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首页> 外文期刊>Journal of hydro-environment research >A new method for estimation of spatially distributed rainfall through merging satellite observations, raingauge records, and terrain digital elevation model data
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A new method for estimation of spatially distributed rainfall through merging satellite observations, raingauge records, and terrain digital elevation model data

机译：通过合并卫星观测，雨量计记录和地形数字高程模型数据估算空间分布降雨的新方法

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摘要

This study develops a new method to estimate spatially distributed rainfall through merging the satellite observation, the raingauge record, and the terrain digital elevation model (DEM) data, including the following four steps: (1) to select a suitable satellite observation dataset, (2) to downscale the selected satellite observation dataset with the DEM data, (3) to determine the weighted differences between the raingauge record and the downscaled satellite observation dataset, and (4) to calculate the spatially distributed rainfall through merging the downscaled satellite observation dataset and the weighted differences. The rainstorm occurred on 21 July 2012 in Beijing, China, was considered as a case study to validate the method. Three satellite observation datasets (i.e., TMPA 3B41RT, 3B42RT and CMORPH) were compared with the related raingauge record. Using the new method, this study generated the spatially distributed rainfall data, which were further compared with the three rainfall datasets, i.e., two original rainfall datasets (the selected satellite observation dataset and the raingauge record) and one merged rainfall dataset without consideration of topographic influence. The result revealed that the merged spatially distributed rainfall data is a more rational representation of the actual rainfall than the three other datasets. Furthermore, using this data merging method and a hydrological model, the Digital Yellow River Integrated Model (DYRIM), this study simulated the streamflow process at the Dashi River basin in the southwest of Beijing and the Qingjian River basin in the middle Yellow River. The simulation results showed that the spatially distributed rainfall data could have better performance than those three other datasets, especially for the peak flow simulation. Overall, it is concluded that this data merging method can enhance our capability in estimating the spatial distribution of rainfall.
机译：这项研究开发了一种通过合并卫星观测，雨量计记录和地形数字高程模型（DEM）数据来估算空间分布降雨的新方法，包括以下四个步骤：（1）选择合适的卫星观测数据集，（ 2）使用DEM数据缩小选定的卫星观测数据集的比例；（3）确定雨量计记录和缩小比例的卫星观测数据集之间的加权差异；以及（4）通过合并缩小比例的卫星观测数据集来计算空间分布的降雨和加权差异。 2012年7月21日发生在中国北京的暴雨被认为是验证该方法的案例研究。将三个卫星观测数据集（TMPA 3B41RT，3B42RT和CMORPH）与相关的雨量计记录进行了比较。使用新方法，本研究生成了空间分布的降雨数据，并将其与三个降雨数据集进行了比较，即两个原始降雨数据集（选定的卫星观测数据集和雨量计记录）和一个合并降雨数据集，而没有考虑地形影响。结果表明，与其他三个数据集相比，合并后的空间分布降雨数据更能代表实际降雨。此外，利用这种数据合并方法和水文模型数字黄河综合模型（DYRIM），本研究模拟了北京西南部的大石河流域和黄河中游的清江流域的水流过程。仿真结果表明，空间分布的降雨数据可能比其他三个数据集具有更好的性能，尤其是对于峰值流量模拟而言。总的来说，可以得出结论，这种数据合并方法可以增强我们估算降雨空间分布的能力。

著录项

  • 来源
    《Journal of hydro-environment research》 |2020年第1期|1-14|共14页
  • 作者

    Shi Haiyun; Chen Ji; Li Tiejian; Wang Guangqian;

  • 作者单位

    Univ Hong Kong Dept Civil Engn Hong Kong Peoples R China|Tsinghua Univ State Key Lab Hydrosci & Engn Beijing Peoples R China|Qinghai Univ State Key Lab Plateau Ecol & Agr Xining Qinghai Peoples R China|Qinghai Univ Sanjiangyuan Collaborat Innovat Ctr Xining Qinghai Peoples R China;

    Univ Hong Kong Dept Civil Engn Hong Kong Peoples R China;

    Tsinghua Univ State Key Lab Hydrosci & Engn Beijing Peoples R China|Qinghai Univ State Key Lab Plateau Ecol & Agr Xining Qinghai Peoples R China|Qinghai Univ Sanjiangyuan Collaborat Innovat Ctr Xining Qinghai Peoples R China;

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  • 正文语种 eng
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  • 关键词

    Rainfall; Satellite observation; Raingauge record; Elevation; Spatial distribution; Data merging;

    机译：雨量;卫星观测;雨量计记录;海拔;空间分布;数据合并;

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