Abstract: The present invention provides a long-term streamflow forecast method and system based on process-data synergic drive.

Abstract: A flood risk prediction method includes: collecting basic meteorological hydrological data of a basin by using a data collection and storage box; calibrating a basin hydrological model and a machine learning model; obtaining a meteorological simulation series under M groups of climate change scenarios and driving the basin hydrological model and the machine learning model to simulate a basin hydrological process under a future scenario; establishing a water and heat coupling balance equation of the basin to obtain annual average underlying surface feature parameters of the basin; extracting feature values of a flood duration and a flood volume and with the feature parameters as co-variates, establishing a joint probability distribution function; obtaining a joint return period of the flood duration and the flood volume; based on a dataset of the shared socioeconomic pathway, deriving a social economic exposure degree of future flood risk increase.