The combination of Multi-Criteria Decision-Making (MCDM) and morphometric parameters for prioritizing the erodibility of sub-watersheds in the Ouljet Es Soltane basin (North of Morocco).

Preserving water and soil resources ranks among the top priorities outlined in the national water strategy. Indeed, the integrated management of water resources in vulnerable territories, particularly in Morocco, requires a deep knowledge of the hydrological functioning and use of water resources in these regions. The diverse hydroclimatic and morphological features within the Ouljet Es Soltane watershed, which is a sub-basin of the extensive Oued Sebou watershed, present significant challenges in managing its water and soil resources. Identifying areas susceptible to soil erosion is crucial for implementing preventive measures in the Ouljet Es Soltane basin and ensuring its sustainable development. Morphometric analysis plays an important role in the effective management and sustainable utilization of the basin's resources. This study used four MCDM models, including the CF (Compound Factor), VIKOR (VIseKriterijumska Optimizacija I Kompromisno Resenje), TOPSIS (Technique for Order Preference by Similarity to Ideal Solution), and SAW (Simple Additive Weighing), to prioritize 20 sub-watersheds of the Ouljet Es Soltane watershed. Based on the sub-watershed prioritization results obtained from the VIKOR, TOPSIS, and SAW models, sub-watershed 16 achieved scores of 0, 0.59, and 0.8, respectively, positioning it as the first rank. These findings highlight that sub-watershed 16 exhibits a high susceptibility to erosion and is classified as one of the most vulnerable areas in terms of erosion risk. Based on the results obtained from the VIKOR, TOPSIS, and SAW models, the susceptibility of the sub-watersheds to erosion can be classified into four categories: low, moderate, high, and very high. On the other hand, the CF model only has two categories: low and moderate susceptibility. Overall, the findings suggest that morphometric parameters are highly effective in identifying areas at risk of erosion. Furthermore, the VIKOR, TOPSIS, and SAW methods exhibit greater predictive accuracy compared to the CF model. The comparison of these models involved the use of Spearman correlation coefficient test (SCCT). The findings of this study can provide valuable insights for making informed decisions in developing an effective framework for soil erosion control strategies.