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.
Stormwater quality modelling in combined sewers: calibration and uncertainty analysis
A. Kanso, G. Chebbo, B. Tassin; Stormwater quality modelling in combined sewers: calibration and uncertainty analysis. Water Sci Technol 1 August 2005; 52 (3): 63–71. doi: https://doi.org/10.2166/wst.2005.0062
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