Chemometric Analysis of Surface Water Quality Data: Case Study of the Gorganrud River Basin, Iran
Canonical correlation analysis (CCA), principal component analysis (PCA), and principal factor analysis (PFA) have been adopted to provide ease of understanding: interpretation of a large complex data set in the Gorganrud River monitoring networks, evaluation of the temporal and spatial variations o...
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| Veröffentlicht in: | Environmental modeling & assessment 2012-08, Vol.17 (4), p.411-420 |
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| creator | Noori, Roohollah Karbassi, Abdulreza Khakpour, Amir Shahbazbegian, Mohammadreza Badam, Hassan Mohammadi Khalf Vesali-Naseh, Mohammadreza |
| description | Canonical correlation analysis (CCA), principal component analysis (PCA), and principal factor analysis (PFA) have been adopted to provide ease of understanding: interpretation of a large complex data set in the Gorganrud River monitoring networks, evaluation of the temporal and spatial variations of water quality, and finally identification of monitoring stations and parameters which are most important in assessing annual variations of water quality in the river. In accomplishing the research, 11 surface water quality data related to both of physical and chemical parameters have been collected from seven monitoring stations from 1996 to 2002. In general, our results from CCA method indicated strong relationship between physical and chemical parameters in the Gorganrud River. In addition, analyzing data through the PCA and PFA techniques revealed that all monitoring stations are important in explaining the annual variation of data set. From the point of view of the degree of importance of parameters contributing to water quality variations, further investigations by running two scenarios (rotated factor correlation coefficient value equal to 0.95 and 0.90 for the first and second scenarios, respectively) showed that the important parameters in one season may not be important for another season. For example, unlike in summer, water temperature, total suspended solids, total phosphorous, and nitrate parameters were important, electrical conductivity, and turbidity parameters had been realized as important parameters in spring through the first scenario. |
| doi_str_mv | 10.1007/s10666-011-9302-2 |
| format | Article |
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In accomplishing the research, 11 surface water quality data related to both of physical and chemical parameters have been collected from seven monitoring stations from 1996 to 2002. In general, our results from CCA method indicated strong relationship between physical and chemical parameters in the Gorganrud River. In addition, analyzing data through the PCA and PFA techniques revealed that all monitoring stations are important in explaining the annual variation of data set. From the point of view of the degree of importance of parameters contributing to water quality variations, further investigations by running two scenarios (rotated factor correlation coefficient value equal to 0.95 and 0.90 for the first and second scenarios, respectively) showed that the important parameters in one season may not be important for another season. For example, unlike in summer, water temperature, total suspended solids, total phosphorous, and nitrate parameters were important, electrical conductivity, and turbidity parameters had been realized as important parameters in spring through the first scenario.</description><identifier>ISSN: 1420-2026</identifier><identifier>EISSN: 1573-2967</identifier><identifier>DOI: 10.1007/s10666-011-9302-2</identifier><language>eng</language><publisher>Dordrecht: Springer Netherlands</publisher><subject>Analysis ; Annual variations ; Applications of Mathematics ; Aquatic resources ; Case studies ; Civil engineering ; Correlation analysis ; Correlation coefficient ; Datasets ; Discriminant analysis ; Earth and Environmental Science ; Electrical conductivity ; Environment ; Environmental monitoring ; Environmental quality ; Factor analysis ; Freshwater ; Groundwater ; Math. Appl. in Environmental Science ; Mathematical Modeling and Industrial Mathematics ; Mathematical models ; Monitoring ; Operations Research/Decision Theory ; Principal components analysis ; River basins ; Rivers ; Seasonal variations ; Seasons ; Stations ; Statistical analysis ; Studies ; Surface water ; Total suspended solids ; Turbidity ; Variables ; VOCs ; Volatile organic compounds ; Water pollution ; Water quality ; Water temperature</subject><ispartof>Environmental modeling & assessment, 2012-08, Vol.17 (4), p.411-420</ispartof><rights>Springer Science+Business Media B.V. 2011</rights><rights>COPYRIGHT 2012 Springer</rights><rights>Springer Science+Business Media B.V. 2012</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c388t-e2725b119492ae943494096edc27b3fa328bd168204e7ab14fc3deb15b83be5a3</citedby><cites>FETCH-LOGICAL-c388t-e2725b119492ae943494096edc27b3fa328bd168204e7ab14fc3deb15b83be5a3</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/s10666-011-9302-2$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s10666-011-9302-2$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,780,784,27924,27925,41488,42557,51319</link.rule.ids></links><search><creatorcontrib>Noori, Roohollah</creatorcontrib><creatorcontrib>Karbassi, Abdulreza</creatorcontrib><creatorcontrib>Khakpour, Amir</creatorcontrib><creatorcontrib>Shahbazbegian, Mohammadreza</creatorcontrib><creatorcontrib>Badam, Hassan Mohammadi Khalf</creatorcontrib><creatorcontrib>Vesali-Naseh, Mohammadreza</creatorcontrib><title>Chemometric Analysis of Surface Water Quality Data: Case Study of the Gorganrud River Basin, Iran</title><title>Environmental modeling & assessment</title><addtitle>Environ Model Assess</addtitle><description>Canonical correlation analysis (CCA), principal component analysis (PCA), and principal factor analysis (PFA) have been adopted to provide ease of understanding: interpretation of a large complex data set in the Gorganrud River monitoring networks, evaluation of the temporal and spatial variations of water quality, and finally identification of monitoring stations and parameters which are most important in assessing annual variations of water quality in the river. 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Roohollah</au><au>Karbassi, Abdulreza</au><au>Khakpour, Amir</au><au>Shahbazbegian, Mohammadreza</au><au>Badam, Hassan Mohammadi Khalf</au><au>Vesali-Naseh, Mohammadreza</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Chemometric Analysis of Surface Water Quality Data: Case Study of the Gorganrud River Basin, Iran</atitle><jtitle>Environmental modeling & assessment</jtitle><stitle>Environ Model Assess</stitle><date>2012-08-01</date><risdate>2012</risdate><volume>17</volume><issue>4</issue><spage>411</spage><epage>420</epage><pages>411-420</pages><issn>1420-2026</issn><eissn>1573-2967</eissn><abstract>Canonical correlation analysis (CCA), principal component analysis (PCA), and principal factor analysis (PFA) have been adopted to provide ease of understanding: interpretation of a large complex data set in the Gorganrud River monitoring networks, evaluation of the temporal and spatial variations of water quality, and finally identification of monitoring stations and parameters which are most important in assessing annual variations of water quality in the river. In accomplishing the research, 11 surface water quality data related to both of physical and chemical parameters have been collected from seven monitoring stations from 1996 to 2002. In general, our results from CCA method indicated strong relationship between physical and chemical parameters in the Gorganrud River. In addition, analyzing data through the PCA and PFA techniques revealed that all monitoring stations are important in explaining the annual variation of data set. From the point of view of the degree of importance of parameters contributing to water quality variations, further investigations by running two scenarios (rotated factor correlation coefficient value equal to 0.95 and 0.90 for the first and second scenarios, respectively) showed that the important parameters in one season may not be important for another season. For example, unlike in summer, water temperature, total suspended solids, total phosphorous, and nitrate parameters were important, electrical conductivity, and turbidity parameters had been realized as important parameters in spring through the first scenario.</abstract><cop>Dordrecht</cop><pub>Springer Netherlands</pub><doi>10.1007/s10666-011-9302-2</doi><tpages>10</tpages></addata></record> |
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| subjects | Analysis Annual variations Applications of Mathematics Aquatic resources Case studies Civil engineering Correlation analysis Correlation coefficient Datasets Discriminant analysis Earth and Environmental Science Electrical conductivity Environment Environmental monitoring Environmental quality Factor analysis Freshwater Groundwater Math. Appl. in Environmental Science Mathematical Modeling and Industrial Mathematics Mathematical models Monitoring Operations Research/Decision Theory Principal components analysis River basins Rivers Seasonal variations Seasons Stations Statistical analysis Studies Surface water Total suspended solids Turbidity Variables VOCs Volatile organic compounds Water pollution Water quality Water temperature |
| title | Chemometric Analysis of Surface Water Quality Data: Case Study of the Gorganrud River Basin, Iran |
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