Modeling Hydrological Processes

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Modeling Hydrological Processes
Ed Maurer PRISM Science Retreat Friday, September
27, 2002
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Acknowledgments
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Hydrological Modeling

• Hydromet System provides a valuable regional
  research tool.
• Maintenance
• Improvement
• Expansion

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MM5-DHSVM Streamflow Forecast System
UW Real-time MM5 Distributed-Hydrology-Soil-
Vegetation Model Completely automated In use
since WY 1998
DHSVM
Streamflow and other forecasts
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Summary of Hydromet System
Real-time Streamflow Forecast System 26
basins 60 USGS Gauge Locations 48,896
km2 2,173,155 pixels DHSVM _at_ 150 m
resolution MM5 _at_ 4 12 km
http//hydromet.atmos.washington.edu
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Some Recent Publications

• 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.
• Mass, C.F., D. Ovens, K. Westrick, and B.A.
  Colle, Does Increasing Horizontal Resolution
  Produce More Skillful Forecasts?. Bull. Amer.
  Meteorol. Soc. 83 407-430, 2002.
• Westrick, K.J. and C.F. Mass, An Evaluation of a
  High-Resolution Hydrometeorological Modeling
  System for Prediction of a Cool-Season Flood
  Event in a Coastal Mountainous Watershed, J.
  Hydrometeorology 2 161-180, 2001.

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Maintenance of System

• As models evolve and data formats change, the
  system must adapt
• Data format for streamflow observations
• Extending forecasts to 48 hours as with 4 km MM5

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Performance of Hydromet System
Sauk
Snoqualmie
Observed
MM5-DHSVM
NWRFC
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Hydromet Performance 2
Deschutes
Nisqually
MM5-DHSVM
Observed
NWRFC
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Summary of Performance

• Results from 6 events Westrick et al., 2002
• Best forecasts w/obs., avg. error 31
• Not significantly better than control or RFC

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Opportunity for Improving Hydromet Forecasts

• One key finding from Westrick et al., 2002
• Precipitation uncertainties in observed data due
  to
• Instrument error
• Areal representativeness of point obs.
• Interpolation method
• These errors can be nearly as large as
  uncertainty in meteorological forecast.

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Lack of Observations

• To improve forecasts, we must identify the
  relative magnitudes of the errors.
• Precipitation observations at a spatial
  resolution sufficient to determine reality do
  not exist in domain
• IMPROVE 2 study provides a valuable context for
  examining the orographic precipitation for
  several events, and provides a basis for
  intercomparing the errors

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IMPROVE-2 Orographic Precipitation Study Nov-Dec
2001

• Raingauges
• Snotel
• Co-op Observer
• Radar
• Disdrometer

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Expansion of Forecasting Tools

• DHSVM produces more than just streamflow
• Soil moistures, slopes in model provide
  additional forecasting capabilities
• Investigate landslide hazard forecasting

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DHSVM Sediment Production and Transport
Watershed Sediment Module
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DHSVM Structure Modifications
f(Soil Cohesion) f(Veg. Cohesion)
Channel flow
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Mass Wasting Module
Factor of Safety
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Summary

• Many Opportunities to Build on the Past Successes
• Coordination with Others in the PRISM Community
  is an Essential Component