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姜倩妮, 李占玲, 张永勇.GLUE框架下似然函数对水文模型不确定性的影响水资源与水工程学报[J].,2018,29(1):25-30
GLUE框架下似然函数对水文模型不确定性的影响
Effect assessment of different likelihood functions on parameter uncertainty of hydrological model under the GLUE framework
  
DOI:10.11705/j.issn.1672-643X.2018.01.04
中文关键词:  不确定性  GLUE方法; 参数敏感性; 预测区间; 似然函数  水文模型
英文关键词:parameter uncertainty  GLUE method  parameter sensitivity  prediction bounds  likelihood function  hydrological model
基金项目:国家重点研发计划项目(2016YFC0400902); 国家自然科学基金项目(41671024); 中国科学院地理科学与资源研究所秉维优秀青年人才计划项目(2015RC201); 中国科学院青年创新促进会项目(2014041)
作者单位
姜倩妮1, 李占玲1, 张永勇2 (1.中国地质大学(北京) 水资源与环境学院 北京 100083 2.中国科学院地理科学与资源研究所陆地水循环及地表过程重点实验室 北京 100101) 
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中文摘要:
      似然函数的选取对模型参数不确定性结果存在较大影响。本文以淮河上游大坡岭水文站控制流域为例,采用GLUE不确定性分析方法、SCE-UA优化算法与流域水循环系统模型(HEQM)耦合,探索Nash-Sutcliffe系数与水量平衡系数这两个似然函数对模型参数敏感性、取值分布特征以及不确定性的影响。结果表明:从敏感性分析结果来看,Nash-Sutcliffe系数作为似然函数时,所选择的9个参数均为敏感性参数,而水量平衡系数作似然函数时,仅有1个敏感性参数,Nash-Sutcliffe系数更适合作似然函数;从不确定性区间评价结果来看,水量平衡系数作为似然函数时,模拟结果的覆盖率和对称性均优于Nash-Sutcliffe系数。以上研究可为GLUE方法似然函数的选取提供参考,也为多目标GLUE方法中权重的分配提供理论依据。
英文摘要:
      The selection of likelihood function has great influence on the uncertainty of model parameters. In this study, taking the control basin of Dapoling Hydrological Station upstream of Huaihe River as an example, the GLUE method was combined with the integrated water system model (HEQM) and the optimization algorithm SCE-UA to analyze the influence of different likelihood functions (i.e., Nash-Sutcliffe coefficient and water balance coefficient) on the model parameter sensitivity, value distribution and uncertainty. The results showed that: From the sensitivity analysis, when the Nash-Sutcliffe coefficient is taken as the likelihood function, all the nine parameters selected are sensitive parameters, and when the water balance coefficient is a likelihood function, there is only one sensitivity parameter. The Nash-Sutcliffe coefficient is more suitable as a likelihood function;Seeing from the evaluation results of uncertainty interval, water balance coefficient was more suitable as a likelihood function, because its coverage and symmetry were better than those of Nash-Sutcliffe coefficient. This study was expected to not only provide some references for selecting likelihood function in GLUE method, but also to give the theoretical basis for weight assignment of the multi-objective GLUE method.
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