Research Highlights: Simulations of treefall patterns during tornado events have been conducted, enabling the coupled effects of tornado characteristics, tree properties and soil conditions to be assessed for the first time. Background and Objectives: Treefall patterns and forest damage assessed in post-storm surveys are dependent on the interaction between topography, biology and meteorology, which makes identification of characteristic behavior challenging. Much of our knowledge of tree damage during extreme winds is based on synoptic storms. Better characterization of tree damage will provide more knowledge of tornado impacts on forests, as well as their ecological significance. Materials and Methods: a numerical method based on a Rankine vortex model coupled with two mechanistic tree models for critical wind velocity for stem break and windthrow was used to simulate tornadic tree damage. To calibrate the models, a treefall analysis of the Alonsa tornado was used. Parametric study was conducted to assess induced tornadic tree failure patterns for uprooting on saturated and unsaturated soils and stem break with different knot factors. Results: A power law relationship between failure bending moments and diameter at breast height (DBH) for the hardwood species provided the best correlation. Observed failure distributions of stem break and windthrow along the tornado track were fitted to lognormal distributions and the mean of the critical wind speeds for windthrow were found to be higher than that for stem break. Relationships between critical wind speed and tree size were negatively correlated for windthrow and positively correlated for stem break. Higher soil moisture contents and lower knot factors reduced the critical wind speeds. The simulations show varying tree fall patterns displaying forward and backward convergence, different tornado damage widths and asymmetry of the tracks. These variations were controlled by the relative magnitudes of radial and tangential tornado velocities, the ratio between translational speed and maximum rotational wind speed and the mode of failure of the trees. Conclusions: The results show the complexity of predicting tornadic damage in forests, and it is anticipated that this type of simulation will aid risk assessments for insurance companies, emergency managers and forest authorities.
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