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    BACTERIAL COMPOSITION INHABITING WATER COLUMN AND BOTTOM SEDIMENT IN TWO DIFFERENT RUNNING WATER ECOSYSTEMS OF MERIC-ERGENE RIVER BASIN (TURKISH THRACE)
    (Parlar Scientific Publications (P S P), 2017) Mimiroglu, Pinar Altinoluk; Elipek, Belgin Camur
    This study has been carried out to determine the presence and distribution of total heterotrophic bacteria (THB), coliform bacteria (CB), faecal coliform bacteria (FCB) and Escherichia coli bacteria inhabiting different running waters of Meric-Ergene River Basin in Turkey. The highest number of THB bacteria in water body was found in August at a site located in the Ergene River, and the lowest in December at a site located in the Meric (Maritsa, Evros) River. The highest number of THB in sediment was found in February at a site located in the Ergene River, and the lowest in July at a site located in the Meric River. Some physicochemical measurements have been done at the same time as the bacterial sampling to determine environmental conditions of the ecosystems. According to Spearman's correlation index, some environmental conditions were found to have a remarkable correlation with bacterial distribution (p<0.05). This research concluded that pollution load significantly increased bacteria count and played an important role in variation of bacterial quality of the rivers.
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    DETERMINING OF WATER QUALITY BY USING MULTIVARIATE ANALYSIS TECHNIQUES IN A DRINKING/USING WATER RESERVOIR IN TURKEY
    (Parlar Scientific Publications (P S P), 2017) Elipek, Belgin Camur; Guher, Huseyin; Oterler, Burak; Divrik, Menekse Tas; Mimiroglu, Pinar Altinoluk
    l This study has been carried out to assess the water quality of a drinking/using water reservoir in Turkey by using the different multivariate statistical techniques (Bray-Curtis cluster analysis (BCCA), principle component analysis (PCA), and correspondence analysis (CA) methods). The annual dataset belonging physical and chemical features in the reservoir was obtained by the monthly intervals between the years 2010 and 2011. A total of 15 parameters (temperature, dissolved oxygen (DO), biological oxygen demand (BOD5), light permeability, conductivity, salinity, chloride, pH, total hardness, Ca, Mg, NO2-N, NO3-N, o-PO4, SO4) have been monitored at three different sampling stations in the reservoir and a total of 495 observations were grouped statistically. The sampled periods have been classified into three different groups by using the BCCA. The results were supported by the PCA and CA statistical methods. Consequently, in order to determine and to evaluate for large complex datasets that belong to environmental properties, multivariate analyses are very useful techniques. Thus, the sampling periods to monitor the physicochemical including in a water resource can be determined.