Hydro-geochemical paths of multi-layer groundwater system in coal mining regions — Using multivariate statistics and geochemical modeling approaches

Liu, Pu; Hoth, Nils; Drebenstedt, Carsten; Sun, Yajun; Xu, Zhimin

doi:10.1016/j.scitotenv.2017.05.146

Cited by 133 publications

(55 citation statements)

References 30 publications

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“…During the process of water-rock interaction, the mineral equilibrium calculation can reflect the thermodynamic process of natural water system [12,13]. Moreover, SI gives an insight of the reactivity of minerals.…”

Section: Mineral Saturationsmentioning

confidence: 99%

“…The correlations applied to the eight variables (pH, TDS and major ions) shed light on the relationships among those variables and water-rock interaction controlling the hydrochemical parameters [1][2][3].The values of R > 0.75 and 0.75 > R > 0.50 suggested strong and moderate correlations between the hydrochemical parameters, respectively [11][12][13]. To avoid the error triggered by different unite, all variables were treated by log-ratio transforms prior to multivariate statistical analysis.…”

Section: Multivariate Statistical Analysismentioning

confidence: 99%

“…The values of R > 0.75 and 0.75 > R > 0.50 suggested strong and moderate correlations between the hydrochemical parameters, respectively [11][12][13]. To avoid the error triggered by different unite, all variables were treated by log-ratio transforms prior to multivariate statistical analysis.…”

Section: Multivariate Statistical Analysismentioning

confidence: 99%

“…To date, hydrochemical analysis [8,9], multivariate statistical analysis [10,11], and geochemical modelling [12,13] have proven to be efficient for constraining the hydrochemical process of natural …”

Section: Introductionmentioning

confidence: 99%

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Hydrochemical Characteristics and Multivariate Statistical Analysis of Natural Water System: A Case Study in Kangding County, Southwestern China

Zhang

et al. 2018

Water

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Abstract:The utilization for water resource has been of great concern to human life. To assess the natural water system in Kangding County, the integrated methods of hydrochemical analysis, multivariate statistics and geochemical modelling were conducted on surface water, groundwater, and thermal water samples. Surface water and groundwater were dominated by Ca-HCO 3 type, while thermal water belonged to Ca-HCO 3 and Na-Cl-SO 4 types. The analyzing results concluded the driving factors that affect hydrochemical components. Following the results of the combined assessments, hydrochemical process was controlled by the dissolution of carbonate and silicate minerals with slight influence from anthropogenic activity. The mixing model of groundwater and thermal water was calculated using silica-enthalpy method, yielding cold-water fraction of 0.56-0.79 and an estimated reservoir temperature of 130-199 • C, respectively. δD and δ 18 O isotopes suggested that surface water, groundwater and thermal springs were of meteoric origin. Thermal water should have deep circulation through the Xianshuihe fault zone, while groundwater flows through secondary fractures where it recharges with thermal water. Those analytical results were used to construct a hydrological conceptual model, providing a better understanding of the natural water system in Kangding County.

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Section: Mineral Saturationsmentioning

confidence: 99%

Section: Multivariate Statistical Analysismentioning

confidence: 99%

Section: Multivariate Statistical Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Hydrochemical Characteristics and Multivariate Statistical Analysis of Natural Water System: A Case Study in Kangding County, Southwestern China

Zhang

et al. 2018

Water

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“…For example, PCA has been applied in hydrochemistry data acquisition [12,13], in geotechnical properties of formations data [14], in quality composition of geological formations and trace elements data [15], etc. PCA is also implemented in various topics concerning mining activities and their impacts, especially coal mining, mainly regarding environmental and quality aspects [16][17][18][19][20][21].…”

Section: Introductionmentioning

confidence: 99%

Multi-Seam Coal Deposit Modeling via Principal Component Analysis & GIS

et al. 2019

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Spatial modeling and evaluation is a critical step for planning the exploitation of mineral deposits. In this work, a methodology for the investigation of a multi-seam coal deposit spatial variability is proposed. The study area includes the Klidi (Florina, Greece) multi-seam lignite deposit which is suitable for surface mining. The analysis is based on the original data of 76 exploratory drill-holes in an area of 10 km 2 , in conjunction with the geological and geomorphological data of the deposit. The analytical methods include drill-hole data analysis and evaluation based on an appropriate algorithm, principal component analysis and geographic information techniques. The results proved to be very satisfactory for the explanation of the maximum variance of the initial data values as well as the identification of the deposit structure and the optimum planning of mine development. The proposed analysis can be also helpful for minimizing cost and optimizing efficiency of surface mining operations. Furthermore, the provided methods could be applied in other areas of geosciences, indicating the theoretical value as well as the important practical implications of the analysis.

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Using multivariate statistical techniques and geochemical modelling to identify factors controlling the evolution of groundwater chemistry in a typical transitional area between Taihang Mountains and North China Plain

Liu

Shou

Yeh

et al. 2020

Hydrological Processes

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Identifying the key factors controlling groundwater chemical evolution in mountain-plain transitional areas is crucial for the security of groundwater resources in both headwater basins and downstream plains. In this study, multivariate statistical techniques and geochemical modelling were used to analyse the groundwater chemical data from a typical headwater basin of the North China Plain. Groundwater samples were divided into three groups, which evolved from Group A with low mineralized Ca-HCO 3 water, through Group B with moderate mineralized Ca-SO 4 -HCO 3 water, to Group C with highly saline Ca-SO 4 and Ca-Cl water. Water-rock interaction and nitrate contamination were mainly responsible for the variation in groundwater chemistry. Groundwater chemical compositions in Group A were mainly influenced by dissolution of carbonates and cation exchange, and suffered less nitrate contamination, closely relating to their locations in woodland and grassland with less pronounced human interference. Chemical evolution of groundwater in Groups B and C was gradually predominated by the dissolution of evaporites, reverse ion exchange, and anthropogenic factors. Additionally, the results of the inverse geochemical model showed that dedolomitization caused by gypsum dissolution, played a key role in the geochemical evolution from Group A to Group B. Heavy nitrate enrichment in most groundwater samples of Groups B and C was closely associated with the land-use patterns of farmland and residential areas. Apart from the high loads of chemical fertilizers in irrigation return flow as the main source for nitrate contamination, the stagnant zones, flood irrigation pattern, mine drainage, and groundwater-exploitation reduction program were also important contributors for such high mineralization and heavy NO 3 − contents in Group C. The important findings of this work not only provide the conceptual framework for the headwater basin but also have important implications for sustainable management of groundwater resources in other headwater basins of the North China Plain. K E Y W O R D S geochemical modelling, groundwater evolution, headwater basin, hydrochemistry, multivariate statistical analysis, North China Plain

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Hydro-geochemical paths of multi-layer groundwater system in coal mining regions — Using multivariate statistics and geochemical modeling approaches

Cited by 133 publications

References 30 publications

Hydrochemical Characteristics and Multivariate Statistical Analysis of Natural Water System: A Case Study in Kangding County, Southwestern China

Hydrochemical Characteristics and Multivariate Statistical Analysis of Natural Water System: A Case Study in Kangding County, Southwestern China

Multi-Seam Coal Deposit Modeling via Principal Component Analysis & GIS

Using multivariate statistical techniques and geochemical modelling to identify factors controlling the evolution of groundwater chemistry in a typical transitional area between Taihang Mountains and North China Plain

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