Using multivariate analysis to develop irrigation water quality index for surface water in Kafr El-Sheikh Governorate, Egypt

Abstract

Abstract At present, there is a little well-established irrigation water quality index (IWQI) for surface water in arid and semi-arid regions. Thus, the current work focused on establishing since-based weights of parameters adopted by FAO 29 guideline to develop IWQI based on the National Sanitation Foundation Water Quality Index (NSFWQI). The new index was then applied in Kafr El-Sheikh Governorate, Egypt as a case study. Forty-five geo-referenced water samples were collected from canals and drains during winter, spring, summer, and autumn of 2018 and analyzed for twenty-two parameters. Data were subjected to correlation analysis, principal component analysis (PCA), and factor analysis (FA). Weights were assigned for initial parameters based on PCA and FA to calculate IWQI-1 and IWQI-2, respectively. The two models resulted in similar trend and showed low to good water quality, with IWQI-2 being more recommended. The initial input parameters were reduced to finally shortlisted seven ones, including Na+, Zn, pH, HCO 3 − , As, NO 3 − , and B. These parameters showed better performance in representing water quality their when weights were derived from PCA rather than FA. Integrated use of PCA/FA and IWQI would make water quality control rapid, low-cost, less biased and more objective to form a base of sustainable development programs in the studied area.