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An Integrated Scenario Ensemble-Based Framework for Hurricane Evacuation Modeling: Part 2-Hazard Modeling
Journal article   Open access   Peer reviewed

An Integrated Scenario Ensemble-Based Framework for Hurricane Evacuation Modeling: Part 2-Hazard Modeling

Brian Blanton, Kendra Dresback, Brian Colle, Randy Kolar, Humberto Vergara, Yang Hong, Nicholas Leonardo, Rachel Davidson, Linda Nozick and Tricia Wachtendorf
Risk analysis, Vol.40(1), pp.117-133
01/01/2020
DOI: 10.1111/risa.13004
PMID: 29694683
url
https://doi.org/10.1111/risa.13004View
Published (Version of record) Open Access

Abstract

Hurricane track and intensity can change rapidly in unexpected ways, thus making predictions of hurricanes and related hazards uncertain. This inherent uncertainty often translates into suboptimal decision-making outcomes, such as unnecessary evacuation. Representing this uncertainty is thus critical in evacuation planning and related activities. We describe a physics-based hazard modeling approach that (1) dynamically accounts for the physical interactions among hazard components and (2) captures hurricane evolution uncertainty using an ensemble method. This loosely coupled model system provides a framework for probabilistic water inundation and wind speed levels for a new, risk-based approach to evacuation modeling, described in a companion article in this issue. It combines the Weather Research and Forecasting (WRF) meteorological model, the Coupled Routing and Excess STorage (CREST) hydrologic model, and the ADvanced CIRCulation (ADCIRC) storm surge, tide, and wind-wave model to compute inundation levels and wind speeds for an ensemble of hurricane predictions. Perturbations to WRF's initial and boundary conditions and different model physics/parameterizations generate an ensemble of storm solutions, which are then used to drive the coupled hydrologic + hydrodynamic models. Hurricane Isabel (2003) is used as a case study to illustrate the ensemble-based approach. The inundation, river runoff, and wind hazard results are strongly dependent on the accuracy of the mesoscale meteorological simulations, which improves with decreasing lead time to hurricane landfall. The ensemble envelope brackets the observed behavior while providing "best-case" and "worst-case" scenarios for the subsequent risk-based evacuation model.
Life Sciences & Biomedicine Mathematical Methods In Social Sciences Mathematics Mathematics, Interdisciplinary Applications Physical Sciences Public, Environmental & Occupational Health Science & Technology Social Sciences Social Sciences, Mathematical Methods

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