Dealing with uncertainty in sewer condition assessment: Impact on inspection programs

Roghani, Bardia; Cherqui, Frédéric; Ahmadi, Mehdi; Gauffre, P. Le; Tabesh, Massoud

doi:10.1016/j.autcon.2019.03.012

Cited by 17 publications

(12 citation statements)

References 37 publications

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“…An overview of how the different defect types and severities contribute to the CS can be seen in Table 2. 1 Connection with lining defection or intruding connection, 2 Connection through cut hole in reline pipe, 3 Connection through drill hole in pipe, 4 Connection through chop hole in pipe. The color indicates the CS and goes from green to red.…”

Section: Methodsmentioning

confidence: 99%

“…CCTV inspection is done by manually sending a TV-inspection robot into the sewer and annotating all observations. As this is very time consuming, expensive, and imprecise due to a number of subjective factors [3,4], much research has been put into automating these processes [1,5]. However, full automatization of sewer inspection is not imminent.…”

Section: Introductionmentioning

confidence: 99%

“…Development of sewer deterioration models is complicated by a high uncertainty in the data. This uncertainty is influenced, among other things, by subjectivity in the annotation of CCTV inspections, lack of data, and subjective selection of which pipes to inspect [3]. Dirksen et al [4] found that defects with distinct features like roots were easy to find, while the probability of getting a false negative for other defect types varied around 0.25.…”

Section: Introductionmentioning

confidence: 99%

“…This is not encountered when using the build-in feature analysis in Random Forest [10], however. Due to the uncertainty in the data, Roghani et al [3] found that using the two or three most informative predictor variables was sufficient to build the deterioration model. However, using a deterioration model was better than just basing it on the inspection age.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Comprehensive Feature Analysis for Sewer Deterioration Modeling

Hansen

Rasmussen²,

Uggerby³

et al. 2021

Water

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Timely maintenance of sewers is essential to preventing reduced functionality and breakdown of the systems. Due to the high costs associated with inspecting a sewer system, substantial research has focused on sewer deterioration modeling and identification of the most useful features. However, there is a lack of consensus in the findings. This study investigates how the feature importance depends on the definition of bad pipes and how the feature importance changes between utilities with similar data bases. A dataset containing 318,457 pipes from 35 utilities with a condition state (CS) ranging from one to four was used. The dataset was cleaned, and a backward step analysis (BSA) was applied to two ways of binarizing the CS. Additionally, a BSA was applied for each utility with ≥100 pipes in CS four. The results showed that a selective definition of bad pipes reduced the performance and changed the order of which features contributed the most. In each case, either year of construction, age, groundwater, year of rehabilitation, or dimension was the most important feature. On average 6.5 features contributed to the utility-specific models. The feature analysis was sensitive to the inspection strategy, the size of the dataset, and interdependency between the features.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Comprehensive Feature Analysis for Sewer Deterioration Modeling

Hansen

Rasmussen²,

Uggerby³

et al. 2021

Water

View full text Add to dashboard Cite

show abstract

“…Another issue, with respect to sewer inspection in general, is the fact that inspection schedules are often based on operator experience and intuition, customer complaints or on preselections based on either age, material or operational conditions that are believed to have adverse effects on the state of the assets. This may result in biased data and inefficient inspection programs (Roghani et al 2019), making extrapolation from available data to a whole system extremely uncertain.…”

Section: Inspection Techniquesmentioning

confidence: 99%

Sewer asset management – state of the art and research needs

Tscheikner-Gratl

Caradot

Cherqui

et al. 2019

Urban Water Journal

Self Cite

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Sewer asset management gained momentum and importance in recent years due to economic considerations, since infrastructure maintenance and rehabilitation directly represent major investments. Because physical urban water infrastructure has life expectancies of up to 100 years or more, contemporary urban drainage systems are strongly influenced by historical decisions and implementations. The current decisions taken in sewer asset management will, therefore, have a long-lasting impact on the functionality and quality of future services provided by these networks. These decisions can be supported by different approaches ranging from various inspection techniques, deterioration models to assess the probability of failure or the technical service life, to sophisticated decision support systems crossing boundaries to other urban infrastructure. This paper presents the state of the art in sewer asset management in its manifold facets spanning a wide field of research and highlights existing research gaps while giving an outlook on future developments and research areas.

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A parsimonious approach to predict regions affected by sewer-borne contaminants in urban aquifers

Rojas-Gómez,

Binder,

Walther

et al. 2023

Environ Monit Assess

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Leaky urban drainage networks (UDNs) exfiltrating wastewater can contaminate aquifers. Detailed knowledge on spatiotemporal distributions of water-dissolved, sewer-borne contaminants in groundwater is essential to protect urban aquifers and to optimize monitoring systems. We evaluated the effect of UDN layouts on the spreading of sewer-borne contaminants in groundwater using a parsimonious approach. Due to the UDN’s long-term leakage behavior and the existence of non-degradable sewer-borne contaminants (equivalent to a conservative and constant contaminant source), we employed a concept of horizontal line sources to mimic the UDN layout. This does not require the consideration of bio-degradation processes or temporal delay and effectively bypasses the vadose zone, thus reducing computational requirements associated with a full simulation of leakages. We used a set of synthetic leakage scenarios which were generated using fractals and are based on a real-world UDN layout. We investigated the effects of typical leakage rates, varying groundwater flow directions, and UDN’s layouts on the shape of the contaminant plume, disregarding the resulted concentration. Leakage rates showed minimal effects on the total covered plume area, whereas 89% of the variance of the plume’s geometry is explained by both the UDN’s layout (e.g., length and level of complexity) and groundwater flow direction. We demonstrated the potential of applying this approach to identify possible locations of groundwater observation wells using a real UDN layout. This straightforward and parsimonious method can serve as an initial step to strategically identify optimal monitoring systems locations within urban aquifers, and to improve sewer asset management at city scale.

show abstract

Dealing with uncertainty in sewer condition assessment: Impact on inspection programs

Cited by 17 publications

References 37 publications

Comprehensive Feature Analysis for Sewer Deterioration Modeling

Comprehensive Feature Analysis for Sewer Deterioration Modeling

Sewer asset management – state of the art and research needs

A parsimonious approach to predict regions affected by sewer-borne contaminants in urban aquifers

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