Data analysis of the Gumusler Dam Lake Reservoir soils using multivariate statistical methods (Nigde, Türkiye)


Tumuklu A., Sunkari E. D., Yalçın F., Özer Atakoğlu Ö.

International Journal of Environmental Science and Technology, cilt.20, sa.5, ss.5391-5404, 2023 (SCI-Expanded) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 20 Sayı: 5
  • Basım Tarihi: 2023
  • Doi Numarası: 10.1007/s13762-022-04519-8
  • Dergi Adı: International Journal of Environmental Science and Technology
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Aqualine, Aquatic Science & Fisheries Abstracts (ASFA), Biotechnology Research Abstracts, CAB Abstracts, Compendex, Environment Index, Geobase, INSPEC, Pollution Abstracts, Veterinary Science Database
  • Sayfa Sayıları: ss.5391-5404
  • Anahtar Kelimeler: Dam sediment, Geochemical analysis, Heavy metals, Origin of dam soil, Statistical analysis
  • Akdeniz Üniversitesi Adresli: Evet

Özet

© 2022, The Author(s) under exclusive licence to Iranian Society of Environmentalists (IRSEN) and Science and Research Branch, Islamic Azad University.Heavy metal accumulation in aquatic environments is a global problem as it affects the quality of sediments and aquatic life. Therefore, this study examines the geochemical composition of heavy metals and their relationships, as well as their sources by applying multivariate statistical techniques to the geochemical content of the soil in the Gumusler Dam in central Turkey. The area is dominated by Paleozoic to Quaternary-aged igneous and metamorphic rocks. Average concentrations of all the major elements in terms of their abundance in descending order are as follows: SiO2, CaO, Al2O3, Fe2O3, MgO, K2O, TiO2, MnO, and Na2O. This suggests that SiO2 is the dominant major element in the soils. The contents of heavy metals have been found to vary in the following order: Strong positive correlations have been found among the following major elements: SiO2, CaO, MgO, TiO2, Ni, Rb, Pb, Zn, and As. According to the result of the principal component analysis using the extraction criterion, six factors were found to have an eigenvalue > 1, and they were found to explain 81.854% of the total variance of the dataset. All these factors reveal that the lithogenic effect and base metal mineralization are the two main sources of heavy metals in the sediments. Also, the results of the factor analysis were confirmed by hierarchical cluster analysis, which also yielded four clusters with similar element clusters. Regression analysis also confirmed that the host rocks and base metal mineralization in the area directly affect the sediment geochemistry in the dam.