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

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.

Otras publicaciones de la misma revista o congreso con autores/as de la Universidad de Cantabria

 Fuente: Marine Pollution Bulletin Volume 146, September 2019, Pages 962-976

Editorial: Elsevier Ltd

 Fecha de publicación: 01/09/2019

Nº de páginas: 15

Tipo de publicación: Artículo de Revista

DOI: 10.1016/j.marpolbul.2019.07.053

ISSN: 0025-326X,1879-3363

Proyecto español: TRA2017-89164-R

Url de la publicación: https://doi.org/10.1016/j.marpolbul.2019.07.053