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首页> 外文期刊>Geoscience and Remote Sensing Letters, IEEE >Microwave Satellite Data for Hydrologic Modeling in Ungauged Basins
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Microwave Satellite Data for Hydrologic Modeling in Ungauged Basins

机译：疏漏盆地水文模拟的微波卫星数据

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An innovative flood-prediction framework is developed using Tropical Rainfall Measuring Mission precipitation forcing and a proxy for river discharge from the Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) onboard the National Aeronautics and Space Administration's Aqua satellite. The AMSR-E-detected water surface signal was correlated with in situ measurements of streamflow in the Okavango Basin in Southern Africa as indicated by a Pearson correlation coefficient of 0.90. A distributed hydrologic model, with structural data sets derived from remote-sensing data, was calibrated to yield simulations matching the flood frequencies from the AMSR-E-detected water surface signal. Model performance during a validation period yielded a Nash-Sutcliffe efficiency of 0.84. We concluded that remote-sensing data from microwave sensors could be used to supplement stream gauges in large sparsely gauged or ungauged basins to calibrate hydrologic models. Given the global availability of all required data sets, this approach can be potentially expanded to improve flood monitoring and prediction in sparsely gauged basins throughout the world.
机译：开发了一种创新的洪水预报框架，使用了热带降雨测量任务的降水强迫和美国国家航空航天局的Aqua卫星上先进的地球观测系统微波扫描辐射仪（AMSR-E）的河流排放代理。 AMSR-E检测到的水面信号与南部非洲奥卡万戈盆地的水流原位测量值相关，如皮尔森相关系数0.90所示。校准了分布式水文模型，其结构数据集来自遥感数据，以产生与AMSR-E检测到的水面信号中的洪水频率匹配的模拟。验证期间的模型性能得出的Nash-Sutcliffe效率为0.84。我们得出的结论是，微波传感器的遥感数据可用于补充大面积稀疏或未灌洗盆地中的水位计，以校准水文模型。考虑到所有必需数据集的全球可用性，可以对这种方法进行潜在的扩展，以改善全球稀疏流域的洪水监测和预报。

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