An index of relative displacement risk to hurricanes

Abstract

Indicator and index-building activities have become commonplace for assessing and estimating social, environmental, and economic strengths and vulnerabilities of communities, regions and even countries. In the context of disasters, much of the empirical research has focused on identifying places and populations that are vulnerable to catastrophic hurricane and flood disasters. However, there have not been parallel efforts to capture measures for displacement risk. This article seeks to fill this gap by focusing on (1) a preliminary conceptualization of displacement risk; (2) a set of related indicators and measures at various scales, including indicators tapping policy capacity and commitment; and (3) development of an operational displacement risk index (DRI) and results for a snapshot year of 2007. The study area, 158 counties in the United States, was the coastal portion (an area two counties ''deep'') of eight states. Findings suggest that the mean levels of DRI scores were much higher for coastal counties. Clusters of the highest DRI scores are particularly evident for coastal counties of Florida, especially the South Florida counties of Miami Dade, Monroe, Palm Beach, and Broward. Florida also scores high in terms of the top ten most vulnerable counties (i.e., 7 of the top 10) as well as exposure to hurricanes (i.e., 6 of the top 10 counties with the highest probability of hurricane strikes). Despite the limitations explained in the paper, we hope that the creation of the DRI has helped to fill a gap in knowledge and will lead to higher level theoretical and research discussions on the population displacement phenomenon, its determinants and planning and policy interventions.

Spatial characteristics of storm‐total rainfall swaths associated with tropical cyclones over the Eastern United States

“…Last, we produced a series of maps with frequency distribution for overland locations impacted by wind and rainfall associated with TCs. The frequency was summarized in county units, since many tasks including hazard preparation and planning, loss estimation, risk analysis, mitigation, and response to TCs are handled at the county level (Keim et al, 2007;Zandbergen, 2009;Czajkowski et al, 2011;Esnard et al, 2011). To further estimate how frequently a particular location was impacted by TCP events, we calculated return intervals, which are defined as the ratio of study period (e.g.…”

A Geographic Analysis of Post-Disaster Social Impacts on a Municipal Scale – A Case Study of a Potential Major Flood in the Paris Region (France)

“…A vulnerable person during the evacuation stage may not be vulnerable during the recovery stage. Thus, the few methods developed to map recovery capability or post-disaster displacement risk (Esnard et al, 2011;Finch et al, 2010;Myers et al, 2008) rely on a general state-of-the-art regarding vulnerability, and fail to fully consider the peculiarities of post-disaster situations. The index of vulnerability that has been developed in this paper, called Index of Social Destabilization (ISD), aims at representing the potential difficulties of a given population to recover in a post-disaster context.…”

The Effects of Infrastructure Service Disruptions and Socio-Economic Vulnerability on Hurricane Recovery

“…The survey instrument used was administered in 30 counties in central and south Florida. Historical records of hurricane activity stretching over 152 years indicate that six of the counties included in the study area (Monroe, Miami Dade, Martin, Collier, Broward and Palm Beach) are among the top ten counties with the highest probabilities of a hurricane strike along the Atlantic seaboard and the Gulf of Mexico [38]. The area was affected by Hurricane Matthew in 2016 (28 September-10 October 2016) and Hurricane Irma (30 August-12 September 2017).…”