Collaborative Research: Aeolian Grain Entrainment Over Flexible Vegetation Canopies: Theoretical Models, Laboratory Experiments and Fieldwork

合作研究：灵活植被冠层的风沙颗粒夹带：理论模型、实验室实验和实地考察

• 批准号: 2327916
• 负责人: Yaqing Jin
• 金额: $ 33.59万
• 依托单位: University of Texas at Dallas
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-11-01 至 2026-10-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2327916&HistoricalAwards=false
• 关键词: Collaborative; Research; Aeolian; Grain; Entrainment

Vegetation plays a significant role in modulating the entrainment of sediment by wind. Once entrained sand and dust particles have a crucial influence on weather and climate, air quality, landforms, and other components in the land-atmosphere system. Vast regions across the planet in areas susceptible to wind erosion have vegetation covers composed of grasses and herbs with flexible stems and blades. This type of vegetation deforms under sufficiently-high wind speeds, which alters wind-particle interactions. However, current understanding of the complex interactions remains limited, and predictive models of grain entrainment that account for the impact of canopy morphing are lacking. This project aims to elucidate the underlying physics of wind-vegetation-particle interactions for flexible canopies and develop predictive equations for aeolian grain entrainment. The model developed and validated in this research will open a pathway for understanding and predicting aeolian entrainment across a wide range of vegetation cover amounts, wind conditions, and grain properties. Results from the research endeavors will be integrated into educational activities involving K-12 education, undergraduate research, and graduate research training. The outreach activities including hands-on experiments and field trips will provide unique opportunities for attracting students, especially young women in STEM career-paths.The primary objective of this project is to combine theoretical modeling, laboratory experiments and field tests to elucidate the underlying physics of grain entrainment for flexible vegetation canopies that will aid in improving prediction of particle entrainment thresholds, concentrations and flux rates. A reduced-order model based on the balance between wind load on vegetation and blade restoring forces will be developed and validated by wind tunnel experiments to predict vegetation postures and velocity statistics within the canopy. This understanding will then be applied to determine the aerodynamic loads on aeolian particles, where an advection-dispersion equation will be used to predict vertical profiles of particle mass concentration. Finally, results from the predictive models and laboratory experiments will be further evaluated by field tests at the Oceano Dunes State Vehicular Recreation Area, Pismo Beach, CA using recently developed sand transport instruments for measuring vertical profiles of particle flux for different flexible and rigid vegetation densities. Altogether, this project will deepen fundamental understanding of the mechanisms through which flexible vegetation covers modulate particle entrainment by wind, leading to improved predictive threshold and transport rate models. The research results can also lead to developing more effective control strategies for reducing wind erosion and dust emissions using vegetative covers.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

植被在调节风夹带沉积物方面发挥着重要作用。一旦夹带的沙尘颗粒对天气和气候、空气质量、地貌和陆地大气系统的其他组成部分产生至关重要的影响。地球上广大易受风蚀影响的地区都有由草和草本植物组成的植被，这些草本植物具有灵活的茎和叶片。这种类型的植被在足够高的风速下会变形，从而改变风与粒子的相互作用。然而，目前对复杂相互作用的理解仍然有限，并且缺乏解释冠层变形影响的谷物夹带的预测模型。该项目旨在阐明柔性冠层的风-植被-颗粒相互作用的基本物理原理，并开发风沙颗粒夹带的预测方程。本研究开发和验证的模型将为理解和预测各种植被覆盖量、风力条件和谷物特性的风夹带开辟一条途径。研究成果将融入到 K-12 教育、本科生研究和研究生研究培训等教育活动中。 包括实践实验和实地考察在内的外展活动将为吸引学生，尤其是 STEM 职业道路上的年轻女性提供独特的机会。该项目的主要目标是将理论建模、实验室实验和现场测试结合起来，以阐明基础物理原理灵活植被冠层的谷物夹带的研究将有助于改进颗粒夹带阈值、浓度和通量率的预测。将开发基于植被风荷载和叶片恢复力之间平衡的降阶模型，并通过风洞实验进行验证，以预测冠层内的植被姿态和速度统计数据。然后，这种理解将应用于确定风颗粒上的空气动力载荷，其中平流扩散方程将用于预测颗粒质量浓度的垂直分布。最后，预测模型和实验室实验的结果将通过在加州皮斯莫海滩 Oceano Dunes 州立车辆游乐区的现场测试进一步评估，使用最近开发的沙运仪器测量不同柔性和刚性植被密度的颗粒通量垂直剖面。总而言之，该项目将加深对柔性植被覆盖调节风颗粒夹带机制的基本理解，从而改进预测阈值和传输率模型。研究结果还可以导致开发更有效的控制策略，以利用植被覆盖来减少风蚀和灰尘排放。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力优点和更广泛的影响审查标准进行评估，被认为值得支持。