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Applications of Satellite-Based Rainfall Estimates in Flood Inundation Modeling—A Case Study in Mundeni Aru River Basin, Sri Lanka

机译:基于卫星的降雨估计在洪水泛滥模型中的应用-以斯里兰卡Mundeni Aru流域为例

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The performance of Satellite Rainfall Estimate (SRE) products applied to flood inundation modelling was tested for the Mundeni Aru River Basin in eastern Sri Lanka. Three SREs (PERSIANN, TRMM, and GSMaP) were tested, with the Rainfall-Runoff-Inundation (RRI) model used as the flood inundation model. All the SREs were found to be suitable for applying to the RRI model. The simulations created by applying the SREs were generally accurate, although there were some discrepancies in discharge due to differing precipitation volumes. The volumes of precipitation of the SREs tended to be smaller than those of the gauged data, but using a scale factor to correct this improved the simulations. In particular, the SRE, i.e., the GSMaP yielding the best simulation that correlated most closely with the flood inundation extent from the satellite data, was considered the most appropriate to apply to the model calculation. The application procedures and suggestions shown in this study could help authorities to make better-informed decisions when giving early flood warnings and making rapid flood forecasts, especially in areas where in-situ observations are limited.
机译:在斯里兰卡东部的Mundeni Aru流域,对应用于洪水泛滥模型的卫星降雨估算(SRE)产品的性能进行了测试。测试了三个SRE(PERSIANN,TRMM和GSMaP),并将降雨-径流-洪水(RRI)模型用作洪水淹没模型。发现所有SRE都适用于RRI模型。尽管存在不同的降水量,但在排放方面存在一些差异,但通过应用SRE创建的模拟通常是准确的。 SRE的降水量往往小于实测数据的降水量,但是使用比例因子进行校正可以改善模拟效果。特别是,SRE(即GSMaP)产生的最佳模拟与卫星数据中的洪水泛滥程度最密切相关,被认为最适合应用于模型计算。这项研究中显示的应用程序和建议可以帮助当局在发出早期洪水警报和进行快速洪水预报时做出更明智的决策,尤其是在现场观测有限的地区。

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