水科学进展2012，Vol.23Issue(5)：642-649,8.
基于统计理论方法的水文模型参数敏感性分析
Sensitivity analysis of hydrological model parameters using a statistical theory approach
摘要
Abstract
The sensitivity analysis is a key step in model uncertainty quantification. And it can identify the dominant parameters, reduce the model uncertainty, and enhance the model optimization efficiency. In order to make quantitative global sensitivity analysis ( GSA) more tractable, the Morris screening method is used to qualitatively assess a model first. Then, the response surface methodology ( RSM) based on the statistical theory will be applied to construct a surrogate model, and to integrate with the variance-based Sobol' method to establishing a new method, named as the RSMSobol method. The new method is tested on the Yanduhe basin using the Xin'anjiang model with daily precipitation data and hydrographs. The sensitivity analysis is conducted for four different objective functions. The results demonstrate that the new integrated qualitative and quantitative method can improve the efficiency of the sensitivity analysis , in which the Morris qualitative method can decrease the number of parameters by 50% for the next round of the quantitative analysis. The RSMSobol method can improve the computational cost.关键词
新安江模型/敏感性分析/RSMSobol方法/响应曲面方法/Morris方法Key words
Xin'anjiang model/ sensitivity analysis/ RSMSobol method/ response surface model/ Morris screening melhorj分类
天文与地球科学引用本文复制引用
宋晓猛,孔凡哲,占车生,韩继伟..基于统计理论方法的水文模型参数敏感性分析[J].水科学进展,2012,23(5):642-649,8.基金项目
国家自然科学基金资助项目(40901023) （40901023）
中国科学院"一三五"战略科技计划重点项目(2012ZD003) （2012ZD003）
