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基于积雪数据的HBV模型改进及应用

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大渡河流域内站点分布较少,历史观测数据不足,给该地区的融雪径流预报带来困难.基于欧洲中期天气预报中心提供的最新一代高分辨率陆面再分析数据集ERA5-Land,将积雪覆盖率和积雪平均深度引入度日因子雪量计算公式中,对HBV模型的积融雪模块进行改进,以提升融雪径流计算的可靠性.以大渡河上游为研究对象,选取1961-2018年的水文气象资料对模型进行率定和验证,并以2019年为例进行试预报研究.结果表明,通过引入ERA5-Land再分析数据,以及对积融雪模块进行改进,发挥了其在模拟积融雪上的优势,有效提升了融雪径流预报精度,对大渡河流域具有适用性.研究成果可为稀缺资料地区融雪径流模拟预报提供经验.
Improvement and Application of HBV Model Based on Snow Data
The insufficient rain gauges and historical observational data bring difficulties to snowmelt runoff forecast in the Dadu River Basin.Based on the high-resolution ERA5-Land reanalysis dataset,snow cover fraction and average snow depth were intro-duced into the snowmelt model to improve the snowmelt routine of the HBV hydrological model,so as to enhance the reliability of simulating snowmelt runoff.Taking the upper reaches of the Dadu River as the study area,hydro-meteorological data from 1961 to 2018 were selected for model calibration and validation,and 2019 for trial forecasting.The results demonstrate that by in-corporating ERA5-Land reanalysis data and improving the snowmelt module,the advantages of simulating snow accumulation and ablation are fully utilized,which effectively enhances the accuracy of forecasting snowmelt runoff,showing the applicability of this approach in the data-scarce Dadu River Basin.This study could provide references of snowmelt runoff simulation and forecasting to regions with limited hydrological data.

HBV modelhydrological forecastERA5-Landaverage snow depthsnow cover fractionDadu river basin

俞炜博、梁忠民

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河海大学水文水资源学院,江苏南京 210098

HBV模型 水文预报 ERA5-Land 积雪平均深度 积雪覆盖率 大渡河流域

2024

水文
水利部水文局 水利部水利信息中心

水文

CSTPCD北大核心
影响因子:0.742
ISSN:1000-0852
年,卷(期):2024.44(1)
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