Abstract
Water distribution networks are vital to delivering potable water. They commonly include interconnected water mains (WMs), pumps and other hydraulic controls. Numerous WM failures have occurred due to ageing and harsh climate. This paper aims to predict the probability of future failures and integrate the predictions into risk-management strategies. The novelty lies in emphasising on the relevance to networks in cold regions like Canada. This study applied clustering and principal component analysis to the WM data from the Canadian City of Kitchener network. Clustering is shown to improve the failure prediction outcomes from the random forest algorithm and risk analysis output. Compared to without implementing clustering, the improvement reached 67–80% for WMs with high-rating risk. This paper successfully produced risk maps for Kitchener’s network, showing that only a small percentage (0.07–1.02%) of the existing WMs needs immediate action (prioritised rehabilitation or replacement). In addition to WM length and diameter, freeze index is shown to be an influence factor for failure predictions. The integrated, proactive approach discussed in this article can be applied to other cold-region WDNs. The results help reduce water losses and develop cost-effective, practical risk-management strategies.
Published Version
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