SWOT-fitted river bathymetry for global hydrodynamic models

We present a robust, global method to reconcile absolute water surface elevations (WSE) from the Surface Water and Ocean Topography (SWOT) mission with a large-scale hydrodynamic model by iteratively correcting river bathymetry. After removing systematic sensor and representativeness biases, we update riverbed elevations under DEM and min-depth feasibility constraints and interpolate corrections along reaches. Applied worldwide at 0.05° resolution over 2023–2025, the approach reduces the global median absolute WSE bias (3.10m→0.18m), preserving the same global median correlation (0.38). A modest ~4% increase in the standard deviation ratio (1.07→1.11) indicates slight variance inflation. Evaluation over 2015–2025 at 16,746 Hydroweb sites and 2123 GRDC gauges, restricted to reaches with updated beds, confirms substantially reduced bias, negligible changes in correlation and variability, and no significant change in global median discharge skill. When combined with models, this bias-aware bathymetry will enable a refined numerical representation of floods globally.