Controls of local geology and cross-shore/longshore processes on embayed beach shoreline variability

Abstract

Shoreline variability along the 3.6-km long Narrabeen Beach embayment in SE Australia is investigated over a 5-year period. We apply the one-line shoreline change model LX-Shore, which couples longshore and cross-shore processes and can handle complex shoreline planforms, non-erodible emerged headlands and submerged rocky features. The model skilfully reproduces the three dominant modes of shoreline variability, which are by decreasing order of variance: cross-shore migration, rotation, and a third mode possibly related to breathing. Model results confirm previous observations that longshore processes primarily contribute to the rotation and third modes on the timescales of months to seasons, while cross-shore processes control the shoreline migration on shorter timescales from hours (storms) to months. Additional simulations simplifying progressively the bathymetry show how the inherent geology strongly modulates the spatial modes of shoreline variability. The offshore central rocky outcrop is found to limit the rotation. In contrast, the submerged rocky platforms that extend from the headlands enhance the shoreline rotation mode and increase alongshore variability of the cross-shore migration mode, owing to increased alongshore variability in wave exposure. Offshore wave transformation across large-scale submerged rocky features and headland shape are therefore critical to contemporary shoreline dynamics.

16 years of topographic surveys of rip-channelled high-energy meso-macrotidal sandy beach

“…Sandy beaches buffer shores from storm waves and surge. They constantly evolve in response to storm, seasonal, and interannual variations in incident wave conditions 1,2 , anthropogenic forcings [3][4][5] , changes in natural sand supply 6,7 , to morphological adjustment of nearby tidal inlets or estuary mouth 8,9 , with sometimes a profound influence of geological settings 7,[10][11][12][13] . Permanent video stations can infer daily shoreline proxy at reasonably low cost over years/decades 14,15 .…”

Impact of model free parameters and sea‐level rise uncertainties on 20‐years shoreline hindcast: the case of Truc Vert beach (SW France)

“…This generation of RCMs has been applied successfully at many sites where longshore processes have little influence on shoreline variability (e.g. Castelle et al, 2014; Dodet et al, 2019; Ludka et al, 2015; Lemos et al, 2018; Montaño et al (2020); Robinet et al, 2020; Splinter et al, 2014). However, these RCMs rely heavily on a data‐driven approach to search for the best free parameters.…”

Efficient Modeling of Complex Sandy Coastal Evolution at Monthly to Century Time Scales

“…Such applications are already applied in practice and ShorelineS supports this through the use of a fast 2D wave refraction solver. Steps further are to feed back the shoreline changes into the bathymetry used in the wave model, as e.g., in Robinet et al (2018), or to even consider emerged, un-erodible layers due to geological formations, which may potentially be buried by sand but may have a significant influence on shoreline evolution, as in Robinet et al (2020).…”

“…These analyses pointed out the importance of the refraction on the foreshore of shoreline undulations, which generally stabilize the coastline relative to the original HAWI mechanism proposed by Ashton et al (2001). Recently, Robinet et al (2018Robinet et al ( , 2020, starting from the same grid-based one-line approach, extended the concept by coupling it with a 2D wave refraction model and including cross-shore transport. Such models are quite powerful in describing complex coastal shapes but at the cost of requiring complex and relatively timeconsuming codes.…”