Modelling the uncertainties in predicting produced water concentrations in the North Sea

IF 4.6 2区 环境科学与生态学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Environmental Modelling & Software Pub Date : 2001-11-01 DOI:10.1016/S1364-8152(01)00036-6
A.M Riddle , E.M Beling , R.J Murray-Smith
{"title":"Modelling the uncertainties in predicting produced water concentrations in the North Sea","authors":"A.M Riddle ,&nbsp;E.M Beling ,&nbsp;R.J Murray-Smith","doi":"10.1016/S1364-8152(01)00036-6","DOIUrl":null,"url":null,"abstract":"<div><div><span>A random walk model has been used to compute concentration distributions of dispersed oil in the North Sea resulting from produced water discharges. This formed part of a joint<span> study commissioned by Statoil, OLF and BP International with modelling being undertaken by SINTEF and the Brixham Environmental Laboratory. The model has been set up using predicted tidal currents<span><span> from the Norwegian Meteorological Office 20-km grid three-dimensional Continental Shelf model for the year 1990. Climatology data from the North Sea have been used to define the variation of the </span>thermocline depth at monthly intervals over the year, and wind data from the East Shetland Basin have been used to compute the vertical mixing rates. Peak concentrations of dispersed oil were predicted to be approximately 3 μg l</span></span></span><sup>−1</sup><span> in the East Shetland Basin, assuming no biodegradation; this value is consistent with the measurements of Stagg et al. (In: Reed, M., Johnsen, S. (Eds), Produced Water 2, Environmental Issues and Mitigation Technologies, Plenum Press, 1996), where the data were collected in the immediate vicinity of the discharges and the effects of degradation would be expected to be negligible.</span></div><div>A matrix of model runs was undertaken with different parameter values for the degradation of dispersed oil, horizontal and vertical mixing, and the mixing across the thermocline. These results were used to estimate the sensitivity of the model and the uncertainty in the predicted concentration fields. The results indicate that for the areas of high concentration, a band approximately 150-km wide stretching up the centre of the North Sea, parameterisation of the vertical mixing is most important for predicting the concentration levels. For areas more remote from the discharges and closer to the land masses, the degradation rate of material has most effect on predicted concentrations.</div></div>","PeriodicalId":310,"journal":{"name":"Environmental Modelling & Software","volume":"16 7","pages":"Pages 659-668"},"PeriodicalIF":4.6000,"publicationDate":"2001-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Environmental Modelling & Software","FirstCategoryId":"93","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1364815201000366","RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0

Abstract

A random walk model has been used to compute concentration distributions of dispersed oil in the North Sea resulting from produced water discharges. This formed part of a joint study commissioned by Statoil, OLF and BP International with modelling being undertaken by SINTEF and the Brixham Environmental Laboratory. The model has been set up using predicted tidal currents from the Norwegian Meteorological Office 20-km grid three-dimensional Continental Shelf model for the year 1990. Climatology data from the North Sea have been used to define the variation of the thermocline depth at monthly intervals over the year, and wind data from the East Shetland Basin have been used to compute the vertical mixing rates. Peak concentrations of dispersed oil were predicted to be approximately 3 μg l−1 in the East Shetland Basin, assuming no biodegradation; this value is consistent with the measurements of Stagg et al. (In: Reed, M., Johnsen, S. (Eds), Produced Water 2, Environmental Issues and Mitigation Technologies, Plenum Press, 1996), where the data were collected in the immediate vicinity of the discharges and the effects of degradation would be expected to be negligible.
A matrix of model runs was undertaken with different parameter values for the degradation of dispersed oil, horizontal and vertical mixing, and the mixing across the thermocline. These results were used to estimate the sensitivity of the model and the uncertainty in the predicted concentration fields. The results indicate that for the areas of high concentration, a band approximately 150-km wide stretching up the centre of the North Sea, parameterisation of the vertical mixing is most important for predicting the concentration levels. For areas more remote from the discharges and closer to the land masses, the degradation rate of material has most effect on predicted concentrations.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
模拟预测北海采出水浓度的不确定性
采用随机游走模型计算了北海采出水排放引起的分散油浓度分布。这是由挪威国家石油公司、OLF和BP国际公司委托进行的联合研究的一部分,由SINTEF和Brixham环境实验室进行建模。该模型是根据挪威气象局1990年20公里网格三维大陆架模型预测的潮流建立的。来自北海的气候学数据被用来确定一年中每月间隔的温跃层深度的变化,来自东设得兰盆地的风数据被用来计算垂直混合率。假设没有生物降解,预计东设得兰盆地分散油的峰值浓度约为3 μg l−1;该值与Stagg等人的测量值一致(见:Reed, M., Johnsen, S.(主编),采出水2,环境问题和缓解技术,全会出版社,1996年),其中的数据是在排放点附近收集的,预计降解的影响可以忽略不计。对分散油的降解、水平和垂直混合以及跨越温跃层的混合进行了不同参数值的模型运行矩阵。这些结果用于估计模型的敏感性和预测浓度场的不确定性。结果表明,对于沿北海中心向上延伸约150公里宽的高浓度区域,垂直混合的参数化对于预测浓度水平是最重要的。在离排放点较远和离陆地较近的地区,物质的降解速率对预测浓度的影响最大。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Environmental Modelling & Software
Environmental Modelling & Software 工程技术-工程:环境
CiteScore
9.30
自引率
8.20%
发文量
241
审稿时长
60 days
期刊介绍: Environmental Modelling & Software publishes contributions, in the form of research articles, reviews and short communications, on recent advances in environmental modelling and/or software. The aim is to improve our capacity to represent, understand, predict or manage the behaviour of environmental systems at all practical scales, and to communicate those improvements to a wide scientific and professional audience.
期刊最新文献
Advancing participatory decision support system in water management: An agent-based model for socially-informed collective allocation Parallelization of the Estuarine Saltwater Intrusion Numerical Forecast Model UFDECOM-i Using Fortran DO CONCURRENT The ODE (Overview, Data, and Execution) protocol for a standardized use of machine learning in environmental, social and related interdisciplinary sciences. Climate Risk STAC: A living metadata catalog of geospatial data for climate risk assessments A Stepwise Back-Correction Function for Precipitation Representation in Hydrologic Models
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1