Rule Based Simulation Models for Sewer Infrastructure

Predicting and evaluating the future condition of underground infrastructure systems has become a necessity for municipalities as they try to strategically plan for short-term and long-term budget allocation. Current practice is to first assess the condition of sewer lines and then translate these ratings into predictive models. Numerous predictive analytical modeling techniques have been utilized including the use of straight-line extrapolation, regression models, Markovian models, non-linear regression, artificial neural networks, and simulation. This paper presents the methodology of a model concluded very recently using rule based simulation to predict the condition rating of the local sewer network maintained by the City of Edmonton, Alberta.