Articles | Volume 22, issue 8
https://doi.org/10.5194/hess-22-4165-2018
© Author(s) 2018. 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-22-4165-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Technical note
| 
07 Aug 2018
Technical note |
| 07 Aug 2018
| 07 Aug 2018
Technical note: Bathymetry observations of inland water bodies using a tethered single-beam sonar controlled by an unmanned aerial vehicle
Department of Environmental Engineering, Technical University of
Denmark, Kgs. Lyngby, Denmark
Daniel Olesen
National Space Institute, Technical University of Denmark, Kgs.
Lyngby, 2800, Denmark
Jakob Jakobsen
National Space Institute, Technical University of Denmark, Kgs.
Lyngby, 2800, Denmark
Cecile Marie Margaretha Kittel
Department of Environmental Engineering, Technical University of
Denmark, Kgs. Lyngby, Denmark
Sheng Wang
Department of Environmental Engineering, Technical University of
Denmark, Kgs. Lyngby, Denmark
Monica Garcia
Department of Environmental Engineering, Technical University of
Denmark, Kgs. Lyngby, Denmark
Peter Bauer-Gottwein
Department of Environmental Engineering, Technical University of
Denmark, Kgs. Lyngby, Denmark
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51 citations as recorded by crossref.
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- Buoyant calving and ice-contact lake evolution at Pasterze Glacier (Austria) in the period 1998–2019 A. Kellerer-Pirklbauer et al. 10.5194/tc-15-1237-2021
- Methodology for Carrying out Measurements of the Tombolo Geomorphic Landform Using Unmanned Aerial and Surface Vehicles near Sopot Pier, Poland C. Specht et al. 10.3390/jmse8060384
- Mapping inland water bathymetry with Ground Penetrating Radar (GPR) on board Unmanned Aerial Systems (UASs) F. Bandini et al. 10.1016/j.jhydrol.2022.128789
- Geospatial Artificial Intelligence (GeoAI) in the Integrated Hydrological and Fluvial Systems Modeling: Review of Current Applications and Trends C. Gonzales-Inca et al. 10.3390/w14142211
- Applications of Unmanned Aerial Systems (UASs) in Hydrology: A Review M. Vélez-Nicolás et al. 10.3390/rs13071359
- sUAS-Based Remote Sensing of River Discharge Using Thermal Particle Image Velocimetry and Bathymetric Lidar P. Kinzel & C. Legleiter 10.3390/rs11192317
- GRDL: A New Global Reservoir Area‐Storage‐Depth Data Set Derived Through Deep Learning‐Based Bathymetry Reconstruction Z. Hao et al. 10.1029/2023WR035781
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- UAV-Based Subsurface Data Collection Using a Low-Tech Ground-Truthing Payload System Enhances Shallow-Water Monitoring A. Thomasberger & M. Nielsen 10.3390/drones7110647
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- Exploring RPAS potentiality using a RGB camera to understand short term variation on sandy beaches R. Gonçalves et al. 10.1016/j.catena.2021.105949
- Exploring modern bathymetry: A comprehensive review of data acquisition devices, model accuracy, and interpolation techniques for enhanced underwater mapping Z. Li et al. 10.3389/fmars.2023.1178845
- Methodology for Combining Data Acquired by Unmanned Surface and Aerial Vehicles to Create Digital Bathymetric Models in Shallow and Ultra-Shallow Waters J. Lubczonek et al. 10.3390/rs14010105
- Elevation modelling of an area of the Siverskyi Donets riverbed (near Haidary village, Chuguyevskiy district, Kharkiv region) K. Borysenko et al. 10.26565/2410-7360-2021-55-10
- Assessing the nature of seasonal meteorological change in people’s dependency on wetland: a case study of Bhagirathi–Hooghly floodplain system M. Roy et al. 10.1007/s10668-021-01419-8
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- Lake water storage estimation method based on similar characteristics of above-water and underwater topography C. Fang et al. 10.1016/j.jhydrol.2023.129146
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- The Bathy-Drone: An Autonomous Unmanned Drone-Tethered Sonar System A. Diaz et al. 10.3390/drones6080220
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- A Drone‐Borne Method to Jointly Estimate Discharge and Manning's Roughness of Natural Streams F. Bandini et al. 10.1029/2020WR028266
- Deriving bathymetries from unmanned aerial vehicles: a case study of a small intermittent reservoir S. Massuel et al. 10.1080/02626667.2021.1988614
- Remote sensing of river corridors: A review of current trends and future directions C. Tomsett & J. Leyland 10.1002/rra.3479
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- Exploring the Feasibility of Mitigating Flood Hazards by an Existing Pond System in Taoyuan, Taiwan K. Tseng et al. 10.3390/drones7010001
- Smart Sensors System Based on Smartphones and Methodology for 3D Modelling in Shallow Water Scenarios G. Vozza et al. 10.3390/asi6010028
- Quantification of bedform dynamics and bedload sediment flux in sandy braided rivers from airborne and satellite imagery R. Strick et al. 10.1002/esp.4558
- Modeling lake bathymetry and water storage from DEM data constrained by limited underwater surveys K. Liu & C. Song 10.1016/j.jhydrol.2021.127260
- Modelling of ice jam floods under past and future climates: A review P. Rokaya et al. 10.1016/j.hydroa.2022.100120
- Can we estimate the lake mean depth and volume from the deepest record and auxiliary geospatial parameters? P. Zhan et al. 10.1016/j.jhydrol.2022.128958
2 citations as recorded by crossref.
- Unmanned aerial vehicle observations of water surface elevation and bathymetry in the cenotes and lagoons of the Yucatan Peninsula, Mexico F. Bandini et al. 10.1007/s10040-018-1755-9
- Bathymetric Measurements of a Retention Reservoir Using Integrated Hydrographic and Photogrammetric Techniques B. Mach & M. Skrzypek 10.26552/com.C.2022.1.E19-E27
Latest update: 26 Jul 2024
Short summary
Water depth observations are essential data to forecast flood hazard, predict sediment transport, or monitor in-stream habitats. We retrieved bathymetry with a sonar wired to a drone. This system can improve the speed and spatial scale at which water depth observations are retrieved. Observations can be retrieved also in unnavigable or inaccessible rivers. Water depth observations showed an accuracy of ca. 2.1 % of actual depth, without being affected by water turbidity or bed material.
Water depth observations are essential data to forecast flood hazard, predict sediment...
