To consider the contribution of snowmelt in flood forecast, this paper presents an integrated model, which combines a rigorous snow model with a distributed run-off model, based on unstructured triangular meshes. Using precipitation, air temperature and wind speed as input data, the integrated model can continuously estimate temporal-spatial variation of both snow depth and amount of snowmelt and subsequently forecast river flow caused by snowmelt. The result of a long-term simulation of past floods showed a good match with observations. It is evinced that consideration of snowmelt in a flood forecast can help avoid incorrect prediction. This includes overestimation in the snow accumulation season and/or underestimation in the snowmelt season caused by using precipitation directly as the input data of the run-off model. A real-time flood forecasting system has been established for the Hii River basin, Japan, by using the model. This system now operates uninterruptedly to make a forecast 6 h ahead, with an interval of 10 min.