2022
  • Non-ICIMOD publication

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Thermal Recovery of Backfilled Pit in the Gulianhe Strip Coalmine in the Hola Basin in Northern Da Xing’Anling Mountains, NE China

  • He R.
  • Li Y.
  • Jin H.
  • Wang H.
  • Jin X.
  • Zhu M.
  • Li X.
  • Huang Y.
  • Jin D.
  • Ma F.
  • Summary
In the northern Da Xing’anling Mountains in Northeast China on the southern margin of the Eastern Asia permafrost body, the ground thermal state and boreal ecological environment are sensitive to climate change and human activities. Since the 1980s, the Hola Basin here has been continuously and extensively developed. In particular, open pits and later backfilling in strip coal mining alters land–atmospheric hydrothermal exchanges in permafrost regions, leading to serious damages to the permafrost environment and boreal forest. After mining, pits need to be backfilled timely and properly for hydrothermal recovery of Xing’an permafrost and the boreal ecological environment. In this study, based on the comparative analysis of monitored ground temperatures in backfilled and undisturbed areas, influencing factors of thermal recovery after backfilling were analyzed through numerical simulations. Results show that the thermal recovery of permafrost in the backfilled area is closely related to temperature, depth, material, and soil moisture content of backfill. The warmer, finer, and thicker the backfill soils, the longer the permafrost recovery. Thermal recovery of permafrost also depends on the moisture content of backfill; the shortest recovery occurs at 15–25% in the backfilled soil moisture content. Based on numerical simulations and combined with enlightenments from features of the ecosystem-protected Xing’an permafrost in Northeast China, a composite configuration of organic soil, crush-rock layer, and proper re-vegetation measures is advised. Based on prudent regulation of heat transfer modes, this composite backfilling method can effectively cool the backfilled ground and can even possibly offset the climate warming. Copyright © 2022 He, Li, Jin, Wang, Jin, Zhu, Li, Huang, Jin and Ma.