Agricultural and Forest Meteorology 157 (2012) 77–85
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Agricultural and Forest Meteorology
journal homepage: www.elsevier.com/locate/agrformet
Dynamics of evapotranspiration partitioning in a semi-arid forest as affected by
temporal rainfall patterns
Naama Raz-Yaseef a,1 , Dan Yakir a,∗ , Gabriel Schiller b , Shabtai Cohen b
a
b
Department of Environmental Science and Energy Research, Weizmann Institute of Science, Rehovot, Israel
Department of Environmental Physics and Irrigation, Institute of Soil, Water and Environmental Science, A.R.O. Volcani Center, Israel
a r t i c l e
i n f o
Article history:
Received 1 August 2011
Received in revised form
26 December 2011
Accepted 21 January 2012
Keywords:
Evapotranspiration partitioning
Tree transpiration
Soil evaporation
Temporal precipitation pattern
Semi-arid
Pine forest
Soil water adsorption
a b s t r a c t
We extend our recent study of the effects of tree density on evapotranspiration (ET) partitioning in a
semi-arid pine forest by examining the influence of the temporal patterns in rainfall (P) on the dynamic
contributions of tree transpiration (Tt ), soil evaporation (Es ) and rainfall interception (IP ) to total ET. Soil
evaporation accounted for 39% of average annual ET over the four-year period, and was associated with
soil moisture content in the upper 5 cm and solar radiation, therefore peaking during the wetting and
drying seasons (up to 0.75 mm day−1 ). In the dry summer, Es diminished and as much as 50% of the
residual flux was due to re-evaporation of moisture condensed at night (adsorption). Tree transpiration
accounted for 49% of average annual ET, and was associated with soil moisture at a depth of 10–20 cm.
Transpiration peaked only in late spring (1.5 mm day−1 ), after the accumulation of large storms allowing
infiltration below the topsoil. Moisture at these depths was maintained for longer periods and was even
carried over between rain seasons following a high precipitation year. Interception was 12% of annual ET
but was larger than 20% during the rainy period. The results indicated that both Tt /ET and Es /ET could vary
between 30% and 60% due to their differential response to seasonal environmental drivers. Annual Tt /ET,
a major parameter indicating forest productivity and survival, was more influenced by the occurrence of
large storms (>30 mm; P30 /P ratio) than by P itself. In an assessment of the potential warming and drying
trends predicted for the Mediterranean region in the next century, changes in both total precipitation
and in its temporal patterns must be considered.
© 2012 Elsevier B.V. All rights reserved.
1. Introduction
Evapotranspiration (ET) is an integrated term, composed of the
linked vapor fluxes of plant transpiration (T), soil evaporation (Es )
and canopy-intercepted precipitation (IP ). Whereas Es is a physically controlled flux, T is strongly influenced by plant physiology
and can be affected by abiotic environmental conditions, but also
by plant species characteristics, stomatal sensitivity, mycorrhizal
associations, plant disease, atmospheric CO2 concentrations and
nutrients. A growing awareness of the importance of ecohydrology has motivated efforts to partition ET into its components, as a
key to unraveling processes underlying ecosystem water use and
its response to change (Huxman et al., 2005). Previous studies show
that the T/ET ratio varies greatly among ecosystems and timescales,
but on an annual basis it is mostly in the range 40–70% (Reynolds
∗ Corresponding author. Tel.: +972 8 934 2549; fax: +972 8 934 4124.
E-mail addresses: [email protected] (N. Raz-Yaseef),
[email protected] (D. Yakir).
1
Current address: Department of Environmental Science, Policy and Management, UC Berkeley, Berkeley, CA, USA.
0168-1923/$ – see front matter © 2012 Elsevier B.V. All rights reserved.
doi:10.1016/j.agrformet.2012.01.015
et al., 2000; Mitchell et al., 2009; Moran et al., 2009; Zhongmin
et al., 2009; Cavanaugh et al., 2010; Staudt et al., 2011). This range of
ratios emphasizes that even in water-limited environments, plants
do not use all of the precipitation input and major water losses
occur, mainly to Es and runoff. Vegetation type, through its effect
on the proportion of the shaded surface fraction, also influences
T/ET, which generally increases from grasses to shrubs to trees
(Kostner, 2001; Moran et al., 2009; Raz-Yaseef et al., 2010a; Wang
et al., 2010). The T/ET ratio has been shown to vary among ecosystems according to the depth of water uptake, and is larger for
deep-rooted trees than for grasses, as well as for soils with better infiltration regimes than more impermeable soils (Scholes and
Archer, 1997; Laio et al., 2001; Kurc and Small, 2004; Cavanaugh
et al., 2010).
When precipitation is characterized by short and sporadic
showers, such as observed in some semi-arid sites (e.g. Sharon,
1972; Sala and Lauenroth, 1982; Lapitan and Parton, 1996; Loik
et al., 2004), infiltration depth can be reduced, limiting moisture to
shallow depths. Soils with high densities and fine textures exhibit
low infiltration rates and high water holding capacities, further constraining infiltration (e.g. Noy-Meir, 1973; Reynolds et al., 2000;
Scott et al., 2000; Kochendorfer and Ramírez, 2008). Even in such
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N. Raz-Yaseef et al. / Agricultural and Forest Meteorology 157 (2012) 77–85
cases, infiltration below the topsoil can occur following infrequent
events with relatively large rain amounts. In some extreme events,
deep infiltration can lead to soil moisture “storage” through the dry
season and into the following wet seasons, as has been reported in
dry ecosystems (Paruelo et al., 2000; Kurpius et al., 2003; Tietjen
et al., 2009; Raz-Yaseef et al., 2010b). Pulsed precipitation events
that lead to infiltration deep enough to increase root uptake have
a marked effect on above-ground biomass production (Schwinning
and Sala, 2004; Heisler-White et al., 2008; Knapp et al., 2008) and
can contribute to ecosystem resilience and survival under drought
conditions.
Quantifying T/ET is key to predicting ecosystem survival and
productivity, especially in water-limited regions. This is extremely
important in light of the drying and warming trends predicted for
the entire Mediterranean region and the southwestern US (IPCC,
2007). The objective of this four-year study was first, to define
the dynamics of ET partitioning on seasonal and, within limits of
the data-collection period, annual time scales. Second, we aimed
to identify the main environmental and meteorological conditions
affecting this flux partitioning. Finally, we attempted to connect ET
partitioning to the large observed variations in temporal precipitation patterns in the semi-arid pine forest ecosystem.
2. Methods
2.1. Study area
Yatir Forest is located in Southern Israel, at the transition zone
between sub-humid Mediterranean and arid climates, on the edge
of the Judean Mountain ridge (31◦ 21 N and 35◦ 02 E, 630 m AMSL).
The site is a ca. 45-year-old Pinus halepensis afforestation, currently
spread over an area of 28 km2 , with a density of ∼300 trees ha−1 ,
leaf area index (LAI) of ∼1.50 m2 m−2 , and sparse understory vegetation (Maseyk et al., 2008; Grunzweig et al., 2009; Rotenberg
and Yakir, 2010; Sprintsin et al., 2011). Average air temperatures for this region are 10 and 25 ◦ C for the coldest and hottest
months, January and July, respectively. Average precipitation for
the last 30 years is 285 ± 88 mm year−1 . Nearly all precipitation
falls between December and March, followed by an extended dry
period during the hot summer. Potential ET (1600 mm year−1 )
largely exceeds precipitation inputs. The soil at the research site
is shallow (20–40 cm), Aeolian-origin loess with a clay-loam texture (0.31 ± 0.02 sand, 0.41 ± 0.10 silt and 0.28 ± 0.04 clay; density:
1.65 ± 0.14 g cm−3 ) overlying chalk and limestone bedrock. Deeper
soils (up to 1.5 m) are sporadically located at topographic hollows. While the natural rocky hillslopes of the semi-arid northern
Negev are known to produce flash floods, the forest reduces runoff
dramatically (to less than 5% of precipitation, Shachnovich et al.,
2008). Groundwater is deep (>300 m), eliminating the possibility
of groundwater recharge or utilization.
2.2. Meteorological measurements
An instrumented tower was erected in the geographical center of Yatir forest, following Euroflux methodology (Aubinet et al.,
2000). The system uses a 3D sonic anemometer (Omnidirectional
R3, Gill Instruments) and a closed path LI-COR 7000 CO2 /H2 O gas
analyzer (LI-COR Inc.) to measure the evapotranspiration flux (ET)
and net CO2 flux (NEE). The flux tower’s footprint was defined
according to Gockede et al. (2008), indicating that the largest contribution to the flux during the day was from an area 34 m away
from the tower and that 95% of the recorded flux came from an area
within 1300 m of the tower. Wind direction was from the northwest
to southwest sector during 64% of the day.
Air temperature (Tempa ) was measured with temperature
probes at heights of 1, 5, 9, 15 and 19 m. Soil temperatures (Temps )
at 2 and 6 cm depth were measured at six different points around
the tower with thermocouples. Wind speed (Ws ), wind direction
(WD ), relative humidity of the atmosphere (RH), shortwave radiation, longwave radiation and photosynthetically active radiation
were measured above and below the canopy, at heights of 15 and
1 m, respectively; both the upward and downward components of
radiation were measured (Rotenberg and Yakir, 2011).
Precipitation (P) was measured by (1) a recording rain gauge
(Campbell Scientific, USA) positioned at a height of 15 m on top of
the flux tower, collecting data every half hour, and (2) a standard
rain station positioned in a clearing in the forest, at a distance of
1.50 km from the tower site, from which data have been manually
collected on rainy days since 1971. Data from this rain station (Yatir
forest, KKL) were used to determine long-term average annual
precipitation for the site. Data from the rain gauge were used to
calculate intercepted precipitation (IP ) for individual rain events,
based on the equation provided by Shachnovich et al. (2008):
IP(mm) = P (mm) − 0.94 · P (mm) − 0.76
(1)
2.3. Soil water content
Volumetric soil water content () was measured at a half-hour
time resolution with three reflectrometry sensors (CS616, Campbell Scientific) positioned vertically in the ground and measuring an
average value for soil depth of 0–30 cm ( 0–30 ). A specific calibration
equation was prepared in the laboratory for these sensors to fit the
dense soil at our site (according to the manufacturer’s instructions).
The sensitivity of the CS616 measurements to temperature was
corrected by the factory-defined temperature-correction equation.
Soil temperatures were measured at depths of 1, 5, 15 and 30 cm
in close proximity to the CS616 sensors (HOBO H8 loggers, Onset
Computers). In 2005, time domain reflectometry (TDR) sensors
(TRIME, IMKO Inc.) were installed horizontally in three different
pits dug around the tower. The pits varied in depth according to
the soil/bedrock structure at each site. Sensors were installed horizontally, at constant depths of 5, 15, 30 (deepest sensor in pit 1),
50, 70 (deepest sensor in pit 2) and 125 cm (deepest sensor in pit
3). Variability between sensors of similar depths but different positions (pits) was less than 5%. Values of x (x = 5, 15, 30, 50, 70 or
125 cm) presented herein are averages of the one to three sensors
available for a particular depth. These values denote soil moisture
measured at a specific depth, rather than the integral measurement
of the previous method (CS616) for depth 0–30 cm ( 0–30 ).
2.4. Transpiration
Sap flux was used to estimate tree transpiration (Tt ; the subscript ‘t’ is added to emphasize that while there is an additional,
very small below-canopy component, here only tree transpiration
is considered) with two similar techniques: the ‘Tmax ’ heat-pulse
velocity method (HPV; Cohen, 1994) and the Granier method
(Granier, 1987). HPV temperature signals were converted to mass
flow rate based on empirical calibration coefficients suitable for
Yatir trees (type and size; Schiller and Cohen, 1998; Cohen et al.,
2008). The HPV system was operated during 2003/2004 and
2004/2005; the Granier system was operated during 2005/2006.
Measurements were conducted hourly (including night hours) for
eight trees representing average forest tree size, age and slope
aspect in the flux-tower footprint. Water uptake (L h−1 tree−1 )
was converted to Tt (mm h−1 ) according to forest tree density
(300 ha−1 ). The Granier sensors were shorter than the HPV sensors
(20 and 60 mm, respectively) and did not reach all depths of the
conductive sapwood. According to Cohen et al. (2008), conductive
sapwood diameter for semi-arid Pinus halepensis is ∼40 mm, but
sap velocity decreases with diameter. According to these findings,
N. Raz-Yaseef et al. / Agricultural and Forest Meteorology 157 (2012) 77–85
79
a correction factor of 1.72 was applied to the Granier sensors, to
compensate for measuring to a depth of only 20 mm. We compared
data from the HPV and Granier systems for an overlapping period
(March–May 2005) and found a high correlation between the
two methods, with a ratio resembling the above correction factor
(Tt (HPV) = 1.70·Tt (Granier), R2 = 0.95). Fluxes for 2006/2007 were
simulated based on the relationships observed in Yatir (G. Schiller,
unpublished), simulating Tt (mm day−1 ) as a function of 0–30
(%) and potential evapotranspiration (PET; mm day−1 ), during the
2-year measuring period. All terms in the model were highly significant (P < 0.0001), and the overall adjusted R2 of the model was 0.61.
PET for Yatir was computed according to the Penman–Monteith
equation procedure recommended by Allen et al. (1998).
2.5. Soil evaporation
2.5.1. Plot-scale flux measurements
Measurements of soil evaporation (Es ) were conducted with a
modified LI-COR 6400-09 soil CO2 flux chamber. Prior to the measurements, this methodology was calibrated and tested against
fluxes measured with microlysimeters, and showed high reliability (for fluxes in the range of −0.02 to 0.40 mm h−1 , n = 59,
R2 = 0.93; Raz-Yaseef et al., 2010a). In the field, Es was measured
from 14 permanently placed soil collars. Measurements were conducted manually on 42 days, spread evenly throughout the research
period (October 2004–May 2007) and representing different seasons and environmental conditions. Measurements were carried
out between 1100 and 1200 h, the expected time of peak diurnal Es
flux (Baldocchi et al., 2000; Williams et al., 2004).
2.5.2. From plot- to stand-scale measurements
Spatial variability between the 14 measured soil collars was high
(STD = ±47%), and upscaling was achieved according to the methodology elaborated in Raz-Yaseef et al. (2010a). This methodology is
based on the difference between Es fluxes measured below tree
canopies and in the gaps between trees, and the ratio of shaded to
exposed areas of the forest floor, which varies seasonally according
to the solar declination.
2.5.3. Estimating daily fluxes
Full diurnal cycles of Es (starting before sunrise and ending after
sunset) were measured in six campaigns representing different
seasons and conditions. On these days, measurements were taken
every half-hour on two adjacent soil collars (2 m apart), one positioned below a tree canopy (shaded) and the other positioned in
a gap between the trees (exposed to direct sun). During three of
the six days, soil-chamber measurements of Es were conducted
hourly on five additional chambers, confirming that the diurnal
trend measured at the two main soil chambers was similar to that
measured at other locations (results not shown). Although daily
fluxes and trends varied seasonally, a strong relationship between
peak noontime values and total daily values of Es was observed for
all measured days (R2 = 0.91; n = 12):
EDT (mm day−1 ) = 0.39 · ln[Es-noon (mm h−1 )] + 1.49
(2)
where EDT is the daily total soil evaporation and Es-noon is the peak
noontime flux of soil evaporation. We used this relationship to estimate total daily Es values from measured noontime values on days
for which a full diurnal cycle was not obtained.
Good hydrological closure was achieved on daily timescales for
most days, with 0.97 > [(Es + Tt )/ET] > 0.90 (where Es , Tt , and ET were
obtained from soil chambers, sap flow and eddy covariance at the
flux tower, respectively).
Fig. 1. Daily values of precipitation (P), soil water content averaged for depth
0–30 cm ( 0–30 ), air temperature at 1 m (Tempa ) and evaporation fluxes (total evapotranspiration – ET, tree transpiration – Tt and soil evaporation – Es ) during the
4-year study period.
2.5.4. Simulating soil evaporation
The 42 days on which Es was measured were divided into four
seasonal groups (autumn, winter, spring and summer). The division into seasons was conducted according to thresholds in soil
water content and air temperature, and not according to fixed
calendar definitions (see Section 3.2). Using multiple linear correlation regression analysis (SPSS 13.0 Software, SPCC Inc., 2004), a
stepwise selection defined the dominant variables controlling Es
for each season. The environmental parameters included in the
analysis were: soil water content at different depths ( 5 to 125 ),
net radiation (Rn ), vapor-pressure deficit (VPD), air temperature
at different heights (Tempa 1 m to Tempa 19 m ), soil temperature at
different depths (Temps 2 cm and Temps 6 cm ) and wind speed (Ws ).
This procedure was conducted for half-hour and daily time steps.
The obtained regressions were used together with the continuous
measurements of the environmental variables at our permanent
flux-measurement site to extend our 42 measurement campaigns
to a continuous estimated record of Es over the 4-year study period
(Fig. 1).
3. Results
3.1. Precipitation and soil water content
Environmental conditions were typical for the region (Fig. 1),
with the rainy season usually starting in October with small
rain events (∼5 mm day−1 ), while the main rain period, between
December and March, had larger storm events (∼20 mm day−1 but
up to 60 mm day−1 ). Rain typically ceased in March/April. Soil water
content mirrored the seasonality in precipitation: 0–30 responded
almost instantaneously to the first autumn rains, and remained
above 0.30 m3 m−3 throughout most winters. Spring drying lasted
approximately two months, during which 0–30 decreased to
0.09 m3 m−3 . These low soil moisture conditions persisted throughout the approximately half year long dry summer period.
Average annual precipitation during the four year research
period was similar to the long-term (35-year) mean value (285
vs. 290 mm, respectively), with one year of near-average precipitation, two dry years and one wet year (Table 1). The two years with
low precipitation, 2003/2004 and 2005/2006, had similar annual
precipitation (231 and 224 mm), but differed in its temporal distribution: a similar number of rain events, 27 and 28 rainy days,
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N. Raz-Yaseef et al. / Agricultural and Forest Meteorology 157 (2012) 77–85
Fig. 2. Diurnal cycles of evapotranspiration (ET; half-hour values, flux tower), tree transpiration (Tt ; half-hour values, average of 8 trees, sap flux method), soil evaporation
(E1 , E2 ; half-hour values, two adjacent soil collars, soil-chamber technique) and net radiation (Rn ). Tt was not measured on the first two measurement days. Negative values
represent downward fluxes from the atmosphere to the forest or soil.
respectively, were spread over 132 days in the first year and over
179 days in the second year. The long intervals between precipitation events during 2005/2006 allowed soil water content to decline
to near summer values (Fig. 1).
3.2. Dynamics of the evaporation fluxes
Diurnal cycles: During the wet season, a clear diurnal cycle in
evaporation fluxes was observed (Fig. 2), generally resembling the
cycle of net radiation. In summer, fluxes were small and the diurnal cycle was less noticeable. During a heat-wave episode (9 June
2005), tree transpiration values remained similar to those during
the mid-day depression throughout the day (Fig. 2f). During the
dry season, small negative fluxes in soil evaporation (i.e. from the
atmosphere to the soil; −0.04 to −0.05 mm day−1 ) were detected
with the soil chamber technique before sunrise and after sunset
(Fig. 3, upper panels). A similar phenomenon was measured with
our soil chamber during the laboratory calibration process on ovendried soils, and the negative fluxes measured with the soil chamber
were validated by balanced-based measurements (Raz-Yaseef et al.,
2010a). These fluxes were consistent with water adsorption from a
cool and humid atmosphere into the dry air within the soil pores,
and possibly to the hygroscopic soil water. Negative fluxes measured in the field were further supported by the 1.5–3.0 h delay in
diurnal peak soil moisture measured with the TDR, when compared
to atmospheric RH values (the moisture adsorption period, Fig. 3,
lower panels; summer night RH > 75%, 5 < 0.10 m3 m−3 ).
Seasonal cycles: The seasonal cycle of ET was characterized by low fluxes during the dry season (0.25–0.75 mm day−1 ,
Figs. 1 and 4), and an increase only from the middle of the rainy
season (November/December) peaking in early spring (with typical March ET fluxes of ∼1.50 mm day−1 , but up to 3.25 mm day−1 ).
Fluxes rapidly decreased after rain cessation, and reached the low
summer values by April/May. Seasonal variations in transpiration
were similar to those of ET (Figs. 1 and 4), with a gradual rise in late
November, a peak in March/April (typical fluxes of 0.65 mm day−1 ,
but up to 1.50 mm day−1 on some days) and a rapid decrease to a
low summer flux of ∼0.20 mm day−1 from June and until the following rainy season. Intercepted precipitation was significant only
during the rainy season (October–April), and peaked on average in
February, at 0.39 mm day−1 .
Soil evaporation measurements indicated high fluxes during the
transition wetting and drying periods (autumn and spring, respectively; maximum daily fluxes of 0.75 mm day−1 ) and lower fluxes
in the range of 0.05–0.25 mm day−1 during both the wet winter and
dry summer (Fig. 5). We therefore divided soil evaporation into seasons of characteristic fluxes, and used multivariable correlation on
the predefined seasonal basis to estimate daily Es . These seasons
Table 1
Annual sums of precipitation (P), tree transpiration (Tt ), soil evaporation (Es ) and intercepted precipitation (IP ) and their partial contribution to total evapotranspiration (ET)
during the study period. The ratio between precipitation occurring in storms larger than 30 mm and total P (P30 /P) and the water-use efficiency index (WUE; NEE/ET) for
each year are also shown. The average value and standard deviation (STD) for the 4-yearstudy period are noted below.
P
Tt
Es
mm year−1
P30 /P
mm year−1
Tt /ET
mm year−1
2003/2004
2004/2005
2005/2006
2006/2007
231
377
224
308
0.56
0.64
0.43
0.55
134
156
111
115
0.57
0.45
0.49
0.44
99
112
93
106
Average
STD
285
72
0.55
0.09
129
21
0.49
0.06
102
8
IP
ET
WUE
mm year−1
IP /ET
mm year−1
gCO2 kg H2 O−1 year−1
0.42
0.33
0.41
0.40
27
39
26
33
0.11
0.11
0.11
0.13
235
343
227
263
0.93
1.06
0.74
0.89
39
0.04
31
6
0.12
0.01
267
53
0.90
0.13
Es /ET
N. Raz-Yaseef et al. / Agricultural and Forest Meteorology 157 (2012) 77–85
81
Fig. 3. Upper panels: diurnal cycles of soil evaporation (Es ) and net radiation (Rn ) measured over two summer days. Soil adsorption (negative fluxes of Es ) was measured
during the hours before sunrise and after sunset. Lower panels: relative humidity (RH) and soil moisture in the topsoil ( 5 ) on the same days as in upper panels. A 1.5–3 h
delay was observed between peak 5 and peak RH, but otherwise diurnal trends were similar. This suggests that the negative values measured for Es originated from the
cooler, wetter night-time atmosphere, which produced an increase in moisture in the topsoil.
were as follows: summer (the water-limited season) where soil
moisture content at the topsoil, 5 was above 0.06 m3 m−3 ; winter (the energy-limited season) with daily average Tempa < 15 ◦ C;
the autumn and spring transition seasons (both energy and surface
soil water content are abundant), in which 0.06 < 5 < 0.23 m3 m−3
and daily average Tempa > 15 ◦ C. Applying these environmental
thresholds resulted in variations in the timing of the seasonal
changes among years. The summer season started on day of year
(DOY) 142 ± 10 days. The autumn transition season was not identifiable in two of the study years, implying a direct shift from
summer to winter conditions. During the other two years, the transition to “autumn” conditions was on DOY 356 (2005/2006) and
DOY 301 (2006/2007). Transition to “winter” conditions was on
DOY 351 ± 21. Transition to “spring” conditions occurred on DOY
89 ± 10.
Tt
Es
Ip
ET
Evaporation Flux
(mm d-1)
1.50
1.00
The resulting season-specific multivariable linear correlations
between Es and environmental parameters were high and significant (0.68 < R2 < 1.00, P < 0.05, Table 2). The analysis defined the
relative contribution of each parameter to the regressions (ˇ%). Soil
water content in the topsoil was found to control soil evaporation
during the wetting period (ˇ = 81%). During the winter, there was
no one important variable, but air temperature was the most influential one (ˇ = 28%). Soil water content (ˇ = 40%) and wind speed
(ˇ = 33%) were the largest contributing variables during the drying
season. During the summer, the main factor affecting Es was net
radiation (ˇ = 35%), and soil water content was insignificant. Note
that similar correlations were not statistically significant when the
above seasonality was not applied.
Annual cycles: On an annual basis, ET varied between 227
and 343 mm year−1 with a normalized standard deviation (NSTD;
STD/average) of 0.20, comparable to that for precipitation
(NSTD = 0.25). The ET/P ratio varied between 1.02 and 0.85, and
was negatively correlated with precipitation: evaporation losses
were slightly larger than precipitation inputs during the dry years.
Despite the large interannual variability in precipitation and ET,
the hydrological budget was nearly closed in all years, and on average for the four year research period, [(Es + Tt + IP )/ET] = 1.00 ± 0.09,
validating our experimental approach.
0.50
0.00
Relative contibution
to ET
1.00
0.75
0.50
!"
#$
%&
0.25
0.00
Oct
Dec
Feb
Apr
Tt
Es
Jun
Aug
Ip
−1
Fig. 4. Upper panel: monthly averages (mm day ) of the separate fluxes of tree
transpiration (Tt ), soil evaporation (Es ) and intercepted precipitation (IP ) for the
research period. Lower panel: relative contribution of each of these fluxes to total
ET. The seasonal cycle, as well as the relative contribution of each flux, was different
for each of the fluxes.
Fig. 5. Seasonal trend of air temperature (Tempa ) and soil moisture in the topsoil
( 5 ), averaged over the three years. Es fluxes were high during the wetting and drying
transition periods and low during the winter period (energy-limited, Tempa < 15 ◦ C)
and summer period (water-limited, 5 < 0.06 m3 m−3 ).
82
N. Raz-Yaseef et al. / Agricultural and Forest Meteorology 157 (2012) 77–85
Table 2
Analytical results of seasonal multiple linear regressions between noontime soil evaporation (Es ) and environmental and meteorological variables. A list of all variables used
for this analysis appears in the methods section. The dominant variables for each regression were chosen automatically by stepwise procedure: water content in the topsoil
( 5 ), net radiation (Rn ), vapor-pressure deficit (VPD), air temperature (Tempa ) and wind speed (Ws ). The number of days used for the analysis (n), correlation coefficient with
measured parameters (R2 ) and significance (P) are presented for each regression; the coefficients (B) and their relative contributions (ˇ%) are presented for each variable.
Wetting season
2
Winter
R
P
n
R
P
n
R
P
n
R2
P
7
0.682
0.045
16
0.813
0.034
5
1.000
–
14
0.977
0.046
B
Winter
ˇ%
−6.57E−02
1.22E+00
81
1.03E−02
19
B
−4.90E−02
3.20E−01
4.82E−05
−1.24E−02
2.31E−03
−8.09E−03
Annual values of tree transpiration varied in the range of
111–156 mm year−1 (NSTD = 0.16). Annual values of soil evaporation varied between 93 and 112 mm year−1 (NSTD = 0.08).
Calculated values of intercepted precipitation (IP ; using Eq. (1))
varied between 26 and 39 mm year−1 (NSTD = 0.17).
3.3. ET partitioning as affected by the temporal precipitation
pattern
On average for the whole research period, tree transpiration was the largest water flux, making up 49% of ET with
129 ± 21 mm year−1 . Soil evaporation accounted for 39% of ET
(102 ± 8 mm year−1 ), and intercepted precipitation was 12% of ET
at 31 ± 6 mm year−1 . Annual values of soil water adsorption were
estimated to be in the range of 10–15 mm year−1 , adding ∼5% to
precipitation inputs.
On a monthly and seasonal basis, the relative contributions of
the individual evaporation fluxes to total ET varied greatly (Fig. 4,
lower panel). Soil evaporation values were similarly high during
the wetting and drying seasons, but the relative contribution of Es
was largest during the wetting season (Es /ET up to 60%). During
the drying season, when photosynthesis and transpiration fluxes
were highest, Es accounted for less than 40% of ET. The contribution
from tree transpiration, Tt /ET varied, between 30% and 60%, and its
seasonal cycle differed from that of Tt (Tt peaked in March and Tt /ET
peaked in May). As previously noted, intercepted precipitation was
a relatively small component on an annual scale (12% on average),
but values accounted for up to 20% of ET during the rainy months.
The differential seasonal variations in Tt and Es also reflected the
differential changes in soil moisture at different depths. Soil evaporation correlated best with 5 , soil moisture at the topsoil, while Tt
correlated best with 15 (Fig. 6). The latter correlation was consistent with maximal root density at a depth of 10–20 cm (Grunzweig
et al., 2009: fine root density at depths 0–10, 10–20 and 20–30 cm
was 3.40, 5.30 and 1.60 mg cm−3 , respectively). Interannual comparison showed that 5 was consistently high throughout the wet
season and could support high soil evaporation fluxes when energy
was available. In contrast, soil moisture in the main root zone, 15 ,
increased only toward the middle of the winter season, as reflected
in the timing of peak Tt flux.
This effect can be demonstrated by two consecutive years, a wet
year (2004/2005: P = 377 mm), followed by a dry one (2005/2006:
P = 224 mm). In the topsoil layer, the duration of excess water (the
period during which soil moisture increased above the low, constant, summer values) was similar for both years, despite the large
difference in P (Fig. 7). In contrast, at a depth of 30 cm, the period of
excess water was much shorter during the low precipitation year.
2
Summer
n
Wetting season
Cons.
5
Rn
VPD
Tempa
Ws
Drying season
2
Drying season
ˇ%
22
16
22
28
13
B
Summer
ˇ%
−4.22E−02
2.07E−01
40
−2.41E−03
7.56E−04
3.66E−02
10
17
33
B
ˇ%
1.03E−01
−5.05E−03
−2.53E−03
−8.08E−04
−4.27E−04
35
24
26
14
Furthermore, the period of excess soil moisture at depth in the wet
year extended into the following hydrological year, constituting
‘water storage’ between years.
4. Discussion
Recently, we showed (Raz-Yaseef et al., 2010a) that ET partitioning, mainly between Tt and Es , is related to LAI, with larger
proportions of Es for open forests, consistent with other studies
(Yepez et al., 2005; Lawrence et al., 2007; Mitchell et al., 2009;
Newman et al., 2010). Thus an increase in LAI (representing tree size
and density) will increase Tt and decrease Es , both because of the
larger tree canopy and because of the larger shaded under-canopy
fraction. The 65% canopy cover at our study site was previously
shown to produce a near optimal Tt /ET ratio, as greater tree density and canopy cover would lead to a negative hydrological budget
and tree mortality (Raz-Yaseef et al., 2010a). Here we extended that
study by focusing on the hypothesis that at a given forest tree density, the temporal patterns of precipitation, and consequently the
distribution of soil moisture, also have an important influence on ET
partitioning and dynamics. This, in turn, must have consequences
Fig. 6. Relationships between the evaporation fluxes and soil water content at different depths. Es was synchronized with soil water content in the topsoil ( 5 ; upper
panel), while Tt correlated best with soil water content in the main root zone ( 15 ;
lower panel). Below the graphs, a table with the linear regression coefficients (R2 )
between at different depths and Es or Tt are shown, expressing the best fits are
between Es and 5 and Tt and 15 .
N. Raz-Yaseef et al. / Agricultural and Forest Meteorology 157 (2012) 77–85
Fig. 7. The period of excess soil water in the soil profile over two consecutive years: a
wet year (2004/2005, P=377 mm) and a dry year (2005/2006, P=224 mm). Thresholds
for excess soil water content were defined for each layer based on summer values:
5 > 0.10, 15 > 0.16, 30 > 0.19, 50 > 0.25, 70 > 0.27 and 125 > 0.30 m3 m−3 . Wet soil
conditions in the deepest soil layer following the wet year were still observed at the
beginning of the following dry year.
for forest productivity and tree survival in semi-arid zones, which
could greatly expand under predicted climate change scenarios for
the Mediterranean and other regions.
A key observation in our results was the differential response
of the individual evaporation flux components to environmental
drivers. This resulted in large variations in the contribution of the
different components, Tt , Es and IP , to total ET during the seasonal
cycle (Fig. 4). What, then, are the main processes affecting the
dynamics of ET partitioning on a seasonal timescale? Not surprisingly, results showed that soil water content in the topsoil layer
was the dominant factor in Es variations (Table 2). Although a large
number of parameters were used for these regressions, our analysis
demonstrated that measurements of topsoil water content, temperature, net radiation and VPD are sufficient to estimate Es . The
parameterization of these variables, however, changed seasonally,
as generally consistent with a two-stage process-based modeling
approach (e.g. the two-stage evaporative model of Ritchie, 1972;
Ritchie et al., 2009). Wind speed influenced Es mainly during the
drying season (spring), but its effect was variable throughout the
day and between days, similar to results reported by Gentine et al.
(2007). Meaningful estimates of Es are dependent on the division
into seasons, highlighting the importance of the large seasonal variability, which leads to a shift in the dominant environmental drivers
between seasons.
The results presented in Fig. 6 clearly demonstrate that Es is
controlled by soil water content in the topsoil, 5 , whereas Tt is controlled by soil water content in the root zone (10–20 cm depth at
our site, Maseyk et al., 2008; Grunzweig et al., 2009). While our site
mostly lacks the grass component, the above process resembles the
Walkers’ two layers hypothesis for grass-tree savanna coexistence,
where grasses use the topsoil moisture and trees use the subsoil
moisture (Archer, 1971; Scholes and Archer, 1997). Our research
shows that this depth-separation further affects the sensitivity
of the different ecosystem components to inter-annual climatic
83
variability in precipitation. The results presented in Fig. 7 demonstrate that while soil moisture in the topsoil remains similar, even in
years with different precipitation regimes, soil moisture in the subsoil root zone varies markedly between years, and this difference
increases with depth. Furthermore, when large storms and deep
infiltration did occur, we found evidence for soil moisture carryover (‘legacy effect’) between hydrological years, a process that is
often neglected in modeling efforts, either for the lack of such evidence or because it allows modeling each season independently
with greater computational efficiency.
A four-year period of study is insufficient to produce robust
conclusions on what influences interannual variations in ET partitioning. But it does provide some preliminary indications of
effects that warrant further research. For example, 2003/2004 and
2005/2006 were relatively dry hydrological years with comparable amounts of precipitation. But the two years differed in their
temporal precipitation patterns, such that P30 /P (the fraction of
precipitation in storms >30 mm) was 0.56 for 2003/2004, but only
0.43 for 2005/2006 (Table 1). As expected, the higher storm intensity of the first year generated high soil moisture content in the
root zone and, in turn, higher Tt /ET (0.57 vs. 0.49). Another example is in comparing 2003/2004 to 2006/2007. The first was a dry
year (P = 231 mm) while the second was a wet year (P = 308 mm),
but both had comparable P30 /P values: 0.56 and 0.55, respectively,
and the dry year had even higher Tt /ET (0.57 vs. 0.44), likely due
to deeper infiltration depth during that year. The importance of
precipitation temporal dynamics and not merely total precipitation amounts, has been previously shown (Pitt and Heady, 1978;
Nordbotten et al., 2007; Miranda et al., 2001), but was limited to
its effect on grasses. Our results show, that P30 /P was clearly more
important than P itself in influencing tree transpiration. Below, we
explain how in this ecosystem precipitation patterns effect deep
infiltration and tree water availability.
Soil moisture distribution in the time-depth dimension is
affected by the interactions between precipitation pattern and the
physical nature of the soil. Soil characteristics, which are constant
over the time scale of this study, can help translate temporal precipitation patterns to predicted patterns of soil moisture content,
and ultimately to timing of peak Tt . Differences in soil characteristics, for example, explain the differences in the results obtained
by Cavanaugh et al. (2010), who reported that transpiration correlated with soil moisture at depths of 37.5 and 75 cm in two creosote
bush sites with sandy loam, high gravel content and better infiltration compared to the Yatir site (which has a loess with clay-loam
texture). In a previous study (Raz-Yaseef et al., 2010b), we calculated soil water holding capacities for each layer, and found that
due to the clayish nature of the soils at the research site, storms
smaller than 30 mm cannot penetrate below the upper 5 cm layer.
Accordingly, we used a 30 mm storm size threshold to characterize
annual precipitation patterns at our research site. Other sites are
likely to differ according to interactions between the depth defining the topsoil, initiating mainly soil evaporation and the deeper
root zone, providing plant water uptake, and between the storm
size needed to overcome this boundary.
Most precipitation events (81% of storms) at our research site
were smaller than this 30 mm threshold. Therefore, while 5 is
continuously high during the wet seasons in all years, 15 is
dictated by the temporal pattern of the precipitation and the occurrence of larger precipitation events. These more rare event often
account for most of the interannual variability in total precipitation (Schwinning and Sala, 2004), and can explain the observed
larger interannual variability in Tt compared to Es (NSTD of 16 vs.
8%). In our case, we found that the partial contribution of large
storms was not always correlated to total annual precipitation, and
therefore years with similar precipitation amounts experienced different water flux dynamic. This further emphasizes the control of
84
N. Raz-Yaseef et al. / Agricultural and Forest Meteorology 157 (2012) 77–85
the temporal precipitation pattern on ecosystem functioning in this
water-limited system.
In this semi-arid ecosystem, P30 /P is probably the most significant component influencing forest productivity and ultimately,
survival. It is not surprising, therefore, that when incorporating
data from the CO2 flux exchange at our site (Maseyk et al., 2008;
Rotenberg and Yakir, 2010) to estimate water-use efficiency (the
ratio of net CO2 uptake to ET), a tight linear correlation was
observed for the research period with P30 /P (R2 = 0.98), but not
with P (R2 = 0.63). Similar conclusions have been recently made for
arid grassland using rain manipulation experiment (Thomey et al.,
2011), showing these environments will benefit from extreme rain
precipitation events (as previously suggested by Knapp et al., 2008;
Raz-Yaseef et al., 2010a).
Summers are dry and hot in semi-arid regions, presenting a
challenge to forest survival. Low tree transpiration fluxes during
the summer are likely influenced by residual soil moisture levels in the deep soil horizons or bedrock crevices (Schwinning,
2010), soil water storage following wet years (Raz-Yaseef et al.,
2010b), hydraulic resistance (Klein et al., 2011), and possibly moisture redistribution, as suggested for ponderosa pine (Fernandez
et al., 2008; Warren et al., 2008). While it is possible to explain
the low levels of Tt that persist under dry summer conditions, it
is more difficult to explain the maintenance of Es , however low,
during the period in which soil moisture approaches hygroscopic
levels. Our results clearly indicated soil water adsorption during
the dry season, and although small, these fluxes were not negligible when related to the residual Es flux during the summer
period. We estimated that re-evaporation from night-time adsorption can account for up to 50% of the daily residual summer Es
fluxes (adsorption of −0.05 mm day−1 , while typical summer Es
fluxes were 0.10 mm day−1 ). The handful of research efforts focusing on this process have measured soil adsorption within the range
of 0.10–1.44 mm day−1 , varying mainly as a result of soil texture
and canopy cover (Jacobs et al., 2000; Ninari and Berliner, 2002;
Verhoef et al., 2006). Whereas these studies were conducted at
bare-soil sites, the lower values measured at Yatir can be attributed
to the reported negative influence of trees and shrubs on adsorption amounts (Kosmas et al., 2001; Ramírez et al., 2007). The effect
of adsorption on tree water uptake is likely to be negligible, but this
process may provide some protection by decelerating the upward
movement of deeper soil water.
5. Conclusions
Evapotranspiration in vegetated ecosystems is often treated as a
one-source component, mainly due to methodological difficulties.
Nevertheless, partitioning ET is critical to better understanding the
processes underlying variations in this flux. Indeed, we showed that
the contribution of tree transpiration, soil evaporation and intercepted precipitation change on diurnal, seasonal and interannual
scales.
Temporal precipitation patterns and the proportional contribution of large rain events to total precipitation (P30 /P) appear to
strongly influence the partitioning of ET, with increasing tree transpiration and ecosystem water-use efficiency being associated with
increasing P30 /P. This ratio may therefore be at least as important as
total precipitation for the survival and productivity of forest ecosystems in dry environments. This is significant in light of persistent
predictions of drying in the entire Mediterranean region and elsewhere, which is also often linked to increasing storm intensities.
Acknowledgements
The long-term operation of the Yatir Forest Research Field Site
is supported by the Cathy Wills and Robert Lewis Program in
Environmental Science. Financial support from the JNF, KKL, Israel
Ministry of Agriculture and GLOWA-JR (Israel–Germany ministries
of Science) is gratefully acknowledged. We thank Dr. M. Sprintsin
and D. Elmowitz for help with sap flow measurements, the entire
Yatir team for technical support, and the local KKL personnel for
their cooperation.
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