Login | Register

Particle-tracking Methods for Wastewater Dispersion in Coastal Waters


Particle-tracking Methods for Wastewater Dispersion in Coastal Waters

Liu, Song (2011) Particle-tracking Methods for Wastewater Dispersion in Coastal Waters. Masters thesis, Concordia University.

Text (application/pdf)
Liu_MSc_F2011.pdf - Accepted Version


This study describes the development of a particle-tracking model which predicts the trajectories of particles that apportion wastewater effluents discharged into coastal waters. The subsequent spreading of the effluents is simulated by a large number of particles evolving as clouds. The evolving cloud patterns are predicted for given time-dependent ambient currents and density stratification. The model allows for advection, non-Fickian horizontal diffusion and Richardson number-dependent vertical diffusion. The model is applied to a discharge of wastewater effluents into Burrard Inlet in British Columbia, Canada, where the ambient currents are tidally-driven and the ambient stratification results from river freshwater inflows. This application uses field measurements of ambient conditions as model input. Vertical profiles of effluent concentration derived from simulated particle distributions compare well with field measurements of effluent concentration. The model has shown advantages in handling large spatial gradients of the concentration field, and serves as a useful water-quality modelling tool.

Divisions:Concordia University > Gina Cody School of Engineering and Computer Science > Building, Civil and Environmental Engineering
Item Type:Thesis (Masters)
Authors:Liu, Song
Institution:Concordia University
Degree Name:M.A. Sc.
Program:Civil Engineering
Date:30 May 2011
Thesis Supervisor(s):Li, Samuel
ID Code:7723
Deposited By: SONG LIU
Deposited On:12 Jun 2014 14:52
Last Modified:18 Jan 2018 17:31
All items in Spectrum are protected by copyright, with all rights reserved. The use of items is governed by Spectrum's terms of access.

Repository Staff Only: item control page

Downloads per month over past year

Back to top Back to top