Modeling groundwater quality over a humid subtropical region using numerical indices, earth observation datasets, and X-ray diffraction technique: a case study of Allahabad district, India

Water is undoubtedly the vital commodity for all living creatures and required for well-being of the human society. The present work is based on the surveys and chemical analyses performed on the collected groundwater samples in a part of the Ganga basin in order to understand the sources and evolut...

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Veröffentlicht in:Environmental geochemistry and health 2015-02, Vol.37 (1), p.157-180
Hauptverfasser: Singh, Sudhir Kumar, Srivastava, Prashant K, Singh, Dharmveer, Han, Dawei, Gautam, Sandeep Kumar, Pandey, A. C
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container_issue 1
container_start_page 157
container_title Environmental geochemistry and health
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creator Singh, Sudhir Kumar
Srivastava, Prashant K
Singh, Dharmveer
Han, Dawei
Gautam, Sandeep Kumar
Pandey, A. C
description Water is undoubtedly the vital commodity for all living creatures and required for well-being of the human society. The present work is based on the surveys and chemical analyses performed on the collected groundwater samples in a part of the Ganga basin in order to understand the sources and evolution of the water quality in the region. The two standard indices such as water quality index and synthetic pollution index for the classification of water in the region are computed. The soil and sediment analysis are carried out with the help of X-ray diffractometer (XRD) for the identification of possible source of ions in water from rock and soil weathering. The dominant minerals which include quartz, muscovite, plagioclase, and orthoclase are reported in the area. The study further utilizes the multivariate statistical techniques for handling large and complex datasets in order to get better information about the groundwater quality. The following statistical methods such as cluster analysis (CA), factor analysis (FA), and principal component analysis (PCA) are applied to handle the large datasets and to understand the latent structure of the data. Through FA/PCAs, we have identified a total of 3 factors in pre-monsoon and 4 factors in post-monsoon season, which are responsible for the whole data structure. These factors explain 77.62 and 82.39 % of the total variance of the pre- and post-monsoon datasets. On the other hand, CA depicted the regions that have similar pollutants origin. The average value of synthetic pollution index of groundwater during pre-monsoon is 9.27, while during post-monsoon, it has been recorded as 8.74. On the other hand, the average values of water quality index of groundwater during pre-monsoon and post-monsoon seasons are found as 217.59 and 233.02, respectively. The study indicates that there occurs an extensive urbanization with gradual vast development of various small- and large-scale industries, which is responsible for degradation in water quality. The overall analysis reveals that the agricultural runoff, waste disposal, leaching, and irrigation with wastewater are the main causes of groundwater pollution followed by some degree of pollution from geogenic sources such as rock and soil weathering, confirmed through XRD analysis.
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C</creatorcontrib><title>Modeling groundwater quality over a humid subtropical region using numerical indices, earth observation datasets, and X-ray diffraction technique: a case study of Allahabad district, India</title><title>Environmental geochemistry and health</title><addtitle>Environ Geochem Health</addtitle><addtitle>Environ Geochem Health</addtitle><description>Water is undoubtedly the vital commodity for all living creatures and required for well-being of the human society. The present work is based on the surveys and chemical analyses performed on the collected groundwater samples in a part of the Ganga basin in order to understand the sources and evolution of the water quality in the region. The two standard indices such as water quality index and synthetic pollution index for the classification of water in the region are computed. The soil and sediment analysis are carried out with the help of X-ray diffractometer (XRD) for the identification of possible source of ions in water from rock and soil weathering. The dominant minerals which include quartz, muscovite, plagioclase, and orthoclase are reported in the area. The study further utilizes the multivariate statistical techniques for handling large and complex datasets in order to get better information about the groundwater quality. The following statistical methods such as cluster analysis (CA), factor analysis (FA), and principal component analysis (PCA) are applied to handle the large datasets and to understand the latent structure of the data. Through FA/PCAs, we have identified a total of 3 factors in pre-monsoon and 4 factors in post-monsoon season, which are responsible for the whole data structure. These factors explain 77.62 and 82.39 % of the total variance of the pre- and post-monsoon datasets. 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The two standard indices such as water quality index and synthetic pollution index for the classification of water in the region are computed. The soil and sediment analysis are carried out with the help of X-ray diffractometer (XRD) for the identification of possible source of ions in water from rock and soil weathering. The dominant minerals which include quartz, muscovite, plagioclase, and orthoclase are reported in the area. The study further utilizes the multivariate statistical techniques for handling large and complex datasets in order to get better information about the groundwater quality. The following statistical methods such as cluster analysis (CA), factor analysis (FA), and principal component analysis (PCA) are applied to handle the large datasets and to understand the latent structure of the data. Through FA/PCAs, we have identified a total of 3 factors in pre-monsoon and 4 factors in post-monsoon season, which are responsible for the whole data structure. These factors explain 77.62 and 82.39 % of the total variance of the pre- and post-monsoon datasets. On the other hand, CA depicted the regions that have similar pollutants origin. The average value of synthetic pollution index of groundwater during pre-monsoon is 9.27, while during post-monsoon, it has been recorded as 8.74. On the other hand, the average values of water quality index of groundwater during pre-monsoon and post-monsoon seasons are found as 217.59 and 233.02, respectively. The study indicates that there occurs an extensive urbanization with gradual vast development of various small- and large-scale industries, which is responsible for degradation in water quality. The overall analysis reveals that the agricultural runoff, waste disposal, leaching, and irrigation with wastewater are the main causes of groundwater pollution followed by some degree of pollution from geogenic sources such as rock and soil weathering, confirmed through XRD analysis.</abstract><cop>Dordrecht</cop><pub>Springer-Verlag</pub><pmid>25086613</pmid><doi>10.1007/s10653-014-9638-z</doi><tpages>24</tpages></addata></record>
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subjects Agricultural runoff
Agriculture
Case studies
chemical analysis
cluster analysis
data collection
Diffraction
Earth and Environmental Science
Environment
Environmental Chemistry
Environmental Health
Environmental Monitoring
Factor analysis
Factor Analysis, Statistical
Geochemistry
Geologic Sediments - chemistry
groundwater
Groundwater - analysis
Groundwater - chemistry
groundwater contamination
Groundwater flow
Groundwater pollution
humans
India
Industry
ions
Leaching
Models, Chemical
Monsoons
muscovite
Numerical analysis
Original Paper
plagioclase
pollutants
Pollution index
Principal Component Analysis
Principal components analysis
Public Health
quartz
Rainforests
Rocks
Seasons
Sediment analysis
sediments
society
soil
Soil Science & Conservation
soil weathering
Statistical methods
subtropics
surveys
Terrestrial Pollution
Urbanization
variance
Waste disposal
Waste Water - chemistry
wastewater irrigation
Water analysis
Water Pollutants, Chemical - analysis
Water Quality
Water quality standards
Water sampling
Weathering
X-Ray Diffraction
title Modeling groundwater quality over a humid subtropical region using numerical indices, earth observation datasets, and X-ray diffraction technique: a case study of Allahabad district, India
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