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Impacts of hydrological variability and change on water resources
Dennis P. LettenmaierDepartment of Civil and Environmental Engineering
University of Washington
for presentation at
Fifth IHP/IAHS George Kovacs Colloquium
UNESCO, Paris
2 June 2000
Outline of this talk1) Approach to long-lead hydrological
forecasts utilizing resampling anddownscaled climate models (ColumbiaRiver example)
2) Evolving approach to forecasting U.S.soil moisture and streamflow usingensemble climate forecasts
3) Assessment of sensitivity of globalrivers to climate change, and detailedexample for Columbia River basin
Modeling the Connections Between Climate and Streamflow
Currently Modeled US Basins
1 Northwest 5 Rio Grande 10 Upper Mississippi2 California 6 Missouri 11 Lower Mississippi3 Great Basin 7 Arkansas-Red 12 Ohio4 Colorado 8 Gulf 13 East Coast
9 Great Lakes
Long-LeadClimate Forecast
ENSO
PDO
Run Initialized Hydrologic Model
Ensemble StreamflowForecast
Select Met Data Ensemble fromHistoric Record Associated with
Forecast Climate Category
Schematic for Forecasting Experiments Using Resampled Observed Data
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PDO Warm
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PDO/ENSO Effects
Columbia PDO Effects Columbia ENSO Effects
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PDO/ENSO Effects
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Chester Morse PDO Effects
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El Nino
Chester Morse ENSO Effects
Time Line for 12-month Lead Time Retrospective Forecasts
Climate Forecast
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J J A S O N D J F M A M J J A S
Estimated Initial Conditions
ForecastEnsemble
Lead time = 12 months
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Str
eam
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Columbia River Streamflow Forecast at The Dalles for 2001
Highest Simulation (1948-1997)
Lowest Simulation (1948-1997)
Cool PDO/ENSO Neut.Ensemble
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Cool PDO/Cool ENSOEnsemble
Columbia River Streamflow Forecast at The Dalles for 2000
Global Climate Models
Regional Climate Models
Hydrology Models
WaterResources
Models
Overview of Streamflow Forecasting Schemes Using Climate Models
water demand
streamflowTemp. Precip. winddownscaling
Oct
Nov
May
Dec Feb Mar Apr
Jun Jul . . .
Repeating 1960 Observed Temp and Precip Time Series with Nov-April Replaced by MM5 Forecasts
MM5 Sim
Constructing the Hydrology Model Driving Data Using a Normal SST Nov-Apr Climate Forecast
MM5 SimMM5 SimMM5 SimMM5 SimMM5 SimMM5 SimMM5 SimMM5 SimMM5 SimMM5 SimMM5 SimMM5 SimMM5 Sim
24 MM5 Forecasts
. . .
Jan
1960
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(CF
S)
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(CFS
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Control(observed Nov-Apr’s)
RCM(raw climate simulationsfor Nov-Apr’s)
Test Simulations for the Columbia River at The Dalles
Mean
Variance
Simple Bias Correction Used in MM5 Experiments(Nov-Mar Ensembles inserted in repeating 1960)
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observedvariance
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bias correctedsimulatedvariance
Quantile Mapping Bias Correction
Mean
Variance
Kanawha River Basin Simulations Using Observed Data and Bias Corrected GCM Output
Observations
Bias-Corrected GCM
Downscaled GSM forecast ensembles compared to historical climatological bounds
1 Ohio 3 Delaware 4 Alabama-Coosa-Tallapoosa2 Potomac 5 Apalachicola-Chattahoochee-Flint
Current Streamflow Forecast Basins
Current Streamflow Forecast Basins
Climate Scenarios
Transient GCM Simulations for Increasing CO2 and Aerosols
AdjustmentsTo ObservedMeteorology
Delta Precip,Temp
HydrologicModel (VIC)
Natural Streamflow
ReservoirModel (ColSim)
DamReleases,Regulated
Streamflow
PerformanceMeasures
Reliability of System Objectives
CORRA
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ICE HARBOR
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2025
CORRA
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ICE HARBOR
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DALLES
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MPI
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FirmEnergy
Non-FirmEnergy
McNaryFlow
SnakeIrrigation
LakeRooseveltRecreation
System Objective
Rel
iab
ilit
y (%
) Base Case
HC 2025
HC 2045
HC 2095
MPI 2025
MPI 2045
ColSim Reliability of System Objectives