TITLE:
Groundwater Vulnerability and Sensitivity Optimization Using Geographical Information System for Kano Metropolis, North-Western Nigeria
AUTHORS:
Zaharatu Mohammed Babika, Lee D. Bryant, Thomas R. Kieldsen, Abubakar Ibrahim Tukur
KEYWORDS:
Groundwater Pollution, Sensitivity, Modelling, Optimization
JOURNAL NAME:
Journal of Geoscience and Environment Protection,
Vol.10 No.4,
April
26,
2022
ABSTRACT: This paper developed an optimization technique for groundwater
vulnerability in Kano Metropolis, North-Western Nigeria. A combination of
DRASTIC is taken from initial letters of seven parameters namely depth to water
table (D), net recharge (R), aquifer media (A), soil media (S), topography (T), impact of vadose zone (V) and
hydraulic conductivity (C), while GOD also represents groundwater
confinement (G), overlaying strata (O), depth of water (D) and
multi-criteria evaluation (MCE) techniques were used in the optimization method
by integrating other important and sensitive parameters for groundwater pollution,
principally the anthropogenic point source pollution parameters (dump site,
petroleum stations, automobile shops and under storage tanks). Geographic
Information System was used to perform the sensitivity analysis (SA) using the
single parameter and map removal sensitivity methods. Result of sensitivity
optimization revealed the depth to groundwater (D), net recharge (N), impact of
vadose zone (V) from DRASTIC model, and groundwater conferment (G) from GOD
model having significant impact on the groundwater vulnerability, respectively.
A combination of these four parameters was used to generate DNVG groundwater
vulnerability for the area. This suggests that an integration of other point
source pollution parameters can enhance the
influence of DRASTIC and GOD model parameters on groundwater
vulnerability condition. The paper recommends for the application of the
optimization method used in this study in another area with similar geological
and anthropogenic point source of pollution with a view to validating or
improving on it. In this study, several input data, such as anthropogenic point
sources of contamination, are added to the existing DRASTIC and GOD model
parameters as part of a sensitivity analysis aiming to optimise the performance
of the resultant models.