Spatial Mapping of Groundwater Potentiality Applying Geometric Average and Fractal Models: A Sustainable Approach

Abstract

Water scarcity affects all continents, with approximately 1.2 billion people living in areas where water is physically lacking. This scarcity is more accentuated in countries with an arid climate, and its impact becomes more threatening when the economy depends mainly on it. The Kingdom of Morocco, with its agricultural vocation, is one of them, especially in its southern regions. Therefore, mapping areas with high groundwater potential based on available geospatial data allows for optimizing the choice of a future well in such areas. Geometric average and fractal models were used to assess and delineate potential groundwater areas in the Tissent basin, Southeast Morocco. Eight factors, including topography, geology, hydrology, and hydrogeology, influencing the distribution of water resources was used. The formation permeability factor presents the most significant impact among the others, although it is directly related to most of them. The areas located in the central and downstream part of the basin are characterized by a high water potentiality due to increased geological formations’ permeability near the drainage system, which constitutes a recharge zone, and a low slope allowing a prolonged water-formation contact time favoring a gradual infiltration of the water towards the deep aquifers. The groundwater potential map has been edited and validated by comparing it with data from 52 wells scattered throughout the basin. The favorable potential sectors cover 15.81% of the basin’s total area. The moderate ones account for 21.36% while the unfavorable areas cover 62.83%. These results aim to provide policymakers and managers with a guide map for groundwater research and reduce hydrogeological investigation costs.

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].…”

“…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.…”

“…To delineate GWPA using this model, four key steps are taken: standardization of prospecting factors, generation of a pairwise comparison matrix, checking the consistency of the matrix, and weighting the evaluation factors in a GIS environment [4,10,21,22]. (3) Machine learning techniques (MLT) have shown improved accuracy in many situations due to their ability to process non-linear data with varying scales and from different sources [23][24][25][26].…”

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)

“…From documented reports, the groundwater potential zones have been defined and mapped using various techniques. 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.…”