Ensemble flood forecasting based on a coupled atmospheric-hydrological modeling system with data assimilation

In order to prolong the lead time of the flood forecasts, numerical weather prediction (NWP) models are more and more widely used to provide high-resolution rainfall forecasts as the feed of the rainfall-runoff model for flood forecasts. In this study, a coupled atmospheric-hydrological modeling system is constructed by integrating the weather research forecasting (WRF) model and the Hebei rainfall-runoff model together with the WRF three-dimensional variational (3DVar) data assimilation module. Four storm events from two mountainous catchments in Jin-Jing-Ji Region of Northern China are selected to evaluate the performance of the coupled system for real-time flood forecasting. Five different combinations of physical parameterizations are adopted with the WRF model to provide a forecast rainfall ensemble. Conventional observations and radar reflectivity data are assimilated by the 3DVar data assimilation module to update the initial and lateral boundary conditions of the WRF model in order to provide more reliable rainfall forecasts. The results show that the atmospheric-hydrological modeling system can provide satisfactory flood forecasts, especially for the storm events with relatively even rainfall distribution in the spatial dimension. Appropriate data assimilation show positive effect on improving the accumulation process of the rainfall which therefore helps effectively increase the forecast accuracy of the coupled modeling system.