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.

中文翻译：

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城市水系垂直资产的劣化模型及使用寿命预测

本研究提出了一种使用回归分析开发恶化模型并预测城市供水系统垂直资产（即储水箱和泵站）使用寿命的方法。分析了导致这些资产恶化的主要因素。计算了 22 个储水罐和 17 个污水泵站的平均和最大恶化的简单和多元线性回归模型。一组四个储水箱的数据用于验证所开发的恶化模型。使用开发的模型进行使用寿命预测，并考虑两个最大劣化水平：最大建议和允许的劣化水平。进一步研究了两个储水罐，通过比较干预前后的资产劣化情况来说明和讨论维护和修复干预措施对资产使用寿命的影响。结果包括作为资产年龄函数的平均和最大恶化指数的简单线性回归模型以及包含其他物理、操作和环境因素的多元线性回归模型。结果表明，资产恶化的简单线性回归模型比多元回归模型具有更好的预测能力。尽管多元回归模型的数据变异性较高，但这些模型允许通过计算标准差来包含资产恶化的随机过程。这项研究还表明，与主要的零星康复干预相比，定期干预是一种更好的维护和康复策略，因为它可以使资产保持良好状态并几乎无限期地延长其使用寿命。