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The European Union (EU) adopted the Water Framework Directive (WFD) in 2000 aiming to achieve a 'good status' in its aquatic ecosystems by 2015. In this respect, a numerical spatio-temporal model is developed to describe the nitrogen dynamics in large river basins with the Scheldt basin as pilot study area. The uncertainty about the input data and the groundwater flow at this scale, and the intended application for scenario analyses prompted the use of an open model structure where the model developer can test different process descriptions to match the observed characteristics of water flow and water quality. Therefore, the fate model is programmed in a Python environment using the PCRaster library enabling an adequate balance between process descriptions and necessary input data. The PCRaster software expands the traditional GIS software packages with a time dimension and domain specific functions that operate on the defined GIS layers. The Python/NumPy environment enables a modeller with no advanced programming skills to add new or existing code to simulate specific environmental processes. The resulting GIS-based model uses a monthly time step and a spatial resolution of 1 km 2 to simulate time-dependent discharges and concomitant nitrogen dynamics in the Scheldt basin. It discerns 4 compartments in the basin: the soil, shallow subsurface, deep subsurface and the river network. Water flows along the steepest slope in all model compartments. The mass transport module uses these calculated flows to translate emissions to loads in the aquatic ecosystem. Diffuse emissions and direct inputs are calculated from administrative and statistical data. These emissions are geographically defined or are distributed over the domain according to land use and connectivity to the sewer system. Datasets provided at the EU level are used to construct the model when available. Different scenarios with conventional and innovative rehabilitation technologies are defined to estimate the effect of a measure on the reduction of the nitrogen load in the aquatic ecosystem. Conventional measures mainly reduce the future amount of nitrogen emitted in the basin, e.g. a reduction of livestock numbers, while innovative rehabilitation technologies such as wetlands reduce the amount of nitrogen that finally reaches the surface waters and, as such, are also effective in reducing nitrogen loads from historical emissions. The results of the scenario analysis will be used to derive knowledge rules translating nitrogen emissions and reductions thereof to loads in the aquatic ecosystem. This information will be used in a database driven Decision Support System. The open model structure in Python/NumPy with the PCRaster library yielded a fast prototyping environment enabling scientists with no advanced programming skills to test different process descriptions to match the observed characteristics of water flow and water quality. The prototyping environment was an asset since the application of the conceptual model approach for scenario analysis in a fully distributed large river basin at a monthly time step proved difficult. The resulting GIS-based model will be used for a first evaluation of innovative rehabilitation technologies versus conventional measures at the river basin scale, taking into account the current limitations for predictions at the subbasin scale.

Translating nitrogen emissions to loads in the aquatic ecosystem of the Scheldt basin