Simulation-based severe weather-induced container terminal economic loss estimation

Container terminals play a critical role in maritime supply chains. However, they show vulnerabilities to severe weather events due to the sea–land interface locations. Previous severe weather risk analysis focused more on larger assessment units, such as regions and cities. Limited studies assessed...

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Main Authors: Cao, Xinhu, Lam, Jasmine Siu Lee
Other Authors: School of Civil and Environmental Engineering
Format: Article
Language:English
Published: 2018
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Online Access:https://hdl.handle.net/10356/89403
http://hdl.handle.net/10220/46238
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-894032020-03-07T11:43:39Z Simulation-based severe weather-induced container terminal economic loss estimation Cao, Xinhu Lam, Jasmine Siu Lee School of Civil and Environmental Engineering Institute of Catastrophe Risk Management Port Risk Severe Weather DRNTU::Engineering::Civil engineering Container terminals play a critical role in maritime supply chains. However, they show vulnerabilities to severe weather events due to the sea–land interface locations. Previous severe weather risk analysis focused more on larger assessment units, such as regions and cities. Limited studies assessed severe weather risks on a smaller scale of seaports. This paper aims to propose a severe weather-induced container terminal loss estimation framework. Based on a container terminal operation simulation model, monthly average loss and single event-induced loss are obtained by using historical hazard records and terminal operation records as model inputs. By studying the Port of Shenzhen as the case study, we find that the fog events in March lead to the longest monthly port downtime and the highest monthly severe weather-induced economic losses in the studied port. The monthly average loss is estimated to be 30 million USD, accounting for 20% of the intact income. The worst-case scenario is found to be a red-signal typhoon attack which results in nearly 20% decrease in the month’s income. The results provide useful references for various container terminal stakeholders in severe weather risk management. Accepted version 2018-10-08T01:59:52Z 2019-12-06T17:24:44Z 2018-10-08T01:59:52Z 2019-12-06T17:24:44Z 2018 Journal Article Cao, X., & Lam, J. S. L. (2018). Simulation-based severe weather-induced container terminal economic loss estimation. Maritime Policy & Management, 1-25. doi:10.1080/03088839.2018.1516049 0308-8839 https://hdl.handle.net/10356/89403 http://hdl.handle.net/10220/46238 10.1080/03088839.2018.1516049 en Maritime Policy & Management © 2018 Taylor & Francis. This is the author created version of a work that has been peer reviewed and accepted for publication by Maritime Policy & Management, Taylor & Francis. It incorporates referee’s comments but changes resulting from the publishing process, such as copyediting, structural formatting, may not be reflected in this document. The published version is available at: [http://dx.doi.org/10.1080/03088839.2018.1516049]. 42 p. application/pdf
institution Nanyang Technological University
building NTU Library
country Singapore
collection DR-NTU
language English
topic Port Risk
Severe Weather
DRNTU::Engineering::Civil engineering
spellingShingle Port Risk
Severe Weather
DRNTU::Engineering::Civil engineering
Cao, Xinhu
Lam, Jasmine Siu Lee
Simulation-based severe weather-induced container terminal economic loss estimation
description Container terminals play a critical role in maritime supply chains. However, they show vulnerabilities to severe weather events due to the sea–land interface locations. Previous severe weather risk analysis focused more on larger assessment units, such as regions and cities. Limited studies assessed severe weather risks on a smaller scale of seaports. This paper aims to propose a severe weather-induced container terminal loss estimation framework. Based on a container terminal operation simulation model, monthly average loss and single event-induced loss are obtained by using historical hazard records and terminal operation records as model inputs. By studying the Port of Shenzhen as the case study, we find that the fog events in March lead to the longest monthly port downtime and the highest monthly severe weather-induced economic losses in the studied port. The monthly average loss is estimated to be 30 million USD, accounting for 20% of the intact income. The worst-case scenario is found to be a red-signal typhoon attack which results in nearly 20% decrease in the month’s income. The results provide useful references for various container terminal stakeholders in severe weather risk management.
author2 School of Civil and Environmental Engineering
author_facet School of Civil and Environmental Engineering
Cao, Xinhu
Lam, Jasmine Siu Lee
format Article
author Cao, Xinhu
Lam, Jasmine Siu Lee
author_sort Cao, Xinhu
title Simulation-based severe weather-induced container terminal economic loss estimation
title_short Simulation-based severe weather-induced container terminal economic loss estimation
title_full Simulation-based severe weather-induced container terminal economic loss estimation
title_fullStr Simulation-based severe weather-induced container terminal economic loss estimation
title_full_unstemmed Simulation-based severe weather-induced container terminal economic loss estimation
title_sort simulation-based severe weather-induced container terminal economic loss estimation
publishDate 2018
url https://hdl.handle.net/10356/89403
http://hdl.handle.net/10220/46238
_version_ 1681043071750373376