Parameterization of Beach and Dune Recovery to Inform Decadal Scale Prediction of Barrier Island Evolution

Advances in deterministic models have facilitated the prediction of sandy beach and barrier island evolution in response to storm events over time scales of hours to days. Empirical data-driven approaches, including probabilistic models, also have demonstrable success using prior observations to make longer-term predictions (decadal and century-scale) of overall trends in parameters (e.g., shoreline position). Despite these advancements, however, the ability to predict evolution of the subaerial beach on more intermediate time (10-50 years) and spatial (O(10s) of meters) scales is limited due to a lack of understanding of, and predictive capability for, evolution between storms. Without the ability to predict the recovery of the system, it is impossible to estimate the antecedent conditions that govern the response to the next storm or estimate cumulative evolution during longer quiescent periods. The focus of this study is analysis of beach recovery using long-term observational data sets collected at Dauphin Island, Alabama, in the northern Gulf of Mexico. The observations include 14 topographic lidar data sets spanning from 1998-2013, including both post-storm and baseline conditions, as well as aerial and satellite imagery taken over the same period. The data are analyzed to quantify changes in subaerial elevation and evolution of the dune and upper beach, and to relate those changes to temporal and spatial variability in environmental conditions (e.g., offshore wave height, local winds, vegetation, etc.). The overarching goal of the project will be to use this analysis to build a parameterized model for beach recovery following storms that can be applied for decadal scale morphological modeling at Dauphin Island and elsewhere in support of coastal zone management.