Hydrochemical characterization of groundwater system of biodiversity experimental field: Jena, Germany
Abstract Hydrochemical modeling, graphical methods, and different statistical techniques were applied to understand the nature of geological and hydrochemical processes in a shallow groundwater aquifer of the Jena biodiversity experimental field. Factor and cluster analyses were used to identify the...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Tessema, S. G. [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2012 |
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| Schlagwörter: |
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| Anmerkung: |
© Springer-Verlag Berlin Heidelberg 2012 |
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| Übergeordnetes Werk: |
Enthalten in: Environmental earth sciences - Berlin : Springer, 2009, 70(2012), 2 vom: 14. Dez., Seite 821-837 |
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| Übergeordnetes Werk: |
volume:70 ; year:2012 ; number:2 ; day:14 ; month:12 ; pages:821-837 |
| Links: |
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| DOI / URN: |
10.1007/s12665-012-2171-4 |
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SPR02668778X |
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| 100 | 1 | |a Tessema, S. G. |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Hydrochemical characterization of groundwater system of biodiversity experimental field: Jena, Germany |
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| 520 | |a Abstract Hydrochemical modeling, graphical methods, and different statistical techniques were applied to understand the nature of geological and hydrochemical processes in a shallow groundwater aquifer of the Jena biodiversity experimental field. Factor and cluster analyses were used to identify the governing underlying processes and to detect the spatial similarity between the sampling points. The hydrochemical modeling, using PHREEQC, was used to interpret the reactive minerals. Results of factor analysis indicated that there are five dominant factors which account for about 90 % of the variance of the chemical dataset in the cold season (March, April, November) and warm season (June, August). Factor analysis showed that 43 % of the variation in the cold season and 53 % of the variation in the warm season of the groundwater hydrochemical data are due to major cations and anions which reveals groundwater-geological matrix interaction. Redox and redox-sensitive elements are the next important factors and account for 15 % and 19 % variation in the cold season and warm season, respectively. The hydrochemical modeling using PHREEQC and X-ray diffraction results showed that calcite, dolomite, quartz, and siderite are reactive minerals and are responsible for changes in chemical composition. The hydrochemical data of the two seasons were also compared and the results showed that the groundwater chemistry of the study area varied seasonally in terms of some parameters such as mainly heavy metals (Ba, B, Fe, Mn, U, V, Zn, Sr, Ni), $ HCO_{3} $−, and DOC. | ||
| 650 | 4 | |a Jena experiment |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Multivariate statistics |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a PHREEQC |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Hydrochemical modeling |7 (dpeaa)DE-He213 | |
| 700 | 1 | |a Mirgorodsky, D. |4 aut | |
| 700 | 1 | |a Merten, D. |4 aut | |
| 700 | 1 | |a Hildebrandt, A. |4 aut | |
| 700 | 1 | |a Attinger, S. |4 aut | |
| 700 | 1 | |a Büchel, G. |4 aut | |
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10.1007/s12665-012-2171-4 doi (DE-627)SPR02668778X (SPR)s12665-012-2171-4-e DE-627 ger DE-627 rakwb eng Tessema, S. G. verfasserin aut Hydrochemical characterization of groundwater system of biodiversity experimental field: Jena, Germany 2012 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer-Verlag Berlin Heidelberg 2012 Abstract Hydrochemical modeling, graphical methods, and different statistical techniques were applied to understand the nature of geological and hydrochemical processes in a shallow groundwater aquifer of the Jena biodiversity experimental field. Factor and cluster analyses were used to identify the governing underlying processes and to detect the spatial similarity between the sampling points. The hydrochemical modeling, using PHREEQC, was used to interpret the reactive minerals. Results of factor analysis indicated that there are five dominant factors which account for about 90 % of the variance of the chemical dataset in the cold season (March, April, November) and warm season (June, August). Factor analysis showed that 43 % of the variation in the cold season and 53 % of the variation in the warm season of the groundwater hydrochemical data are due to major cations and anions which reveals groundwater-geological matrix interaction. Redox and redox-sensitive elements are the next important factors and account for 15 % and 19 % variation in the cold season and warm season, respectively. The hydrochemical modeling using PHREEQC and X-ray diffraction results showed that calcite, dolomite, quartz, and siderite are reactive minerals and are responsible for changes in chemical composition. The hydrochemical data of the two seasons were also compared and the results showed that the groundwater chemistry of the study area varied seasonally in terms of some parameters such as mainly heavy metals (Ba, B, Fe, Mn, U, V, Zn, Sr, Ni), $ HCO_{3} $−, and DOC. Jena experiment (dpeaa)DE-He213 Multivariate statistics (dpeaa)DE-He213 PHREEQC (dpeaa)DE-He213 Hydrochemical modeling (dpeaa)DE-He213 Mirgorodsky, D. aut Merten, D. aut Hildebrandt, A. aut Attinger, S. aut Büchel, G. aut Enthalten in Environmental earth sciences Berlin : Springer, 2009 70(2012), 2 vom: 14. Dez., Seite 821-837 (DE-627)599673451 (DE-600)2493699-6 1866-6299 nnns volume:70 year:2012 number:2 day:14 month:12 pages:821-837 https://dx.doi.org/10.1007/s12665-012-2171-4 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2360 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 70 2012 2 14 12 821-837 |
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10.1007/s12665-012-2171-4 doi (DE-627)SPR02668778X (SPR)s12665-012-2171-4-e DE-627 ger DE-627 rakwb eng Tessema, S. G. verfasserin aut Hydrochemical characterization of groundwater system of biodiversity experimental field: Jena, Germany 2012 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer-Verlag Berlin Heidelberg 2012 Abstract Hydrochemical modeling, graphical methods, and different statistical techniques were applied to understand the nature of geological and hydrochemical processes in a shallow groundwater aquifer of the Jena biodiversity experimental field. Factor and cluster analyses were used to identify the governing underlying processes and to detect the spatial similarity between the sampling points. The hydrochemical modeling, using PHREEQC, was used to interpret the reactive minerals. Results of factor analysis indicated that there are five dominant factors which account for about 90 % of the variance of the chemical dataset in the cold season (March, April, November) and warm season (June, August). Factor analysis showed that 43 % of the variation in the cold season and 53 % of the variation in the warm season of the groundwater hydrochemical data are due to major cations and anions which reveals groundwater-geological matrix interaction. Redox and redox-sensitive elements are the next important factors and account for 15 % and 19 % variation in the cold season and warm season, respectively. The hydrochemical modeling using PHREEQC and X-ray diffraction results showed that calcite, dolomite, quartz, and siderite are reactive minerals and are responsible for changes in chemical composition. The hydrochemical data of the two seasons were also compared and the results showed that the groundwater chemistry of the study area varied seasonally in terms of some parameters such as mainly heavy metals (Ba, B, Fe, Mn, U, V, Zn, Sr, Ni), $ HCO_{3} $−, and DOC. Jena experiment (dpeaa)DE-He213 Multivariate statistics (dpeaa)DE-He213 PHREEQC (dpeaa)DE-He213 Hydrochemical modeling (dpeaa)DE-He213 Mirgorodsky, D. aut Merten, D. aut Hildebrandt, A. aut Attinger, S. aut Büchel, G. aut Enthalten in Environmental earth sciences Berlin : Springer, 2009 70(2012), 2 vom: 14. Dez., Seite 821-837 (DE-627)599673451 (DE-600)2493699-6 1866-6299 nnns volume:70 year:2012 number:2 day:14 month:12 pages:821-837 https://dx.doi.org/10.1007/s12665-012-2171-4 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2360 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 70 2012 2 14 12 821-837 |
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10.1007/s12665-012-2171-4 doi (DE-627)SPR02668778X (SPR)s12665-012-2171-4-e DE-627 ger DE-627 rakwb eng Tessema, S. G. verfasserin aut Hydrochemical characterization of groundwater system of biodiversity experimental field: Jena, Germany 2012 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer-Verlag Berlin Heidelberg 2012 Abstract Hydrochemical modeling, graphical methods, and different statistical techniques were applied to understand the nature of geological and hydrochemical processes in a shallow groundwater aquifer of the Jena biodiversity experimental field. Factor and cluster analyses were used to identify the governing underlying processes and to detect the spatial similarity between the sampling points. The hydrochemical modeling, using PHREEQC, was used to interpret the reactive minerals. Results of factor analysis indicated that there are five dominant factors which account for about 90 % of the variance of the chemical dataset in the cold season (March, April, November) and warm season (June, August). Factor analysis showed that 43 % of the variation in the cold season and 53 % of the variation in the warm season of the groundwater hydrochemical data are due to major cations and anions which reveals groundwater-geological matrix interaction. Redox and redox-sensitive elements are the next important factors and account for 15 % and 19 % variation in the cold season and warm season, respectively. The hydrochemical modeling using PHREEQC and X-ray diffraction results showed that calcite, dolomite, quartz, and siderite are reactive minerals and are responsible for changes in chemical composition. The hydrochemical data of the two seasons were also compared and the results showed that the groundwater chemistry of the study area varied seasonally in terms of some parameters such as mainly heavy metals (Ba, B, Fe, Mn, U, V, Zn, Sr, Ni), $ HCO_{3} $−, and DOC. Jena experiment (dpeaa)DE-He213 Multivariate statistics (dpeaa)DE-He213 PHREEQC (dpeaa)DE-He213 Hydrochemical modeling (dpeaa)DE-He213 Mirgorodsky, D. aut Merten, D. aut Hildebrandt, A. aut Attinger, S. aut Büchel, G. aut Enthalten in Environmental earth sciences Berlin : Springer, 2009 70(2012), 2 vom: 14. Dez., Seite 821-837 (DE-627)599673451 (DE-600)2493699-6 1866-6299 nnns volume:70 year:2012 number:2 day:14 month:12 pages:821-837 https://dx.doi.org/10.1007/s12665-012-2171-4 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2360 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 70 2012 2 14 12 821-837 |
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10.1007/s12665-012-2171-4 doi (DE-627)SPR02668778X (SPR)s12665-012-2171-4-e DE-627 ger DE-627 rakwb eng Tessema, S. G. verfasserin aut Hydrochemical characterization of groundwater system of biodiversity experimental field: Jena, Germany 2012 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer-Verlag Berlin Heidelberg 2012 Abstract Hydrochemical modeling, graphical methods, and different statistical techniques were applied to understand the nature of geological and hydrochemical processes in a shallow groundwater aquifer of the Jena biodiversity experimental field. Factor and cluster analyses were used to identify the governing underlying processes and to detect the spatial similarity between the sampling points. The hydrochemical modeling, using PHREEQC, was used to interpret the reactive minerals. Results of factor analysis indicated that there are five dominant factors which account for about 90 % of the variance of the chemical dataset in the cold season (March, April, November) and warm season (June, August). Factor analysis showed that 43 % of the variation in the cold season and 53 % of the variation in the warm season of the groundwater hydrochemical data are due to major cations and anions which reveals groundwater-geological matrix interaction. Redox and redox-sensitive elements are the next important factors and account for 15 % and 19 % variation in the cold season and warm season, respectively. The hydrochemical modeling using PHREEQC and X-ray diffraction results showed that calcite, dolomite, quartz, and siderite are reactive minerals and are responsible for changes in chemical composition. The hydrochemical data of the two seasons were also compared and the results showed that the groundwater chemistry of the study area varied seasonally in terms of some parameters such as mainly heavy metals (Ba, B, Fe, Mn, U, V, Zn, Sr, Ni), $ HCO_{3} $−, and DOC. Jena experiment (dpeaa)DE-He213 Multivariate statistics (dpeaa)DE-He213 PHREEQC (dpeaa)DE-He213 Hydrochemical modeling (dpeaa)DE-He213 Mirgorodsky, D. aut Merten, D. aut Hildebrandt, A. aut Attinger, S. aut Büchel, G. aut Enthalten in Environmental earth sciences Berlin : Springer, 2009 70(2012), 2 vom: 14. Dez., Seite 821-837 (DE-627)599673451 (DE-600)2493699-6 1866-6299 nnns volume:70 year:2012 number:2 day:14 month:12 pages:821-837 https://dx.doi.org/10.1007/s12665-012-2171-4 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2360 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 70 2012 2 14 12 821-837 |
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10.1007/s12665-012-2171-4 doi (DE-627)SPR02668778X (SPR)s12665-012-2171-4-e DE-627 ger DE-627 rakwb eng Tessema, S. G. verfasserin aut Hydrochemical characterization of groundwater system of biodiversity experimental field: Jena, Germany 2012 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer-Verlag Berlin Heidelberg 2012 Abstract Hydrochemical modeling, graphical methods, and different statistical techniques were applied to understand the nature of geological and hydrochemical processes in a shallow groundwater aquifer of the Jena biodiversity experimental field. Factor and cluster analyses were used to identify the governing underlying processes and to detect the spatial similarity between the sampling points. The hydrochemical modeling, using PHREEQC, was used to interpret the reactive minerals. Results of factor analysis indicated that there are five dominant factors which account for about 90 % of the variance of the chemical dataset in the cold season (March, April, November) and warm season (June, August). Factor analysis showed that 43 % of the variation in the cold season and 53 % of the variation in the warm season of the groundwater hydrochemical data are due to major cations and anions which reveals groundwater-geological matrix interaction. Redox and redox-sensitive elements are the next important factors and account for 15 % and 19 % variation in the cold season and warm season, respectively. The hydrochemical modeling using PHREEQC and X-ray diffraction results showed that calcite, dolomite, quartz, and siderite are reactive minerals and are responsible for changes in chemical composition. The hydrochemical data of the two seasons were also compared and the results showed that the groundwater chemistry of the study area varied seasonally in terms of some parameters such as mainly heavy metals (Ba, B, Fe, Mn, U, V, Zn, Sr, Ni), $ HCO_{3} $−, and DOC. Jena experiment (dpeaa)DE-He213 Multivariate statistics (dpeaa)DE-He213 PHREEQC (dpeaa)DE-He213 Hydrochemical modeling (dpeaa)DE-He213 Mirgorodsky, D. aut Merten, D. aut Hildebrandt, A. aut Attinger, S. aut Büchel, G. aut Enthalten in Environmental earth sciences Berlin : Springer, 2009 70(2012), 2 vom: 14. Dez., Seite 821-837 (DE-627)599673451 (DE-600)2493699-6 1866-6299 nnns volume:70 year:2012 number:2 day:14 month:12 pages:821-837 https://dx.doi.org/10.1007/s12665-012-2171-4 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2360 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 70 2012 2 14 12 821-837 |
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Enthalten in Environmental earth sciences 70(2012), 2 vom: 14. Dez., Seite 821-837 volume:70 year:2012 number:2 day:14 month:12 pages:821-837 |
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Tessema, S. G. @@aut@@ Mirgorodsky, D. @@aut@@ Merten, D. @@aut@@ Hildebrandt, A. @@aut@@ Attinger, S. @@aut@@ Büchel, G. @@aut@@ |
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G.</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Hydrochemical characterization of groundwater system of biodiversity experimental field: Jena, Germany</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2012</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">© Springer-Verlag Berlin Heidelberg 2012</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract Hydrochemical modeling, graphical methods, and different statistical techniques were applied to understand the nature of geological and hydrochemical processes in a shallow groundwater aquifer of the Jena biodiversity experimental field. Factor and cluster analyses were used to identify the governing underlying processes and to detect the spatial similarity between the sampling points. The hydrochemical modeling, using PHREEQC, was used to interpret the reactive minerals. Results of factor analysis indicated that there are five dominant factors which account for about 90 % of the variance of the chemical dataset in the cold season (March, April, November) and warm season (June, August). Factor analysis showed that 43 % of the variation in the cold season and 53 % of the variation in the warm season of the groundwater hydrochemical data are due to major cations and anions which reveals groundwater-geological matrix interaction. Redox and redox-sensitive elements are the next important factors and account for 15 % and 19 % variation in the cold season and warm season, respectively. 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Tessema, S. G. |
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Tessema, S. G. misc Jena experiment misc Multivariate statistics misc PHREEQC misc Hydrochemical modeling Hydrochemical characterization of groundwater system of biodiversity experimental field: Jena, Germany |
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Hydrochemical characterization of groundwater system of biodiversity experimental field: Jena, Germany Jena experiment (dpeaa)DE-He213 Multivariate statistics (dpeaa)DE-He213 PHREEQC (dpeaa)DE-He213 Hydrochemical modeling (dpeaa)DE-He213 |
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Hydrochemical characterization of groundwater system of biodiversity experimental field: Jena, Germany |
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hydrochemical characterization of groundwater system of biodiversity experimental field: jena, germany |
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Hydrochemical characterization of groundwater system of biodiversity experimental field: Jena, Germany |
| abstract |
Abstract Hydrochemical modeling, graphical methods, and different statistical techniques were applied to understand the nature of geological and hydrochemical processes in a shallow groundwater aquifer of the Jena biodiversity experimental field. Factor and cluster analyses were used to identify the governing underlying processes and to detect the spatial similarity between the sampling points. The hydrochemical modeling, using PHREEQC, was used to interpret the reactive minerals. Results of factor analysis indicated that there are five dominant factors which account for about 90 % of the variance of the chemical dataset in the cold season (March, April, November) and warm season (June, August). Factor analysis showed that 43 % of the variation in the cold season and 53 % of the variation in the warm season of the groundwater hydrochemical data are due to major cations and anions which reveals groundwater-geological matrix interaction. Redox and redox-sensitive elements are the next important factors and account for 15 % and 19 % variation in the cold season and warm season, respectively. The hydrochemical modeling using PHREEQC and X-ray diffraction results showed that calcite, dolomite, quartz, and siderite are reactive minerals and are responsible for changes in chemical composition. The hydrochemical data of the two seasons were also compared and the results showed that the groundwater chemistry of the study area varied seasonally in terms of some parameters such as mainly heavy metals (Ba, B, Fe, Mn, U, V, Zn, Sr, Ni), $ HCO_{3} $−, and DOC. © Springer-Verlag Berlin Heidelberg 2012 |
| abstractGer |
Abstract Hydrochemical modeling, graphical methods, and different statistical techniques were applied to understand the nature of geological and hydrochemical processes in a shallow groundwater aquifer of the Jena biodiversity experimental field. Factor and cluster analyses were used to identify the governing underlying processes and to detect the spatial similarity between the sampling points. The hydrochemical modeling, using PHREEQC, was used to interpret the reactive minerals. Results of factor analysis indicated that there are five dominant factors which account for about 90 % of the variance of the chemical dataset in the cold season (March, April, November) and warm season (June, August). Factor analysis showed that 43 % of the variation in the cold season and 53 % of the variation in the warm season of the groundwater hydrochemical data are due to major cations and anions which reveals groundwater-geological matrix interaction. Redox and redox-sensitive elements are the next important factors and account for 15 % and 19 % variation in the cold season and warm season, respectively. The hydrochemical modeling using PHREEQC and X-ray diffraction results showed that calcite, dolomite, quartz, and siderite are reactive minerals and are responsible for changes in chemical composition. The hydrochemical data of the two seasons were also compared and the results showed that the groundwater chemistry of the study area varied seasonally in terms of some parameters such as mainly heavy metals (Ba, B, Fe, Mn, U, V, Zn, Sr, Ni), $ HCO_{3} $−, and DOC. © Springer-Verlag Berlin Heidelberg 2012 |
| abstract_unstemmed |
Abstract Hydrochemical modeling, graphical methods, and different statistical techniques were applied to understand the nature of geological and hydrochemical processes in a shallow groundwater aquifer of the Jena biodiversity experimental field. Factor and cluster analyses were used to identify the governing underlying processes and to detect the spatial similarity between the sampling points. The hydrochemical modeling, using PHREEQC, was used to interpret the reactive minerals. Results of factor analysis indicated that there are five dominant factors which account for about 90 % of the variance of the chemical dataset in the cold season (March, April, November) and warm season (June, August). Factor analysis showed that 43 % of the variation in the cold season and 53 % of the variation in the warm season of the groundwater hydrochemical data are due to major cations and anions which reveals groundwater-geological matrix interaction. Redox and redox-sensitive elements are the next important factors and account for 15 % and 19 % variation in the cold season and warm season, respectively. The hydrochemical modeling using PHREEQC and X-ray diffraction results showed that calcite, dolomite, quartz, and siderite are reactive minerals and are responsible for changes in chemical composition. The hydrochemical data of the two seasons were also compared and the results showed that the groundwater chemistry of the study area varied seasonally in terms of some parameters such as mainly heavy metals (Ba, B, Fe, Mn, U, V, Zn, Sr, Ni), $ HCO_{3} $−, and DOC. © Springer-Verlag Berlin Heidelberg 2012 |
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Hydrochemical characterization of groundwater system of biodiversity experimental field: Jena, Germany |
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Mirgorodsky, D. Merten, D. Hildebrandt, A. Attinger, S. Büchel, G. |
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| score |
7.3995314 |