方法对比

	Multi-Hazard Risk Assessment	Semi-Quantitative Risk Matrix Analysis
领域	Disaster Studies	Disaster Studies
方法族	Process / pipeline	Process / pipeline
起源年份	2012	2019
提出者	Kappes, Keiler, von Elverfeldt & Glade (review synthesis); ISO/IEC 31010	ISO/IEC 31010 (standardized practice); critical analysis by L. A. Cox
类型	Combined hazard-exposure-vulnerability risk pipeline for multiple perils	Semi-quantitative consequence-likelihood rating and ranking pipeline
开创性文献	Kappes, M. S., Keiler, M., von Elverfeldt, K., & Glade, T. (2012). Challenges of analyzing multi-hazard risk: a review. Natural Hazards, 64(2), 1925-1958.	International Organization for Standardization. (2019). IEC 31010:2019 Risk management — Risk assessment techniques. ISO/IEC, Geneva.
别名	Multi-Risk Assessment, Multi-Hazard Analysis, Combined Hazard Risk Assessment, Multi-Peril Risk Analysis	Risk Matrix Analysis, Consequence-Likelihood Matrix, Probability-Impact Matrix, Risk Rating Matrix
相关	3	3
摘要	Multi-hazard risk assessment estimates and compares the risk that several distinct hazards pose to a shared set of people and assets, rather than studying each peril in isolation. Building on the risk-science convention that risk is the product of hazard, exposure and vulnerability, the approach characterizes each hazard's intensity-frequency behavior, overlays a common exposure inventory, applies hazard-specific vulnerability functions, and then aggregates the resulting losses across hazards. Kappes, Keiler, von Elverfeldt and Glade's 2012 review in Natural Hazards set out the central difficulties: hazards differ in their spatial footprint, return period, and measurement units, and they can interact through cascades and coincidences, so a defensible multi-hazard assessment must harmonize incompatible inputs and explicitly model how perils relate. ISO/IEC 31010 places the method within the standard toolbox of risk-assessment techniques used to support prioritization and treatment decisions.	Semi-quantitative risk matrix analysis rates each risk on ordinal likelihood and consequence scales and combines the two in a grid to assign a risk level that drives prioritization. It is the workhorse of practical risk management: ISO/IEC 31010 lists the consequence-likelihood matrix among its standard techniques precisely because it lets analysts compare many disparate risks quickly without the data demands of a full quantitative model. The 'semi-quantitative' label captures its hybrid character — ordinal categories such as 'rare' or 'catastrophic' are anchored to rough numeric bands, giving more discipline than a purely verbal judgment but far less than a probabilistic calculation. The method's popularity is matched by sharp critique: L. A. Cox's 2008 analysis in Risk Analysis showed that poorly designed matrices can rank risks incorrectly, compress very different risks into the same cell, and even perform worse than random, making careful scale design and consistency checks essential rather than optional.