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dc.contributor.author | Beneyto, Carles | es_ES |
dc.contributor.author | Vignes, Gloria | es_ES |
dc.contributor.author | Aranda Domingo, José Ángel | es_ES |
dc.contributor.author | Francés, F. | es_ES |
dc.date.accessioned | 2024-01-10T19:03:40Z | |
dc.date.available | 2024-01-10T19:03:40Z | |
dc.date.issued | 2023-10 | es_ES |
dc.identifier.issn | 2073-4441 | es_ES |
dc.identifier.uri | http://hdl.handle.net/10251/201745 | |
dc.description.abstract | [EN] The combined use of weather generators (WG) and hydrological models (HM) in what is called synthetic continuous simulation (SCS) has become a common practice for carrying out flood studies. However, flood quantile estimations are far from presenting relatively high confidence levels, which mostly relate to the uncertainty of models¿ input data. The main objective of this paper is to assess how different precipitation regimes, climate extremality, and basin hydrological characteristics impact the uncertainty of daily flood quantile estimates obtained by SCS. A Monte Carlo simulation from 18 synthetic populations encompassing all these scenarios was performed, evaluating the uncertainty of the simulated quantiles. Additionally, the uncertainty propagation of the quantile estimates from the WG to the HM was analyzed. General findings show that integrating the regional precipitation quantile (XT,P) in the WG model calibration clearly reduces the uncertainty of flood quantile estimates, especially those near the regional XT,P. Basin size, climate extremality, and the hydrological characteristics of the basin have been proven not to affect flood quantiles¿ uncertainty substantially. Furthermore, it has been found that uncertainty clearly increases with the aridity of the climate and that the HM is not capable of buffering the uncertainty of flood quantiles, but rather increases it. | es_ES |
dc.description.sponsorship | The authors thank AEMET and the UC for the data provided to carry out this work (Spain02 dataset). This work was supported by the Spanish Ministry of Science and Innovation through the research projects TETISCHANGE (RTI2018-093717-B-100) and TETISPREDICT (PID2022-141631OBI00). Funding for the open-access charge has been provided by Universitat Politècnica de València | es_ES |
dc.language | Inglés | es_ES |
dc.publisher | MDPI AG | es_ES |
dc.relation.ispartof | Water | es_ES |
dc.rights | Reconocimiento (by) | es_ES |
dc.subject | Weather generator | es_ES |
dc.subject | Hydrological model | es_ES |
dc.subject | Uncertainty | es_ES |
dc.subject | Monte Carlo simulation | es_ES |
dc.subject | Daily flood quantile | es_ES |
dc.subject.classification | EXPRESION GRAFICA EN LA INGENIERIA | es_ES |
dc.subject.classification | INGENIERIA HIDRAULICA | es_ES |
dc.title | Sample Uncertainty Analysis of Daily Flood Quantiles Using a Weather Generator | es_ES |
dc.type | Artículo | es_ES |
dc.identifier.doi | 10.3390/w15193489 | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/RTI2018-093717-B-I00/ES/MEJORAS DEL CONOCIMIENTO Y DE LAS CAPACIDADES DE MODELIZACION PARA LA PROGNOSIS DE LOS EFECTOS DEL CAMBIO GLOBAL EN UNA CUENCA HIDROLOGICA/ | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/AEI//PID2022-141631OB-I00//MEJORAS EN LA PREDICCION ECOHIDROLOGICA A DIFERENTES ESCALAS ESPACIALES Y CON HORIZONTES DE PREDICCION A CORTO (INUNDACIONES), MEDIO (SEQUIAS) Y LARGO PLAZO (CAMBIO GLOBAL)/ | es_ES |
dc.rights.accessRights | Abierto | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Escuela Técnica Superior de Ingenieros de Caminos, Canales y Puertos - Escola Tècnica Superior d'Enginyers de Camins, Canals i Ports | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Instituto Universitario de Ingeniería del Agua y del Medio Ambiente - Institut Universitari d'Enginyeria de l'Aigua i Medi Ambient | es_ES |
dc.description.bibliographicCitation | Beneyto, C.; Vignes, G.; Aranda Domingo, JÁ.; Francés, F. (2023). Sample Uncertainty Analysis of Daily Flood Quantiles Using a Weather Generator. Water. 15(19):1-16. https://doi.org/10.3390/w15193489 | es_ES |
dc.description.accrualMethod | S | es_ES |
dc.relation.publisherversion | https://doi.org/10.3390/w15193489 | es_ES |
dc.description.upvformatpinicio | 1 | es_ES |
dc.description.upvformatpfin | 16 | es_ES |
dc.type.version | info:eu-repo/semantics/publishedVersion | es_ES |
dc.description.volume | 15 | es_ES |
dc.description.issue | 19 | es_ES |
dc.relation.pasarela | S\500536 | es_ES |
dc.contributor.funder | AGENCIA ESTATAL DE INVESTIGACION | es_ES |