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Ensemble flood forecasting based on a coupled atmospheric-hydrological modeling system with data assimilation

机译：基于带数据同化的大气水文耦合建模系统的组合洪水预报

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摘要

In order to prolong the lead time of the flood forecasts, numerical weather prediction (NWP) models are more and more widely used to provide high-resolution rainfall forecasts as the feed of the rainfall-runoff model for flood forecasts. In this study, a coupled atmospheric-hydrological modeling system is constructed by integrating the weather research forecasting (WRF) model and the Hebei rainfall-runoff model together with the WRF three-dimensional variational (3DVar) data assimilation module. Four storm events from two mountainous catchments in Jin-Jing-Ji Region of Northern China are selected to evaluate the performance of the coupled system for real-time flood forecasting. Five different combinations of physical parameterizations are adopted with the WRF model to provide a forecast rainfall ensemble. Conventional observations and radar reflectivity data are assimilated by the 3DVar data assimilation module to update the initial and lateral boundary conditions of the WRF model in order to provide more reliable rainfall forecasts. The results show that the atmospheric-hydrological modeling system can provide satisfactory flood forecasts, especially for the storm events with relatively even rainfall distribution in the spatial dimension. Appropriate data assimilation show positive effect on improving the accumulation process of the rainfall which therefore helps effectively increase the forecast accuracy of the coupled modeling system.
机译：为了延长洪水预报的提前期，数值天气预报（NWP）模型被越来越广泛地用于提供高分辨率降雨预报，作为洪水径流模型的预报源。在这项研究中，通过将气象研究预报（WRF）模型和河北降雨径流模型与WRF三维变分（3DVar）数据同化模块集成在一起，构建了一个耦合的大气水文学模型系统。选择了来自中国北方晋津冀地区两个山区集水区的四个风暴事件，以评估耦合系统的实时洪水预报性能。 WRF模型采用了五种不同的物理参数设置组合，以提供预报降雨集合。 3DVar数据同化模块将常规观测和雷达反射率数据同化，以更新WRF模型的初始和横向边界条件，以便提供更可靠的降雨预报。结果表明，大气水文模拟系统可以提供令人满意的洪水预报，特别是对于暴雨事件，在空间尺度上降雨分布相对均匀。适当的数据同化对改善降雨的累积过程具有积极作用，因此有助于有效地提高耦合模型系统的预报精度。

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  • 来源
    《Atmospheric research》 |2019年第8期|127-137|共11页
  • 作者

    Tian Jiyang; Liu Jia; Yan Denghua; Ding Liuqian; Li Chuanzhe;

  • 作者单位

    China Inst Water Resources & Hydropower Res, State Key Lab Simulat & Regulat Water Cycle River, 1 Fuxing Rd, Beijing 100038, Peoples R China;

    China Inst Water Resources & Hydropower Res, State Key Lab Simulat & Regulat Water Cycle River, 1 Fuxing Rd, Beijing 100038, Peoples R China;

    China Inst Water Resources & Hydropower Res, State Key Lab Simulat & Regulat Water Cycle River, 1 Fuxing Rd, Beijing 100038, Peoples R China;

    China Inst Water Resources & Hydropower Res, State Key Lab Simulat & Regulat Water Cycle River, 1 Fuxing Rd, Beijing 100038, Peoples R China;

    China Inst Water Resources & Hydropower Res, State Key Lab Simulat & Regulat Water Cycle River, 1 Fuxing Rd, Beijing 100038, Peoples R China;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Numerical weather prediction; Data assimilation; Rainfall-runoff model; Atmospheric-hydrological modeling system; Ensemble flood forecasting;

    机译：数值天气预报数据同化降雨径流模型大气水文模拟系统组合洪水预报;

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