A multivariate statistical approach for monitoring of groundwater quality: a case study of Beri block, Haryana, India

Panghal, V.P.S.; Bhateria, Rachna

doi:10.1007/s10653-020-00654-8

Cited by 13 publications

(2 citation statements)

References 21 publications

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“…Pre-monsoon alkalinity levels ranged from 188.57 mg/L (pre-monsoon) to 191.39 mg/L (post-monsoon). Alkalinity is another critical metric for assessing water quality; alkalinities comprise essential components such as carbonates and bicarbonates (Panghal et al, 2020 ).…”

Section: Resultsmentioning

confidence: 99%

Hydrochemical characterization of groundwater quality using chemometric analysis and water quality indices in the foothills of Himalayas

Nayak

Matta

Uniyal

2022

Environ Dev Sustain

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Groundwater pollution of the watershed is mainly influenced by the multifaceted interactions of natural and anthropogenic process. To analyse the spatial–temporal variation and pollution source identification and apportionment, the dataset was subjected to a globally acknowledged coherent technique using water quality indices and chemometric techniques (principal component analysis (PCA) and cluster analysis. The bulk of the samples tested were below the BIS’s permissible levels. Groundwater samples from the pre- and post-monsoon seasons mostly contained the anions HCO − 3 > Cl − > SO 2− 4 > NO − 3 , while the primary cations were Ca 2+ > Mg 2+ > Na + > K + . Groundwater was alkaline and hard at most of the sites. According to hydro-geochemical facies and relationships, Piper diagrams, and principal component analysis, weathering, dissolution, leaching, ion exchange, and evaporation were the key mechanisms influencing groundwater quality. The hydrochemical facies classified the groundwater samples into the Ca-Mg-HCO 3 type. For all the sampling locations, PIG was determined to be 0.43, 0.52, 0.47, 0.48, 1.00, and 0.70; respectively. The majority of the test locations fell into the low to medium contamination zone, as determined by the groundwater pollution index (PIG) and contamination index. Three principal components, which together account for 93.8% of the total variance, were identified via PCA. The study’s findings confirm the value of these statistical techniques in interpreting and understanding large datasets and offering reliable information to reduce the time and expense of programmes for monitoring and evaluating water quality.

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Section: Resultsmentioning

confidence: 99%

Hydrochemical characterization of groundwater quality using chemometric analysis and water quality indices in the foothills of Himalayas

Nayak

Matta

Uniyal

2022

Environ Dev Sustain

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“…With the growing usage of geographical information system (GIS), indices mapped using GIS techniques evaluate the spatial extent and temporal variation of the groundwater quality (Adhikary et al, 2012;Jhariya et al, 2017;Ketata et al, 2012;Saeedi et al, 2010;Tiwari et al, 2018;Jha et al, 2020). Time series analysis using non-parametric tests such as the Mann-Kendall test (Kendall, 1975;Mann, 1945) and multivariate statistical techniques such as principal component analysis (PCA) and correlation matrix analysis (CMA) are widely used tools which may also be integrated with GIS (Awomeso et al, 2020;Bodrud-Doza et al, 2020;Farid et al, 2019;Kaown et al, 2012;Mukate et al, 2020;Nandakumaran & Balakrishnan, 2020;Nguyen et al, 2020;Niu et al, 2017;Panghal & Bhateria, 2020;Radelyuk et al, 2021;Rezaei et al, 2020;Sheikhy Narany et al, 2017;Wahlin & Grimvall, 2010;Zhang Wang et al, 2020a). More recent methods such as artificial intelligent (AI) models perform well under limited data situations and are able to predict pollutant concentrations in groundwater systems.…”

Section: Introductionmentioning

confidence: 99%

Simulating contaminant transport in unsaturated and saturated groundwater zones

Sarma

Singh

2021

Water Environment Research

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The demand for clean and adequate water is rising rapidly with increasing population. This growing demand for water necessitates the measurement of the quantity and quality of water. Simulation modeling has become increasingly popular in the last two decades largely because of their predictive ability. This paper reviews the approaches for simulation modeling in groundwater resources management, focusing on models that have been used to simulate contaminant transport through the aquifer system. Recent research papers that have integrated the models for unsaturated and saturated zones have also been studied and described. Integrated models require assessment of the complex interactions between the groundwater zones and the movement of water and solute through them. Due to this, integrated models provide a more accurate modeling approach than models that have been independently developed for saturated and unsaturated zones. Application of such models is encouraged at the regional level to arrive at the best groundwater management decisions. © 2021 Water Environment Federation • Practitioner points• In the past few decades, modeling of contaminant transport in groundwater systems has seen tremendous applications. • A number of models exist that independently simulate flow and solute transport in unsaturated and saturated zones. • Recently, focus has been given on developing advanced coupled modeling approaches that require less inputs and run times.

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Assessment of water quality, trace metal pollution, source apportionment and health risks in the groundwater of Chakwal, Pakistan

Batool

Toqeer

Shah

2023

Environ Geochem Health

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A multivariate statistical approach for monitoring of groundwater quality: a case study of Beri block, Haryana, India

Cited by 13 publications

References 21 publications

Hydrochemical characterization of groundwater quality using chemometric analysis and water quality indices in the foothills of Himalayas

Hydrochemical characterization of groundwater quality using chemometric analysis and water quality indices in the foothills of Himalayas

Simulating contaminant transport in unsaturated and saturated groundwater zones

Assessment of water quality, trace metal pollution, source apportionment and health risks in the groundwater of Chakwal, Pakistan

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