The Once and Future Pulse of Colorado River Flow

Mitigating Water Supply Risk Under Changing Climate

Balaji Rajagopalan Department of Civil, Environmental and Architectural

EngineeringAnd

Cooperative Institute for Research in Environmental Sciences

(CIRES)

University of ColoradoBoulder, CO

23 February, 2010Presentation to Michael Kinter-MeyerEnergy and Environment DirectoratePacific Northwest National Laboratory

Key Questions

What is the Colorado River System-wide Water supply risk profile under climate change?

Need to consider the entire syste (~60AF Storage) Need to generate streamflow scenarios consistent

with climate projections and combining (Paleo?)

Is there flexibility within the existing management framework?

Can Management Mitigate the future risk?

Rajagopalan et al. (2009, WRR)

Colorado River Basin Overview 7 States, 2 Nations

Upper Basin: CO, UT, WY, NM Lower Basin: AZ, CA, NV

Fastest Growing Part of the U.S. Over 1,450 miles in length Basin makes up about 8% of

total U.S. lands Highly variable Natural Flow

which averages 15 MAF 60 MAF of total storage

4x Annual Flow 50 MAF in Powell + Mead

Irrigates 3.5 million acres Serves 30 million people Very Complicated Legal

Environment Denver, Albuquerque, Phoenix,

Tucson, Las Vegas, Los Angeles, San Diego all use CRB water

DOI Reclamation Operates Mead/Powell

Source:Reclamation

1 acre-foot = 325,000 gals, 1 maf = 325 * 109 gals1 maf = 1.23 km3 = 1.23*109 m3

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2006

Calnder Year

Annu

al Flo

w (M

AF)

Total Colorado River Use 9-year moving average.

NF Lees Ferry 9-year moving average

Colorado River Demand - Supply

UC CRSS stream gaugesLC CRSS stream gauges

Colorado River at Lees Ferry, AZ

Recent conditions in the Colorado River Basin

Paleo Context Below normal flows into

Lake Powell 2000-2004 62%, 59%, 25%, 51%,

51%, respectively 2002 at 25% lowest

inflow recorded since completion of Glen Canyon Dam

Some relief in 2005 105% of normal inflows

Not in 2006 ! 73% of normal inflows

2007 at 68% of Normal inflows 2008 at 111% of Normal inflows

5 year running average

Winter and Summer Precipitation Changes at 2100 – High Emissions

SummerHatching Indicates Areas of Strong Model Agreement

Study Climate Change Technique (Scenario/GCM)

Flow Generation Technique (Regression equation/Hydrologic model)

Runoff Results Operations Model Used [results?]

Notes

Stockton and Boggess, 1979

Scenario Regression: Langbein's 1949 US Historical Runoff- Temperature-Precipitation Relationships

+2C and -10% Precip = ~ -33% reduction in Lees Ferry Flow

  Results are for the warmer/drier and warmer/wetter scenarios.

   

Revelle and Waggoner, 1983

Scenario Regression on Upper Basin Historical Temperature and Precipitation

+2C and -10% Precip= -40% reduction in Lee Ferry Flow

  +2C only = -29% runoff,

    -10% Precip only = -11% runoff.

Nash and Gleick, 1991 and 1993

Scenario and GCM

NWSRFS Hydrology model runoff derived from 5 temperature & precipitation Scenarios and 3 GCMs using doubled CO2 equilibrium runs.

+2C and -10% Precip = ~ -20% reduction in Lee Ferry Flow

Used USBR CRSS Model for operations impacts.

Many runoff results from different scenarios and sub-basins ranging from decreases of 33% to increases of 19%.

Christensen et al., 2004

GCM UW VIC Hydrology model runoff derived from temperature & precipitation from NCAR GCM using Business as Usual Emissions.

+2C and -3% Precip at 2100 = -17% reduction in total basin runoff

Created and used operations model, CRMM.

Used single GCM known not to be very temperature sensitive to CO2 increases.

Hoerling and Eischeid, 2006

GCM Regression on PDSI developed from 18 AR4 GCMs and 42 runs using Business as Usual Emissions.

+2.8C and ~0% Precip at 2035-2060 = -45% reduction in Lee Fee Flow

   

Christensen and Lettenmaier, 2006

GCM UW VIC Hydrology Model runoff using temperature & precipitation from 11 AR4 GCMs with 2 emissions scenarios.

+4.4C and -2% Precip at 2070-2099 = -11% reduction in total basin runoff

Also used CRMM operations model.

Other results available, increased winter precipitation buffers reduction in runoff.

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6070

8090

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Temp Increase in C

Pre

cip

Cha

nge

in %

2C to 6 C

-40% to +30% Runoff changes in 2070-2099

~115%

~80%

CRB RunoffFromC&L

Precipitation, Temperatures and Runoff in 2070-2099

Triangle size proportional to runoff changes:

Up = IncreaseDown = Decrease

Green = 2010-2039Blue = 2040-2069Red = 2070-2099

Scale Matters Runoff Efficiency (How much Precip actually runs off) Varies Greatly

from ~5% (Dirty Devil) to > 40% (Upper Mainstem) You can’t model the basin at large scales and expect accurate results

GCMs (e.g. Milly, Seager) and H&E 2006 may get the right answer, but miss important topographical effects

14.4%

16.1%

24.9%

14.1%6.3%

9.9%

11.8%

2.4%

% of Total Runoff

Most runoff comes from small part of the basin > 9000 feet Very Little of the Runoff Comes from Below 9000’ (16% Runoff, 87% of Area) 84% of Total Runoff Comes from 13% of the Basin Area – all above 9000’

% Total Runoff

Basin Area

Runoff

Elevation % Total Runoff % Total Area "Productivity"9000-10,000 25% 6.3% 3.9

10,000-11,000 27% 4.3% 6.211,000-12000 22% 2.1% 10.412,000-13,000 11% 0.5% 20.4

Sums 9-13 84% 13.2%Below 9000 16% 87% 0.2

Future Flow Summary Future projections of Climate/Hydrology in the

basin based on current knowledge suggest Increase in temperature with less uncertainty Decrease in streamflow with large uncertainty Uncertain about the summer rainfall (which forms a

reasonable amount of flow) Unreliable on the sequence of wet/dry (which is key for

system risk/reliability)

The best information that can be used is the projected mean flow

Clearly, need to combine paleo + observed + projection to generate plausible flow scenarios

System Risk

•Streamflow Simulation•Prairie et al. (2008) WRR

• System Water Balance Model

•Management Alternatives(Reservoir Operation +

Demand Growth)

Rajagopalan et al. (2009), WRR

Lees Ferry Natural Flow (15.0)+

Intervening flows (0.8)-

Upper Basin Consumptive Use (4.5+)

Evaporation (varies with stage; 1.4 avg

declining to 1.1)

“Bank Storage is near long-term equilibrium’

LB Consumptive Use+ MX Delivery + losses (9.6)

Climate Change-20% LF flows over

50 years

Initial Net Inflow = +0.4

Water Balance Model: Our version

Water Balance Model

Storage in any year is computed as: Storage = Previous Storage + Inflow - ET- Demand •Upper and Lower Colorado Basin demand = 13.5 MAF/yr• Total Active Storage in the system 60 MAF reservoir• Initial storage of 30 MAF (i.e., current reservoir content)• Inflow values are natural flows at Lee’s Ferry, AZ + Intervening flows between Powell and Mead and below Mead• ET computed using Lake Area – Lake volume relationship and an average ET coefficient of 0.436•Transmission Losses ~6% of Releases

Flow and Demand Trendsapplied to the simulations

Red – demand trend13.5MAF – 14.1MAF

by 2030

Blue – mean flow trend15MAF – 12MAF

By 2057-0.06MAF/year

Under 20% - reduction

Alternative Demand Shortage Policy Initial Storage

A7.5 MaF to LB, 1.5 MaF to MX and UB deliveries per EIS depletion schedule

333 KaF DS when S < 36%, 417 KaF DS when S < 30% and 500 KaF DS when S <23%

30 MAF

B7.5 MaF to LB, 1.5 MaF to MX and UB deliveries per EIS depletion schedule

5% DS when S < 36%, 6% DS when S < 30% and 7% DS when S < 23%

30 MAF

C

7.5 MaF to LB, 1.5 MaF to MX and UB deliveries at a 50% rate of increase as compared to the EIS depletion schedule

5% DS when S < 36%, 6% DS when S < 30% and 7% DS when S < 23%

30 MAF

D

7.5 MaF to LB, 1.5 MaF to MX and UB deliveries at a 50% rate of increase as compared to the EIS depletion schedule

5% DS when S < 36%, 6% DS when S < 30% and 7% d DS when S < 23%

60 MAF*

E

7.5 MaF to LB, 1.5 MaF to MX and UB deliveries at a 50% rate of increase as compared to the EIS depletion schedule

5% DS when S < 50%, 6% DS when S < 40%, 7% d DS when S < 30% and 8 % DS when S < 20%

30 MAF

Management and Demand Growth Combinations

Table 1 Descriptions of alternatives considered in this study. (LB = Lower Basin, MX = Mexico, UB = Upper Basin, DS = Delivery Shortage and S = Storage). Per EIS depletion schedule the total deliveries are projected to be 13.9 MaF by 2026 and 14.4 MaF by 2057.* One alternative with full initial storage (E) illustrates the effects of a full system.

Natural Climate Variability

Climate Change – 20% reduction

Climate Change – 10% reduction

20% Reduction

10% ReductionShortage Volume Under Climate Change

Initial Demand – 12.7MaFActual Average Consumption

In the recent decade

Sensitivity to Initial Demand - 20% reduction

Initial Demand – 13.5MaF

Summary Water supply risk (i.e., risk of drying) is small (< 5%) in the near term ~2026, for any

climate variability (good news)

Risk increases dramatically by about 7 times in the three decades thereafter (bad news)

Risk increase is highly nonlinear

There is flexibility in the system that can be exploited to mitigate risk. Considered alternatives provide ideas

Smart operating policies and demand growth strategies need to be instilled Demand profiles are not rigid

Delayed action can be too little too late

Water supply risk occurs well before any ‘abrupt’ climate change – even under modest changes

Nonlinear response

What do we do?