The research focuses on analyzing historical climate variability over the period 1982-2022, as well as future projections of climate change over the period 2025-2099, with regard to the Souss-Massa watershed, a semi-arid region with high dependency on agricultural activities. Precipitation and temperature data were collected annually from five meteorological stations, Agadir, Amaghouz, Amsoul, Aoulouz, and Taroudant, in order to analyze long-term climatic trends and predict possible scenarios of climate change. A trend analysis was carried out using a combination of the Mann-Kendall test and Sen's slope estimator. The findings of this study indicate that there is an increase in mean annual temperature that is statistically significant (p < 0.05) across all stations, ranging from +0.28 degrees C per decade at Agadir, which is located along the coastal region of Morocco, to as high as +0.45 degrees C per decade at Taroudant, which is located inland. Conversely, the precipitation trend is decreasing and not statistically significant (p > 0.05). For projecting future climatic conditions, we used the Statistical Down-Scaling Model (SDSM v4.2.9) with global climate models using outputs from CanESM2 under two emission scenarios, namely RCP 4.5 and RCP8.5. The calibration period (1982-2001) and the validation period (2002-2022) were satisfactory, as indicated by the high values of the coefficients of determination (R-2 > 0.6) for temperature and moderate values (R-2 = 0.5-0.6) for precipitation. Projections indicate an increase in temperature, with the mean temperature change ranging from +4.8 degrees C and +8.7 degrees C by 2099 depending on the station's location. Projected precipitation decreases are found under both scenarios, but with stronger decreases under RCP8.5, especially along the coastal regions, with decreases as large as -53.8% at Agadir. However, the precipitation projections have to be used with caution due to the limitations associated with the downscaling methods and the use of a single global climate model. All the projections indicate a trend towards arid conditions, emphasizing the need for adaptive water resources management and improving the ensemble models for climate projections.