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High-resolution multi-hazard approach to quantify hurricane-induced risk for coastal and inland communities




Nofal, Omar M., author
van de Lindt, John W., advisor
Cutler, Harvey, committee member
Mahmoud, Hussam N., committee member
Guo , Yanlin, committee member

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Hurricanes are devastating natural hazards that often cause damage to coastal and in-land communities as a result of their loadings which include storm surge, waves, wind, and rainfall and riverine flooding, often in combination. Modeling these hazards individually and their effects on buildings is a complex process in that each loading component within the hazard behaves differently affecting either the building envelope, the structural system, or the interior contents. For coastal communities, realistic modeling of hurricane effects requires a multi-hazard approach that considers the combined effects of wind, surge, and waves. Previous studies have focused primarily on modeling these hazards individually with less focus on the multi-hazard impact on the whole building system made up of the combination of structure and its interior contents. For inland communities, high-resolution hydrologic and hydrodynamic models are required to develop high-fidelity flood hazard maps that account for the different hazard characteristics (e.g., flood depth, velocity, duration, etc.). The current flood damage assessment standards are still using stage-damage functions to account for flood damage to buildings. These functions include inherent uncertainties in the damage assessment with significant limitations on their applications. Additionally, the analysis resolution used in these previous studies did not allow hurricane risk assessment through at the building component level (e.g., interior content, structural, and non-structural components). To address these research gaps, a high-resolution flood risk model was developed for inland communities using robust probabilistic flood fragility functions developed for a portfolio of 15 building archetypes that can model the flood vulnerability at the community-level. For coastal communities, a regional-level multi-hazard hurricane risk analysis methodology is proposed to account for the combined impacts of wind-surge-wave loadings driven by hurricanes for both the building system and its interior contents. Fragility functions are used to describe building vulnerability to the multiple loadings driven by hurricanes, and a new convolutional vulnerability approach was developed to combine wind and wave/surge fragilities. The models developed in this dissertation were included in an open-source Interdependent Networked Community Resilience Modeling Environment (IN-CORE) to allow researchers/users to systematically use these models in different types of engineering, social, and economic analyses. The analysis resolution used in the hazard, exposure, and vulnerability models allowed investigation of different levels of mitigation measures including component-, building-, and community-level mitigation strategies. The proposed hurricane risk models for coastal and in-land communities were then applied to a number of case studies to demonstrate the ability of the developed methods to predict damage at the building level across a large spatial domain of small and large communities. The main contribution of these efforts is the development of generalized fragility-based flood vulnerability functions that were applied to a suit of building archetypes and are extendable to be used for other buildings/facilities. These fragilities were then combined with another suite of existing wind fragilities and other storm surge-wave fragility functions to account for the impact of the hurricane-induced hazards on coastal communities. These models enable a better understanding of the damages caused by hurricanes for coastal and in-land communities, thereby setting initial post-impact conditions for community resilience assessment and investigation of recovery policy alternatives.


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flood damage
mitigation analysis
wind damage analysis
fragility analysis
damage analysis
surge-wave damage analysis


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