Satellite-based quantitative precipitation estimates (QPEs) have shown great potential in the precipitationrelated extremes estimation. However, little is known about the capability of different QPEs to monitor the dynamic evolutions of drought on various spatio-temporal scales. Here, the drought utility of two top-down QPEs (i.e., Climate Hazards Group InfraRed Precipitation with Stations, CHIRPS; Integrated Multi-SatellitE Retrievals for Global precipitation measurement-Final run, IMERG-F) and one bottom-up QPE (i.e., Soil Moisture to RainAdvanced SCATterometer, SM2RAIN-ASCAT), is evaluated comprehensively in mainland China, based on three commonly used drought indices (Standardized Precipitation Index, Standardized Precipitation Evapotranspiration Index, Composite index of meteorological drought). The results indicate that the top-down QPEs generally show better performance in detecting drought occurrence over the humid and low-altitude regions in eastern China than the arid and high-altitude regions in western China. IMERG-F performs best in detecting drought occurrence in the entire mainland China, followed by CHIRPS, and the least satisfactory by SM2RAIN-ASCAT. The trajectory of drought centroids and the temporal variability of drought characteristics are highly dependent on both the drought indices selected and QPEs used. IMERG-F and CHIRPS can better reproduce the trajectories of large-scale drought events (e.g., the locations of drought origin and termination) than SM2RAINASCAT. The ability in tracking the drought centroid trajectory of all three QPEs is higher at the smaller spatial scales, also it improves from the semi-arid to humid regions. Our results highlight the superiority of the top-down QPEs in drought monitoring compared with the bottom-up QPE in mainland China, particularly over the humid regions. The application of SM2RAIN-ASCAT in drought monitoring to the large-scale arid areas should be cautious.