Hybrid deep learning-numerical modeling framework for long-term prediction of groundwater discharge and radionuclide transport

Key Points

• Groundwater discharge and radionuclide transport predictions improve with the hybrid model, enhancing environmental monitoring.
• Key evidence includes a significant predictive accuracy of 85% measured against traditional modeling techniques.
• Assessment involves a hybrid deep learning-numerical modeling approach to enhance prediction of groundwater dynamics.
• Supports the need for advanced predictive frameworks to better manage and monitor environmental contaminants, indicating future directions.