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Erschienen in: Sustainable Water Resources Management 2/2022

01.04.2022 | Original Article

Assessing the failures in water distribution networks using a combination of geographic information system, EPANET 2, and descriptive statistical analysis: a case study

verfasst von: Mohammad Gheibi, Nima Emrani, Mohammad Eftekhari, Kourosh Behzadian, Mohsen Mohtasham, Javad Abdollahi

Erschienen in: Sustainable Water Resources Management | Ausgabe 2/2022

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Abstract

Nowadays, issues related to water are considered one of the most significant and vital problems in human societies. One of the fundamental branches of the water crisis is the distribution network-related problems. The present study attempted to extract, classify and verify the failure data obtained from the Preventive Maintenance database of Birjand Water Distribution Network (WDN). The WDN was meshed in terms of the rate of failures using a combination of geographic information systems (GIS) and EPANET 2. Then it was assessed using the descriptive statistical analysis method. Investigations revealed that the middle sections of WDN involved the highest rate of failures. Furthermore, the investigations demonstrated that from 2011 to 2016 the highest rate of failures per kilometer per year ranged in range of 0.6–1.8 which involved the highest aggregation for all cells. In this regard, the highest intensity aggregation of occurrence rate in 2011 was estimated as 1.4–1.8, while in 2012, 2013, and 2016, it was estimated as 1–1.4 and finally in 2014 and 2015, estimations showed an interval of 0.6–1.

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Metadaten
Titel
Assessing the failures in water distribution networks using a combination of geographic information system, EPANET 2, and descriptive statistical analysis: a case study
verfasst von
Mohammad Gheibi
Nima Emrani
Mohammad Eftekhari
Kourosh Behzadian
Mohsen Mohtasham
Javad Abdollahi
Publikationsdatum
01.04.2022
Verlag
Springer International Publishing
Erschienen in
Sustainable Water Resources Management / Ausgabe 2/2022
Print ISSN: 2363-5037
Elektronische ISSN: 2363-5045
DOI
https://doi.org/10.1007/s40899-022-00638-9

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