Water utilities are facing significant challenges, such as supplying, with less water resources, more and more water due to population growth, amid the current scenario of climate change. In this context, urban water systems represent a crucial component of global public infrastructure for water utilities, with municipalities entrusted with the responsibility of managing and enhancing them for both current and future generations. The main challenge arises when these infrastructures inevitably age and deteriorate, significantly increasing water losses. Since it is unrealistic and unnecessary to rehabilitate and/or replace all pipes in an existing water distribution system, this manuscript is focused on identifying the independent key parameters which can be used to detect reinforced concrete pipe deterioration. To this end, the variables that affect mechanical properties are narrowed down, and the most significant factors crucial for pipe failure are identified. In this process, reinforced concrete pipe samples were collected to characterize them based on a set of potential key parameters. All potential key parameters were analyzed, with the objectives of identifying which key parameters were significant for the model and determining the interactions among them. All data were stored in a dataset which was used to generate a predictive model to estimate average concrete strength and pipe condition assessment versus independent key parameters. The predictive model, utilizing a design of experiments (DoE) and based on the analysis of variance (ANOVA), could estimate the average concrete strength with an accuracy of around 90%, and the external porosity was found to be the main factor. On the other hand, it was also possible to estimate a range of porosity values for the purpose of maintaining the reinforced concrete pipe in optimal condition.
