Abstract

Mercury Storage, Export, and Process Rates in Two Beaver-Dominated River Corridors in the Colorado, Rocky Mountains

Sarah Rogers — Tue, 01 Apr 2025 20:20:00 +0000

Mercury Storage, Export, and Process Rates in Two Beaver-Dominated River Corridors in the Colorado, Rocky Mountains Sarah Rogers Tue, 04/01/2025 - 14:20 Clifford Adamchak

Land managers are reintroducing North American beaver (Castor canadensis) into Western United States (U.S) waterways to restore degraded riparian ecosystems. Beavers create cascades of sequential dams that alter river corridor (the channel and adjacent landscape) geomorphology and redox chemistry. These changes can produce conditions conducive to the production of methylmercury (MeHg), a bioaccumulating neurotoxin. Increasing atmospheric mercury (Hg) deposition in the western U.S., combined with beaver expansion, has the potential to dramatically change aquatic biogeochemical cycling and ecological processes, particularly rates of methylmercury (MeHg) production. In this study, we investigated the degree to which beaver activity expands anoxic conditions, influences the interaction of carbon (C), sulfur (S), and Hg cycles, and increases potential rates of Hg methylation in montane ecosystems. We present results from water and sediment samples from Coal Creek (Crested Butte, CO) and Trout Creek (Colorado Springs, CO). We quantified total Hg and MeHg concentrations in water and sediment, and further developed a technique to quantify sulfate reduction rates in sediment using the radioisotope 35S. Preliminary results indicate that periodically inundated sediment within a beaver meadow had on average, higher MeHg concentrations (2.15 ± 3.32 ng g-1) than the stream sediment (0.93 ± 1.51 ng g-1, p < 0.05). Additionally, MeHg concentrations in pond surface water (0.322 ± 0.041 ng L-1) and the beaver pond outlet (0.11 ± 0.41 ng L-1) were elevated compared to the inlet (0.05 ng L-1). Although not significant (p > 0.05), the results suggest that beaver ponds may be associated with higher production of MeHg, which can be transported downstream. Overall, this study expands our understanding of MeHg production in high elevation beaver meadows and provides insights for mountain communities and land managers regarding the consequences of continued beaver expansion for water quality.

Clifford Adamchak · ENVS · PhD Student

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Geomorphic Response to Low-Head Dam Removal in Steep Mountain Streams

Sarah Rogers — Tue, 01 Apr 2025 20:15:00 +0000

Geomorphic Response to Low-Head Dam Removal in Steep Mountain Streams Sarah Rogers Tue, 04/01/2025 - 14:15 Virgil Alfred

Dams disrupt sediment and hydrologic connectivity, fragmenting river ecosystems and altering geomorphic and ecological processes. In response, dam removals have increased to restore longitudinal stream connectivity and ecosystem function. However, we still lack a comprehensive understanding of the geomorphic responses to dam removal, particularly for low-head dams in high-gradient environments. This study examines the geomorphic and ecological effects following the removal of the Lake George diversion structure, a small diversion dam on the South Fork of the South Platte River, CO, in 2023. During removal, reservoir sediment was removed and the channel was re-shaped. Using a Before-After-Control-Impact design, we are monitoring three control cross-sections far enough upstream of the former dam to be unaffected by the removal, three cross-sections in the former impoundment immediately upstream of the dam, and three cross-sections immediately downstream of the structure location, collecting pre- and post-removal data.

At each cross-section, we are conducting RTK-GPS surveys to assess morphologic change caused by, and in the years following, dam removal. We are also collecting bed and subsurface sediment samples for grain size analysis to evaluate textural changes in response to the removal and restoration work. We are collecting benthic macroinvertebrates to provide insight into the early ecological responses to the removal. Preliminary results indicate that although the dam removal and restoration work dramatically reshaped the channel (width and depth changes of several meters), only minor natural geomorphic change has occurred in the year since removal (maximum width and depth changes of a few decimeters). Ongoing and future work will include developing models to predict geomorphic responses to dam removals and channel restoration in steep mountain streams. This research enhances our understanding of how rivers adjust to human-driven disturbances, both in the short term and over longer timescales, following dam removal and restoration.

Virgil Alfred · GEOG · MA Student

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Evapotranspiration and soil water content estimation of four urban landscape vegetations using UAV-based multispectral and thermal imagery

Sarah Rogers — Tue, 01 Apr 2025 20:10:00 +0000

Evapotranspiration and soil water content estimation of four urban landscape vegetations using UAV-based multispectral and thermal imagery Sarah Rogers Tue, 04/01/2025 - 14:10 Zahra Amiri

Accurate assessment of evapotranspiration along with soil water content (SWC) dynamics in a heterogeneous urban landscape is fundamental for developing effective water management practices. The unmanned aerial vehicle (UAV) remote sensing with high spatial and temporal resolution offers a promising method for monitoring SWC and spatial mapping of ET. In this study, UAV-based multispectral and thermal data were acquired in an experimental field with four landscape groundcover species over two years (May-October 2022 and 2023). Two regression models, including multiple linear regression (MLR) and random forest regression (RFR), were used to predict soil moisture at depths of 10 and 30 cm. The results indicated that both regression models, MLR and FRF, exhibited a relatively good SWC prediction accuracy with Pearson’s r ranging 0.62-0.68, root mean square error (RMSE) ranging 0.034-0.048 cm3cm-3, and mean absolute error (MAE) ranging 0.034-0.038 cm3cm-3. Additionally, two energy balance models, a modified version of SSEBop and pySEBAL, were used to estimate ET for four groundcover species. The performances of models were evaluated against measured ET using the soil water balance approach. Model comparisons indicated that ET estimates for both models correlated well with ET measurements, with Pearson’s r ranging from 0.798-0.928 for the modified SSEBop and 0.843-0.961 for the pySEBAL model. However, the pySEBAL model had lower RMSE values (0.660-1.155 mm day-1) compared to the SSEBop model (0.870-1.270 mm day-1). This study shows that high-resolution UAV imagery combined with energy balance models can be used to estimate ET accurately for different urban vegetation types.

Zahra Amiri · CVEN · Postdoctoral Associate

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Using Photogrammetry to Monitor Hydrologic and Geomorphic Changes in West Stroh Gulch

Sarah Rogers — Tue, 01 Apr 2025 20:00:00 +0000

Using Photogrammetry to Monitor Hydrologic and Geomorphic Changes in West Stroh Gulch Sarah Rogers Tue, 04/01/2025 - 14:00 Eric Balderrama Sanchez

Urban development can have a large impact on streams, and tracking these changes over time is important for future urban planning. This project focuses on West Stroh Gulch, a non-perennial stream in Parker, Colorado, where new housing development is underway. To monitor how the landscape and stream morphology change, we are using drone-based photogrammetry to create high-resolution Digital Elevation Models (DEMs) and orthomosaic maps. By flying a drone every few months and processing aerial imagery, we can generate a visual timeline of how urbanization affects the stream channel and surrounding area. These models will be compared over time to highlight topographic changes and help improve our understanding of development-driven hydrologic shifts.

Eric Balderrama Sanchez · CVEN · BS Student

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Evaluating the effect of spatial discretization on the predictive ability of western U.S. snow-streamflow relationships

Sarah Rogers — Tue, 01 Apr 2025 19:55:00 +0000

Evaluating the effect of spatial discretization on the predictive ability of western U.S. snow-streamflow relationships Sarah Rogers Tue, 04/01/2025 - 13:55 Kaitlyn Bishay

Across much of the western U.S., the prediction of seasonal water supply (defined here as April-July total streamflow volume) depends on annual snow accumulation, with snowmelt accounting for up to 70% of total runoff. Although many operational forecasts rely heavily on sparse in situ snow measurements, previous work by the author team found that in many cases, satellite-derived snow timing variables (e.g., the day of snow disappearance) are as, or even more, effective than in situ data in predicting seasonal water supply when applied to data-driven regression models. This work expands previous spatial and temporal ranges to include approximately 100 study basins and satellite-derived data from the water years 1985-2021. This larger set of basins includes both ‘monitored’ basins — equipped with in situ snow monitoring stations — and ‘unmonitored’ basins — allowing the team to assess the ability of remotely sensed snow data to replace in situ measurements in data-scarce locations. This analysis considers the effect of varied discretization methodologies (i.e., dividing each basin into subdomains by aspect, clustering algorithms, etc.) on model skill. By quantifying the importance of these subdomains and their skill in forecasting seasonal water supply across the western U.S., this analysis provides insights that will guide future data-driven analyses.

Kaitlyn Bishay · CVEN · PhD Student

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Analyzing Urban Rain-on-Snow Events

Sarah Rogers — Tue, 01 Apr 2025 19:50:00 +0000

Analyzing Urban Rain-on-Snow Events Sarah Rogers Tue, 04/01/2025 - 13:50 Maryam Buhamad

Climate impacts have been causing changes in weather patterns, increasing extreme weather events, and changing the frequency and timing of rain events, causing them to happen earlier in the season leading to rain-on-snow events. These events generate more runoff compared to rainfall or snowfall alone, making them a critical concern for stormwater management. While rain-on-snow events have been studied in mountainous regions, research on their impacts in urban areas with high imperviousness in the United States remains limited and stormwater systems are designed without considering ROS impacts. Previous literature revealed that Low Impact Development designs and detention ponds worked best in cold climates to mitigate excess runoff.

In this study, historical climate data from the National Weather Service was used to analyze the frequency and extremity of rain-on-snow events in Cleveland Ohio, with their hydrologic impacts simulated through the Storm Water Management Model (SWMM). The study aims to improve the identification of rain-on-snow events and assess key characteristics and drivers. We found that varying definitions of rain-on-snow events can influence the number and type of events identified. Of particular interest were those events that have a significant hydrologic impact in urban areas, causing more runoff. Those events are better identified with a combined criterion and are found to generate substantially greater hydrologic response.

Results indicate that the precipitation component of rain-on-snow events plays a crucial role in driving snowpack melting and increased runoff generation. Compared to elevated temperatures alone, rainfall was the dominant factor in accelerating snowmelt and producing higher peak flows. Notably ROS events resulted in 18% higher peak flows compared to an all rainfall condition. These findings highlight the significance of precipitation as a primary driver in rain-on-snow events and the need to adapt stormwater infrastructure to account for such events in urban environments. Future studies should further investigate mitigation strategies that reduce runoff impacts in urban settings.

Maryam Buhamad · CVEN MS · Student

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Investigating the emergence of climate change signals in the Upper Colorado River Basin

Sarah Rogers — Tue, 01 Apr 2025 19:45:00 +0000

Investigating the emergence of climate change signals in the Upper Colorado River Basin Sarah Rogers Tue, 04/01/2025 - 13:45 Sydney Carr

Seasonal snowmelt is a primary contributor to annual runoff in the Upper Colorado River Basin (UCRB), a region that serves as a critical water resource for the western United States. Recent shifts in temperature and precipitation patterns due to climate change have altered the behavior of annual snowpack in the mountain headwaters, increasing variability in downstream basin hydrology. Identifying the timing and magnitude of significant hydrometeorological change is critical for assessing the impacts of anthropogenic climate change on snow-driven water resources. As many natural and human systems are adapted to local climate variability, further characterizing these changes relative to a reference climate state is essential for informing operations and management decisions. We present a multi-model framework to detect the emergence of anthropogenic climate change signals in snow water resource metrics for the UCRB. Four members of the CESM2 Large Ensemble were dynamically downscaled to a 3 km grid resolution at a daily timestep from 1980-2100. Time series for air temperature, precipitation, and peak snow water equivalent (SWE) were spatially averaged to nine HUC 6 subbasins and aggregated to seasonal and annual averages. Time of Emergence (ToE) was defined as a statistically significant deviation from historical (1980-2010) variability. On average, trends in air temperature emerge from the historical distribution for all subbasins by 2017, with a warming rate of 0.50 C / decade. Conversely, declines in annual peak snow water equivalent emerged much later, by 2072 in all but one subbasin, at an average rate of -4.08% / decade. Trends in annual or seasonal precipitation did not emerge in most subbasins. Results emphasize the importance of evaluating multiple hydrometeorological metrics in the assessment of UCRB snow water resource trends. Future work will extend to include a comprehensive evaluation of relevant metrics, including discharge and elevation bands within subbasins of the UCRB.

Sydney Carr · GEOG · PhD Student

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Improving Access to High-Elevation Snowpack Data for Regional Water Resource Management

Sarah Rogers — Tue, 01 Apr 2025 19:40:00 +0000

Improving Access to High-Elevation Snowpack Data for Regional Water Resource Management Sarah Rogers Tue, 04/01/2025 - 13:40 Emelina Catterson , Eric Gosnell , Samuel Plunkett , Isabelle Sease

High elevation snowpack plays an important role in providing regional water resource management, however there is no current practice that efficiently summarizes data at high elevation sites. This gap in accessible information highlights the need for efficient data compilation methods and collaboration between researchers and resource managers. There is potential to consolidate high elevation snowpack data so it is better suited for use by Boulder’s water resource managers. As snow hydrology interns with Niwot Ridge LTER, we collect SWE from snow depth, snow temperature, grain type/size, and snow density. Data is collected on a weekly basis, with the source alternating between a subalpine forest site and an alpine tundra site. SWE varies drastically throughout the Boulder Creek Watershed, and can prove difficult to accurately estimate from data collected at the subalpine SNOTEL sites alone. The high elevation data is especially useful for resource managers obtaining an accurate representation of regional snowpack and water resources.

Our goal with this project is to compile the data we have collected throughout the 2025 season and standardize it in a usable format for resource managers. We intend to create a graphical representation that resembles a similar format to SNOTEL data, which is typically used by water resource managers in the City of Boulder. This will serve as a more accurate representation of snowpack close to our watershed and enable resource managers to see high-elevation snowpack from the alpine site, which they do not currently have easy access to, promoting collaboration between research institutions and water resource managers. There is potential for this data sharing framework to continue being used throughout the future snow seasons.

Emelina Catterson, Eric Gosnell, Samuel Plunkett, Isabelle Sease · GEOG · BA Students

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Using Stream Outflow Data to Hindcast Ice Dynamics for a Subalpine Lake in Colorado

Sarah Rogers — Tue, 01 Apr 2025 19:30:00 +0000

Using Stream Outflow Data to Hindcast Ice Dynamics for a Subalpine Lake in Colorado Sarah Rogers Tue, 04/01/2025 - 13:30 Bryan Gager

As the global climate changes and temperatures continue to increase, lakes with seasonal ice coverage are experiencing reductions in ice duration. Decreased ice duration can have impacts on the chemical, biological, and physical processes in the lakes as well as downstream ecosystems. Records of ice-on and ice-off timing (“ice phenology”) on lakes are imperative for understanding the potential impacts on subsequent biogeochemical and ecological conditions. However, records of ice phenology are non-existent for many lakes. This gap could be filled with models that use meteorological or hydrological variables to reconstruct (“hindcast”) past ice phenology. To date, two modeling approaches have been used to determine the presence of ice on lakes: leveraging meteorological variables recorded in or near the watershed, or using water temperature sensors on buoys in the center of the lake. In contrast, this study tested the degree to which hydrological variables recorded at the outlet of The Loch, a subalpine lake in Rocky Mountain National Park, could be used to reconstruct an ice-clearance record.
To calibrate a model that determines ice presence, I used 10 years of streamflow, water temperature, and conductivity data from a Parshall flume at the lake outlet, alongside weekly photos of the lake that confirmed whether ice was on or off the lake. From there, I built logistic regression model versions that hindcasted the presence of ice on The Loch. I then applied the model version with the highest accuracy to the entire hydrological dataset for The Loch, which spans back to 1984, and created a time series of hindcasted ice-off dates. The variables used in the final model version (R2 = 0.88) were stream temperature and cumulative discharge. In most years, the probability of The Loch’s being ice free increased rapidly after cumulative discharge exceeded 14.16 m3/s, and stream temperature exceeded 5°C. This method for reconstructing ice clearance on lakes may be useful for other systems with infrequent in situ observations, and future work can evaluate its efficacy where both long-term ice measurements and lake outflow data exist. This method also takes advantage of automated and relatively inexpensive pressure and temperature sensors placed in the outflow of lakes , which could allow more lakes to be monitored.

Bryan Gager · EBIO · BA Student

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Validating the Results of a Coupled Daily Discharge and Stream Temperature Model for Southeast Alaska

Sarah Rogers — Tue, 01 Apr 2025 19:25:00 +0000

Validating the Results of a Coupled Daily Discharge and Stream Temperature Model for Southeast Alaska Sarah Rogers Tue, 04/01/2025 - 13:25 Colin Gilbert

River discharge and temperature are key indicators of change in hydrologic systems. Coupled daily streamflow and river temperature data provide extremely useful datasets in regions that otherwise would not have data. In this study, we adapt a model framework for coupled streamflow and river temperature estimation that was recently implemented in interior and northern Alaska. We then apply it to the smaller, glacier-dominated region of Southeast Alaska. The proposed research will employ three different models, two versions of a coupled atmospheric/land surface model that builds inputs for the River Basin Model (RBM), which produces daily river temperature data. we estimate daily streamflow and river temperature for Southeast Alaska. The model was run for a historical (1991-2020) scenario. To validate the results, we compared the daily discharge values of the gauges with modeled discharge along the gauge’s stream segment. In the case of this project, observations come from several USGS stream gauges in the study area. We assess model performance using Kling-Gupta and Nash-Sutcliffe efficiency metrics to compare the efficacy of our two atmospheric/land surface models. Observations are basin specific, thus localized conditions can indicate trends in model results and performance. We conducted a sensitivity test of physical parameters based on a state-wide calibration to determine the most appropriate parameter sets for this smaller study region. This modified version of the model framework for Southeast Alaska is transferable to other climate model input and regions. It will help assess the efficacy of both input models and assist in determining strengths and weaknesses of each model framework.

Colin Gilbert · GEOG · MA Student

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Abstract

Mercury Storage, Export, and Process Rates in Two Beaver-Dominated River Corridors in the Colorado, Rocky Mountains

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Geomorphic Response to Low-Head Dam Removal in Steep Mountain Streams

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Evapotranspiration and soil water content estimation of four urban landscape vegetations using UAV-based multispectral and thermal imagery

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Using Photogrammetry to Monitor Hydrologic and Geomorphic Changes in West Stroh Gulch

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Evaluating the effect of spatial discretization on the predictive ability of western U.S. snow-streamflow relationships

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Analyzing Urban Rain-on-Snow Events

Related Articles

Investigating the emergence of climate change signals in the Upper Colorado River Basin

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Improving Access to High-Elevation Snowpack Data for Regional Water Resource Management

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Using Stream Outflow Data to Hindcast Ice Dynamics for a Subalpine Lake in Colorado

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Validating the Results of a Coupled Daily Discharge and Stream Temperature Model for Southeast Alaska

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