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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.
Fuente: Marine Pollution Bulletin Volume 146, September 2019, Pages 962-976
Publisher: Elsevier Ltd
Publication date: 01/09/2019
No. of pages: 15
Publication type: Article
DOI: 10.1016/j.marpolbul.2019.07.053
ISSN: 0025-326X,1879-3363
Spanish project: TRA2017-89164-R
Publication Url: https://doi.org/10.1016/j.marpolbul.2019.07.053
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HELIOS CHIRI
ANA JULIA ABASCAL SANTILLANA
MARIA SONIA CASTANEDO BARCENA
RAUL MEDINA SANTAMARIA
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