Date of Award
1-1-2023
Document Type
Dissertation
Degree Name
Ph.D. in Engineering Science
First Advisor
Robert M. Robert
Second Advisor
Craig J. Hickey
Third Advisor
Robert M. Robert
Relational Format
dissertation/thesis
Abstract
This dissertation presents an exploration of the Self-Potential (SP) and Electrical Resistivity Tomography (ERT) methods applied within the context of the Managed Aquifer Recharge (MAR) project near the Tallahatchie River at Shellmound, MS. The research introduces tools and methodologies, including 80-electrode SP data acquisition systems (80E-SPDAS) and the Hydro-Electrical Aquifer Properties Estimator (HEAPE), to measure SP data in the laboratory and the field. The first segment of the dissertation introduces the Hydro- Electrical Aquifer Properties Estimator (HEAPE), an apparatus designed for high-resolution Self-Potential (SP) data collection. The HEAPE apparatus is utilized in laboratory experiments to measure SP under varying conditions of hydraulic head, temperature, and hydrogeochemistry of water in soil cores. This section also highlights the development of a custom SP data processing program, which is capable of cleaning noisy data and performing regression analyses. Furthermore, this part of the research presents the development of forward modeling of SP and parameter estimation programs. These tools are designed to estimate aquifer parameters from SP data, demonstrating the practical application of the measured data using the apparatus. The second segment of the dissertation introduces the development of the 80E-SPDAS and its application in the laboratory for measuring SP data associated with a pumping test. This section addresses the challenge of noise in SP data, primarily due to the oscillating pressure of the peristaltic pump and ambient electrical influences. To combat this, the Nonlinear Least Squares method, coupled with the Levenberg-Marquardt optimization algorithm, is applied to fit the noisy SP and hydraulic head data. This approach effectively eliminates noise, rendering the data suitable for further analysis and inversion. This segment also delves into the spatial and temporal analysis of SP data, demonstrating the application of SP data in predicting the groundwater flow boundary, determining the extent of the cone of depression, and identifying the locations of drawdown. These analyses show the potential utility of SP data in investigating surface-groundwater interactions for the MAR project. The final segment focuses on characterizing the Mississippi River Valley Alluvial (MRVA) aquifer using ERT and the field application of the developed 80E-SPDAS for collecting SP data to investigate surface-groundwater interactions. The high degree of heterogeneity in the aquifer is revealed, with several zones of higher resistivity anomalies identified as loosely packed sand and gravel zones, preferential groundwater flow pathways, and potential sites for drilling extraction wells. This section also demonstrates the effectiveness of the 80-electrodes SP data acquisition system in real-time monitoring of surface-groundwater interaction, drawdown prediction, and flow direction determination. In conclusion, this dissertation makes contributions to the field of hydrogeology by developing data acquisition systems and applying them in the laboratory and the field. The findings not only enhance our understanding of SP data and aquifer systems but also provide practical solutions for managing groundwater resources effectively, thereby paving the way for future research and applications in this field.
Recommended Citation
Mamud, Md Lal, "Experimental and Modeling Approaches to Groundwater Flow and Self-Potential for Estimating Aquifer Parameters and Investigating Surface-Groundwater Interaction" (2023). Electronic Theses and Dissertations. 2758.
https://egrove.olemiss.edu/etd/2758