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Appraisal of NLDAS-2 Multi-Model Simulated Soil Moistures for Hydrological Modelling

机译:用于水文模型的NLDAS-2多模型模拟土壤水分的评估

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摘要

Soil moisture is a key variable in hydrological modelling, which could be estimated by land surface modelling. However the previous studies have focused on evaluating these soil moisture estimates by using point-based measurements, and there is a lack of attention for their appraisal over basin scales particularly for hydrological applications. In this study, we carry out for the first time, a detailed evaluation of five sources of soil moisture products (NLDAS-2 multi-model simulated soil moistures: Noah, VIC, Mosaic and SAC; and a ground observation), against a widely used hydrological model Xinanjiang (XAJ) as a benchmark at a U.S. basin. Generally speaking, all products have good agreements with the hydrological soil moisture simulation, with superior performance obtained from the SAC model and the VIC model. Furthermore, the results indicate that the in-situ measurements in deeper soil layer are still usable for hydrological applications. Nevertheless further improvement is still required on the definition of land surface model layer thicknesses and the related data fusion with the remotely sensed soil moisture. The potential usage of the NLDAS-2 soil moisture datasets in real-time flood forecasting is discussed.
机译:土壤水分是水文模拟中的关键变量,可以通过地表模拟来估算。然而,先前的研究集中在通过使用基于点的测量来评估这些土壤湿度估计值,并且缺乏对它们在流域尺度上的评估的关注,特别是在水文应用方面。在这项研究中,我们首次针对五种土壤水分产品(NLDAS-2多模型模拟土壤水分:Noah,VIC,Mosaic和SAC;以及地面观察)进行了详细评估,在美国流域以水文模型新安江(XAJ)为基准。一般而言,所有产品与水文土壤湿度模拟都具有良好的一致性,并且从SAC模型和VIC模型获得的性能优越。此外,结果表明,在更深的土壤层中进行的现场测量仍可用于水文应用。然而,在陆面模型层厚度的定义以及与遥感土壤水分的相关数据融合方面仍需要进一步的改进。讨论了NLDAS-2土壤水分数据集在实时洪水预报中的潜在用途。

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