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基于物理基础的水文模型预测精度受不确定性影响显著,分析这些不确定性因素对模型预测精度的提高十分必要.目前对于水文模型不确定性研究比较成熟,众多专家已经提出了模型不确定分析的框架,同时设计了一些模型优化算法,但较为缺乏针对模型结构不确定性研究的系统内容.通过选择具有物理基础的水文模型——HYDRUS,分别开展模型参数和结构的不确定性研究.结果表明,详实的观测信息是模型选择不可缺少的;不同时间点的模型信息对模型的确定更为有用;在选择模型时,应充分了解真实结构信息,减少因模型结构误差所带来的模型预测不确定性.在目标函数的选择上,也应充分考虑模型结构的不确定性.要减少模型不确定性,必须加强对模型参数和结构的认识.
The prediction accuracy of hydrological model based on physical foundation is significantly affected by the uncertainty, and it is necessary to analyze these uncertainties to improve the prediction accuracy of the model.At present, the research on the uncertainty of hydrological model is relatively mature, and many experts have proposed the model uncertainty analysis , And some model optimization algorithms are designed at the same time, but there is a lack of systematic research on the uncertainty of model structure.Hyddynamic model is chosen to study the uncertainty of model parameters and structure by selecting HYDRUS, a physical model.Results It shows that detailed observation information is indispensable for model selection. Model information at different time points is more useful for model determination. When choosing model, we should fully understand the real structure information and reduce the model prediction caused by model structure error Uncertainty In the choice of the objective function, the uncertainty of the model structure should also be fully taken into account. To reduce the uncertainty of the model, the knowledge of the model parameters and structure must be strengthened.