Monitoring the health status of water mains using a scorecard modelling approach
Yuzhi Huang,
Raufdeen Rameezdeen,
Christopher W. K. Chow,
Nima Gorjian,
Yangyue Li,
Zijun Liu,
Peiqing Ju
Affiliations
Yuzhi Huang
UniSA STEM (Science, Technology, Engineering and Mathematics), University of South Australia, Scarce Resources and Circular Economy (ScaRCE), Mawson Lakes, South Australia 5095, Australia
Raufdeen Rameezdeen
UniSA STEM (Science, Technology, Engineering and Mathematics), University of South Australia, Scarce Resources and Circular Economy (ScaRCE), Mawson Lakes, South Australia 5095, Australia
Christopher W. K. Chow
UniSA STEM (Science, Technology, Engineering and Mathematics), University of South Australia, Scarce Resources and Circular Economy (ScaRCE), Mawson Lakes, South Australia 5095, Australia
Nima Gorjian
UniSA STEM (Science, Technology, Engineering and Mathematics), University of South Australia, Scarce Resources and Circular Economy (ScaRCE), Mawson Lakes, South Australia 5095, Australia
Yangyue Li
UniSA STEM (Science, Technology, Engineering and Mathematics), University of South Australia, Scarce Resources and Circular Economy (ScaRCE), Mawson Lakes, South Australia 5095, Australia
Zijun Liu
UniSA STEM (Science, Technology, Engineering and Mathematics), University of South Australia, Scarce Resources and Circular Economy (ScaRCE), Mawson Lakes, South Australia 5095, Australia
Peiqing Ju
UniSA STEM (Science, Technology, Engineering and Mathematics), University of South Australia, Scarce Resources and Circular Economy (ScaRCE), Mawson Lakes, South Australia 5095, Australia
There has been considerable research into prediction of water mains failure, however, those models are very complex and fail to convey the message of the health status of an asset to the relevant stakeholders. The study developed a ‘pipe health scorecard’ based on historical failure data which could be used for operation, maintenance, refurbishment, or replacement decisions by a water utility. This scorecard model was developed by using 160,413 pipe-condition data sets from the South Australian Water Corporation over ten years. Measures such as the Kolmogorov–Smirnov (KS) statistic, Area Under the ROC Curve (AUC), and Population Stability Index (PSI) showed the model is strong enough to predict the health status of water mains. The study found the factors influencing water mains failure to be in the order of importance: length, material, age, location (road vs verge), diameter, and operating parameters. The development of a simple but reliable model for the assessment of the health status of water mains will have major benefits to the water utility with the ability to identify and potentially replace water pipes prior to failure. Additional benefits of flexible scheduling of maintenance and replacement programs would contribute to cost savings. HIGHLIGHTS This study explored the use of a scorecard to prioritise pipe-replacement decisions.; A scorecard model was developed using a large real pipe-condition data set extracted from a water utility's computerised asset management system.; Factors influencing water mains failure have been identified in the order of importance: length, material, age, location (road vs verge), diameter, and operating parameters.;