A graphical model, the extended fuzzy causal network is introduced and applied to a case study of waste water treatment plants. The structure of the network is developed using parameter sensitivity studies and the relationships between connected parameters are obtained using a learning approach adapted from fuzzy neural networks. The graphical model is shown to be able to translate the complex inter-relationships between process parameters into an easily understood form. Comparisons of the approach with neural and fuzzy neural networks are also made.