Articles | Volume 12, issue 1
https://doi.org/10.5194/os-12-285-2016
https://doi.org/10.5194/os-12-285-2016
Research article
 | 
23 Feb 2016
Research article |  | 23 Feb 2016

Combining operational models and data into a dynamic vessel risk assessment tool for coastal regions

R. Fernandes, F. Braunschweig, F. Lourenço, and R. Neves

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Cited articles

Ascione Kenov, I., Campuzano, F., Franz, G., Fernandes, R., Viegas, C., Sobrinho, J., de Pablo, H., Amaral, A., Pinto, L., Mateus, M., and Neves, R.: Advances in modeling of water quality in estuaries, in: Remote Sensing and Modeling, edited by: Finkl, C. W., and Makowski, C., Springer International Publishing, 237–276, https://doi.org/10.1007/978-3-319-06326-3_10, 2014.
Bi, H. and Si, H.: Dynamic risk assessment of oil spill scenario for Three Gorges Reservoir in China based on numerical simulation, Safety Sci., 50, 1112–1118, https://doi.org/10.1016/j.ssci.2011.11.012, 2012.
Canu, D., Solidoro, C., Bandelj, V., Quattrocchi, G., Sorgente, R., Olita, A., Fazioli, L., and Cucco, A.: Assessment of oil slick hazard and risk at vulnerable coastal sites, Mar. Pollut. Bull., 94, 84–95, https://doi.org/10.1016/j.marpolbul.2015.03.006, 2015.
Carracedo, P., Torres-López, S., Barreiro, M., Montero, P., Balseiro, C. F., Penabad, E., Leitão, P. C., and Pérez-Munuzuri, V.: Improvement of pollutant drift forecast system applied to the prestige oil spills in Galicia Coast (NW of Spain): development of an operational system, Mar. Pollut. Bull., 53, 350–360, https://doi.org/10.1016/j.marpolbul.2005.11.014, 2006.
Castanedo, S., Abascal, A. J., Medina, R., Fernandez, F., Liste, M., and Olabarrieta, M.: Development of a GIS-based oil spill risk assessment system, OCEANS 2009 – EUROPE, Bremen, 1–6, https://doi.org/10.1109/OCEANSE.2009.5278283, 2009.
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Short summary
A combined methodology to estimate time and space variable shoreline risk levels from ships has been developed, integrating metocean forecasts and oil spill simulations with vessel tracking automatic identification systems (AIS) and coastal vulnerability indices. Results show the ability of the proposed methodology to estimate the risk properly sensitive to dynamic metocean conditions and oil transport behaviour, enhancing the maritime situational awareness and the decision support model.