Modeling and Computational Challenges in Post-disaster Building Recovery under Multiple Hazard Scenarios

Recent disasters (e.g., the 2023 Türkiye-Syria earthquake and floods) have underscored the potential for multiple natural hazards occurring during a community’s recovery, further prolonging post-disaster recovery times. This study investigates modeling and computational challenges involved in assessing post-disaster recovery trajectories for building structures subjected to plausible initial and secondary hazard scenarios by accounting for various interarrival times and relative intensities (in terms of event mean return period). An illustrative example of a building subjected to an earthquake followed by a flood scenario (with explicit consideration of climate change effects on the flood’s severity and frequency) is showcased by discussing relevant post-disaster delays that occurred before the start of repairs (i.e., impeding factor delays) for each hazard scenario and the impact of the secondary event on the recovery trajectory. For instance, financing through insurance settlement for two hazard events occurring within a short time frame (weeks or months) could be complex and require a much longer time to settle, which then impedes the recovery of the asset. Furthermore, the impact of different damage levels (and corresponding repair classes) to critical structural/non-structural components across both hazards, as well as their potential interactions, on the recovery trajectory is investigated. Finally, this study examines how various policy decisions made at different stages post-disaster influence recovery trajectories. It highlights the complexities and significant uncertainties involved in decision-making, such as delays caused by impeding factors and their interactions under extreme and unexpected secondary events. This understanding can aid in developing dynamic and adaptive policy pathways.