This study proposes a rainfall-runoff modeling framework for the Teesta River watershed, a glacial and topographically challenging region in the eastern Himalayas. This study used Google Earth Engine (GEE), a web-based planetary-scale platform that allows us to use high spatial resolutions of datasets in the analysis or integration process. The data used in this study included CHIRPS daily precipitation, 30-m land use/land cover, and digital elevation dataset for the period of 2022–2024. The runoff estimates were developed using a remote sensing-based adaptation of the Soil Conservation Service Curve Number (SCS-CN) method for runoff estimation. This study shows that most runoff response is attributed to steep mountainous and glacial regions, and urban land had little contribution to runoff because of the limited coverage of urban land in the total area of the watershed extent. This study shows a highly correlated linear relationship between total rainfall inputs and total runoff outputs of the Teesta River watershed with a coefficient of determination (R2) of 0.934443. These findings indicate the important role terrain and glacial processes have in terms of hydrological responses across the watershed and illustrate the benefits associated with using cloud-based geospatial platforms that promote efficient, scalable, and reproducible modeling in remote, high-elevation areas with limited datasets.