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dc.contributor.authorRisco Sence, Eber
dc.contributor.authorLavado-Casimiro, W.
dc.contributor.authorRau, Pedro
dc.date.accessioned2021-06-30T19:39:52Z
dc.date.available2021-06-30T19:39:52Z
dc.date.issued2020
dc.identifier.citationRisco, E., Lavado, W., and Rau, P. (2020) Snow-Hydrological modeling using remote sensing data in Vilcanota basin, Peru, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11515, https://doi.org/10.5194/egusphere-egu2020-11515es_PE
dc.identifier.urihttps://hdl.handle.net/20.500.12542/1022
dc.description.abstractWater resources availability in the southern Andes of Peru is being affected by glacier and snow retreat. This problem is already perceived in the Vilcanota river basin, where hydro-climatological information is scarce. In this particular mountain context, any water plan represents a great challenge. To cope with these limitations, we propose to assess the space-time consistency of 10 satellite-based precipitation products (CMORPH–CRT v.1, CMORPH–BLD v.1, CHIRP v.2, CHIRPS v.2, GSMaP v.6, GSMaP correction, MSWEP v.2.1, PERSIANN, PERSIANN–CDR, TRMM 3B42) with 25 rain gauge stations in order to select the best product that represents the variability in the Vilcanota basin. For this purpose, through a direct evaluation of sensitivity analysis via the GR4J parsimonious hydrological model over the basin. GSMap v.6, TRMM 3B42 and CHIRPS were selected to represent rainfall spatial variability according with different statistical criteria, such as correlation coefficient (CC), standard deviation (SD), percentage of bias (%B) and centered mean square error (CRMSE). To facilitate the interpretation of statistical results, Taylor's diagram was used to represent the CC statistics, normalized values of SD and CRMSE.es_PE
dc.formatapplication/pdfes_PE
dc.language.isoenges_PE
dc.publisherEuropean Geosciences Uniones_PE
dc.relation.urihttps://meetingorganizer.copernicus.org/EGU2020/EGU2020-11515.htmles_PE
dc.rightsinfo:eu-repo/semantics/openAccesses_PE
dc.rightsAtribución-NoComercial-SinDerivadas 3.0 Estados Unidos de América*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/us/*
dc.sourceRepositorio Institucional - SENAMHIes_PE
dc.sourceServicio Nacional de Meteorología e Hidrología del Perúes_PE
dc.subjectRecursos Hídricoses_PE
dc.subjectGlaciareses_PE
dc.subjectNievees_PE
dc.subjectCuencases_PE
dc.subjectModelos y Simulaciónes_PE
dc.titleSnow-Hydrological modeling using remote sensing data in Vilcanota basines_PE
dc.typeinfo:eu-repo/semantics/conferenceObjectes_PE
dc.identifier.doihttps://doi.org/10.5194/egusphere-egu2020-11515
dc.subject.ocdehttps://purl.org/pe-repo/ocde/ford#1.05.11es_PE
dc.subject.siniavariabilidad climatica - Clima y Eventos Naturales
dc.type.siniatext/libro.presentacion
dc.identifier.urlhttps://hdl.handle.net/20.500.12542/1022
dc.identifier.urlhttps://hdl.handle.net/20.500.12542/1022


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