QMRAcatch: Microbial Quality Simulation of Water Resources including Infection Risk Assessment

Forecasting fish mortality from water and air quality data using deep learning models

The high rate of aquatic mortality incidents recorded in Taiwan and worldwide is creating an urgent demand for more accurate fish mortality prediction. Present study innovatively integrated air and water quality data to measure water quality degradation, and utilized deep learning methods to predict accidental fish mortality from the data. Keras library was used to build multilayer perceptron and long short-term memory models for training purposes, and the models' accuracies in fish mortality prediction were compared with that of the naïve Bayesian classifier. Environmental data from the 5 days before a fish mortality event proved to be the most important data for effective model training. Multilayer perceptron model reached an accuracy of 93.4%, with a loss function of 0.01, when meteorological and water quality data were jointly considered. It was found that meteorological conditions were not the sole contributors to fish mortality. Predicted fish mortality rate of 4.7% closely corresponded to the true number of fish mortality events during the study period, that is, four. A significant surge in fish mortality, from 20% to 50%, was noted when the river pollution index increased from 5.36 to 6.5. Moreover, the probability of fish mortality increased when the concentration of dissolved oxygen dropped below 2 mg/L. To mitigate fish mortality, ammonia nitrogen concentrations should be capped at 5 mg/L. Dissolved oxygen concentration was found to be the paramount factor influencing fish mortality, followed by the river pollution index and meteorological data. Results of the present study are expected to aid progress toward achieving the Sustainable Development Goals and to increase the profitability of water resources.

Current status of microbial source tracking applications in constructed wetlands serving as nature-based solutions for water management and wastewater treatment

Microbial source tracking (MST) has been recognised as an effective tool for determining the origins and sources of faecal contamination in various terrestrial and aquatic ecosystems. Thus, it has been widely applied in environmental DNA (eDNA) surveys to define specific animal- and human-associated faecal eDNA. In this context, identification of and differentiation between anthropogenic and zoogenic faecal pollution origins and sources are pivotal for the evaluation of waterborne microbial contamination transport and the associated human, animal, and environmental health risks. These concerns are particularly pertinent to diverse nature-based solutions (NBS) that are being applied specifically to secure water safety and human and ecosystem well-being, for example, constructed wetlands (CWs) for water and wastewater treatment. The research in this area has undergone a constant evolution, and there is a solid foundation of publications available across the world. Hence, there is an early opportunity to synthesise valuable information and relevant knowledge on this specific topic, which will greatly benefit future work by improving NBS design and performance. By selecting 15 representative research reports published over 20 years, we review the current state of MST technology applied for faecal-associated contamination measures in NBS/CWs throughout the world.

Forecasting acute rainfall driven E. coli impacts in inland rivers based on sewer monitoring and field runoff

Surface water quality is frequently impacted by acute rainfall driven pollutant sources such as sewer overflows. Understanding the risk of exposure from faecal pollution from short term impacts is challenging due to a paucity of high-resolution data from river systems. This paper proposes practical modelling approach for forecasting arrival time and durations of elevated E. coli levels based on hydrological routing of catchment source loadings, characterized by distributed and remote sensing techniques (including sewer overflow monitoring). The model is calibrated and validated using new high resolution E. coli datasets from a UK catchment featuring both diffuse field runoff and storm overflow impacts. Hourly/Bihourly sampling of E. coli was undertaken in the river following different rainfall events across a range of seasonal conditions. The model provides a good estimate of arrival times and durations of elevated E. coli periods following rainfall events. Model simulations suggest that key sources in the catchment are event specific, with sewer overflow spills being more significant following short, intense rainfall events.

A probabilistic-deterministic approach for assessing climate change effects on infection risks downstream of sewage emissions from CSOs

The discharge of pathogens into urban recreational water bodies during combined sewer overflows (CSOs) pose a potential threat for public health which may increase in the future due to climate change. Improved methods are needed for predicting the impact of these effects on the microbiological urban river water quality and infection risks during recreational use. The aim of this study was to develop a novel probabilistic-deterministic modelling approach for this purpose building on physically plausible generated future rainfall time series. The approach consists of disaggregation and validation of daily precipitation time series from 21 regional climate models for a reference period (1971-2000, C20), a near-term future period (2021-2050, NTF) and a long-term future period (2071-2100, LTF) into sub-daily scale, and predicting the concentrations of enterococci and Giardia and Cryptosporidium, and infection risks during recreational use in the river downstream of the sewage emissions from CSOs. The approach was tested for an urban river catchment in Austria which is used for recreational activities (i.e. swimming, playing, wading, hand-to-mouth contact). According to a worst-case scenario (i.e. children bathing in the river), the 95th percentile infection risks for Giardia and Cryptosporidium range from 0.08 % in winter to 8 % per person and exposure event in summer for C20. The infection risk increase in the future is up to 0.8 log10 for individual scenarios. The results imply that measures to prevent CSOs may be needed to ensure sustainable water safety. The approach is promising for predicting the effect of climate change on urban water safety requirements and for supporting the selection of sustainable mitigation measures. Future studies should focus on reducing the uncertainty of the predictions at local scale.

Water, Water Everywhere, but Every Drop Unique: Challenges in the Science to Understand the Role of Contaminants of Emerging Concern in the Management of Drinking Water Supplies

The protection and management of water resources continues to be challenged by multiple and ongoing factors such as shifts in demographic, social, economic, and public health requirements. Physical limitations placed on access to potable supplies include natural and human-caused factors such as aquifer depletion, aging infrastructure, saltwater intrusion, floods, and drought. These factors, although varying in magnitude, spatial extent, and timing, can exacerbate the potential for contaminants of concern (CECs) to be present in sources of drinking water, infrastructure, premise plumbing and associated tap water. This monograph examines how current and emerging scientific efforts and technologies increase our understanding of the range of CECs and drinking water issues facing current and future populations. It is not intended to be read in one sitting, but is instead a starting point for scientists wanting to learn more about the issues surrounding CECs. This text discusses the topical evolution CECs over time (Section 1), improvements in measuring chemical and microbial CECs, through both analysis of concentration and toxicity (Section 2) and modeling CEC exposure and fate (Section 3), forms of treatment effective at removing chemical and microbial CECs (Section 4), and potential for human health impacts from exposure to CECs (Section 5). The paper concludes with how changes to water quantity, both scarcity and surpluses, could affect water quality (Section 6). Taken together, these sections document the past 25 years of CEC research and the regulatory response to these contaminants, the current work to identify and monitor CECs and mitigate exposure, and the challenges facing the future.

Microbial source tracking using molecular and cultivable methods in a tropical mixed-use drinking water source to support water safety plans

Microbial contamination deteriorates source water quality, posing a severe problem for drinking water suppliers worldwide and addressed by the Water Safety Plan framework to ensure high-quality and reliable drinking water. Microbial source tracking (MST) is used to examine different microbial pollution sources via host-specific intestinal markers for humans and different types of animals. However, the application of MST in tropical surface water catchments that provide raw water for drinking water supplies is limited. We analyzed a set of MST markers, namely, three cultivable bacteriophages and four molecular PCR and qPCR assays, together with 17 microbial and physicochemical parameters, to identify fecal pollution from general, human-, swine-, and cattle-specific sources. Seventy-two river water samples at six sampling sites were collected over 12 sampling events during wet and dry seasons. We found persistent fecal contamination via the general fecal marker GenBac3 (100 % detection; 2.10-5.42 log₁₀ copies/100 mL), with humans (crAssphage; 74 % detection; 1.62-3.81 log₁₀ copies/100 mL) and swine (Pig-2-Bac; 25 % detection; 1.92-2.91 log₁₀ copies/100 mL). Higher contamination levels were observed during the wet season (p < 0.05). The conventional PCR screening used for the general and human markers showed 94.4 % and 69.8 % agreement with the respective qPCR results. Specifically, in the studied watershed, coliphage could be a screening parameter for the crAssphage marker (90.6 % and 73.7 % positive and negative predictive values; Spearman's rank correlation coefficient = 0.66; p < 0.001). The likelihood of detecting the crAssphage marker significantly increased when total and fecal coliforms exceeded 20,000 and 4000 MPN/100 mL, respectively, as Thailand Surface Water Quality Standards, with odds ratios and 95 % confidence intervals of 15.75 (4.43-55.98) and 5.65 (1.39-23.05). Our study confirms the potential benefits of incorporating MST monitoring into water safety plans, supporting the use of this approach to ensure high-quality drinking water supplies worldwide.

Geo-referenced simulations of E. coli in a sub-catchment of the Vecht River using a probabilistic approach

The proportion of wild swimmers at non-official bathing sites has increased during the Covid-19 pandemic. Bathing water quality at designated sites is monitored through analysis of the concentration of fecal indicator bacteria such as E. coli. However, non-official sites are generally not monitored. In a previous work, steady state modelling of E. coli was achieved at catchment scale, enabling a comparison of expected concentrations along an entire catchment for longtime average. However, E. coli concentrations can vary over several orders of magnitude at the same monitoring site throughout the year. To capture the temporal variability of E. coli concentrations on the catchment scale, we extended the existing deterministic E. coli sub-module of the GREAT-ER (Geo-referenced Exposure Assessment tool for European Rivers) model for probabilistic Monte-Carlo simulations. Here, selected model parameters are represented by probability distributions instead of fixed values. Wastewater treatment plant (WWTP) emissions and diffuse emissions were parameterized using selected data from a previous monitoring campaign (calibration data set) and in-stream processes were modeled using literature data. Comparison of simulation results with monitoring data (evaluation data set) indicates that predicted E. coli concentrations well-represent median measured concentrations, although the range of predicted concentrations is slightly larger than the observed concentration variability. The parameters with the largest influence on the range of predicted concentrations are flow rate and E. coli removal efficiency in WWTPs. A comparison of predicted 90th percentiles with the threshold for sufficient bathing water quality (according to the EU Bathing Water Directive) indicates that year-round swimming at sites influenced by WWTP effluents is advisable almost nowhere in the study area. A refinement of the model can be achieved if quantitative relationships between the WWTP removal efficiency and both, the treatment technologies as well as the operating parameters are further established.

Waterborne virus transport and the associated risks in a large lake

Waterborne enteric viruses in lakes, especially at recreational water sites, may have a negative impact on human health. However, their fate and transport in lakes are poorly understood. In this study, we propose a coupled water quality and quantitative microbial risk assessment (QMRA) model to study the transport, fate and infection risk of four common waterborne viruses (adenovirus, enterovirus, norovirus and rotavirus), using Lake Geneva as a study site. The measured virus load in raw sewage entering the lake was used as the source term in the water quality simulations for a hypothetical scenario of discharging raw wastewater at the lake surface. After discharge into the lake, virus inactivation was modeled as a function of water temperature and solar irradiance that varied both spatially and temporally during transport throughout the lake. Finally, the probability of infection, while swimming at a popular beach, was quantified and compared among the four viruses. Norovirus was found to be the most abundant virus that causes an infection probability that is at least 10 times greater than the other viruses studied. Furthermore, environmental inactivation was found to be an essential determinant in the infection risks posed by viruses to recreational water users. We determined that infection risks by enterovirus and rotavirus could be up to 1000 times lower when virus inactivation by environmental stressors was accounted for compared with the scenarios considering hydrodynamic transport only. Finally, the model highlighted the role of the wind field in conveying the contamination plume and hence in determining infection probability. Our simulations revealed that for beaches located west of the sewage discharge, the infection probability under eastward wind was 43% lower than that under westward wind conditions. This study highlights the potential of combining water quality simulation and virus-specific risk assessment for a safe water resources usage and management.

(Antibiotic-Resistant) E. coli in the Dutch-German Vecht Catchment─Monitoring and Modeling

Fecally contaminated waters can be a source for human infections. We investigated the occurrence of fecal indicator bacteria (E. coli) and antibiotic-resistant E. coli, namely, extended spectrum beta-lactamase (ESBL)-producing E. coli (ESBL-EC) and carbapenemase-producing E. coli (CP-EC) in the Dutch-German transboundary catchment of the Vecht River. Over the course of one year, bacterial concentrations were monitored in wastewater treatment plant (WWTP) influents and effluents and in surface waters with and without WWTP influence. Subsequently, the GREAT-ER model was adopted for the prediction of (antibiotic-resistant) E. coli concentrations. The model was parametrized and evaluated for two distinct scenarios (average flow scenario, dry summer scenario). Statistical analysis of WWTP monitoring data revealed a significantly higher (factor 2) proportion of ESBL-EC among E. coli in German compared to Dutch WWTPs. CP-EC were present in 43% of influent samples. The modeling approach yielded spatially accurate descriptions of microbial concentrations for the average flow scenario. Predicted E. coli concentrations exceed the threshold value of the Bathing Water Directive for a good bathing water quality at less than 10% of potential swimming sites in both scenarios. During a single swimming event up to 61 CFU of ESBL-EC and less than 1 CFU of CP-EC could be taken up by ingestion.

Review of generic screening level assumptions for quantitative microbial risk assessment (QMRA) for estimating public health risks from Australian drinking water sources contaminated with Cryptosporidium by recreational activities

As urban communities continue to grow, demand for recreational access (including swimming) in drinking water sources have increased, yet relatively little is understood about the public health implications this poses for drinking water consumers. Preventative risk-based approaches to catchment management, informed by quantitative microbial risk assessment (QMRA), requires accurate input data to effectively model risks. A sound understanding of the knowledge gaps is also important to comprehend levels of uncertainty and help prioritise research needs. Cryptosporidium is one of the most important causes of waterborne outbreaks of gastroenteritis globally due to its resistance to chlorine. This review was undertaken by Water Research Australia to provide the most up-to-date information on current Cryptosporidium epidemiological data and underlying assumptions for exposure assessment, dose response and risk assessment for generic components of QMRA for Cryptosporidium and highlights priorities for common research. Key interim recommendations and guidelines for numerical values for relatively simple screening level QMRA modelling are provided to help support prospective studies of risks to drinking water consumers from Cryptosporidium due to body-contact recreation in source water. The review does not cover site-specific considerations, such as the levels of activity in the source water, the influence of dilution and inactivation in reservoirs, or water treatment. Although the focus is Australia, the recommendations and numerical values developed in this review, and the highlighted research priorities, are broadly applicable across all drinking source water sources that allow recreational activities.

Impact of sewer overflow on public health: A comprehensive scientometric analysis and systematic review

Sewer overflow (SO), which has attracted global attention, poses serious threat to public health and ecosystem. SO impacts public health via consumption of contaminated drinking water, aerosolization of pathogens, food-chain transmission, and direct contact with fecally-polluted rivers and beach sediments during recreation. However, no study has attempted to map the linkage between SO and public health including Covid-19 using scientometric analysis and systematic review of literature. Results showed that only few countries were actively involved in SO research in relation to public health. Furthermore, there are renewed calls to scale up environmental surveillance to safeguard public health. To safeguard public health, it is important for public health authorities to optimize water and wastewater treatment plants and improve building ventilation and plumbing systems to minimize pathogen transmission within buildings and transportation systems. In addition, health authorities should formulate appropriate policies that can enhance environmental surveillance and facilitate real-time monitoring of sewer overflow. Increased public awareness on strict personal hygiene and point-of-use-water-treatment such as boiling drinking water will go a long way to safeguard public health. Ecotoxicological studies and health risk assessment of exposure to pathogens via different transmission routes is also required to appropriately inform the use of lockdowns, minimize their socio-economic impact and guide evidence-based welfare/social policy interventions. Soft infrastructures, optimized sewer maintenance and prescreening of sewer overflow are recommended to reduce stormwater burden on wastewater treatment plant, curtail pathogen transmission and marine plastic pollution. Comprehensive, integrated surveillance and global collaborative efforts are important to curtail on-going Covid-19 pandemic and improve resilience against future pandemics.

Genetic Microbial Source Tracking Support QMRA Modeling for a Riverine Wetland Drinking Water Resource

Riverine wetlands are important natural habitats and contain valuable drinking water resources. The transport of human- and animal-associated fecal pathogens into the surface water bodies poses potential risks to water safety. The aim of this study was to develop a new integrative modeling approach supported by microbial source tracking (MST) markers for quantifying the transport pathways of two important reference pathogens, Cryptosporidium and Giardia, from external (allochthonous) and internal (autochthonous) fecal sources in riverine wetlands considering safe drinking water production. The probabilistic-deterministic model QMRAcatch (v 1.1 python backwater) was modified and extended to account for short-time variations in flow and microbial transport at hourly time steps. As input to the model, we determined the discharge rates, volumes and inundated areas of the backwater channel based on 2-D hydrodynamic flow simulations. To test if we considered all relevant fecal pollution sources and transport pathways, we validated QMRAcatch using measured concentrations of human, ruminant, pig and bird associated MST markers as well as E. coli in a Danube wetland area from 2010 to 2015. For the model validation, we obtained MST marker decay rates in water from the literature, adjusted them within confidence limits, and simulated the MST marker concentrations in the backwater channel, resulting in mean absolute errors of < 0.7 log₁₀ particles/L (Kruskal–Wallis p > 0.05). In the scenarios, we investigated (i) the impact of river discharges into the backwater channel (allochthonous sources), (ii) the resuspension of pathogens from animal fecal deposits in inundated areas, and (iii) the pathogen release from animal fecal deposits after rainfall (autochthonous sources). Autochthonous and allochthonous human and animal sources resulted in mean loads and concentrations of Cryptosporidium and Giardia (oo)cysts in the backwater channel of 3–13 × 10⁹ particles/hour and 0.4–1.2 particles/L during floods and rainfall events, and in required pathogen treatment reductions to achieve safe drinking water of 5.0–6.2 log₁₀. The integrative modeling approach supports the sustainable and proactive drinking water safety management of alluvial backwater areas.

Modelling the interplay of future changes and wastewater management measures on the microbiological river water quality considering safe drinking water production

Rivers are important for drinking water supply worldwide. However, they are often impacted by pathogen discharges via wastewater treatment plants (WWTP) and combined sewer overflows (CSO). To date, accurate predictions of the effects of future changes and pollution control measures on the microbiological water quality of rivers considering safe drinking water production are hindered due to the uncertainty of the pathogen source and transport variables. The aim of this study was to test an integrative approach for an improved understanding of these effects, i.e. climate change and population growth as well as enhanced treatment at WWTPs and/or prevention of CSOs. We applied a significantly extended version of QMRAcatch (v1.0 Python), a probabilistic-deterministic model that combines fate and transport modelling with quantitative microbial infection risk assessment. The impact of climatic changes until the period 2035-2049 was investigated by a conceptual semi-distributed hydrological model, based on regional climate model outputs. QMRAcatch was calibrated and validated using site- and source-specific data (human-associated genetic microbial source tracking marker and enterovirus). The study showed that the degree to which future changes affect drinking water safety strongly depends on the type and magnitude of faecal pollution sources and are thus highly site- and scenario-specific. For example, if the load of pathogens from WWTPs is reduced through enhanced treatment, climate-change driven increases in CSOs had a considerable impact. Preventing CSOs and installing enhanced treatment at the WWTPs together had the most significant positive effect. The simultaneous consideration of source apportionment and concentrations of reference pathogens, focusing on human-specific viruses (enterovirus, norovirus) and cross-comparison with bacterial and protozoan pathogens (Campylobacter, Cryptosporidium), was found crucial to quantify these effects. While demonstrated here for a large, wastewater-impacted river, the approach is applicable at other catchments and pollution sources. It allows assessing future changes and selecting suitable pollution control measures for long-term water safety planning.

An agent-based model that simulates the spatio-temporal dynamics of sources and transfer mechanisms contributing faecal indicator organisms to streams. Part 1: Background and model description

A new Model for the Agent-based simulation of Faecal Indicator Organisms (MAFIO) is developed that attempts to overcome limitations in existing faecal indicator organism (FIO) models arising from coarse spatial discretisations and poorly-constrained hydrological processes. MAFIO is a spatially-distributed, process-based model presently designed to simulate the fate and transport of agents representing FIOs shed by livestock at the sub-field scale in small (<10 km²) agricultural catchments. Specifically, FIO loading, die-off, detachment, surface routing, seepage and channel routing are modelled on a regular spatial grid. Central to MAFIO is that hydrological transfer mechanisms are simulated based on a hydrological environment generated by an external model for which it is possible to robustly determine the accuracy of simulated catchment hydrological functioning. The spatially-distributed, tracer-aided ecohydrological model EcH₂O-iso is highlighted as a possible hydrological environment generator. The present paper provides a rationale for and description of MAFIO, whilst a companion paper applies the model in a small agricultural catchment in Scotland to provide a proof-of-concept.

Implementation of quantitative microbial risk assessment (QMRA) for public drinking water supplies: Systematic review

In the more than 15 years since its introduction, quantitative microbial risk assessment (QMRA) has become a widely used technique for assessing population health risk posed by waterborne pathogens. However, the variation in approaches taken for QMRA in relation to drinking water supply is not well understood. This systematic review identifies, categorises, and critically synthesises peer-reviewed and academic case studies of QMRA implementation for existing distributed public drinking water supplies. Thirty-nine English-language, peer-reviewed and academic studies published from 2003 to 2019 were identified. Key findings were synthesised in narrative form. The overall designs of the included studies varied widely, as did the assumptions used in risk calculation, especially in relation to pathogen dose. There was also substantial variation in the degree to which the use of location-specific data weighed with the use of assumptions when performing risk calculation. In general, the included studies' complexity did not appear to be associated with greater result certainty. Factors relating to pathogen dose were commonly influential on risk estimates whereas dose-response parameters tended to be of low relative influence. In two of the included studies, use of the 'susceptible fraction' factor was inconsistent with recognised guidance and potentially led to the underestimation of risk. While approaches and assumptions used in QMRA need not be standardised, improvement in the reporting of QMRA results and uncertainties would be beneficial. It is recommended that future authors consider the water supply QMRA reporting checklist developed for the current review. Consideration of the broad types of uncertainty relevant to QMRA is also recommended. Policy-makers should consider emergent discussion on acute microbial health-based targets when setting normative guidelines. The continued representation of QMRA case studies within peer-reviewed and academic literature would also enhance future implementation. Further research is needed on the optimisation of QMRA resourcing given the application context.

Assessing microbial risk through event-based pathogen loading and hydrodynamic modelling

The aim of this study was to assess the variability of microbial risk associated with drinking water under various contaminant loading conditions in a drinking water source. For this purpose, a probabilistic-deterministic approach was applied to estimate the loadings of Cryptosporidium, Giardia, and Escherichia coli (E. coli) from fecal contamination sources during both dry and wet weather conditions. The relative importance of loads originating from various fecal contamination sources was also determined by a probabilistic approach. This study demonstrates that water resource recovery facilities were the dominant source of Giardia, yet rivers were more important with regards to Cryptosporidium. Estimated loadings were used as input to a three-dimensional hydrodynamic model of Lake Ontario; the fate and transport of microbial organisms were simulated at the influent of a drinking water intake. Discharge-based hydrodynamic modelling results were compared to observed concentrations. Simulated probability distributions of concentrations at the intake were used as an input to a quantitative microbial risk assessment (QMRA) model such that the variability of microbial risk in the context of drinking water could be examined. Depending on wind and currents, higher levels of fecal contamination reached the intake during wet weather loading scenarios. Probability distribution functions of Cryptosporidium, Giardia and E. coli concentrations at the intake were significantly higher during wet weather conditions when compared to dry conditions (p < 0.05). For all contaminants studied, the QMRA model showed a higher risk during wet weather (over 1 order of magnitude) compared to dry weather conditions. When considering sewage by-pass scenarios, risks remained below 2.7 × 10^-7 person^-1 day^-1 for Giardia and E. coli O157:H7. Limited data were available for Cryptosporidium in by-pass effluents and the risk is unknown; hence it is critical to obtain reliable loading data for the riskiest scenarios, such as those associated with water resource recovery facility by-passes.

Synergy between quantitative microbial source tracking (qMST) and quantitative microbial risk assessment (QMRA): A review and prospectus

The use of microbial source tracking (MST) marker genes has grown in recent years due to the need to attribute point and non-point fecal contamination to specific sources. Quantitative microbial risk assessment (QMRA) is a modeling approach used to estimate health risks from exposure to feces-contaminated water and associated pathogens. A combination of these approaches [quantitative MST (qMST) and QMRA] can provide additional pathogen-related information for prioritizing and addressing health risks, compared to reliance on conventional fecal indicator bacteria (FIB). To inform expansion of this approach, a review of published qMST-QMRA studies was conducted to summarize the state of the science and to identify research needs. The reviewed studies primarily aimed to identify what levels of MST marker genes in hypothetical recreational waterbodies would exceed the United States Environmental Protection Agency (USEPA) risk benchmarks for primary contact recreators. The QMRA models calculated relationships between MST marker gene(s) and reference pathogens based on published data in the literature. The development of a robust, accurate relationship was identified as an urgent research gap for qMST-QMRA. This metric requires additional knowledge to quantify the relationship between MST marker genes and the degree of variability in decay of pathogens as a dynamic function of environmental conditions and combinations of fecal sources at multiple spatial and temporal scales. Improved characterization of host shedding rates of host-associated microorganisms (i.e., MST marker genes), as well as fate and transport of these microorganisms and their nucleic acids, would facilitate expansion of this approach to other exposure pathways. Incorporation of information regarding the recovery efficiency, and host-specificity of MST marker genes into QMRA model parameters, and the sensitivity analysis, would greatly improve risk management and site-specific water monitoring criteria.

Quantitative microbial risk assessment and its applications in small water systems: A review

Quantitative microbial risk assessment (QMRA) has been mainstreamed in many large municipal water systems as part of a paradigm shift in the drinking water industry towards water safety planning and risk-based system assessment. Small water systems (SWSs) are generally more vulnerable to typical water system hazards, and consequently have a higher risk of waterborne disease outbreak. In this paper, a review of experiences in implementing QMRA in SWSs helps elaborate the sources of risks and highlights some of the challenges facing SWSs in developed countries. A critical review of the important elements for practical implementation of QMRA was conducted. The investigation focuses on aspects related to challenges in identifying relevant hazards to SWSs to create failure scenarios, acquiring monitoring data for pathogens' concentrations in source water, estimating treatment efficiencies of typical small system technologies, and access to software tools to support successful implementation. The review helped outline ways through which SWSs can overcome the identified challenges in implementing QMRA. An adjusted framework for implementing QMRA for small water systems was formulated and discussed.

Methods for Handling Left-Censored Data in Quantitative Microbial Risk Assessment

Data below detection limits, left-censored data, are common in environmental microbiology, and decisions in handling censored data may have implications for quantitative microbial risk assessment (QMRA). In this paper, we utilize simulated data sets informed by real-world enterovirus water data to evaluate methods for handling left-censored data. Data sets were simulated with four censoring degrees (low [10%], medium [35%], high [65%], and severe [90%]) and one real-life censoring example (97%) and were informed by enterovirus data assuming a lognormal distribution with a limit of detection (LOD) of 2.3 genome copies/liter. For each data set, five methods for handling left-censored data were applied: (i) substitution with LOD/[Formula: see text], (ii) lognormal maximum likelihood estimation (MLE) to estimate mean and standard deviation, (iii) Kaplan-Meier estimation (KM), (iv) imputation method using MLE to estimate distribution parameters (MI method 1), and (v) imputation from a uniform distribution (MI method 2). Each data set mean was used to estimate enterovirus dose and infection risk. Root mean square error (RMSE) and bias were used to compare estimated and known doses and infection risks. MI method 1 resulted in the lowest dose and infection risk RMSE and bias ranges for most censoring degrees, predicting infection risks at most 1.17 × 10^-2 from known values under 97% censoring. MI method 2 was the next overall best method. For medium to severe censoring, MI method 1 may result in the least error. If unsure of the distribution, MI method 2 may be a preferred method to avoid distribution misspecification.IMPORTANCE This study evaluates methods for handling data with low (10%) to severe (90%) left-censoring within an environmental microbiology context and demonstrates that some of these methods may be appropriate when using data containing concentrations below a limit of detection to estimate infection risks. Additionally, this study uses a skewed data set, which is an issue typically faced by environmental microbiologists.

Global Distribution of Human-Associated Fecal Genetic Markers in Reference Samples from Six Continents

Numerous bacterial genetic markers are available for the molecular detection of human sources of fecal pollution in environmental waters. However, widespread application is hindered by a lack of knowledge regarding geographical stability, limiting implementation to a small number of well-characterized regions. This study investigates the geographic distribution of five human-associated genetic markers (HF183/BFDrev, HF183/BacR287, BacHum-UCD, BacH, and Lachno2) in municipal wastewaters (raw and treated) from 29 urban and rural wastewater treatment plants (750-4 400 000 population equivalents) from 13 countries spanning six continents. In addition, genetic markers were tested against 280 human and nonhuman fecal samples from domesticated, agricultural and wild animal sources. Findings revealed that all genetic markers are present in consistently high concentrations in raw (median log₁₀ 7.2-8.0 marker equivalents (ME) 100 mL^-1) and biologically treated wastewater samples (median log₁₀ 4.6-6.0 ME 100 mL^-1) regardless of location and population. The false positive rates of the various markers in nonhuman fecal samples ranged from 5% to 47%. Results suggest that several genetic markers have considerable potential for measuring human-associated contamination in polluted environmental waters. This will be helpful in water quality monitoring, pollution modeling and health risk assessment (as demonstrated by QMRAcatch) to guide target-oriented water safety management across the globe.

Opening the black box of spring water microbiology from alpine karst aquifers to support proactive drinking water resource management

Over the past 15 years, pioneering interdisciplinary research has been performed on the microbiology of hydrogeologically well-defined alpine karst springs located in the Northern Calcareous Alps (NCA) of Austria. This article gives an overview on these activities and links them to other relevant research. Results from the NCA springs and comparable sites revealed that spring water harbors abundant natural microbial communities even in aquifers with high water residence times and the absence of immediate surface influence. Apparently, hydrogeology has a strong impact on the concentration and size of the observed microbes, and total cell counts (TCC) were suggested as a useful means for spring type classification. Measurement of microbial activities at the NCA springs revealed extremely low microbial growth rates in the base flow component of the studied spring waters and indicated the importance of biofilm-associated microbial activities in sediments and on rock surfaces. Based on genetic analysis, the autochthonous microbial endokarst community (AMEC) versus transient microbial endokarst community (TMEC) concept was proposed for the NCA springs, and further details within this overview article are given to prompt its future evaluation. In this regard, it is well known that during high-discharge situations, surface-associated microbes and nutrients such as from soil habitats or human settlements-potentially containing fecal-associated pathogens as the most critical water-quality hazard-may be rapidly flushed into vulnerable karst aquifers. In this context, a framework for the comprehensive analysis of microbial pollution has been proposed for the NCA springs to support the sustainable management of drinking water safety in accordance with recent World Health Organization guidelines. Near-real-time online water quality monitoring, microbial source tracking (MST) and MST-guided quantitative microbial-risk assessment (QMRA) are examples of the proposed analytical tools. In this context, this overview article also provides a short introduction to recently emerging methodologies in microbiological diagnostics to support reading for the practitioner. Finally, the article highlights future research and development needs. This article is categorized under: 1Engineering Water > Water, Health, and Sanitation2Science of Water > Water Extremes3Water and Life > Nature of Freshwater Ecosystems.

A catchment-scale model to predict spatial and temporal burden of E. coli on pasture from grazing livestock

Effective management of diffuse microbial water pollution from agriculture requires a fundamental understanding of how spatial patterns of microbial pollutants, e.g. E. coli, vary over time at the landscape scale. The aim of this study was to apply the Visualising Pathogen &Environmental Risk (ViPER) model, developed to predict E. coli burden on agricultural land, in a spatially distributed manner to two contrasting catchments in order to map and understand changes in E. coli burden contributed to land from grazing livestock. The model was applied to the River Ayr and Lunan Water catchments, with significant correlations observed between area of improved grassland and the maximum total E. coli per 1km² grid cell (Ayr: r=0.57; p<0.001, Lunan: r=0.32; p<0.001). There was a significant difference in the predicted maximum E. coli burden between seasons in both catchments, with summer and autumn predicted to accrue higher E. coli contributions relative to spring and winter (P<0.001), driven largely by livestock presence. The ViPER model thus describes, at the landscape scale, spatial nuances in the vulnerability of E. coli loading to land as driven by stocking density and livestock grazing regimes. Resulting risk maps therefore provide the underpinning evidence to inform spatially-targeted decision-making with respect to managing sources of E. coli in agricultural environments.

Fit-for-purpose wastewater treatment: Conceptualization to development of decision support tool (I)

This article is the first in a series of two papers. Paper I focuses on model conceptualization and development, and Paper II in the series focuses on model validation and implementation. The amount of water reuse has been increasing across the globe. Wastewater can be treated based on the intended end use of reclaimed water. Fit-for-purpose wastewater treatment (WWT) simultaneously considers intended end use, economic viability, and environmental sustainability. WWT technologies differ mainly in terms of treatment efficiency, cost, energy use, and associated carbon emissions. The planning and evaluation of water reuse projects requires a decision support tool (DST) to evaluate alternative WWT trains and water reuse applications. However, such a DST is not available in the publically accessible literature. A DST, FitWater, has been developed for the evaluation of WWT for various urban reuses. The evaluation is based on the following criteria: amount of reclaimed water production, health risk of water reuse, cost, energy use, and carbon emissions. The cost is estimated as annualized life cycle cost and health risk is estimated using quantitative microbial risk assessment. The uncertainty analysis has been performed using probabilistic and fuzzy-based methods. A multi-criteria decision analysis, using fuzzy weighted average, is employed to aggregate different criteria and generate a final score. FitWater ranks alternative WWT trains based on the resulting final score. The proposed FitWater DST is user-friendly, and its application is demonstrated using an example. The DST can be enhanced to include additional treatment technologies and carbon emissions of different treatment processes.

Modeling fate and transport of fecally-derived microorganisms at the watershed scale: State of the science and future opportunities

Natural waters serve as habitat for a wide range of microorganisms, a proportion of which may be derived from fecal material. A number of watershed models have been developed to understand and predict the fate and transport of fecal microorganisms within complex watersheds, as well as to determine whether microbial water quality standards can be satisfied under site-specific meteorological and/or management conditions. The aim of this review is to highlight and critically evaluate developments in the modeling of microbial water quality of surface waters over the last 10 years and to discuss the future of model development and application at the watershed scale, with a particular focus on fecal indicator organisms (FIOs). In doing so, an agenda of research opportunities is identified to help deliver improvements in the modeling of microbial water quality draining through complex landscape systems. This comprehensive review therefore provides a timely steer to help strengthen future modeling capability of FIOs in surface water environments and provides a useful resource to complement the development of risk management strategies to reduce microbial impairment of freshwater sources.

QMRAcatch: Human-Associated Fecal Pollution and Infection Risk Modeling for a River/Floodplain Environment

Protection of drinking water resources requires addressing all relevant fecal pollution sources in the considered catchment. A freely available simulation tool, QMRAcatch, was recently developed to simulate concentrations of fecal indicators, a genetic microbial source tracking (MST) marker, and intestinal pathogens in water resources and to conduct a quantitative microbial risk assessment (QMRA). At the same time, QMRAcatch was successfully applied to a region of the Danube River in Austria, focusing on municipal wastewater emissions. Herein, we describe extension of its application to a Danube River floodplain, keeping the focus on fecal sources of human origin. QMRAcatch was calibrated to match measured human-associated MST marker concentrations for a dry year and a wet year. Appropriate performance characteristics of the human-associated MST assay were proven by simulating correct and false-positive marker concentrations, as determined in human and animal feces. With the calibrated tool, simulated and measured enterovirus concentrations in the rivers were compared. Finally, the calibrated tool allowed demonstrating that 4.5 log enterovirus and 6.6 log norovirus reductions must be achieved to convert current surface water to safe drinking water that complies with a health-based target of 10 infections person yr. Simulations of the low- and high-pollution scenarios showed that the required viral reductions ranged from 0 to 8 log. This study has implications for water managers with interests in assessing robust catchment protection measures and water treatment criteria by considering the fate of fecal pollution from its sources to the point of abstraction.

Microbial Transport and Fate in the Subsurface Environment: Introduction to the Special Section

Microorganisms constitute an almost exclusive form of life in the earth's subsurface environment (not including caves), particularly at depths exceeding the soil horizon. While of broad interest to ecology and geology, scientific interest in the fate and transport of microorganisms, particularly those introduced through the anthropogenic environment, has focused on understanding the subsurface environment as a pathway for human pathogens and on optimizing the use of microbial organisms for remediation of potable groundwater. This special section, inspired by the 2014 Ninth International Symposium for Subsurface Microbiology, brings together recent efforts to better understand the spatiotemporal occurrence of anthropogenic microbial groundwater contamination and the fate and transport of microbes in the subsurface environment: in soils, deep unsaturated zones, and within aquifer systems. Work includes field reconnaissance, controlled laboratory studies to improve our understanding of specific fate and transport processes, and the development and application of improved mechanistic understanding of microbial fate and transport processes in the subsurface environment. The findings confirm and also challenge the limitations of our current understanding of highly complex microbial fate and transport processes across spatiotemporal scales in the subsurface environment; they also add to the increasing knowledge base to improve our ability to protect drinking water resources and perform in situ environmental remediation.