Multi-scale comparison of urban socio-economic vulnerability in the Washington, DC metropolitan region resulting from compound flooding

Autor: Felício Cassalho, Tugkan Tanir, Celso M. Ferreira, Selina J. Sumi, Gustavo de A. Coelho, Andre de Souza de Lima, Sukru Uzun
Rok vydání: 2021
Předmět:
Zdroj: International Journal of Disaster Risk Reduction. 61:102362
ISSN: 2212-4209
Popis: The co-occurrence of different flood types (i.e. compound floods), such as coastal storms, riverine flow, and urban pluvial runoff, can cause severe damage to urban areas. Like many U.S. metropolitan regions along the coast, the Washington, DC metropolitan area, where increasing precipitation rates and sea-level rise have been observed, is vulnerable to the impacts from such events. This study aims to evaluate urban socio-economic vulnerability in the Washington, DC Metropolitan Region resulting from compound flooding at multiple scales. The socioeconomic damages from riverine flood and storm surges, which is defined as exposure index, were combined with the Socio-Economic Vulnerability Index (SOVI) in order to detect vulnerable populations to compound flood events at a range of scales (tract, group, and block). The highest damage was found on the banks of the Potomac River in the compound flood scenario. A high-precipitation scenario was also performed, leading to severe damages in locations with denser infrastructures, such as DC. The multi-scale comparison suggested that block scale analysis is more sensitive to vulnerability and flood damages compared to coarser scales, i.e., group and tract. The distribution of the risk was found significantly dependent on both the type of the compound flood event and the scale of the analysis. From a flood management perspective, coarser scale assessments can mislead efforts as it is not able to highlight specific locations with substantial vulnerable populations. The method presented in this study can potentially aid decision-makers to identify the vulnerable populations to compound floods in large coastal metropolitan areas.
Databáze: OpenAIRE