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Global joint assimilation of GRACE and SMOS for improved estimation of root-zone soil moisture and vegetation response

机译:改善根区土壤水分和植被反应的恩典和SMO的全球联合同化

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摘要

The lack of direct measurement of root-zone soil moisture poses a challenge to the large-scale prediction of ecosystem response to variation in soil water. Microwave remote sensing capability is limited to measuring moisture content in the uppermost few centimetres of soil. The GRACE (Gravity Recovery and Climate Experiment) mission detected the variability in storage within the total water column. However, root-zone soil moisture cannot be separated from GRACE-observed total water storage anomalies without ancillary information on surface water and groundwater changes. In this study, GRACE total water storage anomalies and SMOS near-surface soil moisture observations were jointly assimilated into a hydrological model globally to better estimate the impact of changes in root-zone soil moisture on vegetation vigour. Overall, the accuracy of root-zone soil moisture estimates through the joint assimilation of surface soil moisture and total water storage retrievals showed improved consistency with ground-based soil moisture measurements and satellite-observed greenness when compared to open-loop estimates (i.e. without assimilation). For example, the correlation between modelled and in situ measurements of root-zone moisture increased by 0.1 (from 0.48 to 0.58) and 0.12 (from 0.53 to 0.65) on average for grasslands and croplands, respectively. Improved correlations were found between vegetation greenness and soil water storage on both seasonal variability and anomalies over water-limited regions. Joint assimilation results show a more severe deficit in soil water anomalies in eastern Australia, southern India and eastern Brazil over the period of 2010 to 2016 than the open-loop, consistent with the satellite-observed vegetation greenness anomalies. The assimilation of satellite-observed water content contributes to more accurate knowledge of soil water availability, providing new insights for monitoring hidden water stress and vegetation conditions.
机译:根区土壤水分的直接测量缺乏对土壤水域变化的大规模预测对土壤水域变化的大规模预测构成了挑战。微波遥感能力仅限于测量少数厘米的土壤中的水分含量。 Grace(重力恢复和气候实验)任务检测了总水柱内储存的可变性。然而,根区土壤水分不能与恩典观察到的总储水异常分开,没有关于地表水和地下水的辅助信息。在这项研究中,恩典总储水异常和SMOS近地面土壤水分观察被共同同化到全球水文模型中,以更好地估计根区土壤水分变化对植被活力的影响。总的来说,通过与开环估计相比,通过与表面土壤水分的关节同化和总储水检索的联合同化的根区土壤水分估算的准确性显示出改善与地面土壤水分测量和卫星观察的绿色一致性(即没有同化)。例如,对于草地和农田的平均水分和根部区域水分的建模和原位测量之间的相关性增加0.1(从0.48至0.58)和0.12(从0.53到0.65)。植被绿色和土壤储水之间的季节性变异和异常在有限地区的异常中发现了改进的相关性。联合同化结果在2010年至2016年的2010年至2016年,澳大利亚东部的土壤水异常中的土壤水异常具有更严重的赤字,而不是卫星观察卫星植被绿色异常。观察卫星含水量的同化有助于更准确地了解土壤水量可用性,为监测隐藏的水分应激和植被条件提供新的见解。

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