Development of prediction models for sewer deterioration

Due to their low visibility, rehabilitation of sanitary sewers is often neglected until catastrophic failures occur. Neglecting regular maintenance of these underground utilities adds to life-cycle costs and liabilities, and in extreme cases, stoppage or reduction of vital services. Incorporating condition data and deterioration patterns of the city's sewer system is pivotal for obtaining a realistic assessment of the city's infrastructure. This paper will explore the probability-based Markovian approach for modeling deterioration. This approach is based on the assumption that since the behavior of sewer lines (i.e., the rate of deterioration) is probabilistic, the selection of an appropriate repair strategy is also an uncertain procedure. Probability-based prediction models enable the comparison of the expected proportions in given condition states with the actual proportions observed in the field, and in this way possible defects in construction, materials, quality control, etc., can be identified. Expert opinions from engineers, who have developed the sewer assessment surveys for the City of Indianapolis Department of Capital Asset Management (DCAM), will be used to validate the deterioration models developed in the research. More realistic deterioration models will assist asset managers in improved performance modeling of the sewer infrastructure and also in determining this infrastructure's rehabilitation costs based on improved estimates of deterioration.