Deterioration Models and Service Life Prediction of Vertical Assets of Urban Water Systems

Abstract

This study proposes a methodology for developing deterioration models and predicting the service lives of vertical assets of urban water systems (i.e., water storage tanks and pumping stations) using regression analysis. The main factors contributing to the deterioration of these assets are analyzed. Simple and multiple linear regression models of average and maximum deterioration are calculated for 22 water storage tanks and 17 wastewater pumping stations. Data on a set of four water storage tanks are used to validate the developed deterioration models. Service life prediction is carried out using the developed models and considering two maximum deterioration levels: the maximum recommended and admissible deterioration levels. Two water storage tanks are further studied to illustrate and discuss the effect of maintenance and rehabilitation interventions on asset service life by comparing the asset deterioration before and after the interventions. Results include simple linear regression models of average and maximum deterioration indices as a function of asset age and multiple linear regression models that incorporate other physical, operational and environmental factors. The results show that simple linear regression models of asset deterioration show a better predictive power than multiple regression models. Despite the higher data variability of multiple regression models, these models allow to include the random process of asset deterioration, through the calculation of the standard deviation. This study also shows that periodic interventions are a preferable maintenance and rehabilitation strategy over major sporadic rehabilitation interventions since it allows to maintain assets in good condition and to extend their service life almost indefinitely.