Water Distribution Systems Research Articles

Applications of Machine Learning in Drinking Water Quality Management: A Critical Review on Water Distribution System

Applications of Machine Learning in Drinking Water Quality Management: A Critical Review on Water Distribution System

Building the social. A query into the societal impact of the Pompeian water supply

This study explores the importance of the means of ensuring water supply in the formation of the architectural profile and basic social organization of Pompeii. It sees the city’s domestic water supply, for over two centuries ensured through rainwater-harvesting areas, basins and cisterns situated mainly in and below the many atria, as a stabilizing factor of both cityscape and household. Through the introduction of the city aqueduct in the 1st century AD and the creation of a generous network of public fountains this situation changes and the need to maintain the traditional organization of the “houseful”, comprising enlarged family, slaves and dependents of various kind including shopkeepers, is lessened; the physical proximity between those of different status renegotiated. This development, witnessed in adaptations of the architecture, can be followed through close study of the standing structures in Insula V 1. The hallmarks are the creation of upperfloor living quarters seemingly independent from the life of the large households of the atrium houses, and in parallel the introduction of private water lines from the city aqueduct. The remodelling that resulted in the creation of the double-atrium house of Caecilius Iucundus is focal to the discussion since it offers a coeval chronological fix point in the AD 40s for both remodelling and obtention of piped water. Given that the change in the domestic architecture observed was merely in its embryonic state in AD 79, the tenability to attribute a lower dating than that traditionnaly attributed not just to the private lines, but to the city’s distribution system of public aqueduct water as well, is reasoned. The particularities of Pompeii’s geomorphological situation and political status and how they impacted the discussed change in social relationships are also raised.

Practical drought risk assessment and management framework: A step toward sustainable modernization in agricultural water management

A proposed framework to assess and manage risks associated with Agricultural Water Off-farm Conveyance and Distribution Systems (AWOCDS), quantify potential failure due to drought-induced scenarios, and provide short to long-term recovery plans to mitigate drought impacts. It makes an intellectual contribution by creating a new proactive risk assessment focusing specifically on AWOCDS as a crucial part of agricultural water management. The risk assessment comprises two components − risk probability and consequence. The former is calculated by analyzing droughts via the streamflow drought index using the DrinC calculator. The latter is determined through AWOCDS’ performance evaluation using hydraulic simulation via HEC-RAS. Additionally, water distribution is assessed spatiotemporally using adequacy and equity indicators, and an integrated consequence is developed by applying the simple additive weighting method. AWOCDS’ rehabilitation and modernization projects worldwide include three practical practices in its risk management component. These practices involve modifying standard operating procedures (SOPs) by updating maintenance, upgrading manual-based operations, and developing a centralized Model Predictive Controller (MPC) for AWOCDS automatic operation. The proposed framework underwent testing in an arid region. Based on the risk assessment results, the AWOCDS operating system failure rate ranges from 70% to 96% during extreme-severe drought scenarios and 53% to 65% during moderate-mild drought scenarios. Risk management analysis shows that a short-term recovery plan reduces the drought risk by 4% monthly and 3% yearly. However, the risk of failure ranges from 50 to 94% in mild to extreme drought scenarios. Upgrading SOPs decreases impact by 4–11% in extreme, 4–7% in moderate-severe and 7–9% in mild-moderate drought. Automating the operating system with MPC reduces impact by 40–43% and 30–56% in mild-moderate and severe-extreme drought scenarios. This proactive-based strategy can help water managers plan for rehabilitation and improve surface water distribution reliability.

Legionella community dynamics in a drinking water distribution system: Impact of residual chlorine depletion

This study investigated the occurrence of Legionella spp. in a chlorinated drinking water distribution system (DWDS), focusing on their community compositions and association with physicochemical water quality. Water samples were collected throughout the DWDS, covering from the treated water reservoir to distal ends. Although Legionella spp. genes were not detected at the reservoir, their abundance dramatically increased along the distribution network, reaching up to 4.4 log copies/L at distal sites. The Legionella communities were further characterized by high-throughput amplicon sequencing targeting the genus-specific 16S rRNA gene. The results revealed a diverse Legionella community, including amplicon sequence variants with high similarity (> 99 %) to potentially pathogenic species such as L. drozanskii and L. pneumophila, albeit at low levels. Moreover, Legionella community diversity increased significantly along the distribution system, leading to distinct community compositions at distal sites. Importantly, decay of residual chlorine concentration was identified as a key factor both in increasing the Legionella gene levels and shaping the community structure. Overall, this study underscores the importance of preventing pipe corrosion and maintaining adequate disinfectant residuals to minimize Legionella regrowth in DWDS.

Development of a Machine-learning-based Framework to Assess the Performance of Water Distribution Systems

Recent statistics indicate that the national water supply coverage is approximately 99%, reflecting a high level of service. However, the aging infrastructure continues to cause issues such as pipe failures and water quality concerns, creating operational difficulties. To solve these issues, performance assessments are used to quantitatively evaluate the system conditions and ensure effective maintenance. In Korea, these assessments are based on a scoring system that combines direct and indirect assessments. However, direct assessment of all pipes is limited by cost and time constraints. To address this issue, a deep neural network is used to assess the aging of water distribution systems. This study develops a framework to estimate direct results from indirect data by analyzing the correlation between indirect and direct assessments. Additionally, data augmentation is considered to compensate for the lack of training data in direct assessments, improve the reliability of performance assessments, and support better prioritization in system maintenance.

The role of automated surface water distribution systems in energy-saving agriculture: A case study from central Iran’s Arid Plateau

Study regionThe NekooAbad Irrigation District in central Iran faces challenges due to inefficient surface water distribution. 82 million m3 of groundwater is extracted annually from 15,000 tube-wells, leading to decreased groundwater levels and increased energy consumption of 234 million kWh per year. Study focusThis study explores implementing automation in surface water distribution to reduce groundwater extraction and conserve energy. A hydraulic simulation model and a centralized Model Predictive Control approach were used to analyze the existing system and propose a recovery plan. The potential impact of automated surface water distribution on reducing groundwater extraction and energy conservation was evaluated through spatial assessment in GIS. New hydrological insights for the regionThe results demonstrate that the introduction of automation can significantly improve surface water distribution and, accordingly, groundwater overexploitation and, consequently, energy conservation, particularly during water scarcity. Energy conservation increased by 42.3 %, 54.8 %, 56.2 %, and 57.7 % under normal conditions, with water shortages of less than 10 %, 10–15 %, and 15–20 %, respectively. However, as the surface water shortages intensified, the energy conservation rates decreased to 57.7 %, 43.7 %, 25.4 %, and 18.9 % for normal conditions, water shortages of 15–20 %, 20–30 %, 30–40 %, and over 40 %, respectively. The automation introduction effectively provided reliable surface water resources, prompting farmers to shut down pumping stations or reduce working hours. Even in extreme scenarios, the project achieved up to 18.9 % energy savings.

Chlorine dosage management in drinking water systems: comparing Bayesian optimization to evolutionary algorithms

ABSTRACT To maintain a sufficient chlorine residual in water distribution systems (WDSs), chlorine dosage needs to be optimized. The majority of previous studies that aimed to optimize chlorine dosage in WDSs considered single-species water quality (WQ) models featuring chlorine decay with simple reaction kinetics. Recent efforts have proposed using multi-species water quality (MS-WQ) models to account for chlorine interactions with various chemical and microbiological species, thus providing a comprehensive and accurate evaluation of the WQ within WDSs. Nevertheless, the key challenge of implementing MS-WQ models within optimization frameworks is their high computational cost and poor scalability for larger WDSs. Furthermore, previous optimization studies generally relied on evolutionary algorithms (EAs), which require conducting a significant number of WQ simulations. Bayesian optimization (BO) has been recently suggested as an efficient alternative to EAs for the optimization of computationally expensive functions. This study aims to present a systematic comparison between BO and other widely used EAs for the optimization of MS-WQ in WDSs. A case study featuring a real-life, midsized benchmark WDS was implemented to comprehensively evaluate all three optimization techniques. The results revealed that BO is notably more computationally efficient and less sensitive to changes in the constraints than EAs.

Qualitative and Quantitative Analyses of Microplastics in Tap Water Supply Network in Iran

Background: Microplastics (MPs) exposure can affect humans in various ways, with tap water being one of the potential sources. Microplastics can absorb other pollutants and pose risks to both humans and the environment. Objectives: The aim of this study was to investigate the presence of MPs in tap water from the drinking water distribution system of Isfahan, Iran, and to determine the exposure to MPs from drinking tap water. Methods: Samples were collected from different points in the drinking water distribution system of Isfahan, Iran. Samples were prepared for analysis through filtration and chemical digestion. The MPs were counted using a scanning electron microscope (SEM), and the composition of MPs was analyzed using a micro-Raman spectrometer. Results: The concentration of MPs in tap water was found to be 287.0 ± 65.9 MPs/l. MPs ≤ 10 µm were the predominant sizes, and fibers were the predominant shape. Polyethylene terephthalate, polyethylene, and polypropylene were the most frequently identified MPs, respectively. Conclusions: Considering that the Iranian population consumes 7 - 15 liters of water daily for drinking and cooking, it is estimated that the average intake of MPs through cooking and drinking water is 2009 - 43,051 particles per day.

Water Security in the Context of the Piracicaba River Sub-Basin During the COVID-19 Pandemic

Objective: To analyze the challenges for water security in municipalities belonging to the Piracicaba River (SP) sub-basin, during the COVID-19 pandemic. Method: This is an exploratory and bibliographical research with a qualitative approach and case study and with a technical documentary procedure. The data sources were: Water Resources Situation Report; number of COVID-19 cases and deaths obtained from the Brazilian Ministry of Health website. In addition, a questionnaire on aspects related to water was administered to experts from the Technical Chamber for Conservation and Protection of Natural Resources of the Piracicaba, Capivari and Jundiaí River Basin Committees. Results and conclusions: The number of cases and deaths from the COVID-19 pandemic increased significantly in the 1st half of 2021 compared to the same period in 2020. The experts interviewed attributed high importance to prevention measures, the trend of decreasing water availability and the reduction of losses from water distribution systems. Research implications: The research presented theoretical reflections on the COVID-19 pandemic and water security. Water is an extremely important resource, especially in times of epidemics, as occurred with COVID-19. Water security affects the availability of water both to meet the needs of the population and to maintain ecosystems. Originality/value: The research carried out highlights the need for public policies regarding water and sanitation in order to achieve the protection of the population's health and sustainable development.

Energy-efficient and reliable coordinated scheduling for water distribution systems: enhancing hydraulic conditions and water quality

ABSTRACT Multi-objective operation optimization of water distribution systems (WDSs) in large metropolitan areas is essential; however, it is complex and time-consuming. Effective and reliable scheduling of WDSs can significantly enhance the efficiency and reliability of urban water resources management, which requires further research. This paper develops an optimization method combining genetic algorithm and multiple criteria analysis that coordinates energy conservation, hydraulic condition improvement, and water age optimization in WDSs. Results showed that the optimal scheduling method could achieve a 23.0, 16.7, and 2.5% decrease in energy consumption, and water supply volume with unsatisfied pressure, and average water age, respectively. To achieve optimal results, this study indicated that it is crucial to properly allocate water supply volume and pressure across multiple drinking water treatment plants. This finding provides important guidance for water utilities in scheduling. Furthermore, the emergency scenario analysis shows that the newly proposed method can significantly enhance the social and economic sustainability of WDSs through the coordinated optimization of energy consumption, hydraulic conditions, and water age.

Towards more realistic stochastic modelling of leakage in water distribution systems

ABSTRACT A new stochastic model is developed to predict leak types and sizes in water distribution systems. By linking records of actual failures in water networks with new tools for stochastic modelling, the study provides more accurate estimates of network leakage behaviour. District metered areas (DMAs) have been adopted internationally as best practice for monitoring and controlling leakage, with the infrastructure leakage index (ILI) as the main performance indicator. The leakage exponent (N1), which quantifies the relationship between leakage rate and pressure, is a key parameter in describing DMA leakage behaviour. After analysing thousands of stochastic networks for different combinations of pipe material and ILI, the study found that different pipe materials have distinct leakage exponent distributions. Iron and asbestos cement (AC) pipes display N1 values close to 0.5, polyvinyl chloride (PVC) pipes have the highest N1 values, and polyethylene (PE) lies between PVC and iron/AC. The study further showed that current guidelines linking ILI to N1 for different pipe materials depart substantially from the observed results, indicating that these guidelines may need to be updated. The study provides a tool for more realistic modelling of leakage that offers valuable insights into the behaviour of leakage in different pipe materials.

Smart Building Digital Twin for Interior Water Distribution System Management

Abstract. A smart campus integrates the Internet of Things, artificial intelligence, and real-time sensor data to optimize campus functions and create a context-aware decision-support platform for effective campus management. A crucial aspect of a smart campus is the water distribution system, which faces several challenges due to bursts, leaks, and water quality issues. This study uses Digital Twin technology to address these challenges through real-time monitoring, detection, and management of campus water distribution networks. A building-level digital twin is developed for the interior water networks of the Daphne Cockwell Complex at Toronto Metropolitan University. The major components include a 3D network model capable of analysis and simulations, a smart water management system, and real-time visualization. A 3D static model of the interior water utility network is created using the Industrial Foundation Class data. The semantic and topological models based on graph models are developed for network analysis. The models are integrated into the ESRI ArcGIS Pro to facilitate BIM-GIS integration. A dynamic model is created by incorporating automatic meter readings based on IoT. Combined with the 3D model of the utility network, the digital twin monitors and visualizes building water consumption, facilitating anomaly detection and real-time maintenance by the facilities management department. This study provides practical guidance for managing water distribution systems in university buildings, with potential applications in other complex environments. Future work aims to develop a system for detecting complex event processes by integrating different utilities.

Water Leak Detection: A Comprehensive Review of Methods, Challenges, and Future Directions

This paper provides a comprehensive review of the methods and techniques developed for detecting leaks in water distribution systems, with a focus on highlighting their strengths, weaknesses, and areas for future research. Given the substantial economic, social, and environmental impacts of undetected leaks, timely detection and precise location of leaks are critical concerns for water authorities. This review categorizes existing methods into traditional approaches, such as manual sounding, and modern techniques involving smart water management and sensor technologies. A multidimensional bibliometric analysis was employed to systematically identify, select, and evaluate 600 scholarly articles on water leak detection, sourced from the Scopus database over a 23-year period (2000–2023). The paper evaluates each method based on leak sensitivity, burst detection, continuous monitoring, alarm accuracy, and implementation costs. Novel insights include an analysis of emerging smart water technologies and their integration into real-world water distribution networks, offering improved efficiency in leak detection. The paper also identifies key gaps in current research and suggests future directions for advancing the accuracy and cost-effectiveness of these technologies.

Insights into water insecurity in Indigenous communities in Canada: assessing microbial risks and innovative solutions, a multifaceted review.

Canada is considered a freshwater-rich country, despite this, several Indigenous reserves struggle with household water insecurity. In fact, some of these communities have lacked access to safe water for almost 30 years. Water quality in Canadian Indigenous reserves is influenced by several factors including source water quality, drinking water treatments applied, water distribution systems, and water storage tanks when piped water is unavailable. The objective of this multifaceted review is to spot the challenges and consequences of inadequate drinking water systems (DWS) and the available technical and microbiological alternatives to address water sanitation coverage in Indigenous reserves of Canada, North America (also known as Turtle Island). A comprehensive literature review was conducted using national web portals from both federal and provincial governments, as well as academic databases to identify the following topics: The status of water insecurity in Indigenous communities across Canada; Microbiological, chemical, and natural causes contributing to water insecurity; Limitations of applying urban-style drinking water systems in Indigenous reserves in Canada and the management of DWS for Indigenous communities in other high-income countries; and the importance of determining the microbiome inhabiting drinking water systems along with the cutting-edge technology available for its analysis. A total of 169 scientific articles matched the inclusion criteria. The major themes discussed include: The status of water insecurity and water advisories in Canada; the risks of pathogenic microorganisms (i.e., Escherichia coli and total coliforms) and other chemicals (i.e., disinfection by-products) found in water storage tanks; the most common technologies available for water treatment including coagulation, high- and low-pressure membrane filtration procedures, ozone, ion exchange, and biological ion exchange and their limitations when applying them in remote Indigenous communities. Furthermore, we reviewed the benefits and drawbacks that high throughput tools such as metagenomics (the study of genomes of microbial communities), culturomics (a high-efficiency culture approach), and microfluidics devices (microminiaturized instruments) and what they could represent for water monitoring in Indigenous reserves. This multifaceted review demonstrates that water insecurity in Canada is a reflection of the institutional structures of marginalization that persist in the country and other parts of Turtle Island. DWS on Indigenous reserves are in urgent need of upgrades. Source water protection, and drinking water monitoring plus a comprehensive design of culturally adapted, and sustainable water services are required. Collaborative efforts between First Nations authorities and federal, provincial, and territorial governments are imperative to ensure equitable access to safe drinking water in Indigenous reserves.

GraphSmart: a method for green and accurate IoT water monitoring

Water scarcity is nowadays a critical global concern and an efficient management of water resources is paramount. This paper presents an original approach for monitoring Water Distribution Systems (WDSs) through Internet of Things (IoT) that involves the integration of multiple sensors placed across the distribution network to accurately measure water flow. To enhance energy efficiency for green monitoring and communication process, we harness the power of graph theory and graph signal processing to represent in a tunable and accurate way the water flow and simultaneously minimize the number of IoT sensors communicating those measurements. We propose a graph model where water flow is represented as signal on graph and we introduce an algorithm, named GraphSmart, designed to reconstruct the graph signal when certain measurements are unknown or missing. Our framework is applied on synthetic realistic environment within the context of LoRaWAN (Long Range Wide Area Network), an infrastructure and protocol designed for ultra-low-power IoT devices. Our findings show that GraphSmart significantly reduces energy consumption while ensuring precise flow estimation. Our research demonstrates high potential for energy-efficient and accurate water flow monitoring, paving the way to improve the management of WDSs and enabling water operators to address water scarcity challenges.

Impacts of Missing Data Imputation on Resilience Evaluation for Water Distribution System

Impacts of Missing Data Imputation on Resilience Evaluation for Water Distribution System

Effect of Pipe Materials and Interspecific Interactions on Biofilm Formation and Chlorine Resistance: Turn Enemies into Friends

Drinking water distribution systems (DWDSs) may be contaminated to various degrees when different microorganisms attach to the pipe walls. Understanding the characteristics of biofilms on pipe walls can help prevent and control microbial contamination in DWDSs. The biofilm formation, interspecific interactions, and chlorine resistance of 10 dual-species biofilms in polyethylene (PE) and cast iron (CI) pipes were investigated in this paper. The biofilm biomass (heterotrophic bacterial plate count and crystal violet) of dual species in CI pipes is significantly higher than that in PE pipes, but the biofilm activity in CI pipes is significantly lower than that in PE pipes. The interspecific interaction of Sphingomonas-containing group presented synergistic or neutral relationship in PE pipes, whereas the interspecific interaction of the Acidovorax-containing group showed a competitive relationship in CI pipes. Although interspecific relationships may help bacteria resist chlorine, the chlorine resistance was more reliant on dual-species groups and pipe materials. In CI pipes, the Microbacterium containing biofilm groups showed better chlorine resistance, whereas in PE pipes, most biofilm groups with Bacillus exhibited better chlorine resistance. The biofilm groups with more extracellular polymeric substance (EPS) secretion showed stronger chlorine resistance. The biofilm in the PE pipe is mainly protected by EPS, while both EPS and corrosion products shield the biofilms within CI pipe. These results supported that dual-species biofilms are affected by pipe materials and interspecific interactions and provided some ideas for microbial control in two typical pipe materials.

Control valve simulation method integrable into the global gradient algorithm

ABSTRACT This paper presents a refinement of a method that simulates flow- and pressure-regulating valves by replacing them with pipes and adjusting the resistances (diameters) of those pipes to meet the valve settings. The method, referred to as the replacing pipe method (RPM), is readily integrable into the global gradient algorithm, which is the heart of the commonly used EPANET 2 water distribution system modeling software. The RPM proved to be more robust, yet slower than the EPANET 2 valve handling heuristics. In this work, the RPM was modified to increase its computational speed. The modification involved the RPM check valve handling algorithm and condition for updating the diameters of the valve-replacing pipes. The modified RPM was tested as part of a hybrid simulator, which switches from the EPANET 2 valve handling heuristics to the RPM when the former fails. The test networks included a large network with thousands of nodes, pipes, and valves, and a case of an ill-posed problem. As the testing showed, the modified RPM offers a significant reduction in the number of iterations compared to its previous version.

Graph convolutional network for water network partitioning

The partitioning of a water distribution network into several district-metered areas (DMAs) yields is of great benefits for the management of water distribution systems, including enhanced leak control, pollution monitoring, and pressure optimization. However, achieving an effective partitioning that simultaneously incorporates node characteristics and network connections is challenging. Previous studies have tackled water network partitioning by focusing on either node features or pipe connections individually. In response to the limitations of current approaches for water distribution network partitioning, this study introduces an innovative unsupervised clustering approach for node partitioning based on graph convolutional network (GCN) techniques. Initially, the network nodes are clustered using the Cross-Attention Fusion Based Enhanced Graph Convolutional Network (CaEGCN) deep clustering algorithm, considering both the network’s topological layout and hydraulic properties. The resulting clusters categorize the network nodes into distinct regions. We evaluate our approach and other methods through a real world water distribution network using five different metrics commonly used to evaluate applied in assessing water supply network zoning issues. By comparing and analyzing the performance of experiments with other schemes, the experimental results demonstrate that the CaEGCN deep clustering method featured a remarkable performance. The proposed method showcases its potential for practical application by offering a dependable and easily interpretable water network partitioning solution.

A Global Resilience Analysis-Based Benchmark Framework for Comparing Reliability Surrogate Measures of Water Distribution Systems

Various reliability surrogate measures have emerged over the last three decades to design water distribution systems. However, existing comparative studies cannot assess surrogate measures from the resilience perspective considering the dynamic absorption–recovery process imposed by pipe failures. In this work, we propose a novel benchmark framework based on the global resilience analysis to examine surrogate measures’ performance. Surrogate measures were compared via the stress–strain curve derived from the global resilience analysis under extended period simulation. In particular, we identify the comparable stress range to articulate the differences among surrogate measures and significantly reduce the computational burden. Then, we develop the normalized resilience score (NRS) to evaluate the quality of solutions to network design. Five well-known measures are compared for the multiobjective design of two benchmark networks. Results show that the Network Resilience Index achieves 2.5% to 10.1% better NRSs than the mean NRSs over five surrogate measures, implying that both nodal surplus energy and pipe diameter uniformity greatly impact the network system’s resilience. The uniformity of pipe diameters is more significant than the uniformity of flow rate. Our findings contribute to the design of new and better surrogate measures for network resilience evaluation.