Prioritizing Sanitary Sewers for Rehabilitation Using Least-Cost Classifiers
Publication: Journal of Infrastructure Systems
Volume 12, Issue 3
Abstract
Sewer rehabilitation is one control option for relieving wet-weather sanitary sewer overflows by reducing rainfall dependent inflow and infiltration. The prioritization of rehabilitation activities is based on the physical condition of a collection system, which is usually only partially known. Linear regression methods have been used to estimate the condition of the unobserved set of pipes based on relationships derived from the observed set of pipes. This method can provide unsatisfactory relationships between the sewer condition and measured independent variables, resulting in highly uncertain rehabilitation cost estimates. Discriminant analysis has been effective at weighing the costs of misclassifying pipes and deriving least-cost classification rules. Classification rules may be derived within a data-mining framework using evolutionary algorithms or with logistic regression methods. The estimated spatial distribution of deficient pipes may then be refined on an aggregated scale with a bootstrap estimate of classification error. The result is a screening and prioritization tool for providing cost estimates for rehabilitation and replacement activities. This method is demonstrated with an 8,919 pipe sanitary sewer system in Vallejo, Calif.
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Acknowledgments
The writers would like to thank Mr. Ron Matheson, General Manager, and Dr. Rolf Ohlemutz, Director of Engineering and Field Operations for the Vallejo Sanitation and Flood Control District, and Carollo Engineers, for their support, encouragement, and valuable guidance. In addition, the valuable contributions made by the anonymous reviewers are gratefully acknowledged, especially with regard to the concepts regarding the least-cost probability threshold when using the logistic discrimination method.
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Published In
Journal of Infrastructure Systems
Volume 12 • Issue 3 • September 2006
Pages: 174 - 183
Copyright
© 2006 ASCE.
History
Received: Feb 5, 2002
Accepted: Jun 15, 2005
Published online: Sep 1, 2006
Published in print: Sep 2006
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