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

含水层是储存和输送地下水的地质材料，为美国总人口的51%提供饮用水。地下水也是能源生产、农业和工业用途不可或缺的资源。岩溶含水层是一种特殊类型的含水层，形成于可溶性岩石（通常为碳酸盐岩）下方的区域。岩溶含水层拥有美国40%的地下水。随着时间的推移，可溶性岩石的溶解在岩溶含水层中产生了复杂的地下水流系统，其典型特征是裂缝和管道网络，通过天坑，下沉的溪流和泉水连接到地表水。 这些特点使岩溶含水层可能容易受到气候变化和污染的影响。拟议的研究旨在加强对岩溶含水层中复杂的裂缝和管道网络的理解，以促进对水流，地表水和地下水相互作用，污染物运输，营养循环以及人类活动增加的压力下许多岩溶含水层中的碳循环的预测。 该项目也将大大有利于经济困难的喀斯特阿巴拉契亚地区，那里的学生在STEM（科学，技术，工程和数学）中的代表性不足。该项目由水文科学（HS）计划和刺激竞争研究（EPSCoR）的既定计划共同资助。这项研究将集中在使用互补的数据融合方法进行合作研究。该方法融合了从水力层析成像，河流阶段层析成像，电阻率层析成像和示踪剂测试收集的数据，以成本效益高的方式产生更可靠的岩溶含水层裂缝和管道图。反过来，结果将导致更好的理解和预测的流量和溶质运移的岩溶含水层。 该项目的总体目标是开发、测试和验证一种基于数据融合概念详细描述岩溶含水层特征的创新方法。为了实现这一目标，本研究将设计两个新的实地调查：地表和地下河流阶段层析成像和移动电流源电阻率层析成像。这项研究还将探讨大规模电阻率调查的自然闪电层析成像的可行性。从这些调查中收集的数据将被纳入一个基于地球物理学的反演框架，以非常详细地描述裂缝和管道的分布和形态。融合方法将在肯塔基州中部的凯恩润皇家泉盆地进行测试和验证。将使用一个单独的模型，结合现场收集的水位、水化学、示踪剂和稳定同位素数据，对岩溶含水层的有效性进行评估。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

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.