A geometric solar radiation model with applications in agriculture and forestry

Abstract

Incoming solar radiation (insolation) is fundamental to most physical and biophysical processes because of its role in energy and water balance. We calculated insolation maps from digital elevation models, using an insolation model that accounts for atmospheric conditions, elevation, surface orientation, and influences of surrounding topography. Herein, we focus on the application of this insolation model for spatial interpolation of soil temperature measurements over complex topography at landscape scales. Existing interpolation techniques generally apply only at continental or broad regional scales and do not capture the high variation of finer scales. In our field study in the vicinity of the Rocky Mountain Biological Laboratory, average soil temperature was correlated with insolation and elevation. Whereas daily minimum temperature was negatively correlated with elevation ( r=−0.730, P<0.05), daily temperature change (maximum minus minimum) was positively correlated with daily insolation ( r=0.504, P<0.01). We generated daily minimum and maximum soil temperature maps based on regression analyses. Residual variation was explained by factors such as vegetation cover. This application demonstrates the importance of characterizing spatial and temporal variation of insolation for studies of energy and water balance.