β-D-glucuronidase activity triggered monitoring of fecal contamination using microbial and chemical source tracking markers at drinking water intakes

Intense rainfall and snowmelt events may affect the safety of drinking water, as large quantities of fecal material can be discharged from storm or sewage overflows or washed from the catchment into drinking water sources. This study used β-d-glucuronidase activity (GLUC) with microbial source tracking (MST) markers: human, bovine, porcine mitochondrial DNA markers (mtDNA) and human-associated Bacteroidales HF183 and chemical source tracking (CST) markers including caffeine, carbamazepine, theophylline and acetaminophen, pathogens (Giardia, Cryptosporidium, adenovirus, rotavirus and enterovirus), water quality indicators (Escherichia coli, turbidity) and hydrometeorological data (flowrate, precipitation) to assess the vulnerability of 3 drinking water intakes (DWIs) and identify sources of fecal contamination. Water samples were collected under baseline, snow and rain events conditions in urban and agricultural catchments (Québec, Canada). Dynamics of E. coli, HF183 and WWMPs were similar during contamination events, and concentrations generally varied over 1 order of magnitude during each event. Elevated human-associated marker levels during events demonstrated that urban DWIs were impacted by recent contamination from an upstream municipal water resource recovery facility (WRRF). In the agricultural catchment, mixed fecal pollution was observed with the occurrences and increases of enteric viruses, human bovine and porcine mtDNA during peak contaminating events. Bovine mtDNA qPCR concentrations were indicative of runoff of cattle-derived fecal pollutants to the DWI from diffuse sources following rain events. This study demonstrated that the suitability of a given MST or CST indicator depend on river and catchment characteristics. The sampling strategy using continuous online GLUC activity coupled with MST and CST markers analysis was a more reliable source indicator than turbidity to identify peak events at drinking water intakes.

Persistence of endogenous RNA biomarkers of SARS-CoV-2 and PMMoV in raw wastewater: Impact of temperature and implications for wastewater-based epidemiology

Understanding the persistence of SARS-CoV-2 biomarkers in wastewater should guide wastewater-based epidemiology users in selecting best RNA biomarkers for reliable detection of the virus during current and future waves of the pandemic. In the present study, the persistence of endogenous SARS-CoV-2 were assessed during one month for six different RNA biomarkers and for the pepper mild mottle virus (PMMoV) at three different temperatures (4, 12 and 20 °C) in one wastewater sample. All SARS-CoV-2 RNA biomarkers were consistently detected during 6 days at 4° and differences in signal persistence among RNA biomarkers were mostly observed at 20 °C with N biomarkers being globally more persistent than RdRP, E and ORF1ab ones. SARS-CoV-2 signal persistence further decreased in a temperature dependent manner. At 12 and 20 °C, RNA biomarker losses of 1-log₁₀ occurred on average after 6 and 4 days, and led to a complete signal loss after 13 and 6 days, respectively. Besides the effect of temperature, SARS-CoV-2 RNA signals were more persistent in the particulate phase compared to the aqueous one. Finally, PMMoV RNA signal was highly persistent in both phases and significantly differed from that of SARS-CoV-2 biomarkers. We further provide a detailed overview of the latest literature on SARS-CoV-2 and PMMoV decay rates in sewage matrices.

Changes in Escherichia coli to enteric protozoa ratios in rivers: Implications for risk-based assessment of drinking water treatment requirements

Minimum treatment requirements are set in response to established or anticipated levels of enteric pathogens in the source water of drinking water treatment plants (DWTPs). For surface water, contamination can be determined directly by monitoring reference pathogens or indirectly by measuring fecal indicators such as Escherichia coli (E. coli). In the latter case, a quantitative interpretation of E. coli for estimating reference pathogen concentrations could be used to define treatment requirements. This study presents the statistical analysis of paired E. coli and reference protozoa (Cryptosporidium, Giardia) data collected monthly for two years in source water from 27 DWTPs supplied by rivers in Canada. E. coli/Cryptosporidium and E. coli/Giardia ratios in source water were modeled as the ratio of two correlated lognormal variables. To evaluate the potential of E. coli for defining protozoa treatment requirements, risk-based critical mean protozoa concentrations in source water were determined with a reverse quantitative microbial risk assessment (QMRA) model. Model assumptions were selected to be consistent with the World Health Organization (WHO) Guidelines for drinking-water quality. The sensitivity of mean E. coli concentration trigger levels to identify these critical concentrations in source water was then evaluated. Results showed no proportionalities between the log of mean E. coli concentrations and the log of mean protozoa concentrations. E. coli/protozoa ratios at DWTPs supplied by small rivers in agricultural and forested areas were typically 1.0 to 2.0-log lower than at DWTPs supplied by large rivers in urban areas. The seasonal variations analysis revealed that these differences were related to low mean E. coli concentrations during winter in small rivers. To achieve the WHO target of 10^-6 disability-adjusted life year (DALY) per person per year, a minimum reduction of 4.0-log of Cryptosporidium would be required for 20 DWTPs, and a minimum reduction of 4.0-log of Giardia would be needed for all DWTPs. A mean E. coli trigger level of 50 CFU 100 mL^-1 would be a sensitive threshold to identify critical mean concentrations for Cryptosporidium but not for Giardia. Treatment requirements higher than 3.0-log would be needed at DWTPs with mean E. coli concentrations as low as 30 CFU 100 mL^-1 for Cryptosporidium and 3 CFU 100 mL^-1 for Giardia. Therefore, an E. coli trigger level would have limited value for defining health-based treatment requirements for protozoa at DWTPs supplied by small rivers in rural areas.

Comparison of approaches to quantify SARS-CoV-2 in wastewater using RT-qPCR: Results and implications from a collaborative inter-laboratory study in Canada

Detection of SARS-CoV-2 RNA in wastewater is a promising tool for informing public health decisions during the COVID-19 pandemic. However, approaches for its analysis by use of reverse transcription quantitative polymerase chain reaction (RT-qPCR) are still far from standardized globally. To characterize inter- and intra-laboratory variability among results when using various methods deployed across Canada, aliquots from a real wastewater sample were spiked with surrogates of SARS-CoV-2 (gamma-radiation inactivated SARS-CoV-2 and human coronavirus strain 229E [HCoV-229E]) at low and high levels then provided "blind" to eight laboratories. Concentration estimates reported by individual laboratories were consistently within a 1.0-log10 range for aliquots of the same spiked condition. All laboratories distinguished between low- and high-spikes for both surrogates. As expected, greater variability was observed in the results amongst laboratories than within individual laboratories, but SARS-CoV-2 RNA concentration estimates for each spiked condition remained mostly within 1.0-log10 ranges. The no-spike wastewater aliquots provided yielded non-detects or trace levels (<20 gene copies/mL) of SARS-CoV-2 RNA. Detections appear linked to methods that included or focused on the solids fraction of the wastewater matrix and might represent in-situ SARS-CoV-2 to the wastewater sample. HCoV-229E RNA was not detected in the no-spike aliquots. Overall, all methods yielded comparable results at the conditions tested. Partitioning behavior of SARS-CoV-2 and spiked surrogates in wastewater should be considered to evaluate method effectiveness. A consistent method and laboratory to explore wastewater SARS-CoV-2 temporal trends for a given system, with appropriate quality control protocols and documented in adequate detail should succeed.

Importance of Distributional Forms for the Assessment of Protozoan Pathogens Concentrations in Drinking-Water Sources

The identification of appropriately conservative statistical distributions is needed to predict microbial peak events in drinking water sources explicitly. In this study, Poisson and mixed Poisson distributions with different upper tail behaviors were used for modeling source water Cryptosporidium and Giardia data from 30 drinking water treatment plants. Small differences (<0.5-log) were found between the "best" estimates of the mean Cryptosporidium and Giardia concentrations with the Poisson-gamma and Poisson-log-normal models. However, the upper bound of the 95% credibility interval on the mean Cryptosporidium concentrations of the Poisson-log-normal model was considerably higher (>0.5-log) than that of the Poisson-gamma model at four sites. The improper choice of a model may, therefore, mislead the assessment of treatment requirements and health risks associated with the water supply. Discrimination between models using the marginal deviance information criterion (mDIC) was unachievable because differences in upper tail behaviors were not well characterized with available data sets ( n<30 ). Therefore, the gamma and the log-normal distributions fit the data equally well but may predict different risk estimates when they are used as an input distribution in an exposure assessment. The collection of event-based monitoring data and the modeling of larger routine monitoring data sets are recommended to identify appropriately conservative distributions to predict microbial peak events.

Impact of Hydrometeorological Events for the Selection of Parametric Models for Protozoan Pathogens in Drinking-Water Sources

Temporal variations in concentrations of pathogenic microorganisms in surface waters are well known to be influenced by hydrometeorological events. Reasonable methods for accounting for microbial peaks in the quantification of drinking water treatment requirements need to be addressed. Here, we applied a novel method for data collection and model validation to explicitly account for weather events (rainfall, snowmelt) when concentrations of pathogens are estimated in source water. Online in situ β-d-glucuronidase activity measurements were used to trigger sequential grab sampling of source water to quantify Cryptosporidium and Giardia concentrations during rainfall and snowmelt events at an urban and an agricultural drinking water treatment plant in Quebec, Canada. We then evaluate if mixed Poisson distributions fitted to monthly sampling data ( n = 30 samples) could accurately predict daily mean concentrations during these events. We found that using the gamma distribution underestimated high Cryptosporidium and Giardia concentrations measured with routine or event-based monitoring. However, the log-normal distribution accurately predicted these high concentrations. The selection of a log-normal distribution in preference to a gamma distribution increased the annual mean concentration by less than 0.1-log but increased the upper bound of the 95% credibility interval on the annual mean by about 0.5-log. Therefore, considering parametric uncertainty in an exposure assessment is essential to account for microbial peaks in risk assessment.

Using surrogate data to assess risks associated with microbial peak events in source water at drinking water treatment plants

A monitoring strategy was implemented at two drinking water treatment plants in Quebec, Canada, to evaluate microbial reduction performances of full-scale treatment processes under different source water conditions. β-D-glucuronidase activity in source water was automatically monitored in near-real-time to establish baseline and event conditions at each location. High-volume water samples (50-1,500 L) were collected at the inflow and the outflow of coagulation/flocculation, filtration, and UV disinfection processes and were analysed for two naturally occurring surrogate organisms: Escherichia coli and Clostridium perfringens. Source water Cryptosporidium data and full-scale C. perfringens reduction data were entered into a quantitative microbial risk assessment (QMRA) model to estimate daily infection risks associated with exposures to Cryptosporidium via consumption of treated drinking water. Daily mean E. coli and Cryptosporidium concentrations in source water under event conditions were in the top 5% (agricultural site) or in the top 15% (urban site) of what occurs through the year at these drinking water treatment plants. Reduction performances of up to 6.0-log for E. coli and 5.6-log for C. perfringens were measured by concentrating high-volume water samples throughout the treatment train. For both drinking water treatment plants, removal performances by coagulation/flocculation/sedimentation processes were at the high end of the range of those reported in the literature for bacteria and bacterial spores. Reductions of E. coli and C. perfringens by floc blanket clarification, ballasted clarification and rapid sand filtration did not deteriorate during two snowmelt/rainfall events. QMRA results suggested that daily infection risks were similar during two rainfall/snowmelt events than during baseline conditions. Additional studies investigating full-scale reductions would be desirable to improve the evaluation of differences in treatment performances under various source water conditions.

Demonstrating the reduction of enteric viruses by drinking water treatment during snowmelt episodes in urban areas

This study investigates short-term fluctuations in virus concentrations in source water and their removal by full-scale drinking water treatment processes under different source water conditions. Transient peaks in raw water faecal contamination were identified using in situ online β-d-glucuronidase activity monitoring at two urban drinking water treatment plants. During these peaks, sequential grab samples were collected at the source and throughout the treatment train to evaluate concentrations of rotavirus, adenovirus, norovirus, enterovirus, JC virus, reovirus, astrovirus and sapovirus by reverse transcription and real-time quantitative PCR. Virus infectivity was assessed through viral culture by measurement of cytopathic effect and integrated cell culture qPCR. Virus concentrations increased by approximately 0.5-log during two snowmelt/rainfall episodes and approximately 1.0-log following a planned wastewater discharge upstream of the drinking water intake and during a β-d-glucuronidase activity peak in dry weather conditions. Increases in the removal of adenovirus and rotavirus by coagulation/flocculation processes were observed during peak virus concentrations in source water, suggesting that these processes do not operate under steady-state conditions but dynamic conditions in response to source water conditions. Rotavirus and enterovirus detected in raw and treated water samples were predominantly negative in viral culture. At one site, infectious adenoviruses were detected in raw water and water treated by a combination of ballasted clarification, ozonation, GAC filtration, and UV disinfection operated at a dose of 40 mJ cm^-2. The proposed sampling strategy can inform the understanding of the dynamics associated with virus concentrations at drinking water treatment plants susceptible to de facto wastewater reuse.

Near real-time notification of water quality impairments in recreational freshwaters using rapid online detection of β-D-glucuronidase activity as a surrogate for Escherichia coli monitoring

Waterborne disease outbreaks associated with recreational waters continue to be reported around the world despite existing microbiological water quality monitoring frameworks. Most regulations resort to the use of culture-based enumeration of faecal indicator bacteria such as Escherichia coli to protect bathers from gastrointestinal illness risks. However, the long sample-to-result time of standard culture-based assays (minimum 18-24 h) and infrequent regulatory sampling (weekly or less) do not enable detection of episodic water quality impairments and associated public health risks. The objective of this study was to assess the suitability of an autonomous online technology measuring β-D-glucuronidase (GLUC) activity for near real-time monitoring of microbiological water quality in recreational waters and for the resulting beach management decisions. GLUC activity and E. coli concentrations were monitored at three freshwater sites in Quebec, Canada (sites Qc1-3) and one site in New Zealand (site NZ) between 2016 and 2018. We found site-dependent linear relationships between GLUC activity and E. coli concentrations and using confusion matrices, we developed site-specific GLUC activity beach action values (BAVs) matching the regulatory E. coli BAVs. Using the regulatory E. coli BAV as the gold standard, rates of false alarms (unnecessary beach advisories using GLUC activity BAV) and failures to act (failure to trigger advisories using GLUC activity) ranged between 0 and 32% and between 3 and 10%, respectively, which is comparable to the rates reported in other studies using qPCR-defined BAVs. However, a major benefit of the autonomous enzymatic technology is the real-time reporting of threshold exceedances, while temporal trends in GLUC activity can assist in understanding the underlying dynamics of faecal pollution and potential health risks. Our study is the first to describe the applicability of online near real-time monitoring of microbiological water quality as a tool for improved beach management and public health protection.

Can routine monitoring of E. coli fully account for peak event concentrations at drinking water intakes in agricultural and urban rivers?

In several jurisdictions, the arithmetic mean of Escherichia coli concentrations in raw water serves as the metric to set minimal treatment requirements by drinking water treatment plants (DWTPs). An accurate and precise estimation of this mean is therefore critical to define adequate requirements. Distributions of E. coli concentrations in surface water can be heavily skewed and require statistical methods capable of characterizing uncertainty. We present four simple parametric models with different upper tail behaviors (gamma, log-normal, Lomax, mixture of two log-normal distributions) to explicitly account for the influence of peak events on the mean concentration. The performance of these models was tested using large E. coli data sets (200-1800 samples) from raw water regulatory monitoring at six DWTPs located in urban and agricultural catchments. Critical seasons of contamination and hydrometeorological factors leading to peak events were identified. Event-based samples were collected at an urban DWTP intake during two hydrometeorological events using online β-d-glucuronidase activity monitoring as a trigger. Results from event-based sampling were used to verify whether selected parametric distributions predicted targeted peak events. We found that the upper tail of the log-normal and the Lomax distributions better predicted large concentrations than the upper tail of the gamma distribution. Weekly sampling for two years in urban catchments and for four years in agricultural catchments generated reasonable estimates of the average raw water E. coli concentrations. The proposed methodology can be easily used to inform the development of sampling strategies and statistical indices to set site-specific treatment requirements.

Tracking the contribution of multiple raw and treated wastewater discharges at an urban drinking water supply using near real-time monitoring of β-d-glucuronidase activity

Past waterborne outbreaks have demonstrated that informed vulnerability assessment of drinking water supplies is paramount for the provision of safe drinking water. Although current monitoring frameworks are not designed to account for short-term peak concentrations of fecal microorganisms in source waters, the recent development of online microbial monitoring technologies is expected to fill this knowledge gap. In this study, online near real-time monitoring of β-d-glucuronidase (GLUC) activity was conducted for 1.5 years at an urban drinking water intake impacted by multiple point sources of fecal pollution. Parallel routine and event-based monitoring of E. coli and online measurement of physico-chemistry were performed at the intake and their dynamics compared over time. GLUC activity fluctuations ranged from seasonal to hourly time scales. All peak contamination episodes occurred between late fall and early spring following intense rainfall and/or snowmelt. In the absence of rainfall, recurrent daily fluctuations in GLUC activity and culturable E. coli were observed at the intake, a pattern otherwise ignored by regulatory monitoring. Cross-correlation analysis of time series retrieved from the drinking water intake and an upstream Water Resource Recovery Facility (WRRF) demonstrated a hydraulic connection between the two sites. Sewage by-passes from the same WRRF were the main drivers of intermittent GLUC activity and E. coli peaks at the drinking water intake following intense precipitation and/or snowmelt. Near real-time monitoring of fecal pollution through GLUC activity enabled a thorough characterization of the frequency, duration and amplitude of peak contamination periods at the urban drinking water intake while providing crucial information for the identification of the dominant upstream fecal pollution sources. To the best of our knowledge, this is the first characterization of a hydraulic connection between a WRRF and a downstream drinking water intake across hourly to seasonal timescales using high frequency microbial monitoring data. Ultimately, this should help improve source water protection through catchment mitigation actions, especially in a context of de facto wastewater reuse.

Precipitation effects on parasite, indicator bacteria, and wastewater micropollutant loads from a water resource recovery facility influent and effluent

The variability of fecal microorganisms and wastewater micropollutants (WWMPs) loads in relation to influent flow rates was evaluated for a water resource recovery facility (WRRF) in support of a vulnerability assessment of a drinking water source. Incomplete treatment and bypass discharges often occur following intense precipitation events that represent conditions that deviate from normal operation. Parasites, fecal indicator bacteria, and WWMPs concentrations and flow rate were measured at the WRRF influent and effluent during dry and wet weather periods. Influent concentrations were measured to characterize potential bypass concentrations that occur during wet weather. Maximum influent Giardia and C. perfringens loads and maximum effluent Escherichia coli and C. perfringens loads were observed during wet weather. Influent median loads of Cryptosporidium and Giardia were 6.8 log oocysts/day and 7.9 log cysts/day per 1,000 people. Effluent median loads were 3.9 log oocysts/day and 6.3 log cysts/day per 1,000 people. High loads of microbial contaminants can occur during WRRF bypasses following wet weather and increase with increasing flow rates; thus, short-term infrequent events such as bypasses should be considered in vulnerability assessments of drinking water sources in addition to the increased effluent loads during normal operation following wet weather.

Autonomous online measurement of β-D-glucuronidase activity in surface water: is it suitable for rapid E. coli monitoring?

Microbiological water quality is traditionally assessed using culture-based enumeration of faecal indicator bacteria such as Escherichia coli. Despite their relative ease of use, these methods require a minimal 18-24 h-incubation step before the results are obtained. This study aimed to assess the suitability of an autonomous online fluorescence-based technology measuring β-glucuronidase (GLUC) activity for rapid near-real time monitoring of E. coli in water. The analytical precision was determined and compared to an automated microbial detection system, two culture-based assays and quantitative real-time PCR (qPCR). Using replicate measurements of grab samples containing E. coli concentrations between 50 and 2330 CFU.100 mL^-1, the autonomous GLUC activity measurement technology displayed an average coefficient of variation (CV) of less than 5% that was 4-8-fold lower than other methods tested. Comparable precision was observed during online in situ monitoring of GLUC activity at a drinking water intake using three independent instruments. GLUC activity measurements were not affected by sewage or sediments at concentrations likely to be encountered during long-term monitoring. Furthermore, significant (p < 0.05) correlations were obtained between GLUC activity and the other assays including defined substrate technology (r = 0.77), membrane filtration (r = 0.73), qPCR (r = 0.55) and the automated microbial detection system (r = 0.50). This study is the first to thoroughly compare the analytical performance of rapid automated detection technologies to established culture and molecular-based methods. Results show that further research is required to correlate GLUC activity to the presence of viable E. coli as measured in terms of CFU.100 mL^-1. This would allow the use of autonomous online GLUC activity measurements for rapid E. coli monitoring in water supplies used for drinking water production and recreation.

Temporal variability of parasites, bacterial indicators, and wastewater micropollutants in a water resource recovery facility under various weather conditions

Wastewater discharges lead to the deterioration of receiving waters through treated effluents and by-passes, combined and sanitary sewer overflows, and cross-connections to storm sewers. The influence of weather conditions on fecal indicator bacteria, pathogens and wastewater micropollutants on raw and treated sewage concentrations has not been extensively characterized. However, such data are needed to understand the effects of by-pass discharges and incomplete treatment on receiving waters. A water resource recovery facility was monitored for pathogenic parasites (Cryptosporidium oocysts, Giardia cysts), fecal indicator bacteria (Escherichia coli, Clostridium perfringens), and wastewater micropollutants (caffeine, carbamazepine, 2-hydroxycarbamazepine, acesulfame, sucralose, and aspartame) during 6 events under different weather conditions (snowmelt and trace to 32 mm 2-day cumulative precipitation). Greater intra- and inter-event variability was observed for Giardia, E. coli and C. perfringens than for studied WWMPs. Even with the addition of inflow and infiltration, daily variations dominated concentration trends. Thus, afternoon and early evening were identified as critical times with regards to high concentrations and flows for potential by-pass discharges. Peak concentrations of Giardia were observed during the June wet weather event (1010 cysts/L), with the highest flowrates relative to the mean monthly flowrate. Overall, Giardia, E. coli and C. perfringens concentrations were positively correlated with flowrate (R > 0.32, p < 0.05). In raw sewage samples collected under high precipitation conditions, caffeine, carbamazepine and its metabolite 2-OH-carbamazepine were significantly correlated (p < 0.05) with Giardia, E. coli, and C. perfringens demonstrating that they are useful markers for untreated sewage discharges. Data from the study are needed for estimating peak concentrations discharged from wastewater sources in relation to precipitation or snowmelt events.

How does the cladoceran Daphnia pulex affect the fate of Escherichia coli in water?

The faecal indicator Escherichia coli plays a central role in water quality assessment and monitoring. It is therefore essential to understand its fate under various environmental constraints such as predation by bacterivorous zooplankton. Whereas most studies have examined how protozooplankton communities (heterotrophic nanoflagellates and ciliates) affect the fate of E. coli in water, the capacity of metazooplankton to control the faecal indicator remains poorly understood. In this study, we investigated how the common filter-feeding cladoceran, Daphnia pulex, affects the fate of E. coli under different experimental conditions. Daphnia ingested E. coli and increased its loss rates in water, but the latter rates decreased from 1.65 d^-1 to 0.62 d^-1 after a 1,000-fold reduction in E. coli initial concentrations, due to lower probability of encounter between Daphnia and E. coli. The combined use of culture and PMA qPCR (viability-qPCR) demonstrated that exposure to Daphnia did not result into the formation of viable but non-culturable E. coli cells. In lake water, a significant part of E. coli population loss was associated with matrix-related factors, most likely due to predation by other bacterivorous biota and/or bacterial competition. However, when exposing E. coli to a D. pulex gradient (from 0 to 65 ind.L^-1), we observed an increasing impact of Daphnia on E. coli loss rates, which reached 0.47 d^-1 in presence of 65 ind.L^-1. Our results suggest that the filter-feeder can exert a non-negligible predation pressure on E. coli, especially during seasonal Daphnia population peaks. Similar trials using other Daphnia species as well as stressed E. coli cells will increase our knowledge on the capacity of this widespread zooplankter to control E. coli in freshwater resources. Based on our results, we strongly advocate the use of natural matrices to study these biotic interactions in order to avoid overestimation of Daphnia impact.

Spatial and temporal distribution of Cryptosporidium and Giardia in a drinking water resource: implications for monitoring and risk assessment

Because of their significant public health impact, waterborne Cryptosporidium and Giardia have been monitored in surface water in order to assess microbial quality of water bodies used for drinking water production and/or for recreational purposes. In this context, sampling strategy is of key importance and should be representative enough to appropriately assess the related microbial risk. This, however, requires sound knowledge on the behaviour of both pathogens in water. In the present study, the spatial and temporal distribution of Cryptosporidium and Giardia was explored in the rural Upper-Sûre watershed used for drinking water production in Luxembourg. By subdividing it into three compartments including (i) sub-catchments, (ii) the Sûre River fed by the sub-catchments and (iii) the Upper-Sûre reservoir fed by the Sûre River, parasite distribution was assessed using sampling designs adapted to the hydro-dynamic characteristics of the respective compartments. Results highlighted the high spatial and temporal variability in parasite distribution at watershed scale, as well as the prevalence of Giardia over Cryptosporidium. Besides land use features and catchment characteristics, hydro-climatology appeared to be a major driver of parasite behaviour in the watershed. It introduced a seasonal trend in their occurrence, highest densities being detected during the wet season. Peaks of contamination triggered out by rainfall-induced runoff were further observed in the three compartments. In the Sûre River, Cryptosporidium and Giardia fluxes peaked at 10(9) and 10(10) (oo)cysts.d(-1), respectively, and were discharged into the drinking water reservoir, where they underwent a 2 to 3 log10 removal rate. Despite this, parasite fluxes entering the drinking water treatment plant were still high (10(6) to 10(7) (oo)cysts.d(-1)) and stressed on the need for improved watershed management upstream the water treatment barrier. The catchment-wide analysis described here constitutes a valuable tool for assessment of catchment microbial dynamics, especially within the framework of Water Safety Plans.

Two-year monitoring of Cryptosporidium parvum and Giardia lamblia occurrence in a recreational and drinking water reservoir using standard microscopic and molecular biology techniques

Starting in 2006, a monitoring of Giardia lamblia and Cryptosporidium parvum occurrence was conducted for 2 years in the largest drinking water reservoir of Luxembourg (Esch-sur-Sûre reservoir) using microscopy and qPCR techniques. Parasite analyses were performed on water samples collected from three sites: site A located at the inlet of the reservoir, site B located 18 km downstream site A, at the inlet of the drinking water treatment plant near the dam of the reservoir and site C where the finished drinking water is injected in the distribution network. Results show that both parasites are present in the reservoir throughout the year with a higher occurrence of G. lamblia cysts compared to C. parvum oocysts. According to our results, only 25% of the samples positive by microscopy were confirmed by qPCR. (Oo)cyst concentrations were 10 to 100 times higher at site A compared to site B and they were positively correlated to the water turbidity and negatively correlated to the temperature. Highest (oo)cyst concentrations were observed in winter. In contrast, no relationship between the concentrations of (oo)cysts in the reservoir and rain events could be established. Though a correlation has been observed between both parasites and faecal indicators in the reservoir, some discrepancies highlight that the latter do not represent a reliable tool to predict the presence/absence of these pathogenic protozoa. In summer 2007, the maximal risk of parasite infection per exposure event for swimmers in the reservoir was estimated to be 0.0015% for C. parvum and 0.56% for G. lamblia. Finally, no (oo)cysts could be detected in large volumes of finished drinking water.