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Evaluating source water protection strategies : a soft computing approach

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Title: Evaluating source water protection strategies : a soft computing approach
Author: Islam, Nilufar
Degree Master of Applied Science - MASc
Program Civil Engineering
Copyright Date: 2010
Publicly Available in cIRcle 2011-01-26
Abstract: Source water protection is an important step in the implementation of a multi-barrier approach that ensures delivery of safe drinking water cost effectively. However, implementing source water protection strategies can be a challenging task due to technical and administrative issues. Currently many decision support tools are available that mainly use complex mathematical formulations. These tools require large data sets to conduct the analysis, which make their use very limited. A simple soft-computing model is proposed in this research that can estimate and predict a reduction in the pollutant loads based on selected source water protection strategies that include storm water management ponds, vegetated filter strips, and pollution control by agricultural practice. The proposed model uses an export coefficient approach and number of animals to calculate the pollutant loads generated from different land uses (e.g., agricultural lands, forests, roads, livestock, and pasture). A surrogate measure, water quality index, is used for the water assessment after the pollutant loads are discharged into the source water. To demonstrate the proof of concept of the proposed model, a Page Creek Case Study in Clayburn Watershed (British Columbia, Canada) was conducted. The results show that rapid urban development and improperly managed agricultural area have the most adverse effects on the source water quality. On the other hand, forests were found to be the best land use around the source water that ensures acceptable drinking water quality with a minimal requirement for treatment. The proposed model can help decision-makers at different levels of government (Federal/ Provincial/ Municipal) to make informed decisions related to land use, resource allocation and capital investment
URI: http://hdl.handle.net/2429/30842
Scholarly Level: Graduate

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