Distributed state estimation plays a very important role in process control. Improper subsystem decomposition for distributed state estimation may increase the computational burdens, degrade the estimation performance, or even deteriorate the observability of the entire system. The subsystem decomposition problem for distributed state estimation of nonlinear systems is investigated. A systematic procedure for subsystem decomposition for distributed state estimation is proposed. Key steps in the procedure include observability test of the entire system, observable states identification for each output measurement, relative degree analysis and sensitivity analysis between measured outputs and states. Considerations with respect to time-scale multiplicity and direct graph are discussed. A few examples are used to illustrate the applicability of the methods used in different steps. The effectiveness of the entire distributed state estimation configuration procedure is also demonstrated via an application to a chemical process example used in coal handling and preparation plants. (C) 2016 American Institute of Chemical Engineers