298 R. Casa et al. Agricultural and Forest Meteorology 104 2000 289–301
in parallel the resistances for individual leaves above a representative area of ground. Fig. 8 plots r
s
against GAI for all dates when GAI was measured. The data
points span the periods before and after the achieve- ment of maximum GAI but there was no evidence of
hysteresis in the curve. The points are close to the line representing the relationship:
r
s
= r
s min
G where r
s min
is 90 s m
− 1
and G is GAI. The constant of proportionality, r
s min,
which is the surface resistance of an actively growing linseed crop
completely covering the ground and freely supplied with water, was estimated, using the data in Fig. 7, as
the average value of r
s
for DAS 69-75 23 May–29 May, when the ground cover exceeded 0.80, the soil
water deficit was relatively low and rain was not a complicating factor. The equation given above gives a
value for r
s
of 45 s m
− 1
at the maximum GAI recorded whereas Fig. 8 suggests that r
s
does not decrease once GAI exceeds 1.00. Thus, r
s
can be modelled as the higher of the values calculated from GAI and 90 s m
− 1
. Before investigating the effect of soil water deficit
on r
s
, it was necessary to ascertain whether periods of rain were complicating the interpretation since r
s
should be zero for wet foliage. Four occasions were
Fig. 8. Relationship between linseed surface resistance r
s
and green area index GAI. The r
s
values are shown only for the days on which direct GAI measurements were carried out. r
s
was derived from evapotranspiration BREBS measurements and inversion of the Penman–Monteith equation. The data are fitted by
the line representing the relationship r
s
= 90G, where G is GAI.
Fig. 9. Relationship between excess r
s
, defined as the measured r
s
minus the modelled r
s,
calculated from GAI green area index with a minimum value of 90 s m
− 1
, and the measured soil water deficit SWD over the entire growing season.
found when a day on which more than 5 mm rain fell was both preceded and followed by a day with no
significant rain. There was no consistent or significant difference between the values of r
s
on the three days and thus rainfall was not a factor having a main effect
on surface resistance. The effect of soil water deficit on r
s
was evaluated by computing the difference between the measured
and the modelled r
s
and plotting it against the mea- sured soil water deficit Fig. 9. The values of GAI
required by the model were estimated by linear inter- polation between the field measurements. Contrary to
expectations, there was no effect of SWD on surface resistance. This is particularly obvious for deficits ex-
ceeding 50 mm where any affect should be clear. The apparent decrease of resistance at high deficits is prob-
ably an artefact caused by an underestimate of GAI near crop maturity and the extreme sensitivity of r
s
to GAI at values of GAI near zero.
4. Discussion
It is difficult to estimate the error in the Bowen ratio estimate of daytime evapotranspiration from our data,
because there was no independent check of the two BREBS. However the procedure used to estimate E
a
seemed to be robust, as shown from the tests where in- creasing amounts of data were deleted. Although two
R. Casa et al. Agricultural and Forest Meteorology 104 2000 289–301 299
apparently identical BREBS were used, they yielded rather different daytime evapotranspiration values on
some occasions even after suspect values had been re- moved. It is possible that the threshold value used to
discard data when the fetch was insufficient 20:1 was inadequate and although Heilman and Brittin 1989
showed that this limit was appropriate in their situ- ation, more conservative fetch values should perhaps
have been used. Our data on the insignificance of night-time evapotranspiration are consistent with those
of Malek 1992. He found that in a semi-arid environ- ment, although night-time evapotranspiration from an
alfalfa Medicago sativa L. crop could reach 14 of the 24 h average under conditions of high windspeed
at night i.e. reaching 5 m s
− 1
the growing season av- erage was less than 2. During the growing season
only six nights had average windspeeds that exceeded 2 m s
− 1
. Night-time evapotranspiration was thus not significant in the present work.
The difference between the calculated and measured SWDs in the earlier phase of growth can be explained
by errors in the estimation of profile available water. After day 60, the measured SWD underestimated the
calculated value. During this period, the soil did not return to field capacity and drainage from the profile
is unlikely. However, the measurement of SWD was unable to take into account the removal of water from
the layer between 0.60 m and the base of the root- ing zone. Although the maximum SWD exceeded the
calculated profile available water, the discrepancy can be explained by the use of −0.03 MPa to assess field
capacity. Webster and Beckett 1972 found that the matric potential of well-drained soils at field capacity
was only about −0.005 MPa. Although these measure- ments were made in England during winter when the
low soil temperature would have resulted in greater surface tension and viscosity of the water than in Italy
in summer, the appropriate matric potential is likely to have been nearer the latter than the former, thus
leading to an underestimate of available water.
Analysis of the surface resistance data was com- plicated by its variability. A sensitivity analysis was
carried out to establish the effect of a ±20 change in daily evapotranspiration E
a
on surface resistance c.f. Fig. 2. Decreasing E
a
by 20 increased r
s
typi- cally by less than 10 but occasionally by up to 30.
Increasing E
a
typically resulted in a decrease of 30 in but occasionally 100. These errors, however, are
small compared with the seasonal trends and are un- likely to cause a systematic bias although they may
go some way to explaining why the estimates are so variable.
When the Penman–Monteith model is used over pe- riods of minutes, as was originally the case, r
s
can fall to zero when the foliage is wet. However, this ef-
fect is less clear when daily averages are calculated as the foliage may be wet for only a part of the day.
This will be particularly the case when rain falls in the afternoon after the rate of evapotranspiration has
passed its daily peak. Interception losses are notori- ously difficult to estimate accurately. However, the in-
terception losses of linseed must be considerably less than the 7 of rainfall recorded by Lull 1964 for
oats because the linseed leaves are much smaller and the leaf axils are unlikely to act as reservoirs for wa-
ter. Thus, the leaves will dry relatively quickly after rain, particularly, if they are shaken by the wind, and
r
s
will increase. After DAS 60 14th May, i.e. when the soil water deficit started to increase, there were
few days with rain and on those days the rainfall was less than E
a
. Rain infiltrating the soil can temporarily reduce the effective soil water deficit experienced by
crops provided the roots near the surface are still ac- tive which would not be the case after a prolonged dry
spell. Thus, it is not surprising that no consistent effect of rainfall on r
s
could be detected in the present study. As GAI increases, there comes a point where r
s
is no longer inversely proportional to green area index
but becomes essentially constant because the lower leaves become shaded and are subject to a smaller hu-
midity gradient while there is an extra aerodynamic resistance involved in the transport of water vapour to
the effective canopy exchange surface. It was fortu- itous that the minimum r
s
calculated from the seasonal trend was dominated by measurements near a GAI of
1.00 thus fixing one point on the inverse relationship between r
s
and GAI. The value of r
s min
in the present study was higher than the 70 s m
− 1
fixed surface re- sistance used to calculate E
in the FAO version of the Penman–Monteith equation Section 2.3. However,
E is calculated for a reference crop such as a pas-
ture grass or lucerne rather than linseed. Although the stomatal resistance of the linseed leaves was not mea-
sured independently, an estimate was obtained by sub- stituting the maximum rate of photosynthesis obtained
by Rode and Bethenod 1980 for their control, i.e.
300 R. Casa et al. Agricultural and Forest Meteorology 104 2000 289–301
not drought-stressed, glasshouse-grown linseed plants into the regression equation of Körner et al. 1979
and assuming a GAI of 1.0. This procedure gave a pre- dicted value for the minimum r
s
of 104 s m
− 1
, which is consistent with the values calculated in the present
paper, particularly, as glasshouse grown plants often exhibit a higher stomatal resistance than those grown
in the field Körner et al., 1979.
Other research has shown a positive relationship between r
s
and soil water deficit e.g. Russell, 1980 caused by an increase of stomatal resistance in re-
sponse to soil drying. In the present work, the soil effectively dried monotonically after DAS 60 and
surface resistance showed the expected increase. However, the mechanism appears not to be through
increased stomatal resistance of individual leaves but rather through canopy senescence. This observation
may explain the overestimate of K
c adj
obtained using the FAO 56 methodology Section 3.3, which implic-
itly assumes an effect on stomatal closure. Casa et al. 1999 similarly found that it was not drought as such
that reduced linseed yield in Mediterranean conditions but rather the associated high temperatures which
shortened the growth cycle and thus hastened canopy senescence. Linseed seems to be well adapted to avoid
drought in an environment characterised by a summer drought, a phenomenon that may be more widespread
in Mediterranean environments than is generally realised.
5. Conclusions
