Development of a fast all-seasons model for the state of the ground

For predicting soil conditions in support of mobility, combat, or engineering simulations, it is important to have verified models that can reliably predict the state of the ground in all weather conditions. While variations in the state of the ground in summer are due primarily to soil type, vegetation, and slope, the winter and spring seasons present additional challenges that are currently not addressed by most Army models. Because the depth of snow on the ground varies greatly through the winter, a prediction capability is needed for the rate of snow accumulation and melt that will allow predictions of snow depth. Ground freezing/thawing or the presence of mud can significantly change soil strength, requiring a prediction capability for soil moisture and freeze/thaw. This paper describes progress in the development of FASST, the Fast All-Seasons Soil STate model. FASST is a physically based model currently under development to predict the state of the sound using minimal computational time and resources. FASST predicts soil moisture, snow depth, frost depth, snowpack melt outflow, soil temperature, and soil strength on an hourly basis. The physical basis of the model is presented, and preliminary model predictions are compared to measured field data