balaji rajagopalan department of civil, environmental and architectural engineering and
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The Once and Future Pulse of Colorado River Flow Mitigating Water Supply Risk Under Changing Climate. Balaji Rajagopalan Department of Civil, Environmental and Architectural Engineering And Cooperative Institute for Research in Environmental Sciences (CIRES) University of Colorado - PowerPoint PPT PresentationTRANSCRIPT
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
0
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4
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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
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.
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
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?