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Ardila A, Rodriguez MJ, Pelletier G. Spatiotemporal optimization of water quality degradation monitoring in water distribution systems supplied by surface sources: A chronological and critical review. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2023; 337:117734. [PMID: 36996548 DOI: 10.1016/j.jenvman.2023.117734] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/22/2022] [Revised: 02/14/2023] [Accepted: 03/10/2023] [Indexed: 06/19/2023]
Abstract
Drinking water may undergo spatiotemporal changes in quality as it leaves the treatment plant and enters the distribution system. This variability means that not all consumers receive water of the same quality. Monitoring water quality in distribution networks makes it possible to verify the compliance of current regulations and reduce consumption risks associated with water quality degradation. An inaccurate interpretation of the spatiotemporal variability of water quality affects the selection of monitoring locations and the sampling frequency, which may conceal problems with the water quality and increase consumers' risk. This paper presents a chronological and critical review of the literature on the evolution, benefits and limitations of methodologies for the optimization of water quality degradation monitoring in water distribution systems supplied by surface sources. This review compares the different methodologies and examines the types of approaches, optimization objectives, variables, and types of spatial and temporal analysis, as well as the main advantages and limitations. A cost-benefit analysis was conducted to assess applicability in different-sized municipalities (small, medium and large). Future research recommendations for optimal water quality monitoring in distribution networks are also provided.
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Affiliation(s)
- Andres Ardila
- Graduate School of Land Planning and Regional Development, Faculty of Planning, Architecture, Art and Design, Université Laval, CA, Québec, G1V 0A6, Canada.
| | - Manuel J Rodriguez
- Graduate School of Land Planning and Regional Development, Faculty of Planning, Architecture, Art and Design, Université Laval, CA, Québec, G1V 0A6, Canada.
| | - Geneviève Pelletier
- Department of Civil and Water Engineering, Faculty of Sciences and Engineering, Université Laval, CA, Québec, G1V 0A6, Canada.
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Huang Y, Wang X, Xiang W, Wang T, Otis C, Sarge L, Lei Y, Li B. Forward-Looking Roadmaps for Long-Term Continuous Water Quality Monitoring: Bottlenecks, Innovations, and Prospects in a Critical Review. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2022; 56:5334-5354. [PMID: 35442035 PMCID: PMC9063115 DOI: 10.1021/acs.est.1c07857] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/17/2021] [Revised: 04/05/2022] [Accepted: 04/06/2022] [Indexed: 05/29/2023]
Abstract
Long-term continuous monitoring (LTCM) of water quality can bring far-reaching influences on water ecosystems by providing spatiotemporal data sets of diverse parameters and enabling operation of water and wastewater treatment processes in an energy-saving and cost-effective manner. However, current water monitoring technologies are deficient for long-term accuracy in data collection and processing capability. Inadequate LTCM data impedes water quality assessment and hinders the stakeholders and decision makers from foreseeing emerging problems and executing efficient control methodologies. To tackle this challenge, this review provides a forward-looking roadmap highlighting vital innovations toward LTCM, and elaborates on the impacts of LTCM through a three-hierarchy perspective: data, parameters, and systems. First, we demonstrate the critical needs and challenges of LTCM in natural resource water, drinking water, and wastewater systems, and differentiate LTCM from existing short-term and discrete monitoring techniques. We then elucidate three steps to achieve LTCM in water systems, consisting of data acquisition (water sensors), data processing (machine learning algorithms), and data application (with modeling and process control as two examples). Finally, we explore future opportunities of LTCM in four key domains, water, energy, sensing, and data, and underscore strategies to transfer scientific discoveries to general end-users.
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Affiliation(s)
- Yuankai Huang
- Department
of Civil and Environmental Engineering, University of Connecticut, Storrs, Connecticut 06269, United States
| | - Xingyu Wang
- Department
of Civil and Environmental Engineering, University of Connecticut, Storrs, Connecticut 06269, United States
| | - Wenjun Xiang
- Department
of Civil and Environmental Engineering, University of Connecticut, Storrs, Connecticut 06269, United States
| | - Tianbao Wang
- Department
of Civil and Environmental Engineering, University of Connecticut, Storrs, Connecticut 06269, United States
| | - Clifford Otis
- Department
of Civil and Environmental Engineering, University of Connecticut, Storrs, Connecticut 06269, United States
| | - Logan Sarge
- Department
of Civil and Environmental Engineering, University of Connecticut, Storrs, Connecticut 06269, United States
| | - Yu Lei
- Department
of Chemical and Biomolecular Engineering, University of Connecticut, Storrs, Connecticut 06269, United States
| | - Baikun Li
- Department
of Civil and Environmental Engineering, University of Connecticut, Storrs, Connecticut 06269, United States
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Evaluating the Pressure and Loss Behavior in Water Pipes Using Smart Mathematical Modelling. WATER 2021. [DOI: 10.3390/w13243500] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Due to the constant need to enhance water supply sources, water operators are searching for solutions to maintain water quality through leakage protection. The capability to monitor the day-to-day water supply management is one of the most significant operational challenges for water companies. These companies are looking for ways to predict how to improve their supply operations in order to remain competitive, given the rising demand. This work focuses on the mathematical modeling of water flow and losses through leak openings in the smart pipe system. The research introduces smart mathematical models that water companies may use to predict water flow, losses, and performance, thereby allowing issues and challenges to be effectively managed. So far, most of the modeling work in water operations has been based on empirical data rather than mathematically described process relationships, which is addressed in this study. Moreover, partial submersion had a power relationship, but a total immersion was more likely to have a linear power relationship. It was discovered in the experiment that the laminar flows had Reynolds numbers smaller than 2000. However, when testing with transitional flows, Reynolds numbers were in the range of 2000 to 4000. Furthermore, tests with turbulent flow revealed that the Reynolds number was more than 4000. Consequently, the main loss in a 30 mm diameter pipe was 0.25 m, whereas it was 0.01 m in a 20 mm diameter pipe. However, the fitting pipe had a minor loss of 0.005 m, whereas the bending pipe had a loss of 0.015 m. Consequently, mathematical models are required to describe, forecast, and regulate the complex relationships between water flow and losses, which is a concept that water supply companies are familiar with. Therefore, these models can assist in designing and operating water processes, allowing for improved day-to-day performance management.
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Optimal Water Quality Sensor Placement by Accounting for Possible Contamination Events in Water Distribution Networks. WATER 2021. [DOI: 10.3390/w13151999] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Contamination in water distribution networks (WDNs) can occur at any time and location. One protection measure in WDNs is the placement of water quality sensors (WQSs) to detect contamination and provide information for locating the potential contamination source. The placement of WQSs in WDNs must be optimally planned. Therefore, a robust sensor-placement strategy (SPS) is vital. The SPS should have clear objectives regarding what needs to be achieved by the sensor configuration. Here, the objectives of the SPS were set to cover the contamination event stages of detection, consumption, and source localization. As contamination events occur in any form of intrusion, at any location and time, the objectives had to be tested against many possible scenarios, and they needed to reach a fair value considering all scenarios. In this study, the particle swarm optimization (PSO) algorithm was selected as the optimizer. The SPS was further reinforced using a databasing method to improve its computational efficiency. The performance of the proposed method was examined by comparing it with a benchmark SPS example and applying it to DMA-sized, real WDNs. The proposed optimization approach improved the overall fitness of the configuration by 23.1% and showed a stable placement behavior with the increase in sensors.
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Sela L, Abbas W. Distributed Sensing for Monitoring Water Distribution Systems. ENCYCLOPEDIA OF SYSTEMS AND CONTROL 2021. [DOI: 10.1007/978-3-030-44184-5_100105] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/08/2023]
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Berglund EZ, Pesantez JE, Rasekh A, Shafiee ME, Sela L, Haxton T. Review of Modeling Methodologies for Managing Water Distribution Security. JOURNAL OF WATER RESOURCES PLANNING AND MANAGEMENT 2020; 146:1-23. [PMID: 33627936 PMCID: PMC7898161 DOI: 10.1061/(asce)wr.1943-5452.0001265] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/25/2023]
Abstract
Water distribution systems are vulnerable to hazards that threaten water delivery, water quality, and physical and cybernetic infrastructure. Water utilities and managers are responsible for assessing and preparing for these hazards, and researchers have developed a range of computational frameworks to explore and identify strategies for what-if scenarios. This manuscript conducts a review of the literature to report on the state of the art in modeling methodologies that have been developed to support the security of water distribution systems. First, the major activities outlined in the emergency management framework are reviewed; the activities include risk assessment, mitigation, emergency preparedness, response, and recovery. Simulation approaches and prototype software tools are reviewed that have been developed by government agencies and researchers for assessing and mitigating four threat modes, including contamination events, physical destruction, interconnected infrastructure cascading failures, and cybernetic attacks. Modeling tools are mapped to emergency management activities, and an analysis of the research is conducted to group studies based on methodologies that are used and developed to support emergency management activities. Recommendations are made for research needs that will contribute to the enhancement of the security of water distribution systems.
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Affiliation(s)
- Emily Zechman Berglund
- Dept. of Civil, Construction, and Environmental Engineering, North Carolina State Univ., C.B. 7908, Raleigh, NC 27695
| | - Jorge E Pesantez
- Dept. of Civil, Construction, and Environmental Engineering, North Carolina State Univ., C.B. 7908, Raleigh, NC 27695
| | - Amin Rasekh
- Xylem Inc., 8601 Six Forks Rd., Raleigh, NC 27615
| | | | - Lina Sela
- Dept. of Civil, Architectural, and Environmental Engineering, Univ. of Texas at Austin, 301 E Dean Keeton St. Stop C1786, Austin, TX 78712
| | - Terranna Haxton
- Office of Research and Development, US Environmental Protection Agency, 26 W. Martin Luther King Dr., Cincinnati, OH 45268
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Garcia D, Puig V, Quevedo J. Prognosis of Water Quality Sensors Using Advanced Data Analytics: Application to the Barcelona Drinking Water Network. SENSORS 2020; 20:s20051342. [PMID: 32121444 PMCID: PMC7085711 DOI: 10.3390/s20051342] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/28/2019] [Revised: 02/16/2020] [Accepted: 02/25/2020] [Indexed: 11/16/2022]
Abstract
Water Utilities (WU) are responsible for supplying water for residential, commercial and industrial use guaranteeing the sanitary and quality standards established by different regulations. To assure the satisfaction of such standards a set of quality sensors that monitor continuously the Water Distribution System (WDS) are used. Unfortunately, those sensors require continuous maintenance in order to guarantee their right and reliable operation. In order to program the maintenance of those sensors taking into account the health state of the sensor, a prognosis system should be deployed. Moreover, before proceeding with the prognosis of the sensors, the data provided with those sensors should be validated using data from other sensors and models. This paper provides an advanced data analytics framework that will allow us to diagnose water quality sensor faults and to detect water quality events. Moreover, a data-driven prognosis module will be able to assess the sensitivity degradation of the chlorine sensors estimating the remaining useful life (RUL), taking into account uncertainty quantification, that allows us to program the maintenance actions based on the state of health of sensors instead on a regular basis. The fault and event detection module is based on a methodology that combines time and spatial models obtained from historical data that are integrated with a discrete-event system and are able to distinguish between a quality event or a sensor fault. The prognosis module analyses the quality sensor time series forecasting the degradation and therefore providing a predictive maintenance plan avoiding unsafe situations in the WDS.
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Affiliation(s)
- Diego Garcia
- Supervision, Safety and Automatic Control Research Center (CS2AC), Universitat Politécnica de Catalunya (UPC), Terrassa Campus, Gaia Research Bldg., Rambla Sant Nebridi, 22, Terrassa, 08222 Barcelona, Spain; (D.G.); (J.Q.)
- Aigues de Barcelona, Empresa Metropolitana de Gestió del Cicle Integral de l’Aigua S.A., 08028 Barcelona, Spain
| | - Vicenç Puig
- Supervision, Safety and Automatic Control Research Center (CS2AC), Universitat Politécnica de Catalunya (UPC), Terrassa Campus, Gaia Research Bldg., Rambla Sant Nebridi, 22, Terrassa, 08222 Barcelona, Spain; (D.G.); (J.Q.)
- Institut de Robòtica i Informàtica Industrial (CSIC-UPC), Carrer Llorens i Artigas 4-6, 08028 Barcelona, Spain
- Correspondence:
| | - Joseba Quevedo
- Supervision, Safety and Automatic Control Research Center (CS2AC), Universitat Politécnica de Catalunya (UPC), Terrassa Campus, Gaia Research Bldg., Rambla Sant Nebridi, 22, Terrassa, 08222 Barcelona, Spain; (D.G.); (J.Q.)
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Hu C, Dai L, Yan X, Gong W, Liu X, Wang L. Modified NSGA-III for sensor placement in water distribution system. Inf Sci (N Y) 2020. [DOI: 10.1016/j.ins.2018.06.055] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/28/2022]
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Sela L, Abbas W. Distributed Sensing for Monitoring Water Distribution Systems. ENCYCLOPEDIA OF SYSTEMS AND CONTROL 2020. [DOI: 10.1007/978-1-4471-5102-9_100105-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/08/2023]
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Optimal Selection and Monitoring of Nodes Aimed at Supporting Leakages Identification in WDS. WATER 2019. [DOI: 10.3390/w11030629] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Many efforts have been made in recent decades to formulate strategies for improving the efficiency of water distribution systems (WDS), led by the socio-demographic evolution of modern society and the climate change scenario. The improvement of WDS management is a complex task that can be addressed by providing services to maximize revenues while ensuring that the quality standards required by national and international regulations are upheld. These two objectives can be fulfilled by utilizing optimized techniques for the operational and maintenance strategies of WDS. This paper proposes a methodology for assisting engineers in identifying water leakages in WDS, thus providing an effective procedure for ensuring high level hydraulic network functionality. The proposed approach is based on an inverse analysis of measured flow rates and pressure data, and consists of three steps: The analysis of measurements to select the most suitable period for leakage identification, the localization of the best measurement points based on a correlation analysis, and leakage identification with a hybrid optimization that combines the exploration capability of the differential evolution algorithm with the rapid convergence of particle swarm optimization. The proposed procedure is validated on a reference hydraulic network, known as the Apulian network.
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Winter CD, Palleti VR, Worm D, Kooij R. Optimal placement of imperfect water quality sensors in water distribution networks. Comput Chem Eng 2019. [DOI: 10.1016/j.compchemeng.2018.10.021] [Citation(s) in RCA: 26] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/28/2022]
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Khorshidi MS, Nikoo MR, Sadegh M. Optimal and objective placement of sensors in water distribution systems using information theory. WATER RESEARCH 2018; 143:218-228. [PMID: 29960176 DOI: 10.1016/j.watres.2018.06.050] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/13/2018] [Revised: 05/11/2018] [Accepted: 06/20/2018] [Indexed: 06/08/2023]
Abstract
Optimization-based deployment of contamination warning system in water distribution systems has been widely used in the literature, due to their superior performance compared to rule- and opinion-based approaches. However, optimization techniques impose an excessive computational burden, which in turn is compensated for by shrinking the problem's decision space and/or using faster optimization algorithms with less accuracy. This imposes subjectivity in interpretation of the system and associated risks, and undermines model's accuracy by not exploring the entire feasible space. We propose a framework that uses information theoretic techniques, including value of information and transinformation entropy, for optimal sensor placement. This can be used either as pre-selection, i.e. pinpointing best potential locations of sensors to be in turn used in optimization framework, or ultimate selection, i.e. single-handedly selecting sensor locations from the feasible space. The proposed framework is then applied to Lamerd water distribution system, in Fars province, Iran, and the results are compared to the suggested potential locations of sensors in previous studies and results of TEVA-SPOT model. The proposed information theoretic scheme enhances the decision space, provides more accurate results, significantly reduces the computational burden, and warrants objective selection of sensor placement.
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Affiliation(s)
- Mohammad S Khorshidi
- School of Engineering, Department of Environmental Engineering, Shiraz University, Shiraz, Iran.
| | - Mohammad Reza Nikoo
- School of Engineering, Department of Environmental Engineering, Shiraz University, Shiraz, Iran.
| | - Mojtaba Sadegh
- Department of Civil Engineering, Boise State University, Boise, USA.
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Zulkifli SN, Rahim HA, Lau WJ. Detection of contaminants in water supply: A review on state-of-the-art monitoring technologies and their applications. SENSORS AND ACTUATORS. B, CHEMICAL 2018; 255:2657-2689. [PMID: 32288249 PMCID: PMC7126548 DOI: 10.1016/j.snb.2017.09.078] [Citation(s) in RCA: 71] [Impact Index Per Article: 11.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/14/2016] [Revised: 08/22/2017] [Accepted: 09/13/2017] [Indexed: 05/12/2023]
Abstract
Water monitoring technologies are widely used for contaminants detection in wide variety of water ecology applications such as water treatment plant and water distribution system. A tremendous amount of research has been conducted over the past decades to develop robust and efficient techniques of contaminants detection with minimum operating cost and energy. Recent developments in spectroscopic techniques and biosensor approach have improved the detection sensitivities, quantitatively and qualitatively. The availability of in-situ measurements and multiple detection analyses has expanded the water monitoring applications in various advanced techniques including successful establishment in hand-held sensing devices which improves portability in real-time basis for the detection of contaminant, such as microorganisms, pesticides, heavy metal ions, inorganic and organic components. This paper intends to review the developments in water quality monitoring technologies for the detection of biological and chemical contaminants in accordance with instrumental limitations. Particularly, this review focuses on the most recently developed techniques for water contaminant detection applications. Several recommendations and prospective views on the developments in water quality assessments will also be included.
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Affiliation(s)
| | - Herlina Abdul Rahim
- Faculty of Electrical Engineering, Universiti Teknologi Malaysia, 81310 Skudai, Johor, Malaysia
| | - Woei-Jye Lau
- Advanced Membrane Technology Research Centre (AMTEC), Faculty of Chemical and Energy Engineering, Universiti Teknologi Malaysia, 81310 Skudai, Johor, Malaysia
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Banik B, Alfonso L, Torres A, Mynett A, Di Cristo C, Leopardi A. Optimal Placement of Water Quality Monitoring Stations in Sewer Systems: An Information Theory Approach. ACTA ACUST UNITED AC 2015. [DOI: 10.1016/j.proeng.2015.08.956] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
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