Groundwater Potential Evaluation using Simple Regression Analysis at Gidan Kwano Campus Phase II, Minna, Northcentral Nigeria

Abstract

The statistical method of simple regression analysis (SRA) is employed here to test for subsurface resistivity prediction of vertical electrical sounding (VES) data collected at the Gidan Kwano Campus Phase II. Usually, the 100m station-spacing specification implies that each VES was carried through to the 100m depth-mark, entailing 21 individual sequences of measurements; this obviously implies longer survey time. It is instructive, then, to enquire if a process exists by which an empirical route based on just a few survey sequences can be developed such that the entire 21 individual sequences of measurements of the VES stage can be fairly predicted to a high degree of accuracy. The aim of this study is the building of a valid VES statistical prediction model for the planned Gidan Kwano Campus Development Phase II. This investigation was aided by the SRA statistical tool; the SRA method shows the relationship between an independent and a dependent variable, as well as providing a means for the derivation of an equation to predict the dependent variable based on the values of the independent variable. The result of this study shows that a two-fifth or 40% positive correlation for y and y1 of groundwater prospect locations down to 40m for the first cross-profile means that the simple regression analysis route for this first cross-profile cannot be used as a cost-cutting routine. Based on the results of subsequent cross-profiles, it is not recommended to adopt the SRA method as a cost-cutting routine whereby maximum depths of survey of intervening prospect locations should be limited to just 40m.