Wind is the principal driver of the Wind Erosion Prediction System (WEPS), which is a process-based computermodel for the simulation of wind-blown sediment loss from a field. WEPS generates wind using a stochastic wind generator.The objectives of this study were to improve the stochastic generation of wind speed and direction and to update the windstatistics used by the generator with statistics derived from more recent, quality-controlled data for the 48 contiguous statesof the U.S. Erosive wind power density (WPD) was chosen to evaluate how well wind is generated, since it is proportionalto sediment transport by wind. It is important that WPD calculated from stochastically generated data (WPDg) closelyreproduces WPD calculated from the underlying measured data (WPDm). The commonly used two-parameter Weibull modeldid not fit wind speed distributions well enough for application in wind erosion models. WPDg deviated more than 20% fromWPDm for 168 out of the 332 stations having WPDm > 5 W m-2. Fitting the model to the high wind speeds only, with theexpectation of a better curve fit, resulted in some generated wind speeds exceeding 100 m s-1, which is unacceptable. A moredirect method uses the wind speed distributions themselves instead of the Weibull model that describes them. Wind speedsare then generated directly from the distributions using linear interpolation between data points. With this more robust directapproach, there was only one station (down from 168 stations) where WPDg deviated more than 20% from WPDm. The directmethod of wind speed generation reproduces wind speeds more accurately than the Weibull model, which is important forwind erosion prediction and may be important for other applications as well.
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Donk et al. (2005) studied this question.
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