Spatial and Temporal Evaluation of Physicochemical Quality of Drinking/Using Water In Kırklareli Reservoir (Turkish Thrace)


Güher H., Öterler B., Elipek B., Yeler O. , Aydın G. B.

Journal Of The Serbian Chemical Society, vol.86, no.10, pp.74, 2021 (Journal Indexed in SCI Expanded)

  • Publication Type: Article / Article
  • Volume: 86 Issue: 10
  • Publication Date: 2021
  • Doi Number: 10.2298/jsc210601074g
  • Title of Journal : Journal Of The Serbian Chemical Society
  • Page Numbers: pp.74

Abstract

Kırklareli Reservoir locating in Meriç-Ergene River Basin is an important drinking/using a freshwater resource of Kırklareli Province. In order to ensure the sustainable use of this important reservoir, its current situation should be examined periodically and evaluated by multivariate analyses. For this reason, the water samples were taken between the dates April 2018 and February 2019 at monthly intervals from 3 different stations. The data of environmental and physicochemical variables (water temperature, dissolved oxygen, pH, salinity, conductivity, total dissolved solids, Chlorophyll-a, light permeability, fluoride, chloride, NO2-N, NO3-N, PO4, SO4, and essential/potentially toxic elements) measured and evaluated according to the classes in surface water quality control regulation of Turkey. The parameters exceeding first-class water quality values (chlorophyll-a, pH, NO2-N, chloride, selenium) were mapped in GIS using Spline integration approach. Also, Sodium Absorbtion Ratio, Kelly Index Values, and Magnesium Ratio, were calculated to evaluate the water quality for agricultural irrigation water standards. The water quality of the reservoir was evaluated by using multivariance analyses (Bray-Curtis Similarity Index, Correspondence Analyses, Pearson Correlation Index). As a result, it was emphasized that using GIS approach is a potential useful method of monitoring the sustainable water quality of Kırklareli reservoir which is determined to have an oligomesotrophic character.

Keywords: water quality, GIS, environmental variables, multivariate analyses