Transcript PNWRC Snake River Basin-wide streamflow forecasting

PNWRC Snake River Basin-wide
streamflow forecasting
Dennis P. Lettenmaier
Marketa McGuire
Department of Civil and Environmental Engineering
University of Washington
Climate Impacts Group Annual
Fall Forecast Meeting
Boise, ID
September 15, 2003
What is PNWRC (Pacific Northwest
Regional Collaboratory)?
“… to facilitate the integration of geospatial
technologies and data to serve the needs of
resource managers and decision-makers
across the PNW region
PNWRC
Mission &
Objectives
Strategic Objectives
 Provide solutions to problems of critical
regional importance
 Create enduring collaborations that position
the PNWRC as a key asset to government
and industry in the region
 Build geospatial capacity within the end
user community and participant institutions
 Ensure the financial sustainability of the
enterprise
Regional
Partners of
the PNWRC


Two National
Laboratories and four
regional universities
Partner base will be
expanded in future
years
Organizing
the Effort
Example
End Users
Government policymakers
Example
End Users
Commercial interests
PNW Sustainability Atlas
•Trend analysis
•Information integration
•Adaptive management
Sustaining
Framework
Technical
Projects
Public interest groups
Water management
•Snowpack
•Stream flow
•Water use efficiency
Government agencies
•Natural Resources Conservation
Service
•Bureau of Reclamation
•Washington Dept of Ecology
•Baseline characterization
•Sustainability indicators
•Forecasts and scenarios
Non-Governmental
organizations & Tribes
•Watershed councils
•NW Environment Watch
•Duck Valley Reservation
Land management
•Rangeland & forest health
•Invasive species
•Wildland habitat
Private/Commercial entities
•Irrigators
•Forest land managers
•Hydropower producers
Improved Streamflow Prediction and Water Resource
Management in
Snowmelt-Dominated Basins
A Raytheon/SYNERGY
Pacific Northwest Regional Collaboratory Project
BENEFITS: more optimal water use and
informed decision-making
More optimal
reservoir
operations
Conservation
Planning
Recreation
Industry
Water Resource Managers
Farmers
Important NASA programmatic goal: Utilize
Earth Observing System data for “real world”
decision-making
•
Improved Streamflow Prediction and Water Resource
Management in Snowmelt-Dominated Basins
COMPONENTS:
Hydrologic Modeling
• Large scale: Upper Snake (Year 1);
Klamath (Year 2 - ) (UW)
• Finer scale for critical sub-basins (ex: Big
Lost,) (INEEL, UI, PNNL)
Drivers for Hydrologic Models
• Snowcover and SWE (UI, INEEL)
• Forecast Met. Variables (UI, PNNL)
Reservoir Operations (UW)
Example: Upper Snake
36,000 mi2
• Crop Water Demand (UI)
Comprehensive Stream System
Resource Management
• Big Lost Sub-Basin (INEEL)
• Regional scale (UW)
University of Washington Element
(Snake River basin hydrology and
water resources forecasting using
remote sensing products)
Draws from UW
Experimental
Westwide
Hydrologic
Forecast System
(see Hamlet
presentation for
details)
www.hydro.washington.edu/
Lettenmaier/Projects/fcst/
index.htm
S/I Hydrologic Forecasting System
Products
• Streamflow
• Reservoir System:
• storages
• releases
• derived variables
• Spatial variables:
• snow water equiv.
• soil moisture
• runoff
• Verifications
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
MODIS Snowcover
March 3, 2000
VIC Snowcover
March 3, 2000
Snow
Land
Snow (SWE >= 5mm)
Clouds
No Data/No Decision/Saturated
Land (within Columbia River Basin)
MODIS Snowcover
April 4, 2000
VIC Snowcover
April 4, 2000
Snow
Land
Snow (SWE >= 5mm)
Clouds
No Data/No Decision/Saturated
Land (within Columbia River Basin)
Evaluation of the
Snow-Covered Area Data Product
from MODIS
in the context of
(Continental-Scale) Hydrological Modeling
Edwin P. Maurer and others
University of Washington
Department of Civil and Environmental Engineering
Originally presented at AGU Fall Meeting, December 2001
Study Area Selection
Study areas:
Columbia River Basin
Missouri River Basin
Image Comparison Data (all in spring 2001)
•MODIS Images (nominal 500 m res.)
•NOHRSC (AVHRR) images (1 km)
•Snow observations
•Missouri - 1325 observation points
•Columbia - 773 observation points
•Select days of interest:
Relatively cloud-free days
Both MODIS and AVHRR available
Missouri
Columbia
3/2
3/30
3/9
4/3
3/16
4/4
3/22
4/7
3/29
4/18
4/4
4/19
4/5
4/24
4/7
5/1
4/11
5/17
4/17
Observation Point Locations
MODIS, AVHRR and Gridded Observations
MODIS
AVHRR
Gridded
Observations
April 4, 2000
MODIS, AVHRR and Gridded Observations
MODIS
AVHRR
Gridded
Observations
April 7, 2000
Pixel-by-Pixel Comparisons
Classification grid:
Error of Omission
Snow in
Image
Snow
Observed
No Snow
Observed
No Snow
in Image
Cloud in
Image
Undetermined
Correctly
classified
snow
Correctly
classified
no snow
Error of Commission
1) Using image resolutions of 30-arc seconds for AVHRR and
15 arc-seconds for MODIS
Missouri River Basin
Snow
MODIS
0.35
0.09
AVHRR
0.27
0.03
0.17
0.4
0.48
0.49
0
0.02
0.12
0.4
0.61
0.56
0
0.01
Less Cloud for
MODIS
Columbia River Basin
Snow
MODIS
0.51
0.13
AVHRR
0.29
0.06
0.09
0.47
0.39
0.39
0.01
0.01
0.22
0.42
0.48
0.51
0.01
0.01
Less Cloud for
MODIS
2) Using aggregated MODIS image -- AVHRR and MODIS at
30 arc-seconds
Missouri River Basin
MODIS
0.34
0.06
AVHRR
0.27
0.03
0.19
0.44
0.46
0.48
0
0.01
0.12
0.4
0.61
0.56
0
0.01
Less Cloud for
MODIS
Columbia River Basin
MODIS has
more snow
pixels correct
MODIS
0.49
0.12
AVHRR
0.29
0.06
0.11
0.50
0.38
0.37
0.02
0.01
0.22
0.42
0.48
0.51
0.01
0.01
Less Cloud for
MODIS
3) Examining Differences in Cloud Cover and Vegetation
Missouri River Basin
Fraction of Error
Fraction of Basin
in Classified
Classified
Cells
MODIS
AVHRRMODIS
AVHRR
All Days
0.51
0.42
0.16
0.10
Cloudiest Days
0.39
0.33
0.17
0.11
Clearest Days
0.80
0.64
0.13
0.07
Forested Pixels
0.60
0.41
0.34
0.28
Columbia River Basin
All Days
Cloudiest Days
Clearest Days
Forested Pixels
Fraction of Basin
Classified
MODIS
AVHRR
0.62
0.49
0.49
0.36
0.88
0.75
0.56
0.43
Fraction of Error
in Classified
Cells
MODIS
AVHRR
0.19
0.20
0.17
0.19
0.22
0.21
0.24
0.43
Red shading indicates difference is significant at 95% confidence level
SUMMARY
MODIS generally classifies less as “cloud” than
NOHRSC/AVHRR
MODIS SCA product is a measurable improvement
over AVHRR images where:
Terrain is complex – (greater relief)
Forested area is dominant
MODIS exhibits greater errors than AVHRR in:
Cloudy days over grassland/low relief basin
Other plans for large area forecasting
and water management
• Extend westwide forecast products over the
Snake to include reservoir storage, releases, etc
(via routing of forecast ensembles through
SNAKESIM)
• Evaluation of AMSR SWE products
• Evaluation of MODIS-based crop water use
(available in near-real time) – current
SNAKESIM approach prescribes water use as
fixed