Rainfall is one of the important parameters for evaluating flood hazard risk. Cambodia is a vulnerable country to extreme rainfall where the number of rain gauges over the country is limited. Therefore, the possibilities of applying rainfall products from satellite observation and rainfall forecasting models are crucial for the country. The purpose of this research is to evaluate the detecting accuracy of the rainfall-based Weather Research Forecasting (WRF) model and TRMM rainfall products by comparing with observed rainfall during heavy rainfall for different topography over Cambodia. The categorical statistic is used to calibrate the rainfall from the WRF model with observed rainfall from 23 stations over Cambodia on selected heavy rainfall dates of 15, 17, and 19 September 2019. Cambodia experienced floods along the Tonle Sap River and the Mekong Basin by the triggered heavy rainfall. The results show that the detecting accuracy of days 15, 17, and 19 from TRMM rainfall matched with observed rainfall are 55%, 71%, and 63%, respectively. The average detecting accuracy of mountainous is 65% whereas plains are 63.33%. The average detecting accuracy of coastal and Tonle Sap is 53.66% and 63%, respectively. Moreover, the detecting accuracy of days 15, 17, and 19 forecasts from the WRF model compared with observed rainfall are 41%, 69%, and 63%, respectively. The average detecting accuracy of mountainous, plains, coastal, and Tonle Sap are 52%, 55.66%, 52.33%, and 65.66%, individually. The forecast rainfall from the WRF model and TRMM could detect the rainfall. They are therefore should be used in the areas that lack rainfall stations in Cambodia.