Theses and Dissertations at Montana State University (MSU)
Permanent URI for this collectionhttps://scholarworks.montana.edu/handle/1/733
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Item 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.Item 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.Item 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.Item 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. AdamsA 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.Item 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 HammondsSeasonal 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.Item 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.