scholarly journals Hydrochemical Characteristics, Quality Assessment and Solute Source Identification of Coal Bearing Fractured Aquifer in Dingji Coal Mine, Huainan Coalfield, China

2021 ◽  
Vol 20 (4) ◽  
Author(s):  
Jie Ma ◽  
Jianghong Wang ◽  
Song Chen ◽  
Hongbao Dai ◽  
Jingyu Zhao ◽  
...  
Keyword(s):  
Water Quality ◽  
Quality Assessment ◽  
Coal Mine ◽  
Major Ions ◽  
Water Inrush ◽  
Ion Source ◽  
Drinking Water Source ◽  
Hydrochemical Characteristics ◽  
Fractured Aquifer ◽  
Huainan Coalfield

Coal-bearing fractured aquifer is regarded as one of the most dynamic mine water inrush sources, and after pumping and treating, it can be used as a water supply for coal mine production, coal preparation plant, rural irrigation, and even reserved drinking water source. Hence, this study focuses on the hydrochemical characteristics, ion source, and water quality evaluation with respect to drinking and irrigation of the coal-bearing fractured aquifer in Dingji coal mine, Huainan coalfield, China. Descriptive statistics and hydrochemical classification diagrams including the Piper diagram and Chadha rectangular diagram were carried out to depict the hydrochemical characteristics and facies. The water quality of the aquifer was assessed for irrigation and drinking purposes using the WHO threshold value, water quality index (WQI), SAR, % Na and RSC. Hydrochemical formation mechanism and solute origin of major ions were explained by Gibbs diagram, bivariate diagrams, and multivariate statistical analysis. The results show that the dominant hydrochemical facies are the Cl-Na type and the HCO3-Na type. The sequence of ions is Na+ > Ca2+ > Mg2+ for cations, and HCO3? > Cl- > SO42- > CO32- for anions. The main solute sources are controlled by various factors including the dissolution of halite, sulfate, and carbonate rocks, the weathering of silicate, and cation exchange. Water quality assessment based on WQI suggests that none of the samples fall under the excellent category, even 32.5% is not suitable for direct drinking. Meanwhile, the samples of the aquifer are generally unsuitable for irrigation. Before utilization for irrigation and even drinking, appropriate water treatment should be applied to guarantee its security during usage.

Major ion chemistry and water quality assessment of groundwater in the Shigaze urban area, Qinghai-Tibetan Plateau, China

2019 ◽  
Vol 20 (1) ◽  
pp. 335-347 ◽  
Author(s):  
Yingzhi Li ◽  
Jiutan Liu ◽  
Zongjun Gao ◽  
Min Wang ◽  
Leqi Yu
Keyword(s):  
Water Quality ◽  
Tibetan Plateau ◽  
Quality Assessment ◽  
Major Ions ◽  
Water Quality Assessment ◽  
Ion Chemistry ◽  
Major Ion Chemistry ◽  
Major Ion ◽  
The Mean ◽  
Over Time

Abstract Shigaze city is situated in the southwestern Tibetan Plateau and is the second largest city in the Tibet Autonomous Region. Groundwater is the major source of domestic and drinking water for urban inhabitants. In this study, the major ion chemistry and a water quality assessment of groundwater were studied using geochemical methods and fuzzy comprehensive assessment. Groundwater was classified as slightly alkaline soft and hard freshwater, and the influence of anthropogenic activities on groundwater was relatively weak. The dominant cations and anions were Ca2+ and Mg2+ and HCO3− and SO42−, respectively. Overall, the mean concentrations of major ions in groundwater increase gradually over time, except for NO3−; however, the mean value of pH decreases over time. Most groundwater samples belong to the type of HCO3-Ca, and the groundwater has a trend of evolution from HCO3-Ca to the mixed type. Rock weathering was the main hydrogeochemical process controlling groundwater hydrochemistry, and the dissolution of carbonate and silicate minerals were the primary contributors to the formation of the major ion chemistry of groundwater. Major ions of groundwater in the urban area of Shigaze are below the standard limits, and the groundwater is excellent for drinking according to the fuzzy comprehensive assessment.

scholarly journals Sources Identification of Water Inrush in Coal Mines Using Technique of Multiple Non-Linear Machine Learning Modelling

2020 ◽  
Author(s):  
Yao Shan
Keyword(s):  
Machine Learning ◽  
Coal Mine ◽  
Major Ions ◽  
Water Inrush ◽  
Coal Mines ◽  
Water Source ◽  
Northern China ◽  
Machine Learning Algorithms ◽  
Support Vector ◽  
Model Training

Water inrush is a major threat to the working safety for coal mines in the Northern China coal district. The inrush pattern, threaten level, and also the geochemical characteristics varies according to the different of water sources. Therefore, identifying the water source correctly is an important task to predict and control the water inrush accidents. In this chapter, the algorithms and attempts to identify the water inrush sources, especially in the Northern China coal mine district, are reviewed. The geochemical and machine learning algorithms are two main methods to identify the water inrush sources. Four main steps need to apply, namely data processing, feature selection, model training, and evaluation, in the process of machine learning (ML) modelling. According to a calculation instance, most of the major ions, and some trace elements, such as Ti, Sr, and Zn, were identified to be important in light of geochemical analysis and machine learning modelling. The ML algorithms, such as random forest (RF), support vector machine (SVM), Logistica regression (LR) perform well in the source identification of coal mine water inrush.

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