期刊
COASTAL ENGINEERING
卷 168, 期 -, 页码 -出版社
ELSEVIER
DOI: 10.1016/j.coastaleng.2021.103961
关键词
Shoreline evolution; Climate change; Reduced-complexity model; Ensemble estimates
资金
- Spanish Ministry of Science and Innovation [PRE2018-085009]
- Spanish Ministry of Science and Innovation through the grant RISKOADAPT [BIA2017-89401-R]
- Spanish Ministry for the Ecological Transition and the Demographic Challenge
A methodology combining multiple model projections and a simplified shoreline evolution model is used to predict coastal changes in a highly anthropized area along the Mediterranean coast of Spain. By analyzing time series of shoreline evolution, both long-term and short-term processes are revealed, providing insights into different physical contributions to shoreline change and extreme retreat scenarios.
Here, a methodology to obtain ensemble shoreline change projections at regional scale by combining multimodel 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.
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