Soil-Vegetation-Atinosphere
Transfer Schemes and Large-Scale Hydrological
Models (Proceedings of a
s y m p o s i u m held during the Sixth I A H S Scientific Assembly at Maastricht, The Netherlands, July 2 0 0 1 ) .
I A H S Publ. no. 270, 2 0 0 1 .
53
Estimation model for litter moisture content ratio
on forest floor
KOJI T A M A I
Kansai Regional
Momoyama-cho,
Research
Center, Forestry
and Forest
Fushimi-ku,
Kyoto 612-0855,
Japan
Products
Research
Institute,
e-mail: al [email protected]
Abstract A model was developed to estimate litter moisture content for use in
predicting the risk of forest fire in individual forest stands. A formula to
calculate the rate of evaporation from litter was determined experimentally,
using simulated litter moisture content and observed solar radiation. The
model was applied to both a deciduous and a mixed deciduous-evergreen
forest. The incidence of periods when the gravimetric moisture content was
below 20% (Rio) coincided with the incidence of real forest fires in the
surrounding area. Values of R o were higher in deciduous than in mixed
deciduous-evergreen forests because of the different sky view factors. These
results suggest that estimates of litter moisture content can be used to assess
the risk of fire in individual forest stands.
2
K e y w o r d s forest fire; t a n k m o d e l ; s k y v i e w factor; s o l a r r a d i a t i o n ; d e c i d u o u s forest
INTRODUCTION
Historically, the probability of a forest fire occurring has been estimated using time
series weather data (e.g. Pyne et al., 1996). Few studies have estimated the risk of
forest fire in individual forest stands using forest data such as the sky view factor.
Mapped estimates of the risk of forest fire would benefit forest management, and could
guide restrictions on public use of the forest. Forest fires typically originate in forest
litter, before spreading upward to stems and canopies. Thus, the moisture content of
litter is likely to correlate with the risk of forest fire, and to depend on solar radiation
on the forest floor. A model to estimate litter moisture content based on solar data was
developed and applied to adjacent mixed deciduous-evergreen and deciduous forests.
The SVAT scheme consists of many simple processes concerning water movement
in plant communities. The evaporation from a litter layer is one such process which
can be estimated with the model proposed herein.
MODEL
Model structure
2
The litter layer in the model was assumed to have a density of 400 g m" and a
maximum gravimetric moisture content (0) of 200%, based on field observations.
Precipitation onto the forest floor was considered to be stored in the litter layer until
the gravimetric content exceeded 200%, at which point moisture entered the soil layer.
54
Koji Tamai
Evaporation from the litter layer reduced the value of 0. The movement of moisture
between the litter and deeper soil layers during evaporation was neglected. The model
calculates the evaporation (E) using the formula for 0 and the solar radiation on the
forest floor (5).
Formula to estimate the evaporation
To find the relationship between S, 0 and E, evaporation from the litter layer was
measured by placing litter in 20-cm square micro-lysimeters under open sky on
18-19 June 1993. The lysimeters were saturated and then exposed to the sun. An
electric balance sensitive to 0.025 m m of evaporation was used to determine E (mm)
and 0 (kJ m" ). Measurements were typically made every 30 min, but 10-s intervals
were introduced whenever 0 was high. Solar radiation, S (%), was monitored using a
pyranometer (Eko, MS-100).
Linear regressions of E and S were observed for all values of 0 (Fig. 1, Table 1).
Every regression constant was sufficiently small (between - 0 . 0 1 2 and 0.012 m m ) to
2
0
500
1000
1500
Solar radiation (kJ m2)
•
40-60%
O
100-120%
A
140-160%
•
220-240%
Fig. 1 Relationship between evaporation from the forest floor (E) and solar radiation (S).
Table 1 The linear regressions of E and S for values of 0.
Water content ratio, 9
(%)
Regression coefficient
(xlO- )
Regression constant
(xlO' )
Correlation coefficient
20^10
40-60
100-120
120-140
140-160
160-180
180-200
220-240
260-280
280-300
0.204
0.441
0.728
1.155
1.583
1.278
2.001
1.935
1.658
1.738
1.25
0.64
1.15
0.18
0.93
0.87
-1.20
-0.16
1.21
0.01
0.998
0.985
0.950
0.991
0.997
0.999
0.768
0.995
0.939
0.948
4
2
Estimation model for litter moisture content ratio on forest floor
.2 w
55
2.5E-04 -,
f c 2.0E-04 o
o UJ 1.5E-04 ra
o g
1.0E-04 -
jg I
5.0E-05 •
g>E
0.0E+00 -
^
0
100
200
300
Litter gravimetric water content ratio (%)
Fig. 2 Relationship between the litter gravimetric moisture content (0) and the
regression coefficients for E and S.
approximate as 0 mm. When 8 was less than 180%, the regression coefficient between
E and S related to 0 as a linear regression with a slope of 1.02 x 10" and an intercept of
- 1 . 3 x 10" . When 0 was more than 180%, the regression coefficient of E against S was
constant at 1.7 x 10" (Fig. 2). Thus, the formula for evaporation from the litter layer
can be expressed as:
6
5
4
6
5
£ = ( 1 . 0 2 x 10" 6 - 1.3 x 10" )5
when 0 < 180%
(1)
£ = 1 . 7 x IQ' S
when 180% < 0
At each interval the water content was reduced by an amount equivalent to E in the
previous interval.
4
4
APPLICATION TO FORESTS
Description of sites and observations
The model was applied to a mixed deciduous-evergreen forest (35°rN, 135°46'E) and
a deciduous forest ( 3 4 4 V N , 135°51'E). Details of the forest structures are shown in
Table 2.
0
Table 2 The structure of the observed forest to estimate the litter moisture content in the model.
Mixed deciduous-evergreen forest
Deciduous forest
Location
Kyoto City, Kyoto Pref.
Altitude (m)
Dominant species
200
Ilex pendunculosa
Symplocos prunifolia
Clethra barbinervis
Evodiopanax innovons
Yamashiro Town, Kyoto Pref.
230
Quercus serrata
Ilex pendunculosa
2
1
Basal area (m ha" ):
Evergreen species
Deciduous species
15.82
12.46
6.29
13.31
Sky view factor:
Leafy period
Leafless period
13.3
23.0
15.0
50.0
56
Koji Tamai
In the mixed forest, S was measured with a pyranometer (Eko, MS-100), and
precipitation was measured at the nearby Kyoto Regional Meteorological Observatory
(5 1cm west of the study site). In the deciduous forest, S was calculated as a function of
the observed solar radiation (Eko, MS-42) above the forest canopy and a relative solar
radiation ratio, which was estimated to be 15% and 4 0 % in the leafy and leafless
periods, respectively, based on observation. Precipitation in the deciduous forest was
measured by an in situ raingauge (Ikeda, SKI-1).
In both forests, precipitation on the forest floor was estimated to be 90%> of the
value above the canopy, using a standard regression coefficient (0.07-0.12) linking
surface precipitation and canopy interception in Japanese broadleaf forests. The value
of 0 at each 30-min interval was calculated.
The periods September 1994-August 1995 and June 1990-May 1991 were used
for calculations for mixed deciduous-evergreen and deciduous forests, respectively.
The precipitation above the canopy in these periods was 1680 and 1760 mm,
respectively.
R E S U L T S A N D DISCUSSION
In this study, forest fires were considered to occur only when 0 was below 2 0 %
(Kobayashi et al., 1991). The monthly values of the percentage of days when 0 was
less than 2 0 % against total days (R20, Fig. 3) and of the number of forest fires (NFF,
Fig. 4) both showed a peak in spring. The NFF is also high in August and September;
but i?2o values are not high in autumn. Mitchell (1992) simulated the influence of
vernal leafing and autumnal leaf fall on photosynthetically active radiation (PAR)
under a forest canopy. His model suggests that PAR values under the canopy are
50
Ï-4-T
Jan.
Apr.
Jul.
Oct.
—•— Mxed forest —•— Deciduous forest
Fig. 3 Monthly percentage of the days when 6 was below 20% against the total days (i? o)2
^
Jan.
Apr.
Jul.
Oct.
Fig. 4 Average monthly number of forest fires (NFF) in the area (1963.35 km )
around the observed forests in 1984-1993.
2
Estimation model for litter moisture content ratio on forest floor
57
highest just before the appearance of leaves in the spring, and that a small peak
sometimes occurs just after leaf fall. The sky view factor and the height of the sun in
the sky dominated Mitchell's results. In this present study, R20 was consistent with the
PAR under canopy for leafing in May, and the seasonal peak in the NFF is based on
leafing in M a y and leaf fall in August. An August leaf fall m a y not be appropriate for
the local forests used in this study, thus affecting estimates of the autumn peak in .#20
values.
The 7?2o values were higher in the deciduous forest than in the mixed forest. This
was especially marked between February and April, even though the precipitation in
the deciduous forest (415 m m ) far exceeded that in the mixed forest (172 m m ) . In
addition, R o was 5 - 1 0 % in the deciduous forest during June and September but 0%o in
the mixed forest. The value of R20 was larger in the deciduous forest than in the mixed
forest during June and September in spite of the fact that precipitation in these periods
was greater in the deciduous forest (795.5 m m ) than that in the mixed forest
(673.0 mm). These differences are caused by the sky view factor (Table 1): litter dries
faster in deciduous forest than in mixed forest, because more radiation reaches the
forest floor.
2
The difference in 0 between the two forests is a function of their structure, which
suggests that estimates of litter moisture content can be used to predict the risk of fire
in individual forest stands.
REFERENCES
K o b a y a s h i , C , T a m a i , K., Hattori, S. & N i s h i y a m a , Y. (1991) T h e spread rates of forest fires. Influence of degree of slope
and forest floor fuels. J. Japan.
For. Soc.73,
7 3 - 7 7 (in Japanese).
Mitchell, P. L. (1992) G r o w t h stages and m i c r o c l i m a t e in c o p p i c e and high forest. In: Ecology and Management
of
Coppice Woodlands (ed. by G. P. Buckley), 3 1 - 5 1 . C h a p m a n & Hall, London, UK.
Pyne, S. J., A n d r e w s , P. L. & Laven, R. D . ( 1 9 9 6 ) Introduction
to Wild/and Fire (second edn). John W i l e y & Sons Inc.,
N e w York, USA.