Abstract:Error and uncertainty can be found in every stage of travel and land use modeling. Data errors and uncertainties in socioeconomic forecasts are largely ignored in many model calibration and validation exercises. Uncertainty in these models is passed from submodel to submodel and across model years thus producing a propagation of error over time. The practice of reporting the outputs of these models' as point estimates ignores uncertainty and can portray a level of accuracy far beyond the models' actual abilities. The purpose of this study is to interject uncertainty into the inputs of a fully integrated land use and transportation forecasting model, monitor the impacts of uncertainty on model's outputs, and determine which sources of uncertainty have the largest impact on these outputs. Of the several sources of uncertainty examined here, the commercial trip generation rates have the largest impact on model outputs.