Research Article Influence of Land Use Patterns on ...downloads.hindawi.com/journals/amete/2015/452603.pdfIts Components in a Temperate Grassland Ecosystem YuzheLi, 1,2 JiangwenFan,

Research ArticleInfluence of Land Use Patterns on Evapotranspiration andIts Components in a Temperate Grassland Ecosystem

Yuzhe Li12 Jiangwen Fan1 Zhongmin Hu3 Quanqin Shao1

Liangxia Zhang12 and Hailing Yu12

1Key Laboratory of Land Surface Pattern and Simulation Institute of Geographical Sciences and Natural Resources ResearchChinese Academy of Sciences Beijing 100101 China2University of Chinese Academy of Sciences Beijing 100049 China3Key Laboratory of EcosystemNetwork Observation andModeling Synthesis Research Center of Chinese Ecosystem Research NetworkInstitute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing 100101 China

Correspondence should be addressed to Jiangwen Fan fanjwigsnrraccn

Received 18 September 2014 Accepted 9 December 2014

Academic Editor Jinwei Dong

Copyright copy 2015 Yuzhe Li et alThis is an open access article distributed under the Creative Commons Attribution License whichpermits unrestricted use distribution and reproduction in any medium provided the original work is properly cited

To better understand variation in response of components of ecosystem evapotranspiration (ET) to grassland use differences weselected three typical land use patterns in a temperate steppe area grazed steppe (G) steppe with grazers excluded (GE) and steppecultivated to cropland (C) ET was divided into its components evaporation (E) and canopy transpiration (T) using herbicide and achamber attached to a portable infrared gas analyzer (Li-6400) The results indicated that daily water consumption by ET in G was330 kgmminus2 dminus1 compared with G ET increased significantly in GE at 134 and showed a trend of 673 increase in C Daily waterconsumption by E increased 243 in GE relative to G and C showed 202 more than GE At 046 EET in C was significantlyhigher than G at 035 Air temperature and the vapor pressure deficit were closely correlated with variation in diurnal ET E andT The leaf area index (LAI) was also positively correlated with daily ET and E varied among grassland use patterns and explainedvariation in EET (81) Thus variation in LAI strongly influences the overall magnitude of ecosystem ET and the composition ofits components under different grassland use patterns

1 Introduction

Large-scale changes in land use are strongly connected toglobal climate change [1ndash3] In recent years changes in landuse patterns in large areas of grassland in Northern China[4] have altered surface vegetation cover [5] and as a resultsignificantly influenced the ecosystem and regional environ-ment [6] Grazed steppe covers the majority of grasslandarea in the European-Asian continent [7] InNorthernChinagrazing by livestock has long been the major anthropogenicinfluence on the temperate grassland ecosystem In recentyears however grassland destruction by sandstorms hasincreased environmental protection awareness and govern-ment input for grassland restoration in China resulting in arapid increase in steppe area where grazing is excluded [1]In contrast in response to crop-planting limits and the need

for economic benefit a large grassland area in the pastoral-farming ecotone of the steppe in China has been convertedto cropland [8] By altering vegetation original soil structureandmicroclimate changes in grassland usemay affect overallecosystem evapotranspiration (ET) as well as its componentssoil surface evaporation by vapor loss (E) and canopy vaporconsumption by transpiration (T)These processes contributeto carbon uptake [9]

Water is a critical limiting factor in arid and semiaridgrassland area inNorthernChina and influences productivityand regional climate [10 11] ET is related to a number ofecosystemprocesses including photosynthesis soilmoistureand latent heat transfer [12] and plays an important rolein global energy and water cycles [8] The magnitude anddynamics of ET differ with changes in vegetation traits mete-orological conditions and soil characteristics [13] Therefore

Hindawi Publishing CorporationAdvances in MeteorologyVolume 2015 Article ID 452603 12 pageshttpdxdoiorg1011552015452603

2 Advances in Meteorology

it is important to investigate how change in grassland usepatterns in the Northern China steppe has altered localvapor budget and water balances thereby influencing naturalecological functions in these grasslands [14 15] and impactingregional climate

Previous work on ET has been conducted primarily usingthe eddy covariance system [15ndash17] and the lysimeter [18]The eddy covariance system can record ET automaticallyover long durations but because of its whole-ecosystem scale[19] it is difficult to distinguish differences in water fluxamong local sites This problem can be resolved by usinga chamber attached to a portable infrared analyzer [20ndash22] which is more suitable for measuring flux of adjacentplots Thus it can be used to determine the influence of theland use type on water exchange within an ecosystem Inaddition few previous studies have correctly divided ET intosoil evaporation (E) and transpiration (T) [8] resulting indifficulty uncovering underlying mechanisms of variation inET [23 24] However with a fine treatment such as clippingportable infrared gas analyzers measured the contributionof E to total ET [25] Measuring the components of ET (Eand T) is key not only to understand mechanisms underlyingvariation in ecosystem ET with grassland use patterns [23]but also to help resolve uncertainties in modeling simulationof ET or latent heat and thereby to increase simulationprecision [25 26]

We used herbicide rather than clipping and removingthe vegetation to more accurately divide ecosystem ET intocanopy T and surface E as killing the vegetation withherbicide leaves the structure intact largely maintainingthe original level of shading Specifically we aimed to (i)understand the effect of the varied grassland use patterns onthe components of ET and the daily vapor transfer betweenthe ecosystem and the atmosphere and (ii) investigate themechanisms underlying changes in ET and its compositionamong different grassland use patterns in the steppe

2 Materials and Methods

21 Study Area This study was conducted on Stipa grandisa dominant grass of the temperate steppe at Xilinhot InnerMongolia Northern China (43∘321015840240610158401015840N 116∘331015840417610158401015840Eelevation 1250m) The study site is located at 500 km northto Beijing and is considered as an important sand sourceof Beijing (Figure 1) Between 1982 and 2004 mean annualtemperature was 06∘C and mean monthly temperatureranged from minus214∘C (January) to 185∘C (July) [20] Meanannual precipitation was 350mmmainly falling from June toAugust during themain growth periodTheweather ismainlydry and windy and the soils are chestnut or chernozemsoil Data of the main meteorological parameters during theexperimental period (August 2012) are shown in Figure 2

22 Observation Design Three types of land use in adjacentareas were selected for study grazed steppe (G) steppe withgrazers excluded (GE) and steppe cultivated to cropland (C)G is a typical steppe that has been grazed by sheep andhorses for more than 20 years GE is steppe where herbivores

0 290

580

1160

(km)

N

Study sitePastoral-farming ecotone

XilinhotBeijing

Figure 1 The location of the study area and the pastoral-farmingecotone in Northern China

0

10

20

30

40

0

100

200

300)

Aug 1 Aug 6 Aug 11 Aug 16 Aug 21 Aug 26 Aug 31

Precipitation

Date

Prec

ipita

tion

(mm

) AT

(∘C)

TmaxTmin

Ta

Rn

Rn

(Wm

2)

Figure 2 Daily precipitation air temperature (119879119886

daily mean119879max daily maximum 119879min daily minimum) and net radiation (119877

119899

)during the experimental period from 1 August to 31 August 2012 ina typical temperate steppe at Xilinhot Inner Mongolia

have been excluded since 1979 and a large amount of plantlitter remains on the ground The original land use andcommunity structure of C were similar to G until 5 yearsprior to the study when the land was cultivated for wheatcropping No irrigation is applied to cropped areas Organicmanure was applied prior to crop planting and 240 kg hmminus2effective fertilizer (N 110 kgha P

2

O5

70 kgha and K2

O60 kgha)was applied in two applications during crop growthAt the center of the grazed steppe (G) (43∘321015840240610158401015840N116∘331015840417610158401015840E) an eddy covariance system was set up tomeasure the water carbon and heat exchange between the

Advances in Meteorology 3

Table 1 Microclimate characteristics of land use types (LT) and vegetation cover treatments (TR)

LTTr ST (∘C) SM () AT (∘C) VPDG

DS 2068 plusmn 081a 2198 plusmn 081a 2184 plusmn 100a 172 plusmn 014a

CL 2094 plusmn 037a 2134 plusmn 078a 2189 plusmn 102a 178 plusmn 016a

CK 1982 plusmn 071ab 2191 plusmn 079a 2179 plusmn 102a 168 plusmn 013a

GEDS 1769 plusmn 055bc 2610 plusmn 056bc 2171 plusmn 105a 176 plusmn 016a

CL 1847 plusmn 032b 2283 plusmn 067ab 2201 plusmn 108a 181 plusmn 016a

CK 1725 plusmn 046c 2441 plusmn 030b 2163 plusmn 097a 168 plusmn 014a

CDS 1876 plusmn 026abc 2709 plusmn 051c 2315 plusmn 089a 129 plusmn 014a

CL 2055 plusmn 037a 2423 plusmn 044b 2339 plusmn 090a 128 plusmn 014a

CK 1817 plusmn 042bc 2633 plusmn 014c 2309 plusmn 086a 122 plusmn 013a

Different letters in the same column indicate statistical differences at 119875 lt 005 ST soil temperature SM soil moisture AT air temperature VPD vapor deficitCK control DS dry standing Cl clipped

ecosystem and atmosphere The flux tower was positionedmore than 800m from the boundaries of GE and C

The study area was set up using a randomized blockdesignWithin each type of land use there were four replicateblocks (35m times 35m with 5m space between blocks) Four1m times 1m plots were randomly arranged within each blockwith 15m between plots Two weeks before observationbegan one plot in each block (DS)was randomly selected andsprayed with herbicide (41 glyphosate diluted with water150 times) All vegetation in these plots withered in 2 daysbut the canopy remained standing and dry throughout theobservation period Another plot in each block (CL) waschosen in which the aboveground tissue was removed byclipping following the procedure used in previous studies[20 23] The third randomly selected plot in each blockserved as the control plot (CK) to which no further treatmentwas administered The fourth plot was used for destructivesampling to determine the community characteristics of eachblock including abovebelowground biomass leaf area index(LAI) and soil properties

For determination of ET we found that the herbicidemethod (DS) resulted in shading and surface roughnessmore similar to the control plots (CK) than the commonlyused clipping method [20 23] (CL) providing more realisticevaporation and microclimate conditions Thus the DSmethodprovides amore accurate determination of ecosystemE consequently improving the accuracy of separating T fromET This method assumes that transpiration in herbicide-sprayed plots (DS) was completely suppressed by witheringof all living plant tissues Thus vapor exchange in DS plotswould mainly come from earth surface evaporation (E)Plant transpiration (T) was calculated by subtracting E inthe DS treatment from ET in the control Of the differentobservational methods to partition the components of soilevaporation (E) and canopy transpiration (T) from ecosystemET our approach appears to be the most accurate as itdisturbs the original environmental conditions the least(Table 1) and avoids the influence of air advection or largeeddies [15 18 23]

23 Vapor Flux Measurements Two weeks before observa-tions began a square metal base rim (50 cm times 50 cm inarea 10 cm in height with 3 cm aboveground) was installedin each of the three types of observed plot (CK CL andDS) for the measurement of the vapor exchange rate Thevapor exchange rate was determined by a cubic chamber(50 cm times 50 cm times 50 cm) attached to an infrared gas analyzer(IRGA LI-6400 LiCor Lincoln NE USA) When measure-ments commenced thirty consecutive recordings of vaporconcentrations were taken for each placed chamber at 1 sintervals during 30 s periods H

2

O flux rates were calculatedfrom the time courses of changing concentrationsThe fluxesof E were directly determined in the treatments of DS andthe fluxes of ET were determined in CK plots This static-chamber method has been used and validated in previousstudies [23] One temperature probe at the center measuredair temperature (AT) and another pushed into the soil asidethe chamber measured soil temperature (ST) at 5 cm depthThe soil moisture (SM) was measured with a portable soilmoisture device (TDR100 Spectrum Plainfield IL USA)

The water exchange ET and E rates were calculated basedon the formula [20 23]

119865ℎ

=1000119881119875av119877119878 (119879av + 273)

times119889119888

119889119905 (1)

where 119865ℎ

is H2

O flux (mmolmminus2 sminus1 positive 119865ℎ

valuesrepresent ecosystem vapor release and negative representvapor condensation) 119881 is the chamber volume (m3) 119875avis the average pressure (kPa) 119877 is the ideal gas constant(8314 Jmolminus1 Kminus1) S is the surface area covered by chamber(m2)119879av is the average temperature (∘C) during themeasure-ment and 119889119888119889119905 is the slope of linear least squares regressionof H2

O concentration by timeThe transpiration rate (T) was calculated by the difference

between ET and ET = ET minus E (2)

Observations were conducted on clear sunny days duringthe peak in live grassland biomass (August) Observations


Table 2 Community characteristics of the three land uses

Use pattern Grazing (G) Grazing exclusion (GE) Cultivation to cropland (C)Constructive species Stipa grandis Stipa grandis Triticum aestivumAverage cover () 563 plusmn 24a 950 plusmn 20b 938 plusmn 125b

Average height (cm) 1475 plusmn 095a 5625 plusmn 554b 890 plusmn 129c

Soil organic carbon (gkg) 1198 plusmn 173a 1510 plusmn 189b 1977 plusmn 105c

Soil bulk density (gcm3) 163 plusmn 002a 137 plusmn 006b 129 plusmn 002b

Leaf area index (LAI) 042 plusmn 003a 068 plusmn 005a 133 plusmn 013b

Total biomass (kg lowast sminus1) 204 plusmn 014a 301 plusmn 138b 102 plusmn 006c

Aboveunderground biomass () 373 plusmn 020a 595 plusmn 029b 6450 plusmn 224c

C4 total biomass () 3298 plusmn 170a 610 plusmn 226b 0c

Litter fall (gm2) 160 plusmn 055a 8481 plusmn 447b 1098 plusmn 100c

Species abundance (S) 725 plusmn 063a 400 plusmn 041b 225 plusmn 025c

Mean plusmn standard the different letters in the same row signify significant changes between them (119875 lt 005)

were conducted continuously through the day at 1-hourintervals over 12 days During each day measurements weretaken within one land use type to ensure similar weatherconditions within an ecosystem to maintain comparability ofdata Thus each land use or ecosystem type (C G and GE)had 4 replicate days of observation

Daily vapor exchange (E T and ET) in each of the threeecosystems was calculated from the H

2

O flux rates obtainedwith the portable infrared gas analyzers using the followingequation

Daily water exchange = int2400

000

119865ℎ

lowast 18 lowast 10minus6

(kg H2

O)

(3)

where 119865ℎ

is the H2


valuesrepresent ecosystem vapor release and negative values repre-sent vapor uptake)

24 Measurement of Community Characteristics Speciescomposition average height and plant cover were measuredin the 12 observational plots in each of the three differentland uses of steppe (G GE and C) Aboveground biomasswas measured with the clipping method and undergroundbiomass was measured with the root drill method [4] LAIwas measured using the method proposed by Miao et al [8]

25 Data Analysis Origin 80 was used for figure drawingand SPSS 120 was used for data analysis Three one-wayANOVAs followed by Duncan tests were used to analyze thedifferences of ecosystem microclimates and community andsoil characteristics among the three land uses Paired 119905-testscompared the diurnal dynamics of ecosystem vapor exchangewithin each of the three types of land use One-way ANOVAsand Duncan tests analyzed the mean daily accumulated ET and ET among the three land uses Linear regressionanalysis compared the consistency of ET measurementsbetween the eddy covariance systemand the portable infraredchamber method Linear regression analysis was used toevaluate the relationships of ET and its composition EET onenvironmental factors

3 Results

31 Microclimate and Community Characteristics of Land UseTypes Soil temperature of G was significantly higher thanthat of GE At 25 less than GE and 442 less than C G hadthe lowest soil moisture (Table 1) Land use also significantlyaffected soil condition but had little effect on aerial micro-climate factors including temperature and VPD Clippingdid not cause marked microclimate change in G blocks butin GE and C blocks CL plots had increased temperaturesand reduced soil moisture relative to CK plots (Table 1)There were no significant differences of microclimate factorsbetween paired DS and CK plots

Land use pattern substantially influenced the grasslandcommunity characteristics Total biomass in C and G wassignificantly lower than inGE (Table 2)Theproportion of theaboveground biomass and biomass of C4 plants also variedsignificantly among the three types of land use (Table 2)Litter fall was significantly higher in GE than in G or C TheLAI was the lowest in G with 300 higher LAI in C and62 higher in GE (Table 2) The influence of land use onsoil properties was visible in the soil organic carbon (Table 2119875 lt 005) and bulk density

32 Components of ET in Response to Different Land UsesThe daily dynamics of E T and ET among the differentland uses of grassland steppe were generally represented bya unimodal curve that peaked around midday (Figures 3(a)ndash3(c)) although a minor midday depression in T (Figure 3(b))may have driven a similar trend in ET (Figure 3(c))

GE and C both tend to increase the average daily ETof the grazed steppe which was 330 kgmminus2 dminus1 (Figure 4)Cultivation significantly increased ecosystem ET 134 overthat of grazed steppe (374 kgmminus2 dminus1 119875 lt 005) whereas thechange in grazing exclusion (352 kgmminus2 dminus1 119875 lt 005) wasnot significant

Land use type did not significantly affect T (119875 gt 005)but increased rates of E relative to C in G and GE (243and 402 resp) (119875 lt 005) Consequently variation in Ewas the driving cause of differences in ET among the threegrassland uses (Figures 3(a) and 4(a)) The proportion of


0

1

2

3

0000 0600 1200 1800 2400Time

E(m

mol

mminus2

sminus1)

(a)

0

1

2

3

4

5

6

0000 0600 1200 1800 2400Time

T(m

mol

mminus2

sminus1)

(b)

0000 0600 1200 1800 2400012345678

Time

ET (m

mol

mminus2

sminus1)

CGEG

(c)

Figure 3 Daily dynamics of vapor exchange composition ofdifferent land uses during the peak growing period (a) Evaporation(E) (b) transpiration (T) (c) evapotranspiration (ET) Error bar was1 SE G grazing GE grazing excluded C crop

evaporation to total vapor consumption (EET Figure 4) of Cwas significantly increased in comparison with G (119875 lt 005)

33 Relationships between Components of ET and Microcli-mate Factors The components (E T) of total ecosystemvapor consumption (ET) were significantly correlated withAT and VPD among different grassland uses (Figures 5(a)ndash5(f) 119875 lt 0001) AT explained a large proportion ofthe variance in ET among the types of steppe land uses(Figure 5(a) 81ndash83)

Variation among the grassland uses in sensitivity of thecomponents of ET to microclimate factors was reflected by

E T ET EET0

2

4

baba

baba

aaac

ab

Components of ecosystem vapour exchange

GGEC

00

03

06

09

EET

Mea

n da

ily v

apou

r exc

hang

e(k

gH

2O m

minus2

d)

Figure 4 Compositions of mean daily ecosystem vapor consump-tion (E T ET and EET) for different steppe grassland uses Thevalues represent the daily mean values (means plusmn 1 SE) in thepeak growing period Different letters in each bar group indicatesignificant difference (119875 lt 005) G grazing GE grazing excludedC crop

differences in their regression slopes The sensitivity of Tto VPD (Figure 5(f) 014ndash016) and AT (Figure 5(c) 120ndash131) did not differ substantially among the three land usesHowever crop cultivation increased the sensitivity of E to ATby 160 relative to grazed steppe (Figure 5(b)) Moreover inGE andCplots the slope of the regression of E toVPDwas 14and 33 times that of grazed plots respectively (Figure 5(e))The differential sensitivity of E led to a variable overallresponse of ET to VPD and AT among the three grasslanduses ET responded more strongly to AT (Figure 5(a)) andVPD (Figure 5(d)) in cultivated plots than grazed or grazerexclusion plots

34 Relationships between Components of ET and CommunityTraits Variation in each of the community traits (above-ground biomass LAI soil bulk density and mean soil mois-ture) was significantly linearly correlated with mean dailyvapor consumption by E and ET among different patternsof grassland use (Figure 6 all 119875 lt 001) In particular alarge proportion of the variance in both ET and E wereexplained by LAI (78ndash87) and soil moisture (89ndash90)Trends of linear correlation between ET and biomass LAIsoil bulk density and soil moisture were consistent with thoseof E There were no significant relationships between T andaboveground biomass LAI soil bulk density or soil moisture(Figure 6 119875 gt 005)

35 Mechanisms Underlying Variance in EET among SteppeGrassland Uses Linear correlations between mean dailyvapor consumption and mean daily EET were significantfor both E (Figure 7(a) 119875 lt 0001) and T (Figure 7(b)119875 lt 005) though the relationship was stronger for EAdditionally mean daily water consumption by E explained


10 20 30 40Air temperature (∘C)

0

3

6

9

12ET

(mm

ol m

minus2

sminus1)

G slope = 022 R2 = 081lowastlowastlowast

GE slope = 020 R2 = 083lowastlowastlowast

C slope = 031 R2 = 082lowastlowastlowast

GGE

C

(a)

0

2

4

6


E(m

mol

mminus2

sminus1) G slope = 005 R2 = 064lowastlowastlowast

C slope = 013 R2 = 077lowastlowastlowast= 007 R2 = 069lowastlowastlowastGE slope

GGE

C

(b)

0

3

6


T(m

mol

mminus2

sminus1)




GGE

C

(c)

0 2 4VPD (kPa)

0

3

6

9

12

ET (m

mol

mminus2

sminus1)




GGE

C

(d)

0 2 4VPD (kPa)

0

2

4

6E

(mm

ol m

minus2

sminus1)




GGE

C

(e)

0 2 4VPD (kPa)

0

3

6

T(m

mol

mminus2

sminus1)

G slope = 120 R2 = 082

GE slope = 125 R2 = 079

C slope = 131 R2 = 060

GGE

C

(f)

10 20 30Soil temperature (∘C)

0

3

6

9

12

ET (m

mol

mminus2

sminus1)




GGE

C

(g)

10 20 30

0

2

4

6

E(m

mol

mminus2

sminus1)




GGE

CSoil temperature (∘C)

(h)

10 20 30

0

3

6

T(m

mol

mminus2

sminus1)



C slope = 014 R2 = 005lowastlowast

GGE


(i)

20 30

0

3

6

9

12

ET (m

mol

mminus2

sminus1)

Gand

GEand

Cand

Soil moisture (vv)GGE

C

(j)

20 30

0

2

4

6

E(m

mol

mminus2

sminus1)

G slope = 003 R2 = 003lowast

GE slope = 004 R2 = 003lowast

Cand

Soil moisture (vv)

GGE

C

(k)

20 30

0

3

6

T(m

mol

mminus2

sminus1) Gand

GEand

Cand


C

(l)

Figure 5 Relationships between microclimate factors (AT VPD ST and SM) on vapor exchange rates (ET E and T) across the three landuses of steppe R2 and probabilities of regressions are shown and119875 gt 005 lowast119875 lt 005 lowastlowast119875 lt 001 lowastlowastlowast119875 lt 0001 G grazing GE grazingexcluded C crop


30

35

40

Mea

n da

ily E

T (m

m)

0 200 400 600 800

R2 = 064lowastlowast

C

GEG

Aboveground biomass (g mminus2)

(a)

10

15

20

25

0 200 400 600 800M

ean

daily

E (m

m)


R2 = 082lowastlowastlowast

C

GEG

(b)

0 200 400 600 800

15

20

25

Mea

n da

ilyT

(mm

)

C

GEG

R2 = 004and


(c)

30

35

40

Mea

n da

ily E

T (m

m)

05 10 15LAI


C

GEG

(d)

10

15

20

25

05 10 15LAI

Mea

n da

ily E

(mm

)


C

GEG

(e)

05 10 15LAI

15

20

25

Mea

n da

ilyT

(mm

)

R2 = 009and

C

GEG

(f)

12 14 16 18

C

GEG

Soil bulk density (g cmminus3)

R2 = 087lowastlowastlowast30

35

40

Mea

n da

ily E

T (m

m)

(g)

12 14 16 18

10

15

20

25

C

GEG

Mea

n da

ily E

(mm

)



(h)

12 14 16 18

C

GEG

15

20

25

Mea

n da

ilyT

(mm

)


R2 = 017and

(i)

Figure 6 Continued


Mea

n da

ily E

T (m

m)

30

35

40

C

GEG

21 24 27


Mean daily soil moisture (vv)

(j)

C

GEG

10

15

20

25

Mea

n da

ily E

(mm

)


21 24 27Mean daily soil moisture (vv)

(k)

C

GEG

15

20

25

Mea

n da

ilyT

(mm

)

R2 = 008and


(l)

Figure 6 Relationships between mean daily water consumption components (E T and ET) on aboveground biomass leaf area index (LAI)soil bulk density and soil moisture across the three different steppe land uses Error bar in WUE was 1 SE R2 and probabilities of regressionsare shown and119875 gt 005 lowast119875 lt 005 lowastlowast119875 lt 001 lowastlowastlowast119875 lt 0001 G grazing GE grazing excluded C crop

three times more variance in EET than T (90 versus30) LAI (Figure 7(c)) and soil moisture (Figure 7(d)) werealso positively correlated with EET while the relationshipbetween LAI and soil moisture depended on the level ofLAI When LAI was less than 1 soil moisture was positivelylinearly correlated with LAI but values of LAI larger than 1did not stimulate corresponding increases in soil moisture(Figure 7(e))

4 Discussion

41 Effect of Grassland Use Types on the Components ofET Because ecosystem ET takes away heat from the earthsurface through latent heat transport variation in ET withdifferent grassland uses may alter the energy budget andconsequently affect the regional climate [8] ET rates deter-mined by converted latent heat measurements taken bythe eddy covariance system were highly correlated with ETrates measured using the chamber method (Figure 8 119875 lt001) confirming the reliability of chamber-measured vaporexchange rates In addition our measurements of ET rates inthe three different patterns of grassland use were comparableto relevant previous work and modeled data for adjacentareas [1 8 26] Though the chamber-measured ET rates werehighly correlated with eddy covariancemethods yet there areuncertainties which are caused by the measurement devicesin ET compositions (E and T) The certain deviation in thismethod is due to the chamber Since the chamber blocked thenatural wind this should cause underestimate of surface Eand lead to a certain overestimate of T rates

Previous research has shown that different land usescan significantly change community structure [27 28] soilproperties [29 30] and microclimate conditions [31ndash33]which may be correlated with ecosystem vapor exchange

[34ndash37] Consistent with this previous work [8 24] ourstudy demonstrated that cultivation and exclusion of grazingincreased ET the total vapor consumption of an ecosys-tem Our examination of the individual components of ETrevealed that it was evaporation (Figure 4 119875 lt 005) nottranspiration (Figure 4 119875 gt 005) that caused the variancein ET among the different land uses of the steppe (Figure 4Figure 6) Although few previous experimental studies ingrassland ecosystems have separated ET into E and T [25]a study doing so in an agricultural ecosystem also found thatchanges in E were more important than those in T in drivingpatterns of ET among different crop species [24]

Despite the suggestion of previous large-scale studiesincluding cross regional simulations [26 37] and long-termobservations [8] that vegetation with higher LAI shouldhave lower EET our findings corroborated those of anotherregional study [24] showing that EET was higher in landuse types with higher LAI in adjacent areas (Figure 4) Thesecontrasting results demonstrate that the components of ETmay respond variably to increases in LAI depending onthe spatial and temporal scale of the study The positiverelationship between EET and LAI in our study (Figure 7(c))may be owing to the shading effect of redundant LAI Duringthe peak growing season when LAI reaches its maximuman individual plant in any grassland use type has redundantleaves which are shaded by those newer and higher leavesof its own Thus in those land uses with higher LAI theincrease of LAI just enhanced the shading ineffective leaveswould not contribute substantially to an increase in canopyT In contrast increased shading in communities with alarger LAI would result in higher soil moisture In arid andsemiarid areas where water supply is a limiting factor of E[26] increased soil moisture would stimulate higher rates ofsurface E


09 12 15 18 21

03

04

05

Mea

n da

ily E

ET

Mean daily E (mm)


(a)

15 18 21 24

03

04

05

Mea

n da

ily E

ET

Mean daily T (mm)

R2 = 030lowast

(b)

04 08 12 16

03

04

05

Mea

n da

ily E

ET

LAI


(c)

20 22 24 26 28

03

04

05

Mea

n da

ily E

ET



(d)

21

24

27

05 10 15LAI

Slope = 1034


Slope = 067

R2 = 085and

Mea

n da

ily so

il m

oistu

re (v

v

)

(e)

Figure 7 Relationships between mean daily EET and mean daily (a) E (b) T (c) LAI and (d) soil moisture and (e) the relationship betweenLAI and mean daily soil moisture and119875 gt 005 lowast119875 lt 005 lowastlowast119875 lt 001 lowastlowastlowast119875 lt 0001


0 2 4 6 8 10

0

2

4

6

8

10Ch

ambe

r-m

easu

red

ET (m

mol

mminus2

sminus1 )

Eddy covariance measured ET (mmol mminus2 sminus1)

y = 094x minus 018 (P lt 001)

R2 = 092 n = 88

Figure 8 Comparison of the ecosystem vapor exchange (ET)obtained by the chamber method and the eddy covariance systemData were obtained from the eddy covariance system located in thecenter of grazed grassland (G)

Relative to grazed areas grazer exclusion and cultivationboth tended to increase ecosystem ET (Figure 4) which facil-itates water transfer from the grassland to the atmosphereDespite similar effects on ET these two patterns of grasslanduse (GE C) may have differing effects on regional climateElevated rates of ET would increase regional precipitationin both types of systems but the larger mass of accumu-lated litter in grasslands with grazers excluded (Table 2)would increase rainfall absorption and infiltration reducingwater loss by overflow and evaporation In contrast withoutaccumulated litter (Table 2) lower rainfall infiltration incultivated steppe [8] would reduce ground water supplemen-tation and ground water may eventually be exhausted byelevated vapor loss (Figure 4) Thus long-term cultivation ofsteppe may intensify drought and cause damage to regionalground water stores whereas grazer exclusion may increasesoil moisture content sustainably with corresponding effectson regional climate through increased precipitation andhumidity

42 Factors Driving the Variation of Components of ET amongPatterns of Grassland Use In arid and semiarid areas soilwater content is a key factor controlling vapor loss [823] and previous studies have shown that soil moisture isclosely related to ET and E [20 23 31] Similarly in thisstudy variation in soil moisture among different land usesexplained 90 and 89 of the mean daily ET (Figure 6(j))and E (Figure 6(k)) respectively Additionally we foundthat soil moisture variation among patterns of grassland usemay be caused by changes in LAI with land use (Table 2)This was demonstrated by strong positive relationships ofLAI and soil moisture (Figure 7(e)) where LAI explained95 of soil moisture variation and may also underliethe close correlations of LAI with ET (Figure 6(d)) and E(Figure 6(e)) Furthermore significant relationships of ETandEwith abovegroundbiomass and soil bulk densitymay be

because these community traits are inherently related to LAI(Figure 6) In contrast to previous work conducted on largespatial and temporal scales [26 31] we found no significantrelationships between LAI and T (Figure 6(f)) Comparisonof these studies with our work and similar findings in anagricultural system [24] suggest that the influence of LAI onvapor consumption may vary with scale

Few studies have been conducted on the daily dynamicsand controlling factors of ecosystem ET and its componentsAt the large spatial and temporal scale evidence suggests thatchange in ET may be closely related to some microclimatefactors and soil traits such as VPD air temperature soiltemperature and soil moisture [23 26 31] Consistent withprevious conclusions we found thatVPDand air temperaturewere significantly related to ET E and T (Figure 5) Inparticular AT explained 80 of the variation in ET ratesamong varied land uses (Figure 5(a)) However unlike previ-ous studies [23 31] changes in soil temperature andmoisturewere not correlated with E and T (Figure 5) Instead wesuggest that soil moisture may contribute to vapor exchangeregulation indirectly Since soil water supply ability varieswith soil moisture we assumed that soil moisture may be theprimary factor controlling the regression slope of E and ETwith AT and VPD under different grassland use patterns

EET the contribution of E (rather than T) to totalecosystem vapor consumption (ET) [24 38] is an importanttrait of water vapor exchange and the ecosystem in general[39] Measurements of EET in this study (approximately 04Figure 4) were comparable with those obtained by modeling[37] and experimental observation [31] in similar ecosystemsVariation in mean daily E (Figure 7(a)) and T (Figure 7(b))both significantly affected EET although E explained threetimes more variation in EET than T Thus variation insurface vapor consumption (E) was more important incontrolling patterns of EET among grassland use typesMoreover because soil moisture directly regulates E [10]soil moisture was also significantly positively related to EET(Figure 7(d)) Finally change in LAI with varying patternsof land use was a significant predictor of soil moisture(Figure 7(e)) which is similar to Xu et alrsquos result [32]Consequently LAI explained 81 of the variation in EET(Figure 7(c)) These results corroborate the conclusions of aprevious modeling study [26] that LAI is a primary commu-nity characteristic involved in regulation of the componentsof ecosystem ET

5 Conclusions

Land use changes in grasslands of temperate steppe ecosys-tems such as cultivation and grazing exclusion may signifi-cantly influence vegetation and soil properties as well as somemicroclimate factors Thus variation in grassland use mayhave large effects on the vapor budget Our results indicatedthat grassland cultivation and grazing exclusion both tendto increase ecosystem ET with a significant increase in cul-tivated steppe Differential litter accumulation and resultantinfiltration of rainfall to ground water among grassland usessuggest that large-scale cultivationmay intensify aridity of the


steppe area in Northern China while the grazing exclusionmay gradually alleviate local arid conditions Division of ETinto its components indicated that changes in ET in cultivatedand grazer excluded grassland were primarily caused byelevated E while T did not increase significantly Throughshading variation in LAI with land use type substantiallyinfluenced the soil moisture thus acting as a key regulatorof E and even ET and EET in the ecosystem ConsequentlyLAI is the primary regulating factor of the magnitude andcomposition of grassland-atmosphere vapor exchange underdifferent grassland uses These observed results would helpreduce the uncertainty of relevant models in simulatingET and the surface energy budget and provide significantreference for the land usemanagement to alleviate the climatechange

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

Acknowledgments

This research was jointly funded by the State Key Technolo-gies RampD Program (Grant no 2013BAC03B04) the NaturalSciences Foundation of China (41301043) the Funding forTalent Young Scientists of IGSNRR (2013RC203) and theNational ldquo973rdquo Project (no 2010CB950902) In addition theauthors thank Dr Ning Jia for her help in improving theirfigures as well as the editor and two anonymous reviewers fortheir constructive comments which helped them to improvethe paper

References

[1] S Chen J Chen G Lin et al ldquoEnergy balance and partitionin Inner Mongolia steppe ecosystems with different land usetypesrdquo Agricultural and Forest Meteorology vol 149 no 11 pp1800ndash1809 2009

[2] IPCC Climate Change 2007 The Physical Science Basis Contri-bution of Working Group I to the Fourth Assessment Reportof the Intergovernmental Panel on Climate Change edited byS Solomon D Qin M Manning Z Chen M Marquis K BAveryt M Tignor and H L Mille Cambridge University PressCambridge UK 2007

[3] J Liu M Liu D Zhuang Z Zhang and X Deng ldquoStudy onspatial pattern of land-use change in China during 1995ndash2000rdquoScience in China Series D Earth Sciences vol 46 no 4 pp 373ndash384 2003

[4] Y-Z Li J-W Fan L-X Zhang J Di G-F Liu and J Li ldquoTheimpact of different land use and management on communitycomposition species diversity and productivity in a typicaltemperate grasslandrdquoActa Pratacultuae Sinica vol 22 no 1 pp1ndash9 2013

[5] L Jiyuan and B Aoser ldquoStudy on spatial-temporal featureof modern land use change in China using remote sensingtechniquesrdquo Quaternary Sciences vol 20 no 3 pp 229ndash2392000

[6] W Tao ldquoLand use and sandy desertification in the northChinardquoJournal of Desert Research vol 20 no 2 pp 103ndash107 2000

[7] R Lal ldquoLand use and soil management effects on soil organicmatter dynamics on Alfisols in Western Nigeriardquo in Soil Pro-cesses and the Carbon Cycle pp 109ndash126 CRC Press BocaRaton Fla USA 1997

[8] HMiao S Chen J Chen et al ldquoCultivation and grazing alteredevapotranspiration and dynamics in Inner Mongolia steppesrdquoAgricultural and Forest Meteorology vol 149 no 11 pp 1810ndash1819 2009

[9] J M Wraith D A Johnson R J Hanks and D V SissonldquoSoil and plant water relations in a crested wheatgrass pastureresponse to spring grazing by cattlerdquo Oecologia vol 73 no 4pp 573ndash578 1987

[10] W Bai S Wan S Niu et al ldquoIncreased temperature and pre-cipitation interact to affect root production mortality andturnover in a temperate steppe implications for ecosystem Ccyclingrdquo Global Change Biology vol 16 no 4 pp 1306ndash13162010

[11] Y Bai J Wu Q Xing et al ldquoPrimary production and rainuse efficiency across a precipitation gradient on the Mongoliaplateaurdquo Ecology vol 89 no 8 pp 2140ndash2153 2008

[12] L A Wever L B Flanagan and P J Carlson ldquoSeasonal andinterannual variation in evapotranspiration energy balanceand surface conductance in a northern temperate grasslandrdquoAgricultural and Forest Meteorology vol 112 no 1 pp 31ndash492002

[13] D D Baldocchi L Xu and N Kiang ldquoHow plant functional-type weather seasonal drought and soil physical propertiesalter water and energy fluxes of an oak-grass savanna and anannual grasslandrdquo Agricultural and Forest Meteorology vol 123no 1-2 pp 13ndash39 2004

[14] D J Bremer L M Auen J M Ham and C E OwensbyldquoEvapotranspiration in a prairie ecosystem effects of grazing bycattlerdquo Agronomy Journal vol 93 no 2 pp 338ndash348 2001

[15] D G Williams W Cable K Hultine et al ldquoEvapotranspirationcomponents determined by stable isotope sap flow and eddycovariance techniquesrdquo Agricultural and Forest Meteorologyvol 125 no 3-4 pp 241ndash258 2004

[16] L B Hutley A P OrsquoGrady and D Eamus ldquoMonsoonal influ-ences on evapotranspiration of savanna vegetation of northernAustraliardquo Oecologia vol 126 no 3 pp 434ndash443 2001

[17] J F Reynolds P R Kemp and J D Tenhunen ldquoEffects of long-term rainfall variability on evapotranspiration and soil waterdistribution in the Chihuahuan Desert a modeling analysisrdquoPlant Ecology vol 150 no 1-2 pp 145ndash159 2000

[18] C Liu X Zhang and Y Zhang ldquoDetermination of dailyevaporation and evapotranspiration of winter wheat and maizeby large-scale weighing lysimeter andmicro-lysimeterrdquoAgricul-tural and Forest Meteorology vol 111 no 2 pp 109ndash120 2002

[19] D D Baldocchi ldquoAssessing the eddy covariance technique forevaluating carbon dioxide exchange rates of ecosystems pastpresent and futurerdquoGlobal Change Biology vol 9 no 4 pp 479ndash492 2003

[20] S Chen G Lin J Huang and G D Jenerette ldquoDependence ofcarbon sequestration on the differential responses of ecosystemphotosynthesis and respiration to rain pulses in a semiaridstepperdquo Global Change Biology vol 15 no 10 pp 2450ndash24612009

[21] R L Scott T E Huxman W L Cable and W E EmmerichldquoPartitioning of evapotranspiration and its relation to carbondioxide exchange in a Chihuahuan Desert shrublandrdquo Hydro-logical Processes vol 20 no 15 pp 3227ndash3243 2006


[22] L B Flanagan E J Sharp and M G Letts ldquoResponse ofplant biomass and soil respiration to experimental warmingand precipitation manipulation in a Northern Great PlainsgrasslandrdquoAgricultural and Forest Meteorology vol 173 pp 40ndash52 2013

[23] S Niu X Xing Z Zhang et al ldquoWater-use efficiency inresponse to climate change from leaf to ecosystem in atemperate stepperdquoGlobal Change Biology vol 17 no 2 pp 1073ndash1082 2011

[24] P Beziat V Rivalland T Tallec et al ldquoEvaluation of a simpleapproach for crop evapotranspiration partitioning and analysisof the water budget distribution for several crop speciesrdquoAgricultural and Forest Meteorology vol 177 pp 46ndash56 2013

[25] D Kool N Agam N Lazarovitch J L Heitman T J Sauerand A Ben-Gal ldquoA review of approaches for evapotranspirationpartitioningrdquo Agricultural and Forest Meteorology vol 184 pp56ndash70 2014

[26] Z Hu G Yu Y Zhou et al ldquoPartitioning of evapotranspirationand its controls in four grassland ecosystems application ofa two-source modelrdquo Agricultural and Forest Meteorology vol149 no 9 pp 1410ndash1420 2009

[27] P Schonbach HWan M Gierus et al ldquoGrassland responses tograzing effects of grazing intensity and management system inan Inner Mongolian steppe ecosystemrdquo Plant and Soil vol 340no 1-2 pp 103ndash115 2011

[28] T A Day and J K Detling ldquoWater relations of Agropyronsmithii and Bouteloua gracilis and community evapotranspira-tion following long-term grazing by prairie dogsrdquoTheAmericanMidland Naturalist vol 132 no 2 pp 381ndash392 1994

[29] ANNunes A C deAlmeida andCO A Coelho ldquoImpacts ofland use and cover type on runoff and soil erosion in amarginalarea of Portugalrdquo Applied Geography vol 31 no 2 pp 687ndash6992011

[30] F Shi H Chen Y Wu and N Wu ldquoEffects of livestock exclu-sion on vegetation and soil properties under two topographichabitats in an alpine meadow on the eastern Qinghai-TibetanPlateaurdquo Polish Journal of Ecology vol 58 no 1 pp 125ndash1332010

[31] S NiuMWu YHan J Xia L Li and SWan ldquoWater-mediatedresponses of ecosystem carbon fluxes to climatic change in atemperate stepperdquo New Phytologist vol 177 no 1 pp 209ndash2192008

[32] X Xu R A Sherry S Niu D Li and Y Luo ldquoNet primaryproductivity and rain-use efficiency as affected by warmingaltered precipitation and clipping in a mixed-grass prairierdquoGlobal Change Biology vol 19 no 9 pp 2753ndash2764 2013

[33] S Niu H Yang Z Zhang et al ldquoNon-additive effects of waterand nitrogen addition on ecosystem carbon exchange in atemperate stepperdquo Ecosystems vol 12 no 6 pp 915ndash926 2009

[34] T F Keenan D Y Hollinger G Bohrer et al ldquoIncreasein forest water-use efficiency as atmospheric carbon dioxideconcentrations riserdquo Nature vol 499 no 7458 pp 324ndash3272013

[35] T E HuxmanM D Smith P A Fay et al ldquoConvergence acrossbiomes to a common rain-use efficiencyrdquo Nature vol 429 no6992 pp 651ndash654 2004

[36] A K Knapp and M D Smith ldquoVariation among biomesin temporal dynamics of aboveground primary productionrdquoScience vol 291 no 5503 pp 481ndash484 2001

[37] Z Hu G Yu Y Fu et al ldquoEffects of vegetation control onecosystemwater use efficiencywithin and among four grassland

ecosystems in Chinardquo Global Change Biology vol 14 no 7 pp1609ndash1619 2008

[38] W K Lauenroth and J B Bradford ldquoEcohydrology and thepartitioning AET between transpiration and evaporation in asemiarid stepperdquo Ecosystems vol 9 no 5 pp 756ndash767 2006

[39] C Brummer T A Black R S Jassal et al ldquoHow climate andvegetation type influence evapotranspiration and water use effi-ciency in Canadian forest peatland and grassland ecosystemsrdquoAgricultural and Forest Meteorology vol 153 pp 14ndash30 2012

Submit your manuscripts athttpwwwhindawicom

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

ClimatologyJournal of

EcologyInternational Journal of


EarthquakesJournal of


Hindawi Publishing Corporationhttpwwwhindawicom

Applied ampEnvironmentalSoil Science

Volume 2014

Mining


Journal of

Hindawi Publishing Corporation httpwwwhindawicom Volume 2014

International Journal of

Geophysics

OceanographyInternational Journal of


Journal of Computational Environmental SciencesHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Journal ofPetroleum Engineering


GeochemistryHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Journal of

Atmospheric SciencesInternational Journal of


OceanographyHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Advances in


MineralogyInternational Journal of


MeteorologyAdvances in

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Paleontology JournalHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

ScientificaHindawi Publishing Corporationhttpwwwhindawicom Volume 2014


Geological ResearchJournal of


Geology Advances in


it is important to investigate how change in grassland usepatterns in the Northern China steppe has altered localvapor budget and water balances thereby influencing naturalecological functions in these grasslands [14 15] and impactingregional climate

Previous work on ET has been conducted primarily usingthe eddy covariance system [15ndash17] and the lysimeter [18]The eddy covariance system can record ET automaticallyover long durations but because of its whole-ecosystem scale[19] it is difficult to distinguish differences in water fluxamong local sites This problem can be resolved by usinga chamber attached to a portable infrared analyzer [20ndash22] which is more suitable for measuring flux of adjacentplots Thus it can be used to determine the influence of theland use type on water exchange within an ecosystem Inaddition few previous studies have correctly divided ET intosoil evaporation (E) and transpiration (T) [8] resulting indifficulty uncovering underlying mechanisms of variation inET [23 24] However with a fine treatment such as clippingportable infrared gas analyzers measured the contributionof E to total ET [25] Measuring the components of ET (Eand T) is key not only to understand mechanisms underlyingvariation in ecosystem ET with grassland use patterns [23]but also to help resolve uncertainties in modeling simulationof ET or latent heat and thereby to increase simulationprecision [25 26]

We used herbicide rather than clipping and removingthe vegetation to more accurately divide ecosystem ET intocanopy T and surface E as killing the vegetation withherbicide leaves the structure intact largely maintainingthe original level of shading Specifically we aimed to (i)understand the effect of the varied grassland use patterns onthe components of ET and the daily vapor transfer betweenthe ecosystem and the atmosphere and (ii) investigate themechanisms underlying changes in ET and its compositionamong different grassland use patterns in the steppe

2 Materials and Methods

21 Study Area This study was conducted on Stipa grandisa dominant grass of the temperate steppe at Xilinhot InnerMongolia Northern China (43∘321015840240610158401015840N 116∘331015840417610158401015840Eelevation 1250m) The study site is located at 500 km northto Beijing and is considered as an important sand sourceof Beijing (Figure 1) Between 1982 and 2004 mean annualtemperature was 06∘C and mean monthly temperatureranged from minus214∘C (January) to 185∘C (July) [20] Meanannual precipitation was 350mmmainly falling from June toAugust during themain growth periodTheweather ismainlydry and windy and the soils are chestnut or chernozemsoil Data of the main meteorological parameters during theexperimental period (August 2012) are shown in Figure 2

22 Observation Design Three types of land use in adjacentareas were selected for study grazed steppe (G) steppe withgrazers excluded (GE) and steppe cultivated to cropland (C)G is a typical steppe that has been grazed by sheep andhorses for more than 20 years GE is steppe where herbivores

0 290

580

1160

(km)

N

Study sitePastoral-farming ecotone

XilinhotBeijing

Figure 1 The location of the study area and the pastoral-farmingecotone in Northern China

0

10

20

30

40

0

100

200

300)

Aug 1 Aug 6 Aug 11 Aug 16 Aug 21 Aug 26 Aug 31

Precipitation

Date

Prec

ipita

tion

(mm

) AT

(∘C)

TmaxTmin

Ta

Rn

Rn

(Wm

2)

Figure 2 Daily precipitation air temperature (119879119886

daily mean119879max daily maximum 119879min daily minimum) and net radiation (119877

119899

)during the experimental period from 1 August to 31 August 2012 ina typical temperate steppe at Xilinhot Inner Mongolia

have been excluded since 1979 and a large amount of plantlitter remains on the ground The original land use andcommunity structure of C were similar to G until 5 yearsprior to the study when the land was cultivated for wheatcropping No irrigation is applied to cropped areas Organicmanure was applied prior to crop planting and 240 kg hmminus2effective fertilizer (N 110 kgha P

2

O5

70 kgha and K2

O60 kgha)was applied in two applications during crop growthAt the center of the grazed steppe (G) (43∘321015840240610158401015840N116∘331015840417610158401015840E) an eddy covariance system was set up tomeasure the water carbon and heat exchange between the


















2



119865ℎ

=1000119881119875av119877119878 (119879av + 273)

times119889119888

119889119905 (1)

where 119865ℎ

is H2





















2



000

119865ℎ


(kg H2

O)

(3)

where 119865ℎ

is the H2





3 Results







0

1

2

3

0000 0600 1200 1800 2400Time

E(m

mol

mminus2

sminus1)

(a)

0

1

2

3

4

5

6

0000 0600 1200 1800 2400Time

T(m

mol

mminus2

sminus1)

(b)

0000 0600 1200 1800 2400012345678

Time

ET (m

mol

mminus2

sminus1)

CGEG

(c)





E T ET EET0

2

4

baba

baba

aaac

ab


GGEC

00

03

06

09

EET

Mea

n da

ily v

apou

r exc

hang

e(k

gH

2O m

minus2

d)







0

3

6

9

12ET

(mm

ol m

minus2

sminus1)




GGE

C

(a)

0

2

4

6


E(m

mol

mminus2



GGE

C

(b)

0

3

6


T(m

mol

mminus2

sminus1)




GGE

C

(c)

0 2 4VPD (kPa)

0

3

6

9

12

ET (m

mol

mminus2

sminus1)




GGE

C

(d)

0 2 4VPD (kPa)

0

2

4

6E

(mm

ol m

minus2

sminus1)




GGE

C

(e)

0 2 4VPD (kPa)

0

3

6

T(m

mol

mminus2

sminus1)

G slope = 120 R2 = 082

GE slope = 125 R2 = 079

C slope = 131 R2 = 060

GGE

C

(f)


0

3

6

9

12

ET (m

mol

mminus2

sminus1)




GGE

C

(g)

10 20 30

0

2

4

6

E(m

mol

mminus2

sminus1)




GGE


(h)

10 20 30

0

3

6

T(m

mol

mminus2

sminus1)




GGE


(i)

20 30

0

3

6

9

12

ET (m

mol

mminus2

sminus1)

Gand

GEand

Cand


C

(j)

20 30

0

2

4

6

E(m

mol

mminus2

sminus1)



Cand

Soil moisture (vv)

GGE

C

(k)

20 30

0

3

6

T(m

mol

mminus2

sminus1) Gand

GEand

Cand


C

(l)



30

35

40

Mea

n da

ily E

T (m

m)

0 200 400 600 800


C

GEG


(a)

10

15

20

25

0 200 400 600 800M

ean

daily

E (m

m)



C

GEG

(b)

0 200 400 600 800

15

20

25

Mea

n da

ilyT

(mm

)

C

GEG

R2 = 004and


(c)

30

35

40

Mea

n da

ily E

T (m

m)

05 10 15LAI


C

GEG

(d)

10

15

20

25

05 10 15LAI

Mea

n da

ily E

(mm

)


C

GEG

(e)

05 10 15LAI

15

20

25

Mea

n da

ilyT

(mm

)

R2 = 009and

C

GEG

(f)

12 14 16 18

C

GEG



35

40

Mea

n da

ily E

T (m

m)

(g)

12 14 16 18

10

15

20

25

C

GEG

Mea

n da

ily E

(mm

)



(h)

12 14 16 18

C

GEG

15

20

25

Mea

n da

ilyT

(mm

)


R2 = 017and

(i)

Figure 6 Continued


Mea

n da

ily E

T (m

m)

30

35

40

C

GEG

21 24 27



(j)

C

GEG

10

15

20

25

Mea

n da

ily E

(mm

)



(k)

C

GEG

15

20

25

Mea

n da

ilyT

(mm

)

R2 = 008and


(l)



4 Discussion






09 12 15 18 21

03

04

05

Mea

n da

ily E

ET

Mean daily E (mm)


(a)

15 18 21 24

03

04

05

Mea

n da

ily E

ET

Mean daily T (mm)

R2 = 030lowast

(b)

04 08 12 16

03

04

05

Mea

n da

ily E

ET

LAI


(c)

20 22 24 26 28

03

04

05

Mea

n da

ily E

ET



(d)

21

24

27

05 10 15LAI

Slope = 1034


Slope = 067

R2 = 085and

Mea

n da

ily so

il m

oistu

re (v

v

)

(e)



0 2 4 6 8 10

0

2

4

6

8

10Ch

ambe

r-m

easu

red

ET (m

mol

mminus2

sminus1 )


y = 094x minus 018 (P lt 001)

R2 = 092 n = 88







5 Conclusions






Acknowledgments


References



















































Volume 2014

Mining


Journal of



Geophysics







Journal of




Advances in











Geology Advances in


















2



119865ℎ

=1000119881119875av119877119878 (119879av + 273)

times119889119888

119889119905 (1)

where 119865ℎ

is H2





















2



000

119865ℎ


(kg H2

O)

(3)

where 119865ℎ

is the H2





3 Results







0

1

2

3

0000 0600 1200 1800 2400Time

E(m

mol

mminus2

sminus1)

(a)

0

1

2

3

4

5

6

0000 0600 1200 1800 2400Time

T(m

mol

mminus2

sminus1)

(b)

0000 0600 1200 1800 2400012345678

Time

ET (m

mol

mminus2

sminus1)

CGEG

(c)





E T ET EET0

2

4

baba

baba

aaac

ab


GGEC

00

03

06

09

EET

Mea

n da

ily v

apou

r exc

hang

e(k

gH

2O m

minus2

d)







0

3

6

9

12ET

(mm

ol m

minus2

sminus1)




GGE

C

(a)

0

2

4

6


E(m

mol

mminus2



GGE

C

(b)

0

3

6


T(m

mol

mminus2

sminus1)




GGE

C

(c)

0 2 4VPD (kPa)

0

3

6

9

12

ET (m

mol

mminus2

sminus1)




GGE

C

(d)

0 2 4VPD (kPa)

0

2

4

6E

(mm

ol m

minus2

sminus1)




GGE

C

(e)

0 2 4VPD (kPa)

0

3

6

T(m

mol

mminus2

sminus1)

G slope = 120 R2 = 082

GE slope = 125 R2 = 079

C slope = 131 R2 = 060

GGE

C

(f)


0

3

6

9

12

ET (m

mol

mminus2

sminus1)




GGE

C

(g)

10 20 30

0

2

4

6

E(m

mol

mminus2

sminus1)




GGE


(h)

10 20 30

0

3

6

T(m

mol

mminus2

sminus1)




GGE


(i)

20 30

0

3

6

9

12

ET (m

mol

mminus2

sminus1)

Gand

GEand

Cand


C

(j)

20 30

0

2

4

6

E(m

mol

mminus2

sminus1)



Cand

Soil moisture (vv)

GGE

C

(k)

20 30

0

3

6

T(m

mol

mminus2

sminus1) Gand

GEand

Cand


C

(l)



30

35

40

Mea

n da

ily E

T (m

m)

0 200 400 600 800


C

GEG


(a)

10

15

20

25

0 200 400 600 800M

ean

daily

E (m

m)



C

GEG

(b)

0 200 400 600 800

15

20

25

Mea

n da

ilyT

(mm

)

C

GEG

R2 = 004and


(c)

30

35

40

Mea

n da

ily E

T (m

m)

05 10 15LAI


C

GEG

(d)

10

15

20

25

05 10 15LAI

Mea

n da

ily E

(mm

)


C

GEG

(e)

05 10 15LAI

15

20

25

Mea

n da

ilyT

(mm

)

R2 = 009and

C

GEG

(f)

12 14 16 18

C

GEG



35

40

Mea

n da

ily E

T (m

m)

(g)

12 14 16 18

10

15

20

25

C

GEG

Mea

n da

ily E

(mm

)



(h)

12 14 16 18

C

GEG

15

20

25

Mea

n da

ilyT

(mm

)


R2 = 017and

(i)

Figure 6 Continued


Mea

n da

ily E

T (m

m)

30

35

40

C

GEG

21 24 27



(j)

C

GEG

10

15

20

25

Mea

n da

ily E

(mm

)



(k)

C

GEG

15

20

25

Mea

n da

ilyT

(mm

)

R2 = 008and


(l)



4 Discussion






09 12 15 18 21

03

04

05

Mea

n da

ily E

ET

Mean daily E (mm)


(a)

15 18 21 24

03

04

05

Mea

n da

ily E

ET

Mean daily T (mm)

R2 = 030lowast

(b)

04 08 12 16

03

04

05

Mea

n da

ily E

ET

LAI


(c)

20 22 24 26 28

03

04

05

Mea

n da

ily E

ET



(d)

21

24

27

05 10 15LAI

Slope = 1034


Slope = 067

R2 = 085and

Mea

n da

ily so

il m

oistu

re (v

v

)

(e)



0 2 4 6 8 10

0

2

4

6

8

10Ch

ambe

r-m

easu

red

ET (m

mol

mminus2

sminus1 )


y = 094x minus 018 (P lt 001)

R2 = 092 n = 88







5 Conclusions






Acknowledgments


References



















































Volume 2014

Mining


Journal of



Geophysics







Journal of




Advances in











Geology Advances in
















2



000

119865ℎ


(kg H2

O)

(3)

where 119865ℎ

is the H2





3 Results







0

1

2

3

0000 0600 1200 1800 2400Time

E(m

mol

mminus2

sminus1)

(a)

0

1

2

3

4

5

6

0000 0600 1200 1800 2400Time

T(m

mol

mminus2

sminus1)

(b)

0000 0600 1200 1800 2400012345678

Time

ET (m

mol

mminus2

sminus1)

CGEG

(c)





E T ET EET0

2

4

baba

baba

aaac

ab


GGEC

00

03

06

09

EET

Mea

n da

ily v

apou

r exc

hang

e(k

gH

2O m

minus2

d)







0

3

6

9

12ET

(mm

ol m

minus2

sminus1)




GGE

C

(a)

0

2

4

6


E(m

mol

mminus2



GGE

C

(b)

0

3

6


T(m

mol

mminus2

sminus1)




GGE

C

(c)

0 2 4VPD (kPa)

0

3

6

9

12

ET (m

mol

mminus2

sminus1)




GGE

C

(d)

0 2 4VPD (kPa)

0

2

4

6E

(mm

ol m

minus2

sminus1)




GGE

C

(e)

0 2 4VPD (kPa)

0

3

6

T(m

mol

mminus2

sminus1)

G slope = 120 R2 = 082

GE slope = 125 R2 = 079

C slope = 131 R2 = 060

GGE

C

(f)


0

3

6

9

12

ET (m

mol

mminus2

sminus1)




GGE

C

(g)

10 20 30

0

2

4

6

E(m

mol

mminus2

sminus1)




GGE


(h)

10 20 30

0

3

6

T(m

mol

mminus2

sminus1)




GGE


(i)

20 30

0

3

6

9

12

ET (m

mol

mminus2

sminus1)

Gand

GEand

Cand


C

(j)

20 30

0

2

4

6

E(m

mol

mminus2

sminus1)



Cand

Soil moisture (vv)

GGE

C

(k)

20 30

0

3

6

T(m

mol

mminus2

sminus1) Gand

GEand

Cand


C

(l)



30

35

40

Mea

n da

ily E

T (m

m)

0 200 400 600 800


C

GEG


(a)

10

15

20

25

0 200 400 600 800M

ean

daily

E (m

m)



C

GEG

(b)

0 200 400 600 800

15

20

25

Mea

n da

ilyT

(mm

)

C

GEG

R2 = 004and


(c)

30

35

40

Mea

n da

ily E

T (m

m)

05 10 15LAI


C

GEG

(d)

10

15

20

25

05 10 15LAI

Mea

n da

ily E

(mm

)


C

GEG

(e)

05 10 15LAI

15

20

25

Mea

n da

ilyT

(mm

)

R2 = 009and

C

GEG

(f)

12 14 16 18

C

GEG



35

40

Mea

n da

ily E

T (m

m)

(g)

12 14 16 18

10

15

20

25

C

GEG

Mea

n da

ily E

(mm

)



(h)

12 14 16 18

C

GEG

15

20

25

Mea

n da

ilyT

(mm

)


R2 = 017and

(i)

Figure 6 Continued


Mea

n da

ily E

T (m

m)

30

35

40

C

GEG

21 24 27



(j)

C

GEG

10

15

20

25

Mea

n da

ily E

(mm

)



(k)

C

GEG

15

20

25

Mea

n da

ilyT

(mm

)

R2 = 008and


(l)



4 Discussion






09 12 15 18 21

03

04

05

Mea

n da

ily E

ET

Mean daily E (mm)


(a)

15 18 21 24

03

04

05

Mea

n da

ily E

ET

Mean daily T (mm)

R2 = 030lowast

(b)

04 08 12 16

03

04

05

Mea

n da

ily E

ET

LAI


(c)

20 22 24 26 28

03

04

05

Mea

n da

ily E

ET



(d)

21

24

27

05 10 15LAI

Slope = 1034


Slope = 067

R2 = 085and

Mea

n da

ily so

il m

oistu

re (v

v

)

(e)



0 2 4 6 8 10

0

2

4

6

8

10Ch

ambe

r-m

easu

red

ET (m

mol

mminus2

sminus1 )


y = 094x minus 018 (P lt 001)

R2 = 092 n = 88







5 Conclusions






Acknowledgments


References



















































Volume 2014

Mining


Journal of



Geophysics







Journal of




Advances in











Geology Advances in


0

1

2

3

0000 0600 1200 1800 2400Time

E(m

mol

mminus2

sminus1)

(a)

0

1

2

3

4

5

6

0000 0600 1200 1800 2400Time

T(m

mol

mminus2

sminus1)

(b)

0000 0600 1200 1800 2400012345678

Time

ET (m

mol

mminus2

sminus1)

CGEG

(c)





E T ET EET0

2

4

baba

baba

aaac

ab


GGEC

00

03

06

09

EET

Mea

n da

ily v

apou

r exc

hang

e(k

gH

2O m

minus2

d)







0

3

6

9

12ET

(mm

ol m

minus2

sminus1)




GGE

C

(a)

0

2

4

6


E(m

mol

mminus2



GGE

C

(b)

0

3

6


T(m

mol

mminus2

sminus1)




GGE

C

(c)

0 2 4VPD (kPa)

0

3

6

9

12

ET (m

mol

mminus2

sminus1)




GGE

C

(d)

0 2 4VPD (kPa)

0

2

4

6E

(mm

ol m

minus2

sminus1)




GGE

C

(e)

0 2 4VPD (kPa)

0

3

6

T(m

mol

mminus2

sminus1)

G slope = 120 R2 = 082

GE slope = 125 R2 = 079

C slope = 131 R2 = 060

GGE

C

(f)


0

3

6

9

12

ET (m

mol

mminus2

sminus1)




GGE

C

(g)

10 20 30

0

2

4

6

E(m

mol

mminus2

sminus1)




GGE


(h)

10 20 30

0

3

6

T(m

mol

mminus2

sminus1)




GGE


(i)

20 30

0

3

6

9

12

ET (m

mol

mminus2

sminus1)

Gand

GEand

Cand


C

(j)

20 30

0

2

4

6

E(m

mol

mminus2

sminus1)



Cand

Soil moisture (vv)

GGE

C

(k)

20 30

0

3

6

T(m

mol

mminus2

sminus1) Gand

GEand

Cand


C

(l)



30

35

40

Mea

n da

ily E

T (m

m)

0 200 400 600 800


C

GEG


(a)

10

15

20

25

0 200 400 600 800M

ean

daily

E (m

m)



C

GEG

(b)

0 200 400 600 800

15

20

25

Mea

n da

ilyT

(mm

)

C

GEG

R2 = 004and


(c)

30

35

40

Mea

n da

ily E

T (m

m)

05 10 15LAI


C

GEG

(d)

10

15

20

25

05 10 15LAI

Mea

n da

ily E

(mm

)


C

GEG

(e)

05 10 15LAI

15

20

25

Mea

n da

ilyT

(mm

)

R2 = 009and

C

GEG

(f)

12 14 16 18

C

GEG



35

40

Mea

n da

ily E

T (m

m)

(g)

12 14 16 18

10

15

20

25

C

GEG

Mea

n da

ily E

(mm

)



(h)

12 14 16 18

C

GEG

15

20

25

Mea

n da

ilyT

(mm

)


R2 = 017and

(i)

Figure 6 Continued


Mea

n da

ily E

T (m

m)

30

35

40

C

GEG

21 24 27



(j)

C

GEG

10

15

20

25

Mea

n da

ily E

(mm

)



(k)

C

GEG

15

20

25

Mea

n da

ilyT

(mm

)

R2 = 008and


(l)



4 Discussion






09 12 15 18 21

03

04

05

Mea

n da

ily E

ET

Mean daily E (mm)


(a)

15 18 21 24

03

04

05

Mea

n da

ily E

ET

Mean daily T (mm)

R2 = 030lowast

(b)

04 08 12 16

03

04

05

Mea

n da

ily E

ET

LAI


(c)

20 22 24 26 28

03

04

05

Mea

n da

ily E

ET



(d)

21

24

27

05 10 15LAI

Slope = 1034


Slope = 067

R2 = 085and

Mea

n da

ily so

il m

oistu

re (v

v

)

(e)



0 2 4 6 8 10

0

2

4

6

8

10Ch

ambe

r-m

easu

red

ET (m

mol

mminus2

sminus1 )


y = 094x minus 018 (P lt 001)

R2 = 092 n = 88







5 Conclusions






Acknowledgments


References



















































Volume 2014

Mining


Journal of



Geophysics







Journal of




Advances in











Geology Advances in



0

3

6

9

12ET

(mm

ol m

minus2

sminus1)




GGE

C

(a)

0

2

4

6


E(m

mol

mminus2



GGE

C

(b)

0

3

6


T(m

mol

mminus2

sminus1)




GGE

C

(c)

0 2 4VPD (kPa)

0

3

6

9

12

ET (m

mol

mminus2

sminus1)




GGE

C

(d)

0 2 4VPD (kPa)

0

2

4

6E

(mm

ol m

minus2

sminus1)




GGE

C

(e)

0 2 4VPD (kPa)

0

3

6

T(m

mol

mminus2

sminus1)

G slope = 120 R2 = 082

GE slope = 125 R2 = 079

C slope = 131 R2 = 060

GGE

C

(f)


0

3

6

9

12

ET (m

mol

mminus2

sminus1)




GGE

C

(g)

10 20 30

0

2

4

6

E(m

mol

mminus2

sminus1)




GGE


(h)

10 20 30

0

3

6

T(m

mol

mminus2

sminus1)




GGE


(i)

20 30

0

3

6

9

12

ET (m

mol

mminus2

sminus1)

Gand

GEand

Cand


C

(j)

20 30

0

2

4

6

E(m

mol

mminus2

sminus1)



Cand

Soil moisture (vv)

GGE

C

(k)

20 30

0

3

6

T(m

mol

mminus2

sminus1) Gand

GEand

Cand


C

(l)



30

35

40

Mea

n da

ily E

T (m

m)

0 200 400 600 800


C

GEG


(a)

10

15

20

25

0 200 400 600 800M

ean

daily

E (m

m)



C

GEG

(b)

0 200 400 600 800

15

20

25

Mea

n da

ilyT

(mm

)

C

GEG

R2 = 004and


(c)

30

35

40

Mea

n da

ily E

T (m

m)

05 10 15LAI


C

GEG

(d)

10

15

20

25

05 10 15LAI

Mea

n da

ily E

(mm

)


C

GEG

(e)

05 10 15LAI

15

20

25

Mea

n da

ilyT

(mm

)

R2 = 009and

C

GEG

(f)

12 14 16 18

C

GEG



35

40

Mea

n da

ily E

T (m

m)

(g)

12 14 16 18

10

15

20

25

C

GEG

Mea

n da

ily E

(mm

)



(h)

12 14 16 18

C

GEG

15

20

25

Mea

n da

ilyT

(mm

)


R2 = 017and

(i)

Figure 6 Continued


Mea

n da

ily E

T (m

m)

30

35

40

C

GEG

21 24 27



(j)

C

GEG

10

15

20

25

Mea

n da

ily E

(mm

)



(k)

C

GEG

15

20

25

Mea

n da

ilyT

(mm

)

R2 = 008and


(l)



4 Discussion






09 12 15 18 21

03

04

05

Mea

n da

ily E

ET

Mean daily E (mm)


(a)

15 18 21 24

03

04

05

Mea

n da

ily E

ET

Mean daily T (mm)

R2 = 030lowast

(b)

04 08 12 16

03

04

05

Mea

n da

ily E

ET

LAI


(c)

20 22 24 26 28

03

04

05

Mea

n da

ily E

ET



(d)

21

24

27

05 10 15LAI

Slope = 1034


Slope = 067

R2 = 085and

Mea

n da

ily so

il m

oistu

re (v

v

)

(e)



0 2 4 6 8 10

0

2

4

6

8

10Ch

ambe

r-m

easu

red

ET (m

mol

mminus2

sminus1 )


y = 094x minus 018 (P lt 001)

R2 = 092 n = 88







5 Conclusions






Acknowledgments


References



















































Volume 2014

Mining


Journal of



Geophysics







Journal of




Advances in











Geology Advances in


30

35

40

Mea

n da

ily E

T (m

m)

0 200 400 600 800


C

GEG


(a)

10

15

20

25

0 200 400 600 800M

ean

daily

E (m

m)



C

GEG

(b)

0 200 400 600 800

15

20

25

Mea

n da

ilyT

(mm

)

C

GEG

R2 = 004and


(c)

30

35

40

Mea

n da

ily E

T (m

m)

05 10 15LAI


C

GEG

(d)

10

15

20

25

05 10 15LAI

Mea

n da

ily E

(mm

)


C

GEG

(e)

05 10 15LAI

15

20

25

Mea

n da

ilyT

(mm

)

R2 = 009and

C

GEG

(f)

12 14 16 18

C

GEG



35

40

Mea

n da

ily E

T (m

m)

(g)

12 14 16 18

10

15

20

25

C

GEG

Mea

n da

ily E

(mm

)



(h)

12 14 16 18

C

GEG

15

20

25

Mea

n da

ilyT

(mm

)


R2 = 017and

(i)

Figure 6 Continued


Mea

n da

ily E

T (m

m)

30

35

40

C

GEG

21 24 27



(j)

C

GEG

10

15

20

25

Mea

n da

ily E

(mm

)



(k)

C

GEG

15

20

25

Mea

n da

ilyT

(mm

)

R2 = 008and


(l)



4 Discussion






09 12 15 18 21

03

04

05

Mea

n da

ily E

ET

Mean daily E (mm)


(a)

15 18 21 24

03

04

05

Mea

n da

ily E

ET

Mean daily T (mm)

R2 = 030lowast

(b)

04 08 12 16

03

04

05

Mea

n da

ily E

ET

LAI


(c)

20 22 24 26 28

03

04

05

Mea

n da

ily E

ET



(d)

21

24

27

05 10 15LAI

Slope = 1034


Slope = 067

R2 = 085and

Mea

n da

ily so

il m

oistu

re (v

v

)

(e)



0 2 4 6 8 10

0

2

4

6

8

10Ch

ambe

r-m

easu

red

ET (m

mol

mminus2

sminus1 )


y = 094x minus 018 (P lt 001)

R2 = 092 n = 88







5 Conclusions






Acknowledgments


References



















































Volume 2014

Mining


Journal of



Geophysics







Journal of




Advances in











Geology Advances in


Mea

n da

ily E

T (m

m)

30

35

40

C

GEG

21 24 27



(j)

C

GEG

10

15

20

25

Mea

n da

ily E

(mm

)



(k)

C

GEG

15

20

25

Mea

n da

ilyT

(mm

)

R2 = 008and


(l)



4 Discussion






09 12 15 18 21

03

04

05

Mea

n da

ily E

ET

Mean daily E (mm)


(a)

15 18 21 24

03

04

05

Mea

n da

ily E

ET

Mean daily T (mm)

R2 = 030lowast

(b)

04 08 12 16

03

04

05

Mea

n da

ily E

ET

LAI


(c)

20 22 24 26 28

03

04

05

Mea

n da

ily E

ET



(d)

21

24

27

05 10 15LAI

Slope = 1034


Slope = 067

R2 = 085and

Mea

n da

ily so

il m

oistu

re (v

v

)

(e)



0 2 4 6 8 10

0

2

4

6

8

10Ch

ambe

r-m

easu

red

ET (m

mol

mminus2

sminus1 )


y = 094x minus 018 (P lt 001)

R2 = 092 n = 88







5 Conclusions






Acknowledgments


References



















































Volume 2014

Mining


Journal of



Geophysics







Journal of




Advances in











Geology Advances in


09 12 15 18 21

03

04

05

Mea

n da

ily E

ET

Mean daily E (mm)


(a)

15 18 21 24

03

04

05

Mea

n da

ily E

ET

Mean daily T (mm)

R2 = 030lowast

(b)

04 08 12 16

03

04

05

Mea

n da

ily E

ET

LAI


(c)

20 22 24 26 28

03

04

05

Mea

n da

ily E

ET



(d)

21

24

27

05 10 15LAI

Slope = 1034


Slope = 067

R2 = 085and

Mea

n da

ily so

il m

oistu

re (v

v

)

(e)



0 2 4 6 8 10

0

2

4

6

8

10Ch

ambe

r-m

easu

red

ET (m

mol

mminus2

sminus1 )


y = 094x minus 018 (P lt 001)

R2 = 092 n = 88







5 Conclusions






Acknowledgments


References



















































Volume 2014

Mining


Journal of



Geophysics







Journal of




Advances in











Geology Advances in


0 2 4 6 8 10

0

2

4

6

8

10Ch

ambe

r-m

easu

red

ET (m

mol

mminus2

sminus1 )


y = 094x minus 018 (P lt 001)

R2 = 092 n = 88







5 Conclusions






Acknowledgments


References



















































Volume 2014

Mining


Journal of



Geophysics







Journal of




Advances in











Geology Advances in





Acknowledgments


References



















































Volume 2014

Mining


Journal of



Geophysics







Journal of




Advances in











Geology Advances in






























Volume 2014

Mining


Journal of



Geophysics







Journal of




Advances in











Geology Advances in










Volume 2014

Mining


Journal of



Geophysics







Journal of




Advances in











Geology Advances in

Documents

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