Water temperature modeling in the Garonne River (France)

Stream water temperature is one of the most important parameters for water quality and ecosystem studies. Temperature can influence many chemical and biological processes and therefore impacts on the living conditions and distribution of aquatic ecosystems. Simplified models such as statistical models can be very useful for practitioners and water resource management. The present study assessed two statistical models – an equilibrium-based model and stochastic autoregressive model with exogenous inputs – in modeling daily mean water temperatures in the Garonne River from 1988 to 2005. The equilibrium temperature-based model is an approach where net heat flux at the water surface is expressed as a simpler form than in traditional deterministic models. The stochastic autoregressive model with exogenous inputs consists of decomposing the water temperature time series into a seasonal component and a short-term component (residual component). The seasonal component was modeled by Fourier series and residuals by a second-order autoregressive process (Markov chain) with use of short-term air temperatures as exogenous input. The models were calibrated using data of the first half of the period 1988–2005 and validated on the second half. Calibration of the models was done using temperatures above 20 ◦C only to ensure better prediction of high temperatures that are currently at stake for the aquatic conditions of the Garonne River, and particularly for freshwater migrating fishes such as Atlantic Salmon (Salmo salar L.). The results obtained for both approaches indicated that both models performed well with an average root mean square error for observed temperatures above 20 ◦C that varied on an annual basis from 0.55 ◦C to 1.72 ◦C on validation, and good predictions of temporal occurrences and durations of three temperature threshold crossings linked to the conditions of migration and survival of Atlantic Salmon

Data assimilation method for real-time flash flood forecasting using a physically based distributed model

The MARINE model (Roux et al, 2011) is a physically based distributed model dedicated to real time flash flood forecasting on small to medium catchments. The infiltration capacity is evaluated by the Green and Ampt equation and the surface runoff calculation is divided into two parts: the land surface flow and the flow in the drainage network both based on kinematic wave hypothesis. In order to take into account rainfall spatial-temporal variability as well as the various behaviours of soil types among the catchment, the model is spatially distributed, which can also help to understand the flood driving processes. The model integrates remote sensing data such as the land coverage map with spatial resolution adapted to hydrological scales. Minimal data requirements for the model are: the Digital Elevation Model describing catchment topography and the location and description of the drainage network. Moreover some parameters are not directly measurable and need to be calibrated. Most of the sources of uncertainties can be propagated thanks to variational method (Castaings et al, 2009) and finally help to determine time dependent uncertainty intervals. This study also investigates the methodology developed for real-time flash flood forecasting using the MARINE model and data assimilation techniques. According to prior sensitivity analyses and calibrations, parameters values were determined as constants or initial guess. Then a data assimilation method called the adjoint state method is used to update some of the most sensitive parameters to improve accuracy of discharges predictions. The forecast errors are evaluated as a function of lead time and discussed from an operational point of view. Multiple strategies in term of updatable parameters set, length of time window, parameters bounds and observation threshold used to trigger the assimilation method are discussed regarding accuracy, robustness and real-time feasibility

Characterization of process-oriented hydrologic model behavior with temporal sensitivity analysis for flash floods in Mediterranean catchments

This paper presents a detailed analysis of 10 flash flood events in the Mediterranean region using the distributed hydrological model MARINE. Characterizing catchment response during flash flood events may provide new and valuable insight into the dynamics involved for extreme catchment response and their dependency on physiographic properties and flood severity. The main objective of this study is to analyze flash-flood-dedicated hydrologic model sensitivity with a new approach in hydrology, allowing model outputs variance decomposition for temporal patterns of parameter sensitivity analysis. Such approaches enable ranking of uncertainty sources for nonlinear and nonmonotonic mappings with a low computational cost. Hydrologic model and sensitivity analysis are used as learning tools on a large flash flood dataset. With Nash performances above 0.73 on average for this extended set of 10 validation events, the five sensitive parameters of MARINE process-oriented distributed model are analyzed. This contribution shows that soil depth explains more than 80% of model output variance when most hydrographs are peaking. Moreover, the lateral subsurface transfer is responsible for 80% of model variance for some catchment-flood events’ hydrographs during slow-declining limbs. The unexplained variance of model output representing interactions between parameters reveals to be very low during modeled flood peaks and informs that model parsimonious parameterization is appropriate to tackle the problem of flash floods. Interactions observed after model initialization or rainfall intensity peaks incite to improve water partition representation between flow components and initialization itself. This paper gives a practical framework for application of this method to other models, landscapes and climatic conditions, potentially helping to improve processes understanding and representation

Understanding Wage Floor Setting in Industry-Level Agreements: Evidence from France

This paper examines empirically how industry-level wage floors are set in French industry-level wage agreements and how the national minimum wage (NMW) interacts with industry-level wage bargaining. For this, we use a unique dataset containing about 50,000 occupation-specific wage floors in 365 French industries over the period 2007-2015. We find that the NMW has a significant impact on the seasonality and on the timing of the wage bargaining process. Inflation, past sectoral wage increases and real NMW increases are the main drivers of wage floor adjustments; elasticities of wage floors with respect to these macro variables are 0.6, 0.4 and 0.2 respectively. Wage floor elasticities to inflation and to the NMW both decrease along the wage floor distribution but are still positive for all levels of wage floors

A physically-based parsimonious hydrological model for flash floods in Mediterranean catchments

A spatially distributed hydrological model, dedicated to flood simulation, is developed on the basis of physical process representation (infiltration, overland flow, channel routing). Estimation of model parameters requires data concerning topography, soil properties, vegetation and land use. Four parameters are calibrated for the entire catchment using one flood event. Model sensitivity to individual parameters is assessed using Monte-Carlo simulations. Results of this sensitivity analysis with a criterion based on the Nash efficiency coefficient and the error of peak time and runoff are used to calibrate the model. This procedure is tested on the Gardon d'Anduze catchment, located in the Mediterranean zone of southern France. A first validation is conducted using three flood events with different hydrometeorological characteristics. This sensitivity analysis along with validation tests illustrates the predictive capability of the model and points out the possible improvements on the model's structure and parameterization for flash flood forecasting, especially in ungauged basins. Concerning the model structure, results show that water transfer through the subsurface zone also contributes to the hydrograph response to an extreme event, especially during the recession period. Maps of soil saturation emphasize the impact of rainfall and soil properties variability on these dynamics. Adding a subsurface flow component in the simulation also greatly impacts the spatial distribution of soil saturation and shows the importance of the drainage network. Measures of such distributed variables would help discriminating between different possible model structures

La congruence dans le parrainage : définition, rôle et mesure.

La congruence est un concept introduit récemment dans le domaine du parrainage, mais déjà largement utilisé dans la littérature sur l’extension de marque ou sur la publicité. Nous montrerons l’intérêt de considérer ce concept selon les deux dimensions définies par Heckler et Childers (1992), la pertinence et le côté attendu, et nous en proposons une échelle de mesure.The concept of congruence has been recently introduced in sponsorship research, whereas it has been already widely integrated in the literature on brand extensions or advertising effectiveness. We will show the importance of this concept defined through the two dimensions proposed by Heckler and Childers (1992): relevancy and expectancy; we will then develop a scale to measure this concept.sponsorship; relevancy; expectancy; scale; échelle; côté attendu; pertinence; fit; congruence; parrainage;

Méthodes de régionalisation pour un modèle pluie-débit distribué et à base physique dédié aux crues éclair

Cette étude s’intéresse aux méthodes de régionalisation pour des jeux de paramètres d’un modèle pluie‑débit distribué et à base physique, dédié aux crues éclair. Les performances du modèle MARINE sont testées sur un total de 117 évènements de crues éclair survenues sur des bassins versants de l’arc méditerranéen français. Etant donnée la relative rareté des enregistrements de crues éclair, ce jeu de données représente un échantillon conséquent des paysages et de l’hydrologie des régions allant du piémont pyrénéen à la Provence en passant par les Cévennes et le Vivarais. Des approches de régionalisation basées sur la proximité géographique ou les similarités physiographiques sont testées avec plusieurs combinaisons de descripteurs. Des résultats encourageants sont obtenus avec les deux méthodes de similarités physiographiques basées sur deux ou trois bassins donneurs. Une perte de performance de 10% en régionalisation par rapport à la calibration/validation est relevée pour ces méthodes. Pour 13 bassins versants sur 16, au moins un évènement est simulé avec de bonnes performances. Cette étude met en avant l’importance des informations hydrologiques contenues dans les évènements de calibration disponibles sur site ou sur les bassins donneurs. De plus les techniques de régionalisation produisent de meilleures performances sur les bassins présentant un comportement hydrologique apparemment plus régulier. Le paramètre le plus sensible du modèle MARINE, CZ, contrôlant le volume de sol et ainsi le bilan en eau, est plutôt bien contraint par les approches de régionalisation par similarité grâce aux descripteurs du socle rocheux

Relations between streamflow indices, rainfall characteristics and catchment physical descriptors for flash flood events

Flash flood is a very intense and quick hydrologic response of a catchment to rainfall. This phenomenon has a high spatial-temporal variability as the generating storm often hits small catchments (few km²). Given the small spatial temporal scales and high variability of flash floods, their prediction remains a hard exercise as the necessary data are often scarce. This study investigates the potential of hydrologic indices at different scales to improve understanding of flash floods dynamics and characterize catchment response in a model independent approach. These hydrologic indices gather information on hydrograph shape or catchment dynamic for instance and are useful to examine catchment signature in function of their size. Results show that for middle-size (>100 km²) catchments response shape can be correlated to storm cell position within the catchment contrarily to smaller catchments. In a multi-scale point of view, regional characteristics about catchment geomorphology or rainfall field statistics should provide useful insight to find pertinent hydrologic response indices. The combined use of these indices with a physically-based distributed modelling could facilitate calibration on ungauged catchments

Using a multi-hypothesis framework to improve the understanding of flow dynamics during flash floods

A method of multiple working hypotheses was applied to a range of catchments in the Mediterranean area to analyse different types of possible flow dynamics in soils during flash flood events. The distributed, process-oriented model, MARINE, was used to test several representations of subsurface flows, including flows at depth in fractured bedrock and flows through preferential pathways in macropores. Results showed the contrasting performances of the submitted models, revealing different hydrological behaviours among the catchment set. The benchmark study offered a characterisation of the catchments’ reactivity through the description of the hydrograph formation. The quantification of the different flow processes (surface and intra-soil flows) was consistent with the scarce in situ observations, but it remains uncertain as a result of an equifinality issue. The spatial description of the simulated flows over the catchments, made available by the model, enabled the identification of counterbalancing effects between internal flow processes, including the compensation for the water transit time in the hillslopes and in the drainage network. New insights are finally proposed in the form of setting up strategic monitoring and calibration constraints

Flash flood modelling for ungauged catchments

Flash flood is a very intense and quick hydrologic response of a catchment to rainfall. This phenomenon has a high spatial-temporal variability as its generating storm, often hitting small catchments (few km2). Data collected by (Gaume et al. 2009) about 500 flash floods over the last 50 years showed that they could occur everywhere in Europe and more often in the Mediterranean regions, Alpine regions and continental Europe. Given the small spatial-temporal scales and high variability of flash floods, their prediction remains a hard exercise as the necessary data are often scarce. Flash flood prediction on ungauged catchments is one of the challenges of hydrological modelling as defined by (Sivapalan et al. 2003). Several studies have been headed up with the MARINE model (Modélisation de l’Anticipation du Ruissellement et des Inondations pour des évèNements Extrêmes) for the Gard region (France), (Roux et al. 2011), (Castaings et al. 2009). This physically based spatially distributed rainfall runoff model is dedicated to flash flood prediction. The study aims at finding a methodology for flash flood prediction at ungauged locations in the Cévennes-Vivarais region in particular. The regionalization method is based on multiple calibrations on gauged catchments in order to extract model structures (model + parameter values) for each catchment. Several mathematical methods (multiple regressions, transfer functions, krigging. . . ) will then be tested to calculate a regional parameter set. The study also investigates the usability of additional hydrologic indices at different time scales to constrain model predictions from parameters obtained using these indices, and this independently of the model considered. These hydrologic indices gather information on hydrograph shape or catchment dynamic for instance. Results explainingglobal catchments behaviour are expected that way. The spatial-temporal variability of storms is also described through indices and linked with hydrograph shape descriptors in order to constrain model at ungauged locations. In a multi scale point of view, regional characteristics about catchments geomorphology or rainfall fields’ statistics should provide useful insight to find pertinent hydrologic response indices. These considerations with physically based distributed modelling may bring better understanding on flash floods generating mechanisms and catchment responses