The degree of coupling between canopy and atmosphere, through the decoupling factor Ω, well describe the behaviour of a crop with respect to its water use and carbon dioxide exchange. Super high density hedgerow olive orchard system is in great expansion all over the world and, since it has a complex field structure in rows of adjacent trees, investigations are necessary to assess the Ω patterns, as well as aerodynamic (ga) and canopy (gc) conductances in different water conditions. In this study, in a hedgerow olive orchard (cv. “Arbosana”) submitted to full (FI) and regulated deficit irrigation (RDI), cropped under Mediterranean semi-arid climate (southern Italy), Ω has been determined using gc, as deduced by inverting the Penman-Monteith equation, and ga, by upscaling the wind speed measured in a close station to the canopy; the transpiration has been measured by sap flow thermal dissipation method. The results showed that this olive orchard results very well coupled to the atmosphere, in any soil water conditions; Ω is generally very low, being equal in mean to 0.015 ± 0.008 and 0.019 ± 0.012 for FI and RDI, respectively. This condition is linked to ga and gc values; in fact, canopy conductance is much smaller than the aerodynamic one in any water and climatic conditions, except when all canopy surfaces are saturated in water. In this latter case, the gc assumes highest values due to the contribution of the part of conductance attributable to the structure of the orchard.
Research Article
Decoupling factor, aerodynamic and canopy conductances of a hedgerow olive orchard under Mediterranean climate
https://doi.org/10.21203/rs.3.rs-1953601/v1
This work is licensed under a CC BY 4.0 License
Journal Publication
published 15 May, 2023
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Olea europaea cv. Arbosana
sap flow thermal dissipation
water stress conditions
semi-arid climate
Penman-Monteith
critical conductance
The thermo- and aero-dynamic relationships between vegetate surfaces and atmosphere, at different space scales from leaves to stand, have been amply investigated in the second half of the 20th century. Since the introduction of the concept of elastic coupling between canopy and atmosphere, quantified through the decoupling factor Ω by McNaughton and Jarvis (1983), canopy transpiration (T) has been effectively characterized by canopy (gc) and stomatal (Gs) conductances, both in terms of magnitude and environmental control, especially for tree crops and stands (Wullschleger et al., 2000). If the decoupling factor is high, transpiration is more strongly controlled by incoming radiation and less by changes in stomatal conductance; if Ω is low the stomatal control of transpiration is high and a change in stomatal conductance leads to a correspondent change in transpiration.
Insights about the degree of coupling between vegetation and atmosphere permit to investigate the behaviour of a specie with respect to its water use, as well as to the exchange of carbon dioxide between canopy and atmosphere (De Kauwe et al., 2017).
The degree of coupling strongly depends on the aerodynamic characteristics of the vegetate surface (Jarvis and McNaughton, 1986; McNaughton and Jarvis, 1991), such as surface roughness, foliage clumping, leaves shape and density, canopy density, plants’ height, and training system. Tall canopies and species with small leaves are expected to be more coupled to atmosphere than low canopies and species with large leaves: this because tall plants have high surface roughness, and hence high aerodynamic conductance which directly links the transpiration surface to the above atmospheric environment. In a continuous scale of plants’ height and surface roughness, a range of intermediate possibilities occurs.
Actual transpiration at canopy scale results from the integration of instantaneous processes at leaf level. However, investigations at canopy space scale can be faced by treating the vegetate surface as a single entity, characterized by (i) a bulk canopy conductance (gc) to the transfer of water and (ii) an aerodynamic conductance (ga) to the transfer of momentum and other scalars between canopy and atmosphere; the canopy can be thus considered as a single “big-leaf” (Monteith and Unsworth, 1990).
In the relationship vegetate surface - atmosphere, Gs and gc have different boundary conditions, because they express exchange processes at different space scales. When the big-leaf approach is used, the net radiation (Rn) is supposed to be received in the same environment by an identical surface at air temperature processes (Martin, 1987; Monteith and Unsworth, 1991). Furthermore, the relation between canopy as a whole and air vapour pressure deficit (D) is different from the relation between leaf and D in the local leaf boundary layer (McNaughton and Jarvis, 1991; Baldocchi et al., 1991; Katerji and Rana, 2011). Therefore, precautions about where thermodynamic measurements are realized and how the canopy aerodynamic characteristics are determined must be taken when the coupling with atmosphere is studied at canopy scale where, usually, gc is derived by inverting the model estimating the transpiration (Zhang et al., 2016; De Kauwe et al. 2017). The Penman-Monteith model (Monteith, 1965) or simplified versions of it (Köstner et al., 1992) are typically used in this kind of investigations.
While many studies on the decoupling factor have been devoted to forest and wood species (see De Kauwe et al., 2017 for a review), the studies on fruit trees are relatively uncommon. Focusing attention on fruit orchards, Forster et al. (2022) found that along the growth season Ω varied in the range 0.55–0.65 and 0.50–0.55 for apple and pear, respectively, the plants` height was around 5 m for both crops. Marin et al. (2016) gave for Ω a mean value of 0.1 for a citrus orchard of 4 m height, without any indication on the dynamics. Spinelli et al. (2018) give a seasonal dynamic of Ω in the range 0.2–1.0 for an almond orchard following the crop water conditions. Except for the latter study, where measurements were carried out in the centre of the plot by the eddy covariance technique (Lee et al., 2004), the measurements of the weather variables, useful for the application of the used models, were carried out in stations more or less far from the canopy under study, without any type of correction or upscaling.
Starting from last years of the past century olive growing moved towards great intensification, with the large diffusion and the strong increasing in Mediterranean region of the super high density (SHD) cropping systems (Godini et al., 2011). These new full mechanized olive groves, known as “hedgerow orchards”, are characterised by a density over 1,200 trees per hectare and by the continuous fruit harvesting (Vivaldi et al., 2015). Moreover, irrigated hedgerow orchards show positive both economic and environmental impact compared to rainfed traditional olive orchards (Russo et al., 2015). Having in mind the actual increasing drought conditions in Mediterranean regions (Katerji et al., 2017), different investigations (Iniesta et al., 2009; Fernández et al., 2013; Rosecrance et al., 2015) suggest the regulated deficit irrigation (RDI) as a suitable strategy in SHD olive orchards for reducing the typical excessive vigour of the species, through limiting the soil water availability.
Tognetti et al. (2006) analysed the Ω values of a standard plantation of 15-year-old olive trees cultivated in Mediterranean region, under different water conditions. They found that in a dry summer Ω was relatively low, implicating a strong control of transpiration by stomatal regulation, with the water stressed canopy more coupled to the atmosphere than the well-watered one. Vice versa, in a wet summer Ω approached to 1 and the transpiration becomes increasingly dependent on Rn received and less dependent on D. Although in this last case it seems that water vapour exchange was mainly controlled by leaf conductance, the evaporative demand, the solar radiation, the soil moisture and the aboveground and belowground plant functioning had varying complex influences on canopy-scale stomatal control of water, needing further mid-term investigations under contrasting weather conditions (Tognetti et al., 2006; De Kauwe et al., 2017; Chebbi et al., 2018).
Hedgerow tree orchards have peculiar aerodynamic characteristics, because the regular scheme of close adjacent trees, in rows separated by soil strips, makes the roughness highly dependent on the angle between the wind direction and the orientation of rows (Alfieri et al., 2019). Zeng and Wang (2007) found that neglecting factors beyond canopy height and structure of plantation can affect surface roughness by introducing significant errors of up to 50%. Maurer et al. (2013; 2015) have shown that errors in roughness length and zero-plane displacement height can result in significant errors in modelled fluxes and related variables. Therefore, the impacts of both the aerodynamic characteristics and the aerodynamic conductance on Ω need to be deeply analysed for assessing the control of the environment on the water canopy behaviour in different crop water conditions, mainly when the plantation has such an in-row hedgerow structure.
The general objective of this mid–term study was to investigate and analyse the relationships among decoupled factor, aerodynamic and canopy conductances of olive trees (cv. Arbosana) grown in a hedgerow orchard submitted to full irrigation (FI) versus regulated deficit irrigation regime (RDI). Measurements were carried out in the hottest months of three growing seasons (2019–2021) in a Mediterranean environment (southern Italy), characterised by contrasting weather.
a. Theoretical framework
The transpiration is a process occurring at leaf level. However, “the single-layer model (…) is adequate to illustrate the nature of the meteorological feedback processes which operate in much the way we describe, although they must be represented in a more complex fashion in more complex models of canopy processes” (McNaughton and Jarvis, 1991). Hence, the theoretical upscaling framework of transpiration from leaves to canopy is left to the cited literature: here we adopt the “big-leaf” approach to estimate the hedgerow olive orchard transpiration under the following form:
$$\lambda T=\frac{{\epsilon }A+\varrho {c}_{p}D{g}_{a}/\gamma }{{\epsilon }+1+{g}_{a}/{g}_{c}}$$
1
where λ is the latent heat of vaporization of water (J kg− 1), A is the available energy (Rn-G), with Rn the net all-wave radiation above the stand (J m− 2 s− 1), G the heat flux to soils (J m− 2 s− 1), ρ the density of dry air (kg m− 3), cp the specific heat of air at constant pressure (J kg− 1 K− 1), D the atmospheric vapour pressure deficit (kPa), ε = Δ/γ with Δ the rate of change of saturation water vapor pressure with temperature (kPa K− 1) and γ the psychrometric constant (kPa K− 1), ga the aerodynamic conductance (m s− 1) and gc the canopy conductance (m s− 1). Since the olive orchard was drip irrigated, the evaporation component is low than 10% of evapotranspiration (Bonacela et al., 2001; Egea et al., 2016) and was here neglected.
In Eq. (1) it is supposed (Monteith, 1965) that the energy conservation principle is applied to the zero-plane displacement (the height of the plane, d (m), considered as origin, z = 0, for the coordinate system in which the model is formulated or, in other words, the level of the base of the roughness elements). Thus, the energy balance is a boundary condition applied on a plane z(0) where the energy is entirely available, i.e. z(0) = d + z0, with z0 the roughness length for momentum transfer.
The model expressed by Eq. (1) introduces two conductances expressing the transport of water from the canopy to the atmosphere: (i) the canopy conductance, gc, which describes the diffusion of vapour due to stomatal regulation of the canopy thought as a big leaf; (ii) the aerodynamic conductance, ga, between the zero-plane displacement and a reference plane over the canopy, which accounts for the convective transport of vapour toward the atmosphere.
In this study, since the evaporative surface is heterogeneous and the architecture of such a hedgerow canopy is complex and has impacts on the convective transport of water vapour, we make the following hypothesis:
i the canopy is a semi-porous medium where the mechanism of vapor diffusion is strongly influenced by both the architecture of the canopy and the stomatal regulation (Perrier, 1975a; Daudet et al., 1999, among others);
ii the energy conservation boundary condition is applied to the top of the canopy, so that
iii the aerodynamic resistance is experimented between this plane and the reference surface;
iv the canopy conductance indicated as diffusion canopy conductance, gcd, (Perrier, 1975b; Katerji and Rana, 2011), can be written as:
$$\frac{1}{{g}_{cd}}={r}_{c}+{r}_{0}$$
2
with r0 resistance depending on the canopy structure (Appendix I) and rc resistance depending on the mean stomatal regulation of leaves.
Under these hypotheses, introducing Eq. (2) in Eq. (1), the canopy conductance of Eq. (1) becomes “gcd“ and maintains the same meaning of the big leaf approach by Monteith (1965), while the aerodynamic conductance is expressed as (Perrier, 1975a; Rana et al., 1994; Katerji and Rana, 2011)
$${g}_{a}=\frac{{k}^{2}u\left(z\right)}{ln\left(\frac{z-d}{{z}_{0}}\right)ln\left(\frac{z-d}{{h}_{c}-d}\right)}$$
3
z (m) is the height of the reference plane, d (m) is the zero-plane displacement height of the measurement surface, z0 (m) is the roughness length for momentum transfer, hc (m) is the mean crop height, k (0.4) is the von Karman constant; u(z) (m s− 1) is the wind speed at the reference height above the canopy. The above relationship is valid in neutral atmospheric conditions, and it assumes a logarithmic profile of wind speed and air temperature in the convective boundary layer and on the mixing length turbulent model. Note that in the expression of ga, the roughness length to the diffusion of water vapour and heat is expressed by (hc-d).
Under the above assumptions, the actual transpiration for the hedgerow olive orchard can be written as
$$\lambda T=\frac{{\epsilon }A}{{\epsilon }+1+{g}_{a}/{g}_{cd}}+\frac{\rho {c}_{p}D{g}_{a}/\gamma }{\epsilon +1+{g}_{a}/{g}_{cd}}$$
4
Two terms appear in this expression: the first one is the "radiative term", representing the contribution of the radiative energy to T, the second one, called "convective term", is due to both the natural and forced convection in the low atmosphere above the canopy (Monteith, 1965; McNaughton and Jarvis, 1986; Rana et al., 1994).
To establish the boundary values of ga, the limits of λT for ga→∞ and ga→0 must be calculated for the full and null coupling between canopy and atmosphere, as (McNaughton and Jarvis, 1986):
The term (5a) is known as “equilibrium transpiration”, because the canopy is completely decoupled from the atmosphere and the transpiration is addressed only by the available energy at the canopy reference surface; the term (5b) is known as “imposed transpiration”, because the canopy is fully connected to the atmosphere and the transpiration is addressed by the stomatal regulation at a given thermodynamic condition of air expressed by vapour pressure deficit D. Between these two boundary values for ga, a decoupled factor Ω, having values in the range 0–1, can be defined (McNaughton and Jarvis, 1986) to take into account all actual possibilities, as:
$${\Omega }=\frac{\epsilon +1}{\epsilon +1+{g}_{a}/{g}_{cd}}$$
6
therefore, the transpiration can be determined in “elastic” way as:
$$\lambda T={\Omega }\lambda {T}_{eq}+\left(1-{\Omega }\right)\lambda {T}_{imp}$$
7
Figure 1 reports some examples of relationship between λT and gcd for some values of wind speed v, at given thermodynamic condition of the atmosphere for a typical clear spring morning in Mediterranean region. A particular value of gcd, known as “critical conductance”, g* (firstly described by Daudet and Perrier, 1968, in an unfamiliar and rarely cited study of several decades ago) divides the graph in two zones, A and B; in the zone A (gcd > g*) the transpiration is an increasing function of the wind speed; in the zone B (gcd < g*) the transpiration decreases with the wind speed; the latter phenomenon is less evident but has strong impacts on the coupling of tree orchards (Daudet et al., 1999). To give an expression to the critical conductance g* it is necessary to look for the characteristic value of gcd that annuls the derivative \(\partial \lambda T/\partial {g}_{a}\)(Rana et al. 1994; 1997) i.e.:
$${g}^{*}=\frac{\varDelta A}{\left(\epsilon +1\right)D\rho {c}_{p}}$$
8
It is useful to underline the dependence of g* on climatological factors only and that it is quasi-linearly correlated to the Monteith’s (1986) “climatic or isothermal conductance”
$${g}_{i}=\frac{\gamma A}{\varrho {c}_{p}D}$$
9
If we substitute the expression (8) into (4), it is possible to write the decoupling framework of λT under the form:
\(\frac{\lambda T}{A}={\Omega }\frac{\epsilon }{\epsilon +1}+\left(1-{\Omega }\right)\frac{\epsilon }{\epsilon +1}\) \(\frac{{g}_{cd}}{{g}^{*}}\) (10)
The above expression provides a clear interpretation for the coupling process between canopy and atmosphere (McNaughton and Jarvis, 1986):
1. When Ω = 1 (canopy isolated by atmosphere), the transpiration is an almost fixed constant fraction of available energy (Priestley and Taylor, 1972) at equilibrium between the crop in given water conditions and the atmosphere.
2. When Ω = 0 (canopy fully coupled to atmosphere), the conditions are imposed by the atmosphere and the crop proceeds at transpiration rates depending on the weather (g*) and is effectively controlled by the stomata at instantaneous time scale (gcd).
b. The aerodynamic conductance
The value of Ω may be submitted to wide variations depending on the aerodynamic roughness of the transpiring unit (see Eqs. 3 and 6). Furthermore, correct estimations of the aerodynamic conductance, which determine the degree of coupling, are difficult to obtain because wind speed is usually measured at short distance from the surface, whereas gradients of temperature and humidity often persist for large distance above the reference level; McNaughton and Jarvis (1983) estimated that about one-third of the conductance across the surface layer is located above the usual instrument height.
Therefore, the aerodynamic characteristics at the interface canopy-atmosphere inside the fully developed boundary layer, through the roughness and zero plane-displacement lengths and the wind speed at the reference height, must be accurately determined to have correct Ω values.
Here, since the canopy structure of the olive stand is in rows of closed adjacent trees, the roughness length of momentum transfer was calculated following Alfieri et al. (2019), who identified a sigmoidal relationship between z0 and wind direction:
$${z}_{0}={\xi }_{min}+\frac{{\xi }_{max}-{\xi }_{min}}{1+exp\left[-\beta \left(\omega -{\omega }_{0}\right)\right]}$$
11
where ω is the relative wind direction, defined as 0° when the wind direction is parallel to the row direction, i.e., north to south, and 90° when the wind direction is perpendicular to the row. ξmin = 0.1642, ξmax = 0.3107, β = 0.1270, ω0 = 24.52 are fitting parameters of the sigmoid function, representing the minimum and maximum z0, the slope and the offset in ω, respectively. The zero- plane displacement height was set d = 0.67 hc.
Since Ω is referred to the canopy site, and the weather variables were here measured in a separate meteorological station (see next section), Rana and Katerji (2009) were followed to upscale variables from the station to the canopy (supplementary material 1).
c. The canopy stomatal conductance
Although here the analysis was made at canopy level, and the canopy conductance was derived by the inversion of the Penman-Monteith model (Eq. 1) and conscious that the canopy conductance is not a purely physiological variable (i.a., Rochette et al., 1991), an investigation by using independent measurements at leaf scale can support the correctness of the found gcd, at least regarding the order of magnitude. The theoretical development of the leaf stomatal conductance scaling up to the canopy is left to the huge literature on the subject (see for example the physical approach proposed by Baldocchi et al., 1991, among many others); here we estimate a mean stomatal canopy conductance (gsc, m s− 1) as (Szeicz and Long, 1969):
$${g}_{sc}=\frac{R{T}_{l}}{{P}_{a}}\stackrel{-}{{G}_{s}}LAI$$
12
with \(\stackrel{-}{{G}_{s}}\) (mol m− 2 s− 1) the mean conductance measured at leaf level, LAI leaf area index, R (8.314 J mol− 1 K− 1) the gas constant, Tl (K) the leaf temperature and Pa the atmospheric pressure (set at standard value = 101325 Pa). The LAI values were estimated as detailed in Supplementary material 2.
d. The site, the crop and ancillary measurements
The study was realized in three years (2019, 2020 and 2021) focusing on the most evaporative demanding periods in the site (Katerji et al., 2017), i.e. from 1 July to 31 August. The olive orchard (cv. Arbosana) is located at the University of Bari experimental farm at Valenzano, southern Italy (41° 01’ N; 16° 45’ E; 110 m a.s.l.), on a sandy clay soil (sand, 630 g kg− 1; silt, 160 g kg− 1; clay, 210 g kg− 1) classified as a Typic Haploxeralf (USDA) or Chromi-Cutanic Luvisol (FAO). The site is characterised by typical Mediterranean climate with a long-term average (1988–2018) annual rainfall of 560 mm, two third concentrated from autumn to winter, and a long-term average annual temperature of 15.6°C. The olive grove has been planted in early summer 2006; the self-rooted trees were trained according to the central leader system and spaced 4.0 m × 1.5 m (1,667 trees ha− 1) with a North–South rows orientation, according to the SHD cropping system. Trees were 1.75 ± 0.46 m high. Routine cultural nutrition, soil management, pests and diseases control practices were set up as described by Camposeo and Godini (2010). Lots of 180 m2 surface, 60 m apart, with 35 trees in each one, were submitted to two irrigation regimes: full irrigated (FI) versus regulated deficit irrigation (RDI), the last applicated throughout the pit hardening phase, when the tree is least sensitive to water deficit; during this phenological phase, irrigation was interrupted for about one month (19/07–20/08/2019; 15/07–18/08/2020; 14/7–14/08/2021). Irrigation was scheduled following the evapotranspiration method, by restoring 100% of crop evapotranspiration lost in each irrigation interval, as recommended by the FAO56 guideline. The plots were irrigated by a dripline equipped with 2.5 L h− 1 emitters, 0.6 m apart.
Air temperature (Tair, °C) and vapour pressure deficit (D, kPa) through air relative humidity, global radiation (Rg, MJ m− 2 s− 1) and precipitation (P, mm), wind speed (u, ms− 1) and wind direction (degree) were collected at a standard agrometeorological station 120 m far from the experimental field.
R n and G, both in Wm− 2, was calculated as follows (Rana and Katerji, 2009, among others):
$$Rn=\left(1-\alpha \right){R}_{g}-\sigma \left(\frac{{T}_{max}^{4}+{T}_{min}^{4}}{2}\right)\left(0.34-0.15\sqrt{{e}_{a}}\right)\left(1.35\frac{{R}_{g}}{{R}_{g0}}-0.35\right)$$
13
where α albedo of the crop directly determined on the orchard as mean of hourly daytime values (0.27) from January to December 2021; Tmax and Tmin (°K) are maximal and minimal air temperatures; ea (kPa) is the actual vapour pressure; and Rg0 (MJ m− 2) is the calculated clear-sky radiation. After a local calibration of twelve months (January-December 2021), G was considered as a constant at daily scale and equal to 0.09 Rn.
The degree of drought for each year under investigation was evaluated by the standard precipitation index (SPI, Naresh Kumar et al., 2009).
The Canopy conductance gcd to calculate Ω (Eq. 6) was obtained by inverting Eq. (1)
$${g}_{cd}=\frac{\lambda T{g}_{a}}{\epsilon A+\varrho {c}_{p}D{g}_{a}/\gamma +\left(\epsilon +1\right)\lambda T}$$
14
Here actual transpiration was measured by sap flow thermal dissipation method (TDM, Granier, 1985, 1987). λT was determined by the sap flow density, Js0 (g m− 2 s− 1) was measured in a set of selected plants and corrected for the underestimation induced by the wounds and other errors as described in Supplementary material 3.
Soil water content in volume (θ, m3 m− 3) was measured by capacitive probes (5TM, Decagon Devices Inc., USA). For each treatment, three points were monitored following the protocol described in Campi et al. (2020). At each point, two capacitive probes were installed horizontally into the soil profile and transversely to the row, at -0.12 and − 0.37 m from the soil surface to intercept the dynamics of θ below the dripping lines. One set of probes was installed between the tree rows. All sensors were connected to data-loggers (Tecno.el srl, Italy); integrated soil water content daily was determined for the soil profile (0.5 m) by integrating the three values measured at each depth, since each probe was supposed to detect the water content in a 0.25 m soil layer (Campi et al., 2019). θ measurements from the three points were pooled to obtain a single average value for each treatment.
Soil water availability was described through the relative extractable water (REW, unitless) calculated using the average soil water content across positions around the tree and soil layers (Granier, 1987; Tognetti et al., 2009):
$$REW=\frac{\theta -{\theta }_{min}}{{\theta }_{max}-{\theta }_{min}}$$
15
where θ is the actual soil water content in the root zone, θmin the minimum soil water content observed during the experiment, and θmax is the maximum soil water content in the area (e.g., at field capacity).
Stomatal conductance (Gs, molH2O m− 2 s− 1) was measured (2, 23, 31 July and 29 August 2019) on two healthy well light-exposed leaf per tree (on the West and East side) selected in the middle part of the canopy, by using a portable open gas-exchange system, fitted with a LED light source (LI-6400XT, LI-COR, Lincoln, NE, USA). At each measurement and canopy side, light intensity was maintained constant across the two treatments setting the LED light source at the natural irradiance detected near the leaf. For each treatment, Gs measurements were performed in the three plants where transpiration was measured by TDM and other two trees similar for dimension, vigour and health state, chosen in correspondence with the soil moisture probes. The data were subjected to one-way ANOVA using SAS/STAT 9.2 software package (SAS/STAT, 2010).
a. Weather, soil water and aerodynamic characteristics of the orchard
The time evolution of main meteorological parameters (daily values of Tair, D, Rg and P) in the experimental periods are shown in Fig. 2. The three periods were characterized by very different weathers, including the extreme water scarcity conditions during the 2019 and 2021 drought summers, and the exceptionally rainy summer in 2020 characterized by few events and high rain intensity. In few minutes, 31 and 23 mm of rain fell on 5th and 7th August 2020, respectively. The much-contrasted weather of the three years confirm the great variability following the climate change, in terms both of temperature and rain of the last years in this Mediterranean area (Rana et al., 2016; Katerji et al., 2017). The yearly mean air temperature was 18.1, 16.4 and 17.0°C in 2019, 2020 and 2021, respectively, being always warmer than in the past (15.6°C). Furthermore, an intense heat wave crossed the experimental period in 2021, between end July and beginning of August, when irrigation was withheld in the RDI plot. Mean air temperature attained 34°C and peaks of 42°C was observed during daytime. Moreover, in these periods D reached high values, unusual for the region. The SPI was equal to -1.61, + 0.96 and − 1.45 for whole years 2019, 2020 and 2021, respectively, indicating that 2020 was extremely wet, while 2019 and 2020 were very dry.
The REW trends at daily scale in the three growth seasons are shown in Fig. 3, together with irrigations and precipitations, for FI and RDI treatments. In both treatments the REW increased immediately after any water supply or rainfall and, conversely, decreased quite steeply follow plants’ transpiration. For RDI treatment the soil water recovery after the irrigation interruption period happened in the same day of watering accordingly with Fernández, 2014.
According to irrigation scheduling, before and after the withhold irrigation period, water supply results the same in FI and in RDI. In these periods, FI and RDI trends are almost superimposable. Small differences are due to the different total water availability in the two plots (0.105 and 0.122 m3 m− 3 for FI and RDI, respectively) and to different minimum value of SWC in the two soils (0.144 and 0.151 m3 m− 3 for FI and RDI, respectively). In the FI treatment, REW values did not fallow below 0.3, reaching values near or greater than 1 when soil water conditions were at field capacity or above it, just after frequent irrigations and/or heavy precipitations. In the RDI treatment, REW values was below 0.4 for most of the irrigation season, indicating soil water conditions quite far from the field capacity, except in short periods just after frequent irrigations and/or heavy precipitations. In RDI treatment, REW values decreased when irrigation supply was reduced, in any growth season. The minimum REW values in RDI treatment were 0, 0.1 and 0.15 in the first, second and third season, respectively.
Several studies indicated that when REW value declined below 0.4 the plants are submitted to increasing water stress, mainly for woody species under arid and semiarid Mediterranean conditions (Bréda et al., 1995; Fernández et al., 1997; Grossiord et al., 2015). In the present study, focusing on the RDI period, REW values fell below 0.4 for 7 and 29 days in FI and RDI treatments, respectively in the first season; 13 and 18 days in the second season; 2 and 25 days in the third season.
In Fig. 4 the distribution of z0 values at hourly scale, as number of values in a class of 0.01 m, calculated using Eq. (11), are shown for all seasons. z0 ranged between 0.17 m and 0.31 m, having a mean value of 0.25 m; the highest values correspond to winds in the direction East-West, perpendicular to the tree rows. If a fixed value of z0 is used, for example z0 = 0.1hc, the underestimation on z0 was about − 20% (data not shown), but it is strongly dependent on the wind direction, of course. In fact, when the wind flows perpendicularly to the rows (East - West) the underestimation is until − 47%, while when the wind flow parallelly to the tree rows (North - South) the underestimation is much lower (until − 7%); in our site the predominant winds come from North and South (63% of runs).
b. The canopy conductance and the decoupling factor
Before the presentation of the decoupling factor trend for the two treatments FI and RDI, it is worth to evaluate all terms involved in the transpiration process for this hedgerow olive orchards: i.e., the aerodynamic, the critical and the diffusion canopy conductances (see Eqs. 6 and 10).
The aerodynamic conductance values are shown in Fig. 5 in function of the wind direction for the three seasons. The values calculated using the corrected upscaled wind speed (see Eq. 1.1 in Supplementary material 1) are much lower than the values of ga calculated using the wind speed as measured by the nearby weather station: this last ga overestimates of about 55% the actual ga value above the orchard. The highest ga values were found when the wind flowed from East, in correspondence of the highest values of the roughness length. The ga mean values in the three seasons were equal to 0.10, 0.11 and 0.12 m s− 1 for the years 2019, 2020 and 2021, respectively.
The hourly trends during the day of aerodynamic, critical and canopy conductances, are shown in Fig. 6, for both treatments; the results are divided in three periods: the first one before the withholding irrigation for RDI, the second one corresponding to the withholding irrigation and the third one after it. Note the logarithmic scale of Y axe, for focusing the difference on the order among conductances; the standard deviations were not shown for clarity. The aerodynamic canopy conductance, ga, is in any case much greater than the other conductances, having almost the same trends for all periods and seasons. In fact, it always follows a bell shape (masked of course by the logarithmic scale) with maximum values in early afternoon. The trends of the canopy conductances gcdFI and gcdRDI for FI and RDI treatments, respectively, follow complex paths along the day. Their values were generally higher for RDI treatment than FI in the first and second period, when water was supplied to both plots by irrigation, even if the differences were not significant (P < 0.05). In the withholding irrigation period gcdRDI values decreased with respect to the first period, becoming lower then gcdFI in the first year 2019 and very close to FI treatment in the third year 2021, along the hottest hours. The most significant difference between the diffusive conductance in the two treatments was detected during the night-time, with lower values in FI with respect to RDI only during the first-year night-time. Significantly (P < 0.05) high values during night of gcdFI and gcdRDI, comparable to that found by López-Bernal et al. (2010) for an olive orchard in Spain, are probably due to nocturnal transpiration which would merit to be further investigated. In any case, the values for both treatments present an increasing during early morning, followed by a decreasing in the hottest hours and a further increasing in early afternoon.
The critical conductance g* followed trends with intermediate values between ga and gcd, always having a well-defined bell shape during the day, when the solar radiation is positive. The values of g* are always greater than gcd, except in a few cases around the sunset or sundown; therefore, for this specific hedgerow olive orchard we are in the zone B of the graph in Fig. 1, which theorizes that transpiration decreases with increasing of wind speed. To verify and represent this behaviour, in Fig. 7 the relationships between transpiration (in energy terms) and wind speed are shown for different specific meteorological conditions for both treatments, at hourly scale; for clarity all available values were binned (bin equal to 0.5 m s− 1) and the standard deviations are not indicated. The figure underlines that, at specific given meteorological condition expressed by D and A, the transpiration decreases with the increase of the wind speed, which is a counterintuitive fact rarely illustrated with experimental data (Daudet et al., 1999). This is due, of course, to very lower values of the canopy conductance with respect to the aerodynamic conductance, which means that the canopy is completely coupled to the atmosphere. In this case the transpiration is very little affected by the aerodynamic conductance and completely addressed by the canopy behaviour in terms of stomatal regulation, which in turn depends on the D and, much less, on the available energy.
To dispel any doubts about the orders of magnitude found in the estimated canopy conductance, and to avoid any artifact introduced from the Penman-Monteith inversion mathematical procedure, a comparison between gcd and the canopy stomatal conductance, gsc, directly deduced by measurements at leaves scale and LAI (Eq. 12) was realized, for several days of 2019, when hourly measurements of \(\stackrel{-}{{G}_{s}}\) were carried out along daytime. Figure 8 illustrates the hourly patterns of diffuse canopy and stomatal conductances calculated as mean of available values, for both FI and RDI treatment. From the comparison it is clear that the patterns have similar trend for both variables in the part of day considered, showing a decrease from the morning until the afternoon; however, the values are not significantly different (P < 0.1), although the stomatal canopy conductances showed systematic higher values for both treatments, being 40 and 47% greater than diffuse canopy conductances for FI and RDI treatments, respectively. These differences are probably imputable to huge uncertainties due to the estimation of LAI from NDVI and to the physiological meaning of the two conductances.
The patterns of gcd and ga during the day (Fig. 6) address the trends of the decoupled factor Ω (see Eq. 6), illustrated at hourly scale during the day in Fig. 9, for all available data in the three seasons and both treatments; Ω follows the canopy conductance trends, with double peaks in the morning and in the afternoon, and minimum values in the hottest hours. In any case Ω, as mean of all hourly available data, was always very low, ranging between 0 and 0.05; generally, it is higher in RDI than in FI, at least in the hotter hours for the three years, exactly as for the canopy conductance.
The hourly trend of Ω in the experimental period is illustrated in Fig. 10. It is generally low, but increasing after rain events, reaching value of 0.32–0.55 in the year 2019, 0.2–0.55 in the year 2020; it remains low in the third year also after rain. This corresponds to very high values of canopy conductance just in the first hours after rain (data not shown in detail) when the plants have fully soil water, available energy become fully available, and all surfaces are saturated.
This suggests a link between the decoupling factor and the structure resistance r0, measurable only in these specific conditions of water saturation (see Appendix I). In fact, an estimation of r0 in those conditions brings to a value of 68.8 ± 28.9 s m− 1, corresponding to a canopy conductance of 0.019 ± 0.013 m s− 1, comparable to the aerodynamic conductance values, and permitting a partial coupling to the atmosphere.
The studied hedgerow olive orchard results generally very well coupled to the atmosphere, in any soil water conditions, therefore, the transpiration is mainly addressed by the canopy conductance. For this super high density olive orchard, the decoupling factor Ω is generally very low being in mean equal to 0.015 ± 0.008 and 0.019 ± 0.012 for FI and RDI respectively, because the canopy conductance is much smaller than the aerodynamic conductance in any water and climatic conditions, except when all canopy surfaces are saturated in water. In this case the canopy conductance increases its value due to the contribution of the part of conductance attributable to the structure of the transpiration surfaces. Hence, the canopy structure resistance (conductance) plays a fundamental role in the process of coupling between the canopy and the atmosphere.
The approximations introduced in this study (mainly the neglecting soil evaporation and the adoption of standard Granier’s a and b coefficients in TDM instead of specie-specific values) do not affect the general conclusions, since the aerodynamic conductance determined in the investigated hedgerow olive orchard is always almost two orders greater than the estimated diffuse canopy conductance.
The following points should be considered when the decoupling process is studied for hedgerow tree canopies:
1. The roughness of the canopy depends on the wind direction and the orientation of the row and should be calculated accordingly, avoiding constant values of z0 in the aerodynamic conductance calculation.
2. In the estimation of the aerodynamic conductance the wind speed should be determined above the crop or upscaled from the station to the vegetated crop if the measurement of the wind speed is carried out far from the canopy.
Author Declarations
Funding
This study was fund by and carried out within the MOLTI project (Decree n. 13938, April the 24th 2018) funded by the Italian Ministry of Agriculture (MiPAAF).
Conflicts of interest/Competing interests
The authors, Gianfranco Rana, Gabriele De Carolis, Liliana Gaeta, Sergio Ruggeri, Rossana M. Ferrara, declare no conflict of interest.
Ethics approval/declarations
Not applicable
Consent to participate
The authors, Gianfranco Rana, Gabriele De Carolis, Liliana Gaeta, Sergio Ruggeri, Rossana M. Ferrara, declare their consent to participate to the research on the hedgerow olive orchard in Mediterranean region.
Consent for publication
The authors, Gianfranco Rana, Gabriele De Carolis, Liliana Gaeta, Sergio Ruggeri, Rossana M. Ferrara, declare their consent to publish the study: “Decoupling factor, aerodynamic and canopy conductances of a hedgerow olive orchard under Mediterranean climate”.
Availability of data and material/ Data availability (data transparency, if link please provide the link to access. For further information, go to - https://www.springernature.com/gp/authors/research-data-policy/data-availability-statements/12330880)
Data are available under request to the authors. Pictures and description of used equipment are available under request.
Code availability
Not applicable.
Authors' contributions (all authors should be individually mentioned in the author contribution statement.
Conceptualization: G.R.; Methodology: G.R., L.G., R.M.F.; Investigation: G.R., L.G., S.R., G.D.; Formal analysis: G.R., R.M.F., G.D., Writing - original draft preparation: G.R., R.M.F.; Writing - review and editing: G.R., R.M.F.; Funding acquisition: G.R. All authors have read and agreed to the published version of the manuscript.
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No competing interests reported.