Wind Erosion:
An International Symposium/Workshop

Udai B. Singh, James M. Gregory, and Gregory R. Wilson

       Soil erosion by wind reduces soil productivity, decreases agricultural production, and the associated dust generation from wind erosion affects human health and the environment by polluting the air. There is a high on-site as well as off-site cost due to wind erosion in various parts of the world. It has been estimated that off-site cost due to wind erosion is much higher than on-site cost.
       Texas Tech Erosion Analysis Model (TEAM) is a physically based mathematical model which simulates the detachment and maximum transport rate and associated atmospheric loading of dust from agricultural and non-agricultural sources. The model simulates the effect of surface cover, wind velocity, soil shear strength, soil particle size and particle size distribution, and soil moisture on the maximum transport rate. The maximum transport rate equation has been calibrated and verified with measured field and wind tunnel data.
       The amount of dust production, excluding the initial dust already present in the soil system, is a byproduct of the saltation process during wind erosion. A dust generation equation has also been developed by relating the change in detachment of dust particle to the number of impacts from particle abrasion during saltation. The dust generation equation was verified with data collected from a controlled energy dust generator (CEDG) designed and developed at the Wind Engineering Research Center, Texas Tech University, Lubbock, Texas. The effects of soil type and moisture content on amount of dust generation were also studied.
      An overview of the theoretical development and experimental validation of various key components of TEAM are presented in this paper. TEAM was adopted and currently in use by a major environmental consulting firm to perform an air quality safety analysis for cleaning up a major environmental contamination site. TEAM was compared to 20 other models and was adopted because of its ability to consider detailed data input and its robustness in modeling the wind erosion and dust generation processes.