COASTMOVE What drives human behavior regarding global coastal migration and adaptation in response to sea level rise and extreme flood events?

Summary

Future sea level rise (SLR), extreme flood events, and urbanization pressure will increase coastal flood risk, and in the absence of costly flood protection measures in numerous regions, millions of coastal residents will be forced to migrate to safer locations. This research addresses the significant challenge these trends pose to adaptation and migration policy: Which coastal areas will be protected, and in which regions will coastal migration become the inevitable adaptation option?
To tackle this challenge, I propose focusing on the human adaptive and migration behavior of residents and other agents within one global framework by integrating (1) a global coastal flood risk model with (2) an agent-based model (ABM). Current global coastal risk assessment and migration methods do not address individuals’ dynamic decisions regarding SLR and extreme flood events, and instead assume their adaptive behavior remains constant. However, the drivers that motivate people to migrate and adapt vary over time and space, and to capture these drivers (3) empirical data will be collected across seven surveys to parametrize realistic ranges for the behavioral rules in the ABM. (4) Novel global databases on flood protection, demography and socio-economy will be developed to extrapolate behavioral rules from the cases to other coastal areas. (5) State-of-the-art big-data methods using Twitter, mobile phone and IRS tax-filing data will be used to calibrate and validate migration patterns simulated by the global framework.
The framework offers several advantages: high resolution (1x1km2) global migration, adaptation, and risk projections (2020–2100); novel maps of future migration hotspots; an improved understanding of what drivers (environmental, socio-economic, demographic, etc.) and interactions between stakeholders influence adaptation and migration decisions; and groundbreaking big-data validation. The framework will be used to assess adaptation and migration policies.

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Web resources:	https://cordis.europa.eu/project/id/884442
Start date:	01-01-2021
End date:	30-06-2026
Total budget - Public funding:	2 499 608,75 Euro - 2 499 608,00 Euro

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Original description

Future sea level rise (SLR), extreme flood events, and urbanization pressure will increase coastal flood risk, and in the absence of costly flood protection measures in numerous regions, millions of coastal residents will be forced to migrate to safer locations. This research addresses the significant challenge these trends pose to adaptation and migration policy: Which coastal areas will be protected, and in which regions will coastal migration become the inevitable adaptation option?
To tackle this challenge, I propose focusing on the human adaptive and migration behavior of residents and other agents within one global framework by integrating (1) a global coastal flood risk model with (2) an agent-based model (ABM). Current global coastal risk assessment and migration methods do not address individuals dynamic decisions regarding SLR and extreme flood events, and instead assume their adaptive behavior remains constant. However, the drivers that motivate people to migrate and adapt vary over time and space, and to capture these drivers (3) empirical data will be collected across seven surveys to parametrize realistic ranges for the behavioral rules in the ABM. (4) Novel global databases on flood protection, demography and socio-economy will be developed to extrapolate behavioral rules from the cases to other coastal areas. (5) State-of-the-art big-data methods using Twitter, mobile phone and IRS tax-filing data will be used to calibrate and validate migration patterns simulated by the global framework.
The framework offers several advantages: high resolution (1x1km2) global migration, adaptation, and risk projections (20202100); novel maps of future migration hotspots; an improved understanding of what drivers (environmental, socio-economic, demographic, etc.) and interactions between stakeholders influence adaptation and migration decisions; and groundbreaking big-data validation. The framework will be used to assess adaptation and migration policies.