Michael T. Durand | USGS Science

USGS2024

Siting considerations for satellite observation of river discharge

With growing global capability for satellite measurement of river discharge (flow) comes a need to understand and reduce error in satellite-based discharge measurements. Satellite-based discharge estimates are based on measurements of water surface width, elevation, slope, and potentially velocity. Site selection is important for reducing error and uncertainty in both conventional and satellite-based discharge measurements because geomorphic river characteristics have strong control over the relationships between discharge and width, water surface elevation (or depth), slope, and velocity. A large ground-truth data set of 8,445 conventional hydraulic measurements, collected by acoustic Doppler current profilers at 503 stations in the United States, was developed and quality assured to examine correlation between river discharge and water surface width, depth, velocity, and cross-sectional area. A separate database of river surface slope and discharge time-series was developed from paired continuous monitoring stations to examine slope-discharge correlations. Results show that discharge correlates most strongly with velocity, cross-sectional area, depth, width, and slope, in that order. Uncertainty of satellite discharge estimates is affected by observed hydraulic variable and reach-specific variability in observed variable(s) characteristics including range of variability, georegistration accuracy, and stability over time of relationships between discharge and observed hydraulic variable.

Water Resources Research↗

USGS2021

Exploring the factors controlling the error characteristics of the Surface Water and Ocean Topography mission discharge estimates

The Surface Water and Ocean Topography (SWOT) satellite mission will measure river width, water surface elevation, and slope for rivers wider than 50-100 m. SWOT observations will enable estimation of river discharge by using simple flow laws such as the Manning-Strickler equation, complementing in-situ streamgages. Several discharge inversion algorithms designed to compute unobserved flow law parameters ( e.g. friction coefficient, bathymetry) have been proposed, but to date, a systematic assessment of factors controlling algorithm performance has not been conducted. Here, we assess the performance of the five algorithms that are expected to be used in the construction of the SWOT product. To perform this assessment, we used synthetic SWOT observations created with hydraulic model output corrupted with SWOT-like error. Prior information provided to the algorithms was purposefully limited to an estimate of mean annual flow (MAF), designed to produce a “worst case” benchmark. Prior MAF error was an important control on algorithm performance, but discharge estimates produced by the algorithms are less biased than the MAF; thus, the discharge algorithms improve on the prior. We show for the first time that accuracy and frequency of remote sensing observations are less important than prior bias, hydraulic variability among reaches, and flow law accuracy in governing discharge algorithm performance. The discharge errors and error sensitivities reported herein are a bounding benchmark, representing worst possible expected errors and error sensitivities. This study lays the groundwork to develop predictive power of algorithm performance, and thus map the global distribution of worst-case SWOT discharge accuracy.

Water Resources Research↗