The landforms and human activities play important roles in quantifying surface water and groundwater interactions (SGIs) for water resources management. The study uses the groundwater and surface water flow (GSFLOW) model to quantify the dynamics of SGIs in the Pingtung Plain groundwater basin (PPGB) in southern Taiwan. Specifically, the study uses a physical-based numerical model to quantify the spatial and seasonal variations of water cycles influenced by complex fluvial landform conditions and human activities. Results of the model calibrations show good agreement with the data obtained from the available groundwater monitoring network and the selected stream stations. The basin-scale water budgets show highly nonuniform precipitation in the study area, and over 80% annual precipitation is from wet seasons in the PPGB. With high permeable surficial deposits in the PPGB, the year-averaged surface runoff and infiltration are approximately 57% and 40% of the total precipitation. The fluvial landforms with the high slope in the PPGB lead to 70% of annual surface runoff that becomes the streamflow, and the interflow dominates water interactions near streambeds. Results show that the interflow rate in the wet seasons is 200% more than that in the dry seasons. The net groundwater discharge to the streams is relatively small as compared to the interflow. Only 10% of the river flow is from the net groundwater discharge. In the PPGB, The pumping-induced variations of groundwater levels are insignificant as compared with the factor of the natural landforms. Because of the relatively small area of the proposed artificial lake, the contribution of the artificial lake on the local water budgets is insignificant, indicating the low impact of the artificial recharge lake on the surface water environment.

Interflow is an important water source contributing to river flow. It directly influences the near-surface water cycles for water resource management. This study focuses on assessing the interflow potential and quantifying the interflow in the downstream area along the Kaoping River in southern Taiwan. The interflow potential is first determined based on the modified index-overlay model, which employs the analytical hierarchy process (AHP) to calculate the ratings and weightings of the selected factors. The groundwater and surface water flow (GSFLOW) numerical model is then used to link the index-overlay model to quantify the interflow potential for practical applications. This study uses the Monte Carlo simulations to assess the influence of rainfall-induced variations on the interflow uncertainty in the study area. Results show that the high potential interflow zones are located in the high to middle elevation regions along the Kaoping River. Numerical simulations of the GSFLOW model show an interflow variation pattern that is similar to the interflow potential results obtained from the index-overlay model. The average interflow rates are approximately 3.5 × 10⁴ (m³/d) in the high elevation zones and 2.0 × 10⁴ (m³/d) near the coastal zones. The rainfall uncertainty strongly influences interflow rates in the wet seasons, especially the peaks of the storms or heavy rainfall events. Interflow rates are relatively stable in the dry seasons, indicating that interflow is a reliable water resource in the study area.