[EN] The problem of predicting the failure of water mains has been considered from different perspectives and using several methodologies in engineering literature. Nowadays, it is important to be able to accurately calculate the failure probabilities of pipes over time, since water company profits and service quality for citizens depend on pipe survival; forecasting pipe failures could have important economic and social implications. Quantitative tools (such as managerial or statistical indicators and reliable databases) are required in order to assess the current and future state of networks. Companies managing these networks are trying to establish models for evaluating the risk Of failure in order to develop a proactive approach to the renewal process, instead of using traditional reactive pipe substitution schemes.
The main objective of this paper is to compare models for evaluating the risk of failure in water supply networks. Using real data from a water Supply company, this study has identified which network characteristics affect the risk of failure and which models better fit data to predict service breakdown.
The comparison using the receiver operating characteristics (ROC) graph leads us to the conclusion that the best model is a generalized linear model. Also, we propose a procedure that can be applied to a pipe failure database, allowing the most appropriate decision rule to be chosen. (C) 2009 Elsevier Ltd. All rights reserved.The authors are indebted to the anonymous referees whose suggestions improved the original manuscript. This study was partially supported by a grant from MEyC (Ministerio de Educacion y Ciencia, Spain, Project CGL2004-05507). The research of Ana Debon was partially supported by a grant from Generalitat Valenciana (Grant no. GVPRE/2008/103).Debón Aucejo, AM.; Carrión García, A.; Cabrera Marcet, E.; Solano, H. (2010). Comparing risk of failure models in water supply networks using ROC curves. Reliability Engineering & System Safety. 95(1):43-48. doi:10.1016/j.ress.2009.07.004S434895
