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Runoff projections are subject to uncertainties related to model structure and parameters. This study aims to analyze uncertainties in longterm runoff estimations from an empirical (Budyko framework) and a conceptual hydrological model (MHD-INPE). Results indicate that both MHD-INPE and Budyko estimations tend to overestimate long-term runoff during years of recurring droughts. Pareto front solutions in MHDINPE exhibited small uncertainties in long-term runoff estimations regarding parameter calibration (bias between 5 and 7%); differences were observed in low (bellow 5% variation) and high (bellow 10% variation) daily runoff. Related to model structure uncertainties, both models follow similar patterns and performance for a qualitative analysis. Budykos future projections tend to exceed MHD-INPEs during high precipitation estimates, where at 2000 mm yearly precipitation the estimated runoff from Budyko tends to be 100 mm greater than the hydrological model. Under arid conditions Budyko tends to estimate smaller runoff than MHD-INPE due to variations in soil moisture and water storage not properly represented in Budykos parameter. Although uncertainties were identified related to model complexity and calibrated parameters, higher uncertainties were identified as related to the climate models. Therefore, the Budyko method is a viable alternative for first-order analysis of long-term impacts.