## 4 Results
### Direct Validation with In Situ Datasets  
The temporal accuracy of the fine-RES SM datasets was assessed via comparisons with in situ SM measurements from the selected in situ measurement sites with low and stable heterogeneity in the three networks over the period of 1 April 2016 to 31 December 2016. Based on our above analysis of the spatial representativeness of the ground measurements, the direct validation of the fine-RES SM datasets was only implemented over the selected grids identified in Section 4.1. Figure 4 shows the temporal evolutions of 0.01\({}^{\circ}\)\(\times\) 0.01\({}^{\circ}\) fine-RES SM products over the selected grids, with precipitation plotted as an auxiliary time series. For the Naqu P3 grid cell, the ATA-OWCM and ER-OWCM time series accurately capture the in situ SM dynamic change, and are closer to the ground measurements than the corresponding GM-derived SM product in spring. RF-GM SM overestimates SM throughout the period, and NN-GM SM is too flat in the summer. For the Naqu MS3494 and MS3518 grid cells, GM-derived SM poorly follows the ground measurements--especially during pluvial summer conditions. In contrast, OWCM-based estimates are generally better. In the Maqu NST03 grid cell, for example, fine-RES SM is distinctly underestimated by GMs, while OWCM-derived SM accurately captures sharp temporal changes associated with observed precipitation. \begin{table}
\begin{tabular}{c c c c c c c c c c c} \hline \hline \multirow{2}{*}{**Network**} & \multirow{2}{*}{**Rank**} & \multicolumn{2}{c}{**2014, Unfrozen**} & \multicolumn{2}{c}{**2014–2015, Frozen**} & \multicolumn{2}{c}{**2015, Unfrozen**} & \multicolumn{2}{c}{**2015–2016, Frozen**} & \multicolumn{2}{c}{**2016, Unfrozen**} \\ \cline{3-11}  & & **Grid** & \(Score_{pixel}\) & **Grid** & \(Score_{pixel}\) & **Grid** & \(Score_{pixel}\) & **Grid** & \(Score_{pixel}\) \\ \hline \multirow{10}{*}{Naqu} & \multirow{5}{*}{Lowest 8 sites} & MS3518 & 0.1789 & P11 & 0.2822 & F4 & 0.2489 & MSBJ & 0.3145 & P11 & 0.3226 \\  & & MS3501 & 0.1774 & MS3488 & 0.2755 & BC05 & 0.2302 & F  
Over the Ngai SQ06 grid cell, the fine-RES SMs derived from all eight methods follow the observed in situ SM trend. Note that OWCM-derived SM products perform better than GM-derived SM products--that is, they exhibit greater consistency with in situ observations, and relatively better dynamics. Overall, it can be observed that the OWCM-derived SM products are generally closer to the in situ SM, and are well matched with in situ SM dynamic changes during the wet season, while the GM-derived SM results show fewer temporal changes and more stable trends. These differences can likely be attributed to the improved fitting of OWCMs within the WT space. Figure 4 also shows the mismatch between GM-/OWCM-derived SM and in situ SM. GM- and OWCM-derived SM products are generally underestimated in the wet environment (Maqu) or season (summer), and slightly overestimated in the relatively dry environment (Ngai) or seasons (spring and autumn). This likely relates to the differences in the soil layer observation depths of satellite (1-2 cm) and in situ measurements (-5 cm). These different observation depths can lead to (1) an underestimation of SM by satellite in the dry season, as the upper soil layers are dryer than the deeper layers; and (2) an overestimation in the wet season (summer) or soon after a rain event, because the upper layers are better than the deeper layers [9; 44; 90]. By separating the high- and low-frequency feature information of SM and SM fitting factors, OWCMs may be able to obtain high-/low-frequency wavelet components of SM and SM fitting factors that can reflect SM information in the deeper layers, so as to obtain more consistent verification results with ground observations [44]. Figure 4: Time-series comparisons of daily GM-/OWCM-derived fine-RES SM with in situ SM measurements: (**a**) GM and OWCM results based on ATA and ER; (**b**) GM and OWCM results based on RF and NN.