NSF CAREER AWARD: OU Engineer to Develop Technologies for Studying Snowpack
This five-year project will allow the McDaniel Microwave Group to develop a custom unmanned aerial vehicle, or UAV-based radar suite with sophisticated signal processing techniques, to measure the depth and distribution of snow and ice to support actionable risk management strategies and socioeconomic resiliency from snow-related weather events.
The Power of Snow
Snowfall is a crucial component to Earth’s climate system. According to the U.S. Environmental Protection Agency and the U.S. Geological Survey, snowmelt provides approximately 75% of the water supply for the western United States.
“Here in the mid-central part of America, much of our water starts as snow on mountains. The water from that snow goes into watersheds in our lakes and rivers. Some of the water trickles down into our aquifers – what’s used for domestic, industrial or agricultural purposes,” McDaniel said.
In mountainous regions, the impacts of snowfall, snowmelt and snow distribution by the wind, are much broader.
“For residents in mountainous regions, especially in the Arctic, people rely on (snowmelt) for drinking water. They rely on it for ice roads, so transportation – and more importantly, they rely on it to not hurt their well-being because if that ice melts, it affects transportation routes. If a large piece of ice or several pieces of ice break off and clump together in a river – called an ice jamming event – it can cause floods. And probably the most notorious, snow avalanches, are a huge concern and the number one deadliest snow-related natural hazard,” he said.
“All of this comes back to understanding snow and its onset and melt, its characteristics or material properties, and its impact on the thermal balance between the underlying terrain, or ice, and the atmosphere,” he added.
Developing UAS-Based Radar Technology
For this project, McDaniel will develop custom snow- and ice-penetrating sensor technology that can be flown by UAS over snow-covered areas with the ability to produce detailed and fine-tuned data of snow hydrology, the study of the composition, dispersion, movement and distribution of snow, as well as data on snow-loading – the weight and density of snow – on freshwater lakes and river ice.
“In Year 1, we will take all of the science and what we know about snow and ice, and we will correlate that back to what part of the electromagnetic spectrum is most ideal for remote sensing and then build a system around it,” McDaniel said.
“One of the things that we want to look at is, can we utilize this radar data and use coherent change detection – a signal processing technique where you can fly over snowpack one day and understand where the distribution is. And then you can fly over the next day and based on how the snow moved, you can represent that change. That could give you a pretty good indicator of a high-risk avalanche zone if a large portion of the snow was relocated into one area,” he added.
By improving their understanding of bulk-snow characteristics and redistribution of snow by the wind, McDaniel and his collaborators, including researchers from CReSIS, or the Center for Remote Sensing and Integrated Systems at the University of Kansas, will be able to support snow-related risk mitigation methods like the potential for supporting safer and more effective avalanche search and rescue efforts, avalanche forecasting models, and snow fence placement used to prevent avalanches.
Once the initial system is developed, the research team will begin testing the system in the Fraser Experiment Forest, located on the outskirts of Denver and maintained by the U.S. Forest Service.
“(Fraser) is a representative testing ground because it is a mountainous region where we can experience many of the complexities in a field experiment that we expect to see in the Arctic,” he said. “Once this system is built and done some field testing, we can start data processing. How well did it work? What can you learn from that? What fine-tuning on the radar system can you do to make it work better?”
After refinement and continued iterations, McDaniel ultimately hopes this radar system will be able to scale for future Arctic and climate modeling applications beyond this five-year project.
Training the Next Generation
A unique component of the NSF CAREER program is an educational outreach component that connects students into research efforts. McDaniel, who was a first-generation college student, is particularly excited about the opportunities this presents. He will incorporate aspects of this project into his graduate and undergraduate courses, experiential laboratory exercises, summer internships, and as part of a “RISING STudent Ambassador Research” program, dubbed RISING STAR, aimed at supporting Native American and first-generation students.
“I'm excited about two things – one is, I'm going to offer summer internships, primarily targeted at the undergraduate level because I'm a major believer in undergraduate research,” McDaniel said.
One of the internship positions will be targeted at first-generation, economically disadvantaged and disabled students through Project Threshold, a program of OU’s TRIO Center – a federal outreach and student services program designed to identify and provide services for individuals from disadvantaged backgrounds. Another internship position will be filled through AISES, OU’s American Indian Science and Engineering Society.
The second component, McDaniel’s student ambassador program is intended to foster peer mentorship and support through the education pipeline.
“It's essentially a way to train students, get them integrated, get them very involved and well-versed in this kind of research as an undergraduate versus waiting until grad school,” said McDaniel. “The newcomers to the program are paired with a graduate student within my group, then they get research guidance, provided materials on career planning, graduate school, and creating a resume. And then these new students build their way up the program, return to their representative communities, and help recruit newer students to get involved with my research.”
“I'm very excited about first-generation students and bringing them into my group, to build a very strong, successful, and diverse group of researchers who help build the pipeline, and then ideally, that pipeline doesn't ever end,” he added.
About the Project
“CAREER: UAV-Based Radar Suite for Bulk-Snow Characterization and Risk Management” is funded by the National Science Foundation, award no. 2238620. The project begins Aug. 1, 2023, and is expected to conclude July 31, 2028.
By Chelsea Julian, Office of the Vice President for Research and Partnerships
