Hydrochemical characteristics and identification of groundwater pollution sources in tropical savanna
Groundwater pollution of the watershed is mainly influenced by the multifaceted interactions of natural and anthropogenic processes. In this study, classic chemical and multivariate statistical methods were utilized to assess the groundwater quality and ascertain the potential contamination sources...
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| Veröffentlicht in: | Environmental science and pollution research international 2022-05, Vol.29 (25), p.37384-37398 |
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| creator | Abdulsalam, Abduljalal Ramli, Mohammad Firuz Jamil, Nor Rohaizah Ashaari, Zulfa Hanan Umar, Da’u Abba |
| description | Groundwater pollution of the watershed is mainly influenced by the multifaceted interactions of natural and anthropogenic processes. In this study, classic chemical and multivariate statistical methods were utilized to assess the groundwater quality and ascertain the potential contamination sources affecting the groundwater quality of Galma sub-watershed in a tropical savanna. For this purpose, the data set of 18 groundwater quality variables covering 57 different sampling boreholes (BH) was used. The groundwater samples essentially contained the cations in the following order of dominance: Ca
2+
> Na
+
> Mg
2+
> K
+
. However, the anions had HCO
3
–
> Cl
–
> SO
4
–2
> NO
3
–
respectively. The hydrochemical facies classified the groundwater types of the sub-watershed into mixed Ca–Mg–Cl type of water, which means no cations and anions exceeds 50%. The second dominant water type was Ca–Cl. The Mg–HCO
3
water type was found in BH 9, and Na–Cl water type in BH 29 of the studied area. The weathering of the basement rocks was responsible for the concentrations of these ions in the groundwater chemistry of the sub-watershed. Hierarchical cluster analysis (HCA) grouped the groundwater samples (boreholes) into five clusters that are statistically significant regarding the similarities of groundwater quality characteristics. The principal component analysis (PCA) extracted two major principal components explained around 65% of the variance and suggested the natural and anthropogenic processes especially the agricultural pollutants including synthetic fertilizers, and leaching of agricultural waste as the main factors affecting the groundwater quality. The integrated method proved to be efficient and robust for groundwater quality evaluation, as it guaranteed the precise assessment of groundwater chemistry in the sub-watershed of the tropical savanna. The findings of this investigation could be useful to the policy makers for developing effective groundwater management plans for the groundwater resources and protection of the sub-watershed. |
| doi_str_mv | 10.1007/s11356-022-18552-0 |
| format | Article |
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2+
> Na
+
> Mg
2+
> K
+
. However, the anions had HCO
3
–
> Cl
–
> SO
4
–2
> NO
3
–
respectively. The hydrochemical facies classified the groundwater types of the sub-watershed into mixed Ca–Mg–Cl type of water, which means no cations and anions exceeds 50%. The second dominant water type was Ca–Cl. The Mg–HCO
3
water type was found in BH 9, and Na–Cl water type in BH 29 of the studied area. The weathering of the basement rocks was responsible for the concentrations of these ions in the groundwater chemistry of the sub-watershed. Hierarchical cluster analysis (HCA) grouped the groundwater samples (boreholes) into five clusters that are statistically significant regarding the similarities of groundwater quality characteristics. The principal component analysis (PCA) extracted two major principal components explained around 65% of the variance and suggested the natural and anthropogenic processes especially the agricultural pollutants including synthetic fertilizers, and leaching of agricultural waste as the main factors affecting the groundwater quality. The integrated method proved to be efficient and robust for groundwater quality evaluation, as it guaranteed the precise assessment of groundwater chemistry in the sub-watershed of the tropical savanna. The findings of this investigation could be useful to the policy makers for developing effective groundwater management plans for the groundwater resources and protection of the sub-watershed.</description><identifier>ISSN: 0944-1344</identifier><identifier>EISSN: 1614-7499</identifier><identifier>DOI: 10.1007/s11356-022-18552-0</identifier><identifier>PMID: 35066782</identifier><language>eng</language><publisher>Berlin/Heidelberg: Springer Berlin Heidelberg</publisher><subject>Agricultural pollution ; Agricultural wastes ; Agrochemicals ; Anions ; Anions - analysis ; Anthropogenic factors ; Aquatic Pollution ; Atmospheric Protection/Air Quality Control/Air Pollution ; Boreholes ; calcium ; Calcium ions ; Cations ; Cluster analysis ; Contamination ; data collection ; Earth and Environmental Science ; Ecotoxicology ; Environment ; Environmental Chemistry ; Environmental Health ; Environmental Monitoring ; Environmental science ; Fertilizers ; Grassland ; Groundwater ; Groundwater chemistry ; groundwater contamination ; Groundwater data ; Groundwater management ; Groundwater pollution ; Groundwater quality ; Human influences ; hydrochemistry ; Ions - analysis ; issues and policy ; Leaching ; Magnesium ; Pollutants ; Pollution sources ; principal component analysis ; Principal components analysis ; Quality assessment ; Research Article ; Savannahs ; savannas ; Sodium ; Statistical analysis ; Statistical methods ; subwatersheds ; variance ; Waste Water Technology ; Water - analysis ; Water Management ; Water Pollutants, Chemical - analysis ; Water Pollution Control ; Water Quality ; Water resources ; Water sampling ; Watersheds</subject><ispartof>Environmental science and pollution research international, 2022-05, Vol.29 (25), p.37384-37398</ispartof><rights>The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022</rights><rights>2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.</rights><rights>The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c408t-950bbca5bce0e1f78c67fcee4b20f692790da138055b044887868a77d12e1daf3</citedby><cites>FETCH-LOGICAL-c408t-950bbca5bce0e1f78c67fcee4b20f692790da138055b044887868a77d12e1daf3</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/s11356-022-18552-0$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s11356-022-18552-0$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,776,780,27901,27902,41464,42533,51294</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/35066782$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Abdulsalam, Abduljalal</creatorcontrib><creatorcontrib>Ramli, Mohammad Firuz</creatorcontrib><creatorcontrib>Jamil, Nor Rohaizah</creatorcontrib><creatorcontrib>Ashaari, Zulfa Hanan</creatorcontrib><creatorcontrib>Umar, Da’u Abba</creatorcontrib><title>Hydrochemical characteristics and identification of groundwater pollution sources in tropical savanna</title><title>Environmental science and pollution research international</title><addtitle>Environ Sci Pollut Res</addtitle><addtitle>Environ Sci Pollut Res Int</addtitle><description>Groundwater pollution of the watershed is mainly influenced by the multifaceted interactions of natural and anthropogenic processes. In this study, classic chemical and multivariate statistical methods were utilized to assess the groundwater quality and ascertain the potential contamination sources affecting the groundwater quality of Galma sub-watershed in a tropical savanna. For this purpose, the data set of 18 groundwater quality variables covering 57 different sampling boreholes (BH) was used. The groundwater samples essentially contained the cations in the following order of dominance: Ca
2+
> Na
+
> Mg
2+
> K
+
. However, the anions had HCO
3
–
> Cl
–
> SO
4
–2
> NO
3
–
respectively. The hydrochemical facies classified the groundwater types of the sub-watershed into mixed Ca–Mg–Cl type of water, which means no cations and anions exceeds 50%. The second dominant water type was Ca–Cl. The Mg–HCO
3
water type was found in BH 9, and Na–Cl water type in BH 29 of the studied area. The weathering of the basement rocks was responsible for the concentrations of these ions in the groundwater chemistry of the sub-watershed. Hierarchical cluster analysis (HCA) grouped the groundwater samples (boreholes) into five clusters that are statistically significant regarding the similarities of groundwater quality characteristics. The principal component analysis (PCA) extracted two major principal components explained around 65% of the variance and suggested the natural and anthropogenic processes especially the agricultural pollutants including synthetic fertilizers, and leaching of agricultural waste as the main factors affecting the groundwater quality. The integrated method proved to be efficient and robust for groundwater quality evaluation, as it guaranteed the precise assessment of groundwater chemistry in the sub-watershed of the tropical savanna. The findings of this investigation could be useful to the policy makers for developing effective groundwater management plans for the groundwater resources and protection of the sub-watershed.</description><subject>Agricultural pollution</subject><subject>Agricultural wastes</subject><subject>Agrochemicals</subject><subject>Anions</subject><subject>Anions - analysis</subject><subject>Anthropogenic factors</subject><subject>Aquatic Pollution</subject><subject>Atmospheric Protection/Air Quality Control/Air Pollution</subject><subject>Boreholes</subject><subject>calcium</subject><subject>Calcium ions</subject><subject>Cations</subject><subject>Cluster analysis</subject><subject>Contamination</subject><subject>data collection</subject><subject>Earth and Environmental Science</subject><subject>Ecotoxicology</subject><subject>Environment</subject><subject>Environmental Chemistry</subject><subject>Environmental Health</subject><subject>Environmental Monitoring</subject><subject>Environmental science</subject><subject>Fertilizers</subject><subject>Grassland</subject><subject>Groundwater</subject><subject>Groundwater chemistry</subject><subject>groundwater contamination</subject><subject>Groundwater data</subject><subject>Groundwater management</subject><subject>Groundwater pollution</subject><subject>Groundwater quality</subject><subject>Human influences</subject><subject>hydrochemistry</subject><subject>Ions - analysis</subject><subject>issues and policy</subject><subject>Leaching</subject><subject>Magnesium</subject><subject>Pollutants</subject><subject>Pollution sources</subject><subject>principal component analysis</subject><subject>Principal components analysis</subject><subject>Quality assessment</subject><subject>Research Article</subject><subject>Savannahs</subject><subject>savannas</subject><subject>Sodium</subject><subject>Statistical analysis</subject><subject>Statistical methods</subject><subject>subwatersheds</subject><subject>variance</subject><subject>Waste Water Technology</subject><subject>Water - analysis</subject><subject>Water Management</subject><subject>Water Pollutants, Chemical - analysis</subject><subject>Water Pollution Control</subject><subject>Water Quality</subject><subject>Water resources</subject><subject>Water sampling</subject><subject>Watersheds</subject><issn>0944-1344</issn><issn>1614-7499</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>BENPR</sourceid><recordid>eNqNkT1P5DAQhi0Egj3gD1CgSDQ0gbHjr5QI3cFJSDRQW44zAaOsvdjJIf49ZpcD6YoTlYv3mXc8egg5onBGAdR5prQRsgbGaqqFYDVskQWVlNeKt-02WUDLeU0bzvfIj5yfABi0TO2SvUaAlEqzBcHr1z5F94hL7-xYuUebrJsw-Tx5lysb-sr3GCY_lHzyMVRxqB5SnEP_YgtXreI4zusgxzk5zJUP1ZTiat2X7R8bgj0gO4MdMx5-vPvk_tfPu8vr-ub26vflxU3tOOipbgV0nbOicwhIB6WdVIND5B2DQZavt9Bb2mgQogPOtVZaaqtUTxnS3g7NPjnd9K5SfJ4xT2bps8NxtAHjnA2TSgjFOVXfQBnjqhVSF_TkH_SpnBrKIYWSjeYSNC0U21AuxZwTDmaV_NKmV0PBvPsyG1-m-DJrXwbK0PFH9dwtsf8c-SuoAM0GyCUKD5i-dv-n9g05EaGM</recordid><startdate>20220501</startdate><enddate>20220501</enddate><creator>Abdulsalam, Abduljalal</creator><creator>Ramli, Mohammad Firuz</creator><creator>Jamil, Nor Rohaizah</creator><creator>Ashaari, Zulfa Hanan</creator><creator>Umar, Da’u Abba</creator><general>Springer Berlin Heidelberg</general><general>Springer Nature B.V</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7QL</scope><scope>7SN</scope><scope>7T7</scope><scope>7TV</scope><scope>7U7</scope><scope>7WY</scope><scope>7WZ</scope><scope>7X7</scope><scope>7XB</scope><scope>87Z</scope><scope>88E</scope><scope>88I</scope><scope>8AO</scope><scope>8C1</scope><scope>8FD</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>8FL</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BEZIV</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FRNLG</scope><scope>FYUFA</scope><scope>F~G</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>K60</scope><scope>K6~</scope><scope>K9.</scope><scope>L.-</scope><scope>M0C</scope><scope>M0S</scope><scope>M1P</scope><scope>M2P</scope><scope>M7N</scope><scope>P64</scope><scope>PATMY</scope><scope>PQBIZ</scope><scope>PQBZA</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PYCSY</scope><scope>Q9U</scope><scope>7X8</scope><scope>7S9</scope><scope>L.6</scope></search><sort><creationdate>20220501</creationdate><title>Hydrochemical characteristics and identification of groundwater pollution sources in tropical savanna</title><author>Abdulsalam, Abduljalal ; Ramli, Mohammad Firuz ; Jamil, Nor Rohaizah ; Ashaari, Zulfa Hanan ; Umar, Da’u Abba</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c408t-950bbca5bce0e1f78c67fcee4b20f692790da138055b044887868a77d12e1daf3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Agricultural pollution</topic><topic>Agricultural wastes</topic><topic>Agrochemicals</topic><topic>Anions</topic><topic>Anions - analysis</topic><topic>Anthropogenic factors</topic><topic>Aquatic Pollution</topic><topic>Atmospheric Protection/Air Quality Control/Air Pollution</topic><topic>Boreholes</topic><topic>calcium</topic><topic>Calcium ions</topic><topic>Cations</topic><topic>Cluster analysis</topic><topic>Contamination</topic><topic>data collection</topic><topic>Earth and Environmental Science</topic><topic>Ecotoxicology</topic><topic>Environment</topic><topic>Environmental Chemistry</topic><topic>Environmental Health</topic><topic>Environmental Monitoring</topic><topic>Environmental science</topic><topic>Fertilizers</topic><topic>Grassland</topic><topic>Groundwater</topic><topic>Groundwater chemistry</topic><topic>groundwater contamination</topic><topic>Groundwater data</topic><topic>Groundwater management</topic><topic>Groundwater pollution</topic><topic>Groundwater quality</topic><topic>Human influences</topic><topic>hydrochemistry</topic><topic>Ions - analysis</topic><topic>issues and policy</topic><topic>Leaching</topic><topic>Magnesium</topic><topic>Pollutants</topic><topic>Pollution sources</topic><topic>principal component analysis</topic><topic>Principal components analysis</topic><topic>Quality assessment</topic><topic>Research Article</topic><topic>Savannahs</topic><topic>savannas</topic><topic>Sodium</topic><topic>Statistical analysis</topic><topic>Statistical methods</topic><topic>subwatersheds</topic><topic>variance</topic><topic>Waste Water Technology</topic><topic>Water - 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Academic</collection><collection>AGRICOLA</collection><collection>AGRICOLA - Academic</collection><jtitle>Environmental science and pollution research international</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Abdulsalam, Abduljalal</au><au>Ramli, Mohammad Firuz</au><au>Jamil, Nor Rohaizah</au><au>Ashaari, Zulfa Hanan</au><au>Umar, Da’u Abba</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Hydrochemical characteristics and identification of groundwater pollution sources in tropical savanna</atitle><jtitle>Environmental science and pollution research international</jtitle><stitle>Environ Sci Pollut Res</stitle><addtitle>Environ Sci Pollut Res Int</addtitle><date>2022-05-01</date><risdate>2022</risdate><volume>29</volume><issue>25</issue><spage>37384</spage><epage>37398</epage><pages>37384-37398</pages><issn>0944-1344</issn><eissn>1614-7499</eissn><abstract>Groundwater pollution of the watershed is mainly influenced by the multifaceted interactions of natural and anthropogenic processes. In this study, classic chemical and multivariate statistical methods were utilized to assess the groundwater quality and ascertain the potential contamination sources affecting the groundwater quality of Galma sub-watershed in a tropical savanna. For this purpose, the data set of 18 groundwater quality variables covering 57 different sampling boreholes (BH) was used. The groundwater samples essentially contained the cations in the following order of dominance: Ca
2+
> Na
+
> Mg
2+
> K
+
. However, the anions had HCO
3
–
> Cl
–
> SO
4
–2
> NO
3
–
respectively. The hydrochemical facies classified the groundwater types of the sub-watershed into mixed Ca–Mg–Cl type of water, which means no cations and anions exceeds 50%. The second dominant water type was Ca–Cl. The Mg–HCO
3
water type was found in BH 9, and Na–Cl water type in BH 29 of the studied area. The weathering of the basement rocks was responsible for the concentrations of these ions in the groundwater chemistry of the sub-watershed. Hierarchical cluster analysis (HCA) grouped the groundwater samples (boreholes) into five clusters that are statistically significant regarding the similarities of groundwater quality characteristics. The principal component analysis (PCA) extracted two major principal components explained around 65% of the variance and suggested the natural and anthropogenic processes especially the agricultural pollutants including synthetic fertilizers, and leaching of agricultural waste as the main factors affecting the groundwater quality. The integrated method proved to be efficient and robust for groundwater quality evaluation, as it guaranteed the precise assessment of groundwater chemistry in the sub-watershed of the tropical savanna. The findings of this investigation could be useful to the policy makers for developing effective groundwater management plans for the groundwater resources and protection of the sub-watershed.</abstract><cop>Berlin/Heidelberg</cop><pub>Springer Berlin Heidelberg</pub><pmid>35066782</pmid><doi>10.1007/s11356-022-18552-0</doi><tpages>15</tpages></addata></record> |
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| ispartof | Environmental science and pollution research international, 2022-05, Vol.29 (25), p.37384-37398 |
| issn | 0944-1344 1614-7499 |
| language | eng |
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| source | MEDLINE; Springer Nature - Complete Springer Journals |
| subjects | Agricultural pollution Agricultural wastes Agrochemicals Anions Anions - analysis Anthropogenic factors Aquatic Pollution Atmospheric Protection/Air Quality Control/Air Pollution Boreholes calcium Calcium ions Cations Cluster analysis Contamination data collection Earth and Environmental Science Ecotoxicology Environment Environmental Chemistry Environmental Health Environmental Monitoring Environmental science Fertilizers Grassland Groundwater Groundwater chemistry groundwater contamination Groundwater data Groundwater management Groundwater pollution Groundwater quality Human influences hydrochemistry Ions - analysis issues and policy Leaching Magnesium Pollutants Pollution sources principal component analysis Principal components analysis Quality assessment Research Article Savannahs savannas Sodium Statistical analysis Statistical methods subwatersheds variance Waste Water Technology Water - analysis Water Management Water Pollutants, Chemical - analysis Water Pollution Control Water Quality Water resources Water sampling Watersheds |
| title | Hydrochemical characteristics and identification of groundwater pollution sources in tropical savanna |
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