COASTMOVE: A global agent-based model of adaptation and migration decisions in face of sea level rise

Sea-level rise (SLR) and socioeconomic trends are increasing the population and assets exposed to extreme coastal flood events in the coming decades. People residing in communities experiencing this increase in coastal flood risk may choose to stay, to stay and adapt, or to migrate towards safer areas. However, these migration decisions are influenced by many socio- economic and environmental factors. For example, current assessments of SLR adaptation and migration do often not address risk perceptions of residents related to different environmental risks, such as flooding and erosion. These factors influence adaptation decisions, and thus exposure and vulnerability. In this study, we aim to improve the representation of the dynamics of adaptive behavior of coastal communities in flood risk assessment by including human behavior and its effect on adaptation decisions, in face of SLR. Therefore, we develop an agent-based model grounded in subjective expected utility theory and simulate adaptation- and migration decisions of households facing coastal flood risk in France between 19xx and 2020. The model is empirically calibrated using survey data on flood risk perception and people’s willingness to implement adaptation measures. Then, we use socio-demographic projections to estimate future changes (2020-2080) in demographic composition, and apply the model to simulate coastal adaptation. The agent-based model presented in this study functions as a platform for further development of 1) more realistic decision models and 2) global modelling approaches of both coastal adaptation and migration under projections of future development.