1. Helper Variables Why do we want them? How do we create them? What to avoid with them? Tom Pagano tom.pagano@por.usda.gov 503-414-3010

2. Why helper variables? The target (i.e. predictand) time series may have holes in important years or a short period of record. If that data is easily estimated, filling the gaps may lead to a better, or at least more honest, forecast.

3. Sargents is missing during a hydrologically interesting period. This is also the period of most of our predictors (i.e. SNOTEL). Gunnison could be used to fill in gaps. Why?

4. Sargents is missing during a hydrologically interesting period. This is also the period of most of our predictors (i.e. SNOTEL). Gunnison could be used to fill in gaps. Strength of correlation very good Why?

5. Another example… seasonally operated gages

6. Correlation between mar-sep and apr-sep = 0.9996 No point in throwing away years where only march is missing.

7. Helper variable interface Neat stuff here but don’t touch if you don’t know what you’re doing. Default is unchecked.

8. Main ways to use helper variables Different station, same months: (Upstream vs downstream) Estimating one gage from another Same station, different months: (May-Jul vs Apr-Jul) Estimating longer time period from shorter Same station, months, different sources: (USGS vs AWDB) Estimating natural flow from observed

9. Helper not used

11. Helper vs target scatterplot Helper used Wider range of years… More stable relationship More consistent with nearby forecasts

12. Dangers of helper variables Statistically, we do not include the imperfect relationship between helper and original target in the final forecast error bounds. We are increasing our chances of overconfident forecasts. Therefore, it is best to only estimate a few years and only if the relationship is very good (e.g. r 2 >0.9)

13. Dangers of helper variables Statistically, we do not include the imperfect relationship between helper and original target in the final forecast error bounds. We are increasing our chances of overconfident forecasts. Therefore, it is best to only estimate a few years and only if the relationship is very good (e.g. r 2 >0.9) Consider too whether the relationship between the helper and the original target is stable versus time… For example… Use observed flow as helper to estimate natural flow. Have the regulations changed over time?