CONICET | Buscador de Institutos y Recursos Humanos

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 research 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 1-month and 3-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, and both false positive and false negative rates. In our experiments, SMADI showed the best overall performance, with the highest true positive rate and F1-score, and the second best false positive rate, positive predictive value, and overall accuracy. SMADI also showed the largest difference between true positive rate and false positive rate. SSMA showed the lowest false positive rate, but also the lowest true positive rate, 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 1-month nor in the 3-month scale.