Special Issue "Smart Urban Water Networks"

A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "Urban Water Management".

Deadline for manuscript submissions: closed (31 January 2021).

Special Issue Editors

Prof. Dr. Armando Di Nardo
E-Mail Website
Guest Editor
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
Special Issues and Collections in MDPI journals
Prof. Dominic L. Boccelli
E-Mail Website
Guest Editor
Department of Civil and Architectural Engineering and Mechanics, University of Arizona, USA
Interests: urban water infrastructure; drinking water distribution networks; real-time modeling; water security; water quality; decision support; uncertainty analysis
Dr. Manuel Herrera
E-Mail Website
Guest Editor
Institute for Manufacturing – Department of Engineering, University of Cambridge, 17 Charles Babbage Road, Cambridge CB3 0FS, UK
Interests: Network science; Graph signal processing; Distributed AI; Decentralized systems; Predictive analytics; Critical infrastructure; Asset management; Digital water
Special Issues and Collections in MDPI journals
Prof. Dr. Enrico Creaco
E-Mail Website
Guest Editor
DICAr, University of Pavia, Via Ferrata 3, 27100 Pavia, Italy
Interests: water distribution modelling; urban drainage modelling; real-time control; sediment transport in sewers; sustainable solutions for urban drainage systems; flood control in urban areas
Special Issues and Collections in MDPI journals
Prof. Dr. Andrea Cominola
E-Mail Website
Guest Editor
Chair of Smart Water Networks, Technische Universität Berlin and Einstein Center Digital Future, 10623, Berlin, Germany
Interests: digitization of water systems; demand-side management; water–energy nexus, smart metering, non-intrusive load monitoring, data-driven behavior modelling; anomaly detection; water conservation
Special Issues and Collections in MDPI journals
Dr. Riccardo Taormina
E-Mail Website
Guest Editor
Assistant Professor in Urban Water Infrastructure, Department of Water Management, TU Delft
Interests: urban water infrastructure, digital water, smart urban water networks, artificial intelligence, machine learning, data science, cyber-physical security, cyber-physical systems, cyber-security
Prof. Dr. Robert Sitzenfrei
E-Mail Website
Guest Editor
Unit of Environmental Engineering, University of Innsbruck, 6020 Innsbruck, Austria
Interests: modelling of urban water networks; complex network analysis; transition modelling; Smart Water City
Special Issues and Collections in MDPI journals

Special Issue Information

Dear Colleagues,

The deployment of digital information and communication technology (ICT) in different assets of urban life has contributed to generating the notion of the Smart City, recently recognized in the scientific and technical international community (Chourabi et al. 2012) as a city where the use of ICT allows making “the critical infrastructure components and services—which include city administration, education, healthcare, public safety, real estate, transportation and utilities—more intelligent, interconnected and efficient” (Washburn et al. 2010).

The development of new monitoring and control sensor technologies and the recent growth of computational power used by simulation software have changed the traditional paradigms to analyze, design, and manage water distribution systems (WDSs) towards data-driven approaches fed by big sensor data (Lambert 2002). The availability of low-cost monitoring and management devices, controlled by remote systems, is pushing WDSs to fill the technological gap with other network utilities, such as electricity, gas, Internet, etc. This transition of WDSs pushed by ICTs has also generated the new concept of the smart water network (SWAN) as a key subsystem of the Smart City.

Further, in the more general framework of Industry 4.0, the recent development of Internet of Things (IoT) technologies applied to smart-grids opens novel opportunities in the management of water network systems and beyond.

At the current state, it is possible to imagine novel solutions based on these innovations to study, analyze, protect, and improve on some traditional challenges in water distribution systems, such as water losses, pressure management, optimal maintenance, water protection from accidental and intentional contamination, network calibration, water use identification, water demand modelling and management, water network partitioning, adaptive and dynamic control, etc., as well as new challenges raised in the digital era (e.g., cyber-security), thus transforming the traditional operational criteria and contributing to an increase in the resilience of urban water systems. In addition, novel concepts by cross-linking the urban water infrastructure to other fields like energy grids, urban drainage, smart homes, etc. can enable the integrated Smart City.

The objective of this Special Issue is to gather contributions advancing scientific and technical methodologies, technologies, and best practices that can be applied with the implementation of actual computational power in simulation, IoT systems, and smart meter devices. Through this open access journal, this will show, to a wide community of researchers, operators, and water utilities, the possibilities to significantly improve some operational problems of water distribution networks by coupling ICT technologies and physically-based mathematical procedures and data-driven techniques such as identification, optimization, complex network theory, etc. This will foster the digitization of urban water networks towards the realization of the vision of smart cities and societies.

Prof. Armando Di Nardo
Prof. Dominic L. Boccelli
Dr. Manuel Herrera
Prof. Enrico Creaco
Prof. Andrea Cominola
Dr. Riccardo Taormina
Prof. Robert Sitzenfrei
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 papers will be 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. Water 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 2000 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

  • innovative methodologies, techniques and technology for smart water systems
  • optimal network design and management  
  • innovative modeling approaches for smart urban water network
  • application of IoT in smart urban water systems
  • adaptive control of urban water network
  • big data for water utilities management
  • identification and disaggregation of water demand
  • divide-and-conquer techniques for water network partitioning
  • innovative metrics for resilience computation in smart water networks
  • actions to protect water distribution networks from accidental and intentional contamination
  • water safety plan in urban water systems
  • residential water demand management
  • data-driven water demand modeling
  • non-intrusive load monitoring
  • water and energy nexus
  • end use disaggregation of water consumption
  • water demand user profiling
  • behavioral modeling
  • energy demand management
  • machine learning and big data for urban water systems
  • decision support systems for smart urban water
  • hydroinformatic applications in water distribution networks
  • innovative intermittent uses in drought periods
  • pump and turbine (PAT)  
  • pricing and tariff policing for water uses
  • cyber-security of urban water networks

Published Papers (16 papers)

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Editorial

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Editorial
Smart Urban Water Networks: Solutions, Trends and Challenges
Water 2021, 13(4), 501; https://doi.org/10.3390/w13040501 - 15 Feb 2021
Viewed by 789
Abstract
This Editorial presents the paper collection of the Special Issue (SI) on Smart Urban Water Networks [...] Full article
(This article belongs to the Special Issue Smart Urban Water Networks)

Research

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Article
Cyber-Attack Detection in Water Distribution Systems Based on Blind Sources Separation Technique
Water 2021, 13(6), 795; https://doi.org/10.3390/w13060795 - 14 Mar 2021
Viewed by 540
Abstract
Service quality and efficiency of urban systems have been dramatically boosted by various high technologies for real-time monitoring and remote control, and have also gained privileged space in water distribution. Monitored hydraulic and quality parameters are crucial data for developing planning, operation and [...] Read more.
Service quality and efficiency of urban systems have been dramatically boosted by various high technologies for real-time monitoring and remote control, and have also gained privileged space in water distribution. Monitored hydraulic and quality parameters are crucial data for developing planning, operation and security analyses in water networks, which makes them increasingly reliable. However, devices for monitoring and remote control also increase the possibilities for failure and cyber-attacks in the systems, which can severely impair the system operation and, in extreme cases, collapse the service. This paper proposes an automatic two-step methodology for cyber-attack detection in water distribution systems. The first step is based on signal-processing theory, and applies a fast Independent Component Analysis (fastICA) algorithm to hydraulic time series (e.g., pressure, flow, and tank level), which separates them into independent components. These components are then processed by a statistical control algorithm for automatic detection of abrupt changes, from which attacks may be disclosed. The methodology is applied to the case study provided by the Battle of Attack Detection Algorithms (BATADAL) and the results are compared with seven other approaches, showing excellent results, which makes this methodology a reliable early-warning cyber-attack detection approach. Full article
(This article belongs to the Special Issue Smart Urban Water Networks)
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Article
A Smart Water Grid for Micro-Trading Rainwater: Hydraulic Feasibility Analysis
Water 2020, 12(11), 3075; https://doi.org/10.3390/w12113075 - 02 Nov 2020
Cited by 1 | Viewed by 650
Abstract
Water availability is increasingly stressed in cities across the world due to population growth, which increases demands, and climate change, which can decrease supply. Novel water markets and water supply paradigms are emerging to address water shortages in the urban environment. This research [...] Read more.
Water availability is increasingly stressed in cities across the world due to population growth, which increases demands, and climate change, which can decrease supply. Novel water markets and water supply paradigms are emerging to address water shortages in the urban environment. This research develops a new peer-to-peer non-potable water market that allows households to capture, use, sell, and buy rainwater within a network of water users. A peer-to-peer non-potable water market, as envisioned in this research, would be enabled by existing and emerging technologies. A dual reticulation system, which circulates non-potable water, serves as the backbone for the water trading network by receiving water from residential rainwater tanks and distributing water to households for irrigation purposes. Prosumer households produce rainwater by using cisterns to collect and store rainwater and household pumps to inject rainwater into the network at sufficiently high pressures. The smart water grid would be enabled through an array of information and communication technologies that provide capabilities for automated and real-time metering of water flow, control of infrastructure, and trading between households. The goal of this manuscript is to explore and test the hydraulic feasibility of a micro-trading system through an agent-based modeling approach. Prosumer households are represented as agents that store rainwater and pump rainwater into the network; consumer households are represented as agents that withdraw water from the network for irrigation demands. An all-pipe hydraulic model is constructed and loosely coupled with the agent-based model to simulate network hydraulics. A set of scenarios are analyzed to explore how micro-trading performs based on the level of irrigation demands that could realistically be met through decentralized trading; pressure and energy requirements at prosumer households; pressure and water quality in the pipe network. Full article
(This article belongs to the Special Issue Smart Urban Water Networks)
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Article
Is Clustering Time-Series Water Depth Useful? An Exploratory Study for Flooding Detection in Urban Drainage Systems
Water 2020, 12(9), 2433; https://doi.org/10.3390/w12092433 - 30 Aug 2020
Cited by 2 | Viewed by 1009
Abstract
As sensor measurements emerge in urban water systems, data-driven unsupervised machine learning algorithms have drawn tremendous interest in event detection and hydraulic water level and flow prediction recently. However, most of them are applied in water distribution systems and few studies consider using [...] Read more.
As sensor measurements emerge in urban water systems, data-driven unsupervised machine learning algorithms have drawn tremendous interest in event detection and hydraulic water level and flow prediction recently. However, most of them are applied in water distribution systems and few studies consider using unsupervised cluster analysis to group the time-series hydraulic-hydrologic data in stormwater urban drainage systems. To improve the understanding of how cluster analysis contributes to flooding location detection, this study compared the performance of K-means clustering, agglomerative clustering, and spectral clustering in uncovering time-series water depth dissimilarity. In this work, the water depth datasets are simulated by an urban drainage model and then formatted for a clustering problem. Three standard performance evaluation metrics, namely the silhouette coefficient index, Calinski–Harabasz index, and Davies–Bouldin index are employed to assess the clustering performance in flooding detection under various storms. The results show that silhouette coefficient index and Davies–Bouldin index are more suitable for assessing the performance of K-means and agglomerative clustering, while the Calinski–Harabasz index only works for spectral clustering, indicating these clustering algorithms are metric-dependent flooding indicators. The results also reveal that the agglomerative clustering performs better in detecting short-duration events while K-means and spectral clustering behave better in detecting long-duration floods. The findings of these investigations can be employed in urban stormwater flood detection at the specific junction-level sites by using the occurrence of anomalous changes in water level of correlated clusters as flood early warning for the local neighborhoods. Full article
(This article belongs to the Special Issue Smart Urban Water Networks)
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Article
Comparative Analysis of Reliability Indices and Hydraulic Measures for Water Distribution Network Performance Evaluation
Water 2020, 12(9), 2399; https://doi.org/10.3390/w12092399 - 26 Aug 2020
Cited by 1 | Viewed by 686
Abstract
The performance of water distribution networks (WDNs) can be quantified by several types of hydraulic measure. In design and operation of a WDN, sufficient consideration should be given to system performance, and it would be inefficient to separately consider individual characteristics of hydraulic [...] Read more.
The performance of water distribution networks (WDNs) can be quantified by several types of hydraulic measure. In design and operation of a WDN, sufficient consideration should be given to system performance, and it would be inefficient to separately consider individual characteristics of hydraulic measures. Instead, various reliability indices have been developed and utilized to evaluate the performance of WDNs; however, deciding which index to use according to a particular WDN situation has not been investigated in sufficient depth. In this regard, this study analyzes the correlation between representative reliability indices and hydraulic measures to propose the most adequate reliability index according to the desired system performance in various situations. Specifically, six hydraulic measures representing system performance were selected from the viewpoint of redundancy, robustness, and serviceability. In addition, nine indices for estimating system reliability were classified based on theoretical backgrounds such as hydraulic, topological, entropic, and mixed approaches. The correlations between the nine indices and six measures were analyzed using 17 sample hypothetical networks with different layouts, under three water supply scenarios, and the overall evaluation results for each reliability index are presented through multi-criteria decision analysis. Full article
(This article belongs to the Special Issue Smart Urban Water Networks)
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Article
Spatial Aggregation Effect on Water Demand Peak Factor
Water 2020, 12(7), 2019; https://doi.org/10.3390/w12072019 - 16 Jul 2020
Cited by 3 | Viewed by 595
Abstract
A methodological framework for the estimation of the expected value of hourly peak water demand factor and its dependence on the spatial aggregation level is presented. The proposed methodology is based on the analysis of volumetric water meter measurements with a 1-h time [...] Read more.
A methodological framework for the estimation of the expected value of hourly peak water demand factor and its dependence on the spatial aggregation level is presented. The proposed methodology is based on the analysis of volumetric water meter measurements with a 1-h time aggregation, preferred by water companies for monitoring purposes. Using a peculiar sampling design, both a theoretical and an empirical estimation of the expected value of the peak factor and of the related standard error (confidence bands) are obtained as a function of the number of aggregated households (or equivalently of the number of users). The proposed methodology accounts for the cross-correlation among consumption time series describing local water demand behaviours. The effects of considering a finite population is also discussed. The framework is tested on a pilot District Metering Area with more than 1000 households equipped with a telemetry system with 1-h time aggregation. Results show that the peak factor can be expressed as a power function tending to an asymptotic value greater than one for the increasing number of aggregated households. The obtained peak values, compared with several literature studies, provide useful indications for the design and management of secondary branched pipes of water distribution systems. Full article
(This article belongs to the Special Issue Smart Urban Water Networks)
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Article
Hybrid Model for Short-Term Water Demand Forecasting Based on Error Correction Using Chaotic Time Series
Water 2020, 12(6), 1683; https://doi.org/10.3390/w12061683 - 12 Jun 2020
Cited by 1 | Viewed by 736
Abstract
Short-term water demand forecasting plays an important role in smart management and real-time simulation of water distribution systems (WDSs). This paper proposes a hybrid model for the short-term forecasting in the horizon of one day with 15 min time steps, which improves the [...] Read more.
Short-term water demand forecasting plays an important role in smart management and real-time simulation of water distribution systems (WDSs). This paper proposes a hybrid model for the short-term forecasting in the horizon of one day with 15 min time steps, which improves the forecasting accuracy by adding an error correction module to the initial forecasting model. The initial forecasting model is firstly established based on the least square support vector machine (LSSVM), the errors time series obtained by comparing the observed values and the initial forecasted values is next transformed into chaotic time series, and then the error correction model is established by the LSSVM method to forecast errors at the next time step. The hybrid model is tested on three real-world district metering areas (DMAs) in Beijing, China, with different demand patterns. The results show that, with the help of the error correction module, the hybrid model reduced the mean absolute percentage error (MAPE) of forecasted demand from (5.64%, 4.06%, 5.84%) to (4.84%, 3.15%, 3.47%) for the three DMAs, compared with using LSSVM without error correction. Therefore, the proposed hybrid model provides a better solution for short-term water demand forecasting on the tested cases. Full article
(This article belongs to the Special Issue Smart Urban Water Networks)
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Article
On the Use of an IoT Integrated System for Water Quality Monitoring and Management in Wastewater Treatment Plants
Water 2020, 12(4), 1096; https://doi.org/10.3390/w12041096 - 12 Apr 2020
Cited by 5 | Viewed by 2227
Abstract
The deteriorating water environment demands new approaches and technologies to achieve sustainable and smart management of urban water systems. Wireless sensor networks represent a promising technology for water quality monitoring and management. The use of wireless sensor networks facilitates the improvement of current [...] Read more.
The deteriorating water environment demands new approaches and technologies to achieve sustainable and smart management of urban water systems. Wireless sensor networks represent a promising technology for water quality monitoring and management. The use of wireless sensor networks facilitates the improvement of current centralized systems and traditional manual methods, leading to decentralized smart water quality monitoring systems adaptable to the dynamic and heterogeneous water distribution infrastructure of cities. However, there is a need for a low-cost wireless sensor node solution on the market that enables a cost-effective deployment of this new generation of systems. This paper presents the integration to a wireless sensor network and a preliminary validation in a wastewater treatment plant scenario of a low-cost water quality monitoring device in the close-to-market stage. This device consists of a nitrate and nitrite analyzer based on a novel ion chromatography detection method. The analytical device is integrated using an Internet of Things software platform and tested under real conditions. By doing so, a decentralized smart water quality monitoring system that is conceived and developed for water quality monitoring and management is accomplished. In the presented scenario, such a system allows online near-real-time communication with several devices deployed in multiple water treatment plants and provides preventive and data analytics mechanisms to support decision making. The results obtained comparing laboratory and device measured data demonstrate the reliability of the system and the analytical method implemented in the device. Full article
(This article belongs to the Special Issue Smart Urban Water Networks)
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Article
Optimal Placement of Pressure Sensors Using Fuzzy DEMATEL-Based Sensor Influence
Water 2020, 12(2), 493; https://doi.org/10.3390/w12020493 - 12 Feb 2020
Cited by 5 | Viewed by 1095
Abstract
Nowadays, optimal sensor placement (OSP) for leakage detection in water distribution networks is a lively field of research, and a challenge for water utilities in terms of network control, management, and maintenance. How many sensors to install and where to install them are [...] Read more.
Nowadays, optimal sensor placement (OSP) for leakage detection in water distribution networks is a lively field of research, and a challenge for water utilities in terms of network control, management, and maintenance. How many sensors to install and where to install them are crucial decisions to make for those utilities to reach a trade-off between efficiency and economy. In this paper, we address the where-to-install-them part of the OSP through the following elements: nodes’ sensitivity to leakage, uncertainty of information, and redundancy through conditional entropy maximisation. We evaluate relationships among candidate sensors in a network to get a picture of the mutual influence among the nodes. This analysis is performed within a multi-criteria decision-making approach: specifically, a herein proposed variant of DEMATEL, which uses fuzzy logic and builds comparison matrices derived from information obtained through leakage simulations of the network. We apply the proposal first to a toy example to show how the approach works, and then to a real-world case study. Full article
(This article belongs to the Special Issue Smart Urban Water Networks)
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Article
Reducing Impacts of Contamination in Water Distribution Networks: A Combined Strategy Based on Network Partitioning and Installation of Water Quality Sensors
Water 2019, 11(6), 1315; https://doi.org/10.3390/w11061315 - 25 Jun 2019
Cited by 12 | Viewed by 1590
Abstract
This paper proposes a combined management strategy for monitoring water distribution networks (WDNs). This strategy is based on the application of water network partitioning (WNP) for the creation of district metered areas (DMAs) and on the installation of sensors for water quality monitoring. [...] Read more.
This paper proposes a combined management strategy for monitoring water distribution networks (WDNs). This strategy is based on the application of water network partitioning (WNP) for the creation of district metered areas (DMAs) and on the installation of sensors for water quality monitoring. The proposed methodology was tested on a real WDN, showing that boundary pipes, at which flowmeters are installed to monitor flow, are good candidate locations for sensor installation, when considered along with few other nodes detected through topological criteria on the partitioned WDN. The option of considering only these potential locations, instead of all WDN nodes, inside a multi-objective optimization process, helps in reducing the search space of possible solutions and, ultimately, the computational burden. The solutions obtained with the optimization are effective in reducing affected population and detection time in contamination scenarios, and in increasing detection likelihood and redundancy of the monitoring system. Last but most importantly, these solutions offer benefits in terms of management and costs. In fact, installing a sensor alongside the flowmeter present between two adjacent DMAs yields managerial advantages associated with the closeness of the two devices. Furthermore, economic benefits due to the possibility of sharing some electronical components for data acquisition, saving, and transmission are derived. Full article
(This article belongs to the Special Issue Smart Urban Water Networks)
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Article
An Inverse Transient-Based Optimization Approach to Fault Examination in Water Distribution Networks
Water 2019, 11(6), 1154; https://doi.org/10.3390/w11061154 - 01 Jun 2019
Cited by 2 | Viewed by 1264
Abstract
This research introduces an inverse transient-based optimization approach to automatically detect potential faults, such as leaks, partial blockages, and distributed deteriorations, within pipelines or a water distribution network (WDN). The optimization approach is named the Pipeline Examination Ordinal Symbiotic Organism Search (PEOS). A [...] Read more.
This research introduces an inverse transient-based optimization approach to automatically detect potential faults, such as leaks, partial blockages, and distributed deteriorations, within pipelines or a water distribution network (WDN). The optimization approach is named the Pipeline Examination Ordinal Symbiotic Organism Search (PEOS). A modified steady hydraulic model considering the effects of pipe aging within a system is used to determine the steady nodal heads and piping flow rates. After applying a transient excitation, the transient behaviors in the system are analyzed using the method of characteristics (MOC). A preliminary screening mechanism is adopted to sift the initial organisms (solutions) to perform better to reduce most of the unnecessary calculations caused by incorrect solutions within the PEOS framework. Further, a symbiotic organism search (SOS) imitates symbiotic relationship strategies to move organisms toward the current optimal organism and eliminate the worst ones. Two experiments on leak and blockage detection in a single pipeline that have been presented in the literature were used to verify the applicability of the proposed approach. Two hypothetical WDNs, including a small-scale and large-scale system, were considered to validate the efficiency, accuracy, and robustness of the proposed approach. The simulation results indicated that the proposed approach obtained more reliable and efficient optimal results than other algorithms did. We believe the proposed fault detection approach is a promising technique in detecting faults in field applications. Full article
(This article belongs to the Special Issue Smart Urban Water Networks)
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Article
Comparison of Flow-Dependent Controllers for Remote Real-Time Pressure Control in a Water Distribution System with Stochastic Consumption
Water 2019, 11(3), 422; https://doi.org/10.3390/w11030422 - 27 Feb 2019
Cited by 7 | Viewed by 1130
Abstract
The control of pressure at a remote critical node using a pressure control valve is a highly effective way to attain pressure management. To perform real-time control, various kinds of controllers can be used, including flow-dependent controllers. These controllers calculate valve setting adjustment [...] Read more.
The control of pressure at a remote critical node using a pressure control valve is a highly effective way to attain pressure management. To perform real-time control, various kinds of controllers can be used, including flow-dependent controllers. These controllers calculate valve setting adjustment based both on the deviation of the pressure from the set-point and on the flow rate at the valve site. After putting all the flow-dependent controllers present in the scientific literature within the same framework, this paper presents a numerical comparison of their performance under realistic conditions of stochastic demand. Two controllers were selected for the comparison, namely the simple LCF (parameter-less proportional controller with known constant pressure control valve flow); and LVF (parameter-less controller with known variable pressure control valve flow), which uses a flow rate forecast. Indeed, this study considered an upgrade of LVF, in which the flow rate forecast was tailored to the conditions of stochastic demand. The application in a specific example network proved the performance of these controllers to be quite similar, although LCF was preferable due to its simple structure. For LCF, the average pressure at the critical node had a clear relationship to the consumption pattern. LVF outperformed when the hourly variation dominates the fluctuations in the flow. The conditions under which this out-performance occurred are comprehensively discussed. Full article
(This article belongs to the Special Issue Smart Urban Water Networks)
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Review

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Review
A Systematic Review of the State of Cyber-Security in Water Systems
Water 2021, 13(1), 81; https://doi.org/10.3390/w13010081 - 01 Jan 2021
Cited by 3 | Viewed by 1188
Abstract
Critical infrastructure systems are evolving from isolated bespoke systems to those that use general-purpose computing hosts, IoT sensors, edge computing, wireless networks and artificial intelligence. Although this move improves sensing and control capacity and gives better integration with business requirements, it also increases [...] Read more.
Critical infrastructure systems are evolving from isolated bespoke systems to those that use general-purpose computing hosts, IoT sensors, edge computing, wireless networks and artificial intelligence. Although this move improves sensing and control capacity and gives better integration with business requirements, it also increases the scope for attack from malicious entities that intend to conduct industrial espionage and sabotage against these systems. In this paper, we review the state of the cyber-security research that is focused on improving the security of the water supply and wastewater collection and treatment systems that form part of the critical national infrastructure. We cover the publication statistics of the research in this area, the aspects of security being addressed, and future work required to achieve better cyber-security for water systems. Full article
(This article belongs to the Special Issue Smart Urban Water Networks)
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Review
Urban Water Consumption at Multiple Spatial and Temporal Scales. A Review of Existing Datasets
Water 2021, 13(1), 36; https://doi.org/10.3390/w13010036 - 28 Dec 2020
Cited by 4 | Viewed by 1157
Abstract
Over the last three decades, the increasing development of smart water meter trials and the rise of demand management has fostered the collection of water demand data at increasingly higher spatial and temporal resolutions. Counting these new datasets and more traditional aggregate water [...] Read more.
Over the last three decades, the increasing development of smart water meter trials and the rise of demand management has fostered the collection of water demand data at increasingly higher spatial and temporal resolutions. Counting these new datasets and more traditional aggregate water demand data, the literature is rich with heterogeneous urban water demand datasets. They are characterized by heterogeneous spatial scales—from urban districts, to households or individual water fixtures—and temporal sampling frequencies—from seasonal/monthly up to sub-daily (minutes or seconds). Motivated by the need of tracking the existing datasets in this rapidly evolving field of investigation, this manuscript is the first comprehensive review effort of the state-of-the-art urban water demand datasets. This paper contributes a review of 92 water demand datasets and 120 related peer-review publications compiled in the last 45 years. The reviewed datasets are classified and analyzed according to the following criteria: spatial scale, temporal scale, and dataset accessibility. This research effort builds an updated catalog of the existing water demand datasets to facilitate future research efforts end encourage the publication of open-access datasets in water demand modelling and management research. Full article
(This article belongs to the Special Issue Smart Urban Water Networks)
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Review
Water Network Partitioning into District Metered Areas: A State-Of-The-Art Review
Water 2020, 12(4), 1002; https://doi.org/10.3390/w12041002 - 01 Apr 2020
Cited by 11 | Viewed by 1739
Abstract
A water distribution network (WDN) is an indispensable element of civil infrastructure that provides fresh water for domestic use, industrial development, and fire-fighting. However, in a large and complex network, operation and management (O&M) can be challenging. As a technical initiative to improve [...] Read more.
A water distribution network (WDN) is an indispensable element of civil infrastructure that provides fresh water for domestic use, industrial development, and fire-fighting. However, in a large and complex network, operation and management (O&M) can be challenging. As a technical initiative to improve O&M efficiency, the paradigm of “divide and conquer” can divide an original WDN into multiple subnetworks. Each subnetwork is controlled by boundary pipes installed with gate valves or flow meters that control the water volume entering and leaving what are known as district metered areas (DMAs). Many approaches to creating DMAs are formulated as two-phase procedures, clustering and sectorizing, and are called water network partitioning (WNP) in general. To assess the benefits and drawbacks of DMAs in a WDN, we provide a comprehensive review of various state-of-the-art approaches, which can be broadly classified as: (1) Clustering algorithms, which focus on defining the optimal configuration of DMAs; and (2) sectorization procedures, which physically decompose the network by selecting pipes for installing flow meters or gate valves. We also provide an overview of emerging problems that need to be studied. Full article
(This article belongs to the Special Issue Smart Urban Water Networks)
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Review
Rethinking the Framework of Smart Water System: A Review
Water 2020, 12(2), 412; https://doi.org/10.3390/w12020412 - 04 Feb 2020
Cited by 10 | Viewed by 2305
Abstract
Throughout the past years, governments, industries, and researchers have shown increasing interest in incorporating smart techniques, including sensor monitoring, real-time data transmitting, and real-time controlling into water systems. However, the design and construction of such a smart water system are still not quite [...] Read more.
Throughout the past years, governments, industries, and researchers have shown increasing interest in incorporating smart techniques, including sensor monitoring, real-time data transmitting, and real-time controlling into water systems. However, the design and construction of such a smart water system are still not quite standardized for massive applications due to the lack of consensus on the framework. The major challenge impeding wide application of the smart water network is the unavailability of a systematic framework to guide real-world design and deployment. To address this challenge, this review study aims to facilitate more extensive adoption of the smart water system, to increase effectiveness and efficiency in real-world water system contexts. A total of 32 literature pieces including 1 international forum, 17 peer-reviewed papers, 10 reports, and 4 presentations that are directly related to frameworks of smart water system have been reviewed. A new and comprehensive smart water framework, including definition and architecture, was proposed in this review paper. Two conceptual metrics (smartness and cyber wellness) were defined to evaluate the performance of smart water systems. Additionally, three pieces of future research suggestions were discussed, calling for broader collaboration in the community of researchers, engineers, and industrial and governmental sectors to promote smart water system applications. Full article
(This article belongs to the Special Issue Smart Urban Water Networks)
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