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
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/153611
Ver los metadatos del registro completo
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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 Técnicas2025-09-29T10:14:58Zoai: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:34982025-09-29 10:14:58.378CONICET 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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13.070432 |