dc.contributor.author | Kılıç, Ece | |
dc.contributor.author | Yücel, Nebil | |
dc.date.accessioned | 2019-07-04T12:50:55Z | |
dc.date.available | 2019-07-04T12:50:55Z | |
dc.date.issued | 2019 | en_US |
dc.identifier.citation | Kılıc, E., Yucel, N. (2019). Determination of spatial and temporal changes in water quality at asi river using multivariate statistical techniques. Turkish Journal of Fisheries and Aquatic Sciences. 19(9), 727-737. | en_US |
dc.identifier.uri | http://doi.org/10.4194/1303-2712-v19_9_02 | |
dc.identifier.uri | https://hdl.handle.net/20.500.12508/399 | |
dc.description | Science Citation Index Expanded | en_US |
dc.description.abstract | Water quality in surface waters is a critical issue since they are used in domestic, agricultural and industrial purposes. Therefore, proper water management strategies should be taken care of to protect water bodies. To accomplish this goal, ten years (2004-2014) seasonal water quality monitoring results consisting of 16 parameters (BOD5, COD, DO, NO2-, NO3-, NH4+, PO4 2-, SO4 2-, EC, SS, TDS, T, Na+, Mg2, Ca2+, Q ) measured at 5 stations taken from State of Hydraulic Works of Turkey was examined using multivariate statistical techniques like cluster analysis (CA), discriminant analysis (DA) and principal component / factor analysis (PCA/FA). Hierarchical CA grouped 5 monitoring stations and 4 seasons into two clusters as polluted/less polluted area and wet/dry season, respectively. DA showed that parameters responsible for temporal change in Asi River are Na+, Mg2+, Ca2+, Q, BOD, NH4+ and SS with 92.2% accuracy. Likewise, SO42-, DO and T were found as parameters responsible for temporal change with 90% accuracy. PCA revealed that mineral pollution, nutrient pollution, and organic pollution are major latent factors which influence the water quality of Asi River. It also showed that erosion, agricultural activities, domestic and industrial discharges are fundamental causes of water pollution in the study area. To conclude, the study revealed that multivariate statistical methods are beneficial tools for the evaluation of complex datasets like water quality monitoring data. | en_US |
dc.language.iso | eng | en_US |
dc.publisher | Central Fisheries Research Inst | en_US |
dc.relation.isversionof | 10.4194/1303-2712-v19_9_02 | en_US |
dc.rights | info:eu-repo/semantics/openAccess | en_US |
dc.subject | Orontes River | en_US |
dc.subject | Environmental Impact Assessment | en_US |
dc.subject | Cluster Analysis | en_US |
dc.subject | Discriminant Analysis | en_US |
dc.subject | Principal Component Analysis | en_US |
dc.subject.classification | Water quality | Multivariant analysis | Total variance | en_US |
dc.subject.classification | Fisheries | Marine & Freshwater Biology | en_US |
dc.subject.other | source identification | en_US |
dc.subject.other | pollution sources | en_US |
dc.subject.other | basin | en_US |
dc.subject.other | chemometrics | en_US |
dc.subject.other | bod | en_US |
dc.title | Determination of spatial and temporal changes in water quality at asi river using multivariate statistical techniques | en_US |
dc.type | article | en_US |
dc.relation.journal | Turkish Journal of Fisheries and Aquatic Sciences | en_US |
dc.contributor.department | Deniz Bilimleri ve Teknolojisi Fakültesi | en_US |
dc.identifier.volume | 19 | en_US |
dc.identifier.issue | 9 | en_US |
dc.identifier.startpage | 727 | en_US |
dc.identifier.endpage | 737 | en_US |
dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | en_US |
dc.contributor.isteauthor | Kılıç, Ece | en_US |
dc.contributor.isteauthor | Yücel, Nebil | en_US |
dc.relation.index | Web of Science (ESCI) - Scopus - TR-Dizin | en_US |