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, most-used drought indices by Argentinian National Meteorological and Hydrological Services are based field precipitation data, standardized index (SPI) evapotranspiration (SPEI). this article, we explored performance of satellite-based soil moisture agricultural (SMADI) for detection in Argentina during 2010-2015, compared it with one from anomalies (SSMA), SPI SPEI (at one-month three-month temporal scales), using Agricultural Ministry's emergency database a benchmark. The performances were analyzed terms suitability each to be included an early warning system droughts, including true positive rate (TPR), both false negative rates. our experiments, SMADI showed best overall performance, highest TPR F1-score, second (FPR), predictive value, accuracy. also largest difference between FPR. SSMA lowest FPR, but TPR, making not useful alert system. Furthermore, precipitation-based indices, yet simple widely used, suitable indicators neither nor scale.