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Return Flow Discussion

This presentation by Stacey Taylor at the ESHMC meeting on March 6, 2008, provides a comprehensive overview of return flow data analyses from the Big and Little Wood Rivers (IESW007) and Richfield (IESW054). It discusses historical data, ongoing Snake River return data, and various calculation methods for determining returns from diversions. Additionally, the presentation includes regression analysis and graphical representations of diversions and returns over time. Key conclusions suggest that current methods using a linear approach may offer the best estimates for return flows.

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Return Flow Discussion

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  1. Return Flow Discussion ESHMC Meeting 6 March 2008 Presented by Stacey Taylor

  2. Overview • Bryce Contor’s slides • Historical data analysis: • IESW007 (Big and Little Wood Rivers) • IESW054 (Richfield) • Ongoing Snake River return data (groups) • General conclusions

  3. Current Calculation Method Returns = b1* Diversions (one equation for each entity) Returns Diversions

  4. Alternate Methods Alternate Method (1) Alternate Method (2) Returns = -bo+ b1* Diversions) (one equation for each entity) Returns = logarithmic function (one equation for each entity) Returns Diversions Returns Returns = bo (one equation for each entity) Returns Alternate Method (3) Alternate Methods (4) and (5) Returns = exponential function (one equation for each entity) Returns OR Returns = bo + b1* Diversions (one equation for each entity) Diversions Diversions Diversions

  5. Raster Graphics • Created several raster graphics to represent returns and diversions for IESW007 and IESW054 • Different colors represent different diversions/returns.

  6. Example Raster (1) Diversion 1,000 ac-ft 1928 0 Water Year 5 10 15 2004 20 Oct. Sept. Month

  7. Example Raster (2) Diversion 1,000 ac-ft 1928 0 Water Year 5 10 15 2004 20 Oct. Sept. Month

  8. Example Raster (3) Diversion 1,000 ac-ft 1928 0 Water Year 5 10 15 2004 20 Oct. Sept. Month

  9. IESW007 Total Diversions(Big and Little Wood Rivers) Diversion (1,000 ac-ft) Water Year 0 1928 10 1940 20 30 1950 40 1960 50 1970 60 1980 70 80 1990 90 2004 10 11 12 1 2 3 4 5 6 7 8 9 Month

  10. IESW007 Total Returns(Big and Little Wood Rivers) Return (1,000 ac-ft) Water Year 1928 0 0.1 0.2 1940 0.3 0.4 1950 0.5 0.6 0.7 1960 0.8 0.9 1970 1.0 1.1 1980 1.2 1.3 1990 1.4 1.5 1.6 1.7 2004 10 11 12 1 2 3 4 5 6 7 8 9 Month

  11. IESW054 Total Diversions(Richfield) Diversion (1,000 ac-ft) Water Year 0 1928 1940 1950 10 1960 1970 20 1980 1990 30 2004 10 11 12 1 2 3 4 5 6 7 8 9 Month

  12. IESW054 Total Returns(Richfield) Return (1,000 ac-ft) Water Year 0 1928 1940 1950 1960 5 1970 1980 10 1990 20 2004 10 11 12 1 2 3 4 5 6 7 8 9 Month

  13. Cumulative Return vs. Cumulative DiversionIESW054 (Richfield)

  14. What Caused the Change? • Change in slope of cumulative plots • Possibly related to conversion to sprinklers • Calibration data shows percentage these increases: • IESW007 – May 1980 to May 2002 sprinkler % increased from 14.7% to 28.0%(13% increase) • IESW054 – May 1980 to May 2002 sprinkler % increased from 31.9% to 59.7% (28% increase) • Aerial photography covering the area encompassed by both entities has been requested for 1969 and 1977

  15. Regression Analysis • A regression analysis was performed on each set of data (1928-1950, 1951-1970, etc) • P-values were found for each intercept and slope (95% confidence interval) • Given shared ranges between each set of data, a general equation may describe both entities (IESW007 and IESW054)

  16. IESW007 Intercepts and Slopes(Based on 95% CI) Shared intercept range: -3.76 to -3.67 Shared slope range: 0.0173 to 0.0235 y = 0.02x – 3.70

  17. IESW054 Intercepts and Slopes(Based on 95% CI) No shared slope range between all sets; 1981-2004 slope is negative Shared slope range: 0.170 to 0.177 y = 0.17x - ???

  18. Ongoing Snake River Return Data • Group data for 2002-2006 were compared to IESW007 and IESW054 • Plotted returns vs. diversions • Plotted returns vs. normalized diversion (Normalized diversion = diversion/max diversion of single entity) • Plotted normalized returns vs. normalized diversions

  19. Returns vs. Diversions for Separate Entities

  20. Returns vs. Normalized Diversion

  21. Conclusions • Current technique of assuming straight line plot with zero intercept may still be best (Returns = b1*Diversions) • Slope (b1) based on historical data OR lag factors (depends on which is available) • Slope may be better estimated with inclusion of latest data

  22. Discussion

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