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Measuring river surface velocity using UAS-borne Doppler radar
  • +17
  • Zhen Zhou,
  • Laura Riis-Klinkvort,
  • Emilie Ahrnkiel Jørgensen,
  • Christine Lindenhoff,
  • Monica Coppo Frí As,
  • Alexander Rietz Vesterhauge,
  • Daniel Haugård Olesen,
  • Makar Lavish,
  • Alexey Dobrovolskiy,
  • Alexey Kadek,
  • Niksa Orlic,
  • Tomislav Grubesa,
  • Luka Drmić,
  • Henrik Grosen,
  • Sune Nielsen,
  • Daniel Wennerberg,
  • Viktor Fagerström,
  • Jenny Axé,
  • David Gustafsson,
  • Peter Bauer-Gottwein
Zhen Zhou
DTU Sustain, Technical University of Denmark

Corresponding Author:[email protected]

Author Profile
Laura Riis-Klinkvort
DTU Sustain, Technical University of Denmark
Emilie Ahrnkiel Jørgensen
DTU Sustain, Technical University of Denmark
Christine Lindenhoff
DTU Space, Technical University of Denmark
Monica Coppo Frí As
DTU Sustain, Technical University of Denmark
Alexander Rietz Vesterhauge
DTU Space, Technical University of Denmark
Daniel Haugård Olesen
DTU Space, Technical University of Denmark
Makar Lavish
SPH Engineering
Alexey Dobrovolskiy
SPH Engineering
Alexey Kadek
SPH Engineering
Niksa Orlic
Geolux DOO
Tomislav Grubesa
Geolux DOO
Luka Drmić
Geolux DOO
Henrik Grosen
Drone Systems Aps
Sune Nielsen
Drone Systems Aps
Daniel Wennerberg
SMHI Sveriges Meteorologiska och Hydrologiska Institut
Viktor Fagerström
SMHI Sveriges Meteorologiska och Hydrologiska Institut
Jenny Axé
SMHI Sveriges Meteorologiska och Hydrologiska Institut
David Gustafsson
SMHI Sveriges Meteorologiska och Hydrologiska Institut
Peter Bauer-Gottwein
DTU Sustain, Technical University of Denmark

Abstract

Using Unmanned Aerial Systems (UAS) equipped with optical RGB cameras and Doppler radar, surface velocity can be efficiently measured at high spatial resolution. UAS-borne Doppler radar is particularly attractive because it is suitable for real-time velocity determination, because the measurement is contactless, and because it has fewer limitations than image velocimetry techniques. In this paper, five cross-sections (XSs) were surveyed within a 10 km stretch of Rönne Å in Sweden. Ground-truth surface velocity observations were retrieved with an electromagnetic velocity sensor (OTT MF Pro) along the XS at 1 m spacing. Videos from a UAS RGB camera were analyzed using both Particle Image Velocimetry (PIV) and Space-Time Image Velocimetry (STIV) techniques. Furthermore, we recorded full waveform signal data using a Doppler radar at multiple waypoints across the river. An algorithm fits two alternative models to the average amplitude curve to derive the correct river surface velocity: a Gaussian one peak model, or a Gaussian two peak model. Results indicate that river flow velocity and propwash velocity caused by the drone can be found in XS where the flow velocity is low, while the drone-induced propwash velocity can be neglected in fast and highly turbulent flows. To verify the river flow velocity derived from Doppler radar, a mean PIV value within the footprint of the Doppler radar at each waypoint was calculated. Finally, quantitative comparisons of OTT MF Pro data with STIV, mean PIV and Doppler radar revealed that UAS-borne Doppler radar could reliably measure the river surface velocity.
26 Feb 2024Submitted to ESS Open Archive
28 Feb 2024Published in ESS Open Archive