Integrated decision-support framework for enhancing coastal community resilience against hurricane-induced hazards

Coastal communities face escalating threats from hurricanes, necessitating a shift from descriptive risk assessment to prescriptive, optimized portfolio planning to enhance resilience. This study introduces an integrated decision-support framework that couples high-fidelity, multihazard socio-physical system modeling with a multi-objective optimization model. The framework quantifies the cascading impacts of hurricane-induced wind, storm surge, and waves on a community’s interdependent buildings, transportation network, and high-resolution electric power network (EPN), along with the resulting population dislocation and long-term recovery. It then identifies Pareto-optimal portfolios of mitigation strategies by simultaneously minimizing three competing objectives—economic loss, population dislocation, and recovery time—under various budget constraints. The framework is applied to a case study of Galveston Island, Texas, under a representative 100-year hurricane scenario. Results demonstrate that the framework can reveal the inherent trade-offs between protecting property value versus minimizing social disruption and identify retrofitting strategies associated with them. A post-processing analysis using a Computable General Equilibrium (CGE) model and social equity metrics further reveals that while optimized mitigation provides system-wide economic co-benefits, improvements in social equity are not guaranteed and require explicit consideration. By translating complex simulation outputs into a portfolio of actionable, resource-efficient strategies, this work provides a powerful tool for stakeholders to make informed, priority-driven investments to enhance coastal community resilience.