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ee2d460686e999efb441b890d316f9b88adea97c Mon Sep 17 00:00:00 2001 From: The Open Journals editorial robot <89919391+editorialbot@users.noreply.github.com> Date: Tue, 7 Nov 2023 16:38:10 +0000 Subject: [PATCH 2/4] Creating 10.21105.joss.05446.crossref.xml --- joss.05446/10.21105.joss.05446.crossref.xml | 242 ++++++++++++++++++++ 1 file changed, 242 insertions(+) create mode 100644 joss.05446/10.21105.joss.05446.crossref.xml diff --git a/joss.05446/10.21105.joss.05446.crossref.xml b/joss.05446/10.21105.joss.05446.crossref.xml new file mode 100644 index 0000000000..e5200ae30e --- /dev/null +++ b/joss.05446/10.21105.joss.05446.crossref.xml @@ -0,0 +1,242 @@ + + + + 20231107T163738-23e4981d44171b70eaa4fc36d74a865319ce59d2 + 20231107163738 + + JOSS Admin + admin@theoj.org + + The Open Journal + + + + + Journal of Open Source Software + JOSS + 2475-9066 + + 10.21105/joss + https://joss.theoj.org + + + + + 11 + 2023 + + + 8 + + 91 + + + + pyflowline: a mesh-independent river network generator +for hydrologic models + + + + Chang + Liao + https://orcid.org/0000-0002-7348-8858 + + + Matt G + Cooper + https://orcid.org/0000-0002-0165-209X + + + + 11 + 07 + 2023 + + + 5446 + + + 10.21105/joss.05446 + + + http://creativecommons.org/licenses/by/4.0/ + http://creativecommons.org/licenses/by/4.0/ + http://creativecommons.org/licenses/by/4.0/ + + + + Software archive + 10.5281/zenodo.10076553 + + + GitHub review issue + https://github.com/openjournals/joss-reviews/issues/5446 + + + + 10.21105/joss.05446 + https://joss.theoj.org/papers/10.21105/joss.05446 + + + https://joss.theoj.org/papers/10.21105/joss.05446.pdf + + + + + + ’Unified’ laguerre-Power Meshes For Coupled +Earth System Modelling + Engwirda + 29th International Meshing Roundtable (IMR), +Virtual Conference + 10.5281/zenodo.5558988 + 2021 + Engwirda, D., & Liao, C. (2021). +’Unified’ laguerre-Power Meshes For Coupled Earth System Modelling. 29th +International Meshing Roundtable (IMR), Virtual Conference. +https://doi.org/10.5281/zenodo.5558988 + + + Investigating coastal backwater effects and +flooding in the coastal zone using a global river transport model on an +unstructured mesh + Feng + Hydrology and Earth System +Sciences + 21 + 26 + 10.5194/hess-26-5473-2022 + 1027-5606 + 2022 + Feng, D., Tan, Z., Engwirda, D., +Liao, C., Xu, D., Bisht, G., Zhou, T., Li, H.-Y., & Leung, L. R. +(2022). Investigating coastal backwater effects and flooding in the +coastal zone using a global river transport model on an unstructured +mesh. Hydrology and Earth System Sciences, 26(21), 5473–5491. +https://doi.org/10.5194/hess-26-5473-2022 + + + Topological Relationship-Based Flow Direction +Modeling: Mesh-Independent River Networks Representation + Liao + Journal of Advances in Modeling Earth +Systems + 2 + 15 + 10.1029/2022MS003089 + 2023 + Liao, C., Zhou, T., Xu, D., Cooper, +M. G., Engwirda, D., Li, H.-Y., & Leung, L. R. (2023). Topological +Relationship-Based Flow Direction Modeling: Mesh-Independent River +Networks Representation. Journal of Advances in Modeling Earth Systems, +15(2), e2022MS003089. +https://doi.org/10.1029/2022MS003089 + + + mizuRoute version 1: A River Network Routing +Tool for a Continental Domain Water Resources +Applications + Mizukami + Geoscientific Model +Development + 6 + 9 + 10.5194/gmd-9-2223-2016 + 1991-959X + 2016 + Mizukami, N., Clark, M. P., Sampson, +K., Nijssen, B., Mao, Y., McMillan, H., Viger, R. J., Markstrom, S. L., +Hay, L. E., Woods, R., Arnold, J. R., & Brekke, L. D. (2016). +mizuRoute version 1: A River Network Routing Tool for a Continental +Domain Water Resources Applications. Geoscientific Model Development, +9(6), 2223–2238. +https://doi.org/10.5194/gmd-9-2223-2016 + + + RivGraph: Automatic extraction and analysis +of river and delta channel network topology + Schwenk + Journal of Open Source +Software + 59 + 6 + 10.21105/joss.02952 + 2021 + Schwenk, J., & Hariharan, J. +(2021). RivGraph: Automatic extraction and analysis of river and delta +channel network topology. Journal of Open Source Software, 6(59), 2952. +https://doi.org/10.21105/joss.02952 + + + Arc Hydro Tools - Tutorial +[Software] + Esri Water Resources Team + 2011 + Esri Water Resources Team. (2011). +Arc Hydro Tools - Tutorial [Software]. + + + A new global river network database for +macroscale hydrologic modeling + Wu + Water Resources Research + 9 + 48 + 10.1029/2012WR012313 + 2012 + Wu, H., Kimball, J. S., Li, H., +Huang, M., Leung, L. R., & Adler, R. F. (2012). A new global river +network database for macroscale hydrologic modeling. Water Resources +Research, 48(9). +https://doi.org/10.1029/2012WR012313 + + + PyEarth: A lightweight Python package for +Earth science + Liao + 10.5281/zenodo.6109987 + 2022 + Liao, C. (2022). PyEarth: A +lightweight Python package for Earth science (Version 0.1.20). Zenodo. +https://doi.org/10.5281/zenodo.6109987 + + + User documentation for discrete global grid +generation software + Sahr + Southern Oregon Univ., Ashland, OR, USA, +Tech. Rep. Dggrid version + 3 + 2011 + Sahr, K. (2011). User documentation +for discrete global grid generation software. Southern Oregon Univ., +Ashland, OR, USA, Tech. Rep. Dggrid Version, 3. + + + Topological Relationship-Based Flow Direction +Modeling: Stream Burning and Depression Filling + Liao + Journal of Advances in Modeling Earth +Systems + 11 + 15 + 10.1029/2022MS003487 + 2023 + Liao, C., Zhou, T., Xu, D., Tan, Z., +Bisht, G., Cooper, M. G., Engwirda, D., Li, H.-Y., & Leung, L. R. +(2023). Topological Relationship-Based Flow Direction Modeling: Stream +Burning and Depression Filling. Journal of Advances in Modeling Earth +Systems, 15(11), e2022MS003487. +https://doi.org/10.1029/2022MS003487 + + + + + + From daec6425d5254092d58210abf74c9869446b7e74 Mon Sep 17 00:00:00 2001 From: The Open Journals editorial robot <89919391+editorialbot@users.noreply.github.com> Date: Tue, 7 Nov 2023 16:38:11 +0000 Subject: [PATCH 3/4] Creating 10.21105.joss.05446.jats --- joss.05446/10.21105.joss.05446.jats | 466 ++++++++++++++++++++++++++++ 1 file changed, 466 insertions(+) create mode 100644 joss.05446/10.21105.joss.05446.jats diff --git a/joss.05446/10.21105.joss.05446.jats b/joss.05446/10.21105.joss.05446.jats new file mode 100644 index 0000000000..f16433a5d1 --- /dev/null +++ b/joss.05446/10.21105.joss.05446.jats @@ -0,0 +1,466 @@ + + +
+ + + + +Journal of Open Source Software +JOSS + +2475-9066 + +Open Journals + + + +5446 +10.21105/joss.05446 + +pyflowline: a mesh-independent river network generator +for hydrologic models + + + +https://orcid.org/0000-0002-7348-8858 + +Liao +Chang + + + + +https://orcid.org/0000-0002-0165-209X + +Cooper +Matt G + + + + + +Atmospheric, Climate, and Earth Sciences, Pacific Northwest +National Laboratory, Richland, WA, USA + + + + +23 +3 +2023 + +8 +91 +5446 + +Authors of papers retain copyright and release the +work under a Creative Commons Attribution 4.0 International License (CC +BY 4.0) +2022 +The article authors + +Authors of papers retain copyright and release the work under +a Creative Commons Attribution 4.0 International License (CC BY +4.0) + + + +Python +hydrologic model +river networks +mesh +geographic information system + + + + + + Summary +

River networks are crucial in hydrologic and Earth system models. + Accurately representing river networks in hydrologic models requires + considering the model’s spatial resolution and computational mesh. + However, current river network representation methods often have + several limitations: (1) vector-based; (2) they perform poorly at + coarse resolution (3) they do not support unstructured meshes. To + overcome these limitations, we developed PyFlowline, a Python package + that generates mesh-independent river networks. With PyFlowline, + hydrologic modelers can generate conceptual river networks at various + spatial resolutions for both structured and unstructured computational + meshes. The generated river network datasets can be used by hydrologic + models across scales.

+
+ + Statement of need +

For hydrologic modelers, river networks are a key input for + hydrologic models. While some hydrologic models accept vector-based + river networks + (Mizukami + et al., 2016; + Schwenk + & Hariharan, 2021), others only accept mesh cell-based + representations, or require a generation method from a vector-based + river network. Currently, generating a mesh cell-based river network + from a given vector-based river network and arbitrary computational + mesh is a major challenge. Existing methods are typically limited to + structured rectangular meshes, such as 30m x 30m cartesian grids for + high-resolution watershed-scale modeling or 0.5 degree x 0.5 degree + geographic grids for global climate modeling. In PyFlowline, we define + structured meshes (e.g., lat-lon, raster files with projections, and + hexagon) as those with fixed cell sizes and shapes and unstructured + meshes as those with variable cell sizes and shapes.

+

Structured mesh-based methods use fixed cartesian or geographic + cell sizes, which have several limitations: (1) they cannot resolve + fine-scale river networks at coarse cell resolutions (>1km), and + (2) they cannot be seamlessly coupled with other unstructured + mesh-based hydrologic models such as oceanic models + (Engwirda + & Liao, 2021). In contrast, unstructured meshes offer a + flexible structure with variable grid-cell sizes and shapes. This + flexibility makes them ideal for adapting to complex geometry such as + river channels and coastlines. Besides, unstructured meshes provide + the flexibility to couple different hydrologic models under a unified + framework. Thus, unstructured meshes are increasingly being adopted in + hydrologic modeling.

+

Although unstructured meshes offer these flexibilities, additional + efforts are required to generate conceptual river networks that + capture real-world river networks across different spatial scales.

+

A mesh-independent river network representation method that + preserves topological relationships across scales could address this + limitation. PyFlowline is a Python package that provides a framework + for generating river networks for hydrologic models, meeting the + identified need. Using an object-oriented programming approach, + PyFlowline represents river network elements and mesh cell + relationships. It relies on open-source Python libraries like GDAL and + Cython for data input/output and spatial data operations.

+

The computational geometry algorithms used in PyFlowline are + designed and implemented using a unified spherical framework, making + it suitable for regional and global-scale simulations. PyFlowline uses + topological relationships to capture the river networks so they are + preserved even at coarse spatial resolutions. Moreover, PyFlowline is + mesh-independent, supporting both structured and unstructured meshes. + It can quickly adopt other mesh types, such as triangulated irregular + networks (TIN) or discrete global grid systems (DGGs) + (Sahr, + 2011). PyFlowline is a core component of the HexWatershed + model, a mesh-independent flow direction model. Several scientific + studies focusing on coupled Earth system models + (Feng + et al., 2022; + Liao, + Zhou, Xu, Cooper, et al., 2023; + Liao, + Zhou, Xu, Tan, et al., 2023) have utilized PyFlowline. A + workshop tutorial has also been provided online and in person to + support its implementation.

+
+ + Model features +

PyFlowline uses Python’s object-oriented programming (OOP) + architecture to describe river networks using three essential + elements: segments, reaches, and confluences. When applicable, river + networks are processed as objects throughout the package.

+ +

The data model. A vertex class object represents a point + on the Earth surface. It has three coordinates. An edge class object + represents a directed line between two points. Besides, it has a + length attribute. A flowline class object represents a list of + connected lines. +

+ +
+

PyFlowline provides several key features, including

+ + +

Support for both structured and unstructured meshes, with JSON + as the default file I/O format. For geospatial datasets such as + vector river networks, GEOJSON is used.

+
+ +

Regional and global-scale processing capabilities through the + use of fast Cython- and (global-only) AABB tree-based + algorithms.

+
+ +

Built-in visualization functions (experimental) based on the + Python Matplotlib package + (Liao, + 2022), making it easy to visualize and analyze the + PyFlowline model outputs.

+
+
+
+ + State of the field +

Existing river network representation methods often fall into three + categories, each with associated strengths and weaknesses:

+ + +

Vector-based. Hydrologic models that use this method can + represent fine-scale river networks, but cannot couple river and + land without one-to-one mapping between river segments and land + model cells + (Schwenk + & Hariharan, 2021);

+
+ +

High-resolution DEM-based. Flow networks derived from + structured rectangle-grid DEMs are widely available, but resolving + fine-scale river networks requires grids with very high spatial + resolution (e.g., 30m x 30m or finer) + (Esri + Water Resources Team, 2011);

+
+ +

Upscaling-based methods address the scale mismatch between + coarse-resolution grids and fine-scale river networks, but only + support structured geographic grids (e.g., 0.5 degree x 0.5 + degree) at coarse resolutions + (Wu + et al., 2012). This method often cannot provide global + coverage, including Greenland and the Antarctic.

+
+
+

PyFlowline is the only modeling software that provides these unique + features:

+ + +

It can generate river networks on unstructured meshes;

+
+ +

It uses topological relationships to capture river networks + precisely;

+
+ +

It can be applied at both high and coarse resolutions;

+
+ +

It can provide global coverage, including Greenland and the + Antarctic.

+
+
+

Model documentation is hosted at + https://pyflowline.readthedocs.io/en/latest/, including a case study + for the Susquehanna River Basin in the Mid-Atlantic region of the + United States.

+
+ + Acknowledgment +

The model described in this repository was supported by the + following:

+ + +

the Earth System Model Development and Regional and Global + Model Analysis program areas of the U.S. Department of Energy, + Office of Science, Biological and Environmental Research program + as part of the multi-program, collaborative Integrated Coastal + Modeling (ICoM) project.

+
+ +

the Earth System Model Development and Regional and Global + Model Analysis program areas of the U.S. Department of Energy, + Office of Science, Biological and Environmental Research program + as part of the multi-program, collaborative Interdisciplinary + Research for Arctic Coastal Environments (InteRFACE) project.

+
+ +

the Next Generation Ecosystem Experiments-Tropics project, + funded by the U.S. Department of Energy, Office of Science, Office + of Biological and Environmental Research at Pacific Northwest + National Laboratory.

+
+
+

A portion of this research was performed using PNNL Research + Computing at Pacific Northwest National Laboratory.

+

PNNL is operated for DOE by Battelle Memorial Institute under + contract DE-AC05-76RL01830.

+
+ + + + + + + EngwirdaDarren + LiaoChang + + ’Unified’ laguerre-Power Meshes For Coupled Earth System Modelling + 29th International Meshing Roundtable (IMR), Virtual Conference + 2021 + 10.5281/zenodo.5558988 + + + + + + FengDongyu + TanZeli + EngwirdaDarren + LiaoChang + XuDonghui + BishtGautam + ZhouTian + LiHong-Yi + LeungL Ruby + + Investigating coastal backwater effects and flooding in the coastal zone using a global river transport model on an unstructured mesh + Hydrology and Earth System Sciences + Copernicus GmbH + 2022 + 26 + 21 + 1027-5606 + 10.5194/hess-26-5473-2022 + 5473 + 5491 + + + + + + LiaoChang + ZhouTian + XuDonghui + CooperMatthew G. + EngwirdaDarren + LiHong-Yi + LeungL. Ruby + + Topological Relationship-Based Flow Direction Modeling: Mesh-Independent River Networks Representation + Journal of Advances in Modeling Earth Systems + 2023 + 15 + 2 + https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2022MS003089 + 10.1029/2022MS003089 + e2022MS003089 + + + + + + + MizukamiNaoki + ClarkMartyn P. + SampsonKevin + NijssenBart + MaoYixin + McMillanHilary + VigerRoland J. + MarkstromSteve L. + HayLauren E. + WoodsRoss + ArnoldJeffrey R. + BrekkeLevi D. + + mizuRoute version 1: A River Network Routing Tool for a Continental Domain Water Resources Applications + Geoscientific Model Development + Copernicus GmbH + 201606 + 20230803 + 9 + 6 + 1991-959X + 10.5194/gmd-9-2223-2016 + 2223 + 2238 + + + + + + SchwenkJon + HariharanJayaram + + RivGraph: Automatic extraction and analysis of river and delta channel network topology + Journal of Open Source Software + The Open Journal + 2021 + 6 + 59 + https://doi.org/10.21105/joss.02952 + 10.21105/joss.02952 + 2952 + + + + + + + Esri Water Resources Team + + Arc Hydro Tools - Tutorial [Software] + 2011 + + + + + + WuHuan + KimballJohn S. + LiHongyi + HuangMaoyi + LeungL. Ruby + AdlerRobert F. + + A new global river network database for macroscale hydrologic modeling + Water Resources Research + 2012 + 48 + 9 + https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2012WR012313 + 10.1029/2012WR012313 + + + + + + + + LiaoChang + + PyEarth: A lightweight Python package for Earth science + Zenodo + 202203 + https://doi.org/10.5281/zenodo.6109987 + 10.5281/zenodo.6109987 + + + + + + SahrK + + User documentation for discrete global grid generation software + Southern Oregon Univ., Ashland, OR, USA, Tech. Rep. Dggrid version + 2011 + 3 + + + + + + LiaoChang + ZhouTian + XuDonghui + TanZeli + BishtGautam + CooperMatthew G. + EngwirdaDarren + LiHong-Yi + LeungL. Ruby + + Topological Relationship-Based Flow Direction Modeling: Stream Burning and Depression Filling + Journal of Advances in Modeling Earth Systems + 2023 + 15 + 11 + https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2022MS003487 + 10.1029/2022MS003487 + e2022MS003487 + + + + + +
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