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Hydrologic Forecasting Alan F. Hamlet Dennis P. Lettenmaier JISAO/CSES Climate Impacts Group Dept. of Civil and Environmental Engineering University of Washington
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DJF Temp (°C) NDJFM Precip (mm) Winter Climate of the Western U.S.
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Runoff Timing in the PNW is Determined Primarily by Winter Temperature Regimes
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Source: Booth D.B., 2000, Forest Cover, Impervious-Surface Area, and the Mitigation of Urbanization Impacts in King County, WA http://depts.washington.edu/cwws/Research/Reports/forest.pdf Typical Effects of Urbanization on a Small Watershed Des Moines Creek (developed)
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Effects of the Pacific Decadal Oscillation (PDO) and El Niño Southern Oscillation (ENSO) on Columbia River Summer Streamflows Cool PDO Warm PDO Red = Warm ENSO, Blue = Cool ENSO, Green = ENSO neutral
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Global Surface Temperatures are Increasing Rapidly
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1hr - 1 week 1– 24 months10-100 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
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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
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Simulated Water Balance for the Pacific Northwest
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In October future precipitation dominates the inputs to the water balance. In April inputs to the water balance from future precipitation 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
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Examples of Hydrologic Forecasting Systems
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MM5 mesoscale atmospheric model DHSVM distributed hydrologic model Streamflow Forecast River Stage Forecast Example of a Short Time Scale Flood Forecasting System Estimated Hydrologic State
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Example of a Seasonal Forecasting System Based on Regression Models Hydrologic Index Regression Equation Streamflow Volume NRCS SNOTEL Network NRCS/NWRFC Water Supply Forecasts
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Example of a Seasonal Forecasting System Using a Physically-Based Hydrologic Model http://www.hydro.washington.edu/forecast/westwide/ Temperature and Precipitation Forecast Estimated Hydrologic State Hydrologic Forecast VIC Hydrologic Model UW West-Wide Seasonal Hydrologic Forecast System
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Background: Forecast System Schematic NCDC met. station obs. up to 2-4 months from current local scale (1/8 degree) weather inputs soil moisture snowpack Hydrologic model spin up SNOTEL Update streamflow, soil moisture, snow water equivalent, runoff 25 th Day, Month 0 1-2 years back LDAS/other real-time met. forcings for spin-up gap Hydrologic forecast simulation Month 6 - 12 INITIAL STATE SNOTEL Update ensemble forecasts ESP traces (40) CPC-based outlook (13) NCEP GSM ensemble (20) NSIPP-1 ensemble (9)
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Red = Unconditional mean Blue = Ensemble mean Black = 2005 Observed Natural Streamflow (cfs) Retrospective tests in the Columbia River basin have shown that during cool or warm events, ENSO-based streamflow 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
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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.
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