The added-value of remotely-sensed soil moisture data for agricultural drought detection in Argentina

Autores
Salvia, Maria Mercedes; Sanchez, Nilda; Piles, María; Ruscica, Romina; González Zamora, Ángel; Roitberg, Esteban Gabriel; Martinez Fernandez, Jose
Año de publicación
2021
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
In countries where the economy relies mostly on agricultural-livestock activities, such as Argentina, droughts cause significant economic losses. Currently, the most-used drought indices by the Argentinian National Meteorological and Hydrological Services are based on field precipitation data, such as the standardized precipitation index (SPI) and the standardized precipitation evapotranspiration index (SPEI). In this article, we explored the performance of the satellite-based soil moisture agricultural drought index (SMADI) for agricultural drought detection in Argentina during 2010-2015, and compared it with the one from the standardized soil moisture anomalies (SSMA), SPI and SPEI (at one-month and three-month temporal scales), using the Agricultural Ministry's drought emergency database as a benchmark. The performances were analyzed in terms of the suitability of each index to be included in an early warning system for agricultural droughts, including true positive rate (TPR), and both false positive and false negative rates. In our experiments, SMADI showed the best overall performance, with the highest TPR and F1-score, and the second best false positive rate (FPR), positive predictive value, and overall accuracy. SMADI also showed the largest difference between TPR and FPR. SSMA showed the lowest FPR, but also the lowest TPR, making it not useful for an alert system. Furthermore, field precipitation-based indices, yet simple and widely used, showed not to be suitable indicators for detection of agricultural drought for Argentina, neither in the one-month nor in the three-month scale.
Fil: Salvia, Maria Mercedes. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Astronomía y Física del Espacio. - Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Astronomía y Física del Espacio; Argentina
Fil: Sanchez, Nilda. Universidad de Salamanca; España
Fil: Piles, María. Universidad de Valencia; España
Fil: Ruscica, Romina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Centro de Investigaciones del Mar y la Atmósfera. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Investigaciones del Mar y la Atmósfera; Argentina. Instituto Franco-Argentino sobre Estudios del Clima y sus Impactos; Argentina
Fil: González Zamora, Ángel. Universidad de Salamanca; España
Fil: Roitberg, Esteban Gabriel. Consejo Nacional de Investigaciónes Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Astronomía y Física del Espacio. - Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Astronomía y Física del Espacio; Argentina
Fil: Martinez Fernandez, Jose. Universidad de Salamanca; España
Materia
AGRICULTURAL DROUGHT DETECTION
ARGENTINA
SOIL MOISTURE AGRICULTURAL DROUGHT INDEX (SMADI)
STANDARDIZED PRECIPITATION EVAPOTRANSPIRATION INDEX (SPEI)
STANDARDIZED PRECIPITATION INDEX (SPI)
STANDARDIZED SOIL MOISTURE ANOMALIES (SSMA)
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:11336/163464
Acceder
id CONICETDig_01aeff674eda41ab79ed7e191ad760b6
oai_identifier_str oai:ri.conicet.gov.ar:11336/163464
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling The added-value of remotely-sensed soil moisture data for agricultural drought detection in ArgentinaSalvia, Maria MercedesSanchez, NildaPiles, MaríaRuscica, RominaGonzález Zamora, ÁngelRoitberg, Esteban GabrielMartinez Fernandez, JoseAGRICULTURAL DROUGHT DETECTIONARGENTINASOIL MOISTURE AGRICULTURAL DROUGHT INDEX (SMADI)STANDARDIZED PRECIPITATION EVAPOTRANSPIRATION INDEX (SPEI)STANDARDIZED PRECIPITATION INDEX (SPI)STANDARDIZED SOIL MOISTURE ANOMALIES (SSMA)https://purl.org/becyt/ford/1.5https://purl.org/becyt/ford/1In countries where the economy relies mostly on agricultural-livestock activities, such as Argentina, droughts cause significant economic losses. Currently, the most-used drought indices by the Argentinian National Meteorological and Hydrological Services are based on field precipitation data, such as the standardized precipitation index (SPI) and the standardized precipitation evapotranspiration index (SPEI). In this article, we explored the performance of the satellite-based soil moisture agricultural drought index (SMADI) for agricultural drought detection in Argentina during 2010-2015, and compared it with the one from the standardized soil moisture anomalies (SSMA), SPI and SPEI (at one-month and three-month temporal scales), using the Agricultural Ministry's drought emergency database as a benchmark. The performances were analyzed in terms of the suitability of each index to be included in an early warning system for agricultural droughts, including true positive rate (TPR), and both false positive and false negative rates. In our experiments, SMADI showed the best overall performance, with the highest TPR and F1-score, and the second best false positive rate (FPR), positive predictive value, and overall accuracy. SMADI also showed the largest difference between TPR and FPR. SSMA showed the lowest FPR, but also the lowest TPR, making it not useful for an alert system. Furthermore, field precipitation-based indices, yet simple and widely used, showed not to be suitable indicators for detection of agricultural drought for Argentina, neither in the one-month nor in the three-month scale.Fil: Salvia, Maria Mercedes. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Astronomía y Física del Espacio. - Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Astronomía y Física del Espacio; ArgentinaFil: Sanchez, Nilda. Universidad de Salamanca; EspañaFil: Piles, María. Universidad de Valencia; EspañaFil: Ruscica, Romina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Centro de Investigaciones del Mar y la Atmósfera. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Investigaciones del Mar y la Atmósfera; Argentina. Instituto Franco-Argentino sobre Estudios del Clima y sus Impactos; ArgentinaFil: González Zamora, Ángel. Universidad de Salamanca; EspañaFil: Roitberg, Esteban Gabriel. Consejo Nacional de Investigaciónes Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Astronomía y Física del Espacio. - Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Astronomía y Física del Espacio; ArgentinaFil: Martinez Fernandez, Jose. Universidad de Salamanca; EspañaInstitute of Electrical and Electronics Engineers2021-05info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/163464Salvia, Maria Mercedes; Sanchez, Nilda; Piles, María; Ruscica, Romina; González Zamora, Ángel; et al.; The added-value of remotely-sensed soil moisture data for agricultural drought detection in Argentina; Institute of Electrical and Electronics Engineers; IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing; 14; 5-2021; 6487-65001939-1404CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://ieeexplore.ieee.org/document/9444130info:eu-repo/semantics/altIdentifier/doi/10.1109/JSTARS.2021.3084849info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-29T12:10:37Zoai:ri.conicet.gov.ar:11336/163464instacron: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:34982025-10-29 12:10:37.553CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv The added-value of remotely-sensed soil moisture data for agricultural drought detection in Argentina
title The added-value of remotely-sensed soil moisture data for agricultural drought detection in Argentina
spellingShingle The added-value of remotely-sensed soil moisture data for agricultural drought detection in Argentina
Salvia, Maria Mercedes
AGRICULTURAL DROUGHT DETECTION
ARGENTINA
SOIL MOISTURE AGRICULTURAL DROUGHT INDEX (SMADI)
STANDARDIZED PRECIPITATION EVAPOTRANSPIRATION INDEX (SPEI)
STANDARDIZED PRECIPITATION INDEX (SPI)
STANDARDIZED SOIL MOISTURE ANOMALIES (SSMA)
title_short The added-value of remotely-sensed soil moisture data for agricultural drought detection in Argentina
title_full The added-value of remotely-sensed soil moisture data for agricultural drought detection in Argentina
title_fullStr The added-value of remotely-sensed soil moisture data for agricultural drought detection in Argentina
title_full_unstemmed The added-value of remotely-sensed soil moisture data for agricultural drought detection in Argentina
title_sort The added-value of remotely-sensed soil moisture data for agricultural drought detection in Argentina
dc.creator.none.fl_str_mv Salvia, Maria Mercedes
Sanchez, Nilda
Piles, María
Ruscica, Romina
González Zamora, Ángel
Roitberg, Esteban Gabriel
Martinez Fernandez, Jose
author Salvia, Maria Mercedes
author_facet Salvia, Maria Mercedes
Sanchez, Nilda
Piles, María
Ruscica, Romina
González Zamora, Ángel
Roitberg, Esteban Gabriel
Martinez Fernandez, Jose
author_role author
author2 Sanchez, Nilda
Piles, María
Ruscica, Romina
González Zamora, Ángel
Roitberg, Esteban Gabriel
Martinez Fernandez, Jose
author2_role author
author
author
author
author
author
dc.subject.none.fl_str_mv AGRICULTURAL DROUGHT DETECTION
ARGENTINA
SOIL MOISTURE AGRICULTURAL DROUGHT INDEX (SMADI)
STANDARDIZED PRECIPITATION EVAPOTRANSPIRATION INDEX (SPEI)
STANDARDIZED PRECIPITATION INDEX (SPI)
STANDARDIZED SOIL MOISTURE ANOMALIES (SSMA)
topic AGRICULTURAL DROUGHT DETECTION
ARGENTINA
SOIL MOISTURE AGRICULTURAL DROUGHT INDEX (SMADI)
STANDARDIZED PRECIPITATION EVAPOTRANSPIRATION INDEX (SPEI)
STANDARDIZED PRECIPITATION INDEX (SPI)
STANDARDIZED SOIL MOISTURE ANOMALIES (SSMA)
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.5
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv In countries where the economy relies mostly on agricultural-livestock activities, such as Argentina, droughts cause significant economic losses. Currently, the most-used drought indices by the Argentinian National Meteorological and Hydrological Services are based on field precipitation data, such as the standardized precipitation index (SPI) and the standardized precipitation evapotranspiration index (SPEI). In this article, we explored the performance of the satellite-based soil moisture agricultural drought index (SMADI) for agricultural drought detection in Argentina during 2010-2015, and compared it with the one from the standardized soil moisture anomalies (SSMA), SPI and SPEI (at one-month and three-month temporal scales), using the Agricultural Ministry's drought emergency database as a benchmark. The performances were analyzed in terms of the suitability of each index to be included in an early warning system for agricultural droughts, including true positive rate (TPR), and both false positive and false negative rates. In our experiments, SMADI showed the best overall performance, with the highest TPR and F1-score, and the second best false positive rate (FPR), positive predictive value, and overall accuracy. SMADI also showed the largest difference between TPR and FPR. SSMA showed the lowest FPR, but also the lowest TPR, making it not useful for an alert system. Furthermore, field precipitation-based indices, yet simple and widely used, showed not to be suitable indicators for detection of agricultural drought for Argentina, neither in the one-month nor in the three-month scale.
Fil: Salvia, Maria Mercedes. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Astronomía y Física del Espacio. - Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Astronomía y Física del Espacio; Argentina
Fil: Sanchez, Nilda. Universidad de Salamanca; España
Fil: Piles, María. Universidad de Valencia; España
Fil: Ruscica, Romina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Centro de Investigaciones del Mar y la Atmósfera. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Investigaciones del Mar y la Atmósfera; Argentina. Instituto Franco-Argentino sobre Estudios del Clima y sus Impactos; Argentina
Fil: González Zamora, Ángel. Universidad de Salamanca; España
Fil: Roitberg, Esteban Gabriel. Consejo Nacional de Investigaciónes Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Astronomía y Física del Espacio. - Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Astronomía y Física del Espacio; Argentina
Fil: Martinez Fernandez, Jose. Universidad de Salamanca; España
description In countries where the economy relies mostly on agricultural-livestock activities, such as Argentina, droughts cause significant economic losses. Currently, the most-used drought indices by the Argentinian National Meteorological and Hydrological Services are based on field precipitation data, such as the standardized precipitation index (SPI) and the standardized precipitation evapotranspiration index (SPEI). In this article, we explored the performance of the satellite-based soil moisture agricultural drought index (SMADI) for agricultural drought detection in Argentina during 2010-2015, and compared it with the one from the standardized soil moisture anomalies (SSMA), SPI and SPEI (at one-month and three-month temporal scales), using the Agricultural Ministry's drought emergency database as a benchmark. The performances were analyzed in terms of the suitability of each index to be included in an early warning system for agricultural droughts, including true positive rate (TPR), and both false positive and false negative rates. In our experiments, SMADI showed the best overall performance, with the highest TPR and F1-score, and the second best false positive rate (FPR), positive predictive value, and overall accuracy. SMADI also showed the largest difference between TPR and FPR. SSMA showed the lowest FPR, but also the lowest TPR, making it not useful for an alert system. Furthermore, field precipitation-based indices, yet simple and widely used, showed not to be suitable indicators for detection of agricultural drought for Argentina, neither in the one-month nor in the three-month scale.
publishDate 2021
dc.date.none.fl_str_mv 2021-05
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/11336/163464
Salvia, Maria Mercedes; Sanchez, Nilda; Piles, María; Ruscica, Romina; González Zamora, Ángel; et al.; The added-value of remotely-sensed soil moisture data for agricultural drought detection in Argentina; Institute of Electrical and Electronics Engineers; IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing; 14; 5-2021; 6487-6500
1939-1404
CONICET Digital
CONICET
url http://hdl.handle.net/11336/163464
identifier_str_mv Salvia, Maria Mercedes; Sanchez, Nilda; Piles, María; Ruscica, Romina; González Zamora, Ángel; et al.; The added-value of remotely-sensed soil moisture data for agricultural drought detection in Argentina; Institute of Electrical and Electronics Engineers; IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing; 14; 5-2021; 6487-6500
1939-1404
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://ieeexplore.ieee.org/document/9444130
info:eu-repo/semantics/altIdentifier/doi/10.1109/JSTARS.2021.3084849
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
application/pdf
dc.publisher.none.fl_str_mv Institute of Electrical and Electronics Engineers
publisher.none.fl_str_mv Institute of Electrical and Electronics Engineers
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
_version_ 1847426937075531776
score 13.10058

Publicaciones similares