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Water resource management in regions with complex topography, such as Uttarakhand, requires precise estimation and spatial characterization of water yield. This study assesses water yield across the state of Uttarakhand using the Budyko Framework, land use/land cover (LULC) data, and Google Earth Engine (GEE) as a cloud-based geospatial platform for the analysis. This study integrates hydrological modelling with high-resolution climatic and land cover datasets to estimate WY at district and watershed levels. Our results highlight significant spatial variability in water yield, with Chamoli 6.30 billion cubic meters (BCM), Pithoragarh (5.75 BCM), and Uttarkashi (5.27 BCM) exhibiting the highest district-wise yields, while Haridwar (0.95 BCM) and Udham Singh Nagar (1.01 BCM) showed the lowest. Watershed-level assessment identified Basin 1 and Basin 6 as major contributors, each generating 8.79 BCM of water yield, whereas Basin 7 demonstrated the lowest yield (0.12 BCM). LULC analysis revealed that tree cover, occupying 56.13% of the total area, contributed the highest WY (20.93 BCM), followed by grassland and cropland. Conversely, barren lands, built-up areas, and herbaceous wetlands exhibited minimal contributions. Surplus and deficit zone classification showed that approximately 24.37% of the area falls under severe water deficit, while 5.67% experiences severe water surplus, indicating pronounced hydrological imbalances. The findings highlight the utility of the Budyko Framework and GEE in large-scale hydrological assessments and their potential for improving water resource management strategies. This study provides critical insights for policymakers and stakeholders to prioritize watershed conservation, mitigate water deficits, and enhance water security in Uttarakhand. This study also highlights the importance of forest conservation and sustainable land management in maintaining hydrological balance in mountainous regions by linking LULC dynamics with water yield and has implications for local and regional water resource management.
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