Table 3 Multiple linear regression models.

From: Control factors and scale analysis of annual river water, sediments and carbon transport in China

Response variable

Component

Estimate

Std. Error

t value

Pr (>|t|)

Multiple R2

p-value

Degrees of freedom

Rc

(Intercept)

0.0994783

0.0182923

5.438

<0.001***

0.5445

<0.001

311

MAT

−0.0082886

0.0022667

−3.657

<0.001 ***

MAP

0.0003681

0.0000272

13.532

<0.001 ***

TSSC

(Intercept)

1612.56517

906.46327

1.779

0.0805

0.4025

<0.001

58

MAP

−0.27744

1.30623

−0.212

0.8325

RSCI

20.06351

5.02247

3.995

<0.001 ***

RD

0.02242

1.95068

0.011

0.9909

S

34.27221

388.65927

0.088

0.9300

Vc

−46.17586

14.56646

−3.17

0.0024 **

TSSL

(Intercept)

323.9008

58.1214

5.573

<0.001***

0.3205

<0.001

60

RSCI

−0.8753

0.354

−2.473

0.0162 *

RD

0.3294

0.1302

2.53

0.0140 *

MAP

−0.2555

0.1325

−1.929

0.0585

MAT

5.4893

6.9371

0.791

0.4319

Vc

−3.0994

0.9683

−3.201

0.0022 **

TOCL

(Intercept)

−9.003674

3.679632

−2.447

0.0308 *

0.6782

0.0056

12

RSCI

0.021688

0.02108

1.029

0.3238

Vc

0.324286

0.119063

2.724

0.0185 *

S

0.462308

2.248804

0.206

0.8406

RD

−0.002305

0.006908

−0.334

0.7444

  1. The multiple linear regression results were based on the following formulas for the response variables: Rc = −0.00829 × MAT + 0.00037 × MAP + 0.0995 (R2 = 0.5445, P < 0.001); TSSC = −0.2774 × MAP + 20.06 × RSCI + 0.02 × RD + 34.27 × S - 46.18 × Vc + 1612 (R2 = 0.4025, P < 0.001); TSSL = −0.8753 × RSCI + 0.3294 × RD - 0.2555 × MAP + 5.4893 × MAT - 3.0994 × Vc + 323.9 (R2 = 0.3205, P < 0.001); and TOCL = 0.022 × RSCI + 0.324 × Vc + 0.462 × S - 0.0023 × RD - 9 (R2 = 0.6782, P = 0.0056).
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