The US Army Engineering Research Development Center (ERDC) uses a modified form of the Revised Universal Soil Loss Equation (RUSLE) to estimate spatially explicit rates of soil erosion by water across military training facilities. One modification involves the RUSLE support practice factor (P factor), which is used to account for the effect of disturbance by human activities on erosion rates. Since disturbance from off-road military vehicular traffic moving through complex landscapes varies spatially, a spatially explicit nonlinear regression model (disturbance model) is used to predict the distribution of P factor values across a training facility. This research analyzes the uncertainty in this model's disturbance predictions for the Fort Riley training facility in order to determine both the spatial distribution of prediction uncertainty and the contribution of different error sources to that uncertainty. This analysis shows that the model parameters associated with Soil-Speed, Thematic Mapper imagery, and land cover were the greatest source of prediction uncertainty, and Soil-Speed was very likely the most responsible explanatory variable to the spatial distribution of prediction uncertainty. In areas where uncertainty is not too high, mapping error, especially error from slope map, was another major uncertainty source. These results indicate that to improve the prediction model and slope map would produce the greatest reductions in disturbance prediction uncertainty. KEYWORDS: Support practice factor, disturbance, off-road vehicle traffic, uncertainty analysis, error budget, RUSLE.