Water Distribution Systems Research Articles

Optimal Design of Water Distribution System Using Improved Life Cycle Energy Analysis: Development of Optimal Improvement Period and Unit Energy Formula

Water distribution systems (WDSs) are crucial for providing clean drinking water, requiring an efficient design to minimize costs and energy usage. This study introduces an enhanced life cycle energy analysis (LCEA) model for an optimal WDS design, incorporating novel criteria for pipe maintenance and a new resilience index based on nodal pressure. The improved LCEA model features a revised unit energy formula and sets standards for pipe rehabilitation and replacement based on regional regulations. Applied to South Korea’s Goyang network, the model reduces energy expenditure by approximately 35% compared to the cost-based design. Unlike the cost-based design, the energy-based design achieves results that can relatively reduce energy when designing water distribution networks by considering recovered energy. This allows designers to propose designs that consume relatively less energy. Analysis using the new resilience index shows that the energy-based design outperforms the cost-based design in terms of pressure and service under most pipe failure scenarios. The implementation of the improved LCEA in real-world pipe networks, including Goyang, promises a practical life cycle-based optimal design.

Leveraging Urban Water Distribution Systems with Smart Sensors for Sustainable Cities

Optimizing urban water distribution systems is essential for reducing economic losses, minimizing water wastage, and addressing resource access gaps, particularly in drought-prone regions impacted by climate change. We apply advanced artificial intelligence (AI) techniques and the Internet of Things (IoT) to optimize water networks in Spain using simulation. By employing EPANET for hydraulic modeling and a linear regression-based algorithm for optimization, we achieved up to 96.62% system efficiency with a mean absolute error of 0.049. Our approach demonstrates the potential to conserve up to 648,000 L of water daily at high-demand nodes, contributing to substantial resource savings across urban water networks. We propose a global architecture utilizing Low Power Wide Area Network and Low Earth Orbit solutions for widespread deployment. This study underscores the potential of AI in water network optimization and suggests future research avenues for implementing the proposed architecture in real urban water systems.

Analysis of Variability of Water Quality Indicators in the Municipality Water Supply System—A Case Study

This study investigated the variability of water quality indicators in four municipal water distribution systems near a medium-sized city. Despite the proximity of water intakes, water quality in different distribution systems can vary significantly due to local factors such as infrastructure conditions, treatment technology, and specific environmental conditions affecting water in each water supply network. Water samples were collected from multiple points in each system and analyzed for physicochemical properties. The results showed significant differences in total carbon, dissolved organic carbon, and ammonium nitrogen, indicating variability in water quality between systems. These results emphasize the need for integrated management strategies, innovative technologies, and real-time monitoring to maintain water quality. The study also highlights challenges such as aging infrastructure, pollution, and financial constraints in managing water supplies.

An integrated approach to evaluating water contaminants and evaporation in agricultural water distribution systems

This study presents an innovative approach for assessing water quality in agricultural irrigation networks, integrating stable isotope analysis, in vivo zebrafish screening, and comprehensive chemical profiling to investigate the occurrence, transformation, and potential toxicity of organic contaminants. Stable isotope analysis was used to measure evaporation as a proxy for water residence time in the canal, while liquid chromatography-high resolution mass spectrometry (LC-HRMS) identified a range of organic compounds in water samples collected from both the irrigation canal and its source river. Results indicated a reduction in contaminant levels in the canal compared to the river, with the most significant evaporation and concentration changes occurring at a holding reservoir, suggesting that managing residence time could help reduce water loss in arid irrigation networks. The data also highlighted how evaporation, particularly during the dry, hot season, influences contaminant dynamics. Hierarchical clustering of LC-HRMS results showed notable differences between the chemical profiles of canal and river samples, indicating that irrigation systems may contribute to the degradation or removal of certain compounds. Over 60 % of detected compounds were naturally derived, with anthropogenic contaminants like pesticides and personal care products further highlighting human impacts. Priority contaminants, including DEET and 2-naphthalene sulfonic acid, likely originated from urban activities upstream. Initial screening using zebrafish embryos showed bioactivity across sites, confirming the presence of contaminants needing further examination. Correlation analysis linked natural compounds to evaporation rates, suggesting that flora and fauna play significant roles in the chemical makeup of canal water. Overall, this approach provides a comprehensive framework for monitoring irrigation water, offering insights into contaminant behavior and supporting the development of standardized methods for assessing chemical fate and ecological risks in agricultural irrigation systems.

Long Duration Forecasting and its Performance Capability for Seasonal Variation Modelling of Residual Chlorine Concentrations: A Comparative Evaluation of two Small-scale Water Distribution Systems in Japan

Chlorine dosing control is a critical task for health security, complying with drinking water quality standards while achieving customer satisfaction. In Japan, this became more difficult due to decreasing number of technical personnel as a result of declining population and huge retirement of veterans. As experienced-based dosing control still exists and is considered inefficient due to risks of inaccurate dosing and need of experienced manpower, streamlining of operations is needed. This study aims to address these concerns through the development and evaluation of a deep learning model for residual chlorine concentrations capable of forecasting long durations. In this paper, the model is investigated in seasonal timeframe analyzing trends and variations. Two water distributions systems of varying network—simple and complex, are also compared to further analyze model performance and versatility. The model utilizes the past 24 hours of flow rate, chlorine level at treatment plant, water temperature, and residual chlorine at private homes as input to predict the 12 hours ahead of residual chlorine at private homes evaluated at hourly training lengths of 0.5, 1, 1.5, 2 years. Results revealed that the model achieved high accuracy in predicting hourly residual chlorine with general increasing model error from winter, spring, autumn, and summer due to the progressing instabilities in chlorine concentrations from low to high temperatures. Moreover, smaller system tends to be more unstable incurring lower model performance relative to larger system. In terms of optimal training length, ≥1Y training models are found to have lesser chance of data drift occurrence prospectively reducing model retraining frequency in the future.

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.

A survey on massive IoT for water distribution systems: Challenges, simulation tools, and guidelines for large-scale deployment

A survey on massive IoT for water distribution systems: Challenges, simulation tools, and guidelines for large-scale deployment

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.

Water Volume and 3D Topographic Analysis of Hub Dam, Karachi, Using Remote Sensing and Global Bathymetry Data

Background: Karachi one of the largest and fastest-growing cities in the world, the city faces severe water scarcity and aggravated by climate change, excessive groundwater extraction in dense urban areas and inefficient water distribution systems. The Hub Dam, along with the Keenjhar Lake, is the source of water for Karachi's population as well as for the industrial and urban agricultural sectors. It is therefore important to have current information on the dam's storage capacity, its topographic features and the hydrological dynamics of its catchment area, which remains poorly understood to date. Objectives: This study's primary objectives are (1) to assess the hydrography of Hub Dam using global bathymetric and remote sensing data and (2) to create a detailed 3D model of the dam to facilitate analysis of its hydrological features. (3) Also generate data-driven insights to guide improvements in Karachi’s urban water management policies. Methods: The methodology integrates global bathymetric data with remote sensing and Google Earth Engine (GEE) for analysing Hub Dam’s hydrological and topographic characteristics. Data processing and visualization were conducted in Google Colab by python codes. This process enabling an efficient workflow for handling and analysing large datasets. Results: Hub Dam 3D model is developed. The approaches is enhancing visualization of the dam's water volume and terrain features to support detailed hydrological analysis. 3D volumetric analysis estimates with total water volume at approximately 79.954 · 106 m3. It was found that currently, the Hub Dam reservoir has enough water to fulfil Karachi needs for 503 days, a critical reserve for urban planning, resource management. Using a topographic analysis that includes surrounding slopes and watershed features, key elements affecting dam performance were identified. This result helps to adjust the filling of the dam with water. The Hub Dam's ability to store water was confirmed through a preliminary volume assessment. Conclusion: The study successfully achieved its objectives. The results obtained highlight the importance of adaptive well informed strategies for sustaining well managed water resources in response to environmental pressures. The current study further advance rational water management by integrating remote sensing and data-driven methodologies into this area of knowledge. That is, the effectiveness of Using Remote Sensing and Global Bathymetry Data has been repeatedly proven by other studies in different areas of knowledge. However, in the current study, this scientific approach has successfully demonstrated the efficient and rapid acquisition of accurate, up-to-date information on reservoir capacity and hydrological characteristics, which opens up new opportunities for efficient water management.

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.