A knowledge-based approach to regional acidification modelling

Data from over 2000 stations and knowledge from experts on atmospheric transport, soil geochemistry, lake chemistry, wetland processes and acidification modelling were assembled in an expert system. The data were grouped by aggregates of tertiary watersheds based on water chemistry knowledge. A set of expert rules was used to determine which of six existing models was most appropriate for a given set of data. Comparison of computed and observed alkalinity indicated median relative errors from 11.3-17.9%, with regression slopes ranging from 0.91-1.18 and regression coefficients between 0.82 and 0.99. The expert model performance was further confirmed with paleolimnological data and other independent sets of data. The sensitivity of the predicted alkalinity was illustrated by changing some of the rules. Given that the rules were acceptable by experts and produced reasonable agreement with observations, the knowledge-based system seemed a viable approach to the impact assessment of acidic deposition.