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首页> 外文期刊>Journal of Hydrology >Continental satellite soil moisture data assimilation improves root-zone moisture analysis for water resources assessment
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Continental satellite soil moisture data assimilation improves root-zone moisture analysis for water resources assessment

机译:大陆卫星土壤水分数据同化改善了用于水资源评估的根区水分分析

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摘要

A framework was developed for the continental assimilation of satellite soil moisture (SM) into an operational water balance modelling system. The ensemble Kalman filter (EnKF) was implemented to assimilate AMSR-E and ASCAT-derived SM products into the landscape model of the Australian Water Resources Assessment system (AWRA-L) and generate ensembles of daily top-layer and shallow root-zone soil moisture analyses for the continent at 0.05 degrees resolution. We evaluated the AWRA-L SM estimates with and without assimilation against in situ moisture measurements in southeast Australia (OzNet), as well as against a new network of cosmic-ray moisture probes (CosmOz) spread across the country. Results show that AWRA-L root-zone moisture estimates are improved though the assimilation of satellite SM: model estimates of 0-30 cm moisture content improved for more than 90% of OzNet sites, with an increase in average correlation from 0.68 (before assimilation) to 0.73 (after assimilation); while estimates 0-90 cm moisture improved for 60% of sites with increased average correlation from 0.56 to 0.65. The assimilation of AMSR-E and ASCAT appeared to yield similar performance gains for the top-layer, however ASCAT data assimilation improved root-zone estimation for more sites. Poor performance of one data set was compensated by the other through joint assimilation. The most significant improvements in AWRA-L root-zone moisture estimation (with increases in correlation as high as 90%) occurred for sites where both the assimilation of satellite soil moisture improved top-layer SM accuracy and the open-loop deep-layer storage estimates were reasonably good. CosmOz SM measurements exhibited highest correlation with AWRA-L estimates for modelled root-zones layer thicknesses ranging from 20 cm to 1 m. Slight improvements through satellite data assimilation were observed for only 2 of 7 CosmOz sites, but the comparison was affected by a short data overlap period. The location of some of the CosmOz probes was not optimal for evaluation of satellite SM assimilation, but their utility is demonstrated and the observations may become suitable for assimilation themselves in future. (C) 2014 Elsevier B.V. All rights reserved.
机译:开发了一个框架,用于将卫星土壤水分(SM)大陆吸收到可运行的水平衡模型系统中。实施集成卡尔曼滤波器(EnKF)将AMSR-E和ASCAT衍生的SM产品吸收到澳大利亚水资源评估系统(AWRA-L)的景观模型中,并生成每日顶层和浅根区土壤的集合大陆以0.05度的分辨率进行水分分析。我们评估了澳大利亚东南部(OzNet)的原位水分测量以及未分布在澳大利亚全国各地的新的宇宙射线水分探测器(CosmOz)网络的同化和不同化情况下的AWRA-L SM估算值。结果表明,尽管卫星SM的同化使AWRA-L根区含水量估计值有所改善:OzNet站点中90%以上的OzNet站点的0-30 cm含水量模型估计有所改善,平均相关性从0.68起增加(同化之前) )至0.73(同化后);而估计0-90厘米的湿度改善了60%的位置,平均相关性从0.56增加到0.65。 AMSR-E和ASCAT的同化似乎为顶层产生了类似的性能提升,但是ASCAT数据的同化改善了更多站点的根域估计。一个数据集的性能不佳通过联合同化来弥补。 AWRA-L根区水分估算的最显着改进(相关性增加高达90%)发生在卫星土壤水分同化提高了顶层SM准确性和开环深层存储的地方估计是相当不错的。 CosmOz SM测量结果与模拟的根区层厚度范围为20 cm至1 m的AWRA-L估计值显示出最高的相关性。在7个CosmOz站点中,只有2个站点观测到通过卫星数据同化带来的轻微改善,但是比较受到较短数据重叠周期的影响。对于评估卫星SM同化而言,某些CosmOz探针的位置并非最佳,但已证明了其实用性,并且这些观察结果将来可能会变得更适合自身同化。 (C)2014 Elsevier B.V.保留所有权利。

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