Water and Climate: What's Changing, and Does It Matter to Water Managers?

Dennis P. LettenmaierDepartment of Civil and Environmental Engineering

University of Washington

for

2009 AAAS Annual Meeting

Session on 21st Century Water: Friend or Foe?

Chicago

February 14, 2009

What are the “grand challenges” in hydrology?

• From Science (2006) 125th Anniversary issue (of eight in Environmental Sciences): Hydrologic forecasting – floods, droughts, and contamination

• From the CUAHSI Science and Implementation Plan (2007): … a more comprehensive and … systematic understanding of continental water dynamics …

• From the USGCRP Water Cycle Study Group, 2001 (Hornberger Report): [understanding] the causes of water cycle variations on global and regional scales, to what extent [they] are predictable, [and] how … water and nutrient cycles [are] linked?

Important problems all, but I will argue instead (in addition) that understanding hydrologic change should rise to the level of a grand challenge to the community.

From Stewart et al, 2005

Magnitude and Consistency of Model-Projected Changesin Annual Runoff by Water Resources Region, 2041-2060

Median change in annual runoff from 24 numerical experiments (color scale)and fraction of 24 experiments producing common direction of change (inset numerical values).

+25%

+10%

+5%

+2%

-2%

-5%

-10%

-25%

Dec

reas

eIn

crea

se

(After Milly, P.C.D., K.A. Dunne, A.V. Vecchia, Global pattern of trends in streamflow andwater availability in a changing climate, Nature, 438, 347-350, 2005.)

96%

75%67%

62%87%

87%

71%

67%62%

58%

67%

62%58%

67%100%

Timeseries Annual Average

Period 1 2010-2039 Period 2 2040-2069 Period 3 2070-2098

hist. avg.

ctrl. avg.

PCM Projected Colorado R. Temperature

hist. avg.

ctrl. avg.

PCM Projected Colorado R. Precipitation

Timeseries Annual Average

Period 1 2010-2039 Period 2 2040-2069 Period 3 2070-2098

Annual Average Hydrograph

Simulated Historic (1950-1999) Period 1 (2010-2039)Control (static 1995 climate) Period 2 (2040-2069)

Period 3 (2070-2098)

Natural Flow at Lee Ferry, AZ

Currently used 16.3 BCM

allocated20.3 BCM

Total Basin Storage

Annual Releases to the Lower Basin

target release

Annual Releases to Mexico

target release

Annual Hydropower Production

2040-2069

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80

100

120

140

FirmHydropower

Annual FlowDeficit atMcNary

Pe

rce

nt

of

Co

ntr

ol

Ru

n C

lim

ate

PCM Control Climate andCurrent Operations

PCM Projected Climateand Current Operations

PCM Projected Climatewith Adaptive Management

2070-2098

60

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100

120

140

FirmHydropower

Annual FlowDeficit atMcNary

Perc

en

t o

f C

on

tro

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mate

PCM Control Climate andCurrent Operations

PCM Projected Climateand Current Operations

PCM Projected Climatewith AdaptiveManagement

Case study 1: Yakima River Basin

• Irrigated crops largest agriculture value in the state

• Precipitation (fall-winter), growing season (spring-summer)

• Five USBR reservoirs with storage capacity of ~1 million acre-ft, ~30% unregulated annual runoff

• Snowpack sixth reservoir• Water-short years impact water

entitlements

Yakima River Basin

• Basin shifts from snow to more rain dominant• Water prorating, junior water users receive 75% of allocation• Junior irrigators less than 75% prorating (current operations):

14% historically32% in 2020s A1B (15% to 54% range of ensemble members)36% in 2040s A1B77% in 2080s A1B

historical2020s

2080s

0

5

10

15

20

25

No CO2 CO2 No CO2 CO2 No CO2 CO2 No CO2 CO2 No CO2 CO2 No CO2 CO2

A1B B1 A1B B1 A1B B1

Historical 2020 2040 2080

Scenario

To

ns/

Acr

e

0

5

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20

25

No CO2 CO2 No CO2 CO2 No CO2 CO2 No CO2 CO2 No CO2 CO2 No CO2 CO2

A1B B1 A1B B1 A1B B1

Historical 2020 2040 2080

Sr. Irrigators

Jr Irrigators

0

5

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25

No CO2 CO2 No CO2 CO2 No CO2 CO2 No CO2 CO2 No CO2 CO2 No CO2 CO2

A1B B1 A1B B1 A1B B1

Historical 2020 2040 2080

To

ns/

Acr

e

Crop Model - Apple Yields

• Yields decline from historic by 20% to 25% (2020s) and 40% to 50% (2080s)

PCM Business-as-Usual scenarios

California(Basin Average)

control (2000-2048)

historical (1950-99)

BAU 3-run average

PCM Business-as-Usual Scenarios

Snowpack ChangesCaliforniaApril 1 SWE

Central Valley Water Year Type Occurrence

0.0

0.1

0.2

0.3

0.4

0.5

0.6

Critically Dry Dry Below Normal Above Normal Wet

Water Year Type

Per

cen

t G

iven

WY

Typ

e

hist (1906-2000) 2020s 2050s 2090s

Storage Decreases• Sacramento

Range: 5 - 10 %Mean: 8 %

• San Joaquin Range: 7 - 14 %Mean: 11 %

Current Climate vs. Projected Climate

Current Climate vs. Projected Climate

Central Valley Hydropower Production

200000

400000

600000

800000

1000000

1200000

1400000

OctNov

Dec Jan

Feb Mar Apr

May Ju

nJu

lAug

Sep

Meg

awat

t-H

ou

rs

Ctrl mean

2000-2019

2020-2039

2040-2059

2060-2079

2080-2098

Hydropower Losses• Central Valley

Range: 3 - 18 %Mean: 9 %

• Sacramento System Range: 3 – 19 %Mean: 9%

• San Joaquin System Range: 16 – 63 %Mean: 28%

Stationarity—the idea that natural systems fluctuate within an unchanging envelope of variability—is a foundational concept that permeates training and practice in water-resource engineering.

In view of the magnitude and ubiquity of the hydroclimatic change apparently now under way, however, we assert that stationarity is dead and should no longer serve as a central, default assumption in water-resource risk assessment and planning.

How can the water management community respond?

Central methodological problem: While water managers are used to dealing with risk, they mostly use methods that are heavily linked to the historical record

“Synthetic hydrology” c. 1970

Figure adapted from Mandelbrot and Wallis (1969)

Ensembles of Colorado River (Lees Ferry) temperature, precipitation, and discharge for IPCC A2 and B1 scenarios (left), and 50-year segments of tree ring reconstructions of Colorado Discharge (from Woodhouse et al, 2006)

Hybrid Climate Change Perturbations

Objective:

Combine the time series behavior of an observed precipitation, temperature, or streamflow record with changes in probability distributions associated with climate change.

0

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15000

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35000

0 0.2 0.4 0.6 0.8 1

Probability of Exceedence

Flo

w (

cfs

)

obs

climate change

New time series value = 19000

Value from observed time series = 10000

Observed and Climate Change Adjusted Naturalized Streamflow Time Series for the Snake River at Ice Harbor

Blue = Observed time seriesRed = Climate change time series

KA

FK

AF

Other implications of nonstationarity

• Hydrologic network design (station discontinuance algorithms won’t work)

• Need for stability in the evolution of climate scenarios (while recognizing that they will almost certainly change over time)

Another complication: Water resources research has died in the U.S.

• No federal agency has a competitive research program dedicated to water resources research (e.g., equivalent to the old OWRT)

• As a result, very few Ph.D. students (and hence young faculty) have entered the area

• And in turn, the research that would identify alternatives to classic stationarity assumptions is not being done

See Lettenmaier, “Have we dropped the ball on water resources”, ASCE JWRPM editorial, to appear Nov., 2008

Conclusions

• Ample evidence that stationarity assumption is no longer defensible for water planning (especially in the western U.S.)

• What to replace it with remains an open question• A key element though will have to be weaning

practitioners from critical period analysis, to risk based approaches (not a new idea!!)

• Support for the basic research needed to develop alternative methods (a new Harvard Water Program?) is lacking