Appraisal of Surface Water Quality of Nile River Using Water Quality Indices, Spectral Signature and Multivariate Modeling

Surface water quality management is an important facet of the effort to meet increasing demand for water. For that purpose, must be monitored and assessed via use innovative techniques, such as indices (WQIs), spectral reflectance (SRIs), multivariate modeling. Throughout Rosetta Damietta branches Nile River, samples were collected, WQIs at 51 different distinct locations. The drinking index (DWQI), metal (MI), pollution (PI), turbidity (Turb.) total suspended solids (TSS) estimate status. Twenty-three physicochemical parameters examined using standard analytical procedures. average values ions metals exhibited following sequences: Ca2+ > Na2+ Mg2+ K+, HCO32− Cl− SO42− NO3− CO3− Al Fe Mn Ba Ni Zn Mo Cr Cr, respectively. Furthermore, under stress evaporation reverse ion exchange process, main hydrochemical facies Ca-HCO3 mixed Ca-Mg-Cl-SO4. DWQI two revealed 53% varied from excellent good water, 43% poor very 4% unsuitable drinking. In addition, results showed new SRIs extracted VIS NIR region strong relationships with MI moderate Turb. TSS each branch River their combination. R2 between 0.65 0.82, 0.64 0.83, 0.41 0.60 0.35 0.79 DWQI, MI, TSS, PLSR model produced a more accurate assessment based on slope than other indices. partial least squares regression (PLSR) generated predictions in Val. datasets 0.82 0.79, respectively, 0.93 0.78, Therefore, combination WQIs, SRIs, GIS approaches are effective give us clear picture assessing suitability surface its controlling factors.