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Journal Article

Citation

Yang K, Davidson RA, Blanton B, Colle B, Dresback K, Kolar R, Nozick LK, Trivedi J, Wachtendorf T. Int. J. Disaster Risk Reduct. 2019; 36: e101093.

Copyright

(Copyright © 2019, Elsevier Publishing)

DOI

10.1016/j.ijdrr.2019.101093

PMID

unavailable

Abstract

The evolution of a hurricane--how the track, intensity, forward speed, and resulting hazard effects on land (strong winds, flooding) develop over its lifetime--is often highly uncertain. Further, the uncertainty is dynamic because it is resolved as events unfold until ultimately the storm's evolution is known completely, and because the ensemble of forecasts changes over time. Emergency managers recognize these challenges and may engage in some combination of robust, adaptive, or repeated planning to address them. However, science- and engineering-based evacuation decision support models typically do not formally incorporate uncertainty. This article discusses the use of formal modeling to support robust, adaptive, and repeated decision-making during an impending hurricane. It also details a case study of Hurricane Isabel (2003) in North Carolina using the recently introduced Integrated Scenario-based Evacuation (ISE) computational framework to compare the effects of including each of the three features in the modeling.

FINDINGS suggest that making the evacuation planning robust, adaptive, and repeated should improve results by reducing both the numbers of people at risk and unnecessary evacuation orders and travel. The magnitude of those benefits, however, depends on uncertainty in, and evolution of, the attributes of the particular hurricane.


Language: en

Keywords

Adaptive; Evacuation; Hurricane; Multi-stage stochastic program; Orders; Planning

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