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Predicting Post-Mining Hydrologic Effects of Underground Coal Mines in Ohio through Multivariate Statistical Analyses and GIS Tool Building

Steinberg, Rebecca M.
http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1555429886192267

Abstract Details

2019, Master of Science (MS), Ohio University, Environmental Studies (Voinovich).
Coal mining activities can result in a variety of environmental issues and, worldwide, one of the greatest threats from coal mining is acid mine drainage (AMD). In the eastern U.S. coal bearing regions, AMD is a wide spread environmental impairment to waterways, especially from abandoned or closed underground coal mines. Pollutional discharge can result from flooding of underground mines, or mine pools, resulting in reactions that create AMD and discharge to surface water. Research has focused on improving reclamation and treatment methods for AMD to address ongoing pollution problems, but there is a need for more reliable prediction methods for use in continued permitting of lands for coal mining. Under the Surface Mining Control and Reclamation Act (SMCRA), coal companies are required to estimate the post-mining water levels to determine if a mine pool will form and if there may be a pollutional discharge, but there is a lack of a science-based method for determining the hydrologic response to mining. This thesis sought to address the gap in prediction by expanding previously explored parameters of mine pool formation in post-SMCRA mines through expanding previous multivariate statistical analyses. Analyses were done in both the Unscrambler X and Neuroshell. An algorithm produced in Neuroshell, an artificial neural network program, resulted in the least amount of error and was incorporated into a tool for modeling post-mining potentiometric head elevation through ArcGIS Pro model building function. The predictive tool developed in ArcGIS Pro was made to output points of predicted post-mining water levels. The tool only requires input of data that would be required for an underground mine permit application. This work has continued the work of an ongoing project to provide mine companies and regulators with a predictive ArcGIS tool that determines if a mine pool will form and discharge to the surface. This project’s final output is an empirically predictive ArcGIS tool that is publicly available for download to be used as a new approach to science-based estimation of underground mining effects on area hydrology. Methods used to develop both the algorithm and the tool in ArcGIS Pro can be used in other coal bearing regions around the world to develop a similarly useful tool for understanding connections between hydrology and underground mining.
Natalie Kruse (Committee Chair)
Dina Lopez (Committee Member)
Gaurav Sinha (Committee Member)
Daniel Che (Committee Member)
186 p.
Environmental Engineering; Environmental Geology; Environmental Management; Environmental Science; Environmental Studies; Geographic Information Science; Geography; Geological; Geology; Hydrologic Sciences; Hydrology; Information Science; Mining; Natural Resource Management; Water Resource Management
acid mine drainage; mine pools; prediction methods; modeling; gis; geographic information systems

Recommended Citations

Citations

  • Steinberg, R. M. (2019). Predicting Post-Mining Hydrologic Effects of Underground Coal Mines in Ohio through Multivariate Statistical Analyses and GIS Tool Building [Master's thesis, Ohio University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1555429886192267

    APA Style (7th edition)

  • Steinberg, Rebecca. Predicting Post-Mining Hydrologic Effects of Underground Coal Mines in Ohio through Multivariate Statistical Analyses and GIS Tool Building. 2019. Ohio University, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1555429886192267.

    MLA Style (8th edition)

  • Steinberg, Rebecca. "Predicting Post-Mining Hydrologic Effects of Underground Coal Mines in Ohio through Multivariate Statistical Analyses and GIS Tool Building." Master's thesis, Ohio University, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1555429886192267

    Chicago Manual of Style (17th edition)

ohiou1555429886192267
121
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This open access ETD is published by Ohio University and OhioLINK.