Nathan VanRheenen Rick Palmer Civil and Environmental Engineering University of Washington ...

Nathan VanRheenenRick Palmer

Civil and Environmental EngineeringUniversity of Washington

www.tag.washington.edu

Attention Snake River Water Users:

You Really Can Have It All!(or Maybe You Can’t)

-Optimization as a means to better long-term water policies in the Snake River

Basin-

CIG Weekly Seminar Series – Nov 16, 2004

Overview

Research Goals Setting Model intro Model inputs Model approach and processes Model output On deck

Goals of Research

What are the long-range impacts of climate change on the managed Snake River system? Goal: Develop a model that incorporates

current and future operating rules and management strategies

Simulation Model of Snake River Basin (SnakeSim)

How can the potential impacts of climate change be mitigated? Goal: Develop a model that provides the

“best” management strategy for SRB usersNew starting point for policy-makers Optimization Model of SRB (SIRAS)

Setting - Snake River Basin

Basin in parts of 7 states Largest tributary of Columbia River 1000 miles long 20 major reservoirs 14 MAF surface storage 250 MAF groundwater aquifer 17 MAF allocated water rights Agriculture Productivity - 3rd in US Hydropower, Fish

Snake River Basin WR Network

Political Landscape

Many users Many opinions Scientific controversy Established positions Political activism

Political Landscape

No More Ignoring the Obvious – Idaho Sucks Itself Dry – High Country News, 2/95

“The department has handed out water rights and groundwater permits as if there’s no tomorrow."

"The fish were there first, but they didn’t fill out the (water rights) forms." Ongoing Issues

Basin Adjudication Biological Opinions Groundwater supply uncertainty Changing water supply needs Relationship to the Columbia River and the PNW Uncertainty of future climate and impacts on water resources

Snake River Models

SnakeSimOperations Model

VICHydrology Model

Changes in Mean Temperature and

Precipitation or Bias Corrected Output

from GCMs

SIRASOptimization Model

SIRAS

Snake River Basin Integrated Water Resources Allocation System Purpose: Identify the “best” management

strategy for SRB users Considers

Major surface water features (94% of system storage)

System uses e.g., flood control, irrigation, fish, hydropower

Groundwater impacts 8 major irrigation districts

Economic Objective Function

SIRAS Inputs

Streamflow PET Precipitation Crop coefficient Groundwater response

SIRAS Inputs - Streamflows

J ackson Lake

0

50

100

150

200

250

Oct

-79

Jan

-80

Ap

r-8

0

Jul-

80

Oct

-80

Jan

-81

Ap

r-8

1

Jul-

81

Oct

-81

Jan

-82

Ap

r-8

2

Jul-

82

Oct

-82

Jan

-83

Ap

r-8

3

Jul-

83

Oct

-83

Jan

-84

Ap

r-8

4

Jul-

84

Oct

-84

Jan

-85

Ap

r-8

5

Jul-

85

Oct

-85

Jan

-86

Ap

r-8

6

Jul-

86

Oct

-86

Jan

-87

Ap

r-8

7

Jul-

87

Oct

-87

Jan

-88

Ap

r-8

8

Jul-

88

Oct

-88

Jan

-89

Ap

r-8

9

Jul-

89

Oct

-89

TA

F

hist

base

J ackson Lake

0

50

100

150

200

250

Oct

-79

Jan

-80

Ap

r-8

0

Jul-

80

Oct

-80

Jan

-81

Ap

r-8

1

Jul-

81

Oct

-81

Jan

-82

Ap

r-8

2

Jul-

82

Oct

-82

Jan

-83

Ap

r-8

3

Jul-

83

Oct

-83

Jan

-84

Ap

r-8

4

Jul-

84

Oct

-84

Jan

-85

Ap

r-8

5

Jul-

85

Oct

-85

Jan

-86

Ap

r-8

6

Jul-

86

Oct

-86

Jan

-87

Ap

r-8

7

Jul-

87

Oct

-87

Jan

-88

Ap

r-8

8

Jul-

88

Oct

-88

Jan

-89

Ap

r-8

9

Jul-

89

Oct

-89

TA

F

base

comp2020

SIRAS Inputs - StreamflowsJ ackson Lake, 1976-1992

0

10

20

30

40

50

60

70

80

90

100

Oct

Oct

No

v

De

c

De

c

Jan

Fe

b

Fe

b

Ma

r

Ap

r

Ap

r

Ma

y

Jun

Jul

Jul

Au

g

Se

p

Se

p

TA

F

histbase

J ackson Lake, 1976-1992

0

20

40

60

80

100

120

Oct

Oct

No

v

De

c

De

c

Jan

Fe

b

Fe

b

Ma

r

Ap

r

Ap

r

Ma

y

Jun

Jul

Jul

Au

g

Se

p

Se

p

TA

F

basecomp2020


Milner

0

200

400

600

800

1000

1200

Oct

-79

Jan

-80

Ap

r-8

0

Jul-

80

Oct

-80

Jan

-81

Ap

r-8

1

Jul-

81

Oct

-81

Jan

-82

Ap

r-8

2

Jul-

82

Oct

-82

Jan

-83

Ap

r-8

3

Jul-

83

Oct

-83

Jan

-84

Ap

r-8

4

Jul-

84

Oct

-84

Jan

-85

Ap

r-8

5

Jul-

85

Oct

-85

Jan

-86

Ap

r-8

6

Jul-

86

Oct

-86

Jan

-87

Ap

r-8

7

Jul-

87

Oct

-87

Jan

-88

Ap

r-8

8

Jul-

88

Oct

-88

Jan

-89

Ap

r-8

9

Jul-

89

Oct

-89

TA

F

hist

base

Milner

0

200

400

600

800

1000

1200

1400

Oct

-79

Jan

-80

Ap

r-8

0

Jul-

80

Oct

-80

Jan

-81

Ap

r-8

1

Jul-

81

Oct

-81

Jan

-82

Ap

r-8

2

Jul-

82

Oct

-82

Jan

-83

Ap

r-8

3

Jul-

83

Oct

-83

Jan

-84

Ap

r-8

4

Jul-

84

Oct

-84

Jan

-85

Ap

r-8

5

Jul-

85

Oct

-85

Jan

-86

Ap

r-8

6

Jul-

86

Oct

-86

Jan

-87

Ap

r-8

7

Jul-

87

Oct

-87

Jan

-88

Ap

r-8

8

Jul-

88

Oct

-88

Jan

-89

Ap

r-8

9

Jul-

89

Oct

-89

TA

F

base

comp2020


Milner, 1976-1992

0

100

200

300

400

500

600

Oct

Oct

No

v

De

c

De

c

Jan

Fe

b

Fe

b

Ma

r

Ap

r

Ap

r

Ma

y

Jun

Jul

Jul

Au

g

Se

p

Se

p

TA

F

hist

base

Milner, 1976-1992

0

100

200

300

400

500

600

Oct

Oct

No

v

De

c

De

c

Jan

Fe

b

Fe

b

Ma

r

Ap

r

Ap

r

Ma

y

Jun

Jul

Jul

Au

g

Se

p

Se

p

TA

F

base

comp2020


Lower Granite, 1976-1992

0

500

1000

1500

2000

2500

Oct

Oct

No

v

De

c

De

c

Jan

Fe

b

Fe

b

Ma

r

Ap

r

Ap

r

Ma

y

Jun

Jul

Jul

Au

g

Se

p

Se

p

TA

F

base

comp2020

Lower Granite

0

500

1000

1500

2000

2500

3000

3500

4000

4500

Oct

-79

Jan

-80

Ap

r-8

0

Jul-

80

Oct

-80

Jan

-81

Ap

r-8

1

Jul-

81

Oct

-81

Jan

-82

Ap

r-8

2

Jul-

82

Oct

-82

Jan

-83

Ap

r-8

3

Jul-

83

Oct

-83

Jan

-84

Ap

r-8

4

Jul-

84

Oct

-84

Jan

-85

Ap

r-8

5

Jul-

85

Oct

-85

Jan

-86

Ap

r-8

6

Jul-

86

Oct

-86

Jan

-87

Ap

r-8

7

Jul-

87

Oct

-87

Jan

-88

Ap

r-8

8

Jul-

88

Oct

-88

Jan

-89

Ap

r-8

9

Jul-

89

Oct

-89

TA

F

base

comp2020

SIRAS Inputs – GW Discharge Change

Milner to King Hill, 1976-1992

29.0

29.5

30.0

30.5

31.0

31.5

32.0

Oct

Oct

No

v

De

c

De

c

Jan

Fe

b

Fe

b

Ma

r

Ap

r

Ap

r

Ma

y

Jun

Jul

Jul

Au

g

Se

p

Se

p

TA

F

gw-base

gw-comp2020

Milner to King Hill

25

26

27

28

29

30

31

32

33

34

35

Jan

-76

Ap

r-7

6

Jul-

76

Oct

-76

Jan

-77

Ap

r-7

7

Jul-

77

Oct

-77

Jan

-78

Ap

r-7

8

Jul-

78

Oct

-78

Jan

-79

Ap

r-7

9

Jul-

79

Oct

-79

Jan

-80

Ap

r-8

0

Jul-

80

Oct

-80

Jan

-81

Ap

r-8

1

Jul-

81

Oct

-81

Jan

-82

Ap

r-8

2

Jul-

82

Oct

-82

Jan

-83

Ap

r-8

3

Jul-

83

Oct

-83

Jan

-84

Ap

r-8

4

Jul-

84

Oct

-84

Jan

-85

Ap

r-8

5

Jul-

85

Oct

-85

Jan

-86

TA

F

gw-base

gw-comp2020

SIRAS Inputs - PET

PET WD01

0.00

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0.08

Oct

-79

De

c-7

9

Fe

b-8

0

Ap

r-8

0

Jun

-80

Au

g-8

0

Oct

-80

De

c-8

0

Fe

b-8

1

Ap

r-8

1

Jun

-81

Au

g-8

1

Oct

-81

De

c-8

1

Fe

b-8

2

Ap

r-8

2

Jun

-82

Au

g-8

2

Oct

-82

De

c-8

2

Fe

b-8

3

Ap

r-8

3

Jun

-83

Au

g-8

3

Oct

-83

De

c-8

3

Fe

b-8

4

Ap

r-8

4

Jun

-84

Au

g-8

4

Oct

-84

De

c-8

4

Fe

b-8

5

Ap

r-8

5

Jun

-85

Au

g-8

5

Oct

-85

De

c-8

5

Fe

b-8

6

Ap

r-8

6

Jun

-86

Au

g-8

6

Oct

-86

De

c-8

6

Fe

b-8

7

Ap

r-8

7

Jun

-87

Au

g-8

7

Oct

-87

De

c-8

7

Fe

b-8

8

Ap

r-8

8

Jun

-88

Au

g-8

8

Oct

-88

De

c-8

8

Fe

b-8

9

Ap

r-8

9

Jun

-89

Au

g-8

9

Oct

-89

FT

et.base

et.comp2020

PET WD01, 1976-1992

0.00

0.01

0.02

0.03

0.04

0.05

0.06

Oct

Oct

Oct

Nov

Nov

Dec

Dec Ja

n

Jan

Feb

Feb Mar

Mar

Apr

Apr

Apr

May

May

Jun

Jun

Jul

Jul

Aug

Aug

Sep

Sep

FT

et.baseet.comp2020

SIRAS Inputs – Precip

Precip WD01

0.00

0.02

0.04

0.06

0.08

0.10

0.12

0.14

0.16

0.18

Oct

-79

De

c-7

9

Fe

b-8

0

Ap

r-8

0

Jun

-80

Au

g-8

0

Oct

-80

De

c-8

0

Fe

b-8

1

Ap

r-8

1

Jun

-81

Au

g-8

1

Oct

-81

De

c-8

1

Fe

b-8

2

Ap

r-8

2

Jun

-82

Au

g-8

2

Oct

-82

De

c-8

2

Fe

b-8

3

Ap

r-8

3

Jun

-83

Au

g-8

3

Oct

-83

De

c-8

3

Fe

b-8

4

Ap

r-8

4

Jun

-84

Au

g-8

4

Oct

-84

De

c-8

4

Fe

b-8

5

Ap

r-8

5

Jun

-85

Au

g-8

5

Oct

-85

De

c-8

5

Fe

b-8

6

Ap

r-8

6

Jun

-86

Au

g-8

6

Oct

-86

De

c-8

6

Fe

b-8

7

Ap

r-8

7

Jun

-87

Au

g-8

7

Oct

-87

De

c-8

7

Fe

b-8

8

Ap

r-8

8

Jun

-88

Au

g-8

8

Oct

-88

De

c-8

8

Fe

b-8

9

Ap

r-8

9

Jun

-89

Au

g-8

9

Oct

-89

FT

p.base

p.comp2020

Precip WD01, 1976-1992

0.00

0.01

0.02

0.03

0.04

0.05

0.06

Oct

Oct

Oct

Nov

Nov

Dec

Dec Ja

n

Jan

Feb

Feb Mar

Mar

Apr

Apr

Apr

May

May

Jun

Jun

Jul

Jul

Aug

Aug

Sep

Sep

FT

p.base

p.comp2020

SIRAS Inputs - Crops

Available Crops: AlfalfaMean, BarleyFeed, BarleyMalt, Beans,

CornField1, CornField2, CornSweet1, CornSweet2, Onions, Pasture, Potatoes, Sugarbeets, WheatSpringHard, WheatSpringSoft

Crop Coefficient (K) dictates water needs through growing cycle (K is nonlinear)

Crop Water Use (PETcrop)= Kcrop * PETref(alfalfa)

Irrig Need = Acres * (PETcrop – Precip)

SIRAS Approach and Processes

SIRAS Approach – Obj Function Objective Function

Weekly timestep Maximize

Z = Agriculture Revenue ($) + Hydropower Revenue ($) - Flood damages ($) - Environmental Target Penalties

Subject to Inflows, PET Water rights Groundwater availability Farmland availability, crop values and costs,

irrigation efficiency Energy demand and rates Infrastructure limitations (reservoir and

powerplant capacity, etc.) Network flow constraints

SIRAS Approach – Also Optimized

Surface vs. groundwater use Cropping area Crops planted Environmental flow targets, as desired

427 rule Flows at Milner, etc.

Real value is in generating tradeoff curves for testing in simulation tools

SIRAS Approach – LP/SLP Decomp

Run model from 1950-1992 LP/SLP Decomposition Rolling 5-year window Step 1

Maximize over 5 years (260 mo.) Extract conditions at week 52 Redefine constraints Rerun first 52 weeks to determine first year model

optimum Step 2

Move to 2nd 5-year window Redefine constraints with Step 1 end conditions Proceed with 2nd window as per Step 1

Step 1: Optimize over 5 years

Step 2: Extract year 1 ending conditions

Step 3: Redefine conditions as constraints

Step 4: Optimize year 1 only with new constraints

Step 6: Move to next rolling 5-year block and repeat Steps 1-5

Step 5: Initialize year 2 starting storage and gw responses

Year 1 Year 2 Year 3 Year 4 Year 5

Year 2 Year 3 Year 4 Year 5 Year 6

End StorageTotal Power

Irrig AreaGW Response

End Storage

GW Response



1971-1975

1972-1976

1973-1977

1974-1978

1975-1979

1976-1980

1977-1981

71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96

SIRAS Output

SIRAS Output – Storage

Upper Snake, Base Case, 1979-1988 Traces

UpperSnake

2000

2500

3000

3500

4000

4500

Oct

Oct

Nov

Dec

Dec Jan

Feb

Feb

Mar

Apr

Apr

May Jun

Jul

Jul

Aug

Sep

Sep

TA

F


UpperSnake

0

500

1000

1500

2000

2500

3000

3500

4000

4500

5000

Oct

-79

Jan

-80

Ap

r-8

0

Jul-

80

Oct

-80

Jan

-81

Ap

r-8

1

Jul-

81

Oct

-81

Jan

-82

Ap

r-8

2

Jul-

82

Oct

-82

Jan

-83

Ap

r-8

3

Jul-

83

Oct

-83

Jan

-84

Ap

r-8

4

Jul-

84

Oct

-84

Jan

-85

Ap

r-8

5

Jul-

85

Oct

-85

Jan

-86

Ap

r-8

6

Jul-

86

Oct

-86

Jan

-87

Ap

r-8

7

Jul-

87

Oct

-87

Jan

-88

Ap

r-8

8

Jul-

88

Oct

-88

Jan

-89

Ap

r-8

9

Jul-

89

TA

F

basecomp2020hist

UpperSnake, 1979-1988

0

500

1000

1500

2000

2500

3000

3500

4000

4500O

ct

Oct

Oct

No

v

No

v

De

c

De

c

Jan

Jan

Fe

b

Fe

b

Ma

r

Ma

r

Ap

r

Ap

r

Ap

r

Ma

y

Ma

y

Jun

Jun

Jul

Jul

Au

g

Au

g

Se

p

Se

p

TA

F

base

comp2020

hist

Elev Raised for EnergyElev Raised for Energy


Dworshak, Base Case, 1979-1988 Traces

Dworshak

1000

1200

1400

1600

1800

2000

2200

2400

2600

2800

3000O

ct

Oct

No

v

De

c

De

c

Jan

Fe

b

Fe

b

Mar

Ap

r

Ap

r

May

Jun

Jul

Jul

Au

g

Se

p

Se

p

TA

F


Dworshak, 1979-1988

1000

1500

2000

2500

3000

3500

4000

Oct

Oct

Oct

No

v

No

v

De

c

De

c

Jan

Jan

Fe

b

Fe

b

Ma

r

Ma

r

Ap

r

Ap

r

Ap

r

Ma

y

Ma

y

Jun

Jun

Jul

Jul

Au

g

Au

g

Se

p

Se

p

TA

F

base

comp2020

hist

Dworshak

1000

1500

2000

2500

3000

3500

4000

Oct

-79

Jan

-80

Ap

r-8

0

Jul-

80

Oct

-80

Jan

-81

Ap

r-8

1

Jul-

81

Oct

-81

Jan

-82

Ap

r-8

2

Jul-

82

Oct

-82

Jan

-83

Ap

r-8

3

Jul-

83

Oct

-83

Jan

-84

Ap

r-8

4

Jul-

84

Oct

-84

Jan

-85

Ap

r-8

5

Jul-

85

Oct

-85

Jan

-86

Ap

r-8

6

Jul-

86

Oct

-86

Jan

-87

Ap

r-8

7

Jul-

87

Oct

-87

Jan

-88

Ap

r-8

8

Jul-

88

Oct

-88

Jan

-89

Ap

r-8

9

Jul-

89

TA

F

basecomp2020hist

Max Hydro Eff

Drafted for Fish

Drafted for Fish

SIRAS Output – Releases for Fish

Supplemental releases to meet Lower Granite targets

427 TAF rule is met every year

Total, 1979-1988

0

20

40

60

80

100

120

140

Oct

Oct

Oct

No

v

No

v

De

c

Dec Ja

n

Jan

Fe

b

Fe

b

Ma

r

Ma

r

Ap

r

Ap

r

Ap

r

Ma

y

Ma

y

Jun

Jun

Jul

Jul

Au

g

Au

g

Se

p

Sep

TA

F

base

comp2020

Total

0

50

100

150

200

250

300

350

400

450

Oct

-79

Jan

-80

Ap

r-8

0

Jul-

80

Oct

-80

Jan

-81

Ap

r-8

1

Jul-

81

Oct

-81

Jan

-82

Ap

r-8

2

Jul-

82

Oct

-82

Jan

-83

Ap

r-8

3

Jul-

83

Oct

-83

Jan

-84

Ap

r-8

4

Jul-

84

Oct

-84

Jan

-85

Ap

r-8

5

Jul-

85

Oct

-85

Jan

-86

Ap

r-8

6

Jul-

86

Oct

-86

Jan

-87

Ap

r-8

7

Jul-

87

Oct

-87

Jan

-88

Ap

r-8

8

Jul-

88

Oct

-88

Jan

-89

Ap

r-8

9

Jul-

89

TA

F

SIRAS Output – Releases for Fish

Bulk of fish releases are from Jackson-Palisades complex

So, why is that?

J ackPal, 1979-1988

0

10

20

30

40

50

60

70

80

90

100

Oct

Oct

Oct

No

v

No

v

De

c

De

c

Jan

Jan

Fe

b

Fe

b

Ma

r

Ma

r

Ap

r

Ap

r

Ap

r

Ma

y

Ma

y

Jun

Jun

Jul

Jul

Au

g

Au

g

Se

p

Se

p

TA

F

base

comp2020

Total, 1979-1988

0

20

40

60

80

100

120

140

Oct

Oct

Oct

No

v

No

v

De

c

De

c

Jan

Jan

Fe

b

Fe

b

Ma

r

Ma

r

Ap

r

Ap

r

Ap

r

Ma

y

Ma

y

Jun

Jun

Jul

Jul

Au

g

Au

g

Se

p

Se

p

TA

F

base

comp2020

SIRAS Output – Hydropower

J ackson

0

100

200

300

400

500

600

700

800

900

Oct

-79

Jan

-80

Ap

r-8

0

Jul-

80

Oct

-80

Jan

-81

Ap

r-8

1

Jul-

81

Oct

-81

Jan

-82

Ap

r-8

2

Jul-

82

Oct

-82

Jan

-83

Ap

r-8

3

Jul-

83

Oct

-83

Jan

-84

Ap

r-8

4

Jul-

84

Oct

-84

Jan

-85

Ap

r-8

5

Jul-

85

Oct

-85

Jan

-86

Ap

r-8

6

Jul-

86

Oct

-86

Jan

-87

Ap

r-8

7

Jul-

87

Oct

-87

Jan

-88

Ap

r-8

8

Jul-

88

Oct

-88

Jan

-89

Ap

r-8

9

Jul-

89

TA

F

Jackson capacity is very low (9.8 MW), so better off drafting for other uses (fish, ROR hydropower, ag)


BOR, 1979-1988

0

100

200

300

400

500

600

700

800

Oct

Oct

Oct

No

v

No

v

De

c

De

c

Jan

Jan

Fe

b

Fe

b

Ma

r

Ma

r

Ap

r

Ap

r

Ap

r

Ma

y

Ma

y

Jun

Jun

Jul

Jul

Au

g

Au

g

Se

p

Se

p

MW

base

comp2020

IP, 1979-1988

1000

1050

1100

1150

1200

1250

1300

1350

1400

Oct

Oct

Oct

No

v

No

v

De

c

De

c

Jan

Jan

Fe

b

Fe

b

Ma

r

Ma

r

Ap

r

Ap

r

Ap

r

Ma

y

Ma

y

Jun

Jun

Jul

Jul

Au

g

Au

g

Se

p

Se

p

MW

base

comp2020

COE, 1979-1988

2700

2800

2900

3000

3100

3200

3300

3400

3500

3600

Oct

Oct

Oct

No

v

No

v

De

c

De

c

Jan

Jan

Fe

b

Fe

b

Ma

r

Ma

r

Ap

r

Ap

r

Ap

r

Ma

y

Ma

y

Jun

Jun

Jul

Jul

Au

g

Au

g

Se

p

Se

p

MW

base

comp2020

Snake River Energy Production, 1975-1985Optimized: Current vs Comp2040 Flows

900000

1100000

1300000

1500000

1700000

1900000

2100000

2300000

2500000

2700000

Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep

MW

h

Current

Comp2040

Historic


10% Overall Decrease, Loss of $82 M/yr

SIRAS Output – Irrigation

Total Diversionsin largest district

WD01, 1979-1988

0

50

100

150

200

250

300

350

400

450

Oct

Oct

No

v

De

c

De

c

Jan

Fe

b

Fe

b

Ma

r

Ap

r

Ap

r

Ma

y

Jun

Jul

Jul

Au

g

Se

p

Se

p

TA

F

base

comp2020

WD01, 1979-1988

0

2

4

6

8

10

12

14

16

18

Oct

Oct

Oct

No

v

No

v

De

c

De

c

Jan

Jan

Fe

b

Fe

b

Ma

r

Ma

r

Ap

r

Ap

r

Ap

r

Ma

y

Ma

y

Jun

Jun

Jul

Jul

Au

g

Au

g

Se

p

Se

p

TA

F

base

comp2020

GW pumpingin largest district

SIRAS Output – Irrigation

Total Diversionsin second largestdistrict

WD02, 1979-1988

0

10

20

30

40

50

60

70

80

Oct

Oct

No

v

De

c

De

c

Jan

Fe

b

Fe

b

Ma

r

Ap

r

Ap

r

Ma

y

Jun

Jul

Jul

Au

g

Se

p

Se

p

TA

F

base

comp2020

GW pumpingin second largestdistrict

WD02, 1979-1988

0

1

2

3

4

5

6

7

Oct

Oct

Oct

No

v

No

v

De

c

De

c

Jan

Jan

Fe

b

Fe

b

Ma

r

Ma

r

Ap

r

Ap

r

Ap

r

Ma

y

Ma

y

Jun

Jun

Jul

Jul

Au

g

Au

g

Se

p

Se

p

TA

F

base

comp2020

SIRAS –Management Options

Unconstrained system (capacities only) Flood space preserved 427 rule (or others) met every year All reservoirs operated conjunctively BOR, IP, COE hydropower not

conjunctive Groundwater not used or used

selectively

Implications

Climate change will negatively impact agriculture productivity, fish flow satisfaction, and energy production

But… If the system is operated in a “more

optimal” way, the improvement over historical management far outpaces predicted climate change impacts

Implications

Why isn’t the system operated like this now? Historical precedent

Snake River managed as 2 distinct rivers Irrigators get the “first fruits” Belief that extensive groundwater pumping in the

upper river is necessary to ensure high flows (vis-à-vis gw discharge) in the lower river

However, users in the Basin may now be receptive to new ideas…

Feasibility testing of optimal rules in SnakeSim

Annual planning 52-week forecast and 4 years climate

change prediction How much water can irrigators, utilities, and

fish get in the next year to ensure a sustainable future?

Where are the tradeoffs?

SnakeOpt – Future Work

SIRAS – The Value of Optimization

What can be learned from an optimization? Can management alternatives be tested in an

optimization? Why must it be in economic terms? What

about “values”? Can an optimization model “stand alone” or

must it be used with a simulation model?

Optimizing Sleeping, Eating, Diaper changing, Marriage, and (oh, yeah) a

Dissertation, with Triplets and a Two-Year Old

Subtitle: I Sleep at Red Lights

Nathan VanRheenen Rick Palmer Civil and Environmental Engineering University of Washington ...

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