Modeling Failure of Wastewater Collection Lines Using Various Section-Level Regression Models
Publication: Journal of Infrastructure Systems
Volume 18, Issue 2
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.
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Acknowledgments
This research was funded by a grant from the Metropolitan Sewer District of Greater Cincinnati (MSDGC). The authors would like to thank the deputy director, Mr. Biju George, and the staff at MSDGC for its guidance and assistance.
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Information & Authors
Information
Published In
Journal of Infrastructure Systems
Volume 18 • Issue 2 • June 2012
Pages: 146 - 154
Copyright
© 2012. American Society of Civil Engineers.
History
Received: Feb 7, 2011
Accepted: Aug 18, 2011
Published online: Aug 20, 2011
Published in print: Jun 1, 2012
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