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USGS2025

Launching into societal benefits from the Surface Water and Ocean Topography (SWOT) mission

The 10th Surface Water and Ocean Topography (SWOT) Applications Meeting, held one year after the satellite's launch, highlighted significant milestones in mission progress and showcased the innovative work of SWOT Early Adopters (EA) using mission data products. Over 100 participants from diverse sectors convened to discuss operational applications leveraging SWOT's unprecedented water surface measurements. The meeting emphasized applied science efforts to enhance hydrology and oceanographic models. This summary highlights the breadth of operational and private-sector uses of SWOT data, emphasizing its potential to drive new innovations and deliver societal benefits, such as improved water resource management, flood prediction, and climate resilience.

Water Resources Research↗

USGS2016

An intercomparison of remote sensing river discharge estimation algorithms from measurements of river height, width, and slope

The Surface Water and Ocean Topography (SWOT) satellite mission planned for launch in 2020 will map river elevations and inundated area globally for rivers >100 m wide. In advance of this launch, we here evaluated the possibility of estimating discharge in ungauged rivers using synthetic, daily ‘‘remote sensing’’ measurements derived from hydraulic models corrupted with minimal observational errors. Five discharge algorithms were evaluated, as well as the median of the five, for 19 rivers spanning a range of hydraulic and geomorphic conditions. Reliance upon a priori information, and thus applicability to truly ungauged reaches, varied among algorithms: one algorithm employed only global limits on velocity and depth, while the other algorithms relied on globally available prior estimates of discharge. We found at least one algorithm able to estimate instantaneous discharge to within 35% relative root-mean-squared error (RRMSE) on 14/16 nonbraided rivers despite out-of-bank flows, multichannel planforms, and backwater effects. Moreover, we found RRMSE was often dominated by bias; the median standard deviation of relative residuals across the 16 nonbraided rivers was only 12.5%. SWOT discharge algorithm progress is therefore encouraging, yet future efforts should consider incorporating ancillary data or multialgorithm synergy to improve results

Water Resources Research↗