A Place-based Assessment of Flash Flood Hazard and Vulnerability in the Contiguous United States

Abstract

Flash flood is among the most catastrophic natural hazards which causes disruption in the environment and societies. Flash flood is mainly initiated by intense rainfall, and due to its rapid onset (within six hours of rainfall), taking action for effective response is challenging. Building resilience to flash floods require understanding of the socio-economic characteristics of the societies and their vulnerability to these extreme events. This study provides a comprehensive assessment of socio-economic vulnerability to flash floods and investigates the main characteristics of flash flood hazard, i.e. frequency, duration, severity, and magnitude. A socio-economic vulnerability index is developed at the county level across the Contiguous United States (CONUS). For this purpose, an ensemble of social and economic variables from the US Census and the Bureau of Economic Analysis were analyzed. Then, the coincidence of socioeconomic vulnerability and flash flood hazard were investigated to identify the critical and non-critical regions. Results show that the southwest U.S. experienced severe flash flooding with high magnitude, whereas the Northern Great Plains experience lower severity and frequency. Critical counties (highvulnerable-hotspot) are mostly located in the southern and southwestern parts of the U.S. The majority of counties in the Northern Great Plains indicate a non-critical status.

Social Vulnerability across the Great Lakes Basin: A County-Level Comparative and Spatial Analysis

“…Social vulnerability results when social, political, and economic processes combine to produce heightened susceptibility to hazards for some populations [13][14][15][16]. The application of the concept can be found in health research, hazard mitigation planning, and environmental social sciences, but the use and selection of indicators can significantly vary [9,12,15,17,18].…”

Comprehensive Evaluation of Flood and Flood in the Yellow River Basin Based on Gray Correlation Analysis

“…Based on the Multicollinearity study and estimation of predictive power and information gain method, the study of Costache et al revealed that the Multilayer Perceptron Statistical Index integration has the highest efficiency and is applied to the actual region mapping (Costache et al, 2020). The socio-economic vulnerability of flash floods was comprehensively assessed by Khajehei et al, and the main characteristics of flash floods, such as frequency, duration, severity, and magnitude, were investigated (Khajehei et al, 2020). Sezen et al describe the process of developing computational risk assessment methods that incorporate the risks associated with earthquake and flood events into the traditional probabilistic risk assessment (Sezen et al, 2019) (Banda, 2019).…”

Leveraging machine learning for predicting flash flood damage in the Southeast US

“…Recently, Ahmadalipour and Moradkhani (2019) investigated the spatiotemporal characteristics of flash flooding hazard over the Contiguous United States (CONUS). Also, Khajehei et al (2020) assessed the socioeconomic vulnerability of flash flooding at the county scale across the entire CONUS while accounting for flash flood characteristics including duration, frequency, magnitude and severity.…”