Water Supply Network Research Articles

Water Supply Pipeline Failure Evaluation Model Based on Particle Swarm Optimization Neural Network

The degradation and failure of the urban water supply network may lead to serious safety hazards, including pipe breaks, water supply interruptions, water resource losses, and contaminant intrusions. The risk evaluation of water supply pipeline failure in a distribution network is a challenging task, because most of the available data cannot fully reflect pipeline failure events and many of the mechanisms still cannot be fully understood. Therefore, a predictive model is urgently needed to assess pipeline failure risk based on available data. In this paper, based on the traditional risk assessment theory, seven main factors affecting pipeline failure are selected and scored, and then a pipeline failure model is established by using the particle swarm optimization (PSO) neural network. The model uses the neural network training of historical data to evaluate the failure of the water supply pipeline, and the PSO is used to optimize the neural network to effectively improve the training time and accuracy. The model error and correlation coefficient are 0.003 and 0.987, respectively. The proposed model can be used as a powerful support tool to assist infrastructure managers and pipeline maintainers in their plans and decision-making.

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.

Application of Hydrochemical Parameters as Tool for Sustainable Management of Water Supply Network

Effective management of Water Supply Systems (WSSs) is crucial for ensuring safe drinking water. The WSS of Varaždin County is a complex network involving three groundwater sources: Bartolovec and Vinokovščak wellfields (alluvial aquifers) and Bela karstic spring. To achieve a comprehensive characterization of WSSs, routine laboratory data was integrated with stable isotopes and geochemical modeling. Within this study, all measured parameters remain below the Maximum Contaminant Level (MCL), ensuring water safety for human consumption. The Piper diagram identified variations in water sources based on their chemical composition, providing a simplified overview of mixing patterns within WSSs. Among the modeling approaches, inverse modeling (IM) was found to be more reliable than forward modeling (FM) and mass balance modeling (BM). Despite the limited capacity of δ18O to provide accurate mixing results, it was revealed that the reservoir water was in equilibrium with the air (no evaporation effects), indicating well-sealed reservoirs. Mixing modeling showed that the western, southwestern, and northern parts of the WSS mixed all three sources, whereas the eastern and southeastern areas primarily relied on the deeper aquifer of the Bartolovec source, indicating potential vulnerability. Strict validation criteria ensured the reliability of results, demonstrating the effectiveness and applicability of geochemical modeling in water security management plans.

RAINWATER HARVESTING AND LEAKAGE REDUCTION AS ALTERNATIVES TO OPTIMISE FRESHWATER MANAGEMENT

The need of water is a reality for human life. Due to climate change, rainfall patterns are being altered and there is a growing conscience of the need for water collection in society. Any additional water could help to mitigate daily needs and therefore, this study has determined the water provision that could be determined for each population based on rainwater collection "in situ". It has been estimated in several cities in Spain, which are representative of the peninsular and island climatology, according to the respective roof surface and annual precipitation. On the other hand, it is well known that water supply networks have leaks. The International Water Association (IWA) defined a series of indicative parameters, including the IFE/ILI parameter, which has been incorporated into Spanish regulations, specifically in RD 3/2023 of 10 January. Consequently, this study has also determined the aforementioned parameter for the same cities. It has also been calculated what the improvement in water savings could mean by applying corrective measures and sustained plans for repairing leaks and optimising pressures.

Mitigating aging infrastructure risks: An optimized epoxy resin system for water supply pipeline rehabilitation

Urban water supply networks are crucial for ensuring the delivery of safe drinking water to urban populations; however, the aging infrastructure in these systems has led to a rising incidence of leaks and frequent pipeline failures, posing serious risks. Traditional repair approaches encounter limitations in terms of efficiency, durability, and environmental safety, particularly when employed in potable water pipelines. To address these challenges, we developed a novel multi-component amine-cured epoxy resin system specifically optimized for in-situ curing under ambient conditions. This study comprehensively examines the mechanical properties, water absorption behavior, and curing kinetics of this resin system, formulated to reduce volatile organic compound emissions while enhancing durability under prolonged water exposure. Experimental findings demonstrate that the E2 formulation exhibited superior tensile strength, flexural properties, and fracture toughness relative to other formulations, with a two-stage water absorption model accurately predicting resin behavior in moisture-laden environments. Moreover, finite element modeling and laboratory testing confirmed the influence of bubble defects on mechanical performance, and a negative pressure defoaming technique effectively reduced defect volume, resulting in a 17.6% improvement in tensile strength. Collectively, this research advances the practical application of rapid-curing resins, offering a resilient, safe, and sustainable solution for the rehabilitation of aging water pipeline networks.

Comparative Analysis of Using Water Quality in Urban Areas of Duhok City, Iraq

Water is sourced from various locations, including lakes, wells, artificial reservoirs, and rivers. Contamination of these sources poses a significant threat to human health, highlighting the need to monitor water quality. This study focuses on evaluating the water quality in the Duhok governorate of the Kurdistan region, Iraq, by analyzing several key physicochemical parameters: turbidity, pH, total dissolved solids (TDS), electrical conductivity (EC), total alkalinity (TAL), total hardness (TH), calcium (Ca²⁺), magnesium (Mg²⁺), chloride (Cl⁻), sulfate (SO₄²⁻), nitrate (NO₃⁻), sodium (Na⁺), and potassium (K⁺). Over a period spanning from January 2019 to December 2021, a total of 1,374 water samples were collected from different sources, including reservoirs, deep wells, springs, the Duhok dam, and the water supply network within the Duhok governorate. The analysis revealed that parameters such as turbidity, pH, TH, Ca²⁺, Mg²⁺, SO₄²⁻, NO₃⁻, and Na⁺ varied significantly across the three years studied. In contrast, other parameters like TDS, EC, TAL, Cl⁻, and K⁺ showed no significant fluctuations. The results also indicated a decrease in most physicochemical parameter values in 2021 compared to 2019 and 2020, with the exception of turbidity. Overall, the majority of water samples were found to be within safe drinking limits. Ongoing monitoring of these water sources is essential to detect any variations in water quality promptly.

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.

Assessing Irrigation Efficiency Improvements in Paddy Fields Using Granular SWMM Simulations

As water scarcity intensifies due to climate change, improving the efficiency of agricultural water use has become increasingly critical. Current irrigation systems often experience significant water losses, especially in paddy fields in South Korea that largely rely on open-channel water supply networks. However, previous studies have simulated irrigation improvement strategies by aggregating multiple paddy fields into larger unites rather than modeling them individually, which limits the accurate representation of field conditions. To address this limitation, we applied a granular simulation approach, collecting detailed input data through field surveys. Using this granular model, the study evaluated strategies to enhance irrigation efficiency in paddy fields serviced by the Baekma Agricultural Reservoir in South Korea. We assessed four scenarios: the current open-channel system, conversion of open channels to closed conduits, installation of farm ponds, and a combination of closed conduits and farm ponds. These scenarios were simulated using the Strom Water Management Model (SWMM), meticulously configured to represent individual paddy fields and channel networks. The results show that converting open channels to closed conduits increased irrigation efficiency by 5.4% compared to the current open-channel system. Combining closed conduits with farm ponds achieved the highest efficiency, although the independent effect of farm ponds was minimal. These findings suggested that converting open-channels to closed conduits was a highly effective solution for reducing water losses, while farm ponds played a limited role. This study provides valuable insights into the development of precise irrigation strategies, offering a detailed assessment of real-world conditions in paddy fields.

Pipeline Leak Identification and Prediction of Urban Water Supply Network System with Deep Learning Artificial Neural Network

Pipeline leakage, which leads to water wastage, financial losses, and contamination, is a significant challenge in urban water supply networks. Leak detection and prediction is urgent to secure the safety of the water supply system. Relaying on deep learning artificial neural networks and a specific optimization algorithm, an intelligential detection approach in identifying the pipeline leaks is proposed. A hydraulic model is initially constructed on the simplified Net2 benchmark pipe network. The District Metering Area (DMA) algorithm and the Cuckoo Search (CS) algorithm are integrated as the DMA-CS algorithm, which is employed for the hydraulic model optimization. Attributing to the suspected leak area identification and the exact leak location, the DMA-CS algorithm possess higher accuracy for pipeline leakage (97.43%) than that of the DMA algorithm (92.67%). The identification pattern of leakage nodes is correlated to the maximum number of leakage points set with the participation of the DMA-CS algorithm, which provide a more accurate pathway for identifying and predicting the specific pipeline leaks.

Correlation of Water and Energy Parameters in a South of Minas Gerais Water Supply System

Objective: The objective of this study is to investigate the correlation between water and energy parameters in order to obtain water and energy consumption, according to studies by a local water utility. Theoretical Framework: The main theories presented here are the water and energy balances of a water supply network, whose authors can be found throughout the work. Such concepts are fundamental, as they allow correlating the parameters that are the objective of the study. Method: The methodology adopted for this research comprises a literature review to obtain the necessary theoretical basis, as well as data collection carried out through campaigns by the research group throughout its trajectory, in previous works. The processing of the collected data was carried out using water and energy balances, with the consequent correlation of such parameters in relation to water losses in the sector under study. Results and Discussion: The results obtained revealed that losses can reach up to R$249,949.06 in 5 years in the sector under study, reconciling water and energy losses due to the inefficiency of the system under study. Research Implications: This research, due to its approach, can guide measures to increase water and energy efficiency in sanitation companies, resulting in important financial and environmental gains for society by reducing water and energy waste and reducing operating costs, with resulting financial relief for society. Originality/Value: This study contributes to the literature by correlating water and energy parameters in the study of water distribution losses, having revealed the monetary values ​​of the losses and their impacts on society.

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.

Prototyping of vibration-sensing-actuation device which is contained high-power electrodynamic speaker for diagnosis of actual water main network

Water leakage and bursting due to deterioration of water distribution mains lead to water outages and economic losses. To prevent the accidents, we are conducting research to develop measurements and diagnostic methods for buried water mains. In this study, we focused on the shift in eigenfrequencies of in-plane bending vibration of rings because of deterioration. Therefore, we are developing the vibration-sensing-actuation device which detects the frequency changes of in-plane bending mode. The water distribution network is mainly composed from cast iron pipe. Moreover, the attached facilities for example fire hydrant and water valve are contained. Since attached facilities are fabricated from cast iron component, actual water main network is heavy facilities which have high rigidity. In order to excite the desired in-plane bending mode in heavy components, the proposed sensing-actuation device requires the high-power actuator. In this study, we introduce the high-power electromagnetic actuator more than 100W output into the proposed device. Furthermore, the fundamental operational tests were conducted under the various input signals in the laboratory situations. In addition, the field operation confirmation was performed in an actual water main network.

Analysis of water losses in seven small and medium-sized water distribution networks in the south region of Cameroon (Central Africa)

ABSTRACT This paper analyzes and evaluates water losses in seven small and medium-sized water supply networks (WSNs) in the south region of Cameroon in order to contribute to improving the most effective approaches to reducing water losses in Sub-Saharan Africa's WSNs. Data were obtained from the regional delegation of the Camwater in the south region of Cameroon and analyzed using a variety of indices, including the failure intensity index, the unit coefficient of water loss per kilometer, the real leakage balance index, the non-revenue water basic, and the infrastructure leakage index. Results indicate that all the WSNs analyzed achieved mixed results compared with national data and very weak results compared with international standards. This is partly due to outdated infrastructure, rapid urbanization and urban population expansion, poor operation and maintenance policies, inadequate technical skills and technology, a lack of financial discipline, and political, cultural, and social influences. The results place the cumulative volume of water losses in the seven networks studied during the 5 years at 7.3 million cubic meters, which costs the water utility about 2.4 billion FCFA (or 4.4 million USD).

Investigation of an annular photonic crystal sensor for real-time monitoring of calcium carbonate scales in water distribution systems

This research exhibits a new configuration of photonic crystals known as annular photonic crystals (APCs) for real-time detection of calcium carbonate (CaCO3) scale in the water pipeline. The proposed sensor features a circular arrangement of porous silicon materials with varying levels of porosity. A central defect layer is incorporated into the design to capture the target analyte, allowing it to detect changes in the refractive index caused by scale formation. To analyze the reflectance spectrum of this structure, a modified transfer matrix method is utilized. An extensive optimization process is conducted based on the characteristics of the defect mode, focusing on various geometric parameters, including layer thickness, porosity levels, core circle radius, and structural periodicity, to achieve optimal sensor performance. The simulation outcomes revealed that at the optimized structure parameters, the sensor offers a remarkable QF, sensitivity, and FoM of 1215, 176.85 nm/RIU, and 350.5 1/RIU, respectively. Moreover, the proposed structure is simple, cost-effective, and compact, which makes it an ideal candidate for the detection of calcium carbonate scales formed in pipes and devices in water supply networks.

Optimization Analysis of Water Supply Mode for Fire Protection System of Super High Rise Building

Abstract In order to improve the applicability and reliability of the fire water supply capacity of super high-rise buildings, the fluid analysis software Flomaster was used for simulation. Through the existing pumps, valves, pipelines, pressure reducing valves and newly developed fire hydrants and other components, the fire water supply system of super high-rise buildings is modeled. The pressure distribution of the system pipe network under a given fire water supply mode is studied. The research shows that the simulation can analyze whether there is excessive pressure in the fire hydrant system under different flow conditions in the actual fire extinguishing process. This paper simulates the actual fire extinguishing process of the fire hydrant system through a specific engineering case. The pressure distribution and flow distribution under different flow conditions are obtained. The excessive pressure position of the fire pipe network system under the given fire pump model is obtained. It provides a method for guiding the selection of fire pump and the design of fire hydrant system pipe network. It has certain guiding significance for the subsequent optimization of the design scheme of the fire water supply network and the prediction of the performance of the R&D equipment.

Water Demand Forecasting in Multiple District Metered Areas Based on a Multi-Scale Correction Module Neural Network Architecture

Short-term water demand forecasting (STWDF) for multiple spatially and temporally correlated District Metering Areas (DMAs) is an essential foundation for achieving more refined management of urban water supply networks. However, due to the greater uncertainty associated with specific DMA demand compared to overall water usage, accurately predicting STWDF poses significant challenges. This study introduces an innovative network architecture—the multi-scale correction module neural network, built upon Long Short-Term Memory (LSTM) networks and Convolutional Neural Networks (CNN) enhanced with Attention mechanisms—for simultaneous STWDF with a temporal resolution of one hour over a week for 10 DMAs located in a single city in northern Italy. This framework utilizes multivariate corrections to refine and enhance the output accuracy. The results reveal that, in comparison to traditional Gated Recurrent Unit or LSTM models, the proposed model with integrated correction modules, particularly those that leverage inter-DMA correlations, improves performance across all evaluation metrics by an average of 5%-20% per DMA. Additionally, it consistently delivers superior accuracy across three scenarios: single DMA forecasting, total water demand, and extreme conditions, while maintaining stable performance throughout. Furthermore, the interpretability analysis underscores the feasibility of this innovative structure and highlights the contribution of meteorological features to the predictive model in some DMA-level STWDF. The unified input-output framework elegantly simplifies the STWDF process across multiple DMAs, providing new insights and methodologies for future research in this domain.

МЕТОДИ І ПРАКТИКИ ВПРОВАДЖЕННЯ ТА ЗАСТОСУВАННЯ РІЗНИХ ТИПІВ ШТУЧНОГО ІНТЕЛЕКТУ І НАУКИ ПРО ДАНІ ДЛЯ РІШЕННЯ ПРОБЛЕМ У ВОДНІЙ ІНФРАСТРУКТУРІ

The subject of the study in this article was the practice of implementing and applying various types of artificial intelligence and data science to detect leaks from water supply networks, to monitor freshwater conditions and to detect pollution, clean freshwater bodies from waste from industrial and mining enterprises, control freshwater flow and develop more efficient water filtration methods. The article identifies the advantages and disadvantages of the practice of introducing and applying various types of artificial intelligence and data science technologies to automate traditional methods of monitoring, control and related work in the water industry. The article addresses the following objectives: to substantiate the effectiveness of implementation of various types of artificial intelligence technologies and data science methods and their practical application with software and hardware technologies to automate traditional methods of performing work in the water industry. To solve the tasks set, the methodology used was based on general scientific and special research methods, such as theoretical methods (analysis, explanation, generalisation, comparison). The use of this approach allowed us to obtain the following results: the features that affect the accuracy of the analysis of collected data used by technologies of various types of artificial intelligence and data science methods were identified. Practices and methods for more efficient and accurate application of this technology are reflected. Scientific data are analysed. The study allowed identifying the practical opportunities and problems of this technology. Recommendations for the effective use of this technology have been developed. The factors that influence the effective use of this technology in industry are identified.

Groundwater in Katowice - center of a large urban and deep coal mining area in Poland

The paper presents the groundwater resources of Katowice and the results of studies conducted to identify prospective areas in aquifers with sufficient water resources for the location of public water intakes. The city of Katowice is the capital of Upper Silesia, the largest urban-industrial area in Poland, the region with a highly developed hard coal mining and many other different industries covering almost the entire scope of the economy. Due to long term drainage of mines causing the depletion and deterioration of groundwater and surface water resources, the main municipal water intakes have been located outside Katowice. Most of the pumped mine water is discharged into surface waters, causing significant salinity of water and disallow its use for municipal or industrial purposes in Katowice. The water collection and supply system is very extensive and covers a significant part of the Silesian agglomeration which is why Katowice is supplied with water from surface water intakes located outside the city. According to older published materials, such as the Hydrogeological map of Poland, there were no aquifers in the city that could have been used to supply the city with drinking water, however recent studies have shown that groundwater in the Quaternary aquifers in the western part of the city can be used to supply the city with public water. Less productive, Quaternary aquifers in north-eastern parts of the city may constitute the basis for drinking water supply in emergency situations, when surface intakes cannot be used, such as toxic, radiological or viral contamination or damage to the water supply network eg. as a result of an earthquake or warfare.

Analyzing the effects of extreme cold waves on urban water supply network safety: A case study from 2020 to 2021

Urban water supply networks are crucial for the transportation of water resources. However, with the increasing frequency and severity of cold wave disasters linked to climate change, the impact on water supply systems has become a critical concern. These impacts include pipe failures, customer water outages, and challenges in meeting peak winter water demand. To address this, our study analyzes data from cold waves in Shanghai from late 2020 to early 2021. We statistically examined daily water supply volume, pressure, and pipe failures to detect abnormal changes. We also analyzed pipe failure rates based on different characteristics to identify which pipes are most vulnerable to cold wave damage. Understanding the winter cold wave's effects can help water companies prioritize maintenance on aging pipes before such events, reducing damage and improving service. This research adds to the understanding of climate change's impact on urban infrastructure and provides valuable insights for global water companies to optimize their maintenance strategies.

NON-DESTRUCTIVE METHODS OF ESTABLISHING A CAUSE-AND-EFFECT RELATIONSHIP BETWEEN WATER SUPPLY NETWORK ACCIDENTS AND THE CONDITIONS FOR PRESERVING ARCHITECTURAL HERITAGE

Accidents on water supply networks have the most significant negative consequences on the state of the historical and architectural heritage, which was formed over many centuries. The paper analyzes the cause-and-effect relationship between accidents of water-carrying networks and the conditions of architectural heritage preservation using the example of the Kyiv-Pechersk Lavra. The results of determining waterlogging zones and their factors by non-destructive monitoring methods on the territory of the Metropolitan Garden of the Upper Lavra are given. This area combines complex engineering and geological conditions and technogenic mastering, creating conditions for developing dangerous engineering and geological processes and emergency situations. In terms of danger, the garden’s territory belongs to unstable areas for preserving historical monuments of the UNESCO world heritage. The last accident on the water supply networks occurred in October 2022. It caused sinkholes on the surface, rising groundwater levels, significant destruction of an underground structure of historical importance – the Metropolitan Cellar. The research was carried out using the methods of electrotomography and natural electric field. The results of electrotomography were interpreted using two- and three-dimensional models. The existence of an anomalous dome (soils of low resistance), which is observed in the central part of the site, is probably the focus of waterlogging of the soil massif as a result of an accident on the heating network. The analysis of the adapted 3D model based on the results of non-destructive methods of monitoring the geological environment made it possible to indirectly establish the places of unsatisfactory technical condition of engineering networks (cold water supply), where a wetted section with low values of apparent resistance was recorded. Research has confirmed the presence of an inflow of man-made waters (leaks) from main water supply networks in the western part of all profiles as a constant source and factor of waterlogging of the array of soil bases of architectural monuments – Monastyrski walls, Kushnyka tower, etc. Based on the research results, the need to develop compensatory measures to strengthen part of the fortress walls was proposed, and a safe distance for moving networks from historical objects was substantiated to preserve them.