SCIENCE CHINA
Earth Sciences
• RESEARCH PAPER •
September 2010 Vol.53 No.9: 1358–1364
doi: 10.1007/s11430-010-4028-6
Water consumption in artificial desert oasis based on net primary
productivity
ZHAO WenZhi1,2*, NIU ZuiRong1, CHANG XueLi3 & LI ShouBo1,2
1
Laboratory of Ecohydrology and Integrated River Basin Science, Cold and Arid Regions Environmental and Engineering Research Institute,
Chinese Academy of Sciences, Lanzhou 730000, China;
2
Linze Inland River Basin Research Station, Chinese Ecosystem Research Network, Lanzhou 730000, China;
3
Geography and Resource Management College, Ludong University, Yantai 264025, China
Received March 15, 2009; August 4, 2009; published online July 16, 2010
Analysis of the water consumption is the basis for water allocation in oasis. However, the method of estimating oasis water
consumption remains a great challenge. Based on net primary productivity (NPP) and the transpiration coefficient, a vegetation
water consumption model was developed to estimate the water consumption in desert oasis in ERDAS environment. Our results demonstrated that the ecosystem in the middle reaches of the Heihe oasis consumed water of 18.41×108–21.9×108 m3 for
irrigation. Without taking precipitation into account, the water consumption in farmland accounted for 77.1%–77.8% (or about
13.97×108–16.84×108 m3) of the oasis vegetation water consumption and in the farmland protection system accounting for
22%. The growing period precipitation in desert environments is about 7.02×108 m3, and the total annual precipitation is about
8.29×108 m3. The modeled water consumption of desert vegetation, however, is about 4.57×108 m3, equivalent to only 65% of
the growing period precipitation or 55% of the total annual precipitation. The modeled value equals to the cumulative precipitation of greater than 5 mm, which is defined as the effective precipitation in arid desert.
net primary productivity (NPP), transpiration coefficient, water consumption, oasis
Citation:
Zhao W Z, Niu Z R, Chang X L, et al. Water consumption in artificial desert oasis based on net primary productivity. Sci China Earth Sci, 2010, 53:
1358–1364, doi: 10.1007/s11430-010-4028-6
Water use in Oasis includes not only the water used for agricultural production and environmental sustainment, but
also the water provided for industrial and living. In the arid
oasis of China, primary producers account for more than
80% of water consumption. Therefore, analysis of vegetation water consumption is the basis for allocation of water
resources in arid oasis [1]. Evapotranspiration is the main
process of vegetation water consumption. Many studies on
evapotranspiration have been carried out. For example,
Brunel et al. [2] used eddy correlation technique and energy
balance method to examine the evapotranspiration process
*Corresponding author (email: [email protected])
© Science China Press and Springer-Verlag Berlin Heidelberg 2010
in Syrian oasis. Han et al. [3] investigated the annual
evaporation law in a typical oasis in the Tarim Basin based
on a coupled water-energy balance model with extended
Budyko hypothesis. Hu et al. [4] studied the evapotranspiration process in the atmospheric surface layer in the Heihe
River Basin with the coupled soil-vegetation-atmosphere
water evaporation model. Chen et al. [5] modeled the
evapotranspiration process using a distributed hydrological
model by using DEM, remote sensing, and hydro-meteorological information. Ji et al. used Penman-Monteith formula
and improved Shuttleworth-Wallace model to simulate
evaporation and transpiration in desert oasis [6]. Guo [7]
used the Priestley-Taylor formula and NOVA AVHRR image to calculate and verify the evapotranspiration in the
earth.scichina.com
ZHAO WenZhi, et al.
Sci China Earth Sci
Heihe River Basin.
In addition to the above studies and simulations of atmospheric physics mechanisms, there are also methods of
water consumption estimation by using theprimary productivity of vegetation and the transpiration coefficient. Transpiration coefficient is defined as the amount of water in
weight or volume unit that is required for the production of
a unit of plant dry weight. In general, about 300–600 g of
water is required for plants to produce one gram of dry
matter. Postel et al. [8] used transpiration coefficient to estimate the evapotranspiration of global terrestrial ecosystems in 1996. Zhao et al. [9] studied the vegetation ecological water requirements in the Ejina Oasis by using a similar
method. Compared with the natural oasis, artificial desert
oasis has more vegetation types, and as a result, estimation
of the water consumption of the artificial desert oasis is
more complicated. There are many methods for evapotranspiration estimation, including experimental and theoretical
equation [10], statistical model based on experimental data
[11], GIS-based model with experimental data and theoretical analysis based on the spectral characteristics, and GIS
and experimental data [12, 13]. All of these studies contained two common elements: one is the spatial extent of
vegetation types; the other is the transpiration coefficient of
vegetation types. The most accurate and advanced way to
get the spatial extent of vegetation types is land-use and
land-cover interpretation using remote sensing. Various
methods have been developed to get the transpiration coefficient, such as the methods using vegetation types [12, 14],
soil water balance [11], and phreatic water evaporation [9,
15], and every method has its own merits and pitfalls.
Common methods that have been used to analyze and
evaluate water consumption in arid plain oasis mainly include the instream-and-outstream methods, the water balance methods, the dissipative hydrological models, and the
remote sensing models [1]. Uncertainties, however, exist in
the estimation of water consumption by using instreamand-outstream methods and water balance methods because
of the circulating utilization of water in desert oasis region.
The combined method of NPP and transpiration coefficient
can effectively remedy the defect of uncertainty, because it
has fixed data sources, the calculation procedure is repeatable, and the results can be used to validate and verify the
other physical mechanism models. However, there is still
few reports on the calculation of water consumption by using a combined method of NPP and transpiration coefficient
in artificial desert oasis.
In this study, TM images were used as the sources of information. The NPP was calculated base on the relationship
between NDVI and NPP, and then we estimated vegetation
water consumption using transpiration coefficient of every
vegetation type. The results were interpreted with the same
spatial resolution as the TM image (30 m). The heterogeneities of the NPP spatial distribution of the same vegetation
types were fully stressed to improve accuracy of the estima-
September (2010) Vol.53 No.9
1359
tion.
1
Description of study area
The study area is located in the middle reaches of Heihe
River with the area of 10.753×103 km2, including Linze,
Gaotai, and Ganzhou (Figure 1). Climate in this region is
temperate arid with cold and dry winters and warm and wet
summers. The average annual precipitation over the study
area is 117 mm with high inter-annual variation; about 65%
of it falls between July and September. The average annual
evaporation is 2390 mm. The average annual temperature is
7.6°C with the highest temperature in summer is 39.1°C and
the lowest temperature in winter is −27.3°C. In 2006, the
annual precipitation is 98 mm in Linze, 95 mm in Gaotai,
and 121 mm in Ganzhou.
2
2.1
Study methods
Remote sensing interpretation
According to the TM images (Orbital Nos. 133-33 and
133-34, Figure 2(a)) taken on 11 September, 2006, the study
area was divided into 9 land-cover types, namely, arbor
forest, sparse forest and shrubs, farmland, wetland, desert
grassland, water body, gobi desert, bare land, and residential
area. Geometric correction of ETM images was performed
in the ERDAS IMAGINE environment (using the Albers
conical Equal Area Krasovsky projection method). Land use
map (Figure 2(c)) was completed by computer visual interpretation in the accuracy level of 1:100000.
Figure 1
Location of the study area.
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ZHAO WenZhi, et al.
Sci China Earth Sci
September (2010) Vol.53 No.9
Figure 2 TM image, NDVI and land-cover map of the study area. (a) TM image; (b) NDVI; (c) land-cover map.
2.2
Calculation of NDVI
Since the visible light (RED) channel and near-infrared light
(NIR) channel of TM scanning radiometer are very sensitive
to plant leaves and their growing period, the normalized
difference vegetation index (NDVI) derived from RED and
NIR is the best choice in reflecting and defining the relative
abundances and activities of vegetation [16]. Because the
relationship between NDVI and NPP, as well as the relationship between NDVI and LAI, was widely used to estimate regional vegetation productivities [16, 17], it was used
in this study to calculate the regional vegetation productivity of the study area based on the relationship between
NDVI and NPP. The calculation formula is NDVI=(λNIR−
λRED)/(λNIR+λRED). According to this formula, the
NDVI values can be calculated with the corrected composite images through ERDAS software (Figure 2(b)).
2.3
Measurement of the vegetation spectrum
In the study area, the prominent vegetation types are farmland, protection forest, desert vegetation, and wetland. The
farmland is dominated by corn and wheat, with a few other
crops. The protection forest is composed of Populus gansuensis, Tamarix spp., and Haloxylon ammodendron, which
are distributed around the farmland or between the desert
and oasis. The desert vegetation is distributed on the fringe
of oasis, while the wetland is distributed along the Heihe
River in the central of the oasis. We used the ASD FieldSpec Portable Handheld Spectroradiometer to measure the
spectrum of corn, wheat, desert vegetation, and wetland in
July 2008. To be convenient in the measurement of vegetation spectrum, the TM images used in this study were taken
in September when the biomass is at its highest level for
most vegetation types. Significant errors, however, could
exist in the spectrum estimation because the harvest season
of wheat had been closed in this time period. Fortunately
due to the relatively far smaller coverage of wheat field, and
the fact that the reaped fields were usually not reseeded in
the study area, wheat field can be easily differentiated from
the other vegetation types in the NDVI images (as the particularly low amongst the high value regions). Areas in
farmland with NDVI less than 0.637 were defined as wheat
fields and were assigned the average spectrum. The interpreted result showed that the area of wheat was about
175.38 km2 in 2008, which was only about 8.81% of farmland. The data statistics suggest that the NPP was proportional linearly to the NDVI, and the significance was more
than 0.05 (Figure 3, Table 1).
Spectrum of vegetation types were measured during the
period of July 20, 2008 to July 28, 2008, and almost all the
measurements were performed in Zhangye, Linze, and
Gaotai, except the spectral measurement of wheat in Minle
where wheat was still at the end of filling stage due to the
altitude effect (wheat in other regions has been reaped in
July). Measuring method: 5 times on every vegetation type
plot between 10 am to 4 pm, and took the average spectrum
as the result. Aboveground and underground biomasses
have been also determined by dry-weight method. Based on
the measurement of the vegetation type spectrum, aboveground and underground biomass, regression relationships
have been established between the spectrum and NPPs.
Table 1
Linear regression equations between NDVI and Bim
Correlation
F
P
coefficient
Corn
0.855
48.869 <0.01
Bim=5113.701NDVI−2645.286
Wheat Bim=1788.966NDVI+559.681
0.809
43.579 <0.01
0.826
75.248 <0.01
Wetland Bim=965.269NDVI−136.754
Desert Bim=1730.176NDVI−200.126
0.626
6.442 <0.05
Vegetation
2.4
Linear regression equation
Determination of transpiration coefficient
There are two important parts in the water consumption
calculation by using 3S technology. One is spatial extent of
vegetation types, and another is definition of the transpiration coefficient and the variance of water consumption in
different regions. The first one has been worked out in
ZHAO WenZhi, et al.
Figure 3
Sci China Earth Sci
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September (2010) Vol.53 No.9
Relationship between NDVI and aboveground biomass (Bim).
many other results, whereas the variance of water consumption for the same type of vegetation is difficult to determine,
especially in arid desert oasis. In this study, water consumption is calculated in every grid with the regression equations
in Table 1 and the equation below:
desert vegetation 300 (dominated by Tamarix spp.), protection forest (dominated by Populus gansuensis) 513, wetland
(dominated by Phragmites communis and Searia viridis,
which has a similar transpiration coefficient of 300 as
Searia viridis, Sorghum sudanemse and corn).
n
VEWR = Ki × ∑ Bim × Wue × A,
i =1
where VEWR is vegetation water consumption (g), Ki is the
ratio of NPP and aboveground biomass, which is about
1.6933:1 for herbs in the study area; Wue is transpiration
coefficient; A is the area of every grid, which is 34 m×34 m
in this study; and n is the quantity of grids.
Bim was calculated using the equations in Table 1. Wue
was derived by referring to the earlier research results in
arid region. Usually, about 300–600 g of water is required
for plants to produce one gram of dry matter. However, different plants species have different water requirement
amounts, for example, the transpiration coefficient of Searia
viridis is 285, Sorghum sudanemse 304, corn 349, wheat
557, Brassica campestris 714 and Medicago sativa 844 [18].
Huang gave out the transpiration coefficients of 138–344
for some arid desert plants, such as Haloxylon ammodendron, Caragana Korshinskii, Artemisia salsoloides, Caligonum mongolicum, Hedysarum scoparium and Tamarix
spp.; the corresponding value for Elaeagnus angustifolia is
383 and Populus gansuensis 513 [19]. Of course, the
amount of water requirement is also related to other ecological factors, such as solar radiation intensity, temperature,
atmospheric, soil regimes, plant development stage, etc. By
referring to the published results and comprehensively considering the influencing factors, the transpiration coefficients in this study were defined as: corn 349, wheat 557,
2.5
Build the water consumption model
The water consumption model was built in Model Maker in
ERDAS 9.1. This program module has its own algorithmic
language and program library, information of water consumption (or NPP) in per unit area can be easily expressed
as gray values by using user-defined syntax and conditional
statement. The calculating procedure is shown in Figure 4.
2.6
The water consumption at regional scale
The water consumption at regional scale was calculated by
using the following equations:
n
VSWV = (1 / ki ) × ∑ (VEWR − ERi ),
i =1
RVEWR = VSWV + ERi ,
where VSWV and RVEWR are irrigation water use and consumption at regional scale, ERi is effective rainfall, n is
number of vegetation type, and ki is water use efficiency of
irrigation. The value of k depends on the irrigation times in
the area. The water use efficiency of farmland irrigation is
about 0.42–0.52 in growing periods according to the monitoring data from the Linze Station. The water use efficiency
of protection forest irrigation was determined by experts
marking methods, and the value is 0.42–0.60 (Table 2),
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Figure 4
Table 2
ZHAO WenZhi, et al.
Sci China Earth Sci
Calculating procedure of the water consumption model.
Water use efficiency of irrigation
Sparse forest
Vegetation
Farmland Arbor forest
and shrubs
type
Water efficiency
1.00
0.42–0.52 0.50–0.60
of irrigation
Wetland
1.00
suggesting that 40%–58% of irrigation water is lost in the
form of soil water evaporation and deep percolation.
3
Results
As can be seen in Table 3, farmland takes the greatest part
of the water consumption (about 51.4%) in the study area,
followed by desert vegetation (28.7%) and arbor forest
(12.4%). Across all the vegetation types, desert grassland
and Gobi desert depend on natural rainfall to sustain,
whereas the others mainly depend on river or irrigation. In
2006, the water consumption we calculated is 4.57×108 m3
in desert vegetation, while the total precipitation is 8.29×108
and 7.02×108 m3 in growing period (Tables 4, 5). These results suggest that the water consumption is less than the
precipitation in desert vegetation. The total precipitation of
the other vegetation types is 2.50×108 m3 and in growing
period is 2.18×108 m3 (Figure 5).
According to the Tables 2, 3, 5 and those equations, the
water consumption we calculated is about 18.41×108–
Figure 5
September (2010) Vol.53 No.9
Precipitation of the study area.
21.92×108 m3 (Table 6), which have taken the loss of irrigation and ineffective rainfall into account. In the water consumption, farmland is taking a part of 77.1%–77.8%, followed by arbor forest (16.1%–16.4%).
4
Discussion and conclusions
The relationship between NPP and evapotranspiration is
useful to calculate the water consumption of ecosystems.
Postel et al. [8] have used this method to estimate the
evapotranspiration of global terrestrial ecosystems in 1996.
Zhao et al. [9] used the similar method to study the vegetation ecological water requirement in Ejina oasis. The core
of this method is to estimate the transpiration coefficient
and the distribution of vegetation as veracious as possible.
The transpiration coefficient of global terrestrial ecosystems is estimated as 500 by Postel. Based on the plant
physiology research in arid regions, the transpiration coefficient is estimated to be 300–500 in our study, depending
on the vegetation types. Besides, the NDVI and NPP are
calculated at a grid scale in order to improve the precision
of the results.
Because of the circulating utilization of water in desert
oasis region, the water consumption is uncertain using water
balance method. Our results can verify the results of the
water balance method. Chen et al. [5] have modeled the
hydrological processes of the middle reaches in the Heihe
River using a distributed hydrology model based on observation data. The result shows that the precipitation is 193
mm, while the evapotranspiration is 294.5 mm. Multiplying
the area of their study area, the rainfall water is about
34.5×108 m3, while the evapotranspiration is 52×108 m3.
Therefore, the required irrigation water is about 18.13×108
m3. It is slightly less than our estimation of 18.41×108–
21.92×108 m3. This difference may be caused by circulating
utilization of water. According to the statistics from the
Zhangye Water Authority, the actual irrigation water was
ZHAO WenZhi, et al.
Sci China Earth Sci
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September (2010) Vol.53 No.9
Table 3 Water consumption based on NPP
Vegetation type
Farmland
Arbor forest
Sparse forest and shrubs
Wetland
Desert
Total
Water consumption (×108 m3)
8.18
1.97
0.74
0.45
4.57
15.91
Percent (%)
51.41
12.38
4.66
2.83
28.72
100.00
Table 4
The area of every land-cover type in 2006 (km2)
Land-cover type
Farmland
Arbor forest
Sparse forest and
shrubs
Desert grassland
Wetland
Water body
Residential area
Gobi desert
Bare land
Total
Table 5
Ganzhou
1061.23
28.69
Linze
457.50
4.44
Gaotai
472.01
20.84
Total
1990.74
53.97
39.93
25.49
21.70
87.12
675.74
9.35
8.98
147.25
1597.84
96.40
3665.40
189.19
43.55
15.77
36.99
1893.38
12.95
2679.25
525.61
112.51
52.48
46.11
3124.86
32.63
4408.74
1390.53
165.41
77.23
230.35
6616.08
141.98
10753.39
Precipitation of every vegetation type (×108 m3)
Period
Ganzhou
Growing
1.17
period
Farmland
Whole year 1.29
Growing
0.03
period
Arbor forest
Whole year 0.031
Growing
0.04
Sparse forest &
period
shrubs
Whole year 0.05
Growing
0.01
period
Wetland
Whole year 0.01
Vegetation type
Linze
Gaotai
Total
0.39
0.36
1.91
0.45
0.45
2.19
0.004
0.02
0.05
0.004
0.02
0.06
0.02
0.02
0.08
0.03
0.02
0.10
0.04
0.09
0.13
0.04
0.11
0.16
Table 6 The water consumption which have taken the loss of irrigation and ineffective rainfall into account (×108 m3)
Vegetation type
Effectively irrigation
Arbor forest
Maximum
16.84
3.89
Minimum
13.97
3.25
1.91
0.05
Effectively precipitation
Water consumption
Farmland
Maximum
18.75
3.94
Minimum
15.78
3.30
about 22.35×108 m3 in 2006, suggesting that 0.43×108–
3.94×108 m3 of the irrigated water was probably discharged
into the river or groundwater [20].
The result from Chen et al. [5] shows that almost all the
precipitation in the desert around oasis is consumed by
evapotranspiration. However, in our research, the water
consumed by desert vegetation is only 55% of the precipitation. Earlier research suggests that most rainfall in this area
is less than 5 mm, about 46.2% of the total precipitation
[21]. Generally, small rainfall less than 5 mm was considered ineffective because it can easily be intercepted and
evaporated, and thus unproductive for vegetation. Base on
that, the effective rainfall (53.8% of total precipitation) is
almost consumed by desert vegetation. Our results also
show that, without taking precipitation into account, the
water consumption for farmlands is about 77.1%–77.8% of
the total water consumed in desert oasis, which is about
13.97×108–16.84×108 m3; the other 22% water is used by
the farmland protection system.
In conclusion, the results of water consumption are in
line with the report from Zhangye Water Authority, and are
slightly larger than the result of water balance method. The
Sparse forest and shrubs
Wetland
0.74
0.45
0.08
0.13
0.91
0.48
Total
21.92
18.41
2.17
24.08
20.47
vegetation water consumption model based on NPP, which
is estimated using the relationship established by vegetation
spectrum with NDVI, is feasible in artificial desert oasis.
This work was supported by National Basic Research Program of China
(Grant No. 2009CB421302), Key Project of Knowledge Innovation Program of Chinese Academy of Sciences (Grant No. KZCX2-XB2-04-01), and
National Natural Science Foundation of China (Grant No. 40930634).
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