FloodSeverityIndex

Flood index based on Gumbel distribution of annual maxima of volumetric flow.

Table of contents

What is it?
Version Information
User Guide
Requirements
Files in this repository
Contact
License

What is it?

This Python routine calculates a flood severity index based on the annual maxima of volumetric flow for the period 1981-2017. The thresholds were estimated from a Gumbel distribution using the methods of L-moments. The severity is based on a 2-yr return period (medium), 5-yr return period (high), and 20-yr return period (severe).

This routine requires data from GloFAS.

Version information

v0.0.1: Support for severity index for South Sudan and Ethiopia.

User Guide

Command line implementations:

python FloodSeverityIndex.py data thresholds bounding_box year fig

docker run -ti mintproject/floodseverityindex:latest bash
python FloodSeverityIndex.py data thresholds bounding_box year fig

where:

data: Either:
- Path to the folder containing the GloFAS data. Data should be organized in folders per year.
- Path to single netcdf file with concatenated data for South Sudan and Ethiopia
thresholds: path to the file containing the flood threshold from the Gumbel distribution.
bounding_box: List of [min_lon,max_lon,min_lat,max_lat]. Note that only South Sudan and Ethiopia are currently supported. Therefore the maximum extent of the box is: [23,48,3,15]
year: The year of interest. Should be provided as a list to support for multiple years.
fig: whether to return a movie

Note:

The outputs are in netcdf format. The index is a boolean corresponding to the severity of the flood:
0: None
1: Medium (2-yr return period)
2: high (5-yr return period)
3: severe (20-yr return period)

Examples: python FloodSeverityIndex.py ./ GloFAS_FloodThreshold.nc [23,48,3,15] [2016,2017] True