Evaluation Of The Soil Moisture Agricultural Drought Index (SMADI) And Precipitation-Based Drought Indices In Argentina

M. Salvia, N. Sánchez, M. Piles, Á. González-Zamora, J. Martínez-Fernández
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Abstract

Agricultural drought is one of the most critical hazards with regard to intensity, severity, frequency, spatial extension and impact on livelihoods. This is especially true for Argentina, where agricultural exports can represent up to 10% of gross domestic product (GDP), and where drought events for 2018 led to a decrease of nearly 0.5% of GDP. In this work, we investigate the applicability of the Soil Moisture Agricultural Drought Index (SMADI) for detection of droughts in Argentina, and compare its performance with the use of two well-known precipitation-based indices: the Standardized Precipitation Index (SPI) and the Standardized Precipitation-Evaporation Index (SPEI). SMADI includes satellite-based information of soil moisture, surface temperature and vegetation greenness, and was designed to capture the hydric stress on the soil-vegetation ensemble. Results indicate that SMADI has greater capabilities for agricultural drought detection than SPI and SPEI: it was able to recognize more than 83% of the registered emergencies, correctly classifying 75% of them as extreme droughts, and outperforming SPI and SPEI in all the analyzed metrics.
阿根廷土壤水分农业干旱指数(SMADI)和基于降水的干旱指数评价
农业干旱在强度、严重程度、频率、空间延伸和对生计的影响方面都是最严重的灾害之一。阿根廷尤其如此,该国的农产品出口可占国内生产总值(GDP)的10%,而2018年的干旱事件导致该国GDP下降了近0.5%。在这项工作中,我们研究了土壤水分农业干旱指数(SMADI)在阿根廷干旱检测中的适用性,并将其与两个著名的基于降水的指数:标准化降水指数(SPI)和标准化降水蒸发指数(SPEI)的性能进行了比较。SMADI包括基于卫星的土壤湿度、地表温度和植被绿度信息,旨在捕获土壤-植被整体的水分胁迫。结果表明,SMADI比SPI和SPEI具有更强的农业干旱检测能力:它能够识别超过83%的登记紧急情况,正确地将75%的紧急情况归类为极端干旱,并且在所有分析指标上都优于SPI和SPEI。
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