Jeffrey Wade (Jet Propulsion Laboratory, Caltech, United States); Cédric David (Jet Propulsion Laboratory, Caltech, United States); Michael Durand (School of Earth Sciences, and Byrd Polar and Climate Research Center, The Ohio State University, United States); Renato P. M. Frasson (Jet Propulsion Laboratory, Caltech, United States); Tamlin Pavelsky (Department of Earth, Marine and Environmental Sciences, University of North Carolina, United States); Hind Oubanas (INRAE, France)

Despite only making up a fraction of total inland surface water storage, rivers are among Earth's most critical renewable and accessible freshwater resources. Yet, global estimates of river water storage magnitude and variability remain scarce and highly uncertain, largely due to limited understanding of surface water balance, unknown channel bathymetry, and sparse observations. Existing estimates rely on either uncertain hydrological routing models or spatially limited remote sensing observations. Here we present the first global observational dataset of reach-specific river volume variability derived from the first year (10-2023 to 09-2024) of the Surface Water and Ocean Topography (SWOT) mission’s science orbit at 126,674 reaches worldwide. Clear seasonal patterns and hotspots of variability emerge in major basins such as the Amazon, Ob, Orinoco, Congo, and Ganges-Brahmaputra. The global river volume anomaly observed by SWOT is estimated at 321.6 km³, approximately 30% lower than the lowest known modeled estimates for the same reaches. This discrepancy likely reflects both the Amazon’s 2024 record drought and previous limitations in our understanding of the shape of river beds. Additionally, this underlines key opportunities for improving the fundamental representation of surface water dynamics in global models.

Note: These authors contributed equally: Wade Jeffrey, Cerbelaud Arnaud.