Transcript Water and Climate: What`s Changing, and Does It Matter to Water

Water and Climate: What's Changing,
and Does It Matter to Water Managers?
Dennis P. Lettenmaier
Department 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 Changes
in 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).
58%
+10%
67%
62%
58%
96%
+2%
62%
62%
71%
87%
-2%
75%
100%
67%
67%
67%
-5%
-10%
-25%
(After Milly, P.C.D., K.A. Dunne, A.V. Vecchia, Global pattern of trends in streamflow and
water availability in a changing climate, Nature, 438, 347-350, 2005.)
Decrease
87%
+5%
Increase
+25%
PCM Projected Colorado R. Temperature
Timeseries
Annual Average
ctrl. avg.
hist. avg.
Period 1 2010-2039
Period 2 2040-2069
Period 3 2070-2098
PCM Projected Colorado R. Precipitation
Timeseries
Annual Average
hist. avg.
ctrl. avg.
Period 1 2010-2039
Period 2 2040-2069
Period 3 2070-2098
Annual Average Hydrograph
Simulated Historic (1950-1999)
Control (static 1995 climate)
Period 1 (2010-2039)
Period 2 (2040-2069)
Period 3 (2070-2098)
Natural Flow at Lee Ferry, AZ
Natural Flow at Lee Ferry Stream Gage
30
Annual Flow (BCM)
25
allocated
20.3 BCM
20
15
Currently used
16.3 BCM
10
5
0
1900
1910
1920
1930
Annual Flow
1940
1950
10 Year Average
1960
1970
1980
Running Average
1990
2000
Total Basin Storage
Figure 8
70
Minimum
60
Average
Maximum
Storage, BCM
50
40
30
20
10
0
Historical
Control
Period 1
Period 2
Period 3
Annual Releases to the Lower Basin
Figure 9
14
1.2
Average Annual Release to Lower Basin (BCM/YR)
Probability release to Lower Basin meets or exceeds target (probability)
12
1
target release
10
8
0.6
6
0.4
4
0.2
2
0
0
Historical
Control
Period 1
Period 2
Period 3
Probability
BCM / YR.
0.8
Annual Releases to Mexico
Figure 10
1.2
Average Annual Release to Mexico
(BCM/YR)
3
Probability release to Mexico meets or
exceeds target (probability)
BCM / YR.
2.5
1
0.8
2
target release
0.6
1.5
0.4
1
0.2
0.5
0
0
Historical
Control
Period 1
Period 2
Period 3
Probability
3.5
Annual Hydropower Production
Figure 12
18000
Minimum
16000
Average
Energy, GW - hr
14000
Maximum
12000
10000
8000
6000
4000
2000
0
Historical
Control
Period 1
Period 2
Period 3
Percent of Control Run Climate
2040-2069
140
120
PCM Control Climate and
Current Operations
100
PCM Projected Climate
and Current Operations
PCM Projected Climate
with Adaptive Management
80
60
Firm
Hydropower
Annual Flow
Deficit at
McNary
Percent of Control Run Climate
2070-2098
140
PCM Control Climate and
Current Operations
120
PCM Projected Climate
and Current Operations
100
PCM Projected Climate
with Adaptive
Management
80
60
Firm
Hydropower
Annual Flow
Deficit at
McNary
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
2080s
2020s
historical
•
•
•
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% historically
32% in 2020s A1B (15% to 54% range of ensemble members)
36% in 2040s A1B
77% in 2080s A1B
Crop Model - Apple Yields
20
Average Apple Yields
25
20
15
Sr. Irrigators
Jr Irrigators
Tons/Acre
Tons/Acre
15
Sr. Irrigators
Jr Irrigators
10
10
5
0
No CO2
CO2
No CO2
B1
A1B
Historical
CO2
No CO2
No CO2
CO2
B1
A1B
No CO2
CO2
No CO2
CO2
B1
A1B
2080
2040
2020
5
•
CO2
Scenario
Yields decline from historic by 20% to 25% (2020s) and 40% to 50% (2080s)
No CO2
CO20 No CO2
CO2
No CO2
CO2
No CO2
CO2
BAU 3-run average
historical (1950-99)
control (2000-2048)
PCM
Business-as-Usual
scenarios
California
(Basin Average)
PCM
Business-as-Usual Scenarios
Snowpack Changes
California
April 1 SWE
Central Valley Water Year Type Occurrence
Percent Given WY Type
0.6
hist (1906-2000)
0.5
2020s
2050s
2090s
0.4
0.3
0.2
0.1
0.0
Critically Dry
Dry
Below Normal
Water Year Type
Above Normal
Wet
Current Climate vs. Projected Climate
Storage Decreases
• Sacramento
Range: 5 - 10 %
Mean: 8 %
• San Joaquin
Range: 7 - 14 %
Mean: 11 %
Current Climate vs. Projected Climate
Hydropower Losses
Central Valley Hydropower Production
1400000
• Central Valley
Range: 3 - 18 %
Mean: 9 %
• Sacramento System
Range: 3 – 19 %
Mean: 9%
• San Joaquin System
Range: 16 – 63 %
Mean: 28%
Ctrl mean
2000-2019
2020-2039
2040-2059
2060-2079
2080-2098
1200000
Megawatt-Hours
1000000
800000
600000
400000
200000
ct
O
ov
N
D
ec
Ja
n
b
Fe
M
ar
pr
A
M
ay
n
Ju
l
Ju
ug
A
p
Se
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
New time series value = 19000
35000
30000
Objective:
Combine the time series
behavior of an observed
precipitation, temperature,
or streamflow record with
changes in probability
distributions associated
with climate change.
Flow (cfs)
25000
20000
obs
15000
climate change
10000
5000
0
0
0.2
0.4
0.6
0.8
1
Probability of Exceedence
Value from observed time series = 10000
KAF
KAF
Observed and Climate Change Adjusted Naturalized
Streamflow Time Series for the Snake River at Ice Harbor
Blue = Observed time series
Red = Climate change time series
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