Assessment of Physicochemical Water Quality using Principal Component Analysis: A Case Study Wadi Hanifa, Riyadh

Abstract

In the current study variable statistical approaches are used; understanding of huge and complicated data matrix obtained throughout an observation of the Wadi Hanifa, Riyadh, Kingdom of Saudi Arabia. Twenty-three chemistry factors are investigated in water samples collected all month for one year from eight investigation sites wherever the Wadi influenced anthropogenic influences. The physicochemical dataset was handled using Principal Component Analysis (PCA) to extract the foremost vital parameters in assessing variation in water quality. 2 Principal issue were known as liable for the info structure explaining 87.6 percent of the whole variance of the dataset, in which season of the year (temperature) with share of variance equals to 71.3 percent and with a lesser impact the discharge of waste material treatment plants into the wadi (Conductivity) with percentage of variance of 16.3 % that represents total variance of water quality in wadi Hanifa. this study suggests that PCA techniques are helpful tools for identification of vital surface water quality parameters.