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Examining the Effects of Objective Hurricane Risks and Community Resilience on Risk Perceptions of Hurricanes at the County Level in the U.S. Gulf Coast: An Innovative Approach

Wanyun Shao, Maaz Gardezi and Siyuan Xian

Annals of the American Association of Geographers, 2018, vol. 108, issue 5, 1389-1405

Abstract: Communities' risk perceptions can influence their abilities to cope with coastal hazards such as hurricanes and coastal flooding. Our study presents an initial effort to examine the relationship between community resilience and risk perception at the county level, through innovative construction of aggregate variables. Using the 2012 Gulf Coast Climate Change Survey merged with historical hurricane data and community resilience indicators, we first apply a spatial statistical model to construct a county-level risk perception indicator based on survey responses. Next, we employ regression to reveal the relationship between contextual hurricane risk factors and community resilience on one hand and county-level perceptions of hurricane risks on the other. Results of this study are directly applicable in the policymaking domain as many hazard mitigation plans and adaptation policies are designed and implemented at the county level. Specifically, two major findings stand out. First, the contextual hurricane risks represented by peak height of storm surge associated with the last hurricane landfall and land area exposed to historical storm surge flooding positively affect county-level risk perceptions. This indicates that another threat of hurricanes—wind risks—needs to be clearly communicated with the public and fully incorporated into hazard mitigation plans and adaptation policies. Second, two components of community resilience—higher levels of economic resilience and community capital—are found to lead to heightened perceptions of hurricane risks, which suggests that concerted efforts are needed to raise awareness of hurricane risks among counties with less economic and community capital.

Date: 2018
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Citations: View citations in EconPapers (9)

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DOI: 10.1080/24694452.2018.1426436

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