Clean groundwater, a primary source of drinking water for many people, is a valuable Earth resource. Risks of groundwater contamination frequently arise from natural, agricultural, or industrial activities. To preserve the safety of these drinking water sources, it is crucial to understand how contaminants are expected to move and spread underground. An important factor that influences the movement of contaminants is the variability of the void spaces in soil and rocks known as pores. Complex flow patterns arise as groundwater moves through intricate pores of different shapes and sizes, which make predictions of flow complicated. Many mathematical predictions of groundwater flow ignore the complex variability in pores. This oversimplification results in a large discrepancy between flow predictions and observations. The central scientific goal of this project is to better understand how contaminant movement is controlled by measurable features of the pores. The first step of this project will statistically identify the most relevant attributes of pores that effectively describe flow in rock. The second step will apply this relationship to develop a new mathematical model of flow and contaminant movement. Collectively, this work will deliver more accurate tools to predict contaminant movement and to help protect water resources. The project will train students and water managers through the development of an interactive web-based tool designed to allow users to understand and manipulate groundwater flow in a virtual environment.
Solving the flow and mass transport through heterogeneous porous media is central to many technological applications spanning groundwater remediation, oil recovery, and geotechnical engineering. The approaches to do so are currently limited, because the required calculations become computationally expensive as accuracy and domain size increase. The central scientific goal of this project is to establish a formal quantitative relationship that explains how local fluid velocities and overall flow arrangement are controlled by spatially correlated variations of geometric pore characteristics. This association would enable predicting non-Gaussian velocity distributions from relevant statistical descriptors of the pore space alone, which in turn can be used to predict effective transport. Finding this elusive link will lead to significant improvements in predictive capabilities for groundwater flow and contaminant transport in heterogeneous porous systems of arbitrary domain size. To achieve this goal, the proposed work will first statistically identify how velocity variations are induced by the physical attributes of the underlying pore space in digitally-scanned rock samples of diverse heterogeneities. These virtual data contain detailed information of the structure, the flow and the transport. Next, the newly-determined pore structure-flow relation will be integrated into the leading modeling framework for anomalous transport behavior and assessed for performance. The main educational goal is to enhance student understanding about how groundwater flows and how contaminants spread in it. This will be done through the development of interactive web tools for non-experts (targeting high-school, college and continued education students) that can be used in flipped-classroom environments. The interactive tool design allows the user to manipulate groundwater models, explore the results as automatically-generated graphics, and discover answers to their own questions in a self-directed application of the scientific method.
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.
