title: [Parameter uncertainty analysis for urban rainfall runoff modelling].
abstract: An urban watershed in Xiamen was selected to perform the parameter uncertainty analysis for urban stormwater runoff modeling in terms of identification and sensitivity analysis based on storm water management model (SWMM) using Monte-Carlo sampling and regionalized sensitivity analysis (RSA) algorithm. Results show that Dstore-Imperv, Dstore-Perv and Curve Number (CN) are the identifiable parameters with larger K-S values in hydrological and hydraulic module, and the rank of K-S values in hydrological and hydraulic module is Dstore-Imperv > CN > Dstore-Perv > N-Perv > conductivity > Con-Mann > N-Imperv. With regards to water quality module, the parameters in exponent washoff model including Coefficient and Exponent and the Max. Buildup parameter of saturation buildup model in three land cover types are the identifiable parameters with the larger K-S values. In comparison, the K-S value of rate constant in three landuse/cover types is smaller than that of Max. Buildup, Coefficient and Exponent.
authors.affiliation: Fujian Provincial Key Laboratory of Coastal Ecology and Environmental Studies, Xiamen University, Xiamen 361005, China. jlhuang@xmu.edu.cn
authors.forename: Jin-Liang
authors.initials: JL
authors.lastname: Huang
authors.forename: Jie
authors.initials: J
authors.lastname: Lin
authors.forename: Peng-Fei
authors.initials: PF
authors.lastname: Du
mesh_terms: D000465:Algorithms; D002681:China; D002947:Cities; D003198:Computer Simulation; D004784:Environmental Monitoring / Q000379:methods*; D008962:Models, Theoretical; D009010:Monte Carlo Method; D011891:Rain; D035501:Uncertainty; D014872:Water Movements