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Resumen
Study region: The Pampas region is located in the central-east part of Argentina, and is one of the most productive agricultural regions of the world under rainfed conditions. Study focus: This study aims at examining how different Land Surface Models (LSMs) and satellite estimations reproduce daily surface and root zone soil moisture variability over 8 in-situ observation sites. The ability of the LSMs to detect dry and wet events is also [ver mas...]
dc.contributor.authorSpennemann, Pablo C.
dc.contributor.authorFernández-Long, María Elena
dc.contributor.authorGattinoni, Natalia Noemí
dc.contributor.authorCammalleri, Carmelo
dc.contributor.authorNaumann, Gustavo
dc.date.accessioned2020-10-27T19:55:18Z
dc.date.available2020-10-27T19:55:18Z
dc.date.issued2020-08-05
dc.identifier.issn2214-5818
dc.identifier.otherhttps://doi.org/10.1016/j.ejrh.2020.100723
dc.identifier.urihttp://hdl.handle.net/20.500.12123/8138
dc.identifier.urihttps://www.sciencedirect.com/science/article/pii/S221458182030197X
dc.description.abstractStudy region: The Pampas region is located in the central-east part of Argentina, and is one of the most productive agricultural regions of the world under rainfed conditions. Study focus: This study aims at examining how different Land Surface Models (LSMs) and satellite estimations reproduce daily surface and root zone soil moisture variability over 8 in-situ observation sites. The ability of the LSMs to detect dry and wet events is also evaluated. New hydrological insights for the region: The surface and root zone soil moisture of the LSMs and the surface soil moisture of the ESA CCI (European Space Agency Climate Change Initiative, hereafter ESA-SM) show in general a good performance against the in-situ measurements. In particular, the BHOA (Balance Hidrológico Operativo para el Agro) shows the best representation of the soil moisture dynamic range and variability, and the GLDAS (Global Land Data Assimilation System)-Noah, ERA-Interim TESSEL (Tiled ECMWF’s Scheme for Surface Exchanges over Land) and Global Drought Observatory (GDO)-LISFLOOD are able to adequately represent the soil moisture anomalies over the Pampas region. In addition to the LSM results, also the ESASM satellite estimated anomalies proved to be valuable. However, the LSMs and the ESA-SM have difficulties in reproducing the soil moisture frequency distributions. Based on this study, it is clear that accurate forcing data and soil parameters are critical to substantially improve the ability of LSMs to detect dry and wet events.eng
dc.formatapplication/pdfes_AR
dc.language.isoenges_AR
dc.publisherElsevieres_AR
dc.relationThe Inter-American Institute for Global Change Research (IAI) CRN3035, which is supported by the U.S. National Science Foundation (Grant GEO-1128040)es_AR
dc.rightsinfo:eu-repo/semantics/openAccesses_AR
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/
dc.sourceJournal of Hydrology : Regional Studies 31 : 100723 (October 2020)es_AR
dc.subjectSoil Water Contenteng
dc.subjectContenido de Agua en el Sueloes_AR
dc.subjectEvaluationeng
dc.subjectEvaluaciónes_AR
dc.subjectSatelliteseng
dc.subjectSatéliteses_AR
dc.subject.otherLand Surface Modelseng
dc.subject.otherModelos de Superficie Terrestrees_AR
dc.subject.otherEstimationseng
dc.subject.otherEstimacioneses_AR
dc.subject.otherRegión Pampeana
dc.titleSoil moisture evaluation over the Argentine Pampas using models satellite estimations and in - situ measurementses_AR
dc.typeinfo:ar-repo/semantics/artículoes_AR
dc.typeinfo:eu-repo/semantics/articlees_AR
dc.typeinfo:eu-repo/semantics/publishedVersiones_AR
dc.rights.licenseCreative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
dc.description.filFil: Spennemann, P.C. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Servicio Meteorológico Nacional; Argentina Universidad Nacional de Tres de Febrero; Argentinaes_AR
dc.description.filFil: Fernández - Long, M.E. Universidad de Buenos Aires. Facultad de Agronomía; Argentinaes_AR
dc.description.filFil: Gattinoni, Natalia N. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Clima y Agua; Argentinaes_AR
dc.description.filFil: Cammalleri, C. European Commission, Joint Research Centre; Italiaes_AR
dc.description.filFil: Naumann, G. European Commission, Joint Research Centre; Italiaes_AR
dc.subtypecientifico


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