1.7917594692 I #> 2913 2045 3M CC15 2018 2018-05-24 TURB 1.3350010667 #> 2914 2045 3M CC15 2018 2018-05-24 SALIN 1.8991179875 + #> 2915 2045 3M CC15 2018 2018-05-24 COND 9.4091912307 #> 2916 2045 3M CC15 2018 2018-05-24 DO 1.7833912196 #> 2917 2045 3M CC15 2018 2018-05-24 DOSAT 4.3630986248 #> 2918 2045 3M CC15 2018 2018-05-24 CHLAC 2.2925347571 #> 2919 2045 3M CC15 2018 2018-05-24 COND 9.3056505518 #> 2920 2045 3M CC15 2018 2018-05-24 DO 1.9198594719 #> 2921 2045 3M CC15 2018 2018-05-24 DOSAT 4.4589876758 #> 2922 2045 3M CC15 2018 2018-05-24 NO23 -3.4737680745 #> 2923 2045 3M CC15 2018 2018-05-24 SALIN 1.7833912196 + #> 2924 2045 3M CC15 2018 2018-05-24 TKN -0.1053605157 #> 2925 2045 3M CC15 2018 2018-05-24 TN -0.0714960017 + #> 2926 2045 3M CC15 2018 2018-05-24 TP -1.6094379124 #> 2927 2045 3M CC15 2018 2018-05-24 TSS 1.7917594692 I #> 2928 2045 3M CC15 2018 2018-05-24 TURB 1.2237754316 #> 2929 2045 3M CC15 2018 2018-07-23 CHLAC 2.0149030205 #> 2930 2045 3M CC15 2018 2018-07-23 COND 6.5087691370 #> 2931 2045 3M CC15 2018 2018-07-23 DO 1.7800242130 #> 2932 2045 3M CC15 2018 2018-07-23 DOSAT 4.3567088267 #> 2933 2045 3M CC15 2018 2018-07-23 NO23 -1.9661128564 #> 2934 2045 3M CC15 2018 2018-07-23 SALIN -1.1394342832 #> 2935 2045 3M CC15 2018 2018-07-23 TKN 0.1823215568 #> 2936 2045 3M CC15 2018 2018-07-23 TN 0.2926696140 + #> 2937 2045 3M CC15 2018 2018-07-23 TP -1.1394342832 #> 2938 2045 3M CC15 2018 2018-07-23 TSS 1.3862943611 I #> 2939 2045 3M CC15 2018 2018-07-23 TURB 1.3083328197 #> 2940 2045 3M CC15 2018 2018-08-21 CHLAC 2.0794415417 #> 2941 2045 3M CC15 2018 2018-08-21 COND 6.4393503711 #> 2942 2045 3M CC15 2018 2018-08-21 DO 1.6601310267 #> 2943 2045 3M CC15 2018 2018-08-21 DOSAT 4.2341065046 #> 2944 2045 3M CC15 2018 2018-08-21 NO23 -2.6736487744 #> 2945 2045 3M CC15 2018 2018-08-21 SALIN -1.2039728043 #> 2946 2045 3M CC15 2018 2018-08-21 TKN 0.0953101798 #> 2947 2045 3M CC15 2018 2018-08-21 TN 0.1561486825 + #> 2948 2045 3M CC15 2018 2018-08-21 TP -1.2378743560 #> 2949 2045 3M CC15 2018 2018-08-21 TSS 1.0986122887 I #> 2950 2045 3M CC15 2018 2018-08-21 TURB 1.0986122887 #> 2951 2045 3M CC15 2018 2018-08-21 COND 6.4264884575 #> 2952 2045 3M CC15 2018 2018-08-21 DO 1.6114359151 #> 2953 2045 3M CC15 2018 2018-08-21 DOSAT 4.1774594689 #> 2954 2045 3M CC15 2018 2018-08-21 SALIN -1.2039728043 #> 2955 2045 3M CC15 2019 2019-02-07 CHLAC 3.2188758249 A #> 2956 2045 3M CC15 2019 2019-02-07 COND 8.6916505732 #> 2957 2045 3M CC15 2019 2019-02-07 NO23 -5.1159958098 I #> 2958 2045 3M CC15 2019 2019-02-07 SALIN 1.1755733298 #> 2959 2045 3M CC15 2019 2019-02-07 TKN 0.0953101798 #> 2960 2045 3M CC15 2019 2019-02-07 TN 0.0989399479 + #> 2961 2045 3M CC15 2019 2019-02-07 TP -1.6607312068 #> 2962 2045 3M CC15 2019 2019-02-07 TSS 2.3025850930 I #> 2963 2045 3M CC15 2019 2019-02-07 TURB 2.0281482473 #> 2964 2045 3M CC15 2019 2019-03-13 CHLAC 1.8870696490 #> 2965 2045 3M CC15 2019 2019-03-13 COND 9.4304392931 #> 2966 2045 3M CC15 2019 2019-03-13 DO 1.8961194846 #> 2967 2045 3M CC15 2019 2019-03-13 DOSAT 4.4188406078 #> 2968 2045 3M CC15 2019 2019-03-13 NO23 -5.2983173665 I #> 2969 2045 3M CC15 2019 2019-03-13 SALIN 1.9657127764 #> 2970 2045 3M CC15 2019 2019-03-13 TKN -0.1625189295 #> 2971 2045 3M CC15 2019 2019-03-13 TN -0.1578240852 + #> 2972 2045 3M CC15 2019 2019-03-13 TP -1.8325814637 #> 2973 2045 3M CC15 2019 2019-03-13 TSS 2.0794415417 I #> 2974 2045 3M CC15 2019 2019-03-13 TURB 1.5892352051 #> 2975 2045 3M CC15 2019 2019-04-23 CHLAC 1.7749523509 #> 2976 2045 3M CC15 2019 2019-04-23 COND 9.9110588180 #> 2977 2045 3M CC15 2019 2019-04-23 DO 1.8562979904 #> 2978 2045 3M CC15 2019 2019-04-23 DOSAT 4.3845235149 #> 2979 2045 3M CC15 2019 2019-04-23 NO23 -5.5214609179 U #> 2980 2045 3M CC15 2019 2019-04-23 SALIN 2.4882344399 #> 2981 2045 3M CC15 2019 2019-04-23 TKN -0.2744368457 #> 2982 2045 3M CC15 2019 2019-04-23 TN -0.2718087233 + #> 2983 2045 3M CC15 2019 2019-04-23 TP -1.6607312068 #> 2984 2045 3M CC15 2019 2019-04-23 TSS 2.0794415417 I #> 2985 2045 3M CC15 2019 2019-04-23 TURB 1.4586150227 #> 2986 2045 3M CC15 2019 2019-04-23 CHLAC 1.1631508098 #> 2987 2045 3M CC15 2019 2019-04-23 NO23 -5.5214609179 U #> 2988 2045 3M CC15 2019 2019-04-23 TKN -0.2876820725 #> 2989 2045 3M CC15 2019 2019-04-23 TN -0.2850189550 + #> 2990 2045 3M CC15 2019 2019-04-23 TP -1.7147984281 #> 2991 2045 3M CC15 2019 2019-04-23 TSS 1.9459101491 I #> 2992 2045 3M CC15 2019 2019-04-23 TURB 1.0296194172 #> 2993 2045 3M CC15 2019 2019-07-22 CHLAC 2.4849066498 #> 2994 2045 3M CC15 2019 2019-07-22 COND 8.5083542427 #> 2995 2045 3M CC15 2019 2019-07-22 DO 1.7227665977 #> 2996 2045 3M CC15 2019 2019-07-22 DOSAT 4.3174881135 #> 2997 2045 3M CC15 2019 2019-07-22 NO23 -3.5065578973 #> 2998 2045 3M CC15 2019 2019-07-22 SALIN 0.9707789172 #> 2999 2045 3M CC15 2019 2019-07-22 TKN -0.0512932944 #> 3000 2045 3M CC15 2019 2019-07-22 TN -0.0202027073 + #> 3001 2045 3M CC15 2019 2019-07-22 TP -1.1086626245 #> 3002 2045 3M CC15 2019 2019-07-22 TSS 1.6094379124 I #> 3003 2045 3M CC15 2019 2019-07-22 TURB 1.3862943611 #> 3004 2045 3M CC15 2019 2019-09-04 COND 7.2896105215 #> 3005 2045 3M CC15 2019 2019-09-04 DO 1.6213664833 #> 3006 2045 3M CC15 2019 2019-09-04 DOSAT 4.2061840440 #> 3007 2045 3M CC15 2019 2019-09-04 NO23 -2.4191189092 #> 3008 2045 3M CC15 2019 2019-09-04 SALIN -0.3147107448 #> 3009 2045 3M CC15 2019 2019-09-04 TKN 0.1823215568 #> 3010 2045 3M CC15 2019 2019-09-04 TN 0.2538667240 + #> 3011 2045 3M CC15 2019 2019-09-04 TP -0.9675840263 #> 3012 2045 3M CC15 2019 2019-09-04 TSS 1.0986122887 I #> 3013 2045 3M CC15 2019 2019-09-04 TURB 1.0986122887 #> 3014 2045 3M CC15 2020 2020-02-18 CHLAC 2.7080502011 #> 3015 2045 3M CC15 2020 2020-02-18 COND 10.0136863448 #> 3016 2045 3M CC15 2020 2020-02-18 DO 1.9358598132 #> 3017 2045 3M CC15 2020 2020-02-18 DOSAT 4.5272086445 #> 3018 2045 3M CC15 2020 2020-02-18 NO23 -4.8283137373 I #> 3019 2045 3M CC15 2020 2020-02-18 SALIN 2.5967461315 #> 3020 2045 3M CC15 2020 2020-02-18 TKN -0.1165338163 #> 3021 2045 3M CC15 2020 2020-02-18 TN -0.1120495038 + #> 3022 2045 3M CC15 2020 2020-02-18 TP -1.6094379124 #> 3023 2045 3M CC15 2020 2020-02-18 TSS 2.7080502011 #> 3024 2045 3M CC15 2020 2020-02-18 TURB 1.7227665977 #> 3025 2045 3M CC15 2020 2020-02-18 COND 10.0120728629 #> 3026 2045 3M CC15 2020 2020-02-18 DO 1.9227877316 #> 3027 2045 3M CC15 2020 2020-02-18 DOSAT 4.5086592856 #> 3028 2045 3M CC15 2020 2020-02-18 SALIN 2.5952547070 #> 3029 2045 3M CC15 2020 2020-06-09 CHLAC 2.4849066498 #> 3030 2045 3M CC15 2020 2020-06-09 COND 9.2513863414 #> 3031 2045 3M CC15 2020 2020-06-09 DO 1.9315214116 #> 3032 2045 3M CC15 2020 2020-06-09 DOSAT 4.5239601306 #> 3033 2045 3M CC15 2020 2020-06-09 NO23 -3.3813947544 #> 3034 2045 3M CC15 2020 2020-06-09 SALIN 1.7664416612 #> 3035 2045 3M CC15 2020 2020-06-09 TKN -0.0304592075 #> 3036 2045 3M CC15 2020 2020-06-09 TN 0.0039920213 + #> 3037 2045 3M CC15 2020 2020-06-09 TP -1.4696759701 #> 3038 2045 3M CC15 2020 2020-06-09 TSS 1.0986122887 I #> 3039 2045 3M CC15 2020 2020-06-09 TURB 0.9162907319 #> 3040 2045 3M CC15 2020 2020-06-09 COND 9.5815590414 #> 3041 2045 3M CC15 2020 2020-06-09 DO 1.6544112781 #> 3042 2045 3M CC15 2020 2020-06-09 DOSAT 4.2076732475 #> 3043 2045 3M CC15 2020 2020-06-09 SALIN 2.1552445051 #> 3044 2045 3M CC15 2020 2020-08-10 COND 9.2688922589 #> 3045 2045 3M CC15 2020 2020-08-10 DO 1.6370530795 #> 3046 2045 3M CC15 2020 2020-08-10 DOSAT 4.2710950740 #> 3047 2045 3M CC15 2020 2020-08-10 SALIN -1.4567168254 #> 3048 2045 3M CC15 2020 2020-08-10 COND 9.4812068515 #> 3049 2045 3M CC15 2020 2020-08-10 DO 1.4398351280 #> 3050 2045 3M CC15 2020 2020-08-10 DOSAT 4.0758410907 #> 3051 2045 3M CC15 2020 2020-08-10 SALIN 0.2207406667 #> 3052 2045 3M CC15 2020 2020-09-22 CHLAC 2.2192034841 #> 3053 2045 3M CC15 2020 2020-09-22 COND 6.5750758406 #> 3054 2045 3M CC15 2020 2020-09-22 DO 1.7934247485 #> 3055 2045 3M CC15 2020 2020-09-22 DOSAT 4.3359826962 #> 3056 2045 3M CC15 2020 2020-09-22 NO23 -2.7968814148 #> 3057 2045 3M CC15 2020 2020-09-22 SALIN -1.0498221245 #> 3058 2045 3M CC15 2020 2020-09-22 TKN 0.2623642645 #> 3059 2045 3M CC15 2020 2020-09-22 TN 0.3082197237 + #> 3060 2045 3M CC15 2020 2020-09-22 TP -0.9942522733 #> 3061 2045 3M CC15 2020 2020-09-22 TSS 1.3862943611 I #> 3062 2045 3M CC15 2020 2020-09-22 TURB 1.2809338455 #> 3063 2045 3M CC15 2020 2020-10-20 CHLAC 3.0445224377 #> 3064 2045 3M CC15 2020 2020-10-20 COND 8.3209349689 #> 3065 2045 3M CC15 2020 2020-10-20 DO 1.7119945008 #> 3066 2045 3M CC15 2020 2020-10-20 DOSAT 4.2640873368 #> 3067 2045 3M CC15 2020 2020-10-20 NO23 -2.5010360317 #> 3068 2045 3M CC15 2020 2020-10-20 SALIN 0.7747271676 #> 3069 2045 3M CC15 2020 2020-10-20 TKN 0.2623642645 #> 3070 2045 3M CC15 2020 2020-10-20 TN 0.3235317253 + #> 3071 2045 3M CC15 2020 2020-10-20 TP -0.9942522733 #> 3072 2045 3M CC15 2020 2020-10-20 TSS 1.6094379124 I #> 3073 2045 3M CC15 2020 2020-10-20 TURB 1.2809338455 #> 3074 2045 3M CC15 2020 2020-12-14 CHLAC 2.6390573296 #> 3075 2045 3M CC15 2020 2020-12-14 COND 9.2314166976 #> 3076 2045 3M CC15 2020 2020-12-14 DO 2.0930978681 #> 3077 2045 3M CC15 2020 2020-12-14 DOSAT 4.5695430083 #> 3078 2045 3M CC15 2020 2020-12-14 NO23 -4.9618451299 I #> 3079 2045 3M CC15 2020 2020-12-14 SALIN 1.7526720805 #> 3080 2045 3M CC15 2020 2020-12-14 TKN 0.0000000000 #> 3081 2045 3M CC15 2020 2020-12-14 TN 0.0039920213 + #> 3082 2045 3M CC15 2020 2020-12-14 TP -1.4696759701 #> 3083 2045 3M CC15 2020 2020-12-14 TSS 1.6094379124 I #> 3084 2045 3M CC15 2020 2020-12-14 TURB 1.3609765531 A #> 3085 2045 3M CC15 2021 2021-02-03 CHLAC 1.7404661748 #> 3086 2045 3M CC15 2021 2021-02-03 COND 9.8506140629 #> 3087 2045 3M CC15 2021 2021-02-03 DO 2.1424163408 #> 3088 2045 3M CC15 2021 2021-02-03 DOSAT 4.5528237056 #> 3089 2045 3M CC15 2021 2021-02-03 NO23 -5.5214609179 U #> 3090 2045 3M CC15 2021 2021-02-03 SALIN 2.4248027257 #> 3091 2045 3M CC15 2021 2021-02-03 TKN -0.3424903089 #> 3092 2045 3M CC15 2021 2021-02-03 TN -0.3396773676 + #> 3093 2045 3M CC15 2021 2021-02-03 TP -1.9661128564 #> 3094 2045 3M CC15 2021 2021-02-03 TSS 1.3862943611 I #> 3095 2045 3M CC15 2021 2021-02-03 TURB 1.0296194172 #> 3096 2045 3M CC15 2021 2021-03-09 CHLAC 2.4849066498 #> 3097 2045 3M CC15 2021 2021-03-09 COND 9.8787336881 #> 3098 2045 3M CC15 2021 2021-03-09 DO 2.1690537004 #> 3099 2045 3M CC15 2021 2021-03-09 DOSAT 4.6510991179 #> 3100 2045 3M CC15 2021 2021-03-09 NO23 -5.5214609179 I #> 3101 2045 3M CC15 2021 2021-03-09 SALIN 2.4544474423 #> 3102 2045 3M CC15 2021 2021-03-09 TKN 0.0000000000 #> 3103 2045 3M CC15 2021 2021-03-09 TN 0.0039920213 + #> 3104 2045 3M CC15 2021 2021-03-09 TP -1.4696759701 #> 3105 2045 3M CC15 2021 2021-03-09 TSS 3.2958368660 #> 3106 2045 3M CC15 2021 2021-03-09 TURB 2.3978952728 A #> 3107 2045 3M CC15 2021 2021-05-05 CHLAC 1.8082887712 #> 3108 2045 3M CC15 2021 2021-05-05 COND 10.2487071336 #> 3109 2045 3M CC15 2021 2021-05-05 DO 1.8082887712 #> 3110 2045 3M CC15 2021 2021-05-05 DOSAT 4.4986979415 #> 3111 2045 3M CC15 2021 2021-05-05 NO23 -5.5214609179 U #> 3112 2045 3M CC15 2021 2021-05-05 SALIN 2.8489708922 #> 3113 2045 3M CC15 2021 2021-05-05 TKN -0.2231435513 #> 3114 2045 3M CC15 2021 2021-05-05 TN -0.2206466711 + #> 3115 2045 3M CC15 2021 2021-05-05 TP -1.6094379124 #> 3116 2045 3M CC15 2021 2021-05-05 TSS 1.9459101491 I #> 3117 2045 3M CC15 2021 2021-05-05 TURB 1.3350010667 #> 3118 2045 3M CC15 2021 2021-06-03 CHLAC 1.8245492921 #> 3119 2045 3M CC15 2021 2021-06-03 COND 10.3770473511 #> 3120 2045 3M CC15 2021 2021-06-03 DO 1.7715567619 #> 3121 2045 3M CC15 2021 2021-06-03 DOSAT 4.4331949212 #> 3122 2045 3M CC15 2021 2021-06-03 NO23 -5.5214609179 U #> 3123 2045 3M CC15 2021 2021-06-03 SALIN 2.9937302709 #> 3124 2045 3M CC15 2021 2021-06-03 TKN -0.1743533871 #> 3125 2045 3M CC15 2021 2021-06-03 TN -0.1719752647 + #> 3126 2045 3M CC15 2021 2021-06-03 TP -1.5606477483 #> 3127 2045 3M CC15 2021 2021-06-03 TSS 1.7917594692 I #> 3128 2045 3M CC15 2021 2021-06-03 TURB 1.2237754316 #> 3129 2045 3M CC15 2021 2021-07-01 CHLAC 2.1860512767 #> 3130 2045 3M CC15 2021 2021-07-01 COND 10.1292277297 #> 3131 2045 3M CC15 2021 2021-07-01 DO 1.7351891177 #> 3132 2045 3M CC15 2021 2021-07-01 DOSAT 4.3541414312 #> 3133 2045 3M CC15 2021 2021-07-01 NO23 -5.5214609179 U #> 3134 2045 3M CC15 2021 2021-07-01 SALIN 2.7232671669 #> 3135 2045 3M CC15 2021 2021-07-01 TKN -0.4155154440 #> 3136 2045 3M CC15 2021 2021-07-01 TN -0.4124897230 + #> 3137 2045 3M CC15 2021 2021-07-01 TP -1.5606477483 #> 3138 2045 3M CC15 2021 2021-07-01 TSS 1.0986122887 U #> 3139 2045 3M CC15 2021 2021-07-01 TURB 1.3083328197 #> 3140 2045 3M CC15 2021 2021-07-29 CHLAC 1.5892352051 #> 3141 2045 3M CC15 2021 2021-07-29 COND 7.4764723812 #> 3142 2045 3M CC15 2021 2021-07-29 DO 1.4303112465 #> 3143 2045 3M CC15 2021 2021-07-29 DOSAT 4.0145795938 #> 3144 2045 3M CC15 2021 2021-07-29 NO23 -2.4769384801 #> 3145 2045 3M CC15 2021 2021-07-29 SALIN -0.1165338163 #> 3146 2045 3M CC15 2021 2021-07-29 TKN 0.3364722366 #> 3147 2045 3M CC15 2021 2021-07-29 TN 0.3947411447 + #> 3148 2045 3M CC15 2021 2021-07-29 TP -0.4780358009 #> 3149 2045 3M CC15 2021 2021-07-29 TSS 1.7917594692 I #> 3150 2045 3M CC15 2021 2021-07-29 TURB 1.6292405397 #> 3151 2045 3M CC15 2021 2021-08-25 CHLAC 2.7725887222 #> 3152 2045 3M CC15 2021 2021-08-25 COND 6.9107507880 #> 3153 2045 3M CC15 2021 2021-08-25 DO 1.3376291891 #> 3154 2045 3M CC15 2021 2021-08-25 DOSAT 3.9120230054 #> 3155 2045 3M CC15 2021 2021-08-25 NO23 -2.9565115604 #> 3156 2045 3M CC15 2021 2021-08-25 SALIN -0.7133498879 #> 3157 2045 3M CC15 2021 2021-08-25 TKN 0.0953101798 #> 3158 2045 3M CC15 2021 2021-08-25 TN 0.1414995623 + #> 3159 2045 3M CC15 2021 2021-08-25 TP -0.8915981193 #> 3160 2045 3M CC15 2021 2021-08-25 TSS 1.0986122887 I #> 3161 2045 3M CC15 2021 2021-08-25 TURB 1.0647107370 #> 3162 2045 3M CC15 2021 2021-09-23 CHLAC 2.2300144002 #> 3163 2045 3M CC15 2021 2021-09-23 COND 6.2653012127 #> 3164 2045 3M CC15 2021 2021-09-23 DO 1.4060969884 #> 3165 2045 3M CC15 2021 2021-09-23 DOSAT 3.9550824949 #> 3166 2045 3M CC15 2021 2021-09-23 NO23 -3.0365542681 #> 3167 2045 3M CC15 2021 2021-09-23 SALIN -1.3862943611 #> 3168 2045 3M CC15 2021 2021-09-23 TKN 0.0953101798 #> 3169 2045 3M CC15 2021 2021-09-23 TN 0.1380212979 + #> 3170 2045 3M CC15 2021 2021-09-23 TP -1.3093333200 #> 3171 2045 3M CC15 2021 2021-09-23 TSS 1.3862943611 I #> 3172 2045 3M CC15 2021 2021-09-23 TURB 1.2527629685 #> 3173 2045 3M CC15 2021 2021-10-21 CHLAC 3.5263605246 #> 3174 2045 3M CC15 2021 2021-10-21 COND 8.7135820054 #> 3175 2045 3M CC15 2021 2021-10-21 DO 1.7732559977 #> 3176 2045 3M CC15 2021 2021-10-21 DOSAT 4.2918283668 #> 3177 2045 3M CC15 2021 2021-10-21 NO23 -2.9957322736 #> 3178 2045 3M CC15 2021 2021-10-21 SALIN 1.1939224685 #> 3179 2045 3M CC15 2021 2021-10-21 TKN 0.2623642645 #> 3180 2045 3M CC15 2021 2021-10-21 TN 0.3001045925 + #> 3181 2045 3M CC15 2021 2021-10-21 TP -1.1711829815 #> 3182 2045 3M CC15 2021 2021-10-21 TSS 1.6094379124 I #> 3183 2045 3M CC15 2021 2021-10-21 TURB 1.2809338455 #> 3184 2045 3M CC15 2021 2021-11-22 COND 9.2692694395 #> 3185 2045 3M CC15 2021 2021-11-22 DO 1.9516081702 #> 3186 2045 3M CC15 2021 2021-11-22 DOSAT 4.4647580323 #> 3187 2045 3M CC15 2021 2021-11-22 NO23 -4.7105307016 I #> 3188 2045 3M CC15 2021 2021-11-22 SALIN 1.7917594692 #> 3189 2045 3M CC15 2021 2021-11-22 TKN -0.1863295782 #> 3190 2045 3M CC15 2021 2021-11-22 TN -0.1815218766 + #> 3191 2045 3M CC15 2021 2021-11-22 TP -1.7147984281 #> 3192 2045 3M CC15 2021 2021-11-22 TSS 1.0986122887 I #> 3193 2045 3M CC15 2021 2021-11-22 TURB 0.9932517730 #> 3194 2045 3M CC15 2022 2022-02-22 CHLAC 1.5040773968 #> 3195 2045 3M CC15 2022 2022-02-22 COND 10.3013572215 #> 3196 2045 3M CC15 2022 2022-02-22 DO 1.9169226122 #> 3197 2045 3M CC15 2022 2022-02-22 DOSAT 4.4986979415 #> 3198 2045 3M CC15 2022 2022-02-22 NO23 -5.5214609179 U #> 3199 2045 3M CC15 2022 2022-02-22 SALIN 2.9139797717 #> 3200 2045 3M CC15 2022 2022-02-22 TKN -0.3285040670 #> 3201 2045 3M CC15 2022 2022-02-22 TN -0.3257301401 + #> 3202 2045 3M CC15 2022 2022-02-22 TP -2.0402208285 #> 3203 2045 3M CC15 2022 2022-02-22 TSS 2.3978952728 #> 3204 2045 3M CC15 2022 2022-02-22 TURB 1.3083328197 #> 3205 2045 3M CC15 2022 2022-04-20 CHLAC 0.4700036292 U #> 3206 2045 3M CC15 2022 2022-04-20 COND 10.5349454823 #> 3207 2045 3M CC15 2022 2022-04-20 DO 1.6919391339 #> 3208 2045 3M CC15 2022 2022-04-20 DOSAT 4.2972854062 #> 3209 2045 3M CC15 2022 2022-04-20 NO23 -5.5214609179 U #> 3210 2045 3M CC15 2022 2022-04-20 SALIN 3.1722034167 #> 3211 2045 3M CC15 2022 2022-04-20 TKN -0.1508228897 #> 3212 2045 3M CC15 2022 2022-04-20 TN -0.1485000083 + #> 3213 2045 3M CC15 2022 2022-04-20 TP -1.9661128564 #> 3214 2045 3M CC15 2022 2022-04-20 TSS 2.5649493575 #> 3215 2045 3M CC15 2022 2022-04-20 TURB 1.8082887712 #> 3216 2043 3M CC16 2013 2013-02-26 CHLAC 2.9444389792 #> 3217 2043 3M CC16 2013 2013-02-26 COND 10.3228226922 #> 3218 2043 3M CC16 2013 2013-02-26 DO 1.7833912196 #> 3219 2043 3M CC16 2013 2013-02-26 DOSAT 4.3894986495 #> 3220 2043 3M CC16 2013 2013-02-26 NO23 -5.5214609179 U #> 3221 2043 3M CC16 2013 2013-02-26 SALIN 2.9301265165 + #> 3222 2043 3M CC16 2013 2013-02-26 TKN -0.0408219945 #> 3223 2043 3M CC16 2013 2013-02-26 TN -0.0387408283 + #> 3224 2043 3M CC16 2013 2013-02-26 TP -2.2072749132 #> 3225 2043 3M CC16 2013 2013-02-26 TSS 2.1972245773 I #> 3226 2043 3M CC16 2013 2013-02-26 TURB 1.6863989536 #> 3227 2043 3M CC16 2013 2013-04-08 CHLAC 2.9444389792 #> 3228 2043 3M CC16 2013 2013-04-08 COND 10.2957323225 #> 3229 2043 3M CC16 2013 2013-04-08 DO 2.0955609236 #> 3230 2043 3M CC16 2013 2013-04-08 DOSAT 4.6913478822 #> 3231 2043 3M CC16 2013 2013-04-08 NO23 -4.9618451299 I #> 3232 2043 3M CC16 2013 2013-04-08 SALIN 2.9096295745 + #> 3233 2043 3M CC16 2013 2013-04-08 TKN -0.0833816089 #> 3234 2043 3M CC16 2013 2013-04-08 TN -0.0790432073 + #> 3235 2043 3M CC16 2013 2013-04-08 TP -1.9661128564 #> 3236 2043 3M CC16 2013 2013-04-08 TSS 2.4849066498 #> 3237 2043 3M CC16 2013 2013-04-08 TURB 2.0014800002 #> 3238 2043 3M CC16 2013 2013-07-02 CHLAC 2.2300144002 #> 3239 2043 3M CC16 2013 2013-07-02 COND 7.4798641312 #> 3240 2043 3M CC16 2013 2013-07-02 DO 1.6114359151 #> 3241 2043 3M CC16 2013 2013-07-02 DOSAT 4.1351665567 #> 3242 2043 3M CC16 2013 2013-07-02 NO23 -3.7297014486 #> 3243 2043 3M CC16 2013 2013-07-02 SALIN -0.1392620673 + #> 3244 2043 3M CC16 2013 2013-07-02 TKN -0.0304592075 #> 3245 2043 3M CC16 2013 2013-07-02 TN -0.0060180723 + #> 3246 2043 3M CC16 2013 2013-07-02 TP -1.5606477483 #> 3247 2043 3M CC16 2013 2013-07-02 TSS 2.5649493575 #> 3248 2043 3M CC16 2013 2013-07-02 TURB 1.9169226122 #> 3249 2043 3M CC16 2013 2013-02-26 CHLAC 2.7080502011 #> 3250 2043 3M CC16 2013 2013-02-26 COND 10.4025037183 #> 3251 2043 3M CC16 2013 2013-02-26 DO 1.8405496334 #> 3252 2043 3M CC16 2013 2013-02-26 DOSAT 4.4612998156 #> 3253 2043 3M CC16 2013 2013-02-26 NO23 -3.9120230054 U #> 3254 2043 3M CC16 2013 2013-02-26 SALIN 3.0116056227 + #> 3255 2043 3M CC16 2013 2013-02-26 TKN -0.1278333715 #> 3256 2043 3M CC16 2013 2013-02-26 TN -0.1165338163 + #> 3257 2043 3M CC16 2013 2013-02-26 TP -1.8325814637 #> 3258 2043 3M CC16 2013 2013-02-26 TSS 2.6390573296 #> 3259 2043 3M CC16 2013 2013-02-26 TURB 2.0412203289 A #> 3260 2043 3M CC16 2013 2013-04-08 CHLAC 2.2407096893 #> 3261 2043 3M CC16 2013 2013-04-08 COND 10.3623670373 #> 3262 2043 3M CC16 2013 2013-04-08 DO 2.1871742415 #> 3263 2043 3M CC16 2013 2013-04-08 DOSAT 4.8023803553 #> 3264 2043 3M CC16 2013 2013-04-08 NO23 -4.5098600062 #> 3265 2043 3M CC16 2013 2013-04-08 SALIN 2.9678470701 + #> 3266 2043 3M CC16 2013 2013-04-08 TKN -0.2231435513 #> 3267 2043 3M CC16 2013 2013-04-08 TN -0.2094872249 + #> 3268 2043 3M CC16 2013 2013-04-08 TP -2.1202635362 #> 3269 2043 3M CC16 2013 2013-04-08 TSS 2.0794415417 I #> 3270 2043 3M CC16 2013 2013-04-08 TURB 1.3862943611 #> 3271 2043 3M CC16 2013 2013-07-02 CHLAC 2.6390573296 A #> 3272 2043 3M CC16 2013 2013-07-02 COND 6.1025585946 #> 3273 2043 3M CC16 2013 2013-07-02 DO 1.6253112616 #> 3274 2043 3M CC16 2013 2013-07-02 DOSAT 4.1399550735 #> 3275 2043 3M CC16 2013 2013-07-02 NO23 -3.6496587410 #> 3276 2043 3M CC16 2013 2013-07-02 SALIN -1.5606477483 + #> 3277 2043 3M CC16 2013 2013-07-02 TKN 1.3350010667 #> 3278 2043 3M CC16 2013 2013-07-02 TN 1.3418198710 + #> 3279 2043 3M CC16 2013 2013-07-02 TP -1.7147984281 #> 3280 2043 3M CC16 2013 2013-07-02 TSS 1.9459101491 I #> 3281 2043 3M CC16 2013 2013-07-02 TURB 1.2237754316 #> 3282 2043 3M CC16 2013 2013-02-26 CHLAC 2.1282317058 #> 3283 2043 3M CC16 2013 2013-02-26 NO23 -5.5214609179 U #> 3284 2043 3M CC16 2013 2013-02-26 TKN -0.2357223335 #> 3285 2043 3M CC16 2013 2013-02-26 TN -0.2331938872 + #> 3286 2043 3M CC16 2013 2013-02-26 TP -1.7147984281 #> 3287 2043 3M CC16 2013 2013-02-26 TSS 2.6390573296 #> 3288 2043 3M CC16 2013 2013-02-26 TURB 2.0014800002 #> 3289 2043 3M CC16 2013 2013-04-08 CHLAC 2.0014800002 #> 3290 2043 3M CC16 2013 2013-04-08 COND 10.4457827732 #> 3291 2043 3M CC16 2013 2013-04-08 DO 2.1222615389 #> 3292 2043 3M CC16 2013 2013-04-08 DOSAT 4.7229532216 #> 3293 2043 3M CC16 2013 2013-04-08 NO23 -5.1159958098 I #> 3294 2043 3M CC16 2013 2013-04-08 SALIN 3.0914968955 + #> 3295 2043 3M CC16 2013 2013-04-08 TKN -0.1984509387 #> 3296 2043 3M CC16 2013 2013-04-08 TN -0.1935847491 + #> 3297 2043 3M CC16 2013 2013-04-08 TP -2.0402208285 #> 3298 2043 3M CC16 2013 2013-04-08 TSS 2.1972245773 I #> 3299 2043 3M CC16 2013 2013-04-08 TURB 1.6094379124 #> 3300 2043 3M CC16 2013 2013-07-02 CHLAC 3.5835189385 #> 3301 2043 3M CC16 2013 2013-07-02 COND 7.3051882154 #> 3302 2043 3M CC16 2013 2013-07-02 DO 1.6752256530 #> 3303 2043 3M CC16 2013 2013-07-02 DOSAT 4.1956970565 #> 3304 2043 3M CC16 2013 2013-07-02 NO23 -3.8167128256 #> 3305 2043 3M CC16 2013 2013-07-02 SALIN -0.3285040670 + #> 3306 2043 3M CC16 2013 2013-07-02 TKN 0.1823215568 #> 3307 2043 3M CC16 2013 2013-07-02 TN 0.2004888607 + #> 3308 2043 3M CC16 2013 2013-07-02 TP -0.9942522733 #> 3309 2043 3M CC16 2013 2013-07-02 TSS 1.7917594692 I #> 3310 2043 3M CC16 2013 2013-07-02 TURB 1.6486586256 #> 3311 2043 3M CC16 2013 2013-10-07 CHLAC 3.7841896339 A #> 3312 2043 3M CC16 2013 2013-10-07 COND 6.6411821697 #> 3313 2043 3M CC16 2013 2013-10-07 NO23 -4.7105307016 I #> 3314 2043 3M CC16 2013 2013-10-07 SALIN -1.0498221245 + #> 3315 2043 3M CC16 2013 2013-10-07 TKN 0.1823215568 #> 3316 2043 3M CC16 2013 2013-10-07 TN 0.1856493469 + #> 3317 2043 3M CC16 2013 2013-10-07 TP -1.2729656758 #> 3318 2043 3M CC16 2013 2013-10-07 TSS 2.1972245773 I #> 3319 2043 3M CC16 2013 2013-10-07 TURB 1.7404661748 #> 3320 2043 3M CC16 2014 2014-06-26 COND 9.8119751520 #> 3321 2043 3M CC16 2014 2014-06-26 DO 2.4230312461 #> 3322 2043 3M CC16 2014 2014-06-26 DOSAT 5.0801613567 #> 3323 2043 3M CC16 2014 2014-06-26 COND 9.5792797987 #> 3324 2043 3M CC16 2014 2014-06-26 DO 1.2441545940 #> 3325 2043 3M CC16 2014 2014-06-26 DOSAT 3.9852734672 #> 3326 2043 3M CC16 2018 2018-03-07 CHLAC 1.8870696490 #> 3327 2043 3M CC16 2018 2018-03-07 COND 10.1527665775 #> 3328 2043 3M CC16 2018 2018-03-07 DO 1.9878743482 #> 3329 2043 3M CC16 2018 2018-03-07 DOSAT 4.5347477217 #> 3330 2043 3M CC16 2018 2018-03-07 NO23 -5.5214609179 U #> 3331 2043 3M CC16 2018 2018-03-07 SALIN 2.8081971497 + #> 3332 2043 3M CC16 2018 2018-03-07 TKN -0.3424903089 #> 3333 2043 3M CC16 2018 2018-03-07 TN -0.3396773676 + #> 3334 2043 3M CC16 2018 2018-03-07 TP -1.7719568419 #> 3335 2043 3M CC16 2018 2018-03-07 TSS 1.6094379124 I #> 3336 2043 3M CC16 2018 2018-03-07 TURB 1.0986122887 #> 3337 2043 3M CC16 2018 2018-03-07 COND 10.2049615773 #> 3338 2043 3M CC16 2018 2018-03-07 DO 2.0281482473 #> 3339 2043 3M CC16 2018 2018-03-07 DOSAT 4.5653893160 #> 3340 2043 3M CC16 2018 2018-03-07 SALIN 2.8701690506 + #> 3341 2043 3M CC16 2018 2018-04-09 CHLAC 1.9315214116 #> 3342 2043 3M CC16 2018 2018-04-09 COND 10.4399809231 #> 3343 2043 3M CC16 2018 2018-04-09 DO 1.8082887712 #> 3344 2043 3M CC16 2018 2018-04-09 DOSAT 4.4426512565 #> 3345 2043 3M CC16 2018 2018-04-09 NO23 -5.2983173665 I #> 3346 2043 3M CC16 2018 2018-04-09 SALIN 3.0445224377 + #> 3347 2043 3M CC16 2018 2018-04-09 TKN -0.3011050928 #> 3348 2043 3M CC16 2018 2018-04-09 TN -0.2957142441 + #> 3349 2043 3M CC16 2018 2018-04-09 TP -1.6607312068 #> 3350 2043 3M CC16 2018 2018-04-09 TSS 2.0794415417 I #> 3351 2043 3M CC16 2018 2018-04-09 TURB 1.4816045409 #> 3352 2043 3M CC16 2018 2018-05-24 CHLAC 2.2925347571 #> 3353 2043 3M CC16 2018 2018-05-24 COND 9.8201059436 #> 3354 2043 3M CC16 2018 2018-05-24 DO 1.7749523509 #> 3355 2043 3M CC16 2018 2018-05-24 DOSAT 4.3719762988 #> 3356 2043 3M CC16 2018 2018-05-24 NO23 -4.4228486292 #> 3357 2043 3M CC16 2018 2018-05-24 SALIN 2.3360198691 + #> 3358 2043 3M CC16 2018 2018-05-24 TKN -0.1984509387 #> 3359 2043 3M CC16 2018 2018-05-24 TN -0.1839228382 + #> 3360 2043 3M CC16 2018 2018-05-24 TP -1.6094379124 #> 3361 2043 3M CC16 2018 2018-05-24 TSS 2.3025850930 I #> 3362 2043 3M CC16 2018 2018-05-24 TURB 1.6863989536 #> 3363 2043 3M CC16 2018 2018-05-24 COND 9.8362788028 #> 3364 2043 3M CC16 2018 2018-05-24 DO 1.7698546338 #> 3365 2043 3M CC16 2018 2018-05-24 DOSAT 4.3681812279 #> 3366 2043 3M CC16 2018 2018-05-24 SALIN 2.3532782073 + #> 3367 2043 3M CC16 2018 2018-07-23 CHLAC 2.4849066498 #> 3368 2043 3M CC16 2018 2018-07-23 COND 7.2034055211 #> 3369 2043 3M CC16 2018 2018-07-23 DO 1.7833912196 #> 3370 2043 3M CC16 2018 2018-07-23 DOSAT 4.3694478525 #> 3371 2043 3M CC16 2018 2018-07-23 NO23 -2.1202635362 #> 3372 2043 3M CC16 2018 2018-07-23 SALIN -0.4004775666 #> 3373 2043 3M CC16 2018 2018-07-23 TKN 0.1823215568 #> 3374 2043 3M CC16 2018 2018-07-23 TN 0.2776317366 + #> 3375 2043 3M CC16 2018 2018-07-23 TP -1.1394342832 #> 3376 2043 3M CC16 2018 2018-07-23 TSS 1.0986122887 I #> 3377 2043 3M CC16 2018 2018-07-23 TURB 1.0986122887 #> 3378 2043 3M CC16 2018 2018-07-23 COND 7.2034055211 #> 3379 2043 3M CC16 2018 2018-07-23 DO 1.7578579176 #> 3380 2043 3M CC16 2018 2018-07-23 DOSAT 4.3438054219 #> 3381 2043 3M CC16 2018 2018-07-23 SALIN -0.4155154440 #> 3382 2043 3M CC16 2018 2018-08-21 CHLAC 2.8332133441 A #> 3383 2043 3M CC16 2018 2018-08-21 COND 6.5308776277 #> 3384 2043 3M CC16 2018 2018-08-21 DO 1.7083778603 #> 3385 2043 3M CC16 2018 2018-08-21 DOSAT 4.2931954210 #> 3386 2043 3M CC16 2018 2018-08-21 NO23 -2.8824035882 #> 3387 2043 3M CC16 2018 2018-08-21 SALIN -1.1086626245 #> 3388 2043 3M CC16 2018 2018-08-21 TKN 0.0953101798 #> 3389 2043 3M CC16 2018 2018-08-21 TN 0.1449657703 + #> 3390 2043 3M CC16 2018 2018-08-21 TP -1.2378743560 #> 3391 2043 3M CC16 2018 2018-08-21 TSS 1.0986122887 I #> 3392 2043 3M CC16 2018 2018-08-21 TURB 1.2809338455 #> 3393 2043 3M CC16 2018 2018-08-21 COND 6.5337888379 #> 3394 2043 3M CC16 2018 2018-08-21 DO 1.6882490929 #> 3395 2043 3M CC16 2018 2018-08-21 DOSAT 4.2724907476 #> 3396 2043 3M CC16 2018 2018-08-21 SALIN -1.1086626245 #> 3397 2043 3M CC16 2019 2019-02-07 CHLAC 3.1354942159 #> 3398 2043 3M CC16 2019 2019-02-07 COND 9.1573614472 #> 3399 2043 3M CC16 2019 2019-02-07 NO23 -5.5214609179 U #> 3400 2043 3M CC16 2019 2019-02-07 SALIN 1.6733512382 #> 3401 2043 3M CC16 2019 2019-02-07 TKN -0.0725706928 #> 3402 2043 3M CC16 2019 2019-02-07 TN -0.0704224643 + #> 3403 2043 3M CC16 2019 2019-02-07 TP -1.8325814637 #> 3404 2043 3M CC16 2019 2019-02-07 TSS 1.9459101491 I #> 3405 2043 3M CC16 2019 2019-02-07 TURB 1.6863989536 #> 3406 2043 3M CC16 2019 2019-03-13 CHLAC 2.1517622033 #> 3407 2043 3M CC16 2019 2019-03-13 COND 9.7229244488 #> 3408 2043 3M CC16 2019 2019-03-13 DO 1.7369512327 #> 3409 2043 3M CC16 2019 2019-03-13 DOSAT 4.2780540443 + #> 3410 2043 3M CC16 2019 2019-03-13 NO23 -5.5214609179 U #> 3411 2043 3M CC16 2019 2019-03-13 SALIN 2.2823823857 #> 3412 2043 3M CC16 2019 2019-03-13 TKN -0.2613647641 #> 3413 2043 3M CC16 2019 2019-03-13 TN -0.2587707290 + #> 3414 2043 3M CC16 2019 2019-03-13 TP -1.8971199849 #> 3415 2043 3M CC16 2019 2019-03-13 TSS 1.6094379124 I #> 3416 2043 3M CC16 2019 2019-03-13 TURB 1.2527629685 #> 3417 2043 3M CC16 2019 2019-03-13 COND 9.7228046524 #> 3418 2043 3M CC16 2019 2019-03-13 DO 1.6992786164 #> 3419 2043 3M CC16 2019 2019-03-13 DOSAT 4.2398868675 #> 3420 2043 3M CC16 2019 2019-03-13 SALIN 2.2823823857 #> 3421 2043 3M CC16 2019 2019-04-23 CHLAC 2.3978952728 #> 3422 2043 3M CC16 2019 2019-04-23 COND 9.9710060043 #> 3423 2043 3M CC16 2019 2019-04-23 DO 1.8341801851 #> 3424 2043 3M CC16 2019 2019-04-23 DOSAT 4.3707128748 #> 3425 2043 3M CC16 2019 2019-04-23 NO23 -5.5214609179 U #> 3426 2043 3M CC16 2019 2019-04-23 SALIN 2.5533438113 #> 3427 2043 3M CC16 2019 2019-04-23 TKN -0.1863295782 #> 3428 2043 3M CC16 2019 2019-04-23 TN -0.1839228382 + #> 3429 2043 3M CC16 2019 2019-04-23 TP -1.7147984281 #> 3430 2043 3M CC16 2019 2019-04-23 TSS 1.6094379124 I #> 3431 2043 3M CC16 2019 2019-04-23 TURB 1.0296194172 #> 3432 2043 3M CC16 2019 2019-07-22 CHLAC 2.4849066498 #> 3433 2043 3M CC16 2019 2019-07-22 COND 8.7887458819 #> 3434 2043 3M CC16 2019 2019-07-22 DO 1.7850704811 #> 3435 2043 3M CC16 2019 2019-07-22 DOSAT 4.3969152472 #> 3436 2043 3M CC16 2019 2019-07-22 NO23 -5.5214609179 U #> 3437 2043 3M CC16 2019 2019-07-22 SALIN 1.2669476035 #> 3438 2043 3M CC16 2019 2019-07-22 TKN -0.0833816089 #> 3439 2043 3M CC16 2019 2019-07-22 TN -0.0812100554 + #> 3440 2043 3M CC16 2019 2019-07-22 TP -1.2378743560 #> 3441 2043 3M CC16 2019 2019-07-22 TSS 1.0986122887 I #> 3442 2043 3M CC16 2019 2019-07-22 TURB 1.0986122887 #> 3443 2043 3M CC16 2019 2019-09-04 CHLAC 2.3025850930 #> 3444 2043 3M CC16 2019 2019-09-04 COND 7.9875244798 #> 3445 2043 3M CC16 2019 2019-09-04 DO 1.7101878155 #> 3446 2043 3M CC16 2019 2019-09-04 DOSAT 4.2972854062 #> 3447 2043 3M CC16 2019 2019-09-04 NO23 -2.3025850930 #> 3448 2043 3M CC16 2019 2019-09-04 SALIN 0.4187103349 #> 3449 2043 3M CC16 2019 2019-09-04 TKN 0.1823215568 #> 3450 2043 3M CC16 2019 2019-09-04 TN 0.2623642645 + #> 3451 2043 3M CC16 2019 2019-09-04 TP -0.9162907319 #> 3452 2043 3M CC16 2019 2019-09-04 TSS 1.7917594692 I #> 3453 2043 3M CC16 2019 2019-09-04 TURB 1.3350010667 #> 3454 2043 3M CC16 2020 2020-02-18 CHLAC 2.3978952728 #> 3455 2043 3M CC16 2020 2020-02-18 COND 10.0826374182 #> 3456 2043 3M CC16 2020 2020-02-18 DO 2.0202221820 #> 3457 2043 3M CC16 2020 2020-02-18 DOSAT 4.6170987569 #> 3458 2043 3M CC16 2020 2020-02-18 NO23 -5.5214609179 U #> 3459 2043 3M CC16 2020 2020-02-18 SALIN 2.6720775406 #> 3460 2043 3M CC16 2020 2020-02-18 TKN -0.1984509387 #> 3461 2043 3M CC16 2020 2020-02-18 TN -0.1960148839 + #> 3462 2043 3M CC16 2020 2020-02-18 TP -1.7147984281 #> 3463 2043 3M CC16 2020 2020-02-18 TSS 2.4849066498 #> 3464 2043 3M CC16 2020 2020-02-18 TURB 1.5260563035 #> 3465 2043 3M CC16 2020 2020-02-18 COND 10.0856841015 #> 3466 2043 3M CC16 2020 2020-02-18 DO 2.0055258587 #> 3467 2043 3M CC16 2020 2020-02-18 DOSAT 4.6001576442 #> 3468 2043 3M CC16 2020 2020-02-18 SALIN 2.6755270094 #> 3469 2043 3M CC16 2020 2020-06-09 CHLAC 1.9459101491 #> 3470 2043 3M CC16 2020 2020-06-09 COND 9.1632487644 #> 3471 2043 3M CC16 2020 2020-06-09 DO 1.8779371655 #> 3472 2043 3M CC16 2020 2020-06-09 DOSAT 4.4716387934 #> 3473 2043 3M CC16 2020 2020-06-09 NO23 -3.5404594490 #> 3474 2043 3M CC16 2020 2020-06-09 SALIN 1.6695918353 #> 3475 2043 3M CC16 2020 2020-06-09 TKN -0.1743533871 #> 3476 2043 3M CC16 2020 2020-06-09 TN -0.1404121537 + #> 3477 2043 3M CC16 2020 2020-06-09 TP -1.5606477483 #> 3478 2043 3M CC16 2020 2020-06-09 TSS 1.0986122887 I #> 3479 2043 3M CC16 2020 2020-06-09 TURB 0.8329091229 #> 3480 2043 3M CC16 2020 2020-06-09 COND 9.4707797080 #> 3481 2043 3M CC16 2020 2020-06-09 DO 1.8855533485 #> 3482 2043 3M CC16 2020 2020-06-09 DOSAT 4.4986979415 #> 3483 2043 3M CC16 2020 2020-06-09 SALIN 2.0041790572 #> 3484 2043 3M CC16 2020 2020-08-10 COND 9.6776528834 #> 3485 2043 3M CC16 2020 2020-08-10 DO 1.5973653312 #> 3486 2043 3M CC16 2020 2020-08-10 DOSAT 4.2541932632 #> 3487 2043 3M CC16 2020 2020-08-10 SALIN 2.2093727113 #> 3488 2043 3M CC16 2020 2020-09-22 CHLAC 2.1041341543 #> 3489 2043 3M CC16 2020 2020-09-22 COND 6.8012830345 #> 3490 2043 3M CC16 2020 2020-09-22 DO 1.8500283774 #> 3491 2043 3M CC16 2020 2020-09-22 DOSAT 4.3932138241 #> 3492 2043 3M CC16 2020 2020-09-22 NO23 -2.6882475738 #> 3493 2043 3M CC16 2020 2020-09-22 SALIN -0.8209805521 #> 3494 2043 3M CC16 2020 2020-09-22 TKN 0.1823215568 #> 3495 2043 3M CC16 2020 2020-09-22 TN 0.2374408560 + #> 3496 2043 3M CC16 2020 2020-09-22 TP -1.0498221245 #> 3497 2043 3M CC16 2020 2020-09-22 TSS 1.3862943611 I #> 3498 2043 3M CC16 2020 2020-09-22 TURB 1.1314021115 A #> 3499 2043 3M CC16 2020 2020-10-20 CHLAC 2.3978952728 #> 3500 2043 3M CC16 2020 2020-10-20 COND 8.8590793179 #> 3501 2043 3M CC16 2020 2020-10-20 DO 1.7281094422 #> 3502 2043 3M CC16 2020 2020-10-20 DOSAT 4.2835865619 #> 3503 2043 3M CC16 2020 2020-10-20 NO23 -2.2072749132 #> 3504 2043 3M CC16 2020 2020-10-20 SALIN 1.3480731483 #> 3505 2043 3M CC16 2020 2020-10-20 TKN 0.1823215568 #> 3506 2043 3M CC16 2020 2020-10-20 TN 0.2700271372 + #> 3507 2043 3M CC16 2020 2020-10-20 TP -1.1086626245 #> 3508 2043 3M CC16 2020 2020-10-20 TSS 1.7917594692 I #> 3509 2043 3M CC16 2020 2020-10-20 TURB 1.3350010667 #> 3510 2043 3M CC16 2020 2020-12-14 CHLAC 2.6390573296 #> 3511 2043 3M CC16 2020 2020-12-14 COND 9.3722891390 #> 3512 2043 3M CC16 2020 2020-12-14 DO 2.0554049639 #> 3513 2043 3M CC16 2020 2020-12-14 DOSAT 4.5261269786 #> 3514 2043 3M CC16 2020 2020-12-14 NO23 -5.5214609179 U #> 3515 2043 3M CC16 2020 2020-12-14 SALIN 1.9035989510 #> 3516 2043 3M CC16 2020 2020-12-14 TKN -0.0408219945 #> 3517 2043 3M CC16 2020 2020-12-14 TN -0.0387408283 + #> 3518 2043 3M CC16 2020 2020-12-14 TP -1.6094379124 #> 3519 2043 3M CC16 2020 2020-12-14 TSS 1.6094379124 I #> 3520 2043 3M CC16 2020 2020-12-14 TURB 1.2237754316 #> 3521 2043 3M CC16 2021 2021-02-03 CHLAC 2.3978952728 #> 3522 2043 3M CC16 2021 2021-02-03 COND 9.8437906253 #> 3523 2043 3M CC16 2021 2021-02-03 DO 2.0360119838 #> 3524 2043 3M CC16 2021 2021-02-03 DOSAT 4.4379342666 #> 3525 2043 3M CC16 2021 2021-02-03 NO23 -5.5214609179 U #> 3526 2043 3M CC16 2021 2021-02-03 SALIN 2.4185887688 #> 3527 2043 3M CC16 2021 2021-02-03 TKN -0.2484613593 #> 3528 2043 3M CC16 2021 2021-02-03 TN -0.2459005384 + #> 3529 2043 3M CC16 2021 2021-02-03 TP -2.2072749132 #> 3530 2043 3M CC16 2021 2021-02-03 TSS 1.3862943611 I #> 3531 2043 3M CC16 2021 2021-02-03 TURB 1.0986122887 #> 3532 2043 3M CC16 2021 2021-03-23 CHLAC 2.5649493575 #> 3533 2043 3M CC16 2021 2021-03-23 COND 10.0172179429 #> 3534 2043 3M CC16 2021 2021-03-23 DO 1.8484548129 #> 3535 2043 3M CC16 2021 2021-03-23 DOSAT 4.3320482649 #> 3536 2043 3M CC16 2021 2021-03-23 NO23 -5.5214609179 U #> 3537 2043 3M CC16 2021 2021-03-23 SALIN 2.6056482675 #> 3538 2043 3M CC16 2021 2021-03-23 TKN -0.1165338163 #> 3539 2043 3M CC16 2021 2021-03-23 TN -0.1142891464 + #> 3540 2043 3M CC16 2021 2021-03-23 TP -1.8971199849 #> 3541 2043 3M CC16 2021 2021-03-23 TSS 1.7917594692 I #> 3542 2043 3M CC16 2021 2021-03-23 TURB 1.3862943611 #> 3543 2043 3M CC16 2021 2021-05-05 CHLAC 2.2823823857 #> 3544 2043 3M CC16 2021 2021-05-05 COND 10.2634321453 #> 3545 2043 3M CC16 2021 2021-05-05 DO 1.7263316639 #> 3546 2043 3M CC16 2021 2021-05-05 DOSAT 4.4200447019 #> 3547 2043 3M CC16 2021 2021-05-05 NO23 -5.5214609179 I #> 3548 2043 3M CC16 2021 2021-05-05 SALIN 2.8650539499 #> 3549 2043 3M CC16 2021 2021-05-05 TKN -0.0833816089 #> 3550 2043 3M CC16 2021 2021-05-05 TN -0.0790432073 + #> 3551 2043 3M CC16 2021 2021-05-05 TP -1.5606477483 #> 3552 2043 3M CC16 2021 2021-05-05 TSS 2.0794415417 I #> 3553 2043 3M CC16 2021 2021-05-05 TURB 1.4816045409 #> 3554 2043 3M CC16 2021 2021-06-03 CHLAC 2.4849066498 #> 3555 2043 3M CC16 2021 2021-06-03 COND 10.3258753278 #> 3556 2043 3M CC16 2021 2021-06-03 DO 1.6524974019 #> 3557 2043 3M CC16 2021 2021-06-03 DOSAT 4.3094559418 #> 3558 2043 3M CC16 2021 2021-06-03 NO23 -5.5214609179 U #> 3559 2043 3M CC16 2021 2021-06-03 SALIN 2.9375733594 #> 3560 2043 3M CC16 2021 2021-06-03 TKN 0.0000000000 #> 3561 2043 3M CC16 2021 2021-06-03 TN 0.0019980027 + #> 3562 2043 3M CC16 2021 2021-06-03 TP -1.6607312068 #> 3563 2043 3M CC16 2021 2021-06-03 TSS 2.0794415417 I #> 3564 2043 3M CC16 2021 2021-06-03 TURB 1.4109869737 #> 3565 2043 3M CC16 2021 2021-07-01 CHLAC 3.0910424534 #> 3566 2043 3M CC16 2021 2021-07-01 COND 10.1819522754 #> 3567 2043 3M CC16 2021 2021-07-01 DO 1.6956156087 #> 3568 2043 3M CC16 2021 2021-07-01 DOSAT 4.3567088267 #> 3569 2043 3M CC16 2021 2021-07-01 NO23 -3.0791138825 #> 3570 2043 3M CC16 2021 2021-07-01 SALIN 2.7775762638 #> 3571 2043 3M CC16 2021 2021-07-01 TKN -0.2357223335 #> 3572 2043 3M CC16 2021 2021-07-01 TN -0.1791266659 + #> 3573 2043 3M CC16 2021 2021-07-01 TP -1.5606477483 #> 3574 2043 3M CC16 2021 2021-07-01 TSS 2.3025850930 #> 3575 2043 3M CC16 2021 2021-07-01 TURB 1.7404661748 #> 3576 2043 3M CC16 2022 2022-02-22 CHLAC 1.0986122887 #> 3577 2043 3M CC16 2022 2022-02-22 COND 10.3057809695 #> 3578 2043 3M CC16 2022 2022-02-22 DO 1.8794650496 #> 3579 2043 3M CC16 2022 2022-02-22 DOSAT 4.4543472963 #> 3580 2043 3M CC16 2022 2022-02-22 NO23 -4.9618451299 I #> 3581 2043 3M CC16 2022 2022-02-22 SALIN 2.9199305601 #> 3582 2043 3M CC16 2022 2022-02-22 TKN -0.4307829161 #> 3583 2043 3M CC16 2022 2022-02-22 TN -0.4246479275 + #> 3584 2043 3M CC16 2022 2022-02-22 TP -2.3859667019 #> 3585 2043 3M CC16 2022 2022-02-22 TSS 2.3025850930 I #> 3586 2043 3M CC16 2022 2022-02-22 TURB 0.6931471806 #> 3587 2043 3M CC16 2021 2021-02-03 CHLAC 3.1354942159 #> 3588 2043 3M CC16 2021 2021-02-03 COND 9.5834200199 #> 3589 2043 3M CC16 2021 2021-02-03 DO 2.0041790572 #> 3590 2043 3M CC16 2021 2021-02-03 DOSAT 4.4042772436 #> 3591 2043 3M CC16 2021 2021-02-03 NO23 -5.5214609179 U #> 3592 2043 3M CC16 2021 2021-02-03 SALIN 2.1365305087 #> 3593 2043 3M CC16 2021 2021-02-03 TKN -0.1278333715 #> 3594 2043 3M CC16 2021 2021-02-03 TN -0.1255632230 + #> 3595 2043 3M CC16 2021 2021-02-03 TP -2.1202635362 #> 3596 2043 3M CC16 2021 2021-02-03 TSS 1.9459101491 I #> 3597 2043 3M CC16 2021 2021-02-03 TURB 1.7578579176 #> 3598 2043 3M CC16 2021 2021-03-23 CHLAC 3.2188758249 #> 3599 2043 3M CC16 2021 2021-03-23 COND 9.8242819944 #> 3600 2043 3M CC16 2021 2021-03-23 DO 1.7867469274 #> 3601 2043 3M CC16 2021 2021-03-23 DOSAT 4.2640873368 #> 3602 2043 3M CC16 2021 2021-03-23 NO23 -5.5214609179 U #> 3603 2043 3M CC16 2021 2021-03-23 SALIN 2.3951642743 #> 3604 2043 3M CC16 2021 2021-03-23 TKN 0.0953101798 #> 3605 2043 3M CC16 2021 2021-03-23 TN 0.0971267107 + #> 3606 2043 3M CC16 2021 2021-03-23 TP -1.6094379124 #> 3607 2043 3M CC16 2021 2021-03-23 TSS 2.3978952728 #> 3608 2043 3M CC16 2021 2021-03-23 TURB 2.0412203289 #> 3609 2043 3M CC16 2021 2021-05-05 CHLAC 2.7725887222 #> 3610 2043 3M CC16 2021 2021-05-05 COND 10.1696522784 #> 3611 2043 3M CC16 2021 2021-05-05 DO 1.3711807233 #> 3612 2043 3M CC16 2021 2021-05-05 DOSAT 4.0342406382 #> 3613 2043 3M CC16 2021 2021-05-05 NO23 -5.5214609179 U #> 3614 2043 3M CC16 2021 2021-05-05 SALIN 2.7638002162 #> 3615 2043 3M CC16 2021 2021-05-05 TKN -0.0304592075 #> 3616 2043 3M CC16 2021 2021-05-05 TN -0.0283994745 + #> 3617 2043 3M CC16 2021 2021-05-05 TP -1.5606477483 #> 3618 2043 3M CC16 2021 2021-05-05 TSS 1.7917594692 I #> 3619 2043 3M CC16 2021 2021-05-05 TURB 1.5260563035 #> 3620 2043 3M CC16 2021 2021-06-03 CHLAC 2.8903717579 #> 3621 2043 3M CC16 2021 2021-06-03 COND 10.2473963549 #> 3622 2043 3M CC16 2021 2021-06-03 DO 1.5475625087 #> 3623 2043 3M CC16 2021 2021-06-03 DOSAT 4.2002049529 #> 3624 2043 3M CC16 2021 2021-06-03 NO23 -4.9618451299 I #> 3625 2043 3M CC16 2021 2021-06-03 SALIN 2.8518619031 #> 3626 2043 3M CC16 2021 2021-06-03 TKN 0.1823215568 #> 3627 2043 3M CC16 2021 2021-06-03 TN 0.1856493469 + #> 3628 2043 3M CC16 2021 2021-06-03 TP -1.5606477483 #> 3629 2043 3M CC16 2021 2021-06-03 TSS 2.3978952728 #> 3630 2043 3M CC16 2021 2021-06-03 TURB 1.6486586256 #> 3631 2043 3M CC16 2021 2021-07-01 CHLAC 3.4339872045 #> 3632 2043 3M CC16 2021 2021-07-01 COND 10.0458547938 #> 3633 2043 3M CC16 2021 2021-07-01 DO 1.9837562915 #> 3634 2043 3M CC16 2021 2021-07-01 DOSAT 4.6091622073 #> 3635 2043 3M CC16 2021 2021-07-01 NO23 -3.4420193762 #> 3636 2043 3M CC16 2021 2021-07-01 SALIN 2.6304489551 #> 3637 2043 3M CC16 2021 2021-07-01 TKN -0.0304592075 #> 3638 2043 3M CC16 2021 2021-07-01 TN 0.0019980027 + #> 3639 2043 3M CC16 2021 2021-07-01 TP -1.3862943611 #> 3640 2043 3M CC16 2021 2021-07-01 TSS 1.7917594692 I #> 3641 2043 3M CC16 2021 2021-07-01 TURB 1.6677068206 #> 3642 2043 3M CC16 2022 2022-02-22 CHLAC 1.6094379124 #> 3643 2043 3M CC16 2022 2022-02-22 COND 10.1823685085 #> 3644 2043 3M CC16 2022 2022-02-22 DO 1.7422190237 #> 3645 2043 3M CC16 2022 2022-02-22 DOSAT 4.3148178850 #> 3646 2043 3M CC16 2022 2022-02-22 NO23 -4.6051701860 I #> 3647 2043 3M CC16 2022 2022-02-22 SALIN 2.7788192720 #> 3648 2043 3M CC16 2022 2022-02-22 TKN -0.2484613593 #> 3649 2043 3M CC16 2022 2022-02-22 TN -0.2433462586 + #> 3650 2043 3M CC16 2022 2022-02-22 TP -2.3025850930 #> 3651 2043 3M CC16 2022 2022-02-22 TSS 2.4849066498 #> 3652 2043 3M CC16 2022 2022-02-22 TURB 1.6486586256 #> 3653 2048A 3M CC18 2013 2013-01-07 CHLAC 1.4816045409 #> 3654 2048A 3M CC18 2013 2013-01-07 COLOR 3.4011973817 #> 3655 2048A 3M CC18 2013 2013-01-07 DO 1.8082887712 #> 3656 2048A 3M CC18 2013 2013-01-07 DOSAT 4.3669129969 + #> 3657 2048A 3M CC18 2013 2013-01-07 NO23 -4.7105307016 I #> 3658 2048A 3M CC18 2013 2013-01-07 SALIN 3.1045866785 #> 3659 2048A 3M CC18 2013 2013-01-07 TKN -0.2876820725 #> 3660 2048A 3M CC18 2013 2013-01-07 TN -0.2823629110 + #> 3661 2048A 3M CC18 2013 2013-01-07 TP -2.4769384801 #> 3662 2048A 3M CC18 2013 2013-01-07 TURB 0.2623642645 #> 3663 2048A 3M CC18 2013 2013-02-04 CHLAC 1.3862943611 #> 3664 2048A 3M CC18 2013 2013-02-04 COLOR 3.1354942159 A #> 3665 2048A 3M CC18 2013 2013-02-04 DOSAT 4.3502779364 + #> 3666 2048A 3M CC18 2013 2013-02-04 NO23 -5.2983173665 I #> 3667 2048A 3M CC18 2013 2013-02-04 SALIN 3.1354942159 #> 3668 2048A 3M CC18 2013 2013-02-04 TKN -0.4942963218 #> 3669 2048A 3M CC18 2013 2013-02-04 TN -0.4877603508 + #> 3670 2048A 3M CC18 2013 2013-02-04 TP -3.4112477175 #> 3671 2048A 3M CC18 2013 2013-02-04 TURB 0.4700036292 #> 3672 2048A 3M CC18 2013 2013-03-04 CHLAC 1.8562979904 A #> 3673 2048A 3M CC18 2013 2013-03-04 COLOR 3.0910424534 A #> 3674 2048A 3M CC18 2013 2013-03-04 DO 1.7404661748 #> 3675 2048A 3M CC18 2013 2013-03-04 DOSAT 4.1926804629 + #> 3676 2048A 3M CC18 2013 2013-03-04 NO23 -3.6496587410 #> 3677 2048A 3M CC18 2013 2013-03-04 SALIN 3.2386784522 #> 3678 2048A 3M CC18 2013 2013-03-04 TKN 0.0000000000 #> 3679 2048A 3M CC18 2013 2013-03-04 TN 0.0256677467 + #> 3680 2048A 3M CC18 2013 2013-03-04 TP -2.4769384801 #> 3681 2048A 3M CC18 2013 2013-03-04 TURB 0.8329091229 #> 3682 2048A 3M CC18 2013 2013-04-01 CHLAC 1.5040773968 #> 3683 2048A 3M CC18 2013 2013-04-01 COLOR 2.8903717579 #> 3684 2048A 3M CC18 2013 2013-04-01 DO 1.4109869737 #> 3685 2048A 3M CC18 2013 2013-04-01 DOSAT 4.0000338828 + #> 3686 2048A 3M CC18 2013 2013-04-01 NO23 -4.9618451299 I #> 3687 2048A 3M CC18 2013 2013-04-01 SALIN 3.3105430134 #> 3688 2048A 3M CC18 2013 2013-04-01 TKN -0.2231435513 #> 3689 2048A 3M CC18 2013 2013-04-01 TN -0.2181560098 + #> 3690 2048A 3M CC18 2013 2013-04-01 TP -2.3025850930 #> 3691 2048A 3M CC18 2013 2013-04-01 TURB 1.0986122887 #> 3692 2048A 3M CC18 2013 2013-05-06 CHLAC 2.2617630985 #> 3693 2048A 3M CC18 2013 2013-05-06 COLOR 3.4339872045 #> 3694 2048A 3M CC18 2013 2013-05-06 DO 1.6677068206 #> 3695 2048A 3M CC18 2013 2013-05-06 DOSAT 4.2972854062 + #> 3696 2048A 3M CC18 2013 2013-05-06 NO23 -5.1159958098 I #> 3697 2048A 3M CC18 2013 2013-05-06 SALIN 3.2884018875 #> 3698 2048A 3M CC18 2013 2013-05-06 TKN -0.2876820725 #> 3699 2048A 3M CC18 2013 2013-05-06 TN -0.2823629110 + #> 3700 2048A 3M CC18 2013 2013-05-06 TP -1.8325814637 #> 3701 2048A 3M CC18 2013 2013-05-06 TURB 1.0647107370 #> 3702 2048A 3M CC18 2013 2013-06-03 CHLAC 2.0014800002 #> 3703 2048A 3M CC18 2013 2013-06-03 COLOR 3.5263605246 #> 3704 2048A 3M CC18 2013 2013-06-03 NO23 -5.2983173665 I #> 3705 2048A 3M CC18 2013 2013-06-03 TKN -0.0833816089 #> 3706 2048A 3M CC18 2013 2013-06-03 TN -0.0790432073 + #> 3707 2048A 3M CC18 2013 2013-06-03 TP -1.4271163556 #> 3708 2048A 3M CC18 2013 2013-06-03 TURB 0.9555114450 #> 3709 2048A 3M CC18 2013 2013-07-08 CHLAC 2.7080502011 #> 3710 2048A 3M CC18 2013 2013-07-08 COLOR 5.1929568509 #> 3711 2048A 3M CC18 2013 2013-07-08 DO 1.0296194172 #> 3712 2048A 3M CC18 2013 2013-07-08 DOSAT 3.5862928653 + #> 3713 2048A 3M CC18 2013 2013-07-08 NO23 -4.8283137373 I #> 3714 2048A 3M CC18 2013 2013-07-08 SALIN 1.0647107370 #> 3715 2048A 3M CC18 2013 2013-07-08 TKN 0.0000000000 #> 3716 2048A 3M CC18 2013 2013-07-08 TN 0.0039920213 + #> 3717 2048A 3M CC18 2013 2013-07-08 TP -1.8971199849 #> 3718 2048A 3M CC18 2013 2013-07-08 TURB 0.5877866649 A #> 3719 2048A 3M CC18 2013 2013-08-05 CHLAC 2.5649493575 #> 3720 2048A 3M CC18 2013 2013-08-05 COLOR 5.1357984371 #> 3721 2048A 3M CC18 2013 2013-08-05 DOSAT 3.3877743613 + #> 3722 2048A 3M CC18 2013 2013-08-05 NO23 -4.1997050779 #> 3723 2048A 3M CC18 2013 2013-08-05 SALIN 1.3083328197 #> 3724 2048A 3M CC18 2013 2013-08-05 TKN 0.2623642645 #> 3725 2048A 3M CC18 2013 2013-08-05 TN 0.2738366656 + #> 3726 2048A 3M CC18 2013 2013-08-05 TP -1.3862943611 #> 3727 2048A 3M CC18 2013 2013-08-05 TURB 0.8329091229 #> 3728 2048A 3M CC18 2013 2013-10-07 CHLAC 2.2617630985 #> 3729 2048A 3M CC18 2013 2013-10-07 COLOR 5.0106352941 #> 3730 2048A 3M CC18 2013 2013-10-07 DO 1.8562979904 #> 3731 2048A 3M CC18 2013 2013-10-07 DOSAT 4.4079380165 + #> 3732 2048A 3M CC18 2013 2013-10-07 NO23 -4.6051701860 #> 3733 2048A 3M CC18 2013 2013-10-07 SALIN 1.1631508098 #> 3734 2048A 3M CC18 2013 2013-10-07 TKN -0.1863295782 #> 3735 2048A 3M CC18 2013 2013-10-07 TN -0.1743533871 + #> 3736 2048A 3M CC18 2013 2013-10-07 TP -1.9661128564 #> 3737 2048A 3M CC18 2013 2013-10-07 TURB 0.4700036292 #> 3738 2048A 3M CC18 2013 2013-11-04 CHLAC 2.0541237337 #> 3739 2048A 3M CC18 2013 2013-11-04 COLOR 4.3820266347 #> 3740 2048A 3M CC18 2013 2013-11-04 DO 1.5892352051 #> 3741 2048A 3M CC18 2013 2013-11-04 DOSAT 4.0893320204 + #> 3742 2048A 3M CC18 2013 2013-11-04 NO23 -4.2686979494 #> 3743 2048A 3M CC18 2013 2013-11-04 SALIN 2.5176964726 #> 3744 2048A 3M CC18 2013 2013-11-04 TKN -0.4462871026 #> 3745 2048A 3M CC18 2013 2013-11-04 TN -0.4246479275 + #> 3746 2048A 3M CC18 2013 2013-11-04 TP -1.6607312068 #> 3747 2048A 3M CC18 2013 2013-11-04 TURB 0.4700036292 #> 3748 2048A 3M CC18 2013 2013-12-02 CHLAC 1.9878743482 #> 3749 2048A 3M CC18 2013 2013-12-02 COLOR 3.7612001157 #> 3750 2048A 3M CC18 2013 2013-12-02 DO 1.9459101491 #> 3751 2048A 3M CC18 2013 2013-12-02 DOSAT 4.4461744545 + #> 3752 2048A 3M CC18 2013 2013-12-02 NO23 -4.3428059215 #> 3753 2048A 3M CC18 2013 2013-12-02 SALIN 2.9444389792 #> 3754 2048A 3M CC18 2013 2013-12-02 TKN -0.4462871026 #> 3755 2048A 3M CC18 2013 2013-12-02 TN -0.4261781497 + #> 3756 2048A 3M CC18 2013 2013-12-02 TP -2.3227878003 #> 3757 2048A 3M CC18 2013 2013-12-02 TURB 0.5877866649 A #> 3758 2048A 3M CC18 2014 2014-01-06 DO 1.7917594692 #> 3759 2048A 3M CC18 2014 2014-01-06 DOSAT 4.3107991254 + #> 3760 2048A 3M CC18 2014 2014-01-06 NO23 -4.7105307016 I #> 3761 2048A 3M CC18 2014 2014-01-06 SALIN 3.0819099698 #> 3762 2048A 3M CC18 2014 2014-01-06 TKN -0.3011050928 #> 3763 2048A 3M CC18 2014 2014-01-06 TN -0.2957142441 + #> 3764 2048A 3M CC18 2014 2014-01-06 TP -2.7333680091 #> 3765 2048A 3M CC18 2014 2014-02-03 CHLAC 1.3350010667 #> 3766 2048A 3M CC18 2014 2014-02-03 COLOR 3.2188758249 #> 3767 2048A 3M CC18 2014 2014-02-03 DO 1.6677068206 #> 3768 2048A 3M CC18 2014 2014-02-03 DOSAT 4.1820501426 + #> 3769 2048A 3M CC18 2014 2014-02-03 NO23 -4.5098600062 #> 3770 2048A 3M CC18 2014 2014-02-03 SALIN 2.9496883351 #> 3771 2048A 3M CC18 2014 2014-02-03 TKN -0.6348782724 #> 3772 2048A 3M CC18 2014 2014-02-03 TN -0.6143360001 + #> 3773 2048A 3M CC18 2014 2014-02-03 TP -2.5133061243 #> 3774 2048A 3M CC18 2014 2014-02-03 TURB 0.4700036292 #> 3775 2048A 3M CC18 2014 2014-03-03 CHLAC 1.0296194172 #> 3776 2048A 3M CC18 2014 2014-03-03 COLOR 3.2580965380 #> 3777 2048A 3M CC18 2014 2014-03-03 DOSAT 4.3201512310 + #> 3778 2048A 3M CC18 2014 2014-03-03 NO23 -5.5214609179 I #> 3779 2048A 3M CC18 2014 2014-03-03 SALIN 3.0349529867 #> 3780 2048A 3M CC18 2014 2014-03-03 TKN -0.4155154440 #> 3781 2048A 3M CC18 2014 2014-03-03 TN -0.4094731295 + #> 3782 2048A 3M CC18 2014 2014-03-03 TP -2.3859667019 #> 3783 2048A 3M CC18 2014 2014-03-03 TURB 0.6418538862 #> 3784 2048A 3M CC18 2014 2014-04-07 CHLAC 1.5892352051 #> 3785 2048A 3M CC18 2014 2014-04-07 COLOR 3.3322045102 #> 3786 2048A 3M CC18 2014 2014-04-07 DO 2.2082744135 #> 3787 2048A 3M CC18 2014 2014-04-07 DOSAT 4.7492705300 + #> 3788 2048A 3M CC18 2014 2014-04-07 NO23 -4.9618451299 I #> 3789 2048A 3M CC18 2014 2014-04-07 SALIN 2.0794415417 #> 3790 2048A 3M CC18 2014 2014-04-07 TKN -0.4155154440 #> 3791 2048A 3M CC18 2014 2014-04-07 TN -0.4094731295 + #> 3792 2048A 3M 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-0.3856624808 + #> 3810 2048A 3M CC18 2014 2014-06-02 TP -1.5606477483 #> 3811 2048A 3M CC18 2014 2014-06-02 TURB 0.9555114450 #> 3812 2048A 3M CC18 2014 2014-08-04 CHLAC 1.9740810260 #> 3813 2048A 3M CC18 2014 2014-08-04 COLOR 4.7874917428 #> 3814 2048A 3M CC18 2014 2014-08-04 DO 0.7371640660 #> 3815 2048A 3M CC18 2014 2014-08-04 DOSAT 3.3568971228 + #> 3816 2048A 3M CC18 2014 2014-08-04 NO23 -4.8283137373 I #> 3817 2048A 3M CC18 2014 2014-08-04 TKN 0.0953101798 #> 3818 2048A 3M CC18 2014 2014-08-04 TN 0.0989399479 + #> 3819 2048A 3M CC18 2014 2014-08-04 TP -1.3862943611 #> 3820 2048A 3M CC18 2014 2014-08-04 TURB 1.2527629685 #> 3821 2048A 3M CC18 2014 2014-09-08 CHLAC 1.8082887712 #> 3822 2048A 3M CC18 2014 2014-09-08 COLOR 4.1108738642 #> 3823 2048A 3M CC18 2014 2014-09-08 DO 1.3083328197 #> 3824 2048A 3M CC18 2014 2014-09-08 DOSAT 3.8958936235 + #> 3825 2048A 3M CC18 2014 2014-09-08 NO23 -4.5098600062 #> 3826 2048A 3M CC18 2014 2014-09-08 SALIN 2.1162555148 #> 3827 2048A 3M CC18 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#> 4056 2048A 3M CC18 2017 2017-04-03 NO23 -4.7105307016 I #> 4057 2048A 3M CC18 2017 2017-04-03 SALIN 1.5260563035 #> 4058 2048A 3M CC18 2017 2017-04-03 TN -0.2691874898 + #> 4059 2048A 3M CC18 2017 2017-04-03 TURB 0.9555114450 #> 4060 2048A 3M CC18 2017 2017-05-01 CHLAC 2.2407096893 A #> 4061 2048A 3M CC18 2017 2017-05-01 COLOR 3.4011973817 A #> 4062 2048A 3M CC18 2017 2017-05-01 DO 1.9169226122 #> 4063 2048A 3M CC18 2017 2017-05-01 DOSAT 4.6061696863 + #> 4064 2048A 3M CC18 2017 2017-05-01 NO23 -5.5214609179 U #> 4065 2048A 3M CC18 2017 2017-05-01 SALIN 3.4210000090 #> 4066 2048A 3M CC18 2017 2017-05-01 TKN 0.0953101798 #> 4067 2048A 3M CC18 2017 2017-05-01 TN 0.0971267107 + #> 4068 2048A 3M CC18 2017 2017-05-01 TP -2.1202635362 #> 4069 2048A 3M CC18 2017 2017-05-01 TURB 1.3609765531 #> 4070 2048A 3M CC18 2017 2017-06-05 CHLAC 1.4350845253 #> 4071 2048A 3M CC18 2017 2017-06-05 COLOR 3.6635616461 #> 4072 2048A 3M CC18 2017 2017-06-05 DO 1.8870696490 #> 4073 2048A 3M CC18 2017 2017-06-05 DOSAT 4.6141299274 + #> 4074 2048A 3M CC18 2017 2017-06-05 NO23 -5.2983173665 I #> 4075 2048A 3M CC18 2017 2017-06-05 SALIN 3.4843122884 #> 4076 2048A 3M CC18 2017 2017-06-05 TN -0.1461825102 + #> 4077 2048A 3M CC18 2017 2017-06-05 TURB 0.8754687374 #> 4078 2048A 3M CC18 2017 2017-07-10 CHLAC 2.0281482473 #> 4079 2048A 3M CC18 2017 2017-07-10 COLOR 5.1357984371 #> 4080 2048A 3M CC18 2017 2017-07-10 DO 0.8754687374 #> 4081 2048A 3M CC18 2017 2017-07-10 DOSAT 3.4904285154 + #> 4082 2048A 3M CC18 2017 2017-07-10 SALIN 2.3513752572 #> 4083 2048A 3M CC18 2017 2017-07-10 TN 0.2768738737 + #> 4084 2048A 3M CC18 2017 2017-07-10 TURB 0.6931471806 #> 4085 2048A 3M CC18 2017 2017-08-07 CHLAC 0.7419373447 #> 4086 2048A 3M CC18 2017 2017-08-07 COLOR 5.3471075307 #> 4087 2048A 3M CC18 2017 2017-08-07 DOSAT 2.9123506646 + #> 4088 2048A 3M CC18 2017 2017-08-07 NO23 -2.6592600369 #> 4089 2048A 3M CC18 2017 2017-08-07 SALIN 0.9162907319 #> 4090 2048A 3M CC18 2017 2017-08-07 TKN 0.1823215568 #> 4091 2048A 3M CC18 2017 2017-08-07 TN 0.2390169005 + #> 4092 2048A 3M CC18 2017 2017-08-07 TP -1.3470736480 #> 4093 2048A 3M CC18 2017 2017-08-07 TURB 1.0296194172 #> 4094 2048A 3M CC18 2017 2017-09-05 CHLAC 2.2512917986 #> 4095 2048A 3M CC18 2017 2017-09-05 COLOR 5.2470240722 #> 4096 2048A 3M CC18 2017 2017-09-05 DO 2.2721258855 #> 4097 2048A 3M CC18 2017 2017-09-05 DOSAT 4.8354879411 + #> 4098 2048A 3M CC18 2017 2017-09-05 NO23 -3.2968373663 #> 4099 2048A 3M CC18 2017 2017-09-05 SALIN 1.1631508098 #> 4100 2048A 3M CC18 2017 2017-09-05 TKN 0.0000000000 #> 4101 2048A 3M CC18 2017 2017-09-05 TN 0.0363319292 + #> 4102 2048A 3M CC18 2017 2017-09-05 TP -1.8971199849 #> 4103 2048A 3M CC18 2017 2017-09-05 TURB 0.7419373447 #> 4104 2048A 3M CC18 2017 2017-11-06 CHLAC 1.2809338455 #> 4105 2048A 3M CC18 2017 2017-11-06 COLOR 4.3307333403 #> 4106 2048A 3M CC18 2017 2017-11-06 DO 2.0412203289 #> 4107 2048A 3M CC18 2017 2017-11-06 NO23 -4.3428059215 #> 4108 2048A 3M CC18 2017 2017-11-06 SALIN 2.2721258855 #> 4109 2048A 3M CC18 2017 2017-11-06 TKN -0.3285040670 #> 4110 2048A 3M CC18 2017 2017-11-06 TN -0.3106095771 + #> 4111 2048A 3M CC18 2017 2017-11-06 TP -1.8325814637 #> 4112 2048A 3M CC18 2017 2017-11-06 TURB 0.3364722366 #> 4113 2048A 3M CC18 2017 2017-12-04 CHLAC 0.8329091229 #> 4114 2048A 3M CC18 2017 2017-12-04 COLOR 3.8066624898 #> 4115 2048A 3M CC18 2017 2017-12-04 DO 2.0794415417 #> 4116 2048A 3M CC18 2017 2017-12-04 DOSAT 4.6700211583 + #> 4117 2048A 3M CC18 2017 2017-12-04 NO23 -5.5214609179 U #> 4118 2048A 3M CC18 2017 2017-12-04 SALIN 3.3214324132 #> 4119 2048A 3M CC18 2017 2017-12-04 TKN -0.2876820725 #> 4120 2048A 3M CC18 2017 2017-12-04 TN -0.2850189550 + #> 4121 2048A 3M CC18 2017 2017-12-04 TP -2.2072749132 #> 4122 2048A 3M CC18 2017 2017-12-04 TURB -0.1625189295 #> 4123 2048A 3M CC18 2018 2018-01-02 CHLAC 1.5475625087 #> 4124 2048A 3M CC18 2018 2018-01-02 COLOR 3.4965075615 #> 4125 2048A 3M CC18 2018 2018-01-02 DOSAT 4.3161538905 + #> 4126 2048A 3M CC18 2018 2018-01-02 NO23 -5.5214609179 U #> 4127 2048A 3M CC18 2018 2018-01-02 SALIN 2.4248027257 #> 4128 2048A 3M CC18 2018 2018-01-02 TN -0.4910229965 + #> 4129 2048A 3M CC18 2018 2018-01-02 TURB 0.5877866649 #> 4130 2048A 3M CC18 2018 2018-03-05 CHLAC 0.8329091229 #> 4131 2048A 3M CC18 2018 2018-03-05 COLOR 3.5835189385 #> 4132 2048A 3M CC18 2018 2018-03-05 NO23 -5.5214609179 U #> 4133 2048A 3M CC18 2018 2018-03-05 TKN -0.3011050928 #> 4134 2048A 3M CC18 2018 2018-03-05 TN -0.2984060358 + #> 4135 2048A 3M CC18 2018 2018-03-05 TP -1.8971199849 #> 4136 2048A 3M CC18 2018 2018-03-05 TURB 1.0296194172 #> 4137 2048A 3M CC18 2018 2018-04-02 CHLAC 1.6677068206 #> 4138 2048A 3M CC18 2018 2018-04-02 COLOR 3.3322045102 #> 4139 2048A 3M CC18 2018 2018-04-02 DOSAT 4.2513483110 + #> 4140 2048A 3M CC18 2018 2018-04-02 NO23 -5.2983173665 I #> 4141 2048A 3M CC18 2018 2018-04-02 SALIN 3.2027464429 #> 4142 2048A 3M CC18 2018 2018-04-02 TKN -0.2613647641 #> 4143 2048A 3M CC18 2018 2018-04-02 TN -0.2561834054 + #> 4144 2048A 3M CC18 2018 2018-04-02 TP -1.9661128564 #> 4145 2048A 3M CC18 2018 2018-04-02 TURB 1.3083328197 #> 4146 2048A 3M CC18 2018 2018-05-07 CHLAC 1.8562979904 #> 4147 2048A 3M CC18 2018 2018-05-07 COLOR 3.3322045102 A #> 4148 2048A 3M CC18 2018 2018-05-07 DO 2.1016921506 #> 4149 2048A 3M CC18 2018 2018-05-07 DOSAT 4.6051701860 #> 4150 2048A 3M CC18 2018 2018-05-07 NO23 -5.5214609179 I #> 4151 2048A 3M CC18 2018 2018-05-07 SALIN 3.2812870850 #> 4152 2048A 3M CC18 2018 2018-05-07 TKN -0.0943106795 #> 4153 2048A 3M CC18 2018 2018-05-07 TN -0.0899247075 + #> 4154 2048A 3M CC18 2018 2018-05-07 TP -2.2072749132 #> 4155 2048A 3M CC18 2018 2018-05-07 TURB 1.2527629685 #> 4156 2048A 3M CC18 2018 2018-06-04 CHLAC 1.8405496334 #> 4157 2048A 3M CC18 2018 2018-06-04 COLOR 4.6051701860 #> 4158 2048A 3M CC18 2018 2018-06-04 DO 2.0906287311 #> 4159 2048A 3M CC18 2018 2018-06-04 DOSAT 4.6011621646 #> 4160 2048A 3M CC18 2018 2018-06-04 NO23 -4.6051701860 I #> 4161 2048A 3M CC18 2018 2018-06-04 SALIN 1.8115620965 #> 4162 2048A 3M CC18 2018 2018-06-04 TKN -0.0725706928 #> 4163 2048A 3M CC18 2018 2018-06-04 TN -0.0682788408 + #> 4164 2048A 3M CC18 2018 2018-06-04 TP -1.6094379124 #> 4165 2048A 3M CC18 2018 2018-06-04 TURB 0.5306282511 #> 4166 2048A 3M CC18 2018 2018-07-09 CHLAC 2.4849066498 #> 4167 2048A 3M CC18 2018 2018-07-09 COLOR 4.9416424226 #> 4168 2048A 3M CC18 2018 2018-07-09 DO 1.4929040962 #> 4169 2048A 3M CC18 2018 2018-07-09 DOSAT 4.1415461637 #> 4170 2048A 3M CC18 2018 2018-07-09 NO23 -4.9618451299 I #> 4171 2048A 3M CC18 2018 2018-07-09 SALIN 1.3402504226 #> 4172 2048A 3M CC18 2018 2018-07-09 TKN -0.2231435513 #> 4173 2048A 3M CC18 2018 2018-07-09 TN -0.2181560098 + #> 4174 2048A 3M CC18 2018 2018-07-09 TP -1.7719568419 #> 4175 2048A 3M CC18 2018 2018-07-09 TURB 0.8754687374 #> 4176 2048A 3M CC18 2019 2019-05-06 CHLAC 0.9555114450 #> 4177 2048A 3M CC18 2019 2019-05-06 COLOR 3.6109179126 #> 4178 2048A 3M CC18 2019 2019-05-06 DO 0.8837675402 #> 4179 2048A 3M CC18 2019 2019-05-06 DOSAT 3.5351453542 #> 4180 2048A 3M CC18 2019 2019-05-06 NO23 -5.2983173665 I #> 4181 2048A 3M CC18 2019 2019-05-06 SALIN 2.9719517449 #> 4182 2048A 3M CC18 2019 2019-05-06 TKN -0.2744368457 #> 4183 2048A 3M CC18 2019 2019-05-06 TN -0.2691874898 + #> 4184 2048A 3M CC18 2019 2019-05-06 TP -1.7719568419 #> 4185 2048A 3M CC18 2019 2019-05-06 TURB 0.7419373447 #> 4186 2048A 3M CC18 2019 2019-06-03 CHLAC 1.5686159179 #> 4187 2048A 3M CC18 2019 2019-06-03 COLOR 3.7376696183 #> 4188 2048A 3M CC18 2019 2019-06-03 DO 0.6418538862 #> 4189 2048A 3M CC18 2019 2019-06-03 DOSAT 3.3322045102 #> 4190 2048A 3M CC18 2019 2019-06-03 NO23 -5.5214609179 U #> 4191 2048A 3M CC18 2019 2019-06-03 SALIN 3.0363942553 #> 4192 2048A 3M CC18 2019 2019-06-03 TKN -0.0725706928 #> 4193 2048A 3M CC18 2019 2019-06-03 TN -0.0704224643 + #> 4194 2048A 3M CC18 2019 2019-06-03 TP -1.3470736480 #> 4195 2048A 3M CC18 2019 2019-06-03 TURB 1.4586150227 A #> 4196 2048A 3M CC18 2019 2019-07-01 CHLAC 1.6863989536 #> 4197 2048A 3M CC18 2019 2019-07-01 COLOR 3.6635616461 #> 4198 2048A 3M CC18 2019 2019-07-01 DO 0.9162907319 #> 4199 2048A 3M CC18 2019 2019-07-01 DOSAT 3.4483989831 #> 4200 2048A 3M CC18 2019 2019-07-01 NO23 -5.5214609179 U #> 4201 2048A 3M CC18 2019 2019-07-01 SALIN 2.9678470701 #> 4202 2048A 3M CC18 2019 2019-07-01 TKN -0.2484613593 #> 4203 2048A 3M CC18 2019 2019-07-01 TN -0.2459005384 + #> 4204 2048A 3M CC18 2019 2019-07-01 TP -1.2729656758 #> 4205 2048A 3M CC18 2019 2019-07-01 TURB 0.4054651081 #> 4206 2048A 3M CC18 2019 2019-08-05 CHLAC 1.4109869737 #> 4207 2048A 3M CC18 2019 2019-08-05 COLOR 5.0751738152 #> 4208 2048A 3M CC18 2019 2019-08-05 DO 1.1378330018 #> 4209 2048A 3M CC18 2019 2019-08-05 DOSAT 3.7305011288 #> 4210 2048A 3M CC18 2019 2019-08-05 NO23 -5.5214609179 I #> 4211 2048A 3M CC18 2019 2019-08-05 SALIN 1.6134299337 #> 4212 2048A 3M CC18 2019 2019-08-05 TKN -0.0618754037 #> 4213 2048A 3M CC18 2019 2019-08-05 TN -0.0576291128 + #> 4214 2048A 3M CC18 2019 2019-08-05 TP -1.5606477483 #> 4215 2048A 3M CC18 2019 2019-08-05 TURB 0.8754687374 #> 4216 2048A 3M CC18 2019 2019-10-07 CHLAC 1.0986122887 I #> 4217 2048A 3M CC18 2019 2019-10-07 COLOR 4.3820266347 #> 4218 2048A 3M CC18 2019 2019-10-07 DO 1.0152306797 #> 4219 2048A 3M CC18 2019 2019-10-07 DOSAT 3.6375861597 #> 4220 2048A 3M CC18 2019 2019-10-07 NO23 -4.9618451299 I #> 4221 2048A 3M CC18 2019 2019-10-07 SALIN 2.7389026646 #> 4222 2048A 3M CC18 2019 2019-10-07 TKN -0.1278333715 #> 4223 2048A 3M CC18 2019 2019-10-07 TN -0.1232982163 + #> 4224 2048A 3M CC18 2019 2019-10-07 TP -1.3862943611 #> 4225 2048A 3M CC18 2019 2019-10-07 TURB 0.4054651081 #> 4226 2048A 3M CC18 2019 2019-11-04 CHLAC 1.0296194172 #> 4227 2048A 3M CC18 2019 2019-11-04 COLOR 4.1431347264 #> 4228 2048A 3M CC18 2019 2019-11-04 DO 1.2267122913 #> 4229 2048A 3M CC18 2019 2019-11-04 DOSAT 3.8177123260 #> 4230 2048A 3M CC18 2019 2019-11-04 NO23 -5.5214609179 I #> 4231 2048A 3M CC18 2019 2019-11-04 SALIN 2.8075938314 #> 4232 2048A 3M CC18 2019 2019-11-04 TKN -0.1508228897 #> 4233 2048A 3M CC18 2019 2019-11-04 TN -0.1461825102 + #> 4234 2048A 3M CC18 2019 2019-11-04 TP -1.6094379124 #> 4235 2048A 3M CC18 2019 2019-11-04 TURB 0.2623642645 A #> 4236 2048A 3M CC18 2019 2019-11-04 CHLAC 1.2809338455 #> 4237 2048A 3M CC18 2019 2019-11-04 COLOR 4.1431347264 A #> 4238 2048A 3M CC18 2019 2019-11-04 DO 1.2267122913 #> 4239 2048A 3M CC18 2019 2019-11-04 DOSAT 3.8177123260 #> 4240 2048A 3M CC18 2019 2019-11-04 NO23 -5.2983173665 I #> 4241 2048A 3M CC18 2019 2019-11-04 SALIN 2.8075938314 #> 4242 2048A 3M CC18 2019 2019-11-04 TKN -0.2231435513 #> 4243 2048A 3M CC18 2019 2019-11-04 TN -0.2181560098 + #> 4244 2048A 3M CC18 2019 2019-11-04 TP -1.7147984281 #> 4245 2048A 3M CC18 2019 2019-11-04 TURB 0.0953101798 #> 4246 2048A 3M CC18 2019 2019-12-02 CHLAC 1.2809338455 #> 4247 2048A 3M CC18 2019 2019-12-02 COLOR 3.6888794541 A #> 4248 2048A 3M CC18 2019 2019-12-02 DO 1.5518087996 #> 4249 2048A 3M CC18 2019 2019-12-02 DOSAT 4.1059436981 #> 4250 2048A 3M CC18 2019 2019-12-02 NO23 -5.5214609179 U #> 4251 2048A 3M CC18 2019 2019-12-02 SALIN 2.9412760878 #> 4252 2048A 3M CC18 2019 2019-12-02 TKN -0.2613647641 #> 4253 2048A 3M CC18 2019 2019-12-02 TN -0.2587707290 + #> 4254 2048A 3M CC18 2019 2019-12-02 TP -2.2072749132 #> 4255 2048A 3M CC18 2019 2019-12-02 TURB 0.0953101798 #> 4256 2048A 3M CC18 2020 2020-01-06 CHLAC 1.7578579176 #> 4257 2048A 3M CC18 2020 2020-01-06 COLOR 3.5263605246 #> 4258 2048A 3M CC18 2020 2020-01-06 DO 1.6770965609 #> 4259 2048A 3M CC18 2020 2020-01-06 DOSAT 4.1541845626 #> 4260 2048A 3M CC18 2020 2020-01-06 NO23 -5.5214609179 U #> 4261 2048A 3M CC18 2020 2020-01-06 SALIN 2.8713021952 #> 4262 2048A 3M CC18 2020 2020-01-06 TKN -0.5276327421 #> 4263 2048A 3M CC18 2020 2020-01-06 TN -0.5242486441 + #> 4264 2048A 3M CC18 2020 2020-01-06 TP -1.8971199849 #> 4265 2048A 3M CC18 2020 2020-01-06 TURB 0.3364722366 #> 4266 2048A 3M CC18 2020 2020-02-03 CHLAC 2.6390573296 #> 4267 2048A 3M CC18 2020 2020-02-03 COLOR 3.3672958300 #> 4268 2048A 3M CC18 2020 2020-02-03 DO 1.7137979278 #> 4269 2048A 3M CC18 2020 2020-02-03 DOSAT 4.1941898972 #> 4270 2048A 3M CC18 2020 2020-02-03 NO23 -4.8283137373 I #> 4271 2048A 3M CC18 2020 2020-02-03 SALIN 2.9538680695 #> 4272 2048A 3M CC18 2020 2020-02-03 TKN -0.0725706928 #> 4273 2048A 3M CC18 2020 2020-02-03 TN -0.0682788408 + #> 4274 2048A 3M CC18 2020 2020-02-03 TP -1.9661128564 #> 4275 2048A 3M CC18 2020 2020-02-03 TURB 2.1400661635 #> 4276 2048A 3M CC18 2020 2020-03-02 CHLAC 1.8562979904 #> 4277 2048A 3M CC18 2020 2020-03-02 COLOR 3.2958368660 #> 4278 2048A 3M CC18 2020 2020-03-02 DO 2.1388890003 #> 4279 2048A 3M CC18 2020 2020-03-02 DOSAT 4.6530075154 #> 4280 2048A 3M CC18 2020 2020-03-02 NO23 -5.5214609179 I #> 4281 2048A 3M CC18 2020 2020-03-02 SALIN 3.0061775314 #> 4282 2048A 3M CC18 2020 2020-03-02 TKN -0.3710636814 #> 4283 2048A 3M CC18 2020 2020-03-02 TN -0.3652833185 + #> 4284 2048A 3M CC18 2020 2020-03-02 TP -2.3025850930 #> 4285 2048A 3M CC18 2020 2020-03-02 TURB 1.3609765531 #> 4286 2048A 3M CC18 2020 2020-09-08 CHLAC 1.2809338455 #> 4287 2048A 3M CC18 2020 2020-09-08 COLOR 4.5432947823 #> 4288 2048A 3M CC18 2020 2020-09-08 DO 0.6418538862 #> 4289 2048A 3M CC18 2020 2020-09-08 DOSAT 3.2809112158 #> 4290 2048A 3M CC18 2020 2020-09-08 NO23 -4.3428059215 #> 4291 2048A 3M CC18 2020 2020-09-08 SALIN 2.8237570088 #> 4292 2048A 3M CC18 2020 2020-09-08 TKN -0.2231435513 #> 4293 2048A 3M CC18 2020 2020-09-08 TN -0.2070241694 + #> 4294 2048A 3M CC18 2020 2020-09-08 TP -1.3470736480 #> 4295 2048A 3M CC18 2020 2020-09-08 TURB 0.9555114450 #> 4296 2048A 3M CC18 2020 2020-10-05 DO 1.0885619528 #> 4297 2048A 3M CC18 2020 2020-10-05 DOSAT 3.6323091026 #> 4298 2048A 3M CC18 2020 2020-10-05 NO23 -3.3524072175 #> 4299 2048A 3M CC18 2020 2020-10-05 TKN 0.0000000000 #> 4300 2048A 3M CC18 2020 2020-10-05 TN 0.0344014267 + #> 4301 2048A 3M CC18 2020 2020-10-05 TP -1.4696759701 #> 4302 2048A 3M CC18 2020 2020-11-02 CHLAC 1.4816045409 I #> 4303 2048A 3M CC18 2020 2020-11-02 COLOR 4.7004803658 #> 4304 2048A 3M CC18 2020 2020-11-02 DO 1.1631508098 #> 4305 2048A 3M CC18 2020 2020-11-02 DOSAT 3.7376696183 #> 4306 2048A 3M CC18 2020 2020-11-02 NO23 -3.0365542681 #> 4307 2048A 3M CC18 2020 2020-11-02 SALIN 2.2884861686 #> 4308 2048A 3M CC18 2020 2020-11-02 TKN -0.1743533871 #> 4309 2048A 3M CC18 2020 2020-11-02 TN -0.1187835360 + #> 4310 2048A 3M CC18 2020 2020-11-02 TP -1.4271163556 #> 4311 2048A 3M CC18 2020 2020-11-02 TURB 0.8329091229 #> 4312 2048A 3M CC18 2020 2020-12-07 CHLAC 0.6931471806 I #> 4313 2048A 3M CC18 2020 2020-12-07 COLOR 4.2195077052 #> 4314 2048A 3M CC18 2020 2020-12-07 DO 1.7783364489 #> 4315 2048A 3M CC18 2020 2020-12-07 DOSAT 4.2297491992 #> 4316 2048A 3M CC18 2020 2020-12-07 NO23 -4.6051701860 #> 4317 2048A 3M CC18 2020 2020-12-07 SALIN 2.8870328566 #> 4318 2048A 3M CC18 2020 2020-12-07 TKN -0.0202027073 #> 4319 2048A 3M CC18 2020 2020-12-07 TN -0.0100503359 + #> 4320 2048A 3M CC18 2020 2020-12-07 TP -1.7719568419 #> 4321 2048A 3M CC18 2020 2020-12-07 TURB 1.4350845253 #> 4322 2048A 3M CC18 2020 2020-12-07 CHLAC 0.6931471806 I #> 4323 2048A 3M CC18 2020 2020-12-07 COLOR 4.2484952420 #> 4324 2048A 3M CC18 2020 2020-12-07 NO23 -4.7105307016 I #> 4325 2048A 3M CC18 2020 2020-12-07 TKN -0.2107210313 #> 4326 2048A 3M CC18 2020 2020-12-07 TN -0.2057949130 + #> 4327 2048A 3M CC18 2020 2020-12-07 TP -1.8325814637 #> 4328 2048A 3M CC18 2020 2020-12-07 TURB 1.3862943611 #> 4329 2048A 3M CC18 2021 2021-01-04 CHLAC 0.5306282511 I #> 4330 2048A 3M CC18 2021 2021-01-04 COLOR 3.9120230054 A #> 4331 2048A 3M CC18 2021 2021-01-04 NO23 -5.1159958098 I #> 4332 2048A 3M CC18 2021 2021-01-04 SALIN 2.6518325211 #> 4333 2048A 3M CC18 2021 2021-01-04 TKN -0.2231435513 #> 4334 2048A 3M CC18 2021 2021-01-04 TN -0.2181560098 + #> 4335 2048A 3M CC18 2021 2021-01-04 TP -2.3025850930 #> 4336 2048A 3M CC18 2021 2021-01-04 TURB 0.1823215568 #> 4337 2048A 3M CC18 2021 2021-02-01 CHLAC 0.8329091229 I #> 4338 2048A 3M CC18 2021 2021-02-01 COLOR 3.5553480615 #> 4339 2048A 3M CC18 2021 2021-02-01 NO23 -5.5214609179 U #> 4340 2048A 3M CC18 2021 2021-02-01 SALIN 2.8219739474 #> 4341 2048A 3M CC18 2021 2021-02-01 TKN -0.4462871026 #> 4342 2048A 3M CC18 2021 2021-02-01 TN -0.4431669753 + #> 4343 2048A 3M CC18 2021 2021-02-01 TP -2.3025850930 #> 4344 2048A 3M CC18 2021 2021-02-01 TURB 0.0000000000 #> 4345 2048A 3M CC18 2021 2021-03-01 CHLAC 1.3350010667 #> 4346 2048A 3M CC18 2021 2021-03-01 COLOR 3.6109179126 #> 4347 2048A 3M CC18 2021 2021-03-01 NO23 -4.9618451299 I #> 4348 2048A 3M CC18 2021 2021-03-01 TKN -0.5276327421 #> 4349 2048A 3M CC18 2021 2021-03-01 TN -0.5208759596 + #> 4350 2048A 3M CC18 2021 2021-03-01 TP -2.0402208285 #> 4351 2048A 3M CC18 2021 2021-03-01 TURB 0.8329091229 #> 4352 2048A 3M CC18 2021 2021-04-05 CHLAC 0.4700036292 I #> 4353 2048A 3M CC18 2021 2021-04-05 COLOR 3.3672958300 #> 4354 2048A 3M CC18 2021 2021-04-05 DO 1.8245492921 #> 4355 2048A 3M CC18 2021 2021-04-05 DOSAT 4.3870141762 #> 4356 2048A 3M CC18 2021 2021-04-05 NO23 -5.2983173665 I #> 4357 2048A 3M CC18 2021 2021-04-05 SALIN 3.1170645587 #> 4358 2048A 3M CC18 2021 2021-04-05 TKN -0.4155154440 #> 4359 2048A 3M CC18 2021 2021-04-05 TN -0.4094731295 + #> 4360 2048A 3M CC18 2021 2021-04-05 TP -2.3434070875 #> 4361 2048A 3M CC18 2021 2021-04-05 TURB 0.3364722366 #> 4362 2048A 3M CC18 2021 2021-05-03 CHLAC 1.5475625087 #> 4363 2048A 3M CC18 2021 2021-05-03 COLOR 3.4339872045 A #> 4364 2048A 3M CC18 2021 2021-05-03 DO 1.4182774070 #> 4365 2048A 3M CC18 2021 2021-05-03 DOSAT 4.1174098352 #> 4366 2048A 3M CC18 2021 2021-05-03 NO23 -5.5214609179 I #> 4367 2048A 3M CC18 2021 2021-05-03 SALIN 3.1726224404 #> 4368 2048A 3M CC18 2021 2021-05-03 TKN -0.3566749439 #> 4369 2048A 3M CC18 2021 2021-05-03 TN -0.3509769228 + #> 4370 2048A 3M CC18 2021 2021-05-03 TP -1.8325814637 #> 4371 2048A 3M CC18 2021 2021-05-03 TURB 0.5877866649 #> 4372 2048A 3M CC18 2021 2021-06-07 CHLAC 1.5686159179 I #> 4373 2048A 3M CC18 2021 2021-06-07 COLOR 3.5835189385 #> 4374 2048A 3M CC18 2021 2021-06-07 DO 1.0508216248 #> 4375 2048A 3M CC18 2021 2021-06-07 DOSAT 4.2918283668 #> 4376 2048A 3M CC18 2021 2021-06-07 NO23 -5.2983173665 I #> 4377 2048A 3M CC18 2021 2021-06-07 SALIN 3.2476576263 #> 4378 2048A 3M CC18 2021 2021-06-07 TKN -0.2484613593 #> 4379 2048A 3M CC18 2021 2021-06-07 TN -0.2433462586 + #> 4380 2048A 3M CC18 2021 2021-06-07 TP -1.5141277326 #> 4381 2048A 3M CC18 2021 2021-06-07 TURB 0.5306282511 #> 4382 2048A 3M CC18 2021 2021-08-02 CHLAC 1.8082887712 #> 4383 2048A 3M CC18 2021 2021-08-02 COLOR 5.0106352941 #> 4384 2048A 3M CC18 2021 2021-08-02 DO 0.0582689081 #> 4385 2048A 3M CC18 2021 2021-08-02 DOSAT 2.7080502011 #> 4386 2048A 3M CC18 2021 2021-08-02 NO23 -5.5214609179 U #> 4387 2048A 3M CC18 2021 2021-08-02 SALIN 1.8702625307 #> 4388 2048A 3M CC18 2021 2021-08-02 TKN 0.0953101798 #> 4389 2048A 3M CC18 2021 2021-08-02 TN 0.0971267107 + #> 4390 2048A 3M CC18 2021 2021-08-02 TP -0.9416085399 #> 4391 2048A 3M CC18 2021 2021-08-02 TURB 1.0986122887 A #> 4392 2048A 3M CC18 2021 2021-09-07 CHLAC 1.7917594692 #> 4393 2048A 3M CC18 2021 2021-09-07 COLOR 4.9416424226 #> 4394 2048A 3M CC18 2021 2021-09-07 NO23 -3.6888794541 #> 4395 2048A 3M CC18 2021 2021-09-07 SALIN 1.5581446180 #> 4396 2048A 3M CC18 2021 2021-09-07 TKN -0.0725706928 #> 4397 2048A 3M CC18 2021 2021-09-07 TN -0.0460439385 + #> 4398 2048A 3M CC18 2021 2021-09-07 TP -1.6094379124 #> 4399 2048A 3M CC18 2021 2021-09-07 TURB 0.4054651081 #> 4400 2048A 3M CC18 2021 2021-10-04 CHLAC 1.0986122887 #> 4401 2048A 3M CC18 2021 2021-10-04 COLOR 5.0106352941 #> 4402 2048A 3M CC18 2021 2021-10-04 DO 1.1631508098 #> 4403 2048A 3M CC18 2021 2021-10-04 DOSAT 3.7208625000 #> 4404 2048A 3M CC18 2021 2021-10-04 NO23 -3.2441936329 #> 4405 2048A 3M CC18 2021 2021-10-04 SALIN 1.5390154481 #> 4406 2048A 3M CC18 2021 2021-10-04 TKN -0.0304592075 #> 4407 2048A 3M CC18 2021 2021-10-04 TN 0.0089597414 + #> 4408 2048A 3M CC18 2021 2021-10-04 TP -1.4696759701 #> 4409 2048A 3M CC18 2021 2021-10-04 TURB -0.1625189295 #> 4410 2048A 3M CC18 2021 2021-11-01 CHLAC 0.9162907319 I #> 4411 2048A 3M CC18 2021 2021-11-01 COLOR 4.3567088267 #> 4412 2048A 3M CC18 2021 2021-11-01 DO 1.5973653312 #> 4413 2048A 3M CC18 2021 2021-11-01 DOSAT 4.1447207695 #> 4414 2048A 3M CC18 2021 2021-11-01 NO23 -3.1700856607 #> 4415 2048A 3M CC18 2021 2021-11-01 TKN -0.2744368457 #> 4416 2048A 3M CC18 2021 2021-11-01 TN -0.2206466711 + #> 4417 2048A 3M CC18 2021 2021-11-01 TP -1.5141277326 #> 4418 2048A 3M CC18 2021 2021-11-01 TURB 0.0953101798 #> 4419 2048A 3M CC18 2021 2021-12-06 CHLAC 0.9932517730 I #> 4420 2048A 3M CC18 2021 2021-12-06 COLOR 3.4657359028 #> 4421 2048A 3M CC18 2021 2021-12-06 DO 1.7351891177 #> 4422 2048A 3M CC18 2021 2021-12-06 DOSAT 4.2794400459 #> 4423 2048A 3M CC18 2021 2021-12-06 NO23 -5.2983173665 I #> 4424 2048A 3M CC18 2021 2021-12-06 SALIN 3.4452142671 #> 4425 2048A 3M CC18 2021 2021-12-06 TKN -0.7550225843 #> 4426 2048A 3M CC18 2021 2021-12-06 TN -0.7465479573 + #> 4427 2048A 3M CC18 2021 2021-12-06 TP -2.3126354288 #> 4428 2048A 3M CC18 2021 2021-12-06 TURB -0.2876820725 #> 4429 2048A 3M CC18 2022 2022-01-03 CHLAC 0.8329091229 I #> 4430 2048A 3M CC18 2022 2022-01-03 COLOR 3.3322045102 A #> 4431 2048A 3M CC18 2022 2022-01-03 DO 1.6733512382 #> 4432 2048A 3M CC18 2022 2022-01-03 DOSAT 4.2541932632 #> 4433 2048A 3M CC18 2022 2022-01-03 NO23 -4.9618451299 I #> 4434 2048A 3M CC18 2022 2022-01-03 SALIN 2.9714395810 #> 4435 2048A 3M CC18 2022 2022-01-03 TKN -0.6348782724 #> 4436 2048A 3M CC18 2022 2022-01-03 TN -0.6273594400 + #> 4437 2048A 3M CC18 2022 2022-01-03 TP -2.5902671654 #> 4438 2048A 3M CC18 2022 2022-01-03 TURB 0.1823215568 #> 4439 2048A 3M CC18 2022 2022-02-07 CHLAC 0.6931471806 I #> 4440 2048A 3M CC18 2022 2022-02-07 COLOR 3.0910424534 A #> 4441 2048A 3M CC18 2022 2022-02-07 DO 0.0000000000 #> 4442 2048A 3M CC18 2022 2022-02-07 DOSAT 4.0412953411 #> 4443 2048A 3M CC18 2022 2022-02-07 NO23 -4.7105307016 I #> 4444 2048A 3M CC18 2022 2022-02-07 SALIN 3.1144038033 #> 4445 2048A 3M CC18 2022 2022-02-07 TKN -0.4620354596 #> 4446 2048A 3M CC18 2022 2022-02-07 TN -0.4557063245 + #> 4447 2048A 3M CC18 2022 2022-02-07 TP -2.4418471603 #> 4448 2048A 3M CC18 2022 2022-02-07 TURB 0.6931471806 #> 4449 2048A 3M CC18 2022 2022-03-07 CHLAC 1.0647107370 I #> 4450 2048A 3M CC18 2022 2022-03-07 COLOR 3.2580965380 #> 4451 2048A 3M CC18 2022 2022-03-07 DO 1.3217558400 #> 4452 2048A 3M CC18 2022 2022-03-07 DOSAT 3.9318256327 #> 4453 2048A 3M CC18 2022 2022-03-07 NO23 -4.7105307016 I #> 4454 2048A 3M CC18 2022 2022-03-07 SALIN 3.2216719122 #> 4455 2048A 3M CC18 2022 2022-03-07 TKN -0.0304592075 #> 4456 2048A 3M CC18 2022 2022-03-07 TN -0.0263439753 + #> 4457 2048A 3M CC18 2022 2022-03-07 TP -2.1202635362 #> 4458 2048A 3M CC18 2022 2022-03-07 TURB 1.3083328197 #> 4459 2048A 3M CC18 2022 2022-04-04 CHLAC 1.7227665977 #> 4460 2048A 3M CC18 2022 2022-04-04 COLOR 3.2580965380 A #> 4461 2048A 3M CC18 2022 2022-04-04 DO 1.3244189574 #> 4462 2048A 3M CC18 2022 2022-04-04 DOSAT 3.9415818077 #> 4463 2048A 3M CC18 2022 2022-04-04 NO23 -4.6051701860 #> 4464 2048A 3M CC18 2022 2022-04-04 SALIN 3.2928695048 #> 4465 2048A 3M CC18 2022 2022-04-04 TKN -0.3856624808 #> 4466 2048A 3M CC18 2022 2022-04-04 TN -0.3710636814 + #> 4467 2048A 3M CC18 2022 2022-04-04 TP -1.8325814637 #> 4468 2048A 3M CC18 2022 2022-04-04 TURB 1.3350010667 #> 4469 2048A 3M CC18 2022 2022-05-02 CHLAC 0.9162907319 I #> 4470 2048A 3M CC18 2022 2022-05-02 COLOR 3.4965075615 A #> 4471 2048A 3M CC18 2022 2022-05-02 DO 1.3164082337 #> 4472 2048A 3M CC18 2022 2022-05-02 DOSAT 3.9550824949 #> 4473 2048A 3M CC18 2022 2022-05-02 NO23 -4.1997050779 #> 4474 2048A 3M CC18 2022 2022-05-02 SALIN 3.2343553957 #> 4475 2048A 3M CC18 2022 2022-05-02 TKN -0.3566749439 #> 4476 2048A 3M CC18 2022 2022-05-02 TN -0.3354727363 + #> 4477 2048A 3M CC18 2022 2022-05-02 TP -1.8971199849 #> 4478 2048A 3M CC18 2022 2022-05-02 TURB 0.8329091229 #> 4479 2060A1 2 CC25 2013 2013-01-09 CHLAC 1.3737155789 #> 4480 2060A1 2 CC25 2013 2013-01-09 COLOR 3.4011973817 #> 4481 2060A1 2 CC25 2013 2013-01-09 COND 10.5416504248 #> 4482 2060A1 2 CC25 2013 2013-01-09 DO 2.1126345090 #> 4483 2060A1 2 CC25 2013 2013-01-09 DOSAT 4.7022968967 + #> 4484 2060A1 2 CC25 2013 2013-01-09 NO23 -5.2983173665 I #> 4485 2060A1 2 CC25 2013 2013-01-09 SALIN 3.1805507105 #> 4486 2060A1 2 CC25 2013 2013-01-09 TKN -0.7635696449 #> 4487 2060A1 2 CC25 2013 2013-01-09 TN -0.7528971850 #> 4488 2060A1 2 CC25 2013 2013-01-09 TP -2.0099154790 #> 4489 2060A1 2 CC25 2013 2013-01-09 TSS 1.5644405465 #> 4490 2060A1 2 CC25 2013 2013-01-09 TURB 0.5306282511 #> 4491 2060A1 2 CC25 2013 2013-01-09 COND 10.5421785473 #> 4492 2060A1 2 CC25 2013 2013-01-09 DO 2.1138429684 #> 4493 2060A1 2 CC25 2013 2013-01-09 DOSAT 4.7022968967 + #> 4494 2060A1 2 CC25 2013 2013-01-09 SALIN 3.1809662518 #> 4495 2060A1 2 CC25 2013 2013-06-13 CHLAC 1.9344157696 #> 4496 2060A1 2 CC25 2013 2013-06-13 COLOR 4.2484952420 #> 4497 2060A1 2 CC25 2013 2013-06-13 COND 9.6434206471 #> 4498 2060A1 2 CC25 2013 2013-06-13 DO 1.7298840655 #> 4499 2060A1 2 CC25 2013 2013-06-13 DOSAT 4.3438054219 + #> 4500 2060A1 2 CC25 2013 2013-06-13 NO23 -4.1351665567 I #> 4501 2060A1 2 CC25 2013 2013-06-13 SALIN 2.1905355892 #> 4502 2060A1 2 CC25 2013 2013-06-13 TKN -0.9493305860 #> 4503 2060A1 2 CC25 2013 2013-06-13 TN -0.9088187170 #> 4504 2060A1 2 CC25 2013 2013-06-13 TP -1.7372712839 #> 4505 2060A1 2 CC25 2013 2013-06-13 TSS 0.9400072585 #> 4506 2060A1 2 CC25 2013 2013-06-13 TURB 0.3364722366 #> 4507 2060A1 2 CC25 2013 2013-06-13 COND 10.3019280457 #> 4508 2060A1 2 CC25 2013 2013-06-13 DO 1.5195132049 #> 4509 2060A1 2 CC25 2013 2013-06-13 DOSAT 4.1896547420 + #> 4510 2060A1 2 CC25 2013 2013-06-13 SALIN 2.9096295745 #> 4511 2060A1 2 CC25 2013 2013-06-13 COND 10.3862222961 #> 4512 2060A1 2 CC25 2013 2013-06-13 DO 1.5195132049 #> 4513 2060A1 2 CC25 2013 2013-06-13 DOSAT 4.1956970565 + #> 4514 2060A1 2 CC25 2013 2013-06-13 SALIN 3.0027078873 #> 4515 2060A1 2 CC25 2013 2013-11-06 CHLAC 0.6981347221 #> 4516 2060A1 2 CC25 2013 2013-11-06 COLOR 4.2484952420 #> 4517 2060A1 2 CC25 2013 2013-11-06 COND 10.4234711141 #> 4518 2060A1 2 CC25 2013 2013-11-06 DO 1.7526720805 #> 4519 2060A1 2 CC25 2013 2013-11-06 DOSAT 4.3359826962 + #> 4520 2060A1 2 CC25 2013 2013-11-06 NO23 -4.7105307016 I #> 4521 2060A1 2 CC25 2013 2013-11-06 SALIN 3.0492730405 #> 4522 2060A1 2 CC25 2013 2013-11-06 TKN -0.4812668215 #> 4523 2060A1 2 CC25 2013 2013-11-06 TN -0.4668087383 #> 4524 2060A1 2 CC25 2013 2013-11-06 TP -1.8643301621 #> 4525 2060A1 2 CC25 2013 2013-11-06 TSS 2.1747517215 #> 4526 2060A1 2 CC25 2013 2013-11-06 TURB 0.7419373447 #> 4527 2060A1 2 CC25 2013 2013-11-06 COND 10.4222813460 #> 4528 2060A1 2 CC25 2013 2013-11-06 DO 1.7509374747 #> 4529 2060A1 2 CC25 2013 2013-11-06 DOSAT 4.3333614627 + #> 4530 2060A1 2 CC25 2013 2013-11-06 SALIN 3.0478502278 #> 4531 2060A1 2 CC25 2014 2014-02-12 CHLAC 1.4109869737 #> 4532 2060A1 2 CC25 2014 2014-02-12 COLOR 3.2188758249 #> 4533 2060A1 2 CC25 2014 2014-02-12 COND 10.5921245776 #> 4534 2060A1 2 CC25 2014 2014-02-12 DO 1.9933388426 #> 4535 2060A1 2 CC25 2014 2014-02-12 DOSAT 4.5570298107 + #> 4536 2060A1 2 CC25 2014 2014-02-12 NO23 -5.5214609179 U #> 4537 2060A1 2 CC25 2014 2014-02-12 SALIN 3.2367157430 #> 4538 2060A1 2 CC25 2014 2014-02-12 TKN -0.7657178734 #> 4539 2060A1 2 CC25 2014 2014-02-12 TN -0.7657178734 #> 4540 2060A1 2 CC25 2014 2014-02-12 TP -2.0099154790 #> 4541 2060A1 2 CC25 2014 2014-02-12 TSS 1.7917594692 #> 4542 2060A1 2 CC25 2014 2014-02-12 TURB 0.1823215568 #> 4543 2060A1 2 CC25 2014 2014-02-12 COND 10.5938809449 #> 4544 2060A1 2 CC25 2014 2014-02-12 DO 1.9919755159 #> 4545 2060A1 2 CC25 2014 2014-02-12 DOSAT 4.5559799418 + #> 4546 2060A1 2 CC25 2014 2014-02-12 SALIN 3.2386784522 #> 4547 2060A1 2 CC25 2014 2014-07-09 CHLAC 2.1838015570 #> 4548 2060A1 2 CC25 2014 2014-07-09 COLOR 3.8066624898 #> 4549 2060A1 2 CC25 2014 2014-07-09 COND 10.5001238327 #> 4550 2060A1 2 CC25 2014 2014-07-09 DO 1.7047480922 #> 4551 2060A1 2 CC25 2014 2014-07-09 DOSAT 4.4164280614 + #> 4552 2060A1 2 CC25 2014 2014-07-09 NO23 -5.5214609179 U #> 4553 2060A1 2 CC25 2014 2014-07-09 SALIN 3.1271990363 #> 4554 2060A1 2 CC25 2014 2014-07-09 TKN -0.2319320573 #> 4555 2060A1 2 CC25 2014 2014-07-09 TN -0.2319320573 #> 4556 2060A1 2 CC25 2014 2014-07-09 TP -1.3167682985 #> 4557 2060A1 2 CC25 2014 2014-07-09 TSS 1.9286186519 #> 4558 2060A1 2 CC25 2014 2014-07-09 TURB 0.8329091229 #> 4559 2060A1 2 CC25 2014 2014-07-09 COND 10.5012245483 #> 4560 2060A1 2 CC25 2014 2014-07-09 DO 1.7029282555 #> 4561 2060A1 2 CC25 2014 2014-07-09 DOSAT 4.4115854369 + #> 4562 2060A1 2 CC25 2014 2014-07-09 SALIN 3.1285133848 #> 4563 2060A1 2 CC25 2014 2014-08-12 CHLAC 3.6558396000 #> 4564 2060A1 2 CC25 2014 2014-08-12 COLOR 4.3820266347 #> 4565 2060A1 2 CC25 2014 2014-08-12 COND 9.9744118909 #> 4566 2060A1 2 CC25 2014 2014-08-12 DO 1.9643112344 #> 4567 2060A1 2 CC25 2014 2014-08-12 DOSAT 4.6424659707 + #> 4568 2060A1 2 CC25 2014 2014-08-12 NO23 -5.5214609179 U #> 4569 2060A1 2 CC25 2014 2014-08-12 SALIN 2.5478814489 #> 4570 2060A1 2 CC25 2014 2014-08-12 TKN 0.1484200051 #> 4571 2060A1 2 CC25 2014 2014-08-12 TN 0.1484200051 #> 4572 2060A1 2 CC25 2014 2014-08-12 TP -0.9808292530 #> 4573 2060A1 2 CC25 2014 2014-08-12 TSS 2.3887627892 #> 4574 2060A1 2 CC25 2014 2014-08-12 TURB 1.6292405397 #> 4575 2060A1 2 CC25 2014 2014-08-12 COND 9.9753429896 #> 4576 2060A1 2 CC25 2014 2014-08-12 DO 1.9586853405 #> 4577 2060A1 2 CC25 2014 2014-08-12 DOSAT 4.6366688530 + #> 4578 2060A1 2 CC25 2014 2014-08-12 SALIN 2.5486636156 #> 4579 2060A1 2 CC25 2014 2014-08-12 COND 9.9753429896 #> 4580 2060A1 2 CC25 2014 2014-08-12 DO 1.9530276168 #> 4581 2060A1 2 CC25 2014 2014-08-12 DOSAT 4.6308379327 + #> 4582 2060A1 2 CC25 2014 2014-08-12 SALIN 2.5486636156 #> 4583 2060A1 2 CC25 2014 2014-10-21 CHLAC 0.9555114450 #> 4584 2060A1 2 CC25 2014 2014-10-21 COLOR 4.7874917428 #> 4585 2060A1 2 CC25 2014 2014-10-21 COND 10.1330107108 #> 4586 2060A1 2 CC25 2014 2014-10-21 DO 1.4701758451 #> 4587 2060A1 2 CC25 2014 2014-10-21 DOSAT 4.0809215419 + #> 4588 2060A1 2 CC25 2014 2014-10-21 NO23 -3.1941832123 #> 4589 2060A1 2 CC25 2014 2014-10-21 SALIN 2.7258901192 #> 4590 2060A1 2 CC25 2014 2014-10-21 TKN -0.1053605157 #> 4591 2060A1 2 CC25 2014 2014-10-21 TN -0.0608121394 #> 4592 2060A1 2 CC25 2014 2014-10-21 TP -1.4354846053 #> 4593 2060A1 2 CC25 2014 2014-10-21 TSS 1.5973653312 #> 4594 2060A1 2 CC25 2014 2014-10-21 TURB 0.8329091229 #> 4595 2060A1 2 CC25 2014 2014-10-21 COND 10.1472177375 #> 4596 2060A1 2 CC25 2014 2014-10-21 DO 1.4182774070 #> 4597 2060A1 2 CC25 2014 2014-10-21 DOSAT 4.0271358125 + #> 4598 2060A1 2 CC25 2014 2014-10-21 SALIN 2.7414849772 #> 4599 2060A1 2 CC25 2014 2014-10-21 COND 10.1612257486 #> 4600 2060A1 2 CC25 2014 2014-10-21 DO 1.3862943611 #> 4601 2060A1 2 CC25 2014 2014-10-21 DOSAT 3.9963641539 + #> 4602 2060A1 2 CC25 2014 2014-10-21 SALIN 2.7581094010 #> 4603 2060A1 2 CC25 2015 2015-02-03 CHLAC 1.7209792872 #> 4604 2060A1 2 CC25 2015 2015-02-03 COLOR 3.8066624898 #> 4605 2060A1 2 CC25 2015 2015-02-03 COND 10.4795389612 #> 4606 2060A1 2 CC25 2015 2015-02-03 DO 2.1758874399 #> 4607 2060A1 2 CC25 2015 2015-02-03 DOSAT 4.6596583713 + #> 4608 2060A1 2 CC25 2015 2015-02-03 NO23 -5.5214609179 U #> 4609 2060A1 2 CC25 2015 2015-02-03 SALIN 3.1130707660 #> 4610 2060A1 2 CC25 2015 2015-02-03 TKN -0.4975803970 #> 4611 2060A1 2 CC25 2015 2015-02-03 TN -0.4975803970 #> 4612 2060A1 2 CC25 2015 2015-02-03 TP -2.1037342342 #> 4613 2060A1 2 CC25 2015 2015-02-03 TSS 2.6100697927 #> 4614 2060A1 2 CC25 2015 2015-02-03 TURB 0.7884573604 #> 4615 2060A1 2 CC25 2015 2015-02-03 COND 10.4887710872 #> 4616 2060A1 2 CC25 2015 2015-02-03 DO 2.1644717909 #> 4617 2060A1 2 CC25 2015 2015-02-03 DOSAT 4.6482296754 + #> 4618 2060A1 2 CC25 2015 2015-02-03 SALIN 3.1232455939 #> 4619 2060A1 2 CC25 2015 2015-02-03 COND 10.4921072037 #> 4620 2060A1 2 CC25 2015 2015-02-03 DO 2.1621729393 #> 4621 2060A1 2 CC25 2015 2015-02-03 DOSAT 4.6463121293 + #> 4622 2060A1 2 CC25 2015 2015-02-03 SALIN 3.1267605360 #> 4623 2060A1 2 CC25 2016 2016-09-13 CHLAC 1.4206957878 #> 4624 2060A1 2 CC25 2016 2016-09-13 COND 8.8724871823 #> 4625 2060A1 2 CC25 2016 2016-09-13 DO 1.7191887764 #> 4626 2060A1 2 CC25 2016 2016-09-13 DOSAT 4.3346729383 + #> 4627 2060A1 2 CC25 2016 2016-09-13 NO23 -2.7333680091 #> 4628 2060A1 2 CC25 2016 2016-09-13 SALIN 1.3584091576 #> 4629 2060A1 2 CC25 2016 2016-09-13 TKN 0.2851789422 #> 4630 2060A1 2 CC25 2016 2016-09-13 TN 0.3364722366 #> 4631 2060A1 2 CC25 2016 2016-09-13 TP -1.2207799226 #> 4632 2060A1 2 CC25 2016 2016-09-13 TSS 0.4700036292 I #> 4633 2060A1 2 CC25 2016 2016-09-13 TURB 0.6418538862 #> 4634 2060A1 2 CC25 2016 2016-09-13 COND 9.4834162920 #> 4635 2060A1 2 CC25 2016 2016-09-13 DO 1.6882490929 #> 4636 2060A1 2 CC25 2016 2016-09-13 DOSAT 4.3134800921 + #> 4637 2060A1 2 CC25 2016 2016-09-13 SALIN 2.0162354658 #> 4638 2060A1 2 CC25 2016 2016-09-13 COND 9.6395220067 #> 4639 2060A1 2 CC25 2016 2016-09-13 DO 1.6544112781 #> 4640 2060A1 2 CC25 2016 2016-09-13 DOSAT 4.2835865619 + #> 4641 2060A1 2 CC25 2016 2016-09-13 SALIN 2.1849270495 #> 4642 2046 3M CC31 2018 2018-03-07 CHLAC 1.6094379124 #> 4643 2046 3M CC31 2018 2018-03-07 COND 10.3531928066 #> 4644 2046 3M CC31 2018 2018-03-07 DO 1.9021075264 #> 4645 2046 3M CC31 2018 2018-03-07 DOSAT 4.4670568839 #> 4646 2046 3M CC31 2018 2018-03-07 NO23 -4.7105307016 I #> 4647 2046 3M CC31 2018 2018-03-07 SALIN 3.0170044088 + #> 4648 2046 3M CC31 2018 2018-03-07 TKN -0.3710636814 #> 4649 2046 3M CC31 2018 2018-03-07 TN -0.3652833185 + #> 4650 2046 3M CC31 2018 2018-03-07 TP -1.8971199849 #> 4651 2046 3M CC31 2018 2018-03-07 TSS 1.3862943611 I #> 4652 2046 3M CC31 2018 2018-03-07 TURB 0.8754687374 #> 4653 2046 3M CC31 2018 2018-04-09 CHLAC 1.2809338455 A #> 4654 2046 3M CC31 2018 2018-04-09 COND 10.6261935353 #> 4655 2046 3M CC31 2018 2018-04-09 DO 1.3083328197 #> 4656 2046 3M CC31 2018 2018-04-09 DOSAT 3.9702919136 #> 4657 2046 3M CC31 2018 2018-04-09 NO23 -3.7297014486 #> 4658 2046 3M CC31 2018 2018-04-09 SALIN 3.2484346271 + #> 4659 2046 3M CC31 2018 2018-04-09 TKN -0.3147107448 #> 4660 2046 3M CC31 2018 2018-04-09 TN -0.2823629110 + #> 4661 2046 3M CC31 2018 2018-04-09 TP -1.7147984281 #> 4662 2046 3M CC31 2018 2018-04-09 TSS 1.6094379124 I #> 4663 2046 3M CC31 2018 2018-04-09 TURB 0.6931471806 #> 4664 2046 3M CC31 2018 2018-05-24 CHLAC 2.7080502011 #> 4665 2046 3M CC31 2018 2018-05-24 COND 9.7756541810 #> 4666 2046 3M CC31 2018 2018-05-24 DO 1.5303947051 #> 4667 2046 3M CC31 2018 2018-05-24 DOSAT 4.1009891049 #> 4668 2046 3M CC31 2018 2018-05-24 NO23 -3.1010927892 #> 4669 2046 3M CC31 2018 2018-05-24 SALIN 2.3065771143 + #> 4670 2046 3M CC31 2018 2018-05-24 TKN -0.2613647641 #> 4671 2046 3M CC31 2018 2018-05-24 TN -0.2045671657 + #> 4672 2046 3M CC31 2018 2018-05-24 TP -1.4271163556 #> 4673 2046 3M CC31 2018 2018-05-24 TSS 1.6094379124 I #> 4674 2046 3M CC31 2018 2018-05-24 TURB 0.9932517730 #> 4675 2046 3M CC31 2018 2018-07-23 CHLAC 1.4350845253 #> 4676 2046 3M CC31 2018 2018-07-23 COND 8.9291703831 #> 4677 2046 3M CC31 2018 2018-07-23 DO 1.6937790609 #> 4678 2046 3M CC31 2018 2018-07-23 DOSAT 4.3040650932 #> 4679 2046 3M CC31 2018 2018-07-23 NO23 -2.0402208285 #> 4680 2046 3M CC31 2018 2018-07-23 SALIN 1.4182774070 #> 4681 2046 3M CC31 2018 2018-07-23 TKN 0.0000000000 #> 4682 2046 3M CC31 2018 2018-07-23 TN 0.1222176327 + #> 4683 2046 3M CC31 2018 2018-07-23 TP -0.9162907319 #> 4684 2046 3M CC31 2018 2018-07-23 TSS 1.3862943611 I #> 4685 2046 3M CC31 2018 2018-07-23 TURB 0.9162907319 A #> 4686 2046 3M CC31 2018 2018-08-21 CHLAC 2.7080502011 #> 4687 2046 3M CC31 2018 2018-08-21 COND 8.6210125201 #> 4688 2046 3M CC31 2018 2018-08-21 DO 1.4586150227 #> 4689 2046 3M CC31 2018 2018-08-21 DOSAT 4.0724397268 #> 4690 2046 3M CC31 2018 2018-08-21 NO23 -3.4737680745 #> 4691 2046 3M CC31 2018 2018-08-21 SALIN 1.0885619528 #> 4692 2046 3M CC31 2018 2018-08-21 TKN 1.7047480922 #> 4693 2046 3M CC31 2018 2018-08-21 TN 1.7103686310 + #> 4694 2046 3M CC31 2018 2018-08-21 TSS 1.6094379124 I #> 4695 2046 3M CC31 2018 2018-08-21 TURB 1.3350010667 #> 4696 2046 3M CC31 2018 2018-11-12 CHLAC 1.5686159179 #> 4697 2046 3M CC31 2018 2018-11-12 COND 10.1213773269 #> 4698 2046 3M CC31 2018 2018-11-12 DO 1.6695918353 #> 4699 2046 3M CC31 2018 2018-11-12 DOSAT 4.3121405072 #> 4700 2046 3M CC31 2018 2018-11-12 NO23 -3.4112477175 #> 4701 2046 3M CC31 2018 2018-11-12 SALIN 2.7127060126 #> 4702 2046 3M CC31 2018 2018-11-12 TKN -0.3011050928 #> 4703 2046 3M CC31 2018 2018-11-12 TN -0.2574762304 + #> 4704 2046 3M CC31 2018 2018-11-12 TP -1.8325814637 #> 4705 2046 3M CC31 2018 2018-11-12 TSS 1.3862943611 I #> 4706 2046 3M CC31 2018 2018-11-12 TURB 0.4700036292 #> 4707 2046 3M CC31 2018 2018-11-12 COND 10.3160937688 #> 4708 2046 3M CC31 2018 2018-11-12 DO 1.5581446180 #> 4709 2046 3M CC31 2018 2018-11-12 DOSAT 4.2076732475 #> 4710 2046 3M CC31 2018 2018-11-12 SALIN 2.9269179576 #> 4711 2046 3M CC31 2019 2019-02-07 CHLAC 3.3672958300 #> 4712 2046 3M CC31 2019 2019-02-07 COND 9.8807305654 #> 4713 2046 3M CC31 2019 2019-02-07 NO23 -5.5214609179 U #> 4714 2046 3M CC31 2019 2019-02-07 SALIN 2.4544474423 #> 4715 2046 3M CC31 2019 2019-02-07 TKN -0.3710636814 #> 4716 2046 3M CC31 2019 2019-02-07 TN -0.3681693234 + #> 4717 2046 3M CC31 2019 2019-02-07 TP -1.6607312068 #> 4718 2046 3M CC31 2019 2019-02-07 TSS 3.3322045102 A #> 4719 2046 3M CC31 2019 2019-02-07 TURB 2.4849066498 A #> 4720 2046 3M CC31 2019 2019-03-13 CHLAC 2.3978952728 #> 4721 2046 3M CC31 2019 2019-03-13 COND 10.1587109973 #> 4722 2046 3M CC31 2019 2019-03-13 DO 1.5830939371 #> 4723 2046 3M CC31 2019 2019-03-13 DOSAT 4.1588830834 #> 4724 2046 3M CC31 2019 2019-03-13 NO23 -5.5214609179 U #> 4725 2046 3M CC31 2019 2019-03-13 SALIN 2.7568403653 #> 4726 2046 3M CC31 2019 2019-03-13 TKN -0.2876820725 #> 4727 2046 3M CC31 2019 2019-03-13 TN -0.2850189550 + #> 4728 2046 3M CC31 2019 2019-03-13 TP -1.7719568419 #> 4729 2046 3M CC31 2019 2019-03-13 TSS 1.3862943611 I #> 4730 2046 3M CC31 2019 2019-03-13 TURB 0.8754687374 #> 4731 2046 3M CC31 2019 2019-03-13 CHLAC 2.3978952728 #> 4732 2046 3M CC31 2019 2019-03-13 NO23 -5.5214609179 U #> 4733 2046 3M CC31 2019 2019-03-13 TKN -0.4004775666 #> 4734 2046 3M CC31 2019 2019-03-13 TN -0.3974969385 + #> 4735 2046 3M CC31 2019 2019-03-13 TP -1.7147984281 #> 4736 2046 3M CC31 2019 2019-03-13 TSS 1.3862943611 I #> 4737 2046 3M CC31 2019 2019-03-13 TURB 1.0647107370 #> 4738 2046 3M CC31 2019 2019-04-23 CHLAC 1.8562979904 #> 4739 2046 3M CC31 2019 2019-04-23 COND 10.2120745857 #> 4740 2046 3M CC31 2019 2019-04-23 DO 1.8389610707 #> 4741 2046 3M CC31 2019 2019-04-23 DOSAT 4.4188406078 #> 4742 2046 3M CC31 2019 2019-04-23 NO23 -5.5214609179 U #> 4743 2046 3M CC31 2019 2019-04-23 SALIN 2.8154087194 #> 4744 2046 3M CC31 2019 2019-04-23 TKN -0.4307829161 #> 4745 2046 3M CC31 2019 2019-04-23 TN -0.4277107171 + #> 4746 2046 3M CC31 2019 2019-04-23 TP -1.6094379124 #> 4747 2046 3M CC31 2019 2019-04-23 TSS 2.5649493575 #> 4748 2046 3M CC31 2019 2019-04-23 TURB 1.4350845253 #> 4749 2046 3M CC31 2019 2019-07-22 CHLAC 2.0281482473 #> 4750 2046 3M CC31 2019 2019-07-22 COND 9.5882287123 #> 4751 2046 3M CC31 2019 2019-07-22 DO 1.6808279085 #> 4752 2046 3M CC31 2019 2019-07-22 DOSAT 4.3174881135 #> 4753 2046 3M CC31 2019 2019-07-22 NO23 -5.1159958098 I #> 4754 2046 3M CC31 2019 2019-07-22 SALIN 2.1282317058 #> 4755 2046 3M CC31 2019 2019-07-22 TKN -0.2484613593 #> 4756 2046 3M CC31 2019 2019-07-22 TN -0.2433462586 + #> 4757 2046 3M CC31 2019 2019-07-22 TP -1.3862943611 #> 4758 2046 3M CC31 2019 2019-07-22 TSS 0.6931471806 I #> 4759 2046 3M CC31 2019 2019-07-22 TURB 0.7419373447 #> 4760 2046 3M CC31 2019 2019-09-04 CHLAC 2.6390573296 #> 4761 2046 3M CC31 2019 2019-09-04 COND 9.5618419571 #> 4762 2046 3M CC31 2019 2019-09-04 DO 1.6486586256 #> 4763 2046 3M CC31 2019 2019-09-04 DOSAT 4.2752762647 #> 4764 2046 3M CC31 2019 2019-09-04 NO23 -3.1465551633 #> 4765 2046 3M CC31 2019 2019-09-04 SALIN 2.1004689089 #> 4766 2046 3M CC31 2019 2019-09-04 TKN -0.1863295782 #> 4767 2046 3M CC31 2019 2019-09-04 TN -0.1358197231 + #> 4768 2046 3M CC31 2019 2019-09-04 TP -1.5141277326 #> 4769 2046 3M CC31 2019 2019-09-04 TSS 1.3862943611 I #> 4770 2046 3M CC31 2019 2019-09-04 TURB 0.6418538862 #> 4771 2046 3M CC31 2020 2020-01-14 COND 10.2603574775 #> 4772 2046 3M CC31 2020 2020-01-14 DO 1.8341801851 #> 4773 2046 3M CC31 2020 2020-01-14 DOSAT 4.4140096805 #> 4774 2046 3M CC31 2020 2020-01-14 SALIN 2.8690346205 #> 4775 2046 3M CC31 2020 2020-02-18 CHLAC 0.8329091229 I #> 4776 2046 3M CC31 2020 2020-02-18 COND 10.3879178649 #> 4777 2046 3M CC31 2020 2020-02-18 DO 1.8976198599 #> 4778 2046 3M CC31 2020 2020-02-18 DOSAT 4.5075573571 #> 4779 2046 3M CC31 2020 2020-02-18 NO23 -4.8283137373 I #> 4780 2046 3M CC31 2020 2020-02-18 SALIN 3.0106208860 #> 4781 2046 3M CC31 2020 2020-02-18 TKN -0.5447271754 #> 4782 2046 3M CC31 2020 2020-02-18 TN -0.5378542962 + #> 4783 2046 3M CC31 2020 2020-02-18 TP -2.0402208285 #> 4784 2046 3M CC31 2020 2020-02-18 TSS 1.0986122887 I #> 4785 2046 3M CC31 2020 2020-02-18 TURB 0.4700036292 #> 4786 2046 3M CC31 2020 2020-06-09 CHLAC 2.9444389792 #> 4787 2046 3M CC31 2020 2020-06-09 COND 10.1025842827 #> 4788 2046 3M CC31 2020 2020-06-09 DO 1.5973653312 #> 4789 2046 3M CC31 2020 2020-06-09 DOSAT 4.2297491992 #> 4790 2046 3M CC31 2020 2020-06-09 NO23 -4.9618451299 I #> 4791 2046 3M CC31 2020 2020-06-09 SALIN 2.6919208192 #> 4792 2046 3M CC31 2020 2020-06-09 TKN 0.0000000000 #> 4793 2046 3M CC31 2020 2020-06-09 TN 0.0039920213 + #> 4794 2046 3M CC31 2020 2020-06-09 TP -1.2729656758 #> 4795 2046 3M CC31 2020 2020-06-09 TSS 1.3862943611 I #> 4796 2046 3M CC31 2020 2020-06-09 TURB 0.5306282511 #> 4797 2046 3M CC31 2020 2020-08-10 COND 10.0585663729 #> 4798 2046 3M CC31 2020 2020-08-10 DO 0.7419373447 #> 4799 2046 3M CC31 2020 2020-08-10 DOSAT 3.4177266836 #> 4800 2046 3M CC31 2020 2020-08-10 SALIN 2.6426223958 #> 4801 2046 3M CC31 2020 2020-09-22 CHLAC 2.4849066498 #> 4802 2046 3M CC31 2020 2020-09-22 COND 9.3350328159 #> 4803 2046 3M CC31 2020 2020-09-22 DO 1.5789787049 #> 4804 2046 3M CC31 2020 2020-09-22 DOSAT 4.1573193614 #> 4805 2046 3M CC31 2020 2020-09-22 NO23 -3.0791138825 #> 4806 2046 3M CC31 2020 2020-09-22 SALIN 1.8578592709 #> 4807 2046 3M CC31 2020 2020-09-22 TKN -0.0408219945 #> 4808 2046 3M CC31 2020 2020-09-22 TN 0.0059820717 + #> 4809 2046 3M CC31 2020 2020-09-22 TP -1.4271163556 #> 4810 2046 3M CC31 2020 2020-09-22 TSS 1.0986122887 I #> 4811 2046 3M CC31 2020 2020-09-22 TURB 0.9932517730 #> 4812 2046 3M CC31 2020 2020-10-20 CHLAC 1.4586150227 #> 4813 2046 3M CC31 2020 2020-10-20 COND 9.7670949276 #> 4814 2046 3M CC31 2020 2020-10-20 DO 1.4085449701 #> 4815 2046 3M CC31 2020 2020-10-20 DOSAT 4.0000338828 #> 4816 2046 3M CC31 2020 2020-10-20 NO23 -2.5510464523 #> 4817 2046 3M CC31 2020 2020-10-20 SALIN 2.3282528397 #> 4818 2046 3M CC31 2020 2020-10-20 TKN -0.0833816089 #> 4819 2046 3M CC31 2020 2020-10-20 TN -0.0020020027 + #> 4820 2046 3M CC31 2020 2020-10-20 TP -1.5141277326 #> 4821 2046 3M CC31 2020 2020-10-20 TSS 1.0986122887 I #> 4822 2046 3M CC31 2020 2020-10-20 TURB 0.5877866649 #> 4823 2046 3M CC31 2020 2020-12-14 CHLAC 1.0647107370 #> 4824 2046 3M CC31 2020 2020-12-14 COND 9.9551782679 #> 4825 2046 3M CC31 2020 2020-12-14 DO 1.8293763328 #> 4826 2046 3M CC31 2020 2020-12-14 DOSAT 4.3528552574 #> 4827 2046 3M CC31 2020 2020-12-14 NO23 -2.7181005370 #> 4828 2046 3M CC31 2020 2020-12-14 SALIN 2.5360749364 #> 4829 2046 3M CC31 2020 2020-12-14 TKN -0.2107210313 #> 4830 2046 3M CC31 2020 2020-12-14 TN -0.1323891880 + #> 4831 2046 3M CC31 2020 2020-12-14 TP -2.1202635362 #> 4832 2046 3M CC31 2020 2020-12-14 TSS 1.6094379124 I #> 4833 2046 3M CC31 2020 2020-12-14 TURB 0.5306282511 #> 4834 2046 3M CC31 2021 2021-02-03 CHLAC 0.9932517730 #> 4835 2046 3M CC31 2021 2021-02-03 COND 10.2269830978 #> 4836 2046 3M CC31 2021 2021-02-03 DO 2.0655961349 #> 4837 2046 3M CC31 2021 2021-02-03 DOSAT 4.5130548971 #> 4838 2046 3M CC31 2021 2021-02-03 NO23 -4.0745419349 #> 4839 2046 3M CC31 2021 2021-02-03 SALIN 2.8355635214 #> 4840 2046 3M CC31 2021 2021-02-03 TKN -0.4780358009 #> 4841 2046 3M CC31 2021 2021-02-03 TN -0.4509856234 + #> 4842 2046 3M CC31 2021 2021-02-03 TP -2.3025850930 #> 4843 2046 3M CC31 2021 2021-02-03 TSS 1.7917594692 I #> 4844 2046 3M CC31 2021 2021-02-03 TURB 0.5306282511 #> 4845 2046 3M CC31 2021 2021-03-09 CHLAC 2.0918640617 #> 4846 2046 3M CC31 2021 2021-03-09 COND 10.3281668796 #> 4847 2046 3M CC31 2021 2021-03-09 DO 2.2523438766 #> 4848 2046 3M CC31 2021 2021-03-09 DOSAT 4.7757564866 #> 4849 2046 3M CC31 2021 2021-03-09 NO23 -5.5214609179 U #> 4850 2046 3M CC31 2021 2021-03-09 SALIN 2.9460166813 #> 4851 2046 3M CC31 2021 2021-03-09 TKN -0.1863295782 #> 4852 2046 3M CC31 2021 2021-03-09 TN -0.1839228382 + #> 4853 2046 3M CC31 2021 2021-03-09 TP -1.5606477483 #> 4854 2046 3M CC31 2021 2021-03-09 TSS 2.8332133441 #> 4855 2046 3M CC31 2021 2021-03-09 TURB 2.0412203289 #> 4856 2046 3M CC31 2021 2021-05-05 CHLAC 0.9555114450 #> 4857 2046 3M CC31 2021 2021-05-05 COND 10.5683895677 #> 4858 2046 3M CC31 2021 2021-05-05 DO 1.3402504226 #> 4859 2046 3M CC31 2021 2021-05-05 DOSAT 4.0465538984 #> 4860 2046 3M CC31 2021 2021-05-05 NO23 -5.5214609179 U #> 4861 2046 3M CC31 2021 2021-05-05 SALIN 3.2043711387 #> 4862 2046 3M CC31 2021 2021-05-05 TKN -0.4620354596 #> 4863 2046 3M CC31 2021 2021-05-05 TN -0.4588658848 + #> 4864 2046 3M CC31 2021 2021-05-05 TP -1.5141277326 #> 4865 2046 3M CC31 2021 2021-05-05 TSS 1.7917594692 I #> 4866 2046 3M CC31 2021 2021-05-05 TURB 0.4700036292 #> 4867 2046 3M CC31 2021 2021-06-03 CHLAC 0.9932517730 I #> 4868 2046 3M CC31 2021 2021-06-03 COND 10.6275033568 #> 4869 2046 3M CC31 2021 2021-06-03 DO 0.8329091229 #> 4870 2046 3M CC31 2021 2021-06-03 DOSAT 3.5322256441 #> 4871 2046 3M CC31 2021 2021-06-03 NO23 -5.5214609179 U #> 4872 2046 3M CC31 2021 2021-06-03 SALIN 3.2718477096 #> 4873 2046 3M CC31 2021 2021-06-03 TKN -0.3285040670 #> 4874 2046 3M CC31 2021 2021-06-03 TN -0.3257301401 + #> 4875 2046 3M CC31 2021 2021-06-03 TP -1.4271163556 #> 4876 2046 3M CC31 2021 2021-06-03 TSS 1.0986122887 I #> 4877 2046 3M CC31 2021 2021-06-03 TURB 0.5306282511 #> 4878 2046 3M CC31 2021 2021-07-01 CHLAC 2.7080502011 #> 4879 2046 3M CC31 2021 2021-07-01 COND 10.4739019677 #> 4880 2046 3M CC31 2021 2021-07-01 DO 1.6770965609 #> 4881 2046 3M CC31 2021 2021-07-01 DOSAT 4.3107991254 #> 4882 2046 3M CC31 2021 2021-07-01 NO23 -5.2983173665 I #> 4883 2046 3M CC31 2021 2021-07-01 SALIN 3.1014427280 #> 4884 2046 3M CC31 2021 2021-07-01 TKN -0.4462871026 #> 4885 2046 3M CC31 2021 2021-07-01 TN -0.4400565529 + #> 4886 2046 3M CC31 2021 2021-07-01 TP -1.2729656758 #> 4887 2046 3M CC31 2021 2021-07-01 TSS 1.7917594692 I #> 4888 2046 3M CC31 2021 2021-07-01 TURB 0.4054651081 #> 4889 2046 3M CC31 2021 2021-07-29 CHLAC 2.9444389792 #> 4890 2046 3M CC31 2021 2021-07-29 COND 9.3783094225 #> 4891 2046 3M CC31 2021 2021-07-29 DO 1.3558351536 #> 4892 2046 3M CC31 2021 2021-07-29 DOSAT 3.9646154555 #> 4893 2046 3M CC31 2021 2021-07-29 NO23 -3.3242363405 #> 4894 2046 3M CC31 2021 2021-07-29 SALIN 1.9021075264 #> 4895 2046 3M CC31 2021 2021-07-29 TKN 0.0953101798 #> 4896 2046 3M CC31 2021 2021-07-29 TN 0.1275133203 + #> 4897 2046 3M CC31 2021 2021-07-29 TP -0.9942522733 #> 4898 2046 3M CC31 2021 2021-07-29 TSS 1.6094379124 I #> 4899 2046 3M CC31 2021 2021-07-29 TURB 1.6094379124 #> 4900 2046 3M CC31 2021 2021-08-25 CHLAC 2.4849066498 #> 4901 2046 3M CC31 2021 2021-08-25 COND 9.4766200382 #> 4902 2046 3M CC31 2021 2021-08-25 DO 0.8153648133 #> 4903 2046 3M CC31 2021 2021-08-25 DOSAT 3.4404180948 #> 4904 2046 3M CC31 2021 2021-08-25 NO23 -4.0745419349 #> 4905 2046 3M CC31 2021 2021-08-25 SALIN 2.0095554142 #> 4906 2046 3M CC31 2021 2021-08-25 TKN 0.0000000000 #> 4907 2046 3M CC31 2021 2021-08-25 TN 0.0168571171 + #> 4908 2046 3M CC31 2021 2021-08-25 TP -1.1086626245 #> 4909 2046 3M CC31 2021 2021-08-25 TSS 1.7917594692 I #> 4910 2046 3M CC31 2021 2021-08-25 TURB 1.1939224685 #> 4911 2046 3M CC31 2021 2021-09-23 CHLAC 3.0445224377 #> 4912 2046 3M CC31 2021 2021-09-23 COND 8.7826296549 #> 4913 2046 3M CC31 2021 2021-09-23 DO 1.4747630091 #> 4914 2046 3M CC31 2021 2021-09-23 DOSAT 4.0483006237 #> 4915 2046 3M CC31 2021 2021-09-23 NO23 -3.0576076773 #> 4916 2046 3M CC31 2021 2021-09-23 SALIN 1.2641267271 #> 4917 2046 3M CC31 2021 2021-09-23 TKN -0.0943106795 #> 4918 2046 3M CC31 2021 2021-09-23 TN -0.0439518875 + #> 4919 2046 3M CC31 2021 2021-09-23 TP -1.4271163556 #> 4920 2046 3M CC31 2021 2021-09-23 TSS 1.3862943611 I #> 4921 2046 3M CC31 2021 2021-09-23 TURB 1.1631508098 #> 4922 2046 3M CC31 2021 2021-10-21 CHLAC 2.3025850930 #> 4923 2046 3M CC31 2021 2021-10-21 COND 9.9156631285 #> 4924 2046 3M CC31 2021 2021-10-21 DO 1.5040773968 #> 4925 2046 3M CC31 2021 2021-10-21 DOSAT 4.0690267542 #> 4926 2046 3M CC31 2021 2021-10-21 NO23 -3.1465551633 #> 4927 2046 3M CC31 2021 2021-10-21 SALIN 2.4907230351 #> 4928 2046 3M CC31 2021 2021-10-21 TKN -0.1278333715 #> 4929 2046 3M CC31 2021 2021-10-21 TN -0.0801260445 + #> 4930 2046 3M CC31 2021 2021-10-21 TP -1.5141277326 #> 4931 2046 3M CC31 2021 2021-10-21 TSS 1.0986122887 U #> 4932 2046 3M CC31 2021 2021-10-21 TURB 0.4700036292 A #> 4933 2046 3M CC31 2021 2021-11-22 COND 10.1079374614 #> 4934 2046 3M CC31 2021 2021-11-22 DO 1.7316555452 #> 4935 2046 3M CC31 2021 2021-11-22 DOSAT 4.2877159552 #> 4936 2046 3M CC31 2021 2021-11-22 NO23 -2.8134107168 #> 4937 2046 3M CC31 2021 2021-11-22 SALIN 2.7020321288 #> 4938 2046 3M CC31 2021 2021-11-22 TKN -0.6733445533 #> 4939 2046 3M CC31 2021 2021-11-22 TN -0.5621189182 + #> 4940 2046 3M CC31 2021 2021-11-22 TP -2.3025850930 #> 4941 2046 3M CC31 2021 2021-11-22 TSS 1.6094379124 I #> 4942 2046 3M CC31 2021 2021-11-22 TURB 0.1823215568 A #> 4943 2046 3M CC31 2022 2022-02-22 CHLAC 1.3083328197 #> 4944 2046 3M CC31 2022 2022-02-22 COND 10.5165899421 #> 4945 2046 3M CC31 2022 2022-02-22 DO 1.8547342684 #> 4946 2046 3M CC31 2022 2022-02-22 DOSAT 4.4320065670 #> 4947 2046 3M CC31 2022 2022-02-22 NO23 -5.5214609179 U #> 4948 2046 3M CC31 2022 2022-02-22 SALIN 3.1527360224 #> 4949 2046 3M CC31 2022 2022-02-22 TKN -0.6931471806 #> 4950 2046 3M CC31 2022 2022-02-22 TN -0.6891551593 + #> 4951 2046 3M CC31 2022 2022-02-22 TP -2.4304184645 #> 4952 2046 3M CC31 2022 2022-02-22 TSS 2.0794415417 I #> 4953 2046 3M CC31 2022 2022-02-22 TURB 0.4054651081 A #> 4954 2046 3M CC31 2022 2022-04-20 CHLAC 1.5260563035 #> 4955 2046 3M CC31 2022 2022-04-20 COND 10.6492271832 #> 4956 2046 3M CC31 2022 2022-04-20 DO 1.5581446180 #> 4957 2046 3M CC31 2022 2022-04-20 DOSAT 4.1805222585 #> 4958 2046 3M CC31 2022 2022-04-20 NO23 -5.5214609179 U #> 4959 2046 3M CC31 2022 2022-04-20 SALIN 3.2987954480 #> 4960 2046 3M CC31 2022 2022-04-20 TKN -0.5447271754 #> 4961 2046 3M CC31 2022 2022-04-20 TN -0.5412848313 + #> 4962 2046 3M CC31 2022 2022-04-20 TP -1.8325814637 #> 4963 2046 3M CC31 2022 2022-04-20 TSS 2.0794415417 I #> 4964 2046 3M CC31 2022 2022-04-20 TURB 1.0296194172 #> 4965 2056E 3M CC34 2015 2015-04-06 CHLAC 1.5040773968 #> 4966 2056E 3M CC34 2015 2015-04-06 COLOR 3.8066624898 #> 4967 2056E 3M CC34 2015 2015-04-06 COND 10.4003156667 #> 4968 2056E 3M CC34 2015 2015-04-06 DO 2.1317967720 #> 4969 2056E 3M CC34 2015 2015-04-06 DOSAT 4.7899886230 + #> 4970 2056E 3M CC34 2015 2015-04-06 NO23 -5.5214609179 U #> 4971 2056E 3M CC34 2015 2015-04-06 SALIN 3.0194488002 #> 4972 2056E 3M CC34 2015 2015-04-06 TKN -0.3509769228 #> 4973 2056E 3M CC34 2015 2015-04-06 TN -0.3509769228 #> 4974 2056E 3M CC34 2015 2015-04-06 TP -1.6928195214 #> 4975 2056E 3M CC34 2015 2015-04-06 TSS 1.6253112616 #> 4976 2056E 3M CC34 2015 2015-04-06 TURB 1.0647107370 #> 4977 2056E 3M CC34 2015 2015-04-06 COND 10.4033533361 #> 4978 2056E 3M CC34 2015 2015-04-06 DO 2.1341664414 #> 4979 2056E 3M CC34 2015 2015-04-06 DOSAT 4.7899886230 + #> 4980 2056E 3M CC34 2015 2015-04-06 SALIN 3.0233474406 #> 4981 2056E 3M CC34 2015 2015-04-06 COND 10.4069864009 #> 4982 2056E 3M CC34 2015 2015-04-06 DO 2.1435893615 #> 4983 2056E 3M CC34 2015 2015-04-06 DOSAT 4.7949637576 + #> 4984 2056E 3M CC34 2015 2015-04-06 SALIN 3.0272309406 #> 4985 2056E 3M CC36 2015 2015-04-06 CHLAC 1.5040773968 #> 4986 2056E 3M CC36 2015 2015-04-06 COLOR 3.8066624898 #> 4987 2056E 3M CC36 2015 2015-04-06 COND 10.4003156667 #> 4988 2056E 3M CC36 2015 2015-04-06 DO 2.1317967720 #> 4989 2056E 3M CC36 2015 2015-04-06 DOSAT 4.7899886230 + #> 4990 2056E 3M CC36 2015 2015-04-06 NO23 -5.5214609179 U #> 4991 2056E 3M CC36 2015 2015-04-06 SALIN 3.0194488002 #> 4992 2056E 3M CC36 2015 2015-04-06 TKN -0.3509769228 #> 4993 2056E 3M CC36 2015 2015-04-06 TN -0.3509769228 #> 4994 2056E 3M CC36 2015 2015-04-06 TP -1.6928195214 #> 4995 2056E 3M CC36 2015 2015-04-06 TSS 1.6253112616 #> 4996 2056E 3M CC36 2015 2015-04-06 TURB 1.0647107370 #> 4997 2056E 3M CC36 2015 2015-04-06 COND 10.4033533361 #> 4998 2056E 3M CC36 2015 2015-04-06 DO 2.1341664414 #> 4999 2056E 3M CC36 2015 2015-04-06 DOSAT 4.7899886230 + #> 5000 2056E 3M CC36 2015 2015-04-06 SALIN 3.0233474406 #> 5001 2056E 3M CC36 2015 2015-04-06 COND 10.4069864009 #> 5002 2056E 3M CC36 2015 2015-04-06 DO 2.1435893615 #> 5003 2056E 3M CC36 2015 2015-04-06 DOSAT 4.7949637576 + #> 5004 2056E 3M CC36 2015 2015-04-06 SALIN 3.0272309406 #> 5005 2056E 3M CC37 2013 2013-01-07 CHLAC 2.4849066498 #> 5006 2056E 3M CC37 2013 2013-01-07 COLOR 3.0445224377 A #> 5007 2056E 3M CC37 2013 2013-01-07 DO 1.8718021769 #> 5008 2056E 3M CC37 2013 2013-01-07 DOSAT 4.4379342666 + #> 5009 2056E 3M CC37 2013 2013-01-07 NO23 -4.9618451299 I #> 5010 2056E 3M CC37 2013 2013-01-07 SALIN 3.1612467120 #> 5011 2056E 3M CC37 2013 2013-01-07 TKN -0.2876820725 #> 5012 2056E 3M CC37 2013 2013-01-07 TN -0.2823629110 + #> 5013 2056E 3M CC37 2013 2013-01-07 TP -2.0402208285 #> 5014 2056E 3M CC37 2013 2013-01-07 TURB 1.0647107370 #> 5015 2056E 3M CC37 2013 2013-02-04 CHLAC 1.8870696490 #> 5016 2056E 3M CC37 2013 2013-02-04 COLOR 2.5649493575 #> 5017 2056E 3M CC37 2013 2013-02-04 DOSAT 4.4624538838 + #> 5018 2056E 3M CC37 2013 2013-02-04 NO23 -5.2983173665 I #> 5019 2056E 3M CC37 2013 2013-02-04 SALIN 3.2619353143 #> 5020 2056E 3M CC37 2013 2013-02-04 TKN -0.5798184953 #> 5021 2056E 3M CC37 2013 2013-02-04 TN -0.5727010275 + #> 5022 2056E 3M CC37 2013 2013-02-04 TP -2.9565115604 #> 5023 2056E 3M CC37 2013 2013-02-04 TURB 1.0296194172 A #> 5024 2056E 3M CC37 2013 2013-03-04 CHLAC 2.1282317058 #> 5025 2056E 3M CC37 2013 2013-03-04 COLOR 2.6390573296 A #> 5026 2056E 3M CC37 2013 2013-03-04 DOSAT 4.0073331852 + #> 5027 2056E 3M CC37 2013 2013-03-04 NO23 -3.5755507688 #> 5028 2056E 3M CC37 2013 2013-03-04 SALIN 3.2921262866 #> 5029 2056E 3M CC37 2013 2013-03-04 TKN -0.2231435513 #> 5030 2056E 3M CC37 2013 2013-03-04 TN -0.1887421246 + #> 5031 2056E 3M CC37 2013 2013-03-04 TP 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CC37 2013 2013-05-06 TKN -0.1392620673 #> 5050 2056E 3M CC37 2013 2013-05-06 TN -0.1346749033 + #> 5051 2056E 3M CC37 2013 2013-05-06 TP -1.3470736480 #> 5052 2056E 3M CC37 2013 2013-05-06 TURB 1.6486586256 A #> 5053 2056E 3M CC37 2013 2013-06-03 CHLAC 2.2823823857 #> 5054 2056E 3M CC37 2013 2013-06-03 COLOR 2.9957322736 #> 5055 2056E 3M CC37 2013 2013-06-03 DOSAT 4.2724907476 + #> 5056 2056E 3M CC37 2013 2013-06-03 NO23 -4.8283137373 I #> 5057 2056E 3M CC37 2013 2013-06-03 SALIN 3.2464909919 #> 5058 2056E 3M CC37 2013 2013-06-03 TKN -0.2231435513 #> 5059 2056E 3M CC37 2013 2013-06-03 TN -0.2181560098 + #> 5060 2056E 3M CC37 2013 2013-06-03 TP -1.2729656758 #> 5061 2056E 3M CC37 2013 2013-06-03 TURB 1.1939224685 #> 5062 2056E 3M CC37 2013 2013-07-08 CHLAC 2.4849066498 #> 5063 2056E 3M CC37 2013 2013-07-08 COLOR 4.5325994932 #> 5064 2056E 3M CC37 2013 2013-07-08 DO 1.6292405397 #> 5065 2056E 3M CC37 2013 2013-07-08 DOSAT 4.1805222585 + #> 5066 2056E 3M CC37 2013 2013-07-08 NO23 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2013-09-09 DOSAT 4.0127729085 + #> 5085 2056E 3M CC37 2013 2013-09-09 NO23 -3.2968373663 #> 5086 2056E 3M CC37 2013 2013-09-09 SALIN 1.9600947840 #> 5087 2056E 3M CC37 2013 2013-09-09 TKN 0.0000000000 #> 5088 2056E 3M CC37 2013 2013-09-09 TN 0.0363319292 + #> 5089 2056E 3M CC37 2013 2013-09-09 TP -0.7339691751 #> 5090 2056E 3M CC37 2013 2013-09-09 TURB 0.6418538862 #> 5091 2056E 3M CC37 2013 2013-10-07 CHLAC 0.8329091229 #> 5092 2056E 3M CC37 2013 2013-10-07 COLOR 4.5747109785 A #> 5093 2056E 3M CC37 2013 2013-10-07 DOSAT 4.1335652754 + #> 5094 2056E 3M CC37 2013 2013-10-07 NO23 -2.3025850930 #> 5095 2056E 3M CC37 2013 2013-10-07 SALIN 2.2617630985 #> 5096 2056E 3M CC37 2013 2013-10-07 TKN 0.0000000000 #> 5097 2056E 3M CC37 2013 2013-10-07 TN 0.0953101798 + #> 5098 2056E 3M CC37 2013 2013-10-07 TP -0.8439700703 #> 5099 2056E 3M CC37 2013 2013-10-07 TURB 0.3364722366 A #> 5100 2056E 3M CC37 2013 2013-11-04 CHLAC 1.2527629685 #> 5101 2056E 3M CC37 2013 2013-11-04 COLOR 3.8066624898 A #> 5102 2056E 3M CC37 2013 2013-11-04 DOSAT 4.1573193614 + #> 5103 2056E 3M CC37 2013 2013-11-04 NO23 -3.9633162998 #> 5104 2056E 3M CC37 2013 2013-11-04 SALIN 2.9704144656 #> 5105 2056E 3M CC37 2013 2013-11-04 TKN -0.5447271754 #> 5106 2056E 3M CC37 2013 2013-11-04 TN -0.5124936809 + #> 5107 2056E 3M CC37 2013 2013-11-04 TP -1.7147984281 #> 5108 2056E 3M CC37 2013 2013-11-04 TURB 0.5877866649 A #> 5109 2056E 3M CC37 2013 2013-12-02 CHLAC 1.3350010667 #> 5110 2056E 3M CC37 2013 2013-12-02 COLOR 3.0910424534 A #> 5111 2056E 3M CC37 2013 2013-12-02 DO 1.9169226122 #> 5112 2056E 3M CC37 2013 2013-12-02 DOSAT 4.4624538838 + #> 5113 2056E 3M CC37 2013 2013-12-02 NO23 -3.5404594490 #> 5114 2056E 3M CC37 2013 2013-12-02 SALIN 3.2188758249 #> 5115 2056E 3M CC37 2013 2013-12-02 TKN -0.4780358009 #> 5116 2056E 3M CC37 2013 2013-12-02 TN -0.4323225623 + #> 5117 2056E 3M CC37 2013 2013-12-02 TP -2.1202635362 #> 5118 2056E 3M CC37 2013 2013-12-02 TURB 0.3364722366 #> 5119 2056E 3M CC37 2014 2014-01-06 CHLAC 1.5686159179 #> 5120 2056E 3M CC37 2014 2014-01-06 COLOR 2.9957322736 A #> 5121 2056E 3M CC37 2014 2014-01-06 DOSAT 4.3832758541 + #> 5122 2056E 3M CC37 2014 2014-01-06 NO23 -4.3428059215 #> 5123 2056E 3M CC37 2014 2014-01-06 SALIN 3.3032169733 #> 5124 2056E 3M CC37 2014 2014-01-06 TKN -0.5978370008 #> 5125 2056E 3M CC37 2014 2014-01-06 TN -0.5744756508 + #> 5126 2056E 3M CC37 2014 2014-01-06 TP -2.3025850930 #> 5127 2056E 3M CC37 2014 2014-01-06 TURB 0.2623642645 #> 5128 2056E 3M CC37 2014 2014-02-03 CHLAC 1.4816045409 #> 5129 2056E 3M CC37 2014 2014-02-03 COLOR 2.7725887222 #> 5130 2056E 3M CC37 2014 2014-02-03 DO 1.8562979904 #> 5131 2056E 3M CC37 2014 2014-02-03 DOSAT 4.3502779364 + #> 5132 2056E 3M CC37 2014 2014-02-03 NO23 -3.2968373663 #> 5133 2056E 3M CC37 2014 2014-02-03 SALIN 2.6461747974 #> 5134 2056E 3M CC37 2014 2014-02-03 TKN -0.1743533871 #> 5135 2056E 3M CC37 2014 2014-02-03 TN -0.1312482866 + #> 5136 2056E 3M CC37 2014 2014-02-03 TP -2.3025850930 #> 5137 2056E 3M CC37 2014 2014-02-03 TURB 0.7419373447 #> 5138 2056E 3M CC37 2014 2014-03-03 CHLAC 1.7578579176 #> 5139 2056E 3M CC37 2014 2014-03-03 COLOR 2.8903717579 A #> 5140 2056E 3M CC37 2014 2014-03-03 DO 1.8082887712 #> 5141 2056E 3M CC37 2014 2014-03-03 DOSAT 4.3579900568 + #> 5142 2056E 3M CC37 2014 2014-03-03 NO23 -4.5098600062 #> 5143 2056E 3M CC37 2014 2014-03-03 SALIN 3.1000922889 #> 5144 2056E 3M CC37 2014 2014-03-03 TKN -0.2744368457 #> 5145 2056E 3M CC37 2014 2014-03-03 TN -0.2600669054 + #> 5146 2056E 3M CC37 2014 2014-03-03 TP -1.8971199849 #> 5147 2056E 3M CC37 2014 2014-03-03 TURB 1.0296194172 #> 5148 2056E 3M CC37 2014 2014-04-07 CHLAC 2.2721258855 #> 5149 2056E 3M CC37 2014 2014-04-07 COLOR 2.9444389792 #> 5150 2056E 3M CC37 2014 2014-04-07 DO 1.8718021769 #> 5151 2056E 3M CC37 2014 2014-04-07 DOSAT 4.4953553200 + #> 5152 2056E 3M CC37 2014 2014-04-07 NO23 -4.9618451299 I #> 5153 2056E 3M CC37 2014 2014-04-07 SALIN 3.1000922889 #> 5154 2056E 3M CC37 2014 2014-04-07 TKN -0.4942963218 #> 5155 2056E 3M CC37 2014 2014-04-07 TN -0.4877603508 + #> 5156 2056E 3M CC37 2014 2014-04-07 TP -1.7147984281 #> 5157 2056E 3M CC37 2014 2014-04-07 TURB 1.2237754316 #> 5158 2056E 3M CC37 2014 2014-05-05 CHLAC 3.0445224377 #> 5159 2056E 3M CC37 2014 2014-05-05 COLOR 3.0910424534 #> 5160 2056E 3M CC37 2014 2014-05-05 DO 1.7917594692 #> 5161 2056E 3M CC37 2014 2014-05-05 DOSAT 4.4152196020 + #> 5162 2056E 3M CC37 2014 2014-05-05 NO23 -5.1159958098 I #> 5163 2056E 3M CC37 2014 2014-05-05 SALIN 3.2068032436 #> 5164 2056E 3M CC37 2014 2014-05-05 TKN -0.0100503359 #> 5165 2056E 3M CC37 2014 2014-05-05 TN -0.0060180723 + #> 5166 2056E 3M CC37 2014 2014-05-05 TP -1.2729656758 #> 5167 2056E 3M CC37 2014 2014-05-05 TURB 1.9315214116 #> 5168 2056E 3M CC37 2014 2014-06-02 CHLAC 2.2617630985 #> 5169 2056E 3M CC37 2014 2014-06-02 COLOR 3.2188758249 #> 5170 2056E 3M CC37 2014 2014-06-02 DO 1.6292405397 #> 5171 2056E 3M CC37 2014 2014-06-02 DOSAT 4.3040650932 + #> 5172 2056E 3M CC37 2014 2014-06-02 NO23 -5.1159958098 I #> 5173 2056E 3M CC37 2014 2014-06-02 SALIN 3.2425923515 #> 5174 2056E 3M CC37 2014 2014-06-02 TKN -0.1625189295 #> 5175 2056E 3M CC37 2014 2014-06-02 TN -0.1578240852 + #> 5176 2056E 3M CC37 2014 2014-06-02 TP -1.0216512475 #> 5177 2056E 3M CC37 2014 2014-06-02 TURB 1.4816045409 #> 5178 2056E 3M CC37 2014 2014-07-07 CHLAC 2.5649493575 #> 5179 2056E 3M CC37 2014 2014-07-07 COLOR 3.3672958300 A #> 5180 2056E 3M CC37 2014 2014-07-07 NO23 -5.5214609179 I #> 5181 2056E 3M CC37 2014 2014-07-07 SALIN 3.1398326175 #> 5182 2056E 3M CC37 2014 2014-07-07 TKN -0.0304592075 #> 5183 2056E 3M CC37 2014 2014-07-07 TN -0.0263439753 + #> 5184 2056E 3M CC37 2014 2014-07-07 TP -0.9675840263 #> 5185 2056E 3M CC37 2014 2014-07-07 TURB 1.5260563035 #> 5186 2056E 3M CC37 2014 2014-08-04 CHLAC 2.7080502011 #> 5187 2056E 3M CC37 2014 2014-08-04 COLOR 4.0073331852 A #> 5188 2056E 3M CC37 2014 2014-08-04 DO 1.7047480922 #> 5189 2056E 3M CC37 2014 2014-08-04 DOSAT 4.3214801348 + #> 5190 2056E 3M CC37 2014 2014-08-04 NO23 -4.5098600062 #> 5191 2056E 3M CC37 2014 2014-08-04 SALIN 2.4336133554 #> 5192 2056E 3M CC37 2014 2014-08-04 TKN 0.0953101798 #> 5193 2056E 3M CC37 2014 2014-08-04 TN 0.1052605107 + #> 5194 2056E 3M CC37 2014 2014-08-04 TP -0.7550225843 #> 5195 2056E 3M CC37 2014 2014-08-04 TURB 1.0296194172 #> 5196 2056E 3M CC37 2014 2014-09-08 CHLAC 0.5877866649 #> 5197 2056E 3M CC37 2014 2014-09-08 COLOR 3.6375861597 A #> 5198 2056E 3M CC37 2014 2014-09-08 DOSAT 3.7588718259 + #> 5199 2056E 3M CC37 2014 2014-09-08 NO23 -4.1997050779 #> 5200 2056E 3M CC37 2014 2014-09-08 SALIN 2.6318888401 #> 5201 2056E 3M CC37 2014 2014-09-08 TKN -0.1743533871 #> 5202 2056E 3M CC37 2014 2014-09-08 TN -0.1566538100 + #> 5203 2056E 3M CC37 2014 2014-09-08 TP -1.0498221245 #> 5204 2056E 3M CC37 2014 2014-09-08 TURB 0.6931471806 A #> 5205 2056E 3M CC37 2014 2014-10-06 CHLAC 1.7917594692 #> 5206 2056E 3M CC37 2014 2014-10-06 COLOR 4.1588830834 A #> 5207 2056E 3M CC37 2014 2014-10-06 DO 1.3350010667 #> 5208 2056E 3M CC37 2014 2014-10-06 DOSAT 3.8458832029 + #> 5209 2056E 3M CC37 2014 2014-10-06 NO23 -2.9957322736 #> 5210 2056E 3M CC37 2014 2014-10-06 SALIN 1.9600947840 #> 5211 2056E 3M CC37 2014 2014-10-06 TKN -0.1508228897 #> 5212 2056E 3M CC37 2014 2014-10-06 TN -0.0943106795 + #> 5213 2056E 3M CC37 2014 2014-10-06 TP -1.1086626245 #> 5214 2056E 3M CC37 2014 2014-10-06 TURB 0.8754687374 #> 5215 2056E 3M CC37 2014 2014-11-03 CHLAC 2.1517622033 #> 5216 2056E 3M CC37 2014 2014-11-03 COLOR 3.9318256327 A #> 5217 2056E 3M CC37 2014 2014-11-03 DO 1.8245492921 #> 5218 2056E 3M CC37 2014 2014-11-03 DOSAT 4.2499227940 + #> 5219 2056E 3M CC37 2014 2014-11-03 NO23 -4.2686979494 #> 5220 2056E 3M CC37 2014 2014-11-03 SALIN 2.7600099400 #> 5221 2056E 3M CC37 2014 2014-11-03 TKN -0.1508228897 #> 5222 2056E 3M CC37 2014 2014-11-03 TN -0.1346749033 + #> 5223 2056E 3M CC37 2014 2014-11-03 TP -1.5606477483 #> 5224 2056E 3M CC37 2014 2014-11-03 TURB 0.7884573604 #> 5225 2056E 3M CC37 2014 2014-12-01 CHLAC 2.1633230257 #> 5226 2056E 3M CC37 2014 2014-12-01 COLOR 3.4657359028 #> 5227 2056E 3M CC37 2014 2014-12-01 DO 1.9600947840 #> 5228 2056E 3M CC37 2014 2014-12-01 DOSAT 4.4343818650 + #> 5229 2056E 3M CC37 2014 2014-12-01 NO23 -3.4737680745 #> 5230 2056E 3M CC37 2014 2014-12-01 SALIN 2.8622008809 #> 5231 2056E 3M CC37 2014 2014-12-01 TKN -0.3147107448 #> 5232 2056E 3M CC37 2014 2014-12-01 TN -0.2731219211 + #> 5233 2056E 3M CC37 2014 2014-12-01 TP -1.9661128564 #> 5234 2056E 3M CC37 2014 2014-12-01 TURB 0.7884573604 #> 5235 2056E 3M CC37 2015 2015-01-05 CHLAC 1.8870696490 #> 5236 2056E 3M CC37 2015 2015-01-05 COLOR 3.2958368660 A #> 5237 2056E 3M CC37 2015 2015-01-05 DO 1.7917594692 #> 5238 2056E 3M CC37 2015 2015-01-05 DOSAT 4.3732381286 + #> 5239 2056E 3M CC37 2015 2015-01-05 NO23 -3.9633162998 #> 5240 2056E 3M CC37 2015 2015-01-05 SALIN 2.9549102790 #> 5241 2056E 3M CC37 2015 2015-01-05 TKN -0.4780358009 #> 5242 2056E 3M CC37 2015 2015-01-05 TN -0.4478508246 + #> 5243 2056E 3M CC37 2015 2015-01-05 TP -2.1202635362 #> 5244 2056E 3M CC37 2015 2015-01-05 TURB 0.8754687374 #> 5245 2056E 3M CC37 2015 2015-02-02 CHLAC 1.6094379124 #> 5246 2056E 3M CC37 2015 2015-02-02 COLOR 2.8332133441 A #> 5247 2056E 3M CC37 2015 2015-02-02 DO 1.8245492921 #> 5248 2056E 3M CC37 2015 2015-02-02 DOSAT 4.3333614627 + #> 5249 2056E 3M CC37 2015 2015-02-02 NO23 -4.6051701860 #> 5250 2056E 3M CC37 2015 2015-02-02 SALIN 3.0773122605 #> 5251 2056E 3M CC37 2015 2015-02-02 TKN -0.6733445533 #> 5252 2056E 3M CC37 2015 2015-02-02 TN -0.6539264674 + #> 5253 2056E 3M CC37 2015 2015-02-02 TP -2.1202635362 #> 5254 2056E 3M CC37 2015 2015-02-02 TURB 0.9162907319 #> 5255 2056E 3M CC37 2015 2015-03-02 CHLAC 2.0014800002 #> 5256 2056E 3M CC37 2015 2015-03-02 COLOR 3.2958368660 #> 5257 2056E 3M CC37 2015 2015-03-02 DO 1.6486586256 #> 5258 2056E 3M CC37 2015 2015-03-02 DOSAT 4.2002049529 + #> 5259 2056E 3M CC37 2015 2015-03-02 NO23 -2.9759296463 #> 5260 2056E 3M CC37 2015 2015-03-02 SALIN 2.9285235239 #> 5261 2056E 3M CC37 2015 2015-03-02 TKN -0.3566749439 #> 5262 2056E 3M CC37 2015 2015-03-02 TN -0.2863496272 + #> 5263 2056E 3M CC37 2015 2015-03-02 TP -2.0402208285 #> 5264 2056E 3M CC37 2015 2015-03-02 TURB 0.7419373447 #> 5265 2056E 3M CC37 2015 2015-04-06 CHLAC 1.8245492921 #> 5266 2056E 3M CC37 2015 2015-04-06 COLOR 3.2188758249 A #> 5267 2056E 3M CC37 2015 2015-04-06 DO 1.6292405397 #> 5268 2056E 3M CC37 2015 2015-04-06 DOSAT 4.2297491992 + #> 5269 2056E 3M CC37 2015 2015-04-06 NO23 -4.5098600062 #> 5270 2056E 3M CC37 2015 2015-04-06 SALIN 3.0252910758 #> 5271 2056E 3M CC37 2015 2015-04-06 TKN -0.1165338163 #> 5272 2056E 3M CC37 2015 2015-04-06 TN -0.1042500214 + #> 5273 2056E 3M CC37 2015 2015-04-06 TP -1.6094379124 #> 5274 2056E 3M CC37 2015 2015-04-06 TURB 1.3083328197 #> 5275 2056E 3M CC37 2015 2015-05-04 CHLAC 1.7917594692 #> 5276 2056E 3M CC37 2015 2015-05-04 COLOR 3.2958368660 A #> 5277 2056E 3M CC37 2015 2015-05-04 DO 1.4816045409 #> 5278 2056E 3M CC37 2015 2015-05-04 DOSAT 4.0724397268 + #> 5279 2056E 3M CC37 2015 2015-05-04 NO23 -5.2983173665 I #> 5280 2056E 3M CC37 2015 2015-05-04 SALIN 3.0773122605 #> 5281 2056E 3M CC37 2015 2015-05-04 TKN -0.3856624808 #> 5282 2056E 3M CC37 2015 2015-05-04 TN -0.3797973614 + #> 5283 2056E 3M CC37 2015 2015-05-04 TP -2.0402208285 #> 5284 2056E 3M CC37 2015 2015-05-04 TURB 1.3350010667 #> 5285 2056E 3M CC37 2015 2015-06-01 CHLAC 2.7080502011 #> 5286 2056E 3M CC37 2015 2015-06-01 COLOR 3.2188758249 A #> 5287 2056E 3M CC37 2015 2015-06-01 DOSAT 4.0587173846 + #> 5288 2056E 3M CC37 2015 2015-06-01 NO23 -5.1159958098 I #> 5289 2056E 3M CC37 2015 2015-06-01 SALIN 2.8332133441 #> 5290 2056E 3M CC37 2015 2015-06-01 TKN 0.0000000000 #> 5291 2056E 3M CC37 2015 2015-06-01 TN 0.0039920213 + #> 5292 2056E 3M CC37 2015 2015-06-01 TP -1.1711829815 #> 5293 2056E 3M CC37 2015 2015-06-01 TURB 1.5475625087 A #> 5294 2056E 3M CC37 2015 2015-08-03 CHLAC 3.2580965380 #> 5295 2056E 3M CC37 2015 2015-08-03 COLOR 3.8286413965 #> 5296 2056E 3M CC37 2015 2015-08-03 DO 1.9169226122 #> 5297 2056E 3M CC37 2015 2015-08-03 DOSAT 4.4784725329 + #> 5298 2056E 3M CC37 2015 2015-08-03 NO23 -4.0173835211 #> 5299 2056E 3M CC37 2015 2015-08-03 SALIN 1.9021075264 #> 5300 2056E 3M CC37 2015 2015-08-03 TKN 0.0000000000 #> 5301 2056E 3M CC37 2015 2015-08-03 TN 0.0178399181 + #> 5302 2056E 3M CC37 2015 2015-08-03 TP -0.8439700703 #> 5303 2056E 3M CC37 2015 2015-08-03 TURB 1.0986122887 A #> 5304 2056E 3M CC37 2015 2015-09-08 CHLAC 2.7080502011 #> 5305 2056E 3M CC37 2015 2015-09-08 COLOR 4.7004803658 A #> 5306 2056E 3M CC37 2015 2015-09-08 DO 1.7227665977 #> 5307 2056E 3M CC37 2015 2015-09-08 DOSAT 4.3067641502 + #> 5308 2056E 3M CC37 2015 2015-09-08 NO23 -3.3242363405 #> 5309 2056E 3M CC37 2015 2015-09-08 SALIN 1.7749523509 #> 5310 2056E 3M CC37 2015 2015-09-08 TKN 0.1823215568 #> 5311 2056E 3M CC37 2015 2015-09-08 TN 0.2118803590 + #> 5312 2056E 3M CC37 2015 2015-09-08 TP -0.2613647641 #> 5313 2056E 3M CC37 2015 2015-09-08 TURB 1.3083328197 #> 5314 2056E 3M CC37 2015 2015-10-05 CHLAC 2.3978952728 #> 5315 2056E 3M CC37 2015 2015-10-05 COLOR 4.5643481915 A #> 5316 2056E 3M CC37 2015 2015-10-05 DO 1.8562979904 #> 5317 2056E 3M CC37 2015 2015-10-05 DOSAT 4.3732381286 + #> 5318 2056E 3M CC37 2015 2015-10-05 NO23 -3.7722610631 #> 5319 2056E 3M CC37 2015 2015-10-05 SALIN 2.2721258855 #> 5320 2056E 3M CC37 2015 2015-10-05 TKN -0.2876820725 #> 5321 2056E 3M CC37 2015 2015-10-05 TN -0.2574762304 + #> 5322 2056E 3M CC37 2015 2015-10-05 TP -0.9416085399 #> 5323 2056E 3M CC37 2015 2015-10-05 TURB 0.4054651081 #> 5324 2056E 3M CC37 2016 2016-02-01 CHLAC 2.6390573296 #> 5325 2056E 3M CC37 2016 2016-02-01 COLOR 4.5217885770 A #> 5326 2056E 3M CC37 2016 2016-02-01 NO23 -1.9661128564 #> 5327 2056E 3M CC37 2016 2016-02-01 TKN -0.3285040670 #> 5328 2056E 3M CC37 2016 2016-02-01 TN -0.1508228897 + #> 5329 2056E 3M CC37 2016 2016-02-01 TP -1.0216512475 #> 5330 2056E 3M CC37 2016 2016-02-01 TURB 0.9162907319 #> 5331 2056E 3M CC37 2016 2016-03-07 CHLAC 2.4849066498 #> 5332 2056E 3M CC37 2016 2016-03-07 COLOR 3.8918202981 A #> 5333 2056E 3M CC37 2016 2016-03-07 DO 1.6331544391 #> 5334 2056E 3M CC37 2016 2016-03-07 DOSAT 4.0859763126 + #> 5335 2056E 3M CC37 2016 2016-03-07 NO23 -4.1997050779 #> 5336 2056E 3M CC37 2016 2016-03-07 SALIN 2.7040421797 #> 5337 2056E 3M CC37 2016 2016-03-07 TKN -0.3011050928 #> 5338 2056E 3M CC37 2016 2016-03-07 TN -0.2810375297 + #> 5339 2056E 3M CC37 2016 2016-03-07 TP -1.5141277326 #> 5340 2056E 3M CC37 2016 2016-03-07 TURB 1.2527629685 #> 5341 2056E 3M CC37 2016 2016-04-04 CHLAC 2.3978952728 #> 5342 2056E 3M CC37 2016 2016-04-04 COLOR 3.6635616461 #> 5343 2056E 3M CC37 2016 2016-04-04 DO 1.3711807233 #> 5344 2056E 3M CC37 2016 2016-04-04 DOSAT 3.9512437186 + #> 5345 2056E 3M CC37 2016 2016-04-04 NO23 -3.5065578973 #> 5346 2056E 3M CC37 2016 2016-04-04 SALIN 2.6905648868 #> 5347 2056E 3M CC37 2016 2016-04-04 TKN -0.0202027073 #> 5348 2056E 3M CC37 2016 2016-04-04 TN 0.0099503309 + #> 5349 2056E 3M CC37 2016 2016-04-04 TP -1.3470736480 #> 5350 2056E 3M CC37 2016 2016-04-04 TURB 1.5260563035 #> 5351 2056E 3M CC37 2017 2017-02-06 CHLAC 2.8903717579 #> 5352 2056E 3M CC37 2017 2017-02-06 COLOR 2.9444389792 A #> 5353 2056E 3M CC37 2017 2017-02-06 DO 1.6311994042 #> 5354 2056E 3M CC37 2017 2017-02-06 DOSAT 4.2239097666 + #> 5355 2056E 3M CC37 2017 2017-02-06 NO23 -5.5214609179 U #> 5356 2056E 3M CC37 2017 2017-02-06 SALIN 3.3138223022 #> 5357 2056E 3M CC37 2017 2017-02-06 TKN -0.0943106795 #> 5358 2056E 3M CC37 2017 2017-02-06 TN -0.0921152889 + #> 5359 2056E 3M CC37 2017 2017-02-06 TP -1.7147984281 #> 5360 2056E 3M CC37 2017 2017-02-06 TURB 1.8562979904 #> 5361 2056E 3M CC37 2017 2017-03-06 CHLAC 2.1517622033 #> 5362 2056E 3M CC37 2017 2017-03-06 COLOR 2.7080502011 #> 5363 2056E 3M CC37 2017 2017-03-06 DO 1.7191887764 #> 5364 2056E 3M CC37 2017 2017-03-06 DOSAT 4.2931954210 + #> 5365 2056E 3M CC37 2017 2017-03-06 NO23 -5.5214609179 U #> 5366 2056E 3M CC37 2017 2017-03-06 SALIN 3.3279095859 #> 5367 2056E 3M CC37 2017 2017-03-06 TKN -0.1743533871 #> 5368 2056E 3M CC37 2017 2017-03-06 TN -0.1719752647 + #> 5369 2056E 3M CC37 2017 2017-03-06 TP -1.9661128564 #> 5370 2056E 3M CC37 2017 2017-03-06 TURB 1.3862943611 #> 5371 2056E 3M CC37 2017 2017-04-03 CHLAC 2.3978952728 #> 5372 2056E 3M CC37 2017 2017-04-03 COLOR 2.7080502011 A #> 5373 2056E 3M CC37 2017 2017-04-03 DO 1.5727739281 #> 5374 2056E 3M CC37 2017 2017-04-03 DOSAT 4.2640873368 + #> 5375 2056E 3M CC37 2017 2017-04-03 NO23 -5.5214609179 U #> 5376 2056E 3M CC37 2017 2017-04-03 SALIN 3.3914836895 #> 5377 2056E 3M CC37 2017 2017-04-03 TKN -0.1508228897 #> 5378 2056E 3M CC37 2017 2017-04-03 TN -0.1485000083 + #> 5379 2056E 3M CC37 2017 2017-04-03 TP -1.6607312068 #> 5380 2056E 3M CC37 2017 2017-04-03 TURB 1.3862943611 A #> 5381 2056E 3M CC37 2017 2017-07-10 CHLAC 2.7080502011 #> 5382 2056E 3M CC37 2017 2017-07-10 COLOR 4.7874917428 A #> 5383 2056E 3M CC37 2017 2017-07-10 DO 0.8415671857 #> 5384 2056E 3M CC37 2017 2017-07-10 DOSAT 3.4965075615 + #> 5385 2056E 3M CC37 2017 2017-07-10 NO23 -5.1159958098 I #> 5386 2056E 3M CC37 2017 2017-07-10 TKN 0.1823215568 #> 5387 2056E 3M CC37 2017 2017-07-10 TN 0.1856493469 + #> 5388 2056E 3M CC37 2017 2017-07-10 TP -0.4780358009 #> 5389 2056E 3M CC37 2017 2017-07-10 TURB 1.1939224685 #> 5390 2056E 3M CC37 2017 2017-08-07 CHLAC 1.6863989536 #> 5391 2056E 3M CC37 2017 2017-08-07 COLOR 4.7004803658 #> 5392 2056E 3M CC37 2017 2017-08-07 DO 0.7793248768 #> 5393 2056E 3M CC37 2017 2017-08-07 DOSAT 3.4144426084 + #> 5394 2056E 3M CC37 2017 2017-08-07 NO23 -2.2072749132 #> 5395 2056E 3M CC37 2017 2017-08-07 SALIN 1.7647307968 #> 5396 2056E 3M CC37 2017 2017-08-07 TKN 0.1823215568 #> 5397 2056E 3M CC37 2017 2017-08-07 TN 0.2700271372 + #> 5398 2056E 3M CC37 2017 2017-08-07 TP -0.8209805521 #> 5399 2056E 3M CC37 2017 2017-08-07 TURB 0.7884573604 #> 5400 2056E 3M CC37 2017 2017-09-05 CHLAC 2.8332133441 #> 5401 2056E 3M CC37 2017 2017-09-05 COLOR 4.4998096703 #> 5402 2056E 3M CC37 2017 2017-09-05 DO 1.4516138272 #> 5403 2056E 3M CC37 2017 2017-09-05 DOSAT 4.0377742107 + #> 5404 2056E 3M CC37 2017 2017-09-05 NO23 -2.4889146712 #> 5405 2056E 3M CC37 2017 2017-09-05 SALIN 0.1906203596 #> 5406 2056E 3M CC37 2017 2017-09-05 TKN -0.0725706928 #> 5407 2056E 3M CC37 2017 2017-09-05 TN 0.0129162253 + #> 5408 2056E 3M CC37 2017 2017-09-05 TP -0.9675840263 #> 5409 2056E 3M CC37 2017 2017-09-05 TURB 1.0986122887 #> 5410 2056E 3M CC37 2017 2017-10-02 CHLAC 1.9169226122 #> 5411 2056E 3M CC37 2017 2017-10-02 COLOR 4.4886363697 A #> 5412 2056E 3M CC37 2017 2017-10-02 NO23 -2.9565115604 #> 5413 2056E 3M CC37 2017 2017-10-02 TKN -0.8675005677 #> 5414 2056E 3M CC37 2017 2017-10-02 TN -0.7507762934 + #> 5415 2056E 3M CC37 2017 2017-10-02 TP -0.6348782724 #> 5416 2056E 3M CC37 2017 2017-10-02 TURB 0.7419373447 #> 5417 2056E 3M CC37 2017 2017-11-06 CHLAC 1.6292405397 #> 5418 2056E 3M CC37 2017 2017-11-06 COLOR 3.8918202981 A #> 5419 2056E 3M CC37 2017 2017-11-06 DO 1.7595805709 #> 5420 2056E 3M CC37 2017 2017-11-06 DOSAT 4.3605476030 #> 5421 2056E 3M CC37 2017 2017-11-06 NO23 -3.7722610631 #> 5422 2056E 3M CC37 2017 2017-11-06 SALIN 2.9549102790 #> 5423 2056E 3M CC37 2017 2017-11-06 TKN -0.4620354596 #> 5424 2056E 3M CC37 2017 2017-11-06 TN -0.4261781497 + #> 5425 2056E 3M CC37 2017 2017-11-06 TP -1.4696759701 #> 5426 2056E 3M CC37 2017 2017-11-06 TURB 0.2623642645 #> 5427 2056E 3M CC37 2017 2017-12-04 CHLAC 1.6677068206 #> 5428 2056E 3M CC37 2017 2017-12-04 COLOR 3.4657359028 #> 5429 2056E 3M CC37 2017 2017-12-04 DO 1.5686159179 #> 5430 2056E 3M CC37 2017 2017-12-04 DOSAT 4.1541845626 #> 5431 2056E 3M CC37 2017 2017-12-04 NO23 -5.5214609179 U #> 5432 2056E 3M CC37 2017 2017-12-04 SALIN 3.0914968955 #> 5433 2056E 3M CC37 2017 2017-12-04 TKN -0.1743533871 #> 5434 2056E 3M CC37 2017 2017-12-04 TN -0.1719752647 + #> 5435 2056E 3M CC37 2017 2017-12-04 TP -1.2039728043 #> 5436 2056E 3M CC37 2017 2017-12-04 TURB 1.0647107370 #> 5437 2056E 3M CC37 2018 2018-01-02 CHLAC 2.8332133441 #> 5438 2056E 3M CC37 2018 2018-01-02 COLOR 3.2188758249 #> 5439 2056E 3M CC37 2018 2018-01-02 DO 1.7101878155 #> 5440 2056E 3M CC37 2018 2018-01-02 DOSAT 4.1789920363 + #> 5441 2056E 3M CC37 2018 2018-01-02 NO23 -5.2983173665 I #> 5442 2056E 3M CC37 2018 2018-01-02 SALIN 3.1045866785 #> 5443 2056E 3M CC37 2018 2018-01-02 TKN -0.1278333715 #> 5444 2056E 3M CC37 2018 2018-01-02 TN -0.1232982163 + #> 5445 2056E 3M CC37 2018 2018-01-02 TP -0.6348782724 #> 5446 2056E 3M CC37 2018 2018-01-02 TURB 1.5040773968 #> 5447 2056E 3M CC37 2018 2018-02-05 CHLAC 3.0445224377 #> 5448 2056E 3M CC37 2018 2018-02-05 COLOR 3.0910424534 #> 5449 2056E 3M CC37 2018 2018-02-05 DO 1.7227665977 #> 5450 2056E 3M CC37 2018 2018-02-05 DOSAT 4.3067641502 #> 5451 2056E 3M CC37 2018 2018-02-05 NO23 -4.1351665567 #> 5452 2056E 3M CC37 2018 2018-02-05 SALIN 3.1311369106 #> 5453 2056E 3M CC37 2018 2018-02-05 TKN -0.5108256238 #> 5454 2056E 3M CC37 2018 2018-02-05 TN -0.4845083154 + #> 5455 2056E 3M CC37 2018 2018-02-05 TP -2.0402208285 #> 5456 2056E 3M CC37 2018 2018-02-05 TURB 1.3609765531 #> 5457 2056E 3M CC37 2018 2018-03-05 CHLAC 1.9315214116 #> 5458 2056E 3M CC37 2018 2018-03-05 COLOR 3.1780538303 A #> 5459 2056E 3M CC37 2018 2018-03-05 DO 1.4973884086 #> 5460 2056E 3M CC37 2018 2018-03-05 DOSAT 4.0656020934 #> 5461 2056E 3M CC37 2018 2018-03-05 NO23 -5.2983173665 I #> 5462 2056E 3M CC37 2018 2018-03-05 SALIN 3.1540172525 #> 5463 2056E 3M CC37 2018 2018-03-05 TKN -0.2613647641 #> 5464 2056E 3M CC37 2018 2018-03-05 TN -0.2561834054 + #> 5465 2056E 3M CC37 2018 2018-03-05 TP -1.6607312068 #> 5466 2056E 3M CC37 2018 2018-03-05 TURB 1.3083328197 #> 5467 2056E 3M CC37 2018 2018-04-02 CHLAC 2.3978952728 #> 5468 2056E 3M CC37 2018 2018-04-02 COLOR 2.9444389792 A #> 5469 2056E 3M CC37 2018 2018-04-02 DO 1.3660916538 #> 5470 2056E 3M CC37 2018 2018-04-02 DOSAT 3.9963641539 #> 5471 2056E 3M CC37 2018 2018-04-02 NO23 -4.8283137373 I #> 5472 2056E 3M CC37 2018 2018-04-02 SALIN 3.2461018111 #> 5473 2056E 3M CC37 2018 2018-04-02 TKN -0.2613647641 #> 5474 2056E 3M CC37 2018 2018-04-02 TN -0.2561834054 + #> 5475 2056E 3M CC37 2018 2018-04-02 TP -1.6607312068 #> 5476 2056E 3M CC37 2018 2018-04-02 TURB 1.4109869737 A #> 5477 2056E 3M CC37 2018 2018-05-07 CHLAC 2.6390573296 #> 5478 2056E 3M CC37 2018 2018-05-07 COLOR 3.0445224377 #> 5479 2056E 3M CC37 2018 2018-05-07 DO 1.4011829736 #> 5480 2056E 3M CC37 2018 2018-05-07 DOSAT 4.0656020934 #> 5481 2056E 3M CC37 2018 2018-05-07 NO23 -5.2983173665 I #> 5482 2056E 3M CC37 2018 2018-05-07 SALIN 3.3225148596 #> 5483 2056E 3M CC37 2018 2018-05-07 TKN -0.0833816089 #> 5484 2056E 3M CC37 2018 2018-05-07 TN -0.0790432073 + #> 5485 2056E 3M CC37 2018 2018-05-07 TP -1.5606477483 #> 5486 2056E 3M CC37 2018 2018-05-07 TURB 1.5260563035 #> 5487 2056E 3M CC37 2018 2018-06-04 CHLAC 3.2958368660 #> 5488 2056E 3M CC37 2018 2018-06-04 COLOR 4.4773368145 #> 5489 2056E 3M CC37 2018 2018-06-04 DO 1.9286186519 #> 5490 2056E 3M CC37 2018 2018-06-04 DOSAT 4.5390303835 #> 5491 2056E 3M CC37 2018 2018-06-04 NO23 -4.0745419349 #> 5492 2056E 3M CC37 2018 2018-06-04 SALIN 1.9095425049 #> 5493 2056E 3M CC37 2018 2018-06-04 TKN 0.1823215568 #> 5494 2056E 3M CC37 2018 2018-06-04 TN 0.1963888140 + #> 5495 2056E 3M CC37 2018 2018-06-04 TP -0.9942522733 #> 5496 2056E 3M CC37 2018 2018-06-04 TURB 1.3862943611 #> 5497 2056E 3M CC37 2018 2018-07-09 CHLAC 2.6390573296 #> 5498 2056E 3M CC37 2018 2018-07-09 COLOR 4.8675344505 #> 5499 2056E 3M CC37 2018 2018-07-09 DO 1.2919836816 #> 5500 2056E 3M CC37 2018 2018-07-09 DOSAT 3.7977338590 #> 5501 2056E 3M CC37 2018 2018-07-09 NO23 -2.6310891600 #> 5502 2056E 3M CC37 2018 2018-07-09 SALIN 1.8148247422 #> 5503 2056E 3M CC37 2018 2018-07-09 TKN 0.1823215568 #> 5504 2056E 3M CC37 2018 2018-07-09 TN 0.2405904649 + #> 5505 2056E 3M CC37 2018 2018-07-09 TP -0.8675005677 #> 5506 2056E 3M CC37 2018 2018-07-09 TURB 0.6931471806 A #> 5507 2056E 3M CC37 2018 2018-08-06 CHLAC 1.8562979904 #> 5508 2056E 3M CC37 2018 2018-08-06 COLOR 4.8675344505 #> 5509 2056E 3M CC37 2018 2018-08-06 DO 1.3428648032 #> 5510 2056E 3M CC37 2018 2018-08-06 DOSAT 3.9435216725 #> 5511 2056E 3M CC37 2018 2018-08-06 NO23 -1.8325814637 #> 5512 2056E 3M CC37 2018 2018-08-06 SALIN 1.1281710909 #> 5513 2056E 3M CC37 2018 2018-08-06 TKN 0.0953101798 #> 5514 2056E 3M CC37 2018 2018-08-06 TN 0.2311117210 + #> 5515 2056E 3M CC37 2018 2018-08-06 TP -0.8209805521 #> 5516 2056E 3M CC37 2018 2018-08-06 TURB 0.5877866649 #> 5517 2056E 3M CC37 2019 2019-02-04 CHLAC 1.9878743482 A #> 5518 2056E 3M CC37 2019 2019-02-04 COLOR 3.3322045102 #> 5519 2056E 3M CC37 2019 2019-02-04 DO 2.0438143640 #> 5520 2056E 3M CC37 2019 2019-02-04 DOSAT 4.5622626850 #> 5521 2056E 3M CC37 2019 2019-02-04 NO23 -5.2983173665 I #> 5522 2056E 3M CC37 2019 2019-02-04 SALIN 2.7447035188 #> 5523 2056E 3M CC37 2019 2019-02-04 TKN -0.4780358009 #> 5524 2056E 3M CC37 2019 2019-02-04 TN -0.4716049106 + #> 5525 2056E 3M CC37 2019 2019-02-04 TP -1.7147984281 #> 5526 2056E 3M CC37 2019 2019-02-04 TURB 0.7884573604 #> 5527 2056E 3M CC37 2019 2019-05-06 CHLAC 2.3978952728 #> 5528 2056E 3M CC37 2019 2019-05-06 COLOR 3.1780538303 A #> 5529 2056E 3M CC37 2019 2019-05-06 DO 1.3110318766 #> 5530 2056E 3M CC37 2019 2019-05-06 DOSAT 3.9759363312 #> 5531 2056E 3M CC37 2019 2019-05-06 NO23 -5.5214609179 U #> 5532 2056E 3M CC37 2019 2019-05-06 SALIN 3.0320642028 #> 5533 2056E 3M CC37 2019 2019-05-06 TN -0.2331938872 + #> 5534 2056E 3M CC37 2019 2019-05-06 TP -1.4696759701 #> 5535 2056E 3M CC37 2019 2019-05-06 TURB 1.3350010667 #> 5536 2056E 3M CC37 2019 2019-06-03 CHLAC 2.0281482473 #> 5537 2056E 3M CC37 2019 2019-06-03 COLOR 3.2188758249 A #> 5538 2056E 3M CC37 2019 2019-06-03 DO 1.2864740258 #> 5539 2056E 3M CC37 2019 2019-06-03 DOSAT 3.9815490681 #> 5540 2056E 3M CC37 2019 2019-06-03 NO23 -5.5214609179 U #> 5541 2056E 3M CC37 2019 2019-06-03 SALIN 2.9982291538 #> 5542 2056E 3M CC37 2019 2019-06-03 TKN -0.0512932944 #> 5543 2056E 3M CC37 2019 2019-06-03 TN -0.0491902442 + #> 5544 2056E 3M CC37 2019 2019-06-03 TP -0.9416085399 #> 5545 2056E 3M CC37 2019 2019-06-03 TURB 0.8754687374 #> 5546 2056E 3M CC37 2019 2019-07-01 CHLAC 3.1354942159 #> 5547 2056E 3M CC37 2019 2019-07-01 COLOR 3.5553480615 A #> 5548 2056E 3M CC37 2019 2019-07-01 DO 0.6259384309 #> 5549 2056E 3M CC37 2019 2019-07-01 DOSAT 3.1441522787 #> 5550 2056E 3M CC37 2019 2019-07-01 NO23 -5.5214609179 I #> 5551 2056E 3M CC37 2019 2019-07-01 SALIN 2.7825390531 #> 5552 2056E 3M CC37 2019 2019-07-01 TKN -0.1278333715 #> 5553 2056E 3M CC37 2019 2019-07-01 TN -0.1232982163 + #> 5554 2056E 3M CC37 2019 2019-07-01 TP -0.5798184953 #> 5555 2056E 3M CC37 2019 2019-07-01 TURB 1.0296194172 #> 5556 2056E 3M CC37 2019 2019-08-05 CHLAC 3.1354942159 #> 5557 2056E 3M CC37 2019 2019-08-05 COLOR 4.2341065046 A #> 5558 2056E 3M CC37 2019 2019-08-05 DO 1.9685099810 #> 5559 2056E 3M CC37 2019 2019-08-05 DOSAT 4.5880240272 #> 5560 2056E 3M CC37 2019 2019-08-05 NO23 -4.9618451299 I #> 5561 2056E 3M CC37 2019 2019-08-05 SALIN 2.0744289999 #> 5562 2056E 3M CC37 2019 2019-08-05 TKN -0.1053605157 #> 5563 2056E 3M CC37 2019 2019-08-05 TN -0.1009259186 + #> 5564 2056E 3M CC37 2019 2019-08-05 TP -1.1086626245 #> 5565 2056E 3M CC37 2019 2019-08-05 TURB 1.1314021115 #> 5566 2056E 3M CC37 2019 2019-10-07 CHLAC 2.0794415417 #> 5567 2056E 3M CC37 2019 2019-10-07 COLOR 3.7376696183 A #> 5568 2056E 3M CC37 2019 2019-10-07 DO 1.4036429995 #> 5569 2056E 3M CC37 2019 2019-10-07 DOSAT 4.0910056610 #> 5570 2056E 3M CC37 2019 2019-10-07 NO23 -5.5214609179 U #> 5571 2056E 3M CC37 2019 2019-10-07 SALIN 3.0842009215 #> 5572 2056E 3M CC37 2019 2019-10-07 TKN -0.3566749439 #> 5573 2056E 3M CC37 2019 2019-10-07 TN -0.3538218750 + #> 5574 2056E 3M CC37 2019 2019-10-07 TP -1.6607312068 #> 5575 2056E 3M CC37 2019 2019-10-07 TURB 0.4054651081 #> 5576 2056E 3M CC37 2019 2019-10-07 CHLAC 1.3609765531 #> 5577 2056E 3M CC37 2019 2019-10-07 COLOR 3.7612001157 A #> 5578 2056E 3M CC37 2019 2019-10-07 NO23 -5.5214609179 U #> 5579 2056E 3M CC37 2019 2019-10-07 TKN -0.3011050928 #> 5580 2056E 3M CC37 2019 2019-10-07 TN -0.2984060358 + #> 5581 2056E 3M CC37 2019 2019-10-07 TP -1.7147984281 #> 5582 2056E 3M CC37 2019 2019-10-07 TURB 0.4700036292 #> 5583 2056E 3M CC37 2019 2019-11-04 CHLAC 1.1939224685 #> 5584 2056E 3M CC37 2019 2019-11-04 COLOR 3.5835189385 #> 5585 2056E 3M CC37 2019 2019-11-04 DO 1.6034198401 #> 5586 2056E 3M CC37 2019 2019-11-04 DOSAT 4.2470656492 #> 5587 2056E 3M CC37 2019 2019-11-04 NO23 -4.4228486292 #> 5588 2056E 3M CC37 2019 2019-11-04 SALIN 2.9922261342 #> 5589 2056E 3M CC37 2019 2019-11-04 TKN -0.3285040670 #> 5590 2056E 3M CC37 2019 2019-11-04 TN -0.3119747650 + #> 5591 2056E 3M CC37 2019 2019-11-04 TP -1.4271163556 #> 5592 2056E 3M CC37 2019 2019-11-04 TURB 0.0000000000 #> 5593 2056E 3M CC37 2019 2019-12-02 CHLAC 1.8245492921 A #> 5594 2056E 3M CC37 2019 2019-12-02 COLOR 3.3322045102 #> 5595 2056E 3M CC37 2019 2019-12-02 DO 1.3532545070 #> 5596 2056E 3M CC37 2019 2019-12-02 DOSAT 3.9740583963 #> 5597 2056E 3M CC37 2019 2019-12-02 NO23 -5.2983173665 I #> 5598 2056E 3M CC37 2019 2019-12-02 SALIN 3.1363634033 #> 5599 2056E 3M CC37 2019 2019-12-02 TKN -0.4942963218 #> 5600 2056E 3M CC37 2019 2019-12-02 TN -0.4877603508 + #> 5601 2056E 3M CC37 2019 2019-12-02 TP -1.8325814637 #> 5602 2056E 3M CC37 2019 2019-12-02 TURB 0.7884573604 #> 5603 2056E 3M CC37 2020 2020-01-06 CHLAC 2.7080502011 #> 5604 2056E 3M CC37 2020 2020-01-06 COLOR 3.1354942159 A #> 5605 2056E 3M CC37 2020 2020-01-06 DO 2.0055258587 #> 5606 2056E 3M CC37 2020 2020-01-06 DOSAT 4.5347477217 #> 5607 2056E 3M CC37 2020 2020-01-06 NO23 -4.7105307016 I #> 5608 2056E 3M CC37 2020 2020-01-06 SALIN 3.0387917630 #> 5609 2056E 3M CC37 2020 2020-01-06 TKN -0.3710636814 #> 5610 2056E 3M CC37 2020 2020-01-06 TN -0.3652833185 + #> 5611 2056E 3M CC37 2020 2020-01-06 TP -1.6607312068 #> 5612 2056E 3M CC37 2020 2020-01-06 TURB 1.0647107370 #> 5613 2056E 3M CC37 2020 2020-02-03 CHLAC 2.5649493575 #> 5614 2056E 3M CC37 2020 2020-02-03 COLOR 2.9957322736 #> 5615 2056E 3M CC37 2020 2020-02-03 DO 1.8148247422 #> 5616 2056E 3M CC37 2020 2020-02-03 DOSAT 4.2808241292 #> 5617 2056E 3M CC37 2020 2020-02-03 NO23 -4.3428059215 #> 5618 2056E 3M CC37 2020 2020-02-03 SALIN 3.1175073305 #> 5619 2056E 3M CC37 2020 2020-02-03 TKN -0.3856624808 #> 5620 2056E 3M CC37 2020 2020-02-03 TN -0.3667252798 + #> 5621 2056E 3M CC37 2020 2020-02-03 TP -1.9661128564 #> 5622 2056E 3M CC37 2020 2020-02-03 TURB 1.4109869737 A #> 5623 2056E 3M CC37 2020 2020-03-02 CHLAC 1.9740810260 #> 5624 2056E 3M CC37 2020 2020-03-02 COLOR 2.8903717579 #> 5625 2056E 3M CC37 2020 2020-03-02 DO 1.8484548129 #> 5626 2056E 3M CC37 2020 2020-03-02 DOSAT 4.3832758541 #> 5627 2056E 3M CC37 2020 2020-03-02 NO23 -5.2983173665 I #> 5628 2056E 3M CC37 2020 2020-03-02 SALIN 3.1320098918 #> 5629 2056E 3M CC37 2020 2020-03-02 TKN -0.4004775666 #> 5630 2056E 3M CC37 2020 2020-03-02 TN -0.3945251681 + #> 5631 2056E 3M CC37 2020 2020-03-02 TP -1.9661128564 #> 5632 2056E 3M CC37 2020 2020-03-02 TURB 1.2809338455 A #> 5633 2056E 3M CC37 2020 2020-09-08 CHLAC 1.6486586256 #> 5634 2056E 3M CC37 2020 2020-09-08 COLOR 4.4998096703 #> 5635 2056E 3M CC37 2020 2020-09-08 DO 0.8837675402 #> 5636 2056E 3M CC37 2020 2020-09-08 DOSAT 3.5085559000 #> 5637 2056E 3M CC37 2020 2020-09-08 NO23 -3.1465551633 #> 5638 2056E 3M CC37 2020 2020-09-08 SALIN 2.2428350886 #> 5639 2056E 3M CC37 2020 2020-09-08 TKN -0.1743533871 #> 5640 2056E 3M CC37 2020 2020-09-08 TN -0.1244300784 + #> 5641 2056E 3M CC37 2020 2020-09-08 TP -0.9162907319 #> 5642 2056E 3M CC37 2020 2020-09-08 TURB 0.4700036292 #> 5643 2056E 3M CC37 2020 2020-10-05 CHLAC 1.7047480922 #> 5644 2056E 3M CC37 2020 2020-10-05 COLOR 4.5951198501 A #> 5645 2056E 3M CC37 2020 2020-10-05 DO 0.8837675402 #> 5646 2056E 3M CC37 2020 2020-10-05 DOSAT 3.4657359028 #> 5647 2056E 3M CC37 2020 2020-10-05 NO23 -3.2701691193 #> 5648 2056E 3M CC37 2020 2020-10-05 SALIN 2.6181254936 #> 5649 2056E 3M CC37 2020 2020-10-05 TKN 0.1823215568 #> 5650 2056E 3M CC37 2020 2020-10-05 TN 0.2134971743 + #> 5651 2056E 3M CC37 2020 2020-10-05 TP -0.7765287895 #> 5652 2056E 3M CC37 2020 2020-10-05 TURB 0.3364722366 #> 5653 2056E 3M CC37 2020 2020-10-05 CHLAC 1.8718021769 #> 5654 2056E 3M CC37 2020 2020-10-05 COLOR 4.6051701860 #> 5655 2056E 3M CC37 2020 2020-10-05 NO23 -3.5404594490 #> 5656 2056E 3M CC37 2020 2020-10-05 TKN 0.1823215568 #> 5657 2056E 3M CC37 2020 2020-10-05 TN 0.2062008306 + #> 5658 2056E 3M CC37 2020 2020-10-05 TP -0.7550225843 #> 5659 2056E 3M CC37 2020 2020-10-05 TURB 0.2623642645 #> 5660 2056E 3M CC37 2020 2020-11-02 CHLAC 2.1400661635 #> 5661 2056E 3M CC37 2020 2020-11-02 COLOR 4.2046926194 #> 5662 2056E 3M CC37 2020 2020-11-02 DO 1.8468787684 #> 5663 2056E 3M CC37 2020 2020-11-02 DOSAT 4.4670568839 #> 5664 2056E 3M CC37 2020 2020-11-02 NO23 -3.2968373663 #> 5665 2056E 3M CC37 2020 2020-11-02 SALIN 2.6525374912 #> 5666 2056E 3M CC37 2020 2020-11-02 TKN -0.3147107448 #> 5667 2056E 3M CC37 2020 2020-11-02 TN -0.2652684776 + #> 5668 2056E 3M CC37 2020 2020-11-02 TP -1.3093333200 #> 5669 2056E 3M CC37 2020 2020-11-02 TURB 0.6931471806 A #> 5670 2056E 3M CC37 2020 2020-12-07 CHLAC 1.6677068206 #> 5671 2056E 3M CC37 2020 2020-12-07 COLOR 3.8712010109 #> 5672 2056E 3M CC37 2020 2020-12-07 DO 1.9050881545 #> 5673 2056E 3M CC37 2020 2020-12-07 DOSAT 4.4164280614 #> 5674 2056E 3M CC37 2020 2020-12-07 NO23 -3.9633162998 #> 5675 2056E 3M CC37 2020 2020-12-07 SALIN 2.8735646396 #> 5676 2056E 3M CC37 2020 2020-12-07 TKN -0.4942963218 #> 5677 2056E 3M CC37 2020 2020-12-07 TN -0.4636240223 + #> 5678 2056E 3M CC37 2020 2020-12-07 TP -1.8325814637 #> 5679 2056E 3M CC37 2020 2020-12-07 TURB 0.1823215568 #> 5680 2056E 3M CC37 2021 2021-01-04 CHLAC 0.8754687374 I #> 5681 2056E 3M CC37 2021 2021-01-04 COLOR 3.5835189385 #> 5682 2056E 3M CC37 2021 2021-01-04 DO 1.4279160358 #> 5683 2056E 3M CC37 2021 2021-01-04 DOSAT 3.9569963711 #> 5684 2056E 3M CC37 2021 2021-01-04 NO23 -4.1351665567 #> 5685 2056E 3M CC37 2021 2021-01-04 SALIN 2.8249439526 #> 5686 2056E 3M CC37 2021 2021-01-04 TKN -0.3285040670 #> 5687 2056E 3M CC37 2021 2021-01-04 TN -0.3065251603 + #> 5688 2056E 3M CC37 2021 2021-01-04 TP -1.8971199849 #> 5689 2056E 3M CC37 2021 2021-01-04 TURB 0.6418538862 #> 5690 2056E 3M CC37 2021 2021-02-01 CHLAC 1.0986122887 #> 5691 2056E 3M CC37 2021 2021-02-01 COLOR 3.2958368660 A #> 5692 2056E 3M CC37 2021 2021-02-01 DO 2.0464016876 #> 5693 2056E 3M CC37 2021 2021-02-01 DOSAT 4.5767707115 #> 5694 2056E 3M CC37 2021 2021-02-01 NO23 -5.1159958098 I #> 5695 2056E 3M CC37 2021 2021-02-01 SALIN 2.9957322736 #> 5696 2056E 3M CC37 2021 2021-02-01 TKN -0.5108256238 #> 5697 2056E 3M CC37 2021 2021-02-01 TN -0.5041810810 + #> 5698 2056E 3M CC37 2021 2021-02-01 TP -2.1202635362 #> 5699 2056E 3M CC37 2021 2021-02-01 TURB 0.6418538862 #> 5700 2056E 3M CC37 2021 2021-03-01 CHLAC 1.5260563035 #> 5701 2056E 3M CC37 2021 2021-03-01 COLOR 3.2580965380 A #> 5702 2056E 3M CC37 2021 2021-03-01 DO 1.4134230285 #> 5703 2056E 3M CC37 2021 2021-03-01 DOSAT 4.0412953411 #> 5704 2056E 3M CC37 2021 2021-03-01 NO23 -5.1159958098 I #> 5705 2056E 3M CC37 2021 2021-03-01 SALIN 3.0445224377 #> 5706 2056E 3M CC37 2021 2021-03-01 TKN -0.6161861394 #> 5707 2056E 3M CC37 2021 2021-03-01 TN -0.6088060321 + #> 5708 2056E 3M CC37 2021 2021-03-01 TP -1.9661128564 #> 5709 2056E 3M CC37 2021 2021-03-01 TURB 1.1314021115 A #> 5710 2056E 3M CC37 2021 2021-04-05 CHLAC 1.7917594692 #> 5711 2056E 3M CC37 2021 2021-04-05 COLOR 3.1354942159 #> 5712 2056E 3M CC37 2021 2021-04-05 DO 1.5040773968 #> 5713 2056E 3M CC37 2021 2021-04-05 DOSAT 4.0604430105 #> 5714 2056E 3M CC37 2021 2021-04-05 NO23 -4.5098600062 #> 5715 2056E 3M CC37 2021 2021-04-05 SALIN 3.1599747169 #> 5716 2056E 3M CC37 2021 2021-04-05 TKN -0.1984509387 #> 5717 2056E 3M CC37 2021 2021-04-05 TN -0.1851254841 + #> 5718 2056E 3M CC37 2021 2021-04-05 TP -1.7719568419 #> 5719 2056E 3M CC37 2021 2021-04-05 TURB 1.7047480922 #> 5720 2056E 3M CC37 2021 2021-05-03 CHLAC 2.0149030205 #> 5721 2056E 3M CC37 2021 2021-05-03 COLOR 3.1354942159 #> 5722 2056E 3M CC37 2021 2021-05-03 DO 1.1314021115 #> 5723 2056E 3M CC37 2021 2021-05-03 DOSAT 3.8286413965 #> 5724 2056E 3M CC37 2021 2021-05-03 NO23 -4.8283137373 I #> 5725 2056E 3M CC37 2021 2021-05-03 SALIN 3.2196755050 #> 5726 2056E 3M CC37 2021 2021-05-03 TKN -0.3011050928 #> 5727 2056E 3M CC37 2021 2021-05-03 TN -0.2957142441 + #> 5728 2056E 3M CC37 2021 2021-05-03 TP -1.4696759701 #> 5729 2056E 3M CC37 2021 2021-05-03 TURB 1.5260563035 #> 5730 2056E 3M CC37 2021 2021-06-07 CHLAC 2.2617630985 #> 5731 2056E 3M CC37 2021 2021-06-07 COLOR 2.8903717579 #> 5732 2056E 3M CC37 2021 2021-06-07 DO 1.1314021115 #> 5733 2056E 3M CC37 2021 2021-06-07 DOSAT 3.8286413965 #> 5734 2056E 3M CC37 2021 2021-06-07 NO23 -5.5214609179 U #> 5735 2056E 3M CC37 2021 2021-06-07 SALIN 3.2196755050 #> 5736 2056E 3M CC37 2021 2021-06-07 TKN 0.0953101798 #> 5737 2056E 3M CC37 2021 2021-06-07 TN 0.0971267107 + #> 5738 2056E 3M CC37 2021 2021-06-07 TP -1.3093333200 #> 5739 2056E 3M CC37 2021 2021-06-07 TURB 1.2809338455 #> 5740 2056E 3M CC37 2021 2021-08-02 CHLAC 2.7080502011 #> 5741 2056E 3M CC37 2021 2021-08-02 COLOR 4.5217885770 #> 5742 2056E 3M CC37 2021 2021-08-02 DO 1.6034198401 #> 5743 2056E 3M CC37 2021 2021-08-02 DOSAT 4.2766661190 #> 5744 2056E 3M CC37 2021 2021-08-02 NO23 -5.5214609179 U #> 5745 2056E 3M CC37 2021 2021-08-02 SALIN 2.1871742415 #> 5746 2056E 3M CC37 2021 2021-08-02 TKN -0.1053605157 #> 5747 2056E 3M CC37 2021 2021-08-02 TN -0.1031407589 + #> 5748 2056E 3M CC37 2021 2021-08-02 TP -0.6733445533 #> 5749 2056E 3M CC37 2021 2021-08-02 TURB 0.8754687374 #> 5750 2056E 3M CC37 2021 2021-09-07 CHLAC 1.8405496334 #> 5751 2056E 3M CC37 2021 2021-09-07 COLOR 4.2341065046 #> 5752 2056E 3M CC37 2021 2021-09-07 DO 1.5260563035 #> 5753 2056E 3M CC37 2021 2021-09-07 DOSAT 4.1447207695 #> 5754 2056E 3M CC37 2021 2021-09-07 NO23 -3.6119184130 #> 5755 2056E 3M CC37 2021 2021-09-07 SALIN 2.0041790572 #> 5756 2056E 3M CC37 2021 2021-09-07 TKN -0.0943106795 #> 5757 2056E 3M CC37 2021 2021-09-07 TN -0.0650719967 + #> 5758 2056E 3M CC37 2021 2021-09-07 TP -1.0788096614 #> 5759 2056E 3M CC37 2021 2021-09-07 TURB 0.5306282511 A #> 5760 2056E 3M CC37 2021 2021-10-04 CHLAC 2.4849066498 #> 5761 2056E 3M CC37 2021 2021-10-04 COLOR 4.5643481915 A #> 5762 2056E 3M CC37 2021 2021-10-04 DO 0.4446858213 #> 5763 2056E 3M CC37 2021 2021-10-04 DOSAT 3.0587070727 #> 5764 2056E 3M CC37 2021 2021-10-04 NO23 -3.0576076773 #> 5765 2056E 3M CC37 2021 2021-10-04 SALIN 2.4932054526 #> 5766 2056E 3M CC37 2021 2021-10-04 TKN 0.0953101798 #> 5767 2056E 3M CC37 2021 2021-10-04 TN 0.1371498381 + #> 5768 2056E 3M CC37 2021 2021-10-04 TP -0.7985076962 #> 5769 2056E 3M CC37 2021 2021-10-04 TURB 0.4054651081 #> 5770 2056E 3M CC37 2021 2021-10-04 CHLAC 2.3978952728 A #> 5771 2056E 3M CC37 2021 2021-10-04 COLOR 4.5849674787 #> 5772 2056E 3M CC37 2021 2021-10-04 NO23 -3.0576076773 #> 5773 2056E 3M CC37 2021 2021-10-04 TKN 0.0000000000 #> 5774 2056E 3M CC37 2021 2021-10-04 TN 0.0459289319 + #> 5775 2056E 3M CC37 2021 2021-10-04 TP -0.8209805521 #> 5776 2056E 3M CC37 2021 2021-10-04 TURB 0.4700036292 #> 5777 2056E 3M CC37 2021 2021-11-01 CHLAC 1.7749523509 #> 5778 2056E 3M CC37 2021 2021-11-01 COLOR 3.7612001157 A #> 5779 2056E 3M CC37 2021 2021-11-01 DO 1.2325602612 #> 5780 2056E 3M CC37 2021 2021-11-01 DOSAT 3.8177123260 #> 5781 2056E 3M CC37 2021 2021-11-01 NO23 -3.5065578973 #> 5782 2056E 3M CC37 2021 2021-11-01 SALIN 2.9444389792 #> 5783 2056E 3M CC37 2021 2021-11-01 TKN -0.2231435513 #> 5784 2056E 3M CC37 2021 2021-11-01 TN -0.1863295782 + #> 5785 2056E 3M CC37 2021 2021-11-01 TP -1.6094379124 #> 5786 2056E 3M CC37 2021 2021-11-01 TURB 0.2623642645 #> 5787 2056E 3M CC37 2021 2021-12-06 CHLAC 1.7578579176 #> 5788 2056E 3M CC37 2021 2021-12-06 COLOR 3.0445224377 #> 5789 2056E 3M CC37 2021 2021-12-06 DO 1.5260563035 #> 5790 2056E 3M CC37 2021 2021-12-06 DOSAT 4.1157798429 #> 5791 2056E 3M CC37 2021 2021-12-06 NO23 -4.7105307016 I #> 5792 2056E 3M CC37 2021 2021-12-06 SALIN 3.1471649773 #> 5793 2056E 3M CC37 2021 2021-12-06 TKN -0.5978370008 #> 5794 2056E 3M CC37 2021 2021-12-06 TN -0.5905905922 + #> 5795 2056E 3M CC37 2021 2021-12-06 TP -2.1202635362 #> 5796 2056E 3M CC37 2021 2021-12-06 TURB 0.4700036292 #> 5797 2056E 3M CC37 2022 2022-01-03 CHLAC 2.1162555148 #> 5798 2056E 3M CC37 2022 2022-01-03 COLOR 2.8903717579 #> 5799 2056E 3M CC37 2022 2022-01-03 DO 1.2974631474 #> 5800 2056E 3M CC37 2022 2022-01-03 DOSAT 3.9160150267 #> 5801 2056E 3M CC37 2022 2022-01-03 NO23 -4.9618451299 I #> 5802 2056E 3M CC37 2022 2022-01-03 SALIN 3.1289511173 #> 5803 2056E 3M CC37 2022 2022-01-03 TKN -0.4780358009 #> 5804 2056E 3M CC37 2022 2022-01-03 TN -0.4716049106 + #> 5805 2056E 3M CC37 2022 2022-01-03 TP -1.9661128564 #> 5806 2056E 3M CC37 2022 2022-01-03 TURB 1.2809338455 A #> 5807 2056E 3M CC37 2022 2022-02-07 CHLAC 2.0918640617 #> 5808 2056E 3M CC37 2022 2022-02-07 COLOR 2.6390573296 #> 5809 2056E 3M CC37 2022 2022-02-07 DO 1.5518087996 #> 5810 2056E 3M CC37 2022 2022-02-07 DOSAT 4.1075897890 #> 5811 2056E 3M CC37 2022 2022-02-07 NO23 -4.1351665567 #> 5812 2056E 3M CC37 2022 2022-02-07 SALIN 3.2323841749 #> 5813 2056E 3M CC37 2022 2022-02-07 TKN -0.2484613593 #> 5814 2056E 3M CC37 2022 2022-02-07 TN -0.2281560931 + #> 5815 2056E 3M CC37 2022 2022-02-07 TP -2.1202635362 #> 5816 2056E 3M CC37 2022 2022-02-07 TURB 0.5877866649 #> 5817 2056E 3M CC37 2022 2022-03-07 CHLAC 1.3350010667 #> 5818 2056E 3M CC37 2022 2022-03-07 COLOR 2.3978952728 #> 5819 2056E 3M CC37 2022 2022-03-07 DO 1.5769147207 #> 5820 2056E 3M CC37 2022 2022-03-07 DOSAT 4.2150861799 #> 5821 2056E 3M CC37 2022 2022-03-07 NO23 -5.5214609179 I #> 5822 2056E 3M CC37 2022 2022-03-07 SALIN 3.2820383998 #> 5823 2056E 3M CC37 2022 2022-03-07 TKN -0.4004775666 #> 5824 2056E 3M CC37 2022 2022-03-07 TN -0.3945251681 + #> 5825 2056E 3M CC37 2022 2022-03-07 TP -2.0402208285 #> 5826 2056E 3M CC37 2022 2022-03-07 TURB 1.0647107370 #> 5827 2056E 3M CC37 2022 2022-04-04 CHLAC 1.6863989536 #> 5828 2056E 3M CC37 2022 2022-04-04 COLOR 2.5649493575 #> 5829 2056E 3M CC37 2022 2022-04-04 DO 1.4816045409 #> 5830 2056E 3M CC37 2022 2022-04-04 DOSAT 4.1319614258 #> 5831 2056E 3M CC37 2022 2022-04-04 NO23 -4.5098600062 #> 5832 2056E 3M CC37 2022 2022-04-04 SALIN 3.3311325072 #> 5833 2056E 3M CC37 2022 2022-04-04 TN -0.6520052372 + #> 5834 2056E 3M CC37 2022 2022-04-04 TP -1.7719568419 #> 5835 2056E 3M CC37 2022 2022-04-04 TURB 1.1631508098 #> 5836 2056E 3M CC37 2022 2022-05-02 CHLAC 1.5892352051 #> 5837 2056E 3M CC37 2022 2022-05-02 COLOR 2.7080502011 #> 5838 2056E 3M CC37 2022 2022-05-02 DO 1.3660916538 #> 5839 2056E 3M CC37 2022 2022-05-02 DOSAT 4.0500443033 #> 5840 2056E 3M CC37 2022 2022-05-02 NO23 -5.2983173665 I #> 5841 2056E 3M CC37 2022 2022-05-02 SALIN 3.3755376349 #> 5842 2056E 3M CC37 2022 2022-05-02 TKN -0.2744368457 #> 5843 2056E 3M CC37 2022 2022-05-02 TN -0.2691874898 + #> 5844 2056E 3M CC37 2022 2022-05-02 TP -1.6094379124 #> 5845 2056E 3M CC37 2022 2022-05-02 TURB 1.2527629685 A #> 5846 2056E 3M CC42 2019 2019-10-10 CHLAC 1.5892352051 #> 5847 2056E 3M CC42 2019 2019-10-10 COND 9.8078573215 #> 5848 2056E 3M CC42 2019 2019-10-10 NO23 -3.7722610631 #> 5849 2056E 3M CC42 2019 2019-10-10 SALIN 2.3721111556 #> 5850 2056E 3M CC42 2019 2019-10-10 TKN -0.3566749439 #> 5851 2056E 3M CC42 2019 2019-10-10 TN -0.3243460568 + #> 5852 2056E 3M CC42 2019 2019-10-10 TP -1.0498221245 #> 5853 2056E 3M CC42 2019 2019-10-10 TSS 1.7917594692 I #> 5854 2056E 3M CC42 2019 2019-10-10 TURB 1.0647107370 #> 5855 2056C2 3M CC45 2014 2014-06-10 COND 9.8892364868 #> 5856 2056C2 3M CC45 2014 2014-06-10 DO 1.9344157696 #> 5857 2056C2 3M CC45 2014 2014-06-10 DOSAT 4.5920849464 + #> 5858 2056C2 3M CC45 2014 2014-06-10 SALIN 2.4595888418 #> 5859 2056C2 3M CC45 2014 2014-06-10 NO23 -5.5214609179 U #> 5860 2056C2 3M CC45 2014 2014-06-10 TKN 1.2809338455 #> 5861 2056C2 3M CC45 2014 2014-06-10 TN 1.2809338455 #> 5862 2056C2 3M CC45 2014 2014-06-10 TSS 2.3513752572 #> 5863 2056C2 3M CC45 2014 2014-06-10 COND 9.8874597915 #> 5864 2056C2 3M CC45 2014 2014-06-10 DO 2.0014800002 #> 5865 2056C2 3M CC45 2014 2014-06-10 DOSAT 4.6587109529 + #> 5866 2056C2 3M CC45 2014 2014-06-10 SALIN 2.4587337755 #> 5867 2056C2 3M CC45 2014 2014-06-10 COND 9.9269599087 #> 5868 2056C2 3M CC45 2014 2014-06-10 DO 1.9933388426 #> 5869 2056C2 3M CC45 2014 2014-06-10 DOSAT 4.6510991179 + #> 5870 2056C2 3M CC45 2014 2014-06-10 SALIN 2.5014359517 #> 5871 2056C2 3M CC45 2014 2014-06-10 COND 9.9782238987 #> 5872 2056C2 3M CC45 2014 2014-06-10 DO 1.8916048042 #> 5873 2056C2 3M CC45 2014 2014-06-10 DOSAT 4.5475410732 + #> 5874 2056C2 3M CC45 2014 2014-06-10 SALIN 2.5572273114 #> 5875 2056C2 3M CC45 2014 2014-06-10 COND 10.0037852739 #> 5876 2056C2 3M CC45 2014 2014-06-10 DO 1.8017098001 #> 5877 2056C2 3M CC45 2014 2014-06-10 DOSAT 4.4578295981 + #> 5878 2056C2 3M CC45 2014 2014-06-10 SALIN 2.5862591440 #> 5879 2056C2 3M CC45 2014 2014-06-10 COND 10.0950165901 #> 5880 2056C2 3M CC45 2014 2014-06-10 DO 1.5475625087 #> 5881 2056C2 3M CC45 2014 2014-06-10 DOSAT 4.2061840440 + #> 5882 2056C2 3M CC45 2014 2014-06-10 SALIN 2.6932749155 #> 5883 2056C2 3M CC45 2014 2014-06-10 COND 10.1085078656 #> 5884 2056C2 3M CC45 2014 2014-06-10 DO 1.4562867329 #> 5885 2056C2 3M CC45 2014 2014-06-10 DOSAT 4.1141471895 + #> 5886 2056C2 3M CC45 2014 2014-06-10 SALIN 2.6932749155 #> 5887 2056C2 3M CC45 2014 2014-06-10 COND 10.1103391071 #> 5888 2056C2 3M CC45 2014 2014-06-10 DO 1.4182774070 #> 5889 2056C2 3M CC45 2014 2014-06-10 DOSAT 4.0775374439 + #> 5890 2056C2 3M CC45 2014 2014-06-10 SALIN 2.7020321288 #> 5891 2056C2 3M CC45 2014 2014-06-10 COND 10.1112331617 #> 5892 2056C2 3M CC45 2014 2014-06-10 DO 1.4109869737 #> 5893 2056C2 3M CC45 2014 2014-06-10 DOSAT 4.0690267542 + #> 5894 2056C2 3M CC45 2014 2014-06-10 SALIN 2.7027025948 #> 5895 2056C2 3M CC45 2014 2014-06-10 COND 10.1134242764 #> 5896 2056C2 3M CC45 2014 2014-06-10 DO 1.3787660947 #> 5897 2056C2 3M CC45 2014 2014-06-10 DOSAT 4.0377742107 + #> 5898 2056C2 3M CC45 2014 2014-06-10 SALIN 2.7053799725 #> 5899 2056C2 3M CC45 2014 2014-07-10 COND 9.9863570304 #> 5900 2056C2 3M CC45 2014 2014-07-10 DO 2.9204697891 #> 5901 2056C2 3M CC45 2014 2014-07-10 DOSAT 5.6028565561 + #> 5902 2056C2 3M CC45 2014 2014-07-10 SALIN 2.5664866368 #> 5903 2056C2 3M CC45 2014 2014-07-10 NO23 -4.1351665567 I #> 5904 2056C2 3M CC45 2014 2014-07-10 TKN 0.5933268453 #> 5905 2056C2 3M CC45 2014 2014-07-10 TN 0.5988365011 #> 5906 2056C2 3M CC45 2014 2014-07-10 TSS 2.6602595373 #> 5907 2056C2 3M CC45 2014 2014-07-10 COND 10.2631181243 #> 5908 2056C2 3M CC45 2014 2014-07-10 DO 2.5136560631 #> 5909 2056C2 3M CC45 2014 2014-07-10 DOSAT 5.1935122522 + #> 5910 2056C2 3M CC45 2014 2014-07-10 SALIN 2.7219531063 #> 5911 2056C2 3M CC45 2014 2014-07-10 COND 10.5858012624 #> 5912 2056C2 3M CC45 2014 2014-07-10 DO 1.3584091576 #> 5913 2056C2 3M CC45 2014 2014-07-10 DOSAT 4.0893320204 + #> 5914 2056C2 3M CC45 2014 2014-07-10 SALIN 3.2284300377 #> 5915 2056C2 3M CC45 2014 2014-07-10 COND 10.5893079577 #> 5916 2056C2 3M CC45 2014 2014-07-10 DO 1.2383742310 #> 5917 2056C2 3M CC45 2014 2014-07-10 DOSAT 3.9702919136 + #> 5918 2056C2 3M CC45 2014 2014-07-10 SALIN 3.2327787300 #> 5919 2056C2 3M CC45 2014 2014-07-10 COND 10.5894086880 #> 5920 2056C2 3M CC45 2014 2014-07-10 DO 1.2178757095 #> 5921 2056C2 3M CC45 2014 2014-07-10 DOSAT 3.9493187902 + #> 5922 2056C2 3M CC45 2014 2014-07-10 SALIN 3.2335673736 #> 5923 2056C2 3M CC45 2014 2014-07-10 COND 10.5868621364 #> 5924 2056C2 3M CC45 2014 2014-07-10 DO 0.7654678421 #> 5925 2056C2 3M CC45 2014 2014-07-10 DOSAT 3.4965075615 + #> 5926 2056C2 3M CC45 2014 2014-07-10 SALIN 3.2331731296 #> 5927 2053 2 CC50 2013 2013-02-26 CHLAC 2.0541237337 #> 5928 2053 2 CC50 2013 2013-02-26 COND 10.5960845818 #> 5929 2053 2 CC50 2013 2013-02-26 DO 1.8531680974 #> 5930 2053 2 CC50 2013 2013-02-26 DOSAT 4.4953553200 #> 5931 2053 2 CC50 2013 2013-02-26 NO23 -5.5214609179 I #> 5932 2053 2 CC50 2013 2013-02-26 SALIN 3.2347491740 + #> 5933 2053 2 CC50 2013 2013-02-26 TKN -0.4462871026 #> 5934 2053 2 CC50 2013 2013-02-26 TN -0.4400565529 + #> 5935 2053 2 CC50 2013 2013-02-26 TP -1.8971199849 #> 5936 2053 2 CC50 2013 2013-02-26 TSS 1.7917594692 I #> 5937 2053 2 CC50 2013 2013-02-26 TURB 0.8754687374 #> 5938 2053 2 CC50 2013 2013-04-08 CHLAC 1.9740810260 #> 5939 2053 2 CC50 2013 2013-04-08 COND 10.6030143401 #> 5940 2053 2 CC50 2013 2013-04-08 DO 2.1329823086 #> 5941 2053 2 CC50 2013 2013-04-08 DOSAT 4.7655869074 #> 5942 2053 2 CC50 2013 2013-04-08 NO23 -5.2983173665 I #> 5943 2053 2 CC50 2013 2013-04-08 SALIN 3.2557861789 + #> 5944 2053 2 CC50 2013 2013-04-08 TKN -0.3710636814 #> 5945 2053 2 CC50 2013 2013-04-08 TN -0.3652833185 + #> 5946 2053 2 CC50 2013 2013-04-08 TP -1.7719568419 #> 5947 2053 2 CC50 2013 2013-04-08 TSS 2.0794415417 I #> 5948 2053 2 CC50 2013 2013-04-08 TURB 1.1631508098 #> 5949 2053 2 CC50 2013 2013-05-15 COND 10.4100340338 #> 5950 2053 2 CC50 2013 2013-05-15 DO 1.7900914121 #> 5951 2053 2 CC50 2013 2013-05-15 DOSAT 4.4331949212 #> 5952 2053 2 CC50 2013 2013-05-15 SALIN 3.0223742045 + #> 5953 2053 2 CC50 2013 2013-07-02 CHLAC 1.6486586256 #> 5954 2053 2 CC50 2013 2013-07-02 COND 7.8062892893 #> 5955 2053 2 CC50 2013 2013-07-02 DO 1.5851452199 #> 5956 2053 2 CC50 2013 2013-07-02 DOSAT 4.1125118662 #> 5957 2053 2 CC50 2013 2013-07-02 NO23 -2.7968814148 #> 5958 2053 2 CC50 2013 2013-07-02 SALIN 0.1988508587 + #> 5959 2053 2 CC50 2013 2013-07-02 TKN -0.1743533871 #> 5960 2053 2 CC50 2013 2013-07-02 TN -0.1042500214 + #> 5961 2053 2 CC50 2013 2013-07-02 TP -1.5141277326 #> 5962 2053 2 CC50 2013 2013-07-02 TSS 1.7917594692 I #> 5963 2053 2 CC50 2013 2013-07-02 TURB 1.0647107370 #> 5964 2053 2 CC50 2013 2013-08-14 COND 8.7817089858 #> 5965 2053 2 CC50 2013 2013-08-14 DO 1.8261608959 #> 5966 2053 2 CC50 2013 2013-08-14 DOSAT 4.4693504628 #> 5967 2053 2 CC50 2013 2013-09-18 COND 8.7180093308 #> 5968 2053 2 CC50 2013 2013-09-18 DO 1.4011829736 #> 5969 2053 2 CC50 2013 2013-09-18 DOSAT 3.9493187902 #> 5970 2053 2 CC50 2013 2013-09-18 SALIN 1.1474024528 + #> 5971 2053 2 CC50 2013 2013-10-07 CHLAC 3.1780538303 #> 5972 2053 2 CC50 2013 2013-10-07 COND 8.9351137408 #> 5973 2053 2 CC50 2013 2013-10-07 NO23 -2.9374633654 #> 5974 2053 2 CC50 2013 2013-10-07 SALIN 1.3686394259 + #> 5975 2053 2 CC50 2013 2013-10-07 TKN 0.1823215568 #> 5976 2053 2 CC50 2013 2013-10-07 TN 0.2255406759 + #> 5977 2053 2 CC50 2013 2013-10-07 TP -1.2729656758 #> 5978 2053 2 CC50 2013 2013-10-07 TSS 2.0794415417 I #> 5979 2053 2 CC50 2013 2013-10-07 TURB 1.2527629685 #> 5980 2053 2 CC50 2013 2013-10-31 COND 10.0177978987 #> 5981 2053 2 CC50 2013 2013-10-31 DO 1.5411590717 #> 5982 2053 2 CC50 2013 2013-10-31 DOSAT 4.0976723523 #> 5983 2053 2 CC50 2013 2013-10-31 SALIN 2.6108048167 + #> 5984 2053 2 CC50 2013 2013-11-20 COND 10.3586313189 #> 5985 2053 2 CC50 2013 2013-11-20 DO 2.1459312829 #> 5986 2053 2 CC50 2013 2013-11-20 DOSAT 4.7655869074 #> 5987 2053 2 CC50 2013 2013-11-20 SALIN 2.9454910571 + #> 5988 2053 2 CC50 2013 2013-12-11 COND 10.4527066243 #> 5989 2053 2 CC50 2013 2013-12-11 SALIN 3.0731561705 + #> 5990 2053 2 CC50 2013 2013-02-26 CHLAC 2.3978952728 #> 5991 2053 2 CC50 2013 2013-02-26 COND 10.6059165237 #> 5992 2053 2 CC50 2013 2013-02-26 DO 1.7595805709 #> 5993 2053 2 CC50 2013 2013-02-26 DOSAT 4.3981460166 #> 5994 2053 2 CC50 2013 2013-02-26 NO23 -4.8283137373 I #> 5995 2053 2 CC50 2013 2013-02-26 SALIN 3.2530839962 + #> 5996 2053 2 CC50 2013 2013-02-26 TKN -0.3011050928 #> 5997 2053 2 CC50 2013 2013-02-26 TN -0.2957142441 + #> 5998 2053 2 CC50 2013 2013-02-26 TP -1.8971199849 #> 5999 2053 2 CC50 2013 2013-02-26 TSS 1.9459101491 I #> 6000 2053 2 CC50 2013 2013-02-26 TURB 0.9162907319 #> 6001 2053 2 CC50 2013 2013-04-08 CHLAC 1.8870696490 #> 6002 2053 2 CC50 2013 2013-04-08 COND 10.6120896877 #> 6003 2053 2 CC50 2013 2013-04-08 DO 2.2321626287 #> 6004 2053 2 CC50 2013 2013-04-08 DOSAT 4.8574841146 #> 6005 2053 2 CC50 2013 2013-04-08 NO23 -4.5098600062 #> 6006 2053 2 CC50 2013 2013-04-08 SALIN 3.2775220203 + #> 6007 2053 2 CC50 2013 2013-04-08 TKN -0.5108256238 #> 6008 2053 2 CC50 2013 2013-04-08 TN -0.4926583198 + #> 6009 2053 2 CC50 2013 2013-04-08 TP -1.9661128564 #> 6010 2053 2 CC50 2013 2013-04-08 TSS 1.3862943611 I #> 6011 2053 2 CC50 2013 2013-04-08 TURB 0.7419373447 A #> 6012 2053 2 CC50 2013 2013-05-15 COND 10.5088685258 #> 6013 2053 2 CC50 2013 2013-05-15 DO 1.7950872593 #> 6014 2053 2 CC50 2013 2013-05-15 DOSAT 4.4320065670 #> 6015 2053 2 CC50 2013 2013-05-15 SALIN 3.1245651454 + #> 6016 2053 2 CC50 2013 2013-07-02 CHLAC 1.2527629685 #> 6017 2053 2 CC50 2013 2013-07-02 COND 7.8355792467 #> 6018 2053 2 CC50 2013 2013-07-02 DO 1.7065646232 #> 6019 2053 2 CC50 2013 2013-07-02 DOSAT 4.2224445648 #> 6020 2053 2 CC50 2013 2013-07-02 NO23 -2.3025850930 #> 6021 2053 2 CC50 2013 2013-07-02 SALIN 0.2468600779 + #> 6022 2053 2 CC50 2013 2013-07-02 TKN 0.0000000000 #> 6023 2053 2 CC50 2013 2013-07-02 TN 0.0953101798 + #> 6024 2053 2 CC50 2013 2013-07-02 TP -0.5621189182 #> 6025 2053 2 CC50 2013 2013-07-02 TSS 1.6094379124 I #> 6026 2053 2 CC50 2013 2013-07-02 TURB 0.8754687374 #> 6027 2053 2 CC50 2013 2013-08-14 COND 8.7740036002 #> 6028 2053 2 CC50 2013 2013-08-14 DO 1.7387102481 #> 6029 2053 2 CC50 2013 2013-08-14 DOSAT 4.3795235045 #> 6030 2053 2 CC50 2013 2013-09-18 COND 8.6015343398 #> 6031 2053 2 CC50 2013 2013-09-18 DO 1.6937790609 #> 6032 2053 2 CC50 2013 2013-09-18 DOSAT 4.2297491992 #> 6033 2053 2 CC50 2013 2013-09-18 SALIN 1.0438040522 + #> 6034 2053 2 CC50 2013 2013-10-07 CHLAC 4.2341065046 #> 6035 2053 2 CC50 2013 2013-10-07 COND 8.5477223965 #> 6036 2053 2 CC50 2013 2013-10-07 NO23 -2.4304184645 #> 6037 2053 2 CC50 2013 2013-10-07 SALIN 0.9477893989 + #> 6038 2053 2 CC50 2013 2013-10-07 TKN 0.0953101798 #> 6039 2053 2 CC50 2013 2013-10-07 TN 0.1722712209 + #> 6040 2053 2 CC50 2013 2013-10-07 TP -1.0216512475 #> 6041 2053 2 CC50 2013 2013-10-07 TSS 2.0794415417 I #> 6042 2053 2 CC50 2013 2013-10-07 TURB 0.7884573604 #> 6043 2053 2 CC50 2013 2013-10-31 COND 9.9967046342 #> 6044 2053 2 CC50 2013 2013-10-31 DO 1.6789639751 #> 6045 2053 2 CC50 2013 2013-10-31 DOSAT 4.2268337453 #> 6046 2053 2 CC50 2013 2013-10-31 SALIN 2.6012071055 + #> 6047 2053 2 CC50 2013 2013-11-20 COND 10.3609123996 #> 6048 2053 2 CC50 2013 2013-11-20 DO 1.9974177062 #> 6049 2053 2 CC50 2013 2013-11-20 DOSAT 4.6131383556 #> 6050 2053 2 CC50 2013 2013-11-20 SALIN 2.9554309768 + #> 6051 2053 2 CC50 2013 2013-12-11 COND 10.4538030840 #> 6052 2053 2 CC50 2013 2013-12-11 SALIN 3.1009927842 + #> 6053 2053 2 CC50 2013 2013-02-26 CHLAC 1.0647107370 #> 6054 2053 2 CC50 2013 2013-02-26 COND 10.6206441856 #> 6055 2053 2 CC50 2013 2013-02-26 DO 1.9227877316 #> 6056 2053 2 CC50 2013 2013-02-26 DOSAT 4.5549289696 #> 6057 2053 2 CC50 2013 2013-02-26 NO23 -5.1159958098 I #> 6058 2053 2 CC50 2013 2013-02-26 SALIN 3.2786530289 + #> 6059 2053 2 CC50 2013 2013-02-26 TKN -0.4307829161 #> 6060 2053 2 CC50 2013 2013-02-26 TN -0.4246479275 + #> 6061 2053 2 CC50 2013 2013-02-26 TP -1.9661128564 #> 6062 2053 2 CC50 2013 2013-02-26 TSS 2.0794415417 I #> 6063 2053 2 CC50 2013 2013-02-26 TURB 1.4109869737 #> 6064 2053 2 CC50 2013 2013-04-08 CHLAC 0.9932517730 #> 6065 2053 2 CC50 2013 2013-04-08 COND 10.6384002823 #> 6066 2053 2 CC50 2013 2013-04-08 DO 2.1529243184 #> 6067 2053 2 CC50 2013 2013-04-08 DOSAT 4.7672890355 #> 6068 2053 2 CC50 2013 2013-04-08 NO23 -5.2983173665 I #> 6069 2053 2 CC50 2013 2013-04-08 SALIN 3.3250360207 + #> 6070 2053 2 CC50 2013 2013-04-08 TKN -0.2744368457 #> 6071 2053 2 CC50 2013 2013-04-08 TN -0.2691874898 + #> 6072 2053 2 CC50 2013 2013-04-08 TP -1.7719568419 #> 6073 2053 2 CC50 2013 2013-04-08 TSS 2.6390573296 #> 6074 2053 2 CC50 2013 2013-04-08 TURB 1.7749523509 #> 6075 2053 2 CC50 2013 2013-05-15 COND 10.5426800055 #> 6076 2053 2 CC50 2013 2013-05-15 DO 1.7526720805 #> 6077 2053 2 CC50 2013 2013-05-15 DOSAT 4.3907385753 #> 6078 2053 2 CC50 2013 2013-05-15 SALIN 3.1970391303 + #> 6079 2053 2 CC50 2013 2013-07-02 CHLAC 2.7725887222 #> 6080 2053 2 CC50 2013 2013-07-02 COND 8.2877800271 #> 6081 2053 2 CC50 2013 2013-07-02 DO 1.8131947499 #> 6082 2053 2 CC50 2013 2013-07-02 DOSAT 4.3567088267 #> 6083 2053 2 CC50 2013 2013-07-02 NO23 -3.4737680745 #> 6084 2053 2 CC50 2013 2013-07-02 SALIN 0.6981347221 + #> 6085 2053 2 CC50 2013 2013-07-02 TKN 0.1823215568 #> 6086 2053 2 CC50 2013 2013-07-02 TN 0.2078268472 + #> 6087 2053 2 CC50 2013 2013-07-02 TP -0.8439700703 #> 6088 2053 2 CC50 2013 2013-07-02 TSS 2.3025850930 I #> 6089 2053 2 CC50 2013 2013-07-02 TURB 1.8245492921 #> 6090 2053 2 CC50 2013 2013-08-14 COND 8.7295588696 #> 6091 2053 2 CC50 2013 2013-08-14 DO 1.6467336972 #> 6092 2053 2 CC50 2013 2013-08-14 DOSAT 4.2598590007 #> 6093 2053 2 CC50 2013 2013-09-18 COND 8.4191392509 #> 6094 2053 2 CC50 2013 2013-09-18 DO 1.8131947499 #> 6095 2053 2 CC50 2013 2013-09-18 DOSAT 4.3694478525 #> 6096 2053 2 CC50 2013 2013-09-18 SALIN 0.8241754430 + #> 6097 2053 2 CC50 2013 2013-10-07 CHLAC 3.6888794541 #> 6098 2053 2 CC50 2013 2013-10-07 COND 8.8189260871 #> 6099 2053 2 CC50 2013 2013-10-07 NO23 -2.6882475738 #> 6100 2053 2 CC50 2013 2013-10-07 SALIN 1.2470322938 + #> 6101 2053 2 CC50 2013 2013-10-07 TKN 0.0953101798 #> 6102 2053 2 CC50 2013 2013-10-07 TN 0.1552928844 + #> 6103 2053 2 CC50 2013 2013-10-07 TP -1.0498221245 #> 6104 2053 2 CC50 2013 2013-10-07 TSS 1.9459101491 I #> 6105 2053 2 CC50 2013 2013-10-07 TURB 1.0986122887 #> 6106 2053 2 CC50 2013 2013-10-31 COND 9.9927339301 #> 6107 2053 2 CC50 2013 2013-10-31 DO 1.8082887712 #> 6108 2053 2 CC50 2013 2013-10-31 DOSAT 4.3541414312 #> 6109 2053 2 CC50 2013 2013-10-31 SALIN 2.6049094422 + #> 6110 2053 2 CC50 2013 2013-11-20 COND 10.3246619543 #> 6111 2053 2 CC50 2013 2013-11-20 DO 2.1713368064 #> 6112 2053 2 CC50 2013 2013-11-20 DOSAT 4.7908195329 #> 6113 2053 2 CC50 2013 2013-11-20 SALIN 2.9123506646 + #> 6114 2053 2 CC50 2013 2013-12-11 COND 10.4566827727 #> 6115 2053 2 CC50 2013 2013-12-11 SALIN 3.1223649245 + #> 6116 2053 2 CC50 2018 2018-03-15 CHLAC 0.9932517730 #> 6117 2053 2 CC50 2018 2018-03-15 COND 10.6964800681 #> 6118 2053 2 CC50 2018 2018-03-15 DO 2.0918640617 #> 6119 2053 2 CC50 2018 2018-03-15 DOSAT 4.6249728133 #> 6120 2053 2 CC50 2018 2018-03-15 NO23 -5.5214609179 U #> 6121 2053 2 CC50 2018 2018-03-15 SALIN 3.5010427166 + #> 6122 2053 2 CC50 2018 2018-03-15 TKN -0.5108256238 #> 6123 2053 2 CC50 2018 2018-03-15 TN -0.5074978337 + #> 6124 2053 2 CC50 2018 2018-03-15 TP -1.8325814637 #> 6125 2053 2 CC50 2018 2018-03-15 TSS 1.7917594692 I #> 6126 2053 2 CC50 2018 2018-03-15 TURB 1.1631508098 A #> 6127 2053 2 CC50 2018 2018-03-29 CHLAC 1.9459101491 #> 6128 2053 2 CC50 2018 2018-03-29 COND 10.6310361598 #> 6129 2053 2 CC50 2018 2018-03-29 DO 1.8405496334 #> 6130 2053 2 CC50 2018 2018-03-29 DOSAT 4.4426512565 #> 6131 2053 2 CC50 2018 2018-03-29 NO23 -5.5214609179 U #> 6132 2053 2 CC50 2018 2018-03-29 SALIN 3.3382575819 + #> 6133 2053 2 CC50 2018 2018-03-29 TKN 0.4054651081 #> 6134 2053 2 CC50 2018 2018-03-29 TN 0.4067975533 + #> 6135 2053 2 CC50 2018 2018-03-29 TP -1.8325814637 #> 6136 2053 2 CC50 2018 2018-03-29 TSS 2.6390573296 #> 6137 2053 2 CC50 2018 2018-03-29 TURB 1.7047480922 #> 6138 2053 2 CC50 2018 2018-04-23 CHLAC 2.0794415417 #> 6139 2053 2 CC50 2018 2018-04-23 COND 10.6468524493 #> 6140 2053 2 CC50 2018 2018-04-23 DO 1.9459101491 #> 6141 2053 2 CC50 2018 2018-04-23 DOSAT 4.6249728133 #> 6142 2053 2 CC50 2018 2018-04-23 NO23 -5.5214609179 U #> 6143 2053 2 CC50 2018 2018-04-23 SALIN 3.2649957605 + #> 6144 2053 2 CC50 2018 2018-04-23 TKN -0.3710636814 #> 6145 2053 2 CC50 2018 2018-04-23 TN -0.3681693234 + #> 6146 2053 2 CC50 2018 2018-04-23 TP -1.5141277326 #> 6147 2053 2 CC50 2018 2018-04-23 TSS 3.3322045102 A #> 6148 2053 2 CC50 2018 2018-04-23 TURB 1.8718021769 #> 6149 2053 2 CC50 2018 2018-05-10 CHLAC 1.7917594692 #> 6150 2053 2 CC50 2018 2018-05-10 COND 10.6712318713 #> 6151 2053 2 CC50 2018 2018-05-10 DO 1.5040773968 #> 6152 2053 2 CC50 2018 2018-05-10 DOSAT 4.1588830834 #> 6153 2053 2 CC50 2018 2018-05-10 NO23 -5.2983173665 I #> 6154 2053 2 CC50 2018 2018-05-10 SALIN 3.3214324132 #> 6155 2053 2 CC50 2018 2018-05-10 TKN -0.1165338163 #> 6156 2053 2 CC50 2018 2018-05-10 TN -0.1120495038 + #> 6157 2053 2 CC50 2018 2018-05-10 TP -1.3862943611 #> 6158 2053 2 CC50 2018 2018-05-10 TSS 2.7080502011 #> 6159 2053 2 CC50 2018 2018-05-10 TURB 1.9021075264 #> 6160 2053 2 CC50 2018 2018-06-11 CHLAC 2.6390573296 #> 6161 2053 2 CC50 2018 2018-06-11 COND 9.5468126086 #> 6162 2053 2 CC50 2018 2018-06-11 DO 1.6094379124 #> 6163 2053 2 CC50 2018 2018-06-11 DOSAT 4.2341065046 #> 6164 2053 2 CC50 2018 2018-06-11 NO23 -2.7806208939 #> 6165 2053 2 CC50 2018 2018-06-11 SALIN 2.0918640617 #> 6166 2053 2 CC50 2018 2018-06-11 TKN 0.1823215568 #> 6167 2053 2 CC50 2018 2018-06-11 TN 0.2326977641 + #> 6168 2053 2 CC50 2018 2018-06-11 TP -0.7133498879 #> 6169 2053 2 CC50 2018 2018-06-11 TSS 1.3862943611 I #> 6170 2053 2 CC50 2018 2018-06-11 TURB 0.7419373447 #> 6171 2053 2 CC50 2018 2018-06-25 CHLAC 3.4011973817 #> 6172 2053 2 CC50 2018 2018-06-25 COND 10.0243768698 #> 6173 2053 2 CC50 2018 2018-06-25 DO 1.7209792872 #> 6174 2053 2 CC50 2018 2018-06-25 DOSAT 4.3719762988 #> 6175 2053 2 CC50 2018 2018-06-25 NO23 -2.9374633654 #> 6176 2053 2 CC50 2018 2018-06-25 SALIN 2.5055259370 + #> 6177 2053 2 CC50 2018 2018-06-25 TKN 0.0953101798 #> 6178 2053 2 CC50 2018 2018-06-25 TN 0.1423672413 + #> 6179 2053 2 CC50 2018 2018-06-25 TP -0.9162907319 #> 6180 2053 2 CC50 2018 2018-06-25 TSS 1.3862943611 I #> 6181 2053 2 CC50 2018 2018-06-25 TURB 0.9932517730 #> 6182 2053 2 CC50 2018 2018-08-07 CHLAC 2.8332133441 #> 6183 2053 2 CC50 2018 2018-08-07 COND 7.3382381501 #> 6184 2053 2 CC50 2018 2018-08-07 DO 1.7698546338 #> 6185 2053 2 CC50 2018 2018-08-07 DOSAT 4.3438054219 #> 6186 2053 2 CC50 2018 2018-08-07 NO23 -3.1235656451 #> 6187 2053 2 CC50 2018 2018-08-07 SALIN -0.2613647641 #> 6188 2053 2 CC50 2018 2018-08-07 TKN 0.0953101798 #> 6189 2053 2 CC50 2018 2018-08-07 TN 0.1345308930 + #> 6190 2053 2 CC50 2018 2018-08-07 TP -1.2378743560 #> 6191 2053 2 CC50 2018 2018-08-07 TSS 1.3862943611 I #> 6192 2053 2 CC50 2018 2018-08-07 TURB 0.9162907319 A #> 6193 2053 2 CC50 2018 2018-09-06 CHLAC 2.0014800002 #> 6194 2053 2 CC50 2018 2018-09-06 COND 8.6513743729 #> 6195 2053 2 CC50 2018 2018-09-06 DO 1.8341801851 #> 6196 2053 2 CC50 2018 2018-09-06 DOSAT 4.4236483094 #> 6197 2053 2 CC50 2018 2018-09-06 NO23 -2.5383074265 #> 6198 2053 2 CC50 2018 2018-09-06 SALIN 1.1281710909 #> 6199 2053 2 CC50 2018 2018-09-06 TKN 0.1823215568 #> 6200 2053 2 CC50 2018 2018-09-06 TN 0.2460785226 + #> 6201 2053 2 CC50 2018 2018-09-06 TP -1.2378743560 #> 6202 2053 2 CC50 2018 2018-09-06 TSS 1.3862943611 I #> 6203 2053 2 CC50 2018 2018-09-06 TURB 0.6931471806 #> 6204 2053 2 CC50 2018 2018-09-20 CHLAC 2.5649493575 #> 6205 2053 2 CC50 2018 2018-09-20 COND 9.3369730229 #> 6206 2053 2 CC50 2018 2018-09-20 DO 1.6582280766 #> 6207 2053 2 CC50 2018 2018-09-20 DOSAT 4.1682144108 #> 6208 2053 2 CC50 2018 2018-09-20 NO23 -4.1351665567 #> 6209 2053 2 CC50 2018 2018-09-20 SALIN 1.8562979904 #> 6210 2053 2 CC50 2018 2018-09-20 TKN -0.0725706928 #> 6211 2053 2 CC50 2018 2018-09-20 TN -0.0555127099 + #> 6212 2053 2 CC50 2018 2018-09-20 TP -1.1394342832 #> 6213 2053 2 CC50 2018 2018-09-20 TSS 1.3862943611 I #> 6214 2053 2 CC50 2018 2018-09-20 TURB 0.4700036292 #> 6215 2053 2 CC50 2018 2018-10-24 CHLAC 1.9600947840 #> 6216 2053 2 CC50 2018 2018-10-24 COND 10.0400269167 #> 6217 2053 2 CC50 2018 2018-10-24 DO 1.9430489168 #> 6218 2053 2 CC50 2018 2018-10-24 DOSAT 4.5496574761 #> 6219 2053 2 CC50 2018 2018-10-24 NO23 -2.7488721956 #> 6220 2053 2 CC50 2018 2018-10-24 SALIN 2.6246685922 #> 6221 2053 2 CC50 2018 2018-10-24 TKN -0.3011050928 #> 6222 2053 2 CC50 2018 2018-10-24 TN -0.2181560098 + #> 6223 2053 2 CC50 2018 2018-10-24 TP -1.4271163556 #> 6224 2053 2 CC50 2018 2018-10-24 TSS 1.6094379124 I #> 6225 2053 2 CC50 2018 2018-10-24 TURB 0.9162907319 #> 6226 2053 2 CC50 2019 2019-04-17 CHLAC 1.5892352051 I #> 6227 2053 2 CC50 2019 2019-04-17 COND 10.3074515345 #> 6228 2053 2 CC50 2019 2019-04-17 DO 1.9878743482 #> 6229 2053 2 CC50 2019 2019-04-17 DOSAT 4.5981455711 #> 6230 2053 2 CC50 2019 2019-04-17 NO23 -5.5214609179 U #> 6231 2053 2 CC50 2019 2019-04-17 SALIN 2.9193910403 #> 6232 2053 2 CC50 2019 2019-04-17 TKN -0.4462871026 #> 6233 2053 2 CC50 2019 2019-04-17 TN -0.4431669753 + #> 6234 2053 2 CC50 2019 2019-04-17 TP -1.6607312068 #> 6235 2053 2 CC50 2019 2019-04-17 TSS 2.9444389792 A #> 6236 2053 2 CC50 2019 2019-04-17 TURB 1.0296194172 #> 6237 2053 2 CC50 2019 2019-07-15 CHLAC 3.0910424534 #> 6238 2053 2 CC50 2019 2019-07-15 COND 10.0506999322 #> 6239 2053 2 CC50 2019 2019-07-15 DO 1.9430489168 #> 6240 2053 2 CC50 2019 2019-07-15 DOSAT 4.5971380143 #> 6241 2053 2 CC50 2019 2019-07-15 NO23 -5.5214609179 U #> 6242 2053 2 CC50 2019 2019-07-15 SALIN 2.6333266549 #> 6243 2053 2 CC50 2019 2019-07-15 TKN -0.2107210313 #> 6244 2053 2 CC50 2019 2019-07-15 TN -0.2082549388 + #> 6245 2053 2 CC50 2019 2019-07-15 TP -1.4696759701 #> 6246 2053 2 CC50 2019 2019-07-15 TSS 2.0794415417 I #> 6247 2053 2 CC50 2019 2019-07-15 TURB 0.9932517730 #> 6248 2053 2 CC50 2019 2019-08-19 CHLAC 1.4816045409 #> 6249 2053 2 CC50 2019 2019-08-19 COND 7.3530819205 #> 6250 2053 2 CC50 2019 2019-08-19 DO 1.5665304114 #> 6251 2053 2 CC50 2019 2019-08-19 DOSAT 4.1367652781 #> 6252 2053 2 CC50 2019 2019-08-19 NO23 -2.6036901858 #> 6253 2053 2 CC50 2019 2019-08-19 SALIN -0.2484613593 #> 6254 2053 2 CC50 2019 2019-08-19 TKN 0.3364722366 #> 6255 2053 2 CC50 2019 2019-08-19 TN 0.3879797938 + #> 6256 2053 2 CC50 2019 2019-08-19 TP -0.8209805521 #> 6257 2053 2 CC50 2019 2019-08-19 TSS 1.0986122887 I #> 6258 2053 2 CC50 2019 2019-08-19 TURB 0.7884573604 #> 6259 2053 2 CC50 2019 2019-09-11 CHLAC 3.0910424534 #> 6260 2053 2 CC50 2019 2019-09-11 COND 9.8378817954 #> 6261 2053 2 CC50 2019 2019-09-11 DO 1.9139771020 #> 6262 2053 2 CC50 2019 2019-09-11 DOSAT 4.5475410732 #> 6263 2053 2 CC50 2019 2019-09-11 NO23 -4.0173835211 #> 6264 2053 2 CC50 2019 2019-09-11 SALIN 2.4015250408 #> 6265 2053 2 CC50 2019 2019-09-11 TKN -0.0725706928 #> 6266 2053 2 CC50 2019 2019-09-11 TN -0.0534007767 + #> 6267 2053 2 CC50 2019 2019-09-11 TP -1.2039728043 #> 6268 2053 2 CC50 2019 2019-09-11 TSS 1.6094379124 I #> 6269 2053 2 CC50 2019 2019-09-11 TURB 0.7884573604 #> 6270 2053 2 CC50 2019 2019-10-09 CHLAC 1.1939224685 #> 6271 2053 2 CC50 2019 2019-10-09 COND 10.2652793829 #> 6272 2053 2 CC50 2019 2019-10-09 DO 1.7065646232 #> 6273 2053 2 CC50 2019 2019-10-09 DOSAT 4.3554259529 #> 6274 2053 2 CC50 2019 2019-10-09 NO23 -5.5214609179 I #> 6275 2053 2 CC50 2019 2019-10-09 SALIN 2.8713021952 #> 6276 2053 2 CC50 2019 2019-10-09 TKN -0.4155154440 #> 6277 2053 2 CC50 2019 2019-10-09 TN -0.4094731295 + #> 6278 2053 2 CC50 2019 2019-10-09 TP -1.5141277326 #> 6279 2053 2 CC50 2019 2019-10-09 TSS 1.0986122887 U #> 6280 2053 2 CC50 2019 2019-10-09 TURB -0.1625189295 #> 6281 2053 2 CC50 2020 2020-02-13 CHLAC 1.5475625087 #> 6282 2053 2 CC50 2020 2020-02-13 COND 10.4652439050 #> 6283 2053 2 CC50 2020 2020-02-13 DO 1.8017098001 #> 6284 2053 2 CC50 2020 2020-02-13 DOSAT 4.4067192473 #> 6285 2053 2 CC50 2020 2020-02-13 NO23 -5.5214609179 U #> 6286 2053 2 CC50 2020 2020-02-13 SALIN 3.0946722214 #> 6287 2053 2 CC50 2020 2020-02-13 TKN -0.4620354596 #> 6288 2053 2 CC50 2020 2020-02-13 TN -0.4588658848 + #> 6289 2053 2 CC50 2020 2020-02-13 TP -1.8325814637 #> 6290 2053 2 CC50 2020 2020-02-13 TSS 2.7080502011 #> 6291 2053 2 CC50 2020 2020-02-13 TURB 2.0014800002 A #> 6292 2053 2 CC50 2020 2020-03-24 CHLAC 1.3350010667 #> 6293 2053 2 CC50 2020 2020-03-24 COND 10.5688523521 #> 6294 2053 2 CC50 2020 2020-03-24 DO 1.9401794743 #> 6295 2053 2 CC50 2020 2020-03-24 DOSAT 4.6434288981 #> 6296 2053 2 CC50 2020 2020-03-24 NO23 -5.5214609179 U #> 6297 2053 2 CC50 2020 2020-03-24 SALIN 3.2047769005 #> 6298 2053 2 CC50 2020 2020-03-24 TKN -0.4462871026 #> 6299 2053 2 CC50 2020 2020-03-24 TN -0.4431669753 + #> 6300 2053 2 CC50 2020 2020-03-24 TP -1.8325814637 #> 6301 2053 2 CC50 2020 2020-03-24 TSS 2.7725887222 #> 6302 2053 2 CC50 2020 2020-03-24 TURB 1.5260563035 #> 6303 2053 2 CC50 2020 2020-06-22 CHLAC 3.1780538303 #> 6304 2053 2 CC50 2020 2020-06-22 COND 9.9972510823 #> 6305 2053 2 CC50 2020 2020-06-22 DO 1.7173950539 #> 6306 2053 2 CC50 2020 2020-06-22 DOSAT 4.3795235045 #> 6307 2053 2 CC50 2020 2020-06-22 NO23 -4.5098600062 #> 6308 2053 2 CC50 2020 2020-06-22 SALIN 2.5718485799 #> 6309 2053 2 CC50 2020 2020-06-22 TKN -0.0100503359 #> 6310 2053 2 CC50 2020 2020-06-22 TN 0.0009995003 + #> 6311 2053 2 CC50 2020 2020-06-22 TP -1.2039728043 #> 6312 2053 2 CC50 2020 2020-06-22 TSS 1.7917594692 I #> 6313 2053 2 CC50 2020 2020-06-22 TURB 0.7884573604 A #> 6314 2053 2 CC50 2020 2020-07-27 CHLAC 1.7578579176 #> 6315 2053 2 CC50 2020 2020-07-27 COND 10.1123293191 #> 6316 2053 2 CC50 2020 2020-07-27 DO 1.5644405465 #> 6317 2053 2 CC50 2020 2020-07-27 DOSAT 4.2239097666 #> 6318 2053 2 CC50 2020 2020-07-27 NO23 -4.1351665567 #> 6319 2053 2 CC50 2020 2020-07-27 SALIN 2.7006898467 #> 6320 2053 2 CC50 2020 2020-07-27 TN -0.3481400415 + #> 6321 2053 2 CC50 2020 2020-07-27 TP -1.3093333200 #> 6322 2053 2 CC50 2020 2020-07-27 TSS 1.0986122887 U #> 6323 2053 2 CC50 2020 2020-07-27 TURB 0.5306282511 #> 6324 2053 2 CC50 2020 2020-08-26 CHLAC 2.2300144002 #> 6325 2053 2 CC50 2020 2020-08-26 COND 9.8854254097 #> 6326 2053 2 CC50 2020 2020-08-26 DO 1.7850704811 #> 6327 2053 2 CC50 2020 2020-08-26 DOSAT 4.4188406078 #> 6328 2053 2 CC50 2020 2020-08-26 NO23 -5.5214609179 U #> 6329 2053 2 CC50 2020 2020-08-26 SALIN 2.4535879665 #> 6330 2053 2 CC50 2020 2020-08-26 TKN -0.1984509387 #> 6331 2053 2 CC50 2020 2020-08-26 TN -0.1960148839 + #> 6332 2053 2 CC50 2020 2020-08-26 TP -1.3862943611 #> 6333 2053 2 CC50 2020 2020-08-26 TSS 1.0986122887 U #> 6334 2053 2 CC50 2020 2020-08-26 TURB 0.0953101798 #> 6335 2053 2 CC50 2021 2021-01-14 CHLAC 1.6094379124 A #> 6336 2053 2 CC50 2021 2021-01-14 COND 10.2228136303 #> 6337 2053 2 CC50 2021 2021-01-14 DO 2.0967901800 #> 6338 2053 2 CC50 2021 2021-01-14 DOSAT 4.5580785785 #> 6339 2053 2 CC50 2021 2021-01-14 NO23 -5.5214609179 I #> 6340 2053 2 CC50 2021 2021-01-14 SALIN 2.8314470792 #> 6341 2053 2 CC50 2021 2021-01-14 TKN -0.2876820725 #> 6342 2053 2 CC50 2021 2021-01-14 TN -0.2823629110 + #> 6343 2053 2 CC50 2021 2021-01-14 TP -1.7147984281 #> 6344 2053 2 CC50 2021 2021-01-14 TSS 2.5649493575 A #> 6345 2053 2 CC50 2021 2021-01-14 TURB 1.4586150227 #> 6346 2053 2 CC50 2021 2021-02-24 COND 10.2486009183 #> 6347 2053 2 CC50 2021 2021-02-24 DO 2.0955609236 #> 6348 2053 2 CC50 2021 2021-02-24 DOSAT 4.6453519756 #> 6349 2053 2 CC50 2021 2021-02-24 NO23 -5.5214609179 U #> 6350 2053 2 CC50 2021 2021-02-24 SALIN 2.8581928595 #> 6351 2053 2 CC50 2021 2021-02-24 TKN -0.6733445533 #> 6352 2053 2 CC50 2021 2021-02-24 TN -0.6694306539 + #> 6353 2053 2 CC50 2021 2021-02-24 TP -1.8971199849 #> 6354 2053 2 CC50 2021 2021-02-24 TSS 1.0986122887 I #> 6355 2053 2 CC50 2021 2021-03-23 CHLAC 0.9555114450 #> 6356 2053 2 CC50 2021 2021-03-23 COND 10.5061901968 #> 6357 2053 2 CC50 2021 2021-03-23 DO 1.9685099810 #> 6358 2053 2 CC50 2021 2021-03-23 DOSAT 4.5119578043 #> 6359 2053 2 CC50 2021 2021-03-23 NO23 -5.2983173665 I #> 6360 2053 2 CC50 2021 2021-03-23 SALIN 3.1419947805 #> 6361 2053 2 CC50 2021 2021-03-23 TKN -0.4620354596 #> 6362 2053 2 CC50 2021 2021-03-23 TN -0.4557063245 + #> 6363 2053 2 CC50 2021 2021-03-23 TP -1.8971199849 #> 6364 2053 2 CC50 2021 2021-03-23 TSS 1.0986122887 U #> 6365 2053 2 CC50 2021 2021-03-23 TURB 0.6418538862 #> 6366 2053 2 CC50 2021 2021-07-28 CHLAC 2.2721258855 #> 6367 2053 2 CC50 2021 2021-07-28 COND 9.4095190458 #> 6368 2053 2 CC50 2021 2021-07-28 DO 0.9516578757 #> 6369 2053 2 CC50 2021 2021-07-28 DOSAT 3.5638829639 #> 6370 2053 2 CC50 2021 2021-07-28 NO23 -3.1700856607 #> 6371 2053 2 CC50 2021 2021-07-28 SALIN 1.9373017745 #> 6372 2053 2 CC50 2021 2021-07-28 TKN 0.1823215568 #> 6373 2053 2 CC50 2021 2021-07-28 TN 0.2167229835 + #> 6374 2053 2 CC50 2021 2021-07-28 TP -0.7550225843 #> 6375 2053 2 CC50 2021 2021-07-28 TSS 1.3862943611 I #> 6376 2053 2 CC50 2021 2021-07-28 TURB 1.7404661748 #> 6377 2053 2 CC50 2021 2021-08-26 CHLAC 1.5260563035 #> 6378 2053 2 CC50 2021 2021-08-26 COND 9.2069345788 #> 6379 2053 2 CC50 2021 2021-08-26 DO 1.0296194172 #> 6380 2053 2 CC50 2021 2021-08-26 DOSAT 3.6270040504 #> 6381 2053 2 CC50 2021 2021-08-26 NO23 -2.7488721956 #> 6382 2053 2 CC50 2021 2021-08-26 SALIN 1.7191887764 #> 6383 2053 2 CC50 2021 2021-08-26 TKN -0.3285040670 #> 6384 2053 2 CC50 2021 2021-08-26 TN -0.2433462586 + #> 6385 2053 2 CC50 2021 2021-08-26 TP -1.0216512475 #> 6386 2053 2 CC50 2021 2021-08-26 TSS 1.0986122887 I #> 6387 2053 2 CC50 2021 2021-08-26 TURB 0.9555114450 #> 6388 2053 2 CC50 2021 2021-09-13 CHLAC 1.7578579176 #> 6389 2053 2 CC50 2021 2021-09-13 COND 9.5941731800 #> 6390 2053 2 CC50 2021 2021-09-13 DO 1.4422019931 #> 6391 2053 2 CC50 2021 2021-09-13 DOSAT 4.0707346966 #> 6392 2053 2 CC50 2021 2021-09-13 NO23 -2.7806208939 #> 6393 2053 2 CC50 2021 2021-09-13 SALIN 2.1365305087 #> 6394 2053 2 CC50 2021 2021-09-13 TKN -0.0618754037 #> 6395 2053 2 CC50 2021 2021-09-13 TN 0.0019980027 + #> 6396 2053 2 CC50 2021 2021-09-13 TP -1.2039728043 #> 6397 2053 2 CC50 2021 2021-09-13 TSS 1.0986122887 I #> 6398 2053 2 CC50 2021 2021-09-13 TURB 0.5877866649 #> 6399 2053 2 CC50 2022 2022-03-16 COND 10.6209126256 #> 6400 2053 2 CC50 2022 2022-03-16 DO 1.9080599249 #> 6401 2053 2 CC50 2022 2022-03-16 DOSAT 4.5152454785 #> 6402 2053 2 CC50 2022 2022-03-16 SALIN 3.2676659890 #> 6403 2053 2 CC50 2022 2022-05-04 COND 10.6380165709 #> 6404 2053 2 CC50 2022 2022-05-04 DO 1.8748743759 #> 6405 2053 2 CC50 2022 2022-05-04 DOSAT 4.5622626850 #> 6406 2053 2 CC50 2022 2022-05-04 SALIN 3.2839142210 #> 6407 2054 3F CC53 2013 2013-01-07 CHLAC 2.3025850930 #> 6408 2054 3F CC53 2013 2013-01-07 COLOR 3.8501476017 #> 6409 2054 3F CC53 2013 2013-01-07 DO 1.6094379124 #> 6410 2054 3F CC53 2013 2013-01-07 NO23 -2.5639498571 #> 6411 2054 3F CC53 2013 2013-01-07 TKN -0.0833816089 #> 6412 2054 3F CC53 2013 2013-01-07 TN -0.0030045090 + #> 6413 2054 3F CC53 2013 2013-01-07 TP -2.0402208285 #> 6414 2054 3F CC53 2013 2013-01-07 TURB 1.2527629685 #> 6415 2054 3F CC53 2013 2013-02-04 CHLAC 2.7725887222 #> 6416 2054 3F CC53 2013 2013-02-04 COLOR 3.8066624898 #> 6417 2054 3F CC53 2013 2013-02-04 DOSAT 4.0000338828 + #> 6418 2054 3F CC53 2013 2013-02-04 NO23 -5.5214609179 U #> 6419 2054 3F CC53 2013 2013-02-04 SALIN 0.0953101798 #> 6420 2054 3F CC53 2013 2013-02-04 TKN -0.2744368457 #> 6421 2054 3F CC53 2013 2013-02-04 TN -0.2718087233 + #> 6422 2054 3F CC53 2013 2013-02-04 TP -1.9661128564 #> 6423 2054 3F CC53 2013 2013-02-04 TURB 0.8754687374 #> 6424 2054 3F CC53 2013 2013-03-04 CHLAC 2.1282317058 #> 6425 2054 3F CC53 2013 2013-03-04 COLOR 3.7376696183 #> 6426 2054 3F CC53 2013 2013-03-04 DO 1.9169226122 #> 6427 2054 3F CC53 2013 2013-03-04 DOSAT 4.2180360346 + #> 6428 2054 3F CC53 2013 2013-03-04 NO23 -3.0365542681 #> 6429 2054 3F CC53 2013 2013-03-04 TKN -0.3285040670 #> 6430 2054 3F CC53 2013 2013-03-04 TN -0.2639655458 + #> 6431 2054 3F CC53 2013 2013-03-04 TP -1.7719568419 #> 6432 2054 3F CC53 2013 2013-03-04 TURB 1.0986122887 #> 6433 2054 3F CC53 2013 2013-04-01 CHLAC 2.1633230257 #> 6434 2054 3F CC53 2013 2013-04-01 COLOR 3.7376696183 #> 6435 2054 3F CC53 2013 2013-04-01 DO 1.8082887712 #> 6436 2054 3F CC53 2013 2013-04-01 DOSAT 4.2570301445 + #> 6437 2054 3F CC53 2013 2013-04-01 NO23 -4.2686979494 #> 6438 2054 3F CC53 2013 2013-04-01 SALIN 1.6094379124 #> 6439 2054 3F CC53 2013 2013-04-01 TKN -0.2107210313 #> 6440 2054 3F CC53 2013 2013-04-01 TN -0.1935847491 + #> 6441 2054 3F CC53 2013 2013-04-01 TP -1.7719568419 #> 6442 2054 3F CC53 2013 2013-04-01 TURB 0.9555114450 #> 6443 2054 3F CC53 2013 2013-05-06 CHLAC 2.1400661635 #> 6444 2054 3F CC53 2013 2013-05-06 COLOR 3.8712010109 #> 6445 2054 3F CC53 2013 2013-05-06 DO 1.8562979904 #> 6446 2054 3F CC53 2013 2013-05-06 DOSAT 4.3294166844 + #> 6447 2054 3F CC53 2013 2013-05-06 NO23 -3.8167128256 #> 6448 2054 3F CC53 2013 2013-05-06 SALIN 0.5596157879 #> 6449 2054 3F CC53 2013 2013-05-06 TKN -0.2107210313 #> 6450 2054 3F CC53 2013 2013-05-06 TN -0.1839228382 + #> 6451 2054 3F CC53 2013 2013-05-06 TP -1.5606477483 #> 6452 2054 3F CC53 2013 2013-05-06 TURB 1.2527629685 #> 6453 2054 3F CC53 2013 2013-06-03 CHLAC 0.9162907319 #> 6454 2054 3F CC53 2013 2013-06-03 COLOR 4.0775374439 #> 6455 2054 3F CC53 2013 2013-06-03 DO 1.3862943611 #> 6456 2054 3F CC53 2013 2013-06-03 NO23 -2.4418471603 #> 6457 2054 3F CC53 2013 2013-06-03 TKN -0.2876820725 #> 6458 2054 3F CC53 2013 2013-06-03 TN -0.1779312085 + #> 6459 2054 3F CC53 2013 2013-06-03 TP -1.3862943611 #> 6460 2054 3F CC53 2013 2013-06-03 TURB 0.3364722366 #> 6461 2054 3F CC53 2013 2013-07-08 CHLAC 0.7884573604 #> 6462 2054 3F CC53 2013 2013-07-08 COLOR 5.1929568509 #> 6463 2054 3F CC53 2013 2013-07-08 DO 1.5260563035 #> 6464 2054 3F CC53 2013 2013-07-08 DOSAT 4.0943445622 + #> 6465 2054 3F CC53 2013 2013-07-08 NO23 -4.7105307016 I #> 6466 2054 3F CC53 2013 2013-07-08 TKN 0.0953101798 #> 6467 2054 3F CC53 2013 2013-07-08 TN 0.0989399479 + #> 6468 2054 3F CC53 2013 2013-07-08 TP -2.0402208285 #> 6469 2054 3F CC53 2013 2013-07-08 TURB 0.9162907319 A #> 6470 2054 3F CC53 2013 2013-08-05 CHLAC 1.0296194172 #> 6471 2054 3F CC53 2013 2013-08-05 COLOR 4.8675344505 #> 6472 2054 3F CC53 2013 2013-08-05 DO 1.1314021115 #> 6473 2054 3F CC53 2013 2013-08-05 DOSAT 3.6963514690 + #> 6474 2054 3F CC53 2013 2013-08-05 NO23 -3.5065578973 #> 6475 2054 3F CC53 2013 2013-08-05 TKN 0.2623642645 #> 6476 2054 3F CC53 2013 2013-08-05 TN 0.2851789422 + #> 6477 2054 3F CC53 2013 2013-08-05 TP -2.0402208285 #> 6478 2054 3F CC53 2013 2013-08-05 TURB 0.7884573604 #> 6479 2054 3F CC53 2013 2013-09-09 CHLAC 0.6418538862 #> 6480 2054 3F CC53 2013 2013-09-09 COLOR 4.7004803658 #> 6481 2054 3F CC53 2013 2013-09-09 DO 1.6094379124 #> 6482 2054 3F CC53 2013 2013-09-09 DOSAT 4.0775374439 + #> 6483 2054 3F CC53 2013 2013-09-09 NO23 -5.1159958098 I #> 6484 2054 3F CC53 2013 2013-09-09 TKN -0.0618754037 #> 6485 2054 3F CC53 2013 2013-09-09 TN -0.0576291128 + #> 6486 2054 3F CC53 2013 2013-09-09 TP -2.3751557858 #> 6487 2054 3F CC53 2013 2013-09-09 TURB 0.9932517730 #> 6488 2054 3F CC53 2013 2013-10-07 CHLAC 0.9932517730 #> 6489 2054 3F CC53 2013 2013-10-07 COLOR 4.8675344505 #> 6490 2054 3F CC53 2013 2013-10-07 DOSAT 3.9298629236 + #> 6491 2054 3F CC53 2013 2013-10-07 NO23 -2.2072749132 #> 6492 2054 3F CC53 2013 2013-10-07 SALIN 0.0000000000 #> 6493 2054 3F CC53 2013 2013-10-07 TKN -0.0304592075 #> 6494 2054 3F CC53 2013 2013-10-07 TN 0.0769610411 + #> 6495 2054 3F CC53 2013 2013-10-07 TP -1.8971199849 #> 6496 2054 3F CC53 2013 2013-10-07 TURB 1.2809338455 #> 6497 2054 3F CC53 2013 2013-11-04 CHLAC 3.0445224377 #> 6498 2054 3F CC53 2013 2013-11-04 COLOR 4.2904594411 #> 6499 2054 3F CC53 2013 2013-11-04 DO 1.8245492921 #> 6500 2054 3F CC53 2013 2013-11-04 DOSAT 4.2541932632 + #> 6501 2054 3F CC53 2013 2013-11-04 NO23 -2.1202635362 #> 6502 2054 3F CC53 2013 2013-11-04 TKN -0.1508228897 #> 6503 2054 3F CC53 2013 2013-11-04 TN -0.0202027073 + #> 6504 2054 3F CC53 2013 2013-11-04 TP -1.8971199849 #> 6505 2054 3F CC53 2013 2013-11-04 TURB 0.9555114450 A #> 6506 2054 3F CC53 2013 2013-12-02 CHLAC 2.4849066498 #> 6507 2054 3F CC53 2013 2013-12-02 COLOR 4.1108738642 #> 6508 2054 3F CC53 2013 2013-12-02 DO 1.9169226122 #> 6509 2054 3F CC53 2013 2013-12-02 DOSAT 4.3214801348 + #> 6510 2054 3F CC53 2013 2013-12-02 NO23 -1.7147984281 #> 6511 2054 3F CC53 2013 2013-12-02 SALIN -0.2231435513 #> 6512 2054 3F CC53 2013 2013-12-02 TKN -0.1863295782 #> 6513 2054 3F CC53 2013 2013-12-02 TN 0.0099503309 + #> 6514 2054 3F CC53 2013 2013-12-02 TP -1.9661128564 #> 6515 2054 3F CC53 2013 2013-12-02 TURB 0.9162907319 #> 6516 2054 3F CC53 2014 2014-01-06 CHLAC 3.3672958300 #> 6517 2054 3F CC53 2014 2014-01-06 COLOR 4.1271343850 A #> 6518 2054 3F CC53 2014 2014-01-06 DO 1.8245492921 #> 6519 2054 3F CC53 2014 2014-01-06 DOSAT 4.2209772132 + #> 6520 2054 3F CC53 2014 2014-01-06 NO23 -2.5133061243 #> 6521 2054 3F CC53 2014 2014-01-06 SALIN 0.3364722366 #> 6522 2054 3F CC53 2014 2014-01-06 TKN -0.1625189295 #> 6523 2054 3F CC53 2014 2014-01-06 TN -0.0714960017 + #> 6524 2054 3F CC53 2014 2014-01-06 TP -2.9565115604 #> 6525 2054 3F CC53 2014 2014-01-06 TURB 1.1939224685 A #> 6526 2054 3F CC53 2014 2014-02-03 CHLAC 2.5649493575 #> 6527 2054 3F CC53 2014 2014-02-03 COLOR 4.0073331852 #> 6528 2054 3F CC53 2014 2014-02-03 DO 2.0014800002 #> 6529 2054 3F CC53 2014 2014-02-03 DOSAT 4.3956829611 + #> 6530 2054 3F CC53 2014 2014-02-03 NO23 -2.1202635362 #> 6531 2054 3F CC53 2014 2014-02-03 SALIN -0.3566749439 #> 6532 2054 3F CC53 2014 2014-02-03 TKN 0.0953101798 #> 6533 2054 3F CC53 2014 2014-02-03 TN 0.1988508587 + #> 6534 2054 3F CC53 2014 2014-02-03 TP -1.9661128564 #> 6535 2054 3F CC53 2014 2014-02-03 TURB 1.3350010667 #> 6536 2054 3F CC53 2014 2014-03-03 CHLAC 2.4849066498 #> 6537 2054 3F CC53 2014 2014-03-03 COLOR 4.1271343850 #> 6538 2054 3F CC53 2014 2014-03-03 DO 1.8082887712 #> 6539 2054 3F CC53 2014 2014-03-03 DOSAT 4.2398868675 + #> 6540 2054 3F CC53 2014 2014-03-03 NO23 -5.5214609179 U #> 6541 2054 3F CC53 2014 2014-03-03 SALIN 0.8754687374 #> 6542 2054 3F CC53 2014 2014-03-03 TKN 0.0953101798 #> 6543 2054 3F CC53 2014 2014-03-03 TN 0.0971267107 + #> 6544 2054 3F CC53 2014 2014-03-03 TP -2.0402208285 #> 6545 2054 3F CC53 2014 2014-03-03 TURB 1.7227665977 #> 6546 2054 3F CC53 2014 2014-04-07 CHLAC 2.3978952728 #> 6547 2054 3F CC53 2014 2014-04-07 COLOR 4.0253516907 #> 6548 2054 3F CC53 2014 2014-04-07 DO 1.6292405397 #> 6549 2054 3F CC53 2014 2014-04-07 DOSAT 4.0960098415 + #> 6550 2054 3F CC53 2014 2014-04-07 NO23 -4.3428059215 #> 6551 2054 3F CC53 2014 2014-04-07 TKN -0.0943106795 #> 6552 2054 3F CC53 2014 2014-04-07 TN -0.0801260445 + #> 6553 2054 3F CC53 2014 2014-04-07 TP -2.1202635362 #> 6554 2054 3F CC53 2014 2014-04-07 TURB 1.1939224685 #> 6555 2054 3F CC53 2014 2014-05-05 CHLAC 2.4849066498 #> 6556 2054 3F CC53 2014 2014-05-05 COLOR 4.0073331852 #> 6557 2054 3F CC53 2014 2014-05-05 DO 1.9459101491 #> 6558 2054 3F CC53 2014 2014-05-05 DOSAT 4.4006030202 + #> 6559 2054 3F CC53 2014 2014-05-05 NO23 -3.5755507688 #> 6560 2054 3F CC53 2014 2014-05-05 SALIN 0.4054651081 #> 6561 2054 3F CC53 2014 2014-05-05 TKN -0.1053605157 #> 6562 2054 3F CC53 2014 2014-05-05 TN -0.0747235462 + #> 6563 2054 3F CC53 2014 2014-05-05 TP -1.8325814637 #> 6564 2054 3F CC53 2014 2014-05-05 TURB 1.0296194172 #> 6565 2054 3F CC53 2014 2014-06-02 CHLAC 2.3978952728 #> 6566 2054 3F CC53 2014 2014-06-02 COLOR 4.1108738642 #> 6567 2054 3F CC53 2014 2014-06-02 DO 1.7578579176 #> 6568 2054 3F CC53 2014 2014-06-02 DOSAT 4.2780540443 + #> 6569 2054 3F CC53 2014 2014-06-02 NO23 -4.9618451299 I #> 6570 2054 3F CC53 2014 2014-06-02 TKN -0.0408219945 #> 6571 2054 3F CC53 2014 2014-06-02 TN -0.0366639844 + #> 6572 2054 3F CC53 2014 2014-06-02 TP -1.5141277326 #> 6573 2054 3F CC53 2014 2014-06-02 TURB 1.2527629685 #> 6574 2054 3F CC53 2014 2014-07-07 CHLAC 2.3025850930 #> 6575 2054 3F CC53 2014 2014-07-07 COLOR 4.8675344505 #> 6576 2054 3F CC53 2014 2014-07-07 NO23 -3.0365542681 #> 6577 2054 3F CC53 2014 2014-07-07 TKN 0.4054651081 #> 6578 2054 3F CC53 2014 2014-07-07 TN 0.4369637752 + #> 6579 2054 3F CC53 2014 2014-07-07 TP -1.0788096614 #> 6580 2054 3F CC53 2014 2014-07-07 TURB 1.3609765531 A #> 6581 2054 3F CC53 2014 2014-08-04 CHLAC 1.0647107370 #> 6582 2054 3F CC53 2014 2014-08-04 COLOR 5.2983173665 #> 6583 2054 3F CC53 2014 2014-08-04 DO 1.2837077723 #> 6584 2054 3F CC53 2014 2014-08-04 DOSAT 3.8565102955 + #> 6585 2054 3F CC53 2014 2014-08-04 NO23 -2.7030626596 #> 6586 2054 3F CC53 2014 2014-08-04 SALIN -1.8971199849 #> 6587 2054 3F CC53 2014 2014-08-04 TKN 0.4054651081 #> 6588 2054 3F CC53 2014 2014-08-04 TN 0.4491629634 + #> 6589 2054 3F CC53 2014 2014-08-04 TP -1.6607312068 #> 6590 2054 3F CC53 2014 2014-08-04 TURB 1.2237754316 #> 6591 2054 3F CC53 2014 2014-09-08 CHLAC 0.5877866649 #> 6592 2054 3F CC53 2014 2014-09-08 COLOR 4.4998096703 #> 6593 2054 3F CC53 2014 2014-09-08 DO 1.2527629685 #> 6594 2054 3F CC53 2014 2014-09-08 DOSAT 3.7887247891 + #> 6595 2054 3F CC53 2014 2014-09-08 NO23 -3.9120230054 #> 6596 2054 3F CC53 2014 2014-09-08 TKN -0.1984509387 #> 6597 2054 3F CC53 2014 2014-09-08 TN -0.1743533871 + #> 6598 2054 3F CC53 2014 2014-09-08 TP -2.6036901858 #> 6599 2054 3F CC53 2014 2014-09-08 TURB 0.6418538862 #> 6600 2054 3F CC53 2014 2014-10-06 CHLAC 0.5306282511 I #> 6601 2054 3F CC53 2014 2014-10-06 COLOR 4.6051701860 A #> 6602 2054 3F CC53 2014 2014-10-06 DO 1.3083328197 #> 6603 2054 3F CC53 2014 2014-10-06 DOSAT 3.7932394694 + #> 6604 2054 3F CC53 2014 2014-10-06 NO23 -3.8167128256 #> 6605 2054 3F CC53 2014 2014-10-06 TKN -0.0833816089 #> 6606 2054 3F CC53 2014 2014-10-06 TN -0.0597500044 + #> 6607 2054 3F CC53 2014 2014-10-06 TP -2.2072749132 #> 6608 2054 3F CC53 2014 2014-10-06 TURB 0.5306282511 A #> 6609 2054 3F CC53 2014 2014-11-03 CHLAC 2.0149030205 #> 6610 2054 3F CC53 2014 2014-11-03 COLOR 4.2046926194 A #> 6611 2054 3F CC53 2014 2014-11-03 DOSAT 4.4841318576 + #> 6612 2054 3F CC53 2014 2014-11-03 NO23 -2.3538783874 #> 6613 2054 3F CC53 2014 2014-11-03 SALIN -1.6094379124 #> 6614 2054 3F CC53 2014 2014-11-03 TKN -0.0725706928 #> 6615 2054 3F CC53 2014 2014-11-03 TN 0.0246926126 + #> 6616 2054 3F CC53 2014 2014-11-03 TP -2.3025850930 #> 6617 2054 3F CC53 2014 2014-11-03 TURB 0.9555114450 #> 6618 2054 3F CC53 2014 2014-12-01 CHLAC 3.2580965380 #> 6619 2054 3F CC53 2014 2014-12-01 COLOR 4.2626798770 #> 6620 2054 3F CC53 2014 2014-12-01 DO 1.7578579176 #> 6621 2054 3F 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3F CC53 2015 2015-02-02 SALIN -1.2039728043 #> 6640 2054 3F CC53 2015 2015-02-02 TKN -0.1625189295 #> 6641 2054 3F CC53 2015 2015-02-02 TN -0.1601687522 + #> 6642 2054 3F CC53 2015 2015-02-02 TP -2.2072749132 #> 6643 2054 3F CC53 2015 2015-02-02 TURB 1.0296194172 #> 6644 2054 3F CC53 2015 2015-03-02 CHLAC 2.7080502011 #> 6645 2054 3F CC53 2015 2015-03-02 COLOR 3.8712010109 #> 6646 2054 3F CC53 2015 2015-03-02 DO 1.9169226122 #> 6647 2054 3F CC53 2015 2015-03-02 DOSAT 4.3399017084 + #> 6648 2054 3F CC53 2015 2015-03-02 NO23 -3.9120230054 #> 6649 2054 3F CC53 2015 2015-03-02 TKN -0.1984509387 #> 6650 2054 3F CC53 2015 2015-03-02 TN -0.1743533871 + #> 6651 2054 3F CC53 2015 2015-03-02 TP -2.5770219387 #> 6652 2054 3F CC53 2015 2015-03-02 TURB 1.4109869737 #> 6653 2054 3F CC53 2015 2015-04-06 CHLAC 2.0412203289 #> 6654 2054 3F CC53 2015 2015-04-06 COLOR 4.1431347264 #> 6655 2054 3F CC53 2015 2015-04-06 DO 1.5260563035 #> 6656 2054 3F CC53 2015 2015-04-06 DOSAT 4.0018637094 + #> 6657 2054 3F CC53 2015 2015-04-06 NO23 -4.2686979494 #> 6658 2054 3F CC53 2015 2015-04-06 TKN 0.0953101798 #> 6659 2054 3F CC53 2015 2015-04-06 TN 0.1079571415 + #> 6660 2054 3F CC53 2015 2015-04-06 TP -2.1202635362 #> 6661 2054 3F CC53 2015 2015-04-06 TURB 1.2237754316 #> 6662 2054 3F CC53 2015 2015-05-04 CHLAC 2.5649493575 #> 6663 2054 3F CC53 2015 2015-05-04 COLOR 4.9416424226 #> 6664 2054 3F CC53 2015 2015-05-04 DO 1.7917594692 #> 6665 2054 3F CC53 2015 2015-05-04 DOSAT 4.2513483110 + #> 6666 2054 3F CC53 2015 2015-05-04 NO23 -2.9187712324 #> 6667 2054 3F CC53 2015 2015-05-04 TKN 0.1823215568 #> 6668 2054 3F CC53 2015 2015-05-04 TN 0.2263384422 + #> 6669 2054 3F CC53 2015 2015-05-04 TP -2.3968957725 #> 6670 2054 3F CC53 2015 2015-05-04 TURB 1.2809338455 #> 6671 2054 3F CC53 2015 2015-06-01 CHLAC 2.3025850930 #> 6672 2054 3F CC53 2015 2015-06-01 COLOR 4.2766661190 #> 6673 2054 3F CC53 2015 2015-06-01 DO 1.3711807233 #> 6674 2054 3F CC53 2015 2015-06-01 DOSAT 3.9259259106 + #> 6675 2054 3F 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2054 3F CC53 2016 2016-01-04 TURB 0.7419373447 #> 6730 2054 3F CC53 2016 2016-02-01 CHLAC -0.1984509387 U #> 6731 2054 3F CC53 2016 2016-02-01 COLOR 4.5432947823 #> 6732 2054 3F CC53 2016 2016-02-01 DO 1.9974177062 #> 6733 2054 3F CC53 2016 2016-02-01 DOSAT 4.3630986248 + #> 6734 2054 3F CC53 2016 2016-02-01 NO23 -5.5214609179 I #> 6735 2054 3F CC53 2016 2016-02-01 SALIN -3.5065578973 #> 6736 2054 3F CC53 2016 2016-02-01 TKN -0.6161861394 #> 6737 2054 3F CC53 2016 2016-02-01 TN -0.6088060321 + #> 6738 2054 3F CC53 2016 2016-02-01 TP -2.6592600369 #> 6739 2054 3F CC53 2016 2016-02-01 TURB 0.5877866649 A #> 6740 2054 3F CC53 2016 2016-03-07 CHLAC 0.4054651081 I #> 6741 2054 3F CC53 2016 2016-03-07 COLOR 4.3174881135 #> 6742 2054 3F CC53 2016 2016-03-07 DO 1.6074359098 #> 6743 2054 3F CC53 2016 2016-03-07 DOSAT 4.0127729085 + #> 6744 2054 3F CC53 2016 2016-03-07 NO23 -3.6119184130 #> 6745 2054 3F CC53 2016 2016-03-07 SALIN -2.3025850930 #> 6746 2054 3F CC53 2016 2016-03-07 TKN 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2017-01-03 TP -1.9661128564 #> 6837 2054 3F CC53 2017 2017-01-03 TURB 0.9555114450 #> 6838 2054 3F CC53 2017 2017-02-06 CHLAC 1.7047480922 #> 6839 2054 3F CC53 2017 2017-02-06 COLOR 3.6635616461 #> 6840 2054 3F CC53 2017 2017-02-06 DO 1.3609765531 #> 6841 2054 3F CC53 2017 2017-02-06 DOSAT 3.7819143201 + #> 6842 2054 3F CC53 2017 2017-02-06 NO23 -2.6310891600 #> 6843 2054 3F CC53 2017 2017-02-06 SALIN 1.2527629685 #> 6844 2054 3F CC53 2017 2017-02-06 TKN -0.2876820725 #> 6845 2054 3F CC53 2017 2017-02-06 TN -0.1960148839 + #> 6846 2054 3F CC53 2017 2017-02-06 TP -2.1202635362 #> 6847 2054 3F CC53 2017 2017-02-06 TURB 1.1939224685 A #> 6848 2054 3F CC53 2017 2017-03-06 CHLAC 1.0986122887 #> 6849 2054 3F CC53 2017 2017-03-06 COLOR 3.7135720667 #> 6850 2054 3F CC53 2017 2017-03-06 DO 1.5789787049 #> 6851 2054 3F CC53 2017 2017-03-06 DOSAT 4.0145795938 + #> 6852 2054 3F CC53 2017 2017-03-06 NO23 -2.5770219387 #> 6853 2054 3F CC53 2017 2017-03-06 SALIN 1.4445632692 #> 6854 2054 3F CC53 2017 2017-03-06 TKN -0.3856624808 #> 6855 2054 3F CC53 2017 2017-03-06 TN -0.2797139028 + #> 6856 2054 3F CC53 2017 2017-03-06 TP -1.6094379124 #> 6857 2054 3F CC53 2017 2017-03-06 TURB 0.9932517730 #> 6858 2054 3F CC53 2017 2017-04-03 CHLAC 2.0149030205 #> 6859 2054 3F CC53 2017 2017-04-03 COLOR 3.8286413965 #> 6860 2054 3F CC53 2017 2017-04-03 DO 1.0612565021 #> 6861 2054 3F CC53 2017 2017-04-03 DOSAT 3.6163087613 + #> 6862 2054 3F CC53 2017 2017-04-03 NO23 -3.4112477175 #> 6863 2054 3F CC53 2017 2017-04-03 SALIN 2.1610215287 #> 6864 2054 3F CC53 2017 2017-04-03 TKN -0.0725706928 #> 6865 2054 3F CC53 2017 2017-04-03 TN -0.0377018672 + #> 6866 2054 3F CC53 2017 2017-04-03 TP -1.4271163556 #> 6867 2054 3F CC53 2017 2017-04-03 TURB 1.0296194172 A #> 6868 2054 3F CC53 2017 2017-05-01 CHLAC 2.2512917986 #> 6869 2054 3F CC53 2017 2017-05-01 COLOR 4.0253516907 A #> 6870 2054 3F CC53 2017 2017-05-01 DO 1.1817271954 #> 6871 2054 3F CC53 2017 2017-05-01 DOSAT 3.7796338174 + #> 6872 2054 3F CC53 2017 2017-05-01 NO23 -4.7105307016 I #> 6873 2054 3F CC53 2017 2017-05-01 SALIN 2.6049094422 #> 6874 2054 3F CC53 2017 2017-05-01 TKN 0.5306282511 #> 6875 2054 3F CC53 2017 2017-05-01 TN 0.5329784284 + #> 6876 2054 3F CC53 2017 2017-05-01 TP -1.5141277326 #> 6877 2054 3F CC53 2017 2017-05-01 TURB 0.7884573604 #> 6878 2054 3F CC53 2017 2017-06-05 COLOR 4.0430512678 A #> 6879 2054 3F CC53 2017 2017-06-05 NO23 -4.0173835211 #> 6880 2054 3F CC53 2017 2017-06-05 TKN 0.0000000000 #> 6881 2054 3F CC53 2017 2017-06-05 TN 0.0178399181 + #> 6882 2054 3F CC53 2017 2017-06-05 TP -1.2378743560 #> 6883 2054 3F CC53 2017 2017-07-10 CHLAC 1.0986122887 #> 6884 2054 3F CC53 2017 2017-07-10 COLOR 5.2983173665 #> 6885 2054 3F CC53 2017 2017-07-10 DO 0.8020015855 #> 6886 2054 3F CC53 2017 2017-07-10 DOSAT 3.3707381742 + #> 6887 2054 3F CC53 2017 2017-07-10 NO23 -1.9661128564 #> 6888 2054 3F CC53 2017 2017-07-10 SALIN -1.2378743560 #> 6889 2054 3F CC53 2017 2017-07-10 TKN 0.3364722366 #> 6890 2054 3F CC53 2017 2017-07-10 TN 0.4317824164 + #> 6891 2054 3F CC53 2017 2017-07-10 TP -1.4696759701 #> 6892 2054 3F CC53 2017 2017-07-10 TURB 1.1939224685 #> 6893 2054 3F CC53 2017 2017-11-06 CHLAC 1.8870696490 #> 6894 2054 3F CC53 2017 2017-11-06 COLOR 4.9416424226 #> 6895 2054 3F CC53 2017 2017-11-06 DO 1.5973653312 #> 6896 2054 3F CC53 2017 2017-11-06 DOSAT 4.0621656639 #> 6897 2054 3F CC53 2017 2017-11-06 NO23 -1.3470736480 #> 6898 2054 3F CC53 2017 2017-11-06 SALIN -1.4696759701 #> 6899 2054 3F CC53 2017 2017-11-06 TKN 0.0953101798 #> 6900 2054 3F CC53 2017 2017-11-06 TN 0.3074846997 + #> 6901 2054 3F CC53 2017 2017-11-06 TP -2.0402208285 #> 6902 2054 3F CC53 2017 2017-11-06 TURB 1.3609765531 #> 6903 2054 3F CC53 2017 2017-12-04 CHLAC 2.7080502011 #> 6904 2054 3F CC53 2017 2017-12-04 COLOR 4.2341065046 #> 6905 2054 3F CC53 2017 2017-12-04 DO 1.7422190237 #> 6906 2054 3F CC53 2017 2017-12-04 DOSAT 4.1759245492 #> 6907 2054 3F CC53 2017 2017-12-04 NO23 -1.6094379124 #> 6908 2054 3F CC53 2017 2017-12-04 SALIN -0.7133498879 #> 6909 2054 3F CC53 2017 2017-12-04 TKN -0.0202027073 #> 6910 2054 3F CC53 2017 2017-12-04 TN 0.1655144385 + #> 6911 2054 3F CC53 2017 2017-12-04 TP -2.0402208285 #> 6912 2054 3F CC53 2017 2017-12-04 TURB 1.2809338455 A #> 6913 2054 3F CC53 2018 2018-01-02 CHLAC 3.2188758249 #> 6914 2054 3F CC53 2018 2018-01-02 COLOR 4.0253516907 #> 6915 2054 3F CC53 2018 2018-01-02 DO 1.7298840655 #> 6916 2054 3F CC53 2018 2018-01-02 DOSAT 4.0758410907 + #> 6917 2054 3F CC53 2018 2018-01-02 NO23 -2.0402208285 #> 6918 2054 3F CC53 2018 2018-01-02 SALIN -0.8915981193 #> 6919 2054 3F CC53 2018 2018-01-02 TKN 0.0000000000 #> 6920 2054 3F CC53 2018 2018-01-02 TN 0.1222176327 + #> 6921 2054 3F CC53 2018 2018-01-02 TP -1.9661128564 #> 6922 2054 3F CC53 2018 2018-01-02 TURB 1.8245492921 #> 6923 2054 3F CC53 2018 2018-02-05 CHLAC 3.5263605246 #> 6924 2054 3F CC53 2018 2018-02-05 COLOR 4.2484952420 #> 6925 2054 3F CC53 2018 2018-02-05 DO 1.9712993831 #> 6926 2054 3F CC53 2018 2018-02-05 DOSAT 4.3681812279 #> 6927 2054 3F CC53 2018 2018-02-05 NO23 -0.9416085399 #> 6928 2054 3F CC53 2018 2018-02-05 SALIN -0.9416085399 #> 6929 2054 3F CC53 2018 2018-02-05 TKN 0.1823215568 #> 6930 2054 3F CC53 2018 2018-02-05 TN 0.4637340162 + #> 6931 2054 3F CC53 2018 2018-02-05 TP -1.7719568419 #> 6932 2054 3F CC53 2018 2018-02-05 TURB 1.8870696490 #> 6933 2054 3F CC53 2018 2018-05-07 CHLAC 2.6390573296 #> 6934 2054 3F CC53 2018 2018-05-07 COLOR 3.9318256327 #> 6935 2054 3F CC53 2018 2018-05-07 DO 1.3217558400 #> 6936 2054 3F CC53 2018 2018-05-07 DOSAT 3.8877303129 #> 6937 2054 3F CC53 2018 2018-05-07 NO23 -5.1159958098 I #> 6938 2054 3F CC53 2018 2018-05-07 SALIN 1.9974177062 #> 6939 2054 3F CC53 2018 2018-05-07 TKN -0.0100503359 #> 6940 2054 3F CC53 2018 2018-05-07 TN -0.0060180723 + #> 6941 2054 3F CC53 2018 2018-05-07 TP -1.3862943611 #> 6942 2054 3F CC53 2018 2018-05-07 TURB 1.1939224685 #> 6943 2054 3F CC53 2018 2018-07-09 CHLAC 0.9162907319 #> 6944 2054 3F CC53 2018 2018-07-09 COLOR 5.0106352941 #> 6945 2054 3F CC53 2018 2018-07-09 DO 1.3532545070 #> 6946 2054 3F CC53 2018 2018-07-09 DOSAT 3.9435216725 #> 6947 2054 3F CC53 2018 2018-07-09 NO23 -4.3428059215 #> 6948 2054 3F CC53 2018 2018-07-09 SALIN -3.2188758249 #> 6949 2054 3F CC53 2018 2018-07-09 TKN 0.0953101798 #> 6950 2054 3F CC53 2018 2018-07-09 TN 0.1070590723 + #> 6951 2054 3F CC53 2018 2018-07-09 TP -2.5510464523 #> 6952 2054 3F CC53 2018 2018-07-09 TURB 0.9555114450 #> 6953 2054 3F CC53 2019 2019-02-04 CHLAC 1.2527629685 #> 6954 2054 3F CC53 2019 2019-02-04 COLOR 4.2766661190 #> 6955 2054 3F CC53 2019 2019-02-04 DO 1.7011051010 #> 6956 2054 3F CC53 2019 2019-02-04 DOSAT 4.0976723523 #> 6957 2054 3F CC53 2019 2019-02-04 NO23 -0.8439700703 #> 6958 2054 3F CC53 2019 2019-02-04 SALIN -1.1394342832 #> 6959 2054 3F CC53 2019 2019-02-04 TKN 0.2623642645 #> 6960 2054 3F CC53 2019 2019-02-04 TN 0.5481214085 + #> 6961 2054 3F CC53 2019 2019-02-04 TP -2.0402208285 #> 6962 2054 3F CC53 2019 2019-02-04 TURB 1.4350845253 #> 6963 2054 3F CC53 2019 2019-03-04 CHLAC 3.4657359028 #> 6964 2054 3F CC53 2019 2019-03-04 COLOR 4.3040650932 #> 6965 2054 3F CC53 2019 2019-03-04 DO 1.8115620965 #> 6966 2054 3F CC53 2019 2019-03-04 DOSAT 4.2986450257 #> 6967 2054 3F CC53 2019 2019-03-04 NO23 -2.9759296463 #> 6968 2054 3F CC53 2019 2019-03-04 SALIN -1.1711829815 #> 6969 2054 3F CC53 2019 2019-03-04 TKN 0.1823215568 #> 6970 2054 3F CC53 2019 2019-03-04 TN 0.2239432315 + #> 6971 2054 3F CC53 2019 2019-03-04 TP -2.2072749132 #> 6972 2054 3F CC53 2019 2019-03-04 TURB 2.0918640617 #> 6973 2054 3F CC53 2019 2019-04-01 CHLAC 2.0794415417 #> 6974 2054 3F CC53 2019 2019-04-01 COLOR 4.1896547420 #> 6975 2054 3F CC53 2019 2019-04-01 DO 1.6074359098 #> 6976 2054 3F CC53 2019 2019-04-01 DOSAT 4.0775374439 #> 6977 2054 3F CC53 2019 2019-04-01 NO23 -4.8283137373 I #> 6978 2054 3F CC53 2019 2019-04-01 SALIN -0.9675840263 #> 6979 2054 3F CC53 2019 2019-04-01 TKN 0.0000000000 #> 6980 2054 3F CC53 2019 2019-04-01 TN 0.0039920213 + #> 6981 2054 3F CC53 2019 2019-04-01 TP -2.3434070875 #> 6982 2054 3F CC53 2019 2019-04-01 TURB 1.0986122887 #> 6983 2054 3F CC53 2019 2019-05-06 CHLAC 2.1400661635 #> 6984 2054 3F CC53 2019 2019-05-06 COLOR 4.2046926194 A #> 6985 2054 3F CC53 2019 2019-05-06 DO 1.4182774070 #> 6986 2054 3F CC53 2019 2019-05-06 DOSAT 3.9608131696 #> 6987 2054 3F CC53 2019 2019-05-06 NO23 -4.8283137373 I #> 6988 2054 3F CC53 2019 2019-05-06 SALIN 0.7371640660 #> 6989 2054 3F CC53 2019 2019-05-06 TKN 0.0953101798 #> 6990 2054 3F CC53 2019 2019-05-06 TN 0.0989399479 + #> 6991 2054 3F CC53 2019 2019-05-06 TP -1.8325814637 #> 6992 2054 3F CC53 2019 2019-05-06 TURB 1.0647107370 #> 6993 2054 3F CC53 2019 2019-08-05 CHLAC 0.4700036292 I #> 6994 2054 3F CC53 2019 2019-08-05 COLOR 5.3936275464 #> 6995 2054 3F CC53 2019 2019-08-05 DO 1.2383742310 #> 6996 2054 3F CC53 2019 2019-08-05 DOSAT 3.7750571504 #> 6997 2054 3F CC53 2019 2019-08-05 NO23 -2.3859667019 #> 6998 2054 3F CC53 2019 2019-08-05 SALIN -1.7719568419 #> 6999 2054 3F CC53 2019 2019-08-05 TKN 0.4700036292 #> 7000 2054 3F CC53 2019 2019-08-05 TN 0.5259112612 + #> 7001 2054 3F CC53 2019 2019-08-05 TP -1.3862943611 #> 7002 2054 3F CC53 2019 2019-08-05 TURB 0.9162907319 #> 7003 2054 3F CC53 2020 2020-01-06 CHLAC 1.8405496334 #> 7004 2054 3F CC53 2020 2020-01-06 COLOR 3.8712010109 A #> 7005 2054 3F CC53 2020 2020-01-06 DO 1.7439688054 #> 7006 2054 3F CC53 2020 2020-01-06 DOSAT 4.1255201797 #> 7007 2054 3F CC53 2020 2020-01-06 NO23 -2.8824035882 #> 7008 2054 3F CC53 2020 2020-01-06 SALIN -0.5276327421 #> 7009 2054 3F CC53 2020 2020-01-06 TKN -0.4155154440 #> 7010 2054 3F CC53 2020 2020-01-06 TN -0.3340751120 + #> 7011 2054 3F CC53 2020 2020-01-06 TP -2.3644604967 #> 7012 2054 3F CC53 2020 2020-01-06 TURB 0.7884573604 #> 7013 2054 3F CC53 2020 2020-02-03 CHLAC 1.6292405397 #> 7014 2054 3F CC53 2020 2020-02-03 COLOR 3.7612001157 #> 7015 2054 3F CC53 2020 2020-02-03 DO 1.6808279085 #> 7016 2054 3F CC53 2020 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2021-02-01 COLOR 4.2046926194 A #> 7071 2054 3F CC53 2021 2021-02-01 DO 1.8779371655 #> 7072 2054 3F CC53 2021 2021-02-01 DOSAT 4.2822062994 #> 7073 2054 3F CC53 2021 2021-02-01 NO23 -5.5214609179 U #> 7074 2054 3F CC53 2021 2021-02-01 SALIN 0.1739533071 #> 7075 2054 3F CC53 2021 2021-02-01 TKN -0.0408219945 #> 7076 2054 3F CC53 2021 2021-02-01 TN -0.0387408283 + #> 7077 2054 3F CC53 2021 2021-02-01 TP -2.0402208285 #> 7078 2054 3F CC53 2021 2021-02-01 TURB 1.4350845253 A #> 7079 2054 3F CC53 2021 2021-03-01 CHLAC 2.6390573296 #> 7080 2054 3F CC53 2021 2021-03-01 COLOR 4.0604430105 #> 7081 2054 3F CC53 2021 2021-03-01 DO 1.7369512327 #> 7082 2054 3F CC53 2021 2021-03-01 DOSAT 4.2239097666 #> 7083 2054 3F CC53 2021 2021-03-01 NO23 -5.5214609179 U #> 7084 2054 3F CC53 2021 2021-03-01 SALIN -0.5108256238 #> 7085 2054 3F CC53 2021 2021-03-01 TKN 0.0953101798 #> 7086 2054 3F CC53 2021 2021-03-01 TN 0.0971267107 + #> 7087 2054 3F CC53 2021 2021-03-01 TP -2.0402208285 #> 7088 2054 3F CC53 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2022-02-07 NO23 -4.9618451299 I #> 7179 2054 3F CC53 2022 2022-02-07 SALIN 1.3270750015 #> 7180 2054 3F CC53 2022 2022-02-07 TKN -0.1863295782 #> 7181 2054 3F CC53 2022 2022-02-07 TN -0.1815218766 + #> 7182 2054 3F CC53 2022 2022-02-07 TP -1.8325814637 #> 7183 2054 3F CC53 2022 2022-02-07 TURB 1.2237754316 #> 7184 2054 3F CC53 2022 2022-03-07 CHLAC 2.3025850930 #> 7185 2054 3F CC53 2022 2022-03-07 COLOR 3.8066624898 A #> 7186 2054 3F CC53 2022 2022-03-07 NO23 -5.2983173665 I #> 7187 2054 3F CC53 2022 2022-03-07 TKN -0.1278333715 #> 7188 2054 3F CC53 2022 2022-03-07 TN -0.1232982163 + #> 7189 2054 3F CC53 2022 2022-03-07 TP -1.6094379124 #> 7190 2054 3F CC53 2022 2022-03-07 TURB 1.0296194172 #> 7191 2054 3F CC53 2022 2022-04-04 CHLAC 2.7725887222 #> 7192 2054 3F CC53 2022 2022-04-04 COLOR 3.9702919136 A #> 7193 2054 3F CC53 2022 2022-04-04 DO 1.1908875648 #> 7194 2054 3F CC53 2022 2022-04-04 DOSAT 3.7208625000 #> 7195 2054 3F CC53 2022 2022-04-04 NO23 -4.1997050779 #> 7196 2054 3F CC53 2022 2022-04-04 SALIN 2.1860512767 #> 7197 2054 3F CC53 2022 2022-04-04 TKN -0.3147107448 #> 7198 2054 3F CC53 2022 2022-04-04 TN -0.2943710606 + #> 7199 2054 3F CC53 2022 2022-04-04 TP -1.2378743560 #> 7200 2054 3F CC53 2022 2022-04-04 TURB 1.0296194172 #> 7201 2054 3F CC53 2022 2022-05-02 CHLAC 2.4849066498 #> 7202 2054 3F CC53 2022 2022-05-02 COLOR 4.0073331852 #> 7203 2054 3F CC53 2022 2022-05-02 NO23 -3.9120230054 #> 7204 2054 3F CC53 2022 2022-05-02 SALIN 2.5152741864 #> 7205 2054 3F CC53 2022 2022-05-02 TKN 0.0953101798 #> 7206 2054 3F CC53 2022 2022-05-02 TN 0.1133286853 + #> 7207 2054 3F CC53 2022 2022-05-02 TP -1.1394342832 #> 7208 2054 3F CC53 2022 2022-05-02 TURB 1.0986122887 #> 7209 2054 3F CC53 2014 2014-04-07 CHLAC 1.0986122887 #> 7210 2054 3F CC53 2014 2014-04-07 COLOR 5.0751738152 #> 7211 2054 3F CC53 2014 2014-04-07 COND 7.1701195434 #> 7212 2054 3F CC53 2014 2014-04-07 DO 1.7029282555 #> 7213 2054 3F CC53 2014 2014-04-07 DOSAT 4.0976723523 #> 7214 2054 3F CC53 2014 2014-04-07 NO23 -3.1700856607 #> 7215 2054 3F CC53 2014 2014-04-07 SALIN -0.3566749439 + #> 7216 2054 3F CC53 2014 2014-04-07 TKN 0.6418538862 #> 7217 2054 3F CC53 2014 2014-04-07 TN 0.6637183699 + #> 7218 2054 3F CC53 2014 2014-04-07 TP 0.0953101798 #> 7219 2054 3F CC53 2014 2014-04-07 TSS 2.9444389792 #> 7220 2054 3F CC53 2014 2014-04-07 TURB 2.7725887222 #> 7221 2054 3F CC53 2015 2015-05-21 COND 7.9291264873 #> 7222 2054 3F CC53 2015 2015-05-21 DO 1.4109869737 #> 7223 2054 3F CC53 2015 2015-05-21 DOSAT 3.9702919136 #> 7224 2054 3F CC53 2015 2015-05-21 SALIN 0.2851789422 + #> 7225 2054 3F CC53 2015 2015-07-15 COND 6.5439118456 #> 7226 2054 3F CC53 2015 2015-07-15 COND 6.5453496603 #> 7227 2054 3F CC53 2015 2015-07-15 SALIN -1.1711829815 + #> 7228 2054 3F CC53 2015 2015-08-06 COND 4.9052747784 #> 7229 2054 3F CC53 2015 2015-08-06 DO 1.4109869737 #> 7230 2054 3F CC53 2015 2015-08-06 DOSAT 3.9702919136 #> 7231 2054 3F CC53 2015 2015-08-19 COND 4.8751973232 #> 7232 2054 3F CC53 2015 2015-08-19 DO 1.2527629685 #> 7233 2054 3F CC53 2015 2015-08-19 DOSAT 3.8501476017 #> 7234 2054 3F CC53 2015 2015-09-15 COND 5.4764635519 #> 7235 2054 3F CC53 2015 2015-09-15 DO 1.1314021115 #> 7236 2054 3F CC53 2015 2015-09-15 DOSAT 3.6888794541 #> 7237 2054 3F CC53 2015 2015-09-15 SALIN -2.2072749132 + #> 7238 2054 3F CC53 2015 2015-09-15 COND 5.4764635519 #> 7239 2054 3F CC53 2015 2015-09-15 DO 1.0986122887 #> 7240 2054 3F CC53 2015 2015-09-15 DOSAT 3.6635616461 #> 7241 2054 3F CC53 2015 2015-09-15 SALIN -2.2072749132 + #> 7242 2054 3F CC53 2015 2015-11-25 COND 6.2225762681 #> 7243 2054 3F CC53 2015 2015-11-25 DO 1.7047480922 #> 7244 2054 3F CC53 2015 2015-11-25 DOSAT 4.1431347264 #> 7245 2054 3F CC53 2015 2015-11-25 SALIN -1.3470736480 + #> 7246 2054 3F CC53 2015 2015-11-25 COND 6.2285110036 #> 7247 2054 3F CC53 2015 2015-11-25 DO 1.6863989536 #> 7248 2054 3F CC53 2015 2015-11-25 DOSAT 4.1431347264 #> 7249 2054 3F CC53 2015 2015-11-25 SALIN -1.3470736480 + #> 7250 2054 3F CC53 2021 2021-02-02 COND 7.0184017991 #> 7251 2054 3F CC53 2021 2021-02-02 DO 1.9183921202 #> 7252 2054 3F CC53 2021 2021-02-02 DOSAT 4.2822062994 #> 7253 2054 3F CC53 2021 2021-02-02 SALIN -0.5798184953 #> 7254 2054 3F CC53 2021 2021-03-16 COND 7.8504931809 #> 7255 2054 3F CC53 2021 2021-03-16 DO 1.7783364489 #> 7256 2054 3F CC53 2021 2021-03-16 DOSAT 4.2527717988 #> 7257 2054 3F CC53 2021 2021-03-16 SALIN 0.2776317366 #> 7258 2054 3F CC53 2021 2021-09-30 COND 4.8880909413 #> 7259 2054 3F CC53 2021 2021-09-30 DO 1.3532545070 #> 7260 2054 3F CC53 2021 2021-09-30 DOSAT 3.8774315607 #> 7261 2054 3F CC53 2021 2021-09-30 SALIN -2.8134107168 #> 7262 2054 3F CC53 2021 2021-09-30 COND 4.8797670189 #> 7263 2054 3F CC53 2021 2021-09-30 DO 1.2412685891 #> 7264 2054 3F CC53 2021 2021-09-30 DOSAT 3.7750571504 #> 7265 2054 3F CC53 2021 2021-09-30 SALIN -2.8134107168 #> 7266 2054 3F CC53 2021 2021-10-27 COND 6.5250296578 #> 7267 2054 3F CC53 2021 2021-10-27 DO 1.5195132049 #> 7268 2054 3F CC53 2021 2021-10-27 DOSAT 4.0412953411 #> 7269 2054 3F CC53 2021 2021-10-27 SALIN -1.1086626245 #> 7270 2054 3F CC53 2021 2021-10-27 COND 6.5264948596 #> 7271 2054 3F CC53 2021 2021-10-27 DO 1.5129270121 #> 7272 2054 3F CC53 2021 2021-10-27 DOSAT 4.0342406382 #> 7273 2054 3F CC53 2021 2021-10-27 SALIN -1.1086626245 #> 7274 2054 3F CC53 2021 2021-11-18 COND 4.7104306966 #> 7275 2054 3F CC53 2021 2021-11-18 DO 1.8578592709 #> 7276 2054 3F CC53 2021 2021-11-18 DOSAT 4.2682978693 #> 7277 2054 3F CC53 2021 2021-11-18 SALIN -2.9957322736 #> 7278 2059 3M CC55 2015 2015-05-21 COND 7.3472997007 #> 7279 2059 3M CC55 2015 2015-05-21 DO 0.9932517730 #> 7280 2059 3M CC55 2015 2015-05-21 DOSAT 3.4657359028 #> 7281 2059 3M CC55 2015 2015-05-21 SALIN -0.3285040670 + #> 7282 2059 3M CC55 2015 2015-07-15 COND 9.6044074351 #> 7283 2059 3M CC55 2015 2015-08-06 COND 6.4068799861 #> 7284 2059 3M CC55 2015 2015-08-06 DO 1.6486586256 #> 7285 2059 3M CC55 2015 2015-08-06 DOSAT 4.2195077052 #> 7286 2059 3M CC55 2015 2015-08-06 SALIN -1.3093333200 + #> 7287 2059 3M CC55 2015 2015-08-19 COND 6.2653012127 #> 7288 2059 3M CC55 2015 2015-08-19 DO 1.3862943611 #> 7289 2059 3M CC55 2015 2015-08-19 DOSAT 4.0604430105 #> 7290 2059 3M CC55 2015 2015-08-19 SALIN -1.4271163556 + #> 7291 2059 3M CC55 2015 2015-09-15 COND 6.2519038832 #> 7292 2059 3M CC55 2015 2015-09-15 DO 1.6863989536 #> 7293 2059 3M CC55 2015 2015-09-15 DOSAT 4.1271343850 #> 7294 2059 3M CC55 2015 2015-09-15 SALIN -1.4271163556 + #> 7295 2059 3M CC55 2015 2015-11-25 COND 8.4348979487 #> 7296 2059 3M CC55 2015 2015-11-25 DO -0.1053605157 #> 7297 2059 3M CC55 2015 2015-11-25 DOSAT 2.3025850930 #> 7298 2059 3M CC55 2015 2015-11-25 SALIN 1.0152306797 + #> 7299 2059 3M CC55 2015 2015-05-21 COND 9.9007337643 #> 7300 2059 3M CC55 2015 2015-05-21 DO 1.2237754316 #> 7301 2059 3M CC55 2015 2015-05-21 DOSAT 3.8286413965 #> 7302 2059 3M CC55 2015 2015-05-21 SALIN 2.4105422345 + #> 7303 2059 3M CC55 2015 2015-07-15 COND 6.7190131544 #> 7304 2059 3M CC55 2015 2015-07-15 SALIN -0.9416085399 + #> 7305 2059 3M CC55 2015 2015-08-06 COND 6.4019171967 #> 7306 2059 3M CC55 2015 2015-08-06 DO 1.6292405397 #> 7307 2059 3M CC55 2015 2015-08-06 DOSAT 4.1896547420 #> 7308 2059 3M CC55 2015 2015-08-06 SALIN -1.3093333200 + #> 7309 2059 3M CC55 2015 2015-08-19 COND 6.2785214242 #> 7310 2059 3M CC55 2015 2015-08-19 DO 1.6094379124 #> 7311 2059 3M CC55 2015 2015-08-19 DOSAT 4.1431347264 #> 7312 2059 3M CC55 2015 2015-08-19 SALIN -1.3862943611 + #> 7313 2059 3M CC55 2015 2015-09-15 COND 6.2205901701 #> 7314 2059 3M CC55 2015 2015-09-15 DO 1.4816045409 #> 7315 2059 3M CC55 2015 2015-09-15 DOSAT 4.0073331852 #> 7316 2059 3M CC55 2015 2015-09-15 SALIN -1.4271163556 + #> 7317 2059 3M CC55 2015 2015-10-08 CHLAC 0.2623642645 I #> 7318 2059 3M CC55 2015 2015-10-08 COND 6.3969296552 #> 7319 2059 3M CC55 2015 2015-10-08 DO 1.6486586256 #> 7320 2059 3M CC55 2015 2015-10-08 DOSAT 4.2046926194 #> 7321 2059 3M CC55 2015 2015-10-08 NO23 -2.7646205526 #> 7322 2059 3M CC55 2015 2015-10-08 SALIN -1.2378743560 + #> 7323 2059 3M CC55 2015 2015-10-08 TKN -0.1625189295 #> 7324 2059 3M CC55 2015 2015-10-08 TN -0.0910193984 + #> 7325 2059 3M CC55 2015 2015-10-08 TP -2.6310891600 #> 7326 2059 3M CC55 2015 2015-10-08 TSS 1.9459101491 I #> 7327 2059 3M CC55 2015 2015-10-08 TURB 2.0794415417 #> 7328 2059 3M CC55 2015 2015-11-05 CHLAC 0.5877866649 #> 7329 2059 3M CC55 2015 2015-11-05 COND 6.6982680541 #> 7330 2059 3M CC55 2015 2015-11-05 DO 1.9600947840 #> 7331 2059 3M CC55 2015 2015-11-05 DOSAT 4.4773368145 #> 7332 2059 3M CC55 2015 2015-11-05 SALIN -0.9416085399 + #> 7333 2059 3M CC55 2015 2015-11-05 TN -0.0693500781 + #> 7334 2059 3M CC55 2015 2015-11-05 TSS 1.7917594692 I #> 7335 2059 3M CC55 2015 2015-11-05 TURB 2.2721258855 #> 7336 2059 3M CC55 2015 2015-11-25 COND 6.7007311095 #> 7337 2059 3M CC55 2015 2015-11-25 DO 2.0014800002 #> 7338 2059 3M CC55 2015 2015-11-25 DOSAT 4.4188406078 #> 7339 2059 3M CC55 2015 2015-11-25 SALIN -0.8209805521 + #> 7340 2059 3M CC55 2015 2015-12-03 CHLAC 0.5306282511 #> 7341 2059 3M CC55 2015 2015-12-03 COLOR 4.7004803658 #> 7342 2059 3M CC55 2015 2015-12-03 COND 6.8448154792 #> 7343 2059 3M CC55 2015 2015-12-03 DO 1.8900953699 #> 7344 2059 3M CC55 2015 2015-12-03 DOSAT 4.3694478525 #> 7345 2059 3M CC55 2015 2015-12-03 NO23 -2.7488721956 #> 7346 2059 3M CC55 2015 2015-12-03 SALIN -0.7550225843 + #> 7347 2059 3M CC55 2015 2015-12-03 TKN -0.2357223335 #> 7348 2059 3M CC55 2015 2015-12-03 TN -0.1578240852 + #> 7349 2059 3M CC55 2015 2015-12-03 TP -2.8647040111 #> 7350 2059 3M CC55 2015 2015-12-03 TSS 1.3862943611 I #> 7351 2059 3M CC55 2015 2015-12-03 TURB 2.1282317058 #> 7352 2059 3M CC56 2015 2015-05-21 COND 9.6019769721 #> 7353 2059 3M CC56 2015 2015-05-21 DO 0.6931471806 #> 7354 2059 3M CC56 2015 2015-05-21 DOSAT 3.1780538303 #> 7355 2059 3M CC56 2015 2015-05-21 SALIN 2.1459312829 + #> 7356 2059 3M CC56 2015 2015-07-15 COND 8.4859089014 #> 7357 2059 3M CC56 2015 2015-07-15 SALIN 0.9001613499 + #> 7358 2059 3M CC56 2015 2015-08-06 COND 6.3952615981 #> 7359 2059 3M CC56 2015 2015-08-06 DO 0.9932517730 #> 7360 2059 3M CC56 2015 2015-08-06 DOSAT 3.4657359028 #> 7361 2059 3M CC56 2015 2015-08-06 SALIN -1.3093333200 + #> 7362 2059 3M CC56 2015 2015-08-19 COND 6.1820849067 #> 7363 2059 3M CC56 2015 2015-08-19 DO 0.9932517730 #> 7364 2059 3M CC56 2015 2015-08-19 DOSAT 3.4965075615 #> 7365 2059 3M CC56 2015 2015-08-19 SALIN -1.5141277326 + #> 7366 2059 3M CC56 2015 2015-09-15 COND 6.2576675879 #> 7367 2059 3M CC56 2015 2015-09-15 DO 0.0953101798 #> 7368 2059 3M CC56 2015 2015-09-15 DOSAT 2.5649493575 #> 7369 2059 3M CC56 2015 2015-09-15 SALIN -1.4271163556 + #> 7370 2059 3M CC56 2015 2015-11-25 COND 7.6343372356 #> 7371 2059 3M CC56 2015 2015-11-25 DO 0.9555114450 #> 7372 2059 3M CC56 2015 2015-11-25 DOSAT 3.4011973817 #> 7373 2059 3M CC56 2015 2015-11-25 SALIN 0.1570037488 + #> 7374 2059 3M CC56 2015 2015-05-21 COND 9.9350831141 #> 7375 2059 3M CC56 2015 2015-05-21 DO 0.7884573604 #> 7376 2059 3M CC56 2015 2015-05-21 DOSAT 3.3672958300 #> 7377 2059 3M CC56 2015 2015-05-21 SALIN 2.4865719291 + #> 7378 2059 3M CC56 2015 2015-07-15 CHLAC 1.0986122887 #> 7379 2059 3M CC56 2015 2015-07-15 COND 9.6128678361 #> 7380 2059 3M CC56 2015 2015-07-15 NO23 -5.5214609179 U #> 7381 2059 3M CC56 2015 2015-07-15 SALIN 2.0881534823 + #> 7382 2059 3M CC56 2015 2015-07-15 TKN 0.2623642645 #> 7383 2059 3M CC56 2015 2015-07-15 TN 0.2639015438 + #> 7384 2059 3M CC56 2015 2015-07-15 TP -0.9416085399 #> 7385 2059 3M CC56 2015 2015-07-15 TSS 1.0986122887 U #> 7386 2059 3M CC56 2015 2015-07-15 TURB 1.3862943611 #> 7387 2059 3M CC56 2015 2015-08-06 COND 6.5366915976 #> 7388 2059 3M CC56 2015 2015-08-06 DO 0.2623642645 #> 7389 2059 3M CC56 2015 2015-08-06 DOSAT 2.7725887222 #> 7390 2059 3M CC56 2015 2015-08-06 SALIN -1.1394342832 + #> 7391 2059 3M CC56 2015 2015-08-19 CHLAC 1.0296194172 #> 7392 2059 3M CC56 2015 2015-08-19 COLOR 5.4380793089 #> 7393 2059 3M CC56 2015 2015-08-19 COND 6.4488893941 #> 7394 2059 3M CC56 2015 2015-08-19 DO 0.1823215568 #> 7395 2059 3M CC56 2015 2015-08-19 DOSAT 2.7725887222 #> 7396 2059 3M CC56 2015 2015-08-19 NO23 -5.5214609179 U #> 7397 2059 3M CC56 2015 2015-08-19 SALIN -1.2378743560 + #> 7398 2059 3M CC56 2015 2015-08-19 TKN 0.4054651081 #> 7399 2059 3M CC56 2015 2015-08-19 TN 0.4067975533 + #> 7400 2059 3M CC56 2015 2015-08-19 TP -0.0304592075 #> 7401 2059 3M CC56 2015 2015-08-19 TSS 1.7917594692 I #> 7402 2059 3M CC56 2015 2015-08-19 TURB 1.5686159179 #> 7403 2059 3M CC56 2015 2015-09-15 COND 6.8134445995 #> 7404 2059 3M CC56 2015 2015-09-15 DO 0.0000000000 #> 7405 2059 3M CC56 2015 2015-09-15 DOSAT 2.3025850930 #> 7406 2059 3M CC56 2015 2015-09-15 SALIN -0.8439700703 + #> 7407 2059 3M CC56 2015 2015-11-25 COND 7.8038433035 #> 7408 2059 3M CC56 2015 2015-11-25 DO 1.8718021769 #> 7409 2059 3M CC56 2015 2015-11-25 DOSAT 4.2626798770 #> 7410 2059 3M CC56 2015 2015-11-25 SALIN 0.3576744443 + #> 7411 2059 3M CC56 2018 2018-03-06 CHLAC 1.7917594692 #> 7412 2059 3M CC56 2018 2018-03-06 COND 9.8471817163 #> 7413 2059 3M CC56 2018 2018-03-06 DO 0.6205764877 #> 7414 2059 3M CC56 2018 2018-03-06 DOSAT 3.0445224377 #> 7415 2059 3M CC56 2018 2018-03-06 NO23 -2.6592600369 #> 7416 2059 3M CC56 2018 2018-03-06 SALIN 2.5748996883 + #> 7417 2059 3M CC56 2018 2018-03-06 TKN -0.0833816089 #> 7418 2059 3M CC56 2018 2018-03-06 TN -0.0100503359 + #> 7419 2059 3M CC56 2018 2018-03-06 TP -1.2378743560 #> 7420 2059 3M CC56 2018 2018-03-06 TSS 1.0986122887 U #> 7421 2059 3M CC56 2018 2018-03-06 TURB 0.1823215568 #> 7422 2059 3M CC56 2018 2018-03-29 CHLAC 2.1747517215 #> 7423 2059 3M CC56 2018 2018-03-29 COND 10.2506170836 #> 7424 2059 3M CC56 2018 2018-03-29 DO 1.3083328197 #> 7425 2059 3M CC56 2018 2018-03-29 DOSAT 3.8501476017 #> 7426 2059 3M CC56 2018 2018-03-29 NO23 -4.7105307016 I #> 7427 2059 3M CC56 2018 2018-03-29 SALIN 2.9156062291 + #> 7428 2059 3M CC56 2018 2018-03-29 TKN -0.2484613593 #> 7429 2059 3M CC56 2018 2018-03-29 TN -0.2433462586 + #> 7430 2059 3M CC56 2018 2018-03-29 TP -1.2039728043 #> 7431 2059 3M CC56 2018 2018-03-29 TSS 1.3862943611 I #> 7432 2059 3M CC56 2018 2018-03-29 TURB 0.8754687374 #> 7433 2059 3M CC56 2018 2018-04-12 COND 10.0096027833 #> 7434 2059 3M CC56 2018 2018-04-12 DO -0.3566749439 #> 7435 2059 3M CC56 2018 2018-04-12 DOSAT 2.0794415417 #> 7436 2059 3M CC56 2018 2018-04-12 SALIN 2.6932749155 + #> 7437 2059 3M CC56 2018 2018-04-19 CHLAC 0.0953101798 I #> 7438 2059 3M CC56 2018 2018-04-19 COND 10.2545668701 #> 7439 2059 3M CC56 2018 2018-04-19 DO 1.0260415958 #> 7440 2059 3M CC56 2018 2018-04-19 DOSAT 3.5025498759 #> 7441 2059 3M CC56 2018 2018-04-19 NO23 -4.6051701860 I #> 7442 2059 3M CC56 2018 2018-04-19 SALIN 2.9150643705 + #> 7443 2059 3M CC56 2018 2018-04-19 TKN -0.1863295782 #> 7444 2059 3M CC56 2018 2018-04-19 TN -0.1815218766 + #> 7445 2059 3M CC56 2018 2018-04-19 TP -1.0788096614 #> 7446 2059 3M CC56 2018 2018-04-19 TSS 1.3862943611 I #> 7447 2059 3M CC56 2018 2018-04-19 TURB 0.1823215568 #> 7448 2059 3M CC56 2018 2018-05-10 CHLAC 1.0296194172 #> 7449 2059 3M CC56 2018 2018-05-10 COND 10.2722540975 #> 7450 2059 3M CC56 2018 2018-05-10 DO -0.1053605157 #> 7451 2059 3M CC56 2018 2018-05-10 DOSAT 2.4849066498 #> 7452 2059 3M CC56 2018 2018-05-10 NO23 -5.5214609179 U #> 7453 2059 3M CC56 2018 2018-05-10 SALIN 2.8848007128 #> 7454 2059 3M CC56 2018 2018-05-10 TKN -0.0725706928 #> 7455 2059 3M CC56 2018 2018-05-10 TN -0.0704224643 + #> 7456 2059 3M CC56 2018 2018-05-10 TP -0.8209805521 #> 7457 2059 3M CC56 2018 2018-05-10 TSS 1.0986122887 I #> 7458 2059 3M CC56 2018 2018-05-10 TURB 0.5306282511 #> 7459 2059 3M CC56 2018 2018-06-25 CHLAC 0.6931471806 #> 7460 2059 3M CC56 2018 2018-06-25 COND 7.7536235466 #> 7461 2059 3M CC56 2018 2018-06-25 DO 1.0296194172 #> 7462 2059 3M CC56 2018 2018-06-25 DOSAT 3.2695689392 #> 7463 2059 3M CC56 2018 2018-06-25 NO23 -5.5214609179 U #> 7464 2059 3M CC56 2018 2018-06-25 SALIN 0.1397619424 + #> 7465 2059 3M CC56 2018 2018-06-25 TKN 0.2623642645 #> 7466 2059 3M CC56 2018 2018-06-25 TN 0.2639015438 + #> 7467 2059 3M CC56 2018 2018-06-25 TP -1.4696759701 #> 7468 2059 3M CC56 2018 2018-06-25 TSS 1.0986122887 I #> 7469 2059 3M CC56 2018 2018-06-25 TURB 1.3862943611 #> 7470 2059 3M CC56 2018 2018-07-17 CHLAC 0.9932517730 #> 7471 2059 3M CC56 2018 2018-07-17 COND 6.8437499490 #> 7472 2059 3M CC56 2018 2018-07-17 DO -0.1863295782 #> 7473 2059 3M CC56 2018 2018-07-17 DOSAT 2.3418058061 #> 7474 2059 3M CC56 2018 2018-07-17 NO23 -3.3524072175 #> 7475 2059 3M CC56 2018 2018-07-17 SALIN -0.8439700703 + #> 7476 2059 3M CC56 2018 2018-07-17 TKN 0.2623642645 #> 7477 2059 3M CC56 2018 2018-07-17 TN 0.2889312919 + #> 7478 2059 3M CC56 2018 2018-07-17 TP -1.3093333200 #> 7479 2059 3M CC56 2018 2018-07-17 TSS 1.0986122887 I #> 7480 2059 3M CC56 2018 2018-07-17 TURB 0.0953101798 #> 7481 2059 3M CC56 2018 2018-08-01 CHLAC 0.8754687374 #> 7482 2059 3M CC56 2018 2018-08-01 COND 6.0038870671 #> 7483 2059 3M CC56 2018 2018-08-01 DO 0.7129498079 #> 7484 2059 3M CC56 2018 2018-08-01 DOSAT 3.2580965380 #> 7485 2059 3M CC56 2018 2018-08-01 NO23 -3.6119184130 #> 7486 2059 3M CC56 2018 2018-08-01 SALIN -1.6607312068 #> 7487 2059 3M CC56 2018 2018-08-01 TKN 0.0953101798 #> 7488 2059 3M CC56 2018 2018-08-01 TN 0.1195592351 + #> 7489 2059 3M CC56 2018 2018-08-01 TP -1.7719568419 #> 7490 2059 3M CC56 2018 2018-08-01 TSS 0.6931471806 U #> 7491 2059 3M CC56 2018 2018-08-01 TURB 0.0953101798 #> 7492 2059 3M CC56 2018 2018-08-20 CHLAC 0.4054651081 I #> 7493 2059 3M CC56 2018 2018-08-20 NO23 -1.4696759701 #> 7494 2059 3M CC56 2018 2018-08-20 TKN -0.3147107448 #> 7495 2059 3M CC56 2018 2018-08-20 TN -0.0408219945 + #> 7496 2059 3M CC56 2018 2018-08-20 TP -0.9416085399 #> 7497 2059 3M CC56 2018 2018-08-20 TSS 1.0986122887 U #> 7498 2059 3M CC56 2018 2018-08-20 TURB 0.7419373447 #> 7499 2059 3M CC56 2018 2018-08-21 CHLAC 0.7419373447 #> 7500 2059 3M CC56 2018 2018-08-21 COND 5.9401712527 #> 7501 2059 3M CC56 2018 2018-08-21 DO 0.9516578757 #> 7502 2059 3M CC56 2018 2018-08-21 DOSAT 3.4436180975 #> 7503 2059 3M CC56 2018 2018-08-21 NO23 -3.7297014486 #> 7504 2059 3M CC56 2018 2018-08-21 SALIN -1.7147984281 #> 7505 2059 3M CC56 2018 2018-08-21 TKN 0.0000000000 #> 7506 2059 3M CC56 2018 2018-08-21 TN 0.0237165266 + #> 7507 2059 3M CC56 2018 2018-08-21 TP -1.8325814637 #> 7508 2059 3M CC56 2018 2018-08-21 TSS 1.0986122887 I #> 7509 2059 3M CC56 2018 2018-08-21 TURB 0.3364722366 A #> 7510 2059 3M CC56 2018 2018-09-20 CHLAC 1.5040773968 #> 7511 2059 3M CC56 2018 2018-09-20 COND 7.2661287796 #> 7512 2059 3M CC56 2018 2018-09-20 DO 0.9555114450 #> 7513 2059 3M CC56 2018 2018-09-20 DOSAT 3.5862928653 #> 7514 2059 3M CC56 2018 2018-09-20 NO23 -3.1010927892 #> 7515 2059 3M CC56 2018 2018-09-20 SALIN -0.3424903089 #> 7516 2059 3M CC56 2018 2018-09-20 TKN 0.1823215568 #> 7517 2059 3M CC56 2018 2018-09-20 TN 0.2191355299 + #> 7518 2059 3M CC56 2018 2018-09-20 TP -1.0788096614 #> 7519 2059 3M CC56 2018 2018-09-20 TSS 1.0986122887 I #> 7520 2059 3M CC56 2018 2018-09-20 TURB 0.9162907319 #> 7521 2059 3M CC56 2018 2018-10-24 CHLAC 1.1314021115 #> 7522 2059 3M CC56 2018 2018-10-24 COND 9.4323632956 #> 7523 2059 3M CC56 2018 2018-10-24 DO 0.5068176024 #> 7524 2059 3M CC56 2018 2018-10-24 DOSAT 3.0726933147 #> 7525 2059 3M CC56 2018 2018-10-24 NO23 -3.4737680745 #> 7526 2059 3M CC56 2018 2018-10-24 SALIN 1.9671123567 #> 7527 2059 3M CC56 2018 2018-10-24 TKN -0.0408219945 #> 7528 2059 3M CC56 2018 2018-10-24 TN -0.0090407447 + #> 7529 2059 3M CC56 2018 2018-10-24 TP -1.2039728043 #> 7530 2059 3M CC56 2018 2018-10-24 TSS 0.6931471806 I #> 7531 2059 3M CC56 2018 2018-10-24 TURB 1.7227665977 #> 7532 2059 3M CC56 2019 2019-01-16 CHLAC -0.1053605157 I #> 7533 2059 3M CC56 2019 2019-01-16 COND 9.0122552200 #> 7534 2059 3M CC56 2019 2019-01-16 DO 0.3852624008 #> 7535 2059 3M CC56 2019 2019-01-16 DOSAT 2.7080502011 #> 7536 2059 3M CC56 2019 2019-01-16 NO23 -2.5010360317 #> 7537 2059 3M CC56 2019 2019-01-16 SALIN 1.5216989981 #> 7538 2059 3M CC56 2019 2019-01-16 TKN -0.0618754037 #> 7539 2059 3M CC56 2019 2019-01-16 TN 0.0217614918 + #> 7540 2059 3M CC56 2019 2019-01-16 TP -1.3862943611 #> 7541 2059 3M CC56 2019 2019-01-16 TSS 0.6931471806 U #> 7542 2059 3M CC56 2019 2019-01-16 TURB 0.0000000000 #> 7543 2059 3M CC56 2019 2019-01-24 COND 9.8578100390 #> 7544 2059 3M CC56 2019 2019-01-24 DO 1.6770965609 #> 7545 2059 3M CC56 2019 2019-01-24 DOSAT 4.1588830834 #> 7546 2059 3M CC56 2019 2019-01-24 NO23 -3.2968373663 #> 7547 2059 3M CC56 2019 2019-01-24 SALIN 2.4327357775 #> 7548 2059 3M CC56 2019 2019-01-24 TKN -0.3147107448 #> 7549 2059 3M CC56 2019 2019-01-24 TN -0.2652684776 + #> 7550 2059 3M CC56 2019 2019-01-24 TP -1.3470736480 #> 7551 2059 3M CC56 2019 2019-01-24 TSS 1.0986122887 U #> 7552 2059 3M CC56 2019 2019-01-24 TURB 0.6418538862 #> 7553 2059 3M CC56 2019 2019-03-12 CHLAC 0.1823215568 I #> 7554 2059 3M CC56 2019 2019-03-12 COND 9.1291303166 #> 7555 2059 3M CC56 2019 2019-03-12 DO 0.4824261492 #> 7556 2059 3M CC56 2019 2019-03-12 DOSAT 2.9496883351 #> 7557 2059 3M CC56 2019 2019-03-12 NO23 -3.2968373663 #> 7558 2059 3M CC56 2019 2019-03-12 SALIN 1.6114359151 #> 7559 2059 3M CC56 2019 2019-03-12 TKN -0.0408219945 #> 7560 2059 3M CC56 2019 2019-03-12 TN -0.0030045090 + #> 7561 2059 3M CC56 2019 2019-03-12 TP -1.0498221245 #> 7562 2059 3M CC56 2019 2019-03-12 TSS 0.6931471806 I #> 7563 2059 3M CC56 2019 2019-03-12 TURB 0.0000000000 #> 7564 2059 3M CC56 2019 2019-04-23 CHLAC 1.1939224685 #> 7565 2059 3M CC56 2019 2019-04-23 COND 9.4766200382 #> 7566 2059 3M CC56 2019 2019-04-23 DO 0.7929925155 #> 7567 2059 3M CC56 2019 2019-04-23 DOSAT 3.3286266888 #> 7568 2059 3M CC56 2019 2019-04-23 NO23 -3.5755507688 #> 7569 2059 3M CC56 2019 2019-04-23 SALIN 2.0175661380 #> 7570 2059 3M CC56 2019 2019-04-23 TKN -0.1984509387 #> 7571 2059 3M CC56 2019 2019-04-23 TN -0.1648746432 + #> 7572 2059 3M CC56 2019 2019-04-23 TP -1.1086626245 #> 7573 2059 3M CC56 2019 2019-04-23 TSS 0.6931471806 I #> 7574 2059 3M CC56 2019 2019-04-23 TURB 0.2623642645 #> 7575 2059 3M CC56 2019 2019-06-11 CHLAC 1.8245492921 I #> 7576 2059 3M CC56 2019 2019-06-11 COND 9.8113722636 #> 7577 2059 3M CC56 2019 2019-06-11 DO -1.0216512475 #> 7578 2059 3M CC56 2019 2019-06-11 DOSAT 1.6094379124 #> 7579 2059 3M CC56 2019 2019-06-11 NO23 -5.5214609179 U #> 7580 2059 3M CC56 2019 2019-06-11 SALIN 2.4221443281 #> 7581 2059 3M CC56 2019 2019-06-11 TKN 0.0000000000 #> 7582 2059 3M CC56 2019 2019-06-11 TN 0.0019980027 + #> 7583 2059 3M CC56 2019 2019-06-11 TP -1.0498221245 #> 7584 2059 3M CC56 2019 2019-06-11 TSS 1.3862943611 I #> 7585 2059 3M CC56 2019 2019-06-11 TURB 1.4350845253 A #> 7586 2059 3M CC56 2019 2019-08-13 CHLAC 0.4054651081 I #> 7587 2059 3M CC56 2019 2019-08-13 COND 6.6644090204 #> 7588 2059 3M CC56 2019 2019-08-13 DO -0.3285040670 #> 7589 2059 3M CC56 2019 2019-08-13 DOSAT 2.2192034841 #> 7590 2059 3M CC56 2019 2019-08-13 NO23 -2.7488721956 #> 7591 2059 3M CC56 2019 2019-08-13 SALIN -0.9675840263 #> 7592 2059 3M CC56 2019 2019-08-13 TKN 0.1823215568 #> 7593 2059 3M CC56 2019 2019-08-13 TN 0.2342812957 + #> 7594 2059 3M CC56 2019 2019-08-13 TP -1.3470736480 #> 7595 2059 3M CC56 2019 2019-08-13 TSS 0.6931471806 I #> 7596 2059 3M CC56 2019 2019-08-13 TURB 0.0000000000 #> 7597 2059 3M CC56 2019 2019-10-01 COND 8.7345600900 #> 7598 2059 3M CC56 2019 2019-10-01 DO 0.1310282624 #> 7599 2059 3M CC56 2019 2019-10-01 DOSAT 2.6532419646 #> 7600 2059 3M CC56 2019 2019-10-01 SALIN 1.2149127444 #> 7601 2059 3M CC56 2019 2019-11-04 COND 8.7934603611 #> 7602 2059 3M CC56 2019 2019-11-04 DO 0.0000000000 #> 7603 2059 3M CC56 2019 2019-11-04 DOSAT 2.5649493575 #> 7604 2059 3M CC56 2019 2019-11-04 SALIN 1.2809338455 #> 7605 2059 3M CC56 2019 2019-11-19 CHLAC 1.2809338455 #> 7606 2059 3M CC56 2019 2019-11-19 COND 9.6775902130 #> 7607 2059 3M CC56 2019 2019-11-19 DO 0.9631743178 #> 7608 2059 3M CC56 2019 2019-11-19 DOSAT 3.4078419244 #> 7609 2059 3M CC56 2019 2019-11-19 NO23 -2.9565115604 #> 7610 2059 3M CC56 2019 2019-11-19 SALIN 2.2364452905 #> 7611 2059 3M CC56 2019 2019-11-19 TKN -0.3011050928 #> 7612 2059 3M CC56 2019 2019-11-19 TN -0.2331938872 + #> 7613 2059 3M CC56 2019 2019-11-19 TP -1.2378743560 #> 7614 2059 3M CC56 2019 2019-11-19 TSS 1.0986122887 U #> 7615 2059 3M CC56 2019 2019-11-19 TURB 0.1823215568 #> 7616 2059 3M CC56 2020 2020-01-28 CHLAC 0.7419373447 U #> 7617 2059 3M CC56 2020 2020-01-28 COND 8.9703049530 #> 7618 2059 3M CC56 2020 2020-01-28 DO 1.0784095814 #> 7619 2059 3M CC56 2020 2020-01-28 DOSAT 3.4468078929 #> 7620 2059 3M CC56 2020 2020-01-28 NO23 -1.4271163556 #> 7621 2059 3M CC56 2020 2020-01-28 SALIN 1.4747630091 #> 7622 2059 3M CC56 2020 2020-01-28 TKN -0.2744368457 #> 7623 2059 3M CC56 2020 2020-01-28 TN 0.0000000000 + #> 7624 2059 3M CC56 2020 2020-01-28 TP -1.9661128564 #> 7625 2059 3M CC56 2020 2020-01-28 TSS 0.6931471806 U #> 7626 2059 3M CC56 2020 2020-01-28 TURB 0.0000000000 #> 7627 2059 3M CC56 2020 2020-03-05 CHLAC 0.6418538862 I #> 7628 2059 3M CC56 2020 2020-03-05 COND 10.0861423871 #> 7629 2059 3M CC56 2020 2020-03-05 DO 0.4700036292 #> 7630 2059 3M CC56 2020 2020-03-05 DOSAT 2.9957322736 #> 7631 2059 3M CC56 2020 2020-03-05 NO23 -2.9004220937 #> 7632 2059 3M CC56 2020 2020-03-05 SALIN 2.6817062258 #> 7633 2059 3M CC56 2020 2020-03-05 TKN -0.3424903089 #> 7634 2059 3M CC56 2020 2020-03-05 TN -0.2678794452 + #> 7635 2059 3M CC56 2020 2020-03-05 TP -1.2378743560 #> 7636 2059 3M CC56 2020 2020-03-05 TSS 1.3862943611 I #> 7637 2059 3M CC56 2020 2020-03-05 TURB 0.9932517730 #> 7638 2059 3M CC56 2020 2020-07-28 CHLAC 1.3083328197 #> 7639 2059 3M CC56 2020 2020-07-28 COND 9.3060141220 #> 7640 2059 3M CC56 2020 2020-07-28 DO -0.1053605157 #> 7641 2059 3M CC56 2020 2020-07-28 DOSAT 2.4849066498 #> 7642 2059 3M CC56 2020 2020-07-28 NO23 -3.6119184130 #> 7643 2059 3M CC56 2020 2020-07-28 SALIN 1.8261608959 #> 7644 2059 3M CC56 2020 2020-07-28 TKN 0.0000000000 #> 7645 2059 3M CC56 2020 2020-07-28 TN 0.0266419309 + #> 7646 2059 3M CC56 2020 2020-07-28 TP -0.6733445533 #> 7647 2059 3M CC56 2020 2020-07-28 TSS 0.6931471806 I #> 7648 2059 3M CC56 2020 2020-07-28 TURB 1.1939224685 #> 7649 2059 3M CC56 2020 2020-08-31 CHLAC 0.4700036292 U #> 7650 2059 3M CC56 2020 2020-08-31 COND 7.2751723195 #> 7651 2059 3M CC56 2020 2020-08-31 DO -1.2378743560 #> 7652 2059 3M CC56 2020 2020-08-31 DOSAT 1.3083328197 #> 7653 2059 3M CC56 2020 2020-08-31 NO23 -3.5404594490 #> 7654 2059 3M CC56 2020 2020-08-31 SALIN -0.3285040670 #> 7655 2059 3M CC56 2020 2020-08-31 TKN 0.3364722366 #> 7656 2059 3M CC56 2020 2020-08-31 TN 0.3569748989 + #> 7657 2059 3M CC56 2020 2020-08-31 TP -1.3862943611 #> 7658 2059 3M CC56 2020 2020-08-31 TSS 0.6931471806 U #> 7659 2059 3M CC56 2020 2020-08-31 TURB 0.4054651081 #> 7660 2059 3M CC56 2020 2020-09-16 CHLAC 0.4700036292 U #> 7661 2059 3M CC56 2020 2020-09-16 COND 6.8068293604 #> 7662 2059 3M CC56 2020 2020-09-16 DO 0.4054651081 #> 7663 2059 3M CC56 2020 2020-09-16 DOSAT 2.9444389792 #> 7664 2059 3M CC56 2020 2020-09-16 NO23 -2.6882475738 #> 7665 2059 3M CC56 2020 2020-09-16 SALIN -0.8209805521 #> 7666 2059 3M CC56 2020 2020-09-16 TKN -0.2107210313 #> 7667 2059 3M CC56 2020 2020-09-16 TN -0.1301086853 + #> 7668 2059 3M CC56 2020 2020-09-16 TP -1.3862943611 #> 7669 2059 3M CC56 2020 2020-09-16 TSS 0.6931471806 I #> 7670 2059 3M CC56 2020 2020-09-16 TURB 0.6418538862 #> 7671 2059 3M CC56 2018 2018-07-16 CHLAC 1.1314021115 #> 7672 2059 3M CC56 2018 2018-07-16 COLOR 5.9661467391 #> 7673 2059 3M CC56 2018 2018-07-16 COND 6.0969500550 #> 7674 2059 3M CC56 2018 2018-07-16 DO 0.1988508587 #> 7675 2059 3M CC56 2018 2018-07-16 DOSAT 2.7536607124 #> 7676 2059 3M CC56 2018 2018-07-16 NO23 -3.1700856607 #> 7677 2059 3M CC56 2018 2018-07-16 SALIN -1.6094379124 + #> 7678 2059 3M CC56 2018 2018-07-16 TKN 0.2623642645 #> 7679 2059 3M CC56 2018 2018-07-16 TN 0.2941610385 + #> 7680 2059 3M CC56 2018 2018-07-16 TP -1.4271163556 #> 7681 2059 3M CC56 2018 2018-07-16 TSS 0.6931471806 I #> 7682 2059 3M CC56 2018 2018-07-16 TURB -0.0512932944 #> 7683 2063 3M CC64 2013 2013-01-07 CHLAC 0.9932517730 #> 7684 2063 3M CC64 2013 2013-01-07 COLOR 2.6390573296 #> 7685 2063 3M CC64 2013 2013-01-07 DO 1.6292405397 #> 7686 2063 3M CC64 2013 2013-01-07 DOSAT 4.2209772132 + #> 7687 2063 3M CC64 2013 2013-01-07 NO23 -3.8167128256 #> 7688 2063 3M CC64 2013 2013-01-07 SALIN 3.3214324132 #> 7689 2063 3M CC64 2013 2013-01-07 TKN -0.6348782724 #> 7690 2063 3M CC64 2013 2013-01-07 TN -0.5942072327 + #> 7691 2063 3M CC64 2013 2013-01-07 TP -2.3025850930 #> 7692 2063 3M CC64 2013 2013-01-07 TURB 0.8329091229 #> 7693 2063 3M CC64 2013 2013-02-04 CHLAC 0.8329091229 #> 7694 2063 3M CC64 2013 2013-02-04 COLOR 2.4849066498 #> 7695 2063 3M CC64 2013 2013-02-04 DO 1.7404661748 #> 7696 2063 3M CC64 2013 2013-02-04 DOSAT 4.2794400459 + #> 7697 2063 3M CC64 2013 2013-02-04 NO23 -4.7105307016 I #> 7698 2063 3M CC64 2013 2013-02-04 SALIN 3.4011973817 #> 7699 2063 3M CC64 2013 2013-02-04 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NO23 -5.2983173665 I #> 7718 2063 3M CC64 2013 2013-04-01 SALIN 3.4499875458 #> 7719 2063 3M CC64 2013 2013-04-01 TKN -0.6161861394 #> 7720 2063 3M CC64 2013 2013-04-01 TN -0.6088060321 + #> 7721 2063 3M CC64 2013 2013-04-01 TP -2.4889146712 #> 7722 2063 3M CC64 2013 2013-04-01 TURB 0.5877866649 A #> 7723 2063 3M CC64 2013 2013-05-06 CHLAC 1.4816045409 #> 7724 2063 3M CC64 2013 2013-05-06 COLOR 2.8332133441 #> 7725 2063 3M CC64 2013 2013-05-06 DO 1.6292405397 #> 7726 2063 3M CC64 2013 2013-05-06 DOSAT 4.2822062994 + #> 7727 2063 3M CC64 2013 2013-05-06 NO23 -4.6051701860 #> 7728 2063 3M CC64 2013 2013-05-06 SALIN 3.4011973817 #> 7729 2063 3M CC64 2013 2013-05-06 TKN -0.6161861394 #> 7730 2063 3M CC64 2013 2013-05-06 TN -0.5978370008 + #> 7731 2063 3M CC64 2013 2013-05-06 TP -2.3025850930 #> 7732 2063 3M CC64 2013 2013-05-06 TURB 0.4700036292 #> 7733 2063 3M CC64 2013 2013-06-03 CHLAC 1.5686159179 #> 7734 2063 3M CC64 2013 2013-06-03 COLOR 2.2082744135 #> 7735 2063 3M CC64 2013 2013-06-03 DO 1.2237754316 #> 7736 2063 3M CC64 2013 2013-06-03 DOSAT 3.9569963711 + #> 7737 2063 3M CC64 2013 2013-06-03 NO23 -4.6051701860 #> 7738 2063 3M CC64 2013 2013-06-03 SALIN 3.4657359028 #> 7739 2063 3M CC64 2013 2013-06-03 TKN -0.4462871026 #> 7740 2063 3M CC64 2013 2013-06-03 TN -0.4307829161 + #> 7741 2063 3M CC64 2013 2013-06-03 TP -2.3025850930 #> 7742 2063 3M CC64 2013 2013-06-03 TURB 0.7884573604 #> 7743 2063 3M CC64 2013 2013-07-08 CHLAC 2.8903717579 #> 7744 2063 3M CC64 2013 2013-07-08 COLOR 4.1108738642 #> 7745 2063 3M CC64 2013 2013-07-08 DO 1.6486586256 #> 7746 2063 3M CC64 2013 2013-07-08 DOSAT 4.2556127098 + #> 7747 2063 3M CC64 2013 2013-07-08 NO23 -4.5098600062 #> 7748 2063 3M CC64 2013 2013-07-08 SALIN 1.6292405397 #> 7749 2063 3M CC64 2013 2013-07-08 TKN -0.2107210313 #> 7750 2063 3M CC64 2013 2013-07-08 TN -0.1972321695 + #> 7751 2063 3M CC64 2013 2013-07-08 TP -1.7719568419 #> 7752 2063 3M CC64 2013 2013-07-08 TURB 1.1314021115 #> 7753 2063 3M CC64 2013 2013-08-05 CHLAC 2.0281482473 #> 7754 2063 3M CC64 2013 2013-08-05 COLOR 4.8675344505 #> 7755 2063 3M CC64 2013 2013-08-05 DO 1.4350845253 #> 7756 2063 3M CC64 2013 2013-08-05 DOSAT 4.0673158898 + #> 7757 2063 3M CC64 2013 2013-08-05 NO23 -3.3242363405 #> 7758 2063 3M CC64 2013 2013-08-05 SALIN 2.0794415417 #> 7759 2063 3M CC64 2013 2013-08-05 TKN 0.0000000000 #> 7760 2063 3M CC64 2013 2013-08-05 TN 0.0353671438 + #> 7761 2063 3M CC64 2013 2013-08-05 TP -1.2729656758 #> 7762 2063 3M CC64 2013 2013-08-05 TURB 0.3364722366 #> 7763 2063 3M CC64 2013 2013-09-09 CHLAC 0.4700036292 I #> 7764 2063 3M CC64 2013 2013-09-09 COLOR 4.3820266347 A #> 7765 2063 3M CC64 2013 2013-09-09 DO 1.1939224685 #> 7766 2063 3M CC64 2013 2013-09-09 DOSAT 3.8394523126 + #> 7767 2063 3M CC64 2013 2013-09-09 SALIN 2.5336968140 #> 7768 2063 3M CC64 2013 2013-09-09 TN -0.1636960927 + #> 7769 2063 3M CC64 2013 2013-09-09 TURB -0.2231435513 #> 7770 2063 3M CC64 2013 2013-10-07 CHLAC 2.9444389792 #> 7771 2063 3M CC64 2013 2013-10-07 COLOR 4.3820266347 #> 7772 2063 3M CC64 2013 2013-10-07 DO 1.6094379124 #> 7773 2063 3M CC64 2013 2013-10-07 DOSAT 4.2355547308 + #> 7774 2063 3M CC64 2013 2013-10-07 SALIN 2.5176964726 #> 7775 2063 3M CC64 2013 2013-10-07 TN -0.1707883210 + #> 7776 2063 3M CC64 2013 2013-10-07 TURB 0.5877866649 #> 7777 2063 3M CC64 2013 2013-11-04 CHLAC 0.7419373447 #> 7778 2063 3M CC64 2013 2013-11-04 COLOR 3.6375861597 #> 7779 2063 3M CC64 2013 2013-11-04 DO 1.5475625087 #> 7780 2063 3M CC64 2013 2013-11-04 DOSAT 4.1125118662 + #> 7781 2063 3M CC64 2013 2013-11-04 NO23 -3.0576076773 #> 7782 2063 3M CC64 2013 2013-11-04 SALIN 2.9601050959 #> 7783 2063 3M CC64 2013 2013-11-04 TKN -0.4155154440 #> 7784 2063 3M CC64 2013 2013-11-04 TN -0.3467246131 + #> 7785 2063 3M CC64 2013 2013-11-04 TP -1.9661128564 #> 7786 2063 3M CC64 2013 2013-11-04 TURB 0.2623642645 #> 7787 2063 3M CC64 2013 2013-12-02 CHLAC 0.9555114450 #> 7788 2063 3M CC64 2013 2013-12-02 COLOR 2.6390573296 #> 7789 2063 3M CC64 2013 2013-12-02 DOSAT 4.3067641502 + #> 7790 2063 3M CC64 2013 2013-12-02 NO23 -3.5065578973 #> 7791 2063 3M CC64 2013 2013-12-02 SALIN 3.2958368660 #> 7792 2063 3M CC64 2013 2013-12-02 TKN -0.4004775666 #> 7793 2063 3M CC64 2013 2013-12-02 TN -0.3566749439 + #> 7794 2063 3M CC64 2013 2013-12-02 TP -2.3025850930 #> 7795 2063 3M CC64 2013 2013-12-02 TURB 0.2623642645 #> 7796 2063 3M CC64 2014 2014-01-06 CHLAC 1.3862943611 #> 7797 2063 3M CC64 2014 2014-01-06 COLOR 2.6390573296 #> 7798 2063 3M CC64 2014 2014-01-06 DO 1.7785053535 #> 7799 2063 3M CC64 2014 2014-01-06 DOSAT 4.3412046402 + #> 7800 2063 3M CC64 2014 2014-01-06 NO23 -5.1159958098 I #> 7801 2063 3M CC64 2014 2014-01-06 SALIN 3.3534067178 #> 7802 2063 3M CC64 2014 2014-01-06 TKN -0.8915981193 #> 7803 2063 3M CC64 2014 2014-01-06 TN -0.8818893052 + #> 7804 2063 3M CC64 2014 2014-01-06 TP -2.4889146712 #> 7805 2063 3M CC64 2014 2014-01-06 TURB 0.4700036292 #> 7806 2063 3M CC64 2014 2014-02-03 CHLAC 0.1823215568 I #> 7807 2063 3M CC64 2014 2014-02-03 COLOR 1.7227665977 I #> 7808 2063 3M CC64 2014 2014-02-03 DO 1.6992786164 #> 7809 2063 3M CC64 2014 2014-02-03 DOSAT 4.2527717988 + #> 7810 2063 3M CC64 2014 2014-02-03 NO23 -4.7105307016 I #> 7811 2063 3M CC64 2014 2014-02-03 SALIN 3.3432150991 #> 7812 2063 3M CC64 2014 2014-02-03 TKN -0.7339691751 #> 7813 2063 3M CC64 2014 2014-02-03 TN -0.7256703723 + #> 7814 2063 3M CC64 2014 2014-02-03 TP -2.4534079827 #> 7815 2063 3M CC64 2014 2014-02-03 TURB 0.1823215568 #> 7816 2063 3M CC64 2014 2014-03-03 CHLAC 1.3609765531 #> 7817 2063 3M CC64 2014 2014-03-03 COLOR 2.3025850930 #> 7818 2063 3M CC64 2014 2014-03-03 DO 1.7173950539 #> 7819 2063 3M CC64 2014 2014-03-03 DOSAT 4.3201512310 + #> 7820 2063 3M CC64 2014 2014-03-03 NO23 -5.2983173665 I #> 7821 2063 3M CC64 2014 2014-03-03 SALIN 3.3307749174 #> 7822 2063 3M CC64 2014 2014-03-03 TKN -0.6161861394 #> 7823 2063 3M CC64 2014 2014-03-03 TN -0.6088060321 + #> 7824 2063 3M CC64 2014 2014-03-03 TP -2.3644604967 #> 7825 2063 3M CC64 2014 2014-03-03 TURB 0.4054651081 #> 7826 2063 3M CC64 2014 2014-04-07 CHLAC 1.2237754316 #> 7827 2063 3M CC64 2014 2014-04-07 COLOR 2.6390573296 #> 7828 2063 3M CC64 2014 2014-04-07 DO 1.3244189574 #> 7829 2063 3M CC64 2014 2014-04-07 DOSAT 3.9759363312 + #> 7830 2063 3M CC64 2014 2014-04-07 NO23 -4.8283137373 I #> 7831 2063 3M CC64 2014 2014-04-07 SALIN 3.3246762438 #> 7832 2063 3M CC64 2014 2014-04-07 TKN -0.4942963218 #> 7833 2063 3M CC64 2014 2014-04-07 TN -0.4877603508 + #> 7834 2063 3M CC64 2014 2014-04-07 TP -2.3330443005 #> 7835 2063 3M CC64 2014 2014-04-07 TURB 0.8329091229 #> 7836 2063 3M CC64 2014 2014-05-05 CHLAC 1.3350010667 #> 7837 2063 3M CC64 2014 2014-05-05 COLOR 2.6390573296 #> 7838 2063 3M CC64 2014 2014-05-05 DO 1.4398351280 #> 7839 2063 3M CC64 2014 2014-05-05 DOSAT 4.0910056610 + #> 7840 2063 3M CC64 2014 2014-05-05 NO23 -4.9618451299 I #> 7841 2063 3M CC64 2014 2014-05-05 SALIN 3.3039519972 #> 7842 2063 3M CC64 2014 2014-05-05 TKN -0.4780358009 #> 7843 2063 3M CC64 2014 2014-05-05 TN -0.4716049106 + #> 7844 2063 3M CC64 2014 2014-05-05 TP -2.2072749132 #> 7845 2063 3M CC64 2014 2014-05-05 TURB 0.9555114450 #> 7846 2063 3M CC64 2014 2014-06-02 CHLAC 1.3083328197 #> 7847 2063 3M CC64 2014 2014-06-02 COLOR 2.3978952728 #> 7848 2063 3M CC64 2014 2014-06-02 DO 1.0116009117 #> 7849 2063 3M CC64 2014 2014-06-02 DOSAT 3.7111300630 + #> 7850 2063 3M CC64 2014 2014-06-02 NO23 -5.1159958098 I #> 7851 2063 3M CC64 2014 2014-06-02 SALIN 3.3347013904 #> 7852 2063 3M CC64 2014 2014-06-02 TKN -0.4462871026 #> 7853 2063 3M CC64 2014 2014-06-02 TN -0.4400565529 + #> 7854 2063 3M CC64 2014 2014-06-02 TP -2.0402208285 #> 7855 2063 3M CC64 2014 2014-06-02 TURB 0.6931471806 #> 7856 2063 3M CC64 2014 2014-07-07 CHLAC 1.7047480922 #> 7857 2063 3M CC64 2014 2014-07-07 COLOR 3.1354942159 #> 7858 2063 3M CC64 2014 2014-07-07 DOSAT 3.7495040759 + #> 7859 2063 3M CC64 2014 2014-07-07 NO23 -4.5098600062 #> 7860 2063 3M CC64 2014 2014-07-07 SALIN 3.2611687371 #> 7861 2063 3M CC64 2014 2014-07-07 TKN -0.1863295782 #> 7862 2063 3M CC64 2014 2014-07-07 TN -0.1731636190 + #> 7863 2063 3M CC64 2014 2014-07-07 TP -2.0402208285 #> 7864 2063 3M CC64 2014 2014-07-07 TURB 0.6931471806 #> 7865 2063 3M CC64 2014 2014-08-04 CHLAC 2.4849066498 #> 7866 2063 3M CC64 2014 2014-08-04 COLOR 3.7612001157 #> 7867 2063 3M CC64 2014 2014-08-04 DO 0.9932517730 #> 7868 2063 3M CC64 2014 2014-08-04 DOSAT 3.6863763239 + #> 7869 2063 3M CC64 2014 2014-08-04 NO23 -4.8283137373 I #> 7870 2063 3M CC64 2014 2014-08-04 SALIN 2.9439125248 #> 7871 2063 3M CC64 2014 2014-08-04 TKN -0.1743533871 #> 7872 2063 3M CC64 2014 2014-08-04 TN -0.1696027844 + #> 7873 2063 3M CC64 2014 2014-08-04 TP -1.6607312068 #> 7874 2063 3M CC64 2014 2014-08-04 TURB 1.0296194172 #> 7875 2063 3M CC64 2014 2014-09-08 CHLAC 0.9162907319 #> 7876 2063 3M CC64 2014 2014-09-08 COLOR 3.4011973817 #> 7877 2063 3M CC64 2014 2014-09-08 DO 0.7178397932 #> 7878 2063 3M CC64 2014 2014-09-08 DOSAT 3.3911470458 + #> 7879 2063 3M CC64 2014 2014-09-08 NO23 -4.1351665567 #> 7880 2063 3M CC64 2014 2014-09-08 SALIN 2.9242362718 #> 7881 2063 3M CC64 2014 2014-09-08 TKN -0.2231435513 #> 7882 2063 3M CC64 2014 2014-09-08 TN -0.2033409240 + #> 7883 2063 3M CC64 2014 2014-09-08 TP -1.9661128564 #> 7884 2063 3M CC64 2014 2014-09-08 TURB -0.0512932944 #> 7885 2063 3M CC64 2014 2014-10-06 CHLAC 1.5040773968 #> 7886 2063 3M CC64 2014 2014-10-06 COLOR 4.5951198501 #> 7887 2063 3M CC64 2014 2014-10-06 DO 0.9162907319 #> 7888 2063 3M CC64 2014 2014-10-06 DOSAT 3.4781584228 + #> 7889 2063 3M CC64 2014 2014-10-06 NO23 -3.3813947544 #> 7890 2063 3M CC64 2014 2014-10-06 SALIN 2.0819384219 #> 7891 2063 3M CC64 2014 2014-10-06 TKN -0.0408219945 #> 7892 2063 3M CC64 2014 2014-10-06 TN -0.0060180723 + #> 7893 2063 3M CC64 2014 2014-10-06 TP -1.8325814637 #> 7894 2063 3M CC64 2014 2014-10-06 TURB 0.4054651081 #> 7895 2063 3M CC64 2014 2014-11-03 CHLAC 0.9162907319 #> 7896 2063 3M CC64 2014 2014-11-03 COLOR 3.7841896339 #> 7897 2063 3M CC64 2014 2014-11-03 DO 1.5686159179 #> 7898 2063 3M CC64 2014 2014-11-03 DOSAT 4.0826093060 + #> 7899 2063 3M CC64 2014 2014-11-03 NO23 -3.5065578973 #> 7900 2063 3M CC64 2014 2014-11-03 SALIN 2.9423314968 #> 7901 2063 3M CC64 2014 2014-11-03 TKN -0.3285040670 #> 7902 2063 3M CC64 2014 2014-11-03 TN -0.2876820725 + #> 7903 2063 3M CC64 2014 2014-11-03 TP -1.9661128564 #> 7904 2063 3M CC64 2014 2014-11-03 TURB 0.5306282511 #> 7905 2063 3M CC64 2014 2014-12-01 CHLAC 0.4700036292 I #> 7906 2063 3M CC64 2014 2014-12-01 COLOR 3.4011973817 #> 7907 2063 3M CC64 2014 2014-12-01 DO 1.6956156087 #> 7908 2063 3M CC64 2014 2014-12-01 DOSAT 4.1941898972 + #> 7909 2063 3M CC64 2014 2014-12-01 NO23 -2.7181005370 #> 7910 2063 3M CC64 2014 2014-12-01 SALIN 3.0449985149 #> 7911 2063 3M CC64 2014 2014-12-01 TKN -0.3566749439 #> 7912 2063 3M CC64 2014 2014-12-01 TN -0.2665731092 + #> 7913 2063 3M CC64 2014 2014-12-01 TP -2.3025850930 #> 7914 2063 3M CC64 2014 2014-12-01 TURB 0.4700036292 #> 7915 2063 3M CC64 2015 2015-01-05 CHLAC 0.7884573604 A #> 7916 2063 3M CC64 2015 2015-01-05 COLOR 2.9444389792 #> 7917 2063 3M CC64 2015 2015-01-05 NO23 -2.8824035882 #> 7918 2063 3M CC64 2015 2015-01-05 SALIN 3.2592497190 #> 7919 2063 3M CC64 2015 2015-01-05 TKN -0.5621189182 #> 7920 2063 3M CC64 2015 2015-01-05 TN -0.4684049079 + #> 7921 2063 3M CC64 2015 2015-01-05 TP -2.3025850930 #> 7922 2063 3M CC64 2015 2015-01-05 TURB 0.6931471806 #> 7923 2063 3M CC64 2015 2015-02-02 CHLAC 0.2623642645 I #> 7924 2063 3M CC64 2015 2015-02-02 COLOR 2.3025850930 #> 7925 2063 3M CC64 2015 2015-02-02 DOSAT 4.3932138241 + #> 7926 2063 3M CC64 2015 2015-02-02 NO23 -4.3428059215 #> 7927 2063 3M CC64 2015 2015-02-02 SALIN 3.3214324132 #> 7928 2063 3M CC64 2015 2015-02-02 TKN -0.9942522733 I #> 7929 2063 3M CC64 2015 2015-02-02 TN -1.7544636845 + #> 7930 2063 3M CC64 2015 2015-02-02 TP -2.4534079827 #> 7931 2063 3M CC64 2015 2015-02-02 TURB 0.7884573604 A #> 7932 2063 3M CC64 2015 2015-03-02 CHLAC 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2015-06-01 TN -0.5551258827 + #> 7969 2063 3M CC64 2015 2015-06-01 TP -2.3025850930 #> 7970 2063 3M CC64 2015 2015-06-01 TURB 0.4700036292 #> 7971 2063 3M CC64 2015 2015-08-03 CHLAC 2.2407096893 #> 7972 2063 3M CC64 2015 2015-08-03 COLOR 4.1588830834 #> 7973 2063 3M CC64 2015 2015-08-03 DO 0.7654678421 #> 7974 2063 3M CC64 2015 2015-08-03 DOSAT 3.4045251718 + #> 7975 2063 3M CC64 2015 2015-08-03 NO23 -4.6051701860 I #> 7976 2063 3M CC64 2015 2015-08-03 SALIN 2.8039662579 #> 7977 2063 3M CC64 2015 2015-08-03 TKN -0.0512932944 #> 7978 2063 3M CC64 2015 2015-08-03 TN -0.0470916075 + #> 7979 2063 3M CC64 2015 2015-08-03 TP -2.0402208285 #> 7980 2063 3M CC64 2015 2015-08-03 TURB 0.5877866649 #> 7981 2063 3M CC64 2015 2015-09-08 CHLAC 1.3609765531 #> 7982 2063 3M CC64 2015 2015-09-08 COLOR 4.5432947823 #> 7983 2063 3M CC64 2015 2015-09-08 NO23 -3.6888794541 #> 7984 2063 3M CC64 2015 2015-09-08 SALIN 1.3584091576 #> 7985 2063 3M CC64 2015 2015-09-08 TKN -0.1743533871 #> 7986 2063 3M CC64 2015 2015-09-08 TN -0.1450257721 + #> 7987 2063 3M CC64 2015 2015-09-08 TP -2.2072749132 #> 7988 2063 3M CC64 2015 2015-09-08 TURB 0.5306282511 #> 7989 2063 3M CC64 2015 2015-10-05 CHLAC 1.5892352051 #> 7990 2063 3M CC64 2015 2015-10-05 COLOR 4.5643481915 #> 7991 2063 3M CC64 2015 2015-10-05 DO 1.1085626195 #> 7992 2063 3M CC64 2015 2015-10-05 DOSAT 3.6888794541 + #> 7993 2063 3M CC64 2015 2015-10-05 NO23 -3.3524072175 #> 7994 2063 3M CC64 2015 2015-10-05 SALIN 2.4069451083 #> 7995 2063 3M CC64 2015 2015-10-05 TKN -0.1984509387 #> 7996 2063 3M CC64 2015 2015-10-05 TN -0.1566538100 + #> 7997 2063 3M CC64 2015 2015-10-05 TP -1.5606477483 #> 7998 2063 3M CC64 2015 2015-10-05 TURB 0.3364722366 A #> 7999 2063 3M CC64 2015 2015-12-07 CHLAC 0.9555114450 #> 8000 2063 3M CC64 2015 2015-12-07 COLOR 3.4965075615 #> 8001 2063 3M CC64 2015 2015-12-07 DO 1.1314021115 #> 8002 2063 3M CC64 2015 2015-12-07 DOSAT 3.6988297850 + #> 8003 2063 3M CC64 2015 2015-12-07 NO23 -2.8824035882 #> 8004 2063 3M CC64 2015 2015-12-07 SALIN 3.0540011817 #> 8005 2063 3M CC64 2015 2015-12-07 TKN -0.4780358009 #> 8006 2063 3M CC64 2015 2015-12-07 TN -0.3915622029 + #> 8007 2063 3M CC64 2015 2015-12-07 TP -2.2072749132 #> 8008 2063 3M CC64 2015 2015-12-07 TURB 0.7884573604 #> 8009 2063 3M CC64 2016 2016-01-04 CHLAC 0.4700036292 I #> 8010 2063 3M CC64 2016 2016-01-04 COLOR 3.1780538303 #> 8011 2063 3M CC64 2016 2016-01-04 DO 1.1631508098 #> 8012 2063 3M CC64 2016 2016-01-04 DOSAT 3.7281001673 + #> 8013 2063 3M CC64 2016 2016-01-04 NO23 -2.7030626596 #> 8014 2063 3M CC64 2016 2016-01-04 SALIN 3.1112906142 #> 8015 2063 3M CC64 2016 2016-01-04 TKN -0.3011050928 #> 8016 2063 3M CC64 2016 2016-01-04 TN -0.2144316107 + #> 8017 2063 3M CC64 2016 2016-01-04 TP -2.0402208285 #> 8018 2063 3M CC64 2016 2016-01-04 TURB 0.9162907319 #> 8019 2063 3M CC64 2016 2016-02-01 COLOR 4.1896547420 A #> 8020 2063 3M CC64 2016 2016-02-01 DOSAT 4.5053498507 + #> 8021 2063 3M CC64 2016 2016-02-01 NO23 -4.1997050779 #> 8022 2063 3M CC64 2016 2016-02-01 SALIN 1.9810014689 #> 8023 2063 3M CC64 2016 2016-02-01 TKN -0.5447271754 #> 8024 2063 3M CC64 2016 2016-02-01 TN -0.5191938734 + #> 8025 2063 3M CC64 2016 2016-02-01 TP -2.8473122684 #> 8026 2063 3M CC64 2016 2016-02-01 TURB 0.5877866649 #> 8027 2063 3M CC64 2016 2016-03-07 CHLAC 0.6418538862 I #> 8028 2063 3M CC64 2016 2016-03-07 COLOR 3.7841896339 #> 8029 2063 3M CC64 2016 2016-03-07 NO23 -4.1997050779 #> 8030 2063 3M CC64 2016 2016-03-07 SALIN 2.6159349122 #> 8031 2063 3M CC64 2016 2016-03-07 TKN -0.2231435513 #> 8032 2063 3M CC64 2016 2016-03-07 TN -0.2045671657 + #> 8033 2063 3M CC64 2016 2016-03-07 TP -2.3538783874 #> 8034 2063 3M CC64 2016 2016-03-07 TURB 0.4700036292 #> 8035 2063 3M CC64 2016 2016-04-04 CHLAC 1.2237754316 #> 8036 2063 3M CC64 2016 2016-04-04 COLOR 3.3322045102 A #> 8037 2063 3M CC64 2016 2016-04-04 DO 1.6094379124 #> 8038 2063 3M CC64 2016 2016-04-04 DOSAT 4.2061840440 + #> 8039 2063 3M CC64 2016 2016-04-04 NO23 -3.7297014486 #> 8040 2063 3M CC64 2016 2016-04-04 SALIN 2.9236990707 #> 8041 2063 3M CC64 2016 2016-04-04 TN -0.3092462504 + #> 8042 2063 3M CC64 2016 2016-04-04 TP -2.2072749132 #> 8043 2063 3M CC64 2016 2016-04-04 TURB 0.7419373447 #> 8044 2063 3M CC64 2016 2016-05-02 CHLAC 0.8754687374 #> 8045 2063 3M CC64 2016 2016-05-02 COLOR 3.1780538303 #> 8046 2063 3M CC64 2016 2016-05-02 DO 1.1631508098 #> 8047 2063 3M CC64 2016 2016-05-02 DOSAT 3.8394523126 + #> 8048 2063 3M CC64 2016 2016-05-02 NO23 -4.5098600062 #> 8049 2063 3M CC64 2016 2016-05-02 SALIN 3.1428583384 #> 8050 2063 3M CC64 2016 2016-05-02 TKN -0.5276327421 #> 8051 2063 3M CC64 2016 2016-05-02 TN -0.5091603444 + #> 8052 2063 3M CC64 2016 2016-05-02 TP -2.3025850930 #> 8053 2063 3M CC64 2016 2016-05-02 TURB 0.6931471806 #> 8054 2063 3M CC64 2016 2016-06-06 NO23 -4.6051701860 I #> 8055 2063 3M CC64 2016 2016-06-06 SALIN 3.2120525995 #> 8056 2063 3M CC64 2016 2016-06-06 TKN -0.4462871026 #> 8057 2063 3M CC64 2016 2016-06-06 TN -0.4400565529 + #> 8058 2063 3M CC64 2016 2016-06-06 TP -2.1202635362 #> 8059 2063 3M CC64 2016 2016-07-05 CHLAC 1.0296194172 #> 8060 2063 3M CC64 2016 2016-07-05 COLOR 3.9702919136 #> 8061 2063 3M CC64 2016 2016-07-05 DO 0.5596157879 #> 8062 2063 3M CC64 2016 2016-07-05 DOSAT 3.2503744919 + #> 8063 2063 3M CC64 2016 2016-07-05 NO23 -5.5214609179 U #> 8064 2063 3M CC64 2016 2016-07-05 SALIN 2.8864752876 #> 8065 2063 3M CC64 2016 2016-07-05 TKN -0.2484613593 #> 8066 2063 3M CC64 2016 2016-07-05 TN -0.2459005384 + #> 8067 2063 3M CC64 2016 2016-07-05 TP -1.6607312068 #> 8068 2063 3M CC64 2016 2016-07-05 TURB 0.6418538862 #> 8069 2063 3M CC64 2016 2016-08-01 CHLAC 0.7884573604 #> 8070 2063 3M CC64 2016 2016-08-01 COLOR 4.0073331852 A #> 8071 2063 3M CC64 2016 2016-08-01 DO 0.9669838462 #> 8072 2063 3M CC64 2016 2016-08-01 DOSAT 3.6428355156 + #> 8073 2063 3M CC64 2016 2016-08-01 NO23 -4.3428059215 #> 8074 2063 3M CC64 2016 2016-08-01 SALIN 2.6232182656 #> 8075 2063 3M CC64 2016 2016-08-01 TKN -0.1625189295 #> 8076 2063 3M CC64 2016 2016-08-01 TN -0.1473405879 + #> 8077 2063 3M CC64 2016 2016-08-01 TP -1.9661128564 #> 8078 2063 3M CC64 2016 2016-08-01 TURB 0.3364722366 #> 8079 2063 3M CC64 2016 2016-10-03 CHLAC 1.3350010667 #> 8080 2063 3M CC64 2016 2016-10-03 COLOR 3.9702919136 #> 8081 2063 3M CC64 2016 2016-10-03 DO 0.7178397932 #> 8082 2063 3M CC64 2016 2016-10-03 DOSAT 3.3568971228 + #> 8083 2063 3M CC64 2016 2016-10-03 NO23 -4.1351665567 #> 8084 2063 3M CC64 2016 2016-10-03 SALIN 2.5892666651 #> 8085 2063 3M CC64 2016 2016-10-03 TKN -0.4620354596 #> 8086 2063 3M CC64 2016 2016-10-03 TN -0.4369557752 + #> 8087 2063 3M CC64 2016 2016-10-03 TP -1.8325814637 #> 8088 2063 3M CC64 2016 2016-10-03 TURB 0.1823215568 #> 8089 2063 3M CC64 2016 2016-11-07 CHLAC 0.8754687374 #> 8090 2063 3M CC64 2016 2016-11-07 COLOR 2.8332133441 A #> 8091 2063 3M CC64 2016 2016-11-07 DO 1.3402504226 #> 8092 2063 3M CC64 2016 2016-11-07 DOSAT 3.9473901493 + #> 8093 2063 3M CC64 2016 2016-11-07 NO23 -4.7105307016 I #> 8094 2063 3M CC64 2016 2016-11-07 SALIN 3.3178157727 #> 8095 2063 3M CC64 2016 2016-11-07 TKN -0.4155154440 #> 8096 2063 3M CC64 2016 2016-11-07 TN -0.4094731295 + #> 8097 2063 3M CC64 2016 2016-11-07 TP -2.3330443005 #> 8098 2063 3M CC64 2016 2016-11-07 TURB 0.6418538862 #> 8099 2063 3M CC64 2016 2016-12-05 CHLAC 2.6390573296 #> 8100 2063 3M CC64 2016 2016-12-05 COLOR 2.7080502011 #> 8101 2063 3M CC64 2016 2016-12-05 DO 1.6094379124 #> 8102 2063 3M CC64 2016 2016-12-05 DOSAT 4.2165621949 + #> 8103 2063 3M CC64 2016 2016-12-05 NO23 -5.5214609179 U #> 8104 2063 3M CC64 2016 2016-12-05 SALIN 3.3792925463 #> 8105 2063 3M CC64 2016 2016-12-05 TKN -0.3285040670 #> 8106 2063 3M CC64 2016 2016-12-05 TN -0.3257301401 + #> 8107 2063 3M CC64 2016 2016-12-05 TP -1.7147984281 #> 8108 2063 3M CC64 2016 2016-12-05 TURB 0.8329091229 #> 8109 2063 3M CC64 2017 2017-01-03 CHLAC 0.7419373447 #> 8110 2063 3M CC64 2017 2017-01-03 COLOR 2.1860512767 #> 8111 2063 3M CC64 2017 2017-01-03 DO 1.6292405397 #> 8112 2063 3M CC64 2017 2017-01-03 DOSAT 4.2370008626 + #> 8113 2063 3M CC64 2017 2017-01-03 NO23 -5.5214609179 U #> 8114 2063 3M CC64 2017 2017-01-03 SALIN 3.3911470458 #> 8115 2063 3M CC64 2017 2017-01-03 TKN -0.6733445533 #> 8116 2063 3M CC64 2017 2017-01-03 TN -0.6694306539 + #> 8117 2063 3M CC64 2017 2017-01-03 TP -2.3751557858 #> 8118 2063 3M CC64 2017 2017-01-03 TURB 0.4700036292 #> 8119 2063 3M CC64 2017 2017-02-06 CHLAC 1.3083328197 #> 8120 2063 3M CC64 2017 2017-02-06 COLOR 2.2300144002 #> 8121 2063 3M CC64 2017 2017-02-06 DO 1.6770965609 #> 8122 2063 3M CC64 2017 2017-02-06 DOSAT 4.2654928184 + #> 8123 2063 3M CC64 2017 2017-02-06 NO23 -3.3242363405 #> 8124 2063 3M CC64 2017 2017-02-06 SALIN 3.3965197921 #> 8125 2063 3M CC64 2017 2017-02-06 TKN -0.3566749439 #> 8126 2063 3M CC64 2017 2017-02-06 TN -0.3065251603 + #> 8127 2063 3M CC64 2017 2017-02-06 TP -2.4418471603 #> 8128 2063 3M CC64 2017 2017-02-06 TURB 0.9555114450 #> 8129 2063 3M CC64 2017 2017-03-06 CHLAC 1.2237754316 #> 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#> 8148 2063 3M CC64 2017 2017-04-03 TURB 0.8754687374 #> 8149 2063 3M CC64 2017 2017-05-01 CHLAC 1.0296194172 #> 8150 2063 3M CC64 2017 2017-05-01 COLOR 2.6390573296 #> 8151 2063 3M CC64 2017 2017-05-01 DO 1.3480731483 #> 8152 2063 3M CC64 2017 2017-05-01 DOSAT 4.0604430105 + #> 8153 2063 3M CC64 2017 2017-05-01 NO23 -5.5214609179 U #> 8154 2063 3M CC64 2017 2017-05-01 SALIN 3.5377658244 #> 8155 2063 3M CC64 2017 2017-05-01 TKN -0.2876820725 #> 8156 2063 3M CC64 2017 2017-05-01 TN -0.2850189550 + #> 8157 2063 3M CC64 2017 2017-05-01 TP -2.6736487744 #> 8158 2063 3M CC64 2017 2017-05-01 TURB 0.7419373447 #> 8159 2063 3M CC64 2017 2017-06-05 CHLAC 1.3862943611 A #> 8160 2063 3M CC64 2017 2017-06-05 COLOR 2.7080502011 #> 8161 2063 3M CC64 2017 2017-06-05 DO 2.1294214740 #> 8162 2063 3M CC64 2017 2017-06-05 DOSAT 4.8835592115 + #> 8163 2063 3M CC64 2017 2017-06-05 NO23 -4.5098600062 #> 8164 2063 3M CC64 2017 2017-06-05 SALIN 3.5322256441 #> 8165 2063 3M CC64 2017 2017-06-05 TKN -0.3147107448 #> 8166 2063 3M CC64 2017 2017-06-05 TN -0.2997546537 + #> 8167 2063 3M CC64 2017 2017-06-05 TP -2.5639498571 #> 8168 2063 3M CC64 2017 2017-06-05 TURB 0.8754687374 #> 8169 2063 3M CC64 2017 2017-07-10 CHLAC 2.2512917986 #> 8170 2063 3M CC64 2017 2017-07-10 COLOR 4.4426512565 #> 8171 2063 3M CC64 2017 2017-07-10 DO 0.8458682676 #> 8172 2063 3M CC64 2017 2017-07-10 DOSAT 3.5292973843 + #> 8173 2063 3M CC64 2017 2017-07-10 NO23 -4.6051701860 I #> 8174 2063 3M CC64 2017 2017-07-10 SALIN 2.7408400239 #> 8175 2063 3M CC64 2017 2017-07-10 TKN 0.0000000000 #> 8176 2063 3M CC64 2017 2017-07-10 TN 0.0039920213 + #> 8177 2063 3M CC64 2017 2017-07-10 TP -1.5141277326 #> 8178 2063 3M CC64 2017 2017-07-10 TURB 0.4054651081 #> 8179 2063 3M CC64 2017 2017-08-07 CHLAC 1.5892352051 #> 8180 2063 3M CC64 2017 2017-08-07 COLOR 4.5747109785 A #> 8181 2063 3M CC64 2017 2017-08-07 DO 0.4121096508 #> 8182 2063 3M CC64 2017 2017-08-07 DOSAT 3.0349529867 + #> 8183 2063 3M CC64 2017 2017-08-07 NO23 -3.7297014486 #> 8184 2063 3M CC64 2017 2017-08-07 SALIN 2.0693912058 #> 8185 2063 3M CC64 2017 2017-08-07 TKN -0.0202027073 #> 8186 2063 3M CC64 2017 2017-08-07 TN 0.0039920213 + #> 8187 2063 3M CC64 2017 2017-08-07 TP -1.6607312068 #> 8188 2063 3M CC64 2017 2017-08-07 TURB 0.6931471806 #> 8189 2063 3M CC64 2017 2017-09-05 CHLAC 1.6094379124 #> 8190 2063 3M CC64 2017 2017-09-05 COLOR 4.7874917428 #> 8191 2063 3M CC64 2017 2017-09-05 DO 0.8586616190 #> 8192 2063 3M CC64 2017 2017-09-05 DOSAT 3.4404180948 + #> 8193 2063 3M CC64 2017 2017-09-05 NO23 -3.0159349809 #> 8194 2063 3M CC64 2017 2017-09-05 SALIN 0.9001613499 #> 8195 2063 3M CC64 2017 2017-09-05 TKN -0.1508228897 #> 8196 2063 3M CC64 2017 2017-09-05 TN -0.0954101848 + #> 8197 2063 3M CC64 2017 2017-09-05 TP -2.0402208285 #> 8198 2063 3M CC64 2017 2017-09-05 TURB 0.5877866649 #> 8199 2063 3M CC64 2017 2017-10-02 CHLAC 1.3083328197 #> 8200 2063 3M CC64 2017 2017-10-02 COLOR 4.4998096703 #> 8201 2063 3M CC64 2017 2017-10-02 NO23 -3.1465551633 #> 8202 2063 3M CC64 2017 2017-10-02 TKN -0.9675840263 #> 8203 2063 3M CC64 2017 2017-10-02 TN -0.8603830999 + #> 8204 2063 3M CC64 2017 2017-10-02 TP -1.6094379124 #> 8205 2063 3M CC64 2017 2017-10-02 TURB 0.3364722366 #> 8206 2063 3M CC64 2017 2017-11-06 CHLAC 0.7419373447 #> 8207 2063 3M CC64 2017 2017-11-06 COLOR 3.5835189385 #> 8208 2063 3M CC64 2017 2017-11-06 DO 2.0014800002 #> 8209 2063 3M CC64 2017 2017-11-06 DOSAT 4.5890408041 + #> 8210 2063 3M CC64 2017 2017-11-06 NO23 -3.4420193762 #> 8211 2063 3M CC64 2017 2017-11-06 SALIN 3.0864866368 #> 8212 2063 3M CC64 2017 2017-11-06 TKN -0.5798184953 #> 8213 2063 3M CC64 2017 2017-11-06 TN -0.5242486441 + #> 8214 2063 3M CC64 2017 2017-11-06 TP -1.8971199849 #> 8215 2063 3M CC64 2017 2017-11-06 TURB 0.3364722366 #> 8216 2063 3M CC64 2017 2017-11-06 CHLAC 0.8754687374 #> 8217 2063 3M CC64 2017 2017-11-06 COLOR 3.5553480615 #> 8218 2063 3M CC64 2017 2017-11-06 NO23 -3.4112477175 #> 8219 2063 3M CC64 2017 2017-11-06 TKN -0.6161861394 #> 8220 2063 3M CC64 2017 2017-11-06 TN -0.5568695623 + #> 8221 2063 3M CC64 2017 2017-11-06 TP -1.8971199849 #> 8222 2063 3M CC64 2017 2017-11-06 TURB 0.1823215568 #> 8223 2063 3M CC64 2017 2017-12-04 CHLAC 0.9162907319 #> 8224 2063 3M CC64 2017 2017-12-04 COLOR 3.1780538303 #> 8225 2063 3M CC64 2017 2017-12-04 DO 1.5644405465 #> 8226 2063 3M CC64 2017 2017-12-04 DOSAT 4.1287459889 #> 8227 2063 3M CC64 2017 2017-12-04 NO23 -4.5098600062 #> 8228 2063 3M CC64 2017 2017-12-04 SALIN 3.3403852423 #> 8229 2063 3M CC64 2017 2017-12-04 TKN -0.5276327421 #> 8230 2063 3M CC64 2017 2017-12-04 TN -0.5091603444 + #> 8231 2063 3M CC64 2017 2017-12-04 TP -2.2072749132 #> 8232 2063 3M CC64 2017 2017-12-04 TURB 0.3364722366 #> 8233 2063 3M CC64 2018 2018-01-02 CHLAC 2.7725887222 #> 8234 2063 3M CC64 2018 2018-01-02 COLOR 3.0910424534 #> 8235 2063 3M CC64 2018 2018-01-02 DOSAT 4.0360089852 + #> 8236 2063 3M CC64 2018 2018-01-02 NO23 -5.5214609179 U #> 8237 2063 3M CC64 2018 2018-01-02 SALIN 3.2657594108 #> 8238 2063 3M CC64 2018 2018-01-02 TKN -0.3147107448 #> 8239 2063 3M CC64 2018 2018-01-02 TN -0.3119747650 + #> 8240 2063 3M CC64 2018 2018-01-02 TP -1.6607312068 #> 8241 2063 3M CC64 2018 2018-01-02 TURB 2.3978952728 #> 8242 2063 3M CC64 2018 2018-03-05 CHLAC 0.5306282511 I #> 8243 2063 3M CC64 2018 2018-03-05 COLOR 2.6390573296 #> 8244 2063 3M CC64 2018 2018-03-05 DOSAT 4.2416144810 #> 8245 2063 3M CC64 2018 2018-03-05 NO23 -5.5214609179 I #> 8246 2063 3M CC64 2018 2018-03-05 SALIN 3.3467411959 #> 8247 2063 3M CC64 2018 2018-03-05 TKN -0.5621189182 #> 8248 2063 3M CC64 2018 2018-03-05 TN -0.5551258827 + #> 8249 2063 3M CC64 2018 2018-03-05 TP -2.1202635362 #> 8250 2063 3M CC64 2018 2018-03-05 TURB 0.4700036292 #> 8251 2063 3M CC64 2018 2018-04-02 CHLAC 0.7884573604 #> 8252 2063 3M CC64 2018 2018-04-02 COLOR 2.3978952728 #> 8253 2063 3M CC64 2018 2018-04-02 DO 1.5040773968 #> 8254 2063 3M CC64 2018 2018-04-02 DOSAT 3.4307561839 #> 8255 2063 3M CC64 2018 2018-04-02 NO23 -4.9618451299 I #> 8256 2063 3M CC64 2018 2018-04-02 SALIN 3.4330189940 #> 8257 2063 3M CC64 2018 2018-04-02 TKN -0.5798184953 #> 8258 2063 3M CC64 2018 2018-04-02 TN -0.5727010275 + #> 8259 2063 3M CC64 2018 2018-04-02 TP -2.2072749132 #> 8260 2063 3M CC64 2018 2018-04-02 TURB 0.7419373447 #> 8261 2063 3M CC64 2018 2018-05-07 CHLAC 1.4350845253 #> 8262 2063 3M CC64 2018 2018-05-07 COLOR 2.5649493575 #> 8263 2063 3M CC64 2018 2018-05-07 DO 1.3962446920 #> 8264 2063 3M CC64 2018 2018-05-07 DOSAT 4.0842942264 #> 8265 2063 3M CC64 2018 2018-05-07 NO23 -5.1159958098 I #> 8266 2063 3M CC64 2018 2018-05-07 SALIN 3.4388142452 #> 8267 2063 3M CC64 2018 2018-05-07 TKN -0.3424903089 #> 8268 2063 3M CC64 2018 2018-05-07 TN -0.3368723166 + #> 8269 2063 3M CC64 2018 2018-05-07 TP -2.0402208285 #> 8270 2063 3M CC64 2018 2018-05-07 TURB 1.0986122887 #> 8271 2063 3M CC64 2018 2018-07-09 CHLAC 0.9555114450 #> 8272 2063 3M CC64 2018 2018-07-09 COLOR 4.5747109785 #> 8273 2063 3M CC64 2018 2018-07-09 DO 0.6312717768 #> 8274 2063 3M CC64 2018 2018-07-09 DOSAT 3.2308043957 #> 8275 2063 3M CC64 2018 2018-07-09 NO23 -3.6119184130 #> 8276 2063 3M CC64 2018 2018-07-09 SALIN 1.8640801308 #> 8277 2063 3M CC64 2018 2018-07-09 TKN 0.0000000000 #> 8278 2063 3M CC64 2018 2018-07-09 TN 0.0266419309 + #> 8279 2063 3M CC64 2018 2018-07-09 TP -2.3025850930 #> 8280 2063 3M CC64 2018 2018-07-09 TURB 0.1823215568 #> 8281 2063 3M CC64 2018 2018-08-06 CHLAC 1.0986122887 #> 8282 2063 3M CC64 2018 2018-08-06 COLOR 4.5951198501 #> 8283 2063 3M CC64 2018 2018-08-06 DO 0.8796267475 #> 8284 2063 3M CC64 2018 2018-08-06 DOSAT 3.4339872045 #> 8285 2063 3M CC64 2018 2018-08-06 NO23 -3.4737680745 #> 8286 2063 3M CC64 2018 2018-08-06 SALIN 1.6448050563 #> 8287 2063 3M CC64 2018 2018-08-06 TKN -0.1508228897 #> 8288 2063 3M CC64 2018 2018-08-06 TN -0.1154108515 + #> 8289 2063 3M CC64 2018 2018-08-06 TP -2.3227878003 #> 8290 2063 3M CC64 2018 2018-08-06 TURB 0.5877866649 #> 8291 2063 3M CC64 2019 2019-02-04 CHLAC 1.1314021115 #> 8292 2063 3M CC64 2019 2019-02-04 COLOR 3.0910424534 #> 8293 2063 3M CC64 2019 2019-02-04 DO 1.8764069433 #> 8294 2063 3M CC64 2019 2019-02-04 DOSAT 4.4200447019 #> 8295 2063 3M CC64 2019 2019-02-04 NO23 -4.8283137373 I #> 8296 2063 3M CC64 2019 2019-02-04 SALIN 3.0928589843 #> 8297 2063 3M CC64 2019 2019-02-04 TKN -0.7765287895 #> 8298 2063 3M CC64 2019 2019-02-04 TN -0.7678707268 + #> 8299 2063 3M CC64 2019 2019-02-04 TP -2.3025850930 #> 8300 2063 3M CC64 2019 2019-02-04 TURB 0.6418538862 #> 8301 2063 3M CC64 2019 2019-03-04 CHLAC 0.8329091229 #> 8302 2063 3M CC64 2019 2019-03-04 COLOR 3.1354942159 #> 8303 2063 3M CC64 2019 2019-03-04 DO 1.6014057407 #> 8304 2063 3M CC64 2019 2019-03-04 DOSAT 4.2297491992 #> 8305 2063 3M CC64 2019 2019-03-04 NO23 -4.8283137373 I #> 8306 2063 3M CC64 2019 2019-03-04 SALIN 2.9992261628 #> 8307 2063 3M CC64 2019 2019-03-04 TKN -0.5798184953 #> 8308 2063 3M CC64 2019 2019-03-04 TN -0.5727010275 + #> 8309 2063 3M CC64 2019 2019-03-04 TP -2.3025850930 #> 8310 2063 3M CC64 2019 2019-03-04 TURB 0.5306282511 #> 8311 2063 3M CC64 2019 2019-04-01 CHLAC 0.4700036292 I #> 8312 2063 3M CC64 2019 2019-04-01 COLOR 2.7725887222 #> 8313 2063 3M CC64 2019 2019-04-01 DO 1.3962446920 #> 8314 2063 3M CC64 2019 2019-04-01 DOSAT 3.9889840466 #> 8315 2063 3M CC64 2019 2019-04-01 NO23 -4.5098600062 #> 8316 2063 3M CC64 2019 2019-04-01 SALIN 3.1210424645 #> 8317 2063 3M CC64 2019 2019-04-01 TKN -0.5276327421 #> 8318 2063 3M CC64 2019 2019-04-01 TN -0.5091603444 + #> 8319 2063 3M CC64 2019 2019-04-01 TP -2.3126354288 #> 8320 2063 3M CC64 2019 2019-04-01 TURB 0.4700036292 #> 8321 2063 3M CC64 2019 2019-05-06 CHLAC 0.6931471806 I #> 8322 2063 3M CC64 2019 2019-05-06 COLOR 2.9444389792 #> 8323 2063 3M CC64 2019 2019-05-06 DO 0.8372475245 #> 8324 2063 3M CC64 2019 2019-05-06 DOSAT 3.5292973843 #> 8325 2063 3M CC64 2019 2019-05-06 NO23 -4.6051701860 I #> 8326 2063 3M CC64 2019 2019-05-06 SALIN 3.2331731296 #> 8327 2063 3M CC64 2019 2019-05-06 TKN -0.5621189182 #> 8328 2063 3M CC64 2019 2019-05-06 TN -0.5551258827 + #> 8329 2063 3M CC64 2019 2019-05-06 TP -2.2072749132 #> 8330 2063 3M CC64 2019 2019-05-06 TURB 0.2623642645 #> 8331 2063 3M CC64 2019 2019-06-03 CHLAC 0.7419373447 I #> 8332 2063 3M CC64 2019 2019-06-03 COLOR 2.8903717579 #> 8333 2063 3M CC64 2019 2019-06-03 DO 1.2974631474 #> 8334 2063 3M CC64 2019 2019-06-03 DOSAT 3.7220724215 #> 8335 2063 3M CC64 2019 2019-06-03 NO23 -5.2983173665 I #> 8336 2063 3M CC64 2019 2019-06-03 SALIN 3.2703291065 #> 8337 2063 3M CC64 2019 2019-06-03 TKN -0.3856624808 #> 8338 2063 3M CC64 2019 2019-06-03 TN -0.3797973614 + #> 8339 2063 3M CC64 2019 2019-06-03 TP -2.3025850930 #> 8340 2063 3M CC64 2019 2019-06-03 TURB 0.2623642645 #> 8341 2063 3M CC64 2019 2019-07-01 CHLAC 1.0986122887 #> 8342 2063 3M CC64 2019 2019-07-01 COLOR 2.8903717579 #> 8343 2063 3M CC64 2019 2019-07-01 DO 1.4036429995 #> 8344 2063 3M CC64 2019 2019-07-01 DOSAT 4.1108738642 #> 8345 2063 3M CC64 2019 2019-07-01 NO23 -5.1159958098 I #> 8346 2063 3M CC64 2019 2019-07-01 SALIN 3.1675825305 #> 8347 2063 3M CC64 2019 2019-07-01 TKN -0.4780358009 #> 8348 2063 3M CC64 2019 2019-07-01 TN -0.4716049106 + #> 8349 2063 3M CC64 2019 2019-07-01 TP -2.2072749132 #> 8350 2063 3M CC64 2019 2019-07-01 TURB 0.5877866649 #> 8351 2063 3M CC64 2019 2019-08-05 CHLAC 1.7578579176 #> 8352 2063 3M CC64 2019 2019-08-05 COLOR 3.9120230054 #> 8353 2063 3M CC64 2019 2019-08-05 DO 1.3001916621 #> 8354 2063 3M CC64 2019 2019-08-05 DOSAT 3.9702919136 #> 8355 2063 3M CC64 2019 2019-08-05 NO23 -5.5214609179 U #> 8356 2063 3M CC64 2019 2019-08-05 SALIN 2.8273136219 #> 8357 2063 3M CC64 2019 2019-08-05 TKN -0.1863295782 #> 8358 2063 3M CC64 2019 2019-08-05 TN -0.1839228382 + #> 8359 2063 3M CC64 2019 2019-08-05 TP -1.8325814637 #> 8360 2063 3M CC64 2019 2019-08-05 TURB 0.4700036292 #> 8361 2063 3M CC64 2019 2019-10-07 CHLAC 1.1939224685 #> 8362 2063 3M CC64 2019 2019-10-07 COLOR 3.2958368660 #> 8363 2063 3M CC64 2019 2019-10-07 DO 1.6863989536 #> 8364 2063 3M CC64 2019 2019-10-07 DOSAT 4.3412046402 #> 8365 2063 3M CC64 2019 2019-10-07 NO23 -5.1159958098 I #> 8366 2063 3M CC64 2019 2019-10-07 SALIN 3.2672849641 #> 8367 2063 3M CC64 2019 2019-10-07 TKN -0.4780358009 #> 8368 2063 3M CC64 2019 2019-10-07 TN -0.4716049106 + #> 8369 2063 3M CC64 2019 2019-10-07 TP -2.1202635362 #> 8370 2063 3M CC64 2019 2019-10-07 TURB 0.2623642645 #> 8371 2063 3M CC64 2019 2019-11-04 CHLAC 1.1939224685 #> 8372 2063 3M CC64 2019 2019-11-04 COLOR 3.1354942159 #> 8373 2063 3M CC64 2019 2019-11-04 DO 1.3110318766 #> 8374 2063 3M CC64 2019 2019-11-04 DOSAT 3.9646154555 #> 8375 2063 3M CC64 2019 2019-11-04 NO23 -4.6051701860 #> 8376 2063 3M CC64 2019 2019-11-04 SALIN 3.2503744919 #> 8377 2063 3M CC64 2019 2019-11-04 TKN -0.4307829161 #> 8378 2063 3M CC64 2019 2019-11-04 TN -0.4155154440 + #> 8379 2063 3M CC64 2019 2019-11-04 TP -2.1202635362 #> 8380 2063 3M CC64 2019 2019-11-04 TURB 0.0953101798 #> 8381 2063 3M CC64 2020 2020-01-06 CHLAC 1.0296194172 #> 8382 2063 3M CC64 2020 2020-01-06 COLOR 2.8332133441 #> 8383 2063 3M CC64 2020 2020-01-06 DO 1.6937790609 #> 8384 2063 3M CC64 2020 2020-01-06 DOSAT 4.2312037449 #> 8385 2063 3M CC64 2020 2020-01-06 NO23 -4.0745419349 #> 8386 2063 3M CC64 2020 2020-01-06 SALIN 3.2188758249 #> 8387 2063 3M CC64 2020 2020-01-06 TKN -0.4155154440 #> 8388 2063 3M CC64 2020 2020-01-06 TN -0.3900840061 + #> 8389 2063 3M CC64 2020 2020-01-06 TP -2.2072749132 #> 8390 2063 3M CC64 2020 2020-01-06 TURB 0.6931471806 #> 8391 2063 3M CC64 2020 2020-02-03 CHLAC 0.2623642645 I #> 8392 2063 3M CC64 2020 2020-02-03 COLOR 2.8332133441 #> 8393 2063 3M CC64 2020 2020-02-03 DO 1.5789787049 #> 8394 2063 3M CC64 2020 2020-02-03 DOSAT 4.0842942264 #> 8395 2063 3M CC64 2020 2020-02-03 NO23 -3.5755507688 #> 8396 2063 3M CC64 2020 2020-02-03 SALIN 3.2104403460 #> 8397 2063 3M CC64 2020 2020-02-03 TKN -0.6539264674 #> 8398 2063 3M CC64 2020 2020-02-03 TN -0.6014799920 + #> 8399 2063 3M CC64 2020 2020-02-03 TP -2.3434070875 #> 8400 2063 3M CC64 2020 2020-02-03 TURB 0.9162907319 #> 8401 2063 3M CC64 2020 2020-02-03 CHLAC 0.4700036292 I #> 8402 2063 3M CC64 2020 2020-02-03 COLOR 2.8332133441 #> 8403 2063 3M CC64 2020 2020-02-03 NO23 -3.5404594490 #> 8404 2063 3M CC64 2020 2020-02-03 TKN -0.7339691751 #> 8405 2063 3M CC64 2020 2020-02-03 TN -0.6753072624 + #> 8406 2063 3M CC64 2020 2020-02-03 TP -2.3859667019 #> 8407 2063 3M CC64 2020 2020-02-03 TURB 0.7884573604 #> 8408 2063 3M CC64 2020 2020-03-02 CHLAC 0.6931471806 I #> 8409 2063 3M CC64 2020 2020-03-02 COLOR 2.5649493575 A #> 8410 2063 3M CC64 2020 2020-03-02 DO 1.7749523509 #> 8411 2063 3M CC64 2020 2020-03-02 DOSAT 4.3067641502 #> 8412 2063 3M CC64 2020 2020-03-02 NO23 -5.5214609179 I #> 8413 2063 3M CC64 2020 2020-03-02 SALIN 3.2924979647 #> 8414 2063 3M CC64 2020 2020-03-02 TKN -0.8915981193 #> 8415 2063 3M CC64 2020 2020-03-02 TN -0.8818893052 + #> 8416 2063 3M CC64 2020 2020-03-02 TP -2.3968957725 #> 8417 2063 3M CC64 2020 2020-03-02 TURB 0.2623642645 #> 8418 2063 3M CC64 2020 2020-09-08 CHLAC 2.3025850930 A #> 8419 2063 3M CC64 2020 2020-09-08 COLOR 4.0253516907 #> 8420 2063 3M CC64 2020 2020-09-08 DO 0.1484200051 #> 8421 2063 3M CC64 2020 2020-09-08 DOSAT 2.8332133441 #> 8422 2063 3M CC64 2020 2020-09-08 NO23 -5.1159958098 I #> 8423 2063 3M CC64 2020 2020-09-08 SALIN 2.9693882982 #> 8424 2063 3M CC64 2020 2020-09-08 TKN -0.2231435513 #> 8425 2063 3M CC64 2020 2020-09-08 TN -0.2181560098 + #> 8426 2063 3M CC64 2020 2020-09-08 TP -1.5141277326 #> 8427 2063 3M CC64 2020 2020-09-08 TURB 0.5306282511 #> 8428 2063 3M CC64 2020 2020-10-05 CHLAC 1.5040773968 #> 8429 2063 3M CC64 2020 2020-10-05 COLOR 4.2626798770 #> 8430 2063 3M CC64 2020 2020-10-05 DO 1.1600209168 #> 8431 2063 3M CC64 2020 2020-10-05 DOSAT 3.7495040759 #> 8432 2063 3M CC64 2020 2020-10-05 NO23 -3.0365542681 #> 8433 2063 3M CC64 2020 2020-10-05 SALIN 2.5649493575 #> 8434 2063 3M CC64 2020 2020-10-05 TKN -0.0408219945 #> 8435 2063 3M CC64 2020 2020-10-05 TN 0.0079681696 + #> 8436 2063 3M CC64 2020 2020-10-05 TP -1.8971199849 #> 8437 2063 3M CC64 2020 2020-10-05 TURB 0.0953101798 #> 8438 2063 3M CC64 2020 2020-11-02 CHLAC 1.1631508098 I #> 8439 2063 3M CC64 2020 2020-11-02 COLOR 4.0073331852 A #> 8440 2063 3M CC64 2020 2020-11-02 NO23 -3.9633162998 #> 8441 2063 3M CC64 2020 2020-11-02 SALIN 2.7562052430 #> 8442 2063 3M CC64 2020 2020-11-02 TKN -0.3710636814 #> 8443 2063 3M CC64 2020 2020-11-02 TN -0.3438997525 + #> 8444 2063 3M CC64 2020 2020-11-02 TP -2.0402208285 #> 8445 2063 3M CC64 2020 2020-11-02 TURB 0.2623642645 #> 8446 2063 3M CC64 2020 2020-12-07 CHLAC 0.3364722366 I #> 8447 2063 3M CC64 2020 2020-12-07 COLOR 3.6635616461 #> 8448 2063 3M CC64 2020 2020-12-07 DO 1.6677068206 #> 8449 2063 3M CC64 2020 2020-12-07 DOSAT 4.1743872699 #> 8450 2063 3M CC64 2020 2020-12-07 NO23 -3.8167128256 #> 8451 2063 3M CC64 2020 2020-12-07 SALIN 2.9982291538 #> 8452 2063 3M CC64 2020 2020-12-07 TKN -0.3856624808 #> 8453 2063 3M CC64 2020 2020-12-07 TN -0.3538218750 + #> 8454 2063 3M CC64 2020 2020-12-07 TP -2.4769384801 #> 8455 2063 3M CC64 2020 2020-12-07 TURB 0.1823215568 #> 8456 2063 3M CC64 2021 2021-01-04 CHLAC 0.3364722366 I #> 8457 2063 3M CC64 2021 2021-01-04 COLOR 3.1780538303 #> 8458 2063 3M CC64 2021 2021-01-04 DO 1.4816045409 #> 8459 2063 3M CC64 2021 2021-01-04 DOSAT 4.0271358125 #> 8460 2063 3M CC64 2021 2021-01-04 NO23 -4.1351665567 #> 8461 2063 3M CC64 2021 2021-01-04 SALIN 3.1376657694 #> 8462 2063 3M CC64 2021 2021-01-04 TKN -0.5276327421 #> 8463 2063 3M CC64 2021 2021-01-04 TN -0.5008752929 + #> 8464 2063 3M CC64 2021 2021-01-04 TP -2.3025850930 #> 8465 2063 3M CC64 2021 2021-01-04 TURB 0.2623642645 #> 8466 2063 3M CC64 2021 2021-02-01 CHLAC 0.9932517730 #> 8467 2063 3M CC64 2021 2021-02-01 COLOR 2.8332133441 #> 8468 2063 3M CC64 2021 2021-02-01 DO 1.8082887712 #> 8469 2063 3M CC64 2021 2021-02-01 DOSAT 4.3489867806 #> 8470 2063 3M CC64 2021 2021-02-01 NO23 -4.9618451299 I #> 8471 2063 3M CC64 2021 2021-02-01 SALIN 3.2120525995 #> 8472 2063 3M CC64 2021 2021-02-01 TKN -0.5276327421 #> 8473 2063 3M CC64 2021 2021-02-01 TN -0.5208759596 + #> 8474 2063 3M CC64 2021 2021-02-01 TP -2.3751557858 #> 8475 2063 3M CC64 2021 2021-02-01 TURB 1.1631508098 #> 8476 2063 3M CC64 2021 2021-03-01 CHLAC 0.6418538862 I #> 8477 2063 3M CC64 2021 2021-03-01 COLOR 2.6390573296 #> 8478 2063 3M CC64 2021 2021-03-01 DO 1.5454325825 #> 8479 2063 3M CC64 2021 2021-03-01 DOSAT 4.1956970565 #> 8480 2063 3M CC64 2021 2021-03-01 NO23 -4.8283137373 I #> 8481 2063 3M CC64 2021 2021-03-01 SALIN 3.2861605717 #> 8482 2063 3M CC64 2021 2021-03-01 TKN -0.9675840263 I #> 8483 2063 3M CC64 2021 2021-03-01 TN -1.8078888512 + #> 8484 2063 3M CC64 2021 2021-03-01 TP -2.3859667019 #> 8485 2063 3M CC64 2021 2021-03-01 TURB 0.6931471806 A #> 8486 2063 3M CC64 2021 2021-04-05 CHLAC 1.5475625087 #> 8487 2063 3M CC64 2021 2021-04-05 COLOR 2.7080502011 #> 8488 2063 3M CC64 2021 2021-04-05 DO 1.6505798558 #> 8489 2063 3M CC64 2021 2021-04-05 DOSAT 4.2370008626 #> 8490 2063 3M CC64 2021 2021-04-05 NO23 -5.5214609179 U #> 8491 2063 3M CC64 2021 2021-04-05 SALIN 3.3010086544 #> 8492 2063 3M CC64 2021 2021-04-05 TN -0.4277107171 + #> 8493 2063 3M CC64 2021 2021-04-05 TP -2.2072749132 #> 8494 2063 3M CC64 2021 2021-04-05 TURB 1.2527629685 #> 8495 2063 3M CC64 2021 2021-05-03 CHLAC 0.9932517730 #> 8496 2063 3M CC64 2021 2021-05-03 COLOR 2.9957322736 #> 8497 2063 3M CC64 2021 2021-05-03 DO 1.2584609896 #> 8498 2063 3M CC64 2021 2021-05-03 DOSAT 3.9740583963 #> 8499 2063 3M CC64 2021 2021-05-03 NO23 -5.5214609179 U #> 8500 2063 3M CC64 2021 2021-05-03 SALIN 3.3641875560 #> 8501 2063 3M CC64 2021 2021-05-03 TKN -0.7133498879 #> 8502 2063 3M CC64 2021 2021-05-03 TN -0.7092765625 + #> 8503 2063 3M CC64 2021 2021-05-03 TP -2.3227878003 #> 8504 2063 3M CC64 2021 2021-05-03 TURB 0.7419373447 #> 8505 2063 3M CC64 2021 2021-05-03 CHLAC 1.2809338455 #> 8506 2063 3M CC64 2021 2021-05-03 COLOR 2.9444389792 #> 8507 2063 3M CC64 2021 2021-05-03 NO23 -5.5214609179 U #> 8508 2063 3M CC64 2021 2021-05-03 TKN -0.5621189182 #> 8509 2063 3M CC64 2021 2021-05-03 TN -0.5586162876 + #> 8510 2063 3M CC64 2021 2021-05-03 TP -2.3227878003 #> 8511 2063 3M CC64 2021 2021-05-03 TURB 0.7884573604 #> 8512 2063 3M CC64 2021 2021-06-07 CHLAC 1.7578579176 #> 8513 2063 3M CC64 2021 2021-06-07 COLOR 2.8332133441 #> 8514 2063 3M CC64 2021 2021-06-07 DO 0.9707789172 #> 8515 2063 3M CC64 2021 2021-06-07 DOSAT 3.6788291183 #> 8516 2063 3M CC64 2021 2021-06-07 NO23 -4.3428059215 #> 8517 2063 3M CC64 2021 2021-06-07 SALIN 3.2839142210 #> 8518 2063 3M CC64 2021 2021-06-07 TKN -0.4620354596 #> 8519 2063 3M CC64 2021 2021-06-07 TN -0.4416105547 + #> 8520 2063 3M CC64 2021 2021-06-07 TP -2.4304184645 #> 8521 2063 3M CC64 2021 2021-06-07 TURB 0.4054651081 #> 8522 2063 3M CC64 2021 2021-08-02 CHLAC 1.6094379124 #> 8523 2063 3M CC64 2021 2021-08-02 COLOR 4.3438054219 #> 8524 2063 3M CC64 2021 2021-08-02 DO 1.4255150743 #> 8525 2063 3M CC64 2021 2021-08-02 DOSAT 4.1092331747 #> 8526 2063 3M CC64 2021 2021-08-02 NO23 -4.8283137373 I #> 8527 2063 3M CC64 2021 2021-08-02 SALIN 2.4292177439 #> 8528 2063 3M CC64 2021 2021-08-02 TKN -0.1278333715 #> 8529 2063 3M CC64 2021 2021-08-02 TN -0.1232982163 + #> 8530 2063 3M CC64 2021 2021-08-02 TP -1.7719568419 #> 8531 2063 3M CC64 2021 2021-08-02 TURB 0.6418538862 #> 8532 2063 3M CC64 2021 2021-09-07 CHLAC 0.9555114450 #> 8533 2063 3M CC64 2021 2021-09-07 COLOR 4.1271343850 #> 8534 2063 3M CC64 2021 2021-09-07 DO 0.9820784724 #> 8535 2063 3M CC64 2021 2021-09-07 DOSAT 3.6375861597 #> 8536 2063 3M CC64 2021 2021-09-07 NO23 -3.8167128256 #> 8537 2063 3M CC64 2021 2021-09-07 SALIN 2.5687881338 #> 8538 2063 3M CC64 2021 2021-09-07 TKN -0.1053605157 #> 8539 2063 3M CC64 2021 2021-09-07 TN -0.0812100554 + #> 8540 2063 3M CC64 2021 2021-09-07 TP -1.8325814637 #> 8541 2063 3M CC64 2021 2021-09-07 TURB 0.0953101798 #> 8542 2063 3M CC64 2021 2021-10-04 CHLAC 1.1939224685 #> 8543 2063 3M CC64 2021 2021-10-04 COLOR 3.7841896339 #> 8544 2063 3M CC64 2021 2021-10-04 DO 1.0577902941 #> 8545 2063 3M CC64 2021 2021-10-04 DOSAT 3.7135720667 #> 8546 2063 3M CC64 2021 2021-10-04 NO23 -4.7105307016 I #> 8547 2063 3M CC64 2021 2021-10-04 SALIN 2.9069010598 #> 8548 2063 3M CC64 2021 2021-10-04 TKN -0.3566749439 #> 8549 2063 3M CC64 2021 2021-10-04 TN -0.3509769228 + #> 8550 2063 3M CC64 2021 2021-10-04 TP -1.8325814637 #> 8551 2063 3M CC64 2021 2021-10-04 TURB 0.0953101798 #> 8552 2063 3M CC64 2021 2021-11-01 CHLAC 0.9162907319 I #> 8553 2063 3M CC64 2021 2021-11-01 COLOR 3.6109179126 A #> 8554 2063 3M CC64 2021 2021-11-01 DO 1.0331844833 #> 8555 2063 3M CC64 2021 2021-11-01 DOSAT 3.6375861597 #> 8556 2063 3M CC64 2021 2021-11-01 NO23 -3.1941832123 #> 8557 2063 3M CC64 2021 2021-11-01 SALIN 3.0964821767 #> 8558 2063 3M CC64 2021 2021-11-01 TKN -0.3566749439 #> 8559 2063 3M CC64 2021 2021-11-01 TN -0.2997546537 + #> 8560 2063 3M CC64 2021 2021-11-01 TP -1.9661128564 #> 8561 2063 3M 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8597 2063 3M CC64 2022 2022-03-07 SALIN 3.4170707308 #> 8598 2063 3M CC64 2022 2022-03-07 TKN -0.7339691751 #> 8599 2063 3M CC64 2022 2022-03-07 TN -0.7298111649 + #> 8600 2063 3M CC64 2022 2022-03-07 TP -2.7968814148 #> 8601 2063 3M CC64 2022 2022-03-07 TURB 0.4054651081 #> 8602 2063 3M CC64 2022 2022-04-04 CHLAC 1.4109869737 #> 8603 2063 3M CC64 2022 2022-04-04 COLOR 2.2823823857 #> 8604 2063 3M CC64 2022 2022-04-04 DO 1.3350010667 #> 8605 2063 3M CC64 2022 2022-04-04 DOSAT 3.9889840466 #> 8606 2063 3M CC64 2022 2022-04-04 NO23 -4.6051701860 I #> 8607 2063 3M CC64 2022 2022-04-04 SALIN 3.4157575330 #> 8608 2063 3M CC64 2022 2022-04-04 TKN -0.9942522733 I #> 8609 2063 3M CC64 2022 2022-04-04 TN -1.8078888512 + #> 8610 2063 3M CC64 2022 2022-04-04 TP -2.4079456087 #> 8611 2063 3M CC64 2022 2022-04-04 TURB 0.2623642645 #> 8612 2063 3M CC64 2022 2022-05-02 CHLAC 1.0986122887 #> 8613 2063 3M CC64 2022 2022-05-02 COLOR 1.0647107370 I #> 8614 2063 3M CC64 2022 2022-05-02 DO 1.3987168811 #> 8615 2063 3M CC64 2022 2022-05-02 DOSAT 4.0775374439 #> 8616 2063 3M CC64 2022 2022-05-02 NO23 -5.2983173665 I #> 8617 2063 3M CC64 2022 2022-05-02 SALIN 3.4229588734 #> 8618 2063 3M CC64 2022 2022-05-02 TKN -0.5447271754 #> 8619 2063 3M CC64 2022 2022-05-02 TN -0.5378542962 + #> 8620 2063 3M CC64 2022 2022-05-02 TP -2.4651040225 #> 8621 2063 3M CC64 2022 2022-05-02 TURB -0.0512932944 I #> 8622 2063 3M CC64 2013 2013-01-08 TN -0.7339691751 #> 8623 2063 3M CC64 2013 2013-01-08 TP -4.5098600062 #> 8624 2063 3M CC64 2013 2013-02-05 CHLAC 0.0000000000 I #> 8625 2063 3M CC64 2013 2013-03-05 CHLAC 0.6931471806 #> 8626 2063 3M CC64 2013 2013-03-05 TN -1.0788096614 #> 8627 2063 3M CC64 2013 2013-03-05 TP -2.6310891600 #> 8628 2063 3M CC64 2013 2013-04-02 CHLAC 1.0986122887 #> 8629 2063 3M CC64 2013 2013-04-02 TN -0.4620354596 #> 8630 2063 3M CC64 2013 2013-04-02 TP -2.4651040225 #> 8631 2063 3M CC64 2013 2013-05-07 CHLAC 1.0986122887 #> 8632 2063 3M CC64 2013 2013-05-07 TN -0.4942963218 #> 8633 2063 3M CC64 2013 2013-05-07 TP -2.2827824657 #> 8634 2063 3M CC64 2013 2013-06-04 CHLAC 0.6931471806 #> 8635 2063 3M CC64 2013 2013-06-04 TN -0.3285040670 #> 8636 2063 3M CC64 2013 2013-06-04 TP -2.5510464523 #> 8637 2063 3M CC64 2013 2013-07-03 CHLAC 0.6931471806 #> 8638 2063 3M CC64 2013 2013-07-03 TN -0.2107210313 #> 8639 2063 3M CC64 2013 2013-07-03 TP -2.6882475738 #> 8640 2063 3M CC64 2013 2013-08-06 CHLAC 1.0986122887 #> 8641 2063 3M CC64 2013 2013-08-06 TN -0.5276327421 #> 8642 2063 3M CC64 2013 2013-08-06 TP -2.2730262908 #> 8643 2063 3M CC64 2013 2013-09-10 CHLAC 1.3862943611 #> 8644 2063 3M CC64 2013 2013-09-10 TN -0.6733445533 #> 8645 2063 3M CC64 2013 2013-09-10 TP -2.5133061243 #> 8646 2063 3M CC64 2013 2013-10-01 CHLAC 1.9459101491 #> 8647 2063 3M CC64 2013 2013-10-01 TN -0.7765287895 #> 8648 2063 3M CC64 2013 2013-10-01 TP -3.1235656451 #> 8649 2063 3M CC64 2013 2013-11-05 CHLAC 1.0986122887 #> 8650 2063 3M CC64 2013 2013-11-05 TN -0.6733445533 #> 8651 2063 3M CC64 2013 2013-11-05 TP -2.2926347621 #> 8652 2063 3M CC64 2013 2013-12-03 TN -0.8209805521 #> 8653 2063 3M CC64 2013 2013-12-03 TP -2.3330443005 #> 8654 2063 3M CC64 2014 2014-01-07 CHLAC 1.0986122887 #> 8655 2063 3M CC64 2014 2014-01-07 TN -0.9942522733 #> 8656 2063 3M CC64 2014 2014-01-07 TP -2.5510464523 #> 8657 2063 3M CC64 2014 2014-02-04 CHLAC 0.0000000000 #> 8658 2063 3M CC64 2014 2014-02-04 TN -1.0498221245 #> 8659 2063 3M CC64 2014 2014-02-04 TP -2.6310891600 #> 8660 2063 3M CC64 2014 2014-03-04 CHLAC 1.3862943611 #> 8661 2063 3M CC64 2014 2014-03-04 TN -0.5978370008 #> 8662 2063 3M CC64 2014 2014-03-04 TP -2.7333680091 #> 8663 2063 3M CC64 2014 2014-04-01 CHLAC 1.0986122887 #> 8664 2063 3M CC64 2014 2014-04-01 TN -1.0788096614 #> 8665 2063 3M CC64 2014 2014-04-01 TP -2.7181005370 #> 8666 2063 3M CC64 2014 2014-06-03 CHLAC 1.3862943611 #> 8667 2063 3M CC64 2014 2014-06-03 TN -0.5798184953 #> 8668 2063 3M CC64 2014 2014-06-03 TP -2.2072749132 #> 8669 2063 3M CC64 2014 2014-09-02 CHLAC 3.1354942159 #> 8670 2063 3M CC64 2014 2014-09-02 TP -2.3126354288 #> 8671 2063 3M CC64 2014 2014-11-04 CHLAC 0.6931471806 #> 8672 2063 3M CC64 2014 2014-11-04 TN -0.5798184953 #> 8673 2063 3M CC64 2014 2014-11-04 TP -2.6310891600 #> 8674 2063 3M CC64 2014 2014-12-02 CHLAC 0.0000000000 #> 8675 2063 3M CC64 2014 2014-12-02 TN -0.4942963218 #> 8676 2063 3M CC64 2014 2014-12-02 TP -2.3751557858 #> 8677 2063 3M CC64 2015 2015-01-03 CHLAC 0.0000000000 #> 8678 2063 3M CC64 2015 2015-01-03 TN -0.3011050928 #> 8679 2063 3M CC64 2015 2015-01-03 TP -1.8018098051 #> 8680 2063 3M CC64 2015 2015-02-02 CHLAC 0.6931471806 #> 8681 2063 3M CC64 2015 2015-03-03 CHLAC 0.0000000000 #> 8682 2063 3M CC64 2015 2015-03-03 TN -0.5798184953 #> 8683 2063 3M CC64 2015 2015-03-03 TP -2.2730262908 #> 8684 2063 3M CC64 2015 2015-04-02 CHLAC 0.6931471806 #> 8685 2063 3M CC64 2015 2015-04-02 TN -0.4462871026 #> 8686 2063 3M CC64 2015 2015-04-02 TP -2.2926347621 #> 8687 2063 3M CC64 2015 2015-05-05 CHLAC 1.0986122887 #> 8688 2063 3M CC64 2015 2015-05-05 TN -0.8209805521 #> 8689 2063 3M CC64 2015 2015-05-05 TP -2.5257286443 #> 8690 2063 3M CC64 2015 2015-09-09 CHLAC 1.0986122887 #> 8691 2063 3M CC64 2015 2015-09-09 TN -0.5978370008 #> 8692 2063 3M CC64 2015 2015-09-09 TP -2.9759296463 #> 8693 2063 3M CC64 2015 2015-10-07 CHLAC 1.6094379124 #> 8694 2063 3M CC64 2015 2015-11-04 CHLAC 1.0986122887 #> 8695 2063 3M CC64 2015 2015-11-04 TN -0.6539264674 #> 8696 2063 3M CC64 2015 2015-11-04 TP -2.6172958378 #> 8697 2063 3M CC64 2015 2015-11-15 CHLAC 1.6094379124 #> 8698 2063 3M CC64 2015 2015-11-15 TN -0.8439700703 #> 8699 2063 3M CC64 2015 2015-11-15 TP -2.7968814148 #> 8700 2063 3M CC64 2016 2016-01-06 TN -0.1053605157 #> 8701 2063 3M CC64 2016 2016-01-06 TP -2.3126354288 #> 8702 2063 3M CC64 2016 2016-02-02 CHLAC 1.6094379124 #> 8703 2063 3M CC64 2016 2016-02-02 TN -0.2231435513 #> 8704 2063 3M CC64 2016 2016-02-02 TP -2.9957322736 #> 8705 2063 3M CC64 2016 2016-06-11 CHLAC 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#> 8724 2081 3F CC67 2016 2016-04-27 DOSAT 4.5849674787 #> 8725 2081 3F CC67 2016 2016-04-27 NO23 -4.3428059215 #> 8726 2081 3F CC67 2016 2016-04-27 SALIN -1.3093333200 + #> 8727 2081 3F CC67 2016 2016-04-27 TKN -0.1625189295 #> 8728 2081 3F CC67 2016 2016-04-27 TN -0.1473405879 + #> 8729 2081 3F CC67 2016 2016-04-27 TP -2.9187712324 #> 8730 2081 3F CC67 2016 2016-04-27 TSS 1.0986122887 I #> 8731 2081 3F CC67 2016 2016-04-27 TURB 1.8870696490 #> 8732 2081 3F CC67 2016 2016-09-21 CHLAC 2.2082744135 A #> 8733 2081 3F CC67 2016 2016-09-21 COLOR 4.9416424226 #> 8734 2081 3F CC67 2016 2016-09-21 COND 5.8636311756 #> 8735 2081 3F CC67 2016 2016-09-21 DO 1.7227665977 #> 8736 2081 3F CC67 2016 2016-09-21 DOSAT 4.3040650932 #> 8737 2081 3F CC67 2016 2016-09-21 NO23 -2.9565115604 #> 8738 2081 3F CC67 2016 2016-09-21 SALIN -1.6094379124 #> 8739 2081 3F CC67 2016 2016-09-21 TKN -0.1863295782 #> 8740 2081 3F CC67 2016 2016-09-21 TN -0.1255632230 + #> 8741 2081 3F CC67 2016 2016-09-21 TP -2.3025850930 #> 8742 2081 3F CC67 2016 2016-09-21 TSS 2.8332133441 #> 8743 2081 3F CC67 2016 2016-09-21 TURB 2.3025850930 #> 8744 2081 3F CC67 2016 2016-12-13 CHLAC 0.5306282511 I #> 8745 2081 3F CC67 2016 2016-12-13 COLOR 4.0253516907 #> 8746 2081 3F CC67 2016 2016-12-13 COND 6.2709884319 #> 8747 2081 3F CC67 2016 2016-12-13 DO 2.1860512767 #> 8748 2081 3F CC67 2016 2016-12-13 DOSAT 4.5951198501 #> 8749 2081 3F CC67 2016 2016-12-13 NO23 -1.8971199849 #> 8750 2081 3F CC67 2016 2016-12-13 SALIN -1.6094379124 #> 8751 2081 3F CC67 2016 2016-12-13 TKN -0.4942963218 #> 8752 2081 3F CC67 2016 2016-12-13 TN -0.2744368457 + #> 8753 2081 3F CC67 2016 2016-12-13 TP -2.9759296463 #> 8754 2081 3F CC67 2016 2016-12-13 TSS 1.3862943611 I #> 8755 2081 3F CC67 2016 2016-12-13 TURB 1.6486586256 #> 8756 2081 3F CC67 2016 2016-12-28 CHLAC 1.0296194172 #> 8757 2081 3F CC67 2016 2016-12-28 COLOR 4.1896547420 A #> 8758 2081 3F CC67 2016 2016-12-28 COND 6.2747620212 #> 8759 2081 3F CC67 2016 2016-12-28 NO23 -2.2072749132 #> 8760 2081 3F CC67 2016 2016-12-28 SALIN -1.3093333200 + #> 8761 2081 3F CC67 2016 2016-12-28 TKN -0.4004775666 #> 8762 2081 3F CC67 2016 2016-12-28 TN -0.2484613593 + #> 8763 2081 3F CC67 2016 2016-12-28 TP -2.6882475738 #> 8764 2081 3F CC67 2016 2016-12-28 TSS 1.7917594692 I #> 8765 2081 3F CC67 2016 2016-12-28 TURB 1.9878743482 A #> 8766 2081 3F CC67 2017 2017-07-26 CHLAC 2.3025850930 #> 8767 2081 3F CC67 2017 2017-07-26 COLOR 5.3471075307 #> 8768 2081 3F CC67 2017 2017-07-26 COND 5.8435444170 #> 8769 2081 3F CC67 2017 2017-07-26 DO 1.6486586256 #> 8770 2081 3F CC67 2017 2017-07-26 DOSAT 4.2626798770 #> 8771 2081 3F CC67 2017 2017-07-26 NO23 -3.3813947544 #> 8772 2081 3F CC67 2017 2017-07-26 TKN 0.0953101798 #> 8773 2081 3F CC67 2017 2017-07-26 TN 0.1257512053 + #> 8774 2081 3F CC67 2017 2017-07-26 TP -2.4191189092 #> 8775 2081 3F CC67 2017 2017-07-26 TSS 2.4849066498 #> 8776 2081 3F CC67 2017 2017-07-26 TURB 1.9315214116 #> 8777 2081 3F CC67 2017 2017-08-21 CHLAC 1.4350845253 #> 8778 2081 3F CC67 2017 2017-08-21 COLOR 4.7874917428 #> 8779 2081 3F CC67 2017 2017-08-21 COND 6.0497334552 #> 8780 2081 3F CC67 2017 2017-08-21 DO 1.9169226122 #> 8781 2081 3F CC67 2017 2017-08-21 DOSAT 4.5108595065 #> 8782 2081 3F CC67 2017 2017-08-21 NO23 -2.9957322736 #> 8783 2081 3F CC67 2017 2017-08-21 TKN -0.1984509387 #> 8784 2081 3F CC67 2017 2017-08-21 TN -0.1392620673 + #> 8785 2081 3F CC67 2017 2017-08-21 TP -2.7488721956 #> 8786 2081 3F CC67 2017 2017-08-21 TSS 2.3025850930 I #> 8787 2081 3F CC67 2017 2017-08-21 TURB 1.9740810260 A #> 8788 2081 3F CC67 2017 2017-10-04 CHLAC 2.0014800002 #> 8789 2081 3F CC67 2017 2017-10-04 COLOR 4.7874917428 #> 8790 2081 3F CC67 2017 2017-10-04 COND 5.9188938543 #> 8791 2081 3F CC67 2017 2017-10-04 DO 1.8718021769 #> 8792 2081 3F CC67 2017 2017-10-04 DOSAT 4.3944491547 #> 8793 2081 3F CC67 2017 2017-10-04 NO23 -3.1235656451 #> 8794 2081 3F CC67 2017 2017-10-04 SALIN -1.7719568419 + #> 8795 2081 3F CC67 2017 2017-10-04 TKN -0.2231435513 #> 8796 2081 3F CC67 2017 2017-10-04 TN -0.1696027844 + #> 8797 2081 3F CC67 2017 2017-10-04 TP -2.7488721956 #> 8798 2081 3F CC67 2017 2017-10-04 TSS 2.0794415417 I #> 8799 2081 3F CC67 2017 2017-10-04 TURB 1.6486586256 A #> 8800 2081 3F CC67 2017 2017-11-08 CHLAC 1.7404661748 #> 8801 2081 3F CC67 2017 2017-11-08 COLOR 4.2341065046 #> 8802 2081 3F CC67 2017 2017-11-08 COND 6.1377270541 #> 8803 2081 3F CC67 2017 2017-11-08 DO 2.1747517215 #> 8804 2081 3F CC67 2017 2017-11-08 DOSAT 4.6634390941 #> 8805 2081 3F CC67 2017 2017-11-08 NO23 -2.7030626596 #> 8806 2081 3F CC67 2017 2017-11-08 SALIN -1.4696759701 + #> 8807 2081 3F CC67 2017 2017-11-08 TKN -0.4942963218 #> 8808 2081 3F CC67 2017 2017-11-08 TN -0.3900840061 + #> 8809 2081 3F CC67 2017 2017-11-08 TP -3.1235656451 #> 8810 2081 3F CC67 2017 2017-11-08 TSS 1.0986122887 I #> 8811 2081 3F CC67 2017 2017-11-08 TURB 1.5686159179 #> 8812 2081 3F CC67 2017 2017-11-30 CHLAC 1.6677068206 #> 8813 2081 3F CC67 2017 2017-11-30 COLOR 4.1271343850 A #> 8814 2081 3F CC67 2017 2017-11-30 COND 6.2519038832 #> 8815 2081 3F CC67 2017 2017-11-30 DO 2.3025850930 #> 8816 2081 3F CC67 2017 2017-11-30 DOSAT 4.7535901911 #> 8817 2081 3F CC67 2017 2017-11-30 NO23 -3.2188758249 #> 8818 2081 3F CC67 2017 2017-11-30 SALIN -1.3470736480 + #> 8819 2081 3F CC67 2017 2017-11-30 TKN -0.5798184953 #> 8820 2081 3F CC67 2017 2017-11-30 TN -0.5108256238 + #> 8821 2081 3F CC67 2017 2017-11-30 TP -3.1700856607 #> 8822 2081 3F CC67 2017 2017-11-30 TSS 1.3862943611 I #> 8823 2081 3F CC67 2017 2017-11-30 TURB 1.5475625087 #> 8824 2081 3F CC67 2018 2018-04-12 COND 6.1717005974 #> 8825 2081 3F CC67 2018 2018-04-12 DO 2.6461747974 #> 8826 2081 3F CC67 2018 2018-04-12 DOSAT 5.1239639794 #> 8827 2081 3F CC67 2018 2018-04-12 SALIN -1.4696759701 + #> 8828 2081 3F CC67 2018 2018-04-19 CHLAC 2.2512917986 #> 8829 2081 3F CC67 2018 2018-04-19 COLOR 4.0943445622 #> 8830 2081 3F CC67 2018 2018-04-19 COND 6.0980742822 #> 8831 2081 3F CC67 2018 2018-04-19 DO 2.7317667277 #> 8832 2081 3F CC67 2018 2018-04-19 DOSAT 5.3107398865 #> 8833 2081 3F CC67 2018 2018-04-19 NO23 -5.5214609179 U #> 8834 2081 3F CC67 2018 2018-04-19 SALIN -1.6094379124 + #> 8835 2081 3F CC67 2018 2018-04-19 TKN -0.3424903089 #> 8836 2081 3F CC67 2018 2018-04-19 TN -0.3396773676 + #> 8837 2081 3F CC67 2018 2018-04-19 TP -4.2686979494 #> 8838 2081 3F CC67 2018 2018-04-19 TSS 1.0986122887 I #> 8839 2081 3F CC67 2018 2018-04-19 TURB 0.4054651081 #> 8840 2081 3F CC67 2018 2018-07-17 CHLAC 2.3978952728 #> 8841 2081 3F CC67 2018 2018-07-17 COLOR 5.2470240722 #> 8842 2081 3F CC67 2018 2018-07-17 COND 5.6559918108 #> 8843 2081 3F CC67 2018 2018-07-17 DO 1.6677068206 #> 8844 2081 3F CC67 2018 2018-07-17 DOSAT 4.2541932632 #> 8845 2081 3F CC67 2018 2018-07-17 NO23 -3.8167128256 #> 8846 2081 3F CC67 2018 2018-07-17 TKN -0.0304592075 #> 8847 2081 3F CC67 2018 2018-07-17 TN -0.0080321717 + #> 8848 2081 3F CC67 2018 2018-07-17 TP -2.7968814148 #> 8849 2081 3F CC67 2018 2018-07-17 TSS 1.7917594692 I #> 8850 2081 3F CC67 2018 2018-07-17 TURB 1.7047480922 #> 8851 2081 3F CC67 2018 2018-08-01 CHLAC 2.0014800002 #> 8852 2081 3F CC67 2018 2018-08-01 COLOR 4.9416424226 #> 8853 2081 3F CC67 2018 2018-08-01 COND 5.9269260260 #> 8854 2081 3F CC67 2018 2018-08-01 DO 1.8900953699 #> 8855 2081 3F CC67 2018 2018-08-01 DOSAT 4.4624538838 #> 8856 2081 3F CC67 2018 2018-08-01 NO23 -3.2188758249 #> 8857 2081 3F CC67 2018 2018-08-01 SALIN -1.7147984281 #> 8858 2081 3F CC67 2018 2018-08-01 TKN -0.2613647641 #> 8859 2081 3F CC67 2018 2018-08-01 TN -0.2107210313 + #> 8860 2081 3F CC67 2018 2018-08-01 TP -2.8824035882 #> 8861 2081 3F CC67 2018 2018-08-01 TSS 1.7917594692 I #> 8862 2081 3F CC67 2018 2018-08-01 TURB 1.7404661748 #> 8863 2081 3F CC67 2018 2018-08-01 CHLAC 2.1041341543 #> 8864 2081 3F CC67 2018 2018-08-01 COLOR 4.9416424226 #> 8865 2081 3F CC67 2018 2018-08-01 COND 5.9269260260 #> 8866 2081 3F CC67 2018 2018-08-01 DO 1.8900953699 #> 8867 2081 3F CC67 2018 2018-08-01 DOSAT 4.4624538838 #> 8868 2081 3F CC67 2018 2018-08-01 NO23 -3.2188758249 #> 8869 2081 3F CC67 2018 2018-08-01 SALIN -1.7147984281 #> 8870 2081 3F CC67 2018 2018-08-01 TKN -0.2357223335 #> 8871 2081 3F CC67 2018 2018-08-01 TN -0.1863295782 + #> 8872 2081 3F CC67 2018 2018-08-01 TP -2.8302178351 #> 8873 2081 3F CC67 2018 2018-08-01 TSS 1.7917594692 I #> 8874 2081 3F CC67 2018 2018-08-01 TURB 1.6863989536 #> 8875 2081 3F CC67 2018 2018-08-20 CHLAC 2.2407096893 #> 8876 2081 3F CC67 2018 2018-08-20 COLOR 5.0751738152 #> 8877 2081 3F CC67 2018 2018-08-20 COND 5.3706380281 #> 8878 2081 3F CC67 2018 2018-08-20 DO 1.5216989981 #> 8879 2081 3F CC67 2018 2018-08-20 DOSAT 4.0758410907 #> 8880 2081 3F CC67 2018 2018-08-20 NO23 -3.4420193762 #> 8881 2081 3F CC67 2018 2018-08-20 SALIN -2.3025850930 #> 8882 2081 3F CC67 2018 2018-08-20 TKN -0.0618754037 #> 8883 2081 3F CC67 2018 2018-08-20 TN -0.0283994745 + #> 8884 2081 3F CC67 2018 2018-08-20 TP -2.4534079827 #> 8885 2081 3F CC67 2018 2018-08-20 TSS 2.1972245773 I #> 8886 2081 3F CC67 2018 2018-08-20 TURB 1.9315214116 #> 8887 2081 3F CC67 2018 2018-09-10 CHLAC 1.5260563035 #> 8888 2081 3F CC67 2018 2018-09-10 COLOR 4.4998096703 A #> 8889 2081 3F CC67 2018 2018-09-10 COND 6.0520891689 #> 8890 2081 3F CC67 2018 2018-09-10 DO 1.9865035460 #> 8891 2081 3F CC67 2018 2018-09-10 DOSAT 4.5941092386 #> 8892 2081 3F CC67 2018 2018-09-10 SALIN -1.6094379124 #> 8893 2081 3F CC67 2018 2018-09-10 TN -0.2057949130 + #> 8894 2081 3F CC67 2018 2018-09-10 TSS 2.3025850930 A #> 8895 2081 3F CC67 2018 2018-09-10 TURB 2.0281482473 #> 8896 2081 3F CC67 2018 2018-11-12 CHLAC 2.2300144002 #> 8897 2081 3F CC67 2018 2018-11-12 COLOR 3.9120230054 #> 8898 2081 3F CC67 2018 2018-11-12 COND 6.2595814641 #> 8899 2081 3F CC67 2018 2018-11-12 DO 2.1174596089 #> 8900 2081 3F CC67 2018 2018-11-12 DOSAT 4.6180864113 #> 8901 2081 3F CC67 2018 2018-11-12 NO23 -2.3751557858 #> 8902 2081 3F CC67 2018 2018-11-12 SALIN -1.3862943611 #> 8903 2081 3F CC67 2018 2018-11-12 TKN -0.2484613593 #> 8904 2081 3F CC67 2018 2018-11-12 TN -0.1358197231 + #> 8905 2081 3F CC67 2018 2018-11-12 TP -2.8473122684 #> 8906 2081 3F CC67 2018 2018-11-12 TSS 2.1972245773 I #> 8907 2081 3F CC67 2018 2018-11-12 TURB 2.0014800002 A #> 8908 2065B 2 CC67 2013 2013-01-08 CHLAC 1.2809338455 #> 8909 2065B 2 CC67 2013 2013-01-08 COLOR 2.9957322736 #> 8910 2065B 2 CC67 2013 2013-01-08 COND 10.7359617983 #> 8911 2065B 2 CC67 2013 2013-01-08 DO 1.8870696490 #> 8912 2065B 2 CC67 2013 2013-01-08 DOSAT 4.4773368145 + #> 8913 2065B 2 CC67 2013 2013-01-08 NO23 -4.9618451299 I #> 8914 2065B 2 CC67 2013 2013-01-08 SALIN 3.3968546322 #> 8915 2065B 2 CC67 2013 2013-01-08 TKN -1.3093333200 #> 8916 2065B 2 CC67 2013 2013-01-08 TN -1.2837377728 #> 8917 2065B 2 CC67 2013 2013-01-08 TP -2.6172958378 #> 8918 2065B 2 CC67 2013 2013-01-08 TSS 0.9001613499 #> 8919 2065B 2 CC67 2013 2013-01-08 TURB -0.1053605157 #> 8920 2065B 2 CC67 2013 2013-01-08 COND 10.7368313636 #> 8921 2065B 2 CC67 2013 2013-01-08 DO 1.8946168547 #> 8922 2065B 2 CC67 2013 2013-01-08 DOSAT 4.4796069630 + #> 8923 2065B 2 CC67 2013 2013-01-08 SALIN 3.3981928726 #> 8924 2065B 2 CC67 2013 2013-01-08 COND 10.7435449784 #> 8925 2065B 2 CC67 2013 2013-01-08 DO 1.9021075264 #> 8926 2065B 2 CC67 2013 2013-01-08 DOSAT 4.4830025520 + #> 8927 2065B 2 CC67 2013 2013-01-08 SALIN 3.4055213531 #> 8928 2065B 2 CC67 2015 2015-04-07 CHLAC 0.6931471806 #> 8929 2065B 2 CC67 2015 2015-04-07 COLOR 3.4011973817 #> 8930 2065B 2 CC67 2015 2015-04-07 COND 10.6960274770 #> 8931 2065B 2 CC67 2015 2015-04-07 DO 1.8164520818 #> 8932 2065B 2 CC67 2015 2015-04-07 DOSAT 4.4931206822 + #> 8933 2065B 2 CC67 2015 2015-04-07 NO23 -5.1159958098 I #> 8934 2065B 2 CC67 2015 2015-04-07 SALIN 3.3492020865 #> 8935 2065B 2 CC67 2015 2015-04-07 TKN -0.2587707290 #> 8936 2065B 2 CC67 2015 2015-04-07 TN -0.2510287548 #> 8937 2065B 2 CC67 2015 2015-04-07 TP -2.4079456087 #> 8938 2065B 2 CC67 2015 2015-04-07 TSS 2.2257040487 #> 8939 2065B 2 CC67 2015 2015-04-07 TURB 0.2623642645 #> 8940 2065B 2 CC67 2015 2015-04-07 COND 10.6958011046 #> 8941 2065B 2 CC67 2015 2015-04-07 DO 1.8033586051 #> 8942 2065B 2 CC67 2015 2015-04-07 DOSAT 4.4796069630 + #> 8943 2065B 2 CC67 2015 2015-04-07 SALIN 3.3488509013 #> 8944 2065B 2 CC67 2015 2015-11-03 CHLAC 2.0476928434 #> 8945 2065B 2 CC67 2015 2015-11-03 COLOR 4.0073331852 #> 8946 2065B 2 CC67 2015 2015-11-03 COND 10.5339611386 #> 8947 2065B 2 CC67 2015 2015-11-03 DO 2.0731719287 #> 8948 2065B 2 CC67 2015 2015-11-03 DOSAT 4.7723781050 + #> 8949 2065B 2 CC67 2015 2015-11-03 NO23 -5.5214609179 U #> 8950 2065B 2 CC67 2015 2015-11-03 SALIN 3.1658969001 #> 8951 2065B 2 CC67 2015 2015-11-03 TKN -0.4557063245 #> 8952 2065B 2 CC67 2015 2015-11-03 TN -0.4557063245 #> 8953 2065B 2 CC67 2015 2015-11-03 TP -2.0557250151 #> 8954 2065B 2 CC67 2015 2015-11-03 TSS 1.7369512327 #> 8955 2065B 2 CC67 2015 2015-11-03 TURB -0.3566749439 #> 8956 2065B 2 CC67 2015 2015-11-03 COND 10.5312958918 #> 8957 2065B 2 CC67 2015 2015-11-03 DO 2.0955609236 #> 8958 2065B 2 CC67 2015 2015-11-03 DOSAT 4.7966166506 + #> 8959 2065B 2 CC67 2015 2015-11-03 SALIN 3.1629401925 #> 8960 2065B 2 CC67 2017 2017-04-05 CHLAC -0.0502412164 I #> 8961 2065B 2 CC67 2017 2017-04-05 COND 10.7904503955 #> 8962 2065B 2 CC67 2017 2017-04-05 DO 1.9586853405 #> 8963 2065B 2 CC67 2017 2017-04-05 DOSAT 4.6653241088 + #> 8964 2065B 2 CC67 2017 2017-04-05 NO23 -4.8283137373 I #> 8965 2065B 2 CC67 2017 2017-04-05 SALIN 3.4541060373 #> 8966 2065B 2 CC67 2017 2017-04-05 TKN -0.4261781497 #> 8967 2065B 2 CC67 2017 2017-04-05 TN -0.4140014391 #> 8968 2065B 2 CC67 2017 2017-04-05 TP -2.7030626596 #> 8969 2065B 2 CC67 2017 2017-04-05 TSS 2.1972245773 #> 8970 2065B 2 CC67 2017 2017-04-05 TURB 0.0000000000 #> 8971 2065B 2 CC67 2017 2017-04-05 COND 10.7904771690 #> 8972 2065B 2 CC67 2017 2017-04-05 DO 1.9699056546 #> 8973 2065B 2 CC67 2017 2017-04-05 DOSAT 4.6784206477 + #> 8974 2065B 2 CC67 2017 2017-04-05 SALIN 3.4541060373 #> 8975 2065B 2 CC67 2017 2017-04-05 COND 10.7905760186 #> 8976 2065B 2 CC67 2017 2017-04-05 DO 1.9712993831 #> 8977 2065B 2 CC67 2017 2017-04-05 DOSAT 4.6802776585 + #> 8978 2065B 2 CC67 2017 2017-04-05 SALIN 3.4541060373 #> 8979 2065B 2 CC67 2017 2017-04-05 COND 10.7905821964 #> 8980 2065B 2 CC67 2017 2017-04-05 DO 1.9726911717 #> 8981 2065B 2 CC67 2017 2017-04-05 DOSAT 4.6812048723 + #> 8982 2065B 2 CC67 2017 2017-04-05 SALIN 3.4541060373 #> 8983 2065B 2 CC67 2017 2017-06-05 CHLAC 1.3686394259 #> 8984 2065B 2 CC67 2017 2017-06-05 NO23 -4.1351665567 #> 8985 2065B 2 CC67 2017 2017-06-05 TKN -0.2600669054 #> 8986 2065B 2 CC67 2017 2017-06-05 TN -0.2395270306 #> 8987 2065B 2 CC67 2017 2017-06-05 TP -2.5770219387 #> 8988 2065B 2 CC67 2017 2017-06-05 TSS 2.4595888418 #> 8989 2065B 2 CC67 2017 2017-06-05 TURB 0.0000000000 #> 8990 2065B 2 CC67 2017 2017-06-05 COND 10.8045448425 #> 8991 2065B 2 CC67 2017 2017-06-05 DO 1.6134299337 #> 8992 2065B 2 CC67 2017 2017-06-05 DOSAT 4.3592696476 + #> 8993 2065B 2 CC67 2017 2017-06-05 SALIN 3.4679210137 #> 8994 2065B 2 CC67 2017 2017-06-05 COND 10.8049143616 #> 8995 2065B 2 CC67 2017 2017-06-05 DO 1.6524974019 #> 8996 2065B 2 CC67 2017 2017-06-05 DOSAT 4.3981460166 + #> 8997 2065B 2 CC67 2017 2017-06-05 SALIN 3.4682327830 #> 8998 2065B 2 CC67 2017 2017-06-05 COND 10.8052533058 #> 8999 2065B 2 CC67 2017 2017-06-05 DO 1.6677068206 #> 9000 2065B 2 CC67 2017 2017-06-05 DOSAT 4.4140096805 + #> 9001 2065B 2 CC67 2017 2017-06-05 SALIN 3.4685444551 #> 9002 2065B 2 CC67 2017 2017-08-15 CHLAC 2.7850112422 #> 9003 2065B 2 CC67 2017 2017-08-15 COND 10.0070409363 #> 9004 2065B 2 CC67 2017 2017-08-15 DO 1.7474592103 #> 9005 2065B 2 CC67 2017 2017-08-15 DOSAT 4.4693504628 + #> 9006 2065B 2 CC67 2017 2017-08-15 NO23 -3.2968373663 #> 9007 2065B 2 CC67 2017 2017-08-15 SALIN 2.5794589667 #> 9008 2065B 2 CC67 2017 2017-08-15 TKN 0.0953101798 #> 9009 2065B 2 CC67 2017 2017-08-15 TN 0.1310282624 #> 9010 2065B 2 CC67 2017 2017-08-15 TP -1.0555527992 #> 9011 2065B 2 CC67 2017 2017-08-15 TSS 0.8458682676 #> 9012 2065B 2 CC67 2017 2017-08-15 TURB 0.6931471806 #> 9013 2065B 2 CC67 2017 2017-08-15 COND 10.1682757999 #> 9014 2065B 2 CC67 2017 2017-08-15 DO 0.5822156199 #> 9015 2065B 2 CC67 2017 2017-08-15 DOSAT 3.2771447330 + #> 9016 2065B 2 CC67 2017 2017-08-15 SALIN 2.7593768283 #> 9017 2065B 2 CC67 2017 2017-08-15 COND 10.1784604545 #> 9018 2065B 2 CC67 2017 2017-08-15 DO 0.5306282511 #> 9019 2065B 2 CC67 2017 2017-08-15 DOSAT 3.2268439945 + #> 9020 2065B 2 CC67 2017 2017-08-15 SALIN 2.7707119622 #> 9021 2065B 2 CC67 2018 2018-04-09 CHLAC 0.8109302162 #> 9022 2065B 2 CC67 2018 2018-04-09 COND 10.7756173069 #> 9023 2065B 2 CC67 2018 2018-04-09 DO 1.9387416596 #> 9024 2065B 2 CC67 2018 2018-04-09 DOSAT 4.6395716127 + #> 9025 2065B 2 CC67 2018 2018-04-09 NO23 -4.8283137373 I #> 9026 2065B 2 CC67 2018 2018-04-09 SALIN 3.4375293109 #> 9027 2065B 2 CC67 2018 2018-04-09 TKN -0.3945251681 #> 9028 2065B 2 CC67 2018 2018-04-09 TN -0.3827256211 #> 9029 2065B 2 CC67 2018 2018-04-09 TP -2.5902671654 #> 9030 2065B 2 CC67 2018 2018-04-09 TSS 1.4816045409 #> 9031 2065B 2 CC67 2018 2018-04-09 TURB 0.0953101798 #> 9032 2065B 2 CC67 2018 2018-04-09 COND 10.7754082549 #> 9033 2065B 2 CC67 2018 2018-04-09 DO 1.9473377010 #> 9034 2065B 2 CC67 2018 2018-04-09 DOSAT 4.6482296754 + #> 9035 2065B 2 CC67 2018 2018-04-09 SALIN 3.4375293109 #> 9036 2065B 2 CC67 2018 2018-04-09 COND 10.7754082549 #> 9037 2065B 2 CC67 2018 2018-04-09 DO 1.9487632180 #> 9038 2065B 2 CC67 2018 2018-04-09 DOSAT 4.6501435516 + #> 9039 2065B 2 CC67 2018 2018-04-09 SALIN 3.4375293109 #> 9040 2065B 2 CC67 2018 2018-05-23 CHLAC 1.1216775616 #> 9041 2065B 2 CC67 2018 2018-05-23 COND 10.7435212354 #> 9042 2065B 2 CC67 2018 2018-05-23 DO 1.8885836539 #> 9043 2065B 2 CC67 2018 2018-05-23 DOSAT 4.5910712616 + #> 9044 2065B 2 CC67 2018 2018-05-23 NO23 -4.6051701860 I #> 9045 2065B 2 CC67 2018 2018-05-23 SALIN 3.4011973817 #> 9046 2065B 2 CC67 2018 2018-05-23 TKN -0.1696027844 #> 9047 2065B 2 CC67 2018 2018-05-23 TN -0.1578240852 #> 9048 2065B 2 CC67 2018 2018-05-23 TP -2.0794415417 #> 9049 2065B 2 CC67 2018 2018-05-23 TSS 1.5686159179 #> 9050 2065B 2 CC67 2018 2018-05-23 TURB 1.0647107370 #> 9051 2065B 2 CC67 2018 2018-05-23 DOSAT 4.6793495842 + #> 9052 2065B 2 CC67 2018 2018-05-23 COND 10.7527727226 #> 9053 2065B 2 CC67 2018 2018-05-23 DO 1.9782390362 #> 9054 2065B 2 CC67 2018 2018-05-23 SALIN 3.4118075608 #> 9055 2065B 2 CC67 2018 2018-10-11 CHLAC 1.4109869737 #> 9056 2065B 2 CC67 2018 2018-10-11 COND 10.5316641186 #> 9057 2065B 2 CC67 2018 2018-10-11 DO 1.6467336972 #> 9058 2065B 2 CC67 2018 2018-10-11 DOSAT 4.3148178850 + #> 9059 2065B 2 CC67 2018 2018-10-11 NO23 -4.9618451299 I #> 9060 2065B 2 CC67 2018 2018-10-11 SALIN 3.1654750481 #> 9061 2065B 2 CC67 2018 2018-10-11 TKN -0.1960148839 #> 9062 2065B 2 CC67 2018 2018-10-11 TN -0.1875351238 #> 9063 2065B 2 CC67 2018 2018-10-11 TP -2.1202635362 #> 9064 2065B 2 CC67 2018 2018-10-11 TSS 1.8453002362 #> 9065 2065B 2 CC67 2018 2018-10-11 TURB 0.6931471806 #> 9066 2065B 2 CC67 2018 2018-10-11 COND 10.5317548204 #> 9067 2065B 2 CC67 2018 2018-10-11 DO 1.6448050563 #> 9068 2065B 2 CC67 2018 2018-10-11 DOSAT 4.3121405072 + #> 9069 2065B 2 CC67 2018 2018-10-11 SALIN 3.1654750481 #> 9070 2065B 2 CC67 2018 2018-10-11 COND 10.5326214074 #> 9071 2065B 2 CC67 2018 2018-10-11 DO 1.6370530795 #> 9072 2065B 2 CC67 2018 2018-10-11 DOSAT 4.3054155323 + #> 9073 2065B 2 CC67 2018 2018-10-11 SALIN 3.1663185741 #> 9074 2065B 2 CC67 2019 2019-03-05 CHLAC 1.6094379124 #> 9075 2065B 2 CC67 2019 2019-03-05 COND 10.4627604245 #> 9076 2065B 2 CC67 2019 2019-03-05 DO 1.8325814637 #> 9077 2065B 2 CC67 2019 2019-03-05 DOSAT 4.5163389723 + #> 9078 2065B 2 CC67 2019 2019-03-05 NO23 -5.1159958098 U #> 9079 2065B 2 CC67 2019 2019-03-05 SALIN 3.5550051456 #> 9080 2065B 2 CC67 2019 2019-03-05 TKN -0.2691874898 #> 9081 2065B 2 CC67 2019 2019-03-05 TN -0.2691874898 #> 9082 2065B 2 CC67 2019 2019-03-05 TP -2.3644604967 #> 9083 2065B 2 CC67 2019 2019-03-05 TSS 1.9919755159 #> 9084 2065B 2 CC67 2019 2019-03-05 TURB 0.8754687374 #> 9085 2065B 2 CC67 2019 2019-03-05 COND 10.4628461645 #> 9086 2065B 2 CC67 2019 2019-03-05 DO 1.8309801824 #> 9087 2065B 2 CC67 2019 2019-03-05 DOSAT 4.5152454785 + #> 9088 2065B 2 CC67 2019 2019-03-05 SALIN 3.5550908856 #> 9089 2065B 2 CC67 2019 2019-03-05 COND 10.4631604817 #> 9090 2065B 2 CC67 2019 2019-03-05 DO 1.8277699068 #> newComment disqual disqual2 #> 1 I NA NA #> 2 U NA NA #> 3 + NA NA #> 4 NA NA #> 5 NA NA #> 6 NA NA #> 7 + NA NA #> 8 NA NA #> 9 NA NA #> 10 I NA NA #> 11 I NA NA #> 12 NA NA #> 13 NA NA #> 14 NA NA #> 15 + NA NA #> 16 NA NA #> 17 NA NA #> 18 I NA NA #> 19 I NA NA #> 20 I NA NA #> 21 NA NA #> 22 NA NA #> 23 + NA NA #> 24 NA NA #> 25 NA NA #> 26 NA NA #> 27 NA NA #> 28 I NA NA #> 29 + NA NA #> 30 A NA NA #> 31 NA NA #> 32 NA NA #> 33 NA NA #> 34 + 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 NA NA #> 44 NA NA #> 45 + NA NA #> 46 NA NA #> 47 NA NA #> 48 NA NA #> 49 U NA NA #> 50 NA NA #> 51 + NA NA #> 52 I NA NA #> 53 NA NA #> 54 NA NA #> 55 + NA NA #> 56 NA NA #> 57 NA NA #> 58 NA NA #> 59 U NA NA #> 60 + NA NA #> 61 U NA NA #> 62 NA NA #> 63 NA NA #> 64 + NA NA #> 65 NA NA #> 66 NA NA #> 67 I NA NA #> 68 U NA NA #> 69 NA NA #> 70 + NA NA #> 71 I NA NA #> 72 NA NA #> 73 NA NA #> 74 + NA NA #> 75 NA NA #> 76 NA NA #> 77 NA NA #> 78 NA NA #> 79 NA NA #> 80 + NA NA #> 81 I NA NA #> 82 NA NA #> 83 NA NA #> 84 + NA NA #> 85 NA NA #> 86 A NA NA #> 87 NA NA #> 88 NA NA #> 89 NA NA #> 90 + NA NA #> 91 I NA NA #> 92 NA NA #> 93 NA NA #> 94 + NA NA #> 95 NA NA #> 96 NA NA #> 97 NA NA #> 98 NA NA #> 99 NA NA #> 100 U NA NA #> 101 NA NA #> 102 + NA NA #> 103 NA NA #> 104 NA NA #> 105 NA NA #> 106 NA NA #> 107 NA NA #> 108 + NA NA #> 109 U NA NA #> 110 NA NA #> 111 + NA NA #> 112 NA NA #> 113 NA NA #> 114 NA NA #> 115 NA NA #> 116 + NA NA #> 117 I 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 NA NA #> 128 NA NA #> 129 + NA NA #> 130 NA NA #> 131 NA NA #> 132 A NA NA #> 133 A 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 A 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 I NA NA #> 155 NA NA #> 156 NA NA #> 157 + NA NA #> 158 NA NA #> 159 NA NA #> 160 I NA NA #> 161 U NA NA #> 162 NA NA #> 163 + NA NA #> 164 I NA NA #> 165 NA NA #> 166 I NA NA #> 167 + NA NA #> 168 NA NA #> 169 NA NA #> 170 NA NA #> 171 NA NA #> 172 NA NA #> 173 + NA NA #> 174 U 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 U NA NA #> 185 NA NA #> 186 I NA NA #> 187 + 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 + NA NA #> 204 NA NA #> 205 NA NA #> 206 NA NA #> 207 + NA NA #> 208 NA NA #> 209 NA NA #> 210 NA NA #> 211 NA NA #> 212 NA NA #> 213 + NA NA #> 214 NA NA #> 215 NA NA #> 216 NA NA #> 217 + 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 + NA NA #> 238 NA NA #> 239 NA NA #> 240 NA NA #> 241 NA NA #> 242 NA NA #> 243 + NA NA #> 244 I 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 + NA NA #> 254 NA NA #> 255 NA NA #> 256 NA NA #> 257 + NA NA #> 258 NA NA #> 259 NA NA #> 260 I NA NA #> 261 NA NA #> 262 NA NA #> 263 + NA NA #> 264 U NA NA #> 265 NA NA #> 266 I NA NA #> 267 + NA NA #> 268 NA NA #> 269 NA NA #> 270 NA NA #> 271 NA NA #> 272 NA NA #> 273 + NA NA #> 274 I NA NA #> 275 NA NA #> 276 NA NA #> 277 + 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 + NA NA #> 288 NA NA #> 289 NA NA #> 290 NA NA #> 291 NA NA #> 292 NA NA #> 293 + NA NA #> 294 I NA NA #> 295 NA NA #> 296 NA NA #> 297 + NA NA #> 298 NA NA #> 299 NA NA #> 300 NA NA #> 301 NA NA #> 302 NA NA #> 303 + NA NA #> 304 NA NA #> 305 NA NA #> 306 NA NA #> 307 + NA NA #> 308 NA NA #> 309 NA NA #> 310 I NA NA #> 311 U NA NA #> 312 NA NA #> 313 + NA NA #> 314 I NA NA #> 315 NA NA #> 316 NA NA #> 317 + NA NA #> 318 NA NA #> 319 NA NA #> 320 NA NA #> 321 I NA NA #> 322 NA NA #> 323 + NA NA #> 324 NA NA #> 325 NA NA #> 326 NA NA #> 327 + NA NA #> 328 NA NA #> 329 NA NA #> 330 I NA NA #> 331 U NA NA #> 332 NA NA #> 333 + NA NA #> 334 U NA NA #> 335 NA NA #> 336 NA NA #> 337 + NA NA #> 338 NA NA #> 339 NA NA #> 340 NA NA #> 341 NA NA #> 342 + NA NA #> 343 NA NA #> 344 I NA NA #> 345 NA NA #> 346 NA NA #> 347 + NA NA #> 348 I 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 A NA NA #> 359 NA NA #> 360 + NA NA #> 361 I NA NA #> 362 NA NA #> 363 NA NA #> 364 + NA NA #> 365 NA NA #> 366 NA NA #> 367 NA NA #> 368 NA NA #> 369 NA NA #> 370 + NA NA #> 371 NA NA #> 372 NA NA #> 373 NA NA #> 374 + NA NA #> 375 NA NA #> 376 A NA NA #> 377 NA NA #> 378 NA NA #> 379 I NA NA #> 380 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 NA NA #> 391 + NA NA #> 392 NA NA #> 393 NA NA #> 394 I NA NA #> 395 NA NA #> 396 NA NA #> 397 + NA NA #> 398 I NA NA #> 399 NA NA #> 400 NA NA #> 401 + NA NA #> 402 NA NA #> 403 NA NA #> 404 I NA NA #> 405 NA NA #> 406 NA NA #> 407 + NA NA #> 408 NA NA #> 409 NA NA #> 410 NA NA #> 411 + NA NA #> 412 NA NA #> 413 NA NA #> 414 NA NA #> 415 NA NA #> 416 NA NA #> 417 + NA NA #> 418 NA NA #> 419 NA NA #> 420 NA NA #> 421 + NA NA #> 422 NA NA #> 423 A NA NA #> 424 I NA NA #> 425 NA NA #> 426 NA NA #> 427 + NA NA #> 428 U NA NA #> 429 NA NA #> 430 NA NA #> 431 + NA NA #> 432 NA NA #> 433 NA NA #> 434 I NA NA #> 435 I NA NA #> 436 + NA NA #> 437 U NA NA #> 438 NA NA #> 439 NA NA #> 440 + NA NA #> 441 NA NA #> 442 NA NA #> 443 NA NA #> 444 NA NA #> 445 NA NA #> 446 NA NA #> 447 U NA NA #> 448 NA NA #> 449 NA NA #> 450 + NA NA #> 451 NA NA #> 452 NA NA #> 453 NA NA #> 454 NA NA #> 455 NA NA #> 456 NA NA #> 457 NA NA #> 458 NA NA #> 459 NA NA #> 460 + NA NA #> 461 NA NA #> 462 NA NA #> 463 NA NA #> 464 NA NA #> 465 NA NA #> 466 NA NA #> 467 I NA NA #> 468 NA NA #> 469 NA NA #> 470 + NA NA #> 471 NA NA #> 472 NA NA #> 473 I NA NA #> 474 NA NA #> 475 NA NA #> 476 NA NA #> 477 NA NA #> 478 NA NA #> 479 NA NA #> 480 + NA NA #> 481 NA NA #> 482 NA NA #> 483 I NA NA #> 484 NA NA #> 485 NA NA #> 486 NA NA #> 487 I NA NA #> 488 NA NA #> 489 + NA NA #> 490 NA NA #> 491 NA NA #> 492 NA NA #> 493 NA NA #> 494 NA NA #> 495 NA NA #> 496 I NA NA #> 497 NA NA #> 498 I NA NA #> 499 + NA NA #> 500 NA NA #> 501 NA NA #> 502 I NA NA #> 503 I NA NA #> 504 NA NA #> 505 NA NA #> 506 I NA NA #> 507 NA NA #> 508 NA NA #> 509 + NA NA #> 510 NA NA #> 511 NA NA #> 512 I NA NA #> 513 NA NA #> 514 NA NA #> 515 NA NA #> 516 I NA NA #> 517 NA NA #> 518 NA NA #> 519 + NA NA #> 520 NA NA #> 521 NA NA #> 522 NA NA #> 523 I NA NA #> 524 NA NA #> 525 NA NA #> 526 I NA NA #> 527 NA NA #> 528 NA NA #> 529 + NA NA #> 530 NA NA #> 531 NA NA #> 532 NA NA #> 533 I NA NA #> 534 NA NA #> 535 NA NA #> 536 NA NA #> 537 NA NA #> 538 NA NA #> 539 + NA NA #> 540 NA NA #> 541 NA NA #> 542 NA NA #> 543 I NA NA #> 544 NA NA #> 545 NA NA #> 546 + NA NA #> 547 NA NA #> 548 NA NA #> 549 I NA NA #> 550 U NA NA #> 551 I NA NA #> 552 NA NA #> 553 + NA NA #> 554 NA NA #> 555 NA NA #> 556 I 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 U NA NA #> 567 I NA NA #> 568 NA NA #> 569 NA NA #> 570 NA NA #> 571 NA NA #> 572 NA NA #> 573 + NA NA #> 574 NA NA #> 575 NA NA #> 576 I NA NA #> 577 I NA NA #> 578 NA NA #> 579 NA NA #> 580 U NA NA #> 581 NA NA #> 582 I NA NA #> 583 + NA NA #> 584 NA NA #> 585 NA NA #> 586 I NA NA #> 587 I NA NA #> 588 NA NA #> 589 NA NA #> 590 NA NA #> 591 + NA NA #> 592 NA NA #> 593 A NA NA #> 594 I NA NA #> 595 I NA NA #> 596 NA NA #> 597 NA NA #> 598 U NA NA #> 599 NA NA #> 600 I NA NA #> 601 + NA NA #> 602 NA NA #> 603 NA NA #> 604 NA NA #> 605 I NA NA #> 606 NA NA #> 607 NA NA #> 608 U NA NA #> 609 NA NA #> 610 NA NA #> 611 + NA NA #> 612 NA NA #> 613 NA NA #> 614 NA NA #> 615 NA NA #> 616 NA NA #> 617 NA NA #> 618 I NA NA #> 619 NA NA #> 620 NA NA #> 621 + NA NA #> 622 NA NA #> 623 NA NA #> 624 NA NA #> 625 NA NA #> 626 NA NA #> 627 NA NA #> 628 NA NA #> 629 NA NA #> 630 NA NA #> 631 + NA NA #> 632 NA NA #> 633 NA NA #> 634 NA NA #> 635 NA NA #> 636 NA NA #> 637 NA NA #> 638 U NA NA #> 639 NA NA #> 640 NA NA #> 641 + NA NA #> 642 NA NA #> 643 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 NA NA #> 654 I NA NA #> 655 U NA NA #> 656 NA NA #> 657 NA NA #> 658 I NA NA #> 659 NA NA #> 660 NA NA #> 661 + NA NA #> 662 NA NA #> 663 NA NA #> 664 I NA NA #> 665 U NA NA #> 666 NA NA #> 667 NA NA #> 668 I NA NA #> 669 NA NA #> 670 I NA NA #> 671 + NA NA #> 672 NA NA #> 673 A NA NA #> 674 I NA NA #> 675 U NA NA #> 676 NA NA #> 677 NA NA #> 678 I NA NA #> 679 NA NA #> 680 NA NA #> 681 + NA NA #> 682 NA NA #> 683 NA NA #> 684 I NA NA #> 685 U NA NA #> 686 NA NA #> 687 NA NA #> 688 U NA NA #> 689 NA NA #> 690 + NA NA #> 691 NA NA #> 692 NA NA #> 693 I NA NA #> 694 U NA NA #> 695 NA NA #> 696 NA NA #> 697 U NA NA #> 698 NA NA #> 699 NA NA #> 700 + NA NA #> 701 NA NA #> 702 NA NA #> 703 I NA NA #> 704 U NA NA #> 705 NA NA #> 706 NA NA #> 707 U NA NA #> 708 NA NA #> 709 NA NA #> 710 + NA NA #> 711 NA NA #> 712 NA NA #> 713 I NA NA #> 714 I NA NA #> 715 NA NA #> 716 NA NA #> 717 NA NA #> 718 + NA NA #> 719 NA NA #> 720 NA NA #> 721 I NA NA #> 722 U NA NA #> 723 + NA NA #> 724 NA NA #> 725 NA NA #> 726 NA NA #> 727 + NA NA #> 728 NA NA #> 729 NA NA #> 730 I NA NA #> 731 I NA NA #> 732 I NA NA #> 733 NA NA #> 734 NA NA #> 735 + NA NA #> 736 NA NA #> 737 NA NA #> 738 I NA NA #> 739 U NA NA #> 740 NA NA #> 741 + NA NA #> 742 I NA NA #> 743 NA NA #> 744 NA NA #> 745 + NA NA #> 746 NA NA #> 747 NA NA #> 748 NA NA #> 749 NA NA #> 750 + NA NA #> 751 NA NA #> 752 NA NA #> 753 NA NA #> 754 + NA NA #> 755 NA NA #> 756 A NA NA #> 757 NA NA #> 758 NA NA #> 759 + NA NA #> 760 I 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 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 NA NA #> 794 NA NA #> 795 NA NA #> 796 NA NA #> 797 NA NA #> 798 I NA NA #> 799 NA NA #> 800 NA NA #> 801 + NA NA #> 802 NA NA #> 803 A NA NA #> 804 NA NA #> 805 A 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 I NA NA #> 816 NA NA #> 817 I NA NA #> 818 NA NA #> 819 NA NA #> 820 + NA NA #> 821 NA NA #> 822 NA NA #> 823 NA NA #> 824 I NA NA #> 825 NA NA #> 826 + NA NA #> 827 I NA NA #> 828 NA NA #> 829 NA NA #> 830 + NA NA #> 831 NA NA #> 832 NA NA #> 833 NA NA #> 834 NA NA #> 835 + NA NA #> 836 I NA NA #> 837 NA NA #> 838 NA NA #> 839 + NA NA #> 840 NA NA #> 841 NA NA #> 842 NA NA #> 843 NA NA #> 844 NA NA #> 845 + NA NA #> 846 I NA NA #> 847 NA NA #> 848 NA NA #> 849 + NA NA #> 850 NA NA #> 851 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 I 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 I NA NA #> 871 I NA NA #> 872 NA NA #> 873 I 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 NA NA #> 885 NA NA #> 886 + NA NA #> 887 NA NA #> 888 NA NA #> 889 NA NA #> 890 NA NA #> 891 NA NA #> 892 NA NA #> 893 NA NA #> 894 NA NA #> 895 + NA NA #> 896 NA NA #> 897 NA NA #> 898 NA NA #> 899 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 A NA NA #> 915 I 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 A NA NA #> 926 NA NA #> 927 + NA NA #> 928 I NA NA #> 929 NA NA #> 930 NA NA #> 931 + NA NA #> 932 NA NA #> 933 NA NA #> 934 NA NA #> 935 NA NA #> 936 NA NA #> 937 + NA NA #> 938 NA NA #> 939 NA NA #> 940 NA NA #> 941 + NA NA #> 942 NA NA #> 943 NA NA #> 944 NA NA #> 945 NA NA #> 946 NA NA #> 947 NA NA #> 948 NA NA #> 949 + NA NA #> 950 NA NA #> 951 NA NA #> 952 I NA NA #> 953 NA NA #> 954 NA NA #> 955 + NA NA #> 956 NA NA #> 957 NA NA #> 958 NA NA #> 959 + NA NA #> 960 NA NA #> 961 A NA NA #> 962 I NA NA #> 963 NA NA #> 964 NA NA #> 965 + NA NA #> 966 I NA NA #> 967 NA NA #> 968 NA NA #> 969 + NA NA #> 970 NA NA #> 971 NA NA #> 972 I NA NA #> 973 NA NA #> 974 NA NA #> 975 + NA NA #> 976 I NA NA #> 977 NA NA #> 978 NA NA #> 979 + 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 + 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 I NA NA #> 1013 U NA NA #> 1014 NA NA #> 1015 + NA NA #> 1016 NA NA #> 1017 NA NA #> 1018 NA NA #> 1019 + NA NA #> 1020 NA NA #> 1021 A NA NA #> 1022 NA NA #> 1023 I NA NA #> 1024 NA NA #> 1025 + NA NA #> 1026 NA NA #> 1027 NA NA #> 1028 NA NA #> 1029 + NA NA #> 1030 NA NA #> 1031 NA NA #> 1032 NA NA #> 1033 A NA NA #> 1034 NA NA #> 1035 + NA NA #> 1036 NA NA #> 1037 NA NA #> 1038 NA NA #> 1039 + NA NA #> 1040 NA NA #> 1041 NA NA #> 1042 I NA NA #> 1043 NA NA #> 1044 NA NA #> 1045 + NA NA #> 1046 I NA NA #> 1047 NA NA #> 1048 NA NA #> 1049 + NA NA #> 1050 NA NA #> 1051 NA NA #> 1052 NA NA #> 1053 NA NA #> 1054 NA NA #> 1055 + NA NA #> 1056 I NA NA #> 1057 NA NA #> 1058 NA NA #> 1059 + NA NA #> 1060 NA NA #> 1061 NA NA #> 1062 NA NA #> 1063 I NA NA #> 1064 NA NA #> 1065 + NA NA #> 1066 U NA NA #> 1067 NA NA #> 1068 NA NA #> 1069 + NA NA #> 1070 NA NA #> 1071 NA NA #> 1072 NA NA #> 1073 NA NA #> 1074 NA NA #> 1075 + NA NA #> 1076 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 NA NA #> 1087 NA NA #> 1088 NA NA #> 1089 + NA NA #> 1090 NA NA #> 1091 NA NA #> 1092 NA NA #> 1093 NA NA #> 1094 I NA NA #> 1095 NA NA #> 1096 + NA NA #> 1097 NA NA #> 1098 NA NA #> 1099 NA NA #> 1100 NA NA #> 1101 NA NA #> 1102 + NA NA #> 1103 NA NA #> 1104 NA NA #> 1105 NA NA #> 1106 + NA NA #> 1107 NA NA #> 1108 A NA NA #> 1109 NA NA #> 1110 NA NA #> 1111 NA NA #> 1112 + NA NA #> 1113 I NA NA #> 1114 NA NA #> 1115 NA NA #> 1116 + NA NA #> 1117 NA NA #> 1118 A NA NA #> 1119 NA NA #> 1120 NA NA #> 1121 NA NA #> 1122 + NA NA #> 1123 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 NA NA #> 1132 + NA NA #> 1133 NA NA #> 1134 NA NA #> 1135 NA NA #> 1136 + NA NA #> 1137 NA NA #> 1138 NA NA #> 1139 NA NA #> 1140 NA NA #> 1141 NA NA #> 1142 + NA NA #> 1143 I NA NA #> 1144 NA NA #> 1145 NA NA #> 1146 + NA NA #> 1147 NA NA #> 1148 A NA NA #> 1149 A NA NA #> 1150 I NA NA #> 1151 NA NA #> 1152 + NA NA #> 1153 NA NA #> 1154 NA NA #> 1155 NA NA #> 1156 + NA NA #> 1157 NA NA #> 1158 NA NA #> 1159 NA NA #> 1160 NA NA #> 1161 NA NA #> 1162 NA NA #> 1163 I NA NA #> 1164 NA NA #> 1165 NA NA #> 1166 + NA NA #> 1167 NA NA #> 1168 NA NA #> 1169 NA NA #> 1170 NA NA #> 1171 NA NA #> 1172 NA NA #> 1173 I NA NA #> 1174 NA NA #> 1175 NA NA #> 1176 + NA NA #> 1177 NA NA #> 1178 NA NA #> 1179 A NA NA #> 1180 NA NA #> 1181 NA NA #> 1182 I NA NA #> 1183 NA NA #> 1184 NA NA #> 1185 + NA NA #> 1186 NA NA #> 1187 A NA NA #> 1188 I NA NA #> 1189 NA NA #> 1190 NA NA #> 1191 NA NA #> 1192 NA NA #> 1193 NA NA #> 1194 NA NA #> 1195 + NA NA #> 1196 NA NA #> 1197 NA NA #> 1198 I NA NA #> 1199 NA NA #> 1200 I NA NA #> 1201 NA NA #> 1202 NA NA #> 1203 + NA NA #> 1204 NA NA #> 1205 NA NA #> 1206 I NA NA #> 1207 NA NA #> 1208 U NA NA #> 1209 NA NA #> 1210 + NA NA #> 1211 NA NA #> 1212 NA NA #> 1213 I NA NA #> 1214 NA NA #> 1215 NA NA #> 1216 NA NA #> 1217 I NA NA #> 1218 NA NA #> 1219 NA NA #> 1220 + NA NA #> 1221 NA NA #> 1222 NA NA #> 1223 I NA NA #> 1224 I NA NA #> 1225 NA NA #> 1226 NA NA #> 1227 NA NA #> 1228 NA NA #> 1229 NA NA #> 1230 + NA NA #> 1231 NA NA #> 1232 NA NA #> 1233 I NA NA #> 1234 NA NA #> 1235 I 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 I NA NA #> 1246 NA NA #> 1247 NA NA #> 1248 + NA NA #> 1249 NA NA #> 1250 NA NA #> 1251 NA NA #> 1252 I NA NA #> 1253 NA NA #> 1254 NA NA #> 1255 I NA NA #> 1256 NA NA #> 1257 NA NA #> 1258 + NA NA #> 1259 NA NA #> 1260 NA NA #> 1261 NA NA #> 1262 I NA NA #> 1263 NA NA #> 1264 NA NA #> 1265 NA NA #> 1266 NA NA #> 1267 NA NA #> 1268 + NA NA #> 1269 NA NA #> 1270 NA NA #> 1271 I NA NA #> 1272 U NA NA #> 1273 NA NA #> 1274 NA NA #> 1275 NA NA #> 1276 NA NA #> 1277 NA NA #> 1278 + NA NA #> 1279 NA NA #> 1280 NA NA #> 1281 I NA NA #> 1282 NA NA #> 1283 NA NA #> 1284 NA NA #> 1285 NA NA #> 1286 + NA NA #> 1287 NA NA #> 1288 NA NA #> 1289 I NA NA #> 1290 NA NA #> 1291 NA NA #> 1292 NA NA #> 1293 NA NA #> 1294 NA NA #> 1295 NA NA #> 1296 + NA NA #> 1297 NA NA #> 1298 NA NA #> 1299 I NA NA #> 1300 U NA NA #> 1301 NA NA #> 1302 NA NA #> 1303 I NA NA #> 1304 NA NA #> 1305 + NA NA #> 1306 NA NA #> 1307 A NA NA #> 1308 NA NA #> 1309 A NA NA #> 1310 NA NA #> 1311 NA NA #> 1312 NA NA #> 1313 NA NA #> 1314 NA NA #> 1315 + NA NA #> 1316 NA NA #> 1317 NA NA #> 1318 I NA NA #> 1319 A NA NA #> 1320 NA NA #> 1321 NA NA #> 1322 NA NA #> 1323 NA NA #> 1324 NA NA #> 1325 + NA NA #> 1326 NA NA #> 1327 A NA NA #> 1328 + NA NA #> 1329 NA NA #> 1330 NA NA #> 1331 NA NA #> 1332 NA NA #> 1333 NA NA #> 1334 NA NA #> 1335 NA NA #> 1336 NA NA #> 1337 NA NA #> 1338 U NA NA #> 1339 NA NA #> 1340 NA NA #> 1341 NA NA #> 1342 NA NA #> 1343 NA NA #> 1344 + NA NA #> 1345 NA NA #> 1346 NA NA #> 1347 I NA NA #> 1348 U NA NA #> 1349 NA NA #> 1350 NA NA #> 1351 I NA NA #> 1352 NA NA #> 1353 NA NA #> 1354 + NA NA #> 1355 NA NA #> 1356 NA NA #> 1357 I NA NA #> 1358 I NA NA #> 1359 NA NA #> 1360 NA NA #> 1361 I NA NA #> 1362 NA NA #> 1363 NA NA #> 1364 + NA NA #> 1365 NA NA #> 1366 NA NA #> 1367 I NA NA #> 1368 I NA NA #> 1369 I NA NA #> 1370 NA NA #> 1371 + NA NA #> 1372 NA NA #> 1373 NA NA #> 1374 + NA NA #> 1375 I NA NA #> 1376 NA NA #> 1377 NA NA #> 1378 NA NA #> 1379 I NA NA #> 1380 NA NA #> 1381 I NA NA #> 1382 NA NA #> 1383 NA NA #> 1384 I NA NA #> 1385 NA NA #> 1386 NA NA #> 1387 NA NA #> 1388 I NA NA #> 1389 NA NA #> 1390 NA NA #> 1391 + NA NA #> 1392 NA NA #> 1393 NA NA #> 1394 I NA NA #> 1395 I NA NA #> 1396 NA NA #> 1397 NA NA #> 1398 I NA NA #> 1399 NA NA #> 1400 NA NA #> 1401 + NA NA #> 1402 NA NA #> 1403 NA NA #> 1404 NA NA #> 1405 NA NA #> 1406 NA NA #> 1407 NA NA #> 1408 U NA NA #> 1409 NA NA #> 1410 NA NA #> 1411 + NA NA #> 1412 NA NA #> 1413 NA NA #> 1414 NA NA #> 1415 NA NA #> 1416 NA NA #> 1417 NA NA #> 1418 I NA NA #> 1419 NA NA #> 1420 NA NA #> 1421 + NA NA #> 1422 NA NA #> 1423 NA NA #> 1424 NA NA #> 1425 NA NA #> 1426 NA NA #> 1427 NA NA #> 1428 I NA NA #> 1429 NA NA #> 1430 NA NA #> 1431 + NA NA #> 1432 NA NA #> 1433 A NA NA #> 1434 NA NA #> 1435 NA NA #> 1436 NA NA #> 1437 NA NA #> 1438 NA NA #> 1439 NA NA #> 1440 NA NA #> 1441 + NA NA #> 1442 NA NA #> 1443 NA NA #> 1444 I NA NA #> 1445 U NA NA #> 1446 NA NA #> 1447 NA NA #> 1448 I NA NA #> 1449 NA NA #> 1450 NA NA #> 1451 + NA NA #> 1452 NA NA #> 1453 NA NA #> 1454 I NA NA #> 1455 I NA NA #> 1456 NA NA #> 1457 NA NA #> 1458 NA NA #> 1459 NA NA #> 1460 NA NA #> 1461 + NA NA #> 1462 NA NA #> 1463 NA NA #> 1464 I NA NA #> 1465 U NA NA #> 1466 NA NA #> 1467 NA NA #> 1468 NA NA #> 1469 NA NA #> 1470 NA NA #> 1471 + NA NA #> 1472 NA NA #> 1473 NA NA #> 1474 I NA NA #> 1475 U NA NA #> 1476 NA NA #> 1477 NA NA #> 1478 U NA NA #> 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#> 1547 NA NA #> 1548 NA NA #> 1549 NA NA #> 1550 NA NA #> 1551 NA NA #> 1552 NA NA #> 1553 + NA NA #> 1554 NA NA #> 1555 I NA NA #> 1556 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 A NA NA #> 1567 A NA NA #> 1568 NA NA #> 1569 I NA NA #> 1570 NA NA #> 1571 NA NA #> 1572 + NA NA #> 1573 NA NA #> 1574 NA NA #> 1575 NA NA #> 1576 A NA NA #> 1577 + NA NA #> 1578 I NA NA #> 1579 NA NA #> 1580 NA NA #> 1581 + NA NA #> 1582 NA NA #> 1583 NA NA #> 1584 I NA NA #> 1585 NA NA #> 1586 + NA NA #> 1587 I NA NA #> 1588 NA NA #> 1589 NA NA #> 1590 + NA NA #> 1591 NA NA #> 1592 NA NA #> 1593 NA NA #> 1594 NA NA #> 1595 NA NA #> 1596 + NA NA #> 1597 I NA NA #> 1598 NA NA #> 1599 NA NA #> 1600 + NA NA #> 1601 NA NA #> 1602 NA NA #> 1603 NA NA #> 1604 NA NA #> 1605 NA NA #> 1606 + NA NA #> 1607 I NA NA #> 1608 NA NA #> 1609 NA NA #> 1610 + NA NA #> 1611 NA NA #> 1612 NA NA #> 1613 NA NA #> 1614 NA NA #> 1615 NA NA #> 1616 + 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 + 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 + 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 + NA NA #> 1647 I NA NA #> 1648 NA NA #> 1649 NA NA #> 1650 + NA NA #> 1651 NA NA #> 1652 NA NA #> 1653 I NA NA #> 1654 NA NA #> 1655 NA NA #> 1656 + NA NA #> 1657 I 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 + NA NA #> 1677 I NA NA #> 1678 NA NA #> 1679 NA NA #> 1680 + NA NA #> 1681 NA NA #> 1682 NA NA #> 1683 NA NA #> 1684 A NA NA #> 1685 NA NA #> 1686 + NA NA #> 1687 NA NA #> 1688 NA NA #> 1689 NA NA #> 1690 + NA NA #> 1691 NA NA #> 1692 A NA NA #> 1693 NA NA #> 1694 NA NA #> 1695 NA NA #> 1696 + NA NA #> 1697 NA NA #> 1698 NA NA #> 1699 NA NA #> 1700 + NA NA #> 1701 NA NA #> 1702 NA NA #> 1703 NA NA #> 1704 A NA NA #> 1705 NA NA #> 1706 + NA NA #> 1707 I NA NA #> 1708 NA NA #> 1709 NA NA #> 1710 + NA NA #> 1711 NA NA #> 1712 NA NA #> 1713 NA NA #> 1714 A NA NA #> 1715 NA NA #> 1716 + NA NA #> 1717 I 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 + NA NA #> 1727 I 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 + NA NA #> 1737 U NA NA #> 1738 NA NA #> 1739 NA NA #> 1740 + NA NA #> 1741 NA NA #> 1742 NA NA #> 1743 NA NA #> 1744 NA NA #> 1745 NA NA #> 1746 + NA NA #> 1747 I 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 I NA NA #> 1778 NA NA #> 1779 NA NA #> 1780 + NA NA #> 1781 NA NA #> 1782 NA NA #> 1783 A NA NA #> 1784 NA NA #> 1785 NA NA #> 1786 + NA NA #> 1787 NA NA #> 1788 NA NA #> 1789 NA NA #> 1790 + NA NA #> 1791 NA NA #> 1792 NA NA #> 1793 NA NA #> 1794 NA NA #> 1795 NA NA #> 1796 + NA NA #> 1797 U NA NA #> 1798 NA NA #> 1799 NA NA #> 1800 + NA NA #> 1801 NA NA #> 1802 NA NA #> 1803 NA NA #> 1804 NA NA #> 1805 NA NA #> 1806 + NA NA #> 1807 I NA NA #> 1808 NA NA #> 1809 NA NA #> 1810 + NA NA #> 1811 NA NA #> 1812 NA NA #> 1813 NA NA #> 1814 NA NA #> 1815 NA NA #> 1816 + NA NA #> 1817 I 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 I NA NA #> 1828 NA NA #> 1829 NA NA #> 1830 + NA NA #> 1831 NA NA #> 1832 NA NA #> 1833 NA NA #> 1834 NA NA #> 1835 NA NA #> 1836 + NA NA #> 1837 I NA NA #> 1838 NA NA #> 1839 NA NA #> 1840 + NA NA #> 1841 NA NA #> 1842 NA NA #> 1843 NA NA #> 1844 A NA NA #> 1845 NA NA #> 1846 + NA NA #> 1847 U NA NA #> 1848 NA NA #> 1849 NA NA #> 1850 + NA NA #> 1851 NA NA #> 1852 NA NA #> 1853 NA NA #> 1854 NA NA #> 1855 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 NA NA #> 1870 + NA NA #> 1871 NA NA #> 1872 NA NA #> 1873 NA NA #> 1874 NA NA #> 1875 + NA NA #> 1876 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 + NA NA #> 1886 I NA NA #> 1887 NA NA #> 1888 NA NA #> 1889 + NA NA #> 1890 NA NA #> 1891 A NA NA #> 1892 NA NA #> 1893 NA NA #> 1894 NA NA #> 1895 + NA NA #> 1896 NA NA #> 1897 NA NA #> 1898 NA NA #> 1899 + NA NA #> 1900 NA NA #> 1901 NA NA #> 1902 I NA NA #> 1903 NA NA #> 1904 NA NA #> 1905 + NA NA #> 1906 U NA NA #> 1907 NA NA #> 1908 NA NA #> 1909 + NA NA #> 1910 NA NA #> 1911 NA NA #> 1912 NA NA #> 1913 NA NA #> 1914 + NA NA #> 1915 U NA NA #> 1916 NA NA #> 1917 NA NA #> 1918 + NA NA #> 1919 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 NA NA #> 1930 NA NA #> 1931 NA NA #> 1932 A NA NA #> 1933 U NA NA #> 1934 NA NA #> 1935 + NA NA #> 1936 NA NA #> 1937 NA NA #> 1938 NA NA #> 1939 NA NA #> 1940 NA NA #> 1941 + NA NA #> 1942 I NA NA #> 1943 NA NA #> 1944 NA NA #> 1945 + NA NA #> 1946 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 I NA NA #> 1958 NA NA #> 1959 NA NA #> 1960 + NA NA #> 1961 NA NA #> 1962 NA NA #> 1963 A NA NA #> 1964 NA NA #> 1965 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 + NA NA #> 1977 I NA NA #> 1978 NA NA #> 1979 NA NA #> 1980 + NA NA #> 1981 NA NA #> 1982 NA NA #> 1983 U NA NA #> 1984 U NA NA #> 1985 NA NA #> 1986 + NA NA #> 1987 NA NA #> 1988 NA NA #> 1989 NA NA #> 1990 + NA NA #> 1991 NA NA #> 1992 NA NA #> 1993 I NA NA #> 1994 NA NA #> 1995 NA NA #> 1996 NA NA #> 1997 U NA NA #> 1998 NA NA #> 1999 NA NA #> 2000 + NA NA #> 2001 NA NA #> 2002 NA NA #> 2003 NA NA #> 2004 NA NA #> 2005 NA NA #> 2006 NA NA #> 2007 I NA NA #> 2008 NA NA #> 2009 NA NA #> 2010 + NA NA #> 2011 NA NA #> 2012 NA NA #> 2013 I NA NA #> 2014 NA NA #> 2015 NA NA #> 2016 NA NA #> 2017 U NA NA #> 2018 NA NA #> 2019 NA NA #> 2020 + NA NA #> 2021 NA NA #> 2022 NA NA #> 2023 NA NA #> 2024 NA NA #> 2025 NA NA #> 2026 NA NA #> 2027 U NA NA #> 2028 NA NA #> 2029 NA NA #> 2030 + NA NA #> 2031 NA NA #> 2032 NA NA #> 2033 NA NA #> 2034 NA NA #> 2035 NA NA #> 2036 NA NA #> 2037 U NA NA #> 2038 NA NA #> 2039 NA NA #> 2040 + NA NA #> 2041 NA NA #> 2042 NA NA #> 2043 NA NA #> 2044 A NA NA #> 2045 NA NA #> 2046 NA NA #> 2047 U NA NA #> 2048 NA NA #> 2049 NA NA #> 2050 + NA NA #> 2051 NA NA #> 2052 A NA NA #> 2053 + NA NA #> 2054 I NA NA #> 2055 NA NA #> 2056 NA NA #> 2057 NA NA #> 2058 I 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 NA NA #> 2070 NA NA #> 2071 NA NA #> 2072 NA NA #> 2073 NA NA #> 2074 NA NA #> 2075 NA NA #> 2076 NA NA #> 2077 + NA NA #> 2078 NA NA #> 2079 NA NA #> 2080 I NA NA #> 2081 NA NA #> 2082 NA NA #> 2083 NA NA #> 2084 NA NA #> 2085 NA NA #> 2086 NA NA #> 2087 + NA NA #> 2088 NA NA #> 2089 NA NA #> 2090 NA NA #> 2091 A NA NA #> 2092 NA NA #> 2093 NA NA #> 2094 NA NA #> 2095 NA NA #> 2096 NA NA #> 2097 + NA NA #> 2098 NA NA #> 2099 NA NA #> 2100 I NA NA #> 2101 NA NA #> 2102 NA NA #> 2103 NA NA #> 2104 I NA NA #> 2105 NA NA #> 2106 NA NA #> 2107 + NA NA #> 2108 NA NA #> 2109 NA NA #> 2110 I NA NA #> 2111 NA NA #> 2112 NA NA #> 2113 NA NA #> 2114 I NA NA #> 2115 NA NA #> 2116 NA NA #> 2117 + NA NA #> 2118 NA NA #> 2119 NA NA #> 2120 NA NA #> 2121 NA NA #> 2122 NA NA #> 2123 NA NA #> 2124 U NA NA #> 2125 NA NA #> 2126 NA NA #> 2127 + NA NA #> 2128 NA NA #> 2129 NA NA #> 2130 NA NA #> 2131 NA NA #> 2132 NA NA #> 2133 NA NA #> 2134 I NA NA #> 2135 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 I NA NA #> 2145 NA NA #> 2146 NA NA #> 2147 + NA NA #> 2148 NA NA #> 2149 NA NA #> 2150 I NA NA #> 2151 A NA NA #> 2152 NA NA #> 2153 NA NA #> 2154 NA NA #> 2155 NA NA #> 2156 NA NA #> 2157 + NA NA #> 2158 NA NA #> 2159 NA NA #> 2160 NA NA #> 2161 A NA NA #> 2162 NA NA #> 2163 NA NA #> 2164 NA NA #> 2165 NA NA #> 2166 NA NA #> 2167 + NA NA #> 2168 NA NA #> 2169 NA NA #> 2170 I NA NA #> 2171 NA NA #> 2172 NA NA #> 2173 NA NA #> 2174 NA NA #> 2175 NA NA #> 2176 NA NA #> 2177 + NA NA #> 2178 NA NA #> 2179 NA NA #> 2180 I NA NA #> 2181 NA NA #> 2182 NA NA #> 2183 NA NA #> 2184 U NA NA #> 2185 NA NA #> 2186 NA NA #> 2187 + NA NA #> 2188 NA NA #> 2189 NA NA #> 2190 I NA NA #> 2191 A NA NA #> 2192 NA NA #> 2193 NA NA #> 2194 U NA NA #> 2195 NA NA #> 2196 NA NA #> 2197 + NA NA #> 2198 NA NA #> 2199 A NA NA #> 2200 I NA NA #> 2201 NA NA #> 2202 NA NA #> 2203 NA NA #> 2204 U NA NA #> 2205 NA NA #> 2206 NA NA #> 2207 + NA NA #> 2208 NA NA #> 2209 NA NA #> 2210 NA NA #> 2211 NA NA #> 2212 NA NA #> 2213 NA NA #> 2214 U NA NA #> 2215 NA NA #> 2216 NA NA #> 2217 + NA NA #> 2218 NA NA #> 2219 NA NA #> 2220 NA NA #> 2221 NA NA #> 2222 U NA NA #> 2223 NA NA #> 2224 + NA NA #> 2225 NA NA #> 2226 NA NA #> 2227 NA NA #> 2228 NA NA #> 2229 NA NA #> 2230 NA NA #> 2231 U NA NA #> 2232 NA NA #> 2233 NA NA #> 2234 + NA NA #> 2235 NA NA #> 2236 NA NA #> 2237 NA NA #> 2238 A NA NA #> 2239 NA NA #> 2240 NA NA #> 2241 I NA NA #> 2242 NA NA #> 2243 NA NA #> 2244 + NA NA #> 2245 NA NA #> 2246 NA NA #> 2247 I NA NA #> 2248 NA NA #> 2249 NA NA #> 2250 NA NA #> 2251 I NA NA #> 2252 NA NA #> 2253 NA NA #> 2254 + NA NA #> 2255 NA NA #> 2256 A NA NA #> 2257 I 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 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 A NA NA #> 2279 NA NA #> 2280 NA NA #> 2281 I NA NA #> 2282 NA NA #> 2283 NA NA #> 2284 + NA NA #> 2285 NA NA #> 2286 NA NA #> 2287 I NA NA #> 2288 A NA NA #> 2289 NA NA #> 2290 NA NA #> 2291 I NA NA #> 2292 NA NA #> 2293 NA NA #> 2294 + NA NA #> 2295 NA NA #> 2296 NA NA #> 2297 I NA NA #> 2298 NA NA #> 2299 NA NA #> 2300 NA NA #> 2301 I NA NA #> 2302 NA NA #> 2303 + NA NA #> 2304 NA NA #> 2305 NA NA #> 2306 U NA NA #> 2307 NA NA #> 2308 NA NA #> 2309 U NA NA #> 2310 NA NA #> 2311 + NA NA #> 2312 NA NA #> 2313 NA NA #> 2314 NA NA #> 2315 NA NA #> 2316 I NA NA #> 2317 + NA NA #> 2318 NA NA #> 2319 + NA NA #> 2320 NA NA #> 2321 I NA NA #> 2322 NA NA #> 2323 NA NA #> 2324 NA NA #> 2325 NA NA #> 2326 NA NA #> 2327 U NA NA #> 2328 + NA NA #> 2329 NA NA #> 2330 + NA NA #> 2331 NA NA #> 2332 I NA NA #> 2333 NA NA #> 2334 NA NA #> 2335 NA NA #> 2336 NA NA #> 2337 NA NA #> 2338 U NA NA #> 2339 + NA NA #> 2340 NA NA #> 2341 + NA NA #> 2342 I NA NA #> 2343 NA NA #> 2344 NA NA #> 2345 NA NA #> 2346 NA NA #> 2347 NA NA #> 2348 I NA NA #> 2349 NA NA #> 2350 + NA NA #> 2351 NA NA #> 2352 U NA NA #> 2353 A NA NA #> 2354 NA NA #> 2355 NA NA #> 2356 NA NA #> 2357 NA NA #> 2358 NA NA #> 2359 NA NA #> 2360 NA NA #> 2361 + NA NA #> 2362 NA NA #> 2363 I NA NA #> 2364 NA NA #> 2365 NA NA #> 2366 NA NA #> 2367 NA NA #> 2368 NA NA #> 2369 I NA NA #> 2370 NA NA #> 2371 NA NA #> 2372 + NA NA #> 2373 NA NA #> 2374 I NA NA #> 2375 NA NA #> 2376 NA NA #> 2377 NA NA #> 2378 NA NA #> 2379 NA NA #> 2380 + NA NA #> 2381 I NA NA #> 2382 NA NA #> 2383 NA NA #> 2384 NA NA #> 2385 I NA NA #> 2386 NA NA #> 2387 NA NA #> 2388 + NA NA #> 2389 NA NA #> 2390 I NA NA #> 2391 NA NA #> 2392 NA NA #> 2393 NA NA #> 2394 NA NA #> 2395 NA NA #> 2396 U NA NA #> 2397 NA NA #> 2398 NA NA #> 2399 + NA NA #> 2400 NA NA #> 2401 I NA NA #> 2402 NA NA #> 2403 NA NA #> 2404 NA NA #> 2405 NA NA #> 2406 NA NA #> 2407 U NA NA #> 2408 NA NA #> 2409 NA NA #> 2410 + NA NA #> 2411 NA NA #> 2412 I NA NA #> 2413 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 U NA NA #> 2424 NA NA #> 2425 NA NA #> 2426 NA NA #> 2427 NA NA #> 2428 NA NA #> 2429 I NA NA #> 2430 NA NA #> 2431 NA NA #> 2432 + NA NA #> 2433 NA NA #> 2434 I NA NA #> 2435 NA NA #> 2436 NA NA #> 2437 NA NA #> 2438 NA NA #> 2439 NA NA #> 2440 NA NA #> 2441 NA NA #> 2442 NA NA #> 2443 NA NA #> 2444 NA NA #> 2445 NA NA #> 2446 NA NA #> 2447 NA NA #> 2448 NA NA #> 2449 NA NA #> 2450 NA NA #> 2451 NA NA #> 2452 U NA NA #> 2453 NA NA #> 2454 NA NA #> 2455 + NA NA #> 2456 NA NA #> 2457 I NA NA #> 2458 A NA NA #> 2459 A NA NA #> 2460 NA NA #> 2461 NA NA #> 2462 NA NA #> 2463 U NA NA #> 2464 NA NA #> 2465 NA NA #> 2466 + NA NA #> 2467 NA NA #> 2468 I NA NA #> 2469 NA NA #> 2470 NA NA #> 2471 NA NA #> 2472 NA NA #> 2473 NA NA #> 2474 U NA NA #> 2475 NA NA #> 2476 NA NA #> 2477 + NA NA #> 2478 NA NA #> 2479 A NA NA #> 2480 NA NA #> 2481 NA NA #> 2482 NA NA #> 2483 NA NA #> 2484 NA NA #> 2485 I NA NA #> 2486 NA NA #> 2487 NA NA #> 2488 + NA NA #> 2489 NA NA #> 2490 I NA NA #> 2491 NA NA #> 2492 A NA NA #> 2493 NA NA #> 2494 NA NA #> 2495 NA NA #> 2496 U NA NA #> 2497 NA NA #> 2498 NA NA #> 2499 + NA NA #> 2500 NA NA #> 2501 I NA NA #> 2502 NA NA #> 2503 NA NA #> 2504 NA NA #> 2505 NA NA #> 2506 NA NA #> 2507 U NA NA #> 2508 NA NA #> 2509 NA NA #> 2510 + NA NA #> 2511 NA NA #> 2512 I NA NA #> 2513 NA NA #> 2514 NA NA #> 2515 NA NA #> 2516 NA NA #> 2517 NA NA #> 2518 NA NA #> 2519 NA NA #> 2520 NA NA #> 2521 + NA NA #> 2522 NA NA #> 2523 I NA NA #> 2524 NA NA #> 2525 NA NA #> 2526 NA NA #> 2527 NA NA #> 2528 I NA NA #> 2529 NA NA #> 2530 NA NA #> 2531 + NA NA #> 2532 NA NA #> 2533 I NA NA #> 2534 NA NA #> 2535 NA NA #> 2536 NA NA #> 2537 NA NA #> 2538 I NA NA #> 2539 NA NA #> 2540 NA NA #> 2541 + NA NA #> 2542 NA NA #> 2543 NA NA #> 2544 NA NA #> 2545 NA NA #> 2546 NA NA #> 2547 NA NA #> 2548 NA NA #> 2549 U NA NA #> 2550 NA NA #> 2551 NA NA #> 2552 + NA NA #> 2553 NA NA #> 2554 I NA NA #> 2555 NA NA #> 2556 NA NA #> 2557 NA NA #> 2558 NA NA #> 2559 NA NA #> 2560 U NA NA #> 2561 NA NA #> 2562 NA NA #> 2563 + NA NA #> 2564 NA NA #> 2565 I NA NA #> 2566 NA NA #> 2567 NA NA #> 2568 NA NA #> 2569 NA NA #> 2570 NA NA #> 2571 U NA NA #> 2572 NA NA #> 2573 NA NA #> 2574 + NA NA #> 2575 NA NA #> 2576 I NA NA #> 2577 A NA NA #> 2578 NA NA #> 2579 NA NA #> 2580 NA NA #> 2581 NA NA #> 2582 U NA NA #> 2583 NA NA #> 2584 NA NA #> 2585 + NA NA #> 2586 NA NA #> 2587 NA NA #> 2588 A NA NA #> 2589 NA NA #> 2590 NA NA #> 2591 NA NA #> 2592 NA NA #> 2593 U NA NA #> 2594 NA NA #> 2595 NA NA #> 2596 + NA NA #> 2597 NA NA #> 2598 I NA NA #> 2599 NA NA #> 2600 NA NA #> 2601 NA NA #> 2602 NA NA #> 2603 NA NA #> 2604 U NA NA #> 2605 NA NA #> 2606 NA NA #> 2607 + NA NA #> 2608 NA NA #> 2609 I NA NA #> 2610 NA NA #> 2611 I NA NA #> 2612 NA NA #> 2613 NA NA #> 2614 NA NA #> 2615 U 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 NA NA #> 2626 U NA NA #> 2627 NA NA #> 2628 NA NA #> 2629 + NA NA #> 2630 NA NA #> 2631 I NA NA #> 2632 NA NA #> 2633 A NA NA #> 2634 NA NA #> 2635 NA NA #> 2636 NA NA #> 2637 U NA NA #> 2638 NA NA #> 2639 NA NA #> 2640 + NA NA #> 2641 NA NA #> 2642 I NA NA #> 2643 NA NA #> 2644 NA NA #> 2645 NA NA #> 2646 NA NA #> 2647 NA NA #> 2648 U NA NA #> 2649 NA NA #> 2650 NA NA #> 2651 + NA NA #> 2652 NA NA #> 2653 I NA NA #> 2654 NA NA #> 2655 NA NA #> 2656 NA NA #> 2657 NA NA #> 2658 NA NA #> 2659 U NA NA #> 2660 NA NA #> 2661 NA NA #> 2662 + NA NA #> 2663 NA NA #> 2664 I NA NA #> 2665 NA NA #> 2666 NA NA #> 2667 NA NA #> 2668 NA NA #> 2669 NA NA #> 2670 U NA NA #> 2671 NA NA #> 2672 NA NA #> 2673 + NA NA #> 2674 NA NA #> 2675 I NA NA #> 2676 NA NA #> 2677 I NA NA #> 2678 I NA NA #> 2679 NA NA #> 2680 + NA NA #> 2681 NA NA #> 2682 NA NA #> 2683 NA NA #> 2684 NA NA #> 2685 NA NA #> 2686 NA NA #> 2687 NA NA #> 2688 + NA NA #> 2689 NA NA #> 2690 NA NA #> 2691 NA NA #> 2692 + 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 I 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 I NA NA #> 2792 NA NA #> 2793 I NA NA #> 2794 A 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 I NA NA #> 2804 A NA NA #> 2805 NA NA #> 2806 A NA NA #> 2807 NA NA #> 2808 NA NA #> 2809 NA NA #> 2810 NA NA #> 2811 NA NA #> 2812 NA NA #> 2813 + NA NA #> 2814 NA NA #> 2815 I NA NA #> 2816 A NA NA #> 2817 NA NA #> 2818 NA NA #> 2819 NA NA #> 2820 NA NA #> 2821 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 NA NA #> 2831 NA NA #> 2832 NA NA #> 2833 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 NA NA #> 2843 + NA NA #> 2844 NA NA #> 2845 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 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 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 U NA NA #> 2886 + NA NA #> 2887 NA NA #> 2888 + NA NA #> 2889 NA NA #> 2890 U NA NA #> 2891 NA NA #> 2892 NA NA #> 2893 NA NA #> 2894 NA NA #> 2895 NA NA #> 2896 I NA NA #> 2897 + NA NA #> 2898 NA NA #> 2899 + NA NA #> 2900 NA NA #> 2901 NA NA #> 2902 A 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 I 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 I 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 I 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 I NA NA #> 2950 NA NA #> 2951 NA NA #> 2952 NA NA #> 2953 NA NA #> 2954 NA NA #> 2955 A NA NA #> 2956 NA NA #> 2957 I NA NA #> 2958 NA NA #> 2959 NA NA #> 2960 + NA NA #> 2961 NA NA #> 2962 I NA NA #> 2963 NA NA #> 2964 NA NA #> 2965 NA NA #> 2966 NA NA #> 2967 NA NA #> 2968 I NA NA #> 2969 NA NA #> 2970 NA NA #> 2971 + NA NA #> 2972 NA NA #> 2973 I NA NA #> 2974 NA NA #> 2975 NA NA #> 2976 NA NA #> 2977 NA NA #> 2978 NA NA #> 2979 U NA NA #> 2980 NA NA #> 2981 NA NA #> 2982 + NA NA #> 2983 NA NA #> 2984 I NA NA #> 2985 NA NA #> 2986 NA NA #> 2987 U NA NA #> 2988 NA NA #> 2989 + NA NA #> 2990 NA NA #> 2991 I NA NA #> 2992 NA NA #> 2993 NA NA #> 2994 NA NA #> 2995 NA NA #> 2996 NA NA #> 2997 NA NA #> 2998 NA NA #> 2999 NA NA #> 3000 + NA NA #> 3001 NA NA #> 3002 I NA NA #> 3003 NA NA #> 3004 NA NA #> 3005 NA NA #> 3006 NA NA #> 3007 NA NA #> 3008 NA NA #> 3009 NA NA #> 3010 + NA NA #> 3011 NA NA #> 3012 I NA NA #> 3013 NA NA #> 3014 NA NA #> 3015 NA NA #> 3016 NA NA #> 3017 NA NA #> 3018 I 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 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 NA NA #> 3045 NA NA #> 3046 NA NA #> 3047 NA NA #> 3048 NA NA #> 3049 NA NA #> 3050 NA NA #> 3051 NA NA #> 3052 NA NA #> 3053 NA NA #> 3054 NA NA #> 3055 NA NA #> 3056 NA NA #> 3057 NA NA #> 3058 NA NA #> 3059 + NA NA #> 3060 NA NA #> 3061 I NA NA #> 3062 NA NA #> 3063 NA NA #> 3064 NA NA #> 3065 NA NA #> 3066 NA NA #> 3067 NA NA #> 3068 NA NA #> 3069 NA NA #> 3070 + NA NA #> 3071 NA NA #> 3072 I NA NA #> 3073 NA NA #> 3074 NA NA #> 3075 NA NA #> 3076 NA NA #> 3077 NA NA #> 3078 I NA NA #> 3079 NA NA #> 3080 NA NA #> 3081 + NA NA #> 3082 NA NA #> 3083 I NA NA #> 3084 A NA NA #> 3085 NA NA #> 3086 NA NA #> 3087 NA NA #> 3088 NA NA #> 3089 U 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 A NA NA #> 3107 NA NA #> 3108 NA NA #> 3109 NA NA #> 3110 NA NA #> 3111 U NA NA #> 3112 NA NA #> 3113 NA NA #> 3114 + NA NA #> 3115 NA NA #> 3116 I NA NA #> 3117 NA NA #> 3118 NA NA #> 3119 NA NA #> 3120 NA NA #> 3121 NA NA #> 3122 U NA NA #> 3123 NA NA #> 3124 NA NA #> 3125 + NA NA #> 3126 NA NA #> 3127 I NA NA #> 3128 NA NA #> 3129 NA NA #> 3130 NA NA #> 3131 NA NA #> 3132 NA NA #> 3133 U NA NA #> 3134 NA NA #> 3135 NA NA #> 3136 + NA NA #> 3137 NA NA #> 3138 U NA NA #> 3139 NA NA #> 3140 NA NA #> 3141 NA NA #> 3142 NA NA #> 3143 NA NA #> 3144 NA NA #> 3145 NA NA #> 3146 NA NA #> 3147 + NA NA #> 3148 NA NA #> 3149 I NA NA #> 3150 NA NA #> 3151 NA NA #> 3152 NA NA #> 3153 NA NA #> 3154 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 NA NA #> 3166 NA NA #> 3167 NA NA #> 3168 NA NA #> 3169 + NA NA #> 3170 NA NA #> 3171 I NA NA #> 3172 NA NA #> 3173 NA NA #> 3174 NA NA #> 3175 NA NA #> 3176 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 I NA NA #> 3188 NA NA #> 3189 NA NA #> 3190 + NA NA #> 3191 NA NA #> 3192 I NA NA #> 3193 NA NA #> 3194 NA NA #> 3195 NA NA #> 3196 NA NA #> 3197 NA NA #> 3198 U NA NA #> 3199 NA NA #> 3200 NA NA #> 3201 + NA NA #> 3202 NA NA #> 3203 NA NA #> 3204 NA NA #> 3205 U NA NA #> 3206 NA NA #> 3207 NA NA #> 3208 NA NA #> 3209 U NA NA #> 3210 NA NA #> 3211 NA NA #> 3212 + NA NA #> 3213 NA NA #> 3214 NA NA #> 3215 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 I 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 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 U NA NA #> 3254 + NA NA #> 3255 NA NA #> 3256 + NA NA #> 3257 NA NA #> 3258 NA NA #> 3259 A NA NA #> 3260 NA NA #> 3261 NA NA #> 3262 NA NA #> 3263 NA NA #> 3264 NA NA #> 3265 + NA NA #> 3266 NA NA #> 3267 + NA NA #> 3268 NA NA #> 3269 I NA NA #> 3270 NA NA #> 3271 A NA NA #> 3272 NA NA #> 3273 NA NA #> 3274 NA NA #> 3275 NA NA #> 3276 + NA NA #> 3277 NA NA #> 3278 + NA NA #> 3279 NA NA #> 3280 I NA NA #> 3281 NA NA #> 3282 NA NA #> 3283 U NA NA #> 3284 NA NA #> 3285 + NA NA #> 3286 NA NA #> 3287 NA NA #> 3288 NA NA #> 3289 NA NA #> 3290 NA NA #> 3291 NA NA #> 3292 NA NA #> 3293 I NA NA #> 3294 + NA NA #> 3295 NA NA #> 3296 + NA NA #> 3297 NA NA #> 3298 I NA NA #> 3299 NA NA #> 3300 NA NA #> 3301 NA NA #> 3302 NA NA #> 3303 NA NA #> 3304 NA NA #> 3305 + NA NA #> 3306 NA NA #> 3307 + NA NA #> 3308 NA NA #> 3309 I NA NA #> 3310 NA NA #> 3311 A 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 NA NA #> 3325 NA NA #> 3326 NA NA #> 3327 NA NA #> 3328 NA NA #> 3329 NA NA #> 3330 U NA NA #> 3331 + NA NA #> 3332 NA NA #> 3333 + NA NA #> 3334 NA NA #> 3335 I NA NA #> 3336 NA NA #> 3337 NA NA #> 3338 NA NA #> 3339 NA NA #> 3340 + NA NA #> 3341 NA NA #> 3342 NA NA #> 3343 NA NA #> 3344 NA NA #> 3345 I NA NA #> 3346 + NA NA #> 3347 NA NA #> 3348 + NA NA #> 3349 NA NA #> 3350 I NA NA #> 3351 NA NA #> 3352 NA NA #> 3353 NA NA #> 3354 NA NA #> 3355 NA NA #> 3356 NA NA #> 3357 + NA NA #> 3358 NA NA #> 3359 + NA NA #> 3360 NA NA #> 3361 I 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 + NA NA #> 3375 NA NA #> 3376 I NA NA #> 3377 NA NA #> 3378 NA NA #> 3379 NA NA #> 3380 NA NA #> 3381 NA NA #> 3382 A NA NA #> 3383 NA NA #> 3384 NA NA #> 3385 NA NA #> 3386 NA NA #> 3387 NA NA #> 3388 NA NA #> 3389 + NA NA #> 3390 NA NA #> 3391 I NA NA #> 3392 NA NA #> 3393 NA NA #> 3394 NA NA #> 3395 NA NA #> 3396 NA NA #> 3397 NA NA #> 3398 NA NA #> 3399 U NA NA #> 3400 NA NA #> 3401 NA NA #> 3402 + NA NA #> 3403 NA NA #> 3404 I NA NA #> 3405 NA NA #> 3406 NA NA #> 3407 NA NA #> 3408 NA NA #> 3409 + NA NA #> 3410 U NA NA #> 3411 NA NA #> 3412 NA NA #> 3413 + NA NA #> 3414 NA NA #> 3415 I NA NA #> 3416 NA NA #> 3417 NA NA #> 3418 NA NA #> 3419 NA NA #> 3420 NA NA #> 3421 NA NA #> 3422 NA NA #> 3423 NA NA #> 3424 NA NA #> 3425 U NA NA #> 3426 NA NA #> 3427 NA NA #> 3428 + NA NA #> 3429 NA NA #> 3430 I NA NA #> 3431 NA NA #> 3432 NA NA #> 3433 NA NA #> 3434 NA NA #> 3435 NA NA #> 3436 U NA NA #> 3437 NA NA #> 3438 NA NA #> 3439 + NA NA #> 3440 NA NA #> 3441 I NA NA #> 3442 NA NA #> 3443 NA NA #> 3444 NA NA #> 3445 NA NA #> 3446 NA NA #> 3447 NA NA #> 3448 NA NA #> 3449 NA NA #> 3450 + NA NA #> 3451 NA NA #> 3452 I NA NA #> 3453 NA NA #> 3454 NA NA #> 3455 NA NA #> 3456 NA NA #> 3457 NA NA #> 3458 U NA NA #> 3459 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 NA NA #> 3470 NA NA #> 3471 NA NA #> 3472 NA NA #> 3473 NA NA #> 3474 NA NA #> 3475 NA NA #> 3476 + NA NA #> 3477 NA NA #> 3478 I NA NA #> 3479 NA NA #> 3480 NA NA #> 3481 NA NA #> 3482 NA NA #> 3483 NA NA #> 3484 NA NA #> 3485 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 NA NA #> 3497 I NA NA #> 3498 A NA NA #> 3499 NA NA #> 3500 NA NA #> 3501 NA NA #> 3502 NA NA #> 3503 NA NA #> 3504 NA NA #> 3505 NA NA #> 3506 + NA NA #> 3507 NA NA #> 3508 I NA NA #> 3509 NA NA #> 3510 NA NA #> 3511 NA NA #> 3512 NA NA #> 3513 NA NA #> 3514 U NA NA #> 3515 NA NA #> 3516 NA NA #> 3517 + NA NA #> 3518 NA NA #> 3519 I NA NA #> 3520 NA NA #> 3521 NA NA #> 3522 NA NA #> 3523 NA NA #> 3524 NA NA #> 3525 U NA NA #> 3526 NA NA #> 3527 NA NA #> 3528 + NA NA #> 3529 NA NA #> 3530 I NA NA #> 3531 NA NA #> 3532 NA NA #> 3533 NA NA #> 3534 NA NA #> 3535 NA NA #> 3536 U NA NA #> 3537 NA NA #> 3538 NA NA #> 3539 + NA NA #> 3540 NA NA #> 3541 I NA NA #> 3542 NA NA #> 3543 NA NA #> 3544 NA NA #> 3545 NA NA #> 3546 NA NA #> 3547 I 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 NA NA #> 3570 NA NA #> 3571 NA NA #> 3572 + NA NA #> 3573 NA NA #> 3574 NA NA #> 3575 NA NA #> 3576 NA NA #> 3577 NA NA #> 3578 NA NA #> 3579 NA NA #> 3580 I 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 U 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 NA NA #> 3608 NA NA #> 3609 NA NA #> 3610 NA NA #> 3611 NA NA #> 3612 NA NA #> 3613 U NA NA #> 3614 NA NA #> 3615 NA NA #> 3616 + NA NA #> 3617 NA NA #> 3618 I 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 NA NA #> 3630 NA NA #> 3631 NA NA #> 3632 NA NA #> 3633 NA NA #> 3634 NA NA #> 3635 NA NA #> 3636 NA NA #> 3637 NA NA #> 3638 + NA NA #> 3639 NA NA #> 3640 I NA NA #> 3641 NA NA #> 3642 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 NA NA #> 3652 NA NA #> 3653 NA NA #> 3654 NA NA #> 3655 NA NA #> 3656 + NA NA #> 3657 I NA NA #> 3658 NA NA #> 3659 NA NA #> 3660 + NA NA #> 3661 NA NA #> 3662 NA NA #> 3663 NA NA #> 3664 A NA NA #> 3665 + NA NA #> 3666 I NA NA #> 3667 NA NA #> 3668 NA NA #> 3669 + NA NA #> 3670 NA NA #> 3671 NA NA #> 3672 A NA NA #> 3673 A NA NA #> 3674 NA NA #> 3675 + NA NA #> 3676 NA NA #> 3677 NA NA #> 3678 NA NA #> 3679 + NA NA #> 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NA NA #> 4367 NA NA #> 4368 NA NA #> 4369 + NA NA #> 4370 NA NA #> 4371 NA NA #> 4372 I NA NA #> 4373 NA NA #> 4374 NA NA #> 4375 NA NA #> 4376 I NA NA #> 4377 NA NA #> 4378 NA NA #> 4379 + NA NA #> 4380 NA NA #> 4381 NA NA #> 4382 NA NA #> 4383 NA NA #> 4384 NA NA #> 4385 NA NA #> 4386 U NA NA #> 4387 NA NA #> 4388 NA NA #> 4389 + NA NA #> 4390 NA NA #> 4391 A NA NA #> 4392 NA NA #> 4393 NA NA #> 4394 NA NA #> 4395 NA NA #> 4396 NA NA #> 4397 + NA NA #> 4398 NA NA #> 4399 NA NA #> 4400 NA NA #> 4401 NA NA #> 4402 NA NA #> 4403 NA NA #> 4404 NA NA #> 4405 NA NA #> 4406 NA NA #> 4407 + NA NA #> 4408 NA NA #> 4409 NA NA #> 4410 I NA NA #> 4411 NA NA #> 4412 NA NA #> 4413 NA NA #> 4414 NA NA #> 4415 NA NA #> 4416 + NA NA #> 4417 NA NA #> 4418 NA NA #> 4419 I NA NA #> 4420 NA NA #> 4421 NA NA #> 4422 NA NA #> 4423 I NA NA #> 4424 NA NA #> 4425 NA NA #> 4426 + NA NA #> 4427 NA NA #> 4428 NA NA #> 4429 I NA NA #> 4430 A NA NA #> 4431 NA NA #> 4432 NA NA #> 4433 I NA NA #> 4434 NA NA #> 4435 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NA #> 4574 NA NA #> 4575 NA NA #> 4576 NA NA #> 4577 + NA NA #> 4578 NA NA #> 4579 NA NA #> 4580 NA NA #> 4581 + NA NA #> 4582 NA NA #> 4583 NA NA #> 4584 NA NA #> 4585 NA NA #> 4586 NA NA #> 4587 + NA NA #> 4588 NA NA #> 4589 NA NA #> 4590 NA NA #> 4591 NA NA #> 4592 NA NA #> 4593 NA NA #> 4594 NA NA #> 4595 NA NA #> 4596 NA NA #> 4597 + NA NA #> 4598 NA NA #> 4599 NA NA #> 4600 NA NA #> 4601 + NA NA #> 4602 NA NA #> 4603 NA NA #> 4604 NA NA #> 4605 NA NA #> 4606 NA NA #> 4607 + NA NA #> 4608 U NA NA #> 4609 NA NA #> 4610 NA NA #> 4611 NA NA #> 4612 NA NA #> 4613 NA NA #> 4614 NA NA #> 4615 NA NA #> 4616 NA NA #> 4617 + NA NA #> 4618 NA NA #> 4619 NA NA #> 4620 NA NA #> 4621 + NA NA #> 4622 NA NA #> 4623 NA NA #> 4624 NA NA #> 4625 NA NA #> 4626 + NA NA #> 4627 NA NA #> 4628 NA NA #> 4629 NA NA #> 4630 NA NA #> 4631 NA NA #> 4632 I NA NA #> 4633 NA NA #> 4634 NA NA #> 4635 NA NA #> 4636 + NA NA #> 4637 NA NA #> 4638 NA NA #> 4639 NA NA #> 4640 + NA NA #> 4641 NA NA #> 4642 NA NA #> 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NA NA #> 9057 NA NA #> 9058 + NA NA #> 9059 I NA NA #> 9060 NA NA #> 9061 NA NA #> 9062 NA NA #> 9063 NA NA #> 9064 NA NA #> 9065 NA NA #> 9066 NA NA #> 9067 NA NA #> 9068 + NA NA #> 9069 NA NA #> 9070 NA NA #> 9071 NA NA #> 9072 + NA NA #> 9073 NA NA #> 9074 NA NA #> 9075 NA NA #> 9076 NA NA #> 9077 + NA NA #> 9078 U NA NA #> 9079 NA NA #> 9080 NA NA #> 9081 NA NA #> 9082 NA NA #> 9083 NA NA #> 9084 NA NA #> 9085 NA NA #> 9086 NA NA #> 9087 + NA NA #> 9088 NA NA #> 9089 NA NA #> 9090 NA NA #> [ reached 'max' / getOption(\"max.print\") -- omitted 165566 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 = 2022)"},{"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 = 2022) #> # 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 NA 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 = 2022, 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 = 2022) head(dat) #> id name JEI wbid class year CHLAC COLOR COND DO DOSAT #> 1 2 Rock Creek CC01 2052 3M 2013 2.725391 9.607368 NA 6.819091 73.50770 #> 2 2 Rock Creek CC01 2052 3M 2014 2.380249 14.694735 NA 3.308289 60.31523 #> 3 2 Rock Creek CC01 2052 3M 2015 2.647817 21.911128 NA 4.034172 55.41609 #> 4 2 Rock Creek CC01 2052 3M 2016 2.265462 19.130797 NA 3.980251 55.96637 #> 5 2 Rock Creek CC01 2052 3M 2017 2.851726 15.395763 NA 4.157777 60.18017 #> 6 2 Rock Creek CC01 2052 3M 2018 1.934899 11.655004 NA 4.219790 63.32630 #> NO23 ORGN SALIN TKN TN TP TSS TURB #> 1 0.009781633 NA 30.90561 0.6510575 0.7108146 0.06842811 NA 1.698004 #> 2 0.007575792 NA 26.63714 0.6161702 0.6228782 0.06938150 NA 2.044623 #> 3 0.009361504 NA 19.10494 0.6465161 0.5678241 0.07602770 NA 1.814818 #> 4 0.008532522 NA 25.84531 0.5813818 0.5408161 0.08330509 NA 2.082253 #> 5 0.007447260 NA 24.86909 0.6255197 0.6326848 0.07566682 NA 1.802161 #> 6 0.006994714 NA 31.32419 0.5668727 0.5734574 0.07432007 NA 2.454007 #> chla_tn_ratio tn_tp_ratio chla_tsi tn_tsi tn2_tsi tp_tsi tp2_tsi #> 1 3.834180 10.387756 31.23761 49.24140 52.26414 60.19958 75.92850 #> 2 3.821371 8.977584 29.28775 46.62660 49.42526 60.45694 76.25504 #> 3 4.663093 7.468648 30.82179 44.79432 47.43600 62.15842 78.41391 #> 4 4.188970 6.491994 28.57601 43.82942 46.38844 63.85868 80.57123 #> 5 4.507341 8.361456 31.89011 46.93590 49.76107 62.06992 78.30162 #> 6 3.374095 7.716050 26.30480 44.98978 47.64821 61.73589 77.87779 #> nut_tsi tsi no23_source no23_tidal no23_ratio do_bnml do_prop #> 1 54.72049 42.97905 NA NA NA 0 0 #> 2 49.42526 39.35651 NA NA NA 0 1 #> 3 47.43600 39.12890 NA NA NA 0 1 #> 4 46.38844 37.48223 NA NA NA 0 1 #> 5 49.76107 40.82559 NA NA NA 0 0 #> 6 47.64821 36.97650 NA NA NA 0 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\"), 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\" 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: 182 × 3 #> yr Savspecies foest #> #> 1 1998 Caulerpa 0.0166 #> 2 1998 Halodule 0.361 #> 3 1998 Halophila 0 #> 4 1998 Ruppia 0.0112 #> 5 1998 Syringodium 0.0451 #> 6 1998 Thalassia 0.254 #> 7 1998 total 0.580 #> 8 1999 Caulerpa 0.0277 #> 9 1999 Halodule 0.306 #> 10 1999 Halophila 0.00118 #> # ℹ 172 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, whereas attached drift algae species aggregated.","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 \"CYAN: Lyngbya/Dapis\" 41 0 0 #> 3 1997-10-11 S2T3 \"Caulerpa\" 41 0 0 #> 4 1997-10-11 S2T3 \"DA\" 41 0 0 #> 5 1997-10-11 S2T3 \"DB: Dictyota\\r\\n\" 41 0 0 #> 6 1997-10-11 S2T3 \"DB: Drift Brown\\r\\n\" 41 0 0 #> 7 1997-10-11 S2T3 \"DG: Chaetomorpha\\r\\n\" 41 0 0 #> 8 1997-10-11 S2T3 \"DG: Drift Green\" 41 0 0 #> 9 1997-10-11 S2T3 \"DG: Ulva\" 41 0 0 #> 10 1997-10-11 S2T3 \"DG: Ulva fasciata\\r\\n\" 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 = 2022) #> # A tibble: 4 × 6 #> bay_segment chla_val chla_target la_val la_target outcome #> #> 1 OTB 7.12 8.5 0.787 0.83 green #> 2 HB 8.86 13.2 0.922 1.58 green #> 3 MTB 5.05 7.4 0.553 0.83 green #> 4 LTB 3.59 4.6 0.658 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 12142023 — benthicdata","title":"Benthic data for the Tampa Bay Benthic Index current as of 12142023 — benthicdata","text":"Benthic data Tampa Bay Benthic Index current 12142023","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 12142023 — 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 12142023 — 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 12142023 — 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 12142023 — 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 20230710 — fibdata","title":"All Fecal Indicator Bacteria (FIB) data as of 20230710 — fibdata","text":"Fecal Indicator Bacteria (FIB) data 20230710","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 20230710 — 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 20230710 — fibdata","text":"data frame 74872 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 20230710 — 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') }"},{"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 64 — iwrraw","title":"FDEP IWR run 64 — iwrraw","text":"Florida Department Environmental Protection, Impaired Waters Rule, Run 64","code":""},{"path":"https://tbep-tech.github.io/tbeptools/reference/iwrraw.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"FDEP IWR run 64 — 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 64 — iwrraw","text":"data frame 194881 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 64 — 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 64 — 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 05192022 — phytodata","title":"Phytoplankton data current as of 05192022 — phytodata","text":"Phytoplankton data current 05192022","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 05192022 — 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 05192022 — phytodata","text":"nested tibble 23848 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 05192022 — phytodata","text":"","code":"if (FALSE) { # location to download data path <- '~/Desktop/phyto_data.xlsx' # load and assign to object phytodata <- read_importphyto(path, download_latest = TRUE) save(phytodata, file = 'data/phytodata.RData', compress = 'xz') }"},{"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 \"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). 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) 2022 target 2022 target OTB 7.1 8.5 0.79 0.83 HB 8.9 13.2 0.92 1.58 MTB 5.0 7.4 0.55 0.83 LTB 3.6 4.6 0.66 0.63 Water quality outcomes 2022. Segment Chl-(ug/L) Light Penetration (m-1) 2022 target 2022 target OTB 7.1 8.5 0.79 0.83 HB 8.9 13.2 0.92 1.58 MTB 5.0 7.4 0.55 0.83 LTB 3.6 4.6 0.66 0.63","code":"show_annualassess(epcdata, yrsel = 2022) .cl-ee59b24c{}.cl-ee50ced4{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-ee50cede{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-ee534c22{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-ee534c2c{margin:0;text-align:center;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid 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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, 2022), 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 = 2022, 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, 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mV474ztDZ7HO5DSeCSH1zJQn/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,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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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Class: Marine (Enterococcus<\\/i>)
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Class: Marine (Enterococcus<\\/i>)
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Class: Marine (Enterococcus<\\/i>)
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Class: Marine (Enterococcus<\\/i>)
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Class: Marine (Enterococcus<\\/i>)
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Class: Marine (Enterococcus<\\/i>)
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Class: Marine (Enterococcus<\\/i>)
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Class: Marine (Enterococcus<\\/i>)
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Class: Marine (Enterococcus<\\/i>)
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Class: Marine (Enterococcus<\\/i>)
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Class: Marine (Enterococcus<\\/i>)
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Class: Marine (Enterococcus<\\/i>)
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Class: Marine (Enterococcus<\\/i>)
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Class: Marine (Enterococcus<\\/i>)
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Class: Marine (Enterococcus<\\/i>)
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Class: Marine (Enterococcus<\\/i>)
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Class: Marine (Enterococcus<\\/i>)
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Class: Marine (Enterococcus<\\/i>)
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Class: Marine (Enterococcus<\\/i>)
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Class: Marine (Enterococcus<\\/i>)
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Class: Marine (Enterococcus<\\/i>)
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Class: Marine (Enterococcus<\\/i>)
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Class: Marine (Enterococcus<\\/i>)
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Class: Marine (Enterococcus<\\/i>)
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Class: Marine (Enterococcus<\\/i>)
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Class: Marine (Enterococcus<\\/i>)
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Class: Marine (Enterococcus<\\/i>)
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Class: Marine (Enterococcus<\\/i>)
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Class: Marine (Enterococcus<\\/i>)
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Class: Marine (Enterococcus<\\/i>)
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Class: Marine (Enterococcus<\\/i>)
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Class: Marine (Enterococcus<\\/i>)
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Class: Marine (Enterococcus<\\/i>)
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Class: Freshwater (E. coli<\\/i>)
Category: < 126 (100/100mL)<\\/html>\",\"Station Number: 132
Class: Freshwater (E. coli<\\/i>)
Category: > 999 (1367/100mL)<\\/html>\",\"Station Number: 133
Class: Marine (Enterococcus<\\/i>)
Category: 130 - 999 (550/100mL)<\\/html>\",\"Station Number: 135
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (4/100mL)<\\/html>\",\"Station Number: 137
Class: Marine (Enterococcus<\\/i>)
Category: 35 - 129 (128/100mL)<\\/html>\",\"Station Number: 138
Class: Freshwater (E. coli<\\/i>)
Category: 126 - 409 (267/100mL)<\\/html>\",\"Station Number: 139
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (73/100mL)<\\/html>\",\"Station Number: 140
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (80/100mL)<\\/html>\",\"Station Number: 141
Class: Freshwater (E. coli<\\/i>)
Category: 126 - 409 (307/100mL)<\\/html>\",\"Station Number: 142
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (7/100mL)<\\/html>\",\"Station Number: 143
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (76/100mL)<\\/html>\",\"Station Number: 144
Class: Marine (Enterococcus<\\/i>)
Category: 130 - 999 (380/100mL)<\\/html>\",\"Station Number: 145
Class: Freshwater (E. coli<\\/i>)
Category: 126 - 409 (180/100mL)<\\/html>\",\"Station Number: 146
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (32/100mL)<\\/html>\",\"Station Number: 147
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (6/100mL)<\\/html>\",\"Station Number: 148
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (92/100mL)<\\/html>\",\"Station Number: 149
Class: Freshwater (E. coli<\\/i>)
Category: 126 - 409 (180/100mL)<\\/html>\",\"Station Number: 151
Class: Freshwater (E. coli<\\/i>)
Category: 410 - 999 (527/100mL)<\\/html>\",\"Station Number: 152
Class: Marine (Enterococcus<\\/i>)
Category: > 999 (1010/100mL)<\\/html>\",\"Station Number: 153
Class: Marine (Enterococcus<\\/i>)
Category: 130 - 999 (550/100mL)<\\/html>\",\"Station Number: 154
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (80/100mL)<\\/html>\",\"Station Number: 155
Class: Freshwater (E. coli<\\/i>)
Category: 126 - 409 (170/100mL)<\\/html>\",\"Station Number: 158
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (53/100mL)<\\/html>\",\"Station Number: 160
Class: Freshwater (E. coli<\\/i>)
Category: 126 - 409 (140/100mL)<\\/html>\",\"Station Number: 161
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (100/100mL)<\\/html>\",\"Station Number: 163
Class: Freshwater (E. coli<\\/i>)
Category: 126 - 409 (240/100mL)<\\/html>\",\"Station Number: 164
Class: Freshwater (E. coli<\\/i>)
Category: 126 - 409 (160/100mL)<\\/html>\",\"Station Number: 165
Class: Freshwater (E. coli<\\/i>)
Category: 126 - 409 (287/100mL)<\\/html>\",\"Station Number: 166
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (60/100mL)<\\/html>\",\"Station Number: 168
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (47/100mL)<\\/html>\",\"Station Number: 169
Class: Freshwater (E. coli<\\/i>)
Category: 126 - 409 (240/100mL)<\\/html>\",\"Station Number: 170
Class: Freshwater (E. coli<\\/i>)
Category: 126 - 409 (140/100mL)<\\/html>\",\"Station Number: 171
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (14/100mL)<\\/html>\",\"Station Number: 172
Class: Freshwater (E. coli<\\/i>)
Category: 126 - 409 (240/100mL)<\\/html>\",\"Station Number: 173
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (107/100mL)<\\/html>\",\"Station Number: 174
Class: Marine (Enterococcus<\\/i>)
Category: 35 - 129 (63/100mL)<\\/html>\",\"Station Number: 175
Class: Freshwater (E. coli<\\/i>)
Category: 126 - 409 (400/100mL)<\\/html>\",\"Station Number: 176
Class: Marine (Enterococcus<\\/i>)
Category: 130 - 999 (377/100mL)<\\/html>\",\"Station Number: 177
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (12/100mL)<\\/html>\",\"Station Number: 178
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (20/100mL)<\\/html>\",\"Station Number: 179
Class: Marine (Enterococcus<\\/i>)
Category: 130 - 999 (130/100mL)<\\/html>\",\"Station Number: 180
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (2/100mL)<\\/html>\",\"Station Number: 181
Class: Marine (Enterococcus<\\/i>)
Category: 35 - 129 (78/100mL)<\\/html>\",\"Station Number: 182
Class: Marine (Enterococcus<\\/i>)
Category: 35 - 129 (128/100mL)<\\/html>\",\"Station Number: 264
Class: Marine (Enterococcus<\\/i>)
Category: < 35 (20/100mL)<\\/html>\",\"Station Number: 265
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (100/100mL)<\\/html>\",\"Station Number: 266
Class: Freshwater (E. coli<\\/i>)
Category: 126 - 409 (135/100mL)<\\/html>\",\"Station Number: 267
Class: Freshwater (E. coli<\\/i>)
Category: > 999 (1700/100mL)<\\/html>\",\"Station Number: 268
Class: Freshwater (E. coli<\\/i>)
Category: > 999 (1400/100mL)<\\/html>\",\"Station Number: 269
Class: Freshwater (E. coli<\\/i>)
Category: > 999 (2400/100mL)<\\/html>\",\"Station Number: 270
Class: Marine (Enterococcus<\\/i>)
Category: > 999 (2600/100mL)<\\/html>\",\"Station Number: 271
Class: Freshwater (E. coli<\\/i>)
Category: > 999 (2400/100mL)<\\/html>\",\"Station Number: 520
Class: Freshwater (E. coli<\\/i>)
Category: 410 - 999 (700/100mL)<\\/html>\",\"Station Number: 523
Class: Freshwater (E. coli<\\/i>)
Category: 410 - 999 (670/100mL)<\\/html>\",\"Station Number: 528
Class: Freshwater (E. coli<\\/i>)
Category: 126 - 409 (400/100mL)<\\/html>\",\"Station Number: 529
Class: Freshwater (E. coli<\\/i>)
Category: 410 - 999 (880/100mL)<\\/html>\",\"Station Number: 533
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (90/100mL)<\\/html>\",\"Station Number: 534
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (60/100mL)<\\/html>\",\"Station Number: 536
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (82/100mL)<\\/html>\",\"Station Number: 541
Class: Freshwater (E. coli<\\/i>)
Category: 410 - 999 (650/100mL)<\\/html>\",\"Station Number: 543
Class: Freshwater (E. coli<\\/i>)
Category: 126 - 409 (200/100mL)<\\/html>\",\"Station Number: 545
Class: Freshwater (E. coli<\\/i>)
Category: 126 - 409 (160/100mL)<\\/html>\",\"Station Number: 547
Class: Freshwater (E. coli<\\/i>)
Category: 126 - 409 (400/100mL)<\\/html>\",\"Station Number: 548
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (28/100mL)<\\/html>\",\"Station Number: 549
Class: Freshwater (E. coli<\\/i>)
Category: > 999 (2100/100mL)<\\/html>\",\"Station Number: 550
Class: Freshwater (E. coli<\\/i>)
Category: > 999 (1800/100mL)<\\/html>\",\"Station Number: 551
Class: Freshwater (E. coli<\\/i>)
Category: 410 - 999 (500/100mL)<\\/html>\",\"Station Number: 552
Class: Freshwater (E. coli<\\/i>)
Category: > 999 (2220/100mL)<\\/html>\",\"Station Number: 553
Class: Freshwater (E. coli<\\/i>)
Category: 410 - 999 (433/100mL)<\\/html>\",\"Station Number: 554
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (4/100mL)<\\/html>\",\"Station Number: 555
Class: Freshwater (E. coli<\\/i>)
Category: > 999 (2733/100mL)<\\/html>\",\"Station Number: 556
Class: Freshwater (E. coli<\\/i>)
Category: 126 - 409 (140/100mL)<\\/html>\",\"Station Number: 557
Class: Freshwater (E. coli<\\/i>)
Category: > 999 (1700/100mL)<\\/html>\",\"Station Number: 558
Class: Freshwater (E. coli<\\/i>)
Category: 126 - 409 (170/100mL)<\\/html>\",\"Station Number: 559
Class: Freshwater (E. coli<\\/i>)
Category: 410 - 999 (500/100mL)<\\/html>\",\"Station Number: 573
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (100/100mL)<\\/html>\",\"Station Number: 574
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (90/100mL)<\\/html>\",\"Station Number: 575
Class: Freshwater (E. coli<\\/i>)
Category: 126 - 409 (240/100mL)<\\/html>\",\"Station Number: 576
Class: Freshwater (E. coli<\\/i>)
Category: 410 - 999 (833/100mL)<\\/html>\",\"Station Number: 604
Class: Freshwater (E. coli<\\/i>)
Category: 126 - 409 (350/100mL)<\\/html>\",\"Station Number: 605
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (76/100mL)<\\/html>\",\"Station Number: 606
Class: Freshwater (E. coli<\\/i>)
Category: < 126 (80/100mL)<\\/html>\",\"Station Number: 607
Class: Freshwater (E. coli<\\/i>)
Category: 126 - 409 (150/100mL)<\\/html>\",\"Station Number: 612
Class: Freshwater (E. coli<\\/i>)
Category: > 999 (1160/100mL)<\\/html>\",\"Station Number: 615
Class: Freshwater (E. coli<\\/i>)
Category: 410 - 999 (600/100mL)<\\/html>\",\"Station Number: 618
Class: Freshwater (E. coli<\\/i>)
Category: 126 - 409 (250/100mL)<\\/html>\",\"Station Number: 623
Class: Freshwater (E. coli<\\/i>)
Category: 410 - 999 (680/100mL)<\\/html>\",\"Station Number: 625
Class: Freshwater (E. coli<\\/i>)
Category: 126 - 409 (240/100mL)<\\/html>\",\"Station Number: 626
Class: Freshwater (E. coli<\\/i>)
Category: 126 - 409 (380/100mL)<\\/html>\",\"Station Number: 627
Class: Freshwater (E. coli<\\/i>)
Category: 410 - 999 (560/100mL)<\\/html>\",\"Station Number: 1510
Class: Marine (Enterococcus<\\/i>)
Category: > 999 (1200/100mL)<\\/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\":[27.53248,28.16544],\"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') 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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: 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>)
Category: < 126 (30/100mL)<\\/html>\",\"Station Number: 139
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, 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\" 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, 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":"Colors indicate target goal met, trending (red), target goal met, trending (yellow), target goal met, trending (light green), target goal met, trending (green). Numbers cell show proportion target goal met year data available. 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,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\":[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\":[-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\":[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: 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show_ratab","text":"epcdata data frame epc data returned read_importwq yrsel numeric indicating chosen year bay_segment chr string bay segment, one \"OTB\", \"HB\", \"MTB\", \"LTB\", \"RALTB\" partialyr logical indicating incomplete annual data recent year 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) 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/ 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","code":"show_ratab(epcdata, yrsel = 2022, bay_segment = 'OTB') #> Registered S3 method overwritten by 'ftExtra': #> method from #> as_flextable.data.frame flextable .cl-f4587552{}.cl-f452ac3a{font-family:'Lato light';font-size:13pt;font-weight:normal;font-style:normal;text-decoration:none;color:rgba(0, 0, 0, 1.00);background-color:transparent;}.cl-f452ac44{font-family:'Lato light';font-size:13pt;font-weight:bold;font-style:normal;text-decoration:none;color:rgba(0, 0, 0, 1.00);background-color:transparent;}.cl-f452ac4e{font-family:'Lato 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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;}.cl-f4553bb2{width:0.6in;background-color:rgba(144, 238, 144, 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;}.cl-f4553bb3{width:0.6in;background-color:rgba(255, 255, 255, 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;}.cl-f4553bb4{width:1.5in;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;}.cl-f4553bb5{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)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 yearsNoAll 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/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: Transformation introduced infinite values in continuous y-axis #> Warning: Transformation introduced infinite values in continuous x-axis"},{"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, 2022), 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, 2022), 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],\"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],\"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
\"],\"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\":[1974.52,2022.48],\"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\":[1974.52,2022.48],\"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\":[1974.52,2022.48],\"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],\"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],\"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,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,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],\"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: 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
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yval: 1.1896016
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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
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yval: 0.7686231
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yval: 0.7783039
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yval: 0.7871073
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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\":[5.6958409090909088,18.584007575757578],\"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 = 2022) #> 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 = 2022) show_tdlcrk(dat) 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MiniMap\",\"showText\":\"Show MiniMap\"},[]]},{\"method\":\"addLegend\",\"args\":[{\"colors\":[\"#ADD8E6\",\"#2DC938\",\"#E9C318\",\"#EE7600\",\"#FF4040\"],\"labels\":[\"No Data\",\"Monitor\",\"Caution\",\"Investigate\",\"Prioritize\"],\"na_color\":null,\"na_label\":\"NA\",\"opacity\":1,\"position\":\"topright\",\"type\":\"factor\",\"title\":\"Creek scores\",\"extra\":null,\"layerId\":null,\"className\":\"info 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score: 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: Caution\",\"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: Caution\",\"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: Monitor\",\"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: Monitor\",\"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: Investigate\",\"WBID: 1725, JEI: HC31, Name: NA, Creek score: Monitor\",\"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: Monitor\",\"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: Monitor\",\"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: No Data\",\"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: Monitor\",\"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: Monitor\",\"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: No Data\",\"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: Caution\",\"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: Prioritize\",\"WBID: 3258D4, JEI: LC48, Name: Estero River/Halfway Creek, Creek score: No Data\",\"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: Monitor\",\"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: No Data\",\"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: Investigate\",\"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: Investigate\",\"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: Caution\",\"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: Monitor\",\"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: Investigate\",\"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 = 2022, 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 = 2022) 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 = 2022, 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 = 2022) 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 = 2022) 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 = 2022, 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, 2022), 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 = c(\"Halodule\", \"Syringodium\", \"Thalassia\", \"Halophila\", \"Ruppia\", \"Caulerpa\"), yrrng = c(1998, 2023), varplo = c(\"Abundance\", \"Blade Length\", \"Short Shoot Density\"), base_size = 12, facet = FALSE, ncol = NULL, plotly = FALSE, width = NULL, height = NULL, sppcol = NULL )"},{"path":"https://tbep-tech.github.io/tbeptools/reference/show_transect.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot results for a seagrass transect by time and location — show_transect","text":"transect data frame returned read_transect site chr string indicating site results plot species chr string indicating one many species plot yrrng numeric indicating year ranges evaluate varplo chr string indicating variable plot base_size numeric indicating text scaling size plot facet logical indicating plots separated facets species ncol numeric indicating number columns facet = TRUE plotly logical plot created using plotly 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_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. 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'), varplo = 'Abundance') # multiple species, multiple plots show_transect(transect, site = 'S3T10', species = c('Halodule', 'Syringodium', 'Thalassia', 'Halophila', 'Ruppia', 'Caulerpa'), 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\"), 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\" 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","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\"), 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.","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 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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, 2022), 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 64 — tidalcreeks","title":"Spatial data object of tidal creeks in Impaired Waters Rule, Run 64 — tidalcreeks","text":"Spatial data object tidal creeks Impaired Waters Rule, Run 64","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 64 — 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 64 — 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 64 — 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 64 — 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 12062023 — transect","title":"Seagrass transect data for Tampa Bay current as of 12062023 — transect","text":"Seagrass transect data Tampa Bay current 12062023","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 12062023 — 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 12062023 — 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 12062023 — 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 — util_orgin","title":"Get organization name from organization identifier — util_orgin","text":"Get organization name organization identifier","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 — 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 — 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 — 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 — util_orgin","text":"","code":"util_orgin('21FLHILL_WQX') #> [1] \"Hillsborough\" util_orgin('21FLPASC_WQX', stanm = TRUE) #> [1] \"pasco_station\""}]