Browsing by Author "Fassnacht, Steven R., committee member"
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Item Open Access A climatological study of snow covered areas in the western United States(Colorado State University. Libraries, 2012) Moore, Cara, author; Kampf, Stephanie K., advisor; Fassnacht, Steven R., committee member; Sibold, Jason S., committee memberSnow accumulation and timing of melt affect the availability of water resources for the Western United States. Climate warming can significantly impact the hydrology of this region by decreasing the amount of precipitation falling as snow and altering the timing of snowmelt and associated runoff. Therefore, it is essential to characterize how regional climatology affects snow accumulation and ablation and to identify areas that may be especially sensitive to climate warming. This can help resource managers plan appropriately for hydrologic changes. This study utilizes 11-year average (2000 - 2010) MODIS Snow Cover Area (SCA) and Land Surface Temperature (LST) data and annual PRISM precipitation to determine how elevation, slope orientation, latitude, and continentality influence regional characteristics of SCA and LST for early April, early May, early June, and early July in four focus regions: the Colorado Rockies, the Sierra Nevada, the Washington Cascades, and the Montana Rockies. Then, using monthly averages of the 11-year MODIS SCA for January to June, we examine the spatiotemporal evolution of the snowpack and LST throughout the Western U.S. We use threshold values of January to July 11-year average SCA to determine the duration of snow persistence and delineate zones of intermittent, transitional, persistent and seasonal snow. Within the transitional and persistent snow zones, we use 11-year average LST data for January-February-March (LSTJFM) to categorize five different snow sensitivity zones. Areas with the highest winter average land surface temperatures are assumed to be most sensitive to climate warming, whereas areas with the lowest land surface temperature are assumed to be least sensitive. Results show that snow cover tends to increase with increasing elevation, and the elevation of snow cover is lower in higher latitudes, maritime environments, and most western slopes. Land surface temperature tends to decrease with increasing elevation, increasing latitude, and tends to be colder on most western slope sites. The largest divergence between eastern and western slope SCA and LST characteristics is observed in the Sierra Nevada, while little divergence is observed in the Colorado Rockies. Snow cover in the Western U.S. is observed predominantly along two main axes: from north to south along the Cascades and the Sierra Nevada, and from northwest to southeast along the axis of the Rocky Mountain Cordillera. The snow line is lowest in the Washington Cascades and highest in the Colorado Rockies; between these two areas a northwest/southeast elevation gradient is observed. The warmest snow zones (warmest JFMLST) are at lower elevations of the Cascades/Sierra Nevada and in the southwest, whereas coolest snow zones (coldest JFMLST) are in the interior northern Rockies, mid to higher elevations of the Cascades, and the higher elevations of the Colorado Rockies and the Sierra Nevada. The warmest snow zones are likely to be most sensitive to climate warming, as these locations are vulnerable to shifting toward intermittent winter snow cover.Item Open Access Changes in winter storm characteristics and lake-effect snow in convection-permitting regional climate simulations in the U.S.(Colorado State University. Libraries, 2019) Riesenberg, Mark Ryan, author; Rasmussen, Kristen L., advisor; Schumacher, Russ S., committee member; Fassnacht, Steven R., committee memberLake-effect snowfall events have extreme regional impacts with some of the largest snowfall totals on record. Previous studies hypothesize that in a future climate, less ice coverage will be present over the Great Lakes in winter, allowing for more latent and sensible heat fluxes released into the atmosphere. An investigation of the changes in winter season precipitation systems, including lake-effect snowstorms, uses two convection-permitting regional climate continuous 13-year simulations driven by: (1) ERA-Interim reanalysis and (2) ERA-Interim reanalysis plus a climate perturbation for the RCP8.5 scenario. These simulations are used to investigate meteorological and land surface changes in a future climate during the winter months across the U.S. Results from this study show that weak precipitation decreases, while moderate to stronger precipitation is enhanced in a future climate with strong signals over the Great Lakes. Therefore, a lake-effect snowstorm event in the Great Lakes region is used to examine the effects of a warming climate on mesoscale lake-effect snowstorm dynamics and their regional impacts. Analysis of these simulations shows that lake-effect snowstorms in a future climate may have enhanced snow accumulations downwind of the lakes due to more frequent ice-free conditions of the Great Lakes. Enhanced latent and sensible heat fluxes, as a result of less ice-coverage, add moisture and energy to the atmosphere to enhance storm development. The increase in surface fluxes are important for meteorological processes within the planetary boundary layer, which interact with the overlaying atmosphere. These interactions may change the mechanisms that are important for lake-effect snowfall events, such as the 850 mb to surface temperature differences, relative humidity, layer instability, and surface pressure. In addition, less ice coverage may enhance mesoscale circulations due to the thermal contrast (i.e., land-lake breeze) and differential surface roughness. This research will improve our understanding of the question, "What will today's weather look like in a future, warmer climate?" to examine possible socioeconomic and public safety implications of changing precipitation patterns in the winter season.Item Open Access Comparison of regionalization methods for a process based hydrologic model in major river basins of Colorado(Colorado State University. Libraries, 2010) Sanadhya, Pranay, author; Arabi, Mazdak, advisor; Fassnacht, Steven R., committee member; Salas, Jose D., committee memberDistributed watershed models are increasingly used for management of scarce water resources around the world. However, the utility of these models in ungaged or poorly gaged basins is a major issue in the field of hydrological sciences. Performance of watershed models cannot be evaluated for regions with paucity or unavailability of observed streamflow records; thus, a challenge is posed for the effective management of water resources in a region. Regionalization methods that relate watershed characteristics to model parameters are considered as a potential approach to overcome this challenge. The aim of this research is to analyze different regionalization methods and categorize the ones performing efficiently for the regionalization of the Soil and water assessment tool (SWAT) in five major river basins of Colorado. These River basins include: the Arkansas River basin at Canon City, the Cache la Poudre River basin at mouth of canyon, the Gunnison River basin above Blue Mesa dam, the San Juan River basin near Archuleta, and the Yampa River basin near Maybell. SWAT models were prepared for the study watersheds and their performance was evaluated corresponding to naturalized monthly streamflow available for these watersheds. Initially, these prepared models were reconciled with a global sensitivity analysis method known as Fourier Amplitude Sensitivity Test (FAST) to identify sensitive model parameters and the corresponding hydrologic processes they represent. Sensitivity analysis was performed for the two objective functions; mean monthly streamflow and the corresponding root mean square error (RMSE). Results of the sensitivity analysis showed that the majority of sensitive parameters were similar between the watersheds, resulting in a common parameter set selection for Colorado watersheds. Interestingly, sensitivity of parameters was observed to be varying depending upon the objective function. Through this part of the study, the significance of association between snowmelt and sub-surface hydrologic processes for generation of streamflow in mountainous watersheds was realized. Secondly, regionalization methods based on different approaches were used to compute the values of parameters identified as sensitive in the previous step. Later, performances of SWAT models developed for the study watersheds were evaluated by using the parameter values obtained from diverse regionalization methods. These methods included: arithmetic mean approach, approaches based on similarity indices (SI) related to watershed attributes, spatial proximity, Bayesian statistical analysis, and multisite calibration. In order to perform regionalization, a watershed was considered as ungaged and the parameter values for the watershed were obtained by using regionalization methods. Performances of these methods were evaluated by using the jack-knife cross validation technique and computing a performance measure ‘E’. The method based on the weighted arithmetic mean approach using SI and the multi-site calibration approach were observed as the most favorable regionalization methods for Colorado watersheds. Likewise, regionalization methods with average and rather poor performances were also identified. This research analyze the applicability of SWAT in mountainous regions and shows that the distributed hydrologic models like SWAT are capable of flow simulations and hydrologic modeling in mountainous regions like Colorado. Observed interactions between the SWAT parameters related to sub-surface processes and snow related processes helps in understanding the role of these hydrologic processes in magnitude and timing of streamflow generation in mountainous watersheds. This study shows that a great extent of similarity in terms of critical hydrologic processes exists between the major river basins of Colorado and thus helps in selecting a common SWAT parameter set for snow dominated mountainous regions. Performance of regionalization methods as analyzed in this study shows the importance of methods based on weighted arithmetic mean approach and the multi-site calibration approach for performing regionalization of SWAT in snow dominated mountainous regions.Item Open Access Effect of mountain pine beetle kill on streamflow generation mechanisms(Colorado State University. Libraries, 2016) Wehner, Christine Elisabeth, author; Stednick, John D., advisor; Fassnacht, Steven R., committee member; Niemann, Jeffrey, committee memberThe mountain pine beetle (Dendroctonus ponderosae) is an endemic species to Colorado, but a recent epidemic resulted in the mortality of millions of acres of lodgepole pine forest in Colorado since 2002. This study examined the effect of the mountain pine beetle kill on streamflow generation mechanisms using different tracer methods. Eleven nested watersheds with varying level of beetle-killed forest area (47.1% to 97.4%) were chosen for study. Groundwater, surface water, and precipitation samples were taken and analyzed for stable isotope composition (2H and 18O), specific conductivity, and chloride concentrations. Four methods were employed to partition sources of streamflow, or streamflow generation mechanisms (SGM), in beetle-killed watersheds. Stable isotopes (2H and 18O) were used to determine mean fractional contribution of each source (groundwater, rain, and snow) to streamflow. Rain and snow contribution were negatively correlated with beetle-killed forest area (p=0.08 and p=0.35 respectively). Groundwater was positively correlated with increasing beetle-killed forest area (p=0.23). Specific conductivity and chloride were each used in a 2-component (groundwater and precipitation) hydrograph separation. Using specific conductivity, beetle kill was negatively correlated with average groundwater contribution (ρ = -0.13), but the result was not significant (p = 0.71). Using chloride, the results were correlated (ρ=0.19), but not significant (p = 0.58). Specific conductivity and chloride measurements were then coupled in a 3-component (groundwater, rain, and snow) end member mixing analysis (EMMA). Beetle-killed forest area and fractional groundwater contribution were positively correlated (ρ=0.26), but not significant (p = 0.43). Watershed characteristics were examined to determine potential metrics of groundwater contribution. Mean watershed elevation displayed a significant negative correlation with mean groundwater contribution (p = 0.08).Item Open Access Estimation of snow microphysical properties with application to millimeter-wavelength radar retrievals for snowfall rate(Colorado State University. Libraries, 2011) Wood, Norman Bryce, author; Stephens, Graeme L., advisor; Cotton, William R., committee member; Fassnacht, Steven R., committee member; Kummerow, Christian D., committee member; Matrosov, Sergey Y., committee memberThe need for measuring snowfall is driven by the roles snow plays providing freshwater resources and affecting climate. Snow accumulations are an important resource for ecological and human needs and in many areas appear vulnerable to climate change. Snow cover modifies surface heat fluxes over areas extensive enough to influence climate at regional and perhaps global scales. Seasonal runoff from snowmelt, along with over-ocean snowfall, contributes to freshening in the Arctic and high-latitude North Atlantic oceans. Yet much of the Earth's area for which snowfall plays such significant roles is not well-monitored by observations. Radar reflectivity at 94 GHz is sensitive to scattering by snow particles and CloudSat, in a near-polar orbit, provides vertically resolved measurements of 94 GHz reflectivity at latitudes from 82 N to 82 S. While not global in areal coverage, CloudSat does provide observations sampled from regions where snowfall is the dominant form of precipitation and an important component of hydrologic processes. The work presented in this study seeks to exploit these observations by developing and assessing a physically-base snowfall retrieval which uses an explicit representation of snow microphysical properties. As the reflectivity-based snowfall retrieval problem is significantly underconstrained, a priori information about snow microphysical properties is required. The approaches typically used to develop relations between reflectivity and snowfall rate, so-called Ze-S relations, require assumptions about particle properties such as mass, area, fallspeed, and shape. Limited information about the distributions of these properties makes difficult the characterization of how uncertainties in the properties influence uncertainties in the Ze-S relations. To address this, the study proceeded in two parts. In the first, probability distributions for snow particle microphysical properties were assessed using optimal estimation applied to multi-sensor surface-based snow observations from a field campaign. Mass properties were moderately well determined by the observations, the area properties less so. The retrieval revealed nontrivial correlations between mass and area parameters not apparent in prior studies. Synthetic testing showed that the performance of the retrieval was hampered by uncertainties in the fallspeed forward model. The mass and area properties obtained from this retrieval were used to construct particle models including 94 GHz scattering properties for dry snow. These properties were insufficient to constrain scattering properties to match observed 94 GHz reflectivities. Vertical aspect ratio supplied a sufficient additional constraint. In the second part, the CloudSat retrieval, designed to estimate vertical profiles of snow size distribution parameters from reflectivity profiles, was applied to measurements from the field campaign and from an orbit of CloudSat observations. Uncertainties in the mass and area microphysical properties, obtained from the first part of this study, were substantial contributors to the uncertainties in the retrieved snowfall rates. Snowfall rate fractional uncertainties were typically 140% to 200%. Accumulations of snowfall calculated from the retrieval results matched observed accumulations to within 13%, however, when allowances were made for snowfall with properties likely inconsistent with the snow particle model. Information content metrics showed that the size distribution slope parameters were moderately to strongly constrained by the reflectivity observations, while the intercept parameters were determined primarily by the a priori constraints. Results from the CloudSat orbit demonstrated the ability of the CloudSat retrieval to represent a range of scene-dependent Ze-S relations.Item Open Access Long-term-robust adaptation strategies for reservoir operation considering magnitude and timing of climate change: application to Diyala River Basin in Iraq(Colorado State University. Libraries, 2020) Waheed, Saddam Qahtan, author; Grigg, Neil S., advisor; Ramirez, Jorge A., committee member; Bailey, Ryan T., committee member; Fassnacht, Steven R., committee memberVulnerability assessment due to climate change impacts is of paramount importance for reservoir operation to achieve the goals of water resources management. This requires accurate forcing and basin data to build a valid hydrology model and assessment of the sensitivity of model results to the forcing data and uncertainty of model parameters. The first objective of this study is to construct the model and identify its sensitivity to the model parameters and uncertainty of the forcing data. The second objective is to develop a Parametric Regional Weather Generator (RP-WG) for use in areas with limited data availability that mimics observed characteristics. The third objective is to propose and assess a decision-making framework to evaluate pre-specified reservoir operation plans, determine the theoretical optimal plan, and identify the anticipated best timeframe for implementation by considering all possible climate scenarios. To construct the model, the Variable Infiltration Capacity (VIC) platform was selected to simulate the characteristics of the Diyala River Basin (DRB) in Iraq. Several methods were used to obtain the forcing data and they were validated using the Kling–Gupta efficiency (KGE) metric. Variables considered include precipitation, temperature, and wind speed. Model sensitivity and uncertainty were examined by the Generalized Likelihood Uncertainty Estimation (GLUE) and the Differential Evolution Adaptive Metropolis (DREAM) techniques. The proposed RP-WG was based on (1) a First-order, Two-state Markov Chain to simulate precipitation occurrences; (2) use of Wilks' technique to produce correlated weather variables at multiple sites with conservation of spatial, temporal, and cross correlations; and (3) the capability to produce a wide range of synthetic climate scenarios. A probabilistic decision-making framework under nonstationary hydroclimatic conditions was proposed with four stages: (1) climate exposure generation (2) supply scenario calculations, (3) demand scenario calculations, and (4) multi-objective performance assessment. The framework incorporated a new metric called Maximum Allowable Time to examine the timeframe for robust adaptations. Three synthetic pre-suggested plans were examined to avoid undesirable long-term climate change impacts, while the theoretical-optimal plan was identified by the Non-dominated Sorting Genetic Algorithm II. The multiplicative random cascade and Schaake Shuffle techniques were used to determine daily precipitation data, while a set of correction equations was developed to adjust the daily temperature and wind speed. The depth of the second soil layer caused most sensitivity in the VIC model, and the uncertainty intervals demonstrated the validity of the VIC model to generate reasonable forecasts. The daily VIC outputs were calibrated with a KGE average of 0.743, and they were free from non-normality, heteroscedasticity, and auto-correlation. Results of the PR-WG evaluation show that it exhibited high values of the KGE, preserved the statistical properties of the observed variables, and conserved the spatial, temporal, and cross correlations among the weather variables at all sites. Finally, risk assessment results show that current operational rules are robust for flood protection but vulnerable in drought periods. This implies that the project managers should pay special attention to the drought and spur new technologies to counteract. Precipitation changes were dominant in flood and drought management, and temperature and wind speed changes effects were significant during drought. The results demonstrated the framework's effectiveness to quantify detrimental climate change effects in magnitude and timing with the ability to provide a long-term guide (and timeframe) to avert the negative impacts.Item Open Access Numerical modeling of streamflow accretion by conjunctive use at Tamarack Ranch State Wildlife Area, Colorado(Colorado State University. Libraries, 2013) Roudebush, Jason A., author; Stednick, John D., advisor; Ronayne, Michael J., committee member; Fassnacht, Steven R., committee memberConjunctive use of groundwater at Tamarack Ranch State Wildlife Area is used to augment streamflow in the Platte River during low flow periods, critical for aquatic species. As part of a cooperative Tri-State Agreement (TSA) with Nebraska and Wyoming, Colorado's portion of the TSA is to pump alluvial groundwater (up to 1,233 ha-m) during periods of unappropriated flow in the river, to recharge ponds located in upland eolian sand deposits, where the water infiltrates into the ground and returns to the river at a later time. Understanding the location of these recharge ponds and the timing of streamflow accretion is critical for evaluating the effectiveness of recharge operations at Tamarack but has proven difficult to physically measure. To better understand the streamflow-aquifer system changes, a detailed numerical model was created using the MODFLOW Streamflow-Routing technique to simulate physically based groundwater-surface water interaction from managed groundwater recharge. The simulation modeled groundwater pumping from December 2012 through March 2013 and showed that managed groundwater recharge at Tamarack is producing a quantifiable contribution to streamflow in the desired period of April to September and on the Tamarack property. Streamflow accretion began ten days after the pumps were turned off and the center of mass arrived at the river 16 days later. The total volume of streamflow accretion simulated in this study at the Red Lion Bridge was 878,000 m3, 13% of the 6,887,000 m3 of groundwater pumped into the recharge ponds in water year 2013. Streamflow accretion had not fully diminished by the end of model simulation in August 2013, warranting further study to better account for all streamflow accretions.Item Open Access Response of streamflow and stream chemistry to pine beetle induced tree mortality across northern Colorado(Colorado State University. Libraries, 2015) Menger, Ashley Lynn, author; Stednick, John D., advisor; Fassnacht, Steven R., committee member; Ronayne, Michael C., committee memberThe lodgepole pine (Pinus contorta) forests of western North America recently endured the most severe insect-induced mortality in recorded history. The hydrological and biogeochemical impacts of mountain pine beetle (Dendroctonous ponderosae) (MPB) induced die-off are uncertain even with recent conceptual and physical research. The purpose of this study is to provide insight into changes in annual water yield, streamflow generation mechanisms and stream water nutrient concentrations due to the recent MPB epidemic. To evaluate the possible impact, watersheds with varying amounts of MPB induced tree mortality in the north-central Colorado Rocky Mountains are examined. It was hypothesized that the canopy loss associated with the MPB epidemic has led to significant changes in annual water yield, streamflow generation mechanisms and stream water total nitrogen, nitrate, and total organic carbon (TOC) concentrations. Data stationarity analysis using the Mann-Kendall test showed no significant trend in annual water yield from 1991-2013 with increasing beetle-killed area. Annual mean isotopic signature (¹⁸O and ²H) analysis of rain, snow, soil water and stream water showed snow (44%) to be the largest contributor to annual streamflow followed by soil water (38%) and rain (14%). No correlation was found between any mean annual source water and percent beetle-killed area. Isotopic analysis of peak streamflow showed soil water (43%) and snow (42%) to be the largest contributors to peak flow. Snow's streamflow contribution was negatively correlated (p = 0.02) to percent beetle-killed indicating that snow as a source for streamflow decreased as a watershed had a higher proportion of MPB-killed trees. No correlation was found between rain or soil water as source waters to peak streamflow and percent beetle-killed. Stream water total nitrogen, nitrate and TOC concentrations and fluxes were not significantly changed by the MPB epidemic. There was no correlation between stream water total nitrogen, nitrate or TOC concentrations or flux and percentage of beetle-killed area. Even though Colorado's forests have been significantly impacted by MPB induced tree mortality, this study suggests that percentage of beetle-killed watershed area has had little impact on annual water yield and stream water nutrient levels. Source water contribution to streamflow is impacted as a result of MPB induced tree mortality as the fraction of peak streamflow from snow decreased with increasing percentage of beetle-killed area.Item Open Access Snowmelt runoff analysis and modeling for the upper Cache la Poudre River basin, Colorado(Colorado State University. Libraries, 2009) Richer, Eric E., author; Kampf, Stephanie K., advisor; Fassnacht, Steven R., committee member; Arabi, Mazdak, committee memberThe Cache la Poudre River is a vital water source in Northern Colorado, and it exhibits high variability in annual water yield. This research examines sources of variability in snowmelt runoff as a means of identifying methods that could help improve streamflow prediction for the basin. The objectives of this thesis are to: (1) develop a naturalized flow record for the river and determine the effects of flow modification on the magnitude and timing of discharge; (2) analyze relationships between snow cover distributions and naturalized discharge to identify important areas for runoff production; and (3) evaluate the ability of the Snowmelt Runoff Model (SRM) to simulate seasonal hydrographs. Naturalized flow records were developed by accounting for all diversions from the river, inputs of foreign water via trans-basin diversions, and reservoir operations. Moderate Resolution Imaging Spectroradiometer (MODIS) 8-day snow cover products were obtained for the snowmelt season, mid-March through June, from 2000-2006. Snow cover depletion was analyzed within spatial subsets of sub-basins and elevation zones, and regression analyses were used to compare snow covered area (SCA) to naturalized discharge (Q). To investigate spatial and temporal snow distribution trends, probability of snow cover datasets were derived, which show the frequency of snow cover for different parts of the basin. Using these SCA data, the SRM was then configured to simulate snowmelt runoff hydrographs for the basin using both optimized and standard sets of model parameters. Daily hydrographs were simulated from March 1 to September 30 for each year in the 2000-2006 study period. Results show that flow modification delayed hydrograph timing and reduced water yields for all years included in the study period. The naturalized hydrograph displayed a wide range of relationships to SCA depletion patterns in the basin. At low and high elevations in the basin, SCA patterns had poor relationships to naturalized discharge. Snow cover depletion in middle elevations, however, had a much stronger relationship to discharge, with steady snow cover depletion occurring in these areas during hydrograph rise. Snow cover analyses point to strong elevation dependence in runoff generation, with most runoff coming from a small area in the basin above a mid-elevation snow cover transition zone. Snow cover data prove useful for configuring snowmelt runoff simulations, and the SRM simulated seasonal hydrographs with good model performance (Nash-Sutcliffe coefficient of efficiency > 0.9) when calibrated to the naturalized hydrographs for individual years. This suggests that the SRM could be used to generate seasonal streamflow forecasts given appropriate selection of parameter values and input variables. These conclusions all point to the utility of long-term snow cover datasets for improved water resources planning and management in snowmelt dominated mountain basins.Item Open Access The fate of Dinwoody Glacier: present state of mass balance and downstream impacts of glacier runoff(Colorado State University. Libraries, 2018) Stamper, Brooke E., author; Bliss, Andrew K., advisor; Grigg, Neil S., committee member; Fassnacht, Steven R., committee memberThe Wind River Range in Wyoming supports many of the few remaining continental glaciers of the North American Rocky Mountains; the glacier meltwater runoff feeds four major river systems within the U.S. West. Runoff from glaciers affects downstream ecosystems by influencing the quantity, seasonality, and chemistry of the water. We describe the present state of Dinwoody Glacier, the fourth largest glacier in the Wind River Range. We utilize photogrammetry, snow depth measurements, and ablation measurements to characterize surface mass balance for summer of 2017. Localized and nearby stream gauge measurements help to quantify glacial meltwater runoff inputs to Dinwoody Creek. Both of these methods allowed us to put the changes of the Dinwoody Glacier into the broader context of the Missouri River Watershed. If melted, Dinwoody Glacier would no longer provide a reliable source of melt water for thousands of people living in the Missouri River Watershed. Understanding how shrinking glaciers and decreasing melt-water runoff will impact communities and ecosystems downstream is critical for effective environmental management. The response of the Wind River glaciers to future climate is uncertain; however, past research has shown declines in glacial mass, snow cover, snowmelt timing and stream power. The data we collected in the summer of 2017 tells the story of a quickly diminishing and critical resource despite 2017 being a uniquely wet and cold year. While glacier meltwater runoff contributions to Dinwoody Creek were above average, the Accumulation Area Ratio for Dinwoody Glacier in 2017 was 21% suggesting a glacier in severe recession.Item Open Access The spatial distribution patterns of snow water equivalent data for the accumulation phase across the southern Rocky Mountains(Colorado State University. Libraries, 2020) Schrock, Isaac J. Y., author; Grigg, Neil, advisor; Fassnacht, Steven R., committee member; Sharvelle, Sybil, committee memberThe 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.