This study had two goals. One was to gather baseline data about the soils before thinning and burning treatments for fuel reduction. The other goal was to develop a model that would predict soil characteristics. It was hoped that a model could be developed that would be reliable in the study area and the surrounding region. After analyzing her data, it was concluded that models based on it could only explain 30 to 40 % of the soil variability. The soils were too variable for the models to predict the characteristics. This was disappointing, but it was important information to have. It told researchers they would need to collect data from each point before and after treatment. If they did not compare before and after data from the same spot, the high variability of the soils would mask the treatment effects. It was originally thought that topography would be a key factor in explaining soil characteristics. This study was located in the dry Ponderosa pine and Douglas-fir forest in central Washington. Many soil-forming factors (climate, parent material, vegetative species) were relatively constant across the study area. Topography was highly variable and was expected to be an important factor explaining soil variability. Vegetative cover was the factor that was most consistently associated with soil characteristics. Models were developed from information gathered from 48 soil pits located in 12 experimental plots. Three pits in each plot were located at specific slope positions (ridge, backslope, and valley), and a fourth pit was sited in an area with little vegetation in order to gather a range of vegetative information. The models were tested against data collected from grid points distributed across the same study area. Information collected included aspect, slope, slope position, erosion, vegetation type (grass, herbaceous, or shrub), vegetative cover, presence of volcanic ash, soil bulk density, soil horizon type and thickness of soil horizons. In the future, researchers may build upon Dolan's study to develop models that predict soil characteristics in this area.