Application of PCA-RSR Model in Reservoir Water Quality Evaluation

Abstract

Water quality evaluation is a critical component of water environmental quality management, and conducting water quality assessments for reservoirs is quite practical. The inaccuracy induced by information overlap of several water quality measures is rarely taken into account in current water quality assessment systems. To solve this problem, the Principal component analysis-Rank sum ratio (PCA-RSR) water quality evaluation model was used to quantitatively evaluate the water quality of the Daheiting reservoir based on the monitoring data of different water layers in 2019. The results show that the water quality of Daheiting reservoir in 2019 is slightly better than that of the end of the reservoir, due to the influence of human factors downstream of the Upper Panjiakou Dam and the topography of the Luan River System, and the water quality from the dam head to the reservoir tail shows a decreasing trend. The PCA-RSR model has a good correlation with the traditional water quality indexes (WQI) system, which can avoid errors caused by overlapping information among the indexes while also taking into account the weight of the environmental factors of the study area. It is feasible and has some practical value in reservoir water quality evaluation..