The impact of natural disasters has been increasing in recent years. Despite the developing international interest in multihazard events, few studies quantify the dynamic interactions that characterize these phenomena. It is argued that without considering the dynamic complexity of natural catastrophes, impact assessments will underestimate risk and misinform emergency management priorities. The ability to generate multihazard scenarios with impacts at a desired level is important for emergency planning and resilience assessment. This article demonstrates a framework for using graph theory and networks to generate and model the complex impacts of multihazard scenarios. First, the combination of maximal hazard footprints and exposed nodes (e.g., infrastructure) is used to create the hazard network. Iterative simulation of the network, defined by actual hazard magnitudes, is then used to provide the overall compounded impact from a sequence of hazards. Outputs of the method are used to study distributional ranges of multihazards impact. The 2016 Kaikōura earthquake is used as a calibrating event to demonstrate that the method can reproduce the same scale of impacts as a real event. The cascading hazards included numerous landslides, allowing us to show that the scenario set generated includes the actual impacts that occurred during the 2016 events.
Keywords: disaster scenario; impact; multihazards; natural hazard; network.
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