This study presents an integrated approach to groundwater level monitoring in the Tashkent region, combining classical piezometric measurements, automated sensors, and satellite-based remote sensing. A regression model linking groundwater levels to monthly precipitation (P) and water abstraction volumes (Q) was developed using simulated 2024 data. The results reveal a clear seasonal pattern: groundwater levels peak during the wet season and decline sharply during the irrigation-intensive summer months. The model provides a scientific basis for adaptive water management policies under increasing climatic and anthropogenic pressures.