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International audience; Repeated measures experiments can be conducted to empirically estimate the uncertainty of a stream gauging method, such as the widespread moving‐boat acoustic Doppler current profilers (ADCPs) approach. Previous ADCP repeated measures experiments, also known as interlaboratory comparisons, provided a credible range of uncertainty estimates reflecting the quality of the site conditions. However, the method, which is a one‐way analysis of variance, only addresses the uncertainty of one lumped factor that combines several distinct factors: instrument, operator, procedure, and cross‐section effects. To decompose the uncertainty of ADCP streamflow measurements due to cross‐section selection and team effects, a large repeated measures experiment has been conducted in the Taurion River (France). The experiment design was crossed and balanced, with two sets of 24 teams circulated over two sets of 12 cross sections. A constant flow rate was released from a dam, located immediately upstream of the experimental site. Prior to the statistical analysis, a data quality review was performed using the U.S. Geological Survey QRev software to clean the data set from avoidable errors and to homogenize the discharge computations. A two‐way analysis of variance was applied to quantify the cross‐section effect, the team effect, and their interaction, which was found to dominate the pure cross‐section effect. It was then possible to predict the average uncertainty of multiple‐transect ADCP discharge measurements, depending on the number of teams, cross sections, and repeated transects included in the discharge average. The method opens interesting avenues for documenting difficult‐to‐estimate uncertainty sources of stream gauging techniques in other measuring conditions, especially the most adverse ones.

HMEM, Durham, New Hampshire, USA, 09-/07/2017 - 12/07/2017; International audience; Stage-discharge rating curves are used to relate streamflow discharge to continuously measured river stage readings to create a continuous record of streamflow discharge. The stage-discharge relationship is estimated and refined using discrete streamflow measurements over time, during which both the discharge and stage are measured. There is uncertainty in the resulting rating curve due to multiple factors including the curve-fitting process, assumptions on the form of the model used, fluvial geomorphology of natural channels, and the approaches used to extrapolate the rating equation beyond available observations. This rating curve uncertainty leads to uncertainty in the streamflow timeseries, and therefore to uncertainty in predictive models that use the streamflow data. Many different methods have been proposed in the literature for estimating rating curve uncertainty, differing in mathematical rigor, in the assumptions made about the component errors, and in the information required to implement the method at any given site. This study describes the results of an international experiment to test and compare streamflow uncertainty estimation methods from 7 research groups across 9 institutions. The methods range from simple LOWESS fits to more complicated Bayesian methods that consider hydraulic principles directly. We evaluate these different methods when applied to three diverse gauging stations using standardized information (channel characteristics, hydrographs, and streamflow measurements). Our results quantify the resultant spread of the stage-discharge Quantifying the uncertainty of discharge measurements (or "gaugings") is a challenge in the hydrometric community. A useful tool to empirically estimate the uncertainty of a gauging method is the field inter-laboratory experiment (Le Coz et al., 2016). Previous inter-laboratory experiments conducted in France (in 2009, 2010, 2011 and 2012) showed that the expanded uncertainty (with a probability level of 95%) of an ADCP gauging made of six successive transects is typically around 5% under optimum site conditions (straight reach, uniform and smooth streambed cross-section, homogeneous flow, etc.) and may be twice higher under poorer site conditions. In practice, the selected cross-section does not always match all quality requirements which may result in larger uncertainty. However, the uncertainty due to site selection is very difficult to estimate with predictive equations. From 9 to 10 November 2016, 50 teams from 8 different countries, using 50 ADCPs simultaneously, conducted more than 600 discharge measurements in steady flow conditions (~14 m3/s released by a dam). 26 cross-sections with various shapes and flow conditions were distributed over 500 meters along the Taurion River at Saint-Priest-de-Taurion, France. A specific experiment protocol, which consisted of circulating every team over half of the cross-sections, was implemented in order to quantify the impact of site selection on the discharge measurement uncertainty. Beyond the description of the experiments, uncertainty estimates are presented. The overall expanded uncertainty of a 6-transect ADCP gaugings (duration around 720 seconds) is estimated to be around 6%.The uncertainty of the discharge measurements varies among the cross-sections. These variations are well correlated to the expert judgment on the cross-section quality made by each team. First results seem to highlight a relation between uncertainty computed for each cross-section and criteria such as flow shallowness and measured discharge ratio. Further investigations are necessary to identify the criteria related to error sources that are possibly meaningful for categorizing measurement conditions and site selection. Moreover, experimental uncertainty and the uncertainty predicted by analytical methods such as QRev, QUant, OURSIN, RiverFlowUA or QMSys software will be compared.

International audience; While the application of uncertainty propagation methods to hydrometry is still challenging, in situ collaborative interlaboratory experiments are a valuable tool for empirically estimating the uncertainty of streamgauging techniques in given measurement conditions. We propose a simple procedure for organizing such experiments and processing the results according to the authoritative ISO standards related to interlaboratory experiments, which are of common practice in many metrological fields. Beyond the computation and interpretation of the results, some issues are discussed as regards: the estimation of the streamgauging technique bias in the absence of accurate enough discharge references in rivers; the uncertainty of the uncertainty estimates, according to the number of participants and repeated measurements; the criteria related to error sources which are possibly meaningful for categorizing measurement conditions. The interest and limitations of the in situ collaborative interlaboratory experiments are exemplified by an application to the hydro-acoustic profiler (ADCP) streamgauging technique conducted in 2010 at two different sites downstream of Génissiat hydropower plant in the Rhône river, France. Typically, the expanded uncertainty (with a probability level of 95%) of the average discharge over 6 successive transects varied from +/-5% at one site with favourable conditions to +/-9% at the other site due to unstable flow conditions.