Assessment of water quality using Moroccan WQI and multivariate statistics in the Sebou watershed (Morocco)

Abstract

The Sebou watershed, one of the most dynamic Moroccan basins concerning industrial and agricultural activities, has witnessed sharp increased water resources pressure over the last twenty years. These pressures affect both the quality and quantity of water resources. A river system’s characterization involves knowing its quality and the various factors that can influence its composition. The objective of this study is to evaluate water quality and to determine the major sources of contamination. Forty-eight samples collected from the Sebou watershed were measured for twenty-six physico-chemical parameters. Moroccan water quality index was used to assess water quality. Principal component analysis and cluster analysis were applied to identify probable water contamination sources. The majority of the Sebou watershed presents a poor to very poor quality (73%) due to intense agricultural, industrial, and urban activities. Principal component analysis reveals three factors explaining 62% of the total variance and indicates that the NH4+, COND, and CO32 are the most important parameters contributing to the data variation. Cluster analysis divides samples into four classes, based on similar water quality characteristics. PCA and CA highlight two main possible factors influencing water quality which are anthropogenic and natural processes. We also observe a decrease in water quality from upstream (cluster 1) downstream (cluster 4). The poor water quality results may delay the achievement of sustainable development goals related to water quality protection by the 2030 agenda of the United Nations and therefore deserve consideration by decision-makers. This study also shows that multivariate statistical methods can be a valuable tool to better understand water quality factors.