EP23B-0955
Understanding the Dynamic Interactions of Barrier Island Morphology and Hydrodynamic Drivers

Tuesday, 15 December 2015
Poster Hall (Moscone South)
Davina Lisa Passeri, University of Central Florida, Orlando, FL, United States, Nathaniel G Plant, U.S Geological Survey, Coastal and Marine Science Center, Saint Petersburg, FL, United States and Kathryn E.L. Smith, Organization Not Listed, Washington, DC, United States
Abstract:
Coasts are dynamic systems that are continuously transforming over different temporal and spatial scales as a result of geomorphologic and oceanographic drivers. Tropical and extratropical storms have the potential to alter coastlines with a myriad of effects including storm-driven overwash. Barrier islands are examples of coastlines which are especially susceptible to impacts from storms, depending on characteristics such as surge, waves, and the geometry of the island. On the event scale, the effects of overwash processes may result in damage or loss to property, infrastructure and habitat. On the decadal scale, overwash can be considered a continuous process that reshapes barrier morphology, and drives changes in the backshore environment by altering dune elevations and contributing to barrier island migration. Long-term management assessments and planning should account for overwash processes when examining impacts to coastal environments.

This study implements a Bayesian Network to relate barrier island morphology and hydrodynamic drivers to predict event-driven and long-term morphologic change. The network is trained with a variety of data for Assateague Island, MD/VA, including remote sensing and numerical modeling. The network is tested on its ability to predict morphologic variables including ocean-facing shorelines, dunes, overwash deposits and back-barrier shoreline changes. The model provides a better understanding of the interactions between coastal processes that influence the vulnerability of barrier islands, and identifies which processes and timescales can be predicted with statistical skill versus those that must be treated as random processes whose variance must be quantified. This allows for the evaluation of long-term and storm-driven morphologic changes under various scenarios that can be used by coastal managers and policy makers to make more informed decisions regarding monitoring, sustainability and restoration activities.