A Multidisciplinary Approach for Groundwater Potential Mapping in a Fractured Semi-Arid Terrain (Kerdous Inlier, Western Anti-Atlas, Morocco)

Abstract

This study is focused on developing an approach for spatial mapping of groundwater by considering four types of factors (geological, topographical, hydrological, and climatic factors), and by using different bivariate statistical models, such as frequency ratio (FR) and Shannon’s entropy (SE). The developed approach was applied in a fractured aquifer basin (Ameln Basin, Western Anti-Atlas, Morocco), to map the spatial variation of groundwater potential. Fifteen factors (15) influencing groundwater were considered in this study, including slope degree, slope aspect, elevation, topographic wetness index (TWI), slope length (LS), topographic position index (TPI), plane curvature, profile curvature, drainage density, lineament density, distance to rivers and fault network, normalized difference vegetation index (NDVI), lithology, and land surface temperature (LST). The potential maps produced were then classified into five classes to illustrate the spatial view of each potential class obtained. The predictive capacity of the frequency ratio and Shannon’s entropy models was determined using two different methods, the first one based on the use of flow data from 49 boreholes drilled in the study area, to test and statistically calibrate the predictive capacity of each model. The results show that the percentage of positive water points corresponds to the most productive areas (high water flow) (42.86% and 30.61% for the FR and SE models, respectively). On the other hand, the low water flows are consistent with the predicted unfavorable areas for hydrogeological prospecting (4.08% for the FR model and 6.12% for the SE model). Additionally, the second validation method involves the integration of 7200 Hz apparent resistivity data to identify conductive zones that are groundwater circulation zones. The interpretation of the geophysical results shows that the high-potential zones match with low apparent resistivity zones, and therefore promising targets for hydrogeological investigation. The FR and SE models have proved very efficient for hydrogeological mapping at a fractured basement area and suggest that the northern and southern part of the study area, specifically the two major fault zones (Ameln Valley in the north, and the Tighmi-Tifermit Valley in the south) has an adequate availability of groundwater, whereas the central part, covering the localities of Tarçouat, Boutabi, Tililan, and Ighalen, presents a scarcity of groundwater. The trend histogram of the evolution of positive water points according to each potentiality class obtained suggests that the FR model was more accurate than the SE model in predicting the potential groundwater areas. The results suggest that the proposed approach is very important for hydrogeological mapping of fractured aquifers, and the resulting maps can be helpful to managers and planners to generate groundwater development plans and attenuate the consequences of future drought.

Delineation of Groundwater Potential Area using an AHP, Remote Sensing, and GIS Techniques in the Ifni Basin, Western Anti-Atlas, Morocco

“…In this study, we use the AHP model with 14 factors to map the potential groundwater areas (GWPA) in the Ifni basin. This approach has yielded satisfactory results in similar basins [4,5,9,11,19,22]. Our analysis of the factors, such as those used in previous studies [4,5,10,22], revealed that certain relevant factors, such as land use, the intersection between geological lineaments and the hydrographic network, the density of the nodes, and TPI, were not considered in the model.…”

“…This approach has yielded satisfactory results in similar basins [4,5,9,11,19,22]. Our analysis of the factors, such as those used in previous studies [4,5,10,22], revealed that certain relevant factors, such as land use, the intersection between geological lineaments and the hydrographic network, the density of the nodes, and TPI, were not considered in the model. In discontinuous environments, aquifer recharge primarily occurs through faults and lineaments that intersect with the hydrographic network [34].…”

“…To improve the accuracy of our model results, 14 factors, including geological, topographical, and hydrological factors, were used [4,5,10,19,21,50,51].…”

“…Water resources in these regions are characterized by scarcity and irregularity, both spatially and temporally [3]. The growing demands for freshwater in these densely populated areas necessitates exploring alternative sources of renewable groundwater resources [1,4,5]. The Ifni basin in Morocco serves as a prime example of the challenges faced by regions dealing with increasing demand for water to satisfy the growing needs of agriculture and population.…”

Identification of groundwater potential zones in the Rabigh-Yanbu area on the western coast of Saudi Arabia using remote sensing (RS) and geographic information system (GIS)

“…For instance, some researchers have used probabilistic models like the frequency ratio (Ozdemir 2011;Razandi et al, 2015), logistic regression (Ozdemir 2011;Pourtaghi and Pourghasemi 2014;Pourghasemi and Beheshtirad, 2015), weights of evidence (Corsini et al, 2009;Ozdemir 2011;Lee et al, 2012;Echogdali et al, 2023), evidential belief function (Mogaji et al, 2015;Pourghasemi and Beheshtirad, 2015), certainty factor (Razandi et al, 2015), decision tree (Chenini and Mammou 2010), artificial neural network model (Lee et al, 2012), Shannon's entropy (Naghibi et al, 2015), on the whole, remote sensing and GIS are powerful tools that can quickly estimate natural resources. The methods are affordable and can be utilized to successfully explore groundwater (Faust et al, 1991;Hinton 1996;Jha et al, 2010;Benjmel et al, 2022) before utilizing more involved and expensive surveying techniques. The success of the application of remote sensing and geographic information system (GIS) techniques for mapping groundwater potential zones in various regions of the world has been reported (Madrucci et al, 2003;Jaiswal et al, 2003;Solomon and Quiel, 2006;Madrucci et al, 2008;Prasad et al, 2008;Chowdhury et al, 2009;Yeh et al, 2009;Dar et al, 2010;Dar et al, 2010;Saha et al, 2010).…”