Satellite observations and modeling of oil spill trajectories in the Bohai Sea

Xu, Qing; Li, Xiaofeng; Wei, Yongliang; Tang, Zeyan; Cheng, Yongcun; Pichel, William G.

doi:10.1016/j.marpolbul.2013.03.028

Cited by 88 publications

(37 citation statements)

References 18 publications

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“…With the wind speed decreasing and direction changing, as well as the reciprocating flow influence, some simulated oil particles drift towards the west or north, and the overall distribution also became relatively scattered (from 15 to 19 June). This is consistent with the publication by Xu et al [4].…”

Section: Penglai Results Validationsupporting

confidence: 94%

“…For example, the Deepwater Horizon oil spill, which occurred on 20 April 2010, killed 11 people and presented an unprecedented threat to Gulf of Mexico marine resources [2]; the Dalian Xingang oil spill incident, which happened on 16 July 2010, spread an estimated 1500 metric tons of crude oil into the Yellow Sea and stretched over 430 km 2 of ocean, with 12 km 2 severely affected [3]; on 4 and 17 June 2011, two separate oil spill accidents occurred at platforms B and C of the Bohai Penglai 19-3 oilfield, and they caused 5500 km 2 of seawater pollution, roughly equivalent to 7% of the Bohai Sea area; and in the same year, on 12 July, the Liaoning Suizhong oil spill incident spread an estimated 0.1 to 0.15 cubic meters of crude oil into the Bohai Sea and stretched over 1 km 2 of ocean, according to the China State Oceanic Administration (SOA) [4]. Remote sensing technology plays an important role in monitoring marine pollution caused by oil spills.…”

Section: Introductionmentioning

confidence: 99%

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A Dynamic Remote Sensing Data-Driven Approach for Oil Spill Simulation in the Sea

et al. 2015

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In view of the fact that oil spill remote sensing could only generate the oil slick information at a specific time and that traditional oil spill simulation models were not designed to deal with dynamic conditions, a dynamic data-driven application system (DDDAS) was introduced. The DDDAS entails both the ability to incorporate additional data into an executing application and, in reverse, the ability of applications to dynamically steer the measurement process. Based on the DDDAS, combing a remote sensor system that detects oil spills with a numerical simulation, an integrated data processing, analysis, forecasting and emergency response system was established. Once an oil spill accident occurs, the DDDAS-based oil spill model receives information about the oil slick extracted from the dynamic remote sensor data in the simulation. Through comparison, information fusion and feedback updates, continuous and more precise oil spill simulation results can be obtained. Then, the simulation results can provide help for disaster control and clean-up. The Penglai, Xingang and Suizhong oil spill results showed our simulation model could increase the prediction accuracy and reduce the error caused by empirical parameters in existing simulation systems. Therefore, the DDDAS-based detection and simulation system can effectively improve oil spill simulation and diffusion forecasting, as well as provide decision-making information and technical support for emergency responses to oil spills.Remote Sens. 2015, 7 7106

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Section: Penglai Results Validationsupporting

confidence: 94%

Section: Introductionmentioning

confidence: 99%

A Dynamic Remote Sensing Data-Driven Approach for Oil Spill Simulation in the Sea

et al. 2015

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“…Operational Modeling Environment (GNOME) (see for instance [3,4,5] for their implementation in different oil spill events). Our analysis utilizes fundamental ideas from dynamical systems theory which search for sharper insights.…”

mentioning

confidence: 99%

A dynamical systems perspective for a real-time response to a marine oil spill

García-Garrido

Ramos

Mancho

et al. 2016

Marine Pollution Bulletin

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General rightsThis document is made available in accordance with publisher policies. Please cite only the published version using the reference above. AbstractThis paper discusses the combined use of tools from dynamical systems theoryand remote sensing techniques and shows how they are effective instruments which may greatly contribute to the decision making protocols of the emergency services for the real-time management of oil spills. This work presents the successful interplay of these techniques for a recent situation, the sinking of the Oleg Naydenov fishing ship that took place in Spain, close to the Canary Islands, in April 2015.

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“…Through investing in the software research and development, the monitoring system of aviation, navigation, radar and satellite remote sensing detection should be set up in all sea areas to achieve stereoscopic monitoring in all-time and all-weather. In addition, the scope and precision of prediction models for oil spill should be improved to allow scientific and timely decisions on oil spill emergency (Xu et al, 2013).…”

Section: Randd Projectsmentioning

confidence: 99%