A storm water basin model using settling velocity distribution. Issue 4 (24th October 2016)

• Record Type: Journal Article
• Authors: Vallet, Bertrand; Lessard, Paul; Vanrolleghem, Peter A.
• Is Part Of: Journal of environmental engineering and science. Volume 11:Issue 4(2016)
• Page Start: 84
• Page End: 95
• Publication Date: 2016-10-24
• Subjects: hydrology & water resource -- mathematical modelling -- municipal & public service engineering; Environmental engineering -- Periodicals; Sanitary engineering -- Periodicals; Environmental engineering -- Canada -- Periodicals; Environnement, Technique de l' -- Périodiques; Technique sanitaire -- Périodiques; Environnement, Technique de l' -- Canada -- Périodiques; Environmental engineering; Sanitary engineering; Canada; Electronic journals; Computer network resources; Periodicals; 628.05
• DOI: 10.1680/jenes.15.00017
• Languages: English
• ISSNs: 1496-2551

Abstract

Abstract : Quantifying processes that affect the fate of particles in storm water basins is a complex but necessary step to predict the effect of various pollutants on receiving waters. A dynamic model for storm water basins taking advantage of the experimental fractionation of particles in different settling velocity classes has been developed to describe the water quality dynamics in the basin. This paper is focused on the calibration of the model using total suspended solids (TSS) time series data and settling velocity distribution data obtained from ViCAs ( vitesse de chute en assainissement ) tests. Experimental sampling campaigns have been conducted at an actual storm water basin to identify the TSS behaviour under various operational conditions. For one set of experiments, the outlet was always open, and for another, the outlet was kept closed to allow settling before release to the receiving water. The experimental results reveal spatial heterogeneity of the particle concentrations in the basin during the initial phases of water retention for the closed outlet sampling campaign. A calibration procedure is proposed to fit the model to the experimental data. This model was found able to reproduce both open and closed outlet TSS concentration time series with only three particle classes.