Management Of Water Distribution Networks Research Articles

Optimizing District Metered Areas and Associated Pressure Reducing Valves and Pumping Stations for Effective and Efficient Management of Water Distribution Network

Optimizing District Metered Areas and Associated Pressure Reducing Valves and Pumping Stations for Effective and Efficient Management of Water Distribution Network

An Improved DeNSE Methodology for Optimal Sectorization of Water Distribution Networks

Sectorization of a water distribution network (WDN) into district meter areas (DMAs) is considered a key strategy for an efficient management of WDNs. Typically, it involves a two-stage procedure: a clustering stage, in which the division of the WDN into clusters is performed, and a dividing stage, which involves the placement of valves and flow meters on the cluster’s boundary pipes to define the DMAs. While recently published methods attempt to enhance both the clustering and dividing stages, they fail to provide decision-making flexibility. They also neglect to consider the presence of existing valves in the WDN, which can significantly affect the evaluated implementation cost, often considered the primary decision-driving factor. This paper presents improvements to the previously introduced DeNSE method for sectorization of WDNs, aiming to address these deficiencies. The methodology consists of a clustering stage, based on the network uniformity index, and a dividing stage, in which the originally used heuristic procedure is replaced with Genetic Algorithm (GA) optimization, minimizing implementation cost. Consideration of existing valves in WDN and criteria for water supply security are also included in the dividing stage to offer a better estimate of implementation costs and post-sectorized operational efficiency of the WDN. Finally, GIS visualization is implemented, and a hydraulic model of the sectorized WDN (EPANET file) is generated, providing practitioners with valuable insights and decision-making flexibility. The methodology is tested on a part of the Amsterdam WDN in the Netherlands, serving as a pilot for methodology evaluation. A range of feasible sectorization solutions is generated and compared based on implementation cost and three performance indicators (PIs). The paper provides an in-depth discussion on the selection of preferable sectorization solution. The reported results demonstrate the method’s efficiency in optimizing sectorization solutions with minimum implementation cost whilst preserving the WDN operational efficiency and meeting the local design criteria.

Integrated intelligent models for predicting water pipe failure probability

Sustainable management of water distribution networks (WDNs) is essential to ensure the continuous supply of water. However, the water pipes in WDNs often experience unprecedented failure, which causes disruption in services, flooding, increased maintenance costs, and reduced water quality. Although researchers have developed models to predict the failure of water pipes, the literature lacks fully optimized and robust models. Therefore, this study proposes a new methodology to develop optimized models for predicting the failure probability of water pipes by fusing logistic regression with genetic algorithms. The methodology was applied to the data of the Hong Kong WDN, and experiments were conducted to optimize the hyperparameters and features of logistic regression models. The performance of the proposed methodology is evaluated using five key metrics: accuracy, precision, recall, F1 score, and Area Under the Curve (AUC). The results show significant improvement over conventional approaches, with the best model achieving an F1 score of 0.868 and an AUC of 0.944. These results show that the model can effectively predict the failure probability of water pipes. The relative contribution of each feature to the model's outcome was investigated using the SHapley Additive exPlanations. Additionally, a web application based on the proposed methodology in this study was developed for Hong Kong that other water utility management can benefit from, which can facilitate reliable decision-making for the management of WDNs.

Influence of noise masking on leak pinpointing: Experimental analysis on a laboratory test rig for leak noise correlation.

The efficient management of water distribution networks requires the detection and mitigation of leaks that result in significant water losses, economic costs, and potential health hazards. This experimental study focuses on the optimal frequency range for accurately locating a water leak in a distribution network using the noise correlation approach while mitigating the influence of background noise associated with water consumption from users. Through laboratory experimental tests, a digital bandpass filter was defined in order to pre-process signals and to improve cross-correlation analysis within the pertinent frequency range. This was done by characterising the frequency content of leak-induced noise, noise masking resulting from water consumption, and background noise. The analysed signals were recorded using hydrophones installed within the pipes of a laboratory test rig under different conditions of water flow rate. The spectra analysis assessed the influence of varying water flow rates on the acoustic sound field within the pipeline system. Additionally, the results of the analysis made it possible to discriminate clearly between noise generated by leaks and noise attributed to water consumption. This distinction is useful for implementing suitable filters, and also to establish a threshold ratio of leak flow rate to water consumption flow rate for effective pre-filtering. This study aims to establish a methodological framework that can effectively differentiate between acoustic signals stemming from leaks and noise generated by other sources within the system, to improve leak location accuracy through the noise correlation approach.

Application of pressure reducing and throttle control valves for optimal pressure management in water distribution networks

ABSTRACT Advanced pressure control facilitates the smart management of water distribution networks (WDNs). In this study, an optimization-based method is proposed to develop a time-based schedule for pressure reducing valves (PRVs). For this purpose, a single-objective optimization problem is initially delineated, seeking to minimize spatiotemporal variations in the nodal pressures. Then, the application of PRVs is addressed in two scenarios, viz. individual (i.e. employing PRVs) and hybrid (i.e. the combined use of PRVs and throttle control valves [TCVs]). The proposed scenarios are subsequently applied to the hydraulic model of synthetic and real WDNs. A set of hydraulic evaluation indices, including variation index (VI), are further measured to spot the optimal pressure management scenario. The study results establish that the hybrid scenario leads to a larger decrease in the VI along with more efficient pressure control (namely, 39.9% and 11.8% in the synthetic and real WDNs, respectively), compared with the individual one.

Water quality, governance issues, people's perception and water distribution network management through integrated techniques under changing climate

Climate change-induced quality and quantity deterioration has been emerging throughout the globe. Rising temperatures, and fluctuating rainfall patterns are alarming signs of climate change. Urbanization and industrialization under the influence of climate change have severely affected our resources. Deficiencies in management, quality and distribution network of sector I-8 Islamabad, Pakistan, were investigated. Based on the GIS mapping, appropriate locations for the installation of smart meters have been identified accompanied by awareness-raising activities and assessment of quality of supply network through standard methods. The idea of billing as per use rather than flat rates and metering was supported by 73% through survey. Bottled for drinking purpose was used by 54.9% while 86% people were using public supply for other purposes showing mistrust of people on public supply. Similarly, quality analysis showed that all the samples analyzed (n = 23) were safe chemically but 57% samples (n = 13) found contaminated microbiologically. This study is important for the policy makers to resolve the governance issues in the study area and GIS mapping can be applied on all types of supply networks around the globe.

Hybrid Optimization Algorithms of Firefly with GA and PSO for the Optimal Design of Water Distribution Networks

A novel two-hybrid optimization model of particle swarm optimization (FAPSO) and firefly algorithm with genetic algorithm (FAGA) are introduced to improve the performance of the conventional firefly algorithm for the least cost design of water distribution networks. The performance of the models is tested through application to three of the well-known benchmark networks available in the literature and also to the real case study of the El-Mostakbal City network, Ismailia, Egypt. The performance of the different algorithms was determined by evaluating the minimum, maximum, mean and standard deviation of costs, the function evaluation number, the consumed computational time for 1000 evaluations and the success rate calculated using the fuzzy logic concept for different optimal solutions slightly greater than the known optimal solution (by about 1.0% and 2.0%) were utilized for testing the convergence and search capabilities of the models. It was found that the FAGA model is superior to the standard firefly and FAPSO models in exploring the search space, exploiting the promising areas and convergence to the optimal solution and can be considered as a reasonable optimization technique for the management of water distribution networks.

A convenient and stable graph-based pressure estimation methodology for water distribution networks: Development and field validation

Accurate estimation of unknown nodal pressures (nodal heads) is necessary for efficient operation and management of water distribution networks (WDNs), but existing methods such as hydraulic simulation and data interpolation can hardly reconcile estimation accuracy with model construction and maintenance costs. Recent developments in graph signal processing (GSP) techniques provide us with new tools to utilize information in WDN hydraulics and available measurements. In a pilot study, a graph-based head reconstruction (GHR) method was proposed, which used GSP to reconstruct the spatially slow-varying parts of nodal heads from a limited number of field measurements to approximate original heads. GHR has illustrated the effectiveness and ease of implementation of GSP-based methods. However, due to the ill-conditioning reconstruction process and inherent uncertainties, GHR may show unstable results with large errors if pressure meters are not installed at specific optimized locations, which limits its applicability. To solve this problem and discover a stable and convenient method that can support a wider range of applications, a graph-based head reconstruction method with improved stability (GHR-S) is proposed. GHR-S utilizes a rough estimation of unknown pressures as pseudo measurements, which provide additional constraints and avoid the occurrence of unreasonable results during the reconstruction process. A middle-sized network with synthetic data illustrates the stability, convenience, and accuracy of GHR-S with arbitrary meter locations and uncalibrated model parameters. GHR-S is also applied to a large real-life network with field measurements, and successfully estimates the unknown pressures of 83,000 nodes with only 58 measurements, showing its effectiveness in practical engineering.

Digital Water Services using Digital Twin paradigm

In the last years, the digital transition concept has spread all over public and private life as a process designed for improving problem solving in industry by the combination of models, information, and connectivity technologies. In the Water Distribution Networks (WDNs) management sector, the innovations in the areas of ICT/IoT, virtual representation of infrastructure elements in GIS/BIM platforms and the advancements in hydraulic modelling offer the opportunity to open a new era for water engineering. Nonetheless, a unique consensus about the digital transformation meaning in WDNs management is still missing. In this paper a recent paradigm for the digital transformation for WDNs is exposed and further extended, starting from the concept of Digital Twin for WDNs management. It encompasses the virtual representation of features and devices of the network integrated with advanced hydraulic modelling and Artificial Intelligence for supporting WDNs management tasks. The WDN Digital Twin is used within tools, named Digital Water Services (DWSs), working on GIS platforms. DWSs are conceived to support distinct phases of WDNs management by improving engineering awareness on technical decisions. Several DWSs, previously adopted for real WDNs management and planning, are here presented, as support tools for technicians and water utilities for achieving short-term and long-term management tasks.

A complete digital water experience to support real leakage management planning

In the next years digital transition of Water Distribution Networks (WDNs) will represent a long-standing challenge for triggering innovations in the WDNs management tasks. The ongoing impulse for innovation, boosted also by the economic resources for post-pandemic recovery, is opening novel opportunities for technicians and researchers in the context of Digital Water. This work reports the key steps where novel concepts and tools of Digital Water have been used to support consultant companies in designing WDN leakage management actions in a real WDN managed by Acquedotto Pugliese, in Southern Italy. The Digital Water Services (DWSs) were used to support key phases of the workflow, including validation of topological data and integration of georeferenced connection to private properties; calibration of advanced hydraulic model exploiting mass-balance in pressure-driven analysis; the application of strategies for DMA design and pressure control; and the planning of pipe rehabilitation. WDNetXL platform was used to develop WDN Digital Twin and exploit the DWSs. Applying the Digital Water experience to multiple WDNs managed by the same provider also enabled planning the best courses of actions accounting for investments vs. expected leakage reduction at global scale.

Leakage Management Influence on Water Age of Water Distribution Networks

AbstractLeakage management of Water Distribution Networks (WDNs) is a relevant technical task worldwide. Background leakages along mains and connections to properties in aged infrastructures represent a significant portion of the WDN water outflow, sometimes exceeding customer demands. Pressure control and District Metering Areas (DMAs) design are two classic activities aimed at leakage management. The former reduces the background leakages, and thus the velocities in pipes, especially those along main paths for water transport across the WDN. The latter involves closed valves confining each DMA, which change network connectivity reducing redundancy and eventually pressure, that is, background leakages. Hence, both activities reduce water velocity in pipes because of leakage reduction (i.e., the overall WDN inflow), while DMAs could increase it in some pipes. Therefore, leakage management activities might affect the water age in WDNs, as a general water quality indicator, depending on the initial level of leakages, the WDN connectivity and topology, and the attained reduction. This work studies the effect of leakage management on water age for two real WDNs, which are characterized by different initial levels of leakages and expected reduction, after planning pressure control and DMAs. The advanced hydraulic modeling, employing pressure‐driven leakage modeling at pipe level, is integrated with water age analysis, allowing unlimited number of parcels. The sensitivity of water age to the maximum number of parcels in the model is studied to identify the trade‐off between accuracy and computational runtime. The variation of mean daily water age due to change of demand pattern is analyzed considering a 4‐week operative cycle.

Comparative Analysis on the DMA Partitioning Methods Whether Trunk Mains Participated

In recent years, the District Metered Area (DMA) of water distribution networks (WDNs) has become a major development trend in the water leakage control area. It has significant value in the active leakage control and pressure management of WDNs. This study comments on two DMA partitioning methods (Scheme A and B, previously introduced in another paper) and compares three aspects of their respective performances to elucidate their respective strengths and weaknesses. Scheme A partitions all the network nodes, whereas Scheme B only partitions the remaining network nodes, except the trunk mains. Whether the trunk mains participated in the partitioning process is the key distinction between the two approaches. There is little relevant research that compares and analyzes the effects of the above two methods. This paper applies these two types of partitioning methods to a case network. The respective performances in three aspects, namely economy, water quality, and leakage control, were evaluated and compared. For economy, Scheme A is more economical than Scheme B, saving about 15.34%. For water quality, Scheme B is the best partitioning method because it reduces water age better than Scheme A does. For leakage control, Scheme B has a drop of 19.46%, which is better than Scheme A (a decline of 15.12%) in comparison to the initial leakage.

Efficient Pipe Burst Detection in Tree‐Shape Water Distribution Networks Using Forward‐Backward Transient Analysis

AbstractTransient‐based leak/burst detection has received more and more attentions in the operation and management of water distribution networks. However, with the increase in pipe network complexity, it is hard to detect and locate the potential pipe defects and water losses efficiently. Recently, we proposed an efficient leak/burst localization strategy in single pipelines based on the forward and backward transient analysis, and in this work, this effective approach is customized for the more realistic branched (tree‐shaped) pipe networks. Unlike traditional transient‐based methods which rely on tedious optimization procedures, the proposed method uses a mismatch property between forward and backward analyses of transient signals for the pipe burst detection during the water supply process. Compared with other developed methods, this method can directly calculate the defect location, so it is expected to have high efficiency and wide applicability. To fulfill this goal, a framework for burst detection in a tree‐shaped pipe network is developed in this paper. Using the mass conservation and energy relations at the branched junctions, the forward and backward transient analysis is extended from one pipe to another until the burst is found and then located in the network. Both experimental and numerical tests show the effectiveness of the proposed method, and further analysis has shown that the method is also valid for leak detection in both transient and steady conditions, confirming the robustness and practicality of this proposed method. At last, this paper discusses the influence of transient sources and the potential combination of the method with other methods.

Multiphase Procedure for Identifying District Metered Areas in Water Distribution Networks Using Community Detection, NSGA-III Optimization, and Multiple Attribute Decision Making

The formation of district metered areas (DMAs) is an efficient strategy for the operation and management of water distribution networks (WDNs). Identifying the most suitable DMA layout is a challenging task for water utilities as it may involve several aspects that need to be addressed simultaneously. This study presents a novel multiphase approach for optimal DMA design that involves: (1) a combination of a fast Newman algorithm (FNA) to identify initial clusters; (2) a nondominated sorting genetic algorithm (NSGA-III) to obtain a set of good DMA configurations while considering several objectives simultaneously; and (3) a multiple attribute decision-making method (MADM) to find the best suited DMA configuration from a set of feasible alternative solutions based on the preference given to each objective. The proposed methodology is applied to two networks including a large benchmark network and a real-life water network. Four problem objectives out of several possible objectives were considered. These are: (1) the total cost of implementation (economic criterion); (2) the pressure deviation (hydraulic criterion); (3) a resilience index (energy criterion); and (4) the total demand shortfall (customer satisfaction criterion). Finally, a multiple attribute decision-making tool [i.e., a simple additive weighing (SAW) method] was used to arrive at a unique solution out of a set of feasible solutions. Results show that the proposed methodology can effectively identify DMAs while considering multiple objectives.

Exploring the key facets of leakage dynamics in water distribution networks: Experimental verification, hydraulic modeling, and sensitivity analysis

Hydraulic solvers are extensively used for the real-time operational analysis and asset management of water distribution networks. However, the influence of leakage on network hydraulics is still not fully understood, and limited experimental verification concerning leakage modeling and calibration efficacy of hydraulic solvers is presently available. To address these limitations, this research develops a novel strategy to quantitatively assess the efficacy of the popular hydraulic solver, EPANET 2.0 in emulating the leakage dynamics through an extensive experimental study conducted on a realistic sensor-equipped network prototype followed by comprehensive leakage modeling and analysis. The network response to diverse leak scenarios is experimentally analyzed, and the inferences derived are utilized to configure the leak models. A stage-wise calibration routine of the base and leak models is executed, which exhibits reasonable accuracy with mean absolute errors of 0.011 and 0.060, respectively. The calibrated leak models manifest satisfactory performance concerning the simulated system pressure and effectively predict the leak flow trends at all leakage levels. The sensitivity matrix of the leak models also captures the variation in the localized and global impact of leak levels on system flow and pressure concerning different leak scenarios. Thus, this research experimentally verifies the efficacy of leakage modeling using EPANET 2.0 and delineates the potential challenges concerning efficient calibration and performance analysis of leak models using the predefined leak parameters. The implications of this study can be instrumental for utility managers and researchers in configuring improved leak models using hydraulic solvers and strategizing model-based leakage management plans.

Principal Component Based Sampling for the Continuous Maintenance of Hydraulic Models

The calibration and continuous maintenance of hydraulic models is essential for the optimisation, planning and management of water distribution networks (WDNs). This process requires model fitting against multiple hydraulic states. However, when extended time series of hydraulic data are considered, it is essential to know which hydraulic states to use for model fitting as too many become computationally impractical. This paper presents a novel principal component analysis (PCA) based sampling method, which evaluates the significance of newly observed hydraulic data to be included in the model calibration and maintenance. A framework is presented, which allows for different sized batches of hydraulic data to be utilised. This enables both model calibration on extended time series of data, or model calibration and maintenance with continuous data. An extensive experimental program was conducted to investigate the performance of the proposed framework with different sampling methods compared to other conventional approaches. The results demonstrate that the presented sampling methods can maintain and improve model prediction accuracy both for retrospective and concurrent implementations when used with extended time series data, which capture different hydraulic states. The hydraulic model of the operational WDN used in this study and the acquired hydraulic data are provided as supplementary data to facilitate reproducible research.

New Challenges towards Smart Systems’ Efficiency by Digital Twin in Water Distribution Networks

Nowadays, in the management of water distribution networks (WDNs), particular attention is paid to digital transition and the improvement of the energy efficiency of these systems. New technologies have been developed in the recent years and their implementation can be crucial to achieve a sustainable level of water networks, namely, in water and energy losses. In particular, Digital Twins (DT) represents a very innovative technology, which relies on the integration of virtual network models, optimization algorithms, real time data collection, and smart actuators information with Geographic Information System (GIS) data. This research defines a new methodology for an efficient application of DT expertise within water distribution networks. Assuming a DMA of a real water distribution network as a case study, it was demonstrated that a fast detection of leakage along with an optimal setting of pressure control valves by means of DT together with an optimization procedure can ensure up to 28% of water savings, contributing to significantly increase the efficiency of the whole system.

Improvement of the energy efficiency in water systems through water losses reduction using the district metered area (DMA) approach

The reduction of water losses is a crucial aspect to be addressed in Water Distribution Networks (WDNs) since they account for almost 50% of the water supply globally. To have a better figure of the involved water volumes, the District Metered Area (DMA) approach has been used in a WDN of a town located in the center of Italy (Osimo). In particular, a complete methodology for calculating and then detecting the water losses is described and applied using the end-users’ water volumes consumptions obtained by inspecting water bills and the supplied water through on-field measurements. These values have been subsequently used to develop and calibrate a hydraulic model of the district under investigation through EPANET, thus allowing the WDN management to estimate both flow rates and pressures to assess the zones where smart meters have to be installed. Water losses have been controlled by monitoring the flow rates through smart meters with an innovative 868 MHz remote reading infrastructure, thus leading to 5,558.8 m3 of avoided water losses (12.5% less than the initial case) that corresponds to an energy reduction and an economic saving of 7,332 kWh and 1,857 € in the last three-month period of the year 2020, respectively.

IoT-Enabled Water Distribution Systems—A Comparative Technological Review

Water distribution systems are one of the critical infrastructures and major assets of the water utility in a nation. The infrastructure of the distribution systems consists of resources, treatment plants, reservoirs, distribution lines, and consumers. A sustainable water distribution network management has to take care of accessibility, quality, quantity, and reliability of water. As water is becoming a depleting resource for the coming decades, the regulation and accounting of the water in terms of the above four parameters is a critical task. There have been many efforts towards the establishment of a monitoring and controlling framework, capable of automating various stages of the water distribution processes. The current trending technologies such as Information and Communication Technologies (ICT), Internet of Things (IoT), and Artificial Intelligence (AI) have the potential to track this spatially varying network to collect, process, and analyze the water distribution network attributes and events. In this work, we investigate the role and scope of the IoT technologies in different stages of the water distribution systems. Our survey covers the state-of-the-art monitoring and control systems for the water distribution networks, and the status of IoT architectures for water distribution networks. We explore the existing water distribution systems, providing the necessary background information on the current status. This work also presents an IoT Architecture for Intelligent Water Networks - IoTA4IWNet, for real-time monitoring and control of water distribution networks. We believe that to build a robust water distribution network, these components need to be designed and implemented effectively.

Reliability analysis of complex water distribution systems: the role of the network connectivity and tanks

Abstract A reliable water distribution network (WDN) can provide an adequate supply service to customers under both normal and abnormal working conditions. The WDN reliability analysis, therefore, is a keystone to improve the supply service efficiency. Strategies for reliability analysis are usually proved on small WDNs, which do not compare with large real complex systems in terms of number of water tanks, pressure reduction valves, variable speed pumps, controlled devices and possible alternative water supply schemes. The topological changes due to pipeline interruptions impact on emptying–filling of water tanks and network pressure status. This work proposes a two-level procedure for mechanical reliability assessment, suited for large real WDNs. It leverages a path/connectivity-based approach to set up reliability indicators for global-level analysis and local screening of the most critical scenarios. The employed advanced hydraulic model includes the automatic detection of topological changes and the robust modelling of water level in tanks using the generalized global gradient algorithm. The extended period simulation enables the reliability assessment of alternative water supply schemes and the sensitivity of tanks and controlled devices to single failure events. The procedure is demonstrated on a real complex network, being consistent with the ongoing digital transition in the WDN management sector.