Alan F. Hamlet

•JISAO/CSES Climate Impacts Group•Dept. of Civil and Environmental Engineering

University of Washington

Overview of Streamflow Scenario Generation Procedures and a Test Case for the Columbia River Optimization Study

Issues Related to Choice of Hydrologic Model

Snow Model

Schematic of VIC Hydrologic Model and Energy Balance Snow Model

Designing Climate Change Scenarios For Flood Studies

Issues Related to Choice of Downscaling Procedure

1) Delta method experiments In this approach realistic daily sequencing and variability from the

historic record are combined with systematic changes in temperature and precipitation extracted from GCMs.

2) Advanced statistical downscaling These approaches add spatial variability and transient time series

behavior from GCMs as well as more detailed statistical information about changes in temperature and precipitation at monthly time scales. Daily sequences are usually extracted from the historic record.

3) Dynamic downscaling using nested meso-scale modelsThese approaches dynamically simulate weather using GMM

simulations as the large scale forcing. The approach has the potential to construct new weather statistics at small spatial and temporal scales, but with considerable uncertainty due to

model limitations and small sample sizes.

Pacific Northwest

°C

0.4-1.0°C0.9-2.4°C 1.2-5.5°C

Obse

rved 2

0th

centu

ry v

ari

abili

ty

+1.7°C+0.7°C

+3.2°C

Pacific Northwest

% -1 to +3%

-1 to +9% -2 to +21%

Obse

rved 2

0th

centu

ry v

ari

abili

ty

+1% +2%

+6%

-3

-2

-1

0

1

2

3

419

16

1920

1924

1928

1932

1936

1940

1944

1948

1952

1956

1960

1964

1968

1972

1976

1980

1984

1988

1992

1996

2000

Std

An

om

alie

s R

elat

ive

to 1

961-

1990

PNW

CA

CRB

GB

Regionally Averaged Cool Season Precipitation Anomalies

PRECIP

-1.00

-0.50

0.00

0.50

1.00

1.50

2.00

2.50

3.00

oct nov dec jan feb mar apr may jun jul aug sepL

inea

r T

ren

d (

Deg

. C p

er c

entu

ry)

CA

CRB

GBAS

PNW

0.00

0.50

1.00

1.50

2.00

2.50

3.00

3.50

4.00

oct nov dec jan feb mar apr may jun jul aug sep

Lin

ear

Tre

nd

(D

eg. C

per

cen

tury

)

CA

CRB

GBAS

PNWTmin

Tmax

PNW

CA CRB

GB

Regionally Averaged Temperature Trends Over the Western U.S. 1916-2003

Test Case for the Columbia Basin Optimization Studies

1) First, monthly temperature trends are removed from the daily time step hydrologic model driving data set, pivoting around the year 2000. (Temperature variability is preserved, but temperature records are more consistent through time.)

2) A systematic increase in temperature of 2 C is then added to the driving data at monthly time step, based on a consensus of seasonal increases in temperature from four GCMs. Precipitation is not altered. Thus historic storm sequences are paired with systematically warmer conditions in the test case.

3) Daily time step hydrologic simulations from 1916-2003 were produced using the perturbed driving data, and monthly bias was removed from the simulations using quantile mapping techniques (See Snover et al. 2003).

4) The bias adjusted streamflow time series are then used as input to the optimization and simulation models.

Overview of Monthly Hydrologic Simulations for the Optimization Test Case

Tem

pera

ture

Historic temperature trend

in each calendar month

1915 2003

Detrended Temperature Driving Data for Flood Risk Experiments

“Pivot 2000” Data Set

“Pivot 1915” Data Set

Precipitation Fraction, 2020s

0.5

0.75

1

1.25

1.5

1.75

J F M A M J J A S O N D

Frac

tion

hadCM2

hadCM3

PCM3

ECHAM4

mean

Delta T, 2020s

-1

0

1

2

3

4

5

J F M A M J J A S O N D

De

gre

es

C

hadCM2

hadCM3

PCM3

ECHAM4

mean

Delta T, 2040s

-1

0

1

2

3

4

5

J F M A M J J A S O N D

De

gre

es

C

hadCM2

hadCM3

PCM3

ECHAM4

mean

Precipitation Fraction, 2040s

0.5

0.75

1

1.25

1.5

1.75

J F M A M J J A S O N D

Fra

ctio

n

hadCM2

hadCM3

PCM3

ECHAM4

mean

Delta Method Climate Change Scenarios for the PNW

~ + 1.7 C ~ + 2.5 C

Quantile-Based Bias Correction (Wood et al. 2002; Snover et al. 2003)

0

5000

10000

15000

20000

25000

30000

35000

0 0.2 0.4 0.6 0.8 1

Probability of Exceedence

Flo

w (

cfs)

obs

vic

VIC Input = 19000

Bias Corrected Output = 10000

0

10000

20000

30000

40000

50000

60000

1 62 123 184 245 306 367 428 489 550 611 672 733 794 855 916 977 1038 1099 1160 1221 1282 1343 1404 1465 1526 1587 1648 1709 1770

obs week

adj vic week

0

5000

10000

15000

20000

25000

30000

35000

40000

1 62 123 184 245 306 367 428 489 550 611 672 733 794 855 916 977 1038 1099 1160 1221 1282 1343 1404 1465 1526 1587 1648 1709 1770

obs daily

adj vic daily

Reconstructed Naturalized Weekly and Daily Flows at Palisades Dam for 1958-1992

Str

eam

flow

(cf

s)

Weekly Flow 1958-1992

Daily Flow 1958-1962

Conclusions

A number of well developed procedures are available for constructing streamflow scenarios for large-scale planning studies using physically based hydrologic models at monthly to daily time scales.

Different downscaling strategies are appropriate for different kinds of planning studies.

For the Columbia Basin flood control optimization test case we chose to use a simple and effective procedure in which systematically warmer temperatures are paired with observed storm sequences to produce realizations of snowmelt flooding events in the Columbia basin in a warmer climate.

In other systems, other downscaling choices may be more appropriate.

Salathé, E.P., 2004: Methods for selecting and downscaling simulations of future global climate with application to hydrologic modeling, International J. of Climatology, 25: 419-436

Wiley, M.W., Palmer, R.N., Salathé, E.P., 2006: The development of GCM-based climate scenarios for use in water resource system impact evaluations, ASCE J. Water Resources Planning and Management, (in review)

Wood A.W., Maurer E.P., Kumar A. and Lettenmaier, D.P., 2002: Long range experimental hydrologic forecasting for the eastern U.S. J. Geophys. Res., 107 (D20): 4429

Wood, A.W., Leung, L.R., Sridhar, V. and Lettenmaier, D.P., 2004: Hydrologic implications of dynamical and statistical approaches to downscaling climate model outputs, Climatic Change, 62 (1-3): 189-216

Selected References on Downscaling Strategies