Towards a decentralized solution for sewer leakage detection – a review

Abstract

Sewer pipelines often leak due to physical, operational, and environmental deterioration factors. Due to the hidden infrastructure of the sewer systems, leakage detection is often costly, challenging, and crucial at the city scale. Various sewer inspection methods (SIMs) have been developed and implemented these days. This study evaluates the existing SIMs and categorizes them based on their area of impact (AoI) into three classes. Tier-one (T-I) methods, such as deterioration models and hotspot mapping, tend to grasp a broader and reliable understanding of the sewer systems' structural health and pinpoint the network sections that are more prone to leakage. As an intermediate solution, Tier-two (T-II) non-destructive methods, such as aerial thermal imagery (ATI) and electrical resistivity tomography (ERT), inspect the potential pipe clusters regardless of their material and visualize the leaked plume generated from defects and cracks. Tier-three (T-III) methods include in-pipe SIMs, such as visual and multi-sensory inspections, that can provide an in-depth understanding of the pipe and its deterioration stage. In this study, we suggest that a sustainable sewer inspection plan should include at least two SIMs belonging to different tiers to provide a dual investigation of precision and AoI, a balance between cost and time as well as an equilibrium between self-sufficiency and decentralization.

Water infrastructure asset management: state of the art and emerging research themes

“…This paper is not a systematic review as others encountered in the current literature and used in the following (Bradley et al, 2016;L. Chen & Bai, 2019;Daulat et al, 2022;Hawari et al, 2020;Langeveld et al, 2022;Matejko, 1983;McDonald, 2019;Mohammadi et al, 2019;Mohammadi et al, 2020;Nkwunonwo et al, 2023;Sadeghikhah et al, 2022). It highlights research proposals based on the authors' experience faced with an analysis of the perspectives set out in recent articles (2018)(2019)(2020)(2021)(2022), and supported by a state of the art largely based on the literature in the field.…”