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Faced with extended periods of drought and short supply of water, arid-weather countries have turned to intermittent water supply (IWS) as a means to reduce water consumption and to prolong their national water reserves. Unfortunately, such drastic measures usually fail to consider the effects of intermittent supply on the condition of piping networks and the resulting water losses, inefficiencies and overall maintenance cost on these networks. Presented herein is research work on the effects of IWS on the vulnerability of urban water distribution networks (UWDN) based on a 3-year dataset from major urban centres in Cyprus. The dataset includes information on breakage incidents, operating network parameters, external factors and vulnerability assessment and by use of data-mining and survival analysis techniques evaluates the effects of such intermittent supply strategies on the vulnerability of the water pipes and on the sustainability of the strategy.

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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.