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Evaluation of urban stormwater quality models: a bayesian approach

Assem Kanso
Abstract : This thesis aims at analyzing and evaluating the urban stormwater quality models. For this reason, a benchmark based on the utilization of a methodology founded on the Bayesian theory was established. This benchmark was utilized in different space scales all along the water course from street surfaces to the sewage outlet at the "Le Marais" watershed in Paris. This benchmark methodology uses a Metropolis Algorithm, from the Monte Carlo Markov Chain family of techniques, to estimate the posterior probability distribution of the model's parameters, which permits: - A quantitative estimation of uncertainties related to the estimation of parameters as well as their interaction; - A quantitative assessment of the uncertainty level in the results of the models' application; - An estimation of the predictive power of the model. At the local scale, models of pollutants' accumulation and erosion on 6 street subcatchments, and solids' erosion models in 2 combined sewer pipes were tested and analyzed. At the watershed level, the coupling of elementary models as they are currently used in software was evaluated. The methodology produced reliable results particularly of the models' parameter distributions that help in the mathematical analysis and the interpretation of the currently used models. It has demonstrated the existence of large uncertainties related to the utilization of the MCFP at the catchment scale. These models only explain a modest part of the variation of the MES concentration between two rain events or inside the same event.
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Submitted on : Thursday, June 2, 2005 - 8:00:00 AM
Last modification on : Friday, October 23, 2020 - 4:52:00 PM
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Assem Kanso. Evaluation of urban stormwater quality models: a bayesian approach. Sciences of the Universe [physics]. Ecole des Ponts ParisTech, 2004. English. ⟨pastel-00001264⟩

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