Charles Merritt Shobe , Samuel J Bower, Aaron E Maxwell, Rachel Glade, Nacere M Samassi

Surface mining may be humanity's most tangible impact on Earth's surface and will become more prevalent as the energy transition progresses. Prediction of post-mining landscape change can help mitigate environmental damage, but requires understanding how mining changes geomorphic processes and variables. Here we investigate surface mining's complex influence on surface processes in a case study of mountaintop removal/valley fill (MTR/VF) coal mining in the Appalachian Coalfields, USA. The future of MTR/VF landscapes is unclear because mining's effects on geomorphic processes are poorly understood. We use geospatial analysis---leveraging the existence of pre- and post-MTR/VF elevation models---and synthesis of literature to ask how MTR/VF alters topography, hydrology, and land-surface erodibility and how these changes could be incorporated into numerical models of post-MTR/VF landscape evolution.

MTR/VF reduces slope and area--slope product, and rearranges drainage divides. Creation of closed depressions alters flow routing and casts doubt on the utility of models that assume steady flow. MTR/VF creates two contrasting hydrologic domains, one in which overland flow is generated efficiently due to a lack of infiltration capacity, and one in which waste rock deposits act as extensive subsurface reservoirs. This dichotomy creates localized hotspots of overland flow and erosion. Loss of forest cover probably reduces cohesion in near-surface soils for at least the timescale of vegetation recovery, while waste rock fills and mine soils also likely experience reduced erosion resistance. Our analysis suggests three necessary ingredients for numerical modeling of post-MTR/VF landscape change: 1) accurate routing and accumulation of unsteady overland flow and accompanying sediment across low-gradient, depression-rich, engineered landscapes, 2) separation of the landscape into cut, filled, and unmined regions, and 3) incorporation of vegetation recovery trajectories. Improved modeling of post-mining landscapes will mitigate environmental degradation from past mining and reduce the impacts of future mining that supports the energy transition.