Mainstream river discharge dataset of the Yangtze River estimated from SWOT satellite observations

River discharge is a fundamental indicator of basin-scale hydrological and ecological processes, yet its spatially continuous estimation remains challenging due to the sparse distribution of in situ gauge networks and the limitations of traditional satellite altimetry. The launch of the Surface Water and Ocean Topography (SWOT) mission provides unprecedented opportunities to retrieve river hydraulic variables at high spatial resolution; however, existing discharge algorithms still suffer from excessive reach-scale averaging and simplified geometric assumptions that obscure local hydraulic heterogeneity.This study develops a spatially explicit, remote sensing–driven discharge inversion framework based on an Effective Hydraulic Model (EHM), which reformulates the classical Manning equation to ensure compatibility with satellite-observable variables. By integrating SWOT-derived water surface elevation and slope with Sentinel-2–based river width constrained by OpenStreetMap centerlines, the model enables grid-based, reach-scale discharge estimation along the main stem of the Yangtze River. Model parameters are calibrated using in situ observations, yielding robust performance with Nash–Sutcliffe efficiency values predominantly exceeding 0.8 across multiple stations.The proposed framework effectively captures seasonal discharge dynamics and spatial variability associated with channel morphology, backwater effects, and anthropogenic influences. Correlation analyses further reveal strong linkages between discharge variability and meteorological, topographic, and vegetation-related factors. These results demonstrate the capability of multi-source satellite observations to support physically grounded, spatially continuous discharge monitoring, providing a scalable methodological foundation for hydrological analysis and water-resources management in large and ungauged river basins.