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Ensemble flood forecasting based on ensemble NWP and the GMKHM distributed hydrological model

机译:基于合奏NWP和GMKHM分布式水文模型的合奏洪水预报

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The incorporation of numerical weather predictions (NWP) into a flood forecasting system can increase forecast lead times from a few hours to a few days. A single NWP forecast from a single forecast centre, however, is insufficient as it involves considerable non-predictable uncertainties and lead to a high number of false alarms. The availability of global ensemble numerical weather prediction systems through the THORPEX Interactive Grand Global Ensemble’ (TIGGE) offers a new opportunity for flood forecast. The GMKHM distributed hydrological model, which is based on a mixed runoff generation model and overland flow routing model based on kinematic wave theory, and the topographical information of each grid cell extracted from the Digital Elevation Model (DEM), is coupled with ensemble weather predictions based on the TIGGE database (CMC, CMA, ECWMF, UKMO, NCEP) for flood forecast. This paper presents a case study using the coupled flood forecasting model on the Xixian catchment (a drainage area of 8826 km2) located in Henan province, China. A probabilistic discharge is provided as the end product of flood forecast. Results show that the association of the GMKHM model and the TIGGE database gives a promising tool for the anticipation of flood events several days ahead,, comparable with that driven by raingauge observation.
机译:将数值天气预报(NWP)纳入洪水预测系统,可以从几小时到几天增加预测转速时间。然而,从单个预测中心的单一NWP预测不足,因为它涉及相当大的不可预测的不确定性并导致大量的误报。通过Thorpex Interactive Grand Glase Ensemble'(Tigge)的全球合奏数值天气预报系统的可用性为洪水预报提供了新的机会。基于基于运动波理论的混合径流生成模型和陆地流量路由模型的GMKHM分布式水文模型,以及从数字高程模型(DEM)中提取的每个网格单元的地形信息,与集合天气预报相耦合基于TIGGE数据库(CMC,CMA,ECWMF,UKMO,NCEP)进行洪水预测。本文介绍了在中国河南省Xixian集水区(8826 KM2)耦合洪水预测模型的案例研究。提供概率放电作为洪水预报的最终产品。结果表明,GMKHM型号和TIGGE数据库的关联为未来几天的洪水事件预期提供了一个有前途的工具,可与由RaInjge观察的驱动相比。

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