Prediction of soil exchangeable sodium ratio based on soil sodium adsorption ratio in saline soils of Khorasan Razavi, Iran

Sodium absorption ratio (SAR) and exchangeable sodium ratio (ESR) are two indicators of sodic soils. Accurate prediction on exchangeable sodium ratio (ESR), which is often using costly and time-consuming laboratory tests is important in reclamation of sodium (Na)-affected soils. A significant correlation between ESR and Sodium Adsorption Ratio (SAR) has been documented in many studies in different regions.  The main purpose of this study is to develop a linear regression model between soluble and exchangeable cations in the Sarakhs Plain, Northeast Iran. In this study, 124 soil samples were randomly taken from the surface and subsurface the experimental site. The soil samples collected using a soil auger at 0-30 cm and 30-60 cm depth. Then the linear regression model was used for predicting soil (ESR) in saline soils. The soil ESR values measured in soil samples compared to the soil ESR values predicted using the soil ESR-SAR model. The results revealed that ESR and SAR are highly variable irrespective of depth despite a slight decrease with depth. The statistical results indicate that the linear regression model ESR=0.0182SAR-0.027 (R2= 0.92, P <0.001) and ESR=0.0157SAR-0.020 (R2=0.83, P<0.001) recommended to predict soil ESR from soil SAR in surface soil (0-30 cm) and subsurface soil (30-60 cm), respectively. In conclusion, the soil ESR-SAR model can be used instead of time-consuming and costly experiments in this study area.