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.

[1] Intense rain events frequently result in devastating flash floods in Mediterranean regions. To improve the understanding and prediction of these phenomena, the Cévennes-Vivarais Mediterranean Hydrometeorological Observatory (CVMHO) was set up in 2000. The observation strategies deployed include the detailed and long-lasting (>10 years) observation in the Cévennes-Vivarais region (France) using both operational observation systems and research instrumentation. The present note describes the procedures implemented by CVMHO to critically analyze and generate hydrometeorological products for research. The related data can be viewed or downloaded via the Système d'Extraction et de Visualisation des Données de l'Observatoire en Ligne (SEVnOL) interface on the CVMHO Web site.

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Spatial and temporal scales of occurrence of flash floods, combined with the space and time scales of conventional measurement networks of rain and discharge, make these events particularly difficult to observe. The effective documentation of flash floods requires post-flood survey strategies encompassing accurate radar rainfall estimation, field observations of the geomorphic processes associated with the flood, indirect reconstruction of peak discharges and interviews of eyewitnesses. This paper describes the methods applied and the results achieved in the survey of a flash flood that occurred on 18th September 2007 in the Selška Sora watershed (Western Slovenia). Hydrometeorological analyses of the storm are based on radar reflectivity observations. The documentation of the flash flood reveals high peak flood discharges and a complex flood response. Peak discharges were estimated at 22 cross sections, with drainage areas ranging from 0·2 to 147 km 2 . Among the lessons learned from the field study of the Selška Sora flash flood, there are three key conclusions that can inform similar studies. Firstly, geomorphological surveys are an important prerequisite for flood discharge reconstruction in mountainous watersheds affected by debris flow and intense sediment transport. Secondly, the accounts of eyewitnesses of the flood provide a unique contribution to event reconstruction. Finally, it is necessary to have quality controlled weather radar data, which may permit coupling field observations with rainfall-runoff modelling.

International audienceThis paper describes and illustrates a methodology to conduct postflood investigations based on interdisciplinary collaboration between social and physical scientists. The method, designed to explore the link between crisis behavioral response and hydrometeorological dynamics, aims at understanding the spatial and temporal capacities and constraints on human behaviors in fast-evolving hydrometeorological conditions. It builds on methods coming from both geosciences and transportations studies to complement existing post-flood field investigation methodology used by hydrometeorologists. The authors propose an interview framework, structured around a chronological guideline to allow people who experienced the flood firsthand to tell the stories of the circumstances in which their activities were affected during the flash flood. This paper applies the data collection method to the case of the 15 June 2010 flash flood event that killed 26 people in the Draguignan area (Var, France). As a first step, based on the collected narratives, an abductive approach allowed the identification of the possible factors influencing individual responses to flash floods. As a second step, behavioral responses were classified into categories of activities based on the respondents' narratives. Then, aspatial and temporal analysis of the sequences made of the categories of action to contextualize the set of coping responses with respect to local hydrometeorological conditions is proposed. During this event, the respondents mostly follow the pace of change in their local environmental conditions as the flash flood occurs, official flood anticipation being rather limited and based on a large-scale weather watch. Therefore, contextual factors appear as strongly influencing the individual's ability to cope with the event in such a situation

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Radar quantitative precipitation estimates (QPEs) were assessed using reference values established by means of a geostatistical approach. The reference values were estimated from raingauge data using the block kriging technique, and the reference meshes were selected on the basis of the kriging estimation variance. Agreement between radar QPEs and reference rain amounts was shown to increase slightly with the space-time scales. The statistical distributions of the errors were modelled conditionally with respect to several factors using the GAMLSS approach. The conditional bias of the errors presents a complex structure that depends on the space-time scales and the considered geographical sub-domains, while the standard deviation of the errors has a more homogeneous behaviour. The estimation standard deviation of the reference rainfall and the standard deviation of the errors between radar and reference rainfall were found to have the same magnitude, indicating the limitations of the available network in terms of providing accurate reference values for the spatial scales considered (5-100 km 2 ).