Reprint of: Modelling long-term shoreline evolution in highly anthropized coastal areas. Part 2: Assessing the response to climate change

• Published in: Coastal engineering (Amsterdam) Vol. 169; p. 103985
• Main Authors: Alvarez-Cuesta, M., Toimil, A., Losada, I.J.
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01-10-2021
• Subjects: Climate change; Ensemble estimates; Reduced-complexity model; Shoreline evolution; Reduced-complexity model; Climate change; Ensemble estimates; Shoreline evolution
• ISSN: 0378-3839; 1872-7379
• DOI: 10.1016/j.coastaleng.2021.103985

Here, a methodology to obtain ensemble shoreline change projections at regional scale by combining multi-model projections of wave climate and water levels and the reduced-complexity shoreline evolution model in Alvarez-Cuesta et al. (2021) is presented. In order to account for climate change uncertainty, dynamically downscaled and bias corrected projected waves and storm surge series from five different combinations of global and regional climate models and three potential mean sea-level rise (SLR) trajectories for two representative concentration pathways, are used to force the erosion impact model IH-LANS . The methodology is applied to a 40 km highly anthropized coastal stretch in the Mediterranean coast of Spain. Thirty hourly time series of shoreline evolution between 2020 and 2100 are obtained, each of them linked to one future realization of waves and water levels. From the shoreline time-series analysis, long and short -term processes are unraveled, yielding permanent retreats and beach area losses, contribution of individual physical processes (longshore, short-term cross-shore, and SLR) to shoreline change and non-stationary extreme retreats. The methodology presented herein is intended to be a useful tool for evaluating potential climate change risks while enabling the evaluation and prioritization of adaptation measures.
•An ensemble of end-of-century shoreline positions is obtained at a highly anthropized Mediterranean coastal area.•Waves and water levels from several climate models and emissions scenarios are used to drive a shoreline evolution model.•Results at multiple time scales are unraveled, yielding useful information for coastal planning and adaptation.