Groundwater Quality Assessment in Aba (Abia State) Using WQI and GIS Techniques
Ogbonnaya Paul Kanu *
Centre for Occupational Health, Safety and Environment, University of Port Harcourt, Nigeria.
Ejikeme Ugwoha
Department of Civil and Environmental Engineering, University of Port Harcourt, Nigeria.
Ngozi U. Udeh
Department of Civil and Environmental Engineering, University of Port Harcourt, Nigeria.
Victor Amah
Department of Civil and Environmental Engineering, University of Port Harcourt, Nigeria.
*Author to whom correspondence should be addressed.
Abstract
Groundwater is considered as the most important source of freshwater for human consumption and activities in the urban environment. The assessment of groundwater quality is critical to avoid the negative effects of polluted groundwater on human health, agriculture, and the economy. In this study, the quality of groundwater in Aba (Abia State), Nigeria was assessed. Thirty-two water samples were taken from sixteen boreholes during the rainy and dry seasons, and analysed for pH, Electrical Conductivity, Total Hardness, Turbidity, Temperature, BOD5, COD, Pb, Cd, Cr, NH3, TDS, SO4, NO3 and PO4. The Weighted Average Water Quality Index (WAWQI) approach was used to compute the Water Quality Index (WQI). Geostatistical analysis methods such as Ordinary Kriging, Empirical Bayesian Kriging (EBK), Inverse Distance Weighting (IDW) and Spline interpolation methods were compared in the spatial evaluation of variable concentrations using ArcGIS. In the dry season, 100% of the borehole locations had Water Quality Index values above 100 which is Unsuitable for drinking purpose. For the rainy season, 87.5% of the borehole locations had WQI values above 100 which is Unsuitable for drinking purpose, 6.25% had WQI which was of very poor quality and 6.25% had WQI values within the range of good water quality between 26 and 50. With a mean error of 0.372483, RMSE of 0.5515, and RMSSE of 1.030492 for the dry season and a mean error of 0.05625, RMSE of 10, and RMSSE of 0.986448 for the rainy season, the EBK interpolation approach was the best fit model for the WQI determination. WQI values for rainy season were generally lower than the WQI values of the dry season, attributable to surface water run-off during the rains.
Keywords: Water quality index, WAWQI, Aba, groundwater quality, geostatistical analysis
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References
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