Long-Term Bacterial Dynamics in a Full-Scale Drinking Water Distribution System

Abstract

Large seasonal variations in microbial drinking water quality can occur in distribution networks, but are often not taken into account when evaluating results from short-term water sampling campaigns. Temporal dynamics in bacterial community characteristics were investigated during a two-year drinking water monitoring campaign in a full-scale distribution system operating without detectable disinfectant residual. A total of 368 water samples were collected on a biweekly basis at the water treatment plant (WTP) effluent and at one fixed location in the drinking water distribution network (NET). The samples were analysed for heterotrophic plate counts (HPC), Aeromonas plate counts, adenosine-tri-phosphate (ATP) concentrations, and flow cytometric (FCM) total and intact cell counts (TCC, ICC), water temperature, pH, conductivity, total organic carbon (TOC) and assimilable organic carbon (AOC). Multivariate analysis of the large dataset was performed to explore correlative trends between microbial and environmental parameters. The WTP effluent displayed considerable seasonal variations in TCC (from 90 × 103 cells mL-1 in winter time up to 455 × 103 cells mL-1 in summer time) and in bacterial ATP concentrations (<1–3.6 ng L-1), which were congruent with water temperature variations. These fluctuations were not detected with HPC and Aeromonas counts. The water in the network was predominantly influenced by the characteristics of the WTP effluent. The increase in ICC between the WTP effluent and the network sampling location was small (34 × 103 cells mL-1 on average) compared to seasonal fluctuations in ICC in the WTP effluent. Interestingly, the extent of bacterial growth in the NET was inversely correlated to AOC concentrations in the WTP effluent (Pearson’s correlation factor r = -0.35), and positively correlated with water temperature (r = 0.49). Collecting a large dataset at high frequency over a two year period enabled the characterization of previously undocumented seasonal dynamics in the distribution network. Moreover, high-resolution FCM data enabled prediction of bacterial cell concentrations at specific water temperatures and time of year. The study highlights the need to systematically assess temporal fluctuations in parallel to spatial dynamics for individual drinking water distribution systems.

Flow cytometric bacterial cell counts challenge conventional heterotrophic plate counts for routine microbiological drinking water monitoring

“…Some specific examples include: (i) assessment of chlorine disinfection efficacy (e.g. LeChevallier et al, 1984); (ii) studying the bacteriological activity in biofiltration systems (e.g., Camper et al, 1986); (iii) tracking microbiological changes as a result of regrowth and biological instability of drinking water (e.g., Francisque et al, 2009;Uhl and Schaule, 2004;Prest et al, 2016a); (iv) quantifying batch growth of bacteria during incubation (i.e. stagnation) of nano-filtered drinking water (Liikanen et al, 2003) and unfiltered drinking water (Uhl and Schaule, 2004), and during overnight stagnation in building plumbing (e.g., Pepper et al, 2004;Lautenschlager et al, 2010).…”

Online flow cytometry reveals microbial dynamics influenced by concurrent natural and operational events in groundwater used for drinking water treatment

“…The costs and labor-intensive nature of the latter hinder the investigation of short-term dynamics at adequate temporal resolution. While infrequent measurements of raw and treated water can capture long-term (months-to-years) trends such as seasonal changes in abiotic and microbial variables293031, it fails to capture dynamics on shorter terms (hours-to-weeks)3233. Specifically, with infrequent sampling a considerable amount of uncertainty remains with respect to i) the predominant contaminant concentration levels (e.g., prevalent dry-weather conditions in temperate climates), ii) the frequency of deviations from this level, iii) whether the deviations are real (rather than single erroneous measurements), and iv) the full magnitude and duration of the deviations.…”

The impact of rainfall on drinking water quality in Antananarivo, Madagascar

“…Among these factors, the effectiveness of the treatment process is certainly the most important and must be carefully adapted to the quality of the incoming raw water. However, hydraulic conditions (e.g., flow velocity and intermittent water supply) and water quality (e.g., presence of sediments or excess of turbidity) can enhance bacterial growth and sediment dissolution in final drinking water [17,42].…”