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Simulation-based catastrophe-induced port loss estimation

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  • Cao, Xinhu
  • Lam, Jasmine Siu Lee

Abstract

Seaports are critical infrastructure systems in the international economy. They are at the same time vulnerable to various types of natural and man-made catastrophes due to their special coastal and low-lying locations. Traditional catastrophe risk analyses focused more on regions, port cities, and port communities. Limited studies assessed catastrophe risks on ports as a specific system. This paper aims to develop a catastrophe-induced port loss estimation framework, based on a port operation simulation model, actual terminal records and historical hazard records. By using the typhoon hazard and the Port of Shenzhen as a case study, we find that (1) the worst-case scenario of a typhoon impact could cause a total loss of US$0.91 billion for a terminal with 16 berths; and (2) the annual predicted typhoon-induced loss for the same terminal for the next 5 years will reach approximately US$64 million, accounting for 19.7% of the terminal net profit in 2015. The results provide useful references for various port stakeholders in catastrophe risk assessment and mitigation.

Suggested Citation

  • Cao, Xinhu & Lam, Jasmine Siu Lee, 2018. "Simulation-based catastrophe-induced port loss estimation," Reliability Engineering and System Safety, Elsevier, vol. 175(C), pages 1-12.
    • Handle: RePEc:eee:reensy:v:175:y:2018:i:c:p:1-12
    DOI: 10.1016/j.ress.2018.02.008
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    References listed on IDEAS

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    4. Kuhla, Kilian & Willner, Sven N & Otto, Christian & Levermann, Anders, 2023. "Resilience of international trade to typhoon-related supply disruptions," Journal of Economic Dynamics and Control, Elsevier, vol. 151(C).
    5. Shen, Zhonghui & Wei, Kai, 2021. "Stochastic model of tropical cyclones along China coast including the effects of spatial heterogeneity and ocean feedback," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
    6. Hong, Xu & Wan, Zhiqiang & Chen, Jianbing, 2023. "Parallel assessment of the tropical cyclone wind hazard at multiple locations using the probability density evolution method integrated with the change of probability measure," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
    7. Cremen, Gemma & Bozzoni, Francesca & Pistorio, Silvia & Galasso, Carmine, 2022. "Developing a risk-informed decision-support system for earthquake early warning at a critical seaport," Reliability Engineering and System Safety, Elsevier, vol. 218(PA).
    8. Zhou, Yusheng & Li, Xue & Yuen, Kum Fai, 2022. "Holistic risk assessment of container shipping service based on Bayesian Network Modelling," Reliability Engineering and System Safety, Elsevier, vol. 220(C).

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