The consistency of visual sewer inspection data
J. Dirksen
a,b
, F.H.L.R. Clemens
a,c
, H. Korving
a,c
, F. Cherqui
d
, P. Le
Gauffre
d
, T. Ertl
e
, H. Plihal
e
, K. Müller
f
; C.T.M. Snaterse
g
a
Department of Civil Engineering and Geosciences, Delft University of Technology,
Delft, The Netherlands;
b
Waternet, Amsterdam, The Netherlands;
c
Witteveen + Bos
Consulting Engineers, Deventer, The Netherlands;
d
INSA Lyon, LGCIE,
Villeurbanne, France;
e
Institute of Sanitary Engineering and Water Pollution
Control, University of Natural Resources and Life Science, Vienna, Austria;
f
Research Institute for Water and Waste Management, RWTH Aachen University,
Aachen, Germany;
g
Snaterse Civiele Techniek & Management, Ermelo, The
Netherlands
j.dirksen@tudelft.nl
(Received xx Xxx 20xx; final version received xx Xxx 20xx)
In common with most infrastructure systems, sewers are often inspected visually.
Currently, the results from these inspections inform decisions for significant investments
regarding sewer rehabilitation or replacement. In practice the quality of the data and its
analysis is not questioned although psychological research indicates that, as a
consequence of the use of subjective analysis of the collected images, errors are
inevitable. This paper assesses the quality of the analysis of visual sewer inspection data
by analyzing data reproducibility; three types of capabilities to subjectively assess data
are distinguished: the recognition of defects, the description of defects according to a
prescribed coding system and the interpretation of sewer inspection reports. The
introduced uncertainty is studied using three types of data: inspector examination results
of sewer inspection courses, data gathered in day-to-day practice, and the results of
repetitive interpretation of the inspection results. After a thorough analysis of the data it
can be concluded that for all cases visual sewer inspection data proved poorly
reproducible. For the recognition of defects it was found that the probability of a false
positive is in the order of a few percent, the probability of a false negative is in the order
of 25%.
Keywords: Sewer inspection, Reproducibility, Uncertainty
1. Introduction
Visual sewer inspection is the primary investigation technique used in sewer system
management. Decisions on the provision of the large investments associated with
sewer rehabilitation and replacement are often based on the interpretation of visual
inspection reports. These reports, as can be seen in figure 1, occur in the first
investigation stage and so impact on all future stages and therefore are an important
factor in the sewer management process. Often in practice, and even in some research
studies reported in the literature (e.g. Baur and Herz, 2002), the quality of the data is
not questioned. Some papers on deterioration modelling stress the importance of data
quality (Wirahadikusumah et al. 2001 Ariaratnam et al. 2001). However, a
comprehensive evaluation of the quality of visual sewer inspection data has not yet