## 4 Conclusions  
The MS region is experiencing severe droughts, leading to failed cereal crops, food scarcity, epidemics, and large-scale migration. Obtaining precise drought data is crucial to mitigating these impacts, as they enable the accurate assessment of drought risks and the evaluation of the region's vulnerability. This study utilized five statistical metrics to assess the efficacy of the CHIRPS satellite rainfall products for drought monitoring. Comparing the monthly CHIRPS data with the observation data indicated a statistically significant correlation in the plains and the coastal zones (\(r\) up to 0.9, \(R^{2}\) up to 0.82). However, discrepancies were noted, with the CHIRPS tending to overestimate rainfall in the plains and the coastal zones, while underestimating it in the High Atlas foothills and the mountainous regions. Despite these discrepancies, the CHIRPS exhibited promising capability for reliable SPEI estimation and drought monitoring, particularly in semi-arid, low-altitude areas with limited observed data. The spatio-temporal distribution of the SPEI at different timescales (3, 6, and 12 months) displayed consistency between the CHIRPS and observed data in identifying drought events. However, variations in the intensity of wet and dry conditions arose due to terrain complexity and low station density. Notably, the CHIRPS proved valuable in regions with sparse ground-based measurements by providing comprehensive coverage, though terrain complexity, potential measurement errors, and algorithm limitations, especially in the mountainous regions, may affect its accuracy. The analysis of the cereal yield (SYRS) trends between 2003 and 2018 in the different provinces revealed diverse patterns, primarily due to climatic factors such as recurrent droughts. Some provinces experienced notable fluctuations, including exceptionally high yields in some years, while others suffered losses. The correlation analysis between the SYRS and the CHIRPS-based SPEI reveals a significant impact of drought on agricultural productivity. Strong correlations, particularly with SPEI-6 in April and SPEI-12 in June, highlight the critical importance of cumulative annual rainfall, especially during the later growing season, for securing adequate cereal yields. Climate change-induced drought intensification challenges food security, underscoring the need for tailored approaches to mitigate drought impacts and ensure sustainable agricultural practices. Improving the accuracy of the CHIRPS precipitation data, especially in mountainous regions, is crucial for future drought assessments. Integrating additional remote sensing datasets could provide valuable insights for effective drought mitigation and agricultural planning in response to climate change. The following supporting information can be downloaded at: [[https://www.mdpi.com/article/10.3390/app15041865/s1](https://www.mdpi.com/article/10.3390/app15041865/s1)]([https://www.mdpi.com/article/10.3390/app15041865/s1](https://www.mdpi.com/article/10.3390/app15041865/s1)), Figure S1: Scatter plots comparing SPEI-1, SPEI-3, SPEI-6, and SPEI-12 using monthly rainfall data from rain gauge measurements and CHIRPS estimates; Figure S2: Spatial distribution of monthly drought index SPEI-6 in June for each year from 1981 to 2018 in MS region; Figure S3: Spatial distribution of monthly drought index SPEI-12 in December for each year from 1981 to 2018 in MS region; Figure S4: Monthly correlation between SYRS and SPEI at different timescales for each province in MS region (2003-2018). Table S1: Statistical comparison of SPEI (1, 3, 6, and 12 months) calculated by CHIRPS and rain gauge data. Conceptualization, C.E., K.R.C. and A.H.; methodology, C.E. and A.H.; software, C.E. ; validation, C.E., K.R.C., I.K. and A.H.; formal analysis, C.E., K.R.C., I.K. and A.H.; investigation, C.E. ; resources, C.E. and A.H.; data curation, C.E. ; writing--original draft preparation, C.E. ; writing--review and editing, C.E., K.R.C., I.K. and A.H.; visualization, C.E., K.R.C., I.K.