Transforming Stormwater Renewal Strategies in the City of Greater Geelong

Abstract

Effective management of the asset lifecycle for a stormwater network requires a combination of engineering prioritization, cross-team collaboration, and field-based civil works. This case study explores how the City of Greater Geelong identified inefficiencies and barriers within their workflow for stormwater asset management and the adjustments they made to enhance their approach to renewals.

Location: The City of Greater Geelong is located 75 km southwest of Melbourne, Victoria, has a population of 280,000 and manages a stormwater network of 2,500 km of pipes.

Challenge: Geelong conducts annual pipe condition assessments, inspecting about 5% of the network each year. This data is collected to inform a capital rehabilitation program targeting the rehabilitation of deteriorating pipes as part of an overarching lifecycle management strategy. With a $2 million drainage renewal budget, the Asset Management team faced the challenge of developing an efficient workflow to evaluate extensive condition data, prioritize assets for rehabilitation, determine repair methods, and package works into capital projects. Successive years of underspending on renewal budgets, due to the time and difficulty of reviewing all CCTV results, highlighted the need for a new approach. Enhancing collaboration with the Engineering Services team was also crucial for prompt maintenance works to avoid flooding.

New Approach: The transformation of the stormwater renewal program involved integrating artificial intelligence and automation through smart logic to eliminate existing decision-making barriers and identify opportunities for efficiency improvements in communication and civil works packaging. This presentation aims to explain why this is a common problem and demonstrate how next-generation technology can streamline workflows and expedite outcomes.

Addressing the Backlog: It is common for extensive pipe condition inspection data to remain unanalysed on thumb drives or network folders for months or even years. Geelong aimed to reduce this timeframe, enabling decisions to be made within minutes of viewing the results. This was achieved by adopting a new software platform with an interface designed to facilitate decision-making. A substantial backlog of historic inspections was used to test the workflow transformation at Geelong, including assessing changes in team responsibility and communication. The goal of the new workflow was to efficiently make and record decisions regarding the next steps for each asset, which typically included: • No action required • Maintenance activity • Trenchless rehabilitation • Non-trenchless rehabilitation Engineers transitioned from a slow, laborious process involving videos, inspection reports, and spreadsheets to a streamlined single internet browser page that provided all necessary information for immediate decision-making. For each inspection, engineers received relevant information and a repair suggestion, with the ability to incorporate failure consequence inputs and record their decisions directly against each asset.

Optimizing Future Inspections: A simplified scope for CCTV works was introduced, leveraging AI for defect image processing. This increased the distance that CCTV contractors could cover each day. Future backlogs were eliminated with workflow improvements, and a streamlined process was used to prioritize maintenance activities and prepare capital works programs that align with annual budgets and community levels of service.