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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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</creator><creatorcontrib>Singh, Sudhir Kumar ; Srivastava, Prashant K ; Singh, Dharmveer ; Han, Dawei ; Gautam, Sandeep Kumar ; Pandey, A. C</creatorcontrib><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.</description><identifier>ISSN: 0269-4042</identifier><identifier>EISSN: 1573-2983</identifier><identifier>DOI: 10.1007/s10653-014-9638-z</identifier><identifier>PMID: 25086613</identifier><language>eng</language><publisher>Dordrecht: Springer-Verlag</publisher><subject>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</subject><ispartof>Environmental geochemistry and health, 2015-02, Vol.37 (1), p.157-180</ispartof><rights>Springer Science+Business Media Dordrecht 2014</rights><rights>Springer Science+Business Media Dordrecht 2015</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-a474t-78f490deb875d9790bf1feeb9fb75d08d36c261e5e949b5f5caceaa5b9346b503</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s10653-014-9638-z$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s10653-014-9638-z$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,778,782,27907,27908,41471,42540,51302</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/25086613$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Singh, Sudhir Kumar</creatorcontrib><creatorcontrib>Srivastava, Prashant K</creatorcontrib><creatorcontrib>Singh, Dharmveer</creatorcontrib><creatorcontrib>Han, Dawei</creatorcontrib><creatorcontrib>Gautam, Sandeep Kumar</creatorcontrib><creatorcontrib>Pandey, A. 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. 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.</description><subject>Agricultural runoff</subject><subject>Agriculture</subject><subject>Case studies</subject><subject>chemical analysis</subject><subject>cluster analysis</subject><subject>data collection</subject><subject>Diffraction</subject><subject>Earth and Environmental Science</subject><subject>Environment</subject><subject>Environmental Chemistry</subject><subject>Environmental Health</subject><subject>Environmental Monitoring</subject><subject>Factor analysis</subject><subject>Factor Analysis, Statistical</subject><subject>Geochemistry</subject><subject>Geologic Sediments - chemistry</subject><subject>groundwater</subject><subject>Groundwater - analysis</subject><subject>Groundwater - chemistry</subject><subject>groundwater contamination</subject><subject>Groundwater flow</subject><subject>Groundwater pollution</subject><subject>humans</subject><subject>India</subject><subject>Industry</subject><subject>ions</subject><subject>Leaching</subject><subject>Models, Chemical</subject><subject>Monsoons</subject><subject>muscovite</subject><subject>Numerical analysis</subject><subject>Original Paper</subject><subject>plagioclase</subject><subject>pollutants</subject><subject>Pollution index</subject><subject>Principal Component Analysis</subject><subject>Principal components analysis</subject><subject>Public Health</subject><subject>quartz</subject><subject>Rainforests</subject><subject>Rocks</subject><subject>Seasons</subject><subject>Sediment analysis</subject><subject>sediments</subject><subject>society</subject><subject>soil</subject><subject>Soil Science & Conservation</subject><subject>soil weathering</subject><subject>Statistical methods</subject><subject>subtropics</subject><subject>surveys</subject><subject>Terrestrial Pollution</subject><subject>Urbanization</subject><subject>variance</subject><subject>Waste disposal</subject><subject>Waste Water - chemistry</subject><subject>wastewater irrigation</subject><subject>Water analysis</subject><subject>Water Pollutants, Chemical - analysis</subject><subject>Water Quality</subject><subject>Water quality standards</subject><subject>Water sampling</subject><subject>Weathering</subject><subject>X-Ray Diffraction</subject><issn>0269-4042</issn><issn>1573-2983</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2015</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNp9kctuFDEQRVsIRIbAB7ABS2xYpMFuux9mF0U8IgWxgEjsrHK7POOopz3xI2jybXwcnnRAiAUry65z6175VtVzRt8wSvu3kdGu5TVlopYdH-rbB9WKtT2vGznwh9WKNp2sBRXNUfUkxitKqezF8Lg6alo6dB3jq-rnZ29wcvOarIPPs_kBCQO5zjC5tCf-plyAbPLWGRKzTsHv3AgTCbh2fiY5HpRz3mK4e3azcSPGE4IQ0oZ4HTHcQDqgBhJETGUGsyHf6wB7Ypy1Aca7ecJxM7vrjO-K4VhQElM2JYIlp9MEG9BgiiCm4pROyHlxgqfVIwtTxGf353F1-eH9t7NP9cWXj-dnpxc1iF6kuh-skNSgHvrWyF5SbZlF1NLq8kAHw7ux6Ri2KIXUrW1HGBGg1ZKLTreUH1evl7274EvCmNTWxRFLrBl9jop1oi9_PXBZ0Ff_oFc-h7mkO1AN40Mv-kKxhRqDjzGgVbvgthD2ilF1qFYt1apSrTpUq26L5sX95qy3aP4ofndZgGYBYhnNawx_Wf9n68tFZMErWAcX1eXXhrKWUiaZFAP_BWcuvNo</recordid><startdate>20150201</startdate><enddate>20150201</enddate><creator>Singh, Sudhir Kumar</creator><creator>Srivastava, Prashant K</creator><creator>Singh, Dharmveer</creator><creator>Han, Dawei</creator><creator>Gautam, Sandeep Kumar</creator><creator>Pandey, A. 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C</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>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</atitle><jtitle>Environmental geochemistry and health</jtitle><stitle>Environ Geochem Health</stitle><addtitle>Environ Geochem Health</addtitle><date>2015-02-01</date><risdate>2015</risdate><volume>37</volume><issue>1</issue><spage>157</spage><epage>180</epage><pages>157-180</pages><issn>0269-4042</issn><eissn>1573-2983</eissn><abstract>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.</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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