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Assessment of hydrogeochemical processes in a coastal region: Application of multivariate statistical model
Hydrogeochemical studies have been carried out in a coastal region, using multivariate statistical model, for better understanding the controlling processes that influence the aquifer chemistry. Two principal components (PC1 and PC2) are extracted from the data set of chemical variables (pH, TDS, Ca...
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Published in: | Journal of the Geological Society of India 2014-10, Vol.84 (4), p.494-500 |
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description | Hydrogeochemical studies have been carried out in a coastal region, using multivariate statistical model, for better understanding the controlling processes that influence the aquifer chemistry. Two principal components (PC1 and PC2) are extracted from the data set of chemical variables (pH, TDS, Ca
2+
, Mg
2+
, Na
+
, K
+
, HCO
3
−
, Cl
−
, SO
4
2−
, NO
3
−
and F
−
), which account for 79% of the total variation in the quality of groundwater. The PC1 (salinity controlled process) includes the concentrations of TDS, Mg
2+
, Na
+
, K
+
, Cl
−
, SO
4
2−
and NO
3
−
, while the PC2 (alkalinity controlled process) comprises the concentrations of pH, HCO
3
−
and F
−
. The spatial distribution of PC scores identifies the locations of high salinity and alkalinity processes. The first process corresponds to the influences of geogenic, anthropogenic and marine sources, and the second one to the influence of water-soil-rock interaction. Thus, the present study shows the usefulness of multivariate statistical model as an effective means of interpretation of spatial controlling processes of groundwater chemistry. |
doi_str_mv | 10.1007/s12594-014-0155-6 |
format | article |
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2+
, Mg
2+
, Na
+
, K
+
, HCO
3
−
, Cl
−
, SO
4
2−
, NO
3
−
and F
−
), which account for 79% of the total variation in the quality of groundwater. The PC1 (salinity controlled process) includes the concentrations of TDS, Mg
2+
, Na
+
, K
+
, Cl
−
, SO
4
2−
and NO
3
−
, while the PC2 (alkalinity controlled process) comprises the concentrations of pH, HCO
3
−
and F
−
. The spatial distribution of PC scores identifies the locations of high salinity and alkalinity processes. The first process corresponds to the influences of geogenic, anthropogenic and marine sources, and the second one to the influence of water-soil-rock interaction. Thus, the present study shows the usefulness of multivariate statistical model as an effective means of interpretation of spatial controlling processes of groundwater chemistry.</description><identifier>ISSN: 0016-7622</identifier><identifier>EISSN: 0974-6889</identifier><identifier>DOI: 10.1007/s12594-014-0155-6</identifier><language>eng</language><publisher>India: Springer India</publisher><subject>Alkalinity ; Anthropogenic factors ; Aquifers ; Coastal areas ; Coastal zone ; Earth and Environmental Science ; Earth Sciences ; Geochemistry ; Geology ; Groundwater ; Hydrogeochemistry ; Hydrogeology ; Marine ; Mathematical models ; Multivariate analysis ; Salinity ; Spatial distribution ; Statistical analysis ; Statistical models</subject><ispartof>Journal of the Geological Society of India, 2014-10, Vol.84 (4), p.494-500</ispartof><rights>Geological Society of India 2014</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-a438t-268ad9179209717b3e3ea98a2bdc4c9000779727a405f1dcc6bf018197012f643</citedby><cites>FETCH-LOGICAL-a438t-268ad9179209717b3e3ea98a2bdc4c9000779727a405f1dcc6bf018197012f643</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,27903,27904</link.rule.ids></links><search><creatorcontrib>Subba Rao, N.</creatorcontrib><creatorcontrib>Vidyasagar, G.</creatorcontrib><creatorcontrib>Surya Rao, P.</creatorcontrib><creatorcontrib>Bhanumurthy, P.</creatorcontrib><title>Assessment of hydrogeochemical processes in a coastal region: Application of multivariate statistical model</title><title>Journal of the Geological Society of India</title><addtitle>J Geol Soc India</addtitle><description>Hydrogeochemical studies have been carried out in a coastal region, using multivariate statistical model, for better understanding the controlling processes that influence the aquifer chemistry. Two principal components (PC1 and PC2) are extracted from the data set of chemical variables (pH, TDS, Ca
2+
, Mg
2+
, Na
+
, K
+
, HCO
3
−
, Cl
−
, SO
4
2−
, NO
3
−
and F
−
), which account for 79% of the total variation in the quality of groundwater. The PC1 (salinity controlled process) includes the concentrations of TDS, Mg
2+
, Na
+
, K
+
, Cl
−
, SO
4
2−
and NO
3
−
, while the PC2 (alkalinity controlled process) comprises the concentrations of pH, HCO
3
−
and F
−
. The spatial distribution of PC scores identifies the locations of high salinity and alkalinity processes. The first process corresponds to the influences of geogenic, anthropogenic and marine sources, and the second one to the influence of water-soil-rock interaction. Thus, the present study shows the usefulness of multivariate statistical model as an effective means of interpretation of spatial controlling processes of groundwater chemistry.</description><subject>Alkalinity</subject><subject>Anthropogenic factors</subject><subject>Aquifers</subject><subject>Coastal areas</subject><subject>Coastal zone</subject><subject>Earth and Environmental Science</subject><subject>Earth Sciences</subject><subject>Geochemistry</subject><subject>Geology</subject><subject>Groundwater</subject><subject>Hydrogeochemistry</subject><subject>Hydrogeology</subject><subject>Marine</subject><subject>Mathematical models</subject><subject>Multivariate analysis</subject><subject>Salinity</subject><subject>Spatial distribution</subject><subject>Statistical analysis</subject><subject>Statistical models</subject><issn>0016-7622</issn><issn>0974-6889</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2014</creationdate><recordtype>article</recordtype><recordid>eNqNkU1r3DAQhkVJoZttf0BvhlxycTMj2_rIbVmSNLDQS3sWWlneOLWtjaQN7L_vuNtDCIT0IPTB876jmZexrwjfEEBeJeSNrkvAeTVNKT6wBWhZl0IpfUZnQFFKwfkndp7SI4CoQVUL9nuVkk9p9FMuQlc8HNsYdj64Bz_2zg7FPgbnZ6Top8IWLtiU6Tn6XR-m62K13w_EZbrM8vEw5P7Zxt5mXxCY-5T_2oyh9cNn9rGzQ_Jf_u1L9uv25uf6e7n5cXe_Xm1KW1cql1wo22qUmlMDKLeVr7zVyvJt62qngdqVWnJpa2g6bJ0T2w5QoZaAvBN1tWSXJ1_6_NPBp2zGPjk_DHby4ZAMKlASEWT1PyjUXNPg3kdpuAK0kkDoxSv0MRziRD0ThY3QUFHxJcMT5WJIKfrO7GM_2ng0CGYO1ZxCNRSqmUM1gjT8pEnETjsfXzi_KfoD0oajkg</recordid><startdate>20141001</startdate><enddate>20141001</enddate><creator>Subba Rao, N.</creator><creator>Vidyasagar, G.</creator><creator>Surya Rao, P.</creator><creator>Bhanumurthy, P.</creator><general>Springer India</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>04Q</scope><scope>04W</scope><scope>3V.</scope><scope>7UA</scope><scope>7XB</scope><scope>88I</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FK</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>BKSAR</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>F1W</scope><scope>FR3</scope><scope>GNUQQ</scope><scope>H96</scope><scope>HCIFZ</scope><scope>KR7</scope><scope>L.G</scope><scope>L6V</scope><scope>M2P</scope><scope>M7S</scope><scope>PATMY</scope><scope>PCBAR</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PTHSS</scope><scope>PYCSY</scope><scope>Q9U</scope><scope>7TG</scope><scope>KL.</scope></search><sort><creationdate>20141001</creationdate><title>Assessment of hydrogeochemical processes in a coastal region: Application of multivariate statistical model</title><author>Subba Rao, N. ; 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Two principal components (PC1 and PC2) are extracted from the data set of chemical variables (pH, TDS, Ca
2+
, Mg
2+
, Na
+
, K
+
, HCO
3
−
, Cl
−
, SO
4
2−
, NO
3
−
and F
−
), which account for 79% of the total variation in the quality of groundwater. The PC1 (salinity controlled process) includes the concentrations of TDS, Mg
2+
, Na
+
, K
+
, Cl
−
, SO
4
2−
and NO
3
−
, while the PC2 (alkalinity controlled process) comprises the concentrations of pH, HCO
3
−
and F
−
. The spatial distribution of PC scores identifies the locations of high salinity and alkalinity processes. The first process corresponds to the influences of geogenic, anthropogenic and marine sources, and the second one to the influence of water-soil-rock interaction. Thus, the present study shows the usefulness of multivariate statistical model as an effective means of interpretation of spatial controlling processes of groundwater chemistry.</abstract><cop>India</cop><pub>Springer India</pub><doi>10.1007/s12594-014-0155-6</doi><tpages>7</tpages></addata></record> |
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issn | 0016-7622 0974-6889 |
language | eng |
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source | Springer Nature |
subjects | Alkalinity Anthropogenic factors Aquifers Coastal areas Coastal zone Earth and Environmental Science Earth Sciences Geochemistry Geology Groundwater Hydrogeochemistry Hydrogeology Marine Mathematical models Multivariate analysis Salinity Spatial distribution Statistical analysis Statistical models |
title | Assessment of hydrogeochemical processes in a coastal region: Application of multivariate statistical model |
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