324 N.A. Jackson Agricultural and Forest Meteorology 100 2000 323–336
trolled by regular manipulation of the tree canopy, achieved through pruning. This paper compares the
measurement and modelling of rainfall interception by G. robusta A. Cunn. ex R. Br. trees in a tropical
agroforestry system in Kenya. The previously refor- mulated version of the Gash analytical model Gash,
1979; Gash et al., 1995 was used to model the inter- ception loss from the discontinuous Grevillea canopy.
Interception estimates from tropical forests are of- ten more uncertain than those obtained in temperate
climates due to the complexity of the tree canopy struc- ture Jackson, 1971; Bruijnzeel and Wiersum, 1987;
Lloyd and Marques, 1988; Asdak et al., 1998a. Rain- fall interception loss in an agroforestry system will
depend on the extent of the tree canopy cover, and this in turn depends on factors such as the tree planting
density at establishment, and subsequent thinning and pruning practices.
Most of the literature comprises studies from closed forest canopies, although some cases exist where in-
terception by discontinuous tree canopies has been studied Rao, 1987; Teklehaimanot and Jarvis, 1991;
Valente et al., 1997; Asdak et al., 1998a. In terms of tropical forestry and agroforestry systems, Veracion
and Lopez 1976 examined interception below Pinus kesiya stands, and interception under multi-storey
systems incorporating coffee and cocoa and shade tree species has been explored by Imbach et al.
1989. Tropical agroforestry systems often comprise fast-growing tree species grown in rotations as short
as 6 or 7 years. Both measurements and models of interception loss are needed to predict the effects of
the tree component on the overall water balance of the system at all stages from establishment to the harvest
of the trees.
2. Materials and methods
2.1. Site and climate The rainfall interception measurements presented,
were made at the ICRAF field station at Machakos, Kenya, 80 km south-east of Nairobi 1
◦
33
′
S, 37
◦
8
′
E at an altitude of 1560 m. The site runs downhill to
the Maruba river at a slope of ∼22. The soil con- sists of a series of shallow 0.2–2 m reddish-brown
to brown sandy clay loams well-drained luvisols — FAO soil classification. The surface 0.4 m was com-
paratively homogenous, while soil layers below this varied widely in gravel and clay content, with a num-
ber of distinct horizons Kibe et al., 1981; Huxley et al., 1989. The soil is underlain by layers of first
weathered and then coherent rock gneiss at varying depths. A band of very shallow soils 0.2–0.6 m deep
ran across the site from the top north-west corner to- wards the bottom south-east corner. Soils were gen-
erally deeper 0.7–1.5 m above and below this band Wallace et al., 1995.
Annual rainfall is bi-modal, with a short rainy sea- son usually lasting from late October to late December,
and a longer rainy season running from late February to the end of May. Monthly rainfall peaks in April and
November, and little rainfall occurs between June and October see Table 1 . Rainfall during much of the
two crop growth seasons is largely orographic in origin as moisture-laden air travels from the coast westwards
towards the Kenyan highlands. Machakos district has a very large inter-annual variation in monthly and
seasonal rainfall Huxley et al., 1989.
2.2. Experimental design This rainfall interception study formed part of a
larger agroforestry trial which was established in October 1991. This trial combined rows of maize with
G. robusta, a rainforest tree species Proteaceae from the north of Australia, introduced to East Africa as an
ornamental in the last century. A detailed description of the experimental design is given by Jackson et al.
1999.
The planting arrangements of the plots in which rainfall interception was measured, consisted of a
sole tree T
d
treatment, where G. robusta trees were planted in a 3 m × 4 m grid pattern, and an inter-
cropped CT
d
treatment with trees planted in the same grid pattern, but with maize planted in rows 1 m
apart 0.3 m between plants along row, following the contours of the slope. Maize was grown twice a year,
and was planted at the start of each rainy season, after at least 20 mm of rainfall had occurred.
2.3. Instrumentation Gross rainfall was measured using a tipping-bucket
raingauge 0.5 mm bucket, Rimco, Vic., Australia positioned uphill from the plots, approximately 20 m
N.A. Jackson Agricultural and Forest Meteorology 100 2000 323–336 325
Table 1 Monthly and annual rainfall mm at Machakos: historical means and recorded values at the project site between tree planting October
1991 and the end of the project June 1997 Average
a
1991 1992
1993 1994
1995 1996
1997 January
50 23
28 283
1 38
20 3
February 50
13 4
110 90
77 80
March 105
48 5
41 87
152 91
58 April
183 77
164 35
92 103
69 229
May 56
89 68
14 15
32 57
66 June
11 4
17 21
17 4
July 4
11 7
1 5
6 2
na August
4 11
1 3
5 13
7 na
September 5
5 1
1 3
6 1
na October
43 47
40 10
61 48
na November
175 175
126 162
317 82
156 na
December 96
150 214
118 144
95 10
na Annual total
782 653
675 799
820 652
510 na
a
Data for 9-year period 1963–1971 from Machakos Maruba Dam station.
from the nearest trees, and four manually recorded raingauges 125 mm diameter at distances of between
20 and 100 m from the nearest trees. An automatic weather station Didcot Instruments,
Abingdon, UK was sited on a tower above the trees in the centre of the site, with the tree canopy extending
between 40 and 80 m in all directions. The mast was raised at least once each season to ensure that the mea-
surements were always made ∼2 m above the mean tree height. The variables measured at this position
were: dry- and wet-bulb air temperatures recorded us- ing an aspirated psychrometer; incident solar radia-
tion Model CM5, Kipp and Zonen, Netherlands; and wind speed and direction Campbell Scientific, Leics.,
UK, used to determine prevailing wind directions dur- ing rainfall events. Wind speed was also measured at
various heights below and within the tree canopy. All automatic instruments were measured every 10 s, and
hourly totals for rainfall and wind speed or averages wind direction were stored on a data logger Model
21, Campbell Scientific Instruments, UK.
Jackson 1971 demonstrated that estimates of trop- ical forest interception varied greatly as a result of high
spatial heterogeneity in canopy architecture. Although the agroforestry system was less spatially complex
than most tropical forests, the grid pattern of tree plant- ing meant that the canopy was markedly ‘clumped’.
It was expected that such a canopy distribution might lead to significant differences in throughfall over rela-
tively small horizontal distances. Eschner 1967 noted that considerable micro-scale variability in through-
fall existed between points below tree canopies, with stemflow sometimes accounting for significantly en-
hanced and localised rainfall inputs to the soil surface. Given this anticipated variation in throughfall,
it would have been preferable to use large-scale sheet-type interception gauges of the sort described
by Calder and Rosier 1976 and Rao 1987. How- ever, the presence of the understorey maize crop made
it impossible to adopt this technique. In addition, as part of the larger experiment it was necessary to
obtain measurements of net rainfall input to the soil at specific positions relative to the trees, to match
other measurements being made, such as soil water content Jackson et al., 1999 and soil evaporation
Jackson and Wallace, 1999a. Therefore, throughfall was measured in both the T
d
and CT
d
treatments us- ing manually recorded raingauges, measuring 125 mm
diameter. Initially in October 1994, sets of raingauges were
installed in the following arrangements. Six gauges were placed in one of the CT
d
plots, at various dis- tances 0.3–2.5 m from the base of the tree see
Fig. 1, covering one quarter of the 12 m
2
area occu- pied by each tree, and in such a way that each lay mid-
way between two rows of maize. Six more gauges were installed in one of T
d
plots, in the same spatial ar- rangement. The raingauges were inspected after each
rainfall event and the volumes recorded. Lloyd and Marques 1988 demonstrated how the effect of spatial
variation in throughfall beneath a rainforest canopy could be reduced by randomly relocating interception
326 N.A. Jackson Agricultural and Forest Meteorology 100 2000 323–336
Fig. 1. Location of the raingauges used to measure throughfall over a 12 m
2
area below the G. robusta tree canopy CT
d
intercropped treatment shown here. Six gauges were deployed in November 1994, and the network was augmented with a further twelve gauges
in early 1995. An identical spatial arrangement was employed in the sole tree T
d
treatment.
gauges on a regular basis. To compensate for varia- tion in interception by tree canopies of different sizes
and shapes in this study, the raingauges in both the T
d
and CT
d
were moved to identical positions around different, randomly chosen trees, after approximately
five rainfall events 5 mm had been recorded. Areal average interception over the 12 m
2
per tree was de- termined by weighting the volumes recorded in indi-
vidual gauges by the fractional area they represented. An analysis of the wind direction during 885 h
of rainfall showed that the bulk of the rain 73 of vol., 81 of rainfall h came from directions between
north-east and south-east. As there was measurable interception at 2.5 m midway between the trees, some
rainfall must have been inclined away from vertical fall paths and was therefore being intercepted by
the adjacent tree canopies, as reported in previous interception studies Eschner, 1967; Aldridge, 1975;
Herwitz and Slye, 1995. Therefore, the number of gauges was increased early in 1995 to 18 per tree, so
that the entire 12 m
2
area occupied by each tree was measured see Fig. 1.
To measure stemflow, S
f
, 18 gauges were installed on trees in the T
d
plot and a further 18 gauges in the CT
d
plot, consisting of a flexible plastic collar which was sealed to the trunk of the tree with a non-toxic sil-
icone compound about 0.75 m above the ground. The collars drained to plastic jerry-cans of 35 l capacity.
Stemflow gauges were moved from tree to tree on a regular basis, in order to sample trees with varying
trunk diameters and canopy sizes.
2.4. Tree canopy cover There were no discernible seasonal fluctuations in
leaf area index L during the experiment, nor did the
N.A. Jackson Agricultural and Forest Meteorology 100 2000 323–336 327
rate of leaf fall seem to be seasonally dependent. The trees were pruned at various stages during the exper-
iment, usually prior to planting the crop, by remov- ing the lowermost 1 m of canopy. In November 1996
the trees were severely pruned, removing all but the uppermost 1 m of canopy. This reduced the canopy
volume by approximately 85, and was designed to minimise the competition for soil water between trees
and crops as part of an associated experiment on root competition Smith et al., 1999.
Leaf area index L
∗
values for G. robusta was estimated using a calibrated pipe model Lott et
al., 1997, for the entire period from establishment October 1991 to the end of the study June 1997.
Estimates of projected crown area A
p
were made at various intervals throughout the experiment, using
canopy radius measurements and assuming a circular canopy distribution. An empirical relationship be-
tween projected canopy area m
2
and leaf area index was determined, and is shown in Fig. 2:
A
p
= − 0.594L
∗ 2
+ 3.669L
∗
; r
2
= 0.932; n = 74
1 The curved nature of the relationship reflects the fact
that the adopted pruning regime encouraged the trees
Fig. 2. Empirical relationship determined between the leaf area index L
∗
and the projected area A
p
, in m
2
of G. robusta crowns at the Machakos site. The relationship has the form:
A
p
= − 0.594L
∗ 2
+ 3.669L
∗
.
to grow vertically more rapidly than laterally, and therefore, towards the end of the experiment, tree
leaf area index increased faster than did the projected canopy area. The relationship was used to calculate
monthly values of A
p
, which were in turn converted to fractional canopy cover values, c, where a dense
closed canopy = 1 using a planting density of one tree per 12 m
2
. 2.5. Model description
Gash et al. 1995 revised the original Gash, 1979 analytical rainfall interception model to improve esti-
mation of interception from sparse tree canopies. The model, which is a simplification of the Rutter model
Rutter et al., 1971, 1975, assumes that daily rainfall occurs as one single storm event each day, an assump-
tion that Lloyd et al. 1988 considered valid given the prevailing rainfall conditions in much of the tropics,
i.e. short but intense convective storms. Each of these rainfall events is considered to comprise three distinct
phases: firstly, a period from the onset of rainfall un- til the canopy becomes saturated wetting-up phase;
secondly, a saturation phase; and lastly a period of drying out, from the point at which rainfall stops until
the canopy and trunks are absolutely dry. It is assumed that both the canopy and trunks dry out completely
between rainfall events.
To calculate the various components of the inter- ception loss, the revised model requires several initial
parameters see Table 2. A value for canopy cover, c, is required, defined as the projected area of the tree
canopy on the ground below. Canopy storage, S
c
, is as- sumed to remain constant, however, the canopy cover,
c, varies. Also required are daily rainfall, P
g
, the trunk storage capacity, S
t
, the rainfall fraction redirected to stemflow, p
t
, and the ratio between the mean rainfall rate, R, and the mean evaporation rate during rainfall
per unit area of canopy cover,E
c
. 2.6. Model parameterisation
For purposes of data analysis, rainfall was sepa- rated into discrete storm events where these were de-
fined as periods of rainfall with at least eight clear hours with no rainfall occurring both before and
after the event Lloyd and Marques, 1988. The typi- cal storm duration was 4–5 h, 87 of which occurred
overnight.
328 N.A. Jackson Agricultural and Forest Meteorology 100 2000 323–336
Table 2 The parameters and analytical forms for components of rainfall interception loss from sparse tree canopies after Gash et al., 1995
Parameters Daily rainfall, P
g
mm Canopy storage capacity, S
c
mm Rainfall necessary to fill canopy storage, P
′ g
mm Trunk storage capacity, S
t
mm Rainfall fraction redirected to stemflow, p
t
Fractional canopy cover, c Mean rainfall rate onto saturated canopy, ¯
R mm h
− 1
Mean evaporation rate from saturated canopy, ¯ E
c
mm h
− 1
Component of the interception loss Analytical formulation
From the tree canopy: For a number of storms, m, too small to saturate the canopy P
g
P
′ g
c P
m j =1
P
g,j
Wetting up the canopy, for n storms which saturate the canopy P
g
≥ P
′ g
ncP
′ g
− ncS
c
Evaporation from the saturated canopy during rainfall c ¯
E
c
¯ R
P
n j =1
P
g,j
− P
′ g
Evaporation from the canopy after rainfall stops ncS
c
From the trunks: For a number of storms, q, that saturate the trunks P
g
≥ S
t
p
t
qS
t
For a number of storms, n − q, which do not P
g
S
t
p
t
p
t
P
n−q j =1
P
g,j
From 885 h of rainfall recorded between 1991 and 1993 i.e. before interception measurements com-
menced, the mean rainfall rate was determined to be 2.28 ± 0.92 mm h
− 1
. However, individual storms of more than 90 mm were recorded, as well as very oc-
casional rainfall intensities of more than 15 mm h
− 1
. For this reason, monthly rainfall rates ¯
R
m
were also calculated, which varied between 0.5 and 3.2 mm h
− 1
. Both the long term and monthly values were used in
modelling. Bruijnzeel and Wiersum 1987 found that the mean daily rainfall rate in a sparse Acacia planta-
tion varied significantly at different times throughout the rainy season.
The mean
evaporation rate
during rainfall,
¯ E
c
, was calculated as 0.23 mm h
− 1
, using the Penman–Monteith formula, estimating values of net
radiation R
n
above the tree canopy from measured solar radiation see Rao, 1987; Lloyd et al., 1988.
The aerodynamic conductance, g
a
, was calculated according to Valente et al. 1997, as g
a
= fu, where u
is the windspeed and f is a constant. It was assumed that the aerodynamic conductances for momentum,
water vapour and sensible heat remained the same, and therefore f was calculated as:
f = k
ln[z − dz ]
2
2 where k is the von Kármán constant 0.41, z is the ref-
erence level, d is the zero-plane displacement height, and z
is the roughness length, determined to be 0.75 and 0.1, respectively, of the mean tree height Rutter
et al., 1975; Valente et al., 1997, which increased from 0.5 to 9.5 m over the course of the experiment.
Although the effect on g
a
of increasing tree height was taken into account by varying the value of the two
roughness parameters, it is possible that the nature of the relationship between d and z
and tree height may have varied over time, as pruning changed the shape
and distribution of the canopy. There is some uncer- tainty about determining d and z
in widely spaced canopies Jarvis et al., 1976. Pruning would widen
the gaps between individual tree canopies, often lead- ing to more effective turbulent exchange within the
canopy layer and greater conductances per tree.
Teklehaimanot et al. 1991 studied the effect of tree planting density on boundary layer conductance
and found that g
a
increased linearly as the spacing between trees grew larger. It is unlikely that removing
the lowermost branches would have had a large effect on the value of g
a
, as windspeeds below and within the tree canopy did not increase significantly. However,
when radical pruning took place towards the end of the experiment, removing 85 of the canopy, wind
speeds greatly increased and it is logical to assume
N.A. Jackson Agricultural and Forest Meteorology 100 2000 323–336 329
that the value of g
a
did also. However, as canopy cover was less than 2 at this stage, any error in the value
of g
a
would account for a negligible percentage of the overall interception.
As the canopy storage capacity S
c
was known to be affected by canopy architecture Asdak et al., 1998b
it was expected to vary, depending on the height and shape of the trees as they grew, and on the degree
of canopy cover resulting from the pruning regime adopted. Canopy storage capacity was determined us-
ing the envelope method of Leyton et al. 1967, from the negative intercepts of linear regressions between
throughfall and gross rainfall with a pre-defined slope set to 1 − p
t
. There is an inevitable degree of subjectivism in-
volved in the envelope approach Rowe, 1983, who noted that seasonal variations, rainfall intensities and
wind speeds had a marked effect on determining S
c
using the Leyton et al. 1967 method. Data from 172 rainfall events recorded at various stages dur-
ing the experiment were used to derive S
c
values of between 0.71 and 0.93 mm. In general, as the tree
canopies expanded, S
c
increased. Pruning reduced S
c
, but to varying degrees, as might be expected from removing either the lowermost branches or
foliage higher up the tree. Variation in S
c
also re- flected monthly and seasonal variations in the rainfall
intensity.
Fig. 3. Changes in the fractional cover, c, from the G. robusta canopies in the sole tree thick line and intercropped thin line treatments, estimated from the formula from Fig. 2. Arrows denote times at which the canopies were pruned. Bars show weekly rainfall during the
long February–July and short October–January rainy seasons.
Trunk storage capacities for smooth barked Aus- tralian rainforest tree species like Grevillea were found
to be much lower than rough barked equivalents Her- witz, 1985, suggesting that stemflow from the Grevil-
lea in our experiment might be significant. Due to the observed variability in stemflow from trees of different
sizes, S
t
and p
t
were derived following the procedure of Lloyd et al. 1988. Separate linear regressions of
stemflow against gross rainfall were determined for 42 trees. The averages of the intercepts 0.185 ±0.03 mm
and of the slopes 0.026 ± 0.007 were taken as esti- mates of S
t
and p
t
, respectively. Monthly values of the canopy cover, c, were calculated using values of A
p
, as shown in Fig. 3.
3. Results and discussion
