CAREER: UAV-Based Radar Suite for Bulk-Snow Characterization and Risk Management

University Of Oklahoma Norman Campus, Norman OK

Investigators

Abstract

Snow is a crucial component of the earth’s climate system due to its extensive surface coverage and the critical role it plays as part of the cryosphere. Seasonal snowpack runoff profoundly influences the distribution of meltwater in watersheds, which constitutes roughly one-sixth of the freshwater needs globally, and the majority of water resources in mountainous regions. Moreover, snow acts as a thermal blanket between the atmosphere and underlying ice, that leads to impacts on freshwater lake ecosystems and has socioeconomic implications given its critical role in transportation (e.g., ice-road duration) and ice-jam flooding. Therefore, studying this hydrological cycle is crucial, especially with model projections suggesting a low-to-no snow future due to persistent emissions of greenhouse gases and globally rising temperatures. However, there are large uncertainties in capturing the fine details of this cycle and the hydrological consequences. This is partly because there are not enough measurements of distributed bulk-snow characteristics in important areas such as inaccessible mountainous regions. These observational gaps limit our ability to accurately develop robust modeling and forecasting techniques for improved risk management and hazard mitigation proposes. This CAREER project addresses this data need by equipping a small unmanned aerial vehicle (UAV) with an advanced radar suite to produce fine spatial and temporal resolution measurements of snowpack properties such as snow depth, snow water equivalent, relative density, and liquid water content. The integrated research and education project also involves preparing, training, and exciting the next generation of remote sensing engineers to engage in multi-disciplinary careers. Beyond providing research opportunities to undergraduate and graduate students, this project will integrate research concepts into the teaching and laboratory curriculum, providing academic and experiential learning opportunities. This CAREER project would encompass both the development of a new UAV-based custom snow-penetrating sensor technology and enable research on the snow hydrology and snow-loading on freshwater lakes and river ice. The technological research will produce fine spatiotemporal data using intelligent monitoring capabilities that allow mapping of snow loading and ice thickness on freshwater lakes and rivers through 3D echogram formation and wind redistribution of snow using coherent change detection. These data would support actionable risk management strategies that drastically improve residents’ lives and socioeconomic resiliency. The CAREER project will also incorporate aspects of this research in graduate and undergraduate courses, includes experiential laboratory exercises through design-build projects, and as part of the RISING STudent Ambassador Research (RISING STAR) program will involve Native American and first-generation students to increase diversity and interest in STEM careers. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.