Forecasting groundwater level changes using machine learning techniques in Tazerbo area, Al Kufra Basin, southeast Libya

, MSE, and RMSE, achieving high predictive accuracy across all wells. The model performed excellently during training and testing. Using NARX-NN, scenario-based forecasts for 2030 and 2040 were generated for 14 wells under two pumping rates 255,000 m³/day and 400,000 m³/day. At the current rate, groundwater is projected to decline by ~ 2 m by 2030 and ~ 1.6 m by 2040. Under higher pumping rates, drawdowns could exceed 50 m by 2030 and 2040. The results reveal spatially variable trends in groundwater decline, with significant drops projected in the northern and eastern zones under increased extraction. These findings offer valuable insights into sustainable groundwater management and long-term planning in water-stressed basins.