Search Results (82)

Understanding how the development of large-scale coal mining bases affects river hydrochemistry is a key scientific issue in the field of water environment research. In this study, the Qingyang–Binzhou section of the Jinghe River Basin was selected as the study area, and a total of 29 water samples were collected in April 2025 from the upper to lower reaches of the coal mining base. Hydrochemical analysis, ion ratio methods, and the positive matrix factorization (PMF) model were comprehensively applied to systematically characterize the hydrochemical features and identify the pollution sources in the river under the influence of large-scale coal mining activities. The results showed that the mean concentrations of Na⁺, SO₄²⁻, Cl⁻, and total dissolved solids (TDS) in the mainstream were as high as 414 mg/L, 728 mg/L, 226 mg/L, and 1636 mg/L, respectively, reflecting a significant impact of coal mining activities on river hydrochemistry. Four spatial variation patterns were observed along the river: the first pattern was characterized by “stable in the upper reaches, sharp increase in the middle reaches, and fluctuating increase in the lower reaches,” represented by Na⁺ and SO₄²⁻; the second pattern showed “stable in the upper reaches, slight decrease in the middle reaches, and fluctuating decrease in the lower reaches,” represented by pH; the third pattern exhibited “fluctuating in the upper reaches, sharp decrease in the middle reaches, and extremely low levels in the lower reaches,” represented by NO₃⁻; and the fourth pattern was dominated by irregular variations controlled by nitrogen transformation processes, represented by NH₄⁺ and NO₂⁻. Gibbs plots and ion ratio diagrams indicated that the hydrochemistry of sites unaffected by coal mine drainage was primarily controlled by rock weathering, whereas contaminated samples shifted toward the evaporation-concentration zone and extended beyond its typical range, reflecting an “anthropogenic salinization effect” induced by the input of mine water superimposed on the arid to semi-arid climatic background. The PMF model identified three main pollution sources: coal mining and mine water discharge (48.3%), domestic sewage (30.2%), and carbonate weathering (21.5%). This study reveals the significant modification mechanism of river hydrochemistry by large-scale coal mining base development, providing a scientific basis for targeted water pollution control in the Jinghe River Basin and for water environment management in similar mining areas. Full article

Mining-induced subsidence monitoring is essential for safe coal production and ecological protection in mining areas. UAV photogrammetry has become a widely adopted technique for constructing Digital Subsidence Models (DSuM); however, multi-scale composite noise significantly limits model accuracy and parameter extraction reliability. Taking the 2S201 working face of Wangjiata Coal Mine in a western arid–semi-arid region as the study area, this study systematically investigates DSuM noise characteristics and proposes a hierarchical multi-scale denoising framework. First, subsidence value interval stratification is employed to analyze the spatial distribution of noise. Based on this analysis, a two-stage strategy is developed. In the first stage, large-scale outliers are identified and removed using an improved DBSCAN algorithm with empirically calibrated and density-adaptive parameter computation. In the second stage, small-scale mixed noise is suppressed through a curvature-adaptive multi-stage denoising method. Validation using 20 ground monitoring points demonstrates that the RMSE decreases from 154 mm to 86 mm after large-scale denoising and further to 59 mm, achieving a 61.5% overall accuracy improvement. The denoised model exhibits enhanced surface continuity, smoother deformation profiles, and clearer subsidence boundaries while preserving overall deformation trends. The proposed framework effectively improves DSuM geometric accuracy and spatial consistency, providing reliable technical support for subsidence monitoring with improved accuracy in complex mining environments. Full article

The Yellow River Basin in Inner Mongolia (YRBIM) is a typical arid—semiarid ecological transition zone highly sensitive to climate change. Using long-term Normalized Difference Vegetation Index (NDVI) data together with meteorological and land cover data, this study applied the Sen+Mann–Kendall method and path coefficient analysis to quantify the direct and indirect effects of climatic factors on vegetation coverage. The YRBIM experienced a non-significant warm–wet trend from 1998 to 2019, characterized by slight increases in precipitation and temperature with asynchronous spatial patterns. Vegetation coverage generally improved, with high coverage areas expanding by 12.66% and low coverage areas decreasing by 10.04%. Improvement occurred mainly in eastern croplands and grasslands, while degradation in the northwest coincided with urban expansion and mining. Precipitation showed a highly significant positive correlation with the NDVI at 0.7510. The direct effect of precipitation was dominant at 0.7515, while the indirect effect was negligible at 0.0005. Temperature showed a weak inhibitory effect with a comprehensive effect of 0.0302, where the indirect inhibitory effect at 0.0400 slightly exceeded the direct promotional effect at 0.0098. These response patterns were consistent across most land cover types, except in rural settlements and unused land where temperature showed a weak positive influence. This study provides a scientific basis for ecological conservation and sustainable management in arid—semiarid transition zones. Full article

With the growing demand for strategic metals and the gradual depletion of traditional metal ore deposits, coal and coal-bearing strata are regarded as potential sources of rare metals; consequently, research into the characteristics of associated elements in coal-bearing strata has become one of the primary avenues of searching for new alternative resources. To investigate the sedimentary environmental characteristics and controlling factors of the coal-bearing strata along the southern margin of the Junggar Basin, coal seams 9–15 of the Xishanyao Formation in Sulphur Gully (Early Middle Jurassic) were selected as the subject of this study. This study employed analytical techniques including industrial analysis, total sulphur analysis, X-ray powder diffraction (XRD), X-ray fluorescence spectroscopy (XRF) and inductively coupled plasma mass spectrometry (ICP-MS) to determine the mineralogical and elemental geochemical characteristics of coal samples from Seylangou mining area, specifically from coal seams 9–15 and their overlying and underlying strata. Based on analyses of elemental ratios such as Al₂O₃/TiO₂, Sr/Ba, Rb/Sr, Ni/Co and V/(Ni + V), the source of material during the deposition of this deposit was identified, and the characteristics of the depositional environment, as indicated by palaeosalinity, palaeoclimate and redox conditions, were revealed. The results indicate that the macroscopic coal-rock types of coal seams 9–15 at the Sulphur Gully Coal Mine on the southern margin of the Junggar Basin are predominantly semi-dull to dull, with small amounts of filamentous coal and lustrous coal. The average proportion of the vitrinite group in the coal is 42.75%, the inertinite group is 51.40%, and the liptinite is 2.25%. The average content of inorganic matter in the coal is 3.60%, and the average maximum reflectance of the vitrinite group is 0.651%. The coal represents a transitional stage from low-rank to medium-rank coal, corresponding to a metamorphic stage of Grade I–II. The coal is classified as a bituminous coal with medium total moisture, very low ash, medium-volatile matter, medium-to-high fixed carbon and very low sulphur. The minerals in the coal seam are predominantly kaolinite, calcite and quartz. The major elements in the ceiling of the coal seam are dominated by SiO₂, followed by Al₂O₃; the coal itself is dominated by CaO, SiO₂ and Al₂O₃; and the base plate of the coal seam is dominated by Al₂O₃. The trace elements Cs and Bi are relatively enriched in the coal seam ceiling; Sr is relatively enriched in the coal; whilst Li, Cr and other elements are highly enriched in the coal seam base plate. The source rocks of the coal and the roof consist of deposits of felsic igneous rock (dacite), whilst the source rocks of the floor consist of deposits of intermediate igneous rock (andesite). The depositional environment ranges from marine brackish water at the base to transitional slightly brackish water and then to terrestrial freshwater at the top; the depositional climate was cold and arid, and the depositional environment was oxidising. This study provides valuable insights for further research into the elemental geochemical characteristics, sediment sources and depositional environments of the Xishanyao Formation coal seams in Liuhuangou, Xinjiang. Full article

Accurately monitoring the surface stabilization of waste dumps in open-pit coal mines is critical for hazard prevention and ecological reclamation. In arid and semi-arid regions, traditional optical remote sensing vegetation indices suffer from a systematic “response lag” in assessing physical stability due to the slow establishment of pioneer vegetation. To overcome this biological limitation, this study proposes a quantitative spatiotemporal monitoring framework based on time-series Interferometric Synthetic Aperture Radar (InSAR) coherence to detect early-stage geotechnical stabilization. Using Sentinel-1 imagery of the Balongtu coal mine, a sliding-window detection algorithm was developed to capture the physical transition of surface electromagnetic scattering mechanisms from active disturbance to stable consolidation. The main findings are as follows: (1) Statistical analysis identified a critical geophysical coherence threshold of 0.15, which effectively and objectively distinguishes active dumping disturbance zones from structurally stable areas. (2) The spatiotemporal evolution dynamics of the completed dump areas from 2017 to 2023 were successfully characterized, revealing that 87.6% of the open-pit areas achieved physical stabilization within three years post-mining, with a spatial distribution highly consistent with the objective operational rule of “mining first, dumping later”. (3) Accuracy assessment using 700 spatiotemporally balanced validation points—derived through strict visual interpretation of high-resolution optical imagery—demonstrated high algorithm reliability, achieving overall accuracies (OA) of 87.57% and 90.43% at half-yearly and annual monitoring intervals, respectively. By decoupling physical surface stabilization from optical greenness, this study provides a timely abiotic precursor indicator, offering scientific, quantitative decision support for precision ecological zoning and accelerated land turnover approval in mining areas. Full article

In arid open-pit mines, rainfall-triggered slope instability presents significant risks, but quantitative thresholds are poorly defined due to limited integration of transient seepage and stability in low-permeability soils. This study fills this gap by using GeoStudio’s SEEP/W and SLOPE/W modules to simulate rainfall effects on a moderately steep-slope (51° average) limestone mine slope in Ningxia’s Kazimiao Mining Area (annual precipitation: 181.1 mm). The novelty lies in identifying a 12 h saturation window under intense rainfall (≥100 mm h⁻¹), during which pore water pressure stabilizes as soil reaches saturation, creating an “infiltration buffering effect” driven by arid soil properties (hydraulic conductivity: 2.12 × 10⁻⁴ cm s⁻¹). Results show that the factor of safety (FOS) drops sharply within 12 h (e.g., from 1.614 naturally to 1.010 at 200 mm h⁻¹) and then stabilizes, with FOS remaining >1.05 (basically stable) under rainfall intensities ≤ 50 mm h⁻¹, but drops into the less-stable range (1.00–1.05) at 100–200 mm h⁻¹, reaching marginal stability (FOS ≈ 0.98–1.02) after 24 h of extreme events, according to GB/T 32864-2016. Slope protection measures increase FOS (e.g., 2.518 naturally). These findings quantify higher instability thresholds in arid compared to humid regions, supporting regional guidelines and informing early-warning systems amid climate-related extremes. This framework enhances sustainable slope management for mines worldwide in arid–semi-arid zones. Full article

Mining-induced subsidence has significantly altered the structure of the vadose zone in coal mining areas, where soil cracks act as preferential pathways controlling water infiltration and redistribution. In this study, a Hydrus-2D dual-domain seepage model incorporating geometric parameterization of cracks was developed to simulate water migration in the vadose zone of a typical subsidence area in the Ordos Basin. The model integrates field-measured crack geometry, soil texture, and rainfall characteristics to quantitatively analyze preferential flow formation under twelve combinations of crack width, soil type, and rainfall intensity. The results show that (i) crack width dominates preferential flow behavior, with wider cracks (≥5 cm) deepening the wetting front from approximately 107 cm to 144 cm within 120 h and sustaining high conductivity after rainfall; (ii) soil texture governs infiltration pathways, as sandy soils promote deeper wetting fronts (up to 99 cm, ~40% deeper than loam) and layered soils induce interface retention or “jump” infiltration; and (iii) rainfall intensity controls infiltration depth, with storm events producing wetting fronts more than four times deeper than those under light rain. Overall, this study demonstrates the feasibility and significance of integrating crack parameterization into vadose-zone hydrological modeling using Hydrus-2D, providing a quantitative basis for understanding rapid infiltration–migration–recharge processes and supporting ecological restoration and water resource management in arid and semi-arid mining regions. Full article

Since the 2000s, Burkina Faso has experienced a rapid mining expansion with more than one hundred sites established, leading to increased waste generation often discharged untreated into the environment. Assessing water quality in these areas is therefore critical to mitigate environmental degradation and public health risks. This study develops a site-specific water quality index (WQI) for a gold mining area in Bam Province, Burkina Faso, with the objective of improving pollution monitoring and management in relation to tailing dams. Surface and groundwater samples were collected between 2021 and 2024. Physico-chemical and bacteriological analyses of groundwater sources including wells, piezometers and boreholes revealed that several parameters such as pH, turbidity, nitrates, sulphates, total iron, aluminium, arsenic, cadmium, cyanide and total and faecal coliforms exceeded international drinking water standards. Geospatial techniques were employed to identify the main contamination sources: domestic wastewater, industrial and artisanal mining and agricultural runoff. The evolution of these parameters in relation to the dynamics of soil occupation and the influence of geological structure has enabled the distinction of key parameters associated with discharges. Although individual contaminant levels were mostly moderate, their combined effects pose a significant long-term risk to ecosystems and human health. The tailored WQI is suitable for both surface water and groundwater. It provides an integrated tool for classifying and monitoring water quality in mining environments, supporting evidence-based decision making in the management of tailing dams, environmental protection and public health. Full article

Alpine permafrost plays a vital role in regional hydrology and ecology. Alpine permafrost is highly sensitive to climate change and human disturbance. The Muri area, which is located in the headwaters of the Datong River, northeast of the Tibetan Plateau, has undergone decadal mining, and the permafrost stability there has attracted substantial concerns. In order to decipher how and to what extent the permafrost in the Muri area has responded to the decadal mining in the context of climate change, daily MODIS land surface temperatures (LSTs) acquired during 2000–2024 were downscaled to 30 m × 30 m. The active layer thickness (ALT)–ground thaw index (DDT) coefficient was derived from in situ ALT measurements. An annual ALT of 30 m × 30 m spatial resolution was subsequently estimated from the downscaled LST for the Muri area using the Stefan equation. Validation of the LST and ALT showed that the root of mean squared error (RMSE) and the mean absolute error (MAE) of the downscaled LST were 3.64 °C and −0.1 °C, respectively. The RMSE and MAE of the ALT estimated in this study were 0.5 m and −0.25 m, respectively. Spatiotemporal analysis of the downscaled LST and ALT found that (1) during 2000–2024, the downscaled LST and estimated ALT delineated the spatial extent and time of human disturbance to permafrost in the Muri area; (2) human disturbance (i.e., mining and replantation) caused ALT increase without significant spatial expansion; and (3) the semi-arid climate, rough terrain, thin root zone and gappy vertical structure beneath were the major controlling factors of ALT variations. ALT, estimated in this study with a high resolution and accuracy, filled the data gaps of this kind for the Muri area. The ALT variations depicted in this study provide references for understanding alpine permafrost evolution in other areas that have been subject to human disturbance and climate change. Full article

Large-scale vegetation loss induced by surface coal mining constitutes a critical driver of regional ecological degradation. However, the applicability of existing change detection methodologies based on remote sensing within complex mining areas under diverse climatic conditions remains systematically unverified. To address this gap and reveal nationwide disturbance patterns, this study systematically evaluates the performance of two algorithms—Continuous Change Detection and Classification (CCDC) and Landsat-based Detection of Trends in Disturbance and Recovery (LandTrendr)—in identifying vegetation loss across three major climatic zones of China (the humid, semi-humid, and semi-arid zones). Based on the optimal algorithm, the vegetation loss year and loss magnitude across all of China’s surface coal mining areas from 1990 to 2020 were accurately identified, enabling the reconstruction of the comprehensive, nationwide spatio-temporal pattern of mining-induced vegetation loss over the past 30 years. The results show that: (1) CCDC demonstrated superior stability and significantly higher accuracy (OA = 0.82) than LandTrendr (OA = 0.31) in identifying loss years across all zones. (2) The cumulative vegetation loss area reached 1429.68 km², with semi-arid zones accounting for 86.76%. Temporal analysis revealed a continuous expansion of the loss area from 2003 to 2013, followed by a distinct inflection point and decline during 2014–2016 attributable to policy-driven regulations. (3) Further analysis revealed significant variations in the average magnitude of loss across different climatic zones, namely semi-arid (0.11), semi-humid (0.21), and humid (0.25). These findings underscore the imperative for region-specific restoration strategies to ensure effective conservation outcomes. This study provides a systematic quantification and analysis of long-term, nationwide evolution patterns and regional differentiation characteristics of vegetation loss induced by surface coal mining in China, offering critical support for sustainable development decision-making in balancing energy development and ecological conservation. Full article

Coal mining disturbances in semi-arid grasslands affect land surface phenology (LSP), impacting ecosystem functions, restoration target setting, and carbon sequestration; however, the magnitude and spatial extent of these disturbances and their detectability across vegetation indices (VIs), remain insufficiently constrained. We developed and applied a streamlined quantitative framework to delineate the extent and intensity of mining-induced phenological disturbance and to compare the sensitivity and stability of commonly used VIs. Using Harmonized Landsat Sentinel (HLS) surface reflectance data over the Yimin mine, we reconstructed multitemporal VI trajectories and derived phenological metrics; directional phenology gradients were used to delineate disturbance, and VI responsiveness was evaluated via mean difference (MD) and standard deviation (SD) between affected and control areas. Research findings indicate that the impact of mining extends to an area approximately four times the size of the mining site, with the start of season (SOS) in affected areas occurring about 10 days later than in unaffected areas. Responses varied markedly among VIs, with the Modified Soil-Adjusted Vegetation Index (MSAVI) exhibiting the highest spectral stability under disturbance. This framework yields an information-rich quantification of phenological impacts attributable to mining and provides operational guidance for index selection and the prioritization of restoration and environmental management in semi-arid mining landscapes. Full article

The rehabilitation of coal mine sites in semi-arid environments is a step in combating desertification. A promising rehabilitation approach involves the development of anthropic soils that can support vegetation. However, reliable soil quality indicators are needed to evaluate long-term sustainability of rehabilitation strategies. In a coal mine area in northeastern Spain, two anthropic soils (0.5 m thick) were constructed by layering fine-textured coal residues at the bottom, topped with coarse overburden materials. Chemical fertility was enhanced using combinations of semi-liquid manure (25 or 60 mm) and straw (0 or 15 Mg ha⁻¹), resulting in four treatments randomly distributed across both soil surfaces. Two abiotic indicators were selected for sustainability assessment: soil organic carbon (SOC) fractions and microstructure. Seven years after rehabilitation activities were completed, SOC fractions were analyzed. In addition, two years later, soil porosity and specific pore perimeter were also assessed in soil thin section images. The results indicated that the lower manure rate promoted more efficient SOC stabilization, evidenced by a 4–5-fold increase in specific pore perimeter at 0–5 cm depth, and lower fulvic acid content at 5–20 cm depth, compared with the higher manure rate. Micromorphological analysis proved to be a sensitive method for detecting early improvements in the physical quality of anthropic soils, highlighting the importance of adjusting manure rates for sustainable coal mine rehabilitation. Full article

Preferential flow in coal mining subsidence areas leads to shallow soil moisture loss, vegetation reducing and ecological degradation. However, the factors influencing the development of preferential flow remain unclear. This study analyzed the morphological characteristics of preferential flow using a staining tracer test in coal mining subsidence areas along the middle reaches of the Yellow River Basin. Characteristic parameters including the dye-stained area ratio, preferential flow ratio, length index, variation coefficient were comparatively evaluated under different initial soil moisture conditions. Results showed that shallow soils exhibited substrate flow, while preferential flow occurred in deeper soil layers below the matrix flow. As initial soil moisture increased, the extent of both substrate flow and preferential flow decreased. The dye-stained area ratio declined with increasing soil depth, and the relationship between dye-stained area and soil layer depth was best described by a cubic function. Higher initial soil moisture reduced maximum infiltration depth and length indices while increasing the coefficient of the stained pattern. Furthermore, a higher of initial soil water content corresponded to a lower preferential flow index. Overall, increased initial soil moisture may reduce the extent of preferential flow and the rapid infiltration of water into soil. These findings provides a basis for further hydrological studies in coal mining subsidence areas in arid and semi-arid regions and offer scientific support for ecological restoration efforts in mining areas. Full article

Land degradation is one of the significant ecological and environmental issues threatening regional sustainable development. Datong Coalfield is located in an arid and semi-arid ecologically fragile area and is also an important energy base, the mining of coal resources and natural factors have caused serious land degradation problems. Therefore, dynamic monitoring and influencing factor analysis of land degradation in the Datong Coalfield is particularly important for land degradation prevention and land reclamation in mining areas. This study focuses on the Datong Coalfield, using remote sensing technology to dynamically extract soil erosion, net primary productivity of vegetation, land desertification, soil moisture content. Based on the Analytic Hierarchy Process (AHP), a comprehensive assessment model for land degradation was constructed to analyze the spatiotemporal evolution of land degradation in the Datong Coalfield from 2000 to 2021, and the influencing factors of land degradation were explored using a geographic detector. The results indicate that (1) from 2000 to 2021, the land degradation level in Datong Coalfield changed to mild degradation and non degradation, with the mild degradation area increasing by 30.48% and the non degradation area increasing by 13.9%, and spatially expanding contiguously from localized areas outwards. (2) Over the past 21 years, the land degradation situation in Datong Coalfield predominantly showed an improving trend, accounting for 69.11%, indicating an overall positive trajectory. However, 0.54% of the area experienced significantly intensified land degradation, scattered in the eastern and southwestern parts of the Datong Coalfield, which are areas requiring focused governance efforts. (3) Vegetation and land use are the main factors affecting land degradation in Datong Coalfield. At the same time, the influence of land use has gradually increased over the years, and the influence of vegetation and land use interaction is the highest in the two-factor interaction. Full article

Soil fertility is the essential attribute of soil quality. Large-scale coal mining has led to the continuous deterioration of the fragile ecosystems in arid and semi-arid mining areas. As one of the key indicators for land ecological restoration in these coal mining regions, rapidly and accurately monitoring topsoil fertility and its spatial variation information holds significant importance for ecological restoration evaluation. This study takes Wuhai City in the Inner Mongolia Autonomous Region of China as a case study. It establishes and evaluates various soil indicator inversion models using multi-temporal Landsat8 OLI multispectral imagery and measured soil sample nutrient content data. The research constructs a comprehensive evaluation method for surface soil fertility based on multispectral remote sensing monitoring and achieves spatiotemporal variation analysis of soil fertility characteristics. The results show that: (1) The 6SV (Second Simulation of the Satellite Signal in the Solar Spectrum Vector version)-SVM (Support Vector Machine) prediction model for surface soil indicators based on Landsat8 OLI imagery achieved prediction accuracy with R² values above 0.85 for all six soil nutrient contents in the study area, thereby establishing for the first time a rapid assessment method for comprehensive topsoil fertility using multispectral remote sensing monitoring. (2) Long-term spatiotemporal evaluation of soil indicators was achieved: From 2015 to 2025, the spatial distribution of soil indicators showed certain variability, with soil organic matter, total phosphorus, available phosphorus, and available potassium contents demonstrating varying degrees of increase within different ranges, though the increases were generally modest. (3) Long-term spatiotemporal evaluation of comprehensive soil fertility was accomplished: Over the 10 years, Grade IV remained the dominant soil fertility level in the study area, accounting for about 32% of the total area. While the overall soil fertility level showed an increasing trend, the differences in soil fertility levels decreased, indicating a trend toward homogenization. Full article