Evaluation of Hurricane Evacuation Order Plans: Hurricane Florence Case Study
Publication: Natural Hazards Review
Volume 23, Issue 4
Abstract
This paper introduces an approach to evaluate the performance of a previously implemented or proposed hurricane evacuation plan that describes where and when official evacuation orders are issued. The approach involves use of the new integrated scenario-based evacuation (ISE) decision support tool to define a best track evacuation plan as a reference point and measure the performance of other plans in relation to that according to their ability to meet multiple stated objectives: minimizing risk to the population, travel time, and time people are away from their homes. Using North Carolina in Hurricane Florence (2018) as a case study, we demonstrate the process by evaluating performance of both the actual set of orders as executed and the orders that would have been recommended if the new ISE decision support tool had been used during the event. All three plans were evaluated for two cases—assuming the hurricane unfolds as it actually did, and if the hurricane had instead evolved like one of 21 other realistic scenarios. Results suggest the actual evacuation was quite good, and the ISE tool could have resulted in improved evacuation performance.
Practical Applications
This paper introduces a comprehensive, replicable approach to evaluating the performance of a previously implemented or proposed hurricane evacuation plan (i.e., a plan that describes where and when official evacuation orders are issued). Currently, there is no formal way to do so. The method presented defines as a reference point the evacuation plan that would minimize the stated aims if there was no uncertainty in the hurricane behavior, that is, if we had a crystal ball so that at the time the hurricane formed we could know the eventual track, intensity, and associated wind, rain, and flooding hazards exactly. The approach then measures the performance of other plans in relation to that reference, with performance based on their ability to meet multiple objectives: minimizing risk to the population, travel time, and time people are away from their homes. This new method can be of practical use to (1) provide after-the-fact evaluation of past evacuations to facilitate learning, (2) support planning through comparison of alternative strategies and decision support tools for hypothetical future hurricanes, and (3) gauge expectations about what performance can be reasonably expected in different circumstances.
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Data Availability Statement
Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request (input data, resulting evacuation plans, and evaluations).
Acknowledgments
This research was supported in part through the use of information technology (IT) resources at the University of Delaware, specifically the high-performance computing resources. We thank Stephen Powers and Dianne Curtis of the North Carolina Division of Emergency Management for insights on the practice of hurricane evacuation management. We also thank the National Science Foundation (CMMI-1331269) for financial support of this research. The statements, findings, and conclusions are those of the authors and do not necessarily reflect the views of the National Science Foundation, the University of Delaware, or the North Carolina Division of Emergency Management.
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Information & Authors
Information
Published In
Natural Hazards Review
Volume 23 • Issue 4 • November 2022
Copyright
© 2022 American Society of Civil Engineers.
History
Received: Apr 15, 2021
Accepted: Jun 13, 2022
Published online: Aug 26, 2022
Published in print: Nov 1, 2022
Discussion open until: Jan 26, 2023
ASCE Technical Topics:
- Business management
- Case studies
- Decision making
- Decision support systems
- Disaster preparedness
- Disaster risk management
- Disasters and hazards
- Engineering fundamentals
- Evacuation
- Hurricanes, typhoons, and cyclones
- Management methods
- Methodology (by type)
- Natural disasters
- Practice and Profession
- Quality control
- Research methods (by type)
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