Satellite-based analysis of precipitation across algeria’s hydrographic watersheds (1983–2022) and their relationship with climate indices

Effective dam planning and water management in Algeria depend on detailed monthly precipitation data at the watershed scale. Rainfed agriculture dominates the country, making rainfall patterns critical for food security. High spatial and temporal variability, combined with limited data, challenges accurate climate trend analysis and impact assessment. This study analyzes precipitation in 17 Algerian watersheds from 1983 to 2022 using PERSIANN, ERA5-Land, and CHIRPS datasets. Monthly and annual precipitation volumes were calculated to assess spatiotemporal variations. Spearman correlation analyses were conducted with large-scale climate indices, while the Modified Mann–Kendall test was applied to detect long-term trends in precipitation. The results show notable differences in precipitation among watersheds. The Sahara watershed contributed the largest share of the total national precipitation volume, representing 50.5% according to PERSIANN (with the remaining 49.5% distributed among the other 16 watersheds), 36.2% according to ERA5-Land (63.8% for the others), and 48.9% according to CHIRPS (51.1% for the others), despite its low average annual precipitation (52.9 mm, 27.9 mm, 47.0 mm respectively). The Algiers and Constantine coastal watersheds received the highest average precipitation (480.1–610.9 mm and 538.9–765.9 mm). The Cheliff (16.5–17.0 billion m 3 , 354.2–375.7 mm) and Chott Melrhir (10.0–13.3 billion m 3 , 187.0–386.6 mm) showed moderate variability. The trend analysis of monthly precipitation volumes using PERSIANN, ERA5-Land, and CHIRPS datasets revealed similarities between CHIRPS and ERA5-Land but notable differences with PERSIANN. Significant positive trends were observed in April and August for several watersheds, particularly in the Sahara. Conversely, January and December showed decreasing precipitation trends, although these were mostly not statistically significant across the watersheds. Correlation analyses with large-scale climate indices highlight the dominant role of the NAO and MOI in winter precipitation variability, AMO’s positive influence on spring rainfall, and generally weaker impacts from SOI and EA, emphasizing that basin-scale precipitation dynamics are strongly influenced by broader climatic teleconnections, which should be considered in long-term planning and water resource modeling.