Abstract
Underground coal mining inevitably causes ground subsidence, especially in the coal-grain composite area with a high groundwater table (HGT) in eastern China, where mining subsidence causes waterlogging of arable land and threatens regional food security. Concurrent Mining and Reclamation (CMR) of underground coal mines emphasizes the implementation of reclamation measures in the subsidence process, so it is necessary to simulate and analyze dynamic subsidence to optimize reclamation planning. In this paper, the Guqiao coal mine, one of the HGT coal mining areas in eastern China, is used as a research area. First, the New Water Index (NWI) method and Otsu image segmentation algorithm were adopted to quantitatively analyze the spatial distribution and expansion of surface ponding caused by underground coal mining from 2008 to 2020 based on Landsat remote sensing images. Second, Fast Lagrangian Analysis of Continua in three Dimensions (FLAC3D) was used to invert the law of surface subsidence and the evolution characteristics of surface water caused by different mining schemes. Finally, each simulated mining scheme's reclamation timing, earthwork allocation, and reclamation rate were compared. The results show that: (1) the waterlogging area increases yearly with coal mining, reaching 1049 hm2 in 2020; (2) compared with the traditional reclamation (TR) rate of 32%, the reclamation rate of CMR could be increased to 65%; (3) the best mining scheme for CMR was up-warding skip mining with a reclamation duration of three years in this case. Optimization of mining schemes could control the temporal and spatial distribution of surface subsidence and determine the land reclamation plan. Meanwhile, the land use planning feedback could guide the mining scheme's design and realize sustainable land use during the mining life cycle in other similar areas.
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