Global scale river discharge and mean depth from radar altimetry and model

Rivers are vital for water security, yet scalable freshwater monitoring and global knowledge of river mean depth and discharge remains limited by sparse in situ data, satellite observations of river surface only and global river flow estimations relying on models with insufficient hydraulic information. Without a robust global product for river bathymetry derived from satellite altimetry, large-scale hydrodynamic assessments remain limited. Here we present a near-global dataset of discharge rating curves, and river mean depths at 26 000+ river locations, integrating satellite water elevation observations with a global discharge monthly reanalysis over 30 years. Climatic anomaly-filtering and Bayesian calibration provide robust river elevation-discharge relationships yielding median KGE between rated and modeled discharge of 0.41. We produce reliable discharge estimates, validated against public discharge databases, and river mean depth derived from multiple satellite altimetry missions across diverse hydroclimates and flow conditions, along with uncertainty. These results offer a scalable, transferable framework for deriving hydraulic geometry relationships from satellite-model synergies. The approach is likely to improve with the emergence of future high-resolution missions, as well as advancements in global hydrology models and datasets.