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Meteo-hydrological forecasting models are an effective way to generate high-resolution gridded rainfall data for water source research and flood forecast. The quality of rainfall data in terms of both intensity and distribution is very important for establishing a reliable meteo-hydrological forecasting model. To improve the accuracy of rainfall data, the successive correction method is introduced to correct the bias of rainfall, and a meteo-hydrological forecasting model based on WRF and WRF-Hydro is applied for streamflow forecast over the Zhanghe River catchment in China. The performance of WRF rainfall is compared with the China Meteorological Administration Multi-source Precipitation Analysis System (CMPAS), and the simulated streamflow from the model is further studied. It shows that the corrected WRF rainfall is more similar to the CMPAS in both temporal and spatial distribution than the original WRF rainfall. By contrast, the statistical metrics of the corrected WRF rainfall are better. When the corrected WRF rainfall is used to drive the WRF-Hydro model, the simulated streamflow of most events is significantly improved in both hydrographs and volume than that of using the original WRF rainfall. Among the studied events, the largest improvement of the NSE is from -0.68 to 0.67. It proves that correcting the bias of WRF rainfall with the successive correction method can greatly improve the performance of streamflow forecast. In general, the WRF / WRF-Hydro meteo-hydrological forecasting model based on the successive correction method has the potential to provide better streamflow forecast in the Zhanghe River catchment. 相似文献
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以漳河流域为研究区域,以CMORPH卫星-地面自动站-雷达三源降水融合数据和ERA5再分析降水资料为WRF-Hydro模式的输入,进行径流模拟,对比分析模拟径流与实测径流的差异,探讨基于两种降水数据的WRF-Hydro模式在漳河流域的径流模拟效果。结果表明:三源降水融合数据的径流模拟效果较优,纳什系数均达到0.7以上,模拟径流与实测径流过程吻合较好;采用三源降水融合数据和ERA5再分析降水资料率定WRF-Hydro模式,以ERA5再分析降水资料为输入,径流模拟结果都不佳;总体而言,三源降水融合数据与WRF-Hydro模式耦合能够较好地模拟漳河流域径流过程。 相似文献
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目前多数快速更新循环同化系统在各分析时刻常使用固定的背景场误差协方差。为在快速更新循环同化系统中采用日变化的背景场误差协方差,基于RMAPS-ST系统分析了其夏季和冬季日变化背景场误差协方差特征,并进行了同化及预报对比试验。结果表明,该系统夏、冬两季的背景场误差协方差均呈现出明显的日变化特征,且夜间各变量(U、V、T、RH)的误差标准差与特征值均大于日间,反映模式系统夜间的预报误差大于日间;而夏季各变量误差标准差和特征值大于冬季,也说明系统在夏季的模式预报误差比冬季大;连续3 d的循环同化试验初步表明,采用日变化背景场误差协方差可以提高同化及预报效果。 相似文献
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基于WRF模式,采用4层嵌套方案,选取3种积云参数化方案和7种微物理方案组成21种组合,对清江流域2016—2018年6—10月6次典型降雨事件进行数值预报,结合CMORPH卫星-地面自动站-雷达三源融合降水产品,采用TS评分和FSS评分,分析不同分辨率和云微物理方案的降雨预报效果;基于较优组合方案的WRF模式与WRF-Hydro水文模式耦合进行径流模拟,分析WRF模式在水文模拟中的应用效果。结果表明:3 km和1 km分辨率对降雨中心位置及强度预报的差别不大,对降雨落区都有较好的预报能力;在积云参数化方案中,KF方案和BMJ方案的降雨预报效果优于GF方案;在微物理方案中,WSM3、WSM5、WSM6、Thompson方案的预报结果与融合数据有较好的一致性;基于较优组合方案BMJ_WSM3,将WRF模式与WRF-Hydro模式耦合,耦合模式能较好地模拟洪水过程,径流模拟相关系数都在0.67以上,且NSE最高可达0.79。 相似文献
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