evaluating forecasts in reservoir operations: the role of ... · power tunnel pelton to r5 r5 below...
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Department of Civil and Environmental Engineering
Rebecca Guihan
Dr. Austin Polebitski, Dr. Richard Palmer
February 26, 2014
Evaluating Forecasts in Reservoir Operations: The Role
of Reforecast Products in Examining Extremes
2 Department of Civil and Environmental Engineering
NOAA SARP
When should I
plant my corn?
Should I buy crop
insurance?
Will our
reservoir refill
completely
this year?
Should we initiate
flood stage
protocol or not?
I have a cool
climate model!
I have a cool
hydrology model!
3 Department of Civil and Environmental Engineering
NOAA SARP
When should I
plant my corn?
Should I buy crop
insurance?
Will our
reservoir refill
completely
this year?
Should we initiate
flood stage
protocol or not?
I have a cool
climate model!
I have a cool
hydrology model!
NOAA SARP
4 Department of Civil and Environmental Engineering
NOAA SARP
NOAA SARP
Federal,
State, Local
Agencies
End Users
Private/Consulting
Academia/University
5 Department of Civil and Environmental Engineering
Demonstrate the potential usefulness of climate forecasts and create an appropriate framework for their application
• Co-generate knowledge concerning system operations between researchers and water managers
• Generate ESP streamflow using reforecasts at partner locations
• Evaluate skill of GFS and CFSv2 and corresponding streamflow in the context of decision making
• Disseminate data, case studies, and recommendations to the broader water community
Project Goals
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Project Partners - Case Studies
Salt Lake City
Parley’s System:
Drinking Water, Flood Control
Snohomish County PUD
Jackson Hydropower System:
Multi-purpose
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Project Partners - Case Studies
PacifiCorps Bear Lake:
Irrigation Supply, Flood Control
Dallas Water Utilities System:
Drinking Water
8 Department of Civil and Environmental Engineering
Demonstrate the potential usefulness of climate forecasts and create an appropriate framework for their application
• Co-generate knowledge concerning system operations between researchers and water managers
• Generate ESP streamflow using reforecasts at partner locations
• Evaluate skill of GFS and CFSv2 and corresponding streamflow in the context of decision making
• Disseminate data, case studies, and recommendations to the broader water community
Project Goals
9 Department of Civil and Environmental Engineering
Workshop
Department of Civil and Environmental Engineering
Partner Hydropower Water Supply Environmental Flows
Dallas None
• Firm yield • Frequency of instituting
voluntary or mandatory restrictions
• Total revenues generated • Minimum storages in reservoirs
None
PacifiCorp Bear Lake
• Energy production lost relative to baseline
• Volume of water provided to irrigation
• Annual allocation of water • Accuracy of forecast of water to
be allocated • Irrigation supply lost
None
Salt Lake City
• None
• Appropriate storage level at the beginning of water supply season
• Balancing water sources and supplies
• Cannot divert into pipeline until >5 cfs at Lamb’s Diversion
SnoPUD
• Mega-watts hours produced per year,
• Total avoided costs from other purchases
• Annual energy value
• Water provided to Everett • Need to implement curtailments
• Number of times fish flows are unmet
• Minimizing peak releases that harm fish
• Provide “flushing flows” to move fish down stream
Department of Civil and Environmental Engineering
Partner Hourly/Daily Weekly Monthly
PacifiCorp Bear Lake
• None • Flood Control
Decisions
• Flood Control Decisions
• Irrigation Allocations
• Drought
Salt Lake City
• Flood Mitigation
• Flood Mitigation • Drinking Water
Deliveries • Flood Mitigation
SnoPUD
• Hydropower Generation
• Channel forming flows
• Drinking Water • Hydropower
Scheduling • Flood Control • Environmental Flows
• Refill/Drafting Rates
12 Department of Civil and Environmental Engineering
Demonstrate the potential usefulness of climate forecasts and create an appropriate framework for their application
• Co-generate knowledge concerning system operations between researchers and water managers
• Generate ESP streamflow using reforecasts at partner locations
• Evaluate skill of GFS and CFSv2 and corresponding streamflow in the context of decision making
• Disseminate data, case studies, and recommendations to the broader water community
Project Goals
13 Department of Civil and Environmental Engineering
Types of Streamflow Forecasts Used
• ESP – Ensemble Streamflow Prediction
• HEFS – Hydrologic Ensemble Forecast System
• CFS– Climate Forecast System
• GEFS – Global Ensemble Forecast System
14 Department of Civil and Environmental Engineering
Types of Streamflow Forecasts Used
• ESP – Ensemble Streamflow Prediction
• HEFS – Hydrologic Ensemble Forecast System
• CFS– Climate Forecast System
• GEFS – Global Ensemble Forecast System
Expectation:
Variability
decreases
15 Department of Civil and Environmental Engineering
Types of Streamflow Forecasts Used
• ESP – Ensemble Streamflow Prediction
• HEFS – Hydrologic Ensemble Forecast System
• CFS– Climate Forecast System
• GEFS – Global Ensemble Forecast System
Expectation:
Variability
decreases
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CFS Forecast vs. Observed Temperature (°C)
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CFS Correlations by Lead Day
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Snowpack as a Crude Forecasting Method: SLC
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Additional skill when using ESP forecast
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Additional skill when using HEFS forecast
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HEFS DELL
22 Department of Civil and Environmental Engineering
Means of ESP and HEFS (kaf)
23 Department of Civil and Environmental Engineering
Demonstrate the potential usefulness of climate forecasts and create an appropriate framework for their application
• Co-generate knowledge concerning system operations between researchers and water managers
• Generate ESP streamflow using reforecasts at partner locations
• Evaluate skill of GFS and CFSv2 and corresponding streamflow in the context of decision making
• Disseminate data, case studies, and recommendations to the broader water community
Project Goals
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Proof of Concept - Method
Do this for each week, for
52 weeks to determine
the benefit of 60 day
forecasts.
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Proof of Concept - Results
Use DSS to evaluate revenue gains in three hydrologically different years
Compare the use of forecast information against ‘perfect knowledge’
Annual Inflow
(AF)
Average Energy
Price
Standard Deviation
In Energy Prices
2001-2002 697,800 $25.93 $13.44
2002-2003 522,489 $31.07 $13.29
2003-2004 554,374 $39.49 $6.70
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Proof of Concept - Results
$0
$2,000,000
$4,000,000
$6,000,000
$8,000,000
$10,000,000
$12,000,000
$14,000,000
$16,000,000
$18,000,000
$20,000,000
6/8/2001 7/28/2001 9/16/2001 11/5/2001 12/25/2001 2/13/2002 4/4/2002 5/24/2002 7/13/2002 9/1/2002
Cumulative Avoided Cost From Hydropower Production (2001-2002)
Forecast x 2 PerfS_ForeE ForeS_PerfE Perfect x 2
Actual Avoided Cost Rule of Thumb Optimal
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Proof of Concept - Results
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Current Operations and Forecast Use
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Current Operations and Forecast Use
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Incorporating Forecasts
Simulation Model – Stella or R
• Simulates system operations
• Calculates how water is routed
through the system
Spada Lake
Jackson Powerhouse
Div ersion Dam
Lake Chaplain
Reach1
Power Tunnel
Pelton to R5
R5 below Powerhouse
Francis to Chaplain
Chaplain to DD
Q1
Reach 34
Reach5
Q2
Q5
Q1 Inflow
~
Release to R1
To Ev erett
Q5 Inflow ~
Q4 Inflow
~
Q3
Q2 Inflow
~
Q3 Inflow
~
Everett Demand
~
Empty Diversion Dam
SPILL
Q4
Chaplain Spill
FINAL Francis Release
DD demand FINAL
R5 Outflow
DD to Chaplain
Backup Supply
Pelton Release FINAL
Power Tunnel FINAL
MODEL!!!
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Incorporating ESP Forecasts: Parley’s System
• Operated by Salt Lake City
• Releases to supply drinking
water
• Releases for flood
management
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Incorporating Forecasts: Salt Lake City
For today’s example:
1. ESP traces used as inflow to
the model
2. Static Rule Curve based on the
median historic storage determines
how releases are made
Reservoir
Storage Inflows Releases
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Potential Benefits of Using Forecast
Critical Period Concern Value
Low inflow or low pool elevation
Not providing enough water
How much releases should be reduced
High inflows or high pool elevation
Spilling, flooding Chance of spilling, potential peak inflows
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ESP DELL
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Example of Results: High Flow Year
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ESP Streamflow – High Inflow Year
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ESP Streamflow – Low Inflow Year
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January ESP – Operational Output (af)
Co
mb
ined S
tora
ge
R
ele
ases
Wate
r R
ele
ases
Jan 1
Jan 1
Jan 1
Dec 31
Dec 31
Dec 31
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April ESP - Operational Output (af)
Co
mb
ined S
tora
ge
R
ele
ases
Wate
r R
ele
ases
Apr 1
Apr 1
Apr 1
Mar 31
Mar 31
Mar 31
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January ESP - Operational Output (af)
Co
mb
ined S
tora
ge
R
ele
ases
Wate
r R
ele
ases
Jan 1
Jan 1
Jan 1
Dec 31
Dec 31
Dec 31
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April ESP - Operational Output (af)
Co
mb
ined S
tora
ge
R
ele
ases
Wate
r R
ele
ases
Apr 1
Apr 1
Apr 1
Mar 31
Mar 31
Mar 31
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Iterative Process Getting New Tech Into Ops
We’re Research
Hydrologists!
Our new
models are
awesome, let’s
use them!
How come you
are not using X at
an X frequency?
Floods are our
priority We’re Operational
Hydrologists!
43 Department of Civil and Environmental Engineering
Iterative Process Getting New Tech Into Ops
We’re Research
Hydrologists!
Our new
models are
awesome, let’s
use them!
How come you
are not using X at
an X frequency?
We’re Operational
Hydrologists!
NOAA SARP
Floods are our
priority
44 Department of Civil and Environmental Engineering
Final Thoughts and Future Work
ESP and HEFS/CFSv2 traces applied in operational framework will provide benefits,
• we are finishing evaluating at what scales and for what decisions, final evaluations completed by September
Generating hindcast data for evaluating system in existing framework is iterative process
• generating data, processing through system, trouble shooting…
Matching End User needs (update frequency, forecast length, etc.) must be priority in beginning of process
45 Department of Civil and Environmental Engineering
Acknowledgements
• NOAA SARP – Nancy Beller-Simms
• Advisors: Dr. Austin Polebitski,
Dr. Richard Palmer
• CBRFC: Kevin Werner, Ashley Nielson
• Dr. Andy Wood
• Case Study Partners: Bruce Meaker,
Connely Baldwin, Jeff Niermeyer,
Tracie Kirkham, Denis Qualls
46 Department of Civil and Environmental Engineering
Thank You!
Questions?
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Project Goals
• Analyze the quality of climate forecast products,
• Work with study partners to develop ways to use
products in reservoir operations.
Water
Managers Researchers
Forecasters
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Future Work
• Quantitatively compare the results against perfect
forecast information
• Is this a useful seasonal prediction tool?
• Does including the GEFS forecast improve the
regular ESP forecast?
• What benefits do CFS model provide?
CONCLUSION: Preliminary analysis of these data suggest
that climatological skill between the ESP and CFS are similar.
More work is needed as the data are still very new.
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Example of Results: High Flow Year
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Example of Results: High Flow Year
*9/30 expected
releases would
exceed 1500 cfs
for an average of
19 days
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ESP LAMB
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HEFS LAMB
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ESP DELL
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Example of Results: High Flow Year
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Example of Results: High Flow Year
Max Storage
Min Storage
Target Range
Critical Flood Threshold
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Example of Results: Low Flow Year
57 Department of Civil and Environmental Engineering
Example of Results: High Flow Year
Max Storage
Min Storage
Target Range
Critical Flood Threshold