Enhancing resilience through recovery modeling in multi-hazard contexts

Abstract Natural hazards striking in 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. While the framework is applicable to any hazard combination (i.e., independent and dependent hazards - for example, cascading hazards), we consider simulations of representative building repairs under varied earthquake–flood scenarios to identify key sources of interaction in the post-disaster recovery phase. We identify key delay factors, such as financing constraints (i.e., the time required to secure funding through a public loan, private loan, or private insurance), that can dominate overall recovery durations even when secondary events occur months later. Our results demonstrate that accounting for multi-hazard interactions leads to exacerbated restoration times, informing adaptive policy measures that support efficient resource allocation. Finally, we show that incorporating sequence-dependent recovery dynamics can aid decision-making to enhance post-disaster community resilience.