WATER DISTRIBUTION NETWORKS AND DIGITAL TRANSFORMATION: IDENTIFICATION OF TRENDS AND GAPS WITH SUPPORT IN BIBLIOMETRIC ANALYSIS
Keywords:
Hydraulic modeling, Smart water, Information model, BIMAbstract
Due to the dynamic nature of water distribution systems, their operational management ideally should be supported by hydraulic modeling, which is recommended by ABNT NBR 12.218/2017 as a planning and operation instrument. Hydraulic models are tools capable of representing in simulations the behavior of the system, according to its physical, logical and topological configuration, making it possible to analyze its current conditions and make predictions. In order to achieve the purpose of operational management supported by modeling, instead of only using it as punctual applications for specific analysis, the quality of the asset register, real-time monitoring capabilities, data analysis, forecasting and anomaly detection models are increasingly relevant. Given NBR 12.218; Decree No. 9.9.83, of 2019, which sets as a goal the implementation of Building Information Modeling (BIM) for engineering works and services; and Decree No. 10.306 which determines BIM be applied to building’s operations and management as far year 2028, the objective of this research was to investigate the relationships between these tools in the context of the water sector’s digital transformation focusing on water distribution networks. Therefore, a literature bibliometric review was conducted based on three research axes, comprising 114 articles: 1) Hydraulic modeling and operational management; 2) Information models and distribution networks; 3) Smart water and related concepts. Among the main results, it was observed that until 2015, the research focus mostly lied on subjects related to hydraulic modeling and calibration methods. From 2016, topics related to more dynamic approaches, such as real-time monitoring, cyber security and smart water started gaining traction, with great interest in smart metering and the use of IoT technologies. There was a prevalence of studies focusing on technical solutions addressing benchmark systems, considering systems already calibrated and with well-known hydraulic parameters, and a gap was found in research relating to the practical needs of service providers, such as business cases evidencing the advantages and opportunities of return on investments in digital technologies.
References
ABOKIFA, A. A. et al. Real-Time Identification of Cyber-Physical Attacks on Water Distribution Systems via Machine Learning–Based Anomaly Detection Techniques. Journal of Water Resources Planning and Management, v. 145, n. 1, p. 04018089, jan. 2019.
ABU-MAHFOUZ, A. M. et al. Real-time dynamic hydraulic model of water distribution networks. Water (Switzerland), v. 11, n. 3, 1 mar. 2019.
ADDEEN, H. H. et al. A survey of cyber-physical attacks and detection methods in smart water distribution systems. IEEE Access, v. 9, p. 99905–99921, 2021.
ALANI, Y. et al. A semantic common model for product data in the water industry. Journal of Information Technology in Construction, v. 26, p. 566–590, 1 jul. 2021.
ALLEN, M. et al. Real-time in-network distribution system monitoring to improve operational efficiency. Journal AWWA, v. 103, n. 7, p. 63–75, 2011.
ALVISI, S. et al. Wireless middleware solutions for smart water metering. Sensors (Switzerland), v. 19, n. 8, 2 abr. 2019.
ANTZOULATOS, G. et al. Making urban water smart: The SMART-WATER solution. Water Science and Technology, v. 82, n. 12, p. 2691–2710, 15 dez. 2020.
ASSOCIAÇÃO BRASILEIRA DE NORMAS TÉCNICAS. ABNT NBR 12218: Projeto de rede de distribuição de água para abastecimento público — Procedimento. Rio de Janeiro: ABNT, 2017.
AUTIOSALO, J. et al. A Feature-Based Framework for Structuring Industrial Digital Twins. IEEE Access, v. 8, p. 1193–1208, 2020.
AZEVEDO, M. T. DE. Transformação digital na indústria: indústria 4.0 e a rede de água inteligente no Brasil. 2017. Tese (Doutorado em Ciências) - Sistemas Eletrônicos, Escola Politécnica da Universidade de São Paulo, São Paulo, 2017.
BEAL, C. D.; FLYNN, J. Toward the digital water age: Survey and case studies of Australian water utility smart-metering programs. Utilities Policy, v. 32, p. 29–37, 1 mar. 2015.
BERARDI, L.; GIUSTOLISI, O. Calibration of Design Models for Leakage Management of Water Distribution Networks. Water Resources Management, v. 35, n. 8, p. 2537–2551, 1 jun. 2021.
BONILLA, C. A. et al. A Digital Twin of a Water Distribution System by Using Graph Convolutional Networks for Pump Speed‐Based State Estimation. Water (Switzerland), v. 14, n. 4, 1 fev. 2022.
BORGE-DIEZ, D. et al. Pico turbines, the solution to self-supply energy to the water supply network. A case study in Las Palmas de Gran Canaria. Energy, v. 229, 15 ago. 2021.
BOULOS, P. F. et al. Real-time modeling of water distribution systems: A case studyJournal - American Water Works AssociationAmerican Water Works Association, , 1 set. 2014.
BOYLE, T. et al. Intelligent metering for urban water: A review. Water (Switzerland), v. 5, n. 3, p. 1052–1081, 2013.
BRADLEY, A., et al. BIM for infrastructure: An overall review and constructor perspective. Automation construction, v.71, p. 139-152, 2016.
BRASIL. Decreto n. 9.377, de 17 de maio de 2018. Institui a Estratégia de Disseminação do Building Information Modelling. Diário Oficial da União, Brasília, Edição 95, Seção 1, p. 3, mai. 2018. Atos do Poder Executivo. Disponível em: http://www.planalto.gov.br/ccivil_03/_ato2015-2018/2018/Decreto/D9377.htm. Acesso em: 5 out. 2018
BRASIL. Decreto n° 9.983 de 22 de agosto de 2019. Dispõe sobre a Estratégia Nacional de Disseminação do Building Information Modelling e institui o Comitê Gestor da Estratégia do Building Information Modelling. Diário Oficial da União: seção 1, Brasília, DF, p. 2, 23 agosto 2020.
BRASIL. Decreto n° 10.306 de 2 de abril de 2020. Estabelece a utilização do Building Information Modelling na execução direta ou indireta de obras e serviços de engenharia realizada pelos órgãos e pelas entidades da administração pública federal, no âmbito da Estratégia Nacional de Disseminação do Building Information Modelling – Estratégia BIM BR, instituída pelo Decreto nº 9.983, de 22 de agosto de 2019. Diário Oficial da União: seção 1, Brasília, DF, p. 5, 3 abril 2020.
BRENTAN, B. et al. Joint Operation of Pressure-Reducing Valves and Pumps for Improving the Efficiency of Water Distribution Systems. Journal of Water Resources Planning and Management, v. 144, n. 9, p. 04018055, set. 2018.
CAHN, A.; KATZ, D.; GHERMANDI, A. Analyzing Water Customer Preferences for Online Feedback Technologies in Israel: A Prototype Study. Journal of Water Resources Planning and Management, v. 146, n. 4, p. 06020002, abr. 2020.
Câmara Brasileira da Indústria da Construção (CBIC). 2016. Fundamentos BIM – Parte 1: Implementação do BIM para Construtoras e Incorporadoras. Vol. 1, 124 p. Brasília, 2016.
CARRIJO, I. B. et al. Operational optimization of WDS based on multiobjective genetic algorithms and operational extraction rules using data mining. Proceedings of the 2004 World Water and Environmetal Resources Congress: Critical Transitions in Water and Environmetal Resources Management, p. 4475–4482, 2004.
CASSIDY, J. et al. Taking water efficiency to the next level: Digital tools to reduce non-revenue water. Journal of Hydroinformatics, v. 23, n. 3, p. 453–465, 1 maio 2021.
CHECCUCCI, É. DE S. Teses e dissertações brasileiras sobre BIM: uma análise do período de 2013 a 2018. PARC Pesquisa em Arquitetura e Construção, v. 10, p. e019008–e019008, 26 fev. 2019.
CHEW, E. Value Co-Creation in the Organizations of the Future. ([], Ed.)European Conference on Management, Leadership & Governance. Anais...Kidmore End: Academic Conferences International Limited, 2013.
COELHO, F.J.M. Estudo de sistemas cadastrais de empresas de saneamento através de benchmarking. 2004. Dissertação (Mestrado em Ciências Geodésicas e Tecnologias da Informação) – Centro de Tecnologia e Geociências, Universidade Federal de Pernambuco, Recife, 2004.
COLE, G.; STEWART, R. A. Smart meter enabled disaggregation of urban peak water demand: Precursor to effective urban water planning. Urban Water Journal, v. 10, n. 3, p. 174–194, jun. 2013.
COLLIN, J. et al., (2015). IT Leadership in Transition - The Impact of Digitalization on Finnish Organizations. Research report, Aalto University. Department of Computer Science.
COMINOLA, A. et al. Implications of data sampling resolution on water use simulation, end-use disaggregation, and demand management. Environmental Modelling & Software, v. 102, p. 199–212, 1 abr. 2018.
COVELLI, C. et al. Optimal Location and Setting of PRVs in WDS for Leakage Minimization. Water Resources Management, v. 30, n. 5, p. 1803–1817, 1 mar. 2016.
CREACO, E.; PEZZINGA, G.; SAVIC, D. On the choice of the demand and hydraulic modeling approach to WDN real-time simulation. Water Resources Research, v. 53, n. 7, p. 6159–6177, 1 jul. 2017.
DAVIDSON, J. W.; BOUCHART, J.-C. Adjusting Nodal Demands in SCADA Constrained Real-Time Water Distribution Network Models. Journal of Hydraulic Engineering , v. 132, n. 1, p. 102–110, 2006.
DE CARVALHO, G. D. G. et al. Bibliometrics and systematic reviews: A comparison between the Proknow-C and the Methodi Ordinatio. Journal of Informetrics, v. 14, n. 3, 1 ago. 2020.
DE MARCHIS, M. et al. Energy Recovery in Water Distribution Networks. Implementation of Pumps as Turbine in a Dynamic Numerical Model. Procedia Engineering, v. 70, p. 439–448, 1 jan. 2014.
DI NARDO, A. et al. An Automated Tool for Smart Water Network Partitioning. Water Resources Management, v. 27, n. 13, p. 4493–4508, out. 2013.
DIAO, K. et al. Global resilience analysis of water distribution systems. Water Research, v. 106, p. 383–393, 1 dez. 2016.
DO, N. C. et al. Calibration of Water Demand Multipliers in Water Distribution Systems Using Genetic Algorithms. Journal of Water Resources Planning and Management, v. 142, n. 11, p. 04016044, nov. 2016.
EDIRISINGHE, R. et al. Building information modelling for facility management: Are we there yet? Engineering, Construction and Architectural Management, v. 24, n. 6, p. 1119–1154, 2017.
ENSSLIN, L. et al. Research Process for Selecting a Theoretical Framework and Bibliometric Analysis of a Theme: Illustration for the Management of Customer Service in a Bank. Modern Economy, v. 06, n. 06, p. 782–796, 2015.
FABBIANO, L.; VACCA, G.; DINARDO, G. Smart water grid: A smart methodology to detect leaks in water distribution networks. Measurement: Journal of the International Measurement Confederation, v. 151, 1 fev. 2020.
FANG, X. et al. Smart grid - The new and improved power grid: A survey. IEEE Communications Surveys and Tutorials, v. 14, n. 4, p. 944–980, 2012.
FARAH, E.; SHAHROUR, I. Leakage Detection Using Smart Water System: Combination of Water Balance and Automated Minimum Night Flow. Water Resources Management, v. 31, n. 15, p. 4821–4833, 1 dez. 2017.
FARAH, E.; SHAHROUR, I. Smart water technology for leakage detection: feedback of large-scale experimentation. Analog Integrated Circuits and Signal Processing, v. 96, n. 2, p. 235–242, 1 ago. 2018.
FARLEY, B.; MOUNCE, S. R.; BOXALL, J. B. Development and Field Validation of a Burst Localization Methodology. Journal of Water Resources Planning and Management, v. 139, n. 6, p. 604–613, nov. 2013.
FERREIRA, B. Desenvolvimento de metodologias BIM de apoio aos trabalhos construtivos de medição e orçamentação. 2015. Dissertação (Mestrado Integrado em Engenharia Civil) - Faculdade de Engenharia da Universidade do Porto, Porto, 2015.
FUERTES, C. P. et al. Building and exploiting a Digital Twin for the management of drinking water distribution networks. Urban Water Journal, v. 17, n. 8, p. 704–713, 13 set. 2020.
GERMANOPOULOS, G. A technical note on the inclusion of pressure dependent demand and leakage terms in water supply network models. http://dx.doi.org/10.1080/02630258508970401, v. 2, n. 3, p. 171–179, 2007.
GILBERT, T. et al. Topological integration of BIM and geospatial water utility networks across the building envelope. Computers, Environment and Urban Systems, v. 86, 1 mar. 2021.
GIUSTOLISI, O. et al. Operational and Tactical Management of Water and Energy Resources in Pressurized Systems: Competition at WDSA 2014. Journal of Water Resources Planning and Management, v. 142, n. 5, maio 2016.
GIUSTOLISI, O.; KAPELAN, Z.; SAVIC, D. Extended Period Simulation Analysis Considering Valve Shutdowns. Journal of Water Resources Planning and Management, v. 134, n. 6, p. 527–537, 2008.
GONG, J. et al. Detection of Emerging through-Wall Cracks for Pipe Break Early Warning in Water Distribution Systems Using Permanent Acoustic Monitoring and Acoustic Wave Analysis. Water Resources Management, v. 34, n. 8, p. 2419–2432, 1 jun. 2020.
GRIEVES, M.; VICKERS, J. Digital twin: Mitigating unpredictable, undesirable emergent behavior in complex systems. Transdisciplinary Perspectives on Complex Systems: New Findings and Approaches, p. 85–113, 1 jan. 2016.
GURUNG, T. R. et al. Smart meters for enhanced water supply network modelling and infrastructure planning. Resources, Conservation and Recycling, v. 90, p. 34–50, 2014.
HALFAWY, M. R. Municipal information models and federated software architecture for implementing integrated infrastructure management environments. Automation in Construction, v. 19, n. 4, p. 433–446, jul. 2010.
HJELSETH, E. Exchange of Relevant Information in BIM Objects Defined by the Roleand life-Cycle Information Model. Architectural Engineering and Design Management, Vol. 6, Iss. 4, 2010.
HOWELL, S.; REZGUI, Y.; BEACH, T. Integrating building and urban semantics to empower smart water solutions. Automation in Construction, v. 81, p. 434–448, 1 set. 2017.
HOWELL, S.; REZGUI, Y.; BEACH, T. Water utility decision support through the semantic web of things. Environmental Modelling and Software, v. 102, p. 94–114, 1 abr. 2018.
HUTTON, C. J. et al. Dealing with Uncertainty in Water Distribution System Models: A Framework for Real-Time Modeling and Data Assimilation. Journal of Water Resources Planning and Management, v. 140, n. 2, p. 169–183, 2014.
INTERNATIONAL ORGANIZATION FOR STANDARDIZATION. ISO 16.739-1: Industry Foundation Classes (IFC) for data sharing in the construction and facility management industries – Part 1: Data schema. 2018
JAMIESON, D. G. et al. Conceptual design of a generic, real-time, near-optimal control system for water-distribution networks. Journal of Hydroinformatics, v. 9, n. 1, p. 3–14, 2007.
KAMUNDA, A. et al. BIM in the water industry: addressing challenges to improve the project delivery process. Engineering, Construction and Architectural Management, v. 28, n. 2, p. 510–529, 15 fev. 2021.
KANAKOUDIS, V.; GONELAS, K. Non-revenue water reduction through pressure management in Kozani’s water distribution network: from theory to practice. Desalination and Water Treatment, v. 57, n. 25, p. 11436–11446, 6 jan. 2016.
KARA, S. et al. Real time monitoring and control in water distribution systems for improving operational efficiency. Desalination and Water Treatment, v. 57, n. 25, p. 11506–11519, 2016.
KARADIREK, I. E. et al. Implementation of Hydraulic Modelling for Water-Loss Reduction Through Pressure Management. Water Resources Management, v. 26, n. 9, p. 2555–2568, jul. 2012.
KOO, K. M. et al. Smart water grid research group project: An introduction to the smart water grid living-lab demonstrative operation in yeongjong island, korea. Sustainability (Switzerland), v. 13, n. 9, 1 maio 2021.
KOWALSKI, D.; KOWALSKA, B.; SUCHORAB, P. Smart water supply system: a quasi intelligent diagnostic method for a distribution network. Applied Water Science, v. 12, n. 135, 2022.
KULKARNI, P.; FARNHAM, T. Smart City Wireless Connectivity Considerations and Cost Analysis: Lessons Learnt from Smart Water Case Studies. IEEE Access, v. 4, p. 660–672, 2016.
LAMBERT, A. O.; MCKENZIE, D. R. D. Practical Experience in using the Infrastructure Leakage Index. (W. B. of Lemesos, Ed.)IWA Conf. on Leakage Management: A practical approach. Anais...Lemesos, Cyprus: IWA Publishing, 2002.
LEE, S. W. et al. Smart water grid: the future water management platform. Desalination and Water Treatment, v. 55, n. 2, p. 339–346, 10 jul. 2015.
LI, J.; YANG, X.; SITZENFREI, R. Rethinking the framework of smart water system: A review. Water (Switzerland), v. 12, n. 2, 1 fev. 2020.
LIU, A. et al. Detailed water-use feedback: A review and proposed framework for program implementation. Utilities Policy, v. 43, p. 140–150, 1 dez. 2016.
LOUCKS, D. WATER RESOURCE SYSTEMS MODELS: THEIR ROLE IN PLANNING 3. Journal of Water Resources Planning and Management, v. 118, n. 3, p. 214–223, 1992.
MA, Z.; REN, Y. Integrated Application of BIM and GIS: An Overview. Procedia Engineering, v. 196, p. 1072–1079, 1 jan. 2017.
MARCH, H. et al. Household smart water metering in Spain: Insights from the experience of remote meter reading in alicante. Sustainability (Switzerland), v. 9, n. 4, 11 abr. 2017.
MARSILIO, M.; CAPPELLARO, G.; CUCCURULLO, C. The intellectual structure of research into PPPS: A bibliometric analysis. Public Management Review, v. 13, n. 6, p. 763–782, 2011.
MARZOUK, M.; OTHMAN, A. Planning utility infrastructure requirements for smart cities using the integration between BIM and GIS. Sustainable Cities and Society, v. 57, p. 102120, 1 jun. 2020.
MESEGUER, J. et al. A decision support system for on-line leakage localization. Environmental Modelling and Software, v. 60, p. 331–345, 2014.
MOAZENI, F.; KHAZAEI, J. Formulating false data injection cyberattacks on pumps’ flow rate resulting in cascading failures in smart water systems. Sustainable Cities and Society, v. 75, 1 dez. 2021.
MOMENI, A. et al. Leveraging Hydraulic Cyber-Monitoring Data to Support Primitive Condition Assessment of Water Mains. 2021.
MOMENI, A.; PIRATLA, K. R. A Proof-of-Concept Study for Hydraulic Model-Based Leakage Detection in Water Pipelines Using Pressure Monitoring Data. Frontiers in Water, v. 3, 12 ago. 2021.
MONKS, I. et al. Revealing unreported benefits of digital water metering: Literature review and expert opinionsWater (Switzerland)MDPI AG, , 1 abr. 2019.
MONKS, I. et al. Expert opinion valuation method to quantify digital water metering benefits. Water (Switzerland), v. 12, n. 5, 1 maio 2020.
MOUNCE, S. R. et al. Knowledge management for more sustainable water systems. Electronic Journal of Information Technology in Construction, v. 15, n. February, p. 140–148, 2010.
MUHAMMETOGLU, A. et al. Full-Scale PAT Application for Energy Production and Pressure Reduction in a Water Distribution Network. Journal of Water Resources Planning and Management, v. 143, n. 8, p. 04017040, ago. 2017.
MÜLLER-CZYGAN, G. et al. How does digitization succeed in the municipal water sector? The waterexe4.0 meta-study identifies barriers as well as success factors, and reveals expectations for the future. Energies, v. 14, n. 22, 1 nov. 2021.
ORMSBEE, L. E. Implicit Network Calibration. Journal of Water Resources Planning and Management, v. 115, n. 2, p. 243–257, 1989.
PADULANO, R.; DEL GIUDICE, G. A Mixed Strategy Based on Self-Organizing Map for Water Demand Pattern Profiling of Large-Size Smart Water Grid Data. Water Resources Management, v. 32, n. 11, p. 3671–3685, 1 set. 2018.
PAGE, P. R.; ABU-MAHFOUZ, A. M.; YOYO, S. Parameter-Less Remote Real-Time Control for the Adjustment of Pressure in Water Distribution Systems. Journal of Water Resources Planning and Management, v. 143, n. 9, p. 04017050, set. 2017.
PAGE, P. R.; CREACO, E. Comparison of flow-dependent controllers for remote real-time pressure control in awater distribution system with stochastic consumption. Water (Switzerland), v. 11, n. 3, 1 mar. 2019.
PALO, P.R. Avaliação da eficácia de modelos de simulação hidráulica na obtenção de informações para diagnóstico de perdas de água. 2010. Dissertação (Mestrado em Engenharia) – Escola Politécnica da Universidade de São Paulo, Universidade de São Paulo, São Paulo, 2010.
PATELIS, M.; KANAKOUDIS, V.; GONELAS, K. Combining pressure management and energy recovery benefits in a water distribution system installing PATs. Journal of Water Supply: Research and Technology - AQUA, v. 66, n. 7, p. 520–527, 1 nov. 2017.
PATELIS, M.; KANAKOUDIS, V.; KRAVVARI, A. Pressure regulation vs. water aging in water distribution networks. Water (Switzerland), v. 12, n. 5, 1 maio 2020.
PEDERSEN, A. N. et al. Living and prototyping digital twins for urban water systems: Towards multi-purpose value creation using models and sensors. Water (Switzerland), v. 13, n. 5, 1 mar. 2021.
PESANTEZ, J. E. et al. Using a digital twin to explore water infrastructure impacts during the COVID-19 pandemic. Sustainable Cities and Society, v. 77, 1 fev. 2022.
PREDESCU, A. et al. An advanced learning-based multiple model control supervisor for pumping stations in a smart water distribution system. Mathematics, v. 8, n. 6, 1 jun. 2020.
RAHIM, M. S. et al. Machine learning and data analytic techniques in digitalwater metering: A reviewWater (Switzerland)MDPI AG, , 1 jan. 2020.
RAHIM, M. S. et al. A clustering solution for analyzing residential water consumption patterns. Knowledge-Based Systems, v. 233, 5 dez. 2021.
RAMOS, H. M. et al. Smart water management towards future water sustainable networks. Water (Switzerland), v. 12, n. 1, 1 jan. 2020.
RAMOS, H. M. et al. New Challenges towards Smart Systems’ Efficiency by Digital Twin in Water Distribution Networks. Water, v. 14, n. 8, p. 1304, 17 abr. 2022.
RAMOS, H. M.; CARRAVETTA, A.; MC NABOLA, A. New challenges in water systemsWater (Switzerland)MDPI AG, , 1 set. 2020.
ROMANO, M.; KAPELAN, Z. Adaptive water demand forecasting for near real-time management of smart water distribution systems. Environmental Modelling and Software, v. 60, p. 265–276, 2014.
ROSSMAN, L. A. EPANET 2 Users Manual EPA/600/R-00/57Water Supply and Water Resources Division, U.S. Agency, Environmental Protection, 2000.
SAAB, C.; SHAHROUR, I.; HAGE CHEHADE, F. Risk Assessment of Water Accidental Contamination Using Smart Water Quality Monitoring. Exposure and Health, v. 12, n. 2, p. 281–293, 1 jun. 2020.
SALDARRIAGA, J. et al. Rehabilitation and Leakage Reduction on C-Town Using Hydraulic Criteria. Journal of Water Resources Planning and Management, v. 142, n. 5, p. 1–8, 2016.
SALOMONS, E.; SELA, L.; HOUSH, M. Hedging for Privacy in Smart Water Meters. Water Resources Research, v. 56, n. 9, 1 set. 2020.
SARNI, W. et al. Digital Water. Industry Leaders chart the transformation journeyDigital Water. International Water Association in partnership with Xylem inc. London, 2019.
SEBBAGH, K.; SAFRI, A.; ZABOT, M. Pre-Localization Approach of Leaks on a Water Distribution Network by Optimization of the Hydraulic Model Using an Evolutionary Algorithm. p. 588, 2018.
SHAFIEE, M. E. et al. Streaming Smart Meter Data Integration to Enable Dynamic Demand Assignment for Real-Time Hydraulic Simulation. Journal of Water Resources Planning and Management, v. 146, n. 6, p. 06020008, jun. 2020.
SHAHRA, E. Q.; WU, W. Water contaminants detection using sensor placement approach in smart water networks. Journal of Ambient Intelligence and Humanized Computing, 2020.
SHAMIR, U.; HOWARD, C. D. D. Engineering Analysis of Water-Distribution Systems. 1977.
SHAO, Y. et al. Real-Time Water Distribution System Hydraulic Modeling Using Prior Demand Information by Formal Bayesian Approach. Journal of Water Resources Planning and Management, v. 145, n. 12, p. 04019059, dez. 2019.
SINGH, J.; ANUMBA, C. J. Real-time pipe system installation schedule generation and optimization using artificial intelligence and heuristic techniques. Journal of Information Technology in Construction, v. 27, p. 173–190, 23 fev. 2022.
SIQUEIRA, J. P. G. Métodos de partição de rede de abastecimento de água : um estudo de caso em Pederneiras/SP. 2019. Dissertação (Mestrado em Ciências) - Engenharia Hidráulica e Saneamento, Universidade de São Paulo, São Carlos, 2019.
SLANÝ, V. et al. An integrated iot architecture for smart metering using next generation sensor for water management based on lorawan technology: A pilot study. Sensors (Switzerland), v. 20, n. 17, p. 1–23, 1 set. 2020.
SOPHOCLEOUS, S.; SAVIĆ, D.; KAPELAN, Z. Leak Localization in a Real Water Distribution Network Based on Search-Space Reduction. Journal of Water Resources Planning and Management, v. 145, n. 7, p. 04019024, jul. 2019.
STEPHENS, M. et al. Leak-Before-Break Main Failure Prevention for Water Distribution Pipes Using Acoustic Smart Water Technologies: Case Study in Adelaide. Journal of Water Resources Planning and Management, v. 146, n. 10, p. 05020020, out. 2020.
SUMER, D.; LANSEY, K. Effect of Uncertainty on Water Distribution System Model Design Decisions. Journal of Water Resources Planning and Management, v. 135, n. 1, p. 38–47, 2009.
TABESH, M.; DELAVAR, M. R.; DELKHAH, A. Use of geospatial information system based tool for renovation and rehabilitation of water distribution systems 1. Int. J. Environ. Sci. Tech, v. 7, n. 1, p. 47–58, 2010.
TADEU DE OLIVEIRA LACERDA, R.; ENSSLIN, L.; ENSSLIN, S. R. Uma análise bibliométrica da literatura sobre estratégia e avaliação de desempenho A bibliometric analysis of strategy and performance measurement. Gest. Prod., v. 19, n. 1, p. 59–78, 2012.
TAORMINA, R. et al. Characterizing Cyber-Physical Attacks on Water Distribution Systems. Journal of Water Resources Planning and Management, v. 143, n. 5, p. 04017009, maio 2017.
TAORMINA, R. et al. Battle of the Attack Detection Algorithms: Disclosing Cyber Attacks on Water Distribution Networks. Journal of Water Resources Planning and Management, v. 144, n. 8, p. 04018048, ago. 2018.
TAORMINA, R. et al. A toolbox for assessing the impacts of cyber-physical attacks on water distribution systems. Environmental Modelling and Software, v. 112, p. 46–51, 1 fev. 2019.
VAN ECK, N. J.; WALTMAN, L. VOSviewer Manual version 1.6.16. Univeristeit Leiden, n. November, p. 1–52, 2020.
WALSKI, T. M. Case Study: Pipe Network Model Calibration Issues. Journal of Water Resources Planning and Management, v. 112, n. 2, p. 238–249, 1 abr. 1986.
WEI, Z. et al. Optimal Sampling of Water Distribution Network Dynamics Using Graph Fourier Transform. IEEE Transactions on Network Science and Engineering, v. 7, n. 3, p. 1570–1582, 1 jul. 2020.
WRIGHT, L.; DAVIDSON, S. How to tell the difference between a model and a digital twin. Advanced Modeling and Simulation in Engineering Sciences, v. 7, n. 1, 2020.
WU, Z. Y.; SAGE, P.; TURTLE, D. Pressure-Dependent Leak Detection Model and Its Application to a District Water System. Journal of Water Resources Planning and Management, v. 136, n. 1, p. 116–128, 2010.
XIE, X.; ZHANG, H.; HOU, D. Bayesian Approach for Joint Estimation of Demand and Roughness in Water Distribution Systems. Journal of Water Resources Planning and Management, v. 143, n. 8, p. 04017034, ago. 2017.
ZHANG, C. et al. A convolutional neural network for pipe crack and leak detection in smart water network. Structural Health Monitoring, p. 147592172210801, 15 abr. 2022.
ZHANG, Q. et al. Leakage Zone Identification in Large-Scale Water Distribution Systems Using Multiclass Support Vector Machines. Journal of Water Resources Planning and Management, v. 142, n. 11, p. 04016042, nov. 2016.
ZHANG, Q. et al. Efficient Numerical Approach for Simultaneous Calibration of Pipe Roughness Coefficients and Nodal Demands for Water Distribution Systems. Journal of Water Resources Planning and Management, v. 144, n. 10, p. 04018063, out. 2018.
ZHANG, X.; LI, F.; LI, X. Bibliometric analysis of ecological compensation and its application in land resources Landscape and Ecological Engineering. Springer Japan, 1 out. 2021.
ZHAO, L.; LIU, Z.; MBACHU, J. An Integrated BIM–GIS Method for Planning of Water Distribution System. ISPRS International Journal of Geo-Information, v. 8, n. 8, p. 331, 27 jul. 2019.
ZHAO, X. A scientometric review of global BIM research: Analysis and visualization. Automation in Construction, v. 80, p. 37–47, 1 ago. 2017.
ZHOU, X. et al. Self-Adaptive Calibration of Real-Time Demand and Roughness of Water Distribution Systems. Water Resources Research, v. 54, n. 8, p. 5536–5550, 1 ago. 2018.
ZHOU, X. et al. Deep learning identifies accurate burst locations in water distribution networks. Water Research, v. 166, 1 dez. 2019.
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