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To evaluate the effects of nitrogen (N) emission policies, reliable information on nitrate concentrations and leaching fluxes from forest ecosystems is necessary. Insight into the regional variability of nitrate concentrations, to support local policy on emission abatement strategies is especially desirable. In this paper, three methods for the calculation of a spatial distribution of soil nitrate concentrations in Dutch forest ecosystems are compared. These are (i) a regression model based on observed nitrate concentrations and additional data on explanatory variables such as soil type, tree species and nitrogen deposition (ii) a semi-empirical dynamic model WANDA, and (iii) a process-oriented dynamic model SMART2. These two dynamic models are frequently used to evaluate the effects of reductions in nitrogen deposition at scales ranging from regional to countrywide. The results of the regression model evaluated the performance of the two dynamic models. Furthermore, the results of the three methods are compared with the steady-state approach currently used for the derivation of nitrogen critical loads. Both dynamic models, in the form of cumulative distribution functions, give similar results on a national scale. Regional variability is predicted differently by both models. Discrepancies are caused mainly by a difference in handling forest filtering and denitrification. All three methods show that, despite the high nitrogen inputs, Dutch forests still accumulate more N than they release. This implies that, in respect of groundwater quality, presently acceptable nitrogen deposition is higher than the (long-term) critical loads. However, in areas with high atmospheric nitrogen input, all three methods indicate that the EU standard for nitrate in groundwater (50 mg NO3 l–1) is exceeded. Steady-state with nitrogen deposition seems to have been reached in about 10% of the forested area, with a nitrate concentration greater than 50 mg NO3–1. Keywords: soil modelling, up-scaling, model validation, critical load

This study focuses on spatial variability of throughfall water and chemistry and forest floor water content within a Douglas fir (Pseudotsuga menziesii, Franco L.) forest plot. Spatial patterns of water and chemistry (NH4+, NO3‾, SO42-, Cl‾, Mg2+, Ca2+, Na+ and K+) were compared and tested for stability over time. The spatial coefficient of variation (CV) was between 18 and 26% for amounts of throughfall water and ions, and 17% for forest floor water content. Concentrations and amounts of all ions were correlated significantly. Ion concentrations were negatively correlated with throughfall water amounts, but, except for NH4+, there was no such relation between throughfall water and ion amounts. Spatial patterns of throughfall water fluxes and forest floor water contents were consistent over time; patterns of ion fluxes were somewhat less stable. Because of the spatial variability of forest floor thickness and drainage, it was not possible to relate patterns in throughfall water directly to patterns in water content. The spatial variability of throughfall nitrogen and forest floor water contents can cause significant variability in NO3‾ production within the plot studied. Keywords: nutrient throughfall, forest floor water, spatial variability, time-stability, nitrogen

Elevated carbon dioxide levels, caused by anthropogenic emissions of carbon dioxide to the atmosphere, and higher temperature may lead to increased plant growth and uptake of nitrogen, but increased temperature may lead to increased nitrogen mineralisation causing enhanced nitrogen leaching. The overall result of both counteracting effects is largely unknown. To gain insight into the long-term effects, the geochemical model SMART2 was applied using data from the catchment-scale experiments of the RAIN and CLIMEX projects, conducted on boreal forest ecosystems at Risdalsheia, southern Norway. These unique experiments at the ecosystem scale provide information on the short-term effects and interactions of nitrogen deposition and increased temperature and carbon dioxide on carbon and nitrogen cycling and especially the run-off chemistry. To predict changes in soil processes in response to climate change, the model was extended by including the temperature effect on mineralisation, nitrification, denitrification, aluminium dissolution and mineral weathering. The extended model was tested on the two manipulated catchments at Risdalsheia and long-term effects were evaluated by performing long-time runs. The effects of climate change treatment, which resulted in increased nitrogen fluxes at both catchments, were slightly overestimated by SMART2. The temperature dependency of mineralisation was simulated adequately but the temperature effect on nitrification was slightly overestimated. Monitored changes in base cation concentrations and pH were quite well simulated with SMART2. The long-term simulations indicate that the increase in nitrogen run-off is only a temporary effect; in the long-term, no effect on total nitrogen leaching is predicted. At higher deposition levels the temporary increase in nitrogen leaching lasts longer than at low deposition. Contrary to nitrogen leaching, temperature increase leads to a permanent decrease in aluminium concentrations and pH. Keywords: elevated carbon dioxide, temperature, forest ecosystem, modelling, nitrogen run-off.

Great effort has been dedicated to developing soil acidification models for use on different scales. This paper focuses on the changes in model performance of a site scale soil acidification model (NUCSAM) and a national to European scale soil acidification model (SMART 2). This was done to gain insight into the effects of model simplification. Because these models aim to predict the response to reduction in acid deposition, these models must be tested under such circumstances. A straightforward calibration and validation of the regional model, however, is hampered by lack of observations over a sufficient time period. Consequently, NUCSAM was calibrated and validated to a manipulation experiment involving reduced acid deposition in the Speuld forest, the Netherlands. SMART 2 was then used with calibrated input data from NUCSAM. The acid deposition was excluded by a roof beneath the canopy. The roofed area consists of a plot receiving pristine deposition levels of nitrogen (N) and sulphur (S) and a control plot receiving ambient deposition. NUCSAM was calibrated on the ambient plot, followed by a validation of both models on the pristine plot. Both models predicted soil solution concentrations within the 95% confidence interval of the observed responses for both the ambient plot and the pristine plot at 90 cm depth. Despite the large seasonal and vertical (spatial) variation in soil solution chemistry, the trends in annual flux- weighted soil solution chemistry, as predicted by SMART 2 and NUCSAM, corresponded well.The annual leaching fluxes below the root zone were also similar although differences exist for the topsoil. For the topsoil, NUCSAM simulated the nutrients and acid related constituents better than SMART 2. Both models overestimated the ammonium (NH4) concentration at 10 cm depth. SMART 2 underestimated calcium and magnesium (BC2+) concentration at 10 depth, whereas NUCSAM overestimated BC2+ concentration at 90 cm depth. NUCSAM predicted the effect of deposition reduction on N concentrations at both depths, whereas SMART 2 underestimated the effect of deposition reduction at 10 cm depth. Both models predicted faster effects of deposition reduction on aluminum (Al), sulphate (SO4) and base cations than was observed. Generally, it appeared that the differences were large during the period of profound deposition changes whereas small differences occurred during slight variations in deposition level. It is concluded that a simpler model description does not affect the model's performance significantly as regards flux-weighted annual average concentrations at greater depth. Model improvements must focus on processes related to N-dynamics.