Effective Optimization Technique for a Nonlinear Rainfall-Runoff Model

Abstract

The purpose of this paper is to propose an effective optimization technique that can overcome the local minimum problem resulting from the nonlinear construction of the rainfall-runoff model. First, this technique attempts to approximate the nonlinear function by using a finite number of terms of linear functions, referred to as the linearization process. Then, these linear functions would be optimized by the sum of squared errors (MSSE). Finally, the optimized parameters of a nonlinear function using the step-iterative algorithm were obtained. Its features and capabilities are demonstrated by means of a binary function and a conceptual rainfall-runoff model (Xinanjiang model). To optimize the model parameters, 10 years of historical data in the Changzhao basin are applied, whereas the most recent three years are utilized to verify these parameters. With reference to the binary function, the proposed linearlized search technique (LST) converge quickly from any starting point. With regard to the hydrological conceptual model, the simulation results are as the same as those obtained by shuffled complex evolution (SCE-UA).