07. Impacts of Migration on Coastal Adaptation Costs and Damages

Climate change is causing increasing coastal hazards around the world, including storm surge and sea level rise. Coastal adaptation models are useful tools for assessing the economic effects of these hazards on coastal regions. Migration is an important factor to consider in this context, as it is a human response to protect themselves against sea level rise. However, models´ ability to implement human migration in response to these environmental hazards remains limited, despite the growing importance of migration as a strategy to manage the risks posed by coastal flooding. To address this, we developed a model for county-level migration using U.S. Census data from 2016 to 2020 in the MimiCIAM, coastal impact and adaptation model, for the state of Florida. Additionally, we implement a fixed or flexible adaptation strategy. Our goal is to examine the uncertainties and sensitivities associated with migration-based adaptation strategies. Here, we show how migration is a critical feature of coastal adaptation efforts over the next century, enabling significant change in overall adaptation costs and damages. Previous studies have often viewed migration as an external factor or considered it a retreat. Our findings show that integrating migration into adaptation models can lead to a reduction in adaptation costs of up to $713 million for the entire coast of Florida. Moreover, while people prefer to migrate to larger cities like Miami and Hollywood, the results indicate that there are greater benefits to migrating to inland areas. These findings underscore the need to integrate dynamic human behavior into climate impact models, particularly in areas where coastal hazards are most severe. Forward migration modeling within the climate impact framework, our research contributes to more accurate projections of future population distributions and resource needs.

Sea level rise

Migration

Coastal adaptation

Economic impacts

Adaptation planing 

Mid-Level

Influence

Women in Statistics and Data Science 2025