Urban Water Supply Research Articles

Risk Assessment of Urban Water and Energy Supply Using Copula Function: A Water–Energy Nexus Approach in an Arid City

Planning for the future of water and energy supply systems in urban areas requires a thorough assessment of associated risks. In this study, monthly water and energy demand data from 2011 to 2022 in an arid city was used to predict the corresponding demands from 2023 to 2032 using the seasonal auto-regressive integrated moving average (SARIMA) method. The aim is to estimate future water and energy supply risks both individually and jointly, using cumulative distribution functions (CDFs) derived from historical data. The main focus is to calculate the combined risk of water and energy, referred to as the water–energy nexus (WEN) risk. Based on the interdependent relationship between water and energy, the Copula function was utilized to model the bivariate distribution between these two variables. Pearson correlation analysis indicated a strong correlation between water and energy supplies. Among the distributions fitted to the data, the log-normal and gamma distributions were the best fit for water supply and energy supply systems, respectively, with the lowest Akaike information criterion (AIC) values. The Gumbel Copula, with a parameter of 1.66, was identified as the most suitable for modeling the joint distribution, yielding the lowest AIC value. The results indicate that the risks associated with energy supply, water supply, and their joint dependency could exceed 0.8% in the future, highlighting a potentially critical situation for the city. The trend analysis revealed that forecasted water and energy demands and their corresponding risks and the WEN risk are expected to have a significant upward trend in the future. Finally, local authorities need to explore alternative sources to supply water and energy in the future to address the ever-growing water and energy demands.

‘Taming’ a Wicked Problem: Selective Problematisation of Issues of Urban Water Supply in Mumbai

The lack of universal urban water access in the cities in the global south is a wicked problem. Using the case of Mumbai, this paper illustrates how consistently this wicked problem was chiselled and selectively problematised to turn it into a tame problem – a problem of water shortages at the city level. The chiselling included neglecting the essential aspects of urban water supply, such as supply coverage, pressure and leakages, which define the quality of urban water service received by citizens. Through chiselling and selective problematisation, the paper illustrates how the problem of providing universal urban water access in Mumbai was ignored for decades and the issues of water shortages were emphasised alone to justify and prioritise the development of dams.

Living within the Watershed: Managing Urban Water Supply in a Growing Metropolis

London’s rapid population growth during the nineteenth century drove demand for larger volumes of higher-quality water. This gave rise to Parliamentary bills for large infrastructure projects to transfer water to London from outside the Thames watershed and for the transfer of private company assets to municipal management. Wales was the most frequently suggested source, as it was argued to have cleaner, softer, and more abundant water. London’s water companies favored using improved infrastructure, connected networks, and demand management. Despite substantial investment, London’s water company assets and responsibilities were transferred to the Metropolitan Water Board in 1904. Looking back in 1953, fifty years after it was formed to take over London’s water infrastructure, the Metropolitan Water Board noted that extensive acquisition of land for reservoirs and watershed protection by the water companies proved invaluable in securing a sustainable water supply for the metropolis a century later.

Evaluating the Role of Customer Relationship Management in Enhancing Customer Satisfaction: A Study of Arusha Urban Water Supply and Sanitation

This study explores the impact of Customer Relationship Management (CRM) on customer satisfaction at the Arusha Urban Water Supply and Sanitation Authority (AUWSA). Employing a case study research design, the research targeted AUWSA customers and staff, using convenience and purposive sampling techniques to select a sample size of 100 individuals. Both primary and secondary data were utilized, with primary data gathered through questionnaires and interviews, and secondary data obtained from various documentary sources. Data analysis involved both quantitative and qualitative methods, with descriptive and inferential statistics applied to the quantitative data using SPSS. Qualitative data was analyzed through content analysis. The findings reveal that Information Technology (IT) significantly enhances timely information processing, facilitates effective customer communication, and promotes efficient service delivery, thereby reducing customer complaints and administrative errors. The study concludes that IT is crucial for improving customer satisfaction and recommends further research to explore CRM's impact on customer satisfaction in other service industries in Tanzania.

Collaborative water governance model for potable urban water supply in Riau Province, Indonesia

ABSTRACT The literature suggests that collaborative governance is a promising framework for addressing complex public problems while some cases have also marked failure in its implementation. Furthermore, the complexities and factors of the collaborative governance context must be understood at the early stage, as they may affect its sustainability. Therefore, this study aims to understand ‘what works and what doesn't’ and the need for sustainability of urban potable water management in Dumai City, Rokan Hilir Regency, and Bengkalis Regency through cross-sectoral collaboration and develop the best model to be developed for this collaboration. This study uses a soft system methodology in the urban potable water supply system of Riau Province with a wide range of stakeholders through in-depth interviews, thematic analysis, and the creation of purposeful activity models and rich pictures to uncover and address complex issues. The study found that the implementation of collaborative water management in urban areas with the collaborative water governance approach has worked well in the short term. However, it has not enhanced organizational autonomy or fostered trust and reciprocity dimensions in the long term. Additionally, we emphasize the importance of a collaborative supervisory board that will open internal and external opportunities.

Pipeline Leak Identification and Prediction of Urban Water Supply Network System with Deep Learning Artificial Neural Network

Pipeline leakage, which leads to water wastage, financial losses, and contamination, is a significant challenge in urban water supply networks. Leak detection and prediction is urgent to secure the safety of the water supply system. Relaying on deep learning artificial neural networks and a specific optimization algorithm, an intelligential detection approach in identifying the pipeline leaks is proposed. A hydraulic model is initially constructed on the simplified Net2 benchmark pipe network. The District Metering Area (DMA) algorithm and the Cuckoo Search (CS) algorithm are integrated as the DMA-CS algorithm, which is employed for the hydraulic model optimization. Attributing to the suspected leak area identification and the exact leak location, the DMA-CS algorithm possess higher accuracy for pipeline leakage (97.43%) than that of the DMA algorithm (92.67%). The identification pattern of leakage nodes is correlated to the maximum number of leakage points set with the participation of the DMA-CS algorithm, which provide a more accurate pathway for identifying and predicting the specific pipeline leaks.

Prediction of Pressure Fluctuation of Double-Suction Centrifugal Pump in Different Cavitation Conditions based on EMD-GRU

Abstract The double-suction centrifugal pumps play a crucial role in various applications such as in irrigation-drainage projects, water diversion projects, and urban water supply and drainage projects. The pressure fluctuation is one of the crucial parameters for assessing the operational stability of pump. The pressure fluctuation exhibits distinct characteristics in various cavitation conditions. A pressure fluctuation prediction method based on Empirical Mode Decomposition (EMD) and Gated Recurrent Unit (GRU) is proposed in this paper. The model enables accurate forecasting of pressure fluctuation signals when pump operates at different cavitation conditions. The data were obtained from experimental measurements of a double-suction centrifugal pump. The original signal was decomposed into multiple sub-signals with varying energy levels using the EMD method. The neural network of GRU was employed for training and data prediction on individual sub-signals. The predicted results of each sub-signal were combined to form the final pressure fluctuation signals. The method based on EMD-GRU proves effective in predicting pressure fluctuation in three different cavitation conditions. The mean absolute error (MAE) in time-domain characteristics is below 6%, and the prediction error for the main frequency is below 1%. The prediction of low-frequency characteristics still requires improvement.

Sustainable urban water management: Evaluating two pilot-scale advanced decentralized treatment systems for removal of organic contaminants of emerging concern in reclaimed groundwater

The rapid growth of population and the effects of climate change have placed unprecedented pressure on urban water supplies and pollution control. Consequently, it is essential to explore new local water resources in water-strained areas. To this end, this work focuses on evaluating pollutant removal effectiveness of decentralized treatment systems for groundwater reclamation. Two pilot-scale treatment trains, Treatment Line 1 (L1) and Treatment Line 2 (L2), which use membrane-free (with granulated activated carbon as the main process) or membrane-based (with reverse osmosis as the primary technology), were compared for their effectiveness in reducing concentrations of organic contaminants of emerging concern (CECs). Additionally, the effect of sodium hypochlorite addition for biofilm control on the contaminant removal performance was also examined. Results from the analysis of nearly 120 trace organic compounds (only 21 were detected in the raw water) showed that L2 significantly overperformed L1. Furthermore, the addition of a pre-chlorination step did not improve the removal performance. Regarding trace organic compounds, L1 without pre-chlorination averaged an overall good removal performance (94 ± 12%). However, Irbesartan, gemfibrozil and gabapentin showed moderate removals (50–90%) and Valsartan was poorly removed (<50%). After pre-chlorinating L1, the overall removal performance decreased (86 ± 20%). Nearly one third of the target contaminants showed moderate removal (50–90%), with Irbesartan and Valsartan exhibiting poor attenuations (<50%), highlighting that negatively-charged compounds were challenging to eliminate. In contrast, L2 exhibited very high removals (>99%) on all studied trace organic contaminants regardless of pre-chlorination. Our study also identified several indicator compounds to monitor CEC removal. Finally, considering the trade-offs between cost and final water use (non-potable), L1-based schemes with intermittent pre-chlorination could be the preferred implementation option. The results of this work will offer valuable insights into decentralized treatment systems, assisting decision-makers in choosing suitable approaches for sustainable urban water management.

Water Demand Forecasting in Multiple District Metered Areas Based on a Multi-Scale Correction Module Neural Network Architecture

Short-term water demand forecasting (STWDF) for multiple spatially and temporally correlated District Metering Areas (DMAs) is an essential foundation for achieving more refined management of urban water supply networks. However, due to the greater uncertainty associated with specific DMA demand compared to overall water usage, accurately predicting STWDF poses significant challenges. This study introduces an innovative network architecture—the multi-scale correction module neural network, built upon Long Short-Term Memory (LSTM) networks and Convolutional Neural Networks (CNN) enhanced with Attention mechanisms—for simultaneous STWDF with a temporal resolution of one hour over a week for 10 DMAs located in a single city in northern Italy. This framework utilizes multivariate corrections to refine and enhance the output accuracy. The results reveal that, in comparison to traditional Gated Recurrent Unit or LSTM models, the proposed model with integrated correction modules, particularly those that leverage inter-DMA correlations, improves performance across all evaluation metrics by an average of 5%-20% per DMA. Additionally, it consistently delivers superior accuracy across three scenarios: single DMA forecasting, total water demand, and extreme conditions, while maintaining stable performance throughout. Furthermore, the interpretability analysis underscores the feasibility of this innovative structure and highlights the contribution of meteorological features to the predictive model in some DMA-level STWDF. The unified input-output framework elegantly simplifies the STWDF process across multiple DMAs, providing new insights and methodologies for future research in this domain.

Groundwater resilience, security, and safety in the four largest cities in Denmark

Denmark's complete reliance on groundwater for water supply presents a unique case study in management of natural resources, urban planning, and water resilience in the face of climate change. This paper examines the groundwater management strategies in Denmark in general, focusing on Denmark's four largest cities—Copenhagen, Aarhus, Odense, and Aalborg— each facing distinct challenges due to their demographic, geographical, hydrogeological, and economic characteristics. Through analysis of these cities' approaches to groundwater management, this research contributes to the global discourse on sustainable urban water supply systems. As coastal groundwater cities (CGC), these urban areas must navigate the complexities of sustaining growing populations, mitigating climate change impacts, and coastal processes while ensuring the long-term viability of their groundwater resources. Copenhagen and Aalborg, built atop semi-confined fractured and locally karstic carbonate rocks, highlights the specific challenges associated with karstic groundwater systems, while, Aarhus, and Odense built on glaciofluvial aquifers faces different issues. The different groundwater challenges in these cities underscores the importance of integrating urban development with water resource management and environmental sustainability, offering valuable insights and lessons learned for other regions facing similar challenges. This study, thus not only sheds light on Denmark's groundwater management practices, but also emphasizes the need for innovative solutions to ensure the resilience of urban water supply systems in a changing climate and increasing pressures of emerging organic contaminants and elevated concentrations of geogenic elements induced by water abstraction and fluctuating water tables. Advanced Danish monitoring and modelling tools applied to support decision-making and innovation within the water sector are continuously developed and improved to support resilient and sustainable management of the available water resources.

Groundwater for urban water supply in Ukraine: a case study of Mykolaiv (Military challenges and lessons for the future)

The paper discusses the possibility of using groundwater as a source of water supply for Mykolaiv during emergencies or military operations. A hydrogeological model of the Mykolaiv groundwater field was developed to investigate the water exchange pattern and sources of operational groundwater reserves in the Upper Sarmatian aquifer, which is a primary source of drinking groundwater in the Mykolaiv area. The influence of various factors on water-bearing capacity of the Upper Sarmatian sediments was assessed, including the vulnerability of the fresh groundwater to the intrusion of brackish water from the Bug Estuary. The study also examined the feasibility of operating the aquifer under forced conditions, depending on the duration of emergency periods or military operations.

Determining the Economic Benefit of Watershed Conservation for Urban Water Supply Based on Scarcity rent for Water and Consumer Surplus

Determining the Economic Benefit of Watershed Conservation for Urban Water Supply Based on Scarcity rent for Water and Consumer Surplus

Analyzing the effects of extreme cold waves on urban water supply network safety: A case study from 2020 to 2021

Urban water supply networks are crucial for the transportation of water resources. However, with the increasing frequency and severity of cold wave disasters linked to climate change, the impact on water supply systems has become a critical concern. These impacts include pipe failures, customer water outages, and challenges in meeting peak winter water demand. To address this, our study analyzes data from cold waves in Shanghai from late 2020 to early 2021. We statistically examined daily water supply volume, pressure, and pipe failures to detect abnormal changes. We also analyzed pipe failure rates based on different characteristics to identify which pipes are most vulnerable to cold wave damage. Understanding the winter cold wave's effects can help water companies prioritize maintenance on aging pipes before such events, reducing damage and improving service. This research adds to the understanding of climate change's impact on urban infrastructure and provides valuable insights for global water companies to optimize their maintenance strategies.

Research on Signal Noise Reduction and Leakage Localization in Urban Water Supply Pipelines Based on Northern Goshawk Optimization.

In order to enhance the accuracy and adaptability of urban water supply pipeline leak localization, based on the Northern Goshawk Optimization, a novel joint denoising method is proposed in this paper to reduce noise in negative pressure wave signals caused by leaks. Firstly, the Northern Goshawk Optimization optimizes the decomposition levels and penalty factors of Variational Mode Decomposition, and obtains their optimal combination. Subsequently, the optimized parameters are used to decompose the pressure signals into modal components, and the effective components and noise components are distinguished according to the correlation coefficients. Then, an optimized wavelet thresholding method is applied to the selected effective components for secondary denoising. Finally, the signal components that have been denoised twice are reconstructed with the effective signal components, and the denoised negative pressure wave signals are obtained. Simulation experiments demonstrate that compared to wavelet transforms and Empirical Mode Decomposition, our method achieves the highest signal-to-noise ratio improvement of 12.23 dB and normalized cross correlation of 0.991. It effectively preserves useful leak information in the signal while suppressing noise, laying a solid foundation for improving leak localization accuracy. After several leak simulation tests on the leakage simulation test platform, the test results verify the effectiveness of the proposed method. The minimum relative error of the leakage localization is 0.29%, and an average relative error is 1.64%, achieving accurate leakage localization.

Using Artificial Neural Networks to Predict Leakage Location in Water Distribution Networks

One of the major types of water wastage in a distribution network is the leakage that occurs in pipes or other network components such as connections. Leaks in urban water supply networks impose many costs and workforce on governments and related organizations annually. If the cause of leakage is traced to the cracks and slits on various parts of a network, the amount of leakage from the location of the crack is said to be directly associated with the amount of pressure at that point. To trace leakage in water distribution networks, this study introduced a method based on hydraulics modeling and the inverse solution of flow equations to predict the location and amount of leakage in water distribution networks, by considering the values of the measured pressure in some network nodes. For this, a hydraulic model of the network under study was provided in the EPANET Hydraulic Analysis software, and the network analysis of various values and states of hypothetical leaks led to obtaining pressure values in the different nodes of the network via modeling water modeling under a steady state. Then, the artificial neural network, having been trained, was used to provide measured pressures in some network nodes at the testing hour as input data to the neural network to locate possible leaks in the water distribution network and to predict their approximate values. The findings were found to enjoy desirable accuracy. DOI: https://doi.org/10.52783/pst.835

Implication of Urban Domestic Water Distribution on Human Health in Machakos Central Ward, Machakos County

The world's water resources are running out, and this situation is made worse by how quickly people are populating new areas, particularly in developing nations. This has highlighted the critical requirement for prepared action to manage water resources for sustainable development efficiently. Increasing water demands due to climate change, global pressures from urbanization, the already-existing unsustainable variables, and challenges of water supply systems in urban centres pose a challenge in managing water resource effectively. The purpose of the study was to investigate the implication of urban domestic water supply on human health in Machakos Central Ward, Machakos County. Using a Survey Research Design (SRD) both primary and secondary data was collected by use of questionnaires, face-to-face interviews, photography, use of GIS, authors’ observation, and the review of relevant literature in order to (1) document household water supply, (2) determine water quality for the identified categories of households and domestic water supply systems, and (3) Determine how the distribution and coverage of domestic water in a household or home affects the prevalence of water-borne illnesses. The target population was 8,331 households, from which a sample size of 381 respondents was selected. These included households, water vendors and key informants from the Machakos Water and Sewerage Company. Questionnaires (for households and vendors), interview schedules (for water officers and chiefs) and observation schedules were used as instruments for data collection. Data was analysed using Microsoft Excel and Statistical Package for Social Sciences (SPSS) software. The results revealed that the major factors attributed to lower accessibility are shortage of water, high cost of piped water connection, poor coordination, and participation of stakeholders, repairing of old and broken pipes. As a result, nearly half of the dwellers prefer to use alternative sources, exposing them to the risks of water-born diseases

Water resources management under climate change and anthropogenic pressure in the upper Bandama catchment in Northern Côte d'Ivoire

ABSTRACT The upper Bandama basin at Badikaha in the North of Côte d'Ivoire, subject to climate change, has recorded a rapid population growth that significantly affects water availability. This study applies the water evaluation and planning (WEAP) system model to explore how the water resources available currently can meet people's needs in the future, mainly for irrigation, mining activities, rural and urban water supply and cattle breeding. The outputs from two regional climate models RACMO 22T and CCLM 4-8-17 under representative concentration pathway (RCP) 4.5 and RCP 8.5 scenarios were used for the climate change impact assessment. Results predict an increase in mean annual temperature by 1.5°C while precipitation could decrease by 21% by 2090. The climate model outputs coupled with the WEAP model show that unmet water demand estimated to 50 million m3 in 2020 could reach 115 million m3 in 2050. Nevertheless, climate change mitigation scenarios by the WEAP model, including the implementation of dams, boreholes and the hydraulics infrastructure improvement reveal that water scarcity could be reduced significantly in the catchment.

Identification of defects on the inner wall of water supply pipes based on the optimized residual network

ABSTRACT The urban water supply network is part of the infrastructure that sustains the economic and social functions of cities and regions. Timely inspection and maintenance of the network can effectively reduce resource wastage and prevent accidents. Traditional manual detection methods are inefficient and can be based on subjective judgments. A classification model based on an improved ResNet34 network has been proposed to classify and detect various types of corrosion on the inner walls of pipes under challenging conditions. The introduction of the attention mechanism and multi-scale feature fusion modules further improved the model's effectiveness in classifying defects within the inner walls of pipes. The model can detect various types of pipeline corrosion with a detection accuracy of 98.61%. This accuracy is significantly superior to that achieved with traditional models such as ResNet34, AlexNet, MobileNet, and VGGNet.

Optimizing water supply systems in developing regions: a sustainable approach using ESCO model system for urban water supply in Dehradun, India

The critical importance of water makes it an indispensable natural resource. In context of urban infrastructure, particularly in the developing world, supplying water to urban households poses a notable challenge. Optimizing water supply systems (WSS) is one of the most arduous challenges in addressing this issue, primary contributors being energy and water losses during supply process. This paper focuses on the method adopted for minimizing losses in WSSs and creating a self-sustainable model for water supply in the urban settlement of Dehradun, India. The solution entails deployment of Energy Savings Companies (ESCO) service delivery model and the utilization of Supervisory Control and Data Acquisition (SCADA) system. This approach, thus far has yielded saving in both revenue, energy and water consumption at source, potentially generating saving that would enable covering the operational and maintenance changes for the established system for around 10 years.

Numerical modeling of cavity collapse water hammer in pipeline systems: Internal mechanisms and influential factors of transient flow and secondary pressure rise dynamics

This study explores the dynamics of pressure wave propagation and cavitation in pressurized pipelines during and after the rapid closure of the pipeline's end ball valve, utilizing a three-dimensional computational fluid dynamics approach with the method of characteristics, validated against Bergant and Simpson's experimental data of three degrees of cavitation. It innovatively examines transient pressure dynamics through both energy transformation and wave propagation perspectives, focusing on the phases of water column separation and coalescence, and the dynamics of flow interruption bubbles. The research delves into the detailed mechanisms of pressure wave propagation and further assesses the effects of physical factors. Key findings include: (1) As initial inlet velocities increase, cavitation starts earlier, extends further, and intensifies, with higher final volume fractions near the valve, indicating that higher velocities exacerbate cavitation. Higher inlet velocities also correlate with more intricate and expansive vortex formations. (2) Secondary pressure surges in water hammer result from the superposition of two-stage positive pressure waves. Initially, positive pressure waves within the conduit reflect twice from air pockets and the upstream boundary, remaining positive. Subsequently, they interact with secondary positive pressure waves reflected by the valve, causing a secondary pressure surge. (3) The fluid flow is laterally symmetry in the pipe cross section, except for minor local asymmetrical spikes in areas with vapor bubbles. Velocity discrepancies are notable near the pipe walls due to vapor accumulation, primarily on the upper wall due to buoyancy. This accumulation may narrow the flow area, possibly accelerating the water passing by. (4) Lower flow velocities, downward inclines, and slower valve closures diminish secondary pressure rise amplitudes in water hammer events, while reduced static heads intensify cavitation despite lessening pulse amplitudes. These findings offer valuable insights for the design and operational guidance of complex hydraulic systems during transient processes in urban water supplies.