MOGESTpy

Hydrological and water resources management modeling library in Python, supporting quantity and quality simulations for decision-making.

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Table of Contents

• MOGESTpy
  • What is MOGESTpy?
    • Water Resources Management Model
  • Models used in MOGESTpy
  • Repository Structure
  • How to Use MOGESTpy?
    • Installing MOGESTpy
      • Locally
      • Using pip
  • How to Contribute to the Project?
  • Citation

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What is MOGESTpy?

MOGESTpy is an acronym for Modelo de Gestão de Recursos Hídricos (Water Resources Management Model), developed in Python.

Water Resources Management Model

A water resources management model integrates quantity and quality modeling tools to support decision-making processes. These models simulate natural processes, from precipitation over the watershed to flow routing in rivers and channels, ultimately representing the system response at the watershed outlet.

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Models used in MOGESTpy

The models currently available in MOGESTpy include:

• SIHQUAL
• SMAP
• 0D (Zero Dimensional)
• BuildUp-Washoff

For more details, please refer to the documentation within the repository.

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Repository Structure

The package is organized as following:

MOGESTpy
├─ quality
│  ├─ buwo.py
│  └─ zerod.py
└─ quantity
   ├─ hydrological
   │  ├─ smap.py
   │  ├─ muskingum.py
   │  └─ mass_balance.py
   └─ hydrodynamic
      └─ sihqual.py

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How to Use MOGESTpy?

Installing MOGESTpy

Locally

Using pip

The package is available on PyPI, and you can install it using pip:

pip install mogestpy

Alternatively, it is possible to clone the repository and install the package using pip:

pip install .

Or in editable mode:

pip install -e .

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How to Contribute to the Project?

Contributions are welcome!

• Open an issue to report bugs or suggest features
• Submit pull requests with improvements or new models

Please make sure to follow the guidelines described in the contributing document.

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Citation

If you use MOGESTpy in your research, please cite:

@software{mogestpy,
  author = {Dario Hachisu Hossoda},
  title = {MOGESTpy},
  year = {2026},
  url = {https://doi.org/10.5281/zenodo.19308873},
  doi = {10.5281/zenodo.19308873}
}

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Acknowledgments
Laboratory of Decision Support Systems