Estimation of Correlation Between Electrical Conductivity, Solids and Hardness of Highway Stormwater Run-off

Short Communication: Correlation Between Parameters of Highway Stormwater Run-off

  • Muhammad Arslan College of Earth and Environmental Sciences, University of the Punjab, Lahore, Pakistan
  • lrfan Ahmed Shaikh College of Earth and Environmental Sciences, University of the Punjab, Lahore, Pakistan
Keywords: urban areas, highway stormwater, physiochemical, regression analysis, determination coefficient



A comprehensive understanding of pollutants of highway stormwater run-off is required for accurate prediction of various constituents and for planning and assessment of proposed or existing highway corridors. Besides the adequate availability of staff and laboratory equipment, regular monitoring and estimation of all constituents in highway runoff water is very difficult. Hence, alternate statistical methods for the comparison of constituents are highly appreciated. In this research work, an attempt was made to estimate the relationship between electrical conductivity (Ec), total dissolved solids (TDS), total suspended solids (TSS) and hardness of highway stormwater run-off to decrease the time and cost required for collection, testing and measurement of samples for quality data. Eight consecutive storm events were monitored during monsoon season from June to July 2019 and twenty-four stormwater samples were collected from an urban highway in Lahore, Pakistan and analyzed for pH, temperature (T), Ec, TDS, TSS and hardness to determine physiochemical properties of highway run-off water. After analyzing selected physiochemical parameters, regression-based predictive relationships were developed between these parameters. A strong linear relationship with a high coefficient of determination i.e., 0.97 was found between Ec and TDS, while the correlation of Ec with TSS and hardness is very poor having a weak coefficient of determination i.e., 0.49 and 0.76 respectively revealing the unreliability of developed correlations.