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Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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HESS | Articles | Volume 22, issue 8
Hydrol. Earth Syst. Sci., 22, 4165–4181, 2018
https://doi.org/10.5194/hess-22-4165-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Hydrol. Earth Syst. Sci., 22, 4165–4181, 2018
https://doi.org/10.5194/hess-22-4165-2018
© Author(s) 2018. This work is distributed under
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

Filippo Bandini et al.

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Status: closed
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AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision
ED: Publish subject to revisions (further review by editor and referees) (16 Mar 2018) by Anas Ghadouani
AR by Filippo Bandini on behalf of the Authors (24 Apr 2018)  Author's response    Manuscript
ED: Referee Nomination & Report Request started (07 May 2018) by Anas Ghadouani
RR by Anonymous Referee #2 (03 Jun 2018)
ED: Publish subject to minor revisions (review by editor) (04 Jun 2018) by Anas Ghadouani
AR by Filippo Bandini on behalf of the Authors (10 Jun 2018)  Author's response    Manuscript
ED: Publish subject to minor revisions (review by editor) (22 Jun 2018) by Anas Ghadouani
ED: Publish as is (29 Jun 2018) by Anas Ghadouani
Publications Copernicus
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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...
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