Previous scholarly investigations have mainly concentrated on examining water intake, particularly within the specific domain of coal mines. Nevertheless, the scholarly discourse lacks significant research on predicting water inflow in environments with complex multi-layer mineral distributions. The Yanlong mining area is a complex mine containing coal and bauxite. Forecasting the water inflow of bauxite deposits is crucial for designing mining drainage and formulating a mining plan in a coal-bearing rock series mining area. The water inflow on the roof and floor of bauxite was studied with various numerical simulation and analytical methods (such as the big well method). The hydrogeological conceptual and numerical model of the mining area was established by the MODFLOW module in Groundwater Modeling System (GMS (7.1)) software, and the measured groundwater level was identified and verified in the model. The results show that the model average values of $R^2$, $E_{ns}$, and PBIAS are 0.86, 0.81 and 2.71, respectively, indicating that the established numerical simulation model can accurately forecast water inflow into the aquifer. Taking No. XII orebody in the eastern Songshan Mining area as an example, a virtual well group consisting of 12 wells was set up, and the numerical model forecast a water inflow of 71,500 m³/d from the Taiyuan Formation aquifer in the bauxite ore roof, which was lower than the value predicted by the large well method (72,786.66 m³/d). The numerical method predicted an average water inflow of 59,000 m³/d and a maximum water inflow of 82,600 m³/d from the Majiagou Formation in the bauxite ore floor. A dependence has been established that the numerical method estimates water inflow with accuracy. Additionally, the model predicts future mining water inflow, and also provides a standard framework for estimating inflow in similar mining conditions.

As a typical desert in the Inner Mongolia Autonomous Region, the Ulan Buh Desert has a dry climate and scarce precipitation all year round. Groundwater has become the main factor limiting the growth of vegetation in this region. It is of great significance to study the influence of groundwater depth on the spatial distribution pattern of vegetation in this region. Based on the PIE-Engine platform and using long-term time-series Landsat data, this paper analyzed the spatial–temporal distribution characteristics and trends in vegetation coverage in the Ulan Buh Desert in the last 20 years using a pixel dichotomy model and the image difference method. The Kriging interpolation method was used to interpolate the groundwater depth data from 106 monitoring wells in the Ulan Buh Desert over the past 20 years, and the spatial distribution characteristics of groundwater depth in the Ulan Buh Desert were analyzed. Finally, the correlation coefficient between changes in vegetation coverage and changes in groundwater depth was calculated. The results showed the following: (1) The vegetation coverage in the Ulan Buh Desert was higher in the periphery and lower in the center of the desert. The overall vegetation level showed an increasing trend year by year; the growth rate was 4.73%/10 years, and the overall vegetation cover showed an improving trend. (2) The overall groundwater depth in the Ulan Buh Desert was deep in the southwest and shallow in the northeast. In the past 20 years, the groundwater depth in the Ulan Buh area has become shallower, and the ecological condition has gradually improved. (3) On the whole, the vegetation coverage varied with the groundwater depth, and the shallower the groundwater depth, the greater the vegetation coverage. When the groundwater depth increased to more than 4 m, the change in the groundwater depth had a significant effect on the vegetation coverage. However, when the groundwater depth was greater than 6 m, the change in the groundwater depth had no significant effect on the change in vegetation coverage.

Malan loess is an eolian sediment in arid and semi-arid areas. It is of great significance to study the pore structure of Malan loess for its evolution, strength, and mechanical properties. In order to quantitatively characterize the absolute permeability tensor of Malan loess and to simulate the seepage process of Malan loess, this study calculated the specific yield of intact Malan loess with a homemade seepage experimental device and recorded the water flow process on the surface of Malan loess during the seepage process. Modern computed tomography was used to scan the intact Malan loess samples from Jiuzhoutai, Lanzhou (western part of the Loess Plateau, China); the specific yield of the intact loess was used as the parameter value for the threshold segmentation of the scanned image for the 3D reconstruction of the connected pore space, the solver program in AVIZO software was used to solve the absolute permeability tensor of Malan loess using the volume averaging method combined with the CT scan to reconstruct the 3D pore space, and the simulation of the seepage process was carried out. The simulation results showed that Malan loess is a highly anisotropic loess; the absolute permeability in the vertical direction is 9.02 times and 3.86 times higher than the permeability in the horizontal direction. The pore spaces are well connected in the vertical direction (forming a near-vertical arrangement of pipes) and weakly connected in the horizontal direction. In the seepage simulation, it was found that the water flows first along the vertically oriented channels and then fills the horizontally oriented pores; the absolute permeability coefficient was calculated to be 0.3482 μm². The indoor seepage experiment was consistent with the simulation experiment, which verifies the reliability of the calculated model.