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

1.5

2.0

2.5

3.0

10 11 12 1 2 3 4 5 6 7 8 9

Month

Nor

mal

ized

Pre

cip

or R

unof

f SnowDominatedTransientSnowRainDominatedPNWPrecip

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

1900

1910

1920

1930

1940

1950

1960

1970

1980

1990

2000

Apr-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

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 apr

may jun jul

aug

sep

Are

a A

vera

ge W

ater

(d

epth

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

Wat

er B

alan

ce (d

epth

in m

m)

precipitationsnowmeltsoil drainagestreamflowevaporation

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

Stre

amflo

w (c

fs)

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.