Application of Multivariate Statistical Methods for Water Quality Assessment of Karasu-Sarmisakli Creeks and Kizilirmak River in Kayseri, Turkey

Abstract

Monitoring water quality of rivers has particular ecological, economic, and environmental importance for a region. However, long-term monitoring of a river network requires a large amount of analysis with high work load and cost. In this study, multivariate analysis was performed to decrease the number of parameters and sampling points for monitoring water quality in the Kızılırmak River and its southern ranches of Karasu and Sarmısaklı creeks. On the study area, water quality parameters were collected from seven sampling points for 2004-07 and 2010-14. Multivariate statistical analysis was performed by hierarchical cluster analysis and principal component analysis for the evaluation of parameter variations and dataset interpretation. The dataset was divided into periods A and B to evaluate the effects of seasonal changes on sampling points and parameters.

Water Quality Index (WQI) for Main Source of Drinking Water (Karaçomak Dam) in Kastamonu City, Turkey

“…Likewise, the monitoring to our source water that the best way to understand and to avoid pollution problems [13]. According to [14] has done evaluate the impacts of seasonal differences on sampling points of Karasu-Sarmisakli Creeks and Kizilirmak River in KayseriTurkey. In general, Water Quality Index (WQI) is a statistical functional tool for simplifying, detailed and describing complex information collected from any body of water which reflects the integrated influence on the overall quality variables this value is understandable and use by the decision makers, planer and the general public [15,16].…”

Assessment of Water Quality of Yağlidere Stream (Turkey) Using Multivariate Statistical Techniquess

“…According to Turkish legislation, it is very important to define and elaborate upon the quality of water before use for various purposes in light of physico-chemical parameters [17][18]. Water quality of surface water is classified into four groups.…”

“…All parameters based on average values were found to be Class I water quality except for NO 2 -N, TP, and BOD 5 . Nitrate nitrogen concentrations did not exceed water standards (>5 ppm) [17][18][19] and were generally well below this level, but sometimes TP and NH 4 were Class IV. The use of agricultural fertilizers and urban sewage are believed to increase the ammonia nitrogen, nitrate, phosphate, and nitrite concentrations because the absence of freshwater plants might affect the increase in nitrogen ion concentrations in the stream.…”

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“…Additionally, multivariate analysis of the pond water quality data set was performed through Hierarchical Cluster Analysis (HCA) techniques (Liu, Lin, & Kuo, 2003). The pond water quality data were initially standardized by zscale transformation (Özdemir, 2016;Kannel, Lee, Kanel, & Khan, 2007).…”