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

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.

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

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.

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).

Stress Period/Soil Type McVay Sum (ft) Schreuder Sum (ft) Diff (%McVay Sum) Abs Diff (%McVay Sum) Dec 2001 Lava % Nov 1984 Thin % Dec 1998 Thin % May 1980 Thin % Jan 1982 Lava % Dec 2004 Lava % May 1993 Lava % Sep 1993 Thick % Sep 1997 Thin % Aug 1999 Thin % Sep 1994 Thick % Aug 1989 Thick % Jun 2003 Thin % Feb 1990 Lava % Oct 2002 Thick % Sep 1994 Lava % Jul 1995 Thick % Oct 2008 Lava % Apr 1982 Thin % May 2008 Lava % Apr 1994 Lava % Jan 1995 Thick % Oct 1984 Thick % Mar 1988 Thick % Oct 1999 Lava % Jun 1986 Lava % Mar 1997 Thick % Dec 1995 Thick % Jan 1992 Thin % Absolute Value Average 0.55%

Some figures to assess agreement between Kriging Efforts

McVay Schreuder

McVay Schreuder

McVay Schreuder 38.76

McVay Schreuder 76.26

McVay Schreuder 84.09

McVay Schreuder

McVay Schreuder

McVay Schreuder

McVay Schreuder

McVay Schreuder

McVay Schreuder 34.10

McVay Schreuder 73.73

McVay Schreuder 43.29

McVay Schreuder

McVay Schreuder 22.74

McVay Schreuder 67.09

McVay Schreuder 67.98

McVay Schreuder

McVay Schreuder

McVay Schreuder

McVay Schreuder

McVay Schreuder

McVay Schreuder 59.89

McVay Schreuder 65.10

McVay Schreuder

McVay Schreuder 49.62

McVay Schreuder 27.79

McVay Schreuder

McVay Schreuder

Calculating Recharge

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.

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, Note: All values are in units of [L/T] which are multiplied by the number of days in each month.

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.

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

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.

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

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

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

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.

Any Questions?