Adaptively monitoring streamflow using a stereo computer vision system Article Swipe
Nicholas Hutley
,
Ryan Beecroft
,
Daniel A. Wagenaar
,
Josh Soutar
,
Blake Edwards
,
Nathaniel Deering
,
Alistair Grinham
,
Simon Albert
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.5194/egusphere-2022-735
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.5194/egusphere-2022-735
The gauging of free surface flows in waterways provides the foundation for monitoring and managing the water resources of built and natural environments. A significant body of literature exists around the techniques and benefits of optical surface velocimetry methods to estimate flows in waterways without intrusive instruments or structures. However, to date the operational application of these surface velocimetry methods has been limited by site configuration and inherent challenging optical variability across different natural and constructed waterway environments. This work demonstrates a significant advancement in the operationalisation of non-contact stream discharge gauging applied in the computer vision stream gauging (CVSG) system through the use of methods for remotely estimating water levels and adaptively learning discharge ratings over time. A cost-effective stereo camera-based stream gauging device (CVSG device) has been developed for streamlined site deployments and automated data collection. Evaluations between reference state-of-the-art discharge measurement technologies using DischargeLab (using surface structure image velocimetry), Hydro-STIV (using space-time image velocimetry), ADCPs (acoustic doppler current profilers), and gauging station discharge ratings demonstrated that the optical surface velocimetry methods were capable of estimating discharge within best available measurement error margins of 5–15 %. Furthermore, results indicated model machine learning approaches leveraging data to improve performance over a period of months at the study sites produced a marked 5–10 % improvement in discharge estimates, despite underlying noise in stereophotogrammetry water level or optical flow measurements. The operationalisation of optical surface velocimetry technology, such as CVSG, offers substantial advantages towards not only improving the overall density and availability of data used in stream gauging, but also providing a safe and non-contact approach for effectively measuring high flow rates while providing an adaptive solution for gauging streams with non-stationary characteristics.
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.5194/egusphere-2022-735
- OA Status
- gold
- Cited By
- 2
- References
- 59
- Related Works
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- OpenAlex ID
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All OpenAlex metadata
Raw OpenAlex JSON
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https://openalex.org/W4294243354Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.5194/egusphere-2022-735Digital Object Identifier
- Title
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Adaptively monitoring streamflow using a stereo computer vision systemWork title
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preprintOpenAlex work type
- Language
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enPrimary language
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2022Year of publication
- Publication date
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2022-09-02Full publication date if available
- Authors
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Nicholas Hutley, Ryan Beecroft, Daniel A. Wagenaar, Josh Soutar, Blake Edwards, Nathaniel Deering, Alistair Grinham, Simon AlbertList of authors in order
- Landing page
-
https://doi.org/10.5194/egusphere-2022-735Publisher landing page
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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https://doi.org/10.5194/egusphere-2022-735Direct OA link when available
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Velocimetry, Remote sensing, Environmental science, Computer science, Particle image velocimetry, Marine engineering, Geology, Meteorology, Engineering, Geography, Optics, Physics, TurbulenceTop concepts (fields/topics) attached by OpenAlex
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2Total citation count in OpenAlex
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2025: 1, 2022: 1Per-year citation counts (last 5 years)
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59Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| referenced_works | https://openalex.org/W2103316487, https://openalex.org/W2898979689, https://openalex.org/W2331946696, https://openalex.org/W2292058934, https://openalex.org/W2050093956, https://openalex.org/W3034781776, https://openalex.org/W1998521375, https://openalex.org/W2946755099, https://openalex.org/W3097535281, https://openalex.org/W3130444584, https://openalex.org/W1502190839, https://openalex.org/W2165346010, https://openalex.org/W2014458751, https://openalex.org/W1974627413, https://openalex.org/W2787184083, https://openalex.org/W2104302225, https://openalex.org/W3115878367, https://openalex.org/W2900732181, https://openalex.org/W2890404982, https://openalex.org/W3122007051, https://openalex.org/W2885449134, https://openalex.org/W2799745580, https://openalex.org/W1997604738, https://openalex.org/W2926423010, https://openalex.org/W1579717868, https://openalex.org/W2082183319, https://openalex.org/W2913836248, https://openalex.org/W61348572, https://openalex.org/W2035713012, https://openalex.org/W2995667716, https://openalex.org/W1981566948, https://openalex.org/W2077623746, https://openalex.org/W2005671348, https://openalex.org/W3165382508, https://openalex.org/W2032146370, https://openalex.org/W2109606373, https://openalex.org/W2972269523, https://openalex.org/W8437397, https://openalex.org/W2329151378, https://openalex.org/W2005660297, https://openalex.org/W3156990795, https://openalex.org/W2046955782, https://openalex.org/W3024366545, https://openalex.org/W4213281528, https://openalex.org/W3172510062, https://openalex.org/W1983889717, https://openalex.org/W2517886499, https://openalex.org/W2809996219, https://openalex.org/W2070996984, https://openalex.org/W2999271209, https://openalex.org/W2973392964, https://openalex.org/W2758946331, https://openalex.org/W2222952503, https://openalex.org/W2111410742, https://openalex.org/W2969409037, https://openalex.org/W2160312409, https://openalex.org/W2973181430, https://openalex.org/W3007840760, https://openalex.org/W3020896488 |
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