Theses and Dissertations

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Recent and future Colorado water: snow drought, streamflow, and winter recreation
(Colorado State University. Libraries, 2023) Pfohl, Anna K. D., author; Fassnacht, Steven R., advisor; Barnard, David M., committee member; Kampf, Stephanie K., committee member; Rasmussen, Kristen L. , committee member
Water in the western United States is a crucial resource for ecosystems, the abiotic environment, and people (for industrial, agricultural, and residential purposes). A majority of this water originates in the seasonal snowpack in the mountains. The snowpack is responsible for maintaining the water supply, and changes to this system have broad and severe implications. Various metrics have been used to quantify these patterns when snow is less than normal, often referred to as a snow drought or a low snow year. In recent decades, the number of years with low snow have increased, and this will continue and intensify into the future. With observed decreases in long-term snow and modeled decreases for the future, high snow years become more critical to support the water supply. Beyond supplying water for downstream use, the seasonal snowpack also sustains the winter recreation industry, which is a large component of many local and state economies. The Weather Research and Forecasting Model (WRF) is a 4-km mesoscale model that can capture orography and convective processes over complex terrain. WRF includes two time periods: the control (CTL) based on historic conditions and the future under pseudo-global warming (PGW) conditions. This dataset was used to drive SnowModel (WRF-SM) to produce 100-m, daily snow water equivalent (SWE), total precipitation, solid precipitation, snowmelt, runoff, and air temperature. Using these datasets, this research examines past and future snow and streamflow in Colorado. We evaluated 1) common metrics and trends for snow drought; 2) used WRF data to drive the Ages hydrologic model to examine changes (snow, streamflow, and flow partitioning) in two high snow years; and 3) ski opportunities at nine different resorts. To evaluate methods of defining snow drought, we used SWE and winter precipitation data from Snow Telemetry stations and the WRF-SM dataset described above. Classifying drought with the ratio of SWE to winter precipitation resulted in drought occurrence for more than 50% of station-years from 1981 to 2020. Using percentiles of long-term peak SWE indicated that occurrence of low or very low years increased from 2001 to 2020 compared with the previous 20 years. Under PGW conditions, elevations between 1800 and 2400 m shifted drought classification towards low or very low, with higher elevations (3200 m and above) remaining relatively unchanged. To examine changes in snow, streamflow, and flow partitioning under a PGW scenario for two high snow years (2008 and 2011), we used Ages, a spatially distributed watershed model, in the Upper Blue River watershed in central Colorado. Changes in snow (snowmelt and solid precipitation) were greatest in magnitude at high elevations. Timing of peak streamflow shifted to nearly two months earlier under a PGW scenario. To examine ski opportunities, we developed metrics to quantify ski conditions. The number of opportunities for snowmaking in the future will decrease throughout the season, but especially in October and November. Ski days (snow depth greater than 50 cm) will decrease in early and late season and increase at lower elevations from January through March. Powder days (fresh depth greater than 15 cm and fresh density greater than 125 kg/m3) follow a similar pattern. Ski resorts at low elevations will generally be more susceptible to changes under a PGW scenario. Additionally, using a fine-resolution dataset allowed investigation of smaller study areas to understand the changes that are not captured with coarser resolutions.
Open Access
Snowfall-driven topographic evolution: impacts on snow distribution patterns
(Colorado State University. Libraries, 2023) Olsen-Mikitowicz, Alexander Richard, author; Fassnacht, Steven, advisor; McGrath, Daniel, committee member; Leisz, Stephen, committee member
This study develops a scalable meteorologically independent snow accumulation model to better estimate snowpack depth using an enhanced representation of actual processes. Current snow accumulation models incorporate bare or snow-free surface properties derived from elevation, aspect, vegetation, and prevailing wind characteristics to determine the drivers of snow distribution yet neglect to consider how subsequent snowfalls can reshape the initial terrain conditions. We hypothesize that a snow depth model that accumulates snowfall while accounting for the antecedent snow-affected surface characteristics is more representative of natural processes and will therefore yield more accurate depth estimates than models that reference a snow-free topographic surface. To address this premise, the research explores (1) conducting a sensitivity analysis to evaluate the behavior of both models, (2) determining the differences between the two snow accumulation modeling approaches, and (3) assessing each model's performance in different location, scale, and temporal resolution conditions to determine their resiliency and transferability. Terrestrial LiDAR was employed at two field sites following snow deposition events and captured a range of spatial extents and resolutions. The Upper Piceance Creek (UPC) site near Meeker, CO covered approximately 10 m2 at centimeter resolution; the Izas Experimental Catchment in the Spanish Pyrenees covered 1 km2 at meter resolution. A regression tree machine learning model was utilized to estimate snow depth based on 14 topographic features. This process engaged in two mechanisms: 1. Static method, where snow depth (dst) determined from the bare earth digital terrain model (ds0) was estimated with snow-free topographic features and 2. Dynamic method, where snow depth (dst) determined from the previous snow surface height (dst-1) was estimated with the dst-1 snowfall affected surface. The analyses found that the models were resilient to changes in training allocations under a random sampling method, but sensitive to both the prevailing wind direction used for feature creation and the overall resolution used to represent surface features. The primary difference between the static and dynamic models for snow depth estimates was the number of features used and their relative importance. The static method had a higher overall median importance and relied mainly on Directional Relief and Relative Topographic Position for snow depth estimates, while the dynamic method displayed lower overall median importance but utilized more surface features over a single accumulation season. The dynamic method outperformed the static method at UPC by approximately 0.07 in a Nash-Sutcliffe efficiency comparison, and only 0.01 at Izas Experimental Catchment suggesting issues with process-scale representation of snow accumulation at the Izas site.
Open Access
Effects of post-fire mulch applications on hillslope-scale erosion
(Colorado State University. Libraries, 2023) Geller, Jordyn, author; Kampf, Stephanie, advisor; Barnard, David, advisor; Nelson, Peter, committee member
Wildfires are increasing in frequency and intensity, greatly altering the landscape and increasing risk of erosion. Mulching is a common restoration technique used after wildfire to enhance protective ground cover and reduce erosion, yet most studies are conducted at the plot-scale. This study applies an experimental approach to evaluate the impact of mulch treatments at the hillslope-scale using varying mulch levels. Similar adjacent hillslopes were chosen to minimize variability in landscape features. The objectives of this research are to 1) examine the effectiveness of post-fire mulching in reducing erosion at the hillslope-scale, and 2) identify landscape features and precipitation factors contributing to the occurrence and magnitude of sediment yield. Sediment fences were installed in convergent swales and planar hillslopes to quantify sediment yields before and after aerial wood mulch application. Rain gauges were installed to compute rainfall amount (mm), duration (hr), and maximum intensities (mm/hr) by storm event. Field observations, coupled with game camera footage, were utilized to evaluate whether each storm produced sediment in the fences. Surface cover surveys were conducted to assess cover changes over the season. Collectively these data were used to 1) identify rainfall intensity thresholds for erosion, 2) examine controls on sediment generation occurrence with a binomial distribution mixed-effects model, 3) examine controls on the magnitude of sediment yield using a gamma distribution mixed-effect model, and 4) assess relative importance of variables relating to sediment yield using random forest models. Threshold rainfall intensities for generating erosion at the study sites were 32-38 mm/hr for MI5, 11-18 mm/hr for MI15, 7-13 mm/hr for MI30, and 5-8 mm/hr for MI60. Across all models of erosion occurrence and magnitude of sediment yield, maximum rainfall intensity and total precipitation were primary drivers of erosion. There was no evidence of a mulch treatment effect on sediment occurrence or magnitude, likely resulting from insufficient initial mulch cover and a high-intensity storm that removed much of the mulch shortly after it was dropped on the hillslopes. Contributing area, slope mean, and slope length showed no influence on sediment yield, likely due to limited variation in these variables between hillslopes. These results highlight the importance of mulch cover that will stay in place under extreme rainfall. Future hillslope-scale studies should consider dropping mulch during a time period that is unlikely to have high intensity rainfall and explore mulch materials and application methods that will better ensure adequate initial cover for reducing hillslope-scale erosion.
Open Access
Building on sustainable development goal indicator 11.3.1. for improved utility and guidance
(Colorado State University. Libraries, 2023) Cardenas-Ritzert, Orion, author; Vogeler, Jody, advisor; McHale, Melissa, committee member; Leisz, Stephen, committee member
The increased production of broad-coverage spatial datasets and investigation of these datasets by spatial analysis techniques allows for consistent examinations of urbanization patterns across the globe. Spatial data and analyses have proven valuable for sustainable urban development initiatives, including Sustainable Development Goal (SDG) 11 under the United Nation's 2030 Agenda for Sustainable Development. SDG Indicator 11.3.1 is a geospatially measured indicator implemented under SDG 11 for monitoring rates of urban expansion and population growth in a specific area over a period of time. Current methodological approaches and data inputs may hinder the application of SDG Indicator 11.3.1 at certain scales and extents. The overarching goal of this research is to build on the utility of SDG Indicator 11.3.1 by enhancing an existing urban delineation method for automated function, examining urban change at the urban agglomeration level across broad extents, highlighting hotspots of SDG Indicator 11.3.1, and evaluating the impacts of the spatial resolution of data inputs on SDG Indicator 11.3.1 and related outputs. In Chapter 1, we advanced an existing urban delineation method for the automatic identification of individual urban agglomerations across broad extents. We accomplished this by integrating various open-source datasets and tools with spatial analysis techniques. We used this methodology to examine SDG Indicator 11.3.1 and additional urban change metrics for urban agglomerations in Ethiopia, Nigeria, and South Africa over the 2016 to 2020 period. In Chapter 2, we applied our delineation methodology and examined the influence of spatial resolution of land use data on urban delineation, urban change metrics, and urban related land use change in Ethiopia over the 2016 to 2020 period. The results of Chapter 1 revealed trends of urban change and highlighted hotspots of SDG Indicator 11.3.1 at multiple levels across the three African countries. Chapter 2 revealed the implications of using varied spatial resolutions of land use maps when delineating urban areas, assessing SDG Indicator 11.3.1 and other urban change metrics, and examining urbanization-driven land use change.
Open Access
Experts vs. novices: a comparison of the quality and quantity of Bombus observations between citizen scientists and researchers in national parks
(Colorado State University. Libraries, 2023) Smith, Alia, author; Bowser, Gillian, advisor; Halliwell, Philip, advisor; Balgopal, Meena, committee member; Newman, Gregory, committee member
Citizen science data is plentiful and diverse in its collection, storage, and subsequent application. Different platforms have unique methods of storing data and limitations in accessing the data contributed to the platform. This study explored the accessibility of citizen science data from several citizen science platforms and compared two different methods of collecting data from iNaturalist, a global citizen science platform for observing and identifying organisms. It focused on Bombus species observations made in Grand Teton and Yellowstone National Parks. The study found that different platforms are not equal in the ability to access and utilize data. It also found that on iNaturalist one method of searching for data yielded 14% more results than the other. The separate and incomplete nature of accessible data across citizen science platforms and subjectivity of searching methods on iNaturalist are indicative of the difficulty in creating a complete dataset that is representative of the collective contributions of citizen scientists. The validity of citizen science research has been controversial in recent history. There is a general consensus, however, that citizen science must be verifiable to be trustworthy. iNaturalist is a crowdsourced citizen science platform that allows other users to corroborate or dispute species identifications that individuals post. This research seeks to determine whether there is a difference in the quantity and quality of Bombus observations in Grand Teton and Yellowstone National Parks made by expert researchers and citizen scientists on iNaturalist. It found that the professional researchers, or experts, contributed 68% of the observations, but there was not a significant difference between the achievement rate of Research Grade observations between the experts and novices. This indicates that citizen scientists have the ability, through iNaturalist, to accurately make difficult taxonomic identifications.
Open Access
Partnerships on Colorado conservation lands: social-ecological outcomes of collaborative grazing management
(Colorado State University. Libraries, 2022) Monlezun, Anna Clare, author; Lynn, Stacy, advisor; Boone, Randall, committee member; Jones, Kelly, committee member; Rhoades, Ryan, committee member
To view the abstract, please see the full text of the document.
Open Access
Streamflow generation across an elevation gradient after the 2020 Cameron Peak Fire
(Colorado State University. Libraries, 2022) Miller, Quinn, author; Kampf, Stephanie, advisor; Nelson, Peter, committee member; Hammond, John, committee member
The western United States is experiencing an increase in catastrophic wildfire in virtually all ecoregions. Many of these fires burn in forested headwaters that communities rely on for water supply, underscoring the need for a greater understanding of how wildfire impacts streamflow timing and magnitude. Though many studies have examined the hydrologic response to fire, the site-specific nature of this type of research has made it difficult to generalize findings. The 2020 Cameron Peak fire burned across a broad swathe of the Colorado Front Range, making it an ideal case study to examine the factors that affect post-fire runoff. The goal of this work is to identify how streamflow responses to rainfall vary from pre-to post-fire conditions and between mountain regions defined by seasonal snow cover and aridity. To this end, we selected three watersheds to compare fire effects on rainfall runoff between snow zones. These watersheds were unburned, moderately burned, and severely burned in each of two snow zones: the high-elevation persistent snow zone, and the mid-elevation intermittent snow zone. These watersheds were instrumented to monitor rainfall and stream discharge throughout water year 2021. To evaluate how wildfire affected runoff, we developed multi-variate statistical models and used Tukey's Honestly Significant Differences test to compare streamflow responses to rainfall between watersheds. Across all burn categories, the high elevation sites were more responsive to rainfall compared to streams at lower elevations; ~50% of rain events produced a streamflow response in the persistent snow zone, compared to ~25% in the intermittent snow zone. In both snow zones, the unburned sites were the least responsive to summer rainfall and had the highest summer baseflows. Although the high elevation streams were more responsive to rain, they did not exhibit evidence of infiltration excess overland flow. Lags between peak rainfall and peak discharge were 1.2-31.3 hr at these sites; in contrast, the low elevation severely burned site had a much more rapid rise to peak discharge (0.6 hr on average) that indicated infiltration excess overland flow. The rainfall intensity threshold necessary for runoff generation at this site was 4 mm hr-1, which agreed with thresholds reported in similar studies of burned areas in this region. We found no evidence that the moderately burned site in the intermittent snow zone generated rapid runoff, likely because that watershed did not experience enough moderate to high burn severity to promote widespread overland flow. Additionally, the flow response at burned sites was uniformly shorter than for the unburned sites in both snow zones. The magnitude of the flow response was higher in the persistent snow zone than in the intermittent snow zone; however, the effect of burn status on streamflow magnitude was difficult to ascertain. These results demonstrate that the streamflow responses to fire vary between snow zones, indicating a need to account for elevation and snow persistence in post-fire risk assessments. Future work in other regions could evaluate whether this snow zone effect is unique to the study area or a common cause of differences in post-fire streamflow.
Open Access
Variation in soil organic carbon across lowland tropical forest gradients: soil fertility and precipitation effects on soil carbon organic chemistry and age
(Colorado State University. Libraries, 2022) Blackaby, Emily, author; Cusack, Daniela F., advisor; Boot, Claudia M., committee member; Cotrufo, M. Francesca, committee member
Tropical forests hold large amounts of carbon (C) in both aboveground biomass and belowground soil organic carbon (SOC) stocks. Climate change is expected to alter tropical forests' precipitation with some forests already showing decreased rainfall. We analyzed SOC molecular composition and age in lowland tropical forests of Panama across fertility gradients, rainfall ranges, and soil order. We hypothesized that H1) rainforests with relatively greater rainfall store larger amounts of proteins (N-alkyl) and lipids (alkyl) in SOC because of greater microbial biomass and H2) subsurface SOC stocks in more strongly weathered, clay-rich soils are older (as indicated by radiocarbon) because of great sorption capacity. We found that overall, carbon decreased and became older with depth across all samples. Solid-state 13C NMR spectroscopy indicated that soil order and depth were significant predictors of C functional group abundances while phosphorus (P) was a significant predictor of alkyl, aromatic, and carboxyl C. Alkyl/O-Alkyl ratios increased with depth indicating increased degradation of the SOC. ∆14C values indicated older C with depth and varied significantly with soil order where Oxisols were the oldest and Mollisols the youngest. Soil N % and K % were significant predictors of younger soil C. Additionally, biomolecular composition of SOM from 0-10 cm was a significant predictor of ∆14C at 25-50 cm. We found that higher abundances of alkyl and O-alkyl C corresponded with younger C at depth and higher abundances of aromatic and phenolic C contained older C at depth.
Open Access
Multi-decadal impacts of high-severity wildfire on ecosystem nitrogen cycling
(Colorado State University. Libraries, 2022) Rhea, Allison Elizabeth, author; Covino, Tim, advisor; Rhoades, Charles, advisor; Kampf, Stephanie, committee member; Rathburn, Sara, committee member
Wildfires modify the amount, form, and distribution of nitrogen (N) throughout an ecosystem. Though N stocks are lost during the combustion of vegetation and surface organic matter, there is often a subsequent increase in inorganic N delivery to streams that provide drinking water to the Western US. This can make streams and reservoirs more susceptible to eutrophication and algal blooms, threatening the delivery of clean drinking water. While many post-fire studies have documented short-term (<5 years) increases in soil and stream inorganic N, long-term monitoring after the Hayman fire has revealed that increases in stream N can persist for decades. This dissertation investigates the long-term controls of elevated post-fire N across spatial scales. Chapter 2 describes the stream biotic response to the Hayman and High Park fires that burned along the Colorado Front Range. I evaluated stream water chemistry, algal nutrient limitation, benthic biomass, and stream metabolism along stream reaches within three burned and three unburned watersheds. Although the two high-severity wildfires occurred five and 15 years prior to the study, the streams draining burned watersheds still had 23-times higher nitrate (NO3-) concentrations than unburned watersheds, a trend that is consistent across seasons and throughout the 15-year post-fire record. Autotrophic N-limitation was reduced in these nitrate-rich burned streams. Consequently, autotrophic biomass and primary productivity were 2.5 and 20-times greater, respectively, in burned relative to unburned streams which indicates post-fire increases in stream N demand. However, the continued export of N out of these burned streams suggests that terrestrial N supply exceeds in-stream N demand. This suggests that streams have a limited capacity to attenuate N exports from burned watersheds. It was unclear if terrestrial N delivery to streams was driven by long-term elevated soil inorganic N supply (i.e., pools and net transformation rates) or depressed post-fire vegetation recovery and plant nutrient demand. I address this knowledge gap in chapter 3, by measuring inorganic N in surface mineral soils (0-15 cm), soil leachate (30 cm), and shallow groundwater (40-100 cm) in unburned watersheds dominated by ponderosa pine (Pinus ponderosa) and shrub-dominated watersheds that burned 17 years prior in the 2002 Hayman fire. Wildfire caused large C and N losses from soil O horizon during combustion (~1,500 and 50 g /m2 of C and N, respectively). However, total C and N stocks, soil-extractable inorganic N, plant-available inorganic N, and net N transformation rates (i.e., nitrification, and N mineralization) differed little between burned and unburned mineral soils. This indicates that there were no long-term post-fire increases in soil N supply. In contrast to the near surface patterns, NO3- concentrations were four- and ten-times higher, respectively in shallow groundwater and streams of burned watersheds. Tree regeneration has been slower than expected following the Hayman and other fires in the western US and these biogeochemical patterns suggest that low plant N demand may prolong the impacts of wildfires on stream nutrients where more extreme fire behavior and climatic conditions inhibit vegetation recovery. Finally, in chapter 4, I investigated the landscape and stream network drivers of persistent elevated stream NO3- in nine watersheds that were burned to varying degrees by the Hayman fire. I evaluated the ability of multiple linear regression and spatial stream network modeling approaches to predict observed concentrations of the biologically active solute NO3- compared to the conservative solute sodium (Na+). No landscape variables were strong predictors of stream Na+. Rather, stream Na+ variability was largely attributed to flow-connected spatial autocorrelation, indicating that downstream hydrologic transport was the primary driver of spatially distributed Na+ concentrations. In contrast, vegetation cover, measured as mean normalized differenced water index (NDMI) was the strongest predictor of spatially distributed stream NO3- concentrations. Furthermore, stream NO3- had weak flow-connected spatial autocorrelation and exhibited high spatial variability. This pattern is likely the result of spatially heterogeneous wildfire behavior that leaves intact forest patches interspersed with high burn severity patches that are dominated by shrubs and grasses. Post-fire vegetation also interacts with watershed structure to influence stream NO3- patterns. For example, severely burned convergent hillslopes in headwaters positions were associated with the highest stream NO3- concentrations due to the high proportional influence of hillslope water in these locations. My findings help characterize the potential magnitude, duration, and location of water quality concerns following fire. Slow forest recovery in large, high severity burn patches will likely sustain post-fire N export by limiting vegetation N uptake. As regeneration failures become more common with increasing fire severity and climate aridity, ecosystems will be more susceptible to sustained NO3- losses. If reforestation is desired, targeted plantings in riparian corridors, severely burned convergent hillslopes, and headwater positions will likely have the largest impact on stream NO3- concentrations.
Open Access
The dynamic nature of snow surface roughness
(Colorado State University. Libraries, 2022) Sanow, Jessica, author; Fassnacht, Steven, advisor; Sexstone, Graham, committee member; McGrath, Dan, committee member; Bauerle, William L., committee member
Throughout the winter season, the snowpack becomes the surface-atmosphere boundary for the energy balance within the hydrologic cycle and is key for understanding and modeling meltwater availability, streamflow, and groundwater recharge. The aerodynamic roughness length, z0, is one metric to quantify the roughness characteristics of the snowpack surface. Roughness is a key component when analyzing the snowpack surface energy exchange because it exerts a strong influence on turbulent energy exchanges between the snowpack and atmosphere. Snow surface roughness fluctuates throughout the winter season due to snowpack accumulation and melt, redistribution, ecological, and meteorological influences. However, current hydrologic and energy balance models use a static z0 value despite the snowpack surface, and resulting z0 value, being spatially and temporally dynamic throughout the winter. Inclusion of a site specific, spatially, and temporally variable z0 is expected to improve hydrologic and energy balance models. Therefore, the following research investigates 1) comparing the anemometric and geometric methods of measuring z0, 2) the correlation between z0 and snow depth, 3) spatial and temporal variability of z0, 4) post-processing effects on z0 measurements, and 5) application of a variable z0 within the SNOWPACK model. Results of this study indicate a strong correlation when comparing geometric versus anemometrical methods of calculation. 30 wind profiles were compared to 30 corresponding geometrically calculated surface measurements using a terrestrial based LiDAR. These combined profiles had a Nash-Sutcliffe Coefficient of Efficiency of 0.75, an r2 of 0.96, a best fit slope of 0.98, and a Root Mean Square Error of 8.9 millimeters. The correlation between snow depth and z0 is variable depending on periods of melt, accumulation, and the initial snow-free roughness. The z0 was shown to be spatially and temporally variable across study sites. Interpolation resolution during post processing of z0 was found to modify z0 by several orders of magnitude. Variable z0 values were found to alter SNOWPACK model results within several of the output variables. The most sensitive output variables were sublimation, latent, and sensible heat due to the direct use of z0 within the calculations. These key findings highlight the importance of a variable z0. Inclusion of a variable z0 parameterization within models should be site specific, spatially and temporally dynamic, with special attention to post-processing steps.
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
The topology and ecohydrology of river corridors in mountain river networks
(Colorado State University. Libraries, 2022) Brooks, Alexander C., author; Covino, Tim, advisor; Morrison, Ryan, committee member; Rhoades, Chuck, committee member; Ross, Matt, committee member; Wohl, Ellen, committee member
River corridors are comprised of the river, the surrounding valley and riparian areas, and subsurface hyporheic zones. River corridors have the potential to regulate hydrological, biogeochemical, and ecological processes and patterns from reach to watershed scales. Within mountainous landscapes, narrow sections of the river corridor are often interspersed within wider, yet less frequent, river corridor sections. Reach-scale studies (i.e., 1 km) suggest that wide river corridors, also referred to as river-floodplain systems and river beads in this dissertation, have disproportionate impacts on river network behavior. In chapter one, I introduce the concept of river corridors, briefly review the history of the concept's development, the hydrologic and eco-geomorphic factors that drive functioning in these systems, and alterations driven by anthropogenic activities. In chapter two, as a first step to deepening understanding of the influence of river network valley morphology on watershed process, I quantify the spatial distribution of wide and narrow river corridor segments in twenty river networks in the Southern Rockies Ecoregion. I then characterize the spatial configuration of river beads including their frequency, abundance, and spacing. These results reveal variable network topology of river beads in the region and illustrate the need to consider network position when investigating functioning in these systems. I conclude that characterizing river bead configurations can improve river network understanding and aid decision making in prioritizing conservation and restoration efforts. In chapter three, I explore water-mediated linkages, termed hydrologic connectivity, that connect landscape components within an intact beaver mediated river-floodplain system in Rocky Mountain National Park. I evaluate surface water hydrologic connectivity using field indicators and develop a continuous connectivity metric that represents a vector strength between a source along the North St Vrain River to ten surface water target sites within the river-floodplain system. To measure this connectivity strength, I analyzed hydrometric, injected conservative tracers, and natural occurring geochemical and microbial tracers across streamflows in 2018. I developed empirical models of surface water hydrologic connectivity as a function of river stage to predict daily connectivity strength across multiple floodplain sites for 2018 and assessed the sensitivity of surface connectivity to inter-annual streamflow variability between 2016-2020. At the river-floodplain system scale, I found hydrologic connectivity always increased with streamflow while across-system variance in connectivity peaked at intermediate streamflow. At sites with intermittent connections to the river, river stage disconnection thresholds were variable and their connectivity dynamics were sensitive to inter-annual variation in streamflows, suggesting that future connectivity behavior under climate change will depend on how flow durations change across a range of flow states. These results suggest that the intermediate flows are critical periods for understanding seasonal connectivity within river-floodplain systems. Accordingly, our results suggest that alteration to connectivity regimes as dictated by future hydrologic change will be in part a function of the speed at which streamflow moves from peak to low flow states. In chapter four, I examine the spatial patterns in land cover within the Southern Rockies Ecoregion and assess the implications of wetland cover on river corridor productivity and the sensitivity of productivity to inter-annual climate variability across geographic and climatic gradients in the region. We found that wetlands, which comprise today only around a third of river corridor area, maintain high productivity even in river corridor segments within water limited landscapes. However, degradation in wetlands and the loss of woody cover create river corridors with high sensitivity to climate variability, particularly in areas with lower climatic water availability. Wetlands with woody cover were clustered in proximity to rivers and maintain relatively low climate sensitivity even in more water limited landscapes. Vegetation productivity and sensitivity patterns in river corridors without wetlands were largely driven by climatic water availability. Areas with high water availability generally contained forested cover with high productivity and low climate sensitivity while water limited areas generally contained shrub lands and grasslands cover with low productivity and high climate sensitivity. These results suggest that wetland loss and/or degradation have resulted in losses in productivity and climate resilience, particularly within more water limited portions of the region.
Open Access
The effects of temperature-elevation gradients on snowmelt in a high-elevation watershed
(Colorado State University. Libraries, 2022) Sears, Megan G., author; Fassnacht, Steven, advisor; Kampf, Stephanie, committee member; Rasmussen, Kristen, committee member
The majority of snowmelt in the western U.S. occurs at high elevation where hydrometeorological measurements needed for monitoring snowpack processes are often in complex terrain. Data are often extrapolated based on point measurements at lower elevation stations and the elevation to be modeled. In this study, we compute near-surface air temperature-elevation gradients and dew point temperature-elevation gradients (TEG and DTEG, respectively) and compare values to widely accepted rates (e.g., environmental lapse rate). Further, the implications on snowmelt modeling of TEG and DTEG versus accepted temperature-elevation gradients are quantified using two index snowmelt models, 1) temperature and 2) temperature and radiation. TEG and DTEG were found to be highly variable and during nighttime often influenced by cold air drainage. Several modeling scenarios were applied that manipulated air temperature and dew point temperature, via incoming longwave radiation. When compared to the control scenario, these scenarios ranged in snow-all-gone date by -1 to +6 days. The model utilizing observed air temperature and an estimated DTEG performed most similarly to the control scenario. Thus, the estimated DTEG is adequate for index snowmelt models used in similar domains; however, further investigation should be done prior to applying the environmental lapse rate or other estimated TEG values.
Open Access
Predicting flow duration and assessing its drivers in north-central Colorado using crowdsourced data
(Colorado State University. Libraries, 2022) Peterson, David, author; Kampf, Stephanie K., advisor; Ross, Matt, committee member; Gallen, Sean, committee member
Headwater streams are globally important both ecologically and for human resource needs. These streams represent the majority of stream network length, but their flow regimes are often unknown. Streams can be classified by flow regime as perennial, intermittent, or ephemeral. These classifications are used in forest land management decisions and may affect Clean Water Act jurisdiction; however, the National Hydrography Dataset (NHD) often misclassifies headwater streams. The goal of this study is to model flow duration across the stream networks of eight subbasins in north-central Colorado. We used crowdsourced flow presence/absence data from 82 sites in the Stream Tracker program and eight flow sensors to train random forest regression models; these models predicted the fraction of time a stream flows from April-September for both the average from 2016-2020 (dubbed mean annual) and yearly averages (annual). Model predictor variables included climatic, physiographic, and land cover attributes of the study area. Models were developed using a sample of the sites for training and leaving the remaining sites for model testing. The resulting mean annual model's Nash-Sutcliffe efficiency (NSE) was 0.88 for test data, and the annual model's test data had an NSE value of 0.81. We found climate variables such as snow persistence, precipitation, and potential evapotranspiration most influential in predicting flow fraction based on the random forest-ranked variable importance. Forested and herbaceous land cover as well as depth to bedrock, available water storage, hydraulic conductivity, hydrologic soil group, drainage area, and watershed curvature were also identified as important drivers. We developed maps of predicted flow fractions and compared them to NHD flow classifications. In the Cache La Poudre subbasin, the mean annual model predicted perennial flow in 10% of streams and intermittent or ephemeral flow in 90% of streams. Our model predicted nonperennial flow for 76% of the streams that were mapped as perennial in the medium-resolution NHD. Based on these findings, the NHD over-represented perennial streams, classifying them three times more than our model, and under-represented intermittent and ephemeral streams by 32% in our study area. The annual model captured interannual variability in flow fraction and highlighted isolated areas of high variability in flow fraction between years in mid-to-low elevations. The models we developed using crowdsourced data can improve flow classifications of headwater streams and inform resource management decisions in northern Colorado. Crowdsourced streamflow data can be used in streamflow predictions anywhere that nonperennial flow is common.
Open Access
Effects of early snowmelt on plant phenophase timing and duration across an elevation gradient
(Colorado State University. Libraries, 2021) Wilmer, Chelsea, author; Kampf, Stephanie, advisor; Steltzer, Heidi, advisor; Hufbauer, Ruth, committee member
Plant phenology is an important indicator of the effects of climate change, yet the relative importance of both the drivers of plant phenology and the importance of individual phenophases in how plants respond to climate change is not well understood. Here we assess the impact of early snowmelt, a critical climate perturbation in mountain regions, on the timing and duration of individual plant phenophases across an elevation gradient in Crested Butte, Colorado. We observed a sequence of plant phenophases, new leaves, full leaf expansion, first open flower, and full leaf color change at five sites at distinct elevations (2774 m, 2957 m, 3167 m, 3475 m, 3597 m) across three mountain life zones (montane, subalpine, and alpine) in 2017 and 2018. In the spring of 2018, we used solar radiation absorbing fabric to accelerate the timing of snowmelt and observed the differences in timing for early snowmelt plots relative to control plots. The two study years had different snowmelt timing with 2018 being much earlier than 2017, so we analyzed the data to evaluate the effect of year using unmanipulated plots only, and also, separately the snowmelt manipulation, on phenophase start dates and durations. Phenophase timing was advanced at nearly all sites in 2018 and was not clearly linked to shifts in duration, which were variable. The snowmelt manipulation did not shift the timing of phenophases at the lowest elevation in our elevation gradient and the effect of the experiment on the timing of phenophases decreased as elevation increased. Even though snowmelt was significantly accelerated in the manipulation plots in 2018 at the lowest elevation the timing of phenophases were not advanced. This may indicate a threshold beyond which early snowmelt no longer advanced leaf emergence. Earlier snowmelt in mountain regions can shift the timing and duration of plant growth, though not consistently, which will have consequences on how plants affect the movement of water and retention of nutrients and metals in mountain watersheds.
Open Access
Exploring compensation programs and depredation reporting for wolf-livestock conflict across the North American West
(Colorado State University. Libraries, 2021) Nickerson, Rae, author; Evangelista, Paul, advisor; Breck, Stewart, advisor; Niemiec, Rebecca, committee member; Hoag, Dana, committee member
With the continuing reestablishment of wolves (Canis lupus) across the American West, livestock producers will be increasingly exposed to wolf-related conflict such as livestock depredation. The financial implications of wolf conflict can be significant depending on the context of an individual livestock operation. Compensation programs administered by government agencies and occasionally non-government organizations aim to ameliorate some of the financial risks associated with wolves and the loss of livestock; yet the effectiveness of these programs at fostering tolerance and adequately addressing losses is increasingly questioned. Reporting depredation is often required for compensation eligibility, and reports are the primary source of data used by wildlife agencies to address conflict and inform local management. Yet not all producers report depredation or utilize compensation, and we know very little about what factors motivate reporting and compensation use. Additionally, we know very little about producer perspectives on existing compensation programs or whether producers are interested in alternatives. I designed an exploratory survey based on an expanded version of the Theory of Planned Behavior to identify the social-psychological and demographic factors most strongly correlated with compensation use and wolf depredation reporting intentional outcomes. I also utilized a simplified Discrete Choice Question to gauge producer interest in alternatives to traditional compensation programs. My online survey was sent to livestock producers across Arizona, California, Colorado, Idaho, Montana, New Mexico, Washington, Wyoming, and Alberta, Canada (n=165 responses). While 87% of respondents experiencing wolf depredation had reported a depredation in the past, only 69% had utilized compensation. Levels of satisfaction with existing compensation programs were mixed. The most common reasons stated for not applying for compensation included dissatisfaction with the depredation confirmation process (too much validation and/or paperwork), that the amount of compensation available is not enough or not worth the hassle of applying for compensation, and a lack of trust and satisfaction with state government employees and their wolf management decisions. Using Lasso regression, I found that descriptive norms (p<0.01), age (p<0.01), and past experience with depredation (p<0.05) were the strongest predictors of reporting intention. Trust (p<0.001), perceived risk (p<0.05), descriptive and personal norms (p≦0.05), attitudes (p<0.05), and state of residence (varied by state) had the strongest relationship with compensation use intention. The overall predictive power of my models was high, suggesting the expanded Theory of Planned Behavior model was effective at predicting both behavioral intentions. The results of my Choice Question suggest that my surveyed population wants access to diverse and adaptive payment and engagement options for wolf depredation. I also found that although these producers are interested in alternatives like Habitat Leases and Cost-Shares for financial and technical assistance with conflict reduction tools, they still want access to traditional compensation for depredation to address local variation in depredation across neighboring operations. Although limited by my sample size, these findings suggest that 1. building interpersonal trust between wildlife agency personnel and livestock producers, 2. reducing wolf-related financial vulnerability by providing compensation for indirect losses and/or undetected wolf depredations in addition to payments for depredation, and 3. building descriptive norms by providing peer-to-peer knowledge sharing opportunities for producers to share with one another may all increase reporting and compensation use intentions among livestock producers, and by extension, may influence behavior.
Open Access
Streamflow forecasting in a snow-dominated river of Chile
(Colorado State University. Libraries, 2021) Pérez Peredo, Felipe Andrés, author; Fassnacht, Steven, advisor; Sibold, Jason, committee member; Barnard, Dave, committee member
The combination of 10 years of drought in the Chilean Andes and an increased demand water supply and agricultural activities has created the need for better forecasts to inform water management and decision making. The existing water supply forecasts have been insufficient for the snow-dominated systems originating in the mountains, especially under the new drought conditions. Future climate change and inter-annual variability will further require the use of more detailed snowpack information to create better water supply forecasts. This research focuses on the monthly water supply forecast for the basin upstream the flow gauging station called Río Aconcagua en Chacabuquito, in central Chile. This basin is located in the Mediterranean climate zone, originating at the highest peak in the Andes, Aconcagua. Meteorological data are collected at several stations in the lower elevations, and snowpack information, specifically monthly snow water equivalent (SWE) has been collected at the higher elevation Portillo snow course since 1951. Here, a new methodology is created to improve the seasonal volume and the monthly distribution streamflow forecasts, using available information from operational and more representative stations. Results are being evaluated for the current snowmelt period (September 2020 to March 2021), with monthly updates. Improvements have been seen in the seasonal volume, due the use of historical data and because the new methodology also incorporates the recent dry years, unlike the previous forecast model. Improvement in the monthly distributions are seen due the newly adopted methodology distribution.
Open Access
Variable fresh snow albedo: how snowpack and sub-nivean properties influence fresh snow reflectance
(Colorado State University. Libraries, 2021) Reimanis, Danielle C., author; Fassnacht, Steven, advisor; Butters, Gregory, committee member; McGrath, Daniel, committee member
The understanding of albedo, or ratio of outgoing to incoming shortwave radiation, is necessary for modeling the melt characteristics of a snowpack in snow-dominated areas. The timing and supply of meltwater downstream is influenced by the energy balance, and albedo is used in those calculations. Current snow albedo models range from simple models that only reset albedo with new snowfall to complex models that are not feasible for most applications. We present a variable fresh snow model that enhances a simple albedo model, initially created by the U.S. Army Corps of Engineers, and used extensively in the Canadian LAnd Surface Scheme (CLASS). The new approach considers conditions prior to and during a snowfall event to improve fresh snow albedo estimates, instead of resetting to a static value; it also considers differences in the albedo decay rate.Hourly shortwave radiation (incoming and outgoing), snow depth, temperature, and other meteorological data from two stations at the Senator Beck Basin in the San Juan Mountains of Southwest, Colorado were used for the period from 2005 to 2014. We evaluated changes in albedo of a high-elevation seasonal snowpack during fresh snow events and apply a set of multivariate regressions to recreate values of broadband albedo. The variable fresh snow albedo model approaches the Visible and Near-Shortwave Infrared portion of the electromagnetic spectrum differently and groups values by temperature. The model needs few inputs, specifically measurements of depth and temperature, an estimation of ground albedo, and for increased accuracy, a quantification of the number of aeolian dust deposition events on the snowpack every year. This variable fresh snow model showed higher accuracy in albedo values, both of fresh and decayed snow (R2 of 0.77 and Nash Sutcliffe Efficiency, NSE of 0.75) than of CLASS (R2 of 0.67 and NSE of 0.62). When isolating fresh snow events, the variable fresh snow albedo model was much more accurate than the single-reset albedo provided by CLASS but still had a weak correlation to measured values (R2 of 0.38). The variable fresh snow albedo model especially outperformed CLASS during the melt period, with ~24% more accurate absorption values to measured values than CLASS. Since fresh snow albedo is primarily weighted by albedo from the timestep before, we suggest this model also be used to correct erroneous values of albedo given incorrect sensor measurements, such as due to snow accumulation on the upward looking shortwave radiation sensor (pyranometer).
Open Access
Trends and controls on lake color in the high elevation western United States
(Colorado State University. Libraries, 2021) Austin, Miles T., author; Ross, Matthew R. V., advisor; Hall, Ed, committee member; Bailey, Ryan, committee member
Lakes are perceived to be having an increase in algal blooms across the Western United States due to climate change driven and other anthropogenic drivers. Despite this perception, long-term records do not exist for many lakes, so looking at macroscale patterns is challenging. We present and discuss here our results from using a remote sensing dataset, LimnoSat-US. LimnoSat-US contains Landsat imagery from 1984 to 2020. In the intermountain west, our focus study region of Colorado, Wyoming, Idaho, Montana, New Mexico, and Utah, LimnoSat includes 1,200 lakes and over 150,000 summer observations of water color and reflectance. We used LimnoSat-US to examine what controls lake color and what, if any, changes are occurring lake color, which is a strong indicator of whether a lake is prone to algae blooms. A lake's mean depth and annual temperature were the strongest predictors of whether a lake was, on average, blue and clear or green and murky. Despite the perception of increased algae blooms, we found no consistent evidence of lakes 'greening' or shifting from mostly oligotrophic, blue, and clear to eutrophic, green, and murky. Instead, the vast majority of our lakes (> 80%) had no trend in lake color. Further, we found that our approach did not capture the dominant controls on whether not a lake was shifting from blue to green or green to blue, highlighting the need for additional work.
Open Access
Exploring summer cooling electricity consumption in a mid-sized, semi-arid city
(Colorado State University. Libraries, 2021) Abram, Lauren, author; McHale, Melissa, advisor; Keller, Joshua, committee member; Tulanowski, Elizabeth, committee member
As climate change advances, it will threaten urban livability in the summer months through elevated temperatures and more severe heat waves. These increased temperatures, coupled with urbanization and the introduction of more impervious surfaces, will positively feed into the Urban Heat Island (UHI) effect. The combination of hotter temperatures and the inevitable population growth urban areas are going to experience will threaten sustainability through the increased demand for cooling energy resources. While there are many ways to address sustainable energy consumption in a city, one commonly cited method has been through the establishment of urban tree canopy (UTC), which has been shown to cool outdoor temperatures and decrease summer energy use through shading and microclimate regulation. Additionally, investing in research to understand local drivers of cooling energy use can help inform the development of municipal goals and programs for energy reduction. Using household electricity consumption, we aimed to understand if UTC and impervious surfaces were impacting summer cooling electricity use in single-family homes, and if so, at what distance and orientation around homes were these land covers most impactful. We then investigated drivers of summer cooling electricity use with additional urban form, building, sociodemographic, and behavioral variables to try to account for cooling consumption patterns. We found that our results showed trends that differed from previous studies and that east side UTC was the most impactful on cooling use. In addition, impervious surfaces were the most impactful when they were closer to the home. However, land cover was minimally impactful on cooling use, and additional behavioral, building, urban form, and sociodemographic characteristics explained more variability in cooling consumption patterns and highlighted the uniqueness of our study area in comparison to previous studies.