1. Richard Palmer Michael Miller University of Washington Department of Civil and Environmental Engineering Water Supply and Allocation Issues in the Puget Sound

2. Objective and Outline What will be the climate and hydrology of the Puget Sound in 2020/2040 and what are the impacts of climate change on water supply issues? How can mid-term forecasts improve management of water supplies for people and fish?

5. Objective and Outline What will be the climate and hydrology of the Puget Sound in 2020/2040 and what are the impacts of climate change on water supply issues? How can mid-term forecasts improve management of water supplies for people and fish?

7. Current state of climate modeling Climate models are currently capable of credibly simulating present climate at the continental scale. Models are continually improving, yet key physical relationships remain poorly understood, the water vapor/cloud formation and feedback process being the most significant. Greater resolution and more complex parameterization of physical processes will continue as computing power increases and study continues. Models are not predictions of future, but can be considered as credible simulations of a multitude of possible futures.

8. GCMs - General Circulation Models IPCC discusses 34 GCMs Coupled Model Intercomparison Study examines 29 in more detail –Compares GCMs via historical observations for air temperature, precipitation, sea temperature, air pressure, ice extent. We have selected nine of the more prominent models to demonstrate GCM selection process

9. ModelDeveloped byReference CCSR/NIES2Center for Climate System Research, University of Tokyo/National Institute for Environmental Studies Emori et al, 1999 CGCM2Canadian Centre of Climate Modelling and Analysis Flato and Boer, 2001 CSIRO mk2Commonwealth Scientific & Industrial Research Organisation Gordon and O ’ Farrell, 1997 CSM1.3 * NCAR – National Center for Atmospheric Research Boville et al., 2001 DOE PCMNCAR, US Department of Energy, Los Alamos, Naval Post Graduate Program, and US Army Corps of Engineers. Washington et al., 2000 ECHAM4Netherlands center for Climate Research - and Max Planck Institute (MPI) Roeckner et al., 1996 GFDL_R30Geophysical Fluid Dynamics Laboratory (GFDL) & NOAA Knutson et al., 1999 HadCM3Hadley Centre for Climate Prediction and Research Gordon et al., 2000 MRI2Meteorological Research Institute (Numerical prediction Division) Yukimoto et al., 2000

10. Downscaling Methods Dynamical downscaling –Regional climate models: Difficult and computer intensive. Not yet proven to be any more reliable. Statistical downscaling –Transfer functions : Based on observed empirical relationships. –Weather generators: Extension of stochastic hydrology –Weather typing: Use of historic patterns, predicated on observed climactic variables.

11. Downscaling Methods Method :Perturbation Source: Lettenmaier and Gan (1990) Synopsis:  Compute difference between historic monthly averages and GCM simulated values for a given location for a chosen time period.  Shift a selected historic weather sequence by the computed ‘delta’  Modified weather record become future climate for chosen period. Advantages:  Preserves local spatial and temporal variability  Computationally parsimonious  Well established in scientific literature Challenges:  Assumes an elemental consistency in weather patterns and associations between measured variables even under climate change scenarios. May result in underestimation of climate change signal.

12. Downscaling Methods Method :Quantile Mapping Source: Wood (2002) Synopsis:  Statistical distribution of observed climate and ‘historic’ modeled climate are compared to remove model bias.  Future GCM values are mapped to the modeled history, then the corresponding quantile is selected from the observed historic record.  Selected historic value of monthly means are disaggregated to daily values to generate model driving weather sequences. Advantages:  Use of historic data to derive desecration coefficients reproduces local spatial and temporal variability.  Removes GCM model bias. Challenges:  Requires use of a single transient GCM run to develop statistical distributions. The resulting distribution is questionably in terms of its reliability.

13. Evaluation of Climate Change Climate Shift Meteorological Data Hydrology Model Demand Model Operations Model

14. Precipitation will increase in the winter and decrease in the summer. Temperatures will increase by 2° C by 2040, with higher temperatures in the summer

15. DHSVM Distributed Hydrology-Soil-Vegetation Model

16. Sultan River Inflows into Spada Reservoir Average Annual Hydrograph

17. Tolt River Inflows into Tolt Reservoir Average Annual Hydrograph

18. Cedar River Inflows into Chester Morse Reservoir Average Annual Hydrograph

19. Green River Inflows into Howard Hansen Reservoir Average Annual Hydrograph

20. Ranked Cumulative Winter Flow (JFM) 2040 32%43% cfs- weeks

21. Ranked Cumulative Spring (AMJ) Flow 2040 -30% cfs- weeks

22. Results – Impacts on Hydrology Percent difference from current climate cumulative seasonal flows JFMAMJJFMAMJ Mean Absolute Percent Difference 2020 2040 Sultan32-1843-3031 Tolt16-1620-2118 Cedar36-2349-3636 Green28-2537-3732 Average 28-2037-31

23. Conclusions Climate impacts on the four basins’ hydrology are similar Average percent difference in seasonal flows –2020 Winter : 28% 2020 Spring : -20% –2040 Winter : 37% 2040 Spring : -31% Absolute average percent difference –Sultan : 31% –Tolt : 18% –Cedar : 36% –Green : 32% Average supply system impact is 15-17% increase in System Use (surface storage, groundwater and/or system shortfalls)

24. Climate Impact on Water Supply Average climate impact on Supply Used, Percent Difference from Current Climate BasinMaxMinAvg Sultan37015 Cedar/Tolt321217 Green28216

25. Possible Reactions to Climate Change Information Supply –Tacoma to Seattle Connection (2 nd Supply Project) –Seattle to Everett Connection –Water Reuse Demand –Conservation Measures –Pricing –Change Service Base

26. Objective and Outline What will be the climate and hydrology of the Puget Sound in 2020/2040 and what are the impacts of climate change on water supply issues? How can mid-term forecasts improve management of water supplies for people and fish?

27. Why do a Forecast? 6-month forecast applied to the PRISM models Usefulness of forecasts –Why forecasts are useful –Who could use the forecasts How are the forecasts developed Examples of the forecasts Future direction with the forecasts

29. Applying 6-month Forecast Prior to a forecast –Water management decisions 50 years of meteorological records 73 years water supply and demand records With a forecast –Water management decisions based on potential future conditions Forecast continue using DHSVM and CRYSTAL for water supply and management

30. PRISM

31. Usefulness of Forecast For policymakers –M&I Demands During below average conditions –Improve timing of water restrictions –Provide more information as to the type of restriction –HCPs During above average conditions –Determine amount and length of large flow releases During below average conditions –Revise timing of releases to minimize habitat damage

32. Usefulness of the Forecast For water managers –During average and above average flow Forecast potential of these resources Discharge necessary to meet future flood control –During below average flows Forecast initial drought conditions a couple months sooner In the early summer months, forecasts could indicate when fall and winter flows will increase

33. Forecast Development Developed by Andy Wood, Edwin Maurer, Arun Kumar, and Dennis Lettenmaier NCEP Data –Bias Correction –Downscaling DHSVM

34. NCEP Data National Center for Environmental Prediction (NCEP) –Global Spectral Models (GSMs) –Hindcasts Temperature and precipitation 10 initial conditions 21 years (79 – 99) –Forecasts 20 ensembles 6-month forecast

35. Bias Correction

36. Downscaling Forecasted meteorological data –Based on month from the historic 21-year record (79-99), most similar precipitation –Precipitation is scaled (multiplicative process) –Temperature is shifted (additive process) Preformed to each month of each ensemble

37. DHSVM Distributed Hydrologic Soil Vegetation Model (DHSVM) Most recent year of actual data run prior to the forecast –To have the model set for the forecasted data. –Keep model run time reasonable

38. DHSVM Output 20 forecasts of stream flow Forecasts are compared to historic average flows Comparison used to forecast higher or lower then average flow.

39. June Forecast – Cedar

42. Summary Climate Change –Initial results suggest significant impacts on water supply –Lower summer flows will challenge releases for both fish and folks –New management strategies are necessary –Future planning should include this impact

43. Summary on Forecasting Forecasting with longer-range climate indicators offers promise Past forecasts did not provide sufficient lead time for certain times of year Will have on line forecasts this quarter