A relatively short list of reference viral, bacterial and protozoan pathogens appears adequate to assess microbial risks and inform a system-based management of drinking waters. Nonetheless, there are data gaps, e.g. human enteric viruses resulting in endemic infection levels if poorly performing disinfection and/or distribution systems are used, and the risks from fungi. Where disinfection is the only treatment and/or filtration is poor, cryptosporidiosis is the most likely enteric disease to be identified during waterborne outbreaks, but generally non-human-infectious genotypes are present in the absence of human or calf fecal contamination. Enteric bacteria may dominate risks during major fecal contamination events that are ineffectively managed. Reliance on culture-based methods exaggerates treatment efficacy and reduces our ability to identify pathogens/indicators; however, next-generation sequencing and polymerase chain reaction approaches are on the cusp of changing that. Overall, water-based Legionella and non-tuberculous mycobacteria probably dominate health burden at exposure points following the various societal uses of drinking water.

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Microbial Contamination of Drinking Water and Human Health from Community Water Systems

Antibiotic resistance in drinking water systems: Occurrence, removal, and human health risks.

Biological stability of drinking water refers to the concept of providing consumers with drinking water of same microbial quality at the tap as produced at the water treatment facility. However, uncontrolled growth of bacteria can occur during distribution in water mains and premise plumbing, and can lead to hygienic (e.g., development of opportunistic pathogens), aesthetic (e.g., deterioration of taste, odor, color) or operational (e.g., fouling or biocorrosion of pipes) problems. Drinking water contains diverse microorganisms competing for limited available nutrients for growth. Bacterial growth and interactions are regulated by factors, such as (i) type and concentration of available organic and inorganic nutrients, (ii) type and concentration of residual disinfectant, (iii) presence of predators, such as protozoa and invertebrates, (iv) environmental conditions, such as water temperature, and (v) spatial location of microorganisms (bulk water, sediment, or biofilm). Water treatment and distribution conditions in water mains and premise plumbing affect each of these factors and shape bacterial community characteristics (abundance, composition, viability) in distribution systems. Improved understanding of bacterial interactions in distribution systems and of environmental conditions impact is needed for better control of bacterial communities during drinking water production and distribution. This article reviews (i) existing knowledge on biological stability controlling factors and (ii) how these factors are affected by drinking water production and distribution conditions. In addition, (iii) the concept of biological stability is discussed in light of experience with well-established and new analytical methods, enabling high throughput analysis and in-depth characterization of bacterial communities in drinking water. We discussed, how knowledge gained from novel techniques will improve design and monitoring of water treatment and distribution systems in order to maintain good drinking water microbial quality up to consumer’s tap. A new definition and methodological approach for biological stability is proposed.

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Biological Stability of Drinking Water: Controlling Factors, Methods, and Challenges

A water demand end-use model was developed to predict water demand patterns with a small time scale (1 s) and small spatial scale (residence level). The end-use model is based on statistical inform...

Simulating Residential Water Demand with a Stochastic End-Use Model

In drinking water distribution systems (DWDS), biofilms are the predominant mode of microbial growth, with the presence of extracellular polymeric substance (EPS) protecting the biomass from environmental and shear stresses. Biofilm formation poses a significant problem to the drinking water industry as a potential source of bacterial contamination, including pathogens, and, in many cases, also affecting the taste and odor of drinking water and promoting the corrosion of pipes. This article critically reviews important research findings on biofilm growth in DWDS, examining the factors affecting their formation and characteristics as well as the various technologies to characterize and monitor and, ultimately, to control their growth. Research indicates that temperature fluctuations potentially affect not only the initial bacteria-to-surface attachment but also the growth rates of biofilms. For the latter, the effect is unique for each type of biofilm-forming bacteria; ammonia-oxidizing bacteria, for examp...

/pdf/understanding-monitoring-and-controlling-biofilm-growth-in-5ez2rie58i.pdf

Understanding, Monitoring, and Controlling Biofilm Growth in Drinking Water Distribution Systems

Pipe bursts in water distribution networks lead to water losses and a risk of damaging the urban environment. We studied hydraulic data and customer contact records of 44 real bursts for a better understanding of the phenomena. We found that most bursts were reported to the water company shortly after the beginning, and the negative consequences of the bursts were limited. However, smaller bursts that stayed unnoticed for a longer time period or larger bursts that began in the late evening or in the night were problematic to the water company that had no burst detection method installed. Detection of those bursts was critical to minimise the negative consequences, and a burst detection method could perform this task. We studied the relation between the size of supply area and the size of the bursts that can be detected. Therefore, we applied a heuristic burst detection method on historic datasets of eight areas varying in size between 1,500 and 48,300 connections. We found a correlation between the size of the area and the minimum detectable burst size and quickly detectable burst size. To reduce the risk of substantial water losses or damage to the urban environment, the burst detection method can effectively be applied to areas with an average demand of 150 m(3)/h or less.

Analysis of historic bursts and burst detection in water supply areas of different size

There is growing interest in modeling water demands on short time scales (as brief as one second) and small spatial scales (typically single homes). Buchberger et al. (1996, 2003) have developed the Poisson Rectangular Pulse (PRP) model for this purpose. Blokker et al. (in prep.) have developed an end-use model SIMDEUM (which stands for SIMulation of Demand, and End-Use Model) which is based on statistical information from end-uses and does not require any flow measurements. SIMDEUM was developed and validated for Dutch water use. In this paper the PRP model and SIMDEUM are compared with each other and with measured indoor water demands from 21 homes in Milford, Ohio. Both models compare well to the measurements; the PRP model works better in simulating the cumulative flows of a sum of 20, SIMDEUM works better in simulating the flows of a single home.

Comparison of water demand models: prp and simdeum applied to milford, ohio, data

Measuring discoloration risk: resuspension potential method

Conventional automatic production flow control and pump pressure control of water supply systems are robust and simple: production flow is controlled based on the level in the clear water reservoir and pump pressure is controlled on a static set-point. Recently, more advanced computer-based control methods were developed in which production flow is controlled by using a short-term water demand forecasting model and pressure is controlled by a dynamic pressure control module. To assess the differences between conventional and advanced control, we examined operational data of water treatment plantGruszczyn that supplies drinking water to a part of the city of Poznan, Poland. We compared two periods of three weeks of conventional and advanced control. The comparison showed that with advanced control the variation in the production flow was 83% lower, and the pump pressure of the clear water pumps was 29% lower. The lower pressure resulted in 20% less background leakage and the overall system's energy costs were 11.5% lower.

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Advanced control of a water supply system: a case study

https://repository.tudelft.nl/islandora/object/uuid%3A8204fa5b-9c7b-4caa-b590-74bb733362fc/datastream/OBJ/download

J.H.G. Vreeburg

Papers

Analysis of historic bursts and burst detection in water supply areas of different size

Comparison of water demand models: prp and simdeum applied to milford, ohio, data

Measuring discoloration risk: resuspension potential method

Advanced control of a water supply system: a case study

Detecting Pipe Bursts Using Heuristic and CUSUM Methods