Measurement and modeling of evapotranspiration of olive
(
Olea europaea
L.) orchards
F.J. Villalobos
a,b,*, F. Orgaz
a, L. Testi
a, E. Fereres
a,baInstituto de Agricultura Sostenible,CSIC,Apartado 4084,14080Cordoba, Spain bDep. Agronomı´a,Uni6ersidad Co´rdoba,Apartado 3048,14080 Cordoba, Spain
Received 19 February 1999; received in revised form 6 July 1999; accepted 4 February 2000
Abstract
Efficient irrigation management requires a good quantification of evapotranspiration. In the case of olive orchards, which are the dominant crop in vast areas of southern Europe, very little information exists on evaporation. Measurements of aerodynamic conductance and evaporation above and below an olive orchard allowed the calibration of a transpiration model of olive trees based on the Penman – Monteith equation. The model was combined with Ritchie’s soil evaporation model and tested against an independent data set, indicating its validity unless a substantial fraction of the soil surface is wetted by irrigation emitters, which is not taken into account by the model and deserves further research. Simulated crop coefficients of olive orchards in southern Spain changed during the year in response to changes in vapor pressure deficit (VPD) and evaporation from the soil surface. The average annual crop coefficient (0.62) was rather low due to the low ground cover and to the enhanced control of canopy conductance by stomatal responses to VPD. According to our results the crop coefficient will vary among locations and even among years, depending on rainfall and temperature. © 2000 Elsevier Science B.V. All rights reserved.
Keywords:Evaporation; Evapotranspiration; Olive;Olea europaeaL.; Eddy covariance
www.elsevier.com/locate/eja
1. Introduction
Olive orchards are the main component of agri-cultural systems in many semiarid regions around the Mediterranean, with more than 2 million ha in Spain and around 5 Mha in the whole European Union (Civantos, 1997). Most olive orchards are rainfed, with yields limited mainly by water
sup-ply. Traditional olive orchards in Spain have typi-cally around 100 trees per ha with ground cover rarely exceeding 25%. Modern orchards are usu-ally drip-irrigated, with 200 – 300 trees per ha and ground cover of 40 – 50%. Drip irrigation has also extended to numerous traditional orchards using groundwater of poor quality and uncertain supply.
Good irrigation management requires an accu-rate quantification of olive evapotranspiration. The most common approach to calculate evapo-transpiration (ET) has been as the product of * Corresponding author. Tel.:+34-957-499234; fax:+
34-957-499252.
E-mail address:[email protected] (F.J. Villalobos).
reference (grass) ET (ETo) by the crop coefficient
Kc=crop ET/grass ET, which depends on ground
cover and crop characteristics (FAO method, Doorenbos and Pruitt, 1977; Allen et al., 1998). In the case of olive the information on Kc is scarce
and obtained mainly from ET measurements us-ing the soil water balance (e.g. Mickelakis et al., 1994). Orgaz and Fereres (1997) reported crop coefficients from 0.45 to 0.75 in different locations which are far below the values of annual crops, typically from 1.0 to 1.2 (Doorenbos and Pruitt, 1977). The variability ofKcmeasured at different
locations makes it difficult to apply the FAO method to locations where no experimental infor-mation exists. An alternative approach to deter-mine olive ET is to calculate its two components, transpiration (Ep) and evaporation from the soil
surface (Es), independently, with an Ep model
based on the equation of Penman – Monteith (Monteith, 1965) and an Es model like the one
proposed by Ritchie (1972). The Ep model
re-quires a parameterization of canopy conductance (Gc) as a function of environmental variables (e.g.
Stewart, 1988) which has to be based on accurate measurements of evaporation at short time steps (e.g. Dolman et al., 1988).
The objectives of this work were (a) to develop a jointEs–Epmodel to determine
evapotranspira-tion of intensive irrigated olive orchards, and (b) to analyze temporal variations in the crop coeffi-cient.
2. Materials and methods
The experiments were performed in a 6 ha drip-irrigated olive (Olea europaea L.) cv. ‘Picual’ orchard located at the Agricultural Research Cen-ter of Cordoba, Spain (38°N, 4°W, altitude 110 m). Plant spacing was 6×6 m. The trees had an average leaf area index (LAI) of 1.5 in May 1996 and 1.2 in May 1997, as determined with a Plant Canopy Analyzer (model LAI-2000, Li-Cor Inc., Lincoln, NE) following the procedure of Villalo-bos et al. (1995). Mean tree height was 4 m and ground cover was 40%.
Hourly weather data were determined over an irrigated grass (Festuca arundinaceaL.) plot of 1.5 ha, located 400 m northwest of the olive orchard.
2.1. Experiment 1
Sensible (H) and latent heat flux (LE) were measured using the eddy covariance method above and below the trees from day of year (DOY) 162 (11 June) to DOY 181 (30 June), 1997. Transpiration (LEp) was computed as the
difference between LE above (ET) and LE below (Es). The fluxes were measured with a single-axis
sonic anemometer (model CA27, Campbell Scien-tific, Logan, UT) and a krypton hygrometer (model KH20, Campbell Scientific). The sensors above were set at a height of 5 m with a horizon-tal separation of 0.3 m, while the sensors below were separated 0.13 m at a height of 0.4 m. Sampling frequency was 10.67 Hz (inverse of 6/64 s). Fetch was 170 m in the west direction, which might be considered adequate as it contributed 90% of the measured fluxes according to the footprint analysis of Schuepp et al. (1990). Cor-rection to the LE fluxes due to sensible and latent flux (Webb et al., 1980), oxygen absorption (Tan-ner et al., 1993) and sensor separation (Villalobos, 1997) were applied. Fluxes were calculated and stored using a datalogger (model CR10X, Camp-bell Scientific) for 10-min periods and then aver-aged for hourly periods.
2.2. Experiment 2
Energy balance and evaporation measurements were performed from March 1996 to June 1996. LE and H were determined above the canopy as in Section 2.1. Net radiation (Rn) was measured
heat flux plates and thermocouples were located beside the net radiometers below the canopy. Measurements of Rn and G were performed at
60 s intervals while 10 min averages were stored using a datalogger (model CR10X) and then averaged for hourly periods. Net radiation above the orchard was regressed on solar radiation measured using a pyranometer (see below). Soil heat flux was regressed on net radiation below the canopy. These relationships were later used to run the evaporation model using weather data.
The performance of the eddy covariance system was assessed by regressing (LE+H) on (Rn−G)
for 24-h periods. The intercept (5.9 W m−2) and
the slope (0.88) were not different from 0 and 1, respectively, at the 0.95 probability level. The regression forced through the origin yielded a slope of 0.91 indicating an underprediction of the fluxes of less than 10% which is similar to that reported by other authors (e.g. Rochette et al., 1995) using the eddy covariance technique. Daily evaporation data were corrected by dividing by the ratio (LE+H)/(Rn−G).
2.3. Calculations
Hourly canopy conductance (Gc) for daylight
conditions was derived from the Penman – Mon-teith equation:
whereD is the slope of saturation vapor pressure on temperature,gthe psycrometric constant,rair density, Cp specific heat of air at constant
pres-sure, VPD vapor pressure deficit and Ga is
aero-dynamic conductance (see below). Absorbed net radiation (Rna) was estimated as the product ofRn
above the orchard and the fraction of intercepted photosynthetically-active radiation (PAR), which was in turn calculated using a model of PAR interception by olive orchards (Mariscal, 1998).
The sensitivity of LEpto changes inGcand Ga
where calculated according to Raupach and Finnigan (1988).
2.4. Experiment 3
The objective of this experiment was to deter-mine the relationship between aerodynamic con-ductance over the olive orchard and wind speed over a grass (reference) plot.
A three-dimensional sonic anemometer (model CSAT-3, Campbell Scientific) was installed at a 5 m height over the olive orchard at the same position where the sensors were located during measurements in 1996. The sensor was monitored at 10.7 Hz using a CR10X datalogger. The mea-surements were performed from 28/04/97 to 05/
05/97 (DOY 118-DOY 125). Fluxes were calculated and stored for 10-min periods and then averaged for hourly periods.
Simultaneous measurements of wind speed at 2 m height (Ug) using a propeller anemometer
(Young 05103) were performed over the irrigated grass plot.
Aerodynamic conductance over the olive or-chard was calculated as:
instantaneous departures from the average hori-zontal and vertical wind speed, respectively, and horizontal bar indicates an average. Empirical relationships between Ga and Ug and between u
and Uowere derived.
2.5. Transpiration model
We fitted an empirical model (e.g. Stewart, 1988) to estimate canopy conductance (Gc) in the
orchard described above as a function of irradi-ance (Rs), vapor pressure deficit (VPD) and
tem-perature (T):
Gc=Gcm f1(VPD)f2(Rs)f3(T) (3)
f1(VPD)=1−KDD 0BDBDc (4a)
f2(Rs)=
Rs(1000+KR)
1000(Rs+KR)
(5)
f3(T)=
(T–TL)(TH–T)a
(KT–TL)(TH–KT)a
(6)
wherea=(TH−KT)/(KT−TL). In order to
mini-mize the number of unknown parameters (Gcm,
KD, Dc, KR, KT, TL, TH) we assumed that the
lower and upper limiting temperatures wereTH=
40°C and TL=0°C, which are the values
sug-gested by Stewart (1988) for pine trees.
The model was combined with Ritchie (1972) model as modified by Bonachela et al. (1999) to calculate Es. The combined model was tested
against the data of Section 2.2 (spring 1996). The model was then used to calculate the daily crop coefficient (Kc, ratio of evaporation to grass ET)
of the orchard, (case A, typical of intensive plan-tations) using weather data of Cordoba from 1964 to 1986, as Kc is a commonly used parameter for
calculating irrigation requirements. The model was also applied to a traditional orchard (case B) with the same LAI and ground cover of 30%, assuming that maximum Gc was 80% of that of
the intensive orchard, due to the lower radiation interception. The value of 80% corresponds to the ratio of intercepted radiation between the two orchards. Although future work should be di-rected to the scaling-up of olive canopy conduc-tance our assumption is supported by the general
link between canopy conductance, and assimila-tion (e.g. Wang and Leuning, 1998) and the rela-tion between assimilation and radiation interception of olive trees shown by Mariscal et al. (2000).
3. Results and discussion
3.1. Radiation balance
Net radiation above the tree was not statisti-cally different from net radiation above the alley, thus data from the two net radiometers above were averaged. Hourly net radiation was regressed on solar radiation:
Rn=0.81Rs−69 (W m−2), r2=0.99 (7)
Regression of Rn against Rs for 24-h periods
had an intercept not different from 0 and a slope of 0.6.
Soil heat flux was related to Rn below the
canopy (Rnb):
G=0.17Rnb−16 (W m
−2), r2=0.74 (8)
3.2. Aerodynamic conductance
The relation between friction velocity (u) and wind speed above the olive orchard is shown in Fig. 1. There was an apparent reduction in slope for Uo greater than 1 m s−
1
, which could be due to swaying of the trees. The linear regression was:
u= −0.026+0.302Uo r 2
=0.92 (9)
with the intercept different from 0 at the 95% probability level. The regression forced through the origin yielded a slope of 0.282. From the logarithmic wind profile we may calculate:
z−d zo
=exp
ku/u
n
(10) where k is Von Karman’s constant (0.4), d zero plane displacement (m), zo roughness length (m),and z is the measurement height (m). Assuming thatd is in the interval 0.5 – 0.75h, wherehis the mean tree height (4 m) then zowould lie between
0.48 and 0.61 m. Fig. 1. Relation between friction velocity (u) and wind speed
Fig. 2. Daily course of latent heat flux measured above (total) and below (soil) an olive orchard. Data are the averages of hourly fluxes for DOY’s 171, 172 and 173, Cordoba, Spain, June 1997.
roughness elements which are concentrated in the tree canopies. Measured aerodynamic conduc-tance yielded values around four times higher than those of a nearby grass (Festuca arundinacea, L.) plot.
3.3. Soil and plant e6aporation
Fig. 2 presents the daily course of total (LE) and soil (LEs) latent heat flux measured in Section
2.1. Data correspond to averages of hourly data for DOY’s 171, 172 and 173, which are the only days when complete 24 h data are available. Both LE and LEswere close to 0 during the night, and
reached maximum values of 222 and 54 W m−2,
respectively, 2 h after solar noon. The latent heat flux corresponding to transpiration (LE−LEs)
reached a maximum of 167 W m−2, but it was
fairly constant during most of the daylight period (09:00 – 18:00 h) ranging from 131 to 167 W m−2.
Total values of evapotranspiration, soil evapo-ration and transpievapo-ration were 3.12, 0.74 and 2.38 mm per day, respectively. At the time these mea-surements were made, the soil surface was dry. Nevertheless, soil evaporation contributed 24% to the orchard ET. The ratio soil evaporation/ET would probably increase substantially when the soil is partially wetted by drip irrigation.
3.4. Canopy conductance
Fig. 3 shows the daily course of estimatedGcon
a sunny day of June 1997 (DOY 172). A typical asymmetrical pattern is seen, and it may be ex-plained by the combined effects of irradiance and VPD on stomatal aperture, similar to the response at the leaf level shown by Fereres (1984). Average
Gcincreased rapidly from sunrise to its maximum
value (8.5 mm s−1
) 4 h afterwards, and then decreased throughout the daytime period, with a rapid decline until 13:00 h and a slower change thereafter, when the air humidity deficit had al-most reached its maximum. Similar trends of Gc
have been reported for other tree species (e.g. Nothofagus, Schulze et al., 1995; Maritime pine, Gash et al., 1989).
The parameters of the Jarvis – Stewart model fitted to our data are shown in Table 1. Data for Aerodynamic conductance (m s−1) over the
orchard was regressed againstUg:
Ga=0.0053+0.0496Ug r2=0.85 (11)
with the intercept not different from 0 at the 95% probability level. The regression forced through the origin yielded a slope of 0.052, which is simi-lar to the value calculated for Pinus pinaster Ait. (0.056) of 20 m height by Gash et al. (1989). Thus, olive trees show a comparatively higher aerody-namic roughness than pines which may be due to the highly heterogeneous arrangement of the
Fig. 3. Daily course of canopy (Gc) and aerodynamic (Ga)
Table 1
Parameters for calculating canopy conductance of olive trees obtained by optimizationa
Pine
Parameter Olive
Gcmax(mm s−1) 15.4 33.4
KR(W m−2) 1194 261
0.061 0.059
KD(kg g−1)
11.8
Dc(g kg−1) 10.9
20.0 20.2
KT(°C)
aData for pine trees (Gash et al., 1989) are also shown.
that of pine. According to the Gc model, the
response of evaporation to changes in SHD shows a maximum at SHD=0.5/KD, being 8.5 g kg
−1
for olives (1.4 kPa).
Air temperature for maximum Gc, which is
equal to KT, was 20.2°C for olive. No attempts to
derive low (TL) and high (TH) temperature
thresholds were performed because of the limited range of temperature during our measurements. It is important to emphasize the limitations of this type of analysis as radiation, temperature and humidity are not varied independently, and more important, there is a direct dependence between calculatedGcand the environmental variables (via
the Penman – Monteith equation), which means that this type of model ofGcis statistically
incor-rect. However, most of our current knowledge on canopy conductance for different types of vegeta-tion is based on the same model which has been shown adequate for predicting evaporation in many cases (e.g. Dolman et al., 1988). Neverthe-less the overall agreement of our olive data with previous studies on pine indicate that olive Gc
responds to environmental conditions very much like coniferous forests despite differences in both height and LAI. Further research is needed to determine the effect of LAI and soil water deficit on olive Gc.
The relative sensitivity of LEpto changes in Gc
was large (Fig. 4), with values around 0.9 during most of the daytime period, indicating that changes in Gc will cause changes of the same
magnitude in olive evaporation. On the other hand, the sensitivity of LEp to changes in Ga,
which is associated with wind speed, was ex-tremely low with absolute values typically below 0.03. These sensitivities indicate that accurate pre-diction of olive evaporation requires a sound model of Gc(a function of irradiance, air
humid-ity and temperature) and that wind speed will play a minor role in determining LEp.
3.5. Model test
Calculated and measured daily ET data of the orchard in spring 1996 (Section 2.2) are shown in Fig. 5. This data set was used to derive the relationships between net and solar radiation and pine (Pinus pinaster Ait.) trees determined by
Gash et al. (1989) for Les Landes forest are shown for comparison. Maximum Gc was 15.4
mm s−1, which would correspond to an average
0-deficit stomatal conductance of ca. 13 mm s−1
(assuming that gs scales-up linearly with LAI),
which is close to maximum values of stomatal conductance observed by Orgaz (pers. commun.) in this orchard. Maximum values ofGcare lower
for olive trees than for pine (Table 1) which may be partly explained by a lower LAI (1.2 vs. 2.3). The response ofGcto radiation indicates a slower
opening of olive stomata as radiation increases when compared with pine. For instance, 75% of maximum gs will be attained at radiation
intensi-ties of 620 and 383 W m−2, for olive and pine,
respectively. On the other hand, the response of oliveGcto specific humidity deficit was similar to
Fig. 4. Daily course of sensitivity of evaporation to canopy ((dLE/LE)/(dGc/Gc)) and to aerodynamic conductance ((dLE/
Fig. 5. Calculated and measured daily ET of the olive orchard, Cordoba, Spain, 1996.
tween 5 and 10%, which is extremely wide when compared with commercial orchards (1 – 5%). An-other possible factor could have been an increase in Gc when irrigation started, although rainfall
amount during this spring was probably enough to avoid any water stress. These results are en-couraging in terms of model validity for condi-tions of uniformly wetted soil. The under-prediction shown after the start of drip irrigation may be associated with evaporation from the wet bulbs; the study of this association deserves fur-ther research.
3.6. Orchard ET and crop coefficient
The annual course of simulated average decadal ET is presented in Fig. 6. Minimum values are close to 1 mm per day during the winter, while maximum values around 3.5 mm per day occurred in June and July. The differences between the two orchards are negligible in winter and increase as ET increases, due to changes in the relative im-portance of Es(Fig. 7), which is the main
compo-nent of ET during the winter and decreases to less than 10% of ET during the summer. This is caused by the typical Mediterranean pattern of rainfall in Cordoba, with a wet season from Octo-ber to April and a dry season during the summer. Average annual ET’s were 855 and 758 mm, for orchard A and B, respectively, while average an-soil heat flux andRnbelow the canopy, thus it is
not strictly independent, although it is so in terms of the transpiration – evaporation model.
Measured ET ranged from 2 to 5.5 mm per day, while reference (grass) ET varied from 2.7 to 8.5 mm per day. The agreement between observed and measured ET was good up to DOY 145 (24 May), when drip irrigation was started. From then on measured ET exceeded estimated ET by 0.5 – 1 mm per day. This difference might be the contribution of evaporation from the soil wetted by the emitters, which was neither included in the model nor measured. The wetted area was
be-Fig. 6. Simulated average decadal ET of olive orchards of LAI=1.4 and 40 (A) or 30% ground cover (B) at Cordoba (Spain), 1964 – 1986. Vertical bars represent the S.D.
Fig. 7. Simulated average decadal soil evaporation (Es) of olive
Fig. 8. Simulated average decadal crop coefficient (ET/grass ET=ETo) of olive orchards of LAI=1.4 and 40 (A) or 30%
ground cover (B) at Cordoba (Spain), 1964 – 1986. Vertical bars represent the S.D.
cases. Therefore, accurate prediction of Esis also
required to estimate ET of olive orchards. Crop coefficients varied substantially through the year with maximum values close to one during winter (Fig. 8) and minimum values around 0.4 in August. The variability in decadal Kc’s also
de-creased from winter to summer. The high Kc in
winter is the result of enhanced soil evaporation due to rainfall, which also explains the greater variability of theKc. As the season progressed, the
probability of rainfall decreased and so did Es,
and consequently, theKcand its variability. Apart
from the decrease in Es from winter to summer,
increasing VPD from spring to summer and the reduction in the fraction of intercepted radiation led to a relative minimum in the ratio Ep/ETo in
the summer (Fig. 9).
For annual values the crop coefficient was 0.62 for case A and 0.55 for case B, well below annual crop maximum Kc. The variation of the olive Kc
throughout the year and its dependence on VPD, intercepted radiation and Es, and thus, on the
rainfall pattern, clearly indicates the difficulty in proposing a unique Kc value valid for different
locations. Even in a given area, interannual vari-ability in rainfall dates and amount will lead to changes in both winter and spring Kc.
4. Conclusion
Measurements of evaporation above and below an olive orchard and aerodynamic conductance allowed the calibration of a transpiration model of olive trees. The model was combined with a soil evaporation model and tested against an inde-pendent data set, indicating a fair performance unless a substantial fraction of the soil surface is wetted by irrigation emitters, which is not taken into account by the model. Crop coefficients of olive orchards in southern Spain change during the year in response to changes in net radiation, air temperature, windspeed, VPD and evapora-tion from the soil surface. The average crop co-efficient is rather low due to the low ground cover and to the enhanced control of canopy conduc-tance by stomatal responses to VPD. These results indicate that estimates of olive water requirements nual ETowas 1373 mm. Annual values ofEswere
the same for the two cases (290 and 293 mm) which might be explained by the conservative nature of the Es process, a higher ground cover
(case A) leads to lower Es during the first stage
(energy limited) after wetting of the soil, leading to a slower drying of the soil surface which in turn keeps a higher evaporation rate for a longer period. The contribution ofEs to annual ET was
higher in the traditional (39%) than in the inten-sive orchard (34%), but it was substantial in both
Fig. 9. Simulated average decadal transpiration coefficient (Ep/grass ET=ETo) of olive orchards of LAI=1.4 and 40 (A)
can not be assessed accurately with the crop co-efficient method, thus an articulate approach, like the one presented here, is needed.
Acknowledgements
We would like to thank Dr Miguel Pastor for providing access to the experimental orchard. Dr Marcello Donatelli and an anonymous reviewer contributed substantially to improving the manuscript. This work was supported by grants HID96-1295-CO4-01 of Programa Nacional de Recursos Hidricos and OLI96-2212 of Programa de Aceite de Oliva Comision Interministerial de Ciencia y Tecnologia, Spain. LT held a fellowship from Fundacion del Olivar de la Provincia de Jaen.
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