Metropolitan governments and water operators are continuously facing the ever-growing challenges of evaluating the risks and optimizing investment in the rehabilitation of the buried aging infrastructure of water distribution systems (WDS). Proper asset management and efficient rehabilitation planning require monitoring, condition assessment, degradation risk analysis and a data-based model for degradation forecasting to support investment decision-making and significantly reduce the infrastructure rehabilitation cost. This paper presents a statistical and stochastic spatial data analysis of failure records of the WDS of the City of Wattrelos, France. The research objective is to develop and demo-illustrate the application of an operator's experience-based Risk Assessment Method (RAM) for network micro-zone prioritization of rehabilitation/replacement works to optimize preemptive asset management. The data used is a 74-year historical dataset from Wattrelos, France. The database includes approximately 424 observed failures for the period of 1991–2004. The data analysis demonstrates that understanding and using stochastic modeling to characterize the pattern of relationship between Failure Rate (FR), Age (T) and the Probability (or Risk) of exceeding a specific Failure Rate (Pr(FR)) of a micro-zone can effectively support the operator's assessment, risk management and prioritization in the maintenance and rehabilitation of the WDS.

You do not currently have access to this content.