research article reference evapotranspiration changes

Research ArticleReference Evapotranspiration Changes Sensitivities toand Contributions of Meteorological Factors in the Heihe RiverBasin of Northwestern China (1961ndash2014)

Chaoyang Du12 Jingjie Yu1 Ping Wang1 and Yichi Zhang1

1Key Laboratory of Water Cycle and Related Land Surface Processes Institute of Geographic Sciences and Natural Resources ResearchChinese Academy of Sciences Beijing 100101 China2University of Chinese Academy of Sciences Beijing 100049 China

Correspondence should be addressed to Jingjie Yu yujjigsnrraccn

Received 2 August 2015 Accepted 5 November 2015

Academic Editor Jan Friesen

Copyright copy 2016 Chaoyang Du et al This is an open access article distributed under the Creative Commons Attribution Licensewhich permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited

This paper investigates reference evapotranspiration (ET0) changes sensitivities to and contributions of meteorological factors

in the Heihe River Basin (arid and inland region) Results show that annual ET0over the whole basin has increasing trend

(201mmsdot10 yrminus2) and there are significant increasing spatial variations from the upper (753mmyrminus1) to the lower (1553mmyrminus1)regions Sensitivity analysis indicates that relative humidity is the most sensitive factor for seasonal and annual ET

0change and the

influence is negative The sensitivity of minimum temperature is the weakest and negative Contribution analysis shows that themain contributors to ET

0changes are aerodynamic factors rather than radiative factors This study could be helpful to understand

the response of ecoenvironment to the meteorological factors changes in the Heihe River Basin

1 Introduction

Evapotranspiration is an excellent indicator of hydroclimaticchange and the response of watermanagement food securityand ecoenvironment [1] Among different evapotranspirationterms such as actual evapotranspiration (ET

119886) potential

evapotranspiration (ET119901) pan evaporation (119864pan) and refer-

ence evapotranspiration (ET0) 119864pan and ET

0are often used

as surrogates of ET119901to reflect the evaporation capability

in a specific region Because ET119901and ET

0are dependent

only onmeteorological condition not underlying surface andare measurable or calculable they are important hydrocli-matic indicators for reflecting regional water-energy balancechanges and the effect of climate change Spatiotemporalvariations of ET

0in different climatic regions have been

globally reported over the past decades [2 3] Many regionshave experienced significant decreasing trends of 119864pan orET0 such as the US [4] China [5] Canada [6] Australia

[7] India [8] Japan [9] and Romania [10] However ET0

changes with significant positive trends have been reported

in other regions such as the Mediterranean region [11] Iran[12] Spain [13] and Serbia [14] Moreover the interannualfluctuations of ET

0for some regions are very significant ET

0

may increase during one period but decrease during the nextperiod [5 7] Therefore the temporal variations of ET

0are

complex and diverse in different climatic zones Reasons forthe different temporal variations of ET

0in different climatic

zones need to be explored in further detailThe causes of ET

0changes in many regions have been

studied First the effects of different methods on ET0changes

have been discussed in different climatic zones Popularmethods for ET

0calculation mainly include FAO P-M

Priestley-Taylor Hargreaves Makkink Blaney-Criddle andSamani-Hargreaves methods [15] Comparisons showed thatFAO P-M performs better among the different methods dueto having the clear physical meaning and is recommended asa standard method for the ET

0calculation [16 17] Second

a sensitivity coefficient was used to investigate the effects ofmeteorological factors on ET

0change [18ndash20] Most studies

showed that aerodynamic factors are the major factors in

Hindawi Publishing CorporationAdvances in MeteorologyVolume 2016 Article ID 4143580 17 pageshttpdxdoiorg10115520164143580

2 Advances in Meteorology

different regions For example air temperature wind speedand relative humidity have stronger effects on ET

0change in

Spain [20] Air temperature andwind speed are the dominantvariables influencing ET

0in Iran [12] Air temperature is the

most sensitive variable to ET0change in India [21] Similar

results have also been found in some regions of China inwhichwind speed air temperature and vapor pressure deficitare the major sensitive factors for ET

0change in such areas as

the Loess Plateau Region [22] the Liaohe delta [23] the TibetPlateau [24] the Changjiang River Basin [19] and the HaiheRiver Basin [25] Some studies proposed a close agreementbetween changes in ET

0and solar energy in Greece [26]

Korea [27] and the Yellow River Basin [28] Sensitivityanalysis could only describe the responses of ET

0to changes

in individual factor However it cannot determine howmuchthe impact of each meteorological factor on ET

0change is

The Heihe River basin (HRB) the second largest inlandriver basin in northwestern China consists of three regionswith different landscapes and climate conditions where theupper mountainous region is semiarid and natural with littlehuman interference the middle region is dry and intensivelyirrigated plain and the lower region is an extremely dry Gobidesert plain The spatial variation of ET

0in such basin may

supply more information of regional response to the climateThe previous studies only reported the spatiotemporal varia-tions of ET

0[29 30] at a given period but there is no common

understanding of ET0change so far due to different data

time series The aim of this paper is to clarify the effect ofmeteorological factors on ET

0change by comprehensively

analyzing the sensitivity of ET0change and contributions

of meteorological factors in the HRB using reliable andcomplete daily meteorological data from 16 stations for theperiod 1961ndash2014 This paper will determine (1) the spatialpattern and temporal trends of ET

0for the HRB (2) the

sensitivity of ET0to meteorological factors and (3) the

contributions of the meteorological factors to ET0change

2 Study Area and Data

21 Study Area As shown in Figure 1 the drainage mapand the basin border of the HRB are extracted using a90m resolution digital elevation model (DEM) data from theShuttle Radar Topography Mission (SRTM) website of theNASA (httpsrtmcsicgiarorgSELECTIONinputCoordasp) (basin length 820 km total area 143000 km2 elevation870ndash5545m)

The HRB is divided into three regions according to basincharacteristics shown in Figure 1 The upper mountainousregion belongs to the cold and semiarid mountain zonewith an elevation from 2000 to 5000m annual mean tem-perature of less than 2∘C pan evaporation of 700mmyrminus1and precipitation of 350ndash400mmyrminus1 The middle regionis the main irrigation zone and residential area with morethan 90 of the total population of the basin it has aprecipitation of 100ndash250mmyrminus1 and pan evaporation of2000mmyrminus1 The lower region is covered by the arid Gobi

U3

U2U1

M4

M3

M2 M1

L2

L1

N

37∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

94∘0998400E

95∘0998400E

96∘0998400E

97∘0998400E

98∘0998400E

99∘0998400E

100∘0998400E

101∘0998400E

102∘0998400E

Lower

Middle

UpperQilian Mountain(km)

Elev

atio

n (m

)

5545

870

0 50 100 200

Radiation stationMeteorological stationRiver

Figure 1 Location of the HRB and spatial distribution of themeteorological and radiation stations U M and L represent theupper middle and lower regions in the basin respectively

desert in the north of the basin with an elevation of 870ndash1500mand is characterized by an extremely arid climate withpan evaporation of 3500mmyrminus1 and precipitation of 10ndash50mmyrminus1

22 Data In this study daily meteorological data of 16stations from 1961 to 2014 in and around the HRB areavailable from the National Climatic Centre of the ChinaMeteorological Administration The three solar radiationstations correspond to the upper the middle and the lowerregion (Figure 1) The data set includes daily observationsof atmospheric pressure maximum and minimum air tem-peratures at 2m height (119879max 119879min) relative humidity at2m height (RH) daily sunshine duration pan evaporationmeasured using a metal pan 20 cm in diameter and 10 cmhigh installed 70 cm above the ground and wind speedmeasured at 10m height which was transformed to windspeed at 2m height (WS) by the wind profile relationshipfrom Chapter 3 of the FAO paper 56 [16] In addition thethree radiation stations were used to calibrate the Angstromparameters of extraterrestrial radiation reaching the earth onclear days in the FAO P-M equation The spatial patterns ofthe meteorological factors ET

0 and sensitivity coefficients

were obtained by the inverse distance weight (IDW) interpo-lation method

In this study the four seasons of the HRB are defined asspring (fromMarch to May) summer (from June to August)autumn (from September to November) and winter (fromDecember to February)

Advances in Meteorology 3

3 Methodology

31 FAO Penman-Monteith Method The Penman-Monteithmethod can be used globally to estimate potential evapo-transpiration Allen et al simplified the Penman-Monteithequation and defined the hypothetical reference grass withan assumed height of 012m a fixed surface resistance of70 smminus1 and an albedo of 023 [16]This method can providegood and reliable results for ET

0because it is physically

based and explicitly incorporates both physiological andaerodynamic parameters and has been accepted as a standardto compare evapotranspiration capability for various climaticregions [31] Moreover this method has been successfullyapplied across the whole of China [32 33] The FAO P-M forcalculating daily ET

0is described as

ET0

=0408Δ (119877

119899minus 119866) + 120574 (900 (119879mean + 273)) 1199062 (119890119904 minus 119890119886)

Δ + 120574 (1 + 0341199062)

(1)

where ET0is the reference evapotranspiration (mmdayminus1)

119877119899is the net radiation at the crop surface (MJmminus2 dayminus1) 119866

is the soil heat flux density (MJmminus2 dayminus1) 119879mean is the meandaily air temperature at 2m height (∘C) 119906

2is the wind speed

at 2mheight (m sminus1) 119890119904is the saturation vapor pressure (kPa)

119890119886is the actual vapor pressure (kPa) Δ is the slope vapor

pressure curve (kPa∘Cminus1) 120574 is the psychrometric constant(kPa∘Cminus1) the atmospheric pressure used in this study is themeasured value More details regarding the data processingin (1) can be found in FAO paper 56

In (1) the solar radiation (119877119904) is obtained with the

following Angstrom formula

119877119904= (119886 + 119887

119899

119873)119877119886 (2)

where 119877119904is the solar radiation (MJmminus2 dayminus1) 119899 is the

actual sunshine duration (hours)119873 is themaximumpossiblesunshine duration or daylight hours (hours) 119877

119886is the

extraterrestrial radiation (MJmminus2 dayminus1) and 119886 and 119887 areregression constants

Because of the effects of the atmospheric conditions(humidity dust) and solar declination (latitude and month)as well as the elevation variations the Angstrom values 119886 and119887 in the HRB were calibrated using the observed radiationdata at the three solar radiation stations (Figure 2)

32 TrendAnalysis The long-term trends and changes of ET0

andmeteorological factors are detected using the linear fittedmethod

= 119905 + 119887 (3)

where is the fitted trend during a given period and and are the estimated regression slope and the regressionconstant respectively Positive slope indicates an increasingtrend and negative slope indicates a decreasing trend

For data sets without seasonality the significance of atrend is described using theMann-Kendall (MK) testmethod

[34 35] which is to statistically assess if there is a monotonictrend of the variable of interest over time [36] whilst theSeasonal Kendall (SK) test is extension of the MK test andis suitable for trend applicable to data sets with seasonalitymissing values and serial correlation over time [37 38]The SK test begins by computing the MK test separately foreach month or season and then summing the statistic 119878

119894

and variance Var(119878119894) Following Hirsch et al [37] the entire

sample119883 is made up of subsamples1198831through119883

12(one for

each month) and each subsample 119883119894contains the 119899

119894annual

values from month 119894119883 = (119883

1 1198832 119883

12)

119883119894= (1198831198941 1198831198942 119883

11989412)

(4)

The null hypothesis 1198670for the SK test is that the 119883 is a

sample of independent random variables (119909119894119895) and that each

1198831is a subsample of independent and identically distributed

random variables over yearsThe alternative hypothesis1198671is

that for one or more months the subsample is not distributedidentically over years

According to the MK test the statistic 119878119894is defined by

119878119894=

119899119894minus1

sum119896=1

119899119894

sum119895=119896+1

sign (119909119894119895minus 119909119894119896) (5)

where

sign (120579) =

1 120579 gt 0

0 120579 = 0

minus1 120579 lt 0

(6)

Now the subsample 119883119894satisfies the null hypothesis of

Mannrsquos test Therefore relying on Mann and Kendall we have

119864 (119878119894) = 0 (7a)

Var (119878119894)

=1

18

1003816100381610038161003816100381610038161003816100381610038161003816

119899119894(119899119894minus 1) (2119899

119894+ 5) minus

119892119894

sum119905119894

119905119894(119905119894minus 1) (2119905

119894+ 5)

1003816100381610038161003816100381610038161003816100381610038161003816

(7b)

where 119892119894is the number of tied groups for the 119894th month and

119905119894119901is the number of data in the 119901th group for the 119894th month

119878119894is normal in the limit as 119899

119894rarr infin The SK test statistic 119878 is

given by

119878 =

119898

sum119894=1

119878119894 (8)

where 119898 is the number of months for which data have beenobtained over years The expectation and variance can bederived as follows

119864 (119878) =

119898

sum119894=1

119864 (119878119894) (9a)

Var (119878) =119898

sum119894=1

Var (119878119894) +

119898

sum119894=1

119898

sum119895=1

cov (119878119894119878119895) (9b)


RsR

a

nN

a = 0213 b = 0611

R2= 0873

10

08

06

04

02

00100806040200

(a)

RsR

a

a = 0218 b = 0531

R2= 0844

10

08

06

04

02

00100806040200

nN

(b)

RsR

a

a = 0260 b = 0519

R2= 0815

10

08

06

04

02

00100806040200

nN

(c)

Figure 2 Calibration of the Angstrom coefficients for the three radiation stations (a) Gangcha station in the upper region (b) Jiuquan stationin the middle region and (c) Ejina station in the lower region

where 119878119894and 119878119895(119894 = 119895) are function of independent random

variables so cov(119878119894119878119895) = 0

For 1198991gt 10 the standard normal deviate 119885 is estimated

by (10) to test the significance of trends

119885 =

(119878 minus 1)

radic119881 (119878) 119878 gt 0

0 119878 = 0

(119878 + 1)

radic119881 (119878) 119878 lt 0

(10)

For the SK test the null hypothesis 1198670means that there

is no monotonic trend over time when |119885| gt 1198851minus1205722

theoriginal null hypothesis is rejected this means that the trendof the time series is statistically significant In this studysignificance level of 120572 = 01 is employed

33 Sensitivity Analysis Saxton [18] and Smajstrla et al [39]defined the sensitivity coefficient by drawing a curve of

the change of a dependent variable versus the changes ofindependent variables For multifactor models (eg the FAOP-M) due to different dimensions and ranges of differentfactors the ratios of ET

0changes and factors changes cannot

be compared In addition this approach could introduceerrors to understand the response of model behaviors tothe factors because of changing one of the factors butholding other factors stationary [27] To avoid the abovetwo disadvantages the dimensionless sensitivity coefficientdefined by the dimensionless partial derivative with respectto the independent factors is used in this study

119878 (119909119894) = limΔ119909119894rarr0

(ΔET0ET0

Δ119909119894119909119894

) =120597ET0

120597119909119894

sdot119909119894

ET0

(11)

where 119909119894is the 119894th meteorological factor and 119878(119909

119894) is the

dimensionless sensitivity coefficient of reference evapotran-spiration related to 119909

119894 Greve et al [40] used this method to

estimate the effects of variation in meteorological factors and


measurement error on evaporation change If the sensitivitycoefficient of a factor is positive (negative) ET

0will increase

(decrease) as the factor increases The larger the absolutevalue of the sensitivity coefficient the more ET

0is sensitive

to a factorIn this study the meteorological factors 119879max 119879min WS

RH and 119877119904are chosen for sensitivity analysis Sensitivity

coefficients (119878119879max

119878119879min

119878WS 119878RH and 119878119877119904) were calculatedon a daily dataset Monthly and annual average sensitivitycoefficients were obtained by average daily values Regionalsensitivity coefficients were obtained by averaging stationvalues

34 Contribution Estimation Although sensitivity coeffi-cients can reflect the sensitivity of ET

0change to the per-

turbation of a factor it cannot describe the contributionof a factor change to ET

0change Because both of the

sensitivity and changes inmeteorological factors affected ET0

change an approach to integrating the sensitivity and changesof meteorological factors is proposed to quantify influencemagnitude individual meteorological factors changes to thetrends of ET

0

Mathematically for the function ET0= 119891(119909

1 1199092 119909

119899)

where 1199091 1199092 119909

119899are independent variables the first order

Taylor approximation of the dependent variable ET0in terms

of the independent variables is expressed as

ΔET0= sum

120597ET0

120597119909119894

sdot Δ119909119894+ 120575 (12)

where ΔET0is the change of ET

0during a period 119909

119894is the 119894th

meteorological factorΔ119909119894is the change of 119909

119894during the same

period 120597ET0120597119909119894is the partial differential of ET

0with respect

to 119909119894 and 120575 is the Lagrange remainderIf both sides of (12) are divided by ET

0(the average value

of ET0during a period) (12) can be written as

ΔET0

ET0

= sum120597ET0

120597119909119894

sdotΔ119909119894

ET0

+ 120576 (13)

where ΔET0ET0is the relative change of ET

0during a given

period 120576 = 120575ET0is the error item which can be neglected

because of its small valueThe first term in the right side of equation is multiplied

by 119909119894119909119894 (13) can be written as

ΔET0

ET0

= sum120597ET0

120597119909119894

sdot119909119894

ET0

Δ119909119894

119909119894

+ 120576 (14)

where (120597ET0120597119909119894) sdot (119909119894ET0) is the average sensitivity coef-

ficient of factor 119909119894during a period denoted as 119878

119909119894 If we let

119862(119909119894) = sum 119878

119909119894sdot (Δ119909119894119909119894) (14) can be written as

ΔET0

ET0

asymp sum119862(119909119894) (15)

119862(119909119894) is the relative change in ET

0contributed by 119879max 119879min

WS RH and 119877119904

Table 1 Coefficient of determination of monthly 119864pan and ET0for

nine meteorological stations

Station U1 U2 U3 M1 M2 M3 M4 L1 L21198772 0945 0939 0966 0969 0973 0959 0968 0965 0986

4 Results

41 Correlation of 1198641198790and 119864

119901119886119899 The coefficients of deter-

mination 119877 of monthly 119864pan and ET0for different stations

(Table 1) are between 0939 and 0986 which means that themonthly 119864pan and ET0 have a very close linear relationship inthe HRB Such a close linear relationship suggests that ET

0

can be a good estimation using the observed 119864pan in the HRBif the regression coefficients are given Moreover Figures 3(a)and 3(b) show that monthly and annual 119864pan and ET

0both

present good linearity The monthly and annual 119877 values are0967 and 0906 respectively And the correlation of monthly119864pan and ET

0appears to be a strong seasonal characteristic

and becomes less centralized from winter to summer

42 Evolution and Spatial Pattern of 1198641198790at Different Time

Scales Figure 4 shows the average monthly ET0change

during a year for the whole basin during 1961 and 2014 Themean monthly ET

0is 978mmmonthminus1 over the whole basin

in the last 50 years Monthly ET0first increases and then

decreases during a year The peak value occurs in June andJuly approximately 177mmmonthminus1 whereas the bottomvalues occur during November and February and are lessthan 50mmmonthminus1 This strong monthly variation has asimilar shape feature to the natural change in temperatureand solar radiation (Figures 4 and 7) In addition ET

0

in summer months differs more dramatically than that inwinter months And the difference between the maximumand the minimum of ET

0reaches 50mm in July whereas

the difference in December is only 10mm The evaporationcapability in summer months accounts for 44 of annualET0Figure 5 shows the trends of annual and seasonal ET

0

for the whole basin from 1961 to 2014 The mean annualET0is 1175mmyrminus1 The increasing trend of annual ET

0

is 201mmsdot10 yrminus2 over the 54 years and has no statisticalsignificance Annual ET

0variations exhibit three different

phases which has a significant increasing trend during 1961ndash1974 and 1997ndash2014 but clearly decreases during 1975ndash1996 at005 levels (Figure 5(e)) The 1961ndash2014 means of ET

0from

spring to winter are 363mmyrminus1 511mmyrminus1 220mmyrminus1and 814mmyrminus1 respectively The climatic trends of ET

0in

spring and winter are 207mmsdot10 yrminus2 and 052mmsdot10 yrminus2respectively whereas ET

0changes in summer andwinter have

decreasing trends of minus07mmsdot10 yrminus2 and minus006mmsdot10 yrminus2Table 2 reports the mean values and trends of seasonal

and annual ET0in the three subregions from 1961 to 2014

The seasonal and annual ET0have gradually increasing

spatial gradients from the upper region to the lower regionThe mean annual ET

0of the upper middle and lower

regions are 902mmyrminus1 1051mmyrminus1 and 1289mmyrminus1


R2= 0967

400

300

200

100

0

0 50 100 150 200

Summer

Autumn

Spring

Winter

Epan = 204 times ET0 minus 338

Epa

n(m

m m

onth

minus1)

ET0 (mm monthminus1)

(a)

R2= 0906

Epa

n(m

m yr

minus1)

5000

4000

3000

2000

1000

0

600 800 1000 1200 1400 1600


ET0 (mm yrminus1)

(b)

Figure 3 Relationship between 119864pan and ET0at monthly (a) and annual (b) scales for nine meteorological stations from 1961 to 2001

Month

250

200

150

100

50

01 2 3 4 5 6 7 8 9 10 11 12

ET0

(mm

mon

thminus1)

Figure 4 Box and whisker plots of monthly ET0of the HRB from 1961 to 2014 The line inside the boxes represents the median and the

upper and lower lines of the boxes indicate the 75th and 25th percentiles respectively The upper and lower parts of the whiskers indicate themaximum and the minimum of monthly ET

0 respectively

respectivelyTheET0change in the upper region appears to be

a statistically increasing trend at 661mmsdot10 yrminus2The climatictrends of annual ET

0in the middle and lower regions are

225mmsdot10 yrminus2 and 091mmsdot10 yrminus2 respectively withoutstatistical significance

The maximum and minimum values of seasonal ET0

consistently occur in summer and winter respectively for thethree regions Whereas the seasonal ET

0trends are different

ET0for the upper region has significant increasing trends

in spring autumn and winter with increasing rates of 241119 and 154mmsdot10 yrminus2 respectively Seasonal ET

0has no

significant trend for the middle and lower regionsThe spatial patterns of seasonal and annual ET

0in the

HRB from 1961 to 2014 are plotted in Figure 6There are clearspatial gradients for annual ET

0from the upper region to the

lower region The maximum occurs in the lower region andis up to 1553mmyrminus1 near station L2 and the minimum is

found in the upper region and is as low as 757mmyrminus1 nearstation U2 in the upper region

The spatial variation of seasonal ET0is smaller than

that of annual ET0 The ET

0changes in spring summer

and autumn have similar spatial features The ET0changes

only in summer have a clear spatial pattern ranging from300mmyrminus1 to 700mmyrminus1 over the whole basin Variationsof ET

0in the other three seasons have very small spatial

gradients across thewhole basinThe spatial difference in ET0

in spring is between 232mmyrminus1 and 472mmyrminus1 with a SDof 49mmyrminus1 and the ET

0variation in the autumn ranges

from 145mmyrminus1 to 290mmyrminus1 with a SD of 30mmyrminus1The spatial distribution of ET

0in winter varies little and its

SD is only 58mmyrminus1 over the whole basin

43 Trends in Meteorological Factors According to the FAOP-M method described in (1) 119879max 119879min WS RH and 119877

119904


Spring Slope 021(NS)

1960 1970 1980 1990 2000 2010

420

400

380

360

340

320

ET0

(mm

yrminus1)

(a)

SummerSlope minus007

(NS)

1960 1970 1980 1990 2000 2010

580

560

540

520

500

480

460

ET0

(mm

yrminus1)

(b)

Autumn Slope minus001(NS)

1960 1970 1980 1990 2000 2010

260

240

220

200

ET0

(mm

yrminus1)

(c)

Winter Slope 005(NS)

1960 1970 1980 1990 2000 2010

120

100

80

60

40

ET0

(mm

yrminus1)

(d)

AnnualSlope 020

(NS)

1960 1970 1980 1990 2000 2010

1300

1250

1200

1150

1100

1050

Trend lineLine of five-year moving average

ET0

(mm

yrminus1)

ET0 change

(e)

Figure 5 Annual and seasonal ET0trends for the HRB during 1961 and 2014 NS means not significant at the level of 120572 lt 005 by the MK

test

Table 2 Means of seasonal and annual ET0and their trends in the three subregions during 1961ndash2014

Region Annual Spring Summer Autumn Winter

Upper region Mean (mmyrminus1) 902 280 380 171 711

Trend (mmsdot10 yrminus2) 661lowast 241lowast 133 119lowast 154lowast

Middle region Mean (mmyrminus1) 1051 330 446 196 786

Trend (mmsdot10 yrminus2) 225 203 minus033 minus021 058

Lower region Mean (mmyrminus1) 1289 395 568 241 848


Note lowastmeans the significance level of 01


Spring Summer Autumn

Winter

Seasonallt6060ndash7575ndash9090ndash100100ndash150150ndash200200ndash250250ndash300300ndash350350ndash400400ndash450450ndash500500ndash550550ndash600600ndash650gt650

Annual

Annual

lt800800ndash850850ndash900900ndash950950ndash10001000ndash10501050ndash11001100ndash11501150ndash12001200ndash12501250ndash13001300ndash13501350ndash14001400ndash14501450ndash1500gt1500

Spring ummer Autumn

Winter Annual

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

97∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E 97

∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E

97∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E 97

∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E

97∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E

Max 470Min 232SD 49

Max 700Min 310SD 84

Max 290Min 145SD 30

Max 59Min 93SD 58

Max 1553Min 757SD 166

Figure 6 Spatial patterns of the seasonal and annual mean ET0in the whole HRB from 1961 to 2014 Max andMin denote the maximum and

minimum values respectively of ET0over the whole basin SD indicates the standard deviation of the spatial variations of ET

0

are selected as the major meteorological factors having animportant influence on ET

0 119879mean (the average of 119879max and

119879min) is a comprehensive indicator for analyzing temperaturevariation

Figure 7 shows monthly variations of meteorologicalfactors in the upper middle and lower regions and the wholebasin during 1961 and 2014 The variations of monthly 119879meanand 119877

119904are similar to those of monthly ET

0(Figure 4) and

their peak values occur in the middle of the year with a

minimum at the ends of the year The air temperature inthe upper region is the smallest over the whole basin whichranges from minus126∘Cmonthminus1 to 129∘Cmonthminus1 Althoughthe average monthly 119879mean in the middle and lower regionsare both 81∘Cmonthminus1 the maximum value of 119879mean in thelower region is larger than that in the middle region and theminimum value in the lower region is smaller than that in themiddle region Moreover the standard deviation of monthly119879mean in the middle region is the smallest


WWWW

Tm

ean(∘

C)

WS

(m sminus

1)

RH (

)

Rs

(MJ m

minus2

dminus1)

2 4 6 8 10 122 4 6 8 10 122 4 6 8 10 122 4 6 8 10 12

30

20

10

0

minus10

minus20

5

4

3

2

1

80

60

40

20

30

25

20

15

10

Month Month Month Month

UUUU

Tm

ean(∘

C)

WS

(m sminus

1)

RH (

)

Rs

(MJ m

minus2

dminus1)

2 4 6 8 10 12 2 4 6 8 10 12 2 4 6 8 10 12 2 4 6 8 10 12

30

20

10

0

minus10

minus20

5

4

3

2

1

80

60

40

20

30

25

20

15

10

MonthMonthMonthMonth

MMMM

Tm

ean(∘

C)

WS

(m sminus

1)

RH (

)

Rs

(MJ m

minus2

dminus1)

2 4 6 8 10 122 4 6 8 10 122 4 6 8 10 122 4 6 8 10 12

30

20

10

0

minus10

minus20

5

4

3

2

1

80

60

40

20

30

25

20

15

10


LLLL

Tm

ean(∘

C)

WS

(m sminus

1)

RH (

)

Rs

(MJ m

minus2

dminus1)

2 4 6 8 10 12 2 4 6 8 10 12 2 4 6 8 10 12 2 4 6 8 10 12

30

20

10

0

minus10

minus20

5

4

3

2

1

80

60

40

20

30

25

20

15

10


Figure 7 Monthly variations of meteorological factors (119879mean WS RH and 119877119904) in the upper (U) middle (M) and lower (L) regions and the

whole basin (W) The 54-year mean (solid line) and standard deviation (error bar) are shown

The variation of wind speed during a year is relativelysmall The peak of monthly WS occurs in April There aresimilar variation features of WS for the three subregionsThe monthly WS in the lower region is the largest with anaverage of 28m sminus1 monthminus1 during the year whereas that inthe lower region is the smallest with an average of 18m sminus1monthminus1 The higher error bar means that the monthly WShas significant fluctuations during the year

The monthly RH from the lower to the upper regiongradually increases and the fluctuations of RH are alsosubstantial The monthly RH in the upper region increasesat first and then decreases and its peak is during June andAugust The monthly RH in the middle and lower regionsdecreases at first and then increases and its bottom is inApril

The monthly 119877119904in different regions have the same

variation features and standard deviations during the yearThe high value of monthly 119877

119904is found during June and

August and the low value occurs in winter The standard

deviation during May and August is larger than that fromNovember to February

Figure 8 shows trends of annual 119879mean WS RH and119877119904for the upper middle and lower regions and the whole

basin during 1961 and 2014 Positive trends of annual 119879meanduring 1961 and 2014 are detected in the upper middle andlower regions and the whole basin with significant rates ofchange of 032∘Csdot10 yrminus2 033∘Csdot10 yrminus2 038∘Csdot10 yrminus2 and036∘Csdot10 yrminus2 respectively

The mean annual WS in the lower region is 25m sminus1 yrminus1and is larger than that in other regions The interannualoscillations of annual WS for the middle and lower regionsand the whole basin are similar and have three phases tworelatively steady periods from 1961 to 1968 and 1969 to 1974followed by a long-term statistically significant decline phasefrom 1974 to the 1990 s However the trend of annual WS inthe upper region has only a statistically significant declinephase from 1961 to 2014 There are significant decreasing


1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

Tm

ean(∘

C)

WS

(m sminus

1)

RH (

)

Rs

(MJ m

minus2

dminus1)

YearYearYearYear

Slope 0036 (S)10

9

8

7

6

5

35

30

25

20

15

55

50

45

40

35

185

180

175

170

165

W W W WSlope minus0017 (S) Slope minus0053 (S) Slope minus0002 (NS)1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

Tm

ean(∘

C)

WS

(m sminus

1)

RH (

)

Rs

(MJ m

minus2

dminus1)

Year Year Year Year

Slope 0032 (S)35

30

25

20

15

60

55

50

45

40

35

185

180

175

170

165

U U U U4

3

2

1

Slope minus0013 (S)

Slope minus0035 (S)

Slope minus0002 (NS)

1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

Tm

ean(∘

C)

WS

(m sminus

1)

RH (

)

Rs

(MJ m

minus2

dminus1)

YearYearYearYear

Slope 0033 (S) Slope minus0002 (NS)10

9

8

7

6

5

35

30

25

20

15

55

50

45

40

35

185

180

175

170

165

M M M M

Slope minus0048 (S)

Slope minus0017 (S)

1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

Tm

ean(∘

C)

WS

(m sminus

1)

RH (

)

Rs

(MJ m

minus2

dminus1)

Year Year Year Year

Slope 0038 (S)10

9

8

7

6

5

35

30

25

20

15

55

50

45

40

35

185

180

175

170

165

L L L L

Slope minus0020 (S)

Slope minus0059 (S)

Slope minus0002 (S)

Figure 8 Trends of annual 119879mean WS RH and 119877119904for the upper (U) middle (M) and lower (L) region and the whole basin (W) S indicates

that the trend is statistically significant and NS indicates that the trend is not significant at the 005 level

trends for the upper middle and lower regions withchange rates of minus013m sminus1sdot10 yrminus2 minus017m sminus1sdot10 yrminus2 andminus020m sminus1sdot10 yrminus2 respectively

The mean annual RH in the lower middle and upperregions is 41 yrminus1 50 yrminus1 and 52 yrminus1 respectivelyDuring 1961 and 2014 decreasing trends in the upper andmiddle regions are not statistically significant whereas thechanges in annual RH in the lower region and whole basinhave significant decreasing trends Therefore the changes inRH across the whole basin are mainly affected by the trend ofRH in the lower region

The change of annual 119877119904for the different regions has

no significant decreasing trend during the 54-year periodwhereas the interannual oscillations of 119877

119904are clearer than

those of RH

44 Variations of the Sensitivity Coefficients Mean dailysensitivity coefficients for major meteorological factors thatexhibit large fluctuations during a year (Figure 11) Althoughannual 119879max and 119879min have the same trend the variationsof 119878119879max

and 119878119879min

are different 119878119879max

gradually increases fromnegative to positive at first and then decreases from positiveto negative and achieves a larger and stable peak value duringMay and August (Figure 9(a))The daily variation patterns of119878119879min

have a unimodal distribution and the peak occurs onthe 200th day of the year (Figure 9(b)) 119878

119879maxand 119878

119879minare

positive during summer and the former is larger than thelatter 119878

119879maxand 119878119879min

are negative during winter days and thelatter is smaller than the formerThus ET

0is sensitive to119879max

in summer but 119879min in winter The value of 119878119879max

is greater inthe lower region than in the other two regions 119878

119879minfor the


ST

max

Day0 50 100 150 200 250 300 350

06

04

02

00

minus02

LMU

(a)

ST

min

Day0 50 100 150 200 250 300 350

01

00

minus01

minus02

minus03

LMU

(b)

SW

S

Day0 50 100 150 200 250 300 350

05

04

03

02

01

LMU

(c)

SRH

Day0 50 100 150 200 250 300 350

minus02

minus04

minus06

minus08

minus10

LMU

(d)

SR119904

Day0 50 100 150 200 250 300 350

06

04

02

00

minus02

LMU

(e)

Sens

itivi

ty co

effici

ents

Day0 50 100 150 200 250 300 350

06

03

00

minus03

minus06

minus09

Tmax

Tmin

RsWSRH

(f)

Figure 9 Mean daily sensitivity coefficients for maximum temperature (a) minimum temperature (b) wind speed (c) relative humidity (d)and shortwave radiation (e) in the upper (U) middle (M) and lower (L) regions of the HRB (f) Comparison of the mean daily sensitivitycoefficients for major meteorological factors in the whole basin

middle and lower regions is almost the same and is greaterthan that in the upper region

The values of 119878WS in the three regions are positivethroughout the year ET

0is most sensitive to WS in the

beginning and end of a year but is insensitive to WS insummer (Figure 9(c)) The variation patterns of 119878WS for the

three regions are the same The values of 119878WS for the threeregions have significant differences during a year The valuein the lower region is the largest thus ET

0is more sensitive

to WS in the lower region than in the other two regionsRelatively strong negative sensitivity coefficients were

obtained for RH (Figure 9(d)) ET0is less sensitive to RH in


1960 1970 1980 1990 2000 2010

Year1960 1970 1980 1990 2000 2010

Year

1960 1970 1980 1990 2000 2010

Year1960 1970 1980 1990 2000 2010

Year

1960 1970 1980 1990 2000 2010

Year

ST

max

ST

min

SW

S

SR119904

SRH

035

030

025

020

033

030

027

024

036

033

030

027

024

minus002

minus004

minus006

minus008

minus030

minus035

minus040

minus045

minus050

S

NS

NS

S

S

Annual sensitivity coefficientLong-term average valueTrend line

Figure 10 Interannual variations of sensitivity of ET0in relation to 119879max 119879min WS RH and 119877

119904

the winter for the upper region compared with the two otherregions However ET

0is more negative sensitive to RH in the

lower region during April and SeptemberThe daily variation patterns of 119878

119877119904agree with those

of shortwave radiation (Figure 9(e)) ET0is insensitive to

119877119904in winter and 119878

119877119904increases and achieves its maximum

value in summer The variations of 119878119877119904

for the three regionsshow similar patterns whereas 119878

119877119904in the lower region is

significantly less than that in the upper and middle regionsThe variation of daily 119878

119877119904and 119878WS appears to be an opposite

pattern during a year Similar findings were reported byGonget al [19] 119878

119879maxand 119878

119877119904have a similar variation pattern

whereas 119878119879min

and 119878WS appear to have opposite patterns RHis the most sensitive factor and WS and 119879min are the leastsensitive factors in the whole basin throughout the year

Figure 10 shows the interannual variations of annualsensitivity coefficients from 1961 to 2014 The variationof annual 119878WS has a significant increasing trend whereasthe absolute values of 119878

119879minand 119878RH show that they have

statistically significant decreasing trends during 1961 and

2014 ET0becomes more sensitive to WS but less sensitive

to 119879min and RH The annual 119878119879max

and 119878119877119904

have increasingand decreasing trends respectively but their trends are notstatistically significant during the period of 1961ndash2014 Thisshows that the relative changes of the meteorological factors119879min and 119877119904 and the relative change of ET

0maintain a stable

ratio [41]Figure 11 describes the spatial patterns of the sensitivity

coefficients of ET0to the major meteorological factors across

the whole HRB The mean annual values of sensitivity for119879max 119879min WS RH and 119877

119904are 028 minus004 027 minus038 and

029 at the basin scale respectively RH is the most sensitivefactor and 119879min is less sensitive to ET

0over the whole basin

It seems that 119878119879max

and 119878119879min

have similar spatial patternswhereas spatial distributions of the absolute values of 119878

119879maxand 119878119879min

are opposite due to the negative sign of 119878119879min

Overallthere are three different spatial distributions for the fivemeteorological factors (1) 119878

119879maxand 119878WS have a similar spatial

pattern increasing from the south to the north of the basinwith significant spatial gradients (2) The spatial patterns of


38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

97∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E 103

∘30

998400E 97∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E 103

∘30

998400E 97∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E 103

∘30

998400E

Mean 028SD 0047

Mean minus004SD 0023

Mean 027SD 0058


Mean 029SD 0063

STminSWS

SRH SR119904

minus015ndashminus013minus013ndashminus011minus011ndashminus009minus009ndashminus007

minus007ndashminus005minus005ndashminus003minus003ndashminus001

013ndash016016ndash019019ndash022022ndash025


minus047ndashminus045minus045ndashminus043minus043ndashminus041minus041ndashminus039minus039ndashminus037




97∘30998400E

99∘0998400E

100∘30998400E

102∘0998400E

103∘30998400E

97∘30998400E

99∘0998400E

100∘30998400E

102∘0998400E

103∘30998400E

STmax012ndash015015ndash018018ndash021021ndash024


Figure 11 Spatial distribution of the mean annual sensitivity coefficients for ET0to the major meteorological factors (119879max 119879min WS RH

and 119877119904) during 1961ndash2014

119878119879min

and 119878119877119904are similar and the sensitivity for the two factors

decreases from the upper region to the lower region (3) Thespatial variation of 119878RH has no significant gradient from thelower region to the upper region

45 Contribution of the Trends of the Meteorological Factors toThat of119864119879

0 Thesensitivity coefficient describes the response

of ET0to changes in meteorological factors but is not able

to reflect change magnitude in ET0caused by meteorolog-

ical factors Namely ET0change is strongly sensitive to a

meteorological factor but the meteorological factor must notcause a significant change in ET

0 This is because other than

the sensitivity coefficients changes in ET0are influenced by

changes in meteorological factors as well Consequently (15)

is used to diagnose the contribution of meteorological factorsto ET0changes

As shown in Figure 12 the relative changes of monthlyseasonal and annual ET

0calculated using (15) well fit those of

the actual ET0from observed data This result illustrates that

sensitivity coefficients and changes in meteorological factorscould be used to analyze the contribution of one or moremeteorological factors to ET

0changes in the HRB

Figure 13 shows the contributions of meteorological fac-tor changes to relative changes in annual and seasonal ET

0for

the 9 stations in the HRB during 1961ndash2014 WS is the largestcontributor to ET

0change among meteorological factors in

the middle and lower regions The decreasing trends of WScause ET

0decreases with relative changes in ET

0of minus3

14 Advances in MeteorologyC(E

T 0)

()

TR(ET0) ()

Monthly R2= 096

Seasonal R2= 085

Annual R2= 093

40

20

0

minus20

minus40

40200minus20minus40

Figure 12 Relationship of 119862(ET0) to TR(ET

0) at different time

scales for all stations in the HRB 119862(ET0) is the sum of the relative

change of ET0contributed by changes in meteorological factors

using (15) TR(ET0) is the long-term relative change of ET

0from the

observed data

to minus18 corresponding to changes of minus30 to minus250mmHowever 119879min and 119877

119904trends from 1961 to 2014 have little

influence on the changes in ET0for themiddle-lower regions

For the upper region the trends of 119879max and 119879min for allstations significantly increase ET

0 and relative changes of

ET0are between 23 and 32 corresponding to changes of

19 to 26mmThepositive effects ofWS andRHonET0change

are similar to air temperature which cannot be ignored forstation U3

The contribution of the seasonal change ofmeteorologicalfactors to ET

0change is similar to that at an annual scale

WS is still the dominant contributor to ET0change for the

middle-lower regions at all seasons The relative changes ofET0caused by WS change are greater than 5 for most

stations in the middle and lower regions whereas the relativechanges of ET

0caused by other factors are less than 5 The

trends of seasonal 119879max and 119879min still result in an increasein ET

0for the upper region However there are differences

for the contribution levels of each meteorological factorin different seasons and regions For example the trendsof 119877119904for stations U1 U2 and M1 have more significant

contributions to the changes of ET0only in summer whereas

the 119877119904trends for all stations have little effect on the changes

of ET0in other seasons Moreover the 119879min trends in lower

regions do not contribute to changes in ET0in autumn

whereas the contribution of 119879min to ET0change is strong

in the other three seasons RH and WS for station U3 havesimilar effects on ET

0change for which the effect is stronger

in summer than that in other regions

5 Discussion

This paper carefully and thoroughly analyzed the trendsand spatial variations of the annual and seasonal ET

0for

different regions over the HRBThe spatial patterns of annualand seasonal ET

0during the last 54 years in this study are

consistent with the previous studies [34 35] However theoverall increasing trend (201mmsdot10 yrminus2) of annual ET

0for

the whole basin in this paper is different from the significantdecreasing trend reported by previous studies [29 30] Afterserious comparison and analysis the causes of the differencescome from inconsistent study areas and from differences inthe data time series treatment of missing data and analysismethods (i) Because the lower region of theHRB is the desertarea and is difficult to fix the basin divides four different basinareas have been defined by the Yellow River ConservancyCommission during different periodsThe basin area definedmost recently in 2005 is larger than the basin areas defined in1985 1995 and 2000 and can better describe the hydrologicalcharacteristics especially for the lower region of the basinThis study adopted the latest basin area data defined in 2005and previous studies adopted the earlier basin area datadefined in 1995 (ii) Different data time series may resultin different trends of annual ET

0 The trends of annual and

seasonal ET0calculated by the data series of 1959ndash1999 or

1961ndash2000 were earlier and shorter than the data series of1961ndash2014 in this study This latest data series covering morethan 50 years of climate stage and data quality during thislatest period is more reliable and is without missing data(iii) Because meteorological stations are scarce in the inlandarid basin in China the stations around the basin must beconsidered to increase the precision of calculation of regionalET0 Clearly the results obtained using only the 10 stations

in the previous studies are less reliable than those using 16stations related to the basin

Equation (15) was used to assess the contribution ofmeteorological factors to ET

0trends Figure 12 shows that

correlation of the estimated and the actual relative changesof ET

0are very good whereas the correlation coefficients

decrease with increasing time scales from monthly scaleto annual scale This illustrated that the accuracy of (15)decreases with increasing time scaleThe error sources of (15)are that (i) the five major meteorological factors cannot com-pletely cover all impact factors of the FAO P-M equation (ii)the selected factors interact with each other and are not totallyindependent and (iii) the annual averaging variations of thedaily sensitivity coefficient could produce different offsets toET0changes contributed by different meteorological factors

6 Summary

In arid regions investigating the causes of reference evapo-transpiration (ET

0) change is important for understanding

hydroclimatic change and the response of ecoenvironmentThe Heihe River Basin (HRB) the second largest inland riverbasin in China is divided into the upper middle and lowersubregions to diagnose the causes of ET

0changes in different

dryness environmentFirst the ET

0changes for the HRB were obtained by

FAO P-M method and meteorological data series from 16stations during 1961ndash2014 The seasonal and annual ET

0have

no significant increasing trends for the whole basin whereas



Winter Annual

10

0

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

97∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E 97

∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E

TmaxTmin

Rs

WSRH

10

010

0

10

0

10

0

97∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E97

∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E97

∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E

Figure 13 Contributions of meteorological factor changes to relative changes in ET0at annual and seasonal time scales for the stations in the

HRB An upward bar means that the factor trend causes a positive change in ET0 and a downward bar means that the factor trend causes a

negative change in ET0

there is a clear increasing spatial gradient from the upperregion to the lower region

Second the dimensionless sensitivity analysis showedthat relative humidity is most sensitive to ET

0change and

negative followed by maximum temperature and shortwaveradiation but with positive sensitivity The sensitivity ofminimum temperature is weakest and negative

Finally to quantify the influence magnitude of the majormeteorological factors on ET

0changes an approach to

integrating the sensitivity and changes of meteorologicalfactors is proposed Contribution analysis showed that windspeed is the dominant factor to cause the decrease of ET

0

for the middle and lower regions And the maximum andminimum temperatures are the main contributors to theincreasing trends of ET

0for the upper region Therefore

the ET0changes are mainly affected by aerodynamic factors

rather than radiative factors as dryness increase

Conflict of Interests

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

Acknowledgments

This research was supported by the National Natural ScienceFoundation of China (41271049) and the National BasicResearch Program of China (2009CB421305) The authorsthank the National Climate Center of China for offering


the meteorological data used in this study The first authorappreciates the constructive suggestions of Professor MoXingguo Associate Professor Sang Yanfang and DoctorZhang Dan for the improvement of this paper All authorswish to acknowledge the editor and anonymous reviewers fortheir patience and the detailed and helpful comments to theoriginal paper

References

[1] P G Oguntunde J Friesen N van de Giesen and H H GSavenije ldquoHydroclimatology of the Volta river basin in westAfrica trends and variability from 1901 to 2002rdquo Physics andChemistry of the Earth vol 31 no 18 pp 1180ndash1188 2006

[2] CMatsoukas N Benas N Hatzianastassiou K G Pavlakis MKanakidou and I Vardavas ldquoPotential evaporation trends overland between 1983ndash2008 driven by radiative fluxes or vapour-pressure deficitrdquoAtmospheric Chemistry and Physics vol 11 no15 pp 7601ndash7616 2011

[3] K Wang and R E Dickinson ldquoA review of global terrestrialevapotranspiration observation modeling climatology andclimatic variabilityrdquo Reviews of Geophysics vol 50 no 2 2012

[4] V S Golubev J H Lawrimore P Y Groisman et al ldquoEvapora-tion changes over the contiguous United States and the formerUSSR a reassessmentrdquoGeophysical Research Letters vol 28 no13 pp 2665ndash2668 2001

[5] X Liu Y Luo D ZhangM Zhang and C Liu ldquoRecent changesin pan-evaporation dynamics in Chinardquo Geophysical ResearchLetters vol 38 no 13 2011

[6] D H Burn and N M Hesch ldquoTrends in evaporation for theCanadian prairiesrdquo Journal of Hydrology vol 336 no 1-2 pp61ndash73 2007

[7] M L Roderick and G D Farquhar ldquoChanges in Australianpan evaporation from 1970 to 2002rdquo International Journal ofClimatology vol 24 no 9 pp 1077ndash1090 2004

[8] N Chattopadhyay and M Hulme ldquoEvaporation and potentialevapotranspiration in India under conditions of recent andfuture climate changerdquoAgricultural and Forest Meteorology vol87 no 1 pp 55ndash73 1997

[9] J Asanuma ldquoLong-term trend of pan evaporation measure-ments in Japan and its relevance to the variability of the hydro-logical cyclerdquo Tenki vol 51 no 9 pp 667ndash678 2004

[10] A-E Croitoru A Piticar C S Dragota and D C BuradaldquoRecent changes in reference evapotranspiration in RomaniardquoGlobal and Planetary Change vol 111 pp 127ndash136 2013

[11] S Saadi M Todorovic L Tanasijevic L S Pereira C Pizzigalliand P Lionello ldquoClimate change and Mediterranean agricul-ture impacts on winter wheat and tomato crop evapotranspi-ration irrigation requirements and yieldrdquo Agricultural WaterManagement vol 147 pp 103ndash115 2015

[12] A Sharifi and Y Dinpashoh ldquoSensitivity analysis of thepenman-monteith reference crop evapotranspiration to cli-matic variables in Iranrdquo Water Resources Management vol 28no 15 pp 5465ndash5476 2014

[13] S M Vicente-Serrano C Azorin-Molina A Sanchez-Lorenzoet al ldquoReference evapotranspiration variability and trends inSpain 1961ndash2011rdquoGlobal and Planetary Change vol 121 pp 26ndash40 2014

[14] M Gocic and S Trajkovic ldquoAnalysis of trends in reference evap-otranspiration data in a humid climaterdquo Hydrological SciencesJournal vol 59 no 1 pp 165ndash180 2014

[15] M Valipour ldquoImportance of solar radiation temperaturerelative humidity and wind speed for calculation of referenceevapotranspirationrdquo Archives of Agronomy and Soil Science vol61 no 2 pp 239ndash255 2015

[16] R G Allen L S Pereira D Raes and M Smith Crop Evap-otranspiration Guidelines for Computing Crop Water Require-ments vol 56 of FAO Irrigation and Drainage Paper Food andAgric Organ Rome Italy 1998

[17] M M Heydari R Aghamajidi G Beygipoor and M HeydarildquoComparison and evaluation of 38 equations for estimatingreference evapotranspiration in an arid regionrdquo Fresenius Envi-ronmental Bulletin vol 23 no 8 pp 1985ndash1996 2014

[18] K E Saxton ldquoSensitivity analyses of the combination evapo-transpiration equationrdquo Agricultural Meteorology vol 15 no 3pp 343ndash353 1975

[19] L Gong C-Y Xu D Chen S Halldin and Y D Chen ldquoSensi-tivity of the Penman-Monteith reference evapotranspiration tokey climatic variables in the Changjiang (Yangtze River) basinrdquoJournal of Hydrology vol 329 no 3-4 pp 620ndash629 2006

[20] S M Vicente-Serrano C Azorin-Molina A Sanchez-Lorenzoet al ldquoSensitivity of reference evapotranspiration to changes inmeteorological parameters in Spain (1961ndash2011)rdquo WaterResources Research vol 50 no 11 pp 8458ndash8480 2014

[21] R K Goyal ldquoSensitivity of evapotranspiration to global warm-ing a case study of arid zone of Rajasthan (India)rdquo AgriculturalWater Management vol 69 no 1 pp 1ndash11 2004

[22] Y Zhao X Zou J Zhang et al ldquoSpatio-temporal variationof reference evapotranspiration and aridity index in the LoessPlateau Region of China during 1961ndash2012rdquo Quaternary Inter-national vol 349 pp 196ndash206 2014

[23] B Wang and G Li ldquoQuantification of the reasons for referenceevapotranspiration changes over the Liaohe Delta NortheastChinardquo Scientia Geographica Sinica vol 34 no 10 pp 1233ndash1238 2014 (Chinese)

[24] H Xie and X Zhu ldquoReference evapotranspiration trends andtheir sensitivity to climatic change on the Tibetan Plateau(1970ndash2009)rdquo Hydrological Processes vol 27 no 25 pp 3685ndash3693 2013

[25] X Liu H Zheng C Liu and Y Cao ldquoSensitivity of the potentialevapotranspiration to key climatic variables in the Haihe RiverBasinrdquo Resources Science vol 31 no 9 pp 1470ndash1476 2009(Chinese)

[26] G Papaioannou G Kitsara and S Athanasatos ldquoImpact ofglobal dimming and brightening on reference evapotranspira-tion in Greecerdquo Journal of Geophysical Research Atmospheresvol 116 no 9 Article ID D09107 2011

[27] C-S Rim ldquoA sensitivity and error analysis for the penmanevapotranspiration modelrdquo KSCE Journal of Civil Engineeringvol 8 no 2 pp 249ndash254 2004

[28] Q Liu Z Yang B Cui and T Sun ldquoThe temporal trends ofreference evapotranspiration and its sensitivity to key meteoro-logical variables in the Yellow River Basin ChinardquoHydrologicalProcesses vol 24 no 15 pp 2171ndash2181 2010

[29] N Ma N Wang P Wang Y Sun and C Dong ldquoTemporal andspatial variation characteristics and quantification of the affectfactors for reference evapotranspiration in Heihe River basinrdquoJournal of Natural Resources vol 27 no 6 pp 975ndash989 2012(Chinese)

[30] J Zhao Z Xu and D Zuo ldquoSpatiotemporal variation ofpotential evapotranspiration in the Heihe River basinrdquo Journalof Beijing Normal University Natural Science vol 49 no 2-3 pp164ndash169 2013 (Chinese)


[31] C-Y Xu L Gong T Jiang D Chen andV P Singh ldquoAnalysis ofspatial distribution and temporal trend of reference evapotran-spiration and pan evaporation in Changjiang (Yangtze River)catchmentrdquo Journal of Hydrology vol 327 no 1-2 pp 81ndash932006

[32] A Thomas ldquoSpatial and temporal characteristics of potentialevapotranspiration trends over Chinardquo International Journal ofClimatology vol 20 no 4 pp 381ndash396 2000

[33] C Liu D Zhang X Liu and C Zhao ldquoSpatial and temporalchange in the potential evapotranspiration sensitivity to meteo-rological factors in China (1960ndash2007)rdquo Journal of GeographicalSciences vol 22 no 1 pp 3ndash14 2012

[34] H BMann ldquoNonparametric tests against trendrdquo Econometricavol 13 no 3 pp 245ndash259 1945

[35] M G Kendall Rank Correlation Methods Griffin Oxford UK1948

[36] S Yue and P Pilon ldquoA comparison of the power of the ttest Mann-Kendall and bootstrap tests for trend detectionrdquoHydrological Sciences Journal vol 49 no 1 pp 21ndash37 2004

[37] R M Hirsch J R Slack and R A Smith ldquoTechniques oftrend analysis for monthly water quality datardquoWater ResourcesResearch vol 18 no 1 pp 107ndash121 1982

[38] R M Hirsch and J R Slack ldquoA nonparametric trend testfor seasonal data with serial dependencerdquo Water ResourcesResearch vol 20 no 6 pp 727ndash732 1984

[39] A G Smajstrla F S Zazueta and G M Schmidt ldquoSensitivityof potential evapotranspiration to four climatic variables inFloridardquo ProceedingsmdashSoil and Crop Science Society of Floridavol 46 1987 paper presented at

[40] P Greve L Gudmundsson B Orlowsky and S I SeneviratneldquoIntroducing a probabilistic Budyko frameworkrdquo GeophysicalResearch Letters vol 42 no 7 pp 2261ndash2269 2015

[41] H Zheng X Liu C Liu X Dai and R Zhu ldquoAssessingcontributions to panevaporation trends in Haihe River BasinChinardquo Journal of Geophysical Research Atmospheres vol 114no 24 Article ID D24105 2009

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


different regions For example air temperature wind speedand relative humidity have stronger effects on ET

0change in

Spain [20] Air temperature andwind speed are the dominantvariables influencing ET

0in Iran [12] Air temperature is the

most sensitive variable to ET0change in India [21] Similar

results have also been found in some regions of China inwhichwind speed air temperature and vapor pressure deficitare the major sensitive factors for ET

0change in such areas as

the Loess Plateau Region [22] the Liaohe delta [23] the TibetPlateau [24] the Changjiang River Basin [19] and the HaiheRiver Basin [25] Some studies proposed a close agreementbetween changes in ET

0and solar energy in Greece [26]

Korea [27] and the Yellow River Basin [28] Sensitivityanalysis could only describe the responses of ET

0to changes

in individual factor However it cannot determine howmuchthe impact of each meteorological factor on ET

0change is

The Heihe River basin (HRB) the second largest inlandriver basin in northwestern China consists of three regionswith different landscapes and climate conditions where theupper mountainous region is semiarid and natural with littlehuman interference the middle region is dry and intensivelyirrigated plain and the lower region is an extremely dry Gobidesert plain The spatial variation of ET

0in such basin may

supply more information of regional response to the climateThe previous studies only reported the spatiotemporal varia-tions of ET

0[29 30] at a given period but there is no common

understanding of ET0change so far due to different data

time series The aim of this paper is to clarify the effect ofmeteorological factors on ET

0change by comprehensively

analyzing the sensitivity of ET0change and contributions

of meteorological factors in the HRB using reliable andcomplete daily meteorological data from 16 stations for theperiod 1961ndash2014 This paper will determine (1) the spatialpattern and temporal trends of ET

0for the HRB (2) the

sensitivity of ET0to meteorological factors and (3) the

contributions of the meteorological factors to ET0change

2 Study Area and Data

21 Study Area As shown in Figure 1 the drainage mapand the basin border of the HRB are extracted using a90m resolution digital elevation model (DEM) data from theShuttle Radar Topography Mission (SRTM) website of theNASA (httpsrtmcsicgiarorgSELECTIONinputCoordasp) (basin length 820 km total area 143000 km2 elevation870ndash5545m)

The HRB is divided into three regions according to basincharacteristics shown in Figure 1 The upper mountainousregion belongs to the cold and semiarid mountain zonewith an elevation from 2000 to 5000m annual mean tem-perature of less than 2∘C pan evaporation of 700mmyrminus1and precipitation of 350ndash400mmyrminus1 The middle regionis the main irrigation zone and residential area with morethan 90 of the total population of the basin it has aprecipitation of 100ndash250mmyrminus1 and pan evaporation of2000mmyrminus1 The lower region is covered by the arid Gobi

U3

U2U1

M4

M3

M2 M1

L2

L1

N

37∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

94∘0998400E

95∘0998400E

96∘0998400E

97∘0998400E

98∘0998400E

99∘0998400E

100∘0998400E

101∘0998400E

102∘0998400E

Lower

Middle

UpperQilian Mountain(km)

Elev

atio

n (m

)

5545

870

0 50 100 200

Radiation stationMeteorological stationRiver

Figure 1 Location of the HRB and spatial distribution of themeteorological and radiation stations U M and L represent theupper middle and lower regions in the basin respectively

desert in the north of the basin with an elevation of 870ndash1500mand is characterized by an extremely arid climate withpan evaporation of 3500mmyrminus1 and precipitation of 10ndash50mmyrminus1

22 Data In this study daily meteorological data of 16stations from 1961 to 2014 in and around the HRB areavailable from the National Climatic Centre of the ChinaMeteorological Administration The three solar radiationstations correspond to the upper the middle and the lowerregion (Figure 1) The data set includes daily observationsof atmospheric pressure maximum and minimum air tem-peratures at 2m height (119879max 119879min) relative humidity at2m height (RH) daily sunshine duration pan evaporationmeasured using a metal pan 20 cm in diameter and 10 cmhigh installed 70 cm above the ground and wind speedmeasured at 10m height which was transformed to windspeed at 2m height (WS) by the wind profile relationshipfrom Chapter 3 of the FAO paper 56 [16] In addition thethree radiation stations were used to calibrate the Angstromparameters of extraterrestrial radiation reaching the earth onclear days in the FAO P-M equation The spatial patterns ofthe meteorological factors ET

0 and sensitivity coefficients

were obtained by the inverse distance weight (IDW) interpo-lation method

In this study the four seasons of the HRB are defined asspring (fromMarch to May) summer (from June to August)autumn (from September to November) and winter (fromDecember to February)


3 Methodology




0is described as

ET0

=0408Δ (119877

119899minus 119866) + 120574 (900 (119879mean + 273)) 1199062 (119890119904 minus 119890119886)

Δ + 120574 (1 + 0341199062)

(1)




2is the wind speed






119877119904= (119886 + 119887

119899

119873)119877119886 (2)



119886is the





= 119905 + 119887 (3)




119894



12(one for


119894annual


1 1198832 119883

12)

119883119894= (1198831198941 1198831198942 119883

11989412)

(4)







119878119894=

119899119894minus1

sum119896=1

119899119894

sum119895=119896+1

sign (119909119894119895minus 119909119894119896) (5)

where

sign (120579) =

1 120579 gt 0

0 120579 = 0

minus1 120579 lt 0

(6)



119864 (119878119894) = 0 (7a)

Var (119878119894)

=1

18

1003816100381610038161003816100381610038161003816100381610038161003816

119899119894(119899119894minus 1) (2119899

119894+ 5) minus

119892119894

sum119905119894

119905119894(119905119894minus 1) (2119905

119894+ 5)

1003816100381610038161003816100381610038161003816100381610038161003816

(7b)





given by

119878 =

119898

sum119894=1

119878119894 (8)


119864 (119878) =

119898

sum119894=1

119864 (119878119894) (9a)

Var (119878) =119898

sum119894=1

Var (119878119894) +

119898

sum119894=1

119898

sum119895=1

cov (119878119894119878119895) (9b)


RsR

a

nN

a = 0213 b = 0611

R2= 0873

10

08

06

04

02

00100806040200

(a)

RsR

a

a = 0218 b = 0531

R2= 0844

10

08

06

04

02

00100806040200

nN

(b)

RsR

a

a = 0260 b = 0519

R2= 0815

10

08

06

04

02

00100806040200

nN

(c)



variables so cov(119878119894119878119895) = 0



119885 =

(119878 minus 1)

radic119881 (119878) 119878 gt 0

0 119878 = 0

(119878 + 1)

radic119881 (119878) 119878 lt 0

(10)








119878 (119909119894) = limΔ119909119894rarr0

(ΔET0ET0

Δ119909119894119909119894

) =120597ET0

120597119909119894

sdot119909119894

ET0

(11)


119894) is the






0will increase


0is sensitive




119878119879min



0change to the per-





0


1 1199092 119909

119899)

where 1199091 1199092 119909




ΔET0= sum

120597ET0

120597119909119894

sdot Δ119909119894+ 120575 (12)



119894is the 119894th




0with respect


0(the average value


ΔET0

ET0

= sum120597ET0

120597119909119894

sdotΔ119909119894

ET0

+ 120576 (13)


0during a given




ΔET0

ET0

= sum120597ET0

120597119909119894

sdot119909119894

ET0

Δ119909119894

119909119894

+ 120576 (14)



119909119894 If we let

119862(119909119894) = sum 119878


ΔET0

ET0

asymp sum119862(119909119894) (15)



WS RH and 119877119904




4 Results





0


0both










0




0


0




0from


0in










R2= 0967

400

300

200

100

0

0 50 100 150 200

Summer

Autumn

Spring

Winter


Epa

n(m

m m

onth

minus1)


(a)

R2= 0906

Epa

n(m

m yr

minus1)

5000

4000

3000

2000

1000

0

600 800 1000 1200 1400 1600


ET0 (mm yrminus1)

(b)


Month

250

200

150

100

50

01 2 3 4 5 6 7 8 9 10 11 12

ET0

(mm

mon

thminus1)



0 respectively










0has no


0in the


















119904



1960 1970 1980 1990 2000 2010

420

400

380

360

340

320

ET0

(mm

yrminus1)

(a)


(NS)

1960 1970 1980 1990 2000 2010

580

560

540

520

500

480

460

ET0

(mm

yrminus1)

(b)


1960 1970 1980 1990 2000 2010

260

240

220

200

ET0

(mm

yrminus1)

(c)


1960 1970 1980 1990 2000 2010

120

100

80

60

40

ET0

(mm

yrminus1)

(d)

AnnualSlope 020

(NS)

1960 1970 1980 1990 2000 2010

1300

1250

1200

1150

1100

1050


ET0

(mm

yrminus1)

ET0 change

(e)


test












Winter


Annual

Annual


Spring ummer Autumn

Winter Annual

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

97∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E 97

∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E

97∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E 97

∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E

97∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E

Max 470Min 232SD 49

Max 700Min 310SD 84

Max 290Min 145SD 30

Max 59Min 93SD 58

Max 1553Min 757SD 166



0






0(Figure 4) and




WWWW

Tm

ean(∘

C)

WS

(m sminus

1)

RH (

)

Rs

(MJ m

minus2

dminus1)

2 4 6 8 10 122 4 6 8 10 122 4 6 8 10 122 4 6 8 10 12

30

20

10

0

minus10

minus20

5

4

3

2

1

80

60

40

20

30

25

20

15

10


UUUU

Tm

ean(∘

C)

WS

(m sminus

1)

RH (

)

Rs

(MJ m

minus2

dminus1)

2 4 6 8 10 12 2 4 6 8 10 12 2 4 6 8 10 12 2 4 6 8 10 12

30

20

10

0

minus10

minus20

5

4

3

2

1

80

60

40

20

30

25

20

15

10


MMMM

Tm

ean(∘

C)

WS

(m sminus

1)

RH (

)

Rs

(MJ m

minus2

dminus1)

2 4 6 8 10 122 4 6 8 10 122 4 6 8 10 122 4 6 8 10 12

30

20

10

0

minus10

minus20

5

4

3

2

1

80

60

40

20

30

25

20

15

10


LLLL

Tm

ean(∘

C)

WS

(m sminus

1)

RH (

)

Rs

(MJ m

minus2

dminus1)

2 4 6 8 10 12 2 4 6 8 10 12 2 4 6 8 10 12 2 4 6 8 10 12

30

20

10

0

minus10

minus20

5

4

3

2

1

80

60

40

20

30

25

20

15

10















1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

Tm

ean(∘

C)

WS

(m sminus

1)

RH (

)

Rs

(MJ m

minus2

dminus1)

YearYearYearYear

Slope 0036 (S)10

9

8

7

6

5

35

30

25

20

15

55

50

45

40

35

185

180

175

170

165


1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

Tm

ean(∘

C)

WS

(m sminus

1)

RH (

)

Rs

(MJ m

minus2

dminus1)

Year Year Year Year

Slope 0032 (S)35

30

25

20

15

60

55

50

45

40

35

185

180

175

170

165

U U U U4

3

2

1

Slope minus0013 (S)

Slope minus0035 (S)


1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

Tm

ean(∘

C)

WS

(m sminus

1)

RH (

)

Rs

(MJ m

minus2

dminus1)

YearYearYearYear


9

8

7

6

5

35

30

25

20

15

55

50

45

40

35

185

180

175

170

165

M M M M

Slope minus0048 (S)

Slope minus0017 (S)

1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

Tm

ean(∘

C)

WS

(m sminus

1)

RH (

)

Rs

(MJ m

minus2

dminus1)

Year Year Year Year

Slope 0038 (S)10

9

8

7

6

5

35

30

25

20

15

55

50

45

40

35

185

180

175

170

165

L L L L

Slope minus0020 (S)

Slope minus0059 (S)

Slope minus0002 (S)








those of RH


and 119878119879min




119879maxand 119878

119879minare


119879maxand 119878119879min





119879minfor the


ST

max

Day0 50 100 150 200 250 300 350

06

04

02

00

minus02

LMU

(a)

ST

min

Day0 50 100 150 200 250 300 350

01

00

minus01

minus02

minus03

LMU

(b)

SW

S

Day0 50 100 150 200 250 300 350

05

04

03

02

01

LMU

(c)

SRH

Day0 50 100 150 200 250 300 350

minus02

minus04

minus06

minus08

minus10

LMU

(d)

SR119904

Day0 50 100 150 200 250 300 350

06

04

02

00

minus02

LMU

(e)

Sens

itivi

ty co

effici

ents

Day0 50 100 150 200 250 300 350

06

03

00

minus03

minus06

minus09

Tmax

Tmin

RsWSRH

(f)







0is more sensitive




1960 1970 1980 1990 2000 2010

Year1960 1970 1980 1990 2000 2010

Year

1960 1970 1980 1990 2000 2010

Year1960 1970 1980 1990 2000 2010

Year

1960 1970 1980 1990 2000 2010

Year

ST

max

ST

min

SW

S

SR119904

SRH

035

030

025

020

033

030

027

024

036

033

030

027

024

minus002

minus004

minus006

minus008

minus030

minus035

minus040

minus045

minus050

S

NS

NS

S

S



119904






119877119904in winter and 119878








119879maxand 119878









and 119878119877119904


0maintain a stable








and 119878119879min


119879maxand 119878119879min






38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

97∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E 103

∘30

998400E 97∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E 103

∘30

998400E 97∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E 103

∘30

998400E

Mean 028SD 0047


Mean 027SD 0058


Mean 029SD 0063

STminSWS

SRH SR119904









97∘30998400E

99∘0998400E

100∘30998400E

102∘0998400E

103∘30998400E

97∘30998400E

99∘0998400E

100∘30998400E

102∘0998400E

103∘30998400E




and 119877119904) during 1961ndash2014

119878119879min

















0changes in the HRB


0for





0of minus3


T 0)

()

TR(ET0) ()

Monthly R2= 096

Seasonal R2= 085

Annual R2= 093

40

20

0

minus20

minus40

40200minus20minus40






0from the

observed data


























5 Discussion


0for




0for











6 Summary








0have




Winter Annual

10

0

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

97∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E 97

∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E

TmaxTmin

Rs

WSRH

10

010

0

10

0

10

0

97∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E97

∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E97

∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E






0change and





0







Acknowledgments




References




















































Volume 2014

Mining


Journal of



Geophysics







Journal of




Advances in











Geology Advances in


3 Methodology




0is described as

ET0

=0408Δ (119877

119899minus 119866) + 120574 (900 (119879mean + 273)) 1199062 (119890119904 minus 119890119886)

Δ + 120574 (1 + 0341199062)

(1)




2is the wind speed






119877119904= (119886 + 119887

119899

119873)119877119886 (2)



119886is the





= 119905 + 119887 (3)




119894



12(one for


119894annual


1 1198832 119883

12)

119883119894= (1198831198941 1198831198942 119883

11989412)

(4)







119878119894=

119899119894minus1

sum119896=1

119899119894

sum119895=119896+1

sign (119909119894119895minus 119909119894119896) (5)

where

sign (120579) =

1 120579 gt 0

0 120579 = 0

minus1 120579 lt 0

(6)



119864 (119878119894) = 0 (7a)

Var (119878119894)

=1

18

1003816100381610038161003816100381610038161003816100381610038161003816

119899119894(119899119894minus 1) (2119899

119894+ 5) minus

119892119894

sum119905119894

119905119894(119905119894minus 1) (2119905

119894+ 5)

1003816100381610038161003816100381610038161003816100381610038161003816

(7b)





given by

119878 =

119898

sum119894=1

119878119894 (8)


119864 (119878) =

119898

sum119894=1

119864 (119878119894) (9a)

Var (119878) =119898

sum119894=1

Var (119878119894) +

119898

sum119894=1

119898

sum119895=1

cov (119878119894119878119895) (9b)


RsR

a

nN

a = 0213 b = 0611

R2= 0873

10

08

06

04

02

00100806040200

(a)

RsR

a

a = 0218 b = 0531

R2= 0844

10

08

06

04

02

00100806040200

nN

(b)

RsR

a

a = 0260 b = 0519

R2= 0815

10

08

06

04

02

00100806040200

nN

(c)



variables so cov(119878119894119878119895) = 0



119885 =

(119878 minus 1)

radic119881 (119878) 119878 gt 0

0 119878 = 0

(119878 + 1)

radic119881 (119878) 119878 lt 0

(10)








119878 (119909119894) = limΔ119909119894rarr0

(ΔET0ET0

Δ119909119894119909119894

) =120597ET0

120597119909119894

sdot119909119894

ET0

(11)


119894) is the






0will increase


0is sensitive




119878119879min



0change to the per-





0


1 1199092 119909

119899)

where 1199091 1199092 119909




ΔET0= sum

120597ET0

120597119909119894

sdot Δ119909119894+ 120575 (12)



119894is the 119894th




0with respect


0(the average value


ΔET0

ET0

= sum120597ET0

120597119909119894

sdotΔ119909119894

ET0

+ 120576 (13)


0during a given




ΔET0

ET0

= sum120597ET0

120597119909119894

sdot119909119894

ET0

Δ119909119894

119909119894

+ 120576 (14)



119909119894 If we let

119862(119909119894) = sum 119878


ΔET0

ET0

asymp sum119862(119909119894) (15)



WS RH and 119877119904




4 Results





0


0both










0




0


0




0from


0in










R2= 0967

400

300

200

100

0

0 50 100 150 200

Summer

Autumn

Spring

Winter


Epa

n(m

m m

onth

minus1)


(a)

R2= 0906

Epa

n(m

m yr

minus1)

5000

4000

3000

2000

1000

0

600 800 1000 1200 1400 1600


ET0 (mm yrminus1)

(b)


Month

250

200

150

100

50

01 2 3 4 5 6 7 8 9 10 11 12

ET0

(mm

mon

thminus1)



0 respectively










0has no


0in the


















119904



1960 1970 1980 1990 2000 2010

420

400

380

360

340

320

ET0

(mm

yrminus1)

(a)


(NS)

1960 1970 1980 1990 2000 2010

580

560

540

520

500

480

460

ET0

(mm

yrminus1)

(b)


1960 1970 1980 1990 2000 2010

260

240

220

200

ET0

(mm

yrminus1)

(c)


1960 1970 1980 1990 2000 2010

120

100

80

60

40

ET0

(mm

yrminus1)

(d)

AnnualSlope 020

(NS)

1960 1970 1980 1990 2000 2010

1300

1250

1200

1150

1100

1050


ET0

(mm

yrminus1)

ET0 change

(e)


test












Winter


Annual

Annual


Spring ummer Autumn

Winter Annual

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

97∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E 97

∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E

97∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E 97

∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E

97∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E

Max 470Min 232SD 49

Max 700Min 310SD 84

Max 290Min 145SD 30

Max 59Min 93SD 58

Max 1553Min 757SD 166



0






0(Figure 4) and




WWWW

Tm

ean(∘

C)

WS

(m sminus

1)

RH (

)

Rs

(MJ m

minus2

dminus1)

2 4 6 8 10 122 4 6 8 10 122 4 6 8 10 122 4 6 8 10 12

30

20

10

0

minus10

minus20

5

4

3

2

1

80

60

40

20

30

25

20

15

10


UUUU

Tm

ean(∘

C)

WS

(m sminus

1)

RH (

)

Rs

(MJ m

minus2

dminus1)

2 4 6 8 10 12 2 4 6 8 10 12 2 4 6 8 10 12 2 4 6 8 10 12

30

20

10

0

minus10

minus20

5

4

3

2

1

80

60

40

20

30

25

20

15

10


MMMM

Tm

ean(∘

C)

WS

(m sminus

1)

RH (

)

Rs

(MJ m

minus2

dminus1)

2 4 6 8 10 122 4 6 8 10 122 4 6 8 10 122 4 6 8 10 12

30

20

10

0

minus10

minus20

5

4

3

2

1

80

60

40

20

30

25

20

15

10


LLLL

Tm

ean(∘

C)

WS

(m sminus

1)

RH (

)

Rs

(MJ m

minus2

dminus1)

2 4 6 8 10 12 2 4 6 8 10 12 2 4 6 8 10 12 2 4 6 8 10 12

30

20

10

0

minus10

minus20

5

4

3

2

1

80

60

40

20

30

25

20

15

10















1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

Tm

ean(∘

C)

WS

(m sminus

1)

RH (

)

Rs

(MJ m

minus2

dminus1)

YearYearYearYear

Slope 0036 (S)10

9

8

7

6

5

35

30

25

20

15

55

50

45

40

35

185

180

175

170

165


1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

Tm

ean(∘

C)

WS

(m sminus

1)

RH (

)

Rs

(MJ m

minus2

dminus1)

Year Year Year Year

Slope 0032 (S)35

30

25

20

15

60

55

50

45

40

35

185

180

175

170

165

U U U U4

3

2

1

Slope minus0013 (S)

Slope minus0035 (S)


1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

Tm

ean(∘

C)

WS

(m sminus

1)

RH (

)

Rs

(MJ m

minus2

dminus1)

YearYearYearYear


9

8

7

6

5

35

30

25

20

15

55

50

45

40

35

185

180

175

170

165

M M M M

Slope minus0048 (S)

Slope minus0017 (S)

1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

Tm

ean(∘

C)

WS

(m sminus

1)

RH (

)

Rs

(MJ m

minus2

dminus1)

Year Year Year Year

Slope 0038 (S)10

9

8

7

6

5

35

30

25

20

15

55

50

45

40

35

185

180

175

170

165

L L L L

Slope minus0020 (S)

Slope minus0059 (S)

Slope minus0002 (S)








those of RH


and 119878119879min




119879maxand 119878

119879minare


119879maxand 119878119879min





119879minfor the


ST

max

Day0 50 100 150 200 250 300 350

06

04

02

00

minus02

LMU

(a)

ST

min

Day0 50 100 150 200 250 300 350

01

00

minus01

minus02

minus03

LMU

(b)

SW

S

Day0 50 100 150 200 250 300 350

05

04

03

02

01

LMU

(c)

SRH

Day0 50 100 150 200 250 300 350

minus02

minus04

minus06

minus08

minus10

LMU

(d)

SR119904

Day0 50 100 150 200 250 300 350

06

04

02

00

minus02

LMU

(e)

Sens

itivi

ty co

effici

ents

Day0 50 100 150 200 250 300 350

06

03

00

minus03

minus06

minus09

Tmax

Tmin

RsWSRH

(f)







0is more sensitive




1960 1970 1980 1990 2000 2010

Year1960 1970 1980 1990 2000 2010

Year

1960 1970 1980 1990 2000 2010

Year1960 1970 1980 1990 2000 2010

Year

1960 1970 1980 1990 2000 2010

Year

ST

max

ST

min

SW

S

SR119904

SRH

035

030

025

020

033

030

027

024

036

033

030

027

024

minus002

minus004

minus006

minus008

minus030

minus035

minus040

minus045

minus050

S

NS

NS

S

S



119904






119877119904in winter and 119878








119879maxand 119878









and 119878119877119904


0maintain a stable








and 119878119879min


119879maxand 119878119879min






38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

97∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E 103

∘30

998400E 97∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E 103

∘30

998400E 97∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E 103

∘30

998400E

Mean 028SD 0047


Mean 027SD 0058


Mean 029SD 0063

STminSWS

SRH SR119904









97∘30998400E

99∘0998400E

100∘30998400E

102∘0998400E

103∘30998400E

97∘30998400E

99∘0998400E

100∘30998400E

102∘0998400E

103∘30998400E




and 119877119904) during 1961ndash2014

119878119879min

















0changes in the HRB


0for





0of minus3


T 0)

()

TR(ET0) ()

Monthly R2= 096

Seasonal R2= 085

Annual R2= 093

40

20

0

minus20

minus40

40200minus20minus40






0from the

observed data


























5 Discussion


0for




0for











6 Summary








0have




Winter Annual

10

0

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

97∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E 97

∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E

TmaxTmin

Rs

WSRH

10

010

0

10

0

10

0

97∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E97

∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E97

∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E






0change and





0







Acknowledgments




References




















































Volume 2014

Mining


Journal of



Geophysics







Journal of




Advances in











Geology Advances in


RsR

a

nN

a = 0213 b = 0611

R2= 0873

10

08

06

04

02

00100806040200

(a)

RsR

a

a = 0218 b = 0531

R2= 0844

10

08

06

04

02

00100806040200

nN

(b)

RsR

a

a = 0260 b = 0519

R2= 0815

10

08

06

04

02

00100806040200

nN

(c)



variables so cov(119878119894119878119895) = 0



119885 =

(119878 minus 1)

radic119881 (119878) 119878 gt 0

0 119878 = 0

(119878 + 1)

radic119881 (119878) 119878 lt 0

(10)








119878 (119909119894) = limΔ119909119894rarr0

(ΔET0ET0

Δ119909119894119909119894

) =120597ET0

120597119909119894

sdot119909119894

ET0

(11)


119894) is the






0will increase


0is sensitive




119878119879min



0change to the per-





0


1 1199092 119909

119899)

where 1199091 1199092 119909




ΔET0= sum

120597ET0

120597119909119894

sdot Δ119909119894+ 120575 (12)



119894is the 119894th




0with respect


0(the average value


ΔET0

ET0

= sum120597ET0

120597119909119894

sdotΔ119909119894

ET0

+ 120576 (13)


0during a given




ΔET0

ET0

= sum120597ET0

120597119909119894

sdot119909119894

ET0

Δ119909119894

119909119894

+ 120576 (14)



119909119894 If we let

119862(119909119894) = sum 119878


ΔET0

ET0

asymp sum119862(119909119894) (15)



WS RH and 119877119904




4 Results





0


0both










0




0


0




0from


0in










R2= 0967

400

300

200

100

0

0 50 100 150 200

Summer

Autumn

Spring

Winter


Epa

n(m

m m

onth

minus1)


(a)

R2= 0906

Epa

n(m

m yr

minus1)

5000

4000

3000

2000

1000

0

600 800 1000 1200 1400 1600


ET0 (mm yrminus1)

(b)


Month

250

200

150

100

50

01 2 3 4 5 6 7 8 9 10 11 12

ET0

(mm

mon

thminus1)



0 respectively










0has no


0in the


















119904



1960 1970 1980 1990 2000 2010

420

400

380

360

340

320

ET0

(mm

yrminus1)

(a)


(NS)

1960 1970 1980 1990 2000 2010

580

560

540

520

500

480

460

ET0

(mm

yrminus1)

(b)


1960 1970 1980 1990 2000 2010

260

240

220

200

ET0

(mm

yrminus1)

(c)


1960 1970 1980 1990 2000 2010

120

100

80

60

40

ET0

(mm

yrminus1)

(d)

AnnualSlope 020

(NS)

1960 1970 1980 1990 2000 2010

1300

1250

1200

1150

1100

1050


ET0

(mm

yrminus1)

ET0 change

(e)


test












Winter


Annual

Annual


Spring ummer Autumn

Winter Annual

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

97∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E 97

∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E

97∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E 97

∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E

97∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E

Max 470Min 232SD 49

Max 700Min 310SD 84

Max 290Min 145SD 30

Max 59Min 93SD 58

Max 1553Min 757SD 166



0






0(Figure 4) and




WWWW

Tm

ean(∘

C)

WS

(m sminus

1)

RH (

)

Rs

(MJ m

minus2

dminus1)

2 4 6 8 10 122 4 6 8 10 122 4 6 8 10 122 4 6 8 10 12

30

20

10

0

minus10

minus20

5

4

3

2

1

80

60

40

20

30

25

20

15

10


UUUU

Tm

ean(∘

C)

WS

(m sminus

1)

RH (

)

Rs

(MJ m

minus2

dminus1)

2 4 6 8 10 12 2 4 6 8 10 12 2 4 6 8 10 12 2 4 6 8 10 12

30

20

10

0

minus10

minus20

5

4

3

2

1

80

60

40

20

30

25

20

15

10


MMMM

Tm

ean(∘

C)

WS

(m sminus

1)

RH (

)

Rs

(MJ m

minus2

dminus1)

2 4 6 8 10 122 4 6 8 10 122 4 6 8 10 122 4 6 8 10 12

30

20

10

0

minus10

minus20

5

4

3

2

1

80

60

40

20

30

25

20

15

10


LLLL

Tm

ean(∘

C)

WS

(m sminus

1)

RH (

)

Rs

(MJ m

minus2

dminus1)

2 4 6 8 10 12 2 4 6 8 10 12 2 4 6 8 10 12 2 4 6 8 10 12

30

20

10

0

minus10

minus20

5

4

3

2

1

80

60

40

20

30

25

20

15

10















1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

Tm

ean(∘

C)

WS

(m sminus

1)

RH (

)

Rs

(MJ m

minus2

dminus1)

YearYearYearYear

Slope 0036 (S)10

9

8

7

6

5

35

30

25

20

15

55

50

45

40

35

185

180

175

170

165


1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

Tm

ean(∘

C)

WS

(m sminus

1)

RH (

)

Rs

(MJ m

minus2

dminus1)

Year Year Year Year

Slope 0032 (S)35

30

25

20

15

60

55

50

45

40

35

185

180

175

170

165

U U U U4

3

2

1

Slope minus0013 (S)

Slope minus0035 (S)


1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

Tm

ean(∘

C)

WS

(m sminus

1)

RH (

)

Rs

(MJ m

minus2

dminus1)

YearYearYearYear


9

8

7

6

5

35

30

25

20

15

55

50

45

40

35

185

180

175

170

165

M M M M

Slope minus0048 (S)

Slope minus0017 (S)

1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

Tm

ean(∘

C)

WS

(m sminus

1)

RH (

)

Rs

(MJ m

minus2

dminus1)

Year Year Year Year

Slope 0038 (S)10

9

8

7

6

5

35

30

25

20

15

55

50

45

40

35

185

180

175

170

165

L L L L

Slope minus0020 (S)

Slope minus0059 (S)

Slope minus0002 (S)








those of RH


and 119878119879min




119879maxand 119878

119879minare


119879maxand 119878119879min





119879minfor the


ST

max

Day0 50 100 150 200 250 300 350

06

04

02

00

minus02

LMU

(a)

ST

min

Day0 50 100 150 200 250 300 350

01

00

minus01

minus02

minus03

LMU

(b)

SW

S

Day0 50 100 150 200 250 300 350

05

04

03

02

01

LMU

(c)

SRH

Day0 50 100 150 200 250 300 350

minus02

minus04

minus06

minus08

minus10

LMU

(d)

SR119904

Day0 50 100 150 200 250 300 350

06

04

02

00

minus02

LMU

(e)

Sens

itivi

ty co

effici

ents

Day0 50 100 150 200 250 300 350

06

03

00

minus03

minus06

minus09

Tmax

Tmin

RsWSRH

(f)







0is more sensitive




1960 1970 1980 1990 2000 2010

Year1960 1970 1980 1990 2000 2010

Year

1960 1970 1980 1990 2000 2010

Year1960 1970 1980 1990 2000 2010

Year

1960 1970 1980 1990 2000 2010

Year

ST

max

ST

min

SW

S

SR119904

SRH

035

030

025

020

033

030

027

024

036

033

030

027

024

minus002

minus004

minus006

minus008

minus030

minus035

minus040

minus045

minus050

S

NS

NS

S

S



119904






119877119904in winter and 119878








119879maxand 119878









and 119878119877119904


0maintain a stable








and 119878119879min


119879maxand 119878119879min






38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

97∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E 103

∘30

998400E 97∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E 103

∘30

998400E 97∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E 103

∘30

998400E

Mean 028SD 0047


Mean 027SD 0058


Mean 029SD 0063

STminSWS

SRH SR119904









97∘30998400E

99∘0998400E

100∘30998400E

102∘0998400E

103∘30998400E

97∘30998400E

99∘0998400E

100∘30998400E

102∘0998400E

103∘30998400E




and 119877119904) during 1961ndash2014

119878119879min

















0changes in the HRB


0for





0of minus3


T 0)

()

TR(ET0) ()

Monthly R2= 096

Seasonal R2= 085

Annual R2= 093

40

20

0

minus20

minus40

40200minus20minus40






0from the

observed data


























5 Discussion


0for




0for











6 Summary








0have




Winter Annual

10

0

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

97∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E 97

∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E

TmaxTmin

Rs

WSRH

10

010

0

10

0

10

0

97∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E97

∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E97

∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E






0change and





0







Acknowledgments




References




















































Volume 2014

Mining


Journal of



Geophysics







Journal of




Advances in











Geology Advances in



0will increase


0is sensitive




119878119879min



0change to the per-





0


1 1199092 119909

119899)

where 1199091 1199092 119909




ΔET0= sum

120597ET0

120597119909119894

sdot Δ119909119894+ 120575 (12)



119894is the 119894th




0with respect


0(the average value


ΔET0

ET0

= sum120597ET0

120597119909119894

sdotΔ119909119894

ET0

+ 120576 (13)


0during a given




ΔET0

ET0

= sum120597ET0

120597119909119894

sdot119909119894

ET0

Δ119909119894

119909119894

+ 120576 (14)



119909119894 If we let

119862(119909119894) = sum 119878


ΔET0

ET0

asymp sum119862(119909119894) (15)



WS RH and 119877119904




4 Results





0


0both










0




0


0




0from


0in










R2= 0967

400

300

200

100

0

0 50 100 150 200

Summer

Autumn

Spring

Winter


Epa

n(m

m m

onth

minus1)


(a)

R2= 0906

Epa

n(m

m yr

minus1)

5000

4000

3000

2000

1000

0

600 800 1000 1200 1400 1600


ET0 (mm yrminus1)

(b)


Month

250

200

150

100

50

01 2 3 4 5 6 7 8 9 10 11 12

ET0

(mm

mon

thminus1)



0 respectively










0has no


0in the


















119904



1960 1970 1980 1990 2000 2010

420

400

380

360

340

320

ET0

(mm

yrminus1)

(a)


(NS)

1960 1970 1980 1990 2000 2010

580

560

540

520

500

480

460

ET0

(mm

yrminus1)

(b)


1960 1970 1980 1990 2000 2010

260

240

220

200

ET0

(mm

yrminus1)

(c)


1960 1970 1980 1990 2000 2010

120

100

80

60

40

ET0

(mm

yrminus1)

(d)

AnnualSlope 020

(NS)

1960 1970 1980 1990 2000 2010

1300

1250

1200

1150

1100

1050


ET0

(mm

yrminus1)

ET0 change

(e)


test












Winter


Annual

Annual


Spring ummer Autumn

Winter Annual

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

97∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E 97

∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E

97∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E 97

∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E

97∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E

Max 470Min 232SD 49

Max 700Min 310SD 84

Max 290Min 145SD 30

Max 59Min 93SD 58

Max 1553Min 757SD 166



0






0(Figure 4) and




WWWW

Tm

ean(∘

C)

WS

(m sminus

1)

RH (

)

Rs

(MJ m

minus2

dminus1)

2 4 6 8 10 122 4 6 8 10 122 4 6 8 10 122 4 6 8 10 12

30

20

10

0

minus10

minus20

5

4

3

2

1

80

60

40

20

30

25

20

15

10


UUUU

Tm

ean(∘

C)

WS

(m sminus

1)

RH (

)

Rs

(MJ m

minus2

dminus1)

2 4 6 8 10 12 2 4 6 8 10 12 2 4 6 8 10 12 2 4 6 8 10 12

30

20

10

0

minus10

minus20

5

4

3

2

1

80

60

40

20

30

25

20

15

10


MMMM

Tm

ean(∘

C)

WS

(m sminus

1)

RH (

)

Rs

(MJ m

minus2

dminus1)

2 4 6 8 10 122 4 6 8 10 122 4 6 8 10 122 4 6 8 10 12

30

20

10

0

minus10

minus20

5

4

3

2

1

80

60

40

20

30

25

20

15

10


LLLL

Tm

ean(∘

C)

WS

(m sminus

1)

RH (

)

Rs

(MJ m

minus2

dminus1)

2 4 6 8 10 12 2 4 6 8 10 12 2 4 6 8 10 12 2 4 6 8 10 12

30

20

10

0

minus10

minus20

5

4

3

2

1

80

60

40

20

30

25

20

15

10















1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

Tm

ean(∘

C)

WS

(m sminus

1)

RH (

)

Rs

(MJ m

minus2

dminus1)

YearYearYearYear

Slope 0036 (S)10

9

8

7

6

5

35

30

25

20

15

55

50

45

40

35

185

180

175

170

165


1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

Tm

ean(∘

C)

WS

(m sminus

1)

RH (

)

Rs

(MJ m

minus2

dminus1)

Year Year Year Year

Slope 0032 (S)35

30

25

20

15

60

55

50

45

40

35

185

180

175

170

165

U U U U4

3

2

1

Slope minus0013 (S)

Slope minus0035 (S)


1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

Tm

ean(∘

C)

WS

(m sminus

1)

RH (

)

Rs

(MJ m

minus2

dminus1)

YearYearYearYear


9

8

7

6

5

35

30

25

20

15

55

50

45

40

35

185

180

175

170

165

M M M M

Slope minus0048 (S)

Slope minus0017 (S)

1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

Tm

ean(∘

C)

WS

(m sminus

1)

RH (

)

Rs

(MJ m

minus2

dminus1)

Year Year Year Year

Slope 0038 (S)10

9

8

7

6

5

35

30

25

20

15

55

50

45

40

35

185

180

175

170

165

L L L L

Slope minus0020 (S)

Slope minus0059 (S)

Slope minus0002 (S)








those of RH


and 119878119879min




119879maxand 119878

119879minare


119879maxand 119878119879min





119879minfor the


ST

max

Day0 50 100 150 200 250 300 350

06

04

02

00

minus02

LMU

(a)

ST

min

Day0 50 100 150 200 250 300 350

01

00

minus01

minus02

minus03

LMU

(b)

SW

S

Day0 50 100 150 200 250 300 350

05

04

03

02

01

LMU

(c)

SRH

Day0 50 100 150 200 250 300 350

minus02

minus04

minus06

minus08

minus10

LMU

(d)

SR119904

Day0 50 100 150 200 250 300 350

06

04

02

00

minus02

LMU

(e)

Sens

itivi

ty co

effici

ents

Day0 50 100 150 200 250 300 350

06

03

00

minus03

minus06

minus09

Tmax

Tmin

RsWSRH

(f)







0is more sensitive




1960 1970 1980 1990 2000 2010

Year1960 1970 1980 1990 2000 2010

Year

1960 1970 1980 1990 2000 2010

Year1960 1970 1980 1990 2000 2010

Year

1960 1970 1980 1990 2000 2010

Year

ST

max

ST

min

SW

S

SR119904

SRH

035

030

025

020

033

030

027

024

036

033

030

027

024

minus002

minus004

minus006

minus008

minus030

minus035

minus040

minus045

minus050

S

NS

NS

S

S



119904






119877119904in winter and 119878








119879maxand 119878









and 119878119877119904


0maintain a stable








and 119878119879min


119879maxand 119878119879min






38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

97∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E 103

∘30

998400E 97∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E 103

∘30

998400E 97∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E 103

∘30

998400E

Mean 028SD 0047


Mean 027SD 0058


Mean 029SD 0063

STminSWS

SRH SR119904









97∘30998400E

99∘0998400E

100∘30998400E

102∘0998400E

103∘30998400E

97∘30998400E

99∘0998400E

100∘30998400E

102∘0998400E

103∘30998400E




and 119877119904) during 1961ndash2014

119878119879min

















0changes in the HRB


0for





0of minus3


T 0)

()

TR(ET0) ()

Monthly R2= 096

Seasonal R2= 085

Annual R2= 093

40

20

0

minus20

minus40

40200minus20minus40






0from the

observed data


























5 Discussion


0for




0for











6 Summary








0have




Winter Annual

10

0

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

97∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E 97

∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E

TmaxTmin

Rs

WSRH

10

010

0

10

0

10

0

97∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E97

∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E97

∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E






0change and





0







Acknowledgments




References




















































Volume 2014

Mining


Journal of



Geophysics







Journal of




Advances in











Geology Advances in


R2= 0967

400

300

200

100

0

0 50 100 150 200

Summer

Autumn

Spring

Winter


Epa

n(m

m m

onth

minus1)


(a)

R2= 0906

Epa

n(m

m yr

minus1)

5000

4000

3000

2000

1000

0

600 800 1000 1200 1400 1600


ET0 (mm yrminus1)

(b)


Month

250

200

150

100

50

01 2 3 4 5 6 7 8 9 10 11 12

ET0

(mm

mon

thminus1)



0 respectively










0has no


0in the


















119904



1960 1970 1980 1990 2000 2010

420

400

380

360

340

320

ET0

(mm

yrminus1)

(a)


(NS)

1960 1970 1980 1990 2000 2010

580

560

540

520

500

480

460

ET0

(mm

yrminus1)

(b)


1960 1970 1980 1990 2000 2010

260

240

220

200

ET0

(mm

yrminus1)

(c)


1960 1970 1980 1990 2000 2010

120

100

80

60

40

ET0

(mm

yrminus1)

(d)

AnnualSlope 020

(NS)

1960 1970 1980 1990 2000 2010

1300

1250

1200

1150

1100

1050


ET0

(mm

yrminus1)

ET0 change

(e)


test












Winter


Annual

Annual


Spring ummer Autumn

Winter Annual

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

97∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E 97

∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E

97∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E 97

∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E

97∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E

Max 470Min 232SD 49

Max 700Min 310SD 84

Max 290Min 145SD 30

Max 59Min 93SD 58

Max 1553Min 757SD 166



0






0(Figure 4) and




WWWW

Tm

ean(∘

C)

WS

(m sminus

1)

RH (

)

Rs

(MJ m

minus2

dminus1)

2 4 6 8 10 122 4 6 8 10 122 4 6 8 10 122 4 6 8 10 12

30

20

10

0

minus10

minus20

5

4

3

2

1

80

60

40

20

30

25

20

15

10


UUUU

Tm

ean(∘

C)

WS

(m sminus

1)

RH (

)

Rs

(MJ m

minus2

dminus1)

2 4 6 8 10 12 2 4 6 8 10 12 2 4 6 8 10 12 2 4 6 8 10 12

30

20

10

0

minus10

minus20

5

4

3

2

1

80

60

40

20

30

25

20

15

10


MMMM

Tm

ean(∘

C)

WS

(m sminus

1)

RH (

)

Rs

(MJ m

minus2

dminus1)

2 4 6 8 10 122 4 6 8 10 122 4 6 8 10 122 4 6 8 10 12

30

20

10

0

minus10

minus20

5

4

3

2

1

80

60

40

20

30

25

20

15

10


LLLL

Tm

ean(∘

C)

WS

(m sminus

1)

RH (

)

Rs

(MJ m

minus2

dminus1)

2 4 6 8 10 12 2 4 6 8 10 12 2 4 6 8 10 12 2 4 6 8 10 12

30

20

10

0

minus10

minus20

5

4

3

2

1

80

60

40

20

30

25

20

15

10















1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

Tm

ean(∘

C)

WS

(m sminus

1)

RH (

)

Rs

(MJ m

minus2

dminus1)

YearYearYearYear

Slope 0036 (S)10

9

8

7

6

5

35

30

25

20

15

55

50

45

40

35

185

180

175

170

165


1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

Tm

ean(∘

C)

WS

(m sminus

1)

RH (

)

Rs

(MJ m

minus2

dminus1)

Year Year Year Year

Slope 0032 (S)35

30

25

20

15

60

55

50

45

40

35

185

180

175

170

165

U U U U4

3

2

1

Slope minus0013 (S)

Slope minus0035 (S)


1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

Tm

ean(∘

C)

WS

(m sminus

1)

RH (

)

Rs

(MJ m

minus2

dminus1)

YearYearYearYear


9

8

7

6

5

35

30

25

20

15

55

50

45

40

35

185

180

175

170

165

M M M M

Slope minus0048 (S)

Slope minus0017 (S)

1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

Tm

ean(∘

C)

WS

(m sminus

1)

RH (

)

Rs

(MJ m

minus2

dminus1)

Year Year Year Year

Slope 0038 (S)10

9

8

7

6

5

35

30

25

20

15

55

50

45

40

35

185

180

175

170

165

L L L L

Slope minus0020 (S)

Slope minus0059 (S)

Slope minus0002 (S)








those of RH


and 119878119879min




119879maxand 119878

119879minare


119879maxand 119878119879min





119879minfor the


ST

max

Day0 50 100 150 200 250 300 350

06

04

02

00

minus02

LMU

(a)

ST

min

Day0 50 100 150 200 250 300 350

01

00

minus01

minus02

minus03

LMU

(b)

SW

S

Day0 50 100 150 200 250 300 350

05

04

03

02

01

LMU

(c)

SRH

Day0 50 100 150 200 250 300 350

minus02

minus04

minus06

minus08

minus10

LMU

(d)

SR119904

Day0 50 100 150 200 250 300 350

06

04

02

00

minus02

LMU

(e)

Sens

itivi

ty co

effici

ents

Day0 50 100 150 200 250 300 350

06

03

00

minus03

minus06

minus09

Tmax

Tmin

RsWSRH

(f)







0is more sensitive




1960 1970 1980 1990 2000 2010

Year1960 1970 1980 1990 2000 2010

Year

1960 1970 1980 1990 2000 2010

Year1960 1970 1980 1990 2000 2010

Year

1960 1970 1980 1990 2000 2010

Year

ST

max

ST

min

SW

S

SR119904

SRH

035

030

025

020

033

030

027

024

036

033

030

027

024

minus002

minus004

minus006

minus008

minus030

minus035

minus040

minus045

minus050

S

NS

NS

S

S



119904






119877119904in winter and 119878








119879maxand 119878









and 119878119877119904


0maintain a stable








and 119878119879min


119879maxand 119878119879min






38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

97∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E 103

∘30

998400E 97∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E 103

∘30

998400E 97∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E 103

∘30

998400E

Mean 028SD 0047


Mean 027SD 0058


Mean 029SD 0063

STminSWS

SRH SR119904









97∘30998400E

99∘0998400E

100∘30998400E

102∘0998400E

103∘30998400E

97∘30998400E

99∘0998400E

100∘30998400E

102∘0998400E

103∘30998400E




and 119877119904) during 1961ndash2014

119878119879min

















0changes in the HRB


0for





0of minus3


T 0)

()

TR(ET0) ()

Monthly R2= 096

Seasonal R2= 085

Annual R2= 093

40

20

0

minus20

minus40

40200minus20minus40






0from the

observed data


























5 Discussion


0for




0for











6 Summary








0have




Winter Annual

10

0

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

97∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E 97

∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E

TmaxTmin

Rs

WSRH

10

010

0

10

0

10

0

97∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E97

∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E97

∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E






0change and





0







Acknowledgments




References




















































Volume 2014

Mining


Journal of



Geophysics







Journal of




Advances in











Geology Advances in



1960 1970 1980 1990 2000 2010

420

400

380

360

340

320

ET0

(mm

yrminus1)

(a)


(NS)

1960 1970 1980 1990 2000 2010

580

560

540

520

500

480

460

ET0

(mm

yrminus1)

(b)


1960 1970 1980 1990 2000 2010

260

240

220

200

ET0

(mm

yrminus1)

(c)


1960 1970 1980 1990 2000 2010

120

100

80

60

40

ET0

(mm

yrminus1)

(d)

AnnualSlope 020

(NS)

1960 1970 1980 1990 2000 2010

1300

1250

1200

1150

1100

1050


ET0

(mm

yrminus1)

ET0 change

(e)


test












Winter


Annual

Annual


Spring ummer Autumn

Winter Annual

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

97∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E 97

∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E

97∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E 97

∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E

97∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E

Max 470Min 232SD 49

Max 700Min 310SD 84

Max 290Min 145SD 30

Max 59Min 93SD 58

Max 1553Min 757SD 166



0






0(Figure 4) and




WWWW

Tm

ean(∘

C)

WS

(m sminus

1)

RH (

)

Rs

(MJ m

minus2

dminus1)

2 4 6 8 10 122 4 6 8 10 122 4 6 8 10 122 4 6 8 10 12

30

20

10

0

minus10

minus20

5

4

3

2

1

80

60

40

20

30

25

20

15

10


UUUU

Tm

ean(∘

C)

WS

(m sminus

1)

RH (

)

Rs

(MJ m

minus2

dminus1)

2 4 6 8 10 12 2 4 6 8 10 12 2 4 6 8 10 12 2 4 6 8 10 12

30

20

10

0

minus10

minus20

5

4

3

2

1

80

60

40

20

30

25

20

15

10


MMMM

Tm

ean(∘

C)

WS

(m sminus

1)

RH (

)

Rs

(MJ m

minus2

dminus1)

2 4 6 8 10 122 4 6 8 10 122 4 6 8 10 122 4 6 8 10 12

30

20

10

0

minus10

minus20

5

4

3

2

1

80

60

40

20

30

25

20

15

10


LLLL

Tm

ean(∘

C)

WS

(m sminus

1)

RH (

)

Rs

(MJ m

minus2

dminus1)

2 4 6 8 10 12 2 4 6 8 10 12 2 4 6 8 10 12 2 4 6 8 10 12

30

20

10

0

minus10

minus20

5

4

3

2

1

80

60

40

20

30

25

20

15

10















1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

Tm

ean(∘

C)

WS

(m sminus

1)

RH (

)

Rs

(MJ m

minus2

dminus1)

YearYearYearYear

Slope 0036 (S)10

9

8

7

6

5

35

30

25

20

15

55

50

45

40

35

185

180

175

170

165


1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

Tm

ean(∘

C)

WS

(m sminus

1)

RH (

)

Rs

(MJ m

minus2

dminus1)

Year Year Year Year

Slope 0032 (S)35

30

25

20

15

60

55

50

45

40

35

185

180

175

170

165

U U U U4

3

2

1

Slope minus0013 (S)

Slope minus0035 (S)


1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

Tm

ean(∘

C)

WS

(m sminus

1)

RH (

)

Rs

(MJ m

minus2

dminus1)

YearYearYearYear


9

8

7

6

5

35

30

25

20

15

55

50

45

40

35

185

180

175

170

165

M M M M

Slope minus0048 (S)

Slope minus0017 (S)

1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

Tm

ean(∘

C)

WS

(m sminus

1)

RH (

)

Rs

(MJ m

minus2

dminus1)

Year Year Year Year

Slope 0038 (S)10

9

8

7

6

5

35

30

25

20

15

55

50

45

40

35

185

180

175

170

165

L L L L

Slope minus0020 (S)

Slope minus0059 (S)

Slope minus0002 (S)








those of RH


and 119878119879min




119879maxand 119878

119879minare


119879maxand 119878119879min





119879minfor the


ST

max

Day0 50 100 150 200 250 300 350

06

04

02

00

minus02

LMU

(a)

ST

min

Day0 50 100 150 200 250 300 350

01

00

minus01

minus02

minus03

LMU

(b)

SW

S

Day0 50 100 150 200 250 300 350

05

04

03

02

01

LMU

(c)

SRH

Day0 50 100 150 200 250 300 350

minus02

minus04

minus06

minus08

minus10

LMU

(d)

SR119904

Day0 50 100 150 200 250 300 350

06

04

02

00

minus02

LMU

(e)

Sens

itivi

ty co

effici

ents

Day0 50 100 150 200 250 300 350

06

03

00

minus03

minus06

minus09

Tmax

Tmin

RsWSRH

(f)







0is more sensitive




1960 1970 1980 1990 2000 2010

Year1960 1970 1980 1990 2000 2010

Year

1960 1970 1980 1990 2000 2010

Year1960 1970 1980 1990 2000 2010

Year

1960 1970 1980 1990 2000 2010

Year

ST

max

ST

min

SW

S

SR119904

SRH

035

030

025

020

033

030

027

024

036

033

030

027

024

minus002

minus004

minus006

minus008

minus030

minus035

minus040

minus045

minus050

S

NS

NS

S

S



119904






119877119904in winter and 119878








119879maxand 119878









and 119878119877119904


0maintain a stable








and 119878119879min


119879maxand 119878119879min






38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

97∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E 103

∘30

998400E 97∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E 103

∘30

998400E 97∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E 103

∘30

998400E

Mean 028SD 0047


Mean 027SD 0058


Mean 029SD 0063

STminSWS

SRH SR119904









97∘30998400E

99∘0998400E

100∘30998400E

102∘0998400E

103∘30998400E

97∘30998400E

99∘0998400E

100∘30998400E

102∘0998400E

103∘30998400E




and 119877119904) during 1961ndash2014

119878119879min

















0changes in the HRB


0for





0of minus3


T 0)

()

TR(ET0) ()

Monthly R2= 096

Seasonal R2= 085

Annual R2= 093

40

20

0

minus20

minus40

40200minus20minus40






0from the

observed data


























5 Discussion


0for




0for











6 Summary








0have




Winter Annual

10

0

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

97∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E 97

∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E

TmaxTmin

Rs

WSRH

10

010

0

10

0

10

0

97∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E97

∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E97

∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E






0change and





0







Acknowledgments




References




















































Volume 2014

Mining


Journal of



Geophysics







Journal of




Advances in











Geology Advances in



Winter


Annual

Annual


Spring ummer Autumn

Winter Annual

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

97∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E 97

∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E

97∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E 97

∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E

97∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E

Max 470Min 232SD 49

Max 700Min 310SD 84

Max 290Min 145SD 30

Max 59Min 93SD 58

Max 1553Min 757SD 166



0






0(Figure 4) and




WWWW

Tm

ean(∘

C)

WS

(m sminus

1)

RH (

)

Rs

(MJ m

minus2

dminus1)

2 4 6 8 10 122 4 6 8 10 122 4 6 8 10 122 4 6 8 10 12

30

20

10

0

minus10

minus20

5

4

3

2

1

80

60

40

20

30

25

20

15

10


UUUU

Tm

ean(∘

C)

WS

(m sminus

1)

RH (

)

Rs

(MJ m

minus2

dminus1)

2 4 6 8 10 12 2 4 6 8 10 12 2 4 6 8 10 12 2 4 6 8 10 12

30

20

10

0

minus10

minus20

5

4

3

2

1

80

60

40

20

30

25

20

15

10


MMMM

Tm

ean(∘

C)

WS

(m sminus

1)

RH (

)

Rs

(MJ m

minus2

dminus1)

2 4 6 8 10 122 4 6 8 10 122 4 6 8 10 122 4 6 8 10 12

30

20

10

0

minus10

minus20

5

4

3

2

1

80

60

40

20

30

25

20

15

10


LLLL

Tm

ean(∘

C)

WS

(m sminus

1)

RH (

)

Rs

(MJ m

minus2

dminus1)

2 4 6 8 10 12 2 4 6 8 10 12 2 4 6 8 10 12 2 4 6 8 10 12

30

20

10

0

minus10

minus20

5

4

3

2

1

80

60

40

20

30

25

20

15

10















1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

Tm

ean(∘

C)

WS

(m sminus

1)

RH (

)

Rs

(MJ m

minus2

dminus1)

YearYearYearYear

Slope 0036 (S)10

9

8

7

6

5

35

30

25

20

15

55

50

45

40

35

185

180

175

170

165


1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

Tm

ean(∘

C)

WS

(m sminus

1)

RH (

)

Rs

(MJ m

minus2

dminus1)

Year Year Year Year

Slope 0032 (S)35

30

25

20

15

60

55

50

45

40

35

185

180

175

170

165

U U U U4

3

2

1

Slope minus0013 (S)

Slope minus0035 (S)


1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

Tm

ean(∘

C)

WS

(m sminus

1)

RH (

)

Rs

(MJ m

minus2

dminus1)

YearYearYearYear


9

8

7

6

5

35

30

25

20

15

55

50

45

40

35

185

180

175

170

165

M M M M

Slope minus0048 (S)

Slope minus0017 (S)

1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

Tm

ean(∘

C)

WS

(m sminus

1)

RH (

)

Rs

(MJ m

minus2

dminus1)

Year Year Year Year

Slope 0038 (S)10

9

8

7

6

5

35

30

25

20

15

55

50

45

40

35

185

180

175

170

165

L L L L

Slope minus0020 (S)

Slope minus0059 (S)

Slope minus0002 (S)








those of RH


and 119878119879min




119879maxand 119878

119879minare


119879maxand 119878119879min





119879minfor the


ST

max

Day0 50 100 150 200 250 300 350

06

04

02

00

minus02

LMU

(a)

ST

min

Day0 50 100 150 200 250 300 350

01

00

minus01

minus02

minus03

LMU

(b)

SW

S

Day0 50 100 150 200 250 300 350

05

04

03

02

01

LMU

(c)

SRH

Day0 50 100 150 200 250 300 350

minus02

minus04

minus06

minus08

minus10

LMU

(d)

SR119904

Day0 50 100 150 200 250 300 350

06

04

02

00

minus02

LMU

(e)

Sens

itivi

ty co

effici

ents

Day0 50 100 150 200 250 300 350

06

03

00

minus03

minus06

minus09

Tmax

Tmin

RsWSRH

(f)







0is more sensitive




1960 1970 1980 1990 2000 2010

Year1960 1970 1980 1990 2000 2010

Year

1960 1970 1980 1990 2000 2010

Year1960 1970 1980 1990 2000 2010

Year

1960 1970 1980 1990 2000 2010

Year

ST

max

ST

min

SW

S

SR119904

SRH

035

030

025

020

033

030

027

024

036

033

030

027

024

minus002

minus004

minus006

minus008

minus030

minus035

minus040

minus045

minus050

S

NS

NS

S

S



119904






119877119904in winter and 119878








119879maxand 119878









and 119878119877119904


0maintain a stable








and 119878119879min


119879maxand 119878119879min






38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

97∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E 103

∘30

998400E 97∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E 103

∘30

998400E 97∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E 103

∘30

998400E

Mean 028SD 0047


Mean 027SD 0058


Mean 029SD 0063

STminSWS

SRH SR119904









97∘30998400E

99∘0998400E

100∘30998400E

102∘0998400E

103∘30998400E

97∘30998400E

99∘0998400E

100∘30998400E

102∘0998400E

103∘30998400E




and 119877119904) during 1961ndash2014

119878119879min

















0changes in the HRB


0for





0of minus3


T 0)

()

TR(ET0) ()

Monthly R2= 096

Seasonal R2= 085

Annual R2= 093

40

20

0

minus20

minus40

40200minus20minus40






0from the

observed data


























5 Discussion


0for




0for











6 Summary








0have




Winter Annual

10

0

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

97∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E 97

∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E

TmaxTmin

Rs

WSRH

10

010

0

10

0

10

0

97∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E97

∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E97

∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E






0change and





0







Acknowledgments




References




















































Volume 2014

Mining


Journal of



Geophysics







Journal of




Advances in











Geology Advances in


WWWW

Tm

ean(∘

C)

WS

(m sminus

1)

RH (

)

Rs

(MJ m

minus2

dminus1)

2 4 6 8 10 122 4 6 8 10 122 4 6 8 10 122 4 6 8 10 12

30

20

10

0

minus10

minus20

5

4

3

2

1

80

60

40

20

30

25

20

15

10


UUUU

Tm

ean(∘

C)

WS

(m sminus

1)

RH (

)

Rs

(MJ m

minus2

dminus1)

2 4 6 8 10 12 2 4 6 8 10 12 2 4 6 8 10 12 2 4 6 8 10 12

30

20

10

0

minus10

minus20

5

4

3

2

1

80

60

40

20

30

25

20

15

10


MMMM

Tm

ean(∘

C)

WS

(m sminus

1)

RH (

)

Rs

(MJ m

minus2

dminus1)

2 4 6 8 10 122 4 6 8 10 122 4 6 8 10 122 4 6 8 10 12

30

20

10

0

minus10

minus20

5

4

3

2

1

80

60

40

20

30

25

20

15

10


LLLL

Tm

ean(∘

C)

WS

(m sminus

1)

RH (

)

Rs

(MJ m

minus2

dminus1)

2 4 6 8 10 12 2 4 6 8 10 12 2 4 6 8 10 12 2 4 6 8 10 12

30

20

10

0

minus10

minus20

5

4

3

2

1

80

60

40

20

30

25

20

15

10















1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

Tm

ean(∘

C)

WS

(m sminus

1)

RH (

)

Rs

(MJ m

minus2

dminus1)

YearYearYearYear

Slope 0036 (S)10

9

8

7

6

5

35

30

25

20

15

55

50

45

40

35

185

180

175

170

165


1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

Tm

ean(∘

C)

WS

(m sminus

1)

RH (

)

Rs

(MJ m

minus2

dminus1)

Year Year Year Year

Slope 0032 (S)35

30

25

20

15

60

55

50

45

40

35

185

180

175

170

165

U U U U4

3

2

1

Slope minus0013 (S)

Slope minus0035 (S)


1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

Tm

ean(∘

C)

WS

(m sminus

1)

RH (

)

Rs

(MJ m

minus2

dminus1)

YearYearYearYear


9

8

7

6

5

35

30

25

20

15

55

50

45

40

35

185

180

175

170

165

M M M M

Slope minus0048 (S)

Slope minus0017 (S)

1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

Tm

ean(∘

C)

WS

(m sminus

1)

RH (

)

Rs

(MJ m

minus2

dminus1)

Year Year Year Year

Slope 0038 (S)10

9

8

7

6

5

35

30

25

20

15

55

50

45

40

35

185

180

175

170

165

L L L L

Slope minus0020 (S)

Slope minus0059 (S)

Slope minus0002 (S)








those of RH


and 119878119879min




119879maxand 119878

119879minare


119879maxand 119878119879min





119879minfor the


ST

max

Day0 50 100 150 200 250 300 350

06

04

02

00

minus02

LMU

(a)

ST

min

Day0 50 100 150 200 250 300 350

01

00

minus01

minus02

minus03

LMU

(b)

SW

S

Day0 50 100 150 200 250 300 350

05

04

03

02

01

LMU

(c)

SRH

Day0 50 100 150 200 250 300 350

minus02

minus04

minus06

minus08

minus10

LMU

(d)

SR119904

Day0 50 100 150 200 250 300 350

06

04

02

00

minus02

LMU

(e)

Sens

itivi

ty co

effici

ents

Day0 50 100 150 200 250 300 350

06

03

00

minus03

minus06

minus09

Tmax

Tmin

RsWSRH

(f)







0is more sensitive




1960 1970 1980 1990 2000 2010

Year1960 1970 1980 1990 2000 2010

Year

1960 1970 1980 1990 2000 2010

Year1960 1970 1980 1990 2000 2010

Year

1960 1970 1980 1990 2000 2010

Year

ST

max

ST

min

SW

S

SR119904

SRH

035

030

025

020

033

030

027

024

036

033

030

027

024

minus002

minus004

minus006

minus008

minus030

minus035

minus040

minus045

minus050

S

NS

NS

S

S



119904






119877119904in winter and 119878








119879maxand 119878









and 119878119877119904


0maintain a stable








and 119878119879min


119879maxand 119878119879min






38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

97∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E 103

∘30

998400E 97∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E 103

∘30

998400E 97∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E 103

∘30

998400E

Mean 028SD 0047


Mean 027SD 0058


Mean 029SD 0063

STminSWS

SRH SR119904









97∘30998400E

99∘0998400E

100∘30998400E

102∘0998400E

103∘30998400E

97∘30998400E

99∘0998400E

100∘30998400E

102∘0998400E

103∘30998400E




and 119877119904) during 1961ndash2014

119878119879min

















0changes in the HRB


0for





0of minus3


T 0)

()

TR(ET0) ()

Monthly R2= 096

Seasonal R2= 085

Annual R2= 093

40

20

0

minus20

minus40

40200minus20minus40






0from the

observed data


























5 Discussion


0for




0for











6 Summary








0have




Winter Annual

10

0

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

97∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E 97

∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E

TmaxTmin

Rs

WSRH

10

010

0

10

0

10

0

97∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E97

∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E97

∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E






0change and





0







Acknowledgments




References




















































Volume 2014

Mining


Journal of



Geophysics







Journal of




Advances in











Geology Advances in


1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

Tm

ean(∘

C)

WS

(m sminus

1)

RH (

)

Rs

(MJ m

minus2

dminus1)

YearYearYearYear

Slope 0036 (S)10

9

8

7

6

5

35

30

25

20

15

55

50

45

40

35

185

180

175

170

165


1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

Tm

ean(∘

C)

WS

(m sminus

1)

RH (

)

Rs

(MJ m

minus2

dminus1)

Year Year Year Year

Slope 0032 (S)35

30

25

20

15

60

55

50

45

40

35

185

180

175

170

165

U U U U4

3

2

1

Slope minus0013 (S)

Slope minus0035 (S)


1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

Tm

ean(∘

C)

WS

(m sminus

1)

RH (

)

Rs

(MJ m

minus2

dminus1)

YearYearYearYear


9

8

7

6

5

35

30

25

20

15

55

50

45

40

35

185

180

175

170

165

M M M M

Slope minus0048 (S)

Slope minus0017 (S)

1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

1960

1970

1980

1990

2000

2010

Tm

ean(∘

C)

WS

(m sminus

1)

RH (

)

Rs

(MJ m

minus2

dminus1)

Year Year Year Year

Slope 0038 (S)10

9

8

7

6

5

35

30

25

20

15

55

50

45

40

35

185

180

175

170

165

L L L L

Slope minus0020 (S)

Slope minus0059 (S)

Slope minus0002 (S)








those of RH


and 119878119879min




119879maxand 119878

119879minare


119879maxand 119878119879min





119879minfor the


ST

max

Day0 50 100 150 200 250 300 350

06

04

02

00

minus02

LMU

(a)

ST

min

Day0 50 100 150 200 250 300 350

01

00

minus01

minus02

minus03

LMU

(b)

SW

S

Day0 50 100 150 200 250 300 350

05

04

03

02

01

LMU

(c)

SRH

Day0 50 100 150 200 250 300 350

minus02

minus04

minus06

minus08

minus10

LMU

(d)

SR119904

Day0 50 100 150 200 250 300 350

06

04

02

00

minus02

LMU

(e)

Sens

itivi

ty co

effici

ents

Day0 50 100 150 200 250 300 350

06

03

00

minus03

minus06

minus09

Tmax

Tmin

RsWSRH

(f)







0is more sensitive




1960 1970 1980 1990 2000 2010

Year1960 1970 1980 1990 2000 2010

Year

1960 1970 1980 1990 2000 2010

Year1960 1970 1980 1990 2000 2010

Year

1960 1970 1980 1990 2000 2010

Year

ST

max

ST

min

SW

S

SR119904

SRH

035

030

025

020

033

030

027

024

036

033

030

027

024

minus002

minus004

minus006

minus008

minus030

minus035

minus040

minus045

minus050

S

NS

NS

S

S



119904






119877119904in winter and 119878








119879maxand 119878









and 119878119877119904


0maintain a stable








and 119878119879min


119879maxand 119878119879min






38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

97∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E 103

∘30

998400E 97∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E 103

∘30

998400E 97∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E 103

∘30

998400E

Mean 028SD 0047


Mean 027SD 0058


Mean 029SD 0063

STminSWS

SRH SR119904









97∘30998400E

99∘0998400E

100∘30998400E

102∘0998400E

103∘30998400E

97∘30998400E

99∘0998400E

100∘30998400E

102∘0998400E

103∘30998400E




and 119877119904) during 1961ndash2014

119878119879min

















0changes in the HRB


0for





0of minus3


T 0)

()

TR(ET0) ()

Monthly R2= 096

Seasonal R2= 085

Annual R2= 093

40

20

0

minus20

minus40

40200minus20minus40






0from the

observed data


























5 Discussion


0for




0for











6 Summary








0have




Winter Annual

10

0

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

97∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E 97

∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E

TmaxTmin

Rs

WSRH

10

010

0

10

0

10

0

97∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E97

∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E97

∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E






0change and





0







Acknowledgments




References




















































Volume 2014

Mining


Journal of



Geophysics







Journal of




Advances in











Geology Advances in


ST

max

Day0 50 100 150 200 250 300 350

06

04

02

00

minus02

LMU

(a)

ST

min

Day0 50 100 150 200 250 300 350

01

00

minus01

minus02

minus03

LMU

(b)

SW

S

Day0 50 100 150 200 250 300 350

05

04

03

02

01

LMU

(c)

SRH

Day0 50 100 150 200 250 300 350

minus02

minus04

minus06

minus08

minus10

LMU

(d)

SR119904

Day0 50 100 150 200 250 300 350

06

04

02

00

minus02

LMU

(e)

Sens

itivi

ty co

effici

ents

Day0 50 100 150 200 250 300 350

06

03

00

minus03

minus06

minus09

Tmax

Tmin

RsWSRH

(f)







0is more sensitive




1960 1970 1980 1990 2000 2010

Year1960 1970 1980 1990 2000 2010

Year

1960 1970 1980 1990 2000 2010

Year1960 1970 1980 1990 2000 2010

Year

1960 1970 1980 1990 2000 2010

Year

ST

max

ST

min

SW

S

SR119904

SRH

035

030

025

020

033

030

027

024

036

033

030

027

024

minus002

minus004

minus006

minus008

minus030

minus035

minus040

minus045

minus050

S

NS

NS

S

S



119904






119877119904in winter and 119878








119879maxand 119878









and 119878119877119904


0maintain a stable








and 119878119879min


119879maxand 119878119879min






38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

97∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E 103

∘30

998400E 97∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E 103

∘30

998400E 97∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E 103

∘30

998400E

Mean 028SD 0047


Mean 027SD 0058


Mean 029SD 0063

STminSWS

SRH SR119904









97∘30998400E

99∘0998400E

100∘30998400E

102∘0998400E

103∘30998400E

97∘30998400E

99∘0998400E

100∘30998400E

102∘0998400E

103∘30998400E




and 119877119904) during 1961ndash2014

119878119879min

















0changes in the HRB


0for





0of minus3


T 0)

()

TR(ET0) ()

Monthly R2= 096

Seasonal R2= 085

Annual R2= 093

40

20

0

minus20

minus40

40200minus20minus40






0from the

observed data


























5 Discussion


0for




0for











6 Summary








0have




Winter Annual

10

0

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

97∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E 97

∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E

TmaxTmin

Rs

WSRH

10

010

0

10

0

10

0

97∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E97

∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E97

∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E






0change and





0







Acknowledgments




References




















































Volume 2014

Mining


Journal of



Geophysics







Journal of




Advances in











Geology Advances in


1960 1970 1980 1990 2000 2010

Year1960 1970 1980 1990 2000 2010

Year

1960 1970 1980 1990 2000 2010

Year1960 1970 1980 1990 2000 2010

Year

1960 1970 1980 1990 2000 2010

Year

ST

max

ST

min

SW

S

SR119904

SRH

035

030

025

020

033

030

027

024

036

033

030

027

024

minus002

minus004

minus006

minus008

minus030

minus035

minus040

minus045

minus050

S

NS

NS

S

S



119904






119877119904in winter and 119878








119879maxand 119878









and 119878119877119904


0maintain a stable








and 119878119879min


119879maxand 119878119879min






38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

97∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E 103

∘30

998400E 97∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E 103

∘30

998400E 97∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E 103

∘30

998400E

Mean 028SD 0047


Mean 027SD 0058


Mean 029SD 0063

STminSWS

SRH SR119904









97∘30998400E

99∘0998400E

100∘30998400E

102∘0998400E

103∘30998400E

97∘30998400E

99∘0998400E

100∘30998400E

102∘0998400E

103∘30998400E




and 119877119904) during 1961ndash2014

119878119879min

















0changes in the HRB


0for





0of minus3


T 0)

()

TR(ET0) ()

Monthly R2= 096

Seasonal R2= 085

Annual R2= 093

40

20

0

minus20

minus40

40200minus20minus40






0from the

observed data


























5 Discussion


0for




0for











6 Summary








0have




Winter Annual

10

0

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

97∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E 97

∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E

TmaxTmin

Rs

WSRH

10

010

0

10

0

10

0

97∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E97

∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E97

∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E






0change and





0







Acknowledgments




References




















































Volume 2014

Mining


Journal of



Geophysics







Journal of




Advances in











Geology Advances in


38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

97∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E 103

∘30

998400E 97∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E 103

∘30

998400E 97∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E 103

∘30

998400E

Mean 028SD 0047


Mean 027SD 0058


Mean 029SD 0063

STminSWS

SRH SR119904









97∘30998400E

99∘0998400E

100∘30998400E

102∘0998400E

103∘30998400E

97∘30998400E

99∘0998400E

100∘30998400E

102∘0998400E

103∘30998400E




and 119877119904) during 1961ndash2014

119878119879min

















0changes in the HRB


0for





0of minus3


T 0)

()

TR(ET0) ()

Monthly R2= 096

Seasonal R2= 085

Annual R2= 093

40

20

0

minus20

minus40

40200minus20minus40






0from the

observed data


























5 Discussion


0for




0for











6 Summary








0have




Winter Annual

10

0

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

97∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E 97

∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E

TmaxTmin

Rs

WSRH

10

010

0

10

0

10

0

97∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E97

∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E97

∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E






0change and





0







Acknowledgments




References




















































Volume 2014

Mining


Journal of



Geophysics







Journal of




Advances in











Geology Advances in


T 0)

()

TR(ET0) ()

Monthly R2= 096

Seasonal R2= 085

Annual R2= 093

40

20

0

minus20

minus40

40200minus20minus40






0from the

observed data


























5 Discussion


0for




0for











6 Summary








0have




Winter Annual

10

0

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

97∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E 97

∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E

TmaxTmin

Rs

WSRH

10

010

0

10

0

10

0

97∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E97

∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E97

∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E






0change and





0







Acknowledgments




References




















































Volume 2014

Mining


Journal of



Geophysics







Journal of




Advances in











Geology Advances in



Winter Annual

10

0

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

38∘0998400N

39∘0998400N

40∘0998400N

41∘0998400N

42∘0998400N

97∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E 97

∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E

TmaxTmin

Rs

WSRH

10

010

0

10

0

10

0

97∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E97

∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E97

∘30

998400E 99∘0998400E 100

∘30

998400E 102∘0998400E






0change and





0







Acknowledgments




References




















































Volume 2014

Mining


Journal of



Geophysics







Journal of




Advances in











Geology Advances in



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

research article reference evapotranspiration changes

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