Water security relies on accurately representing hydrological processes in river-aquifer dynamics, including aquifer recharge driven by rainfall, hyporheic flow, and lateral tributary inflow. River-aquifer studies often overlook these processes. Using a parsimonious numerical model, we accurately calculated these processes in a data-scarce region, at scales relevant to water management. The model's performance measures (Kling-Gupta efficiency, Nash-Sutcliffe efficiency, and percent bias) show that it effectively estimates river and groundwater flow using a simple modeling approach, requiring only minimal calibration (three parameters). Notably, the data required for the model are often available in regions with scarce data. Sensitivity analysis of the simplified model parameters shows that riverbed hydraulic conductivity and aquifer width significantly affect outflow in data-scarce environments. Hyporheic flow is crucial for the water balance in dryland rivers. In contrast, sub-catchment runoff demonstrated minimal influence compared to inflow and groundwater fluxes, suggesting a greater dependence on river volume and stage than on intraseasonal rainfall. This study contributes to a more accurate water balance of key hydrological processes in data-scarce regions and provides valuable tools for similar areas that require viable management solutions.