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R² = 0.0042

0

5

10

15

20

25

0 5 10 15 20 25

R² = 0.01

0

2

4

6

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10

12

0 2 4 6 8 10 12

?

yb

yg

g

ygb

yybbgg

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CC

CCQ

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Liu et al. (2008)

1321 fff1

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1

32

1

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1

1 tCfCfCfC 2

3

2

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1 tCfCfCfC

))(())((

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3

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1

2

2

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1

3

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2

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3

1

2

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3

2

2

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1CCCCCCCC

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11

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PCA Matlab PCA R (ade4) PCA R (prcomp)

[COEFF,SCORE] = princomp(X) [COEFF,SCORE,latent] = princomp(X) [COEFF,SCORE,latent,tsquare] = princomp(X) [...] = princomp(X,'econ')

data2<-read.table("data2.txt",header=T) attach(data2) names(data2) pca_data2<-dudi.pca(data2,scannf=T) pca_data2 pca_data2$li pca_data2$co s.corcircle(pca_data2$co) par(mfrow=c(2,2)) s.corcircle(pca_data2$co) pca_data2$eig

data2<-read.table("data2.txt",header=T) attach(data2) names(data2) prcomp(data2) summary(prcomp(data2, scale = TRUE))

0.0

2.0

4.0

6.0

8.0

10.0

12.0

14.0

16.0

100.0 150.0 200.0 250.0

Dis

char

ge(m

3 /se

c)

Calender day

Glacier melt

Snow melt

Ground water

◦ −5,+5 1.221

0, 300 150 ◦ −5,+5 2.823

0, 1 0.032

◦ 0, 10 4.825 ◦ 0, 10 3.319

0, 500 300

NSE = 1 −

Xiobs − Xi

sim 2ni=1

Xiobs − Xi

mean 2ni=1

PBIAS = Xi

obs − Xisim × 100n

i=1

Xiobsn

i=0

SR =RMSE

STDEVobs=

Xiobs − Xi

sim 2ni=1

Xiobs − Xi

mean 2ni=1

Xiobs m3s−1

Xisim m3s−1

Ximean

≤

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