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Flood Occurrence and Intensity Prediction in North America

Electronic Theses and Dissertations

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abstract
In this paper, we fit models to the occurrence and intensity of flood in North America to study risk for insurance purposes. North America is separated into 625 hydro basins with unique hydro graphic information. We collected basin features and climate data as predictors for flood occurrence and intensity. We chose both property losses and inundated areas as response variables for a flood. Our first goal is a predictive model for flood occurrence and intensity, and our second goal is to use this model with future regional climate model data to explore projected changes in flood risk due to climate change. The models we use are logistic regression and random forests. Logistic regression gave a better result and is chosen as the final model. We used a bias-corrected regional climate model to project future flood risk under a climate change scenario.
subject
hydro basin
property losses
quantile match
simulated climate data
contributor
Yu, Kejia (author)
Erhardt, Robert (committee chair)
Erhardt, Robert (committee member)
Jiang, Miaohua (committee member)
Hepler, Staci (committee member)
date
2020-05-29T08:36:03Z (accessioned)
2020-05-29T08:36:03Z (available)
2020 (issued)
degree
Mathematics and Statistics (discipline)
identifier
http://hdl.handle.net/10339/96829 (uri)
language
en (iso)
publisher
Wake Forest University
title
Flood Occurrence and Intensity Prediction in North America
type
Thesis

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