## 3 Results
### Evaluation Using Independent Datasets
#### 3.2.3 Streamflow  
A subset of 258 out of 531 gauging stations was selected for the evaluation according to the criteria described in the methodology section, with KGE scores within the [0, 1] interval. Figure 8 presents the performance of analysed streamflow with respect to the one from the model run for this pool of stations, with a focus on the eastern part of the domain. NIC\({}_{\text{KGE}}\) values are presented following the same classification as NIC\({}_{\text{R}}\) applied to soil moisture. Scores are presented in Table 4. Looking at NIC\({}_{\text{KGE}}\), 62% of the pool of stations (258 stations) present a rather neutral impact (at NIC\({}_{\text{KGE}}\) between [\(-\)3; 3]) and 26% of the stations present a positive impact (at NIC\({}_{\text{KGE}}\)\(>\) +3), while only 12% of stations have a negative impact (at NIC\({}_{\text{KGE}}\)\(<\) \(-\)3). NICR, N\({}_{\text{RE}\sigma}\), and N\({}_{\text{RE}\mu}\) follow the same classification (with even a smaller percentage of stations being negatively affected by the analysis; 1%); when the analysis is impacting streamflow representation, it tends to be a positive impact.  
Figure 8: Normalized information contribution scores based on Kling–Gupta efficiency (KGE) scores (NIC\({}_{\text{KGE}}\)) (**a**) analysis with respect to the model, (**b**) zoom over the eastern part of the domain. Small diamonds represent stations for which NIC\({}_{\text{KGE}}\) are between [\(-\)3; +3]. NIC\({}_{\text{KGE}}\) greater than 3 (blue large circles) suggest an improvement from the analysis over the model, values smaller than \(-\)3 (red large circles) suggest a degradation. For sake of clarity, a factor of 100 has been applied to NIC.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**110 (110)** & \multirow{2}{*}{
\begin{tabular}{c} **Median R** \\ **(Anomaly R)** \\ \end{tabular} } & **Median R** & **Median** & **Positive** & **\(\leftarrow\)3 Negative** & **Neutral Impact** \\
**Significant R** & **(Anomaly R)** & **ubRMSD** & **Impact: \(\boldsymbol{>}\)+3** & **Impact: \(\boldsymbol{<}\)\(\boldsymbol{-}\)3** & **[\(-\)3; +3]** \\ \hline \multirow{2}{*}{Model} & 0.72 \(\pm\) 0.02 \({}^{\star}\) & 0.049 \(\pm\) 0.004 & \multirow{2}{*}{N/A} & \multirow{2}{*}{N/A} & \multirow{2}{*}{N/A} \\  & (0.60 \(\pm\) 0.02 \({}^{\star}\)) & & & & \\ \hline \multirow{2}{*}{Analysis} & 0.74 \(\pm\) 0.02 \({}^{\star}\) & 0.048 \(\pm\) 0.004 & \multirow{2}{*}{46\% (18\%)} & \multirow{2}{*}{8\% (1\%)} & \multirow{2}{*}{46\% (81\%)} \\  & (0.60 \(\pm\) 0.02 \({}^{\star}\)) & & & & \\ \hline \hline \end{tabular} \({}^{\star}\) 95% confidence interval of the median derived from a 10,000 samples bootstrapping.  
\end{table}
Table 3: Analysis impact evaluation against in situ measurements of soil moisture from the US Climate Reference Network (USCRN) network. In situ measurements at a depth of 5 cm are used to evaluate soil moisture from the third layer of soil (4–10 cm) from either the model or analysis experiment over 2010–2016. The normalized information contribution (NIC) is applied to the correlation (anomaly correlations) values. NIC scores are classified according to three categories: (i) negative impact from the analysis with respect to the model with values smaller than \(-\)3%, (ii) positive impact from the analysis with respect to the model with values greater than \(+\)3%, and (iii) neutral impact from the analysis with respect to the model with values between \(-\)3% and 3%.