Integrating Rainfall Erosivity with RUSLE for Spatial Soil Erosion Assessment in an Arid Watershed: Wadi Numan, Saudi Arabia

Soil erosion in arid mountainous watersheds is driven by intense rainfall, steep terrain, and sparse vegetation. This study presents a high-resolution spatial assessment of soil erosion in the 683 km2 Wadi Numan watershed, western Saudi Arabia, using the Revised Universal Soil Loss Equation (RUSLE) integrated with GIS, remote sensing, and global soil datasets. The watershed was subdivided into 12 sub-basins (SBs) to quantify the spatial variability of estimated soil loss and identify erosion-prone areas requiring priority management. Daily rainfall data were disaggregated using the SCS Type II 24-h synthetic storm distribution to derive sub-daily intensity profiles, from which storm kinetic energy (E) and maximum 30-min rainfall intensity (I30) were estimated. Soil erodibility (K) was estimated from SoilGrids 2.0 sand, silt, clay, and organic carbon data using the Environmental Policy Integrated Climate (EPIC) equation. The topographic factor (LS) was derived from a 10 m KACST digital elevation model, while the cover-management factor (C) was calculated from Sentinel-2 NDVI. Because no significant soil conservation practices were identified within the watershed, the support-practice factor (P) was assigned a value of 1.0. The RUSLE-estimated mean annual soil loss was 19.24 t ha−1 yr−1, with sub-basin averages ranging from 15.73 to 23.55 t ha−1 yr−1. SB-7 exhibited the highest estimated soil loss (23.55 t ha−1 yr−1), where high rainfall erosivity and steep topography combined to intensify soil loss. Areas with severe estimated soil loss (>30 t ha−1 yr−1) accounted for approximately 12% of the watershed, while severe classes occupied 40.9% of SB-7, the highest proportion among the 12 sub-basins. Rainfall erosivity exhibited the greatest spatial variability among the RUSLE factors and was the dominant factor associated with differences in estimated soil loss among the sub-basins, with steep topography further amplifying its effect. In contrast, the K-factor showed limited variation across the watershed (0.031–0.035 t·h MJ−1 mm−1), indicating relatively homogeneous soil erodibility. Because measured soil-loss data were unavailable, the RUSLE estimates could not be independently validated against field-based soil-loss measurements. The approach provides a practical basis for spatial soil erosion assessment and watershed prioritization in arid mountainous environments.