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Evaluation of water quality of Kızılırmak River (Sivas/Turkey) using geo-statistical and multivariable statistical approaches

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  • Can Bülent Karakuş

    (Sivas Cumhuriyet University)

Abstract

Groundwater and surface water qualities are evaluated using geographic information system (GIS)-based geo-statistical and multivariable statistical methods. This research aims to investigate the water quality of Kızılırmak River, that remain within the provincial boundaries of Sivas, using geo-statistical and multivariable statistical methods, and to provide the water quality map of Kızılırmak River. In this regard, surface water samples from 28 surface water quality monitoring stations were analysed for wet and dry seasons. The hydro-chemical properties of surface water quality were determined, and the water quality index was evaluated for each station. Spherical, exponential and Gaussian models were determined as the best semi-variogram models according to the minimum root mean square error values and the cross-validation method. The final water surface quality map of Kızılırmak River was obtained by weighted superposition of the spatial distribution maps of the surface water quality parameters which were obtained by the geo-statistical method. The correlations between the surface water quality parameters were determined using multivariable statistical analysis methods such as correlation analysis and factor analysis (principal component analysis). The surface water quality in the study area was categorized as excellent, good, poor and very poor. The water quality of Kızılırmak River’s portion near Sivas city centre and in the South of the province did not meet the standards for drinking water purposes. This research provides the surface water quality map of the study area by use of GIS-based statistical methods.

Suggested Citation

  • Can Bülent Karakuş, 2020. "Evaluation of water quality of Kızılırmak River (Sivas/Turkey) using geo-statistical and multivariable statistical approaches," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 22(5), pages 4735-4769, June.
    • Handle: RePEc:spr:endesu:v:22:y:2020:i:5:d:10.1007_s10668-019-00472-8
    DOI: 10.1007/s10668-019-00472-8
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    References listed on IDEAS

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    1. Lazhar Belkhiri & Tahoora Narany, 2015. "Using Multivariate Statistical Analysis, Geostatistical Techniques and Structural Equation Modeling to Identify Spatial Variability of Groundwater Quality," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(6), pages 2073-2089, April.
    2. Qing Gu & Yao Zhang & Ligang Ma & Jiadan Li & Ke Wang & Kefeng Zheng & Xiaobin Zhang & Li Sheng, 2016. "Assessment of Reservoir Water Quality Using Multivariate Statistical Techniques: A Case Study of Qiandao Lake, China," Sustainability, MDPI, vol. 8(3), pages 1-17, March.
    3. Md Haque & Ataur Rahman & Dharma Hagare & Golam Kibria, 2014. "Probabilistic Water Demand Forecasting Using Projected Climatic Data for Blue Mountains Water Supply System in Australia," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(7), pages 1959-1971, May.
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    Cited by:

    1. Can Bülent Karakuş, 2024. "Assessment of ecotourism potentiality based on GIS-based fuzzy logarithm methodology of additive weights (F-LMAW) method for sustainable natural resource management," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 26(10), pages 27001-27055, October.

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