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

Autores
Spennemann, Pablo Cristian; Fernández Long, María Elena; Gattinoni, Natalia Noemi; Cammalleri, C.; 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 ESA-SM 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, Pablo Cristian. Ministerio de Defensa. Secretaria de Planeamiento. Servicio Meteorológico Nacional. Servicio Metereológico Nacional (sede Dorrego).; Argentina. Universidad Nacional de Tres de Febrero; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Fernández Long, María Elena. Universidad de Buenos Aires. Facultad de Agronomía; Argentina
Fil: Gattinoni, Natalia Noemi. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación de Recursos Naturales. Instituto de Clima y Agua; Argentina
Fil: Cammalleri, C.. Istituto Superiore Per la Protezione E la Ricerca Ambientale (ispra); Italia
Fil: Naumann, Gustavo. Istituto Superiore Per la Protezione E la Ricerca Ambientale (ispra); Italia
Materia
EVALUATION
LAND SURFACE MODELS
SATELLITE ESTIMATIONS
SOIL MOISTURE
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/153611
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/153611
network_acronym_str CONICETDig
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network_name_str CONICET Digital (CONICET)
spelling Soil moisture evaluation over the Argentine Pampas using models, satellite estimations and in-situ measurementsSpennemann, Pablo CristianFernández Long, María ElenaGattinoni, Natalia NoemiCammalleri, C.Naumann, GustavoEVALUATIONLAND SURFACE MODELSSATELLITE ESTIMATIONSSOIL MOISTUREhttps://purl.org/becyt/ford/1.5https://purl.org/becyt/ford/1Study 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 ESA-SM 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, Pablo Cristian. Ministerio de Defensa. Secretaria de Planeamiento. Servicio Meteorológico Nacional. Servicio Metereológico Nacional (sede Dorrego).; Argentina. Universidad Nacional de Tres de Febrero; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Fernández Long, María Elena. Universidad de Buenos Aires. Facultad de Agronomía; ArgentinaFil: Gattinoni, Natalia Noemi. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación de Recursos Naturales. Instituto de Clima y Agua; ArgentinaFil: Cammalleri, C.. Istituto Superiore Per la Protezione E la Ricerca Ambientale (ispra); ItaliaFil: Naumann, Gustavo. Istituto Superiore Per la Protezione E la Ricerca Ambientale (ispra); ItaliaElsevier Science2020-10info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/153611Spennemann, Pablo Cristian; Fernández Long, María Elena; Gattinoni, Natalia Noemi; Cammalleri, C.; Naumann, Gustavo; Soil moisture evaluation over the Argentine Pampas using models, satellite estimations and in-situ measurements; Elsevier Science; Journal of Hydrology: Regional Studies; 31; 10-2020; 1-182214-5818CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S221458182030197X?via%3Dihubinfo:eu-repo/semantics/altIdentifier/doi/10.1016/j.ejrh.2020.100723info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-22T11:45:12Zoai:ri.conicet.gov.ar:11336/153611instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-10-22 11:45:13.137CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
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 Cristian
EVALUATION
LAND SURFACE MODELS
SATELLITE ESTIMATIONS
SOIL MOISTURE
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 Cristian
Fernández Long, María Elena
Gattinoni, Natalia Noemi
Cammalleri, C.
Naumann, Gustavo
author Spennemann, Pablo Cristian
author_facet Spennemann, Pablo Cristian
Fernández Long, María Elena
Gattinoni, Natalia Noemi
Cammalleri, C.
Naumann, Gustavo
author_role author
author2 Fernández Long, María Elena
Gattinoni, Natalia Noemi
Cammalleri, C.
Naumann, Gustavo
author2_role author
author
author
author
dc.subject.none.fl_str_mv EVALUATION
LAND SURFACE MODELS
SATELLITE ESTIMATIONS
SOIL MOISTURE
topic EVALUATION
LAND SURFACE MODELS
SATELLITE ESTIMATIONS
SOIL MOISTURE
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.5
https://purl.org/becyt/ford/1
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 ESA-SM 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, Pablo Cristian. Ministerio de Defensa. Secretaria de Planeamiento. Servicio Meteorológico Nacional. Servicio Metereológico Nacional (sede Dorrego).; Argentina. Universidad Nacional de Tres de Febrero; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Fernández Long, María Elena. Universidad de Buenos Aires. Facultad de Agronomía; Argentina
Fil: Gattinoni, Natalia Noemi. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación de Recursos Naturales. Instituto de Clima y Agua; Argentina
Fil: Cammalleri, C.. Istituto Superiore Per la Protezione E la Ricerca Ambientale (ispra); Italia
Fil: Naumann, Gustavo. Istituto Superiore Per la Protezione E la Ricerca Ambientale (ispra); 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 ESA-SM 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
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/11336/153611
Spennemann, Pablo Cristian; Fernández Long, María Elena; Gattinoni, Natalia Noemi; Cammalleri, C.; Naumann, Gustavo; Soil moisture evaluation over the Argentine Pampas using models, satellite estimations and in-situ measurements; Elsevier Science; Journal of Hydrology: Regional Studies; 31; 10-2020; 1-18
2214-5818
CONICET Digital
CONICET
url http://hdl.handle.net/11336/153611
identifier_str_mv Spennemann, Pablo Cristian; Fernández Long, María Elena; Gattinoni, Natalia Noemi; Cammalleri, C.; Naumann, Gustavo; Soil moisture evaluation over the Argentine Pampas using models, satellite estimations and in-situ measurements; Elsevier Science; Journal of Hydrology: Regional Studies; 31; 10-2020; 1-18
2214-5818
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S221458182030197X?via%3Dihub
info:eu-repo/semantics/altIdentifier/doi/10.1016/j.ejrh.2020.100723
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Elsevier Science
publisher.none.fl_str_mv Elsevier Science
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 12.982451

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