期刊文献+

海绵城市LID设施模型参数敏感性研究 被引量:12

Sensitivity analysis of SWMM model LID facility parameters based on morris analysis
下载PDF
导出
摘要 随着各地海绵城市建设的推进,模型评估在海绵城市低影响开发设计中得到广泛运用,准确的LID设施模型参数确定是其应用可靠的关键性问题。以厦门海绵城市试点建设为契机,采用Morris分析方法,对SWMM模型中的几类LID设施模型参数进行敏感性分析。研究结果表明,表面粗糙系数对于植草沟设施而言是高敏感参数,土壤导水率对于绿色屋顶、生物滞留池设施而言是高敏感参数,土壤导水率和表面粗糙系数对于透水铺装设施而言是高敏感参数。 With the advancement of sponge city construction in various cities, model evaluation has been widely used in the low-impact development design of sponge cities. Accurate LID facility model parameter determination is a key issue for its application reliability. Taking the Xiamen sponge city pilot area as an example, this paper uses the Morris analysis method to analyze the sensitivity of several types of LID facility model parameters in the SWMM model. The results show that the surface roughness is a highly sensitive parameter for the planting ditch facility. The soil hydraulic conductivity is a highly sensitive parameter for green roof and bioretention pond facilities. The soil hydraulic conductivity and surface roughness are for permeable paving facilities. It is a highly sensitive parameter.
作者 王泽阳 Wang Zeyang(Xiamen Urban Planning and Design Institute,Xiamen Sponge City Engineering Technology Research Center,Xiamen 361012,China)
出处 《给水排水》 CSCD 北大核心 2019年第11期57-62,共6页 Water & Wastewater Engineering
基金 国家“十三五”重点研发计划(2016YFC0502903)
关键词 MORRIS SWMM模型 参数敏感性 LID设施 Morris SWMM model Sensitivity analysis LID facility
  • 相关文献

参考文献3

二级参考文献25

  • 1Saltelli A, Chan K, Scott E M. Sensitivity Analysis [M]. New York (Eds.) :Wiley, 2000.
  • 2Beven K, Prophecy. Reality and uncertainty in distributed hydro- logical modeling [J]. Advances in Water Resources, 1993,16(1) :41 -51.
  • 3Melching C S, Yoon C G. Key sources of uncertainty in QUAL2E model of Passaic river [J]. ASCE Journal of Water Resources Planning and Management, 1996,122(2) : 105- 113.
  • 4Mekay M D, Beckman R J, Conover W J. A comparison of threemethods for selecting values of input variables in the analysis of output from a computer code [-J]. Technometrics, 1979,21:239 -245.
  • 5Van Griensven A, Meixner T, Grunwald S, et al. A global sensi- tivity analysis tool for the parameters of multi- variable catch- ment methods [J]. Journal of Hydrology, 2006,324 ( 1 - 4) .. 10- 23.
  • 6Morris M D. Factorial sampling plans for preliminary computa- tional experiments [J]. Technometrics, 1991,33(2) .. 161- 174.
  • 7Karim C, Jing Yang. Modeling hydrology and water quality in the pre-alpine Thur watershed using SWAT [-J]. Journal of Hydrol- ogy, 2007,333,413-430.
  • 8Van Griensven A, T Meixner, S Grunwald, T Bishop, et al. A global sensitivity analysis tool for the parameters of multivariable catchment models [J]. Hydrology, 2006,324,10-23.
  • 9Sobol I. Sensitivity analysis for non-linear mathematical models [J]. Mathematical Modeling & Computational Experiment, 1993,1..407-414.
  • 10Fishman G S. Monte Carlo: concepts, algorithms and appliea- tions[M] New York: Springer,1996.

共引文献59

同被引文献139

引证文献12

二级引证文献55

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部