Fuzzy knowledge-based models for prediction of Asellus and Gammarus in watercourses in Flanders (Belgium)

Fuzzy logic has become an interesting technique in modelling ecosystem processes and ecological assessment. Aside its capacity to take the inherent uncertainty of ecological variables into account during inference processing, it can express non-linear relations between ecological variables in a transparent way. In the present study, fuzzy knowledge-based models are constructed for the prediction of abundance levels of the macroinvertebrate taxa Asellus and Gammarus in river basins in Flanders (Belgium) and the results are validated by means of empirical data from the Zwalm river basin. Although the fuzzy models are based on a small set of input variables and the inference system is relatively simple, their performance was comparable to that of other modelling techniques, such as classification trees. This research therefore illustrates the strength of simple and robust predictive fuzzy models, and can be a valuable contribution to the practical application of predictive models for river management purposes.