Mid-long term oil spill forecast based on logistic regression modelling of met-ocean forcings.

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ID: 13941
2019
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Ranked #67 of 169 articles by views in Marine pollution bulletin

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Abstract
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.
Reference Key
chiri2019midlongmarine Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Chiri, Helios;Abascal, Ana Julia;Castanedo, Sonia;Medina, Raul;
Journal Marine pollution bulletin
Year 2019
DOI
S0025-326X(19)30591-0
URL
Keywords Keywords not found

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