Multiple linear regression based water quality parameter modeling to detect hexavalent chromium in drinking water

摘要

The purpose of this research is to examine the relationship between pH, Total Dissolved Solids (TDS) and Conductivity Water Quality Parameters (WQPs) involved in the detection of hexavalent chromium contamination in the drinking water distribution system. Initially, the WQPs are obtained for four different hexavalent chromium contaminated samples experimentally using pH, TDS and conductivity sensors. Multiple Linear Regression (MLR) model is utilized to determine the correlation among the considered WQPs. Based on these results, estimation of WQPs for the new sample is computed. The errors between the actual and estimated WQPs are computed. It is found that the estimated values are closer to the measured values and the estimated errors lie between 0.33% and 19.18%.