Abstract

In recent years, greater attention has been given to advancing the theory and practice of assessing risk from multiple hazards. Most approaches calculate multi-hazard risk by aggregating risk scores for individual hazards and ignore the combined exceedance probability of multiple hazards. We address this problem by developing a simple and practicable multi-hazard risk assessment method that uses information diffusion theory to overcome the difficulty posed by a lack of historical or spatial data on natural hazard-induced loss. China’s Yangtze River Delta region is used as a demonstrative example, and the exceedance probability distribution of multi-hazard risk to human life was calculated using natural hazard disaster life loss data for 1950–2010. Multi-hazard risk to human life is mapped as exceedance probability at different mortality rates and loss at different risk return periods using a geographical information system. Results show that Hangzhou and Ningbo are at a relatively high risk from multiple natural hazards, and Shanghai is at a relatively low risk. For scenarios of 10-, 20- and 50-year risk return periods, there are no significant changes in the risk rank of the cities; Hangzhou, Ningbo and Zhoushan are at a relatively high risk, while Shanghai is at a relatively low risk.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.