Hydrochemical investigation of groundwater in a trans-Himalayan region of Ladakh, India, using geochemical modelling and entropy technique

被引:4
|
作者
Chorol, Lobzang [1 ]
Gupta, Sunil Kumar [1 ]
机构
[1] Indian Inst Technol Indian, Sch Mines, Dept Environm Sci & Engn, Dhanbad 826004, India
关键词
Hydrochemical assessment; Geochemical modelling; Entropy technique; Trans-Himalayan; Environmental risk; Heavy metals; WATER-QUALITY INDEX; RIVER-BASIN; HEALTH-RISK; INDUS RIVER; MINING AREA; HYDROGEOCHEMISTRY; DISTRICT; IRRIGATION; POLLUTION; CONTAMINATION;
D O I
10.1007/s10653-023-01650-4
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Evaluating the hydrogeochemistry and groundwater quality status is vital to understand the sources and extent of groundwater contamination. Chemometric analysis, geochemical modelling and entropy technique were explored to delineate the hydrogeochemistry of groundwater in the transHimalayan region. Analysis of hydrochemical facies revealed that 57.14, 39.29, and 3.57% of samples were Ca-Mg-HCO3-, Ca-Mg-Cl- and Mg-HCO3- water types, respectively. Gibbs diagrams illustrate the effects of the dissolution of carbonates and silicates during weathering on groundwater hydrogeochemistry. The PHREEQC modelling depicted that most of the secondary minerals are supersaturated except for halite, sylvite, and magnetite which are undersaturated and in equilibrium with nature. Multivariate statistical techniques, including principal component analysis, were applied for source apportionment indicating that the hydrochemistry of the groundwater was mainly controlled by geogenic sources (rock-water interaction) along with secondary pollution through increased anthropogenic sources. Heavy metal accumulation in groundwater depicted the order of Cd > Cr > Mn > Fe > Cu > Ni > Zn. EWQI analysis revealed that none of the samples fell into excellent and good categories. In total, 92.86% of groundwater samples were in an average category while the rest of the samples (7.14%) were unfit for drinking. This study will provide baseline data and a scientific framework which can be used in source apportionment studies, predictive modelling and efficient management of water resources. [GRAPHICS]
引用
收藏
页码:6567 / 6583
页数:17
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