Soil salinity is a severe environmental hazard (Hillel, 2000) that
impacts the growth of many crops. Worldwide, salinization problems are
spreading at a rate up to 2 million hectares a year, which offsets a good
portion of the increased productivity achieved by expanding irrigation
(Postel, 1999). Soil salinity affects the soil physico-chemical properties
and the water availability to plants. Therefore, its accurate measurement
is a key factor for developing appropriate guidelines for planning future
reclamation and rehabilitation projects for salt affected lands.
Conventionally soil salinity is determined by laboratory analysis (electrical
conductivity of the saturated paste extract ECe. This procedure
is expensive and time consuming and provides an incomplete view of the
extent of soil salinity. An alternative to laboratory analysis to assess
soil salinity in the field by determining the apparent electrical conductivity
(ECa). Nichol et al. (2002) stated that Dual_tangent
analysis of the raw waveform is found to be more accurate than the remote
diode shorting method within water solutions and within silica sand saturated
with an electrically conductive water solution. Hamed et al. (2003)
observed that the Sigma Probe (SP), which measures water content, gave
accurate readings for electrical conductivity of the soil solution only
slightly dependent on water content and soil type. However, Robinson et
al. (2003) concluded that the key to Time Domain Reflectometry (TDR)
success is its ability to accurately measure the permittivity of a material
and the fact that there is a good relationship between the permittivity
of a material and its water content. A further advantage is the ability
to estimate water content and measure bulk soil EC simultaneously using
TDR. Castiglione et al. (2006) used coaxial multiplexers to monitor
up to hundreds of TDR probes through computer or data-logger interface.
They observed the different probes connected to a common multiplexer or
multiplexer network interfere with one another. They further mentioned
that the interference did not affect the signal travel time and therefore
the water content measurement, but resulted in appreciable errors in measured
electrical conductivity. Lin et al. (2007) stated that methods
accounting for cable resistance in time domain reflectometry (TDR) base
electrical conductivity measurements remained controversial and the effect
of TDR recording time was underrated when long cables were used. Bieganowski
(2003) used current-voltage curve interpretation, registered in the saturated
soil, in categories of soil salinity evaluation. A quantity containing
the information about the salinity is electrical conductivity of the soil.
This conductivity could be evaluated by the analysis of the slope of a
straight line, fitted into the part of the current-voltage curve, which
is responsible for the reduction of hydrogen ions during electrolysis
of water contained in the soil. Konukcu et al. (2003) in a study
on soil salinity measurement indicated that thermal-conductivity probes
measured water content over a wide range from saturation to 0.16 m3
m3 for clay loam and to 0.09 m3 m3 for sandy loam soil with
great sensitivity (R2>0.95) and were unaffected by the clay
accumulation. The 4-probe electrode probes provided reliable measurements
(R2> 0.95) of the salinity of the soil solution for the
range relevant to agricultural application. Boutin and Martin (2006) examined
the salinity variability recorded by Array for Real-Time geotropic Oceanography
(ARGO) floats in the upper 10 m layer of the surface ocean. They showed
that the surface salinity variability at ten days and 200 km scales is
above ±0.1 psu fro 30% of the drifters and that this variability
is larger than 0.2 psu in tropical regions affected by strong discharges
and by precipitations and in frontal areas characterized by strong mesoscale
activity. Amezketa (2006) used a mobile and geo-referenced electromagnetic
sensing system to assess soil salinization at spatial and temporal scales
in irrigated fields. He concluded that the development of new technologies
such as electromagnetic (EM) induction sensors has revolutionized the
way in which soil salinity is measured. Eldiery et al. (2005) described
an approach to develop soil salinity maps using remotely sensed data.
The approach involved integrating remote sensing data from Ikonos, GIS
and special analysis. The results showed that the green band, the near
infrared band and the near infrared band divided by the red band ratio
are strongly related to soil salinity. Bouksila et al. (2008) used
Time Domain Reflectometry (TDR) and the new wet WET sensor based on Frequency
Domain Reflectometry (FDR) for the determination of soil water content
and salinity. They found that WET sensor gave similar accuracy to TDR
if calibrated values of the soil parameters were used instead of standard
values. Zhang et al. (2004) conducted laboratory tests to simultaneously
measure soil water content and salinity using a four-electrode Wenner
array sensor. They showed that, in general, the calibration models predicted
the water content more accurately than salinity. The R2 values
for predicting water content and salinity at the 30 mm penetration depth
reached 0.89 and 0.91, respectively. Whereas the root-mean-square errors
for volumetric water content and salinity measurements were 0.019 m3
m3 and 0.173 cmol kg1, respectively. The determination of salinity through
the use of conductivity measurements was first recognized by Kudsen (1901)
but was not developed until the 1950`s. AT that time, a conductivity salinometer
was developed for the International Ice Patrol that was capable of measuring
salinity to better than 0.01 ppt (Emery and Thomson, 1998).
Soil electrical conductivity, which is known as EC, is the ability of
soil to conduct electrical current. EC is expressed in milliSiemens per
meter (mS m1). Traditionally, soil paste EC has been used to assess soil
salinity (Rhoades et al. 1989), but now commercial devices are
available to rapidly and economically measure and map bulk soil EC across
agricultural fields. However, EC measurements also have the potential
for estimating variation in some of the soil physical properties in a
field where soil salinity is not a problem. Kemper (1959) developed the
first in situ salinity sensor. It consisted of electrodes imbedded
in porous ceramic to measure the Electrical Conductivity (EC) of the solution
within the ceramic cell. When placed in soil, these devices imbibe water
which, in time, comes to diffusional equilibrium with the soil water.
Richard (1966) improved the design of the soil salinity sensor to shorten
its response time and to eliminate external electrical current paths.
Austin and Rhoades (1979) developed and introduced a compact four-electrodes
salinity sensor into routine agricultural practices. Relationship between
electrical conductivity measured in situ with four-electrodes probe
and conductivity of soil solution or saturated soil paste were developed
(Nadler, 1981; Rhoades et al., 1989; Slavich and Peterson, 1990).
Recent developments in EC sensors and their ability to produce EC variation
maps has attracted much attention among producers about potential applications
of this sensor for improving field management. Presently there are two
types of EC sensors currently on the market to measure soil EC in the
field. These are (1): Contact Method. This type of sensor uses electrodes,
usually in the shape of coulters that make contact with the soil to measure
the electrical conductivity and (2): Non-contact method: This type of
sensor works on the principal of electromagnetic Induction.
The EC value is a combined result of physical and chemical properties
of soil. It has potential applications in precision agriculture for management
decisions and the delineation of management zones. For precision agriculture
applications, EC information works best when yields are primarily affected
by factors that are best related to EC, for example, water holding capacity,
salinity level, depth of top soil and so on. The main objective of this
study was to evaluate soil salinity measurements by conventional methods
and the salinity sensors and also to develop relationship between these
measurements for field application.
MATERIALS AND METHODS
The experiment was carried out at KACST research station Al-Muzahmiyia,
Kingdom of Saudi Arabia from 1999-2002 where the high saline pond water
(residue of RO-Plant) and the fresh groundwater were available. Treatments
include Soil = 1 (Sandy), Plants = 3 (Prosopis juliflora, Prosopis
specigera, Prosopis tamarugo), water salinity = 4 (2, 4, 8
and 12 thousand mg L1), irrigation system = 1 (Bubbler), irrigation level
= 1 (Irrigation at 20% moisture depletion of field capacity) and replications
= 4. Statistical Design used was a Complete Randomized Block Design. The
experiment was laid out in an area of 200x30 m and divided into four blocks
of equal size for the application of different water salinity treatments.
The selected plants were transplanted during November, 1999. The plant
to plant and row to row distance was 1 and 2 m, respectively. The initial
physical and chemical characteristics of experimental soil are presented
in Table 1.
Irrigation of Plants: Total amount of water for irrigation, to fulfill field capacity
of soil of a plant basin measuring 1 m (diameter) and 0.5 m depth, was
calculated from the soil moisture data. The total amount of irrigation
water was applied on the basis of maximum water holding capacity of soil
at field capacity. The irrigation was applied at 20% depletion of soil
moisture at field capacity and came to 10 L plant1 per irrigation. All
the plants received 15% excess water, above the field capacity level of
soil, as leaching requirement to maintain soil salinity within acceptable
limits for normal growth. Three water tanks, each having a capacity of
10 m3, were placed near the block to apply irrigation water
of desired salinity for different treatments.
||Initial physical and chemical characteristics of experimental
Composition of Waters of Different Salinities: Waters for different salinity treatments were composed by mixing
freshwater from a well having an EC of around 2.5 dS m1 with the water
from an evaporation pond having EC between 31-42 dS m1. The freshwater
and the saline pond water were mixed in proper proportions to attain water
EC of 6.25, 12.5 and 18.75 dS m1 for T2, T3 and
T4, respectively. Freshwater from the well was kept as the
control treatment. Water samples were collected from the well, evaporation
pond (before composition) and irrigation tanks (after composition) and
analyzed for pH, EC, Ca, Mg, Na, K, CO3, HCO3 and
Cl. The chemical composition of the well water, pond water and the treatment
waters is given in Table 2.
Installation of Tensiometers: Three sets of tensiometers (each set of two tensiometers) were installed
in each block at 12 cm distance from the main trunk of a plant at 15 and
30 cm depth of soil to monitor soil moisture depletion. In all, there
were 12 sets of tensiometers in 4-blocks (Fig. 1).
Installation of Salinity Sensors: Three sets of salinity sensors (each set of two) were installed
in each block at 10 cm distance from the main trunk of a plant at 15 and
30 cm depth of soil to monitor soil salinity. In all, there were 12 sets
of salinity sensors in 4-blocks (Fig. 1).
Plant Growth Measurements: Plant growth measurements included plant height and total biomass.
Plants were harvested after completion of one year growing season. A total
of two crop seasons were completed for the experiment. Fresh biomass was
recorded for each plant at the time of harvesting.
||Salinity sensor and Tensiometers in the field
Soil Samples: Soil samples were taken from 0-15, 15-30 and 30-60 cm depth of soil
from each plant before and after the harvesting to measure soil salinity.
The soil samples were analyzed for pH, EC, SAR and physical separates
(sand, silt and clay %) according to US Salinity Staff (1954).
Factors Affecting Soil Electrical Conductivity (EC): The conduction of electricity in soil takes place through the moisture-filled
pores that occur between individual soil particles. Therefore, the EC
of soil is determined by the following soil properties.
||Porosity: The greater the soil porosity, the
more easily electricity is conducted. Soil with high clay content
has higher porosity than sandy soil. Compaction normally increases
||Water content: Dry soil is much lower in conductivity than
the moist soil.
||Salinity level: Increasing concentration of electrolytes
(salts) in soil water will dramatically increases soil EC.
||Cation Exchange Capacity (CEC): Mineral soil containing high
levels of organic matter (humus) and or 2:1 clay minerals such as
montmorillonite, illite, or vermiculite have a much higher ability
to retain positively charged ions (such as Ca, Mg, K, Na, NH4
or H) than soil lacking these constituents. The presence of these
ions in the moisture filled soil pores will enhance soil EC in the
same way that salinity does.
||Temperature: As temperature decreases towards the freezing
point of water, soil EC decreases slightly. Below freezing, soil pores
become increasingly insulated from each other and overall soil EC
The following dilution factors are recommended to convert 1:5 suspension
EC into saturation paste extract EC for practical purpose.
|Dilution factors to convert 1:5 suspension EC into saturation
|Source: Slavich and Petterson (1990)
The data were subjected to statistical analysis according to Snedecor
and Cochran (1973).
Plant Fresh Biomass Mean biomass per plant ranged between 8.2-11.2 kg in various water salinity
treatments (Table 3). The biomass yield increased significantly
with increasing water salinity than the control treatment (LSD0.05
= 1.042). The difference in yield was significant among all the treatments
except T1 and T2 where it was not significant. The
trend of increase in biomass for the effect of irrigation water salinity
was almost similar in both the growing seasons. This increasing trend
could be due to the fact that the plant, being semi to high salt tolerant
might have utilized the mineral elements from irrigation water to meet
its nutritional requirements. Since Prosopis juliflora belongs to the
leguminous family, it might also have fixed some of the atmospheric nitrogen
which countered the adverse effects of high irrigation water salinity
thus resulting in better growth under saline irrigation.
Plant Fresh Biomass: Mean biomass per plant ranged between 0.7-1.3 kg in various water salinity
treatments (Table 3). The biomass yield increased significantly
up to water salinity of 4,000 mg L1 and then decreased significantly with
increasing water salinity than the control treatment (LSD0.05
= 0.242). The difference in yield was significant between T1
and T4, but it was not significant among T1, T2
and T3 treatments. The data further show that increase in irrigation
water salinity to a certain level supported the plant growth but later
on it adversely affected the plant growth. The trend for the effect of
irrigation water salinity was similar in both the growing seasons.
Plant Fresh Biomass: Mean biomass per plant ranged between 0.3-0.6 kg in various water salinity
treatments (Table 3). The biomass yield showed significant
increases up to water salinity of 4,000 mg L1 and then decreased significantly
with increasing water salinity than the control treatment (LSD0.05
= 0.228). The difference in yield was not significant between T1
and T2 and among T1, T3 and T4
treatments. The data further show that increase in irrigation water salinity
to moderate level supported the plant growth but above that it adversely
affected the plant growth.
Soil Salinity: Depending upon different irrigation water salinity treatments, mean
soil salinity ranged between 3.59-18.26 dS m1 in the surface 0-15 cm and
4.33-21.33 dS m1 in the sub-surface 15-30 cm depth of soil (Table
4). The soil salinity increased significantly with the application
of waters of different salinities and seemed approaching to equilibrium
with the irrigation water salinity.
||Effect of irrigation water salinity on biomass yield of plants
|Figures in a column followed by the same letter(s) are
not significantly different at 5% level of significance, BM = Biomass
||Effect of saline irrigation treatments on ECe
Laboratory Measurements: Mean soil salinity ranged between 1.9-7.81 dS m1 (First Year) and
3.54-9.95 dS m1 (Second Year) in different water salinity treatments (Table
5). The soil salinity increased significantly with increasing irrigation
water salinity than the control (TDS of water = 2,000 mg L1) treatment.
The difference in soil salinity was significant among all the treatments
except for the second growing season where it was not significant between
T3 and T4 treatments. Overall percent increase in
soil salinity ranged between 151-620% after first harvesting and 281-773%
after second harvesting. This also indicated that salt build up in soils
depends on the total water salinity and the time period over which the
land remained under irrigation.
Soil salinity measured by salinity sensors was significantly higher than
the conventional methods. This might be due to the fact that the soil
solution around plant root zone contain maximum amount of dissolved salts
upon irrigation. Whereas, in the laboratory, the soil saturation paste
extract is prepared which is kept overnight and then the soil salinity
is measured which might have diluted the salts and depicted low values
than in situ measurements. In conclusion, the salinity sensors
proved a better tool for monitoring soil salinity under field conditions
in the vicinity of roots of the growing plants than the conventional laboratory
methods. Moreover, in situ soil salinity measurement technique
is less destructive to soil and plants, needs less time for taking observation
and is cost effective.
Relationship Between ECw vs ECe and EC:s
A regression analysis was run to determine relationship between ECw
and the soil salinity measured by soil saturation paste extract and salinity
sensors (Fig. 2). The soil salinity measured by salinity sensors
is closely related to the irrigation water salinity as compared to EC of saturated
||Comparison of ECe values for different analytical
This indicates that in situ soil salinity measurements were better
indicators of the actual solute potential around plant roots than ECe.
As such, the use of salinity sensors should be preferred over other time consuming
Presently many conventional methods and quick techniques are being
used for accurate measurement of soil salinity under saline irrigation
practices. The study findings indicated that the soil salinity measured
by salinity sensors was very close to the irrigation water salinity and
1-1.5 times higher than that obtained by the conventional methods. The
research findings agree with those of Bouksila et al. (2008),
Amezketa (2006), Zhang et al. (2004), Konukcu et al. (2003),
Hamed et al. (2003), Robinson et al. (2003) and Nichol
et al. (2002) who concluded that soil salinity sensors and salinity
probes were better, quick and accurate in determining the soil salinity
than the conventional methods for better understanding salt accumulation
in saline irrigated soils in order to reduce crop yield losses.
Soil salinity increased significantly with the application of saline
water, but the application of 15% leaching requirements prevented soil
salinity development to a greater extent. Mean fresh biomass of all plants
decreased significantly with increasing irrigation water salinity except
Prosopis juliflora, which showed increases in fresh biomass
with increasing irrigation water salinity. Contrastingly, Prosopis
specigera, showed increases in biomass with water salinity between
4000 and 8000 mg L1 but showed decreasing trend above this limit. Whereas,
Prosopis tamarugo showed continuous decrease in biomass with increasing
irrigation water salinity.
Salinity sensors proved a reliable tool for measuring in situ soil
salinity than the conventional laboratory methods which are laborious
and time consuming. Also, the tensiometers did not prove a reliable equipment
for monitoring soil moisture in coarse textured (sandy) soils.