title: Applying global sensitivity analysis to the modelling of flow and water quality in sewers.
abstract: While several approaches for global sensitivity analysis (GSA) have been proposed in literature, only few applications exist in urban drainage modelling. This contribution discusses two GSA methods applied to a sewer flow and sewer water quality model: Standardised Regression Coefficients (SRCs) using Monte-Carlo simulation as well as the Morris Screening method. For selected model variables we evaluate how the sensitivities are influenced by the choice of the rainfall event. The aims are to i) compare both methods concerning the similarity of results and their applicability, ii) discuss the implications for factor fixing (identifying non-influential parameters) and factor prioritisation (identifying important parameters) and iii) rank the important parameters for the investigated model. It was shown that both methods lead to similar results for the hydraulic model. Parameter interactions and non-linearity were identified for the water quality model and the parameter ranking differs between the methods. For the investigated model the results allow a sound choice of output variables and rainfall events in view of detailed uncertainty analysis or model calibration. We advocate the simultaneous use of both methods for a first model assessment as they allow answering both factor fixing and factor prioritisation at low computational cost.
authors.affiliation: Graz University of Technology, Institute of Urban Water Management and Landscape Water Engineering, Stremayrgasse 10/1, A-8010 Graz, Austria. gamerith@hydroconsult.net
authors.forename: Valentin
authors.initials: V
authors.lastname: Gamerith
authors.forename: Marc B
authors.initials: MB
authors.lastname: Neumann
authors.forename: Dirk
authors.initials: D
authors.lastname: Muschalla
mesh_terms: D004323:Drainage, Sanitary; D008962:Models, Theoretical; D009010:Monte Carlo Method; D011891:Rain; D012044:Regression Analysis; D012212:Rheology; D060753:Water Quality
keywords: Global sensitivity analysis; Parameter ranking; Sewer water quality; Urban drainage modelling