Graduation Year
2021
Graduation Month
May
Document Type
Thesis
Degree Name
Bachelor of Science
School or Department
Geosciences
Major
Geosciences
Faculty Mentor Department
Geosciences
Faculty Mentor
Hilary Martens
Keywords
GPS, Geology, GNSS
Subject Categories
Geology
Abstract
Thousands of Global Positioning System (GNSS) receivers worldwide record signals sent by satellites to infer how each receiver (and the ground they are attached to) moves over time. The motion of GNSS receivers is used for many purposes, including studying tectonic deformation and changes in Earth's shape caused by surface loading. In this project, reflected wave arrivals contained within the multipath signal of GNSS time series are extracted and analyzed to advance understanding of snow properties in mountainous regions of Montana/Idaho, USA. Analyzing reflected signals in GNSS series has the potential to reveal properties of local snowpack, such as height, water content, snow surface temperature, dielectric properties, and density. Improving our ability to monitor the physical characteristics of snowpack and how they evolve over space and time is essential as properties of snow are key to understanding the slippage of one layer on another, which impacts avalanche hazard. Moreover, snowpack monitoring provides information about the availability of water resources and snow hydrology. This project focuses on analyzing the ray paths and attenuation of reflected GNSS signals, also using reflections to infer properties of snow. Traditionally, to study snow properties, one must manually dig a snow pit to study the snowpack and/or use expensive remote-sensing technologies (e.g. InSAR). However, digging snow pits can be dangerous due to avalanche risk as well as costly and time inefficient. Relatively low-cost GNSS stations that are now widely deployed worldwide present new opportunities to study snow properties, including in developing nations with fewer financial resources. We will use GNSS interferometric reflectometry (GNSS-IR) software developed by Kristine Larson (CCAR) to infer snow depth data from GNSS multipath. Results will be validated with snow-height data from nearby Snow Telemetry (SNOTEL) stations.
Honors College Research Project
Yes
GLI Capstone Project
no
Recommended Citation
Khatiwada, Ashlesha, "Analyzing the multipath of GPS time series to study snow properties" (2021). Undergraduate Theses, Professional Papers, and Capstone Artifacts. 352.
https://scholarworks.umt.edu/utpp/352
Included in
© Copyright 2021 Ashlesha Khatiwada