Water Distribution Infrastructure Research Articles

Water Banking as a Strategy for the Management and Conservation of a Critical Resource: A Case Study from Tunisia’s Medjerda River Basin (MRB)

The increasingly adverse impacts of climate change (e.g., rainfall patterns, droughts, and floods), coupled with the ever-increasing water demands, are often translated into a contingent liability for water users’ communities. Additional complexities arise due to competing priorities, water rights, and transboundary water sources. Therefore, conventional water management practices should shift toward more comprehensive and responsive integrative approaches, even for systems with limited data. Furthermore, water managers must prioritize dynamic and interactive management techniques for existing systems. One such management technique is water banking, which is the focus of this study. Herein, a dynamic interactive water allocation model, which encompasses the water managers and heterogeneous parties with competing demands, is developed. The voluntary sales of water shares between parties are illustrated through the specific case of the Medjerda River in Tunisia, an excellent example of a transboundary basin with limited hydrologic data and conflicting water use requirements between its upstream and downstream sectors. A set of scenarios is developed for the first analysis with this model: two management scenarios that include the no-water trade and the water banking option; three demand scenarios that include a combination of steady-, low-, and high-water demand conditions; and two hydrologic scenarios that include dry and wet conditions. Based on an economic model, the economic impacts of water banking are calculated using estimates of the costs of water shortages brought to users that illustrate the magnitude. The results show that the water banking technique can improve water resource availability by optimizing the management, operation, and conservation of natural and artificial water storage systems and water distribution infrastructure. Specifically, water banking can offset users’ profit losses during severe conditions (i.e., drought), even with limited hydrologic data. This water management technique would allow the Tunisian government to minimize the economic impacts on farmers from drought and to plan for future uncertainties by optimizing the water storage potential in years of abundant rainfall.

Real-time IoT architecture for water management in smart cities

This paper presents a digital system that aims to analyze real-time data obtained from sensors installed in a city's water distribution infrastructure. The system’s primary objective is to monitor water quality and generate alerts when necessary. The following water quality metrics are used: Flow, pH, Turbidity, Free Chlorine, Nitrate, and Fluoride. The data gathered from sensors is initially processed by a distributed system, which generates multiple visualizations that synthesize large amounts of information. These visualizations facilitate real-time monitoring of the sensor's status. Additionally, citizens can receive updates on any possible issues in the water distribution network through WhatsApp messages. By addressing the limitations of traditional water quality monitoring methods, this system contributes to a noteworthy enhancement in public water supply services. Consequently, it improves the overall quality of life for the citizens.

International rivers as national borders: the functional complexity of border river governance with a case study of the Khorgos river

ABSTRACT Current research is concerned more with transboundary river interactions among the asymmetric riparian parties, lacking analyses on the influence of borders and bordering processes. Given that rivers that also form national borders have particular geopolitical features that are distinct from transboundary rivers, this paper approaches border river governance with the functional complexity of security and development. Affected by heterogeneous water-related issues and their interdependent relations, border river governance reflects nonlinear functions of security and development, respectively or collectively. Taking the Khorgos River as an example, we argue that, although the river governance was confined to water distribution because of the Sino-Soviet Split and the Sino-Kazakh boundary negotiations in the 20th century, friendly inter-state relations and increasing cross-border mobility have encouraged China and Kazakhstan to adopt a hybrid approach to water distribution, water monitoring, data exchange, riverbank protection, and water infrastructure for both water utilization and flood control since the 21st century. In response to water supply challenges made by increasing economic agglomeration and complex administrative divisions on China’s side, the local government has decided to take new measures to keep water security and development in recent years.

Detection of Per‐ and Polyfluoroalkyl Substances (PFAS) by Interrupted Energy Transfer

AbstractThe ubiquitous presence of per‐ and polyfluoroalkyl substances (PFAS) in aqueous environments has aroused societal concern. Nonetheless, effective sensing technologies for continuous monitoring of PFAS within water distribution infrastructures currently do not exist. Herein, we describe a ratiometric sensing approach to selectively detect aqueous perfluorooctanoic acid (PFOA) and perfluorooctane sulfonate (PFOS) at concentrations of μg ⋅ L−1. Our method relies on the excitonic transport in a highly fluorinated poly(p‐phenylene ethynylene) to amplify a ratiometric emission signal modulated by an embedded fluorinated squaraine dye. The electronic coupling between the polymer and dye occurs through overlap of π‐orbitals and is designed such that energy transfer is dominated by an electron‐exchange (Dexter) mechanism. Exposure to aqueous solutions of PFAS perturbs the orbital interactions between the squaraine dye and the polymer backbone, thereby diminishing the efficiency of the energy transfer and producing a “polymer‐ON/dye‐OFF” response. These polymer/dye combinations were evaluated in spin‐coated films and polymer nanoparticles and were able to selectively detect PFAS at concentrations of ca. 150 ppb and ca. 50 ppb, respectively. Both polymer films and nanoparticles are not affected by the type of water, and similar responses to PFAS were found in milliQ and well water.

Detection of Per- and Polyfluoroalkyl Substances (PFAS) by Interrupted Energy Transfer.

The ubiquitous presence of per- and polyfluoroalkyl substances (PFAS) in aqueous environments has aroused societal concern. Nonetheless, effective sensing technologies for continuous monitoring of PFAS within water distribution infrastructures currently do not exist. Herein, we describe a ratiometric sensing approach to selectively detect aqueous perfluorooctanoic acid (PFOA) and perfluorooctane sulfonate (PFOS) at concentrations of μg ⋅ L-1 . Our method relies on the excitonic transport in a highly fluorinated poly(p-phenylene ethynylene) to amplify a ratiometric emission signal modulated by an embedded fluorinated squaraine dye. The electronic coupling between the polymer and dye occurs through overlap of π-orbitals and is designed such that energy transfer is dominated by an electron-exchange (Dexter) mechanism. Exposure to aqueous solutions of PFAS perturbs the orbital interactions between the squaraine dye and the polymer backbone, thereby diminishing the efficiency of the energy transfer and producing a "polymer-ON/dye-OFF" response. These polymer/dye combinations were evaluated in spin-coated films and polymer nanoparticles and were able to selectively detect PFAS at concentrations of ca. 150 ppb and ca. 50 ppb, respectively. Both polymer films and nanoparticles are not affected by the type of water, and similar responses to PFAS were found in milliQ and well water.

From Radio to In-Pipe Acoustic Communication for Smart Water Networks in Urban Environments: Design Challenges and Future Trends

The smart management of water resources is an increasingly important topic in today’s society. In this context, the paradigm of Smart Water Grids (SWGs) aims at a constant monitoring through a network of smart nodes deployed over the water distribution infrastructure. This facilitates a continuous assessment of water quality and the state of health of the pipeline infrastructure, enabling early detection of leaks and water contamination. Acoustic-wave-based technology has arisen as a viable communication technique among the nodes of the network. Such technology can be suitable for replacing traditional wireless networks in SWGs, as the acoustic channel is intrinsically embedded in the water supply network. However, the fluid-filled pipe is one of the most challenging media for data communication. Existing works proposing in-pipe acoustic communication systems are promising, but a comparison between the different implementations and their performance has not yet been reported. This paper reviews existing works dealing with acoustic-based communication networks in real large-scale urban water supply networks. For this purpose, an overview of the characteristics, trends and design challenges of existing works is provided in the present work as a guideline for future research.

Effect of DMA characteristics on risk and asset analysis of the Metropolitan Waterworks Authority pipe network

AbstractThis study examines the District Metering Area (DMA) characteristics in the pipe networks of Metropolitan Waterworks Authority (MWA), with a specific focus on risk and asset analysis, including water loss rate, water usage, and pipe density. The objective is to classify the DMA types based on these characteristics and to determine the influence of area characteristics on water distribution infrastructure. This is achieved by employing risk assessment and asset valuation techniques to identify pipes that require replacement. Initially, the Area Characteristic Index (ACI) for all 64 DMAs within the Ladprao service office branch was evaluated using a fuzzy inference system. Subsequently, six selected DMAs from three distinct area types were analyzed by the fuzzy logic model to figure out the Risk Index (RI) values. Concurrently, the Infrastructure Value Index (IVI) contributed to the asset valuation. These indices pinpointed both the high‐risk pipe routes and the poor‐condition infrastructure. Moreover, the Modified Risk‐Value Index (MRVI) was adopted to prioritize these pipe routes within a constrained budget. The main conclusion drawn is that while DMA characteristics do not directly influence the identification of deteriorated pipes through risk assessment and asset analysis methods, the characteristic of a high water loss rate does impact the number of pipe routes identified by the RI.

Integrating spatial clustering with predictive modeling of pipe failures in water distribution systems

ABSTRACT Pipe failures in water distribution infrastructure (WDI) have significant economic, environmental and public health impacts. To alleviate these impacts, repair and replacement decisions need to be prioritized to effectively reduce failure rates. In this study, a computational framework is proposed for WDI asset management that couples spatial clustering analysis with predictive modeling of pipe failures. First, hotspot/coldspot clusters of statistically significant high/low failure rates are identified using local indicators of spatial association. Second, the predictive abilities of eight statistical learning techniques are systematically tested, and the best-performing method is implemented to forecast failure rates,(breaks/(km.year)) within different sectors of the WDI. Third, the framework is implemented to compare the impact of adopting proactive instead of reactive pipe replacement strategies. Applying the framework to a real-life, large-scale WDI revealed that spatial clustering of pipe failures improves the accuracy of the prediction models.

Advances in quantifying microbial contamination in potable water: Potential of fluorescence‐based sensor technology

AbstractImproved monitoring of potable water is essential if we are to achieve the UN Sustainable Development Goals (SDGs), specifically SDG6: to make clean water and sanitation available to all. Typically monitoring of potable water requires laboratory analysis to detect indicators of fecal pollution, such as thermotolerant coliforms (TTCs), Escherichia coli (E. coli), or intestinal enterococci. However, these analyses are time‐consuming and expensive, and recent advances in field deployable sensing technology offer opportunities to investigate both the spatial and temporal dynamics of microbial pollution in a more resolved and cost‐effective manner, thus advancing process‐based understanding and practical application for human health. Fluorescence offers a realistic proxy for monitoring coliforms in freshwaters with potential for quantification of potable water contamination in near real‐time with no need for costly reagents. Here, we focus on E. coli to provide a state‐of‐the‐art review of potential technologies capable of delivering an effective real‐time E. coli sensor system. We synthesize recent research on the use of fluorescence spectroscopy to quantify microbial contamination and discuss a variety of approaches (and constraints) to relate the raw fluorescence signal to E. coli enumerations. Together, these offer an invaluable platform to monitor drinking water quality which is required in situations where the water treatment and distribution infrastructure is degraded, for example in less economically developed countries; and during disaster‐relief operations. Overall, our review suggests that the fluorescence of dissolved organic matter is the most viable current method—given recent advances in field‐deployable technology—and we highlight the potential for recent developments to enhance approaches to water quality monitoring.This article is categorized under: Engineering Water > Water, Health, and Sanitation Engineering Water > Methods Human Water > Methods

An Assessment of Water Supply Governance in Armed Conflict Areas of Rakhine State, Myanmar

This study aims to analyze the actors and institutions for public water supply governance in armed conflict areas of Rakhine State, Myanmar. Using Stakeholder Salience Theory and Institutional Analysis of data collected from four participatory workshops and interviews with 160 water stakeholders from the four townships in Rakhine State, the findings revealed that although the water supply system is managed and governed by the state water authorities with the involvement of many administrative, political, and sectoral technical agencies and organizations, the non-formal community organizations such as ethnic armed military and religious institutions also have a strong interest in water supply and are considered dangerous actors in the water supply governance process. Diverse water actors held different perspectives and perceptions of water supply quality and quantity because of their different power holdings and political and economic interests. The state actors seemed biased on their positive performance, demonstrating their satisfaction with the current water supply governance, while community, private sectors, and household water users instead showed their dissatisfaction with the quality and quantity of the current water supply system, but they stayed neutral about the water supply governance performance. The research showed the complexity and dynamics of water actors’ powers and interests in armed conflict areas. In addition, there is a lack of socio-technical and financial capacity for the investment and maintenance of water distribution and collection infrastructure and facility, as well as water quality and quantity monitoring and evaluation. The study appeals to the development and peacebuilding organizations working in conflict areas to promote adaptive governance for community learning and adaptation to social-political and environmental change over time.

Phosphate drinking water softeners promote Legionella growth.

Phosphate-based drinking water softeners are commonly used to prevent scale formation in drinking water distribution infrastructure. The main reason for drinking water softening is primarily economic (protection of pipes and extension of equipment life), while the health aspect of such treatment is usually neglected. The aim of this work is to investigate the effects of phosphate-based drinking water softeners on growth stimulation of Legionella pneumophila. Bacterial growth was observed at two different phosphate concentrations. On average, an increase in growth of 1.19-1.28 log CFU/mL was observed in selected samples with added phosphates compared with the control. The results of the in vitro experiment confirmed that the added phosphates stimulate the growth of L. pneumophila; growth stimulation could therefore be expected in drinking water distribution systems (DWDS) when phosphates are used as well. The availability of phosphorus in DWDS may be a crucial limiting factor for biofouling control. Consequently, phosphate-based chemicals for drinking water should be avoided or used with prudence, especially in drinking water with high concentrations of other nutrients.

Does Access to Public Drinking Water Services Positively Impact Health in Cameroon?

The objective of this study is to determine the impact of household access to the drinking water distribution network on the state of health of populations in Cameroon. Considering child health (diarrheal morbidity and underweight) and based on data from the Cameroonian Household Survey (ECAM4) of 2014 and the Cameroon Demographic and Health Survey (EDSC-V) of 2018 and adopting probity models with instrumental variable in a dichotomous approach, we obtain the following results. Access to public drinking water services contributes significantly to improving the well-being of populations in Cameroon, significantly reducing the risk of diarrhea and exposure to underweight children. Also, the public authorities will have to develop water production and distribution infrastructures to promote greater access for the population and allow an improvement in the water quality and quantity.

Evaluation of water supply reliability improvement enabled by on-site greywater reuse systems

Water utilities are under enormous pressure to provide a continuous supply of potable water under the presence of an increasing supply-demand deficit. The deteriorating condition of our centralized water distribution infrastructure exacerbates this uncertainty due to the growing number of main breaks and the associated supply interruptions. Distributed water supply systems leveraging treated household and industrial greywater or blackwater are currently being explored as a sustainable alternative in many arid regions to reduce their dependence on conventional freshwater resources. While the sustainability benefits of such alternate water resources have been established, the reliability improvement benefits have seen limited research. To address this need, the objective of this study is to evaluate the reliability improvement when on-site greywater reuse systems complement existing centralized water distribution infrastructure. This paper presents a computational water supply reliability model adapted to suit both centralized and on-site supply scenarios. This model is applied to a small water distribution system to evaluate the reliability improvement benefits and further assess their sensitivity to a variety of adoption scenarios and infrastructure characteristics. The results reveal that when on-site greywater reuse systems supplement existing water supply systems, the supply reliability improved up to 195% and 65% for the least cost and the reasonable design scenarios, respectively. However, the reliability improved only up to 31% and 23% for the least-cost and reasonable scenarios, respectively, when the centralized system was merely retrofitted with on-site freshwater storage. The subsequent sensitivity analyses found that the improvement in supply reliability decreased with the increase in system age and pipeline failure growth rate, whereas it increased with an increase in maximum usable reclaimed water, treatment efficiency, and the pipeline roughness coefficient. Overall, the results encourage the adoption of on-site greywater reuse systems from the perspective of infrastructure supply reliability.

A Multi-Leak Identification Scheme Using Multi-Classification for Water Distribution Infrastructure

Water distribution infrastructure (WDI) is well-established and significantly improves living quality. Nonetheless, aging WDI has posed an awkward worldwide problem, wasting natural resources and leading to direct and indirect economic losses. The total losses due to leaks are valued at USD 7 billion per year. In this paper, a multi-classification multi-leak identification (MC-MLI) scheme is developed to combat the captioned problem. In the MC-MLI, a novel adaptive kernel (AK) scheme is developed to adapt to different WDI scenarios. The AK improves the overall identification capability by customizing a weighting vector into the extracted feature vector. Afterwards, a multi-classification (MC) scheme is designed to facilitate efficient adaptation to potentially hostile inhomogeneous WDI scenarios. The MC comprises multiple classifiers for customizing to different pipelines. Each classifier is characterized by the feature vector and corresponding weighting vector and weighting vector pertinent to system requirements, thus rendering the developed scheme strongly adaptive to ever-changing operating environments. Hence, the MC scheme facilitates low-cost, efficient, and accurate water leak detection and provides high practical value to the commercial market. Additionally, graph theory is utilized to model the realistic WDIs, and the experimental results verify that the developed MC-MLI achieves 96% accuracy, 96% sensitivity, and 95% specificity. The average detection time is about 5 s.

Evaluation of the Factors Impacting the Water Pipe Leak Detection Ability of GPR, Infrared Cameras, and Spectrometers under Controlled Conditions

Leakages from water distribution infrastructures are responsible for a considerable amount of water losses. Consequently, innovative, non-destructive techniques (NDT) of leakage detection for early recognition is vital. In this study, the leak detection abilities of Ground Penetration Radar (GPR), spectrometers, and infrared (IR) cameras were investigated, and the factors affecting the leak detection response were assessed. Three experimental setups were constructed to simulate underground pipes in dune sand. Three different pipe materials (PVC, PPR, and PE) were investigated under three levels of moisture content (MC; 2%, 5%, and 10%) and three types of leaks (hole, crack, and faulty joint). The IR camera was the most effective among the different NDTs used in this study. The IR camera detected all types of leaks at 2% and 5% MC but was inconclusive at 10% MC. Similarly, the GPR detected the leaks at 2% and 5% MC successfully but was inconclusive at 10% MC. Lastly, the spectrometer was the least reliable NDT to detect leaks. Results suggest that IR cameras and spectrometers that operate in the mid-IR range (5–25 µm) can detect leaks.

Integrated approach for pipe failure prediction and condition scoring in water infrastructure systems

Pipe failures in water distribution infrastructure have significant economic, environmental, and public health impacts. To alleviate these impacts, pipe deterioration modeling has been increasingly implemented to characterize and predict pipe failure patterns with the aim of prioritizing repair and replacement decisions. Logistic regression has been recognized in recent literature as a strong candidate for failure prediction modeling. However, previous studies have often been limited to demonstrating the application of logistic regression for estimating failure probabilities. This study builds on previous efforts by proposing an approach for implementing logistic regression into a holistic framework for asset management decision-making. This framework incorporates logistic regression modeling, with a flexible time-interval, into a practical condition scoring methodology that accounts for the attitude of water utilities towards risk. The developed framework is demonstrated and tested on a 20-year pipe failure dataset of a large metropolitan US city. The logistic regression model displayed high accuracy in estimating the probability of failure within different time intervals, and the scoring method showed a reasonable ability to predict the criticality of repair decisions for pipes based on their condition.

Modernization of the left bank irrigation system of the Kaudulla reservoir of Sri Lanka

Abstract Irrigation water management in the paddy cultivation area under the left bank canal of the Kaudulla reservoir (Kaudulla tank) in the North Central Province of Sri Lanka has become a serious issue due to limited water availability and inefficient water distribution infrastructure at present. Insufficient storage capacities of the village tanks in the cultivation area, low rainfall during some months and regulated inflow from the transbasin diversion to Kaudulla tank have had a significant impact on yield in the two cultivation seasons of the year. In this article, modernization of irrigation infrastructure in the command area was investigated for effective utilization of limited available water. The results of the calibrated and validated Hydrologic Engineering Centre - Hydrologic Modeling System (HEC-HMS) model and Crop Water and Irrigation Requirements Program (CROPWAT) model were used with Water Evaluation and Planning Model (WEAP) to evaluate the water balance and demand to identify the best investment for improving irrigation water supply to maximize the return. Economic analysis was carried out using the net present values for different modernization options. Accordingly, the construction of a new canal system and augmentation of the capacities of village tanks from the present total capacity of 3.8–20 MCM was found to be the most appropriate option. This intervention will increase the income from yield by 205 million with a payback period of 12 years in the Yala season.

Reduction in Non-Revenue Water in Water Distribution System

Water is the world’s most critical natural resource. Rapid population growth and economic development have led to higher demand for water worldwide whereas on the supply side, natural sources of water have become less reliable. This demand-supply imbalance in the water sector calls for more innovative water management practices and suitable technologies. Utilities cannot afford the water loss because of poor operation and maintenance of water distribution infrastructure facilities. The terms theft, smuggling and leakages are most common sources of generation of Non- revenue water (NRW). Newspaper articles around the world, particularly in countries experiencing intense drought and water shortages, are highlighting water theft as a growing problem. Analysis of various city development plans in India shows that water leakages, theft and unauthorized water connections gives rise to a high level of unaccounted water. A recent study on Water Governance (2013) reveals that unaccounted water in Delhi amounts to around 50% of the total water pumped into the system, whereas it is 35-40% in Hyderabad and Bengaluru. The World Bank in its report, ‘The Challenge of Reducing Non-Revenue Water in Developing Countries’, reveals that 48 million cubic meters of drinkable water escape daily from official supply networks, which is enough to provide water for 200 million people. The same report on India had clearly highlighted that 40-60% of water in Mumbai is lost through illegal diversion. In This paper we have made an attempt to analyze the current methods, their drawbacks and we have provided solution in the form of software-based approach (using Bentley Watergems) which is more relevant as compared to the current field method.

Non-revenue water ratio prediction with serial triple diagram model

Abstract Water administrations attempt to control the Non-Revenue Water Ratio (NRWR) values in sustainable and well-performing water distribution infrastructures. In this respect, the NRWR value prediction through appropriate models over a small number of controllable variables is significant. The collection, monitoring, and predictions of data on variables that are used in the NRWR calculations are not practical and required significant time besides financial resources. In this study, the NRWR predictions have been made through the suggested method over three parameters. The model prediction accuracies, in the literature obtained by using the Triple Diagram Model (TDM) over two parameters, have been increased through the Serial Triple Diagram Model (STDM) suggested in this study. This method shows that better predictions are possible in the NRWR modeling. Thanks to the model applications developed in this study, water administrations can make predictions with the least error (less than 10% relative error) and certain variables, according to the characteristics of each water distribution network.

Incorporating use phase chemical leaching and water quality testing for life cycle toxicity assessment of cross-linked polyethylene (PEX) piping

Life cycle assessment (LCA) is increasingly being considered in material selection decisions for residential drinking water piping, but chemical leaching during the use phase has typically been excluded, even though the delivery of safe water is the core function of water distribution infrastructure. We have quantified the contribution of leached organics to life cycle human toxicity of piping materials through the integration of empirical leaching data within LCA. Eight cross-linked polyethylene (PEX) pipe brands were examined. Upstream emissions from PEX pipe production were combined with empirical total organic carbon (TOC) data from leaching tests for new pipes. The total mass of organic contaminants ingested over the pipe's lifetime was estimated by fitting leaching data with kinetic models and integrating leaching concentrations and daily water use over time, rather than using an initial concentration that does not accurately depict actual lifetime exposures. Potential human toxicity from use phase ingestion was evaluated using a range of human effect factors from the consensus USEtox model to create plausible bounds of toxicity through different exposure and effect scenarios. New non-carcinogenic human toxicological effect factors were derived for approximately half of the 62 leached organic compounds identified. Results indicate that potential human toxicity from upstream pipe production generally exceeds use phase toxicity, but that leached contaminants can be a substantial contributor to overall life cycle toxicity, depending on the PEX brand, particularly for carcinogenic effects. Deleterious effects can be reduced both by thorough system flushing after initial installation and periods of stagnation, but also through improvements in manufacturing processes that reduce upstream emissions. The bounding approach demonstrates a viable method for considering water quality in LCA when comprehensive characterization and concentration data are not available.