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    245 Soil Wetting Pattern Monitoring is a Key Factor in Precision Irrigation of Grapevines S. Fuentes 1 , G. Rogers 2,4 , J. Conroy 1 , S. Ortega-Farias 3  and C. Acevedo 3   1  Centre for Horticulture and Plant Sciences (CHAPS), University of Western Sydney, Australia 2  AHR Crop Science, University of Sydney NSW 2006, Australia 3  Research and Extension Centre for Irrigation and Agroclimatology (CITRA) University of Talca, Chile 4  Faculty of Agriculture, Food and Natural Resources, University of Sydney NSW 2006, Australia Keywords:  Partial root-zone drying; regulated deficit irrigation; soil moisture monitoring; 3D wetting patterns; grapevines Abstract Non-uniform Soil Wetting Patterns are commonly found in the field and numerical or empirical models developed to characterise them may or may not be accurate. Quantitative assessment of non-uniform wetted zones is essential for optimal irrigation management of crops under precision irrigation techniques such as Regulated Deficit Irrigation (RDI) or Partial Root-zone Drying (PRD). A field study was carried out to visualise the wetting pattern in situ on Grapevines ( Vitis vinifera var. Cabernet Sauvignon) at Pencahue VII Region, Chile (University of Talca) and ( Vitis vinifera var. Shiraz) at Richmond NSW, Australia (University of Western Sydney). In Chile, soil moisture and soil wetting pattern volumes were correlated with plant water status, measured as stem water potential ( ! stem ) on RDI treatments. In Australia soil moisture data were collected using an array of capacitance probes (Sentek Pty. Ltd.) and used to generate 3D real time animations of soil wetting patterns at different irrigation systems (drip and sub-surface drip) using WPA© (Wetting Pattern Analyser), which is a novel software tool for visualisation and animation of field soil wetting patterns. Preliminary results have shown the critical importance of the location of soil moisture probes to schedule irrigation and a strong correlation of total available water in the wetted zone, (r 2  = 0.77) and normalised soil moisture (r 2  = 0.84) with ! stem . INTRODUCTION Regulated Deficit Irrigation (RDI) and Partial Root-zone Drying (PRD) have been developed to control vigour, increase water use efficiency and improve grape quality (Gu et al., 2000; Davies et al., 2002; Dry et al., 2001; Loveys et al., 2001; Dry and Loveys, 1999; Matthews and Anderson, 1987; Matthews and Anderson, 1988). Soil moisture monitoring is commonly used to schedule irrigation under RDI and PRD; and can be correlated with daily variation of estimated grapevine evapotranspiration (Stevens and Harvey, 1996; Stevens et al., 1995, Reynolds and Naylor, 1994; McCarthy, 1997). However, irrigation scheduling has become more challenging since the development of new irrigation technologies to optimise water use efficiency, such as RDI and PRD, which have created narrow soil moisture and plant stress target thresholds. Quantitative soil water status measurements are limited by the need to sample adequately to characterise water status of the large volume of soil in the root-zone, leading to uncertainty in the adequate positioning of probes. (Li et al., 2002). Quantitative assessment of local and total water uptake responses to soil moisture is essential for optimal irrigation design and management, but non-uniform soil wetting patterns are commonly found in the field (Reid and Huck, 1990), which complicates the assessment. Soil wetting patterns in the field can be predicted using numerical or empirical models (Brandt et al., 1971; Nakayama and Bucks, 1986; Ben Asher, Charach and Zemel, 1986; Zur, 1995; Warrick, 2003). However, results from laboratory experiments or IV th   IS on Irrigation of Hort. Crops Ed. R.L. Snyder Acta Hort. 664, ISHS 2004    246 simulations may not be or are only partially applicable to the field (Reid and Huck, 1990). Also numerical models are less practical because of their complexity, cost and the difficulty of reproducing the field spatial variability of the wetting front on the soil profile (Lafolie et al., 1989). This paper describes preliminary results showing a close correlation  between shape and dimension of soil wetting patterns (SWP) with plant water status. Also, we present the implementation of a novel technique to monitor 3D soil wetting  patterns and the development of computer based wetting pattern analysis tool (WPA© software) to process, visualise and animate 3D soil moisture data in real time to be correlated with plant water status for precision irrigation in grapevines. MATERIALS AND METHODS Field experiments to monitor soil wetting patterns were carried out at two sites, Chile and Australia. In Chile, the site was at Pencahue, VII region (35 o 22’ LS; 71 o 47’ LW) on 9 years old grapevines, var. Cabernet Sauvignon (3m x 1.2m), irrigated by 1 x 3 L ⋅ h -1  drippers per vine. In Australia, the site was at Richmond NSW (33 o 36’ LS; 150 o 44’ LE) on 5 years old grapevines, var. Shiraz (3.0m x 1.8m), irrigated by 2 x 2 L ⋅ h -1  drippers per vine. Undisturbed soil samples were taken in both sites to obtain soil physical properties, such as water content at field capacity (FC), permanent wilting point (PWP) and bulk density ( ! B ). The soil type was a sandy – loam soil in both sites, with the following soil  physical properties; Chile: FC= 23.7%; PWP= 12.05%; ! B = 1.44 g " cm -3 ; Australia: FC= 22.6%; PWP= 10.3%; ! B = 1.6 g " cm -3 . Measurements of volumetric soil moisture ( θ ) were  by Time Domain Reflectometry instrument (TDR – TRASE; Soil Moisture Equipment Corp. Sta. Barbara, Ca. USA) with a pair of 1 m long waveguides installed vertically at the middle of the wet bulb in all the 24 plants monitored. In Australia, 6 capacitance  probes (EasyAG®, Sentek) were installed in a radial distribution around a dripper (Fig. 1a) for normal drip irrigation. Another 9 capacitance probes were installed in grapevines with sub-surface irrigation system installed at 30cm of depth 35cm away from the middle-row with drippers every 50cm (Fig. 1b). Each probe had 4 sensors positioned at 10, 20, 30 and 50cm of depth. Measurements of soil moisture content were made every 10 min and recorded using a datalogger (RT6® Sentek) connected to a GSM modem for telemetry access. Data were used to construct progressive images, along the plant row and across the plant row, to visualise the evolution of the soil wetting pattern and drying out  processes with minimal soil disturbance using a novel software package (Wetting Pattern Analysis, WPA©). Stem water potential ( # stem ) was measured once per plant in the 24 measuring sites in Chile, during the irrigation event, using a Sholander bomb (Soil Moisture Equipment Corp. Sta. Barbara, Ca. USA), following the method described by McCutchan and Shackel (1992).  Normalised soil moisture and soil moisture stress levels were estimated using the normalised soil moisture (F) (Jarvis, 1976) and inverse value (F -1 ).  PWP i PWP  FC   F  θ  θ  θ  θ   −−=   (Eq.1)    PWP  FC  PWP i  F  θ  θ  θ  θ   −−= − 1   (Eq.2) where  F   = normalised soil moisture (dimensionless);  FC  θ   = volumetric soil moisture content at field capacity (dimensionless);  PWP  θ    = volumetric soil moisture content at  permanent wilting point (dimensionless); i θ   = volumetric soil moisture content in the wetted-zone (dimensionless).  F  -1  is the inverse value of normalised soil moisture, which represents the level of water stress imposed on the plant by the available soil moisture close to the root-zone (Ortega-Farias and Fuentes, 1999). A correlation between # stem and the Total Available Water (TAW) was also tested. TAW for RDI treatments was calculated as: TAW = RAW + DAW = (  !   FC – !   PWP) * SWPV   where  RAW   = readily available water;  DAW = deficit available water; SWPV   = soil (Eq.3)      247wetting pattern volume (L) (Goodwin, 1995). SWPV was calculated as: where w  = soil wetting pattern width (cm); d   = soil wetting pattern depth (cm). Assuming a paraboloid shape for sandy – loam soil wetting patterns (Donahue et al., 1983). The dimensions of SWP were visually assessed through inspection pit excavations in the 24 measuring sites, after soil moisture and physiological measurements ( # stem ) during the irrigation event. RESULTS AND DISCUSSIONS In Chile, there was a strong correlation between F (Eq.2)   and # stem  (r  2  = 0.84) during a single irrigation event. When F increases, # stem  approach to a moderated stress level of -1.4 MPa (Patakas and Noitsakis, 1997), on the contrary, when the F value decreases, # stem  increases, reaching non-stress values (Bogart, 2000) of –0.78 MPa (see Fig. 2a). F -1  can be used as a soil water stress index, which was linearly correlated with # stem  (r  2  = 0.91) data not shown. TAW (Eq. 3) was also correlated with # stem , in this case, the correlation was significant (r  2  = 0.77). With a maximum TAW of 120 L per vine, # stem  reaches a plateau close to –0.75 MPa for a wetting pattern of 100 cm of width and 75cm of depth (Fig. 2b). Longer irrigation, after this point, results in losses of water to deeper layers, beyond root-zone (Moncef et al., 2002), with little further improvement in plant water status. The shape of the wetting patterns visually assessed corresponded to a  paraboloid with a wetted volume described mathematically using Eq. 4. For this shape, depth will contribute more significantly, rather than width, over plant water status ( # stem ) (r  2  = 0.94 between d and # stem ; r  2  = 0.56 between w and # stem , data not shown). Therefore, the most representative position for a single probe would be in the middle of the wetting pattern for this particular soil type. Fig. 3 shows the initial, middle and end 2D snapshots, taken from WPA©, of a single irrigation event (5 hours) in a normal drip irrigation system in Australia. Figs. 3 a, 3b and 3c corresponded to the inter-plant dimension (N-S) and Figs. 3 d, 3e and 3f to the inter-row (E-W), giving cross section views along and between rows. According to these observations, an elliptic paraboloid shape would more accurately describe the soil wetting  pattern characteristics observed. The narrower width found in the inter-row, compared with that found in the inter-plant dimension could be the result of compaction generated  by machinery transit, according to significant differences found in ! B  (data not shown). Fig. 4 shows the initial, middle and end snapshots (from WPA©) of a single irrigation event (5 hours) for a PRD (wet side) sub-surface irrigation system in Australia. There is a clear capillarity movement of water to the surface (Figs. 4b and 4e) and a more uniform lateral spreading of the wetting pattern at the root-zone (20 – 55cm depth) than normal drip, which is in accordance with the technical specifications of the Safe T Flo ® drip-line used. Figs. 4c and 4f, shows that irrigation duration for this specific irrigation system, was too long. After the capillarity effect, most of the water starts to migrate to deeper layers,  below 60cm (active root-zone) and below the dripper position (Fig. 4c, lower left). Subsurface irrigation timings should be shorter and more frequently than normal surface drip. The two main questions in irrigation scheduling can be answered using a combination of these techniques. When to irrigate could be answered monitoring plant water status or # stem  (Choné et al., 2001), and how much to irrigate using the soil wetting  pattern visualisation technique described in this paper. Soil wetting patterns and volumetric water content measurements are good indicators of available water in the soil, which can be correlated with plant water status to achieve accurate irrigation scheduling. Soil moisture probes distribution in the field and WPA© could be practical and powerful tools to visualise complex soil wetting pattern shapes at each irrigation event with minimal soil disturbance. The use of this technique could prevent water losses to layers ( ) 100021])[( 202 d wdz d  z wSWPV  d  ⋅⋅⋅=⋅⋅⋅= !  π  π   (Eq.4)      248 outside the root-zone maximising water application efficiency in irrigations. This  preliminary study needs further research and corroboration using other plant water status measurements. ACKNOWLEDGEMENTS  We thank The Australian Research Council for funding this project. Also we thank Mr. Carlos Camus, David Hinton from IWT Pty. Ltd. and Seven Sisters vineyard for all the support given through this research. Literature Cited Brandt, A., Bresler, E., Diner, N., Ben Asher, I., Heller, J. and Godeldberg, D. 1971. Infiltration from a trickle source. Soil Sci. Soc. Am. Proc .  35: 675-682. Ben Asher, J., Charach, C.H. and Zemel, A. 1986. Infiltration and water extraction from trickle irrigation source: the effective hemisphere model. Soil Sci. Soc. Am.  J.  50: 882-887. Choné, X., van Leeuwen, C., Dubourdieu, D. and Gaudillère, J.P. 2001. 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Trickle irrigation for crop production - Design,    249operation, and management. Elsevier Publishing Co., Amsterdam. Raynolds, A.G. and Naylor, A.P. 1994. Pinot noir and Riesling grapevines respond to water stress duration and soil water holding capacity. HortScience, 29(12): 1505-1510. Reid, J.B. and Huck, M.G. 1990. Diurnal variation of crop hydraulic resistance: a new analysis. Agronomy Journal, 82: 827-834. Stevens, R. and Harvey, G. 1996. Soil water depletion rates under large grapevine. Aust. J. of Grape and Wine Res. 2(3): 155-162. Stevens, R., Harvey, G. and Aspinall, D. 1995. Grapevine growth of shoots and fruit linearly correlated with water stress indices based on root-weighted soil matric  potential. Aust. J. of Grape and Wine Res. 1(2): 58-66. Warrick, A.W. 2003. Soil water dynamics. Oxford University Press. New York. 391pp. Zur, B. 1995. Wetted soil volume as a design objective in trickle irrigation. Agricultural Engineer Department, Technion – Israel Inst. of Tech. 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