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Advances in seasonal hydrologic prediction

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Presentation on theme: "Advances in seasonal hydrologic prediction"— Presentation transcript:

1 Advances in seasonal hydrologic prediction
Dennis P. Lettenmaier Department of Civil and Environmental Engineering University of Washington GEOSS Workshop XXXIII: Using Earth Observations for Water Management San Francisco December 18, 2009

2 Talk Outline Background
The University of Washington west-wide seasonal hydrologic forecast system Current and recent research -- assimilation of satellite data Is there hydrologically useful skill in climate forecasts? Concluding thoughts

3 1. Background: The importance of Seasonal Hydrologic Forecasting
water management hydropower irrigation flood control water supply fisheries recreation navigation water quality Aug Dec Apr Reservoir Storage

4 Application of statistical methods to seasonal hydrologic prediction in the western U.S.
PNW Snow water content on April 1 SNOTEL Network McLean, D.A., 1948 Western Snow Conf. April to August runoff

5 Overview: ESP Hydrologic prediction strategy
ESP data flow The ESP “spider web”

6 2. The University of Washington west-wide seasonal hydrologic forecast system
6-month ESP streamflow forecasts for western U.S. and Mexico effective 12/7/09

7

8 UW Seasonal Hydrologic Forecast System Website
Another new feature is that we’re now plotting up several analyses of snow observations, and these update on a daily basis. We’ve 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 that’s 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.

9 Forecast System Initial State information
Observed SWE Snowpack Simulated Initial Condition Soil Moisture Simulated Initial Condition

10 Streamflow Forecast Details
Clicking the stream flow forecast map also accesses current basin-averaged conditions Flow location maps give access to monthly hydrograph plots, and also to raw forecast data. In addition to the streamflow hydrographs that we’ve 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.

11 Streamflow Forecast Results: Westwide at a Glance
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.

12 3a: Current and recent research: Snow data assimilation

13

14

15 local scale weather inputs
MODIS updating of snow covered area local scale weather inputs Initial Conditions: soil moisture, snowpack Hydrologic model spin up Hydrologic simulation Ensemble Forecast: streamflow, soil moisture, snowpack, runoff NCDC met. station obs. up to 2-4 months from current LDAS/other real-time met. forcings for remaining spin-up MODIS Update 1-2 years back 25th Day of Month 0 End of Month Change in Snowcover as a Result of MODIS Update for April 1, 2004 Forecast Snowcover before MODIS update Snowcover after MODIS update

16 Unadjusted vs adjusted forecast errors, , for reservoir inflow volumes (left plot) and reservoir storage (right)

17 4: Is there hydrologically relevant skill in climate forcings

18 Wood et al 2005: Retrospective Assessment: Results using GSM
General finding is that NCEP GSM climate forecasts do not add to skill of ESP forecasts, except… April GSM forecast with respect to climatology (left) and to ESP (right)

19 Wood et al 2005: Retrospective results for ENSO years
Summary: During strong ENSO events, for some river basins (California, Pacific Northwest) runoff forecasts improved with strong-ENSO composite; but Colorado River, upper Rio Grande River basin RO forecasts worsened. October GSM forecast w.r.t ESP: unconditional (left) and strong-ENSO (right)

20 Reverse ESP vs ESP – typical results for the western U.S.
Columbia R. Basin fcst more impt ICs more impt Rio Grande R. Basin

21 DEMETER forecast evaluation
VIC model long-term ( ) simulations at ½ degree spatial resolution assumed to be truth DEMETER reforecasts with ECMWF seasonal forecast model for 6 month lead, forecasts made on Feb 1, May 1, Aug 1, Nov 9 forecast ensembles on each date Forecast forcings (precipitation and temperature) downscaled and bias corrected using Wood et al approach (also incorporated in UW West-wide system) On each forecast date, 9 ensemble members also resampled at random from to form ESP ensemble Forecast skill evaluated using Cp for unrouted runoff

22 Test sites

23 Missouri River at Fort Benton

24 Snake River at Milne

25 Concluding thoughts Hydrologic prediction skill at S/I lead times comes mostly from initial conditions. Hence more focus on data assimilation, and its implications for hydrologic forecast skill, needs more attention. The role of model error in hydrologic predictions needs more focus – how do we best weight land models in multimodel ensemble? Do hydrologists (and the land data assimilation community) need to expend more effort on hydrologic forecasting?

26 Streamflow forecast skill, observed streamflow simulated (left panel) and forecasted (right two) using model soil moisture and SWE; MAMJ streamflow conditioned on January 1 model conditions

27 7) Multimodel approaches

28 UW Multi-model monitor
Same approach as VIC-based SWM Models include VIC, Noah, CLM, Sac

29 The challenge: Different land schemes have different soil moisture dynamics
Model simulated soil moisture at cell (40.25N, W)

30 Areas for spatially averaged soil moisture percentiles
NW NE SW SE Box sizes are 5 x 5 degrees

31 NW

32 SE

33 Soil Moisture Percentiles w.r.t. 1920-2003
VIC CLM SAC NOAH ENSEMBLE US Drought Monitor

34 Summary West-wide forecast system and SW Monitor are templates for exploration of new forecasting methods Methods perform well in the U.S., where surface obs are relatively abundant. However, ongoing work illustrates the potential for using similar methods in areas where in situ obs are sparse, using e.g. remotely sensed precipitation, and/or weather prediction model analysis fields. New remote sensing data sources (e.g. SWOT) offer tremendous opportunities for extension of these methods to the underdeveloped world.

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