Forecasting Streamflow with the UW Hydrometeorological

Forecast System

Ed MaurerDepartment of Atmospheric Sciences, University of Washington

Pacific Northwest Weather WorkshopMarch 8, 2003

Photos from: www.metrokc.gov

UW Hydromet System and Water Resource Time Scales

Ref: A Plan for a New Science Initiativeon the Global Water Cycle, www.usgcrp.gov

Weather: floods, drainage, operations

Seasonal/Interannual: water supply planning, droughts

Climate: climate change, urbanization

Temporal and Spatial Scales of Hydrologic Variability

Ref: A Plan for a New Science Initiativeon the Global Water Cycle, www.usgcrp.gov

Accurate representation of spatial and temporal variability in:•Precipitation•Land surface hydrologyis essential for simulating hydrological response at this scale

MM5-DHSVM Streamflow Forecast System

Completely automatedIn use since WY 1998For details: Westrick, K.J., P. Storck, and C.F.

Mass, Description and Evaluation of a Hydrometeorological Forecast System for Mountainous Watersheds, Weather and Forecasting 17: 250-262, 2002.

Streamflow and Streamflow and other forecastsother forecasts

DHSVM

UW Real-time MM5

Distributed-Hydrology-Soil-Vegetation Model

Penn State/NCAR Mesoscale Model MM5

Used throughout the world for both research and operational forecasting

48-hour (and some 72-hour and longer) forecasts run twice daily at the University of Washington

High-resolution model (4-km) capable of capturing the complex orography of the region, including lee shading and windward precipitation enhancement

FOR MORE INFO...

http://www.atmos.washington.edu/mm5rt/http://www.atmos.washington.edu/mm5rt/

DHSVM land surface hydrology model

•Physically-based, distributed model

•Solves a water balance at each grid cell at each time step

•Horizontal scales typically 30m to 150m

•Designed for and extensively tested in complex terrain

Details on DHSVM at:Details on DHSVM at:http://www.hydro.washington.edu/http://www.hydro.washington.edu/

DHSVM CalibrationCalibration at 2 sites in Snohomish River

Basin• Used all available meteorological

observations (50sites), 1987-1991 • Used flow observations at two USGS

gauges:– Skykomish R. near Gold Bar– Snoqualmie R. at Carnation

Snoqualmie R. at Carnation

Peaks flows and average water balance are well simulated by DHSVM when forced by observed meteorology

UW Hydromet Domain - 2003

26 basins

~60 USGS Gauge Locations

48,896 km2

2,173,155 pixels

DHSVM @ 150 m resolution

MM5 @ 4 & 12 km

Web Site for Forecast Dissemination

•Automatically updated twice daily

•Graphic display indicates forecasted flood status

•Click through to:

‑Hydrographs‑Snow state (maps and points)

‑Point weather forecasts

Performance of Hydromet System

MM5-DHSVM

Observed

NWRFC

Sauk Snoqualmie

Using the Hydromet system for MM5 diagnosis

One exceptionally bad forecast for the Cedar R., events from January 25 to Feb 4, 2003Second peak:•Forecast:1200 cfs•Observed: 3700 cfs•Flood stages above bankfull occurred, and were not forecast

Of, course, not all forecasts were so bad…

Representative Meteorological Station – Mt. Gardner

Avg. Precipitation from 1/24 - 2/7:Observed: 1.0 mm/hSimulated: 0.7 mm/hTotal difference: ~100 mm

Precip

Average Temperature:Observed: +2.1CPredicted*: -0.1C

SWE:Observed: -50 mmPredicted*: +100 mm

MM5 biases in P and T combine to produce large underestimation in runoff

Temp SWE

Opportunity for Improving UW Hydromet Forecasts

1 – Precipitation/Temperature Bias Correction

Remove systematic biases in P, T, at land surface

2 – IMPROVE-2 Take advantage of the IMPROVE-2 experiment to examine the interplay between observation density and bias correction performance

3 – Initial State Updating Assimilation of snow and soil moisture information from an observationally constrained data set.

Use ground observations (SNOTEL sites) to adjust the basin snow stateChallenge:45-50 snow water observations for 48,000 km2 domain – low density places high dependence on interpolation assumptions

Snow State Updating with Observations

Expansion of Forecast Products

Source: Grimit and Eckel, 2003

•Probabilistic streamflow forecasts

‑Take advantage of ensemble MM5 simulations to estimate uncertainty in forecasts

•Forecasts of slope stability‑ DHSVM produces more than just streamflow

‑ Soil moistures, slopes in model provide additional forecasting capabilities

‑ Investigate landslide hazard forecasting

Probability of failure

Image courtesy of L. Bowling

Summary• UW Hydrometeorological Forecast System provides

accurate streamflow and snowpack predictions when forced with accurate meteorology and when properly initialized

• Improvements in both initialization and meteorological forecasts are ongoing, by analyzing current flood events and retrospective analysis

• The capabilities of the system are being expanded to include both probabilistic forecasts using ensembles, and to include landslide hazard evaluation

Acknowledgments

Current Streamflow Forecasts

•NWRFC provides river flow and stage forecasts at strategic points in Puget Sound region

•Use point forecasts of precipitation and temperature

•Streamflow produced by a lumped parameter hydrologic model (does not produce spatially distributed water

balance estimates) www.nwrfc.noaa.gov

Original Motivation for Developing UW Hydromet System

• Integrated modeling over a variety of spatial and temporal scales to examine:– Regionally consistent modeling of weather and land

surface hydrology, avoid site-specific calibration– Capture topographically-driven spatial variation in

precipitation, temperature, and wind fields– Produce experimental streamflow forecasts to

investigate skill in a coupled model setting

• Use hydrometeorological forecasts as a diagnostic tool for mesoscale atmospheric model