<p>Flooding is a chronic disaster that occurs almost every year in various parts of the world. Among all environmental hazards, floods affect the largest number of people and pose a significant barrier to sustainable development. In northeast India, the state of Assam, entirely covered by the Brahmaputra and Barak basins, is severely affected by floods and erosion each year, leading to loss of life and widespread devastation. In this study, a hydrometeorological-based flood early warning system has been developed using space-based inputs and operationalized for all 35 districts of Assam, India. Semi-distributed hydrological models were built using the HEC-HMS model for 43 major tributaries of the Brahmaputra and Barak basins. Rainfall forecasts generated by the Weather Research and Forecasting (WRF) model were used as input for these hydrological models. The results indicate that the Root Mean Square Error (RMSE), Nash–Sutcliffe Efficiency (NSE), and correlation values fall within acceptable ranges for all 43 models. The developed framework has been in operation since 2009, and during the monsoon season, flood alerts are issued to the respective revenue circles and districts of Assam with an average lead time of 12–48 hours. Since the model’s inception, an average alert success rate of 88% has been achieved. The alerts generated using this methodology have proven beneficial to local authorities by helping reduce the impact of floods across the state of Assam.</p>