Article

Impact of Drought and Changing Water Sources on Water Useand Soil Salinity of Almond and Pistachio Orchards:
1. Observations
Sarah A. Helalia 1 , Ray G. Anderson 1,2, * , Todd H. Skaggs 2 , G. Darrel Jenerette 3 ,Dong Wang 4 and Jirka Šimůnek 1, *
1

2

3

4

*

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Citation: Helalia, S.A.; Anderson,
R.G.; Skaggs, T.H.; Jenerette, G.D.;
Wang, D.; Šimůnek, J. Impact ofDrought and Changing Water Sources
on Water Use and Soil Salinity of
Almond and Pistachio Orchards: 1.
Observations. Soil Syst. 2021, 5, 50.
https://doi.org/10.3390/
soilsystems5030050
Academic Editors:
Thomas Baumgartl andMandana Shaygan

Department of Environmental Sciences, University of California Riverside, Riverside, CA 92521, USA;shela001@ucr.edu or sarah.awad.helalia@gmail.com
US Salinity Laboratory, Agricultural Water Efficiency and Salinity Research Unit, USDA—Agricultural
Research Service, Riverside, CA 92507, USA; todd.skaggs@usda.gov
Department of Botany and Plant Sciences, University of California Riverside, Riverside, CA 92521, USA;
gdjen@ucr.edu
San Joaquin Valley Agricultural Sciences Center, Water Management Unit, USDA—Agricultural ResearchService, Parlier, CA 93648, USA; dong.wang@usda.gov
Correspondence: ray.anderson@usda.gov (R.G.A.); jsimunek@ucr.edu (J.Š.); Tel.: +1-951-369-4851 (R.G.A.)

Abstract: Soil salinity increases when growers are forced to use higher salinity irrigation waters
due to water shortages. It is necessary to estimate the impact of irrigation water on soil properties
and conditions for crop growth to manage the effects of salinity on perennial crops. Therefore, inthis study, we monitored root zone salinity in five almond and pistachio orchards in eastern andwestern San Joaquin Valley (SJV), California (CA). Volumetric soil water contents and bulk electricalconductivities were measured at four root-zone depths. Evapotranspiration was measured by eddy
covariance along with three other types of data. The first is seasonal precipitation and irrigation
patterns, including the temporal distribution of rains, irrigation events, and irrigation water salinity.
The second is soil chemistry, including the initial sodium adsorption ratio (SAR) and soil soluteelectrical conductivity (ECe). The third type is the physical properties, including soil type, hydraulicconductivity, and bulk density. As expected, we found low salinity at the eastern sites and higher
salinity at the western sites. The western sites have finer textured soils and lower quality irrigationwater; measured actual ET was about 90% of modeled crop ET. Across the three western sites, theannual average apparent leaching fraction ranged from 11 to 28%. At the eastern sites, measured ET
almost exactly matched modeled crop ET each year. Apparent leaching fractions in the eastern sites
were approximately 20%.

Received: 19 July 2021
Accepted: 17 August 2021
Published: 25 August 2021

Keywords: almonds; pistachios; evapotranspiration; salinity; sodicity

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1. Introduction
The San Joaquin Valley (SJV), located in the southern portion of California’s Central
Valley, is one of the most productive farming areas of the United States. Irrigation in the SJV,
CA, started at the end of the 19th century, and substantial groundwater pumping started
in the 1920s [1]. However, continuous salt buildup in the soils limits the western SJV’s productivity and sustainability [1]. The lack of drainage and increasing use of higher salinity
groundwater (versus lower salinity surface water from the State of California and U.S. federal goverments’ State Water Project and Central Valley Project) have been the main factors
increasing soil salinity in the western SJV. Recently, drip irrigation has become increasingly
prevalent in the SJV [2]. Drip irrigation increases the complexities of wetting fronts andsalinity management [3]. Under less effective management and potentially insufficiently
low leaching [3], drip irrigation leads to increases in the salinity-impacted zones [4].

4.0/).

Soil Syst. 2021, 5, 50. https://doi.org/10.3390/soilsystems5030050

https://www.mdpi.com/journal/soilsystems

Soil Syst. 2021, 5, 50

2 of 25

Approximately 47,000 hectares in SJV have been retired (permanently removed from
irrigation) due to regional drainage problems (high salinity, shallow groundwater), andeven more land retirement is anticipated in the future [5]. However, annual rainfall in SJV
is not enough to sustain cultivated agriculture [6] as 85% of rain occurs between November
and April with significant interannual variations. Hence, the highly productive SJV relies
on irrigation on a massive scale, which is possible because of an extensive statewide water
distribution system that brings water from the northern part of the state and from the Sierra
Nevada mountains [7].
Beyond water and water availability, a second key to understanding SJV agriculture issoil geology. The SJV floor is formed primarily by alluvial and lacustrine plains [8]. The
western SJV consists of alluvial and lacustrine deposits, from which much of the Valley
soils are derived. These soils of marine origin are mostly high in natural salts and traceelements such as boron and selenium [9]. Groundwater in the western SJV tends to be
more saline than in the east, where unconfined aquifers contain coarser sands of granitic
origin and better quality water [8]. The poor drainage conditions in the western SJV impact
crop production adversely [10–12].
In recent years, the SJV has seen a significant shift from annual to perennial crops andfrom furrow and flood irrigation to microirrigation (drip or microsprinklers). Agriculturein the SJV has a long history, but the trend towards perennial orchards and drip irrigation
systems is relatively recent. Although tree nut farmers are committed to improving theefficiency of water used for food production [13], the impact of drip irrigation and perennial
cropping systems on long-term salinity and water management is not fully understood,
especially under highly variable water quantity and quality conditions that may become
increasingly common in California in the future.
To understand the salinity and water use impacts of this changing water availability
in perennial nut crops, we conducted a combined observational and modeling study in
the SJV using data from five eddy covariance sites across a salinity gradient [14–18]. In
the first paper (part 1), we report observations on the effects of drip irrigation systems,
irrigation water quality, soil quality, and rain on soil root zone salinity, soil moisture, andcrop evapotranspiration in commercial orchards. These data and observations are needed
to develop models that can be used to assess the possible future use of lower quality saline
groundwater for irrigation in dry years. The data will also help clarify the salinity and water
dynamics that occur in salt-affected almond and pistachio orchards under drip irrigation.
2. Materials and Methods
2.1. Field Sites
Five commercial SJV orchards were chosen for monitoring and evaluating seasonal
water and salinity trends under drip irrigation. The network of field sites was part of aconcurrent USDA-ARS study assessing soil and water quality impacts on crop productivity,with eddy covariance towers at all five orchards [14–18] (Figure 1 and Table 1—see also
Fisher et al. [19]). The orchards had varying crop types (almond, pistachio), soil and watersalinities (low, medium, high), and geographic locations (east vs. west SJV). The pistachio
sites were of the Kerman (female)/Peters (male) cultivars with UCB-1 rootstock. ASL and
ASH had three cultivars (Nonpareil, Monterey, and Mission) planted in alternating rows,
while ASM had Butte and Padre cultivars. All almond sites had Nemaguard rootstock.
In Table 1, the salinity designations low, medium, and high are informal descriptors
indicating relative salinity levels at the sites. As a point of reference, USDA advises thatsalinity effects on crop yields are mostly negligible in the range ECe = 0–2 dS/m, canrestrict the yields of sensitive crops in the range 2–4 dS/m, and will restrict the yields
of most crops in the range 4–8 dS/m [20]. Almond is classified as a “sensitive” cropwith reported Maas–Hoffman [21,22] threshold and slope parameters of 1.5 dS/m and
19% per dS/m, respectively [21]. Maas and Hoffman [21] rated pistachio as “moderately
sensitive”, although subsequent studies found the threshold to be 8–10 dS/m and the slope
around 10% per dS/m [23–25].

Site Name

Soil Syst. 2021, 5, 50

Designation
Almond Salinity High
US-ASH
Almond Salinity Medium
US-ASM
Almond Salinity Low
US-ASL
Pistachio Salinity HighUS-PSH
Pistachio Salinity Low
US-PSL
1 Soil solution extract electrical conductivity (ECe).

Size (ha)(dS/m) 1
2.2–4.1
1.8–3.5
1.3–1.9
2.3–4.7
1.1–2.1

81
53
16
63
16

Year Planted
1998
2006
2010
2006 3 of 25
2008

Figure 1. Map of the location of the five field sites in the San Joaquin Valley, California. The inset
Figure 1. Map of the location of the five field sites in the San Joaquin Valley, California. The inset
map shows the extent of the study area within the state of California.
map shows the extent of the study area within the state of California.

Site Name
Almond Salinity High
Almond Salinity Medium
Almond Salinity Low
Pistachio Salinity High
Pistachio Salinity Low

The fiveorchards
all andirrigatedwith dual drip line systems (one line on either
Table
1. Listof study wereorchards
their characteristics.
side of the tree line). As detailed below, the installation of monitoring equipment for theAmeriflux
Designation
Sizeyears,(ha) most SJVYearPlantedhave
Initial(dS/m)In1 wet water
current
study
occurred during
theSalinity
fall of 2016.
farmers
access toUS-ASH
high-quality surface waterforirrigation.
The
four
years
precedingthe current
2.2–4.1
81
1998
study hadbeen
historically
dry
years
[26].
Duringthedrought,
surfacewater
deliveries
US-ASM
1.8–3.5
53
2006
US-ASL
US-PSH
US-PSL

1.3–1.9
2.3–4.7
1.1–2.1

16
63
16

2010
2006
2008

1 Soil solution extract electrical conductivity (ECe).

The five orchards were all irrigated with dual drip line systems (one line on eitherside of the tree line). As detailed below, the installation of monitoring equipment for thecurrent study occurred during the fall of 2016. In wet water years, most SJV farmers haveaccess to high-quality surface water for irrigation. The four years preceding the current
study had been historically dry years [26]. During the drought, surface water deliveries
were sharply curtailed for western SJV farmers. Many western SJV growers turned to
groundwater for irrigation, which is frequently of lower quality (higher salinity) in thewestern SJV compared to less saline groundwater frequently found in the eastern SJV. For
example, a recent USGS analysis found that the median total dissolved solids concentration
for wells in the western SJV exceeded 1000 ppm (>1.5 dS/m) [27].

Soil Syst. 2021, 5, 50

4 of 25

As our study started, our collaborators at the western sites believed their use ofgroundwater was beginning to salinize the soil and that the orchards were starting to show
signs of distress, with one grower reporting a yield decline of more than 30%. However, ahistorically wet 2017 winter replenished much of the state’s water reservoirs, and surface
water was generally available for irrigation during our study at all field sites except ASL,
which uses high-quality groundwater exclusively. Signs of physiological stress at ASH (e.g.,
relatively greater prevalence of canker and tree mortality) persisted throughout the study
period. Farmer-reported groundwater depths ranged from 52 m (~170 ft) at the easternsites to over 240 m (~800 ft depth) in the west.
2.2. Soil Properties
Concurrent with the soil instrument installation locations, we collected soil samples
for characterizing soil physical and chemical properties and root distributions. Samples
were taken down to 1.2 m in 20 cm intervals for a total of 36 samples per orchard (3 pairs ofsample holes along a drip line and in the middle of the row with six depth increments per
sampling hole). Each of these individual samples provided bulk soil for chemical and root
analysis. Soil textures were determined using an automated particle size analyzer (PARIO,METER Group, Pullman, Washington, DC, USA), which uses the integral suspension
pressure method to analyze particle settling [28,29]. Bulk densities were determined fromthe oven-dry mass of undisturbed soil cores of known volume (6 Tempe cell samples persite concurrent with instrument installation—3 pairs of drip line and in the middle of
the row samples gathered at the surface) [30]. The saturated hydraulic conductivity wasmeasured for each depth interval using the constant head method on samples repacked to
the field bulk densities [31]. Soluble cation concentrations of soil saturation extracts were
determined by the ICP analysis. The electrical conductivity of the saturation paste extract(ECe) and pH were measured for collected soil samples using a conductivity/pH electrodecalibrated against 0.01 M and 0.001 M KCl [32,33]. The cation exchange capacity (CEC)
was determined using the ammonium acetate method [34]. Extracted cation solutions wereanalyzed for Ca, Mg, Na, and K. Roots were separated from the soil of each sample, and themass of roots per sample was recorded. The measured roots were then used to constructnormalized root density vs. depth curves for the sites.
2.3. Meteorological, Evapotranspiration, and Irrigation Data
Evapotranspiration in the orchards was measured using eddy covariance following
the approach of Anderson et al. [35] and is described here briefly. Instrumentation included
sonic anemometers, open-path infrared gas analyzers (IRGAs) for CO2 and H2 O, fourcomponent radiometers, and soil thermal heat flux plates. We grouped similar IRGAs
by manufacturer, with EC150/IRGASON (Campbell Scientific, Logan, UT, USA) at PSL
and PSH and 7500/7500A (Licor Inc., Lincoln, NE, USA) at ASL, ASM, and ASH. The
high-frequency sonic anemometer and IRGA observations were processed to 30-min fluxes
using EddyPro (v6.0; Licor, Inc. [36]). Gap filling [37,38] and energy budget closure offluxes [39,40] were done following established approaches. Additional information about
these sites can be found with their Ameriflux data descriptions [14–18]. The fetch for allsites was >200 m in all directions with the exception of the smaller ASL orchard, where
the tower needed to be placed in the southeast corner of the orchard to maximize the fetch
in the dominant prevailing wind direction (west-northwest). Fluxes at ASL where winds
were from the east or southeast were gap-filled.
Modeled crop evapotranspiration (ETc) was estimated by multiplying monthly basal
crop coefficients from the TOPS-SIMS satellite product [41] and reference evapotranspiration (ET0 ). Daily reference evapotranspiration (ET0 ) was available from nearby weather
stations from the California Irrigation Management Information System (CIMIS) [42],and we used the closest stations to each of the orchards (Stations #15 Stratford for PSH,
#80 Fresno State for PSL and ASL, and #205 Coalinga for ASH and ASM). We used thePenman–Monteith ET0 [43] instead of the default Pruitt–Doorenbos ET0 [44]. Tipping rain

Soil Syst. 2021, 5, 50

5 of 25

gauges were installed on the eddy covariance towers. Measured rain was compared withrain reported at nearby CIMIS weather stations, and the amounts were similar.
Irrigation water samples were collected periodically from drip lines during irrigation
events when they coincided with field site visits; the sampling frequency thus varied
considerably from site to site depending upon the frequency of irrigation. Collectedirrigation water samples were analyzed for Ca, Mg, Na, and K using the ICP analysis. The
irrigation water’s electrical conductivity and pH were measured with a conductivity/pHelectrode. The number of samples at ASL was limited due to the higher-rate (and shorter
duration) drip emitters that resulted in relatively few ongoing irrigation events when wewere visiting the site for data collection and instrumentation maintenance. A record ofirrigation depths vs. time for each site was constructed based on emitter discharge rates,
the spatial density of emitters in the orchards, reports from growers on the timing andduration of irrigations, and our adjustment and augmentation of those reports based on areview of soil moisture time series data and tipping rain gauge data.
2.4. Soil Moisture, Salinity, and Statistical Analysis
The orchards were instrumented with frequency domain reflectometry sensors (GS3,
METER Group Inc., Pullman, Washington, DC, USA), measuring bulk permittivity, temperature, and bulk electrical conductivity. Within each orchard, sensors were installedat three locations: a central “tower” location (so-called due to being co-located with aneddy covariance instrument tower) and two outlying locations referred to as “outer 1” and“outer 2”. The outer sensors were installed at approximately 75 m to the west-northwest
and north-northwest directions from the tower within the larger tower footprint. At the
tower locations, four sensors were installed directly beneath a dripline at 25, 50, 75, and100 cm depths, and four sensors were installed midway between the dual drip lines (treeline or mid-row between the two driplines) at 25, 50, 75, and 100 cm depths. Installations
at the outer locations were at 50 and 100 cm in the mid-row position. Three sensors were
installed at the 25, 75, and 100 cm depths at the drip position (5 total sensors).
Soil-specific calibrations for the GS3 sensors were developed according to “Method A”
of METER [45–47]. Representative soil samples were collected from 25 cm at each site. In
the lab, dry soil was mixed and packed in containers to the field bulk density, and a GS3
sensor was installed in the same manner as in the field. Water was added to the containers
in steps. The soil container was weighed, and sensor readings were taken at each step. Soilvolumetric water contents were calculated at each step from the soil dry bulk density andmeasured wet mass. The measurements of dielectric permittivity versus the soil volumetricwater contents were plotted, and a quadratic calibration function for each site was fitted(r2 > 0.99 for all sites). Bulk electrical conductivity measured with the GS3 sensor wasconverted to pore-water electrical conductivity according to the Hilhorst method [48] asshown in Equation (1):ε p .ECBECw =(1)
ε b − ε ECB =0
where ECw is the pore-water electrical conductivity (dS/m), εp is the real portion of thedielectric permittivity of the soil pore water (unitless), ECB is the bulk electrical conductivity (dS/m) measured directly by the GS3 sensor, εb is the real portion of the dielectric
permittivity of the bulk soil (unitless), and εECB = 0 is the real portion of the dielectric
permittivity of the soil when bulk EC is 0 (unitless). As recommended by Hilhorst [48], we
set εECB = 0 = 4.1. The real part of the permittivity εp was calculated from [METER, 2020a]
following Equation (2):ε P = 80.3 − 0.37 ( Tsoil − 20)(2)
where Tsoil is the soil temperature (in degrees Celsius) measured by the GS3 sensor.
We used bootstrapping analysis (sampling with replacement) to assess the statisticalsignificance of the micrometeorological and soil time-series data [49]. We assessed the sumof ET on a whole record and seasonal basis and the mean value for all other properties.

= 80.3 − 0.37 (Soil Syst. 2021, 5, 50

− 20)

(2)

where Tsoil is the soil temperature (in degrees Celsius) measured by the GS3 sensor.
We used bootstrapping analysis (sampling with replacement) to assess the statisticalsignificance of the micrometeorological and soil time-series data [49]. We assessed the
6 of 25
sum of ET on a whole record and seasonal basis and the mean value for all other properties. For each variable, we ran 10,000 simulations to determine the 95% and 99% confidence intervals for each variable. Different variables were assessed as statistically signifivariable,
we ran10,000 simulations
determinethe 95% and
99% confidence
cantForor eachhighlystatisticallysignificant
if their 95%toand
99% confidence
intervals
did not
intervals for each variable. Different variables were assessed as statistically significant oroverlap.
highly statistically significant if their 95% and 99% confidence intervals did not overlap.
3. Results
3. Results
3.1. Soil Properties and Root Distribution
3.1. Soil Properties and Root Distribution
The measured soil characterization data are given in Appendix A (Tables A1–A5).
The measured soil characterization data are given in Appendix A (Tables A1–A5).
Figure 2 summarizes the soil textural properties of the five field sites. As expected from
Figure 2 summarizes the soil textural properties of the five field sites. As expected fromtheir geographic location, the eastern SJV sites generally have coarser textured soils thantheir geographic location, the eastern SJV sites generally have coarser textured soils than
the western SJV sites. The p-values for statistical significance comparing the percent sandthe western SJV sites. The p-values for statistical significance comparing the percent sandfractions of ASL and ASM were p = 0.017 and p < 1 × 10−5, respectively.
The p-value for afractions of ASL and ASM were p = 0.017 and p < 1 × 10−5 , respectively. The p-value forsand fraction of PSL and PSH was less than 1 × 10−9. ASH−andPSL
had
the largest variaa sand fraction of PSL and PSH was less than 1 × 10 9 . ASH and PSL had the largest
bility,with soilwith
samplesencompassing
five andfive
six texturalclasses, respectively.
The PSHThevariability,
soil samples
encompassing
and six texturalclasses, respectively.
sampleswererelatively
homogeneous
with
a
clay
texture(TableA4).
Samplesfrom
PSH samples were relatively homogeneous with a clay texture (Table A4). Samplesthe
fromASM
hadsiterelatively
high silthighcontent(Table A2).
The
ASL
siteASLwassitealsowasrelatively
unithesite
ASM
had relatively
silt content(TableA2).
The
also relatively
form
and mostly
loam. loam.
Averagehydraulicconductivity(Ksat)
was waslowestin thewestern
uniform
and mostly
Averagehydraulicconductivity(Ksat)
lowestin thewestern
SJV,SJV,
withvalues
of
6.8,
8.9,
and
8.9
cm/day
at
ASM,
ASH,
and
PSH,
respectively.
As ex- Aswith values of 6.8, 8.9, and 8.9 cm/day at ASM, ASH, and PSH, respectively.
pected,Ksat washigherhigher(p-valueof 0.014ofandp-value< 0.01 for<PSL
expected,
Ksatsignificantly
was significantly(p-value
0.014
and p-value
0.01andfor ASL),PSL and
withaveragevalues
of
24.1
and
31.3
cm/day
for
ASL
and
PSL,
respectively.
ASL), with average values of 24.1 and 31.3 cm/day for ASL and PSL, respectively.

Figure2. Percentagesof soil
separates
at thesites:(greendots),
ASH(orangedots),
ASM
Figure2. Percentagesof soil
separates
at thefivefivesites:ASLASL(greendots),
ASH(orangedots),ASM(reddots),
PSL(yellowdots),
andPSH(blackdots).
Chart
made
using
https://www.nrcs.usda.gov/(red dots), PSL (yellow dots), and PSH (black dots). Chart made using
wps/portal/nrcs/detail/soils/survey/?cid=nrcs142p2_054167 (accessed on 16 August 2021).

3.2. Soil Salinity and Root Distribution
The electrical conductivities (ECe) of saturation extracts for the soil samples collectedduring fall 2016 are shown in Figure 3. Corresponding sodium adsorption ratios (SARs)
are shown in Figure 3. Initial soil salinity at the pistachio sites (Figure 3d,e) was below
the reported pistachio threshold of 8–10 dS/m. Many of the salinity profiles measured
in the almond fields had depth-averaged values that exceeded the reported threshold of
1.5 dS/m, particularly at the finer textured, western sites ASH and ASM (Figure 3a–c). At
the ASH and ASM sites, salinity was highest and saturated hydraulic conductivity waslowest in the middle depths, 40–100 cm (Figure 3b,c; Table A2). ASL, ASM, and PSH all had
locations where high sodium content in the soil profile suggests a possible sodicity hazard

Soil Syst. 2021, 5, 50

during fall
fall 20162016 areare shownshown inin Figure
Figure 3.
3. Corresponding
Corresponding sodium
sodium adsorption
adsorption ratios
ratios (SARs)(SARs)
duringare shownshown inin Figure
Figure 3.
3. Initial
Initial soil
soil salinity
salinity atat thethe pistachio
pistachio sites
sites (Figure(Figure 3d,e)3d,e) waswas below
below thethearereported
pistachio
threshold
of
8–10
dS/m.
Many
of
the
salinity
profilesmeasuredinthereported pistachio threshold of 8–10 dS/m. Many of the salinity profiles measured in thealmond fields
fields had
had depth-averaged
depth-averaged values
values thatthat exceeded
exceeded thethe reported
reported threshold
threshold ofof 1.5
1.5
almonddS/m, particularly
particularly atat thethe finer
finer textured,
textured, western
western sites
sites ASH
ASH andand ASMASM (Figure(Figure 3a–c).
3a–c). At
At thethedS/m,
7 of 25
ASH andand ASMASM sites,
sites, salinity
salinity was
was highest
highest andand saturated
saturated hydraulichydraulic conductivity
conductivity was
was lowest
lowestASH
in thethe middle
middle depths,
depths, 40–100
40–100 cm
cm (Figure(Figure 3b,c;
3b,c; Table
Table A2).
A2). ASL,
ASL, ASM,
ASM, andand PSH
PSH all
all had
had loloin
cationswhere
highsodiumcontent
inthesoil
profilesuggestsapossible
sodicityhazardcations where high sodium content in the soil profile suggests a possible sodicity hazard
4a,c,e). On
had significantlyof 0.02
0.02 forfor ASL-ASH
ASL-ASH(Figure(Figure 4a,c,e).
On average,
average, easterneastern sites
sites hadsignificantly (p-value(p-value of
0.01 forfor PSL-PSH)
PSL-PSH) lower
lower sodium
sodium content
content (Table(Table A7)
A7) thanthan thethe western
western sites.
sites.
and pp << 0.01
andFigure 3.
3. Profiles
Profiles ofofatof thethe soil
soil saturation
saturation extract
extract electricalelectrical conductivity
conductivity (EC(ECeee)) at
at monitoring
monitoring locations
locationsFigurethesoilsaturation
extract
electricalconductivity(EC
monitoring
locations
within the five
study
sites
ASL,
ASH,
ASM,
PSL,
and
PSH
(a,
b,
c,
d,
and
e,
respectively),
five study sites ASL, ASH, ASM, PSL, and PSH (a, b, c, d, and e, respectively),respectively),fall
fall2016.
2016.
fall
2016.

Figure 4. Sodium adsorption ratio (SAR) profiles at monitoring locations within the five study sites
ASL, ASH, ASM, PSL, and PSH (a, b, c, d, and e, respectively), fall 2016.

Figure 5 shows the observed root density profiles. The plotted values are the mass of
the roots in a 20 cm soil sample (section of soil core) divided by the total mass found ateach of the field sampling locations (i.e., the combined mass from the “drip” and “mid”
excavations at each location within the field sites). For most of the sites and locations, mostof the root mass was found between 20 and 60 cm. The eastern pistachio site PSL was an
exception. Under the drip point at all three PSL locations, the peak root mass occurred
within the 0–20 cm layer. Nevertheless, we found significant root biomass down to 100 cm
under the midpoints. The coarse soil texture at the PSL site results in lower rates of lateralwater spreading and, consequently, higher water availability and greater abundance of root
mass at deeper locations beneath the mid-points. At the ASM and PSH sites, a relatively
larger proportion of the root mass was found in the mid-point excavations than in the drip
point excavations (Figure 5c,e).

Soil Syst. 2021, 5, 50

exception. Under the drip point at all three PSL locations, the peak root mass occurred
within the 0–20 cm layer. Nevertheless, we found significant root biomass down to 100
cm under the midpoints. The coarse soil texture at the PSL site results in lower rates oflateral water spreading and, consequently, higher water availability and greater abunof 25
dance of root mass at deeper locations beneath the mid-points. At the ASM and PSH 8sites,a relatively larger proportion of the root mass was found in the mid-point excavations
than in the drip point excavations (Figure 5c,e).

Figure 5. Fractions of the total roots under the drip and mid measurement points where root
Figureof thetotal
under
the dripdivided
and midbymeasurementroot
fraction
fraction5.=Fractions
mass of theroots
in aroots
20 cm
soil sample
the total masspoints
foundwhereat eachof thefield= mass of the roots in a 20 cm soil sample divided by the total mass found at each of the field samsampling locations (sites ASL, ASH, ASM, PSL, and PSH are shown in a, b, c, d, and e, respectively).
pling locations (sites ASL, ASH, ASM, PSL, and PSH are shown in a, b, c, d, and e, respectively).

3.3. Evapotranspiration and Water Balances
3.3. Evapotranspiration
and and
Water
Balances
The water years 20172019
were similar to one another, and both were wetter than
The waterdry
years
and
2019
were 2–6).
similarto one another,and bothwere
the relatively
20182017
wateryear(Tables
Irrigationwater quality
results
arewetter
given
than
the relatively
dryA7.
2018year(Tables
2–6). Irrigation
quality
resultsarein Figure6 and Table
Thewatereasternsites
had irrigationwaterswaterwith thelowestsalinity,
given
in Figure
6 andTable A7.
The easternsites
had irrigationwaterswith the lowest
generally
less than
0.1 dS/m.
Samplesfrom thewesternsites ranged
approximately
fromsalinity,
generally
0.25 to 0.9
dS/m. less than 0.1 dS/m. Samples from the western sites ranged approximately from 0.25 to 0.9 dS/m.
Table 2. Seasonal water balance at site ASH.
Year

SeasonSeason Start

Irrigation (cm)Rain (cm)

ETc (cm)ETa (cm)

Irrigation +Rain (cm)Apparent
LF (−)

2017

F 16
W 17
SP 17
SU 17
Annual
F 17
W 18
SP 18
SU 18
Annual
F 18
W 19
SP 19
SU 19
Annual15 October 201615 December 2016
15 March 201715 June 20172017
15 September 201715 December 2017
15 March 201815 June 20182018
15 September 201815 December 201815 March 201915 June 2019
2019

7.49
13.10
50.32
55.65
126.56
27.55
30.59
50.85
65.20
174.20
24.14
12.21
50.32
55.65
142.32

3.76
14.58
4.01
0.00
22.35
0.30
4.55
6.10
0.00
10.95
3.76
14.58
4.01
0.00
22.35

13.56
14.21
46.55
76.21
150.52
29.57
18.02
42.40
72.20
162.19
25.81
14.14
43.16
71.95
155.06

11.47
10.68
45.32
51.38
118.85
23.30
8.26
51.05
63.51
146.12
27.76
10.77
51.58
54.19
144.30

11.25
27.68
54.33
55.65
148.91
27.85
35.14
56.95
65.20
185.15
27.90
26.79
54.33
55.65
164.67

−0.02
0.61
0.17
0.08
0.20
0.16
0.77
0.10
0.03
0.21
0.00
0.60
0.05
0.03
0.12

2018

2019

Average LF = 18%, average ETa/ETc = 87%. Bolded values indicate ETa that is significantly different from ASL ETa on a seasonal basis at the
99% confidence interval. Italicized dates indicate that the season had a highly significantly higher salinity than ASL (as measured by thebulk EC on a 99% confidence interval). Rows with gray background give annual values.

Soil Syst. 2021, 5, 50

9 of 25

Table 3. Seasonal water balance at site ASM.
Year

SeasonSeason Start

Irrigation (cm)Rain (cm)

ETc (cm)ETa (cm)

Irrigation +Rain (cm)Apparent
LF (−)

2017

F 16
W 17
SP 17
SU 17
Annual
F 17
W 18
SP 18
SU 18
Annual
F 18
W 19
SP 19
SU 19
Annual15 October 201615 December 2016
15 March 201715 June 2017201715 December 201715 December 2017
15 March 201815 June 20182018
15 September 201815 December 201815 March 201915 June 2019
2019

22.26
6.68
47.22
50.98
127.13
22.35
12.35
50.22
75.00
159.92
22.35
6.68
50.22
65.00
144.25

4.01
12.78
4.04
0.00
20.83
0.28
4.70
6.02
0.00
11.00
2.87
10.52
2.62
0.00
16.00

13.56
14.21
46.55
76.21
150.52
29.57
18.02
45.84
78.72
172.15
24.80
12.25
43.77
72.20
153.02

10.54
10.10
47.86
50.37
118.87
23.52
7.28
54.29
73.22
158.30
26.14
9.30
49.59
64.49
149.52

26.27
19.46
51.26
50.98
147.96
22.63
17.05
56.24
75.00
170.91
25.22
17.20
52.83
65.00
160.25

0.60
0.48
0.07
0.01
0.20
−0.04
0.57
0.03
0.02
0.07
−0.04
0.46
0.06
0.01
0.07

2018

2019

Average LF = 11%, average ETa/ETc = 90%. Bolded values indicate ETa that is significantly different from ASL ETa on a seasonal basis at the
99%2021,
confidence
interval. Italicized dates indicate that season had a highly significantly higher salinity than ASL (as measured
Soil Syst.
5, x
11 ofby
27the bulk
EC on a 99% confidence interval). Rows with gray background give annual values.

Table 4. Seasonal water balance at site ASL.
Table 6. Seasonal water balance at site PSL.

Year

Season

2017
2017

FF16
15 October
16
15 October
2016 201617.67
W
15 December
W 17
17 15 December
2016 2016
14.19
SP
15 March
SP 17
17
15 March
20172017 35.76
SU
15 June
SU 17
17
15 June20172017 65.56
AnnualAnnual20172017
133.17FF17
15 September
17 15 September
2017 2017
15.19
W
15 December
W 18
18 15 December
2017 2017
18.21
SP
15 March
SP 18
18
15 March
20182018 38.19
SU
15 June
SU 18
18
15 June20182018 65.56
AnnualAnnual20182018
137.14FF18
15 September
18 15 September
2018 2018
17.67
W
15 December
W 19
19 15 December
2018 2018
14.19
SP
15 March
SP 19
19
15 March
20192019 35.76
SU
15 June
SU 19
19
15 June20192019 65.56
AnnualAnnual20192019
133.17

Year

2018
2018

2019
2019

SeasonSeason StartIrrigationIrrigation (cm)Season Start(cm)

Rain (cm)Rain (cm)

ETc (cm)

ETc (cm)Irrigation
Eta (cm)+ RainETa (cm)

Irrigation +Apparent
Rain (cm)LF (-) LF (−)
Apparent

(cm)
9.27
26.71
10.436.55
9.50 10.95
24.22
0.61
12.37
62.24
13.6814.00
11.64 13.19
34.19
0.66
55.86
53.97
35.806.20
37.01 43.32
41.96
0.12
67.89
62.10
63.420.28
66.16 70.05
65.84
0.00
27.03 124.31137.52
145.40205.01
123.33166.20
0.25
20.12
31.68
23.222.36
21.51 25.06
17.55
−0.23
11.29
23.20
15.578.69
8.19 15.48
26.89
0.70
55.23
53.52
23.558.18
36.30 45.65
46.37
0.22
64.96
42.92
62.560.00
57.83 70.20
65.56
0.12
19.23 123.83156.40
151.60151.33124.91156.37
0.21
19.14
29.03
22.297.65
24.74 22.65
25.31
0.02
16.62
57.55
14.8316.00
11.22 13.29
35.58
0.68
50.52
55.95
35.348.18
34.85 41.40
43.94
0.21
59.19
61.77
63.850.00
70.91 69.72
65.56
−0.08
31.82 141.71147.06
145.46204.29136.30170.380.17
Average
LF=
21%,
average
ETa/ETc
=
101%.
Rows
with
gray
backgroundgive
annualvalues.
Average LF = 19%, average ETa/ETc = 101. Rows with gray background give annual values.

20.16
6.55
35.19
20.00
47.77
6.20
61.77
0.28
164.88
33.03
29.32
2.36
14.42
8.69
45.45
8.18
42.92
0.00
132.10
19.23
21.38
7.65
36.16
21.39
47.77
8.18
61.77
0.00
167.08
37.21

0.65
0.80
−0.04
−0.09
0.29
0.37
0.51
−0.03
−0.51
0.00
0.34
0.71
0.10
0.04
0.29

Figure
6. Irrigation
qualityfour
siteswith repeated
Due to theirrigation strategy
Figure
6. Irrigationwaterwater
qualityfor fourfor
sites
with
repeatedsampling.sampling.
Due to the irrigation
strategy
at ASL,relatively
few samples
were collected
at this site
irrigatedexclusively
with well water.
A
at ASL,relatively
few samples
were collected
at thissite irrigatedexclusively
with well
water. A
couple of observations in 2016 and later 2019 showed EC for ASL’s irrigation water to be 0.11 dS/m
couple of observations in 2016 and later 2019 showed EC for ASL’s irrigation water to be 0.11 dS/mor lower.
or lower.

A detailed accounting of the seasonal water balances for the five sites across all seasons and years is given in Tables 2–6. Note that due to the start date of the current study,
values provided for the first season, fall 2016, are only totals for two months rather than
three. The apparent leaching fractions included in the tables were calculated as follows:Soil Syst. 2021, 5, 50

10 of 25

Table 5. Seasonal water balance at site PSH.
Year

SeasonSeason Start

Irrigation (cm)Rain (cm)

ETc (cm)ETa (cm)

Irrigation +Rain (cm)Apparent
LF (−)

2017

F 16
W 17
SP 17
SU 17
Annual
F 17
W 18
SP 18
SU 18
Annual
F 18
W 19
SP 19
SU 19
Annual15 October 201615 December 2016
15 March 201715 June 20172017
15 September 201715 December 2017
15 March 201815 June 20182018
15 September 201815 December 201815 March 201915 June 2019
2019

15.11
17.23
38.23
69.08
139.65
15.73
17.48
45.24
40.00
118.45
16.45
17.23
29.57
67.74
130.99

3.86
14.33
3.35
0.03
21.56
0.61
4.34
3.58
0.00
8.53
3.38
10.01
9.04
0.00
22.43

12.19
14.30
40.09
66.70
133.27
25.84
16.48
24.86
63.66
130.84
24.58
13.16
35.42
60.48
133.64

6.19
13.87
38.56
63.47
122.08
13.77
10.36
37.06
29.01
90.21
15.21
13.71
37.76
67.26
133.94

18.97
31.55
41.58
69.11
161.21
16.34
21.82
48.83
40.00
126.99
19.83
27.23
38.61
67.74
153.42

0.67
0.56
−0.22
0.08
0.24
0.16
0.53
0.24
0.88
0.48
0.23
0.50
0.02
0.01
0.13

2018

2019

Average LF = 28%, average ETa/ETc = 87%. Bolded values indicate ETa that is significantly different from PSL ETa on a seasonal basis at the
99% confidence interval. Italicized dates indicate that the season had a highly significantly higher salinity than PSL (as measured by thebulk EC on a 99% confidence interval). Rows with gray background give annual values.

Table 6. Seasonal water balance at site PSL.
Year

SeasonSeason Start

Irrigation (cm)Rain (cm)

ETc (cm)ETa (cm)

Irrigation +Rain (cm)Apparent
LF (−)

2017

F 16
W 17
SP 17
SU 17
Annual
F 17
W 18
SP 18
SU 18
Annual
F 18
W 19
SP 19
SU 19
Annual15 October 201615 December 2016
15 March 201715 June 20172017
15 September 201715 December 2017
15 March 201815 June 20182018
15 September 201815 December 201815 March 201915 June 2019
2019

17.67
14.19
35.76
65.56
133.17
15.19
18.21
38.19
65.56
137.14
17.67
14.19
35.76
65.56
133.17

6.55
20.00
6.20
0.28
33.03
2.36
8.69
8.18
0.00
19.23
7.65
21.39
8.18
0.00
37.21

10.43
13.68
35.80
63.42
123.33
23.22
15.57
23.55
62.56
124.91
22.29
14.83
35.34
63.85
136.30

9.50
11.64
37.01
66.16
124.31
21.51
8.19
36.30
57.83
123.83
24.74
11.22
34.85
70.91
141.71

24.22
34.19
41.96
65.84
166.20
17.55
26.89
46.37
65.56
156.37
25.31
35.58
43.94
65.56
170.38

0.61
0.66
0.12
0.00
0.25
−0.23
0.70
0.22
0.12
0.21
0.02
0.68
0.21
−0.08
0.17

2018

2019

Average LF = 21%, average ETa/ETc = 101%. Rows with gray background give annual values.

A detailed accounting of the seasonal water balances for the five sites across all seasons
and years is given in Tables 2–6. Note that due to the start date of the current study, values
provided for the first season, fall 2016, are only totals for two months rather than three. The
apparent leaching fractions included in the tables were calculated as follows:ETa
LF = 1 −(3)( I + P)
where I, P, and ETa are seasonal or annual totals of irrigation, precipitation, and measured
ET, respectively. Thus, the leaching fraction (LF) calculations are based on an effective
one-dimensional model of the soil and root zone, assuming water stored in the soil at the
beginning of the season is the same as at the end as required by the steady-state assumptionof the leaching fraction concept. Note that with this definition, LF will be negative if
ETa > I + P. Negative values were observed in some summer seasons.
Measured evapotranspiration, ETa, matched modeled crop evapotranspiration, ETc,
relatively well at the low salinity eastern sites ASL and PSL (data for the water year 2017

Soil Syst. 2021, 5, 50

Soil Syst. 2021, 5, x
Soil Syst. 2021, 5, x

11 of 25

12 of 27

12 of was
27 highly
shown in Figures 7a and 8a, respectively). However, at the western sites, ETasignificantly lower on an annual and multiannual basis for almonds, with some seasonalvalues also showing significance (Tables 2 and 4; Figure 7b,c, respectively). Almond harvest
values also showing significance (Tables 2 and 4; Figure 7b,c, respectively). Almond harvalues
also showing
significance(Tables
2 andin4;theFigure7b,c,discrepancies
respectively). between
Almond hartook placein mid-August,
which
resultedlargestETa and ETc
vest took place in mid-August, which resulted in the largest discrepancies between ETa
vestplace inmid-August,
which
resulted inlargest discrepancies
betweenETathat took
are likely
due
to irrigation
restrictions
tothe
encourage
nut cracking
and droppage
forand ETc that are likely due to irrigation restrictions to encourage nut cracking and dropand
ETc
that
are
likelydue
toirrigation
restrictions
toencouragenut
cracking
anddropharvest.
From thedata,
is impossible
to determine
if theETET
discrepancies
page for harvest.
From
theitdata,
it is impossible
to determine
if thediscrepanciesat
at thethe western
page
for
harvest.
thedata,8b)
it is impossible
determine
ifpoorthe ET
discrepancies
at thesites(Figure7b,cFromand7b,cFigureduetototo
relatively
model
estimates
or ifwesternsites (Figuresand 8b) were
were dueaarelatively
poor
model
forforETcETcestimates
westernsites (Figures
7b,c
and 8b)ET
were due
to a relatively
poor model
forlimited
ETc estimates
the
sites
had
reducedconditions
being
by higher soil
or ifwestern
the western
sites
had
reduced ETduedueto
to growth
growth conditions
being
limitedby higher
or if the western sites had reduced ET due to growth conditions being limited by higher
andirrigationwater
salinities.
soil andirrigationwater
salinities.

soil and irrigation water salinities.

Figure 7.
Measured
evapotranspiration(ETa) and) modeled
evapotranspiration(ETc) for the 2017
FigureMeasured
evapotranspirationand modeled
evapotranspiration) for the 2017a modeledFigure7.7.Measured
evapotranspiration(ETa)(ETandevapotranspiration(ETc) for (ETthe c2017
water year at ASL (a), ASH (b), and ASM (c).
water
year
at
ASL
(a),
ASH
(b),
and
ASM
(c).
water year at ASL (a), ASH (b), and ASM (c).

Figure 8. Measured evapotranspiration (ETa ) and modeled evapotranspiration (ETc ) for the 2017
water year at PSL (a) and PSH (b).

Soil Syst. 2021, 5, 50

12 of 25

Eddy covariance data quality metrics ranged slightly for different sites. The percentage
of gap-filled data ranged from 19 to 39% at ASH that required directional wind filling. PSL
and PSH had gap filling of 31% and 32%, respectively, while ASM had 22%. ASM and ASL
had the lowest gap-filling, likely due to higher nighttime winds at the adjacent sites. Daily
energy balance closure ranged from 74 and 75% at PSH and PSL and was higher at thealmond sites (87%, 85%, and 83% at ASH, ASM, and ASL, respectively).
The low salinity sites in the east were very consistent with respect to the ratio of
measured annual evapotranspiration and calculated crop evapotranspiration. At the PSL
eastern pistachio site, the ratio of measured and reference evapotranspiration, ETa/ETc,
was 101%, 99%, and 104% for the water years 2017, 2018, and 2019, respectively (Table A6).
The corresponding values for the ASL eastern almond site were 106%, 97%, and 99%. The
overall three-year average for both sites was 101%.
The ETa/ETc ratios at the salt-affected western sites were notably lower on average,
which is consistent with a lower canopy cover (as assessed through visual observations)and a statistically significantly higher ground heat flux (p < 0.01) and salinity stress. The
ratios also exhibited greater interannual variability (Tables 2–6). The annual ET ratios at
the western sites in 2017, 2018, and 2019 were 92%, 69%, and 101% at PSH; 79%, 92%, and
97% at ASM; and 79%, 90%, and 93% at ASH. The three-year average values were 87% at
PSH, 90% at ASM, and 87% at ASH.
The apparent equivalent leaching fractions at the sites varied with year and season(Tables 2–6). PSL had the lowest range of annual leaching fractions, where the annual
leaching fractions were 25%, 21%, and 17%, with a three-year average value of 21%. Othersites were more variable. For example, the ASL site had a similar average value of 19%, butwith annual values of 29%, 0%, and 29%. Sites PSL (21%), ASL (19%), and ASH (18%) all
had three-year averages near 20%, and the leaching fraction was not significantly different
between sites of the same species. Site PSH had the highest annual leaching fraction at
27%, whereas ASM had the lowest at 11%.
Inter-seasonal variations in leaching were high (Tables 2–6). Winter is the rainy season,
and a significant amount of leaching occurred, with apparent seasonal leaching fractions
generally greater than or equal to 50%. Apparent leaching during the other seasons varied
substantially, both across five field sites and year-to-year at individual sites.
3.4. Soil Water and Salinity
Seasonal root zone salinity profiles for 2017–2019 are shown for the five study sites in
Figures A1–A5. Seasonal and annual trends are not easily identified from the plotted data.
The plots in the top two rows of Figures A1–A5 are for the tower locations. Because they
contain an extra monitoring depth, detailed interpretation and discussion of these plots areprovided below.
Among the western field sites, ASH (Figure A1) and ASM (Figure A2) showed ageneral trend of increasing salinity between 2017 and 2019. Both sites relied on relatively
saline irrigation water (Figure 6) and have medium-to-fine textured soils. The ASM site also
had the lowest apparent average leaching fraction among the five sites at 11% (Table 3).
At the other western site, PSH, root zone salinity remained relatively constant during
the three years. However, some higher salinity readings were obtained at the shallowest
depths at the mid-tower position in 2019 (Figure A4). Site PSH had the highest averageleaching fraction at 28% (Table 6). The western sites are in the rain shadow of the California
Coast Ranges, and consequently, the eastern sites receive higher amounts of winter rains.
The effect of winter rains at ASL and PSL can be seen in Figures A3 and A5. The highest
salinities are obtained in the summer (red curves) and then reduced between growing
seasons by winter rain (blue curves).
One key question that can be addressed with in situ soil sensors is how frequently(and for how long) soil EC exceeds the Maas–Hoffman threshold [21]. While not exact,
we can approximate extract EC (ECe) from pore-water EC (ECw) by relating the ECw andvolumetric water content to saturated water content for the soil. When we evaluate this

Soil Syst. 2021, 5, 50

13 of 25

pseudo-ECe on a seasonal and long-term basis, a clearer divergence emerges between
almonds and pistachios. At ASH and ASM, pseudo-ECe exceeds the Maas–Hoffman
threshold for almonds (1.5 dS/m) for every season of this study. However, there werediffering ranges of exceedance, with ASH exceeding 5 dS/m every quarter and reaching
7.4 dS/m in the fall/winter of the first year before substantial leaching water could beapplied. Conversely, ASM was above the threshold but remained in the 2–4 dS/m range forthe study period. PSH remained below the pistachio threshold of 8 dS/m (with the highest
value of 7 dS/m in fall 2016), even though the site was above the “moderate” salinity
threshold of Maas–Hoffman [21].
4. Discussion and Conclusions
As expected, the western sites had more significant salinity problems than the easternsites. The western sites have finer textured soils and poorer quality irrigation water.
Assuming the crop ET for the western sites was adequately modeled, the measured actual
ET was about 90% of reference ET. While it is not possible to identify the cause of the
ET reductions definitively from these observational data, it is plausible that salinity wasa contributing factor. Two of the western sites showed some evidence of increasing soil
salinity levels throughout the study. The third western site appeared to maintain the same
salinity level by imposing a relatively high apparent leaching fraction (28%). Across thethree western sites, the annual average apparent leaching fraction ranged from 11 to 28%.
Evidence of restricted water flow at deeper soil layers was evident at ASH, with somesamples having low saturated hydraulic conductivity (<2 cm/day). The highest leaching
fraction at ASH, combined with that orchard’s use of gypsum for salinity control, likely
explains the similarly high initial EC profiles at ASH and PSH, but the lower SAR at ASH
compared to PSH.
In contrast to the western sites, overall salinity was controlled at the eastern sites, andcrop ET appeared maximal, with measured ET matching modeled ET almost exactly eachyear (crop coefficients of ~1 for both PSL and ASL). Apparent leaching fractions at theeastern sites were approximately 20%. The lack of any evidence of salinity issues at PSL
and ASL indicate that carefully selected orchards in the eastern SJV can serve as suitable
controls for salinity comparisons with salt-affected fields in the western SJV.
Reductions in crop ET with salinity stress are often modeled as being proportional
to the yield reductions due to salinity. For example, the Maas–Hoffman threshold andslope parameters are explicitly incorporated into the FAO-56 model for calculating cropET [43]. Based on the high soil electrical conductivities observed at ASH (Figure A1), wewould expect substantial decreases in ET due to the exceedance of the Maas–Hoffman
threshold for almonds. However, while there are some declines in ET at ASH comparedto ASL, they do not track the Maas–Hoffman parameters for almonds. Sanden et al. [50]found similarly higher salinity tolerance for almond orchards in the western SJV, with nosignificant yield decreases up to the maximum observed ECe of ~4 dS/m. The results fromboth Sanden et al. [50] and this study suggest that current commercial cultivars may havea higher salinity tolerance than previously assumed for almonds. Further work is needed
to understand how irrigation management, cultivation practices, and new cultivars may
increase almond salinity tolerance.
One possible approach to re-evaluate Maas–Hoffman parameters for almonds would
be to conduct regional scale analyses. These could include relating yield to larger scale
salinity maps such as those produced by Scudiero et al. [51], which would help further
determine whether the Maas–Hoffman threshold and slope are overly conservative. In theabsence of yield data, an analysis of regional ET for orchards in the SJV compared against
salinity maps [51] could help assess salinity impacts on crop productivity
Another approach for understanding the mechanisms of salinity movement in the soil
and their impact on soil water and solute balances is applying a process-based model. In
the accompanying manuscript (part 2), we present the results of a one-dimensional model

Soil Syst. 2021, 5, 50

14 of 25

(HYDRUS 1-D) in helping us to understand the seasonal and interannual salinity dynamics
across a natural salinity gradient.
Author Contributions: Conceptualization, S.A.H., R.G.A., T.H.S. and J.Š.; Data curation, R.G.A.;
Formal analysis, S.A.H.; Funding acquisition, S.A.H. and J.Š.; Methodology, S.A.H., R.G.A., T.H.S.
and J.Š.; Resources, S.A.H., R.G.A., T.H.S., G.D.J., D.W. and J.Š.; Software, J.Š.; Writing—original draft,
S.A.H., R.G.A., T.H.S. and J.Š.; Writing—review & editing, S.A.H., R.G.A., T.H.S., G.D.J., D.W. and J.Š.
All authors have read and agreed to the published version of the manuscript.
Funding: S.A.H was in part by an international Ph.D. fellowship from the Cultural and Education
section, Egyptian Higher Education Ministry, Egypt, and by a graduate student research fellowshipfrom the Department of Environmental Sciences, University of California, Riverside. Field datacollection was funded by the USDA-ARS Office of National Programs projects 2036-61000-018-00-D(R.G.A. and T.H.S.) and 2034-13000-012-00-D (D.W.). J.S. was funded by the USDA National Institutesof Food and Agriculture Multistate Project W4188 (Project No. 1021006 CA-R-ENS-5047-RR).
Institutional Review Board Statement: Not applicable.
Informed Consent Statement: Not applicable.
Data Availability Statement: Eddy covariance data are available via Ameriflux. Other data are
available upon reasonable request to the corresponding authors.
Acknowledgments: The authors would like to thank Dennise Jenkins, Towfiq Khan, and Kailuh
Menefee (USDA-ARS) for their assistance with field and laboratory work. We also thank Professors
Laosheng Wu and Robert Graham (University of California, Riverside) and their laboratories forassistance with soil and water sample analysis. Mention of trade names or commercial productsin this publication is solely for the purpose of providing specific information and does not imply
recommendation or endorsement by the U.S. Department of Agriculture. The U.S. Department ofAgriculture prohibits discrimination in all its programs and activities on the basis of race, color,
national origin, age, disability, and where applicable, sex, marital status, familial status, parental
status, religion, sexual orientation, genetic information, political beliefs, reprisal, or because all or partof an individual’s income is derived from any public assistance program. (Not all prohibited bases
apply to all programs.) Persons with disabilities who require alternative means for communicationof program information (Braille, large print, audiotape, etc.) should contact USDA’s TARGET Centerat (202) 720-2600 (voice and TDD). To file a complaint of discrimination, write to USDA, Director,
Office of Civil Rights, 1400 Independence Avenue, S.W., Washington, D.C. 20250-9410, or call (800)795-3272 (voice) or (202) 720-6382 (TDD). USDA is an equal opportunity provider and employer.
Conflicts of Interest: The authors declare no conflict of interest.

Soil Syst. 2021, 5, 50

15 of 25

Appendix
AppendixAA

Figure A1. Seasonal average root zone soil water EC at six monitoring locations at the western alFigure
average root zone soil water EC at six monitoring locations at the western
mondA1.
site SeasonalASH.
almond site ASH.

Soil Syst. 2021, 5, x. https://doi.org/10.3390/xxxxx

www.mdpi.com/journal/soilsystems

Soil Syst. 2021, 5, 50
Soil Syst. 2021, 5, x

16 of 25
2 of 5Figure A2. Seasonal average root zone soil water EC at six monitoring locations at the western alFigure A2. Seasonal average root zone soil water EC at six monitoring locations at the western
mond site ASM.
almond site ASM.

Soil Syst. 2021, 5, 50
Soil Syst. 2021, 5, x

17 of 25
3 of 5Figure A3. Seasonal average root zone soil water EC at six monitoring locations at the eastern alFigure A3. Seasonal average root zone soil water EC at six monitoring locations at the eastern almondmond site ASL.
site ASL.

Soil Syst. 2021, 5, 50
Soil Syst. 2021, 5, x

18 of 25
4 of 5Figure A4. Seasonal average root zone soil water EC at six monitoring locations at the western pisFigure
Seasonal average root zone soil water EC at six monitoring locations at the westerntachio A4.
site PSH.
pistachio site PSH.

Soil Syst. 2021, 5, 50
Soil Syst. 2021, 5, x

19 of 25
5 of 5Figure A5. Seasonal average root zone soil water EC at six monitoring locations at the eastern pis-FigureA5.PSL.
Seasonal average root zone soil water EC at six monitoring locations at the easterntachio site
pistachio site PSL.

Soil Syst. 2021, 5, 50

20 of 25

Table A1. Measured soil properties of the ASH site.
Location

Tower

Position

Drip

Mid

Outlying 1

Drip

Mid

Outlying 2

Drip

Mid

Depth

CEC

Exchangeable
SodiumPercentage

SodiumAdsorption Ratio

ECe

cm

mmolc /kg%

(mmolc /L)0.5

dS/m

0–20
20–40
40–60
60–80
100–12062.57
130.64151.47138.13

22.15
34.79
32.02
33.24

3.6
6.0
5.0
3.8

2.4
5.9
7.0
6.7

6.7
8.0
8.0
8.0

0–20
20–40
40–60
60–80
100–120

7.79
8.51
56.41
47.71

22.40
16.32
1.21
1.47

0–20
20–40
40–60
60–80
100–120

1.33
3.86
13.31
1.34

1.4
4.4
3.7
2.0

6.6
8.1
8.2
7.8

0–20
20–40
40–60
60–80
100–120

12.3
7.3
3.1
3.4

5.0
4.4
3.6
2.7

7.9
8.1
8.1
7.7

pH

0–20
20–40
40–60
60–80
100–120

63.24
112.14134.43
78.30

23.88
21.97
22.72
22.60

2.8
3.6
5.3
2.3

3.0
4.6
5.9
2.6

8.4
8.5
8.4
8.2

0–20
20–40
40–60
60–80
100–12073.43
109.50113.17
99.94

22.36
20.44
22.50
27.34

1.5
2.0
3.2
3.3

0.3
0.5
0.5

8.1
8.3

Sand

Silt

Clay

Saturated
Hydraulic
Conductivity

%

%

%

cm d−1

49.5
40.9

20.1
28.9

30.4
30.2

5.2
4.9

59.2
57.3

35.6
37.8

1.0

65.0

34.0

45.2
40.8

23.4
27.0

31.4
32.2

10.2
38.0

49.6
44.2

40.2
17.8

Sand

Silt

Clay

Saturated
Hydraulic
Conductivity

16.15
5.62
0.5
2.05

10.83
6.33
2.87
26.59

Table A2. Measured soil properties of the ASM site.
Location

Tower

Position

Drip

Mid

Outlying 1

Outlying 2

Drip

Drip

Depth

CEC

Exchangeable
SodiumPercentage

SodiumAdsorption Ratio

ECe

cm

mmolc /kg%

(mmolc /L)0.5

dS·m−1

0–20
20–40
40–60
60–80
100–120124.4975.78
133.11115.22

5.17
6.46
3.87
4.95

0–20
20–40
40–60
60–80
100–120
0–20
20–40
40–60
60–80
80–100
100–120
0–20
20–40
60–80
80–100
100–120100.28125.34128.82

15.05
16.96
20.19

pH

1.5
1.1
3.2
2.0

1.3
2.2
4.5
3.9

8.5
8.6
8.2
8.2

2.1
1.5
2.9
3.7

3.0
3.0
4.4
6.1

8.3
8.1
8.3
8.1

16.0
9.9
15.1

3.5
6.1

8.1
8.4

16.6
0.9
2.6
4.8
2.4

1.3
2.8
5.9
3.6

7.9
8.6
8.2
8.2

%

%

%

cm/d−1

18.8
17.7

43.6
43.5

37.6
38.8

9.37
3.38

4.6
7.0

56.8
66.4

38.6
26.6

1.01
8.72

15.7
22.7

40.5
37.5

43.8
39.8

15.3
13.0

49.7
47.0

35.0
40.0

25.2
23.2

35.4
37.0

39.4
39.8

5.77
2.27

19.1
10.5

46.5
51.7

34.4
37.8

7.48
16.71

Soil Syst. 2021, 5, 50

21 of 25

Table A3. Measured soil properties of the ASL site.
Location

Tower

Outlying 1

Depth

CEC

Exchangeable
SodiumPercentage

SodiumAdsorption Ratio

ECe

cm

mmolc /kg%

(mmolc /L)0.5

dS/m

Drip

20–40
40–60
60–80
100–120

44.59
48.19
68.61
78.01

15.39
16.80
15.62
15.68

Mid

20–40
40–60
60–80
100–120

35.75
38.85
46.26
86.53

10.87
13.45
15.54
13.39

Drip

20–40
40–60
60–80
100–120

35.14
34.38
31.37
29.72

Mid

20–40
40–60
60–80
100–120

33.90
30.36
32.60
33.01

Position

pH

1.7
0.9
1.1
1.7

8.1
8.2
7.3
8.1

2.0
3.1
5.6
7.0

1.1
1.1
0.2
1.3

8.2

22.90
17.73
17.09
23.90

6.0
5.7
6.8
6.8

1.6
2.5
0.8
1.0

8.6
8.3

10.61
13.21
10.82
16.60

1.9
2.7
2.6
4.0

0.7
1.4
1.2
1.1

7.5
7.9
8.2
7.6

16.8
13.3
14.3
17.7

3.0
3.0
4.0
4.5

8.9
8.8
8.2
8.5

20–40
40–60
60–80
100–120

Sand

Silt

Clay

Saturated
Hydraulic
Conductivity

%

%

%

cm d−1

52.7
48.5
53.7
58.6

36.7
37.9
38.7
35.2

10.6
13.6
7.6
6.2

29.18
17.74
21.82
27.78

45.0
48.3
51.3
51.0

33.0
27.7
26.7
29.0

22.0
24.0
22.0
20.0

Sand

Silt

Clay

Saturated
Hydraulic
Conductivity

%

%

%

cm d−1

10.5
8.5
14.3

37.9
39.3
38.1

51.6
52.2
47.6

24.2

35.2

40.6

9.2
7.3
8.7
19.1

39.2
38.9
35.4
37.2

51.6
53.8
55.9
43.7

8.7
8.6

8.3

Table A4. Measured soil properties of the PSH site.
Location

Tower

Outlying 1

Position

Drip

CEC

Exchangeable
SodiumPercentage

SodiumAdsorption Ratio

ECe

cm

mmolc /kg%

(mmolc /L)0.5

dS/m

0–20
20–40
40–60
60–80
100–120

97.07
120.64
96.43

21.05
20.58
19.23

0.3
0.9
2.9
2.6

4
1.5
3.7
4.8

7.5
8.5
7.5

2.16
2.89

5.0
5.8

7.8
7.8

13.32

5.5

7.4

2.6
2.3
3.7
4.9

7.3
7.4
7.2
7.0

3.6
3.8

8.3
8.4

Mid

0–20
20–40
40–60
100–120

Drip

0–20
20–40
40–60
60–80
100–120

126.53119.59129.58
53.07

10.30
10.21
8.04
12.13

0–20
20–40
40–60
60–80
100–120103.42106.44118.36106.34

11.23
10.12
8.01
5.73

0–20
20–40
60–80
100–120117.76124.53166.82

21.43
23.20
25.59

Mid

Outlying 2

Depth

Drip

14.1

14.03
14.05
34.48

pH

21.85
7.03
7.02
13.57

8.90
3.79
9.79

Soil Syst. 2021, 5, 50

22 of 25

Table A5. Measured soil properties of the PSL site.

Location

Tower

Outlying 1

Position Depth

Drip

Drip

Mid

Outlying 2

Drip

Mid

CEC

SodiumExchangeable
Adsorption
Sodium
Ratio
Percentage

ECe

pH

cm

mmolc /kg%

(mmolc /L)0.5

dS/m

0–20
20–40
40–60
60–80
100–120

6.08
8.10
9.90
30.46

16.25
7.96
14.44
11.50

1.42
1.47
1.39
1.33

0.3
0.2
0.5
1.1

7.6
6.9
6.6
7.9

0–20
20–40
40–60
60–80
100–120

1.2
2.0
2.0
1.3

1.1
2.6
1.1
0.6

7.9
8.0
7.9

0–20
20–40
40–60
60–80
100–120

0.5
0.6
0.3
0.6

0.9
0.7
0.9
0.6

8.4
8.2
8.2
7.8

Sand

Silt

Clay

Saturated
Hydraulic
Conductivity

%

%

%

cm d−1

72.4
72.6
70.0
71.1
56.7

21.9
21.4
22.5
24.2
35.6

5.7
5.9
7.5
4.7
7.7

50.95
30.33
13.81
11.20

63.0
59.0
60.3
50.2

13.8
10.0
8.0
8.0

23.2
31.0
31.7
41.8

0–20
20–40
40–60
60–80
100–120

6.12
8.03
54.88
47.84

26.27
16.07
1.31
1.51

1.9
2.3
7.1
8.0

0.3
1.1
5.0
3.3

6.3
6.9
7.2
8.4

42.0
38.0
48.0
31.3

26.0
36.0
22.0
33.0

32.0
26.0
30.0
35.7

0–20
20–40
40–60
60–80
100–120

8.57
21.40
82.25
47.83

11.02
15.59
16.71
16.63

1.2
3.4
6.3
4.9

2.6
1.9
4.3
4.3

7.1
8.2
7.6
8.4

48.0
16.0
27.0
40.7

27.0
34.0
28.0
24.0

25.0
50.0
45.0
35.3

Table A6. Shallow (0–20 cm) soil concentrations for select elements.

ASL
ASM
ASH
PSL
PSH

Cl

Na

Ca

K

Mg

B

Mo

meq/L

meq/L

meq/L

meq/L

meq/L

ppm

ppm

2.15
0.48
1.04
0.28
1.10

2.38
12.26
11.98
1.28
19.20

5.04
20.82
14.77
2.68
17.38

0.28
1.00
0.77
0.83
0.64

2.42
11.40
7.02
1.38
6.53

0.08
0.17
1.17
0.28
2.60

2.42
11.40
7.02
1.38
6.53

Bolded values for PSH, ASM, or ASH values represents values that are significantly (p < 0.05) different than PSL
or ASL.

Soil Syst. 2021, 5, 50

23 of 25

Table A7. Irrigation water salinity, sodicity, and ionic composition.

1

2

Sites

Day of Irrigation

ECiw(dS/m)ASH

30 May 201711 Aug 2017
6 Jul 2018
19 Sep 201820 Jan 2019

0.3
0.24
0.43
0.54
0.79

30 May 201717 May 2018
6 Jul 2018
19 Sep 2018
5 Jan 2019

0.28
0.43
0.54
0.51
0.48

ASM

3

PSL

30 Mar 2017
5 Jul 201717 May 2018
2 Aug 2018

0.05
0.24
0.04
0.05

4

PSH

20 Feb 2018
31 Aug 2018
19 Sep 201830 Jan 2019

0.44
0.89
0.48
0.9

SAR
(mmolc/L)0.5
1.4

1.7
1.8

0.48

4.1
3

pH

Ca2+
(mmolc/L)

Mg2+(mmolc/L)

Na+(mmolc/L)

K+(mmolc.l/L)

7.78
7.14
7.6
6.95
7.8

0.32
0.35
1.04
0.31
1.1

0.32
0.35
0.51
0.29
1.16

1.29
1.54
2.24
1.09
4.76

0.17
0.09
0.1
0.07
0.19

7.7
7.69
7.72
7.89
7.8

0.33
0.87
0.43
0.46
0.91

0.33
0.58
0.61
0.52
0.69

1.47
2.47
3.26
2.31
5.98

0.08
0.13
0.12
0.11
0.14

7.64
7.8
7.2
8.06

0.1
0.49
0.08
0.07

0.02
0.24
0.02
0.01

0.19
1.15
0.19
0.15

0.05
0.07
0.04
0.04

7.57
7.72
7.93
7.77

0.52
0.51
0.44
1.22

0.59
0.56
0.57
0.74

2.86
2.54
3.03
5.89

0.16
0.12
0.11
0.09

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