Water

Research

12 pages, 5181 KiB

Open AccessArticle

Risk Assessment of Water Inrush from Coal Seam Roof Based on the Combined Weighting of the Geographic Information System and Game Theory: A Case Study of Dananhu Coal Mine No. 7, China

by Qingtao Liu, Jie Xu, Qiqing Wang and Wenping Li

Water 2024, 16(5), 710; https://doi.org/10.3390/w16050710 - 28 Feb 2024

Cited by 4 | Viewed by 1293

Abstract

Coal mines’ water inrush is one of the five major disasters that affect the safety of coal mine production. The assessment of coal mines’ water inrush is a prerequisite for preventing and controlling coal mines’ water inrush. To objectively and effectively evaluate the [...] Read more.

Coal mines’ water inrush is one of the five major disasters that affect the safety of coal mine production. The assessment of coal mines’ water inrush is a prerequisite for preventing and controlling coal mines’ water inrush. To objectively and effectively evaluate the risk of water inrush in the coal seam roof and overcome the shortage of single assignment methods, two methods, the analytic hierarchy process and the entropy method, are used in this paper to determine each evaluation factor’s subjective and objective consequences. Game theory is applied to obtain the combined weights of each influencing factor to make up for the lack of a single assignment method. Taking the roof of Coal Seam No. 7 in mining Areas I and II of Dananhu Coal Mine No. 7 as an example, six primary evaluation indexes are created to control water inrush in the coal seam roof. The comprehensive weights of each index is determined; a vulnerability index evaluation model is established; and the results of the water inrush risk zone in the coal seam roof of Dananhu Coal Mine No. 7 are obtained using the GIS spatial analysis function. The results show that the discriminatory effects of the zoning model have a high accuracy and can provide a reference basis for future coal seam mining control work in this mine. Full article

(This article belongs to the Special Issue The Research on Effects of Coal Mining on Groundwater Environment and System)

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15 pages, 7374 KiB

Open AccessArticle

Prediction Model of Water Abundance of Weakly Cemented Sandstone Aquifer Based on Principal Component Analysis–Back Propagation Neural Network of Grey Correlation Analysis Decision Making

by Wei Kuo, Xiaoqin Li, Yuguang Zhang, Wenping Li, Qiqing Wang and Liangning Li

Water 2024, 16(4), 551; https://doi.org/10.3390/w16040551 - 10 Feb 2024

Cited by 2 | Viewed by 1304

Abstract

At present, in the vast majority of coal mine production processes in China, the degree of hydrogeological exploration often lags behind geological exploration. The main difficulty in evaluating the water richness of coal seam top and bottom water-bearing beds is that the existing [...] Read more.

At present, in the vast majority of coal mine production processes in China, the degree of hydrogeological exploration often lags behind geological exploration. The main difficulty in evaluating the water richness of coal seam top and bottom water-bearing beds is that the existing evaluation methods often rely on less hydrogeological investigation data. How to utilize the abundant geological exploration data in the mining area to appraise the water-rich distribution of sandstone aquifers is a feasible and challenging methodology. At present, some experts and scholars have tried to use multivariate factor analysis to solve the problem of water-richness evaluation, and they have achieved certain results, but there are some shortcomings: (1) The prediction results are mostly qualitative estimations of the water-richness grade, and there is a lack of quantitative analysis of the units-inflow; and (2) at present, the more advanced prediction methods, such as the back propagation (BP) neural network model, have the disadvantages of low accuracy, requiring many iterations, and slow convergence speed. Therefore, with geological exploration data of the 1503E working face of the Yili No.1 coal mine as the basis., this paper uses grey correlation analysis to screen out the factor indexes suitable for the evaluation of the water richness of a weakly cemented sandstone aquifer, and it combines principal component analysis (PCA) with a BP neural network. Based on the selected factor indexes, a prediction model of the water richness of a weakly cemented sandstone aquifer is established. The results show that compared with the existing methods, the prediction accuracy is higher and has a certain application value. Full article

(This article belongs to the Special Issue The Research on Effects of Coal Mining on Groundwater Environment and System)

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19 pages, 6607 KiB

Open AccessArticle

Seismic Safety Analysis of Interlaminar Rock Mass in the Distributed Underground Reservoir of a Coal Mine

by Yong Zhang, Zhiguo Cao, Lujun Wang, Ersheng Zha, Shoubiao Li and Zhaofei Chu

Water 2024, 16(3), 366; https://doi.org/10.3390/w16030366 - 23 Jan 2024

Cited by 2 | Viewed by 1435

Abstract

This study focuses on the seismic safety of distributed underground reservoirs in coal mines, especially in scenarios involving the establishment of multiple reservoirs within the same mining area, spanning different coal seams. Dynamic similarity model tests and numerical simulations are employed to investigate [...] Read more.

This study focuses on the seismic safety of distributed underground reservoirs in coal mines, especially in scenarios involving the establishment of multiple reservoirs within the same mining area, spanning different coal seams. Dynamic similarity model tests and numerical simulations are employed to investigate the construction and operation of these reservoirs under extreme conditions, such as mine tremors or earthquakes. Utilizing the Daliuta coal mine underground reservoir as a case study, a similarity material model test platform is established to represent both upper and lower coal mine underground reservoirs. Stability tests are conducted on the interlayer rock mass under various levels of seismic intensity, and the safety of the interlayer rock mass at different safety distances is comparatively analyzed. Meanwhile, using the finite element method, the responses of the upper and lower coal mine underground reservoirs under different seismic intensity levels are simulated with the same conditions of model tests. Through the two types of simulations, the mechanical response and safety of the surrounding rock of the Daliuta coal mine underground reservoir under the influence of different seismic intensities are systematically analyzed, and the reasonable safety distances between the upper and lower reservoirs are obtained. This study provides a valuable scientific insight into the safe design of underground reservoir embankments in coal mines. Full article

(This article belongs to the Special Issue The Research on Effects of Coal Mining on Groundwater Environment and System)

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12 pages, 7468 KiB

Open AccessArticle

Research on the Mechanism and Evolution Law of Delayed Water Inrush Caused by Fault Activation with Mining

by Guangli Zhu, Shuli Wang, Wenquan Zhang and Baoyu Li

Water 2023, 15(24), 4209; https://doi.org/10.3390/w15244209 - 6 Dec 2023

Cited by 1 | Viewed by 1256

Abstract

Confined water inrush caused by fault activation is the main form of water disaster in deep mining. With theoretical analysis and similar simulation tests, the mechanism and evolution law of delayed water inrush caused by fault activation are revealed. At the theoretical level, [...] Read more.

Confined water inrush caused by fault activation is the main form of water disaster in deep mining. With theoretical analysis and similar simulation tests, the mechanism and evolution law of delayed water inrush caused by fault activation are revealed. At the theoretical level, the expansion and extension of the internal microstructure in the fault zone under the action of the mining stress field and seepage field are the essential causes of fault activation. Overlying strata movement and surrounding rock creep failure are the basic reasons for delayed water inrush caused by fault activation, and delayed time caused by surrounding rock creep failure is much longer than that of overlying strata movement. A similar simulation test was carried out with self-development solid–liquid coupling with similar simulation materials; the results show that delayed water inrush caused by fault activation with mining includes three stages. Micro-activation stage: Water inrush weakness point is formed because of the expansion and extension of the micro-fissure and structure at the bottom of the fault zone. Macro-activation stage: With the change in the stress of the waterproof coal pillar and surrounding rock, the micro-fissures and structures in the stress relief area and tension area of the fault zone expand and extend sharply; meanwhile, water intrudes into the interlayer stratification of the floor in the stress relief area, forming a strong laminar flow phenomenon, and cracks in the floor form and expand; finally, water-conducting channels in the fault zone and floor are formed. Water inrush stage: The waterproof coal pillar and water-resisting layer fail and are destroyed, and the first confined water inrush point is located at the junction of the waterproof coal pillar and gob floor. Full article

(This article belongs to the Special Issue The Research on Effects of Coal Mining on Groundwater Environment and System)

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14 pages, 2427 KiB

Open AccessArticle

Research on Subsidence Prediction Method of Water-Conducting Fracture Zone of Overlying Strata in Coal Mine Based on Grey Theory Model

by Jinjun Li, Zhihao He, Chunde Piao, Weiqi Chi and Yi Lu

Water 2023, 15(23), 4177; https://doi.org/10.3390/w15234177 - 2 Dec 2023

Cited by 8 | Viewed by 1548

Abstract

The development height and settlement prediction of water-conducting fracture zones caused by coal seam mining play an important role in the stability of overburden aquifers and the safety of roadways. Based on the engineering geological data of the J60 borehole in the Daliuta [...] Read more.

The development height and settlement prediction of water-conducting fracture zones caused by coal seam mining play an important role in the stability of overburden aquifers and the safety of roadways. Based on the engineering geological data of the J60 borehole in the Daliuta Coal Mine and the mining conditions of the 2⁻² coal seam, China, this study established a similar material test model of mining overburden. The deformation characteristics of overlying strata in the mining process of coal seam were studied by using distributed optical fiber sensing technology, and the development height of water flowing fractured zone was determined. According to the equidistant sampling characteristics of Brillouin optical time domain reflection technology and the principle of the grey theory model, the settlement prediction model of the water-conducting fracture zone was established. By analyzing and comparing the prediction accuracy of the GM (1, 1) model, grey progressive model, and metabolic model, the optimal method for settlement prediction of the water-conducting fracture zone was discussed. The results show that, for the metabolic model, with the increase in the number of test sets and the decrease in the number of prediction sets, the mean square error ratio c and the small error probability p of the prediction accuracy evaluation parameters display a downward trend. The accuracy is related to the sudden change in the settlement of the water-conducting fracture zone caused by the breaking of the key stratum of the overlying rock. The optimal time of test sets selected for the best settlement prediction model is 7~8, and that of prediction sets selected is 5~6. For the GM (1, 1) model and the grey progressive model, the prediction accuracy of mining overburden subsidence is grade 4, which is not suitable for settlement prediction of water-flowing fractured zones. Full article

(This article belongs to the Special Issue The Research on Effects of Coal Mining on Groundwater Environment and System)

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16 pages, 3514 KiB

Open AccessArticle

A Prediction Model of Coal Seam Roof Water Abundance Based on PSO-GA-BP Neural Network

by Xue Dai, Xiaoqin Li, Yuguang Zhang, Wenping Li, Xiangsheng Meng, Liangning Li and Yanbo Han

Water 2023, 15(23), 4117; https://doi.org/10.3390/w15234117 - 28 Nov 2023

Cited by 3 | Viewed by 1306

Abstract

With the gradual increase of coal production capacity, the issue of water hazards in coal seam roofs is increasing in prominence. Accurate and effective prediction of the water content of the roof aquifer, based on limited hydrogeological data, is critical to the identification [...] Read more.

With the gradual increase of coal production capacity, the issue of water hazards in coal seam roofs is increasing in prominence. Accurate and effective prediction of the water content of the roof aquifer, based on limited hydrogeological data, is critical to the identification of the central area of prevention and control of coal seam roof water damage and the reduction of the incidence of such accidents in coal mines. In this paper, we establish a prediction model for the water abundance of the roof slab aquifer, using a PSO-GA-BP neural network. Our model is based on five key factors: aquifer thickness, permeability coefficient, core recovery, number of sandstone and mudstone interbedded layers, and fold fluctuation. The model integrates the genetic algorithm (GA) into the particle swarm optimization (PSO) algorithm, with the particle swarm optimization algorithm serving as the primary approach. It utilizes adaptive inertia weight and quadratic optimization of the weights and thresholds of the backpropagation neural network to minimize the output error threshold for the purpose of minimizing output errors. The prediction model is applied to hydrogeology and coal mine production for the first time. The model is trained using 100 data samples collected by the Surfer 13 software. These samples help to accurately predict the unit inflow of water. The model is then compared with traditional forecasting methods such as FAHP, BP, and GA-BP neural network models to determine its efficiency. The study found that the PSO-GA-BP neural network model accurately predicts aquifer water abundance with higher precision. The root mean square error (RMSE) of the test set is determined to be 8.7 × 10⁻⁴, and the fitting result is measured at 0.9999, indicating minimal error with actual values of the sample. According to the prediction results of the test set, the water abundance capacity of the No. 7 coal mine in Hami Danan Lake is divided, and it is found that the overall difference between the results and the actual value is small, which verifies the reliability of the model. According to the results of the water abundance division, strong water abundance areas are mainly concentrated in the third-partition area. This study provides a new method for the prediction of aquifer water abundance, improves the prediction accuracy of aquifer water abundance, reduces the cost of coal mine production, and provides a scientific evaluation method and a theoretical basis for the prevention and control of water disasters in coal seam roofs. Full article

(This article belongs to the Special Issue The Research on Effects of Coal Mining on Groundwater Environment and System)

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13 pages, 3686 KiB

Open AccessArticle

Water Abundance Evaluation of Aquifer Using GA-SVR-BP: A Case Study in the Hongliulin Coal Mine, China

by Qiqing Wang, Yanbo Han, Liguo Zhao and Wenping Li

Water 2023, 15(18), 3204; https://doi.org/10.3390/w15183204 - 8 Sep 2023

Cited by 5 | Viewed by 1301

Abstract

At present, coal accounts for more than 56% of China’s primary energy consumption and will continue to dominate for a long time in the future. With the continuous expansion of the mining intensity and scale of Jurassic coal resources in Northwestern China, the [...] Read more.

At present, coal accounts for more than 56% of China’s primary energy consumption and will continue to dominate for a long time in the future. With the continuous expansion of the mining intensity and scale of Jurassic coal resources in Northwestern China, the problem of mine roof water disasters is becoming increasingly serious. The degree of harm is related to the hydrogeological structure of the overlying strata of the coal seam. Reasonable and effective prediction and evaluation of the water abundance of the coal seam roof aquifer is conducive to making scientific decisions on the prevention and control of roof water disasters, so as to achieve safe mining. In order to solve the problem of water abundance evaluation in mining areas lacking hydrological holes, taking the Hongliulin coal mine in Shennan mining area as an example, four main control factors for water abundance were selected: sandstone thickness, core recovery ratio, brittle rock thickness ratio, and flushing fluid consumption. Combined with unit water inflow and multiple factor comprehensive analysis, a back propagation (BP) artificial neural network and support vector machine regression (SVR) were introduced into water abundance evaluation. The reciprocal variance method was used to predict the measured unit water inflow. Finally, according to the “Detailed Rules for Coal Mine Water Prevention and Control”, the water abundance of aquifers was classified to verify the accuracy of the model and partition the water abundance of the study area. The results indicate that, based on the predicted results of unit water inflow, out of 37 borehole data, 22 weak water abundance holes and 15 medium water abundance holes were evaluated correctly, verifying their applicability. The study area was generally weak in water abundance, with two grades of medium and weak. The medium water abundance area was mainly located in the north and south of the study area, and the weak water abundance area was mainly located in the east and west. It can be seen that this evaluation model has certain applicability for evaluating the water abundance of coal seam roofs. It is of great significance, especially for the evaluation of water abundance in mining areas where hydrological holes are lacking. Full article

(This article belongs to the Special Issue The Research on Effects of Coal Mining on Groundwater Environment and System)

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13 pages, 663 KiB

Open AccessArticle

Assessment of the Impact of Abandoned Mine Water on Groundwater Environment

by Yuxiang Liu, Guanqun Ma, Yu Han, Yubo Wang, Cui Tang, Ning Tian, Xiaoshan Tang, Lulu Jiang, Hanyue Zuo, Yuexing Zhang, Shanlin Wang, Ao Wang, Deqiang Mao and Shiliang Liu

Water 2023, 15(14), 2649; https://doi.org/10.3390/w15142649 - 21 Jul 2023

Cited by 2 | Viewed by 2784

Abstract

The assessment of the impact of abandoned mine water on the underwater environment is critical for protecting and restoring the groundwater environment. Taking the abandoned coal mining area in the west of Zhangqiu District as the engineering background and comprehensively considering the regional [...] Read more.

The assessment of the impact of abandoned mine water on the underwater environment is critical for protecting and restoring the groundwater environment. Taking the abandoned coal mining area in the west of Zhangqiu District as the engineering background and comprehensively considering the regional groundwater chemical characteristics data during the wet and dry seasons, the main characteristics of the ions, hydrochemical types, and ion correlations of the abandoned mine water with the regional groundwater components were analyzed using mathematical statistics, correlation analysis, and Piper diagrams. An impact assessment was conducted on the water quality index values of the groundwater monitoring point. Furthermore, this research establishes an evaluation method of abandoned mine water in a regional groundwater environment based on the improved Nemero index method and matter element theory. Overall, the groundwater pH is weakly alkaline in Zhangqiu District. The groundwater Ca²⁺ is the dominant cation, while HCO₃⁻ and SO₄²⁻ are the dominant anions. The main ion concentration during the dry season is slightly greater than during the wet season. The main hydrochemical type of groundwater during the wet and dry seasons is HCO₃-Ca. In addition, there is a correlation between NO₃⁻ and F⁻, which may be caused by human activities. The groundwater environment is classified as level IV and severely polluted. Full article

(This article belongs to the Special Issue The Research on Effects of Coal Mining on Groundwater Environment and System)

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17 pages, 5791 KiB

Open AccessArticle

Microbial Community Structure, Metabolic Function, and Phenotypic Characteristics of Sediment in Deep Coal Mine Underground Environment, China

by Di Chen and Qiyan Feng

Water 2023, 15(13), 2371; https://doi.org/10.3390/w15132371 - 27 Jun 2023

Cited by 4 | Viewed by 1828

Abstract

Long-term coal mining has created unique microbial communities in deep coal mines. Revealing the microbial community structure and metabolic functions in the underground environment can contribute to a better understanding of the coal mine ecosystem. In this study, we collected underground sediment samples [...] Read more.

Long-term coal mining has created unique microbial communities in deep coal mines. Revealing the microbial community structure and metabolic functions in the underground environment can contribute to a better understanding of the coal mine ecosystem. In this study, we collected underground sediment samples from producing mines in eastern China at mining depths of −400 to −1100 m and performed high-throughput sequencing. Results showed that most of the genera in the underground sediment can degrade organic matter, such as polycyclic aromatic hydrocarbons (PAHs), benzene, toluene, and xylene, etc. The dominant genera in the underground sediment were Hydrogenophaga, Thauera, Pseudomonas, Rhodobacter, and Dietzia. Samples were divided into coal roadway (CR) and rock roadway (RR) groups according to the sampling location. The microbial community structure differed significantly (p < 0.05) between these two groups of samples, with the distribution of main genera in the CR group samples showing a negative correlation with Cu and a positive correlation with temperature. The samples from the CR and RR groups were significantly different (p < 0.05) in their metabolic functions, including membrane transport, metabolism of other amino acids, folding, sorting, and degradation. Microorganisms in the RR group samples showed high resistance to heavy metals, while microorganisms in the CR group had higher degradation functions of organic pollutants. Bugbase phenotypic predictions indicated a high potential pathogenicity of microorganisms in coal mine sediment, which was mainly contributed by the genera Hydrogenophaga, Pseudomonas, Geothermobacter, and Methylophaga, etc. This study deepens the understanding of microbial communities in deep coal mine environments; however, the organic contamination and biological health risks of underground environments require extensive attention. Full article

(This article belongs to the Special Issue The Research on Effects of Coal Mining on Groundwater Environment and System)

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22 pages, 3748 KiB

Open AccessArticle

Study of Water–Sand Inrush through a Vertical Karst Conduit Uncovered through Tunnel Excavation

by Zhenhua Zhao, Hailong Wang, Lin Han and Zhenlong Zhao

Water 2023, 15(11), 2010; https://doi.org/10.3390/w15112010 - 25 May 2023

Cited by 4 | Viewed by 1331

Abstract

The existence of karst compromises the safety of underground engineering, especially during tunnel excavations. Karst conduits are uncovered through tunnel excavations, which may lead to a water–sand inrush disaster. Taking a vertical karst conduit as an example, the process of water–sand inrush through [...] Read more.

The existence of karst compromises the safety of underground engineering, especially during tunnel excavations. Karst conduits are uncovered through tunnel excavations, which may lead to a water–sand inrush disaster. Taking a vertical karst conduit as an example, the process of water–sand inrush through a karst conduit could be viewed as being similar to the process whereby a water–sand mixture flows through the discharge opening of a storage bin. In this study, based on force analysis of a non-aqueous sand body above a karst conduit, the limiting diameter of the karst conduit under force equilibrium was obtained. Considering the effect of water on aqueous sand bodies, the criterion of water–sand inrush was established. We aimed to study water–sand migration and inrush through vertical karst conduits in order to obtain the distribution of the water pressure near a vertical karst conduit, and to explore the relationship between the conduit size, water pressure, and water–sand flow rate; therefore, a simulated testing system for analyzing water–sand inrush through a vertical karst conduit was developed. When the water pressure in the testing chamber was close to the critical head pressure of the water–sand inrush, the water–sand inrush exhibited a pattern of instability—migration—deposition—stability. When the water pressure in the testing chamber exceeded the critical head pressure, the water–sand flow increased first and then stabilized over time. With the increase in the set values of the water pressure and conduit size, the steady flow of the water–sand mixture increased gradually. When the karst conduit was opened suddenly, the actual water pressure in the testing chamber decreased significantly, due to the water–sand mixture flowing out of the testing chamber and the water supply lagging behind. With the stabilization of the water–sand flow, the actual water pressure gradually tended towards stability, but it was still lower than the initial set water pressure. When the karst conduit was opened, the values of the water pressure monitored by the pore pressure gauges all clearly decreased. With the stabilization of the water–sand flow, the water pressure gradually became stable. With the increase in the distance between the pore pressure sensor and the karst conduit, the water pressure values all increased gradually. These test results are significant for further studies of the formation mechanisms of water–sand inrush through vertical karst conduits. Full article

(This article belongs to the Special Issue The Research on Effects of Coal Mining on Groundwater Environment and System)

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13 pages, 4294 KiB

Open AccessArticle

Evaluation of Control Effect of Confined Water Hazard in Taiyuan Formation Coal Seam Mining in Huanghebei Coalfield

by Jingying Li, Qingguo Xu, Yanbo Hu and Xinmin Chen

Water 2023, 15(11), 1973; https://doi.org/10.3390/w15111973 - 23 May 2023

Cited by 2 | Viewed by 1385

Abstract

The shallow-layer resources in the Huanghebei Coalfield have been depleted, and the deep coal seam of the Taiyuan Formation (lower coal group) is the main continuous resource in mining at this stage. With the annual increase in mining depth, the exploitation of lower [...] Read more.

The shallow-layer resources in the Huanghebei Coalfield have been depleted, and the deep coal seam of the Taiyuan Formation (lower coal group) is the main continuous resource in mining at this stage. With the annual increase in mining depth, the exploitation of lower coal groups is being met with the influence of high ground stress, high water pressure, high temperature, and strong mining disturbances, as a result of which the threat of water inrush is particularly serious. Based on the grouting data of the coalface floor aquifer, this paper proposes an evaluation method for the control of water rushing into the coalface floor. By comparing the test data with mine electrical exploration data through ArcGIS, the results show that the water pressure threshold based on ArcGIS is twice the water pressure of the grouting reconstruction layer as the optimal solution. The research results can provide a reference for the prevention and control of water inrush in the lower coal group of Huanghebei Coalfield. Full article

(This article belongs to the Special Issue The Research on Effects of Coal Mining on Groundwater Environment and System)

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16 pages, 2250 KiB

Open AccessEditor’s ChoiceArticle

Contamination Characteristics and Source Identification of Groundwater in Xishan Coal Mining Area of Taiyuan Based on Hydrochemistry and Sulfur–Oxygen Isotopes

by Di Chen, Qiyan Feng and Min Gong

Water 2023, 15(6), 1169; https://doi.org/10.3390/w15061169 - 17 Mar 2023

Cited by 8 | Viewed by 3110

Abstract

Xishan mining area in Taiyuan is a typical coal industry cluster with a variety of coal-related industrial sites such as coal mines, power plants and coking plants, which seriously pollute the native ecological environment. Study of the hydrochemical characteristics and pollution sources of [...] Read more.

Xishan mining area in Taiyuan is a typical coal industry cluster with a variety of coal-related industrial sites such as coal mines, power plants and coking plants, which seriously pollute the native ecological environment. Study of the hydrochemical characteristics and pollution sources of groundwater in the area can contribute to the ecological protection and remediation of regional groundwater resources. In this study, we collected surface water and groundwater samples from the Xishan mining area and measured and analyzed hydrochemical and sulfur–oxygen isotopes. Results showed that 64.7% of groundwater in the study area exceeded the sulfate standard due to the influence of the coal industry, with some karst groundwater up to 2000 mg/L. In the runoff and discharge area of karst groundwater, the proportion of anthropogenic input of SO₄²⁻ increased, which led to the hydrochemical type of karst groundwater gradually changing from HCO₃-Ca·Mg (recharge area) to SO₄-Ca·Mg (discharge area). Results of sulfur–oxygen isotope tests indicated that the δ³⁴S_SO4 and δ₁₈O_SO4 values of samples were −10.01~24.42‰ and −4.90~12.40‰, respectively, and the sulfur–oxygen isotope values of some karst groundwater were close to the dissolved end of sulfide minerals, indicating their sulfate mainly came from the oxidation of pyrite. Sulfate sources in groundwater water were parsed using IsoSource model. Calculated results revealed that sulfate in pore groundwater mostly originated from pyrite oxidation, and karst groundwater in the recharge area was mainly influenced by atmosphere precipitation, while groundwater in the runoff and discharge areas were significantly affected by pyrite oxidation, accounting for up to 90% in some karst groundwater. Comparing the sulfur–oxygen isotope values of karst groundwater in 1989, 2016 and 2022, we found that the δ³⁴S_SO4 values in 2022 decreased significantly, which indicated the expansion of karst groundwater pollution in the Xishan mining area. This study highlights the pollution of regional groundwater by coal-related industrial agglomerations, and the groundwater pollution in the Xishan mining area requires urgent remediation and restoration. Full article

(This article belongs to the Special Issue The Research on Effects of Coal Mining on Groundwater Environment and System)

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22 pages, 10652 KiB

Open AccessArticle

Mechanism and Control of Grout Propagation in Horizontal Holes in Fractured Rock

by Zhaoxing Liu, Shuning Dong, Hao Wang and Hongbo Shang

Water 2022, 14(24), 4062; https://doi.org/10.3390/w14244062 - 12 Dec 2022

Cited by 3 | Viewed by 2117

Abstract

It is important to control grout propagation and ensure the engineering effectiveness of the advanced regional grouting process in the Middle Ordovician limestone (MOL) aquifer. In our study, we found that the physical and mechanical properties of cement grout are affected mainly by [...] Read more.

It is important to control grout propagation and ensure the engineering effectiveness of the advanced regional grouting process in the Middle Ordovician limestone (MOL) aquifer. In our study, we found that the physical and mechanical properties of cement grout are affected mainly by the water–cement ratio, followed by water glass content and finally by hydro-chemical type. In a horizontal grouting hole inclined single fracture, the grout spread over time depended on the water–cement ratio, grouting pressure, width of fracture and angle between fracture and grouting hole and the rate of spread increased over time. However, when the grout propagation length was hundreds of meters or more, the length in the fracture above the grouting hole was greater than that in the fracture below. The sensitivity sequence of influencing factors of grout propagation length in an inclined fracture of a horizontal grouting hole was as follows, from large to small: width of fracture, fracture angle, water–cement ratio, grouting pressure. Full article

(This article belongs to the Special Issue The Research on Effects of Coal Mining on Groundwater Environment and System)

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18 pages, 5415 KiB

Open AccessFeature PaperArticle

Evaluation on Development Height of Water-Conduted Fractures on Overburden Roof Based on Nonlinear Algorithm

by Qiushuang Zheng, Changfeng Wang, Weitao Liu and Lifu Pang

Water 2022, 14(23), 3853; https://doi.org/10.3390/w14233853 - 26 Nov 2022

Cited by 6 | Viewed by 1562

Abstract

Based on the support vector machine theory, the particle swarm algorithm is used to optimize parameters, combined with an analytic network process in order to feature dimensionality reduction of the original data, and a nonlinear algorithm model combining statistical analysis and machine learning [...] Read more.

Based on the support vector machine theory, the particle swarm algorithm is used to optimize parameters, combined with an analytic network process in order to feature dimensionality reduction of the original data, and a nonlinear algorithm model combining statistical analysis and machine learning analysis is established. Taking the relevant data of overlying rock from two zones in Yingpanhao Coal Mine as an example, the main factors such as rock tectonic development, coal seam dip, mining height, mining operation method and stope width are ranked according to the weights of their contribution to the development height of the two zones in order to determine the main control factors, such as stope width and mining height. Using MATLAB as the experimental platform, 16 sets of two-dimensional mine data similar to the geology of the study area were divided into training and test sets for prediction and simulation, comparing the optimal solutions of various optimization-seeking algorithms to obtain quantitative prediction results based on the nonlinear algorithm model. The kriging interpolation process was carried out by ArcGIS to realize qualitative visualization, and effective classification is carried out according to the natural breakpoint method to obtain six development height divisions of the water-conducting fracture zone in the study area. The results show that the prediction model of the development height of two zones in the coal roof based on the non-linear algorithm has better accuracy and generalization ability. Predicted by the test set, the model’s prediction result MAE is less than 10%, and the accuracy is better than the traditional empirical formula method, which makes up for its lack of rough calculation accuracy and solves the problem of not being able to locate the height of roof crack development at specific borehole locations, which has significance in guiding the prediction and prevention of roof water damage and subsidence disasters. Full article

(This article belongs to the Special Issue The Research on Effects of Coal Mining on Groundwater Environment and System)

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19 pages, 5389 KiB

Open AccessArticle

Hydrogeochemical Characteristics of a Multi-Layer Groundwater System in a Coal Mine Area: A Case Study

by Kaiqing Xu, Wei Qiao, Guanghui Zhu, Lushun Feng, Zhiwen Wang and Wenping Li

Water 2022, 14(19), 3146; https://doi.org/10.3390/w14193146 - 6 Oct 2022

Cited by 3 | Viewed by 2016

Abstract

The Yanzhou coalfield is an important coal production base in north China, wherein a huge amount of mine drainage has occurred; however, there has been relatively little research on the multi-layer groundwater system. In this study, the Dongtan Coal Mine was considered as [...] Read more.

The Yanzhou coalfield is an important coal production base in north China, wherein a huge amount of mine drainage has occurred; however, there has been relatively little research on the multi-layer groundwater system. In this study, the Dongtan Coal Mine was considered as the research object and a total of 95 samples were collected. Furthermore, hydrogeochemical and statistical methods were employed to better understand the hydrogeochemical characteristics of the groundwater system in the Yanzhou coalfield. The results show that the groundwater in the area is alkaline. The Ordovician limestone aquifer is quite different from the other aquifers, and the karst herein shows regional distribution characteristics. During the hydrogeochemical evolution of the groundwater, more carbonate and sulfate dissoluted, more cation exchanged, and a lesser extent of silicate weathering and halite dissolution occurred. A conceptual hydrogeological model was created. It shows that the changes in the drainage conditions further resulted in the water chemistry being complex, and induced the hydrogeochemical evolution. The changes in the groundwater dynamic field and the hydrochemical field should be studied to better understand the evolution of the hydrogeochemical properties and accordingly make preparations for preventing mine water disasters and environmental pollution. Full article

(This article belongs to the Special Issue The Research on Effects of Coal Mining on Groundwater Environment and System)

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