Assessment of water quality classes using self-organizing map and fuzzy C-means clustering methods in Ergene River, Turkey


ORAK E., Akkoyunlu A., CAN Z. S.

ENVIRONMENTAL MONITORING AND ASSESSMENT, vol.192, no.10, 2020 (SCI-Expanded) identifier identifier identifier

  • Publication Type: Article / Article
  • Volume: 192 Issue: 10
  • Publication Date: 2020
  • Doi Number: 10.1007/s10661-020-08560-3
  • Journal Name: ENVIRONMENTAL MONITORING AND ASSESSMENT
  • Journal Indexes: 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, MEDLINE, Pollution Abstracts, Public Affairs Index, Veterinary Science Database, Civil Engineering Abstracts
  • Keywords: Water quality assessment, Self-organizing map, Fuzzy C-mean clustering, Ergene basin
  • Çanakkale Onsekiz Mart University Affiliated: Yes

Abstract

Surface water is one of the primary sources for drinking, irrigation, and industrial activities in Ergene River, Turkey. However, its quality has deteriorated due to the point and non-point pollution sources. Therefore, an appropriate assessment of surface water quality is very important. Water quality classification is calculated separately for each quality parameter in Turkey. An overall assessment of surface water quality is essential for water management. In this study, self-organizing maps (SOMs) and fuzzy C-means clustering (FCM) methods have been used for assessing surface water quality in the Ergene River. Seven water quality parameters have been considered as important indicators to evaluate water quality status in 7 observation points located in the river, covering the period from 1985 to 2013.