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Sustainability in Water Supply and Smart Water Systems

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A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Sustainable Water Management".

Deadline for manuscript submissions: closed (18 March 2023) | Viewed by 21433

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Special Issue Editors

Dr. Carlo Giudicianni

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Dipartimento di Ingegneria, Università degli Studi della Campania “Luigi Vanvitelli”, via Roma 29, 81031 Aversa, Italy
Interests: water systems analysis and management; water system monitoring; hydroinformatics; resilience assessment; complexity science; smart water systems
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Prof. Dr. Armando Di Nardo

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Dipartimento di Ingegneria, Università degli Studi della Campania “Luigi Vanvitelli”, via Roma 29, 81031 Aversa, Italy
Interests: water network management; water network partitioning; water leakage; complex network theory; critical infrastructure; optimization; smart water network; resilience
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Dr. Manuel Herrera

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Institute for Manufacturing – Department of Engineering, University of Cambridge, 17 Charles Babbage Road, Cambridge CB3 0FS, UK
Interests: network analysis; industrial statistics; digital water; infrastructure resilience; complex systems
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Prof. Dr. Chrysi S. Laspidou

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Department of Civil Engineering, University of Thessaly, Pedion Areos, 38334 Volos, Greece
Interests: resource Nexus and water informatics; mathematical modeling and simulation of physical-chemical and biological processes that take place in natural aquatic systems and other ecosystems; urban water issues; resource depletion and sustainability; virtual water and water-carbon-ecological footprint
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Prof. Dr. Helena M. Ramos

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Department of Civil Engineering, Architecture and Environment, CERIS, Instituto Superior Técnico, University of Lisbon, 1049-001 Lisbon, Portugal
Interests: hydropower; hydraulic transients; pumped-storage; water and energy nexus; hydrodynamic; renewables integration; water-energy efficiency
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Special Issue Information

Dear Colleagues,

Water systems represent a critical, complex, dynamic human–environment coupled system whose management transcends individual scientific disciplines. The ever-increasing water demand due to a growing global population should also face increased resource constraints and the request for an ever more efficient service. This scenario, combined with the ongoing consequences of climate change, makes us stand in front of a paradigm shift based on a mandatory holistic infrastructure management to make a more responsible water use and maximise resilience.

The adaptation today of water management to new technologies has become a key policy. This is by setting out the management framework for sustainable solutions on water resource utilisation. Sustainable water systems comprise combinations of traditional and new components and novel asset management strategies to provide adequate water quantity with appropriate quality for a given need (domestic, agricultural, industrial) without compromising the future ability to assure the desired performance standards. Sustainable water supply represents a crucial aspect of integrated water resource management, according to which multiple stakeholders’ viewpoints are brought and considered together to define how water should be better managed. Consequently, key performance indicators related to technological, economic, social and environmental issues should be taken into account in addition to the more purely technical and hydraulic aspects. This leads to a view of water management defined by a sequence of combined actions and not isolated strategies (from the individual’s willingness to governmental regulations). In this regard, if and only if efficiency in both the supply side (e.g., enhancing operation and maintenance capabilities, reducing non-revenue water, leakages, energy use, fair tariff system and investment planning) and the demand side (e.g., investments in technologies to reduce water consumption, less water intensive industrial processes and more efficient buildings) is guaranteed can a water supply system be considered sustainable.

Urban water systems also need quick integration and sharing of assets and infrastructure across multiple utilities. Therefore, beyond the water–energy nexus, this endeavour definitely also includes the interaction of waste, transport and telecommunications for a global analysis of system efficiency and sustainability. To reach this goal, it is necessary to integrate the analysis, modelling, monitoring, operation and management of water systems using an innovative, sustainable and smart perspective. Indeed, the emergence of digital information and communication technologies (ICT), such as the Internet of Things (IoT), combined with easy access to powerful computing resources and availability of low-cost monitoring technologies, as a consequence, has triggered a paradigm shift towards the concept of smart water systems—that is, intelligent, self-aware systems, enhanced with model- and data-driven management approaches for optimal operation and management of urban water infrastructure. In this context, cyber-physical systems (CPS) represent the driving force for automating and smartening such water systems; combining computing, communication and control, aiming towards:

An informative, global consciousness for water consumption and its impact in natural systems;
Innovative pathways in treatment, contamination detection and reusability;
A response to the climate change pressure in water natural sources and infrastructures.

This Special Issue calls for papers to disseminate and share findings on the sustainable and smart solutions for water systems above described. Critical reviews are also invited. The objective of this Special Issue is to gather contributions on advancing scientific and technical methodologies, technologies, best practices and regulations, exploring alternative solutions for making water systems sustainable and smart. Only if system dynamics are better understood will it be possible to provide more insights for a more sustainable and smart water system design and management.

Dr. Carlo Giudicianni
Prof. Dr. Armando Di Nardo
Dr. Manuel Herrera
Prof. Dr. Chrysi S. Laspidou
Prof. Dr. Helena M. Ramos
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sustainability is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

green cities and green infrastructures
closed-loop water systems
rainwater harvesting
recoverable energy
reclaimed water
adaptive control of urban water network
water safety plan
water–energy–food nexus
pricing and tariff policing
advanced metering infrastructure
cyber-security
machine learning and big data analysis
data-driven approach
decision support systems
intermittent water supply
sustainable design and management
securing actions from contamination
water demand management
green economy
circular economy
sustainable consumption
environmental impact assessment
energy recovery
smart water grids
hybrid energy solutions
water systems efficiency

Published Papers (7 papers)

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Research

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26 pages, 3262 KiB

Open AccessArticle

A Knowledge-Based Engineering System for the Planning of Networked Rainwater Harvesting and Distribution Systems

by Paul Christoph Gembarski, Jan Melching and Stefan Plappert

Sustainability 2023, 15(11), 8636; https://doi.org/10.3390/su15118636 - 26 May 2023

Viewed by 1118

Abstract

Rainwater harvesting attracts growing interest from the field of municipal planning. When considering a rainwater harvesting system as a design object, questions include whether the system is designed for a single property or for a local water network serving multiple properties, what allows for the inclusion of buffer tanks and resource balancing among participants in the network, how to size the tanks, and how robust the system is in the face of changing demands. Knowledge-based engineering provides methods and a tool set for such planning objects. For this article, the authors applied techniques based on model-based and resource-based configuration and Bayesian decision networks to propose a knowledge-based engineering system for residential, networked rainwater harvesting and distribution systems. This enables designers to investigate the effects of different catchment areas, adjust or minimize the storage tank sizes in the grid and evaluate their effect on the individual harvest and the exchange with a central network buffer, evaluate the demands within a neighborhood based on a detailed consumer model also over time, and test the sensitivities of the single sinks and sources to the water grid. For urban planners, this offers the possibility, for example, to make design obligations for housing construction or for the refurbishment of settlements. Full article

(This article belongs to the Special Issue Sustainability in Water Supply and Smart Water Systems)

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18 pages, 2661 KiB

Open AccessArticle

A Multi-Dimensional Investigation on Water Quality of Urban Rivers with Emphasis on Implications for the Optimization of Monitoring Strategy

by Xiaonan Ji, Jianghai Chen and Yali Guo

Sustainability 2022, 14(7), 4174; https://doi.org/10.3390/su14074174 - 31 Mar 2022

Cited by 2 | Viewed by 1661

Abstract

Water quality monitoring (WQM) of urban rivers has been a reliable method to supervise the urban water environment. Indiscriminate WQM strategies can hardly emphasize the concerning pollution and usually require high costs of money, time, and manpower. To tackle these issues, this work carried out a multi-dimensional study (large spatial scale, multiple monitoring parameters, and long time scale) on the water quality of two urban rivers in Jiujiang City, China, which can provide indicative information for the optimization of WQM. Of note, the spatial distribution of NH₃-N concentration varied significantly both in terms of the two different rivers as well as the different sections (i.e., much higher in the northern section), with a maximal difference, on average greater, than five times. Statistical methods and machine learning algorithms were applied to optimize the monitoring objects, parameters, and frequency. The sharp decrease in water quality of adjacent sections was identified by Analytical Hierarchy Process of water quality assessment indexes. After correlation analysis, principal component analysis, and cluster analysis, the various WQM parameters could be divided into three principal components and four clusters. With the machine learning algorithm of Random Forest, the relation between concentration of pollutants and rainfall depth was fitted using quadratic functions (calculated Pearson correlation coefficients ≥ 0.89), which could help predict the pollution after precipitation and further determine the appropriate WQM frequency. Generally, this work provides a novel thought for efficient, smart, and low-cost water quality investigation and monitoring strategy determination, which contributes to the construction of smart water systems and sustainable water source management. Full article

(This article belongs to the Special Issue Sustainability in Water Supply and Smart Water Systems)

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18 pages, 3150 KiB

Open AccessArticle

Computer Architectures for Incremental Learning in Water Management

by Klemen Kenda, Nikolaos Mellios, Matej Senožetnik and Petra Pergar

Sustainability 2022, 14(5), 2886; https://doi.org/10.3390/su14052886 - 02 Mar 2022

Cited by 2 | Viewed by 2205

Abstract

This paper presents an architecture and a platform for processing of water management data in real time. Stakeholders in the domain are faced with the challenge of handling large amounts of incoming sensor data from heterogeneous sources after the digitalization efforts within the sector. Our water management analytical platform (WMAP) is built upon the needs of domain experts (it provides capabilities for offline analysis) and is designed to solve real-world problems (it provides real-time data flow solutions and data-driven predictive analytics) for smart water management. WMAP is expected to contribute significantly to the water management domain, which has not yet acquired the competences to implement extensive data analysis and modeling capabilities in real-world scenarios. The proposed architecture extends existing big data architectures and presents an efficient way of dealing with data-driven modeling in the water management domain. The main improvement is in the speed (online analytics) layer of the architecture, where we introduce heterogeneous data fusion in a set of data streams that provide real-time data-driven modeling and prediction services. Using the proposed architecture, the results illustrate that models built with datasets with richer contextual information and multiple data sources are more accurate and thus more useful. Full article

(This article belongs to the Special Issue Sustainability in Water Supply and Smart Water Systems)

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17 pages, 4145 KiB

Open AccessArticle

Contaminant Flushing in Water Distribution Networks Incorporating Customer Faucet Control

by Malvin S. Marlim and Doosun Kang

Sustainability 2022, 14(4), 2249; https://doi.org/10.3390/su14042249 - 16 Feb 2022

Cited by 2 | Viewed by 1794

Abstract

Contamination events in water distribution networks (WDNs) begin with contaminant inception in the network. WDNs respond to events according to the detection, stopping service, and recovery phases. The recovery phase aims to remove hazardous substances by flushing them out so that the network can return to normal conditions. Flushing must be conducted efficiently and safely. The contaminated water is removed by allowing it to flow from outlet points in the network, which is enabled by displacing it with clean water from the source. Conventionally, a hydrant was used as the outlet point. Recent advancements in information and communication technology allow the use of electronic media to broadcast warnings and guidance rapidly. Water utilities can convey information to customers as part of the flushing scheme by notifying them to open and close their faucets at designated times. In this study, the viability of customer involvement in decontamination was examined. The proposed method was tested by evaluating its effectiveness in terms of the time and volume of water needed for decontamination, and the change in hydraulics to drain a fully contaminated district metered area (DMA). A comparable performance to hydrant flushing was found after testing in two actual DMA-sized WDNs. Full article

(This article belongs to the Special Issue Sustainability in Water Supply and Smart Water Systems)

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15 pages, 3170 KiB

Open AccessArticle

Exploring the Effectiveness of Clustering Algorithms for Capturing Water Consumption Behavior at Household Level

by Alexandra E. Ioannou, Enrico F. Creaco and Chrysi S. Laspidou

Sustainability 2021, 13(5), 2603; https://doi.org/10.3390/su13052603 - 01 Mar 2021

Cited by 5 | Viewed by 2710

Abstract

As water scarcity becomes more prevalent, the analysis of urban water consumption patterns at the consumer level and the estimation of the corresponding water demand for water utility are expected to be among the top priorities of water companies in the near future. This study proposes a comprehensive methodology for water managers to achieve an efficient operation of urban water networks, by successfully detecting residential water consumption patterns corresponding to different household needs and behaviors. The methodology uses Self Organizing Maps as the main clustering algorithm in combination with K-means and Hierarchical Agglomerative Clustering. The objective is to create clusters in a literature dataset that includes water consumption from 21 customers located in Milford, Ohio, USA, for a 7-month period. Originally, water consumption data was recorded for every water use incident in the household, while for this analysis, the information is converted to half-hourly water consumption. Individual customers with similar consumption behavior are clustered and water-consumption curves are calculated for each cluster; these curves can be used by the water utility to obtain estimates of the spatio-temporal distribution of demand, thus giving insight into peak demands at different locations. Statistical indices of agreement are used to confirm a good agreement between the estimated and observed water use, when clustering is employed. The resulting curves show a clear improvement in capturing water consumption behavior at household level, when compared to corresponding curves obtained without clustering. This analysis offers water utilities an innovative solution that relies on real time data and uses data science principles for optimizing water supply and network operation and provides tools for the efficient use of water resources. Full article

(This article belongs to the Special Issue Sustainability in Water Supply and Smart Water Systems)

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Review

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25 pages, 5169 KiB

Open AccessReview

Vietnam’s Water Resources: Current Status, Challenges, and Security Perspective

by Quy-Nhan Pham, Ngoc-Ha Nguyen, Thi-Thoang Ta and Thanh-Le Tran

Sustainability 2023, 15(8), 6441; https://doi.org/10.3390/su15086441 - 10 Apr 2023

Cited by 2 | Viewed by 5636

Abstract

The current status of the exploitation, use, and management of water resources in the context of socioeconomic development, climate change, and issues related to the region are causing negative impacts on the water resources of Vietnam. This study aimed to develop a framework for assessing Vietnam’s water security based on the following key aspects: (i) the availability of water resources; (ii) the current status of water exploitation and use; (iii) the current status of waste water and water pollution; (iv) water resource management organization; and (v) water-related disasters, including floods, droughts, subsidence, coastal erosion, landslides, ecological imbalance, and diseases related to water resources. In particular, the challenges of transboundary water resources and the food–energy–water nexus were investigated. We reviewed the assessment frameworks that have recently been developed outside Vietnam or regions with similar climates and analyzed the characteristics of downstream and rapid-growth countries such as Vietnam using a number of key water resource indicators, both qualitative and quantitative. From these processes, we developed an assessment framework and provided a perspective on water security. The results of this study showed that the challenge of transboundary water resources, the impact of climate change, the pressure on socioeconomic development, and the water–energy–food nexus are core issues that need to be addressed from the perspective of water security in Vietnam. This case study may be helpful for downstream and developing countries. Full article

(This article belongs to the Special Issue Sustainability in Water Supply and Smart Water Systems)

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25 pages, 1829 KiB

Open AccessReview

A Critical Review of Short-Term Water Demand Forecasting Tools—What Method Should I Use?

by Azar Niknam, Hasan Khademi Zare, Hassan Hosseininasab, Ali Mostafaeipour and Manuel Herrera

Sustainability 2022, 14(9), 5412; https://doi.org/10.3390/su14095412 - 30 Apr 2022

Cited by 20 | Viewed by 4288

Abstract

The challenge for city authorities goes beyond managing growing cities, since as cities develop, their exposure to climate change effects also increases. In this scenario, urban water supply is under unprecedented pressure, and the sustainable management of the water demand, in terms of practices including economic, social, environmental, production, and other fields, is becoming a must for utility managers and policy makers. To help tackle these challenges, this paper presents a well-timed review of predictive methods for short-term water demand. For this purpose, over 100 articles were selected from the articles published in water demand forecasting from 2010 to 2021 and classified upon the methods they use. In principle, the results show that traditional time series methods and artificial neural networks are among the most widely used methods in the literature, used in 25% and 20% of the articles in this review. However, the ultimate goal of the current work goes further, providing a comprehensive guideline for engineers and practitioners on selecting a forecasting method to use among the plethora of available options. The overall document results in an innovative reference tool, ready to support demand-informed decision making for disruptive technologies such as those coming from the Internet of Things and cyber–physical systems, as well as from the use of digital twin models of water infrastructure. On top of this, this paper includes a thorough review of how sustainable management objectives have evolved in a new era of technological developments, transforming data acquisition and treatment. Full article

(This article belongs to the Special Issue Sustainability in Water Supply and Smart Water Systems)

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