Evaluation of the Performance and the Predictive Capacity of Build-Up and Wash-Off Models on Different Temporal Scales

Abstract : Stormwater quality modeling has arisen as a promising tool to develop mitigation strategies. The aim of this paper is to assess the build-up and wash-off processes and investigate the capacity of several water quality models to accurately simulate and predict the temporal variability of suspended solids concentrations in runoff, based on a long-term data set. A Markov Chain Monte-Carlo (MCMC) technique is applied to calibrate the models and analyze the parameter’s uncertainty. The short-term predictive capacity of the models is assessed based on inter- and intra-event approaches. Results suggest that the performance of the wash-off model is related to the dynamic of pollutant transport where the best fit is recorded for first flush events. Assessment of SWMM (Storm Water Management Model) exponential build-up model reveals that better performance is obtained on short periods and that build-up models relying only on the antecedent dry weather period as an explanatory variable, cannot predict satisfactorily the accumulated mass on the surface. The predictive inter-event capacity of SWMM exponential model proves its inability to predict the pollutograph while the intra-event approach based on data assimilation proves its efficiency for first flush events only. This method is very interesting for management practices because of its simplicity and easy implementation.
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Urban Water, Elsevier, 2016, 8 (8), 〈10.3390/w8080312〉
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https://hal-enpc.archives-ouvertes.fr/hal-01383105
Contributeur : Céline Bonhomme <>
Soumis le : mardi 18 octobre 2016 - 10:13:31
Dernière modification le : vendredi 1 décembre 2017 - 01:19:09

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Saja Al Ali, Céline Bonhomme, Ghassan Chebbo. Evaluation of the Performance and the Predictive Capacity of Build-Up and Wash-Off Models on Different Temporal Scales. Urban Water, Elsevier, 2016, 8 (8), 〈10.3390/w8080312〉. 〈hal-01383105〉

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