The Surface Water and Ocean Topography (SWOT) mission will vastly expand measurements of global rivers, providing critical new data sets for both gaged and ungaged basins. SWOT discharge products (available approximately 1 year after launch) will provide discharge for all river that reaches wider than 100 m. In this paper, we describe how SWOT discharge produced and archived by the US and French space agencies will be computed from measurements of river water surface elevation, width, and slope and ancillary data, along with expected discharge accuracy. We present for the first time a complete estimate of the SWOT discharge uncertainty budget, with separate terms for random (standard error) and systematic (bias) uncertainty components in river discharge time series. We expect that discharge uncertainty will be less than 30% for two-thirds of global reaches and will be dominated by bias. Separate river discharge estimates will combine both SWOT and in situ data; these "gage-constrained" discharge estimates can be expected to have lower systematic uncertainty. Temporal variations in river discharge time series will be dominated by random error and are expected to be estimated within 15% for nearly all reaches, allowing accurate inference of event flow dynamics globally, including in ungaged basins. We believe this level of accuracy lays the groundwork for SWOT to enable breakthroughs in global hydrologic science. Plain Language SummaryThe Surface Water and Ocean Topography (SWOT) satellite mission was launched on 15 December 2022. SWOT is designed to produce estimates of river discharge on many rivers where no in situ discharge measurements are currently available. This paper describes how SWOT discharge estimates will be created, and their expected accuracy. SWOT discharge will be estimated using simple flow laws that combine SWOT measurements of river water elevation above sea level, river width, and river slope, with ancillary data such as river bathymetry. We expect that discharge uncertainty will be less than 30% for DURAND ET AL.

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The forthcoming Surface Water and Ocean Topography (SWOT) mission will vastly expand measurements of global rivers, providing critical new datasets for both gaged and ungaged basins. SWOT discharge products will provide discharge for all river reaches wider than 100 m, but at lower accuracy and temporal resolution than what is possible in situ. In this paper, we describe how SWOT discharge produced and archived by the US and French space agencies will be computed from measurements of river water surface elevation, width, and slope and ancillary data, along with expected discharge accuracy. We present here for the first time a complete estimate of SWOT discharge uncertainty budget, with separate terms for random (standard error) and systematic (bias) uncertainty components in river discharge timeseries. We expect that discharge uncertainty will be less than 30% for two thirds of global reaches and will be dominated by bias. Separate river discharge estimates will combine both SWOT and in situ data; these "gage constrained" discharge estimates can be expected to have lower systematic uncertainty. Temporal variations in river discharge timeseries will be dominated by random error and are expected to be estimated to within 15% for nearly all reaches, allowing accurate inference of event flow dynamics globally, including in ungaged basins. We believe this level of accuracy lays the groundwork for SWOT to enable breakthroughs in global hydrologic science.

Rivers and lakes serve as vital sources of freshwater for ecosystems and civilizations worldwide (Everard & Powell, 2002;Macklin & Lewin, 2015;Yevjevich, 1992). While rivers and lakes are often treated as separate systems in large-scale remote sensing studies, their hydrologies are intimately related such that hydrologic changes in one water body type can be used to constrain the hydrology of an adjacent water body of a different type (Vörösmarty et al., 2000). For example, the relationship between inflow and outflow of a natural lake or human-made reservoir (hereinafter collectively referred to as a "lake" unless otherwise stated) can control the lake's volumetric water storage and water surface elevation. Natural lakes located along river networks can attenuate local discharge downstream and actively managed reservoirs can significantly affect downstream flow regime by altering the natural timing and quantity of river discharge (Doll et al., 2009;Wang et al., 2017;Yang et al., 2022). Reservoir inflow and outflow dynamics are key for modeling reservoir operations, which can be difficult to simulate from water mass balance alone, especially at the continental to global scale (Cohen et al., 2014;Harrigan et al., 2020). At these large scales, understanding of the hydrologic interplay between rivers and lakes has largely been developed through the analysis of streamflow gauges located on lake inflows and outflows (i.e., the rivers flowing into and out of a lake), as well as lake-level gauges (Batalla et al., 2004;Shiklomanov & Lammers, 2009;Yang et al., 2008). Unfortunately, most lakes do not have publicly available gauge data and those that do are primarily located on large lakes or in a few geographically isolated regions (

Long-term, continuous, and real-time streamflow records are essential for understanding and managing freshwater resources. However, we find that 37% of publicly available global gauge records (N=45,837) are discontinuous and 77% of gauge records do not contain real-time data. Historical periods of social upheaval are associated with declines in gauge data availability. Using river width observations from Landsat and Sentinel-2 satellites, we fill in missing records at 2,168 gauge locations worldwide with more than 275,000 daily discharge estimates. This task is accomplished with a river width-based rating curve technique that optimizes measurement location and rating function (median relative bias=1.4%, median Kling-Gupta efficiency=0.46). The rating curves presented here can be used to generate near real-time discharge measurements as new satellite images are acquired, improving our capabilities for monitoring and managing river resources.