Enhancing Resilience Through Recovery Modeling in Multi-Hazard Contexts

Abstract Natural hazards striking in rapid succession impose compound disruptions on communities, extending recovery timelines and challenging resilience planning. Current post‐disaster assessments often treat events in isolation, overlooking how the timing and intensity of secondary hazards influence infrastructure restoration. Here, we develop a probabilistic framework that integrates hazard sequencing, time between hazard events, and relative intensities to quantify their combined effects on the recovery of building structures. Using simulations of representative building repairs under varied earthquake–flood scenarios, we identify key delay factors, such as financing constraints, that can dominate overall recovery durations even when secondary events occur months later. Our results demonstrate that accounting for multi‐hazard interactions yields exacerbated restoration times. This can inform adaptive policy measures that support efficient resource allocation. In this work, we show that incorporating sequence‐dependent recovery dynamics can aid decision-making for enhancing post‐disaster community resilience.