The risk from natural hazards for a specific region is usually assessed predicting the losses associated with a set of representative extreme event scenarios. The selection of these scenarios is delicate, because computational resources constrain heavily the number of cases that can be investigated. Hence, the selected scenarios have to be as few as possible, and yet provide a comprehensive probabilistic description of the regional hazard. We developed a technique called "Multi-Hazard Quantization" that can capture simultaneously multiple hazard intensity measures spread over a region. The approach is grounded in solid mathematics and yields substantial enhancements in the computational efficiency of these analyses, enabling their applicability to practical-size problems and, ultimately, advancing disaster mitigation and response.

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