Climate, Growth and Drought Threat to Colorado River Water Supply

Climate, Growth and Drought Threat to Colorado River Water

Supply

Balaji Rajagopalan Department of Civil, Environmental and Architectural

EngineeringAnd

Cooperative Institute for Research in Environmental Sciences

(CIRES)

University of ColoradoBoulder, CO

Presentation to KOWACO February 3, 2009

Collaborators

Kenneth Nowak - CEAE / CADSWES Edith Zagona - CADSWES James Prairie - USBR, Boulder

Ben Harding - AMEC, Boulder

Marty Hoerling - NOAA Joe Barsugli - CIRES/WWA/NOAA Brad Udall - CIRES/WWA/NOAA Andrea Ray - NOAA

A Water Resources Management Perspective

Time

Horizon

Inter-decadal

Hours Weather

ClimateDecision Analysis: Risk + Values

Data: Historical, Paleo, Scale, Models

• Facility Planning

– Reservoir, Treatment Plant Size

• Policy + Regulatory Framework

– Flood Frequency, Water Rights, 7Q10 flow

• Operational Analysis

– Reservoir Operation, Flood/Drought Preparation

• Emergency Management

– Flood Warning, Drought Response

What Drives Year to Year Variability in regional

Hydrology?(Floods, Droughts etc.)

Hydroclimate Predictions – Scenario Generation

(Nonlinear Time Series Tools, Watershed Modeling)

Decision Support System(Evaluate decision

strategiesUnder uncertainty)

Modeling Framework

Forecast

Diagnosis

Application

Resources

• http://cadswes.colorado.edu/publications

(PhD thesis) Regonda, 2006

Prairie, 2006Grantz, 2006

Stochastic Streamflow Simulation• http://animas.colorado.edu/~prairie/• http://animas.colorado.edu/~nowakkc/

•[email protected]•[email protected]

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

When Will Lake Mead Go Dry?Barnett & Pierce, Water Resources Research,

2008 Water Budget Analysis

One 50 maf reservoir, increasing UB demands (13.5 in 2008 ->14.1 Maf/yr in 2030, 15.1 maf /yr inflows, current starting contents

Linear Climate Change Reduction in Flows w/ some natural variability

Results With Linear 20% Reduction in mean flows Over 50 years

10% Chance Live Storage Gone by 2013

50% Chance Live Storage Gone by 2021

50% Chance Loss of Power by 2017

Is that so?

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2002

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Calnder Year

Ann

ual Flo

w (

MA

F)

Total Colorado River Use 9-year moving average.

NF Lees Ferry 9-year moving average

Colorado River Demand - Supply

Declining Lakes Mead and Powell

75 Foot Drop (Max 140)10.5 maf lost Current: ~56%, 14.5 maf

120 Foot drop13 maf lostCurrent: ~48%, 12 maf

5 Years of 10 maf/yr66% of average flowsWorst drought in historic record

New York Times Sunday Magazine, October 21, 2007

Dropping Lake Mead

~1999

~2004

Lake Powell – June 29, 2002

Lake Powell – December 23, 2003

Lake Mead’s Delta Circa 1999

Source: USGS, Reclamation

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

observed record

Woodhouse et al. 2006

Stockton and Jacoby, 1976

Hirschboeck and Meko, 2005

Hildalgo et al. 2002

Past Flow Summary

Paleo reconstructions indicate 20th century one of the most wettest Long dry spells are not uncommon 20-25% changes in the mean flow Significant interannual/interdecadal variability Rich variety of wet/dry spell sequences

All the reconstructions agree greatly on the ‘state’ (wet or dry) information

How will the future differ?

More important, What is the water supply risk under changing climate?

Future Climate

The Fundamental Problem with Climate Change For Water Management

All water resource planning based on the idea of “climate stationarity” – climate of the future will look like the climate of the past.

Reservoir sizing Flood Control Curves System Yields Water Demands Urban Runoff Amounts

This will be less and less true as we move forward.

Existing Yields now not as certain given both supply and demand changes

New water projects have an additional and new element of uncertainty.

Stuff and m

Science, February 1, 2008

IPCC 2007 AR4 Projections Wet get wetter and dry get drier… Southwest Likely to get drier

Models Precip and Temp Biases

Models show consistent errors (biases)

Western North America is too cold and too wet

Weather models show biases, too

Can be corrected

A Large Number of Studies Point to a Drying American Southwest

Milly et al., 2005 Seager et a.l, 2007 IPCC WG1, IPCC WG2, 2007 National Academy Study, 2007 IPCC Water Report, 2008 CCSP SAP 4.3, 2008

“From 2040 to 2060, anticipated water flows from rainfall in much of the West are likely to approach a 20 percent decrease in the average from 1901 to 1970, and are likely to be much lower in places like the fast-growing Southwest.” ~ May 28, 2008, New York Times

Temperature Precipitation

General CirculationMo

del

Hypothetical Scenarios

Regression

Hydrology Models:NWSRFS

VICPRMS

CRSSCRMM

Reservoir storage Hydroelectric power

UB Releases

1.Climate Change

Data Source

2.Flow Generation

Technique

3.Water Supply

Operations Model

OR

Progression of Data and Models in studies about the influence of climate change on streamflows in the Colorado River Basin

Streamflow

Stuff and m

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.

0 1 2 3 4 5 6

6070

8090

100

110

120

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

Colorado River Climate Change Studies over the Years

Early Studies – Scenarios, About 1980 Stockton and Boggess, 1979 Revelle and Waggoner, 1983*

Mid Studies, First Global Climate Model Use, 1990s Nash and Gleick, 1991, 1993 McCabe and Wolock, 1999 (NAST) IPCC, 2001

More Recent Studies, Since 2004 Milly et al.,2005, “Global Patterns of trends in runoff” Christensen and Lettenmaier, 2004, 2006 Hoerling and Eischeid, 2006, “Past Peak Water?” Seager et al, 2007, “Imminent Transition to more arid climate

state..” IPCC, 2007 (Regional Assessments) Barnett and Pierce, 2008, “When will Lake Mead Go Dry?”

National Research Council Colorado River Report, 2007

•Almost all the water is generated from a small region of the basin at veryhigh altitude

•GCM projections for the high altitude regions are uncertain

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

Streamflow ScenariosConditioned on climate change

projections

Water Supply System Risk Estimation

Water Supply ModelManagement + Demand

growth alternatives

System Risk EstimatesFor each year

Streamflow Simulation

•Paleo•Observations

•Need to Combine

•Colorado River System has enormous storage of approx 60MAF ~ 4 times the average annual flow - consequently,

• wet and dry sequences are crucial for system risk/reliability assessment

•Streamflow generation tool that can generate flow scenarios in the basin that are realistic in

•wet and dry spell sequences•Magnitude

•Paleo reconstructions arePaleo reconstructions are•Good at providing ‘state’ (wet or dry) informationGood at providing ‘state’ (wet or dry) information•Poor with the magnitude informationPoor with the magnitude information

•Observations are reliable with the magnitudeObservations are reliable with the magnitude

•Need for combining all the available information

Observed Annual average flow (15MAF) is used to define Observed Annual average flow (15MAF) is used to define wet/dry state.wet/dry state.

Need to Combine Paleo andObserved flows for stochastic simulation

Generate flow conditionally(K-NN resampling of historical flow)

),,( 11 tttt xSSxf

Generate system state )( tS

Nonhomogeneous Markov Chain Model on the observed

& Paleo data

Proposed Framework Prairie et al. (2008, WRR)

Superimpose Climate Change trend (10% and 20%)

10000 SimulationsEach 50-year long

2008-2057

NaturalClimate

Variability

ClimateChange

h

window = 2h +1Discrete kernel

function1for)1(

)41(

3)( 2

2

xx

h

hxK

Source: Rajagopalan et al., 1996

Nonhomogenous Markov model with Kernel smoothing (Rajagopalan et al., 1996)

Transition Probability (TP) for each year are obtained using a discrete Kernel Estimator

h determined with LSCV

2 state, lag 1 model was chosen ‘wet (1)’ if flow above annual median of observed

record; ‘dry (0)’ otherwise. AIC used for order selection (order 1 chosen)

nd

i dw

d

ndw

i dw

dw

dw

h

ttK

h

ttK

tPi

i

1

1)(

)(1)( tPtP dwdd

n

iit tP

nh

i1

2)](ˆ1[1

)(LSCV

Transition Probabilities

•Re-sample a block of years (as desired for planning – say 50 year)

•Using the TP for each year generate a ‘state’ (St)

•Conditionally Re-sample a streamflow magnitude from the observed flow

•Identify K-nearest neighbors from the observations to the

‘feature vector’ (St , St-1 and xt )

•Re-sample one of the neighbor – i.e., one of the years, say year j

•Flow of year j+1 is the simulated flow, Xt+1

Simulation

Generate flow conditionally(K-NN resampling of historical flow)

),,( 11 tttt xSSxf

Threshold

(e.g., median)

Drought Length

Surplus Length

time

Drought Deficit

Drought and Surplus Statistics

Surplus volumeflo

w

Drought/Surplus StatisticsPaleo + Obs K-NN-1 bootstrap

Of observed flow

Red Paleo statBlue Observed stat

Storage Statistics

60

System Risk

•Streamflow Simulation

• System Water Balance Model

•Management Alternatives(Reservoir Operation +

Demand Growth)

UC CRSS stream gauges

LC CRSS stream gauges

Lees Ferry, AZ gauge Demarcates Upper and

Lower Basin 90% of the entire

basin flow passes through this gauge

Well maintained gauge Annual Average flow

is about 15MaF

Sizeable flow occurs between Lake Powell and Mead ~ 750KaF/year

Small but useful flow below Mead also comes in to the system ~ 250KaF/year

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

Combined Area-volume RelationshipET Calculation

ET coefficients/month (Max and Min)0.5 and 0.16 at Powell0.85 and 0.33 at MeadAverage ET coefficient : 0.436

ET = Area * Average coefficient * 12

0

0.5

1

1.5

2

0 10 20 30 40 50 60 70

Storage (MaF)

ET

(M

aF

)

Management and Demand Growth Combinations

A. The interim EIS operational policies employed with demand growing based on the upper basin depletion schedule.

B with the demand fixed at the 2008 level ~ 13.5MaFC. Same as A but with larger delivery shortagesD. Same as C but with a 50% reduced upper basin depletion

schedule.E. Same as A with full initial storage.F. Same as A but post 2026 policy that establishes new

shortage action thresholds and volumes. G. Demand fixed at 2008 level and post 2026 new shortage

action.

All the reservoir operation policies take effect from 2026

INTERIM EIS INTERIM PLUS NEW THRESHOLD

Res. Storage

(%)

Shortage (kaf)

Res. Storage

(%)

Shortage (% of

current demand)

Res. Storage

(%)

Shortage (% of

current demand)

36 333 36 5 50 5

30 417 30 6 40 6

23 500 23 7 30 7

20 8

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

Flow trend with sample simulation

37.2% of simulations > 15MAF22.3% of simulations > 17MAF

34.7% of simulations > 15MAF18.8% of simulations > 17MAF

PDF of generated streamflows (boxplots)PDF of observed flow (red)

AR-1 NHMM

Natural Climate Variability

Climate Change – 20% reduction

Climate Change – 10% reduction

When Will Lake Mead Go Dry?Water Resources Research, 2008

Water Budget Analysis One 50 maf reservoir, increasing UB demands (13.5 in 2008 ->14.1

maf/yr in 2030, 15.1 maf /yr inflows, current starting contents Linear Climate Change Reduction in Flows w/ some natural variability

Results With Linear 20% Reduction in mean flows Over 50 years 10% Chance Live Storage Gone by 2013 50% Chance Live Storage Gone by 2021 50% Chance Loss of Power by 2017

Problems 1.7 maf/year fixed evaporation plus bank storage Missing 850 kaf/yr inflows

Forgotten / Ignored Issues System is on a knife-edge, even with existing flows Normal climate variability can push us over the edge without climate

change

Probability of at least one drying – Barnett and Pierce (2008)

Yellow – AR-1(Barnett and Pierce,

2008)Red – Scenario I

Green – Scenario IIBlue – Scenario II

Probability of drying in a given year

Shortage Volume (MaF)

Shortage Frequency

Climate Change – 20% reductionShortage Statistics

Shortage Volume (MaF)

Shortage Frequency

Climate Change – 10% reductionShortage Statistics

Initial Demand – 12.7MaFActual Average Consumption

In the recent decade

Sensitivity to Initial DemandClimate Change – 20% reduction

Initial Demand – 13.5MaF

Initial Demand – 12.7MaFActual Average Consumption

In the recent decade

Sensitivity to Initial DemandClimate Change – 10% reduction

Initial Demand – 13.5MaF

Shortage Volume (MaF)

Shortage Frequency

Climate Change – 20% reductionShortage Statistics

Initial Demand ~12.7MaF

Sensitivity to Initial Demand Climate Change – 20% reductionShortage Volume

Initial Demand ~13.5MaF

Summary

Interim Guidelines (EIS) are pretty robust Until 20206 these guidelines are as good as any in reducing risk

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

Risk of various subsystems need to be assessed via the basin wide decision model (CRSS)