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.

Large Scale Particle Image Velocimetry (LS-PIV) is used to measure the surface flow velocities in a mountain stream during high flow conditions due to a reservoir release. A complete installation including video acquisition from a mobile elevated viewpoint and artificial flow seeding has been developed and implemented. The LS-PIV method was adapted in order to take into account the specific constraints of these high flow conditions. Using a usual LS-PIV data processing, significant variations of the water surface elevation were taken into consideration in the image rectification. An intensity threshold was applied to focus on artificial tracers without considering stationary waves and sun reflections on the flow surface. A site-specific float coefficient of 0.79 based on measured vertical velocity profiles was used to convert surface velocities into depth-averaged velocities. Comparison between LS-PIV assessments and 2Dh numerical calculations with the code Rubar20 allows verification and extrapolation of LS-PIV data. LS-PIV velocity measurements permit to assess discharges over the whole high flow event in agreement with leaded current-meter measurements performed at a downstream bridge

This paper investigates the potential of fast flood discharge measurements conducted with a mobile LSPIV device. LSPIV discharge measurements were performed during two hydrological events on the Arc River, a gravel-bed river in the French Alps: a flood greater than the 10-year return period flood in May, 2008, and a reservoir flushing release in June, 2009. The mobile LSPIV device consists of a telescopic mast with a remotely controlled platform equipped with a video camera. The digital video camera acquired sequences of images of the surface flow velocities. Ground Reference Points (GRPs) were positioned using a total station, for further geometrical correction of the images. During the flood peak, surface flow velocities up to 7 m/s and large floating objects prevented any kind of intrusive flow measurements. For the computation of discharge, the velocity coefficient was derived from available vertical velocity profiles measured by current meter. The obtained value range (0.72e0.79) is consistent with previous observations at this site and smaller than the usual default value (0.85) or values observed for deeper river sections (0.90 typically). Practical recommendations are drawn. Estimating stream discharge in high flow conditions from LSPIV measurements entails a complex measurement process since many parameters (water level, surface velocities, bathymetry, velocity coefficient, etc.) are affected by uncertainties and can change during the experiment. Sensitivity tests, comparisons and theoretical considerations are reported to assess the dominant sources of error in such measurements. The multiplicative error induced by the velocity coefficient was confirmed to be a major source of error compared with estimated errors due to water level uncertainty, free-surface deformations, number of image pairs, absence or presence of artificial tracers, and cross-section bathymetry profiles. All these errors are estimated to range from 1% to 5% whereas the velocity coefficient variability may be 10%e15% according to the site and the flow characteristics. The analysis of 36 LSPIV sequences during both events allowed the assessment of the flood discharges with an overall uncertainty less than 10%. A simple hydraulic law based on the geometry of the three sills of the Pontamafrey gauging station was proposed instead of the existing curve that is fitted on available gauging data. The high flow LSPIV discharge measurements indicated that this new curve is more accurate for high discharges since they are evenly distributed in a AE10% interval around it. These results demonstrate the interest of the remote stream gauging techniques together with hydraulic analysis for improving stageedischarge relationships and reducing uncertainties associated with fast flood discharges.

The applicability of a portable, commercially available surface velocity radar (SVR) for noncontact stream gauging was evaluated through a series of field-scale experiments carried out in a variety of sites and deployment conditions. Comparisons with various concurrent techniques showed acceptable agreement with velocity profiles, with larger uncertainties close to the banks. In addition to discharge error sources shared with intrusive velocity-area techniques, SVR discharge estimates are affected by floodinduced changes in the bed profile and by the selection of a depth-averaged to surface velocity ratio, or velocity coefficient (a). Cross-sectional averaged velocity coefficients showed smaller fluctuations and closer agreement with theoretical values than those computed on individual verticals, especially in channels with high relative roughness. Our findings confirm that a 5 0.85 is a valid default value, with a preferred sitespecific calibration to avoid underestimation of discharge in very smooth channels (relative roughness $ 0.001) and overestimation in very rough channels (relative roughness > 0.05). Theoretically derived and site-calibrated values of a also give accurate SVR-based discharge estimates (within 10%) for low and intermediate roughness flows (relative roughness 0.001 to 0.05). Moreover, discharge uncertainty does not exceed 10% even for a limited number of SVR positions along the cross section (particularly advantageous to gauge unsteady flood flows and very large floods), thereby extending the range of validity of rating curves.

New communication and digital image technologies have enabled the public to produce large quantities of flood observations and share them through social media. In addition to flood incident reports, valuable hydraulic data such as the extent and depths of inundated areas and flow rate estimates can be computed using messages, photos and videos produced by citizens. Such crowdsourced data help improve the understanding and modelling of flood hazard. Since little feedback on similar initiatives is available, we introduce three recent citizen science projects which have been launched independently by research organisations to quantitatively document flood flows in catchments and urban areas of Argentina, France, and New Zealand. Key drivers for success appear to be: a clear and simple procedure, suitable tools for data collecting and processing, an efficient communication plan, the support of local stakeholders, and the public awareness of natural hazards.

Abstract. This paper presents a coupled observation and modelling strategy aiming at improving the understanding of processes triggering flash floods. This strategy is illustrated for the Mediterranean area using two French catchments (Gard and Ardèche) larger than 2000 km 2 . The approach is based on the monitoring of nested spatial scales: (1) the hillslope scale, where processes influencing the runoff generation and its concentration can be tackled; (2) the small to medium catchment scale (1-100 km 2 ), where the impact of the network structure and of the spatial variability of rainfall, landscape and initial soil moisture can be quantified; (3) the larger scale (100-1000 km 2 ), where the river routing and flooding processes become important. These observations are part of the HyMeX (HYdrological cycle in the Mediterranean EXperiment) enhanced observation period (EOP), which will last 4 years (2012)(2013)(2014)(2015). In terms of hydrological modelling, the objective is to set up regional-scale models, while addressing small and generally ungauged catchments, which represent the scale of interest for flood risk assessment. Topdown and bottom-up approaches are combined and the models are used as "hypothesis testing" tools by coupling model development with data analyses in order to incrementally evaluate the validity of model hypotheses. The paper first presents the rationale behind the experimental set-up and the instrumentation itself. Second, we discuss the associated modelling strategy. Results illustrate the potential of the approach in advancing our understanding of flash flood processes on various scales.

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

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