To address the difficulty of the traditional infiltration-runoff model based on the infiltration curve deduction method in flexibly and efficiently predicting the total runoff generation from permeable asphalt throughout an entire clogging cycle, a modified fractional loss(FRAC) model was developed by integrally deforming the FRAC model, introducing the permeable asphalt induced initial rainfall loss, and adjusting the runoff conversion ratio parameter (Cr), and the modified model was applied to predict the runoff generation from permeable asphalt throughout the entire clogging cycle. The initial rainfall loss was quantified as a function of the infiltration rate, and its empirical fitting equation was established. Furthermore, a functional relationship between the modified parameter Cr, infiltration rate, and rainfall intensity was constructed, enabling dynamic parameter adjustment with variations in rainfall intensity and clogging degree of permeable asphalt. Measured runoff data were used to validate the models, and the results indicate that the FRAC model overestimates the runoff generation from permeable asphalt throughout the entire clogging cycle, with an average absolute error (MAE) of 15.87 mm, a root mean square error (RMSE) of 16.77 mm, and a Nash Sutcliffe efficiency (NSE) coefficient of -1.06 for runoff generation prediction. In contrast, the modified FRAC model achieves a substantially improved performance, with an MAE of 0.36 mm, an RMSE of 0.67 mm, and an NSE of 0.97. The modified FRAC model demonstrates high accuracy in predicting the runoff generation from permeable asphalt under various clogging degrees, and can effectively captures the actual total runoff generation.