## 4 Discussion  
Our study was based on monthly rainfall data recorded at 35 available stations and ranging from 1970 to 2019. These stations are concentrated in the western part of the basin and along the main rivers. In contrast, the eastern part contains more empty and uninhabited land whose main economic activity is pastoralism [67], which makes the installation of measuring stations in this region less important. The variability of rainfall in our watershed as an arid environment, in the context of global climate change, is of primary importance [68]. Indeed, this importance comes from several points. The first relates to the strong correlation between the rate of rainfall and agricultural yield in the study area and the fact that the Moulouya watershed suffers from chronic water stress and strong water resource demand [22; 23; 50; 52]. The second point is justified by the objective of flood risk management, as the floods of the Moulouya wadi and its tributaries threaten several cities, including Guercif and Taouririt [53]. The third point relates to the silting of dams by the strong erosive activity in the basin, including water erosion transported during the period of floods. Therefore, rain is a driving force of water erosion [69; 70]. The choice of the most efficient method to study this variability poses a challenge [28; 71]. The wavelet transform method used in this work was found internationally to be an effective one, as shown by the work of [34; 35; 42; 72]. In the study of rainfall variability based on this last method, we distinguished five frequency bands of rainfall oscillation with periods of 1 to 2 years, 2 to 4 years, 4 to 8 years, 8 to 16 years, and 16 to 32 years. The duration of the oscillations with significant power at these frequencies varies from one station to another depending on its geographical location, altitude, and exposure. These results are close to those obtained by [PERSON] et al. [34]. In general, the results of our study show a very remarkable spatiotemporal irregularity regarding precipitation. This characterizes the Mediterranean climate and, more particularly, that of the southern part, as shown in the work of [8; 73; 74]. On the other hand, only the first band, the 1- to 2-year period, provides a clear grouping between the stations within the study basin. Indeed, the WPS figures allow us to distinguish two groups of stations, i.e., two blocks of data. In addition to the study of rainfall variability, spectral analysis, or wavelet transformation, has also shown its power and robustness in the regionalization of statistical series by clusters [75], which groups stations with the same form of rainfall variability and similar rainfall patterns [76]. This technique allowed us to find two different climate zones. The first has a winter rainfall regime and is located west and northwest of the Middle Atlas mountain range. This geographical situation makes the region exposed to disturbances from the north and west. A second, located in the heart of the Moulouya watershed in arid territory, has a spring regime and is located east or southeast of the peaks of the Middle Atlas. Our results regarding regionalization are consistent with those of [PERSON] et al. [27], who worked on the homogenization of rainfall data in the Fez-Meknes region, and of [PERSON] et al. [11], who conducted a study on monthly rainfall trends in the northern Middle Atlas. Both studies used Climatol for gap filling and to homogenize the monthly station precipitation data. In addition, these last two works also show that there is a trend towards an increase in annual rainfall in the part of Moulouya located in the shelter of the Middle Atlas. This increase was explained by a significant increase in autumn rainfall, a result also mentioned by [PERSON] [77], despite the small number of stations used in his work compared to the size of the study area. A similar result was reported by [PERSON] et al. [78].