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Public Evacuation Decisions and Hurricane Track Uncertainty

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  • Eva Regnier

    (Defense Resources Management Institute, Naval Postgraduate School, Monterey, California 93943)

Abstract

Public officials with the authority to order hurricane evacuations face a difficult trade-off between risks to life and costly false alarms. Evacuation decisions must be made on the basis of imperfect information, in the form of forecasts. The quality of these decisions can be improved if they are also informed by measures of uncertainty about the forecast, including estimates of the value of waiting for updated, more accurate, forecasts. Using a stochastic model of storm motion derived from historic tracks, this paper explores the relationship between lead time and track uncertainty for Atlantic hurricanes and the implications of this relationship for evacuation decisions. Typical evacuation clearance times and track uncertainty imply that public officials who require no more than a 10% probability of failing to evacuate before a striking hurricane (a false negative) must accept that at least 76%--and for some locations over 90%--of evacuations will be false alarms. Reducing decision lead times from 72 to 48 hours for major population centers could save an average of hundreds of millions of dollars in evacuation costs annually, with substantial geographic variation in savings.

Suggested Citation

  • Eva Regnier, 2008. "Public Evacuation Decisions and Hurricane Track Uncertainty," Management Science, INFORMS, vol. 54(1), pages 16-28, January.
    • Handle: RePEc:inm:ormnsc:v:54:y:2008:i:1:p:16-28
    DOI: 10.1287/mnsc.1070.0764
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    References listed on IDEAS

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    1. Regnier, Eva, 2008. "Doing something about the weather," Omega, Elsevier, vol. 36(1), pages 22-32, February.
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    Cited by:

    1. Bish, Douglas R. & Sherali, Hanif D., 2013. "Aggregate-level demand management in evacuation planning," European Journal of Operational Research, Elsevier, vol. 224(1), pages 79-92.
    2. Crowther, Kenneth G., 2010. "Risk-informed assessment of regional preparedness: A case study of emergency potable water for hurricane response in Southeast Virginia," International Journal of Critical Infrastructure Protection, Elsevier, vol. 3(2), pages 83-98.
    3. Jon M. Stauffer & Subodha Kumar, 2021. "Impact of Incorporating Returns into Pre‐Disaster Deployments for Rapid‐Onset Predictable Disasters," Production and Operations Management, Production and Operations Management Society, vol. 30(2), pages 451-474, February.
    4. Thomas J. Cova & Philip E. Dennison & Dapeng Li & Frank A. Drews & Laura K. Siebeneck & Michael K. Lindell, 2017. "Warning Triggers in Environmental Hazards: Who Should Be Warned to Do What and When?," Risk Analysis, John Wiley & Sons, vol. 37(4), pages 601-611, April.
    5. McLay, Laura A. & Boone, Edward L. & Brooks, J. Paul, 2012. "Analyzing the volume and nature of emergency medical calls during severe weather events using regression methodologies," Socio-Economic Planning Sciences, Elsevier, vol. 46(1), pages 55-66.
    6. S Taskin & E J Lodree,, 2011. "A Bayesian decision model with hurricane forecast updates for emergency supplies inventory management," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(6), pages 1098-1108, June.
    7. Andrew B. Martinez, 2020. "Forecast Accuracy Matters for Hurricane Damage," Econometrics, MDPI, vol. 8(2), pages 1-24, May.
    8. Rachel A. Davidson & Linda K. Nozick & Tricia Wachtendorf & Brian Blanton & Brian Colle & Randall L. Kolar & Sarah DeYoung & Kendra M. Dresback & Wenqi Yi & Kun Yang & Nicholas Leonardo, 2020. "An Integrated Scenario Ensemble‐Based Framework for Hurricane Evacuation Modeling: Part 1—Decision Support System," Risk Analysis, John Wiley & Sons, vol. 40(1), pages 97-116, January.
    9. Moshtagh, Mehrdad & Fathali, Jafar & Smith, J. MacGregor, 2018. "The Stochastic Queue Core problem, evacuation networks, and state-dependent queues," European Journal of Operational Research, Elsevier, vol. 269(2), pages 730-748.
    10. Joanna Burston & Daniel Ware & Rodger Tomlinson, 2015. "The real-time needs of emergency managers for tropical cyclone storm tide forecasting: results of a participatory stakeholder engagement process," 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. 78(3), pages 1653-1668, September.
    11. Alfonso J. Pedraza-Martinez & Sameer Hasija & Luk N. Van Wassenhove, 2020. "Fleet Coordination in Decentralized Humanitarian Operations Funded by Earmarked Donations," Operations Research, INFORMS, vol. 68(4), pages 984-999, July.
    12. Eva D. Regnier & Cameron A. MacKenzie, 2019. "The Hurricane Decision Simulator: A Tool for Marine Forces in New Orleans to Practice Operations Management in Advance of a Hurricane," Service Science, INFORMS, vol. 21(1), pages 103-120, January.
    13. Jean M Carlson & David L Alderson & Sean P Stromberg & Danielle S Bassett & Emily M Craparo & Francisco Guiterrez-Villarreal & Thomas Otani, 2014. "Measuring and Modeling Behavioral Decision Dynamics in Collective Evacuation," PLOS ONE, Public Library of Science, vol. 9(2), pages 1-17, February.
    14. Bretschneider, S. & Kimms, A., 2011. "A basic mathematical model for evacuation problems in urban areas," Transportation Research Part A: Policy and Practice, Elsevier, vol. 45(6), pages 523-539, July.
    15. Rezapour, Shabnam & Farahani, Reza Zanjirani & Morshedlou, Nazanin, 2021. "Impact of timing in post-warning prepositioning decisions on performance measures of disaster management: A real-life application," European Journal of Operational Research, Elsevier, vol. 293(1), pages 312-335.
    16. J. Senkbeil & D. Brommer & P. Dixon & M. Brown & K. Sherman-Morris, 2010. "The perceived landfall location of evacuees from Hurricane Gustav," 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. 54(1), pages 141-158, July.
    17. Dean Kyne & William Donner, 2018. "Kyne–Donner Model of Authority’s Recommendation and Hurricane Evacuation Decisions: A Study of Hypothetical Hurricane Event in the Rio Grande Valley, Texas," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 37(6), pages 897-922, December.
    18. Zhujun Liu & Jiuping Xu & Bernard Han, 2013. "Small- and medium-sized enterprise post-disaster reconstruction management patterns and application," 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. 68(2), pages 809-835, September.
    19. Corene Matyas & Sivaramakrishnan Srinivasan & Ignatius Cahyanto & Brijesh Thapa & Lori Pennington-Gray & Jorge Villegas, 2011. "Risk perception and evacuation decisions of Florida tourists under hurricane threats: a stated preference analysis," 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. 59(2), pages 871-890, November.
    20. Shabana Khan & Jyoti L. Mishra & Kuna-hui Elaine Lin & Emma E. H. Doyle, 2017. "Rethinking communication in risk interpretation and action," 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. 88(3), pages 1709-1726, September.
    21. Samohyl, Robert, 2012. "Audits and logistic regression, deciding what really matters in service processes: a case study of a government funding agency for research grants," MPRA Paper 41557, University Library of Munich, Germany.
    22. Liu, Kanglin & Liu, Changchun & Xiang, Xi & Tian, Zhili, 2023. "Testing facility location and dynamic capacity planning for pandemics with demand uncertainty," European Journal of Operational Research, Elsevier, vol. 304(1), pages 150-168.

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