Document Type
Article
Publication Date
8-17-2022
Department
Department of Geological and Mining Engineering and Sciences
Abstract
Groundwater potential delineation in the Akka basin, southwest Morocco, has been determined through the combination of geospatial techniques and geological data. The geometric average and expected value are two multi-criteria approaches used to integrate a set of factors–data for which the weights of each factor are assigned using the fuzzy logic function, which transforms values of factors influencing groundwater presence in a range of [0, 1]. The efficiency factors used in this study are the lineament density, node density, drainage density, distance from rivers, distance from lineament, permeability, slope, topographic witness index, plan curvature, and profile curvature. Thereafter, the groundwater potential map was generated in a GIS environment. To assess and compare the efficiency of the two models, the well data existing in the basin were used to choose the most efficient model. For that reason, the prediction area (P–A) graph, the normalized density (Nd), and its weight (We) were applied to estimate the capacity of each model to predict the target area. The analysis shows that the expected value model (Nd = 1.86 and We = 0.62) is more efficient than the geometric average model (Nd = 0.96 and We = −0.04). The results of the expected value model can be used in the future planning and management of water resources in the Akka basin.
Publication Title
Sustainability (Switzerland)
Recommended Citation
Echogdali, F.,
Boutaleb, S.,
Kpan, R.,
Ouchchen, M.,
Bendarma, A.,
El Ayady, H.,
Abdelrahman, K.,
Fnais, M.,
Sajinkumar, K.,
&
Abioui, M.
(2022).
Application of Fuzzy Logic and Fractal Modeling Approach for Groundwater Potential Mapping in Semi-Arid Akka Basin, Southeast Morocco.
Sustainability (Switzerland),
14(16).
http://doi.org/10.3390/su141610205
Retrieved from: https://digitalcommons.mtu.edu/michigantech-p/16400
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Version
Publisher's PDF
Publisher's Statement
© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). Publisher’s version of record: https://doi.org/10.3390/su141610205