Application of Multi-Criteria Decision Analysis to Geoelectric and Geologic Parameters for Spatial Prediction of Groundwater Resources Potential and Aquifer Evaluation

TLDR: In this paper, the principle of multi-criteria decision analysis in the context of the analytical hierarchy process is proposed as a technique that can yield a prediction model of higher reliability and precision.

Abstract: Prediction of groundwater resources potential is a spatial decision problem that involves a set of multiple evaluation parameters. In order to produce a groundwater resources potential prediction model of higher reliability and precision in a given study area, the effects of all the important parameters that can contribute to the groundwater occurrence in the area must be integrated. However, the methodology of integrating these parameters such that the relative importance of each is reflected is still a challenge that has not been efficiently handled. In this study, the principle of multi-criteria decision analysis in the context of the analytical hierarchy process is proposed as a technique that can yield a prediction model of higher reliability and precision. The proposed technique was applied to geoelectric and geologic parameters, derived from the results of the interpretation of 2D resistivity imaging data acquired from the study area. The advantage of the proposed technique is that it reduces bias in decision making. The main objective of the study is to produce groundwater potential map for the area. Furthermore, an attempt was also made in the study to characterize the aquifer of the area by estimating the Dar-Zarrouk parameters, using the integration of borehole and 2D resistivity data. The success rate (accuracy) of the prediction was established to be 80 %. Furthermore, the regression line fitted to the aquifer transmissivity and transverse resistance data shows linear relationship with a high regression coefficient of 0.79. The prediction success rate obtained showed that the method proposed in this study is reliable, accurate, and an improved technique of integrating multiple parameters for holistic evaluation of groundwater resources.