Alan F. Hamlet JISAO/CSES Climate Impacts Group Dept. of Civil and Environmental Engineering

1. Overview of Streamflow Scenario Generation Procedures and a Test Case for the Columbia River Optimization Study • Alan F. Hamlet • JISAO/CSES Climate Impacts Group • Dept. of Civil and Environmental Engineering • University of Washington

2. Issues Related to Choice of Hydrologic Model

3. Schematic of VIC Hydrologic Model and Energy Balance Snow Model Snow Model

4. Designing Climate Change Scenarios For Flood Studies

5. Issues Related to Choice of Downscaling Procedure • Delta method experiments • In this approach realistic daily sequencing and variability from the historic record are combined with systematic changes in temperature and precipitation extracted from GCMs. • Advanced statistical downscaling • These approaches add spatial variability and transient time series behavior from GCMs as well as more detailed statistical information about changes in temperature and precipitation at monthly time scales. Daily sequences are usually extracted from the historic record. • Dynamic downscaling using nested meso-scale models • These approaches dynamically simulate weather using GMM simulations as the large scale forcing. The approach has the potential to construct new weather statistics at small spatial and temporal scales, but with considerable uncertainty due to model limitations and small sample sizes.

6. +3.2°C °C +1.7°C +0.7°C 1.2-5.5°C 0.9-2.4°C Observed 20th century variability 0.4-1.0°C Pacific Northwest

7. % -1 to +3% +6% +2% +1% Observed 20th century variability -2 to +21% -1 to +9% Pacific Northwest

8. Regionally Averaged Cool Season Precipitation Anomalies PRECIP

9. Regionally Averaged Temperature Trends Over the Western U.S. 1916-2003 Tmax PNW GB CA CRB Tmin

10. Test Case for the Columbia Basin Optimization Studies

11. Overview of Monthly Hydrologic Simulations for the Optimization Test Case • First, monthly temperature trends are removed from the daily time step hydrologic model driving data set, pivoting around the year 2000. (Temperature variability is preserved, but temperature records are more consistent through time.) • A systematic increase in temperature of 2 C is then added to the driving data at monthly time step, based on a consensus of seasonal increases in temperature from four GCMs. Precipitation is not altered. Thus historic storm sequences are paired with systematically warmer conditions in the test case. • Daily time step hydrologic simulations from 1916-2003 were produced using the perturbed driving data, and monthly bias was removed from the simulations using quantile mapping techniques (See Snover et al. 2003). • The bias adjusted streamflow time series are then used as input to the optimization and simulation models.

12. Detrended Temperature Driving Data for Flood Risk Experiments “Pivot 2000” Data Set Temperature Historic temperature trend in each calendar month “Pivot 1915” Data Set 2003 1915

13. Delta Method Climate Change Scenarios for the PNW ~ + 2.5 C ~ + 1.7 C

14. Quantile-Based Bias Correction (Wood et al. 2002; Snover et al. 2003) VIC Input = 19000 Bias Corrected Output = 10000

15. Reconstructed Naturalized Weekly and Daily Flows at Palisades Dam for 1958-1992 Weekly Flow 1958-1992 Streamflow (cfs) Daily Flow 1958-1962

16. Conclusions A number of well developed procedures are available for constructing streamflow scenarios for large-scale planning studies using physically based hydrologic models at monthly to daily time scales. Different downscaling strategies are appropriate for different kinds of planning studies. For the Columbia Basin flood control optimization test case we chose to use a simple and effective procedure in which systematically warmer temperatures are paired with observed storm sequences to produce realizations of snowmelt flooding events in the Columbia basin in a warmer climate. In other systems, other downscaling choices may be more appropriate.

17. Selected References on Downscaling Strategies Salathé, E.P., 2004: Methods for selecting and downscaling simulations of future global climate with application to hydrologic modeling, International J. of Climatology, 25: 419- 436 Wiley, M.W., Palmer, R.N., Salathé, E.P., 2006: The development of GCM-based climate scenarios for use in water resource system impact evaluations, ASCE J. Water Resources Planning and Management, (in review) Wood A.W., Maurer E.P., Kumar A. and Lettenmaier, D.P., 2002: Long range experimental hydrologic forecasting for the eastern U.S. J. Geophys. Res., 107 (D20): 4429 Wood, A.W., Leung, L.R., Sridhar, V. and Lettenmaier, D.P., 2004: Hydrologic implications of dynamical and statistical approaches to downscaling climate model outputs, Climatic Change, 62 (1-3): 189-216