Estimation of Cation Exchange Capacity in Guilan Soils

Measuring cation exchange capacity (CEC) of soils is both time consuming and expensive. CEC can be estimated, indirectly, from some readily and cheaply measured chemical and physical properties of soils. The objective of this study was to develop a proper pedotransfer function (PTF) for predicting CEC in soils of Guilan by particle size distribution, organic carbon percentage and acidity (pH). A total of 1676 data from the soil chemical laboratory of Rice Research Institute of Iran database in Rasht, Guilan, were used to develop the predictive CEC model: 1260 data were used for model calibration and 416 data were used for validation. The variables were selected by using stepwise regression method. The developed model (CEC = 15.524 + 0.32 Clay + 7.863 OC0.5 - 1.453 pH) was compared with the other existing models and was selected as the best predictive model on the basis of the greatest R2adj and the smallest ME and RMSE. The results showed that 42.8 percentages of CEC variations can be interpreted by clay, organic carbon and pH variables, with the clay variable having the largest impact according to the greatest ß coefficient.