Parameter uncertainty analysis for urban rainfall runoff modelling

Jian Huang, Jie Lin, Peng Fei Du

Research output: Journal article publicationJournal articleAcademic researchpeer-review

4 Citations (Scopus)

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.
Original languageEnglish
Pages (from-to)2224-2234
Number of pages11
JournalHuanjing Kexue/Environmental Science
Volume33
Issue number7
Publication statusPublished - 1 Jul 2012
Externally publishedYes

Keywords

  • Parameter identifiability
  • Regionalized sensitivity analysis (RSA)
  • Storm water management model (SWMM)
  • Uncertainty analysis
  • Urban rainfall runoff

ASJC Scopus subject areas

  • Environmental Science(all)

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