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Use of Multivariate Statistical Analysis for the Assessment of Groundwater Chemical Variations in Wadi Bani Malik Area, Saudi ArabiaView Crossref metadata(active tab) <div id="edit-xml" class="form-item form-type-item"> <?xml version="1.0"?> <doi_batch version="4.4.1" xmlns="http://www.crossref.org/schema/4.4.1" xmlns:jats="http://www.ncbi.nlm.nih.gov/JATS1" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.crossref.org/schema/4.4.1 http://www.crossref.org/schemas/crossref4.4.1.xsd"><head><doi_batch_id>000690</doi_batch_id><timestamp>1713622786</timestamp><depositor><depositor_name>University of the Aegean</depositor_name><email_address>uoa@university.com</email_address></depositor><registrant>Global NEST Journal</registrant></head><body><journal><journal_metadata><full_title>Global NEST Journal</full_title><full_title>Global NEST: the international Journal</full_title><issn media_type="print">1790-7632</issn><issn media_type="electronic">2241-777X</issn></journal_metadata><journal_issue><titles><title>Issue 2</title></titles><publication_date><month>07</month><year>2024</year></publication_date><journal_volume><volume>20</volume></journal_volume><issue>2</issue></journal_issue><journal_article><titles><title>Use of Multivariate Statistical Analysis for the Assessment of Groundwater Chemical Variations in Wadi Bani Malik Area, Saudi Arabia</title></titles><abstract xmlns="http://www.ncbi.nlm.nih.gov/JATS1"><p>Multivariate statistical analysis including cluster analysis, factor analysis and correlation coefficient was applied to the groundwater samples to understand the groundwater condition in Wadi Bani Malik area. Water samples collected from the study area were analysed for physical parameters, major cations and major anions. The groundwater quality is not good in this area and the physicochemical parameters go beyond the acceptable limits of the Kingdom of Saudi Arabia and WHO drinking water standards. The water type in the study area was primarily NaCl. Correlation coefficients were determined among different parameters and then regression analysis was performed to realize the linear relationship between the best correlated parameters. Results of factor analysis specify that factor 1 is dominant and is responsible for 45.5% of the total variance and is dominated by Cl-, Na+, Mg++ and K+. Ground water samples can be divided into four clusters.</p></abstract><publication_date><month>07</month><day>21</day><year>2018</year></publication_date><pages><first_page>355</first_page><last_page>362</last_page></pages><publisher_item><identifier id_type="pii">gnest_02237</identifier></publisher_item><doi_data><doi>10.30955/gnj.002237</doi><timestamp>1713622786</timestamp><resource>https://journal.gnest.org/publication/gnest_02237</resource></doi_data></journal_article></journal></body></doi_batch> </div>
