Science Score: 67.0%
This score indicates how likely this project is to be science-related based on various indicators:
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○CITATION.cff file
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✓codemeta.json file
Found codemeta.json file -
✓.zenodo.json file
Found .zenodo.json file -
✓DOI references
Found 2 DOI reference(s) in README -
✓Academic publication links
Links to: zenodo.org -
✓Committers with academic emails
1 of 3 committers (33.3%) from academic institutions -
✓Institutional organization owner
Organization hydrology-ifh has institutional domain (www.hydro.uni-freiburg.de) -
○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (16.6%) to scientific vocabulary
Repository
Runoff Generation Research in Python
Basic Info
- Host: GitHub
- Owner: Hydrology-IFH
- License: mit
- Language: Python
- Default Branch: main
- Homepage: https://roger.readthedocs.io/en/latest/
- Size: 1.14 GB
Statistics
- Stars: 19
- Watchers: 0
- Forks: 1
- Open Issues: 10
- Releases: 10
Metadata Files
README.md
Runoff Generation Research - a process-based hydrological toolbox model in Python
RoGeR, Runoff Generation Research, is a process-based hydrological model that can be applied from plot to catchment scale. RoGeR is written in pure Python, which facilitates model setup and model workflows. We want to enable high-performance hydrological modelling with a clear focus on flexibility and usability.
RoGeR supports a NumPy backend for small-scale problems, and a high-performance JAX backend with CPU and GPU support. Parallel computation is available via MPI and supports distributed execution on any number of nodes/CPU cores.
Inspired by Veros.
Documentation
We strongly recommend to visit our documentation.
Features
(25 square meter resolved simulations of the Eberbaechle catchment, Germany (2019-2022), click for better quality)
RoGeR provides
- grid-based 1D models
- offline solute transport with several StorAge selection (SAS) functions
- solute-specific biogeochemical processes
- implementations of capillary-driven infiltration (Green-Ampt)
- several pre-implemented diagnostics such as averages or collecting values at given time interval, variable time aggregation, travel time distributions and residence time distributions (written to netCDF4 output)
- pre-configured idealized and realistic setups that are ready to run and easy to adapt
- accessibility and extensibility due to high-level programming language Python
Basic usage
To run RoGeR, you need to set up a model --- i.e., specify which settings
and model domain you want to use. This is done by subclassing the
RogerSetup base class in a setup script that is written in Python. A good
place to start is the
SVAT Tutorial:
After setting up your model, all you need to do is call the model setup: ```bash
move into the folder containing the model script
python svat.py ```
For more information on using RoGeR, have a look at our documentation.
Contributing
Contributions to RoGeR are always welcome, no matter if you spotted an inaccuracy in the documentation, wrote a new setup, fixed a bug, or even extended RoGeR\' core mechanics. There are 2 ways to contribute:
- If you want to report a bug or request a missing feature, please open an issue. If you are reporting a bug, make sure to include all relevant information for reproducing it (ideally through a minimal code sample).
- If you want to fix the issue yourself, or wrote an extension for Roger - great! You are welcome to submit your code for review by committing it to a repository and opening a pull request. However, before you do so, please check the contribution guide for some tips on testing and benchmarking, and to make sure that your modifications adhere with our style policies. Most importantly, please ensure that you follow the PEP8 guidelines, use meaningful variable names, and document your code using Google-style docstrings.
How to cite
If you use Roger in scientific work, please consider citing the following publication:
bibtex
@article{
title = {RoGeR v.3.0.5 - a process-based hydrological toolbox model in Python},
volume = {17},
doi = {https://doi.org/10.5194/gmd-17-5249-2024},
journal = {Geosci. Model Dev.},
author = {Schwemmle, Robin, and Leistert, Hannes, and Weiler, Markus},
year = {2024},
pages = {5249-5262},
}
Or have a look at our documentation for more publications involving Roger.
TODO
- implement runoff and channel routing (e.g. kinematic wave or hydraulic approach)
- implement distributed model with run-on infiltration
- use coarser spatial and temporal resolution for computation of groundwater-related processes
- implement baseflow in the groundwater routine. requires surface water depth.
- implement surface runoff generation for gravity-driven infiltration
- implement gravity-driven infiltration and percolation and include it into the transport routine
- implement time-variant sowing and harvesting of crops
License
This software can be distributed freely under the MIT license. Please read the LICENSE for further information. 2024, Robin Schwemmle (robin.schwemmle@hydrology.uni-freiburg.de)
Owner
- Name: Hydrology group @University of Freiburg
- Login: Hydrology-IFH
- Kind: organization
- Location: Germany
- Website: http://www.hydro.uni-freiburg.de/
- Repositories: 5
- Profile: https://github.com/Hydrology-IFH
GitHub Events
Total
- Release event: 1
- Watch event: 2
- Push event: 158
- Create event: 1
Last Year
- Release event: 1
- Watch event: 2
- Push event: 158
- Create event: 1
Committers
Last synced: 6 months ago
Top Committers
| Name | Commits | |
|---|---|---|
| schwemro | r****e@h****e | 1,636 |
| maxschmi | m****m@y****e | 8 |
| Max Schmit | m****m@h****m | 2 |
Committer Domains (Top 20 + Academic)
Issues and Pull Requests
Last synced: 6 months ago
All Time
- Total issues: 2
- Total pull requests: 64
- Average time to close issues: about 1 hour
- Average time to close pull requests: about 1 month
- Total issue authors: 2
- Total pull request authors: 2
- Average comments per issue: 0.5
- Average comments per pull request: 1.2
- Merged pull requests: 1
- Bot issues: 0
- Bot pull requests: 63
Past Year
- Issues: 0
- Pull requests: 0
- Average time to close issues: N/A
- Average time to close pull requests: N/A
- Issue authors: 0
- Pull request authors: 0
- Average comments per issue: 0
- Average comments per pull request: 0
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
- CodefromJiangHu (1)
- imifrenzel (1)
Pull Request Authors
- dependabot[bot] (60)
- maxschmi (1)
Top Labels
Issue Labels
Pull Request Labels
Packages
- Total packages: 3
-
Total downloads:
- pypi 78 last-month
-
Total dependent packages: 0
(may contain duplicates) -
Total dependent repositories: 0
(may contain duplicates) - Total versions: 30
- Total maintainers: 1
proxy.golang.org: github.com/hydrology-ifh/roger
- Documentation: https://pkg.go.dev/github.com/hydrology-ifh/roger#section-documentation
- License: mit
-
Latest release: v3.0.9+incompatible
published 7 months ago
Rankings
proxy.golang.org: github.com/Hydrology-IFH/roger
- Documentation: https://pkg.go.dev/github.com/Hydrology-IFH/roger#section-documentation
- License: mit
-
Latest release: v3.0.9+incompatible
published 9 months ago
Rankings
pypi.org: roger
Runoff Generation Research - a process-based hydrological toolbox model in Python
- Homepage: https://roger.readthedocs.io
- Documentation: https://roger.readthedocs.io/
- License: MIT
-
Latest release: 3.0.9
published 12 months ago
Rankings
Maintainers (1)
Dependencies
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- conda-incubator/setup-miniconda v2 composite
- actions/checkout v2 composite
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- Sphinx ==5.2.3
- click ==8.0.3
- entrypoints ==0.4
- ipython ==8.5.0
- matplotlib ==3.6.1
- netCDF4 ==1.6.0
- seaborn ==0.11.2
- sphinx-rtd-theme ==1.0.0
- xarray ==2022.6.0