Incorporating inland flooding into hurricane evacuation decision support modeling

  • Kun Yang
  • Rachel A. DavidsonEmail author
  • Humberto Vergara
  • Randall L. Kolar
  • Kendra M. Dresback
  • Brian A. Colle
  • Brian Blanton
  • Tricia Wachtendorf
  • Jennifer Trivedi
  • Linda K. Nozick
Original Paper


Formal engineering hurricane evacuation studies have not typically considered inland flooding explicitly, though it has been shown repeatedly to be a major cause of damage and loss of life in hurricanes. In addition, coastal flooding and strong winds are often treated in a decoupled manner, so that the correlation between them is not captured. The recently introduced Integrated Scenario-based Evacuation (ISE) computational framework offers one approach to achieving evacuation decision support based on a representation of the hazard that considers coastal flooding, inland flooding, and wind in an integrated manner. Using a case study application of the ISE framework for Hurricane Matthew (2016) approaching the North Carolina coast, we evaluate the influence of including inland flooding on the resulting recommended evacuation plan (where and when official evacuation orders are to be issued) and the plan’s performance in terms of risk reduction and travel time increase. Results provide insight into managing hurricane evacuation with consideration of inland flooding. They suggest that in some cases inland areas should be evacuated just as coastal areas are; the scenarios responsible for and the timing of inland flooding can differ from those for coastal areas; the response to the different hazards should be treated together as a system because they can interact in complex ways; and planning for inland flooding can help reduce risk substantially while not adding much to evacuee travel times because inland evacuees do not have to travel as far to safety.


Hurricane Evacuation Inland flood Precipitation Decision support 



The authors thank the National Science Foundation (CMMI-1331269) for financial support of this research. The statements, findings, conclusions are those of the authors and do not necessarily reflect the views of the National Science Foundation. This research was also supported in part through the use of Information Technologies (IT) resources at the University of Delaware, specifically the high-performance computing resources.


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Copyright information

© Springer Nature B.V. 2019

Authors and Affiliations

  • Kun Yang
    • 1
  • Rachel A. Davidson
    • 1
    Email author
  • Humberto Vergara
    • 2
  • Randall L. Kolar
    • 3
  • Kendra M. Dresback
    • 3
  • Brian A. Colle
    • 4
  • Brian Blanton
    • 5
  • Tricia Wachtendorf
    • 6
  • Jennifer Trivedi
    • 7
  • Linda K. Nozick
    • 8
  1. 1.Department of Civil and Environmental EngineeringUniversity of DelawareNewarkUSA
  2. 2.Cooperative Institute for Mesoscale Meteorological StudiesUniversity of OklahomaNormanUSA
  3. 3.School of Civil Engineering and Environmental ScienceUniversity of OklahomaNormanUSA
  4. 4.School of Marine and Atmospheric SciencesStony Brook University, State University of New YorkStony BrookUSA
  5. 5.Renaissance Computing InstituteUniversity of North Carolina at Chapel HillChapel HillUSA
  6. 6.Department of Sociology and Criminal JusticeUniversity of DelawareNewarkUSA
  7. 7.Disaster Research CenterUniversity of DelawareNewarkUSA
  8. 8.School of Civil and Environmental EngineeringCornell UniversityIthacaUSA

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