## 4 Results and Discussion
### Numerical Simulation of Precipitation Infiltration in the Field Test Site
#### 4.2.5 Calibration and Validation  
We divided the soil profiles into nine layers, and the basic parameters for soil water migration simulation include \(\theta_{s}\), \(\theta_{r}\), \(\alpha\), \(n\), \(K_{s}\), and \(l\). Soil particle size distribution data and bulk density data (Table 1) of these nine layers were analyzed in the laboratory. We estimated \(\theta_{r}\), \(K_{s}\), and the empirical shape parameters \(n\) and \(\alpha\) using the H3 mode (Sand, Silt, Clay and Bulk Density; SSCBD for short) of Rosetta Lite (Salinity Laboratory of the USDA, Riverside, CA, USA) based on the neural network embedded in HYDRUS-1D from the data analyzed in the laboratory (Table 1). \(\theta_{r}\), \(K_{s}\), \(n\), and \(\alpha\) were fitted parameters; the soil's mechanical composition (sand, silt, and clay), \(\theta_{s}\), and \(\rho_{b}\) were fixed parameters with specific values derived from measurements. The initial values of the fitted parameters (Table 4) for each layer were estimated using the Neural Network Prediction embedded in the model, and then, the parameters were fitted by fitting the observations measured for this layer in the field test site. We compared observed field measurements with the results of the HYDRUS-1D simulations using the mean absolute errors (MAEs) and root mean square errors (RMSEs) shown in Table 5 [18; 22]. The average value of the simulation data is very close to the average value of observed data at each layer. The values of MAE and RMSE of these four layers are small and close to 0, which means the accuracies of model calibration and validation are good. The observed field measurements and simulation results of the four cohesive layers in the three mass balance zones were roughly the same (Figure 9). The difference between simulation data and observed data (\(\rm{1\,O_{i}-P_{i}\,l_{max}}\)) was larger at the depth of 0.2 m than at 0.9 m, followed by that at 6.0 m and 2.5 m. The numerical model can generally simulate the variation in soil water content in cohesive soil. The parameters of the Van Genuchten-Mualem equation were finally determined after multiple hydraulic parameter adjustments. The optimization results are presented in Table 6. \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline
**Layer** & **Depth (cm)** & \(\theta_{r}\) **(m\({}^{3}\)/m\({}^{3}\))** & \(\theta_{s}\) **(m\({}^{3}\)/m\({}^{3}\))** & \(\alpha\) (l/cm)** & \(n\) & \(K_{s}\) **(cm/d)** & \(l\) \\ \hline
1 & 0–20 & 0.0514 & 0.4005 & 0.0065 & 1.6332 & 30.36 & 0.5 \\
2 & 20–120 & 0.0483 & 0.3902 & 0.0069 & 1.6226 & 30.85 & 0.5 \\
3 & 120–260 & 0.0511 & 0.4071 & 0.0067 & 1.6326 & 33.02 & 0.5 \\
4 & 260–440 & 0.0561 & 0.4089 & 0.0076 & 1.5748 & 11.73 & 0.5 \\
5 & 440–570 & 0.0568 & 0.3949 & 0.0077 & 1.5469 & 8.05 & 0.5 \\
6 & 570–1160 & 0.0496 & 0.3948 & 0.0085 & 1.5626 & 14.75 & 0.5 \\
7 & 1160–1300 & 0.0654 & 0.4407 & 0.0057 & 1.6512 & 24.33 & 0.5 \\
8 & 1300–1400 & 0.0283 & 0.3071 & 0.0249 & 1.3592 & 18.57 & 0.5 \\
9 & 1400–1500 & 0.0280 & 0.4010 & 0.0364 & 1.4277 & 74.82 & 0.5 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Initial hydraulic parameters of cohesive soil layers we obtained via the H3 mode (SSCBD mode) of Rosetta Lite for simulation. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Depth (m)** & \(\overline{\mathbf{O}}\) **(m\({}^{3}\)/m\({}^{3}\))** & \(\overline{\mathbf{P}}\) **(m\({}^{3}\)/m\({}^{3}\))** & \(1\overline{\mathbf{O}}-\overline{\mathbf{P}}\)**i & \(\mathbf{1}\mathbf{O}_{i}-\mathbf{P}_{i}\,l_{max}\)** & **MAE** & **RSME** \\ \hline
0.2 & 0.4096 & 0.3902 & 0.0194 & 0.1167 & 0.0251 & 0.0333 \\
0.9 & 0.3854 & 0.3877 & 0.0023 & 0.0946 & 0.0216 & 0.0296 \\
2.5 & 0.3682 & 0.3854 & 0.0163 & 0.0372 & 0.0166 & 0.0197 \\
6.0 & 0.3764 & 0.3887 & 0.0123 & 0.0421 & 0.0176 & 0.0213 \\ \hline \hline \end{tabular} Note: \(\overline{\mathbf{O}}\) is the average value of observed data; \(\overline{\mathbf{P}}\) is the average value of simulation data; \(\rm{O}_{i}\) is the observed data; \(\rm{P}_{i}\) is the simulation data.  
\end{table}