2023 CSDMS meeting-026


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Towards a spatially explicit, probabilistic, multidecadal model of coastal barrier change

Ian Reeves, Woods Hole Oceanographic Institution; USGS Woods Hole Massachusetts, United States. ian.reeves@whoi.edu
Chris Sherwood, USGS , United States.
Erika Lentz, USGS , United States.
Andrew Ashton, Woods Hole Oceanographic Institution , United States.

Models of coastal barrier ecomorphodynamic change are valuable tools for understanding and predicting when, where, and how barriers evolve, which can inform decision-making and hazard mitigation. Present ecomorphodynamic models of barrier systems, however, tend to operate over spatiotemporal scales incongruous with effective management practices (i.e., too fine-scale/event-based or too coarse/long-term). In contrast, we are developing a new model capable of simulating ecomorphologic change of undeveloped barrier systems over several kilometers and decades with a 1-by-1 m planform grid and weekly time step. The model couples aeolian dune growth and vegetation dynamics (DUBEVEG), storm erosion of the beach and foredunes (CDM/SBEACH), storm overwash (Barrier3D), and shoreline/shoreface adjustment (LTA14). We parameterize the model with elevation and vegetation data from North Core Banks, NC, focusing on changes caused by Hurricane Florence (2018). Calibrating free parameters using a genetic algorithm, we find good to excellent agreement with observed and simulated elevation change for representative, small (<1 km alongshore) barrier segments. Future work will include testing the model with multidecadal hindcasts of ecomorphodynamic barrier change; running suites of simulations will allow us to better capture and quantify the probabilistic nature of the dynamic response of barriers to the forces driving coastal evolution.