TY - JOUR
T1 - Surface Characterisation of Kolk-Boils within Tidal Stream Environments Using UAV Imagery
AU - Slingsby, James
AU - Scott, Beth E.
AU - Kregting, Louise
AU - McIlvenny, Jason
AU - Wilson, Jared
AU - Silva Couto, Ana Sofia
AU - Roos, Deon
AU - Yanez, Marion
AU - Wilson, Benjamin J.
N1 - Funding: This work was funded by the Bryden Centre project, supported by the European Union’s IN- TERREG VA Programme, and managed by the Special EU Programmes Body (SEUPB). The views and opinions expressed in this paper do not necessarily reflect those of the European Commission or SE- UPB. Aspects of this research were also funded by a Royal Society Research Grant [RSG\R1\180430], the NERC VertIBase project [NE/N01765X/1] and the UK Department for Business, Energy and Industrial Strategy’s offshore energy Strategic Environmental Assessment programme.
Data Availability Statement
The data underlying this article will be shared on reasonable request to the corresponding author.
Acknowledgments
We gratefully acknowledge the support of Julien Martin, colleagues at Marine Scotland Science and the crew and scientists of the MRV Scotia 2016 and 2018 cruises (particularly Chief Scientists Eric Armstrong and Adrian Tait). We also acknowledge the work contributed by ERI interns: Gael Gelis and Martin Forestier.
PY - 2021/4/30
Y1 - 2021/4/30
N2 - High-flow tidal stream environments, targeted for tidal turbine installations, exhibit turbulent features, at fine spatio-temporal scales (metres and seconds), created by site-specific topography and bathymetry. Bed-derived turbulent features (kolk-boils) are thought to have detrimental effects on tidal turbines. Characterisation of kolk-boils is therefore essential to inform turbine reliability, control, and maintenance strategies. It will also improve the understanding of potential ecological interactions with turbines, as marine animals use these sites for foraging. Unmanned aerial vehicle (UAV), or drone, imagery offers a novel approach to take precise measurements of kolk-boil characteristics (distribution, presence, and area) at the surface. This study carried out sixty-three UAV surveys within the Inner Sound of the Pentland Firth, Scotland, UK, over four-day periods in 2016 and 2018. Kolk-boil characteristics were examined against relevant environmental covariates to investigate potential drivers of presence and area. The results show that distribution at the surface could be predicted based on tidal phase, with current velocity significantly influencing presence above 3.0 m/s. The technique can be used to inform turbine development, micro-siting and provide better understanding of environmental implications of turbine operation. Finally, it highlights the suitability of UAVs for capturing rapid fine-scale hydrodynamic data in the absence of in situ measurements.
AB - High-flow tidal stream environments, targeted for tidal turbine installations, exhibit turbulent features, at fine spatio-temporal scales (metres and seconds), created by site-specific topography and bathymetry. Bed-derived turbulent features (kolk-boils) are thought to have detrimental effects on tidal turbines. Characterisation of kolk-boils is therefore essential to inform turbine reliability, control, and maintenance strategies. It will also improve the understanding of potential ecological interactions with turbines, as marine animals use these sites for foraging. Unmanned aerial vehicle (UAV), or drone, imagery offers a novel approach to take precise measurements of kolk-boil characteristics (distribution, presence, and area) at the surface. This study carried out sixty-three UAV surveys within the Inner Sound of the Pentland Firth, Scotland, UK, over four-day periods in 2016 and 2018. Kolk-boil characteristics were examined against relevant environmental covariates to investigate potential drivers of presence and area. The results show that distribution at the surface could be predicted based on tidal phase, with current velocity significantly influencing presence above 3.0 m/s. The technique can be used to inform turbine development, micro-siting and provide better understanding of environmental implications of turbine operation. Finally, it highlights the suitability of UAVs for capturing rapid fine-scale hydrodynamic data in the absence of in situ measurements.
KW - turbulence
KW - hydrodynamics
KW - remote sensing
KW - marine renewable energy
KW - tidal energy
U2 - 10.3390/jmse9050484
DO - 10.3390/jmse9050484
M3 - Article
VL - 9
JO - Journal of Marine Science and Engineering
JF - Journal of Marine Science and Engineering
SN - 2077-1312
IS - 5
M1 - 484
ER -
