CAREER: An Integrative Probabilistic Approach for Assessing Solute Transport in Multi-Scale Heterogeneous Aquifers

地下水是农业、能源和其他工业部门的重要自然资源。它也是饮用水的主要来源之一。然而，由于人类的使用和活动，地下水正在枯竭，很容易受到污染。因此，这种宝贵的自然资源的可持续性受到威胁，人类可能会受到污染。为了更好地了解污染物在含水层中的运移，需要新的模拟工具。这一点尤其重要，因为这样的模拟工具可以更好地管理受污染的地下水，以具有成本效益的方式实现补救，保持我们的自然资源可持续，并保护人类健康。然而，实现这一目标是一项具有挑战性的任务，因为污染物在地下环境中的迁移受到多种因素的强烈影响。在这些因素中，我们强调了普遍存在的水文地质特性、井抽作业和污染物释放条件的自然不均一性。该项目旨在开发一个模型框架，以改善我们对这些因素对地下环境中污染物传输的联合影响的基本知识。基础研究将成为改进和综合人类健康风险评估的途径。作为教育和外展活动的一部分，研究方法和成果将通过与当地学校教师协调的一系列活动传达给高中生。通过以地下水为重点的讲座，STEM Academy的高中生将(1)学习保护地下水资源的重要性，(2)利用研究生建造的捐赠设备重现达西的实验。这个项目旨在通过开发一个新的、综合的、概率的框架来提高我们对地下水溶质在复杂的非均质地下环境中的运移的了解。将使用一个新的物理和数据驱动框架来调查(1)溶质源带分布、(2)表征含水层的水文地质性质的空间变异性和(3)外部因素(例如，供水需求引起的抽水率)之间的相互作用如何控制溶质运移的大小和不确定性。将开发一种能够同化水文数据的物理随机方法，其目标是纳入水文地质复杂性(通常在实际场地和应用中遇到)，同时纳入与公共健康有关的决策要素。水文地质的复杂性既源于含水层水力特性的多尺度空间异质性，也源于与供水需求相关的抽水策略的影响。这些因素结合在一起，将导致复杂的流动拓扑特征，这将显著影响溶质羽流的变形，从而影响其稀释率。在这个项目中开发的框架结合了随机水力系统、统计理论、信息理论和流拓扑的创新。通过使用随机数值模拟和分析模拟，本项目将使人们对上述因素在控制运输观测数据的大小和不确定性方面的重要性有新的认识。

Groundwater is a crucial natural resource in agricultural, energy and other industrial sectors. It is also one of the major sources of drinking water. However, through human use and activity, groundwater is being depleted and is vulnerable to contamination. As a consequence, the sustainability of this valuable natural resource is at risk and humans might be exposed to contamination. Novel simulation tools are needed to better understand transport of pollutants in aquifers. This is particularly important since such simulation tools allow to better manage polluted groundwater, achieve remediation in a cost-effective manner, keep our natural resources sustainable and protect human health. However, achieving this goal is a challenging task since contaminant transport in the subsurface environment is strongly affected by multiple factors. Among these factors, we highlight the ubiquitous presence of natural heterogeneity of hydrogeological properties, well pumping operations and the release conditions of pollutants. This project aims to develop a modeling framework that improves our fundamental knowledge of the joint impact of these factors on contaminant transport in the subsurface environment. The fundamental research will serve as a pathway to improved and integrated human health risk assessment. As part of the education and outreach activities, the research methods and results will be conveyed to high school students via a series of activities coordinated with local school teachers. Through lectures focused on groundwater, STEM Academy high school students will (1) learn the importance of protecting groundwater resources and (2) reproduce Darcy's experiment with donated equipment constructed by graduate students. This project aims to advance our knowledge of groundwater solute transport in complex heterogeneous subsurface environments through the development of a novel, integrative, probabilistic framework. A new physically and data driven framework will be used to investigate how the interaction between (1) solute source-zone distribution, (2) the spatial variability of the hydrogeological properties characterizing the aquifer, and (3) external factors (e.g., pumping rates induced by water supply demand) control the magnitude and the uncertainty in solute transport. A physically based stochastic methodology capable of assimilating hydrological data will be developed with the goal of incorporating hydrogeological complexities (normally encountered in real sites and applications), while also incorporating elements toward decision making which are relevant to public health. The hydrogeological complexities derive both from the multi-scale spatial heterogeneity of the aquifer's hydraulic properties, but also the effects of pumping strategies associated with water-supply demand. Combined, these factors will lead to complex flow topological features that will significantly influence the deformation of the solute plume and therefore its dilution rate. The framework developed in this project combines innovations in stochastic hydro-systems, statistical theory, information theory, and flow topology. Through the use of stochastic numerical and analytical simulations, this project will shed new knowledge on the importance of the abovementioned factors in controlling the magnitude and uncertainty of transport observables.