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Implementation of an integrated vulnerability and risk assessment model

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  • Natainia Lummen
  • Fumihiko Yamada

Abstract

An integrated vulnerability and risk assessment model (IVR) is proposed. The proposed model is a composite index that assesses the relationships among four critical components, namely exposure, hazard, vulnerability and capacities and measures, and how these can be used to illustrate the integrated risk and vulnerability situation of an area. These factors are assessed using individual variables. Fifty-four variables, objectively decided upon, were used to measure the contribution of each component factor. The general characteristics of vulnerability, risk, exposure and capacities and measures are well known; however, the relative importance of each variable and their inter-relatedness, in measuring risk and vulnerabilities, as demonstrated by the IVR; and how these in turn affect the impacts of natural hazards, are still debatable. The IVR though provides a valid, reliable and sensitive tool, which can be used to further explore these relationships. Through robust testing and application, subjectivity in the selection of variables can be reduced. Moreover, through the establishment of a database for data collection and storage, objectivity (reliability) can be achieved as well as, availability of the requisite data inputs. The sensitivity of the model allows for the quick identification of strategic action, which will ultimately lead to hazard loss reduction. The values yielded for each component factor can help decision-makers in the allocation of scarce developmental funds as well as identify trends in levels of risk, vulnerability, exposures and capacities and measures as well as determine areas where mitigation strategies are needed most. Copyright Springer Science+Business Media Dordrecht 2014

Suggested Citation

  • Natainia Lummen & Fumihiko Yamada, 2014. "Implementation of an integrated vulnerability and risk assessment model," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 73(2), pages 1085-1117, September.
  • Handle: RePEc:spr:nathaz:v:73:y:2014:i:2:p:1085-1117
    DOI: 10.1007/s11069-014-1123-6
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    1. Norman Ferrier & C. Haque, 2003. "Hazards Risk Assessment Methodology for Emergency Managers: A Standardized Framework for Application," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 28(2), pages 271-290, March.
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    3. Maxx Dilley & Robert S. Chen & Uwe Deichmann & Arthur L. Lerner-Lam & Margaret Arnold, 2005. "Natural Disaster Hotspots: A Global Risk Analysis," World Bank Publications - Books, The World Bank Group, number 7376, December.
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    2. Didier Soto & Florent Renard, 2015. "New prospects for the spatialisation of technological risks by combining hazard and the vulnerability of assets," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 79(3), pages 1531-1548, December.
    3. Guangyun Gao & Shaofeng Yao & Yujun Cui & Qingsheng Chen & Xianlin Zhang & Kewen Wang, 2018. "Zoning of confined aquifers inrush and quicksand in Shanghai region," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 91(3), pages 1341-1363, April.
    4. Zijun Qie & Lili Rong, 2017. "An integrated relative risk assessment model for urban disaster loss in view of disaster system theory," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 88(1), pages 165-190, August.
    5. Tengjiao Guo & Guosheng Li, 2020. "Study on methods to identify the impact factors of economic losses due to typhoon storm surge based on confirmatory factor analysis," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 100(2), pages 515-534, January.

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