IDEAS home Printed from https://ideas.repec.org/a/spr/nathaz/v61y2012i3p1277-1292.html
   My bibliography  Save this article

Exposure of main critical facilities to natural and man-made hazards in Grand Cayman, Cayman Islands

Author

Listed:
  • D. Novelo-Casanova
  • G. Suárez

Abstract

The level of exposure to the impact of natural and man-made hazards of the main critical facilities at Grand Cayman (GC), Cayman Islands, was determined using the methodology developed by the National Oceanic and Atmospheric Administration Coastal Services Center. Previous studies identified hurricanes as the most important natural hazard for GC. However, other hazards include earthquakes, tsunamis and explosions or leaks of fuel storage tanks. Our results indicate that: (1) About 82% of the emergency response infrastructure, 95% of the government facilities, and 85% of the utilities have a level of exposure from low to moderate; (2) only 12% of all identified critical facilities at GC are highly exposed; (3) large explosions or leaks of the Airport Texaco Fuel Depot, the local fuel pipeline, and the Home Gas Terminal could impact nearby critical infrastructure. The facilities identified with a high level of exposure are as follows: the Bodden Town Clinic and Police Station, the West Bay Fire Station, the Georgetown Dock and Port, and the Esso and Texaco Fuel terminals. Most portions of the coastal roads are moderately exposed to natural and man-made hazards. The most exposed sections are four short segments of the road system located along the North Sound, Little Sound and Eastern West Bay area. In some cases, the high exposure of critical facilities stems from their location on the coastline. In other cases, however, adequate policies to either protect or to relocate these facilities would help to reduce their level of exposure to both natural and man-made hazards. Copyright Springer Science+Business Media B.V. 2012

Suggested Citation

  • D. Novelo-Casanova & G. Suárez, 2012. "Exposure of main critical facilities to natural and man-made hazards in Grand Cayman, Cayman Islands," 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. 61(3), pages 1277-1292, April.
  • Handle: RePEc:spr:nathaz:v:61:y:2012:i:3:p:1277-1292
    DOI: 10.1007/s11069-011-9982-6
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s11069-011-9982-6
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1007/s11069-011-9982-6?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Berdica, Katja, 2002. "An introduction to road vulnerability: what has been done, is done and should be done," Transport Policy, Elsevier, vol. 9(2), pages 117-127, April.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Bergström, Anna & Krüger, Niclas A., 2013. "Modeling passenger train delay distributions: evidence and implications," Working papers in Transport Economics 2013:3, CTS - Centre for Transport Studies Stockholm (KTH and VTI).
    2. Richard Connors & David Watling, 2015. "Assessing the Demand Vulnerability of Equilibrium Traffic Networks via Network Aggregation," Networks and Spatial Economics, Springer, vol. 15(2), pages 367-395, June.
    3. Xu, Xiangdong & Qu, Kai & Chen, Anthony & Yang, Chao, 2021. "A new day-to-day dynamic network vulnerability analysis approach with Weibit-based route adjustment process," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 153(C).
    4. Mengying Cui & David Levinson, 2018. "Accessibility analysis of risk severity," Transportation, Springer, vol. 45(4), pages 1029-1050, July.
    5. Milan Janić, 2018. "Modelling the resilience of rail passenger transport networks affected by large-scale disruptive events: the case of HSR (high speed rail)," Transportation, Springer, vol. 45(4), pages 1101-1137, July.
    6. Masiero, Lorenzo & Maggi, Rico, 2012. "Estimation of indirect cost and evaluation of protective measures for infrastructure vulnerability: A case study on the transalpine transport corridor," Transport Policy, Elsevier, vol. 20(C), pages 13-21.
    7. Jing Liu & Huapu Lu & Mingyu Chen & Jianyu Wang & Ying Zhang, 2020. "Macro Perspective Research on Transportation Safety: An Empirical Analysis of Network Characteristics and Vulnerability," Sustainability, MDPI, vol. 12(15), pages 1-18, August.
    8. Xueguo Xu & Chen Xu & Wenxin Zhang, 2022. "Research on the Destruction Resistance of Giant Urban Rail Transit Network from the Perspective of Vulnerability," Sustainability, MDPI, vol. 14(12), pages 1-26, June.
    9. Jenelius, Erik, 2010. "User inequity implications of road network vulnerability," The Journal of Transport and Land Use, Center for Transportation Studies, University of Minnesota, vol. 2(3), pages 57-73.
    10. Mohamad Darayi & Kash Barker & Joost R. Santos, 2017. "Component Importance Measures for Multi-Industry Vulnerability of a Freight Transportation Network," Networks and Spatial Economics, Springer, vol. 17(4), pages 1111-1136, December.
    11. Jenelius, Erik & Mattsson, Lars-Göran, 2012. "Road network vulnerability analysis of area-covering disruptions: A grid-based approach with case study," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(5), pages 746-760.
    12. Sun, Daniel (Jian) & Guan, Shituo, 2016. "Measuring vulnerability of urban metro network from line operation perspective," Transportation Research Part A: Policy and Practice, Elsevier, vol. 94(C), pages 348-359.
    13. Roberto Cardinale, 2022. "State-Owned Enterprises’ Reforms and their Implications for the Resilience and Vulnerability of the Chinese Economy: Evidence from the Banking, Energy and Telecom Sectors," Networks and Spatial Economics, Springer, vol. 22(3), pages 489-514, September.
    14. Rolf Nyberg & Magnus Johansson, 2013. "Indicators of road network vulnerability to storm-felled trees," 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. 69(1), pages 185-199, October.
    15. Zhu, Jingjing & Xu, Xiangdong & Wang, Zijian, 2023. "Economic evaluation of redundancy design for transportation networks under disruptions: Framework and case study," Transport Policy, Elsevier, vol. 142(C), pages 70-83.
    16. Daniel (Jian) Sun & Yuhan Zhao & Qing-Chang Lu, 2015. "Vulnerability Analysis of Urban Rail Transit Networks: A Case Study of Shanghai, China," Sustainability, MDPI, vol. 7(6), pages 1-18, May.
    17. Federico Karagulian & Gaetano Valenti & Carlo Liberto & Matteo Corazza, 2022. "A Methodology to Estimate Functional Vulnerability Using Floating Car Data," Sustainability, MDPI, vol. 15(1), pages 1-15, December.
    18. Bell, Michael G.H. & Kurauchi, Fumitaka & Perera, Supun & Wong, Walter, 2017. "Investigating transport network vulnerability by capacity weighted spectral analysis," Transportation Research Part B: Methodological, Elsevier, vol. 99(C), pages 251-266.
    19. Bagloee, Saeed Asadi & Sarvi, Majid & Wolshon, Brian & Dixit, Vinayak, 2017. "Identifying critical disruption scenarios and a global robustness index tailored to real life road networks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 98(C), pages 60-81.
    20. Andersson, Matts & Berglund, Moa & Flodén, Jonas & Persson, Christer & Waidringer, Jonas, 2017. "A method for measuring and valuing transport time variability in logistics and cost benefit analysis," Research in Transportation Economics, Elsevier, vol. 66(C), pages 59-69.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:nathaz:v:61:y:2012:i:3:p:1277-1292. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.