Abstract
This article aims to investigate the 3D morpho-sedimentary dynamics of two gravel beaches in relation to hydrodynamic forcing, using a multi-sensor approach. Study sites, namely Etretat and Hautot-sur-Mer, are both located in Normandy, France. Thus, they face similar wave conditions of the English channel's eastern side, with megatidal ranges and channelized wave orientations. However, they differ in gravel size (D50 Etretat = 5.2 cm; D50 Hautot-sur-Mer = 7.0 cm), vertical composition (Etretat is a purely gravel beach, Hautot-sur-Mer is a composite one with a low tide terrace) and wave exposure (Etretat is an embayed beach, oriented 47°N, Hautot-sur-Mer is a semi-open beach, oriented 71°N). Used data include shoreline positions automatically extracted from coastal Video Monitoring Systems (VMS) images between 2018 and 2020, wave data provided by the WaveWatch 3 model, and gravel size maps derived from UAV-imagery at different dates (one in Etretat, three in Hautot-sur-Mer). First, an Empirical Orthogonal Function (EOF) analysis was performed on the shoreline position data to extract the Principal Components (PC) describing mechanisms of morphological changes in the shoreline shape at different elevations (−2 to +3 m in Etretat and + 1 to +3 m in Hautot-sur-Mer). Four mechanisms spread within five PCs were found in Etretat: cross-shore translation (PC1), rollover (PC2), scale/elevation dependent rotation (PC3 and PC4) and breathing (PC5). Four PCs describing three mechanisms were identified in Hautot-sur-Mer: right-centered beach cell rotation (PC1), left-centered beach cell rotation (PC2), large scale rotation (PC3) and rollover (PC4). Interpretation of the PCs were supported by significant correlations with morphological parameters such as average beach width (BW), beach orientation angle (BOA) and beach slope (BS). The main mid-term morphological periods of variability include 2, 3, 5 and 8+ months in Etretat and 2, 3 and 6 months in Hautot-sur-Mer (all parameters included), which essentially corresponds to the variability of the wave energy. Finally, the analysis of surface grain size spatial variability revealed the presence of textural patterns with spatial and temporal variations in sorting and average grain size up to 1 cm in two months.
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