A coupled atmospheric-hydrologic-hydraulic ensemble flood forecasting model, driven by The Observing
System Research and Predictability Experiment (THORPEX) Interactive Grand Global Ensemble (TIGGE)
data, has been developed for flood forecasting over the Huaihe River. The incorporation of numerical weather
prediction (NWP) information into flood forecasting systems may increase forecast lead time from a few
hours to a few days. A single NWP model forecast from a single forecast center, however, is insufficient
as it involves considerable non-predictable uncertainties and leads to a high number of false alarms. The
availability of global ensemble NWP systems through TIGGE offers a new opportunity for flood forecast.
The Xinanjiang model used for hydrological rainfall-runoff modeling and the one-dimensional unsteady
flow model applied to channel flood routing are coupled with ensemble weather predictions based on the
TIGGE data from the Canadian Meteorological Centre (CMC), the European Centre for Medium-Range
Weather Forecasts (ECMWF), the UK Met Office (UKMO), and the US National Centers for Environmental
Prediction (NCEP). The developed ensemble flood forecasting model is applied to flood forecasting of the
2007 flood season as a test case. The test case is chosen over the upper reaches of the Huaihe River above
Lutaizi station with flood diversion and retarding areas. The input flood discharge hydrograph from the
main channel to the flood diversion area is estimated with the fixed split ratio of the main channel discharge.
The flood flow inside the flood retarding area is calculated as a reservoir with the water balance method.
The Muskingum method is used for flood routing in the flood diversion area. A probabilistic discharge and
flood inundation forecast is provided as the end product to study the potential benefits of using the TIGGE
ensemble forecasts. The results demonstrate satisfactory flood forecasting with clear signals of probability
of floods up to a few days in advance, and show that TIGGE ensemble forecast data are a promising tool
for forecasting of flood inundation, comparable with that driven by raingauge observations.