Poster

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

Sarah Rogers — Wed, 02 Apr 2025 14:13:52 +0000

Improving Access to High-Elevation Snowpack Data for Regional Water Resource Management Sarah Rogers Wed, 04/02/2025 - 08:13 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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A Statistical Forecasting System for the Water Balance of a Large Terminal Lake in the Great Basin

Sarah Rogers — Wed, 02 Apr 2025 14:08:42 +0000

A Statistical Forecasting System for the Water Balance of a Large Terminal Lake in the Great Basin Sarah Rogers Wed, 04/02/2025 - 08:08 Manish Venumuddula

The rising anthropogenic demand for water and increased variability of water levels is a challenge for lakes across North America. Many terminal lakes in the Great Basin struggle in the face of anthropogenic demand and climate change.

Mono Lake is a terminal lake in eastern California that supplies freshwater to a small fraction of Los Angeles residents. Chronic water level decline has been an issue at Mono Lake for the past century due to a combination of long-term diversions and drought. This has caused ecological and hydrologic damage in the basin, and despite previous conservation efforts and legislation, it still jeopardizes the future of Mono Lake. Mono Lake’s continuing struggle and the subsequent push for new water management legislation underscores the importance of hydrologic modeling of the past, present, and future to understand how water balance components interact and provide more information for policymakers in California.

In this research, we present a two-step statistical approach to tackle the modeling challenges implicit to Mono Lake. More specifically, we use a modeling framework (the Large Lake Statistical Water Balance Model (L2SWBM)) to close the historical water balance, quantify uncertainty, and provide a probabilistic basis for simulating water levels under different climate and water management conditions. Using results from the L2SWBM, we apply a regular vine copula to capture relationships between water balance components and allow for unlimited sampling and range.

The goal of this research is to create a probabilistic forecasting system of the Mono Lake water balance and equip decision makers/community members with an understanding of the impacts of both climate and human activities on Mono Lake. The forecasting system developed in the study area creates a tool to resimulate historical and future water levels under various diversion and climate scenarios. This allows for a deep analysis of the impacts of each climate and diversion scenario on Mono Lake water levels.

Manish Venumuddula · NSF NCAR · Researcher

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Modeling formative floods in gravel-bedded rivers with bedfast ice

Sarah Rogers — Tue, 01 Apr 2025 19:59:04 +0000

Modeling formative floods in gravel-bedded rivers with bedfast ice Sarah Rogers Tue, 04/01/2025 - 13:59 Josie Arcuri

Gravel-bedded rivers are shaped during floods. Over time, certain floods do the most “geomorphic work” on river beds and banks by maximizing the product of sediment transport magnitude and frequency. The flood that does the most geomorphic work is known as the “formative flood” - it may not be the peak, but it reoccurs more often. However, it is unclear if this concept applies to freshet-dominated rivers in the Arctic. Gravel-bedded rivers in the Arctic continuous permafrost zone are occupied by river ice for 7-9 months each year. Freshet-dominated rivers in this region, like the Canning River, AK, receive a peak flood following snow melt while river ice can resist breakup for weeks, extending flood duration and magnitude. Still, the spring freshet occurs when hydraulic cross-sections are restricted by bedfast ice, limiting bed and bank exposure, but maximizing stage height. In contrast, summer floods generated by storm runoff occur when ice is absent, multiple times per year. Still, river bank and bed gravel is coarse and difficult to transport under low flows. We aim to investigate which flood maintains the Canning River’s hydraulic geometry, and more generally the hydraulic geometry of all ice-impacted, gravel-bedded rivers.
We explore if there is a formative flood for rivers that develop bedfast river ice with Basement V4. We focus on a 20 km long reach of the Canning River in Arctic Alaska, where we monitored break-up period from 2021 through 2024. We use USGS data for realistic peak discharges and ArcticDEM for surface topography, and field measurements of river ice thickness as primary model inputs. We assess geomorphic significance with metrics for potential sediment transport. To quantify the geomorphic significance, we compare bed and bank shear stresses produced by floods to thresholds for sediment entrainment and bank widening.
Initial results suggest that no realistic discharge can fill the bankfull channel or erode river banks when the channel is free of ice. Conversely, we find that these floods can sediment transport and bank erosion when bedfast ice persists. For the Canning River, the spring freshet is likely the formative flood. Our findings also show that the bedfast river ice can enhance bank erosion and might lead to wider rivers. The significance of river ice in this setting emphasizes that the stability of Arctic Rivers depends on river ice.

Josie Arcuri · GEOL · PhD Student

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Effects of Air Temperature Warming on Groundwater Flow in an Alpine, Glacierized Watershed

Sarah Rogers — Tue, 01 Apr 2025 19:54:46 +0000

Effects of Air Temperature Warming on Groundwater Flow in an Alpine, Glacierized Watershed Sarah Rogers Tue, 04/01/2025 - 13:54 Corrine Liu

Glacial mass loss due to climate change has been well documented for decades and is projected to continue as air temperatures rise. Baseflow, known as a proxy for groundwater discharge to streams, can be derived from subglacial melt recharge. The groundwater regime thus acts as a hydrologic buffer and connector between glacial melt recharge and streamflow, particularly during periods of low precipitation or overland flow. Understanding the temporal and spatial relationship between glacial melt, baseflow, and subsequent streamflow is necessary to assess the sustainability of current and future streamflow conditions. To evaluate how groundwater flow connects glacial meltwater to downstream hydrology both temporally and spatially, a 2D coupled heat transfer and groundwater flow model with seasonal freeze-thaw was developed using USGS Saturated-Unsaturated Transport modeling software (SUTRA).
Arikaree glacier is an alpine glacier located in Green Lakes Valley in the upper Boulder Creek watershed in Boulder, Colorado. Melting of Arikaree has potentially notable impacts on streamflow. Because of Arikaree’s small size, changes in mass balance occur on human timescales, which can be feasibly observed and underscore the importance of understanding flow dynamics in this region. Using 3 different air temperature warming scenarios, based on the Intergovernmental Panel on Climate Change (IPCC) projections or observed warming trends within the Green Lakes Valley watershed, the subsurface temperature and groundwater flow field underneath Arikaree glacier is simulated. Groundwater flow and heat transport in alpine regions is defined by phase transitions between solid ice and liquid water as subsurface temperature fluctuates seasonally. With future warming the spatial extent of seasonal freeze-thaw may expand, impacting glacial melt-groundwater-surface water dynamics. We elucidate groundwater discharge rates, and how these rates vary seasonally and throughout decades into the future. Furthermore, we aim to quantify how the addition of a frozen soil routine, in which changes to subsurface permeability due to the presence of ice are considered, impacts the magnitude and location of groundwater discharge under projected air temperature warming scenarios.

Corrine Celupica-Liu · GEOL · MS

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

Sarah Rogers — Tue, 01 Apr 2025 19:47:56 +0000

Using Photogrammetry to Monitor Hydrologic and Geomorphic Changes in West Stroh Gulch Sarah Rogers Tue, 04/01/2025 - 13:47 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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Laboratory Experiments to Understand Post-Wildfire Soil Sealing Processes in Complex Terrain

Sarah Rogers — Tue, 01 Apr 2025 19:44:10 +0000

Laboratory Experiments to Understand Post-Wildfire Soil Sealing Processes in Complex Terrain Sarah Rogers Tue, 04/01/2025 - 13:44 Nana Afua Gyau Frimpong

The effects of wildfire ash on soil properties, particularly its role in soil sealing, have far-reaching consequences for hydrological processes. The western United States faces an increasing frequency and intensity of wildfires, which has implications for post-fire soil behavior. Here, we aim to advance the understanding of soil sealing and hydrological fluxes following wildfires, focusing on the impacts of ash on the ground surface after the first rainstorms following a wildfire. Using controlled laboratory experiments, we assessed changes in hydraulic conductivity at the soil-ash interface, utilizing the mini-disk infiltrometer, KSAT, and HYPROP instruments. Soils treated with ash demonstrated an increase in water retention and unsaturated hydraulic conductivity but a decrease in field-saturated hydraulic conductivity. At the soil interface there was an increase in hydraulic conductivity. The (Kfs) for the experiment flumes rose from 48.5 cm/day to 112.97 cm/day post-burn (p-value = 0.00015) and declined from 112.97 cm/day to 51.58 cm/day post-rainfall (p-value = 0.000015). The impact of slope angle on ash erosion was minimal. �鶹��Ƶ 80% of the ash applied to the surfaces is retained after rainfall across different slope areas. Ash affects soil hydraulic properties in the short term, but its impacts can vary depending on environmental factors such as rainfall intensity and suction conditions.

Nana Afua Gyau Frimpong · University of Wyoming Civil Engineering · MS Student

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Comparison of Landscape Types on the Urban Heat Island Effect

Sarah Rogers — Tue, 01 Apr 2025 19:36:24 +0000

Comparison of Landscape Types on the Urban Heat Island Effect Sarah Rogers Tue, 04/01/2025 - 13:36 Nicholas Guthro

The urban heat island effect (UHI) is the studied effect that urbanized areas experience higher temperatures than non-urbanized areas due to the increase in buildings, roads, and other infrastructure. UHI has been seen to affect people living in areas classified as socially vulnerable disproportionately. Newer metrics, like Wet Bulb Globe Temperature (WBGT), are being used instead of air temperature to more accurately capture UHI's effects on individuals as it captures air temperature along with other metrics like humidity, cloud cover, and wind speed. This study looks at initial field data that captured WBGT over five different landscapes over three days in a park in Denver, Colorado. Initial results show that turfgrass alternatives such as native grass and squeegee planting beds have similar cooling effects as conventional turfgrass. Upcoming work, such as remote sensing of large-scale replacement projects and further location of fieldwork, will be discussed.

Nick Guthro CVEN PhD Student

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Rainfall and Streamflow Analysis of Depression Losses at the Rocky Flats National Wildlife Refuge

Anonymous — Wed, 10 Apr 2024 17:39:47 +0000

Rainfall and Streamflow Analysis of Depression Losses at the Rocky Flats National Wildlife Refuge Anonymous (not verified) Wed, 04/10/2024 - 11:39 Eric Balderrama

This study is centered around the analysis of rainfall and streamflow data collected from a watershed located within the Rocky Flats National Wildlife Refuge. The data was systematically filtered and cleaned to avoid skewness and potential error. Afterwards, a statistical analysis of the data was conducted which led to the creation of detailed relationships between rainfall and streamflow with the intention of updating historical depression loss values. Mile High Flood District (MHFD) gives up depression loss values of 0.2-0.6 in. for open fields, with a recommended value of 0.4 in. This means that we can expect 0.2-0.6 in. to get temporarily captured in depression storage, preventing it from becoming runoff. Now, when we look at the highest and lowest (non-zero) rainfall depths captured by the closest rain gage, in relative proximity to the watershed, which did not result in a flow event, we see these values are 2.48 in. and 0.04 in., respectively. This is significant because the largest value that did not result in a streamflow event is magnitudes larger than that of the recommended value of 0.4 in, indicating much of the captured rainfall must have been lost elsewhere. The relevance of this analysis is not to be underestimated, as it allows for the understanding of the threshold at which a flow event occurs. Additionally, there were 13 streamflow events in the 5-years’ worth of data that were captured with a delayed start time. Of the 13 events, the average delay time from the first instance of rainfall to the first detection of streamflow was 04:51 [hh:mm] with a standard deviation of 04:26 [hh:mm]. The data was further filtered and any time delay above 300 minutes was removed. This led to only 9 rainfall events that led to streamflow being analyzed. The time delay average and standard deviation of these events was 02:16 [hh:mm] and 01:21 [hh:mm], respectively. The investigation of depression losses in open fields presented a unique opportunity to examine the intricate relationship between rainfall depth and flow events. It was recognized that just before the threshold for flow events was reached, a significant quantity of rainfall was lost in depression storage. Therefore, the rainfall quantity was recorded for these 9 specific instances of delay time. The rainfall depth average and standard deviation are 0.64 in. and 0.50 in., respectively. These values allow for a much clearer comparison between the depression loss values given by MHFD and the data from the observed watershed.

Eric Balderrama · CEAE · BS Student

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Water Supply Prediction in Unmonitored Basins: Integrating Statistical Models and Remotely Sensed Snow Data

Anonymous — Tue, 09 Apr 2024 18:01:00 +0000

Water Supply Prediction in Unmonitored Basins: Integrating Statistical Models and Remotely Sensed Snow Data Anonymous (not verified) Tue, 04/09/2024 - 12:01 Kaitlyn Bishay

Accurate predictions of seasonal water supply are vital to all communities – regardless of their size, population, or location – as they are the basis for informed water resource decisions. Throughout the western U.S., predictions of total annual streamflow often rely upon spatially limited in situ snow measurements, which may not be available in all watersheds. However, previous work by the author team showed that these in situ measurements can be supplemented (or even replaced) by remotely sensed snow timing data. Initial findings for fifteen snow-dominated basins during the years 2001-2019 indicate the existence of a significant (p ≤ 0.05) predictive linear relationship between remotely sensed day of snow disappearance (DSD) and seasonal water supply, with mean DSD explaining roughly half of the variance in AMJJ total flow volume. This work expands on the spatial and temporal extents of previous research, describing the skill of these remotely sensed variables as predictors of water supply in over one hundred basins with varied watershed characteristics (elevation, SWE/P ratio, etc.) Further, we are particularly interested in the utility of remotely sensed snow disappearance in basins that lack in situ monitoring. By comparing the skill of watershed scale Monte Carlo linear regression models across monitored and unmonitored basins, this analysis provides new insight into the potential for remotely sensed data-driven models across the western U.S.

Kaitlyn Bishay · CEAE · PhD Student

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Comparative Analysis of Snow-Water Equivalent Measurements: Insights from Niwot Ridge

Anonymous — Tue, 09 Apr 2024 17:59:10 +0000

Comparative Analysis of Snow-Water Equivalent Measurements: Insights from Niwot Ridge Anonymous (not verified) Tue, 04/09/2024 - 11:59 Samuel Fitterman , Drake Stasyshyn , Eva Ramm , Jennifer Frances Morse

This study investigates the correlation between snow: depth, water equivalent and density measurements taken by the SNOTEL 663 site and those obtained through the Federal Snow Sampler at C1 on Niwot Ridge from 2016 - 2023. Utilizing linear regression analysis, we examined the relationship between the two measurement techniques to assess their comparability and reliability. Our study identified moderate positive correlations between SNOTEL and Federal Sampler measurements for snow depth and snow water equivalent (SWE) on Niwot Ridge, demonstrating that SNOTEL data can partially explain the variability in Federal Sampler readings. The regression analysis yielded a correction equation for Federal Sampler density measurements based on SNOTEL data, facilitating further insight into achieving accurate water availability forecasting. Niwot Ridge is located in the Front Range of the Colorado Rockies and is a designated United Nations Educational, Scientific and Cultural Organization (UNESCO) Biosphere Reserve. The C1 site is characterized by its relative shelter within a subalpine forest on a ridge with an elevation of 3022 meters. The SNOTEL site is approx. 262 meters to the WNW of the C1 pit site. By analyzing the correlations between these methodologies and employing linear regression to establish a correction equation, this research aims to enhance data comparability and reliability, thereby improving water resource management and predictive modeling in snow hydrology within the subalpine ecosystems of the Colorado Rockies.

Samuel Fitterman, Drake Stasyshyn, Eva Ramm, · GEOG · BA Students

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