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Appendix 9SAVI and LAI for Southern IdahoNote: Equations (14) and (15) for SAVI and the LAI are not well calibrated for universaluse with all vegetation types, and some uncertainties remain on their use. They are,however, utilized in SEBAL for two reasons: (1) LAI might be a better index than NDVI,since it has a physical meaning, and (2) LAI might be a better index for estimating the soilheat flux (G) and the momentum roughness length (z om ).Some of the development or validation of these equations in Idaho is shown below:SAVI0.150.140.130.120.110.10.090.080.070.060.050Change of SAVI number with various L valuesfor 5 soil / dead grass conditions in Southern Idaho, 19890.10.20.3L0.40.50.60.70.010.0090.0080.0070.0060.0050.0040.003Standard Deviation#1#2#3#4#5STDEVSAVI vs. L, where L is the coefficient in the SAVI equation for five soil or dead grass conditions insouthern Idaho; #1: Dry bare field with bright color (4/18/89), #2: Wet bare field with dark color(5/4/89), #3 to #5: Totally dead grassland from desert area with different soil color. The standarddeviation (STDEV) between the five soil locations or conditions becomes minimum when L = 0.1.This indicates that L = 0.1 tends to reduce the impact of soil wetness on the vegetation index. Thevalue of L for SAVI ID was chosen as 0.1 due to this analysis.85