Articles | Volume 27, issue 10
https://doi.org/10.5194/hess-27-2051-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-27-2051-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
31 May 2023
Research article |
| 31 May 2023
| 31 May 2023
Adaptively monitoring streamflow using a stereo computer vision system
Nicholas Reece Hutley
CORRESPONDING AUTHOR
School of Civil Engineering, The University of Queensland, Brisbane
4072, Australia
Ryan Beecroft
School of Civil Engineering, The University of Queensland, Brisbane
4072, Australia
Daniel Wagenaar
Xylem Water Solutions, Newcastle 2292, Australia
Josh Soutar
Xylem Water Solutions, Brisbane 4174, Australia
Blake Edwards
Leading Edge Engineering Solutions, Albury 2640, Australia
Nathaniel Deering
School of Civil Engineering, The University of Queensland, Brisbane
4072, Australia
Alistair Grinham
School of Civil Engineering, The University of Queensland, Brisbane
4072, Australia
Simon Albert
School of Civil Engineering, The University of Queensland, Brisbane
4072, Australia
Related authors
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Martino E. Malerba, Blake Edwards, Lukas Schuster, Omosalewa Odebiri, Josh Glen, Rachel Kelly, Paul Phan, Alistair Grinham, and Peter I. Macreadie
Biogeosciences, 22, 5051–5067, https://doi.org/10.5194/bg-22-5051-2025, https://doi.org/10.5194/bg-22-5051-2025, 2025
Short summary
Short summary
The Pondi is a cost-effective, lightweight logger designed for long-term monitoring of carbon dioxide, methane, and nitrous oxide emissions in both terrestrial and aquatic ecosystems. It addresses key challenges in greenhouse gas monitoring by providing an automated, low-cost, solar-powered solution with cloud connectivity and real-time analytics. Its robust design enables deployment in diverse environmental conditions, supporting large-scale, high-resolution emission assessments.
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Short summary
Measuring flows in streams allows us to manage crucial water resources. This work shows the automated application of a dual camera computer vision stream gauging (CVSG) system for measuring streams. Comparing between state-of-the-art technologies demonstrated that camera-based methods were capable of performing within the best available error margins. CVSG offers significant benefits towards improving stream data and providing a safe way for measuring floods while adapting to changes over time.
Measuring flows in streams allows us to manage crucial water resources. This work shows the...
