RESEARCH ARTICLE


Monitoring Deterioration in a Catchment’s Sewerage System



Ross Sparks1, Andrew Kasmarik*, 2
1 CSIRO Mathematics, Informatics and Statistics, Australia
2 Milroy Jayaveerasingam, and Jovan Titus, Asset Planning, Sydney Water, Australia


Article Metrics

CrossRef Citations:
0
Total Statistics:

Full-Text HTML Views: 312
Abstract HTML Views: 838
PDF Downloads: 325
Total Views/Downloads: 1475
Unique Statistics:

Full-Text HTML Views: 208
Abstract HTML Views: 532
PDF Downloads: 224
Total Views/Downloads: 964



Creative Commons License
© 2013 Sparks and Kasmarik;

open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: https://creativecommons.org/licenses/by/4.0/legalcode. This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

* Address correspondence to this author at the CSIRO Mathematics, Informatics and Statistics, Australia; Tel: +61 2 93253262; Fax: +61 2 93253200; E-mail: Ross.Sparks@csiro.au


Abstract

Groundwater seepage through cracks in the sewerage pipeline is a major maintenance issue in most cities’ sewer networks. The more the sewer pipes crack – and the wider these cracks are – the worse the rainfall seepage problem becomes.

The total volume of rainwater seepage into the sewer pipes for a catchment is correlated with deterioration and can therefore be used to estimate the rate of deterioration. This paper describes a monitoring system that can be used to identify significant trends in sewer deterioration.

Effective monitoring by asset managers can highlight the need for early maintenance such as removing tree roots from pipe cracks and patching the cracks.

Keywords: Bias, degradation, estimation, prediction, seepage, statistical process control.