Graduate Thesis Or Dissertation

 

New Metrics, Modeling Applications, and Observational Strategies for Snowpacks in Remote, Data-Limited, Mountain Environments Public Deposited

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https://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/tb09jc31s

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  • The topics in this dissertation center on the snow processes that dominate mountain environments in the Western U.S. and Alaska, particularly in locations lacking long-term observational datasets or locales that are difficult to access in-person. Some are currently glacierized or have been glaciated in the recent past. Each of the three projects and study areas have hydrographs that are highly influenced by winter snowpack and spring snowmelt, and the processes that govern snowpack evolution and ablation during the water year. Each of the research questions in the following three projects were designed within the context of anthropogenically forced changes to temperature and precipitation, and the downstream implications for water resources management. These forces of change may be enhanced in the coming decades as our global economic pursuits continue to pump, unabated, gigatons of greenhouse gases into the atmosphere. The circumstances of this current and future non-stationarity of the climate system affects the assumptions made during the formation of each research question. The research projects in the following chapters are built on the foundation of the three legs of successful snow research: 1) physically-based modeling of snow processes, 2) remote sensing of snowpacks, and 3) ground observations of snow conditions. Chapter 1 is a general literature review connecting theories and ideas from several disciplines relevant to the research questions from each chapter. The literature review includes a history of energy balance and snowmelt modeling, an overview of physically-based snow modeling, and discusses citizen science in the hydrologic sciences. Chapter 2 is an investigation into the seasonal components of freshwater discharge to Glacier Bay, Alaska. The chapter includes a historical analysis and a future projection scenario of freshwater runoff based on climatic changes in temperature and precipitation by the end of the century. The key findings of this research show that projection scenario runoff to Glacier Bay, Alaska, in the last three decades of the 21st Century will be more influenced by rain and less influenced by snowmelt than the historical conditions from the 1979 to 2015 period. Chapter 3 introduces new snow metrics built from the Moderate Resolution Imaging Spectroradiometer satellite collection of snow covered area using Google Earth Engine’s cloud computing and storage capabilities. This research enables access for a variety of users to terabytes of satellite data in an efficient manner, allowing them to calculate how often snow occurs on the land surface in any location globally (snow cover frequency; SCF) and the day of the year that snow disappears from the landscape (snow disappearance date; SDD). Chapter 4 outlines the Community Snow Observations project that incorporates citizen science-based snow depth measurements into the process modeling chain in order to constrain snow depth and snow water equivalence outputs from the model. This chapter represents the first time citizen science-based snow measurements have been incorporated into the snow process model workflow and the improvements in model output are described within the chapter. Chapter 5 outlines general conclusions from each individual chapter and looks forward to future research topics. Chapter 6 includes all references from each individual chapter.
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  • 2019-09-06 to 2020-10-07

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