Water pipe failure prediction and risk models: state-of-the-art review

This review paper presents the current state-of-the-art pertains to water pipe failure prediction and risk assessment, published in the last ten years (2009–2019). This paper has been motivated by the lack of comprehensive review articles that integrates water network failure and risk modeling. Some of the current practices reviewed the pipe condition and its failure. Others focused on the statistical prediction models, whereas the rest outlined failure prediction models of large diameter mains only. The mainstream of the current practice, highlighted in this paper characterizes the structural deterioration and failure rates using various statistical techniques, whereas the remainder of research covers a proliferation of machine learning and soft computing applications to forecast and model the pipeline risk of failure. The review offers descriptions of the models together with their proposed methodologies, algorithms and equations, contributions and drawbacks, comparisons and critiques, and types of data used to develop the models using the bibliographic review method. Finally, future work and research challenges are recommended to assist the civil engineering research community in setting a clear agenda for the upcoming research.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author