Multi‐Source Satellite Data Fusion Enhances the Accuracy of Water Level Retrieval and Discharge Estimation in the Yellow River

Rivers are crucial for global water resource regulation and ecological conservation, with water level and discharge data serving as essential parameters for river hydrological monitoring. However, conventional hydrological stations have limited representativeness and spatial coverage, hindering basin‐scale water cycle analysis. To address these issues, we developed an integrated retrieval framework based on multi‐source satellite observations, without requiring cross‐sectional geometric measurements, enabling low‐parameter hydraulic discharge estimation and assessment of its behaviour under contrasting river conditions. By combining ICESat‐1&2 and CryoSat‐2 to retrieve water levels while concurrently incorporating channel morphology parameters extracted from Landsat and Sentinel‐1 imagery, we established stage‐discharge rating curves calibrated against historical hydrological records and constructed an optimized Manning's equation that accounts for river‐width dynamics, applying to typical reaches of the Yellow River (river widths of 0.3 to 1.3 km). Seasonal regulation introduced further optimizes model parameters, enabling a more accurate capture of the dynamic impact of sediment transport on channel roughness. Our method achieved the root‐mean‐square error (RMSE) between satellite‐derived water levels and those measured at hydrological stations, ranging from 0.26 to 0.58 m, demonstrating strong spatiotemporal consistency. For discharge estimation, the stage‐discharge curves yielded Nash‐Sutcliffe Efficiency (NSE) values of 0.82 and coefficient of determination ( R 2 ) of 0.88, whereas Manning's equation achieved NSE of 0.83 and R 2 of 0.89, indicating only a modest overall advantage of the latter, but with clearer improvements in morphodynamically active downstream reaches. Our study demonstrates that multisource satellite observations integrating lidar, radar, and optical data can substantially enhance the accuracy of water level and discharge estimation in narrow, sediment‐laden river channels, while also clarifying reach‐scale variations in the hydromorphological controls governing the relation among stage, river width, and discharge.