2017
DOI: 10.1038/s41598-017-13084-x
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Vegetation morphologic and aerodynamic characteristics reduce aeolian erosion

Abstract: AbsractVegetation cover is crucial to controlling aeolian erosion but highly efficient vegetation is critical. How this efficiency is influenced by vegetation response to airflow is not clear. Here we evaluate the responses of Cosmos bipinnatus and Ligustrum lucidum Ait to a range of wind speeds in a wind tunnel. For both species, we calculate shelter effect and sand flux. We show that plant effectiveness in reducing wind speed and sediment transport is linked to their aerodynamic response to airflow which res… Show more

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Cited by 55 publications
(26 citation statements)
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“…The interaction among vegetation elements could greatly change the flow pattern (e.g., skimming flow) in moderate or high density cases 34 , consequently, the distribution pattern or function couldn’t be suitable any more. Besides, experiments 35,36 suggest the canopy shape has great effect on vegetation drag coefficient; and numerical simulation 11 shows the effect of canopy shape on leeward wind speed distribution. The wind speed at the lowest grid in dust forecast models might thus be estimated inaccurately with the increase of vegetation density because of the difference in canopy shape, which could also be able to rise up the uncertainties in prediction of dust events.…”
Section: Discussionmentioning
confidence: 99%
“…The interaction among vegetation elements could greatly change the flow pattern (e.g., skimming flow) in moderate or high density cases 34 , consequently, the distribution pattern or function couldn’t be suitable any more. Besides, experiments 35,36 suggest the canopy shape has great effect on vegetation drag coefficient; and numerical simulation 11 shows the effect of canopy shape on leeward wind speed distribution. The wind speed at the lowest grid in dust forecast models might thus be estimated inaccurately with the increase of vegetation density because of the difference in canopy shape, which could also be able to rise up the uncertainties in prediction of dust events.…”
Section: Discussionmentioning
confidence: 99%
“…Wind tunnel studies on vegetation were, for example conducted by Youssef et al. (2012) who simulated the field‐scale effect of vegetation patterns on wind‐blown mass transport, whereas Miri, Dragovich, and Dong (2017) looked at morphologic and aerodynamic characteristics of two species. These authors indicated that our understanding of the effective vegetation patterns is still incomplete (Miri et al, 2017; Youssef et al., 2012).…”
Section: Introductionmentioning
confidence: 99%
“…For example, Li, Okin, Alvarez, and Epstein (2007) studied quantitative effects of vegetation cover on wind erosion in southern New Mexico, USA, while Touré et al (2019) investigated the dynamics of wind erosion and impact of vegetation cover and land use in southeastern Niger. Wind tunnel studies on vegetation were, for example conducted by Youssef et al (2012) who simulated the fieldscale effect of vegetation patterns on wind-blown mass transport, whereas Miri, Dragovich, and Dong (2017) looked at morphologic and aerodynamic characteristics of two species. These authors indicated that our understanding of the effective vegetation patterns is still incomplete (Miri et al, 2017;Youssef et al, 2012).…”
mentioning
confidence: 99%
“…Vegetation morphology (or windward shape) could affect the region of local wind reduction due to the difference in drag coefficient (Gillies, Nickling, & King, ; Miri, Dragovich, & Dong, ). Frontal area ratio (the ratio of height vs. width) is thus introduced to quantitatively parameterize local wind reduction region for a single element in both theoretical and numerical studies (Raupach, ; Yang et al, ).…”
Section: Introductionmentioning
confidence: 99%
“…Vegetation morphology (or windward shape) could affect the region of local wind reduction due to the difference in drag coefficient (Gillies, Nickling, & King, 2002;Miri, Dragovich, & Dong, 2017).…”
Section: Introductionmentioning
confidence: 99%