Study region: This study focuses on four basins in southern Saudi Arabia: Hali, Baish, Yiba, and Reem. These regions are characterized by arid conditions and are significantly impacted by dam construction. Study focus: The research investigates the environmental impacts of dam construction using a space-for-time substitution approach, remote sensing, and machine learning techniques. A key focus is analyzing non-linear environmental impacts, particularly in data-limited, arid regions where traditional methodologies fall short. The study introduces a novel framework that combines space-for-time substitution and Dynamic Time Warping (DTW) to assess temporal and spatiotemporal changes in key environmental factors such as NDVI, soil salinity, groundwater, and runoff. New hydrological insights: The results reveal significant changes post-dam construction. In the Yiba-Hali basins, DTW values increased across several parameters: NDVI (0.08-0.25), soil salinity (0.09-0.25), and runoff (0.45-0.90), indicating reduced similarity between pre- and post-dam conditions. In the Reem-Baish basins, the Baish dam caused notable increases in DTW values for NDVI (0.16-0.31), soil salinity (0.15-0.30), groundwater (0.52-1.19), and runoff (0.53-1.33), with the most significant changes observed in groundwater and runoff. Additionally, regression models showed a decrease in predictive accuracy from 2010 to 2020, as evidenced by lower R2 values for NDVI (0.82-0.37), soil salinity (0.77-0.38), groundwater (0.98-0.34), and soil moisture (0.96-0.24).