Decision with Uncertain Information: An Application for Leakage Detection in Water Pipelines

Infrastructure rehabilitation comprises remedial and prevention measures; however, preventing failure is not always possible, and direct investigations to find evidence of failure are challenging. Urban buried pipes are among the infrastructure that needs recurrent remedial actions. At this point, it is important to raise the question of what the appropriate strategy to locate or rehabilitate leakage is. This paper aims to implement and evaluate a Bayesian decision model for the maintenance planning of a water network. This includes the treatment of uncertainties in the evaluation of the best decision in a short-term perspective. To this end, a utility-based optimization routine based on the Bayesian theory has been used. The proposed model, due to its simplicity, can facilitate the initial problem-structuring in the process of decision-making under uncertainty. The model has been demonstrated on a water distribution network in Sweden, optimizing the decisions for locating and rehabilitating leakages. The results show that the cost of interventions and probabilities of leakages has a significant influence on the most appropriate decision.

Automated summary

This paper presents a Bayesian decision model for the maintenance planning of water networks, focusing on locating and rehabilitating leakages. The results show that the cost of interventions and probabilities of leakages have a significant influence on the decision-making process.