The Great Area-Wide Debate: O&M Cleaning Optimization using SSO Rates

Summary Per its mission statement, the Water Environment Federation (WEF) is to 'provide a platform for water sector innovation.' Seemingly mundane, cleaning of wastewater collection systems is extremely costly and requires innovation. Area-wide cleaning, the focus of this paper, is estimated at $1.1B per year based on the currently accepted frequency of five years. This criterion has not been subjected to quantitative analysis now possible with the vast data generated by computerized maintenance management systems (CMMS) routinely utilized by modern utilities. The Sanitary Sewer Overflow (SSO) rate provides an accepted criterion on which to base quantitative comparisons. Simply stated, per the Pareto Principle, determine SSO rates for identifiable portions of the collection system and move cleaning efforts from portions with low SSO rates to high SSO rates. Initial analyses, discussed in this abstract, indicate that portions of the collection system can be identified with significantly different SSO rates. These differences, based on pipe attributes, location in the system, and time since cleaning, provide the opportunity for significant savings. Introduction Core Attributes of Effectively Managed Wastewater Collection Systems recommends proactive system-wide (area-wide) cleaning to regularly clean lines not known to suffer recurring blockages. Problem lines are recommended to be addressed in a separate preventative maintenance (hot-spot) cleaning program. A utility, believing more frequent is better, may select a five-year cycle to demonstrate a commitment to decreasing SSOs. US collection systems include 740,000 miles of public mains (WEF, 2011). The annual cost to properly clean the small diameter portion of the public sewer systems is $1.1B assuming 90% of the public mains are small diameter, and 20% are cleaned each year at a rate of $1.50/LF. This is a staggering societal cost that has not been subjected to rigorous efficiency analysis. Methodology Objective and Goal The objective of this study is to examine the proactive area-wide cleaning program for opportunities to improve the effectiveness of the overall program. This will also result in changes to preventive maintenance hot-spot cleaning programs by identifying cleaning resources that can be reallocated. The long-term goal is to reduce dry weather SSOs with equal or less resources. Metric The SSO rate provides a metric to identify poorly performing portions of the system. Figure 1 provides the definition of the SSO rate. Utility Systems Studied This study includes data from two utilities: The Albuquerque Bernalillo County Water Utility Authority (ABCWUA) and Yarra Valley Water (YVW). See Table 1 for a system comparison. YVW has not implemented O&M cleaning. The YVW system can serve as a 'control' sample to observe how a system functions without intervention by cleaning. Therefore, the SLN study was completed for both systems while the remaining studies utilized only WUA data. Segment Loading Number (SLN) The WUA and YVW evaluated SSO rates at different locations, i.e., SLN, in the collection system. Figure 2 shows the counting method and Figure 3 shows the SSO rates for both systems. Note the significant trend for increasing SSO rates as flow progresses downstream. Time Since Cleaning The purpose of this analysis is to determine the need to clean lines that are not in the hot-spot program. In this analysis, the SSO rate is determined for each year after cleaning and prior to cleaning the cohort of lines subject to area-wide cleaning in a particular year. Lines in the hot-spot cleaning program are not included in this analysis. Figure 4 displays the SSO Rate, by years of cleaning, for each cleaning cohort from FY14 through FY21. The rates are aligned by years before or since cleaning. The average rate is provided for each year before and after cleaning. Area-Wide vs. Hot-Spot Cleaning The purpose of this study is to compare the SSO rate in the hot-spot program versus the rest of the system. Figure 5 provides the rates and trendlines. Results The results of these analyses highlight the importance of evaluating the SSO rates for a gravity system before restructuring a cleaning program. First, the SLN analysis shows a difference in SSO rate upstream in the system versus downstream in the system. The SLN analysis shows a clear increase in SSO rates for the lower portion of the two collection systems. Lines with a higher SLN in the WUA and YVW systems are more likely to have a blockage and cause an overflow. The time since cleaning analysis does not indicate a significant change in the SSO rate for the lines not in the hot-spot program. Rather than increasing, as expected, in successive years after cleaning, the rate is consistent possibly decreasing. The SSO rate comparison of hot-spot and non-hot-spot programs demonstrates a long-term success. Even with hot-spot cleaning rates up to 30 times the remainder of the system, the hot-spot lines have historically suffered a higher SSO Rate. The WUA has focused cleaning on the hot-spot lines and has thereby lowered SSOs. Discussion While the WUA is already moving forward with changes to the area-wide cleaning program, meaningful change must be on the industry level. It is our belief that other utilities also have a desire to reduce SSOs with equal or less resources. 'Clean smarter, not harder' should be the new catchphrase amongst utilities. The analyses identified that SSO rates are not identical across the system. Instead, clear differences are identified, and lessons are being learned about how and when to clean based on SSO rates. The same process can be used to evaluate additional inspections. E.g., shifting a crew from cleaning to inspection will result in less footage cleaned, but result in a lower SSO Rate due to significantly more effective cleaning, i.e., cleaning the right lines. If so, should this not be the preferred program? This also allows utilities to focus on the quality of their cleaning in hot-spot lines rather than meeting a specific goal each year. The analyses performed are just some of the possible studies for reallocating cleaning resources based on SSO rates. Other studies that could be considered include, pipe material and age, groundwater level, and pipe slope. Artificial intelligence and machine learning methods are likely to provide valuable insights. Ultimately, these analyses for effectiveness could become a standard process conducted periodically by utilities utilizing in-house staff or through contracting. WEF is the platform to rigorously compare O&M data to existing O&M criteria. The O&M Technical Project Group (TPG) of the Collection Systems Committee has identified supporting industry evaluation of cleaning criteria as consistent with its focus. This is included in the recent fact sheet developed by the TPG with the hope of sponsoring a workshop at WEFTEC 2024. This presentation is a critical first step. We request your support.