Date of Award
Master of Science
Geography and Environmental Resources
In this study, Hazus-MH (v 2.1 SP 2) flood-loss estimation tools were assessed for their sensitivity to an array of different building and model parameters. The purpose of this study is to help guide users of the Hazus-MH flood-loss modeling tool in the selection of most appropriate model parameters. Six model parameters (square footage of the building, building age, construction types, foundation types, first floor heights, and the number of stories in the building) were assessed for their impacts on flood losses using the Hazus-MH user defined and aggregate flood-loss models. Building stock databases for these analyses were developed using county assessor records from two Illinois counties. A validation assessment was also performed using observed flood-damage survey data collected after the 2011 Mississippi River Flood which inundated the Olive Branch Area in Alexander County, Illinois. This analysis was performed to assess the accuracy of the detailed Hazus-MH User Defined Facility (UDF) flood-loss modeling tool. The foundation types and its associated first floor heights and number of stories in the building were found to substantially impact flood-loss estimates using the Hazus-MH flood-loss modeling tool. The model building parameters square footage, building age and construction type had little or no effect on the flood-loss estimates. The validation assessment reveled Hazus-MH UDF flood-loss modeling tool is capable of providing a reasonable estimate of actual flood losses. The validation assessment showed the modeled results to be within 23% of actual losses. The validation study results attained in this study using the detailed UDF flood-loss modeling tool where more realistic (within 23% of actual losses versus > 50% of actual losses) than previous Hazus-MH flood-loss validation assessments. The flood-loss estimates could be further improved by modifying or choosing a more region specific depth-damage curve, using higher resolution DEM and improving the flood-depth grid by incorporating more detailed flood elevation data or estimates using detailed hydraulic models that better reflects the local inundation conditions.
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