Hydrogeological Model for Groundwater Prediction in the Shennan Mining Area, China

Xie, Peng; Li, Wenping; Yang, Dongdong; Jiao, Junjie

doi:10.1007/s10230-017-0490-0

Cited by 12 publications

(4 citation statements)

References 7 publications

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“…Their research provided a reference for water resource management and water inrush prevention in other coal mines. In addition, the finite element theory was used by Xie et al [2] to analyze and solve the groundwater flow field and simulate the impact of coal mining on the upper aquifer. Hou et al [3] used distance discriminant analysis, Bayes discriminant analysis, and Fisher discriminant analysis (FDA) to establish a mine-water source-identification model, and they compared the applicable conditions, sample size, accuracy, and identification capabilities of different models.…”

Section: Introductionmentioning

confidence: 99%

Source Discrimination of Mine Gushing Water Using Self-Organizing Feature Maps: A Case Study in Ningtiaota Coal Mine, Shaanxi, China

Zhao

Zeng

et al. 2022

Sustainability

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Currently, there is a contradiction between coal mining and protection of water resources, meaning that there is a need for an effective method for discriminating the source of mine gushing water. Ningtiaota Coal Mine is a typical and representative main coal mine in the Shennan mining area. Taking this coal mine as an example, the self-organizing feature map (SOM) approach was applied to source discrimination of mine gushing water. Fisher discriminant analysis, water temperature, and traditional hydrogeochemical discrimination methods, such as Piper and Gibbs diagrams, were also employed as auxiliary indicators to verify and analyze the results of the SOM approach. The results from the three methods showed that the source of all the gushing water samples was surface water. This study represents the innovative use of an SOM in source discrimination for the first time. This approach has the advantages of high precision, high efficiency, good visualization, and less human interference. It can quantify sources while also comprehensively considering their hydrogeochemical characteristics, and it is especially suitable for case studies with large sample sizes. This research provides a more satisfactory solution for water inrush traceability, water disaster prevention and control, ecological protection, coal mine safety, and policy intervention.

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Section: Introductionmentioning

confidence: 99%

Source Discrimination of Mine Gushing Water Using Self-Organizing Feature Maps: A Case Study in Ningtiaota Coal Mine, Shaanxi, China

Zhao

Zeng

et al. 2022

Sustainability

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show abstract

“…Scholars have conducted many groundwater research studies in cities [14][15][16], coal mines [17][18][19], and basins and plains [20][21][22]. These studies mainly focus on groundwater circulation [23], groundwater resource evaluations [24,25], groundwater quality evaluations [26,27], and the evolution of the groundwater hydrogeochemical environment [28,29].…”

Section: Introductionmentioning

confidence: 99%

Hydrogeochemical Processes and Connection of Multi-Layer Groundwater System in Sunan Mining Area, Eastern China

Chen

et al. 2022

IJERPH

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Groundwater is an important freshwater resource in the world and serves as the main source of water for mining areas in Northern China. Coal mining may cause changes in water quality. As such, to identify ways to prevent water contamination, this study investigates the hydrogeochemical processes and transport paths of a complex aquifer system in the Sunan mining area in Northern China. Using the APFS-MLR model, a geographic information system (GIS) spatial analysis, and a hydrochemical correlation analysis method, this study identifies the potential mineral phases in groundwater, the spatial distribution of mineral reactions, and the contribution rate of these reactions to hydrochemical variables. Inverse modeling is used to verify hydrogeochemical process. The study reveals the relationship between multiple aquifers and four hydrological transport paths. Here, Path 1 and Path 2 show that the Quaternary aquifer, Carboniferous aquifer, and Ordovician aquifer are recharging the Permian aquifer through mineral dissolution and precipitation, cation exchange, and sulfate reduction. On the other hand, Path 3 and Path 4 show that tthe connections of Carboniferous and Ordovician limestone aquifers are dominated by the dissolution and precipitation of minerals and cation exchange, and that they are mainly recharged by the Quaternary aquifer. In the future, the water level of the Permian aquifer may rise somewhat after mining ends, and the mixing of water from the Permian aquifer, Quaternary aquifer, Carboniferous aquifer, and Ordovician aquifer could cause cross-pollution. In addition, sewage produced by human activities may recharge the deep water through the shallow water, polluting the deep karst water. As such, measures should be taken to reduce the hydraulic connection between Permian mine water and karst aquifers. The results of this study may benefit water quality predictions and treatment approaches in other complex multi-layer aquifer areas in the world.

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“…Recent studies have defined three stages of impact (damage phase, post-damage phase, and restoration phase) based on the effect of mining-induced groundwater changes on vegetation conditions [19]. Xie et al [20] established a hydrogeological conceptual model and a groundwater flow numerical model to predict mining-induced changes in the groundwater flow field over five years (30 April 2015to 30 April 2020. Based on the vegetation index determined using remote-sensing data, Zhang and Wang [21] reported that groundwater depth has a prominent effect on the spatial variation of vegetation distribution in the Ordos Plateau of China.…”

Section: Introductionmentioning

confidence: 99%

Ecological Impact Prediction of Groundwater Change in Phreatic Aquifer under Multi-Mining Conditions

Zhou

Liu

Duan

2022

IJGI

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In aeolian sandy grass shoal catchment areas that rely heavily on groundwater, mining-induced geological deformation and aquifer drainage are likely to cause irreversible damage to natural groundwater systems and affect the original circulation of groundwater, thus threatening the ecological environment. This study aimed to predict the impact of groundwater level decline on vegetation growth in the Hailiutu River Basin (HRB), which is a coal-field area. Based on remote-sensing data, the land use/cover change was interpreted and analyzed, and the central areas of greensward land in the basin were determined. Subsequently, the correlation between groundwater depth and grassland distribution was analyzed. Then, the groundwater system under natural conditions was modeled using MODFLOW, and the groundwater flow field in 2029 was predicted by loading the generalized treatment of coal mine drainage water to the model. The change in groundwater depth caused by coal mining and its influence on the grassland were obtained. The results show that coal mining will decrease the groundwater depth, which would induce degradation risks in 4 of the original 34 aggregation centers of greensward land that originally depended on groundwater for growth in HRB because they exceeded the groundwater threshold. The prediction results show that the maximum settlement of groundwater level can reach 5 m in the northern (Yinpanhao), 6 m in the eastern (Dahaize), and 10 m in the southern (Balasu) region of HRB. Attention should be paid to vegetation degradation in areas where groundwater depth exceeds the minimum threshold for plant growth.

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Hydrogeological Model for Groundwater Prediction in the Shennan Mining Area, China

Cited by 12 publications

References 7 publications

Source Discrimination of Mine Gushing Water Using Self-Organizing Feature Maps: A Case Study in Ningtiaota Coal Mine, Shaanxi, China

Source Discrimination of Mine Gushing Water Using Self-Organizing Feature Maps: A Case Study in Ningtiaota Coal Mine, Shaanxi, China

Hydrogeochemical Processes and Connection of Multi-Layer Groundwater System in Sunan Mining Area, Eastern China

Ecological Impact Prediction of Groundwater Change in Phreatic Aquifer under Multi-Mining Conditions

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