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首页> 外文期刊>Journal of Hydrology >Comprehensive evaluation of multi-satellite precipitation products with a dense rain gauge network and optimally merging their simulated hydrological flows using the Bayesian model averaging method
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Comprehensive evaluation of multi-satellite precipitation products with a dense rain gauge network and optimally merging their simulated hydrological flows using the Bayesian model averaging method

机译:利用密集雨量计网络对多卫星降水产品进行综合评估,并使用贝叶斯模型平均法对模拟水文流量进行最佳合并

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摘要

This study first focuses on comprehensive evaluating three widely used satellite precipitation products (TMPA 3B42V6, TMPA 3B42RT, and CMORPH) with a dense rain gauge network in the Mishui basin (9972km ~2) in South China and then optimally merge their simulated hydrologic flows with the semi-distributed Xinanjiang model using the Bayesian model averaging method. The initial satellite precipitation data comparisons show that the reanalyzed 3B42V6, with a bias of -4.54%, matched best with the rain gauge observations, while the two near real-time satellite datasets (3B42RT and CMORPH) largely underestimated precipitation by 42.72% and 40.81% respectively. With the model parameters first benchmarked by the rain gauge data, the behavior of the streamflow simulation from the 3B42V6 was also the most optimal amongst the three products, while the two near real-time satellite datasets produced deteriorated biases and Nash-Sutcliffe coefficients (NSCEs). Still, when the model parameters were recalibrated by each individual satellite data, the performance of the streamflow simulations from the two near real-time satellite products were significantly improved, thus demonstrating the need for specific calibrations of the hydrological models for the near real-time satellite inputs. Moreover, when optimally merged with respect to the streamflows forced by the two near real-time satellite precipitation products and all the three satellite precipitation products using the Bayesian model averaging method, the resulted streamflow series further improved and became more robust. In summary, the three current state-of-the-art satellite precipitation products have demonstrated potential in hydrological research and applications. The benchmarking, recalibration, and optimal merging schemes for streamflow simulation at a basin scale described in the present work will hopefully be a reference for future utilizations of satellite precipitation products in global and regional hydrological applications.
机译:本研究首先重点对华南密水盆地(9972km〜2)具有密集雨量计网络的三种广泛使用的卫星降水产品(TMPA 3B42V6,TMPA 3B42RT和CMORPH)进行综合评估,然后将它们的模拟水文流量与使用贝叶斯模型平均法的半分布式新安江模型。初始卫星降水数据比较表明,重新分析的3B42V6的偏差为-4.54%,与雨量计观测值最匹配,而两个近实时卫星数据集(3B42RT和CMORPH)大大低估了降水量42.72%和40.81。 % 分别。在模型参数首先以雨量计数据为基准的情况下,来自3B42V6的水流模拟的行为在这三种产品中也是最佳的,而两个近实时卫星数据集产生了恶化的偏差和Nash-Sutcliffe系数(NSCE) )。尽管如此,当通过每个单独的卫星数据重新校准模型参数时,两个近乎实时的卫星产品的水流模拟的性能得到了显着改善,因此表明需要对近实时的水文模型进行特定的校准卫星输入。此外,当使用贝叶斯模型平均法对两个近实时卫星降水产物和所有三个卫星降水产物所强制的水流进行最佳合并时,所得的水流序列将进一步改善并变得更加稳健。总而言之,当前三种最先进的卫星降水产品在水文研究和应用中已显示出潜力。本工作中描述的流域尺度上的水流模拟的基准,重新校准和最佳合并方案有望为将来在全球和区域水文应用中利用卫星降水产品提供参考。

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