The Huaihe River Basin in Anhui Province is prone to flooding and frequent disasters.The flood-prone areas include the low-lying areas along the Huai River，most parts of the Huaibei Plain，and the low-lying areas of Huainan tributaries，which are prone to flood disasters during the flood season.Therefore，studying the local flood process forecasting is of great significance.This study established a daily rainfall quantification algorithm based on public weather forecast data and support vector machine regression.At the same time，a flood simulation model for the polder area was constructed using a water tank model and the principle of runoff generation.The two were combined to form a flood process forecasting model.The results indicate that both the rainfall quantification algorithm and the waterlogging simulation model have good simulation accuracy.The average absolute error of simulating the water storage depth in paddy fields is 2.8 mm，with a correlation coefficient of 0.88.The average error of simulating the water depth in ponds is 4.1 mm，with a correlation coefficient of 0.8.The waterlogging process prediction model shows that the rainfall distribution with a late peak is the most harmful to the polder area.The research results can provide reference and guidance for estimating the degree of flooding in the polder area and managing flood control.