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

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

Hydrology, climate variability, and climate change context

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

Hydrologic Characteristics of PNW Rivers

The earth is warming -- abruptly What it is: Average surface temperature year by year 3 main features: warming to 1940 cooling 1940-1970 warming since 1970 causes of these are different 1996-1999 were generally warmer than the top dots shown (continuing warming trend)

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

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 2100. Best guess: 1C by mid-century, 3C by 2100. Note that constant global temperature is not among the projections

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

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

Trends in snowpack

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.

Trends in April 1 snow water equivalent, 1950-2000

o: observed +: nearest VIC grid point Model-simulated and observed SWE, Pacific Coast to Continental Divide, 1950-97 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

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)

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.

2) Prediction and assessment approach

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

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

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

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.

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.

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

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

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

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

3) Accelerated Climate Prediction Initiative (ACPI)

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)

Climate Change Scenarios PCM Simulations (~ 3 degrees lat-long) Historical B06.22 (greenhouse CO2+aerosols forcing) 1870-2000 Climate Control B06.45 (CO2+aerosols at 1995 levels) 1995-2048 Climate Change B06.44 (BAU6, future scenario forcing) 1995-2099 Climate Change B06.46 (BAU6, future scenario forcing) 1995-2099 Climate Change B06.47 (BAU6, future scenario forcing) 1995-2099 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 (1979-1999) 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 1995-2015 Climate Change B06.44 derived-subset 2040-2060

Future streamflows 3 ensembles averaged summarized into 3 periods;

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.

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

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

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

PCM Business-as-Usual scenarios Columbia River Basin (Basin Averages) BAU 3-run average historical (1950-99) control (2000-2048) 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.

RCM Business-as-Usual scenarios Columbia River Basin (Basin Averages) PCM BAU B06.44 RCM BAU B06.44 control (2000-2048) historical (1950-99) 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.

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. 1 month 12 1 month 12

CRB Operation Alternative 1 (early refill)

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

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

PCM Business-as-Usual scenarios California (Basin Average) BAU 3-run average historical (1950-99) control (2000-2048) 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.

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.

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.

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

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

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 Range: 3 - 18 % Mean: 9 % Sacramento System Range: 3 – 19 % Mean: 9% San Joaquin System Range: 16 – 63 % Mean: 28%

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

Timeseries Annual Average PCM Projected Colorado R. Temperature Timeseries Annual Average ctrl. avg. hist. avg. Period 1 2010-2039 Period 2 2040-2069 Period 3 2070-2098

Timeseries Annual Average 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) Period 1 (2010-2039) Control (static 1995 climate) Period 2 (2040-2069) Period 3 (2070-2098)

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

April 1 Snow Water Equivalent

Natural Flow at Lee Ferry, AZ allocated 20.3 BCM Currently used 16.3 BCM

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

Water Management Model (CRRM) Multi Species Conservation Program year 2000 demands upper basin 5.4 BCM lower basin 9.3 BCM Mexico 1.8 BCM Minimum Annual Release from Glen Canyon Dam of 10.8 BCM Minimum Annual Release from Imperial Dam of 1.8 BCM

Total Basin Storage

Annual Releases to the Lower Basin target release

Annual Releases to Mexico target release

Annual Hydropower Production

Uncontrolled Spills

Deliveries to CAP & MWD

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).