A new distributed parameter stochastic model is introduced for modelling a large-scale wastewater treatment system with distributed water feeding, sludge recycling and removal. The state estimation problem is formulated as a biomass and organic matter profile estimation problem for the aeration basin. It is solved by approximation of the original model with a finite-dimensional bilinear model and the filtration distribution with the normal distribution. It is shown that the profile can be estimated online using dissolved oxygen and gas analysis results measured from several points over the aeration basin. The estimation quality is higher in the case of a large-scale aeration basin than in the case of a completely mixed basin. The estimation algorithm is obtained in a computationally effective form. The model and the estimation algorithm are tested in a simulation experiment. It is demonstrated that the sludge and water distribution has a strong effect on treated water quality. The distribution is considered as a new control parameter. It can be used in practice for improvement of treatment process quality.