dc.contributor.author | Álvarez Cuesta, Moisés | |
dc.contributor.author | Toimil Silva, Alexandra | |
dc.contributor.author | Losada Rodríguez, Iñigo | |
dc.contributor.other | Universidad de Cantabria | es_ES |
dc.date.accessioned | 2025-02-14T14:10:59Z | |
dc.date.available | 2025-02-14T14:10:59Z | |
dc.date.issued | 2021-09 | |
dc.identifier.issn | 0378-3839 | |
dc.identifier.issn | 1872-7379 | |
dc.identifier.other | BIA2017-89401-R | es_ES |
dc.identifier.uri | https://hdl.handle.net/10902/35544 | |
dc.description.abstract | 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. | es_ES |
dc.description.sponsorship | M. Álvarez-Cuesta is indebted to the Spanish Ministry of Science and Innovation for the funding provided in the FPI studentship (PRE2018-085009). This work has been also funded by Spanish Ministry of Science and Innovation through the grant RISKOADAPT (BIA2017-89401-R) and the Spanish Ministry for the Ecological Transition and the Demographic Challenge. The authors would like to acknowledge the data provided by the Spanish Ministry for the Ecological Transition and Demographic challenge. | es_ES |
dc.format.extent | 15 p. | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | Elsevier | es_ES |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 International | es_ES |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.source | Coastal Engineering, 2021, 168, 103961 - (REPRINT), 2021, 169, 103985 | es_ES |
dc.subject.other | Shoreline evolution | es_ES |
dc.subject.other | Climate change | es_ES |
dc.subject.other | Reduced-complexity model | es_ES |
dc.subject.other | Ensemble estimates | es_ES |
dc.title | Modelling long-term shoreline evolution in highly anthropized coastal areas. Part 2: Assessing the response to climate change | es_ES |
dc.type | info:eu-repo/semantics/article | es_ES |
dc.relation.publisherVersion | https://doi.org/10.1016/j.coastaleng.2021.103961 | es_ES |
dc.rights.accessRights | openAccess | es_ES |
dc.identifier.DOI | 10.1016/j.coastaleng.2021.103961 | |
dc.type.version | publishedVersion | es_ES |