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A process-based model for simulating supply-limited aeolian sediment transport

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AeoLiS

AeoLiS is a process-based model for simulating aeolian sediment transport in situations where supply-limiting factors are important, like in coastal environments. Supply-limitations currently supported are soil moisture contents, sediment sorting and armouring, bed slope effects, air humidity and roughness elements.

AEOLIS.animation.-.Parabolic.mp4

Installation

Requirements:

  • Python 3.9 or newer
  • pip 22.0 or newer
  • netCDF4

Installing from PyPI

On the comand line of your working environment (Bash/Shell, Conda, Mamba, or similar), run the following:

pip install aeolis

For Windows users, the recommend way to install AeoLiS is to use Anaconda.

Installing from source

  1. Clone the repository using Git, or download the source code.

  2. AeoLiS users may install the package with only the required dependencies. Go to aeolis-python directory and install using pip

    cd aeolis-python/
    pip install .
  3. AeoLiS users who intend to modify the sourcecode can install additional dependencies for test and documentation as follows. Go to root directory aeolis-python/ and:

    pip install -e .[dev]

Running AeoLiS

Examples from command line:

aeolis run <path/to/aeolis.txt/>
# or wind module
aeolis wind <path/to/wind.txt> --mean=6 --duration=3600

Documentation

Detailed documentation can be found at AeoLiS ReadTheDocs

AeoLiS Developer Team

The maintenance and development is done by a group of very enthusiastic people.

Get Involved: Read our Contribution Guidelines to know how you can help to develop AeoLiS.

Current Members:

Previous Members & Contributors:

  • Bas Hoonhout (founder)
  • Tom Pak
  • Pieter Rauwoens
  • Lisa Meijer

Citation

Please, cite this software as follows:

de Vries, S., Hallin, C., van IJzendoorn, C., van Westen, B., Cohn, N., Strypsteen, G., Skaden, J., Agrawal, N., & Garcia Alvarez, M. (2023). AeoLiS (Version 3.0.0.rc1) [Computer software]. https://github.com/openearth/aeolis-python

Acknowlegdements

© (2023) AeoLiS Development Team, Delft, The Netherlands.

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