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

Year 2017, Volume: 17 Issue: 2, 238 - 246, 27.09.2017

İbrahim Yurtseven

https://doi.org/10.17475/kastorman.266098

Abstract

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 (CO₃^2-),
bicarbonate(HCO₃^-), chloride (Cl^-), sulfate
(SO₄^2-), 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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