Presentation: Oral

Application of Multivariate and Geostatistics in Addressing Some Basic Issues Related to Groundwater Quality Assessment and Monitoring

Professor O. C Izinyon
Civil Engineering, Engineering

Contact: Department of Civil Engineering, Faculty of Engineering, PMB 1154, University of Benin, Benin City.
[email protected]

Year: 2018


In this study, selected statistical techniques were employed to address some vital issues related to groundwater quality analysis and monitoring. Various water quality parameters, namely; pH, turbidity, total suspended solids (TSS), electrical conductivity (EC), total dissolved solids (TDS), dissolved oxygen (DO) e.t.c were investigated for thirty (30) boreholes located at Idunmwowina, Isiohor and Oluku communities using standard laboratory test procedures. The water quality data obtained from the laboratory analysis were used to investigate the spatial dependence and temporal variability of groundwater parameters. In addition, the data were employed to compute the overall groundwater quality index and determine the critical parameters that can influence the overall quality. Statistical methods employed include; weighted average index method, geospatial analysis using kriging interpolation, multivariate analysis of variance (MANOVA), principal component analysis (PCA), hierarchical cluster analysis (HCA) and discriminant analysis (DA). Results obtained show a strong spatial dependence of the parameters. The calculated p-value and partial eta squared of the Pillai’s trace statistics revealed about 89.8% temporal variability occasioned by sampling location.

Keywords: Discriminant analysis, kriging interpolation, multivariate analysis of variance, principal component analysis, clustering and water quality monitoring.