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A Risk Assessment Method for Multi-Hazard Coupling Disasters.

Zhichao He1,2, Wenguo Weng1,2

  • 1Institute of Public Safety Research, Department of Engineering Physics, Tsinghua University, Beijing, China.

Risk Analysis : an Official Publication of the Society for Risk Analysis
|November 2, 2020
PubMed
Summary

Multi-hazard coupling disasters are more severe than single-hazard events due to nonlinear risk interactions. This study introduces a novel model to accurately assess these complex, compounded risks.

Keywords:
Choquet integralfuzzy measuremagnification effectmulti-hazard coupling disaster

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Area of Science:

  • Disaster Risk Assessment
  • Environmental Science
  • Applied Mathematics

Background:

  • Multi-hazard coupling disasters, where multiple hazards interact, pose significant assessment challenges due to nonlinear risk additivity.
  • Existing methods struggle to accurately quantify the compounded consequences of simultaneous or sequential hazardous events.

Purpose of the Study:

  • To present the Choquet integral multiple linear regression model for overcoming nonlinear additivity in multi-hazard risk assessment.
  • To quantitatively assess the magnified severity and victim vulnerability in multi-hazard disasters.

Main Methods:

  • Utilized the Choquet integral multiple linear regression model to superpose nonlinear additive individual risks.
  • Incorporated fuzzy measure nonadditivity and Choquet integral nonlinearity into the risk assessment.
  • Introduced magnification coefficients for quantitative risk calculation.

Main Results:

  • The composite individual risk in multi-hazard coupling disasters exceeds the simple addition of individual hazard risks.
  • The case study of the 2015 Tianjin port disaster confirmed the amplified severity of coupled hazards.
  • The developed method accounts for magnification effects and victim vulnerability.

Conclusions:

  • Multi-hazard coupling disasters are demonstrably more severe than single-hazard events.
  • The proposed risk-assessment method provides effective guidance for disaster prevention, estimation, and response.
  • This approach offers solutions for complex risk analysis in diverse fields like finance, economics, and information science.