Predicting support for flood mitigation based on flood insurance purchase behavior

Wanyun Shao, Kairui Feng, Ning Lin

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

What is the decision-making mechanism people rely upon to mitigate flood risk? Applying Bayesian Network modeling to a comprehensive survey dataset for the US Gulf Coast, we find that the overall support for flood mitigation can be inferred from flood insurance purchase behavior (i.e. without insurance versus with insurance purchased mandatorily, voluntarily, or both). Therefore, we propose a theoretical decision-making mechanism composed of two dimensions including informed flood risk and sense of insecurity. The informed flood risk is the primary determinant on one's overall support for flood mitigation. Risk mitigation decisions are largely contingent on the level of risk that is effectively conveyed to individuals. Additionally, sense of insecurity plays a moderate role in determining individuals' overall support for flood mitigation. The sense of insecurity can move people toward overall support for mitigation, but the effect is not as large as the informed risk. Results of this study have fundamental policy implications. The flood risk informed by Federal Emergency Management Agency's flood maps not only provides the compulsory basis for flood insurance purchase but also determines individuals' overall support for flood mitigation. Flood map inaccuracy can immensely mislead individuals' overall risk mitigation decision. Meanwhile, this flood risk mitigation decision-making mechanism inferred from a survey data in the US Gulf Coast needs to be tested and validated elsewhere.

Original languageEnglish (US)
Article number054014
JournalEnvironmental Research Letters
Volume14
Issue number5
DOIs
StatePublished - May 13 2019

All Science Journal Classification (ASJC) codes

  • Renewable Energy, Sustainability and the Environment
  • General Environmental Science
  • Public Health, Environmental and Occupational Health

Keywords

  • Bayesian network
  • decision-making mechanism
  • flood insurance
  • flood risk mitigation

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