Parameter estimation of river water quality model based on real-coded genetic algorithm

Because of the considerable errors caused by applying the analytic method for the parameter estimation of water quality under ideal conditions, and with a view to solving the problem of several parameter estimations in two-dimensional water quality model, this paper presented the basic steps for the parameter estimation of the two-dimensional water quality model, based on finite element method and real-coded genetic algorithm. The method involved coding the parameters, including longitudinal dispersion coefficient, transversal dispersion coefficient and decay coefficient, and producing the concentration outputs. The results were compared with the actual monitoring data, and the optimal parameter estimating values were obtained. The example shows that this approach of parameter estimation, based on the finite element method and genetic algorithm, is applicable.