Strategies to control the emission of atmospheric pollutants such as sulfur and nitrogen, are generally based in large pat on projections using models that simulate the influence of sulfur and/or nitrogen deposition on the acid-base chemistry of surface waters. One of the principal models used throughout Europe and North America for such assessment is the Model of Acidification of Groundwater in Catchments (MAGIC). All watershed models are simplified representations of reality, and as such require careful testing to establish their veracity prior to use for making policy projections This is particularly hue where the use of these model projections has the potential for serious environmental or economic consequences. During the past five years, we have tested the MAGIC model in a large variety of settings and under quite varying environmental conditions. This work has included comparing model hindcast simulations with diatom-inferences of historical acidification, sensitivity analyses to examine the response of the model to alternative assumptions and formulations and detailed testing of model forecasts by comparing simulated chemistry with the results of catchment-scale and plot-scale experimental acidification and deacidification. Our analyses have elucidated a number of potentially-important deficiencies in model structure and method of application. These have resulted in changes to the model and its calibration procedures. Our work has included in-depth evaluation of issues related to regional aggregation of soils data, background sulfur deposition, natural organic acidity, and aluminum mobilization. The result has been an improved and more thoroughly-tested version of MAGIC. The process we have followed to improve and confirm the MAGIC model has been iterative and time consuming. It required the availability of large volumes of data from experimental manipulation and paleolimnological studies. We believe that such model testing and confirmation efforts should be a critical prerequisite for regional or national assessment activities that are based largely on the results of environmental models.
