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A large share of global freshwater run-off originates from forested areas that are covered in snow during winter. When and how fast this snow melts can influence whether floods occur. It is just as important to determine how much snow is in these forests and how much of it reaches bodies of water during thawing. The thickness of the snow cover in non-forested areas next to these forests is a poor indication of this, as the treetops in a forest can retain up to half the snowfall. A significant proportion of the snow is absorbed directly from the trees back into the air as water vapor, and therefore does not contribute to local run-off generation. Previous models, which aimed to simulate the development of snow cover in forested areas, were oversimplified and provided an inadequate interpretation of the variability of snow cover below trees.
Improved model considers forest structure
In his doctoral work at SLF, David Moeser used laser scanning data to detail the distribution and size of gaps in the canopy. At the same time, researchers from the Snow Hydrology research group at SLF took more than 84,000 snow measurements across nine test sites in the area around Davos over three snow seasons. It is the most comprehensive field study of forest snow distribution in the world. The combination of snow measurements and laser scanning data enabled Moeser to develop a snow model that can accurately predict the amount and spatial distribution of snow, even in irregular forest structures. (Martin Heggli, Diagonal 1/16)