Abstract
Both deterministic and probabilistic strategies are employed in numerical oil spill model to estimate potential oil spill risk. The deterministic model simulates transport and weathering processes by means of a particle tracking method. While a Monte Carlo stochastic simulation approach is run for multiple scenarios, spill size, oil type, and environmental conditions (meteorological and hydrological data) combinations, to characterize the consequences of spills for a specified potential spill location. The statistically-defined oil spill map does not demonstrate the probabilities of oil-slick presence for each grid area, but also provide the information of the shortest arrival time which is quite vital for oil contingency plan.
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Acknowledgments
The work described here would not have been possible without the efforts of my colleagues and students, including Li Zhang, Hui Liu, Yanni Hao, Yan Zou and Qi Guo. This work is sponsored by the Ministry of Transport of China under No. 2013 329 225 240, the Fundamental Research Funds for the Central Universities (2012QN059) and National Natural Science Foundation of China (No. 41206095, No. 51409037).
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Guo, W., Xu, T. (2015). Application of a Numerical Statistical Model to Estimate Potential Oil Spill Risk. In: Ehrhardt, M. (eds) Mathematical Modelling and Numerical Simulation of Oil Pollution Problems. The Reacting Atmosphere, vol 2. Springer, Cham. https://doi.org/10.1007/978-3-319-16459-5_6
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DOI: https://doi.org/10.1007/978-3-319-16459-5_6
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