分布式水文模型全局敏感性高效分析方法研究(英文)

编号 zgly0001585746

文献类型 期刊论文

文献题名 分布式水文模型全局敏感性高效分析方法研究(英文)

作者 宋晓猛  占车生  夏军  孔凡哲 

作者单位 SchoolofResourceandEarthScience  ChinaUniversityofMining&Technology  KeyLaboratoryofWaterCycle&RelatedLandSurfaceProcesses  InstituteofGeographicSciencesandNaturalResourcesResearch  CAS 

母体文献 Journal of Geographical Sciences 

年卷期 2012年02期

年份 2012 

分类号 P334.92 

关键词 responsesurfacemethodology  sensitivityanalysis  supportvectormachines  RSMSobolmethod  HuaiheRiverBasin 

文摘内容 Sensitivity analysis of hydrological model is the key for model uncertainty quantification. However, how to effectively validate model and identify the dominant parameters for distributed hydrological models is a bottle-neck to achieve parameters optimization. For this reason, a new approach was proposed in this paper, in which the support vector machine was used to construct the response surface at first. Then it integrates the SVM-based response surface with the Sobol’ method, i.e. the RSMSobol’ method, to quantify the parameter sensitivities. In this work, the distributed time-variant gain model (DTVGM) was applied to the Huaihe River Basin, which was used as a case to verify its validity and feasibility. We selected three objective functions (i.e. water balance coefficient WB, Nash-Sutcliffe efficiency coefficient NS, and correlation coefficient RC) to assess the model performance as the output responses for sensitivity analysis. The results show that the parameters g1 and g2 are most important for all the objective functions, and they are almost the same to that of the classical approach. Furthermore, 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 approach. And this approach will be effective and reliable in the global sensitivity analysis for a complex modelling system.