Evaluation of Some Streamwater Quality Parameters Using with Multiple Statistical Methods in Mature Pinus sylvestris L. Forest Ecosystems

This study contains modeling water quality data from 3 different experiment stations of Oltu stream, which one of the tributaries of the Çoruh stream has been provided by interpreting multiple statistical methods. In the data set used in the study, runoff (Q), water temperature (WT), pH, electric conductivity (EC), sodium (Na+), potassium (K+), calcium(Ca2+) and magnesium (Mg2+), carbonate (CO32-), bicarbonate(HCO3-), chloride (Cl-), sulfate (SO42-), sodium absorption factor (SAR), and boron (B) concentration results of measurements were present. In the 5 year period between 2003 and 2008, Principal Component Analysis (PCA) and Multiple Regression Analysis (MLR) have been applied to the dataset which was composed of the monthly result of the measurement. PCA were explained to relations between hydrologic and physiochemical parameters and it were examined 6 factor groups created as a result of this examination was generated 90.7% of the whole variance of the data set. According to the results of the analysis, some strong negative relations between the runoff and some other parameters (electric conductivity, sodium, chloride, sulfate, sodium absorption factor, and boron concentration) were found. The runoff has been found as a hydrological parameter working as the key consideration. The estimation method was determined by MLR. The estimation model has been developed among the runoff and those parameters which have strong relations with each other. The performance of this model was tested by using such criteria as coefficient of determination and Mean Squared Error (MSE) method and the results were found to be satisfactory.

Keywords:

Principal Component Analysis (PCA), Multiple Linear Regression (MLR) Water Quality Parameters,

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