water and climate: what's changing, and does it matter to water managers?
Post on 04-Jan-2016
26 Views
Preview:
DESCRIPTION
TRANSCRIPT
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
60
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
80
100
120
140
FirmHydropower
Annual FlowDeficit atMcNary
Perc
en
t o
f C
on
tro
l R
un
Cli
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
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
Sr. Irrigators
Jr Irrigators
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
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
5000
10000
15000
20000
25000
30000
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
top related