Non-Destructively Mapping the In-Situ Hydrologic Properties of Snow, Firn, and Glacial Ice with Georadar

• Main Author: Brown, Joel Matthew
• Format: Text
• Language: unknown
• Published: ScholarWorks 2012
• Subjects: Georadar; Cryosphere; Icesheet; Snow; Geophysics and Seismology; Greenland; Ice Sheet; ice covered areas
• Online Access: https://scholarworks.boisestate.edu/td/318; https://scholarworks.boisestate.edu/context/td/article/1319/viewcontent/Brown_Joel_Matthew_dissertation_May_2012.pdf

Ground penetrating radar (GPR) is a useful tool for studying the in-situ properties of glacial ice, firn, and snowpacks. The main focus of this dissertation is improving and expanding methods employed when collecting, processing, and understanding GPR data collected in the Cryosphere, or the snow and ice covered areas of the earth. The data used herein were collected on the Greenland Ice Sheet (GrIS) and on seasonal snowpacks of Western Montana, USA. This document has three sub-topics. The first sub-topic is comparing the spatial variability of GPR data to the spatial variability of core data collected in two locations within the percolation zone of the GrIS that receive consistently different amounts of melt. At the location with less melt, I collected common offset GPR data over a 20 m x 20 m grid with tightly spaced data (0.2 m x 0.1 m), and then collected 8 cores within the grid. The cores reveal a high degree of spatial variability over short distances with no obvious correlation of layers between cores whereas the radar data reveal many spatially continuous horizons with discontinuities from 0.1 m2 – 1.0 m2. At the site with a higher melt rate, I collected common offset GPR data over a 15 m x 50 m grid with tightly spaced data (0.2 m x 0.1 m), and then collected 2 cores within the grid. The cores revealed some degree of lateral continuity of layers that corresponded well with spatially continuous GPR horizons. The second sub-topic of this dissertation is using Common Midpoint (CMP) GPR data to calculate the density vs. depth profiles at 13 locations within the percolation zone of the GrIS. Here, I constructed a set of rules to constrain an inversion of the data to solve for the EM propagation velocity of the firn column which is dependent on the density of dry snow and firn. The calculated density profiles indicate that firn densification is not greatly affected by melt in the highest elevation areas of the percolation zone whereas firn densification is primarily driven by melt/refreeze processes in the ...