1. Recharge on Non-irrigated Land Mike McVay 06/24/2010

2. Our Process for Estimating Recharge. Our process for estimating recharge on non-irrigated land is to use ET Idaho data from 45 weather stations to calculate the amount of recharge based on precipitation, root zone moisture and soil type. Then we utilize semi-log kriging to interpolate the recharge data across the model domain.

3. Interpolation – Data Transformation Both Willem and I are employing semi-log kriging to interpolate the data. This involves a semi-log transform of the data in which values below a threshold are transformed logarithmically and those values above the threshold are transformed linearly. Transformation of data is necessary to avoid negative extrapolated values. Semi-log transformation employed. Prevents extrapolation of “small” numbers to negative values while maintaining linear behavior of “large” numbers. Threshold (α) of 0.001.

4. Interpolation - Kriging I have employed Geostatistical Analyst in ArcMap to Krige, Willem has written code. Ordinary Kriging – No trend in data, so no drift has been incorporated for interpolation. No nugget has been employed. Linear Variogram Model – Few data points over a large area precludes fitting a variogram model to data. Geostatistical Analyst does not support Linear Variogram, so a Spherical model has been employed with a very large range. Sites with no data have been ignored during Kriging.

5. Interpolation Comparison I have randomly chosen 30 month/soil-type combinations to compare interpolation results. My comparison of the results indicates that the Kriging methods that Willem and I have employed are very similar (see table on next slide).

6. Stress Period/Soil Type McVay Sum (ft) Schreuder Sum (ft) Diff (%McVay Sum) Abs Diff (%McVay Sum) Dec 2001 Lava1455.881455.670.01%0.0001 Nov 1984 Thin1149.731150.38-0.06%0.0006 Dec 1998 Thin459.68459.99-0.07%0.0007 May 1980 Thin1639.821638.590.08%0.0008 Jan 1982 Lava781.20780.420.10%0.0010 Dec 2004 Lava2158.852156.180.12%0.0012 May 1993 Lava1271.831269.690.17%0.0017 Sep 1993 Thick49.5449.62-0.17%0.0017 Sep 1997 Thin183.48183.80-0.17%0.0017 Aug 1999 Thin76.1276.26-0.18%0.0018 Sep 1994 Thick27.8527.790.21%0.0021 Aug 1989 Thick38.8438.760.22%0.0022 Jun 2003 Thin22.6522.74-0.36%0.0036 Feb 1990 Lava311.58310.330.40%0.0040 Oct 2002 Thick65.3665.100.40%0.0040 Sep 1994 Lava423.14421.310.43%0.0043 Jul 1995 Thick43.4843.290.44%0.0044 Oct 2008 Lava443.84441.600.51%0.0051 Apr 1982 Thin381.65379.330.61%0.0061 May 2008 Lava486.53483.350.65%0.0065 Apr 1994 Lava465.45462.400.66%0.0066 Jan 1995 Thick74.2273.730.66%0.0066 Oct 1984 Thick166.46165.250.73%0.0073 Mar 1988 Thick67.7867.091.02%0.0102 Oct 1999 Lava60.5459.891.09%0.0109 Jun 1986 Lava335.28339.81-1.35%0.0135 Mar 1997 Thick69.0067.981.47%0.0147 Dec 1995 Thick85.5884.091.74%0.0174 Jan 1992 Thin34.7934.101.97%0.0197 Absolute Value Average 0.55%

7. Some figures to assess agreement between Kriging Efforts

9. McVay 381.65 Schreuder 379.33

10. McVay 465.45 Schreuder 462.40

11. McVay 38.84 Schreuder 38.76

12. McVay 76.12 Schreuder 76.26

13. McVay 85.58 Schreuder 84.09

14. McVay 459.68 Schreuder 459.99

15. McVay 1455.88 Schreuder 1455.67

16. McVay 2158.85 Schreuder 2156.18

17. McVay 311.58 Schreuder 310.33

18. McVay 781.20 Schreuder 780.42

19. McVay 34.79 Schreuder 34.10

20. McVay 74.22 Schreuder 73.73

21. McVay 43.48 Schreuder 43.29

22. McVay 335.28 Schreuder 339.81

23. McVay 22.65 Schreuder 22.74

24. McVay 67.78 Schreuder 67.09

25. McVay 69.00 Schreuder 67.98

26. McVay 1639.82 Schreuder 1638.59

27. McVay 1271.83 Schreuder 1269.69

28. McVay 486.53 Schreuder 483.35

29. McVay 1149.73 Schreuder 1150.38

30. McVay 166.46 Schreuder 165.25

31. McVay 60.54 Schreuder 59.89

32. McVay 65.36 Schreuder 65.10

33. McVay 443.84 Schreuder 441.60

34. McVay 49.54 Schreuder 49.62

35. McVay 27.85 Schreuder 27.79

36. McVay 423.14 Schreuder 421.31

37. McVay 183.48 Schreuder 183.80

38. Calculating Recharge

39. Our Process for Calculating Recharge. We calculate the amount of recharge at each of the 45 weather stations using ET Idaho precipitation (P), root-zone moisture (P_rz) data. Recharge = P – P_rz We represent recharge for the three general soil types of Thick Soil, Thin Soil and Lava Rock using the ET Idaho root-zone moisture data for Sage Brush and Dormant Turf covers. To represent recharge on the various soil types we use: 1.Precipitation – Sage Brush Root-zone Moisture to represent Thick Soil. 2.Precipitation – Dormant Turf Root-zone Moisture to represent Thin Soil. 3.Precipitation – (2/3*Dormant Turf Root-zone Moisture) to represent Lava Rock.

40. What is P_rz? “P_rz – Precipitation residing in the root zone. P_rz is the amount of gross reported precipitation that infiltrates into the soil (i.e., less any runoff) and that remains in the root zone for consumption by evaporation or transpiration. P_rz is computed as: P – Runoff – DPerc where: P is gross precipitation Runoff is estimated surface runoff Dperc is deep percolation of any precipitation below the max root zone for the land-use condition.” Note: Definition from “Evaporation and Consumptive Irrigation Water Requirements for Idaho.” Allen and Robinson, 2007. Note: All values are in units of [L/T] which are multiplied by the number of days in each month.

41. Our Proxy for Recharge. Our proxy for recharge is calculated as: Recharge = P – P_rz P-(P – Runoff – Dperc) Runoff + Dperc Recharge = Runoff + Dperc where: Recharge is recharge to the aquifer P is gross precipitation P_rz is precipitation residing in root zone Runoff is estimated surface runoff Dperc is deep percolation of any precipitation below the max root zone for the land-use condition. We assume that all runoff will eventually percolate via ponding or stream leakage to become recharge.

42. Root Zone Precipitation Runoff P_rz Dperc Recharge = P – P_rz P-(P – Runoff – Dperc) Runoff + Dperc Recharge = Runoff + Dperc

43. Three scenarios are present in the data from ET Idaho that confound our process for estimating recharge. Recharge = P – P_rz Runoff + Dperc There are three scenarios in the ET Idaho data that we need to address. 1.Precipitation residing in root zone is negative. i.Typically occurs during dry periods. ii.P – (-P_rz) results in abnormally large amount of recharge. 2.Precipitation residing in root zone is greater than gross precipitation. i.Typically occurs during non-summer months (one in July) – only 15 occurrences. ii. Difference is always 0.01 mm/day. iii. P – P_rz results in negative recharge value. 3.Dormant Turf precipitation residing in root zone is greater than that of Sage Brush. i.Occurs in 31% of data. ii.Does not appear to be seasonal. iii.P – P_rz results in more recharge on Thick Soils than on Thin Soils and Lava.

44. Scenario 1 – Root Zone Moisture is negative Our work-around for moving forward is to consider this a soil moisture “deficit” and set recharge to be zero. P_rz = P – Runoff – Dperc Negative values should not occur, based on mass balance. American Falls August 1981: P – P_rz Sage = 0.07 – (-2.06) = 2.13

45. Our work-around for moving forward is to compute recharge as the absolute difference. P_rz = P – Runoff – Dperc P_rz > P should not occur, based on mass balance. Scenario 2 – Root Zone Moisture is greater than precipitation Swan Valley March 1985: P – Prz Sage = 0.80 – 0.81 = -0.01

46. No work-around for moving forward has been employed. Performing the P – P_rz calculation results in more recharge from Thick Soil than from Thin Soil and Lava. Previous work has demonstrated that recharge from precipitation is partly a function of soil texture and depth, and the general relationships between the soil types represented on the ESPA are that recharge from Lava > Thin Soil > Thick Soil (Contor, 2004; Garabedian, 1992). Scenario 3 – Dormant Turf P_rz is greater than Sage Brush P_rz Blackfoot

49. Recharge Calculation Summary Both Willem and I are using the same methodology in calculating recharge. There are three scenarios that confound our recharge proxy process. Precipitation residing in root zone is negative. Precipitation residing in root zone is greater than gross precipitation. Dormant Turf precipitation residing in root zone is greater than that of Sage Brush. We have employed two temporary work-around solutions to move forward with interpolation. Precipitation residing in root zone is negative. Work-around: Recharge = Zero. Precipitation residing in root zone is greater than gross precipitation. Work-around: Recharge = 0.01 mm/day. Dormant Turf precipitation residing in root zone is greater than that of Sage Brush. Work- around: None. Formal solutions should be pursued by the committee once Dr. Allen has had a chance to look at the data.

50. Any Questions?