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. DJF Temp (°C) NDJFM Precip (mm)

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

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

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

Global Surface Temperatures are Increasing Rapidly

Flood Control and Hydropower Management 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

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

Simulated Water Balance for the Pacific Northwest

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

Examples of Hydrologic Forecasting Systems

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

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

UW West-Wide Seasonal Hydrologic 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/

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 25th 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)

Natural Streamflow (cfs) 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)

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.