Poster

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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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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Comparison of Landscape Types on the Urban Heat Island Effect

Sarah Rogers — Tue, 01 Apr 2025 19:20:00 +0000

Comparison of Landscape Types on the Urban Heat Island Effect Sarah Rogers Tue, 04/01/2025 - 13:20 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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A Statistical Forecasting System for the Water Balance of a Large Terminal Lake in the Great Basin

Sarah Rogers — Tue, 01 Apr 2025 18:05:00 +0000

A Statistical Forecasting System for the Water Balance of a Large Terminal Lake in the Great Basin Sarah Rogers Tue, 04/01/2025 - 12:05 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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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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Quantifying Baseflow Using Groundwater Levels in The Upper Colorado River Basin

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

Quantifying Baseflow Using Groundwater Levels in The Upper Colorado River Basin Anonymous (not verified) Tue, 04/09/2024 - 12:00 Corrine Liu

The vitality of the Colorado River faces uncertainty in light of frequent and prolonged droughts induced by climate change. Progressing knowledge concerning the role of groundwater and surface water interactions is critical in informing water resource managers and Colorado River water users—namely, the mechanism of baseflow accounts for a substantial portion of streamflow. Baseflow is considered a proxy for groundwater discharge to streams. Groundwater is vital in sustaining streamflow via baseflow, particularly during periods of low precipitation and overland flow. Limited baseflow studies within the Upper Colorado River Basin indicate that approximately half of streamflow is accounted for by baseflow. This study aims to quantify baseflow to the Roaring Fork River, a major tributary within the Upper Colorado River Basin. The Roaring Fork River flows along the western margins of Colorado’s Southern Rocky Mountains physiographic province.

This study employed a new approach based on groundwater level data from the Colorado Division of Water Resources (CDWR). Groundwater level observations were compiled between 2000 and 2022 from over 150 wells in the Roaring Fork subbasin to ultimately interpolate static groundwater level elevations. Hydraulic gradients near the Roaring Fork River were elucidated from contoured groundwater levels. Existing estimates of hydraulic conductivity were analyzed using empirical pumping test formulae. On the basis of hydraulic gradient and hydraulic conductivity, a mean annual groundwater discharge of 1.57 m3/s to the Roaring Fork River is estimated. In parallel, baseflow separation using a graphical method was conducted, which yields a similar magnitude of baseflow. This study, for the first time, demonstrates the potential of utilizing existing groundwater level data to supplement the study of baseflow. Enriching the arsenal of baseflow analysis will help contribute to sustainable and informed water resource management.

Corrine Celupica-Liu • GEOL • MS 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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Communicating Nature Based Solutions to Reduce Urban Runoff within the Colorado Front Range

Anonymous — Tue, 09 Apr 2024 17:54:35 +0000

Communicating Nature Based Solutions to Reduce Urban Runoff within the Colorado Front Range Anonymous (not verified) Tue, 04/09/2024 - 11:54 Leanna Johnson

·According to the Water Education organization in Colorado, the Colorado population is increasing at a rapid rate and is expected to grow to 8.1 million by the year 2050. At the same time. Freshwater resources will continue to decline as the impacts of climate change continue. This leads to an impending water crisis in Colorado, so water conservation and protection strategies have been created.
Specifically, within the Urban environment, the natural water cycle is being disrupted. In the urban landscape, there are hard surfaces such as roads, sidewalks, and houses that cause increased amounts of runoff. The runoff collects pollutants that run into local waterways harming fish, wildlife, plants, and humans. Strategies, such as low-impact development (LID), Sustainable Urban Drainage Systems (SUDS), and Water Sensitive Urban Design (WSUD), have been created to manage wet weather flows and provide habitat, flood protection, cleaner air, and cleaner water. Our project’s goal was to create a way to communicate these strategies through a visual display to the public. We aimed to make the diorama relevant to the Front Range by deriving our data directly from major cities along the Front Range. The data consists of precipitation amounts, snow, and minimum and maximum temperatures. The diorama shows four scenarios that undergo a similar amount of rain. Natural grassland represents undeveloped land in Colorado, which consists only of native Colorado grass. Traditional Development represents a current house in Colorado with impervious surfaces and conventional landscaping, such as turf which is water intensive. Low Impact Development shows the ideal housing development with green infrastructure implemented. Post-wildfire is meant to show the impact of wildfires on a region's soil and water quality as wildfires are becoming more frequent.
Environmental problems are often viewed as problems that require large-scale solutions that the general public does not have access to implement. As the population of Colorado continues to increase so does the demand for fresh water. Climate change is decreasing the availability of freshwater at the same time. To prevent the loss of water resources both large-scale and local-scale solutions should be implemented. The general public can only help with this issue if they know these solutions. These decentralized nature-based solutions are how the public can get involved in protecting the Front Range for years to come.

Leanna Johnson · CEAE · BS Student

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Image analysis of stream channels for flow presence monitoring

Anonymous — Tue, 09 Apr 2024 17:53:21 +0000

Image analysis of stream channels for flow presence monitoring Anonymous (not verified) Tue, 04/09/2024 - 11:53 Junwon Lee

Efficient and accurate analysis of large amounts of images is critical for water monitoring studies. This study proposes the use of open-source deep learning, RGB and HSL-based OpenCV Python code as a solution to overcome the limitations of manually analyzing large numbers of images by humans. Previous studies have already utilized these technologies for water monitoring and analysis, but which technology is most suitable and efficient is not yet clear. In this study, RGB-based images and HSL images, and we plan to analyze them using RGB-based OpenCV Python code, HSL-based OpenCV Python code, and deep learning techniques. Through this, we will evaluate which technology produces the most accurate results and suggest a direction for developing efficient program tools for water monitoring research. This will support more accurate and reliable data acquisition in the field of water monitoring. And if this technology develops further, it will be possible to detect not only natural river flows but also urban floods using various crowdsource within the city.

Junwon Lee • CEAE• BS Student

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