1) The document analyzes how evapotranspiration (ET) has changed in the Mahanadi River Basin in India due to changes in climate, land use, and water use from 1901-1955 to 1990-2000. 2) It finds that while irrigated land area increased, actual water use per unit of irrigated land varied greatly within the basin, with much higher usage in downstream humid areas leading to higher ET changes there than in upstream water-stressed areas. 3) Modeling the basin under pre-1955, post-1955 climate only, and post-1955 climate with irrigation scenarios shows that climate increased temperatures while precipitation decreased slightly, but irrigation increased ET more than climate changes alone

1. Vapor flux by evapotranspiration: Effects of changes in climate,
land use, and water use
Shilpa M. Asokan,1
Jerker Jarsjö,1
and Georgia Destouni1
Received 26 April 2010; revised 14 September 2010; accepted 7 October 2010; published 17 December 2010.
[1] Enhanced evapotranspiration (ET) over irrigated land and associated latent heat flux
change can modify the climate. Model studies of such climate change effects of irrigation are
commonly based on land use parameterizations, in terms of irrigated land area, or land
area equipped for irrigation. Actual ET change, however, may also be driven by water use
change in addition to land use change. This study quantifies and compares ET changes due to
changes in climate, land use, and water use from the preirrigation period 1901–1955 to
the recent period 1990–2000 (with irrigation) for the example case of Mahanadi River Basin
(MRB) in India. The results show that actual water use per unit area of irrigated land may
vary greatly over a hydrological drainage basin. In MRB, much higher water use per irrigated
land unit in the downstream humid basin parts leads to higher vapor flux by ET, and
irrigation‐induced ET flux change, than in the upstream, water‐stressed basin parts. This is
consistent with water supply limitations in water‐stressed basins. In contrast, the assumption
in land use−based models that irrigation maintains high soil moisture contents can imply
higher modeled water use and therefore also higher modeled ET fluxes under dry conditions
than under humid conditions. The present results indicate water use as an important driver
of regional climate change, in addition to land use and greenhouse gas‐driven changes.
Citation: Asokan, S. M., J. Jarsjö, and G. Destouni (2010), Vapor flux by evapotranspiration: Effects of changes in climate,
land use, and water use, J. Geophys. Res., 115, D24102, doi:10.1029/2010JD014417.
1. Introduction
[2] Globally, agriculture accounts for about 70% of
the total human water withdrawal from lakes, rivers and
aquifers, of which more than 90% is used for irrigation
purposes [Shiklomanov, 2000]. Water use for irrigation
results in streamflow depletion and increased evapotranspi-
ration (ET) [Haddeland et al., 2006; Tang et al., 2007; Shibuo
et al., 2007]. The role of irrigated land in modifying regional
climate through such enhanced evapotranspiration (ET)
increase has been investigated by incorporating different
types of irrigation parameterizations in climate modeling
[Boucher et al., 2004; Sacks et al., 2009; Lobell et al., 2009].
[3] Boucher et al. [2004] estimated an ET flux from irri-
gated areas of about 40% of the total global irrigation water
withdrawal by combining country average ET estimates for
the year 1990 [Seckler et al., 1998] with irrigated area in the
different countries [Döll and Siebert, 2000]. Sacks et al.
[2009] generated an irrigation water withdrawal map based
on fractional cropland area [Leff et al., 2004], fractional area
equipped for irrigation [Siebert et al., 2001] and annual cli-
matic water deficit [Helkowski, 2004]. This map was scaled
up to coarser resolution to match the resolution in climate
model simulations. However, irrigation water was applied
to entire grid cells, leading to overestimation of latent heat
flux [Sacks et al., 2009]. Lobell et al. [2009] modeled regional
differences in irrigation effects over eight major irrigated
regions of the world using a global climate model. Irriga-
tion water was applied to maintain soil saturation at given
thresholds (40% and 30% investigated). Douglas et al. [2006]
modeled regional ET fluxes from irrigated cropland and
rain‐fed cropland, assuming that they equal potential ET
and actual ET, respectively. The modeled vapor and latent
heat fluxes in the relatively dry north and northwest India
increased to such an extent that they influenced regional
atmospheric circulation patterns [Douglas et al., 2009].
[4] These different climate model studies all assumed and
parameterized changes in land use, in terms of irrigated land
area, or land area equipped for irrigation, as main drivers for
the climate change effects of irrigation. These effects were
mainly due to increasing latent heat flux by the irrigation‐
driven ET increase. Actual ET change, however, may also be
driven by water use change in addition to land use change,
even though only the latter parameter is commonly consid-
ered as a main driver in climate modeling.
[5] The main aim of the present study is to quantify and
compare ET flux changes due to changes in climate, land use,
and water use. For this purpose, the study uses the Mahanadi
River Basin (MRB) of India as an example field case. Here
climate change represents observed changes in temperature
and precipitation within the MRB. Main land and water use
changes in MRB include engineered water storage, irrigation,
1
Department of Physical Geography and Quaternary Geology, Bert
Bolin Centre for Climate Research, Stockholm University, Stockholm,
Sweden.
Copyright 2010 by the American Geophysical Union.
0148‐0227/10/2010JD014417
JOURNAL OF GEOPHYSICAL RESEARCH, VOL. 115, D24102, doi:10.1029/2010JD014417, 2010
D24102 1 of 8

2. and water diversion from the storage for the irrigation. Sep-
arate and combined ET effects of such changes are here
quantified and exemplified for MRB.
2. Materials and Methods
[6] Mahanadi River Basin (MRB) drains into Bay of
Bengal, which joins the Indian Ocean. Average annual rain-
fall in the most upstream part of the basin is about 1000 mm,
increasing toward the central basin part (1300 mm) and fur-
ther in the most downstream coastal belt of the basin
(1700 mm). The Hirakud dam with its reservoir, built in 1956
with a gross water storage capacity of 8136 · 106
m3
, is an
engineered water storage structure that facilitates different
human water uses, including water use for irrigation in MRB.
[7] In this study, hydrological modeling of MRB was
carried out using the PCRaster‐based water flow module of
the code POLFLOW, described in detail by de Wit [2001].
The code has been widely used for model applications to
different catchments of the world [de Wit, 2001; Darracq
et al., 2005; Lindgren et al., 2007; Shibuo et al., 2007;
Jarsjö et al., 2008]. The MRB was delineated and its river
network was generated from topographical data at a hori-
zontal grid interval of 0.008 × 0.008 decimal degrees.
Spatially distributed data for monthly precipitation (P) and
near‐surface temperature (T) for the whole basin were further
used and taken from the database CRU TS 2.1 [Mitchell and
Jones, 2005]. In order to comparatively investigate the effects
of changes in climate, land use and water use within MRB, we
quantified and mapped irrigated land area within the basin
from the global map of irrigation areas version 4.0.1 [Siebert
et al., 2007], as well as the amount of water diverted from the
Hirakud reservoir for irrigation use. In the hydrological
modeling, the diverted irrigation water was applied as addi-
tional precipitation over the irrigated areas, following the
same methodology to that previously applied to the Aral Sea
drainage basin in central Asia by Shibuo et al. [2007]. The
MRB contains no major lakes or reservoirs except for the
Hirakud reservoir, which covers only 0.2% of the total land
area of the basin. The water vapor flow from MRB to the
atmosphere is therefore governed by land‐based evapo-
transpiration, which comprises plant transpiration and evap-
oration from inland surface water and subsurface pore water.
The evapotranspiration was calculated in two steps. First, the
potential evapotranspiration (Ep) in each grid cell in mm/yr
was estimated based on the Langbein method [Langbein,
1949],
Ep ¼ 325 þ 21 * T þ 0:9 * T2
; ð1Þ
where T is the annual average temperature of the grid cell in
°C. Second, the actual evapotranspiration ET in mm/yr was
obtained from calculated Ep and available precipitation (P) in
mm/yr based on the method by Turc [1954],
ET ¼
p
ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi
0:9 þ
p2
E2
p
s : ð2Þ
[8] The MRB hydrological model was calibrated by fitting
simulated river runoff to available runoff observation data
obtained from the Central Water Commission New Delhi,
shown in the auxiliary material (Figure S1) and also used in
the MRB hydrological model studies by Asokan [2005] and
Asokan and Dutta [2008].1
The model calibration was carried
out in two steps, as proposed by Jarsjö et al. [2008]. First,
uncalibrated estimates of ET, and associated precipitation
surplus (PS = P − ET) and river runoff (R) were obtained by
use of available independent data in equations (1) and (2);
these empirical equations were obtained for different hydro-
climatic conditions and are not expected to apply uncalibrated
to MRB conditions. A single calibration factor Xcal was
further used to correct uncalibrated ET values everywhere
within the basin,
ETcal ¼ Xcal * ET; ð3Þ
producing calibrated values (ETcal), for which R at the basin
outlet is consistent with available observations. The single
calibration factor Xcal was determined as in work by Jarsjö
et al. [2008],
Xcal ¼
Robs
R0
þ 1 À
Robs
R0
SP
SET
; ð4Þ
where Robs is the observed total runoff at the basin outlet, R0 is
the uncalibrated modeled runoff at the basin outlet, SET is the
total uncalibrated evapotranspiration over the basin (from
equation (2)), and SP is the total precipitation over the basin.
The model was calibrated considering the period 1990–2000.
The resulting value of Xcal was 0.67.
[9] These calculations thus reproduce the effects of pre-
vailing climate and irrigation conditions on ET, PS and R in
MRB during the period 1990–2000, and are consistent with
available observations; in the following, this simulation
scenario is referred to as the Climate‐irrigation scenario.
Following similar comparative methodology as Shibuo et al.
[2007], this realistic Climate‐irrigation scenario for 1990–
2000 was further compared with two other simulation sce-
narios in order to quantify separate climate and irrigation
change effects on ET and R. For the scenario comparison, the
calibrated hydrological model of MRB, i.e., obtained from
the 1990–2000 Climate‐irrigation scenario using equations (3)
and (4), was used together with available independent climate
data for: (1) prereservoir and preirrigation conditions prevail-
ing in the period 1901–1955 (in the following referred to as the
Prereservoir scenario), and (2) a hypothetical 1990–2000
scenario (in the following referred to as the Climate scenario),
neglecting irrigation and considering only the prevailing cli-
mate conditions in this period.
[10] The Prereservoir scenario thus represents hydrology in
MRB prior to the major land use and water use changes that
followed after the reservoir construction. River runoff data
are not available from this period, which means that a com-
parison with modeled runoff is not possible. However, pre-
vious applications of this modeling methodology under
conditions of ambient change have demonstrated that it can
perform well without recalibration. In the Aral Sea drainage
basin of central Asia, Shibuo et al. [2007] showed that the
method could reproduce observed water flows before and
after an extensive irrigation expansion, without involving
1
Auxiliary materials are available in the HTML. doi:10.1029/
2010JD014417.
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3. calibration. Jarsjö et al. [2008] showed that the method
reproduced stream runoff observations by using the single
factor Xcal for calibration of different subbasins of two coastal
areas in Sweden. Shibuo et al. [2007] and Jarsjö et al. [2008]
furthermore showed that the relatively simple ET approach
adopted here performed equally well in their applications as
the methods of Thornthwaite [1948] and Wendland [1992].
[11] The Climate scenario further represents hydrological
conditions for the period 1990–2000 in the hypothetical case,
that only climate had changed from the 1901–1955 condi-
tions, without any irrigation or other reservoir‐related land
use and water use changes. Direct result comparison between
these two scenarios and the realistic Climate‐irrigation sce-
nario for 1990–2000 shows separate and combined ET effects
of climate and irrigation change, and for the latter also of the
change related to land use and to water use, from the 1901–
1955 period to the 1990–2000 period.
3. Results and Discussion
[12] Figures 1a and 1b show the spatial distribution of
irrigated land area and water use for irrigation in MRB,
respectively. Comparison between Figures 1a and 1b shows
considerable difference between the irrigated land use and the
water use for irrigation within the basin. More specifically,
the water use for irrigation is almost negligible in the
upstream part of the basin, even though that land area is
irrigated. The water use map was calculated from known
quantities of water withdrawal for irrigation in the different
parts of the basin [Asokan, 2005; Asokan and Dutta, 2008],
implying maximum water use for irrigation of only 2000 m3
in the upstream part and 106
m3
in the downstream part of
the basin.
[13] Reported T and P data and their change over the 20th
century are further shown in Figure 2. Figure 2 (left) illus-
trates the temporal trend in basin‐average T and P over the
total MRB area of 135,084 km2
. Figure 2 (right) displays the
spatial distribution of T and P changes from their temporal
average during 1901–1955 to that during 1990–2000. The
10 year running T average shows an increase of about 0.3°C
in the second half of the 20th century (1956–2002) in com-
parison with the first half (1901–1955). Although the time
series of P indicates a decreasing basin‐average trend toward
the last quarter of the century, Figure 2 (right) identifies also
subareas with increased precipitation in the most downstream
part of the basin. The T and P data for the 20th century were
used in the hydrological modeling of the three simulation
scenarios. In the realistic 1990–2000 climate‐irrigation sce-
nario, the total amount of water diverted from the reservoir
for irrigation purposes amounts to about 11 km3
. Out of this
total, a whole 10.5 km3
was used for the irrigation in the
downstream part of MRB (see also Figure 1).
[14] Table 1 summarizes the basin‐average T and P
(based on direct observations), and other water balance terms
(modeled, with runoff, R, also observed during 1990–2000)
for all the three MRB simulation scenarios. The basin‐
average T increased by 0.4°C while P decreased by 18 km3
per year during the recent 1990–2000 period in comparison
with the pre‐1955 period. The modeled ET for the 1990–2000
Climate scenario is smaller than for the pre‐1955 conditions
(Prereservoir scenario), due to the P decrease between these
periods. However, for the Climate‐irrigation scenario, the
modeled ET is higher than for the pre‐1955 conditions, due
to increased ET losses from the irrigated areas.
[15] Figure 3 schematically illustrates the main water flow
differences between the Climate‐irrigation and the Climate
scenario for the 1990–2000 period. In the Climate‐irrigation
scenario, the diverted water from the river (11 km3
in total) is
applied over the irrigated land area parts according to actual
use of irrigation water in each part. Some part of the applied
irrigation water is then lost as ET, while the remaining part
eventually flows back into the river. Figure 4 quantifies
the spatial distribution of modeled PS (P‐ET, yielding local
runoff at each location) within MRB for the two 1990–2000
scenarios. Due to the large water use for irrigation in the
downstream part of the irrigated land area in the basin
(Figure 1), PS values are much larger there in the climate‐
irrigation than in the Climate scenario.
[16] Figure 5 further quantifies the spatial distribution
of modeled ET for the Climate‐irrigation and the Climate
scenario for 1990–2000. In the downstream part of the
basin’s irrigated land area, the ET loss to the atmosphere
in the Climate‐irrigation scenario is almost double that of
the Climate scenario, whereas ET in the upstream part of the
Figure 1. (a) Irrigated land [Siebert et al., 2007] and (b) water use within the Mahanadi River Basin
(MRB). Mahanadi River is shown in red color.
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4. irrigated land area is essentially the same for both scenarios.
Consequently, also the relative ET change, which determines
the change in latent heat flux and associated climate change
from the Prereservoir scenario (1900–1955) to 1990–2000
is much larger in the Climate‐irrigation than in the Climate
scenario for the downstream irrigated land area, while it is
essentially the same in both scenarios for the upstream irri-
gated land area (Figure 6). The change in ET is thus governed
by the actual water use for irrigated land, rather than by
whether or not the land is classified as irrigated because it is
subject to some degree of irrigation. As the changes in latent
heat flux and climate effect of irrigation are associated with
ET change, they are also governed by the actual water use.
[17] Errors in hydrological ET estimates arise from
assumptions made to close the water balance equation ET =
P − R − DS. For instance, we have here assumed the available
CRU data set to provide good estimates of P and its spatial
distribution, and the water storage change DS to be negligible
over the 11 year period of the base‐case climate‐irrigation
scenario. A relatively detailed study of 53 different catch-
ments [Australian Water Resources 2005, 2007] indicated
errors of around 14% when deriving ET from water balance
closure based directly on P and R observations, as in our
basic climate‐irrigation scenario. Additional error may arise
from the choice of ET parameterization in the hydrological
modeling. For an indication of this error magnitude, auxiliary
material (auxiliary material Table S1) compares the results
of the ET model by Langbein [1949], which was mainly used
in the present hydrological modeling, with those of using
the Thornthwaite [1948] ET model instead, as one possible
Table 1. Summary of Average Temperature and Water Balance in the MRB
Prereservoir 1901–1955 Climate‐Irrigation 1990–2000 Climate 1990–2000
Average temperature (°C) 25.2 25.6 25.6
Total precipitation (km3
yr−1
) 180 162 162
Total modeled ET (km3
yr−1
) 90 93 86
Reported irrigation water use within the basin (km3
yr−1
) ‐ 11 ‐
Modeled runoff at Mahanadi outlet (km3
yr−1
) 90 69.5 76
Observed runoff at Mahanadi outlet (km3
yr−1
) ‐ 69.5 ‐
Figure 2. (a) Temperature and (b) precipitation data within the MRB [Mitchell and Jones, 2005]. (left)
Temporal trends in basin‐average conditions. (right) Spatial distribution of change in average conditions
over the recent period 1990–2000 compared to the prereservoir period 1901–1955.
ASOKAN ET AL.: VAPOR FLUX BY EVAPOTRANSPIRATION D24102D24102
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5. alternative. The ET and R results of the two different ET
models differ at most by 3%. Even this maximum ET model
error is considerably smaller than the result differences (of
about 8% for ET, and 9–10% for R) between the climate and
the climate‐irrigation scenario. This supports our interpreta-
tion of the scenario results differences being mainly due to the
irrigation. The errors in absolute ET values are further below
20% when considering both the ET model error and the error
(of around 14%) from other assumptions involved in ET
estimation from water balance closure. This is, for instance,
considerably smaller than the around 50% error found for
ET estimates that are not calibrated to runoff observations
[see, e.g., Kite and Droogers, 2000; Verstraeten et al., 2008].
[18] On smaller than annual time scales, regional water
balance, including ET and its latent heat flux and climate
change effects, depend also on the changes of water storage in
engineered reservoirs, like the Hirakud reservoir in the MRB
case. In a previous MRB study, Asokan and Dutta [2008]
explicitly accounted for the effect of the Hirakud reservoir
regulation on monthly river runoff in their hydrological
modeling; this relatively small‐scale temporal variability
effect was not considered in the present hydrological mod-
eling. This is because we use annual water balance averaging
to investigate change effects on longer temporal scales,
expecting only relatively small interannual change in reser-
voir water storage, which is consistent with observations. For
Figure 4. Spatial distribution of modeled precipitation surplus for the period 1990–2000 (a) Climate‐
irrigation scenario and (b) Climate scenario.
Figure 3. Schematic illustration and quantification of the Climate‐irrigation and Climate scenarios for
1990–2000.
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6. monthly water balance averaging, Figure 7 exemplifies the
effect of water storage change in the Hirakud reservoir for
two example months (April and September), based on the
model results of Asokan and Dutta [2008] for year 1998. In
September, stored water is released from the reservoir and
adds considerably to the monthly river runoff. This particu-
larly emphasizes the need to account also for such water
use effects on seasonal ET, and associated latent heat flux
and climate changes. Otherwise, relying only on regional
P and R data for model testing, as may be done in spatially
low‐resolved climate modeling, can considerably mislead
regional estimates of monthly ET and its change.
4. Conclusions
[19] We have considered human water diversions to land
irrigation and shown that in the MRB, the spatial distribution
of irrigated fields (derived from land use maps of Siebert et al.
[2007]) differs considerably from the distribution of water
use for irrigation (derived from water use data of Asokan
[2005] and Asokan and Dutta [2008]). Other studies have
also shown that water diversions for land irrigation may
change considerably over time, such as in the lower Aral Sea
Drainage Basin, where water diversions to parts of the irri-
gated land have ceased in recent times due to acute water
shortage [Johansson et al., 2009].
[20] In the MRB, the actual water use per unit area of irri-
gated land is much higher in the downstream than in the
upstream parts of the basin. The hydrological modeling
results show that the current water use practices cause con-
siderably enhanced water vapor fluxes by ET in the down-
stream part of the basin with the higher water use. The ET flux
distribution over the MRB hence correlates well to the water
use map, but is poorly correlated to the land use map. How-
ever, in irrigation effect studies so far, land use maps have
served as main inputs to ET flux change quantifications [e.g.,
Shibuo et al., 2007], and associated changes in latent heat flux
and regional climate [e.g., Lobell et al., 2009].
[21] More specifically, as also exemplified in section 1,
main land use−based modeling approaches for ET quanti-
fication in irrigated regions imply that water is added in
Figure 6. ET change in average condition over the period 1990–2000 compared to the period 1901–1955
for (a) Climate‐irrigation scenario and (b) Climate scenario.
Figure 5. Spatial distribution of modeled ET for the period 1990–2000 (a) Climate‐irrigation scenario and
(b) Climate scenario.
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7. sufficient (and, in principle, unlimited) amounts to keep the
soil moist. This implies higher modeled water use and gen-
erates higher modeled ET fluxes under dry conditions than
under humid conditions, which is consistent with (ideal) crop
requirements, but does not account for water supply limita-
tions in water‐stressed (dry) drainage basins. For instance,
Lobell et al. [2009] found that modeled water fluxes in the
water‐stressed Aral Sea drainage basin in Central Asia may
have been several times larger than the amount of available
water. We here show that in the drier western MRB, receiving
about half of the precipitation of eastern MRB and classified
as water‐stressed by Asokan and Dutta [2008], the actual
water use per irrigated land unit was about an order of mag-
nitude lower than in the humid eastern MRB. This can hence
explain our finding that irrigation in drier regions caused
much smaller water losses through ET than irrigation in
already humid regions.
[22] Land use data are commonly much more accessible
than water use data, which is a main reason for choosing to
use the former over the latter type of information in both
hydrological and climate change modeling. Our results imply
that such data accessibility limitations hinder relevant mod-
eling and data interpretations, and show the significance
of independent data sets that reflect actual water use. For
instance, soil moisture data [e.g., Njoku et al., 2003] and
vegetation data such as the normalized vegetation index
(NDVI) [e.g., Tucker et al., 2005] can reveal unreported
changes in water use for irrigation through its effects on soil
water content and crop development. Such information and
other possible data on water use, and its spatial variability and
temporal change need to be introduced and accounted for in
climate and Earth system modeling, among the main drivers
and factors of regional climate and environmental change.
[23] Acknowledgment. This work has been carried out within
the framework of the Bert Bolin Centre for Climate Research at Stockholm
University, which is supported by a Linnaeus grant from the Swedish
research councils VR and Formas.
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