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A GIS-Based Water Quality Assessment and Pollution Control Planning Approach for Lake Management (WQAPCP)


A GIS-Based Water Quality Assessment and Pollution Control Planning Approach for Lake Management (WQAPCP)

Geng, Li Kai (2017) A GIS-Based Water Quality Assessment and Pollution Control Planning Approach for Lake Management (WQAPCP). Masters thesis, Concordia University.

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Many lakes are receiving large volumes of contaminants from agricultural discharges, industrial emissions and municipal wastewater, which causes significant surface water pollution. The adverse environmental and health effects of lake contamination are a primary concern in environmental management. Water quality assessment methods and pollution control planning models are useful tools for researchers and decision-makers to protect ecological environments and develop local economies. Also spatial information technologies such as Geographic Information Systems (GIS) make it possible to manage water bodies with more detailed location-based information.
The goal of this thesis is to develop a GIS-based water quality assessment and pollution control planning approach for lake management (WQAPCP), which includes the following components: (1) evaluation of water quality based on four index methods with inter-comparisons; (2) pollution control planning for a lake system based on an integration of pollutant distribution simulation and optimization models along with water quality index measures; (3) GIS technology to help implementing water quality assessment and lake contamination control optimization by creating displayed maps of the study results to provide spatial support for decisions.
Several water quality evaluation methods are first presented in this thesis within the GIS framework to examine water quality index models, including the US Oregon water quality index (OWQI), the Canadian water quality index (CWQI), the Chinese single-factor water quality index (CNWQI-S) and the Chinese comprehensive water quality index (CNWQI-C) methods. These index methods are applied to assess the water quality of a real case. The assessment results are presented in the form of GIS maps containing the spatial distribution of the water quality levels and their ranking. Through an example of sensitivity analysis and comparison of four sets of water quality assessment results, the parameters with the most significant influence on lake water quality are identified and the most suitable method of water quality evaluation is put forward to support future lake management.
Subsequently, this thesis develops a simulation-optimization approach by integrating lake water quality simulation and lake pollution control optimization. A contaminant dispersion simulation is first conducted to provide input for the optimization study. Particularly, a single-objective programming (SOP) model and a multi-objective programming (MOP) model are developed, applied, and compared to support effective lake water contamination control planning under different lake management scenarios. Three periods and a set of significant levels are considered in the real case study to provide a comprehensive dynamic modeling and optimization analysis of lake pollution control through the simulation-optimization approach. Based on the developed optimization method and the case study results, the OWQI and CNWQI-C methods are utilized to help formulating the effective measures for lake water quality management.
GIS technology is employed in this study to link the water quality assessment approaches and the lake pollution control optimization. By integrating the relevant data and creating visualized maps of the study results, GIS plays an important role in extending the modeling and assessment results for the lake water quality management with spatial geo-references.

Divisions:Concordia University > Gina Cody School of Engineering and Computer Science > Building, Civil and Environmental Engineering
Item Type:Thesis (Masters)
Authors:Geng, Li Kai
Institution:Concordia University
Degree Name:M.A. Sc.
Program:Civil Engineering
Date:15 April 2017
Thesis Supervisor(s):Chen, Z.
ID Code:982465
Deposited By: LIKAI GENG
Deposited On:09 Jun 2017 13:55
Last Modified:18 Jan 2018 17:55
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