水文模型参数敏感性快速定量评估的 RSMSobol方法
An Efficient Quantitative Sensitivity Analysis Approach for Hydrological Model Parameters Using RSMSobol Method
查看参考文献30篇
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文摘
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水文模型参数敏感性分析是模型不确定性量化研究的重要环节，其可以有效识别关键参数，减少模型率定的不确定性，提高模型优化效率。然而如何快速有效地定量评估参数敏感性已成为当前大尺度分布式水文模型优化的瓶颈。针对传统的全局定量敏感性分析方法在多参数复杂水文模型的不足，本文采用基于统计学习理论的支持向量机(SVM)建立非参数响应曲面(称为代理模型)，再结合基于方差的Sobol方法，建立了基于响应曲面方法的Sobol定量全局敏感性分析方法(RSMSobol方法)，实现复杂模型系统参数敏感性的快速定量化评估。本文选用淮河流域的日尺度分布式时变增益水文模型进行实例研究，采用水量平衡系数(WB)， Nash-Sutcliffe效率系数(NS)和相关系数(RC)三个目标函数综合评价模拟效果。研究结果显示 RSMSobol方法在实现定量全局敏感性分析的同时降低了模型运行时耗，提高了模型评估效率，且与传统定量方法Sobol方法具有同样的评估效果。该方法的有效应用为大型复杂水文动力模拟系统的参数定量化敏感性评价提供了参考，为模型参数进一步优化提供了可靠依据。 |
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其他语种文摘
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Sensitivity analysis of hydrological models is a key step for model uncertainty quantification.It can identify the dominant parameters,reduce the model calibration uncertainty,and enhance the model optimization efficiency.However,how to effectively validate a model and identify the dominant parameters for a large-scale complex distributed hydrological model is a bottle-neck to achieve the parameters optimization.There are some shortcomings for classical approaches,e.g.time-consuming and high computation cost,to quantitatively assess the sensitivity of the multi-parameters complex hydrological model.For this reason,a new approach was applied in this paper,in which the support vector machine was used to construct the response surface(a surrogate model)at first.Then it integrated the SVM-based response surface with the Sobol method,i.e.the RSMSobol method,to achieve the quantification assessment of sensitivity for complex models.Taking the distributed time-variant gain model in the Huaihe River Basin as a case study,we selected three objective functions(i.e.water balance coefficient WB,Nash-Sutcliffe efficiency coefficient NS,and correlation coefficient RC)to assess the model as the output responses for sensitivity analysis.The results show that the RSMSobol method can not only achieve the quantification of the sensitivity,and also reduce the computational cost,with good accuracy compared to the classical approaches. |
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来源
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地理学报
,2011,66(9):1270-1280 【核心库】
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关键词
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代理模型
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响应曲面方法
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敏感性分析
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支持向量机
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淮河流域
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地址
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1.
(徐州)中国矿业大学资源与地球科学学院, 江苏, 徐州, 221008
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中国科学院地理科学与资源研究所, 中国科学院陆地水循环及地表过程重点实验室, 北京, 100101
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北京师范大学全球变化与地球系统科学研究院, 北京, 100875
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语种
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中文 |
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文献类型
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研究性论文 |
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ISSN
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0375-5444 |
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基金
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国家重大科技专项
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国家973计划
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中国矿业大学中央高校基本科研业务费专项资金
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文献收藏号
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CSCD:4304631
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