Search Results (7)

The Eastern Huang–Huai region of China is a representative mining area with a high groundwater level. High-intensity underground mining activities have not only induced land cover and land use changes (LUCC) but also significantly changed the watershed hydrological behavior. This study integrated the land use prediction model PLUS and the hydrological simulation model MIKE 21. Taking the Bahe River Watershed in Huaibei City, China, as an example, it simulated the hydrological response trends of the watershed in 2037 under different land use scenarios. The results demonstrate the following: (1) The land use predictions for each scenario exhibit significant variation. In the maximum subsidence scenario, the expansion of water areas is most pronounced. In the planning scenario, the increase in construction land is notable. Across all scenarios, the area of cultivated land decreases. (2) In the maximum subsidence scenario, the area of high-intensity waterlogging is the greatest, accounting for 31.35% of the total area of the watershed; in the planning scenario, the proportion of high-intensity waterlogged is the least, at 19.10%. (3) In the maximum subsidence scenario, owing to the water storage effect of the subsidence depression, the flood peak is conspicuously delayed and attains the maximum value of 192.3 m³/s. In the planning scenario, the land reclamation rate and ecological restoration rate of subsidence area are the highest, while the regional water storage capacity is the lowest. As a result, the total cumulative runoff is the greatest, and the peak flood value is reduced. The influence of different degrees of subsidence on the watershed hydrological behavior varies, and the coal mining subsidence area has the potential to regulate and store runoff and perform hydrological regulation. The results reveal the mechanism through which different land use scenarios influence hydrological processes, which provides a scientific basis for the territorial space planning and sustainable development of coal mining subsidence areas. Full article

Surface subsidence and water accumulation are common consequences of underground coal mining in areas with high groundwater levels, leading to waterlogged zones. Predicting the stability of these subsidence-induced water bodies is critical for effective land reclamation, yet current methods remain inadequate, particularly when mining data are limited. This study addresses this gap by introducing a new approach to evaluate the stability of subsidence waterlogging zones. We developed a novel method based on the ray model to assess waterlogging stability in coal mining areas. Rays were cast from origins at 1° intervals to measure changes in water accumulation boundaries over time, using metrics like the Expansion Ratio Index and stability duration. The proposed method was applied to the Huainan coal field, a typical mining area with high groundwater levels in China. We studied 41 subsidence water patches, selecting ray origins for each patch and constructing a total of 14,760 rays at 1° intervals. (2) Out of all effective rays, 4250 (32.6%) were identified as stable. (3) Stability analysis classified 32.6% as “stable”, 66.4% as “observation required”, and 1.6% as “expanding.” Specific reclamation suggestions include filling shallow stable areas and developing permanent projects in larger stable zones. Full article

Underground coal mining induces surface subsidence, leading to disasters such as damage to buildings and infrastructure, landslides, and surface water accumulation. Preventing and controlling disasters in subsidence areas and reutilizing land depend on understanding subsidence regularity and obtaining surface subsidence monitoring data. These data are crucial for the reutilization of regional land resources and disaster prevention and control. Subsidence hazards are also a key constraint to mine development. Recently, with the rapid advancement of UAV technology, the use of UAV photogrammetry for surface subsidence monitoring has become a significant trend in this field. The periodic imagery data quickly acquired by UAV are used to construct DEM through point cloud filtering. Then, surface subsidence information is obtained by differencing DEM from different periods. However, due to the accuracy limitations inherent in UAV photogrammetry, the subsidence data obtained through this method are characterized by errors, making it challenging to achieve high-precision ground surface subsidence monitoring. Therefore, this paper proposes a spatial domain filtering algorithm for UAV photogrammetry combined with surface deformation caused by coal mining based on the surface subsidence induced by coal mining and combined with the characteristics of the surface change. This algorithm significantly reduces random error in the differential DEM, achieving high-precision ground subsidence monitoring using UAV. Simulation and field test results show that the surface subsidence elevation errors obtained in the simulation tests are reduced by more than 50% compared to conventional methods. In field tests, this method reduced surface subsidence elevation errors by 39%. The monitoring error for surface subsidence was as low as 8 mm compared to leveling survey data. This method offers a new technical pathway for high-precision surface subsidence monitoring in mining areas using UAV photogrammetry. Full article

In order to investigate the changes in soil enzyme activity and their influencing factors in coal mining subsidence areas with high underground water levels, in this study, we collected soil samples at different depths (SL: 0–20 cm; ML: 20–40 cm; DL: 40–60 cm) in a deep coal seam subsidence area (T1), a shallow coal seam subsidence area (T2), and control non-subsidence areas (W1 and W2) in eastern China. Soil physicochemical properties and enzyme activities were determined, and the mechanism of the latter’s response to coal mining subsidence was investigated based on correlation analysis, redundancy analysis, and structural equation modeling. The results show the following: (1) In the coal mining subsidence areas, the soil pH value (pH), soil available nitrogen (AN), available phosphorus (AP), available potassium (AK), and soil organic matter (SOM) contents were lower than those in the non-subsidence areas, while the soil water content (SWC) and bulk density (BD) were higher than those in the non-subsidence areas and increased with depth. (2) The activities of soil urease (URE), sucrase (SUC), alkaline phosphatase (ALP), and catalase (CAT) gradually decreased with depth and were all lower than those in the non-subsidence areas; the largest decreases with respect to the latter were 24.33%, 18.73%, 38.89%, and 5.88%, respectively. (3) The soil nutrient environment had a highly significant and direct positive effect on enzyme activity, with AN, AP, and SOM contents having the greatest impact. (4) Soil BD had a highly significant and direct negative effect and an indirect negative effect (by affecting nutrients) on enzyme activity. The results of this study on the effects of soil physicochemical properties on enzyme activity provide a basis for the ecological restoration of mines. Full article

Predicting the height of the fractured water-conducting zone (FWCZ) can be challenging due to their significant grey characteristics and the difficulty in scientifically selecting relevant influencing factors. To address this issue, we utilized the Pearson correlation analysis method and the grey entropy correlation analysis method to identify the significant factors and their degree of correlation with the height of FWCZ. Based on this, several constructed models were optimized, and the reliability of the best regression model was verified through parameter inversion analysis. The results indicate that the spatial distribution differences of the main coal mining seams contribute to the complex and variable occurrence conditions of coal seams. This is an important factor that contributes to the significant gray characteristics in predicting the height of FWCZ in the study area. A modeling approach has been proposed for predicting the height of FWCZ. This method is based on analyzing significant factors and conducting a multi-level evaluation of the selected prediction models. The order of correlation between significant influencing factors and the height of FWCZ is as follows: comprehensive hardness of overlying rock > average thickness of sandstone > mining depth > mining height. The results of the multi-level evaluation analysis show that, when using small sample high-quality datasets, the GA-Catboost algorithm has better prediction accuracy compared to the MSR and GA-BP algorithms. The results of the parameter inversion analysis for the GA-Catboost regression prediction model indicate that within the mining height range of 2.5–5.5 m, the ratio of fractured/mining height in the main coal seams is primarily concentrated between 20.45–30.59. In addition, a prediction method was developed to determine the limiting mining height by considering water conservation in coal mining. The relevant research results can provide fundamental theoretical support for ensuring safety in underground production and protecting groundwater in mining areas. Full article

The overlapped areas of cropland and coal resources play a fundamental role in promoting economic and social progress. However, intensive mining operations in high water-level areas have brought significant spatial–temporal heterogeneity and ecological problems. From the dual dimensions of the ecosystem service value (ESV) and ecological risk (ER), it is of great significance to explore the influence characteristics of underground mining on the landscape, such as above-ground cultivated land, which is valuable to achieving regional governance and coordinated development. In this study, taking Peixian as the research area, a multiple-dimensional correlation framework was constructed based on the revised ESV and ER, integrating the grey relational degree, spatial–temporal heterogeneity, disequilibrium, and inconsistency index to explore the ESV and ER assessment and correlation characteristics from 2010 to 2020. The results show that (1) the ESV showed a high agglomerated distribution pattern in the east, with a net decrease of 13.61%. (2) The ER decreased by 78.18 and was concentrated in the western and southern regions, with overall contiguous and local agglomeration characteristics. This indicates that the ecological security of the region has improved. (3) The comprehensive grey correlation between the cultural service value and the ecological risk index was the highest. Furthermore, the spatial–temporal heterogeneity of the ESV and ER weakened, and the disequilibrium rose and then fell, indicating that the ecosystem gradually tended to be stable. The study is crucial for overlapped cropland and coal resource areas to maintain stability and sustainable development. The multivariate correlation framework provides practical value for ecosystem management and risk control. Full article

Water and land resources are important material bases of economic and social development, and their spatial patterns determine the pattern of the urban development. The development and expansion of coal-resource-based cities have introduced new societal problems, such as the overlapping of new city construction areas and underground coal resources. Underground coal mining also leads to surface subsidence, which destroys water and land resources and seriously affects the sustainable development of coal-resource-based cities. The surface subsidence area takes a long time to stabilize, and may form a large waterlogging area due to the high groundwater level, thereby increasing the difficulty of reconstructing mining subsidence areas. In this context, a scientific and complete method for reconstructing the spatial pattern of water and land resources in unstable coal mining subsidence areas within urban is proposed in this paper. This method initially predicts the surface subsidence value and then divides the subsidence area within the urban region into the waterlogging area and the non-waterlogging area according to the surface subsidence value. The waterlogging area will be renovated into a landscape lake district in the city by a series of transformation measures. Afterwards, goaf rock mass activation and surface stability evaluation analyses are performed in the non-waterlogging area. According to the evaluation results, land resources can be divided into unaffected, restricted and prohibited building areas, with each area being transformed differently. The Lv Jin Lake in Huaibei is selected as a case study, and the proposed method is applied to reconstruct its water and land resources. The original spatial pattern of the large-scale waterlogging area and abandoned land due to mining subsidence in urban areas is then reconstructed into a spatial pattern that integrates the urban landscape, scenario living and eco-tourism. Compared with traditional subsidence area management, the proposed method greatly increases the utilization value of water and land resources, improves the urban ecological environment, enhances the urban quality and effectively alleviates the problems of land shortage and human–land conflict in coal-resource-based cities. Full article