Modeling Failure of Wastewater Collection Lines Using Various Section-Level Regression Models

Baris Salman, Ossama Salem

Research output: Contribution to journalArticle

24 Citations (Scopus)

Abstract

Wastewater utilities are aiming to implement asset management strategies to minimize costly emergency repairs, to justify expenditures, and to optimize future renewal actions. Consequently, development of deterioration models that explain the behavior of wastewater lines and provide predictions regarding potential future condition levels is gaining importance. In this paper, deterioration models are generated to estimate the probability of failure values for sewer sections. A set of variables was obtained by examining the inventory and inspection databases of a sewer network. Three statistical methods (ordinal regression, multinomial logistic regression, and binary logistic regression) were employed in successive steps. Proportionality of odds assumption was tested for ordinal regression models, and suitability of this particular method was discussed. Estimated condition ratings were compared with observed data, and the binary logistic regression model was found to be more suitable for predicting probability of failure than the multinomial logistic regression model. The models presented in this paper are expected to assist wastewater utilities in developing section-level risk assessment models to identify pipe sections that require immediate attention and close monitoring.

Original languageEnglish (US)
Pages (from-to)146-154
Number of pages9
JournalJournal of Infrastructure Systems
Volume18
Issue number2
DOIs
StatePublished - May 31 2012

Fingerprint

Wastewater
Logistics
Sewers
Deterioration
Asset management
Risk assessment
Statistical methods
Repair
Inspection
Pipe
Monitoring

Keywords

  • Deterioration
  • Infrastructure
  • Probability
  • Regression models
  • Sewers
  • Wastewater management

ASJC Scopus subject areas

  • Civil and Structural Engineering

Cite this

Modeling Failure of Wastewater Collection Lines Using Various Section-Level Regression Models. / Salman, Baris; Salem, Ossama.

In: Journal of Infrastructure Systems, Vol. 18, No. 2, 31.05.2012, p. 146-154.

Research output: Contribution to journalArticle

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