Hydro-Geochemistry of Deep Aquifers in Coal Mines in Northern Anhui Province, China: Implications for Water Rock Interaction and Water Source Discrimination

2012 ◽  
Vol 524-527 ◽  
pp. 604-607
Author(s):  
Lin Hua Sun ◽  
He Rong Gui ◽  
Man Li Lin
Keyword(s):  
Discriminant Analysis ◽  
Major Ions ◽  
Coal Mines ◽  
Water Source ◽  
Anhui Province ◽  
Rock Interaction ◽  
Source Discrimination ◽  
Deep Aquifers ◽  
Chemical Signatures ◽  
Groundwater Samples

Thirty-eight groundwater samples from three deep seated aquifers (the Quaternary, the Coal bearing and the Taiyuan Fm aquifers) had been collected from three coal mines in northern Anhui Province, China for analyzing their major ions, and the statistical methods (correlation, cluster and discriminant analysis) had been processed for evaluating the source of ions and relationship between aquifers. The results suggest that: (1) the chemical signatures of the groundwater are mainly controlled by dissolution of plagioclase, K-feldspar and calcite; (2) the aquifers had been mixed with each other, especially the mixing between the Quaternary aquifer and the Taiyuan Fm aquifer. Discriminant analysis has produced two functions and a diagram, which can be used for water source discrimination.

Trace Metal Concentrations in Deep Groundwater in Renlou Coal Mine, Northern Anhui Province, China

2012 ◽  
Vol 209-211 ◽  
pp. 1952-1955
Author(s):  
Lin Hua Sun
Keyword(s):  
Coal Mine ◽  
Water Source ◽  
Anhui Province ◽  
Metal Concentrations ◽  
Source Discrimination ◽  
Drinking Water Standard ◽  
Groundwater Samples ◽  
Icp Ms ◽  
Limestone Aquifers ◽  
Different Sources

Concentrations of six types of metals (including Cr, Co, Ni, Cu, Zn and Pb) in twelve groundwater samples from two different aquifers (coal bearing and limestone aquifers) in Renlou coal mine in northern Anhui Province, China have been analyzed by using ICP-MS and processed by statistical analysis for tracing their sources. The results indicate that the concentrations of metals are as follows: Cu(6.68 mg/L)> Cr(2.39 mg/L)> Ni(1.03 mg/L)> Zn(0.882 mg/L)> Co(0.569 mg/L)> Pb(0.116 mg/L). Concentrations of Cr, Ni, Cu and Pb are several times (47.8, 51.5, 3.3 and 8.0, respectively) higher than the drinking water standard of WHO, and indicating that these groundwater cannot be used for drinking directly. Two components (eigenvalues higher than one) have been obtained by using factor analysis with a total variance explanation of 88.7%, and two sources for metals in the groundwater have been identified that Cr-Cu and Co-Ni-Pb are originated from different sources. Moreover, the differences of metal concentrations between groundwater in these two aquifers suggest that they can be used for water source discrimination.

Multivariate statistical analysis of the hydro-geochemical characteristics for Mining groundwater: a case study from Baishan mining, northern Anhui Province, China

2013 ◽  
Vol 8 (1) ◽  
pp. 131-141 ◽  
Author(s):  
Song Chen ◽  
Xue Hai Fu ◽  
He Rong Gui ◽  
Lin Hua Sun
Keyword(s):  
Major Ions ◽  
High Ratio ◽  
Anhui Province ◽  
High Concentration ◽  
Fisher Discriminant Analysis ◽  
Multivariate Statistical ◽  
Rock Interaction ◽  
Fisher Discriminant ◽  
Groundwater Samples ◽  
Multivariate Statistical Approach

Major ions were analyzed for twenty five groundwater samples collected from diverse aquifer in Baishan mining, northern Anhui province, China. Conventional graphical and multivariate statistical approach were completed to identify the hydro-geochemical process and water-rock interaction, that be combined with the Cluster Analysis (CA) and Fisher discriminant analysis to recognize the sealed samples, the result showed: the diverse samples have vary ions inheriting from aquifer, samples collected from Sandstone aquifer (SA) is characterized by the high concentration of Na+ + K+, for the feldspar weathering is dominant; Ordovician limestone aquifer (OA) waters have abundance Ca2+ and Mg2+, for the dissolution of calcite and dolomite obviously; the dissolution of calcite and other calcareous concretions are dominant in Taiyuan formation water (TA) and Quaternary aquifer (QA) for the high ratio of Ca2+/Mg2+, otherwise the varied content of SO42– and HCO3− could distinguish the two aquifer water. Twenty five groundwater samples, containing six sealed samples, had been subdivided in to four groups by the CA, what are corresponded with four aquifers. Fisher discriminant functions were obtained and the efficiency was acceptable for the error rate 4% in all twenty five samples.

scholarly journals Statistical analyses of groundwater chemistry in the Qingdong coalmine, northern Anhui province, China: implications for water–rock interaction and water source identification

2021 ◽  
Vol 11 (2) ◽  
Author(s):  
Kai Chen ◽  
Linhua Sun ◽  
Jiying Xu
Keyword(s):  
Source Identification ◽  
Major Ions ◽  
Chemical Constituents ◽  
Water Source ◽  
Anhui Province ◽  
Rock Interaction ◽  
Ion Concentrations ◽  
Major Ion ◽  
Inrush Water ◽  
Water Rock Interaction

AbstractHydrochemistry of groundwater is important in coal mines because it can be used for understanding water–rock interaction and inrush water source identification. In this study, major ion concentrations of groundwater samples from the loose layer aquifer (LA), coal-bearing aquifer (CA) and Taiyuan Formation limestone aquifer (TA) in the Qingdong coal mine, northern Anhui province, China, have been analyzed by a series of statistical methods for identifying the source of chemical constituents in groundwater and the source of inrush water. The results indicate that the mean concentration of the major ions in the LA were ordered as follows: HCO3− > SO42− > Na+ + K+  > Cl− > Ca2+ > Mg2+ > CO32−, whereas average values of the CA in decreasing order are SO42−, Na+ + K+, HCO3−, Cl−, Ca2+, Mg2+ and CO32−, and the major ion concentrations of the TA have the following order: SO42− > Na+ + K+ > Ca2+  > HCO3− > Cl− > Mg2+ > CO32−, and most of the samples are Na-SO4 and Ca-SO4 types. TDS content in water increases with aquifer depth, whereas the pH values ranged from 7.1 to 8.9, indicating a weak alkaline environment. Two sources (weathering of silicate minerals and dissolution of evaporate minerals) have been identified by principal component analysis responsible for the chemical variations of the groundwater, and their contribution ratios have been quantified by Unmix model. Moreover, based on the Q-mode cluster and discriminant analyses, the samples with known sources have been identified correctly to be 95.7% and 97.6%, respectively, and the samples with unknown sources have been determined with high probability (78–100%).

Identification of Hydro-Geochemical Processes in Groundwater by Using Major Ion Chemistry: A Case Study

2013 ◽  
Vol 726-731 ◽  
pp. 3424-3428
Author(s):  
Lin Hua Sun
Keyword(s):  
Coal Mine ◽  
Water Source ◽  
Geochemical Processes ◽  
Ion Chemistry ◽  
High Concentration ◽  
Source Discrimination ◽  
Chemical Systems ◽  
Major Ion ◽  
Groundwater Samples ◽  
The Operating Mechanism

Hydro-geochemistry is important for water disaster controlling as it can be used for either understanding of hydrological evolution or water source discrimination. Groundwater samples from the sandstone aquifer in Xutuan coal mine, northern Anhui Province, China have been collected for major ion chemical analysis to understand the operating mechanism of geochemical processes for variation of groundwater chemistry, which will be useful for improving the understanding of hydro-chemical systems in coal mine. The results suggest that they are medium to slightly (6.8 to 8.64 with an average of 7.61) with high concentration of total dissolved solids (943 and 1362 mg/L with mean of 1171 mg/L)). Most of the groundwater samples are classified as Na- HCO3-Cl and Na-Cl- HCO3 types according to their relative concentrations of cations and anions. Correlation between ion concentrations, as well as principle component analysis imply that dissolution of dolomite, halite, gypsum, silicate weathering and ion exchange are responsible for the chemical variations of the groundwater.

scholarly journals Hydrochemical assessment and groundwater pollution parameters in arid zone: Case of the Turonian aquifer in Béchar region, southwestern Algeria

2018 ◽  
Vol 39 (1) ◽  
pp. 109-117
Author(s):  
Ikram Mokeddem ◽  
Meriem Belhachemi ◽  
Touhami Merzougui ◽  
Noria Nabbou ◽  
Salih Lachache
Keyword(s):  
Irrigation Water ◽  
Major Ions ◽  
Arid Zone ◽  
Water Source ◽  
Anthropogenic Sources ◽  
Anthropogenic Source ◽  
Water Sampling ◽  
Drinking And Irrigation ◽  
Groundwater Samples ◽  
High Concentrations

AbstractGroundwater samples from Turonian aquifer of Béchar region were evaluated as drinking and irrigation water sources. physicochemical parameters including pH, EC, TH, Na+, Ca2+, Mg2+, Cl−, SO42– and NO3− were determined for 16 water sampling points. These characterizations show that the groundwater is fresh to brackish, slightly alkaline and the major ions are Na+, Ca2+, Mg2+, Cl− and SO42–. According to WHO standards, 50% of the analysed water are suitable as a drinking source while the other samples are not in compliance with drinking water standards. This non-compliance is basically due to the high concentrations of Na+, Cl−, and SO42– requesting further treatment to reach the stringent standards. According to the results of nitrate concentrations, anthropogenic source seems to influence the groundwater quality. The present study shows that Béchar groundwater may represent an important drinking and irrigation water source. However, a specific management strategy should be adapted in order to avoid the contamination by anthropogenic sources.

scholarly journals Hydrogeochemical and Isotopic Investigations on the Origins of Groundwater Salinization in Çarşamba Coastal Aquifer (North Turkey)

2021 ◽  
Author(s):  
Abdourazakou MAMAN HASSAN ◽  
Arzu Ersoy
Keyword(s):  
Transition Zone ◽  
Coastal Aquifer ◽  
Major Ions ◽  
Coastal Region ◽  
Environmental Isotopes ◽  
Classification Systems ◽  
Physical Parameters ◽  
Rock Interaction ◽  
Hydrogeochemical Process ◽  
Groundwater Samples

Abstract The aim of this study is to determine the origins of salinization and the main hydrogeochemical process that controls the chemistry of Çarşamba coastal aquifer in Turkey. Therefore, a total of 33 groundwater samples and three seawater samples were analyzed in the coastal region of Çarşamba Plain in July 2019 and for these samples’ physical parameters, major ions and environmental isotopes (δ18O, δ2H and 3H) values were determined. Piper, Chadha, Gibbs diagrams and Stuyfzand Classification Systems were used to determine the origins of salinization and the key hydrogeochemical process controlling the groundwater chemistry. According to Stuyfzand classification system, the study showed that the freshwater and fresh-brackish water main types are the most widespread in the study area. Six water subtypes were observed in the study area that include CaHCO3, CaMix, NaMix, NaCl, NaHCO3 and MgHCO3. In addition, the subtypes CaMix indicated the locations of the transition zone, where the groundwater rich in Ca and HCO3 and gradually enriched in Na changes from CaMix with HCO3 as dominant anion to eventually CaCl and NaCl subtypes. Furthermore, the subtypes NaMix, NaHCO3 and MgHCO3 showed the locations of the transition zone where the flushing of the saline aquifer by freshwater takes place. All groundwater samples from study area had a positive cation exchange code and show that four hydrogeochemical facies composed of CaHCO3; Ca-Mg-Cl and NaCl and NaHCO3. Besides, groundwater samples have been influenced by two main mechanisms: the water-rock interaction and evaporation-crystallization. According to δ18O, δ2H and 3H analysis, the water samples have meteoric origin, shallow circulation, and a short residence time.

Application of Rare Earth Elements for Water Source Discrimination in Renlou Coal Mine, Northern Anhui Province, China

2011 ◽  
Vol 99-100 ◽  
pp. 1195-1198
Author(s):  
Lin Hua Sun
Keyword(s):  
Rare Earth ◽  
Coal Mine ◽  
Earth Element ◽  
Water Source ◽  
Wall Rock ◽  
Anhui Province ◽  
Rock Composition ◽  
Source Discrimination ◽  
Limestone Aquifer ◽  
Limestone Aquifers

Rare earth element (REEs) concentrations were measured for groundwater and wall rock samples from two aquifers (sandstone and limestone aquifers) in Renlou coal mine, northern Anhui Province, China. The results indicate that groundwater from these two aquifers are rich in REEs as expressed by their Nd concentrations (0.012 and 0.008 μg/L). They all show heavy REEs enrichment with low NdRN/YbRN ratios (0.35 and 0.40) when normalized to their aquifer rocks. Y- Ho fractionation are only observed for groundwater from limestone aquifer with high Y/Ho ratio (97 in average), whereas groundwater from sandstone aquifer have low Y/Ho ratios (24 in average). The former is considered to be related to the release of Y and Ho from calcite with different partition coefficient. The similarity of some REEs between groundwater and aquifer rock, as well as the different rock composition of aquifers, provide possibility for discrimination of water sources by using REEs, and Y/Ho ratios and Eu anomalies are expected to be useful in Renlou coal mine.

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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