Evaluation of a random displacement model for predicting particle escape from canopies using a simple eddy diffusivity model



Follett, Elizabeth ORCID: 0000-0001-9993-5313, Chamecki, Marcelo and Nepf, Heidi
(2016) Evaluation of a random displacement model for predicting particle escape from canopies using a simple eddy diffusivity model. AGRICULTURAL AND FOREST METEOROLOGY, 224. pp. 40-48.

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Abstract

There is a need for more practical tools for estimating spore escape from crop canopies, which is essential in forecasting the propagation of disease to other fields. In this paper, we evaluated whether a random displacement model (RDM) parameterized with an eddy diffusivity Kz(z) could be used to predict spore escape probability. The proposed RDM does not require detailed turbulence measurements for parameterization. Instead, it constructs profiles of velocity and eddy diffusivity from a simple set of parameters [canopy height, canopy density, vegetation length scale, and wind speed]. The RDM was validated using field measurements of spore concentration. On average, the model predictions matched the field measurements within 28% inside the canopy and 42% above it, comparable to LES results over the same canopy. Once validated, the RDM was used to explore particle escape across a range of canopy densities and particle settling velocities, in order to inform estimates of particle escape from crops of varying maturity or area density. Escape fraction as calculated by the RDM increased as canopy density decreased, as the ratio of particle settling velocity to turbulent shear velocity ratio decreased, and as the source height within the canopy increased.

Item Type: Article
Uncontrolled Keywords: Particle transport, Escape of particles from canopy, Eddy diffusivity, Random displacement model, Maize
Divisions: Faculty of Science and Engineering > School of Engineering
Depositing User: Symplectic Admin
Date Deposited: 06 Jan 2023 11:15
Last Modified: 06 Jan 2023 11:15
DOI: 10.1016/j.agrformet.2016.04.004
Open Access URL: https://dspace.mit.edu/handle/1721.1/117383
Related URLs:
URI: https://livrepository.liverpool.ac.uk/id/eprint/3166855