Characterizing Risk through Water Safety Plans and Investigating Drinking Water Advisories in First Nations Communities using Probabilistic Neural Networks
Safe clean drinking water is a basic human need and yet many communities face challenges in providing clean water to their population. This research looks to address issues in drinking water treatment systems from two different perspectives, first taking a local level approach in the water system itself, then looking at trends in the occurrence, frequency, duration, and cause of drinking water advisories (DWAs) in First Nations communities across Canada. A risk assessment template for identifying hazards in a drinking water system, from source, through treatment and distribution, to the consumer, was evaluated, and a condensed version was developed which was more robust at identifying higher risk areas of the system. Next, an artificial neural network model is used to identify different key factors affecting DWAs in different provinces across Canada, suggesting that a Canada-wide approach is not adequate to reduce DWAs.