Hydrochemical characterization and evaluation of irrigation water quality using indexing approaches, multivariate analysis, and GIS techniques in K'sob Valley, Algeria

Irrigation plays a vital role in addressing increasing need for food production and promoting economic advancement. To meet the demands for food supply and economic progress, it is essential to underscore the significance of assessing water quality in dry regions. The current study was carried out to evaluate and predict the suitability of water quality for agricultural use in the K'sob valley in the M'sila region (Northeast Algeria). A combination of irrigation water quality indices (IWQIs), Geographic Information System (GIS) analysis and multivariate statistical methods were used for this purpose. Several physicochemical parameters, such as temperature (T degrees), hydrogen ion concentration (pH), electrical conductivity (EC), total dissolved solids (TDS), turbidity (Turb), chemical oxygen demand (COD), Ca2+, Mg2+, Na+, K+, HCO3-, Cl-, SO42-, NO3-, NO2-, NH4+, PO4- and SiO22+ were all measured from 40 samples collected at ten surface water locations during four seasons. The concentrations of the main cation and anion were shown as follows: Na+>Ca2+> K+ > Mg2+, and SO42- > HCO3- > Cl- > NO3- indicating mixed Na-Cl-K or Na-SO4 water facies. Significant seasonal variation for each parameter (T, pH, Turbidity, Salinity, COD, NH4+, Cl-, SO4-, and NO2-) was reported (p < 0.05). Additionally, a significant spatial variation (p < 0.05) was observed among different stations for the parameters: TDS, EC, Ca2+, Na+, HCO3-, SO4-, NO3-, and PO43- (p < 0.05). The irrigation water quality index (IWQI), sodium adsorption ratio (SAR), sodium percentage (Na%), Kelly index (KI), and permeability index (PI) had values varying between 28.1 and 56.8, 5.65 and 12.45, 75 and 87, 2.61 and 6.54 and 83, and 97, respectively, and a significant seasonal effect was recorded. According to the Wilcox diagram, 70% of samples were unsuitable for irrigation, while 30% of samples were questionable. The IWQI map revealed that 50% of the samples fell within the very poor category for irrigation, while 20% and 30% of the samples were inside the poor and unsuitable categories, respectively. The principal component analysis (PCA) and hierarchical cluster analysis (HCA) of K'SobValley water revealed three different categories of water based on elemental composition and seasonal variations. The results obtained in this study can be valuable for surface water management. Furthermore, the developed methodology can serve as a useful tool for identifying critical hydrogeochemical components in arid and semi-arid environments related to surface water.