Optical satellite images of the nearshore water surface offer the possibility to invert water depths and thereby constitute the underlying bathymetry. Depth inversion techniques based on surface wave patterns can handle clear and turbid waters in a variety of global coastal environments. Common depth inversion algorithms require video from shore-based camera stations, UAVs or Xband-radars with a typical duration of minutes and at framerates of 1–2 fps to find relevant wave frequencies. These requirements are often not met by satellite imagery. In this paper, satellite imagery is augmented from a sequence of 12 images of Capbreton, France, collected over a period of ∼1.5 min at a framerate of 1/8 fps by the Pleiades satellite, to a pseudo-video with a framerate of 1 fps. For this purpose, a recently developed method is used, which considers spatial pathways of propagating waves for temporal video reconstruction. The augmented video is subsequently processed with a frequency-based depth inversion algorithm that works largely unsupervised and is openly available. The resulting depth estimates approximate ground truth with an overall depth bias of −0.9 m and an interquartile range of depth errors of 5.1 m. The acquired accuracy is sufficiently high to correctly predict wave heights over the shoreface with a numerical wave model and to find hotspots where wave refraction leads to focusing of wave energy that has potential implications for coastal hazard assessments. A more detailed depth inversion analysis of the nearshore region furthermore demonstrates the possibility to detect sandbars. The combination of image augmentation with a frequency-based depth inversion method shows potential for broad application to temporally sparse satellite imagery and thereby aids in the effort towards globally available coastal bathymetry data.@en

The problem of sandbar migration on the storm timescale is revisited with a 3D wave-resolving hydro-sedimentary model. The latter presents an intermediate approach between expensive wave-resolving two-phase flow models and highly parametrized wave-averaged models. Innovative features include the use of weakly compressible assumptions in the hydrodynamics and morphological acceleration of bed changes to speed up numerical simulations. The model accurately simulates the successive offshore and onshore bar migration observed in a large-scale flume experiment in response to wave forcing representing storm and post-storm (recovery) conditions. The diagnosis of sand transport and the analysis of an ensemble-averaged asymmetric wave cycle reveal the migration mechanisms in each phase. In all cases, sediment resuspension is impacted by breaker-induced turbulence, while sediment transport and bed evolution are primarily the result of the undertow distribution – the breaker-induced seaward undercurrent – across the sandbar. There is also a significant contribution from asymmetric wave-related onshore fluxes, due to greater mobilization and currents during the wave crest period.@en

In this paper, a new approach to model wave‐driven, cross‐shore shoreline change incorporating multiple timescales is introduced. As a base, we use the equilibrium shoreline prediction model ShoreFor that accounts for a single timescale only. High‐resolution shoreline data collected at three distinctly different study sites is used to train the new data‐driven model. In addition to the direct forcing approach used in most models, here two additional terms are introduced: a time-upscaling and a time‐downscaling term. The upscaling term accounts for the persistent effect of short‐term events, such as storms, on the shoreline position. The downscaling term accounts for the effect of long‐term shoreline modulations, caused by, for example, climate variability, on shorter event impacts. The multi‐timescale model shows improvement compared to the original ShoreFor model (a normalized mean square error improvement during validation of 18 to 59%) at the three contrasted sandy beaches. Moreover, it gains insight in the various timescales (storms to inter‐an-nual) and reveals their interactions that cause shoreline change. We find that extreme forcing events have a persistent shoreline impact and cause 57–73% of the shoreline variability at the three sites. Moreover, long‐term shoreline trends affect short‐term forcing event impacts and determine 20– 27% of the shoreline variability.

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A large-scale laboratory experiment was completed to investigate the performance of a dynamic cobble berm revetment designed to provide sustainable coastal protection under wave attack and a rising water level. The experiment demonstrated the inherent stability of the dynamic revetment, which was observed to be reshaped by every wave but retained its overall shape throughout the experiment with almost no loss of material. By comparing with a sand beach case, it was found that the revetment reduced shoreline retreat during an erosive wave condition and reduced runup excursions, thus eliminating erosion landward of the revetment. Overall the experiment provided significant new understanding of dynamic revetments and demonstrated the potential for dynamic revetments to provide low cost, robust coastal protection.@en