Search Results (170)

The prevention and control of mine inrush water has always been a major challenge for safety. By identifying the type of water source and analyzing the real-time changes in water composition, sudden water inrush accidents can be monitored in a timely manner to avoid major accidents. This paper proposes a novel explainable machine learning model for source type identification of mine inrush water. The paper expands the original monitoring system into the XinJi No.2 Mine in Huainan Mining Area. Based on the online water composition data, using the Spearman coefficient formula, it analyzes the water chemical characteristics of different aquifers to extract key discriminant factors. Then, the Conv1D-GRU model was built to deeply connect factors for precise water source identification. The experimental results show an accuracy rate of 85.37%. In addition, focused on the interpretability, the experiment quantified the impact of different features on the model using SHAP (Shapley Additive Explanations). It provides new reference for the source type identification of mine inrush water in mine disaster prevention and control. Full article

The overtopping-induced lateral erosion breaching of tailings dams represents a critical disaster mechanism threatening structural safety, particularly in reinforced fine-grained tailings dams where erosion behaviors demonstrate pronounced water–soil coupling characteristics and material anisotropy. Through physical model tests and numerical simulations, this study systematically investigates lateral erosion failure patterns of reinforced fine-grained tailings under overtopping flow conditions. Utilizing a self-developed hydraulic initiation test apparatus, with aperture sizes of reinforced geogrids (2–3 mm) and flow rates (4–16 cm/s) as key control variables, the research elucidates the interaction mechanisms of “hydraulic scouring-particle migration-geogrid anti-sliding” during lateral erosion processes. The study revealed that compared to unreinforced specimens, reinforced specimens with varying aperture sizes (2–3 mm) demonstrated systematic reductions in final lateral erosion depths across flow rates (4–16 cm/s): 3.3–5.8 mm (15.6−27.4% reduction), 3.1–7.2 mm (12.8–29.6% reduction), 2.3–11 mm (6.9–32.8% reduction), and 2.5–11.4 mm (6.2–28.2% reduction). Smaller-aperture geogrids (2 mm × 2 mm) significantly enhanced anti-erosion performance through superior particle migration inhibition. Concurrently, a pronounced positive correlation between flow rate and lateral erosion depth was confirmed, where increased flow rates weakened particle erosion resistance and exacerbated lateral erosion severity. The numerical simulation results are in basic agreement with the lateral erosion failure process observed in model tests, revealing the dynamic process of lateral erosion in the overtopping breach of a reinforced tailings dam. These findings provide critical theoretical foundations for optimizing reinforced tailings dam design, construction quality control, and operational maintenance, while offering substantial engineering applications for advancing green mine construction. Full article

Mining activities in Pakistan’s mineral-rich provinces threaten freshwater security through groundwater depletion, contamination, and flood-induced pollution. This study develops an Inclusive Disaster Risk Reduction (IDRR) framework integrating governance, social, environmental, and technical (GSET) dimensions to holistically assess mining-induced water hazards across Balochistan, Khyber Pakhtunkhwa, and Punjab. Using GIS-based spatial risk mapping with multi-layer hydrological modeling, we combine computational analysis and participatory validation to identify vulnerability hotspots and prioritize high-risk mines. Community workshops involving women water collectors, indigenous leaders, and local experts enhanced map accuracy by translating indigenous knowledge into spatially referenced mitigation plans and integrating gender-sensitive metrics to address gendered water access disparities. Key findings reveal severe groundwater depletion, acid mine drainage, and gendered burdens near Saindak and Cherat mines. Multi-sectoral engagements secured corporate commitments for water stewardship and policy advances in inclusive governance. The framework employs four priority-ranked risk categories (Governance-Economic 15%, Social-Community 30%, Environmental 40%, Technical-Geological 15%) derived via local stakeholder collaboration, enabling context-specific interventions. Despite data limitations, the GIS-driven methodology provides a scalable model for regions facing socio-environmental vulnerabilities. The results demonstrate how community participation directly shaped village-level water management alongside GSET analysis to craft equitable risk reduction strategies. Spatially explicit risk maps guided infrastructure upgrades and zoning regulations, advancing SDG 6 and 13 progress in Pakistan. This work underscores the value of inclusive, weighted frameworks for sustainable mining–water nexus management in Pakistan and analogous contexts. Full article

The shear strength properties of ionic rare earth ore bodies are directly related to the stability of mine slopes, which provides important theoretical and engineering support for preventing geological disasters and ensuring the safe extraction of resources. This study investigates the effects of different confining pressures, leaching agent types, and MgSO₄ concentrations on the shear strength of ionic rare earth ores through triaxial shear tests. A scanning electron microscopy (SEM) analysis of post-shear mineral samples was conducted to examine the microscopic pore structure, revealing the evolution patterns of the ionic rare earth ore’s microscopic pore structure under various leaching conditions. The results show that the shear strength of the ore body varies significantly under different leaching conditions. After leaching, the shear strength values of the ore body, ranked from highest to lowest, are (NH₄)₂SO₄ > MgSO₄ > Al₂(SO₄)₃ > pure water. The (NH₄)₂SO₄ leaching group exhibited an average shear strength approximately 9.8% higher than the pure water group. When comparing the cohesion and internal friction angle of the pure water leaching group, the (NH₄)₂SO₄-leached ore body showed significantly higher cohesion and a smaller internal friction angle. In contrast, the MgSO₄ and Al₂(SO₄)₃ leaching groups demonstrated lower cohesion and higher internal friction angles. As the MgSO₄ concentration increases, the cohesion of the ore body gradually decreases, the internal friction angle increases, and the shear strength correspondingly increases. Under low-concentration MgSO₄ leaching, the number and area of pores in the ore samples initially increase and then decrease, leading to a more complex pore structure. At higher concentrations of MgSO₄, the variety of pore shapes increases and becomes more complex, pore randomness decreases, the probability entropy value decreases, and the pore distribution becomes more ordered. Full article

The prevention and control of disasters in underground mines is a key task to ensure sustainable mining production and the development of society. The disaster chain brings cascading and clustering characteristics to disasters and leads to the expansion of their impacts and losses. It brings great difficulties to disaster prevention and control. This paper focuses on the disaster chain of a non-coal underground mine. It analyzes disaster events triggered by artificial mining activities based on a literature review, expert investigation, and field research. Subsequently, it constructs a complex network model of disaster chains containing 44 disaster nodes and 136 connecting edges. Then it performed a quantitative analysis of the complex network model, and studied complex network model parameters including degree, number of subnets, intermediate centrality, node importance, average path length, edge betweenness, connectivity, and edge vulnerability. On that basis, this paper reveals that the top five key nodes of the disaster chain are surface subsidence (H4), industrial site destruction (H7), well flooding (H21), equipment damage (H8), and living area damage (H11). It also reveals that the top five key edges of the disaster chain are mine water inrush (H6)→well flooding (H21), surface subsidence (H4)→industrial site destruction (H7), underground space failure (H3)→industrial site destruction (H7), gob collapse (H2)→surface subsidence (H4), and gob collapse (H2)→landslide (H5). Finally, this paper proposes specific chain-breaking disaster mitigation measures. Implementing these actions can play a pivotal role in mitigating the impact of mine disasters, preserving lives, and sustaining regional prosperity. Full article

Understanding the coupled evolution mechanisms of stress, fracture, and seepage fields in overburden strata is critical for preventing water inrush disasters during fully mechanized mining in deep coal seams, particularly under complex hydrogeological conditions. To address this challenge, this study integrates laboratory experiments with FLAC3D numerical simulations to systematically investigate the multi-field coupling behavior in the Luotuoshan coal mine. Three types of coal rock samples—raw coal/rock (bending subsidence zone), fractured coal/rock (fracture zone), and broken rock (caved zone)—were subjected to triaxial permeability tests under varying stress conditions. The experimental results quantitatively revealed distinct permeability evolution patterns: the fractured samples exhibited a 23–48 × higher initial permeability (28.03 mD for coal, 13.54 mD for rock) than the intact samples (0.50 mD for coal, 0.21 mD for rock), while the broken rock showed exponential permeability decay (120.32 mD to 23.72 mD) under compaction. A dynamic permeability updating algorithm was developed using FISH scripting language, embedding stress-dependent permeability models (R² > 0.99) into FLAC3D to enable real-time coupling of stress–fracture–seepage fields during face advancement simulations. The key findings demonstrate four distinct evolutionary stages of pore water pressure: (1) static equilibrium (0–100 m advance), (2) fracture expansion (120–200 m, 484% permeability surge), (3) seepage channel formation (200–300 m, 81.67 mD peak permeability), and (4) high-risk water inrush (300–400 m, 23.72 mD stabilized permeability). The simulated fracture zone height reached 55 m, directly connecting with the overlying sandstone aquifer (9 m thick, 1 MPa pressure), validating field-observed water inrush thresholds. This methodology provides a quantitative framework for predicting water-conducting fracture zone development and optimizing real-time water hazard prevention strategies in similar deep mining conditions. Full article

To address the challenge of dynamic monitoring during grouting operations in coal mine fault zones under pressurized mining, this study proposes the Borehole–Tunnel Joint Resistivity Method (BTJRM). By integrating three-dimensional (3D) electrode arrays in both tunnels and boreholes with 3D resistivity inversion technology, this approach enables fully automated underground data acquisition and real-time processing, facilitating comprehensive dynamic monitoring of grout propagation. A case study was conducted on a coal mine fault grouting project, where tunnel and borehole survey lines were deployed to construct a 3D cross-monitoring network, overcoming the limitations of traditional 2D data acquisition. Finite volume method and quasi-Gauss–Newton inversion algorithms were employed to analyze dynamic resistivity variations, enhancing spatial resolution for detailed characterization of grout migration. Key findings include: (1) Grout diffusion reduced resistivity by 10%, aligning with electrical response patterns during fracture-filling stages; (2) 3D inversion reveals that grout propagates along the principal stress axis, forming a “Y”-shaped low-resistivity anomaly zone that penetrates the fault structural block and extends into roadway areas. The maximum planar and vertical displacements of grout reach 100 m and 40 m, respectively. Thirty days post-grouting, resistivity recovers by up to 22%, reflecting the electrical signature of grout consolidation; (3) This method enables 3D reconstruction of grout diffusion pathways, extends the time window for early warning of water-conducting channel development, and enhances pre-warning capabilities for grout migration. It provides a robust framework for real-time sealing control of fault strata, offering a novel dynamic monitoring technology for mine water inrush prevention. The technology can provide reliable grouting evaluation for mine disaster control engineering. Full article

In mining operations, the rock mass located between the water-conducting fault fracture zone and the waterproof protective coal column is highly susceptible to damage, which may result in sudden water inrush disasters. This paper first employs indoor experiments and on-site rock sample analysis to determine the macroscopic mechanical parameters of rocks and rock masses, as well as the microscopic mechanical parameters of block contacts. The fracture and seepage evolution mechanisms in the mining-induced rock mass adjacent to major faults were analyzed utilizing the discrete element-fluid coupling theory in Universal Distinct Element Code (UDEC). The results identified three primary pathways for water hazards caused by mining: the calculated stress field and seepage field indicated that the formation of the water-inrush channels was determined by the parameters of coal seam mining. Different waterproof protective coal columns were set up for the three geological conditions under study. Additionally, a “claw-shaped” detection and flow monitoring method has been proposed for small water-conducting faults. These findings are important and provide valuable guidance for understanding and managing water inrush hazards in mining operations near major faults. Full article

This study proposes a comprehensive model for identifying mine water inrush sources in coal mines throughout the full mining cycle, utilizing an improved whitening function and the CRITIC-weighted grey situational decision method. Traditional water source identification methods often fail to account for the dynamic changes in water sources during the mining process, which can be influenced by geological and hydrological conditions. The model integrates an exponential whitening function with the CRITIC weighting approach to address the high variability and correlations between variables. Through the analysis of 244 groundwater samples from the Sunan mining area, the model demonstrated significant improvements in accuracy across different mining stages. The results showed overall classification accuracies exceeding 85%, indicating the model’s effectiveness in providing real-time early warnings for water hazards. This model not only optimizes traditional methods but also offers a robust tool for dynamic water source identification, thereby supporting safer and more efficient coal mining operations. Full article

During the development of coal resources in China, mine bed-separation water damage has become a new type of disaster in recent years, bringing severe casualties and economic losses to mining areas. This study aims to solve the limitations of the existing bed-separation calculation methods. It proposes a new method of bed-separation discrimination based on the bending deflection of rock strata and a spatial volumetric calculation model that considers the development stage of bed separation. The improved stepwise comparison combination method (ISCCM) was combined with the theory of thin elastic plates to determine the developmental stage of the bed separation, which was able to predict the location of the bed separation and its volume more accurately. An example analysis of the 21301 working face in Cui mu Coal Mine, Shaanxi Province, shows that the proposed method exhibits higher accuracy and reliability in predicting the location of bed-separation development and the water inrush risk. The study shows that changes in the morphology of bed-separation development significantly affect the amount of water accumulation, and the traditional calculation method may produce a significant error after long-distance coal mining. This research result helps to improve the early warning ability and management effect of water damage in the mine bed separation. It provides technical support for the safe and efficient production of the mine. Full article

Emergency water release from underground reservoirs is characterized by its suddenness and significant harm. The quantitative prediction of water spreading processes in mine tunnels is crucial for enhancing underground safety. The study focuses on an underground roadway in a coal mine, constructing a three-dimensional physical model of the complex tunnel network to explore the spatiotemporal characteristics of water flow spreading after water release in coal mine tunnels. The Volume of Fluid (VOF) model of the Eulerian multiphase flow was adopted to simulate the flow state of water in the roadway. The results indicate that after water release from the reservoir, water flows along the tunnel network towards locations with relatively lower altitude terrain. During the initial stage of water release, sloping tunnels act as barriers to water spreading. The water level height at each point in the tunnel network generally experiences three developmental stages: rapid rise, slow increase, and stable equilibrium. The water level height in the tunnel area near the water release outlet rises sharply within a time range of 550 s; tunnels farther from the water release outlet experience a rapid rise in water level height only after 13,200 s. The final stable equilibrium water level in the tunnel depends on the location of the water release outlet and the relative height of the terrain, with a water level height ranging from 0.3 to 3.3 m. The maximum safe evacuation time for personnel within a radius of 300 m from the drainage outlet is only 1 h. In contrast, areas farther away from the drainage location benefit from the water storage capacity of the complex tunnel network and have significantly extended evacuation opportunities. Full article

The transition from open pit to underground mining intensifies water-related hazards such as Acid Mine Drainage (AMD), groundwater contamination, and aquifer depletion, threatening ecological and socio-economic sustainability. This study develops an Inclusive Disaster Risk Reduction (IDRR) framework using a Multi-Dimensional Risk (MDR) approach to holistically assess water hazards in China’s mining regions, integrating environmental, social, governance, economic, technical, community-based, and technological dimensions. A Multi-Criteria Decision-Making (MCDM) model combining the Fuzzy Analytic Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) evaluates risks, enhanced by a Z-number Fuzzy Delphi AHP (ZFDAHP) spatiotemporal model to dynamically weight hazards across temporal (short-, medium-, long-term) and spatial (local to global) scales. Applied to the Sijiaying Iron Mine, AMD (78% severity) and groundwater depletion (72% severity) emerge as dominant hazards exacerbated by climate change impacts (36.3% dynamic weight). Real-time IoT monitoring systems and AI-driven predictive models demonstrate efficacy in mitigating contamination, while gender-inclusive governance and community-led aquifer protection address socio-environmental gaps. The study underscores the misalignment between static regulations and dynamic spatiotemporal risks, advocating for Lifecycle Assessments (LCAs) and transboundary water agreements. Policy recommendations prioritize IoT adoption, carbon–water nexus incentives, and Indigenous knowledge integration to align mining transitions with Sustainable Development Goals (SDGs) 6 (Clean Water), 13 (Climate Action), and 14 (Life Below Water). This research advances a holistic strategy to harmonize mineral extraction with water security, offering scalable solutions for global mining regions facing similar ecological and governance challenges. Full article

Large reservoir-induced landslides pose a persistent threat to the safety of the Three Gorges Project and the Yangtze River shipping channel. A comprehensive multi-field monitoring system has been established to observe potential landslide areas within the Three Gorges Reservoir Area. The tasks of effectively utilizing these extensive datasets and exploring the underlying correlation among various monitoring objects have become critical for understanding landslide movement patterns, assessing stability, and informing disaster prevention measures. This study focuses on the No. 1 riverside sliding mass of the Huangtupo landslide, a representative large-scale landslide in the Three Gorges Area. We specifically analyze the deformation characteristics at multiple monitoring points on the landslide surface and within underground tunnels. The analysis reveals a progressive increase in deformation rates from the rear to the front and from west to east. Representative monitoring points were selected from the front, middle, and rear sections of the landslide, along with four hydrological factors, including two reservoir water factors and two rainfall factors. These datasets were classified using the K-means clustering algorithm, while the FP-Growth algorithm was employed to uncover correlations between landslide deformation and hydrological factors. The results indicate significant spatial variability in the impacts of reservoir water levels and rainfall on the sliding mass. Specifically, reservoir water levels influence the overall deformation of the landslide, with medium-to-low water levels (146.32 to 163.23 m) or drawdowns (−18.70 to −2.16 m/month) accelerating deformation, whereas high water levels (165.37 to 175.10 m) or rising water levels (4.45 to 17.33 m/month) tend to mitigate it. In contrast, rainfall has minimal effects on the front of the landslide but significantly impacts the middle and rear areas. Given that landslide deformation is primarily driven by periodic fluctuations in reservoir water levels at the front, the movement pattern of the landslide is identified as retrogressive. The association rules derived from this study were validated using field monitoring data, demonstrating that the data mining method, in contrast to traditional statistical methods, enables the faster and more intuitive identification of reservoir-induced landslide deformation patterns and underlying mechanisms within extensive datasets. Full article

Bed-separation water hazards are a common and very harmful mining disaster in the mining areas of western China in recent years, which seriously threatens the safe mining of rich and thick coal seam resources in the West. The Yonglong mining area has become a high-risk area for bed-separation water hazards due to its particularly thick coal seams and strong water-rich overlying strata. In view of this, this paper investigates the development height of a water-flowing fractured zone in the fully mechanized caving mining of an ultra-thick coal seam in the Yonglong mining area, the evolution law of the bed separation of overlying strata, and the process of water inrush from a bed separation. Based on the measured water-flowing fractured zone height data of the Yonglong mining area and several surrounding mines, a water-flowing fractured zone height prediction formula suitable for the geological conditions of the Yonglong mining area was fitted. By using discrete element numerical simulation and laboratory similarity simulation, the evolution law of overlying strata separation under the conditions of fully mechanized caving mining in the study area was analyzed, and the space was summarized into “four zones, three arches, and five zones”. Through the stress-seepage coupling simulation of the water inrush process of the roof separation in the fully mechanized caving mining of an ultra-thick coal seam, the migration, accumulation, and sudden inrush of water in the aquifer in overlying strata under the influence of mining were analyzed, and the variation in the pore water pressure in the process of water inrush during coal seam mining separation was summarized. The pore water pressure in the overlying strata showed a trend of first decreasing, then increasing, and, finally, stabilizing. Combined with the height, water inrush volume, and water-rich zoning characteristics of the water-flowing fractured zone of the 1012007 working face of the Yuanzigou Coal Mine, the danger of water inrush from the overlying strata separation of the working face was evaluated. It is believed that it has the conditions for the formation of water accumulation and separation, and the risk of water inrush is high. Prevention and control measures need to be taken on site to ensure mining safety. The research results have important guiding significance for the assessment and prevention of water inrush hazards in overlying strata during fully mechanized longwall top-coal caving of ultra-thick coal seams with similar geological conditions worldwide. Full article

Monitoring river systems is crucial for understanding and managing water resources, predicting natural disasters, and maintaining ecological balance. Assessment of heavy metal pollution derived valuable data which are critical for the environmental management and regulatory compliance of the Jukskei River. Heavy elements were evaluated in the Jukskei River for seasonal impact, potential health risks, and contamination level with concentration levels ranging from 6900 mg/kg iron (Fe) to 0.85 mg/kg cadmium (Cd) in the dry sampling season and 6900 mg/kg Fe to 0.26 mg/kg Cd in the wet season. Enrichment factor analysis indicated high contamination levels of Fe and Pb in both dry and wet seasons. Moreover, pollution indicators revealed extremely high contamination of geo-accumulation and enrichment factors in the downstream to upstream in both seasons with a mild contamination factor for mercury (Hg). Principal Component Analysis revealed anthropogenic sources of arsenic (As), Cd, and Pb due to wastewater and agricultural pesticide application while Thorium (Th), uranium (U) and Hg were attributed as a results of gold mining activities. ANOVA and Pearson correlation analysis showed a high and moderate link between As–Pb, Cd–Pd, and As–Hg, which are significantly correlated. The potential ecological risk index assessment revealed a significant impact of heavy metals on the freshwater ecosystem. Full article