Municipal Water Distribution Networks Research Articles

Occurrence and identification of microplastics retained in corrosion deposits of drinking water transmission pipes

The irregular structure and high porosity of corrosion deposits create suitable conditions for the retention, accumulation and adsorption of microplastics (MPs) and nanoplastics (NPs) transported by distributed water. Due to the low mass and continuous degradation of MPs, under certain conditions (e.g., changes in water composition or hydraulic conditions, network failures), these particles can be re-released into the water, causing secondary contamination. This paper presents preliminary results on the degree of MP contamination of sediments lining the inner surface of metal alloy pipes taken from a municipal drinking water distribution network. The isolated particles were assessed in terms of number, shape, residence time in the network, and origin. Plastic fragments classified as MPs and NPs were found in all analyzed corrosion deposits. Fragments smaller than 50 μm predominated, indicating a high level of plastic fragmentation associated with advanced degradation and prolonged residence in the environment. The predominant plastics identified were polyethylene (PE), polyethylene terephthalate (PET), and polyamides. High-carbon particles, most likely NP particles, whose presence in drinking water may pose a high health risk to consumers due to their potential to migrate into body tissues, were very abundant in the sediments but impossible to count with the techniques used. The results indicate the need to intensify research on the content of MPs and NPs not only in drinking water, but also in the sediments covering the interior of distribution pipes, and to identify factors that may cause their secondary release into bulk water.

Chemical and Microbiological Quality of Municipal Supply Water in Dhaka South Area, Bangladesh

This project aimed to find out the microbiological quality of municipal supply water in Dhaka South area and if the current regime of microbiological quality testing can determine the risk to public health from supply water satisfactorily. Water samples were collected from six different points of the water distribution network of Dhaka’s south locality, starting from the source (Shitalakhyariver, Narayanganj) to Jagannath University, Dhaka. The dominant taxonomic units were isolated using standard culture techniques, followed by biochemical identification, VITEK2 identification, and biofilm-forming potential of each isolate individually and co-cultured with other isolates. Presumptive identification of isolates from the Shitalakhya River revealed the presence of Citrobacter sp., Alcaligenes sp., and Pseudomonas putida. The sample from Saydabad Water Treatment Plant yielded Vibrio mimicus, Pseudomonas fluorescence, and Alcalimonas. The major aerobic bacteria in the water specimen from the community overhead tank included S aureus, Bacillus cereus, Micrococcus sp., Enterococcus sp., Lactococcus sp. Tap water revealed the presence of Escherichia coli, Lactococcus, Enterobacter, Shigella, Klebsiella, Pseudomonas, and Staphylococcus aureus, as well as anaerobic bacteria. Biochemical tests and VITEK2 yielded different results. Potential biofilm formers such as Klebsiella, E. coli, Enterococcus, Aerococcus, Enterobacter, and Cronobacter indicated quality deterioration potential inside the piped water supply system. Alteration in the major taxonomic units throughout the municipal water distribution network and the presence of opportunistic pathogens and biofilm-formers indicate the necessity for an updated water treatment, quality control, and in-line maintenance system.

A regret-based robust optimization model for municipal water distribution network redesign under disruption risks

In recent decades, the increasing demand for water and resource limitations have posed challenges to water resources management. This study proposes a comprehensive model for redesigning urban water distribution network under disruptions, focusing on household consumption. The proposed model integrates strategic decisions for network, and addresses disruption risks. To ensure the resilience of the network against disruptions caused by earthquakes, we developed a regret-based robust optimization model. The model minimizes redesign and operational costs by optimizing water flow, construction locations, and pipeline connections. Numerical results demonstrate the efficacy of the proposed model, revealing a reduction in average costs—approximately 0.6 %—compared to the deterministic model. This reduction is noteworthy given the scale of municipal water distribution configuration costs. Also, resiliency analysis demonstrates the superiority of the robust solution compared to the deterministic structure. The model supports policymakers for operational and long-term decisions, considering complex hydraulic constraints and horizontal transfers between reservoirs.

Water distribution pipe lifespans: Predicting when to repair the pipes in municipal water distribution networks using machine learning techniques

Water is one of the essential matters that keeps living species alive; yet, the lifespan of pipes has two direct impacts on wasting water in very great amounts: pipe leakages and pipe bursts. Consequently, the proper detection of aged pipes in the water distribution networks has always been an issue in overcoming the problem. This makes water pipe monitoring an important duty of municipalities. Traditionally, leakages and bursts were only detected visually or through reports in local areas, leading municipalities to change the old pipes. Although this helps to fix the issue, a more desired way is to perhaps let officials know about the possibilities of such problems in advance by predicting which pipes are aged, so they can prevent the wastage. Therefore, to automate the detection process, in this study, we take the initial steps to predict the pipes needing repair in a particular area using machine learning methods. We first obtain a private dataset provided by the municipality of Saveh, Iran which outlines pipes that were damaged previously. We then train three machine learning algorithms to predict whether a set of pipes in an area is prone to damage. To achieve this, One-Class (OC) Classification methods such as OC-SVM, Isolation Forest, and Elliptic Envelope are used and they achieved the highest accuracy of 0.909. This study is of value since it requires zero additional devices (i.e., sensors).

Community Resilience and Consequence Management of Pollution Intrusion Into Water Distribution Network: A Case Study

Contamination intrusion into the municipal water distribution network (WDN) without appropriate action may lead to disaster. This study examined community resilience (CR) and its effects on optimal consequence management (CM) plans. CR was measured by five dimensions: governance, preparedness, social learning, social trust, and collective efficacy. The above dimensions were measured by conducting a structured questionnaire survey, and CR was then defined using structural equation modeling. Furthermore, water usage changes of consumers in response to contamination intrusion were investigated through questionnaires. NSGA-II algorithm was used for CM optimization with the objectives of minimum contaminated water ingestion and operational interventions, and the results were presented in three scenarios. The proposed method was evaluated in a WDN in the southeastern part of Tehran. The CR was quantified as 2.58 out of 5 using a one-sample t-test which shows that the studied community is not resilient. Without considering the demand changes during WDN contamination, the maximum total ingested polluted water is 184 Kg. Considering demand reduction (scenario 2), it diminishes to 154 Kg. As CR was identified as one of the significant factors for water demand variations via linear regression analysis, by empowering CR by one point (scenario 3), contaminated water ingestion decreases to 151 Kg. The immense difference between the base scenario and the two others (16% and 18% reduction in total ingestion) indicates that it is vital to consider people’s reactions in CM plans and enhance CR to preserve public health.

Principal component analysis in long term assessment of total viable plate count of municipal water distribution network system in healthcare facility

The microbial quality of water is a critical safety aspect that should not be overlooked, especially when considering human consumption in the facilities for healthcare and the treatment of health compromised populations. The present work aimed to study a municipal network for city water within a healthcare facility microbiologically. The implementation of multivariate analysis was conducted over collected data to decipher trends of the microbiological count of samples from different points-of-use. The statistical study involved an Eigenvalue determination, score graph, loading plot study and outlier diagram. Data showed clustering tendency with aberrant values could be observed. The first component appeared to be associated with bioburden density in the water. While the other component showed a link to the relative locations of the distribution points in the facility and the length of the water lines from the source feeding city water to a great extent. The two components explained more than 55% of the variations in data. A property that highlighted a strong agreement between the order of points-of-use in the loading plot with that of ratio factor which was obtained from the Total Viable Count over the hypothetical distance of sampling port from the reference feeding entrance. Thus, there was evidence of variation in the microbial quality affected by the biological stability of the water distribution system that needed attention and an improvement plan for better control of microbial content in city water to prevent possible excursions in the future. The study showed a valuable perspective approach for the quantitative examination of the microbiological stability of the municipal water distribution network system.

Dendrogram Analysis and Statistical Examination for Total Microbiological Mesophilic Aerobic Count of Municipal Water Distribution Network System

The microbiological quality of water for human consumption is a critical safety aspect that should not be overlooked, especially when considering facilities for healthcare and the treatment of ill populations. Thus, the biological stability of water is crucial for the distribution network that delivers potable water to the final users for consumption and other human activities. The present work aimed to study a municipal distribution network system for city water within a healthcare facility. The implementation of the statistical analysis was conducted over long-term data collection, and the comparative study for the microbiological count of the water samples - from different points-of-use was assessed using the non-parametric analysis of the Kruskal-Wallis test. The comparative study involved a preliminary general one-way Analysis of Variance (ANOVA) followed by ad-hoc pairwise comparison. The statistical study involved a correlation matrix and a dendrogram to elucidate the level of association between different sections in the network. The ports C4 and C13 were at the trough in the microbiological count, in contrast to C13, which showed the highest level of the average microbial density. Despite a low to moderate level of correlation between the datasets of the water network, the tree diagram (dendrogram) analysis showed remarkable clustering. Use points could be grouped into three dense groups based on abrupt cuts in the similarity value. The study was useful in the analysis of the pattern and behavior of the microbial quality in a distribution water network in a specific area of the study. This work in turn would help in investigating the areas of improvement and defect spotting, in addition to assessing the biological stability of the water distribution system. The study could be extended to cover other different processed water networks, such as distilled, deionized, and purified water, as well as Water-For-Injection (WFI). Doi: 10.28991/HIJ-2022-03-01-03 Full Text: PDF

GAP FILLERS OR PIONEERS: INFORMAL WATER SUPPLIERS IN PERI-URBAN AREAS OF THE TECHIMAN MUNICIPALITY OF GHANA

There is continuous expansion and growth of urban and peri urban areas in Sub-Saharan Africa with projections indicating that this will double. Some peri-urban areas such as those in the Techiman municipality of Ghana are experiencing this trend. Nonetheless, the spate of growth of these areas outstrips the supply of utilities by municipal water distribution networks. As a result, some areas have little or no public provision. In order to address the water supply challenge, places with favourable hydrological settings are witnessing the emergence of informal water suppliers as “gap fillers” or “pioneers”, providing water services. Noteworthy, however, existing studies about informal water suppliers in peri-urban areas in Ghana lump them together, without considering the water source. This study differs in that it specifically examines the evolution and the features of informal water suppliers who privately and independently abstract and supply groundwater. Additionally, it attempts to understand the nature of informality of the suppliers and the possibility of formalisation. The paper is an exploratory study using the case of private mechanised borehole operators who supply water in their respective areas. The findings showed that in some peri-urban areas in the Techiman municipality, some dwellers constructed and operated mechanised boreholes, which provide in-situ water and utilities to others. They are mostly pioneer water suppliers in some of the areas. Their services are informal by nature because they are largely independent of the formal sector and apply informal arrangements in rendering their services. Seen also as business enterprises, they are not licenced. However, the boreholes are registered with the Municipal Assembly, which indicated some level of formalisation. The study recommended that efforts to formalise them further should focus on improving water quality monitoring for consumption and promoting sustainable abstraction.

Optimal design of looped water supply network by GA-NLP hybrid approach

Any Municipal distribution system consists of pipe network, valves and pressure generating facilities etc. Around 70% of total cost of any water distribution system is towards cost of pipe network only. Therefore, the cost of pipe network is to be reduced by selecting the appropriate lengths of candidate diameter pipes between the nodes in a pipe network.In the present study, a municipal looped water distribution network is designed for least cost by Genetic Algorithm – Non Linear Programming (GA-NLP) hybrid approach. In the present study, optimal lengths of sub pipes of various discrete diameters (sizes) available in the market making the link between the nodes are obtained by minimising the total cost of pipe network. In order to obtain the optimal solution of a looped network, non - linear hydraulic analysis and optimization of network is to be performed. In this study, non - linear hydraulic analysis is made a part of optimization by adding loop head loss and node continuity equations as constraints to the objective function. The model developed is solved by GA-NLP hybrid approach in MATLAB. Near optimal solution obtained by GA is taken as initial solution of NLP for obtaining optimal solution. By adopting GA-NLP hybrid approach, convergence is faster when compared to GA avoiding the complexity in selection of suitable trial values of GA parameters.Many researchers applied different techniques like linear programming, integer linear programming, linear programming gradient method and branch & bound algorithm etc. and optimized the looped pipe network by minimizing the cost. The results obtained by proposed model are compared with that of other investigators and found to be superior. It is also concluded that the proposed model may be applied to any larger municipal looped pipe network through demonstration by applying proposed model to a case study of Rajiv Gandhi Nagar of Guntur Municipal Corporation.

Potentially toxic elements determination and chemical-microbiological analysis of potable water in Taxco de Alarcón, Guerrero

Taxco de Alarcón is an important mining site in Mexico. The town is a well-known tourist destination where the potable water quality is important for guaranteeing the health of the users. Due to the altitude of the city, the surface and rain water are the main sources of water. Thus, the aims of this study were to characterize i) the composition and chemical speciation of particulate matter suspended in water to determine the content of potentially toxic elements, and ii) the chemical and bacteriological composition of the potable water of Taxco de Alarcón, Guerrero, Mexico, according to the Mexican official norm NOM-127-SSA1-1994.
 The analyzed representative samples were taken from the municipal water distribution network, the water treatment plant, the Chacuhalco spring and a mixture of the waters of the Chontalcuatlán river, the Tenería spring, and the San Marcos and El Sombrerito dams. According to the results, 94 % of the analyzed samples did not comply with the standard NOM-127-SSA1-1994. Moreover, the distribution of the analyzed elements in the different chemical fractions of the particulate matter showed that the highest concentration of Cd (4.17 mg∙kg-1) is associated with the carbonate fraction. This means Cd is moderately bioavailable. On the other hand, the highest concentrations of Pb, Zn, Mn and Cu (62.2, 42.3, 243 and 1026 mg∙kg-1, respectively) were detected in the Fe-Mn oxyhydroxide fraction, also considered as moderately bioavailable, whereas the highest concentrations of As, Fe and V (24.0, 7583 and 31.3 mg∙kg-1, respectively) were associated with the residual fraction, considered as non-bioavailable.
 The results indicate that, to improve the quality of potable water, modifications must be incorporated along the water treatment processes, and in the distribution network and management.

Using simulation model to determine the regulation and to optimize the quantity of chlorine injection in water distribution networks

Water can be disinfected by various techniques. Chlorination is the most prevalent and the cheapest method in this regard. One of the most significant factors in chlorination is the location and the amount of chlorine injections, both of which must be chosen in a way that the amount of chlorine remaining in all sections of a city’s water distribution network is within the standard range, and the associated costs are reduced to a considerable extent. Therefore, in this research, we have implemented a technique which takes both of those issues, i.e., the amount of residual chlorine in pipes and the quantity of chlorine consumed in diverse sections of the water distribution network into account leading to a much more cost-effective water disinfection technique. Our technique shows that municipal water distribution network, are effectively in tune with the current highest standards set in the water disinfection procedure for the lowest possible cost. For modeling the water allocation network, the WaterGems software was used. Using this software, the network was modeled into two practical methods, i.e., gravity and direct pumping methods. The productivity of gravity as well as direct pumping methods was shown to control the optimal chlorine injection rate by resolving the two applied models of water distribution networks. The results showed that the residual chlorine content in 70% of the direct pipe network was within the standard range and in 100% of the tubes in the gravity distribution network lower than the standard. Also, the chlorine which was consumed in the direct pumping network was 7% lesser than that in the gravity distribution network. This research showed that the adjusting of chlorine injection into direct-pumped networks compared with gravity distribution networks was more feasible and also required less chlorine consumption.

Optimal Water–Power Flow-Problem: Formulation and Distributed Optimal Solution

This paper formalizes an optimal water–power flow (OWPF) problem to optimize the use of controllable assets across power and water systems while accounting for the couplings between the two infrastructures. Tanks and pumps are optimally managed to satisfy water demand while improving power grid operations; for the power network, an ac optimal power-flow formulation is augmented to accommodate the controllability of water pumps. Unfortunately, the physics governing the operation of the two infrastructures and coupling constraints leads to a nonconvex (and, in fact, NP-hard) problem; however, after reformulating OWPF as a nonconvex, quadratically constrained quadratic problem, a feasible point pursuit-successive convex approximation approach is used to identify feasible and optimal solutions. In addition, a distributed solver based on the alternating direction method of multipliers enables water and power operators to pursue individual objectives while respecting the couplings between the two networks. The merits of the proposed approach are demonstrated for the case of a distribution feeder coupled with a municipal water distribution network.

Optimal layout of pressure monitoring points in water supply network based on Optics

It is necessary to monitor the pressure in the networks in real time, when we face the problem of pipe burst and leakage in urban water supply network. Therefore, it is particularly important to arrange pressure monitoring points in appropriate places in the pipeline networks. The pressure monitoring point layout is often based on similar degree of the node pressure data in the current stage. A method of optimal pressure monitoring point location in the urban water distribution networks was proposed in this paper. Since the above method did not consider spatial properties of network node. The original feature matrix data is constructed by acquiring the spatial attributes of the pressure monitoring nodes and calculating the non-spatial attributes of the nodes. The original feature matrix data will be normalized. Then the Optics clustering algorithm is used to cluster the normalized node feature matrix data to determine the location and number of pressure monitoring points in monitoring area of urban water distribution networks. Experimental results show that the method effectively ensures that the pressure monitoring points can grasp the pressure information of the whole water supply network more comprehensively and rationally, improves the economy of the pressure monitoring points layout, and provides good guidance for the actual layout of pressure monitoring points in municipal water distribution networks.

A two-time-scale point process model of water main breaks for infrastructure asset management

Deterioration modelling has been a bottlenecking step towards risk-informed asset management of municipal water distribution networks. To close the gap, we proposed a two-time-scale (TTS) point process model on a pipe level for modelling and prediction of water main breaks. This paper presents the characterization, statistical parameter estimation, probabilistic features, and application of the model. Combining Poisson and renewal models into one, the proposed TTS process is characterized by a conditional intensity function of two time variables—one in a pipe clock for overall pipe aging and the other in a repair clock for local renewal. As a result, different aging patterns including the complicated bathtub-type behaviour can be modelled. A novel statistical method that combines data augmentation and Markov Chain Monte Carlo was developed for model estimation to deal with partially missing event histories. A case study using real-life data collected from a regional municipality in Canada was presented to illustrate the application of the proposed model. The modelling process ranging from model estimation, verification, validation, and updating to application in asset management was thoroughly demonstrated. This study also demonstrated that one must use the full distributions of the parameters to obtain an unbiased prediction of mean number of water main breaks. The proposed model was also compared with the Poisson process model in terms of break intensity, survival probability, mean cumulative number of breaks, and mean annual number of breaks. The implications of the different results to asset management were carefully discussed as well. Last, the ability of the proposed model to capture the maintenance effectiveness of pipe repair was proven. This work represents a solid advancement towards holistic assessment of the aging risk of a municipal water distribution network.

A prioritization method for replacement of water mains using rank aggregation

Pipe breaks in municipal water distribution networks may cause serious damage economically and socially. Existing methods for replacement scheduling of pipes do not provide practical indicators for replacing an individual deteriorated pipe. This work formulates the selection problem as the decision of preference ordering or ranking and proposes a bipartite ranking-based approach. The suggested approach also considers loss from broken pipes in terms of the costs associated with broken water main and its repair. We use rank aggregation method to integrate multiple ranks into replacement order of water mains. The suggested framework prioritizes current pipe sections for replacement based on the aggregated ranks. Multiple ranks given by the reliability of water pipe sections are aggregated and a cost effective policy for pipe replacement is derived.

Calibration of Proportional Controllers for the RTC of Pressures to Reduce Leakage in Water Distribution Networks

AbstractPressure control is a key issue for the reduction of water loss through leakage in municipal water distribution networks (WDNs). The paper presents a general method to calibrate the proportional controllers for the real time control (RTC) of motorized pressure valves in WDNs to reduce leakage during ordinary operation. The method is based on the comprehensive dimensionless analysis of the behavior of simplified hydraulic systems under RTC scenarios. A numerical approach was used to derive a simple regressive relationship to tune the controller on the basis of the system dimensionless variables involved in the control process. The method was validated by application to a well-known bench-test water distribution network and compared with an existing literature calibration procedure. Results show that the proposed method allows for effective controller tuning and leads to performing leakage reduction-oriented real time control of pressures.

Optimisation of water networks using linear programming

In this study, optimal design of municipal water distribution networks is determined by the mixed-integer real linear programming technique. The method is capable of rapidly obtaining the discrete characteristics of commercially available pipe sizes, pumps and reservoir heights. The hydraulic and optimisation analyses are linked through an iterative procedure which enables a water distribution system to be designed that satisfies all required constraints with a minimum total cost. The constraints include pipe sizes, which are limited to the commercially available sizes, reservoir heights, available pumps, pipe flow velocities and nodal pressures. Unlike integer linear programming, the developed model has the advantages of having short nodal pressure constraint equations and the ability of optimising networks that contain pumps. The proposed model has also been applied to a network solved by others. Comparison of the results indicates that the results of the proposed method are satisfactory.

Assessment of Iron and Manganese Concentration Changes in Kaunas City Drinking Water Distribution System

Environmental factors may affect the quality of drinking water supplied by municipal water distribution network. The aim of this study was to analyze the factors influencing changes in concentrations of iron (Fe) and manganese (Mn) in Kaunas drinking water distribution network. Analytical study on the drinking water quality was performed. Concentrations of manganese and iron in drinking water were assessed by using an atomic absorption spectrophotometer. Correlation between the changes in manganese concentrations and the distance from the water treatment plant was found, the correlation coefficient was -0.367; p=0.022, however, for iron it was 0.179; p = 0.148. At some sampling points the concentrations of Mn and Fe exceeded the regulated limits. To ensure the water quality and to avoid possible adverse health effects it is recommended to install Mn and Fe filter system in a consumer’s drinking water pipeline.

Formulation and Optimization of Robust Sensor Placement Problems for Drinking Water Contamination Warning Systems

The sensor placement problem in contamination warning system design for municipal water distribution networks involves maximizing the protection level afforded by limited numbers of sensors, typically quantified as the expected impact of a contamination event; the issue of how to mitigate against high-consequence events is either handled implicitly or ignored entirely. Consequently, expected-case sensor placements run the risk of failing to protect against high-consequence 9/11-style attacks. In contrast, robust sensor placements address this concern by focusing strictly on high-consequence events and placing sensors to minimize the impact of these events. We introduce several robust variations of the sensor placement problem, distinguished by how they quantify the potential damage due to high-consequence events. We explore the nature of robust versus expected-case sensor placements on three real-world large-scale distribution networks. We find that robust sensor placements can yield large reductions in the number and magnitude of high-consequence events, with only modest increases in expected impact. The ability to trade-off between robust and expected-case impacts is a key unexplored dimension in contamination warning system design.

Designing Contamination Warning Systems for Municipal Water Networks Using Imperfect Sensors

We consider the problem of designing a contaminant warning system for a municipal water distribution network that uses imperfect sensors, which can generate false-positive and false-negative detections. Although sensor placement optimization methods have been developed for contaminant warning systems, most sensor placement formulations assume perfect sensors, which does not accurately reflect the behavior of real sensor technology. We describe a general exact nonlinear formulation for imperfect sensors and a linear approximation. We consider six general solution strategies, some of which have multiple solution methods. We applied these methods to three test networks, including one with over 10,000 nodes. Our experiments indicate that it is worth deploying a sensor network even when sensors have low detection probability. They also indicate it is worth paying attention to sensor imperfections when placing sensors even when there is a response delay of up to 8 h. The best choice of solution strategy depends upon the user's goals and the problem size. However, for large-scale problems with a moderate number of sensors, using a local search for the linear approximation formulation provides a reasonable-quality solution in a few minutes of computation. Our models assume that sensors can fail via false negatives. Additionally, we discuss ways to model false positives, ways to limit them, and how to trade them off against false negatives. All of our solution methods can handle false positives but our experiments do not explicitly consider them.