Determining spatial and temporal changes of surface water quality using principal component analysis

The results showed that the NSFWQI and the WQImin-p could not distinguish between highly impacted stream reaches, while the calculated WQImin-c with two parameters including turbidity and fecal coliforms could meaningfully classify the sampling stations. These two parameters were selected based on results from correlation matrix. This study showed that calculation of the WQImin-c was an effective and easily applicable assessment method for different effluents' impacts on stream water quality. The PCA technique could justifiably show different landscape effects on river water quality whereby the river downstream was found to experience decreased water quality.