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A variety of pathogenic microorganisms can survive in the drinking water distribution systems (DWDS) by forming stable biofilms and, thus, continually disseminating their population through the system's dynamic water bodies. The ingestion of the pathogen-contaminated water could trigger a broad spectrum of illnesses and well-being-related obstacles. These waterborne diseases are a significant concern for babies, pregnant women, and significantly low-immune individuals. This review highlights the recent advances in understanding the microbiological aspects of drinking water quality, biofilm formation and its dynamics, health issues caused by the emerging microbes in biofilm, and approaches for biofilm investigation its prevention and suppression in DWDS.

Biofilm formation in drinking water distribution systems (DWDS) is influenced by the source water, the supply infrastructure and the operation of the system. A holistic approach was used to advance knowledge on the development of mixed species biofilms in situ, by using biofilm sampling devices installed in chlorinated networks. Key physico-chemical parameters and conventional microbial indicators for drinking water quality were analysed. Biofilm coverage on pipes was evaluated by scanning electron microscopy (SEM) and confocal laser scanning microscopy (CLSM). The microbial community structure, bacteria and fungi, of water and biofilms was assessed using pyrosequencing. Conventional wisdom leads to an expectation for less microbial diversity in groundwater supplied systems. However, the analysis of bulk water showed higher microbial diversity in groundwater site samples compared with the surface water site. Conversely, higher diversity and richness were detected in biofilms from the surface water site. The average biofilm coverage was similar among sites. Disinfection residual and other key variables were similar between the two sites, other than nitrates, alkalinity and the hydraulic conditions which were extremely low at the groundwater site. Thus, the unexpected result of an exceptionally low diversity with few dominant genera (Pseudomonas and Basidiobolus) in groundwater biofilm samples, despite the more diverse community in the bulk water, is attributed to the low-flow hydraulic conditions. This finding evidences that the local environmental conditions are shaping biofilm formation, composition and amount, and hence managing these is critical for the best operation of DWDS to safeguard water quality.

This paper presents a two-stage method for simultaneous least-cost design and operation of looped water distribution systems (WDSs). After partitioning the network into a chord and spanning trees, in the first stage, a reformulated linear programming (LP) method is used to find the least cost design of a WDS for a given set of flow distribution. In the second stage, a non-linear programming (NLP) method is used to find a new flow distribution that reduces the cost of the WDS operation given the WDS design obtained in stage one. The following features of the proposed two-stage method make it more appealing compared to other methods: (1) the reformulated LP stage can consistently reduce the penalty cost when designing a WDS under multiple loading conditions; (2) robustness as the number of loading conditions increases; (3) parameter tuning is not required; (4) the method reduces the computational burden significantly when compared to meta-heuristic methods; and (5) in oppose to an evolutionary “black box” based methodology such as a genetic algorithm, insights through analytical sensitivity analysis, while the algorithm progresses, are handy. The efficacy of the proposed methodology is demonstrated using two WDSs case studies.

Water losses in water distribution systems are typically analysed using extended period simulations, where its numerical resolution is commonly achieved using the gradient method. These models assume that adjustments to regulating valves occur, either manually or automatically, over an extended period of time, then the system inertia can be neglected. This research introduces the development of a rigid water column model for analysing water leakages in single pipelines, which can be employed to account for regulation valve adjustments in shorter time periods, thereby providing greater accuracy when assessing water losses. The application to a case study is presented to analyse pressure variations and leakage flow patterns over 30, 60, and 180 s. A comparison between the extended period simulation and rigid water column model is presented in order to note the order of magnitude on leakages when the system inertia is not considered. The results confirm that is crucial for water utilities the consideration of inertial system to simulate adequately opening and closure manoeuvres in water distribution systems, since according to the case study the extended period simulation can overestimated or underestimated the total leakage volume in percentages of 37.1 and 55.2 %, respectively.

It is important for water utilities to provide esthetically acceptable drinking water to the public, because our consumers always initially judge the quality of the tap water by its color, taste, and odor (T&O). Microorganisms in drinking water contribute largely to T&O production and drinking water distribution systems (DWDS) are known to harbor biofilms and microorganisms in bulk water, even in the presence of a disinfectant. These microbes include T&O-causing bacteria, fungi, and algae, which may lead to unwanted effects on the organoleptic quality of distributed water. Importantly, the understanding of types of these microbes and their T&O compound-producing mechanisms is needed to prevent T&O formation during drinking water distribution. Additionally, new disinfection strategies and operation methods of DWDS are also needed for better control of T&O problems in drinking water. This review covers: (1) the microbial species which can produce T&O compounds in DWDS; (2) typical T&O compounds in DWDS and their formation mechanisms by microorganisms; (3) several common factors in DWDS which can influence the growth and T&O generation of microbes; and (4) several strategies to control biofilm and T&O compound formation in DWDS. At the end of this review, recommendations were given based on the conclusion of this review.

In this paper, a simplified methodology to increase the water distribution equity in existing intermittent water distribution systems (WDSs) is presented. The methodology assumes to install valves in the water distribution network with the objective to re-arrange the flow circulation, thus allowing an improved water distribution among the network users. Valve installation in the WDS is based on the use of algorithms of sequential addition (SA). Two optimization schemes based on SA were developed and tested. The first one allows identifying locations of gate valves in order to maximize the global distribution equity of the network, irrespectively of the local impact of the valves on the supply level of the single nodes. Conversely, the second scheme aims to maximize the global equity of the network by optimizing both location and setting (opening degree) of control valves, to include the impact of the new flow circulation on the supply level of each node. The two optimization schemes were applied to a case study network subject to water shortage conditions. The software EPA Storm Water Management Model (SWMM) was used for the simulations in the wake of previous successful applications for the analysis of intermittent water distribution systems. Results of the application of the SA algorithms were also compared with those from the literature and obtained by the use of the multi-objective Non-Dominated Sorted Genetic Algorithm II (NSGA II). The results show the high performance of SA algorithms in identifying optimal position and settings of the valves in the WDS. The comparison pointed out that SA algorithms are able to perform similarly to NSGA II and, at the same time, to reduce significantly the computational effort associated to the optimization process.

Biofilms in drinking water distribution systems (DWDSs) could cause several types of problems, such as the deterioration of water quality, corrosion of pipe walls, and potential proliferation of opportunistic pathogens. In this study, ten biofilm samples from different pipe materials, including ductile cast iron pipe (DCIP), gray cast iron pipe (GCIP), galvanized steel pipe (GSP), stainless steel clad pipe (SSCP), and polyvinyl chloride (PVC), were collected from an actual DWDS to investigate the effect of pipe material on bacterial community. Real-time quantitative polymerase chain reaction (qPCR) and culture-based method were used to quantify bacteria. 454 pyrosequencing was used for bacterial community analysis. The results showed that the numbers of total bacteria and culturable heterotrophic bacteria from iron pipes were higher than that in PVC, while the numbers of Shigella and vibrios were low in biofilms from iron pipes. Bacterial community analysis showed that Hyphomicrobium or Desulfovibrio were the predominant microorganism in iron pipes, whereas Sphingomonas or Pseudomonas were dominant in other types of pipe. This study revealed differences in bacterial communities in biofilms among different pipe materials, and the results were useful for pipeline material selection in DWDSs.

A drinking water distribution system (DWDS) is the final and essential step to supply safe and high-quality drinking water to customers. Biological processes, such as biofilm formation and detachment, microbial growth in bulk water, and the formation of loose deposits, may occur. These processes will lead to deterioration of the water quality during distribution. In extreme conditions, pathogens and opportunistic pathogens may proliferate and pose a health risk to consumers. It is, therefore, necessary to understand the bacteriology of DWDSs to develop effective strategies that can ensure the water quality at consumers' taps. The bacteriology of DWDSs, both the quantitative growth and the qualitative bacterial community, has attracted considerable research attention. However, the researchers have focused mainly on the pipe wall biofilm. In this review, DWDS bacteriology has been reviewed multidimensionally, including both the bacterial quantification and identification. For the first time, the available literature was reviewed with an emphasis on the subdivision of DWDS into four phases: bulk water, suspended solids, loose deposits, and pipe wall biofilm. Special concentration has been given to potential contribution of particulate matter: suspended particles and loose deposits. Two highlighted questions were reviewed and discussed: (1) where does most of the growth occur? And (2) what is the contribution of particle-associated bacteria to DWDS bacteriology and ecology? At the end of this review, recommendations were given based on the conclusion of this review to better understand the integral DWDS bacteriology.

In recent years, as a result of emerging renewable energy markets, several developed regions have already launched Real‐Time Pricing (RTP) strategies for electricity markets. Establishing optimal pump operation for water companies in RTP electricity markets presents a challenging problem. In a RTP market, both positive and negative electricity prices are possible. These negative prices create economically attractive opportunities for Water Distribution System (WDS) to dispatch their energy consumption. On the other hand, excessively high prices may put WDS at risk of supply disruptions and reduced service levels. However, the continuous development of wind power and photovoltaics results in more volatile and unpredictable fluctuations in the price of renewable energy. The risk arising from uncertainty in electricity prices can lead to a significant increase in actual costs. To address this issue, this paper develops an a posteriori random forest (AP‐RF) approach to forecast the probability density function of electricity prices for the next day and provide a risk‐constrained pump scheduling method toward RTP electricity market. The experimental results demonstrate that the developed method effectively addresses the issue of increased costs caused by inaccurate electricity price forecasting. Plain Language Summary With the emergence of renewable energy markets in recent years, several developed regions have introduced Real‐Time Pricing (RTP) strategies for their electricity markets. This has created a difficult challenge for water companies seeking to establish the optimal pump operation in RTP markets. This study investigates the use of a risk‐constrained optimization scheduling approach for water distribution networks to mitigate the risks associated with inaccurate real‐time electricity price forecasting. Our proposed method is designed to reduce the costs associated with inaccurate electricity price prediction. Key Points A robust pump scheduling approach toward real‐time electricity price market is developed Developing a posteriori random forest algorithm to predict the probability density function of Real‐time electricity price Optimal scheduling with risk constraints is an effective approach to mitigating the risks associated with inaccurate electricity forecasting

The water distribution system (WDS) hydraulic model is extensively used for design and management of WDS. The nodal water demand is the crucial parameter of the model that requires accurate estimating by the pressure measurements. Proper pressure sampling design is essential for estimating nodal water demand and improving model accuracy. Existing research has emphasized the need to enhance the observability of monitoring systems and mitigate the adverse effects of monitoring noise. However, methods that simultaneously consider both of these factors in sampling design have not been adequately studied. In this study, a novel two-objective sampling design method is developed to improve the system observability and mitigate the adverse effects of monitoring noise. The approach is applied to a realistic network and results demonstrate that the developed approach can effectively improve the observability and robustness of the system especially when considerable measurement noise is considered.