Groundwater quality assessment using statistical approach and water quality index in Ejisu-Juaben Municipality, Ghana

Boateng, Thomas Kwame; Opoku, Francis; Acquaah, Samuel Osafo; Akoto, Osei

doi:10.1007/s12665-015-5105-0

Cited by 184 publications

(90 citation statements)

References 43 publications

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“…Normal distribution of data is an essential requirement for multivariate statistical analyses because the analyses will be valid only if the standard deviations (variances) are low (very close to 0). Else, the parameters with the highest variances will influence the analysis (Güler et al 2002;Cloutier et al 2008;Yidana et al 2011;Boateng et al 2016). The raw data indicated that Ca, Na, HCO 3 − and SO 4 2− were very close to normal distribution, but the distribution pattern of other parameters was not normal.…”

Section: Data Pretreatmentmentioning

confidence: 99%

Groundwater quality assessment of urban Bengaluru using multivariate statistical techniques

Gulgundi

Shetty

2018

Appl Water Sci

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Groundwater quality deterioration due to anthropogenic activities has become a subject of prime concern. The objective of the study was to assess the spatial and temporal variations in groundwater quality and to identify the sources in the western half of the Bengaluru city using multivariate statistical techniques. Water quality index rating was calculated for pre and post monsoon seasons to quantify overall water quality for human consumption. The post-monsoon samples show signs of poor quality in drinking purpose compared to pre-monsoon. Cluster analysis (CA), principal component analysis (PCA) and discriminant analysis (DA) were applied to the groundwater quality data measured on 14 parameters from 67 sites distributed across the city. Hierarchical cluster analysis (CA) grouped the 67 sampling stations into two groups, cluster 1 having high pollution and cluster 2 having lesser pollution. Discriminant analysis (DA) was applied to delineate the most meaningful parameters accounting for temporal and spatial variations in groundwater quality of the study area. Temporal DA identified pH as the most important parameter, which discriminates between water quality in the pre-monsoon and post-monsoon seasons and accounts for 72% seasonal assignation of cases. Spatial DA identified Mg, Cl and NO 3 as the three most important parameters discriminating between two clusters and accounting for 89% spatial assignation of cases. Principal component analysis was applied to the dataset obtained from the two clusters, which evolved three factors in each cluster, explaining 85.4 and 84% of the total variance, respectively. Varifactors obtained from principal component analysis showed that groundwater quality variation is mainly explained by dissolution of minerals from rock water interactions in the aquifer, effect of anthropogenic activities and ion exchange processes in water.

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Section: Data Pretreatmentmentioning

confidence: 99%

Groundwater quality assessment of urban Bengaluru using multivariate statistical techniques

Gulgundi

Shetty

2018

Appl Water Sci

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“…WQI is defined as a rating that reflects the composite influence of different water quality parameters (Sahu and Sikdar 2008). It is an important parameter for assessing groundwater quality and its suitability for drinking purposes (Tiwari and Mishra 1985;Singh 1992;Subba 1997;Mishra and Patel 2001;Naik and Purohit 2001;Avvannavar and Shrihari 2008;Pawar et al 2014;Boateng et al 2016).…”

Section: Water Quality Index (Wqi)mentioning

confidence: 99%

“…The availability of good quality water is vital for life, wellbeing, food and socio-economic development of mankind and it is generally obtained from two principal natural sources: surface water such as fresh water lakes, rivers, streams etc. and ground water such as borehole water and well water (McMurry and Fay 2004;Mendie 2005;Boateng et al 2016). However, poor contaminated water can be threaten to health, more over to the subsistence of the biotic integrity and therefore hinders the ecosystem services and functions of aquatic ecosystems.…”

Section: Introductionmentioning

confidence: 99%

“…Prevention and control of the surface water pollution must rely on the reliable information of water quality and identification of pollutant sources (Simeonov et al 2003;Shrestha and Kazama 2007;Bu et al 2009;Howladar et al 2017;Howladar 2017). Groundwater moves through porespaces within rocks and reacts with minerals that make up the rocks in the course of migration (Amadi et al 2012;Boateng et al 2016). Groundwater quality in any locality takes after the chemical composition of the aquifer through which it migrates in accordance with the hydrological cycle and flow direction (Offodile 1983;Amadi et al 2010;Boateng et al 2016).…”

Section: Introductionmentioning

confidence: 99%

“…Groundwater moves through porespaces within rocks and reacts with minerals that make up the rocks in the course of migration (Amadi et al 2012;Boateng et al 2016). Groundwater quality in any locality takes after the chemical composition of the aquifer through which it migrates in accordance with the hydrological cycle and flow direction (Offodile 1983;Amadi et al 2010;Boateng et al 2016). The aim of this study is to evaluate the hydrochemical characteristics, water quality, contamination as well as sources of contamination of ground and surface water around Maddhapara Granite Mining Industrial Area, Northwest Bangladesh.…”

Section: Introductionmentioning

confidence: 99%

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An application of Water Quality Index (WQI) and multivariate statistics to evaluate the water quality around Maddhapara Granite Mining Industrial Area, Dinajpur, Bangladesh

2017

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Background: Pure water is an absolutely necessary component of the earth not only for life but also for sustainable socio-economic development of today's civilization. The aim of this study was to analysis the quality of water resources and to investigate the influences of mining activities on water quality around the Maddhapara Granite Mining area, Dinajpur, Bangladesh.Result: 31 samples from surface and groundwater were collected from this selected area to assess their hydrochemistry, suitability, and their possible sources of contamination. Consequently, in the case of physico-chemical analysis, the 24 parameters such as P H , Electrical Conductivity, TDS, TH, Caetc. were analyzed in laboratory. Multivariate statistical methods were adopted for determining the water quality and their sources of contamination. The Gibbs ratio plot suggests that most of the samples fall in the rock dominance fields and some are in the precipitation dominance field. Cluster analysis confirms that three main groups of water samples where cluster I includes 70.97% of water samples, cluster II and cluster III includes rest 22.58 and 6.45% of the water samples respectively. Factor Analysis/Principal Component Analysis (FA/PCA) illustrates five factors extracted which explain 75.89% of the total variance. Conclusion:The collective results of multivariate analysis and Water Quality Index implies that most of the areas around the mining area are dominated by the good to excellent quality water for different purposes. In addition, the results of this research will then be helpful to estimate the major sources of contamination in different areas within the framework of activities intending to improve the quality of water.

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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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Groundwater quality assessment using statistical approach and water quality index in Ejisu-Juaben Municipality, Ghana

Cited by 184 publications

References 43 publications

Groundwater quality assessment of urban Bengaluru using multivariate statistical techniques

Groundwater quality assessment of urban Bengaluru using multivariate statistical techniques

An application of Water Quality Index (WQI) and multivariate statistics to evaluate the water quality around Maddhapara Granite Mining Industrial Area, Dinajpur, Bangladesh

Simulating contaminant transport in unsaturated and saturated groundwater zones

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