An Empirical Model for the Prediction of Structural Behavior of Wastewater Collection Systems

Structural condition of wastewater pipelines is often reported in terms of internal condition grades of 1 through 5, with 1 being the best and 5 the worst condition. The existing models and methodologies for structural deterioration of wastewater pipelines based on ordinary regression or ordinal probit regression violate the model assumptions, and lead to invalid results. Furthermore, the existing ordinal probit models for structural deterioration of Civil infrastructure are overly complex in terms of number of parameters to be estimated. This also makes the interpretation of these models fairly challenging. Another existing modeling technique based on binary logistic regression dichotomizes the data into pass/fail categories, and thus ignores the rank order information available in data. This paper demonstrates the shortcomings of existing methodologies, and presents an ordinal regression model based on cumulative logits with partial proportional odds for modeling the structural degradation behavior of wastewater pipelines. The proposed model is more parsimonious as compared to the existing ordinal probit models as less number of parameters needs to be estimated. The model is also more flexible as it does not assume an overly strict assumption of normally distributed error terms. The model also affords simple interpretation in terms of odds and predicted probabilities. Application, parameters estimation, verification of assumptions, graphical interpretation, and model validation has been demonstrated with real data from the City of Niagara Falls' wastewater collection system. The paper concludes with a discussion of the salient features of the proposed model, and its implications for wastewater systems' performance prediction research.