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Flood Protection Diversification to Reduce Probabilities of Extreme Losses

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  • Qian Zhou
  • James H. Lambert
  • Christopher W. Karvetski
  • Jeffrey M. Keisler
  • Igor Linkov

Abstract

Recent catastrophic losses because of floods require developing resilient approaches to flood risk protection. This article assesses how diversification of a system of coastal protections might decrease the probabilities of extreme flood losses. The study compares the performance of portfolios each consisting of four types of flood protection assets in a large region of dike rings. A parametric analysis suggests conditions in which diversifications of the types of included flood protection assets decrease extreme flood losses. Increased return periods of extreme losses are associated with portfolios where the asset types have low correlations of economic risk. The effort highlights the importance of understanding correlations across asset types in planning for large‐scale flood protection. It allows explicit integration of climate change scenarios in developing flood mitigation strategy.

Suggested Citation

  • Qian Zhou & James H. Lambert & Christopher W. Karvetski & Jeffrey M. Keisler & Igor Linkov, 2012. "Flood Protection Diversification to Reduce Probabilities of Extreme Losses," Risk Analysis, John Wiley & Sons, vol. 32(11), pages 1873-1887, November.
  • Handle: RePEc:wly:riskan:v:32:y:2012:i:11:p:1873-1887
    DOI: 10.1111/j.1539-6924.2012.01870.x
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    1. Barnes, Belinda & Giannini, Fiona & Arthur, Anthony & Walker, James, 2019. "Optimal allocation of limited resources to biosecurity surveillance using a portfolio theory methodology," Ecological Economics, Elsevier, vol. 161(C), pages 153-162.
    2. Francesco Serinaldi & Chris G. Kilsby, 2017. "A Blueprint for Full Collective Flood Risk Estimation: Demonstration for European River Flooding," Risk Analysis, John Wiley & Sons, vol. 37(10), pages 1958-1976, October.
    3. Vinent, Orencio Duran & Johnston, Robert J. & Kirwan, Matthew L. & Leroux, Anke D. & Martin, Vance L., 2019. "Coastal dynamics and adaptation to uncertain sea level rise: Optimal portfolios for salt marsh migration," Journal of Environmental Economics and Management, Elsevier, vol. 98(C).
    4. Michelle C. Hamilton & Shital A. Thekdi & Elisabeth M. Jenicek & Russell S. Harmon & Michael E. Goodsite & Michael P. Case & Christopher W. Karvetski & James H. Lambert, 2013. "Case studies of scenario analysis for adaptive management of natural resource and infrastructure systems," Environment Systems and Decisions, Springer, vol. 33(1), pages 89-103, March.
    5. Ali Jamshidi & Shahrzad Faghih‐Roohi & Siamak Hajizadeh & Alfredo Núñez & Robert Babuska & Rolf Dollevoet & Zili Li & Bart De Schutter, 2017. "A Big Data Analysis Approach for Rail Failure Risk Assessment," Risk Analysis, John Wiley & Sons, vol. 37(8), pages 1495-1507, August.
    6. Lam, C.Y. & Cruz, A.M., 2019. "Risk analysis for consumer-level utility gas and liquefied petroleum gas incidents using probabilistic network modeling: A case study of gas incidents in Japan," Reliability Engineering and System Safety, Elsevier, vol. 185(C), pages 198-212.
    7. Seth D. Baum, 2015. "Risk and resilience for unknown, unquantifiable, systemic, and unlikely/catastrophic threats," Environment Systems and Decisions, Springer, vol. 35(2), pages 229-236, June.
    8. Francesco Serinaldi & Florian Loecker & Chris G. Kilsby & Hubert Bast, 2018. "Flood propagation and duration in large river basins: a data-driven analysis for reinsurance purposes," 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. 94(1), pages 71-92, October.
    9. Convertino, Matteo & Annis, Antonio & Nardi, Fernando, 2019. "Information-theoretic Portfolio Decision Model for Optimal Flood Management," Earth Arxiv k5aut, Center for Open Science.

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