GeoFlood

Flood mapping program based on high-resolution terrain analyses.

Documentation and examples

https://passah2o.github.io/pygeoflood/

Installation

We recommend installing pygeoflood into a conda environment. Python 3.10, 3.11, or 3.12 is required:

$ pip install pygeoflood

For the bleeding-edge version, install from GitHub:

$ pip install git+https://github.com/passah2o/pygeoflood

If you plan on running the Fill-Spill-Merge function to estimate pluvial flooding, you must also install a fork of the richdem package using the following commands:

$ git clone https://github.com/mdp0023/richdem.git richdem
$ cd richdem/wrappers/pyrichdem
$ pip install "setuptools<81"
$ pip install "numpy==2.3.5"
$ pip install --no-deps .

For local pygeoflood development, install in editable mode:

$ git clone https://github.com/passah2o/pygeoflood
$ cd pygeoflood
$ pip install -e .

To run the test suite:

$ pip install pytest
$ pytest tests/test_functionality.py -v

Citing

When using GeoFlood, please cite the following paper:

Zheng, X., D. Maidment, D. Tarboton, Y. Liu, P. Passalacqua (2018), GeoFlood: Large scale flood inundation mapping based on high resolution terrain analysis, Water Resources Research, 54, 12, 10013-10033, doi:10.1029/2018WR023457.

When using GeoNet, please cite the following papers:

Passalacqua, P., T. Do Trung, E. Foufoula-Georgiou, G. Sapiro, W. E. Dietrich (2010), A geometric framework for channel network extraction from lidar: Nonlinear diffusion and geodesic paths, Journal of Geophysical Research Earth Surface, 115, F01002, doi:10.1029/2009JF001254.

Sangireddy, H., R. A. Carothers, C.P. Stark, P. Passalacqua (2016), Controls of climate, topography, vegetation, and lithology on drainage density extracted from high resolution topography data, Journal of Hydrology, 537, 271-282, doi:10.1016/j.jhydrol.2016.02.051.