New Methods in Comprehensive Multi-Hazard Resilience Assessment of Urban Coastal Systems

Flooding has become a major global problem as sea-level rise, increased heavy rainfall, population growth, and urbanization all contribute to greater flood risk. Over the past two decades, numerous devastating hurricanes along the coastal United States have caused massive disruption to socio-economic activities, highlighting the need for a comprehensive understanding of flood damage and resiliency at various spatial scales. Flooding is extremely damaging to the communities’ substructure and economy. Low-lying coastal areas are at severe risk for flood hazards, sea-level rise, land depletion, economic loss, property damage, habitat destruction, and threats to human health and safety. The precise assessment of flood damage and structural resiliency is of the utmost importance for coastal communities, mitigating risk from repeated extreme storm events. However, most flood resiliency studies have been criticized for lack of accuracy and failing to depict the relationships among the hydrodynamics, structural characteristics, and community preparedness. This work intends to present an inclusive approach for quantifying community-scale flood damage and structural resiliency. Large-scale coastal flooding has been simulated and validated with semi-coupled storm surge and 2D inundation models. The depth and momentum components of flood flow were integrated with a newly developed multidimensional flood-damage assessment model, which includes the traditional depth–damage relationship as well as building height, age, configuration, and construction material to calculate the resiliency of structures as a function of recovery time, community preparedness, and level of flood-induced damage. The study region experienced flood depths ranging from 4.91 m to 8.06 m from various hurricane categories with 28.69%, 45.62%, and 92.13% damage to properties. The flood damage and resiliency results were presented via geospatial analytics at the property level (i.e., microscale) and aggregated census block group (i.e., macroscale) levels, indicating the developed framework's universal applicability and scalability.