Forecasting future beach width- A case study along the Florida Atlantic coast

Abstract

Historical cross-shore positions of the shoreline and dune base were used as inputs for a Kalman filter algorithm to forecast the positions of these features in the year 2028. The beach width was also computed as the cross-shore distance between the forecasted 2028 shoreline and dune-base positions. While it does not evaluate the suitability of a nesting beach or identify optimal nesting habitat, the beach width can be used as a proxy for habitat availability. An analysis was conducted along the Florida Atlantic coast with an initial goal of demonstrating a method that combines available data for shoreline and dune positions with a Kalman Filter algorithm developed to predict decadal-scale shoreline evolution and then uses these features to define future beach width. This section of the southeastern United States hosts the largest assemblage of nesting loggerhead sea turtles ( Caretta caretta ) in the world, in addition to other species, and critical habitat is designated as part of the species’ listing package under the Endangered Species Act of 1973 (16 U.S.C. ch. 35 § 1531 et seq) for most of the nesting beaches within the study area. This work introduces an approach to inform ecosystem services assessments using data typically derived for shoreline change and storm vulnerability models.