Environ Earth Sci (2013) 69:1589–1600
DOI 10.1007/s12665-012-1993-4

ORIGINAL ARTICLE

Identification of sulfate sources in groundwater using isotope
analysis and modeling of flood irrigation with waters of different
quality in the Jinghuiqu district of China
Xiuhua Liu • Jirka Šimůnek • Lin Li •Junqi He

Received: 9 February 2012 / Accepted: 12 September 2012 / Published online: 25 September 2012
 Springer-Verlag Berlin Heidelberg 2012

Abstract The main objective of this study was to identify
the main sources and processes that control SO42groundwater concentrations in the Jinghuiqu irrigation
district of China using isotope analysis. Lysimeter irrigation
experiments and numerical modeling were used to assess
the impact of long-term irrigation practices on sulfate
transport, when different sources of irrigation water wereused. SO42- concentrations in the groundwater of the entire
irrigation area increased significantly from the years 1990
(a mean value was 4.8 mmol L-1) to 2009 (a mean value
was 9.84 mmol L-1). The d34S-SO42- values (ranging
from ?5.27 to ?10.69 %) indicated that sulfates ingroundwater were initially predominantly derived from
dissolution of minerals. However, no soluble sulfate minerals (gypsum and/or mirabilite) were detected after 1990.
To better understand this seeming anomaly, water content
and SO42- data were collected before and after the field
irrigation experiment and analyzed using the HYDRUS-1Dand HP1 software packages. The experimental data were

X. Liu (&)
Department of Environmental Science and Engineering,
Chang’an University, No.126 Nanduan Yanta Road,
Xi’an 710054, Chinae-mail: liuxh68@chd.edu.cn
J. Šimůnek
Department of Environmental Sciences, University of California
Riverside, Riverside, CA 92521, USA
L. Li
Xi’an Center of Geological Survey, China Geological Survey,
Xi’an 710054, China
J. He
Water and Development Institute, Chang’an University,
Xi’an 710054, China

also used to assess sulfate leaching when different sourcesof irrigation water were used under current irrigation
practices. The dissolved sulfate concentrations in the soil
profile increased significantly when groundwater was used
for infiltration compared to the use of surface water. Irrigation water sources had a great impact on the increase of
sulfate concentrations in the shallow groundwater, especially when groundwater with elevated concentrations wasused for irrigation.
Keywords Sulfate  Stable isotopes  Irrigation Transport and leaching  HYDRUS-1D and HP1 models

Introduction
Groundwater pollution is increasingly a concern in many
irrigated areas with arid, semi-arid, and even sub-humid
climates with persistently scarce rainfall conditions. Jinghuiqu (34250 2000 –34410 4000 N, 108340 3400 –109210 3500 E)
is a large irrigation district located in the middle of the
Guanzhong plain of the Shaanxi Province of China(Fig. 1). The total area of this irrigation district is
1,180 km2. It belongs to the catchment of the Weihe River,a Cenozoic fault-block basin filled predominantly with
Tertiary fluvial and aeolian sediments and Quaternary loess(Bellier et al. 1988). The upper part of the sedimentary
filling consists mainly of Quaternary fluvial deposits(Fig. 2), having mostly a sandy clay loam texture. The
district has experienced 2,200 years of irrigation history,
and currently possesses a high population density (Liu andZhu 2011).
Due to being located in the semi-arid region, the Jinghuiqu district has a shortage of water resources for irrigation. So far, existing research has focused mainly on

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a

b

c

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Environ Earth Sci (2013) 69:1589–1600
b Fig. 1 a A map showing the location of the irrigation district inChina. b A map of the Jinghuiqu irrigation district (the Shaanxi
province, China) and the location of groundwater sampling wells.
Different colors and symbols (e.g., IA, IIA) represent hydrogeologicalconditions: IA—the Jinghe river first terrace strong water-rich subdistrict, IIA—the Jinghe river second terrace water-rich sub-district(south of the Yeyuhe and Qihe rivers), IIIA—the Jinghe river third
terrace water-rich sub-district, IB—the Weihe river first terrace strong
water-rich sub-district, IIB—the Jinghe river second terrace waterrich sub-district (north of the Qihe river), IIIB—the Weihe river
second terrace water-rich sub-district, IIC—the Jinghe river second
terrace water-rich sub-district (north of the Yeyuhe and Qihe rivers),
IV—the Loess Plateau weak water-rich sub-district. c The experimental arrangement. x, y, and z axes are in meters. Plot (1) was
irrigated only with groundwater, while plot (2) was irrigated withgroundwater and the fertilizer ((NH4)2HPO4). The numbers 0, 1, and6 in the plots indicate times of the sampling (at the beginning of theexperiment, and 1 and 6 days after irrigation) using a twist drill

quantitative water-related issues, such as irrigation systems(Li 1998; Liu 2002), irrigation techniques (Gao 2004),
optimization of water use, the efficient use of irrigationwater, and an optimal conjunctive use of surface andgroundwater (Liu 2005; Zhao and Fei 2006; Li et al. 1999;
Liu and Zhu 2011). Since 1990, due to the lack of available
surface water, the Jinghuiqu district has increased pumping
from the aquifers to provide water for irrigation, which has
resulted in a significant drop in the groundwater table (Liu
2010). However, research is still lacking on qualitative
water-related issues, such as the evolution of sulfate concentrations in the groundwater.
The field survey in the Jinghuiqu district showed that the
groundwater had become seriously polluted with SO42-,
which is a very important and widespread environmental
problem in many irrigated agricultural regions (Böhlke
2002; Rock and Mayer 2009; Szynkiewicz et al. 2011).
Models evaluating these environmental risks should consider an integrated approach (Ramos et al. 2011), andshould be capable of predicting water and solute movementin the vadose zone and analyzing specific laboratory or
field experiments involving unsaturated water flow and1591

solute transport (Gonçalves et al. 2006). Such models could
provide helpful tools for extrapolating information from alimited number of field experiments to different soil types,
crops, and climatic conditions, as well as to different tillage
and water irrigation management schemes (Gonçalves et al.
2006; Forkutsa et al. 2009; Ramos et al. 2011).
The first objective of this study was to identify historicalSO42- sources and controlling hydrogeochemical processes in the groundwater using stable isotopes and byanalyzing spatial and temporal variations of SO42- in the
groundwater of the entire irrigation area. The second
objective was to use the lysimeter irrigation experiment toassess sulfate leaching when different irrigation water
sources were used under current irrigation conditions, andto show the impact of long-term irrigation on sulfate evolution in the groundwater in the Jinghuiqu irrigation district. While the former objective was addressed byanalyzing temporal changes of SO42-, the latter objective
was achieved by evaluating lysimeter data using the HYDRUS-1D and HP1 software packages. The lysimeter
experiment was intended to replicate current irrigation
methods and conditions to determine whether the elevatedSO42- in the groundwater is controlled by the different
irrigation water sources or the sulfate minerals in deposits.

Materials and methods
Irrigation district
In the Jinghuiqu irrigation district, both surface water (fromthe Jinghe River) and groundwater are used by farmers forsurface flood irrigation. The climate is semiarid and has amean annual precipitation of about 533 mm, with nearly
60 % of the annual rainfall received between July and
September. The mean annual temperature is 13.6 C, with amaximum of 42 C in July and a minimum of -24 C in

Fig. 2 Cross-section of the Jinghuiqu irrigation district and locations and depths of sampling wells (from the Groundwater Investigation Reportof Jinghuiqu, Jinghuiqu Irrigation District 1983; (1) unconfined aquifer; (2) confined aquifer)

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Table 1 Ionic compositions of waters used in the irrigation experiment (mmol L-1)
Water type

HCO3-

Cl-

SO42-

Ca2?

Mg2?

Na?

pH

Surface watera

5.21

3.16

2.45

1.45

1.8

7.1

8.02

Groundwater (1)b

5.30

3.50

1.51

0.72

0.41

3.02

7.82

Groundwater (2)c

10.9

8.59

9.64

1.81

6.55

21.0

7.59

a

Used in the irrigation experiment in November of 2009b

Used in the irrigation experiment in November of 2008c

Mean values for irrigation district groundwater in November of 2009

January. The average annual potential evapotranspiration is
1,212 mm. While winter wheat and maize are generally
irrigated using water from the aquifer between June and
September, surface water is typically used between
November and May to preserve the ground water table.
Typically, the fields of the irrigation district are irrigated 3–5
times a year, depending on the amount of precipitation. The
quantity of water used for flood irrigation ranges from 18 to
24 cm.
Groundwater sampling
Groundwater samples were collected in April 1990 (from91 wells), November 2008 (46 wells), and December 2009(46 wells) in the Jinghuiqu irrigation district for chemical
and isotopic analyses (2008) from both shallow and deep
(more than 50 m below the surface) wells used fordomestic and agricultural water supply. Sampling locations
are shown in Fig. 1b. The same sampling locations wereused in different years. As groundwater levels dropped
after 1990, several well screens were above the groundwater table in 2008/2009 and could not be used for thesecond sampling round. Groundwater samples were collected directly from the wells with the submersible pump.
The groundwater samples, collected over a 3-day period,
were filtered through a 0.45-mm membrane, and stored in
60 mL polyethylene bottles for chemical analysis.
Field experiments
Field infiltration processes were studied in the soil profile
irrigated with groundwater at the experimental station of
the Jinghuiqu irrigation area (Fig. 1c). Two experimentalsites (with a size of 11 m2 9 2.0 m deep each) were constructed for this purpose. To prevent lateral movement of
surface irrigation water, the sites were laterally isolatedwith mounds. They were then exposed to atmosphericconditions. The sites were bare (not covered by vegetation)
during the experiments. They were manually surface flood
irrigated with 18 cm (nearly 2 m3) of groundwater during
the normal irrigation period in November 2008. Irrigationwater used for experimental irrigation was collected on

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November 11, 2008, and monitored for concentrations ofNa?, Ca2?, Mg2?, SO42-, HCO3-, and Cl- (Table 1,
groundwater (1)).
At the beginning of the experiment, and at 1 and 6 days
after irrigation, soil samples were collected using the twist
drill from 6 depths of 0–20, 20–40, 40–60, 60–100, 100–150,
and 150–200 cm (mixed samples were used, e.g., the 0- to
20-cm soil sample was mixed from soil collected between
depths of 0 and 20 cm). Samples were stored in a darkchamber and kept at 4 C until laboratory measurements thenext day. Ion concentrations of Cl-, SO42-, HCO3-, Na?,
K?, Ca2?, and Mg2? in the soil samples were measured bydiluting the soil solution in water (1:5 soil/solution) andallowing it to interact for 3 min with the solution. All measurements were performed using three replicates.
The soil water contents were measured during the irrigation experiment using the TDR (Time Domain Reflectometry) system (Intelligent Micromodule Elements,
TRIME, IMKO, Germany) before irrigation, and at 1 and
5 days after irrigation, at 20-cm intervals between depths
of 0.2 and 2 m. The TRIME portable borehole packer unit
used here has a two-electrode probe configuration, with
150-mm long electrodes made from lead. The manufacturer
indicates that the measurement error of the borehole packer
is about ±0.2 %. The packer is lowered into a 100-mm
diameter, uncased borehole and then inflated to push theelectrodes close to the borehole wall, according to themethod described by West and Truss (2006). The borehole
was cased to a 2-m depth with a PE pipe to prevent its
collapse. Three readings were taken at each depth andaveraged. The manufacturer’s calibration was used, whichconverts the measured travel time of a signal directly into
the water content of the material in contact with the packer.
The measured water contents (h) and their statistics arepresented in Table 2.
Sample analyses
The pH was measured using a potentiometric method.
Samples for cation analysis were preserved using ultra-pure
HNO3. Cations were analyzed using inductively coupledplasma-atomic emission spectrometry (ICP-AES). Anions

Environ Earth Sci (2013) 69:1589–1600
Table 2 Measured watercontents and corresponding
statistics during the irrigation
experiment (cm3 cm-3)

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Time (days)

Numberof samples

Maximum

Minimum

MeanStandard
deviation

Coefficientof variation (%)

0

9

0.28

0.18

0.22

0.03

0.14

1

9

0.41

0.22

0.3

0.06

0.20

2

9

0.35

0.23

0.29

0.04

0.14

3

9

0.34

0.23

0.28

0.03

0.11

4

9

0.32

0.25

0.28

0.03

0.11

Table 3 Measured SO42- and Cl- concentrations in groundwater and corresponding statistics in 1990, 2008, 2009, and 2011 (mmol L-1)
Variable

Numberof samples

Maximum

Minimum

MeanStandard deviation

Coefficient ofvariation (%)

Frequency
distributionsof more than
250 mg L-1 (%)

90

38.0

2.63

7.8

4.36

0.59

49.4

90

16.5

1.5

4.8

2.29

0.48

92

Cl-

46

31.5

2.25

8.48

5.02

0.59

52.2

SO42-

46

23.5

2.0

9.23

4.41

0.76

97.8

d34S (%)

11

10.7

5.27

9.11

1.5

0.16

Cl-

46

24.2

1

8.59

4.38

0.51

61.7

SO42-

46

21.9

1.55

9.84

4.37

0.44

97.8

Cl-

41

17.7

1.5

8.65

3.23

0.37

69.6

SO42-

41

35.0

2.63

13.7

5.18

0.38

100

Frequency
distributionsof more than
600 mg L-1 (%)

1990
Cl2-

SO4

16.5

2008
73.9

2009
85.1

2011
95.1

d34S is also given for 2009

Cl- and SO42- were measured with ion chromatography.
Bicarbonate (HCO3-) was measured by acid–base titration.
Cation and anion concentrations were determined with adetection limit of 0.001 mmol/L and an accuracy better
than 2 %. Table 3 presents the statistics for groundwaterCl- and SO42- concentrations in 1990, 2008, 2009, and2011.
Eleven groundwater samples from 2008 were selected
for the analysis of d34S values of SO42-, assuming uniform
distribution in each hydrogeological unit. Sulfates ingroundwater were precipitated as BaSO4, and d34S values
were determined in the State Key Laboratory of Environmental Geochemistry at the Institute of Geochemistry
Guiyang, as described by Shanley et al. (2005). Stable
isotope ratios were reported in the usual d notation, withrespect to international standards V-CDT (Vienna Canyon
Diablo Troilite) for sulfur isotope measurements. An
average precision of measurements was ±0.3 % for d34SSO42- values. The measured d34S-SO42- and their statistics are presented in Table 3.

The isotopic composition of sulfate has been successfully used for examining sources and pathways in the sulfur
cycle, including tracing the contribution of anthropogenic
sulfate to groundwater (e.g., Van Donkelaar et al. 1995;
Mitchell et al. 1998; Kaown et al. 2009). Typical d34S
values range from -15 to ?14 % for mineral sulfate, from
-34 to ?7 % for sulfate from oxidation of reduced sulfur
minerals, and from 0 to ?6 % for sulfate in atmosphericdepositions in industrialized countries (Krouse and Mayer
2000; Rock and Mayer 2002; Mayer 2005).
Numerical models
The HYDRUS-1D software package uses several modelingconcepts for evaluating solute transport (Šimůnek et al.
2008a, b). By combining HYDRUS-1D with PHREEQC(Parkhurst and Appelo 1999), HP1 (Jacques et al. 2008) is asignificant expansion of HYDRUS-1D, while preserving
most or all of the features and capabilities of the two original codes. The program can simulate precipitation/

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dissolution, cation exchange, and sorption processes basedon thermodynamic equilibrium, kinetics, or mixed equilibrium-kinetic reactions (Šimůnek et al. 2009). This model
has been extensively used in simulating water and contaminant transport in variably saturated porous media(Jiang et al. 2010), and for a wide range of applications inboth the research and management of irrigation systems
with poor water quality (e.g., Gonçalves et al. 2006;
Hanson et al. 2008; Forkutsa et al. 2009; Šimůnek et al.
2009).
HYDRUS-1D was applied in two ways in this work.
First, to analyze field experimental data involving watercontents and sulfates to lend greater credibility to simulations and allow for the extrapolation to different soil types,
climatic conditions, and irrigation methods (using
groundwater (1) in Table 1). Second, based on the above
conclusions, to explain the impact of different flood irrigation water sources (local groundwater (2) and surface
water from the Jinghe River in Table 1) on groundwater
quality and the evolution of SO42- in the future.
Water flow
Variably saturated water flow was simulated in HYDRUS1D using the Richards equation, which requires input
parameters describing the soil hydraulic properties. The
van Genuchten–Mualem analytical model (van Genuchten1980) was used to approximate the soil hydraulic properties. Details about the water flow module are given in the
HYDRUS-1D technical manual (Šimůnek et al. 2008a,
2008b).
Solute transport
The partial differential equations governing one-dimensional advective-dispersive solute transport in a variably
saturated rigid porous medium are defined in HYDRUS-1D
as:


ohci
o
oci
oqci
hDw
¼
 Scr;i þ Ri
ð1Þ

i
ox
ot
ox
ox
where i (= 1,…,Nm) is the aqueous species number (Nm isthe total number of aqueous species), h is the volumetricsoil water content [L3 L-3], ci is the aqueous concentrationof the ith species [ML-3], q is the volumetric flux density[L T-1], S is the sink term in the water flow equation[T-1], cr is the concentration of the sink term [M L-3], Dw
is the dispersion coefficient in the liquid phase [L2 T-1],
and Ri is the general source/sink term representing geochemical reactions [M L-3 T-1]. This sink/source term
contains heterogeneous equilibrium reactions, and homogeneous and heterogeneous kinetic reactions.

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Environ Earth Sci (2013) 69:1589–1600

The parameter Ri in Eq. (1) represents equilibrium
precipitation/dissolution reactions of minerals, and can be
described as
NmXpvpji Amj ¼ Aið2Þ

j¼1

where i = 1,…,Np (Np is the number of minerals), Amj andp
Ai are the chemical formulae of the master and secondary
species, respectively, and vpji are the stoichiometriccoefficients in the reaction. The superscript p refers topure phases (minerals). For equilibrium conditions, themass-action equation is
Kip ¼

Nm
Y
p
m vjiðcm
j cj Þ

ð3Þ

j¼1

where Kip is the equilibrium constant of a reaction (2), andcm
j is the activity coefficient of the j master species in thesolution. The activity coefficients can be defined using theDavies equation or the extended Debye-Hückel equation(Langmuir 1997; Parkhurst and Appelo 1999). The activityof a pure phase (mineral) is assumed to be 1.
Initial conditions and input parameters
Initial water contents were specified according to TDR
readings (Table 4) collected immediately before the start ofthe irrigation experiment on November 11, 2008 (anaverage value of the two TRIME probes; Fig. 1b). Solution
compositions of waters used in the experiments and simulations are presented in Table 1.
The particle size distribution was obtained using thepipette method for particles with diameters smaller than
20 lm (clay and silt fractions), and by sieving for particles
between 200 and 2,000 lm (coarse sand), and between 20
and 200 lm (fine sand) (Table 4). The dry bulk density wasmeasured using soil samples of known volume. Dispersivity(k) values were obtained using the HYDRUS-1D inverse
model, based on Cl-1 concentrations during the irrigation
experiment, and set to a uniform value throughout the soil
profile. The sensitivity analysis of the impact of the k value
on SO42- concentrations is presented in Table 5.
Table 6 lists the van Genuchten–Mualem parameters (vanGenuchten 1980) for the soil hydraulic functions of particularsoil layers. These were obtained using the Rosetta module(Schaap et al. 2001), which is implemented in the HYDRUS1D software package, according to the particle size distribution and the bulk density of each layer of the soil.
According to the results of the mineralogical analysis(Liu et al. 2011), concentrations of reactive calcite(CaCO3) and dolomite CaMg(CO3)2 were 10-3 and 10-4mmol kg-1, respectively. Since no gypsum (CaSO42H2O)

Environ Earth Sci (2013) 69:1589–1600

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Table 4 Selected physical and chemical soil characteristics of the soil profile before the irrigation experiment (2008/11/11)
Depth (cm)
0–20

20–40

40–60

60–100Coarse sand (%)

12.5

Fine sand (%)

37.1

Silt (%)

16.4

100–150

150–200

24.7

1.4

23.8

5.1

2.8

32.2

46.3

46.2

56.8

58.3

12.9

15.5

7.0

10.9

10.9

Clay (%)

34.0

30.0

36.8

23.0

27.2

28.0

TextureSandy clay loam

Sandy clay loam

Sandy clay loam

Sandy clay loam

Sandy clay loam

Sandy clay loam

Bulk density (g cm-3)

1.41

1.42

1.35

1.37

1.46

1.57

Water content (cm3 cm-3)
Soil soluble ions

0.18

0.20

0.20

0.22

0.23

0.27

pH (H2O)

8.7

8.2

8.4

8.9

8.4

8.5

Ca2? (mmol L-1)

0.96

0.78

0.58

0.51

0.43

0.49

Mg2? (mmol L-1)

0.58

0.62

0.47

0.47

0.52

0.51

Na? (mmol L-1)

0.10

0.27

0.91

0.96

1.30

1.20

K? (mmol L-1)

0.04

0.12

0.31

0.53

0.77

0.68
0.49

2-

SO4

-1

0.20

0.42

0.40

0.40

0.47

Cl- (mmol L-1)

(mmol L )

0.62

0.40

0.25

0.37

0.62

0.67

Dispersivity (cm)

17.6

17.6

17.6

17.6

17.6

17.6

Table 5 Changes in SO42- (%) at depths of 1 and 2 m based on the sensitivity analysis for selected model parameters
Depth (m)

q

Ks

k

?20 %

-20 %

?20 %

-20 %

?20 %

-20 %

1

3.1

1.3

1.2

1.1

2.4

2.5

2

3.3

1.6

1.1

1.3

3.0

3.3

60–100

100–150

150–200

Ks saturated hydraulic conductivity, q bulk density, k dispersivity
Table 6 van Genuchten–Mualem parameters for the soil hydraulic functions
Depth (cm)
0–20

20–40

40–60

hr (cm3 cm-3)

0.08

0.08

0.08

0.07

0.07

0.07

hs (cm3 cm-3)

0.43

0.44

0.45

0.41

0.41

0.41

a (cm-1)

0.02

0.021

0.02

0.024

0.023

0.023

n (-)

1.34

1.35

1.32

1.39

1.33

1.32

l (-)

0.5

0.5

0.5

0.5

0.5

0.5

19.0

27.9

19.0

33.4

22.2

21.5

Ks (cm day-1)
3

-3

3

-3

-1

hr (cm cm ), residual soil water content; hs (cm cm ), saturated soil water content; a (cm ), parameter in the soil water retention function;n (-), parameter in the soil water retention function; l (-), tortuosity parameter in the conductivity function; Ks (cm day-1), saturated hydraulicconductivity

or mirabilite (Na2SO410H2O) were present, the initialvalues of reactive gypsum (CaSO42H2O) and mirabilite(Na2SO410H2O) in the soil were set to 0 mmol kg-1.
Time-variable boundary conditions
Atmospheric and free drainage conditions were used asboundary conditions at the surface and the bottom of thesoil profile, respectively. Atmospheric boundary conditions
were specified using meteorological data collected at the
Jinghuiqu meteorological station, and were used to compute daily values of the reference evapotranspiration rate(ETC) using the Penman–Monteith method (Allen et al.
1998). The reference evapotranspiration rate was assigned
to potential evaporation, while potential transpiration was
set to zero because the experimental sites were bare.

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Fig. 3 Distribution ofgroundwater SO42concentrations in the Jinghuiquirrigation district in 1990 (top)and 2009 (bottom) (mmol L-1)

Results and discussion
Sulfate geochemistry in groundwater
The SO42- concentrations in groundwater samples obtainedin April, 1990, November, 2008, and December, 2009 aresummarized in Table 3. In 1990, the SO42- concentrations in
the groundwater of the entire irrigation area ranged from 1.5
to 16.5 mmol L-1, with a mean value of 4.8 mmol L-1. In
2008, the concentrations ranged from 2.0 to 23.5 mmol L-1,
with a mean value of 9.23 mmol L-1, and in 2009 it ranged
from 1.55 to 22.0 mmol L-1, with a mean value of
9.8 mmol L-1 (Fig. 3). Although some wells analyzed in

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1990 were not sampled in the following sampling periods,
the percentage of the groundwater samples with elevatedconcentrations has been increasing within the entire irrigation area. Sulfate concentrations greater than 600 mg L-1(about 7 mmol L-1) accounted for 16.5 % of the total irrigated area in 1990, while in 2009, they reached almost
85.1 %. The observed concentrations were far above thenational drinking water standard of 250 mg L-1 (about
3 mmol L-1). Since elevated ion concentrations and distributions were similar in 2008 and 2009, only the 1990 and2009 values are presented here.
While groundwater was characterized mainly as the
HCO3- water type in 1990, in 2009, SO42- was theEnviron Earth Sci (2013) 69:1589–1600

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concentrations and d34S-SO42- indicate two different
SO42- sources (Fig. 5): oxidation of sulfur minerals anddissolution of sulfate minerals. Only d34S-SO42- of
5.27 % for the D07 sample indicated oxidation of sulfur
minerals. d34S-SO42- values for the other 10 groundwater
samples ranged from 8.6 to 10.69 %, indicating dissolution
from early sulfate minerals, such as gypsum and mirabilite,
or from sulfate in the soil.
Transport simulations

Fig. 4 Relation between main anions (SO42-, Cl-, and HCO3-) andtotal dissolved solids (TDS) concentrations in groundwater in 1990
(top) and 2009 (bottom)

Although the isotope analysis discussed above shows that
SO42- is mainly derived from the dissolution of sulfate in
the soil, current mineralogical analysis did not detect any
soluble sulfate minerals in the soil profile (Liu et al. 2011).
To better understand this seeming anomaly, it is necessary
to simulate the dissolution and leaching of sulfate using
different irrigation water sources, and to evaluate its evolution based on current irrigation conditions in the
Jinghuiqu irrigation district.
Volumetric water contents

Fig. 5 Relation between sulfate isotope (d34S-SO4) and SO42concentrations in the irrigation district in 2008. The horizontal line
at d34S = 7 % separates samples from two different SO42- sources

dominant anion (Fig. 4). The extent of areas with elevatedSO42- increased as well. The source of evaluated SO42- ingroundwater will be identified first.
Characteristic d34S values of sulfate
The sulfate concentrations of eleven groundwater samples
varied from 1.75 to 9.24 mmol L-1 and d34S-SO42- values
ranged from ?5.27 to ?10.7 % (Fig. 5). Although there isno baseline study on the level of natural SO42- isotope
values in groundwater in this area, the literature data (Maand Fan 2005) and the relationship between SO42-

The experiments started on November 11, 2008. Inputs for
HYDRUS-1D consisted of the soil hydraulic parameters
for the soil horizons (Table 4) and the quality of theapplied irrigation water (groundwater (1) of Table 1).
Measured and simulated water contents are presented inFig. 6a (see also Liu et al. 2012). The figure shows thatduring the experimental period, water contents increased
and then gradually decreased. Overall, simulated watercontents closely mirrored measured values at all depths.
The correlation coefficients (R) were equal to 0.93, 0.93,
0.9, and 0.81 at 1st, 2nd, 3rd, and 4th day after irrigation,
respectively, with an overall correlation coefficient (R2) of
0.8 for the combined observations. This indicates a good
agreement between measured and simulated values.
Sulfate ions
The input values of SO42- concentrations for HP1 wereobtained from samples collected before the start of theirrigation period and are presented in Table 4. The qualityof the irrigation water (boundary concentrations), andSO42- ion concentrations are presented in Table 1[groundwater (1)]. Irrigating quantity was 18 cm, which is
a common practice in the Jinghuiqu irrigation district.
Measured and simulated concentrations of SO42- in six
depths, 1 and 6 days after irrigation, are presented inFig. 6b. The main differences were found at depths of
0–40 cm at 1 day. We believe that this disagreement could
be largely explained by the sampling approach, as mixed
samples were collected. Thus, the samples cannot

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Fig. 7 Simulated SO42- concentrations at different times (days)(a) and depths (cm) (b)Fig. 6 a Measured (TDR) and simulated (Hydrus) volumetric watercontents (initial and 1, 2, 3, and 4 days after irrigation) andb measured and simulated (HP1) SO42- concentrations (initial and
1 and 6 days after irrigation)accurately represent point values, especially in the first day
after flood irrigation, when water contents and soluteconcentrations changed quickly above the depth of 40 cm.
The simulations of the SO42- concentrations resulted ina good agreement with measured values in the soil profile,with the correlation coefficients for SO42- of 0.87 and 0.91
at days 1 and 6 after irrigation, respectively. This showsthat the model can adequately simulate sulfate transportand dissolution in the soil profile.
Evaluation of different irrigation water sources
Based on this analysis of the simulation results of watercontents and SO42- concentrations after irrigation, it is necessary to use HP1 to further evaluate the impact of the flood
irrigation method and different sources of irrigation water ongroundwater quality under current irrigation practices.

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To better explain involved processes, an evaluation period of 1 year was selected, with irrigations on April 1st(using surface water for winter wheat), August 1st (using
groundwater for maize), and November 1st (using surface
water for winter wheat), as commonly used in this area. The
mean value of SO42- was obtained in irrigation wells in 2009
[groundwater (2)] and in the Jinghe river water which wereused as different irrigation sources (Table 1). Each time, theirrigation quantity was 18 cm. The same soil profile as in thefield experiment described above was used. The soil conditions of that soil profile are presented in Table 4.
Simulated sulfate concentrations versus depth at different times are shown in Fig. 7a. Sulfate concentrations atdays 90 (before irrigation), 92 (1 day after the first irrigation), 93 (2 days after the first irrigation), and 96 (5 days
after the first irrigation) are displayed. Figure 7a shows thatconcentration values on day 92 were substantially higher
than on day 90, primarily due to the mixing and leaching of
the irrigation water (the sulfate concentrations of irrigationwater were higher than the soil initial soluble concentrations). Between days 96 and 212 (before the second irrigation), sulfate concentrations increased in the soil profile atEnviron Earth Sci (2013) 69:1589–1600

depths above 30 cm due to evaporation of soil water. Afterthe second irrigation, sulfate concentrations increased significantly on day 214 (1 day after the second irrigation)compared to day 212 (before irrigation). This is because weused groundwater with a high value of sulfate concentrations for irrigation. During this period, increased values of
sulfate resulted largely from mixing of irrigation water.
Between days 217 and 304 (before the third irrigation),sulfate concentrations increased at depths above 30 cm
because of evaporation, and below 60 cm due to irrigationwater moving downwards. The third irrigation (again using
surface water) caused quite significant leaching of sulfatesfrom the soil profile above 60 cm. Between days 306 and
310, and again at day 365, sulfate concentrations increased
at depths above 30 cm due to evaporation, and at below
60 cm due to the downward movement of irrigation water.
During the simulation period, calculations showed that
there was no dissolution and/or precipitation of gypsum and/or mirabilite. Calcite dissolved largely at depths above 20 cm,
except when it briefly precipitated during the period whengroundwater was used for irrigation (days of 215 and 217).
Simulated sulfate concentrations at depths of 20, 40, 60,
100, 150, and 200 cm of the soil profile are presented inFig. 7b. The figure shows that each irrigation event had an
impact on the increase of sulfate concentrations at all
depths compared to the initial concentrations, especiallywhen groundwater with elevated sulfate concentrations wasused for irrigation (214–304 days). Soluble sulfate concentrations in the soil increased more when groundwater
was used for irrigation than when surface water was used.
After the third irrigation event (305 days), leachingoccurred mainly in depths above 60 cm, where sulfate
concentrations quickly decreased during the 2 days after
irrigation. At deeper depths of 100 cm, sulfate concentrations were increasing during the entire simulated period.
During the simulation, the sulfate concentration increased
up to 3.10 mmol L-1 at a depth of 200 cm from the initialconcentration of 0.5 mmol L-1.
The transport of SO42- in the upper part of the soil
profile depends on the soil properties of the upper soil
layers, which consist mainly of quaternary fluvial deposits(Fig. 2). To assess the effects of model parameters on themagnitude of SO42- leaching, changes in SO42- concentrations at depths of 1 and 2 m due to a 20 % change in thesaturated hydraulic conductivity, Ks; the dry bulk density,q; and the longitudinal dispersivity, k were calculated(Table 5). Table 5 shows that the effect of these selectedparameters on SO42- leaching is relatively minor.
Simulated results show that flood irrigation activities
speed up the amount of sulfate leaching. They further indicate that irrigation water has been the main reason for elevated SO42- concentrations in the groundwater since 1990,
especially when water with elevated SO42- concentrations

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was used. Such water is not suitable as a source of water for
irrigation, since it can speed up the progress of groundwatersalinization. By contrast, the effects of rainfall can beneglected since it has minor effect on the solute movement.

Conclusions
The SO42- values in groundwater for the entire irrigation
area increased from 1990 to 2009. The d34S-SO42- values
indicated that the initial SO42- concentrations resulted
primarily from dissolution of sulfate minerals, but there
was no additional dissolution of soluble sulfate minerals
during the calculation period.
Comparing the sulfate and chloride concentrations in
1990, 2008, 2009, and 2011 (Table 3), ion concentrations
increased when the amount of water decreased due toevaporation. However, mainly irrigation water had a great
impact on the increase of sulfate concentrations in theshallow groundwater, especially when groundwater withelevated sulfate concentrations was used for irrigation.
Changes in SO42- concentrations presented in Fig. 3 andTable 3, as well as the results of the sensitivity analysis in
Table 5, indicate that sources of irrigation water with elevated SO42- concentrations have a significant impact on
the evolution of groundwater SO42- in the entire area.
Measured SO42- concentrations from 2009 and 2011 also
reflect this increasing trend (Table 4).
Many wells in the Jinghuiqu area that are used as sourceof irrigation water have such high sulfate concentrations
that their water can no longer be used for irrigation. During
the last 20 years, elevated sulfate concentrations in theshallow groundwater are mainly due to the use of local
groundwater for irrigation. Since groundwater has highlevels of sulfate concentrations, it can significantly speed
up groundwater salinization.
Acknowledgments This work was supported by the ‘‘Program on
creation and intellectual importation for hydro-ecology and water
security in the arid and semiarid regions’’ of the Ministry of Education and Foreign Expert Bureau of China (‘‘111’’ project), and the
project ‘‘Improving water use efficiency, and the experiment anddemonstration of promoting new socialist countryside construction in
the irrigation areas’’ of the Department of Water Resources of Shaanxi Province. Special thanks also go to the Jinghuiqu administration
for data sharing.

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