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It is important to accurately assess agricultural drought because of its harmful impacts on the ecosystem and economy. Soil moisture reanalysis datasets provide an important way to assess agricultural drought. In this study, the ERA5-Land surface and subsurface soil moisture was used to estimate the soil water deficit index (SWDI) in four southern provinces of China. The ERA5-Land dataset was evaluated with in situ soil moisture observations from agrometeorological stations. Agricultural drought was assessed for three climate zones at a weekly scale from 2017 to 2019 and was compared with the atmospheric water deficit (AWD). It was found that both ERA5-Land soil moisture and the derived SWDI have relatively high accuracy, and the wet bias in the ERA5-Land dataset can be reduced by the calculation of the SWDI. The subsurface layer has better performance than the surface layer in drought monitoring, though they are highly correlated. Different climate zones demonstrate different drought periods and drought severity, and the temperate climate zone with no dry season has less droughts. The most severe droughts with the largest spatial extent occurred in the early winter, especially in 2019. Differences in the SWDI and AWD are mainly shown in southwestern Yunnan. The results of this study have important reference values for drought risk management.

Assessment of Agricultural Drought Using Soil Water Deficit Index Based on ERA5-Land Soil Moisture Data in Four Southern Provinces of China