Computer Modeling of Oil Spill Trajectories With a High Accuracy Method |
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| Institution: | 1. Institute of Geotechnical Engineering, Southeast University, Nanjing, 211189, China;2. School of Highway, Chang’an University, Xi’an, Shaanxi, 710054, China;1. Ajou University, 206, Worldcup-ro, Yeongtong-gu, Suwon-si, Gyeonggi-do 16499, Republic of Korea;2. Korea Institute of Civil Engineering and Building Technology, 283, Goyang-daero, Ilsanseo-gu, Goyang-si, Gyeonggi-do 10223, Republic of Korea;1. Department of Earth, Ocean and Atmospheric Science, Florida State University, Tallahassee, FL, 32306, USA;2. School of Oceanography, University of Washington, Seattle, WA, 98195, USA;3. Geophysical Fluid Dynamics Institute, Florida State University, Tallahassee, FL, 32306, USA;4. Department of Earth, Ocean and Atmospheric Science, Florida State University, 1011 Academic Way, Tallahassee, FL, 32306-4520, USA;5. Department of Scientific Computing, Florida State University, Tallahassee, FL, 32306, USA;1. University of South Australia, Adelaide, Australia;2. Missouri University of Science and Technology, MO, USA |
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| Abstract: | This paper proposes a high accuracy numerical method to model oil spill trajectories using a particle-tracking algorithm. The Euler method, used to calculate oil trajectories, can give adequate solutions in most open ocean applications. However, this method may not predict accurate particle trajectories in certain highly non-uniform velocity fields near coastal zones or in river problems. Simple numerical experiments show that the Euler method may also introduce artificial numerical dispersion that could lead to overestimation of spill areas. This article proposes a fourth-order Runge–Kutta method with fourth-order velocity interpolation to calculate oil trajectories that minimize these problems. The algorithm is implemented in the OilTrack model to predict oil trajectories following the “Nissos Amorgos” oil spill accident that occurred in the Gulf of Venezuela in 1997. Despite lack of adequate field information, model results compare well with observations in the impacted area. |
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