Collaborative Research: Data Fusion for Characterizing and Understanding Water Flow Systems in Karst Aquifers

合作研究：用于表征和理解岩溶含水层水流系统的数据融合

• 批准号: 1931756
• 负责人: Tian-Chyi Yeh
• 金额: $ 45.4万
• 依托单位: University of Arizona
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-03-01 至 2025-02-28
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1931756&HistoricalAwards=false
• 关键词: Collaborative; Research; Data; Fusion; Characterizing

Aquifers are geologic materials that store and transmit groundwater and supply drinking water for 51% of the total U.S. population. Groundwater is also an indispensable resource for energy production, agricultural and industrial uses. A karst aquifer is a special type of aquifer that is formed in regions underlain by soluble rocks, typically carbonate rocks. Karst aquifers hold 40% of U.S. groundwater. The dissolution of soluble rocks through time creates a complex groundwater flow system in karst aquifers, which is typically characterized by a network of fractures and conduits that connect to the surface water through sinkholes, sinking streams, and springs. Those characteristics make karst aquifers potentially vulnerable to both climate change and contamination. The proposed research seeks to enhance understanding of the complex network of fractures and conduits in karst aquifers in order to advance the prediction of water flow, surface water and groundwater interaction, contaminant transport, nutrient cycle, and the carbon cycle in many karst aquifers under increased stresses from human activities. This project will also greatly benefit the economically distressed karst Appalachian region where students are underrepresented in STEM (Science, Technology, Engineering, and Mathematics). This project is jointly funded by the Hydrologic Sciences (HS) Program and the Established Program to Stimulate Competitive Research (EPSCoR). This research will be centered on conducting collaborative research using a complementary data fusion approach. The approach fuses data collected from hydraulic tomography, river stage tomography, electrical resistivity tomography, and tracer tests to produce a more reliable map of fractures and conduits in karst aquifers in a cost-effective manner. In turn, the results will lead to improved understanding and prediction of flow and solute transport in the karst aquifers. The overarching goal of this project is to develop, test, and validate an innovative approach for characterizing karst aquifers in detail based on the data fusion concept. To achieve this goal, this research will design two new field surveys: surface and subsurface river stage tomography and electrical resistivity tomography with moving current sources. This research will also explore the feasibility of natural lightning tomography for large-scale resistivity surveys. The data collected from these surveys will be integrated into a geostatistical-based inversion framework to characterize the distribution and morphology of fractures and conduits with great detail. The fusion approach will be tested and validated at the Cane Run Royal Spring Basin in central Kentucky. The validity of the characterized karst aquifers will be evaluated using a separate model with the field-collected water level, water chemistry, tracer, and stable isotope data.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

含水层是地质材料，可存储和传输地下水并为美国总人口的51％提供饮用水。地下水也是能源生产，农业和工业用途的必不可少的资源。喀斯特含水层是一种特殊类型的含水层，在可溶性岩石（通常是碳酸盐岩石）下方形成的区域形成。喀斯特含水层占美国地下水的40％。通过时间的流通岩石的溶解会在喀斯特含水层中形成一个复杂的地下水流系统，该水层通常以裂缝和导管网络的特征，这些网络通过下沉的溪流和泉水连接到地表水。 这些特征使喀斯特含水层可能易受气候变化和污染的影响。拟议的研究旨在增强喀斯特含水层中裂缝和导管的复杂网络的理解，以推动许多喀斯特含水层在人类活动增加的压力下的水流，地表水和地下水相互作用，污染物运输，养分循环以及碳循环的预测。 该项目还将极大地受益于经济困难的喀斯特阿巴拉契亚地区，在STEM（科学，技术，工程和数学）中，学生人数不足。该项目由水文科学（HS）计划和启发竞争研究（EPSCOR）的既定计划共同资助。这项研究将以互补的数据融合方法进行协作研究。该方法融合了从液压断层扫描，河流断层扫描，电阻层造影术和示踪剂测试中收集的数据，以以具有成本效益的方式在喀斯特含水层中生成更可靠的裂缝和导管图。反过来，结果将导致对喀斯特含水层中流动和溶质传输的理解和预测。 该项目的总体目标是开发，测试和验证一种创新方法，以根据数据融合概念详细介绍喀斯特含水层。为了实现这一目标，这项研究将设计两个新的现场调查：表面和地下河流阶段断层扫描以及具有移动电流源的电阻率层析成像。这项研究还将探索自然闪电断层扫描对大规模电阻率调查的可行性。从这些调查中收集的数据将集成到基于地列的反转框架中，以详细介绍裂缝和导管的分布和形态。融合方法将在肯塔基州中部的Cane Run皇家春季盆地进行测试和验证。特征性的喀斯特含水层的有效性将使用具有现场收集的水位，水化学，示踪剂和稳定同位素数据的单独模型进行评估。该奖项反映了NSF的法定任务，并被认为是值得通过基金会的知识分子优点和更广泛影响的审查标准来通过评估来获得支持的。