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The objective of this study was to analyze the potential of the C-band polarimetric SAR parameters for the soil surface characterization of bare agricultural soils. RADARSAT-2 data and simulations using the Integral Equation Model (IEM) were analyzed to evaluate the polarimetric SAR parameters' sensitivities to the soil moisture and surface roughness. The results showed that the polarimetric parameters in the Cband were not very relevant to the characterization of the soil surface over bare agricultural areas. Low dynamics were often observed between the polarimetric parameters and both the soil moisture content and the soil surface roughness. These low dynamics do not allow for the accurate estimation of the soil parameters, but they could augment the standard inversion approaches to improve the estimation of these soil parameters. The polarimetric parameter  1 could be used to detect very moist soils (>30%), while the anisotropy could be used to separate the smooth soils.

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The SWAT model was tested to simulate the streamflow of two small Mediterranean catchments (the Vène and the Pallas) in southern France. Model calibration and prediction uncertainty were assessed simultaneously by using three different techniques (SUFI-2, GLUE and ParaSol). Initially, a sensitivity analysis was conducted using the LH-OAT method. Subsequent sensitive parameter calibration and SWAT prediction uncertainty were analysed by considering, firstly, deterministic discharge data (assuming no uncertainty in discharge data) and secondly, uncertainty in discharge data through the development of a methodology that accounts explicitly for error in the rating curve (the stage−discharge relationship). To efficiently compare the different uncertainty methods and the effect of the uncertainty of the rating curve on model prediction uncertainty, common criteria were set for the likelihood function, the threshold value and the number of simulations. The results show that model prediction uncertainty is not only case-study specific, but also depends on the selected uncertainty analysis technique. It was also found that the 95% model prediction uncertainty interval is wider and more successful at encompassing the observations when uncertainty in the discharge data is considered explicitly. The latter source of uncertainty adds additional uncertainty to the total model prediction uncertainty.Keywords Mediterranean catchments; parameter uncertainty; uncertainty analysis; model calibration; SWAT; rating curve uncertainty Analyse de la propagation des incertitudes de la courbe de tarage et des paramètres du modèle SWAT pour deux petits bassins versants de la région méditerranéenne Résumé Dans cet article le modèle SWAT a été testé pour simuler l'écoulement de deux petits bassins versants (la Vène et le Pallas) en région méditerranéenne dans le sud de la France. Le calage du modèle et l'incertitude des prévisions ont été évalués simultanément en utilisant trois techniques différentes (SUFI-2, COLLE et Parasol). Tout d'abord, une analyse de sensibilité a été réalisée en utilisant la méthode de LH-OAT. Le calage des paramètres sensibles et l'incertitude des prévisions de SWAT ont été analysés en considérant, dans un premier temps, un débit déterministe (en supposant l'absence d'incertitude dans les données de débit), et dans un second temps, en considérant l'incertitude liée aux données de débit à travers le développement d'une méthodologie qui tient compte explicitement des erreurs dans la courbe de tarage (relation hauteur d'eau et vélocité d'écoulement). Pour comparer efficacement les différentes méthodes d'estimation de l'incertitude et l'effet de l'incertitude de la courbe de tarage sur l'incertitude des prévisions du modèle, des critères communs ont été définis pour la fonction de vraisemblance, la valeur seuil et le nombre de simulations. Les résultats montrent que l'incertitude des prévisions du modèle est non seulement spécifique au cas d'étude mais dépend aussi de la technique d'analyse d'incertitude sélec...

Abstract. In this study a method for propagating the hydrological model uncertainty in discharge predictions of ungauged Mediterranean catchments using a model parameter regionalization approach is presented. The method is developed and tested for the Thau catchment located in Southern France using the SWAT hydrological model. Regionalization of model parameters, based on physical similarity measured between gauged and ungauged catchment attributes, is a popular methodology for discharge prediction in ungauged basins, but it is often confronted with an arbitrary criterion for selecting the "behavioral" model parameter sets (Mps) at the gauged catchment. A more objective method is provided in this paper where the transferrable Mps are selected based on the similarity between the donor and the receptor catchments. In addition, the method allows propagating the modeling uncertainty while transferring the Mps to the ungauged catchments. Results indicate that physically similar catchments located within the same geographic and climatic region may exhibit similar hydrological behavior and can also be affected by similar model prediction uncertainty. Furthermore, the results suggest that model prediction uncertainty at the ungauged catchment increases as the dissimilarity between the donor and the receptor catchments increases. The methodology presented in this paper can be replicated and used in regionalization of any hydrological model parameters for estimating streamflow at ungauged catchment.