Int. J. Environment and Pollution, Vol. 31, Nos. 1/2, 2007 107 Copyright © 2007 Inderscience Enterprises Ltd. Use of qualitative constraints in modelling of the Lake Glumsø Daniel Vladušič*, Boris Kompare and Ivan Bratko Faculty of Computer and Information Science, Trzaska 25, 1000 Ljubljana, Slovenia Fax: 386 1 476 83 86 E-mail: daniel.vladusic@fri.uni-lj.si *Corresponding author Abstract: This paper describes modelling of time behaviour of phytoplankton and zooplankton in the Danish lake Glumsø with a recently developed approach to machine learning in numerical domains, called Q 2 learning. An essential part of this approach is qualitative constraints which were either handcrafted using knowledge from the Lotka-Volterra predator-prey model or induced directly from the collected data with a program called QUIN. The induced models were evaluated by a domain expert. We performed a comparison between numerical results of the Q 2 learning approach and standard machine learning algorithms. The results suggest that use of qualitative constraints leads to more accurate quantitative predictions. Keywords: qualitative reasoning; machine learning; numerical prediction; Lake Glumsø. Reference to this paper should be made as follows: Vladušič, D., Kompare, B. and Bratko, I. (2007) ‘Use of qualitative constraints in modelling of the Lake Glumsø’, Int. J. Environment and Pollution, Vol. 31, Nos. 1/2, pp.107–124. Biographical notes: Daniel Vladušič is a Researcher at the Faculty of Computer and Information Science, University of Ljubljana, Slovenia. He has conducted research in machine learning, behavioural cloning and qualitative modelling. His work is primarily focused on use of qualitative models in numerical prediction. His work was applied to various modelling tasks from the field of dynamic systems control, where he modelled active and passive damper systems, vehicle behaviour and crane control. Using ecological modelling, he conducted research in the prediction of the river Savinja water level and in the Lake Glumsø domain. Boris Kompare is an Associate Professor at the Faculty of Civil and Geodetic Engineering, University of Ljubljana, where he chairs the Institute of Sanitary Engineering. His main field of work is sanitary and ecological engineering. He lectures subjects as Fundamentals of Water Treatment, Water Supply, Drinking Water Treatment, Water Protection, Ecological Modelling, etc. His present research topics are the use of machine learning tools in ecological modelling, improvements of the mercury cycling model, fate of xenobiotic chemicals in urban water cycle, development of robust and economically attractive small waste water treatment plants, development of revised hydraulic friction loss formula, etc. Ivan Bratko is Professor of Computer Science at the Faculty of Computer and Information Science, University of Ljubljana, Slovenia. He heads the AI laboratory at the University. He has conducted research in machine learning,