The use of E. coli phylogrouping and microbial source tracking (non-species specific, human-specific, bovine-specific bacteroidales markers) to elucidate hydro(geo)logical contamination mechanisms in southeastern Ontario, Canada.

In Ontario, monitoring, maintenance, and treatment of private drinking systems (e.g. wells) are the responsibility of the well owner. Fecal contamination of drinking water threatens public health, particularly in rural communities which are often fully reliant on unregulated private groundwater as a primary drinking water source. Private well users face a higher risk of acute gastrointestinal illness compared to those served by municipally operated systems (Murphy et al., 2016). Accordingly, the current study sought to characterize the fecal indicator, E. coli, isolated from southeastern Ontario private groundwater wells, including phylogroups and host source. Results were examined in the context of antecedent climate and local hydrogeological setting to elucidate likely contaminant sources and pathways. A total of 737 E. coli isolates from 260 private wells were assigned to phylogroups using the Clermont PCR phylotyping method, with likely host source determined using host-specific Bacteroidales 16S rRNA RT qPCR assays. Multivariate models were developed for the main E. coli phylogroups (A, B1, B2, and D) and all microbial source tracking markers. Models were coupled for interpretation where possible, based on associations between phylogroups and MST markers. Preferential subsurface flow, and to a lesser degree, overland flow, were likely mechanisms of contamination across all models. Distinct temporal associations were found based on the fecal source. Multiple models were developed and will be discussed, in an attempt to elucidate source-specific contamination mechanisms, in support of risk assessment and appropriate protective actions.

Development of a "big data" groundwater microbial contamination index and spatial comparisons with enteric infection rates in southern Ontario.

Big data have become increasingly important for policymakers and scientists but have yet to be employed for the development of spatially specific groundwater contamination indices or protecting human and environmental health. The current study sought to develop a series of indices via analyses of three variables: Non-E. coli coliform (NEC) concentration, E. coli concentration, and the calculated NEC:E. coli concentration ratio. A large microbial water quality dataset comprising 1,104,094 samples collected from 292,638 Ontarian wells between 2010 and 2021 was used. Getis-Ord Gi* (Gi*), Local Moran's I (LMI), and space-time scanning were employed for index development based on identified cluster recurrence. Gi* and LMI identify hot and cold spots, i.e., spatially proximal subregions with similarly high or low contamination magnitudes. Indices were statistically compared with mapped well density and age-adjusted enteric infection rates (i.e., campylobacteriosis, cryptosporidiosis, giardiasis, verotoxigenic E. coli (VTEC) enteritis) at a subregional (N = 298) resolution for evaluation and final index selection. Findings suggest that index development via Gi* represented the most efficacious approach. Developed Gi* indices exhibited no correlation with well density, implying that indices are not biased by rural population density. Gi* indices exhibited positive correlations with mapped infection rates, and were particularly associated with higher bacterial (Campylobacter, VTEC) infection rates among younger sub-populations (p < 0.05). Conversely, no association was found between developed indices and giardiasis rates, an infection not typically associated with private groundwater contamination. Findings suggest that a notable proportion of bacterial infections are associated with groundwater and that the developed Gi* index represents an appropriate spatiotemporal reflection of long-term groundwater quality. Bacterial infection correlations with the NEC:E. coli ratio index (p < 0.001) were markedly different compared to correlations with the E. coli index, implying that the ratio may supplement E. coli monitoring as a groundwater assessment metric capable of elucidating contamination mechanisms. This study may serve as a methodological blueprint for the development of big data-based groundwater contamination indices across the globe.

An assessment of total coliforms and associated thresholds as water quality indicators using a large Ontario private drinking water well dataset.

A spatiotemporally static total coliform (TC) concentration threshold of five colony-forming units (CFU) per 100 mL is used in Ontario to determine whether well water is of acceptable quality for drinking. The current study sought to assess the role of TC and associated thresholds as microbial water quality parameters as the authors hypothesized that, since static TC thresholds are not evidence-based, they may not be appropriate for all well water consumers. A dataset containing the microbial water quality information of 795,023 samples (including TC and Escherichia coli (E. coli) counts) collected from 253,136 private wells in Ontario between 2010 and 2017 was used. To accurately assess the relationship between E. coli and non-E. coli TC, "non-E. coli coliform" (NEC) counts were calculated from microbial water quality data and replaced TC throughout analyses. This study analysed NEC and E. coli detection rates to determine differences between the two, and NEC:E. coli concentration ratios to assess links, if any, between NEC and E. coli contamination. Study findings suggest that spatiotemporally static NEC thresholds are not appropriate because seasonal, spatial, and well-specific susceptibility factors are associated with distinct contamination trends. For example, NEC detection rates exhibited bimodality, with summer (29.4 %) and autumn (30.2 %) detection rates being significantly higher (p < 0.05) than winter (21.9 %) and spring (19.9 %). E. coli detection rates also varied seasonally, but peaked in summer rather than autumn. As such, it is recommended that these factors be considered during the development of private well water guidelines and that static thresholds be avoided. Furthermore, the authors propose that, because NEC:E. coli concentration ratios change in the context of the aforementioned factors, they may have a role in inferring groundwater contamination mechanisms, with high ratios being associated with generalized aquifer contamination mechanisms and low ratios with localized contamination mechanisms.