中文摘要：

建立基于集合预报的淮河具有行蓄洪区流域洪水预报及早期预警模型。在洪水预报中引入数值天气预报以延长洪水预报的预见期。集合预报采用多模式和多分析集合预报技术，考虑初始场的不确定性和模式的不确定性，避免“单一”确定性数值天气预报结果易存在的预报误区。THORPEX项目支撑的THORPEX Interactive Grand Global Ensemble（TIGGE）集合预报目的是建立全球交互式预报系统。本文以淮河流域为试验流域，以TIGGE集合预报（加拿大气象中心（简称CMC，集合成员数为15个）、欧洲中期天气预报中心（简称ECMWF，集合成员数为51个）、英国气象局（简称UKMO，集合成员数为24个）、美国国家环境预测中心（简称NCEP，集合成员数为15个））驱动构建的水文与水力学相结合的具有行蓄洪区流域洪水预报模型以达延长洪水预报的预见期，新安江模型用于降雨径流计算、一维水动力学模型用于河道洪水演算，实现洪水预报及早期预警。为了进行比较，同时采用地面雨量计观测降水驱动构建的洪水预报模型，对2007和2008年淮河汛期洪水进行检验。结果表明，基于TIGGE集合预报驱动的洪水预报预见期延长了72-120h，证明了TIGGE集合预报可以应用于洪水预报及早期预警。

英文摘要：

An ensemble flood forecasting model, based on the THORPEX Interactive Grand Global Ensemble （TIGGE） ensemble weather predictions was developed for flood forecast and early flood warning of Huaihe River, with the effects of flood diversion and retarding areas taken into account. The combination of numerical weather predictions （NWP） with flood forecasting system can increase the forecast lead time. A single NWP forecast, however, is insufficient as it involves considerable non-predictable uncertainties and can lead to a lot of false or missed warnings. Weather forecasts using ensemble predictions implemented on catchment hydrology can provide significantly improved flood forecast and early flood warning. In this paper, the upper reaches of the Huaihe River, upstream of the Lutaizi Hydrological Station, was taken as a test case. The hydrologic-hydraulic coupled model was applied for flood forecasting driven by ensemble weather predictions based on the TIGGE database （CMC 15members, ECWMF 51members, UKMO 24member, NCEP 15members） in the period of 2007 flood seasons. The Xinanjiang model was used for the hydrological rainfall-runoff modeling. One-dimension hydraulic model was applied for channel flood routing. A probabilistic discharge and flood inundation forecast was provided as the end product to study the potential benefits of using the TIGGE ensemble forecasts. The results demonstrated satisfactory flood forecasting with clear signals of probability of floods up to 72-120 hours in advance, and showed that TIGGE ensemble forecasts is a promising tool to early flood warning inundation, comparable with that based on rain gauge observation.