An Economics-Based Methodology for Analysis of the Inequitable Distribution of Flooding Risk

Abstract

Flooding is a significant hazard that threatens both human life and property. There are a number of flooding mechanisms: fluvial, pluvial, and coastal, which are all being exacerbated by the effects of climate change. Coastal flooding hazards are especially dangerous given population dynamics leading to increased populations that are subject to greater flooding hazard due to sea level rise (SLR). Flooding hazards are taken on by people, but they are not distributed equally throughout populations. This thesis proposes an analysis methodology to analyze this inequity using the First Street Foundation (FSF) Flood Factor® (FF). This methodology produces qualitative and quantitative results based on the economics analysis concepts of the Lorenz curve (LC) and the Gini index (G). These results facilitate comparison of demographics to determine inequitable flooding distributions. This thesis also examines an application of the proposed methodology specifically examining coastal counties in the contiguous U.S. Results indicate that Nonwhite demographics typically experience greater inequity within their demographic in coastal regions while the distribution of flooding exposure is more equal among the White demographic. This new methodology enables determination of inequitable flooding distributions between demographics on a national scale.