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• ISGWM can describe the processes of surface water and groundwater accurately. • ISGWM coupled the optimal allocation and scheduling model. • Ecological water supply to regulate PWTD concentrated in flood season (Jul.-Oct.). • Agricultural water supply and PWTD both influenced by the uniformity of inflow. • Groundwater exploitation controlled difference between PWTD and target below 1 m. Balancing the water consumption of agricultural and ecological is the key point of sustainable social and economic development in an inland river basin. The growth of desert riparian forests in inland river basins mainly depends on a certain phreatic water table depth (PWTD). The main object of this study was to allocate and schedule water resources to regulate the PWTD and satisfy agricultural water demand. Therefore, a multi-objective double layer optimal allocation and scheduling framework based on the computationally efficient integrated surface water-groundwater model (ISGWM), which can simulate the surface water processes, groundwater recharge and discharge processes, and PWTD changes, was constructed and applied to the mainstream of Tarim River Basin (TRB). The top layer model of the framework is an optimal ecological water allocation model, and its optimal allocation results are used as the initial solution of the bottom layer model. The results show that under 5 different inflow frequencies, the agricultural water shortage rate is 0, 17.38 %, 17.41 %, 14.06 %, and 19.94 %, respectively. The PWTD regulation has a great performance. After the optimal scheduling, the proportions of good growth of the control area behind the gate under different inflow frequencies were 98.18 %, 98.18 %, 98.18 %, 90.91 %, and 94.55 %. Agricultural water shortage is mainly due to the non-uniformity distribution of intra-annual inflow and the lack of controlling hydraulic engineering. The regulation of PWTD can guarantee the growth of desert riparian forests on both sides of the mainstream of TRB. Besides, we explored the feasibility of exploiting groundwater to supplement agricultural water consumption. The groundwater exploitation should be controlled within the scope of not causing excessive increase of PWTD (difference between PWTD and target depth <1 m), due to the groundwater exploitation to supplement agricultural water will lead to the increase of PWTD. Overall, this framework, which regulates the PWTD with the change of ecological water supply based on the ISGWM , provides a new idea for the allocation and scheduling of agricultural and ecological water resources in arid inland river basins. It also provides a new method for the coupled cooperative operation of surface water and groundwater. [Display omitted] [ABSTRACT FROM AUTHOR]

• Abundances of ARGs and ARPs decreased with latitude increment. • The groundwater on the Tibetan Plateau was the nonnegligible reservoir of LARGs. • ARPs were the supercarriers of ARGs in groundwater on the Tibetan Plateau. • Co-localization of ARGs and MGEs on MAGs were revealed. • Driving forces for ARGs and ARPs were investigated. Groundwater on the Tibetan Plateau is a critical water resource to people in Asia. However, its prevalence of antibiotic-resistant pathogens (ARPs), bacterial resistome and their driving factors remain unknown. Using metagenomics analysis, a hotspot of antibiotic-resistance genes (ARGs) and last-resort ARGs (LARGs) with a total of 639 subtypes was identified in the groundwater. Importantly, 164 metagenome-assembled genomes (MAGs) which possessed both ARGs and virulence factors (VFs) were assigned as potential ARPs, with the most abundant species being Acinetobacter johnsonii and Acinetobacter pittii. A total of 157 potential ARPs, involving Escherichia coli, were predicted as "natural" ARGs supercarriers. Thirty-six ARPs dominated by the genus Acinetobacter and Pseudomonas were found to harbour LARGs. Co-localizations of the ARG-mobile genetic elements (MGEs) showed that MGEs were significantly associated with ARGs in the ARPs, which suggests ARPs play a prominent role in ARG dissemination. Notably, latitudinal gradient is a driving factor in the occurrence of ARGs and ARPs. The average abundances of ARGs and ARP decreased as the latitude increased, with the highest abundance occurring in the region between 28.6◦N and 29.5◦N. MetaCompare further revealed health risks associated with the resistome decreased as the latitudes increased. These findings indicated different health risks associated with ARPs and bacterial resistome in latitudinal gradient groundwater. They raise the concerns of mitigating ARPs risk in groundwater on the Tibetan Plateau. [Display omitted] [ABSTRACT FROM AUTHOR]

• A Fc-based metal-organic framework (Fe-DFc) with dual synergistic sites was prepared. • The Fe-O 6 moiety in Fe-DFc exhibited high selectivity for As(Ⅲ) over competing ions. • The Fc moiety in Fe-DFc promoted the conversion of As(Ⅲ) to less toxicity As(Ⅴ). • The synergy of the two moieties in Fe-DFc removed As(Ⅲ) with low energy consumption. • The system based on Fe-DFc effectively removed As(Ⅲ) from actual bore water. The effective removal of trace levels of the highly toxic arsenite (As(Ⅲ)) from groundwater is crucial to address the threat to drinking water supply. Herein, we developed an electrochemical separation system utilizing redox-active ferrocene-based metal-organic frameworks (termed Fe-DFc) for selective removal of As(III). This system leveraged 1,1′-ferrocenedicarboxylic acid as a ligand coordinated with iron, enabling the highly selective capture and conversion of As(III) from groundwater. The Fe-DFc electrode-based electrochemical system not only effectively removed As(III) even in the presence of a 1250-fold excess of competing electrolytes, but also converted about 96 % of the adsorbed As(III) into the less toxic As(V), surpassing the results of those documented in the current literature. X-ray absorption fine structure analysis and density functional theory calculations demonstrated that the high selectivity of Fe-O 6 moiety and the exceptional redox activity of Fc synergistically contributed to the efficient removal of As(III). Moreover, the electrochemical separation system enabled the remediation of arsenic-contaminated groundwater at a low energy cost of 0.033 kWh m −3 during long-term operation, highlighting the application potential of the electrochemical technology for arsenic removal from contaminated water. [Display omitted] [ABSTRACT FROM AUTHOR]

• Water residence time shapes the composition of dissolved organic matter in lakes. • Dissolved organic matter found in winter has a more terrestrial signature. • Aquatically produced organic matter is more abundant in warmer months. • Sites with longer water residence time are more temporally stable. • Granular activated carbon effectively removes aquatically produced organic matter. Freshwater ecosystems are critical resources for drinking water. In recent decades, dissolved organic matter (DOM) inputs into aquatic systems have increased significantly, particularly in central and northern Europe, due to climatic and anthropogenic drivers. The associated increase in dissolved organic carbon (DOC) concentration can change lake ecosystem services and adversely affect drinking water treatment processes. In this study, we examined spatial and temporal patterns of DOM treatability with granular activated carbon (GAC) and biological reactivity based on 14-day bacterial respiration incubations at 11 sites across Mälaren during six-time points between July 2019 and February 2021. Mälaren is the third largest lake in Sweden and provides drinking water for over 2 million people including the capital city Stockholm. In our spatio-temporal analysis, we assessed the influence of phytoplankton abundance, water chemistry, runoff, and climate on DOM composition, GAC removal efficiency, and biological reactivity. Variations in DOM composition were characterized using optical measurements and Orbitrap mass spectrometry. Multivariate statistical analyses indicated that DOM produced during warmer months was easier to remove by GAC. Removal efficiency of GAC varied from 41 to 87 %, and the best predictor of treatability using mass spectrometry was double bond equivalents (DBE), while the best optical predictors were specific UV absorbance (SUVA), and freshness index. The oxygen consumption rate (k) from the bacterial respiration incubations ranged from 0.04 to 0.71 d−1 and higher in warmer months and at deeper basins and was associated with more aliphatic and fresh DOM. The three deepest lake basins with the longest water residence time (WRT) were temporally the most stable in terms of DOM composition and had the highest DOC removal efficiency and k rates. DOM composition in these three lake basins was optically clearer than in basins located closer to terrestrial inputs and had a signature suggesting it was derived from in-lake processes including phytoplankton production and bacterial processing of terrestrial DOM. This means that with increasing WRT, DOM derived from terrestrial sources shifts to more aquatically produced DOM and becomes easier to remove with GAC. These findings indicate WRT can be highly relevant in shaping DOM composition and thereby likely to affect its ease of treatability for drinking water purposes. [Display omitted] [ABSTRACT FROM AUTHOR]

• The demosaiced RGB imagery can improve the estimation of E. coli spatial patterns. • The quantile-based data splitting improved modeling of Imbalanced E. coli datasets. • The visible blue intensity and air temperature were the most influential inputs. The rapid and efficient quantification of Escherichia coli concentrations is crucial for monitoring water quality. Remote sensing techniques and machine learning algorithms have been used to detect E. coli in water and estimate its concentrations. The application of these approaches, however, is challenged by limited sample availability and unbalanced water quality datasets. In this study, we estimated the E. coli concentration in an irrigation pond in Maryland, USA, during the summer season using demosaiced natural color (red, green, and blue: RGB) imagery in the visible and infrared spectral ranges, and a set of 14 water quality parameters. We did this by deploying four machine learning models – Random Forest (RF), Gradient Boosting Machine (GBM), Extreme Gradient Boosting (XGB), and K-nearest Neighbor (KNN) – under three data utilization scenarios: water quality parameters only, combined water quality and small unmanned aircraft system (sUAS)-based RGB data, and RGB data only. To select the training and test datasets, we applied two data-splitting methods: ordinary and quantile data splitting. These methods provided a constant splitting ratio in each decile of the E. coli concentration distribution. Quantile data splitting resulted in better model performance metrics and smaller differences between the metrics for both the training and testing datasets. When trained with quantile data splitting after hyperparameter optimization, models RF, GBM, and XGB had R 2 values above 0.847 for the training dataset and above 0.689 for the test dataset. The combination of water quality and RGB imagery data resulted in a higher R 2 value (>0.896) for the test dataset. Shapley additive explanations (SHAP) of the relative importance of variables revealed that the visible blue spectrum intensity and water temperature were the most influential parameters in the RF model. Demosaiced RGB imagery served as a useful predictor of E. coli concentration in the studied irrigation pond [Display omitted] [ABSTRACT FROM AUTHOR]

• In microbial risk analysis, model inputs are typically assumed to be independent. • Incorrect independence assumptions can lead to under- or over-estimation of risk. • Input (in)dependence assumptions can affect decision-making. • Evaluation of effects of input independence on risk requires case-specific analysis. • Independence assumptions on drinking water QMRA can be assessed with new framework. When assessing risk posed by waterborne pathogens in drinking water, it is common to use Monte Carlo simulations in Quantitative Microbial Risk Assessment (QMRA). This method accounts for the variables that affect risk and their different values in a given system. A common underlying assumption in such analyses is that all random variables are independent (i.e., one is not associated in any way with another). Although the independence assumption simplifies the analysis, it is not always correct. For example, treatment efficiency can depend on microbial concentrations if changes in microbial concentrations either affect treatment themselves or are associated with water quality changes that affect treatment (e.g., during/after climate shocks like extreme precipitation events or wildfires). Notably, the effects of erroneous assumptions of independence in QMRA have not been widely discussed. Due to the implications of drinking water safety decisions on public health protection, it is critical that risk models accurately reflect the context being studied to meaningfully support decision-making. This work illustrates how dependence between pathogen concentration and either treatment efficiency or water consumption can impact risk estimates using hypothetical scenarios of relevance to drinking water QMRA. It is shown that the mean and variance of risk estimates can change substantially with different degrees of correlation. Data from a water supply system in Calgary, Canada are also used to illustrate the effect of dependence on risk. Recognizing the difficulty of obtaining data to empirically assess dependence, a framework to guide evaluation of the effect of dependence is presented to enhance support for decision making. This work emphasizes the importance of acknowledging and discussing assumptions implicit to models. [Display omitted] [ABSTRACT FROM AUTHOR]

• Detection of microbial genetic material was highly variable in time and magnitude. • Wet periods showed greatest microbial sums and shortest lag times. • Dry periods showed lower microbial sums and longer lag times. • Recharge pulses represent small contributions of fast-moving groundwater. • Repeat sampling is needed to characterize microbial risk. Yearlong, event based, microbiological and chemical sampling was conducted at four public water supply well sites spanning a range of geologic settings and well depths to look for correlation between precipitation events and microbial occurrence. Near-continuous monitoring using autosamplers occurred just before, during, and after 5–7 sampling events triggered by rainfall and/or snowmelt. Microbial genetic material was noted at all four locations during all but one sampling event, but was exceedingly variable in time, where one sample would have no detections and the next sample could be a relatively high concentration. The highest microbial sums (microbial concentrations summed over an event) were observed during months in which precipitation exceeded historical averages. Extended wet conditions through the spring thaw resulted in the highest percentage of microbial positive samples, though at relatively low concentrations. Sampling events that followed drier than normal periods showed longer lag times between the onset of precipitation and microbial occurrence, as well as lower microbial detection rates. Although a general lag time pattern was observed at each site, the largest offset in time was observed at the site with the greatest depth to water. The study's temporally dense representation of drinking water pathogen characterization suggests that single event or infrequent periodic sampling of a drinking water supply cannot provide a representative characterization of the probability that pathogens are present, which likely has ramifications for calculating health risk assessments. [Display omitted] [ABSTRACT FROM AUTHOR]

Isolation valves play a primary role in water distribution networks as their operation enables isolating the part of the network undergoing planned or extraordinary maintenance, in the context of rehabilitation or pipe break repairs, respectively. This paper presents a review of the current state of the art of isolation valves, with a focus on the problems of analysis, e.g., assessment of the performance of the network in segment isolation scenarios, design of optimal valve locations, and selection criteria/methods for identification of the valves to maintain. After describing and classifying the main scientific contributions, the paper proceeds by reporting the results of a survey to water utility staff in the United States, Italy, Portugal, and Iran, aimed at analysing the current practices adopted for the positioning and maintenance of isolation valves in real case studies. The paper ends with a discussion on the analysis of scientific literature and results of on-field surveys, highlighting critical points for potential future developments, including the connection between the design and maintenance of isolation valves, the trade-off between increasing validity and reducing complexity of reliability assessment methods, and more precise modeling of isolation valves systems., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Ltd.)

Sustainable urban water management is crucial for meeting the growing demands of urban populations. This study presents a novel approach that combines time series clustering, seasonal analysis, and entropy analysis to uncover residential water consumption patterns and their drivers. Using a three-year dataset from the SmartH2o project, encompassing 374 households, we identify nine distinct water consumption patterns through time series clustering, leveraging Dynamic Time Warping (DTW) as the optimal similarity measure. Multiple linear regression reveals key household characteristics influencing water usage behaviors, such as the number of bathrooms and appliance efficiency ratings. Seasonal analysis uncovers temporal dynamics, highlighting shifts towards lower consumption during summer months and increased variability in transitional seasons. Entropy analysis quantifies the diversity and complexity of water consumption at both cluster and household levels, informing targeted interventions. This comprehensive, granular approach enables the development of personalized water conservation strategies and policies, empowering water utilities to optimize resource management and contribute to sustainable urban water practices., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

The Eastern Route of the South-to-North Water Diversion Project (ER-SNWDP) represents a crucial initiative aimed at alleviating water scarcity in China's northern region. Understanding the dynamics governing the composition and assembly processes of micro-eukaryotic communities within the canal during different water diversion periods holds paramount significance for the effective management of the ER-SNWDP. Our study systematically tracks the dynamics of the micro-eukaryotic community and its assembly processes along the 1045.4 km of canals and four impounded lakes, totaling 3455 km 2 , constituting the ER-SNWDP during a complete water diversion cycle, utilizing high-throughput sequencing, bioinformatics tools, and null modeling algorithms. The primary objectives of this study are to elucidate the spatial-temporal succession of micro-eukaryotic communities as the water diversion progresses, to delineate the relative importance of deterministic and stochastic processes in community assembly, and to identify the pivotal factors driving changes in micro-eukaryotic communities. Our findings indicate notable variations in the composition and diversity of micro-eukaryotic communities within the ER-SNWDP across different water diversion periods and geographic locations (P < 0.05). This variation is influenced by a confluence of temporal and environmental factors, with limited impacts from water diversion. In essence, the assembly of micro-eukaryotic communities within the ER-SNWDP primarily stemmed from heterogeneous selection driven by deterministic processes. Water diversion exhibited a tendency to decrease community beta diversity while augmenting the influence of stochastic processes in community assembly, albeit this effect attenuated over time. Furthermore, our analysis identified several pivotal environmental parameters, notably including nitrite-nitrogen, nitrate-nitrogen, orthophosphate, and water temperature, as exerting significant effects on micro-eukaryotic communities across different water diversion periods. Collectively, our study furnishes the inaugural comprehensive exploration of the dynamics, assembly processes, and influencing factors governing micro-eukaryotic communities within the ER-SNWDP, thus furnishing indispensable insights to inform the water quality management of this important project., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Data-driven metamodels reproduce the input-output mapping of physics-based models while significantly reducing simulation times. Such techniques are widely used in the design, control, and optimization of water distribution systems. Recent research highlights the potential of metamodels based on Graph Neural Networks as they efficiently leverage graph-structured characteristics of water distribution systems. Furthermore, these metamodels possess inductive biases that facilitate generalization to unseen topologies. Transferable metamodels are particularly advantageous for problems that require an efficient evaluation of many alternative layouts or when training data is scarce. However, the transferability of metamodels based on GNNs remains limited, due to the lack of representation of physical processes that occur on edge level, i.e. pipes. To address this limitation, our work introduces Edge-Based Graph Neural Networks, which extend the set of inductive biases and represent link-level processes in more detail than traditional Graph Neural Networks. Such an architecture is theoretically related to the constraints of mass conservation at the junctions. To verify our approach, we test the suitability of the edge-based network to estimate pipe flowrates and nodal pressures emulating steady-state EPANET simulations. We first compare the effectiveness of the metamodels on several benchmark water distribution systems against Graph Neural Networks. Then, we explore transferability by evaluating the performance on unseen systems. For each configuration, we calculate model performance metrics, such as coefficient of determination and speed-up with respect to the original numerical model. Our results show that the proposed method captures the pipe-level physical processes more accurately than node-based models. When tested on unseen water networks with a similar distribution of demands, our model retains a good generalization performance with a coefficient of determination of up to 0.98 for flowrates and up to 0.95 for predicted heads. Further developments could include simultaneous derivation of pressures and flowrates., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Against the backdrop of severe leakage issue in water distribution systems (WDSs), numerous researchers have focused on the development of deep learning-based acoustic leak detection technologies. However, these studies often prioritize model development while neglecting the importance of data. This research explores the impact of data augmentation techniques on enhancing deep learning-based acoustic leak detection methods. Five random transformation-based methods-jittering, scaling, warping, iterated amplitude adjusted Fourier transform (IAAFT), and masking-are proposed. Jittering, scaling, warping, and IAAFT directly process original signals, while masking operating on time-frequency spectrograms. Acoustic signals from a real-world WDS are augmented, and the efficacy is validated using convolutional neural network classifiers to identify the spectrograms of acoustic signals. Results indicate the importance of implementing data augmentation before data splitting to prevent data leakage and overly optimistic outcomes. Among the techniques, IAAFT stands out, significantly increasing data volume and diversity, improving recognition accuracy by over 7%. Masking enhances performance mainly by compelling the classifier to learn global features of the spectrograms. Sequential application of IAAFT and masking further strengthens leak detection performance. Furthermore, when applying a complex model to acoustic leakage detection through transfer learning, data augmentation can also enhance the effectiveness of transfer learning. These findings advance artificial intelligence-driven acoustic leak detection technology from a data-centric perspective towards more mature applications., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Yipeng Wu reports financial support was provided by National Natural Science Foundation of China. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Ltd.)

Metals in the drinking water distribution system (DWDS) play an important role on the fate of disinfection by-products (DBPs). They can increase the formation of DBPs through several mechanisms, such as enhancing the proportion of reactive halogen species (RHS), catalysing the reaction between natural organic matter (NOM) and RHS through complexation, or by increasing the conversion of NOM into DBP precursors. This review comprehensively summarizes these complex processes, focusing on the most important metals (copper, iron, manganese) in DWDS and their impact on various DBPs. It organizes the dispersed 'metals-DBPs' experimental results into an easily accessible content structure and presents their underlying common or unique mechanisms. Furthermore, the practically valuable application directions of these research findings were analysed, including the toxicity changes of DBPs in DWDS under the influence of metals and the potential enhancement of generalization in DBP model research by the introduction of metals. Overall, this review revealed that the metal environment within DWDS is a crucial factor influencing DBP levels in tap water., Competing Interests: Declaration of competing interest The authors declared that they have no conflicts of interest to this work. We declare that we do not have any commercial or associative interest that represents a conflict of interest in connection with the work submitted., (Copyright © 2024. Published by Elsevier Ltd.)

Aeration is used globally as a remediation method for lakes and reservoirs with methods generally falling into two categories, those which preserve natural stratification (hypolimnetic aeration; HA) and those which destratify reservoirs through mixing of the water column (destratification aeration; DA). The United Kingdom and Australia largely focus on DA methods to manage harmful algal blooms and decrease trace metal concentrations, whereas the United States and Europe frequently focus on HA techniques to increase dissolved oxygen (DO) concentrations and decrease benthic nutrient and metal release from the sediment. A more holistic understanding of how the different techniques influence water quality in regard to raw water supply and ecosystem health should lead to more efficient treatment, reducing wasted energy and other costs during both reservoir management and the drinking-water treatment process. This study compares HA and DA on stratification, DO, and cyanobacteria concentrations in a single drinking-water supply reservoir during the 2016 summer stratification period. HA preserved stratification but could not maintain sufficient hypolimnetic DO past late April in this functionally eutrophic reservoir, establishing conditions favourable to cyanobacteria. An incipient cyanobacteria bloom formed that was subsequently dispersed after DA was initiated on May 05. Continuous monitoring revealed the formation of these issues in real-time and informed a switch from HA to DA, thereby allowing for a pro-active rather than reactive approach to reservoir management and subsequent drinking-water treatment. Both HA and DA are put forward as successful aeration strategies depending on management goals; however, performance is strongly site-specific. Such approaches are likely to become increasingly important as reservoir management tools to combat stratification-driven water quality issues under the pressing threats of anthropogenic activity and climate change., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: David Austin reports financial support was provided by Jacobs Engineering Group. David Austin reports a relationship with Tampa Bay Water that includes: consulting or advisory. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Water supply companies with reservoirs in peatland areas need to know how land use and vegetation cover in their supply catchments impact the amount and composition of aquatic organic matter in raw waters. Drinking water treatment processes remove organic matter from potable supplies, but recent increases in concentration and changes in composition have made this more difficult. This study analysed the composition of aquatic organic matter from peatland catchments in the UK and Faroe Islands. Both dissolved organic matter (DOM) and particulate organic matter (POM) compositions varied spatially, but these differences were not consistent as water moved through catchments, from headwaters and peatland pools to lake and reservoir outlets. These data showed that lakes and reservoirs are acting as flocculation hotspots, processing OM, releasing carbon (C), hydrogen (H) and oxygen (O) compounds to the atmosphere, and resulting in OM with higher N content. DOM compositions could be grouped into five clusters, showing that water treatment processes can be maximised to target 'envelopes' or clusters of DOM compositions. Catchment factors such as land use, vegetation cover, percentage peat cover and catchment area are good indicators of OM compositions likely to be present in a reservoir, and can guide water companies to maximise efficiency of their raw water treatment processes., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

As global temperatures rise with climate change, the negative effects of heat on drinking water distribution systems (DWDS) are of increasing concern. High DWDS temperatures are associated with degradation of water quality through physical, chemical and microbial mechanisms. Perhaps the most pressing concern is proliferation of thermotolerant opportunistic pathogens (OPs) like Legionella pneumophila and Naegleria Fowleri. Many OPs can be controlled in DWDS by residual disinfectants such as chlorine or chloramine, but maintaining protective residuals can be challenging at high temperatures. This critical review evaluates the literature on DWDS temperature, residual disinfectant decay, and OP survival and growth with respect to high temperatures. The findings are synthesized to determine the state of knowledge and future research priorities regarding OP proliferation and control at high DWDS temperatures. Temperatures above 40 °C were reported from multiple DWDS, with a maximum of 52 °C. Substantial diurnal temperature swings from ∼30-50 °C occurred in one DWDS. Many OPs can survive or even replicate at these temperatures. However, most studies focused on just a few OP species, and substantial knowledge gaps remain regarding persistence, infectivity, and shifts in microbial community structure at high temperatures relative to lower water temperatures. Chlorine decay rates substantially increase with temperature in some waters but not in others, for reasons that are not well understood. Decay rates within real DWDS are difficult to accurately characterize, presenting practical limitations for application of temperature-dependent decay models at full scale. Chloramine decay is slower than chlorine except in the presence of nitrifiers, which are especially known to grow in DWDS in warmer seasons and climates, though the high temperature range for nitrification is unknown. Lack of knowledge about DWDS nitrifier communities may hinder development of solutions. Fundamental knowledge gaps remain which prevent understanding even the occurrence of high temperatures in DWDS, much less the overall effect on exposure risk. Potential solutions to minimize DWDS temperatures or mitigate the impacts of heat were identified, many which could be aided by proven models for predicting DWDS temperature. Industry leadership and collaboration is needed to generate practical knowledge for protecting DWDS water quality as temperatures rise., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Kirin E. Furst reports financial support was provided by National Science Foundation. Katherine E. Graham reports financial support was provided by National Science Foundation. Kadmiel B. Adusei reports financial support was provided by National Science Foundation. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Ltd.)

Legionella is an opportunistic waterborne pathogen that causes Legionnaires' disease. It poses a significant public health risk, especially to vulnerable populations in health care facilities. It is ubiquitous in manufactured water systems and is transmitted via inhalation or aspiration of aerosols/water droplets generated from water fixtures (e.g., showers and hand basins). As such, the effective management of premise plumbing systems (building water systems) in health care facilities is essential for reducing the risk of Legionnaires' disease. Chemical disinfection is a commonly used control method and chlorine-based disinfectants, including chlorine, chloramine, and chlorine dioxide, have been used for over a century. However, the effectiveness of these disinfectants in premise plumbing systems is affected by various interconnected factors that can make it challenging to maintain effective disinfection. This systematic literature review identifies all studies that have examined the factors impacting the efficacy and decay of chlorine-based disinfectant within premise plumbing systems. A total of 117 field and laboratory-based studies were identified and included in this review. A total of 20 studies directly compared the effectiveness of the different chlorine-based disinfectants. The findings from these studies ranked the typical effectiveness as follows: chloramine > chlorine dioxide > chlorine. A total of 26 factors were identified across 117 studies as influencing the efficacy and decay of disinfectants in premise plumbing systems. These factors were sorted into categories of operational factors that are changed by the operation of water devices and fixtures (such as stagnation, temperature, water velocity), evolving factors which are changed in-directly (such as disinfectant concentration, Legionella disinfectant resistance, Legionella growth, season, biofilm and microbe, protozoa, nitrification, total organic carbon(TOC), pH, dissolved oxygen(DO), hardness, ammonia, and sediment and pipe deposit) and stable factors that are not often changed(such as disinfectant type, pipe material, pipe size, pipe age, water recirculating, softener, corrosion inhibitor, automatic sensor tap, building floor, and construction activity). A factor-effect map of each of these factors and whether they have a positive or negative association with disinfection efficacy against Legionella in premise plumbing systems is presented. It was also found that evaluating the effectiveness of chlorine disinfection as a water risk management strategy is further complicated by varying disinfection resistance of Legionella species and the form of Legionella (culturable/viable but non culturable, free living/biofilm associated, intracellular replication within amoeba hosts). Future research is needed that utilises sensors and other approaches to measure these key factors (such as pH, temperature, stagnation, water age and disinfection residual) in real time throughout premise plumbing systems. This information will support the development of improved models to predict disinfection within premise plumbing systems. The findings from this study will inform the use of chlorine-based disinfection within premise plumbing systems to reduce the risk of Legionnaires disease., Competing Interests: Declaration of competing interest Hao Xi and Jason Hinds work for Enware Pty Ltd, Caringbah, NSW, Australia, a manufacturer of specialist plumbing and safety products. All other authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Introduction: The digital transition is meant as the review of processes using digital technologies and strategies to increase efficiency based on a simpler collection of representative data. The process of interest here is the leakage management in systems distributing water., Objective: To develop a novel key performance indicator (KPI) for leakage management considering the needs of ongoing digital transition in the water sector, which is opening a new era in the management of drinking water infrastructures., Methodology: The novel KPI, named Asset Management Support Indicator, is developed starting from advanced hydraulic modelling and the physical laws governing leakage outflows, in order to be physically based and rational for increasing the efficiency of leakage management activities using representative process data., Results: The Asset Management Support Indicator supports effective leakage management strategies by driving towards efficiency, as discussed and demonstrated using several real case studies., Conclusion: The novel indicator is consistent with the digital transition perspective and current need of increasing the efficiency of water utilities, and it is also suitable to be adopted by water authorities to benchmark their performances, because it overcomes the weaknesses of traditional KPIs., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

• The aim of this study was to identify the effective approaches for aqueduct rejuvenation in arid and semi-arid regions. • Water governance reform policies are the most important strategies to revive aqueducts. • The lack of monetary assistance is a notable factor in the decline of aqueducts. • It is necessary to create an independent institution to revive the aqueducts. • Policymakers should focus on macro and institutional strategies related to the restoration of aqueducts. In semi-arid and arid regions, qanats are a vital water source for agricultural needs. However, many communities are abandoning these traditional and sustainable water supply systems in favor of modern and more productive methods. Consequently, this research aimed to identify the most effective approaches for rejuvenating qanats in the dry and semi-arid areas of Razavi Khorasan province, Iran. To accomplish this goal, a comprehensive strategy was employed by merging the Strengths, Weaknesses, Opportunities, and Threats (SWOT, Best-Worst Method (BWM), and the Weighted Aggregated Sum Product Assessment (WASPAS).Based on interviews with experts in water resources and SWOT analysis, 27 factors affecting the restoration of qanats were identified and weighted with BWM. The results of BWM-WASPAS highlight the crucial role of a holistic approach in reviving qanats. The study findings reveal that the highest scores were obtained by the strategies reforming water governance policies to prioritize sustainable indigenous water resources (SO1) and establish an independent institution for qanat restoration (WT7). Conversely, educational (ST1), informational (SO3), and research (WO4) strategies concerning the revival of qanats were categorized as intermediate priorities. Lastly, strategies associated with farm-level support policies were assigned lower priorities. Accordingly, it is recommended that policymakers in Mashhad give priority to macro-level and institutional policies concerning qanat restoration, considering the current state of indigenous water resources. Additionally, a continued emphasis on research policies and farm-level initiatives is advised. [Display omitted] [ABSTRACT FROM AUTHOR]

• Taste&Odor-producing actinobacteria has been overlooked in drinking water reservoirs. • The diversity of actinobacterial communities were significantly different in geographical space. • Stochastic processes determined the assembly process of actinobacterial communities. • Actinobacteria spores remained germination and growth under nutrient scarcity. • Actinobacteria exhibited odor-producing potential capacity in drinking water. The presence of actinobacteria in reservoirs can lead to taste and odor issues, posing potential risks to the safety of drinking water supply. However, the response of actinobacterial communities to environmental factors in drinking water reservoirs remains largely unexplored. To address this gap, this study investigated the community structure and metabolic characteristics of odor-producing actinobacteria in water reservoirs across northern and southern China. The findings revealed differences in the actinobacterial composition across the reservoirs, with Mycobacterium sp. and Candidatus Nanopelagicus being the most prevalent genera. Notably, water temperature, nutrient levels, and metal concentrations were associated with differences in actinobacterial communities, with stochastic processes playing a major role in shaping the community assembly. In addition, three strains of odor-producing actinobacteria were cultured in raw reservoir water, namely Streptomyces antibioticus LJH21, Streptomyces sp. ZEU13, and Streptomyces sp. PQK19, with peak ATP concentrations of 51 nmol/L, 66 nmol/L, and 70 nmol/L, respectively, indicating that odor-producing actinobacteria could remain metabolically active under poor nutrient pressure. Additionally, Streptomyces antibioticus LJH21 produced the highest concentration of geosmin at 24.4 ng/L. These findings enhance our understanding of regional variances and reproductive metabolic mechanisms of actinobacteria in drinking water reservoirs, providing a solid foundation for improving drinking water quality control, especially for taste and odor. [Display omitted] [ABSTRACT FROM AUTHOR]

• A novel approach is proposed for evaluating future intra-basin water resources. • Under the SSP2–4.5 scenario, the MRBM is projected to face water scarcity by 2050. • Population and land use imbalance upstream/downstream reduce the PWR by 37 % and 69 %. • Precipitation, ET, population, agricultural land, and PWR increase downstream. • The upstream areas are expected to have greater PWR per capita and agriculture area. The Major River Basins in Madagascar (MRBM) play a crucial role in providing water to the Malagasy population as well as the ecosystem. Little is known about the impact of climate change on these basins, and it is not clear what factors have the most significant impact on them. There are two central objectives of this study: 1. To assess the future potential water available for daily life and agriculture use across the MRBM. 2. To compare the projected change within the MRBM with the historical trends analysis and identify the water-stressed basins. In this paper, a new method for assessing the future available Intra-basin water resources combined with the impacts of climate change, land use, and population is proposed. Three imbalance indicators are introduced to quantify the spatial availability (indicator N°1), distribution (indicator N°2), and variability (indicator N°3) of the Potential Water Resources (PWR) available and have been applied to the MRBM. Under the SSP2–4.5 scenario, results showed a decreasing trend of the PWR in most of the basins by 2050 with a rise in evapotranspiration and a decline in precipitation. The increasing trend and uneven distribution of the population and agricultural land upstream/downstream are found to cause the reduction of the PWR available per capita (by 37 %) and agriculture area (by 69 %) across the MRBM. This study predicts water scarcity for most of the basins by 2050, especially in the Mangoro and Onilahy Basins. Upstream populations are expected to grow in Mahajamba, Mahavavy, Betsiboka, Manambolo, Tsiribihina, Mangoro, Onilahy, Mananara, and Mandrare basins, along with an expansion of the downstream agricultural land in Sofia, Betsiboka, Manambolo, Mangoky, and Mandrare basins. These findings enhance the cause-effect relationship between climate change, land use change, population growth, and water scarcity in the MRBM. Urgent action is therefore needed for an efficient and sustainable management of these water-stressed basins. [Display omitted] [ABSTRACT FROM AUTHOR]

• Water saving would reduce the quantity of initial water rights. • Water saving decreases demand and supply of water right, shrinking market size. • Water trading would reduce water-saving quantity flowing to enterprise. • Most saved water should be allocated for groundwater and surface water replenishment. • Mechanism with water saving and trading is optimal according to system performance. In this study, a conjunctive water management model based on interval stochastic bi-level programming method (CM-ISBP) is proposed for planning water trading program as well as quantifying mutual effects of water trading and systematic water saving. CM-ISBP incorporates water resources assessment with soil and water assessment tool (SWAT), systematic water-saving simulation combined with water trading, and interval stochastic bi-level programming (ISBP) within a general framework. Systematic water saving involves irrigation water-saving technologies (sprinkler irrigation, micro-irrigation, low-pressure pipe irrigation), enterprise water-saving potential and water-saving subsidy. The CM-ISBP is applied to a real case of a water-scarce watershed (i.e. Dagu River watershed, China). Mutual effects of water trading and water-saving activities are simulated with model establishment and quantified through mechanism analysis. The fate of saved water under the systematic water saving is also revealed. The coexistence of the two systems would increase system benefits by [11.89, 12.19]%, and increase the water use efficiency by [40.04, 40.46]%. Thus mechanism that couples water trading and water saving is optimal and recommended according to system performance. [Display omitted] [ABSTRACT FROM AUTHOR]

• Power-to-X derived pure oxygen inspires opportunities to improve water resource recovery facilities' performance. • Pure oxygen aeration and ozone effluent treatment provide answers to emerging EU regulations. • 'Power-to-X for Water Resource Recovery Facilities' introduces water-energy intersectional circular sustainability. The wastewater industry and the energy system are undergoing significant transformations to address climate change and environmental pollution. Green hydrogen, which will be mainly obtained from renewable electricity water electrolysis (Power-to-Hydrogen, PtH), has been considered as an essential energy carrier to neutralize the fluctuations of renewable energy sources. PtH, or Power-to-X (PtX), has been allocated to multiple sectors, including industry, transport and power generation. However, considering its large potential for implementation in the wastewater sector, represented by Water Resource Recovery Facilities (WRRFs), the PtX concept has been largely overlooked in terms of planning and policymaking. This paper proposes a concept to implement PtX at WRRFs, where sourcing of water, utilization of the oxygen by-product, and PtX itself can be sustainable and diversified strategies. Potential value chains of PtX are presented and illustrated in the frame of a WWRF benchmark simulation model, highlighting the applications of oxygen from PtX through pure oxygen aeration and ozone disinfection. Opportunities and challenges are highlighted briefly, and so is the prospective outlook to the future. Ultimately, it is concluded that 'coupling PtX to WRRFs' is a promising solution, which will potentially bring sustainable opportunities for both WRRFs and the energy system. Apart from regulatory and economic challenges, the limitations in coupling PtX to WRRFs mainly come from energy efficiency concerns and the complexity of the integration of the water framework and the energy system. [Display omitted] [ABSTRACT FROM AUTHOR]

• Densification is a novel low-cost wastewater intensification strategy. • Densification can optimize nutrient removal, settleability, and effluent quality. • Size ranges, food-to-microorganism ratio, and selector use may be optimized for densification. Densification is a novel intensification strategy with the potential to improve treatment capacity within existing continuous-flow (CF) water resource recovery facilities at low capital and operating costs and at relatively small particle sizes compared to typical aerobic granular sludge (AGS) systems. To achieve densification, biological selection principles derived from selector design and AGS concepts have been coupled with physical selection via hydrocyclones at full-scale CF facilities to promote the growth and retention of granules. This combination lowers the sludge volume index (SVI) through superior sludge settling and paves the way for optimized nutrient removal and energy efficiency in low dissolved oxygen conditions. This paper sheds light on the benefits of densification. It delves into areas of advancement to further its implementation: hydrocyclone design, selector zone design, operational guidelines, and the target range for particle sizes and granule fractions. [Display omitted] [ABSTRACT FROM AUTHOR]

• Previous groundwater intelligent models often overlook the inherent limitations. • Integrating data, humans and machines can enhance groundwater modeling. • Multisource data serves as the training basis and insight generator. • Human expertise acts as the source of intelligence and collaborative catalyst. • Machine intelligence is the cornerstone of high accuracy and efficiency. Groundwater models are essential for understanding aquifer systems behavior and effective water resources spatio-temporal distributions, yet they are often hindered by challenges related to model assumptions, parametrization, uncertainty, and computational efficiency. Machine intelligence, especially deep learning, promises a paradigm shift in overcoming these challenges. A critical examination of existing machine-driven methods reveals the inherent limitations, particularly in terms of the interpretability and the ability to generalize findings. To overcome these challenges, we develop a ternary framework that synergizes the valuable insights from multisource data, human expertise, and machine intelligence. This framework capitalizes on the distinct strengths of each element: the value and relevance of multisource data, the innovative capacity of human expertise, and the analytical efficiency of machine intelligence. Our goal is to conceptualize sustainable water management practices and enhance our understanding and predictive capabilities of groundwater systems. Unlike approaches that rely solely on abundant data, our framework emphasizes the quality and strategic use of available data, combined with human intellect and advanced computing, to overcome current limitations and pave the way for more realistic groundwater simulations. [Display omitted] [ABSTRACT FROM AUTHOR]

• Criteria were established for identifying suitable surrogates for water reuse. • 11 viruses, two phage, and three bacteria were monitored throughout a reuse scheme. • Virus pathogens are effectively removed throughout water reuse treatment. • PMMoV, AiV, GII NoV, AdV, FRNA GII were suggested as potential virus surrogates. • Surrogate monitoring can inform water reuse performance for public health safety. Water reuse as an alternative water supply is increasing throughout the world due to water stress and scarcity; however, there are no standard practices for monitoring virus pathogens in such systems. This study aimed to identify suitable surrogates for virus fate, transport, and removal throughout a water reuse scheme. Various microbial targets (11 viruses, two phage, and three bacteria) were monitored using molecular and culture methods across all treatment stages in a wastewater reclamation facility and advanced water treatment facility. Criteria were established for identifying suitable surrogates, which included reliable detection, observable fate and transport, calculable log-reduction values (LRVs), correlations with other targets, and various morphological types. In total, five viruses (PMMoV, AiV, GII NoV, AdV, FRNA GII) met these stringent criteria and were suggested as potential virus surrogates. These surrogates enabled successful comparison of assigned versus actual LRVs throughout a water reuse scheme. Results suggest that virus pathogens are effectively removed throughout water reuse treatment and the suggested surrogates can be utilized for monitoring treatment performance and ensuring public health safety. This study provides a framework that water utilities across the world can reference for establishing virus monitoring practices. [Display omitted] [ABSTRACT FROM AUTHOR]

• Flow management changes affect water quality and phytoplankton dynamics. • Major bushfire and subsequent heavy rainfall triggered eutrophication. • Manganese associated with phytoplankton productivity (Chl- a and cyanobacteria). • Functional grouping and Q index improved water quality assessment. This study analyses over a decade (2009–2022) of monitoring data to understand the impact of hydrological characteristics on water quality and phytoplankton dynamics in Prospect Reservoir, a critical water supply for Greater Sydney, Australia, known for its excellent water quality. Water quality and phytoplankton dynamics were related to hydrodynamics, linked to flow management and the water quality of inflows. Phytoplankton biovolume increased after a prolonged drawdown and subsequent refill event, mainly driven by dinoflagellates, and corresponded to increases in total phosphorus and water temperature. The hydrological period following the 2019/2020 summer bushfires (post-bushfire) that impacted connected reservoirs, was marked by increased flow activity and nutrient loading, leading to significant shifts in the phytoplankton community. Functional group classification and ordination analysis indicated a transition from taxa typically dominant in oligotrophic conditions to meso‑eutrophic. This transition correlated with elevated nutrient levels and chlorophyll-a (Chl-a), and reduced Secchi depth and dissolved oxygen, providing evidence of eutrophication. Q index indicated good water quality post-bushfire, contrasting with a eutrophic status assessment using Chl-a. Our findings highlight the importance of analysing long-term datasets encompassing varied hydroclimatological conditions for a deeper understanding of reservoir behaviour. A comprehensive approach to water quality assessment is recommended, combining functional group classification, Q index and Chl-a measurements for effective reservoir health assessment. This research provides novel insights into the effects of disturbances such as bushfires, on water quality and phytoplankton dynamics in an underrepresented geographic region, offering valuable knowledge for managing water resources amidst growing climate variability. [Display omitted] [ABSTRACT FROM AUTHOR]

• Measurement and modelling of gas mass transfer in oxidation ditch AS reactors. • Identification and calibration of 1- & 2-phase CFD models for surface aeration. • CFD simulation model validation using full-scale DO & N 2 O liquid sensor data. • Sensitivity ranking of parameters, influencing K L a O2 ,clean and N 2 O emission. • Meta-models for K L a O2 ,clean & N 2 O emission in hybrid distributed models inferred. Biokinetic modelling of N 2 O production and emission has been extensively studied in the past fifteen years. In contrast, the physical-chemical hydrodynamics of activated sludge reactor design and operation, and their impact on N 2 O emission, is less well understood. This study addresses knowledge gaps related to the systematic identification and calibration of computational fluid dynamic (CFD) simulation models. Additionally, factors influencing reliable prediction of aeration and N 2 O emission in surface aerated oxidation ditch-type reactor types are evaluated. The calibrated model accurately predicts liquid sensor measurements obtained in the Lynetten Water Resource Recovery Facility (WRRF), Denmark. Results highlight the equal importance of design and operational boundary conditions, alongside biokinetic parameters, in predicting N 2 O emission. Insights into the limitations of calibrating gas mass-transfer processes in two-phase CFD models of surface aeration systems are evaluated. [Display omitted] [ABSTRACT FROM AUTHOR]

• Distinct microbiomes were observed between rainwater and tap-water SWSSs. • Higher relative abundances of potential pathogens noted in rainwater SWSSs. • Notable impact of tank materials only found in rainwater SWSSs. • Deterministic processes shaped the microbiomes in cement and tap-water SWSSs. • Stochastic processes dominated in PVC and steel rainwater SWSSs. Roof-harvested rainwater stored for potable and nonpotable usages represent a clean and sustainable water supply resource. However, the microbial dynamics and mechanisms of community assembly in long-termed operated rainwater storage systems remain elusive. In this study, characteristics of microbial communities in different habitats were systematically compared within rainwater and tap-water simulated storage systems (SWSSs) constructed with different tank materials (PVC, stainless steel and cement). Distinct microbial communities were observed between rainwater and tap-water SWSSs for both water and biofilm samples (ANOSIM, p < 0.05), with lower diversity indexes noted in rainwater samples. Notably, a divergent potential pathogen profile was observed between rainwater and tap-water SWSSs, with higher relative abundances of potential pathogens noted in rainwater SWSSs. Moreover, tank materials had a notable impact on microbial communities in rainwater SWSSs (ANOSIM, p < 0.05), rather than tap-water SWSSs, illustrating the distinct interplay between water chemistry and engineering factors in shaping the SWSS microbiomes. Deterministic processes contributed predominantly to the microbial community assembly in cement rainwater SWSSs and all tap-water SWSSs, which might be ascribed to the high pH levels in cement rainwater SWSSs and low-nutrient levels in all tap-water SWSSs, respectively. However, microbial communities in the PVC and stainless-steel rainwater SWSSs were mainly driven by stochastic processes. Overall, the results provided insights to the distinct microbial assembly mechanisms and potential health risks in stored roof-harvested rainwater, highlighting the importance of developing tailored microbial management strategies for the storage and utilization of rainwater. [Display omitted] [ABSTRACT FROM AUTHOR]

• The first attempt to achieve zero fouling in the UF for SWSS. • Zero fouling could be achieved at a flux of 10 L/(m2 h) without residual chlorine. • Zero fouling was ascribed to the formation of self-regulated bio-cakes. • Microorganisms could degrade the accumulated foulants and loose the cake structure. • Intermittent filtration enabled the achievement of zero fouling at higher fluxes. Ultrafiltration (UF) technology is widely used in secondary water supply systems (SWSS) to provide high-quality drinking water. However, the challenge of severe membrane fouling, which leads to frequent cleaning requirements, makes UF maintenance intensive. In this study, we tried to validate the feasibility of achieving zero fouling without the need for cleaning in the UF for SWSS, i.e., the fouling resistance can be maintained for a very long time without any increase. We operated dead-end UF systems at different fluxes, both with and without residual chlorine, and monitored the formation of fouling layers during filtration. The results demonstrated the successful achievement of zero fouling under a flux of 10 L/(m2 h) in the absence of chlorine, evidenced by no increase in transmembrane pressure for three months. This zero-fouling phenomenon was attributed to the formation of a self-regulating biofouling layer. This biofouling layer could degrade the deposited foulants and featured a loose morphology, facilitated by microbial activities in the cake layer. Although residual chlorine reduced the fouling rate by half at a flux of 30 L/(m2 h), it hindered the achievement of zero fouling at the lower flux of 10 L/(m2 h), due to its inhibitory effect on microbial activity. Intermittent operation of UF was effective in achieving zero fouling at higher fluxes (e.g., 30 L/(m2 h)). This benefit was primarily ascribed to the biodegradation of accumulated foulants and the expansion of biofouling layer during the pause of the intermittent filtration, which prompted the formation of biofouling layers with loose structure and balanced composition. To the best of our knowledge, this study is the first attempt to achieve zero fouling in UF for SWSS, and the findings may offer valuable insights for the development of cleaning-free and low-maintenance membrane processes. [Display omitted] [ABSTRACT FROM AUTHOR]

• Microbial flora in cold and produced hot boiler water was studied in 14 buildings. • Microbiotas were characterized using flow cytometry and metagenomic analysis. • Microbiomes and flow cytometric fingerprints of cold water differed from hot water. • Hot waters contained active thermophilic microbiotas able to grow at 50–60 °C. • Heating of cold water generates nutrients for growth of thermophilic microbiomes. Running cold and hot water in buildings is a widely established commodity. However, interests regarding hygiene and microbiological aspects had so far been focussed on cold water. Little attention has been given to the microbiology of domestic hot-water installations (DHWIs), except for aspects of pathogenic Legionella. World-wide, regulations consider hot (or warm) water as 'heated drinking water' that must comply (cold) drinking water (DW) standards. However, the few reports that exist indicate presence and growth of microbial flora in DHWIs, even when supplied with water with disinfectant residual. Using flow cytometric (FCM) total cell counting (TCC), FCM-fingerprinting, and 16S rRNA-gene-based metagenomic analysis, the characteristics and composition of bacterial communities in cold drinking water (DW) and hot water from associated boilers (operating at 50 – 60 °C) was studied in 14 selected inhouse DW installations located in Switzerland and Austria. A sampling strategy was applied that ensured access to the bulk water phase of both, supplied cold DW and produced hot boiler water. Generally, 1.3- to 8-fold enhanced TCCs were recorded in hot water compared to those in the supplied cold DW. FCM-fingerprints of cold and corresponding hot water from individual buildings indicated different composition of cold- and hot-water microbial floras. Also, hot waters from each of the boilers sampled had its own individual FCM-fingerprint. 16S rRNA-gene-based metagenomic analysis confirmed the marked differences in composition of microbiomes. E.g., in three neighbouring houses supplied from the same public network pipe each hot-water boiler contained its own thermophilic bacterial flora. Generally, bacterial diversity in cold DW was broad, that in hot water was restricted, with mostly thermophilic strains from the families Hydrogenophilaceae, Nitrosomonadaceae and Thermaceae dominating. Batch growth assays, consisting of cold DW heated up to 50 – 60 °C and inoculated with hot water, resulted in immediate cell growth with doubling times between 5 and 10 h. When cold DW was used as an inoculum no significant growth was observed. Even boilers supplied with UVC-treated cold DW contained an actively growing microbial flora, suggesting such hot-water systems as autonomously operating, thermophilic bioreactors. The generation of assimilable organic carbon from dissolved organic carbon due to heating appears to be the driver for growth of thermophilic microbial communities. Our report suggests that a man-made microbial ecosystem, very close to us all and of potential hygienic importance, may have been overlooked so far. Despite consumers having been exposed to microbial hot-water flora for a long time, with no major pathogens so far been associated specifically with hot-water usage (except for Legionella), the role of harmless thermophiles and their interaction with potential human pathogens able to grow at elevated temperatures in DHWIs remains to be investigated. [Display omitted] [ABSTRACT FROM AUTHOR]

Sorption-based atmospheric water harvesting (SAWH) is a promising solution for localized high-quality water production. Application of SAWH indoors offers dual benefits of on-site water generation and humidity control. This study evaluated the use of SAWH for water production in residential or office buildings, employing a portable zeolite-based SAWH device. Over the twelve-month testing period in the arid southwestern USA, the device achieved a median water yield of 3.6 L/day at a cost 30 % less than bottled water sold in the U.S. A mathematical model was developed for predicting water yield under different temperature and relative humidity (RH) conditions. Daily water yields were well fitted with the modified Langmuir model, with absolute humidity serving as the only prediction variable. Water extracted from a well-ventilated office building generally met the drinking water standards set by USEPA. However, elevated levels of dissolved organic carbon (DOC) were detected in the samples collected from the residential house (median = 32.6 mg/L), emphasizing the influence of human activities (e.g., cooking) on the emission of volatile and semi-volatile organic compounds in the air, which consequently reside in harvested water. Aldehydes and volatile fatty acids (formate, acetate) comprised roughly 50 % of the DOC found in the AWE water. A carbon fiber filter was not effective at removing these substances, highlighting the need for further research into effective treatment methods for DOC management before the safe use of AWE water. Overall, this study provides critical insights for the practical application of indoor SAWH as a decentralized source of high-quality water and emphasizes the need to identify and manage DOC for its safe use., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Chao Zeng reports financial support was provided by National Science Foundation. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

There is a risk of contamination by (pathogenic) microorganisms from the outside environment into the drinking water during maintenance or pipe breaches in the drinking water distribution system (DWDS) and, consequently, the drinking water distributed to consumers may result in possible detrimental effects on public health. Traditional time-consuming microbiological testing is, therefore, performed to confirm drinking water is not microbially contaminated. This is done by culturing methods of the faecal indicators Escherichia coli, intestinal enterococci and the technical parameters coliform bacteria and heterotrophic plate counts at 22 °C (HPC22). In this study, fast methods (adenosine triphosphate (ATP), flow cytometry, enzyme activity and qPCR) were compared as an alternative for HPC22. Using dilution series and field samples, ATP (ATP total-lab and ATP cell-mob ) and enzymatic activity (ALP-2) methods proved to be the more reliable and sensitive than flow cytometry and qPCR methods for detecting microbiological contaminations in drinking water. Significant (p < 0.05) and relatively strong correlations (R 2 = 0.61-0.76) were obtained between HPC22 and both ATP methods, enzyme activity and qPCR parameters, but relations with flow cytometry were weak (R 2 = 0.24 - 0.52). The samples taken after repairs or a calamity from the DWDS showed in general limited variation in the HPC22 count and were in most cases below the guidance level of 1,000 CFU/mL. We recommend that the best performing alternative methods, i.e. ATP total-lab and ATP cell-mob and ALP-2, should be included next to HPC22 in additional field studies to further test and compare these methods to be able to decide which fast method can replace HPC22 analysis after maintenance work in the DWDS., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Sorption-based atmospheric water harvesting holds promise for alleviating water scarcity, but current prototypes have not shown significant increases in practical yields despite efforts in the enlarged engineering scale. This is due to weakened heat and mass transfer with a packed sorbent bed. In this work, the desiccant-coated adsorbers were employed to fabricate the water harvesting device that incorporates internal fluid for cooling and heating during sorption and desorption. Featured with an internal cooling effect, practical water productivity could be improved by 1.75-9.96 times with a low desorption temperature (45-62 °C). The continuous water harvesting system could produce 0.77-3.98 L water /kg sorbent /day with a thermal energy consumption of 7.7-30.4 MJ/kg in wide climates from 20 % to 80 % RH, providing a reference for device design in the engineering view. The demonstration revealed that using natural cooling in the sorption stage has great benefits in improving water harvesting performance, which can be integrated into the building sectors or a wider range of scenarios., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Operators of water distribution systems (WDSs) need continuous and timely information on pressures and flows to ensure smooth operation and respond quickly to unexpected events. While hydraulic models provide reasonable estimates of pressures and flows in WDSs, updating model predictions with real-time sensor data provides clearer insights into true system behavior and enables more effective real-time response. Despite the growing prevalence of distributed sensing within WDSs, standard hydraulic modeling software like EPANET do not support synchronous data assimilation. This study presents a new method for state estimation in WDSs that combines a fully physically-based model of WDS hydraulics with an Extended Kalman Filter (EKF) to estimate system flows and heads based on sparse sensor measurements. To perform state estimation via EKF, a state-space model of the hydraulic system is first formulated based on the 1-D Saint-Venant equations of conservation of mass and momentum. Results demonstrate that the proposed model closely matches steady-state extended-period models simulated using EPANET. Next, through a holdout analysis it is found that fusing sensor data with EKF produces flow and head estimates that closely match ground truth flows and heads at unmonitored locations, indicating that state estimation successfully infers internal hydraulic states from sparse sensor measurements. These findings pave the way towards real-time operational models of WDSs that will enable online detection and mitigation of hazards like pipe leaks, main bursts, and hydraulic transients., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Urban water distribution networks (WDNs) have wide range and intricate topology, which include leakage, pipe burst and other abnormal states during production and operation. With the continuous development of the Internet of Things (IoT) technology in recent years, the means of monitoring the WDNs by using wireless sensor network technology has gradually received attention and extensive research. Most of the existing researches select the deployment location of sensors according to the hydraulic state of the WDNs, but the connectivity and topology between the nodes of the WDNs are not fully considered and analyzed. In this study, a new method that can integrate the topological features and hydraulic model information of the WDN is proposed to solve the problem of optimal sensor placement. First, the method preprocesses the covariance matrix of the pressure sensitivity matrix of the water distribution network by a diffusion kernel-based data prefiltering method and obtains the new network topology weights and its Laplacian matrix under the constraints of the network topology through a data-based graphical Laplacian learning method. Then, the sensor placement problem is transformed into a matrix minimum eigenvalue constraint problem by the Graph Laplace Regularization (GLR)-based method, and finally the selection of sensor nodes is accomplished by the method based on Gershgorin Disc Alignment (GDA). The proposed strategy is tested on a passive Hanoi network, an active Net 3 network, and a larger network, PA2, and is compared with some existing methods. The results show that the proposed solution achieves good performance in three different leak localization methods., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Ltd.)

Addressing urban water management challenges requires a holistic view. Sustainable approaches such as blue-green infrastructure (BGI) provide several benefits, but assessing their effectiveness demands a systemic approach. Challenges are magnified in informal areas, leading to the combination of integrated urban water management (IUWM) with BGI as a proposed solution by this research. We employed the Urban Water Use (UWU) model to assess the effectiveness index (EI) of BGI measures in view of IUWM after stakeholder consultation. The procedure in this novel assessment includes expert meetings for scenario building and resident interviews to capture the community's vision. To assess the impact of IUWM on the effectiveness of BGI measures, we proposed a simulation with BGI only and then three simulations with improvements to the water and sewage systems. The results of the EI analysis reveal a substantial improvement in the effectiveness of BGI measures through IUWM combination. Moreover, we offer insights into developing strategies for UWU model application in informal settlements, transferrable to diverse urban areas. The findings hold relevance for policymakers and urban planners, aiding informed decisions in urban water management., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Hypoxia in stratified waters greatly threatens aquatic ecology and societal development owing to enhanced nutrient discharge and increasing global temperature. Current research predominantly alleviates hypoxia by reducing dissolved oxygen (DO) consumption or conducting hypolimnetic oxygenation, yet their implementation has encountered bottlenecks. Therefore, this study explores the potential of increasing the inherent DO supplies in stratified reservoirs to mitigate hypoxia. High-frequency in situ observations and massive modeling experiments are integrated to discern the DO supply mode and the dominant driver of DO evolution. Results indicate that periodic thermodynamic conditions determine the DO supply relationships between oxygen sources (inflow carriage, reaeration, and photosynthesis) for different water layers. Thermal stratification causes the hypolimnion to rely mostly on the inflow for DO supply, leading to a fragile budget prone to hypoxia. However, episodic hydrodynamic events (turnover, wind stir, density current, and flood) can promote DO supply and inhibit hypoxia. Temperature and DO regimes are primarily driven by outflow conditions, followed by inflow and meteorology conditions. Furthermore, hypolimnetic hypoxia can be regulated by altering inflow volume, outflow volume, and outlet elevation. These findings highlight the importance of longitudinal solute exchange in DO evolution in stratified reservoirs, providing a basis for alleviating hypoxia through cascade reservoir operations., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Reconstructing transient states presents significant challenges, particularly within complex pipe networks. These challenges arise due to nonlinear behaviours, inherent uncertainties in the system, and limitations in data availability. This work proposed a novel approach employing Physics-Informed Neural Networks (PINN) to reconstruct transient states in pipe networks, even with limited sensor data. To integrate the complex topology of pipe network systems into neural networks, the method integrates the PINN framework with an efficient elastic water column (EWC) model which can be simply formulated across diverse pipe network configurations. The results showed the proposed PINN method can accurately reconstruct the pressure and flow variation at unmonitored locations, even provided with noisy data at a limited number of locations. One of its advantages lies in its ability to effectively capture extreme values that hold potential significance for pipe infrastructure, providing a promising avenue for pipe failure analysis and enhanced safety management. Laboratory experiments have also been conducted to validate the efficacy and reliability of this method, thus further underlining its potential for real-world applications., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Artificial intelligence (AI) is expected to transform many scientific disciplines, with the potential to significantly accelerate scientific discovery. This perspective calls for the development of data-centric water engineering to tackle water challenges in a changing world. Building on the historical evolution of water engineering from empirical and theoretical paradigms to the current computational paradigm, we argue that a fourth paradigm, i.e., data-centric water engineering, is emerging driven by recent AI advances. Here we define a new framework for data-centric water engineering in which data are transformed into knowledge and insight through a data pipeline powered by AI technologies. It is proposed that data-centric water engineering embraces three principles - data-first, integration and decision making. We envision that the development of data-centric water engineering needs an interdisciplinary research community, a shift in mindset and culture in the academia and water industry, and an ethical and risk framework to guide the development and application of AI. We hope this paper could inspire research and development that will accelerate the paradigm shift towards data-centric water engineering in the water sector and fundamentally transform the planning and management of water infrastructure., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Ltd.)

Urbanization increases the land surface temperature through surface mineralization, adversely affecting vegetation and enhancing the urban heat island (UHI) effect. Global climate change has intensified this warming effect with more frequent and intense heatwaves during hot seasons. While these transformations influence soil temperature, their consequences on drinking water temperature within the drinking water distribution system (DWDS) remains poorly understood. Literature proposes to increase pipe burial depths to mitigate drinking water heating during summer. In this study, we monitored drinking water temperatures in a DWDS in Montreal, Canada with deeply buried pipes (average 1.8 m) during the summer of 2022, focusing on two contrasting zones in terms of UHI and green coverage. Monitoring revealed a 8°C heating effect compared to the water treatment plant, attributed to low green coverage and anthropogenic heat. Conversely, the greener zone exhibited cooler drinking water temperatures, reaching a maximum cooling effect of 8°C as compared to the temperature at the exit of the water treatment plant. Utilizing a soil and water temperature model, we predicted drinking water temperatures within the DWDS with acceptable accuracy. Soil temperature modeling results aligned well with measured water temperatures, highlighting DWDS water temperature approaching its surrounding soil temperature fairly quickly. Despite heatwaves, no immediate correlation emerged between air temperature records and measured water temperatures, emphasizing soil temperature as a superior indicator. An increase in water age displayed no correlation with an increase in measured water temperature, underscoring the dominant influence of UHI and green coverage on water temperature. These findings highlight the cooling advantages of green spaces during summer, providing valuable insights for sustainable urban planning., Competing Interests: Declaration of competing interest The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results., (Copyright © 2024. Published by Elsevier Ltd.)

Microplastics (MPs) and Cu have been detected in drinking water distribution systems (DWDSs). Investigating MP effects on Cu adsorption by pipe scales and concomitant variations of pipe scales was critical for improving the water quality, which remained unclear to date. Therefore, polystyrene microplastics (PSMPs) were adopted for the model MPs to determine their effects on Cu fate and pipe scale stabilization, containing batch adsorption, metal speciation extraction, and Cu release experiments. Findings demonstrated that complexation and electrostatic interactions were involved in Cu adsorption on pipe scales. PSMPs contributed to Cu adsorption via increasing negative charges of pipe scales and providing additional adsorption sites for Cu, which included the carrying and component effects of free and adsorbed PSMPs, respectively. The decreased iron and manganese oxides fraction (45.57 % to 29.91 %) and increased organic fraction (48.51 % to 63.58 %) of Cu in pipe scales when PSMPs were coexisting illustrated that PSMPs had a greater affinity for Cu than pipe scales and thus influenced its mobility. Additionally, the release of Cu could be facilitated by the coexisted PSMPs, with the destabilization of pipe scales. This study was the first to exhibit that Cu fate and pipe scale stabilization were impacted by MPs, providing new insight into MP hazards in DWDSs., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

The exploration of antibiotic resistance genes (ARGs) in drinking water reservoirs is an emerging field. Using a curated database, we enhanced the ARG detection and conducted a comprehensive analysis using 2.2 Tb of deep metagenomic sequencing data to determine the distribution of ARGs across 16 drinking water reservoirs and associated environments. Our findings reveal a greater diversity of ARGs in sediments than in water, underscoring the importance of extensive background surveys. Crucial ARG carriers-specifically Acinetobacter, Pseudomonas, and Mycobacterium were identified in drinking water reservoirs. Extensive analysis of the data uncovered a considerable concern for drinking water safety, particularly in regions reliant on river sources. Mobile genetic elements have been found to contribute markedly to the propagation of ARGs. The results of this research suggest that the establishment of drinking water reservoirs for supplying raw water may be an effective strategy for alleviating the spread of water-mediated ARGs., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Chloramination is an effective strategy for eliminating pathogens from drinking water and repressing their regrowth in water distribution systems. However, the inevitable release of NH 4 + potentially promotes nitrification and associated ammonia-oxidizing bacteria (AOB) contamination. In this study, AOB (Nitrosomona eutropha) were isolated from environmental water and treated with two disinfection stages (chloramine disinfection and chloramine residues) to investigate the occurrence mechanisms of AOB in chloramination. The results showed that N. eutropha had considerable resistance to monochloramine compared to Escherichia coli, whose inactivation rate constant was 19.4-fold lower. The higher resistance was attributed to high levels of extracellular polymer substances (EPS) in AOB, which contribute to AOB surviving disinfection and entering the distribution system. In AOB response to the chloramine residues stage, the respiratory activity of N. eutropha remained at a high level after three days of continuous exposure to high chloramine residue concentrations (0.5-1.5 mg/L). Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) suggested that the mechanism of N. eutropha tolerance involved a significantly high expression of the intracellular oxidative stress-regulating (sodB, txrA) and protein-related (NE1545, NE1546) genes. Additionally, this process enhanced EPS secretion and promoted biofilm formation. Adhesion predictions based on the XDLVO theory corroborated the trend of biofilm formation. Overall, the naturally higher resistance contributed to the survival of AOB in primary disinfection; the enhanced antioxidant response of surviving N. eutropha accompanied by biofilm formation was responsible for their increased resistance to the residual chloramines., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Ltd.)

Water quality management is a pressing global concern, and an increasingly complex issue due to climate and land-use change, legacy pollution, and the persistent release of well-known and emerging contaminants from diffuse and point sources. The increasing availability of high-frequency monitoring data is leading existing, often heuristic approaches, to be judged inadequate. Water managers frequently rely on simple qualitative and/or quantitative approaches for decision-making, but a lack of tangible improvement in freshwater quality outcomes is demanding new and innovative approaches that rely more on physical process understanding, rather than precedent. In this study, we drew upon local geological, hydrogeological, and hydrological data to infer a high-level perceptual model of surface/groundwater interactions in a chalk stream in Dorset, UK. We used the perceptual model to interrogate spatial and temporal trends in historical water quality data and to construct reach-scale nutrient mass balances. Through novel representation with Sankey diagrams, the perceptual model highlighted the relative importance of different hydrological features. Surface/groundwater interactions were found to occur predominantly by spring flow. We demonstrate that river flow accretion was dominated by the Chalk aquifer despite only occupying ca. 15 % of the surface bedrock area, and that spring sources, whilst vital to dilute treated sewage inputs in baseflow conditions, were also major sources of legacy nitrate. Nutrient mass balances showed that sewage treatment works contributed ca. 13 % to soluble reactive phosphorus load, with groundwater accounting for ca. 48 %. Thus, a determinand often associated with point-source pollution was shown to be diffuse dominated in this river. The study demonstrated how a multi-disciplinary approach to water management, based on a comprehensive perceptual modelling approach, could identify hitherto unknown sources and relative contributors to freshwater pollution and allow flow and load apportionment studies to provide useful decision-support to manage nutrient pollution. The novel application of perceptual modelling tools, such as the Sankey diagram, allows different source attributions to be presented in an accessible manner, and can be readily transferred to other study areas., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Ltd.)

Water distribution networks (WDNs) experience significant water loss due to leaks, necessitating advanced water leak detection methods. However, machine learning-based acoustic method heavily relies on signal information and is limited by data scarcity and the limited diversity of available data. To address this challenge and enhance water leak detection in WDNs, this study proposes an LSTM-GAN approach. Acoustic signals are collected from WDNs to train the LSTM-GAN model, which generates synthetic leak signals to enhance the dataset. The validity of the generative method is evaluated through t-SNE and acoustic characteristics analysis. LSTM-based water leak detection models are established and compared using the original and the generated datasets to confirm the efficacy of generated samples in improving water leak detection performances. The capability of LSTM-GAN has been evaluated through different perspectives, including sensitivity analysis and model comparison. The results validate the quality and consistency of the generated acoustic signals under leak conditions. Besides, the optimal number of generated samples should be determined according to the requirements and characteristics of the leak detection task. Furthermore, the comparison between the proposed method and other acoustic generative methods demonstrates the superiority of LSTM-GAN-generated signals in enhancing the performance of leak detection models. The proposed generative method offers an innovative approach to facilitate machine learning-based leak detection models with limited data, thereby enhancing robustness., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

The presence of biofilms in drinking water distribution systems (DWDS) is responsible for water quality deterioration and a possible source of public health risks. Different factors impact the biological stability of drinking water (DW) in the distribution networks, such as the presence and concentration of nutrients, water temperature, pipe material composition, hydrodynamic conditions, and levels of disinfectant residual. This review aimed to evaluate the current state of knowledge on strategies for DW biofilm disinfection through a qualitative and quantitative analysis of the literature published over the last decade. A systematic review method was performed on the 562 journal articles identified through database searching on Web of Science and Scopus, with 85 studies selected for detailed analysis. A variety of disinfectants were identified for DW biofilm control such as chlorine, chloramine, UV irradiation, hydrogen peroxide, chlorine dioxide, ozone, and others at a lower frequency, namely, electrolyzed water, bacteriophages, silver ions, and nanoparticles. The disinfectants can impact the microbial communities within biofilms, reduce the number of culturable cells and biofilm biomass, as well as interfere with the biofilm matrix components. The maintenance of an effective residual concentration in the water guarantees long-term prevention of biofilm formation and improves the inactivation of detached biofilm-associated opportunistic pathogens. Additionally, strategies based on multi-barrier processes by optimization of primary and secondary disinfection combined with other water treatment methods improve the control of opportunistic pathogens, reduce the chlorine-tolerance of biofilm-embedded cells, as well as decrease the corrosion rate in metal-based pipelines. Most of the studies used benchtop laboratory devices for biofilm research. Even though these devices mimic the conditions found in real DWDS, future investigations on strategies for DW biofilm control should include the validity of the promising strategies against biofilms formed in real DW networks., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

In drinking water distribution systems, including premise plumbing, dissolved oxygen (DO) and free chlorine (FC) are common oxidants and ductile iron (DI) and copper (Cu) are commonly used pipe materials. Microelectrodes as a tool have been applied in previous corrosion research and were used in this study to collect quantifiable data and understand DO and FC reactivity and pH changes at the water-metal interface. Using microelectrodes, pH, DO, and FC profiles from the bulk water to near and at the surface of aged DI (154-190 d) and Cu (2 d and 86-156 d) coupons were investigated during periods of flow and stagnation (30 min). Using the measured microelectrode profiles, oxidant fluxes and apparent surface reaction rate constants were calculated to elucidate differences between DO and FC reactivity with the coupons. Microelectrodes were successfully applied to measure pH, DO, and FC profiles from the bulk water to near aged DI and Cu coupon surfaces; Cu coupons aged quickly and exhibited less reactivity at 2 d with DO and FC than aged DI coupons did after 154-190 d; and for the aged DI coupon experiments, orthophosphate presence stabilized pH profiles where without orthophosphate pH fluctuations of greater than 2 pH units occurred from the bulk water to the DI coupon surface., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Ltd.)

The efficient and sustainable supply and transport of water is a key component to any functioning civilisation making the role of urban water systems (UWS) inherently crucial to the wellbeing of its customers. However, managing water is not a simple task. Whether it is ageing infrastructure, transient flows, air cavities or low pressures; water can be lost as a result of many issues that face UWSs. The complexity of those networks grows with the high urbanisation trends and climate change making water companies and regulatory bodies in need of new solutions. So, it comes as no surprise that many researchers are invested in innovating within the water industry to ensure that the future of our water is safe. Deep reinforcement learning (DRL) has the potential to tackle complexities that used to be very challenging as it relies on deep neural networks for function approximation and representation. This technology has conquered many fields due to its impressive results and can effectively revolutionise UWS. In this article, we explain the background of DRL and the milestones of this field using a novel taxonomy of the DRL algorithms. This will be followed by with a novel review of DRL applications in the UWS which focus on water distribution networks and stormwater systems. The review will be concluded with critical insights on how DRL can benefit different aspects of urban water systems., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Ltd.)

Graph theory (GT) and complex network theory play an increasingly important role in the design, operation, and management of water distribution networks (WDNs) and these tasks were originally often heavily dependent on hydraulic models. Facing the general reality of the lack of high-precision hydraulic models in water utilities, GT has become a promising surrogate or assistive technology. However, there is a lack of a systematic review of how and where the GT techniques are applied to the field of WDNs, along with an examination of potential directions that GT can contribute to addressing WDNs' challenges. This paper presents such a review and first summarizes the graph construction methods and topological properties of WDNs, which are mathematical foundations for the application of GT in WDNs. Then, main application areas, including state estimation, performance evaluation, partitioning, optimal design, optimal sensor placement, critical components identification, and interdependent networks analysis, are identified and reviewed. GT techniques can provide acceptable results and valuable insights while having a low computational burden compared with hydraulic models. Combining GT with hydraulic model significantly enhances the performance of analysis methods. Four research challenges, namely reasonable abstraction, data availability, tailored topological indicators, and integration with Graph Neural Networks (GNNs), have been identified as key areas for advancing the application and implementation of GT in WDNs. This paper would have a positive impact on promoting the use of GT for optimal design and sustainable management of WDNs., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)