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Historically, water utilities have relied on tried-and-true practices in the design and operation of their infrastructure, tapping new resources and expanding networks as needed. However, as the effects of climate change and/or urbanization increasingly impact both water supply and demand, utilities need new, holistic planning and management approaches. Integrated planning approaches must account for changing policies, technological progress, and unique, setting-specific operating conditions. Based on this notion, an international web seminar with faculty, researchers, and students from nine universities across five continents was conducted. In the 3-month seminar, participants were split into groups and tasked with developing future-proof, sustainable water management solutions for fictitious settings with unique resource availability, climate change predictions, demographic, and socioeconomic constraints. The goal of the seminar was to combine participants' unique perspectives to tackle challenges in developing future water infrastructure, while forming lasting relationships. Water management concepts became more daring or "out-of-the-box" as the seminar progressed. Most groups opted for a holistic approach, optimizing existing infrastructure, integrating decentralized water management, furthering digitization, and fostering the adoption of innovative policy and planning strategies. To gauge their impact on the evolution of ideas, group dynamics and communication were observed throughout the seminar. As a result, the findings serve not only as a compendium of ideas and concepts for holistic design in the water sector, but also facilitate international collaboration, improve communication in cross-cultural teams or guide the development of training programs in water management for researchers, professional engineers, or water utilities. [ABSTRACT FROM AUTHOR]

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]

This document provides a summary of a special issue of the journal Water, focusing on the topic of rainwater harvesting and treatment. It discusses the benefits of rainwater harvesting, such as providing an alternative water source, reducing flood risk, and limiting pollution. The document presents various studies from different countries, covering topics such as economic feasibility, stormwater quality degradation, real-time control systems, freshwater availability, wastewater treatment, and decentralized treatment units. The studies offer valuable insights into the technical viability, economic feasibility, and environmental impact of rainwater harvesting and treatment in different contexts. The special issue includes twelve research papers that contribute to the advancement of rainwater harvesting and treatment, covering topics such as economic feasibility, water quality, design variables, and rainwater supply in greenhouse areas. These papers provide a comprehensive overview of recent advances in rainwater harvesting and treatment and offer valuable insights for readers interested in this field of 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]

Rainwater harvesting is an ancient practice currently used for flood and drought risk mitigation. It is a well-known solution with different levels of advanced technology associated with it. This study is aimed at reviewing the state of the art with regards to rainwater harvesting, treatment, and management. It focuses on the environmental and social benefits of rainwater harvesting and links them to the Sustainable Development Goals. The review identifies characteristics of laws and regulations that encourage this practice and their current limitations. It presents methodologies to design a rainwater harvesting system, describes the influence of design variables, and the impact of temporal and spatial scales on the system's performance. The manuscript also analyzes the most advanced technologies for rainwater treatment, providing insights into various processes by discussing diverse physiochemical and biological technology options that are in the early stages of development. Finally, it introduces trends and perspectives which serve to increase rainwater harvesting, water reuse, and effective management. [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]