Application of Clustering and Stepwise Discriminant Analysis Based on Hydrochemical Characteristics in Determining the Source of Mine Water Inrush
In order to explore the law of groundwater evolution, the water source connection between faults and aquifers and the main sources of mine water inrush in the deep mining area of Yangcheng Coal Mine in Jining City, 40 groups of hydrochemical samples were collected and analyzed by Piper Diagram and D...
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2021-01-01
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Online Access: | http://dx.doi.org/10.1155/2021/6670645 |
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author | Weitao Liu Jie Yu Jianjun Shen Qiushuang Zheng Mengke Han Yingying Hu Xiangxi Meng |
author_facet | Weitao Liu Jie Yu Jianjun Shen Qiushuang Zheng Mengke Han Yingying Hu Xiangxi Meng |
author_sort | Weitao Liu |
collection | DOAJ |
description | In order to explore the law of groundwater evolution, the water source connection between faults and aquifers and the main sources of mine water inrush in the deep mining area of Yangcheng Coal Mine in Jining City, 40 groups of hydrochemical samples were collected and analyzed by Piper Diagram and Durov Diagram. The results showed that the fluidity of groundwater developing to the deep became weaker, the value of total dissolved solids (TDS) became larger. So, the roof and floor of coal seam were more similar in water quality types due to the conduction of faults. Using principal component analysis (PCA) to the raw data, two principal components were extracted, and the principal component scores were used as clustering variables for hierarchical cluster analysis (HCA), 5 groups of abnormal water samples were eliminated and 3 clustering groups M1, M2 and M3 were obtained from the other water samples on the tree diagram. The results showed that the combination of HCA and hydrochemical analysis was more effective in screening water samples, and the 3 clustering groups could be qualified samples to represent 3 major aquifers (Taiyuan Formation limestone aquifer, Shanxi Formation sandstone aquifer and Ordovician limestone aquifer). Finally, taking M1, M2 and M3 as grouping variables, the discriminant functions f1, f2 and f3 of the 3 aquifers were obtained, the results of stepwise discrimination analysis (SDA) showed that the discrimination model established by using 25 groups of standard water samples could discriminate the known water samples with the correct rate of 96%, 10 groups of unknown water samples collected at the fault are identified as Taiyuan Formation limestone water samples, which was consistent with the classification results of HCA, proving that the water inrush of fault DF53 was from Taiyuan Formation limestone aquifer, while the fault had little influence on Ordovician limestone aquifer. |
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issn | 1468-8115 1468-8123 |
language | English |
publishDate | 2021-01-01 |
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spelling | doaj-art-382d7fdc8417457fb5f65e90d82fa96f2025-02-03T06:11:58ZengWileyGeofluids1468-81151468-81232021-01-01202110.1155/2021/66706456670645Application of Clustering and Stepwise Discriminant Analysis Based on Hydrochemical Characteristics in Determining the Source of Mine Water InrushWeitao Liu0Jie Yu1Jianjun Shen2Qiushuang Zheng3Mengke Han4Yingying Hu5Xiangxi Meng6Key Laboratory of Mining Disaster Prevention and Control, Shandong University of Science and Technology, Qingdao 266590, ChinaKey Laboratory of Mining Disaster Prevention and Control, Shandong University of Science and Technology, Qingdao 266590, ChinaKey Laboratory of Mining Disaster Prevention and Control, Shandong University of Science and Technology, Qingdao 266590, ChinaKey Laboratory of Mining Disaster Prevention and Control, Shandong University of Science and Technology, Qingdao 266590, ChinaKey Laboratory of Mining Disaster Prevention and Control, Shandong University of Science and Technology, Qingdao 266590, ChinaCollege of Safety and Environmental Engineering, Shandong University of Science and Technology, Qingdao 266590, ChinaKey Laboratory of Mining Disaster Prevention and Control, Shandong University of Science and Technology, Qingdao 266590, ChinaIn order to explore the law of groundwater evolution, the water source connection between faults and aquifers and the main sources of mine water inrush in the deep mining area of Yangcheng Coal Mine in Jining City, 40 groups of hydrochemical samples were collected and analyzed by Piper Diagram and Durov Diagram. The results showed that the fluidity of groundwater developing to the deep became weaker, the value of total dissolved solids (TDS) became larger. So, the roof and floor of coal seam were more similar in water quality types due to the conduction of faults. Using principal component analysis (PCA) to the raw data, two principal components were extracted, and the principal component scores were used as clustering variables for hierarchical cluster analysis (HCA), 5 groups of abnormal water samples were eliminated and 3 clustering groups M1, M2 and M3 were obtained from the other water samples on the tree diagram. The results showed that the combination of HCA and hydrochemical analysis was more effective in screening water samples, and the 3 clustering groups could be qualified samples to represent 3 major aquifers (Taiyuan Formation limestone aquifer, Shanxi Formation sandstone aquifer and Ordovician limestone aquifer). Finally, taking M1, M2 and M3 as grouping variables, the discriminant functions f1, f2 and f3 of the 3 aquifers were obtained, the results of stepwise discrimination analysis (SDA) showed that the discrimination model established by using 25 groups of standard water samples could discriminate the known water samples with the correct rate of 96%, 10 groups of unknown water samples collected at the fault are identified as Taiyuan Formation limestone water samples, which was consistent with the classification results of HCA, proving that the water inrush of fault DF53 was from Taiyuan Formation limestone aquifer, while the fault had little influence on Ordovician limestone aquifer.http://dx.doi.org/10.1155/2021/6670645 |
spellingShingle | Weitao Liu Jie Yu Jianjun Shen Qiushuang Zheng Mengke Han Yingying Hu Xiangxi Meng Application of Clustering and Stepwise Discriminant Analysis Based on Hydrochemical Characteristics in Determining the Source of Mine Water Inrush Geofluids |
title | Application of Clustering and Stepwise Discriminant Analysis Based on Hydrochemical Characteristics in Determining the Source of Mine Water Inrush |
title_full | Application of Clustering and Stepwise Discriminant Analysis Based on Hydrochemical Characteristics in Determining the Source of Mine Water Inrush |
title_fullStr | Application of Clustering and Stepwise Discriminant Analysis Based on Hydrochemical Characteristics in Determining the Source of Mine Water Inrush |
title_full_unstemmed | Application of Clustering and Stepwise Discriminant Analysis Based on Hydrochemical Characteristics in Determining the Source of Mine Water Inrush |
title_short | Application of Clustering and Stepwise Discriminant Analysis Based on Hydrochemical Characteristics in Determining the Source of Mine Water Inrush |
title_sort | application of clustering and stepwise discriminant analysis based on hydrochemical characteristics in determining the source of mine water inrush |
url | http://dx.doi.org/10.1155/2021/6670645 |
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