Revisit of a Case Study of Spilled Oil Slicks Caused by the Sanchi Accident (2018) in the East China Sea

Revisit of a Case Study of Spilled Oil Slicks Caused by the Sanchi Accident (2018) in the East China Sea

Journal of Marine Science and Engineering Article Revisit of a Case Study of Spilled Oil Slicks Caused by the Sanchi Accident (2018) in the East China Sea Zhehao Yang 1, Weizeng Shao 2,3,* , Yuyi Hu 1, Qiyan Ji 1,*, Huan Li 4 and Wei Zhou 5 1 Marine Science and Technology College, Zhejiang Ocean University, Zhoushan 316022, China; [email protected] (Z.Y.); [email protected] (Y.H.) 2 College of Marine Sciences, Shanghai Ocean University, Shanghai 201306, China 3 National Satellite Ocean Application Service, Beijing 100081, China 4 National Marine Data and Information Service, Tianjin 300171, China; [email protected] 5 South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou 510301, China; [email protected] * Correspondence: [email protected] (Q.J.); [email protected] (W.S.); Tel.: +86-0580-2550-753 (W.S.) Abstract: Marine oil spills occur suddenly and pose a serious threat to ecosystems in coastal waters. Oil spills continuously affect the ocean environment for years. In this study, the oil spill caused by the accident of the Sanchi ship (2018) in the East China Sea was hindcast simulated using the oil particle-tracing method. Sea-surface winds from the European Centre for Medium-Range Weather Forecasts (ECMWF), currents simulated from the Finite-Volume Community Ocean Model (FVCOM), and waves simulated from the Simulating WAves Nearshore (SWAN) were employed as background marine dynamics fields. In particular, the oil spill simulation was compared with the detection from Chinese Gaofen-3 (GF-3) synthetic aperture radar (SAR) images. The validation of the SWAN- simulated significant wave height (SWH) against measurements from the Jason-2 altimeter showed Citation: Yang, Z.; Shao, W.; Hu, Y.; a 0.58 m root mean square error (RMSE) with a 0.93 correlation (COR). Further, the sea-surface Ji, Q.; Li, H.; Zhou, W. Revisit of a current was compared with that from the National Centers for Environmental Prediction (NCEP) Case Study of Spilled Oil Slicks Climate Forecast System Version 2 (CFSv2), yielding a 0.08 m/s RMSE and a 0.71 COR. Under Caused by the Sanchi Accident (2018) these circumstances, we think the model-simulated sea-surface currents and waves are reliable in the East China Sea. J. Mar. Sci. Eng. for this work. A hindcast simulation of the tracks of oil slicks spilled from the Sanchi shipwreck 2021, 9, 279. https://doi.org/ was conducted during the period of 14–17 January 2018. It was found that the general track of 10.3390/jmse9030279 the simulated oil slicks was consistent with the observations from the collected GF-3 SAR images. Academic Editor: Merv Fingas However, the details from the GF-3 SAR images were more obvious. The spatial coverage of oil slicks between the SAR-detected and simulated results was about 1 km2. In summary, we conclude that Received: 31 January 2021 combining numerical simulation and SAR remote sensing is a promising technique for real-time oil Accepted: 26 February 2021 spill monitoring and the prediction of oil spreading. Published: 4 March 2021 Keywords: oil slick; Sanchi accident; Gaofen-3; synthetic aperture radar Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affil- iations. 1. Introduction Marine oil spills are serious marine disasters that occur in marine ports, docks, and oil drilling platforms. Oil spills cause damage to the marine ecological environment and are a direct threat to public safety. Moreover, oil slicks drift with the movements of ocean Copyright: © 2021 by the authors. circulations and ocean waves, causing oil pollution to persist in the ocean for a long time. Licensee MDPI, Basel, Switzerland. In recent years, due to rapid economic development in China, the Chinese demand for This article is an open access article crude oil and refined products is increasing year by year, leading to a high potential risk distributed under the terms and of marine oil spills. On 16 July 2010, an oil spill occurred in Dalian Xingang Port, leading conditions of the Creative Commons to more than 1500 tons of oil spilling into the sea. The oil spill seriously affected the local Attribution (CC BY) license (https:// fisheries, aquaculture, tourism, and shipping industry and caused huge economic losses creativecommons.org/licenses/by/ to Dalian City. Oil slicks spilled from ships account for the major proportion of oil spill 4.0/). J. Mar. Sci. Eng. 2021, 9, 279. https://doi.org/10.3390/jmse9030279 https://www.mdpi.com/journal/jmse J. Mar. Sci. Eng. 2021, 9, 279 2 of 15 accidents. For example, the pollution in surrounding areas for up to 180 days and more than 50% of bulk oil particles remaining in the ocean after the Sanchi ship accident (2018) in the East China Sea were due to oil slicks [1]. Owing to the frequent occurrence of major oil spill accidents, the development of oil spill monitoring techniques has progressed in the last few decades. It is necessary to promote emergency responses to marine oil spills in China and improve oil slick simulation techniques. Most studies involving spilled oil slick simulations have focused on the development of numerical models [2–5]. Several oil slick prediction models have been developed during the past 20 years and the state of the art in oil slick modeling has been reviewed by various studies [6–8], e.g., Monte Carlo stochastic simulation, Lagrangian transport, and the oil particle-tracing method. Generally, oil transportation is affected by marine environmental dynamic factors as well as the physical and chemical properties of oil, such as weathering [9], evaporation, and emulsification [10]. Compared with the previous algorithms for solving the convection diffusion equation, the oil particle-tracing method can not only solve the deformation and breaking process of oil spill under the influence of marine dynamic environment, but also accurately forecast the expansion process of oil film and the obvious stretch of oil film shape in the wind direction. Therefore, the most widely used oil spill model is based on the particle-tracing method, which simulates the drift and diffusion process of oil slicks in water by dispersing oil into a large number of small oil droplets [11,12]. In principle, the motion of oil particles is expressed by the Lagrange tracing method, and the implementation of this method could directly resolve the physical movement of oil slicks. The advantage of the oil particle-tracing method is that the shape changes and breaking process of oil slicks under the action of complex ocean environments is described while effectively eliminating the numerical divergence problem. However, prior knowledge of the oil particle-tracing method relies on sea-surface dynamics. It is well known that marine dynamic factors, such as sea-surface winds [13], currents [14], and waves [15–17], can be numerically simulated by high-resolution meteorological or hydrodynamic models. With the development of remote-sensing technology, oceanic characteristics such as sea-surface temperature [18], chlorophyll-a [19], and sediment [20] content can be impres- sively imaged through optical satellites, including advanced very high-resolution radiome- ter (AVHRR) [21] and moderate-resolution imaging spectro-radiometer (MODIS) [22]. Satel- lites carrying microwave sensors, such as altimeters [23], scatterometers [24], and synthetic aperture radar (SAR) [25,26], can quantitatively detect information on ocean dynamics under all types of weather and in real time. In particular, it has been proven that SAR is greatly useful in oil spill monitoring [27–31], especially polarmetric SAR (PolSAR) [32], as well as the X-band marine radar [33] and the GNSS-R technique [34]. As for co-polarized SAR, the constant false alarm rate (CFAR) is a well-known method for oil spill detec- tion [35]; the details are described in the AppendixA. Utilizing amplitude coherence and the co-polarized phase difference (CPD) standard deviation to detect the spilled oil slicks in dual-polarimetric TerraSAR-X imagery is proposed in [36]. After analyzing the backscat- tering differences between oil slicks and sea clutter, the feature pedestal height is used to observe oil slicks in quad-polarimetric SAR imagery [37]. Different from these two works, in [38], an advanced method for realizing oil spill detection from the compact polarimetric SAR image was recently developed. It is noteworthy that the accuracy of SAR detection for oil slicks relies on prior information about background dynamics to remove false alarms. The efficiency of oil spill modeling based on the particle-tracing method for the case of the Dalian accident in July 2010 has been confirmed [39]. In recent studies of the Sanchi Event (2018), two individual methods, optical/microwave satellite and numerical modeling, have been widely employed [1,40]. In recent decades, these methods have been improved significantly. Therefore, the present work focused on the real-time monitoring and prediction of oil spills using SAR and numerical models, which are sound and can be practically applied for oil spills. It has also been revealed that the prediction accuracy of oil spill transportation depends on simulations from meteorological or hydrodynamic J. Mar. Sci. Eng. 2021, 9, x FOR PEER REVIEW 3 of 15 J. Mar. Sci. Eng. 2021, 9, 279 3 of 15 practically applied for oil spills. It has also been revealed that the prediction accuracy of oil spill transportation depends on simulations from meteorological or hydrodynamic models. As for driving the oil spill model, the sea-surface wind, current, and wave fields models. As for driving the oil spill model, the sea-surface wind, current, and wave fields are are necessary. The oil particle drift mainly depends on sea-surface winds, tides, and cir- necessary. The oil particle drift mainly depends on sea-surface winds, tides, and circulation culation currents [41].

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