Estimating the level of uncertainty in urban stormwater quality models is vital for their utilization. This paper presents the results of application of a Monte Carlo Markov Chain method based on the Bayesian theory for the calibration and uncertainty analysis of a storm water quality model commonly used in available software. The tested model uses a hydrologic/hydrodynamic scheme to estimate the accumulation, the erosion and the transport of pollutants on surfaces and in sewers. It was calibrated for four different initial conditions of in-sewer deposits. Calibration results showed large variability in the model's responses in function of the initial conditions. They demonstrated that the model's predictive capacity is very low. © IWA Publishing 2005.
CITATION STYLE
Kanso, A., Chebbo, G., & Tassin, B. (2005). Stormwater quality modelling in combined sewers: Calibration and uncertainty analysis. Water Science and Technology, 52(3), 63–71. https://doi.org/10.2166/wst.2005.0062
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