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Table 7 Parameters of linear regression (minimal adequate model according to Bayesian information criterion [41]) between modeled reservoir features and external predictor variables

From: Managing climate change in drinking water reservoirs: potentials and limitations of dynamic withdrawal strategies

Term (predictor variables and interaction)

Characteristic features (response variables)

Int. heat energy

Temp. 3 m

Temp. 25 m

Begin strat.

End strat.

Ice-off

Intercept (\(\beta _{0}\))

1.06

8.89

12

−41

345

220

Predictor variables (\(\beta _{i}\))

 AT_sum

−0.00712

0.331

− 0.153

8.13

–

5.17

 AT_win

0.00973

0.148

− 0.0735

− 2.28

2.31

− 20.8

 Qout

0.000775

–

0.0151

–

−0.00118

0.0544

 Qrw

0.00691

− 0.0601

0.166

1.78

0.51

–

 V

− 0.00637

− 0.00243

− 0.133

0.0269

− 0.000614

− 2.96

 Wind

− 0.0463

− 0.936

–

1.23

−15.6

–

Reservoir (\(\varvec{\beta _{r}}\))

 R.LB

− 0.428

0.0301

− 4.34

85.9

−103

− 168

 R.SB

− 0.273

2.56

− 2.93

− 18.2

36.9

− 133

 Strategy (\(\varvec{\beta _{s}}\))

 S.dyn2

− 0.0043

− 0.154

− 0.151

–

− 0.646

–

 S.high

− 0.00395

− 0.0884

− 0.327

–

11.8

–

 S.low

0.00705

0.0142

0.223

–

− 0.454

–

Interaction reservoir (\(\varvec{\beta _{i:r}}\))

 AT_sum:R.LB

–

− 0.295

–

–

–

–

 AT_sum:R.SB

–

− 0.204

–

–

–

–

 AT_win:R.LB

–

–

0.261

–

–

9.79

 AT_win:R.SB

–

–

0.158

–

–

9.41

 Qout:R.LB

0.00146

–

0.0461

–

− 0.798

0.277

 Qout:R.SB

0.000583

–

0.0154

–

− 0.358

− 0.572

 Qrw:R.LB

0.0117

0.341

− 0.0851

− 8.46

6.2

–

 Qrw:R.SB

− 0.00588

0.08

− 0.135

− 1.49

−1.53

–

 V:R.LB

–

0.00233

–

1.6

5.43

–

 V:R.SB

–

− 0.0822

–

1.16

0.359

–

 wind:R.LB

–

–

–

− 1.1

−11.7

–

 wind:R.SB

–

–

–

21.9

−19.1

–

Interaction strategy (\(\varvec{\beta _{i:s}}\))

 Qout:S.dyn2

− 0.000358

–

− 0.00712

–

–

–

 Qout:S.high

− 0.000559

–

− 0.00986

–

–

–

 Qout:S.low

− 0.000112

–

− 0.00274

–

–

–

 Qrw:S.dyn2

–

–

–

–

0.465

–

 Qrw:S.high

–

–

–

–

− 1.26

–

 Qrw:S.low

–

–

–

–

− 0.761

–

 V:S.dyn2

–

–

–

–

− 0.17

–

 V:S.high

–

–

–

–

0.234

–

 V:S.low

–

–

–

–

0.265

–

Model quality

 \(\hbox {R}^{2}\) full model

0.927

0.738

0.693

0.603

0.85

0.657

 \(\hbox {R}^{2}\)

0.92

0.706

0.626

0.574

0.835

0.622

 BIC full model

− 732

298

416

1354

1462

1780

 BIC

− 866

157

307

1188

1360

1604

  1. See Tables 3 and 4 for explanation of features and predictor variables. Dashes (-) indicate that the respective term was omitted from the model for the particular response variable and colons (e.g., AT_sum:R.SB) indicate interaction terms. The full linear model is provided in Additional file 1: Table S1. The values provided are the corresponding slopes and intercepts of the linear models described in Eq. 3, if the values are depending on the reservoir or used strategy the default values (\(\beta _0\), and \(\beta _i\)) correspond to reservoir ES and strategy dyn1