Abstract
Groundwater is a valuable shared resource in the Moulouya Basin, but it has been in decline due to recent years of low rainfall and rapid population growth. To support socio-economic development, there is increased demand for this precious resource. This paper presents a standard methodology for delimiting potential groundwater zones using geographic information systems (GIS), an integrated analytical hierarchy process (AHP), and remote sensing techniques. Seven parameters that monitor the presence and mobility of groundwater, including drainage density, lithology, slope, precipitation, land use/land cover, distance to river, and lineament density, were incorporated into a raster data model using ArcGIS software. AHP-based expert knowledge was used to prepare a groundwater potential index and assign weights to the thematic layers. The study classified the area into five zones of varying groundwater potential: very high (26%), high (51%), moderate (13%), poor (9%), and very poor (1%). The accuracy of the model was validated by comparing the Groundwater Potential Zones map with data from 96 wells and boreholes across the basin. The validity of the results was confirmed by comparing them with the specific yield of the aquifer in the study area, yielding a high correlation coefficient (R2) of 0.79. The analysis revealed that 89.5% of the boreholes were situated in the high and very high potential zones, demonstrating the reliability and robustness of the employed approach. These findings can aid decision-making and planning for sustainable groundwater use in the water-stressed region.
Similar content being viewed by others
Avoid common mistakes on your manuscript.
Introduction
Water is essential for human survival and has been recognized as a crucial resource worldwide (e.g., Jha et al. 2007; Hilal et al. 2018; Bouadila et al. 2019, 2023; Kostyuchenko et al. 2022; El Yousfi et al. 2022, 2023a,b; Aqnouy et al. 2018, 2019, 2021, 2023; Abioui et al. 2023; Khaddari et al. 2023; Ikirri et al. 2023). Groundwater, in particular, plays a vital role in supporting the growth and development of both rural and urban areas and is crucial for agriculture, industrial activities, and ensuring a safe and clean water supply for communities. As population growth and changing land-use patterns increase water demand, the sustainable management and use of groundwater resources become increasingly important to ensure a secure future for communities and the environment. Groundwater is a finite resource and its availability and quality are threatened by over-extraction, contamination, and climate change. Therefore, the responsible use and management of groundwater are crucial for sustainable development (Jha et al. 2007; Ahmed et al. 2021; Elbadaoui et al. 2023).
Morocco is vulnerable to frequent droughts, particularly in its four main basins including the Moulouya basin (Bouizrou et al. 2022, 2023). This region has experienced a widespread rainfall deficit that has led to a decline of up to 50% in some climate stations. This shortage is a result of both prolonged drought and excessive extraction of groundwater resources, posing a significant threat to the socio-economic development of the area. In this sense, and according to Nouayti et al. (2019), 65% of irrigation water comes from groundwater, and therefore the demand for groundwater is becoming increasingly important. This high demand pushes researchers and managers to seek efficient and economical methods of exploration, evaluation, and development of groundwater to ensure more resources to cover the needs.
Conventional methods used for identifying and mapping groundwater typically involve drilling, geological assessments, hydrogeological studies, geophysical techniques, and field surveys. These approaches necessitate significant labor and resources, including time, finances, and the involvement of specialized professionals, especially during exploration activities (Shao et al. 2020; Nhamo et al. 2020). However, modern alternative approaches such as multi-criteria analysis methods, geographic information system (GIS), and remote sensing (RS) have shown promising results in identifying groundwater potential (Magesh et al. 2012; Ferozu et al. 2019; Khan et al. 2020), offering encouraging and promoting outcomes. Faced with this situation, establishing an assessment and ensuring optimal management of water resources in these areas has become essential and to achieve this, water managers need very precise information on the conditions of recharge and exploitation at the level of each hydrogeological basin. The quantification of groundwater recharge is one of the most relevant topics, but also the most difficult to estimate because it is controlled by parameters and contexts that vary in time and space.
Different approaches have been considered for its estimation such as: the geochemical method based on the use of the chloride balance (Cl−), the direct method which consists in estimating the infiltration using in situ measuring devices, the isotopic method which exploits the ratios of the tritium (3H) contents of the waters of the aquifers compared to those of the precipitations (Allison 1988), the climatic method of Turc (1955) and the physical method which takes into consideration the humidity and soil pressure (Allison 1988). Many authors have faced the task to identify GWPZ using several knowledge and data-driven models (Table 1), but the use and insertion of the parameters that control groundwater recharge constitute an important starting point for the mapping of GWPZs because the climatic, geological, hydrogeological and structural contexts are relative to each geographical area and can change from one area to another. The technique of multi-criteria analysis is a method that considers algorithms and that makes it possible to guide a choice based on several common criteria. This method is primarily intended for understanding and solving decision-making problems (Heywood et al. 1995). A specific weight is attributed to the different parameters to enhance and quantify their relative contribution in the multi-criteria analysis technique. Thus, to have an idea of the situation, the determining parameters must be treated and integrated by giving a specific weight to a particular domain.
Our research builds upon and enhances existing methodologies for groundwater potential mapping in the study area. While Saadi et al. (2021) utilized a cartographic approach with five key parameters, including lithology, rainfall, drainage, lineaments, and slope, we have made substantial contributions by introducing two additional critical parameters, namely the distance to the river and land use. These additions were motivated by their significant roles in influencing aquifer recharge processes, which were not fully accounted for in previous studies. Similarly, in the work conducted by Benjmel et al. (2022) in an arid region of southwest Morocco, precipitation was not considered a determining factor. However, in our research, we acknowledge the vital role of precipitation in our study area and integrate it as one of the key parameters for groundwater potential mapping. By doing so, we provide a more comprehensive understanding of the complex interactions between various hydrological and geological factors that influence groundwater occurrence.
Various estimation methods have been applied to evaluate the GWPZ. These methods include single-factor analysis (Xin-feng et al. 2012), multi-influence factor techniques (Nasir et al. 2021), fuzzy clustering (Tükel et al. 2021), brittle rock proportion (Singaraja et al. 2015), Fuzzy-AHP indices (e.g., Rajasekhar et al. 2019; Echogdali et al. 2022a; Sinha et al. 2023; Bhagya et al. 2023) and GIS information fusion (Arnous et al. 2020). In this particular study, the delineation of GWPZs is conducted using the analytic hierarchy process (AHP) (Saaty 1989) and RS-GIS methods. The identification of GWPZs is based on seven factors, which include drainage density, lithology, slope, precipitation, land use/land cover, distance to river, and lineament density.
The Hierarchical Analysis Process (AHP) is a multi-criteria decision-making tool that structures a complex problem into a hierarchical system. The approach is based on 2-to-2 comparisons of elements, grouped into comparison tables, at each level of the hierarchy (Wind and Saaty 1980). The user starts by defining the criteria comparison table at level 0, followed by sub-criteria comparison tables at level 1 (if it's a 2-level problem) or alternatives on the criteria at level 1. Finally, at level 2, the comparison tables of alternatives on criteria and/or sub-criteria are defined. The result is a comprehensive experimental plan for AHP analysis. The utilization of the AHP approach in evaluating the significance of selected parameters within a hydrogeological model has been adopted by numerous researchers (e.g., Hajkowicz and Higgins 2008). AHP is recognized as a robust decision-making method that takes into account multiple factors, as supported by studies conducted by Mohammadi et al. (2018) and Pinto et al. (2017).
This study aims to harness the potential of AHP, GIS, and remote sensing techniques to identify and map the Groundwater Potential Zones (GWPZ) in the Moulouya basin, located in North-East Morocco. Through the integration of geospatial methods and consideration of various influencing factors, the study seeks to decipher and statistically validate the groundwater potential zones. The ultimate objective is to offer decision-makers a dependable hydrogeological tool for the selection and implementation of future water wells. By doing so, this approach aims to reduce the expenses associated with geophysical investigations and promote sustainable groundwater management practices.
Materials and methods
Study area
The Moulouya basin is the largest Mediterranean basin in Morocco and Northwest Africa with an area of 55,500 km2. Geographically, it is located in the Northeast of Morocco and extends between the parallels 32° 18′ and 35° 9′ North and the meridians 1° 10′ and 5° 40′ West. It is limited to the northwest by the Mediterranean coastal basins, to the west by the basins of Sebou and Oum Rbia, and to the south by the basins of Ziz and Guir, while to the east it extends into the Algerian territory (Fig. 1). The Moulouya basin in Morocco boasts a Mediterranean climate, marked by low and unpredictable annual rainfall amounts (ranging from 200 to 400 mm). Its shape, stretching from the South to the North and slightly slanting to the East, allows it to benefit from the humid Mediterranean winds while being exposed to scorching and dry winds from the South. This region boasts a highly concentrated hydrographic network. The Moulouya River, as the main collector, drains a large number of tributaries along its course, the main ones forming the large sub-basins of the area and which are: Za, Msoun, Melloulou, and Ansegmir wadis.
The geological formations in the Moulouya basin range in age from the Paleozoic to the Quaternary. The Paleozoic era is primarily composed of shale and granite, covering 2.59% of the basin's area (Ahamrouni 1996). In Upper Moulouya, these rocks form primary massifs such as Boumia and Ahouli and are found as schists that make up most of the region's metamorphic series. The Triassic formations outcrop unconformably on the old massifs of Upper Moulouya, and are made up of marls, clays, and altered basalts (Riad 2003). The Jurassic is marked by calcareous-dolomitic facies and red terrigenous paleosol deposits that form the Upper Moulouya. The carbonate formations are found on the borders of the Middle and High Atlas and to the west of the highlands (Riad 2003).
The Cretaceous is characterized by marls, red sandstone, and white limestone, and outcrops mainly along the High Atlas between the Aouli massif and the High Atlas and to the east of Midelt. It begins with conglomerates, followed by marls and limestones that have deposited evaporitic series, particularly gypsum (Nasloubi 1993). The Quaternary formations, which are the most recent, are deposited above all previous formations and consist of fluvial terraces in the form of nested series, covered with silt and conglomeratic deposits (Amrani 2007). The study basin is located within a NE-SW shear zone from a tectonic perspective. The dominant fault structures in the area are oriented in two main directions: E–W and NW–SW, which can be identified as Riedel fractures. The structural evolution of the area is complex due to the varying directions of deformation axes from the Upper Eocene to the present day (Labbassi 1991).
Parameters controlling groundwater recharge
The selection of thematic layers used for determining groundwater recharge in the study area is based on the parameters that affect it. The hydrological conditions in the area, which significantly impact the presence of groundwater, are largely influenced by these thematic layers. Using these layers provides a solid foundation for accurately predicting the groundwater potential of a region. Saadi et al. (2021) found that factors affecting recharge in the middle Moulouya basin include slope, drainage, precipitation, lithology, and fracture lineaments. Guo et al. (2019) reported that proximity to rivers greatly impacts precipitation infiltration, with a 50% effect. Siddik et al. (2022) also highlighted the significant impact of Land Use/Land Cover (LU/LC) changes on groundwater recharge. The study took both of these findings into account by including "Distance to river" and "LU/LC" as parameters in the applied model.
The overlapping layers must possess comparable cartographic features, such as equivalent resolution, geographical extent, length units, and projection system. This requirement ensures that calculations are carried out on a consistent matrix or mesh size (Fig. 2).
Rainfall (Rf)
The recharge of groundwater is monitored by various parameters of which precipitation is the main source of groundwater recharge (e.g., Aswathi et al. 2022; Echogdali et al. 2022b). Precipitation intensity is one of the key factors controlling the recharge-runoff relationship. Average annual precipitation from 2010 to 2021 in the study area was obtained at stations located in the basin. Subsequently, they were spatially interpolated in ArcGIS 10.4.1 to obtain a rainfall contour map. The resulting map was categorized into five main groups: < 100 mm/year (Very low), 100–200 mm/year (low), 200–300 mm/year (Moderate), 300–400 mm/year (High) and > 400 mm/year (Very high) (Fig. 3a). The map shows that the rainfall varies from 220 to more than 350 mm/year. It increases from south to north.
In our adopted cartographic approach, we considered precipitation as a determining parameter influencing groundwater recharge, and we integrated historical data on its trends to assess its impact on groundwater recharge in the region. Additionally, we conducted prospective analyses to project future water needs, taking into account estimates of the local demographics, which increased from 2,102,781 inhabitants in 2004 to 2,505,730 in 2020 and is projected to reach 2,725,106 by 2030, according to the report of the (HCP 2021).
The remarkable expansion of irrigated agricultural areas in the Moulouya basin, which increased from 65,400 hectares in 1986 to 133,721 hectares in 2022, as reported by HCP (2021), along with the number of wells exceeding 2200 (Saadi 2021), was considered in evaluating their implications on groundwater resources. The combination of historical precipitation data, statistical modeling, and demographic projections thus provided a solid foundation for understanding the high water demand and addressing the complex interactions between human activities, climate, and groundwater availability in the region.
Lithology (Lt)
The lithological characterization of soils essentially aims to highlight the classes of soils concerning their runoff capacity. The infiltration of water depends on the permeability of the rock, by porosity or by fracturing, and on the resistance to erosion of the rock itself or of the ground cover which is present above. It provides information on permeability and influences not only groundwater flow but also surface runoff. According to Shaban et al. (2006), the rock type can significantly influence the GWPZ. Similarly, El-Baz and Himida (1995) found that lithology affects recharge by controlling water percolation. Some authors like Arshad et al. (2020) and Kolli et al. (2020) ignored the lithological component in GWP mapping by taking into account drainage characteristics and lineament density as the main factors for measuring porosity. Information on the lithology of the Moulouya basin is obtained by combining the supervised classification of Landsat 8 images with geological maps and technical borehole sections. The lithology thematic map is distinguished into seven lithological units: Carbonate Sedimentary, Unconsolidated Sediments, Mixed Sedimentary, Evaporites, Metamorphic, Plutonic Igneous, and Siliciclastic Sedimentary (Fig. 3b). The major part of the Moulouya is occupied by carbonate sedimentary formations from the Lias and the Middle Jurassic, especially the dolomitic series with 39%, also there are fluvial deposits from the Middle Holocene with 26%, while 21% of the area of the basin is taken by series of gypsum and clayey limestone with deposits of conglomerates (21%), without neglecting the presence of evaporites and siliciclastic sediments with minimal percentages (Birot 1963).
Slope (Sl)
This factor is involved in increasing the velocity of water flow with a subsequent decrease in vertical infiltration and thus influencing the recharge process. The steeper the slope, the faster the surface water circulates and the less the groundwater recharges (Satapathy and Syed 2015). We note that the highest slopes are located mainly on the lines of the ridges of the basin and in the Moroccan High Atlas and part of the Middle Atlas, while the very low class represents the reservoirs of dams and water lakes. The other classes (between 10, 20, and 30°) are generally dispersed in the center of the basin (Fig. 4a).
LU/LC
Land Use/Land cover is the result of physical-geographical factors (relief, lithology, and climate) which are added to the anthropogenic factor via clearing and cultivation as well as reforestation. The LC map was produced using the supervised classification method of the Landsat8 image using the "maximum likelihood" algorithm. The image processing was carried out using ENVI 5.3 software and ArcGIS 10.4.1 by applying the supervised classification technique coupled with field observations, which gave the thematic LULC map (Fig. 4b).
Drainage density (DD)
The hydrographic network is characterized by its drainage density, which expresses different physical phenomena: the relative share of surface flows and underground flows. This criterion, by favoring the drainage of the slopes, makes it possible to understand the importance of surface drainage. This is defined as the average length of the hydrographic network per kilometer. Land that has a dense drainage system has a high recharge rate and the opposite is also true. In this work, drainage density was computed using the Line Density tool in ArcGIS 10.4.1 (Fig. 4c). The very low class (> 3 km/Km2) occupies 57% of the area, followed by the low class (3–2.25 km/km2) with 27%, the moderate class (2.25–1.5 km/km2) with 11 0.5%, the high class (1.5–0.75 km2) With 3% and finally the Very High class (< 0.75 km/km2) which is the smallest and represents 0.84% of the area of the basin.
Distance to the river (DR)
The distance to hydrographic networks is a critical factor in hydrogeology, as it indicates the presence of alluvial aquifers, especially in semi-arid regions, which is the focus of our study (Benjmel et al. 2022). To determine the distance to rivers parameter, we utilized the Euclidean Distance tool in ArcGIS 10.4.1 on the major river network. Based on the spatial distribution of the distance to rivers, we identified two classes: the very low class covering 47% of the basin area and the very high class covering 53% (Fig. 4d).
Lineaments density (Ld)
The mapping of structural objects (lineaments, fractures, faults, lithological limit, etc.) plays an essential role in the different phases of prospecting for underground water resources (Karimoune et al. 1990; Biémie 1992; Shaban 2003; Abdou Ali 2018). As an application in hydrogeology, we can cite for example obtaining and determining from satellite images, information on the nature of the soil and other structural objects such as fractures which sometimes play the role of a drain thus participating in the recharge of groundwater. For Shaban (2003), connected lineaments create a subterranean pathway for groundwater flow. This makes them an indicative parameter of groundwater transport and therefore an analysis criterion in the production of maps of potential water recharge areas (Teeuw 1994; El-Baz and Himida 1995). Lineament density (Ld) is calculated based on the following equation (where ∑i = 1i = n denotes the length of lineament lines, and A denotes the area):
To obtain the lineament map, we used the PCI GEOMATICA software to extract it from Landsat 8 images. Lineament densities in the basin range from < 0.0028 to 1.02 km/km2 (Fig. 4e). The density of lineaments on the groundwater potential map indicates the potentiality of groundwater in a particular area. Areas with higher lineament density are likely to have higher groundwater potential, whereas lower lineament density suggests lower potential. The highest lineament density is commonly found in the western and northwestern parts of the basin, and it appears to be elongated in a northeast-southwest direction. These findings are consistent with those reported by Chennouf et al. (2007).
Analytical hierarchy process (AHP) model
The Analytical Hierarchy Process (AHP) was first introduced by Saaty (1989), and it was used to determine the weights of the thematic layers. This approach involves four fundamental steps: (1) Standardization of the evaluation parameters, (2) Preparation of a pairwise comparison matrix, (3) verification of the inconsistency of the criteria developed, and (4) Aggregation of the weighting results (Allafta et al. 2020).
Pairwise comparison matrix
The Pairwise Comparison Method is a statistical technique that determines the relative importance of each factor in the decision-making process. It is done by comparing the factors pairwise, creating square matrices, and then calculating the weighting coefficients based on the eigenvectors of these matrices. This method provides an objective determination of the weights or weighting coefficients, ensuring a systematic approach to the decision-making process.
The weights of each parameter were determined taking into account the importance of each parameter in the characterization of groundwater potential. This comparison was based on Saaty's 1 to 9 scale (Saaty 1989) in Tables 2 and 3.
Assessing matrix consistency
In this hierarchical classification approach, it is possible to verify the consistency of our method by determining the coherence or consistency ratio (CR). The latter constitutes an acceptance test of the weights of the different criteria. This step aims to identify any inconsistencies in the comparison of the significance of each pair of criteria. The CR is calculated as follows:
The CI in this study is represented by the equation where λmax stands for the major eigenvalue and n signifies the number of parameters involved:
The principal eigenvalue (λmax) of Table 4 was calculated by adding the products of the sum of the columns of parameters and the eigenvectors of Table 3.
To check the consistency (CR) of the decision of the selected parameters, the following equation is used:
where RI represents the random index which is given in Table 5 for different n values. In the current study, RI equals 1.32 for seven parameters. Therefore, CR is:
The obtained CR of 4.6% (less than 10%) is eligible to overlay weighted parameters for GWPZ mapping. The CR value should be lower than 0.1 to confirm that the pairwise comparison judgments are compatible. However, if the CR value is higher than 0.1, the coefficients of the matrix are inconsistent and are not usable for further processing (Wong and Li 2007).
GWPI definition
Groundwater Potential Index (GWPI) is a method of predicting areas of high groundwater potential in a region. Once the thematic layers of the different parameters are prepared with their weights (Table 5), the groundwater potential index (GWPI) is calculated based on the linear combination method indicated by Malczewski (1999):
where Wi is the standardized weight of the thematic layer i, Xj is the ranking of each class for layer j, m is the total set of thematic layers and n is the total set of classes in a thematic layer.
The model's accuracy was assessed through validation against data from 96 wells and boreholes distributed across the Moulouya basin. The statistical comparison was made using the correlation coefficient to evaluate the accuracy of the Groundwater Potential Zones (GWPZ) map (Table 6).
Results
Identification of GWPZ
The development of the groundwater potential map involved the application of formula (6) through a GIS environment, with all parameters chosen based on AHP techniques. The resulting groundwater potential index values were then classified into five distinct (GWPZ): very poor, poor, moderate, high, and very high. These zones covered different percentages of the study area, with the very poor zone covering 60.54 km2 (1%) and the very high zone covering 13,560.59 km2 (26%). The poor, moderate, and high zones covered 4669.09 km2 (9%), 6692.22 km2 (13%), and 26,135.07 km2 (51%), respectively (Figs. 5, 6).
The distribution of groundwater potential in the study area is influenced by various geological and hydrological factors, including rock types, rainfall, and the presence of lineaments. The areas with high groundwater potential are typically associated with favorable conditions for water recharge and storage. For example, the presence of permeable rock formations, such as limestone and dolomitic limestone, in these areas allows for water to percolate and accumulate in the subsurface. Additionally, the moderate annual average rainfall in these areas helps to replenish the groundwater aquifers. The presence of lineaments, or linear fractures in the rock formations, can also contribute to the high groundwater potential by providing pathways for water to penetrate deeper into the subsurface. On the other hand, areas with low groundwater potential are typically associated with unfavorable conditions such as steep slopes, high altitudes, and low densities of lineaments. Areas of very high to high underground water potential are located in the central and northeastern parts and small patches in the southwestern part of the basin (Fig. 6).
These areas are dominated by limestone and dolomitic limestone from the lower to middle Lias influenced by the presence of lineaments, they are characterized by moderate annual average rainfall. Similar observations were also noted by Benjmel et al. (2022). Additionally, the study found that the distribution of different land use and land cover (LULC) types can also greatly impact the groundwater potential in the study area. Das et al. (2019) have demonstrated that wetlands, vegetation, and cropland are associated with good groundwater potential. This is in line with the findings of the present study, where it was confirmed that these LULC types play a crucial role in determining the high to moderate groundwater potential areas. This highlights the interplay between LU/LC and hydrological processes and how they impact slope stability. Thus, it is crucial to consider LU/LC when assessing the groundwater potential and its distribution.
The areas of poor to very poor groundwater potential can be found in the southern region of the basin near the high Moulouya limit. These areas are characterized by steep slopes with inclinations greater than 40 degrees and high elevations in the Moroccan High Atlas mountain range, where the density of lineaments is less than 0.018 km/km2. Despite this challenging landscape, the methodology employed in this study still managed to produce relevant results for predicting groundwater potential, without relying solely on expert opinions.
Results validation
The results were cross-validated with the specific yield of the aquifer within the study area (Fig. 7). The analysis revealed a robust positive correlation with a coefficient (R2 = 0.79) between areas exhibiting excellent groundwater potential and high specific yield. Conversely, areas with poor potential showed a weakening correlation as their specific yield decreased.
The results of the study showed that 89.5% (86 out of 96 wells) of the wells were situated in areas with very high to high groundwater potential. The flow rate of these wells was observed to vary significantly, ranging from 1 L per second (l/s) for shallow boreholes (less than 100 m) that tap into alluvial aquifers to over 90 l/s for deep boreholes (exceeding 500 m) that tap into the dolomitic limestone of the Jurassic aquifer. These findings are consistent with the findings reported by Bouazza et al. (2013).
The groundwater depth is found to be variable and depends on the local hydrogeological and geological conditions. Factors such as topography, slope, land use, and underlying sediments play a crucial role in determining the groundwater recharge rate and hence the depth of the groundwater. The central part of the basin, characterized by flat topography, low slopes, and bare land use with unconsolidated sediments, is more favorable for groundwater recharge, leading to shallow groundwater depths as seen in the research by Saadi et al. (2021). Conversely, in other areas, particularly in the eastern part of the basin, the groundwater depth is found to be relatively deep and confined, with a slow rate of recharge. These findings highlight the importance of understanding the regional variations in groundwater conditions to make informed decisions about groundwater management and resource utilization.
Groundwater sustainability plans
As with any methodology, our approach involves certain assumptions and simplifications. One of the key assumptions is that the factors considered in our GIS model have equal importance, and their weights defined by the Analytic Hierarchy Process (AHP) remain constant both spatially and temporally. These simplifications may have implications for the accuracy of the results over time and space, as hydrological characteristics can vary significantly from one region to another due to factors such as geology, topography, and climate. Consequently, the methodology may not fully account for this local variability, potentially limiting its relevance in certain specific areas. Moreover, our methodology assigns a significant weight to precipitation (34%), which could pose a limitation in extremely arid and dry regions. While rainfall is the most influential factor in mapping, prompting us to prioritize the protection and proper management of recharge areas, it is essential to consider local conditions and adjust the weightings of factors accordingly.
According to IAEA (2010), the recharge zones of the Moulouya basin are situated in the Beni Snassen and Jbel Hamra mountains, at altitudes ranging between 700 and 1200 m. However, most of the groundwater in the basin originates from recent recharge, as indicated by their tritium and carbon-14 content (IAEA 2010). This highlights the recharge ability of the aquifers while also emphasizing their vulnerability to contamination. To safeguard these crucial recharge areas, the following measures are recommended:
-
Establishment of strict regulations for activities that may potentially pollute the groundwater, such as intensive agriculture, chemical industries, or waste disposal.
-
Implementation of adequate infrastructure for the collection and treatment of rainwater to prevent direct infiltration into groundwater recharge areas.
-
Regular monitoring of groundwater quality and the condition of recharge areas. This enables the rapid identification of potential issues and the implementation of appropriate corrective measures.
Encouraging water conservation and promoting efficient water use practices can reduce the overall demand for groundwater and sustainable practices can foster a culture of responsible water use. Implementing technologies such as drip irrigation and rainwater harvesting can help optimize water use and reduce reliance on groundwater. Raising awareness among local communities, stakeholders, and decision-makers about the importance of sustainable groundwater management is essential. By incorporating these strategies, decision-makers can enhance sustainable groundwater management, protecting the vital recharge areas and ensuring the availability of clean and reliable groundwater resources for present and future generations.
Conclusions
This study focuses on the identification of GWPZ using GIS, AHP, and RS techniques in the Moulouya, one of the principal basins of Morocco. Thematic layers of lithology, rainfall, LU and LC, drainage and lineament density, slope, and distance to rivers were created using conventional data, such as topographic maps and remote sensing data. Also, the weight assigned to individual themes and their reciprocal classes applying the AHP technique. The implementation of all the thematic layers in the GIS model created a potential groundwater map of the study area. According to the GWPZ map, the study area is categorized into five different zones, namely a zone of very high water potential (13,560.59 km2), high (26,135.07 km2), moderate (6692. 22 km2), poor (4669.09 km2) and very poor (60.54 km2). The obtained results were validated by comparing them with the specific yield of the aquifers, yielding a correlation coefficient (R2) of 0.79.
The results of the study demonstrate that AHP-based GIS and remote sensing is a viable approach for groundwater potential mapping, and the generated groundwater potential maps can serve as valuable resources for water resource management decision-makers. This research highlights the importance of conducting comprehensive groundwater evaluations and explorations, which could help minimize the high costs of geological surveys and contribute to the success of future water resource planning.
Future research could explore the applicability of advanced modeling techniques, including machine learning algorithms, artificial neural networks, and fuzzy logic, to further improve the accuracy of groundwater potential mapping. Additionally, future studies could focus on analyzing the temporal variability of groundwater potential in the Moulouya Basin by using historical data and trends coupled with the results of isotopic analyses. Understanding the dynamics of groundwater potential over time will provide valuable insights for developing effective groundwater management strategies.
Data availability
The datasets used and/or analyzed during the current study are available from the corresponding authors (M. Abioui & A.Z. Ekoa Bessa) on reasonable request.
References
Abdou Ali I (2018) Caractérisation des réservoirs aquifères multicouches du bassin des Iullemmeden dans la région de Dosso (sud-ouest Niger): apports de la télédétection, du SIG, de la géophysique et de l’hydrogéochimie. Dissertation, Université Abdou Moumouni de Niamey
Abioui M, Ikirri M, Boutaleb S, Faik F, Wanaim A, Id-Belqas M, Echogdali FZ (2023) GIS for Watershed Characterization and Modeling: example of the Taguenit River (Lakhssas, Morocco). In: Chatterjee U, Pradhan B, Kumar S, Saha S, Zakwan M (eds) Water, land, and forest susceptibility and sustainability: geospatial approaches and modeling. Elsevier, Amsterdam, pp 61–85
Agarwal E, Agarwal R, Garg R, Garg P (2013) Delineation of groundwater potential zone: an AHP/ANP approach. J Earth Syst Sci 122:887–898
Ahamrouni J (1996) Érosion hydrique dans le bassin versant de la Moulouya (Maroc Oriental): recherche des zones sources d'envasement de la retenue du barrage Mohamed V. Dissertation, Université Cheikh Anta Diop
Ahmed M, Aqnouy M, Stitou El Messari J (2021) Sustainability of Morocco’s groundwater resources in response to natural and anthropogenic forces. J Hydrol 603:126866
Ajay Kumar V, Mondal NC, Ahmed S (2020) Identification of groundwater potential zones using RS, GIS and AHP techniques: a case study in a part of Deccan Volcanic Province (DVP), Maharashtra, India. J Indian Soc Remote Sens 48:497–511
Allafta H, Opp C, Patra S (2020) Identification of groundwater potential zones using remote sensing and GIS techniques: a case study of the Shatt Al-Arab Basin. Remote Sens 13(1):112
Allison GB (1988) A review of some of the physical, chemical and isotopic techniques available for estimating groundwater recharge. In: Simmers I (ed) Estimation of natural groundwater recharge. Springer, Dordrecht, pp 49–72
Amrani A (2007) Apport des données couplées d'imagerie satellitaires ETM+ de Landsat 7 et modèle numérique de terrain appliqués à l'étude morphogénétique de la Haute et Moyenne Moulouya (Maroc). Dissertation, Mohammed V University
Aqnouy M, Stitou El Messari JE, Bouadila A, Bouizrou I, Aoulad Mansour MR (2018) Application of hydrological model “ HEC HMS ” in a Mediterranean Watershed (Oued Laou, Northern of Morocco). Int J Innov Appl Stud 24:1773–1781
Aqnouy M, Stitou El Messari JE, Hilal I, Bouadila A, Moreno Navarro JG, Bounab L, Aoulad Mansour MR (2019) Assessment of the SWAT model and the parameters affecting the flow simulation in the watershed of Oued Laou (Northern Morocco). J Ecol Eng 20(4):104–113
Aqnouy M, Stitou El Messari JE, Bouadila A, Morabbi A, Benaabidate L, Al-Djazouli MO (2021) Modeling of continuous and extreme hydrological processes using spatially distributed models Mercedes, Vicair and Vishyr in a Mediterranean Watershed. Ecol Eng Environ Technol 22(1):9–23
Aqnouy M, Ahmed M, Ayele GT, Bouizrou I, Bouadila A, Stitou El Messari JE (2023) Comparison of hydrological platforms in assessing rainfall-runoff behavior in a Mediterranean watershed of Northern Morocco. Water 15(3):447
Arnous MO, El-Rayes AE, Geriesh MH, Ghodeif KO, Al-Oshari FA (2020) Groundwater potentiality mapping of tertiary volcanic aquifer in IBB basin, Yemen by using remote sensing and GIS tools. J Coast Conserv 24:27
Arshad A, Zhang Z, Zhang W, Dilawar A (2020) Mapping favorable groundwater potential recharge zones using a GIS-based analytical hierarchical process and probability frequency ratio model: a case study from an agro-urban region of Pakistan. Geosci Front 11(5):1805–1819
Arulbalaji P, Padmalal D, Sreelash K (2019) GIS and AHP techniques based delineation of groundwater potential zones: a case study from Southern Western Ghats, India. Sci Rep 9(1):2082
Aswathi J, Sajinkumar KS, Rajaneesh A, Oommen T, Bouali EH, Binojkumar RB, Rani VR, Thomas J, Thrivikramji KP, Ajin RS, Abioui M (2022) Furthering the precision of RUSLE soil erosion with PSInSAR data: an innovative model. Geocarto Int 37(27):16108–16131
Benjmel K, Amraoui F, Aydda A, Tahiri A, Yousif M, Pradhan B, Abdelrahman K, Fnais MS, Abioui M (2022) A multidisciplinary approach for groundwater potential mapping in a fractured semi-arid Terrain (Kerdous Inlier, Western Anti-Atlas, Morocco). Water 14(10):1553
Bhagya SB, Sumi AS, Balaji S, Danumah JH, Costache R, Rajaneesh A, Gokul A, Chandrasenan CP, Quevedo RP, Johny A, Sajinkumar KS, Saha S, Ajin RS, Mammen PC, Abdelrahman K, Fnais MS, Abioui M (2023) Landslide susceptibility assessment of a part of the Western Ghats (India) employing the AHP and F-AHP models and comparison with existing susceptibility maps. Land 12(2):468
Biémie J (1992) Contribution à l'étude géologique, hydrogéologique par télédétection des bassins versants subsahéliens du socle précambrien d'Afrique de l’Ouest : Hydrostructurale, hydrodynamique, hydrochimie et isotopie des aquifères discontinus de sillons et aire granitique de la haute Marahoué (Côte d'Ivoire). Dissertation, Université d’Abidjan
Birot P (1963) Plaines et piedmonts du bassin de la Moulouya. Méditerranée 4(2):83–85
Bouadila A, Benaabidate L, Bouizrou I, Aqnouy M (2019) Implementation of distributed hydrological modeling in a semi-arid mediterranean catchment Azzaba, Morocco. J Ecol Eng 20:236–254
Bouadila A, Bouizrou I, Aqnouy M, En-nagre K, El Yousfi Y, Khafouri A, Hilal I, Abdelrahman K, Benaabidate L, Abu-Alam T, Stitou El Messari JE, Abioui M (2023) Streamflow simulation in semiarid data-scarce regions: a comparative study of distributed and lumped models at Aguenza Watershed (Morocco). Water 15(8):1602
Bouazza M, Khattach D, Houari MR, Kaufmann O (2013) Apport du modèle géologique 3D à l’étude de la structure de l’aquifère profond d’Aïn Béni Mathar, Maroc Oriental. Bull Inst Sci 35:53–61
Bouizrou I, Aqnouy M, Bouadila A (2022) Spatio-temporal analysis of trends and variability in precipitation across Morocco : comparative analysis of recent and old non-parametric methods. J Afr Earth Sci 196:104691
Bouizrou I, Bouadila A, Aqnouy M, Gourfi A (2023) Assessment of remotely sensed precipitation products for climatic and hydrological studies in arid to semi-arid data-scarce region, central-western Morocco. Remote Sens Appl Soc Environ 30:100976
Chennouf T, Khattach D, Milhi A, Andrieux P, Keating P (2007) Principales lignes structurales du Maroc nord-oriental: apport de la gravimétrie. CR Geosci 339(6):383–395
Choubin B, Rahmati O, Soleimani F, Alilou H, Moradi E, Alamdari N (2019) Regional groundwater potential analysis using classification and regression trees. In: Pourghasemi HR, Gokceoglu G (eds) Spatial modeling in GIS and R for earth and environmental sciences. Elsevier, Amsterdam, pp 485–498
Chowdhury A, Jha MK, Chowdary VM, Mal BC (2009) Integrated remote sensing and GIS-based approach for assessing groundwater potential in West Medinipur district, West Bengal, India. Int J Remote Sens 30(1):231–250
Dar IA, Sankar K, Dar MA (2011) Deciphering groundwater potential zones in hard rock terrain using geospatial technology. Environ Monit Assess 173:597–610
Dar T, Rai N, Bhat A (2021) Delineation of potential groundwater recharge zones using analytical hierarchy process (AHP). Geol Ecol Landsc 5(4):292–307
Das S, Gupta A, Ghosh S (2017) Exploring groundwater potential zones using MIF technique in a semi-arid region: a case study of Hingoli district, Maharashtra. Spat Inf Res 25:749–756
Das B, Pal S, Malik S, Chakrabortty R (2019) Modeling groundwater potential zones of Puruliya district, West Bengal, India using remote sensing and GIS techniques. Geol Ecol Landsc 3(3):223–237
Echogdali FZ, Boutaleb S, Bendarma A, Saidi ME, Aadraoui M, Abioui M, Ouchchen M, Abdelrahman K, Fnais MS, Sajinkumar KS (2022a) Application of analytical hierarchy process and geophysical method for groundwater potential mapping in the Tata Basin, Morocco. Water 14(15):2393
Echogdali FZ, Boutaleb S, Taia S, Ouchchen M, Id-Belqas M, Kpan RB, Abioui M, Aswathi J, Sajinkumar KS (2022b) Assessment of soil erosion risk in a semi-arid climate watershed using SWAT model: case of Tata basin, South-East of Morocco. Appl Water Sci 12(6):137
El Yousfi Y, Himi M, El Ouarghi H, Elgettafi M, Benyoussef S, Gueddari H, Aqnouy M, Salhi A, Alitane A (2022) Hydrogeochemical and statistical approach to characterize groundwater salinity in the Ghiss-Nekkor coastal aquifers in the Al Hoceima province, Morocco. Groundw Sustain Dev 19:100818
El Yousfi Y, Himi M, El Ouarghi H, Aqnouy M, Benyoussef S, Gueddari H, Ait Hmeid H, Alitane A, Chaibi M, Zahid M, Essahlaoui N, Hitouri S, Essahlaoui A, Elaaraj A (2023a) Assessment and prediction of the water quality index for the groundwater of the Ghiss-Nekkor (Al Hoceima, Northeastern Morocco). Sustainability 15(1):402
El Yousfi Y, Himi M, El Ouarghi H, Aqnouy M, Benyoussef S, Gueddari H, Ait Hmeid H, Alitane A, Chahban M, Bourdan S, Riouchi O, Ngadi H, Tahiri A (2023b) GIS preprocessing for rainfall-runoff modeling using HEC-HMS in Nekkor watershed (Al-Hoceima, Northern Morocco). E3S Web Conf 364:01005
Elbadaoui K, Mansour S, Ikirri M, Abdelrahman K, Abu-Alam T, Abioui M (2023) Evaluating the accuracy of EPM and PAP/RAC in Predicting soil erosion in mountainous watersheds: an analysis of the Toudgha River Basin in Southeast Morocco. Land 12(4):837
El-Baz F, Himida I (1995) Groundwater potential of the Sinai Peninsula, Egypt. Project Summary, AID, Cairo
Fashae O, Tijani MN, Talabi AO, Adedeji O (2014) Delineation of groundwater potential zones in the crystalline basement terrain of SW-Nigeria: an integrated GIS and remote sensing approach. Appl Water Sci 4:19–38
Ferozu RM, Jahan CS, Arefin R, Mazumder QH (2019) Groundwater potentiality study in drought prone Barind Tract, NW Bangladesh using remote sensing and GIS. Groundw Sustain Dev 8:205–215
Ghosh P, Bandyopadhyay S, Jana N (2016) Mapping of groundwater potential zones in hard rock terrain using geoinformatics: a case of Kumari watershed in western part of West Bengal. Model Earth Syst Environ 2:1
Gnanachandrasamy G, Yongzhang Z, Bagyaraj M, Venkatramanan S, Ramkumar T, Shugong W (2018) Remote sensing and GIS based groundwater potential zone mapping in Ariyalur District, Tamil Nadu. J Geol Soc India 92:484–490
Guo Q, Yang Y, Han Y, Li J, Wang X (2019) Assessment of surface–groundwater interactions using hydrochemical and isotopic techniques in a coalmine watershed, NW China. Environ Earth Sci 78:91
Hajkowicz S, Higgins A (2008) A comparison of multiple criteria analysis techniques for water resource management. Eur J Oper Res 184(1):255–265
HCP (2021) Monograph of the Eastern Region. High Commission for Planning of Morocco, Rabat
Heywood I, Oliver J, Tomlinson S (1995) Building an exploratory multi-criteria modelling environment for spatial decision support. In: Fisher P (ed) Innovations in GIS2. Taylor & Francis, London, pp 127–136
Hilal I, Stitou El Messari JE, Moreno Navarro JG, Aoulad Mansour MR, Hassani Zerrouk M (2018) Application du modèle DKPR pour la cartographie de la vulnérabilité des eaux de surface à la contamination: cas du barrage 9 avril 1947 (Maroc septentrional). J Water Sci 31:75–86
Hussein AA, Govindu V, Nigusse A (2017) Evaluation of groundwater potential using geospatial techniques. Appl Water Sci 7:2447–2461
Hutti B, Nijagunappa R (2011) Identification of groundwater potential zone using Geoinformatics in Ghataprabha basin, North Karnataka, India. Int J Geomat Geosci 2:91–109
IAEA (2010) Atlas of isotope hydrology: Morocco. International Atomic Energy Agency, Vienna
Ikirri M, Boutaleb S, Ibraheem IM, Abioui M, Echogdali FZ, Abdelrahman K, Id-Belqas M, Abu-Alam T, El Ayady H, Essoussi S, Faik F (2023) Delineation of groundwater potential area using an AHP, remote sensing, and GIS techniques in the Ifni Basin, Western Anti-Atlas, Morocco. Water 5(7):1436
Jha MK, Chowdhury A, Chowdary VM, Peiffer S (2007) Groundwater management and development by integrated remote sensing and geographic information systems: prospects and constraints. Water Resourc Manage 21:427–467
Kaliraj S, Chandrasekar N, Magesh N (2014) Identification of potential groundwater recharge zones in Vaigai upper basin, Tamil Nadu, using GIS-based analytical hierarchical process (AHP) technique. Arab J Geosci 7:1385–1401
Kanagaraj G, Suganthi S, Elango L, Magesh NS (2019) Assessment of groundwater potential zones in Vellore district, Tamil Nadu, India using geospatial techniques. Earth Sci Inform 12:211–223
Karimoune S, Ozer A, Erpicum M (1990) Les modèles éoliens de la région de Zinder (Niger méridional), étude de photogéomorphologie, note préliminaire. In: Lafrance P, Dubois JM (eds) Apports de la télédétection à la lutte contre la sécheresse. Aupelf-Uref, Paris, pp 145–161
Khaddari A, Jari A, Chakiri S, El Hadi H, Labriki A, Hajaj S, El Harti A, Goumghar L, Abioui M (2023) A comparative analysis of analytical hierarchy process and fuzzy logic modeling in flood susceptibility mapping in the Assaka Watershed, Morocco. J Ecol Eng 24(8):62–83
Khan A, Govil H, Taloor AK, Kumar G (2020) Identification of artificial groundwater recharge sites in parts of Yamuna river basin India based on remote sensing and geographical information system. Groundw Sustain Dev 11:100415
Kolli M, Opp C, Groll M (2020) Mapping of potential groundwater recharge zones in the Kolleru Lake catchment, India, by using remote sensing and GIS techniques. Nat Resour 11:127–145
Kostyuchenko Y, Artemenko I, Abioui M, Benssaou M (2022) Global and regional climatic modeling. In: Cheng Q, McKinley J, Agterberg F (eds) Encyclopedia of mathematical geosciences. Encyclopedia of Earth Sciences Series. Springer, Cham
Kumar T, Gautam AK, Kumar T (2014) Appraising the accuracy of GIS-based multi-criteria decision-making technique for delineation of groundwater potential zones. Water Resour Manage 28:4449–4466
Labbassi K (1991) Evolution tectono-sédimentaire de la série méso-cénozoïque de la moyenne Moulouya: Lithostratigraphie, tectonique, décompaction et calcul de la subsidence. Dissertation, Université de Pau et des pays de l'Adour
Magesh NS, Chandrasekar N, Soundranayagam JP (2012) Delineation of groundwater potential zones in Theni district, Tamil Nadu, using remote sensing, GIS and MIF techniques. Geosci Front 3(2):189–196
Maity D, Mandal S (2017) Identification of groundwater potential zones of the Kumari river basin, India: an RS & GIS based semi-quantitative approach. Environ Dev Sustain 21:1013–1034
Malczewski J (1999) GIS and multicriteria decision analysis. Wiley, New York
Mohammadi B, Ranjbar SF, Ajabshirchi Y (2018) Application of dynamic model to predict some inside environment variables in a semi-solar greenhouse. Inf Process Agric 5(2):279–288
Mukherjee P, Singh CK, Mukherjee S (2012) Delineation of groundwater potential zones in arid region of India—A remote sensing and GIS approach. Water Resour Manage 26:2643–2672
Nasir M, Khan S, Zahid H, Khan A (2018) Delineation of groundwater potential zones using GIS and multi influence factor (MIF) techniques: a study of district Swat, Khyber Pakhtunkhwa, Pakistan. Environ Earth Sci 77:367
Nasir MJ, Khan S, Ayaz T, Khan AZ, Ahmad W, Lei M (2021) An integrated geospatial multi-influencing factor approach to delineate and identify groundwater potential zones in Kabul Province, Afghanistan. Environ Earth Sci 80(13):453
Nasloubi M (1993) Genèse et modélisation des minéralisations plombifères de la Haute Moulouya. Maîtrise en Sciences de la Terre, Université du Québec à Montréal
Nhamo L, Ebrahim GY, Mabhaudhi T, Mpandeli S, Magombeyi M, Chitakira M, Magidi J, Sibanda M (2020) An assessment of groundwater use in irrigated agriculture using multi-spectral remote sensing. Phys Chem Earth 115:102810
Nouayti A, Khattach D, Hilali M, Nouayti N (2019) Mapping potential areas for groundwater storage in the High Guir Basin (Morocco): contribution of remote sensing and geographic information system. J Groundw Sci Eng 7(4):309–322
Patra S, Mishra P, Mahapatra S (2018) Delineation of groundwater potential zone for sustainable development: a case study from Ganga Alluvial Plain covering Hooghly district of India using remote sensing, geographic information system and analytic hierarchy process. J Clean Prod 172:2485–2502
Pinto D, Shrestha S, Babel M, Ninsawat S (2017) Delineation of groundwater potential zones in the Comoro watershed, Timor Leste using GIS, remote sensing and analytic hierarchy process (AHP) technique. Appl Water Sci 7:503–519
Rajasekhar M, Sudarsana Raju G, Sreenivasulu Y, Siddi Raju R (2019) Delineation of groundwater potential zones in semi-arid region of Jilledubanderu river basin, Anantapur District, Andhra Pradesh, India using fuzzy logic, AHP and integrated fuzzy-AHP approaches. HydroResearch 2:97–108
Riad S (2003) Typologie et analyse hydrologique des eaux superficielles à partir de quelques bassins versants représentatifs du Maroc. Dissertation, Université Lille1-Sciences et Technologies
Saadi O, Nouayti N, Nouayti A, Dimane F, Elhairechi K (2021) Application of remote sensing data and geographic information system for identifying potential areas of groundwater storage in middle Moulouya Basin of Morocco. Groundw Sustain Dev 14:100639
Saaty T (1989) Group decision making and the AHP. In: Golden BL, Wasil EA, Harker PT (eds) The analytic hierarchy process. Springer, Berlin, Heidelberg, pp 59–67
Satapathy I, Syed TH (2015) Characterization of groundwater potential and artificial recharge sites in Bokaro District, Jharkhand (India), using remote sensing and GIS-based techniques. Environ Earth Sci 74:4215–4232
Shaban A, Khawlie M, Abdallah C (2006) Use of remote sensing and GIS to determine recharge potential zone: the case of Occidental Lebanon. Hydrogeol J 14:433–443
Shaban A (2003) Etude de l’hydrogéologie du Liban occidental: Utilisation de la télédétection. Dissertation, Université de Bordeaux
Shao Z, Huq ME, Cai B, Altan O, Li Y (2020) Integrated remote sensing and GIS approach using Fuzzy-AHP to delineate and identify groundwater potential zones in semi-arid Shanxi Province, China. Environ Model Softw 134:104868
Siddi Raju R, Sudarsana Raju G, Rajasekhar M (2019) Identification of groundwater potential zones in Mandavi River basin, Andhra Pradesh, India using remote sensing, GIS and MIF techniques. HydroResearch 2:1–11
Siddik MS, Tulip SS, Rahman A, Islam MN, Haghighi AT, Mustafa SMT (2022) The impact of land use and land cover change on groundwater recharge in northwestern Bangladesh. J Environ Manage 315:115130
Singaraja C, Chidambaram S, Anandhan P, Prasanna MV, Thivya C, Thilagavathi R (2015) A study on the status of saltwater intrusion in the coastal hard rock aquifer of South India. Environ Dev Sustain 17:443–475
Sinha A, Nikhil S, Ajin RS, Danumah JH, Saha S, Costache R, Rajaneesh A, Sajinkumar KS, Amrutha K, Johny A, Marzook F, Mammen PC, Abdelrahman K, Fnais MS, Abioui M (2023) Wildfire risk zone mapping in contrasting climatic conditions: an approach employing AHP and F-AHP models. Fire 6(2):44
Teeuw RM (1994) Groundwater exploration using remote sensing and a low-cost geographic information system. Hydrogeol J 3(3):21–30
Tükel M, Tunçbilek E, Komerska A, Keskin GA, Arıcı M (2021) Reclassification of climatic zones for building thermal regulations based on thermoeconomic analysis: a case study of Turkey. Energy Build 246:111121
Turc L (1955) Le bilan d’eau des sols: relations entre les précipitations, l’évaporation et l’écoulement. Journées de l’Hydraulique 3(1):36–44
Wind Y, Saaty TL (1980) Marketing applications of the analytic hierarchy process. Manag Sci 26(7):641–658
Wong JKW, Li H (2007) Application of the analytic hierarchy process (AHP) in multicriteria analysis of the selection of intelligent building systems. Build Environ 43(1):108–125
Xin-feng L, Jiu-chuan W, Yan-gang S (2012) Single factor analysis on sandstone aquifer’s water abundance in the coal seam’s roof, Shandong. Coal Sci Technol 5:128–130
Yeh H, Cheng Y, Lin H, Lee C (2016) Mapping groundwater recharge potential zone using a GIS approach in Hualian River, Taiwan. Sustain Environ Res 26(1):33–43
Acknowledgements
The authors would like to thank the Moroccan Water Research and Planning Department (DRPE) and the Moulouya Hydraulic Basin Agency (ABHM) for their support and availability in the field. Deep thanks and gratitude to the Researchers Supporting Project number (RSP2024R351), King Saud University, Riyadh, Saudi Arabia, for funding this research article. In addition, Prof. M. Abioui is thankful to the support of national funds through Fundação para a Ciência e Tecnologia, I. P (FCT), under the projects UIDB/04292/2020, UIDP/04292/2020, granted to MARE, and LA/P/0069/2020, granted to the Associate Laboratory ARNET. Finally, the authors are thankful to both the anonymous reviewers and Prof. Enrico Drioli (Editor-in-Chief, Applied Water Science) for suggestions and comments.
Funding
Open access funding provided by University of Lausanne.
Author information
Authors and Affiliations
Corresponding authors
Ethics declarations
Conflict of interest
The authors declare no conflict of interest.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
About this article
Cite this article
Hilal, I., Qurtobi, M., Saadi, R. et al. Integrating remote sensing, GIS-based, and AHP techniques to delineate groundwater potential zones in the Moulouya Basin, North-East Morocco. Appl Water Sci 14, 122 (2024). https://doi.org/10.1007/s13201-024-02175-6
Received:
Accepted:
Published:
DOI: https://doi.org/10.1007/s13201-024-02175-6