Continuing deposition of nitrogen in forested catchments affects stream and groundwater quality. However, the dependence of nitrogen dynamics on climatic and hydrological boundary conditions is still poorly understood. These dynamics have been investigated by applying the process-oriented Integrated Nitrogen in CAtchments (INCA) model and an artificial neural network to the data set from the forested Steinkreuz catchment in South Germany. The data comprise daily values of precipitation, air temperature and discharge of the catchment runoff. The INCA model simulated the mean nitrate concentration in the stream as well as seasonal fluctuations but it underestimated the short-term variance of the observed stream water nitrate concentration, especially the pronounced concentration peaks in late summer. In contrast, the artificial neural network matched the short-term dynamics using non-linear regressions with stream discharge and air temperature data. The results provide strong evidence that the short-term dynamics of stream nitrate concentration during storm-flow were generated in the riparian zone, which is less than 1% of the catchment area, and is not considered explicitly in the INCA model. The concentration peaks have little effect on the catchments nitrogen budget and the shallow groundwater data suggest that the short-term hydrological dynamics also govern groundwater recharge in the upland parts of the catchment. This substantial underestimate by the INCA model parameterisation is balanced by a corresponding underestimate of denitrification in clayey layers of the deeper aquifer. A better understanding of these processes is necessary to improve long-term risk assessments.

Many forest ecosystems in Central Europe have reached the status of N saturation due to chronically high N deposition. In consequence, the NO 3 leaching into ground-and surface waters is often substantial. Critical loads have been defined to abate the negative consequences of the NO 3 leaching such as soil acidification and nutrient losses. The steady state mass balance method is normally used to calculate critical loads for N deposition in forest ecosystems. However, the steady state mass balance approach is limited because it does not take into account hydrology and the time until the steady state is reached. The aim of this study was to test the suitability of another approach: the dynamic model INCA (Integrated Nitrogen Model for European Catchments). Long-term effects of changing N deposition and critical loads for N were simulated using INCA for the Lehstenbach spruce catchment (Fichtelgebirge, NE Bavaria, Germany) under different hydrological conditions.Long-term scenarios of either increasing or decreasing N deposition indicated that, in this catchment, the response of nitrate concentrations in runoff to changing N deposition is buffered by a large groundwater reservoir. The critical load simulated by the INCA model with respect to a nitrate concentration of 0.4 mg N l -1 as threshold value in runoff was 9.7 kg N ha -1 yr -1 compared to 10 kg ha -1 yr -1 for the steady state model. Under conditions of lower precipitation (520 mm) the resulting critical load was 7.7 kg N ha -1 yr -1 , suggesting the necessity to account for different hydrological conditions when calculating critical loads. The INCA model seems to be suitable to calculate critical loads for N in forested catchments under varying hydrological conditions e.g. as a consequence of climate change.