Abstract: Flood disasters are highly sudden and develop rapidly, posing significant threats to people′s lives and properties safety.Rainfall is a disaster-causing factor for floods, and the accuracy of rainfall data is of great significance for flood control and disaster reduction.Focusing on rainfall monitoring and forecasting technology, we summarized the current state of rain gauge observations, weather radar rainfall estimation and forecasting, numerical weather prediction, and satellite remote sensing inversion.By analyzing the application of spatiotemporal downscaling methods and multi-source data fusion technology in rainfall monitoring and forecasting, we reveal their effectiveness in improving the accuracy of both the “quantity” and “type” of rainfall data.Research indicates that significant progress has been made in rainfall monitoring and forecasting technology.However, challenges remain in complex terrains, such as mountainous and urban environments, where resolution is limited and accuracy and timeliness are insufficient.Multi-source data fusion can improve the accuracy of rainfall data, spatiotemporal coverage, and prediction accuracy.Therefore, optimizing algorithm models and integrating multi-source data from “space-sky-ground” to create high-resolution forecasts is a future research direction.