A unique computer model to measure the snowpacks' water content has been created which will offer an essential tool for scientists, landslide analysis, as well as resource managers. Researchers at Oregon State University developed this new computer model, and they published their findings in The Cryosphere. These results have a connection with a snow depth project that NASA funded which Hill co-led with the involvement of Ryan Crumley, Oregon State Ph.D., student.
As David Hill, a civil engineering professor at OSU noted, all over the world, a vital element of the cycle of hydrological is snow. And to calculate snow-water equivalent directly can be quite expensive and challenging. Also, it is hard for anyone to do it everywhere. However, it is much undemanding to get snow depth information. And as such, the researchers have made a step forward with their new model that can estimate snow depth with the use of snow-water equivalent compared to the earlier models.
As part of Project Citizen Science for Earth Systems by NASA, researchers named the project Community Snow Observations. Also, for the use of snow-water equivalent in computer modeling, data gathering is going on by backcountry skiers, snowshoers, and snow-machine users.
Gabe Wolken from the University of Alaska and Hill led the research team of Community Snow Observation that started in February 2017 along with Anthony Arendt from the University of Washington. The primary focus of the project was Alaskan snowpacks. Then, the researchers began enlisting citizen scientists in the Pacific Northwest. At present, there are more than 2,000 participants in the project.
Through the process of factoring the time of the year, snow depth, 30-year averages of precipitation in winter, differences in seasons between warm and cold temperatures, measuring snow-water equivalent was quite possible with the team of Community Snow Observation's recent model, and their collaborators developed. Hill said that utilizing those climate normals instead of daily weather data accede to their model to offer SWE estimates for regions a long way from any weather station.
With the use of a database of snow pillow measurements, the team was able to validate the model, a snow pillow measures snow-water equivalents through the pressure they exerted by the snow on top of it, and the combination of the northeastern United States and western North America that form a pair of large independent datasets.
Hill further explained that his team also made a comparison of the version against three different models of altering levels of complexity constructed in various geographic regions. With these outcomes, Hill was certain the model they built fared better than any other model because it is not only effective, but its user-friendly process of estimation makes it quite valuable for extensive areas with inadequate weather instrumentation.
