The influence of condition assessment uncertainties on sewer deterioration modelling

Journal article (2019)

Authors

Nicolas Caradot Université Claude Bernard Lyon 1, Kompetenzzentrum Wasser Berlin
Mathias Riechel Kompetenzzentrum Wasser Berlin
Pascale Rouault Kompetenzzentrum Wasser Berlin
Antoine Caradot Institut Camille Jordan
Nic Lengemann Berliner Wasserbetriebe
Elke Eckert Berliner Wasserbetriebe
Alexander Ringe Berliner Wasserbetriebe
F.H.L.R. Clemens Deltares, Sanitary Engineering - CEG
Frédéric Cherqui Université Claude Bernard Lyon 1
Research Group
Sanitary Engineering (CEG) (TU Delft)
Uncertainty Sewer Inspection Asset management Condition assessment Defect Deterioration model Closed-circuit television (CCTV)
More Info
expand_more

Published Date

2019

Language

English

Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Faculty

Civil Engineering & Geosciences

Department

Water Management

Research Group

Sanitary Engineering

Abstract

Deterioration models can be used to forecast the evolution of the condition of the sewer network under different investment strategies. Models are calibrated using condition scores obtained from sewer visual inspection. Many studies highlighted the uncertainties in the procedure of sewer condition assessment, mainly due to the subjectivity of the coding operator. However, the influence of this uncertainty on the outcomes of deterioration modelling remains unknown. This paper analyses the influence of sewer condition uncertainties on the prediction of deterioration models. An optimisation methodology has been applied to quantify uncertainties in sewer condition assessment from the analysis of a set of repeated inspections. Then, a method is proposed to propagate uncertainties in the survival curves of a deterioration model using the inspection dataset of the city of Berlin, Germany. Results indicate that old pipes in bad condition are more prone to False Negative than False Positive (higher probability to miss defects). As a result, the propagation of uncertainties leads to more pessimistic survival curves with a confidence interval of ±12% at 100 years. The analysis shows that the required replacement rate to maintain a constant network condition is underestimated if uncertainties are not considered.