International audienceThe 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 relativeresiduals 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

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Abstract. In this note we are interested in the modelling of sediment transport phenomena. We mostly focus on bedload transport and we do not consider suspension sediment processes. We first propose a numerical scheme for the classical Saint-Venant -Exner model. It is based on a relaxation approach for the whole system and it works with all sediment flux function. The stability of the scheme is investigated and some numerical tests are proposed. We exhibit that this coupled approach is more stable than the splitting approach that is mostly used in industrial softwares. Then we derive an original three layers model in order to overcome the difficulties that are encountered when using the classical Exner approach and we present a related relaxation model.

In this study, we investigate the effect of two key\ud uncertainty sources in one-dimensional (1D) water level calculations:\ud the roughness coefficient and the upstream discharge.\ud The work shows how these two uncertainties, separately\ud and together, propagate through the hydraulic model\ud and result in the uncertainty of water levels. The analysis is\ud conducted for the case of uniformflow in rectangular channels\ud and for steady gradually varied flow in real rivers. In the first\ud case, the exact probability density functions (PDFs) of water\ud levels are obtained analytically through the derived distribution\ud method, while in the second case, the output PDFs are\ud heuristically obtained via Monte Carlo simulations. The results\ud show that (1) the water level PDFs have a lower coefficient\ud of variation than the input PDFs due to the mathematical\ud nature of the relationship between input and output; (2) the\ud propagation of symmetric input distributions through the uniform\ud and steady flow equations determines asymmetric output\ud distributions, due to model nonlinearities. In particular, discharge\ud uncertainty leads to left skewed water level PDFs while\ud roughness uncertainty is responsible for output distributions\ud with heavier right tails. Therefore, in the case of roughness\ud uncertainty, the adoption of symmetrical PDFs would lead to\ud underestimation of high quantiles; (3) water level calculations\ud are more sensitive to uncertainty in the Strickler coefficient\ud rather than in upstream discharge, when the two variables are\ud characterised by the same level of uncertainty, and (4) roughness\ud and discharge uncertainties have a significant effect on\ud the predicted water levels, and they should not be neglected in\ud the practical applications, such as flood forecasting, floodplain\ud mapping and design of flood protection solutions