Sanow, Jessica, authorFassnacht, Steven, advisorSexstone, Graham, committee memberMcGrath, Dan, committee memberBauerle, William L., committee member2022-08-292023-08-222022https://hdl.handle.net/10217/235716Throughout the winter season, the snowpack becomes the surface-atmosphere boundary for the energy balance within the hydrologic cycle and is key for understanding and modeling meltwater availability, streamflow, and groundwater recharge. The aerodynamic roughness length, z0, is one metric to quantify the roughness characteristics of the snowpack surface. Roughness is a key component when analyzing the snowpack surface energy exchange because it exerts a strong influence on turbulent energy exchanges between the snowpack and atmosphere. Snow surface roughness fluctuates throughout the winter season due to snowpack accumulation and melt, redistribution, ecological, and meteorological influences. However, current hydrologic and energy balance models use a static z0 value despite the snowpack surface, and resulting z0 value, being spatially and temporally dynamic throughout the winter. Inclusion of a site specific, spatially, and temporally variable z0 is expected to improve hydrologic and energy balance models. Therefore, the following research investigates 1) comparing the anemometric and geometric methods of measuring z0, 2) the correlation between z0 and snow depth, 3) spatial and temporal variability of z0, 4) post-processing effects on z0 measurements, and 5) application of a variable z0 within the SNOWPACK model. Results of this study indicate a strong correlation when comparing geometric versus anemometrical methods of calculation. 30 wind profiles were compared to 30 corresponding geometrically calculated surface measurements using a terrestrial based LiDAR. These combined profiles had a Nash-Sutcliffe Coefficient of Efficiency of 0.75, an r2 of 0.96, a best fit slope of 0.98, and a Root Mean Square Error of 8.9 millimeters. The correlation between snow depth and z0 is variable depending on periods of melt, accumulation, and the initial snow-free roughness. The z0 was shown to be spatially and temporally variable across study sites. Interpolation resolution during post processing of z0 was found to modify z0 by several orders of magnitude. Variable z0 values were found to alter SNOWPACK model results within several of the output variables. The most sensitive output variables were sublimation, latent, and sensible heat due to the direct use of z0 within the calculations. These key findings highlight the importance of a variable z0. Inclusion of a variable z0 parameterization within models should be site specific, spatially and temporally dynamic, with special attention to post-processing steps.born digitaldoctoral dissertationsengCopyright and other restrictions may apply. User is responsible for compliance with all applicable laws. For information about copyright law, please see https://libguides.colostate.edu/copyright.roughnesshydrologysnowText