Improved forecasting of forest snowmelt

Meltwater from snow makes an important contribution to water supply, and melting snow also triggers ecological processes that are key to plant growth. It is therefore important to be able to predict how much meltwater will be available. However, such calculations are much more difficult to make for forests than for open areas. This is because the patterns of snow distribution and snowmelt in the forest are complicated, with forest density, gaps and edges as well as shadows making a big difference to the melt rates. Most snowmelt models cannot represent the spatial differences in the forest structure and their impact on mass and energy flows. This leads to errors in the calculation of snowmelt, but also to uncertainties in the modelling of the future climate, since the reflection and absorption capacity of snow-covered forests is a factor in this.

Now, researchers in the Snow Hydrology Research Group at the WSL Institute for Snow and Avalanche Research (SLF) have succeeded in significantly improving snowmelt forecasts in forested areas. Measurements and computer modelling both have a key role to play:

• Ground, drone and aircraft-based observations: Solar and thermal radiation are important factors for snowmelt in forests. Radiation sensors, cameras and laser scanners allow solar and thermal radiation patterns of the forest, the forest structure and varied snow cover patterns to be accurately measured.