Using multivariate factor analysis to assess surface/logged water quality and source of contamination at a large irrigation project at Al-Fadhli, Eastern Province, Saudi Arabia

Abstract

A multivariate statistical technique, factor analysis, has been used to assess the impact of irrigation on near-surface water at a farm at Fadhli, Eastern Province, Saudi Arabia. A total of 34 surface water samples were analyzed for 23 different water quality parameters including pH, TDS, conductivity and alkalinity, sulphate, chloride, bicarbonate, nitrate, phosphate, bromide, fluoride, calcium, magnesium, sodium, potassium, arsenic, boron, copper, cobalt, iron, lithium, manganese, molybdenum, nickel, selenium, mercury, and zinc. The water quality data were subjected to both Q-mode and R-mode factor analysis. R-mode analysis resulted in three major factors for both summer and winter sampling events. Factor 1 (representing 48.91% of the summer and 53.66% of the winter variance) comprised elements likely to be due to the application of fertilizers and the dissolution of soil material. Factor 2 (14.04% of the summer and 11.94% of the winter variance) included elements common in irrigation water (related to the dissolution of aquifer materials). Factor 3 (7.36% of the summer and 10.18% of the winter variance) included molybdenum, manganese and nickel, which are common in micro-nutrients. Q-mode analysis showed that the most affected areas are located at the northwest corner of the farm.