Simulating Behavioral Influences on Community Flood Risk under Future Climate Scenarios.
Agent-based model
behavioral influences
climate change
flood risk
mitigation
Journal
Risk analysis : an official publication of the Society for Risk Analysis
ISSN: 1539-6924
Titre abrégé: Risk Anal
Pays: United States
ID NLM: 8109978
Informations de publication
Date de publication:
04 2020
04 2020
Historique:
received:
19
10
2018
revised:
29
05
2019
accepted:
04
11
2019
pubmed:
16
11
2019
medline:
14
10
2021
entrez:
16
11
2019
Statut:
ppublish
Résumé
Flood risk is a function of both climate and human behavior, including individual and societal actions. For this reason, there is a need to incorporate both human and climatic components in models of flood risk. This study simulates behavioral influences on the evolution of community flood risk under different future climate scenarios using an agent-based model (ABM). The objective is to understand better the ways, sometimes unexpected, that human behavior, stochastic floods, and community interventions interact to influence the evolution of flood risk. One historic climate scenario and three future climate scenarios are simulated using a case study location in Fargo, North Dakota. Individual agents can mitigate flood risk via household mitigation or by moving, based on decision rules that consider risk perception and coping perception. The community can mitigate or disseminate information to reduce flood risk. Results show that agent behavior and community action have a significant impact on the evolution of flood risk under different climate scenarios. In all scenarios, individual and community action generally result in a decline in damages over time. In a lower flood risk scenario, the decline is primarily due to agent mitigation, while in a high flood risk scenario, community mitigation and agent relocation are primary drivers of the decline. Adaptive behaviors offset some of the increase in flood risk associated with climate change, and under an extreme climate scenario, our model indicates that many agents relocate.
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Research Support, U.S. Gov't, Non-P.H.S.
Langues
eng
Sous-ensembles de citation
IM
Pagination
884-898Subventions
Organisme : NSF Hazard SEES
ID : 1631409
Pays : International
Organisme : U.S. National Science Foundation IGERT Water, Climate, and Health fellowship at Johns Hopkins University
Pays : International
Informations de copyright
© 2019 Society for Risk Analysis.
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