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Individual learning as a driver of changes in community vulnerability under repeated hurricanes and changing climate.

Authors :
Zhai C
Reilly AC
Guikema SD
Source :
Risk analysis : an official publication of the Society for Risk Analysis [Risk Anal] 2023 Apr; Vol. 43 (4), pp. 762-782. Date of Electronic Publication: 2022 Jun 07.
Publication Year :
2023

Abstract

The risks from singular natural hazards such as a hurricane have been extensively investigated in the literature. However, little is understood about how individual and collective responses to repeated hazards change communities and impact their preparation for future events. Individual mitigation actions may drive how a community's resilience evolves under repeated hazards. In this paper, we investigate the effect that learning by homeowners can have on household mitigation decisions and on how this influences a region's vulnerability to natural hazards over time, using hurricanes along the east coast of the United States as our case study. To do this, we build an agent-based model (ABM) to simulate homeowners' adaptation to repeated hurricanes and how this affects the vulnerability of the regional housing stock. Through a case study, we explore how different initial beliefs about the hurricane hazard and how the memory of recent hurricanes could change a community's vulnerability both under current and potential future hurricane scenarios under climate change. In some future hurricane environments, different initial beliefs can result in large differences in the region's long-term vulnerability to hurricanes. We find that when some homeowners mitigate soon after a hurricane-when their memory of the event is the strongest-it can help to substantially decrease the vulnerability of a community.<br /> (© 2022 The Authors. Risk Analysis published by Wiley Periodicals LLC on behalf of Society for Risk Analysis.)

Details

Language :
English
ISSN :
1539-6924
Volume :
43
Issue :
4
Database :
MEDLINE
Journal :
Risk analysis : an official publication of the Society for Risk Analysis
Publication Type :
Academic Journal
Accession number :
35672878
Full Text :
https://doi.org/10.1111/risa.13955