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Carrie Vuyovich and Steven Daly ERDC-CRREL

Omaha inflow forecasts based on snow regressions Second Annual Missouri Basin River Forecaster’s Meeting 15-17 November 2010. Carrie Vuyovich and Steven Daly ERDC-CRREL Cold Regions Res. and Engr. Lab. (CRREL) U.S. Army Corps of Engineers November 2010. Project overview.

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Carrie Vuyovich and Steven Daly ERDC-CRREL

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  1. Omaha inflow forecasts based on snow regressionsSecond Annual Missouri Basin River Forecaster’s Meeting15-17 November 2010 Carrie Vuyovich and Steven DalyERDC-CRREL Cold Regions Res. and Engr. Lab. (CRREL)U.S. Army Corps of Engineers November 2010

  2. Project overview Improve spring forecasts for reservoir inflow at 6 major basins Current method: • Monthly forecasts for 1 July inflow volume • 1JAN, 1FEB, 1MAR, 1APR • Developed in late 1980s • Multiple linear regression, based on: • Basin average SWE • Average spring (Apr – Jun) precipitation (5.73) • Antecedent flow (Oct – Nov) • Holdouts

  3. Project overview To improve forecasts: • Improve estimate of SWE • Update regression equations with recent data • Look for climate change trends in earlier snowmelt, rising temperatures, changes in precipitation

  4. Canyon Ferry

  5. Improve basin SWE estimate Methods to calculate basin SWE volume • Station Average • IDW • IDW adjusted for elevation trend in SWE Additional SWE regression parameters • Elevation • Latitude • Aspect • Regional Slope

  6. Station Average Total Basin SWE = n = number of reporting stations SWEi= SWE depth reported at SNOTEL station Average Max annual SWE

  7. Interpolation using Inverse Distance Weighting SWEj = AverageSWE depth in 1 km grid cell di,j= distance between station, i and grid cell, j Total Basin SWE = k = number of grid cells in basin

  8. Interpolation using IDW, adjusting for elevation LSWE= estimated rate of change of SWE with elevation Elevi= Elevation of SNOTEL station Elevj = Elevation of1 km grid cell Total Basin SWE = k = number of grid cells in basin

  9. Average 1 Apr SWE by Elevation • Other attributes showed little or no correlation with SWE, including: • Latitude • Aspect • Regional Slope

  10. Canyon Ferry Total Basin SWE estimates Calculated total basin SWE using SSM/I passive microwave data. SWE was significantly underestimated, most likely due to the saturation level of the satellite instrument.

  11. SWE Calculation statistics

  12. 1ST April SWE / Inflow Volume correlations

  13. Max annual accumulated precip

  14. Average annual temperature

  15. Multiple Linear Regression • Variables: • 1 Apr SWE • Antecedent Flow (Oct-Nov) • Previous years Max SWE • Apr – Jun Total Precipitation • Average Apr-Jun Total Precipitation (5.79 in) • Previous years total annual precipitation • Thiessen-weighted precipitation

  16. Canyon Ferry Multiple Linear Regression

  17. 1 Apr SWE 1 Apr SWE + antec inflow 1 Apr SWE + antec inflow + AMJ precip 1 Apr SWE + antec inflow + Prev yrs total precip

  18. Current work Estimation of SWE • Further analysis using SCA • Station weighting Multiple linear regression • Climate indices/NWS long-term forecast for additional information on spring precipitation • Holdouts • Calculate significance of parameters Climate Trends • Timing of precipitation • Regularly incorporate additional data to regression analysis Other basins • Similar SWE analysis • Update regressions New forecast techniques ready to test by 1 Jan 2011.

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