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首页> 外文期刊>European Journal of Environmental and Civil Engineering >Efficiency of using 4DVar, 3DVar and EnKF data assimilation methods in groundwater contaminant transport modelling
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Efficiency of using 4DVar, 3DVar and EnKF data assimilation methods in groundwater contaminant transport modelling

机译:使用4DVAR,3DVAR和ENKF数据同化方法在地下水污染运输建模中的效率

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摘要

Groundwater contaminant has been a serious issue to environmental engineers for long time. To simulate groundwater contaminant flow condition, a three-dimensional subsurface contaminant transport model with advection, dispersion and reaction has been developed to predict transport of a continuous source pollutant. Numerical forward-time-central-space scheme has been used to solve the advection-dispersion-reaction transport model and three-dimensional variational data assimilation (3DVar) and four dimensional variational data assimilation (4DVar) schemes have been used for data assimilation purpose. Then these two schemes were compared with previously implemented ensemble Kalman filter (EnKF) scheme. In this study, contaminant concentration is the state that has been propagated by this model. Reference true solution derived from numerical solution with added noise has been used to compare model results. The results showed that the computational cost of 3DVar and 4DVar were justified in this case. Finally, sensitivity analysis has been performed with different standard deviation and it was seen that 3DVar and 4DVar perform better in contrast to the noise sensitive EnKF.
机译:地下水污染物一直是环境工程师的严重问题。为了模拟地下水污染物流动条件,已经开发了一种具有平流,分散和反应的三维地下污染物运输模型,以预测连续源污染物的运输。已经使用数值前进时 - 中央空间方案来解决方程 - 分散反应传输模型和三维变分数据同化(3DVAR)和四维变分数据同化(4DVAR)方案已被用于数据同化目的。然后将这两种方案与先前实现的集合Kalman滤波器(ENKF)方案进行了比较。在该研究中,污染物浓度是该模型传播的状态。通过添加噪声的数字解决方案导出的参考真实解决方案已用于比较模型结果。结果表明,在这种情况下,3DVAR和4DVAR的计算成本是合理的。最后,已经用不同的标准偏差进行了敏感性分析,看来3DVAR和4DVAR与噪声敏感ENKF相比更好地表现更好。

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