Capability of existing drought indices in reflecting agricultural drought in China

A variety of drought indices have been constructed to monitor agricultural drought using ground and satellite data. Our study aimed to evaluate the performance of drought indices to indicate agricultural drought in China. Seven drought indices of four types were selected over the main agricultural regions of China: indices based on regular meteorological data (DI_met), indices based on vegetation index (DI_vi), indices based on soil moisture (DI_sm), and synthesized indices (DI_syn). The independent reference data used here included three aspects: soil moisture, vegetation photosynthesis and crop yield data. The latter two reference datasets were selected to check drought impact on agriculture. Drought indices with short timescales are more sensitive to topsoil moisture. Drought indices have different abilities to capture vegetation photosynthesis condition during the growing season. Expect for the Yangtze region and North China region during the wheat growing season, the DI_met and DI_syn show significant positive correlations with the sun-induced chlorophyll fluorescence (SIF), while the other drought indices have weaker or no correlations. For crop yield, the prediction ability of the drought indices show a similar pattern with the results for vegetation photosynthesis but with relatively large uncertainty. Generally, our study show that DI_met have better or equivalent performance than that of the other types of drought indices, and DI_syn show the widest applicability. Our study may shed light on agricultural drought research in the future.