Focusing on the low accuracy and insufficient foreseen period of traditional runoff forecast, this study proposed a runoff forecast method based on the similarity of rainfall and runoff. Data mining was used to search for the similar historical rainfall and runoff process, and the most likely runoff hydrograph in the later period was predicted. To prolong the runoff foreseen period to seven days, the real-time rainfall forecast information was inputted into the model and three rolling forecast schemes were proposed. The forecast models could be adaptively switched according to real-time rainfall conditions to further improve the forecast accuracy. The application in Dadu River showed that the Nash coefficients of forecasting the third day and seventh day were greater than 0. 9 and 0. 8, and the average relative errors were less than 10% and 15%, respectively. The research is of great significance to improve the forecast accuracy, extend the foreseen period, and promote the management and operation level of the reservoir group.