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Stormwater quality modelling in combined sewers: calibration and uncertainty analysis
1Centre d'Enseignement et de Recherche Eau, Ville et Environnement, Ecole Nationale des Ponts et Chaussées, 6-8 avenue Blaise Pascal, 77455 Marne-la-Vallée, France. kanso@cereve.enpc.fr
Abstract:
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.
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