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溢油事故发生后, 油膜的漂移扩散会对周围水域和环境敏感目标造成污染。研究溢油事故后油膜漂移扩散, 可为溢油事故的处理提供理论指导。本文应用河口海岸三维水动力模式ECOM-si(semi-implicit estuarine, costal and ocean model), 耦合溢油漂移扩散模块, 模拟和分析长江口宝钢码头发生溢油事故后油膜的漂移扩散, 以及对环境敏感保护目标的影响。基于长江口崇明东滩气象站实测风速风向资料, 给出影响溢油漂移的主导风和不利风向。在冬季多年平均1月径流量11700m³·s-1、主导风、3个不利风和潮汐作用下, 数值模拟并详细给出了宝钢码头溢油事故发生后油膜的平面分布、油膜到达和离开4个水库取水口和饮用水水源保护区以及其他环境敏感保护区的时间、持续影响时间和最大油膜厚度。长江口宝钢码头溢油事故发生后, 油膜随涨落潮流作上下游来回振荡, 径流使油膜向海输运, 风使油膜朝风向方向漂移。在主导风北风5.6m³·s-1风速下, 油膜沿长江口南岸向下游漂移扩散, 小部分进入北槽南侧。在不利风向东南风4.0m³·s-1风速下, 油膜西北方向漂移, 聚集于南支北岸, 受径流作用沿南支和北港的中北侧向下游输运。在不利风向西北风4.8m³·s-1风速下, 西北风减轻了溢油事故点上游和北港、崇明东滩外侧敏感目标的影响, 加重了南港和南槽的环境敏感保护目标的影响。在不利风向西南风3.2m³·s-1风速下, 大部分油膜在北港中北侧向下游漂移扩散, 小部分油膜聚集在北槽的中北侧。西南风减轻了溢油事故点上游和下游南港、南槽环境敏感目标受到的影响, 加重了对北港和崇明东滩外侧敏感目标的影响。不同风向作用下油膜的分布和对环境敏感保护目标影响显著不同, 风在油膜漂移扩散中起着十分重要的作用。 相似文献
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乐清湾北港区溢油轨迹的分形模拟 总被引:1,自引:0,他引:1
在验证良好的区域二维潮流数学模型基础上,建立采用“油粒子”方法的溢油模型,包含油膜的拓展、漂移和扩
散等过程。模型采用四阶龙格库塔法求解粒子的平流过程,采用分数布朗运动产生non-Fickian 扩散来模拟油膜拓延。在
此基础上,对乐清湾北港区溢油风险进行预测模拟,分析在潮流和风不同作用情况下油膜的漂移轨迹和对周围敏感区的影
响。 相似文献
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利用MIKE21水动力模型对徐圩港区附近海域进行潮流数值模拟,并利用实测资料对模型计算的潮位、流速及流向进行验证。验证结果显示:数模结果与实测值吻合较好。该潮流数学模型可以反映研究海域水动力特性,并作为溢油模块的水动力基础数据。基于欧拉-拉格朗日"油粒子"理论考虑油膜运动过程中扩散、蒸发、乳化等过程,建立了徐圩港区邻近海域二维溢油扩散模型,模拟不同潮时情况下发生溢油,考虑不同风况(夏季常风向、冬季常风向和最不利风向),分析不同情况下的溢油油膜漂移路径、漂移路程及扫海面积。结果表明:72 h内油膜最大扫海面积及漂移路程均出现在落潮期最不利风时溢油,分别为28.2 km2和25.8 km。在夏季常风和最不利风的落潮期发生溢油,油膜会经过口门飘向西北侧海域,对该区域生态环境会造成一定影响。 相似文献
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本文采用油粒子模式,在模拟潮流的基础上分别预测了青岛港溢油油膜在静风,冬、夏主频风和不利风向4种情况下的动态漂移过程.通过对油膜运动漂移过程的模拟,具体分析了溢油发生后对周边的敏感目标产生的影响,从而为应急计划的制定提供一定的导向作用. 相似文献
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蓬莱19-3 油田事故溢油数值模拟 总被引:2,自引:0,他引:2
利用FVCOM(Finite-volume coastal ocean numerical model)数值模型和MM5风场预报模式,在对渤海海域水动力场进行数值模拟的基础上,基于"油粒子"的欧拉-拉格朗日跟踪法和随机走动原理,并考虑风对溢油油膜漂移扩散的直接作用,建立了海洋溢油油膜漂移轨迹和扩散的数值预测模型。利用建立的模型对2011年6月蓬莱19-3油田事故溢油进行了数值模拟,模拟结果与RADARSAT卫星遥感监测数据相吻合。研究结果表明:在渤海中部地区夏季事故溢油模拟预测中,风漂移因子取0.024最为合理,模型可用于渤海蓬莱19-3油田附近事故溢油轨迹和扩散的快速预报,从而为该区域的溢油事故应急响应提供科学依据。 相似文献
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本文应用水动力模型及溢油模块对代表性风况下钦州湾金鼓江的溢油事故进行情景模拟,且水动力模型结果与实测潮位和实测潮流吻合较好。低潮时发生溢油,不同风况下油粒子在5.5-8.5h后漂到金鼓江上游养殖区。高潮时发生溢油,油粒子在不同风况下漂移轨迹差别较大,例如无风时油粒子在钦州湾颈和三墩外海附近往复运动,而南风3.3m/s工况下油粒子将最终影响大榄坪港区的东南端。另外,高风速下不利风向会缩减油膜抵达敏感区的时间,同时风速越大,蒸发越快。因此风场对溢油模型有重要意义,今后将在精细化WRF模型基础上优化溢油模型并构建溢油决策系统,为地方经济发展和海洋环境保护提供科技支撑。 相似文献
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NOAA的GNOME溢油模型在湄洲湾的应用 总被引:2,自引:0,他引:2
在湄洲湾试用GNOME溢油模型模拟溢油扩散.先用EFDC建立潮流场,并选用主导风形成常风场,一并输入GNOME建立起溢油模型,模拟涨、落潮过程叠加不同风况下敏感海域的溢油扩散.模拟结果:初始溢油量为100t,扩散到第6小时,8种不同条件下挥发油量都为7.7t,附岸和漂浮油量和为92.3t,其中漂浮油量为6.4~92.0t,相应附岸油量为85.9~0.3t;溢油扩散最大范围为1.3~30.0km。,90%置信区间为2.0~56.0km。,最大距离为1.2~14.6km;与前人模拟溢油扩散结果相比基本一致.经分析,溢油扩散主要受3个方面影响:(1)岸线走向:当岸线靠近油膜漂移的路线时,大量油膜附着在岸上,扩散范围较小;(2)风况与流场关系:如果两者方向一致,油膜会扩散较远;(3)风区长度:风区越长,油膜扩散范围越大.总之,建立GNOME溢油模型较好地模拟了溢油扩散趋势,对溢油应急响应具有参考作用. 相似文献
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In this study, we applied the edge-detection method of oil-spill monitoring to extract oil-spill features observed by the ENVISAT Advanced Synthetic Aperture Radar (ASAR) images over the coastal waters of Hong Kong and vicinity in northern South China Sea. Two examples in 2007 and 2008 over the coastal waters of the study area show that oil spills can be successfully detected by ASAR images at wind speeds around 4~ 6 m/s independent of wind direction. The study also shows that it could be helpful for evaluating the potential impacts of oil spills on the coastal environment in Hong Kong and vicinity. 相似文献
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基于MIKE SA溢油模块,以燃料油为油种,建立了厦门西港海域溢油模型,模拟静风、主导风向(东北东风)和不利风向(西南风)3种风场条件下,一个潮周期内涨急、高潮、落急和低潮4个时段发生10 t溢油后油膜的漂移路径和影响范围.结果显示,发生在厦门西港海域的溢油在海面的漂移过程主要受潮流和风的影响,其中潮流起着主导作用.不同风向条件下,24 h内油膜的影响范围不同,静风条件下溢油浓度超一类(或二类,≥0.05 mg/dm3)、超三类(≥0.30 mg/dm3)和超四类(≥0.50 mg/dm3)的总影响面积分别为31.33、19.63和11.74 km2;主导风向条件下溢油浓度超一类(或二类)、超三类和超四类的总影响面积分别为99.62、69.01和8.99 km2;不利风向溢油浓度超一类(或二类)、超三类和超四类的总影响面积分别为8.38、5.05和2.10 km2.该预测结果可给出溢油事故发生后的影响范围、影响程度和影响敏感目标的时间,可为溢油事故应急决策的制定及溢油损害评估提供科学决策和支持,提升厦门海域环境风险管理应急能力建设. 相似文献
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Maria Gstgifvars Hannu Lauri Annakaisa Sarkanen Kai Myrberg Oleg Andrejev Cecilia Ambjrn 《Estuarine, Coastal and Shelf Science》2006,70(4):567
The Gulf of Finland is an elongated estuary located in the north-eastern extremity of the Baltic Sea. This semi-enclosed sea-area is subject to heavy sea traffic, and is one of the main risk areas for oil accidents in the Baltic. The continuous development and validation of operational particle drift and oil-spill forecasting systems is thus seen to be essential for this sea-area.Here, the results of a three-day drift experiment in May 2003 are discussed. The field studies were performed using GPS-positioned surface floating buoys. The aim of this paper is to evaluate how well models can reproduce the drift of these buoys. Model simulations, both in forecast and hindcast modes, were carried out by three different 3D hydrodynamic models, the results of which are evaluated by comparing the calculated drifts with observations. These models were forced by HIRLAM (High Resolution Limited Area Model) and ECMWF (European Centre for Medium-Range Weather Forecasts) meteorological forecast fields.The simulated drift of the buoys showed a good agreement with observations even when, during the study period, a rapidly-changing wind situation was observed to affect the investigation area; in this situation the winds turned about 100 degrees in half an hour. In such a case it is a very complicated task to forecast the drifters' routes: there is a need to regularly update the meteorological forcing fields and to use these regularly-updated fields throughout the simulations. It is furthermore recommended that forecasts should be made using several circulation models and several meteorological forecasts, in order to get an overview of the accuracy of the forecasted drifts and related differences in between the forecasts. 相似文献
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A probabilistic description of the wind over Liverpool Bay with application to oil spill simulations 总被引:1,自引:0,他引:1
A.J. Elliott 《Estuarine, Coastal and Shelf Science》2004,61(4):569-581
Surface winds from the UK Meteorological Office mesoscale (12 km grid) atmospheric model have been used to define the wind at a location in Liverpool Bay during 1997–2001. Winds from the SW (centred on 240°) with a speed of about 10 m/s (20 knots) were the most frequent, although weaker winds from the SE were also common. The wind spectra were red in character and showed no evidence for a peak at the synoptic (2–5 day) time scale; however, a zero-up-crossing analysis suggested a dominant periodicity at 3.1 days, and at this time scale the winds were spatially coherent over a distance of 300 km. A wind direction transition matrix was derived to quantify the probability with which the wind changed between two specified directions. This information was then used with an estimate of the mean duration of a wind event to compute a stochastic wind time series that contained a similar energy level, periodicity, and direction variability to the archived wind data. The archived and stochastic winds were then used in 1000 oil spill contingency simulations during which estimates of the mean and minimum times taken for oil to reach the coastline, and the percentage of the oil impacting selected sites were computed. The stochastic winds provided more realistic results, when compared against those derived using the wind archive, than those obtained using a wind rose representation of the winds. The derivation and use of a stochastic wind time series has application to a range of modelling studies. 相似文献