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Poster Presentations


Poster Presentations


Forecasting spore escape rates from a soybean canopy using turbulent statistics and a simplified Lagrangian model

Presenter: D. B. Andrade

All authors and affiliations: D. B. ANDRADE, Z. Pan, W. P. Dannevik, and L. Xue. Department of Earth and Atmospheric Sciences, St. Louis University, St. Louis, MO

Meteorological models of soybean rust spore transport depend heavily on accurate spore escape rates from inside a canopy harboring the disease. Unfortunately, many attempts to forecast these release rates have involved theoretical models that are too complex to conveniently incorporate in larger-scale transport models. Thus, we have worked to develop a model that sorts through the theoretical complexities associated with turbulent lifting of spores within a canopy beforehand so that, in an operational setting, accurate escape rates can be computed with the least number of initial conditions and the minimum amount of computational effort. In our model, turbulent statistics (vertical velocity covariance) along with the observed probability density function of vertical velocities inside a soybean canopy and the spores’ terminal velocities are used to infer the average number of spores lifted upward by turbulent fluctuations. The number that penetrate the canopy top is estimated using a filtering function, which depends mainly on leaf area index (LAI) and possibly on turbulent vertical velocities in cases where they are strong enough to reduce the LAI. An adequate 1st-order turbulence closure model will be employed to solve for the shape of the mean wind and turbulent vertical velocity variance profiles given a leaf area density function that describes the canopy. With proper nondimensionalization of these profiles and other important terms, our model can be applied operationally to a wide variety of fields, and spore release rates can be accurately predicted simply from a few measurements, such as mean wind at a single level and initial spore concentrations inside the canopy.

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