Category 5 Hurricane Michael made landfall near Mexico Beach, Florida on October 9, 2018, with measured high water marks (HWMs) reaching 7.2 m NAVD88. The town itself received great damage, with many areas destroyed down to the foundations. In this study, we document the storm and its effects on the greater Mexico Beach area: hazard, structural damage, and their relationships. Wave and surge damage was nearly total for low-lying properties, but damage decreased greatly with increasing elevation. Major wave and surge damage was noted in Federal Emergency Management Agency (FEMA) X zones, which are out of the 100-year floodplain, and it is suggested that the 100-year storm is a deficient measure for categorizing flood risk.

Breaching or overtopping of coastal dunes is associated with greater upland damages. Reliable tools are needed to efficiently assess the likelihood of dune erosion during storm events. Existing methods rely on numerical modeling (extensive investment) or insufficiently parameterize the system. To fill this gap, a fragility curve model using a newly developed dune Engineering Demand Parameter (EDP) is introduced. Conceptually, the EDP is similar to the Shield’s parameter in that it represents the ratio of mobilizing terms to stabilizing terms. Physically, the EDP is a measure of storm intensity over the dune’s resilience. To highlight potential applications, the proposed EDP fragility curve models are fit to a spatially and temporally robust dataset and used to predict dune response subjected to varying storm intensities including both extratropical and tropical storm. This approach allows for the probabilistic prediction of dune impacts through an innovative, computationally efficient model. Several different forms of the EDP are tested to determine the best schematization of the dune resilience. The final recommended EDP is the Peak Erosion Intensity (PEI) raised to the fourth power over the product of the dune volume and berm-width squared. Including both storm intensity and resilience terms in the EDP enables comparison of different beach configurations in different storm events fulfilling a need existing vulnerability assessors cannot currently account for directly.

A comprehensive case study of Keansburg Inlet (New Jersey, USA) is presented with the objective of evaluating inlet management alternatives and assessing the influence of an operational flood gate on channel shoaling. The goal of the research is determining the most effective strategy for minimizing the frequency of maintenance dredging. This study compares the effectiveness of (1) traditional structural solutions; (2) modified dredging templates; and (3) assesses the influence of the flood gate operations during conditions representative of a typical year. Alternative analysis is completed using a coupled hydrodynamic–wave model (Delft3D-Flexible Mesh (FM)) with Real Time Control to simulate morphological changes. The model was calibrated and evaluated using collected field data. Water levels are reproduced within 6% of the spring tide range with lag times less than 20 min. The model results and observations suggest sediment transport is dominated by wave action with pronounced variations in dominant wave direction. The results indicate that changes to the operational dredging, or what the authors have termed broadly as “adaptive dredging techniques”, appear to deliver the most promising improvement. Model results suggest that the current operational procedures of the flood gate do not significantly alter the channel infilling rates and patterns during typical (i.e., non-extreme event) conditions.

Hurricane Sandy (2012) resulted in historic losses to the beach and dune system in many parts of New Jersey, leaving inland structures susceptible to wave and surge-induced damages. To defend against future threats, the state, in conjunction with the US Army Corps of Engineers, has pursued a statewide system of engineered beaches comprised of a dune paired with a beach nourishment. Currently in the state there is much debate over the degree of protection these projects currently offer, and how this may change in the future due to climate change. Process-based models can be used to try to answer these questions; however, as the number of test cases increase the computational costs may become prohibitive. Here, a data-driven modeling approach is used to assess the variability in the vulnerability of the beach-dune system in New Jersey to a range of storms. Inputs to the model include storm intensity as characterized by the Storm Erosion Index (SEI) (Miller and Livermont 2008) and parameterized pre-storm morphology. The resulting classification tree ensemble has been shown to accurately predict dune volume loss (as a percent) due to historical storms (Lemke and Miller, 2021). Here, the model is applied to further investigate how changes to beach-dune system and sea level rise affect the probability of dune impact.

A comprehensive case study of the coastal processes for Fortescue Inlet (New Jersey, USA) is presented with the objective of minimizing maintenance dredging of the navigational channel. This study compares the effectiveness of both traditional sedimentation control structures and modified dredging templates, including construction of a new jetty, modification of the length and orientation of an existing jetty, and the use of upland and offshore deposition basins. The alternatives were analyzed using Deflt3D Flexible Mesh. The results indicate that sediment transport near Fortescue Inlet is dominated by wave action with pronounced seasonal variations in wave direction. The site exhibits relatively shallow depths above the depth of closure and pronounced offshore bars. Consequently, much of the sediment transport occurs well offshore (approximately 300 m offshore) and beyond the existing jetty. The results indicate that structural modifications (i.e., relocation or lengthening) of the existing jetty do not improve the sedimentation rate within the channel. Instead, use of offshore deposition basins delivers the most promising improvement, with potential cost savings over 10% over existing strategies.