Risk Assessment of Factors Influencing Non-Revenue Water Using Bayesian Networks and Fuzzy Logic

Tabesh, Massoud; Roozbahani, Abbas; Roghani, Bardia; Faghihi, Niousha Rasi; Heydarzadeh, Reza

doi:10.1007/s11269-018-2011-8

Cited by 41 publications

(14 citation statements)

References 46 publications

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“…In a cross-national study conducted over 63 countries, the authors concluded that the key drivers of water losses are linked to the physical characteristics of the water system and environmental factors such as urbanization and land settlement patterns [27]. Furthermore, high NRW rates may be caused by poor management, inadequate training of workers and experts, lack of timely replacement of devices, and inappropriate selection of pipes [28]. Research also shows that NRW is influenced by leakages due to aged and corroded underground assets [18].…”

Section: Non-revenue Water (Nrw)mentioning

confidence: 99%

“…This demonstrates the piping system due to incompatibility of the piping material used in the water distribution system. Tabesh et al emphasized that the "inappropriate quality selection of pipes and devices" can result in high NRW rates [28]. Therefore, it is crucial that the piping materials should be assessed before using it in the water distribution system.…”

Section: Types Of Water Pipesmentioning

confidence: 99%

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Non-Revenue Water in Malaysia: Influence of Water Distribution Pipe Types

et al. 2021

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Reducing non-revenue water (NRW) within a water distribution network may lead to significant water savings. Most existing literature tend to focus on the design and implementation aspects of NRW loss through better management of leaks, reservoir overflow, and water theft. In contrast, this paper examines the association between the various water pipe types and their respective impact on NRW loss in an emerging country. Malaysia is currently listed under emerging and developing economies category in the International Monetary Fund World Economic Outlook Database (October 2020). A correlation analysis is carried out using historical data obtained from the Malaysian water authority, covering fiscal years 2013 to 2017 (inclusive of both years). Further analysis is carried out by measuring the number of cases reported for two selected states in relation to the type of pipe materials used. Results show that there is a significant correlation between mild steel and polyethylene pipes to NRW loss. This study provides a better understanding of how water pipe types affect NRW loss, which is pertinent to developing best practices in the marketplace to manage NRW loss and protect water resources.

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Section: Non-revenue Water (Nrw)mentioning

confidence: 99%

Section: Types Of Water Pipesmentioning

confidence: 99%

Non-Revenue Water in Malaysia: Influence of Water Distribution Pipe Types

et al. 2021

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“…Es decir, el acueducto probablemente experimentó dificultades técnicas y comerciales en la reducción de pérdidas debido a la magnitud de su IANCP; lo cual pudo ser una señal de la eficiencia con la que se prestó el servicio, así como de los costos que debieron asumir los usuarios del sistema. Tabesh et al (2018) reportaron que las pérdidas económicas por agua no contabilizada fueron trasladadas di-rectamente a los usuarios facturados, elevando así los costos de suministro del agua. En relación con el índice de pérdidas por usuario facturado (IPUF), los resultados mostraron en promedio que, para el sistema de abastecimiento en estudio, este fue de 6,16 m³/suscriptor*mes.…”

Section: Análisis Estadísticounclassified

“…Las pérdidas de agua en sistemas de abastecimiento posiblemente tuvieron un impacto ambiental negativo por la sobreexplotación del recurso hídrico y, en lo financiero, conllevaron probablemente al incremento de tarifas por prestación del servicio debido a las elevadas inversiones económicas para cubrir estos costos operacionales y administrativos (Tabesh et al, 2018). Las investigaciones a nivel mundial indicaron que, de seguir las prácticas actuales de consumo de agua, enfrentaremos una escasez mundial del 40 %, entre la demanda prevista y el suministro disponible para el año 2030 (Agatón et al, 2016;Salimi et al, 2018).…”

Section: Introductionunclassified

Análisis de agua no contabilizada en el sistema de abastecimiento urbano del municipio de Facatativá, Colombia

Bueno-Herrera¹,

Monroy-Ávila²,

Zafra-Mejía³

2020

Tecnura

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Contexto: Las pérdidas de agua son un obstáculo financiero para empresas prestadoras del servicio de abastecimiento ya que generan pérdidas económicas que son trasladadas a los usuarios, elevando de esta manera los costos de suministro del agua. El objetivo de este artículo es presentar un análisis del agua no contabilizada en un sistema de abastecimiento urbano en Colombia. Método: Este estudio se realizó a partir de información del agua producida (AP) y facturada por el sistema de abastecimiento durante cerca de 16 años. Se realizó un análisis comparativo con respecto a reportes de agua no contabilizada en sistemas colombianos e internacionales de referencia. Se evaluó también la influencia del régimen de precipitación sobre el índice de agua no contabilizada (IANC). Se realizó finalmente un análisis económico prospectivo mediante modelos ARIMA. Resultados: Se observa un incremento del 5,0% en el IANC por cada 100 000 m3 de AP. Existe un incremento del 2,28% en el IANC por cada incremento de 100 mm en la precipitación anual. El sistema posee un menor precio en el AP (22,2%) con respecto a sistemas latinoamericanos de referencia. Sin embargo, el sistema posee un mayor precio (33,3%) en relación con el promedio colombiano. El análisis ARIMA muestra que los efectos del AP en un instante de tiempo determinado se transfieren durante seis meses en el sistema de abastecimiento. Conclusiones: La aplicación del IANC en sistemas de abastecimiento es una herramienta útil para el estudio y desarrollo de programas de control de pérdidas de agua.

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“…Tasarruf edilen toplam debi miktarı 148,9 lt/sn'dir. Bu çalışmalarla birlikte literatürde ayrıca, GGS miktarını azaltmak için idari ve fiziki kayıplar üzerine yapılmış ulusal ve uluslararası pek çok araştırma da bulunmaktadır [7][8][9][10][11][12][13][14].…”

Section: Introductionunclassified

Gelir Getirmeyen Su Oranı Tahmin Modelleri

Kizilöz¹,

Şişman²

2020

Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi

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Bu araştırmada Gelir Getirmeyen Su Oranı (GGSO) tahminleri, Kocaeli'nin en fazla su kaybı yaşanan altı ilçesinin 2018 ve2019 yıllarına ait iki yıllık verisi dikkate alınarak ve tüketilen su miktarı, şebeke uzunluğu, servis bağlantı uzunluğu, toplam şebeke uzunluğu, şebeke yaşı ve şebeke basıncı ana parametreleri kullanılarak gerçekleştirilmiştir. Model tahminleri iki girdi ve tek çıktılı Yapay Sinir Ağı (YSA) modelleri ve Kriging yöntemi ile gerçekleştirilmiştir. Modellerde toplam şebeke uzunluğu ve iki girdili YSA model kombinasyonlarında ise, servis bağlantı uzunluğu ilk kez bu araştırmada model girdisi olarak kullanılmıştır. Yöntemlerin model çıktı performansları R 2 ve HKOK performans ölçütleri üzerinden değerlendirilmiştir. Sonuç olarak; Kriging yöntemi ile gerçekleştirilen modellerin tahmin performansları YSA yöntemine göre oldukça iyidir. Kriging tekniği ile oluşturulan GGSO tahmin model çıktılarının değerlendirilmesi ve yorumlanması elde edilen tahmin haritaları sayesinde daha kolay yapılabilirken, kapalı model yapısına sahip olan YSA model sonuçlarında bu durum nitelikli uzmanlık gerektirmektedir.In this study, Non-Revenue Water Rate (NRWR) predictions have been made by taking into account two-year data (2018 and 2019) of Kocaeli and using the main parameters of consumed water amount, network length, service connection length, total network length, network age and network pressure in only six districts with the highest water loss. Model predictions have been made by both Artificial Neural Network (ANN) models with two inputs one output and Kriging method. In this study, the total network length for all model combinations and the service connection length for ANN combinations with two inputs have been used as a model input for the first time. The model output performances of the above-mentioned methods have been evaluated in accordance with R 2 and HKOK criteria. In conclusion, it is obvious according to the results that the model prediction performances made by Kriging method are better than the other one (ANN method). On the other hand, while evaluating the NRWR prediction model outputs established by Kriging method is easier through the prediction charts, this requires a specialized skill set for evaluating the ANN results

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Risk Assessment of Factors Influencing Non-Revenue Water Using Bayesian Networks and Fuzzy Logic

Cited by 41 publications

References 46 publications

Non-Revenue Water in Malaysia: Influence of Water Distribution Pipe Types

Non-Revenue Water in Malaysia: Influence of Water Distribution Pipe Types

Análisis de agua no contabilizada en el sistema de abastecimiento urbano del municipio de Facatativá, Colombia

Gelir Getirmeyen Su Oranı Tahmin Modelleri

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