Modelling and Prediction of Water Quality Index of Selected Pond Water in Aboh Mbaise Local Government Area, Imo State, Nigeria

Abstract

The aim of this study is the development of water quality models against water quality parameters from 5 selected ponds in Aboh-Mbaise local government area (LGA) of Imo state. Water quality index (WQI) as dependent variable computed based on water quality parameters which were taken as independent variables and modelled as multiple linear regression. Given that there are over 25 water quality parameters (physiochemical, heavy metals and microbials), it was necessary to adopt factor reduction technique using principal component analysis. In this approach, 3 principal component factors were generated having corresponding factors (independent variables of 5, 6 and 5 respectively). The resulting multiple regression for the 3 principal component factors yielded Goodness of Fit of 92.9, 99.0 and 96.6% as well as root mean square error (RMSE) of 66.673, 0.672 and 51.968 respectively. The model verification was accomplished by plotting the computed WQI against predicted values from the developed models and the best option was the one with 99.0% R2 value with the following independent variables-sulphate, TSS, phosphate, turbidity, total solid and nitrates. The model output is relevant in WQI prediction given the applicable water quality characteristics. This predictive model will find wide application in selecting water treatment options for pond water in the study area.