Probabilistic urban cascading multi-hazard risk assessment methodology for ground shaking and post-earthquake fires
Natural Hazards, ISSN: 1573-0840, Vol: 116, Issue: 3, Page: 3165-3200
2023
- 11Citations
- 33Captures
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Article Description
A probabilistic methodology is presented for assessing cascading multi-hazard risk for ground shaking and post-earthquake fires at a regional scale. The proposed methodology focuses on direct economic losses to buildings caused by the combined effect of ground shaking and post-earthquake fires and evaluates the exceedance probability of the regional shaking–fire losses in a predefined future time period by comprehensively considering the effects of various uncertain factors on the losses via Monte Carlo simulations. Probabilistic seismic risk assessments are extended by integrating post-earthquake fire models with seismic activity models, ground motion prediction equations, and seismic fragility functions. The fire models include post-earthquake ignition models, a weather model, a physics-based urban fire spread model, and a fire brigade response model. This integrated modeling enables the incorporation of the following uncertain factors with causal relationships into the assessments: earthquake occurrence, ground motion intensity distribution, damage to buildings resulting from ground shaking, post-earthquake ignition occurrence and occupant firefighting, weather condition, fire brigade response time including time to detection, and damage to buildings resulting from post-earthquake urban fire spread. To demonstrate the methodology, a realistic case study is conducted for a historical urban area with closely spaced wooden buildings in Kyoto, Japan, focusing on possible large earthquakes along major active faults. Contrary to conventional single-hazard approaches, the results highlight the impact of multi-hazard consideration on risk assessments. This indicates that the methodology can be a useful tool for more appropriately understanding earthquake risk and promoting risk-informed decision-making in urban communities for risk reduction.
Bibliographic Details
Springer Science and Business Media LLC
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