Effect of Terrain and Vegetation structure on Snowmelt 2013/06/04 2014/04/04 University of Maryland
The vegetation structure and topography are the primary factors affecting the amount of solar radiation reaching the surface of the earth. Considering the fact that 33 % of the earth surface consists of vegetation it is very important to understand how vegetation affects the variability of solar radiation as it makes it way to the ground surface. This can help us understand how much of variability in surface solar radiation is caused by vegetation structure. This can help us answer several pertinent questions such as: How does the vegetation structure affect the variability of solar radiation on the earth surface? How does this variability scale up on large spatial scales? What is the relative effect of topography and vegetation structure on the surface solar radiation? How is the variability in solar radition relates with variability in vegetation structural parameters such as canopy height, (Leaf Area Index) LAI , fractional canopy cover etc. One of the main challenges in estimating surface solar radiation is the surface heterogeneity and its effect therein on surface solar radiation. The is the first work of its kind which tries to understand the interplay of solar radiation with three dimensional vegetation structure and topography using waveform lidar remote sensing. This work presented here also addresses the effect of vegetation on solar radiation variability at a landscape level.
Relevance to hydrological and snow science
Solar energy drives the hydrological cycle. Solar radiation along with terrain characteristics are the main factors affecting this cycle. In most of the hydrological studies the solar energy estimation over the vegetation areas is either neglected or it is over simplifies by considering vegetation as a turbid medium or using LAI as a proxy for the amount of vegetation. Incorporating the effect of 3-D vegetation structure would help us understand the hydrological cycle and snowmelt better. It will also lead to better estimation of soil moisture, hydrological flow and snowmelt.