A DIFFERENT APPROACH TO THE MONITORING OF THE QUALITY OF DRINKING WATER WITH DATA MINING TOOLS

Camur D., Altin A., TOPBAŞ M., Ilter H.

FRESENIUS ENVIRONMENTAL BULLETIN, cilt.31, sa.1A, ss.1188-1200, 2022 (SCI-Expanded) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 31 Sayı: 1A
  • Basım Tarihi: 2022
  • Dergi Adı: FRESENIUS ENVIRONMENTAL BULLETIN
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Aerospace Database, Agricultural & Environmental Science Database, Aqualine, Aquatic Science & Fisheries Abstracts (ASFA), CAB Abstracts, Chemical Abstracts Core, Communication Abstracts, Environment Index, Geobase, Greenfile, Metadex, Pollution Abstracts, Veterinary Science Database, Civil Engineering Abstracts
  • Sayfa Sayıları: ss.1188-1200
  • Anahtar Kelimeler: Correlation analysis, data min ig factor analysis, heavy metals, monitoring of drinking water quality, HEAVY-METALS, GROUNDWATER, CONTAMINATION, FLUORIDE, ELEMENTS, BROMIDE, BAY
  • Karadeniz Teknik Üniversitesi Adresli: Evet

Özet

In this study, data set (analysis results of Sb, As, B, Cu, Cd, Cr, Pb, Hg, Ni, Sc, Br03, F, NO2, NO3) which belong to 3.560 network samples received for routine monitoring for one year at 8 provinces in different geographic regions of Turkey were evaluated using correlation analysis (CA) and factor analysis (FA) which take place within data mining tools. The relationship between the measured parameters was demonstrated by CA at the provincial level and anthropogenic and geogenic effects that could have an effect on these relationships were explained by FA. It has been discussed how the data set analysis results can retlect the reality in terms of factors such as geologic structures of the provinces examined, the status of water resources, density of agricultural and industrial activities, network structures. As a result, it is understood that the basic water quality patterns in the regions where monitoring studies are performed can be extracted by using the data mining methods envisaged in the study from the data sets obtained during the monitoring of the network waters. Also, it was understood that the factors that could be effective in the formation of these patterns could be identified.