Infrastructure Condition Prediction Models for Sustainable Sewer Pipelines

Abstract

The Federation of Canadian Municipalities reported that approximately 55% of sewer infrastructure in Canada did not meet current standards. Therefore, the burden on Canadian municipalities to maintain and prioritize sewers is increasing. One of the major challenges is to develop a framework to standardize the condition assessment procedures for sewer pipelines. Lack of detailed knowledge on the condition of sewer networks escalates vulnerability to catastrophic failures. This research presents a proactive methodology of assessing the existing condition of sewers by considering various physical, environmental, and operational influence factors. Based on historic data collected from two municipalities in Canada, structural and operational condition assessment models for sewers are developed using the multiple regression technique. The developed regression models show 82 to 86% accuracy when they are applied to the validation data set. These models are utilized to generate deterioration curves for concrete, asbestos cement, and polyvinyl chloride sewers in relation to traffic loads, bedding materials, and other pipe characteristics. The developed models are expected to assist municipal engineers in identifying critical sewers, prioritizing sewer inspections, and rehabilitation requirements.