International audienceThe Mediterranean region is frequently affected by heavy precipitation events associated with flash floods, landslides, and mudslides that cause hundreds of millions of euros in damages per year and often, casualties. A major field campaign was devoted to heavy precipitation and flash floods from 5 September to 6 November 2012 within the framework of the 10-year international HyMeX (Hydrological cycle in the Mediterranean Experiment) dedicated to the hydrological cycle and related high-impact events. The 2- month field campaign took place over the Northwestern Mediterranean Sea and its surrounding coastal regions in France, Italy, and Spain. The observation strategy of the field experiment was devised to improve our knowledge on the following key components leading to heavy precipitation and flash flooding in the region: i) the marine atmospheric flows that transport moist and conditionally unstable air towards the coasts; ii) the Mediterranean Sea acting as a moisture and energy source; iii) the dynamics and microphysics of the convective systems producing heavy precipitation; iv) the hydrological processes during flash floods. This article provides the rationale for developing this first HyMeX field experiment and an overview of its design and execution. Highlights of some Intense Observation Periods illustrate the potential of the unique datasets collected for process understanding, model improvement and data assimilation

Discharge time series in rivers and streams are usually based on simple stage-discharge relations calibrated using a set of direct stage-discharge measurements called gaugings. Bayesian inference recently emerged as a most promising framework to build such hydrometric rating curves accurately and to estimate the associated uncertainty. In addition to providing the rigorous statistical framework necessary to uncertainty analysis, the main advantage of the Bayesian analysis of rating curves arises from the quantitative assessment of (i) the hydraulic controls that govern the stage-discharge relation, and of (ii) the individual uncertainties of available gaugings, which often differ according to the discharge measurement procedure and the flow conditions. In this paper, we introduce the BaRatin method for the Bayesian analysis of stationary rating curves and we apply it to three typical cases of hydrometric stations with contrasted flow conditions and variable abundance of hydraulic knowledge and gauging data. The results exemplify that the thorough analysis of hydraulic controls and the quantification of gauging uncertainties are required to obtain reliable and physically sound results.

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.