NDLI: IT-OSRA: applying ensemble simulations to estimate the oil spill risk associated to operational and accidental oil spills

Content Provider	Springer Nature Link
Author	Sepp Neves, Antonio Augusto Pinardi, Nadia Martins, Flavio
Copyright Year	2016
Abstract	Oil Spill Risk Assessments (OSRAs) are widely employed to support decision making regarding oil spill risks. This article adapts the ISO-compliant OSRA framework developed by Sepp Neves et al. (J Environ Manag 159:158–168, 2015) to estimate risks in a complex scenario where uncertainties related to the meteo-oceanographic conditions, where and how a spill could happen exist and the risk computation methodology is not yet well established (ensemble oil spill modeling). The improved method was applied to the Algarve coast, Portugal. Over 50,000 simulations were performed in 2 ensemble experiments to estimate the risks due to operational and accidental spill scenarios associated with maritime traffic. The level of risk was found to be important for both types of scenarios, with significant seasonal variations due to the the currents and waves variability. Higher frequency variability in the meteo-oceanographic variables were also found to contribute to the level of risk. The ensemble results show that the distribution of oil concentrations found on the coast is not Gaussian, opening up new fields of research on how to deal with oil spill risks and related uncertainties.
Starting Page	939
Ending Page	954
Page Count	16
File Format	PDF
ISSN	16167341
Journal	Deutsche Hydrografische Zeitschrift
Volume Number	66
Issue Number	8
e-ISSN	16167228
Language	English
Publisher	Springer Berlin Heidelberg
Publisher Date	2016-06-08
Publisher Place	Berlin, Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	ISO 31000 Oil spill risk assessment Ensemble oil spill modeling Algarve MEDSLIK-II Oceanography Geophysics/Geodesy Atmospheric Sciences Fluid- and Aerodynamics Environmental Monitoring/Analysis
Content Type	Text
Resource Type	Article
Subject	Oceanography

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