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比较结果表明,为了预测风沙通量,需要付出更多努力来对灌木植被周围的风流进行参数化处理。

Comparisons suggest more efforts are required to parameterize wind flow around shrub vegetation elements for predicting aeolian flux.

作者信息

Fu Lin-Tao

机构信息

School of Mechanical Engineering, Chengdu University, Chengdu, 610106, China.

出版信息

Sci Rep. 2019 Mar 7;9(1):3841. doi: 10.1038/s41598-019-40491-z.

Abstract

Upon interacting with the atmosphere, vegetation could alter the wind distribution and consequently the erodibility of nearby region. The parameterization of wind distribution around vegetation is crucial for the prediction of surface aeolian flux. This paper compared the performances of existing empirical distribution models in the estimation of aeolian flux for shrub vegetation, focusing on distribution pattern and vegetation porosity (main parameter of distribution function). Predicted dust fluxes directly entrained by air flow show weak sensitivity to both distribution pattern and porosity in the case of low vegetation density, which suggests some aspects in dust forecast models might be simplified. However, both distribution pattern and porosity show significant effect on sand saltation transport rate in the lee of vegetation element and, consequently, on the formation and evolution of surface aeolian landforms. The contribution of dust fluxes released in wind increase zone to the total emission by using current parameterizations increases with both the decrease of wind speed and the increase of vegetation density. Nevertheless, the parameterization of wind increase zone needs to be validated and improved by further experimental and numerical investigations.

摘要

植被与大气相互作用时,会改变风的分布,进而影响附近区域的风蚀性。植被周围风分布的参数化对于预测地表风沙通量至关重要。本文比较了现有经验分布模型在估算灌木植被风沙通量方面的性能,重点关注分布模式和植被孔隙度(分布函数的主要参数)。在植被密度较低的情况下,气流直接夹带的预测沙尘通量对分布模式和孔隙度的敏感性较弱,这表明沙尘预报模型的某些方面可能可以简化。然而,分布模式和孔隙度对植被元素背风处的沙跃移输运速率以及地表风沙地貌的形成和演化都有显著影响。使用当前参数化方法,风增强区释放的沙尘通量对总排放的贡献随风速降低和植被密度增加而增加。尽管如此,风增强区的参数化仍需通过进一步的实验和数值研究来验证和改进。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9dad/6405760/8565991ca965/41598_2019_40491_Fig1_HTML.jpg

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