Coefficients for estimating SAR from soil pH and EC data and calculating pH from SAR and EC values in salinity models

Abstract

Abstract Data from highly weathered, low pH, sodic Australian soils have been used to develop a method for estimating soil exchangeable sodium percentage (ESP) or soil extract sodium adsorption ratio (SAR) from soil pH and electrical conductivity (EC) data. The method can also be used to calculate soil pH in soil salinity models using SAR and EC values. The pH was calculated as pH = A + (B × SAR1/2)/(1 + C × EC). Rewriting the equations in terms of SAR (or ESP), gives SAR (or ESP)= [(pH ‐ A)(1 + C × EC)/B]2. This study was conducted to determine whether these same methods could be used to predict the pH and SAR values for arid climate soils that are only slightly weathered and are often sodic under natural conditions. Existing pH, EC, and SAR data from Declo loam (coarse‐loamy, mixed, mesic, Xerollic Calciorthids), Freedom silt loam (fine‐silty, mixed, mesic, Xerollic Calciorthids), and Mazuma sandy loam (coarse‐loamy, mixed (calcareous), mesic Typic Torriorthents) were used to calculate the A, B, and C coefficients for the three high sodium soils. Coefficients obtained for a particular soil site were then used to predict pH or SAR of soil samples at additional sites and the correlation between calculated and measured values were determined. The A values for the Idaho soils are about 0.8 greater than those for the Australian soils, which were not completely base saturated. The Australian soils B values were about twice that of the calcareous Idaho soils, and the C values were not significantly different for the Australian and Idaho soils. In both cases the A coefficient values were slightly smaller than or nearly equal to the smallest pH values in a particular data set. Using coefficients from one location of a particular sodic or saline‐sodic soil to predict pH or SAR of the same soil, at a second location, was shown to be practical. Each soil type, however, requires its own set of coefficients. These relationships provide a rapid field method for estimating SAR or ESP from easily obtainable EC and pH data once the A, B, and C coefficients are determined for a particular soil. They also provide a method for pH calculation in soil salinity models that take into account soil EC and sodium effects on pH.