摘要
A coupled hydro-meteorological modeling system is established for real-time flood forecast and flood alert over the Huaihe River Basin in China. The system consists of the mesoscale atmospheric model MC2 (Canadian Mesoscale Compressible Community) that is one-way coupled to the Chinese Xinanjiang distributed hydrological model, a grid-based flow routing model, and a module for acquiring real-time gauge precipitation. The system had been successfully tested in a hindcast mode using 1998 and 2003 flood cases in the basin, and has been running daily in a real-time mode for the summers of 2005 and 2006 over the Wangjiaba sub-basin of the Huaihe River Basin. The MC2 precipitation combined with gauge values is used to drive the Xinanjiang model for hydrograph prediction and production of flood alert map. The performance of the system is illustrated through an examination of real-time flood forecasts for the severe flood case of July 4―15, 2005 over the sub-basin, which was the first and largest flood event encountered to date. The 96-h forecasts of MC2 precipitation are first evaluated using observations from 41 rain gauges over the sub-basin. The forecast hydrograph is then validated with observations at the Wangjiaba outlet of the sub-basin. MC2 precipitation generally compares well with gauge values. The flood peak was predicted well in both timing and intensity in the 96-hour forecast using the combined gauge-MC2 precipitation. The real-time flood alert map can spatially display the propagation of forecast floods over the sub-basin. Our forecast hydrograph was used as opera-tional guidance by the Bureau of Hydrograph, Ministry of Water Resources. Such guidance has been proven very useful for the Office of State Flood Control and Drought Relief Headquarters in operational decision making for flood management. The encouraging results demonstrate the potential of using mesoscale atmospheric model precipitation for real-time flood forecast, which can result in a longer lead time compared to traditional methods.
A coupled hydro-meteorological modeling system is established for real-time flood forecast and flood alert over the Huaihe River Basin in China. The system consists of the mesoscale atmospheric model MC2 (Canadian Mesoscale Compressible Community) that is one-way coupled to the Chinese Xinanjiang distributed hydrological model, a grid-based flow routing model, and a module for acquiring real-time gauge precipitation. The system had been successfully tested in a hindcast mode using 1998 and 2003 flood cases in the basin, and has been running daily in a real-time mode for the summers of 2005 and 2006 over the Wangjiaba sub-basin of the Huaihe River Basin. The MC2 precipitation combined with gauge values is used to drive the Xinanjiang model for hydrograph prediction and production of flood alert map. The performance of the system is illustrated through an examination of real-time flood forecasts for the severe flood case of July 4–15, 2005 over the sub-basin, which was the first and largest flood event encountered to date. The 96-h forecasts of MC2 precipitation are first evaluated using observations from 41 rain gauges over the sub-basin. The forecast hydrograph is then validated with observations at the Wangjiaba outlet of the sub-basin. MC2 precipitation generally compares well with gauge values. The flood peak was predicted well in both timing and intensity in the 96-hour forecast using the combined gauge-MC2 precipitation. The real-time flood alert map can spatially display the propagation of forecast floods over the sub-basin. Our forecast hydrograph was used as operational guidance by the Bureau of Hydrograph, Ministry of Water Resources. Such guidance has been proven very useful for the Office of State Flood Control and Drought Relief Headquarters in operational decision making for flood management. The encouraging results demonstrate the potential of using mesoscale atmospheric model precipitation for real-time flood forecast, which can result in a longer lead time compared to traditional methods.
基金
the National Natural Science Foundation of China (Grant No. 40371023)
National "948" project (Grant Nos. 200317 and 200758)
National Key Technology R&D Program (Grant No. 2006BAC05B02)
