Hydropower in the Himalayas is facing increasing uncertainty due to changing climate patterns and limitations in current prediction methods. This study combines two different approaches to better understand future water availability: one that uses global climate model projections (top-down) and another based on local data and machine learning simulations (bottom-up). We also consider future land use changes. Results show that climate change could lead to much more rainfall and warmer temperatures, especially under high-emission scenarios. This may increase water flow and energy production in snow-fed rivers near glaciers. However, bottom-up models predict less rainfall after the monsoon and lower streamflows, which could reduce hydropower output. Our analysis shows major differences between the two approaches, especially during periods of very high or very low flow. Snow-fed rivers are more sensitive to these changes than spring-fed ones. These findings show that using multiple methods together provides a fuller picture of what the future may hold and helps in making better, climate-resilient decisions for sustainable hydropower planning.