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). 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. This may also be specified as Hydrograph Name, where options include "short_charles" and "long_charles", which represent premade hydrograph data. The former is the default.

4. Potential Evapotranspiration Percentile: Select the percentile value for potential evapotranspiration

5. Soil Moisture Percentile: Select the percentile value for soil moisture

6. Ground Water Percentile: Select the percentile value for ground water

7. Initial Condition Set: Initial conditions "001", "002", and "003" start real-world emissions from year 1850 with the climate state from the 1001st, 1021st, and 1041st year of a pre-industrial control simulation. Since Earth's climate undergoes multi-year and multi-decadal cycles, the different initializations reveal the range of possible climates in real-world years 2031 and beyond.

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.