Combining statistical and dynamical methods for hydrologic prediction

1. Combining statistical and dynamical methods for hydrologic prediction Andy Wood Seminar Land Surface Hydrology Research Group Civil and Environmental Engineering University of Washington Dec 19, 2006

2. Outline • Ensemble Forecast Calibration • Synoptic Scale Hydrologic Indices

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

4. How does one make a forecast of river flow? • Naïve forecast (“climatology”) – simply use historical averages • Persistence (of states or anomalies) • (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

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

6. Results for Winter 2003-04: volume runoff forecasts

7. recently observed meteorological data ensemble of met. data to generate forecast ESP forecast Spin-up ICs Forecast obs hydrologic state 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.

8. Forecast Calibration: Hydrologic Simulation Uncertainty Simulation error results from: -- parameter uncertainty -- forcing uncertainty -- model physics/structure Techniques for addressing each exist: -- multi-algorithm approaches -- calibration science -- forcing preparation techniques Other approaches for improving simulation: -- data assimilation -- multi-model approaches -- bias-correction

9. Forecast Calibration: Effect of Uncertainty on ESP Model-based ensemble forecasts contain both “hydrologic uncertainty” (associated with the input data, model parameters & physics) and future climate uncertainty. ESP accounts mostly for the latter, but not the former, hence ESP forecasts have an inherent tendency to be overconfident. One approach that can be used to correct this is called forecast calibration.

10. Forecast Calibration: Overconfidence example

11. Forecast Calibration: Approach Following a technique suggested by John Schaake for 15-day temperature forecast ensembles: 1. use only forecast ensemble means 2. correlate forecast means with observations 3. reconstruct forecast uncertainty A hindcast dataset is needed for training of the parameters. Also: - correlation - mean and variance of hindcasts and observations

12. Forecast Calibration: hindcast dataset

13. Forecast Calibration: Approach Algorithm: hindcast long term mean obs long term mean correlation, obs & hindcast means one forecast mean one calibrated forecast mean obs long term std. dev hindcast long term std. dev correlation, obs & hindcast means obs long term variance calibrated forecast variance

14. Forecast Calibration: Results

15. Forecast Calibration: State Dependent Approach

16. Forecast Calibration: Raw ESP

17. Forecast Calibration: Results calib w/ entire hindcast calib w/ sample size N=35 bias-corr only

18. Forecast Calibration: Reliability Improved

19. Outline • Ensemble Forecast Calibration • Synoptic Scale Hydrologic Indices

20. UW 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 update methods to the west-wide forecast system (1/8 degree)

21. The challenge of changing observing systems Meteorological stations that still report in real time today 1920s 1990s

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

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

24. Water Year 2005

28. Land Surface Indices Can capture information from PC1 and PC2 using: NDX1 ~ PC1 = CNTR NDX2 ~ PC2 = NW-SW Then PCs or NDXs can be used in regression framework to predict future flow, e.g., summer runoff

29. Flow prediction results can we use the modes of variability to predict summer streamflow?

30. Flow prediction results

31. Take away message • The dream of a purely physical modeling based prediction system is unlikely to be realized due to uncertainties in data, parameters, physics and so forth. • Statistical techniques can work hand in hand with dynamical ones to move prediction applications forward.

32. Forecast Calibration: ESP N