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The Prince William Sound Risk Assessment

Author

Listed:
  • Jason R. W. Merrick

    (Department of Statistical Sciences and Operations Research, Virginia Commonwealth University, PO Box 843083, 1001 West Main Street, Richmond, Virginia 23284)

  • J. René van Dorp

    (Department of Engineering Management and Systems Engineering, George Washington University, 1776 G Street NW, Suite 110, Washington, DC 20052)

  • Thomas Mazzuchi

    (Department of Engineering Management and Systems Engineering, George Washington University, 1776 G Street NW, Suite 110, Washington, DC 20052)

  • John R. Harrald

    (Department of Engineering Management and Systems Engineering, George Washington University, 1776 G Street NW, Suite 110, Washington, DC 20052)

  • John E. Spahn

    (Department of Engineering Management and Systems Engineering, George Washington University, 1776 G Street NW, Suite 110, Washington, DC 20052)

  • Martha Grabowski

    (Business Department, Le Moyne College, and Department of Decision Sciences and Engineering Systems, Rensselaer Polytechnic Institute, 5555 Mount Pleasant Drive, Cazenovia, New York 13035)

Abstract

After the grounding of the Exxon Valdez and its subsequent oil spill, all parties with interests in Prince William Sound (PWS) were eager to prevent another major pollution event. While they implemented several measures to reduce the risk of an oil spill, the stakeholders disagreed about the effectiveness of these measures and the potential effectiveness of further proposed measures. They formed a steering committee to represent all the major stakeholders in the oil industry, in the government, in local industry, and among the local citizens. The steering committee hired a consultant team, which created a detailed model of the PWS system, integrating system simulation, data analysis, and expert judgment. The model was capable of assessing the current risk of accidents involving oil tankers operating in the PWS and of evaluating measures aimed at reducing this risk. The risk model showed that actions taken prior to the study had reduced the risk of oil spill by 75 percent, and it identified measures estimated to reduce the accident frequency by an additional 68 percent, including improving the safety-management systems of the oil companies and stationing an enhanced-capability tug, called the Gulf Service, at Hinchinbrook Entrance. In all, various stakeholders made multimillion dollar investments to reduce the risk of further oil spills based on the results of the risk assessment.

Suggested Citation

  • Jason R. W. Merrick & J. René van Dorp & Thomas Mazzuchi & John R. Harrald & John E. Spahn & Martha Grabowski, 2002. "The Prince William Sound Risk Assessment," Interfaces, INFORMS, vol. 32(6), pages 25-40, December.
    • Handle: RePEc:inm:orinte:v:32:y:2002:i:6:p:25-40
    DOI: 10.1287/inte.32.6.25.6474
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    References listed on IDEAS

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    Cited by:

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    2. Zhang, Yi & Lam, Jasmine Siu Lee, 2016. "Estimating economic losses of industry clusters due to port disruptions," Transportation Research Part A: Policy and Practice, Elsevier, vol. 91(C), pages 17-33.
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    10. Zhang, Weibin & Feng, Xinyu & Goerlandt, Floris & Liu, Qing, 2020. "Towards a Convolutional Neural Network model for classifying regional ship collision risk levels for waterway risk analysis," Reliability Engineering and System Safety, Elsevier, vol. 204(C).
    11. Giel Wiel & J. Dorp, 2011. "An oil outflow model for tanker collisions and groundings," Annals of Operations Research, Springer, vol. 187(1), pages 279-304, July.
    12. Goerlandt, Floris & Montewka, Jakub, 2015. "Maritime transportation risk analysis: Review and analysis in light of some foundational issues," Reliability Engineering and System Safety, Elsevier, vol. 138(C), pages 115-134.
    13. A. U. Qaisrani & K. M. Khan & M. Khalid, 2004. "Effect Of Eley–Rideal Process On The Phase Diagram Of A Monomer–Dimer Catalytic Reaction On (001) Surface And Subsurface Of A Simple Cubic Structure," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 15(09), pages 1215-1225.
    14. Jason R. W. Merrick & John R. Harrald, 2007. "Making Decisions About Safety in US Ports and Waterways," Interfaces, INFORMS, vol. 37(3), pages 240-252, June.
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    16. Jason R. W. Merrick & Martha Grabowski, 2014. "Decision Performance and Safety Performance: A Value-Focused Thinking Study in the Oil Industry," Decision Analysis, INFORMS, vol. 11(2), pages 105-116, June.
    17. J Montewka & P Krata & F Goerlandt & A Mazaheri & P Kujala, 2011. "Marine traffic risk modelling – an innovative approach and a case study," Journal of Risk and Reliability, , vol. 225(3), pages 307-322, September.
    18. Özgecan S. Ulusçu & Birnur Özbaş & Tayfur Altıok & İlhan Or, 2009. "Risk Analysis of the Vessel Traffic in the Strait of Istanbul," Risk Analysis, John Wiley & Sons, vol. 29(10), pages 1454-1472, October.
    19. Haapasaari, Päivi & Helle, Inari & Lehikoinen, Annukka & Lappalainen, Jouni & Kuikka, Sakari, 2015. "A proactive approach for maritime safety policy making for the Gulf of Finland: Seeking best practices," Marine Policy, Elsevier, vol. 60(C), pages 107-118.
    20. J. Dorp & Jason Merrick, 2011. "On a risk management analysis of oil spill risk using maritime transportation system simulation," Annals of Operations Research, Springer, vol. 187(1), pages 249-277, July.
    21. Tianyang Wang & James S. Dyer & John C. Butler, 2016. "Modeling Correlated Discrete Uncertainties in Event Trees with Copulas," Risk Analysis, John Wiley & Sons, vol. 36(2), pages 396-410, February.
    22. Jason R. W. Merrick & J. Rene Van Dorp & Varun Dinesh, 2005. "Assessing Uncertainty in Simulation‐Based Maritime Risk Assessment," Risk Analysis, John Wiley & Sons, vol. 25(3), pages 731-743, June.

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