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dc.contributor.authorCenobio Cruz, Omar
dc.contributor.authorQuintana Seguí, Pere
dc.contributor.authorBarella Ortiz, Anaïs
dc.contributor.authorZabaleta Lopetegui, Ane
dc.contributor.authorGarrote, Luis
dc.contributor.authorClavera Gispert, Roger
dc.contributor.authorHabets, Florence
dc.contributor.authorBeguería-Portugués, S.
dc.date.accessioned2023-06-29T15:42:30Z
dc.date.available2023-06-29T15:42:30Z
dc.date.issued2023-01
dc.identifier.citationJournal of Hydrology X 18 : (2023) // Article ID 100147es_ES
dc.identifier.issn2589-9155
dc.identifier.urihttp://hdl.handle.net/10810/61803
dc.description.abstractThe physically-based, spatially-distributed hydrometeorological model SASER, which is based on the SURFEX LSM, is used to model the hydrological cycle in several domains in Spain and southern France. In this study, the modeled streamflows are validated in a domain centered on the Pyrenees mountain range and which includes all the surrounding river basins, including the Ebro and the Adour-Garonne, with a spatial resolution of 2.5 km. Low flows were found to be poorly simulated by the model. We present an improvement of the SASER modeling chain, which introduces a conceptual reservoir, to enhance the representation of the slow component (drainage) in the hydrological response. The reservoir introduces two new empirical parameters. First, the parameters of the conceptual reservoir model were determined on a catchment-by-catchment basis, calibrating against daily observed data from 53 hydrological stations representing near-natural conditions (local calibration). The results show, on the median value, an improvement (ΔKGE of 0.11) with respect to the reference simulation. Furthermore, the relative bias of two low-flow indices were calculated and reported a clear improvement. Secondly, a regionalization approach was used, which links physiographic information with reservoir parameters through linear equations. A genetic algorithm was used to optimize the equation coefficients through the median daily KGE. Cross-validation was used to test the regionalization approach. The median KGE improved from 0.60 (default simulation) to 0.67 (ΔKGE = 0.07) after regionalization and execution of the routing scheme, and 79 % of independent catchments showed improvement. The model with regionalized parameters had a performance, in KGE terms, very close to that of the model with locally calibrated parameters. The key benefit if the regionalization is that allow us to determine the new empirical parameter of the conceptual reservoir in basins where calibration is not possible (ungauged or human-influenced basins).es_ES
dc.description.sponsorshipThis work was partially funded by the HUMID project (CGL2017-85687-R, AEI/FEDER, UE), the predoctoral grant PRE2018-085027 (AEI/FSE), the PIRAGUA project (EFA210/16-PIRAGUA, INTERREG V-A España-Francia-Andorra POCTEFA2014-2020) and the IDEWA project (PRIMA PCI2020-112043/AEI/ 10.13039/501100011033).es_ES
dc.language.isoenges_ES
dc.publisherElsevieres_ES
dc.relationinfo:eu-repo/grantAgreement/MINECO/CGL2017-85687-Res_ES
dc.rightsinfo:eu-repo/semantics/openAccesses_ES
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/*
dc.subjecthydrologyes_ES
dc.subjectland-surface modeles_ES
dc.subjectdistributed modelinges_ES
dc.subjectlow flowses_ES
dc.subjectparameter regionalizationes_ES
dc.subjectgenetic algorithmes_ES
dc.titleImprovement of low flows simulation in the SASER hydrological modeling chaines_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.rights.holder© 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by- nc-nd/4.0/).es_ES
dc.rights.holderAtribución-NoComercial-SinDerivadas 3.0 España*
dc.relation.publisherversionhttps://www.sciencedirect.com/science/article/pii/S2589915522000293es_ES
dc.identifier.doi10.1016/j.hydroa.2022.100147
dc.departamentoesDidáctica de la Matemática y de las Ciencias Experimentaleses_ES
dc.departamentoeuMatematikaren eta zientzia esperimentalen didaktikaes_ES


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© 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-
nc-nd/4.0/).
Except where otherwise noted, this item's license is described as © 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by- nc-nd/4.0/).