Assessment of surface water quality using multivariate statistical techniques: El Abid River, Middle Atlas, Morocco as a case study

This study aims at assessing the spatial water quality variation and to determine the main contamination sources in the El Abid River as well as its main tributary Ahencal River. The water quality data were monitored for 16 parameters at 33 different sites. The used parameters were temp, pH, electrical conductivity (EC), turbidity, total hardness, dissolved oxygen, sodium (Na+), potassium (K+), calcium (Ca2+), magnesium (Mg2+), chloride (Cl-), bicarbonate (HCO3-), sulfate (SO42-), nitrite (NO2-), nitrate (NO3-), and ammonia (NH4+). This case study reports different multivariate statistical techniques such as Pearson's correlation, principal component analysis (PCA), and cluster analysis. The results have demonstrated that in downstream stations part of El Abid River, the water quality parameters were near or over Moroccan water standards. The PCA supported in extracting and recognizing the factors that are responsible for river water quality variance. Four factors that are responsible for 78% of the total variance in water quality of the river are identified. This suggests that the variations in water compounds concentration are mainly related to point source contamination (domestic wastewater), non-point source as natural processes (weathering of soil and rock). The CA classified the 33 monitoring sites into three differentiated clusters that showed relatively few spatial change in surface water quality. The results of this work can be used to decrease the number of samples to be analyzed, and to identify the pollution sources, as well as to better comprehend the spatial variations for effective river water-quality management.