Sponsor
Portland State University. Department of Civil & Environmental Engineering
First Advisor
Hamid Moradkhani
Date of Publication
Fall 12-13-2018
Document Type
Dissertation
Degree Name
Doctor of Philosophy (Ph.D.) in Civil & Environmental Engineering
Department
Civil and Environmental Engineering
Language
English
Subjects
Flood forecasting -- United States -- Mathematical models, Hydrologic models, Flood damage prevention, Flood control -- Economic aspects, Flood control -- Social aspects
DOI
10.15760/etd.6550
Physical Description
1 online resource (xi, 108 pages)
Abstract
Flash flood is among the most hazardous natural disasters, and it can cause severe damages to the environment and human life. Flash floods are mainly caused by intense rainfall and due to their rapid onset (within six hours of rainfall), very limited opportunity can be left for effective response. Understanding the socio-economic characteristics involving natural hazards potential, vulnerability, and resilience is necessary to address the damages to economy and casualties from extreme natural hazards. The vulnerability to flash floods is dependent on both biophysical and socio-economic factors. This study provides a comprehensive assessment of socio-economic vulnerability to flash flood alongside a novel framework for flash flood early warning system. A socio-economic vulnerability index was developed for each state and county in the Contiguous United States (CONUS). For this purpose, extensive ensembles of social and economic variables from US Census and the Bureau of Economic Analysis were assessed. The coincidence of socio-economic vulnerability and flash flood events were investigated to diagnose the critical and non-critical regions. In addition, a data-analytic approach is developed to assess the interaction between flash flood characteristics and the hydroclimatic variables, which is then applied as the foundation of the flash flood warning system. A novel framework based on the D-vine copula quantile regression algorithm is developed to detect the most significant hydroclimatic variables that describe the flash flood magnitude and duration as response variables and estimate the conditional quantiles of the flash flood characteristics. This study can help mitigate flash flood risks and improve recovery planning, and it can be useful for reducing flash flood impacts on vulnerable regions and population.
Rights
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Persistent Identifier
https://archives.pdx.edu/ds/psu/27182
Recommended Citation
Khajehei, Sepideh, "From Probabilistic Socio-Economic Vulnerability to an Integrated Framework for Flash Flood Prediction" (2018). Dissertations and Theses. Paper 4666.
https://doi.org/10.15760/etd.6550