Modelling Groundwater Quality of Aba in Abia State Using Principal Component Analysis and Multiple Linear Regression
Ogbonnaya Paul Kanu, Ejikeme Ugwoha, Ngozi U. Udeh, Victor Amah
Journal of Engineering Research and Reports · pp. 39–54 · Published 23 Nov 2023
10.9734/jerr/2023/v25i111019Abstract
The aim of this study was to model the groundwater quality of Aba in Abia state. To achieve the aim, thirty-two water samples were taken from sixteen boreholes during the rainy and dry seasons and analysed in the laboratory for pH, Electrical Conductivity, Total Hardness, BOD5, COD, Pb, Cd, Cr, NH3, TDS, SO4, NO3 and PO4. Principal Component Analysis (PCA) and Multiple Linear Regression (MLR) were employed to extract the principal factors and develop a model for predicting water quality index for Aba, Abia State. In the dry season, water quality index could be estimated using the Water Quality Index (WQI) model with pH, PO4, COD, SO4 and Pb with Adjusted R2 = 0.999999999938 and standard error of 0.043868872. Meanwhile, in the rainy season, WQI could be estimated using the WQI model with Turbidity, PO4, NO3, COD, SO4 and Pb with Adjusted R2 = 0.999999997469 and standard error of 0.066697494. The one-way ANOVA for the parameters in the dry season with p = 0.000 < 0.05 indicated that leachate had a large effect on groundwater quality. During the rainy season, one-way ANOVA result with p = 0.000 < 0.05 asserted that leachate had a large effect on groundwater quality.
Cited by 2
Yajing Wang, Mingyu Wang, Runfeng Liu · Water · 2024
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