land
ArticleOptimization of Irrigation of Wine Grapes with Brackish Waterfor Managing Soil Salinization
Vinod Phogat 1,2,3 , Tim Pitt 1,2,3 , Paul Petrie 1,2,3,4 , Jirka Šimůnek 5, *
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Citation: Phogat, V.; Pitt, T.; Petrie, P.;Šimůnek, J.; Cutting, M. Optimizationof Irrigation of Wine Grapes with
Brackish Water for Managing Soil
Salinization. Land 2023, 12, 1947.
https://doi.org/10.3390/
land12101947
Academic Editors: Tiago Brito Ramos,
Maria da Conceição Gonçalves andMohammad Farzamian
Received: 14 September 2023
Revised: 10 October 2023
Accepted: 18 October 2023

and Michael Cutting 6

Crop Sciences, South Australian Research and Development Institute, GPO Box 397,
Adelaide, SA 5001, Australia; vinod.phogat@sa.gov.au (V.P.); tim.pitt@sa.gov.au (T.P.);
paul.petrie@sa.gov.au (P.P.)
School of Agriculture, Food and Wine, The University of Adelaide, PMB No.1, Adelaide, SA 5064, Australia
College of Science and Engineering, Flinders University, Adelaide, SA 5042, Australia
School of Mechanical and Manufacturing Engineering, The University of New South Wales,
Sydney, NSW 2052, Australia
Department of Environmental Sciences, University of California, Riverside, CA 92521, USA
Murraylands and Riverland Landscape Board, Murray Bridge, SA 5253, Australia; michael.cutting@sa.gov.au
Correspondence: jiri.simunek@ucr.edu

Abstract: Water scarcity and quality are critical impediments to sustainable crop production. In thisstudy, HYDRUS-2D was calibrated using field measurements of water contents and salinities in thesoil under wine grapes irrigated with river water (Rw, 0.32 dS/m). The calibrated model was thenused to evaluate the impact of (a) four different water qualities ranging from 0.32 (Rw) to 3.2 dS/m(brackish water, Gw) including blended (Mix) and monthly alternating (Alt) irrigation modes; (b) two
rainfall conditions (normal and 20% below normal); and (c) two leaching options (with and without
30 mm spring leaching irrigation) during the 2017–2022 growing seasons. Irrigation water quality
greatly impacted root water uptake (RWU) by wine grapes and other water balance components.
Irrigation with brackish water reduced average RWU by 18.7% compared to river water. Irrigation
with blended water or from alternating water sources reduced RWU by 8.8 and 7%, respectively.
Relatively small (2.8–8.2%) average annual drainage (Dr) in different scenarios produced a very low(0.05–0.16) leaching fraction. Modeling scenarios showed a tremendous impact of water quality
on the salts build-up in the soil. The average electrical conductivity of the saturated soil extract(ECe ) increased three times with Gw irrigation compared to Rw (current practices). Blended andalternate irrigation scenarios showed a 21 and 28% reduction in ECe , respectively, compared to Gw.
Irrigation water quality substantially impacted site-specific actual basal (Kcb act ) and single (Kc act )crop coefficients of grapevine. Threshold leaching efficiency estimated in terms of the salt massleached vs. added (LEs ; kg/kg) for salinity control (LEs > 1) was achieved with LFs of 0.07, 0.12, 0.12,
and 0.15 for the Rw, Mix, Alt, and Gw irrigations, respectively. Applying annual leaching irrigation(30 mm) before bud burst (spring) in the Mix and Alt with Rw and Gw scenarios was found to be thebest strategy for managing irrigation-induced salinity in the root zone, lowering the ECe to levels
comparable to irrigation with Rw. Modeling scenarios suggested that judicious use of water resources
and continuous root zone monitoring could be key for salinity management under adverse climate
and low water allocation conditions.

Published: 20 October 2023

Keywords: grapevine; water quality; water balance; soil salinity; leaching; crop coefficients; droughtseasons rainfall; leaf area index; HYDRUS-2D
Copyright: © 2023 by the authors.
Licensee MDPI, Basel, Switzerland.
This article is an open access article
distributed under the terms andconditions of the Creative Commons
Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).

1. Introduction
Water scarcity is a common occurrence and severely impacts irrigated agriculture inarid and semi-arid regions where rainfall totals are far less than the evapotranspiration
demand. This skewed relationship is further widened by rapid population growth, industrialization, and increased living standards that compete directly with irrigated agriculture

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for supplementary water sources [1–3]. Water scarcity is increasing and is expected to become more severe with an unabated rise in greenhouse gas emissions, rising temperatures,
frequent droughts, and changing precipitation patterns [4]. A rise in temperatures, forinstance, could lead to soil moisture deficits and a growing risk of vegetation desiccation
due to increased evapotranspiration [5,6], requiring more irrigation water for crop production [7,8] and reaching yield potentials [9]. Agroecological and economic consequences ofclimate change are expected to vary widely [10–12], and uncertainty in water availability
will remain a crucial factor influencing irrigated agriculture, which already consumes 69%
of freshwater resources on the planet [13].
Water allocations for irrigation in the river basins worldwide depend on rainfall, runoff generation, and resulting flows in the river system. Climate variability and uncertainty
in irrigation water allocations can severely impact irrigated crops’ sustainability, including
viticulture. For example, in Australia, water allocations for irrigation during the Millennium
drought (2002–2009) were severely reduced to as low as 18% of normal allocations, severely
affecting the sustainable production and resilience of vineyards and other irrigated crops.
Similar conditions of unreliable and limited water availability for irrigation also occur inother arid and semi-arid regions worldwide. Judicious integration of other water sources,
such as brackish water, into irrigation schedules would enhance water security and increase
the resilience of cropping systems to climate variability, resulting in long-term sustainability
and economic viability of irrigated production systems. This additional natural resource isoften poorly understood, undervalued, mismanaged, or abused [14].
Irrigation with marginal quality and brackish water has been practiced on various
crops with varied impacts on yield and associated environments depending on site-specificclimate, soil, water quality, crop sensitivity, and management practices [15–22]. Numerous wine-grape growing regions use groundwater or recycled water of varying quality(0.8–3.5 dS/m) for irrigation [23–26]. Saline/brackish water irrigation with unsuitable
management practices can increase soil salinity [21,25–28]. Pitt and Stevens [29] reported
that rootzone electrical conductivity of the soil saturation extract (ECe ) in the soil underthe vine was four times higher than mid-row (1.5 dS/m) in a vineyard that has received
long-term groundwater irrigation. Other studies also reported the development of saline
and sodic conditions in the soil under grapevines [27,30,31] and other crops [15,18,32–34],
which negatively impacts the soil physicochemical conditions and the growth and yieldof crops. However, judicious site-specific use of brackish water following appropriate
ameliorative management techniques can help reduce the harmful impacts on soils andprovide long-term sustainable production of irrigated crops [21].
Grapevine growth, yield, and berry composition are affected to a varied extent by the
degree and duration of salinity stress imposed by saline and brackish water irrigation [35].
Adverse impacts of high salinity on grapevines are two-pronged [36]: (a) reduced water
uptake due to high osmotic pressure [35,37] and (b) vine mortality induced by high Na+
and Cl− concentrations in the leaves. Numerous studies have reported high Na+ and Cl−
concentrations in leaves, juice, and wine [23,25,26,38], depending on the cultivar, rootstock,salt concentrations, and exposure time to saline conditions. High salt concentrationsin the wine can exceed maximum residue limits, preventing sales in specific markets
and producing adverse sensory outcomes [39]. However, Martínez-Moreno et al. [40,41]
reported that deficit irrigation of grapevine with chloride- and sulfate-dominated saline
water of 5 dS/m over five years showed an insignificant impact on vine growth and yield.
Additionally, the wine received the best sensory scores in well-drained soil, highlighting
the importance of drainage for salinity control. They concluded that site-specific soil type,climate, and drainage conditions created a favorable environment for rapid leaching ofsalts and reduced the detrimental impact on vine performance.
The use of saline water for irrigation can be managed through appropriate leaching ofsalts from the root zone depending on the level of crop salt tolerance [42]. The traditional
irrigation management strategy is to provide extra water so that the ratio of the actual
drainage depth to the irrigation depth, i.e., the leaching fraction (LF), satisfies the leach-Land 2023, 12, 1947

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ing requirement (LR) [42], maintaining the root zone salinity below the crops’ tolerance
threshold. Due to the complexities of the interactions between water, soil, and plant uptake,estimating and matching LF with LR is not always straightforward [43]. The unavailabilityof good-quality water and the complexity of implementing proper LR strategies for salinity
control under drip irrigation systems may lead to enormous amounts of salt deposition in
the soils [27,44].
Numerous studies describe multiple approaches to maintain the root zone salinity
below the crop threshold, such as (a) the intra/inter-seasonal or physiological stage alternated use of fresh and saline waters for irrigation [26,31,45,46], (b) blending waters frommultiple water sources [47–49], and (c) applying additional leaching irrigation if rainfall
is insufficient to manage excessive salts [27,43,44,50]. Typically, these options have varied
responses for managing the accumulation of salts in the root zone and require site-specificapproaches, which are a function of soil type, climate, crop, and the composition of theirrigation water. Complex soil heterogeneity, widespread stratification (as it exists in Australian grapevine growing areas), and poor drainage conditions may further confound theefforts to ward off the salts buildup in the crop root zone [27,51,52].
Long-term field experiments involving numerous variables under varied soil, water,
and climate conditions are expansive and labor-intensive. Mathematical models are excellent, cost-effective tools for studying the impact of climate, soil, water, and crop variables
on water and solute transport in the soil [21]. Among available agro-hydrological models,HYDRUS (2D/3D) [53] has been widely used to simulate the water movement and salinity
dynamics under drip irrigation [27,54–58]. The model became popular because of its flexibility to accommodate different types of complex boundary conditions, consider root water
uptake, and account for the coupled impact of water and salinity stresses and its ease ofuse due to its user-friendly graphical interface.
The objectives of this investigation are two-pronged, viz., (1) to estimate the waterbalance components and actual single crop (Kc act ), basal crop (Kcb act ), and evaporation(Ke ) coefficients for improving site-specific irrigation practices; and (2) to optimize theintegration of brackish water in the irrigation schedule of wine grapes while managing
the root zone salinity for sustainable production. To achieve these objectives, HYDRUS2D was first calibrated for water balance and salinity dynamics in the soil under wine
grapes during one season (2021–22). The calibrated model was then used to evaluate theimpact of sixteen scenarios involving two qualities of irrigation water (river water—Rw,
ECiw = 0.4 dS/m and brackish water Gw, ECiw = 3.2 dS/m); two modes of application[blended Rw and Gw in a 1:1 ratio, ECiw = 1.87 dS/m and monthly alternate use of Rw
and Gw)]; two types of rainfall occurance [normal (n) and 20% reduced (d) annual rainfall];and two leaching irrigation options [no leaching irrigation and annual leaching irrigation(l, 30 mm)] over multiple seasons (2017–2022) in heterogeneous soil. Subsequently, themodel-predicted water and salt balance components were used to estimate the leaching
fractions (LF) and leaching efficiency (LE) under different scenarios. Thus, the assessmentof the entire growing system and potential water quality options aims to evaluate theincorporation of brackish water in the wine grapes’ irrigation schedule while controllingsoil salinization to maintain sustainable production with effective leaching strategies.
2. Materials and Methods
2.1. Description of the Experimental Site
An experimental site was established at Kimbolton Wines (Lat −35.32681, Long
139.06178) in the Langhorne Creek (LHC) Geographic indication in South Australia, between the Mount Lofty Ranges and Lake Alexandrina in the flood plains of the Angas
and Bremer rivers. The Cabernet Sauvignon wine grapes were planted in 2001 on the
Teleki 5C rootstock at a spacing of 2 m between vines and 3 m between vine lines. The
vineyards were trained on a single wire double cordon spur pruned system. Vineyard rows
are oriented in a North-South direction, facilitating better absorption of photosynthetically
active radiation. A drip irrigation system was laid out to irrigate the wine grapes, placing

Land 2023, 12, 1947

4 of 29a dripline along the vine line with pressure-compensated emitters spaced at 75 cm witha discharge rate of 2.4 L/h. Irrigation was scheduled based on the estimated soil water
regime and local climate conditions in the Langhorne Creek region. Measurements of soil,
water, and crop parameters were carried out over the entire growing season (July 2021 toJune 2022) as described in the following sections.
Climate data were obtained from the nearest Landscape SA weather station (Langhorne
Creek Central). Rainfall during the simulation period (2017–18 to 2021–22) varied from
283 to 504 mm, with an average of 372 mm, which is close to the long-term average rainfall (390 mm) at Langhorne Creek [59]. Most rain events during this period were smaller
than 5 mm, which tended to wet the soil surface only and evaporate back into the atmosphere. Above-normal rainfall years potentially generate precipitation surplus during
winter months when most rainfall occurs because the LHC region has a Mediterranean
climate with hot and dry summers and cool and moist winters. Large rain events (>20 mm)
play a key role in regulating the salts in the crop root zone. There were 1, 2, 5, 3, and 0 rainfall events of >20 mm during the 2017–18, 2018–19, 2019–20, 2020–21, and 2021–22 growing
seasons, respectively. Seasonal reference crop evapotranspiration (ET0 ) values estimatedby a modified Penman-Monteith approach [60] varied in a narrow range (1015–1096 mm),showing small year-to-year variation.
2.2. Soil Water and Canopy Growth Measurements
Soil water distributions were monitored using in situ calibrated capacitance probes
installed close to an emitter in the vine row by the vineyard manager with sensors every
10 cm to a depth of 120 cm. The soil moisture probe was installed to support irrigation
scheduling for the vineyard. Soil solution extractors were installed at 30, 60, and 90 cm
depths at two locations in the vine row near the lateral and adjoining the moisture probe.
Soil solutions were collected at fortnightly intervals to estimate soil solution electricalconductivity (ECsw ). Soil solution samples could not be collected during the summer
when deficit irrigation was imposed. Alternatively, salinity (EC) in the 1:5 soil-to-water
solution was measured on soil samples collected from 0–15, 15–30, 30–60, and 60–90 cm
soil depths near the extractors during the summer season. These measurements were used
to supplement the calibration of the model.
A high-definition (1080 p) time-lapse camera was installed between two vines tomonitor the canopy growth (Figure 1a). The camera was located at ground level andorientated upward to ensure that the sky was equally visible on each side of the image.
Images were collected during the early morning to avoid overexposure of the image sections
by the sun. Collected images were stored on an SD card and emailed using the 4G network
so that the camera operations could be confirmed.

Figure 1. Grapevine canopy images (a,b) taken by an HD camera and (c) leaf area index (LAI)
estimated by image analysis.

Images were analyzed using the ImageJ software (https://imagej.nih.gov/ij/index.
html version 1.53k/Java1.8.0_172; accessed 27 August 2021). The canopy size for theentire growing season was indirectly assessed as the leaf area index (LAI), improving themethodology described in previous studies [61–64]. The algorithm used in these studies

Land 2023, 12, 1947

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defines three fractions, which are the fractions of foliage of the projective cover (ff ), thecrown cover (fc ), and the crown porosity (Φ). The field view of the full canopy captured by
the image is shown in Figure 1a. However, as the canopy keeps growing, the field view of
the canopy eventually outgrows the vertical field view of the camera (Figure 1b). Under
such conditions, fractional covers (ff and fc ) are not estimated correctly using the partial
image of the canopy and are usually ignored in the LAI analysis [61]. For such situations,an approximate correction factor for the crown cover can be applied, assuming the ff /fc
ratio of the extended canopy is similar to the measurements of the field view by the camera.
Therefore, Equation (A3) in [63] can be rewritten aslnΦ Wcci
LAI M = − f c(1)kWc
where Wc is the width of the field view of the canopy captured by the camera, Wcc is
the maximum width of the canopy measured at the cordon, Wcci is the daily interpolation of width protruding the field view of the camera, and LAIM is the measured LAI,
which corresponds to the ground area covered by the vertical projection of the foliage andbranches [62,63]. LAIM was further corrected to obtain the effective LAI (LAIe ), as reported
in previous studies [61–63]. However, the estimated LAIe deviates from the usual definitionof grapevine LAI, defined as the ratio of total green surfaces (leaves, shoots, and fruits whenpresent) to the unit of the land area allocated to each vine [65,66]. Therefore, the second
correction factor was applied to the LAIe to obtain corrected LAI for the vine spacing (LAIes )as given below:
Wcc
LAIes = LAIe
(2)
Wr
where Wr is the width between vine rows. LAIes estimated using Equation (2) indicateda continuous canopy growth from bud burst to harvest (Figure 1c). These methodology
modifications reduced the average LAIes of mid to late grapevine season by half of LAIe ,measured using the previous method. The LAI values were comparable to those estimatedby the Plant Canopy Analyser (LAI-2200C, LI-COR Biosciences, Lincoln, NE, USA). The
LAI values for other seasons (2017–18 to 2020–21) were estimated from the NDVI drawn
from the Datafarming portal (https://www.datafarming.com.au/about-us/(accessed 27
August 2021)). A linear relationship (Y = 4.07X; R2 = 0.83) was fitted between NDVI andmeasured LAI during the 2021–22 season. This conversion was applied to the NDVI values
from the other seasons (2017–18 to 2020–21) for estimating LAI. Similar relationships havebeen reported for the vineyards across various regions [63] and vineyards in other parts ofthe globe [67].
The LAI data and other soil, climate, and plant parameters were used to estimate
the daily values of potential evaporation and transpiration following the FAO-56 dual
crop coefficient approach [60,68]. These values served as inputs for the numerical model
HYDRUS-2D [53], which was used to simulate the water and salinity dynamics in the soil.
2.3. Irrigation Application and Water Quality
The property manager controlled irrigation application decisions at the study site. Irrigations were applied based on the profile’s total available water (TAW) and the capacitanceprobe data. Profile water availability in the spring is key in initiating irrigation at the startof a new season. In-season irrigations were applied based on the phenological stage of thecrop, climate conditions, and water deficit in the soil profile. Irrigation was applied when
the stored water in the profile declined to a level lower than the readily available water(Table A1).
In-season irrigation water was collected in a catch can installed at the terminal pointof the lateral irrigating vines at the study site. Water samples were collected fortnightly tomeasure electrical conductivity (ECiw ). The measured ECiw values during 2021–22 varied
from 0.17 to 0.38 dS/m and served as the current irrigation water quality for calibrating theLand 2023, 12, 1947

6 of 29

model. For the rest of the simulated period (2017–21), the daily ECiw values of the River
Murray water (Rw) measured at the Langhorne Creek pipeline pumping station were used.
Estimated ECiw values ranged from 0.16 to 0.61 dS/m, lower than the tolerance threshold(0.95 dS/m) of salinity-sensitive crops in Australia and New Zealand [69].
The groundwater quality at the Langhorne Creek Prescribed Groundwater Area ispredominantly brackish, with salinity ranging between 300 and 30,000 mg/L [59]. The
estimated groundwater salinity (Gw) in the nearest prescribed well used for irrigation
remained around 3.2 dS/m, and this value was adopted in the simulations. The rainfall
chemistry analyzed by Cresswell et al. [59] in the study region provides reliable information
about rainfall salinity (ECrw ; 0.16 dS/m) used in simulations.
2.4. Estimation of Soil Hydraulic Properties
Soil hydraulic parameters were estimated from water retention curves determined on
undisturbed soil samples. These samples were collected in 75 mm diameter and 50 mm
tall rings from 0–15, 15–30, 30–50, 50–100, and 100–120 cm soil depths at two locations,representing the site-specific textural heterogeneity. Intact soil rings were first saturated
overnight, and then saturated hydraulic conductivity (Ks ) values were measured using theconstant head method [70]. Subsequently, the cores were used to measure the saturated
water content (θ s ) and volumetric water contents (θ) at −3 and −6, and −10, −33, −100,−300, and −1500 kPa pressure heads using hanging columns and the pressure plateapparatus, respectively. Measured Ks and water content (θ)—pressure head (h) data ofeach soil layer were used to estimate the soil hydraulic parameters (SHP) according to thevan Genuchten-Mualem model [71]. Estimated SHPs were further finetuned by trial anderror during model calibration. The final values used in HYDRUS-2D to simulate water
movement in the soil are given in Table 1.
Table 1. Calibrated soil hydraulic properties (θ s = saturated water content, θ r = air dry water content,
α = inverse of air entry value, Ks = saturated hydraulic conductivity, η = pore size distribution
parameter, and l = pore connectivity parameter) of different textural layers at the Langhorne Creek
study site.
Soil Depth

Texture

θr

(cm)
0–15
15–30
30–50
50–100
100–120θs
cm3 cm−3

Sandy Loam
Sandy Loam
Sandy Clay Loam
Sandy Loam
Sandy Clay Loam

0.041
0.053
0.15270.10440.1908Aη

cm−1
0.42590.347
0.3942
0.34130.37310.03530.058
0.03390.02260.0403Ksl

cm day−1
1.743
1.774
1.495
1.795
1.363

141.238
98.61
10.93
7.75
6.93

0.5
0.5
0.5
0.5
0.5

2.5. Estimation of Potential Evaporation and Transpiration
HYDRUS-2D requires daily inputs of potential evaporation (Es ) and transpiration (Tp ),representing the evaporative flux from the partially wetted soil surface and the transpiration
flux via the canopy, respectively. In this study, these parameters were estimated using the
FAO Penman-Monteith dual crop coefficient approach [60,68]:
ETC = (Kcb + Ke ) ET0(3)

where ETC is evapotranspiration (LT−1 ), ET0 is reference evapotranspiration (LT−1 ), Kcb isthe basal crop coefficient, which represents the plant transpiration component, and Ke is
the soil evaporation coefficient. Generic values of the grapevine Kcb [60] were adjusted forthe local climate and crop conditions, considering crop height, wind speed, and minimum
relative humidity averages. Other crop and soil-related parameters for estimation of Tp
and Es using the FAO 56 approach, e.g., readily available water (RAW), total available
water (TAW), readily evaporable water (REW), total evaporable water (TEW), and fractions

Land 2023, 12, 1947

7 of 29of wetted and shaded areas (fc , fw ), were estimated from the measured data as reported
in previous studies [8,72]. Important climate and other parameters used in FAO-56 fordifferent years are provided in the Appendix A (Figure A1 and Table A1).
2.6. Model Construction, and Initial and Boundary Conditions
Brief theoretical details on water movement and solute transport processes in the soil
adapted in the model are given in the Appendix A. More information on the HYDRUS2D software (version 5.02.0530) and related references can be found at https://www.pcprogress.com/en/Default.aspx?HYDRUS-3D (accessed 27 August 2021). A two-dimensionalmodel domain was constructed to represent a vertical cross-section perpendicular to thevine line and equally spaced between mid-rows (Figure 2). The simulated domain was
120 cm deep and 300 cm wide (the row spacing at the field site), perpendicular to a vinerow. The transport domain was divided into 13,048 finite elements with a very fine grid
below the dripper (0.5 cm) and gradually increasing element sizes laterally (up to 3 cm) andvertically (up to 10 cm) from the dripper. Surface drip irrigation was simulated assuming
an infinite line source, which was shown previously to be a good representation of the drip
irrigation system [44,73].

Figure 2. Model domain showing field observation setup (camera, moisture probe, and solution
extractor), soil textures, and imposed boundary conditions.

Different textural layers (see different colors in Figure 2) were assigned to the domain
depending on the measured depths of textural layers at the study site. A drip line runs
along the vine line, and irrigation water is applied through the drippers placed on the soil
surface. Measured values of the initial water content and soil solution salinity in different
textural layers were used as initial conditions for water flow and solute transport in the soil.
The soil surface was subjected to the atmospheric boundary condition (BC) and a variable
flux BC imposed by dripper discharge (2.3 L/h), resulting in a two-dimensional flow. A
free drainage boundary condition was assigned at the bottom, while a no-flow boundary
condition was imposed on the sides of the domain. Concentration flux conditions were set
as top and bottom boundary conditions for solute transport. Initial conditions reflected theeffects of rainfall, irrigation, evaporation, and transpiration on soil salinity before the startof the experiment.
Root water extraction from the soil was computed using the macroscopic model
approach [74]. This model adjusts plant root water uptake according to the local soil waterLand 2023, 12, 1947

8 of 29

pressure head, h, at any point in the root zone. It defines how potential transpiration(Tp ) is reduced when the soil can no longer supply the plant’s required water under theprevailing climatic conditions. Values of critical pressure heads for grapevine were takenfrom previous investigations in South Australia [8,72]. The multiplicative model for osmoticpressure head reductions is considered in this study. The model states that water is extracted
at the maximum rate below the crop threshold osmotic head (ECe = 2.1 dS/m). The slopeof the curve determines the fractional reduction of water uptake per unit increase in theosmotic head (12.8%/ECe unit) beyond the threshold. These parameters for grapevine wereobtained from previous regional salinity tolerance studies [75].
Soil solution salinity (ECsw ) was simulated as a non-reactive solute, similarly as inmany previous studies [57,72,76]. These studies showed good correspondence between
model predictions and observed soil salinity dynamics in the soil under conditions involving intensive irrigation and fertigation environments. Other solute transport parameters,such as longitudinal and transverse dispersivities, initially assumed to be one-tenth ofthe modeling domain size and one-tenth of the longitudinal dispersivity, respectively [77],were optimized during the calibration.
Model calibration was performed to optimize the soil hydraulic and solute transportparameters in the soil to mimic the field conditions over the entire growing season. Subsequently, a calibrated model was used to simulate the soil’s water balance and salinity
dynamics under different climate and water quality scenarios.
2.7. Water Quality and Water Management Scenarios
Different scenarios were designed to assess the impact of using two water sources on
seasonal evapotranspiration components and salinity dynamics. Water qualities (ECiw ) of
the two sources were involved in various scenarios. For the drought season scenario, a
rainfall reduction of 20% was assumed, which matches the future climate projections forSouth Australia [78]. An annual leaching irrigation (l) of 30 mm of Rw was incorporated invarious scenarios based on the historical salinity issues in the Langhorne Creek area and aprevious leaching study [79]. Sixteen scenarios were designed to evaluate the impact ofvarious quantities and qualities of irrigation water and their use in different application
modes, such as mixing Rw and Gw in a 1:1 ratio (Mix) and alternate monthly use (Alt) of
Rw and Gw (Table 2).
Table 2. Scenarios involving combinations of different water qualities (Rw = river water,
Gw = brackish water, Mix = mixed Rw and Gw in a 1:1 ratio, Alt = a monthly alternate use of Rw
and Gw), the amount of annual rainfall (normal, n; and 20% less, d), and annual pre-season leaching
irrigation (LI) of 30 mm simulated over the five consecutive grapevine growing seasons (2017–22).
Normal Rainfall (n)Drought Season (d)Water Quality

No
Leaching

Leaching
Irrigation (l)No
Leaching

Leaching
Irrigation (l)River water (Rw)
Brackish water (Gw)
Mixing Rw and Gw
Alternate use of Rw and Gw

Rw_n
Gw_n
Mix_n
Alt_n

Rw_nl
Gw_nl
Mix_nlAlt_nl

Rw_d
Gw_d
Mix_d
Alt_d

Rw_dl
Gw_dl
Mix_dlAlt_dlThe calibrated model was used to understand the impact of different scenarios (Table 2)on the soil’s water balance and salinity dynamics over the five seasons (2017–18 to 2021–22),
using the growers’ actual irrigation schedule.
2.8. Statistical Analysis
Model-simulated (S) spatiotemporal water content distributions and ECsw values werecompared with corresponding measured (M) values using three error statistics, i.e., meanerror (ME), mean absolute errors (MAE), and root mean square error (RMSE). RelevantLand 2023, 12, 1947

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equations for the error statistics can be found in [80]. The two-sided Dunnett’s analysis
test (XLSTAT) was applied to compare the differences in the average values of waterbalance components, namely, actual evapotranspiration (ETC act ), root water uptake (RWU)
or actual transpiration (Tp act ), soil evaporation (Es ), and deep drainage (Dr ); leaching
fractions (LF); and rootzone soil salinities (ECe ) obtained for the current irrigation practiceand different water quality, drought, season, and leaching irrigation scenarios at a 95%
confidence interval.
3. Results and Discussion
3.1. Model Calibration
HYDRUS-2D was calibrated for spatiotemporal water content distribution and salinity
dynamics in the soil over the entire grapevine growing season (2021–22). Statistical errors(RMSE, ME, MAE) estimated for water content and salinity dynamics in the soil are shownin Table 3. RMSE, ME, and MAE values at different depths varied from 0.02 to 0.05, 0.00 to
0.05, and 0.02 to 0.05 cm3 /cm3 , respectively, showing slightly higher deviations at the soil
surface than deeper in the soil profile. The average values for the entire profile varied in amuch narrower range (0.02–0.04 cm3 /cm3 ), showing a good agreement between measured
and model-predicted water contents in the soil (Table 3). Similar error estimates between
measured and modeled values have been reported in several studies in different soils,
crops, and climate conditions [54,57,72,81,82]. It is well understood that soil water contents
measured with sensors such as capacitance probes are not error-free. The magnitude oferror estimates observed in the current study is equivalent to those often seen in the fieldmeasurements with capacitance probes [83].
Table 3. Root mean square error (RMSE), mean error (ME), and mean absolute error (MAE) values
for water content dynamics at different soil depths and the average profile salinity.
Water Content (cm3 /cm3 )Statistics
RMSE
ME/MBE
MAE

20 cm

40 cm

60 cm

80 cm

100 cmAverage

ECsw(dS/m)

0.05
0.05
0.04

0.05
0.04
0.05

0.03
0.00
0.02

0.02
0.00
0.02

0.04
0.02
0.03

0.04
0.02
0.03

0.61
−0.13
0.42

The profile-averaged values of RMSE, ME, and MAE for soil solution salinity (ECsw )were 0.61, −0.13, and 0.42 dS/m, respectively (Table 3). Chen et al. [54] reported RMSE
and MAE values ranging between 0.23 and 0.55 dS/m, respectively, while Phogat et al. [84]reported error estimates between 0.35 and 0.86 dS/m for the measured and HYDRUS-2D
predicted soil salinities. Similarly, Ramos et al. [57] estimated ME, MAE, and RMSE in
the range of −0.21 to −0.67, 0.6 to 1.25, and 0.85 to 1.76 dS/m, respectively, for similarcalibration of HYDRUS-2D for the salinity distribution in the soil. There are varied reasonsfor the disparity between measured and model-predicted ECsw values, such as measurement
errors in the model input parameters, soil solution collection, and measurement errors.
Phogat et al. [85] pointed out that the estimation of ECsw of the soil solution extracted fromthe soil under suction (a region of an uncertain size) may vary from ECsw simulated by themodel at a specific point in the soil. The statistical comparison supports the ability of themodel to simulate the distribution of water content and salinity dynamics in the soil.
3.2. Soil Water Balance
Average annual rainfall (P) and seasonal irrigation (I) applied during drought season(d) and leaching irrigation (l) scenarios differed significantly from the current irrigation
practices (the n scenarios) (Table 4). This means that assumed drought season conditions
and ameliorative salt management strategies have been appropriately applied. The averagevalues of wine grape ETC act estimated for the sceanarios where leaching irrigation isapplied (Gw_nl, Alt_nl, and Mix_nl) showed insignificant differences compared to theLand 2023, 12, 1947

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current practice (river water, Rw_n). It implies that integration of leaching irrigation(l) in the current irrigation schedule (n) in the brackish water (Gw), 1:1 blending (Mix),and monthly alternating (Alt) of river and brackish water irrigations can reduce the saltpressure in the root zone and provide a soil environment similar to the current practice.
The blending and alternate mode scenarios without leaching irrigation also showed ETC act
values comparable to current practices.
Table 4. Components of the annual water balance (P = precipitation/rainfall, I = irrigation,
RWU = root water uptake, Es = evaporation, and Dr = drainage), leaching fraction (LF), and averagerootzone salinity (ECe , dS/m) estimated for different irrigation scenarios including the current irrigation practice (Rw_n). Statistical significance was estimated using Duncan’s two-sided analysis of thedifference between Rw_n (control) and other scenarios at a 95% confidence interval.
ScenariosP

I

ETC act

RWU

Es

Dr

(mm)
Rw_n
Rw_d
Rw_nl
Rw_dl
Gw_n
Gw_d
Gw_nl
Gw_dl
Mix_n
Mix_d
Mix_nlMix_dl
Alt_n
Alt_d
Alt_nlAlt_dlCD (0.05)

373
299 *
373
299 *
374
299 *
374
299 *
374
299 *
374
299 *
374
299 *
374
299 *
16.5

209
209
237 *
237 *
209
209
237 *
237 *
209 *
209
237 *
237 *
209
209
237 *
237 *
0.005

424
382 *
438 *
401 *
409 *
366 *
426
387 *
417
375 *
434
395 *
418
376 *
434
396 *
13.5

218
201
223
210
177 *
154 *
188 *
168 *
198 *
177 *
208
190 *
202 *
183 *
210
194 *
16.3

206
181 *
216 *
192 *
232 *
213
238 *
219 *
219 *
197 *
226 *
205
216 *
193 *
224 *
202
8.9

39
15 *
53
26
53
31
65 *
39
45
22
58
31
44
21
57
30
19

LF

ECe

(%)

(dS/m)

0.07
0.03 *
0.09
0.05
0.09
0.06
0.10 *
0.07
0.07
0.04
0.09
0.06
0.08
0.05
0.09
0.06
0.03

2.2
2.7
1.6
2.2
4.5 *
5.5 *
3.9 *
4.9 *
3.6 *
4.3 *
2.9
3.8 *
3.2
3.9 *
2.6
3.4
1.3

* Statistically significant at a p-value of 0.05. Irrigations with river water (Rw, 0.32 dS/m) under normal (n) rain
(Rw_n), brackish water (Gw, 3.2 dS/m) under normal rain (Gw_n), a blend of Rw and Gw in a 1:1 ratio undernormal rain (Mix_n), monthly alternate use of Rw and Gw under normal rain (Alt_n), Rw + 20% less rain (Rw_d),
Gw + 20% less rain (Gw_d), Mix + 20% less rain (Mix_d), Alt + 20% less rain (Alt_d), Rw_n + annual leaching
irrigation of 30 mm (l) before bud burst (Rw_nl), Gw_nl, Mix_nl, Alt_nl, Rw_dl, Gw_dl, Mix_dl, and Alt_dl.

Seasonal vine water uptake (RWU) accounts for 40–51% (154–223 mm) of the total
water application, including irrigation and rainfall during the growing season (Table 4).
The maximum water uptake was predicted for the Rw_nl scenario, representing the mostfavorable conditions for grapevine growth, i.e., river water irrigation coupled with annual
leaching irrigation (l) of 30 mm before the bud burst. The simulated daily water balance
responded to the diurnal changes in the weather conditions, irrigation, canopy characteristics, soil water regime, and osmotic conditions in the soil (Figure 3). Actual daily root
water uptake (RWU) of grapevines under current practices (Rw_n) varied between 0.02
and 3.4 mm during the simulation. Note that higher RWU values were observed overthe December to March period, which coincides with the maximum canopy size and LAI(Figure 1). Numerous studies have reported that transpiration in crops without full groundcover, such as grapevine (an energy surplus system), responds to the canopy size, groundcover, leaf area index [86–88], and canopy density [68,89,90] under non-saline conditions.
Rootzone salinity (ECe ) is an important factor affecting ETC act and RWU (Tp act ) ofgrapevines. Both parameters decreased linearly in response to rootzone salinity. However,
the impact of ECe was more pronounced for RWU, which decreased by 6.8% (R2 = 0.96)
for a unit increase in the rootzone ECe (dS/m). The impact of salinity on ETC act decreased
to less than half (3.1%, R2 = 0.42) as the surface evaporation component increased underbrackish water irrigation. Ben-Asher et al. [91] reported a 20 and 65% reduction in potential

Land 2023, 12, 1947

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vine transpiration for 1.8 and 4.8 dS/m saline water irrigation. Such a drastic reduction
in vine transpiration occurred due to 4 times higher irrigation applications in different
climatic conditions. A linear reduction in ETC in response to saline water irrigation androotzone salinity was reported by many [50,92–95].

Figure 3. Model-predicted daily values of precipitation (P), irrigation (I), root water uptake (RWU),
evaporation (Es), and drainage (Dr) below the root zone (120 cm) of a grapevine irrigated with riverwater under normal rainfall conditions (Rw_n; current practice) during 2017 to 2022.

Water quality and water stress impacted the seasonal water balance components. The
minimum RWU was observed in the Gw_d scenario, where brackish water of 3.2 dS/m
was used for irrigation coupled with 20% less rain (drought season, d), representing anadverse soil environment for grapevine growth. Average seasonal RWU under the brackish,
blending, and alternate mode scenarios showed significant differences compared to thecurrent practices (Rw_n), except in the alternate mode with leching irrigation (Alt_nl) and
1:1 blending (Mix_nl) scenarios (Table 4). This suggests that brackish water irrigation in theblending (Mix) and alternate (Alt) modes could be a viable irrigation strategy if appropriate
leaching of salts from the root zone is maintained with annual leaching irrigation of 30 mm
before the bud burst. The Alt scenarios, where the application of Rw and Gw is alternated,
performed better in terms of greater RWU than the mixing scenarios (Mix), where the twowater sources were blended before irrigation. The average seasonal RWU for the Gw, Mix,
and Alt irrigation scenarios was reduced by 18.7, 8.8, and 7.0%, respectively, comparedto Rw irrigation. Although the mixing and alternate modes of irrigation applications
improved vine water uptake over Gw alone, the impact of salts was still visible comparedto Rw irrigation. The reduction in RWU in the Gw and other scenarios can be ascribed tothe osmotic stress in the root zone due to salt buildup in the soil, which reduces the abilityof vine roots to extract water from the soil [96]. Ben-Asher et al. [65] reported a significant
impact of saline water (4.8 dS/m) irrigation on the seasonal transpiration of grapevines.
Irrigation with saline water not only induced an osmotic effect on the roots but also severely
impacted the green area index, gaseous exchange processes, and photosynthetic activity inthe leaves.
Seasonal evaporation losses (Es) accounted for 46–56% of the water applied, including
rainfall during the growing season (Table 4). Significant differences in Es were observed inall scenarios relative to Rw_n, except for Gw_d, Mix_dl, and Alt_dl. Leaching irrigation (l)scenarios enhanced Es losses as 30 mm irrigation was applied in spring when a large portionof the soil surface was exposed. In the Gw, Mix, and Alt scenarios, a reduction in RWU due
to osmotic stress allowed for an increased Es flux from the soil surface. Under reduced
rainfall conditions (20% less), Es decreased significantly compared to Rw_n, althoughdrought season scenarios with leaching irrigation (l) promoted surface water evaporation
similar to Rw_n. Daily evaporation (Es) losses across different scenarios ranged between
0.01 and 5.6 mm (Figure 3), and high Es losses were observed during spring (August–
September) to mid-summer (December–January). During the early growing period ofLand 2023, 12, 1947

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crops with partial ground cover, such as grapevines, post-winter moist soil water regimes
provide favorable soil surface conditions for evaporation losses. On the other hand, during
mid-summer (December–January), the hot and dry season encourages high Es losses.
Seasonal Es losses of a similar extent in the current study have been reported inother studies in surface and subsurface drip-irrigated grapevines with similar spacing
and climate [72,97]. In contrast, Fandiño et al. [98] reported an Es component comprising
8–15% of ET under different climate conditions due to using a low wetted fraction (0.01)
in their estimation. In sparse vegetation such as grapevine, evaporation often constitutes
a large fraction of ET due to the considerable area between the mid-rows exposed to theatmosphere [99].
Modeled average seasonal drainage (Dr) was remarkably low and varied from 2.8 to
8.2% of the total water application in different scenarios (Table 4). The lowest Dr value wasobserved in the Rw_d scenario, while the maximum Dr was recorded in the Gw_nl scenario.
These scenarios significantly differed from the current practice (Rw_n) and showed theimpact of drought season and annual leaching irrigation, respectively (Table 4). Low Dr
values cannot leach the rootzone salts and favor the deposition of salts in the soil during
the growing season. Daily values of Dr below the root zone (120 cm) varied in responseto rainfall, irrigation, and leaching conditions during 2017–22 (Figure 4). Daily Dr varied
from 0 to 1.2 mm and represented a negligible volume of leaching below the root zone overthe low rainfall period (November 2017 to November 2019). Winter (June–August) rainfall
during 2017 was also much lower (112 mm) than the long-term average (160 mm) in the
study area [59]. The extent of winter rainfall plays a crucial role in generating the bottom
flux below the root zone, which triggers the leaching of salts and maintains a favorable
environment in the soil for water uptake. During the following two vintages (2017–18 and2018–19), there was an extended period of below-average winter rainfall during late spring,when no leaching occurred (Figure 4). Therefore, most rain and irrigation events during
this period were unable to generate drainage surplus below the root zone. This resulted in
the rapid accumulation of salts in the root zone, which could impact the normal growthand yield of the vineyard.

Figure 4. Model-predicted daily bottom fluxes (cm/day) below the root zone (120 cm) of a grapevine
under (a) river water irrigation (Rw_n), (b) Rw + 20% less rain (Rw_d), (c) Rw_n + annual leaching(Rw_nl), and (d) Rw_d + annual leaching (Rw_dl) during 2017–22.

Three major leaching events occurred below the root zone over the simulation period
from 2017–18 to 2021–22 (Figure 4). These were related to above-average annual rainfall
and large rain events during late 2019–20 and throughout 2020–21; this triggered the rapid
flushing of salts from the root zone and restored soil conditions. Phogat et al. [85] found thatprofile establishment is an essential management strategy early in the season to facilitate aLand 2023, 12, 1947

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favorable environment for root development, canopy growth, and profitable horticultural
production in Mediterranean climates. The vineyards in the study region rely heavily on
winter rainfall and flood events in the rain-induced local river catchments to flush the salts
accumulated in the soil profile [100]. Therefore, to enhance the drainage volume, leaching
irrigations play an important role in managing the accumulation of salts in the root zone,
reducing the impact of osmotic stress, and providing a congenial medium for plant growth.
3.3. Crop Coefficients
The model predicted daily values of Tp act , Es , and ETC act for different scenarios wereused to compute the monthly actual basal crop coefficients (Kcb act ), evaporation coefficients(Ke ), and actual single crop coefficients (Kc act ) of wine grapes under current irrigation
practices (Rw_n) over the five seasons (Figure 5). The Kc act values during the initialperiod (Kc act ini ) in the current study varied from 0.33 to 0.84 and showed a large variation
between growing seasons (Figure 5b). A comparison of average values of Kc act,ini (0.56) andKcb act,ini (0.13) (average of September and October) showed a much higher contributionof evaporation during this period, which corresponds to the bud burst and initial canopy
development. Normally, high Kc act ini values and seasonal fluctuations largely reflect thevariability in winter rainfall. For example, monthly rainfall of 61 and 65 mm during
September and October 2020 (compared to 12 and 9 mm during 2018–19) resulted in a
doubling of Kc act ini . A high value of Kc act ini (0.33) was also reported by Silva et al. [101].
The maximum Kc act (0.58) and Kcb act (0.33) were recorded during November-December,which coincides with the maximum canopy size [102].

Figure 5. Estimated monthly values of (a) actual basal crop coefficient (Kcb act ), (b) single crop
coefficient (Kc act ), and (c) evaporation coefficient (Ke ) for drip-irrigated grapevines following current
irrigation practices (Rw_n). Subscripts 1, 2, 3, 4, and 5 represent the values estimated for the 2017–18,
2018–19, 2019–20, 2020–21, and 2021–22 vintages, and ‘av’ represents the average coefficient values
for five vintages.

During the mid-season (November-February), large variations were recorded in theKc act mid values (0.23–0.73). The Kcb act values for the mid-season (Kcb act mid ) varied from
0.23 to 0.44, with a mean value of 0.31, much lower than the average Kcb mid (0.6) adjusted
for the study site under the prevailing climatic conditions. This indicates that grapevines
were irrigated at an almost 50% deficit level. Yunusa et al. [97] and Cancela et al. [103]reported similar Kc act values during the mid-season to the current study. The mean valueof Kc act during the post-harvest period (Kc act end ) was, on average, 0.36, although higher in
April (0.43). The end season Kcb act (Kcb act end ) ranged from 0.02 to 0.51 (average 0.21) andshowed immense variability depending on post-harvest irrigation and soil water regime.
The average Kcb act end is less than half of the corresponding adjusted value (0.48), indicating
deficit moisture regimes adopted by the growers. Very low values of Kcb act end (0.02–0.04)
for the 2017–18 and 2018–19 seasons represent extreme moisture-deficit conditions duringthat period (Figure 5). Significant seasonal fluctuations in the crop coefficients suggest that
irrigation decisions made based on the same/standard Kc values across seasons may leadLand 2023, 12, 1947

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to under- or over-irrigation, affecting the grapevine growth, yield, and efficiency of theirrigation system.
Irrigation water quality had a drastic impact on the crop coefficients. Mean Kcb ini
values for the Gw irrigation were reduced by 7–21% compared to the corresponding
values for the Rw irrigation (Figure 6). The maximum reduction was observed for the
drought (d) scenario, whereas the Gw irrigation with additional annual leaching irrigation(30 mm) showed the lowest impact. The Kcb mid for the Gw irrigation was reduced by 19,
23, 16, and 20% for the normal rain (n), drought (d), l with normal rain (nl), and l withdrought (dl) scenarios, respectively, compared to the respective Kcb mid for the Rw scenario(Figure 6b). A similar reduction pattern (19–27%) in the Kcb end values was observed for theGw irrigation and Kcb act values with other irrigation water quality scenarios (Mix and Alt).
The Kcb ini , Kcb mid , and Kcb end for the Mix and Alt water qualities decreased by 4–12, 7–11,
8–14% and 2–7, 5–8, 8–15%, respectively, compared to the corresponding values for the Rw
irrigation (Figure 6c,d). The reduction in the Kcb act values corresponds to the extent of the
impact of rootzone salinity on RWU by the grapevine, which deviates from the standard
conditions [60]. Rosa et al. [104] reported similar responses on the Kcb act for maize undersaline conditions.

Figure 6. Mean values of monthly actual basal crop coefficients (Kcb act ) (a–d) and evaporation
coefficients (Ke ) (e–h) for a wine grape irrigated with river water (Rw) (a,e), groundwater (Gw) (b,f),
1:1 blending of Rw and Gw (Mix) (c,g), and monthly alternate use of Rw and Gw (Alt) (d,h) undernormal irrigation (n), drought season (d), leaching irrigation with normal rain (nl), and leaching
irrigation under drought (dl).

A wide range of Kc act and Kcb act values of grapevines have been reported in manystudies reviewed by Rallo et al. [90]. These studies have shown that site-specific growing
conditions, including climate, cultivar, training system, ground cover, crop management,
and soil conditions, impact evapotranspiration and crop coefficients of grapevines. Timing,
variability, and extent of these factors lower the generic crop coefficient values [60,68]
estimated by different methods [101,105,106]. Darouich et al. [107] evaluated the crop coefficients of grapevines at three locations in Italy and Portugal using the SIMDualKc model
based on FAO-56 [60]. In their study, low values of Kcb ini (0.09–0.14), Kcb mid (0.27–0.4),
and Kcb end (0.17–0.32) emphasized the impact of site-specific climate, soil, cultivars, andmanagement conditions. In contrast, some studies [108–110] reported high Kc mid values(0.8–1.31). Normally, such deviations in crop coefficients from the generic values occur due
to variable crop conditions due to insufficient or non-uniform irrigation, variable plantdensity and canopy cover, soil salinity, and/or agronomic management [111].
A wide variation was observed in the evaporation coefficient (Ke ) estimated for thecurrent practice (Rw) over the five seasons (Figure 6c). During the initial growth period
under the current practice (Rw_n), large Ke values were recorded (0.23–0.70) because alarge portion of the soil surface was wetted by irrigation and rainfall was exposed to theLand 2023, 12, 1947

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atmospheric evaporative flux. However, the Ke values during the mid-season declined(0.09–0.41; average 0.2) in response to a reduced fraction of the wetted and exposed surface
Phogat [112]. Ke towards the end of the season was only 0.15, except after the post-harvest
irrigation, when it slightly increased (0.2) during April.
3.4. Salinity Dynamics in Soils
The spatial distributions of ECe in the soil under the Rw_n irrigation scenarios werecompared at four phenostages of grapevines, i.e., bud burst, flowering, veraison, andharvest (Figure 7). At bud burst, ECe in the upper 40–50 cm of the soil was <1.5 dS/m, except
during the 2018–19 season, which received below-normal rainfall. Without appropriate
leaching, pockets of ECe in the 1.5–3 dS/m range developed in the surface soil alongside
the vine row. At deeper depths, ECe usually varied in the 1.5–3 dS/m range, but somepockets of ECe in the 3–7 dS/m range were observed. Such variation in ECe in the soil
profile is normal as salt concentrations dynamically vary in space and time in response toirrigation, rainfall, evaporation, and transpiration. Similar salt distributions were observed
until flowering/full bloom, which provided favorable conditions for growth and good vine
health during the initial stages of development sensitive to salinity.

Figure 7. Spatiotemporal prediction of salinity dynamics (ECe ) in the soil under river water (Rw)irrigation at indicated dates (31 August—bud burst, 31 October—flowering, 31 January—veraison,and 30 April—harvest) during (a) 2017–18, (b) 2018–19, (c) 2019–20, (d) 2020–21, and (e) 2021–22
under a grapevine.

At veraison, the soil region with an ECe of 1.5–3 dS/m expanded, and pockets of muchhigher ECe (3–5 and 5–7.5 dS/m) also developed, especially during 2018–19 and 2019–20.
These high salinity zones expanded further during the veraison to harvest period (FebruaryApril). During this stage, regulated deficit irrigation was applied to enhance the wine
quality traits [113,114]. The imposition of deficit conditions results in the upward movementof water and salts in the soil in response to evaporative fluxes at the soil surface andtranspiration fluxes from the root zone. This phenomenon (capillary rise) increases ECe in
the region below the tree line compared to the mid-row region. Numerous studies reported
similar observations under varied climate, cultivar, and irrigation conditions [28,31]. The
salts deposited in the root zone need to be leached deeper into the soil before the start of thenext growing season. Therefore, winter rainfall during the dormant stage plays a criticalrole in managing irrigation-induced salt accumulation in the soil.
The brackish water (Gw) irrigation scenario resulted in a rapid increase in ECe in
the soil (Figure 8). At harvest in the 2017–18 season, ECe in the soil varied between 3

Land 2023, 12, 1947

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and 25 dS/m. These pockets of high salinity were normally observed in the upper soil
layer (0–40 cm) away from the drip line as the lateral wetting front pushed the salts
outward from the vine row [44]. Although subsequent winter rain in the following season(2018–19) reduced the high salinity regions, ECe remained very high at the time of bud
burst and increased continuously during the growing season. In the subsequent seasons(2019–22), high ECe regions further expanded as there was limited rainfall to aid leaching,and more salts were added through irrigation. Eventually, a large region of high salinity(7.5–25 dS/m) developed during the five years of irrigation with Gw, which could impact
the sustainability of irrigated vineyards. High soil salinity due to brackish water irrigationof grapevines has been previously reported in the study region [27,79] and other parts of
the world under similar climates [36]. These results suggest that grapevine irrigation with
Gw is unsustainable and would result in a rapid salt buildup in the soils. Spatiotemporal
ECe distributions in other scenarios are expected to vary between the two extreme examplesof irrigation water quality (Figures 6 and 7).

Figure 8. Spatiotemporal prediction of salinity dynamics (ECe ) in the soil under brackish water (Gw)irrigation at indicated dates during (a) 2017–18, (b) 2018–19, (c) 2019–20, (d) 2020–21, and (e) 2021–22
under a grapevine.

The model-predicted average daily rootzone salinity (ECe ) distributions for the 16 scenarios from 2017 to 2022 are compared in Figure 9. The data showed that the ECe values
remained close to or lower than the tolerance threshold for the river water (Rw) irrigatedscenarios except for reduced rainfall (Rw_d) where the salinity was slightly higher due toa rapid reduction in the drainage component. Alternating Rw and Gw irrigations (Alt_nl)
and blending Rw and Gw in a 1:1 ratio (Mix_nl) with leaching irrigation scenarios showedrootzone ECe comparable to the Rw irrigation. These results suggest that these scenarios
are promising approaches for the adaptation to drought seasons or low water allocations
from the river. In all other scenarios, rootzone ECe increased consistently with time until
April 2020. Thereafter, ECe decreased in response to good winter rainfall and a couple oflarge rain events (30 and 61 mm) occurring in April 2020, which generated intense leaching,pushing the salts deeper into the soil. Salinity (ECe ) increased again during the post-2021
vintage and then decreased gradually during the post-spring season (October 2021). Thesetroughs and peaks in the rootzone salinity are normal occurrences and reflect the extent ofleaching triggered by winter rainfall and irrigation. Normally, troughs contribute significantly to salt leaching below the root zone and help reduce the salinity to a great extent.
Thus, spatiotemporal salinity dynamics in different scenarios represent a dynamic systemthat needs constant monitoring and appraisal of drainage, leaching, and soil degradation.

Land 2023, 12, 1947

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Figure 9. Model predicted average daily rootzone salinity (ECe ) in the soil under a grapevine irrigatedwith different water qualities and reduced rainfall scenarios (Rw = river water, Gw = brackish water,
Alt = an alternate application of river and brackish water, Mix = mixing river and brackish waterin a 1:1 proportion, n = normal rainfall, d = 20% less rainfall, and l = 30 mm annual leaching
irrigation) during 2017–22. The red dotted line shows the threshold ECe (2.1 dS/m) for the grapevinesalinity tolerance.

The daily average ECe values predicted by the model for different scenarios are boxplotted in Figure 10. All scenarios with Rw irrigation (Rw_n, Rw_nl, Rw_d, and Rw_dl)
and alternate mode irrigation (Alt_nl) showed median rootzone ECe values close to thegrapevine tolerance threshold. Rootzone salinity (ECe ) under all Gw, Mix, and Alt scenarios
under drought season (d) showed significantly higher values than Rw_n (current practice). The average ECe under the brackish water (Gw) irrigation with reduced rain (Gw_d)
increased three times relative to Rw_n. The Mix and Alt scenarios with reduced rainfall(drought season) also resulted in salt concentrations higher than the grapevine tolerance
threshold. This indicates increased exposure of grapevine roots to high osmotic pressure,which may restrict plant uptake. Ben-Asher et al. [65] observed a four-fold increase in the
rootzone salinity (from 2 to 8 dS/m) in sandy loam soil with an ECiw of 4.8 dS/m irrigationof grapevine over a single growing season.

Figure 10. Distributions of predicted daily average rootzone salinity (ECe , dS/m) in different scenarios(Rw = river water, Gw = brackish water, Mix = mixing Rw and Gw in a 1:1 proportion, Alt = monthly
alternate use of Rw and Gw, n = normal rainfall, d = 20% less rainfall, and l = 30 mm annual leaching
irrigation) during 2017–22. The red dotted line shows the threshold ECe (2.1 dS/m) for the grapevinesalinity tolerance.

Blended water (Mix_n) showed a 21% reduction in salinity compared to brackish
water irrigation (Gw_n). Monthly alternating Rw and Gw (Alt_n) irrigation reduced thesalinity by 28% compared to Gw_n. Despite a reduction in salinity in these scenarios,

Land 2023, 12, 1947

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the average ECe values (4.5 and 3.8 dS/m) remained higher than the corresponding ECe
observed under the current practice (Rw_n). Average rootzone ECe values in the Alt (Alt_n)
and Mix (Mix_n) scenarios under normal rainfall (n) were further reduced to 3.3 and 3.6
dS/m, respectively, but were still higher than the crop tolerance level. The Alt_n scenario
showed non-significant differences in average ECe compared to the current irrigation
practice (Rw_n).
The annual leaching irrigation of 30 mm during spring (1st September) showed adrastic reduction in the rootzone salinity values in all water quality scenarios (Rw, Gw, Mix,
and Alt). Under normal rain (n), leaching irrigation (l) decreased the average rootzone
salinity by 17–24% in different water quality scenarios, and the mean ECe values decreased
to 2.5 and 2.9 dS/m, respectively, in the Alt_nl and Mix_nl scenarios, which were statisticallyat par with Rw_n and fell in the range of suitable for grapevines [75]. The reduction in
ECe varied from 8 to 17% only under l for reduced rain scenarios (Gw_dl, Mix_dl, and
Alt_dl) compared to their respective scenarios without leaching (Gw_d, Mix_l, and Alt_l)
and ECe (3.2–4.9 dS/m) remained above the tolerance threshold for grapevines. These
results suggest that annual leaching irrigation of more than 30 mm is required for salinity
control in the heterogeneous soils at the study site.
3.5. Leaching Fraction
The fraction of applied water leaving the root zone (leaching fraction, LF) plays a keyrole in flushing the soluble salts and chemicals out of the root zone and helps facilitate thecongenial environment for root water and nutrient uptake essential for plant growth. The
estimated annual LF in the current study varied from 0.05 to 0.16 in different scenarios
over the simulation period (2017–22) (Figure 11). Typically, LF smaller than 0.1 may favor
the salt buildup in soils, posing a threat to the long-term sustainability of crops. Under
the current irrigation practice (Rw_n), the LF was larger than 0.1 only during 2020–21 due
to several large rainfall events (>30 mm) early in the season. It was able to produce anappreciable volume of drainage that transported salts below the root zone. It signifies theimportance of large rain events to flush the irrigation-induced salinity below the root zone.
However, high-intensity rain events may generate more runoff than infiltration into thesoil, depending on the soil type and surface conditions.

Figure 11. Annual leaching fractions (LF) below the root zone (120 cm) of a grapevine under
different water quality (Rw = river water, Gw brackish water, Mix = mixed Rw and Gw in a 1:1 ratio,
Alt = monthly alternate use of Rw and Gw) and management scenarios (n = normal rainfall, d = 20%
less rainfall, and l = 30 mm annual leaching irrigation) during 2017–22 estimated from model predictedwater balance components.

Extremely low LF values (0.005–0.021) were observed during the 2018–19 season
across all scenarios, as annual rainfall (283 mm) was lower than the long-term average of
392 mm [59] in the region, and a few rain events >20 mm (which could generate LF) were
almost negligible. Application of drought season conditions (20% reduction in the annual
rain; the ‘d’ scenarios) had a tremendous impact on the drainage volume because the annualLand 2023, 12, 1947

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LF was reduced by 7–74% during different years. Average LF decreased by 33 to 52% in the
reduced rainfall scenarios (the ‘d’ scenarios) as compared to the normal rainfall scenarios(the ‘n’ scenarios) under different water qualities (Gw, Mix, and Alt); the reduction was
highest in Rw and the lowest in the Gw scenarios. The development of high salinity regionsin the root zone of the Gw irrigation scenarios reduced RWU and allowed more water todrain below the root zone. Negative correlations were observed between the reduction in
RWU and LF under Gw (−0.98), Mix (−0.98), and Alt (−0.98) irrigation scenarios. Other
studies have also reported a similar negative correlation between transpiration and LF [115].
However, numerous other factors, such as soluble chemical constituents, soil physical state,
and flow conditions, may also profoundly impact LF.
The application of annual leaching irrigation (l) of 30 mm in the spring over multiple
growing seasons had a tremendous impact on the extent of drainage and leaching ofsoluble salts in all scenarios (Figure 11). LF increased from 3 to 225% in the normal
irrigation scenarios (nl) and from 9 to 220% in the reduced rainfall scenarios (dl). The mean
increase in LF for river (Rw), brackish (Gw), 1:1 blending (Mix), and monthly alternate(Alt) irrigation under normal and reduced rainfall was 31, 18, 26, and 21% and 55, 22, 38,
and 33%, respectively, compared to the corresponding no-leaching irrigation scenarios.
Among the seasons, 2018–19 recorded a four-fold increase in LF, although it was stillless than 0.1. Even this small leaching fraction can greatly impact the salt balance inthe soil. The LF increased above 0.1 during the 2017–18, 2020–21, and 2021–22 seasons,rapidly flushing the salts out of the root zone. The application of annual leaching irrigation(l) under Rw irrigation (Rw_nl) showed an overall depletion of 1.2 t salts/ha over thesimulation period (Figure 12a). However, in all other scenarios, salt deposition varied
from 2.2 to 16.7 t/ha in response to the salts added through different modes of irrigation
application. Therefore, rootzone salt depletion occurred only in the Rw_nl scenario overthe simulation period. Nonetheless, annual leaching irrigation with the Gw, Mix, and Alt
irrigation modes produced a 1.8–2.2 t/ha reduction in the rootzone salts, indicating this as
a viable management option to manage the irrigation-induced salts in the soil.

Figure 12. Leaching efficiency (a) in terms of salts leached/salts applied (LEs , kg/kg), salts
leached/drainage volume (LEd , kg/m3 ), and salts deposited (+)/depleted (−) in the soil root zone
(120 cm) at the end simulations (b) for different scenarios (Rw = river water, Gw = brackish water,
Mix = mixed Rw and Gw in a 1:1 ratio, Alt = monthly alternate use of Rw and Gw) and managements(under normal n, drought season d, and leaching irrigation l scenarios).

3.6. Leaching Efficiency
The leaching efficiency of salts (LEs ) is defined as the ratio of the salt mass leached
below the crop root zone and the salt mass added through irrigation and rainfall during
a given time (e.g., an annual or crop cycle), which offers a more quantitative measure of
the salt balance [27,116] under drip irrigation. The maximum value of LEs (1.5 kg salts
leached/kg added) was observed in the river water with the leaching irrigation (Rw_nl)
scenario, followed by Rw_n (1.14 kg salts leached/kg added), while the lowest LEs values(0.2–0.3 kg salts leached/kg added) were found in the reduced rainfall scenarios (Gw_d,

Land 2023, 12, 1947

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Rw_d, Alt_d, and Mix_d), indicating a profound influence of drought period conditions,which lead to a rapid reduction in the leaching fraction and drainage volume (Figure 12b).
Annual leaching irrigation (l) (30 mm) increased LEs by 31, 18, 29, and 34% in the Rw,
Gw, Mix, and Alt scenarios, respectively, with normal rainfall compared to their respective
scenarios without leaching irrigation. The annual leaching irrigation also showed a muchhigher increase in LEs (32–139%) in the reduced rain (drought season) scenarios.
Leaching efficiency in terms of the amount of salts leached with a drainage volume(LEd ) below the root zone varied from 1.3 to 4.5 kg/m3 between scenarios (Figure 12b). The
maximum value was observed in Gw_dl whereas the lowest was observed under Rw_dbecause of a higher amount of salts in the former scenario. It suggests that a small leaching
fraction in the Gw_dl scenario triggered large quantities of salts transported out of theroot zone that had accumulated from the Gw irrigation. The average LEd was larger than
1 in all scenarios, which may not imply that rootzone salinity has been reduced below
the crop threshold. For example, even in the Rw_n scenario, the salt balance showed anincrease of the initial salt mass by 0.53 t of salts/ha out of 4.05 tons/ha of salts added
over the simulation period (2017–22) (Figure 12a). It suggests that LEd represents only
the intensity factor for salt leaching and may not provide a valid criterion to estimate theleaching requirement (LR) for salinity management.
The LR is LF, which, when passed through the root zone, reduces the rootzone salts
below the crop threshold [117]. Estimation of LR following steady state uniform soil
conditions typically overestimates LR required for heterogeneous soils that have variationsin their wetting patterns under drip and micro irrigation systems [118,119]. Hanson
et al. [44] observed that, in drip-irrigated systems, it is hard to determine LR due tospatially variable soil wetting patterns that lead to localized leaching below the drip line,
depositing large amounts of salts laterally along the wetting fronts, as observed in thecurrent study (Figures 7 and 8). Calibrated numerical models that accurately simulate waterand salt movement under drip irrigation can help develop better salinity management
guidelines [19]. Phogat et al. [27] estimated LEs in various soils, climatic conditions, water
qualities, and irrigation schedules applied to vineyards. They reported large differences in
LEs values obtained for light-textured deep uniform soil (>1 kg salts leached/kg added)
compared to heavy-textured heterogeneous soils (0.12–0.13 kg salts leached/kg added),showing a tremendous influence of inherent soil transmission properties. They concluded
that in drip irrigation systems, LF that corresponds to LEs ≥ 1 could potentially leachannually added salts from the root zone. Such LF can serve as a good estimate for theleaching of irrigation-induced salts from the root zone. In the current study, LEs > 1 wasobserved in the Rw_nl and Rw_n scenarios, which had an average LF of 0.09 and 0.07
(Figure 13), respectively, and the average rootzone salinity less than the tolerance thresholdof grapevines (Figure 13), maintaining a favorable environment for normal vine growth.
This suggests that LEs > 1 proposed in the previous study [27] can serve as a good indicatorfor sustainable crop production for different soils, climates, and irrigation managements.
However, restricted drainage conditions [51], high SAR of irrigation water, and high soil
ESP, especially in the subsoils, have an immense impact on the mobility of salts in thesoil [116,120,121] and require different management options for salinity control [21].
Water quality and annual rainfall strongly influence the salt leaching in the soil. A
strong positive linear relationship (R2 = 0.99) was found between irrigation water sources(Rw, Gw, Mix, and Alt) and the corresponding leaching fractions (LF) (Figure 13). A
threshold LEs for salinity control (LEs > 1) was achieved with an LF of 0.07, 0.12, 0.12, and0.15 for Rw, Mix, Alt, and Gw water quality irrigation, respectively. This suggests that LR
increased proportionately to the salts added through irrigation. Irrigating the grapevines
below the water requirement added a smaller mass of salts in the soil but could not provide
adequate leaching for salinity control in the study region [79]. The LEs also showed a very
weak but positive linear relationship with annual rainfall, suggesting that an increase inannual rainfall influenced the mobilization of salts out of the root zone, depending on
the timing, amount, and intensity of the rain events. It is worth noting that under theLand 2023, 12, 1947

21 of 29

current irrigation practice (Rw), annual rainfall equal to the long-term average (390 mm) cangenerate LEs > 1, suggesting a typical threshold for maintaining appropriate salt balance inthe soil for irrigated viticulture at the study site (Figure 13b).

Figure 13. Relationship between (a) leaching efficiency in terms of salts leached/salts applied (LEs ,kg/kg) and the leaching fraction (LF) and (b) LEs and annual rainfall under river water (Rw), brackish
water (Gw), mixed Rw and Gw in 1:1 proportion (Mix), and monthly alternate irrigation of Rw and
Gw (Alt) at the study site.

Numerous other studies have shown a strong influence of rainfall on leaching salts
out of the crop root zone. Cucci et al. [122] found that rainfall in autumn and winterproduced a good salt-leaching effect in a sandy clay loam in southern Italy. Isidoro andGrattan [120] also reported that winter rainfall increased leaching compared to rainfall distributed uniformly throughout the year. Similar observations were reported for monsoonal
climates [18], where annual rainfall with high-intensity events occurred during a shortperiod (July–September).
4. Conclusions
An appropriate risk assessment is required for integrating brackish water (Gw) into
crops’ irrigation schedules to provide effective soil salinity management. Estimated low
values of actual basal (Kcb act ) and single (Kc act ) crop coefficients estimated in this study
over five seasons demonstrated that grapevines were irrigated under sustained deficit
conditions. Under the Mediterranean-type climate, winter rainfall is considered to generate
appropriate leaching to maintain a favorable environment. Simulated results confirm
that rainfall reduction (20%) over the five years potentially leads to rapid soil salinization
across all modes of irrigation scenarios [river water (Rw, 0.32 dS/m); brackish water (Gw,
3.2 dS/m); 1:1 blending of brackish and river water; and monthly alternate use of Rw andGw], severely impacting the sustainable production of wine grapes. Under these conditions,
it becomes quite imperative to manage the rootzone salts by applying appropriate leaching
to maintain the sustainability of vineyards.
Models suggested that in the absence of favorable rainfall, leaching irrigation (l) with
good-quality water (Rw) at the beginning of the growing season could best use this highquality but low-availability water source. This strategy significantly increased the saltleaching efficiency (LEs ), and a threshold LEs for salinity control (LEs > 1) was achieved
with a leaching fraction (LF) of 0.07, 0.12, 0.12, and 0.15 for Rw, Mix, Alt, and Gw water
quality irrigation, respectively.
Results further demonstrated that blending or alternating saline brackish water with
non-saline surface water reduced the extent of salt deposition in the soil relative to theapplication of Gw only. These options can be explored further depending on the extent ofsalts in brackish water under projected climate change.
This study recommends applying leaching irrigation early in the season before bu
burst when the soil is almost saturated with winter rain. It provides a strategic management

Land 2023, 12, 1947

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option during drought season and periods of low freshwater allocation to develop resilience
for maintaining sustainable production. However, these options need location-specificevaluation and continuous monitoring of climate, soil, and plant systems to enable longterm adaptation and resilience for irrigated viticulture and other crops.
Author Contributions: Conceptualization, V.P.; methodology, V.P.; software, V.P. and J.Š.; formal analysis,
V.P.; investigation, V.P.; resources and project management, P.P.; data curation, V.P.; writing—originaldraft preparation, V.P.; writing—review and editing, V.P., J.Š., P.P., T.P. and M.C.; visualization, V.P.;
supervision, T.P. All authors have read and agreed to the published version of the manuscript.
Funding: The authors acknowledge the financial support provided by the Department of Agriculture,
Fisheries, and Forestry (DAFF), Australia as part of its Future Drought Fund—Natural Resource
Management—Drought Resilience Program (4-G36U3HW).
Institutional Review Board Statement: Not applicable.
Informed Consent Statement: Not applicable.
Data Availability Statement: Data are available upon reasonable request to the authors.
Acknowledgments: The authors are grateful to Jenny Venus and Nicole Clark of Kimbolton Wines,
Langhorne Creek, South Australia for providing access to the vineyard for conducting research
activities and sharing site management datasets.
Conflicts of Interest: The authors declare no conflict of interest. The funders had no role in the
study’s design, in the collection, analyses, or interpretation of data, in the writing of the manuscript,
or in the decision to publish the results.

Appendix A
Appendix A.1. Brief Description of the Model
This study used a numerical model (HYDRUS-2D; [53]) to simulate the water flow
and salt transport in the soil under wine grapes. The governing two-dimensional waterflow equation for an isothermal and isotropic medium is described as follows:




∂
∂h
∂
∂h
∂θ
=
K (h)
+
K (h)
+ K (h) − S(h, hs , x, z, t)
(A1)
∂t
∂x
∂x
∂z
∂z
where θ is the soil water content (L3 L−3 ); t is the time (T); h is the soil water pressure head(L); x is the horizontal coordinate; z is the vertical coordinate (positive upwards); K(h) is
the hydraulic conductivity (LT−1 ); and S(h, hs , x, z, t) is the sink term accounting for water
uptake by plant roots (L3 L−3 T−1 ).
Water extraction S(h, hs , x, z, t) from the soil was computed according to the Feddes
macroscopic approach [74]. In this method, the potential transpiration rate, Tp , is distributed
over the root zone using the normalized root density distribution function, β(x, z, t), andmultiplied by the dimensionless water [α1 (h)] and salinity stress [α1 (hs )] response functions
as follows:
S(h, hs , x, z, t) = α1 (h, hs , x, z, t)S p ( x, z, t) = α1 (h, hs , x, z, t) β( x, z, t) Tp (t)(A2)

This model calculates plant root water uptake rates according to the local soil waterpressure head, h, at any point in the root zone. It defines how potential transpiration (Tp) is
reduced below potential when the soil can no longer supply the amount of water requiredby the plant under the prevailing climatic conditions. The multiplicative model for theosmotic head reduction is considered in this study as follows:
α1 (h, hs ) = α1 (h)α1 (hs )(A3)Land 2023, 12, 1947

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The reduction of root water uptake due to the water stress, α1 (h), is described as

α1 ( h ) = 0, h > h1 or h ≤ h4 h − h1 , h < h ≤ hh2 − h12

h3 − h4

4

1, h3 < h ≤ h2
 h − h4 , h < h ≤ h

1

(A4)

3

where h1 , h2 , h3 , and h4 are the threshold model parameters. Water uptake is at the potential
rate when the pressure head is between h2 and h3 , decreases linearly when h > h2 or
h < h3 , and becomes zero when h < h4 or h > h1 . These critical values of pressure heads forgrapevine were taken from previous investigations in South Australia [8,72].
Similarly, the threshold model was used to simulate the impact of osmotic (salinity)
stress α1 (hs ), which states that water is extracted at the maximum rate below the crop threshold (ECe = 2.1 dS/m) osmotic head and the slope of the curve determines the fractional
reduction of water uptake per unit increase in osmotic head (12.8%/ECe unit) beyond thethreshold. These parameters for grapevine were obtained from previous regional salinity
tolerance studies [75].
The spatial root distribution is defined in HYDRUS-2D according to Vrugt [123]:zx −( zpz |z∗ −z|+ xpx | x∗ − x|)mβ( x, z) = 1 −
(A5)
1−
e m
zm
xm
where xm and zm are the maximum width and depth of the root zone (cm), respectively, z*
and x* describe the location of the maximum root water uptake from the soil surface in thevertical direction (z*) and from the tree position in the horizontal direction (x*), and px andpz are empirical coefficients. These parameters for grapevine were optimized dependingon the system design parameters and local soil and crop conditions [72].
Appendix A.2. Solute Transport/Salinity Distribution in the Soil
The governing advection-dispersion equation for the simulation of the transport of asingle non-reactive ion in a homogeneous medium is described as








∂
∂
∂
∂
∂
∂
∂(θc)
∂c
∂c
∂c
∂c
=
θDxx
+
θDxz
+
θDzz
+
θDzx
− (q x c) − (qz c)
∂t
∂x
∂x
∂x
∂z
∂z
∂z
∂z
∂x
∂x
∂z

(A6)

where c is the concentration of the solute/salts in the liquid phase (ML−3 ), D is the dispersion coefficient (L2 T), and q is the volumetric flux density (LT−1 ). Soil solution salinity(ECsw ) is simulated as a non-reactive solute in the soil, as described in previous studies [57,76,85]. These studies showed good predictions of soil salinity dynamics in the soil
under intensive irrigation and fertigation conditions.
The longitudinal dispersivity was assumed to be one-tenth of the size of the transportdomain, with the transverse dispersivity being one-tenth of the longitudinal dispersivity
Cote [77]. These values were additionally optimized during the calibration. The salinity ofirrigation (ECiw ) was obtained from the water quality analysis available in the literatureand from previous studies. The rainfall chemistry analysis by Cresswell and Herczeg [59]for the study region provided reliable information about rainfall salinity (ECrw ; 0.16 dS/m).

Land 2023, 12, 1947

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Figure A1. Daily values of reference crop evapotranspiration (ET0 ), rainfall, and irrigation applied towine grapes at the study site during (a) 2017–18, (b) 2018–19, (c) 2019–20, (d) 2020–21, and (e) 2021–22.
Annual amounts of ET0 , rainfall, and irrigation are also given.
Table A1. Values of different parameters used to estimate daily transpiration (Tp ) and daily evaporation (Es ) for wine grapes for the field site following the FAO-56 DCC approach.
Parameter

Value

Parameter

Season

Value

Lini
Ldev
Lmid
Llate
θ fc (0–15 cm)

20
40
120
60
0.23

Mid-season Min RH (%)

2017–18
2018–192019–20
2020–212021–22

39.2
36.9
33.7
36.9
41.0

θ fc (15–30 cm)

0.18

2017–18

1.9

θ fc (30–60 cm)
θ fc (60–100 cm)
fw
fw , Rain
RAW (mm)
TAW (mm)
TEW (mm)
REW (mm)
Plant height h (m)Rooting depth Zr (m)Evaporable depth Ze (m)Kcb ini (generic) 1
Kcb mid (generic) 1
Kcb end (generic) 1

0.31
0.29
0.3
1
84
153
21
7.4
1.5
1.0
0.15
0.20
0.65
0.50

2018–192019–20
2020–212021–222017–18
2018–192019–20
2020–212021–222017–18
2018–192019–20
2020–212021–22

2.1
2.2
1.8
1.8
0.59
0.61
0.62
0.60
0.59
0.46
0.48
0.49
0.47
0.46

Mid-season Av. Wind
speed (m/s)

Kcb mid adj

Kcb end adj

1 Basal crop coefficient values for medium-density wine grapes from Allen and Pereira [68].

Land 2023, 12, 1947

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