The latest advances in remote sensing and satellite technologies have allowed the development of new capabilities in coastal geomorphological analysis. Thanks to satellite-derived shoreline (SDS) analysis using the latest machine learning (ML) segmentation algorithms [6, 1, 2], it is possible to obtain time series of the morphological position of the shoreline from monitoring satellite missions such as Sentinel-2 [7] or PlanetScope [4], with a spatial and temporal resolution that allows one to investigate the effects of the individual wave storms on shoreline changes.

The spatio-temporal resolution of the data makes it possible to compare the response of sandy beaches, in terms of shoreline changes, to different events and a multitude of geological and geomorphological conditions of the sites. In this work, we assessed the contribution of soil loss of river basins to the beach erosion resilience at near-event scale, i.e. its capacity to minimize coastal erosion or to recover after a storm event. After using the CoastSat [6] and CoastSeg [1] Python framework applied to Sentinel-2 data to extract SDSs, a transect analysis with tidal correction was performed using the AVISO+ altimetry dataset [5], validated with tide gauge sensors near sites.

Thanks to the Copernicus Marine Environment Monitoring Services (CMEMS) project, a comprehensive database of hind-cast marine variables is easily accessible; a Peak over Threshold of significant wave height was conducted for each transect to retrieve the main events in the time series. In this way, it was possible to identify the SDS position along the transects before and after each event retrieved. This result was aggregated at beach scale with the average value of transects movement due to the storm events, called ASM (Average Shoreline Movement).

The methodology was applied to a 5-year time period, from 2018 to 2023, on 36 sandy beaches in Southern Sicily (Italy) with same characteristics; in order to characterize the resilience of the beaches in terms of the morphologic response of the shoreline, using ASM values retrieved, we quantified the response to each storm at event scale with the respective shoreline average advancements or retirements. Some beaches have less quantity of movements than others in the 5-year period considered. This behaviour is correlated with the characterization of the upstream basins in terms of soil loss and sediment transport.

A beach that has an upstream basin with a higher erosion annual rate has minor shoreline movements after events; a beach with a low contribution from basins in terms of sediments cannot compensate for short-term erosion and accretion patterns and has a high rate of morphological changing after storms (measured with the root mean square of ASM in the 5-year period). In order to quantify the contribution effect of the upstream basins, we employed the average soil loss with the ”Revised Soil Loss Equation” data provided by Pangos et al. [3] that encompass all European regions. The annual average rate of soil loss of each basin was used to assess the contribution to each beach and the result was a correlation with resilience of adjacent beach resilience to storms in morphological changing of shorelines.

75% of sites had a higher rate of morphological event response and were located near small basins with a low average soil loss rate. 15% of sites have a lower rate of shoreline change in response to events, and these sites are located near large basins or effluents with a high average soil loss rate.

References:[1] Sharon Fitzpatrick, et al. CoastSeg: An accessible and extendable hub forsatellite derived-shoreline (SDS) detection and mapping. Journal of Open Source Software, 9(99):6683, 2024.[2] Jes´us Palomar-V´azquez, et al. Shoreline Analysis and Extraction Tool (SAET): A New Tool for the Automatic Extraction of Satellite-Derived Shorelines with Subpixel Accuracy. Remote Sensing, 15(12):3198, 2023.[3] Panos Panagos, et al. The new assessment of soil loss by water erosion in europe. Environmental Science Policy, 54:438–447, 2015.[4] Planet Labs PBC. Planet application program interface: In space for life on earth, 2018.[5] Detelef Stammer and Anny Cazenave. Satellite Altimetry over Oceans and Land Surfaces. CRC press, Taylor & Francis Group, 2018.[6] Kilian Vos, et al. CoastSat: A Google Earth Engine-enabled Python toolkit to extract shorelines from publicly available satellite imagery. Environmental Modelling & Software, 122:104528, December 2019.[7] Francesco Vuolo, et al. Data service platform for sentinel-2 surface reflectance and value-added products: System
use and examples. Remote Sensing, 8 (938), 2016.