Transcript Document

Forecasting Streamflow with the UW
Hydrometeorological Forecast
System
Dennis P. Lettenmaier
Photos from: www.metrokc.gov
Department of Civil and Environmental Engineering, University of Washington
GAPP Mountain Studies Workshop
July 24, 2003
presentation prepared by Ed Maurer, Dept of Atmospheric Sciences, UW
MM5-DHSVM Streamflow Forecast
System
UW Real-time
MM5
DHSVM
Distributed-Hydrology-Soil-Vegetation
Model
Completely automated
In use since WY 1998
Streamflow and
other forecasts
For 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.
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/
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:
http://www.hydro.washington.edu/
DHSVM Calibration
Calibration at 2 sites in Snohomish
River Basin
• Used all available meteorological
observations (50sites), 1987-1991
• Used flow observations at two USGS
gauges:
–
–
Snoqualmie R. at Carnation
Skykomish R. near Gold Bar
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
Performance of Hydromet System
Sauk
Observed
MM5-DHSVM
NWRFC
Snoqualmie
Using the Hydromet system for
MM5 diagnosis
Onecourse,
exceptionally
bad forecast
for
Of,
not all forecasts
were
thebad…
Cedar R., events from January
so
25 to Feb 4, 2003
Second peak:
•Forecast:1200 cfs
•Observed: 3700 cfs
•Flood stages above bankfull
occurred, and were not forecast
Representative Meteorological
Station – Mt. Gardner
Precip
Avg. Precipitation from 1/24 - 2/7:
Observed: 1.0 mm/h
Simulated: 0.7 mm/h
Total difference: ~100 mm
Average Temperature:
Observed: +2.1C
Predicted*: -0.1C
SWE:
Observed: -50 mm
Predicted*: +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.
Snow State Updating with
Observations
Use ground
observations
(SNOTEL sites)
to adjust the
basin snow state
Challenge:
45-50 snow water
observations for 48,000
km2 domain – low density
places high dependence
on interpolation
assumptions
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
Mountain hydrology issues for
GAPP
• Hydrologic prediction is essentially a one-way
forced problem in these environments. Do the
(atmospheric) models get the processes right,
especially the interaction of topography and model
physics? What can GAPP do to help improve the
models?
• How important are weather scale variations in
precipitation and temperature to S/I predictability,
and at what (spatial) scales?
• Are models able to capture observed longterm changes in snow/rain partitioning
within the transient snow zone of the
western mountains?
• Is there a rationale for a field campaign
associated with cold season orographic
processes in the west? If so, what needs to
be done, particularly in light of results from
PACJET, IMPROVE, etc.?