Linking sewer condition assessment methods to asset managers’ data-needs

Noshahri, Hengameh; Scholtenhuis, Léon Luc olde; Dorée, Andries G.; Dertien, Edwin

doi:10.1016/j.autcon.2021.103878

Cited by 14 publications

(13 citation statements)

References 57 publications

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“…A major goal of this project was to integrate stormwater and sewer infrastructure information with water quality data to develop a ranking system to identify potential areas in need of assessment, remediation, or structural testing [44]. TCE is an ideal case study location for this analysis as the estuary is geographically small, highly valuable for recreational water quality activities, well-studied [18], and the town has detailed information about the infrastructure surrounding the site.…”

Section: Integrating Fib Qmst and Gis-based Infrastructure Datamentioning

confidence: 99%

Using a combination of quantitative culture, molecular, and infrastructure data to rank potential sources of fecal contamination in Town Creek Estuary, North Carolina

Hynes,

Beattie,

Blackwood

et al. 2024

PLoS ONE

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Estuarine water quality is declining worldwide due to increased tourism, coastal development, and a changing climate. Although well-established methods are in place to monitor water quality, municipalities struggle to use the data to prioritize infrastructure for monitoring and repair and to determine sources of contamination when they occur. The objective of this study was to assess water quality and prioritize sources of contamination within Town Creek Estuary (TCE), Beaufort, North Carolina, by combining culture, molecular, and geographic information systems (GIS) data into a novel contamination source ranking system. Water samples were collected from TCE at ten locations on eight sampling dates in Fall 2021 (n = 80). Microbiological water quality was assessed using US Environmental Protection Agency (U.S. EPA) approved culture-based methods for fecal indicator bacteria (FIB), including analysis of total coliforms (TC), Escherichia coli (EC), and Enterococcus spp. (ENT). The quantitative microbial source tracking (qMST) human-associated fecal marker, HF183, was quantified using droplet digital PCR (ddPCR). This information was combined with environmental data and GIS information detailing proximal sewer, septic, and stormwater infrastructure to determine potential sources of fecal contamination in the estuary. Results indicated FIB concentrations were significantly and positively correlated with precipitation and increased throughout the estuary following rainfall events (p < 0.01). Sampling sites with FIB concentrations above the U.S. EPA threshold also had the highest percentages of aged, less durable piping materials. Using a novel ranking system combining concentrations of FIB, HF183, and sewer infrastructure data at each site, we found that the two sites nearest the most aged sewage infrastructure and stormwater outflows were found to have the highest levels of measurable fecal contamination. This case study supports the inclusion of both traditional water quality measurements and local infrastructure data to support the current need for municipalities to identify, prioritize, and remediate failing infrastructure.

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Section: Integrating Fib Qmst and Gis-based Infrastructure Datamentioning

confidence: 99%

Using a combination of quantitative culture, molecular, and infrastructure data to rank potential sources of fecal contamination in Town Creek Estuary, North Carolina

Hynes,

Beattie,

Blackwood

et al. 2024

PLoS ONE

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“…Highly visible smoke will be injected in an isolated pipe section, which is likely to escape the pipe from present cracks and further travel through the porous parts and cavities of the subsoil and eventually observe at the ground level. Smoke testing is unable to quantify the severity and leakage rate of the defect, while large pipe investigation is limited by the smoke blower capacity (Eiswirth et al 2000;Noshahri et al 2021).…”

Section: General Approachesmentioning

confidence: 99%

Towards a decentralized solution for sewer leakage detection – a review

Sadeghikhah

Ahmed

Krebs

2022

Water Science and Technology

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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.

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“…The above scenarios are particularly suitable for metallic pipes. The scientific and engineering communities have developed techniques for detecting defects in operational pipelines, classified into three main categories for pipeline maintenance [18]. These encompass locating pipelines and underground facilities, identifying excavation damage and encroachments to the right of way, leak detection, and damage mitigation [19].…”

Section: Introductionmentioning

confidence: 99%

Non-Destructive Characterization of Cured-in-Place Pipe Defects

Dvořák,

Jakubka,

Topolář

et al. 2023

Materials

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Sewage and water networks are crucial infrastructures of modern urban society. The uninterrupted functionality of these networks is paramount, necessitating regular maintenance and rehabilitation. In densely populated urban areas, trenchless methods, particularly those employing cured-in-place pipe technology, have emerged as the most cost-efficient approach for network rehabilitation. Common diagnostic methods for assessing pipe conditions, whether original or retrofitted with-cured-in-place pipes, typically include camera examination or laser scans, and are limited in material characterization. This study introduces three innovative methods for characterizing critical aspects of pipe conditions. The impact-echo method, ground-penetrating radar, and impedance spectroscopy address the challenges posed by polymer liners and offer enhanced accuracy in defect detection. These methods enable the characterization of delamination, identification of caverns behind cured-in-place pipes, and evaluation of overall pipe health. A machine learning algorithm using deep learning on images acquired from impact-echo signals using continuous wavelet transformation is presented to characterize defects. The aim is to compare traditional machine learning and deep learning methods to characterize selected pipe defects. The measurement conducted with ground-penetrating radar is depicted, employing a heuristic algorithm to estimate caverns behind the tested polymer composites. This study also presents results obtained through impedance spectroscopy, employed to characterize the delamination of polymer liners caused by uneven curing. A comparative analysis of these methods is conducted, assessing the accuracy by comparing the known positions of defects with their predicted characteristics based on laboratory measurements.

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Linking sewer condition assessment methods to asset managers’ data-needs

Cited by 14 publications

References 57 publications

Using a combination of quantitative culture, molecular, and infrastructure data to rank potential sources of fecal contamination in Town Creek Estuary, North Carolina

Using a combination of quantitative culture, molecular, and infrastructure data to rank potential sources of fecal contamination in Town Creek Estuary, North Carolina

Towards a decentralized solution for sewer leakage detection – a review

Non-Destructive Characterization of Cured-in-Place Pipe Defects

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