To overcome the drawbacks faced by the traditional manual calibration of hydrological models, this study employs an adaptive differential evolution (DE) algorithm for automatic calibration of Variable Infiltration Capacity (VIC) hydrological model. In the DE algorithm, proper tuning of its control parameters is laborious and generally needs a great amount of time and resources. Therefore, a self-adaptive scheme is presented to enhance the efficacy of the basic DE. The proposed automatic parameter estimation scheme is applied for a case study and evaluated its performance using standard performance measures of coefficient of correlation (R2), Nash–Sutcliffe coefficient (NSE), percent bias (PBIAS), and index of agreement (IoA). The findings from the study revealed that the adaptive DE was successful to optimize the unknown parameters of the VIC model accurately, which signified that the automatic calibration scheme is a credible alternative to the manual approach.