climate, growth and drought threat to colorado river water supply
DESCRIPTION
Climate, Growth and Drought Threat to Colorado River Water Supply. Balaji Rajagopalan Department of Civil, Environmental and Architectural Engineering And Cooperative Institute for Research in Environmental Sciences (CIRES) University of Colorado Boulder, CO Presentation to KOWACO - PowerPoint PPT PresentationTRANSCRIPT
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/
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?
0
2
4
6
8
10
12
14
16
18
20
1914
1918
1922
1926
1930
1934
1938
1942
1946
1950
1954
1958
1962
1966
1970
1974
1978
1982
1986
1990
1994
1998
2002
2006
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)