Curtis Cooper1, Grant Cardon2, Jessica G. Davis1, and James Wittler3. (1) Colorado State University, Soil and Crop Sciences, Fort Collins, CO 80523-1170, (2) Utah State University, 4820 Old Main Hill, Logan, UT 84322-4820, (3) NRCS, 27200 Hwy 287, PO Box 398, Springfield, CO 81073
Mineralogical variations associated with salinity influence the calibration of the electromagnetic induction meter by transforming the ions that carry the electromagnetic resonance. Soils in the High Plains in the Arkansas River Basin of Colorado are calcareous and are reservoirs of calcium sulfate and magnesium sulfate salts. The form of the mineral precipitates influences the pore water solution chemistry as wetting and drying occurs in these irrigated soils. Many of the precipitated minerals have a lower solubility than the component ions; in particular, calcite and gypsum have limited solubility unlike the magnesium sulfates (typically as epsomite). When ions in solution are precipitated, their influence on the electromagnetic resonance is decreased, whereas laboratory saturated paste methods can increase the dissolution of minerals not readily soluble in the field, and increase the surface area for reactions/dissolution. Current calibration equations for the EM38 (Geonics, Ontario) for the Arkansas River Basin rely upon ECe and water content measurements. Of the mineralogical calibration equations, the more user-friendly equation requires the inclusion of sodium at the calculated pore water concentrations, based upon a simple concentrating factor. Calibration equations that are more complex require the inclusion of calculated calcium concentrations after precipitates are accounted for, due to changes in the water content using programs such as Visual Minteq. For example, the downstream subregion calibration equation's r-square is increased from 0.54 with an RSME of 2.16 to an r-square of 0.84 with a RSME of 1.55 when using the equation accounting for soil texture, pH and calcium concentrations. The inclusion of the mineralogy in the calibration equations serves to limit some of the deviation and/or variation of the ECe-EM calibration, but at the cost of more complex computing and data requirements.
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