综合随机和典型情景模拟的海洋溢油事故污染危害预测评估研究

Predictive assessment of pollution and hazard resulting from marine oil spill accidents with stochastic and deterministic scenario simulations

  • 摘要: 通过分析随机和典型情景模拟法的优点,构建综合这两种方法的海洋溢油事故污染危害预测评估流程和主要评估指数。以渤海辽东湾为研究区域,选取一处海洋石油平台作为潜在溢油地点,7个国家级海洋保护区作为污染受体,开展假设的海底输油管道溢油事故情景算例演示。在经验证的潮流场模拟数据和2012~2013年预报风场数据基础上,利用随机情景模拟来预测全年统计条件下溢油污染概率、危害后果等指数的空间分布,分析评估研究区域的整体污染危害风险;通过典型情景模拟来预测不利风向条件下溢油漂移轨迹与扩散范围、到达时间等指数,分析评估溢油对具体敏感目标的污染风险。应用表明,随机和典型情景模拟的结合能够提供更为全面、客观的溢油污染预测评估结果,有利于提高风险评估结论的科学性和制定有效的风险管理对策。

     

    Abstract: Taking the advantages of stochastic and deterministic scenario simulation methods, a comprehensive approach for predictive assessment of potential pollution and hazard resulting from marine oil spill accidents was developed, both the flowchart and the main indicators of this approach were presented.The Liaodong bay in Bohai Sea was selected as study area to demonstrate the practicability of this approach.An offshore platform was selected as spill site, seven national marine protected areas (MPAs) in Liaodong bay were selected as receptors, and subsea pipeline oil spill was selected as hypothetical accident.Then, with support of current field data generated by hydrodynamic model and predicted wind field data of year 2012-2013, the stochastic simulations were carried out to predict the spatial distribution of the pollution probability and hazard indicators under annual statistical condition, and to assess the overall oil spill pollution and hazard risks of the study area.The deterministic scenario simulations were used to predict the oil spill trajectories, pollution areas, minimum arrival times of oil drifting to the seven MPAs under unfavorable wind conditions, and to assess the pollution risks for specific sensitive protection targets.The above studies show that, the comprehensive approach consisting of the two type of simulations can provide more overall and objective oil spill predictive assessment results, and help support the risk assessment conclusions and put forward reasonable countermeasures for risk management.

     

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