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Interpolation of daily raingauge data for hydrological modelling in data sparse regions using pattern information from satellite data

机译:使用卫星数据的模式信息对每日稀疏数据进行插值,以进行数据稀疏区域的水文建模

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摘要

In order to cope with a severe reduction of the raingauge network in the Great Ruaha River basin over the past 30years, an interpolation scheme using spatial patterns from satellite images as covariate has been evaluated. The regression-based interpolation attempts to combine the advantages of accurate rainfall amounts from raingauge records with the unique spatial pattern information obtained from satellite-based rainfall estimates. A spatial pattern analysis reveals that the simple interpolation of the sparse current raingauge network compares very poorly to the pattern originating from the much denser historic network. In contrast, the rainfall datasets that include patterns from satellite data show good correlation with the historic pattern. The evaluation based on hydrological modelling showed similar and good performance for all rainfall products, including raingauge records, whereas the purely satellite-based product performed poorly.
机译:为了应对过去30年里大鲁阿哈河流域雨量计网络的严重减少,已经对使用卫星图像空间模式作为协变量的插值方案进行了评估。基于回归的插值尝试将雨量计记录中准确的降雨量的优势与从基于卫星的降雨估算中获得的独特空间模式信息相结合。空间模式分析表明,稀疏当前雨量计网络的简单插值与源自更密集的历史网络的模式相比非常差。相反,包括卫星数据模式的降雨数据集与历史模式显示出良好的相关性。基于水文模型的评估显示,所有降雨产品,包括雨量计记录,都具有相似且良好的性能,而纯卫星产品的性能较差。

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