A Systematic Approach for Assessing the Potential Impacts of Beneficial Management Practices on Wells Affected by Non-Point Sources of Contamination

Tuesday, April 21, 2009: 3:10 p.m.
Joshua Tree (Hilton Tucson El Conquistador Golf & Tennis Resort )
Marcelo R. Sousa , University of Waterloo, Waterloo, ON, Canada
David L. Rudolph, Ph.D., PE , University of Waterloo, Waterloo, ON, Canada
Emil O. Frind , University of Waterloo, Waterloo, ON, Canada
Rengina Rahman , University of Waterloo, Waterloo, ON, Canada
Contaminants from non-point sources, such as road de-icing chemicals and nitrate from agricultural areas, are a major concern for ground water management when in high or increasing concentrations on water supply wells. One approach to address the problem is the adoption of Beneficial Management Practices (BMPs) to reduce contaminant loadings within the capture zone of affected wells. In this context, there are several important questions that arise related to the implementation of these measures, such as: What are the ideal target areas? What is the time frame for the effects of implemented BMPs to take place? What should be the reduction of the mass loadings in a certain area within the capture zone in order to keep the concentrations on the pumping well under a desired limit?

In order to assist in the decision making process, a systematic physically-based modeling approach was developed and it is currently being applied to a supply well impacted by nitrate and located in an agricultural setting within a complex glacial aquifer system in Southern Ontario, Canada. This approach consists in a series of steps involving the use of numerical models in two different scales (regional and capture zone), the application of the concept of well vulnerability for unknown sources and the use of sensitivity analysis for both flow and transport parameters. The outcome of this approach allows the comparison between different BMPs scenarios, both in terms of magnitude and time frame of changes in the concentration on the supply wells. Also, the sensitivity steps included in the approach provide the necessary appreciation of the prediction uncertainties and guidance for future data acquisition. The results obtained from this approach, along with the consideration of other aspects involved (economic, social etc.), should provide a solid base to support the decision making process in these situations.