Asset Renewal Forecasting for Water Main Replacement Program

Gardels, Derek; Casey, Nathan; Klopfer, Dan; Spencer, Dave; Duben, Mark

doi:10.1061/9780784481653.003

Cited by 1 publication

(3 citation statements)

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“…Temperature is also important in bacterial growth kinetics (Francisque et al 2009). Despite its known significance, the effects of water temperature were only assessed in four papers (Yaminighaeshi 2009;Nishiyama & Filion 2013a;Mounce et al 2014;Gardels et al 2018).…”

Section: Water Temperaturementioning

confidence: 99%

“…Some water utilities specify that water temperature must be considered in water main condition assessment (Gardels et al 2018), in line with industry experience and institutional knowledge. Many water main condition models include water temperature: for instance, Nishiyama & Filion (2013a) applied water temperature in a statistical model to predict water main failure rates, although no explanation for its inclusion was given.…”

Section: Water Temperaturementioning

confidence: 99%

“…One of the three papers related to prediction models developed specifically for CI pipes (Nishiyama & Filion 2013a). Gardels et al (2018) evaluated a prediction model including temperature for metal pipes, as well as PVC and concrete.…”

Section: Water Temperaturementioning

confidence: 99%

See 2 more Smart Citations

A review of water quality factors in water main failure prediction models

Monfared

Nojumi

Bayat

2021

Water Practice and Technology

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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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