Long-term water quality assessment in a Tropical Monsoon
2019
Gabasawa, Alhassan Idris | Abba Umar, Da’u | Anyika, Chinedum | Nor Rohaizah Jamil | Abdulkareem, Jabir Harna
Multivariate statistical techniques such as principal component analysis (PCA) and cluster analysis (CA) were applied to water quality parameters in order to interpret complex matrices for better assessment of water quality and environmental status of a watershed. A study was conducted to assess water quality and to establish relationship among water quality parameters in Kelantan River basin. Water quality data was obtained from Department of Environment, (DOE) Malaysia from 2005-2014. Multivariate statistical techniques such as principal component analysis (PCA) and cluster analysis (CA) were applied to 15 water quality parameters in order to interpret complex matrices for better assessment of water quality and environmental status of the watershed. From the results, five PCs were extracted which are collectively accountable for controlling approximately 70% of the watershed’s water quality. Results of cluster analysis indicated that three water quality parameters that included total suspended solids, total solids and turbidity control the water quality of the study area. These parameters were allocated into three clusters based on their similarity. The finding of this study will contribute to existing knowledge of the problems associated with water quality in the basin. This information can be put to use by land use managers and policy makers for future planning and development of the watershed.
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