Application of a Numerical Statistical Model to Estimate Potential Oil Spill Risk - Mathematical Modelling and Numerical Simulation of Oil Pollution Problems - page 136

72h, providing sufficient time for adopting protective measures. The sea surface
covered by oil slick more than 10mm distributes mainly around the spill site 10km
from north to south. The complex pattern extends along the local prevailing wind
direction.
Synthesizing each kind of oil spill affecting parameters and the environmental
sensitivity indices, the potential impact by oil spill of Panjin Port is obtained (Fig. 6.7 ).
It is evident that the environmental resource locations closest to the spill site have
the greatest risk. The potential risk of protected areas increased markedly, implying
that their fragile vulnerability to spilled oil.
6.5 Conclusions
The ongoing development of international marine traffic brings serious oil spill risk
to the water bodies adjacent to shipping zone. The regions of semi enclosed sea
area are particularly sensitive with regards to environmental impact from oil spill.
Run numerous times hypothetical spill accidents under varied realistic data fields
of environmental conditions, the numerical statistical model has been developed
to estimate the impact degree of the spills, including the probability of oil slick
occurrence on water surface, mean average slick thickness on a given water surface,
and minimum oil slick arrival time to a specified region. The sensitivity of different
types of marine function zone taken into consideration, the comparative risk map is
acquired which appears to be more effective for assessment of the ocean sensitivity
around the potential hazard. An application is presented to generate the Panjin Port
oil spill riskmap by running the model. The results are quite vital for decision support
providing regulating agencies with a guide for combating oil spills.
Nevertheless, further study is necessary for model improvements. This model
is designed for use as a hazard-based assessment, so the possibility of oil spills
occurring is not taken into consideration adequately in the analysis. In future work,
the probability function of spill location and size based on both location sea state and
human activities should be taken into account to reflect the nature of oil spill risk.
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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