Presentation Title

The Snowpack Toolbox: Water Research in Far-Flung Places

Location

Bobo Room, Hodgin Hall, Third Floor

Start Date

8-11-2017 10:45 AM

End Date

8-11-2017 11:45 AM

Abstract

The Snowpack Toolbox: Water Research in Far-Flung Places Mountain snowpack provides essential water for people and economies around the world with over two billion people relying on snowmelt water for some portion of their daily needs. To understand the mechanisms that connect snow to the streamflow that supports the world’s cities, fields, and industries, we must take a hard look at the tools and data at our disposal. Snow water equivalent (SWE) – or how deep the water would be if the snow were to melt – is the most prevalent variable in analyzing the snowmelt-streamflow connection and provides an accurate measurement of snow water content at a given point. However, measuring SWE faces significant challenges due to limited access, harsh climate, expensive equipment, and difficult maintenance. In addition, many places with a substantial dependence on snowmelt, such as India and Nepal, have few to no weather stations that measure SWE. A lack of data will not change our dependence on snowmelt, so what are our options? Satellite-based measurements of snow allow researchers to study these remote and treacherous regions to gain new insight into snowpack-streamflow dynamics. Snow cover extent (SCE) is a measurement of the presence of snow within an area as a proportion of the total area and is available daily with near-global coverage from two of NASA’s satellites. So, if an area is 95% covered in snow, how does that correlate to SWE measurements in the area? How does the snowpack in that area compare to one with only 30% coverage? Can SCE be used to recreate expected natural patterns such as shorter snow seasons in hotter climates? How can we harness SCE to learn more about snowmelt-streamflow dynamics in areas without traditional snow data? SCE and SWE are both unique representations of the state of mountain snow, each with their own benefits and limitations; But perhaps SCE can provide us with another tool for our toolbox as we continue to learn about the planet we live on.

This document is currently not available here.

Share

COinS
 
Nov 8th, 10:45 AM Nov 8th, 11:45 AM

The Snowpack Toolbox: Water Research in Far-Flung Places

Bobo Room, Hodgin Hall, Third Floor

The Snowpack Toolbox: Water Research in Far-Flung Places Mountain snowpack provides essential water for people and economies around the world with over two billion people relying on snowmelt water for some portion of their daily needs. To understand the mechanisms that connect snow to the streamflow that supports the world’s cities, fields, and industries, we must take a hard look at the tools and data at our disposal. Snow water equivalent (SWE) – or how deep the water would be if the snow were to melt – is the most prevalent variable in analyzing the snowmelt-streamflow connection and provides an accurate measurement of snow water content at a given point. However, measuring SWE faces significant challenges due to limited access, harsh climate, expensive equipment, and difficult maintenance. In addition, many places with a substantial dependence on snowmelt, such as India and Nepal, have few to no weather stations that measure SWE. A lack of data will not change our dependence on snowmelt, so what are our options? Satellite-based measurements of snow allow researchers to study these remote and treacherous regions to gain new insight into snowpack-streamflow dynamics. Snow cover extent (SCE) is a measurement of the presence of snow within an area as a proportion of the total area and is available daily with near-global coverage from two of NASA’s satellites. So, if an area is 95% covered in snow, how does that correlate to SWE measurements in the area? How does the snowpack in that area compare to one with only 30% coverage? Can SCE be used to recreate expected natural patterns such as shorter snow seasons in hotter climates? How can we harness SCE to learn more about snowmelt-streamflow dynamics in areas without traditional snow data? SCE and SWE are both unique representations of the state of mountain snow, each with their own benefits and limitations; But perhaps SCE can provide us with another tool for our toolbox as we continue to learn about the planet we live on.