Evaluating Parameters Influencing the Emergence and Increase of Non-Revenue Water Using Bayesian Networks (Case Study: District 4 of Tehran Water and Wastewater Company)

Effective strategies for optimal management of water distribution networks (WDNs) along with financial resources are clearly identifying design and performance parameters affecting the emergence of non-revenue water and reducing the impact of parameters. In this study, using references and experienc...

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Main Authors: Massoud Tabesh, Niousha Rasi Faghihi, Abbas Roozbahani, Bardia Roghani, Reza Heidarzadeh, Sattar Salehi
Format: Article
Language:fas
Published: Marvdasht Branch, Islamic Azad University 2020-04-01
Series:مهندسی منابع آب
Subjects:
Online Access:https://wej.marvdasht.iau.ir/article_4090_8e34989c3a754a168a033bdaf1cd25d9.pdf
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author Massoud Tabesh
Niousha Rasi Faghihi
Abbas Roozbahani
Bardia Roghani
Reza Heidarzadeh
Sattar Salehi
author_facet Massoud Tabesh
Niousha Rasi Faghihi
Abbas Roozbahani
Bardia Roghani
Reza Heidarzadeh
Sattar Salehi
author_sort Massoud Tabesh
collection DOAJ
description Effective strategies for optimal management of water distribution networks (WDNs) along with financial resources are clearly identifying design and performance parameters affecting the emergence of non-revenue water and reducing the impact of parameters. In this study, using references and experiences of experts in the field of WDN, the factors that are involved in the development of non-revenue water components were identified. Then, to collect the required information on the status of the parameters, officials’ and experts’ opinion were asked through questionnaires. Bayesian Networks (BNs) were used as a modeling tool so as to not only consider uncertainties associated to the lack of sufficient data and detailed information on non-revenue water components but also consider the probabilistic relationships between parameters. Finally, in order to analyze BN models results, a sensitivity index was proposed to prioritize parameters based on their impact. To investigate the usefulness of the proposed model, the area covered by District 4 of Tehran Water and Wastewater Company was selected as a case study. The results indicated that the probability that apparent losses, real losses and non-revenue water are high is 37.48 %, 35.04% and 32.2%, respectively.
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spelling doaj.art-046d222520214ad18f07523f3cae2edc2024-01-10T08:11:08ZfasMarvdasht Branch, Islamic Azad Universityمهندسی منابع آب2008-63772423-71912020-04-01134477964090Evaluating Parameters Influencing the Emergence and Increase of Non-Revenue Water Using Bayesian Networks (Case Study: District 4 of Tehran Water and Wastewater Company)Massoud Tabesh0Niousha Rasi Faghihi1Abbas Roozbahani2Bardia Roghani3Reza Heidarzadeh4Sattar Salehi5Professor and Member of Center of Excellence for Engineering and Management of Civil Infrastructures, School of Civil Engineering, College of Engineering, University of TehranSchool of Civil Engineering, College of Engineering, University of Tehran, Tehran, IranDepartment of Irrigation and Drainage Engineering, College of Abouraihan, University of Tehran, Tehran, IranSchool of Civil Engineering, College of Engineering, University of Tehran, Tehran, IranSchool of Civil Engineering, College of Engineering, University of Tehran, Tehran, IranAssistant Professor, Department of Civil Engineering, Islamic Azad University, Garmsar Branch, Garmsar, IranEffective strategies for optimal management of water distribution networks (WDNs) along with financial resources are clearly identifying design and performance parameters affecting the emergence of non-revenue water and reducing the impact of parameters. In this study, using references and experiences of experts in the field of WDN, the factors that are involved in the development of non-revenue water components were identified. Then, to collect the required information on the status of the parameters, officials’ and experts’ opinion were asked through questionnaires. Bayesian Networks (BNs) were used as a modeling tool so as to not only consider uncertainties associated to the lack of sufficient data and detailed information on non-revenue water components but also consider the probabilistic relationships between parameters. Finally, in order to analyze BN models results, a sensitivity index was proposed to prioritize parameters based on their impact. To investigate the usefulness of the proposed model, the area covered by District 4 of Tehran Water and Wastewater Company was selected as a case study. The results indicated that the probability that apparent losses, real losses and non-revenue water are high is 37.48 %, 35.04% and 32.2%, respectively.https://wej.marvdasht.iau.ir/article_4090_8e34989c3a754a168a033bdaf1cd25d9.pdfapparent lossesbayesian networknon-revenue waterquestionnairereal losses
spellingShingle Massoud Tabesh
Niousha Rasi Faghihi
Abbas Roozbahani
Bardia Roghani
Reza Heidarzadeh
Sattar Salehi
Evaluating Parameters Influencing the Emergence and Increase of Non-Revenue Water Using Bayesian Networks (Case Study: District 4 of Tehran Water and Wastewater Company)
مهندسی منابع آب
apparent losses
bayesian network
non-revenue water
questionnaire
real losses
title Evaluating Parameters Influencing the Emergence and Increase of Non-Revenue Water Using Bayesian Networks (Case Study: District 4 of Tehran Water and Wastewater Company)
title_full Evaluating Parameters Influencing the Emergence and Increase of Non-Revenue Water Using Bayesian Networks (Case Study: District 4 of Tehran Water and Wastewater Company)
title_fullStr Evaluating Parameters Influencing the Emergence and Increase of Non-Revenue Water Using Bayesian Networks (Case Study: District 4 of Tehran Water and Wastewater Company)
title_full_unstemmed Evaluating Parameters Influencing the Emergence and Increase of Non-Revenue Water Using Bayesian Networks (Case Study: District 4 of Tehran Water and Wastewater Company)
title_short Evaluating Parameters Influencing the Emergence and Increase of Non-Revenue Water Using Bayesian Networks (Case Study: District 4 of Tehran Water and Wastewater Company)
title_sort evaluating parameters influencing the emergence and increase of non revenue water using bayesian networks case study district 4 of tehran water and wastewater company
topic apparent losses
bayesian network
non-revenue water
questionnaire
real losses
url https://wej.marvdasht.iau.ir/article_4090_8e34989c3a754a168a033bdaf1cd25d9.pdf
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