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
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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- Application of Drone Technologies in Surface Water Resources Monitoring and Assessment: A Systematic Review of Progress, Challenges, and Opportunities in the Global South M. Sibanda et al. 10.3390/drones5030084
- Structure-from-Motion on shallow reefs and beaches: potential and limitations of consumer-grade drones to reconstruct topography and bathymetry C. David et al. 10.1007/s00338-021-02088-9
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- 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
- Recent Advancements and Perspectives in UAS-Based Image Velocimetry S. Dal Sasso et al. 10.3390/drones5030081
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- Remote sensing of river corridors: A review of current trends and future directions C. Tomsett & J. Leyland 10.1002/rra.3479
- Coupling of Dual Channel Waveform ALS and Sonar for Investigation of Lake Bottoms and Shore Zones J. Chormański et al. 10.3390/rs13091833
- Combining Low-Cost Sonar and High-Precision Global Navigation Satellite System for Shallow Water Bathymetry A. Bio et al. 10.1007/s12237-020-00703-6
- Evaluating low-cost topographic surveys for computations of conveyance H. Samboko et al. 10.5194/gi-11-1-2022
- 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
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- Modelling of ice jam floods under past and future climates: A review P. Rokaya et al. 10.1016/j.hydroa.2022.100120
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- High-Resolution Bathymetry Mapping of Water Bodies: Development and Implementation L. Coggins & A. Ghadouani 10.3389/feart.2019.00330
- 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
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28 citations as recorded by crossref.
- Unmanned Aerial Vehicles in Hydrology and Water Management: Applications, Challenges, and Perspectives B. Acharya et al. 10.1029/2021WR029925
- Shrinkage of Nepal’s Second Largest Lake (Phewa Tal) Due to Watershed Degradation and Increased Sediment Influx C. Watson et al. 10.3390/rs11040444
- 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
- Applications of Unmanned Aerial Systems (UASs) in Hydrology: A Review M. Vélez-Nicolás et al. 10.3390/rs13071359
- SWAMP, an Autonomous Surface Vehicle expressly designed for extremely shallow waters A. Odetti et al. 10.1016/j.oceaneng.2020.108205
- Riverine Plastic Litter Monitoring Using Unmanned Aerial Vehicles (UAVs) M. Geraeds et al. 10.3390/rs11172045
- sUAS-Based Remote Sensing of River Discharge Using Thermal Particle Image Velocimetry and Bathymetric Lidar P. Kinzel & C. Legleiter 10.3390/rs11192317
- A Novel Method on Hydrographic Survey Technology Selection Based on the Decision Tree Supervised Learning I. Golub Medvešek et al. 10.3390/app11114966
- Testing UAV-derived topography for hydraulic modelling in a tropical environment M. Mazzoleni et al. 10.1007/s11069-020-03963-4
- Production, Validation and Morphometric Analysis of a Digital Terrain Model for Lake Trichonis Using Geospatial Technologies and Hydroacoustics T. Perivolioti et al. 10.3390/ijgi10020091
- Application of Drone Technologies in Surface Water Resources Monitoring and Assessment: A Systematic Review of Progress, Challenges, and Opportunities in the Global South M. Sibanda et al. 10.3390/drones5030084
- Structure-from-Motion on shallow reefs and beaches: potential and limitations of consumer-grade drones to reconstruct topography and bathymetry C. David et al. 10.1007/s00338-021-02088-9
- A Drone‐Borne Method to Jointly Estimate Discharge and Manning's Roughness of Natural Streams F. Bandini et al. 10.1029/2020WR028266
- 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
- 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
- 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
- Recent Advancements and Perspectives in UAS-Based Image Velocimetry S. Dal Sasso et al. 10.3390/drones5030081
- 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
- Coupling of Dual Channel Waveform ALS and Sonar for Investigation of Lake Bottoms and Shore Zones J. Chormański et al. 10.3390/rs13091833
- Combining Low-Cost Sonar and High-Precision Global Navigation Satellite System for Shallow Water Bathymetry A. Bio et al. 10.1007/s12237-020-00703-6
- Evaluating low-cost topographic surveys for computations of conveyance H. Samboko et al. 10.5194/gi-11-1-2022
- 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
- Remote inspection of RC structures using unmanned aerial vehicles and heuristic image processing D. Ribeiro et al. 10.1016/j.engfailanal.2020.104813
- High-Resolution Bathymetry Mapping of Water Bodies: Development and Implementation L. Coggins & A. Ghadouani 10.3389/feart.2019.00330
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: 06 Jun 2023
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...
