Estimating windage coefficient of floating marine green tide of Ulva prolifera using UAV optical images

Abstract

Ulva prolifera green tides have emerged every year since 2007 in the Yellow Sea, China. Accurate prediction of trajectories of green tide is very important for early warning and prevention. Surface current and wind are major drivers for drift of green tides. Windage coefficient of $\alpha$ is often used to represent the role of wind in the drift velocity of Ulva masses. However, due to the lack of measured ambient current, the windage coefficient estimate is still highly uncertain. This study presented a novel method which makes it possible for measuring drift velocity and ambient current simultaneously. Using measured drift velocity of Ulva, ambient surface current and wind, the study found that, drift velocity of Ulva is significantly different from ambient current, and the velocity difference between them is well consistent with wind direction. The study established current-depth dependent windage coefficient $\alpha$ (0.41 ± 0.09 % at 2.5 cm depth and 0.74 ± 0.16 % at 10 cm depth). The estimated $\alpha$ in this study is much smaller than previously derived or used, probably because the depth of measured ambient surface current is very close to depth of floating Ulva. The study found that windage coefficient of Ulva is dependent on the depth of the given surface current; windage coefficient increases with increase of surface current depth, implying the necessity to use very-near-surface current to improve model skill of green tides' trajectory simulation. These findings are helpful in understanding the dynamics of drift of green tides and improving accuracy of green tides modeling.