Parameter and rating curve uncertainty propagation analysis of the SWAT model for two small Mediterranean catchments

Abstract

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...

Uncertainty analysis in model parameters regionalization: a case study involving the SWAT model in Mediterranean catchments (Southern France)

“…The eastern part of the Thau catchment area is composed of Jurassic limestone overlaid by Miocene marls in its central part, corresponding to 60 % of the Vène watershed surface. This Jurassic limestone is characterized by the presence of a large karstic aquifer whose limits extend the topographic limit of the catchment and strongly influences the hydrological regime of the Vène catchment (Plus et al, 2006;Gallart et al, 2008;Perrin and Tournoud, 2009;Sellami et al, 2013). Soils in this part of the Thau catchment are mainly sandy-loam and silty-loam soils with porosity ranging from 35 to 50 % at 1 m depth of the soil profile.…”

“…As the Pallas and the Vène catchments have been subject to many previous studies (Aquilina et al, 2002;La Jeunesse et al, 2002;Plus et al, 2006;Chahinian et al, 2011;Sellami et al, 2013), more detailed data are available for these subcatchments. Therefore, the Vène and the Pallas catchments are considered as gauged catchments, while all other small catchments are considered ungauged.…”

“…However, due to the complex nature of the flow processes and the presence of the karstic system in the catchment, a model warm-up period of 4 years (1990)(1991)(1992)(1993)) is considered to be sufficient to minimize the effects of the initial state of the SWAT variables on the river flow prediction (Sellami et al, 2013). The modified SCS curve number method is chosen for surface runoff volume computing.…”

“…Knowledge about the key processes in the system can also assist the selection of the relevant CAs. As an example, the geology is considered as a relevant catchment descriptor in our case study since it is known that the Jurassic limestone aquifer in the eastern part of the Thau catchment strongly influences the hydrological regime of the Vène catchment (Sellami et al, 2013).…”

“…and to the subjectivity in the GLUE method (e.g., threshold value, the likelihood function, the initial parameter distribution) involved at each modeling step (Xiong and O'Connor, 2008;Shrestha et al, 2009). Furthermore, the karstic nature of the study site (especially the Vène catchment) makes the discharge modeling using the SWAT model more challenging and more uncertain (Sellami et al, 2013).…”