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Ocean Science An interactive open-access journal of the European Geosciences Union

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Ocean Sci., 12, 285-317, 2016
http://www.ocean-sci.net/12/285/2016/
doi:10.5194/os-12-285-2016
© Author(s) 2016. This work is distributed
under the Creative Commons Attribution 3.0 License.
Research article
23 Feb 2016
Combining operational models and data into a dynamic vessel risk assessment tool for coastal regions
R. Fernandes1,a, F. Braunschweig2, F. Lourenço2,b, and R. Neves1 1MARETEC – Marine Environment and Technology Centre, Instituto Superior Técnico, Universidade de Lisboa, Avenida Rovisco Pais, 1049-001, Lisbon, Portugal
2Action Modulers, Estrada Principal, 29, 2640-583, Mafra, Portugal
anow at: Action Modulers, Estrada Principal, 29, 2640-583, Mafra, Portugal
bnow at: Aubay Portugal, Av. República, 101 – 3 E, 1050-190 Lisbon, Portugal
Abstract. The technological evolution in terms of computational capacity, data acquisition systems, numerical modelling and operational oceanography is supplying opportunities for designing and building holistic approaches and complex tools for newer and more efficient management (planning, prevention and response) of coastal water pollution risk events.

A combined methodology to dynamically estimate time and space variable individual vessel accident risk levels and shoreline contamination risk from ships has been developed, integrating numerical metocean forecasts and oil spill simulations with vessel tracking automatic identification systems (AIS). The risk rating combines the likelihood of an oil spill occurring from a vessel navigating in a study area – the Portuguese continental shelf – with the assessed consequences to the shoreline. The spill likelihood is based on dynamic marine weather conditions and statistical information from previous accidents. The shoreline consequences reflect the virtual spilled oil amount reaching shoreline and its environmental and socio-economic vulnerabilities. The oil reaching shoreline is quantified with an oil spill fate and behaviour model running multiple virtual spills from vessels along time, or as an alternative, a correction factor based on vessel distance from coast. Shoreline risks can be computed in real time or from previously obtained data.

Results show the ability of the proposed methodology to estimate the risk properly sensitive to dynamic metocean conditions and to oil transport behaviour. The integration of meteo-oceanic + oil spill models with coastal vulnerability and AIS data in the quantification of risk enhances the maritime situational awareness and the decision support model, providing a more realistic approach in the assessment of shoreline impacts. The risk assessment from historical data can help finding typical risk patterns (“hot spots”) or developing sensitivity analysis to specific conditions, whereas real-time risk levels can be used in the prioritization of individual ships, geographical areas, strategic tug positioning and implementation of dynamic risk-based vessel traffic monitoring.


Citation: Fernandes, R., Braunschweig, F., Lourenço, F., and Neves, R.: Combining operational models and data into a dynamic vessel risk assessment tool for coastal regions, Ocean Sci., 12, 285-317, doi:10.5194/os-12-285-2016, 2016.
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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.
A combined methodology to estimate time and space variable shoreline risk levels from ships has...
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