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论文摘要

水文模型不确定性分析的多准则似然判据GLUE方法

Uncertainty analysis of hydrological model using multi-criteria likelihood measure within the GLUE framework

作者:刘艳丽(大连理工大学土木水利学院);梁国华(大连理工大学土木水利学院);周惠成(大连理工大学土木水利学院)

Author:LIU YAN-LI();();()

收稿日期:2008-06-13          年卷(期)页码:2009,41(4):89-96

期刊名称:工程科学与技术

Journal Name:Advanced Engineering Sciences

关键字:洪水预报;不确定性分析;GLUE;多准则似然判据;大伙房模型

Key words:flood forecasting; uncertainty analysis; GLUE; multi-criteria likelihood measure; DHF(Da Huofang) model

基金项目:国家自然科学基金

中文摘要

水文模型不确定性分析GLUE(Generalized Likelihood uncertainty Estimation)方法常用似然判据Nash-Sutcliffe系数(确定性系数),这种判别标准侧重对整体过程误差的估计,对点状况如洪峰的表征不够,不能准确地反映模型的不确定性情况。本研究基于GLUE方法,建立了多准则似然判据,应用北方水库常用的大伙房模型,对碧流河水库洪水预报的不确定性进行研究,并给出预报误差分析。结果表明,将常用的确定性系数似然判据扩展为洪峰误差、洪量、峰现时间、确定性系数四个目标的多准则似然判据,能更好地反映模型的实际不确定情况,对模型参数的率定和不确定性研究具有重要意义。

英文摘要

GLUE(Generalized Likelihood uncertainty Estimation) is a very wide-used methodology for uncertainty analysis of hydrological model. How to select an appropriate likelihood measure is still an open question so far. Usually the Nash-Sutcliffe coefficient is a traditional likelihood measure, but this measure focuses on the global performance without a special assessment in point condition especially for flood peak. A multi-criteria likelihood measure is presented within GLUE methodology, which consists of peak forecast error, runoff error, peak time error, and Nash-Sutcliffe coefficient. Based on the DHF(Da Huofang)model, it was applied to Biliuhe catchment. Forecasting error analysis was deduced. The results show the multi-criteria likelihood measure has improved compared with the original measure in describing the real uncertainty of model, which is very valuable for model calibration and uncertainty study.

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