StormHarvester and Barwon Water began working together in 2025 as part of a transition from reactive to proactive wastewater network management. The project uses a network of sewer level sensors and machine-learning analysis to generate proactive blockage alerts. Barwon Water aimed to resolve issues before they resulted in environmental impact, customer complaints or costly asset replacement, while also evidencing compliance with its General Environmental Duty obligations to the state EPA. StormHarvester also provides inflow and infiltration analysis across the monitored network to help target investigations and reduce excess flows.
Barwon Water needed to detect developing blockages early, prioritise high-risk and high-consequence areas such as known pollution or flooding hotspots, and make sure alerts were genuine and actionable so operational teams could be deployed effectively. The broader project covered multiple locations across its wastewater network, and the case study focuses on Lorne, a coastal town on the Great Ocean Road. During holiday periods Lorne experiences high wastewater flows and has been historically prone to sewer blockages and overflows.
Since the start of the project, StormHarvester's AI-powered machine learning alerting, combined with Barwon Water's rapid response, has enabled the team to identify and address multiple early forming blockages in Lorne. In the first example, StormHarvester's predictive models detected unexpectedly high sewer levels at a manhole, accounting for rainfall and seasonal conditions, and an alert went to the smart networks team. A few days later crews located a developing partial blockage and jetting teams cleared it, which the case study says prevented what could have become a spill during heavy rainfall. In the second, an alert let the team schedule a line clean ahead of a busy holiday weekend; crews found a fat accumulation about the size of a soccer ball approximately 30 metres from the maintenance hole, plus tree roots and a large quantity of wet wipes. The third example was a sewer level sensor reading unexpectedly high even accounting for rainfall, again leading to a partial blockage being cleared.
David Snadden, General Manager, Smart & Sustainable Infrastructure at Barwon Water, said: "Insights from wastewater analytics platforms, such as StormHarvester, have helped us detect and respond to potential sewer blockages earlier, allowing us to investigate and mitigate issues that could have otherwise impacted our customers and the environment."