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The increasing severity of hydrological droughts in the Mediterranean basin related to climate change raises the need to understand the processes sustaining low flow. The purpose of this paper is to evaluate simple mixing model approaches, first to identify and then to quantify streamflow contribution during low-water periods. An approach based on the coupling of geochemical data with hydrological data allows the quantification of flow contributions. In addition, monitoring during the low-water period was used to investigate the drying-up trajectory of each geological reservoir individually. Data were collected during the summers of 2018 and 2019 on a Mediterranean river (Gardon de Sainte-Croix). The identification of the end-members was performed after the identification of a groundwater geochemical signature clustered according to the geological nature of the reservoir. Two complementary methods validate further the characterisation: rock-leaching experiments and unsupervised classification (k-means). The use of the end-member mixture analysis (EMMA) coupled with a generalised likelihood uncertainty estimate (GLUE) (G-EMMA) mixing model coupled with hydrological monitoring of the main river discharge rate highlights major disparities in the contribution of the geological units, showing a reservoir with a minor contribution in high flow becoming preponderant during the low-flow period. This finding was revealed to be of the utmost importance for the management of water resources during the dry period.

This paper describes an integrated, high-resolution dataset of hydro-meteorological variables (rainfall and discharge) concerning a number of high-intensity flash floods that occurred in Europe and in the Mediterranean region from 1991 to 2015. This type of dataset is rare in the scientific literature because flash floods are typically poorly observed hydrological extremes. Valuable features of the dataset (hereinafter referred to as the EuroMedeFF database) include (i) its coverage of varied hydro-climatic regions, ranging from Continental Europe through the Mediterranean to Arid climates, (ii) the high space–time resolution radar rainfall estimates, and (iii) the dense spatial sampling of the flood response, by observed hydrographs and/or flood peak estimates from post-flood surveys. Flash floods included in the database are selected based on the limited upstream catchment areas (up to 3000 km2), the limited storm durations (up to 2 days), and the unit peak flood magnitude. The EuroMedeFF database comprises 49 events that occurred in France, Israel, Italy, Romania, Germany and Slovenia, and constitutes a sample of rainfall and flood discharge extremes in different climates. The dataset may be of help to hydrologists as well as other scientific communities because it offers benchmark data for the identification and analysis of the hydro-meteorological causative processes, evaluation of flash flood hydrological models and for hydro-meteorological forecast systems. The dataset also provides a template for the analysis of the space–time variability of flash flood triggering rainfall fields and of the effects of their estimation on the flood response modelling. The dataset is made available to the public with the following DOI: https://doi.org/10.6096/MISTRALS-HyMeX.1493.

Mediterranean catchments are regularly affected by fast and flash floods. Numerous hydrologic models have been developed, and allow modelling of these floods. However, these approaches often concern average-size basins of a few hundred km2. At larger scales (>1000 km2), coupling of hydrologic and hydraulic models appears to be an adapted solution. This study has as its first objective the evaluation of the performances of a coupling of models for flood hydrograph modelling. Secondly, the coupling results are compared with those of other modelling options. The aim of these comparisons is to clear up the following points. (1) Is a simplified routing model (lag and route) as efficient as a full hydraulic model for the modelling of hydrographs, in the intermediary downstream part of the stream? (2) Is adding lateral inflows necessary for all studied events? (3) What is the impact of the qualities of upstream hydrologic modelling feeding the coupling? The coupling combines the SCS–LR (Soil Conservation Service–lag-and-route) hydrologic model of the ATHYS platform and the MASCARET 1-D hydraulic model based on full Saint-Venant equations. It is applied to the Gardon River basin (2040 km2) in the south of France. For the seven studied events, the results of the coupling are satisfactory, the calculated Nash indexes varying between 0.61 and 0.97. The comparisons with the other modelling options show the important role of the spatial distribution of rains during events: when rains are centered on the intermediary downstream part of the catchment, adding lateral inflows is necessary; when rains are more important in the upstream part, the quality of the hydrologic modelling upstream of the coupling has a strong impact. Furthermore, the used coupling of models seems well adapted for water rising and flooded area forecasting. The future developments of the tool will concentrate on this point.

A good knowledge of rainfall is essential for hydrological operational purposes such as flood forecasting. The objective of this paper was to analyze, on a relatively large sample of flood events, how rainfall-runoff modeling using an event-based model can be sensitive to the use of spatial rainfall compared to mean areal rainfall over the watershed. This comparison was based not only on the model's efficiency in reproducing the flood events but also through the estimation of the initial conditions by the model, using different rainfall inputs. The initial conditions of soil moisture are indeed a key factor for flood modeling in the Mediterranean region. In order to provide a soil moisture index that could be related to the initial condition of the model, the soil moisture output of the Safran-Isba-Modcou (SIM) model developed by Météo-France was used. This study was done in the Gardon catchment (545 km2) in South France, using uniform or spatial rainfall data derived from rain gauge and radar for 16 flood events. The event-based model considered combines the SCS runoff production model and the Lag and Route routing model. Results show that spatial rainfall increases the efficiency of the model. The advantage of using spatial rainfall is marked for some of the largest flood events. In addition, the relationship between the model's initial condition and the external predictor of soil moisture provided by the SIM model is better when using spatial rainfall, in particular when using spatial radar data with R2 values increasing from 0.61 to 0.72.

The Mediterranean area is prone to intense rainfall events triggering flash floods, characterized by very short response times that sometimes lead to dramatic consequences in terms of casualties and damages. These events can affect large territories, but their impact may be very local in catchments that are generally ungauged. These events remain difficult to predict and the processes leading to their generation still need to be clarified. The HyMeX initiative (Hydrological Cycle in the Mediterranean Experiment, 2010-2020) aims at increasing our understanding of the water cycle in the Mediterranean basin, in particular in terms of extreme events. In order to better understand processes leading to flash floods, a four-year experiment (2012-2015) was conducted in the Cévennes region (South-East) France as part of the FloodScale project. Both continuous and opportunistic measurements during floods were conducted in two large catchments (Ardèche and Gard rivers) with nested instrumentation from the hillslopes to catchments of about 1, 10, 100 to 1000 km2 covering contrasted geology and land use. Continuous measurements include distributed rainfall, stream water level, discharge, water temperature and conductivity and soil moisture measurements. Opportunistic measurements include surface soil moisture and geochemistry sampling during events and gauging of floods using non-contact methods: portable radars to measure surface water velocity or image sequence analysis using LS-PIV (Large Scale Particle Image Velocimetry). During the period 2012-2014, and in particular during autumn 2014, several intense events affected the catchments and provided very rich data sets. Data collection was complemented with modelling activity aiming at simulating observed processes. The modelling strategy was setup through a wide range of scales, in order to test hypotheses about physical processes at the smallest scales, and aggregated functioning hypothesis at the largest scales. During the project, a focus was also put on the improvement of rainfall fields characterization both in terms of spatial and temporal variability and in terms of uncertainty quantification. Rainfall reanalyses combining radar and rain gauges were developed. Rainfall simulation using a stochastic generator was also performed. Another effort was dedicated to the improvement of discharge estimation during floods and the quantification of streamflow uncertainties using Bayesian techniques. The paper summarizes the main results gained from the observations and the subsequent modelling activity in terms of flash flood process understanding at the various scales. It concludes on how the new acquired knowledge can be used for prevention and management of flash floods.

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