The Added-Value of Remotely-Sensed Soil Moisture Data for Agricultural Drought Detection in Argentina
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...
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| Format: | Article |
| Language: | English |
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IEEE
2021-01-01
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| Series: | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
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| Online Access: | https://ieeexplore.ieee.org/document/9444130/ |
| _version_ | 1831754614797500416 |
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| author | Mercedes Salvia Nilda Sanchez Maria Piles Romina Ruscica Angel Gonzalez-Zamora Esteban Roitberg Jose Martinez-Fernandez |
| author_facet | Mercedes Salvia Nilda Sanchez Maria Piles Romina Ruscica Angel Gonzalez-Zamora Esteban Roitberg Jose Martinez-Fernandez |
| author_sort | Mercedes Salvia |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-12-21T23:40:44Z |
| format | Article |
| id | doaj.art-97f5d8e502dc40d296c2c08ee9379738 |
| institution | Directory Open Access Journal |
| issn | 2151-1535 |
| language | English |
| last_indexed | 2024-12-21T23:40:44Z |
| publishDate | 2021-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
| spelling | doaj.art-97f5d8e502dc40d296c2c08ee93797382022-12-21T18:46:14ZengIEEEIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing2151-15352021-01-01146487650010.1109/JSTARS.2021.30848499444130The Added-Value of Remotely-Sensed Soil Moisture Data for Agricultural Drought Detection in ArgentinaMercedes Salvia0https://orcid.org/0000-0003-1180-5739Nilda Sanchez1https://orcid.org/0000-0002-8396-6550Maria Piles2https://orcid.org/0000-0002-1169-3098Romina Ruscica3https://orcid.org/0000-0003-0127-9579Angel Gonzalez-Zamora4https://orcid.org/0000-0002-1145-0803Esteban Roitberg5https://orcid.org/0000-0003-3510-7863Jose Martinez-Fernandez6https://orcid.org/0000-0003-0446-9693Grupo de Teledetección Cuantitativa, Instituto de Astronomía y Física del Espacio (IAFE, UBA/CONICET), Ciudad Autónoma de Buenos Aires, ArgentinaInstituto Hispano Luso de Investigaciones Agrarias, University of Salamanca, Salamanca, SpainImage Processing Laboratory, Universitat de València, Valencia, SpainUniversidad de Buenos Aires, Facultad de Ciencias Exactas y Naturales, Ciudad Autónoma de Buenos Aires, ArgentinaInstituto Hispano Luso de Investigaciones Agrarias, University of Salamanca, Salamanca, SpainGrupo de Teledetección Cuantitativa, Instituto de Astronomía y Física del Espacio (IAFE, UBA/CONICET), Ciudad Autónoma de Buenos Aires, ArgentinaInstituto Hispano Luso de Investigaciones Agrarias, University of Salamanca, Salamanca, SpainIn 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.https://ieeexplore.ieee.org/document/9444130/Agricultural drought detectionArgentinasoil moisture agricultural drought index (SMADI)standardized precipitation evapotranspiration index (SPEI)standardized precipitation index (SPI)standardized soil moisture anomalies (SSMA) |
| spellingShingle | Mercedes Salvia Nilda Sanchez Maria Piles Romina Ruscica Angel Gonzalez-Zamora Esteban Roitberg Jose Martinez-Fernandez The Added-Value of Remotely-Sensed Soil Moisture Data for Agricultural Drought Detection in Argentina IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 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 | 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_short | The Added-Value of Remotely-Sensed Soil Moisture Data for Agricultural Drought Detection in Argentina |
| title_sort | added value of remotely sensed soil moisture data for agricultural drought detection in argentina |
| 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) |
| url | https://ieeexplore.ieee.org/document/9444130/ |
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