Affiliation:
1. Department of Civil, Environmental and Ocean Engineering, Stevens Institute of Technology, Hoboken, NJ 07030, USA
Abstract
Nearshore sandbars are common features along sandy coasts. However, identifying sandbars within a beach profile traditionally requires a large historical dataset or subjective input from an observer. Several existing methodologies rely on reference profiles, which is problematic for new study sites with limited data sets and for nourished beaches that have drastic fluctuations in the cross-shore. This novel technique is suitable for beaches where a reference profile does not exist, as it identifies morphological sandbar features by a quantitative automated process. The technique identifies sandbars with a minimum steepness of 2% grade and a minimum height of 0.2 m. The morphological boundaries of sandbars were previously not well-defined, especially the seaward limit of the sandbar, contributing to difficulty in comparing surveys and sandbar morphologies. This technique standardizes the definitions of the bar limits mathematically via standard MATLAB functions, thus removing subjectivity and allowing results to be replicated. Bar identification is focused on the beach profile below the mean high water line, not cross on-shore positions, making the technique appropriate for nourished shorelines as well as those with large seasonal fluctuations. The automated technique was tested on 840 profiles collected near a recently completed beach nourishment project in Long Branch, NJ, USA. Results indicate success in identifying prominent sandbars within the test data set.
Funder
New Jersey Department of Environmental Protection