Journal Article

Models and explanatory variables in modelling failure for drinking water pipes to support asset management: a mixed literature review

Martínez Gomariz, Eduardo, Cucchietti, Fernando, Baque Viader, Ferran, Sàrrias Monton, Miquel, Universitat Politècnica de Catalunya. Doctorat en Enginyeria Civil, Universitat Politècnica de Catalunya. Geo2Aqua - Monitoring, modelling and geomatics for hydro-geomorphological processes, Centre Internacional de Mètodes Numèrics en Enginyeria, Sánchez Juny, Martí, Barcelona Supercomputing Center, Universitat Politècnica de Catalunya. Departament d'Enginyeria Civil i Ambiental, Cardús González, Jaume, Forero Ortiz, Edwar Andres

2023

Overview

There is an increasing demand to enhance infrastructure asset management within the drinking water sector. A key factor for achieving this is improving the accuracy of pipe failure prediction models. Machine learning-based models have emerged as a powerful tool in enhancing the predictive capabilities of water distribution network models. Extensive research has been conducted to explore the role of explanatory variables in optimizing model outputs. However, the underlying mechanisms of incorporating explanatory variable data into the models still need to be better understood. This review aims to expand our understanding of explanatory variables and their relationship with existing models through a comprehensive investigation of the explanatory variables employed in models over the past 15 years. The review underscores the importance of obtaining a substantial and reliable dataset directly from Water Utilities databases. Only with a sizeable dataset containing high-quality data can we better understand how all the variables interact, a crucial prerequisite before assessing the performance of pipe failure rate prediction models.

• Publisher: Springer,Springer International Publishing,Springer Nature B.V,SpringerOpen
• Subject: Aquatic Pollution / Asset management / Comparative Law / Datasets / Drinking water / Earth and Environmental Science / Earth Sciences / Failure rates / Hydrogeology / Industrial and Production Engineering / Infrastructure asset management / International & Foreign Law / Literature reviews / Machine learning / Nanotechnology / Performance assessment / Pipe burst rate prediction / Pipe renewal / Pipes / Prediction models / Private International Law / Review Article / Variables / Waste Water Technology / Water distribution / Water engineering / Water Industry/Water Technologies / Water Management / Water network / Water pipeline failure / Water pipelines / Water Pollution Control / Water utilities