Previous research on ecological restoration in mining areas has predominantly focused on restoration techniques, whereas in-depth investigations into the composition of raw materials for restoration and the assessment of multi-scale spatiotemporal restoration outcomes remain limited.Phyllite has been widely available, directly accessible, and free from heavy metal contamination. It is often required for the investigation into the sourcing of restoration materials and the ecological environment over multiple temporal and spatial scales in mining areas. Among them, the ecological restoration of mining areas can involve backfilling mine pits with artificial soil in the Qinling region. It is crucial to select the optimal soil-building materials. Conventional materials like coal gangue—a byproduct of mineral extraction—contain heavy metals to hinder ecological restoration. In this study, soil cultivation, potted plant, and wilting experiments were conducted to compare optimal conditions for the weathered phyllite artificial soil. Soil quality indices (soil bulk density, pH values, maximum water-holding capacity, and electrical conductivity) were calculated for each combination of weathered phyllite artificial soil. Optimal parameters were identified using variance analysis. Key variables were also determined to enhance the reliability of the optimal parameters. Furthermore, two-dimensional interpolation of biomass and germination rates was also carried out to validate the optimization. The results revealed that microbial inoculants significantly improved the physicochemical properties of weathered phyllite artificial soil. The optimal combination of treatment was 60g of straw composting agent (JG) for 60-day cultivation. The bulk density of artificial soil stabilized at an ideal range near 1.20g/cm³, with the moderate pH and electrical conductivity close to that of natural soil. Notably, the maximum water-holding capacity reached 50.87%, with a 37.93% increase over natural soil, indicating the superior water retention and drought resistance. Pot experiments further validated that this treatment group achieved the highest germination rate (92%) of Bermuda grass seed and high biomass levels. Field verification revealed that crop germination rates and growth conditions significantly outperformed in the plots with this artificial soil, compared with the control group. There was a consistent trend over all measured parameters. Specifically, the bulk density shared a progressive decrease over the cultivation period, eventually plateauing at the optimal 1.20 g/cm³ within the ideal range for root growth and water infiltration. The pH values stabilized between 6.5 and 7.2, which was a neutral to slightly acidic environment conducive to nutrient availability and microbial activity. Low electrical conductivity remained on the minimal salinity stress for plant development in restored sites. The maximum water-holding capacity of 50.87% was enhanced by 37.93% over the local natural soil. The key factor was reduced irrigation demands for seedling survival during dry periods. The pot experiments validated that the 92% germination rate was accompanied by seedling growth. Two-dimensional interpolation of biomass and germination showed that the 60g JG 60-day cultivation point also represented the peak performance. The finding can provide the preliminary theoretical support for the practical needs in ecological conservation, restoration, and sustainable ecosystems. The optimal artificial soil formula can also offer practical, effective, and locally sourced solutions to significantly accelerate the ecosystem recovery in the mining areas.

An accurate prediction of the regional crop yield is often required to simulate the plant growth process. It is very necessary to effectively capture the various environmental factors. Particularly, the soil moisture dynamics can be shaped by the rainfall variability over different seasons. Traditional crop models, like the Environmental Policy Integrated Climate (EPIC) model, have been widely used to assess crop growth, nutrient cycling, and yield formation. However, it is still lacking to represent the watershed-scale hydrological processes. The high accuracy is limited in the regions, where the water availability is highly variable and uncertain. Especially, over 80% of the apple orchards rely entirely on the natural precipitation in dryland on the Loess Plateau in Northern China. Therefore, the soil moisture availability driven by rainfall can be the major constraint on the orchard productivity and sustainability in these water-limited environments. In this study, a coupled modelling approach was developed to integrate the Soil and Water Assessment Tool (SWAT) with the EPIC model. A framework was constructed to simulate both hydrological processes and crop growth at regional scales. Extended Fourier Amplitude Sensitivity Test (E-FAST) was carried out to verify the improved model. The key parameters were then optimized, including the crop water use, water stress response, and soil carbon dynamics. The performance of the model was improved for the overall reliability of the simulation. The coupled SWAT-EPIC model was applied to a typical apple production area in Dali County, northern Shaanxi Province, China. The results revealed that the optimized model reduced the simulation error in the rainfed apple yield prediction by 38.98%, with a root mean square error (RMSE) of 2.56% and a relative RMSE (RRMSE) of approximately 9.8%. The apple yields were simulated under rainfed conditions. The interannual variations in the apple yield were closely linked to the fluctuations in the precipitation and soil moisture. Furthermore, the shallow soil moisture declined significantly in years with less than 700 mm of rainfall. The deep soil layers (6–10 m depth) increased the dry behavior, leading to the water stress that reduced the yield. In contrast, higher water productivity and more stable yields depended on moderate rainfall and better soil moisture balance. Once the cropland was converted into apple orchards, the soil organic carbon storage was enhanced by about 14.85%. A great contribution was then gained to improve soil health and climate mitigation after carbon sequestration. The findings also highlighted the long-term risk of deep soil destruction resulting from excessive water extraction by deep-rooted perennial trees. The water resource strategies were also given, including supplemental irrigation during drought years. Particularly when the annual precipitation was below 700 mm, the available soil moisture was sustained in the shallow root zones. Furthermore, mulching practices and soil moisture conservation should be employed to optimize the orchard water use efficiency for overall fruit productivity. Overall, the SWAT-EPIC coupled model can serve as an effective tool to simulate the complex interactions among rainfall, soil moisture, and apple productivity across large regions. As such, the hydrological and crop growth were integrated to optimize the water use for the long-term sustainability of the apple orchards in water-scarce environments. The finding can also provide valuable insights to assess the regional apple yield and soil carbon dynamics in the Loess Plateau.

A series of ecological and environmental issues often occur in the coal resources and large-scale exploitation activities. The Qinling Mountains have been the most vulnerable ecological areas in China. This study aims to explore the temporal and spatial evolution of mine habitat quality in the northern foot of the Qinling Mountains for regional ecological protection and sustainable development. A systematic investigation was implemented to clarify the impact of human activities on the ecological environment of mining areas under small river basins. The land use pattern was extracted from the Xiangyu mining area in the Feng River basin, according to the remote sensing images in 1985, 2002, 2010, and 2022. The InVEST model and geographical detector were used to quantitatively analyze the habitat quality and driving factors. The results showed that the land use in the Xiangyu mining area was mainly from the dry land to the forest and industrial land from 1985 to 2022, where the transfer area of forest reached 18 245 505.71 m², indicating the remarkable project performance of returning farmland to forest and grassland. Large ranges of bare and cultivated land were occupied by the development of the urban economy after 2010, where the industrial land was expanded rapidly. The habitat quality index decreased from 0.50 to 0.49, whereas, the standard deviation increased from 0.06 to 0.09, indicating the decreasing habitat quality and the ever-expanding spatial difference. Medium and low habitat quality were concentrated mainly in the areas with bare and construction land. In addition, the overall average degree of habitat degradation decreased from 0.48 to 0.47, but the rapid expansion of industrial land continued to affect the surrounding forests. There was a high spatial consistency in the distribution of habitat quality, habitat degradation, and land use patterns. The geographical detector showed that the influence degree of driving factors on habitat quality was ranked in the descending order of the land use (0.82), DEM (0.40), temperature (0.31), precipitation (0.30), population (0.29), NDVI (0.26), GDP (0.22), slope (0.12), and aspect (0.11). Among them, land use was the main cause of the fragile ecological environment. The coupled influence of natural with human factors on the ecological environment was greater than that of single factors. The interaction between land use and natural factors showed a double-factor enhancement, illustrating habitat quality was the result of natural factors and human factors. Research on mining areas should focus mainly on the land use policy and the impact of natural factors on engineering activities. Timely measures should be taken after high-intensity engineering activities, such as industrial construction and mining areas. The vegetation can be reconstructed to restore the water quality in the watershed. This finding can provide the scientific reference for the evolution of the ecological environment in similar mining areas, thus promoting the optimization of landscape patterns and the construction of ecological civilization.