1. THE IMPACT OF CLIMATE CHANGE ON WATER RESOURCES IN THE WESTERN U.S.
Dennis P. Lettenmaier
Department of Civil and Environmental Engineering
University of Washington
Environmental Defense Board of Trustees
Science Day on Water
September 18, 2003

2. Outline of this talk
Hydrology, climate variability, and climate change context
Prediction and assessment approach
Accelerated Climate Prediction Initiative (ACPI)
Hydrology and water management implications for Columbia, Sacramento-San Joaquin, and Colorado River basins
Conclusions and comparative analysis

3. Hydrology, climate variability, and climate change context

4. Humans are altering atmospheric composition
Methane has increased 151%, nitrous oxide 17%, also greenhouse gases

5. Hydrologic Characteristics of PNW Rivers

6. The earth is warming -- abruptly
What it is: Average surface temperature year by year
3 main features:
warming to 1940
cooling
warming since 1970
causes of these are different
were generally warmer than the top dots shown (continuing warming trend)

7. Natural Climate Influence Human Climate Influence
Red: observations of global average temperature
Grey: simulations with a climate model (huge computer program, like weather prediction model only run for hundreds of years)
Natural influence: volcanoes, solar variations – guesses before ~1970, better since then
Human influence: greenhouse gases, sulfate aerosols
it is possible to simulate the climate of the last 100 years, and the conclusion is that humans didn’t matter much before 1960 – the early warming and the cooling were largely natural, and the late-century warming was largely human-caused
All Climate Influences

8. The IPCC used a wide range of assumptions about future economic development, from rapid global economic growth relying mostly on fossil fuels to slow growth in which the developed world goes heavily toward a service economy and the developing world is left behind. For this wide range, CO2 doubles between 2050 and Best guess: 1C by mid-century, 3C by 2100.
Note that constant global temperature is not among the projections

9. Temperature trends in the PNW over the instrumental record
Almost every station shows warming (filled circles)
Urbanization not a major source of warming
BC: 0.5C (0.9F) in coastal region and 1.1C (2F) in CRB

10. Trends in timing of spring snowmelt (1948-2000)
+20d later
–20d earlier
Courtesy of Mike Dettinger, Iris Stewart, Dan Cayan

11. Trends in snowpack

12. Linear trends in annual mean temp.
Each dot represents a station with data going back at least to 1920, size of dot shows magnitude of linear trend. Open circles are negative trends - not many of those. Most trends in the 1-3F range. The regional average (using appropriate area-weighting) is 1.5F/century.
These data have been quality-controlled and corrected by the National Climate Data Center. This includes removing the “urban warming” effect, which is statistically estimated.

13. Trends in April 1 snow water equivalent, 1950-2000

16. o: observed +: nearest VIC grid point
Model-simulated and observed SWE, Pacific Coast to Continental Divide,
The circles show trends for snow courses in the 47N-49N band. The + symbols show the trend at the nearest VIC grid point, which
o: observed +: nearest VIC grid point

17. Model-simulated SWE, Rocky Mountains, 1950-97
Each dot shows the linear trend in Apr 1 SWE, 1950 to 1997, at one VIC grid point. Data used for this plot were between 47 and 49N, and east of 118 degrees longitude (the WA-ID border is 117 degrees)

18. This shows 10-year averages of temperature for the whole PNW; 1990’s were the warmest decade of the 20th century in the Northwest (as well as globally), by almost 1 degree. The rate of warming from 1970 to 2000 has been roughly what the CGCM1 simulates.
We looked at 8 scenarios produced by several different general circulation models from climate modeling centers around the world. All used the same simple scenario for CO2: 1%/year. The spread here does not include the spread from other greenhouse gas scenarios.
Looking ahead to the 2020s and 2040s, the warmest, average, and coolest of these 8 models are shown as red, yellow, and green. The average rate of warming is a bit less than 1 degree per decade. Even the coolest scenario still shows about 2F more warming by the 2040s.

19. 2) Prediction and assessment approach

20. Global climate simulations, next ~100 yrs
Scenarios
Performance
Measures
Downscaling
Global climate simulations, next ~100 yrs
Delta
Precip,
Temp
Reliability
of System
Objectives
Reservoir
Model
Hydrologic
Model (VIC)
DamReleases,
Regulated
Streamflow
Natural
Streamflow

21. Coupled Land-Atmosphere-Ocean General Circulation Model
Reservoir
Model
Hydrology Model

22. Accelerated Climate Prediction Initiative (ACPI) – NCAR/DOE Parallel Climate Model (PCM) grid over western U.S.

23. Bias Correction and Downscaling Approach
climate model scenario
meteorological outputs
 hydrologic model inputs
snowpack
runoff
streamflow
2.8 (T42)/0.5 degree resolution
monthly total P, avg. T
1/8-1/4 degree resolution
daily P, Tmin, Tmax
important point(s):
the approach attempts to make use of forecast skill from 2 sources:
better understanding of synoptic scale teleconnections and the effects of persistence in SSTs on regional climate, as reproduced in coupled ocean-atmosphere models;
the macroscale hydrologic model yields an improved ability to model the persistence in hydrologic states at the regional scale (more compatible with climate model scales than prior hydrologic modeling).
Climate forecasts with monthly and seasonal horizons are now operationally available, and if they can be translated to streamflow, then they may be useful for water management.

24. Bias Correction
from NCDC observations
from PCM historical run
raw climate scenario
bias-corrected climate scenario
month m
Note: future scenario temperature trend (relative to control run) removed before, and replaced after, bias-correction step.

25. interpolated to VIC scale
Downscaling
observed
mean fields
(1/8-1/4 degree)
monthly PCM
anomaly (T42)
VIC-scale
monthly simulation
interpolated to VIC scale

27. Overview of ColSim Reservoir Model
Reservoir Operating Policies
Reservoir Storage
Regulated Streamflow
Flood Control
Energy Production
Irrigation Consumption
Streamflow Augmentation
Physical System
of Dams
and Reservoirs
Streamflow Time Series

28. Dam Operations in ColSim
Storage Dams
Virgin
Regulated
Run-of-River Dams
Flow In=Flow out + Energy H

29. ColSim Storage Reservoirs + Run of River Reservoirs
Releases Depend on:
Storage and Inflow
Rule Curves (streamflow forecasts)
Flood Control Requirements
Energy Requirements
Minimum Flow Requirements
System Flow Requirements
Inflow
ColSim
Consumptive use
Inflow
Inflow
Consumptive use
Inflow
Inflow
Inflow +
Inflow
Run of River Reservoirs
(inflow=outflow + energy)
System Checkpoint

30. 3) Accelerated Climate Prediction Initiative (ACPI)

31. GCM grid mesh over western U. S
GCM grid mesh over western U.S. (NCAR/DOE Parallel Climate Model at ~ 2.8 degrees lat-long)

32. Climate Change Scenarios
PCM Simulations (~ 3 degrees lat-long)
Historical B06.22 (greenhouse CO2+aerosols forcing)
Climate Control B06.45 (CO2+aerosols at 1995 levels)
Climate Change B06.44 (BAU6, future scenario forcing)
Climate Change B06.46 (BAU6, future scenario forcing)
Climate Change B06.47 (BAU6, future scenario forcing)
PNNL Regional Climate Model (RCM) Simulations (~ ¾ degree lat-long)
important point(s):
GSM forecasts take the form of monthly ensembles of length 6 months
we get them early in each month for a start date of the following month.
the climatology ensemble enables us to define the climate model bias and correct it
climatology ensembles run out 6 months just like the forecasts, but use observed rather than predicted tropical Pacific SSTs
also:
210 ensembles for GSM climatology are derived from observed SSTs in each year of the 21 year climatology period ( ) combined with 10 initial atmospheric conditions for each year
GSM is at T42 spatial resolution, but moving to T62 soon (resolution improvement of about 1/3)
Climate Control B06.45 derived-subset
Climate Change B06.44 derived-subset

33. Future streamflows 3 ensembles averaged summarized into 3 periods;

34. Regional Climate Model (RCM) grid and hydrologic model domains
important point(s):
the overall forecasting approach involves using forecast model (the global spectral model) T & P output at a coarse timestep & scale as hydrologic model input at a finer timestep and scale.
to make a hydrologic forecast, you need a transformation of the forecasts that first overcomes climate model bias and the scale differences, then simulates the water balance.
also, GSM is really run at very fine timestep (~5-15 minutes) but only the monthly anomalies are archived for our use. most of the signal is at the monthly scale, however, so this is acceptable.

35. ACPI: PCM-climate change scenarios, historic simulation v air temperature observations

36. ACPI: PCM-climate change scenarios, historic simulation v precipitation observations

37. 4a) Hydrology and water management implications: Columbia River Basin

38. PCM Business-as-Usual scenarios Columbia River Basin (Basin Averages)
BAU 3-run average
historical ( )
control ( )
PCM
Business-as-Usual
scenarios
Columbia River Basin
(Basin Averages)
important point(s):
we’re modeling most of the US at 1/8 degree now with the VIC model, but we are performing this forecasting exercise in the Columbia River basin. The plusses show the grid of the numerical weather prediction (forecasting) model that we used (GSM), and the ¼ degree hydrology model resolution can just be discerned in the figure. 24 climate model grid points were used, and 1,668 VIC model cells. We’ve aggregate the VIC model to ¼ degree from 1/8 degree in the Columbia River basin to speed the forecast runs.

39. RCM Business-as-Usual scenarios Columbia River Basin (Basin Averages)
PCM BAU B06.44
RCM BAU B06.44
control ( )
historical ( )
important point(s):
we’re modeling most of the US at 1/8 degree now with the VIC model, but we are performing this forecasting exercise in the Columbia River basin. The plusses show the grid of the numerical weather prediction (forecasting) model that we used (GSM), and the ¼ degree hydrology model resolution can just be discerned in the figure. 24 climate model grid points were used, and 1,668 VIC model cells. We’ve aggregate the VIC model to ¼ degree from 1/8 degree in the Columbia River basin to speed the forecast runs.

41. PCM Business-As-Usual Mean Monthly Hydrographs Columbia River Basin
@ The Dalles, OR
important point(s):
we’re modeling most of the US at 1/8 degree now with the VIC model, but we are performing this forecasting exercise in the Columbia River basin. The plusses show the grid of the numerical weather prediction (forecasting) model that we used (GSM), and the ¼ degree hydrology model resolution can just be discerned in the figure. 24 climate model grid points were used, and 1,668 VIC model cells. We’ve aggregate the VIC model to ¼ degree from 1/8 degree in the Columbia River basin to speed the forecast runs.
month
month

42. CRB Operation Alternative 1 (early refill)

43. CRB Operation Alternative 2 (reduce flood storage by 20%)
15,000,000
20,000,000
25,000,000
30,000,000
35,000,000
40,000,000
45,000,000
50,000,000
55,000,000 O N D J F M A S
End of Month Total System Storage (acre-feet)
Max Storage
Control
Base Climate Change
Change (Alt. 2)
Dead Pool

48. 4a) Hydrology and water management implications: Sacramento-San Joaquin River Basin

49. PCM Business-as-Usual scenarios California (Basin Average)
BAU 3-run average
historical ( )
control ( )
important point(s):
we’re modeling most of the US at 1/8 degree now with the VIC model, but we are performing this forecasting exercise in the Columbia River basin. The plusses show the grid of the numerical weather prediction (forecasting) model that we used (GSM), and the ¼ degree hydrology model resolution can just be discerned in the figure. 24 climate model grid points were used, and 1,668 VIC model cells. We’ve aggregate the VIC model to ¼ degree from 1/8 degree in the Columbia River basin to speed the forecast runs.

50. PCM Snowpack Changes Business-as-Usual Scenarios California
April 1 SWE
important point(s):
we’re modeling most of the US at 1/8 degree now with the VIC model, but we are performing this forecasting exercise in the Columbia River basin. The plusses show the grid of the numerical weather prediction (forecasting) model that we used (GSM), and the ¼ degree hydrology model resolution can just be discerned in the figure. 24 climate model grid points were used, and 1,668 VIC model cells. We’ve aggregate the VIC model to ¼ degree from 1/8 degree in the Columbia River basin to speed the forecast runs.

51. PCM Business-As-Usual Mean Monthly Hydrographs
Shasta Reservoir Inflows
important point(s):
we’re modeling most of the US at 1/8 degree now with the VIC model, but we are performing this forecasting exercise in the Columbia River basin. The plusses show the grid of the numerical weather prediction (forecasting) model that we used (GSM), and the ¼ degree hydrology model resolution can just be discerned in the figure. 24 climate model grid points were used, and 1,668 VIC model cells. We’ve aggregate the VIC model to ¼ degree from 1/8 degree in the Columbia River basin to speed the forecast runs.

52. Sacramento River Basin
Trinity
Trinity Lake Storage: 2448 taf
Shasta
Lake Shasta
Storage: 4552 taf
Whiskeytown
Storage: 241 taf
Lake Oroville
Storage: 3538 taf
Folsom Lake
Storage: 977 taf
Whiskeytown
Oroville (SWP)
Trinity River
Clear Creek
Oroville is operated by the SWP
Feather River
Dam
Power Plant
River
Transfer
Sacramento River
American River
Folsom
Delta

53. Delta & San Joaquin R Basin
Sacramento-San Joaquin Delta
Area: 1200 mi2
Delta
Pardee/Camanche
Reservoir
Storage: 615 taf
San Luis Reservoir
CVP: 971 taf
SWP: 1070 taf
Mokelumne River
Millerton Lake
Storage: 761 taf
New Melones Res
Storage: 2420 taf
Don Pedro/McClure
Storage: 3055 taf
Pardee & Camanche
Delta Outflow
Delta
Calaveras River
New Hogan
Stanislaus River
San Luis
San Joaquin River
New Hogan is only about 300 taf and is not pictured
San Luis Reservoir jointly operated by Federal and State agencies
- State water flows to demand targets through 400 mi California Aqueduct
- Federal water flows to demand targets through Delta-Mendota Canal – some water is exported back to Upper San Joaquin River
The Sacramento-San Joaquin Delta is the most important thing to point out. Many environmental rules (fish and water quality) in the Delta govern the operation of reservoirs on both the Sacramento and San Joaquin R, as well as the San Luis Reservoir (which is downstream via man-made channels).
New Melones
Dam
Power Plant
River/Canal
Transfer
Tuolumne & Merced Rivers
Eastman, Hensley, & Millerton
New Don Pedro & McClure

55. Current Climate vs. Projected Climate
Storage Decreases
Sacramento
Range: %
Mean: 8 %
San Joaquin
Range: %
Mean: 11 %

56. Current Climate vs. Projected Climate
Hydropower Losses
Central Valley
Range: %
Mean: 9 %
Sacramento System
Range: 3 – 19 %
Mean: 9%
San Joaquin System
Range: 16 – 63 %
Mean: 28%

57. 4a) Hydrology and water management implications: Colorado River basin

58. Timeseries Annual Average
PCM Projected Colorado R. Temperature
Timeseries Annual Average
ctrl. avg.
hist. avg.
Period Period Period

59. Timeseries Annual Average
PCM Projected Colorado R. Precipitation
Timeseries Annual Average
hist. avg.
ctrl. avg.
Period Period Period

60. Annual Average Hydrograph
Simulated Historic ( ) Period 1 ( ) Control (static 1995 climate) Period 2 ( ) Period 3 ( )

61. Projected Spatial Change in Runoff
90 % 86 % 82 % 83 %

62. April 1 Snow Water Equivalent

63. Natural Flow at Lee Ferry, AZ
allocated 20.3 BCM
Currently used BCM

65. Storage Reservoirs Run of River Reservoirs
CRRM
Historic Streamflows to Validate
Projected Inflows to assess future performance of system
Monthly timestep
Basin storage aggregated into 4 storage reservoirs
Lake Powell and Lake Mead have 85% of basin storage
Reservoir evaporation = f(reservoir surface area, mean monthly temperature)
Hydropower = f(release, reservoir elevation)
Storage Reservoirs Run of River Reservoirs

66. Water Management Model (CRRM)
Multi Species Conservation Program year 2000 demands
upper basin BCM
lower basin BCM
Mexico BCM
Minimum Annual Release from Glen Canyon Dam of 10.8 BCM
Minimum Annual Release from Imperial Dam of 1.8 BCM

67. Total Basin Storage

68. Annual Releases to the Lower Basin
target release

69. Annual Releases to Mexico
target release

70. Annual Hydropower Production

71. Uncontrolled Spills

72. Deliveries to CAP & MWD

73. 5) Conclusions and Comparative analysis
1) Columbia River reservoir system primarily provides within-year storage (total storage/mean flow ~ 0.3). California is intermediate (~ 0.3), Colorado is an over-year system (~4)
2) Climate sensitivities in Columbia basin are dominated by seasonality shifts in streamflow, and may even be beneficial for hydropower. However, fish flow targets would be difficult to meet under altered climate, and mitigation by altered operation is essentially impossible.
3) California system operation is dominated by water supply (mostly ag), reliability of which would be reduced significantly by a combination of seaonality shifts and reduced (annual) volumes. Partial mitigation by altered operations is possible, but complicated by flood issues.
4) Colorado system is sensitive primarily to annual streamflow volumes. Low runoff ratio makes the system highly sensitive to modest changes in precipitation (in winter, esp, in headwaters). Sensitivity to altered operations is modest, and mitigation possibilities by increased storage are nil (even if otherwise feasible).