Mohamed Meddi

MODFLOW-informed machine learning for interpretable groundwater level prediction under sparse monitoring conditions in the Eastern Mitidja Aquifer, Northern Algeria

Predicting groundwater levels in semi-arid regions is challenging because groundwater systems are controlled by complex processes and monitoring data are often scarce. This study compares six machine learning models—Random Forest (RF), XGBoost, LightGBM, RBF-SVR, LSTM, and CNN—fo...