Turkish Journal of Fisheries and Aquatic Sciences
2019, Vol 19, Num, 9 (Pages: 727-737)
Determination of Spatial and Temporal Changes in Water Quality at Asi River Using Multivariate Statistical Techniques
Ece Kilic 1 ,Nebil Yucel 1
1 İskenderun Technical University, Faculty of Marine Sciences and Technology, Department of Water Resources Management and Organization, Hatay-Turkey
DOI :
10.4194/1303-2712-v19_9_02
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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+, PO42-, SO42-, 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.
Keywords :
Orontes River, Environmental impact assessment, Cluster analysis, Discriminant analysis, Principal component analysis