Estimating cation exchange capacity from hygroscopic water content change

Abstract The existing models for estimating cation exchange capacity (CEC) from easy‐to‐measure hygroscopic water content ( θ h ) were based on a single water activity ( a w ) value rather than on the processes that govern soil water vapor adsorption for a distinct a w range. Here, we present a new CEC estimation model based on θ h data of 119 soils with different clay mineralogy (i.e., illitic [IL], montmorillonitic [ML], and kaolinitic [KA] samples) and organic carbon (OC) contents for the a w range from 0.23 to 0.57 (Δ θ 0.23–0.57 ) and validate its performance. Based on the hypothesis that multilayer adsorption exhibits a higher correlation with CEC than monolayer adsorption and capillary condensation, the a w range from 0.23 to 0.57 was chosen with CEC calculated as CEC = k × Δ θ 0.23–0.57 . The performance of the new model is compared to the Arthur (2017) model and the Torrent (2015) model, which considers a single θ h value. The average proportionality coefficient ( k ) varied with the dominant clay mineralogy of the investigated soils. For soils dominated by 2:1 clay minerals (i.e., IL and ML), the new model showed a good estimation accuracy (Nash‐Sutcliffe model efficiency [ E ] ≥ 0.85; root mean squared error [RMSE] ≤ 4.18 cmol (+) kg −1 ). The new model performed better for IL and ML samples than for KA samples, and yielded more accurate CEC estimations than the Arthur model and Torrent model for soils with 2:1 clay minerals. For soil with high OC content (>23.2 g kg −1 ), the new model slightly underestimated CEC ( E = 0.66; RMSE = 5.87).

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Publication Details

Journal
Soil Science Society of America Journal
Published
2024-09-21
DOI
https://doi.org/10.1002/saj2.20764
Primary Topic
Agriculture, Soil, Plant Science
Type
article
Field-Weighted Citation Impact
0.00

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article

Estimating cation exchange capacity from hygroscopic water content change

Song Xue, Markus Tuller, Emmanuel Arthur, Chong Chen et al.
Soil Science Society of America Journal
Agriculture, Soil, Plant Science
article

Estimating cation exchange capacity from hygroscopic water content change

Song Xue, Markus Tuller, Emmanuel Arthur, Chong Chen, Hu Zhou, Jianying Shang
article en

Abstract

Abstract The existing models for estimating cation exchange capacity (CEC) from easy‐to‐measure hygroscopic water content ( θ h ) were based on a single water activity ( a w ) value rather than on the processes that govern soil water vapor adsorption for a distinct a w range. Here, we present a new CEC estimation model based on θ h data of 119 soils with different clay mineralogy (i.e., illitic [IL], montmorillonitic [ML], and kaolinitic [KA] samples) and organic carbon (OC) contents for the a w range from 0.23 to 0.57 (Δ θ 0.23–0.57 ) and validate its performance. Based on the hypothesis that multilayer adsorption exhibits a higher correlation with CEC than monolayer adsorption and capillary condensation, the a w range from 0.23 to 0.57 was chosen with CEC calculated as CEC = k × Δ θ 0.23–0.57 . The performance of the new model is compared to the Arthur (2017) model and the Torrent (2015) model, which considers a single θ h value. The average proportionality coefficient ( k ) varied with the dominant clay mineralogy of the investigated soils. For soils dominated by 2:1 clay minerals (i.e., IL and ML), the new model showed a good estimation accuracy (Nash‐Sutcliffe model efficiency [ E ] ≥ 0.85; root mean squared error [RMSE] ≤ 4.18 cmol (+) kg −1 ). The new model performed better for IL and ML samples than for KA samples, and yielded more accurate CEC estimations than the Arthur model and Torrent model for soils with 2:1 clay minerals. For soil with high OC content (>23.2 g kg −1 ), the new model slightly underestimated CEC ( E = 0.66; RMSE = 5.87).

Soil Science Society of America JournalVol. 88(6)
University of Arizona (US), Aarhus University (DK), Ministry of Agriculture and Rural Affairs (CN), China Agricultural University (CN)
National Natural Science Foundation of China, National Key Research and Development Program of China
Openalex Percentile: Top 89%
Agriculture, Soil, Plant Science
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