1. Long-term Trends in Water Supply Forecast Skill Tom.Pagano@por.usda.gov

2. Are there any long-term trends in April 1 st water supply forecast skill? If so, where, when and why?

3. What skill means here… sum(forecast – observed) 2 sum(average – observed) 2 Skill = 1 - +1.0 +0.5 0.0 -0.5 Perfect Could be better No better than guessing average Need to find a different job = 1 - MSE/VAR

4. 29 Study basins Long history of forecasts Still active Unregulated Also made “synthetic” hindcasts using snow and precip data in 35-km buffer Analysis also done on 140 unregulated HCDN basins

5. January April Westwide Official skill for period of record -.25 0.0.25.50.75 1.0 Not Good Not BadPerfect

6. Average skill of all sites over 20-yr moving window For the West, as a whole, skill peaked in ~1965-1985 then slumped afterwards Good Bad

7. Average skill of all sites over 20-yr moving window For the West, as a whole, skill peaked in ~1965-1985 then slumped afterwards “Synthetic” hindcasts reproduce this feature almost exactly Therefore it’s not the human forecaster Good Bad Good Bad

8. Recent skill anomalies Where has skill been going down? Mostly in Oregon, Colorado, AZ/NM Doing fine in CA/NV/UT +.15 0.0 -.15 -.30Worse than usual Better than usual

9. Conventional wisdom: Extreme years are harder to forecast. If streamflow variability goes up, so should error. So, has streamflow become “Wilder”?

10. Varieties of Year-to-Year Seasonal Streamflow Changes Less Variable More Variable years

11. Varieties of Year-to-Year Seasonal Streamflow Changes Less Variable Less Persistent More Persistent More Variable years

12. Of 137 stations around the western US Apr-Sept flow volumes: becoming increasingly variable* Variance End Year 20-yr moving window * at 10% significance level

13. End Year 20-yr moving window Of 137 stations around the western US Apr-Sept flow volumes: becoming increasingly variable* year-to-year persistence also high Variance Persistence Recently, most like: * at 10% significance level

14. Lake Powell Water Year Natural Inflow 1922-2004 1000’s acre-feet % of average

15. University of Washington VIC Model Simulated Soil Moisture Drier ---- Wetter Columbia above the Dalles Can see this in soil moisture too…

16. Whoa, hold on here a minute! In recent years, the streamflow persistence has gone up, driven by precipitation persistence.

17. Whoa, hold on here a minute! In recent years, the streamflow persistence has gone up, driven by precipitation persistence. But, classically, we assume all persistence/autocorrelation is “soil moisture”

18. Apr-Sep Flow last year Apr-Sep Flow this year 1983-2002 r=0.59 Blacksmith Fork, Utah

19. Apr-Sep Flow last year Apr-Sep Flow this year 1963-1982 1983-2002 r=0.59r=0.01 Blacksmith Fork, Utah

20. Since ~1980 western streamflows are the most variable and persistent in modern history However… Where variability is going up skill isn’t necessarily going down.

21. Colorado: Variability up Skill down Oregon: Variability down Skill down CA/NV: Variability up Skill up Variance ‘83-02 persistentAnti- persistent Much less variable than usual Much more variable than usual

22. Variance ‘83-02 Persistence ’83-02 Colorado: Variability up Skill down Oregon: Variability down Skill down CA/NV: Variability up Skill up Much less variable than usual Much more variable than usual persistentAnti- persistent

23. Another possibility for rise in error… Biggest source of April 1 st forecast error: Extreme (wet or dry) spring precipitation Perhaps spring precipitation is becoming more extreme?

24. “Spring Precip Irregularity” defined as… Apr 1 to end of season precip Z-score for each station, averaged across a basin. Index is squared and averaged over 20-year periods. Similar to variance but better Low variability, high irregularity

25. 20-year moving window Spring precipitation “irregularity” More than 1 = more extreme than usual Less than 1 = Calm, reliably near-normal

26. 20-year moving window Spring precipitation “irregularity” More than 1 = more extreme than usual Less than 1 = Calm, reliably near-normal Westwide average of 29 basins Calm Extreme

27. 1961-801981-00 Where is spring precip more irregular? Now, especially in PNW and Southwest, whereas before it was very calm This matches decline in forecast skill Calm Typical Extreme

28. In a nutshell: In CA/NV, extreme precip/snow is happening before April 1 st … Good for forecast skill. In Southwest, Colorado, Oregon extreme precip/snow is happening after April 1 st … Bad for forecast skill. Skill trends dominated by climate

29. Of course, the $100,000 question: or Will trend continue return to normal?

30. Are rising temperatures a problem for water supply forecasts? Or just a problem for water managers? Issues of climate non-stationarity

31. Basic Western US Hydrology Snow pack Soil water Snow Rainfall Highly Simplified Watershed Runoff snow precip runoff Pre-snowpack normals

32. Basic Western US Hydrology Snow pack Soil water Snow Rainfall Highly Simplified Watershed Runoff snow precip runoff Peak of snowpack

33. Basic Western US Hydrology Snow pack Soil water Snow Rainfall Highly Simplified Watershed Runoff snow precip runoff Snowmelt

34. A “What if?” for a warmer climate Soil water Snow Rainfall Runoff snow precip Snow pack runoff

35. A “What if?” for a warmer climate Early Melt Soil water Snow Rainfall Runoff runoff More water into soils by April 1 Early Runoff snow precip

36. A “What if?” for a warmer climate snow precip 2 1 To a statistical water supply forecast system that looks at Apr 1 snowpack as the predictor, these scenarios, An early melt to heavy snow The snow was never there are indistinguishable. However in one case the soil moisture is primed, the other not. Major implications for a forecast of Apr-Jul runoff! 2 1

37. Summary Skill trends evident, trends dominated by climate Flows more variable, persistent Spring precip is more extreme Need to reconsider assumptions about climate stationarity, in context of “soil moisture” Need to know how a warmed climate affects regression forecasts