Agricultural Water Management 131 (2014) 57–69

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Agricultural Water Management
journal homepage: www.elsevier.com/locate/agwat

Effects of the shallow water table on water use of winter wheat andecosystem health: Implications for unlocking the potential ofgroundwater in the Fergana Valley (Central Asia)
Akmal Kh. Karimov a,∗ , Jirka Šimůnek b , Munir A. Hanjra c ,Mirzaolim Avliyakulov d , Irina Forkutsa eaInternational Water Management Institute (IWMI), Central Asia Regional Ofﬁce, Tashkent 700000 Uzbekistan
Department of Environmental Sciences, University of California Riverside, Riverside, CA, USA
c
International Water Management Institute (IWMI), Southern Africa Regional Ofﬁce, Pretoria, South AfricadTashkent Agrarian University, Tashkent, UzbekistaneUniversity of Giessen, Giessen, Germanyb

a r t i c l e

i n f oArticle history:
Received 8 July 2013
Accepted 16 September 2013
Available online 18 October 2013
Keywords:
Food security
Crop transpiration
Shallow water
HYDRUS
Soil salinity
Ecosystem healthWLE

a b s t r a c t
This paper analyzes the effect of the shallow water table on water use of the winter wheat (Triticum
aestivum L.) that has replaced alfalfa (Medicago sativa) on the irrigated lands of the Fergana Valley,
upstream of the Syrdarya River, in Central Asia. The effect of the shallow water table is investigatedusing HYDRUS-1D. Numerical simulations show that the contribution of the groundwater to evapotranspiration increases with a rising water table and decreases with increasing irrigation applications. Under
irrigation conditions, an increase in the groundwater evapotranspiration is associated mainly with anincrease in evaporation loss, causing a buildup of salinity in the crop root zone. Evaporation losses fromﬁelds planted with winter wheat after the harvest amount up to 45–47% of total evaporation thus affecting soil salinity and ecosystem health. Promoting the use of groundwater for irrigation in order to lower
the groundwater table is suggested to achieve water savings from the change in the cropping pattern.
Unlocking the potential of groundwater for irrigation in the Fergana Valley can also contribute toward
managing soil salinity and improving the health and resilience of water, land and ecosystems of water,
land and ecosystems (WLE).
© 2013 Elsevier B.V. All rights reserved.

1. Introduction
The basin water management, including the infrastructure andinstitutions, that was established in the Aral Sea Basin from 1960
to the mid-1980s, initially prioritized the water use for irrigationof cotton. From 1980 to 2010, the population of Central Asia doubled, increasing the demand for food production. Facing this foodsecurity challenge in new geo-political and socioeconomic environment after the forming of new independent states in the region
after 1990, the states of Central Asia reoriented the focus of agricultural policy on food independency and prioritized food security.
This was achieved in the region by the end of the 1990s by shiftingfrom the cotton (6 years)/alfalfa (3 years) crop rotation to the cotton (2 years)/winter wheat (2 years) sequence. Since the irrigationseason of alfalfa extends from March through September while
winter wheat requires irrigation in October and then from March∗ Corresponding author. Tel.: +99 871 2370445; fax: +99 871 2370317.
E-mail address: a.karimov@cgiar.org (A.Kh. Karimov).
0378-3774/$ – see front matter © 2013 Elsevier B.V. All rights reserved.
http://dx.doi.org/10.1016/j.agwat.2013.09.010

through May, the change of the cropping pattern from alfalfa towinter wheat results in the reduction of the summer irrigation.
This released some of the water resources for the needs of thedownstream water users. However, the water saving effect of thisshift requires a certain clariﬁcation. As long as irrigation in Central
Asia is entirely based on surface water, it is often associated withshallow groundwater tables. Water losses from irrigated ﬁelds andirrigation canals are the main source of groundwater recharge in theirrigated areas of Central Asia, amounting up to 70% of groundwater recharge in some regions, such as the Fergana valley (Borisov,
1990). Groundwater recharge from irrigation, coupled with poor
natural and artiﬁcial drainage, leads to widespread shallow watertable. On average, about 30% of the irrigated land has the watertable less than 2 m below the soil surface. The water saving effect of
the change in the cropping pattern becomes illusory for conditions
with a shallow water table when intensive upward ﬂuxes from thewater table to the topsoil cause topsoil salinization, requiring morewater for leaching.
The quantiﬁcation of upward ﬂuxes from a shallow groundwater table is a signiﬁcant topic that has been extensively researched

58

A.Kh. Karimov et al. / Agricultural Water Management 131 (2014) 57–69(Ganiev, 1979; Zhang et al., 1999; Soppe and Ayars, 2003; Kahlown
et al., 2005; Babajimopoulos et al., 2007; Yang et al., 2007; Huo et al.,2011). In the Fergana Valley, Ganiev (1979) studied over a period offour years the capillary rise from a shallow water table in lysimeter
experiments under fallow and natural conditions, and cropped withcotton or alfalfa. He found in loamy soils under cotton an increase in
the capillary rise by 170, 280, and 330 mm for groundwater depths
of 2.5, 2 and 1.5 m below the soil surface, respectively, compared toconditions with the water table below 3 m. In sandy loam soils, thecapillary rise increased by 146 and 287 mm, and in sandy soils by 80
and 168 mm for groundwater depths of 2 and 1.5 m, respectively,
as compared to conditions with the water table at a depth of 2.5 m
or deeper. Zhang et al. (1999) reported that the ratio of the upward
ﬂux to alfalfa evapotranspiration (ET) varied between 25% and 65%
for a non-saline soil with a groundwater table at a depth of 0.6–1 m.
Soppe and Ayars (2003) maintained a groundwater table at a depthof 1.5 m in weighing lysimeters and found that groundwater contributed up to 40% of daily water used by the safﬂower crop. On
a seasonal basis, 25% of the total crop water use originated fromthe groundwater. In the upper Indus basin near Lahore Pakistan,
Kahlown et al. (2005) investigated the effect of shallow groundwater tables on the crop water use via 18 large-size drainage-type
concrete lysimeters. They found that when a groundwater table
was kept at a depth of 0.5 m, the entire water use of wheat was
supplied by groundwater. Sunﬂower required only about 20% of
its total water need from irrigation. However, in the same region,
maize and sorghum were found to be sensitive to waterlogging, andcrop yields were reduced with a rise of the groundwater table. Yanget al. (2007) quantiﬁed water ﬂuxes in large weighing lysimeters,with a ﬂuctuating groundwater table between 1.6 and 2.4 m during the wheat growth period and 0.7 and 2.3 m during the maize
growth period, and found that, in a rotation system of wheat andmaize, the cumulative capillary upward ﬂux and the deep percolation were 89.6 and 55.9 mm, respectively. Liu and Luo (2011)
conducted a lysimeter experiment to quantify the effects of shallow
water tables on the water use and yield of winter wheat under rainfed conditions. The results showed that, under rainfed conditions,the seasonal contribution of groundwater met more than 65% of
potential evapotranspiration of winter wheat when the water table
depth was within 40–150 cm. Huo et al. (2011) studied the effectof the groundwater level and irrigation amounts on the water useof wheat in a lysimeter experiment at the Hongmen experimental
station located in the Henan Province, China. Capillary rise supplied 29% of the water use of wheat during the time period fromripening to harvest when the groundwater table was 1.5 m deep,
and was reduced when the depth of the groundwater tabledecreased. Water productivity of the wheat biomass increases andthe yield decreases when groundwater levels decrease and theamount of irrigation water is reduced. Past studies indicated complex effects of the shallow water table on crop evapotranspiration.
The Fergana Valley, this study focuses on, has 900,000 ha of irrigated land and it thus represents an example of large-scale irrigatedagriculture in Asia (Fig. 1a). The valley has signiﬁcant potential forthe production of food crops. For instance, the valley receives net
radiation with the capacity to evaporate over 1120 mm/yr of water.
Irrigated crops grown in the valley have the potential to utilize
70–80% of the available energy if the crop growth is not constrainedby a water deﬁcit or other factors. However, actual evapotranspiration is even lower and varies in the range of 611–722 mm/yr, of
which only about 70% is transpired by crops (Karimov et al., 2012).
The reduction of the area under fodder crops by replacing alfalfa
with the winter wheat/fallow system reduced the crop water use inthese areas on average by 30%. A risk of increasing soil salinity undershallow groundwater conditions in the Fergana Valley from a low
saline to highly saline level may further reduce the crop water use
and yields of cotton and wheat by about 25%. While productively
utilizing only 38–45% of the available energy (due to many reasons
such as a low fraction of the area covered by crops, short durationof the cropping season, or conventional furrow irrigation practices)
farmers of the Fergana Valley produce over 850,000 Mg of cotton, 1300,000 Mg of wheat, and 1000,000 Mg of vegetables andother agricultural commodities. Current production volumes could
be increased almost twofold if thermal, soil, and water resources
are used in the most productive way. In order to achieve this, it
is important to move into a cyclic process of reallocating waterfrom a use that produces low or no beneﬁts to one that generates
higher beneﬁts (Molden, 1997; Molden and Sakthivadivel, 1999)
and thus achieves more welfare per drop of water (Molden et al.,2010). The change in the cropping pattern is one of the measuresavailable to policymakers to meet the demand for scarce water, toincrease food production through better exploitation of energy andland resources, and to tactically adapt to climate change (Hanjra
and Qureshi, 2010).
Since 1992 the cotton/alfalfa crop rotation, which dominatedin the Fergana Valley, has been replaced by the cotton/wheat
sequence. Additionally, the cotton growing area was reduced by
82,000 ha by allocating 34,000 ha to vegetables and 48,000 ha to
winter wheat. This approach was attractive for policy makers as a

Fig. 1. (a) Central Asia and (b) hydrogeological zones of the Fergana Valley.

A.Kh. Karimov et al. / Agricultural Water Management 131 (2014) 57–69

measure of achieving grain independence and as a low investment
strategy that brought rapid results by decreasing the irrigationwater demand. However, the real water savings via the decreasein the irrigation water demand are often assumed rather thanempirically demonstrated in a post-policy implementation context.
Additionally, associated socioeconomic beneﬁts, including gains infarmers’ income, employment, food security, and livelihood, arealmost always ignored (Spoor, 1998; Cai et al., 2002; Nandalal
and Hipel, 2007; Awan et al., 2011), and issues of salinity build
up and its implications for water, land and ecosystem’s (WLE)
health and resilience are rarely examined. For instance, a shallow
water table in a considerable part of the study area was not taken
into account while the cropping pattern change was implemented.
This is important because salinity, which is often associated withshallow groundwater tables, affects crop yield and reduces the
productivity in large irrigation systems across Asia (Murgai, 2001;
Smedema and Shiati, 2002; Khan and Hanjra, 2008). Additionally,salinization has ecosystem health linkages and implications forenvironmental water security (ADB, 2013).
This paper analyzes potential water savings due to the replacement of alfalfa by winter wheat under conditions with shallow
groundwater in the context of the change of agricultural policy,
implemented since 1992 in the Fergana Valley, the upstream of
the Syrdarya River basin, in Central Asia. The study focuses on thecontribution of shallow groundwater to evaporation and a salinity buildup in the root zone and its implications for ecosystem
health. Therefore, the objectives of this paper are twofold: (1) toestimate the water-saving effect of growing winter wheat undershallow water table conditions, and (2) to suggest measures toreduce non-productive water losses from fallow lands and strategies for managing soil salinity to improve ecosystem health.
For this, the one-dimensional hydrological model HYDRUS-1D(Šimůnek et al., 2008a) was used to simulate crop transpiration andevaporation from winter wheat as affected by shallow groundwater under rainfed, deﬁcit, and full irrigation conditions. Silt loam
soils, dominating in the central part of the valley, were selected forthis analysis. The results of this modeling exercise could be usefulfor planning land and water management in the river basins, facing similar water-scarcity challenges, and addressing salinity issues
that challenge food production and WLE health in large irrigation
systems.

2. Methods and data
2.1. Study area
The Fergana Valley is located upstream of the Syrdarya Riverand is a part of three countries in Central Asia–Kyrgyzstan, Tajikistan, and Uzbekistan. The climate is semi-arid with a low quantityof precipitation and high summer temperatures. Annual precipitation varies from 100 to 200 mm in the central part of the valley
and increases to 300 mm in the piedmont areas. The mean average temperature is 14 ◦ C. The altitude increases from west to east
from 330 m above sea level (m asl) to 600 m asl. The valley isﬁlled with alluvial deposits washed out by multiple rivers in themountain zone. Three hydrogeological zones, representing hydrogeological conditions of the Fergana Valley, are a groundwater
natural-recharge zone (Zone A), a groundwater springs zone (dominated by upward ﬂuxes) (Zone B), and a groundwater dischargezone (Zone C) (Fig. 1b) (Mirzaev, 1974; Borisov, 1990).
These hydrogeological conditions are favorable for supporting
fresh groundwater use. However, groundwater irrigation is practiced only in few areas as a supplement to canal irrigation. Over
55% of irrigated soils are prone to salinity, including 71,922 ha thatare medium and highly saline in the hydrogeological Zone C (Supiev

59

Fig. 2. Changes of the cropping pattern in the Fergana Valley.

and Ganiev, 2005; Ergashev, 2011). Soil salinity poses a serious risk
to sustainability of food production and resilience of ecosystems.
Two main time periods can be identiﬁed in the recent historyof the crop production in the Fergana Valley. Until the begining of the 1990s, the cotton/alfalfa crop rotation dominated on
the irrigated lands of the Fergana Valley (Fig. 2). The areas undercotton and alfalfa were 43% and 22%, respectively, of the total
irrigated area, while winter wheat was grown on just 8% of theirrigated area. The irrigation demand of the Fergana Valley was in arange of 12,324–12,638 million (M) m3 /yr for the irrigated area of
900,000 ha. The crop production was well supplied with plentiful
water in the study area at an early stage. After 1995, the dominantcotton/alfalfa crop rotation in the region was replaced by the cotton/wheat sequence, aimed at increasing the grain production andenhancing food security. The area under irrigated winter wheat wasincreased to 27%, while the area under alfalfa was reduced to 1% of
the total irrigated area. In addition, the cotton growing area was
reduced by 48,000 ha, mostly replaced by the cultivation of vegetables. Currently, two main crops, cotton and winter wheat occupy
about 60% of the irrigated land. Farmers sow winter wheat in early
October and harvest it in June, and sow cotton in April and harvest
it in September-October. These changes in the cropping pattern
had two main aims: (1) to increase the production of food crops,and (2) to reduce the consumption of water per unit of crop production, i.e., to increase water productivity. The ﬁrst objective waseasily achieved as the production of wheat grain in the Fergana Valley increased since 1990 as average wheat yield increased from 2
to 5.5 t/ha and area under wheat crop expanded to 27%.
The achievement of the second objective, i.e., increasing waterproductivity, was not obvious due to a wide spread of shallow
groundwater, which results in upward ﬂuxes to the crop rootzone and mimic potential gains in water productivity. Reducing
irrigation applications after shifting from alfalfa to winter wheat
caused a lowering of the water table in the Fergana Valley (Fig. 3).
Fig. 3 indicates a gradual reduction of the area with the shallow
water table. However, this area, which is located mostly in the central part of the Fergana Valley, is still signiﬁcant. It is estimated to
be about 200,000 ha and it represents the hydrogeological Zone C
with silt loam and loam soils. It is thus necessary to consider theeffects of shallow water tables on the water use of winter wheat. A
detailed description of the soils of the study area is given by Shrederet al. (1977) and Talipov (1992).
2.2. Research method
In this study, HYDRUS-1D, a variably-saturated water ﬂow
model (Šimůnek et al., 2008a), is used to estimate crop transpirationand evaporation. The HYDRUS-1D software package is a ﬁniteelement numerical model that simulates the one-dimensional

60

A.Kh. Karimov et al. / Agricultural Water Management 131 (2014) 57–69

where Smax is the maximum potential water uptake rate
[cm3 /(cm3 day)] and ˛ is a function of the pressure head [–].
HYDRUS-1D assumes that solutes in the soil proﬁle can be transported by convection and dispersion in the liquid phase, as well as
by diffusion in the gas phase (Šimůnek et al., 2008a). In irrigatedﬁelds, the total salt ﬂux density can be described as a sum of convective and dispersive ﬂuxes, while the gas-phase diffusion can beneglected (Singh et al., 2003):
J = Jcon + Jdis , Jcon = qC, Jdis = −qLdis

Fig. 3. Temporal changes in the areas with a shallow water table in the Fergana
Valley.

movement of water, heat, and multiple solutes in variablysaturated media (Šimůnek et al., 2008b). The model has beenpreviously used and veriﬁed in a large number of studies (e.g., Bahet al., 2009; Boudreau et al., 2009; Cao and Gong, 2003; De Vos
et al., 2000; Endo et al., 2009; Gribb et al., 2009; Hao et al., 2008a,b;
Heatwole and McCray, 2007; Hernandez, 2001; Liu and Xie, 1998;
Meng et al., 2004; Sanchez et al., 2003; Šimůnek et al., 2008c; Wanget al., 2005; Xu et al., 2005). For example, Forkutsa et al. (2009) used
the model to simulate water ﬂow in ﬁelds with irrigated cotton andshallow groundwater on loam and sandy loam soils of the Khorezm
region, located in the downstream part of the Amudarya River. Also,
Shouse et al. (2011) used the HYDRUS-1D model for simulating root
water uptake from a soil proﬁle with shallow saline groundwater.
The HYDRUS-1D model simulates variably-saturated ﬂow bysolving the Richards’ equation written as:
∂
∂
=
K
∂t
∂z





∂h
+1
∂z

− S,

Se =

 − r=s − r n −m

1 + ˛r h,(2)where Se is effective saturation [–],  r and  s are residual and saturated water contents [cm3 /cm3 ], respectively, and ˛r [1/cm], m[–], and n [–] are shape parameters. The soil hydraulic conductivity
function is described in HYDRUS-1D using the statistical pore-size
distribution model of Mualem (Mualem, 1976; Van Genuchten,1980):



1/m

K = Ks S l 1 − 1 − Se

m 2
,

(3)

where Ks is the saturated hydraulic conductivity [cm/day], l [–] is apore connectivity parameter, and m = 1 − 1/n, while n > 1.
Root water uptake by plant roots and its dependence on the soil
water pressure head is described using the equation proposed by
Feddes et al. (1978):S = ˛Smax ,

(4)

(5)

where J is the total salt ﬂux density [g/(cm2 day)], Jcon is the convection dispersion ﬂux density [g/(cm2 day)], and Jdis is the dispersion
ﬂux density [g/(cm2 day)]. The convection–dispersion equation is in
HYDRUS-1D solved numerically for speciﬁed initial and boundary(e.g., groundwater salinity concentrations) conditions (Šimůnek
et al., 2008a).
The HYDRUS-1D model estimates crops evapotranspiration (ET)using the Penman–Montheith equation (Allen et al., 1998). Further
details of the numerical approach used in the model are given byŠimůnek et al. (2008a). In this study, the HYDRUS-1D model wasused to simulate water ﬂow and solute transport in the unsaturated
zone of the winter wheat ﬁelds with shallow and deep water tableconditions.
In order to obtain a quantitative assessment of simulation
results, root mean square error (RMSE), relative mean absolute
error (RMAE) and correlation coefﬁcient (r) were used to evaluate
numerical simulation precision:
1n

RMSE =r= (Ei − Mi )2

1⁄2
,

n
− Ei )
i=1 (Mi× 100%,
n
1
M
n
i=1 i

1

RMAE = n(1)

where  is the volumetric water content (cm3 /cm3 ), t represents
time (day), z is the vertical coordinate (positive upward) (cm), hdenotes the pressure head (cm), K is the unsaturated hydraulicconductivity (cm/day), and S is the soil water extraction rate byplant roots (cm3 /cm3 /day). The Richards’ equation is solved numerically for given initial and boundary condition and for speciﬁed soil
hydraulic properties, i.e., relations between soil hydraulic variables
, h, and K. The soil water retention curve is described in the modelusing the formulation of Van Genuchten (1980):

∂C
,
∂z



n
i=1

Mi − Mni=1

Mi − M2Ei − E

(8)

(9)



Ei − E

2 × 100%,(10)where Mi and Ei are the ith measured and simulated values, respectively, and n is the observation frequency.
The yield and water productivity of winter wheat were estimated using the results of numerical simulations. The yield ofwinter wheat was calculated using the FAO expression relating theyield response to ET:



1−

Ya
Yx





= ky 1 −

ETa
ETx



,

(6)

where Yx and Ya are the maximum and actual yields, ETx and ETa
are the maximum and actual cumulative evapotranspiration, andky is a yield responses factor, representing the effect of a reduction in evapotranspiration on yield losses. The relationship between
the yield of winter wheat and transpiration is taken from a studyof Sommer et al. (2013), who using the ﬁeld data proposed thefollowing relation for the study area:
Yb = 0.18272 × T + 0.40562,(7)

where T is crop transpiration (in mm). This relation (7) was used toverify winter wheat yields estimated using the expression (6).
2.2.1. Input parameters in HYDRUS-1D
Calculations for water ﬂow and solute transport, carried out toestimate evapotranspiration from shallow water table, covered asoil proﬁle 300 cm deep. The soil moisture content was determined
before sowing of winter wheat from the same soil horizons. Soil

A.Kh. Karimov et al. / Agricultural Water Management 131 (2014) 57–69

texture and soil bulk density were determined on soil samples collected in 2006 from the ﬁeld in the Kuva district from soil depthsof 0–0.3 m, 0.3–0.6 m, 0.6–0.9 m, 0.9–1.2 m, 1.2–1.8 m and 1.8–3 m.
The Kuva district is located in the Fergana province, Uzbekistan,on the left bank of the Syrdarya River. The soil throughout theentire soil proﬁle could be classiﬁed according to the USDA classiﬁcation as a silt loam. For the purpose of numerical modeling,
the soil proﬁle was divided into six numerical layers and grouped
into four soil horizons, determined by a soil description. The Van
Genuchten–Mualem model (Van Genuchten, 1980) with an airentry value of −2 cm was used to obtain a predictive equation for
the unsaturated hydraulic conductivity function.
An atmospheric boundary condition is applied at the soil surface for the winter wheat growing period starting on October 4
and ending on June 11 of the next year and for the land fallowing
period between winter wheat harvesting and its next sowing date.
The lower boundary condition is the time-variable pressure head. It
was assumed that farmers will continue their traditional practice ofsoil plowing after winter wheat harvesting to a depth of 20–22 cm.
The climate conditions, including daily maximum and minimum
air temperatures (◦ C), relative humidity (%), sunshine hours, rainfall (mm), and wind speed (km/day), were measured at the Fergana
weather station located at longitude of 71.75◦ , latitude of 40.38◦ ,and an elevation of 547 m asl. The canopy ground cover was usedas the basis to separate calculated evapotranspiration (ET) into soil
evaporation (E) and transpiration (T). The crop development is represented in the model by a daily crop height, a rooting depth, and asoil cover fraction (Allen et al., 1998). The maximum rooting depth
was 100 cm. The maximum rooting depth was less than the potential rooting depth, because the shallow water table restricted thegrowth of the roots (Raes et al., 2012). Wheat parameters used innumerical simulations were assumed to be conservative and applicable for a wide range of conditions. Simulations were carried out
for a period of 1717 days. Daily climate data for this time period
were obtained from the Fergana weather station from October 1991
to September 1996.
The root water uptake method proposed by Feddes et al. (1978)
was used to describe water and salinity stress conditions. An additive model was selected for the stress response function of the root
water uptake model. The water stress reduction term was parameterized using parameter values found by Wesseling et al. (1991):
P0 = 0, POpt = −1 cm, P2 H = −500 cm, P2 L = −900 cm, P3 = −16,000 cm,
r2 H = 0.5 cm/day, r2 L = 0.1 cm/day. A critical stress index for root
water uptake was taken as 1 and no root solute uptake was allowed.
Soil hydraulic parameters were determined by an inverse analysis of data from the lysimeter study carried out in the same area
earlier by Ganiev (1979). This study was a part of a comprehensive
assessment of the regional water budget conducted during thattime in Uzbekistan. The lysimeters of 1.44 m2 surface area were
packed with a monolithic silt loam soil. Cotton was sown in thelysimeters. The groundwater table in the lysimeters was kept at aconstant depth of 1.5, 2, 2.5, and 3 m below the soil surface. Soilwater content before and after the crop vegetation season, alongwith the climate and cotton phenology parameters, were inputs
to the model. Initial values of the Van Genuchten–Mualem parameters describing soil hydraulic properties of each soil layer weretaken from the HYDRUS-1D database for silt loam soils. The inverse
simulation period included 365 days from 10 April 1996 to 9 April
1997. Daily estimates of upward ﬂuxes from the groundwater tablewere entered into the model as a data for the inverse solution.
Simulated and measured values of upward ﬂuxes from the watertable are shown in Fig. 4. The RMSE and RMAE between measured
and simulated values were relatively low and equal to 0.0199% and1.48%, respectively. The correlation coefﬁcient between simulated
and measured values (r) was 0.9274. The above analysis indicatesthat simulation results agreed well with the measured data and61

Fig. 4. Comparison between simulated and measured upward ﬂuxes in the lysimeter study (Ganiev, 1979).

Table 1
Van Genuchten–Mualem parameters (Van Genuchten, 1980) to describe soil
hydraulic properties.
Parameter

Soil type r [cm3 /cm3 ] s [cm3 /cm3 ]˛ [1/cm]n [−]Ks [cm/d]l [−]Soil layer [m]0–0.6

0.6–1.2

1.2–1.8

1.8–3

Silt loam
0.038
0.407
0.02451.43
11.4
0.00055

Silt loam
0.001
0.250
0.0001
5.16
1.08
0.054

Silt loam
0.00120.301
0.00161.65
27.6
0.0098Silt loam
0.001
0.336
0.01571.73
4.48
0.0065

 r —Residual soil water content [cm3 /cm3 ],  s —saturated soil water content[cm3 /cm3 ],Ks —Saturated soil hydraulic conductivity [cm/day], ˛ [1/cm] and n [−] are shapeparameters,
l—pore-connectivity parameter [−].

the results from the lysimeter studies. The ﬁnal inversely estimatedvalues of the Van Genuchten–Mualem parameters describing soil
hydraulic properties of each soil layer are presented in Table 1.
Solute transport parameters were represented in the model by
the dispersivity, which was taken to be a one-tenth of the proﬁledepth (Beven, 1993; Cote et al., 2003), and the molecular diffusion coefﬁcient in free water, which was taken equal to 2 cm2 /day.
Salinity was simulated as a non-reactive solute assuming that there
was neither precipitation nor dissolution of salts from soil primarymaterial to the soil solution (Ramos et al., 2011). Absorption was
neglected in the simulations. The initial concentration of soluble
salts in the soil proﬁle was taken as 1.5 g/l. Total dissolved solids(TDS) in the irrigation water were 0.5 g/l and in the groundwater were 1.5 g/l. The solute transport upper and lower boundary
conditions were a concentration ﬂux and the groundwater salinity,
respectively. The concentration of soluble solids in the groundwater is relatively low because of the dominance of the lateral ﬂow
from the upper hydrogeologic zone B and ﬁltration losses fromdense canal systems. The presence of the lateral inﬂow permitted
specifying the constant salinity boundary condition at the bottomof the model.
2.2.2. Irrigation scenarios simulated
Five irrigation regimes (Table 2) were considered:(1) Full irrigation (FI): in addition to precipitation (16.6 cm/yr), twoirrigations with a total of 10.1 cm before the winter season andfour irrigations with a total of 27.8 cm after the winter season
were simulated, with a total water application M = 54.5 cm/yr.
The full irrigation scenario represented the irrigation regime
recommended for silt loam soils with the groundwater table

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A.Kh. Karimov et al. / Agricultural Water Management 131 (2014) 57–69

Table 2The irrigation regimes of winter wheat simulated in HYDRUS-1D to estimate upward ﬂuxes from shallow water table and the topsoil salinity.
Irrigation scenario

Precipitation (cm)Full irrigation (FI)Low deﬁcit irrigation (LDI)
Deﬁcit irrigation (DI)High deﬁcit irrigation
Rainfed winter wheat

16.6
16.6
16.6
16.6
16.6

Irrigation applications (cm)October

March

April

May

Total

10.1
10.1
5
5

5

13.9
5
5
5

8.9
7.9
7.9

37.9
23
17.9
10

at 3 m and deeper below the soil surface (Shreder et al., 1977).
Irrigation dates were speciﬁed using the Excel sheet developedby Allen et al. (1998) and using the depletion fraction of total
available soil water at 0.55;(2) Low deﬁcit irrigation (LDI): compared to scenario FI, only threeirrigations were considered after the winter season that wereadditionally further reduced by 10%, resulting in a total water
application M = 39.6 cm/yr;(3) Deﬁcit irrigation (DI): compared to scenario LDI, only
one irrigation was considered before the winter season,
M = 34.5 cm/yr;(4) High deﬁcit irrigation (HDI): only two short irrigation events,
one in October and one in April, 5 cm each, were considered
under this scenario, M = 26.6 cm/yr;(5) No irrigation: only precipitation, rainfed cultivation of winterwheat (RF), mean annual rainfall M = 16.6 cm/yr.
Variable daily pressure heads, reﬂecting the position of thegroundwater table, were speciﬁed at the bottom of the soil proﬁle. Four groundwater table depths of 3, 2.5, 2, and 1.5 m wereconsidered in the modeling study.
In the entire Fergana Valley, 70% of groundwater recharge isdue to losses from the dense system of canals and irrigated ﬁelds,
while about 12–14% is subsurface inﬂow from upper lands. In thehydrologic zone C, lateral inﬂow from the upper hydrological zone
and leakage from canals are estimated to be between 60% of total
groundwater recharge in dry years to 85% in wet years. The densityof the open drainage system within the hydrological zone C averages 59 m/ha and the close pipe system an additional 2 m/ha. The
drainage depth is from 2.5 to 3.5 m. In spite of the dense drainage
system, the water table in this area is less than 2 m below theground on 57% of the irrigated land. The groundwater table hasa minimum level in April, rises during the crop irrigation season,and then gradually falls in winter.
3. Results and discussion

Fig. 5. Groundwater contribution to crop evapotranspiration as fraction of ET(GWe.ET), as affected by a shallow groundwater table and an irrigation regime forwinter wheat on silt loam soils, Fergana Valley (average for 1992–1996).

and irrigated conditions. This ﬁnding concurs with the conclusionsof Ayars et al. (2006). Using the Meyer equation (Wu et al., 1999),
Ayars et al. (2006) found that the maximum upward ﬂuxes occur
when the root zone is dry and groundwater table is shallow andthe minimum upward ﬂuxes occur when the root zone is wet, witheither deep or shallow groundwater. Huo et al. (2011) came to similar conclusions based on their lysimeter studies of the water useof wheat.
Under conditions with a shallow groundwater table, farmers of
the Fergana Valley tend to apply less irrigation and thus to shift
the crop water supply from surface irrigation to groundwater inorder to meet the crop water demand. However, the results of thesimulations given in Fig. 6 indicate that under such sub-irrigation
conditions, an increasing fraction of total ET is non-productive
evaporation. Evaporation as a fraction of actual ETa (E.ETa ) increased
from 0.43 to 0.46 under rainfed conditions and from 0.44 to 0.50

3.1. Effects on the water use
Raising the water table from 3 to 1.5 m depth below thesoil surface increased crop evapotranspiration (ET) from 36 to
57.9 cm under rainfed conditions and from 58 to 66.5 cm under full
irrigation conditions. These ET values are close to those obtained inlysimeter studies conducted earlier by Ganiev (1979) in the study
area. Fractions of groundwater contributions (a net upward ﬂux)
to total ET (GWe.ET), as affected by a shallow water table and theirrigation schedule, are given in Fig. 5.
Fig. 5 shows that upward ﬂuxes increase when the water table israised and decrease when irrigation applications increase. Thus, fora shallow water table 1.5 m below the soil surface, the groundwater
evapotranspiration decreases from 62% to 9% of total evapotranspiration when natural rainfall (RF) is supplanted with a full irrigation
regime (FI). For a water table at a 3-m depth, the corresponding
decrease is from 17% to 0%. Contribution of groundwater to crop
evapotranspiration is negligible for a deep water table (e.g., 3 m)

Fig. 6. Evaporation as a fraction of ETa (E.ETa ) as affected by a water table depth
and irrigation regime for silt loam soils of the central part of the Fergana Valley(1992–1996).

A.Kh. Karimov et al. / Agricultural Water Management 131 (2014) 57–69

63

Fig. 7. Transpiration as a fraction of ETa (T.ETa ) as affected by a shallow water table
and irrigation regime (1992–1996).

under full irrigation when the water table was raised from 2 to
1.5 m below the soil surface. These numbers suggest that raising thewater table from 2.5 to 1.5 m produces additional non-productive
evaporation of 108 mm under rainfed conditions and 82 mm underfull irrigation. It is important to note, that the minimum value ofthe evaporation fraction was received for the HDI scenario, whenirrigation supplements precipitation (Fig. 6).
Under the same conditions, raising the water table from 3
to 1.5 m below the soil surface increased crop transpiration by
112 mm under rainfed conditions and by only 3 mm under full
irrigation (Fig. 7). However, transpiration as a fraction of ETa (T.ETa )is reduced from 0.57 to 0.54 under rainfed conditions and from 0.57
to 0.50 under full irrigation. The simulation results suggest that raising the water table does not necessarily produce signiﬁcant gains in
productive crop transpiration under full irrigation. Again, the highest transpiration fraction of ETa was estimated for the HDI scenario
when irrigation supplements precipitation.

Fig. 8. Temporal changes in soil salinity (a) in the topsoil (Ctop) and (b) averaged
over the root zone (Croot), as affected by a shallow water table (1.5, 2, 2.5, and 3 m)under rainfed conditions (1992–1996).

3.2. Effects on soil salinity and ecosystem health
An increased contribution of groundwater to soil surface evaporation produced an increase in the soil salinity (Fig. 8). Fig. 8 shows
simulated TSS under the rainfed conditions in the topsoil (Fig. 8a)and in the root zone (a soil layer of 0–100 cm) (Fig. 8b). After ﬁve
years of winter wheat cultivation under the rainfed conditions, thetop soil (0–30 cm soil layer) salinity increased from an initial valueof 1.5 g/l to 5.73, 8.51, 8.66, and 11.23 g/l when the water table was3, 2.5, 2, and 1.5 m below the soil surface, respectively. Similarly, theaverage root zone salinity increased from an initial value of 1.5 g/l
to 5.29, 8.01, 8.51 and 10.41 g/l when the water table was 3, 2.5,
2, and 1.5 m deep, respectively. The salinity at the bottom of thevadose zone is not changed under rainfed conditions.
Under the deﬁcit irrigation (DI) scenario the increases in estimated salinities were smaller than under the scenario of a rainfed
cultivation of winter wheat (Fig. 9). Higher concentrations of salts
in the topsoil as compared to those averaged over the root zone still
indicate the salinity buildup in the soil proﬁle, i.e., salts moving withthe upward ﬂuxes are accumulating in the topsoil. More salts enterthe vadose zone under shallow groundwater conditions, and consequently more salts accumulate in the topsoil—with implications
for crop yield and ecosystem health (Kijne, 2006; Khan and Hanjra,
2008).
Although the full irrigation regimes reduced accumulation ofsalts in the soil proﬁle due to salt ﬂushing (Kijne, 2001), the contribution of shallow groundwater to soil salinization was still obvious(Fig. 10). Under a full irrigation scenario, salinity in the topsoil,in the root zone, and at the bottom of the vadose zone, is lessdependent on the depth of the water table. However, there are

Fig. 9. Temporal changes in soil salinity (a) in the topsoil (Ctop) and (b) averaged
over the root zone (Croot), as affected by a shallow water table (1.5, 2, 2.5, and 3 m)under deﬁcit irrigation conditions (1992–1996).

64

A.Kh. Karimov et al. / Agricultural Water Management 131 (2014) 57–69

salinity levels. Various deﬁcit irrigation scenarios produce intermediate salinity levels between the rainfed farming and full irrigation.
3.4. Toward improved water and land management practices

Fig. 10. Temporal changes in soil salinity (a) in the topsoil (Ctop) and (b) averaged
over the root zone (Croot,), as affected by a shallow water table (1.5, 2, 2.5, and 3 m)under full irrigation (1992–1996).

still peaks in soil salinity under shallow water table conditions
between individual irrigation events. The topsoil salinity increased
from 1.5 to 3.96 g/l when a shallow water table was 1.5 m below thesoil surface. The increase in salinity levels for other groundwatertable depths was much smaller. The average root zone salinity
increased from an initial value of 1.5 to 2.29 g/l and 3.59 g/l forwater table depths of 3 and 1.5 m, respectively. These estimatesindicate a potential stabilization of the topsoil salinity over time
under deep groundwater conditions. The salinity at the bottom of
the vadose zone is not changed signiﬁcantly under full irrigation
conditions.
3.3. Effects on wheat yield and water productivity
Table 3 summarizes simulated results for different groundwater table depths (D) and for different irrigation scenarios in terms of
upward ﬂux from the groundwater table (GWe), transpiration (T),evaporation (E), evapotranspiration (ET), and crop yield (Y). Evaporation and transpiration ﬂuxes are also expressed as a fraction of theactual evapotranspiration (E.ETa and T.ETa , respectively). Variations
in crop transpiration and soil salinity are reﬂected in estimatedyields of winter wheat (Table 3). The RMSE between values of winterwheat yields estimated using relations (6) and (7) was 0.2838.
These estimates of crop yield are based on the assumption that
other inputs to crop production, such as soil tillage, fertilizers, andpest and weed control remain the same. The results presented inTable 3 show that raising the water table from 3 to 1.5 m below thesoil surface produces a 31% increase in the yield of wheat under
the rainfed conditions and no yield increase for a full irrigation scenario. This means that there are no signiﬁcant gains from having ashallow water table under a full irrigation scenario, while a shallow
water table under the rainfed conditions may cause soil salinizationand may require extensive leaching and drainage to maintain low

One of the reasons for high evaporation losses under shallow
water conditions is fallowing of the land from June 11 till October
4 after harvesting of winter wheat and before sowing of the next
year’s crop (Table 4). It must be noted that since the ﬁelds are
not mulched after the harvest, evaporation losses are signiﬁcantand that has practical implications for residual moisture and water
management.
The results of the modeling study show that under full irrigation
conditions, even a shallow groundwater does not contribute tocrop evapotranspiration. Under low deﬁcit irrigation, net upward
ﬂuxes are smaller during a crop vegetation period as compared toa land fallowed period. As the magnitude of the deﬁcit during thecrop vegetation season increases, so does the contribution of thegroundwater to crop evapotranspiration.
For groundwater 1.5 m deep below the soil surface, evaporation from June 10 to October 1 is estimated to be 47% and 45%
of total evaporation under rainfed and full irrigation conditions,
respectively. For conditions with a deep water table (3 m), evaporation after winter wheat harvesting is estimated to be 23% and27%, respectively. Raising the water table from 3 to 1.5 m produces
an increase in evaporation of 1.9 cm during the vegetation season and 8.8 cm after wheat harvesting—that is, greater losses due
to land fallowing practice. For a full irrigation scenario, there isno increase in evaporation during the vegetation season and 8.1cm increase after wheat harvesting. Therefore, lowering the watertable could reduce evaporation losses by 10.7 cm under rainfed
conditions and by 8.1 cm under full irrigation, which will signiﬁcantly contribute to preventing salinity build-up in the topsoil. Thisimplies that improved water and land management practices holdthe key to water savings and environmental sustainability in the
Fergana Valley.
3.5. Unlocking the potential of groundwater for irrigation in the
Fergana Valley
Improved water and land management practices are the main
pathway for unlocking the potential of groundwater for irrigationin the Fergana Valley. For instance, replacement of alfalfa by winter wheat reduces the irrigation demand at least by 200 mm/ha(Shreder et al., 1977), or 486 Mm3 /yr for the entire Fergana valley. However, due to the presence of a shallow water table on
200,000 ha of the irrigated land, a shift to cultivation of winterwheat will increase non-productive evaporation after wheat harvesting by 40–45 mm/ha. Temporarily, at early stages, the yield ofwinter wheat can reach a maximum level but the wheat yield will
be sub-optimal and the yield ceiling will be reached sooner. However, a gradual increase of soil salinity will require an increase in theamount of water for salts leaching. In general, at the initial stage,
rainfall and irrigation will control much of the salt accumulation.
At later stages, under shallow water conditions, the sum of crop
evapotranspiration and water required for leaching of soluble solids
from the root zone of winter wheat may become comparable to theamount of water initially used for evapotranspiration of alfalfa, thus
potentially offsetting a large part of the reduction in the irrigationdeﬁcit and water savings. For example, under full irrigation, evapotranspiration from an alfalfa ﬁeld with a groundwater table 2 m
deep was estimated to be 905 mm, while for a winter wheat/fallow
system 665 mm. The amount of water required for leaching of soluble solids, according to Shreder et al. (1977), is in the range of
200–300 mm/yr.

A.Kh. Karimov et al. / Agricultural Water Management 131 (2014) 57–69

65

Table 3
Water productivity and winter wheat yield as affected by a shallow water table for the silt loam soils of the Fergana Valley (averaged for 1992–1996).
P + I (cm/yr)

D (m)GWe (cm/yr)

T (cm/yr)

E (cm/yr)ETa (cm/yr)

E.ETa (−)

T.ETa (−)

Ya (t/ha)Yb (t/ha)

16.57
(RF)

1.5
2
2.5
3
1.5
2
2.5
3
1.5
2
2.5
3
1.5
2
2.5
3
1.5
2
2.5
3

35.7
26.5
18.1
6.0
29.1
21.7
14.0
2.8
25.1
18.9
12.0
1.3
20.1
13.8
7.0
−3.4
6.1
2.0
−2.5
−9.6

31.6
27.6
24.2
20.4
34.0
31.3
28.1
24.6
34.3
32.9
30.6
27.7
34.2
32.7
30.5
27.7
33.5
33.4
33.4
33.2

26.4
20.9
18.0
15.6
26.5
21.6
19.0
17.1
30.6
25.5
22.9
20.6
30.6
25.5
22.9
20.8
33.0
28.6
26.4
24.8

57.9
48.5
42.2
36.0
60.5
52.8
47.2
41.7
64.9
58.4
53.6
48.3
64.8
58.3
53.4
48.4
66.5
62.1
59.8
58.0

0.46
0.43
0.43
0.43
0.44
0.41
0.40
0.41
0.47
0.44
0.43
0.43
0.47
0.44
0.43
0.43
0.50
0.46
0.44
0.43

0.54
0.57
0.57
0.57
0.56
0.59
0.60
0.59
0.53
0.56
0.57
0.57
0.53
0.56
0.57
0.57
0.50
0.54
0.56
0.57

4.9
4.3
3.9
3.4
5.2
4.8
4.5
4.0
5.5
5.3
5.0
4.6
5.5
5.3
5.0
4.6
5.6
5.6
5.6
5.6

5.4
4.6
4.0
3.3
5.8
5.3
4.7
4.1
5.9
5.6
5.2
4.7
5.8
5.6
5.2
4.7
5.7
5.7
5.7
5.7

26.02
(HDI)

34.65
(DI)

39.62
(LDI)

54.51
(FI)

D = Water table depth (m), P + I = precipitation and irrigation amounts(cm), GWe—upward water ﬂow from the groundwater (cm), T = estimated actual transpiration (cm),E = estimated actual evaporation (cm), ETa = estimated actual evapotranspiration (cm), E.ETa —evaporation as a fraction of ETa (−), T.ETa —transpiration as a fraction of ETa ,Y—yield of wheat (t/ha).

Table 4
Evaporation from the soil surface during the vegetative season of winter wheat and after its harvesting, during the land fallowing season, as affected by a shallow water table
for the silt loam soils of the Fergana Valley (averaged for 1992–1996).
P + I (cm/year)

D (m)Net upward ﬂux
Vegetation
(cm)

16.57
(RF)

26.02
(HDI)

34.65
(DI)

39.62
(LDI)

54.54
(FI)

1.5
2
2.5
3
1.5
2
2.5
3
1.5
2
2.5
3
1.5
2
2.5
3
1.5
2
2.5
3

25.0
19.8
12.8
−1.2
18.5
15.0
8.7
−4.4
15.0
12.9
7.8
−5.0
9.9
7.9
2.8
−9.7
−3.4
−3.3
−5.7
−13.4

Evaporation
Fallow
(cm)

Total
(cm)

Vegetation(cm)

Fallow
(cm)

Total
(cm)

10.7
6.7
5.3
7.3
10.6
6.7
5.3
7.2
10.1
5.9
4.1
6.3
10.1
5.9
4.1
6.3
9.5
5.3
3.1
3.7

35.7
26.5
18.1
6.0
29.1
21.7
14.0
2.8
25.1
18.9
12.0
1.3
20.1
13.8
7.0
−3.4
6.1
2.0
−2.5
−9.6

13.9
13.1
12.6
12.0
14.0
13.8
13.6
13.4
16.8
16.1
15.8
15.4
16.8
16.1
15.8
15.6
18.2
18.2
18.2
18.1

12.5
7.8
5.5
3.7
12.6
7.8
5.5
3.7
13.8
9.4
7.1
5.1
13.8
9.4
7.1
5.1
14.8
10.4
8.2
6.7

26.4
20.9
18.0
15.6
26.5
21.6
19.0
17.1
30.6
25.5
22.9
20.6
30.6
25.5
22.9
20.8
33.0
28.6
26.4
24.8

D = Water table depth (m), P + I = precipitation and irrigation amounts (cm),Non-productive evaporation losses from the wheat grown area
could be reduced by lowering the water table, and unlocking the
productive potential of groundwater. Two alternative approaches
could be suggested to achieve this. First, one can increase theintensity of drainage in the hydrogeological Zone C but thisentails signiﬁcant investment costs for the drainage infrastructure.
Although this approach may lead to managing salinity levels in thecrop root zone and improving the health and resilience of the agroecosystem, it may also generate return ﬂow to the river during thewinter season, when the downstream reservoirs are almost full.
This measure would require additional storage capacities downstream on the Syrdarya River, and would further contribute toincreasing the area with shallow water tables. These tradeoffs andassociated cost-return matrix requires further analysis. The second approach is to shift from canal irrigation to conjunctive useof groundwater and canal water. Extracting groundwater for crop

irrigation would lower its levels and reduce evaporative losses,
salinity buildups in the topsoil, and saline return ﬂows from thestudy area to the Syrdarya River. Extracted groundwater could be
used in conjunction with canal water for irrigation of food crops,
including double cropping. The water supply would become more
uniform and reliable along the long canals, which cross the valley from east to west. Winter ﬂows of rivers of the Fergana Valley
could be used for groundwater recharge. There would be no needfor additional storage capacities downstream, but this requires economic and policy incentives for promoting the conjunctive use ofgroundwater and canal water for irrigation in the Fergana Valley.
3.6. Managing salinity for protecting ecosystem health
Our modeling results and ﬁeld observations show that salinity buildup in the root zone and salinization of agricultural land

66

A.Kh. Karimov et al. / Agricultural Water Management 131 (2014) 57–69

Fig. 11. Changes in areas with shallow groundwater, moderately and highly saline
soils, and the water use over time (1975–2007) in the Fergana province.

with time may become a signiﬁcant issue in the Fergana Valley, if
no urgent action is taken to lower the shallow water table. Since
a combination of over-irrigation in the zone C and lateral subsurface ﬂow are the major source of shallow groundwater recharge,
the shallow water table could be lowered by using groundwater
for irrigation and other purposes and by improving irrigation technologies to arrest the salinity issue in the Fergana Valley. At present,
about 55% of the irrigated land in the Valley is prone to salinity,
including about 72,000 ha of land that are moderately and highly
saline in the hydrological zone C. While irrigation application rates
per ha have been reduced with the policy change that replaced
alfalfa with winter wheat, areas with shallow groundwater andwith moderately and highly saline soils have not, which remains
a signiﬁcant issue (Fig. 11). Furthermore, the spatial data show
large salinity problems in many countries in Central Asia, includingin the Fergana valley (Table 5). Salinity poses huge challenges toenvironmental sustainability and ecosystem health, as well as sustainability of food production, in large irrigation systems across Asia
(Khan and Hanjra, 2008). For instance, China, India, Iran, Pakistan
and Central Asian states are among the countries where a hugeshare of the productive irrigated cropland is affected by salinity. Soilsalinity reduces water availability and crop yields, and threatens
rural industries and livelihoods of millions (Postel, 1999; Khan and
Hanjra, 2008). Irrigation induced soil salinity reduces agricultural
production, threatens food security and imposes other economic,
social and environmental costs. The socioeconomic impacts ofwater logging and salinity include the losses in income, lost returns
on public investments, risks to public health due to saline watersupplies, saline return ﬂows to downstream areas, and damages tonatural and built infrastructure.
Negative impacts of increased soil salinity on ecosystems
include a loss of biodiversity, limitations on crop choices, anincrease in invasive species, a loss of pollinator species, riversystem health linkages, and ecological impacts. For instance,
Qalandarov (2007) carried out a study under saline conditions in
the Mirzachul lowlands, downstream of the Syrdarya River basin,
next to the Fergana Valley. He observed a low microbiota activity
Table 5Land salinization in Central Asia (Bucknall et al., 2003).
Settings

Kyrgyz Republic
Tajikistan
Kazakhstan
Turkmenistan
Uzbekistan
Central Asia

Irrigated area (ha)1,077,100
719,200
2,313,000
1,744,100
4,280,600
10,134,000

Area affected by salinization(ha)(%) of irrigated area

124,300
115,000>763,290
1,672,592
2,140,550
4,815,732

11.5
16.0
>33.0
95.9
50.1
47.5

in the saline soils of Uzbekistan and found low populations ofammoniﬁcators, oligonitrophils, and actinomycetes, that all play animportant role in the soil ecosystem sustainability and resilience.
In other settings, salinity limits crop varieties suitable for irrigatedsoils and affects crop development and yield (Katerji et al., 2003).
It also affects river, stream, and wetland ecosystems (Hart et al.,1990), impacts of climate change on river ecosystems (Suen andLai, 2013), river diversions and ecology (Das et al., 2012), riverenvironmental ﬂow requirements (Sun et al., 2009), tolerance ofmacro-invertebrate and the ecosystem protection trigger values(Dunlop et al., 2008), sustainability of agricultural landscapes, carbon sequestration and biodiversity values (George et al., 2012),
vegetation–groundwater interactions (Humphries et al., 2011),
pesticide toxicity, ecosystem functions and ecosystem services(Schafer et al., 2012), bioavailability of Cu and Zn and other essential
plant micronutrients (Speelmans et al., 2010), and causes changes
in grain ultrastructure, amylase, protein and amino acid proﬁlesunder water, salinity, and combined stresses (Ahmed et al., 2013).
These myriad ecosystem health linkages do imply that under shallow groundwater conditions salinity has implications for river basin
health and ecosystems and thus imposes carrying capacity constrains in terms of water-savings and unlocking the potential ofgroundwater development for irrigation.
Managing salinity has implications for water security as well as
for the sustainability of food production and terrestrial and aquatic
ecosystems and vital services they provide to the mankind (Tilman
et al., 2002). Long-term data on the concentration of total dissolved
solids (TDS—an indicator of salinity and river system pollution normally discussed only for freshwater systems, as salinity comprises
some of the ions constituting the deﬁnition of TDS) show that (a)the salinity has been on the rise over time (1931–2012) in the
Amudarya River and (b) the rise in TDS concentrations was relatively low in upper reaches, higher in the midstream, and highest
in the downstream reaches of the river (Table 6). While the data for
the Syrdarya River show similar temporal trends of salinity patterns
across the upper, middle, and lower reaches of the river system,
the data also show that salinity is relatively higher, especially inthe mid and downstream reaches of the Syrdarya River comparedto those of the Amudarya River. Overall, these data show risingsalinity and poor health of the river system, which has implications for ecosystem health and environmental water security of theregion.
A key dimension of water security is environmental water security, i.e., the status of the water-related environment of river basinsthat can be assessed using the river heath index. The River Basin
Health Index (ADB, 2013) is a composite of four indicators and theirsub-indices that include: watershed disturbance (cropland, livestock, wetlands), pollution (salinization, NPK, Hg, TDS, acidiﬁcation,etc.), water resources development (dams, relative water use compared to supply, agricultural sector water stress, and changes down
streams), and biotic factors (non-native species, catch pressure andaquaculture). Data on environmental water security in selectedbasins and countries show that in Central Asia, agricultural development and salinization have already had major impacts and posea major stress on the region’s rivers and ecosystems (Table 7). For
instance, with the development of water resources and irrigationin the region, vast tracts of underdeveloped land were converted
into productive agricultural ecosystems, leading to the drying upof the Aral Sea. The vast irrigation development and over irrigation
practices have also led to extensive land degradation in the areas
irrigated with waters from Amudarya and Syrdarya rivers. According to recent estimates, nearly 50% of the irrigated areas in Central
Asia are salt affected, water logged, or both (Qadir et al., 2009). The
deterioration and poor health of the rivers and ecosystems potentially threatens the livelihoods of tens of millions who depend onthem for food security and incomes.

A.Kh. Karimov et al. / Agricultural Water Management 131 (2014) 57–69

67

Table 6
Temporal and spatial change of TDS of the Amudarya River and the Syrdarya River (modiﬁed from Abdullaev et al. (2007)).
Amudarya River

1932–50
1951–60
1961–70
1971–80
1981–90
1991–99
2000–2012

Syrdarya River

Upstream

Midstream

Downstream

Upstream

Midstream

Downstream

0.379
0.395
0.402
0.409
0.424
0.424

0.496–0.513
0.514–0.524
0.576
0.59–0.755
0.572–1.12
0.572–1.122

0.513
0.524
0.641
0.755
1.196
1.196
1.113

0.293
0.302
0.307
0.321
0.346
0.359

0.425
0.584
1.034
1.203
1.252
1.265

0.485
0.698
1.137
1.282
1.8
1.829
1.102

Table 7
Environmental water security in selected river basins and countries (ADB, 2013).
Subregion (river
basin or country)

Watershed disturbance(% of basin)

Pollution (% ofbasin)

Resource development(% of basin)

Biotic factors (%of basin)River healthindicator

River healthassessment

Central Asia (Syr Darya)
Central Asia (Aral Sea)
Esat Asia (Yellow River)Southeast Asia (Mekong)Southeast Asia (Vietnam)

0
4.2
0
21
38.8

31.6
6.5
29.7
3.6
26.7

68.4
74.1
70.3
63.8
25.3

0
15,1
0
11.6
4.6

0.30
0.28
0.19
0.27
0.27

Poor
Poor
Bad
Poor
Poor

Improved management of land and water resources for enhancing food security and livelihoods and protecting ecosystems
requires economic incentives and agriculture policies that canaddress the salinity issue head-on. This justiﬁes public funding
for policies for motivating farmers to adopt better water and land
management practices and more efﬁcient irrigation technologies.
This can enhance the beneﬁts to farmers by lowering the excess
irrigation water applications to crops and reducing salinity, a consequent reduction in salt buildup and rise of ground-water table,
and reducing negative impacts on ecosystem health. The suite ofpolicy incentives and interventions include: better crop choices,
better irrigation practices, practicing deﬁcit irrigation while considering the depth of ground water table, a conjunctive use of canaland groundwater (as shown by this analysis), an improved water
use efﬁciency (Molden et al., 2010), better irrigation technologies,
and integrated agro forestry and cropping systems.
4. Conclusion
The results of the study suggest that contributions from shallow
groundwater to crop evapotranspiration for winter wheat cultivated areas highly depend on irrigation regimes and land and water
management practices. Under high deﬁcit irrigation and rainfed
conditions in loam soils, upward ﬂuxes from shallow groundwater
exceed 60% of total crop evapotranspiration. Under full irrigation,
net upward ﬂuxes are small even when the water table is only at
1.5 m depths below the soil surface. The evaporation fraction of
the crop evapotranspiration is minimal and the transpiration fraction maximal for high deﬁcit irrigation under shallow and deep
water table conditions, respectively. However, under shallow waterconditions, the beneﬁts of deﬁcit irrigation during early stages ofcrop growth may be followed by crop yield losses during laterstages of crop growth, due to the rapid increase in topsoil androot zone salinity. Similar phenomena were observed in late 1980s
in irrigated lowlands of Central Asia, where the shift from fullto deﬁcit irrigation under shallow water conditions caused salinity buildup and high economic losses to farming communities.
Increasing the share of winter wheat on the irrigated lands since
the mid 1990s accelerated these processes. Under shallow waterconditions, evaporation from lands fallowed after winter wheat
harvesting represents up to 45–47% of total evaporation losses.
Excessive evaporation losses under shallow groundwater conditions become a source of continuous salinity buildup in the crop
root zone.

The results of this study suggest that cultivation of low waterconsumptive crops under shallow groundwater conditions does notproduce expected water savings. Under shallow water conditions,
reduced irrigation applications may be followed by an increase
in upward ﬂuxes to the topsoil. The numerical model indicatesthat for winter wheat, evaporation as a fraction of crop evapotranspiration increases with raising of the water table, whiletranspiration decreases. Evaporation from fallowed lands after
winter wheat harvesting may represent up to 35–39% of total evaporation losses. Evaporation losses increase when the water table
is raised and irrigation applications increased. Excessive evaporation losses under shallow groundwater conditions become a sourceof salinity buildup in the crop root zone. Evapotranspiration is
identiﬁed as a key driver of groundwater salinity, and Humphries
et al. (2011) support this ﬁnding. The same amount of water supplied earlier for irrigation of high water-consumptive crops may
have to be applied at later stages for irrigation of low waterdemanding food crops and leaching of the progressively salinizedsoils.
The results of this study suggest two alternative approaches that
could be proposed to policy-makers to lower the shallow watertable and unlock its potential for irrigation in the Valley. The ﬁrst
approach would increase the intensity of drainage, which would
allow maintaining salinity levels in the crop root zone, but it would
generate return ﬂows to the river in the winter season, when thereservoirs are full in the Syrdarya River midstream. The second
approach is the shift from canal irrigation to conjunctive groundwater and canal water use. The increased groundwater extraction
will supply the irrigation demand of an intensive cropping systemin the Fergana Valley, while saved surface water could be delivered to other users, midstream of the Syrdarya River. To preventthe environmental consequences of intensive farming practices andprotecting ecosystem health, a wide scale adoption of water saving
technologies has to be put in place. This is another important policy
instrument to produce more food crops using available water andis a subject for future research.

Acknowledgments
The authors would like to express their thanks to the OPEC Fundfor International Development for ﬁnancing this work.
This work has been undertaken as part of the CGIAR Research
Program on Water, Land and Ecosystems (WLE).

68

A.Kh. Karimov et al. / Agricultural Water Management 131 (2014) 57–69

References
Abdullaev, U., Khasankhanova, G., Myagkov, S., Khamzina, T., Agalceva, N.,
Fazilova, M., Lysenko, P., Merkushkin, A., Abdullaev, Sh., Voronov, A., Manuyk,
N., Nechaeva, G., 2007. Water – Critical Resource for Uzbekistan’s Future.
United Nations Development Programme (UNDP), Tashkent, Uzebkistan,
pp. 24.
ADB, 2013. Asian Water Development Outlook 2013. Measuring Water Security in
Asia and the Paciﬁc. Asian Development Bank, Manilla, the Philippines.
Ahmed, I.M., Cao, F., Han, Y., Nadira, U.A., Zhang, G., Wu, F., 2013. Differential changes
in grain ultrastructure, amylase, protein and amino acid proﬁles between
Tibetan wild and cultivated barleys under drought and salinity alone and combined stress. Food Chemistry 141 (3), 2743–2750.
Allen, R.G., Pereira, L.C., Raes, D., Smith, M., 1998. Crop evapotranspiration. Guidelines for computing crop water requirements. In: FAO Irrigation and Drainage
paper 56. FAO, Rome, pp. 1–300.
Awan, U.K., Ibrakhimov, M., Tischbein, B., Kamalov, P., Martius, C., Lamers, J.P.A.,
2011. Improving irrigation water operation in the lower reaches of the
Amu Darya River—current status and suggestions. Irrigation and Drainage 60,
600–612.
Ayars, J.E., Christen, E.W., Soppe, R.W., Meyer, W.S., 2006. The resource potential of
in-situ shallow ground water use in irrigated agriculture: a review. Irrigation
Science 24, 147–160, http://dx.doi.org/10.1007/s00271-005-0003-y.
Babajimopoulos, C., Panoras, A., Georgoussis, H., Arampatzisb, G., Hatzigiannakisb, E., Papamichail, D., 2007. Contribution to irrigation from shallow
groundwater table under ﬁeld conditions. Agricultural Water Management 92,
205–210.
Bah, A.R., Kravchuk, O., Kirchhof, G., 2009. Sensitivity of drainage to rainfall, vegetation and soil characteristics. Computers and Electronics in Agriculture.
Beven, K., 1993. Prophecy, reality and uncertainty in distributed hydrological modeling. Advances in Water Resources 16 (1), 41–51.
Borisov, V.A., 1990. Groundwater Resources and Their use in Uzbekistan (in Russian).
Fan, Tashkent, Uzbekistan.
Boudreau, J., Caron, J., Elrick, D., Fortin, J., Gailichand, J., 2009. Solute transport in
sub-irrigated peat-based growing media. Canadian Journal of Soil Science 89,
301–313.
Bucknall, J., Klytchnikova, I., Lampietti, J., Lundell, M., Scatasta, M., Thurman, M.,
2003. Irrigation in Central Asia: Social, Eco-nomic and Environmental Considerations, World Bank Report, 104 pp.
Cai, X., McKinney, D.C., Rosegrant, M.W., 2002. Sustainability analysis for
irrigation water management in the Aral Sea region. Agricultural Systems 76,
1–24.
Cao, Q.H., Gong, Y.S., 2003. Simulation and analysis of water balance and nitrogen leaching using HYDRUS-1D under winter wheat crop. Plant Nutrition andFertilizer Science 9, 139L 145.
Cote, C.M., Bristow, K.L., Charlesworth, P.B., Cook, F.J., Thorburn, P.J., 2003. Analysis
of soil wetting and solute transport in subsurface trickle irrigation. Irrigation
Science 22, 143–156.
Das, A., Justic, D., Inoue, M., Hoda, A., Huang, H., Park, D., 2012. Impacts of Mississippi
River diversions on salinity gradients in a deltaic Louisiana estuary: ecological and management implications. Estuarine, Coastal and Shelf Science 111 (0),17–26.
De Vos, J.A., Hesterberg, D., Raats, P.A.C., 2000. Nitrate leaching in a tile-drained silt
loam soil. Soil Science Society of America Journal 64, 517L 527.
Dunlop, J.E., Horrigan, N., McGregor, G., Kefford, B.J., Choy, S., Prasad, R., 2008.
Effect of spatial variation on salinity tolerance of macroinvertebrates in Eastern
Australia and implications for ecosystem protection trigger values. Environmental Pollution 151 (3), 621–630.
Endo, A., Mishima, S., Kohyama, K., 2009. Modeling nitrate leaching on a cropped
Andosol. Nutrient Cycling in Agroecosystems 85, 41–61.
Ergashev, Sh., 2011. Technical Report of the Naryn Karadarya Basin Irrigation System
Administration (NKBISA). NKBISA, Andijan, pp. 160.
George, S.J., Harper, R.J., Hobbs, R.J., Tibbett, M., 2012. A sustainable agriculturallandscape for Australia: a review of interlacing carbon sequestration, biodiversity and salinity management in agroforestry systems. Agriculture, Ecosystems& Environment 163 (0), 28–36.
Gribb, M.M., Forkutsa, I., Hansen, A., Chandler, D.G., McNamara, J.P., 2009. The effectof various soil hydraulic property estimates on soil moisture simulations. Vadose
Zone Journal 8, 321–331.
Feddes, R.A., Kowalik, P.J., Zaradny, H., 1978. Simulation of Field Water use and Crop
yield. John Wiley & Sons, New York.
Forkutsa, I., Sommer, R., Shirokova, Y.I., Lamers, J.P., Kienzler, K., Tischbein, B., Martius, C., Vlek, P.L.G., 2009. Modeling irrigated cotton with shallow groundwaterin the Aral Sea Basin of Uzbekistan: I. Water dynamics. Irrigation Science 27,
331–346, http://dx.doi.org/10.1007/s00271-009-0148-1.
Ganiev, K.G., 1979. Evaporation and Inﬁltration Recharge of Groundwater (in Russian). Fan, Tashkent, Uzbekistan.
Hanjra, M.A., Qureshi, M.E., 2010. Global water crisis and future food security in an
era of climate change. Food Policy 35 (2), 365–377.
Hao, F.H., Ou, Y.W., Yue, Y., Yang, F.Z., Li, P., 2008a. Analysis of water cycle characteristics and soil water movement in the agricultural irrigation area in Inner
Mongolia. Acta Scientiae Circunstantiae 28, 825–831.
Hao, F.H., Sun, W., Zeng, A.Y., Li, P., Zhang, J.X., Yue, Y., 2008b. Simulation of
N transfer under different irrigation and fertilization scenarios in the Hetao
irrigation area using HYDRUS-1D model. Acta Scientiae Circunstantiae 28,
853–858.

Hart, B.T., Bailey, P., Edwards, R., Hortle, K., James, K., McMahon, A., Meredith, C.,
Swadling, K., 1990. Effects of salinity on river, stream and wetland ecosystems
in Victoria, Australia. Water Research 24 (9), 1103–1117.
Heatwole, K.K., McCray, J.E., 2007. Modeling potential vadose-zone transport ofnitrogen from onsite wastewater systems at the development scale. Journal ofContaminant Hydrology 91, 184–201.
Hernandez, T.X., 2001. Rainfall-runoff modeling in humid shallow water table environments. In: M.Sc. Thesis. University of South Florida, Tampa, FL.
Humphries, M.S., Kindness, A., Ellery, W.N., Hughes, J.C., Bond, J.K., Barnes, K.B., 2011.
Vegetation inﬂuences on groundwater salinity and chemical heterogeneity in a
freshwater, recharge ﬂoodplain wetland, South Africa. Journal of Hydrology 411(1–2), 130–139.
Huo, Z., Feng, Sh., Huang, G., Zheng, Y., Wang, Y., Guo, P., 2011. Effect of groundwaterlevel depth and irrigation amount on water ﬂuxes at the groundwater table anwater use of wheat. Irrigation and Drainage, http://dx.doi.org/10.1002/ird.685.
Kahlown, M.A., Ashraf, M., Zia-ul-Haq, M., 2005. Effect of shallow groundwater tableon crop water requirement and crop yields. Agricultural Water Management 76,
24–35.
Karimov, A., Molden, D., Khamzina, T., Platonov, A., Ivanov, Y., 2012. A water accounting procedure to determine the water savings potential of the Fergana Valley.
Agricultural Water Management 108, 61–72.
Katerji, N., van Hoorn, J.W., Hamdy, A., Mastrorilli, M., 2003. Salinity effect on cropdevelopment and yield, analysis of salt tolerance according to several classiﬁcation methods. Agricultural Water Management 62 (1), 37–66.
Khan, S., Hanjra, M.A., 2008. Sustainable land and water management policies andpractices: a pathway to environmental sustainability in large irrigation systems.
Land Degradation and Development 19 (3), 469–487.
Kijne, J.W., 2001. Lessons learned from the change from supply to demand water
management in irrigated agriculture: a case study from Pakistan. Water Policy
3, 109–123.
Kijne, J.W., 2006. Salinization in irrigated agriculture in Pakistan: mistaken predictions. Water Policy 8, 325–338.
Liu, Q.C., Xie, S.C., 1998. A study on ﬁeld soil water balance for summer corn in north
China plain. Journal of Hydraulic Engineering 1, 62L 68.
Liu, T., Luo, Y., 2011. Effects of shallow water tables on the water use and yield of winter wheat (Triticum aestivum) under rainfed condition. AJCS 5 (13), 1692–1697.
Meng, J.L., Dong, X.G., Zhou, J.L., Li, J.L., 2004. Application of HYDRUS model to studyof relation between irrigation and soil salinity in the arid area. Journal of Xinjiang
Agricultural University 27, 45–49.
Mirzaev, S.Sh., 1974. Groundwater Storages of Uzbekistan (In Russian). Fan,
Tashkent, Uzbekistan.
Molden, D., 1997. Accounting for Water Use and Productivity. SWIM Paper 1. International Water Management Institute, Sri Lanka.
Molden, D., Sakthivadivel, R., 1999. Water accounting to access use and productivity of water. International Journal of Water Resources Development 15 (1, 2),
55–71.
Molden, D., Oweis, T., Steduto, P., Bindraban, P., Hanjra, M.A., Kijne, J., 2010. Improving agricultural water productivity: between optimism. Agricultural Water
Management 97 (4), 528–535.
Mualem, Y., 1976. A new model for predicting the hydraulic conductivity of unsaturated porous media. Water Resources Research 12, 513–522.
Murgai, R., 2001. The green revolution and the productivity paradox: evidence fromthe Indian Punjab. Agricultural Economics 25, 199–209.
Nandalal, W., Hipel, W., 2007. Strategic decision support for resolving conﬂict overwater sharing among countries along the Syrdarya River in the Aral Sea Basin.
Journal of Water Resources Planning and Management 133, 289–299.
Postel, S.L., 1999. Pillar of Sand: Can the Irrigation Miracle Last? W.W. Norton, NewYork.
Qalandarov, R., 2007. Saline water irrigation and mulching effects on cotton production and soil quality in Syrdarya province of Uzbekistan. In: Thesis Dissertation.
Wageningen University and Tashkent Institute of Irrigation and Melioration,
Uzbekistan, pp. 80.
Qadir, M., Noble, A.D., Qureshi, A.S., Gupta, R.K., Yuldashev, T., Karimov, A., 2009.
Salt-induced land and water degradation in the Aral Sea basin: a challenge tosustainable agriculture in Central Asia. In: Natural Resources Forum 33., pp.
134–149.
Raes, D., Steduto, P., Hsiao, T.C., Fereres, E., 2012. AquaCrop, Version 4. In: Reference
Manual., pp. 130 (Chapter 3).
Ramos, T.B., Šimůnek, J., Gonçalves, M.C., Martins, J.C., Prazeres, A., Castanheira,N.L., Pereira, L.S., 2011. Field evaluation of a multicomponent solute transportmodel in soils irrigated with saline waters. Journal of Hydrology 407 (1–4),
129–144.
Sanchez, C.A., Zerihun, N.I., Warrick, A.W., Furman, A., 2003. Efﬁcient Surface
Fertigation of High Value Horticulture Crops. Western Nutrient Management
Conference, Salt Lake City, UT, pp. 77–82.
Schafer, R.B., Bundschuh, M., Rouch, D.A., Szöcs, E., von der Ohe, P.C., Pettigrove, V.,
Schulz, R., Nugegoda, D., Kefford, B.J., 2012. Effects of pesticide toxicity, salinity
and other environmental variables on selected ecosystem functions in streams
and the relevance for ecosystem services. Science of the Total Environment 415(0), 69–78.
Shouse, P.J., Ayars, E., Šimůnek, J., 2011. Simulating root uptake from a shallow saline
groundwater resource. Agricultural Water Management 98, 784–790.
Shreder, V.R., Vasiliev, I.K., Trunova, T.A., 1977. Hydromodul zoning for calculationof the irrigation rates for cotton under arid environments. In: Proceedings ofthe Middle Asia Research Institute of Irrigation, Tashkent, Middle Asia ResearchInstitute of Irrigation, pp. 28–41, N 8.

A.Kh. Karimov et al. / Agricultural Water Management 131 (2014) 57–69
Šimůnek, J., Šejna, M., Saito, H., Sakai, M., van Genuchten, M.Th., 2008a. The HYDRUS1D Software Package for Simulating the Movement of Water, Heat, and Multiple
Solutes in Variably Saturated Media, Version 4.0, HYDRUS Software Series 3.
Department of Environmental Sciences, University of California Riverside, Riverside, CA, USA, pp. 315.
Šimůnek, J., van Genuchten, M.Th., Šejna, M., 2008b. Development and applicationsof the HYDRUS and STANMOD software packages, and related codes. Vadose
Zone Journal 7 (2), 587–600, http://dx.doi.org/10.2136/VZJ2007.0077, Special
Issue Vadose Zone Modeling.
Šimůnek, J., Köhne, J.M., Kodešova, R., Šejna, M., 2008c. Simulating nonequilibrium
movement of water, solutes and particles using HYDRUS—a review of recent
applications. Soil and Water Research 3, S42–S51 (Special Issue 1).
Singh, R., van Dam, J.C., Jhorar, R.K., 2003. Water and salt balances at farmer ﬁelds.
In: van Dam, J.C., Malik, R.S. (Eds.), Water Productivity of Irrigated Crops in Sirsa
district, India, Integration of Remote Sensing, Crop and Soil Models and Geographical Information Systems. Wageningen University, Department of Water
Resources, Wageningen, pp. 41–58, Chapter 4.
Smedema, L.K., Shiati, K., 2002. Irrigation and salinity: a perspective review ofthe salinity hazards of irrigation development in the arid zone. Irrigation andDrainage Systems 16 (2), 161–174.
Soppe, R.W.O., Ayars, J.E., 2003. Characterizing groundwater use by safﬂower using
lysimeters. Agricultural Water Management 60, 59–71.
Speelmans, M., Lock, K., Vanthuyne, D.R.J., Hendrickx, F., Du Laing, G., Tack, F.M.G.,
Janssen, C.R., 2010. Hydrological regime and salinity alter the bioavailability of
Cu and Zn in wetlands. Environmental Pollution 158 (5), 1870–1875.
Spoor, M., 1998. The Aral Sea Basin crisis: transition and environment in former
Soviet Central Asia. Development and Change 29, 409–435.
Sommer, R., Glazirina, M., Yuldashev, T., Otarov, A., Ibraeva, M., Martynova, L.,
Bekenov, M., Kholov, B., Ibragimov, N., Kobilov, R., Karaev, S., Sultonov, M.,
Khasanova, F., Esanbekov, M., Mavlyanov, D., Isaev, S., Abdurahimov, S., Ikramov,
R., Shezdyukova, L., De Pauw, E., 2013. Impact of climate change on wheat productivity in Central Asia. Agriculture, Ecosystems & Environment 178, 78–99.
Suen, J.-P., Lai, H.-N., 2013. A salinity projection model for determining impacts ofclimate change on river ecosystems in Taiwan. Journal of Hydrology 493 (0),124–131.

69

Sun, T., Yang, Z.F., Shen, Z.Y., Zhao, R., 2009. Environmental ﬂows for the Yangtze
Estuary based on salinity objectives. Communications in Nonlinear Science andNumerical Simulation 14 (3), 959–971.
Supiev, M., Ganiev, A., 2005. Technical Report. The Hydrogeology melioration expedition of the Syrdarya Sokh Basin Irrigation System Administration, Fergana, pp.
109.
Talipov, G.A., 1992. Land Resources of Uzbekistan and Problems of Their Rational
Use. Uzbek Research Institute of Cotton Growing, Tashkent, pp. 232.
Tilman, D., Cassman, K.G., Matson, P.A., Naylor, R., Polasky, S., 2002. Agricultural
sustainability and intensive production practices’. Nature 418, 671–677.
Van Genuchten, M.Th., 1980. A closed-form equation for predicting the hydraulicconductivity of unsaturated soils. Soil Science Society of America Journal 44 (5),892–898.
Wang, S.X., Zhou, F., Yu Dong, X.G., 2005. Application of HYDRUS-1D to evaluating
soil water resource. soil and water conservation 12, 36L 38.
Wesseling, J.G., Elbers, J.A., Kabat, P., Van Den Broek, B.J., Internal note 1991. SWATRE: Instructions for Input. Winane String Centre, International Waterlogging
and Salinity Research Institute, Wageningen, The Netherlands, Lahore, Pakistan,
pp. 29.
Wu, Q., Christen, E.W., Enever, D., 1999. Basinman—a water balance model
for farms with subsurface pipe drainage and on-farm evaporation basins.
In: Technical Report 1/99. CSIRO Land and Water, Grifﬁth, NSW, Australia,
http://www.clw.csiro.au/publications/technical99/tr199.pdf.
Xu, L.G., Yang, J.S., Zhang, Q., Liu, G.M., 2005. Salt-water transport in unsaturated
soils under crop planting: dynamics and numerical simulations. Pedosphere 15,
634–640.
Yang, J., Wan, S., Deng, W., Zhang, G., 2007. Water ﬂuxes at a ﬂuctuating groundwater table and groundwater contributions to wheat water use
in the lower Yellow River ﬂood plain, China. Hydrological Processes 21,
717–724.
Zhang, L., Dawes, W.R., Slavich, P.G., Meyer, W.S., Thorburn, P.J., Smith, D.J., Walker,
G.R., 1999. Growth and groundwater uptake response of Lucerne to changes
in groundwater levels and salinity: lysimeter isotope and modeling studies.
Agricultural Water Management 39, 265–282.