roger

Runoff Generation Research in Python

https://github.com/hydrology-ifh/roger

Science Score: 67.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • CITATION.cff file
  • 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
  • Scientific vocabulary similarity
    Low similarity (16.6%) to scientific vocabulary
Last synced: 6 months ago · JSON representation

Repository

Runoff Generation Research in Python

Basic Info
Statistics
  • Stars: 19
  • Watchers: 0
  • Forks: 1
  • Open Issues: 10
  • Releases: 10
Created over 3 years ago · Last pushed 7 months ago
Metadata Files
Readme License Citation

README.md

Runoff Generation Research - a process-based hydrological toolbox model in Python

Documentation status Test status DOI

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

RoGeR - 25 square meter resolved simulations of the Eberbaechle catchment, Germany (2019-2022)

(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:

  1. 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).
  2. 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

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

All Time
  • Total Commits: 1,646
  • Total Committers: 3
  • Avg Commits per committer: 548.667
  • Development Distribution Score (DDS): 0.006
Past Year
  • Commits: 251
  • Committers: 1
  • Avg Commits per committer: 251.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email 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
bug (1)
Pull Request Labels
dependencies (59)

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
  • Versions: 10
  • Dependent Packages: 0
  • Dependent Repositories: 0
Rankings
Dependent packages count: 5.3%
Average: 5.4%
Dependent repos count: 5.6%
Last synced: 6 months ago
proxy.golang.org: github.com/Hydrology-IFH/roger
  • Versions: 10
  • Dependent Packages: 0
  • Dependent Repositories: 0
Rankings
Dependent packages count: 5.4%
Average: 5.6%
Dependent repos count: 5.8%
Last synced: 6 months ago
pypi.org: roger

Runoff Generation Research - a process-based hydrological toolbox model in Python

  • Versions: 10
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 78 Last month
Rankings
Dependent packages count: 6.6%
Average: 22.6%
Downloads: 30.5%
Dependent repos count: 30.6%
Maintainers (1)
Last synced: 6 months ago

Dependencies

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.github/workflows/test-conda.yml actions
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.github/workflows/test-install.yml actions
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doc/requirements.txt pypi
  • 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