Colorado River Water Availability Assessment Under Climate Variability Annie Yarberry 1, Balaji...
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![Page 1: Colorado River Water Availability Assessment Under Climate Variability Annie Yarberry 1, Balaji Rajagopalan 2,3 and James Prairie 4 1. Humboldt State University,](https://reader030.fdocuments.us/reader030/viewer/2022012922/56649d7d5503460f94a60289/html5/thumbnails/1.jpg)
Colorado River Water Availability Assessment Under Climate Variability
Annie Yarberry1, Balaji Rajagopalan2,3 and James Prairie4
1. Humboldt State University, Arcata, CA2. University of Colorado, Boulder, CO
3. CIRES, University of Colorado, Boulder, CO4. USBR, University of Colorado, Boulder, CO
AGU Fall 2010
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Background• 60 MAF reservoir storage
• 4 times annual flow• 50 MAF in Lake Powell and Mead
• Increasing Demand• Decreasing Streamflows• Compacts/agreements made in the
wettest part of early 20th century • Under stress in recent decades
• Water supply risk and sustainability
19141919
19241929
19341939
19441949
19541959
19641969
19741979
19841989
19941999
20040
2000000
4000000
6000000
8000000
10000000
12000000
14000000
16000000
18000000
20000000
Total Colorado River Use 9-year moving average.
NF Lees Ferry 9-year moving average
Calendar Year
Annu
al F
low
(MAF
)
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Background…
2000 ~ 2008•Declining lakes Mead and Powell •5 years of 10 maf/yr•66% of average flows•Worst drought in historic record•How bad can it go??••Climate change portends 0 ~ 25% reduction in the coming 4-5 decades
0
5000000
10000000
15000000
20000000
25000000
30000000
Year
Volu
me
(MAF
)
120 Foot drop13 maf lostCurrent: ~48%, 12 maf
Lake Mead Volume in Millions of Acre-Feet 1935-2008
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Climate Change – Back to the Future?
• Long dry epochs are very common• 20th century unusually wet• Climate change studies indicate a
consensus of • 0 ~ 30% decline in mean flows in 4-5
decades
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Climate Change – Water supply Risk• What is the risk to water supply under climate change – can
management mitigate? (Rajagopalan et al., 2009) • Basin-wide simple water balance model
• Entire storage as a ‘bath tub’• Stochastic streamflow ensembles from
observed+paleo+climate change projections (Prairie et al., 2008)
• 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 approximately 7 times in
the three decades thereafter (bad news)• Smart operating policies and demand growth strategies
need to be instilled
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This Study – Research Question
• What is the probability distribution of optimal “yield” from the given storage capacity in the basin and ensemble of streamflow sequences?• Can be a complementary tool for stakeholders to make
risk-based planning and development decisions.
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Methodology – Constrained Optimization(Linear)Y = Yield (MAF)Spillt= Overflow (MAF)Qt = Paleo-reconstructed inflow (MAF/yr)K = Reservoir capacity (MAF)St-1 = Previous year storage (MAF)St = Current storage (MAF)
Minimum Storage is specifiedSystem storage = 60MAF•Average storage is computed for the optimal yield Yopt, as the average of:
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Methodology…• 10,000 50-year ensembles of streamflow sequences
each generated using observed and paleo flows (Prairie et al., 2008) – Natural Variability• 10 and 20 percent linear flow reductions applied to
incorporate climate change projections (Rajagopalan et al., 2009) – Climate Change Projections• For each ensemble:
• optimal yield• average storage• standard deviation of storage
• For the three scenarios - natural variability, 10, and 20% flow reductions – we explored five reservoir conditions• Initially full• Minimum storage at:• Zero MAF; and 15%, 30%, and 40% of capacity
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ResultsDensity
12 14 16 18 20
0.0
0.1
0.2
0.3
0.4
Density
10 20 30 40 50
0.000.010.020.030.040.05
Density
5 10 15 20 25
0.00
0.02
0.04
0.06
0.08
0.10
Natural Variability – Minimum Storage of Zero
Optimal Yield (MAF/yr)
Average Storage (MAF)
Storage Standard Deviation (MAF)
Density
12 14 16 18 20
0.0
0.1
0.2
0.3
0.4
Density
10 20 30 40 50
0.00
0.01
0.02
0.03
0.04
Density
5 10 15 20
0.00
0.02
0.04
0.06
0.08
0.10
20% Streamflow Reduction – Minimum Storage of Zero
16 35 17
173516
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Results
12 14 16 18 20
0.0
0.1
0.2
0.3
0.4
0.5
0.6
10 20 30 40 50
0.00
0.02
0.04
0.06
0.08
5 10 15 20 25
0.00
0.05
0.10
0.15
All Scenarios – Minimum Storage at Zero
Optimal Yield (MAF/yr)
Average Storage (MAF)
Storage Standard Deviation (MAF)
Natural Variability10% Flow Reduction20% Flow Reduction
16 35 17
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Results..Density
10 12 14 16 18
0.000.050.100.150.200.250.30
Density
35 40 45 50 550.00
0.02
0.04
0.06
Density
4 6 8 10 12 14
0.00
0.05
0.10
0.15
0.20
Natural Variability - Minimum Storage at 40% Capacity
Optimal Yield (MAF/yr)
Average Storage (MAF)
Storage Standard Deviation (MAF)
Density
10 12 14 16 18
0.0
0.1
0.2
0.3
Density
35 40 45 50 55
0.00
0.02
0.04
0.06
0.08
Density
4 6 8 10 12 14
0.00
0.05
0.10
0.15
0.20
0.25
20% Streamflow Reduction - Minimum Storage at 40% Capacity
16
16
35
35
17
17
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Results..
10 12 14 16 18
0.0
0.1
0.2
0.3
0.4
30 35 40 45 50 55
0.00
0.02
0.04
0.06
0.08
0.10
4 6 8 10 12 14
0.0
0.1
0.2
0.3
All Scenarios - Minimum Storage at 40% Capacity
Optimal Yield (MAF/yr)
Average Storage (MAF)
Storage Standard Deviation (MAF)
Natural Variability10% Flow Reduction20% Flow Reduction
16 35
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Results..
ConditionYield (MAF/yr)
12.7 13.5 14.4 16Reliability (%)
Minimum storage of zeroNatural Variability 99 99 97 6320% flow reduction 99 94 70 9
Minimum storage at 40% capacityNatural Variability 92 83 65 1920% flow reduction 82 57 25 1
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Results..
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Summary and Conclusion
• A simple system-wide water balance model to assess ‘Optimal Yield’ for a given storage and streamflow sequence was developed for the Colorado River Basin• Natural variability, 10% and 20% reduction in mean
flows due to climate change were considered• Reliability of current consumption ~ 12.7MaF • ~99% when the system is let to go dry for any
flow scenario• Drops to ~82% when minimum storage is set to
24MaF and for 20% reduction due to climate change scenario
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Summary and Conclusion
• Reliability of planned demand of ~ 13.5MaF Drops to ~57% when minimum storage is set to 24MaF and for 20% reduction due to climate change scenario
• Higher demands have progressively less reliability
• The PDFs of ‘optimal yields’ provide stakeholders with estimates of risks for various scenarios
• If specific sub-system ‘yields’ and their risks are desired – full system model (e.g., CRSS) needs to be run
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Acknowledgements
• NSF-REU Program at University of Colorado at Boulder, Summer, 2010
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Thank You!
Questions?
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References
Rajagopalan, B., K. Nowak, J. Prairie, M. Hoerling, B. Harding, J. Barsugli, A. Ray and B. Udall; Water supply risk on the Colorado River: Can management mitigate?, Water Resources Research, 45, W08201, 2009.
Christensen, N., A. Wood, N. Voisin, D. Lettenmaier, and R. Palmer; The effects of climate change on the hydrology and water resources of the colorado river basin, Climatic Change, 62, (1-3), 337-63.
U.S. Department of Interior, U.S. Bureau of Reclamation; Colorado River interim guidelines for lower basin shortages and the coordinated operations for lake powell and lake mead, Final EIS, 2007.
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Climate Change Studies
Early Studies – Scenarios, About 1980Stockton and Boggess, 1979 Revelle and Waggoner, 1983*
Mid Studies, First Global Climate Model Use, 1990sNash and Gleick, 1991, 1993McCabe and Wolock, 1999 (NAST)IPCC, 2001
More Recent Studies, Since 2004Milly et al.,2005, “Global Patterns of trends in runoff”Christensen and Lettenmaier, 2004, 2006Hoerling 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