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.

中文翻译：

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利用无人机图像在潮汐流环境中的水垢沸腾物的表面表征

针对潮汐涡轮机安装的高流量潮汐流环境在特定的时空尺度（米和秒）上表现出湍流特征，这是由特定地点的地形和测深法创建的。人们认为，河床湍流特征（卵泡沸腾）会对潮汐涡轮机产生不利影响。因此，对于汽轮机的可靠性，控制和维护策略，至关重要的是对它们进行表征。由于海洋动物会利用这些地点进行觅食，因此还将增进对与涡轮机潜在的生态相互作用的了解。无人机（UAV）或无人机影像提供了一种新颖的方法，可以对表面的鱼骨煮沸特性（分布，存在和面积）进行精确测量。这项研究在苏格兰彭特兰（Pentland）湾的内在声音中进行了63次无人机调查，英国，在2016年和2018年为期四天。针对相关环境协变量检查了煤的煮沸特性，以调查潜在的存在和区域驱动因素。结果表明，可以根据潮汐相来预测地表分布，流速在3.0 m / s以上会显着影响潮汐的存在。该技术可用于为涡轮机开发，微选址提供信息，并更好地了解涡轮机运行对环境的影响。最后，它强调了无人机在没有现场测量的情况下适合捕获快速的精细水动力数据的适用性。结果表明，可以根据潮汐相来预测地表分布，流速在3.0 m / s以上会显着影响潮汐的存在。该技术可用于为涡轮机开发，微选址提供信息，并更好地了解涡轮机运行对环境的影响。最后，它强调了无人机在没有现场测量的情况下适合捕获快速的精细水动力数据的适用性。结果表明，可以根据潮汐相来预测地表分布，流速在3.0 m / s以上会显着影响潮汐的存在。该技术可用于为涡轮机开发，微选址提供信息，并更好地了解涡轮机运行对环境的影响。最后，它强调了无人机在没有现场测量的情况下适合捕获快速的精细水动力数据的适用性。