Title:

Understanding Soil Frost and Snow Depth Dynamics at Kingman Farm

Understanding the dynamics of soil frost and snow variability is critical for improving climate models, hydrological forecasting, and determining agricultural practices in areas with cold seasons. Traditional factors, such as air temperature, are often used to give us insight on frozen ground conditions, but this method oversimplifies the complex interactions taking place between snow cover, soil properties, and solar radiation/land cover. This study investigates how soil frost depth varies in response to differences in snow depth, UV exposure, and the hydraulic conductivity of soil types across a forested landscape at 11 sites located on Kingman Farm in Madbury, New Hampshire. Using time-series field data, LiDAR-derived canopy cover maps, and soil type percentage maps, we create observations of snow and frost variability across Kingman. We hypothesize that soil frost variability is significantly influenced by solar radiation and soil properties. This research aims to provide a more nuanced understanding of soil frost formation and inform more accurate modeling of frozen ground processes. There appears to be a link between snow depth and frost variation, which may be due to the insulating effect of snow. Further research is needed to isolate the effects of snow depth on frost. We hope to further study the correlation between soil frost, soil type, and hydraulic conductance to find a relationship. During the analysis phase we used raster maps of soil and landcover attempt to find relationships. We hope to expand upon our findings in the next phase of this project

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