Subsidence Area Research Articles

Migration mechanisms of soil carbon and nitrogen element during the natural restoration process in coal mining subsidence areas

ABSTRACT Understanding the movement and alteration of carbon and nitrogen elements in soil is crucial for addressing ecological restoration in coal mining subsidence areas. However, the migration process and mechanisms of these elements during the natural restoration process remain unclear. This study analysed the fluctuating variations and formation mechanisms of TC and TN content in soil profiles at different restoration times in coal mining subsidence areas. Initially, both TC and TN contents decreased followed by an increase during the natural restoration process. Soil compaction effects, variation of C/N ratio, and soil enzyme activity were considered as predominant factors controlling carbon and nitrogen element cycles in collapsed soil profiles. This study will provide valuable insights into understanding the mechanisms behind carbon and nitrogen cycles during natural recovery while establishing a scientific basis for ecological restoration in coal mining subsidence areas.

Long-term recovery of compacted reclaimed farmland soil in coal mining subsidence area

During the reclamation process of coal mining subsidence areas, mechanical compaction hinders the rapid recovery of reclaimed mine soil (RMS) functions to their pre-mining levels. To optimize reclaimed farmland management, which can promote the recovery of compacted soils, this study aims to explore the key factors and underlying mechanisms affecting RMS recovery from a systemic perspective using complex network theory (CNT). Soil samples from reclaimed farmland at different recovery stages (0, 2, 6, 12, 16, and 22 years) and adjacent non-subsided cultivated soils (NCS) were collected at a depth of 0 ∼ 20 cm in the eastern plains mining region of China. Twenty-four soil indicators were measured, and their evolution over RMS recovery was analyzed. CNT was employed to systematically analyze the complex network relationships among these indicators, identifying key factors and underlying mechanisms affecting RMS recovery. The results indicated that compaction led to soil macroaggregate (MA) destruction, mineralization losses of organic carbon and nitrogen, reduced microbial activity, degraded soil fertility, and increased complexity and disorder in the relationships among soil indicators. Re-cultivation had a positive effect on the recovery of RMS. After 22 years of cultivation, significant improvements in soil structure were observed, with MA increasing by 30.95 % (P < 0.05). Based on this, organic carbon gradually accumulated, with soil organic carbon (SOC) increasing by 250.94 % (P < 0.05). Microbial abundance similarly improved, with total microbial biomass (TB) increasing by 123.07 % (P < 0.05). Soil fertility was also enhanced, with alkali-hydrolyzed nitrogen (AN), available phosphorus (AP), and available potassium (AK) increasing by 125.96 %, 304.84 %, and 61.90 %, respectively. However, RMS indicators and system structure remained distinct from those of the NCS. The first approximately 12 years after re-cultivation represented a critical period during which soil structure improvements drove RMS functional recovery, with a focus on MA recovery. Increasing particulate organic carbon (POC) accumulation is an effective strategy to promote aggregation in compacted RMS. Microbially mediated carbon–nitrogen cycling emerged as a crucial driver of the gradual recovery of the RMS system after re-cultivation.

Prediction method of surface subsidence induced by block caving method based on UAV oblique photogrammetry

Unmanned Aerial Vehicle (UAV) oblique photogrammetry has been extensively employed in mining, albeit predominantly for reconstructing three-dimensional scenes and detecting changes within mining sites, lacking predictive capabilities. Leveraging 3D real scene model data, this study presents a two-stage prediction model, merging the probabilistic integral method with recurrent neural network (PIMF-RNN), to mitigate the impact of internal and external factors on surface subsidence, thereby enhancing predictive accuracy. Building upon this framework, a methodology was developed to forecast the maximum surface subsidence height and affected area under the block caving method, offering crucial data support for mitigating hazards associated with this mining technique. Analysis of surface data from Pulang copper mine during 2018–2020 demonstrates a prediction accuracy of 91.47% for maximum surface subsidence height and 87.52% for subsidence area. This research expands the potential applications of UAV oblique photogrammetry techniques within mining contexts. Furthermore, it establishes a cost-effective and efficient operational procedure for predicting mine surface subsidence.

Temporal and Spatial Dynamics of Subsidence in Eastern Jharia, India

Abstract. Jharia, one of the oldest and most significant mining areas, is facing the issue of subsidence for different reasons, such as coal fires, underground mining, and soil sensitivity towards seasonal change. This paper concentrates on the subsidence analysis of the Eastern region of the Jharia Coalfield from January 2018 to January 2021. Sentinal-1 SLC SAR imagery is used for multi-image sparse point processing and generating time series. Data processing is done using SARPROZ software. Further, the PS points inside the study area are filtered, and a classification map is drawn using ArcGIS software. The yearly percentage change of different classified zones is examined. The percentage change is significant for subsiding and uplifting zones but minimal for stable zones. Different critically and highly subsiding areas are identified by overlaying the classification zones on the topographic map. The seasonal variation of cumulative displacement is also examined, and patterns are analyzed. Different regions have different sensitivity towards seasonal variation. Overall, this paper provides insightful deformation results over Eastern Jharia for 2018–2021.

Estimation of Surface Water Level in Coal Mining Subsidence Area with GNSS RTK and GNSS-IR

Ground subsidence caused by underground coalmining result in the formation of ponding water on the ground surface. Monitoring the surface water level is crucial for studying the hydrologic cycle in mining areas. In this paper, we propose a combined technique using Global Navigation Satellite System Real-Time Kinematic (GNSS RTK) and GNSS Interferometric Reflectometry (GNSS-IR) to estimate the surface water level in areas of ground subsidence caused by underground coal mining. GNSS RTK is used to measure the geodetic height of the GNSS antenna, which is then converted into the normal height using the local height anomaly model. GNSS-IR is employed to estimate the height from the water surface to the GNSS antenna (or, the reflector height). To enhance the accuracy of the reflector height estimation, a weighted average model has been developed. This model is based on the coefficient of determination of the signal fitted by the Lomb-Scargle spectrogram and can be utilized to combine the reflector height estimations derived from multiple GNSS system and band reflection signals. By subtracting the GNSS-IR reflector height from the GNSS RTK-based normal height, the proposed method-based surface water level estimation can be obtained. In an experimental campaign, a low-cost GNSS receiver was utilized for the collection of dual-frequency observations over a period of 60 days. The collected GNSS observations were used to test the method presented in this paper. The experimental campaign demonstrates a good agreement between the surface water level estimations derived from the method presented in this paper and the reference observations.

Study on the Relationship between Groundwater and Land Subsidence in Bangladesh Combining GRACE and InSAR

Due to a heavy reliance on groundwater, Bangladesh is experiencing a severe decline in groundwater storage, with some areas even facing land subsidence. This study aims to investigate the relationship between groundwater storage changes and land subsidence in Bangladesh, utilizing a combination of GRACE and InSAR technologies. To clarify this relationship from a macro perspective, the study employs GRACE data merged with GLDAS to analyze changes in groundwater storage and SBAS-InSAR technology to assess land subsidence. The Dynamic Time Warping (DTW) method calculates the similarity between groundwater storage and land subsidence time series, incorporating precipitation and land cover types into the data analysis. The findings reveal the following: (1) Groundwater storage in Bangladesh is declining at an average rate of −5.55 mm/year, with the most significant declines occurring in Rangpur, Mymensingh, and Rajshahi. Notably, subsidence areas closely match regions with deeper groundwater levels; (2) The similarity coefficient between the time series of groundwater storage and land subsidence changes exceeds 0.85. Additionally, land subsidence in different regions shows an average lagged response of 2 to 6 months to changes in groundwater storage. This study confirms a connection between groundwater dynamics and land subsidence in Bangladesh, providing essential knowledge and theoretical support for further research.

Multisource remote sensing monitoring and analyzing for land subsidence and crop growth in a coal mining area under different rainfall conditions

Coal has been crucial in driving economic development and production construction. However, the mining-induced subsidence may cause irreversible damage to the surrounding environment of vegetation growth. Meanwhile, with the worsening of global warming, the frequency and intensity of extreme water-related weather events, such as droughts and excessive rainfall, are on the rise, which leads to heightened impacts on ecosystems and agricultural production. Consequently, extreme water-related weather, the distribution of land subsidence, and its effect on vegetation have attracted significant attention. Based on the Sentinel-1 radar data and Sentinel-2 multispectral data from 2017 to 2022, the SBAS-InSAR technology, the object-oriented classification, and the Normalized Difference Vegetation Index (NDVI) were employed respectively in the study to obtain the spatial-temporal evolution of land subsidence, subsidence-induced water, and crop growth in Tiefa mining area, a representative coal mining area in Northeast China. Moreover, the relationship between land subsidence, subsidence-induced water, and vegetation change was analyzed combined with summer precipitation data. The results showed that: (1) The average cumulative subsidence of the mining area was 256.8 mm, and the subsidence area was 42.525 km2 for the six years. Among them, the heaviest subsidence reached a maximum of 380.5 mm in 2022, and the largest subsidence area was 20.109 km2 in 2017. (2) When the rainfall was excessive, the area of subsidence-induced water would increase sharply, with a proportion jumping to 9.71% from 5.37%, which indicated the subsidence would further amplify the destructive effect of excessive rainfall and waterlogging on land resources. (3) In addition to the existing water pits, ground cracks and shallow subsidence pits appeared under the influence of underground coal mining. The direct impact of ground cracks on crops was not apparent, while the effect of subsidence pits on crops under different rainfall conditions was dual character. In dry years, crops in the subsidence pits could grow better due to higher soil moisture. In wet years, crops in the subsidence pits would suffer the more severe waterlogging. The research results are of great significance for further understanding the influence of coal mining on surface vegetation in mining areas in Northeast China.

Segmentation of mining subsidence areas in D-InSAR interferometric phase images using improved UNet++ network

Segmentation of mining subsidence areas in D-InSAR interferometric phase images using improved UNet++ network

Deformation-Adapted Spatial Domain Filtering Algorithm for UAV Mining Subsidence Monitoring

Underground coal mining induces surface subsidence, leading to disasters such as damage to buildings and infrastructure, landslides, and surface water accumulation. Preventing and controlling disasters in subsidence areas and reutilizing land depend on understanding subsidence regularity and obtaining surface subsidence monitoring data. These data are crucial for the reutilization of regional land resources and disaster prevention and control. Subsidence hazards are also a key constraint to mine development. Recently, with the rapid advancement of UAV technology, the use of UAV photogrammetry for surface subsidence monitoring has become a significant trend in this field. The periodic imagery data quickly acquired by UAV are used to construct DEM through point cloud filtering. Then, surface subsidence information is obtained by differencing DEM from different periods. However, due to the accuracy limitations inherent in UAV photogrammetry, the subsidence data obtained through this method are characterized by errors, making it challenging to achieve high-precision ground surface subsidence monitoring. Therefore, this paper proposes a spatial domain filtering algorithm for UAV photogrammetry combined with surface deformation caused by coal mining based on the surface subsidence induced by coal mining and combined with the characteristics of the surface change. This algorithm significantly reduces random error in the differential DEM, achieving high-precision ground subsidence monitoring using UAV. Simulation and field test results show that the surface subsidence elevation errors obtained in the simulation tests are reduced by more than 50% compared to conventional methods. In field tests, this method reduced surface subsidence elevation errors by 39%. The monitoring error for surface subsidence was as low as 8 mm compared to leveling survey data. This method offers a new technical pathway for high-precision surface subsidence monitoring in mining areas using UAV photogrammetry.

Geo-sustainability Challenges and Remediation Strategies: A GIS-based Assessment of Sripur Coalmine Areas, West Bengal, India

This study examines the health, risk, and safety aspects of coal mining in the Sripur area, focusing on the Bhanora West Block, Asansol, West Bengal, India as one of the 14 operational mines of Eastern Coalfields Limited in Asansol. The study addresses the increasing risks of accidents, fires, and subsidence in active, ageing, and closed mines and storage yards. The study’s incorporation of field surveys, satellite imagery, and environmental data ensures that the findings are based on a well-rounded and multi-faceted dataset. The satellite imagery data (GIS and Remote Sensing) are perceived along with available literature and environmental impact compliance reports from time to time, with particular interest in the Bhanora West coal mine, both open cast and underground. The aspect, Hill shade, LULC and stream order maps of the Damodar are generated using Q-GIS, 3.28.7. The environmental clearance data, accident data, subsidence area, and landslide data are analysed. A vast area in Sripur is observed to be under subsidence, with cracks appearing even near residential areas. The flow of the Nunia nallah is nearby, and old closed mines are not adequately backfilled, so the chance of seepage cannot be neglected though regularly attended. Pneumoconiosis (CWP), a lung disease (black lung), chronic obstructive pulmonary disease (COPD), and silicosis are common in Sripur due to dust and substandard water. Effective and riskless mining extractions using proper technologies can avoid mining hazards, such as subsidence, the influx of water in underground mines, health hazards, air/water pollution, mine fire, and intact physical landscape and observing criteria of sustainable Development Goal SDG-1 SDG-3, SDG-6, SDG 12, SDG-13, and SDG 16.

Characteristics of soil moisture transport in the aeration zone of subsidence areas under the disturbance of coal seam mining

High-intensity coal mining has induced a series of ecological and environmental problems issues, including surface subsidence, the development of ground cracks, and the deterioration of vegetation. The disruption of water circulation systems induced by mining, such as perched groundwater, groundwater of aeration zone, and phreatic water, is the root cause of vegetation withering. The aeration zone serves as a crucial nexus in the process of water cycling and exerts a significant influence on soil fertility. To explore the characteristics of soil moisture transport in subsidence areas under the mining disturbance, on-site monitoring of the size and morphology characteristics of subsidence areas and ground cracks was conducted in typical mining areas in Inner Mongolia, China. Subsequently, a typical soil moisture transport model was constructed in subsidence areas, the soil moisture transport patterns under the influence of different types of subsidence and cracks were analyzed, and the influence law of soil damage on soil moisture transport in the aerated zone was clarified. The results indicate that (1) Based on the occurrence and distribution characteristics of subsidence cracks, the subsidence area can be divided into tension zone, compression zone, and neutral zone; the ground cracks are divided into permanent tension cracks and dynamic cracks. (2) The drought stress effect of soil in the subsidence area is significant. Under the influence of soil structure variation, the water-holding capacity of the soil in the subsidence area decreases, and the soil moisture dissipation is strong. The soil moisture transport rate in the aeration zone of the subsidence area is ranked as follows: tension zone > neutral zone > compression zone. (3) Ground cracks can exacerbate the soil moisture transport rate in the aeration zone. After 15 d of crack appearance, the soil moisture transport reaches a relatively stable state, and the soil moisture transport rate in the surface layer of the crack is the fastest, and the loss of soil moisture is the most significant. The crack effect is not significant beyond 100 cm from the crack. This study provides a theoretical and data support for soil and vegetation remediation in mining subsidence areas.

Simulation and prediction of land subsidence in Decheng District under the constraint of InSAR deformation information

Land subsidence, marked by a decline in surface elevation, poses a significant threat to urban infrastructure and safety. Accurate subsidence information and a reliable prediction model are crucial for prevention and control. In this study, we used persistent scatterer interferometric synthetic aperture radar (PS-InSAR) technology to obtain long-term land subsidence data and analyzed subsidence characteristics in Decheng District. By integrating hydrogeological and groundwater data, we developed a three-dimensional groundwater flow and one-dimensional compaction model through numerical simulation. Furthermore, the subsidence data monitored by PS-InSAR were used to further constrain and validate the model. The evolution trend of land subsidence under different groundwater exploitation scenarios was predicted and analyzed. The results showed that from May 2017 to December 2021, the cumulative maximum subsidence in Decheng District reached −173 mm. The subsidence area is mainly concentrated in the northern area, and its subsidence center is near Qiaoyuan Town. According to the Land Subsidence Prevention and Control Plan of Dezhou City, Shandong Province (2018–2025), we set up different groundwater mining scenarios with the goal that the rate of land subsidence in the key prevention and control area is less than 35 mm/yr in 2025.The Fluid-solid coupled model prediction analysis results indicated that a 30% reduction in groundwater exploitation is reasonable.

Soil Characteristics and Response Mechanism of the Microbial Community in a Coal–Grain Compound Area with High Groundwater Levels

Coal mining has led to escalating ecological and environmental issues in significant coal and grain production areas, posing a severe danger to food security. This study examines the disturbance patterns of soil factors and microbial communities in coal and grain production areas, and attempts to understand the impact of subsidence and water accumulation stress on soil characteristics and microbial communities in coal mining subsidence areas with high subsidence levels. Five specific regions of Zhao Gu Yi Mine, situated in Henan Province and under the ownership of Jiaozuo Coal Group, were chosen. Aside from the control group (CK), the study blocks situated in the coal mining subsidence zones consisted of perennial subsidence ponding (PSP), seasonal subsidence ponding (SSP), the neutral zone (NZ), and the horizontal deformation zone (HDZ). The soil nutrient indices and the stoichiometric properties of soil C, N, and P were assessed on the surface of each block. The organization of the soil microbial community was identified using high-throughput sequencing. The findings indicate that: 1. Substantial disparities exist in soil properties and microbial community structure between the subsidence and non-subsidence zones. The levels of soil organic mater (SOM), total nitrogen (TN), total phosphorus (TP), available nitrogen (AN), and available phosphorus (AP) all decrease to different extents in the subsidence area. Additionally, the coal mining subsidence waterlogged area exhibits higher levels compared to the coal mining subsidence non-waterlogged area. Conversely, the soil water content (SWC), C/N ratio, C/P ratio, and N/P ratio all increase to varying degrees. 2. Regarding the composition of the community, the presence of Proteobacteria is considerably greater in the non-water-logged area of coal mining subsidence (NZ, HDZ) compared to the water-logged area and control group (p &lt; 0.05). The prevalence of Firmicutes in the subsidence water area was substantially greater compared to both the subsidence non-waterlogged area and the control group (p &lt; 0.05). The prevalence of Gemmatimonadota is markedly greater in the waterlogged area of mining subsidence compared to the non-waterlogged area and CK (p &lt; 0.05). The Ascomycota population reached its highest value in the neutral zone (NZ), which was significantly greater than the values observed in the seasonal subsidence ponding (SSP) and perennial subsidence ponding (PSP) regions (p &lt; 0.05). On the other hand, the Rozellomycota population had its highest value in the SSP region, which was significantly greater than the values observed in the other regions (p &lt; 0.05). 3. The abundance and variety of soil bacteria and fungi, as well as their important populations, are associated with different levels of soil characteristics. The primary elements that influence the alteration of microbial communities are soil nutrients and soil water content. The presence of coal mine subsidence and water accumulation has a notable impact on the properties of the soil in the surrounding area. This study offers a scientific foundation for reclaiming land affected by subsidence caused by coal mining in regions where coal and grain production are the dominant industries.

Development of a subsurface monitoring system for land subsidence hazard in the Bandung basin: a laboratory prototype

Abstract Land subsidence is a global environmental hazard posed by urban area worldwide, causing degradation in environmental quality and leads to further disasters such as increased flood risk, contamination risk, and infrastructure damages. Anthropogenic causes, such as groundwater extraction and building weight, cause high land subsidence rates. The behaviour of the subsurface under the influence of anthropogenic causes must be well understood to mitigate this problem. Conventional subsurface monitoring is robust and costly. In this case, we aim to first develop a versatile and low-cost subsurface monitoring prototype for land subsidence at a laboratory scale using a model box. Methods employed were constructing an experiment model box, developing the monitoring system, and trial experiments in the laboratory. The sensors are linear vertical displacement transducer, potentiometer, water level and pressure sensors. The monitoring system uses Arduino microcontroller to convert sensors inputs to desirable outputs and a logger to record the real-time data and transmit it to personal computer in the laboratory. Land subsidence in the Gedebage area in Bandung basin was taken as a model case. The model box was filled with soil from Gedebage, Bandung. A scenario of exploitation of confined groundwater and weight of building was applied for the model case. The results show that the laboratory prototype can monitor the subsurface changes due to the applied anthropogenic forces. In the case of Bandung soil, groundwater exploitation did not immediately cause subsidence instantaneously. There is a time delay between the drawdown of groundwater level and the subsequent vertical deformation. The rate of subsidence varies spatially inside the tank, the largest is close to the pump well and surface loads. A maximum of 2.88 mm subsidence over 663 days was recorded following 1 m groundwater drawdown. This information asserts the importance of long-time monitoring in subsidence areas.

WITHDRAWN: Characterization of soil response in mining with grouting into overburden bed-separation based on similar material simulation

Revealing the response laws of soils under various mining conditions is of significance for the scientific protection of farmland in mining areas. To avoid the interference from the spatial heterogeneity of natural soil on the research results, similar simulation experiments were employed. Two models for soil responses under mining with and without grouting into overburden bed-separation were designed, and monitoring was conducted for soil quality factors (moisture content, silt and clay content, and bulk density) and surface deformation factors (subsidence, inclined, and horizontal deformation). The results indicate that it can significantly control surface subsidence in mining with grouting into overburden bed-separation, the maximum subsidence value was reduced by 66.67%, the average subsidence value of each measuring point in the main section was reduced by 78.92%, and the subsidence area was reduced by 34.68%. The coefficient of variation of soil quality factors in the mining-affected area was obviously higher than that in the control area and the initial value before mining. Compared with mining without grouting, the variation coefficient of soil quality factor under mining with grouting was reduced by 2.71-6.79%. Soil quality factors and surface deformation factors show a significant quadratic function relationship, among which horizontal deformation has the greatest influence on soil quality factors, followed by subsidence and inclination. Therefore, it can effectively control surface subsidence and protect cultivated land when mining with grouting into overburden bed-separation.

Evolution Pattern of Land Subsidence Using InSAR Time-Series Analysis in Bangkapi, Bangkok, Thailand

Subsidence in Bangkok has occurred continuously for a long time. This research applied radar satellite imagery (Sentinel-1 101 images, 2017–2022) to track land subsidence using the time series INSAR technique. The study area was in the Bang Kapi area in Bangkok, which has a high level of cumulative subsidence. The pattern of cumulative subsidence change was analyzed using the standard deviation ellipse (SDE) technique. The results showed that the Bang Kapi area had the highest cumulative subsidence in 2019 (-125.31 mm). The movement of the subsidence center changed every year in different directions with three patterns identifiable. The first pattern showed the evolution of subsidence in a northeast-southwest direction, the second pattern showed subsidence evolution in a northwest-southeast direction, and the third pattern presented evolution that did not appear to be in any specific direction. The size of the subsidence area in 2017 and 2022 increased, whereas between 2018 and 2021, the subsidence area decreased compared to other years during the research period.

Effects of coal mining disturbance on spatial and temporal distribution of soil water content in Northwest China‐based on 3D EBK model

AbstractNorthwest China is both an important coal storage base and an ecologically fragile area, and soil water content (SWC) is a key factor limiting the ecological development of Northwest China. Revealing the characteristics of spatial and temporal distribution changes of soil water content in mining areas under coal mining disturbance and the influencing mechanism is crucial for the protection of water resources in mining areas. In this study, the soil water content (depth 0–1000 cm) of a typical coal mine subsidence area in the western part of Shendong Coal Group was monitored in situ for 1 year after mining, and the absolute value, variability, and spatial distribution of soil water content were temporally analysed by combining classical statistics, 2D Ordinary Kriging and 3D Empirical Bayesian kriging spatial interpolation. sequence analysis. The results showed that the shallow SWC (0 ~ 60 cm) was distributed horizontally in bands, and gradually increased along the direction from northwest to southeast; with the increase of coal mining time, the absolute value of SWC decreased by 0.81% ~ 33.58%, and the coefficient of variation decreased and then increased, with the range of variation from 2.19% ~ 34.49%. The deep SWC (100 ~ 1000 cm) was stratified vertically and increased with soil depth, and the shallow and deeper soil moisture would gradually migrate to the middle layer under the influence of coal mining. In addition, this paper accurately portrays the three‐dimensional spatial and temporal distribution of soil water content by the 3D EBK model, which further reveals the mechanism of coal mining's influence on soil water content. This study can provide technical and data support for predicting and evaluating the potential impacts of mining activities on the water cycle, and help mining areas to formulate policies for managing and protecting water resources.

A Study on Historical Big Data Analysis of Surface Ecological Damage in the Coal Mining Area of Lvliang City Based on Two Mining Modes

Coal mining inevitably causes damage to the surface ecological environment. In response to the characteristics of multiple factors, wide scope, and long time series of surface ecological environment damage in coal mining subsidence areas, how to integrate multiple data sources and monitoring methods to achieve monitoring and trend analysis of ecological damage throughout the entire mining cycle still needs to be studied. In addition, the 110 mining method provides an innovative method for underground coal mining to reduce its surface ecological damage, but the differences in surface damage between the two mining modes and the effectiveness of the 110 method in realizing surface ecological damage-reducing mining still need to be studied in depth. Therefore, this study takes the surface ecological damage in the mining area of Lvliang City, a typical resource city in Shanxi Province, China, as the object. It establishes a four-in-one “Satellite–UAV–Ground–Underground” information monitoring method, proposes a historical big data evolution analysis method, constructs three spatial scales of historical big databases, clarifies the current situation and development trend of damage in coal mining areas in Lvliang City and explores the differences in surface ecological environment damage characteristics in coal mining areas based on the 121 and 110 mining methods. The results show that: (1) The existing coal mining subsidence area in Lvliang City is as high as 92,191.47 hectares, and it is expected to continue to increase to 130,739.55 hectares in the future 2035, with a growth rate of 41.812%, which realizes the goals of mapping the current situation, retracing the history and predicting the future of the ecological damage of the surface in Lvliang City. (2) The surface NDVI of the 110 working face is restored to the average level of the mining area faster than that of the 121 working face. The surface crack width, step displacement, length, distribution density, and surface settlement height of the 110 working face are all smaller than those of the 121 working face. It has been verified that the unique top-cutting and swelling filling effect of the 110 methods can effectively reduce the ecological damage caused by coal mining subsidence. And its widespread application can effectively realize the ecological environmental protection of the coal mine area and contribute to the high-quality development of the coal industry in Lvliang City.

Soil moisture evidence of self-restoration in coal mining subsidence area of Shendong Mining area: Cognition based on stable isotopes

The Shendong mining area is the largest coal production base in China. However, the area is dry and water scarce, and the ecological environment is fragile. Large scale mining of shallow and thick coal seam in mining area may affect surface moisture and threaten surface ecological security. In order to understand the change of soil moisture in subsidence area. The evaporation loss rate of undisturbed and subsidence soil in mining area was estimated by using water stable isotope technique. The soil particle size and moisture of undisturbed and subsidence soil were compared. The results showed that the soil particle size did not change significantly in the subsidence area, but the continuity of soil structure changed. The evaporation loss rate of soil in subsidence area is about 15 % lower than that of undisturbed soil, and the soil moisture of soil in subsidence area is about 10 % higher than that of undisturbed soil. Further, the Craig-Gordon model is more accurate than the Rayleigh model in estimating the evaporation loss of soil moisture. Our work showed that the soil structure of coal mining subsidence area becomes much looser and the loose cover formed by the surface soil is the main reason for the reduction of soil moisture evaporation. The significant increase of soil moisture will be beneficial to plant recovery and growth, and lay a water foundation for ecological self-restoration in subsidence area. This study is helpful to understand the influence of coal mining subsidence on soil and surface hydrology in arid and semi-arid areas, and has important significance for optimizing and improving the ecological reclamation model of mining areas in western China.

Research on collaborative management technology of deep multi-coal seam mining and pre-reclamation in coal-grain composite area

Subterranean coal mining results in the occurrence of surface subsidence, soil degradation, and damage to agricultural lands, which is especially severe in regions with high groundwater levels. The collaborative reclamation scheme combining surface pre-reclamation and underground mining layout optimization can effectively control the problem of damage to farmlands. Hence, it is imperative to study the collaborative management technology. The research area for this study is Jiulishan Mine, located in coal-grain composite areas with a high groundwater table. Initially, a combined UAV and USV measuring system was utilized to acquire spatial data of the proposed reclamation area. Furthermore, we examined the evolution features of the subsidence ponding related to various mining methods using FLAC3D numerical modeling. Ultimately, the ArcGIS spatial analysis module was utilized to model and calculate the reclamation volume and rate for each plan. Our findings indicate that: (1) The extent of damage caused by shallow coal seam mining includes an area of 50.67 hm2 for farmland damaged area (FDA), 31.49 hm2 for seasonal subsidence ponding (SSP), and 23.51 hm2 for perennial subsidence ponding (PSP). Additionally, the boundary subsidence values for each damaged area are 0.8 m, 1.6 m, and 2.8 m, respectively. (2) Through the optimization of deep coal seam mining designs, the spatial configuration of the subsidence basin is successfully altered, creating the necessary condition for the development of a dynamic pre-reclamation plan. (3) The reclamation rate of the optimized pre-reclamation (PR) scheme is significantly higher, ranging from 40 % to 44 %, compared to the reclamation rate of 24 % of the traditional reclamation (TR). The choice of a suitable land reclamation and ecological restoration strategy was determined by optimizing mining plans and considering the characteristics of the subsidence area. This offers empirical evidence and specialized assistance for the ecological rehabilitation of coal-grain composite areas with high groundwater levels.