Predicting Soil Erosion Using RUSLE Model in Duhok Governorate, Kurdistan Region of Iraq

Soil erosion is a main cause of land degradation, adveresly impacting soil health, soil fertility, and soil carbon. This study used the revised universal soil loss equation (RUSLE) model and geoinformatics tools to predict soil erosion rates in the Duhok governorate, located in the Kurdistan Region of Iraq (KRI). The RUSLE model integrates several to predict annual soil loss: soil erodibility factor (K), rainfall erosivity factor (R), slope (L), slope steepness factor (S), land use/cover factor (C), and conservation methods (P). Information layers for these variables were created using ArcGIS 10.3, showing the extent of soil erosion. Additionally, we identified and prioritized erosion hotspots to implement conservation practices. The results showed that approximately 78% of the study area experienced very low and low levels of soil erosion, whereas only 4 and 7% were subject to high and very high erosion rates, respectively. The findings also emphasized the significance of slope and land-use interactions in accelerating soil erosion, particularly in agricultural areas characterized by steep slopes.