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Risk Anal. 2018 Mar 30. doi: 10.1111/risa.12990. [Epub ahead of print]

An Integrated Scenario Ensemble-Based Framework for Hurricane Evacuation Modeling: Part 1-Decision Support System.

Author information

1
Dept. of Civil and Environmental Engineering, University of Delaware, Newark, DE, USA.
2
School of Civil and Environmental Engineering, Cornell University, Ithaca, NY, USA.
3
Dept. of Sociology and Criminal Justice, University of Delaware, Newark, DE, USA.
4
Renaissance Computing Institute, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
5
School of Marine and Atmospheric Sciences, Stony Brook University, State University of New York, Stony Brook, NY, USA.
6
School of Civil Engineering and Environmental Science, University of Oklahoma, Norman, OK, USA.
7
Institute for Disaster Management, University of Georgia, Athens, GA, USA.

Abstract

This article introduces a new integrated scenario-based evacuation (ISE) framework to support hurricane evacuation decision making. It explicitly captures the dynamics, uncertainty, and human-natural system interactions that are fundamental to the challenge of hurricane evacuation, but have not been fully captured in previous formal evacuation models. The hazard is represented with an ensemble of probabilistic scenarios, population behavior with a dynamic decision model, and traffic with a dynamic user equilibrium model. The components are integrated in a multistage stochastic programming model that minimizes risk and travel times to provide a tree of evacuation order recommendations and an evaluation of the risk and travel time performance for that solution. The ISE framework recommendations offer an advance in the state of the art because they: (1) are based on an integrated hazard assessment (designed to ultimately include inland flooding), (2) explicitly balance the sometimes competing objectives of minimizing risk and minimizing travel time, (3) offer a well-hedged solution that is robust under the range of ways the hurricane might evolve, and (4) leverage the substantial value of increasing information (or decreasing degree of uncertainty) over the course of a hurricane event. A case study for Hurricane Isabel (2003) in eastern North Carolina is presented to demonstrate how the framework is applied, the type of results it can provide, and how it compares to available methods of a single scenario deterministic analysis and a two-stage stochastic program.

KEYWORDS:

Evacuation; hurricane; multistage stochastic program

PMID:
29601643
DOI:
10.1111/risa.12990

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