Next-gen sensors set to revolutionise monitoring of waterways

Healthy Land and Water Strategic Science Manager Dr Grace Muriuki and Lake Baroon Catchment Care Group Project Manager (Dairy) Paul Mackay.

Promising Australian research is looking into how the latest cutting-edge technology could be applied to water sensors to create a new breed of automated, low-cost water monitoring options.

If successful, it could revolutionise the way we monitor and manage our waterways. It would help to address the problematic lack of data currently available for decision making, due to the prohibitive cost of installing and maintaining gauging stations.

Why the project is important

  • Addresses issues which affect river management worldwide.
  • Potential to transform the way flow is measured and greatly improve understanding of how variability in river flow and flow events (e.g. floods and droughts) impact ecosystem processes and aquatic biodiversity.
  • Provides end-users with unprecedented fine-scale data crucial for flood prediction and advance warning of extreme events.
  • Allows for more accurate sediment and nutrient loads modelling.
  • Empowers better decision-making around water-allocation and waterways management.

It would also allow for more informed, critical decisions about water allocation, flood mitigation and environmental flow requirements, which have implications for water security, industry and the economy. A pilot project funded by QUT and run in collaboration with Healthy Land and Water and the University of Queensland, aims to tackle the critical information gap through the implementation of low-cost equipment and novel statistical methods to provide high resolution streamflow data.

A series of Vision-based Flow Sensors (VFS) have been deployed along a river system in South East Queensland to automatically capture time-lapse imagery of stream water height and velocity.

Innovative statistical methods and models are then applied to the data generated by these sensors. This helps convert the data into information which can be used for real-world river management.

The pilot phase for this project is now complete. The pilot was successful, even though the prevailing drought impacted on stream flows, making it challenging when there was little to no flow.

A Vision-based Flow Sensor (VFS) installed along the river.


Research learnings

  • The researchers learned that bank selection and reflective tape aided in water height detection.
  • The surface flow velocity detection method has room for improvement as the majority of the water in the watershed was too clear and slow to track movement from bubbles, leaves or other debris.
  • Further work includes validating flow calculations and extending models to predict outcomes of interest (such as flood events) and to accommodate an adaptive monitoring design.

The researchers involved in the collaboration are happy that their work has provided a proof-of-concept that demonstrates how automated in-situ flow sensing and prediction can be integrated into broadscale monitoring programs and advances a method that will dramatically decrease the cost of data collection.

Advantages include the low cost, ease of use, and potential to deploy large numbers of sensors, more frequently, and the ease of use opens up opportunity for use by non-experts to participate in monitoring, therefore end to end solutions.

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