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dc.contributor.authorDerepasko, Diana
dc.contributor.authorWiting, Felix
dc.contributor.authorPeñas Silva, Francisco Jesús
dc.contributor.authorBarquín Ortiz, José 
dc.contributor.authorVolk, Martin
dc.contributor.otherUniversidad de Cantabriaes_ES
dc.date.accessioned2023-10-19T15:24:11Z
dc.date.available2023-10-19T15:24:11Z
dc.date.issued2023
dc.identifier.issn2073-4441
dc.identifier.otherPID2020-114427RJ-I00es_ES
dc.identifier.urihttps://hdl.handle.net/10902/30265
dc.description.abstractThe degree of success of river water diversion planning decisions is affected by uncertain environmental conditions. The adaptive water management framework incorporates this uncertainty at all stages of management. While the most effective form of adaptive management requires experimental comparison of practices, the use of optimization modeling is convenient for conducting exploratory simulations to evaluate the spatiotemporal implications of current water diversion management decisions under future environmental changes. We demonstrate such an explorative modeling approach by assessing river water availability for diversion in a river basin in Northern Spain under two future environmental scenarios that combine climate and land use change. An evolutionary optimization method is applied to identify and reduce trade-offs with Supporting Ecosystem Services linked to environmental flow requirements for relevant local freshwater species. The results show that seasonal shifts and spatial heterogeneity of diversion volumes are the main challenges for the future diversion management of the Pas River. Basin-scale diversion management should take into account the seasonal planning horizon and the setting of tailored diversion targets at the local-level to promote the implementation of adaptive management. The presented assessment can help with strategic placement of diversion points and timing of withdrawals, but it also provides deeper insight into how optimisation can support decision-making in managing water diversion under uncertain future environmental conditions.es_ES
dc.description.sponsorshipThis paper was an output of the Euro-FLOW project and received funding from the European Union’s Horizon 2020 Research and Innovation Programme under the Marie Skłodowska-Curie grant, agreement no. 765553. This publication is also part of the I+D+I project RIFFLE PID2020-114427RJ-I00 funded by MCIN/AEI/10.13039/501100011033es_ES
dc.format.extent21 p.es_ES
dc.language.isoenges_ES
dc.publisherMDPIes_ES
dc.rights© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.es_ES
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.sourceWater, 2023, 15(18), 3289es_ES
dc.subject.otherEnvironmental flowses_ES
dc.subject.otherClimate changees_ES
dc.subject.otherLand cover changees_ES
dc.subject.otherMulti-objective optimizationes_ES
dc.subject.otherBasin-scale assessmentes_ES
dc.subject.otherTrade-off analysises_ES
dc.subject.otherInstream flowes_ES
dc.titleTowards adaptive water management-optimizing river water diversion at the basin scale under future environmental conditionses_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.rights.accessRightsopenAccesses_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/EC/H2020/765553/EU/A EUROpean training and research network for environmental FLOW management in river basins/EUROFLOW/es_ES
dc.identifier.DOI10.3390/w15183289
dc.type.versionpublishedVersiones_ES


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© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.Excepto si se señala otra cosa, la licencia del ítem se describe como © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.