Tracing resilience, social dynamics and behavioral change: a review of agent-based flood risk models

Abstract

Climate change and rapid urbanization exacerbate flood risks worldwide. The recognition of the crucial role that human actors play in altering risks and resilience of flood-prone cities triggers a paradigm shift in climate risks assessments and drives the proliferation of computational models that include societal dynamics. Yet, replacing a representative rational actor dominant in climate policy models with a variety of behaviorally-rich agents that interact, learn, and adapt is not straightforward. Focusing on the costliest climate-exacerbated hazard, flooding, we review computational agent-based models that include behavioral change and societal dynamics. We distinguish between two streams of literature: one stemming from economics & behavioral sciences and another from hydrology. Our findings show that most studies focus on households while representing decisions of other agents (government, insurance, urban developers) simplistically and entirely overlooking firms' choices in the face of risks. The two communities vary in the extent they ground agents' rules in social theories and behavioral data when modeling boundedly-rational decisions. While both aspire to trace feedbacks that agents collectively instigate, they employ different learning and interactions when computing societal dynamics in the face of climate risks. Dynamics of hazard, exposure, and vulnerability components of flood risks driven by incremental adaptation of agents are well represented. We highlight that applying a complex adaptive system perspective to trace the evolution of resilience can lead to a better understanding of transformational adaptation. The methodological advances in computational models with heterogeneous behaviorally-rich adaptive agents are relevant for adaptation to different climate-driven hazards beyond flooding.