Evapotranspiration, crop coefficients, and physiological responses of citrus trees in semi-arid climatic conditions

Agricultural Water Management 227 (2020) 105838

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Evapotranspiration, crop coefficients, and physiological responses of citrus trees in semi-arid climatic conditions

T

Sajad Jamshidia,b, Shahrokh Zand-Parsab,⁎, Ali Akbar Kamgar-Haghighib, Ali Reza Shahsavarc, Dev Niyogia,d a

Department of Agronomy- Crops, Soils, and Water Sciences, Purdue University, West Lafayette, IN, 47907, USA Department of Water Engineering, School of Agriculture, Shiraz University, Shiraz, 65186-71441, Iran c Department of Horticultural Science, School of Agriculture, Shiraz University, Shiraz, 65186-71441, Iran d Department of Earth, Atmosphere, Planetary, and Science, Purdue University, West Lafayette, IN, 47907, USA b

ARTICLE INFO

ABSTRACT

Keywords: Crop coefficients Evapotranspiration Leaf water potential Stomatal conductance Washington navel Orange Water productivity

Improved understanding of crop water use is vital for aiding water-saving and sustainable production practices, particularly for water-restricted regions, where limited observations exist. This study investigated the standard evapotranspiration and crop coefficients (single and dual) for drip-irrigated mature orange trees (Citrus sinensis L. cv. Washington navel) for the semi-arid climate of southern Iran. Forty-five Washington navel trees in a cleancultivated orchard were subjected to five irrigation levels (100%, 90%, 75%, 60%, and 45% of reference evapotranspiration) for two consecutive seasons (2016, 2017). Crop physiological responses including stomatal conductance (gs) and leaf water potential (Ψleaf) were measured, and the agronomic effects in terms of plant yield (i.e., fruit number and weight) and evapotranspiration water productivity (WPET) were evaluated. The average standard evapotranspiration rate was measured as 5.11 mm day−1 with the seasonal amount of 1814 mm (partitioned as 84.9–86.5% of transpiration and 13.5–15.1% evaporation), and the crop coefficient ranged from 0.67 in January to 0.96 in June. During periods of high evaporative demand, the non-stressed and moderately stressed trees (100%, 90%, 75% treatments) reduced their gs (0.107–0.075 mol m-2 s−1) to maintain a relatively constant Ψleaf, whereas in severely stressed trees (60% and 45% treatments), Ψleaf significantly reduced when gs dropped below 0.067-0.077 mol m−2 s−1. Considering the current water deficiency in the region, irrigating at 60% ETo (˜67–70% standard crop demand) is recommended for sustainable citrus production.

1. Introduction Improving the irrigation water management strategies in semi-arid regions requires proper knowledge about crop water use and the agronomic responses under water stress conditions. This requirement is even more determinant in citrus orchards in places such as southern Iran, where few in-situ experiences exist (Jamshidi et al., 2019). World citrus production has increased from 61.1 million tons (MT) in 1990 to 99.5 MT in 2017 (FAOSTAT, 2017). Asia contributes to more than 40% of the total citrus production covering 1.8 million hectares (Mha) of cultivated lands (FAOSTAT, 2017). In Iran, citrus orchards cover more than 0.24 Mha of agricultural lands, and over 4.3 MT of fruits are produced annually (Ahmadi et al., 2015). The climatic condition of southern Iran and similar semi-arid regions facing rain scarcity as well as high summer temperatures necessitates the provision of irrigation for enhancing agriculture production. The irrigation requirements have to

⁎

be optimized in the context of limited water resources in the region. Therefore, designing an optimal deficit irrigation strategy to maximize the water savings and minimize the yield losses can alleviate the current orchards vulnerability to water scarcity. From a hydrological perspective, in-situ measurements of standard crop evapotranspiration (ETc) and crop coefficient estimations (Kc; the ratio of ETc to reference evapotranspiration) are the primary steps for improving the crop - water productivity in water-scarce scenarios (De Medeiros et al., 2005; Er-Raki et al., 2008). Several studies have assessed crop water requirement and obtained single and dual forms of crop coefficients (Kc, Kcb). Some examples focusing on the study domain of southern Iran are (Dastranj and Sepaskhah, 2019; Kamali and ZandParsa, 2017; Mehrabi and Sepaskhah, 2018; Mosaffa and Sepaskhah, 2019); however, fruit trees and citrus, in particular, have received limited attention. The FAO recommended Kc values for clean cultivated mature citrus trees, providing 70% of the ground cover, range from

Corresponding author at: Department of Water Engineering, School of Agriculture, Shiraz University, Shiraz, 65186-71441, Iran. E-mail addresses: [email protected], [email protected] (S. Zand-Parsa).

https://doi.org/10.1016/j.agwat.2019.105838 Received 24 June 2019; Received in revised form 28 September 2019; Accepted 28 September 2019 0378-3774/ © 2019 Published by Elsevier B.V.

Agricultural Water Management 227 (2020) 105838

0.79 1.25 0.85 1.00 0.74 0.90 1.02 0.84 0.74 0.50 0.80

0.82 0.94 0.85 0.87 0.84 0.90 1.07 0.86 1.06 0.40 0.80

0.79 0.91 0.80 0.77 0.73 0.90 1.70 0.95 1.15 —— 0.80

0.72 1.00 0.80 0.76 0.63 0.90 1.79 0.61 1.12 —— 0.90

0.65 to 0.75 (Table 1). However, through a number of studies investigating citrus ETc based on single Kc (Castel and Buj, 1990; Castel et al., 1987; Consoli et al., 2006; Maestre-Valero et al., 2017; Rogers et al., 1983), and dual Kc (Er-Raki et al., 2008; Peddinti and Kambhammettu, 2019) a variety of crop coefficient values have been recommended (Table 1). These discrepancies in the reported Kc values is likely due to the variability and complexity of climatic factors (Niziński et al., 2017; Yang et al., 2003), irrigation management (Zitouna-Chebbi et al., 2015), plant physical and biological features (Consoli et al., 2006; Consoli and Papa, 2013; García-Tejero et al., 2011), and soil evaporation rates (Maestre-Valero et al., 2017). The inherent inconsistencies in Kc resulting from its empirical determination also highlight the need for local calibrations, especially under drought scenarios (Rana et al., 2005; Villalobos et al., 2013). In addition to understanding crop water requirement, the feasibility of applying deficit irrigation strategies requires monitoring of crop water status (Sepaskhah and Ahmadi, 2012). Several researchers have identified the citrus leaf water potential (Ψleaf) (de Lima et al., 2015; Rodríguez-Gamir et al., 2010) and stomatal conductance (gs) (Taylor et al., 2015; Villalobos et al., 2009) as sensitive proxies to reflect plant water stress. As soil water potential is reduced, leaf stomates dynamically adjust leaf gas exchange through partial closure (Klein, 2014). Although several physical and chemical signals trigger stomatal closure, including leaf desiccation (turgor loss), environmental factors (e.g., CO2 concentration, light intensity, vapor pressure deficit (VPD)), xylem, foliar and root levels of the abscisic acid (ABA)(Davies and Zhang, 1991; Klein, 2014; Pérez-Pérez et al., 2008), it is well established that leaf water potential (Ψleaf) is a critical factor in regulating guard-cell turgor (Zhang et al., 2013). The interspecific feedback mechanism between Ψleaf and gs is, however, crop-specific and different among species. This study sought to evaluate the applicability of saving water without affecting yield for ‘Washington Navel orange trees’ under the semi-arid climate conditions of the study region. More broadly, the study also aimed to identify and understand the plant feedbacks under the coupling impact of water-stress and climatic condition. The specific objectives include: i) to determine the standard evapotranspiration and crop coefficients (Kc) of field-grown Washington Navel orange trees in a drip-irrigated citrus orchard; ii) to understand the trees responses to different levels of irrigation, and monitor the feedback mechanism between Ψleaf and gs ; and iii) to define an appropriate deficit-irrigation strategy in terms of yield and crop physiological responses.

The values are presented for canopy cover of 70% and modified for the climate of the study region considering relative humidity, and wind speed.

0.79 1.09 0.85 1.10 0.79 0.95 1.02 0.68 0.58 0.60 0.80

2. Material and methods 2.1. Study site The field trial was conducted for two consecutive years (2016 and 2017) in a drip-irrigated citrus orchard located about 45 km from Kazeroon city (Latitude: 29° 27′ N, Longitude: 51° 39′ E, Elevation: 950 m a.s.l.) in Fars province of southern Iran. The study area is characterized by semi-arid Mediterranean climate surrounded by hot semidesert climate (De Pauw et al., 2004; Soufi, 2004), with a mean annual rainfall of 341 mm, hot and dry summers with maximum air temperatures exceeding 45 °C, and mild winters with minimum temperatures around 2 °C. Table 2 summarizes the climate conditions during the experimental period. The soil texture was loam (Table 3) with an average field capacity (FC) and permanent wilting point (PWP) of 27.5% and 10.2%, respectively. The experiments were performed in the middle of a clean cultivated citrus orchard where Navel oranges were planted at 5 × 5 m spacing. The orchard was flat and drip-irrigated with a high-frequency interval during summer (every other day), lower frequency during autumn (after every 4 days or weekly depending on the evaporative demand), and no irrigation during the winter. An average of ten on-line emitters (4 l hr−1) supplied water in each treatment.

*

0.82 1.08 0.85 1.17 0.68 1.00 0.96 0.61 0.49 0.75 0.60 0.89 1.16 0.85 1.05 0.62 1.10 1.03 0.60 0.49 0.75 0.50 0.86 0.95 0.80 0.88 0.55 1.10 1.10 0.58 0.54 0.75 0.30 0.81 0.65 0.80 0.74 0.62 1.10 1.22 0.52 0.40 0.75 0.40 0.78 0.69 0.80 0.66 0.66 1.10 1.37 0.57 0.60 0.70 0.60 0.79 0.76 0.75 0.63 0.65 0.90 1.61 0.88 0.80 0.60 ——— 0.73 0.85 0.75 0.69 0.66 0.90 1.90 0.70 1.08 0.50 —— Dry Mediterranean Humid Arid Semi-Arid Humid Mediterranean Mediterranean semi-arid Arid Mediterranean semi-arid Mediterranean climate Mediterranean semi-arid Tropical savanna Allen et al. (1998), FAO 56* Rogers et al., 1983 Hoffman et al. (1980) Sepaskhah and Kashefipour (1995) Castel et al. (1987) Rana et al. (2005) Snyder and O’Connell (2007) Consoli and Papa (2013) Maestre-Valero et al. (2017) ER-Raki et al. (2008) Peddinti and Kambhammettu (2019) Mixed Citrus Orange and grapefruit Valencia Sweet lemon Sweet and sour orange Clementine Navel orange Orange Hernandina mandarin Mixed citrus citrus orchards

January Region/climate Conducted by Citrus type

Table 1 Mean Kc values reported for Citrus orchard in published studies.

February

March

April

May

June

July

August

September

October

November

December

S. Jamshidi, et al.

2

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Table 2 Representative meteorological data for the study area for 2016, 2017 and decadal. average (2008–2017). Parameter*

Year

January

February

March

April

May

June

July

August

September

October

November

December

TMax ( C)

decadal mean 2016 2017

19.7 17.5 22.9

21.3 18.7 16.5

25.0 25 21.6

28.0 26.2 27

34.7 36.6 36.5

41.0 39.9 42.4

43.1 44 44

43.0 43.3 43.4

40.5 40.9 40.7

35.5 35.3 36.5

26.8 30.1 29.6

20.8 22.2 20.1

TMin (oC)

decadal mean 2016 2017

4.8 4.9 4.1

6.4 2.2 5.5

9.0 7.9 7.3

11.1 9.7 12.5

15.8 15.7 16.2

19.2 17.5 18.2

22.4 22.7 21.9

23.3 24.2 23.2

20.6 20.4 20.1

15.3 13.8 14.4

9.1 8.9 8.8

5.1 7 5.4

U2 (m s−1)

decadal mean 2016 2017

1.7 2.1 1.4

2.3 1.8 2.5

2.3 2.3 1.8

2.6 3.1 2.0

3.5 3.6 3.5

3.3 3.4 3.7

2.8 3.0 2.6

2.5 2.4 2.4

2.3 2.2 2.8

2.0 2.0 2.3

1.6 1.8 1.8

1.4 1.6 1.7

RhMax (%)

decadal mean 2016 2017

85.2 95.0 80.0

84.1 90.0 93.0

80.0 83.0 92.0

78.0 80.0 86.0

63.4 60.0 63.0

46.7 47.0 45.0

46.0 44.0 44.0

50.0 49.0 55.0

57.7 50.0 66.0

62.1 58.0 62.0

74.8 67.0 67.0

86.6 82.0 90.0

RhMin (%)

decadal mean 2016 2017

32.0 45.0 26.0

31.0 29.0 48.0

26.0 24.0 37.0

24.4 23.0 35.0

15.4 14.0 12.0

9.4 8.0 6.0

9.6 8.0 7.0

11.8 12.0 10.0

12.1 9.0 10.0

13.0 11.0 14.0

24.7 15.0 16.0

32.1 30.0 35.0

P(mm)

decadal mean 2016 2017

66.4 145.3 4.5

87.5 29.4 201

26.5 10.1 32.3

39.6 39.1 35.8

8.3 5.3 0.4

0.4 0 0

0.2 0 0

1 5.5 0

1.2 0 0.2

1.9 0 0

43.7 1.2 52.3

66.5 18.4 45.6

o

* TMax and TMin are maximum and minimum air temperature (oC), U2 is wind speed (m s−1) measured at 2-meter height, RhMax and RhMin are relative humidity (%), and P is rainfall (mm).

The citrus trees were mature (12-year old) with an average height of 2.8 m and the area shaded by the canopy was 75%–80% of the allotted spacing. The growing season typically starts at the early February with flower bud induction, and it follows by flowering from mid-March to April. Fruit setting begins around May, followed by the ripening and fruit development stage in June. Fruit harvesting is done during December.

amount of applied water in each treatment, while the ETo values for 2016 and 2017 were used for calculating Kc values. (1)

TMin )0.5 × Ra

ET0 = 0.0026 × (Tavg + 17.8) × (TMax

−1

Where ETo is the reference evapotranspiration (mm day ), Tavg, Tmax and Tmin are the mean, maximum and minimum air temperatures (oC), respectively; Ra is the extraterrestrial radiation (mm day−1), and 0.0026 is the empirical coefficient calibrated by Razzaghi and Sepaskhah (2012). Flowering and post-blooming to fruit set have been reported as the sensitive stages to water deficit in citrus (García-Tejero et al., 2012; Ruiz et al., 2001). Typically, these stages start in February and extend until the end of May over the region of study. Therefore, all trees were irrigated at full water requirement from February through May to minimize the adverse impacts of low irrigation levels on flowering and fruitlet abscission. The trees were exposed to the irrigation levels from June to December, and the following January.

2.2. Irrigation treatments and experimental design To identify the water use, the Washington Navel orange trees were subjected to five irrigation levels (from high to low extents). The irrigation levels covered the water use range suggested by FAO-56 and other studies under similar conditions (Allen et al., 1998; Consoli and Papa, 2013; Rana et al., 2005; Sepaskhah and Kashefipour, 1995). Accordingly, five treatments with three replications and three plants per replication were prescribed in completely randomized blocks with different irrigation amounts based on the fraction of ETo: 100%, 90%, 75%, 60% and 45% named as I100, I90, I75, I60, I45, respectively. ETo was calculated from calibrated Hargreaves-Samani equation for the region (Razzaghi and Sepaskhah, 2012) based on the mean longterm meteorological data, as well as for the study years (2016 and 2017). Note that the long term ETo values were used for calculating the

2.3. Data acquisition and plants measurements Crop evapotranspiration (ETc) was calculated following monthlywater balance method. This choice is based on a number of studies reported in the literature (Flumignan et al., 2011; Intrigliolo et al.,

Table 3 Soil and water characteristics for the study area. Soil characteristics Sand (%)

Silt (%)

Clay (%)

Soil texture

Bulk density (g cm−3)

N (mg kg

40.7

41

18.3

Loam

1.65

380

−1

)

P (mg kg

−1

)

18

K (mg kg 162

−1

)

OCa (mg kg 0.6

−1

)

pH

ECb (dS m−1)

7.9

1.01

Applied water characteristic Alkalinity (mg L−1) 205 Ca2+ 182 a b c d

Mg2+ 57

Na+ 94

Hardness (mg L−1)

SARc

pH

TDSd (mg L−1)

ECb (dS m−1)

414 K+ 3

1.44 Cl− 158

7.3 SO42− 464

1175 HCO3− 240

1.82 CO32− 0

Organic carbon. Electrical conductivity. Sodium adsorption ratio. Total dissolved solid. 3

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2013; Kang et al., 2003; Kusakabe et al., 2016; Miranda et al., 2006; Sepaskhah and Andam, 2001). The following equation is utilized:

Hoddes-don, England). At the end of each season (December), fruits were harvested, and crop load (i.e., number of fruit per tree, fruit size) was quantified. The overall yield of each tree was weighed using an on-site commercial grading machine.

n

ETc = I + P

D

( i=1

2

1)

×

Zi

(2)

where I is the irrigation depth (mm), P is the effective rainfall (mm), D is the deep percolation (mm) from the bottom of the root zone, n is the number of soil layers, ΔZ is the thickness of each soil layer (mm), and θ2 and θ1 are the volumetric soil water contents (SWC) at two consecutive measurements (cm3 cm−3). To ensure accurate delivery of water required for each of the irrigation treatment, analog water meters were installed, and the irrigation volume was measured weekly during the growing seasons. For soil moisture assessments, neutron probe (CPN®503 ELITE HydroprobeTM) was used, and monthly volumetric SWC was measured during the growing seasons at depths of 0.15, 0.45, 0.75 and 1.05 m. The neutron probe was calibrated for the study site using the method suggested by Zand-Parsa and Mahmoodian (1989). The amount of water applied in each irrigation treatment was adjusted by considering the effective rainfall. The rainfall data were obtained from a nearby weather station. To estimate soil evaporation (E), fifteen microlysimeters (one per replication) were used during the study period (Boast and Robertson, 1982). The microlysimeters consisted of double-slotted cylindrical tubes (i.e., an inner hollow plastic tube of 10 × 20 cm radius × height was placed inside an outer plastic tube of 12 × 25 cm). The outer cover was a closed-end cylinder, filled with 5 cm of field soil and placed into the ground under the canopy area. The inner cylinder held a meshedscreen end, which was filled with the field soil and inserted into the outer layer. The mesh-screen was an interface between the soil in the outer and inner tubes. The mesh-screen allowed the soil moisture to drain from the inner tube while keeping the soil weight constant by avoiding soil sliding and mixing between the two cylinders. The soil layer at the bottom of the outer cylinder was selected from the under the canopy (in-situ conditions) to maintain the moisture levels similar to the irrigation treatment and to simulate the actual suction gradient for draining. The microlysimeters were leveled with the soil surface, creating isolated volumes of bare soil, and received the same amount of applied water as each irrigation treatment. Both cylinders of the micro lysimeters were weighted before each irrigation. Evaporation was calculated as:

E=

Winner A1

Wouter A1

2.4. Analysis and calculations For calculating the single crop coefficient (K c ) , the ratio of ETc (measured using monthly water balance approach) to ETo was used:

KC =

ETc ET0

(4)

The ETc is representative of non-stressed, growing conditions considering a high level of management (referred to as standard level for crop evapotranspiration). Non-optimal growing conditions reduce the ET as compared to the standard level, and a reduction factor defined as the stress reduction coefficient (Kstress) was considered: (5)

ETc = K c × Kstress × ET0

The non-standard conditions could occur due to several factors, primarily including soil water deficiency, but also due to soil salinity, and other environmental or physiological stresses. Allen et al. (1998) described a water stress coefficient (this stress term was referred to as ‘Ksoil’ in our study) stemming from low soil water potential as a function of root zone depletion, Dr, i.e., water shortage relative to field capacity ( fc ) . Water stress is assumed to occur when Dr exceeds readily available water (RAW). The stress function was defined as:

TAW Dr TAW RAW

Ksoil =

(6)

where TAW is the total available soil water in the root zone (mm). For Dr ≤ RAW, Ks-T = 1 it was assumed that the plant can utilize water from the root zone without water stress. Since the study includes irrigation at different levels (e.g., applied water at 45% ETo), the Ksoil coefficient was calculated for each irrigation treatment to evaluate the imposed stress level. In the dual crop coefficient approach (Allen et al., 1998; Wright, 1982), Kc is split into two parts, the basal crop coefficient (Kcb) as a representative of the crop transpiration, and the soil water evaporation coefficient (Ke) as:

KC

(3)

dual

(7)

= K cb + K e

The measured soil evaporation (using microlysimeters) was subtracted from the measured ETc, to obtain the transpiration (T) values. The values of Kcb and Ke were defined using the following:

where Winner is the difference in the inner tube weight (reflecting the SWC loss due to evaporation and drainage), Wouter is the difference in the outer tube weight (reflecting the SWC loss due to drainage from the inner layer), and A1, A2 is the surface area of inner and outer cylinders, respectively. Deep percolation is typically assumed to be negligible, as previously suggested for drip-irrigated crops (Parvizi et al., 2014; Zhang et al., 2017). However, in the measurements undertaken the crop water use was not known, and therefore we considered deep percolation in the analysis. The amount of SWC in the root zone beyond the field capacity, as well as the water content that increased between the measurement intervals at the fourth soil layer (>1 m, below the root zone), was considered as deep percolation. Leaf water potential (Ψleaf) was measured at solar midday using pressure chamber (Soil Moisture Equip. Corp. Model 5100A, Santa Barbara, CA, USA) following the procedures described in Turner (1988). Measurements were carried out in randomly selected mature leaves (4–8 leaves from each tree in each experimental unit), covered with foil 1–2 hr before measurements (between 12:00 pm–14:00 pm). Stomatal conductance (gs) was measured bi-weekly at midday for fair weather days (between 12:00 pm to 14:00 pm) on relatively younger leaves using LCi-SD a Photosynthesis System (ADC Bio-Scientific Ltd.

K cb =

T E & Ke = ET0 ET0

(8)

Note that the stress reduction coefficient (Kstress) in dual crop approach for non-ideal condition only affects Kcb component. This stress term was referred to as “Ks-T” (i.e., K C dual = Ks T × K cb + K e ). The mean Kc and Kcb values from the FAO-56 publication (Allen et al., 1998), were reviewed for different crops under a “sub-humid climate condition” with average minimum relative humidity (RHmin) of 45% and average wind speeds (U2) of 2 m s−1. However, variations in climate and plant conditions alter the aerodynamic resistance and the crop coefficients especially for tall canopies (e.g., citrus tree) when compared to the grass surface which is considered as the reference crop in the FAO-56. Therefore, the mid-season and end-season Kc and Kcb values presented in Tables 12 and 17 of FAO-56 publication (Allen et al., 1998) were considered as:

K c mid & end season = K c

FAO

+ [0.04(U2

2)

0.004(RHmin

45)]

h 3

0.3

(9) 4

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K cb mid & end season = K cb

FAO

+ [0.04(U2

2)

0.004(RHmin

45)]

h 3

3.2. Soil water content and crop evapotranspiration

0.3

The average soil water content over each season corresponding to the different irrigation levels is presented in Fig. 2. As expected, the soil moisture levels recorded from the irrigation treatments corresponded to the severity of the imposed water restriction. Thus, high soil moisture values were observed in I100 treatment with the average water content in the soil profile from 0.216 to 0.262 cm−3 cm−3. For I90, the soil moisture ranged from 0.251 cm3 cm−3 to 0.183 cm3 cm−3 during summer, remained relatively constant during autumn, and then increased to 0.245 cm3 cm−3 by the end of winter. The reduction during summer in this treatment suggested the inadequate water supply during June-August, and the crop water requirement was partially compensated from the SWC. The mean seasonal soil moisture in I75 and I60 were 0.164 and 0.156 cm3 cm−3, and in I45 soil moisture depleted close to the PWP with 0.144 cm−3 cm−3 of volumetric water content. Once full irrigation was employed (from February), the soil moisture gradually increased. The soil moisture recovery rate was higher in the I75 and I60 treatments compared to I45. In 2016, heavy rainfall occurred in February and saturated the soil profile and caused a fast recovery in soil moisture. In 2017, the end-season soil moisture during the winter in the I75, I60, and I45 treatments recovered to 0.180, 0.187, 0.198 cm−3 cm−3, respectively. In all treatments, upper soil layers (0–50 cm) exhibited lower water content compared to the lower soils (50–100 cm). This was mainly observed during summer months when high evaporative demand during hot windy days excessively reduced the soil moisture of the top layers. The Ksoil calculated based on the soil water depletion Eq. (6) indicated a non-stressed condition in I100 and I90 treatments (i.e., Ksoil = 1), while the average Ksoil values for the I75, I60, and I45 treatments were 0.87, 0.76, and 0.61, respectively, indicating increasing levels of water stress. The stress coefficient values were further calculated by alternate methods using the inversion of Eqs. (5) and (7) T ET (K S T = K × ET and K S ET = K × aET ) and the measured ETc, Kcb and Kc o c o cb data. The resulting Ks-T and Ks-ET values (Fig. 3) were consistent with the Ksoil values when the soil moisture content was higher than

(10) where U2 and RHmin are the wind speed at 2-m height (m s−1) and the minimum relative humidity (%), respectively, h is the plant canopy height (m). For assessing and comparing the impact of the applied irrigation levels on the crop production, the water productivity (WPET, kg m−3) was calculated as (Fernández et al., 2019):

WPET =

Marketable Yield (kgha 1) TWU (m3ha 1)

(11)

where TWU is the total amount of water (m3) used for crop production per hectare. TWU has been given different definitions in various studies (Fernández et al., 2019). In this study, the amount of crop water use (ETc) was considered in water productivity calculations and referred to as ‘evapotranspiration water productivity’ (WPET). The data from different treatments were compared using Tukey test. 3. Results and discussions 3.1. Reference evapotranspiration The calculated reference evapotranspiration values for the 2016 and 2017 study period, and the irrigation amount for each treatment as well as the rainfall are shown in Fig. 1. The variations in ETo values between the two years were relatively small with January-February having the lowest average daily ETo rate of 2.37 mm, and June-July-August with the highest average daily ETo rate of 8.8 mm. During the course of study, there was no rain over the area in summer, and the cumulative rainfall was 254.3 mm in 2016 (25.1 mm occurring during June-Dec), and 419.1 mm in 2017 (98.1 mm occurring during June-Dec).

Fig. 1. Applied irrigation, reference evapotranspiration, and rainfall (mm) during 2016 and 2017 over the study region. 5

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Fig. 2. Average soil water content profile (during 2016 and 2017) for a) Spring, b) Summer, c) Autumn, and d) Winter.

Fig. 3. Comparison between Ksoil (TAW

TAW

Dr ), RAW

Ks-ET

(

ETC K c × ETo

6

) and K ( s-T

T K cb × ETo

) under different soil water content.

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Table 4 Mean measured values of crop evapotranspiration and its components. Treatment

Apr.

May

June

July

Aug.

Sept.

Oct.

Nov.

Dec.

Jan.

Feb.

Mar.

ETc (mm)

I100 I90 I75 I60 I45

127.5 123.3 126.0 124.5 123.1

223.2 218.4 227.8 220.8 216.0

282.1 279.2 264.1 240.6 209.3

299.3 295.7 247.5 211.9 162.2

252.0 239.4 189.4 153.9 114.0

207.8 202.9 164.1 110.0 78.2

134.2 130.9 117.8 79.2 61.4

94.2 91.9 74.6 59.1 47.1

54.2 52.6 46.9 40.5 30.4

53.3 51.5 44.4 31.4 25.7

51.2 48.6 51.2 50.6 48.6

82.4 80.1 81.7 82.1 79.0

Ksoil

I100 I90 I75 I60 I45

1.00 1.00 1.00 1.00 1.00

1.00 1.00 1.00 1.00 1.00

1.00 1.00 1.00 0.99 0.98

1.00 1.00 0.84 0.72 0.56

1.00 1.00 0.76 0.64 0.47

1.00 1.00 0.78 0.62 0.49

1.00 1.00 0.80 0.69 0.52

1.00 1.00 0.85 0.78 0.58

1.00 1.00 0.93 0.81 0.63

1.00 1.00 0.97 0.85 0.68

1.00 1.00 1.00 1.00 1.00

1.00 1.00 1.00 1.00 1.00

Kc

I100 I90 I75 I60 I45

0.88 0.85 0.87 0.86 0.85

0.93 0.91 0.95 0.92 0.90

0.97 0.96 0.91 0.83 0.72

0.94 0.93 0.78 0.67 0.51

0.88 0.84 0.66 0.54 0.40

0.85 0.83 0.67 0.45 0.32

0.83 0.81 0.73 0.49 0.38

0.82 0.80 0.65 0.51 0.41

0.74 0.72 0.64 0.55 0.42

0.67 0.65 0.56 0.40 0.32

0.78 0.74 0.78 0.77 0.74

0.80 0.78 0.80 0.80 0.77

Ke

I100 I90 I75 I60 I45

0.12 0.12 0.11 0.12 0.12

0.16 0.16 0.17 0.16 0.16

0.19 0.19 0.16 0.11 0.07

0.19 0.18 0.15 0.10 0.07

0.14 0.14 0.12 0.08 0.06

0.16 0.15 0.12 0.09 0.06

0.14 0.14 0.11 0.07 0.06

0.11 0.10 0.08 0.05 0.04

0.11 0.10 0.08 0.04 0.04

0.10 0.09 0.08 0.05 0.04

0.10 0.09 0.10 0.09 0.09

0.11 0.11 0.11 0.11 0.10

Kcb

I100 I90 I75 I60 I45

0.76 0.73 0.76 0.74 0.73

0.77 0.75 0.78 0.76 0.74

0.78 0.77 0.75 0.72 0.65

0.75 0.75 0.62 0.56 0.44

0.75 0.70 0.54 0.46 0.34

0.70 0.68 0.55 0.36 0.26

0.69 0.68 0.62 0.42 0.32

0.71 0.70 0.57 0.47 0.37

0.63 0.62 0.56 0.51 0.38

0.57 0.56 0.49 0.34 0.29

0.68 0.65 0.69 0.68 0.65

0.69 0.67 0.68 0.69 0.67

0.18 cm−3 cm−3 (i.e., two-thirds of field capacity). As the soil profile became drier, the discrepancy between the three coefficients increased. This discrepancy indicates that under non-optimal conditions (e.g., presence of water stress), considering only soil moisture status (i.e., using Ksoil) likely results in overestimating actual evapotranspiration. The Ksoil estimates do not explicitly account for stomatal conductance and evapotranspiration terms, which likely contributes to the overestimation. When the soil dried, as feedback, leaf turgor reduced, and stomatal resistance increased and reduced transpiration (Niyogi et al., 1998, 1999). This feedback process caused the ETc to decrease further and resulted in lowering Ks-T and Ks-ET values. Such feedback was not integrated in Ksoil estimation. The simultaneous analysis of Ks-ET and KsT data at similar soil moisture levels showed lower estimates by Ks-ET, and the differences are evident in the gap between their line graphs shown in Fig. 3. In general, Ks-ET reflects the overall actual stress occurring at each treatment considering the coupled feedback between soil moisture and atmospheric condition on evapotranspiration, while Ks-T primarily reflects the overall plant stress based on transpiration reduction and does not utilize the evaporation component. Therefore, by subtracting evaporation from the overall imposed water-stress (reflected in Ks-ET), higher values ensued for Ks-T. We considered the difference between Ksoil and Ks-T as the controlling effect of stomatal resistance in reducing the water stress. Accordingly, stomatal closure contributed 4.1%, 9.4%, and 16.9% in curtailing water loss in the I75, I60, and I45 treatments. Table 4 summarizes the average measured values of crop evapotranspiration and its components. To quantify the standard evapotranspiration rates in the resulting values obtained from the imposed irrigation levels, we evaluated the variations of ETc and soil moisture content between the treatments. The calculated Ksoil (from Eq. (6)) added further criterion in recognizing the standard versus waterstressed ET rates. The treatments with Ksoil < 1 were regarded as waterstressed trees for which ET rates occur lower than the optimal level (Allen et al., 1998, 2005). For a standard irrigation treatment, the Ksoil value is required to be an equal (or near) unity (Allen et al., 2005). Therefore, the I75, I60, and I45 treatments with average Ksoil of 0.87, 0.76, and 0.61 during the controlled-irrigation period, were considered as deficit irrigation strategies. When the irrigation amount was

increased by 10% from I90 to I100 treatments, the change in ETc rate between the two treatments increased only by 2.5% on average, and the difference was not statistically significant. The higher irrigation level in I100 caused the SWC to increase (0.24 cm3 cm−3) compared to the I90 treatment (0.20 cm3 cm−3), suggesting that ‘extra’ water applied in the I100 treatment was not needed (consumed) by the crop and was instead, stored in the soil profile. As a result, irrigating at 90% of ETo rate was considered as the ‘irrigation treatment’ for which ETc occurred at the standard rate. Accordingly, the I100 was classified as an over-irrigation treatment, while I75, I60, and I45 treatments were considered as mild, moderate, and severe deficit irrigation treatments, respectively. The standard ETc for Washington Navel ranged from 52.7 ± 1.0 mm (during Dec to Feb) to 285.1 ± 4.3 mm in June and July. The total measured ETc was 1843.2 mm in the first year and 1874.6 mm in the following year. For the I90 treatment, considered as the full irrigation treatment, the Kc values ranged from 0.67 in January and gradually increased toward the end of winter (Table 4). During flowering and fruit set stages in March and April, the Kc value reached 0.8 and then peaked at 0.96 during the fruit development stage in the summer. The Kc value dropped during the harvest time and end-season from November to December to 0.75. Comparable to these results, in the study by Rogers et al. (1983) and Sepaskhah and Kashefipour (1995) in a semi-arid climate, the Kc values reached to 1.1 in summer and around 0.70 to 0.75 in winter. Elevated Kc values during the peak season have also been reported by other studies (Maestre-Valero et al., 2017; Snyder and O’Connell, 2007). Depending on the climate and VPD, the peak value varied for different months. Snyder and O’Connell (2007) and MaestreValero et al. (2017) find peak values of 1 and 1.2, respectively, during December for a Mediterranean climate, while Consoli and Papa (2013) reported the maximum Kc values of 0.95 during November for a semiarid Mediterranean climate. Evaporation followed a similar pattern and consisted of 7% of total ETc in winter, doubling to almost 15% in summer as the irrigation amount, frequency (i.e., a persistent wet area under canopy), and VPD increased (Table 4). The evaporation rate correlated with the amount of applied water. The basal crop coefficient also showed a significant reduction in water-stressed trees (Table 4). The decrease in Kcb with 7

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Pereira (2009) reported a range of 0.10 to 0.13 mol m−2 s−1 for citrus which is consistent with our findings. Nevertheless, for a well-watered condition, a considerable variation in gs has been reported highlighting the need for local observations regarding citrus stomatal response to water stress condition. For instance, Dzikiti et al. (2007) reported the stomatal conductance of 2-year old orange trees in a range of 0.005 to 0.175 molm−2 s−1 on a typical clear day, and Pérez-Pérez et al. (2008) reported a range of 0.03 to 0.14 mol m−2 s−1 for fully watered ‘Lane Late’ citrus trees during the phenological stages. For non-optimal conditions, our measured gs values of severely stressed trees (0.011 molm−2 s−1 for I45 in summer) were lower than the values (0.05 mol m−2 s−1 as the lowest reported) for a similar 50% water reduction in a six-year-old orange orchard (Consoli et al., 2017). Consistent with our results, other studies have also reported stomatal conductance as low as 0.020 mol m−2 s−1 (Mossad et al., 2018), 0.018 mol m−2 s−1(Gomes et al., 2004) during the peak stress. Corresponding measurements of the leaf water potential showed that leaf water potential remained relatively steady for non-stressed trees (I100 and I90) at -0.71 ± 0.20 MPa and mildly stressed trees (I75) at -0.94 ± 0.18 MPa. Higher leaf dehydration was observed in the severely stressed trees as in I60 and I45 treatments the average Ψleaf during the water-restriction period were −1.35 and −1.86 MPa. Although some extreme negative values (up −3.21 MPa) were recorded from the mature leaves in I45 treatments, the overall result is consistent with the reported values for 7-years old Navel ‘Lane Late’ (−1.17 to −1.54 MPa; (Ballester et al., 2013), 12-years old orange trees (up to −2 MPa; (García-Tejero et al., 2010), and mature ‘Navelina’ orange trees (up to −2.5 MPa; (Gasque et al., 2016). Note that, the extreme negative recorded value could be due to leaf age, as noted by Syvertsen (1982) the leaf water potential reached -3.50 MPa when the leaves were 3–6 months old. The plant functioning mechanism was further investigated by considering the interactions between gs and Ψleaf with respect to the climatic conditions and soil moisture status. Fig. 5 shows the variations in gs and Ψleaf relative to VPD for each of the irrigation level (cf. (Ballester et al., 2013; Consoli et al., 2017; Parvizi et al., 2016). In our measurements, with increasing VPD, particularly from April to August (VPD >3 K Pa), the stomatal conductance followed a declining trend across all the treatments. The reduced gs was notable as the water stress level intensified between the irrigation treatments, and is shown in Fig. 5. After August, VPD followed a decreasing trend and the trees in I100, I90, and I75 treatments started showing decreasing stomatal resistance. However, the gs for the I60 and I45 treatments remained high until post-

increasing ETo in June-August demonstrated the close coupling of the canopy to the atmospheric condition. The measured values of Kc, Kcb, and Ke resulting from the I90 treatment as the standard values were compared with those reported in the FAO-56 publication (Allen et al., 1998) for canopy cover of 70%. Note that, the relative humidity and wind speed of the study region (Table 2) were not consistent with those of FAO-56 (RHmin of 45% and U2 of 2 m s−1) and therefore, the FAO Kc and Kcb values were modified based on Eqs. (9)–(10) for the climate of the study region. The measured values in our study were higher than those suggested by FAO-56. Using the standard approaches of FAO-56, the yearly ETc was calculated as 1596 mm (13% lower than our measured ETc) with Kc values ranging from 0.72 to 0.89. Such underestimation in ETc and Kc based on FAO-56 is not surprising and was also reported in other studies for different climates and crops (Rana et al., 2005; Shahrokhnia and Sepaskhah, 2013; Snyder and O’Connell, 2007). In addition to climatic factor, the crop physiology including its vigor (e.g., trunk diameter, leaf and shading area), density of planting, types of citrus (e.g., Lime, Orange), variety (e.g., Valencia, Navel), soil type and agricultural practices (e.g., fertilization, tillage, ground coverage) all affect the evapotranspiration reported in different studies. Our study was performed in a well-managed orchard with proper cultivation practices, and the experimented trees were vigorous with high crown density. The experimental conditions and environmental factors can be considered as an incremental factor contributing to the high rate of ETc over the study area. 3.3. Plant water status measurements Plants respond to water stress through physiological response such as stomatal closure and regulating leaf water potential (Davies and Zhang, 1991; Liu et al., 2006). Therefore, we reviewed the physiological indicators to identify the responses of Washington Navel orange trees to the imposed levels of water deficiency. Seasonal variation of stomatal conductance (gs) and leaf water potential (Ψleaf) for the irrigation treatments during 2016 and 2017 are shown in Fig. 4. For all the irrigation treatments during the early growing season, the stomatal conductance was relatively similar at around 0.11 mol m−2 s−1. Water availability was not a limiting factor during this stage, and the plants transpired at their potential. During the water restriction period, while in I100 treatment, the gs values remained relatively constant between 0.10 and 0.12 mol m−2 s−1, in the I45 treatment, the stomatal conductance was markedly low at 0.021 mol m−2 s−1 during summer. For ideal non-stressed condition, Allen and

Fig. 4. The seasonal variation of midday stomatal conductance (gs) and leaf water potential (Ψleaf) measured under different irrigation treatments during the 2016 and 2017 growing season. 8

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Fig. 5. Measured leaf water potential and stomatal conductance values for each irrigation treatment relative to vapor pressure deficit changes.

harvest. The reference (best-fit) lines of gs in Fig. 5, delineate how the stomatal response to VPD as the water stress level changes between the treatments. These best-fit lines can be potentially used as a reference for future studies to assess the physiological stress under different irrigation, and atmospheric (VPD) conditions, especially when detailed measurements are not possible. The leaf water potential in non-stress to mildly stressed trees (i.e., I100, 190, I75) was mildly impacted by the changes in VPD, (also seen in Fig. 4). The average gs values in I100, I90, and I75 during summer were 0.105, 0.095, and 0.079 mol m−2 s−1, while the leaf water potential in these treatments remained relatively similar (I90≥I100≈I75). Jones (1998) noted that stomatal closure could result in higher Ψleaf in mild waterstressed trees as compared to well-watered trees. The impact of VPD on Ψleaf was more pronounced in lower irrigation levels (i.e., I60 and I45); nevertheless, the resulting low correlation (as well as the moderate correlations between gs and VPD) signified that in addition to the atmospheric conditions (i.e., VPD), other factors such as soil moisture deficit, could have a notable feedback on plant water status. Since the soil moisture was not a limiting factor in I100 during high VPD period, the plant continued its high rate of transpiration which caused a slight decrease in the leaf water potential (evident in Fig. 4a and the reference line of Ψleaf for I100 in Fig. 5a). As the irrigation level reduced from I100 to I45, in conjunction with the summer heat stress and high VPD, the mild to severe soil desiccation experienced by the plant roots likely trigger stomatal closure and higher resistance. The covariance between the soil moisture (relative soil moisture deficit, RSMD) and gs -Ψleaf is plotted in Fig. 6a–b. The RSMD values near zero indicate that SWC is approaching the PWP while values close to 1 are indicative of soil moisture levels near the FC. The analysis showed that when the soil moisture was not a limiting factor (low RSMD), the reduction in both gs and Ψleaf was insignificant. For RSMD higher than ˜0.35-0.45, the reduction in gs and Ψleaf became more evident. Soil moisture availability also alters atmospheric humidity, which has an impact on the transpiration rates. To assess this feedback, Fig. 6c shows the variations of gs relative to VPD (gs/VPD) for a range of SWC. Under higher soil moisture conditions, the moderate slope in the gs variation indicated a dominant effect of VPD on stomatal closure. On the other hand, the abrupt slope change with soil moisture depletion indicated that in the lower range of SWC, plant water status was controlled by root water uptake and soil moisture availability. The simultaneous evolution of gs and Ψleaf, showed isohydric behavior of Washington Navel orange trees, particularly in I100, I90, and I75 treatments. In general, isohydric plants maintain constant midday leaf water potential in the absence of water by limiting transpiration with increasing stomatal resistance. Consistent with our finding, several studies have reported increasing stomatal resistance in citrus during drought condition to regulate leaf water potential (Tardieu and

Simonneau, 1998). As the severity of water-restriction intensified in the I60 and I45 treatments, evidently, the stomatal adjustment could not sustain the balance between root water uptake and transpiration rate, leading to a decrease in the leaf turgor. Thus the trees in I60 and I45 relative to other treatments showed higher stomatal resistance for a more extended period to avoid a further loss in Ψleaf. Note that, the reduction in stomatal conductance was more pronounced than Ψleaf reduction, and the trees exhibited isohydric behavior. The concurrent reduction of gs and Ψleaf of citrus with the intensification of water-restriction can also be inferred from other studies (Ballester et al., 2013; García-Tejero et al., 2011; Gasque et al., 2016); however, a few studies investigated the resulting correlation. In our study, the relationship between gs and Ψleaf formed a semi-sigmoid shape as plotted in Fig. 6c. It was noted that for a threshold (0.067–0.077 mol m−2 s−1; Fig. 6d) of stomatal closure the reduction in Ψleaf was not statistically significant (P > 0.05). With decreasing gs values beyond the threshold and soil moisture depleting beyond RAW, the Ψleaf reduced linearly with the gs reduction resulting in the following equation: leaf

=

1.05 +

4.13 1 + e(

gs + 33.81 ) 0.5

(12)

The Ψleaf - gs correlation investigated by Pérez-Pérez et al. (2012) for lemon and Mossad et al. (2018) for Valencia orange was described using a linear fit showing a corresponding reduction in both variables as the stress level increased. The data used in these studies were obtained from the trees subjected to regulated DI and partial root-zone drying methods. More consistent with our findings, a study by Gomes et al. (2004) for ‘Pera’ orange trees obtained relatively constant values of Ψleaf for a range of decreasing stomatal conductance. According to their results, leaf water potential started to drop when gs decreased beyond ˜0.05 mol m−2 s−. 3.4. Yield and evapotranspiration water productivity The number of fruits and recorded yield were not statistically different between the growing seasons (2016 and 2017); however, significant differences were found for among the treatments (Table 5). The yield boosted with increasing irrigation rate (Fig. 7); however, with the higher degree of applied water, the differences were not statistically significant. On average, irrigating at 100% and 90% of ETo yielded 95.6 and 93.3 kg tree−1 with relatively large fruit size (286 and 279 g), respectively, with no significant difference between the two treatments. In the I75 treatment, 17% of water-saving (relative to the I90 treatment) was achieved along with the final yield of 87.1 kg tree-1 and fruit size of 275 g. Overall, the crop load reduction in I75 was statistically significant compared to I100 and not different from I90, but the improvement in WPET was statistically higher than both of I100 and I90. The I60 treatment 9

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Fig. 6. a–b) Relationship between relative soil water content deficit (RSWD) and stomatal conductance (gs) - leaf water potential (Ψleaf) c) The relationship between Ψleaf and gs for different irrigation treatments.

yielded 33% water saving and resulted in significant yield and fruit size reduction (78.3 kg tree−1 and 251 g) compared to I100 and I90 treatments; yet, the decrease was not significant compared to the I75 treatment. In the last set of experiment, the 50% water saving in the I45 treatment caused considerable fruit dropping during the growing season and yielded small fruits (237 g). Overall, the imposed irrigation rates caused 7%, 16% and 29% of yield reduction in I75, I60, and I45, respectively. As expected, the WPET was inversely correlated with irrigation level (Fig. 7), and the highest WPET was achieved in I45 treatment. Irrigating the trees with 100% and 45% ETo yielded 2.05 and 2.31 kg m−3 of WPET, respectively. The intersection point between the relative yield and WPET (Fig. 7c) can be regarded as the optimized irrigation amount that reflects the best equilibrium between water savings and yields. The irrigation amount associated with the intersection point was calculated as 1391 mm, which was approximately similar to the amount of water applied in the I75 treatment (1368 mm). However, a recommendation regarding an optimal strategy for the growers to achieve water savings without significantly compromising the final yield also depends on the available irrigation water for the region. Based on this rationale and recognizing the current water deficiency in the study region (as the

main driver of this study), we suggest irrigating at lower rates (60% and 45% of ET0). Additionally, the yielded WPET in I60 (2.27 kg m−3) was not statistically different from that of I45; however, since the amount of yield was significantly higher than I45, irrigating at the I60 level results in a higher marketable option. Accordingly, the overall results and considerations suggest that irrigating at 60% of ETo or 70% of ETc for citrus (orange) can minimize the amount of water use while still maintaining the benefit of a good yield. 4. Conclusions Effective water management strategies for sustainable agriculture in the semi-arid climate of regions with limited water resources, such as southern Iran, requires enhanced knowledge of plant water use, particularly for the dominant agro-systems. Study results suggest that the standard (default) FAO-56 crop coefficients are low compared to the measurements for the study region, as Kc ranged from 0.71 in winter to 0.96 in summer with seasonal ETc of 1814 mm. The high irrigation rate and frequency (persistent wetted area), hot winds and temperature advection during summer, as well as the high foliage density of the trees, caused the soil evaporation

Table 5 The comparison of yield and water productivity between the irrigation treatments. Treatments

I100 I90 I75 I60 I45

Applied water (mm)

Yield (kg tree−1)

No. of fruits (tree−1)

Fruit weight (g)

WPET (kg m−3)

2016

2017

2016

2016

2017

2016

2016

1706 a* 1585 b 1358 c 1120 d 958 e

1741 a 1607 b 1377 c 1156 d 979 e

97.2 96.0 89.3 80.1 68.7

380 375 357 345 314

304 300 283 280 255

261.0 254.1 250.2 228.0 215.5

2017 a ab bc c d

94.2 90.5 85.0 76.5 65.9

a ab c c d

a ab b c d

a a b b c

2017 a b b c d

310.2 304.9 300.2 273.6 258.6

a ab b c d

2.08 2.12 2.18 2.28 2.30

2017 a a b c c

2.01 2.06 2.16 2.27 2.32

a a b c c

* Within each column, different letters indicate significant differences at P < 0.05 by Tukey test. The presented values in the table are mean values of the replications during 2016 and 2017.

10

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Fig. 7. The variation in a) yield, b) evapotranspiration water productivity (WPET), and c) relative values of yield and WPET resulting from different water application rate for irrigation treatments.

and plant transpiration occurring at a high rate. Analysis of stomatal conductance and leaf water potential in nonwater-stress and low-water-stress conditions showed that the atmospheric condition (VPD, heat-stress, wind) affected the stomatal closer/ opening. Although our findings cannot fully delineate the coupling between the various environmental and physiological factors, a feedback mechanism can be inferred whereby stomatal closure in response to a slight leaf turgor depression results in a consequent increase or preservation of leaf water potential. In severely stressed trees, particularly during summer, the leaf water potential (Ψleaf) was low, and the stomatal resistance remained high for an extended period to avoid the further decrease in Ψleaf. Best-fit (reference) lines were developed gs and Ψleaf under different water stress conditions, which can be used to obtain plant physiological responses for the stressed and non-stressed citrus trees and could be of potential value in irrigation scheduling. Reviewing the resulting yield and WPET, and considering the current water deficiency in the region, irrigating at 60% of ETo (˜0.7 ETc) was identified as the optimized strategy to be adopted by the local growers. Irrigating at this level resulted in ˜16% of yield loss, and increased WPET up to 33%. This recommended strategy could vary depending on the water availability for the region in the future. These findings would be transmitted to the help the knowledge-base for local growers to plan accordingly for adequate irrigation and help agencies and decisionmakers to devise a sustainable agricultural strategy for the semi-arid regions.

irrigation. Irrig. Sci. 11, 121–127. Castel, J.R., Bautista, I., Ramos, C., Cruz, G., 1987. Evapotranspiration and irrigation effeciency of mature orange orchards in Valencia (Spain). Irrig. Drain. Syst. 1, 205–217. Consoli, S., O’Connell, N., Snyder, R., 2006. Estimation of evapotranspiration of differentsized navel-orange tree orchards using energy balance. J. Irrig. Drain. Eng. 132, 2–8. Consoli, S., Papa, R., 2013. Corrected surface energy balance to measure and model the evapotranspiration of irrigated orange orchards in semi-arid Mediterranean conditions. Irrig. Sci. 31, 1159–1171. Consoli, S., Stagno, F., Vanella, D., Boaga, J., Cassiani, G., Roccuzzo, G., 2017. Partial root-zone drying irrigation in orange orchards: effects on water use and crop production characteristics. Eur. J. Agron. 82, 190–202. Dastranj, M., Sepaskhah, A.R., 2019. Saffron response to irrigation regime, salinity and planting method. Sci. Hortic. 251, 215–224. Davies, W.J., Zhang, J., 1991. Root signals and the regulation of growth and development of plants in drying soil. Annu. Rev. Plant Biol. 42, 55–76. de Lima, R.S.N., de Assis, F.A.M.M., Martins, A.O., de Deus, B.Cd.S., Ferraz, T.M., de Assis Gomes, Md.M., de Sousa, E.F., Glenn, D.M., Campostrini, E., 2015. Partial rootzone drying (PRD) and regulated deficit irrigation (RDI) effects on stomatal conductance, growth, photosynthetic capacity, and water-use efficiency of papaya. Sci. Hortic. 183, 13–22. De Medeiros, G.A., Arruda, F.B., Sakai, E., 2005. Crop coefficient for irrigated beans derived using three reference evaporation methods. Agric. For. Meteorol. 135, 135–143. De Pauw, E., Ghaffari, A., Ghasemi, V., 2004. Agroclimatic Zones Map of Iran, Explanatory Notes. ICARDA, Aleppo. Dzikiti, S., Steppe, K., Lemeur, R., Milford, J., 2007. Whole-tree level water balance and its implications on stomatal oscillations in orange trees [Citrus sinensis (L.) Osbeck] under natural climatic conditions. J. Exp. Bot. 58, 1893–1901. Er-Raki, S., Chehbouni, A., Hoedjes, J., Ezzahar, J., Duchemin, B., Jacob, F., 2008. Improvement of FAO-56 method for olive orchards through sequential assimilation of thermal infrared-based estimates of ET. Agric. Water Manag. 95, 309–321. FAOSTAT, 2017. FAOSTAT-statistical database. The food and agriculture organization of the united nations, Rome. Italy. Fernández, J.E., Alcon, F., Diaz-Espejo, A., Hernandez-Santana, V., Cuevas, M.V., 2019. Water productivity and economic analyses for super high density olive orchards. InActa Horticulturae. Flumignan, D.L., de Faria, R.T., Prete, C.E.C., 2011. Evapotranspiration components and dual crop coefficients of coffee trees during crop production. Agric. Water Manag. 98, 791–800. García-Tejero, I., Durán-Zuazo, V.H., Arriaga-Sevilla, J., Muriel-Fernández, J.L., 2012. Impact of water stress on citrus yield. Agron. Sustain. Dev. 32, 651–659. García-Tejero, I., Jiménez-Bocanegra, J., Martínez, G., Romero, R., Durán-Zuazo, V., Muriel-Fernández, J., 2010. Positive impact of regulated deficit irrigation on yield and fruit quality in a commercial citrus orchard [Citrus sinensis (L.) Osbeck, cv. salustiano]. Agric. Water Manag. 97, 614–622. García-Tejero, I.F., Durán-Zuazo, V.H., Muriel-Fernández, J.L., Jiménez-Bocanegra, J.A., 2011. Linking canopy temperature and trunk diameter fluctuations with other physiological water status tools for water stress management in citrus orchards. Funct. Plant Biol. 38, 106–117. Gasque, M., Martí, P., Granero, B., González-Altozano, P., 2016. Effects of long-term summer deficit irrigation on ‘Navelina’citrus trees. Agric. Water Manag. 169, 140–147. Gomes, Md.Md.A., Lagôa, A.M.M.A., Medina, C.L., Machado, E.C., Machado, M.A., 2004. Interactions between leaf water potential, stomatal conductance and abscisic acid content of orange trees submitted to drought stress. Braz. J. Plant Physiol. 16, 155–161. Intrigliolo, D., Bonet, L., Nortes, P., Puerto, H., Nicolas, E., Bartual, J., 2013. Pomegranate trees performance under sustained and regulated deficit irrigation. Irrig. Sci. 31, 959–970. Jamshidi, S., Zand-parsa, S., Pakparvar, M., Niyogi, D., 2019. Evaluation of evapotranspiration over a semi-arid region using multi-resolution data sources. J. Hydrometeorol 20 (5), 947–964. Jones, H.G., 1998. Stomatal control of photosynthesis and transpiration. J. Exp. Bot. 387–398. Kamali, H., Zand-Parsa, S., 2017. Estimation of sugar beet yield and its dry matter partitioning under different irrigation and nitrogen levels. Mod. Appl. Sci. 11.

Declaration of Competing Interest None. Acknowledgments The authors acknowledge the financial support provided by Shiraz University, Grant Number: 96GCU2M1303. References Ahmadi, K., Gholizade, H., Ebadzade, H., Hatami, F., Hoseinpour, R., Kazemifard, R., Abdshah, H., 2015. Agriculture Statistics. (M. O. Agriculture, Ed.), vol. III pp. 240, Iran. Allen, R.G., Pereira, L.S., 2009. Estimating crop coefficients from fraction of ground cover and height. Irrig. Sci. 28, 17–34. Allen, R.G., Pereira, L.S., Raes, D., Smith, M., 1998. Crop Evapotranspiration-Guidelines for Computing Crop Water Requirements-FAO Irrigation and Drainage Paper 56 300 Fao, Rome, D05109. Allen, R.G., Pereira, L.S., Smith, M., Raes, D., Wright, J.L., 2005. FAO-56 dual crop coefficient method for estimating evaporation from soil and application extensions. J. Irrig. Drain. Eng. 131, 2–13. Ballester, C., Castel, J., Jiménez-Bello, M.A., Castel, J., Intrigliolo, D., 2013. Thermographic measurement of canopy temperature is a useful tool for predicting water deficit effects on fruit weight in citrus trees. Agric. Water Manag. 122, 1–6. Boast, C., Robertson, T., 1982. A “Micro-Lysimeter” method for determining evaporation from bare soil: description and laboratory evaluation 1. Soil Sci. Soc. Am. J. 46, 689–696. Castel, J., Buj, A., 1990. Response of salustiana oranges to high frequency deficit

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