Water Supply Forecast using the Ensemble Streamflow Prediction

Model

Kevin Berghoff, Senior HydrologistNorthwest River Forecast Center

Portland, OR

Overview

Community Hydrologic Prediction System (CHPS)

3 Components to model• Calibration• Operational Forecast System• Ensemble Streamflow Prediction - ESP

Analysis

Historical Data

Calibration System (CS)

Real-Time Observed and Forecast Data

Operational Forecast System (OFS)

Ensemble Streamflow Prediction (ESP) System

Hydrologicand

Hydraulic Models

Analysis and Data Assimilation

Hydrologic andHydraulic Models

short term forecasts

current states

StatisticalAnalyses

Probabilistic

Short term to

Extended

time

Analysis

window

InteractiveAdjustments

flow

Community Hydrologic Prediction System - CHPS

Hydrologic and

Hydraulic Models

HEFS

CHPS Model Calibration

Historical precipitation and temperature used to generate Mean Areal Precipitation (MAP) and Mean Areal Temperature (MAT) for each basin

SAC-SMA and SNOW-17 model parameters are adjusted to match the simulated river flow to the observed flow data over the entire calibration period of record

Timing and attenuation of routed flows from upstream points

Precipitation

and

Temperature

Rain or

Snow

Accumulated

Snow Cover

(SWE)

Energy Exchange

At

Snow-Air

Interface

Areal Extent

of

Snow Cover

Snow Cover

Heat deficit

Liquid Water

Storage

Rain

plus

Melt

Deficit = 0

(to Soil Moisture Model)

Snow

Outflow

Snow-17 Model

Transmission

of

Excess Water

Ground

Melt

Snow Model

Soil Moisture/Runoff

Consumptive Use

River Routing

Reservoir Regulation

Flow and Stage

Forecasts

Sacramento Soil Moisture Accounting (SAC-SMA) Model

CHPS Model Calibration

Operational Forecast System

Observed and 10 Day Forecast Inputs Precip, Temperature

Operational Forecast System

ObservedDeterministic

Forecast

Ensemble Streamflow Prediction

ESP Trace Ensemble Plot

1966

1992

ESP Accumulated Flow VolumeApril – Sept Forecast Period

ESP Example: NF John Day at Monument

Median Forecast

622 KAF

101%

Initial model states: 01/18/2011

Analysis Period: 4/1/2011 – 9/30/2011

Each point represents possible outcome based on initial model states,

10 Day fx, historical precip and temperature scenarios

Example: Dillon Reservoir 2011 Forecast

Spaghetti Forecast

April – July forecast

Median forecast:

195 kaf

Calibration(parameter uncertainty)

©The COMET Program

Output of streamflow ensembles (cumulative

uncertainty)

Meteorological Input(precip and temp variability)

Current model states

User/forecaster(level of experience, personal bias)

Computer model(model structure uncertainty)

Real-time data(variability and uncertainty)

Sources of Uncertainty

Data Issues

ESP Uncertainty

ESP Uncertainty

Observed Streamflow

Simulated Streamflow

Summary

ESP Assumption: Past meteorological data is a reasonable representation of future scenarios

Ensemble of forecasts generated using past precip and temperature data, current model states (soil moisture, snowpack)

Flexibility – allows user to specify desired forecast period and statistical analysis

Allows users to incorporate probabilistic information into operational decisions

ESP forecasts useful when strong climatological signal present

ESP Cautions

Less than 30 day lead time (NWRFC specific) Unaccounted for sources of uncertainty Tend to under forecast high years, over forecast

low years

Questions?

Data Issues

ESP Uncertainty

Dec 20 Dec 27 Jan 3 Jan 11 Jan 190

100

200

300

400

500

600

700

800

900

NF John Day River at MonumentInitial Conditions/QPF effects

2011 Apr - Sep Volume Forecast

2010/2011 Forecast Date

Ap

r -

Sep

Vo

lum

e -

KA

F

ESP Sensitivity Study:Summer/Fall Soil Moisture

hours

days/weeks

months

seasonal

annual

Forecast time

Unc

erta

inty

Advances in Time Scales

Forecast Services provided for all time domains

NWRFC Forecast ProductsESP Concept

Time

Fl ow

Deterministic Probabilistic

1959

1989

1954

ESP Trace Ensemble Plot

1966

ESP VerificationDworschak Dam

ESP VerificationHungry Horse Dam

Recent Historical Perspective

JAN - JUL Observed Runoff Volume - MAF

0

20

40

60

80

100

120

140

160

180

Year

Ru

no

ff V

olu

me

- M

AF

Columbia R at Grand Coulee Columbia R at the Dalles Snake R at Lower Granite

Dashed line = 30 Yr Mean (1971-2000)

96.6 – 90%

63.6 - 101%

25.5 – 85%

Calibration(parameter uncertainty)

©The COMET Program

Output of “Raw” streamflow ensembles (cumulative uncertainty)

Meteorological Input(precip and temp variability)

Current model states (spatial and temporal scale dependent bias)

User/forecaster(level of experience, personal bias)

Computer model(model structure uncertainty)

Real-time data(variability and uncertainty)

ESP uncertainty

This slide from Kevin Werner