Many relevant process states in wastewater treatment are not measurable, or their measurements are subject to considerable uncertainty. This poses a serious problem for process monitoring and control. Model-based state estimation can provide estimates of the unknown states and increase the reliability of measurements. In this paper, an integrated approach is presented for the estimation problem employing unconventional, but technically feasible sensor networks. Using the ASM1 model in the reference scenario BSM1, the estimators EKF and MHE are evaluated. Very good estimation results for the system comprising of 78 states are found.