Urbanization modifies hydrological processes by altering water balance components and increasing drought vulnerability. This study proposes an integrated multi-scale framework combining airborne laser scanning (ALS)-based terrain classification with satellite-derived hydrological datasets (GLDAS and GRACE/GRACE-FO) to assess urban water budget (WB) dynamics. ALS data were used to identify permeable and impervious surfaces, while time-series decomposition was applied to evaluate trends, seasonality, and variability of WB components. The results show that permeable surfaces dominate the study area (71.23%), limiting surface runoff. The WB demonstrates pronounced seasonal variability, with increased fluctuations after 2015, while long-term trends remain statistically insignificant. Surface sealing corrections for evapotranspiration and runoff strongly correspond with the original WB (R = 0.977 and R = 0.998), confirming precipitation as the main controlling factor. The proposed framework improves the representation of urban hydrological processes by linking detailed surface characteristics with large-scale climate observations and supports urban water management and climate adaptation planning.