Semester

Spring

Date of Graduation

2025

Document Type

Thesis

Degree Type

MS

College

Statler College of Engineering and Mineral Resources

Department

Civil and Environmental Engineering

Committee Chair

Leslie Hopkinson

Committee Co-Chair

John Quaranta

Committee Member

John Quaranta

Committee Member

Nathan DePriest

Abstract

Acid Mine Drainage (AMD) remains a significant environmental challenge in coal-mining and hard rock regions like West Virginia, degrading water quality and ecosystem health. Traditional site-specific remediation efforts often prove inefficient in addressing AMD at large scale. This study explores watershed-scale restoration as a more effective solution, leveraging centralized treatment facilities and multi-source pollution management. This study will follow Multi-criteria Decision Analysis (MCDA), specifically the Analytical Hierarchy Process (AHP), to develop a structured rubric for grading watersheds. The process involves identifying critical criteria, organizing them into a hierarchy, and generating weights for clusters of criteria through collaboration with decision makers. An intensity of importance scale will be developed for each criterion, followed by scoring and finalizing the watershed’s suitability score (Al-Bayati and Al-Zubaidy, 2020).

The rubric will be applied to two watersheds in Preston County, WV: Muddy Creek and Greens Run. In 2017, West Virginia Department of Environmental Protection (WVDEP) consolidated West Virginia Department of Environmental Protection – Abandoned Mine Lands (WVDEP-AM) and West Virginia Department of Environmental Protection – Office of Special Reclamation (WVDEP-OSR) pollutant sources from Muddy Creek to a centralized treatment facility, marking the first instance of watershed-scale restoration. A retroactive analysis of Muddy Creek will thus provide a valuable baseline for comparison with future projects. In contrast, Greens Run was selected as a high-priority watershed with significant potential for future restoration efforts. By applying the rubric to both a past project and a future project, this study will both validate the tool and identify areas for refinement when dealing with less known information about the watershed.

The rubric evaluates critical factors such as water chemistry, hydrology, topography, land use, and long-term treatment feasibility. As more watershed assessments are conducted, the rubric undergoes iterative refinement to improve its applicability and effectiveness. Findings highlight the importance of scale adjustments, criterion weighting, and real-world implementation feedback in optimizing the rubric for practical decision-making. This research aims to provide policymakers and environmental agencies with a structured tool for prioritizing watershed restoration efforts, ultimately improving AMD mitigation strategies across affected landscapes.

The application of the rubric to Muddy Creek and Greens Run revealed several key insights:

  • Scoring Outcomes: Greens Run received a higher score (0.713) compared to Muddy Creek (0.622), indicating greater suitability for watershed-scale restoration under the current rubric.
  • Key Influencing Factors: While both watersheds exhibited similar levels of impairment and restoration potential, watershed size and pollutant distribution played a decisive role. Greens Run’s smaller watershed area and closely clustered pollutant sources reduced cost and logistical complexity, making it a more viable candidate for centralized treatment.
  • Data Availability and Learning Curve: Scoring Greens Run was more efficient due to experience gained from evaluating Muddy Creek, highlighting the potential for increased efficiency as the rubric is applied to more watersheds.
  • Challenges in Scoring Certain Criteria: Some criteria, such as long-term treatment cost and biological restoration, could not be fully assessed due to data limitations. Leaving these criteria blank was determined to be the best approach to maintain conservative estimations.

Download

Share

COinS