.环境科学,2009,30以澳门与厦门为例[J]对比研究-(12):3514-3521.
[25]邓义祥.稀疏数据条件下河流水质模型的参数识别[D].北
2003.京:清华大学,
[26]王浩昌.基于不确定性分析的SWMM参数识别方法研究及
.北京:清华大学,2009.工具开发[D]
[27]董欣.城市地表径流水质水量特征分析[D].北京:清华大
2007.学,
Journal
of
(1)水文水力模块中Dstore-Imperv、Dstore-Perv
和CurveNumber3个参数可识别性较好;水文水力Imperv>CN>模块的区域灵敏度的排序为:Dstore-Dstore-Perv>N-Perv>Conductivity>Con-Mann>N-Imperv.
(2)SS水质模块中WL1、WL2、BRd1、WRd1、
WRd2、BRf1、BRf3、WRf1、WRf2这9个参数的识别性较好.水质模块SS冲刷函数中的地表冲刷系数(Coefficient)和地表径流幂指数(Exponent)2个参数和累积函数中的地表最大可累积的污染物量(Max.Buildup)的识别性都较高,不确定性较小.而从区域
3种用地类型的RateConstant灵敏度的排序来看,
S距离最小,Max.Buildup、Coefficient和参数K-Exponent参数的K-S距离相对较大.
参考文献:
[1]DrechslerM.Sensitivityanalysisofcomplexmodels[J].
1998,86(3):401-412.BiologicalConservation,
[2]FreniG,ManninaG,VivianiG.Uncertaintyassessmentofan
integratedurbandrainagemodel[J].JournalofHydrology,2009,373(3-4):392-404.
[3]WillemsP.Quantificationandrelativecomparisonofdifferent
J].Watertypesofuncertaintiesinsewerwaterqualitymodeling[Resource,2008,42(13):3539-3551.
[4]ManninaG,FreniG,VivianiG,etal.Integratedurbanwater
modellingwithuncertaintyanalysis[J].WaterScienceandTechnology,2006,54(6-7):379-386.
[5]RadwanM,WillemsP,BerlamontJ.Sensitivityanduncertainty
analysisfor
river
quality
modelling[J].
Hydroinformatics,2004,6(2):83-99.
[6]FreyHC.Quantitativeanalysisofuncertaintyandvariabilityin
environmentalpolicymaking[R].Environmentalscienceandengineeringfellowsprogramreport.Washington,DC:American1992.25-33.AssociationfortheAdvancementofScience,
[7]Bertrand-KrajewskiJL.Stormwaterpollutantloadsmodelling:
epistemologicalaspectsandcasestudiesontheinfluenceoffielddatasetsoncalibrationandverification[J].WaterScienceandTechnology,2007,55(4):1-17.
[8]BeckMB.Waterqualitymodeling:areviewoftheanalysisof
uncertainty[J].WaterResourcesResearch,1987,23(8):1393-1442.
[9]OsideleOO,BeckMB.Identificationofmodelstructurefor
aquaticecosystemsusingregionalizedsensitivityanalysis[J].2001,43(7):271-278.WaterScienceandTechnology,
bbs.99jianzhu.com内容:建筑图纸、PDF/word 流程,表格,案例,最新,施工方案、工程书籍、建筑论文、合同表格、标准规范、CAD图纸等内容。