AUTHOR=Liu Darong , Li Yan , Mu Lin TITLE=Parameterization modeling for wind drift factor in oil spill drift trajectory simulation based on machine learning JOURNAL=Frontiers in Marine Science VOLUME=10 YEAR=2023 URL=https://www.frontiersin.org/journals/marine-science/articles/10.3389/fmars.2023.1222347 DOI=10.3389/fmars.2023.1222347 ISSN=2296-7745 ABSTRACT=

Marine oil spill simulations typically employ the oil particle method to calculate particle trajectories, considering various factors such as wind, current, and turbulence. The wind drift factor (WDF), a random element determining the proportion of wind’s effect on oil particles, is often empirically set as a constant in traditional oil spill models, introducing limitations. This study proposes a support vector regression-based parameterization modeling (SVR-PM) for the WDF. Using extensive buoy data and ocean hydrodynamic reanalysis data, we trained an SVR model to compute the WDF in real-time based on real-time wind speed. The SVR-PM was integrated into an oil spill model to enhance the computation of the wind-induced velocity term. We validated the model using satellite images of two significant oil spills, resulting in an excellent average agreement. The SVR-PM’s advantage lies in enhancing the accuracy of wind-induced velocity term in oil spill simulations and demonstrating strong adaptability and generalizability over time and space. This advancement holds significant implications for maritime departments and emergency disaster response units.