Groundwater quality assessment using principal component analysis and hierarchical cluster analysis in Alacam, Turkey

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Tasan M., Demir Y., Taşan S.

WATER SUPPLY, cilt.22, sa.3, ss.3431-3447, 2022 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 22 Sayı: 3
  • Basım Tarihi: 2022
  • Doi Numarası: 10.2166/ws.2021.390
  • Dergi Adı: WATER SUPPLY
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, PASCAL, Aqualine, Aquatic Science & Fisheries Abstracts (ASFA), BIOSIS, CAB Abstracts, Compendex, EMBASE, Environment Index, Geobase, ICONDA Bibliographic, Pollution Abstracts, Veterinary Science Database, Directory of Open Access Journals
  • Sayfa Sayıları: ss.3431-3447
  • Anahtar Kelimeler: Alacam town, multivariate statistical techniques, piper diagram, seawater intrusion, MULTIVARIATE STATISTICAL-ANALYSIS, RIVER-BASIN, LAND-USE, WATER, DISTRICT, CLASSIFICATION, DRINKING, AQUIFERS, PRADESH
  • Ondokuz Mayıs Üniversitesi Adresli: Evet

Özet

This study assessed groundwater quality in Alacam, where irrigations are performed solely with groundwaters and samples were taken from 35 groundwater wells at pre and post irrigation seasons in 2014. Samples were analyzed for 18 water quality parameters. SAR, RSC and %Na values were calculated to examine the suitability of groundwater for irrigation. Hierarchical cluster analysis and principal component analysis were used to assess the groundwater quality parameters. The average EC value of groundwater in the pre-irrigation period was 1.21 dS/m and 1.30 dS/m after irrigation in the study area. It was determined that there were problems in two wells pre-irrigation and one well post-irrigation in terms of RSC, while there was no problem in the wells in terms of SAR. Piper diagram and cluster analysis showed that most groundwaters had CaHCO3 type water characteristics and only 3% was NaCl- as the predominant type. Seawater intrusion was identified as the primary factor influencing groundwater quality. Multivariate statistical analyses to evaluate polluting sources revealed that groundwater quality is affected by seawater intrusion, ion exchange, mineral dissolution and anthropogenic factors. The use of multivariate statistical methods and geographic information systems to manage water resources will be beneficial for both planners and decision-makers.