In recent years, the decline of groundwater resources in productive aquifers within arid and semi-arid regions has become a growing concern. This depletion leads to lasting changes in aquifer properties due to fine particle rearrangement caused by pore pressure decline. The issue is especially critical in regions lacking reliable field data. Thus, it is crucial to develop methods that are less dependent on in-situ data but still offer reliable tools for monitoring groundwater levels in such regions. This study presents the deformation-driven groundwater head estimation model, primarily developed to estimate storativity by jointly analyzing groundwater head and Interferometric Synthetic Aperture Radar (InSAR)-derived surface deformation, separating seasonal and longterm components. The model then uses these estimated storage coefficients to simulate and predict groundwater levels without requiring detailed knowledge of aquifer type or properties. It can reconstruct historical head data and predict future levels from deformation alone. Model performance was evaluated across two distinct aquifer systems with diverse hydrogeological properties and deformation behaviors. Four wells in each aquifer ensured spatial representativeness. The model showed strong agreement with observed groundwater head, achieving average R2 values of 0.70 and 0.94 in the simulation phase, and 0.65 and 0.34 in the prediction phase for the two aquifers, respectively.