Foundational Asset Condition Assessment Project progress update - December

17 December 2025

The Foundational Asset Condition Assessment Project (FACAP) data processing and analysis has been steadily progressing in the background since the completion of the ground, aerial and bathymetric surveys in September 2025.

We are now pleased to announce that the final project data has been delivered to the Asset Management Team (AMT) on 16 December 2025.

The AMT, along with others, will review the data, deliverables and finalise our way forward to implementing plans to achieve intergenerational sustainability.

We would like to share with you some information about the Machine Learning that was developed and used by Beca to undertake the enormous task of assessing Murray Irrigation's assets.

Using Machine Learning to interpret imagery unlocks the powerful opportunity to automate defect detection.

The use of Machine Learning for Murray Irrigation focuses on applying advanced image analysis to detect key defect types such as erosion, slumping, vegetation within the channel, and trees impacting access or flow.

The system is designed to process high-resolution imagery, flagging areas of concern for further review and integrating with GIS platforms to support condition scoring and maintenance planning.

The below image illustrates the power of the Machine Learning technology, with erosion depicted in orange, vegetation within the channel depicted in green, and trees that may be impacting water flow in purple. 

This initiative represents a shift towards data-driven asset management in the irrigation sector.

By leveraging Machine Learning, Murray Irrigation can move forward on the journey from reactive maintenance to proactive, risk-based strategies; ultimately improving reliability, reducing costs, and supporting sustainable water delivery.