新安江模型参数多目标优化研究

水文模型的参数优化率定一直以来是水文预报领域的重要研究内容,当水文模型的结构确定后,水文模型参数的选择对水文模型整体性能和水文预报结果的好坏有着至关重要的影响.针对传统水文模型参数优选采用单一目标不能充分全面挖掘水文观测资料中蕴含的水文特征信息的缺陷,本文以新安江三水源模型为例,尝试采用多目标优化算法优化率定水文模型,算例应用分析表明,通过合理的选择目标函数的种类和数目,采用多目标进化算法优化率定模型参数,可以获得相对于单目标率定模型参数更优的结果.进一步,研究工作针对模型参数优化的结果进行分析,可以明显看出模型参数优化中存在“异参同效”现象,为后续模型参数不确定性分析等相关研究工作的开展做好了铺垫.

Study on Multi-objective Parameter Optimization of Xinanjiang Model

Parameter estimation of hydrological models is an important matter of hydrological forecasting. As the structure of the model isestablished, the calibration of parameters has great influence on the performance of the hydrological model. Practice experience suggeststhat the conventional calibration of hydrological models with single objective function is often inadequate to properly measure all of thecharacteristic of the observed data deemed to be important. To deal with this defect, the multi-objective evolution algorithm was employedto optimize the parameters of the Xinanjiang model with three runoff components in this paper. The results of the case study indicated thatwith well chosen objective functions, the multi-objective optimization can achieve better results than the single objective optimization. Furthermore, by analyzing the achieved the parameter combination, it is obvious that the phenomenon of same effect of different parametersexists, so as to do some preparations for the uncertainty analysis of the model parameters.