Development of a Quality Assurance Process for Sewer Pipeline Assessment and Certification Program (PACP) Inspection Data

Abstract

Understanding the current condition and deterioration mechanism of sewer pipe networks is a critical step in improving national wastewater systems. Several studies have attempted to develop deterioration models for sewer pipes, and a common concern raised by those studies was data quality. Due to quality issues in current data collection practices, approximately one-third of the data are not usable for asset management purposes. Those data primarily are related to pipes that are in deficient conditions and when the inspection process is interrupted by severe defects in the pipes. The objective of this paper is to present a quality assurance process for the Pipeline Assessment and Certification Program (PACP) inspection data which may be used to develop a unified and useful database for further analysis. PACP is a widely accepted standard data collection format for closed-circuit television (CCTV) inspections of sewer pipes. PACP databases with more than 90,000 inspections provided by four municipalities across the nation were examined to identify common data quality problems. The proposed quality assurance process consists of three steps: (1) Formulating a quality assurance framework; (2) Detecting problematic data; and (3) Resolving problematic data. The results show that, by applying the proposed quality assurance process, the percentage of good quality inspection data increased from 50%–75% (pre-process) to 95% (post-process). This paper contributes to the overall body of knowledge by providing a robust data quality assurance process for underground sewer pipe inspection data, which will result in quality data for sewer asset management endeavors.