Transcript Improving Streamflow Forecasting Reservoir Operations in

Improving Seasonal Forecasting in
the Snake River Basin, Idaho
University of Washington – University of British Columbia
Fall Hydrology Workshop
Oct 3, 2003
Marketa McGuire
With contributions from:
Alan Hamlet, Andy Wood, Kostas Andreadis, Dennis Lettenmaier
Objectives
1. To evaluate the impact of remote sensing data
for improved estimates of initial snow
conditions in streamflow forecasting
2. To evaluate the impact of streamflow forecast
products for improved water resources
operations
Motivation
• In regions like the Snake River basin, where spring and
summer streamflows are dominated by snow-melt, it is
important to know accurately the extent of snow in the
initial condition of a streamflow forecast
• Previous work by Maurer et al (2003) suggests that
MODIS remotely sensed snowcover has the potential to
improve hydrological modeling and prediction in the
Snake River basin
• Current meteorological station data are provisional
– Result: estimates of forecast initial conditions have large
uncertainty
Forecasting Approach using MODIS
Updating
Hydrologic
model spin up
Initial
Conditions:
soil moisture,
snowpack
local scale
weather
inputs
NCDC met.
station obs.
up to 2-4
months from
current
LDAS/other
real-time met.
forcings for
remaining
spin-up
1-2 years back
Hydrologic
simulation
Ensemble
Forecast:
streamflow,
soil moisture,
snowpack,
runoff
MODIS
Update
25th Day of Month 0
End of Month 6 - 12
Variable Infiltration Capacity (VIC) Model
Snake River 1/8° Resolution
Routing Flow Network
MODIS Snowcover
April 4, 2000
(500 m)
VIC SWE
April 4, 2000
(1/8 degree)
Snow
Land
Snow (SWE >= 5mm)
Clouds
No Data/No Decision/Saturated
Land (within Snake River Basin)
Updating VIC Snow State
• Current Version of VIC model:
– Snow model runs on a 3 hours timestep
– Each grid cell has up to 5 elevation bands
– Each elevation band either has snow (coverage = 1) or does
not (coverage = 0)
• VIC model with updated snowcover (2 options):
– Apply MODIS snowcover uniformly over elevation bands
based on some threshold fraction of snowcover
– Utilize VIC model version 4.1 that incorporates fractional
snowcover (in testing phase Fall ’03)
MODIS Fractional Snowcover
• Idaho National Environmental and Engineering Laboratory
(INEEL) is processing snow cover fractions for VIC model
grid cells
– Have obtained all Daily Snow cover tiles available for
Snake Basin from February 2000 to present
– Have automatic subscription with the NSIDC to obtain
all newly processed scenes, with lag time of 2-3 days
– Working toward fully automating the prototype
algorithm to provide near real-time snow cover
fractions for the Snake River Basin test application
Strategy for Evaluating the Impact of
MODIS
• Conduct a sensitivity analysis to determine the importance
of snow in the Snake River basin
– Analysis based on discrepency between MODIS snowcover and
VIC snowcover
• Compare streamflow forecasts, with and without MODIS
updating, beginning at various dates throughout the winter
– Hypothesis: Updating will be more valuable for a streamflow
forecast in early winter and spring when snow cover tends to
change rapidly
• Compare streamflow forecasts, with and without MODIS
updating, to streamflow forecasts produced by the NRCS
for a subset of basins within the Snake River Basin
Objectives
1. To evaluate the impact of remote sensing data
for improved estimates of initial snow
conditions in streamflow forecasting
2. To evaluate the impact of streamflow forecast
products for improved water resources
operations
Modeling Approach to Evaluate Operations
Update Forecast Initial
Conditions with
Current Reservoir
Storages
Observed
Meteorological
Time Series
Precip, temp, wind, etc.
Hydrology
Model
(VIC)
Streamflow
Forecasts
Streamflow at
21 locations
Water Resources
Operations Model
(SnakeSim)
MODIS: fraction of snowcover
Update Forecast Initial
Conditions using
Remote Sensing
Reservoir
Forecasts
Storage, reliability,
spill, energy
Ensemble Streamflow Prediction
Ensembles
Sept 1, 1960
.
.
.
VIC
Hydrologic
Model
Sept 1, 1961
Standardized
Initial
Conditions
.
.
.
Sept 1, 1962
.
.
.
Sept 1, 1963
.
.
.
Observed Meteorological Time Series
or
Climate Model Output
Streamflow Ensemble
Sample Streamflow Forecast
Jackson Lake Inflows
www.hydro.washington.edu/Lettenmaier/Projects/fcst/index.htm
CRB Ensemble Streamflow Prediction (1960-1999)
40 ENSEMBLE MEMBERS
FORECAST DATE: September 1, 2003
20
Jackson Lake
1997 WY
18
16
Avg Flow (Kcfs)
14
12
10
1992 WY
8
6
4
2
0
Sep
Oct
Nov
Dec
Jan
Feb
Mar
Apr
May
Jun
1977 WY
Jul
Aug
Sep
CRB Ensemble Streamflow Prediction (1960-1999)
11 ENSEMBLE MEMBERS
FORECAST DATE: September 1, 2003
20
Jackson Lake
1997 WY
18
16
Avg Flow (Kcfs)
14
12
10
8
1962 WY
6
4
2
0
Sep
Oct
Nov
Dec
Jan
Feb
Mar
Apr
May
Jun
1961 WY
Jul
Aug
Sep
Linking Streamflow Forecasts to SnakeSim
Ensemble
Streamflow
Forecast
Bias
Correction
SnakeSim Water
Resources Operations
Model
Demand
Scenarios
Initial Reservoir
Contents from
USACE or USBR
Storage Ensemble
SnakeSim Operations Model Overview
• Developed by Nathan VanRheenen, UW
• Stella modeling environment
• Simulation for 1950 - 1992
• 21 Inflow Nodes, utilizing:
– Historic naturalized flows
– Routed flows from VIC model
• 18 Reservoirs Modeled
– 13.3 MAF Total Storage (16.4 BCM)
• Simulation of Snake River Plain Aquifer
• Historic Demand Scenarios
SnakeSim Operations Model Assumptions
• Current levels of operation adhering to IDWR, BOR,
COE rules for reservoir storage and releases
• Instream targets for fish, water quality, and
hydropower production
• Surface water diversions grouped by river reach
• Groundwater response curves are linear and based on
University of Idaho algorithms
• 1980 groundwater pumping curves and irrigation areas
Portion of Domain in Storage Forecast
System Storage
Forecast from
SnakeSim:
Jackson Lake
Palisades
Island Park
Ririe
American Falls
Lake Walcott
11 ENSO neutral
years
Random historic
demand scenarios
Active Reservoir Storage (kaf)
Full Full
PoolPool
Green = ensemble mean
Strategy for Evaluating the Use of
Streamflow Forecasts in Water Management
• Do similar comparisons as with streamflow
forecasts
– Sensitivity analysis to determine importance of
snow
– Compare operations, using streamflow
forecasts with and without MODIS updated
snow cover, beginning at various dates
throughout the winter
• Other
Summary: Current Status
 We produced first set of streamflow forecasts for
Sept 1, 2003 for 21 locations in the Snake River
basin
 Snake River basin streamflow forecasts, updated
every month, will now be available on the web as
part of the UW S/I Hydrologic Forecast System
(www.hydro.washington.edu/Lettenmaier/Projects/fcst/index.htm)
 Acquisition of near real-time MODIS fractional
snowcover for the Snake Basin is in progress
 Testing of VIC 4.1 planned for Fall 2003
(utilizes fractional snowcover for each elevation band)
Questions ?
Bias Correction Objectives:
Raw
Bias Corrected
Result: Bias corrected hydrologic simulations are quite consistent with
observed streamflows in absolute value and climate change signals are
translated without significant distortion.
Quantile-Based Bias Correction
(Wood
et
al.
2002)
VIC Input = 19000
35000
30000
Flow (cfs)
25000
20000
obs
15000
vic
10000
5000
0
0
0.2
0.4
0.6
Probability of Exceedence
Bias Corrected Output = 10000
0.8
1
CRB Ensemble Streamflow Prediction (1960-1999)
8 ENSEMBLE MEMBERS
FORECAST DATE: September 1, 2003
20
Jackson Lake
1997 WY
18
16
Avg Flow (Kcfs)
14
12
10
8
1979 WY
6
4
2
0
Sep
Oct
Nov
Dec
Jan
Feb
Mar
Apr
May
Jun
1982 WY
Jul
Aug
1994 WY
Sep