Long-term Prediction of Saltwater Intrusion Based on Sequence Learning Framework

Key Points

• Saltwater intrusion can be predicted over the long term with a sequence learning framework, enabling better coastal management.
• The predictive model demonstrated a significant accuracy rate of 85% in forecasting saltwater intrusion events.
• Analysis was conducted using historical data to train the predictive model, focusing on environmental impacts across coastal areas.
• The findings highlight the need for effective water resource management strategies to combat saline intrusion risks.