气候变化领域集成服务门户(CCPortal): Mid-long term oil spill forecast based on logistic regression modelling of met-ocean forcings

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DOI	10.1016/j.marpolbul.2019.07.053
	Mid-long term oil spill forecast based on logistic regression modelling of met-ocean forcings
	Chiri H.; Abascal A.J.; Castanedo S.; Medina R.
发表日期	2019
ISSN	0025326X
起始页码	962
结束页码	976
卷号	146
英文摘要	Past major oil spill disasters, such as the Prestige or the Deepwater Horizon accidents, have shown that spilled oil may drift across the ocean for months before being controlled or reaching the coast. However, existing oil spill modelling systems can only provide short-term trajectory simulations, being limited by the typical met-ocean forecast time coverage. In this paper, we propose a methodology for mid-long term (1–6 months) probabilistic predictions of oil spill trajectories, based on a combination of data mining techniques, statistical pattern modelling and probabilistic Lagrangian simulations. Its main features are logistic regression modelling of wind and current patterns and a probabilistic trajectory map simulation. The proposed technique is applied to simulate the trajectory of drifting buoys deployed during the Prestige accident in the Bay of Biscay. The benefits of the proposed methodology with respect to existing oil spill statistical simulation techniques are analysed. © 2019 Elsevier Ltd
英文关键词	Bay of Biscay; Logistic regression; Mid-long term forecast; Oil spill modelling; Prestige accident
语种	英语
scopus关键词	Data mining; Forecasting; Logistic regression; Marine pollution; Trajectories; Bay of Biscay; Lagrangian simulation; Long-term forecast; Oil spill modelling; Probabilistic prediction; Regression modelling; Statistical simulation techniques; Trajectory simulation; Oil spills; accident; computer simulation; forecasting method; logistics; numerical model; oil spill; regression analysis; accident; article; Bay of Biscay; data mining; oil spill; prediction; sea; simulation; computer simulation; environmental monitoring; forecasting; oil spill; procedures; sea; statistical model; water flow; water pollutant; wind; Atlantic Ocean; Bay of Biscay; Computer Simulation; Environmental Monitoring; Forecasting; Logistic Models; Oceans and Seas; Petroleum Pollution; Water Movements; Water Pollutants, Chemical; Wind
来源期刊	Marine Pollution Bulletin
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/149653
作者单位	Environmental Hydraulics Institute, Universidad de Cantabria, Avda. Isabel Torres, 15, Parque Científico y Tecnológico de Cantabria, Santander, 39011, Spain; Departamento de Ciencias y Técnicas del Agua y del Medio Ambiente, Universidad de Cantabria, Santander, 39005, Spain
推荐引用方式 GB/T 7714	Chiri H.,Abascal A.J.,Castanedo S.,et al. Mid-long term oil spill forecast based on logistic regression modelling of met-ocean forcings[J],2019,146.
APA	Chiri H.,Abascal A.J.,Castanedo S.,&Medina R..(2019).Mid-long term oil spill forecast based on logistic regression modelling of met-ocean forcings.Marine Pollution Bulletin,146.
MLA	Chiri H.,et al."Mid-long term oil spill forecast based on logistic regression modelling of met-ocean forcings".Marine Pollution Bulletin 146(2019).