Study of the Xinanjiang Model Parameter Calibration

Abstract

The Xinanjiang model parameter calibration is an optimization problem that aims to determine the values of model parameters that provide the best fit between observed and estimated flows. Many researchers have used the shuffled complex evolution (SCE-UA) algorithm in the Xinanjiang model parameter calibration and have found some problems in its application. Identifying methods in choosing an objective function, the amount of calibration data to be used, and the best calibration steps in searching for the best parameters are just some of the application problems that must be solved. The goal of the present study is to resolve the aforementioned problems. This work calibrates the Xinanjiang model for the Yuetan basin in China based on the SCE-UA method. In the objective function study, six objective functions are commonly used. Results demonstrate that the water quantity balance error function is the best choice in both daily and hourly Xinanjiang model calibrations. During the experiment, 20 sets of observed data with length differences of 1–20 years are used. The results reveal that data amounting to a period of 16 years are needed to obtain a relatively stable parameter set. Meanwhile, the objective optimization method is introduced in the calibration step study. This method combines the coupling of the objective optimization method with the SCE-UA algorithm. Parameter calibration results reveal that the combined method can increase the calibration speed and reduce the influence of the calibration data period on the results.