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Surfing Transport of Buoyant Objects Observed in the Nearshore
Summary
Field observations of free-drifting buoys in the nearshore zone documented 3,172 wave-surfing events with a median jump amplitude of 8.3 m, and incorporating a probabilistic surfing parameterization improved prediction of whether objects beached or remained offshore from 76% to 93% accuracy. This nearshore transport model directly advances understanding of how buoyant plastic debris and microplastic particles move toward coastlines, which is essential for predicting beaching patterns and shoreline contamination.
Abstract Free‐drifting buoyant objects, including plastics, marine debris, and organisms, move with the wind, waves, and surface currents. These objects also surf on breaking waves; this process adds to the total transport of the objects and can control beaching. Observations of surfing transport are made using small free‐drifting buoys called microSWIFTs. The drifters are deployed nearshore at the US Army Corps of Engineers Field Research Facility in Duck, NC, USA, as part of the During Nearshore Events Experiment in October 2021. Surfing events are observed in the drift trajectories of the buoys as “jumps” in the time series of cross‐shore position. There are 3,172 surfing events observed, with a median jump amplitude of 8.3 m and a median duration of 2.5 s. These median values are 13 of a characteristic offshore wavelength and 32 of a characteristic offshore wave period, respectively. The median bulk jump speed (jump amplitude/jump duration) is 82 of the linear phase speed for waves in the corresponding jump depth. The buoys' trajectories are simulated using three models of increasing complexity: “Wind‐Only,” “Wind and Waves,” and “Wind, Waves, and Surfing.” The surfing process is represented using a probabilistic parameterization. When surfing is included in the models, the terminal location of the modeled objects (on beach or offshore) is correctly predicted in 93 of cases compared to 76 and 84 for the “Wind‐Only” and “Wind and Waves” models, respectively. Including surfing also significantly improves the accuracy of the time‐to‐beach and alongshore beaching location.