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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
Boulder, CO
23 February, 2010
Presentation to Michael Kinter-Meyer
Energy and Environment Directorate
Pacific 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
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7 States, 2 Nations
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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
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Source:Reclamation
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1 acre-foot = 325,000 gals, 1 maf = 325 * 109 gals
1 maf = 1.23 km3 = 1.23*109 m3
Upper Basin: CO, UT, WY, NM
Lower Basin: AZ, CA, NV
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
UC CRSS stream
gauges
LC CRSS stream gauges
Colorado River Demand - Supply
20
Total Colorado River Use 9-year moving average.
18
NF Lees Ferry 9-year moving average
16
12
10
8
6
4
2
Calnder Year
19
98
20
02
20
06
19
94
19
90
19
86
19
82
19
78
19
74
19
70
19
66
19
62
19
58
19
54
19
50
19
46
19
42
19
38
19
34
19
30
19
26
19
18
19
22
0
19
14
Annual Flow (MAF)
14
Recent conditions in the
Colorado River Basin
Paleo Context

Below normal flows into
Lake Powell 2000-2004
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62%, 59%, 25%, 51%, 51%,
respectively
 2002 at 25% lowest
inflow recorded since
completion of Glen
Canyon Dam
Colorado River at Lees Ferry, AZ
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Some relief in 2005
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105% of normal inflows
Not in 2006 !
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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
Hatching Indicates
Areas of Strong
Model Agreement
Summer
Study
Climate
Change
Technique
(Scenario/GC
M)
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- TemperaturePrecipitation 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,
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 subbasins 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.
-10% Precip only =
-11% runoff.
Green = 2010-2039
Blue = 2040-2069
Red = 2070-2099
120
110
100
90
80
-40% to
+30%
Runoff
changes in
2070-2099
~80%
70
Up
= Increase
Down = Decrease
2C to 6 C
60
Triangle size
proportional to
runoff changes:
~115%
Precip Change in %
CRB
Runoff
From
C&L
Precipitation, Temperatures and Runoff in 2070-2099
0
1
2
3
Temp Increase in C
4
5
6
Scale Matters
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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
% of Total
Runoff
14.4%
16.1%
9.9%
2.4%
24.9%
6.3% 14.1%
11.8%
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Most runoff comes from small part of the basin > 9000 feet
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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’
Basin Area and Runoff By Elevation
20%
Elevation
% Total Runoff
9000-10,000
25%
10,000-11,000
27%
11,000-12000
22% %
12,000-13,000
11%
Sums 9-13
84%
Below 9000
16%
18%
16%
14%
12%
% Total Area "Productivity"
6.3%
3.9
4.3%
6.2
10.4
Total2.1%Runoff
0.5%
20.4
13.2%
87%
0.2
Runoff
10%
8%
Basin Area
6%
4%
2%
0%
0
2000
4000
6000
Runoff as % of Total
8000
10000
Area as % of Upper Basin Total
12000
14000
Future Flow Summary
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Future projections of Climate/Hydrology in the basin
based on current knowledge suggest
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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
Water Balance Model: Our version
Climate Change
-20% LF flows over
50 years
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)
LB Consumptive Use
+ MX Delivery + losses (9.6)
“Bank Storage is near
long-term equilibrium’
Initial Net Inflow = +0.4
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 Trends
applied to the simulations
Red – demand trend
13.5MAF – 14.1MAF
by 2030
Blue – mean flow trend
15MAF – 12MAF
By 2057
-0.06MAF/year
Under 20% - reduction
Management and Demand Growth Combinations
Alternative
Demand
Shortage Policy
Initial
Storage
A
7.5 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
B
7.5 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%
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%
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
60
MAF*
30 MAF
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
Shortage Volume Under Climate Change
10% Reduction
20% Reduction
Sensitivity to Initial Demand - 20% reduction
Initial Demand – 13.5MaF
Initial Demand – 12.7MaF
Actual Average Consumption
In the recent decade
Summary
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Water supply risk (i.e., risk of drying) is small (< 5%) in the near term ~2026, for
any climate variability (good news)
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Risk increases dramatically by about 7 times in the three decades thereafter
(bad news)
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Risk increase is highly nonlinear
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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
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Nonlinear response
What do we do?