Replacement predictions for drinking water networks through historical data

Lifetime distribution functions and current network age data can be combined to provide an assessment of the future replacement needs for drinking water distribution networks. Reliable lifetime predictions are limited by a lack of understanding of deterioration processes for different pipe materials under varied conditions. An alternative approach is the use of real historical data for replacement over an extended time series. In this paper, future replacement needs are predicted through historical data representing more than one hundred years of drinking water pipe replacement in Gothenburg, Sweden. The verified data fits well with commonly used lifetime distribution curves. Predictions for the future are discussed in the context of path dependence theory.

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► In this study we use historical data to predict future replacement needs.
► Data from more than one hundred years are used.
► Historical data provide a reliable prediction.
► The data fits well with commonly used lifetime distribution curves.
► Replacement needs are path dependent and influenced by external factors.