WATER RESOURCES RESEARCH, VOL. 49, 2205–2212, doi:10.1002/wrcr.20202, 2013
Analysis of changing pan evaporation in the arid region of
Northwest China
Zhi Li,1,2 Yaning Chen,1 Yanjun Shen,3 Yongbo Liu,4 and Shuhua Zhang1,2
Received 7 August 2012; revised 10 March 2013; accepted 19 March 2013; published 26 April 2013.
[1] Decreases in pan evaporation (Ep) over the last decades have been reported in many
regions of the world. In this study, we investigated Ep dynamics in the hyper-arid region of
China during the period 1958–2010 using a generic physical model based on long-term
meteorological data collected at 81 ground-based meteorological stations. We also
quantified the contribution of climatic factors to the Ep change using partial derivatives. We
found that Ep in the region exhibited an obvious decreasing trend until early 1990s (1993),
at a rate of 6.0 mm yr2. However, the downward trend reversed in 1993, and the rate of
increase after that was 10.7 mm yr2. We also assessed the sensitivity of rates of
evaporative demand to changes in aerodynamic and radiative components, and found that
pan evaporation could be mostly attributed to changes in the aerodynamic component, with
some regional contributions from solar irradiance. Observed near-surface wind speed is the
primary contributor to the decline of pan evaporation during 1958–1993, while wind speed
(WS) and vapor pressure deficit (VPD) were both major contributors to the increase of pan
evaporation after 1993.
Citation: Li, Z., Y. Chen, Y. Shen, Y. Liu, and S. Zhang (2013), Analysis of changing pan evaporation in the arid region of Northwest
China, Water Resour. Res., 49, 2205–2212, doi:10.1002/wrcr.20202.
1.
Introduction
[2] Evapotranspiration is important in water and energy
cycles, playing a key role in the global and regional hydrological processes under certain climate and landscape conditions. Since evapotranspiration is difficult to measure
directly, traditionally measurements of evaporation from
pans have been used to represent the evaporative demand
of the atmosphere, and often represent potential evaporation. Over the past half century, despite the rise of air temperature, decrease of pan or potential evaporation has been
found common worldwide [Peterson et al., 1995; Lawrimore and Peterson, 2000; Hupet and Vanclooster, 2001;
Moonen et al., 2002; Burn and Hesch, 2007], especially in
the Northern Hemisphere [Brutsaert and Parlange, 1998;
Stanhill and Cohen, 2001; Roderick and Farquhar, 2002;
Roderick et al., 2009a, 2009b; Gong et al., 2006; Liu and
Zhang, 2011]. Scholars have put forward various interpretations to explain this ‘‘paradox’’. Brutsaert and Parlange
1
State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute
of Ecology and Geography, Chinese Academy of Sciences, Urumqi,
China.
2
University of Chinese Academy of Sciences, Beijing, China.
3
Key Laboratory of Agricultural Water Resources, Center for Agricultural Resources Research, Chinese Academy of Sciences, Shijiazhuang
050021, China.
4
Department of Geography, University of Guelph, Ontario, Canada.
Corresponding author: Y. Chen, State Key Laboratory of Desert and
Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese
Academy of Sciences, No. 818 South Beijing Rd., Urumqi, Xinjiang
830011, China. ([email protected])
©2013. American Geophysical Union. All Rights Reserved.
0043-1397/13/10.1002/wrcr.20202
[1998] pointed out that the observed decline did not necessarily mean a declining actual evapotranspiration; in nonhumid environments, decreasing pan evaporation may actually
be a strong indication of increasing terrestrial evaporation.
McVicar et al. [2012a] suggested that the evaporative process is primarily driven by radiative and aerodynamic components, and thus while increase in air temperature in
isolation may cause increases of pan evaporation, changes of
other meteorological variables may have outweighed the
effect of temperature.
[3] Water is critical the energy and mass circulations in
the arid region of Northwest China, and is sensitive to
global climate change. Much effort, based on empirical meteorological data, has been made to investigate the dynamics of pan evaporation in China [Liu et al., 2004; Zhang
et al., 2007; Zeng et al., 2007; Shen et al., 2010]. Liu et al.
[2006] found close relationships between pan evaporation
were diurnal temperature range and wind speed in North
China; Liu et al. [2010] found decreases in diurnal temperature range, sunshine duration, and wind speed were the
main attributing factors in the pan evaporation declines for
China as a whole. However, much effort, based on empirical
meteorological data ended in 2001, those studies focused on
the decline trend of pan evaporation directly, while analysis
on the abrupt change in Ep was not available, moreover, most
previous employed statistical analysis, such as correlation
and stepwise regression, to identify the controlling climatic
variables, few studies have employed physically based theories. Most previous such studies estimated potential evaporation using the Penman-Monteith recommended by the FAO
[Allen et al., 1998]. However, Ep is different from open water
evaporation because the wall of the pan intercepts additional
radiation and enhances heat exchange [Linacre, 1994], and
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LI ET AL.: CHANGE OF PAN EVAPORATION IN THE NORTHWEST CHINA
therefore a physical model should be more accurate in estimating Ep and is thus preferable. In that direction, Linacre
[1994] developed a simplified Penman equation, referred to
as the PenPan equation; Rotstayn et al. [2006] coupled the
aerodynamic component developed by Thom et al. [1981]
with the radiative component of Linacre [1994], and develop
a PenPan model based on the mass and energy balance of the
pan. A limitation of those studies is that they focused on the
Class A pan with diameter of 1.21 m and depth of 0.254 m.
However, the evaporative pan widely used in China has a diameter of 0.2 m and depth of 0.1 m. In this study, we modified the PenPan model to suit it to the Chinese micropan.
[4] We tried to use this model to attribute the changes in
overall trends of pan evaporation to the changes in the
underlying physical climate variables in Northwest China.
2.
Materials and Methods
2.1. Study Area
[5] The Arid Region of Northwest China is located in the
hinterland of the Eurasia continent, with an extend approximately bounded by 35 –50 N and 73 –106 E. It consists of
the entire Xinjiang Uyghur Autonomous, Hexi Corridor in
Gansu Province, and west part of the Helan Mountains in
Inner Mongolia, accounting for 24.5% of the land area of
China. The terrain of the region is featured by huge mountain ranges and vast basins or valleys. Xinjiang, which is in
the west part of the region, is defined by three mountain
ranges from north to south, including the Altay Mountain,
the Tianshan Mountain, and the Kunlun Mountain; the
Tarim River, located in southern Xinjiang with a drainage
area of 1.02106 km2, is the largest inland river in China.
In the eastern part of the region, a lowland area, Hexi Corridor, lies on the north of the Qilian Mountain (Figure 1).
[6] This region has an extremely sparse population distribution, under-developing economy, and fragile ecological
environment, mainly due to its arid climate [Ma et al., 2005,
Figure 1.
Chen et al., 2006]. The climate is dominated by continental
arid conditions because all the oceans are remote. This
region is primarily influenced by Westerly Circulation and
less influenced by East Asian Monsoon [Liu et al., 2010].
Average annual precipitation ranges from 100 mm in the
west to 400 mm in the east [Chen et al., 2012]. At the center
of desert, annual precipitation may be less than 50 mm.
2.2. Data
[7] The data used in this study were collected from 81
ground-based meteorological stations in the study region
operated by the China Meteorological Administration.
These stations have complete records of almost all climatic
factors from 1958 to 2010, including monthly observations
of temperature (minimum, maximum and average) at 2 m
height, wind speed measured at 10 m height, precipitation,
relative humidity, sunshine duration, and average vapor
pressure. Seven stations have complete observations of
monthly direct radiation and solar diffuse radiation. Among
the seven stations, three are in the southern Xinjiang, three
in the northern Xinjiang, and one in the Hexi Corridor. The
observed pan evaporation data at these 81 stations cover
the period 1958–2001. The pans are made of copper with a
diameter of 0.2 m and depth of 0.1 m. They are positioned
on a frame of 0.7 m above the ground and have a rim to
keep birds away from drinking. Compared with Class A
pan, the D20 pan used in China is smaller and holds less
water [Yang and Yang, 2011].
2.3 Methodology
2.3.1. Estimation of Pan Evaporation Using the
PenPan Model
[8] Linacre [1994] developed a simplified Penman equation, referred to as the PenPan equation, and obtained good
agreement between measured and calculated monthly pan
evaporations for a number of sites in Melbourne. Rotstayn
Location of the arid region in Northwest China.
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LI ET AL.: CHANGE OF PAN EVAPORATION IN THE NORTHWEST CHINA
et al. [2006] combined the two models of Thom et al.
[1981] and Linacre [1994], and created a simple one (PenPan). This simple model is at the monthly basis, and calculates the pan evaporation rate (Ep, kg m2 s1) as the sum
of radiative (Epan,R) and aerodynamic (Epan,A) components:
Ep ¼ Ep;R þ Ep; A ¼
s Rn
a
þ
fqðuÞD ;
s þ a s þ a
(1)
where Ep is the pan evaporation rate (kg m2 s1); s, with
a unit of Pa K1, is the slope of the curve created by plotting saturation vapor pressure (es) against air temperature
Ta (K) measured at 2 m above the ground; (67 Pa K1)
is the psychrometric constant ; Rn (W m2) is the net irradiance of the pan; (J kg1) is the latent heat of vaporization; and D¼ esea is the vapor pressure deficit at 2 m, in
which ea is the actual vapor pressure (Pa); and es is the saturation vapor pressure (Pa), the average saturation vapor
pressure is (esmaxþesmin)/2,
17:27Ta max
es max ¼ 610:8 exp
;
Ta max þ 237:3
17:27Ta min
;
es min ¼ 610:8 exp
Ta min þ237:3
(2)
where Ta max (K) and Ta min (K) are observations of maximum temperature and minimum temperature respectively
at 2 m height above the ground.
[9] And a¼ fb(u)/fq(u) ¼ 4.2, is the ratio of effective surface areas for heat and vapor transfer calculated based on
the pan size. Linacre [1994] documented that the convective heat transfer coefficient for water is 2.5u W m2 K1
and the convective for pan wall is about 4u W m2 K1.
Therefore, the effective coefficient for the pan is
(0.03142.5u þ 0.06284u)/0.0314 ¼10.5u W m2 K1.
The resistance to the loss of heat by convection is 1290/
10.5u122.86/u s m1 (i.e., c/h ¼ 1.29 kg1.0103 J
kg1 K1/10.5u W m2 K1), and the resistance to evaporation is 1290/2.5u ¼516/u s m1. Hence, the ratio of the
effective surface areas for heat and water vapor transfer is
a¼ 516/122.864.2.
[10] And fq(u) (kg m2 s1 Pa1), which is an empirical
vapor transfer function:
fqðuÞ ¼ 1:39 108 ð1 þ 1:35u2 Þ;
(3)
incoming shortwave radiation of a pan, which is greater than
the downward solar irradiance at the surface (Rs) because of
additional interception by the walls of the pan [Rotstayn
et al., 2006]. The last two terms, Rl,in and Rl,out, are the
incoming and outgoing long-wave irradiance respectively.
Rl,out is estimated by assuming the pan is a black body radiating at temperature Ta, and Rl,in is estimated using the FAO
56 approach [Allen et al., 1998]:
pffiffiffiffi Rl;in ¼ Ta4 1 ð0:34 0:14 ea Þ 1:35Rs =Ro 0:75 þ 2 105 z
0:35Þ;
(6)
where is the Stefan-Boltzmann constant (W K4 m2);
Ro is the top of the atmosphere solar radiation (W m2);
and z is the station elevation (m).
[13] Rsp in equation (5) is calculated as:
Rsp ¼ ½Prad fdir þ 2ð1 fdir Þ þ Rs ;
where Prad is the pan evaporation factor accounting for the
additional direct radiation intercepted by the pan wall; fdir
is the fraction of direct radiation calculated based on the
observed solar direct radiation and solar diffuse radiation at
the seven stations in the southern and northern Xinjiang and
Hexi corridor; and is the albedo (¼ 0.23) assigned for the
ground surface of the stations. For the D20 pan, the water
surface area is 0.0314 m2, the wall area is 0.0628 m2, and
the vertical wall is effectively exposed to half of the diffuse
and reflected irradiance [Linacre, 1994]. The three terms in
the brackets on the right side of equation (7) represent the
direct, diffuse, and reflected components, respectively.
2.3.2. Attribution of the Change in Pan Evaporation
Rate
[14] For attribution, the change in pan evaporation rate is
given by differentiating the equation of Roderick et al.
[2007]. The contribution of meteorological variables on
evaporative demand is obtained from the partial derivatives:
dEp dEp;R dEp;A
þ
:
¼
dt
dt
dt
4:87
;
lnð67:8z 5:42Þ
(4)
where u10 (m s1) is the mean wind speed at 10 m above
the ground, z¼10.
[11] For the calculation of the net irradiance of the
pan (Rn):
Rn ¼ ð1 ApÞRsp þ Rl;in Rl;out :
(5)
[12] Ap is the pan albedo (¼0.14) [Rotstayn et al., 2006;
Roderick et al., 2007; Yang and Yang, 2011], and Rsp is the
(8)
[15] The term dEp,A/dt is then partitioned into three components representing the changes of wind speed, vapor
pressure deficit, and temperature, respectively.
where u2 (m s1) is the mean wind speed at 2 m above the
ground, and
u2 ¼ u10
(7)
dEp;A @Ep;A du @Ep;A dD @Ep;A ds dTa
:
þ
þ
dt
@u dt
@D dt
@s dTa dt
(9)
2.3.3. Cokriging Geo-Statistical Analyst
[16] Because of the wavy terrain in the study area, which
has great effects on the spatial interpolation result, we used
the Cokriging geo-statistical method in ArcGIS software to
interpolate the annual Ep trend based on the digital elevation model (DEM) data.
3.
Results
3.1. Evaluation of the PenPan Model
[17] We used the monthly pan evaporation data observed
at the 81 ground-based meteorological stations of the China
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LI ET AL.: CHANGE OF PAN EVAPORATION IN THE NORTHWEST CHINA
Figure 2. Comparison of observed (OBS) and calculated (CAL) pan evaporation from 1958 to 2001:
(a) calibration : monthly pan evaporation of 50 stations and 24,096 points in Xinjiang, best fit regression :
y ¼ 0.95x þ 2.4, with R2 of 0.94 and RMSE of 31 mm month1 (y is the OBE Ep, x is the CAL Ep), and
(b) validation: monthly pan evaporation of 31 stations and 10,476 points in Hexi Corridor, best fit
regression : y ¼ 1.02x þ 10.5, with R2 of 0.85 and RMSE of 49 mm month1.
meteorological administration from 1958 to 2001, and
reconstructed the data from 1958 to 2010 with the PenPan
model for the statistical analysis. We used the 50 stations
in Xinjiang, which forms the western part of the study area,
to calibrate the PenPan model (Figure 2a), the agreement
between modeled and observed Ep from 1958 to 2001
(R2¼0.94, n¼24,096, RMSE¼31 mm month1) was excellent, and then we used the 31 stations in the Hexi Corridor
in the eastern part of the study area to validate the model
(Figure 2b), and got an RMSE of 49 mm month1. The calibration result is much better than the validation result,
which is likely due to that there is only one station having
complete observation data of direct radiation and solar
diffuse radiation in the Hexi corridor, which may not be
enough for estimating Rsp.
3.2. Trend of Pan Evaporation Change
[18] We used the PenPan model to calculate Ep at each
station, and compared the results with the observed values
for 1958–2001 at the 81 stations (Figure 3a). We then used
Cokriging to obtain the Ep trends as shown in Figure 3b.
One can see that the interpolated Ep values are bigger than
the simple average of all stations in the study area. Figure 3
shows that the annual pan evaporation exhibits an obvious
decreasing trend from 1958 to early 1990s, and then has
reversed upward. The turning point is around the year
Figure 3. Change of annual Ep in the arid region of Northwest China from 1958 to 2010: (a) comparison between observed and calculated annual pan evaporation, and (b) change of Ep interpolated based on
the DEM in the study area from 1958 to 2010 (The blue line shows the 5 year moving average).
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LI ET AL.: CHANGE OF PAN EVAPORATION IN THE NORTHWEST CHINA
Table 1. Trends in Pan Evaporation and its Components at 81
Sites for the Period of 1958–1993 and 1994–2010
Period
Ep
(mm yr2)
Ep,R
(mm yr2)
Ep,A
(mm yr2)
WS
VPD
Ta
1958–1993
1994–2010
6.0
10.7
0.5
2.1
5.6
8.6
4.9
4.0
0.9
3.9
0.3
0.9
1993. This is consistent with the nationwide average [Sun,
2007; Liu et al., 2011].
3.3. Attribution of Changing Pan Evaporation
[19] From Figure 3, it is found that the pan evaporation
trend in the study changed from downward to upward
around 1993. Therefore, we set the year 1993 as the inflec-
tion point to divide time series into two parts: 1958–1993
and 1994–2010.
[20] Using equation (1), which contains two components,
Ep,A and Ep,R, we estimated the trend of aerodynamic component and radiative component over the two periods at
each station. Table 1 shows the modeled trends in pan
evaporation rate (dEp/dt, mm yr2), radiative component
(dEp,R/dt, mm yr2), and aerodynamic component (dEp,A/dt,
mm yr2) for the periods 1958–1993 and 1994–2010. The
aerodynamic component is partitioned into components of
wind speed (WS), vapor pressure deficit (VPD), and air
temperature (Ta) as indicated in Equation (9). Results show
that changes in aerodynamic component dominate the variation of Ep in both periods, while the radiative component
has a minor impact.
[21] We also calculated the trends of Ep rate and its components at the 81 stations for the two periods (Figure 4). As
shown in Figures 4a and 4b, annual Ep at most stations
Figure 4. Trends in pan evaporation and its two components at 81 stations for the periods 1958–1993
and 1994–2010: (a) pan evaporation trend in 1958–1993 at the 81 stations with an average rate of 6.0
mm yr2, (b) pan evaporation trend in 1994–2010 at an average rate of 10.7 mm yr2, (c) radiative component trend in 1958–1993 at an average rate of 0.5 mm yr2, (d) radiative component trend in 1994–
2010 at an average rate of 2.1 mm yr2, (e) aerodynamic component trend in 1958–1993 at an average
rate of 5.6 mm yr2, (f) aerodynamic component trend in 1994–2010 at an average rate of 8.6 mm yr2.
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LI ET AL.: CHANGE OF PAN EVAPORATION IN THE NORTHWEST CHINA
Figure 5. Trends of aerodynamic component at 81stations for the periods 1958–1993 and 1994–2010:
The calculation results of (a) wind speed in 1958–1993, (b) wind speed in 1994–2010, (c) vapor pressure
deficit in 1958–1993, (d) vapor pressure deficit in 1994–2010, (e) air temperature in 1958–1993, (f) air
temperature in 1994–2010.
(almost 80%) decreased during 1958–1993 at an average
rate of 6.0 mm yr2. From 1994 to 2010, more than 80%
stations increased at an average rate of 10.7 mm yr2.
Among the 15 declining stations during 1994–2010, 7 are
in the northern Xinjiang. The contribution of radiative component to the Ep is very small in both periods (Figures 4c
and 4d). Figures 4e and 4f show that 77% of the stations
having aerodynamic component decreased during 1958–
1993, and 79% of the stations increased during 1994–2010.
These percentages reveal that the variation of aerodynamic
matches that of Ep, which may indicate that aerodynamic is
a major factor underlying the trend of Ep.
[22] The calculation results of wind speed, vapor pressure deficit, and temperature for the two periods at the 81
stations are shown in Figure 5. During 1958–1993, much of
the trend in Ep was due to the changes in wind speed, leading to a decrease of Ep with a rate of 4.9 mm yr2.
Changes due to vapor pressure deficit and temperature are
very limited. During 1994–2010, leading to the inference
that much of the Ep trend in Northern Xinjiang was still
due to the changes in wind speed, the vapor pressure deficit
also plays an important role in this period, causing Ep to
increase at 84% of the observation stations.
[23] Wind speed plays a noticeable role in the changing
pan evaporation. It is noteworthy that wind speed at most of
the 81 stations has opposite trends for the two periods with
an exception in North Xinjiang (Figure 6). During 1958–
1993, significant (p0.05) declining trends were detected at
51 stations, significant increase trends at 4 stations, and no
significant trend at 26 stations; while during 1994–2010,
significant (p0.05) declining trends were detected at 14
stations, significant increase trends at 33 stations. In addition, the spatial distribution of wind speed trends is generally consistent with the spatial distribution of Ep.
4.
Discussion
[24] A previous research investigated the nationwide Ep
dynamics in China based on measurements at 518 stations
from 1960 to 2007, and found that Ep decreased significantly
2210
LI ET AL.: CHANGE OF PAN EVAPORATION IN THE NORTHWEST CHINA
Figure 6. Spatial distribution of wind speed trends identified by the Mann-Kendall test in Northwest
China for the periods of (a) 1958–1993 and (b) 1994–2010.
at a rate of 5.4 mm yr2 from 1960 to 1991, and increased
significantly at a rate of 7.9 mm yr2 from 1992 to 2007
[Liu et al., 2011]. The results from our regional study are
consistent with that nationwide finding. Specifically, we
found that Ep significantly decreased at a rate of 6.0 mm
yr2 from 1958 to 1993, and significantly increased at a rate
of 10.7 mm yr2 from 1994 to 2010 in Northwestern China.
When using the modified PenPan model to estimate the
overall trends in Ep from 1958 to 2010 in our study area, the
modest number of stations for radiative observation might
be a source of error in estimating Rsp, especially in the Hexi
Corridor; several uncertainties in the PenPan model must be
improved, particularly in the calculation of the pan albedo
[Roderick et al., 2007].
[25] Our finding that the aerodynamic component, specifically, the wind speed, might be a major factor underlying the changes of Ep, is consistent with previous studies
on the United States [Hobbins et al., 2004] and Australia
[Rayner, 2007; Roderick et al., 2007; McVicar et al., 2008,
2012a, 2012b]. Dynamics of wind speed is associated with
changes of large scale atmospheric circulations [Rayner,
2007] and land surface roughness [Vautard et al., 2010].
The latter, in turn, is an outcome of changes of vegetation
cover and agricultural production, the factors that have significantly affect the field microclimate. Nevertheless, the
mechanism of wind speed dynamics has not yet to be fully
understood [McVicar et al., 2012b].
[26] In addition, while we understand that irrigation
water for agriculture also has considerable impact on evaporation in arid and semiarid irrigation areas [Han et al.,
2009]. We found it is greatly difficult to quantify the effect
of human activities and separate the effects of natural and
human factors. Further modeling and monitoring studies
are needed to address this issue.
5.
Summary
[27] In this study, we analyzed the interdecadal variation
of pan evaporation (Ep) over the last few decades in the
region of Northwest China using the PenPan model. We
found that Ep in this region exhibited a strong decreasing
trend at a rate of 6.0 mm yr2 from 1958 to 1993. The
downward trend was reversed to upward trend at a rate of
10.7 mm yr2 after then.
[28] Overall, the main driving force underlying the Ep
trend is the aerodynamic component. The aerodynamic
component at 77% of the 81 observation stations involved
in this study decreased during 1958–1993, leading to a
decrease of Ep at a rate of 5.6 mm yr2 ; the component
at 79% of the stations increased during 1994–2010, leading
to an increase of Ep at a rate of 8.6 mm yr2. The near-surface wind speed is the primary factor for the decline of pan
evaporation during 1958–1993, while both wind speed and
vapor pressure are primary factors for the increase of pan
evaporation from 1994 to 2010.
[29] Acknowledgments. The research is supported by the National
Basic Research Program of China (973 Program: 2010CB951003). The
authors thank Xun Shi for proofreading the language, and thank the anonymous reviewers for comments that improved our manuscript.
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