US Army Corps of Engineers BUILDING STRONG ® Omaha Districts Inflow Forecast Regression Analysis Carrie Vuyovich and Steven Daly ERDC-CRREL Cold Regions Res. and Engr. Lab. (CRREL) U.S. Army Corps of Engineers January 2011

BUILDING STRONG ® Overview Background  Multiple linear regression analysis to forecast spring inflows to reservoirs  6 snow-dominated watersheds  Monthly forecasts beginning in January Goals  Update regressions with recent data, improve accuracy  Develop better estimate of SWE  Work towards a more automated process  Identify possible climate trends

BUILDING STRONG ®

Parameters Q (10 6 ac-ft) = Forecasted total volume inflow to reservoir (+ Holdouts) SWE (in) = Average station SWE on first of month ANTQ (10 6 ac-ft) = Total antecedent inflow from Oct – Nov of previous year (+ Holdouts) ANTPREC (in) = Total annual precipitation in previous year P (in) = Total precipitation since beginning of year Holdout Calculation:

BUILDING STRONG ® Canyon Ferry Average monthly total precipitation (in) Area = 15,886 mi 2 Average Apr-Jul total volume inflow = 1.9 M ac-ft (2 M ac-ft Natural) Average Oct-Nov total volume inflow = 0.56 M ac-ft (0.56 M ac-ft Natural)

BUILDING STRONG ® Canyon Ferry

BUILDING STRONG ® Clark Canyon Average monthly total precipitation (in) Area = 2,315 mi 2 Average Apr-Jul total volume inflow = 0.08 M ac-ft (0.09 M ac-ft Natural) Average Oct-Nov total volume inflow = 0.04 M ac-ft (0.05 M ac-ft Natural)

BUILDING STRONG ® Clark Canyon

BUILDING STRONG ® Tiber Average monthly total precipitation (in) Area = 4,724 mi 2 Average Apr-Jul total volume inflow = 0.43 M ac-ft Average Oct-Nov total volume inflow = 0.04 M ac-ft

BUILDING STRONG ® Tiber

BUILDING STRONG ® Yellowtail Average monthly total precipitation (in) Area = 19,693 mi 2 Average Apr-Jul total volume inflow = 1.0 M ac-ft (1.4 M ac-ft Natural) Average Oct-Nov total volume inflow = 0.30 M ac-ft (0.32 M ac-ft Natural)

BUILDING STRONG ® Yellowtail

BUILDING STRONG ® Boysen Average monthly total precipitation (in) Area = 7,750 mi 2 Average Apr-Jul total volume inflow = 0.56 M ac-ft (0.6 M ac-ft Natural) Average Oct-Nov total volume inflow = 0.11 M ac-ft (0.11 M ac-ft Natural)

BUILDING STRONG ® Boysen

BUILDING STRONG ® Glendo Average monthly total precipitation (in) Area = 15,562 mi 2 Average Apr-Jul total volume inflow = 0.60 M ac-ft (0.88 M ac-ft Natural) 0.14 M ac-ft below Alcova Average Oct-Nov total volume inflow = 0.13 M ac-ft (0.09 M ac-ft Natural) 0.03 M ac-ft below Alcova

BUILDING STRONG ® Glendo

BUILDING STRONG ® Percent Error

BUILDING STRONG ® Percent Error *2011 Yellowtail forecast of Actual reservoir inflow for Apr – Jul (USACE and BoR) USACE Forecast for May-Jul, includes holdouts from Boysen, Buffalo Bill and Bull Lake

BUILDING STRONG ® Percent Error

BUILDING STRONG ® Automation Goals: Link regression equations, data and statistics to final forecast sheet Links to data sources (semi-automated) Limit data entry and calculation errors Easily transfer regression coefficients each year Easily transfer annual data to regression analysis workbook

BUILDING STRONG ® 2011 Issues  Late snowfall in April ► Switched from 1 Apr SWE to Max(1 Apr, 1 May)  Real-time precipitation data ► Difficult to automate  Canyon Ferry results ► Not capturing complete water balance by the end of the season

BUILDING STRONG ® Proposed Improvements to Inflow Forecasting  Daily estimates of forecasted inflow for monitoring ► Need to automate regression analysis and data stream  Climate change impacts to regression analysis ► Temperature appears to be increasing, Precipitation neither increasing or decreasing ► Changes in climate will reduce the accuracy of regressions over time ► Limit data used in analysis to recent years rather than entire period of record

BUILDING STRONG ® Proposed Improvements to Inflow Forecasting  Further investigation of better SWE estimation ► Test in different basins ► Field measurements to better understand distribution of snow Canyon Ferry

BUILDING STRONG ® Proposed Improvements to Inflow Forecasting  Passive Microwave Satellite Observations of SWE in the Great Plains ► Algorithms developed in Great Plains region of Canada. ► Shown promising results in Red River of the North Basins ► Independent estimate of SWE, available real-time ► Long period of record (1987 – present) ► Evaluate by comparison to NOHRSC, ground and flight observations, hydrologic analysis

BUILDING STRONG ® Proposed Improvements to Inflow Forecasting  Passive Microwave detection of snowmelt and runoff ► Affected by presence of wet snow ► Research into detection of “ripe” snow and rain-on-snow events ► May provide information on timing of melt and flood forecasting  Hydrologic Analysis of Plains snowpack ► Correlation between timing and volume to SWE in Plains to discharge ► Terrain-state modeling ► Statistical analysis/rank-order

BUILDING STRONG ® Thank you