| Title: |
Measuring River Surface Velocity Using UAS‐Borne Doppler Radar |
| Authors: |
Zhen Zhou; Laura Riis‐Klinkvort; Emilie Ahrnkiel Jørgensen; Christine Lindenhoff; Monica Coppo Frías; 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 Axén; David Gustafsson; Peter Bauer‐Gottwein |
| Source: |
Water Resources Research, Vol 60, Iss 11, Pp n/a-n/a (2024) |
| Publisher Information: |
Wiley, 2024. |
| Publication Year: |
2024 |
| Collection: |
LCC:Environmental sciences |
| Subject Terms: |
Environmental sciences; GE1-350 |
| Description: |
Abstract 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. |
| Document Type: |
article |
| File Description: |
electronic resource |
| Language: |
English |
| ISSN: |
1944-7973; 0043-1397 |
| Relation: |
https://doaj.org/toc/0043-1397; https://doaj.org/toc/1944-7973 |
| DOI: |
10.1029/2024WR037375 |
| Access URL: |
https://doaj.org/article/f24bb092dc424a32b002ac3bc2a641df |
| Accession Number: |
edsdoj.f24bb092dc424a32b002ac3bc2a641df |
| Database: |
Directory of Open Access Journals |