The empirical eigenfunctions obtained from the Karhunen-Loeve decomposition are employed as trial functions of a Galerkin method to construct a dynamic model of a flow reactor (the Karhunen-Loeve Galerkin method). This dynamic model is then used for the purpose of parameter estimation of the flow reactor and the performance of the model is compared to a conventional method such as the method of lines. The dynamic model based on the Karhunen-Loeve Galerkin method can represent a given system with a minimum degree of freedom, and consequently the number of equations to be solved in the estimation of parameters is minimized. It is demonstrated that, for a flow reactor of complicated shape, the present technique of parameter estimation using the Karhunen-Loeve Galerkin procedure is far more efficient than the method of lines.