Collaborative Research: Using Surface Information for Quantitative Modeling of the Subsurface

协作研究：利用地表信息进行地下定量建模

• 批准号: 1719638
• 负责人: Holly Michael
• 金额: $ 28.24万
• 依托单位: University of Delaware
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-08-01 至 2022-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1719638&HistoricalAwards=false
• 关键词: Collaborative; Research; Using; Surface; Information

Surface connections, such as those among channels in river networks, are important for understanding the development and evolution of landscapes, such as densely populated coastal river deltas. Connections in the subsurface are critical in understanding groundwater flow and solute transport. Preferential flowpaths, in fact, can quickly deliver contaminants to water supply wells, a particularly important problem in densely populated coastal areas. Establishing a quantitative link between surface and subsurface patterns will greatly advance our capability to predict the movement of contaminants in groundwater, thus improving access to clean water and limiting pollution and health risks. We propose to investigate quantitatively how the dynamics of surface networks create subsurface networks, and thus determine how surface information can be used to predict properties of the subsurface. This will enable us to better predict sustainability and manage water resources in densely populated deltas such as the Ganges-Brahmaputra Delta, where high concentrations of arsenic are widespread in the groundwater of the upper delta, and salinity problems are pervasive in the lower delta. The models and data analysis tools developed as part of this project will be released as open source and we will collaborate with Bangladeshi institutions to disseminate our findings. Our driving hypothesis is that the 3D subsurface structure can be predicted by combining information on (i) the modern surface network snapshot, (ii) the surface network kinematics (i.e., its temporal evolution), and (iii) accommodation and net sedimentation. We further hypothesize that (iv) the nature of the surface-to-subsurface translation exerts a major influence on structural connectivity and solute transport through the resulting aquifer system. Our goal is to develop new methods to translate surface channel networks to obtain quantitative models of subsurface architecture and flow and transport processes. We will perform this analysis with a combination of experimental, numerical modeling, and observational approaches and we will verify our findings by collecting lithologic and geochemical data in the Ganges-Brahmaputra Delta. Our findings will provide critical information about the predictability of subsurface structure given the surface channel network and its kinematics, and will allow quantification of the factors influencing this predictability. The proposed work will also further the development of quantitative metrics of connectivity of surface networks and subsurface 3D structures and flowpaths, and improve our ability to model the subsurface structure of large deltaic systems where spatial heterogeneity and large spatial extent prevent full characterization via field observations. By extending this structural understanding to dynamic solute transport behavior, the proposed research will enhance the predictability of contaminant migration in highly heterogeneous systems.

地表连接（例如河流网络中河道之间的连接）对于了解景观（例如人口稠密的沿海河流三角洲）的发展和演变非常重要。地下的连接对于了解地下水流和溶质输送至关重要。事实上，优先流道可以快速将污染物输送到供水井，这在人口稠密的沿海地区是一个特别重要的问题。建立地表和地下模式之间的定量联系将极大地提高我们预测地下水污染物运动的能力，从而改善清洁水的获取并限制污染和健康风险。我们建议定量研究地表网络的动态如何创建地下网络，从而确定如何使用地表信息来预测地下的特性。这将使我们能够更好地预测恒河-雅鲁藏布江三角洲等人口稠密三角洲的可持续性并管理水资源，该地区上游三角洲的地下水普遍存在高浓度的砷，而盐度问题在下游三角洲普遍存在。作为该项目一部分开发的模型和数据分析工具将作为开源发布，我们将与孟加拉国机构合作传播我们的研究结果。我们的驱动假设是，3D 地下结构可以通过结合以下信息来预测：(i) 现代地表网络快照，(ii) 地表网络运动学（即其时间演化），以及 (iii) 调节和净沉降。我们进一步假设 (iv) 地表到地下转换的性质对由此产生的含水层系统的结构连通性和溶质运输产生重大影响。我们的目标是开发新方法来转换地表通道网络，以获得地下结构以及流动和运输过程的定量模型。我们将结合实验、数值模型和观测方法进行分析，并通过收集恒河-雅鲁藏布江三角洲的岩性和地球化学数据来验证我们的发现。我们的研究结果将提供有关给定地表通道网络及其运动学的地下结构可预测性的关键信息，并将允许量化影响这种可预测性的因素。拟议的工作还将进一步发展地表网络和地下 3D 结构和流路连通性的定量指标，并提高我们对大型三角洲系统地下结构进行建模的能力，其中空间异质性和大空间范围阻碍了通过现场观测进行全面表征。通过将这种结构理解扩展到动态溶质输运行为，拟议的研究将增强高度异质系统中污染物迁移的可预测性。

项目成果

Modeling the Dynamic Response of River Deltas to Sea‐Level Rise Acceleration

模拟河流三角洲对海平面上升加速度的动态响应

• DOI: 10.1029/2022jf006762
• 发表时间: 2022-09-01
• 期刊: Journal of Geophysical Research: Earth Surface
• 作者: J. Hariharan;P. Passalacqua;Zhongyuan Xu;H. Michael;E. Steel;A. Chadwick;C. Paola;A. Moodie
• 通讯作者: A. Moodie

Reconstructing subsurface sandbody connectivity from temporal evolution of surface networks

从地表网络的时间演化重建地下砂体的连通性

• DOI: 10.1111/bre.12668
• 发表时间: 2022-08
• 期刊: Basin Research
• 影响因子: 3.2
• 作者: Steel, Elisabeth;Paola, Chris;Chadwick, Austin J.;Hariharan, Jayaram;Passalacqua, Paola;Xu, Zhongyuan;Michael, Holly A.;Brommecker, Hannah;Hajek, Elizabeth A.
• 通讯作者: Hajek, Elizabeth A.

Linking the Surface and Subsurface in River Deltas—Part 1: Relating Surface and Subsurface Geometries

连接河流三角洲的地表和地下 - 第 1 部分：关联地表和地下几何形状

• DOI: 10.1029/2020wr029282
• 发表时间: 2021-08-01
• 期刊: Water Resources Research
• 影响因子: 5.4
• 作者: J. Hariharan;Zhongyuan Xu;H. Michael;C. Paola;E. Steel;P. Passalacqua
• 通讯作者: P. Passalacqua

Linking the Surface and Subsurface in River Deltas—Part 2: Relating Subsurface Geometry to Groundwater Flow Behavior

连接河流三角洲的地表和地下 - 第 2 部分：地下几何形状与地下水流行为的关系

• DOI: 10.1029/2020wr029281
• 发表时间: 2021-08
• 期刊: Water Resources Research
• 影响因子: 5.4
• 作者: Xu, Zhongyuan;Hariharan, Jayaram;Passalacqua, Paola;Steel, Elisabeth;Paola, Chris;Michael, Holly A.
• 通讯作者: Michael, Holly A.

Effects of Geologic Setting on Contaminant Transport in Deltaic Aquifers

地质环境对三角洲含水层污染物迁移的影响

• DOI: 10.1029/2022wr031943
• 发表时间: 2022-08-25
• 期刊: Water Resources Research
• 影响因子: 5.4
• 作者: Zhongyuan Xu;J. Hariharan;P. Passalacqua;E. Steel;A. Chadwick;C. Paola;A. Paldor;H. Michael
• 通讯作者: H. Michael