Authors: Moxuan Li*, Texas A&M University, Lei Zou, Professor
Topics: Hazards, Risks, and Disasters, Geographic Information Science and Systems, Spatial Analysis & Modeling
Keywords: Flash flood, vulnerability, spatial-temporal analysis, risk assessment, disaster mitigation
Session Type: Virtual Paper
Start / End Time: 9:35 AM / 10:50 AM
Room: Virtual 41
Presentation File: No File Uploaded
As one of the most dangerous natural disasters, flash floods account for 52% of economic losses and over 70% of fatalities and injuries caused by flood-related disasters. However, forecasting and monitoring flash floods are challenging because they always take place rapidly within few hours in small areas. As a result, there is an urgent need to evaluate community-based flash flood vulnerability, identify its driving factors, and develop mitigation strategies in different communities to reduce damages from future events. Using Texas as the study area, this project developed a framework to assess the temporal and spatial patterns of vulnerability to flash flood at the county-level. Flash flood, built environment, and socioeconomic data collected from the National Oceanic and Atmospheric Administration (NOAA), National Land Cover Databases (NLCD), and U.S. Census Bureau were utilized in this project. First, this study statistically analyzed the time, duration, frequency, and damage of flash flood events in each county. Second, we defined and calculated flash flood vulnerability as the Average Hourly-Damage Per Capita (AHDPC) to reveal its spatial-temporal patterns in each county and the state of Texas. Third, potential driving forces of flash flood vulnerability were identified through correlation and machine learning approaches. The results of this project could support further analysis of natural disaster risk assessment and monitoring and assist disaster mitigation and responding.