Using Canadian Water Quality Index method to evaluate the spatio-variation of water quality and the impacts of quality parameters: a case study of Amasya’s surface water (Northern Turkey)

Konare M., GÜLTEKİN F., HATİPOĞLU TEMİZEL E.

Environmental Monitoring and Assessment, cilt.195, sa.1, 2023 (SCI-Expanded) identifier identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 195 Sayı: 1
  • Basım Tarihi: 2023
  • Doi Numarası: 10.1007/s10661-022-10797-z
  • Dergi Adı: Environmental Monitoring and Assessment
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, ABI/INFORM, Agricultural & Environmental Science Database, Aqualine, Aquatic Science & Fisheries Abstracts (ASFA), BIOSIS, CAB Abstracts, Compendex, EMBASE, Environment Index, Food Science & Technology Abstracts, Geobase, Greenfile, Pollution Abstracts, Public Affairs Index, Veterinary Science Database, Civil Engineering Abstracts
  • Anahtar Kelimeler: Water Quality Index (WQI), Hierarchical Cluster Analysis (HCA), Surface water, Amasya, Turkey, GROUND-WATER, RIVER-BASIN
  • Karadeniz Teknik Üniversitesi Adresli: Evet

Özet

In this study, the spatial variation of water quality in Yeşilırmak River passing through Amasya was investigated using the Canadian Water Quality Index (CWQI). For this aim, the measured 15 parameters in 3-month periods between the years 2008 and 2015 were used at 11 sample points from the Yeşilırmak River and its tributaries. The calculated CWQI scores using parameters of pH, Dissolved Oxygen (DO), Chemical Oxygen Demand (COD), ammonia, ammonium, nitrite, nitrate, phosphate, iron, copper, zinc, potassium, sulfate, sulfite and chlorine range from 33 to 64. These scores indicate that the surface waters in the studied area are poor to marginal in quality. The effect of each parameter on the CWQI scores by excluding each parameter, one by one, considering the water quality of the Yeşilırmak River was investigated using the Hierarchical Cluster Analysis (HCA) method. It was determined that the presence and/or absence of the parameters, which caused an increase or decrease in CWQI scores, were ammonia, phosphate, COD, sulfide, iron, ammonium, nitrite, DO. On the other hand, the parameters having positive effects on CWQI are nitrate, chlorine and potassium. The HCA statistical analysis method is suitable for interpreting complex water quality datasets and understanding time/location dependent changes in water quality. HCA can be used effectively to group parameters in river water quality monitoring programs.