Abstract

Both the well-established condition assessment and the newly developed assessment of a sewers structural substance are based on visual (CCTV)-inspection and defect coding, and thus a prone to errors and incomplete inspection data. In this study, we aim at understanding the sensitivity of structural substance assessment of sewers to several sources of uncertainties in the inspection procedure. We identified main uncertainty sources in the assessment procedure and propagated this uncertainty in the structural substance assessment of 80,000 sewer pipes. By comparing original inspection data with manipulated one, the effect of specific error types became quantifiable. It was observed that the use numerical assumptions for defect severity instead of performing a single case defect evaluation had a smaller impact on the substance assessment than on the condition assessment. However, the structural substance is more sensitive towards errors related to the extension of defects. While some errors can change the substance value / substance class of single reaches significantly, the mean impact is much lower. The substance assessment of a whole sewer network is thus quite robust against the here considered errors of inspection data.

Abstract

A sewer network’s structural condition is an important parameter for medium-term planning support purposes and for the development of rehabilitation strategies. A variety of approaches to classify structural condition have already been developed, but no universal standard so far exists. This article presents the findings of a joint project funded by the German Federal Ministry of Economic Affairs called ‘Development of a Standard to Evaluate and Classify the Structural Condition of Sewers’ (SubKanS).

The project identified wear and tear on a sewer section based on its individual type of damage and its severity using different weighting that is grounded in sewer network operators’ requirements and expectations of a classification of this kind. It is then classified in a category of structural conditions. The project calibrated model parameters and assignment rules by drawing from expert assessments and evaluations of approximately 100,000 sewer sections.

Do you want to download “{filename}” {filesize}?

In order to optimally design and continuously improve our website for you, we use cookies. By continuing to use the website, you agree to the use of cookies. For more information on cookies, please see our privacy policy.