TY - JOUR
T1 - Measuring River Surface Velocity Using UAS-Borne Doppler Radar
AU - Zhou, Zhen
AU - Riis-Klinkvort, Laura
AU - Jørgensen, Emilie Ahrnkiel
AU - Lindenhoff, Christine
AU - Frías, Monica Coppo
AU - Vesterhauge, Alexander Rietz
AU - Olesen, Daniel Haugård
AU - Lavish, Makar
AU - Dobrovolskiy, Alexey
AU - Kadek, Alexey
AU - Orlic, Niksa
AU - Grubesa, Tomislav
AU - Grosen, Henrik
AU - Nielsen, Sune
AU - Wennerberg, Daniel
AU - Fagerström, Viktor
AU - Axén, Jenny
AU - Gustafsson, David
AU - Bauer-Gottwein, Peter
N1 - Publisher Copyright:
© 2024. The Author(s).
PY - 2024
Y1 - 2024
N2 - Using Unoccupied 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 River in Sweden. Ground-truth surface velocity observations were retrieved with an electromagnetic velocity sensor (OTT MF Pro) along the XS at one 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 based on Gaussian models with: (a) one peak, and (b) two peaks. 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.
AB - Using Unoccupied 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 River in Sweden. Ground-truth surface velocity observations were retrieved with an electromagnetic velocity sensor (OTT MF Pro) along the XS at one 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 based on Gaussian models with: (a) one peak, and (b) two peaks. 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.
U2 - 10.1029/2024WR037375
DO - 10.1029/2024WR037375
M3 - Journal article
AN - SCOPUS:85209933673
SN - 0043-1397
VL - 60
JO - Water Resources Research
JF - Water Resources Research
IS - 11
M1 - e2024WR037375
ER -