Soil moisture evaluation over the Argentine Pampas using models satellite estimations and in - situ measurements

Autores
Spennemann, Pablo C.; Fernández-Long, María Elena; Gattinoni, Natalia Noemí; Cammalleri, Carmelo; Naumann, Gustavo
Año de publicación
2020
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
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 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.
Fil: Spennemann, P.C. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Servicio Meteorológico Nacional; Argentina Universidad Nacional de Tres de Febrero; Argentina
Fil: Fernández - Long, M.E. Universidad de Buenos Aires. Facultad de Agronomía; Argentina
Fil: Gattinoni, Natalia N. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Clima y Agua; Argentina
Fil: Cammalleri, C. European Commission, Joint Research Centre; Italia
Fil: Naumann, G. European Commission, Joint Research Centre; Italia
Fuente
Journal of Hydrology : Regional Studies 31 : 100723 (October 2020)
Materia
Soil Water Content
Evaluation
Satellites
Contenido de Agua en el Suelo
Evaluación
Satélites
Land Surface Models
Estimations
Modelos de Superficie Terrestre
Estimaciones
Región Pampeana
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/4.0/
Repositorio
INTA Digital (INTA)
Institución
Instituto Nacional de Tecnología Agropecuaria
OAI Identificador
oai:localhost:20.500.12123/8138
Acceder
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oai_identifier_str oai:localhost:20.500.12123/8138
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network_name_str INTA Digital (INTA)
spelling Soil moisture evaluation over the Argentine Pampas using models satellite estimations and in - situ measurementsSpennemann, Pablo C.Fernández-Long, María ElenaGattinoni, Natalia NoemíCammalleri, CarmeloNaumann, GustavoSoil Water ContentEvaluationSatellitesContenido de Agua en el SueloEvaluaciónSatélitesLand Surface ModelsEstimationsModelos de Superficie TerrestreEstimacionesRegión PampeanaStudy 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.Fil: Spennemann, P.C. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Servicio Meteorológico Nacional; Argentina Universidad Nacional de Tres de Febrero; ArgentinaFil: Fernández - Long, M.E. Universidad de Buenos Aires. Facultad de Agronomía; ArgentinaFil: Gattinoni, Natalia N. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Clima y Agua; ArgentinaFil: Cammalleri, C. European Commission, Joint Research Centre; ItaliaFil: Naumann, G. European Commission, Joint Research Centre; ItaliaElsevier2020-10-27T19:55:18Z2020-10-27T19:55:18Z2020-08-05info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfhttp://hdl.handle.net/20.500.12123/8138https://www.sciencedirect.com/science/article/pii/S221458182030197X2214-5818https://doi.org/10.1016/j.ejrh.2020.100723Journal of Hydrology : Regional Studies 31 : 100723 (October 2020)reponame:INTA Digital (INTA)instname:Instituto Nacional de Tecnología AgropecuariaengThe Inter-American Institute for Global Change Research (IAI) CRN3035, which is supported by the U.S. National Science Foundation (Grant GEO-1128040)info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)2025-10-23T11:17:24Zoai:localhost:20.500.12123/8138instacron:INTAInstitucionalhttp://repositorio.inta.gob.ar/Organismo científico-tecnológicoNo correspondehttp://repositorio.inta.gob.ar/oai/requesttripaldi.nicolas@inta.gob.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:l2025-10-23 11:17:24.534INTA Digital (INTA) - Instituto Nacional de Tecnología Agropecuariafalse
dc.title.none.fl_str_mv Soil moisture evaluation over the Argentine Pampas using models satellite estimations and in - situ measurements
title Soil moisture evaluation over the Argentine Pampas using models satellite estimations and in - situ measurements
spellingShingle Soil moisture evaluation over the Argentine Pampas using models satellite estimations and in - situ measurements
Spennemann, Pablo C.
Soil Water Content
Evaluation
Satellites
Contenido de Agua en el Suelo
Evaluación
Satélites
Land Surface Models
Estimations
Modelos de Superficie Terrestre
Estimaciones
Región Pampeana
title_short Soil moisture evaluation over the Argentine Pampas using models satellite estimations and in - situ measurements
title_full Soil moisture evaluation over the Argentine Pampas using models satellite estimations and in - situ measurements
title_fullStr Soil moisture evaluation over the Argentine Pampas using models satellite estimations and in - situ measurements
title_full_unstemmed Soil moisture evaluation over the Argentine Pampas using models satellite estimations and in - situ measurements
title_sort Soil moisture evaluation over the Argentine Pampas using models satellite estimations and in - situ measurements
dc.creator.none.fl_str_mv Spennemann, Pablo C.
Fernández-Long, María Elena
Gattinoni, Natalia Noemí
Cammalleri, Carmelo
Naumann, Gustavo
author Spennemann, Pablo C.
author_facet Spennemann, Pablo C.
Fernández-Long, María Elena
Gattinoni, Natalia Noemí
Cammalleri, Carmelo
Naumann, Gustavo
author_role author
author2 Fernández-Long, María Elena
Gattinoni, Natalia Noemí
Cammalleri, Carmelo
Naumann, Gustavo
author2_role author
author
author
author
dc.subject.none.fl_str_mv Soil Water Content
Evaluation
Satellites
Contenido de Agua en el Suelo
Evaluación
Satélites
Land Surface Models
Estimations
Modelos de Superficie Terrestre
Estimaciones
Región Pampeana
topic Soil Water Content
Evaluation
Satellites
Contenido de Agua en el Suelo
Evaluación
Satélites
Land Surface Models
Estimations
Modelos de Superficie Terrestre
Estimaciones
Región Pampeana
dc.description.none.fl_txt_mv 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 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.
Fil: Spennemann, P.C. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Servicio Meteorológico Nacional; Argentina Universidad Nacional de Tres de Febrero; Argentina
Fil: Fernández - Long, M.E. Universidad de Buenos Aires. Facultad de Agronomía; Argentina
Fil: Gattinoni, Natalia N. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Clima y Agua; Argentina
Fil: Cammalleri, C. European Commission, Joint Research Centre; Italia
Fil: Naumann, G. European Commission, Joint Research Centre; Italia
description 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 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.
publishDate 2020
dc.date.none.fl_str_mv 2020-10-27T19:55:18Z
2020-10-27T19:55:18Z
2020-08-05
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/20.500.12123/8138
https://www.sciencedirect.com/science/article/pii/S221458182030197X
2214-5818
https://doi.org/10.1016/j.ejrh.2020.100723
url http://hdl.handle.net/20.500.12123/8138
https://www.sciencedirect.com/science/article/pii/S221458182030197X
https://doi.org/10.1016/j.ejrh.2020.100723
identifier_str_mv 2214-5818
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv The Inter-American Institute for Global Change Research (IAI) CRN3035, which is supported by the U.S. National Science Foundation (Grant GEO-1128040)
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv Journal of Hydrology : Regional Studies 31 : 100723 (October 2020)
reponame:INTA Digital (INTA)
instname:Instituto Nacional de Tecnología Agropecuaria
reponame_str INTA Digital (INTA)
collection INTA Digital (INTA)
instname_str Instituto Nacional de Tecnología Agropecuaria
repository.name.fl_str_mv INTA Digital (INTA) - Instituto Nacional de Tecnología Agropecuaria
repository.mail.fl_str_mv tripaldi.nicolas@inta.gob.ar
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score 12.982451

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