Vegetation in eastern Inner Mongolia grasslands plays an important role in preventing desertification, but mineral exploration has negative effects on the vegetation of these regions. In this study, the changing trend types of vegetation in eastern Inner Mongolia were analyzed using the normalized difference vegetation index (NDVI) time series from the Global Inventory Modeling and Mapping Studies (GIMMS) NDVI 3g dataset from 1982 to 2015. Meanwhile, changing trend and influencing factors of 25 large-scale mining areas before and after mining were explored with the methods of trend line, residual calculation, and correlation analysis. The vegetation coverage towards increasing in eastern Inner Mongolia decreased in the order of Tongliao > Hinggan League > Chifeng > Hulunbuir > Xilingol over the past 34 years. Vegetation showed a decreasing tendency in 40% mining areas, but an increasing tendency in 60% mining areas after mining. Vegetation change in Shengli No. 1 had a significant correlation with precipitation and human activities after mining. Except Shengli No. 1, an obvious correlation was found between vegetation change and precipitation in 45.83% mining areas after mining. Human activities had significant positive effects on vegetation growth in 25% mining areas. Significant negative effects of human activities were found in 8.34% mining areas, causing the vegetation degradation. However, there were 20.83% mining areas with vegetation changes not affected by precipitation and human activities.

Accurate runoff forecasting is of great significance for the optimization of water resource management and regulation. Given such a challenge, a novel compound approach combining time-varying filtering-based empirical mode decomposition (TVFEMD), sample entropy (SE)-based subseries recombination, and the newly developed deep sequential structure incorporating convolutional neural network (CNN) into a gated recurrent unit network (GRU) is proposed for monthly runoff forecasting. Firstly, the runoff series is disintegrated into a collection of subseries adopting TVFEMD, considering the volatility of runoff series caused by complex environmental and human factors. The subseries recombination strategy based on SE and recombination criterion is employed to reconstruct the subseries possessing the approximate complexity. Subsequently, the newly developed deep sequential structure based on CNN and GRU (CNNGRU) is applied to predict all the preprocessed subseries. Eventually, the predicted values obtained above are aggregated to deduce the ultimate prediction results. To testify to the efficiency and effectiveness of the proposed approach, eight relevant contrastive models were applied to the monthly runoff series collected from Baishan reservoir, where the experimental results demonstrated that the evaluation metrics obtained by the proposed model achieved an average index decrease of 44.35% compared with all the contrast models.

The gas permeability and mechanical properties of coal, which are seriously influenced by mining-induced stress evolution and gas pressure conditions, are key issues in coal mining and enhanced coalbed methane recovery. To obtain a comprehensive understanding of the effects of mining-induced stress conditions and gas pressures on the mechanical behavior and permeability evolution of coal, a series of mining-induced stress unloading experiments at different gas pressures were conducted. The test results are compared with the results of conventional triaxial compression tests also conducted at different gas pressures, and the different mechanisms between these two methods were theoretically analyzed. The test results show that under the same mining-induced stress conditions, the strength of the coal mass decreases with increasing gas pressure, while the absolute deformation of the coal mass increases. Under real mining-induced stress conditions, the volumetric strain of the coal mass remains negative, which means that the volume of the coal mass continues to increase. The volumetric strain corresponding to the peak stress of the coal mass increases with gas pressure in the same mining layout simulation. However, in conventional triaxial compression tests, the coal mass volume continues to decrease and in a compressional state, and there is no obvious deformation stage that occurs during the mining-induced stress unloading tests. The theoretical and experimental analyses show that mining-induced stress unloading and gas pressure changes greatly impact the deformation, failure mechanism and permeability enhancement of coal.

In order to explore the potential effects of abandoned coal mines on the water quality of Ordovician limestone aquifers, water-rock interaction simulations were conducted. After the closure of the coal mine, the karst water in the goaf area and the waste gangue had a geochemical reaction, and the above-mentioned water-rock process was simulated by an indoor static immersion experiment to explore the differences in the effect of different types of karst water on the dissolution of gangue. The basic water quality parameters pH, EC (electrical conductance), and ORP (oxidation-reduction potential) showed different trends in karst hydro-immersion solution and ultra-pure hydro-immersion solution; pH and EC had greater fluctuations in two sets of ultrapure hydro-immersion solutions, while ORP fluctuated more widely in three groups of karst hydro-immersion solutions. In addition, gangue minerals dissolved more significantly in bodies of water where limestone was added. The results of chemical component clustering showed that TDS (total dissolved solids) and EC were homopolymerized in each immersion solution, and subsequent correlation analysis showed that TDS and EC clusters were more significantly affected by mineral properties in ultrapure water-immersion solutions, and more affected by dominant ions in karst water-immersion solutions.

Surface subsidence caused by underground coal mining has received wide attention due to its impact on the ecological environment. To obtain first-hand data on mining subsidence, we arranged line measurement stations in the mining area of the Weiqiang coalfield and implemented surface movement observation at its first mining working face and obtained the dynamic subsidence curve. The subsidence curves reflected the initial, active and declining stages of subsidence at each measurement point at a basic level, and were consistent with the general rule of surface subsidence. To accurately analyze the surface movement caused by coal mining, based on the probability integral method and considering the actual advancement progress of the working face, a new three-dimensional dynamic prediction model, namely the strip unit mining model, was proposed. The core assumption of this model was that the longwall mining is regarded as the result of superposition of many units of mining. Considering the influence of different mining times and periods after mining, the subsidence time function of two-time factors was introduced into the strip unit mining model, and the final formulation of the dynamic subsidence prediction of the three-dimensional surface is derived by considering the time factor. Based on the analysis of the measured data of the Weiqiang coalfield, the prediction parameters of surface movement were obtained, and the surface movement and deformation are predicted via the probability integral method. Finally, the measured surface subsidence was compared with the theoretically-predicted one. The good match showed that the parameters of the probability integral method, determined according to the measured data, meet the requirements of geological conditions and mining settings in the mining area, and the predicted subsidence curves agreed well with the field measurements, demonstrating the effectiveness of the newly-developed strip unit mining model.

In order to investigate the impact of a crushed rock shape on the storage coefficient of underground reservoirs in coal mines, statistical analysis of the shape characteristics of crushed rocks was conducted, which was followed by numerical packing tests using the rigid block model. These tests aimed to investigate the spatial structure characteristics of underground reservoir water storage space in coal mines under the influence of different shapes of crushed rock. The results demonstrated the following: (1) Crushed rock exhibits a lognormal distribution in its shape characteristic parameters at different scales with a predominant discoid shape. The shape coefficient M can be utilized as a comprehensive indicator to characterize the shape characteristics of crushed rock. (2) The average storage coefficient of crushed rock increases exponentially as the shape coefficient M increases. There is a 50.1% increase in the storage coefficient from M = 1 to 3.5. (3) The spatial structure of the water storage space exhibits self-similarity, and both the void fractal dimension and the void boundary fractal dimension increase with an increase in the shape coefficient M. (4) When comparing the non-spherical particle system with the spherical particle system, it is observed that the spherical particle system has smaller water storage space, lower connectivity among voids, and more irregular void space. In the non-spherical particle system, the water storage space becomes larger as the shape of crushed rock becomes more irregular, resulting in more irregular void space. However, there is no significant effect on void connectivity.