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Three-Dimensional Modeling of Contaminants Transport in Subsurface Environment: From the Land Surface Through the Unsaturated Zone and Fully Saturated Aquifers

Three-Dimensional Modeling of Contaminants Transport in Subsurface Environment: From the Land Surface Through the Unsaturated Zone and Fully Saturated Aquifers
地下环境中污染物迁移的三维建模:从地表到非饱和带和完全饱和含水层
批准号:
9317009
负责人:
Tian-Chyi Yeh
金额:
$24.71万
依托单位:
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
1994
资助国家:
美国
项目状态:
已结题
起止时间:
1994-04-15 至 1998-09-30

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中文摘要
翻译
9317009 Yeh近十年来,地下水污染问题中场非均质性的重要性已得到广泛认识。已经进行了许多实地和理论研究,以增强我们对其影响的理解,并提高我们对实地污染物迁移的预测能力。条件模拟被普遍认为是最符合逻辑的方法,可以提高我们在现场对污染物迁移的预测。然而,许多研究采用了一维或二维稳态流等简化和不现实的场景。污染物通过非饱和带向地下水位多维移动并在含水层中传播的研究从未进行过。其中一个限制因素是计算难度和需要大量的CPU时间进行多维数值模拟。由于控制流动方程的非线性,这一问题在非饱和区域的流动和输运情况下最为严重。随机条件模拟甚至更可怕。研究者最近开发的一种方法将模拟二维非饱和非均质土壤中溶质运输的CPU时间减少了两到三个数量级。这一技术突破使非饱和条件下非均质多孔介质中溶质运移的条件模拟成为可能。该方法的稳健性迫使我们对污染物从非均质不饱和渗透带到完全饱和含水层的三维输送进行试验。本研究的总体目标是开发一种计算上可行的算法,用于模拟在可变饱和条件下三维非均质多孔介质中的污染物迁移,并研究我们提出的条件概念在设计采样程序方面的潜力,从而提高我们对地下环境中污染物迁移的预测。换句话说,我们想评估采样的程度是必要的,以预测污染物在地下环境中的迁移。
英文摘要
9317009 Yeh The importance of field heterogeneities in groundwater pollution problems has been widely recognized during the last decade. Many field and theoretical studies have been conducted to enhance our understanding of their impacts and to improve our predictive ability of contaminant migration in the field. Conditional simulation is generally accepted as the most logical approach that can improve our prediction of contaminant transport in the field. Many studies are, however, adopt simplified and unrealistic scenarios such as one or two-dimensional steady-state flow. Studies have never been conducted where contaminants move multi- dimensionally through the unsaturated zone to the water table and propagate through the aquifer. One of the limiting factors is computational difficulty and the enormous amount of CPU time required for multi-dimensional numerical simulation. This problem is most severe in the case of flow and transport in the unsaturated zone due to the nonlinearity of the governing flow equation. Stochastic conditional simulations are even more formidable. An approach recently developed by the investigator reduces the CPU time for simulating transport of solutes in two-dimensional unsaturated heterogeneous soils by two or three orders of magnitude. This technical breakthrough allows conditional simulation of solute transport in heterogeneous porous media under unsaturated conditions. The robustness of the approach compels us to try it on three-dimensional transport of contaminants from heterogeneous unsaturated vadose zones to fully saturated aquifers. The overall objectives of the study are to develop a computationally feasible algorithm for simulation of contaminant transport in three-dimensional heterogeneous porous media under variably saturated conditions and to investigate the potential of our proposed conditional concept for designing sampling procedures that improves our prediction of contaminant migration in subsurface envir onment. In other words, we would like to assess the degree of sampling is necessary to predict migration of contaminants in the subsurface environment.
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Collaborative Research: Data Fusion for Characterizing and Understanding Water Flow Systems in Karst Aquifers
  • 批准号:
    1931756
  • 项目类别:
    Standard Grant
  • 资助金额:
    $45.4万
  • 财政年份:
    2020
  • 负责人:
    Tian-Chyi Yeh
  • 依托单位:
Development of River-Stage Tomography for Characterizing Groundwater Basins
  • 批准号:
    1014594
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $46.4万
  • 财政年份:
    2010
  • 负责人:
    Tian-Chyi Yeh
  • 依托单位:
Collaborative Research: River Stage Tomography for Automatic Characterization of Fluxes between Surface and Groundwater Reservoirs: A Pilot Study
  • 批准号:
    0450388
  • 项目类别:
    Standard Grant
  • 资助金额:
    $6.25万
  • 财政年份:
    2005
  • 负责人:
    Tian-Chyi Yeh
  • 依托单位:
Collaborative Research: SEI (EAR): Adaptive Fusion of Stochastic Information for Imaging Fractured Vadose Zones
  • 批准号:
    0431079
  • 项目类别:
    Standard Grant
  • 资助金额:
    $55.13万
  • 财政年份:
    2004
  • 负责人:
    Tian-Chyi Yeh
  • 依托单位:
国内基金
海外基金
Scalable Learning and Optimization: High-dimensional Models and Online Decision-Making Strategies for Big Data Analysis