Climate-Driven Snow Cover Dynamics in the Hindu Kush–Himalayan (HKH) Region and Its Implications for Natural Hazard Modeling Using Multi-Satellite Hydrometeorological Data

Earth’s frozen water reserves are inherently dynamic and play a critical role in the hydrological processes of complex, dynamic river basins. Climate-driven environmental changes have led to a significant decrease in the area and duration of seasonal snow cover, particularly in the high-altitude Asian Water Tower (Himalaya). Snow cover estimates are challenging in the high-altitude Hindu Kush-Himalayan (HKH) region, which is a core contributor to water resources that sustain the environment and diverse downstream ecosystems that support more than half of the Earth’s population. This study quantifies the snow cover area over the period of 1993–2023 across the basins of ten major snow- and rainfall-dominated rivers in the HKH region using Landsat-based Normalized Difference Snow Index (NDSI), SNOMAP, Blue Snow Threshold (BST), and Dozier and Painter methods. Additionally, this study used 178 strategically positioned points across the HKH region to explore the relationship between snow cover dynamics and environmental factors such as temperature, precipitation, and greenhouse gas concentrations. The study observed significant temporal and spatial variations in snow cover, driven by regional climatic conditions and anthropogenic influences. The results revealed declining snow cover trends of 2793.15, 2108.86, 1199.49, 247.51, 230.34, and 169.39 km2/year for the Amu Darya, Indus, Yangtze, Tarim, Mekong, Ganges, and Brahmaputra River basins, respectively. Conversely, the Salween, Yellow, and Irrawaddy River basins showed a slight increase of 1002.66, 147.06, and 20.86 km2/year, respectively. These opposing trends underline the vulnerability of snow mass to water supply and hydropower scheduling, stressing the urgent need for integrated, long-term satellite and ground-based observation platforms, as well as robust hydrological and glaciological modeling. A strategic blend of remotely sensed snow cover data and locally calibrated climate and land-use records will empower decision-makers to predict water security threats and refine reservoir operation guidelines, thereby sustaining both socio-economic and ecosystem services across the principal river corridors.