Study on the Influence of Mining Activities on the Quality of Deep Karst Groundwater Based on Multivariate Statistical Analysis and Hydrochemical Analysis
Abstract
:1. Introduction
2. Study Area
3. Sampling Test and Research Method
3.1. Sampling and Testing
3.2. Research Methods
3.2.1. Principal Component Analysis (PCA)
- The data of hydrochemical indexes was standardized to eliminate the errors caused by different dimensions;
- The correlation coefficient was calculated according to the standardized data matrix, and the eigenvalues and eigenvectors of the correlation coefficient matrix were calculated;
- The principal components were determined, the variance contribution rate and cumulative variance contribution rate of the data set were calculated, and professional explanations were given to each principal component according to the actual situation.
3.2.2. Fuzzy Comprehensive Evaluation
- Establish evaluation factor set and evaluation language set
- 2.
- Establish fuzzy relation matrix
- 3.
- Determine weight coefficient matrix
- 4.
- Establish fuzzy comprehensive evaluation model
4. Results and Discussion
4.1. Analysis of Karst Groundwater Chemical Content Characteristics
4.2. Fuzzy Comprehensive Evaluation of Karst Groundwater Quality
4.3. Hydrogeochemical Evolution Process
4.3.1. Hydrochemical Characteristics and Evolution
4.3.2. Source Analysis of Main Ions in Karst Groundwater
4.3.3. Dissolution/Precipitation Equilibrium of Minerals
4.3.4. Correlation Analysis
4.4. Main Factors Affecting Hydrogeochemical Evolution Process
4.5. Prediction of Hydrochemical Evolution
5. Conclusions
- The fuzzy comprehensive evaluation results show that the proportion of class V water in karst groundwater in Taiyuan Formation accounts for more than 80%, and the water quality is poor, which is not suitable for long-term drinking. The high content of Na++K+ and SO42− in groundwater is the main reason for poor water quality.
- By using the Piper diagram, ion ratio analysis, mineral saturation index, and correlation analysis, it is concluded that Na++K+ mainly comes from cation exchange, dissolution of rock salt and silicate, and SO42− mainly comes from sulfate dissolution and pyrite oxidation.
- Through principal component analysis, it is concluded that the main factors controlling the chemistry of karst groundwater in Taiyuan Formation are sulfate dissolution, pyrite oxidation, cation exchange, and dedolomitization.
- Influenced by stratum grouting, the circulation of karst groundwater in Taiyuan Formation in the study area is accelerated, the cation exchange is weakened, and the desulfurization acid effect is enhanced. In the future, the hydrochemical type of karst groundwater will evolve from SO4-Ca Mg type to HCO3-Ca·Mg type.
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Grade | Classification | Parameters (Unit: mg/L) | |||
---|---|---|---|---|---|
TDS | Na+ | Cl− | SO42− | ||
I | Excellent, suitable for drinking water | ≤300 | ≤100 | ≤50 | ≤50 |
II | Good, suitable for drinking water | ≤500 | ≤150 | ≤150 | ≤150 |
III | Moderate, suitable for drinking water | ≤1000 | ≤200 | ≤250 | ≤250 |
IV | Poor, suitable for drinking water | ≤2000 | ≤400 | ≤350 | ≤350 |
V | Unsuitable, suitable for drinking water | >2000 | >400 | >350 | >350 |
Indexs | Unit | GIII | Stage I (n = 35) | Stage II (n = 15) | Stage III (n = 11) | ||||||
---|---|---|---|---|---|---|---|---|---|---|---|
Range | Mean | CV (%) | Range | Mean | CV (%) | Range | Mean | CV (%) | |||
pH | - | 6.5–8.5 | 7.12–7.82 | 7.60 | 2.46 | 7.78–7.92 | 7.86 | 0.57 | 7.12–7.80 | 7.34 | 2.91 |
TDS | mg/L | 1000 | 1591–3186 | 2384.8 | 17.59 | 1891–5145 | 2726.6 | 26.83 | 1358–2552 | 1908.5 | 25.04 |
Na++K+ | mg/L | 200 | 130–814 | 394.7 | 40.87 | 157–927 | 355.6 | 61.59 | 152–284 | 240.1 | 16.64 |
Ca2+ | mg/L | - | 49.9–461 | 246 | 44.08 | 32.4–392 | 173.5 | 74.14 | 96.2–486 | 327.1 | 40.46 |
Mg2+ | mg/L | - | 5.5–143 | 63.2 | 57.28 | 49.7–367 | 205.5 | 47.49 | 67.8–364 | 111.5 | 76.39 |
Cl− | mg/L | 250 | 68.5–207 | 137.6 | 23.38 | 65.4–192 | 134.5 | 28.29 | 122–155 | 140 | 8.23 |
SO42− | mg/L | 250 | 568–1830 | 1215 | 26.37 | 774–3278 | 1528.6 | 36.06 | 862–1754 | 1260.9 | 28.90 |
HCO3− | mg/L | - | 170–605 | 321.4 | 29.53 | 181–524 | 328.9 | 35.21 | 269–439 | 343.9 | 16.13 |
Indexs | Class I Water | Class II Water | Class III Water | Class IV Water | Class V Water |
---|---|---|---|---|---|
Stage I | 0 | 0 | 0 | 8.57% | 91.43% |
Stage II | 0 | 0 | 6.67% | 13.33% | 80% |
Stage III | 0 | 0 | 0 | 18.18% | 81.82% |
Indexs | PC1 | PC2 | PC3 |
---|---|---|---|
Na++K+ | −0.05 | 0.782 | 0.118 |
Ca2+ | 0.316 | −0.369 | 0.637 |
Mg2+ | 0.397 | −0.06 | −0.68 |
Cl− | 0.21 | 0.362 | 0.337 |
SO42− | 0.616 | 0.308 | −0.039 |
HCO3− | −0.562 | 0.152 | −0.051 |
Initial eigenvalue | 1.912 | 1.428 | 1.259 |
Contribution rate (%) | 31.9 | 23.8 | 21 |
Cumulative contribution rate (%) | 31.9 | 55.67 | 76.66 |
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Li, C.; Gui, H.; Guo, Y.; Chen, J.; Li, J.; Xu, J.; Yu, H. Study on the Influence of Mining Activities on the Quality of Deep Karst Groundwater Based on Multivariate Statistical Analysis and Hydrochemical Analysis. Int. J. Environ. Res. Public Health 2022, 19, 17042. https://doi.org/10.3390/ijerph192417042
Li C, Gui H, Guo Y, Chen J, Li J, Xu J, Yu H. Study on the Influence of Mining Activities on the Quality of Deep Karst Groundwater Based on Multivariate Statistical Analysis and Hydrochemical Analysis. International Journal of Environmental Research and Public Health. 2022; 19(24):17042. https://doi.org/10.3390/ijerph192417042
Chicago/Turabian StyleLi, Chen, Herong Gui, Yan Guo, Jiayu Chen, Jun Li, Jiying Xu, and Hao Yu. 2022. "Study on the Influence of Mining Activities on the Quality of Deep Karst Groundwater Based on Multivariate Statistical Analysis and Hydrochemical Analysis" International Journal of Environmental Research and Public Health 19, no. 24: 17042. https://doi.org/10.3390/ijerph192417042