ABSTRACT
ABSTRACT: Conventional objective function of minimum error sum of squares for nonlinear function parameter calibration may increase unrelated local optimal value. To solve the problem, a linearized calibration method of nonlinear function parameter was developed. The aim of this paper is to investigate the ability of the proposed method to find the optimal parameter values during calibration of Xin’anjiang model. An ideal model case, in which the true optimum set of parameter values was known by assumption, was used to examine whether the linearized calibration method can find that optima. The performance of the linearized calibration method was then studied using the real data from Qilijie catchment. The results showed that the linearized calibration method was always able to find the global optima with fast convergence rate, which verified that the proposed method can solve the theoretical problem of unrelated local optima and is an effective parameter optimization technique.
