What 122 Million Meters of Sewer Data Tells Us

What 122 Million Meters of Sewer Data Tells Us About Collection System Management

Moving From Time-Based to Condition-Based Cleaning
Saves Significant Time And Money.

As a result of regulatory pressure to reduce sewer discharges and mitigate environmental damage, there was a shift in the maintenance paradigm toward proactive strategies. Municipalities adopted pre-emptive cleaning schedules – typically based on time intervals. Many municipal utilities also overlaid hot spot programs to clean historically problematic areas at higher frequencies. While the higher frequency of cleaning in proactive programs reduced overflows, it also led to unnecessary cleaning of pipes in good condition. This unnecessary cleaning wastes cleaning resources and can needlessly damage pipes over time. Additionally, municipalities remain vulnerable to SSOs when blockages build up in areas not scheduled for cleaning. As inspection technology advances, more communities have embraced a condition-based maintenance approach. This method assesses the condition of each pipe and uses that information to determine which pipes genuinely require cleaning or further maintenance activity.

The efficacy of the condition-based approach hinges on the fact that most pipes are in good condition and do not need maintenance. In the past, proving this was challenging due to the slow speed and high cost of traditional CCTV-based inspection methods, however, newer technology has lowered this financial barrier of condition assessments. This article contextualizes over 400 million ft of gravity sewer line condition assessments to give insight into the cleanliness of our collections system and the effectiveness of our maintenance practices.

About the Collection System Data

The data was collected using the Sewer Line Rapid Assessment Tool (SL-RAT). The SL-RAT uses transmissive acoustics to detect blockage anomalies in small-diameter gravity sewer lines. The transmitter unit repeats a series of tones that travel through the open airspace in the pipe to the adjacent manhole where the receiver unit listens for the known signal. Normalizing for distance, the SL-RAT assigns a score depending on how the sound is damped or attenuated by conditions in the pipe.

The SL-RAT scores a pipe segment on a scale of 0 to 10. A score of 0 means a complete blockage and 10 indicates excess flow capacity. Pipes scoring 7 to 10 do not need further cleaning, while pipes scoring 3 or below have a significant blockage or anomaly, and the municipality should clean or further investigate the pipe soon.

Pipes that score between 4 and 6 are not urgent but may need future cleaning or inspection, depending on the utility’s risk tolerance and available maintenance resources. The data set is comprised of 10 years’ worth of measurements made by municipalities and service providers between 2013 and 2023. The data is aggregated from approximately 1,500 different municipalities around the world – with the majority based in North America – comprising a sample size of 1.78 million measurements. Each measurement represents the blockage condition of a pipe segment at a point in time. The total footage of the data set sums to approximately 400 million ft with an average pipe length of 226 ft.

How Clean Is the Average Collection System?

Examining this data reveals that a significant portion of collection systems are clean. Approximately 72 percent of pipe segments score a 7 or above, meaning they have significant excess flow capacity. By following a condition-based approach, a utility should prioritize segments that score low (typically a 4 or below). This accounts for approximately 11 percent of lines measured. The remaining 17 percent of lines scored Fair. Although they do not need immediate cleaning, municipalities may put them on a future cleaning or inspection schedule. This result supports the condition-based maintenance protocol. If utilities identify these pipes, they can then use the information to better prioritize their resources and reduce unnecessary cleaning.

Condition-based maintenance becomes cost-effective when the savings from cleaning reduction are greater than the upfront assessment costs. Consider a 50-mile sewer basin. In this basin, the municipality theoretically only needs to clean five to 10 miles. Costing around $0.25 per foot, it would cost roughly $66,000 to conduct an acoustic inspection campaign and an additional $25,000 to $50,000 to clean the lines that score poorly. Comparatively, if a municipality cleaned the entire basin, it would cost upward of $250,000. Alongside the financial savings, the reduction in cleaning can also help ameliorate skilled labor shortages and reduce flushing water usage.

Regional Differences in the Data

The data, segmented by census-designated divisions, reveals that certain areas of the United States have a higher percentage of blocked lines. These regional differences may be the result of multiple factors. One potential reason is the presence of older infrastructure, which has had more time to deteriorate. Another factor might be less stringent regulatory pressure, resulting in less proactive maintenance plans or lower maintenance funding that limits resources in certain regions. Additionally, an area’s topography, weather, vegetation or local construction practices could have a higher propensity to generate sewer failures.

The data may also reflect a higher proportion of small, rural communities lacking resources for proactive maintenance. If so, it highlights a need for increased rural infrastructure funding, so these communities do not bear the burden of sewer backups. Overall, the variables involved in this regional analysis are many and complex; however, it should be noted that even for the worst regions, a condition-based protocol may still be cost-effective because the number of lines that require cleaning make up a relatively small proportion of their system.

Conclusion

As collection system maintenance strategies have evolved over the last 50 years, so must the methods, processes, and technologies municipalities use to keep them clean and functioning properly. An overreliance on proactive cleaning can lead to unnecessary cleaning costs. The subsequent evolution of

condition-based programs accounts for this excess by leveraging new technology to better deploy cleaning assets. Considering over 400 million ft of sewer data, the results confirm a potential overreliance on cleaning and subsequently support the switch to a condition-based maintenance protocol.

Chase Mendell is marketing strategist at InfoSense.

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