Abstract
<p>Marine litter is one of the main threats for the marine environment, causing significant damage at ecological, economic and social levels. Approximately, 80% of the marine litter comes from land-based sources, mainly from rivers. A significant percentage of this litter reaches the open oceans and the rest are retained inside the estuaries. The mechanisms that favor the marine litter accumulation inside the estuaries are determined by the interactions between the tide, the river flow, the waves, and the wind, as well as by the physical features of the estuary. In addition, tides and waves can contribute to the introduction of litter from marine sources. Therefore, estuaries frequently act as sinks for marine litter. In this study, a methodology to identify the most probable areas of marine litter accumulation inside estuaries is developed. The methodology is based on numerical modeling and statistical analysis and consists of 4 fundamental steps. First, a series of metocean scenarios (tidal conditions, river flow, waves, and wind), statistically representative of the studied estuary, are identified using the clustering algorithm K-means. Second, these conditions are used as forcing and boundary conditions of a hydrodynamic model to obtain the high spatial resolution currents and waves that determine the transport of litter. Third, with these high-resolution drivers, a Lagrangian transport model is fed to generate a database of potential marine litter trajectories from different litter-sources, where each litter-source is carefully selected according to the activity developed in the area. Finally, the statistical analysis of these trajectories allows identifying the most probable areas of marine litter accumulation. The efficacy of this methodology is demonstrated by its application to the Pas estuary (northern coast of Spain) by comparing the numerical results with field data. Results show that the greatest accumulations of marine litter take place in the curves that imply important changes in the direction of the flow, where the probabilities range between 20 and 30%, and that the distance to the litter-sources also plays a fundamental role.</p>
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