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jittedingen/FloodPrediction

Domain:

climate

Record type:

model
Creator:
jit
Host:
Flood prediction model for Kenya and Uganda (Master Thesis) # Flood prediction model for Kenya & Uganda ## Thesis Jitte Dingenouts This repository contains the code that was used in Jitte Dingenouts' thesis about flood prediction in Kenya and Uganda. It also includes her thesis for further explanation. Note that sometimes in the script you will see: "Panel level model" which is a synonym for the "Country Level model" as described in the thesis. ### Folders The location specific folders (e.g. kenya) consists of an input and output folder. The input folder contains information about the location such as river discharge, rainfall and soil moisture. The output folder contains some data analysis results. Besides that, the Results folder contains the results for several models & scripts contains all scripts that are used in this thesis. The other folders come from the original benchmark of 510 & are barely used. ### Scripts In the scripts folder you can find all the scripts that were used in this thesis. - Main.py: this is the main script which should be run to get the results. In this script, several other scripts are called. - Interpolation.py: contains a function which interpolates the missing values that are present in the data - Extra_Features.py: contains a function which constructs additional features from the data (cross-product of rainfall and soilmoisture closest to the surface / cross-product of the soil moisture level 4 (deepest in the ground) and level 2 / season indicator / for country level models include additional information on vegetation, percentage of water in district, indicator for how mountaineous a district or county is, the maximum river discharge over 2 weeks & a variable which indicates whether a flood occurred in the last 2 weeks.) - Wavelet_Transform.py: contains a function which performs the Wavelet Transform to the data - Imbalance.py: contains a function which makes the data more balanced - District_Model.py: contains a function which performs a Logistic Regression and Support Vector Machine incl …