Theses and Dissertations at Montana State University (MSU)

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    Applying advanced materials characterization techniques for an enhanced understanding of firn and snow properties
    (Montana State University - Bozeman, College of Engineering, 2024) Schehrer, Evan Nicholas; Chairperson, Graduate Committee: Kevin Hammonds; This is a manuscript style paper that includes co-authored chapters.
    Understanding snow microstructure and stratigraphy is critical for enhancing modeling efforts and instrument validation for the polar regions and seasonal snow. Controlled laboratory experiments help with these efforts and are essential for enhanced comprehension of polar firn densification, snow metamorphism, avalanche mechanics, snow hydrology, and radiative transfer properties. This dissertation aims to characterize snow and ice as they relate to the mechanical and sintering properties of simulated firn subject to trace amounts of sulfuric acid (H 2SO 4). Studies were also developed to characterize faceted snow crystallographic orientation using electron backscatter diffraction (EBSD) and understand the observed reflectance of remote sensing instruments related to mapping changing snow microstructure. To investigate the effects of soluble impurities, 50 ppm H 2SO 4 and impurity-free ice grains were developed to simulate polar firn and then subjected to a series of unconfined uniaxial compression to monitor the effect in mechanical strength at different temperatures and strain rates. Meanwhile, the role of sintering is less defined for ice grains that contain impurities. Two experiments were developed to quantify sintering rates with H 2SO 4. One experiment tracked the changes in microstructure at isothermal conditions using X-ray computed microtomography over 264 days. A second experiment used angle of repose tests to characterize the subsecond sintering between H 2SO 4 and impurity-free ice grains. In addition, it is well known that snow has constantly changing microstructure once deposited during precipitation events. These changes have an immediate impact on the crystallographic and optical properties. Faceted snow crystals, collected from the field and artificially grown, were analyzed using EBSD to map vapor-deposited growth along the three ice (Ih) crystallographic planes. Moreover, validation of remote sensing techniques such as near-infrared hyperspectral imaging (NIR-HSI) and lidar is essential for accurate field measurements. In the laboratory, an intercomparison test was conducted for NIR-HSI and lidar to analyze bidirectional reflectance returns, mapping the effective grain size of snow under different microstructural conditions and during melt/freeze events and surface hoar growth.
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    When and where does irrigation water originate? Leveraging stable water isotopes and synthetic aperture radar to assess the complex hydrology of a snow-dominated catchment in southwestern Montana
    (Montana State University - Bozeman, College of Letters & Science, 2023) Rickenbaugh, Eliza Apple; Chairperson, Graduate Committee: Eric A. Sproles; This is a manuscript style paper that includes co-authored chapters.
    Many agricultural regions around the world rely on water stored in mountainous snowpacks for irrigation supply. Consequently, our current and future ability to produce food is threatened by more frequent, severe, and extended snow droughts. As these snow droughts intensify, water resource managers will need more efficient and accurate methods to characterize the snowmelt cycle and forecast water availability. Focusing on a montane headwater catchment in Southwestern Montana (423 km 2 in area, between 1465 m to 3270 m in elevation), we integrate in-situ and remotely sensed data to assess the relative contributions of groundwater and the current season's snowmelt to irrigation supply for water year (WY, Oct 1 - Sep 30) 2023. To understand the period over which snow contributes to stream water in this catchment, we analyze backscatter data from Sentinel-1 Synthetic Aperture Radar (SAR). This provides approximate dates of snowmelt runoff onset at 10 m resolution every twelve days. We find that the median date of snowmelt runoff onset in WY 2023 in this catchment was April 20, six days later than the 7-year median date of snowmelt runoff onset. To assess relative contributions to streamflow we compare stable water isotope ratios (deltaH2 and deltaO18) from biweekly samples of stream water at low elevations against monthly samples of snow and groundwater. Samples range in elevation from 1,475 m to 2,555 m. We find that stream water below the highest diversion point is predominantly composed of groundwater. Results demonstrate alignment between two disparate approaches for estimating temporal trends in snowpack contribution to stream flow. While our work focuses on a catchment in Montana, the efforts and approaches used are potentially applicable globally for agricultural regions that rely on snowmelt for irrigation.
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    Modeling snow water equivalent in complex mountainous terrain
    (Montana State University - Bozeman, College of Letters & Science, 2023) Beck, Madeline Makenzie; Chairperson, Graduate Committee: Eric A. Sproles; This is a manuscript style paper that includes co-authored chapters.
    The water stored in seasonal mountain snowpacks is a vital resource that approximately 20% of the world's population relies on for freshwater availability. However, accurately quantifying the amount of water stored in a snowpack, known as snow water equivalent (SWE), is difficult. The longest employed technique to quantify SWE is manual measurements. However, manual measurements of SWE are time intensive. As a result, researchers can collect relatively few point-based measurements across spatially extensive and complex regions. Automated weather stations may provide additional measurements of SWE and meteorological conditions but are expensive and difficult to maintain. Thus, reliable measurements of snow characteristics like SWE are scarce across time and space. A lack of extensive measurements causes data from few points to be extrapolated across spatially heterogeneous environments which increases uncertainty in estimates of water availability. Recent advances in satellite remote sensing allow researchers to observe snowpack dynamics across spatially continuous scales instead of relying solely on point-based measurements. However, current satellite technologies are incapable of collecting high- resolution snow data at the hillslope scale. Previous work has shown the importance of high elevation, hillslope-scale water storage reservoirs. Uncrewed aerial vehicles (UAVs) address the limitations of satellite remote sensing on the hillslope scale and are used to create high accuracy (<5 cm) models of snow depth. However, these models of snow depth provide no information on the amount of water stored without a value for snow bulk density. Thus, to capture hillslope dynamics of SWE, researchers must pair high-resolution models of snow depth with either directly measured or modeled bulk density of snow. This master's thesis integrates UAV-derived measurements of snow depth with modeled snow bulk density values to create continuous representations of hillslope-scale SWE across 9 flight dates. We found that each density modeling approach consistently underestimated SWE for the field site for each flight date except one. Further, each method of modeling snow bulk density was statistically indiscernible from each other. These findings highlight the heterogeneity of snow in mountainous terrain. In future work, bulk density models can be further parameterized to better represent site-specific values of SWE.
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    Wireless sensor network development for the purpose of measuring acceleration in snow
    (Montana State University - Bozeman, College of Engineering, 2023) Lesser, James Byron; Chairperson, Graduate Committee: Edward E. Adams
    A WSN (Wireless Sensor Network) was developed for the purpose of measuring snow acceleration in response to loading of various types. In its current state, the WSN is composed of seven nodes (radio enabled sensors) and one controller. Two dynamic ranges, +/- 10 g and +/- 40 g, allow for user adjustment based on the required sensitivity of measurement. Acceleration data is logged simultaneously across all active nodes; data from an analog accelerometer is stored by each node on a microSD card. Data throughput limits the maximal sampling frequency to 10 kHz at 8-bit precision, or 5 kHz at 10-bit precision. Empirical investigation of GEM (Green Environmental Monopropellant) as a tool for avalanche mitigation was conducted with the first iteration of the WSN. The GEM explosive is compared with the industry standard, Pentolite; the metrics of comparison are those of overpressure, impulse per unit area, and the resulting snow acceleration. This study showed the effectiveness of the WSN as a tool for measuring snow dynamic response under explosive loading. Additionally, an ECT (Extended Column Test) instrumented with the WSN on this day elicited continued development of the WSN. A detailed look at the components of the WSN provides the physical and electrical qualities focused on the nodes intended environment - seasonal snow. Theory of operation, and a standard operating procedure, provide fundamental knowledge for the end user. Modal testing was performed to characterize the vibration response of the node. Natural frequencies are identified within the bandwidth of the accelerometer, and it is shown that these frequencies are not present in signals collected in snow under impulsive loading. Acceleration data acquired by the WSN in a series of stability tests, conducted in the lab and in the field, demonstrate the utility of the system.
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    Thermal contact resistance at the snow-ice interface: dependence on grain size
    (Montana State University - Bozeman, College of Engineering, 2022) Dvorsak, Michael Alan; Chairperson, Graduate Committee: Kevin Hammonds
    Seasonal snow covers consist of many stratigraphic layers of varying density and, therefore, thermal conductivity. Weak layers can develop at the interface between these snow layers, reducing stability and increasing avalanche danger. While it is known that a bulk temperature gradient of -10?C m -1 across a snowpack enhances weak layer development via kinetic snow metamorphism, recent studies have identified an enhancement of this temperature gradient across snow interfaces. Previous work has determined that at a snow-ice interface, such as might exist around ice crusts in the snowpack, the driving factor for a temperature gradient enhancement could be a thermal contact resistance. This creates an interfacial phenomenon that induces a large temperature drop at the interface between two connected materials. The primary mechanism is a reduction of contact area for conduction to occur due to the porous nature of snow. Here, we further investigate the thermodynamics of a snow-ice interface by varying the grain size, which directly correlates to the total contact area. Within a controlled laboratory environment, a 4 mm ice lens was artificially made and placed between rounded grains that varied in size (1, 2, and 3 mm) between experiments. Temperature gradients of -10, -50, and -100 ?C m -1 were then applied across the sample. The temperature gradient was measured in-situ within 1 mm of the ice lens using micro-thermocouple measurements. The local temperature gradient at the snowice interface was found to be up to four times the imposed temperature gradient with 2-3 mm snow grains and near the bulk temperature gradient with the 1 mm grains. Following a thermal analysis, it was concluded that the enhancement in the temperature gradient was also due to a thermal contact resistance at the snow-ice interface. Utilizing timelapse x-ray computed microtomography, a microstructural characterization of the snow-ice interface was also performed, where it was observed that new ice crystal growth, kinetic snow metamorphism, and sublimation were all occurring simultaneously near the ice lens. These results indicate that the observed grain size near an ice lens or crust in a natural snowpack may be a pertinent parameter for better understanding kinetic snow metamorphism regimes that may exist at these interfaces.
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    Remote sensing of wet snow processes in a controlled laboratory environment
    (Montana State University - Bozeman, College of Engineering, 2022) Donahue, Christopher Paul; Chairperson, Graduate Committee: Kevin Hammonds; This is a manuscript style paper that includes co-authored chapters.
    Water flow through snow, due to snowmelt or rain-on-snow events, is a heterogeneous process that has implications for snowmelt timing and magnitude, snow metamorphism, albedo evolution, and avalanche hazard. Remote sensing technologies, ranging from ground-based to satellite-borne scales, offer a non-destructive method for monitoring seasonal snowpacks, although there is no single technique that is ideal for monitoring snow. Wet snow, specifically, presents a challenge to both optical and radar remote sensing retrievals. The primary aim of this dissertation was to develop wet snow remote sensing methods from within a controlled laboratory environment, allowing for precise characterization of snow properties. Experiments were conducted by preparing laboratory snow samples of prescribed structures and monitoring them during and after melt using hyperspectral imaging and polarimetric radar. Snow properties were characterized using X-ray computed microtomography, a dielectric liquid water content sensor, and serial-section reconstructions. In addition to laboratory experiments, hyperspectral imaging snow property retrieval methods were developed and tested in the field during wet snow conditions at the ground-based scale. The primary outcomes from this work were three new remote sensing applications for monitoring wet snow processes. First, a new hyperspectral imaging method to map effective snow grain size was developed and used to quantify grain growth due to wet snow metamorphism. Second, the optimal radiative transfer mixing model to simulate wet snow reflectance was determined and used to map liquid water content in snow in 2- and 3- dimensions. Lastly, snow melt progression was monitored using continuous upward-looking polarimetric radar and it was found, by comparison to 3-dimensional liquid water content retrievals from hyperspectral imaging, that the cross-polarized radar signal was sensitive to the presence of preferential flow paths. The work presented here highlights the utility of using a multi-sensor fusion approach to snow remote sensing. Although these laboratory remote sensing experiments were at a small scale, the remote sensing instrument response to specific snow conditions directly translates to larger scales, which is valuable to support algorithm development for ground, airborne, and spaceborne remote sensing missions.
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    Atmospheric processes related to deep persistent slab avalanches in the western United States
    (Montana State University - Bozeman, College of Letters & Science, 2019) Schauer, Andrew Robert; Chairperson, Graduate Committee: Jordy Hendrikx
    Deep persistent slab avalanches are a natural hazard that are particularly difficult to predict. These avalanches are capable of destroying infrastructure in mountain settings, and are generally unsurvivable by humans. Deep persistent slab avalanches are characterized by a thick (> 1 m) slab of cohesive snow overlaying a weak layer in the snowpack, which can fail due to overburden stress of the slab itself or to external triggers such as falling cornices, explosives, or a human. While formation of such snowpack structure is controlled by persistent weather patterns early in the winter, a snowpack exhibiting characteristics capable of producing a deep persistent slab avalanche may exist for weeks or months before a specific weather event such as a heavy precipitation or rapid warming pushes the weak layer to its breaking point. Mountain weather patterns are highly variable down to the local scale (1-10 m), but they are largely driven by atmospheric processes on the continental scale (1000 km). This work relates atmospheric circulation to deep persistent slab events at Mammoth, CA; Bridger Bowl, MT; and Jackson, WY. We classify 5,899 daily 500 millibar geopotential height maps into 20 synoptic types using Self-Organizing Maps. At each location, we examine the frequency of occurrence of each of the 20 types during November through January during major deep persistent slab seasons and compare those frequencies to seasons without deep persistent slab avalanches. We also consider the 72-hour time period preceding deep persistent slab avalanches at each location and identify synoptic types occurring frequently, as well as those rarely occurring prior to onset of activity. At each location, we find specific synoptic types that tend to occur at a higher rate during major deep persistent slab years, while minor years are characterized by different circulation patterns. We also find a small number of synoptic types dominating the 72-hour period prior to onset of deep slab activity. With this improved understanding of the atmospheric processes preceding deep persistent slab avalanches, we provide avalanche practitioners with an additional tool to better anticipate a difficult to predict natural hazard.
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    Using time lapse photography to document terrain preferences of backcountry skiers
    (Montana State University - Bozeman, College of Letters & Science, 2018) Saly, Diana Ilona Patricia; Chairperson, Graduate Committee: Jordy Hendrikx; Jordy Hendrikx, Karl W. Birkeland, Stuart Challender and Jerry Johnson were co-authors of the article, 'Using time lapse photograpy to document terrain preferences of backcountry skiers' submitted to the journal 'Journal of outdoor recreation and tourism' which is contained within this thesis.
    Avalanches are one of the greatest hazards for those recreating in snow covered mountainous terrain. In the past 20 years an average of 13 people in Canada and 27 people in the US are killed in avalanches each winter. Meanwhile, uncontrolled backcountry avalanche terrain use has significantly increased demonstrated by increased demand for avalanche education and increased sales in backcountry equipment. Lift-accessed backcountry (LABC), or avalanche terrain easily accessed from the ski resort, has seen increased usage since resorts opened boundaries in the mid-1990s. This has led to increased research interest in how people are using backcountry avalanche terrain. A simple method to reduce exposure to avalanche hazard is avoidance, however total avoidance is seldom practical. Professionals and recreational skiers alike mitigate avalanche hazard by managing exposure to terrain containing the avalanche hazard. Current research studies use GPS tracking to study the terrain metrics of backcountry skiers. This GPS research is limited to studying volunteers and professionals that willingly track and submit their trips. This approach ignores many users and thus presents a biased picture of use. This paper develops a method to capture the terrain metrics of all skiers on an avalanche-prone backcountry slope. A remote time-lapse camera focused on a high skier-use backcountry slope, (Saddle Peak, in the Bridger Mountain Range of southwest Montana, USA) captured skiers descending Saddle Peak in ten-second increments. Skier locations were digitized from the photos, then transformed onto a geo-referenced digital elevation model (DEM) such that terrain metrics could be applied to each skier location. Analysis of terrain metrics for each skier point compared slope, profile curvature (downslope), and plan curvature (cross slope) over days with different forecasted avalanche hazard. Terrain metrics on Considerable avalanche hazard days differed significantly from Moderate or Low avalanche hazard days (p-value < 0.001). Transformed data fell within a 49-m horizontal accuracy for all skier point locations with a 95% confidence interval. By capturing all skiers on a slope without their knowledge, the data collected provides a large and diverse data set of the terrain preferences of backcountry skiers under varying conditions.
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    Vehicles, grooming, and other factors affecting snowroad longevity in Yellowstone National Park
    (Montana State University - Bozeman, College of Engineering, 2018) Nelson, Molly McKellar; Chairperson, Graduate Committee: Edward E. Adams
    In winter, the National Park Service (NPS) at Yellowstone grooms snow that builds up on the park roads, making 'snowroads' passable by snowmobiles and snowcoaches. The NPS has recently allowed experimental snowcoaches on low-pressure tires (LPTs) in addition to traditional tracks. As they consider a permanent policy on these LPTS, they want to understand these vehicles' impacts on snowroads compared with those of traditional tracked vehicles and snowmobiles. They also want to know how to optimize other operations (e.g., grooming) to maintain quality roads that support safe travel through the park. This two-year field study investigated the snowroad quality in the park and factors influencing this quality. The approach involved data collection on both parkwide road conditions and individual vehicle passes. Both controllable and non-controllable factors were considered to provide information on their relative influence. Parkwide road quality analysis involved collecting GPS data on grooming activity, weather data from existing stations, road depth through radar measurements, traffic counts from motion-sensor cameras, hardness data, and snow sample analysis. The vehicle-by-vehicle impact study involved both subsurface and surface measurements in the road. Load cells, accelerometers, a high-speed, high-definition camera, a penetrometer, and a 'profilometer' provided measurements. Data analysis combined with existing literature provided insights into best practices for the NPS. Parkwide, snowroads harden throughout the season, with temperatures and traffic load being contributing factors. Grooming results in a harder road if snow disaggregation is followed by compaction, and with a longer set time between grooming and traffic. Individual vehicles' impacts are driven by surface interaction rather than motion at depth in the snowroad. On hard, groomed snowroads, both tracked and LPT snowcoaches can form ruts, but tracked vehicles continue to dig ruts deeper whereas LPT coaches' ruts level out and stop deepening with subsequent passes. This seems to be because LPTs form ruts primarily through compaction and tracked vehicles through snow displacement. Reduced tire pressures reduce rut formation and can harden the road. Results from this study demonstrate that LPT coaches should not be disallowed from Yellowstone based on road impacts. Other results will inform NPS operations to optimize grooming practices.
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    A Yellowstone snowroad rutting investigation: a comparison of tracks vs. tires and other contributing factors
    (Montana State University - Bozeman, College of Engineering, 2018) Phipps, Ry Edward; Chairperson, Graduate Committee: Daniel Miller
    Yellowstone National Park (YNP) has been experiencing more snowroad rutting in the last ten years. Additionally, YNP has recently (winter 2013 -2014) been experimenting with permitting large low-pressure tire vehicles to operate on the parks' snowroads. To gain a better understanding of snowroad degradation, YNP employed a team of snow scientists from Montana State University. In the winter of 2015, a large scale, two year, snowroad rutting study began in YNP. Parameters pertaining to snowroad strength and the difference in impact to the snowroads between tracked and wheeled vehicles were examined. This thesis in addition to Nelson's (2018) thesis produce a detailed overview of controllable and uncontrollable factors of maintaining and measuring impacts to the snowroads of Yellowstone National Park. Instruments were developed to collect data in the field and in the Sub-Zero Lab at Montana State University. These instruments allowed researchers to quantify crucial differences between vehicle types and the behaviors associated with them. Once data was collected, the data was post-processed in various ways to analyze trends pertaining to snowroad strength and degradation. With the data processed and analyzed, the profilometer and hardness data proved to be the most informative on snowroad degradation tendencies, however, the other instruments helped reinforce conclusions made with the hardness and profilometer data. The process of taking subsurface measurements on vehicle pass-bys, allowed researchers to confirm that rutting is most closely tied to vehicle-surface interactions (~ top 10 cms). It was determined that wheeled and tracked coaches can both cause ruts but by different processes. Wheeled vehicles are primarily causing ruts through compaction whereas tracked vehicles primarily cause ruts through a process of snow displacement. Ruts form from wheeled coaches but after subsequent passes the cross-sectional area of the rut tends to level off, especially when inflation pressure is decreased. While tracked vehicles' ruts continue to grow in size after subsequent passes. Additionally, snowroad hardness was affected differently between tracks and tires. Tracks and tires at higher pressures (> or = 62 kPa) tended to more often soften the snowroad, whereas lower pressure tires (< 62 kPa) tended to harden the snowroad.
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