Simulating Behavioral Influences on Community Flood Risk under Future Climate Scenarios. Issue 4 (15th November 2019)

• Record Type: Journal Article
• Authors: Tonn, Gina; Guikema, Seth; Zaitchik, Benjamin
• Is Part Of: Risk analysis. Volume 40:Issue 4(2020)
• Page Start: 884
• Page End: 898
• Publication Date: 2019-11-15
• Subjects: Agent‐based model -- behavioral influences -- climate change -- flood risk -- mitigation; Technology -- Risk assessment -- Periodicals; 658.403
• DOI: 10.1111/risa.13428
• Languages: English
• ISSNs: 0272-4332

Abstract

Abstract: 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.