Evaluating risk of water mains failure using a Bayesian belief network model

It has been reported that since year 2000, there have been an average 700 water main breaks per day only in Canada and the USA costing more than CAD 10 billions/year. Moreover, water main leaks affect other neighboring infrastructure that may lead to catastrophic failures. For this, municipality authorities or stakeholders are more concerned about preventive actions rather reacting to failure events. This paper presents a Bayesian Belief Network (BBN) model to evaluate the risk of failure of metallic water mains using structural integrity, hydraulic capacity, water quality, and consequence factors. BBN is a probabilistic graphical model that represents a set of variables and their probabilistic relationships, which also captures historical information about these dependencies. The proposed model is capable of ranking water mains within distribution network that can identify vulnerable and sensitive pipes to justify proper decision action for maintenance/rehabilitation/replacement (M/R/R). To demonstrate the application of proposed model, water distribution network of City of Kelowna has been studied. Result indicates that almost 9% of the total 259 metallic pipes are at high risk in both summer and winter.