Proactive Risk-Based Integrity Assessment of Water Distribution Networks

Abstract

Sustainable management of urban water distribution networks should include not only new methods for monitoring, repairing or replacing aging infrastructure, but also (and more importantly) expanded methods for modelling deteriorating infrastructure, for pro-actively assessing the risk of failure and for devising replace or repair strategies. The study presented herein describes a framework for proactive risk-based integrity monitoring of urban water distribution networks and the results obtained from a case-study based on a 5-year data sample. A combination of artificial neural network and statistical modelling techniques stemming from parametric and nonparametric survival analysis (Kaplan-Meier survival curves with Epanechnikov's kernel) are utilized in the investigation of identified risk factors and for estimation of the forecasted time to failure metric. The data is stratified for different pipe groups for a more targeted analysis.