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dc.contributor.authorJato Espino, Daniel 
dc.contributor.authorSillanpää, Nora
dc.contributor.authorCharlesworth, Susanne M.
dc.contributor.authorRodríguez Hernández, Jorge 
dc.contributor.otherUniversidad de Cantabriaes_ES
dc.date.accessioned2017-08-08T15:56:13Z
dc.date.available2018-06-08T02:45:09Z
dc.date.issued2017-06-07
dc.identifier.issn1364-8152
dc.identifier.issn1873-6726
dc.identifier.otherRHIVU Ref. BIA2012-32463 ; SUPRIS-SUReS (Ref. BIA2015-65240-C2-1-R MINECO/FEDER, UE)es_ES
dc.identifier.urihttp://hdl.handle.net/10902/11548
dc.description.abstractUrban drainage is being affected by Climate Change, whose effects are likely to alter the intensity of rainfall events and result in variations in peak discharges and runoff volumes which stationary-based designs might not be capable of dealing with. Therefore, there is a need to have an accurate and reliable means to model the response of urban catchments under extreme precipitation events produced by Climate Change. This research aimed at optimizing the stormwater modelling of urban catchments using Design of Experiments (DOE), in order to identify the parameters that most influenced their discharge and simulate their response to severe storms events projected for Representative Concentration Pathways (RCPs) using a statistics-based Climate Change methodology. The application of this approach to an urban catchment located in Espoo (southern Finland) demonstrated its capability to optimize the calibration of stormwater simulations and provide robust models for the prediction of extreme precipitation under Climate Change.es_ES
dc.description.sponsorshipThis paper was possible thanks to the research projects RHIVU (Ref. BIA2012-32463) and SUPRIS-SUReS (Ref. BIA 2015-65240-C2-1-R MINECO/FEDER, UE), financed by the Spanish Ministry of Economy and Competitiveness with funds from the State General Budget (PGE) and the European Regional Development Fund (ERDF). The authors wish to express their gratitude to all the entities that provided the data necessary to develop this research: Helsinki Region Environmental Services Authority HSY, Map Service of Espoo, National Land Survey of Finland, Geological Survey of Finland, EURO-CORDEX and European Climate Assessment & Dataset.es_ES
dc.format.extent15 p.es_ES
dc.language.isoenges_ES
dc.publisherElsevier Ltdes_ES
dc.rightsAtribución-NoComercial-SinDerivadas 3.0 Españaes_ES
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/*
dc.sourceEnvironmental Modelling and Software (2017) 1-15es_ES
dc.titleA simulation-optimization methodology to model urban catchments under non-stationary extreme rainfall eventses_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.relation.publisherVersionhttps://doi.org/10.1016/j.envsoft.2017.05.008es_ES
dc.rights.accessRightsopenAccesses_ES
dc.identifier.DOI10.1016/j.envsoft.2017.05.008
dc.type.versionacceptedVersiones_ES


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Atribución-NoComercial-SinDerivadas 3.0 EspañaExcept where otherwise noted, this item's license is described as Atribución-NoComercial-SinDerivadas 3.0 España