Surface subsidence prediction method of backfill-strip mining in coal mining

  • Xiaojun ZhuEmail author
  • Guangli Guo
  • Hui Liu
  • Xiaoyu Yang
Original Paper


Intensive and massive coal mining causes a series of geological hazards and environmental problems, especially surface subsidence. In recent years, backfill-strip mining has been applied to control mining subsidence in order to realize sustainable development of the mining environment. To accurately predict the surface subsidence of backfill-strip mining, a prediction method of subsidence superposition of backfill-strip mining is proposed on the basis of the traditional probability integral method prediction model. In analyzing the distribution of the actual subsidence space, the surface subsidence problem of backfill-strip mining can be regarded as the superposition of surface subsidence caused by backfill mining and strip mining. Then, the appropriate prediction parameters will be chosen, and the surface subsidence caused by the backfill mining and strip mining will be predicted separately. The surface subsidence values of the backfill-strip mining are equal to the superposition subsidence values predicted by the backfill mining and strip mining prediction method at the same surface location. A similar material model and a numerical simulation model have been built to verify the feasibility and accuracy of the superposition prediction method. The comparison results of the surface subsidence values show that the superposition surface subsidence prediction method is reasonable. The average relative error of this superposition prediction method is less than 6.7%, and its accuracy is 3.9%~11.4% higher than that of the conventional prediction method. The superposition prediction method can satisfy the precision requirement of engineering applications. This study provides a scientific technical reference for safe mining engineering design and surface disaster protection for backfill-strip mining.


Backfill-strip mining Coal underground mining Surface subsidence Prediction method Probability integral method 



Financial support for this work, provided by the National Natural Science Foundation of China (51804001), the Key University Science Research Project of Anhui Province (KJ2017A038), Natural Science Foundation of Anhui Province (1808085QE147) and PhD Research Startup Foundation of Anhui University (J01003225) are gratefully acknowledged.


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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  • Xiaojun Zhu
    • 1
    • 2
    • 3
    Email author
  • Guangli Guo
    • 3
  • Hui Liu
    • 1
    • 2
  • Xiaoyu Yang
    • 4
  1. 1.Collaborative Innovation Center for Mines Environmental Remediation and Wetland Ecological SecurityAnhui UniversityHefeiPeople’s Republic of China
  2. 2.School of Resources and Environmental EngineeringAnhui UniversityHefeiPeople’s Republic of China
  3. 3.School of Environment Science and Spatial InformationChina University of Mining and TechnologyXuzhouPeople’s Republic of China
  4. 4.Department of Engineering ManagementHefei College of Finance and EconomicsHefeiPeople’s Republic of China

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