Explainable and physics-informed machine learning for seasonal water quality prediction in the monsoon-driven Padma River Basin, Bangladesh

Key Points

• Water quality prediction improved accuracy by leveraging machine learning techniques, enhancing environmental monitoring.
• The model effectively captured seasonal variations during monsoon periods, with notable predictive performance metrics.
• The methodology employs physics-informed approaches to incorporate environmental data, ensuring robust predictions.
• Enhanced predictive insights may facilitate better water resource management, addressing seasonal challenges in river ecosystems.