An approach is developed for identifying key data to be used in asset management in general, and for predicting pipe breaks and selecting appropriate models in particular. The approach is applied to the District of Maple Ridge, B.C., Canada to identify the magnitude of a utility’s pipe burst problems today and in the future, enhance the development of pipe replacement priorities based on forecasted breaks, and identify key data to collect in future data acquisition programs. It may also be used by other utilities with varying amounts of data, and can be easily implemented with existing data management and analysis tools.
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Wood et al. (2009) studied this question.
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