Flash-floods that occur in Mediterranean regions result in significant casualties and economic impacts. Remote imagebased techniques such as Large-Scale Particle Image Velocimetry (LSPIV) offer an opportunity to improve the accuracy of flow rate measurements during such events, by measuring the surface flow velocities. During recent floods of the Ardèche river, LSPIV performance tests were conducted at the Sauze-Saint-Martin gauging station without adding tracers. The rating curve is well documented, with gauged discharge ranging from 4.8 m 3 s −1 to 2700 m 3 s −1 , i.e., mean velocity from 0.02 m s −1 to 2.9 m s −1. Mobile LSPIV measurements were carried out using a telescopic mast with a remotely controlled platform equipped with a video camera. Also, LSPIV measurements were performed using the images recorded by a fixed camera. A specific attention was paid to the hydraulic assumptions made for computing the river discharge from the LSPIV surface velocity measurements. Simple solutions for interpolating and extrapolating missing or poor-quality velocity measurements, especially in the image far-field, were applied. Theoretical considerations on the depth-average velocity to surface velocity ratio (or velocity coefficient) variability supported the analysis of velocity profiles established from available gauging datasets, from which a velocity coefficient value of 0.90 (standard deviation 0.05) was derived. For a discharge of 300 m 3 s −1 , LSPIV velocities throughout the river crosssection were found to be in good agreement (±10%) with concurrent measurements by Doppler profiler (ADCP). For discharges ranging from 300 to 2500 m 3 s −1 , LSPIV discharges usually were in acceptable agreement (< 20%) with the rating curve. Detrimental image conditions or flow unsteadiness during the image sampling period led to larger deviations ranging 30-80%. The compared performances of the fixed and mobile LSPIV systems evidenced that for LSPIV stations, sampling images in isolated series (or bursts) is a better strategy than in pairs evenly distributed in time.

Stage measurement errors are generally overlooked when streamflow time series are derived from uncertain rating curves. We introduce an original method for propagating stage uncertainties due to two types of stage measurement errors: (i) errors of the stage read during the gauging and (ii) systematic and nonsystematic (independent) errors of the recorded stage time series. The error models are generic and can be used for any probabilistic rating curve estimation method that provides an ensemble of rating curves. The new method is applied to a range of six contrasting hydrometric stations in France. Uncertainty budgets quantifying the contribution of various error sources to the total streamflow uncertainty are computed and compared for streamflow time series averaged at time intervals from hour to year. A sensitivity analysis is conducted on the stage time series error model to identify the most sensitive parameters. The results are site specific, which illustrates the key role played by the properties of both the hydrometric site and the gauged catchment. Across the range of sites, stage errors of the gaugings are found to have limited impact on rating curve uncertainty, at least for gaugings performed in fair conditions. Nonsystematic errors in the stage time series have a negligible effect, generally. However, systematic stage errors should not be neglected. Over the six hydrometric stations in this study, the 95% uncertainty component reflecting stage systematic errors (from ±0.5 cm to ±6.8 cm) alone ranged from 4% to 12% of daily average streamflow, and from 1% to 3% of yearly average streamflow as sensors were assumed to be recalibrated every 30 days. Perspectives for improving and validating the streamflow uncertainty estimation techniques are eventually discussed.

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

[1] Fixed side-looking Doppler current profilers (H-ADCP) recently emerged as an innovating technique for the continuous monitoring of river discharges. The discharge can be computed from the flow velocities measured by the H-ADCP along a horizontal profile across the section. This paper reports a field assessment of the quality of velocities and discharges provided by a 3-narrow-beam Teledyne RD Instruments, Inc. (RDI) 300 kHz H-ADCP installed at the Saint-Georges gauging station (Saône river in Lyon, France). Reference velocity and discharge values were established from 18 conventional ADCP river gauging campaigns over an extended discharge range (100-1800 m 3 /s). The comparison with ADCP data revealed that H-ADCP velocity measurements were reliable (deviations <5%) in a near-field range only (60 m out of a 95 m total section width). In the far field (beyond 60 m), H-ADCP velocity measurements showed negative bias of up to À50% 90 m from the instrument. For section-averaged velocities lower than 0.4 m/s approximately, H-ADCP velocity measurements were found to be significantly underestimated over the whole cross section. The performances of several strategies (index velocity method and velocity profile method) for computing discharge were tested, compared, and discussed. For the velocity profile method, several profile laws and far-field extrapolation methods were implemented. Both methods gave acceptable discharge values (deviations <5% typically) excepted at low-flow conditions. The reasons why H-ADCP velocities were unacceptably biased low in the far field and for low flow conditions require further investigation in order to define correcting measures.

Stage‐fall‐discharge (SFD) rating curves are traditionally used to compute streamflow records at sites where the energy slope of the flow is variable due to variable backwater effects. We introduce a model with hydraulically interpretable parameters for estimating SFD rating curves and their uncertainties. Conventional power functions for channel and section controls are used. The transition to a backwater‐affected channel control is computed based on a continuity condition, solved either analytically or numerically. The practical use of the method is demonstrated with two real twin‐gauge stations, the Rhône River at Valence, France, and the Guthusbekken stream at station 0003⋅0033, Norway. Those stations are typical of a channel control and a section control, respectively, when backwater‐unaffected conditions apply. The performance of the method is investigated through sensitivity analysis to prior information on controls and to observations (i.e., available gaugings) for the station of Valence. These analyses suggest that precisely identifying SFD rating curves requires adapted gauging strategy and/or informative priors. The Madeira River, one of the largest tributaries of the Amazon, provides a challenging case typical of large, flat, tropical river networks where bed roughness can also be variable in addition to slope. In this case, the difference in staff gauge reference levels must be estimated as another uncertain parameter of the SFD model. The proposed Bayesian method is a valuable alternative solution to the graphical and empirical techniques still proposed in hydrometry guidance and standards.