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Hydrologic Forecasting

Hydrologic Forecasting. Alan F. Hamlet Dennis P. Lettenmaier JISAO/CSES Climate Impacts Group Dept. of Civil and Environmental Engineering University of Washington. Winter Climate of the Western U.S. NDJFM Precip ( mm). DJF Temp ( °C). Runoff Timing in the PNW is Determined Primarily by

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Hydrologic Forecasting

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  1. Hydrologic Forecasting Alan F. Hamlet Dennis P. Lettenmaier JISAO/CSES Climate Impacts Group Dept. of Civil and Environmental Engineering University of Washington

  2. Winter Climate of the Western U.S. NDJFM Precip (mm) DJF Temp (°C)

  3. Runoff Timing in the PNW is Determined Primarily by Winter Temperature Regimes

  4. Typical Effects of Urbanization on a Small Watershed Des Moines Creek (developed) 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

  5. Effects of the Pacific Decadal Oscillation (PDO) and El Niño Southern Oscillation (ENSO) on Columbia River Summer Streamflows Red = Warm ENSO, Blue = Cool ENSO, Green = ENSO neutral Cool PDO Cool PDO Warm PDO Warm PDO

  6. Global Surface Temperatures are Increasing Rapidly

  7. 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 1hr - 1 week 1– 24 months 10-100 years Forecast Lead Time

  8. Schematic Diagram of a Hydrologic Forecasting System • Initial Hydrologic State • Soil Moisture • Snowpack • Hydrologic • Forecast: • Streamflow • Soil Moisture • Snowpack • Evaporation Hydrologic Model Future Temperature and Precipitation Forecast

  9. Simulated Water Balance for the Pacific Northwest

  10. Relative Roles of Future Precipitation and Initial Hydrologic State at Different Forecast Dates 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. 99% 46% Simulated Long-Term Water Balance for the Pacific Northwest

  11. Examples of Hydrologic Forecasting Systems

  12. Example of a Short Time Scale Flood Forecasting System DHSVM distributed hydrologic model MM5 mesoscale atmospheric model Estimated Hydrologic State Streamflow Forecast River Stage Forecast

  13. Example of a Seasonal Forecasting System Based on Regression Models NRCS SNOTEL Network NRCS/NWRFC Water Supply Forecasts Hydrologic Index Regression Equation Streamflow Volume

  14. Example of a Seasonal Forecasting System Using a Physically-Based Hydrologic Model Temperature and Precipitation Forecast Estimated Hydrologic State VIC Hydrologic Model UW West-Wide Seasonal Hydrologic Forecast System Hydrologic Forecast http://www.hydro.washington.edu/forecast/westwide/

  15. soil moisture snowpack streamflow, soil moisture, snow water equivalent, runoff local scale (1/8 degree) weather inputs INITIAL STATE Hydrologic model spin up Hydrologic forecast simulation NCDC met. station obs. up to 2-4 months from current LDAS/other real-time met. forcings for spin-up gap ensemble forecasts ESP traces (40) CPC-based outlook (13) NCEP GSM ensemble (20) NSIPP-1 ensemble (9) SNOTEL Update SNOTELUpdate 25th Day, Month 0 1-2 years back Month 6 - 12 Background:Forecast System Schematic

  16. 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 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 Red = Unconditional mean Blue = Ensemble mean Black = 2005 Observed Natural Streamflow (cfs)

  17. 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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