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dc.contributor.authorÁlvarez Cuesta, Moisés 
dc.contributor.authorToimil Silva, Alexandra
dc.contributor.authorLosada Rodríguez, Iñigo 
dc.contributor.otherUniversidad de Cantabriaes_ES
dc.date.accessioned2025-02-14T14:10:59Z
dc.date.available2025-02-14T14:10:59Z
dc.date.issued2021-09
dc.identifier.issn0378-3839
dc.identifier.issn1872-7379
dc.identifier.otherBIA2017-89401-Res_ES
dc.identifier.urihttps://hdl.handle.net/10902/35544
dc.description.abstractHere, 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.sponsorshipM. 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.extent15 p.es_ES
dc.language.isoenges_ES
dc.publisherElsevieres_ES
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internationales_ES
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.sourceCoastal Engineering, 2021, 168, 103961 - (REPRINT), 2021, 169, 103985es_ES
dc.subject.otherShoreline evolutiones_ES
dc.subject.otherClimate changees_ES
dc.subject.otherReduced-complexity modeles_ES
dc.subject.otherEnsemble estimateses_ES
dc.titleModelling long-term shoreline evolution in highly anthropized coastal areas. Part 2: Assessing the response to climate changees_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.relation.publisherVersionhttps://doi.org/10.1016/j.coastaleng.2021.103961es_ES
dc.rights.accessRightsopenAccesses_ES
dc.identifier.DOI10.1016/j.coastaleng.2021.103961
dc.type.versionpublishedVersiones_ES


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Attribution-NonCommercial-NoDerivatives 4.0 InternationalExcepto si se señala otra cosa, la licencia del ítem se describe como Attribution-NonCommercial-NoDerivatives 4.0 International