Analysis of a large spatiotemporal groundwater quality dataset, Ontario 2010-2017: Informing human health risk assessment and testing guidance for private drinking water wells

摘要

Approximately 1.5 million individuals in Ontario are supplied by private water wells (private groundwater supplies). Unlike municipal supplies, private well water quality remains unregulated, with owners responsible for testing, treating, and maintaining their own water supplies. The primary goal of this study was to assess the effect of repeat sampling of private well water in Ontario and investigate the efficacy of geographically- and/or temporally specific testing recommendations and health risk assessments. The current study combines the Well Water Information System Dataset and the Well Water Testing Dataset from 2010 to 2017, inclusive. These two large existing province-wide datasets collated over an eight-year period were merged using an integrated spatial fuzzy logic and (next)- nearest neighbour approach. Provincial sampling data from 239,244 wells (702,861 samples) were analyzed for Escherichia coli to study the relationship between sampling frequency and Escherichia coli detection. Dataset variables were delineated based on hydrogeological setting (e.g. aquifer type, overburden depth, well depth, bedrock type) and seasonality to provide an in-depth understanding of Escherichia coli detection in private well water. Findings reveal differences between detection rates in consolidated and unconsoli-dated aquifers (p = 0.0191), and across seasons (p ＜ 0.0001). The variability associated with Escherichia coli detection rates was explored by estimating sentinel sampling rates for private wells sampled three times, twelve times and twenty-four times per year. As sample size increases on an annual basis, so too does detection rate, highlighting the need to address current testing frequency guidelines. Future health risk assessments for private well water should consider the impact of spatial and temporal factors on the susceptibility of this drinking water source, leading to an increasingly accurate depiction of private well water contamination and the estimated effects on human health.