Cooperative Ecosystem Studies Unit, Colorado Plateau CESU | G19AS00119

Frequently Asked Questions (FAQs)

What is the main purpose of this USGS funding opportunity?

The opportunity supports a focused research effort to measure and better understand mountain snow albedo (the snowpack's reflectance) and how it influences how much solar energy is absorbed versus reflected. The goal is to improve understanding of snowmelt timing, runoff, and broader water resource conditions by producing better, higher-resolution albedo measurements.

What is snow albedo, and why does it matter?

Snow albedo describes the relative reflectance of snow. It matters because it directly affects the surface energy balance: higher albedo reflects more solar energy and can slow melt, while lower albedo absorbs more energy and can accelerate melt. Albedo can change quickly as snow accumulates, ages, becomes dirty, or melts.

What problem is this project trying to solve?

The core problem is that snow albedo varies substantially over time and space, but common measurement approaches operate at mismatched scales. Ground sensors measure very locally at fixed points, while satellite products measure broadly at coarse resolutions. This mismatch creates scaling issues when calibrating and validating satellite-based albedo observations using ground-based measurements.

Why are Unmanned Aerial Systems (UAS/drones) central to this project?

UAS are used to fill the gap between point-based in situ sensors and coarse-resolution satellite imagery. By mounting albedo sensors on a drone, the project can collect high-resolution, spatially continuous measurements that can be repeated over time and across multiple sites and conditions.

What satellite products are referenced in the opportunity?

The opportunity references satellite albedo products from NASA's MODIS and Landsat. These products provide widely used, large-area coverage but can struggle with fine-scale variability caused by terrain, vegetation, post-fire changes, and patchy snow.

How will UAS-based albedo measurements be used with MODIS and Landsat products?

A key part of the work is comparing UAS-derived albedo measurements against established satellite albedo products (MODIS and Landsat). The comparison is intended to identify where they align, where they diverge, and what that implies for improving satellite calibration and validation.

What kinds of landscapes or conditions does the project focus on?

The work explicitly targets both undisturbed areas and post-fire montane landscapes. Post-fire conditions are important because fire can alter surface characteristics and introduce soot and debris that darken snow, reduce reflectance, and accelerate melt.

What are the main deliverables or required outputs of the funded effort?

The opportunity describes three main deliverables: (1) deploy a UAS and refine workflows to quantify scale-dependent controls on snow albedo, including data collection, processing, and analysis; (2) evaluate how UAS-based methods could be transitioned into operational protocols that improve water resource monitoring and forecasting; and (3) archive the resulting albedo measurements on USGS ScienceBase.

What does it mean to "refine workflows" for quantifying snow albedo?

It means developing a repeatable approach for planning flights, collecting UAS-based albedo measurements, processing the data, and analyzing how albedo changes with factors like snow condition, topography, and disturbance. The intent is a practical method that can be applied across sites and over time.

What does "scale-dependent controls on snow albedo" refer to?

It refers to understanding how drivers of albedo variability change depending on the spatial scale being measured. The project addresses how albedo patterns observed at very fine scales (UAS) relate to and inform coarser scales (satellite products), helping reduce scaling problems between ground observations and satellite retrievals.

How does this research connect to water resource monitoring and forecasting?

Better, higher-resolution albedo information improves understanding of energy inputs to snowpacks and can help anticipate melt dynamics. This is relevant to streamflow timing, reservoir operations, drought planning, and hazard awareness, because melt timing and runoff are closely tied to energy absorption and reflectance on the snow surface.

What is meant by transitioning UAS methods into "operational protocols"?

This objective focuses on moving from a research demonstration toward something that could be routinely adopted by agencies or monitoring programs. It includes identifying procedures, repeatability requirements, and data standards needed for routine use to improve water resource monitoring and forecasting.

Where must the resulting albedo data be archived?

The opportunity requires that albedo measurements produced under the award be archived on USGS ScienceBase, supporting transparency, reproducibility, and long-term data stewardship.

Why is ScienceBase data archiving part of the requirements?

ScienceBase helps make datasets discoverable and accessible, which increases the value of the work beyond the immediate study locations. This enables other researchers, resource managers, and modelers to reuse the measurements for additional analyses or for future satellite product development.

Which USGS office and program network are associated with this opportunity?

The opportunity is offered by the U.S. Geological Survey (USGS) Northern Rocky Mountain Science Center (NOROCK) under the Cooperative Ecosystem Studies Unit (CESU) Colorado Plateau network.

What type of award mechanism is used?

This is described as a discretionary funding opportunity issued as a cooperative agreement.

What is the Funding Opportunity Number and CFDA number?

The Funding Opportunity Number is G19AS00119, and the CFDA number is 15.808.

How many awards were anticipated, and what was the funding ceiling?

The opportunity anticipated a single award, with an award ceiling of $50,000.

When was the opportunity originally posted, and what was the original closing date?

The original posting date was July 10, 2019, and the original closing date was July 26, 2019.

Who is eligible to apply based on the information provided?

Eligibility is listed broadly as "Others," with additional clarification referenced in the opportunity's eligibility details. The description notes that CESU-based competitions often involve academic and research partners aligned with the CESU network.

What public benefits or mission relevance does the opportunity emphasize?

The opportunity emphasizes producing a practical, high-resolution bridge between ground measurements and satellite observations of snow albedo. It is framed as relevant to USGS mission areas tied to land resources, ecosystems, and water resources, with public benefits including improved information for decisions about water supply, ecosystem conditions, and natural hazards, particularly in sensitive mountain and post-fire environments.

What makes albedo particularly challenging to measure accurately?

Albedo can swing quickly as snow accumulates, ages, becomes dirty, or melts, and it varies across landscapes due to terrain, vegetation, disturbance, and patchy snow. Because of this rapid temporal change and strong spatial heterogeneity, measurements taken at a point may not represent a wider area, while satellite measurements may miss fine-scale variability.

What technology change is highlighted as enabling this UAS approach?

The opportunity notes that recent improvements in sensor technology are a key enabler because albedo instruments have become small and light enough to be flown on a single UAS platform while still capturing useful radiometric information.