Soil erosion is one of the most common types of land degradation. To provide useful information for proper management, quantitative soil erosion evaluation and identification of effective factors are needed. However, rare studies have been reported on spatial modeling of soil erosion in connection with affective factors to prioritize the locality and the type of erosion control measures Hence, the aim of this study was to (1) assess erosion-prone areas in the Talar Watershed, Iran, using the Revised Universal Soil Loss Equation (RUSLE) model, and (2) investigate the relationship between soil erosion variability and land-use changes. Toward that, the ordinary least squares (OLS), geographically weighted regression (GWR) models, and Principal Component Analysis (PCA) were used to analyze spatial relationships between soil erosion, and land-use, and the RUSLE factors. The results of the OLS and GWR models indicated these relationships are spatially non-stationary and GWR models had a good predictive performance rather than OLS with lower Akaike's Information Criterion (from 254.31 to 276.81 in OLS, and from 247.87 to 269.42 in GWR) and higher adjusted R2 values (from 0.12 to 0.54 in OLS, and from 0.36 to 0.66 in GWR). Among the aforementioned variables, LS factor, P factor, forest, and irrigated land were the most effective variables in GWR models. The results of PCA showed PC1 and PC2 explained 66.2 % of the variation in soil erosion concerning land-use and the RUSLE factors. These results provided appropriate references for managers and experts in the proper planning of the study watershed.