Original Research
Thomas Groenveld
Alon Ben-Gal*
Uri Yermiyahu
Naftali Lazarovitch
We hypothesized that the HYDRUS-1D
model could be used to predict dynamic
changes in plant salinity tolerance for a
greenhouse vegetable crop over a full
season and to determine best management practices regarding blending of
saline with desalinated water for optimization of yields and water use efficiency.
T. Groenveld and N. Lazarovitch, Wyler Dep.
of Dryland Agriculture, French Associates
Institute for Agriculture and Biotechnology of
Drylands, Jacob Blaustein Institutes for Desert Research, Ben-Gurion Univ. of the Negev,
Sede Boqer Campus, 84990, Israel. A. Ben-Gal
and U. Yermiyahu, Soil Water and Environmental Sciences, Agricultural Research
Organization, Gilat Research Center, Mobile
Post Negev 2, 85280 Israel. *Corresponding
author ([email protected]).
Vadose Zone J.
doi:10.2136/vzj2012.0180
Received 8 Nov. 2012.
© Soil Science Society of America
5585 Guilford Rd., Madison, WI 53711 USA.
All rights reserved. No part of this periodical may
be reproduced or transmitted in any form or by any
means, electronic or mechanical, including photocopying, recording, or any information storage
and retrieval system, without permission in writing
from the publisher.
Weather Determined Relative
Sensitivity of Plants to Salinity:
Quantification and Simulation
The amelioration of plant salinity tolerance due to reduction in potential evapotranspiration
is a long recognized phenomenon. In spite of this, salinity tolerance of plants is generally
calculated from full season, time- and space-averaged response data. We hypothesized that
the HYDRUS-1D model could be used to predict dynamic changes in plant salinity tolerance
for a greenhouse vegetable crop over a full season and to determine best management
practices regarding blending of saline with desalinated water for optimization of yields and
water use efficiency (WUE). The specific objectives of the study were to determine dynamic
vapor pressure deficit (VDP)–salinity response relationships of bell pepper plants grown in
lysimeters and to apply them for hypothetical management scenarios when irrigating with
blended desalinated and brackish water under commercial conditions. The transpiration
response of bell pepper plants to salinity in the controlled lysimeter experiment was strongly
influenced by variations in potential transpiration throughout the season. The plants were
relatively tolerant during periods of low VPD and relatively sensitive during periods of high
transpiration demand. Data were used to develop salinity response equations as a function
of VPD. In a case study for Israel’s Arava Valley, transpiration and water productivity of bell
peppers could be increased 5% by blending saline and desalinated water such that less
saline water was applied during periods of relatively high sensitivity (high VPD) and more
during periods of relative tolerance as compared to application of the same total of both
sources of water blended at a constant ratio throughout the season. Sensitivity analysis of
the dynamic crop response model revealed that such increases in water productivity would
be even greater for more salt sensitive crops.
Abbreviations: BW, blended water; DW, desalinated water; GW, groundwater; TBW, transiently blended
water; VDP, vapor pressure deficit; WUE, water use efficiency.
Understanding and treatment of the effect of salinity on crops is largely
based on a conceptual model and empirical database presented by Maas and Hoffman
(1977) and variations contributed by others (Feddes et al., 1978; van Genuchten and
Hoffman, 1984). These models are based on full season yield (biomass production)
response to time and depth averaged salinity. In these models, “sensitivity” refers to the
extent to which biomass production is reduced by a given increase in salinity, while “tolerance” indicates relatively low sensitivity. Plant related parameters that describe the severity
of yield reduction due to salinity are presumed to remain the same over time in the models
(van Genuchten and Hoffman, 1984), basically assuming that the plants grow under a
steady state irrigation regime or can be described by average values. Under field conditions, however, the root zone is far from homogenous both in time and spatial dimensions.
Cardon and Letey (1992) pointed out the importance of time variable parameters in the
salinity response function, but they did not demonstrate this in their model. Bhantana and
Lazarovitch (2010) showed that the salinity tolerance of pomegranate (Punica granatum
L.) increased throughout the growing season, and Tripler et al. (2011) showed that from
season to season the salinity tolerance of date palm (Phoenix dactylifera L., ‘Medjool’)
decreased. In none of these cases were changes in salinity tolerance modeled as a function
of a specific cause.
It has been recognized for some time that crops are injured by salt to a greater extent in
warm compared to cool climates (Magistad et al., 1943). Hoffman and Rawlins (1971)
demonstrated that some crops are more tolerant to salinity stress under higher relative
humidity, while others are not. In accordance with this in the reporting of their wellknown threshold slope model, Maas and Hoffman (1977) noted explicitly that “salt tolerance is a relative value based on the climatic conditions under which the crop was grown.”
Much of the information on which their published salt tolerance database (Maas and
www.VadoseZoneJournal.org
Hoffman, 1977) was built originated from experiments performed
in the southwestern United States, limiting its relevance to places
with similar climatic conditions (Maas, 1993).
The climatic variables that determine potential evapotranspiration
(ETp) are temperature, radiation, wind speed, and relative humidity,
which in many cases—particularly in protective structures—can
be fairly represented by the VPD. Together with root zone water
potential, VPD determines plant water potential (Li and Stanghellini, 2001). Increased VPD is known to reduce the fruit growth
rate in tomato because of increased transpiration, direct water loss
from fruit, and water efflux from the fruit to the stem (Johnson et
al., 1992, Leonardi et al., 2000). It appears that at the fruit level
the mechanism involved in response to high VPD is water shortage
and not assimilate shortage, since the VPD has an effect on fruit
fresh weight but not on the accumulation of dry matter (Leonardi et al., 2000). Leonardi et al. (2000) noted that the effects of
increased VPD in their experiment (1.6 vs. 2.2 kPa) were similar
to those previously observed in response to moderate water and
salt stresses (Ho et al., 1987; Adams, 1991; Mitchell et al., 1991).
An et al. (2001) found that salinity stress was reduced in two soybean cultivars at increased relative humidity. Li and Stanghellini
(2001) performed several experiments with two combinations of
salinity and VPD and concluded that both electrical conductivity
(EC) and potential transpiration affected water content of organs.
They demonstrated that a reduction in VPD modified the effect of
the root zone salinity by both increasing the percentage of marketable yield and increasing fresh fruit weight (Li et al., 2001). The
reduction of fresh yield with increased root zone salinity occurred
simultaneously with an increase in relative fruit sugar content (Li
et al., 2001). Plants grown under a lower VPD had significantly
higher WUE than those grown under a higher VPD. Cuartero et
al. (2006) described a similar experimental setup, which resulted
in salinity effects being minimized under high relative humidity.
Karlberg et al. (2006) explored the effect of weather conditions
and salinity on growth of tomatoes in two distinct seasons. They
discussed the effect of salinity on WUE, described as depending
largely on whether reductions in transpiration were due to increased
osmotic gradient or to specific ion toxicity. They concluded that the
WUE of a crop was the result of the prevailing weather during the
growing season in combination with other environmental conditions. Ityel et al. (2012) experimented with a modified root zone
that increased plant available water content. They noted a higher
sensitivity to salinity with increasing VPD for bell pepper plants
and a lower sensitivity for the modified root zone.
Use of climate control in greenhouses has been demonstrated to
increase salinity tolerance (Li et al., 2001; Li and Stanghellini,
2001). Climate control is limited by humidity thresholds at which
fungi may develop or nutrient uptake reduced (Gisleröd et al., 1987;
Grange and Hand, 1987; Adams and Ho, 1993). Climate control
physical systems are expensive and are only applicable to the confined space of a greenhouse. With the advent of desalination and
www.VadoseZoneJournal.org
its increasing use in agriculture (Yermiyahu et al., 2007; Ben-Gal
et al., 2009), modifications to irrigation water salinity throughout
the season have become possible. In Israel many growers currently
have both saline groundwater (GW) and DW available for independent use or mixing before irrigation. Desalinated water lacks
some of the nutrients essential to plant growth that are abundant
in the GW such as Ca, Mg, and S. One possible solution is to
blend the water of these two sources to supply these nutrients. This
process, however, also reintroduces unwanted salts such as NaCl
to the irrigation water (Ben-Gal et al., 2009). Current blending
management applies a fixed ratio of desalinated and saline water
throughout a cropping season. Equipment allowing changes in the
blending ratio over time, often already in place, open up the possibility to change the irrigation water salinity according to expected
temporal plant salinity tolerance variations.
Numerical models describe plant water uptake and temporal–
spatial variable salinity in the root zone. Plant salinity tolerance
can feasibly be considered in a transient manner, similar to the
approach of Feddes et al. (1978) for water stress, by altering the
parameters used in the salinity response models over time as a function of the VPD. The macroscopic numerical model HYDRUS1D (Šimůnek et al., 2008a) considers transient water flow, solute
transport, and compensated plant root water and nutrient uptake.
These are calculated as a function of soil hydraulic properties, irrigation salinity and amount, root distribution, ETp, and ion uptake,
as described in Šimůnek and Hopmans (2009). The water flow
algorithm in HYDRUS-1D has been widely tested and used for
different applications (Šimůnek et al., 2008b), including use of the
root water uptake model (Zhu et al., 2009) with N transport and
uptake (Cote et al., 2003; Gärdenäs et al., 2005; Hanson et al.,
2006) or with salinity (Skaggs et al., 2006; Shouse et al., 2011;
Oster et al., 2012; Ramos et al., 2012). Yet, until today, simulations of salinity effect on water uptake were performed solely using
parameters that were constant over time.
We hypothesized that the HYDRUS-1D model could be used to
predict dynamic changes in plant salinity tolerance for a greenhouse vegetable crop over a full season and to determine best
management practices regarding blending of saline with desalinated water for optimization of yields and water productivity. The
specific objectives of the study were to determine dynamic VDP–
salinity response relationships of bell pepper plants grown in lysimeters and to apply them for hypothetical management scenarios
when irrigating with blended desalinated and brackish water under
commercial conditions.
66Materials and Methods
Greenhouse Experiment
Bell peppers (Capsicum annuum var. Celica) were grown on an
automated rotating system, consisting of 24 barrel-shaped lysimeters (Lazarovitch et al., 2006), each with a 0.2-m radius and depth
p. 2 of 11
of 0.6 m, located in a greenhouse at the Gilat Research Center in
the northwestern Negev, Israel (31°20¢ N, 34°40¢ E). The lysimeters incorporated a 70-cm drainage extension of highly conductive media (rockwool) to ensure negative soil water potential at
the soil lower boundary without influences water flow through
the system (Ben-Gal and Shani, 2002). The lysimeters were filled
to a depth of 0.55 m with a sandy soil (91% sand, 1% silt, 8% clay).
The lysimeters were flushed with water of their respective salinity
treatment before transplanting the seedlings to leach out any contaminants and to ensure that the drainage water EC was equal to
the irrigation water EC at the start of the experiment.
The irrigation solution was composed of distilled water to which
the nutrients essential for plant growth were added at the concentrations considered optimal for bell pepper production (BenGal et al., 2009). Fertilizers (potassium sulfate, calcium nitrate,
monopotassium phosphate, magnesium nitrate, ammonium sulfate, ammonium nitrate, and micronutrients) were added to reach
65 mg L−1 Ca, 30 mg L−1 Mg, 48 mg L−1 SO4 –S, 0.3 mg L−1 B,
99 mg L−1 N, 23 mg L−1 P, and 176 mg L−1 K. NaCl was added at
eight different concentrations: 0, 2.5, 5, 7.5, 10, 15, 20, and 40 mM.
The resulting irrigation water EC levels were 0.9, 1.2, 1.4, 1.7, 2.1,
3.1, 3.9, and 6.7 dS m−1, reflecting the effect of nutrients as well as
NaCl added to the irrigation water. Each salinity treatment was
replicated three times. Nutrients contributed 0.6 to 0.9 dS m−1 to
each treatment. The soil was sandy enough that effects of sodicity
due to differing Na to Ca and Mg ratios were not expected. The pH
of the irrigation water was stable at approximately 5.8 during the
entire season. Irrigation solution EC was measured weekly, and its
macronutrient composition was measured every 2 wk.
Three pepper seedlings (Capsicum annuum var. Celica) were transplanted to each lysimeter on 13 Sept. 2009 and thinned to one
plant after 2 wk. Each lysimeter was irrigated 2 L d−1 with solution
of its respective salinity for the first 30 d and from then on was irrigated at 130% of the average evapotranspiration (ET) measured in
each treatment (leaching fraction of 0.23), which was determined
twice a week by a water balance:
ET = I - D -S [1]
where I (kg) is irrigation, D (kg) is drainage, and DS (kg) is the
difference in the lysimeter mass between the beginning and end of
the period over which the water balance was determined. Evaporation was kept minimal by mulching the soil with air-permeable
geotextile around the plant so that ET was assumed to equal transpiration (T). The twice weekly mass balance allows the assumption that plant dry matter increases were negligible compared to
water fluxes. Plant protection and maintenance were according
to local commercial practices. Drainage water EC was measured
twice a week and its macronutrient and NaCl concentration were
measured every 2 wk.
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The experiment was conducted from September to December, and
the relative humidity and temperature were continuously measured
to calculate the VPD within the greenhouse. The soil solution
salinity was assumed to be equal to the drainage water salinity
as found in previous similar studies (Ben-Gal et al., 2008). Flowers were removed regularly throughout the season so that growth
was only vegetative. In this way the relative transpiration was kept
similar to the relative plant biomass. Total biomass yield was determined as above ground (leaves and shoots) biomass removed and
dried after 98 d.
Assessing Salinity Sensitivity—Weather
Relationships
A modified version of HYDRUS-1D (Šimůnek et al., 2008a) was
used to simulate plant response of peppers irrigated with varied
irrigation water salinity. Yield was reduced as soil solution salinity
increased according to the sigmoid-shaped function of van Genuchten and Hoffman (1984):
Ya
=
Yp
1
ö÷P
÷÷
÷
e50 ø
æ ECe
1 +ççç
çè EC
[2]
where Ya is actual yield, Yp is potential yield, ECe50 (dS m−1) is the
EC of saturated paste extract of soil (ECe) at which the yield is 50%
of the potential yield, and P (–) is an empirical shape parameter
that determines the steepness of the reduction of yield between
the maximal and 50% yield (van Genuchten and Gupta, 1993).
The ECe50 and P parameters are empirically derived but nonetheless have identifiably biophysical characteristics (Steppuhn et al.,
2005). To consider a change in plant salinity tolerance in time steps
smaller than a full season, a linear correlation between relative
transpiration and relative yield was considered:
Ya Ta
=
Yp Tp
[3]
where Y is the yield, T is transpiration, and the subscripts a and
p stand for actual and potential, respectively (de Wit, 1958; BenGal et al., 2003). Changes in plant salinity tolerance over time
were determined by recalculating the ECe50 parameter according
to 10-d averaged soil solution salinity and transpiration. The P
parameter of Eq. [2] was kept fixed throughout the season and
was determined by optimizing both it and the ECe50 to fit the
season–total yield data. The software used for these calculations
was the solver program of Microsoft Excel.
The threshold–slope salinity reduction model in HYDRUS-1D
includes a database of parameter values for different crops based on
Maas (1990). To normalize the effect of soil type on water content
and salinity seen by the plant roots, these values are based on the
p. 3 of 11
Table 1. Simulation of pepper response to irrigation water salinity and management options.
Treatment†
EC‡
I/ETp§
LF¶
dS m−1
I
T
WP#
Cl drain††
N uptake‡‡
N drain‡‡
————— g m−2 ———————————
——— mm —————
DW
0.96
1.15
0.13
763
478
0.63
37
40.9
11.0
BW
1.78
1.45
0.31
1015
433
0.43
239
35.8
36.5
GW
4.20
2.50
0.60
1661
294
0.18
1299
23.6
101.3
TBW
0.96–2.5
1.18–2.5
0.13–0.6
1011
456
0.45
238
36.9
36.3
† The four treatments applied: DW is desalinated water, BW is blended water, GW is groundwater, and TBW is transiently blended water.
‡ EC is electrical conductivity of the water.
§ I/ETp is applied irrigation (I) divided by potential evapotranspiration (ETp).
¶ LF is target leaching fraction (drainage/irrigation).
# Water productivity (WP; T/I).
†† Cl drained from root zone.
‡‡ N uptake and N drained from root zone.
EC of the saturated paste extract (ECe in dS m−1). HYDRUS1D converts the ECe–based values to the equivalents in terms of
soil solution at field capacity before determining the reduction in
transpiration due to the calculated salinity at every depth in the
root zone (Skaggs et al., 2006). To apply it in HYDRUS-1D, the
ECe50 parameter of the van Genuchten and Hoffman (1984) salinity reduction function was converted to the equivalent value at field
capacity, which we will refer to as ECfc50. To model the effect of
VPD on plant salinity tolerance as observed in the experiment,
the HYDRUS-1D model was manipulated such that the ECfc50
parameter changed transiently as a function of the VPD:
æ VPD ö÷b
ECfc50 = a çç
÷
èç VPD* ø÷
[4]
where VPD* is a reference VPD taken as 1 kPa, a (dS m−1) and
b (–) are empirical parameters describing the dependence of the
ECfc50 parameter on the VPD. For modeling purposes, an asymptotic function was chosen as the VPD range of the dataset used
exceeded that of the experimental data. The a and b parameters
were determined so that the ECfc50 values would not extend
beyond those measured in the experiment.
Simulating Water Management
of Bell Peppers
We demonstrate an example of possible consideration of weather–
plant response to salinity relationships via the simulation of bell
pepper transpiration over a full season under four salinity treatments, namely saline GW, DW, water blended at the same ratio
the entire season (BW), and transiently blended water (TBW).
The BW consisted of DW and GW mixed at a ratio of 3:1, a rate
expected to supply sufficient Ca, Mg, and S for nonlimited plant
growth (Ben-Gal et al., 2009). In the TBW treatment, the irrigation water electrical conductivity (ECiw) was changed over time
to match the plant salinity tolerance:
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ECiw = dECfc50 +e
[5]
where d (–) and e (dS m−1) are empirical parameters determined by
minimizing the total irrigated amount under the condition that
the season–total mixing ratio stayed the same as that of the BW
treatment. The total season irrigation amount was minimized by
solving for the lowest season total irrigation amount under the
constraint that the season total ratio between saline and desalinated water stayed the same as the BW treatment. In this way, the
treatments received identical amounts of Ca, Mg, and S from the
GW. The season total mixing ratio stayed the same so that the
BW and TBW could be compared. This linear conversion formula
was used for simplicity; however, the optimal relationship between
ECiw and ECfc50 may be nonlinear.
Each of the salinity treatments were irrigated at the rate required to
achieve 95% of potential yield, up to an I/ETp (irrigation/potential
evapotranspiration) of 2.5 for GW, as determined using a modified
version of Shani et al.’s (2007) ANSWER model. As opposed to
empirical steady state models that determine the leaching requirement for a specific growth rate (Letey et al., 2011), the ANSWER
model considers plant sensitivity to water stress, ETp, and soil
hydraulic parameters in an analytical expression. The three treatments of fi xed salinity (DW, BW, GW) were irrigated at a fi xed I/
ETp rate. The I/ETp rate of the TBW treatment varied between
1.18 and 2.5 throughout the season as the irrigation water salinity
changed, to achieve 95% yield according to the same model. An
overview of the treatments can be found in Table 1. Examples of
ANSWER model application for bell peppers in the same soil and
climate can be found in Ben-Gal et al. (2008, 2009).
The simulations were run with environmental data (Ben-Gal et
al., 2009) from the August 2006 to April 2007 growing season at
the Zohar Research and Development station located just south of
the Dead Sea (30°57¢ N, 35°23¢ E, 350 m below sea level). In this
p. 4 of 11
Fig. 1. The Class A pan evaporation at the Zohar Experimental Station
during the 2006 to 2007 growing season (ETp) and the vapor pressure
deficit (VPD) inside the net house.
desert region, summer temperatures are extremely high and the
winter temperatures are mild, allowing a winter growing season
when there is a high market demand for vegetables. Seedlings
are planted in the late summer when the potential transpiration
is still relatively high, produce fruit through the winter season
with low potential transpiration, and stop producing when the
transpirational demand becomes exceedingly high in the spring
(Fig. 1). The reference evapotranspiration (ET0) was measured in
a Class A pan located outside the net house, and the crop factor
(Kc) recommended for bell pepper by the extension service of the
Israeli Ministry of Agriculture was used to estimate the potential
transpiration (Tp) for the plants growing inside the net house. The
VPD was calculated from the relative humidity and temperature
measurements performed inside the net house at 2-m height.
The van Genuchten–Mualem model (van Genuchten, 1980) was
used to simulate water flow without considering hysteresis in the
HYDRUS-1D simulations. For solute transport, the equilibrium
model was used with the Crank–Nicholson implicit scheme for the
time weighting and Galerkin finite elements for the space weighting scheme. The longitudinal dispersivity of the soil was 10 cm,
and the bulk density was 1.5 g cm−3. The effect of the matric and
osmotic stresses was considered to be multiplicative, as suggested
by Shani and Dudley (2001). Root distribution, kept constant
throughout the simulation, was linear assuming maximum at surface and 0 at 50 cm depth. The parameters for S-shaped water stress
reduction (van Genuchten, 1987) were kept as the default values,
namely the pressure head at which there is 50% reduction as −800
cm and the P3 parameter (dimensionless shape of drought stress
function) as 3. Soil hydraulic properties used were from Carsel and
Parrish (1988) for sandy soil.
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Fig. 2. Average accumulative transpiration of the eight salinity treatments in the lysimeter experiment. Error bars are standard deviation
of final values.
Relative Importance of Plant Salt
Sensitivity Parameters
After simulating seasonal transpiration according to the experimentally determined VPD–ECfc50 relationship, parameters a and b
(Eq. [4]) and P (Eq. [2]) were varied to explore the effect of climatic
conditions on the plant salinity tolerance over a broader range. The
seasonal Cl load for each treatment was calculated from the irrigation water concentrations and amount. The amount of N taken up
and leached out from below the root zone was calculated with the
model using passive uptake (Šimůnek and Hopmans, 2009).
6 Results and Discussion
Experimental Vapor Pressure Defecit–Salinity
Response Relationships
Increasing irrigation water salinity strongly reduced average accumulated transpiration rates in the lysimeter experiment (Fig. 2).
The most saline treatment reduced transpiration to less than half
of that of the least saline treatment. Increases in transpiration
over time were approximately linear since transpiration demand
decreased due to cooling weather as plant size increased. The
slope and intercept of the linear relationship between relative
transpiration and relative yield (normalized to maximum values
within the experimental dataset) were not different from 1 and 0,
respectively, at a 95% confidence interval (P < 0.0001) (Fig. 3, Eq.
[3]). Th is relationship enabled relative transpiration determined
daily to be used as an indicator of the plant response to salinity
over time. The ECe parameter of Eq. [2] also varied over time and
was estimated from the drainage water salinity. Figure 4 shows
the EC of the drainage water of the eight salinity treatments
measured throughout the season, with the different treatments
clearly distinguished. The fact that the drainage water salinity
did not increase much over time demonstrates apparent steady
p. 5 of 11
Fig. 3. The relationship between whole season relative transpiration
and relative dry biomass yield for the bell pepper lysimeter experiment. Ta is actual transpiration, Tp is potential (maximum) transpiration, Ya is actual dry above ground biomass, and Yp is potential (maximum) biomass.
Fig. 4. Average drainage water salinity of the eight salinity treatments
in the bell pepper lysimeter experiment over time. EC is electrical conductivity. Error bars are standard deviation of final values.
state conditions caused by regular irrigation and the constant
leaching fraction of 0.23 (Tripler et al., 2012).
Parameter optimization of the van Genuchten–Hoff man salinity reduction function (Eq. [2]) for the full season data resulted
in ECfc50 of 6.5 (dS m−1) and P of 1.65 (R 2 = 0.77). The ECfc50
parameter was recalculated for short time steps throughout the
season (Fig. 5), with the P parameter fi xed at 1.65. Contrary to
the common assumption that the parameter stays the same, the
ECfc50 parameter varied greatly over time, tripling in value in a
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Fig. 5. Vapor pressure deficit (VPD) and the electrical conductivity of
soil solution at field capacity causing 50% reduction in transpiration
(ECfc50). ECfc50 and VPD calculated for 10-d running averages at the
bell pepper lysimeter experiment.
Fig. 6. The electrical conductivity of soil solution at field capacity causing 50% reduction in transpiration (ECfc50) as a function of vapor
pressure deficit (VPD) at the bell pepper lysimeter experiment. The
exponential decay function is displayed with best fit a and b parameters (Eq. [4]).
period of less than 2 wk (after DAT 55). The VPD measured in
the greenhouse was inversely correlated to the ECfc50 parameter, indicating that when the transpiration demand dropped,
plant salinity tolerance increased. The ECfc50 values plotted as
a function of the VPD in Fig. 6 results in an inverse correlation
with a power equation having an R 2 value of 0.68. The choice to
describe the correlation by means of a power equation instead of a
linear equation is because it is assumed that as the VPD increases
the ECfc50 parameter will level off gradually, with the heat stress
associated with extremely high VPD causing stomata closure following severe plant stress (Avissar et al., 1985) before the ECfc50
p. 6 of 11
Fig. 8. The effect of increasing and decreasing P (Eq. [2]) and ECe50
(Eq. [4]) on the percentage of difference in transpiration between the
transient and constant blended water treatments (%D).
Fig. 7. (a) Cumulative transpiration and (b) cumulative leached chlorides of the four salinity treatments. Desalinated water (DW), transiently blended water (TBW), blended water (BW), groundwater
(GW).
would reach zero. The best fit a and b parameters were 4.61 (dS
m−1) and −0.61 (–), respectively.
Simulated Water Management Strategies
Simulated accumulated transpiration (Fig. 7) was lowest for GW
(294 mm with 1661 mm irrigation) and highest for DW (478 mm
with 763 mm irrigation). The resultant Cl load to the GWwas 37 g
m−2 for the DW treatment, as opposed to 1299 g m−2 for the GW
treatment. Irrigation with BW resulted in reduced transpiration
eventually reaching 5% less than that of DW. The BW and TBW
treatments received the same amount of saline and desalinated
water over the course of the season (Table 1) and therefore had
identical Cl load (Fig. 7 and Table 1). When considering the a
and b parameters calculated from the experimental data, the P
parameter fi xed at 1.65 and the d and e parameters optimized at
0.294 (–) and 0.384 (dS m−1), respectively, the TBW treatment
transpired around 5% greater than the BW treatment by the end
of the season (Table 1). The increased transpiration was due to
manipulation of irrigation water salinity considering differences
in plant salinity tolerance over time; the transpiration of the TBW
was higher than the BW treatment during the periods of high
www.VadoseZoneJournal.org
potential transpiration (compare Fig. 1 and 7) when the treatment
received less saline water. During the cooler times in the growing
season, the opposite occurred as the TBW irrigation water was
more saline than the BW treatment. Irrigation with lower salinity
water allows higher water productivity (Table 1) since more of the
water is utilized in transpiration (= biomass production) and less
for leaching salts. Manipulating irrigation water salinity such that
higher salinity was applied during periods of relatively low sensitivity was shown to increase water productivity by 5% compared to
a constant blending scheme. Equal irrigation water N concentration was given to the plants and therefore there was much more N
leached from the root zone with the GW treatment where a high
LF was used to leach out the salts (Table 1).
The differences in transpiration between the TBW and BW treatments presented thus far reflect modeling based on parameters
determined from the lysimeter experiment. Results are expected
to be a function of specific crop sensitivity. Figure 8 shows the
effect of increasing and decreasing the P parameter and the range
of ECfc50 values (equivalent to changing the a and b parameters
of Eq. [4]) on the percentage difference in transpiration (%D). Van
Genuchten and Gupta (1993) evaluated the P values of 204 plants
from published studies. They reported a median value of 3.05 and
a reasonable normal distribution with most falling between 1 and
5. A plant with higher sensitivity to salinity (lower ECfc50) would
have an increasing %D over this range of P values, whereas less
sensitive plants to salinity (higher ECfc50) would have decreasing
%D when the P value increases above 3 (Fig. 8). Increases in %D
are the steepest in the low P value range for all ECfc50 ranges. This
exemplifies that the potential to manipulate dynamic, meteorological conditions related response by changing irrigation water salinity or altering leaching fractions is crop dependent and highest for
those with the greatest overall sensitivity to salinity.
p. 7 of 11
In this work the problematic use of whole season data to model
responses occurring over short time periods is addressed. Certainly,
one could raise a similar concern regarding the use of root zone
averaged conditions for driving two- or three-dimensional solutions
of root uptake. In our case, the high leaching fractions and shallow
rooting depths in both the lysimeter experiment and in the simulations were expected to create near one-dimensional conditions
regarding water content and solute concentration in the root zone,
rendering the assumption reasonable. This of course will not always
be the case; therefore, root depth or density specific water uptake
reduction due to salinity should be rectified in future studies.
knowing the plant sensitivity to salinity over time a controlled
stress may be introduced, to induce flowering for example. Other
applications of the transient salinity reduction model may be in
fertigation management to manipulate interactions between salinity and nutrient uptake, in determining which crops are optimal to
grow under certain environmental conditions, or to predict value
of adjusting environmental conditions by means of climate control.
Acknowledgments
This work received funding from The Chief Scientist of Israel’s Ministry of Agriculture and Rural Development (Grant 304-0393), by the I-CORE Program of the Planning and Budgeting Committee and the Israel Science Foundation (Grant 152/11),
and from North-Central Arava Research and Development. Thanks are due to Eugene Presnov, Inna Faingold, and Ludmila Yusupov of the Gilat Research Center for
technical field and laboratory support.
66Conclusions
The transpiration response of bell pepper plants to salinity in a controlled lysimeter experiment was found to be influenced by variations in potential transpiration throughout the season. The plants
were relatively tolerant during periods of low VPD and relatively
sensitive during periods of high transpiration demand. Data were
used to develop salinity response equations as a function of VPD.
In a case study for Israel’s Arava Valley, transpiration and water
productivity of bell peppers could be increased 5% by blending
saline and desalinated water such that less saline water was applied
during periods of relatively high sensitivity (high VPD) and more
during periods of relative tolerance as compared to application of
the same total of both sources of water blended at a constant ratio
throughout the season. Sensitivity analysis of the dynamic crop
response model revealed that such increases in water productivity
would be even greater for more salt sensitive crops.
We believe these results to be of interest, in spite of the fact of the
limitations set by the use of only a single, unique crop (bell pepper) as
a case study. Additional limitations to the approach presented in the
current study were dictated by the HYDRUS model. Consideration
of plant and root growth in response to conditions, not allowed for
by HYDRUS, is certainly necessary for truly accurate simulations.
It is crucial to understand the effect of weather on plant salinity
tolerance to adjust the salinity reduction parameters determined
under one set of conditions for use under different conditions. The
threshold–slope type salinity functions are time-proven robust
models used worldwide; by considering the transient nature of
their parameters, they will remain as relevant in numerical models
as they have been until now in steady state models. Other aspects
that can potentially be explored with this transient approach to
salinity stress modeling include the effects of LF, rooting depth,
or irrigation frequency on salinity and temporal drought stress.
Increasing transpiration by responding to changes in plant salinity tolerance is a potential management practice where different
water qualities are available. Higher water quality comes at a price,
however, and the tradeoff between increased yield and higher cost
of inputs (water) may be calculated by means of this model. By
www.VadoseZoneJournal.org
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