Results in Earth Sciences (Dec 2024)

Assessment of groundwater resources from geophysical and remote sensing data in a basement complex environment using fuzzy-topsis algorithm

  • Kola Abdul-Nafiu Adiat,
  • Abdulgafar Opeyemi Kolawole,
  • Igbagbo Adedotun Adeyemo,
  • Ayokunle Adewale Akinlalu,
  • Daniel Oluwafunmilade Afolabi

Journal volume & issue
Vol. 2
p. 100034

Abstract

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This study addresses the pressing global water challenge by focusing on a typical basement complex area experiencing acute water shortage. Indiscriminate well siting without reliable hydrogeological maps has resulted in failed attempts to address water shortages. To overcome these challenges, this research aims to enhance the accuracy and reliability of groundwater potential assessments by incorporating crucial groundwater-related factors.The Fuzzy Technique for Order Preference by Similarity to Ideal Solution (FTOPSIS) method was adopted due to its ability to improve multi-criteria decision-making (MCDM) techniques for effective groundwater resource management. Unlike TOPSIS, FTOPSIS better reflects decision-makers' intentions, especially concerning geological boundaries and natural phenomena. To achieve the objectives of the study, geophysical and remote sensing datasets were utilized. The study employed the electrical resistivity method, utilising the Vertical Electrical Sounding (VES) technique with the Schlumberger array while the remote sensing data used were the Digital Elevation Model (DEM) image and Landsat ETM image which were processed to generate key groundwater conditioning factors. These factors were integrated using the FTOPSIS algorithm. This algorithm facilitated the calculation of the groundwater potential indices by assigning weights based on their level of significance to influencing groundwater potential in order to generate the groundwater potential map (GPM). The GPM was classified into five zones of varying groundwater potential, with very low and low potential occupying 74 % of the total area. Validation with well data yielded an impressive 79 % accuracy, showcasing the model's enhanced precision. Beyond improved accuracy, the study's implications extend to practical applications in groundwater resource management. By providing a clearer understanding of groundwater potentiality, the research can inform more robust decision-making frameworks, promoting sustainable water use not only in the study area but also in similar geological settings of the world.

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