Modelling snow interception in a spruce forest in varying climate

Spatial and seasonal distribution of runoff in mountain catchments is largely influenced by snow. Therefore, snow storage is an important component of every hydrological model simulating runoff from mountainous catchments. Besides snow cover on the ground, snow storage includes also snow interception, a certain amount of snow captured by vegetation on its canopies. Generally, snow interception is an important part of the hydrological balance in forested catchments. This study builds on results of a snow interception model applied for six consecutive winter seasons 2016-2022 in the Vydra catchment, an experimental research catchment of the Charles University located in the Bohemian Forest, Czechia. The model was validated against measured snow depth and snow water equivalent data in the forest (dominant species Picea abies) and in adjacent open area. Field research has been carried out at the research site to describe the canopy structure of the spruce forest using hemispherical images. The vegetation characteristics were essential for modelling of the snow interception. The mean Leaf Area Index (LAI) calculated from the hemispherical images at the study plot reached 2.34 with the respective canopy closure equal to 86.16%. The LAI values ranged from 2.03 to 2.72 representing the range of canopy closure from 83.6 to 90.2%. These values were further used for calculation of seasonal cumulative snow interception at the study plot for the selected period. The snow interception reached from 68.2 to 105.3 mm in individual years which represent from 31 to 49% of the total seasonal snowfall. The snow interception efficiency differed in every winter season, reflecting the varying weather conditions during seasons and different extremity of snowfall events. Overall, the results of snow interception model is promising and will be further use to improve runoff simulation in experimental catchment.