Modelling water and nutrient fluxes in the Danube River Basin with SWAT

Abstract

This study provides an innovative process-based modelling approach using the SWAT model and shows its application to support the implementation of the European environmental policies in large river basins. The approach involves several pioneering modelling aspects: the inclusion of current management practices; an innovative calibration and validation methodology of streamflow and water quality; a sequential calibration starting from crop yields, followed by streamflow and nutrients; and the use of concentrations instead of loads in the calibration. The approach was applied in the Danube River Basin (800,000km²), the second largest river basin in Europe, that is under great nutrients pressure. The model was successfully calibrated and validated at multiple gauged stations for the period 1995-2009. About 70% and 61% of monthly streamflow stations reached satisfactory performances in the calibration and validation datasets respectively. N-NO₃ monthly concentrations were in good agreement with the observations, albeit SWAT could not represent accurately the spatial variability of the denitrification process. TN and TP concentrations were also well captured. Yet, local discrepancies were detected across the Basin. Baseflow and surface runoff were the main pathways of water pollution. The main sinks of TN and TP diffuse emissions were plant uptake which captured 58% of TN and 92% of TP sources, then soil retention (35% of TN and 2% of TP), riparian filter strips (2% both for TN and TP) and river retention (2% of TN and 4% of TP). Nitrates in the aquifer were estimated to be around 3% of TN sources. New reliable "state-of-the-art" knowledge of water and nutrients fluxes in the Danube Basin were thus provided to be used for assessing the impact of best management practices and for providing support to the implementation of the European Environmental Directives.

Keywords: Danube; Nitrogen and phosphorus balances; Nutrient concentrations; Streamflow; Swat.