Hurricane evacuation modeling: improvement and application of an integrated scenario-based evacuation framework
Date
2018
Authors
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Publisher
University of Delaware
Abstract
This dissertation describes a new computational framework to support hurricane evacuation order decision-making. The integrated scenario-based evacuation (ISE) framework explicitly captures the dynamics, uncertainty, and human-nature system interactions that are fundamental to the challenge of hurricane evacuations but have not been fully captured in previous formal evacuation models. The ISE framework recommendations offer an advance in the state-of-the-art because they: (a) are based on integrated hazard assessment, (b) explicitly balance the aims of minimizing risk and minimizing travel time, (c) offer a well-hedged solution that is robust under the range of ways the hurricane may evolve, and (d) leverage the substantial value of increasing information (or decreasing degree of uncertainty) over the course of a hurricane event. ☐ The ISE framework was developed by an interdisciplinary research team. The contributions of this dissertation specifically are summarized as follows. First, this dissertation introduces scenario-based hazard trees, a new tool that describes the resolution over time of uncertainty in impacts of a hurricane. The primary input is a scenario ensemble, commonly developed as part of a hurricane forecast. Repeated application of a linear integer program transforms the ensemble into a tree. The hazard trees provide a new dynamic way to characterize how uncertainty changes during the course of a hurricane, potentially useful information for emergency managers. The scenario tree that is an intermediate product of the method is a required input for the multi-stage stochastic programming evacuation model in the ISE framework. ☐ Second, three full-scale case studies of the ISE framework are conducted for the eastern half of North Carolina and Hurricane Isabel (2003) with the aim of improving understanding and management of hurricane evacuations. The first case study demonstrates the major benefits of the ISE framework after calibrating and improving the first version of it. Results suggest the multi-stage stochastic plans can efficiently reduce risk for severe scenarios without increasing travel time for scenarios that cause little impact. Emergency managers can run the framework once to generate adaptive plans that are robust for all possible scenarios. ☐ The second case study compares various evacuation decision approaches, including deterministic, robust, adaptive, and repeated planning. It provides new knowledge in dealing with hurricane development uncertainty and hurricane forecast uncertainty. Results indicate that robust, adaptive, and repeated planning should improve the performance of evacuation plan by reducing both number of people at risk and unnecessary evacuation orders and travel time. The magnitude of benefits depends on characteristics of a particular hurricane. ☐ The third case study analyzes the impacts of incorporating inland flooding on evacuation order recommendations and performance of evacuation plans. Results provide insight into managing hurricane evacuation with inclusion of inland flooding. Inland flooding can bring travel risk to evacuees from coastal zones, and the risk may be even higher than their stay-at-home risk. Therefore, incorporation of inland flooding in evacuation order decision-making may influence order issuance and timing in coastal regions. In addition, evacuations from inland zones can efficiently reduce total risk without substantial increase in total travel time since inland zones are close to safety.
Description
Keywords
Applied sciences, Decision support system, Evacuation, Hurricane, Uncertainty