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.

在这里，通过将波浪气候和水位的多模型预测与 Alvarez-Cuesta 等人的复杂性降低的海岸线演化模型相结合，获得区域尺度整体海岸线变化预测的方法。(2021) 提出。为了解释气候变化的不确定性，使用了来自全球和区域气候模型的五种不同组合以及两个代表性浓度路径的三个潜在平均海平面上升 (SLR) 轨迹的动态缩小和偏差校正的预测波浪和风暴潮系列强制侵蚀影响模型 IH-LANS 。该方法应用于西班牙地中海沿岸 40 公里高度人类化的海岸线。获得了 2020 年至 2100 年间海岸线演变的 30 小时时间序列，它们中的每一个都与未来对波浪和水位的实现有关。从海岸线时间序列分析，长期和短期过程被解开，产生永久性撤退和海滩面积损失，个体物理过程（远岸、短期跨岸和 SLR）对海岸线变化和非平稳的贡献极端撤退。本文介绍的方法旨在成为评估潜在气候变化风险的有用工具，同时能够评估和确定适应措施的优先级。