Browsing by Author "Supriya Chaudhary"

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A bibliometric analysis of statistical methods used for river water quality assessment & monitoring during the last three decades (1992–2023)
(John Wiley and Sons Inc, 2025) Supriya Chaudhary; Chhavi Siwach; Shivraj Anand; Virendra kumar Mishra
In the present study, the bibliometric study was performed to assess the river water quality using statistical techniques. There were 681 articles pertinent to river water quality assessment using statistical methods published by the Scopus database from 1992 to 2023. A bibliometric analysis pinpoints the most notable and productive journals, scholars, publications and nations in the subject of study. Keyword analysis also found that river water quality assessment using statistical methods such as machine learning, water quality indexing and health risk assessment are hot topics. The analysis revealed four distinct, interconnected themes that effectively characterize the current state of research on river water quality assessment using statistical methods. These four thematic clusters represent the major areas of focus and methodological approaches currently employed in this field. Based on these identified clusters, highlight promising avenues for future research, suggesting how these established themes can be further developed and expanded upon to advance the field. Subsequently, a research framework was introduced, outlining potential future research directions. This bibliometric analysis provides a comprehensive overview of existing research on river water quality assessment. This study synthesizes prior research to map trends, key contributions and gaps, providing an overview of the field's development. © 2025 CIWEM.
Assessing the water quality of River Ganga in Varanasi, India, through WQI, NPI, and multivariate techniques: a comprehensive study
(IWA Publishing, 2024) Gurudatta Singh; Supriya Chaudhary; Deepak Gupta; Virendra Kumar Mishra
In the present research water quality from nine different sampling points (S1–S9) from the River Ganga at Varanasi was examined for different water quality parameters, and multivariate statistical analyses were carried out. Subsequently, several indices, such as water quality index and Nemerow pollution index (NPI), were calculated. The results indicated that the Ganga River at Varanasi had high levels of coliform concentrations, altered pH, and elevated dissolved oxygen/biochemical oxygen demand and chemical oxygen demand values. The weighted arithmetic water quality index values revealed that sites S8, S9, and S2 were the most polluted and unfit for bathing and drinking. Most of the sampling sites have NPI values greater than 1 for several parameters, indicating high levels of pollution. The study revealed that the water quality is poor for bathing and drinking at most of the sites throughout the year. In addition, the upstream water quality assessment revealed that water quality was good compared with the heavily contaminated downstream region. This knowledge can be useful for environmentalists, policymakers, and water resource managers to develop strategic plans to preserve the cultural and aesthetic worth of the Ganga River in the future. © 2024 The Authors.
Assessment of geochemistry and irrigation suitability of the River Ganga, Varanasi, India: PCA reduction for water quality index and health risk evaluation
(Springer, 2025) Gurudatta Singh; Supriya Chaudhary; Balendu Shekher Giri; Virendra kumar Mishra
Surface water chemistry of the River Ganga at Varanasi was analyzed at 10 locations over 3 years (2019–2021) across pre-monsoon, monsoon, and post-monsoon seasons. The study aimed to assess water parameters using principal component analysis (PCA), calculate the water quality index (WQI), determine processes governing water chemistry, evaluate irrigation suitability, and estimate non-carcinogenic health risks. The physical parameters measured included pH (8.12 ± 0.37, 8.17 ± 0.30, 7.80 ± 0.30), electrical conductivity (EC) (857.58 ± 163.17, 667.17 ± 162.15, 754.46 ± 179.32 µS/cm), total dissolved solid (TDS) (428.98 ± 81.74, 334.99 ± 80.75, 376.14 ± 88.91 mg/L), and total coliform (6201.96 ± 6914.17, 4363.76 ± 3379.98, 6176.53 ± 7080.62 MPN/100 mL) for pre-monsoon, monsoon, and post-monsoon seasons, respectively. WQI, based on 9 major parameters via PCA reduction, indicated poor water quality (53–74) across sites and seasons, except for S1, which was rated as good during the monsoon. The major ion concentrations in the samples followed the trend: (bicarbonate) HCO3⁻ (360.20 mg/L) > (chloride) Cl⁻ (59.80 mg/L) > (sodium) Na⁺ (53.10 mg/L) > (calcium) Ca2⁺ (44.61 mg/L) > (sulphate) SO₄2⁻ (43.81 mg/L) > (magnesium) Mg2⁺ (24.50 mg/L) > (potassium) K⁺ (5.20 mg/L) > (phosphate) PO₄3⁻ (2.41 mg/L) > (fluoride) F⁻ (0.52 mg/L), indicating alkaline water. The Piper diagram is dominated by Ca-Mg-HCO3 and mixed SO4-Cl hydrochemical facies, while the Gibbs plot suggested rock-water interaction as the key driver of ion chemistry. Irrigation indices [sodium percentage (Na%); sodium absorption ratio (SAR); Kelly index (Ki); permeability index (PI); magnesium hazard (MH)] indicated suitability for irrigation. Non-carcinogenic risk assessment showed children were more sensitive to fluoride and chloride ingestion, while teenagers were more affected through dermal exposure. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2025.
Characterization of groundwater potability and irrigation potential in Uttar Pradesh, India using water quality index and multivariate statistics
(IWA Publishing, 2024) Supriya Chaudhary; Gurudatta Singh; Deepak Gupta; Suruchi Singh Maunas; Virendra Kumar Mishra
This study includes groundwater quality data from 290 monitoring sites from 69 districts of Uttar Pradesh, India. The analysis of the data showed that 98.97, 24.48, 52.07, and 68.97% of groundwater samples had concentrations of electrical conductivity (EC), total hardness (TH), Mg2þ, and HCO3-, respectively, higher than the maximum permissible limit. Groundwater quality index (GWQI) was calculated for these 290 monitoring sites which revealed that 21 sites (7.24%) had inappropriate GWQI for drinking water, and 18 sites (6.21%) had an unsuitable index for irrigation. Most of the sampling sites (98.97%) showed high EC contents in groundwater with a mean value of 999.33 μS/cm. Fluoride content was found within the permissible limits in 95.52% of the samples, while 4.48% had high concentrations. The use of hierarchical cluster analysis differentiated all the sites into two clusters: one with high pollution and the other with low pollution. Significant correlations exist between physicochemical and irrigation indicators in the correlation matrix. High loadings of EC, TH, Ca2þ, Mg2þ, Naþ, Cl-, and SO42- were identified in the first principal component, which are thought to be pollution-controlled processes from anthropogenic sources. According to the Chadha diagram, CaHCO3 and Ca–Mg–HCl were the two most prevalent chemicals in the water. © 2024 The Authors.
Hydrochemical assessment of groundwater quality in the Narmada River Basin (Central India)
(IWA Publishing, 2023) Deepak Gupta; Supriya Chaudhary; Anubhuti Singh; Reetika Shukla; Virendra Kumar Mishra
This study details the hydrochemical characterization and human health risk assessment of groundwater in the Narmada River Basin. The study was performed based on data collected from 305 groundwater sample stations in the Narmada River Basin. Hydrochemical evaluation illustrated that cationic ions in the upper and middle Narmada Basin were dominated by Ca2þ; however, in the lower basin it was dominated by Naþ ions. Similarly, anionic ions were dominated by HCO3- throughout the basin. A Chadha plot drawn from the collected data inferred that most groundwater belonged to the recharge water category (Ca-Mg-HCO3 type). Base-exchange indices of the collected data confirmed the presence of Naþ-SO42- type of groundwater. Meteoric genesis indices indicated deep meteoric percolation groundwater. Further, Gibbs plots categorized groundwater samples in the rock dominated section, while chloro-alkaline indices confirmed direct as well as reverse ion-exchange reactions governing groundwater quality. Water Quality Index values showed that groundwater ranged from excellent to very poor. Human health risk of the Narmada River confirmed the non-carcinogenic risk for Nitrate (NO3-) and Fluoride (F-) ions. However, several indices justified that groundwater was ideal for irrigation. However, groundwater treatment is recommended before direct consumption such as drinking. © 2023 The Authors.
Multivariate Approach to Understanding Ganga River Water Quality in Varanasi: A Case Study
(Taylor and Francis Ltd., 2025) Supriya Chaudhary; Virendra kumar Mishra
To establish a foundation for mitigation of river water pollution and ensuring long-term water quality management, this investigation explored the spatial and temporal variability of water quality parameters of the river Ganga at Varanasi. Present study explored the monthly data collected from 14 sampling sites located along the river Ganga at Varanasi between 2017 and 2023. One-way analysis of variance (ANOVA) was used to assess the significance of spatiotemporal variations in river water quality. Additionally, cluster analysis (CA) was utilized to identify spatial groupings (clusters) within the river segment that exhibit similar water quality characteristics. A qualitative assessment of the possible causes of river water contamination and their respective contributions was conducted using principal component analysis (PCA). The two principal components (PCs) that explained the most variance in the water quality data were PC1 (46.546%) and PC2 (24.644%). While there has been a general enhancement in water quality parameters, spatial analysis revealed consistently lower water quality upstream compared to downstream locations. The study offers a comprehensive analysis to identify the precise reasons behind water contamination of river Ganga at Varanasi. © 2025 Informa UK Limited, trading as Taylor & Francis Group.
Simulating and predicting surface water quality for drinking and bathing purposes through combined approach of PCA, entropy-based WQI, and stochastic models
(Springer Science and Business Media Deutschland GmbH, 2024) Supriya Chaudhary; Abinayarajam Duraiyarasan; Deepak Gupta; Virendra Kumar Mishra
Freshwater resources, specially surface water are under threat due to over extraction, discharge of pollutants and improper waste disposal. This study investigates the present status of water quality of the River Ganga at Varanasi, India and further predict its future status using Principal Component Analysis (PCA), Entropy water quality index (EWQI) and Stochastic models. To begin with, water quality data of 37 variables for eleven years were acquired followed by which PCA was applied which reduced the number of water quality variables from 37 to 13. EWQI of River Ganga was calculated for drinking and bathing purposes by using these 13 variables. Most of the physico-chemical variables were within the permissible limit. The EWQI values were calculated for all the samples indicated that none of the water sample was suitable for drinking without treatment. However, 74.24% of the samples were classified as fair, 10.60% as poor, and 15.15% as unfit for bathing. Five different time-series models with 10 different structures were accessed then compared the effectiveness of various time series models in predicting water quality with the help of data from the past eleven years. Finally, the chosen models were used to predict future water quality variables and EWQI for both drinking and bathing purposes. The optimized models were selected based on auto-correlation function and partial auto-correlation function as well as the use of Akaike information criteria and Bayesian Information Criteria. This research suggests that time series modelling can be a cost-effective and time-saving approach for long-term water quality monitoring. Graphical abstract: (Figure presented.) © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.