Water Management: Water Supply Forecasting (Lettenmaier)Improving water 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 CenterBureau of ReclamationCalifornia Department of Water Resources

Science / Applications QuestionsWater Management: Water Supply Forecasting (Lettenmaier)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?

Earth System Models

Land Surface Models:VIC: Land Surface ModelData Assimilation TargetWatershed Hydrology

Coupled L-A-O Models:(1)NSIPP/GMAO

Value & Benefitsto SocietyQuantitative 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

Predictions/ForecastsObservations, Parameters & ProductsEarth Observations Surface Temperature: Co-Op, MODIS, GMAO hindcasts/forecastsPrecipitation: Co-op, GMAO hindcasts/forecastsSnow Cover: MODISSnow Quantity: NRCS Snotel, CADWR Snow PillowSurface Radiation/ET/Temp: MODISDecision Support Systems, Assessments, Management ActionsAnalysesTwo tracks, in parallel for research / operations:real-time (current) nowcast/forecast evaluationRetrospective nowcast/forecast evaluationAssessment of skill contributed by ES Models & Observations relative to operational baseline.Decision Support ToolsVIC-OMS-WHFS ComboIn house BOR reservoir project model (Klamath)CADWR/SWP Delta Coordinated Operations model (at Joint Operations Center)Decisions / ActionsWater Allocations for myriad uses, WY Type declarationsWater Banking (Klamath)Risk CommunicationWater Management: Water Supply Forecasting (Lettenmaier)Information products

Seasonal Precipitation / Temperature Ensemble Forecasts

Streamflow ForecastsMonthly VolumesSummer RunoffUncertaintiesSpatial Nowcasts & Forecasts:Snow CoverSnow Water EquivalentSoil MoistureRunoffEvapotranspirationReservoir EvaporationCrop Water Demand

University of Washington Forecast SystemAt 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

UW Hydrologic Forecast SystemSoil MoistureInitial ConditionSnowpackInitial Condition

UW Forecast Approach SchematicVIC = Variable Infiltration Capacity macroscale hydrologic model of Liang et al. (1994)

UW Forecast System: Spatial ProductsSWESoil MoistureRunoffPrecipTempApr-06

May-06

Jun-06

Streamflow Forecast Results: Westwide at a Glance

Streamflow Forecast DetailsFlow location maps give access to monthly hydrograph plots, and also to raw forecast data.

degree VIC implementation

Free running since last June

Uses data feed from NOAA ACIS server

Browsable Archive, 1915-presentReal-time Daily NowcastSM, SWE(RO)We are currently migrating the daily updating approach to finer resolution project domain models

UW snow data assimilation activitiesMODIS snow covered area assimilation test in Snake R. Basin

Interactions: NRCS NWCCSince 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 requestsNRCS 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.

Interactions: NWSVia 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.)

DomainWater Management: Water Supply Forecasting (Lettenmaier)Feather R. BasinUpper 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

Approach / TasksTask 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)

Water Management: Water Supply Forecasting (Lettenmaier)

Approach / TasksWater Management: Water Supply Forecasting (Lettenmaier)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.

MetricsWater Management: Water Supply Forecasting (Lettenmaier)Forecast Accuracy and DSS PerformanceTraditional accuracy measures and skill scores (on-going)Operator-defined criteria that represent not making mistakes (years 2 & 3)

User acceptance and organizational assimilationUser perspectives on: forecast usefulness, ease of understanding, compatibility with operations, presentation of probabilistic information (years 2 & 3)

Research team managementJournal articles, conference activity, prototype demonstrations, adherence to task schedule (end of years 1, 2 and 3)

StatusWater Management: Water Supply Forecasting (Lettenmaier)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.

StatusWater Management: Water Supply Forecasting (Lettenmaier)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, were now re-implementing the models for this approach at 1/16 degrees:

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

StatusWater Management: Water Supply Forecasting (Lettenmaier)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/

Questions?Water Management: Water Supply Forecasting (Lettenmaier)

Another new feature is that were now plotting up several analyses of snow observations, and these update on a daily basis. Weve been automatically downloading the data for a long time for use in our assimilation, and the goal here was to show the west-wide conditions at a single glance, something thats hard to find elsewhere.

Note, in addition to the NRCS snotel points, we also have the California DWR snow pillows, and the Env. Canada snow pillows in the Columbia R. drainage.There are about 5 plots some of which are for changes during the last week or two.

Here I typically say the system is implemented using VIC (wat/nrg balance model, etc.), and the spinup simulation produces an initial condition for snowpack and soil moisture over a domain of about 18,000 cells.This bubble plot shows the streamflow outlook for summer runoff for about 90 locations in the domain. The anomalies are consistent with those shown in the spatial plots, with the lowest outlooks for the SW streams nearest that very low SM pattern we saw 2 slides back, and normal outlooks in the PNW.

Note, this west-at-a-glance display, with both mouse-overs that show various anomalies for the locations, and clickable points that launch more details, is something we have only recently added.In addition to the streamflow hydrographs that weve had for a while, the clickable streamflow map now brings up the current water year conditions for P,T,SM,SWE, RO which are helpful in showing where we are with respect to climatology. These are averaged over the drainage basin contributing to streamflow at each location. Another area of current research relates to the surface water monitor developed last year by A. Wood. This system, applied at coarse (1/2 degree) resolution over the entire CONUS, is completely automated (free-running) and updates every day. Its just a prototype, demo project that have been unable to get funding to extend, and the main products are maps of current soil moisture & SWE, and an monthly archive that extends back to 1915, that also has SM & SWE maps.

Anyway, we are now adapting the daily update approach for use in the westwide forecast system, and should have the first basin (PNW) land surface conditions updating daily (at 1/8 degree) within the month. After that well move on to other basins, and probably extend the 1/8 nowcast eastward to the Mississippi R.We also have an on-going interaction with the NWCC, and exchange results and comments on a routine basis during the forecast season. Credit Phil Pasteris, Tom Pagano, Tom Perkins, Jolyne Lea.

Note that NWCC is experimenting with a modeling capability based on the USGS PRMS model.We also have an on-going interaction with the NWCC, and exchange results and comments on a routine basis during the forecast season. Credit Phil Pasteris, Tom Pagano, Tom Perkins, Jolyne Lea.

Note that NWCC is experimenting with a modeling capability based on the USGS PRMS model.