https://github.com/opengeoscience/uvdat-flood-sim
Dynamic flood simulation module made in collaboration with Northeastern University
https://github.com/opengeoscience/uvdat-flood-sim
Last synced: 9 days ago
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Dynamic flood simulation module made in collaboration with Northeastern University
- Host: GitHub
- URL: https://github.com/opengeoscience/uvdat-flood-sim
- Owner: OpenGeoscience
- Created: 2025-09-12T18:27:43.000Z (5 months ago)
- Default Branch: main
- Last Pushed: 2025-09-28T17:24:26.000Z (4 months ago)
- Last Synced: 2025-09-28T18:26:11.204Z (4 months ago)
- Language: Python
- Size: 27.3 KB
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Dynamic Flood Simulations
Created in collaboration with Northeastern University
## Overview
This end-to-end dynamic flood simulation is intended for use with the Analytics workflow in [UVDAT (Urban Visualization and Data Analysis Toolkit)](https://github.com/OpenGeoscience/uvdat). This module consists of three parts: downscaling prediction, hydrological prediction, and hydrodynamic prediction.
## Explanation
First, an AI downscaling model uses regional climate projections to determine future local precipitation conditions, such as the intensity of extreme rainstorms. These extreme precipitation levels are fed into a hydrological model, which uses precipitation and evapotranspiration to determine runoff and discharge. Finally, a hydrodynamic model uses discharge to map flood depth over time.
This is a proof of concept for the Charles River in Boston that could be translated to other rivers and cities. The user selects the inputs described below, and the output is a flood simulation, represented as a multiframe stacked GeoTIFF raster, a time-varying map of flood depth with one frame per hour for 24 hours.
## Inputs
1. Time Period: the 20 year time period in which to predict a flood. Options are "2031-2050" and "2041-2060" (the former is the default).
2. Annual Probability: the probability that a flood of this magnitude will occur in any given year. This value must be greater than 0 and less than 1. The default is 0.04, which represents a 1 in 25 year flood.
3. Hydrograph: a list of proportions that sum to 1; these represent fractions of the total rainfall volume per timestep.
4. Potential Evapotranspiration Percentile: Select the 25th, 50th, 75th, or 90th percentile value for potential evapotranspiration
5. Soil Moisture Percentile: Select the 25th, 50th, 75th, or 90th percentile value for soil moisture
6. Ground Water Percentile: Select the 25th, 50th, 75th, or 90th percentile value for ground water
## Installation
```
pip install uvdat-flood-sim
```
## Example usage
To run a flood simulation with default inputs:
```
python -m uvdat_flood_sim
```
To see the help menu explaining how to use arguments to specify input values:
```
python -m uvdat_flood_sim --help
```
## Viewing Results
By default, results will be displayed with a `matplotlib` animation. This animation is saved in the outputs folder as `animation.gif`. Results are also saved in the outputs folder as a multiframe geospatial tiff called `flood_simulation.tif`, which can be added to UVDAT for visualization.