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
- Institución
- Instituto Nacional de Tecnología Agropecuaria
- OAI Identificador
- oai:localhost:20.500.12123/8138
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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)2025-09-29T13:45:03Zoai: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:l2025-09-29 13:45:03.466INTA 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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12.559606 |