Model structure selection and parameter identification for biokinetic modeling of biological wastewater treatment processes is broadly accepted to be a complicated task. Contributing factors include (i) nonlinear behavior, (ii) lack of knowledge, (iii) lack of (accurate) measurements, and (iv) a large number of model parameters to estimate. Several strategies have been proposed in the wastewater engineering literature to deal with the complexity of the modeling task. These include (i) experimental design, (ii) determination of identifiable parameters, and (iii) stochastic nonlinear optimization. Despite these developments, model identification remains challenging. Extent-based modeling simplifies this task by identifying each reaction kinetics separately. The available method fits in a strategy where the reaction network (graph) and its stoichiometry (matrix) are first identified. Then, the extents of reaction are computed and the identification of the individual rate functions is made in terms of extents. In this work, the original extent-based method is modified to take nonlinear constraints and measurements into account. A simulated batch process is used to demonstrate the method.