Cooperative Ecosystem Studies Unit, Colorado Plateau CESU

The summary for the Cooperative Ecosystem Studies Unit, Colorado Plateau CESU grant is detailed below. This summary states who is eligible for the grant, how much grant money will be awarded, current and past deadlines, Catalog of Federal Domestic Assistance (CFDA) numbers, and a sampling of similar government grants. Verify the accuracy of the data FederalGrants.com provides by visiting the webpage noted in the Link to Full Announcement section or by contacting the appropriate person listed as the Grant Announcement Contact. If any section is incomplete, please visit the website for the Geological Survey, which is the U.S. government agency offering this grant.

Cooperative Ecosystem Studies Unit, Colorado Plateau CESU: The US Geological Survey, Northern Rocky Mountain Science Center (NOROCK), is offering a funding opportunity to deploy an Uninhabited Aerial System (UAS) equipped with radiation sensors to quantify scale-dependent controls on snow albedo in areas with no disturbance and in post-fire, montane regions and compare these data to MODIS and Landsat albedo products. Data collection will occur in January through May 2020 and 2021. This project will have field campaigns in three headwater areas. The first, Namaste, is on private land within the Yellowstone Club (YC) in southwest Montana. The second and third study areas are located in Glacier National Park, along the Going-to-the-Sun-Road (GTSR) and Reynolds Creek. The Reynolds Creek site experienced severe wildfire during the summer of 2015. These efforts will address the spatial data gap and scaling issues associated with current in-situ measurements of snow albedo validation data by using UASs to provide high resolution measurements on a larger spatial scale than point measurements at weather monitoring stations. This unique opportunity will allow for the development of tools and techniques to efficiently capture albedo over the snowpack. These data will be used to develop protocols for operational use by managers and decision makers for real time water resource monitoring and forecasting. The methods developed will serve as a guide for resource managers to implement as a workflow in their measurements of mountain snowpack. Anticipated products will be a spatial product dataset of digital surface models and gridded dataset of albedo values for the study sites. Other products include a peer-reviewed article that focuses on the albedo of mountain snowpack as it varies spatially and temporally, and on the scaling issues associated with using the fixed position in situ data to validate remote sensing data.