The City of Huber Heights operates a water distribution system consisting of 200 miles of predominantly cast iron and ductile iron pipe. While their system was already experiencing a relatively high break rate before 2019, the break rate from 2019 through 2021 doubled the prior 10 years. The City needed a remedy but first had to determine what caused the spike in breaks so the remedy could be right-sized.
Utilizing the City’s GIS pipe attribute data and break database, and state-of-the-art failure forecasting software (infraSOFT) that predicts future breaks, the City tested their theories about possible causes, and the answers surprised them. The City had commissioned three new booster stations, decommissioned one of its water treatment plants, and commissioned a new softening process at its primary plant, all of which impacted the break rate over the last five years. Those conclusions were obtained only through a robust analytical tool that allowed for significant interaction with the user.
The proactive watermain replacement strategy recommended after the completed analytics is expected to significantly reduce breaks and associated impacts, providing customers with a more reliable drinking water supply at a far lower cost than anticipated. Not only that, but through the ability to customize the analysis in infraSOFT, recommendations regarding the operation of the distribution system and treatment plant operations to better control finished water quality (pH, softness) were possible, and the break rate is already declining without any pipe replacement.
To build the replacement plan, the City chose not to rely on industry-standard values for predicting pipe life because those values can vary widely and lead to inaccurate, costly replacement decisions. Instead, the City leveraged its pipe attribute data set and empirical break database dating back to 2010 to identify its riskiest pipes.
The City’s GIS contained over 99 percent population of attribute data for installation date, diameter, and material. Estimates of the remaining attributes were made with the City. The 12 years of breaks in the database were all associated with a corresponding pipe. This was a significant effort to ensure the accuracy of break data.
Asset and break data were imported into the infraSOFT online platform, specifically designed to make pipe-by-pipe failure predictions leveraging machine learning algorithms. Before performing the analyses, the software guides the user through a series of quality control steps to verify and improve data quality and assure the most accurate predictions. The faulty data is flagged, and the user can either correct the data quality issues or remove them from the analysis.
Predicted break information is coupled with each pipe’s consequence of failure data generated based on proximity to roads, water, structures, and service to critical customers. With a listing of pipes prioritized by risk, the City evaluated the resultant break rate and risk associated with various proactive watermain replacement investment levels and zeroed in on an affordable annual expenditure that will stabilize the break rate.
The information shared in this session will be presented with Russ Bergman, City Engineer for the City of Huber Heights.