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 fluxchange can modify the climate. Model studies of such climate change effects of irrigation arecommonly based on land use parameterizations, in terms of irrigated land area, or landarea equipped for irrigation. Actual ET change, however, may also be driven by water usechange in addition to land use change. This study quantifies and compares ET changes due tochanges in climate, land use, and water use from the preirrigation period 1901–1955 tothe 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 mayvary greatly over a hydrological drainage basin. InMRB,much higher water use per irrigatedland unit in the downstream humid basin parts leads to higher vapor flux by ET, andirrigation‐induced ET flux change, than in the upstream, water‐stressed basin parts. This isconsistent with water supply limitations in water‐stressed basins. In contrast, the assumptionin land use−based models that irrigation maintains high soil moisture contents can implyhigher modeled water use and therefore also higher modeled ET fluxes under dry conditionsthan under humid conditions. The present results indicate water use as an important driverof 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% ofthe total human water withdrawal from lakes, rivers andaquifers, of which more than 90% is used for irrigationpurposes [Shiklomanov, 2000]. Water use for irrigationresults in streamflow depletion and increased evapotranspi-ration (ET) [Haddeland et al., 2006; Tang et al., 2007; Shibuoet al., 2007]. The role of irrigated land in modifying regionalclimate through such enhanced evapotranspiration (ET)increase has been investigated by incorporating differenttypes 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 waterwithdrawal by combining country average ET estimates forthe year 1990 [Seckler et al., 1998] with irrigated area in thedifferent countries [Döll and Siebert, 2000]. Sacks et al.[2009] generated an irrigation water withdrawal map basedon fractional cropland area [Leff et al., 2004], fractional areaequipped for irrigation [Siebert et al., 2001] and annual cli-matic water deficit [Helkowski, 2004]. This map was scaledup to coarser resolution to match the resolution in climate

model simulations. However, irrigation water was appliedto entire grid cells, leading to overestimation of latent heatflux [Sacks et al., 2009]. Lobell et al. [2009]modeled regionaldifferences in irrigation effects over eight major irrigatedregions of the world using a global climate model. Irriga-tion water was applied to maintain soil saturation at giventhresholds (40% and 30% investigated).Douglas et al. [2006]modeled regional ET fluxes from irrigated cropland andrain‐fed cropland, assuming that they equal potential ETand actual ET, respectively. The modeled vapor and latentheat fluxes in the relatively dry north and northwest Indiaincreased to such an extent that they influenced regionalatmospheric circulation patterns [Douglas et al., 2009].[4] These different climate model studies all assumed and

parameterized changes in land use, in terms of irrigated landarea, or land area equipped for irrigation, as main drivers forthe climate change effects of irrigation. These effects weremainly due to increasing latent heat flux by the irrigation‐driven ET increase. Actual ET change, however, may also bedriven 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 MahanadiRiver Basin (MRB) of India as an example field case. Hereclimate change represents observed changes in temperatureand precipitation within the MRB. Main land and water usechanges inMRB include engineered water storage, irrigation,

1Department of Physical Geography and Quaternary Geology, BertBolin Centre for Climate Research, Stockholm University, Stockholm,Sweden.

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and water diversion from the storage for the irrigation. Sep-arate and combined ET effects of such changes are herequantified and exemplified for MRB.

2. Materials and Methods

[6] Mahanadi River Basin (MRB) drains into Bay ofBengal, 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 1956with a gross water storage capacity of 8136 · 106 m3, is anengineered water storage structure that facilitates differenthuman 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 ofthe code POLFLOW, described in detail by de Wit [2001].The code has been widely used for model applications todifferent catchments of the world [de Wit, 2001; Darracqet al., 2005; Lindgren et al., 2007; Shibuo et al., 2007;Jarsjö et al., 2008]. The MRB was delineated and its rivernetwork 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) andnear‐surface temperature (T) for the whole basin were furtherused and taken from the database CRU TS 2.1 [Mitchell andJones, 2005]. In order to comparatively investigate the effectsof changes in climate, land use andwater use withinMRB, wequantified and mapped irrigated land area within the basinfrom the global map of irrigation areas version 4.0.1 [Siebertet al., 2007], as well as the amount of water diverted from theHirakud reservoir for irrigation use. In the hydrologicalmodeling, the diverted irrigation water was applied as addi-tional precipitation over the irrigated areas, following thesame methodology to that previously applied to the Aral Seadrainage basin in central Asia by Shibuo et al. [2007]. TheMRB contains no major lakes or reservoirs except for theHirakud reservoir, which covers only 0.2% of the total landarea of the basin. The water vapor flow from MRB to theatmosphere 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, thepotential evapotranspiration (Ep) in each grid cell in mm/yrwas estimated based on the Langbein method [Langbein,1949],

Ep ¼ 325þ 21 * Tþ 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 wasobtained from calculated Ep and available precipitation (P) inmm/yr based on the method by Turc [1954],

ET ¼ pffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi0:9þ p2

E2p

s : ð2Þ

[8] The MRB hydrological model was calibrated by fittingsimulated river runoff to available runoff observation dataobtained from the Central Water Commission New Delhi,

shown in the auxiliary material (Figure S1) and also used inthe MRB hydrological model studies by Asokan [2005] andAsokan and Dutta [2008].1 The model calibration was carriedout in two steps, as proposed by Jarsjö et al. [2008]. First,uncalibrated estimates of ET, and associated precipitationsurplus (PS = P − ET) and river runoff (R) were obtained byuse 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 uncalibratedto MRB conditions. A single calibration factor Xcal wasfurther used to correct uncalibrated ET values everywherewithin the basin,

ETcal ¼ Xcal * ET ; ð3Þ

producing calibrated values (ETcal), for which R at the basinoutlet is consistent with available observations. The singlecalibration factor Xcal was determined as in work by Jarsjöet al. [2008],

Xcal ¼ Robs

R0þ 1� Robs

R0

� �SPSET

; ð4Þ

whereRobs is the observed total runoff at the basin outlet,R0 isthe uncalibratedmodeled runoff at the basin outlet,SET is thetotal uncalibrated evapotranspiration over the basin (fromequation (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 inMRB during the period 1990–2000, and are consistent withavailable observations; in the following, this simulationscenario 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 irrigationchange effects on ET and R. For the scenario comparison, thecalibrated hydrological model of MRB, i.e., obtained fromthe 1990–2000 Climate‐irrigation scenario using equations (3)and (4), was used together with available independent climatedata for: (1) prereservoir and preirrigation conditions prevail-ing in the period 1901–1955 (in the following referred to as thePrereservoir scenario), and (2) a hypothetical 1990–2000scenario (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 thatfollowed after the reservoir construction. River runoff dataare 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 underconditions of ambient change have demonstrated that it canperform well without recalibration. In the Aral Sea drainagebasin of central Asia, Shibuo et al. [2007] showed that themethod could reproduce observed water flows before andafter an extensive irrigation expansion, without involving

1Auxiliary materials are available in the HTML. doi:10.1029/2010JD014417.

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calibration. Jarsjö et al. [2008] showed that the methodreproduced stream runoff observations by using the singlefactor Xcal for calibration of different subbasins of two coastalareas in Sweden. Shibuo et al. [2007] and Jarsjö et al. [2008]furthermore showed that the relatively simple ET approachadopted here performed equally well in their applications asthe 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 landuse and water use changes. Direct result comparison betweenthese two scenarios and the realistic Climate‐irrigation sce-nario for 1990–2000 shows separate and combined ET effectsof climate and irrigation change, and for the latter also of thechange 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 ofirrigated land area and water use for irrigation in MRB,respectively. Comparison between Figures 1a and 1b showsconsiderable difference between the irrigated land use and thewater use for irrigation within the basin. More specifically,the water use for irrigation is almost negligible in theupstream part of the basin, even though that land area isirrigated. The water use map was calculated from knownquantities of water withdrawal for irrigation in the differentparts 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 ofthe 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 thetotal MRB area of 135,084 km2. Figure 2 (right) displays thespatial distribution of T and P changes from their temporalaverage during 1901–1955 to that during 1990–2000. The10 year running T average shows an increase of about 0.3°Cin 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 towardthe last quarter of the century, Figure 2 (right) identifies alsosubareas with increased precipitation in the most downstreampart of the basin. The T and P data for the 20th century wereused in the hydrological modeling of the three simulationscenarios. In the realistic 1990–2000 climate‐irrigation sce-nario, the total amount of water diverted from the reservoirfor irrigation purposes amounts to about 11 km3. Out of thistotal, a whole 10.5 km3 was used for the irrigation in thedownstream 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 comparisonwith the pre‐1955 period. Themodeled ET for the 1990–2000Climate scenario is smaller than for the pre‐1955 conditions(Prereservoir scenario), due to the P decrease between theseperiods. However, for the Climate‐irrigation scenario, themodeled ET is higher than for the pre‐1955 conditions, dueto increased ET losses from the irrigated areas.[15] Figure 3 schematically illustrates the main water flow

differences between the Climate‐irrigation and the Climatescenario for the 1990–2000 period. In the Climate‐irrigationscenario, the diverted water from the river (11 km3 in total) isapplied over the irrigated land area parts according to actualuse of irrigation water in each part. Some part of the appliedirrigation water is then lost as ET, while the remaining parteventually flows back into the river. Figure 4 quantifiesthe spatial distribution of modeled PS (P‐ET, yielding localrunoff at each location) within MRB for the two 1990–2000scenarios. Due to the large water use for irrigation in thedownstream 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 Climatescenario for 1990–2000. In the downstream part of thebasin’s irrigated land area, the ET loss to the atmospherein the Climate‐irrigation scenario is almost double that ofthe 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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irrigated land area is essentially the same for both scenarios.Consequently, also the relative ET change, which determinesthe change in latent heat flux and associated climate changefrom the Prereservoir scenario (1900–1955) to 1990–2000is much larger in the Climate‐irrigation than in the Climatescenario for the downstream irrigated land area, while it isessentially the same in both scenarios for the upstream irri-gated land area (Figure 6). The change in ET is thus governedby the actual water use for irrigated land, rather than bywhether or not the land is classified as irrigated because it issubject to some degree of irrigation. As the changes in latentheat flux and climate effect of irrigation are associated withET 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 availableCRU data set to provide good estimates of P and its spatialdistribution, and the water storage changeDS to be negligibleover the 11 year period of the base‐case climate‐irrigationscenario. A relatively detailed study of 53 different catch-ments [Australian Water Resources 2005, 2007] indicatederrors of around 14% when deriving ET from water balanceclosure based directly on P and R observations, as in ourbasic climate‐irrigation scenario. Additional error may arisefrom the choice of ET parameterization in the hydrologicalmodeling. For an indication of this error magnitude, auxiliarymaterial (auxiliary material Table S1) compares the resultsof the ET model by Langbein [1949], which was mainly usedin the present hydrological modeling, with those of usingthe 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 25.6Total precipitation (km3 yr−1) 180 162 162Total modeled ET (km3 yr−1) 90 93 86Reported irrigation water use within the basin (km3 yr−1) ‐ 11 ‐Modeled runoff at Mahanadi outlet (km3 yr−1) 90 69.5 76Observed 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 conditionsover the recent period 1990–2000 compared to the prereservoir period 1901–1955.

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alternative. The ET and R results of the two different ETmodels differ at most by 3%. Even this maximum ET modelerror is considerably smaller than the result differences (ofabout 8% for ET, and 9–10% for R) between the climate andthe climate‐irrigation scenario. This supports our interpreta-tion of the scenario results differences beingmainly due to theirrigation. The errors in absolute ET values are further below20% when considering both the ET model error and the error(of around 14%) from other assumptions involved in ETestimation from water balance closure. This is, for instance,considerably smaller than the around 50% error found forET 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 waterbalance, including ET and its latent heat flux and climatechange effects, depend also on the changes of water storage inengineered reservoirs, like the Hirakud reservoir in the MRBcase. In a previous MRB study, Asokan and Dutta [2008]explicitly accounted for the effect of the Hirakud reservoirregulation on monthly river runoff in their hydrologicalmodeling; this relatively small‐scale temporal variabilityeffect was not considered in the present hydrological mod-eling. This is because we use annual water balance averagingto 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 for1990–2000.

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monthly water balance averaging, Figure 7 exemplifies theeffect of water storage change in the Hirakud reservoir fortwo example months (April and September), based on themodel results of Asokan and Dutta [2008] for year 1998. InSeptember, stored water is released from the reservoir andadds considerably to the monthly river runoff. This particu-larly emphasizes the need to account also for such wateruse effects on seasonal ET, and associated latent heat fluxand climate changes. Otherwise, relying only on regionalP and R data for model testing, as may be done in spatiallylow‐resolved climate modeling, can considerably misleadregional estimates of monthly ET and its change.

4. Conclusions

[19] We have considered human water diversions to landirrigation and shown that in the MRB, the spatial distributionof irrigated fields (derived from land usemaps of Siebert et al.[2007]) differs considerably from the distribution of wateruse 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 maychange considerably over time, such as in the lower Aral SeaDrainage Basin, where water diversions to parts of the irri-gated land have ceased in recent times due to acute watershortage [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 theupstream parts of the basin. The hydrological modelingresults 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 fluxdistribution over the MRB hence correlates well to the wateruse map, but is poorly correlated to the land use map. How-ever, in irrigation effect studies so far, land use maps haveserved as main inputs to ET flux change quantifications [e.g.,Shibuo et al., 2007], and associated changes in latent heat fluxand 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 1901–1955for (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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sufficient (and, in principle, unlimited) amounts to keep thesoil moist. This implies higher modeled water use and gen-erates higher modeled ET fluxes under dry conditions thanunder humid conditions, which is consistent with (ideal) croprequirements, 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 thewater‐stressed Aral Sea drainage basin in Central Asia mayhave been several times larger than the amount of availablewater. We here show that in the drier westernMRB, receivingabout half of the precipitation of eastern MRB and classifiedas water‐stressed by Asokan and Dutta [2008], the actualwater use per irrigated land unit was about an order of mag-nitude lower than in the humid eastern MRB. This can henceexplain our finding that irrigation in drier regions causedmuch smaller water losses through ET than irrigation inalready humid regions.[22] Land use data are commonly much more accessible

than water use data, which is a main reason for choosing touse the former over the latter type of information in bothhydrological and climate change modeling. Our results implythat such data accessibility limitations hinder relevant mod-eling and data interpretations, and show the significanceof independent data sets that reflect actual water use. Forinstance, soil moisture data [e.g., Njoku et al., 2003] andvegetation data such as the normalized vegetation index(NDVI) [e.g., Tucker et al., 2005] can reveal unreportedchanges in water use for irrigation through its effects on soilwater content and crop development. Such information andother possible data on water use, and its spatial variability andtemporal change need to be introduced and accounted for inclimate and Earth system modeling, among the main driversand factors of regional climate and environmental change.

[23] Acknowledgment. This work has been carried out withinthe framework of the Bert Bolin Centre for Climate Research at StockholmUniversity, which is supported by a Linnaeus grant from the Swedishresearch councils VR and Formas.

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S. M. Asokan, G. Destouni, and J. Jarsjö, Department of PhysicalGeography and Quaternary Geology, Bert Bolin Centre for ClimateResearch, Stockholm University, SE‐10691 Stockholm, Sweden. (shilpa.asokan@natgeo.su.se; georgia.destouni@natgeo.su.se; jerker.jarsjo@natgeo.su.se)

ASOKAN ET AL.: VAPOR FLUX BY EVAPOTRANSPIRATION D24102D24102

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