crown area, not dominated by their neighbors, and with the smoothest bark,
collect the largest volume of stemflow case study of laurel forest.
However, stemflow contributes a relatively small portion to the net rainfall
Table 2. Asdak et al 1998a found stemflow 0.3 of gross rainfall in the
logged forest of Central Kalimantan. In this case, throughfall was controlling the net
rainfall. The sum of throughfall and stemflow
measured identified as the net rainfall, the actual rainfall that reach the ground surface,
and mentioned as the proportion to the gross rainfall. Obviously, canopy characteristics
leaf shape, size, surface character, and the nature of branching did have great
influence on the net rainfall, besides the rainfall distribution itself.
Table 1. Comparative result from other interception studies of gross rainfall
Study Site Location
T
f
S
f
I Source
Unlogged forest Indonesia
87.2 1.4
11.4 Asdak et al. 1998a
Logged forest Indonesia
93.5 0.3
6.2 Asdak et al. 1998a
Agroforestry system with no intercropped
Kenya 88.4 0.7
10.9 Jackson
2000 Hardwood stand
Canada 76.4
4.3 19.3
Carlyle-Moses et al. 1999 Natural forest
Indonesia 72.3
1.7 26.1
Anwar 2003 Lowland tropical
rainforest Puerto Rico
- -
50 Schellekens et al. 1999
Tropical upland mixed cropping system
Indonesia 24 188
Van Dijk and Bruijnzel 2001
Laurel forest Canary
Islands -
6.85 -
Aboal et al. 1999 Tropical montane
cloud forest Columbia - -
42 Jarvis 2000
2.3. Influence of canopy characteristics on Interception
Interception calculated as the difference between gross and net rainfall, it was
influenced by both climatic and canopy factors. Rainfall depth, intensity and
distribution both temporally and spatially were dominant climatic factors in
interception. High portion of interception would be resulted from low small rainfall.
This can be understood as in small rainfall, most of the water was used for saturating the
canopy, causing only small portion or even none of the rainfall could reach the ground
surface as net rainfall.
Hall 2003 mentioned that interception loss was relatively insensitive to the
raindrops size which means that for different storm intensity, interception loss would not
much differ from one to another. This might fit for the multi layer forest stands where
large portion of throughfall contributed by canopy drip from upper layer canopy. This
can be understood because kinetic energy from high storm intensity would force water
on the top canopy surface to splash out and dripped to the lower canopy layer. The same
thing happens when low storm intensity occurred for a long rain period or as an
intermittent event because it would allows for longer evaporation process from the
canopy surface.
Gross rainfall in an interception study usually was a single value whether obtained
from a single rain gauge measurement or as average from several distributed rain
gauges for the whole study area to make canopy variability as the only cause for
different net rainfall measured.
Other studies show that interception loss was variable 6 – 50 of gross rainfall at
different forests Table 1. But this interception loss variability was mentioned
caused by the canopy variability, no sufficient instruments was used to explore
the temporal variability and its contribution to the interception loss.
3
Table 2. Canopy capacity and canopy porosity from others interception study Study Site
Location Canopy Capacity,
S mm Canopy
Porosity, p Source
Unlogged forest Indonesia
1.3 0.1
Asdak et al. 1998b Logged forest
Indonesia 1
0.3 Asdak et al. 1998b
Hardwood stand Canada
1 – 1.1 0.61 – 0.85
Carlyle-Moses et al. 1999
Natural forest Indonesia
1.3 0.7
Anwar 2003 Lowland coastal
rainforest Australia 3.5
0.035 Wallace et al. 2006
Lowland tropical rainforest
Puerto Rico 1.15
- Schellekens et al.
1999 Lower montane
forest Ecuador
1.91 – 2.46 0.42 – 0.63
Fleischbein et al. 2005
III. METHODS
