Multivariate Statistical and Hydrochemical Analysis of Drinking Water Resources in Northern Cameroon Watersheds

• Published in: Water (Basel) Vol. 13; no. 21; p. 3055
• Main Authors: Dammi Djimi, Estelle Gaëlle, Abia, Akebe Luther King, Belibi Belibi, Placide Désiré, Takam Soh, Patrice, Che, Randy Nanga, Ghogomu, Julius Numbonui, Ketcha, Joseph Mbadcam
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01-11-2021
• Subjects: Aluminum; Anions; Anthropogenic factors; Aquifers; Basins; Calcite; Calcium ions; Cations; Chemical composition; Deep water; Developing countries; diffuse pollution; Drinking water; drinking water quality; Economic development; Electrical conductivity; Electrical resistivity; Environmental health; Factor analysis; Groundwater; hydrochemical methods; Ion exchange; Iron; LDCs; Low income groups; Magnesium; Metamorphic rocks; Multivariate analysis; Nitrogen dioxide; northern Cameroon watersheds; Pan-Africanism; Pollution sources; Poverty; Principal components analysis; Rainfall; Rainy season; Silicates; silicates dissolution; Soil contamination; Statistical methods; Statistics; Surface runoff; Surface water; Turbidity; Water analysis; Water pollution; Water quality; Water resources; Water sampling; Water treatment; Watersheds; Nigeria; Cameroon; Lake Chad
• ISSN: 2073-4441; 2073-4441
• DOI: 10.3390/w13213055

Watershed pollution by natural and anthropogenic activities remains a global challenge that requires careful and prompt attention. So, identifying possible pollution sources and studying the hydrochemistry of water resources would positively affect human health, especially in resource-limited communities and their economy. Water samples were collected during the rainy season in the North (R-NO) and Adamawa (R-AD) Region communities of Cameroon and assessed for physicochemical parameters using standard methods. The data were analysed using multivariate statistical and hydrochemical methods. Principal component analysis (PCA) retained seven and six principal components explaining 77.65% (R-NO) and 72.24% (R-AD) of the total variance, respectively. The drinking water sources assessed were highly, moderately, and lightly contaminated with turbidity, PO43−, Al3+, Fe2+, Mn2+, NH4+, NO3−, NO2−, and electrical conductivity (EC) from surface runoff and soil erosion sources. PCA and factor analysis (PCA/FA) revealed two main groups, distinguished by natural and anthropogenic sources, responsible for water quality variations. Hierarchical cluster analysis (HCA) grouped sampling sites into three clusters: low, moderate, and high pollution areas in the R-NO and unpolluted, low, and moderate pollution areas in the R-AD. The order of dominant cations was Mg2+ > Ca2+ > K+ and HCO3− > Cl− > SO42− for anions. Based on Piper diagram classification, watersheds studied were predominated by the Mg-Ca-HCO3 water type in 85% (R-NO) and 79% (R-AD) of water samples. The chemical composition of shallow and deep water was dominantly controlled by the dissolution of silicates and carbonate, reverse ion exchange, and precipitation of calcite. These results reveal that diffuse pollution predominantly impacted the study sites during the rainy season, and this should be the focus of policymakers when planning and implementing measures to protect drinking water sources, human health, and reduce water treatment costs.