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To better understand the characteristics and mechanisms of droughts at different drought stages, this study selected the Xiangjiang River Basin in China as the study area, and evaluated soil moisture (SM) at different depths for drought monitoring, through SM data simulated with the variable infiltration capacity (VIC) model. To solve the problem of unreasonable drought/wetness classifications based on the soil moisture anomaly percentage index (SMAPI), an improved soil moisture anomaly percentage index (ISMAPI) was developed by introducing the Box–Cox transformation. The drought/wetness frequency generated by ISMAPI demonstrated preferable spatial comparability in comparison with those from SMAPI. The lag time of ISMAPI relative to the standardized precipitation evapotranspiration index was closely related to soil depth, and was characterized by a fast response in shallow soil layers and a relatively slow response in deep soil layers. SM in shallow soil layers provided a measure for monitoring short-term droughts, whereas SM in deep soil layers provided a better measure for long-term persistent drought events. Furthermore, the occurrence and mitigation time of drought events identified by SM in deep soil layers usually lagged behind that identified by SM in shallow soil layers. Compared with deep SM, SM in shallow soil layers responded faster to meteorological anomalies, thereby resulting in shorter periods of SM persistence in shallow soil layers than in deep soil layers. This can explain the differences of SM at different depths in drought monitoring.
Xu et al. (Tue,) studied this question.