基于不同目标函数GLUE方法参数不确定性研究

Research on Parameter Uncertainty Based on GLUE Method with Different Objective Functions

水文模型在防洪预报中发挥着重要作用,然而由于模型参数具有不确定性,即使有实测的降雨资料,也可能会产生较大的预报误差。针对参数的不确定性问题,以半湿润的陈河流域为研究区域,基于单目标GLUE方法和多目标GLUE方法,分析不同目标函数GLUE方法对实测径流的模拟能力以及参数的敏感性。研究结果表明,参数可分为敏感性参数(SM,CS)和非敏感性参数(K,KG,KI,CG,CI),不同的似然目标函数对径流具有不同的模拟能力,相对于单目标函数,多目标函数预报的不确定性范围较大,区间覆盖率较大,洪水预报的精度更高。

Hydrologic model plays an important role in flood forecasting. However, due to the uncertainty of model parameters,it may produce large prediction error even if the rainfall data is measured. Aiming at the problem of parameter uncertainty, the simulation capabilities of different objective functions on measured runoff are measured and the sensitivity of parameters are analyzed based on single objective GLUE method and multi-objective GLUE method respectively after taking the semi humid Chenhe River Basin as research area. The study results show that the parameters can be divided into sensitive parameters （SM and CS） and non-sensitivity parameters （K, KG, KI, CG and CI）. Different objective functions have different simulation capabilities for runoff. Compared with single objective function, multi-objective function prediction has greater uncertainty and can cover more measured traffic processes, and the accuracy of flood probability prediction is higher.