Benchmarking of drought and climate indices for agricultural drought monitoring in Argentina

Site-specific studies are required to identify suitable drought indices (DIs) for assessing and predicting drought related impacts. This study presents a benchmark of eight DIs and 19 large-scale climate indices (CIs) to monitor agricultural drought in Argentina. First, the link between the CIs and DIs was investigated at the departmental administrative level and at different temporal scales. Then, the effectiveness of the DIs in explaining the variability of crop yields, understood as impacts of agricultural droughts, was evaluated using statistical regression models. Soybeans were used as the reference crop. Additionally, the performances of DIs and CIs in explaining the variability of crop yields were compared. The CIs located in the Pacific Ocean (El Nino 3.4 and El Nino 4) were found to have the best correlations with the DIs (R values up to 0.49). These relationships were stronger with longer temporal aggregations and during the wet and hot seasons (summer), showing a significant role in the triggering of droughts in Argentina. The DIs that best corelated with CIs were those that included temperature in their calculations (STCI, SVHI, and SPEI). The impacts of droughts on soybean production were better explained using DIs than with CIs (up to 89% vs 8% of variability explained) as predictors of the statistical models. SVHI-6 and SPEI-6, depending on the area of interest, were, during the phenological period of crop growth (summer), the most effective DIs in explaining annual variations in soybean yields. The results may be of interest in water resource management, drought risk management, and the Argentinean soybean production sector. Furthermore, they provide a foundation for future studies aimed at forecasting agricultural droughts and their impacts. (c) 2021 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Automated summary

Site-specific studies are necessary to identify suitable drought indices for assessing and predicting drought impacts. This study in Argentina found that indices such as STCI, SVHI, and SPEI, particularly correlated with temperature, were effective in explaining variability in crop yields, with El Nino indices showing the strongest correlations with drought indices. The findings may have implications for water resource management, drought risk management, and the Argentinean soybean production sector.