Evaluating models to estimate cation exchange capacity of calcareous soils

Cation exchange capacity (CEC) is one of the fundamental properties of soil that indicates soil's ability to retain exchangeable cations. Several regression-based models exist to estimate CEC from widely available or easily measured basic soil properties. However, the majority of these models do not include CaCO3 as an input variable. Consequently, the applicability of these models for calcareous soils is largely unknown. This study evaluates the performance of selected CEC models for soils rich in calcium carbonate and assesses the influence of CaCO3 on CEC estimation performance. Thirty-eight soil samples that had a wide range in CEC (4 to 59 cmol((+)) kg(-1)) and CaCO3 content (10 to 97%) were selected to evaluate seven published CEC models that had inputs such as clay, silt, sand, pH, organic carbon/organic matter, CaCO3, and hygroscopic water content. The models that comprised clay, silt, sand, and organic carbon overestimated CEC for samples with CEC > 40 cmol((+)) kg(-1) and vice versa (average RMSE = 13.7 +/- 1.2 cmol((+)) kg(-1) and r(2) = 0.41 +/- 0.03). One model that included CaCO3, performed slightly better (RMSE = 11.7 cmol((+)) kg(-1)). The model based on hygroscopic water content (28% relative humidity) gave the best estimates of CEC (RMSE = 6.2 cmol((+)) kg(-1) and r(2) = 0.88). Apart from the water content-based model, there was a consistent trend of increasing CEC estimation errors with increasing CaCO3 contents. A newly developed CEC model based on clay and CaCO3 contents explained the variation in CEC better than all the published models, except the water content model.

Automated summary

This study evaluated the performance of selected CEC models for calcareous soils, finding that the water content model provided the best estimates of CEC and increasing CaCO3 content led to higher CEC estimation errors.