The quantitative inversion of the concentrations of water quality parameters could clarify the temporal and spatial distribution characteristic, migration, and conversion of water quality parameters. This study took the Danjiangkou Reservoir as the research object, and established an inversion model based on the reflectance of different band combinations of remote sensing analyses on Sentinel-2 images, combined with the water quality monitoring data of total nitrogen (TN) and ammonia nitrogen (NH₃-N) of the sampling sites in February 2016. The inversion results of TN and NH₃-N in 2020 were obtained, the variation of TN and NH₃-N concentrations in the reservoir area were analyzed, and the factors accounting for the variation were discussed. The results indicated that the fitting accuracy using the established model was high for both TN and NH₃-N, and R² was 0.782 for TN and 0.851 for NH₃-N, respectively, showing high predication accuracy, which could be suitable for remote sensing inversion of TN and NH₃-N concentrations in the Danjiangkou Reservoir. The NH₃-N concentration of the Danjiangkou Reservoir was in line with Class I from 2016 to 2020, while the TN concentration was between Class III and IV. The inter-annual changes indicated that the overall water quality had an upward trend. The main tributary in the northern of the Danjiangkou Reservoir had a heavy load of TN, and after entering the reservoir, the flow velocity decreased, which caused nitrogen to accumulate at the river entrance, leading to a high TN concentration. The large slope of the mountainous area cause soil erosion. The lost soil and water carried a large amount of pesticides and fertilizers, and the ground runoff carried a large amount of nitrogen into water body, which could account for the high NH₃-N concentration on the east and west sides of the southern part of the Danjiangkou Reservoir.

Due to its unique geomorphological characteristics, the loess gully region is easy to produce ground fissures under the action of coal mining, destroy the ground infrastructures, induce geological disasters, and threaten the safety of people’s lives and property. Therefore, it is particularly important to accurately obtain information about the development of mining-induced ground fissures and study their spatial-temporal evolution mechanism. Based on the 1212 working face of a mining area in Yulin City, Shaanxi Province, this paper studies the extraction method and spatial-temporal evolution mechanism of ground fissures by combining remote sensing images and field survey data. The study shows that this proposed method significantly reduces noise points and mis-extraction, and the accuracy is more than 80%, improving the extraction accuracy of ground fissures and making the process more automated. By comparing the extraction accuracy of ground fissures at different flight altitudes, we determine that the optimal flight altitude for the research area is 60 m. At the beginning of the working face mining stage, the proportion of low-density areas of ground fissures continues to increase. Some low-density areas transition into high-density areas, which is consistent with the progress of the working face advancement. After the end of the working face retreat, the width of the ground fissures tends to be evenly distributed. The mining-induced ground fissures in the Loess gully and ravine region have good self-similarity. A dynamic development model of ground fissures is constructed to reveal its formation mechanism. The research conclusions can provide a technical support for geological disaster monitoring and land ecological restoration in mining areas.

The mining area in western China is ecologically sensitive. Coal mining can cause the formation of ground fissures, leading to geological disasters and further accelerating the process of land desertification. In this study, the working face of non-coal-pillar mining in the aeolian sand area was considered as the research object. The movement and deformation law of overlying strata were investigated through field measurements, theoretical analysis, and numerical simulation, and the mechanism governing the self-healing characteristics of ground fissures was revealed. The results demonstrated that the surface angular parameters were lower. This implies that the surface movement and the degree of deformation in non-coal-pillar mining in the aeolian sand area are significant, with a large mining influence range and rapid surface subsidence speed. After the mining of the working face, the resulting failure form of the overlying rock was asymmetric. Boundary ground fissures are typically located within the boundary of the working face, and no outward expansion is primarily observed. Dynamic ground fissures have “waviness” morphological characteristics and asymmetric “M” type development characteristics. A location model as well as a development cycle model of dynamic ground fissures were established for the first time, which can be used to predict the location and period of ground fissures. Based on the motion characteristics of hinged rock block structures, the mechanical mechanism of the self-healing phenomenon of dynamic ground fissures was revealed. A partition monitoring mode of working faces without coal pillar mining was proposed for the first time, which can reduce a lot of manpower and material resources. The coal mining subsidence basin is divided into a natural restoration area and an artificial restoration area. The combination of natural restoration and artificial guidance was used to control the ground fissures and reduce the associated costs. The research conclusions can provide a basis for mining damage evaluation and ecological environment protection in the aeolian sand area.