Abstract
Erosion following human disturbance threatens ecosystem health and inhibits effective land use. Mountaintop removal/valley fill (MTR/VF) mined landscapes of the Appalachian Coalfields region, USA, provide a unique opportunity to quantify the geomorphic trajectory of disturbed lands. Here we assess how MTR/VF-induced changes to topography and vegetation influence spatiotemporal erosion patterns in five mined watersheds. We use landscape evolution models starting from pre- and post-MTR/VF topographic data to isolate the influence of mining-induced topographic change. We then constrain ranges of erodibility from incision depths of gully features on mine margins, and use those estimates to model the influence of vegetation recovery trends on erosion. Topographic alterations alone reduce total sediment export from mined catchments. Model runs that incorporate the disturbance and recovery of vegetation in mined watersheds show that complete vegetation recovery keeps millennial sediment export from mined catchments within the range of unmined catchments. If vegetation recovery is anything less than complete, vegetation disturbance drives greater total sediment export from mined catchments than unmined catchments. Full vegetation recovery causes sediment fluxes to decline over millennia beyond the recovery period, while watersheds without full recovery experience fluxes that increase over the same time period. Spatiotemporal erosion trends depend on 1) the extent of vegetation recovery and 2) the extent to which MTR/VF creates slope–area disequilibrium. Valley fills and mine scarps experience erosion rates several times higher than those found in the unmined landscapes. Rapid erosion of mined areas drives deposition in colluvial hollows, headwater stream valleys, and below scarps. Our experiments suggest that reclamation focused on maximizing vegetation recovery and reducing hotspots of slope–area disequilibrium would reduce MTR's influence on Appalachian watersheds both during and long after the vegetation recovery period. Insights from MTR/VF-influenced landscapes can inform mined land management as the renewable energy transition drives increased surface mining.
| Original language | English |
|---|---|
| Article number | 108985 |
| Pages (from-to) | 1-17 |
| Number of pages | 17 |
| Journal | Geomorphology |
| Volume | 446 |
| Early online date | 20 Nov 2023 |
| DOIs | |
| Publication status | Published - 1 Feb 2024 |
Bibliographical note
Funding Information:The findings and conclusions in this publication are those of the authors and should not be construed to represent any official USDA or U.S. Government determination or policy. This work was supported by the NASA Established Program to Stimulate Competitive Research, grant # 80NSSC19M0054 ( NASA West Virginia Space Grant Consortium ). SJB was supported by a Geological Society of America graduate student grant. We acknowledge time on the West Virginia University Thorny Flat high-performance computing cluster, which is supported by the NSF under MRI award # 1726534 . We thank Leslie Hopkinson, Steve Kite, Rick Landenberger, and Miles Reed for helpful discussions. Two anonymous reviewers improved the paper.
Funding Information:
The findings and conclusions in this publication are those of the authors and should not be construed to represent any official USDA or U.S. Government determination or policy. This work was supported by the NASA Established Program to Stimulate Competitive Research, grant #80NSSC19M0054 (NASA West Virginia Space Grant Consortium). SJB was supported by a Geological Society of America graduate student grant. We acknowledge time on the West Virginia University Thorny Flat high-performance computing cluster, which is supported by the NSF under MRI award #1726534. We thank Leslie Hopkinson, Steve Kite, Rick Landenberger, and Miles Reed for helpful discussions. Two anonymous reviewers improved the paper.
Publisher Copyright:
© 2023
Funding
The findings and conclusions in this publication are those of the authors and should not be construed to represent any official USDA or U.S. Government determination or policy. This work was supported by the NASA Established Program to Stimulate Competitive Research, grant # 80NSSC19M0054 ( NASA West Virginia Space Grant Consortium ). SJB was supported by a Geological Society of America graduate student grant. We acknowledge time on the West Virginia University Thorny Flat high-performance computing cluster, which is supported by the NSF under MRI award # 1726534 . We thank Leslie Hopkinson, Steve Kite, Rick Landenberger, and Miles Reed for helpful discussions. Two anonymous reviewers improved the paper. The findings and conclusions in this publication are those of the authors and should not be construed to represent any official USDA or U.S. Government determination or policy. This work was supported by the NASA Established Program to Stimulate Competitive Research, grant #80NSSC19M0054 (NASA West Virginia Space Grant Consortium). SJB was supported by a Geological Society of America graduate student grant. We acknowledge time on the West Virginia University Thorny Flat high-performance computing cluster, which is supported by the NSF under MRI award #1726534. We thank Leslie Hopkinson, Steve Kite, Rick Landenberger, and Miles Reed for helpful discussions. Two anonymous reviewers improved the paper.
Keywords
- Appalachia
- Erosion prediction
- Landscape evolution
- Post-mining erosion
- Reclamation