Nathan VanRheenenRichard N. Palmer

Civil and Environmental EngineeringUniversity of Washington

www.tag.washington.edu

Recasting the Future Developing Adaptive Policies Using Optimization and Decision Analysis

-A Case for the Snake River Basin-

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 (SnakeOpt)

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

SnakeSimOptimization Model

SnakeOpt

Purpose: Develop a model that provides the “best” management strategy for SRB users

Considers Major surface water features System uses

e.g., flood control, irrigation, fish, hydropower Groundwater impacts 8 major irrigation districts

Economic Objective Function

Snake River Basin WR Network

SnakeOpt - Approach

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

SnakeOpt – Approach

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

Comparison to Historical Operation

Snake River Storage, 1975-1985Historic Mean vs Optimized Single Years

5000

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Comparison to Historical Operation

Snake River Storage, 1975-1985Historic vs Optimized Historic

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Historic

Optimized

Drafted for ROR Energy

Elev Raised for EnergyLower SW Irrigation

Increase GW pumping

Comparison to Historical Operation

Dworshak Storage, 1975-1985Historic Mean vs Optimized Single Years

1400

1900

2400

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Comparison to Historical Operation

Dworshak Storage, 1975-1985Historic vs Optimized Historic

1500

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Historic

Optimized

Drafted for Fish

Drafted for Fish

Optimized Storage Response

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

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Comp2040

Current

Earlier runoff

Optimized Storage Response

Dworshak Storage, 1975-1985Optimized: Current vs Comp2040 Flows

1500

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2100

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2700

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Comp2040

Current

Earlier runoffReturn to near historic sto

Optimized SW Diversion Response

Snake River Surface Diversions, 1975-1985Optimized: Current vs Comp2040 Flows

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Current

Comp2040

Seasonal water availability

Optimized GW Pumping Response

Snake River Groundwater Pumping, 1975-1985Optimized: Current vs Comp2040 Flows

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Current

Comp2040

Higher ET, Less recharge

Optimized Hydropower Response

Minidoka Project Energy Production, 1975-1985Optimized: Current vs Comp2040 Flows

140000

160000

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200000

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260000

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300000

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

MW

h

Current

Comp2040

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

Optimized Hydropower Response

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

1506000

1706000

1906000

2106000

2306000

2506000

2706000

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

MW

h

Current

Comp2040

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

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

900000

1100000

1300000

1500000

1700000

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2100000

2300000

2500000

2700000

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

MW

h

Current

Comp2040

Historic

Optimized Hydropower Response

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

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

Example Management Options

Unconstrained system (capacities only) Flood space preserved 427 rule (or others) met every year All reservoirs operated conjunctively BOR, IP, COE operate own reservoirs

optimally Groundwater not used or used

selectively What areas are you interested in? Identify locations to optimize

sustainable managed recharge

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…

SnakeOpt – Potential Future Work

Annual Planning Approach

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 – 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?