1. Applications of macroscale hydrologic models for water cycle monitoring and streamflow prediction Andy Wood Civil and Environmental Engineering Seminar Civil and Environmental Engineering University of Washington April 6, 2006

2. Outline  Macroscale hydrologic modeling  Seasonal forecasting system  overview  sample results  Hydrologic monitoring system  overview  sample results  Interactions, Current and Future

3. Macroscale Hydrologic Modeling  Much of hydrologic theory and practice has been developed at point or bench scale, and at catchment scales.  Early hydrologic models applied over sub-catchment scales, and this is still the most common application today.  These models strike a balance between physical and calibrated parameter inputs Mastin & Vaccaro, 2002, USGS Open File Report 02-404

4. Macroscale Hydrologic Modeling  Macroscale hydrologic models grew out of a need for improved surface representations in general circulation models (GCMs)  Tend to be “flat earth” models  Also contain a mix of measured and calibration parameter inputs

5. The Land-Surface Water Budget EP W Q (Near Surface) Water Balance Equation Almost all hydrologic models have a water budget, e.g., Q: runoff (which may become streamflow) P: precipitation E: evaporation W: water storage There is an enormous range in complexity in how the terms are calculated

6. VIC Hydrologic Model Developed over last 12 years Includes an optional energy budget closure at each time step Multiple vegetation classes in each cell Sub-grid elevation band definition (for snow) Subgrid infiltration/runoff variability Operates at 1 hour and longer timesteps

7. What does a 1/8 degree pixel look like in real life?

8. Precipitation - the best measured U.S. Station density: 1 per 700 km 2 Ameriflux (flux towers) measure E, since mid 1990’s Water Budget: Q = P – E – dW/dt Source: A. Robock, Rutgers U. Top 1-m soil moisture measurements Snow water equivalent obs.

9. Runoff (Streamflow) Observations: Calibration Streamflow in the U.S. measured at roughly 7,000 active gauging stations. Most stations represent regulated flow conditions Source: U.S.G.S.

10. Outline  Macroscale hydrologic modeling  Seasonal forecasting system  overview  sample results  Hydrologic monitoring system  overview  sample results  Interactions, Current and Future

11. The importance of Seasonal Hydrologic Forecasting water management hydropower irrigation flood control water supply fisheries recreation navigation water quality AugDecApr Reservoir Storage Aug

12. How does one make a forecast of river flow?  Naïve forecast (“climatology”) – simply use historical averages  Persistence (or anti-persistence)  (Multiple) Regression Forecast  Traditional Predictors:  snowpack (SWE), accumulated precipitation, current or past river flow, measured over the drainage basin  More advanced predictors:  ENSO state indicators (Nino3.4, SOI)  Predictand: daily, monthly or seasonal streamflow at some lead time in the future.  Model-based approaches

13. Snow water content on April 1 April to August runoff McLean, D.A., 1948 Western Snow Conf. SNOTEL Network Introduction: Hydrologic prediction and the NRCS PNW

14. Technical Advances related to Hydrologic Forecasting 1920s1930s1940s1950s1960s1970s1980s1990s2000s snow survey / graphical forecasts / index methods / i.e., regression computing in water resources aerial snow surveys SNOTEL network ESP method snow cats conceptual hydrologic models

15. Introduction: Hydrologic prediction and ESP NWS River Forecast Center (RFC) approach: rainfall-runoff modeling (i.e., NWS River Forecast System, Anderson, 1973 offspring of Stanford Watershed Model, Crawford & Linsley, 1966) Ensemble Streamflow Prediction (ESP) used for shorter lead predictions; ~ used for longer lead predictions Currently, some western RFCs and NRCS coordinate their seasonal forecasts, using mostly statistical methods. ICs Spin-upForecast obs recently observed meteorological data ensemble of met. data to generate forecast ESP forecast hydrologic state

16. Results for Winter 2003-04: volume runoff forecasts UPPER HUMBOLDT RIVER BASIN Streamflow Forecasts - May 1, 2003 Forecast Pt============ Chance of Exceeding * =========== Forecast90%70%50% (Most Prob)30%10%30 Yr Avg Period(1000AF) (% AVG.)(1000AF) MARY'S R nr Deeth, Nv APR-JUL12.3 18.7 23 59 27 34 39 MAY-JUL4.5 11.3 16.0 55 21 28 29 LAMOILLE CK nr Lamoille, Nv APR-JUL13.7 17.4 20 67 23 26 30 MAY-JUL11.6 15.4 18.0 64 21 24 28 N F HUMBOLDT R at Devils Gate APR-JUL5.1 11.0 15.0 44 19.0 25 34 MAY-JUL1.7 7.2 11.0 50 14.8 20 22

17. Technical Advances related to Hydrologic Forecasting 1920s1930s1940s1950s1960s1970s1980s1990s2000s snow survey / graphical forecasts / index methods / i.e., regression computing in water resources satellite imagery aerial snow surveys desktop computing SNOTEL network ESP method ENSO / seasonal climate forecasts snow cats Internet / real-time data conceptual hydrologic models physical hydrologic models

18. UW Forecast System Website

19. UW Forecast Approach Overview NCDC met. station obs. up to 2-4 months from current local scale (1/8 degree) weather inputs soil moisture snowpack Hydrologic model spin up SNOTEL Update streamflow, soil moisture, snow water equivalent, runoff 25 th Day, Month 0 1-2 years back LDAS/other real-time met. forcings for spin-up gap Hydrologic forecast simulation Month 6 - 12 INITIAL STATE SNOTEL / MODIS* Update ensemble forecasts ESP traces (40) CPC-based outlook (13) NCEP CFS ensemble (20) NSIPP-1 ensemble (9) * experimental, not yet in real-time product

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

21. Assimilation Method weight station OBS’ influence over VIC cell based on distance and elevation difference number of stations influencing a given cell depends on specified influence distances spatial weighting function elevation weighting function SNOTEL/ASP VIC cell Forecast System Initial State Snow Adjustment distances “fit”: OBS weighting increased throughout season OBS anomalies applied to VIC long term means, combined with VIC- simulated SWE adjustment specific to each VIC snow band

22. Streamflow Forecast Results: Westwide at a Glance

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

24. Streamflow Forecast Results: Spatial SWESoil MoistureRunoffPrecipTemp Apr-06 May-06 Jun-06

25. Results for Winter 2003-04: streamflow hydrographs By Fall, slightly low flows were anticipated By winter, moderate deficits were forecasted

26. Results for Winter 2003-04 : volume forecasts for a sample of PNW locations

30. Scientific and Engineering Aspects  The forecast system involves many engineering challenges  There are also important science questions:  Can climate forecast advances be harnessed to advance hydrologic forecasting?  Can remote sensing advances yield enough information to improve hydrologic simulation?  What role should data assimilation have in hydrologic prediction?  How can model-based systems help us understand hydrologic (and climate) variability?  How well can our models account for uncertainty?

31. Testbed work: Using Climate Forecasts

32. Testbed work: MODIS snow cover assimilation Snowcover BEFORE update Snowcover AFTER update MODIS update for April 1, 2004 Forecast snow added removed

33. Outline  Macroscale hydrologic modeling  Seasonal forecasting system  overview  sample results  Hydrologic monitoring system  overview  sample results  Interactions, Current and Future

34. ½ degree VIC implementation Free running since last June Uses data feed from NOAA ACIS server “Browsable” Archive, 1915- present UW Real-time Daily Nowcast SM, SWE (RO) We are currently migrating the daily update methods to the west-wide forecast system (1/8 degree)

35. The challenge of changing observing systems 1920s1990s Meteorological stations that still report in real time today

36. Surface Water Monitor Archive July 2002: the western U.S. drought centers on Colorado March 1997: La Nina conditions bring the highest recorded snowfall to the PNW

37. Surface Water Monitor Archive August 1993: the highest recorded flow on the Mississippi R. March 2002: Virginia experiences severe drought, many well failures

38. Current exploration that combines the two projects modes of variability can we use the modes of variability to predict summer streamflow?

39. Outline  Macroscale hydrologic modeling  Seasonal forecasting system  overview  sample results  Hydrologic monitoring system  overview  sample results  Interactions, Current and Future

40. “User” Interactions associated with these research applications UW Hydrologic Forecast and Nowcast Systems U. Arizona / USBR forecast study, Lower Colorado basin NWS Hydrologic Ensemble Prediction Experiment 3TIER Environmental Forecast Group NRCS National Water and Climate Center NOAA Climate Prediction Center’s US Drought Outlook Miscellaneous: Seattle City Light, energy traders, hydropower utilities, NOAA regional climate offices UW Rick Palmer Group Puget Sound region flow forecasts UW Climate Impacts Group (CIG) Annual Water Outlook meetings NOAA National Centers for Environmental Prediction (NCEP) testbed activities Columbia River Inter-tribal Fish Commission Klamath R. Basin Bureau of Reclamation UCI / California Dept of Water Resources WA State Dept of Ecology & Yakima R. Basin Bureau of Reclamation new US Drought Monitor Princeton University Hydrologic Forecast System

41. Current Activities: Pilot basin operational efforts Two basin-focused water resources forecast efforts just beginning  operational streamflow and hydrologic forecasting in the Yakima R. Basin  NOAA-supported (SARP program, 2 years, starts in April)  collaborate with USBR; target reservoir operations & water allocations for irrigation, and also state-level drought planning  operational streamflow and hydrologic forecasting in the Klamath R. basin and in California (initially the Feather R. basin).  NASA-supported (CAN decision support, 3 years, with UCI)  collaborate with USBR, CADWR  incorporate MODIS snowcover in initial state estimation, and use satellite based crop ET as well.

42. Current Activities: Pilot basin operational efforts For both projects, model resolution in target basins is increasing to 1/16 degree lat-lon resolution The Yakima R. Basin, within WA State domain for SARP project

43. Acknowledgements Dennis Lettenmaier, UW Phil Pasteris, Tom Pagano, Tom Perkins (NRCS Nat. Water & Climate Center) Graduate Students, Post-Docs and Research Staff Ali Akanda George Taylor Niklas Christensen Kathy Devlin Ted Bohn, Nathalie Voisin, Darren Wilton Kaiyun Li Alan Hamlet Ed Maurer Other Advice: Rick Palmer, Steve Burges, Anne Steinemann Major Federal Funding Sources: NASA, NOAA

44. Questions? Websites: www.hydro.washington.edu / forecast / westwide / www.hydro.washington.edu / forecast / monitor / Email: Andy Wood: aww@u.washington.edu

45. How does one make a forecast of river flow?

46. Climate Forecasts : Bias Issue (prior NCEP model) Sample GSM cell located over Ohio River basin obs prcp GSM prcp obs temp GSM temp JULY Regional Bias: spatial example obs GSM

47. Climate Forecasts: Bias Correction Scheme from COOP observations from GSM climatological runsraw GSM forecast scenario bias-corrected forecast scenario month m

48. Validation with Illinois Soil Moisture 19 observing stations are compared to the 17 1/8º modeled grid cells that contain the observation points. Persistence Moisture Level Moisture Flux Variability