Michael T. Durand
Kevin Lanier
Colin Gleason
Konstantinos Andreadis
Mark Hageman
Robert Dudley
David M. Bjerklie
Hind Oubanas
Pierre-André Garambois
Pierre-Olivier Malaterre
Peirong Lin
Tamlin M. Pavelsky
Jerome Monnier
Craig Binkerhoff
Cedric H. David
Renato Frasson
2021
<div class="article-section__content en main"><p>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<span> </span><i>in-situ</i><span> </span>streamgages. Several discharge inversion algorithms designed to compute unobserved flow law parameters (<i>e.g.</i><span> </span>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.</p></div>
application/pdf
10.1029/2020WR028519
en
American Geophysical Union
Exploring the factors controlling the error characteristics of the Surface Water and Ocean Topography mission discharge estimates
article