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Full-Text Articles in Physical Sciences and Mathematics
Hydrologic Implications Of Snow-Vegetation Interactions In A Semiarid Mountain Climate, Maggi Kraft
Hydrologic Implications Of Snow-Vegetation Interactions In A Semiarid Mountain Climate, Maggi Kraft
Boise State University Theses and Dissertations
Knowledge of the complex interaction between snow, vegetation, and streamflow in semiarid mountain climates is necessary for predicting water resources. The effects of warming temperatures on snow distribution will cascade into vegetation water use and streamflow. Due to our reliance on snow water resources, it is necessary to understand how vegetation affects snow distribution, how vegetation uses snow water inputs and the subsequent effects on streamflow in the current and warming climate. The overall objective of this research is to improve our understanding of snow-vegetation interactions in a semiarid climate. In this dissertation, I use field data to evaluate how …
Using Remote Sensing Data Fusion Modeling To Track Seasonal Snow Cover In A Mountain Watershed, Allison N. Vincent
Using Remote Sensing Data Fusion Modeling To Track Seasonal Snow Cover In A Mountain Watershed, Allison N. Vincent
Boise State University Theses and Dissertations
Seasonal snowfall is the largest component of the water budget in many mountain headwater regions around the world. In addition to sustaining biological water needs in drier, lower elevation areas throughout the year, mountain snowpack also provides essential water inputs to the Critical Zone (CZ) - the outer layer of the Earth’s surface, which hosts a variety of biogeochemical processes responsible for transforming inorganic matter into forms usable for life. Water is a known driver of CZ activity, but uncertainty exists in its spatial and temporal interactions with CZ processes, particularly in the complex terrain of heterogeneous mountain areas. Increasing …
Investigating The Annual Water Balance Of A High-Altitude Watershed Using Near-Real Time Lidar Data Integration Into A Physically Based Snowmelt Model, Andrew R. Hedrick
Investigating The Annual Water Balance Of A High-Altitude Watershed Using Near-Real Time Lidar Data Integration Into A Physically Based Snowmelt Model, Andrew R. Hedrick
Boise State University Theses and Dissertations
Knowledge of the amount of water stored in the mountain snowpack is crucial for flood prevention, drought mitigation, and energy production in the Western United States. In modeling terms, the most important component of the hydrologic water balance is the precipitation input to the system. Determining where and how much precipitation falls in mountain catchments, however, is the most difficult problem with regards to closing the water balance. The work presented in this dissertation details the modeling portion of the NASA Airborne Snow Observatory (ASO) using the iSnobal physically based snow model. This combination of remote sensing and modeling at …
Correlating The Spatial Distribution Of Snow Depth To Forest Canopy Parameters Derived From Terrestrial Laser Scans, Zachary Uhlmann
Correlating The Spatial Distribution Of Snow Depth To Forest Canopy Parameters Derived From Terrestrial Laser Scans, Zachary Uhlmann
Boise State University Theses and Dissertations
In nonpolar, cold climate zones, snow accounts for 17% of the total terrestrial water storage. Estimating the amount of water stored in a snowpack, the snow water equivalent (SWE), and its spatial distribution is crucial to providing water managers with parameters to predict runoff timing, duration and amount. Reservoir management, hydropower and flood forecasting depend on SWE estimates. While landscape features such as aspect and slope are dominant controls on radiative energy in non-forested areas, forest cover can shift the energy balance composition from turbulent exchange in exposed, windy sites to primarily radiative inputs in the subcanopy. Additionally, forest cover …
Trace Chemical Evaluation Of Cloud Seeding In The Payette Basin, James Mitchell Fisher
Trace Chemical Evaluation Of Cloud Seeding In The Payette Basin, James Mitchell Fisher
Boise State University Theses and Dissertations
Glaciogenic cloud seeding increases the fraction of super cooled liquid water precipitating from a given storm. Orographic clouds tend to be inefficient at higher cloud temperatures due to the lack of active natural ice nuclei. Adding artificial ice nuclei active at temperatures greater than -12oC (where most natural ice nuclei are inactive) may result in an increase in snow precipitation, especially in orographic clouds. Silver iodide (AgI) is typically the artificial nucleating agent for winter orographic cloud seeding. Recent estimates suggest the addition of AgI to orographic storm clouds enhance precipitation by 3 - 15%. However, the National …
Assessing Local Snow Variability Using A Network Of Ultrasonic Snow Depth Sensors, Erik Thorsten Boe
Assessing Local Snow Variability Using A Network Of Ultrasonic Snow Depth Sensors, Erik Thorsten Boe
Boise State University Theses and Dissertations
During the 2009-2010 winter season, 21 inexpensive ultrasonic snow depth (USD) sensors were constructed and installed, in addition to two standard Judd USD sensors, at Treeline and Lower Deer Point sites located within the snow dominated Dry Creek Experimental Watershed, near Boise, Idaho. Six USD sensors, including a single Judd Communications USD sensor, were installed at the Treeline site along a northeast to southwest transect of the small 0.02 km2 catchment. Seventeen USD sensors, including a single Judd Communications USD sensor, were installed at Lower Deer Point in a randomized stratified pattern with respect to aspect and vegetation to …
Spatial Distribution And Evolution Of A Seasonal Snowpack In Complex Terrain: An Evaluation Of The Snodas Modeling Product, Brian Trail Anderson
Spatial Distribution And Evolution Of A Seasonal Snowpack In Complex Terrain: An Evaluation Of The Snodas Modeling Product, Brian Trail Anderson
Boise State University Theses and Dissertations
Hydrologists and water managers have been attempting to accurately estimate watershed scale snow water equivalent (SWE) for over a century. Extensive monitoring networks, remote sensing technology, and sophisticated modeling approaches have greatly improved these estimates; however, water inputs from snow in mountainous areas are still subject to considerable uncertainty due to SWE spatial variability. In an attempt to improve the understanding of physical processes and controls influencing SWE spatial variability, a field campaign to measure the spatial and temporal distribution of SWE within the Dry Creek Experimental Watershed (DCEW) was conducted during 2009 and 2010. These measurements are compared to …