Liu, B, Siu, YL, Mitchell, G et al. (1 more author) (2013) Exceedance probability of multiple natural hazards: Risk assessment in China's Yangtze River Delta. Natural Hazards, 69 (3). 2039 - 2055. ISSN 0921-030X
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.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Keywords: | Exceedance probability; human life loss; information diffusion theory; multi-hazard risk assessment; Yangtze River Delta |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Environment (Leeds) > School of Geography (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 20 Oct 2014 14:59 |
Last Modified: | 15 Nov 2016 17:33 |
Published Version: | http://dx.doi.org/10.1007/s11069-013-0794-8 |
Status: | Published |
Publisher: | Springer |
Identification Number: | 10.1007/s11069-013-0794-8 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:80355 |