Water Management: Water Supply Forecasting (Lettenmaier)

1. Water Management: Water Supply Forecasting (Lettenmaier) Improvingwater resources management in the western U.S. through use of remote sensing data and seasonal climate forecasts Lead PI: Dennis P. Lettenmaier (U. of Washington) Co-Is: Sooroosh Soorooshian (U. of California-Irvine) Andrew W. Wood (U. of Washington) Anne Steinemann (U. of Washington) Bisher Imam (U. of California-Irvine) Partners: USDA NRCS National Water and Climate Center Bureau of Reclamation California Department of Water Resources

2. Water Management: Water Supply Forecasting (Lettenmaier) Science / Applications Questions • The science and applications questions of the proposed project are highly relevant to NASA ASP Water Management element objectives: • Can advanced hydrologic prediction methods that use state of the art climate forecasts and snow remote sensing to update hydrologic initial conditions result in improved seasonal streamflow forecasts and in turn more efficient water management in the snowmelt-dominated rivers of the western U.S.? • 2) Can the efficiency of water management in the Klamath and Sacramento River basins be improved through the use of real-time estimates of crop water requirements, which can be estimated accurately using remote sensing data?

3. Water Management: Water Supply Forecasting (Lettenmaier) • Earth System Models • Land Surface Models: • VIC: • Land Surface Model • Data Assimilation Target • Watershed Hydrology • Coupled L-A-O Models: • (1) NSIPP/GMAO Predictions/Forecasts • Decision Support Systems, Assessments, Management Actions • Analyses • Two tracks, in parallel for research / operations: • real-time (current) nowcast/forecast evaluation • Retrospective nowcast/forecast evaluation • Assessment of skill contributed by ES Models & Observations relative to operational baseline. • Decision Support Tools • VIC-OMS-WHFS Combo • In house BOR reservoir project model (Klamath) • CADWR/SWP Delta Coordinated Operations model (at Joint Operations Center) • Decisions / Actions • Water Allocations for myriad uses, WY Type declarations • Water Banking (Klamath) • Risk Communication Value & Benefits to Society Quantitative and qualitative benefits from improved decisions Improved characterizations of: (a) current hydrologic conditions (b) evolving water year outlook Greater efficiency and reduced uncertainty in water allocation decisions Improved communication of uncertainties in decisionmaking Reduced conflict over water by stakeholders Increased confidence in federal & state agency decision-making and policy Information products Seasonal Precipitation / Temperature Ensemble Forecasts Streamflow Forecasts Monthly Volumes Summer Runoff Uncertainties Spatial Nowcasts & Forecasts: Snow Cover Snow Water Equivalent Soil Moisture Runoff Evapotranspiration Reservoir Evaporation Crop Water Demand Earth Observations Surface Temperature: Co-Op, MODIS, GMAO hindcasts/forecasts Precipitation: Co-op, GMAO hindcasts/forecasts Snow Cover: MODIS Snow Quantity: NRCS Snotel, CADWR Snow Pillow Surface Radiation/ET/Temp: MODIS Observations, Parameters & Products

4. University of Washington Forecast System At UW, started testing hydrologic uses of real-time climate forecasts in 2000, for East Coast Started producing water supply forecasts in 2001 Started testing snow assimilation techniques in 2003 Launched SW Monitor in 2005

5. UW Hydrologic Forecast System Snowpack Initial Condition Soil Moisture Initial Condition

6. soil moisture snowpack streamflow, soil moisture, snow water equivalent, runoff local scale (1/8 degree) weather inputs INITIAL STATE VIC Hydrologic model spin up Hydrologic forecast simulation NCDC met. station obs. up to 3 months from current LDAS/other real-time met. forcings for spin-up gap ensemble forecasts ESP traces CPC-based outlook NCEP CFS ensemble NSIPP-1 ensemble Observed SWE Assimilaton SNOTELUpdate 25th Day, Month 0 1-2 years back Month 12 UW Forecast Approach Schematic VIC = Variable Infiltration Capacity macroscale hydrologic model of Liang et al. (1994)

7. UW Forecast System: Spatial Products Precip Temp SWE Runoff Soil Moisture Apr-06 May-06 Jun-06

8. Streamflow Forecast Results: Westwide at a Glance

9. Clicking the stream flow forecast map also accesses current basin-averaged conditions Streamflow Forecast Details Flow location maps give access to monthly hydrograph plots, and also to raw forecast data.

10. Real-time Daily Nowcast SM, SWE (RO) ½ degree VIC implementation Free running since last June Uses data feed from NOAA ACIS server “Browsable” Archive, 1915-present We are currently migrating the daily updating approach to finer resolution project domain models

11. UW snow data assimilation activities MODIS snow covered area assimilation test in Snake R. Basin

12. Interactions: NRCS NWCC Since last year, we have exchanged nowcast/forecast results with the NRCS National Water and Climate Center (head: Phil Pasteris) • Under a Memorandum of Understanding between NRCS & UW: • UW provides forecast results and data as NRCS requests • NRCS provides access to stream flow and climate data (primarily via NOAA ACIS) • NRCS has created a place for links to “experimental water supply forecasts” from its official website. Currently the UW is the only one, and they would like more! • We generally attempt to schedule a “pre-forecast” conference call just prior to NRCS coordination of forecasts with NWS RFCs, in which we summarize our forecast outlooks and compare notes. • In addition, there is a good deal of informal exchange.

13. Interactions: NWS Via Kevin Werner of the West. Reg. Sci. Center, with support initially from CBRFC, but now also CNRFC and PNRFC: • Setting up 5 HEPEX* basins for evaluations of retrospective forecasts by VIC (ESP, ESP-ENSO, CPC) with NWSRFS retrospective ESPs (and with statistical forecasts). NRCS will also be involved. • Participation in NWS-led HEPEX (Hydrologic Ensemble Prediction Experiment): e.g., Western US testbed on snow data assimilation is led by: • Frank Weber (BC Hydro), Kevin Werner (NWS), Tom Pagano (NRCS), Andy Wood (UW) Other interactions:U. Ariz / BuRec (Lower Colorado); CPC; NCEP; WA State / BuRec (Yakima R.)

14. Water Management: Water Supply Forecasting (Lettenmaier) Domain • Upper Klamath Basin • UK Lake supplies Klamath Project irrigation • competing uses: instream flows, hydropower, tribal water rights • Feather R. Basin • 16 dams, largest Lake Oroville • operated by DWR for ag & urban WS • competing uses: flood control, hydropower, wat. qual., recreation, F&W Feather R. Basin

15. Water Management: Water Supply Forecasting (Lettenmaier) Approach / Tasks • Task 1: Klamath River forecast system enhancements (UW) • Tailoring components of WHFS to Klamath R. basin, increasing model resolution to 1/16 degrees, implementing MODIS-SCA assimilation, streamlining WHFS framework for acceptance in user environments • Task 2: Upper Klamath Lake net inflow calculation (UW) • Flow forecast impairment to reflect the effects of crop water use (evapotranspiration) and reservoir evaporation -- both satellite-based -- and also ungaged local runoff • Task 3: Forecast system implementation for Sacramento River (UCI) • Tailoring components of WHFS to CA DWR river basins, beginning with the Feather R.; implementing MODIS-SCA assimilation, streamlining WHFS framework for acceptance in CA DWR environment • Task 4: Forecast impairment in Sacramento basins (UCI) • Linkage of WHFS forecast products to CA DWR decision models (a sequence starting with forecast impairment, and leading to water allocations)

16. Water Management: Water Supply Forecasting (Lettenmaier) Approach / Tasks • Task 5: Forecast communication (UW/UCI) • Facilitate NWCC, USBR, and DWR review of the forecast system via reports for regular, real-time forecast updates and any system upgrades; conference calls to interpret the results, and, during the off-season, one-day workshops at partner offices to evaluate forecast system performance and use. • Task 6: Retrospective assessment (UW / UCI) • Perform retrospective forecasts made in a manner consistent with real-time operation, and evaluate changes in forecast skill due to incorporation of remote sensing data, and ensemble climate forecasts. • Task 7: Transition to operations (UW / UCI) • Train operational staff and prepare documentation manuals that will enable NWCC and DWR to operate the forecast system independently.

17. Water Management: Water Supply Forecasting (Lettenmaier) Metrics • Forecast Accuracy and DSS Performance • Traditional accuracy measures and skill scores (on-going) • Operator-defined criteria that represent “not making mistakes” (years 2 & 3) • User acceptance and organizational assimilation • User perspectives on: forecast usefulness, ease of understanding, compatibility with operations, presentation of probabilistic information (years 2 & 3) • Research team management • Journal articles, conference activity, prototype demonstrations, adherence to task schedule (end of years 1, 2 and 3)

18. Water Management: Water Supply Forecasting (Lettenmaier) Status Tasks 1 & 3: Operationalizing the use of MODIS snow cover imagery We are investigating pathways toward reliable real-time acquisition of MODIS snow cover (maximum 1-day lag time). It appears that Tom Painter at NSIDC will work with us to resolve lag-time issues with their real-time product, and establish an autoated pipeline for datasets.

19. Water Management: Water Supply Forecasting (Lettenmaier) Status Tasks 1 & 3: Streamlining / tailoring system to operational environments We have implemented 2 new forecasts points in the Klamath R. Basin (on the major tributaries to Upper Klamath Lake as part of the westwide system). Based on our calibration experiences, we’re now re-implementing the models for this approach at 1/16 degrees:

20. Water Management: Water Supply Forecasting (Lettenmaier) Status Tasks 1 & 3: Streamlining / Tailoring system to operational environments

21. Water Management: Water Supply Forecasting (Lettenmaier) Status • Tasks 1 & 3: Streamlining / tailoring system to operational environments • NRCS NWCC is moving programmatically toward a USDA-ARS led platform/effort called the Object Modeling System (OMS): • After meeting with NWCC, we have opened an official project “VIC Model” with OMS developers to port VIC into OMS. • OMS appears to derive some genetic material from USGS-MMS, which is used in tandem with RiverWare in a number of places. • http://oms.ars.usda.gov/

22. Water Management: Water Supply Forecasting (Lettenmaier) Questions?