Includes bibilographical references.Plan B M.S. project, also called Engineering report.2020 Fall.The spatial characteristics and patterns of snow accumulation and ablation are used to estimate runoff volume, and timing of snowpack in mountainous regions across the western United States. This paper focuses on quantifying and characterizing the snow accumulation phase to investigate the spatio-temporal snow water equivalent (SWE) distribution in the Southern Rocky Mountains (SRM). Average daily SWE data were obtained from 90 Natural Resources Conservation Service (NRCS) Snow Telemetry (SNOTEL) data stations from southern Wyoming to northern New Mexico for the snow years between from 1982 to 2015. The stations range in elevation between 2268 and 3536 meters, and they were aggregated into seven sub-sets, based on elevation (high-low), latitude (north-south) and annual maximum SWE (above average, average, below average snow years). For the entire dataset and the seven data sub-sets, the standard deviation versus mean trajectories were developed. Each trajectory was comprised of average daily data points across the snow year, and each data point represented the standard deviation and mean SWE values from a sub-set of the SNOTEL stations. The trajectory can be used to describe and represent the change in the snowpack over the water year. Within each trajectory, the accumulation (increasing snowpack), hysteretic (increasing and decreasing snowpack) and ablation (decreasing snowpack) phases can be observed, characterized and modeled. For this paper, regression techniques were applied to the accumulation phase only. The regression form, average slope, maximum slope, minimum slope, and coefficient of determination values were extracted. These data were aggregated across elevation, latitude and snow year sub-sets, and spatial patterns were evaluated. Although the prior study (Egli and Jonas, 2009) used snow depth data, SWE data were the focus for this study. SWE data were available for a longer period of record than snow depth data in the SRM, and since SWE measures the mass of water rather than depth snow, the physical effects of snow settling were eliminated from the analysis. The snow settling signature appeared in the data as noise in the standard deviation versus mean depth trajectory plots, compared to SWE trajectory plots. The removal of this noise, i.e., use of SWE trajectory plots, yielded stronger correlations than were produced using snow depth data. The accumulation phase data most closely fit a truncated linear regression model, with the average slopes ranging between 0.36 to 0.40 (seven sub-sets), and the average standard deviation values ranging between 0.042 to 0.097. While the average accumulation slopes were fairly similar across all seven sub-sets, latitude impacted snowpack variability more significantly than did elevation. Within individual years, the accumulation snowpack in the south region was frequently more homogenous than the north region, but when aggregated across the 34-year study, the accumulation snowpack in the south region was less consistent on an inter-annual basis. In contrast to original hypotheses, when SWE were discretized by both elevation and latitude, the standard deviation of the accumulation slopes increased, rather than decreased. Snow year (above average, average, below average) was found to have a negligible impact on spatial homogeneity of the accumulation snowpack, except within the south-high sub-set, where range in average accumulation slope was 0.10. Generally, the snowpack was found to be more homogenous for below average snow years 3 compared to average or above average snow years, because below average snow years exhibited the lowest average accumulation slopes of the three categories
