Watershed Workflow
Python workflows for data-rich, hyper-resolution simulations of hydrologic models on watersheds.
https://github.com/environmental-modeling-workflows/watershed-workflow
Category: Hydrosphere
Sub Category: Freshwater and Hydrology
Last synced: about 4 hours ago
JSON representation
Repository metadata
Python workflows for data-rich, hyper-resolution simulations of hydrologic models on watersheds.
- Host: GitHub
- URL: https://github.com/environmental-modeling-workflows/watershed-workflow
- Owner: environmental-modeling-workflows
- License: other
- Created: 2019-09-26T12:48:59.000Z (over 5 years ago)
- Default Branch: master
- Last Pushed: 2025-04-23T14:22:59.000Z (5 days ago)
- Last Synced: 2025-04-25T18:38:01.350Z (3 days ago)
- Language: Python
- Size: 147 MB
- Stars: 70
- Watchers: 4
- Forks: 32
- Open Issues: 3
- Releases: 8
-
Metadata Files:
- Readme: README.md
- License: LICENSE
- Authors: AUTHORS.rst
README.md
Watershed Workflow
Please prefer to see our documentation.
Watershed Workflow is a python-based, open source chain of tools for generating meshes and other data inputs for hyper-resolution hydrology, anywhere in the (conterminous + Alaska?) US.
Hyper-resolution hydrologic models have huge data requirements, thanks to their large extent (full river basins) and very high resolution (often ~10-100 meters). Furthermore, most process-rich models of integrated, distributed hydrology at this scale require meshes that understand both surface land cover and subsurface structure. Typical data needs for simulations such as these include:
- Watershed delineation (what is your domain?)
- Hydrography data (river network geometry, hydrographs for model evaluation)
- A digital elevation model (DEM) for surface topography
- Surface land use / land cover
- Subsurface soil types and properties
- Meterological data,
and more.
This package is a python library of tools and a set of jupyter notebooks for interacting with these types of data streams using free and open (both free as in freedom and free as in free beer) python and GIS libraries and data. Critically, this package provides a way for automatically and quickly downloading, interpreting, and processing data needed to generate a "first" hyper-resolution simulation on any watershed in the conterminous United States (and most of Alaska/Hawaii/Puerto Rico).
To do this, this package provides tools to automate downloading a wide range of open data streams, including data from United States governmental agencies, including USGS, USDA, DOE, and others. These data streams are then colocated on a mesh which is generated based on a watershed delineation and a river network, and that mesh is written in one of a variety of mesh formats for use in hyper-resolution simulation tools.
Note: Hypothetically, this package works on all of Linux, Mac, and Windows. It has been tested on the first two, but not the third.
Installation
Visit our Installation documentation.
For more...
Funding, attribution, etc
This work was supported by multiple US Department of Energy projects, and was mostly developed at the Oak Ridge National Laboratory. Use of this codebase in the academic literature should cite:
The use of stream-aligned mixed-polyhedral mesh should cite:
Collaborators and contributions are very welcome!
Owner metadata
- Name: environmental-modeling-workflows
- Login: environmental-modeling-workflows
- Email:
- Kind: organization
- Description:
- Website:
- Location:
- Twitter:
- Company:
- Icon url: https://avatars.githubusercontent.com/u/117863331?v=4
- Repositories: 2
- Last ynced at: 2023-12-06T21:26:54.319Z
- Profile URL: https://github.com/environmental-modeling-workflows
GitHub Events
Total
- Issues event: 11
- Watch event: 3
- Delete event: 5
- Issue comment event: 19
- Push event: 56
- Pull request review comment event: 5
- Pull request review event: 7
- Pull request event: 16
- Fork event: 3
- Create event: 7
Last Year
- Issues event: 11
- Watch event: 3
- Delete event: 5
- Issue comment event: 19
- Push event: 56
- Pull request review comment event: 5
- Pull request review event: 7
- Pull request event: 16
- Fork event: 3
- Create event: 7
Committers metadata
Last synced: 7 days ago
Total Commits: 381
Total Committers: 10
Avg Commits per committer: 38.1
Development Distribution Score (DDS): 0.113
Commits in past year: 8
Committers in past year: 3
Avg Commits per committer in past year: 2.667
Development Distribution Score (DDS) in past year: 0.25
| Name | Commits | |
|---|---|---|
| Ethan Coon | c****t@o****v | 338 |
| benliebersohn | b****n@g****m | 17 |
| pinshuai | p****8@g****m | 10 |
| saubhagya-gatech | s****e@o****m | 9 |
| Rich Fiorella | r****a@l****v | 2 |
| jgomezvelez | j****z@g****m | 1 |
| Soumendra Bhanja | s****a@g****m | 1 |
| Jemma Stachelek | j****a | 1 |
| Bo Gao | 8****b | 1 |
| Benjamin Liebersohn | l****t@o****v | 1 |
Committer domains:
Issue and Pull Request metadata
Last synced: 1 day ago
Total issues: 43
Total pull requests: 81
Average time to close issues: 8 months
Average time to close pull requests: about 1 month
Total issue authors: 12
Total pull request authors: 8
Average comments per issue: 1.86
Average comments per pull request: 0.81
Merged pull request: 66
Bot issues: 0
Bot pull requests: 0
Past year issues: 3
Past year pull requests: 10
Past year average time to close issues: 3 months
Past year average time to close pull requests: 24 days
Past year issue authors: 3
Past year pull request authors: 4
Past year average comments per issue: 1.67
Past year average comments per pull request: 0.8
Past year merged pull request: 7
Past year bot issues: 0
Past year bot pull requests: 0
Top Issue Authors
- ecoon (18)
- saubhagya-gatech (6)
- pinshuai (4)
- rfiorella (4)
- lijingwang (3)
- zexuanxu (2)
- Orilu (1)
- jsta (1)
- daniellivingston (1)
- gaobhub (1)
- ZhiLiHydro (1)
- akirke (1)
Top Pull Request Authors
- ecoon (33)
- saubhagya-gatech (19)
- pinshuai (15)
- jgomezvelez (6)
- soumendrabhanja (3)
- gaobhub (2)
- rfiorella (2)
- jsta (1)
Top Issue Labels
- enhancement (8)
- v2.0 (2)
- meta (1)
- bug (1)
Top Pull Request Labels
Dependencies
- rosetta-soil *
- actions/checkout v2 composite
- docker/build-push-action v3 composite
- docker/login-action v2 composite
- docker/setup-buildx-action v2 composite
- actions/checkout v2 composite
- docker/build-push-action v3 composite
- docker/login-action v2 composite
- docker/setup-buildx-action v2 composite
- actions/checkout v2 composite
- docker/build-push-action v3 composite
- docker/login-action v2 composite
- docker/setup-buildx-action v2 composite
- actions/checkout v2 composite
- docker/build-push-action v3 composite
- docker/login-action v2 composite
- docker/setup-buildx-action v2 composite
Score: 6.593044534142437