Influence of sea surface waves on numerical modeling of an oil spill: Revisit of symphony wheel accident

The greatest purpose of this study is to analyze the importance of surface waves on the hindcasting of the oil spill through the Symphony wheel accident in the Qingdao coastal waters. During the accident period, a total of four synthetic aperture radar (SAR) images by Gaofen-3 (GF-3) were acquired from 2 to 19 May 2021. The hindcasting of two sea surface dynamics, namely currents and waves, is carried out using a coupled marine numeric model. This model, known as the finite-volume community ocean model-simulating waves nearshore (FVCOM-SWAVE), employs a triangular grid. Simulated significant wave height (SWH) is validated against remotely sensed product by the Haiyang-2B (HY-2B) altimeter on April 2021 yields a root mean square error (RMSE) of 0.38, a correlation coefficient (COR) of 0.78, and a scatter index (SI) of 0.34. Subsequently, Stokes drift estimated by waves are included to hindcasting oil spills using the oil particle-tracing method. The bias of the spatial coverage (SAR minus simulations) of an algorithm called the constant false alarm rate (CFAR) is −73.92 km2 with Stokes drift, which is significantly less than the 55.45 km2 coverage without Stokes drift. Moreover, compared with model-simulated oil spills, the bias of the geographic location at the center point with Stokes drift is 8.18 km, which is less than the 12.95 km bias without Stokes drift. These results demonstrate that Stokes drift needs to be included in the prediction of oil spills.

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Publication Details

Journal
Journal of Sea Research
Published
2024-08-13
DOI
https://doi.org/10.1016/j.seares.2024.102529
Citations
6
Primary Topic
Oil Spill Detection and Mitigation
Type
article
Field-Weighted Citation Impact
0.80

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article

Influence of sea surface waves on numerical modeling of an oil spill: Revisit of symphony wheel accident

Weizeng Shao, Wei Shen, Huan Li, Jiale Chen et al.
6 citations
Journal of Sea Research
Oil Spill Detection and Mitigation
0.80
article

Influence of sea surface waves on numerical modeling of an oil spill: Revisit of symphony wheel accident

Weizeng Shao, Wei Shen, Huan Li, Jiale Chen, Yiqiu Yang, Song Hu, Xingwei Jiang
article en
6 citations

Abstract

The greatest purpose of this study is to analyze the importance of surface waves on the hindcasting of the oil spill through the Symphony wheel accident in the Qingdao coastal waters. During the accident period, a total of four synthetic aperture radar (SAR) images by Gaofen-3 (GF-3) were acquired from 2 to 19 May 2021. The hindcasting of two sea surface dynamics, namely currents and waves, is carried out using a coupled marine numeric model. This model, known as the finite-volume community ocean model-simulating waves nearshore (FVCOM-SWAVE), employs a triangular grid. Simulated significant wave height (SWH) is validated against remotely sensed product by the Haiyang-2B (HY-2B) altimeter on April 2021 yields a root mean square error (RMSE) of 0.38, a correlation coefficient (COR) of 0.78, and a scatter index (SI) of 0.34. Subsequently, Stokes drift estimated by waves are included to hindcasting oil spills using the oil particle-tracing method. The bias of the spatial coverage (SAR minus simulations) of an algorithm called the constant false alarm rate (CFAR) is −73.92 km2 with Stokes drift, which is significantly less than the 55.45 km2 coverage without Stokes drift. Moreover, compared with model-simulated oil spills, the bias of the geographic location at the center point with Stokes drift is 8.18 km, which is less than the 12.95 km bias without Stokes drift. These results demonstrate that Stokes drift needs to be included in the prediction of oil spills.

Journal of Sea ResearchVol. 201
Ministry of Natural Resources (CN), China Waterborne Transport Research Institute (CN), Shandong Marine Resource and Environment Research Institute (CN), Ministry of Transport (CN), National Satellite Ocean Application Service (CN), National Marine Environmental Forecasting Center (CN), National Marine Data and Information Service, Shanghai Ocean University (CN)
National Natural Science Foundation of China
Life below water
Openalex Percentile: Top 35%
Oil Spill Detection and Mitigation
0.80
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