Water requirements of olive orchards: I simulation of daily evapotranspiration for scenario analysis

Transcription

1 Irrig Sci (2006) 24: DOI /s y IRRIGATION OF FRUIT TREES AND VINES L. Testi Æ F. J. Villalobos Æ F. Orgaz Æ E. Fereres Water requirements of olive orchards: I simulation of daily evapotranspiration for scenario analysis Published online: 14 October 2005 Ó Springer-Verlag 2005 Abstract Water requirements of olive orchards are difficult to calculate, since they are influenced by heterogeneous factors such as age, planting density and irrigation systems. Here we propose a model of olive water requirements, capable of separately calculating transpiration (E p ), intercepted rainfall evaporation (E pd ) and soil evaporation (E s ) from the wet and dry fraction of the soil surface under localized irrigation. The model accounts for the effects of canopy dimension on E p and of the wetted soil surface fraction on E s. The model was tested against actual measurements of olive evapotranspiration (ET) obtained by the eddy covariance technique in a developing olive orchard during 3 years. The predicted ET and crop coefficients showed good agreement with the measured data. The model was then used to simulate the average water requirements of two mature orchards using 20-year meteorological datasets of Cordoba (Spain) and Fresno (CA, USA). Average annual ET of a 300 trees ha 1 orchard at Cordoba was 1,025 mm, while the same orchard at Fresno had an average ET of 927 mm. Transpiration losses were 602 mm at Cordoba and 612 mm at Fresno. Evaporation from the soil can have a large effect on olive ET; thus, olive crop coefficients (K c ) are very sensitive to the rainfall regime. Introduction Communicated by E. Christen L. Testi (&) Æ F. J. Villalobos Æ F. Orgaz Æ E. Fereres Instituto de Agricultura Sostenible, CSIC, Apartado 4084, Cordoba, Spain ag2lucat@uco.es Tel.: Fax: F. J. Villalobos Æ E. Fereres Department of Agronomìa, University of Co rdoba, Apartado 3048, Cordoba, Spain Olive orchards occupy 8.3 Mha in the world, of which more than 90% is concentrated around the Mediterranean basin, with about 5 Mha in the European Union (FAOSTAT 2003), where summer drought severely limits yield. Despite its importance, there is limited understanding of the behavior of this tree species. This may be attributed to the minimal research efforts in traditionally producing countries and to the complex behavior of olive, a perennial and evergreen species. Traditionally raised under rain-fed conditions, the quest for increased productivity has led to an increase in the irrigated area of olives, both in traditional and new growing areas, and the need for information on irrigation water requirements now has a high priority among the list of olive research topics. Many traditional, rain-fed orchards are being converted to irrigation. Tree density and ground cover is low in such orchards, in contrast with the new highdensity plantings that are taking place both in traditional and new producing countries due to the rising demand for olive oil. As a consequence, irrigated olive orchards today show large variations in tree dimensions, canopy architecture and ground cover. This transformation of orchards from rain-fed to irrigation is taking place in areas of chronic water shortages, and irrigation supplies are often well below the potential requirements. Determination of the water requirements for each situation, thus, becomes critical for the efficient use of water in olive irrigation. The traditional empirical determination of crop water requirements (by water or energy balance measurements) would take decades of experimentation if it has to be carried out in many different olive grove situations. An alternative approach to the problem, given the site specificity of both environmental and management aspects, involves three steps: (1) understanding the soilplant-atmosphere system; (2) developing a simulation model of the physical and physiological processes; and, (3) using the model to simulate the process of crop water use by generating crop water requirements for a representative number of scenarios. Traditionally, most models of crop water use have jointly computed the processes of evaporation from soil

2 70 (E s ) and of plant transpiration (E p ) as an evapotranspiration (ET) term. In the case of the olive, an evergreen species in a Mediterranean-type climate, E s could be an important component of ET and it may be desirable to compute E s and E p separately. In fact, Villalobos et al. (2000) calculated ET as the sum of E p and E s for an olive orchard. Transpiration was calculated using the Penman-Monteith equation (Monteith 1965), which had the canopy conductance (G c ) parameterized according to the model of Jarvis (1976), using E p measurements taken in late spring on an orchard with 40% ground cover at Cordoba, Spain (Villalobos et al. 2000). Later, the parameterization of G c was extended to young orchards from planting up to a leaf area index (LAI) of 1.0 (Testi et al. 2005, in press). Bonachela et al. (1999) proposed a model for calculating E s beneath olive orchards, which was later extended to calculate E s from the zones wetted by the emitters under localized irrigation (Bonachela et al. 2001). Orgaz et al. (submitted) have proposed an alternative, olive-specific, G c model for use in conjunction with the Penman-Monteith equation for the calculation of E p in olive. It consists of a functional model that uses canopy-intercepted photosynthetically active radiation (PAR) and average daytime temperature as the two driving variables for calculating a daily bulk canopy conductance G c. The model correctly simulated olive E p by taking into account both the impact of ground cover and the seasonal variations in stomatal conductance that have been observed in olive trees (Moriana et al. 2002b). Intercepted PAR by olive orchards is calculated using the model of Mariscal et al. (2000a). The same authors obtained the radiation-use efficiency (RUE) for young olive plantations (Mariscal et al. 2000b). Go mez et al. (2001) studied rainfall interception and evaporation from olive canopies, and proposed a model of the processes. All the efforts described above have led to the development of a model for the calculation of olive water requirements which may be used for the simulation of irrigation strategies. This work presents a model of olive orchard ET that computes E p and E s (both from area wetted by the emitters and the rest of the soil), and direct evaporation from the canopy wetted by rain (E pd ), all as a function of tree canopy architecture and planting density. The model is then used to simulate orchard water use in two different locations for scenario analysis and to assess the impact of climate on olive irrigation requirements. Materials and methods General model description The model runs on a daily time step, and is composed of a number of sub-models that resemble the different physical and physiological processes relevant to olive water use and their interactions. The meteorological input data needed are daily values of the following variables (standard over grass): maximum (T M ) and minimum (T m ) air temperatures ( C), average vapor pressure (e avg - kpa), solar radiation (R s -MJ m 2 day 1 ) and rainfall (P - mm day 1 ). The irrigation amounts (mm day 1 ) can be either input or calculated dynamically, as a function of the irrigation strategy determined a priori. The input data defining orchard characteristics are: planting density D p (trees ha 1 ), average tree volume V c (m 3 tree 1 ) and average soil surface fraction wetted by irrigation f ws (non-dimensional). The soil input parameters are (for every soil layer, customizable in number and thickness): drained water content upper limit (m 3 m 3 ), lower limit (m 3 m 3 ) and water content at saturation. The runoff, drainage and water flow sub-models are similar to the CERES-type models (Jones and Kiniry 1986), but run independently and separately on the two soil surface fractions (dry or wetted by localized irrigation). The irrigation routine permits either the direct input of the actual daily irrigation amounts (for real time water balance and scheduling) or the definition of an irrigation strategy for predictive calculations. The E s routine uses the models of Bonachela et al. (1999, 2001), which separately calculate E s from the dry and wet soil areas. These models estimate E s with a modified Penman-FAO equation for stage-one evaporation, and the model of Ritchie (1972) for the soil-limited evaporation stage. For the wetted area, microadvection effects are taken into account (Bonachela et al. 2001). The routine for the calculation of intercepted rainfall is based on Go mez et al. (2001), simplified for daily time step calculations. Water intercepted by the canopy evaporates directly at a rate calculated with the Penman-Monteith equation, assuming a null canopy resistance. The aerodynamic resistance is calculated with the model proposed by Raupach (1994), parameterized and validated specifically for olive orchards following Verhoef et al. (1997). Direct wet foliage evaporation is discounted from E p until the intercepted water is completely lost. Transpiration Plant transpiration (E p ) is calculated with the Penman- Monteith equation using a specific bulk canopy conductance (G c ) model. This model is conceptually based on the proportionality of G c to carbon assimilation, A, and on a function of vapor pressure deficit D (Leuning, 1995). Carbon assimilation is directly dependent on intercepted PAR and RUE (Monteith, 1977), while the D function is linearly related to the mean daytime temperature T d (Orgaz et al. submitted). The olive daily bulk G c (in unstressed conditions) is thus given by: G c ¼ QR sp 1; 000 D f ð T dþ ðmm s 1 Þ; ð1þ where R sp is the mean daytime PAR irradiance (W m 2 ), D is the mean daytime vapor pressure deficit (kpa) and

3 71 f ðt d Þ¼2:736 T d 8:71; ð2þ Q is the fraction of PAR intercepted by the canopy (nondimensional), which lies between two boundary values: (a) the fraction of intercepted PAR on clear sky days (Q dtot, non-dimensional) and (b) the fraction of intercepted PAR on overcast days (Q dd non-dimensional): Q dtot ¼ 1 e k 1v ; ð3þ k 1 ¼ m 0:0321L d þ 0:16 þ 0:115L d cos h n ; ð4þ Q dd ¼ 1 e k 2v ; ð5þ ð k 2 ¼ 0:52 0: D p 0:76 e 1:25L dþ ð6þ where h n = the zenith solar angle at noon (function of day of the year and latitude), D p is the tree density (trees ha 1 ) and m is given in Table 1. L d is the leaf area density (m 2 m 3 ), which changes in olive with canopy volume (Villalobos et al. 1995; Mariscal et al. 2000a) in the domain 1.2 L d 2: L d ¼ 2 ½v\0:5Š; ð7þ 0:8 v 0:5 L d ¼ 2 ð Þ ½v > 0:5Š; ð8þ 1:5 where v is the canopy volume per unit ground area (m 3 m 2 ). In Eq. 1, Q is found by interpolating the results of Eqs. 3 and 5, depending on the atmospheric transmissivity (s atm, non-dimensional), defined as the ratio between the actual (R s, input) and the extraterrestrial (R ext, function of day of year and latitude) solar radiation, assuming that s atm =0.8 and Q=Q dtot in clear sky conditions and that s atm =0.2 and Q=Q dd in completely overcast days. Model validation The performance of the olive ET model was tested against actual measurements of olive ET which were collected during three years ( ). The experiment, fully described in Testi et al. (2004), was conducted in a 4-ha flat growing olive orchard planted in the Table 1 Values of the m term of Eq. 4 in different tree densities of plantation (D p trees ha 1 ) m D p (trees ha 1 ) v v > 400 In the lower densities, m is function of the canopy volume per unit ground area v, (m 3 m 2 ) CIFA research center in Cordoba, Spain (37.8 N, 4.8 W, altitude 110 m). The orchard was planted in 1997 with the cv. Arbequino, spaced m; it was irrigated by drip and managed to avoid water stress at all times. The canopy dimensions were periodically measured in a set of ten subplots (eight trees each). The tree canopy volume (V c ) increased from 0.15 to 12.5 m 3 tree 1 and the ground cover fraction (F gc ) increased from 0.01 to 0.26 during the 3 years. The leaf area index (LAI, m 2 m 2 ) also increased from 0.01 to The latent (ke) and sensible (H) heat fluxes were measured by the eddy covariance technique during the 3 years (Swinbank 1951). A sonic anemometer (model CA27, Campbell Scientific, Logan, USA), a krypton hygrometer (model KH20, Campbell Scientific, Logan, USA) and a fast-response thermocouple (assembled in the IAS-CSIC laboratory) were mounted on a 6-m tower, located in a point of the orchard providing a fetch of 170 m along the dominant wind direction. The devices were measuring the vertical wind velocity (w), the water vapor density (q v ) and the air temperature (T a ), at a frequency of Hz. A datalogger (model CR10X, Campbell Scientific, Logan, USA) was used to calculate and store the means, variances and covariances H ¼ qc p w 0 T 0 a ; ke ¼ k w 0 q v0 at 10-min intervals, where q is air density, C p is the specific heat of air at constant pressure and k is the latent heat of vaporization of water (the prime symbol denotes deviation from the 10-min mean and the overbar stands for 10-min average). Net radiation (R n ) was measured using two net radiometers (model Q7, REBS, Seattle, USA), placed over the two points of maximum and minimum ground cover (one above a tree and one above the interception of the diagonals of the rectangle formed by four trees). The raw soil heat flux was measured by three heat flux plates (model HFT3, REBS, Seattle, USA), one placed in the zone wetted by the emitters and two in different locations of radiation reaching the soil. The spatial averaging of G was weighted with F gc. More details on the calculations and corrections performed are given in Testi et al. (2004) The K c was calculated on a daily basis as ET/ET 0 and the value was averaged to 15-day periods. ET 0 was calculated using the standard FAO Penman-Monteith equation (Allen et al. 1998) For the validation tests, the complete water balance model was run using the actual meteorological data of the three years, which were collected by an automatic weather station (Campbell Scientific, Logan, USA) located 400 m away from the orchard, and the measured orchard characteristics. Simulations Mature olive water requirements were simulated with 20 years ( ) of meteorological daily data for Cordoba (Spain) and Fresno (CA, USA). Cordoba, (37.8 N, 4.8 W, altitude 110 m) is a representative site of the main olive oil production area in Spain. Fresno

4 72 (36.8 N, W, altitude 102 m) is located within the olive production area of California. The climate of the two sites differs mainly in annual rainfall: 592 mm in Cordoba and 306 mm in Fresno. The monthly climographs for the two locations are shown in Fig. 1. The reference evapotranspiration (ET 0 ) was calculated on a daily basis with the standard FAO Penman-Monteith equation (Allen et al. 1998): the yearly averages (calculated with the 20-year datasets used in the simulations) were 1,333 mm in Cordoba and 1,476 in Fresno. All the simulations shared the same soil type, with the following characteristics (for all soil layers): drained soil water content upper limit = 0.24 m 3 m 3, lower limit=0.08 m 3 m 3 and water content at saturation=0.34 m 3 m 3. The soil parameters relevant to the E s calculation routine (Ritchie, 1972) were U=12 mm and a=4.9 day 0.5. The soil depth was taken as 1 m, divided into ten layers of 0.1 m. The model s irrigation routine was set to irrigate before the depletion of 30% of the available water, thus avoiding water stress detrimental to yield. The irrigation occurred if ET i P i >0, where ET i =E s + E p (mm) and P i is the rainfall amount (mm) of the day i. The amount of irrigation applied on day i was set to equal (ET i P i ). In both locations irrigation was not performed (if necessary) during December and January, when the olive is considered dormant. The model was used to simulate the water balance and the crop coefficient (K c ) for two hypothetical case studies. Two typical olive orchards scenarios were chosen: one (case A) representative of the traditional planting (100 trees ha 1 at m spacing), which was converted to irrigation. Tree canopy volume (V c ) was assumed to be 120 m 3. The second (case B) is an intensive orchard, typical of modern plantations: 300 trees ha 1 and individual tree canopy volume of 50 m 3. Fig. 1 Monthly climographs of the simulation sites. The gray band is the minimum maximum temperature range ( C), the vertical bars represent the monthly rainfall (mm). The source is the same 20-year ( ) meteorological dataset used for the simulations

5 73 A fraction of soil wetted by the irrigation system (f ws )of 0.1 was assumed in both cases. Results Validation of the model against actual measurements Figure 2 shows a comparison between the measured daily ET of Testi et al. (2004) against the predicted daily ET (15-day averages) for the years 1998, 1999 and 2000, respectively. Also in Fig. 2, the corresponding crop coefficients are presented. The model simulated well both the ET and K c throughout a wide range of LAI values of the orchard; in July 1998 (Fig. 2a, d) the LAI was 0.09, while in September 2000 (Fig. 2c, f) it reached 1.0. The few measurements available in wet soil conditions, when the ET and K c increased due to a large E s contribution (see the end of 1998-Fig. 2d or September 1999-Fig. 2b, e), were also very well simulated by the model, indicating that the performance of the soil evaporation sub-model Fig. 2 The 15-day averages of daily ET (plots a c) and K c (plots d f) in the years 1998 (a, d), 1999 (b, e) and 2000 (c, f) for a growing olive orchard. The circles are the values measured by Testi et al. (2004), while the squares are the values predicted by the model

6 74 was good. During the summer, the model underestimated ET slightly for the three years as discussed below. Case studies The results of the simulation for the two ideal case studies in Cordoba are presented in Table 2. Case 2 shows a higher ET due (mainly) to a difference in E p ; the difference in E s is very small, although the orchard of case 1 (F gc =0.3) covers considerably less ground surface than that of case 2 (F gc =0.5). This difference in F gc explains that the intercepted P is around 40% higher in case 2 than in case 1, which also contributes to the difference in ET. The average annual K c was 0.70 for case 1 and 0.77 for case 2, showing a small variability among years. The same was found for the monthly K c of July, (0.57 and 0.64 for case 1 and 2, respectively) which shows quantitatively the same difference as the annual K c between the cases. The same crop scenarios were simulated for the climatic conditions of Fresno, and are presented in Table 3. The total ET is lower than in Cordoba, because of a smaller E s component due to less annual rainfall in Fresno. The annual average K c is 0.57 in case 1 and 0.63 in case 2 (both lower than in Cordoba). The K c for the month of July is also lower than in Cordoba: the values are 0.49 for the case 1 and 0.55 in case 2. The variation of the calculated monthly K c s, during the average year, for the two cases in the two locations is presented in Fig. 3. The K c is very high at the beginning of the year in both locations and cases, due to high rainfall frequency. The difference between locations is more pronounced in autumn, because rainfall in Fresno is much less than in Cordoba in the fall (see Fig. 1). During mid-summer, the K c differences between locations decreased to values in the range of 0.05 (Fig. 3). Discussion The model simulated well (Fig. 2a c) the ET measured by Testi et al. (2004), correctly interpreting the changes in ET as orchard LAI increased. This suggests that the bulk canopy conductance submodel (Eq. 1), which was developed for a mature orchard (Orgaz et al. submitted), is adequate for properly scaling up the transpiration with orchard size. The changes of ET along the year were also well described by the model, with a small underestimation during the summer. This discrepancy (around 10% of the actual ET of the months of June and July in 1999 and 2000) seems to be associated with E p as this is the major olive ET component during summer. A probable explanation for that underestimation in E p by the model is the canopy conductance differences between the orchard used in the calibration of the canopy conductance model and the young one used for the validation of the model here. Equation 1 was calibrated in a mature orchard cv. Picual (Orgaz et al. submitted) that had stomatal conductance values, measured by Moriana and Fereres (2002a), which were about 30% lower than those measured by Moriana et al. (2002b) in the young orchard used in the validation here; both measurements were performed under well-watered conditions. It is not known if the higher stomatal conductance observed in the Arbequino orchard is associated with the cultivar or with tree age. Further research is needed to incorporate these varietal or age effects in the olive ET model. The annual K c curve of olive has an inverted pattern with respect to the typical K c curves of herbaceous crops (see Fig. 2d f and Fig. 3). This is due to the combined effects of seasonality of the Mediterranean precipitation regime, the incomplete soil cover and the evergreen nature of the olive. During the winter, olive ET is mostly due to E s, which is weakly dependent on ground cover; when the rainy season ends, E s drops to low values, and E p dominates the ET process. The combination of E p and E s increases the K c value to 1 or more during winter. Later, the Kc decreases to lower but stable values during the summer, which depend on canopy size (Testi et al. 2004). The K c of olive during winter periods with high rainfall frequency is further increased by the direct evaporation of the water intercepted by the canopy, and this process is accounted for in model calculations. Experiments performed long ago (Rutter 1963, Helvey Table 2 Results of the water balance simulation of the two olive orchard case studies in Cordoba, Spain. Averages of 20 years ( ) Variable Units Case 1: D p =100 trees ha 1, V c =120 m 3 Case 2: D p =300 trees ha 1, V c =50 m 3 Average r First quartile Third quartile Average r First quartile Third quartile E p (mm year 1 ) E s (mm year 1 ) Intercepted P (mm year 1 ) ET (mm year 1 ) P (mm year 1 ) Annual K c (ratio) July K c (ratio) The standard deviation, r, and the values for the first and third quartiles are also shown D p = planting density; V c = tree canopy volume; E p = transpiration; E s = evaporation from the soil; P = precipitation; ET = evapotranspiration; K c = crop coefficient. In both cases, the fraction of soil wetted by the emitters (f ws ) was assumed to be 0.1 (10%)

7 75 Fig. 3 Variation of the simulated monthly K c during the year for the two case studies in the two locations. K c s are calculated as SET/SET 0 (daily values) for every month. Averages of 20 years ( ) 1967) showed that the water intercepted by forest canopies evaporates at a rate that largely exceed the potential ET rate. Monteith (1965) demonstrated that crops having aerodynamic resistance of an order of magnitude less than canopy resistance like olive can evaporate the intercepted water three to five times the potential transpiration rate. Maintaining foliage during winter, olive groves have a significant canopy water storage capacity that can sustain this rate of E pd for relatively long time before the canopy dries out: the combination of E pd, E s and the much smaller E p can result in very large K c values (Wallace 1995). In the same orchard described here for model validation, during January 2001, Villalobos measured an average K c of 1.54 (with peak daily values of 2.1) using an eddy covariance energy balance system with a water-resistant anemometer (data not published). These large K c values are not in contrast with energy balance limitations during winter, as ET 0 is low; a small energy supply (for example, from canopy or soil cooling) may allow increasing the K c by The measured K c data presented in Fig. 2d f do not include periods of frequent rainfall, as the eddy covariance system used had difficulties when applied to long periods in wet conditions. The rise in K c due to soil wetting is nevertheless evident during the autumns of 1998 (Fig. 2d) and 1999 (Fig. 2e), and this is well simulated by the model. The impact of the summer ET underestimation on the K c s of June and July is very small (less than 0.04). The comparison between the case studies simulated with the model for Cordoba (Table 2) and Fresno (Table 3) allows some generalizations on olive water use in relation to climate and ground cover. In Cordoba, the annual values of E s are remarkably high, even though both cases represent mature orchards with reasonably high ground cover. Approximately 40% and 35% of the annual orchard ET is caused by direct soil evaporation in case 1 and 2, respectively. This is in accordance with the results of Villalobos et al. (2000), who found a 24% contribution of E s to ET in dry soil conditions in an olive orchard with F gc =0.4. The contribution to annual ET of E s from the emitters wet spots is 11 and 10% of total ET in cases 1 and 2, respectively. In the conditions of Fresno, E s is a lower fraction of the ET due to the different precipitation regime; E s becomes 34 and 29% of annual ET in cases 1 and 2, respectively, while E s from the emitters wet spots was 15 and 13% of the annual ET. In both cases, the effect of ground cover on E s (comparing case 1 with case 2) is very small. E p is influenced by ground cover as expected, and in a similar way in the two sites: in fact, the values of E p for the same case are similar in the two climates. The difference in annual ET and K c between the two climates is mainly caused by the rainfall regime. Table 3 Results of the water balance simulation of the two olive orchard case studies in Fresno, California. Averages of 20 years ( ). In both cases, the fraction of soil wetted by the emitters (f ws ) was assumed to be 0.1 (10%). Other symbols as in Table 2 Variable Units Case 1 D p =100 trees ha 1 V c =120 m 3 Case 2 D p =300 trees ha 1 V c =50 m 3 Average r First quartile Third quartile Average r First quartile Third quartile E p (mm year 1 ) E s (mm year 1 ) Intercepted P (mm year 1 ) ET (mm year 1 ) P (mm year 1 ) Annual K c (ratio) July K c (ratio)

8 76 The differences in July K c between locations require an explanation, because they cannot be caused by differences in rainfall, as rainfall in July is very unusual in both locations. The model predicted that olive ET in July was similar in both locations, even though the ET 0 of Fresno is higher in July (Fig. 1), thus the lower K c. The impact of the drier climate of Fresno on the calculations of olive canopy conductance may explain this divergence between sites in olive summer K c s that, certainly, deserves further research. The model predicts very large K c s during winter months (Fig. 3), because it accounts for E pd in the calculation of ET. The effect of E pd on K c can be dramatic in frequently wetted tree canopies, but these large K c are of limited relevance for the irrigation of tree crops in Mediterranean-type climates. In fact, the low ET 0 during winter relative to the high summer demands reduce the importance to these large K c values, as winter ET represents a small fraction of the total water requirements. Furthermore, in many irrigated olive-growing areas, the soil is often at field capacity when the rainy season ends, or at least is considered so for current water balance purposes. The standard crop water requirements model, ET= ET 0 Æ K c which was widely adopted after the FAO handbook of Doorenbos and Pruitt (1977) was published, has proven its robustness and applicability worldwide. However, as progress is made in understanding the ET processes, it is possible to develop more mechanistic models that reflect better the impact on the crop water requirements of: (a) the specific crop physiological responses; (b) the rainfall regime and; (c) the irrigation method and management. It remains to be seen how these, more complex models, perform in routine use under field conditions or whether they need to be simplified for their use in the real world. In conclusion, the model presented in this work effectively calculates olive ET in response to the main soil, climate and canopy conditions that influence it, leading to accurate predictions of orchard water use. This model represents an improvement over others that empirically combine E p and the E s from various sources into a single estimate of orchard ET. The model is also a useful tool in scenario simulations of olive water use and provides the basis to explore the impact of location, tree canopy and planting density on olive irrigation requirements. Acknowledgements This work was funded by grants OLI of Programa Especı fico Movilizador del Aceite de Oliva (Comisio n Interministerial de Ciencia y Tecnologı a - CICYT) and CAO00-02 of Junta de Andalucı a, Spain. 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