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Data Integration to Significantly Improve Hydraulic Tomography and Groundwater Modelling in Complex Geologic Media

Data Integration to Significantly Improve Hydraulic Tomography and Groundwater Modelling in Complex Geologic Media
数据集成可显着改善复杂地质介质中的水力层析成像和地下水建模
批准号:
RGPIN-2017-03859
负责人:
Illman, Walter
金额:
$1.97万
依托单位:
依托单位国家:
加拿大
项目类别:
Discovery Grants Program - Individual
财政年份:
2019
资助国家:
加拿大
项目状态:
已结题
起止时间:
2019-01-01 至 2020-12-31

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中文摘要
翻译
地下水模型已成为供水评价和污染物运移研究中不可或缺的组成部分。各种模型的可用性,其改进的能力,以及不断增加的计算资源,使先进的模型更接近现实。在作出具有商业、政策和社会影响的重要决策时,人们越来越依赖他们。建立更可靠的模型的一个关键因素是采用更准确的流动参数,如水力传导率(K)和特定的存储(Ss)。然而,地下在多个尺度上是不均匀的,这使得松散和断裂岩层中K和Ss的表征显着复杂化。水力层析成像(HT)是一种基于多次抽水试验反演模型的地下介质非均质性成像新方法。虽然HT已被证明是一种用于成像地下非均匀性的稳健方法,但迫切需要检查:1)其他现场数据(如地质、地球物理、温度和化学数据)是否可以增强抽水试验数据并改善HT结果; 2)HT是否可以有效地映射裂缝和岩石基质之间水力性质存在巨大差异的裂缝岩石地形中的非均匀性;和3)HT利用河流洪水脉冲作为地下水位的扰动,可用于表征在流域尺度上控制地表水/地下水交换的参数。通过这项研究计划,我们将首先检查在滑铁卢大学校园的一个特征良好的现场站点,将其他站点数据与HT结果的抽水试验数据相结合的有效性。接下来,我们还将研究HT是否可以通过在日本一个成熟的断裂岩石现场进行数据集成来改进,我们的研究小组可以访问不同但互补的数据。最后,将进行一项计算研究,以调查河流洪水脉冲作为监测威尔斯中检测到的信号的效用,以绘制控制地表水/地下水交换的水力参数的异质性。** 总的来说,我们的研究计划将有助于确定HT是否可以显着改善各种行业(水,修复,能源,废物处理和采矿)所需的分辨率和规模相关的地下表征工作。拟议的研究重点是进行互补的计算和实地调查,应显着提高我们的能力,以映射在多孔和裂缝地质介质的地下异质性。由于地下非均质性将通过HT更准确地映射,这种能力的发展也将使我们能够显着提高地下水模型的准确性,用于制定重要的商业,政策和社会决策。
英文摘要
Groundwater models have become indispensable in water supply assessment and contaminant transport studies. The availability of various models, their improved capabilities, and ever-increasing computational resources have advanced models closer to reality. They are becoming increasingly relied upon to make important decisions that have business, policy and societal consequences. One key ingredient to building more reliable models is employing more accurate flow parameters such as hydraulic conductivity (K) and specific storage (Ss). However, the subsurface is heterogeneous at multiple scales and this significantly complicates the characterization of K and Ss in unconsolidated and fractured rock formations.******Hydraulic tomography (HT) which relies on the inverse modeling of multiple pumping tests, has emerged as a new method to image the subsurface heterogeneity of K and Ss. While HT has been shown to be a robust method for imaging subsurface heterogeneity, there is a critical need to examine whether: 1) other site data such as geological, geophysical, temperature and chemical data can augment pumping test data and improve HT results; 2) HT can effectively map heterogeneities in fractured rock terrains where a large contrast in hydraulic properties between fractures and rock matrix exists; and 3) HT that utilizes river flood pulses as perturbations in groundwater levels can be used to characterize parameters that govern surface-water/groundwater exchange at the basin scale.******Through this research program, we will first examine the effectiveness of integrating other site data with pumping test data on HT results at a well-characterized field site on the University of Waterloo campus. Next, we will also examine whether HT can be improved through data integration at a well-established fractured rock site in Japan where our research group has access to different, yet complementary data. Finally, a computational study will be conducted to investigate the utility of river flood pulses as signals detected in monitoring wells to map the heterogeneity in hydraulic parameters that control surface-water/groundwater exchange. ******Collectively, our research program will help determine whether HT can significantly improve subsurface characterization efforts relevant at the resolution and scale necessary for various industries (water, remediation, energy, waste disposal, and mining). The proposed research focuses on conducting complementary computational and field investigations that should significantly advance our capabilities to map subsurface heterogeneity in both porous and fractured geologic media. Because subsurface heterogeneities will be mapped more accurately through HT, development of such capabilities will also allow us to significantly improve the accuracy of groundwater models used to make important business, policy, and societal decisions.
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Data Integration to Significantly Improve Hydraulic Tomography and Groundwater Modelling in Complex Geologic Media
  • 批准号:
    RGPIN-2017-03859
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $3.93万
  • 财政年份:
    2021
  • 负责人:
    Illman, Walter
  • 依托单位:
Data Integration to Significantly Improve Hydraulic Tomography and Groundwater Modelling in Complex Geologic Media
  • 批准号:
    RGPIN-2017-03859
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $1.97万
  • 财政年份:
    2020
  • 负责人:
    Illman, Walter
  • 依托单位:
Data Integration to Significantly Improve Hydraulic Tomography and Groundwater Modelling in Complex Geologic Media
  • 批准号:
    RGPIN-2017-03859
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $1.97万
  • 财政年份:
    2018
  • 负责人:
    Illman, Walter
  • 依托单位:
Data Integration to Significantly Improve Hydraulic Tomography and Groundwater Modelling in Complex Geologic Media
  • 批准号:
    RGPIN-2017-03859
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $1.97万
  • 财政年份:
    2017
  • 负责人:
    Illman, Walter
  • 依托单位:
海外基金