| Citation: | Zhao Linna, Liu Ying, Dang Haofei, et al. The progress on application of ensemble prediction to flood forecasting. J Appl Meteor Sci, 2014, 25(6): 641-653.
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Hydrological Ensemble Prediction is a forming and developing branch of hydrology. Its development can be roughly divided into two stages. The first stage is the longer term streamflow predictions stage from 1970 to the end of the 20th Century, and the second stage is to learn the concept of the numerical weather forecast applied to hydrological ensemble prediction at the beginning of the 21st Century. Compared with the single deterministic prediction meteorological, ensemble numerical forecasting can describe the uncertainly quantitatively. In recent ten years, the application of meteorological ensemble numerical forecasting to hydrological ensemble prediction on the warning of flood forecasting attaches great importance.In addition to single ensemble system, multiple ensemble system is gradually applied to hydrological ensemble forecast, even in some small basins. To study potential benefits of using the TIGGE database in early flood warning, an atmospheric-hydrologic-hydraulic coupled cascade system driven by TIGGE ensemble forecasts is set up. Some hydrological ensemble prediction systems use high resolution ECMWF-EPS or limited area EPS as weather forecasts as initial and boundary conditions. Over the past decade, many studies show that forecasts based on hydrological ensemble prediction systems not only can add accuracy but also increase the warning lead time. The European Flood Alert System and the Advanced Hydrologic Prediction Services of NOAA realize real-time prediction in flood forecast, but there are still some problems, such as large amount of calculation and massive data to handle.The various pre-process and post-process of ensemble forecasts of techniques are in the stage of exploration and verification. Besides, there are a great deal of challenges and difficulties in understanding how to make flood warning decisions based on probabilistic forecasts better.
Fig. 1 Ensemble forecast discharge comparison of three EPSs and the Grand ensemble at Wangjiaba Station from 23 July to 3 August in 2008(from Reference [36])
Fig. 2 The flow chart of application of ensemble prediction system to warning of inundation
Fig. 3 Brier skill scores (BSS) of post-processing ensemble forecasts of cumulative precipitation for different lead times (1-14 days) and different seasons (including all seasons) in two sub-basins of the Huai River Basin (from Reference [28])
Fig. 4 Evaluation of post-processing of different simulation (from Reference [87])
(a) mean value, (b) root mean square error
Table 1 Examples of operational and pre-operational flood forecasting systems routinely using ensemble weather predictions as inputs (from Reference [40])
| 预报服务机构及项目 | 集合数值预报输入场 |
| 欧盟联合研究中心的欧洲洪水预警系统 (EFAS) | ECMWF，COSMO-LEPS (Consortium for Small-Scale Modelling-Limited-area Ensemble Prediction System) |
| 佐治亚理工学院 (孟加拉国项目) | ECMWF |
| 芬兰水文局 | ECMWF |
| 瑞典水文气象局 | ECMWF |
| 美国国家海洋大气管理局先进水文预报系统 (AHPS) | NOAA |
| 概率水文和大气洪水事件模拟的中尺度高山计划示范 (瑞士阿尔卑斯山地区) | COSMO-LEPS |
| 匈牙利布达佩斯水资源研究所 | ECMWF |
| 荷兰水运局 | ECMWF, COSMO-LEPS |
| 比利时皇家气象研究所 | ECMWF |
| 比利时佛兰德环境署 | ECMWF |
| 法国气象局 | ECMWF，Arpege EPS |
| 奥地利蒂洛尔州萨尔茨堡市土地委员会 | ECMWF和Aladin集成模式 |
| 巴伐利亚洪水预报中心 | COSMO-LEPS |
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