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Water distribution systems (WDSs) are massive infrastructure systems designed to supply water from sources to consumers. The optimal operation problem of WDSs is the problem of determining pump and tank operation to meet the consumers' demands with minimal operating cost, under different constraints, which often include hydraulic feasibility, pressure boundaries, and water quality standards. The water quality aspect of WDSs' operation poses significant challenges due to its complex mathematical nature. Determined by mixing in the systems' nodes, it is affected by flow directions, which are subject to change based on the hydraulic state of the system and are therefore difficult to either predict, control, or be included in an analytical model used for optimization. Water age, which is defined as the time water travels in the system until reaching the consumer, is often used as a general water quality indicator—high values of water age imply low water quality, whereas low values of water age usually mean fresher, cleaner, and safer water. In this work, we present the effects that tank operation has on water age. As tanks contain large amounts of water for long periods of time, water tends to age there significantly, which translates into older water being supplied to consumers. By constraining the tank operation, we aim to present the trade-off between water age, tank operation, and operational cost in the WDS optimal operation problem and provide an operational tool that could assist system operators to decide how to operate their system, based on their budget and desired water age boundary. The analysis is applied to three case studies that vary in size and complexity, using MATLAB version R2021b and EPANET 2.2. The presented results show an ability to mitigate high water age in water networks through tank constraints, which varies in accordance with the system's complexity and tank dominance in supply. The importance of a visual tool that serves as a guide for operators to tackle the complex problem of controlling water age is demonstrated as well. [ABSTRACT FROM AUTHOR]

The Journal of Water Resources Planning and Management (JWRPM) launched a Reproducibility Review Program in 2020 to address the lack of reproducibility in water-related journals. The program encourages authors to publish data, models, code, and directions with their articles so that independent reviewers can replicate their work. The program has five objectives, including promoting reproducibility, facilitating the use of reproducible work, and recognizing authors who make their work more reproducible. The program has already awarded Silver and Bronze badges to several manuscripts and plans to expand to other journals. Challenges include incorporating reproducibility reviews into the submission process and educating authors about the program. The program aims to improve reproducibility in the water resources field and shift towards reproducibility as the default in research. [Extracted from the article]

This study examined the utilization of transient shear stress for cleaning sediment and biofilm materials adhered to the inner walls of pipes in water distribution systems. This approach is presented as a potential method for material resuspension during pipe flushing. This is done to prevent discoloration and low-water-quality events, which can be a major concern for both water utilities and consumers. This work builds and expands on previous work on biofilm detachment under unsteady flows. This study explored the manipulation of existing valves to induce high transient shear stresses that, in turn, resuspend materials adhering to the pipe walls. Through the use of valves strategically positioned along the water distribution system, the systems are subjected to consecutive controlled transient pressure waves. It is possible to capitalize on the interference properties of the controlled transient waves at various points in the system. It is in this condition that various pressure waves can merge within the system, causing high pressures and relatively high shear stresses. However, it is vital to keep the pressure confined within the allowed range to ensure the integrity of the system. A Lagrangian with unsteady friction method was implemented and applied for modeling the transient behavior in two water networks. [ABSTRACT FROM AUTHOR]

Applying mechanistic water quality analysis models that are proficient at simulating the dynamics of heterotrophic bacteria within distribution pipes is a pragmatic approach to maintaining biological stability during drinking water distribution systems (DWDS) operation. Accurate interpretation of hydrodynamics and the uncertainties associated with the multifaceted exchanges within the distribution pipes is crucial to the reliability of these models' predictions. However, knowledge about most exchanges within DWDS is still inadequate. Therefore, state-of-the-art mechanistic models exist merely as theoretical frameworks to understand the causes and effects of microbiological quality fluctuations in DWDS, and they lack general applicability. Advancing the applicability and reliability of the mechanistic models necessitates adequate consideration of epistemic and aleatory uncertainties. This study developed mechanistic models to realize the degree of complexity that needs to be integrated into the modeling framework to accurately describe the water quality dynamics in a real-world DWDS. Under the test conditions considered, the simplest single-phase models that ignore the complex exchanges associated with the pipe biofilm layers were found to make similar microbiological quality predictions as the relatively complicated two-phase models. The results indicate that the knowledge uncertainty associated with mechanisms concerning heterotrophic bacterial regrowth in the bulk phase and biofilm detachment in the wall phase is critical in controlling the reliability of the mechanistic water quality models. [ABSTRACT FROM AUTHOR]

The optimal operation of water distribution systems (WDS) is a paramount objective for water utilities due to the substantial energy consumption associated with pumping. A major challenge in optimizing WDS operation is addressing uncertainties such as those related to consumer demands. Real‐time operation under uncertainty necessitates a dynamic approach that can utilize the newly observed information and adjust the operational policy accordingly. This study presents an adjustable robust optimization (ARO) approach to tackle this challenge. Unlike static optimization methods, ARO generates a decision rule policy that is dynamically adjusted as new data becomes available and the operational horizon evolves, thereby ensuring adaptability to changing conditions. Furthermore, the study includes a quantitative analysis of typical demand uncertainty that supports the formulation of the ARO model. The proposed method is evaluated through two case studies and compared with traditional folding horizon approaches. The results indicate that the ARO method is competitive with traditional methods in terms of objective value and surpasses them in terms of robustness. An additional advantage of the method is its offline operation capability which enables it to produce decision rules independent of real‐time programs. This feature facilitates various practical applications such as what‐if analyses, maintenance work planning, and preparation for other special events. Plain Language Summary: The study is focused on developing strategies to optimize the operation of water distribution systems under uncertainty. Pumping and distributing water consumes a lot of energy, therefore water utilities strive to optimize the system's efficiency. This optimization problem involves uncertainties, such as consumer water demands. To address this challenge, a method is developed based on adjustable robust optimization (ARO) theory. Unlike conventional optimization methods that produce a fixed policy for the entire operational horizon, ARO generates an adjustable policy as a decision rule. It creates a dynamic decision‐making policy that can adapt to new data and evolving conditions. The study also includes an analysis to quantify the typical uncertainty associated with water demand which supports the formulation of the ARO model and justifies parts of the theory behind it. The proposed method is tested on two case studies and compared with traditional approaches. Several sensitivity analyses were held to present the ARO advantages and compare it with other methods. The results showed that ARO performs competitively with other methods and outperforms some of them. Key Points: Optimal operation of water distribution systems under uncertainty is addressed with a dynamic, data‐driven approachAn adjustable robust optimization model is developed to provide a decision rule that adapts to the latest revealed informationComparative analysis of the method against traditional folding horizon methods demonstrates superior performance [ABSTRACT FROM AUTHOR]

Maximizing reliability is imperative for water distribution network (WDN) design. Recent claims about providing adequate and operable isolation valves as a focal aspect of a reliable WDN design have attracted substantial interest. In this direction, this paper attempts to answer the question of which isolation valves in a WDN must be prioritized based on their criticality toward enhancing WDN reliability. Two novel algorithms are proposed, one for ranking every isolation valve in a WDN and the second to identify the location of a new isolation valve to reduce the criticality of a specific valve in a WDN. Unlike the prevailing methodologies, the proposed algorithms are entirely based on the topological attributes of a WDN and do not require a calibrated hydraulic model, which is often a limiting factor in WDN management. Our proof of concept has unveiled the capability of the methodology to deliver preliminary information to water utilities regarding the criticality of valves without any hydraulic simulation. [ABSTRACT FROM AUTHOR]

Forum papers are thought-provoking opinion pieces or essays founded in fact, sometimes containing speculation, on a civil engineering topic of general interest and relevance to the readership of the journal. The views expressed in this Forum article do not necessarily reflect the views of ASCE or the Editorial Board of the journal. [ABSTRACT FROM AUTHOR]

Water distribution network design is a complex multi-objective optimization problem and multi-objective evolutionary algorithms (MOEAs) such as NSGA II have been widely used to solve this optimization problem. However, as networks get larger, NSGA II struggles to find the diverse and uniform solutions that are critical in multi-objective optimization. This research proposes an improved version of NSGA II that uses three new-generation methods to target different regions of the Pareto front and thus increase the number of solutions in critical regions. These methods include saving an archive, local search around extreme and uncrowded Pareto front, and local search around the knee area of the Pareto front. The improved NSGA II is tested on benchmark networks of different sizes and compared to the best-known Pareto front of the networks determined by MOEAs. The results show that the proposed algorithm outperforms the original NSGA II in terms of broadening the Pareto front solution range, increasing solution density, and discovering more non-dominated solutions. The improved NSGA II can find solutions that cover all parts of the Pareto front using a single algorithm without increasing computational effort. [ABSTRACT FROM AUTHOR]

Water distribution systems (WDSs) require high-quality water for safe consumption. To achieve this, disinfectants such as chlorine are often added to the water in the system. However, it is important to regulate the levels of chlorine to ensure they fall within acceptable limits. The higher limit is to control disinfection by-products, while the lower limit is established to guarantee that the water is free of organic contaminants. The rate at which chlorine reacts within the pipes is affected by various factors, such as the type of pipe, its age, the pH level of the water, the temperature, and others. This variability makes it challenging to accurately model water quality in WDSs, which can impact the optimal rate of booster injection. To address the uncertainty in the chlorine reaction rate, the current research proposes a robust counterpart reformulation of the booster chlorination scheduling problem, which considers the chlorination reaction rate as uncertain. The proposed reformulation was tested on two benchmark WDSs and analyzed with a thorough sensitivity analysis. The results showed that as the size of the uncertainty set increased, the injection mass also increased. This reformulated approach can be applied to any WDS and provides a way to obtain optimal scheduling within the desired protection levels. [ABSTRACT FROM AUTHOR]

The operation of water distribution systems (WDS) is an energy-intensive process, which is subject to constraints such as consumer demands, water quality, and pressure domains. As such, tracing an operation policy in which constraints are met while energy costs are minimized, is a foremost objective for water utilities. Given the inherent uncertainties in WDS operation and the importance of supply continuity, it is essential to find an operational strategy that is robust against a wide range of circumstances. One promising approach for optimization under uncertainty is robust optimization (RO), which assures a robust (feasible) solution to realizations of the uncertain parameters, within predefined bounds. This study presents an RO-based method for optimizing pump scheduling under uncertainties of consumer demands and pumping costs. The method can capture various types of correlations between the uncertain parameters, thus better reflecting the uncertain nature of WDS operation. The developed methodology is demonstrated in two case studies with different levels of complexity. The impacts of uncertainty levels and correlation coefficients are analyzed to demonstrate their implications on operation policy. The results show the advantages of using RO with tradeoffs between costs and constraints satisfaction. [ABSTRACT FROM AUTHOR]

A least-cost optimization of a water distribution system (WDS) results in a branched network if some system reliability measures are not considered. Using an explicit level of system redundancy is one way to enhance reliability in the WDS network. This approach consists of first dividing the network into subsystems. Then, during the optimization stage, the subsystems are optimized simultaneously by demanding each one to maintain some level of service. Which pair of subsystems is ultimately selected determines the outcome of the optimization problem. However, there is little if no literature on the optimization of the selection of a pair of subsystems. This study addresses both subsystem and component sizing optimization in designing a level-1 redundant network. Candidate subsystems are enumerated using graph theory where st-numbering for the network is assigned first, and then the backups are generated following the decrement and increment orders of the node's st-numbering. [ABSTRACT FROM AUTHOR]

A key challenge in designing algorithms for leakage detection and isolation in drinking water distribution systems is the performance evaluation and comparison between methodologies using benchmarks. For this purpose, the Battle of the Leakage Detection and Isolation Methods (BattLeDIM) competition was organized in 2020 with the aim to objectively compare the performance of methods for the detection and localization of leakage events, relying on supervisory control and data acquisition (SCADA) measurements of flow and pressure sensors installed within a virtual water distribution system. Several teams from academia and the industry submitted their solutions using various techniques including time series analysis, statistical methods, machine learning, mathematical programming, met-heuristics, and engineering judgment, and were evaluated using realistic economic criteria. This paper summarizes the results of the competition and conducts an analysis of the different leakage detection and isolation methods used by the teams. The competition results highlight the need for further development of methods for leakage detection and isolation, and also the need to develop additional open benchmark problems for this purpose. [ABSTRACT FROM AUTHOR]

Water age is the time taken for water to travel through a distribution system and reach the consumer. Generally, there is a trade-off between water pressure and water age in a water distribution system—higher pressure results in higher flow velocity, which often means shorter traveling time for the water, while lower pressure leads to slower flow and thus higher water age. Low pressure is a desired objective in a distribution system, as it reduces the physical stress on its components and minimizes water losses in the event of a leak. Low water age is a desired objective as well, as increased age is regarded as having a low water quality. Therefore, the two objectives compete with one another. The problem of trying to minimize both water pressure and age is a common problem in water distribution systems' design and management. This paper introduces an algorithm for pressure reducing valves' (PRVs) placement for reducing water age in water distribution systems. The algorithm is based on graph-theory elements and uses EPANET 2.2 for simulation and analysis. The method is demonstrated on two small scale examples, and the results present relatively significant improvements in respect to water age. [ABSTRACT FROM AUTHOR]

The vastness of water distribution systems (WDS) makes them vulnerable to exposure to different types of accidental/intentional contamination. Although most such contamination events that occurred in the recent past were accidental, criminal intent was involved in a few. Considering the accessibility of WDS and the potentially harmful outcomes of drinking-water contamination, online water-quality monitoring sensors are typically positioned in selected locations throughout WDS as a preventive strategy. These sensors, once positioned, communicate over a cyber-infrastructure layer and are liable to cyber-physical attacks—the sensor and/or its communication system becoming compromised or the sensor network becoming malfunctioned such that part of its components is deactivated. However, the sensor network placement state-of-the-art has thus far overlooked these cyber-physical attack scenarios. The current study attempts to overcome this limitation in the state-of-the-art by developing and demonstrating a methodology for evaluating the impact of a cyber-physical attack on a sensor network, compromising its functionality partially. Our proof-of-concept, using a simple network and a straightforward cyber-physical attack scenario, has revealed the vast potential of examining the performance of sensor networks under accidental/intentional malfunctioning and providing valuable information for decision makers in water utilities and regulators. [ABSTRACT FROM AUTHOR]

Contamination events in water distribution systems (WDS) are emergencies that cause public health crises and require fast response by the responsible utility manager. Various models have been developed to explore the reactions of relevant stakeholders during a contamination event, including agent-based modeling. As the COVID-19 pandemic has changed the daily habits of communities around the globe, consumer water demands have changed dramatically. In this study, an agent-based modeling framework is developed to explore social dynamics and reactions of water consumers and a utility manager to a contamination event, while considering regular and pandemic demand scenarios. Utility manager agents use graph theory algorithms to place mobile sensor equipment and divide the network in sections that are endangered of being contaminated or cleared again for water consumption. The status of respective network nodes is communicated to consumer agents in real time, and consumer agents adjust their water demands accordingly. This sociotechnological framework is presented using the overview, design, and details protocol. The results comprise comparisons of reactions and demand adjustments of consumers to a water event during normal and pandemic times, while exploring new methods to predict the fate of a contaminant plume in the WDS. [ABSTRACT FROM AUTHOR]

At the 2013 World Environmental and Water Resources Congress in Cincinnati, Ohio, the ASCE Task Committee on Research Databases for Water Distribution Systems was formed to develop an online open-access repository of water distribution system hydraulic network files for use in applied scientific research. This paper discusses the development of the resulting database, specific model contributions, available model building toolkits, general methods for system classification, and general information related to the database platform and content. It is hoped that the assembled database will promote the advancement of water distribution research into the next decade. [ABSTRACT FROM AUTHOR]

The optimal design of WDS has been extensively researched for centuries, but most of these studies have employed deterministic optimization models, which are premised on the assumption that the parameters of the design are perfectly known. Given the inherently uncertain nature of many of the WDS design parameters, the results derived from such models may be infeasible or suboptimal when they are implemented in reality due to parameter values that differ from those assumed in the model. Consequently, it is necessary to introduce some uncertainty in the design parameters and find more robust solutions. Robust counterpart optimization is one of the methods used to deal with optimization under uncertainty. In this method, a deterministic data set is derived from an uncertain problem, and a solution is computed such that it remains viable for any data realization within the uncertainty bound. This study adopts the newly emerging robust optimization technique to account for the uncertainty associated with nodal demand in designing water distribution systems using the subsystem-based two-stage approach. Two uncertainty data models with ellipsoidal uncertainty set in consumer demand are examined. The first case, referred to as the uncorrelated problem, considers the assumption that demand uncertainty only affects the mass balance constraint, while the second case, referred to as the correlated case, assumes uncertainty in demand and also propagates to the energy balance constraint. [ABSTRACT FROM AUTHOR]

The multi-objective design optimization of water distribution systems (WDS) is to find the Pareto front of optimal designs of WDS for two or more conflicting design objectives. The most popular conflicting objectives considered for the design of WDS are minimization of cost and maximization of resilience index which are considered for the current study. Robust multi-objective optimization is to find the optimal set of the Pareto front considering demand is uncertain. The robustness is controlled by a single parameter that defines the size of the uncertainty set it can vary. The study explores ellipsoidal uncertainty set with different sizes and co-variance matrices. A combined simulation–optimization framework with a combination of self-adaptive multi-objective cuckoo search (SAMOCSA) and the fmincon optimization algorithm is proposed to solve the robust multi-objective design problem. The proposed algorithm is applied to medium and large WDS. The main contribution of this paper is to study the effect of demand uncertainty and the correlation on the WDS designs in a multi-objective framework. The study shows that the inclusion of correlation into the multi-objective design framework can significantly affect the optimal designs. [ABSTRACT FROM AUTHOR]

Accurate interpretation of longitudinal dispersion of solutes within distribution pipes increases the reliability of the predictions of water distribution systems (WDS) water quality analysis models. However, the estimation of longitudinal dispersion from fundamental principles is complicated. Thus, a longitudinal diffusion coefficient, a nonphysical constant depending on the flow and pipe properties, is generally applied to characterize the dispersion mechanism during the advective-dispersive-reactive (ADR) modeling in WDS. Many empirical/semiempirical formulas exist for calculating the coefficient values. Several of them have been applied in WDS water quality modeling research also. However, these formulas have shortcomings concerning overestimating and/or underestimating the longitudinal dispersion coefficient value under transitional/turbulent flow regimes and depicting the transient nature of longitudinal dispersion under laminar flow settings. As yet, no effort has been made to comparatively analyze the implications of the performance of these formulas in ADR modeling in WDS. This paper attempted to critically examine the competence of the prevailing state of the art to accurately represent longitudinal dispersion in pipes from a WDS water quality modeling perspective. The results established that the conceptual dissimilarities in incorporating dispersion memory and transient characteristics between the formulas for laminar regimes have significant impacts on regulating the scale of longitudinal dispersion in the ADR model predictions. The relative variances between the formulas for transitional/turbulent flow settings were found comparatively less significant concerning the ADR model outputs. This study's findings can advance the state of the art to minimize the failure risks involved in simulating the concentration profiles when dispersive transport is dominant over advection in WDS. [ABSTRACT FROM AUTHOR]

Typically, computer-based tools built on mathematical models define the time-series behavior of contaminants, in dissolved or colloidal form, within the spatial boundaries of water distribution systems (WDS). EPANET-MSX has become a standard tool for WDS quality modeling due to its collaboration with EPANET. The critical challenges in applying EPANET-MSX include conceptualizing the exchanges among multiple reacting constituents within the WDS domain and developing the scientific descriptions of these exchanges. Moreover, due to its complicated user interface, the EPANET-MSX application demands programming skills from a software engineering viewpoint. The present study aims to overcome these challenges by developing a novel computer-based tool, EPANET-C. Via built-in and customizable conceptual and mathematical models' directories, EPANET-C simplifies WDS water quality modeling for users, even those lacking programming expertise. Due to its flexibility, EPANET-C can become a de facto standard tool in WDS quality modeling study both for the industry and the academia. [ABSTRACT FROM AUTHOR]

A real-life water distribution system (WDS) contains uncertainty in numerous stages. This makes the optimal management and design of a WDS a complex problem. Water quality has also become a significant factor in the design and management of a WDS. Our objective was to incorporate water quality uncertainty in the WDS design problem. The mixing level was assumed to be uncertain and used to design the WDS such that the design was immune to the level of mixing. This method aimed to yield designs that satisfied the nodal concentration constraints irrespective of the mixing level in the junctions. Two optimization methodologies, robust optimization and info-gap decision theory combined with a cuckoo search optimization algorithm, were proposed to solve this problem. An illustrative example 4×4 grid network was used to understand nonuniform mixing and explain the design methodology using both methodologies. Then these methodologies were applied to solve a similar treatment plant problem on a modified Fossolo network. The results also exhibited a significant variation in cost between complete mixing and nonuniform mixing. The WDS designs obtained from both methods were evaluated through Monte Carlo simulations. [ABSTRACT FROM AUTHOR]

This study presents an approximated model for pressure transient simulations as well as a local wall shear stress analysis to control and dislodge biofilm growth in water distribution systems. It demonstrates the potential of taming hydraulic transients to manage and disrupt the growth of biofilm colonies attached to the inner walls of pipeline systems. The systems are subjected to consecutive controlled transient pressure waves by manipulating valves positioned strategically along the water distribution system. Because the controlled transient waves are generated at different locations in the system, the interference properties of the waves can be capitalized on at points where different pressure waves can come together and merge in the system, thus creating high pressures and powerful shear stresses. Nevertheless, it is vital to keep the head pressure confined within the allowed pressure range to avert extreme devastating pressures and ensure the integrity of the system. Three case study applications of increasing complexity are presented to demonstrate the potential of this approach. These transient wave simulations implemented the Lagrangian-based wave characteristic transient model, and the optimization of valve operation was governed by an evolutionary genetic algorithm. The results indicate that it is possible to trigger transient events for biofilm management purposes without exceeding the allowed critical pressure in various network layouts. [ABSTRACT FROM AUTHOR]

This paper presents a new valve positioning algorithm (VPA) for water network pressure reduction. The proposed algorithm is a graph theory-based algorithm combined with EPANET2.2 to position pressure-reducing valves (PRVs) at the most effective locations, having the most effect on downstream pressure reduction, and then calculates the setpoint for locally controlled valves. Each algorithm solution positions one valve on the edge with the highest-pressure reduction indicator calculated using the depth-first search algorithm. The setpoint is then calculated according to downstream pressure differences to the minimum service pressure to be supplied. The PRV location and setpoint found by the algorithm may be used to install and set locally controlled PRVs or serve as a guide for positioning remote-controlled PRVs. The algorithm is demonstrated on a simple example network using demand-driven analysis (DDA), pressure-driven analysis (PDA), and genetic algorithms (GA) and on a medium and a large example application (DDA). Any number of PRVs may be installed using the algorithm, which returns stable results and very short solution times while maintaining minimum service pressure requirements to the critical consumers. [ABSTRACT FROM AUTHOR]

A mechanistic simulation model predicting the response of water distribution systems (WDSs) operated with or without disinfectant residual toward accidental arsenic contamination is developed in this paper. The impacts of chlorination, chloramination, and organic loading to control the oxidation of arsenous acid [As(III)] and the adsorption/desorption of arsenic acid [As(V)] on/from iron pipe walls were simulated by applying the model to two real-world WDSs. The model predicted that during any As(III) contamination event, the arsenic spread in WDSs would engage conservatively in the absence of a residual disinfectant. Due to the swift reactions between chlorine and As(III), maintaining residual chlorine was recognized as an effective strategy to control the soluble As(III) levels. Chloramine was predicted to be less effective than chlorine in causing As(III) oxidation and subsequent As(V) adsorption onto the pipe wall. Besides, under the test conditions considered, the required chloramine dose in the source water had to be 10 times higher to produce equivalent effects in terms of As(III) depletion as the chlorine dose of 1 mg/L. The results presented that chlorine formation in chloraminated WDSs via the monochloramine hydrolysis mechanism contributes to >99% As(III) depletion inside the distribution pipes. Therefore, the paper recommends maintaining additional chloramine residual in chlorinated WDSs to control the As(III) spread during arsenic contamination events in the downstream sections. [ABSTRACT FROM AUTHOR]

This study presents a heuristic multiobjective approach for segmenting and operating water distribution systems (WDS). The methodology employs a two-pronged strategy: the first is a heuristic method for dividing the network into clusters (i.e., district metering areas) based on connectivity analysis. The second is the application of the evolutionary multiobjective optimization method non-dominated sorting genetic algorithm (NSGA)-II for trading off the operational cost, excess pressure (serving as a proxy to leakage reduction), and water age (acting as a surrogate to water quality) in the WDS. Three example applications of increasing complexities with various cluster partitioning are explored, showing a clear trade-off among the objectives. This study introduces an unprecedented heuristic approach for jointly solving the multiobjective problem under a given system partitioning. However, by enforcing a priori clustering formation (rather than including it in the optimization), optimality, completeness, and precision are compromised in favor of computational speed and effort. Thus, additional sensitivities need to be conducted outside of the optimization for the clusters' impact. Challenges of extending this study are in embedding the clusters' formations in the optimization considering other objectives such as residual capacity, developments of other optimization frameworks outside of the generic link of simulation-optimization, and uncertainty inclusion (e.g., in demands). All data and codes are included for allowing full replications and comparisons. [ABSTRACT FROM AUTHOR]

This paper presents an analytical algorithm for simultaneous least-cost design and operation of looped water distribution systems (WDSs). This method could be used to replace evolutionary methods (which are typically used to solve the design-operation problem), or it can be used in conjunction with evolutionary algorithms to enhance their performance (i.e., a hybrid approach). Unlike previous studies that propose analytical methods for split-pipe or continuous diameter design, the developed method addresses a more realistic case in which the pipe design is restricted to commercially available discrete diameters. The analytical approach consists of three stages. In the first stage, a reformulated linear programming (LP) method is used to find the least-cost design of a WDS for a given set of flow distribution while allowing a pipe-split in the solution. In the second stage, the equivalent pipe diameters of the split-pipe design are calculated and modified to discrete pipe diameters by applying a rounding-up strategy to the next commercially available pipe diameter. In the third stage, a nonlinear programming (NLP) method is used to find a new flow distribution that reduces the cost of the WDS operation given the design of the second stage. It is shown in this study that the results produced by the analytical method outperform the results of evolutionary methods when compared to previously published studies. Moreover, when a hybrid approach is adapted, the analytical method can be used to initialize the evolutionary algorithm to gain enhanced performance. The results of the hybrid approach fine-tune those obtained from the analytical method and demonstrate a substantial improvement when compared to a standard evolutionary algorithm initialized with a randomly generated initial population. [ABSTRACT FROM AUTHOR]

The increasing risk of intentional, negligent, or accidental intrusion of biological, chemical, or radioactive contaminants in water distribution systems is becoming a major concern that has significant and adverse impacts on public health. As such, it is important to have an effective, robust, and flexible plan that can be readily implemented to minimize the impact of these contamination events. However, limited research has been focused on the strategic planning of the decontamination process of the contaminated infrastructure. This paper proposes an analytical method for modeling the slug‐feed method of disinfection given the drainage and disinfectant dosage profiles. The efficacy of the proposed method has been demonstrated by using it as the evaluation function in a genetic algorithm optimization of two case studies. Results show the proposed method exhibits higher robustness compared to the procedures defined in the current standard and literature. The main contributions of this study are to (1) provide a robust and accurate model to describe the slug‐feed method of disinfection, (2) offer additional resource utilization flexibility for water authorities, and (3) providing additional levels of district metered areas prioritization. Key Points: A robust, accurate, and efficient method to model the slug‐feed method of disinfectionA different disinfectant injection time can be assigned to each of the injection points when there are multiple injection pointsProviding additional levels of district metered areas prioritization and resource utilization [ABSTRACT FROM AUTHOR]

Using a system to promptly detect anomalous water quality levels in a water distribution system (WDS) is a critical task to ensure security of a public water supply. Using continuous monitoring stations placed at strategic locations throughout a WDS has shown to be an effective method to detect potential contamination or low water quality; however, the performance of these monitoring stations is highly sensitive to the specific locations at which they are placed throughout the network. As a result, a large amount of research has explored how to determine the locations at which to place monitoring stations in a WDS, which may be composed of tens of thousands of junctions and pipes. These studies have typically used explicit simulations of network hydraulics, and contamination events imposed on a water distribution system, to compare how effectively a network of monitoring stations detects simulated contamination events. Building off these previous studies, the work herein proposes a framework to place fixed monitoring stations and input inline mobile sensors to best detect contamination events under uncertain water quality conditions. An adaptive-noisy-multiobjective-messy genetic algorithm is used to efficiently determine the locations at which to place monitoring stations in two sample water distribution systems for minimum cost. Results show that monitoring stations and sensor networks designed within a demand uncertain framework outperform the solutions designed in a deterministic demand framework when evaluated under more realistic demand uncertain conditions. [ABSTRACT FROM AUTHOR]

The BATtle of the Attack Detection ALgorithms (BATADAL) is the most recent competition on planning and management of water networks undertaken within the Water Distribution Systems Analysis Symposium. The goal of the battle was to compare the performance of algorithms for the detection of cyber-physical attacks, whose frequency has increased in the last few years along with the adoption of smart water technologies. The design challenge was set for the C-Town network, a real-world, medium-sized water distribution system operated through programmable logic controllers and a supervisory control and data acquisition (SCADA) system. Participants were provided with data sets containing (simulated) SCADA observations, and challenged to design an attack detection algorithm. The effectiveness of all submitted algorithms was evaluated in terms of time-to-detection and classification accuracy. Seven teams participated in the battle and proposed a variety of successful approaches leveraging data analysis, model-based detection mechanisms, and rule checking. Results were presented at the Water Distribution Systems Analysis Symposium (World Environmental and Water Resources Congress) in Sacramento, California on May 21-25, 2017. This paper summarizes the BATADAL problem, proposed algorithms, results, and future research directions. [ABSTRACT FROM AUTHOR]

This work contributes a modeling framework to characterize the effect of cyber-physical attacks (CPAs) on the hydraulic behavior of water distribution systems. The framework consists of an attack model and a MATLAB toolbox named epanetCPA. The former identifies the components of the cyber infrastructure (e.g., sensors or programmable logic controllers) that are potentially vulnerable to attacks, whereas the latter allows determining the exact specifications of an attack (e.g., timing or duration) and simulating it with EPANET. The framework is applied to C-Town network for a broad range of illustrative attack scenarios. Results show that the hydraulic response of the network to a cyber-physical attack depends not only on the attack specifications, but also on the system initial conditions and demand at the junctions. It is also found that the same hydraulic response can be obtained by implementing completely different attacks. This has some important implications on the design of attack detection mechanisms, which should identify anomalous behaviors in a water network as well as the cyber components being hacked. Finally, the manuscript presents some ideas regarding the next steps needed to thoroughly assess the risk of cyber attacks on water distribution systems. [ABSTRACT FROM AUTHOR]

This work presents an algorithm for water distribution systems water age clustering. The objective is to cluster a distribution system into water age sub-zones whose water age variability is minimized within each cluster. The algorithm stages are: (1) water age computation for each system node, (2) kick-off at a number of clusters equal to the number of nodes (i.e., each node initially acts as a cluster), (3) search for the two connected (by link) clusters which have the smallest absolute water age difference, and combine them into a single cluster; characterize their water age value as the weighted arithmetic mean of the two clusters, and (4) repeat step 3 until all nodes are lumped into a single cluster (i.e., the entire water distribution system). The algorithm thus spans all possible clusters starting from the total number of system nodes and up to a one cluster which holds the entire system layout. The model, through a clustering numbering trade-off, is demonstrated on a mid-size water distribution system. [ABSTRACT FROM AUTHOR]

Incorporating a system of monitoring stations to insure high quality water is being delivered to consumers has been acknowledged a crucial component required by any public water distribution system (WDS). Extensive studies have acknowledged the risk posed to large populations by an accidental or intentional contamination intrusion within a WDS; failure of an early warning system (EWS) to report a contamination event carries profound economic and public health consequences. Dynamic, stochastic conditions exist in municipal WDSs and a monitoring system needs to be designed according to a robust protocol that incorporates the inherent uncertainty in WDS operation, including: demand variability, and contamination event characteristic variability. This work composes the problem of locating the best junctions within a WDS to place fixed monitoring stations, and the best junctions to input innovative inline mobile sensors, in a multi-objective framework that incorporates uncertainty in the network's demands and EWS operation. Mobile sensors are carried by flow within pipes sampling and monitoring water quality in real time, and wirelessly uploading data to fixed transceiver beacons, providing an implicit preference towards demand dense regions. A multi-objective noisy messy genetic algorithm is structured to the problem at hand and employed on a small, medium, and large-scale model WDS to calculate near-optimal solutions from the large solutions space. This multi-objective framework provides high performing trade off (Pareto) sets comparing an EWS's system cost to numerous performance objectives incorporating non-deterministic objective functions to provide a high performing and resilient EWS. Results show a large trade off surface between the cost and the respective system's performance, with large diminishing returns. Although implementing a more expensive solution may provide little to no benefit from a traditional performance standpoint, implementing a system of higher cost can increase the systems resiliency, highlighting the importance of incorporating proper objective measures in optimization procedure. [ABSTRACT FROM AUTHOR]

Prompt detection of intentional or accidental contamination of the public water supply is vital to maintain public health in any centralized water distribution system. Being able to quickly detect a system contamination event may be the single most influential factor to reduce possible contamination fallout. Consequently, major research has explored how to best protect a water distribution system (WDS) through strategic placement of fixed water quality monitoring stations. Although fixed monitoring stations within a wireless sensor network (WSN) are robust with respect to hydraulic conditions, the stations are expensive to place, and may not provide the highest spatial and temporal resolution of contamination detection. This work sets to build the understanding of a mobile wireless sensor network (MWSN) where inline mobile sensors function within water in pipes to monitor water quality and to wirelessly transmit data to fixed transceivers in real time. Mobile sensor behavior was modeled alongside contamination simulations and the deployment of fixed and mobile sensors was together optimized to minimize the affected population prior contamination event detection constrained by a total system cost. Results show a MWSN to be highly sensitive to sensor battery life, transceiver network coverage, and total system cost. Future obstacles for implementation of a MWSN are highlighted and discussed to be address in future work. [ABSTRACT FROM AUTHOR]

Finding the optimal pump operation in water distribution systems, taking into account hydraulic and water quality constraints, is a complex problem due to the nonlinear relationship between dynamic head loss and flow rate and between chlorine decay and water age, and due to the size of the problem. The proposed algorithm, for minimum cost pump scheduling, utilizes the operational graph algorithm applied to hydraulic and quality constraints. The proposed algorithm utilizes a graph algorithm that considers hydraulic and water quality constraints to find the pump scheduling that minimizes pump operational costs. The algorithm has short solution times and therefore is suitable for real-time water system control or, if used offline, for giving a recommendation on the pump operation taking into account hydraulic and water quality constraints. The algorithm results were compared with the best results found by enumeration to show that the operational graph algorithm returns a global minimal solution and, when combined with quality constraints, returns near-optimal results. The proposed algorithm was successfully demonstrated on a 24-h example application with a single pumping unit and, on the C-Town example application, with 11 pumping units and 168 time steps. [ABSTRACT FROM AUTHOR]

Least-cost operation of water distribution systems (WDS) is a well-known problem in water distribution systems optimization. The formulation of the problem started with deterministic modeling, and the problem was subsequently handled with more sophisticated stochastic models that incorporate uncertainties related to the problem’s parameters. This work applied a recently developed algorithm entitled limited multistage stochastic programming (LMSP) to deal with the stochastic formulation of the least-cost operation of WDS and serves merely as a proof of concept on an illustrative network. The demand is considered as the uncertain parameter in the problem formulation. This algorithm reduces the complexity of the classical multistage stochastic programming (MSP) by adding constraints which result in a linear growth of the problem, as opposed to an exponential growth in the MSP problem. This is accomplished by clustering decision variables based on a postanalysis of the implicit stochastic program of the problem. The clusters allow reduction of the number of decision variables, thus reducing the complexity of the optimization problem. The LMSP is expected to increase the cost because of the additional constraints imposed on the problem; however, a trade-off exists between the computational complexity and the optimality of the objective value to the number of clusters considered. An illustrative example application is provided for demonstrating the suggested methodology abilities. [ABSTRACT FROM AUTHOR]

Least-cost design of water distribution system is a well-known problem in the literature. The formulation of the least-cost design problem started by deterministic modeling and later by more sophisticated stochastic models that incorporate uncertainties related to the problem's parameters. Recently, a new nonprobabilistic modeling, titled the robust counterpart (RC) approach, has been developed for the least-cost design problem to incorporate the uncertainty without the need for full stochastic information. These nonprobabilistic methods, developed in the field of robust optimization, were shown to be advantageous over classical stochastic methods in the following aspects: tractability and computation time, nonnecessity of full probabilistic information, and the ability to integrate correlation of uncertain parameters aspects without adding complexity. Former studies have considered the RC approach for a special case of the least-cost problem with a single load demand uncertainty, and single gravitational source to simplify the problem formulation and facilitate the use of the method. This special case does not handle the joint temporal and spatial correlations between the problem uncertainties and does not include components such as pumping stations and storage facilities. These new components require trading off capital and operation (i.e., energy) costs in the objective function, as the design cost is explicitly influenced by the demand uncertainty, unlike the situation where only capital cost is considered. In this study, the RC approach is expanded to cover the general least-cost design problem, including (1) multiload patterns, (2) pumping stations, and (3) storage facilities. The unknowns are the pipe diameters, pump and tank capacities, and the heads added by the pumping stations. The problem is solved using the cross-entropy method for several possible protection levels, which are defined by the size of the uncertainty set. The results are demonstrated on two examples to show the trade-off between cost and reliability and test the network's ability to cope with unexpected scenarios. [ABSTRACT FROM AUTHOR]

Past water distribution systems (WDS) management studies derived operation protocols to maximize WDS reliability by using residual chlorine as the sole surrogate parameter for water quality reliability. Albeit the advancement in mechanistic modeling to examine the WDS water quality, emerging water quality parameters of concern are not yet involved in solving WDS management problems. This paper attempts to overcome this limitation by developing a flexible decision-making framework -integrating EPANET-C, a mechanistic modeling tool for WDS water quality, with Analytic Hierarchy Process (AHP), a multi-criteria decision-making method - to rank the possible water quality parameter-based operating alternatives (organic matter and residual chlorine levels at the source points) for WDS. The uncertainty analysis was incorporated into the mechanistic modeling using the Monte Carlo method to realize insufficient knowledge about the complex biological and physicochemical interactions inside WDS. Six cases, each ranking the alternatives diversely, were applied to reflect the expert judgment impressions on the AHP outcomes. The consistency of the proposed decision-making framework was verified by deriving the operation protocol for two test networks by making trade-offs between the multiple and conflicting microbiological, chemical, and organoleptic quality criteria. The disinfection by-products formation control and taste and odor problems control emerged as the most critical water quality criteria determining the WDS performance under the operating alternatives examined. Altogether, the obtained results suggested the practicality of adopting a flexible operation protocol to maintain the water quality benchmarks over various plausible WDS performance scenarios, ranging from worst to best. [Display omitted] • General methodology to derive operation protocols for water distribution systems. • All-inclusive water distribution systems quality modeling considering uncertainty. • Flexible decision-making framework based on analytic hierarchy process. • Chemical and organoleptic quality criteria control the hierarchization process. • Flexible operation protocol minimizes contamination risks during operation. [ABSTRACT FROM AUTHOR]

A graph theory-based algorithm is demonstrated for optimal pump scheduling of two example application water networks. The hydraulic part of the problem is solved using a dedicated and efficient hydraulic solver. The pump scheduling part of the problem is solved using a skeletonized operational graph, representing only the basic logic operational relations existing in the network required for pump selection: the pumping units (with nominal operating costs), water tanks and clustered demand nodes. The hydraulic solver advances one time step at a time. After each time step advance, the nodes of the model are checked to see if satisfy minimum service pressure and minimum water tank level. For nodes not satisfying the service constraints, the Dijkstra's shortest path algorithm is applied to the skeletonized graph to determine the optimal pumping unit to be activated and then updating the pumps operation pattern in the model. The hydraulic solver is then reinitialized to resolve and recheck the time steps one by one. The algorithm ends when the solver reaches the last time step with all nodes meeting service constraints. The algorithm returns an optimal minimal cost pump-scheduling pattern under greater-than constraints over the examined time period, such as (1) minimal consumer service pressure, and (2) water balance closure at the water tanks. The algorithm returns discrete pump operation scheduling with minimal pump switching and minimal water age in the tanks, demonstrating short solution times (28 s to schedule 11 pumps over a 168-hour period). The algorithm may be applicable for real-time pump scheduling. Future research may include water quality constraints and variable frequency drive pump scheduling. Pump selection is based on the assumption that the optimal pump operation order is not affected by changes in the network's hydraulic conditions, such as water tank levels and location along the pump efficiency curve (assuming constant efficiency). If hydraulic conditions change the optimal activation order, then the pumps' working points must by updated after each time step solution, which is not addressed in the current work. [ABSTRACT FROM AUTHOR]

This study describes a binary integer programming model for mutually-operating fixed and mobile sensors in water distribution systems. The proposed method applies a deterministic optimization scheme for maximizing the monitored volume within network clusters. For a given budget, the model determines the ratio of mobile sensors to fixed sensors along with their placement and release strategies. Through assessing the benefit of placing each fixed sensor and the time and location of mobile sensors release, the combination of fixed and mobile sensors is determined. Utilizing mobile sensors for water quality monitoring is still in its infancy. Such sensors are equipped with self-powered sensing, sampling, data acquisition, and wireless transmission units. The model initiates with the combined operation of mobile and fixed sensors. It then explores the benefits of mobile sensors compared to fixed. The two battle of the water sensor networks (BWSN) are utilized for demonstrating the model's capabilities. Mobile sensors are found to be beneficial to water distribution system monitoring when operated in conjunction with static sensors. [ABSTRACT FROM AUTHOR]

Water distribution systems are liable to be contaminated. Depending on the nature of the contamination the cleaning process may include disinfection. The common requirement for disinfection is that the disinfectants will have a minimal contact time and a predefined minimum concentration with the pipe. The regulations consider disinfection of a single main but no specific procedures are given for larger portions of the network. This paper presents a multi-objective optimal operation plan for disinfection of water systems. The objective functions are to minimize the disinfection time and minimize the disinfectant quantities used while keeping the required regulations. [ABSTRACT FROM AUTHOR]

Certain soluble heavy metals are known to accumulate in the human body, resulting in ( inter alia ) toxicity to the kidney, liver, lungs, brain, heart and central nervous system. Water quality sensors can monitor small changes in water quality properties such as pH, TOC, turbidity, temperature, free chlorine concentration, and alkalinity. Heavy metals neither react with free chlorine nor consist of organic carbon; therefore, unless the solubility threshold is surpassed, the contaminant presence is distinguishable only by a change in the pH value. This characteristic makes the detection of heavy metal contamination events relatively tricky. In this work, a detailed aquatic chemistry multi-species model was developed within EPANET-MSX for the purpose of simulating the changes in water quality induced by cadmium contamination events. The model was applied on an example application network and the possible effects of various contamination events were explored. [ABSTRACT FROM AUTHOR]

Event detection is one of the current most challenging topics in water distribution systems analysis: how regular on-line hydraulic (e.g., pressure, flow) and water quality (e.g., pH, residual chlorine, turbidity) measurements at different network locations can be efficiently utilized to detect water quality contamination events. This study describes an integrated event detection model which combines multiple sensor stations data with network hydraulics. To date event detection modelling is likely limited to single sensor station location and dataset. Single sensor station models are detached from network hydraulics insights and as a result might be significantly exposed to false positive alarms. This work is aimed at decreasing this limitation through integrating local and spatial hydraulic data understanding into an event detection model. The spatial analysis complements the local event detection effort through discovering events with lower signatures by exploring the sensors mutual hydraulic influences. The unique contribution of this study is in incorporating hydraulic simulation information into the overall event detection process of spatially distributed sensors. The methodology is demonstrated on two example applications using base runs and sensitivity analyses. Results show a clear advantage of the suggested model over single-sensor event detection schemes. [ABSTRACT FROM AUTHOR]

• Analogy between systems biology and water supply engineering for the first time. • Novel strategy for analyzing the changes in delivered drinking water quality. • System-level understanding of the reaction mechanisms within water pipes. • Multiscale-based modeling inspired by the flux balance analysis concepts. • Achieving higher water quality and resource efficiency in water supply management. The complexity of modeling water quality variations in water distribution systems (WDS), studied for decades, stems from multiple constraints and variables involved and the complexity of the system behavior. The conventional macroscale-based WDS water quality models are founded on continuum mechanics. In attempts to provide a broad picture of the multi-species interactions, these models overlook the stochasticity corresponding to the reaction mechanisms within the WDS domain. Furthermore, owing to the black-box type modeling adopted in simulating the multi-species interactions, the existing state-of-the-art models have limitations in representing intermediates and/or by-products formation. Accordingly, they remain ineffective in describing the water chemistry-stoichiometric interactions within the WDS domain. Only a radically new modeling approach could overcome the limitations of the macroscale-based approaches and enables analyzing the stochastic WDS mechanisms by keeping the true nature of the system behavior. Stimulated by the metabolic network modeling principles in systems biology, this article outlines the prospect of developing an innovative 'water'bolic network modeling approach to provide a new outlook to the existing WDS water quality modeling research. [Display omitted] [ABSTRACT FROM AUTHOR]

Despite their potential catastrophic impact, transients are often ignored or presented ad hoc when designing water distribution systems. To address this problem, we introduce a new piece-wise function fitting model that is integrated with mixed integer programming to optimally place and size surge tanks for transient control. The key features of the algorithm are a model-driven discretization of the search space, a linear approximation nonsmooth system response surface to transients, and a mixed integer linear programming optimization. Results indicate that high quality solutions can be obtained within a reasonable number of function evaluations and demonstrate the computational effectiveness of the approach through two case studies. The work investigates one type of surge control devices (closed surge tank) for a specified set of transient events. The performance of the algorithm relies on the assumption that there exists a smooth relationship between the objective function and tank size. Results indicate the potential of the approach for the optimal surge control design in water systems. [ABSTRACT FROM AUTHOR]

The problem of contamination event detection in water distribution systems has become one of the most challenging research topics in water distribution systems analysis. Current attempts for event detection utilize a variety of approaches including statistical, heuristics, machine learning, and optimization methods. Several existing event detection systems share a common feature in which alarms are obtained separately for each of the water quality indicators. Unifying those single alarms from different indicators is usually performed by means of simple heuristics. A salient feature of the current developed approach is using a statistically oriented model for discrete choice prediction which is estimated using the maximum likelihood method for integrating the single alarms. The discrete choice model is jointly calibrated with other components of the event detection system framework in a training data set using genetic algorithms. The fusing process of each indicator probabilities, which is left out of focus in many existing event detection system models, is confirmed to be a crucial part of the system which could be modelled by exploiting a discrete choice model for improving its performance. The developed methodology is tested on real water quality data, showing improved performances in decreasing the number of false positive alarms and in its ability to detect events with higher probabilities, compared to previous studies. [ABSTRACT FROM AUTHOR]

Abstract: This study describes a new methodology for the disinfection booster design, placement, and operation problem in water distribution systems. Disinfectant residuals, which are in most cases chlorine residuals, are assumed to be sufficient to prevent growth of pathogenic bacteria, yet low enough to avoid taste and odor problems. Commonly, large quantities of disinfectants are released at the sources outlets for preserving minimum residual disinfectant concentrations throughout the network. Such an approach can cause taste and odor problems near the disinfectant injection locations, but more important hazardous excessive disinfectant by-product formations (DBPs) at the far network ends, of which some may be carcinogenic. To cope with these deficiencies booster chlorination stations were suggested to be placed at the distribution system itself and not just at the sources, motivating considerable research in recent years on placement, design, and operation of booster chlorination stations in water distribution systems. The model formulated and solved herein is aimed at setting the required chlorination dose of the boosters for delivering water at acceptable residual chlorine and TTHM concentrations for minimizing the overall cost of booster placement, construction, and operation under extended period hydraulic simulation conditions through utilizing a multi-species approach. The developed methodology links a genetic algorithm with EPANET-MSX, and is demonstrated through base runs and sensitivity analyses on a network example application. Two approaches are suggested for dealing with water quality initial conditions and species periodicity: (1) repetitive cyclical simulation (RCS), and (2) cyclical constrained species (CCS). RCS was found to be more robust but with longer computational time. [Copyright &y& Elsevier]

Abstract: The presented study features an event detection model alerting for contamination events in water distribution systems. The developed model comprises a minimum volume ellipsoid (MVE) classifier, detecting outlier measurements, and a following sequence analysis utilizing the MVE binary output, for the classification of events. The model is updated continuously and exploits a constantly growing data base. The MVE enables simultaneous analysis of the water quality parameters. The multivariate analysis explores the relations between water quality parameters and detects changes in their common patterns. The suggested model applied an un-supervised classification method, eliminates the need for simulated events examples in the classifier construction. In the absent of satisfying information regarding the influence of contamination event on the parameter measurements, eliminating the use of any assumption contributes to the model reliability and generality. The model was trained on a real water utility data, and tested on randomly simulated events that were superimposed on the original data base. The model showed high accuracy and detection ability compared to previous studies. [Copyright &y& Elsevier]

The Battle of the Water Networks II (BWN-II) is the latest of a series of competitions related to the design and operation of water distribution systems (WDSs) undertaken within the Water Distribution Systems Analysis (WDSA) Symposium series. The BWN-II problem specification involved a broadly defined design and operation problem for an existing network that has to be upgraded for increased future demands, and the addition of a new development area. The design decisions involved addition of new and parallel pipes, storage, operational controls for pumps and valves, and sizing of backup power supply. Design criteria involved hydraulic, water quality, reliability, and environmental performance measures. Fourteen teams participated in the Battle and presented their results at the 14th Water Distribution Systems Analysis conference in Adelaide, Australia, September 2012. This paper summarizes the approaches used by the participants and the results they obtained. Given the complexity of the BWN-II problem and the innovative methods required to deal with the multiobjective, high dimensional and computationally demanding nature of the problem, this paper represents a snap-shot of state of the art methods for the design and operation of water distribution systems. A general finding of this paper is that there is benefit in using a combination of heuristic engineering experience and sophisticated optimization algorithms when tackling complex real-world water distribution system design problems. [ABSTRACT FROM AUTHOR]