Artificial Intelligence in Climate-Resilient Water Management: A Systematic Review of Applications, Challenges, and Future Directions

Key findings reveal that AI models—particularly long short-term memory (LSTM) and hybrid physics-informed neural networks—achieve superior accuracy in hydrological forecasting, enabling reliable predictions of water availability, droughts, and floods.