Rapid urbanization and intensive agricultural practices in Vietnam's Central Highlands have substantially transformed land use/land cover (LULC) patterns, with implications for groundwater resources necessitating measurement. The objective of this investigation is to examine the links between multi-temporal variations in LULC and changes in underground water flow in Al Ba Commune, Gia Lai Province. Supervised object-based classification of Landsat and Sentinel imagery from the past 25 years has produced consistent LULC maps as inputs for the model. Geospatial data of LULC, meteorological data, and in-situ data of groundwater flow (Q) were used to calibrate and validate the integrated hydrological MIKE SHE model and simulate past Q conditions for correlation analysis. With these data on LULC and groundwater flow, this study investigates the relationship between LULC changes and Q using Multivariate Linear Regression (MLR) and Ridge Regression models. The MLR model showed high R² (0.91) but positive impacts of all LULC classes on Q, contrary to expectations. Further analysis with Variance Inflation Factor (VIF) revealed multicollinearity among LULC variables, which was addressed using Ridge Regression with a bias factor to correct for this issue. The revised model demonstrated that non-vegetative covers negatively affect Q while vegetative covers have a positive impact. These results highlight the complex dynamics of LULC changes on groundwater resources, which can be detected by statistical approaches. The results of study could be important for sustainable land management.