水文模型参数自动优选方法的比较分析

A Comparative Study on Optimization Methods for Calibrating the Hydrological Models

模型参数的识别是模型研制与应用成功与否的关键。介绍了三个自动优选模型参数的方法，以新安江模型为例，应用１４个流域的资料，对罗森布郎克（Ｒｏｓｅｎｂｒｏｃｋ）法、改进的单纯形（Ｓｉｍｐｌｅｘ）法和基因（Ｇｅｎｅｔｉｃ）算法优选模型参数的效果，优化方法的收敛速度及参数初值对优选效果的影响进行了比较分析，初步分析了基因法参数ｌ和ＩＭＡＸ对优选结果的影响，指出以基因法的优选结果作为参数初值，再用其它两种方法进一步优化，是模型参数识别的一个有效途径。

The successful development and application of a conceptual rainfall-runoff model depends mainly on how well it is calibrated. This paper introduces three optimization methods, namely Rosenbrock, Simplex and Genetic algorithm, for automatic calibration of the hydrological models, The performances of the methods were analyzed on the basis of the application of them to the Xinanjiang model using 14 catchments data. The effects of the parameter values of the Genetic method on calibration of the model parameter values were preliminarily investigated. The results suggest that the Genetic algorithm with further tuning by other two methods can provide an efficient and robust means for calibrating the conceptual rainfall-runoff models.