DGIS-BASED DRASTIC MODEL AND VES FOR ASSESSING GROUNDWATER VULNERABILITY IN AQUIFERS IN OWERRI, SOUTH EAST NIGERIA.

Student: Uchenna Emmanuel Obilam
Supervisor: Dr Austin James Okoli
Co-Supervisor: Mr Patrick Chidube Okafor
HOD: Dr Awuchi Israel Ikoro
Department of Geology
Physical Sciences
Federal University of Technology, Owerri, Imo State

Abstract

Groundwater is a vital natural resource, and its vulnerability to contamination needs to be carefully assessed for sustainable management. This research focuses on the development of a Geographic Information System (GIS)-based DRASTIC model, combined with Vertical Electrical Sounding (VES) data, to assess groundwater vulnerability in aquifers within Owerri, South East Nigeria. The research methodology included an initial literature review and the creation of a study area map. Field surveys were conducted to gather data on geological features, hydro-geological aspects, and geo-electrical sounding. Geo-electrical data were interpreted to delineate subsurface structures. The study area, located in Owerri, Imo State, Nigeria, spans approximately 125 square kilometers. The city boasts a dynamic landscape, with mostly level terrain, elevations ranging from 70 to 120 meters above sea level, and two important rivers bordering the area. Data acquisition involved using the Vertical Electrical Sounding (VES) method with ABEM-Terrameter equipment in the Schlumberger configuration. Twelve VES stations were established, but offset VES points were unavoidable due to topographical constraints. Data processing was done using the IP2win software, yielding true resistivity layers and thicknesses. To assess groundwater vulnerability, the DRASTIC model was applied, considering seven critical parameters: depth to water table, net recharge, aquifer media, soil media, topography, impact of the vadose zone, and hydraulic conductivity of the aquifer. Each parameter was assigned a weight and rating, contributing to the DRASTIC Index (DI). The DI values were then categorized into low, moderate, high, and very high vulnerability classes. Results showed varying vulnerability zones across the study area.

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