Storm Surge Risks to Flood Defense Systems and Coastal Communities
Our Nation’s coastal areas face substantial risk from storm surge. Data from modeling efforts can provide crucial information to decision makers to act against these risks, but available models are limited in scope. Current fragility-based models for flood defense systems are primarily focused on a single mode of failure, treat failure assessment as a snapshot in time, and neglect the impact of the performance of flood protection systems on spatio-temporal surge response. Moreover, an accurate conceptualization is lacking regarding how this informational shortfall impairs decision makers in making critical judgments about storm surge risk and infrastructure investment. In order to address these limitations, this research will provide for the development of the next generation in storm surge and fragility models utilizing advanced numerical modeling procedures for hazard and protection infrastructure and will provide for an experimental validation and assessment of the models’ effects on decision makers. These goals will be achieved via development of a novel, dynamically coupled modeling system consisting of hydrodynamic and fragility model components, as well as development and utilization of an approach to human subjects experiments to validate and test the effects of these models on real-time decision making.
The project will generate stochastic finite difference models and utilize machine learning techniques to develop a new class of fragility surfaces that will enhance our understanding of various failure processes. The surge and fragility models will be fully coupled to provide the ability for the surge model to adapt the mesh resolution in response to changing conditions of the flood protection systems resulting in improved forecasting capabilities. The experimental analysis will provide for an assessment of how these modeling capabilities improve real-time decision making; and will inform a broad array of disaster management, risk and decision analysis literatures regarding how risk assessment modeling information should be conveyed to decision makers to minimize hazard risk more broadly. The research will also improve understanding of how decision makers utilize storm risk assessment information to make critical decisions. Ultimately, this research will lead to more informed decisions about catastrophic risk and infrastructure failure e.g. evacuation decisions, search and rescue operations, infrastructure investment, and pre-, during, and post-event planning.
Funding Support: Naional Science Foundation https://www.nsf.gov/awardsearch/showAward?AWD_ID=1563372