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Evaluation of an open portable chamber system for measuring cover crop water use in a vineyard and comparison with a mini-lysimeter approach
Agricultural and Forest Meteorology 149 (2009) 1975–1982
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Evaluation of an open portable chamber system for measuring cover crop water use in a vineyard and comparison with a mini-lysimeter approach Michela Centinari a,*, Stefano Poni b, Ilaria Filippetti a, Eugenio Magnanini a, Cesare Intrieri a a b
Dipartimento di Colture Arboree, Universita` di Bologna, Viale G. Fanin 46, 40127 Bologna, Italy Istituto di Frutti-Viticoltura, Universita` Cattolica del Sacro Cuore, Via Emilia Parmense 84, 29100 Piacenza, Italy
A R T I C L E I N F O
A B S T R A C T
Article history: Received 29 October 2008 Received in revised form 12 July 2009 Accepted 13 July 2009
Cover crops are largely used in viticultural areas because of the many positive agronomic and environmental benefits they provide. However, there is insufficient data describing the amount of water they use. A portable chamber used as an open measurement system and its suitability to measure the cover crop evapotranspiration (E) in a vineyard are described in this study. The performance of the chamber was tested by a calibration experiment (R2 = 0.97). The lowest air flow rate used (9.2 l s1) was found to be suitable to limit the chamber from overheating beyond 3.1 K above the outside temperature. Furthermore, an experiment was designed to compare the daily cover crop (Festuca arundinacea var. barfelix) water use measured by the chamber system with measurements using a mini-lysimeter (ML) method and with estimates using the FAO-56 PM equation (Eo). The experiment was carried out in one inter row of a vineyard over the course of 4 days following an irrigation event. Although the field experiment was limited to 4 days, the results obtained together with the calibration trials support the possibility of the chamber being a useful tool for measuring the cover crop E. The ability of the MLs to represent the water use of the cover crop in the rest of the vineyard was limited to the first two days of the experiment, after which time the soil water content inside the containers was significantly (p = 0.007, p = 0.03) lower than in the surrounding field. ß 2009 Elsevier B.V. All rights reserved.
Keywords: Evapotranspiration Open chamber system Mini-lysimeter Cover crop Vineyard
1. Introduction Climate change projections (Intergovernmental Panel on Climate Change, 2007) indicate a rise in the ambient temperature (1.8–4 8C at the end of the 21st century) and in the frequency of drought periods in most of the Mediterranean regions (Iglesias et al., 2007). In a viticultural context, these changes would cause a reduction in the availability of the natural resource of water for the plants and an increase in cases of vine water stress with likely negative influences on the quality of the grapes and wines. In this scenario the demand for irrigation will increase. To more wisely schedule the irrigation events a comprehensive knowledge of the magnitude of water used by all the vineyard components (vines, cover crops, soil) is required. Previous studies have concentrated mainly on quantifying the vine’s transpiration rate using approaches such as the canopy enclosure system (Poni et al., ˜ a and Tarara, 2004) or sap flow gauges (Lascano 1997; Perez Pen et al., 1992; Braun and Schmid, 1999; Dragoni et al., 2006).
* Corresponding author. Tel.: +39 0512096433; fax: +39 0512096401. E-mail addresses: [email protected], [email protected] (M. Centinari). 0168-1923/$ – see front matter ß 2009 Elsevier B.V. All rights reserved. doi:10.1016/j.agrformet.2009.07.005
However, in order to determine the total vineyard evapotranspiration (E), the amount of water used by the soil and cover crop also needs to be evaluated. In fact, the contribution of these two components on the vineyard water use can be significant depending on several factors such as the vine training systems and the distance between the rows. Yet, there is limited data available regarding the amount of water used by the cover crop in a vineyard (Yunusa et al., 1997; Lopes et al., 2004) and similarly limited information concerning the methods available for measuring it. Since water is both transpiring from the grass and evaporating from the underlying soil simultaneously, the two processes are generally analyzed together as E. The cover crop E can be gravimetrically determined by using a mini-lysimeter (ML) approach (Feldhake et al., 1983; Pool and Lakso, 1994; Bremer, 2003), which represents an alternative solution to the lysimeter as it can be used in a limited space situation such as that available between the vine rows. A ML consists of some kind of container filled with a soil core covered with the same vegetation of the surrounding area and inserted in the ground to the point of being even with the adjacent terrain. The containers used may be a PVC pipe capped at one side (Yunusa et al., 1997; Feldhake et al., 1983) or a plastic pot (Pool and Lakso, 1994) provided of holes at the bottom for the drainage of the water. In this method, MLs are
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irrigated, allowed time for the extra water to drain, and then weighed the following days and the loss in mass during the interval between weighing is attributed to E. The portable chamber is another method that can be used in the vineyard to directly measure cover crop E. In this system, the water loss from a crop enclosed into a plastic chamber is determined by monitoring the changes in humidity of an air stream circulating into the chamber. This technique has been widely used in the past to measure the water loss of entire tree canopies (Corelli Grappadelli and Magnanini, 1993; Poni et al., 1997), shrubs (Stannard and Weltz, 2006) and herbaceous crops (Dugas et al., 1997; Burkart et al., 2007; Balogh et al., 2007; Mu¨ller et al., 2009). Enclosing a crop into a plastic container alters the natural microclimatic conditions around the canopy usually by reducing the solar radiation, increasing the air temperature and modifying the air turbulence. Although, the reduction of the incident radiation inside the chamber was found to be partially compensated by an enhancement of the diffuse light fraction (Pickering et al., 1993). There is some controversy concerning the accuracy of the chamber technique when comparisons have been made with other methods of E measurement. Several studies have shown a good agreement between the daily E data obtained with closed chamber systems and the Energy Balance Bowen Ratio method (Steduto et al., 2002; McLeod et al., 2004). Conversely, other studies reported the plants water use as measured by the chamber technique to be much higher than that determined using other methods, showing differences around 25% with the gravimetric approach (Grau, 1995) and about 26% with the eddy-covariance technique (Stannard and Weltz, 2006). Comparing the results obtained in these studies is complicated because of the different characteristics (shape, size, air mixing efficiency) of the chamber used. Despite several critics addressing this methodology, portable chambers have continued to be largely used because they can be adapted to a small plot size, easily transported into the field and then moved for comparing different treatments. The cover crop E can also be indirectly determined by calculating the reference evapotranspiration, denoted as Eo. Eo estimates the amount of water that is lost through evapotranspiration by a reference crop, a well-watered grass. A large number of equations are available for the computation of the Eo, but the international scientific community recommends the use of the FAO-56 Penman-Monteith (PM) combination model as the standard method (Allen et al., 1998). The PM equation includes the meteorological (radiation, air temperature, humidity and wind speed) and the canopy (bulk canopy and aerodynamics resistances) parameters that govern the E from a uniform expanse vegetation (Allen et al., 1998). While the FAO-56 PM method is the most common approach used to estimate the E of a well-watered crop, a certain imprecision may be introduced in this equation because of the canopy resistance parameter (rc) being considered constant (70 s m1) in all climatic conditions (Ventura et al., 1999; Katerij and Rana, 2006). The use of the FAO-56 PM model to estimate the Eo of the cover crop in a vineyard requires the determination of the daily fraction of energy available (net radiation) to the cover crop for the E process. To calculate this parameter the radiation intercepted by the vine’s canopy needs to be measured. Considering the need to determine the reliability of the methods available to measure the cover crop water use in a vineyard, the objectives of this study are: (1) describe the chamber system equipment used in our experiments and report the calibration carried out to determine the consistency of the chamber measurements before using the equipment in the field; (2) analyze the effect of the air flow rate on the cover crop E and on the temperature change inside the chamber; (3) compare the
vineyard cover crop E directly measured using the mini-lysimeters and the chamber technique and indirectly determined by a method used worldwide (Eo). 2. Materials and methods 2.1. Setup, procedure for calculating evapotranspiration and calibration of the chamber system The chamber design consisted of a cylindrical structure made of ultraviolet-B resistant water clean Plexiglas sheets, an outer alternating current fan (Czo´bel et al., 2005) and a infrared gas analyzer (CIRAS1 PP System, Haverhill, MA, USA) (Fig. 1). The chamber had a ground surface area of 0.28 m2, a height of 0.7 m with a total volume of 0.196 m3 and it was operated as an open system. The ambient air was blown into the chamber by the outer fan through a PVC tube (150 mm diameter) located 10 cm above the ground. The air was leaving the chamber through another PVC tube (150 mm diameter) located at the top of the chamber (Fig. 1). The air flow rate (58.7 l s1) could be reduced to 44.4, 27.0, 21.6 and 9.2 l s1 by alternatively placing diaphragms with different size holes on the fan. A turbulence test was performed by introducing 1 l of expanded polystyrene beads into the chamber and it was repeated for each of the air flow rates used throughout the experiments reported in the study. Complete mixing and uniform distribution of the incoming air was observed within a few seconds for each of the air flow rates used. An increase of the beads speed when enhancing the air flow rate was also observed. The rate of the air flow was determined by measuring the time required to fill a cylindrical polyethylene bag (volume of 0.755 m3) placed on the outlet tube (Giuliani et al., 1997). To verify potential error due to back-pressure during bag filling, a differential manometer with a resolution of 0.2 mm of water (FL 1.5, Airflow Developments Ltd., UK) was used to monitor the variation of the pressure differential between the outside and the inside of the chamber during the bag inflation. A slight variation of the pressure differential, lower than 2 mm of water, was observed only for a few seconds as the bag initially began to fill, after which time no more rise of the pressure inside the chamber was noticed and equilibrium was achieved. This pressure variation was considered to introduce a negligible error in the air flow rate calculation.
Fig. 1. Open chamber system positioned over a cover crop plot in one inter row of the vineyard. The main components are: (A) cylindrical Plexiglas structure; (B) outer alternating current fan; (C) chamber inlet; (D) chamber outlet; (E) CIRAS-1 infrared gas analyzer.
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The attenuation of the solar radiation inside the chamber, measured by an RG030 pyranometer (Silimet, Modena, Italy), was found to be an average of 12%. Other studies showed the reduction in the incident solar radiation inside their chambers to be between 10 and 20% (Reicosky et al., 1983; Pickering et al., 1993; Steduto et al., 2002). The ambient temperature at the chamber’s inlet and outlet was monitored using two digital thermometers (Snap-in FM 880LPEX). Both sensors were well ventilated and shielded against direct radiation by reflecting aluminum foil (Poni et al., 1997). While taking measurements, the chamber was positioned over an area with cover crop vegetation and every 10 s a gas sample was taken from the inlet tube close to the fan and another from the outlet tube by the infra-red gas analyzer. The E (E, mol m2 s1) was determined using the following equation: E¼
uo De A P eo
(1)
where De is the water vapor pressure difference between the air sampled at the chamber outlet and inlet (kPa), P is the atmospheric pressure (assumed constant at 101.325 kPa), eo is the water vapor pressure at the chamber outlet (kPa), A is the ground area of the chamber (m2) and uo is the molar flow of air at the outlet tube (mol s1) calculated as: uo ¼
Fo P R To
(2)
where Fo is the air flow rate (m3 s1), To is the air temperature (K) both measured at the outlet tube and R is the gas constant (J mol1 K1). The unit of E (mol m2 s1) was converted and expressed as mm h1. The acquisition of data began 60 s after positioning the chamber over the sampling location, this time interval was necessary to achieve steady state conditions, specifically a stable water flow rate. Since fluctuations of incoming radiation and vapor pressure of the air may considerably bias the chamber E measurements (Mu¨ller et al., 2009), the data were collected only under clear sky conditions. A calibration of the chamber system was carried out over 2 days in May 2007 at the Cadriano experiment station of the University of Bologna, Italy (448300 N, 118240 E). A comparison of the water loss from cloths measured both gravimetrically and with the chamber system was performed. The calibration procedure also corrected for possible vapor adsorption onto the Plexiglas surface. The measurements were conducted outdoors under clear sky conditions and at different times of the day between 9 a.m. and 7 p.m. During the calibration test the solar radiation, measured by placing an RG030 pyranometer (Silimet, Modena, Italy) immediately next to the chamber, ranged between a minimum value of 75 W m2 and a maximum of 800 W m2. Air temperature and air humidity (water vapor pressure), both measured at the chamber’s inlet, ranged from 20 to 35 8C and from 1.1 to 2.1 kPa, respectively. The calibration consisted of 16 weight runs of variable time lengths (10–30 min). The equipment was positioned over a white table board and the cloths were saturated with water, placed on a flat plastic plate and inserted into the chamber. For each weight run the water loss from the cloths was calculated using the equation previously described (Eq. (1)), whereas the gravimetric loss was determined by weighing the cloths. The weighing system consisted of an electronic scale with a resolution of 0.01 g. The data were expressed as hourly rates of evaporation (mm h1). The weight runs were conducted at 2 different air flow rates: 8 determinations were made at 9.2 l s1 and 8 at 21.6 l s1. A simple linear regression analyses was carried out using the ‘reg’ procedure (SAS Institute, NC, USA) to explore the relationships between the water loss estimated with the equation at each air flow rate and the
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corresponding values determined gravimetrically. Since there were no statistically significant differences in slope (p = 0.09) and intercept (p = 0.44) between the 2 regression lines analyzed, the data logged at the different air flows were pooled together. 2.2. Effect of the air flow rate on the cover crop evapotranspiration and on the temperature change inside the chamber 2.2.1. Site description The experiment was carried out on July 26, 2007 in a 2-year-old Sangiovese (Vitis vinifera L.) vineyard, grafted to SO4, in Bologna, Italy (448300 N, 118240 E). The vines were spaced 1 m apart with 2.8 m between the rows with a North–South orientation. The vineyard soil was loamy (39% sand, 39% silt and 22% clay) with an organic matter content of 1.8% and a pH of 7.8. The hydrological constants of the soil, field capacity and wilting point, were 0.29 and 0.14 cm3 cm3, respectively and the total available soil water was 139 l m3. The soil management consisted of weed control under the vines (100 cm) and of a permanent sward (Festuca arundinacea var. barfelix) in the inter row which was sowed in the previous fall. 2.2.2. Evapotranspiration measurements The experiment was conducted during a clear day in the middle of one inter row of the vineyard on two sampling locations with different grass heights (20 and 5 cm). In both sampling locations the chamber measurements were carried out in sunny conditions and repeated 4 times at 2 h intervals starting at 10 a.m. and finishing at 6 p.m. During each group of measurements the cover crop E data were recorded at 5 different air flow rates corresponding to 9.2, 21.6, 27.0, 44.4 and 58.7 l s1. The rate of the air flow was increased every 7 min by placing a diaphragm on the fan with different size holes. After shifting the air flow speed we allowed 60 s before resuming water flux data collection. The E data were averaged with a time interval of 6 min and were expressed as hourly rates (mm h1). 2.2.3. Environmental conditions The soil water content was determined in the 0–30 cm layer using the time domain reflectrometry (TDR; Trase system 1, Soil Moisture Equipment, Santa Barbara, CA, USA): two 30 mm long waveguides were previously installed in both sites analyzed by the chamber. The soil moisture content was found to be 0.26 cm3 cm3 for the first site (grass 20 cm high) and 0.27 cm3 cm3 for the second site (grass 5 cm high), in both cases close to the field capacity (0.29 cm3 cm3) suggesting that water availability was not a limiting factor throughout the course of the experiment. An in situ calibration of the TDR readings against volumetric soil moisture was previously performed by collecting undisturbed soil samples (n = 30) down to 30 cm depth. The soil moisture, determined gravimetrically, was converted to volumetric water content using the soil bulk density value. A highly significant relationship (R2 = 0.86) was found between the volumetric soil water content and the TDR estimates for a 0.16–0.30 cm3 cm3 range. The climatic conditions (solar radiation, air temperature and relative air humidity) were monitored throughout the experiment. The solar radiation was measured by positioning the RG030 pyranometer immediately next to the chamber. Ambient air temperature and relative humidity were recorded by a weather station located in the vineyard 2 m above the ground. During each measurement session and for each of the air flow rates used, the average and maximum air temperature difference (DT) between the chamber’s outlet and inlet were determined as well as the average air vapor pressure deficit (VPD) of the incoming (VPDi) and outgoing (VPDo) air. The VPDi and VPDo (kPa) were
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calculated as: VPD ¼ es e
(3)
where e is the water vapor pressure (kPa) of the gas sampled by the IRGA at the chamber inlet (ei) when calculating the VPDi and at the chamber outlet (eo) when calculating the VPDo. The saturation water vapor pressure (es) (kPa) was calculated as: bT es ¼ aexp T þc
(4)
where the T is temperature (8C) measured at the chamber inlet and outlet when calculating the VPDi and the VPDo, respectively. The coefficient values are a = 0.6108, b = 17.27 and c = 237.7. 2.3. Comparison between the cover crop evapotranspiration directly measured with the mini-lysimeters, the chamber system and indirectly determined using Eo 2.3.1. Site description The experiment was carried out in August 2007 in a 10-year-old Montepulciano (V. vinifera L.) vineyard, grafted to SO4, in Bologna, Italy. The rows were orientated North–South. The vines were spur pruned and spaced 1 m along the row and 2.8 m between the rows. Cordon height was 1 m aboveground and the canopy height was about 2.20 m. The soil was loamy with the following average characteristics: sand 42%; silt 33%; clay 17%; organic matter 1.8%; pH 6. The total available soil water, up to 30 cm depth, was 133 l m3, the field capacity and the wilting point were 0.29 and 0.15 cm3 cm3, respectively. The soil management consisted of a well established permanent sward (F. arundinacea var. barfelix) in each inter row and of weed control under the vines (100 cm). An overhead irrigation system was installed between the 2 rows where the experiment was carried out. 2.3.2. Evapotranspiration measurements and determinations The E measurements were taken in one inter row of the vineyard over the course of 4 days using three MLs and the portable chamber. The MLs consisted of plastic pots 0.25 m long and with a diameter of 0.30 m installed in the middle of the inter row spaced 3 m apart. The bottom of the pots had several holes for the drainage of the excess water. A vineyard soil core with a well established cover crop (F. arundinacea var. barfelix) was transplanted into each ML. Care was taken to assure that the grass inside and outside the pots had the same characteristics (height and same species). Two days before starting the experiment the MLs and the surrounding areas were irrigated with about 40 mm of water in order to bring the soil moisture inside and outside the pots to similar values. Throughout the experiment, every morning at 9 a.m. the MLs were lifted from the ground, weighed and returned to their locations; the same measurements were repeated every evening around 7 p.m. when the inter row was completely shaded. The weighing system consisted of an electronic scale with a resolution of 1 g. The daily cover crop E (mm d1) was calculated as DW/S, where DW is the change in the ML mass between the 2 daily weights, and S is the area of the ML. Over the course of the 4 days the chamber measurements were taken at hourly intervals from 9 a.m. to 7 p.m. in 3 different plots located in the middle of the inter row in close proximity to the MLs. One measurement from each site was completed in 10 min and the E value was expressed as hourly rate (mm h1). The rate of the volume flow blown through the chamber was 9.2 l s1. To obtain cumulative daily cover crop E (mm d1) from the instantaneous measurements the area under the curve produced by plotting the time of the day versus the hourly E was calculated (McLeod et al., 2004).
Daily reference evapotranspiration (Eo) was determined for the 4 days during which we conducted the measurements. Eo was calculated from the FAO-56 PM equation (Allen et al., 1998) using the hourly data (air temperature, humidity, wind speed) recorded by a weather station located in close proximity to the vineyard. The net radiation values introduced into the equation were estimated using the methodology proposed by Allen et al. (1998). The daily net radiation values were derived from the shortwave solar radiation data collected in the inter row by a scanner bar 2.2 m long equipped with 64 phototransistors (BPW20R Silicon PN Photodiode, Vishay Telefunken, Heilbronn, Germany). A full description of the system components and functioning is found in Poni et al. (2003). Each phototransistor was previously calibrated using an RG030 pyranometer (Silimet, Modena, Italia). A highly significant (0.98 < R2 < 0.99) linear relationship was found when regressing the voltage output (mV) of each sensor versus the incident radiation estimated by the pyranometer for a 0–980 W m2 range. For the duration of the experiment the scanner bar was positioned in the same inter row as the MLs and it was kept horizontal, 10 cm above the ground and perpendicular in respect to the vines. The bar was connected to a CR10 WP datalogger (Campbell Scientific Ltd., Loughborough, UK) for automatically recording the light readings every 5 min. Data from the sensors located in the same area of the inter row as the chamber and MLs were used to calculate the average daily solar radiation. 2.3.3. Soil water content determinations The soil water content was determined by time domain reflectrometry (TDR; Trase system 1, Soil Moisture Equipment, Santa Barbara, CA, USA): two 150 mm long waveguides were carefully installed inside each ML and the same number of probes were installed to correspond with each site to be analyzed by the chamber. Soil moisture readings were taken every morning we weighed the MLs. An in situ calibration of the TDR readings against volumetric soil moisture was previously performed by collecting undisturbed soil samples (n = 21) down to 30 cm depth. The soil moisture gravimetrically determined was converted to volumetric water content using the soil bulk density value. A highly significant relationship (R2 = 0.89) was found between the volumetric soil water content and the TDR estimates for a 0.15–0.30 cm3 cm3 range. 2.4. Statistical analyses Regression analyses were carried out using the ‘reg’ procedure (SAS Institute, Cary, NC, USA) to explore relationships between variables (Sections 3.1 and 3.2). Where the relationship appeared to depart from linearity, statistical tests with nonlinear equations were carried out. For the ML and chamber E (mm d1) data and for soil water content data reported in Section 3.3 the analyses of variance was performed separately for each date using the Mixed procedure of the SAS statistical package. Differences between E means and soil water content means were assessed by a t-test. 3. Results and discussion 3.1. Calibration of the chamber system The plot of the gravimetric evaporation data versus the corresponding values obtained using the chamber system yielded a highly significant linear relationship (Fig. 2). The gravimetric data were expressed as a function of the chamber estimates and the resulting regression equation (0.97x + 0.046) was used to correct the hourly E. The calibration results show the ability of the chamber system to reliably determine the rate of evaporation, although the data distribution does show the chamber values have
M. Centinari et al. / Agricultural and Forest Meteorology 149 (2009) 1975–1982
Fig. 2. Regression analyses between the cloth water loss (hourly averages of evaporation) measured gravimetrically and estimated by the chamber at two different air flow rates (9.2 and 21.6 l s1). Linear regression equation is y = 0.97x + 0.0462, R2 = 0.97. Dashing indicates the 1:1 line.
a tendency to slightly underestimate the actual gravimetric water loss (Fig. 2). 3.2. Effect of the air flow rate on the cover crop evapotranspiration and on the temperature change inside the chamber In both sampling locations a highly significant nonlinear relationship was found between the cover crop E and the rate of the air flow (Fig. 3A). For each site, the E values showed an asymptotic trend with increasing air flow rate. Enhancing the air turbulence inside the chamber is expected to increase the rate of the E by increasing the boundary layer conductance, but in our condition at the air flow rate of 44.4 and 58.7 l s1 the E values tended to be constant (Fig. 3A). One possible explanation could be that the high boundary layer conductance may have affected the
Fig. 3. Effect of the air flow rate (Fo) on (A) the cover crop E and on (B) the average air temperature difference (DT) between the chamber’s outlet and inlet measured on two sites with the different grass heights, 5 (&) and 20 cm (*). The E and DT data are mean values S.D. The interpolation models for (A) are y = 1.52 1.33 exp (x/ 37.3); R2 = 0.99 (grass 5 cm high) and y = 1.70 1.36 exp (x/37.60); R2 = 0.97 (grass 20 cm high). The data were collected between 12 p.m. and 2 p.m.
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grass stomatal conductivity. The rapid replacement of moist air near the leaf surfaces with drier air may have induced a partial stomatal closure (Idso et al., 1988). Fig. 3 shows the results of the measurement session carried out between 12 p.m. and 2 p.m., however, a similar relationship was also obtained from the other 3 groups of measurements that were repeated at different times of the day (data not shown). The E dependency on the air flow rate (Fig. 3A) suggests that the air turbulence regime inside the chamber must correspond to that outside in order to increase the ability of this method to give actual cover crop E values with pinpoint accuracy. For both sampling locations, the difference in the air temperature between the chamber outlet and inlet (DT) decreased by enhancing the air flow rate (Fig. 3B). On the site with the grass 5 cm in height the DT data recorded between 12 p.m. and 2 p.m. ranged from an average of +2.8 K when using the lowest air flow rate (9.2 l s1) to an average of +0.4 K when using the highest one (58.7 l s1). The maximum DT observed for the lowest and highest air flow rates were +3.1 K and +0.5 K, respectively. A direct dependence between the air flow rate and the DT has been reported by several studies (Poni et al., 1999; Alterio et al., 2006; Burkart et al., 2007). Garcia et al. (1990) determined that in absence of any evaporation, an air flow rate which ensures 2.5 changes of chamber air volume min1 must be used to limit the increase in the air temperature to 5 K in their chamber. In our study, the use of the lowest air flow rate (9.2 l s1 corresponding to 2.8 changes of chamber air volume min1) over a grass vegetation 20 and 5 cm high resulted in an average increase in the air temperature inside the chamber of 2.3 and 2.8 K, respectively. Presumably, the higher leaf area (data not reported) and rate of transpiration of the grass 20 cm high in respect to the grass 5 cm high (Fig. 3A) explain the lower DT recorded in the first sampling location as compared to the second one (Fig. 3B). During the collection of the data reported in Fig. 3 the solar radiation, air temperature and relative air humidity ranged between 765 and 816 W m2, 32 and 34 8C, 32 and 38%, respectively. Under such hot climatic conditions, the air flow rate is the best way to maintain a high boundary layer conductance inside the chamber so as to limit overheating (Poni et al., 1999). However, besides a possible offset of the boundary layer conductance by a partial stomatal closure previously reported, it should be kept in mind that enhancing the air flow rate causes a decrease in the water vapor pressure difference (De) between the chamber outlet and inlet. Setting the air flow at the maximum rate may not allow the detection of a small De signal that may occur for
Fig. 4. Effect of the air flow rate (Fo) on the average water vapor pressure difference (De) between the chamber’s outlet and inlet on two cover crop sites with the different grass heights, 5 (&) and 20 cm (*). The De are mean values S.D. The data were collected between 12 p.m. and 2 p.m.
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instance during situations of low evaporative demand or drought stress. The data reported in Fig. 4, collected between 12 p.m. and 2 p.m., show at the highest air flow rate (58.7 l s1) the De being an average value of 0.25 kPa in the site with the grass 20 cm high and 0.22 kPa in the site with the grass 5 cm high. In our situation the reported values are well within the measurement accuracy of the IRGA (precision of 0.003 kPa at 0 kPa and 0.006 kPa at 7.5 kPa) (CIRAS1 Operator’s manual version 1.20). As well, our findings match those of Balogh et al. (2007) who used a chamber and ventilation system with identical characteristics. However, an increase in the variability of the De values has been observed when enhancing the air flow rates (Fig. 4). In the site with the grass 5 cm in height the coefficient of variation ranged from 0.8% when using an air flow rate of 9.2 l s1 to 16% when using an air flow rate of 58.7 l s1, indicating an increase in measurement error with an increase of the air flow rate. The use of a low air flow rate may cause a substantial increase in the water vapor pressure inside the chamber which can lead to a lower VPD and E inside compared to those outside. In the present study, as expected, the water vapor pressure inside the chamber, measured at the chamber outlet (eo), is higher than that outside determined at the chamber inlet (ei), especially when using the lowest air flow rate (data not reported). However, on both sampling locations (grass 20 cm and 5 cm high) and for each of the air flow rates used in the experiment, the VPD values of the air entering (VPDi) and leaving the chamber (VPDo) were quite similar, with the majority of the VPDo data being slightly lower than the VPDi data (Fig. 5). On the site with the grass 20 cm high the average VPDi values ranged between 3.4 and 3.8 kPa and the VPDo values between 3.2 and 3.7 kPa. Presumably, the effect of the rise in air humidity (water vapor pressure) on the VPDo calculation tends to be off set by the increase in the air temperature simultaneously occurring inside the chamber. Small variations of VPDi values are due to normal climatic fluctuations which took place during the 2 h period in which the data were collected. No relationship was found between the VPDo and the rate of air flow used. Since the use of the lowest air flow rate did not cause the chamber to overheat and did not result in a significant change of the VPD inside the chamber we continued using it in the following experiment (Section 3.3) with the intent to match as much as possible the low wind speed condition that is typical of the vineyards in our area.
Fig. 5. (A and B) Comparison of VPD values calculated at the chamber’s inlet (VPDi) (open symbol) and at the chamber’s outlet (VPDo) (closed symbol) for each of the air flow rates (Fo) used during the experiment. The data were collected between 12 p.m. and 2 p.m. on two cover crop sites, one (A) with grass 5 cm in height (&) and the other (B) with the grass 20 cm in height (*). The VPD data are mean values S.D.
3.3. Comparison between the cover crop evapotranspiration directly measured with the mini-lysimeters, the chamber system and indirectly determined using Eo On both the first and second day of measurements (August 13 and 14) no statistically significant differences (p = 0.11 and p = 0.10) were found between the daily E of the cover crop determined using the two direct methods (MLs and chamber) (Fig. 6A). On these two dates a reasonable agreement was also observed between measured and estimated (Eo) water use data (Fig. 6A). On August 13 the daily E values determined with the MLs, the chamber and the Eo were 3.64, 3.12 and 2.97 mm d1, respectively and on August 14 3.36, 2.92 and 2.74 mm d1, respectively. In contrast, on the following 2 dates (August 16 and 17) the MLs water loss values (2.73 and 1.96 mm d1) were significantly lower (p = 0.02 and p = 0.0002) than those determined with the chamber system (3.64 and 4.29 mm d1) (Fig. 6A). At the same time the E measured gravimetrically were noticeably lower than those calculated using the PM equation (3.32 and 3.98 mm d1) (Fig. 6A). The divergence in the E data obtained using the ML approach and the other 2 methods can be explained by the soil moisture trend observed inside the pots in contrast to that of the surrounding soil over the course of the experiment (Fig. 6B). In fact, 5 days following the irrigation event (August 16) the ML water content in the first 15 cm of soil started to be significantly lower (p = 0.007) than that measured in the middle of the inter row at the same depth (Fig. 6B). The rapid reduction of the water available inside the MLs explains the continuous decrease in the daily E of the cover crop inside the pots over the course of the experiment (Fig. 6A). Meanwhile, in the area adjacent to the MLs, where the soil moisture was not a limiting factor (Fig. 6B), the cover crop water use determined by the chamber system increased in the last 2 days of measurements due to higher daily radiation available on those dates comparing to the first 2 (Fig. 6). The short lifetime of the MLs is due to the fact that the pot is a semi-closed system which does not allow lateral and vertical movements of water from the surrounding soil and therefore the
Fig. 6. (A) Vertical bars represent the daily E for the cover crop measured with 3 mini-lysimeters (&), the open portable chamber (&) and estimated by the FAO-56 PM equation ( ) over the course of 4 days. Points indicate the daily average solar radiation (Rs) (&) and VPD (*). (B) Volumetric water content (%) in the first 15 cm of soil inside the MLs (&) and in the surrounding area (*) for the same 4 days. Dashed lines are the volumetric water content values for the wilting point and for the field capacity. The E and volumetric soil water content data are mean values S.E. (n = 3 plots). For a given day different letters indicate significant differences (t-test).
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replenishment of water lost for E that would be expected in a more natural environment. Bremer (2003) reported similar results using the ML approach to investigate the E of a tall fescue (F. arundinacea Schreb.). In his study the volumetric soil water content in the MLs and in the adjacent area was similar for about 3 days following an irrigation event, after which time the MLs started to dry faster. To be sure that the data from the MLs are representative of the rest of the field they should be replaced with new ones every few days (Yunusa et al., 1993; Gong et al., 2007); however, when the soil in the field becomes dry and hard, taking further samples of undisturbed soil cores may be very difficult (Trambouze et al., 1998). Furthermore it is a labor intensive procedure. While the duration of our experiment was limited to 4 days, based on our results, the chamber seems to have the potential to be a useful tool for measuring cover crop E. Throughout the experiment the daily cover crop E data obtained with the chamber system compared well with the Eo data estimated using the FAO56 PM equation. The chamber values were slightly higher, by an average of 7%, compared to the Eo (Fig. 6A). In the present study, a certain imprecision in the Eo calculation may be due to the fact that only the solar radiation, used to determine net radiation, was directly measured in the inter row of the vineyard. All the other meteorological data used in the FAO-56 PM equation (air temperature, air humidity and wind speed) were recorded in close proximity to the experiment location (about 20 m) by a weather station located 2 m above the ground. While the water used by the cover crop is driven mainly by net radiation (McNaughton and Jarvis, 1991) possible differences in air temperature, humidity and wind speed between the weather station and experiment locations may have caused some errors. The daily cover crop E measured using the open chamber was comparable with the values obtained from the gravimetric method only for the first 2 days of measurements, when the MLs soil moisture content was not significantly different from that of the surrounding soil, although the chamber data were consistently lower by an average value of 13% (Fig. 6A). A good agreement between the E data obtained using a chamber system and a lysimeter was observed in studies carried out by Pickering et al. (1993) and by Steduto et al. (2002). In the specific, Steduto et al. (2002) reported a tendency of the chamber to underestimate by 4.2% the daily E gravimetrically determined. On the other hand, Grau (1995) found the E of potted bird’s-foot trefoil plants measured with the chamber to be an average of 25% greater than that measured when weighing the pots. As previously reported the different characteristics and efficiency in the air mixing of the chambers used in the various studies complicate comparisons between results. 4. Conclusions The open chamber described in the paper was successfully calibrated by comparing the water loss from clothes measured gravimetrically with the values obtained using the chamber system. The temperature increase inside the chamber was found to be related to the rate of the air flow used and throughout the experiment the outlet/inlet temperature difference was never more than 3.1 K. The consistency of our chamber measurements was confirmed in the field by a comparison with the ML method and the Eo predictions. A good agreement was obtained between the daily cover crop E determined with the chamber and the values estimated using the FAO-56 PM model throughout the 4 days of the experiment, with the chamber values being higher by an average of 7% the Eo estimates. A reasonable agreement was also observed between the daily cover crop E data obtained using the chamber and 3 MLs in the days immediately following an irrigation event when the soil moisture inside the pots was not significantly
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different from that in the rest of the inter row. Furthermore, we found the chamber equipment to be relatively quick and easy to move within the field making data collection in multiple locations possible. However, in order to treat the E data obtained using this method as absolute values the wind speed inside the chamber should be measured and adjusted to the natural conditions. The other direct method analyzed in this study was based on the use of MLs. As previously stated, this technique was able to realistically measure the cover crop water use in the vineyard only for a few days following an irrigation event. At this point the soil inside the MLs began to dry significantly faster than that of the surrounding area. However, this method can still be a useful tool for comparing the E performance among different treatments of grass in a nonlimiting soil moisture condition, close to the field capacity. Finally, the results obtained suggest that it might be possible to use the FAO-56 PM model to indirectly determine cover crop E in a vineyard in a non water stressed conditions by using measurements of radiation available between the vines rows as well as a few other climatic parameters (wind speed, air temperature and humidity). Acknowledgements We gratefully acknowledge G. Allegro, B. Bucchetti, E. Colucci and G. Valentini for their assistance in fieldwork. The English corrections of William Boone (Cornell University) is gratefully acknowledged. References Allen, R.G., Pereira, L.S., Raes, D., Smith, M., 1998. Crop Evapotranspiration-guidelines for computing crop water requirements. FAO Irrigation and Drainage Paper No. 56. Rome, Italy. Alterio, G., Giorio, P., Sorrentino, G., 2006. Open-system chamber for measurements of gas exchanges at plant level. Environ. Sci. Technol. 40, 1950–1955. Balogh, J., Nagy, Z., Fo´ti, Sz., Pinte´r, K., Czo´bel, Sz., Pe´li, E.R., Acosta, M., Marek, M.V., Csintalan, Zs., Tuba, Z., 2007. Comparison of CO2 and H2O fluxes over grassland vegetations measured by the eddy-covariance technique and by open system chamber. Photosynthetica 45 (2), 288–292. Bremer, D.J., 2003. Evaluation of microlysimeters used in turfgrass ET studies using the dual-probe heat-pulse technique. Agron. J. 95 (6), 1625–1632. Braun, P., Schmid, J., 1999. Sap flow measurements in grapevines (Vitis vinifera L.) 2. Granier measurements. Plant Soil 215, 47–55. Burkart, S., Manderscheid, R., Weigel, H.J., 2007. Design and performance of a portable gas exchange chamber system for CO2-and H2O-flux measurements in crop canopies. Environ. Exper. Bot. 61, 25–34. Corelli Grappadelli, L., Magnanini, E., 1993. A whole-tree system for gas-exchange studies. HortScience 28 (1), 41–45. Czo´bel, Sz., Fo´ti, Sz., Balogh, J., Nagy, Z., Bartha, S., Tuba, Z., 2005. Chamber series and space-scale analysis of CO2 gas-exchange in grassland vegetation: a novel approach. Photosynthetica 43 (2), 267–272. Dragoni, D., Lakso, A.N., Piccioni, R.M., Tarara, J.M., 2006. Transpiration of grapevines in the humid northeastern United States. Am. J. Enol. Vitic. 57 (4), 460– 467. Dugas, W.A., Reicosky, D.C., Kiniry, J.R., 1997. Chamber and micrometeorological measurements of CO2 and H2O fluxes for three C4 grasses. Agric. For. Meteorol. 83, 113–133. Feldhake, C.M., Danielson, R.E., Butler, J.D., 1983. Turfgrass evapotranspiration. I. Factors influencing rate in urban environments. Agron. J. 75, 824–830. Garcia, R.L., Norman, J.M., McDermitt, D.K., 1990. Measurements of canopy gas exchange using an open chamber system. Rem. Sens. Rev. 5 (1), 141–162. Giuliani, R., Nerozzi, F., Magnanini, E., Corelli Grappadelli, L., 1997. Influence of environmental and plant factors on canopy photosynthesis and transpiration of apple trees. Tree Physiol. 17 (10), 637–645. Gong, D., Kang, S., Yao, L., Zhang, L., 2007. Estimation of evapotranspiration and its components from an apple orchard in northwest China using sap flow and water balance methods. Hydrol. Process 21 (7), 931–938. Grau, A., 1995. A closed chamber technique for field measurement of gas exchange of forage canopies. N.Z. J. Agric. Res. 38, 71–77. Idso, S.B., Allen, S.G., Choudhury, B.J., 1988. Problems with porometry: measuring stomatal conductances of potentially transpiring plants. Agric. For. Meteor. 43, 49–58. Iglesias, A., Garrote, L., Flores, F., Moneo, M., 2007. Challenges to manage the risk of water scarcity and climate change in the Mediterranean. Water Resour. Manag. 21, 775–788. Katerij, N., Rana, G., 2006. Modelling evapotranspiration of six irrigated crops under Mediterranean climate conditions. Agric. For. Meteorol. 138, 142–155.
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Lascano, R.J., Baumhardt, R.L., Lipe, W.N., 1992. Measurement of water flow in young grapevines using the stem heat balance method. Am. J. Enol. Vitic. 43 (2), 159– 165. Lopes, C., Monteiro, A., Ru¨ckert, F.E., Gruber, B., Steinberg, B., Schultz, H.R., 2004. Transpiration of grapevines and co-habitating cover crop and weed species in a vineyard. A ‘‘snapshot’’ at diurnal trends. Vitis 43 (2), 111–117. McLeod, M.K., Daniel, H., Faulkner, R., Murison, R., 2004. Evaluation of an enclosed portable chamber to measure crop and pasture actual ET at small scale. Agric. Water Manag. 67 (1), 15–34. McNaughton, K.G., Jarvis, P.G., 1991. Effects of spatial scale on stomatal control of transpiration. Agric. For. Meteorol. 54, 279–302. Mu¨ller, J., Eschenro¨der, A., Diepenbrock, W., 2009. Through-flow chamber CO2/ H2O canopy gas exchange system—construction, microclimate, errors, and measurements in a barley (Hordeum vulgare L.) field. Agric. For. Meteorol. 149, 214–229. ˜ a, J., Tarara, J.M., 2004. A portable whole canopy gas exchange system for Perez Pen several mature field-grown grapevines. Vitis 43 (1), 7–14. Pickering, N.B., Jones, J.W., Boote, K.J., 1993. Evaluation of the portable chamber technique for measuring canopy gas exchange by crops. Agric. For. Meteorol. 63, 239–254. Pool, R.M., Lakso, A.N., 1994. Cover crop management for vineyards. N.Y.State. I.P.M. Report, 14–18. Poni, S., Magnanini, E., Rebucci, B., 1997. An automated chamber system for measurements of whole-vine gas-exchange. HortScience 32 (1), 64–67.
Poni, S., Intrieri, C., Magnanini, E., 1999. Set-up, calibration and testing of a custombuilt system for measuring whole-canopy transpiration in grapevine. Acta Hort. 493, 149–159. Poni, S., Magnanini, E., Bernizzoni, F., 2003. Degree of correlation between total light interception and whole-canopy net CO2 exchange rate in two grapevine growth systems. Aust. J. Grape Wine Res. 9 (1), 2–11. Reicosky, D.C., Sharratt, B.S., Ljungkull, J.E., Baker, D.G., 1983. Comparison of alfalfa ET measured by weighing lysimeter and a portable chamber. Agric. For. Meteorol. 28, 205–211. Stannard, D.I., Weltz, M.A., 2006. Partitioning ET in sparsely vegetated rangeland using a portable chamber. Water Resour. Res. 42 (2), W02413. ¨ ., Albrizio, R., Kanber, R., 2002. Automated closed-system Steduto, P., C¸etinko¨ku¨, O canopy-chamber for continuous field-crop monitoring of CO2 and H2O fluxes. Agric. For. Meteorol. 111, 171–186. Trambouze, W., Bertuzzi, P., Voltz, M., 1998. Comparison of methods for estimating actual evapotranspiration in a row-cropped vineyard. Agric. For. Meteorol. 91, 193–208. Ventura, F., Spano, D., Duce, P., Snyder, R.L., 1999. An evaluation of common evapotranspiration equations. Irrig. Sci. 18 (4), 163–170. Yunusa, I.A.M., Sedgley, R.H., Belford, R.K., Tennant, D., 1993. Dynamics of water use in a dry Mediterranean environment. I. Soil evaporation little affected by presence of plant canopy. Agric. Water Manag. 24, 205–224. Yunusa, I.A.M., Walker, R.R., Guy, I.R., 1997. Partitioning of seasonal evapotranspiration from a commercial furrow-irrigated Sultana vineyard. Irrig. Sci. 18, 45–54.
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Evaluation of an open portable chamber system for measuring cover crop water use in a vineyard and comparison with a mini-lysimeter approach Michela Centinari a,*, Stefano Poni b, Ilaria Filippetti a, Eugenio Magnanini a, Cesare Intrieri a a b
Dipartimento di Colture Arboree, Universita` di Bologna, Viale G. Fanin 46, 40127 Bologna, Italy Istituto di Frutti-Viticoltura, Universita` Cattolica del Sacro Cuore, Via Emilia Parmense 84, 29100 Piacenza, Italy
A R T I C L E I N F O
A B S T R A C T
Article history: Received 29 October 2008 Received in revised form 12 July 2009 Accepted 13 July 2009
Cover crops are largely used in viticultural areas because of the many positive agronomic and environmental benefits they provide. However, there is insufficient data describing the amount of water they use. A portable chamber used as an open measurement system and its suitability to measure the cover crop evapotranspiration (E) in a vineyard are described in this study. The performance of the chamber was tested by a calibration experiment (R2 = 0.97). The lowest air flow rate used (9.2 l s1) was found to be suitable to limit the chamber from overheating beyond 3.1 K above the outside temperature. Furthermore, an experiment was designed to compare the daily cover crop (Festuca arundinacea var. barfelix) water use measured by the chamber system with measurements using a mini-lysimeter (ML) method and with estimates using the FAO-56 PM equation (Eo). The experiment was carried out in one inter row of a vineyard over the course of 4 days following an irrigation event. Although the field experiment was limited to 4 days, the results obtained together with the calibration trials support the possibility of the chamber being a useful tool for measuring the cover crop E. The ability of the MLs to represent the water use of the cover crop in the rest of the vineyard was limited to the first two days of the experiment, after which time the soil water content inside the containers was significantly (p = 0.007, p = 0.03) lower than in the surrounding field. ß 2009 Elsevier B.V. All rights reserved.
Keywords: Evapotranspiration Open chamber system Mini-lysimeter Cover crop Vineyard
1. Introduction Climate change projections (Intergovernmental Panel on Climate Change, 2007) indicate a rise in the ambient temperature (1.8–4 8C at the end of the 21st century) and in the frequency of drought periods in most of the Mediterranean regions (Iglesias et al., 2007). In a viticultural context, these changes would cause a reduction in the availability of the natural resource of water for the plants and an increase in cases of vine water stress with likely negative influences on the quality of the grapes and wines. In this scenario the demand for irrigation will increase. To more wisely schedule the irrigation events a comprehensive knowledge of the magnitude of water used by all the vineyard components (vines, cover crops, soil) is required. Previous studies have concentrated mainly on quantifying the vine’s transpiration rate using approaches such as the canopy enclosure system (Poni et al., ˜ a and Tarara, 2004) or sap flow gauges (Lascano 1997; Perez Pen et al., 1992; Braun and Schmid, 1999; Dragoni et al., 2006).
* Corresponding author. Tel.: +39 0512096433; fax: +39 0512096401. E-mail addresses: [email protected], [email protected] (M. Centinari). 0168-1923/$ – see front matter ß 2009 Elsevier B.V. All rights reserved. doi:10.1016/j.agrformet.2009.07.005
However, in order to determine the total vineyard evapotranspiration (E), the amount of water used by the soil and cover crop also needs to be evaluated. In fact, the contribution of these two components on the vineyard water use can be significant depending on several factors such as the vine training systems and the distance between the rows. Yet, there is limited data available regarding the amount of water used by the cover crop in a vineyard (Yunusa et al., 1997; Lopes et al., 2004) and similarly limited information concerning the methods available for measuring it. Since water is both transpiring from the grass and evaporating from the underlying soil simultaneously, the two processes are generally analyzed together as E. The cover crop E can be gravimetrically determined by using a mini-lysimeter (ML) approach (Feldhake et al., 1983; Pool and Lakso, 1994; Bremer, 2003), which represents an alternative solution to the lysimeter as it can be used in a limited space situation such as that available between the vine rows. A ML consists of some kind of container filled with a soil core covered with the same vegetation of the surrounding area and inserted in the ground to the point of being even with the adjacent terrain. The containers used may be a PVC pipe capped at one side (Yunusa et al., 1997; Feldhake et al., 1983) or a plastic pot (Pool and Lakso, 1994) provided of holes at the bottom for the drainage of the water. In this method, MLs are
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irrigated, allowed time for the extra water to drain, and then weighed the following days and the loss in mass during the interval between weighing is attributed to E. The portable chamber is another method that can be used in the vineyard to directly measure cover crop E. In this system, the water loss from a crop enclosed into a plastic chamber is determined by monitoring the changes in humidity of an air stream circulating into the chamber. This technique has been widely used in the past to measure the water loss of entire tree canopies (Corelli Grappadelli and Magnanini, 1993; Poni et al., 1997), shrubs (Stannard and Weltz, 2006) and herbaceous crops (Dugas et al., 1997; Burkart et al., 2007; Balogh et al., 2007; Mu¨ller et al., 2009). Enclosing a crop into a plastic container alters the natural microclimatic conditions around the canopy usually by reducing the solar radiation, increasing the air temperature and modifying the air turbulence. Although, the reduction of the incident radiation inside the chamber was found to be partially compensated by an enhancement of the diffuse light fraction (Pickering et al., 1993). There is some controversy concerning the accuracy of the chamber technique when comparisons have been made with other methods of E measurement. Several studies have shown a good agreement between the daily E data obtained with closed chamber systems and the Energy Balance Bowen Ratio method (Steduto et al., 2002; McLeod et al., 2004). Conversely, other studies reported the plants water use as measured by the chamber technique to be much higher than that determined using other methods, showing differences around 25% with the gravimetric approach (Grau, 1995) and about 26% with the eddy-covariance technique (Stannard and Weltz, 2006). Comparing the results obtained in these studies is complicated because of the different characteristics (shape, size, air mixing efficiency) of the chamber used. Despite several critics addressing this methodology, portable chambers have continued to be largely used because they can be adapted to a small plot size, easily transported into the field and then moved for comparing different treatments. The cover crop E can also be indirectly determined by calculating the reference evapotranspiration, denoted as Eo. Eo estimates the amount of water that is lost through evapotranspiration by a reference crop, a well-watered grass. A large number of equations are available for the computation of the Eo, but the international scientific community recommends the use of the FAO-56 Penman-Monteith (PM) combination model as the standard method (Allen et al., 1998). The PM equation includes the meteorological (radiation, air temperature, humidity and wind speed) and the canopy (bulk canopy and aerodynamics resistances) parameters that govern the E from a uniform expanse vegetation (Allen et al., 1998). While the FAO-56 PM method is the most common approach used to estimate the E of a well-watered crop, a certain imprecision may be introduced in this equation because of the canopy resistance parameter (rc) being considered constant (70 s m1) in all climatic conditions (Ventura et al., 1999; Katerij and Rana, 2006). The use of the FAO-56 PM model to estimate the Eo of the cover crop in a vineyard requires the determination of the daily fraction of energy available (net radiation) to the cover crop for the E process. To calculate this parameter the radiation intercepted by the vine’s canopy needs to be measured. Considering the need to determine the reliability of the methods available to measure the cover crop water use in a vineyard, the objectives of this study are: (1) describe the chamber system equipment used in our experiments and report the calibration carried out to determine the consistency of the chamber measurements before using the equipment in the field; (2) analyze the effect of the air flow rate on the cover crop E and on the temperature change inside the chamber; (3) compare the
vineyard cover crop E directly measured using the mini-lysimeters and the chamber technique and indirectly determined by a method used worldwide (Eo). 2. Materials and methods 2.1. Setup, procedure for calculating evapotranspiration and calibration of the chamber system The chamber design consisted of a cylindrical structure made of ultraviolet-B resistant water clean Plexiglas sheets, an outer alternating current fan (Czo´bel et al., 2005) and a infrared gas analyzer (CIRAS1 PP System, Haverhill, MA, USA) (Fig. 1). The chamber had a ground surface area of 0.28 m2, a height of 0.7 m with a total volume of 0.196 m3 and it was operated as an open system. The ambient air was blown into the chamber by the outer fan through a PVC tube (150 mm diameter) located 10 cm above the ground. The air was leaving the chamber through another PVC tube (150 mm diameter) located at the top of the chamber (Fig. 1). The air flow rate (58.7 l s1) could be reduced to 44.4, 27.0, 21.6 and 9.2 l s1 by alternatively placing diaphragms with different size holes on the fan. A turbulence test was performed by introducing 1 l of expanded polystyrene beads into the chamber and it was repeated for each of the air flow rates used throughout the experiments reported in the study. Complete mixing and uniform distribution of the incoming air was observed within a few seconds for each of the air flow rates used. An increase of the beads speed when enhancing the air flow rate was also observed. The rate of the air flow was determined by measuring the time required to fill a cylindrical polyethylene bag (volume of 0.755 m3) placed on the outlet tube (Giuliani et al., 1997). To verify potential error due to back-pressure during bag filling, a differential manometer with a resolution of 0.2 mm of water (FL 1.5, Airflow Developments Ltd., UK) was used to monitor the variation of the pressure differential between the outside and the inside of the chamber during the bag inflation. A slight variation of the pressure differential, lower than 2 mm of water, was observed only for a few seconds as the bag initially began to fill, after which time no more rise of the pressure inside the chamber was noticed and equilibrium was achieved. This pressure variation was considered to introduce a negligible error in the air flow rate calculation.
Fig. 1. Open chamber system positioned over a cover crop plot in one inter row of the vineyard. The main components are: (A) cylindrical Plexiglas structure; (B) outer alternating current fan; (C) chamber inlet; (D) chamber outlet; (E) CIRAS-1 infrared gas analyzer.
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The attenuation of the solar radiation inside the chamber, measured by an RG030 pyranometer (Silimet, Modena, Italy), was found to be an average of 12%. Other studies showed the reduction in the incident solar radiation inside their chambers to be between 10 and 20% (Reicosky et al., 1983; Pickering et al., 1993; Steduto et al., 2002). The ambient temperature at the chamber’s inlet and outlet was monitored using two digital thermometers (Snap-in FM 880LPEX). Both sensors were well ventilated and shielded against direct radiation by reflecting aluminum foil (Poni et al., 1997). While taking measurements, the chamber was positioned over an area with cover crop vegetation and every 10 s a gas sample was taken from the inlet tube close to the fan and another from the outlet tube by the infra-red gas analyzer. The E (E, mol m2 s1) was determined using the following equation: E¼
uo De A P eo
(1)
where De is the water vapor pressure difference between the air sampled at the chamber outlet and inlet (kPa), P is the atmospheric pressure (assumed constant at 101.325 kPa), eo is the water vapor pressure at the chamber outlet (kPa), A is the ground area of the chamber (m2) and uo is the molar flow of air at the outlet tube (mol s1) calculated as: uo ¼
Fo P R To
(2)
where Fo is the air flow rate (m3 s1), To is the air temperature (K) both measured at the outlet tube and R is the gas constant (J mol1 K1). The unit of E (mol m2 s1) was converted and expressed as mm h1. The acquisition of data began 60 s after positioning the chamber over the sampling location, this time interval was necessary to achieve steady state conditions, specifically a stable water flow rate. Since fluctuations of incoming radiation and vapor pressure of the air may considerably bias the chamber E measurements (Mu¨ller et al., 2009), the data were collected only under clear sky conditions. A calibration of the chamber system was carried out over 2 days in May 2007 at the Cadriano experiment station of the University of Bologna, Italy (448300 N, 118240 E). A comparison of the water loss from cloths measured both gravimetrically and with the chamber system was performed. The calibration procedure also corrected for possible vapor adsorption onto the Plexiglas surface. The measurements were conducted outdoors under clear sky conditions and at different times of the day between 9 a.m. and 7 p.m. During the calibration test the solar radiation, measured by placing an RG030 pyranometer (Silimet, Modena, Italy) immediately next to the chamber, ranged between a minimum value of 75 W m2 and a maximum of 800 W m2. Air temperature and air humidity (water vapor pressure), both measured at the chamber’s inlet, ranged from 20 to 35 8C and from 1.1 to 2.1 kPa, respectively. The calibration consisted of 16 weight runs of variable time lengths (10–30 min). The equipment was positioned over a white table board and the cloths were saturated with water, placed on a flat plastic plate and inserted into the chamber. For each weight run the water loss from the cloths was calculated using the equation previously described (Eq. (1)), whereas the gravimetric loss was determined by weighing the cloths. The weighing system consisted of an electronic scale with a resolution of 0.01 g. The data were expressed as hourly rates of evaporation (mm h1). The weight runs were conducted at 2 different air flow rates: 8 determinations were made at 9.2 l s1 and 8 at 21.6 l s1. A simple linear regression analyses was carried out using the ‘reg’ procedure (SAS Institute, NC, USA) to explore the relationships between the water loss estimated with the equation at each air flow rate and the
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corresponding values determined gravimetrically. Since there were no statistically significant differences in slope (p = 0.09) and intercept (p = 0.44) between the 2 regression lines analyzed, the data logged at the different air flows were pooled together. 2.2. Effect of the air flow rate on the cover crop evapotranspiration and on the temperature change inside the chamber 2.2.1. Site description The experiment was carried out on July 26, 2007 in a 2-year-old Sangiovese (Vitis vinifera L.) vineyard, grafted to SO4, in Bologna, Italy (448300 N, 118240 E). The vines were spaced 1 m apart with 2.8 m between the rows with a North–South orientation. The vineyard soil was loamy (39% sand, 39% silt and 22% clay) with an organic matter content of 1.8% and a pH of 7.8. The hydrological constants of the soil, field capacity and wilting point, were 0.29 and 0.14 cm3 cm3, respectively and the total available soil water was 139 l m3. The soil management consisted of weed control under the vines (100 cm) and of a permanent sward (Festuca arundinacea var. barfelix) in the inter row which was sowed in the previous fall. 2.2.2. Evapotranspiration measurements The experiment was conducted during a clear day in the middle of one inter row of the vineyard on two sampling locations with different grass heights (20 and 5 cm). In both sampling locations the chamber measurements were carried out in sunny conditions and repeated 4 times at 2 h intervals starting at 10 a.m. and finishing at 6 p.m. During each group of measurements the cover crop E data were recorded at 5 different air flow rates corresponding to 9.2, 21.6, 27.0, 44.4 and 58.7 l s1. The rate of the air flow was increased every 7 min by placing a diaphragm on the fan with different size holes. After shifting the air flow speed we allowed 60 s before resuming water flux data collection. The E data were averaged with a time interval of 6 min and were expressed as hourly rates (mm h1). 2.2.3. Environmental conditions The soil water content was determined in the 0–30 cm layer using the time domain reflectrometry (TDR; Trase system 1, Soil Moisture Equipment, Santa Barbara, CA, USA): two 30 mm long waveguides were previously installed in both sites analyzed by the chamber. The soil moisture content was found to be 0.26 cm3 cm3 for the first site (grass 20 cm high) and 0.27 cm3 cm3 for the second site (grass 5 cm high), in both cases close to the field capacity (0.29 cm3 cm3) suggesting that water availability was not a limiting factor throughout the course of the experiment. An in situ calibration of the TDR readings against volumetric soil moisture was previously performed by collecting undisturbed soil samples (n = 30) down to 30 cm depth. The soil moisture, determined gravimetrically, was converted to volumetric water content using the soil bulk density value. A highly significant relationship (R2 = 0.86) was found between the volumetric soil water content and the TDR estimates for a 0.16–0.30 cm3 cm3 range. The climatic conditions (solar radiation, air temperature and relative air humidity) were monitored throughout the experiment. The solar radiation was measured by positioning the RG030 pyranometer immediately next to the chamber. Ambient air temperature and relative humidity were recorded by a weather station located in the vineyard 2 m above the ground. During each measurement session and for each of the air flow rates used, the average and maximum air temperature difference (DT) between the chamber’s outlet and inlet were determined as well as the average air vapor pressure deficit (VPD) of the incoming (VPDi) and outgoing (VPDo) air. The VPDi and VPDo (kPa) were
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calculated as: VPD ¼ es e
(3)
where e is the water vapor pressure (kPa) of the gas sampled by the IRGA at the chamber inlet (ei) when calculating the VPDi and at the chamber outlet (eo) when calculating the VPDo. The saturation water vapor pressure (es) (kPa) was calculated as: bT es ¼ aexp T þc
(4)
where the T is temperature (8C) measured at the chamber inlet and outlet when calculating the VPDi and the VPDo, respectively. The coefficient values are a = 0.6108, b = 17.27 and c = 237.7. 2.3. Comparison between the cover crop evapotranspiration directly measured with the mini-lysimeters, the chamber system and indirectly determined using Eo 2.3.1. Site description The experiment was carried out in August 2007 in a 10-year-old Montepulciano (V. vinifera L.) vineyard, grafted to SO4, in Bologna, Italy. The rows were orientated North–South. The vines were spur pruned and spaced 1 m along the row and 2.8 m between the rows. Cordon height was 1 m aboveground and the canopy height was about 2.20 m. The soil was loamy with the following average characteristics: sand 42%; silt 33%; clay 17%; organic matter 1.8%; pH 6. The total available soil water, up to 30 cm depth, was 133 l m3, the field capacity and the wilting point were 0.29 and 0.15 cm3 cm3, respectively. The soil management consisted of a well established permanent sward (F. arundinacea var. barfelix) in each inter row and of weed control under the vines (100 cm). An overhead irrigation system was installed between the 2 rows where the experiment was carried out. 2.3.2. Evapotranspiration measurements and determinations The E measurements were taken in one inter row of the vineyard over the course of 4 days using three MLs and the portable chamber. The MLs consisted of plastic pots 0.25 m long and with a diameter of 0.30 m installed in the middle of the inter row spaced 3 m apart. The bottom of the pots had several holes for the drainage of the excess water. A vineyard soil core with a well established cover crop (F. arundinacea var. barfelix) was transplanted into each ML. Care was taken to assure that the grass inside and outside the pots had the same characteristics (height and same species). Two days before starting the experiment the MLs and the surrounding areas were irrigated with about 40 mm of water in order to bring the soil moisture inside and outside the pots to similar values. Throughout the experiment, every morning at 9 a.m. the MLs were lifted from the ground, weighed and returned to their locations; the same measurements were repeated every evening around 7 p.m. when the inter row was completely shaded. The weighing system consisted of an electronic scale with a resolution of 1 g. The daily cover crop E (mm d1) was calculated as DW/S, where DW is the change in the ML mass between the 2 daily weights, and S is the area of the ML. Over the course of the 4 days the chamber measurements were taken at hourly intervals from 9 a.m. to 7 p.m. in 3 different plots located in the middle of the inter row in close proximity to the MLs. One measurement from each site was completed in 10 min and the E value was expressed as hourly rate (mm h1). The rate of the volume flow blown through the chamber was 9.2 l s1. To obtain cumulative daily cover crop E (mm d1) from the instantaneous measurements the area under the curve produced by plotting the time of the day versus the hourly E was calculated (McLeod et al., 2004).
Daily reference evapotranspiration (Eo) was determined for the 4 days during which we conducted the measurements. Eo was calculated from the FAO-56 PM equation (Allen et al., 1998) using the hourly data (air temperature, humidity, wind speed) recorded by a weather station located in close proximity to the vineyard. The net radiation values introduced into the equation were estimated using the methodology proposed by Allen et al. (1998). The daily net radiation values were derived from the shortwave solar radiation data collected in the inter row by a scanner bar 2.2 m long equipped with 64 phototransistors (BPW20R Silicon PN Photodiode, Vishay Telefunken, Heilbronn, Germany). A full description of the system components and functioning is found in Poni et al. (2003). Each phototransistor was previously calibrated using an RG030 pyranometer (Silimet, Modena, Italia). A highly significant (0.98 < R2 < 0.99) linear relationship was found when regressing the voltage output (mV) of each sensor versus the incident radiation estimated by the pyranometer for a 0–980 W m2 range. For the duration of the experiment the scanner bar was positioned in the same inter row as the MLs and it was kept horizontal, 10 cm above the ground and perpendicular in respect to the vines. The bar was connected to a CR10 WP datalogger (Campbell Scientific Ltd., Loughborough, UK) for automatically recording the light readings every 5 min. Data from the sensors located in the same area of the inter row as the chamber and MLs were used to calculate the average daily solar radiation. 2.3.3. Soil water content determinations The soil water content was determined by time domain reflectrometry (TDR; Trase system 1, Soil Moisture Equipment, Santa Barbara, CA, USA): two 150 mm long waveguides were carefully installed inside each ML and the same number of probes were installed to correspond with each site to be analyzed by the chamber. Soil moisture readings were taken every morning we weighed the MLs. An in situ calibration of the TDR readings against volumetric soil moisture was previously performed by collecting undisturbed soil samples (n = 21) down to 30 cm depth. The soil moisture gravimetrically determined was converted to volumetric water content using the soil bulk density value. A highly significant relationship (R2 = 0.89) was found between the volumetric soil water content and the TDR estimates for a 0.15–0.30 cm3 cm3 range. 2.4. Statistical analyses Regression analyses were carried out using the ‘reg’ procedure (SAS Institute, Cary, NC, USA) to explore relationships between variables (Sections 3.1 and 3.2). Where the relationship appeared to depart from linearity, statistical tests with nonlinear equations were carried out. For the ML and chamber E (mm d1) data and for soil water content data reported in Section 3.3 the analyses of variance was performed separately for each date using the Mixed procedure of the SAS statistical package. Differences between E means and soil water content means were assessed by a t-test. 3. Results and discussion 3.1. Calibration of the chamber system The plot of the gravimetric evaporation data versus the corresponding values obtained using the chamber system yielded a highly significant linear relationship (Fig. 2). The gravimetric data were expressed as a function of the chamber estimates and the resulting regression equation (0.97x + 0.046) was used to correct the hourly E. The calibration results show the ability of the chamber system to reliably determine the rate of evaporation, although the data distribution does show the chamber values have
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Fig. 2. Regression analyses between the cloth water loss (hourly averages of evaporation) measured gravimetrically and estimated by the chamber at two different air flow rates (9.2 and 21.6 l s1). Linear regression equation is y = 0.97x + 0.0462, R2 = 0.97. Dashing indicates the 1:1 line.
a tendency to slightly underestimate the actual gravimetric water loss (Fig. 2). 3.2. Effect of the air flow rate on the cover crop evapotranspiration and on the temperature change inside the chamber In both sampling locations a highly significant nonlinear relationship was found between the cover crop E and the rate of the air flow (Fig. 3A). For each site, the E values showed an asymptotic trend with increasing air flow rate. Enhancing the air turbulence inside the chamber is expected to increase the rate of the E by increasing the boundary layer conductance, but in our condition at the air flow rate of 44.4 and 58.7 l s1 the E values tended to be constant (Fig. 3A). One possible explanation could be that the high boundary layer conductance may have affected the
Fig. 3. Effect of the air flow rate (Fo) on (A) the cover crop E and on (B) the average air temperature difference (DT) between the chamber’s outlet and inlet measured on two sites with the different grass heights, 5 (&) and 20 cm (*). The E and DT data are mean values S.D. The interpolation models for (A) are y = 1.52 1.33 exp (x/ 37.3); R2 = 0.99 (grass 5 cm high) and y = 1.70 1.36 exp (x/37.60); R2 = 0.97 (grass 20 cm high). The data were collected between 12 p.m. and 2 p.m.
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grass stomatal conductivity. The rapid replacement of moist air near the leaf surfaces with drier air may have induced a partial stomatal closure (Idso et al., 1988). Fig. 3 shows the results of the measurement session carried out between 12 p.m. and 2 p.m., however, a similar relationship was also obtained from the other 3 groups of measurements that were repeated at different times of the day (data not shown). The E dependency on the air flow rate (Fig. 3A) suggests that the air turbulence regime inside the chamber must correspond to that outside in order to increase the ability of this method to give actual cover crop E values with pinpoint accuracy. For both sampling locations, the difference in the air temperature between the chamber outlet and inlet (DT) decreased by enhancing the air flow rate (Fig. 3B). On the site with the grass 5 cm in height the DT data recorded between 12 p.m. and 2 p.m. ranged from an average of +2.8 K when using the lowest air flow rate (9.2 l s1) to an average of +0.4 K when using the highest one (58.7 l s1). The maximum DT observed for the lowest and highest air flow rates were +3.1 K and +0.5 K, respectively. A direct dependence between the air flow rate and the DT has been reported by several studies (Poni et al., 1999; Alterio et al., 2006; Burkart et al., 2007). Garcia et al. (1990) determined that in absence of any evaporation, an air flow rate which ensures 2.5 changes of chamber air volume min1 must be used to limit the increase in the air temperature to 5 K in their chamber. In our study, the use of the lowest air flow rate (9.2 l s1 corresponding to 2.8 changes of chamber air volume min1) over a grass vegetation 20 and 5 cm high resulted in an average increase in the air temperature inside the chamber of 2.3 and 2.8 K, respectively. Presumably, the higher leaf area (data not reported) and rate of transpiration of the grass 20 cm high in respect to the grass 5 cm high (Fig. 3A) explain the lower DT recorded in the first sampling location as compared to the second one (Fig. 3B). During the collection of the data reported in Fig. 3 the solar radiation, air temperature and relative air humidity ranged between 765 and 816 W m2, 32 and 34 8C, 32 and 38%, respectively. Under such hot climatic conditions, the air flow rate is the best way to maintain a high boundary layer conductance inside the chamber so as to limit overheating (Poni et al., 1999). However, besides a possible offset of the boundary layer conductance by a partial stomatal closure previously reported, it should be kept in mind that enhancing the air flow rate causes a decrease in the water vapor pressure difference (De) between the chamber outlet and inlet. Setting the air flow at the maximum rate may not allow the detection of a small De signal that may occur for
Fig. 4. Effect of the air flow rate (Fo) on the average water vapor pressure difference (De) between the chamber’s outlet and inlet on two cover crop sites with the different grass heights, 5 (&) and 20 cm (*). The De are mean values S.D. The data were collected between 12 p.m. and 2 p.m.
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instance during situations of low evaporative demand or drought stress. The data reported in Fig. 4, collected between 12 p.m. and 2 p.m., show at the highest air flow rate (58.7 l s1) the De being an average value of 0.25 kPa in the site with the grass 20 cm high and 0.22 kPa in the site with the grass 5 cm high. In our situation the reported values are well within the measurement accuracy of the IRGA (precision of 0.003 kPa at 0 kPa and 0.006 kPa at 7.5 kPa) (CIRAS1 Operator’s manual version 1.20). As well, our findings match those of Balogh et al. (2007) who used a chamber and ventilation system with identical characteristics. However, an increase in the variability of the De values has been observed when enhancing the air flow rates (Fig. 4). In the site with the grass 5 cm in height the coefficient of variation ranged from 0.8% when using an air flow rate of 9.2 l s1 to 16% when using an air flow rate of 58.7 l s1, indicating an increase in measurement error with an increase of the air flow rate. The use of a low air flow rate may cause a substantial increase in the water vapor pressure inside the chamber which can lead to a lower VPD and E inside compared to those outside. In the present study, as expected, the water vapor pressure inside the chamber, measured at the chamber outlet (eo), is higher than that outside determined at the chamber inlet (ei), especially when using the lowest air flow rate (data not reported). However, on both sampling locations (grass 20 cm and 5 cm high) and for each of the air flow rates used in the experiment, the VPD values of the air entering (VPDi) and leaving the chamber (VPDo) were quite similar, with the majority of the VPDo data being slightly lower than the VPDi data (Fig. 5). On the site with the grass 20 cm high the average VPDi values ranged between 3.4 and 3.8 kPa and the VPDo values between 3.2 and 3.7 kPa. Presumably, the effect of the rise in air humidity (water vapor pressure) on the VPDo calculation tends to be off set by the increase in the air temperature simultaneously occurring inside the chamber. Small variations of VPDi values are due to normal climatic fluctuations which took place during the 2 h period in which the data were collected. No relationship was found between the VPDo and the rate of air flow used. Since the use of the lowest air flow rate did not cause the chamber to overheat and did not result in a significant change of the VPD inside the chamber we continued using it in the following experiment (Section 3.3) with the intent to match as much as possible the low wind speed condition that is typical of the vineyards in our area.
Fig. 5. (A and B) Comparison of VPD values calculated at the chamber’s inlet (VPDi) (open symbol) and at the chamber’s outlet (VPDo) (closed symbol) for each of the air flow rates (Fo) used during the experiment. The data were collected between 12 p.m. and 2 p.m. on two cover crop sites, one (A) with grass 5 cm in height (&) and the other (B) with the grass 20 cm in height (*). The VPD data are mean values S.D.
3.3. Comparison between the cover crop evapotranspiration directly measured with the mini-lysimeters, the chamber system and indirectly determined using Eo On both the first and second day of measurements (August 13 and 14) no statistically significant differences (p = 0.11 and p = 0.10) were found between the daily E of the cover crop determined using the two direct methods (MLs and chamber) (Fig. 6A). On these two dates a reasonable agreement was also observed between measured and estimated (Eo) water use data (Fig. 6A). On August 13 the daily E values determined with the MLs, the chamber and the Eo were 3.64, 3.12 and 2.97 mm d1, respectively and on August 14 3.36, 2.92 and 2.74 mm d1, respectively. In contrast, on the following 2 dates (August 16 and 17) the MLs water loss values (2.73 and 1.96 mm d1) were significantly lower (p = 0.02 and p = 0.0002) than those determined with the chamber system (3.64 and 4.29 mm d1) (Fig. 6A). At the same time the E measured gravimetrically were noticeably lower than those calculated using the PM equation (3.32 and 3.98 mm d1) (Fig. 6A). The divergence in the E data obtained using the ML approach and the other 2 methods can be explained by the soil moisture trend observed inside the pots in contrast to that of the surrounding soil over the course of the experiment (Fig. 6B). In fact, 5 days following the irrigation event (August 16) the ML water content in the first 15 cm of soil started to be significantly lower (p = 0.007) than that measured in the middle of the inter row at the same depth (Fig. 6B). The rapid reduction of the water available inside the MLs explains the continuous decrease in the daily E of the cover crop inside the pots over the course of the experiment (Fig. 6A). Meanwhile, in the area adjacent to the MLs, where the soil moisture was not a limiting factor (Fig. 6B), the cover crop water use determined by the chamber system increased in the last 2 days of measurements due to higher daily radiation available on those dates comparing to the first 2 (Fig. 6). The short lifetime of the MLs is due to the fact that the pot is a semi-closed system which does not allow lateral and vertical movements of water from the surrounding soil and therefore the
Fig. 6. (A) Vertical bars represent the daily E for the cover crop measured with 3 mini-lysimeters (&), the open portable chamber (&) and estimated by the FAO-56 PM equation ( ) over the course of 4 days. Points indicate the daily average solar radiation (Rs) (&) and VPD (*). (B) Volumetric water content (%) in the first 15 cm of soil inside the MLs (&) and in the surrounding area (*) for the same 4 days. Dashed lines are the volumetric water content values for the wilting point and for the field capacity. The E and volumetric soil water content data are mean values S.E. (n = 3 plots). For a given day different letters indicate significant differences (t-test).
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replenishment of water lost for E that would be expected in a more natural environment. Bremer (2003) reported similar results using the ML approach to investigate the E of a tall fescue (F. arundinacea Schreb.). In his study the volumetric soil water content in the MLs and in the adjacent area was similar for about 3 days following an irrigation event, after which time the MLs started to dry faster. To be sure that the data from the MLs are representative of the rest of the field they should be replaced with new ones every few days (Yunusa et al., 1993; Gong et al., 2007); however, when the soil in the field becomes dry and hard, taking further samples of undisturbed soil cores may be very difficult (Trambouze et al., 1998). Furthermore it is a labor intensive procedure. While the duration of our experiment was limited to 4 days, based on our results, the chamber seems to have the potential to be a useful tool for measuring cover crop E. Throughout the experiment the daily cover crop E data obtained with the chamber system compared well with the Eo data estimated using the FAO56 PM equation. The chamber values were slightly higher, by an average of 7%, compared to the Eo (Fig. 6A). In the present study, a certain imprecision in the Eo calculation may be due to the fact that only the solar radiation, used to determine net radiation, was directly measured in the inter row of the vineyard. All the other meteorological data used in the FAO-56 PM equation (air temperature, air humidity and wind speed) were recorded in close proximity to the experiment location (about 20 m) by a weather station located 2 m above the ground. While the water used by the cover crop is driven mainly by net radiation (McNaughton and Jarvis, 1991) possible differences in air temperature, humidity and wind speed between the weather station and experiment locations may have caused some errors. The daily cover crop E measured using the open chamber was comparable with the values obtained from the gravimetric method only for the first 2 days of measurements, when the MLs soil moisture content was not significantly different from that of the surrounding soil, although the chamber data were consistently lower by an average value of 13% (Fig. 6A). A good agreement between the E data obtained using a chamber system and a lysimeter was observed in studies carried out by Pickering et al. (1993) and by Steduto et al. (2002). In the specific, Steduto et al. (2002) reported a tendency of the chamber to underestimate by 4.2% the daily E gravimetrically determined. On the other hand, Grau (1995) found the E of potted bird’s-foot trefoil plants measured with the chamber to be an average of 25% greater than that measured when weighing the pots. As previously reported the different characteristics and efficiency in the air mixing of the chambers used in the various studies complicate comparisons between results. 4. Conclusions The open chamber described in the paper was successfully calibrated by comparing the water loss from clothes measured gravimetrically with the values obtained using the chamber system. The temperature increase inside the chamber was found to be related to the rate of the air flow used and throughout the experiment the outlet/inlet temperature difference was never more than 3.1 K. The consistency of our chamber measurements was confirmed in the field by a comparison with the ML method and the Eo predictions. A good agreement was obtained between the daily cover crop E determined with the chamber and the values estimated using the FAO-56 PM model throughout the 4 days of the experiment, with the chamber values being higher by an average of 7% the Eo estimates. A reasonable agreement was also observed between the daily cover crop E data obtained using the chamber and 3 MLs in the days immediately following an irrigation event when the soil moisture inside the pots was not significantly
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different from that in the rest of the inter row. Furthermore, we found the chamber equipment to be relatively quick and easy to move within the field making data collection in multiple locations possible. However, in order to treat the E data obtained using this method as absolute values the wind speed inside the chamber should be measured and adjusted to the natural conditions. The other direct method analyzed in this study was based on the use of MLs. As previously stated, this technique was able to realistically measure the cover crop water use in the vineyard only for a few days following an irrigation event. At this point the soil inside the MLs began to dry significantly faster than that of the surrounding area. However, this method can still be a useful tool for comparing the E performance among different treatments of grass in a nonlimiting soil moisture condition, close to the field capacity. Finally, the results obtained suggest that it might be possible to use the FAO-56 PM model to indirectly determine cover crop E in a vineyard in a non water stressed conditions by using measurements of radiation available between the vines rows as well as a few other climatic parameters (wind speed, air temperature and humidity). Acknowledgements We gratefully acknowledge G. Allegro, B. Bucchetti, E. Colucci and G. Valentini for their assistance in fieldwork. The English corrections of William Boone (Cornell University) is gratefully acknowledged. References Allen, R.G., Pereira, L.S., Raes, D., Smith, M., 1998. Crop Evapotranspiration-guidelines for computing crop water requirements. FAO Irrigation and Drainage Paper No. 56. Rome, Italy. Alterio, G., Giorio, P., Sorrentino, G., 2006. Open-system chamber for measurements of gas exchanges at plant level. Environ. Sci. Technol. 40, 1950–1955. Balogh, J., Nagy, Z., Fo´ti, Sz., Pinte´r, K., Czo´bel, Sz., Pe´li, E.R., Acosta, M., Marek, M.V., Csintalan, Zs., Tuba, Z., 2007. Comparison of CO2 and H2O fluxes over grassland vegetations measured by the eddy-covariance technique and by open system chamber. Photosynthetica 45 (2), 288–292. Bremer, D.J., 2003. Evaluation of microlysimeters used in turfgrass ET studies using the dual-probe heat-pulse technique. Agron. J. 95 (6), 1625–1632. Braun, P., Schmid, J., 1999. Sap flow measurements in grapevines (Vitis vinifera L.) 2. Granier measurements. Plant Soil 215, 47–55. Burkart, S., Manderscheid, R., Weigel, H.J., 2007. Design and performance of a portable gas exchange chamber system for CO2-and H2O-flux measurements in crop canopies. Environ. Exper. Bot. 61, 25–34. Corelli Grappadelli, L., Magnanini, E., 1993. A whole-tree system for gas-exchange studies. HortScience 28 (1), 41–45. Czo´bel, Sz., Fo´ti, Sz., Balogh, J., Nagy, Z., Bartha, S., Tuba, Z., 2005. Chamber series and space-scale analysis of CO2 gas-exchange in grassland vegetation: a novel approach. Photosynthetica 43 (2), 267–272. Dragoni, D., Lakso, A.N., Piccioni, R.M., Tarara, J.M., 2006. Transpiration of grapevines in the humid northeastern United States. Am. J. Enol. Vitic. 57 (4), 460– 467. Dugas, W.A., Reicosky, D.C., Kiniry, J.R., 1997. Chamber and micrometeorological measurements of CO2 and H2O fluxes for three C4 grasses. Agric. For. Meteorol. 83, 113–133. Feldhake, C.M., Danielson, R.E., Butler, J.D., 1983. Turfgrass evapotranspiration. I. Factors influencing rate in urban environments. Agron. J. 75, 824–830. Garcia, R.L., Norman, J.M., McDermitt, D.K., 1990. Measurements of canopy gas exchange using an open chamber system. Rem. Sens. Rev. 5 (1), 141–162. Giuliani, R., Nerozzi, F., Magnanini, E., Corelli Grappadelli, L., 1997. Influence of environmental and plant factors on canopy photosynthesis and transpiration of apple trees. Tree Physiol. 17 (10), 637–645. Gong, D., Kang, S., Yao, L., Zhang, L., 2007. Estimation of evapotranspiration and its components from an apple orchard in northwest China using sap flow and water balance methods. Hydrol. Process 21 (7), 931–938. Grau, A., 1995. A closed chamber technique for field measurement of gas exchange of forage canopies. N.Z. J. Agric. Res. 38, 71–77. Idso, S.B., Allen, S.G., Choudhury, B.J., 1988. Problems with porometry: measuring stomatal conductances of potentially transpiring plants. Agric. For. Meteor. 43, 49–58. Iglesias, A., Garrote, L., Flores, F., Moneo, M., 2007. Challenges to manage the risk of water scarcity and climate change in the Mediterranean. Water Resour. Manag. 21, 775–788. Katerij, N., Rana, G., 2006. Modelling evapotranspiration of six irrigated crops under Mediterranean climate conditions. Agric. For. Meteorol. 138, 142–155.
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