Hydrologic Forecasting
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Hydrologic Forecasting Alan F. Hamlet Dennis P. Lettenmaier JISAO/CSES Climate Impacts Group Dept. of Civil and Environmental Engineering University of Washington
description
Hydrologic Forecasting. Alan F. Hamlet Dennis P. Lettenmaier JISAO/CSES Climate Impacts Group Dept. of Civil and Environmental Engineering University of Washington. Winter Climate of the Western U.S. NDJFM Precip ( mm). DJF Temp ( °C). Runoff Timing in the PNW is Determined Primarily by - PowerPoint PPT Presentation
Transcript of Hydrologic Forecasting
Hydrologic Forecasting
Alan F. HamletDennis P. Lettenmaier
JISAO/CSES Climate Impacts GroupDept. of Civil and Environmental EngineeringUniversity of Washington
DJF Temp (°C) NDJFM Precip (mm)
Winter Climate of the Western U.S.
0.0
0.5
1.0
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2.0
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3.0
10 11 12 1 2 3 4 5 6 7 8 9
Month
No
rma
lize
d P
rec
ip o
r R
un
off Snow
Dominated
TransientSnow
RainDominated
PNWPrecip
Runoff Timing in the PNW is Determined Primarily by Winter Temperature Regimes
Source: Booth D.B., 2000, Forest Cover, Impervious-Surface Area, and the Mitigation of Urbanization Impacts in King County, WAhttp://depts.washington.edu/cwws/Research/Reports/forest.pdf
Typical Effects of Urbanization on a Small Watershed Des Moines Creek
(developed)
150000
200000
250000
300000
350000
400000
450000
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Ap
r-S
ept F
low
(cfs
)
Effects of the Pacific Decadal Oscillation (PDO) and El Niño Southern Oscillation (ENSO) on Columbia River
Summer Streamflows
Cool PDO Cool PDOWarm PDO Warm PDO
Red = Warm ENSO, Blue = Cool ENSO, Green = ENSO neutral
Global Surface Temperatures are Increasing Rapidly
Global Surface Temperatures are Increasing Rapidly
1hr - 1 week 1– 24 months 10-100 years
Weather Forecasts
Flood Control and
Hydropower Management
Flood Forecasts
Seasonal to Interannual
Climate Forecasts
Seasonal Streamflow Volumes
Water Resources
Management
Climate Change
Scenarios
Long-Range Streamflow Forecasts
Water Resources Planning
Forecast Lead Time
Future Temperature and Precipitation
Forecast
Hydrologic Model
Initial Hydrologic State
•Soil Moisture•Snowpack Hydrologic
Forecast:
•Streamflow•Soil Moisture
•Snowpack•Evaporation
Schematic Diagram of a Hydrologic Forecasting System
Simulated Water Balance for the Pacific Northwest
0
50
100
150
200
250
oct
nov
dec
jan
feb
mar ap
r
may jun jul
aug
sep
Are
a A
ve
rag
e W
ate
r
(de
pth
in m
m)
precipitation
swe
runoff+baseflow
active soil storage
evapotranspiration
0
100
200
300
400
500
600
700
800
900
1000
oct-sept apr-sept
Wa
ter
Ba
lan
ce
(d
ep
th in
mm
)
precipitation
snowmelt
soil drainage
streamflow
evaporation
In Octoberfutureprecipitationdominates the inputs to the water balance.
In April inputs to the water balance from futureprecipitation and storage are comparable.
Relative Roles of Future Precipitation and Initial Hydrologic State at Different Forecast Dates
99%
46%
Simulated Long-Term Water Balance for the Pacific Northwest
Examples of Hydrologic Forecasting Systems
MM5 mesoscale atmospheric model
DHSVM distributed hydrologic model
Streamflow ForecastRiver Stage Forecast
Example of a Short Time Scale Flood Forecasting System
EstimatedHydrologic
State
Example of a Seasonal Forecasting System Based on Regression Models
Hydrologic Index
RegressionEquation
StreamflowVolume
NRCS SNOTEL Network
NRCS/NWRFC Water Supply Forecasts
Example of a Seasonal Forecasting System Using a Physically-Based Hydrologic Model
http://www.hydro.washington.edu/forecast/westwide/
Temperature and Precipitation
Forecast
EstimatedHydrologic
State
HydrologicForecast
VIC Hydrologic ModelUW West-Wide Seasonal Hydrologic
Forecast System
Background: Forecast System Schematic
NCDC met. station obs.
up to 2-4 months from
current
local scale (1/8 degree) weather inputs
soil moisturesnowpack
Hydrologic model spin up
SNOTEL
Update
streamflow, soil moisture, snow water equivalent, runoff
25th Day, Month 01-2 years back
LDAS/other real-time
met. forcings for spin-up
gap
Hydrologic forecast simulation
Month 6 - 12
INITIAL STATE
SNOTELUpdate
ensemble forecasts ESP traces (40) CPC-based outlook (13) NCEP GSM ensemble (20) NSIPP-1 ensemble (9)
Red = Unconditional meanBlue = Ensemble meanBlack = 2005 Observed
Nat
ural
Str
eam
flow
(cf
s)
Retrospective tests in the Columbia River basin have shown that during cool or warm events, ENSO-basedstreamflow forecasts are superior to assumptions of “normal” conditions about 65 % of the time on Oct 1
Climate forecasts based on ENSO predictions can provide useful information about future streamflows with lead times up to 12 months.
Natural Streamflow Columbia River at The Dalles, OR
Conclusions
Useful hydrologic forecasts based on weather or climate forecasts are available with lead times ranging from a few hours (flood forecasts) to 50 years or more (climate change scenarios).
Many operational hydrologic forecasting systems are currently based on statistical models, however dynamic, physically-based tools are increasingly being used in both academic and operational forecasting systems.
Dynamic forecasting systems based on weather or climate models directly linked to physically-based hydrologic models have important advantages in a rapidly evolving climate system. Short-term forecasts based on weather models have already reached a useful state of development, but many challenges remain at seasonal or longer time scales.
