Soil moisture (SM) measurements from ground stations are often after quality control (QC) in the operational system, but the QC flags may not be reliable in some cases when precipitation events or manual watering happen. This study applies the triple collocation (TC) method to conduct a cross-evaluation of SM data from ERA5 reanalysis estimates, ESA-CCI estimates, and ~2000 ground stations across the China domain. The results show that all datasets can capture the spatial pattern of SM in China. TC-based correlation coefficient (CC) and root mean square error (RMSE) show that the station data have worse performance in western and central China. For most stations, TC-based CC is between 0.6~0.9, and TC-based RMSE is between 0.01~0.06 m3/m3. In addition, TC-based metrics show good agreement with the CC between precipitation and SM, indicating that these metrics can reflect the quality of station data. We further selected typical stations (e.g., CC ≤ 0.2, RMSE ≥ 0.06 m3/m3) to check the quality of the QC procedure. The comparison shows that TC-based metrics can better represent the actual quality for these stations compared to raw QC flags. This study indicates that TC has the potential to detect problematic stations and could be a supplement to traditional QC of station observations.