Due to its location in an arid climate and the rapid expansion of urban land use, Baghdad Province has experienced an increasing trend in soil erosion in recent years. This study aimed to investigate the impact of drought and land-use changes on soil erosion in the province. To assess drought conditions, the Standardized Precipitation Index (SPI) was utilized based on precipitation data from meteorological stations. Additionally, the RUSLE model was employed within a Geographic Information System (GIS) environment to estimate soil erosion rates by integrating factors such as rainfall intensity (R), soil erodibility (K), slope length and steepness (LS), vegetation cover (C), and management practices (P). Land-use changes were also extracted and analyzed using Landsat 5 and 9 satellite imagery and the Maximum Likelihood Classification (MLC) method within the ENVI software. The research findings indicated that persistent drought and reduced precipitation during the study period led to a decline in vegetation density and increased soil susceptibility to erosion. Furthermore, urban expansion, the spread of barren lands, and the reduction of agricultural areas and vegetation cover have intensified soil erosion processes across various parts of the province. The findings of this study demonstrated that the combined effects of drought and land-use changes play a decisive role in increasing soil erosion in Baghdad Province, and that the adoption of management strategies—such as preserving vegetation cover, controlling urban expansion, and sustainably managing water resources—can be effective in reducing erosion severity and improving the region's environmental conditions.In Baghdad Province, the reduction of vegetation cover and the increase in surface runoff—driven primarily by land-use changes and urban expansion—have played a major role in exacerbating erosion. This trend must be seriously considered in future planning for soil conservation and natural resource management in the province. Analyses reveal significant shifts in land-use patterns between 2010 and 2025, characterized by the expansion of agricultural and residential areas, a decline in dense rangelands, and an increase in barren land. Drought conditions in the province were assessed using climatic data—including monthly and daily precipitation—and the Standardized Precipitation Index (SPI). Soil erosion was calculated using the RUSLE model, incorporating data on rainfall intensity, soil type, slope, vegetation cover, and management practices; spatial predictions of erosion rates were generated by integrating five key factors: rainfall intensity (R), soil erodibility (K), slope length and steepness (LS), vegetation cover (C), and management practices (P). The R-factor (rainfall erosivity) was determined based on rainfall intensity and the erosive energy of precipitation events. Slope and flow accumulation layers were generated from the Digital Elevation Model (DEM), and the LS factor was derived by applying the established equations to these layers. The C factor (representing vegetation cover) was extracted from satellite imagery and land-use data, with the NDVI calculated accordingly. Following data preparation—ensuring uniform resolution and a consistent coordinate system across raster layers—soil erosion (A) was calculated for each cell using the RUSLE formula. Land-use changes were analyzed using Landsat satellite imagery and the Maximum Likelihood Classification (MLC) algorithm within the ENVI software environment. The MLC algorithm calculated the probability of each pixel belonging to specific classes, enabling pixel classification; land-use changes were subsequently simulated by comparing classified images from different time periods. To validate the generated layer, sample points were collected via Google Earth, and the Kappa coefficient was calculated for each map. Following data preparation and processing, statistical and spatial analyses were conducted to examine the correlations and interrelationships among drought, soil erosion, and land-use changes. Specialized GIS and ENVI software were employed for data processing, while R software was used for statistical analysis to ensure the reliability of the results. These land-use changes are directly or indirectly linked to increased soil erosion and heightened environmental vulnerability.An analysis of SPI index maps for the years 2010 and 2025 reveals that drought conditions in the region shifted during this period. While relatively more balanced moisture conditions prevailed across large parts of the region in 2010, the decline in SPI values by 2025—particularly in the eastern and southeastern sectors—indicates an intensification of drought conditions. The spatial pattern of these changes shows a concentration of drought cores and an expansion of areas experiencing drier conditions. The map illustrating differences in soil erosion values indicates that changes between 2010 and 2015 occurred in a heterogeneous, patchy manner across Baghdad Province. Given that the province is situated on an alluvial plain with a limited elevation range (13 to 69 meters) and a predominant slope of less than 1 degree the topographic factor (LS) remains relatively uniform and shows little variation at the provincial scale. Furthermore, the soil erodibility factor (K) does not undergo structural changes over short periods; the observed spatial variation and discontinuity in soil erosion across the province are primarily attributable to the low gradient of the terrain. Consequently, the observed fluctuations in the final erosion rate (A) stem mainly from changes in dynamic factors—specifically the rainfall factor (R) and, above all, the land cover and management factors (C and P). The concentration of increased erosion in certain agricultural areas and around urban developments indicates that changes in the condition of the soil surface—and the resulting decline in its protective effectiveness—have been the primary drivers of increased erosion during this period.