Spatio-temporal analysis of nitrogen variations in an irrigation distribution network using reclaimed water for irrigating olive trees

With the increasing adoption of demand management strategies and water conservation practices, domestic water consumption is projected to decline in the future. The subsequent consumer-side demand reductions are expected to result in increased residence times in water distribution networks (WDNs), and thus could have negative effects on the water quality (WQ) reaching the consumers’ taps. This study evaluates the impacts of the projected decrease in residential water demands on the deterioration of the WQ in WDNs. This deterioration will likely be most prominent in the dead-end branches at the perimeters of WDNs, where the flow is characteristically low and intermittent. The assessment of WQ deterioration in the dead-end branches requires the implementation of an accurate WQ simulation model. To this end, a new Python-based software package, WUDESIM_Py, is first introduced. The WQ simulation engine in WUDESIM_Py is based on an advection-dispersion-reaction model and accounts for the spatial distribution of water demands along dead-end pipes. WUDESIM_Py comprises various sets of functions that allow the users to set-up and conduct WQ simulations as well as obtain and visualize simulation results. A complete description of the different functions, together with examples of how these functions can be implemented in different applications, is provided. Through conducting extensive simulations of benchmark WDNs, the results revealed that widespread adoption of water conservation practices can lead to significant WQ deterioration in the dead-end branches. Additionally, the results suggested that neglecting dispersive transport and spatially aggregating demands may result in overestimating residual chlorine concentrations in the dead-end branches, which could mask the real impacts of demand reduction on WQ deterioration.

It is an important task to real-time monitor the water quality in the water distribution networks. But it is difficult to select the representative locations from the whole water distribution networks because of the dynamical hydraulic status in the water distribution networks. The Lagrange method was used to analysis the water dynamic quality path of every node in every water quality time step during the water quality simulation in the networks. An objective function based on the node demand factors and the water dynamic quality path was represented to evaluate the water quality importance of each node in every water quality time step. So the optimal nodes that adapted to be fixed the sensors were selected from the networks. Fast Fourier Transformation and convolution method were used to analysis the signals collected by the water quality on-line sensors. The contamination source can be traced because the sensors impulse reaction matrix can be defined by the water dynamic path analysis. Dynamic water quality path was calculated out in an example water distribution networks. The optimal water quality sensors’ locations were defined by the water quality path calculation and the contamination sources were distinguished in a hypothetical condition through the sensors ‘ signals analysis. It shows that the water dynamic path analysis based on the dynamic node percent information is a useful tool to optimize the water quality sensors locations and the contamination source identification.

Water distribution systems are considered vital arteries of urban communities. The purpose of a water supply distribution system or network is to provide water to consumer with adequate pressure and quality. The quality must be healthy and standards in terms of chemical and biological standards. Chlorine is used as the most common disinfectant in municipal drinking water supply networks due to its high efficiency and economy. The aim of this study was to assess the effect of environmental temperature on residual chlorine, turbidity, TOC and HPC in Abadan, Iran, WDN, during summer and winter seasons. In this cross-sectional study, according to the water supply maps, the 232 samples from different point of WDN were analyzed to measurement of free residual chlorine, total organic carbon (TOC), Turbidity (NTU), and heterotrophic plate count (HPC) (cfu/100 ml), based on the standard methods for examination of water and wastewater (APHA). Samples were collected from effluent of water treatment plant to distribution system according to the Cluster sampling model. Regression analysis was used to investigate the relationship between variables. Results show that temperatures in Abadan typically range from 29 to 46 °C at summer and 12 to 27 °C in winter. Statistical analyzes show that as the ambient temperature increased, the free residual chlorine in the distribution network from the water treatment plant decreased to the end of the distribution network and reached zero at some end points (R2 = 0.97). Also TOC, Turbidity (NTU), and HPC (cfu/100 ml) showed a significant increase with increasing environmental temperature in distribution network (P < 0.05). According to the results of this study, in cities with high seasonal air temperatures, due to changes in the water quality of the distribution network, it is necessary to take re-chlorination, change the coagulation and flocculation process of surface water treatment plants in, and continuous monitoring of WDN in hot seasons.KeywordsEnvironment temperatureFree residual chlorineNOMTurbidity and HPCWater distribution system

Delivering water in sufficient quantity and acceptable quality is the main objective of water distribution networks (WDN) and at the same time is the main challenge. Many factors affect the delivery of water through distribution networks. Some of these factors are relevant to water quality, quantity and the condition of the infrastructure itself. The deterioration of water quality in the WDN leads to failure at the water quality level, which can be critical because it is closest to the point of delivery and there are virtually no safety barriers before consumption. Accordingly, developing a powerful monitoring system that takes into consideration water demand distribution, the vulnerability of the distribution system and the sensitivity of the population to the deterioration of water quality can be very beneficial and, more importantly, could save lives if there was any deterioration of water quality due to operational failure or cross-contamination events. In this paper, a framework for a water quality monitoring system that considers water demand distribution, the vulnerability of the system and the sensitivity of the population using fuzzy synthetic evaluation and optimization algorithms is developed. The proposed approach has been applied to develop a monitoring system for a real WDN in Saudi Arabia.

Rapid detection of anomalous operating conditions within a water distribution network is desirable for the protection of the network against both accidental and malevolent contamination events. In the absence of a suite of in-situ, real-time sensors that can accurately identify a wide range of contaminants, we focus on detecting changes in water quality through analysis of existing data streams from in-situ water quality sensors. Three different change detection algorithms are tested: time series increments, linear filter and multivariate distance. Each of these three algorithms uses previous observations of the water quality to predict future water quality values. Large deviations between the predicted or previously measured values and observed values at future times indicate a change in the expected water quality. The definition of what constitutes a large deviation is quantified by a threshold value applied to the observed differences. Both simulated time series of water quality as well as measured chlorine residual values from two different locations within a distribution network are used as the background water quality values. The simulated time series are created specifically to challenge the change detection algorithms with bimodally distributed water quality values having a square wave and sin wave time series, with and without correlated noise. Additionally, a simulated time series resembling observed water quality time series is created with different levels of variability. The algorithms are tested in two different ways. First, background water quality without any anomalous events are used to test the ability of each algorithm to identify the water quality value at the next time step. Summary statistics on the prediction errors as well as the number of false positive detections quantify the ability of each algorithm to predict the background water quality. The performance of the algorithms with respect to limiting false positives is also compared against a simpler “set point” approach to detecting water quality changes. The second mode of testing employs events in the form of square waves superimposed on top of modeled/measured background water quality data. Three different event strengths are examined and the event detection capabilities of each algorithm are evaluated through the use of receiver operating characteristic (ROC) curves. The area under the ROC curve provides a quantitative basis of comparison across the three algorithms. Results show that the multivariate algorithm produces the lowest prediction errors for all cases of background water quality. A comparison of the number of false positives reported from the change detection algorithms and a set point approach highlights the efficiency of the change detection algorithms. Across all three algorithms, most prediction errors are within one standard deviation of the mean water quality. The event detection results show that the best performing algorithm varies across different background water quality models and simulated event strength.

Water Distribution Networks (WDNs) are crucial for meeting current and future urban water demands. Knowledge of future water demand at different time scales is fundamental for optimal WDN design and operations. Various predictive models of water demand have been proposed in the literature, ranging from traditional time series analysis to cutting-edge machine learning and deep learning techniques. However, the task of forecasting urban water demand remains mostly decoupled from the design of the optimal control of the related WDN. Current performance assessment of demand predictive models focuses predominantly on forecast accuracy, overlooking their practical implications on WDN operations. Meanwhile, the existing research on WDN management often assumes either perfect knowledge of future water demands or employs empirical approximations and aggregate statistics to estimate future water needs. This study bridges this gap by scrutinizing the actual operational value of water demand forecasts in designing optimal operations of WDNs.Here, we develop a forecast-informed optimal WDN control framework to evaluate the operational value of water demand forecasts for WDN operations. Our framework comprises two main modules. The first module computes water demand forecasts. We comparatively evaluate a suite of different forecasting models &amp;#8212;including Seasonal Auto-Regressive Integrated Moving Average with eXogenous factors, Multilayer Perceptron, Convolutional Neural Network, and Long Short-Term Memory (a network augmented with an attention mechanism) &amp;#8212;across various forecast horizons (1/6/12 hours and 1/3/7/14 days ahead). The most accurate forecasts are integrated into the second module, an economic nonlinear Model Predictive Control (MPC) algorithm designed to optimize WDN operations. Within this module, an Artificial Neural Network (ANN) &amp;#8211; based surrogate model encapsulates the hydraulics of the physical WDN, enhancing the optimization process while reducing complexity.We demonstrate our forecast-informed optimal WDN control framework on a real WDN of a rural town with approximately 10,000 inhabitants. Water demand data collected in the Netherlands for a period of 10 years (2007-2017) at 5-minute resolution and corresponding meteorological data are used to train the water demand forecasting models. The MPC module computes the optimal control sequence for 7 pumps and 1 valve in the WDN to minimize pump energy costs while meeting water demands and ensuring safety storage in 5 tanks. Initial findings reveal that the ANN-based surrogate model can accurately incorporate the WDN characteristics (R2 &gt; 0.85), facilitating its integration into the MPC for an efficient and simplified representation of a real-world WDN. Further, MPC fed by 24-hour ahead water demand forecasts achieves potential energy savings of approximately 18% compared to a benchmark rule-based control strategy. Our framework yields a versatile simulation-based optimization tool for evaluating the impact of demand forecasts on WDN management. Future research efforts will aim at refining and comparing deterministic and stochastic water demand forecasts within the MPC framework, under diverse operational objectives.

This paper explores the application of the quality function deployment (QFD) approach to identify and prioritize factors to reconcile ‘actual’ risk with ‘perceived’ risk for drinking water in a distribution network. Consumers' complaints (regarding water odour, taste, colour and other problems) and consumers' perception about water safety are used to define customers' requirements (aka ‘whats’). Twelve water quality parameters and distribution network properties (e.g. turbidity, pipe breaks) are used as indicators for drinking water quality – the product characteristics (aka ‘hows’). Correlations between ‘whats’ and ‘hows’ are established using data obtained from a case study. Opinions of experts in drinking water and consumers are used to define correlations between the ‘what’ ‘microbial safety’ and the ‘hows’. The analytic hierarchy process allows prioritizing customer requirements. Three QFD-based methods are applied to prioritize factors affecting water quality in a distribution network. The proposed approach is demonstrated through a case study of a water distribution network in Quebec City (Canada). Results show that the factors that primarily affect customers' requirements include free residual chlorine, turbidity and trihalomethanes. Sensitivity analyses using three scenarios confirm the robustness of the proposed approach. Utility managers must take action, especially concerning these product characteristics, to satisfy customers' requirements.

Water stands as the fundamental cornerstone of life, and with the human population growing exponentially, the critical importance of sustainable water management becomes increasingly evident. Water not only serves as the essential working fluid for major chemical processes, including thermal energy generation, but it is also integral to manufacturing and domestic use. Despite its significance, water is a scarce commodity, and the planet continues to lose this precious resource due to theft, pipe bursts, and leakages in water distribution networks (WDNs). The consequences of water loss extend beyond the impact on physical resources, as it is intricately linked to financial challenges. Thus, water loss has the potential to result in substantial financial setbacks for companies, organizations, and government entities, underscoring the interdependence of water management and fiscal sustainability. In response to these challenges, digital technologies have been harnessed to optimize WDNs. A major constraint lies in deciphering the applicable digital technologies due to the multidisciplinary nature of the research area encompassing WDNs and digital technologies; therefore, this study adopts a systematic literature review (SLR) combined with digital tools, to comprehensively extract all aspects of a WDN, ranging from sensors to enterprise resource planning (ERP), including equipment and systems. This literature forms the foundational basis for constructing a framework aimed at creating a content repository for digital WDN sustainability. To further develop the framework, this study reviews international best practices in digital WDN. This is adopted in developing a digital WDN framework based on the literature and classifying a database structure from sensor to ERP for a generic WDN. Furthermore, the study explores tools and systems for optimization as well as updating the theoretical structure with Johannesburg WDN data and provides a comprehensive evaluation for enabling digital WDN in South Africa. The digital WDN framework comprises three distinct components: security, a central management database (CMDB), and best practice architecture. The architecture involves five layers, including the physical layer, communication layer, data storage and analysis layer, benefit layer, and application layer. Utilizing systematic literature review and bibliometric keyword analysis, the study determines the equipment, systems, and their uses, leading to the development of a generic WDN. Validation of the framework using the generic WDN emphasizes the equipment and systems used in each of the five layers. Furthermore, the framework is validated using Johannesburg Water's WDN, leading to the development of a CMDB. The CMDB underscores the possibility of storing physical layer and communication layer configuration items (CIs) and highlights asset management, CI relations, change management, and historian capabilities. Maintaining an accurate and updated CMDB necessitates employing asset discovery solutions, while CMDB relationship mapping plays a crucial role in assessing the ripple effects of CI changes within a complex system. Finally, the measurement of the digital maturity of Johannesburg Water's WDN using the Administração e Gestão de Sistemas de Salubridade (AGS) maturity index reveals a maturity index of 62%. The index emphasizes strong capabilities in GIS integration and data collection through the SCADA system. Despite advancements in planning systems, such as domestic flow metering, there remains an opportunity to enhance asset management capabilities for continuous improvement in WDN operations.

Water losses in watersupply and distribution systems have been a serious problem in Turkey and allover the world causing economic costs and environmental drawbacks. Total waterlosses is the summation of real (physical) and apparent (commercial) losses. Mainactivities to reduce water losses include digitizing the components of network usingGeographical Information Systems (GIS), dividing large water distributionnetworks (WDNs) into District Metered Areas (DMAs), monitoring, carrying outyearly water balance, hydraulic modelling, pressure management, active leakagecontrol, recording water consumption of the users, reducing meter errors andillegal water consumption. The Ministry of Forestry and Water Affairs in Turkeyissued a new regulation for water losses reduction in 2014 based on the methodsused to determine and reduce the losses. This is followed by issuing practicaldescription of the technical procedure to reduce the losses in 2015. The newlegislation aims to reduce total water losses in all water authorities below 25%within certain time periods. All the water authorities are required to carryout yearly water balance and report them to the ministry together with forms tofollow up the efforts towards water losses reduction. In order to apply theprescribed techniques in a successful way, first of all water losses problemshould be understood well, technical and human resource capacity should beimproved, and sufficient financial resources should be allocated. Also, thewater utilities should have a strategic plan and a strong commitment to reducewater losses.

The present Ph.D. thesis is devoted to the experimental and numerical analysis of the Pumps As Turbines (PATs) application in hydraulic systems and, specifically, in Water Distribution Networks (WDNs) to generate Energy Recovery (ER) in both urban and rural areas. The use of PATs in WDNs represents a relevant topic in the field of the innovative Best Management Practices (BMPs) of WDNs because addressed to both the pressure regulation and the hydropower generation. Thus, it could represent an alternative approach to the use of Pressure Reducing Valves (PRVs), benefitting of the exceed pressure to produce sustainable energy, otherwise dispersed. The PATs application consists in the use of pump models commercially available running in reverse mode, by inverting the flow direction and making use of the motor as an electrical generator. Their employment can be intended as an effective alternative to the traditional micro-turbines in WDNs, having lower investment and maintenance costs and allowing the model selection among a wide set of pump models available in the market. Conversely, PATs usually assure lower operative ranges, however expandable by arranging proper hydraulic and/or electrical regulations. In addition to the evaluation of the effective opportunities for pressure reduction in water systems, one of the main issue, concerning the PATs use for hydropower generation, regards the limited knowledge about their performance curves, rarely made available by manufactures. In the literature, several experimental, theoretical and numerical models have been proposed, aiming at both predicting the PAT performances and reproducing the internal fluid dynamics. In this regard, Computational Fluid Dynamics (CFD) models are widely applied, because able to both simulate the fluid dynamics of actual configurations and analyse the performance improvement obtainable by modifying the geometric properties of the considered turbo-machine. However, the current knowledge about PAT performances, available in the literature, does not allow to characterize the wide set of pump models, which are on the market, useful for running as turbines. With the aim of making this limitation smaller, in the present study an experimental and numerical investigation of centrifugal PAT models was performed, presenting an operative procedure for the optimal selection of centrifugal PATs in WDNs. A laboratory set-up was specfically installed at the Department of Civil, Architectural and Environmental Engineering (DICEA) of the University of Naples (IT) Federico II where several centrifugal PATs, having different geometric configurations and motor equipment, were tested. The experiments were performed in wide flow rate ranges, typical of WDNs supplying small-medium sized urban and rural centers, by varying the PAT rotational speed from 300 to 3000 rpm. A total of about 7400 operative configurations were investigated, in compliance with the laboratory set-up potentialities, achieving generated head drops up to about 70 m and produced electrical powers up to 16.3 kW. From the experimental analysis, with the aim of characterizing the investigated PATs, comparison with models from the literature was performed and, in order to provide effective tools for predicting the performances of centrifugal PATs, analytic relationships were derived, as a function of the geometric configuration, the number of stages and the motor efficiency class equipment. The attention was specifically drawn to the experimental characterization of: a) a classical Horizontal Axis Single-Stage PAT running at wider operative ranges than those discussed in the literature; b) PAT models, not adequately taken into account in the literature, such as centrifugal Single-Stage and Multi-Stage Vertical Axis PATs. Taking advantage of the experimental results, an operative procedure was developed for the optimal selection of PATs in WDNs, able to maximize the potential ER in WDNs. It could be intended as a basic tool for implementing a Decision Support System (DSS) for hydropower generation in WDNs. Finally, the development of a numerical CFD model, by applying the ANSYS® Fluent™ code, allowed to test the reliability of numerical simulations to both predict the PAT performances and investigate the fluid behaviour across centrifugal PATs.

Water distribution networks (WDN) model optimization is an important part of smart water systems to achieve optimal strategies. WDN optimization focuses on the nonlinearity of the discharge head loss equation, the availability of discrete properties of pipe sizes, and the conservation of constraints. Multi-objective evolutionary algorithms (MOEAs) have been proposed and successfully applied in the field of WDN design optimization. Previous studies have focused on comparing the optimization effects of algorithms in water distribution networks, ignoring the problems of unbalanced pressure distribution and water hammer at the nodes of the pipe network caused by the complex terrain in mountainous areas. In this paper, a multi-objective water supply optimization model that integrated cost, reliability, and water quality was established for a mountainous WDN in real engineering. The method of traversing the nodes to solve the water age was introduced to find a more scientific and practical water age solution model, with setting the weight function to evaluate the water age of the water supply model comprehensively. Strength Pareto Evolutionary Algorithm II (SPEA-II) and Non-dominated Sorting Genetic Algorithm II (NSGA-II) were adopted to optimize the WDN design model in the mountainous complex terrain. The significance levels of the number of Pareto solutions (NOPS) and running time are 0.029 and 0.001, respectively, indicating that the two algorithms have significant differences. Compared to NSGA-II, SPEA-II has a better convergence rate and running time in multi-objective water supply optimization design. The solution set distribution of SPEA-II is more concentrated than that of NSGA-II, also the numerical value is better. The number of SPEA-II optimization schemes is larger and the scheme is more effective. Among them, the Pareto solution set of SPEA-II can obtain more desirable optimization results on cost, reliability index (RI) and water age. In summary, the study provides valuable information for decision makers in WDN with complex terrain.

An optimization model with two stages was proposed for the dynamic schedule of booster chlorination in a water distribution network(WDN)in order to decrease the variability of chlorine residuals. The first stage located the minimum number of booster stations (minimum construction cost) to supply enough chlorine residuals within a WDN,and the residual coverage set represented the impact of booster stations on monitoring nodes. Then the second stage determined the optimal chlorine injection rates based on the desired chlorine residual mass concentration. Numerical results show that the model can effectively obtain the reasonable locations of booster stations and the injection rate schedule. The model can decrease the variability of chlorine residuals and allow a lower chlorination dose,which improves the water quality in WDN.

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

A critical appraisal of selected water distribution networks was made under two modes of operation—intermittent water supply and continuous water supply. The study zones selected in four Indian cities—Ghaziabad, Jaipur, Nagpur, and Panaji—were typical residential areas with metered water supply and were readily amenable to hydraulic isolation from the rest of the area. The study areas included Lohia Nagar in Ghaziabad, Army Welfare Housing Officer's Colony in Jaipur, Shankar Nagar in Nagpur, and Mala Area in Panaji. Preparatory work in the study zones included updating water distribution network plans; installing valves and bulk meters wherever necessary to hydraulically isolate the zone from the rest of the area; and surveying homes to check for stopcocks and water meters and to collect information on household populations and consumers' opinions regarding water supply service. Both water supply modes were studied to collect data on per capita water consumption, pressures at various points in the distribution network, flow rate and variation and total flow into the network, nonrevenue water, water quality, and relevant information for engineering and socioeconomic analysis of the distribution network. Continuous water supply has certain advantages over intermittent water supply. There was an appreciable improvement in nodal pressures and flow patterns in the distribution networks and a decrease in peak factors. Also, microbial quality of the water improved considerably at the consumers' end. However, water consumption and nonrevenue water increased when the mode of supply was switched over from intermittent to continuous, which points to the need for preventive maintenance of distribution systems and proper metering at the consumers' end.

Traditional water distribution network (WDN) design approaches have primarily focused on fulfilling hydraulic conditions such as water pressure and demand while placing less emphasis on water quality issues. Owing to a large number of documented water quality failures, there has been an increasing interest in water quality management throughout the design or operational phases of WDNs. This paper presents a novel approach for designing high-velocity WDNs to improve water quality security and satisfy the hydraulics of the network. The following is a summary of the procedures: (1) define the hydraulic and water quality factors, (2) determine the network layout using the modified branched index, and (3) determine the pipe diameter in the network to achieve self-cleaning velocity. The proposed approach was applied to a portion of the CW city network. As a result, the network layout was transformed to a branched network to reduce the number of pipes that did not meet the self-cleaning velocity requirements. If the pipe did not achieve self-cleaning velocity after transforming the layout, additional pipe diameter adjustments were made to satisfy the self-cleaning velocity requirements. Owing to this effort, the length of the network was reduced, and 78.8% of the pipes achieved self-cleaning velocity. In addition, water age at dead-ends and changes in water age were minimized, allowing for efficient water quality management of the network.