This study addresses the challenge of accurately estimating groundwater-surface water fluxes, essential for sustainable water resource management, by improving traditional temperature time series methods. Existing approaches often struggle with distinguishing natural temperature variations from significant water exchanges, especially across different spatial and temporal scales under varying conditions like recharge and discharge. To overcome these issues, advanced statistical tools were applied to temperature data, and COMSOL Multiphysics was used to simulate interactions by coupling fluid flow and heat transport. Multisite and multivariate calibration techniques refined parameters like hydraulic conductivity and porosity, while models accounted for external factors such as climate variability and land-use changes. The findings reveal that the combined method was effective in estimating groundwater-surface water fluxes under recharge conditions. The COMSOL model achieved an MAE of 0.71, MAP has 0.92, RMSE of 0.80, and RMSLE has 0.30, indicating consistent performance across evaluation metrics. This advancement improves groundwater-surface water model precision, especially in distinguishing natural temperature variations from significant water exchanges. It offers more accurate flux estimation, aiding better water resource management.
