Mountain Scholar :: Browsing by Author "Fassnacht, Steven, committee member"

Browsing by Author "Fassnacht, Steven, committee member"

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Open Access
Changes in the snowpack of the Upper Colorado River basin in a warmer future climate
(Colorado State University. Libraries, 2023) Sherman, Erin Alexys, author; Rasmussen, Kristen, advisor; Schumacher, Russ, committee member; Fassnacht, Steven, committee member
Water is a crucial factor to sustaining life on Earth. Snow acts as a reservoir for water, providing storage during the cold seasons and freshwater resources throughout the warmer months. Streamflow in the upper Colorado River Basin is primarily contributed by seasonal mountain snowmelt that provides critical freshwater resources to humans and wildlife, effectively connecting ecological, hydrological, and atmospheric systems. Global Climate Models (GCMs) and regional climate models do not represent the complex processes that can impact snowpack growth, evolution, and melting, thus they often rely on parameterizations to represent such processes. SnowModel is a high-resolution snowpack-evolution modeling system that can simulate processes such as blowing snow redistribution and sublimation, forest canopy interception, and snow-density evolution. To investigate how snowpack in the Upper Colorado Basin may change in a future warmer climate, high-resolution convection-permitting regional climate atmospheric model simulations at 4-km horizontal grid spacing are used to provide input conditions to drive SnowModel at 100-m in the current and future climate for 13 years. Results show that the average snow season will be shorter in the future, reducing the days that the snowpack can accumulate. In addition, analysis of the characteristics of precipitation in the simulations shows a ~150% increase in convective precipitation frequencies in the winter months, indicating shifts in the character of precipitation in a future climate. Liquid precipitation in winter increases ~200% in a future climate as a result of warmer air temperatures. In contrast, solid precipitation stays roughly the same in the winter, but decreases about 25 percent in the fall and spring. A case study analysis of the high-impact snowstorm on 17-19 March 2003 that delivered between 30-70 inches of snow along the Colorado Front Range in a current and future climate shows a shift from a snow-dominant to a rain-dominant event, as well as increases in moisture and convective precipitation frequencies. The simulated changes in the snowpack of the Upper Colorado River Basin will likely have detrimental impacts on freshwater resources and food production in a future climate that will undoubtedly impact a multitude of humans and ecosystems in the western United States.
Open Access
Effects of mountain pine beetle caused tree mortality on streamflow and streamflow generation mechanisms in Colorado
(Colorado State University. Libraries, 2014) Maggart, Ariann Lenore, author; Stednick, John D., advisor; Fassnacht, Steven, committee member; Ronayne, Michael, committee member
The mountain pine beetle (Dendroctonus ponderosae Hopkins) (MPB), an endemic beetle in Colorado forests, saw dramatic population growth in the 1990's. As a result of this epidemic, the mountain pine beetle killed large tracts of forest as it spread. To evaluate the effects of MPB caused tree mortality on streamflow and streamflow generation mechanisms multiple investigative approaches were taken. In north-central Colorado, 21 watersheds representing minimally to highly affected watershed areas were chosen. Physical watershed characteristics were determined through a geographic information system. Long-term streamflow records for each watershed were assessed for data stationarity and change-points in peak flow, date of peak flow and annual water yield. Peak streamflow, date of peak streamflow and annual water yield all had stationarity. Since data were stationary, change-point analyses were not conducted. Streamflow, groundwater and precipitation samples were collected and analyzed for stable isotope concentrations. Isotopes of 2H and 18O partition source water contributions to streamflow from precipitation as snow or rain and groundwater (as a surrogate for groundwater). Annual δ2H and δ18O isotopic signatures for streamflow and streamflow source waters, as snow, groundwater and rain, were determined and used to partition source water contributions to streamflow for each watershed. In general, during the 2012 water year, source water contributions to streamflow were as follows: snow 60%, groundwater 20% and rain 20%. The correlations between snow, groundwater and rain contributions to streamflow and MPB killed area were not statistically significant at α ≤ 0.05 (psnow = 0.582, pgroundwater = 0.543 and p;rain = 0.897). While Colorado has suffered extensive forest kill since the onset of the MPB epidemic, the results of this study suggest that MPB killed watershed area has little to no effect on peak streamflow, date of peak streamflow, annual water yield or streamflow generation mechanisms.
Open Access
Evaluating L-band radar for the future of snow remote sensing
(Colorado State University. Libraries, 2024) Bonnell, Randall, author; McGrath, Daniel, advisor; Fassnacht, Steven, committee member; Kampf, Stephanie, committee member; Marshall, Hans-Peter, committee member; Ronayne, Michael, committee member
Snowpack monitoring is essential because seasonal snowpacks provide water for billions of people, support streamflow and ecosystems, and are a fundamental component of the Earth's energy system. However, no current snowpack monitoring system is capable of measuring snow water equivalent (SWE), the most important snowpack hydrologic variable, accurately and at high spatiotemporal (<500 m, 20 km of nearly continuous relative permittivity estimates, and thereby bulk density, from combined near-coincident measurements of GPR two-way travel times and lidar snow depths at three different field sites and in both dry and wet snow conditions. Variogram analyses were conducted and revealed a 19 m median correlation length for relative permittivity and density in dry snow. For wet snow, the correlation length increased to >30 m. I then leveraged the derived densities to evaluate six snow density models to better understand the limitations of these models within lidar and radar remote sensing methods. Two models yielded densities that estimated SWE within ±10% when SWE exceeded 400 mm, but model uncertainty increased to >20% when SWE was less than 300 mm. Thus, the refinement of these density models and the development of future density models is a high priority to fully realize the potential of SWE remote sensing methods. The L-band (1–2 GHz) InSAR technique for measuring changes in SWE (ΔSWE) is a promising method for SWE retrievals because the longer wavelength (~0.25 m) has minimal interaction with the snowpack microstructure and has increased canopy penetrative capabilities. In Chapter 3, I evaluated 10 L-band InSAR pairs collected by NASA UAVSAR near Cameron Pass, Colorado with GPR and terrestrial lidar measurements of ΔSWE in open meadows and burned forests. For single InSAR pairs, UAVSAR ΔSWE retrievals yielded an overall Pearson's correlation coefficient of 0.72–0.79, with a RMSE of 19–22 mm. I expanded the analysis beyond the locations of GPR and lidar surveys to evaluate the time series of UAVSAR SWE retrievals by including measurements of SWE from seven automated stations and found a RMSE of 42 mm. These findings support the use of this technique in unforested areas with dry snow conditions for the upcoming L-band NISAR satellite mission Given the findings of Chapter 3 and the canopy penetration capabilities of L-band radar, I designed Chapter 4 to evaluate the influence of forest cover on the UAVSAR signal. In Chapter 4, I evaluated eight L-band InSAR pairs collected by UAVSAR over the montane forests of Fraser Experimental Forest, Colorado with manually surveyed snow depths and snow pits and a pair of airborne lidar surveys. Compared with in situ measurements, I found that forest cover fractions <40% yielded RMSEs of ~15 mm, whereas RMSE more than doubled for forest cover fractions >50%. Further, normalized cumulative UAVSAR SWE and normalized lidar snow depths yielded identical statistical distributions for forest cover fractions <50% across the full study area, but these distributions diverged as forest cover fraction increased. Thus, forest cover fraction is a significant source of uncertainty for L-band InSAR retrievals of SWE, but this technique may be the first space-borne technique capable of retrieving SWE below non-dense forest canopy without any a priori information.
Open Access
Fate of snowmelt in complex subalpine terrain
(Colorado State University. Libraries, 2016) Webb, Ryan W., author; Gooseff, Michael, advisor; Fassnacht, Steven, committee member; Ramirez, Jorge, committee member; Niemann, Jeffrey, committee member
Snow is important to human communities and natural ecosystems around the world that rely on snowmelt runoff for as much as 80% or more of streamflow. In addition to streamflow, snowmelt can drive hydrological processes such as groundwater recharge, soil moisture dynamics, forest ecosystem dynamics, and potentially cause high damage flooding. Multiple environmental controls will cause snow to vary in depth, density, and snow crystal metamorphism causing a complex three dimensional matrix of ice, air, water vapor, and liquid water (during melt) that is non-uniform across a landscape and varies in time at the daily and even hourly scale. Because of the non-uniform dynamics of snow and snowmelt processes, multi-dimensional studies are necessary to determine hydrological flow paths during spring snowmelt. The goal of this dissertation is to investigate the physical processes that control the fate of snowmelt during spring runoff in complex subalpine terrain. These processes were investigated through 1) observing the diurnal pattern of snowmelt in Colorado's Front Range, 2) testing the diversion potential of hydraulic barriers within a layered snowpack through numerical modeling, 3) collecting field data to investigate the spatio-temporal patterns of water distribution during spring snowmelt, and 4) analyzing a network of soil moisture sensors in California's Southern Sierra Nevada to determine the variability of infiltration in a headwater catchment. Observations of the diurnal temporal pattern of snowmelt resulted in a relatively simple method to capture the outflow from a snowpack using hourly snow water equivalent data. The resulting temporal pattern is comparable to design rainfall distribution types specifically for snowmelt that can be important for flood risk analysis or design of channels in previously unmonitored headwater systems. The observed temporal patterns were also used to inform numerical simulations in the modeling package TOUGH2 that utilized additional data from NASA CLPX datasets to simulate meltwater percolation through a melting snowpack. Results of this component of the dissertation displays the potential for hydraulic barriers to form on south, flat, and north aspect hillslopes and potentially divert downward flowing water at similar scales as the topographic or land cover variability. Hydraulic barriers in simulations were permeability barriers only on the south and flat aspect slopes and capillary barriers only on the north aspect slopes. The dynamic nature of a snowpack in the presence of water implies that the capillary barriers are likely short-lived relative to permeability barriers and thus capillary barriers may be important at the day or week timescale and permeability barriers may be more influential at the monthly or seasonal time scale. Field observations near Steamboat Springs, Colorado were made for above normal, relatively normal, and below normal snow seasons including measurements of bulk snow water equivalent and soil moisture on varying slope, aspect, soil parameters, and canopy conditions with results displaying the variability from these influences. Evidence was present of meltwater flowing above the soil surface and through the snowpack. At the base of the north aspect slope the water table rose above the soil surface and the snowpack added storage capacity to the vadose zone. The variability of snowmelt and resulting soil moisture and infiltration dynamics was supported by the analysis of a network of soil moisture sensors in California’s Southern Sierra Nevada. This component of the dissertations displayed the high variability of wetting and drying dynamics beneath a snowpack at the sub-hillslope and watershed scale. Results of this dissertation display that the snowpack acts as an extension of the vadose zone during spring snowmelt and that one-dimensional assumptions are not appropriate in headwater catchments during this time. Consideration of the snowpack and soil together will improve modeling, remote sensing, and water balance calculations for hydrologic studies during spring snowmelt and improvements upon allocation of streamflow, groundwater recharge, and evapotranspiration.
Restricted
|Harm harness harmony|
(Colorado State University. Libraries, 2014) Kenny, Michael, author; Beachy-Quick, Dan, advisor; Steensen, Sasha, advisor; Fassnacht, Steven, committee member
A single agent perceiver explores the arctic self via four elemental forms.
Open Access
Isotope and noble gas study of three aquifers in central and southeast Libya
(Colorado State University. Libraries, 2013) Al Faitouri, Mohamed S. E., author; Sanford, William, advisor; Ronayne, Michael, committee member; Fassnacht, Steven, committee member; Waskom, Reagan, committee member
To view the abstract, please see the full text of the document.
Open Access
Landslide riskscapes in the Colorado Front Range: a quantitative geospatial approach for modeling human-environment interactions
(Colorado State University. Libraries, 2021) Hicks, Heather Brainerd, author; Laituri, Melinda, advisor; Fassnacht, Steven, committee member; Grigg, Neil, committee member; Rathburn, Sara, committee member
This research investigated the application of riskscapes to landslides in the context of geospatial inquiry. Riskscapes are framed as a landscape of risk to represent risk spatially. Geospatial models for landslide riskscapes were developed to improve our understanding of the spatial context for landslides and their risks as part of the system of human-environment interactions. Spatial analysis using Geographic Information Systems (GIS) leveraged modeling methods and the distributed properties of riskscapes to identify and preserve these spatial relationships. This dissertation is comprised of four separate manuscripts. These projects defined riskscapes in the context of landslides, applied geospatial analyses to create a novel riskscape model to introduce spatial autocorrelation methods to the riskscape framework, compared geostatistical analysis methods in these landslide riskscape assessments, and described limitations of spatial science identified in the riskscape development process. The first project addressed the current literature for riskscapes and introduced landslides as a measurable feature for riskscapes. Riskscapes are founded in social constructivist theory and landslide studies are frequently based on quantitative risk assessment practices. The uniqueness of a riskscape is the inclusion of human geography and environmental factors, which are not consistently incorporated in geologic or natural hazard studies. I proposed the addition of spatial theory constructs and methods to create spatially measurable products. I developed a conceptual framework for a landslide riskscape by describing the current riskscape applications as compared to existing landslide and GIS risk model processes. A spatial modeling formula to create a weighted sum landslide riskscape was presented as a modification to a natural hazard risk equation to incorporate the spatial dimension of risk factors. The second project created a novel method for three geospatial riskscapes as an approach to model landslide susceptibility areas in Boulder and Larimer Counties, Colorado. This study synthesized physical and human geography to create multiple landslide riskscape models using GIS methods. These analysis methods used a process model interface in GIS. Binary, ranked, and human factor weighted sum riskscapes were created, using frequency ratio as the basis for developing a weighting scheme. Further, spatial autocorrelation was introduced as a recommended practice to quantify the spatial relationships in landslide riskscape development. Results demonstrated that riskscapes, particularly those for ranked and human factor riskscapes, were highly autocorrelated, non-random, and exhibited clustering. These findings indicated that a riskscape model can support improvements to response modeling, based on the identification of spatially significant clustering of hazardous areas. The third project extended landslide riskscapes to measurable geostatistical comparisons using geostatistical tools within a GIS platform. Logistic regression, weights of evidence, and probabilistic neural networks methods were used to analyze the weighted sum landslide riskscape models using ArcGIS and Spatial Data Modeler (ArcSDM). Results showed weights of evidence models performed better than both logistic regression and neural networks methods. Receiver Operator Characteristic (ROC) curves and Area Under the Curve validation tests were performed and found the weights of evidence model performed best in both posterior probability prediction and AUC validation. A fourth project was developed based on the limitations discovered during the analytical process evaluations from the riskscape model development and geostatistical analysis. This project reviewed the issues with data quality, the variations in results predicated on the input parameters within the analytical toolsets, and the issues surrounding open-source application tools. These limitations stress the importance of parameter selection in a geospatial analytical environment. These projects collectively determined methods for riskscape development related to landslide features. The models presented demonstrate the importance and influence of spatial distributions on landslide riskscapes. Based on the proposed conceptual framework of a spatial riskscape for landslides, weighted sum riskscapes can provide a basis for prioritization of resources for landslides. Ranked and human factor riskscapes indicate the need to provide planning and protection for areas at increased risk for landslides. These studies provide a context for riskscapes to further our understanding of the benefits and limitations of a quantitative riskscape approach. The development of a methodological framework for quantitative riskscape models provides an approach that can be applied to other hazards or study areas to identify areas of increased human-environment interaction. Riskscape models can then be evaluated to inform mitigation and land-use planning activities to reduce impacts of natural hazards in the anthropogenic environment.
Embargo
Mixed populations flood frequency analysis in the mid-Atlantic region of the United States
(Colorado State University. Libraries, 2023) Breverman, Avital, author; Arabi, Mazdak, advisor; Morrison, Ryan, committee member; Fassnacht, Steven, committee member
In many parts of the United States, floods at a single site are caused by multiple mechanisms. Flood mechanisms can broadly be classified as meteorologic, land surface processes, and disturbances. These non-homogeneous flood series are typically referred to as mixed populations. While the two latest revisions of federal flood frequency guidelines, published in 1982 and 2019, identified the treatment of mixed populations as an area of future research, no quantitative guidance exists on the classification of flood events or the incorporation of flood types into frequency analyses. Without quantitative guidance on the treatment of mixed populations in flood frequency analyses, there is the potential for considerable variability in frequency-based flood estimates. The treatment of a flood series resulting from a mixed population violates the assumption that floods at a site are independent and identically distributed. To avoid this issue, separate statistical models should be fit to floods arising from different mechanisms and the resulting curves should be combined to produce flood quantiles. Mixed population and flood typing literature has focused primarily on the western United States. In comparison, the Mid-Atlantic region of the United States is characterized by complex meteorology and numerous flood causal mechanisms but has been studied less frequently in mixed population literature. In addition to the absence of guidance of mixed populations, flood frequency approaches in the United States use the annual maximum series, or the maximum flow each year. The peaks-over-threshold, or partial duration series, approach to selecting flood events has the potential to increase the information content in a flood series which is important when subdividing flood events by causal mechanism. The objectives of the study are to examine: (1) flood typing based on gridded meteorologic products, (2) the advantages of using partial duration series over annual maximum series when performing a flood frequency analysis with consideration of flood type, and (3) the difference in flood quantiles from the proposed combined population methodology compared to those from the current mixed flood frequency analysis. An automated flood classification procedure was developed using gridded meteorologic products. The automated classification procedure was validated manually using historic storm publications. Flood frequency analyses were performed using both partial duration and annual maximum flood series. The method is applied within the Lehigh River watershed in eastern Pennsylvania. While the flood frequency analysis results varied across the watershed, separation of flood series by causal mechanism generally resulted in higher flood quantiles than those obtained from mixed flood series. Design floods based on the treatment of flood series as homogeneous are likely underpredicting event magnitudes. In addition, quantitative guidance on separation of flood events by causal mechanism and treatment of flood type subsets within frequency analyses is needed to produce more reliable flood estimates.
Embargo
Quantifying and mapping tree mortality due to mountain pine bark beetles via analyses of remote sensing data in northern Colorado
(Colorado State University. Libraries, 2024) Taleb, Hamza A. S., author; Laituri, Melinda, advisor; Fassnacht, Steven, committee member; Leisz, Stephen, committee member; Grigg, Neil, committee member
In the past two decades, Mountain Pine Bark Beetle (MPBB) infestations have become more pervasive due to increasing temperatures and drought conditions related to climate change causing regional-scale mortality. Insect effects on tree die-off, fuels, and fire behavior can vary widely. A key problem in understanding insect-fire relationships is the lack of empirical maps that show interrelated changes in the distribution of insect infestations and fire zones over space and time. This study demonstrates an approach to tracking and mapping the spread of MPBB by analyses of vegetation indices calculated from Landsat TM data in the study site in northwestern Colorado. These indices were used for calculations in the Random Forest (RF) classifier algorithm and the Support Vector Machine (SVM) classifier algorithm to determine the presence or absence of MPBB and to illustrate the changes in the distribution of infestations with time. A comparison was made between the accuracy of the two classification algorithms (RF and SVM) in tracking and mapping the spread of MPBB. R2 has proved to be a reliable measure of accuracy of regression models. If the statistical accuracy of all the models, (RF vs. SVM and binary vs. regression) are compared, both the regression and binary models based on RF are more accurate. The results of this study can provide a useful tool for forest managers to make decisions about how changing conditions affect potential problems in forest management.
Open Access
Simulating the effects of coated ice nuclei in the formation of thin ice clouds in the high arctic using RAMS
(Colorado State University. Libraries, 2010) Seigel, Robert, author; Cotton, William, advisor; Stephens, Graeme, advisor; Fassnacht, Steven, committee member; Carrió, Gustavo, committee member
The Polar regions are an integral part of Earth's energy budget, however they are poorly understood mainly due to their remoteness and lack of observations. The recent launch of two successful satellites, CloudSat and CALIPSO, into the A-Train constellation are providing excellent insight into wintertime clouds and precipitation at the Poles. One distinguishable characteristic seen from satellite data during Arctic winter and spring is an optically thin cloud containing ice crystals large enough to precipitate out. These "thin ice clouds" (TIC) occur in regions affected by anthropogenic pollution. It is hypothesized that the anthropogenic pollution, likely sulfuric acid, coat the available ice forming nuclei (IN) and render them inactive for forming ice crystals. Therefore, the effective IN concentrations are reduced in these regions and there is less competition for the same available moisture leading to the formation of relatively small concentrations of large ice crystals. The ice crystals grow large enough for sedimentation, which dehydrates the Arctic atmosphere. We use Colorado State University's Regional Atmospheric Modeling System (RAMS) configured as a cloud resolving high-resolution model (CRM) with horizontal grid-spacing of 1 00m to simulate these TI C's. Varying ice nuclei (IN) concentrations from 5 L-1 to 100L-1 are used to simulate the effects of the acidic coating, whereby the low IN concentration represents the IN particles containing the acidic coating. Results show no concrete evidence in support of the hypothesis. Therefore, a sensitivity experiment is conducted to identify the environmental conditions that maximize the production of TIC's. Results indicate that an increase in both the temperature and supersaturation relative to observations provide a better environment for the production of TIC's.
Open Access
Ski area effects on headwater streamflow
(Colorado State University. Libraries, 2022) Sidell, Marielle Alice, author; Kampf, Stephanie K., advisor; Fassnacht, Steven, committee member; Morrison, Ryan, committee member
Colorado headwater streams produce water supply for the West. The effects of singular land use changes on headwater watersheds have been studied at length, but much less is known about the combined interactions of multiple land use changes on headwater streamflow generation. We examined how the interactions of three land use changes associated with ski area developments (tree clearing, trail and road building, and artificial snow application) affected streamflow at a ski area in northern Colorado. Our study area included three watersheds with stratified levels of development, within a United States Forest Service ski area permit boundary. Three main creeks and their tributaries were equipped with twelve pressure transducers scheduled for data collection at continuous 15 minute intervals over two water years beginning in late summer 2019. Burgess Creek (5.91 km2), which had the greatest degree of development and creek accessibility, was equipped with 9 data loggers; Priest Creek (2.35 km2) had two monitoring sites, and Beaver Creek (2.28 km2) had one. We initially performed an ANOVA comparison of our ski area stream data to two reference watersheds, Hot Spring Creek (14.87 km2) and Spring Creek (2.65 km2) and detected no significant differences in streamflow generation or timing. We then examined how streamflow generation and timing related to the degree of development and watershed characteristics using both univariate correlation analysis and multivariate models. Mean basin elevation was the most significant driver of the timing of flow delivery; development also plays an obvious role in both streamflow generation and timing. Total seasonal and annual streamflow generation increase significantly with development, and the timing of streamflow is earlier in the season in developed watersheds. Overall, this study shows that development affects how and when streamflow is generated from forested headwater stream systems, but our conclusions apply to just one ski area in northern Colorado. Long-term stream monitoring across watersheds with multiple disturbances, like those seen on ski resorts, should be a priority to understand how water delivery is affected by development.
Open Access
Snow persistence and hydrologic response across the intermittent-persistent snow transition
(Colorado State University. Libraries, 2018) Hammond, John Christopher, author; Kampf, Stephanie, advisor; Covino, Tim, committee member; Denning, Scott, committee member; Fassnacht, Steven, committee member
In mountainous regions and high latitudes, seasonal snow is a critical component of the surface energy balance and hydrologic cycle. Snowpacks have been declining in many mountain regions, but the hydrologic responses to snow loss have varied due to interactions of climatic, vegetative, topographic and edaphic factors. With continued climatic change, it remains uncertain whether the southwestern U.S. and other subtropical and mid-latitude dry areas may experience significant reductions in water yield. In this dissertation snow persistence and trends are mapped globally; relationships between snow persistence and annual water yield are examined in different climates, and snowmelt and rain partitioning in the critical zone are modelled to examine potential effects of snow loss on hydrologic response. Chapter 2 involves mapping the distribution of snow persistence (SP), the fraction of time that snow is present on the ground for a specific period, using MODIS snow cover data, classifying similar areas into snow zones, assessing how snow persistence relates to climatic variables and elevation, and testing for trends in annual SP. SP is most variable from year to year near the snow line, which has a relatively consistent decrease in elevation with increasing latitude across all continents. At lower elevations, SP is typically best correlated with temperature, whereas precipitation has greater relative importance for SP at high elevations. The largest areas of declining SP are in the seasonal snow zones of the Northern Hemisphere. Trend patterns vary within individual regions, with elevation, and on windward-leeward sides of mountain ranges. This analysis provides a framework for comparing snow between regions, highlights areas with snow changes, and can facilitate analyses of why snow changes vary within and between regions. In Chapter 3, SP is used to evaluate how water yield relates to snow patterns at the annual time scale across the western U.S. in different climates. I first compare snow cover variables derived from MODIS to more commonly utilized metrics (snow fraction and peak snow water equivalent (SWE)). I then evaluate how SP and SWE relate to annual streamflow (Q) for 119 USGS reference watersheds and examine whether these relationships vary for wet/warm (precipitation surplus) and dry/cold (precipitation deficit) watersheds. Results show high correlations between all snow variables, but the slopes of these relationships differ between climates. In dry/cold watersheds, both SP and SNODAS SWE correlate with Q spatially across all watersheds and over time within individual watersheds. I conclude that SP can be used to map spatial patterns of annual streamflow generation in dry/cold parts of the study region. In Chapter 4 of the dissertation, I use a series of one-dimensional simulations to study how snow loss may impact hydrologic response in mountain areas at event to annual time scales. I use Hydrus 1-D simulations with historical inputs from fifteen SNOTEL snow monitoring sites to investigate how inter-annual variability of water input type (snowmelt, rainfall) and timing affect soil saturation and deep drainage in different soil types and depths. Greater input rate and antecedent moisture are observed for snowmelt compared to rain events, resulting in greater runoff efficiencies. At the annual scale runoff efficiencies increase with snowmelt fraction and decrease when all input is rainfall. In contrast, deep drainage has no clear correlation to snowmelt fraction. Input that is concentrated in time leads to greater surface runoff and deep drainage. Soil texture and depth modify partitioning, but these effects are small compared to those caused by variability in climate. This dissertation's findings have direct implications for climate change impacts in cold dry areas globally. Through the synthesis of the chapters described above I highlight areas where hydrologic response to snow loss may be most sensitive, provide methods for comparing regional snow patterns, demonstrate how snow persistence can help estimate annual streamflow generation, and improve process-based knowledge of hydrologic response to rainfall and snowmelt in the western U.S. Collectively these findings indicate that annual water yield is not directly sensitive to whether input is snowmelt vs. rainfall; instead it is more dependent on the effect that snowpack accumulation has on input timing and rate. Loss of concentrated melt from persistent snowpacks may lead to lower streamflow and compromise deep drainage, and thus aquifer recharge, in semi-arid cold regions. The consequences of streamflow and groundwater recharge loss could be severe in regions already water-stressed, and this needs to be addressed in long-term water supply planning.
Open Access
Snowmelt and rainfall runoff in burned and unburned catchments at the intermittent-persistent snow transition, Colorado Front Range
(Colorado State University. Libraries, 2016) Johnson, Adam, author; Kampf, Stephanie, advisor; Fassnacht, Steven, committee member; Niemann, Jeffrey, committee member
Winter snowmelt and summer monsoonal rains are the dominant sources for streamflow in the Colorado Front Range, and wildfire can greatly affect the hydrologic regime through which these inputs are delivered to the stream. However, the specific changes to the hydrologic processes that drive runoff production made by wildfire are not clearly understood. This research examines how wildfire affects the timing and magnitude of runoff production from snowmelt and rainfall by comparing four catchments in and near the High Park Fire area, two burned and two unburned, at the intermittent-persistent snow transition. Catchments were instrumented to monitor snow accumulation and ablation, rainfall, soil moisture, soil and air temperature, and streamflow response throughout water year 2015. These data were then utilized to determine the primary mechanisms of seasonal runoff generation and the magnitude of that runoff from each catchment. Runoff remained very low at all catchments during winter months. Spring snowmelt runoff in the form of lateral subsurface flow dominated catchment hydrographs for the water year. Following spring snowmelt, runoff production transitioned to a rainfall-dominated, drier summer period. During this time, limited infiltration excess overland flow was produced from high intensity rainfall events. Results of this research suggest that the loss of canopy cover due to wildfire may result in increased snowpack density and more intermittent snowpack throughout the winter months. Burned monitoring sites also maintained higher soil moisture than unburned sites, but this may be a function of site-specific variability rather than burning. Elevated soil moisture at burned sites did not translate to consistently higher runoff production. Both total runoff production and runoff ratios were highest in the high elevation unburned site with the highest snow persistence and the lowest elevation burned site with low snow persistence. During the one high intensity rain event that affected all catchments, burned catchments experienced an increase in discharge above baseflow of a greater magnitude than unburned sites. Overall, all catchments monitored showed site specific characteristics that defied easy classification but illustrated local variability in the hydrologic variables monitored.
Open Access
Spatial and temporal variability of snow cover in the Andes Mountains and its influence on streamflow in snow dominant rivers
(Colorado State University. Libraries, 2016) Pimentel, Freddy Alejandro Saavedra, author; Kampf, Stephanie, advisor; Sibold, Jason, advisor; Fassnacht, Steven, committee member; Niemann, Jeffrey, committee member
The climate is changing, and snowmelt-dominated river basins are particularly sensitive to climate warming. In the Andes Mountains in South America climate measurements are sparse and unevenly distributed in snow-covered areas. Thus, remote sensing offers opportunities to improve understanding of the spatial and temporal snow patterns in this region and explore how these patterns relate to climate and hydrologic response. This study uses snow cover data from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor to (1) identify snow climate regions across the Andes, (2) document trends in snow persistence and their relation to precipitation and temperature, and (3) develop statistical streamflow prediction models. The first chapter of the study identified five snow climate regions: two tropical and three mid-latitude regions. In the tropical regions, snow cover was present only over 5000m on both sides of the Andes. In the mid-latitude regions the elevation of the snow line varied with latitude, dropping from 4000m to 1000m from 23 to 36°S. In the mid-latitudes, particularly where mountain peaks are highest, snow cover accumulates at lower elevations on the west side than on the east side of the Andes. The second chapter quantifies trends in annual snow persistence (SP) from 2000-2014. In the northern part of the study region, limited snow cover is present, and few trends in snow persistence were detected. A large area (70,515 km2) south of 29°S is affected by a significant loss of snow cover (2-5 day less day of snow per year). In this latitude range, most of the land surface area with snow loss (62%) is on the east side of the Andes. The trends of snow persistence relate to both precipitation and temperature, but the relative importance of each parameter changes across elevation and latitude. Precipitation has greater relative importance at lower elevations, whereas temperature has greater relative importance at higher elevations. The final chapter explores the relationship between snow cover patterns and streamflow in snow-dominated rivers in the Chilean Andes (29-36° S). Snow covered area is correlated with water yield in snowmelt-dominated watersheds, but it is not as useful for water yield forecasts in watersheds with more limited snowmelt contributions. The snow cover information was combined with climatic variables (temperature and precipitation), and physiographic variables to develop statistical models of water yield (WY) and peak flow (PF). The final statistical model developed can forecast water year WY and PF in August using precipitation, snow cover, and area of watershed as predictors, with r2 values of 0.8 and 0.7 respectively. The approaches developed for applying snow cover information from remote sensing have led to important new findings about snow patterns in a large latitude range across the Andes Mountains. New tools developed for incorporating snow cover information into water yield and peak flow forecasts can aid water management under changing climate conditions.
Open Access
Spatial simulation of snow and frozen ground using a modified temperature-based model
(Colorado State University. Libraries, 2018) Follum, Michael Lee, author; Niemann, Jeffrey, advisor; Fassnacht, Steven, committee member; Julien, Pierre, committee member; Kampf, Stephanie, committee member
Volume and timing estimates of snowpack and subsequent streamflow are vital for water management and flood forecasting in snow-dominated regions. Numerical models are often employed to estimate the depth of snowpack and presence of frozen ground for assessment of the resulting streamflow. Air temperature based models, such as temperature-index (TI) snow models and degree-day (DD) frozen ground models, are commonly used due to their simplicity and low data requirements. However, because air temperature (a surrogate for available energy) is the main forcing variable, the snowpack and frozen ground in TI and DD models vary spatially based only on elevation. The overall objective of this research is to improve the representation of spatial variations in snowpack and frozen ground within watersheds in order to improve streamflow simulations. To accomplish this goal, this study replaces air temperature in a TI snow model and a DD frozen ground model with a proxy temperature for available energy. The proxy temperature is calculated using a simplified radiation energy balance (requiring precipitation, air temperature, and cloud cover data) that accounts for spatial heterogeneity in both shortwave and longwave radiation due to topography and vegetation. The modified-TI model, referred to as the Radiation-derived Temperature-Index (RTI) snow model, is tested at Senator Beck basin (SBB) in Colorado and at Sleepers River Experimental Watershed (SREW) in Vermont. The RTI model outperforms a pre-existing TI model in simulation of snow water equivalent (SWE) and improves simulation of snow covered area (SCA) at both SBB and SREW. The improvements in snow simulation using the RTI model also improve the streamflow simulation at SBB. The modifications to the DD model, referred to as the modified Continuous Frozen Ground Index (modCFGI) model, also account for insulation of soil by ground cover and simulate frost depth. When tested at SREW, the modCFGI model more accurately captures the variations in frozen ground between the sites, inter-annual variations in frozen ground depths at a given site, and the occurrence of frozen ground than the pre-existing Continuous Frozen Ground Index model. Overall, the modifications made to the snow and frozen ground methods increase the spatial accuracy without requiring much additional data. The RTI and modCFGI methods are also readily transferrable to other hydrologic models.
Open Access
Spatiotemporal complexity in Ginzburg Landau equations for anisotropic systems
(Colorado State University. Libraries, 2012) Zou, Yang, author; Oprea, Iuliana, advisor; Dangelmayr, Gerhard, advisor; Fassnacht, Steven, committee member; Shipman, Patrick, committee member
Nematic electroconvection is a paradigm example of pattern formation in anisotropic extended systems, where spatiotemporal chaos can arise at the onset of electroconvection. This dissertation is devoted to characterize and identify the instability mechanism generating the spatiotemporal complexity in the numerical simulations of a system of Ginzburg Landau equations, used to study the weakly nonlinear stability of waves' amplitudes of nematic electroconvective patterns. In particular, the following results pertaining to spatiotemporal complexity are discussed. First, the simulated patterns are decomposed into central and noncentral spatial Fourier modes. The central modes form an invariant manifold, and the noncentral modes are transverse variables for this manifold. Simulations indicate that the bursts in the noncentral modes induce rapid switchings between a pair of symmetry-conjugated chaotic saddles in the central modes. Even though there are many degrees of freedom involved in these spatiotemporal chaotic patterns, a dimension reduction can be made by exploiting symmetries, leading to a small number of symmetry-adapted variables. A detailed investigation of the dynamics in the space of symmetry-adapted variables reveals that the spatiotemporal complexity is due to in-out intermittency caused by transverse instability of the invariant manifold. Second, in order to understand the instability mechanism causing the switching dynamics in terms of a low dimensional model, a normal form for a Hopf bifurcation with a broken translation variance posed in the space of the central modes is introduced. Theoretical issues relating to symmetries and invariant subspaces are studied. A series of complex phenomena, including symmetry breaking and increasing, period doubling, chaos, transient chaos, crisis-induced intermittency and in-out intermitteny, is observed when an imperfection parameter measuring the strength of the symmetry breaking is varied. In certain parameter regimes bursts with certain magnitudes trigger rapid switchings between a pair of chaotic saddles. A new type of dynamics, identified as a new type of intermittency, is also discussed. Conclusions and further development are presented at the end of the dissertation.
Open Access
Spatiotemporal variations in liquid water content in a seasonal snowpack: implications for radar remote sensing
(Colorado State University. Libraries, 2020) Bonnell, Randall Ray, author; McGrath, Daniel, advisor; Fassnacht, Steven, committee member; Rasmussen, Kristen, committee member
Mountain snowpacks act as seasonal reservoirs, providing a critical water resource to ~1.2 billion people globally. Regions with persistent snowpacks (e.g., mountain and polar environments) are responding quickly to climate change and are warming at faster rates than low-elevation temperate and equatorial regions. Since 1915, snow water equivalent (SWE) in the western U.S. snowpack has declined by 21% and snow covered area is contracting in the Rocky Mountains. Despite the clear importance of this resource and the identification of changes affecting it, no current remote sensing approach can accurately measure SWE at high spactiotemporal resolution. L-band (1-2 GHz) Interferometric Synthetic Aperture Radar (InSAR) is a promising approach for detecting changes in SWE at high spatiotemporal resolution in complex topography, but there are uncertainties regarding its performance, particularly when liquid water content (LWC) is present in the snowpack. LWC exhibits high spatial variability, causing spatially varying radar velocity that introduces significant uncertainty in SWE-retrievals. The objectives of this thesis include: (1) examine the importance of slope, aspect, canopy cover, and air temperature in the development of LWC in a continental seasonal snowpack using 1 GHz ground-penetrating radar (GPR), a proxy for L-band InSAR, and (2) quantify the uncertainty in L-band radar SWE-retrievals in wet-snow. This research was performed at Cameron Pass, a high elevation pass (3120 m) located in north-central Colorado, over the course of multiple survey dates during the melt season of 2019. Transects were chosen which represent a range in slope, aspect and canopy cover. Slope and aspect were simplified using the northness index (NI). Canopy cover was quantified using the leaf area index (LAI). Positive degree days (PDD) was used to represent available melt-energy from air temperature. The spatiotemporal development of LWC was studied along the transects using GPR, probed depths, and snowpit measured density. A subset of this project substituted Terrestrial LiDAR Scans (TLS) for probed depths. Surveys (17 in total, up to 3 surveys per date) were performed on seven dates which began on5 April 2019, where LWC values were ~0 vol. %, and ended on 19 June 2019 where LWC values exceeded 10 vol. %. Point measurements of LWC were observed to change (ΔLWC) by +9 vol. % or -8 vol. % over the course of a single day, but median ΔLWC were ~0 vol. % or slightly negative. LAI was negatively correlated with LWC for 13 out of the 17 surveys. NI was negatively correlated with LWC for 10 out of the 17 surveys. Multi-variable linear regressions to estimate ΔLWC identified several statistically significant variables (p-value < 0.10): LAI, NI, ΔPDD, and NI x ΔPDD. Snow-on Terrestrial LiDAR Scans (TLS) were conducted twice during the melt season, and a snow-off scan was conducted in late summer. Snow-on scans were differenced from the snow-off scan to produce distributed snow depth maps. TLS-derived snow depths compared poorly with probe-derived depths, which is attributed to poor LiDAR penetration through the thick vegetation present during the snow-off scan. Finally, radar measurements of SWE (SWE-retrievals), if coupled with velocities derived from dry-snow densities, overestimated the mean SWE along transects by as much as 40% during the melt season, highlighting a potential issue for water managers during the melt season. Future work to support the testing of L-band radar SWE-retrievals in wet-snow should test radar signal-power attenuation methods and the capabilities of snow models for estimating LWC.
Open Access
Steady state Hopf mode interaction in anisotropic systems
(Colorado State University. Libraries, 2013) Maple, Jennifer, author; Oprea, Iuliana, advisor; Dangelmayr, Gerhard, advisor; Shipman, Patrick, committee member; Fassnacht, Steven, committee member
A paradigm example of pattern formation in anisotropic extended systems is the electroconvection of nematic liquid crystals, due to its easily accessible control parameters and the variety of patterns near onset. Some of the patterns observed are oblique and normal rolls which can be stationary or traveling, and more complex structures such as worms, defects and spatiotemporal complexity, including spatiotemporal intermittency and chaos, can occur, see e.g., Dennin et al, Science 272, 1996. During electroconvection experiments on the nematic liquid crystal mixture Phase V, a mode interaction between oblique stationary rolls and normal traveling rolls has been observed by Acharya et al, Int. J. Mol. Sci. 12, 448, 2011; a system of four globally coupled Ginzburg Landau equations for slowly varying spatiotemporal amplitudes of ideal roll patterns governing the dynamics of anisotropic systems close to the experimentally observed codimension-two point has been set up, two equations for the steady oblique rolls and two for the normal traveling rolls. This dissertation pursues a theoretical and numerical study of the patterns predicted by this system of globally coupled Ginzburg Landau equations. Acharya et al presented a bifurcation analysis of the normal form that follows from the Ginzburg Landau system by ignoring slow variations. The basic solutions of the normal form are two types of pure mode solutions corresponding to ideal oblique stationary and normal traveling rolls, respectively, and superpositions of pure mode solutions, which are referred to as mixed mode solutions. Acharya et al distinguished two cases for the bifurcations of these solutions. In one case the mixed mode solution is stable and a continuous transition between the steady oblique rolls and the normal traveling rolls is predicted. For the other case, the mixed mode solution is unstable and bistability occurs between the steady oblique rolls and the normal traveling rolls. In the present work, a numerical code was developed to simulate the spatiotemporal system of globally-coupled, complex Ginzburg-Landau equations using a pseudo-spectral method. The simulations of the system resulted in patterns that were consistent with the normal form analysis. Steady oblique and normal traveling rolls were found numerically. A region of bistability of the steady oblique rolls and normal traveling rolls was found numerically, and a continuous transformation between the two primary branches via a stable mixed mode branch has been observed when the main bifurcation parameter is varied. Mixed mode solutions have been found that involved either amplitudes of steady rolls aligned in two different ("zig" and "zag") directions, or amplitudes of two counter-propagating normal traveling rolls, for parameter values near the primary instabilities and when the initial conditions favored their appearance, and a bifurcation diagram showing the occurrence of steady state, steady oblique rolls, normal traveling rolls, mixed mode solutions, as well as bistability of the steady oblique rolls and normal traveling rolls has been obtained numerically.
Open Access
Stream nutrient response to contemporary timber harvest practices in western Oregon
(Colorado State University. Libraries, 2017) Harbin, Andrea, author; Stednick, John D., advisor; Fassnacht, Steven, committee member; Sanford, William, committee member
Timber harvesting has historically been shown to increase nutrient concentrations in stream waters by decreasing vegetative cover and nutrient uptake, allowing more nutrients to be leached into stream waters. Contemporary timber harvest practices, in which a streamside buffer is left in place, have not been studied. This study quantified the effects of contemporary timber harvesting practices, with a streamside buffer, in a Douglas-fir dominated watershed in the Oregon Coast Range, using a paired-watershed design. In the treatment (Needle Branch) and the control (Flynn Creek) watersheds, water quality samples collected from October 2006 through March 2016 were analyzed for nutrients. A clearcut harvest took place in the upper basin in 2009 (Phase 1), and in the lower basin in 2014 (Phase 2), and water samples were tested for nitrate (NO3-N), total nitrogen (TN), ammonia (NH3), orthophosphate (OP), and total phosphorus (TP). Intra-watershed comparisons of nutrient concentrations were made using a Wilcoxon Rank Sum Test to determine statistical significance between sites and treatments. A Before-After Control-Impact (BACI) design was used to compare the treatment watershed to the control watershed across treatments. Results at Needle Branch showed statistically significant increases (α < 0.05) in NO3-N between pre-treatment (0.59 mg/L) and Phase 1 (0.97 mg/L), and between pre-treatment and Phase 2 (0.90 mg/L) at the outlet. TN also showed statistically significant increases between pre-treatment (0.87 mg/L), and Phase 1 (1.06 mg/L), and between pre-treatment and Phase 2 (0.92 mg/L). NH3 was also shown to be statistically significant between pre-treatment (0.011 mg/L) and Phase 1 (0.013 mg/L). OP showed statistically significant increases between pre-treatment (0.018 mg/L) and Phase 1 (0.024 mg/L), and between pre-treatment and Phase 2 (0.022 mg/L), as did TP (0.018, 0.026, 0.020 mg/L during pre-treatment, Phase 1, and Phase 2, respectively). Results in Flynn Creek showed statistically significant increases in NH3 between pre-treatment (0.010 mg/L) and Phase 1 (0.013 mg/L). OP also showed statistically significant increases between pre-treatment (0.029 mg/L) and Phase 1 (0.034), and between pre-treatment and Phase 2 (0.032). TP also showed significantly significant increases between pre-treatment (0.028 mg/L) and Phase 1 (0.036 mg/L). Because similar results were observed in both the treatment and control watersheds, changes in these three constituents within the treatment watershed cannot be attributed to timber harvest. Neither NO3-N nor TN showed any change between phases within Flynn Creek, therefore, changes in these constituents within Needle Branch can be attributed to timber harvest. Contemporary timber harvest practices appear to have similar results as past harvesting practices, regarding nutrient concentrations in stream waters. With a streamside buffer, NO3-N and TN concentrations were significantly increased following harvest. Contemporary timber harvest practices, however, did not affect NH3, OP, and TP concentrations.
Open Access
Wildfire impacts on western United States snowpack
(Colorado State University. Libraries, 2022) Giovando, Jeremy, author; Niemann, Jeffrey, advisor; Arabi, Mazdak, committee member; Fassnacht, Steven, committee member; Stevens-Rumann, Camille, committee member
Snowpack in the western U.S. is critical for water supply and is threatened by wildfires, which are becoming larger and more common. Numerous studies have examined impacts of wildfire on snow water equivalent (SWE), but many of these studies are limited in the number of observation locations, and they have sometimes produced conflicting results. The objective of this study is to distinguish the net effects of wildfires on snowpack from those of climate. Data from 45 burned sites from the SNOTEL network are used to perform an empirical analysis to determine SWE impacts from wildfire. For each burned site, unburned control sites are identified from the same level III ecoregion. Impacts of climate changes on snowpack are analyzed first by comparing pre-wildfire and post-wildfire snow water equivalent at the unburned sites. Combined climate and wildfire effects are considered by comparing pre-wildfire and post-wildfire SWE at the burned sites. Wildfire impacts are then isolated by taking the difference between the burned and unburned sites. Four separate snow measures are considered in this analysis and include annual maximum SWE, normalized annual maximum SWE, peak SWE date, and melt-out date. Wildfires have on average advanced melt-out (9 days) and maximum SWE dates (6 days) and reduced annual maximum SWE (10%) across all the sites considered in the analysis. The combined effects of climate and wildfire have advanced melt-out and maximum SWE dates approximately 14 days and 10 days, respectively, while decreasing maximum SWE for the combined effects was approximately 10%. The wildfire-induced changes in SWE were compared to several possible controlling variables including burn severity, leaf-area index change, dominant pre-wildfire tree genus, years since the fire, and site elevation. Due to increasing wildfire magnitude, the potential vulnerability of snowpack is an important consideration for water managers. An analysis to quantify the spatial variability of wildfire impacts on snowpack within the western U.S. ecoregions and vulnerabilities of annual maximum SWE was performed. Random forest models were developed for each measure using topographic, climatic, and land cover predictor variables along with snowpack data from wildfire impacted SNOTEL sites. The results indicate terrain slope is an important variable for maximum SWE, while incoming shortwave radiation and aridity are important for peak SWE date and melt-out date changes, respectively. The largest spatial variability amongst all snow measures is maximum SWE with a range of 5% increase to over 10% decrease due to wildfire impacts. Spatial variability for peak SWE and melt-out dates varied between ecoregions with the largest range in the northern and mid-latitude ecoregions. Peak SWE and melt-out dates are expected to be earlier with the exception of the Arizona-New Mexico Mountains where later melt-out dates are possible. South-facing gentle slopes were identified as the most vulnerable for maximum SWE changes. The total snow water volume difference due to wildfires occurring between 2015 through 2020 ranged from a 1% increase in the North Cascades to a 6% reduction in the Arizona-New Mexico Mountains. A consequence of increased wildfire activity in the western U.S. has resulted in increasing post-wildfire risk assessments by federal, state, and local governments. Locations of these assessments include watersheds which have snowmelt as part of the hydrologic regime. The current gap in generalized recommendations for water managers related to parameter adjustments in snow models presents challenges for water managers performing these risk assessments. Data from wildfire impacted SNOTEL sites were again used to estimate changes in two key parameters (the melt-rate function and the snowfall threshold temperature). The observed changes from pre- and post-wildfire periods at each SNOTEL site were used to develop a suite of general linear models to adjust the melt-rate function and threshold temperature. The model inputs include readily available topographic, climatic, and land cover information. The results indicate melt-rates typically increase after a wildfire, especially for periods later in ablation season. The snowfall threshold temperatures were more variable and site dependent, although the statistically significant changes suggest increases in the threshold temperature will occur post-wildfire. The coefficients from the models suggest that changes to the vegetation canopy are most important for estimating melt-rate and threshold temperature differences beginning immediately after the fire event though approximately 10 years post-wildfire. After vegetation canopy, other important input variables include the air temperature and topographic characteristics (i.e., elevation, northness, and eastness).