Social vulnerability and the natural and built environment: a model of flood casualties in Texas

TLDR

Studies show that poor communities of color suffer disproportionately from hurricanes, tropical storms, and tornadoes, yet few quantitative analyses examine how flood events affect socially vulnerable populations. The authors analyze 832 countywide flood events in Texas (1997‑2001) to test whether localities with high percentages of socially vulnerable residents experience significantly more casualties, controlling for natural and built‑environment characteristics. They employ zero‑inflated negative binomial regression on the flood‑event data, adjusting for precipitation, flood duration, property damage, population density, dam presence, prior precipitation, and mitigation strategies. The models reveal that casualty odds rise with same‑day precipitation, flood duration, property damage, population density, and socially vulnerable populations, but fall when more dams exist, prior precipitation is higher, or mitigation measures are enacted, highlighting the importance of hazard‑resilient communities.

Abstract

Studies on the impacts of hurricanes, tropical storms, and tornados indicate that poor communities of colour suffer disproportionately in human death and injury.(2) Few quantitative studies have been conducted on the degree to which flood events affect socially vulnerable populations. We address this research void by analysing 832 countywide flood events in Texas from 1997-2001. Specifically, we examine whether geographic localities characterised by high percentages of socially vulnerable populations experience significantly more casualties due to flood events, adjusting for characteristics of the natural and built environment. Zero-inflated negative binomial regression models indicate that the odds of a flood casualty increase with the level of precipitation on the day of a flood event, flood duration, property damage caused by the flood, population density, and the presence of socially vulnerable populations. Odds decrease with the number of dams, the level of precipitation on the day before a recorded flood event, and the extent to which localities have enacted flood mitigation strategies. The study concludes with comments on hazard-resilient communities and protection of casualty-prone populations.