Agricultural Water Management 109 (2012) 11–19
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Evaluation of compensated heat-pulse velocity method to determine vine transpiration using combined measurements of eddy covariance system and microlysimeters a ˜ C. Poblete-Echeverría a,∗ , S. Ortega-Farias a , M. Zuniga , S. Fuentes b a b
Research and Extension Center for Irrigation and Agroclimatology (CITRA), Universidad de Talca, Talca, Chile The University of Adelaide, School of Agriculture, Food and Wine, Plant Research Center, Waite Campus, PMB1, Glen Osmond, S.A. 5064, Australia
a r t i c l e
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Article history: Received 24 August 2011 Accepted 31 January 2012 Available online 3 March 2012 Keywords: Sap flow Compensated heat-pulse velocity Eddy covariance system Microlysimeters Merlot vineyard
a b s t r a c t A field experiment was carried out with the objective to evaluate the compensated heat-pulse velocity (CHPV) method used to determine vine transpiration (Tsap). The performance of the CHPV method was evaluated using daily values of residual transpiration (Tr), obtained as the difference between actual evapotranspiration (ETa) and soil evaporation (Es) (Tr = ETa − Es) measured from an eddy covariance (EC) system and microlysimeters, respectively. Data used in this study were collected over a drip-irrigated Merlot vineyard trained on a vertical shoot positioned (VSP) system during three consecutive growing seasons (2006/2007, 2007/2008 and 2008/2009). Results showed that the best agreement between Tsap and Tr was obtained using correction coefficients for a wound size of 2.4 mm. The comparison between Tsap and Tr indicated that the index of agreement (d) was 0.97, and root mean square error (RMSE), mean absolute error (MAE) and mean bias error (MBE) were 0.22, 0.18 and −0.04 mm day−1 , respectively. Also, the sensitivity analysis of fraction of wood (FM), fraction of water (FL) and factor of thermal properties of the woody matrix (k) suggested that the changes of ±30% have a little effect in the final estimation of daily vine transpiration with variations less than 12%. Finally, major disagreements between Tr and Tsap were observed on partially cloudy days where rapid changes (on 30 min time intervals) of solar radiation produced extreme values of volumetric sap flux density. © 2012 Elsevier B.V. All rights reserved.
1. Introduction To achieve an optimal grapevine (Vitis vinifera L.) production in drip-irrigated vineyards, it is necessary an accurate estimation of the actual evapotranspiration components (ETa) [i.e. vine transpiration and soil evaporation] to assess vineyard water requirements (Trambouze et al., 1998; Yunusa et al., 2004). However, the estimation of ETa components in vineyards is a complex task due to discontinuous canopies and architecture imposed by trellis systems (Heilman et al., 1994; Trambouze and Voltz, 2001; Yunusa et al., 2004). Vineyards trained on vertical shoot positioned system (VSP) present a low fractional cover (fc values about 20–40%), which produce considerable variability in solar radiation exposure of canopies and soil between rows (Heilman et al., 1996; OrtegaFarias et al., 2007). Furthermore, in drip-irrigated vineyards, the wetted fraction of soil surface by drippers is low, reducing considerably soil evaporation (Lascano et al., 1992; Ortega-Farias et al.,
∗ Corresponding author. Tel.: +56 71 200426; fax: +56 71 200212. E-mail addresses:
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[email protected] (C. Poblete-Echeverría). 0378-3774/$ – see front matter © 2012 Elsevier B.V. All rights reserved. doi:10.1016/j.agwat.2012.01.019
2010). Therefore, the quantification of vine transpiration in dripirrigated vineyards under dry atmospheric conditions is highly important, since represents between 70% and 80% of ETa (OrtegaFarias et al., 2008). Currently, several techniques are available to measure transpiration in plants (e.g. lysimeters, volumetric methods and gas canopy analyzers). However, the practical application of the majority of these techniques is limited by its cost, and representativeness (Dugas et al., 1993; Smith and Allen, 1996). Thus, in the last 15 years sap flow sensors have become the most used method to estimate whole-plant transpiration under field conditions for research purposes. The vine transpiration can be determined using heat systems, which use heat as a tracer related to water flow through the sap. These systems can be grouped mainly in three types (GonzálezAltozano et al., 2008): (i) heat-pulse (e.g. Eastham and Gray, 1998; Yunusa et al., 2004; Zhang et al., 2009), (ii) stem heat balance (e.g. Braun and Schmid, 1999a; Trambouze et al., 1998; Trambouze and Voltz, 2001) and (iii) thermal heat dissipation (e.g. Braun and Schmid, 1999b; Lu et al., 2003; Patakas et al., 2005). The use of sap flow sensors in vineyards has been applied mainly to: (i) irrigation management and (ii) calibration and validation
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of transpiration models. For irrigation management, some authors have evaluated the use of sap flow sensors to estimate vine transpiration on different grapevine cultivars and atmospheric conditions. Ginestar et al. (1998) and Eastham and Gray (1998) indicated that sap-flow sensors can provide useful information for irrigation management of vineyards. Thus, different irrigation strategies such as regulated deficit irrigation (RDI) used to control vigor and optimize grape quality can be applied based on vine transpiration measured by sap flow sensors, especially for drip-irrigated vineyards. Other types of studies have been carried out with the objective to calibrate and validate transpiration models over vineyards such as: (i) the use of Granier sap flow sensors to evaluate a transpiration model in non-water stressed vines cv. Sultana (Lu et al., 2003), (ii) the use of the compensated heat-pulse velocity (CHPV) method in a drip-irrigated Merlot vineyard to develop a simple model to estimate vine transpiration based on the Penman–Monteith approach (Pereira et al., 2006) and (iii) the use of heat-pulse sap flow sensors to validate a model based on the two layer model of Shuttleworth and Wallace to estimate vine transpiration in a vineyard (cv. Merlot) under partial root-zone drying (Zhang et al., 2009). All of sap flow techniques, mentioned previously have the potential to estimate transpiration in vineyards. However, heat-pulse techniques are often preferred because of their simple instrumentation, and low power requirements (Swanson, 1994; Smith and Allen, 1996). Also, heat-pulse techniques allows to measure sap flow taking into account the variability of the xylem in the cross section through the use of thermocouples at different depth (Green et al., 2003; González-Altozano et al., 2008). In this regard, CHPV method has been widely used in fruit trees such as: (i) olive trees (Olea europaea L.) (e.g. Moreno et al., 1996; Fernández et al., 2001, 2003, 2006; Giorio and Giorio, 2003; Williams et al., 2004; Tognetti et al., 2004; Pereira et al., 2006, 2007), (ii) peach trees (Prunus persica L.) (e.g. Conejero et al., 2007; González-Altozano et al., 2008), (iii) apple trees (Malus domestica L.) (e.g. Green et al., 1989, 2003; Gong et al., 2007; Pereira et al., 2006, 2007), and grapevines (V. vinifera) (e.g. Eastham and Gray 1998; Ginestar et al., 1998; Yunusa et al., 2004; Pereira et al., 2006; Zhang et al., 2009). Also, González-Altozano et al. (2008) in peach trees indicated that CHPV method was the most sensitive system in detecting water stress under experimental conditions. This characteristic is very important in commercial vineyards, which are managed under RDI for optimizing the water use and grape quality. However, several reports pointed out uncertainties in heatpulse techniques, such as the invasive nature of sap flow sensors, which require the use of semi-empirical coefficients to correct heatpulse velocity (V) (Green et al., 2003). Also, in the formulation of sap flow critical assumptions are made in the estimation of the following parameters: (i) sap flux density (J) (determination of wood (FM) and water (FL) volume fractions and factor of thermal properties of the woody matrix (k) factor), (ii) volumetric sap flow (Q) (determination of sapwood conducting area) and (iii) transpiraˇ tion (scaling up procedure) (Cermák et al., 2004; David et al., 2004; Dragoni et al., 2005; Crosbie et al., 2007). Therefore, it is questionable to assume that sap flow sensors are accurate unless they are tested with an alternative technique. In this regard, Dragoni et al. (2005) evaluated the CHPV method using as a reference the apple transpiration measured from canopy gas exchange chambers. This study indicated that it is necessary to calibrate sap flow measurements to obtain reliable estimates of transpiration rates. In the case of grapevines, Intrigliolo et al. (2009) using heat-pulse sap flow sensors with the Tmax method indicated that the direct sap flow transpiration was not reliable because the differences between transpiration obtained by sap flow sensors and that measured by the canopy gas exchange chambers were considerable and varied from vine to vine. This study suggested that there was not a systematic error in sap flow readings but rather a seemingly random
deviation from the reference values. Therefore, the main objective of this research was to evaluate the use of CHPV method to obtain daily vine transpiration for a drip-irrigated Merlot vineyard trained on VSP under semi-arid conditions. The standard value used for evaluating CHPV method was the residual transpiration obtained as the difference between ETa and Es which were measured using the eddy covariance system and microlysimeters, respectively. Additionally, a sensitivity analysis was performed to evaluate the effect of wound sizes, FM, FL and k in the estimation of Tsap using the CHPV method. 2. Materials and methods 2.1. Study site The field experimental plot was located in the Talca Valley, Maule Region, Chile (35◦ 25 LS; 71◦ 32 LW; 125 m.a.s.l.) during three consecutive growing seasons (2006/2007, 2007/2008 and 2008/2009). The climate is Mediterranean semi-arid with an average daily temperature of 17.1 ◦ C and a mean annual rainfall of 679 mm. The summer period is usually dry and hot (2.2% of annual rainfall) while the spring is wet (16% of annual rainfall). The soil at the vineyard is classified as Talca series (Fine, mixed, thermic Ultic Haploxeralfs) with a clay loam texture and an average bulk density of 1.5 g cm−3 . At the effective rooting depth (0–60 cm), the volumetric soil water content at field capacity and wilting point were 0.36 m3 m−3 and 0.22 m3 m−3 , respectively. The vines were irrigated daily using 4 L h−1 drippers spaced at intervals of 1.5 m. Merlot vines grafted on 101–14 Mgt. (rootstock used to control vigor) were planted in 1999 in north–south rows with a distance between rows equal to 2.5 m, a distance within rows of 1.5 m and were trained on VSP with the main wire 1 m above the soil surface. Shoots were maintained in a vertical plane by three wires, the highest one was located 2 m above the soil surface. 2.2. Complementary field measurements Irrigations were scheduled considering a maximum allowed depletion of water from soil profile of 29% at effective root-zone depth (0.6 m). The volumetric soil water content at the root-zone depth was monitored weekly in 12 sampling points distributed inside the vineyard using a portable Time Domain Reflectometry unit (TRASE, Soil Moisture Corp., Santa Barbara, California, USA). Vine water status was evaluated weekly using the midday stem water potential ( x ) measured by a pressure chamber (PMS600, PMS Instruments Company, Corvallis, Oregon, USA). x was measured on 12 young fully expanded leaves (2 leaves per vine). The leaves were selected from the middle zone of the canopy and were bagged on the shoots in plastic bags coated with aluminum foil for at least 2 h before measurements (Choné et al., 2001). The measurements with pressure chamber were made immediately after cutting leaves from the shoots. This parameter was used to evaluate the level of water stress of the vineyard (Williams and Trout, 2005; Sibille et al., 2007). The average fc of the vineyard was estimated 10 times during each season by measuring the projected area occupied by the vine (fraction of ground shaded by the vertical projection of the canopy at midday), using digital images. The analysis of the digital images (white and black pixel count) was made using a script written in MATLAB® 2009a (The Mathworks Inc., Natick, MA, USA). 2.3. Meteorological and micrometeorological measurements Reference evapotranspiration (ETo) was calculated by Penman–Monteith equation (FAO-56 Method) (Allen et al., 1998) using daily meteorological variables obtained by a nearby
C. Poblete-Echeverría et al. / Agricultural Water Management 109 (2012) 11–19
weather station “Panguilemo” (35◦ 37 LS; 71◦ 59 LW; 118 m a.s.l.). Also, weather variables such as air temperature (Ta) and relative humidity (RH) were measured within the experimental vineyard plot using a Vaisala probe (HMP45C, Campbell Scientific Inc., Logan, Utah, USA). Wind speed (Ws) and wind direction were measured using a cup anemometer and a wind vane (YOUNG, 03101-5, Michigan, USA), respectively. Solar radiation (SR) was measured with a Silicon Pyranometer (LI200X, Campbell Scientific Inc., Logan, Utah, USA) and precipitation was measured with a pluviometer (RGB1, Campbell Scientific Inc., Logan, Utah, USA). All variables were monitored at 4.7 m from the soil surface. Vapor pressure deficit (VPD) was calculated from hourly averages of Ta and HR according to Allen et al. (1998). Soil heat flux (G) was measured by heat flux plates of constant thermal conductivity (HFT3, Campbell Scientific Inc., Logan, UT, USA). Net radiation over the vineyard (Rn) was measured at 4.7 m by a four-way net radiometer (CNR1, Kipp&Zonen Inc., Delftechpark, The Netherlands). Fluxes of latent (LE) and sensible (H) heat were measured using an eddy covariance (EC) system, which consisted of a fast response open-path infrared gas analyzer IRGA (LI-7500, LI-COR Inc., Lincoln, Nebraska, USA) and a three-dimension sonic anemometer (CSAT3, Campbell Scientific Inc., Logan, UT, USA). More details about the distribution and configuration of the sensors used to measure the vineyard energy balance components (G, Rn, H and LE) are presented in Poblete-Echeverria and Ortega-Farias (2009). EC system consists basically in a high-frequency measurement of wind and scalar atmospheric data series (in this study heat and water fluxes). The accuracy of the EC system measurements was evaluated using the energy balance ratio (EBR) calculated on a daily basis as follows: EBR =
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2.5. Sap flow measurements The vine transpiration was determined continually using sap flow sensors (700 SF-100, Tranzflo, New Zealand) inserted in the trunk of eight vines (one sap flow sensors per vine) (Fig. 1). Homogeneous vines near to the EC system were selected with similar stem diameters, ranging from 113 to 124 mm in the first season 110 to 126 mm in the second season and 112 to 122 mm in the third season. In this study the CHPV method was used to measure vine transpiration. This method uses two temperature sensor probes installed asymmetrically above and below a line heater probe (Green et al., 2003). The upstream sensor probe is located 5 mm below the heater probe and the downstream sensor is located 10 mm above the heater probe. On each sensor there are three thermistors. The three thermistors for both upstream and downstream sensors are positioned at 5 mm, 10 mm and 15 mm. The thermistors are paired on a vertical plane to facilitate the measurement of sap flow velocity. A metallic plate with pre-drilled holes was used as a guide to drill the three holes and to assure a parallel displacement of the probe needles; drill bits of 1.8 mm in diameter were used to drill the holes (Fig. 1a). After insertion, the probes were covered with aluminum foil to reduce the effects of ambient temperature and solar radiation (Fig. 1b). A datalogger (CR23X, Campbell Scientific Inc., Logan, UT, USA) was used to trigger heat-pulses and record the time interval between initiation of a heat-pulse and equilibration of the temperature difference between upstream and downstream temperature probes (tz ). Heat-pulses of 0.75 s were automatically triggered every hour throughout the day. The system was powered by acid batteries constantly recharged by solar panels. 2.6. Formulation of CHPV method
H + LE Rn − G
(1)
where H, LE, Rn and G are expressed in MJ m2 day−1 and EBR is the energy balance ratio (dimensionless). Days presenting errors less than of 10% (i.e. EBR >0.9 or EBR
