Simulation and prediction of sulfamethazine migration, transformation and risk diffusion during cross-media infiltration from surface water to groundwater driven by dynamic water level : Machine learning coupled HYDRUS-GMS model
Seasonal water level fluctuations in rivers significantly influenced the cross-media migration, transformation, and risk diffusion of antibiotics from the vadose zone into groundwater. This study developed a coupled model integrating machine learning (ML) with HYDRUS-3D and GMS to accurately predict sulfamethazine migration under dynamic water levels. The predictive accuracy (E≥0.98) of this ML-HY
