Prediction of the temporal and spatial evolution of subsidence waters in the Huainan mining area based on the CA–Markov model

Xuyang Zhang (), Xiaoyang Chen (), Yuzhi Zhou (), Yongchun Chen (), Linli Long () and Pian Hu ()
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Xuyang Zhang: Anhui University of Science and Technology
Xiaoyang Chen: Anhui University of Science and Technology
Yuzhi Zhou: Anhui University of Science and Technology
Yongchun Chen: Ping’an Coal Mining Engineering, Research Institute Co., Ltd.
Linli Long: Anhui University of Science and Technology
Pian Hu: Anhui University of Science and Technology

Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, 2025, vol. 27, issue 7, No 89, 17307-17327

Abstract: Abstract Coal mining leads to surface subsidence and accumulation of water, which is the main characteristic of high diving coal mining areas, and the long time series monitoring of coal mining subsidence water bodies can help to assess the integrated impact effects of coal mining on land, ecology and society. In this context, the present study aims to predict water bodies in the Huainan mining area over the 1989–2021 period using the Landsat remote sensing image data and decision tree classification method to investigate the annual changes in the water body areas. In addition, the standard deviation ellipse and center of gravity migration models were used to analyze the spatial heterogeneity of water bodies, while the CA-Markov and MCE-CA-Markov models were applied to predict the future trend of water bodies for 2030. The results showed (1) substantial increases in the subsided water bodies in the Huainan mining area over the 1989–2021 period, with a rapid expansion rate, particularly in the northwestern part of the study area. In addition, water bodies migrated naturally in the northwest-southeast direction from 2015 to 2021; (2) changes in the water body areas in the Huainan mining area from 1989 to 2021 estimated at 284.03 km2, based on decision tree classification, with 1989 as the base year, with an average annual changing rate of 20.23%; (3) a high degree of consistency between the actual water bodies in 2021 and those predicted for 2030 using the CA-Markov and MCE-CA-Markov models, showing substantial increases in the water body areas in 2030. The sinkhole ponding areas formed a large lake, particularly in the Guqiao, Gu Bei, Zhangji, Xieqiao, and Liu Zhuang mines, expanding continuously toward the northwest. Therefore, investigating and predicting the spatiotemporal evolution of water bodies in coal mining subsidence areas with high diving levels are of great importance for providing a scientific basis to ensure the effective ecological restoration of coal mining subsidence areas.

Keywords: NDWI; Huainan mining area; Center of gravity migration; CA-Markov; Decision tree classification (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s10668-024-04631-4

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