## 4 Results and Discussion  
### Model Calibration and Validation  
Among the 39 observation wells, we selected six representative wells at different locations in the PPGB, namely Jiyang, Chiuju, Jianxing, Yongfang, Kanding, and Fangliao, to assess the spatio-temporal variations of the total hydraulic head. Figure 6 shows the results of the comparison for the selected wells. The calibration and validation periods have demonstrated that the coupled groundwater and surface water model can reproduce well the groundwater dynamics in the PPGB. The differences between the observed data and the simulated solution are limited to \(\pm\)1 m. Note that the recharge and pumping rates are two sensitive parameters in the model and that these parameters are the main focus of the model calibration. In the study, the calibrated recharge and precipitation ratios for different cells were then used for the model validation. However, the variations of pumping rates were assumed to be the same through the validation periods. We have shown that the substantial variations of the dry and wet seasons in the PPGB and the influence of precipitation on the groundwater variations are significant. Based on the precipitation data obtained from the PPGB, the period of the wet season is from May to October and the dry season is from November to the next April. The year 2016 was a wet year and had an extremely high total precipitation of 3796 mm. The plots of the monthly average rainfall considered the data from the weather stations that are closest to the monitoring wells. The dry and wet seasons led to groundwater variations of 2 to 20 m, depending on the locations of the monitoring wells. Such variations are significant in the downstream area (i.e., the Fangliao station, see Figure 6f). However, in the upstream area at the Jiyang station, the monitoring well shows the relatively mild variations of the groundwater levels as compared to other selected monitoring wells. The stations in the center area of the PPGB show small variations in groundwater levels. The small variations in groundwater levels might be relevant to the relatively high density of river branches. Note that the variations of groundwater levels are strongly influenced by the agriculture and aquaculture activities in the local areas. In the PPGB, the aquaculture pumping is highly active in the nearshore area. \begin{table}
\begin{tabular}{c c c} \hline
**Parameter** & **Minimum Value** & **Maximum Value** \\ \hline fastcoef\_lin & 0.4 & 0.4 \\ jh\_coef & 0.0024 & 0.004 \\ pref\_flow\_den & 0.4 & 0.4 \\ smidx\_coef & 0.03 & 0.03 \\ soil\_moist\_max & 12 & 12 \\ soil\_rechr\_max & 6 & 6 \\ ssr2 gw\_exp & 0.5 & 0.5 \\ ssr2 gw\_rate & 0.2 & 0.2 \\ wrain\_intcp & 0.05 & 0.05 \\ smidx\_exp & 0.6 & 0.6 \\ soil2 gw\_max & 5 & 5 \\ ssstor\_init & 10 & 10 \\ rain\_adj & 1.76 & 5 \\ \hline \end{tabular}
\end{table} 
Table 1: The ranges of the calibrated parameters for the groundwater and surface water flow (GSFLOW) model. Note that other parameters that are not on the list used the default values proposed by [PERSON] et al. (2008) (2008) (2008). The simulation results indicate that the high groundwater head regions are in the northeastern area near the Central Mountain Range of the PPGB. The hydraulic head values in these regions are higher than 60 m. In general, the groundwater levels gradually decrease from the northeastern area to the lower reaches of the Kaoping, Tungkang, and Linien Rivers. In the downstream area in the basin lowland near the Taiwan Strait, the simulated hydraulic head values are less than 0 m because of the over-pumping of the groundwater along the coastal line (see Figure 7a). We found that the patterns of hydraulic head distributions for wet and dry seasons are nearly identical except for the small regions along the shoreline and near the confluence point at the Li-lin station. Figure 7b further shows the distribution of mean head differences in wet and dry seasons in the entire PPGB.