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Land surface models (LSMs) have been widely used to provide objective monitoring of soil moisture during drought, but large uncertainties exist because of the different parameterizations in LSMs. This study aims to evaluate the ability to monitor soil moisture drought over three key regions in China by using the Noah LSM from the Global Land Data Assimilation System, version 2 (GLDASv2), and the Community Atmosphere Biosphere Land Exchange (CABLE) model that is currently used at the China Meteorological Administration. The modeled soil moisture drought indices were verified against the standardized precipitation evapotranspiration index (SPEI), which served as a reference drought indicator over northern China (NC), northwestern China (NWC), and southwestern China (SWC) from 1961 to 2010. The results show that the precipitation forcing data that drive both LSMs have high accuracy when compared with local observational data. GLDASv2/Noah outperforms CABLE in capturing soil moisture anomalies and variability, especially in SWC, but both show good correlations with the 3-month SPEI (SPEI3) in NC, NWC, and SWC. The autumn drought of 2002 and spring drought of 2010 were selected for the comparison of the modeled drought categories with the SPEI3 drought category, where GLDASv2/Noah performed slightly better than CABLE. This work demonstrates that the choice of LSM is crucial for monitoring soil moisture drought and that the GLDASv2/Noah LSM can be a good candidate for the development of a new operational drought-monitoring system in China. [ABSTRACT FROM AUTHOR]