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Water availability is a key factor in territorial sustainable development. Moreover, groundwater constitutes the survival element of human life and ecosystems in arid oasis areas. Therefore, groundwater potential (GWP) identification represents a crucial step for its management and sustainable development. This study aimed to map the GWP using ten algorithms, i.e., shallow models comprising: multilayer perceptron, k-nearest neighbor, decision tree, and support vector machine algorithms; hybrid models comprising: voting, random forest, adaptive boosting, gradient boosting (GraB), and extreme gradient boosting; and the deep learning neural network. The GWP inventory map was prepared using 884 binary data, with “1” indicating a high GWP and “0” indicating an extremely low GWP. Twenty-three GWP-influencing factors have been classified into numerical data using the frequency ration method. Afterwards, they were selected based on their importance and multi-collinearity tests. The predicted GWP maps show that, on average, only 11% of the total area was predicted as a very high GWP zone and 17% and 51% were estimated as low and very low GWP zones, respectively. The performance analyses demonstrate that the applied algorithms have satisfied the validation standards for both training and validation tests with an average area under curve of 0.89 for the receiver operating characteristic. Furthermore, the models’ prioritization has selected the GraB model as the outperforming algorithm for GWP mapping. This study provides decision support tools for sustainable development in an oasis area.

The Ferkla Oasis is situated in the Rheris watershed in the southeast of Morocco, between the eastern Anti-Atlas in the south (Ougnat inlier) and the Central High Atlas in the north. This oasis is characterized by a semi-desert climate with strong continental influence, marked by low and irregular rainfall as well as high temperatures. This oasis has experienced several agricultural extensions outside the traditional oasis, resulting in overpressure on the groundwater as evidenced by the dramatic decline of its piezometric level, which has engendered an ecological and socio-economic crisis. In these critical conditions, a groundwater flow model was developed to evaluate the impact of climate change and anthropogenic activities on the hydrodynamic behavior of the aquifer. The results obtained confirmed that the region is increasingly threatened by groundwater resource scarcity. Indeed, simulations of the watershed in both a permanent and transient state were generated for the years of 1993 through 2021. These simulations have shown a piezometric level decline, as well as a deficit in the water balance, as well as a deficit in the water balance. This situation is caused by climate effects, particularly frequent droughts, and the overexploitation of the groundwater resources, especially in the agricultural extension areas outside the traditional oasis. The study demonstrates that the oasis faces a serious crisis and may further deteriorate until it disappears within a few years. Therefore, integrated, collective and participatory measures are recommended. The model provides important results that will aid in groundwater resource management in this region.

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