Electrical Conductivity as a General Predictor of Multiple Parameters in Tigris River Based on Statistical Regression Model

Authors

  • Omar Anmar Khlaif College of Engineering - University of Baghdad
  • Khalid adel Abdulrazzaq College of Engineering - University of Baghdad
  • Athraa Hashim Mohammed College of Engineering - University of Baghdad

DOI:

https://doi.org/10.31026/j.eng.2021.02.06

Keywords:

Tigris River, Electrical conductivity, Regression

Abstract

Surface water samples from different locations within Tigris River's boundaries in Baghdad city have been analyzed for drinking purposes. Correlation coefficients among different parameters were determined. An attempt has been made to develop linear regression equations to predict the concentration of water quality constituents having significant correlation coefficients with electrical conductivity (EC). This study aims to find five regression models produced and validated using electrical conductivity as a predictor to predict total hardness (TH), calcium (Ca), chloride (Cl), sulfate (SO4), and total dissolved solids (TDS). The five models showed good/excellent prediction ability of the parameters mentioned above, which is a very good startup to establish a rule of thumb in the laboratories to compare between observations. The importance of linear regression equations in predicting surface water quality parameters is a method that can be applied to any other location.

 

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Published

2021-02-01

How to Cite

Khlaif, O. A., Abdulrazzaq, K. adel and Mohammed, A. H. (2021) “Electrical Conductivity as a General Predictor of Multiple Parameters in Tigris River Based on Statistical Regression Model”, Journal of Engineering, 27(2), pp. 73–82. doi: 10.31026/j.eng.2021.02.06.