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dc.contributor.authorToimil Silva, Alexandra
dc.contributor.authorLosada Rodríguez, Iñigo 
dc.contributor.authorHinkel, J.
dc.contributor.authorNicholls, R.J.
dc.contributor.otherUniversidad de Cantabriaes_ES
dc.date.accessioned2022-02-24T13:25:36Z
dc.date.available2022-02-24T13:25:36Z
dc.date.issued2021
dc.identifier.issn2212-0963
dc.identifier.otherBIA2017-89401-Res_ES
dc.identifier.urihttp://hdl.handle.net/10902/24053
dc.description.abstractABSTRACT: Adaptation requires planning strategies that consider the combined effect of climatic and non-climatic drivers, which are deeply uncertain. This uncertainty arises from many sources, cascades and accumulates in risk estimates. A prominent trend to incorporate this uncertainty in adaptation planning is through adaptive approaches such as the dynamic adaptive policy pathways (DAPP). We present a quantitative DAPP application for coastal erosion management to increase its utilisation in this field. We adopt an approach in which adaptation objectives and actions have continuous quantitative metrics that evolve over time as conditions change. The approach hinges on an adaptation information system that comprises hazard and impact modelling and systematic monitoring to assess changing risks and adaptation signals in the light of adaptation pathway choices. Using an elaborated case study, we force a shoreline evolution model with waves and storm surges generated by means of stochastic modelling from 2010 to 2100, considering uncertainty in extreme weather events, climate variability and mean sea-level rise. We produce a new type of adaptation pathways map showing a set of 90-year probabilistic trajectories that link changing objectives (e.g., no adaptation, limit risk increase, avoid risk increase) and nourishment placement over time. This DAPP approach could be applied to other domains of climate change adaptation bringing a new perspective in adaptive planning under deep uncertainty.es_ES
dc.description.sponsorshipAlexandra Toimil acknowledges the financial support from the FENIX Project funded by the Government of Cantabria. This research was also funded by the Spanish Government through the grant RISKCOADAPT (BIA2017-89401-R).es_ES
dc.format.extent13 p.es_ES
dc.language.isoenges_ES
dc.publisherElsevieres_ES
dc.rightsAttribution 4.0 International. ©Los autoreses_ES
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.sourceClimate Risk Management 2021, 33, 100342es_ES
dc.subject.otherCoastal erosiones_ES
dc.subject.otherClimate change adaptationes_ES
dc.subject.otherAdaptation pathwayses_ES
dc.subject.otherDynamic adaptive policy pathwayses_ES
dc.subject.otherAdaptation information systemes_ES
dc.subject.otherUncertaintyes_ES
dc.titleUsing quantitative dynamic adaptive policy pathways to manage climate change-induced coastal erosiones_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.relation.publisherVersionhttps://doi.org/10.1016/j.crm.2021.100342es_ES
dc.rights.accessRightsopenAccesses_ES
dc.identifier.DOI10.1016/j.crm.2021.100342
dc.type.versionpublishedVersiones_ES


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Attribution 4.0 International. ©Los autoresExcepto si se señala otra cosa, la licencia del ítem se describe como Attribution 4.0 International. ©Los autores