A fast-response, wind angle-sensitive model for predicting mean winds in row-organized canopies

Authors: ULMER, LUCAS - University Of Utah; MARGAIRAZ, FABIEN - University Of Utah; BAILEY, BRIAN - University Of California, Davis; Mahaffee, Walter - Walt; PARDYJAK, ERIC - University Of Utah; STOLL, ROB - University Of Utah

Submitted to: Agricultural and Forest Meteorology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 12/21/2022
Publication Date: 12/21/2022
Citation: Ulmer, L., Margairaz, F., Bailey, B., Mahaffee, W.F., Pardyjak, E., Stoll, R. 2022. A fast-response, wind angle-sensitive model for predicting mean winds in row-organized canopies. Agricultural and Forest Meteorology. 329. Article 109273. https://doi.org/10.1016/j.agrformet.2022.109273.
DOI: https://doi.org/10.1016/j.agrformet.2022.109273

Interpretive Summary: Accurate assessment of spatialized disease risk is dependent on the ability to predict pathogen movement in a very complex environment. Currently approaches do not sufficiently account for how canopy and row structure can influence pathogen dispersion in many perennial crops that are trellised (vineyards, cane berries, apples) or organized into rows with dense canopies separated by wide allies (blue berries, stone fruit,etc.). This rows structure can significantly alter airflow in and round the canopy and impact disease spread and development. A low-cost diagnostic wind solver model (Quick Environmental Simulation ) for mean wind in such canopies was developed and deployed. The model output was tuned using particle image velocimetry data from a wind tunnel experiment, and validated using 3D sonic anemometer data from a field experiment in a vineyard. The model responds appropriately to changes in incident wind direction and captures transport-critical features of the mean wind. The model exhibits wind channeling in oblique winds, where the wind direction inside the canopy turns toward the row direction because of a model component that approximates the effects of form drag upwind of each row. The the air movement above the canopy is also well represented in response to changes in wind direction. The model offers significant improvements over existing low-cost models of canopy flow that ignore the highly ordered row structure and will aide in developing spatialized disease risk and precision applications of fungicides.

Technical Abstract: Parallel arrays of long, porous, fence-like objects (row-organized canopies) are common in agricultural and rural settings. Examples include vineyards, series of windbreaks, snow fences, and some orchards. A low-cost model of the mean flow in such arrays has been developed and deployed in a GPU-accelerated fast-response diagnostic wind solver called Quick Environmental Simulation (QES). The model output is compared against particle image velocimetry (PIV) data from a wind tunnel experiment, and sonic anemometer data from a field experiment in a vineyard. Some tuning of model parameters to the PIV data was performed, and the field data was used for validation. The model responds appropriately to changes in incident wind direction and captures transport-critical features of the mean wind with similar accuracy as other low-cost models implemented in QES. Topological features of the flow match well with PIV data. The model exhibits flow channeling in oblique winds, in which wind vectors inside the canopy turn toward the row direction, due to a model component that approximates the effects of form drag upwind of each row. The canopy-top gradient is well represented, as well as its response to changes in wind direction. The model offers significant improvements over existing low-cost models of canopy flow that ignore the highly ordered structure of the array elements, highlighting the importance of resolving spatial heterogeneity in this class of canopies.