Water Power Peer Review

1. Water Power Peer Review Water Use Optimization Hydrologic Forecasting Mark Wigmosta, Nathalie Voisin, Andre Coleman, Richard Skaggs, Erik Venteris PNNL Dennis Lettenmaier, Vimal Mishra, and Shraddhanand Shukla University of Washington Hydrologic Forecasting Presenter: Mark Wigmosta Organization: PNNL Contact Info: mark.wigmosta@pnl.gov Date: 11/03/2011 Water Use Optimization: Hydrologic Forecasting

2. Purpose, Objectives, & Integration Challenges: Lack of broadly available inflow forecasts to the nation’s reservoir system generally result in overly conservative operational constraints to meet multiple water use objectives and mitigate the impacts of hydrologic extremes (flood, drought). Overly conservative constraints limit the opportunity to optimize electricity generation, environmental performance, and efficient water utilization. Objectives: Integrate and enhance PNNL and University of Washington/Princeton University Ensemble Forecast Systems to provide a national multi-scale streamflow forecasting system for the optimization toolbox • Meteorological and streamflow forecasts at multiple user defined temporal and spatial scales (input to project components 1, 3, and 5) • Longer lead times with reduced forecast uncertainty • Basis for relaxation of constraints without increasing risk • Increased opportunity for plant to system optimization

3. Technical Approach • Build on existing PNNL/UW capabilities • Physics-based, distributed hydrologic model • 1/8 degree (~12 km) grid • Ensemble streamflow forecasting to capture uncertainty • Medium-range (1-14 day lead) to seasonal forecasts • Consistent, national approach for multi-scale ensemble streamflow forecasting • data sets and methodology • Automated assimilation of spatial and temporal data for improved forecast accuracy • streamflow • snowpack snow water equivalent • snowpack spatial extent

4. Plan, Schedule, & Budget Schedule • Initiation date: Nov, 2009 • Planned completion date: February, 2013 • Milestones for FY10 and FY11 • Design document for integrated forecast model (FY10) - completed • Evaluation of remote sensing and alternative ensemble forecasts (FY10) - completed • Install UW/PU forecast system on PNNL high performance compute cluster (FY10) - completed • Prototype integration of PNNL and UW/PU forecast systems (FY11) - completed • Prototype of advanced data assimilation in integrated model (FY11) - completed • Initiate collaboration with National Weather Service (FY11) - completed • Initial application of forecast system to one demonstration basin (FY11) – completed in two basins • Preliminary seasonal forecasts in one demonstration basin (FY11) – completed in two basins • Preliminary medium range forecasts in one demonstration basin (FY11) – completed in two basins • Retrospective analysis of forecast accuracy in one demonstration basin (FY11) – completed in two basins • Milestones for FY12 and FY13 • Demonstrate operability of forecast system at multiple sites • Successful integration in optimization toolbox * *

5. Accomplishments and Results • Completed Forecast System Design Document (FY10) • Completed evaluation of remote sensing and alternative ensemble forecast methodology (FY10) • Installation of UW/PU forecast system on PNNL computer cluster (FY10) • Ongoing modernization and optimization of core software • More flexible and generic approach • Prototype Enhanced Hydrologic Forecast System (EHFS) (FY11) • Initial application in two demonstration basins: Feather River, CA and Gunnison River, CO (FY11) • Calibration • Seasonal forecasts • Medium-range forecasts • Retrospective evaluation

6. Accomplishments and Results Feather River Basin, CA 1998 Seasonal forecasts issued in March and April skillful for 4-5 months ahead. Medium-range forecasts improve upon persistence. 1990 - 2005

7. Accomplishments and Results Gunnison River Basin, CO 1998 Seasonal forecasts issued in early spring are skillful for the first 2-3 months. Seasonal forecasts issued in late spring are skillful for 6 months. Impact of upstream regulation requires further study. 1990 - 2005

8. Challenges to Date • Modernization and optimization of core software architecture in current forecast systems • Upgrade inefficient system/platform specific software • Provide capacity for distributed computing • Development of robust and autonomous system • Data assimilation • Spatially distributed (vs. lumped), physics-based model • Integration of multiple data sources (satellite and ground-based) and corresponding state variables • Spatially-distributed weather forecasts • Multiple temporal scales • Downscaling • Ensembles • Development of nationally consistent and autonomous system • Multiple spatial scales (subbasin – basin) • Multiple temporal scales (day-ahead to seasonal) • Consistent methodology and input datasets for national application

9. Next Steps • Project Plans and Schedule • Refine forecast requirements from operators and study team • Integrate forecast system within Water Use Optimization Toolset • Refine forecast system for improved application in demonstration basins • Evaluate performance and benefit to water use optimization • Next Steps • DOE and hydropower industry forecast requirements • Traditional objectives • Renewable integration • Climate variability/change • Continue interaction with NOAA National Weather Service Office of Hydrologic Development • Calibration of ensemble weather forecasts • Automated data assimilation • Future integration into NWS Community Hydrologic Prediction System • DOE-NOAA MOU