Download Optimized Flood Control in the Columbia River Basin for a Global

Optimized Flood Control in the Columbia River Basin for a Global Warming Scenario
Se-Yeun Lee1, Alan F. Hamlet 1,2, Carolyn J. Fitzgerald3, Stephen J. Burges1
1. Dept. of Civil and Env. Engineering, UW, 2. CSES Climate Impacts Group, UW, 3. U.S. Army Corps of Engineers, Seattle District
Calibration Results
In comparison to current flood control curves for 20th century climate (20th_
Scen_CurFC), HEC-PRM derived flood control curves for 20th century climate
(20th_Scen_HecFC) show lower storage deficits for major dams in Columbia
River Basin and lower flood risks at flood check points: Bonners Ferry,
Columbia Falls and The Dalles
1,000
b)
20th Cent_Cur FC
a)
3000
Current Climate
Sep
Sep
Arrow
Grand
Coulee
Hungry
Horse
Libby
40
30
20
10
20th_Cent_CurFC
20th_Cent_HecFC
-1
0
1
2
3
4
Storage (KAF)
1,000
1,000
Two penalty functions in the
optimization model are calibrated
for the 20th century flow regime
using the procedure outlined in right
figure. The objective function is
then held fixed and optimized flood
control curves for a climate change
scenario are created.
Nov
Dec
Jan
20th_Cent_CurFC
20th_Cent_HecFC
-1
0
1
2
3
4
1,000
500
0
Oct
Nov
Dec
Jan
Feb
Mar
Apr
May
Jun
Jul
1200
Aug
Sep
Month
20th Century
500
200
20th_Cent_CurFC
20th_Cent_HecFC
-1
0
1
2
3
4
5
Extreme Value Type I Distribution Reduced Variate, Y
0
Dec
Jan
Feb
Mar
Apr
Month
May
Jun
Jul
Aug
Dec
Jan
Feb
Mar
Apr
May
Jun
Jul
Sep
b) Climate Change Scenario
7,000
Apr
6,000
6,000
5,000
5,000
Apr
4,000
3,000
3,000
2,000
2,000
1,000
1,000
0
0
Nov
Dec
Jan
Feb
Mar
Apr
May
Jun
Jul
Oct
Nov
Dec
Jan
Feb
Mar
Apr
May
Jun
Jul
Months
Simulation Results
3500
3000
2500
2000
1500
1000
500
0
0
500
1000
1500
2000
2500
3000
HH Apr-Jul Flow volume (KAF)
Hungry Horse Apr-Jul Flow Volume >2.0 MAF
4,000
3500
Below figures show a) Simulated Storage Deficits for major dams in Columbia
River Basin and Flood Frequency Curves at b) Bonners Ferry, c) Columbia Falls
and d) The Dalles for simulated 20th century climate using current flood control
curves (20th_Cent_CurFC) and the climate change scenario climate using
current flood control curves (CC_Secn_CurFC) and HEC-PRM derived flood
control curves (CC_Scen_HecFC).
3,000
a)
1,000
0
Oct Nov Dec Jan Feb Mar Apr May Jun Jul
Months
c)
July 31 Average Storage Deficit (KAF)
2,000
b)
2,000
20th Cent_Cur FC
CC_Scen_CurFC
1,500
CC_Scen_HecFC
1,000
500
60
50
40
30
20th_Cent_CurFC
CC_Scen_CurFC
20
CC_Scen_HecFC
10
0
Mica
Arrow
Grand
Coulee
Hungry
Horse
-2
Libby
d)
40
30
20
20th_Cent_CurFC
10
-1
0
1
2
3
4
5
Extreme Value Type I Distribution Reduced Variate, Y
50
Flow at Columbia Falls (kcfs)
Maximum Flood Space (KAF)
4,000
Months
The flow volumes differ markedly
at the two sites.
Nov
Nov
300
-2
5
400
Oct
Oct
Jul
Months
7,000
400
Climate Change Scenario
800
Jun
a) 20th Century Climate
The Dalles
Left figures show average reservoir inflows to
Dworshak and Libby dams corresponding to the
historical record and the climate change scenario.
Peak flows under the climate change scenario are
reduced and occur earlier in the
Dworshak
spring in comparison with the
20th century climate.
Climate Change Scenario
May
Libby storage (Libby Apr-Aug flow volume >5.5 MAF)
A simple climate change scenario was developed using
VIC model (See right figure) to test the effectiveness of
the approach for developing new flood rule curves that
are appropriate for altered streamflow timing.
The climate change scenario was created by removing
the historic monthly temperature trends from the daily
time step forcing data and then increasing temperature
to approximately 2° C. The precipitation in each year is
assumed to be identical to the unperturbed historical
meteorological forcing data. These altered streamflows
are then used to drive the reservoir optimization and
simulation models.
1,500
Apr
600
To develop continuous flood control curves, the
maximum flood space for each water year is
determined using the optimization model results.
This is then expressed as a non linear function of
seasonal flow volume occurring in each water year
(see right upper figure). The overall seasonal
shape of the rule curve and the typical refill timing
at each project was established from the optimized
results (with a monthly time resolution) by
examining the 50th percentile value, and the
nearest end of month date for the initiation of refill
was used in the simulations (see right lower figure).
This seasonal shape was then scaled to produce
the maximum flood space required for each flow
condition.
20th Century
Mar
5
Creating New Flood Control Curves
2,000
Feb
Months
Oct
2,500
2,000
1,500
Oct
100
Extreme Value Type I Distribution Reduced Variate, Y
Libby
2,500
1,500
Extreme Value Type I Distribution Reduced Variate, Y
d)
Inflow (KAF)
Decrease flood
penalties or increase
storage penalties
2,000
20
-2
Columbia Falls
-2
Inflow (KAF)
The U.S. Army Corps of Engineers Hydrologic Engineering Center’s
Prescriptive Model (HEC-PRM) is used as an existing monthly time step
optimization model for the Columbia basin. Of all penalties representing all
purpose of the Columbia River Basin, only flood
Set up flood-and storage-related penalty functions
control and reservoir refill penalty functions are
used here to solve the water allocaRun optimization
tion problem in terms of a balance
Infer flood control rule curves from optimization run
between flood control and reservoir
(Optimized FCs)
refill. A monthly time step reservoir
simulation model for Columbia
Apply Optimized FCs into simulation model
River Basin (ColSim) is used to test
the performance of the new flood
Compare simulated flood risks and storage deficits
using Optimized FCs with those using Current FCs
control curves inferred from
optimization runs.
No
2,500
3,000
30
Climate Change Scenario
Decrease storage
penalties or increase
flood penalties
3,000
10
Dworshak
0
Tool and Method
Stop
Mica
3,500
40
Storage (KAF)
Jul
Aug
Jun
Aug
Apr
May
Mar
Jan
Feb
Jul
Dec
Oct
Jun
May
Apr
Mar
Feb
Jan
Dec
Nov
Oct
Nov
0
No
0
50
Storage (KAF)
4000
1000
Yes
250
50
2000
Do Optimized FCs show
higher storage deficits
than Current FCs?
500
Flow at The Dalles (kcfs)
5000
c)
Flow at Columbia Falls (kcfs)
Reservoir Inflow
6000
Yes
3,500
Bonners Ferry
Mar
Apr
o
7000
Do Optimized FCs show
higher flood risk than
Current FCs?
750
4,000
4,000
Flow at Bonners Ferry (kcfs)
8000
20th Cent_Hec FC
b) Climate Change Scenario
600
Flow at The Dalles (kcfs)
Storage
o
a) 20th Century Climate
60
Flow at Bonners Ferry (kcfs)
o
Dworshak storage (Dworshak Apr-Jul flow volume >2.6 MAF)
Storage (KAF)
Average Monthly Storage Deficit (KAF)
Anticipated future temperature patterns will cause reduced spring snow pack,
earlier melt, earlier spring peak flow and lower summer flow in transient rainsnow and snowmelt areas. In the context of managed flood control, these
systematic changes are likely to disrupt the balance food control and reservoir
refill in existing reservoir systems .
30000
For example, right figure shows
: Current Climate
conceptual diagram of operational
: + 2.25 C No adaption
: + 2.25 C plus adaption
changes associated with stream25000
flow timing shifts for a hypothetical
dam located on the west slop of
the Cascade Mountains. Without
20000
adjustment of refill schedules, the
+ 2.25 C
hypothetical dam does not refill for
the altered streamflow timing
15000
simulated for a warming scenario.
:
By moving the refill timing one
10000
month earlier, however, the
hypothetical dam successfully
refills for the altered flow regime.
This illustration shows that refill timing and evacuation requirement for flood
control may need to be modified to adapt to these hydrologic changes
associated with global warming. This work
poses a significant systems engineering
problem especially for large water systems.
To solve this problem, there is a need to
develop an objective and well-defined
method to maintain or improve the current
Level of system performance for climate
change scenarios for complex flood control
system. Using the Columbia River basin
(shown in left figure) as an example, an optimization-simulation
procedure is used for restoring the balance
between flood control and reservoir refill
in complex, multi-objective reservoir
systems in response to streamflow timing
shifts under a simple global warming
The Columbia River Basin
scenario.
Optimization Results
Storage (KAF)
Overview
CC_Scen_CurFC
CC_Scen_HecFC
500
400
300
20th_Cent_CurFC
200
CC_Scen_CurFC
CC_Scen_HecFC
100
0
-2
-1
0
1
2
3
4
Extreme Value Type I Distribution Reduced Variate, Y
5
-2
-1
0
1
2
3
4
5
Extreme Value Type I Distribution Reduced Variate, Y
Conclusions
 Optimization studies provide an objective method for rebalancing flood control
and refill objectives in complex reservoir systems in response to hydrologic
changes.
 The changes in flood control rule curves are different for different projects,
corresponding to different changes in flow volume and timing associated with
warming in each sub basin.
 Optimized flood control rule curves show reduced flood evacuation and earlier
refill timing; up to one month earlier for a climate change scenario, compared
with 20th century climate.
 For the climate change scenario, optimized flood rule curves decrease storage
deficits while providing comparable levels of local and system-wide flood
protection in comparison to the current flood control rule curves.