Modelling solar radiation in forest canopy for the purposes of forest growth modelling

Tharandt

2010

S. 27-35

Artikel aus einer Zeitschrift

200170957

The presented model of solar radiation will enable us to refine the growth simulations of the tree semi-empirical model. The resulting simulations will down-scale the output at the level of tree organs and at a time period of 1 month, 1 day, or 1 hour. At the same time, they will also provide a user with the information about the ongoing processes, such as photosynthesis, transpiration, allocation, etc. The advantage of the model is that apart from the specification of the geographical position it does not require any other additional information to perform the simulation, since all other inputs represent standard components of growth simulations. Within the scope of our future research, it is required that the model is to be evaluated on the data describing the solar radiation in a forest canopy. Another so far unsolved question is the representativeness of the simulation plot of size 50 x 50 m, which, particularly in old loose stands, can cause that the model of the hemisphere does not account for the trees outside the plot that cause a decrease of solar radiation intensity, too. In this case, the appropriate solution seems to be to implement the correction model for the edge effect. A similar situation occurs if the assessed tree is situated at or near the boundary of the simulation plot. In such cases, the upper hemisphere is incomplete. The simplest solution would be to draw the boundaries of the simulation plot in the hemisphere, and to calculate the average value of diffuse radiation only from those sectors of the hemisphere that occur inside the simulation plot. If the sun's position lies in the sectors outside the simulation plot, we suggest reflecting its position into the quadrant of the hemisphere, which is completely filled with the forest simulation plot. The presented model of solar radiation represents a convenient amendment that refines growth simulations, which moves the simulations from the empirical towards the process-based approach.