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A review of water quality factors in water main failure prediction models
Author(s) -
Z. Monfared,
Mohamad Molavi Nojumi,
Alireza Bayat
Publication year - 2021
Publication title -
water practice and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.243
H-Index - 15
ISSN - 1751-231X
DOI - 10.2166/wpt.2021.094
Subject(s) - water quality , quality (philosophy) , predictive modelling , identification (biology) , process (computing) , set (abstract data type) , environmental science , computer science , machine learning , ecology , philosophy , botany , epistemology , biology , programming language , operating system
Water main failure can result from structural failure of the pipes, changes in water quality, or a combination. This paper is a review of articles evaluating water quality factors and subfactors in the development of water main failure prediction models since 2000. A systematic process was implemented to capture the most relevant current published papers. Of 4598 published papers, 304 were screened for water main failure prediction models. The resulting set was further screened for water quality factors and subfactors (e.g., pH, temperature, etc.). This led to the identification of 18 relevant research papers, and each of these was reviewed comprehensively. The water quality-related findings, as well as combinations with other information – such as type of prediction model and type of prediction – are summarized and discussed.

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